diff --git a/.github/workflows/claude-ci-failure-auto-fix.yml b/.github/workflows/claude-ci-failure-auto-fix.yml
index e39c6676ce..ab07c8ae10 100644
--- a/.github/workflows/claude-ci-failure-auto-fix.yml
+++ b/.github/workflows/claude-ci-failure-auto-fix.yml
@@ -22,7 +22,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.event.workflow_run.head_branch }}
           fetch-depth: 0
@@ -42,7 +42,7 @@ jobs:
 
       - name: Get CI failure details
         id: failure_details
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const run = await github.rest.actions.getWorkflowRun({
diff --git a/.github/workflows/claude-dependabot.yml b/.github/workflows/claude-dependabot.yml
index ff6935dc2d..da37df6de7 100644
--- a/.github/workflows/claude-dependabot.yml
+++ b/.github/workflows/claude-dependabot.yml
@@ -30,7 +30,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -41,7 +41,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -78,7 +78,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22"
 
@@ -91,7 +91,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -124,7 +124,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes
@@ -309,6 +309,7 @@ jobs:
         uses: anthropics/claude-code-action@v1
         with:
           claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
+          allowed_bots: "dependabot[bot]"
           claude_args: |
             --allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*)"
           prompt: |
diff --git a/.github/workflows/claude.yml b/.github/workflows/claude.yml
index 8c45f930dc..ee901fe5d4 100644
--- a/.github/workflows/claude.yml
+++ b/.github/workflows/claude.yml
@@ -40,7 +40,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -57,7 +57,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -94,7 +94,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22"
 
@@ -107,7 +107,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -140,7 +140,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes
diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml
index a6c36ed86c..966243323c 100644
--- a/.github/workflows/codeql.yml
+++ b/.github/workflows/codeql.yml
@@ -58,7 +58,7 @@ jobs:
         # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
     steps:
     - name: Checkout repository
-      uses: actions/checkout@v4
+      uses: actions/checkout@v6
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL
diff --git a/.github/workflows/copilot-setup-steps.yml b/.github/workflows/copilot-setup-steps.yml
index aac8befee0..dad99cb8d9 100644
--- a/.github/workflows/copilot-setup-steps.yml
+++ b/.github/workflows/copilot-setup-steps.yml
@@ -27,7 +27,7 @@ jobs:
     # If you do not check out your code, Copilot will do this for you.
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true
@@ -39,7 +39,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -76,7 +76,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22"
 
@@ -89,7 +89,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -132,7 +132,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes
diff --git a/.github/workflows/docs-block-sync.yml b/.github/workflows/docs-block-sync.yml
index b1fc986ea7..32f205019f 100644
--- a/.github/workflows/docs-block-sync.yml
+++ b/.github/workflows/docs-block-sync.yml
@@ -23,7 +23,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -33,7 +33,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
diff --git a/.github/workflows/docs-claude-review.yml b/.github/workflows/docs-claude-review.yml
index 511c2efcd5..ca2788b387 100644
--- a/.github/workflows/docs-claude-review.yml
+++ b/.github/workflows/docs-claude-review.yml
@@ -23,7 +23,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
@@ -33,7 +33,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
diff --git a/.github/workflows/docs-enhance.yml b/.github/workflows/docs-enhance.yml
index db750e78ae..52607fa5df 100644
--- a/.github/workflows/docs-enhance.yml
+++ b/.github/workflows/docs-enhance.yml
@@ -28,7 +28,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -38,7 +38,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
diff --git a/.github/workflows/platform-autogpt-deploy-dev.yaml b/.github/workflows/platform-autogpt-deploy-dev.yaml
index 6e1e23d3eb..b415fb1b7b 100644
--- a/.github/workflows/platform-autogpt-deploy-dev.yaml
+++ b/.github/workflows/platform-autogpt-deploy-dev.yaml
@@ -25,7 +25,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.event.inputs.git_ref || github.ref_name }}
 
@@ -52,7 +52,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
diff --git a/.github/workflows/platform-autogpt-deploy-prod.yml b/.github/workflows/platform-autogpt-deploy-prod.yml
index 4d7c16d710..e0c524d8d2 100644
--- a/.github/workflows/platform-autogpt-deploy-prod.yml
+++ b/.github/workflows/platform-autogpt-deploy-prod.yml
@@ -17,7 +17,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.ref_name || 'master' }}
 
@@ -45,7 +45,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
diff --git a/.github/workflows/platform-backend-ci.yml b/.github/workflows/platform-backend-ci.yml
index f66cce8a37..1f0c6da3dd 100644
--- a/.github/workflows/platform-backend-ci.yml
+++ b/.github/workflows/platform-backend-ci.yml
@@ -68,7 +68,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true
@@ -88,7 +88,7 @@ jobs:
         run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
diff --git a/.github/workflows/platform-dev-deploy-event-dispatcher.yml b/.github/workflows/platform-dev-deploy-event-dispatcher.yml
index d7915f64c6..1a581c55c2 100644
--- a/.github/workflows/platform-dev-deploy-event-dispatcher.yml
+++ b/.github/workflows/platform-dev-deploy-event-dispatcher.yml
@@ -17,7 +17,7 @@ jobs:
       - name: Check comment permissions and deployment status
         id: check_status
         if: github.event_name == 'issue_comment' && github.event.issue.pull_request
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const commentBody = context.payload.comment.body.trim();
@@ -55,7 +55,7 @@ jobs:
 
       - name: Post permission denied comment
         if: steps.check_status.outputs.permission_denied == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -68,7 +68,7 @@ jobs:
       - name: Get PR details for deployment
         id: pr_details
         if: steps.check_status.outputs.should_deploy == 'true' || steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const pr = await github.rest.pulls.get({
@@ -82,7 +82,7 @@ jobs:
           
       - name: Dispatch Deploy Event
         if: steps.check_status.outputs.should_deploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -98,7 +98,7 @@ jobs:
 
       - name: Post deploy success comment
         if: steps.check_status.outputs.should_deploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -110,7 +110,7 @@ jobs:
 
       - name: Dispatch Undeploy Event (from comment)
         if: steps.check_status.outputs.should_undeploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -126,7 +126,7 @@ jobs:
 
       - name: Post undeploy success comment
         if: steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -139,7 +139,7 @@ jobs:
       - name: Check deployment status on PR close
         id: check_pr_close
         if: github.event_name == 'pull_request' && github.event.action == 'closed'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const comments = await github.rest.issues.listComments({
@@ -168,7 +168,7 @@ jobs:
           github.event_name == 'pull_request' &&
           github.event.action == 'closed' &&
           steps.check_pr_close.outputs.should_undeploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -187,7 +187,7 @@ jobs:
           github.event_name == 'pull_request' &&
           github.event.action == 'closed' &&
           steps.check_pr_close.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
diff --git a/.github/workflows/platform-frontend-ci.yml b/.github/workflows/platform-frontend-ci.yml
index 499bb03170..6410daae9f 100644
--- a/.github/workflows/platform-frontend-ci.yml
+++ b/.github/workflows/platform-frontend-ci.yml
@@ -27,13 +27,22 @@ jobs:
     runs-on: ubuntu-latest
     outputs:
       cache-key: ${{ steps.cache-key.outputs.key }}
+      components-changed: ${{ steps.filter.outputs.components }}
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
+
+      - name: Check for component changes
+        uses: dorny/paths-filter@v3
+        id: filter
+        with:
+          filters: |
+            components:
+              - 'autogpt_platform/frontend/src/components/**'
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -45,7 +54,7 @@ jobs:
         run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
 
       - name: Cache dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -62,10 +71,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -73,7 +82,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -90,17 +99,20 @@ jobs:
   chromatic:
     runs-on: ubuntu-latest
     needs: setup
-    # Only run on dev branch pushes or PRs targeting dev
-    if: github.ref == 'refs/heads/dev' || github.base_ref == 'dev'
+    # Disabled: to re-enable, remove 'false &&' from the condition below
+    if: >-
+      false
+      && (github.ref == 'refs/heads/dev' || github.base_ref == 'dev')
+      && needs.setup.outputs.components-changed == 'true'
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -108,7 +120,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -136,12 +148,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -164,7 +176,7 @@ jobs:
         uses: docker/setup-buildx-action@v3
 
       - name: Cache Docker layers
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: /tmp/.buildx-cache
           key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
@@ -219,7 +231,7 @@ jobs:
           fi
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -265,12 +277,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -278,7 +290,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
diff --git a/.github/workflows/platform-fullstack-ci.yml b/.github/workflows/platform-fullstack-ci.yml
index c888ace6c5..b4724245dc 100644
--- a/.github/workflows/platform-fullstack-ci.yml
+++ b/.github/workflows/platform-fullstack-ci.yml
@@ -29,10 +29,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -44,7 +44,7 @@ jobs:
         run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
 
       - name: Cache dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -56,19 +56,19 @@ jobs:
         run: pnpm install --frozen-lockfile
 
   types:
-    runs-on: ubuntu-latest
+    runs-on: big-boi
     needs: setup
     strategy:
       fail-fast: false
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -85,10 +85,10 @@ jobs:
 
       - name: Run docker compose
         run: |
-          docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
+          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
diff --git a/.github/workflows/repo-workflow-checker.yml b/.github/workflows/repo-workflow-checker.yml
index 35536ba922..aa94622d31 100644
--- a/.github/workflows/repo-workflow-checker.yml
+++ b/.github/workflows/repo-workflow-checker.yml
@@ -11,7 +11,7 @@ jobs:
     steps:
       # - name: Wait some time for all actions to start
       #   run: sleep 30
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
         # with:
           # fetch-depth: 0
       - name: Set up Python
diff --git a/.gitignore b/.gitignore
index a542526304..af502d19e8 100644
--- a/.gitignore
+++ b/.gitignore
@@ -189,3 +189,4 @@ CLAUDE.local.md
 
 # Test database
 test.db
+.next
diff --git a/README.md b/README.md
index 3572fe318b..349d8818ef 100644
--- a/README.md
+++ b/README.md
@@ -54,7 +54,7 @@ Before proceeding with the installation, ensure your system meets the following
 ### Updated Setup Instructions:
 We've moved to a fully maintained and regularly updated documentation site.
 
-👉 [Follow the official self-hosting guide here](https://docs.agpt.co/platform/getting-started/)
+👉 [Follow the official self-hosting guide here](https://agpt.co/docs/platform/getting-started/getting-started)
 
 
 This tutorial assumes you have Docker, VSCode, git and npm installed.
diff --git a/autogpt_platform/autogpt_libs/poetry.lock b/autogpt_platform/autogpt_libs/poetry.lock
index f4f97cc65a..0a421dda31 100644
--- a/autogpt_platform/autogpt_libs/poetry.lock
+++ b/autogpt_platform/autogpt_libs/poetry.lock
@@ -1,5 +1,17 @@
 # This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
 
+[[package]]
+name = "annotated-doc"
+version = "0.0.4"
+description = "Document parameters, class attributes, return types, and variables inline, with Annotated."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
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+    {file = "annotated_doc-0.0.4.tar.gz", hash = "sha256:fbcda96e87e9c92ad167c2e53839e57503ecfda18804ea28102353485033faa4"},
+]
+
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -87,84 +99,101 @@ files = [
 
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 name = "cffi"
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+version = "2.0.0"
 description = "Foreign Function Interface for Python calling C code."
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+python-versions = ">=3.9"
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 [package.dependencies]
@@ -401,62 +448,75 @@ toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
 [[package]]
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 optional = false
-python-versions = "!=3.9.0,!=3.9.1,>=3.7"
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 [[package]]
@@ -510,25 +570,66 @@ tests = ["coverage", "coveralls", "dill", "mock", "nose"]
 
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-all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
-standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
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+all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
+standard-no-fastapi-cloud-cli = ["email-validator (>=2.0.0)", "fastapi-cli[standard-no-fastapi-cloud-cli] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
+
+[[package]]
+name = "fsspec"
+version = "2026.1.0"
+description = "File-system specification"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "fsspec-2026.1.0-py3-none-any.whl", hash = "sha256:cb76aa913c2285a3b49bdd5fc55b1d7c708d7208126b60f2eb8194fe1b4cbdcc"},
+    {file = "fsspec-2026.1.0.tar.gz", hash = "sha256:e987cb0496a0d81bba3a9d1cee62922fb395e7d4c3b575e57f547953334fe07b"},
+]
+
+[package.extras]
+abfs = ["adlfs"]
+adl = ["adlfs"]
+arrow = ["pyarrow (>=1)"]
+dask = ["dask", "distributed"]
+dev = ["pre-commit", "ruff (>=0.5)"]
+doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
+dropbox = ["dropbox", "dropboxdrivefs", "requests"]
+full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs (>2024.2.0)", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs (>2024.2.0)", "smbprotocol", "tqdm"]
+fuse = ["fusepy"]
+gcs = ["gcsfs"]
+git = ["pygit2"]
+github = ["requests"]
+gs = ["gcsfs"]
+gui = ["panel"]
+hdfs = ["pyarrow (>=1)"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
+libarchive = ["libarchive-c"]
+oci = ["ocifs"]
+s3 = ["s3fs"]
+sftp = ["paramiko"]
+smb = ["smbprotocol"]
+ssh = ["paramiko"]
+test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
+test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
+test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "backports-zstd ; python_version < \"3.14\"", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr"]
+tqdm = ["tqdm"]
 
 [[package]]
 name = "google-api-core"
@@ -651,14 +752,14 @@ grpc = ["grpcio (>=1.38.0,<2.0dev)", "grpcio-status (>=1.38.0,<2.0.dev0)"]
 
 [[package]]
 name = "google-cloud-logging"
-version = "3.12.1"
+version = "3.13.0"
 description = "Stackdriver Logging API client library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google_cloud_logging-3.12.1-py2.py3-none-any.whl", hash = "sha256:6817878af76ec4e7568976772839ab2c43ddfd18fbbf2ce32b13ef549cd5a862"},
-    {file = "google_cloud_logging-3.12.1.tar.gz", hash = "sha256:36efc823985055b203904e83e1c8f9f999b3c64270bcda39d57386ca4effd678"},
+    {file = "google_cloud_logging-3.13.0-py3-none-any.whl", hash = "sha256:f215e1c76ee29239c6cacf02443dffa985663c74bf47c9818854694805c6019f"},
+    {file = "google_cloud_logging-3.13.0.tar.gz", hash = "sha256:3aae0573b1a1a4f59ecdf4571f4e7881b5823bd129fe469561c1c49a7fa8a4c1"},
 ]
 
 [package.dependencies]
@@ -695,23 +796,6 @@ protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4
 [package.extras]
 grpc = ["grpcio (>=1.44.0,<2.0.0)"]
 
-[[package]]
-name = "gotrue"
-version = "2.12.3"
-description = "Python Client Library for Supabase Auth"
-optional = false
-python-versions = "<4.0,>=3.9"
-groups = ["main"]
-files = [
-    {file = "gotrue-2.12.3-py3-none-any.whl", hash = "sha256:b1a3c6a5fe3f92e854a026c4c19de58706a96fd5fbdcc3d620b2802f6a46a26b"},
-    {file = "gotrue-2.12.3.tar.gz", hash = "sha256:f874cf9d0b2f0335bfbd0d6e29e3f7aff79998cd1c14d2ad814db8c06cee3852"},
-]
-
-[package.dependencies]
-httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
-pydantic = ">=1.10,<3"
-pyjwt = ">=2.10.1,<3.0.0"
-
 [[package]]
 name = "grpc-google-iam-v1"
 version = "0.14.2"
@@ -963,14 +1047,14 @@ files = [
 
 [[package]]
 name = "launchdarkly-eventsource"
-version = "1.3.0"
+version = "1.5.1"
 description = "LaunchDarkly SSE Client"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "launchdarkly_eventsource-1.3.0-py3-none-any.whl", hash = "sha256:7afecee7a0f306630e4364994e0816abbbdbaf143fe43b3428ed122fa4e0d487"},
-    {file = "launchdarkly_eventsource-1.3.0.tar.gz", hash = "sha256:5029199b2c344aee2806bbe8784965e9c0197d052d0bab7e1396a94c159f6bc8"},
+    {file = "launchdarkly_eventsource-1.5.1-py3-none-any.whl", hash = "sha256:43dfbc14a3962c9bce252320d690cdcbfda0ca00501226d517ae77e60f570d44"},
+    {file = "launchdarkly_eventsource-1.5.1.tar.gz", hash = "sha256:f122f80b36db6ea1ab20af62c82b8b2668682259b415053c94400dd6c07922a7"},
 ]
 
 [package.dependencies]
@@ -978,20 +1062,20 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.12.0"
+version = "9.14.1"
 description = "LaunchDarkly SDK for Python"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "launchdarkly_server_sdk-9.12.0-py3-none-any.whl", hash = "sha256:c7351e26e6b695b968d49888e967691aae60ded82d73a41a74d59d11252a1413"},
-    {file = "launchdarkly_server_sdk-9.12.0.tar.gz", hash = "sha256:219b100d7569e4f528b6028cbd2a5d61f13539f2b44ed43fc173bb4f456ee580"},
+    {file = "launchdarkly_server_sdk-9.14.1-py3-none-any.whl", hash = "sha256:a9e2bd9ecdef845cd631ae0d4334a1115e5b44257c42eb2349492be4bac7815c"},
+    {file = "launchdarkly_server_sdk-9.14.1.tar.gz", hash = "sha256:1df44baf0a0efa74d8c1dad7a00592b98bce7d19edded7f770da8dbc49922213"},
 ]
 
 [package.dependencies]
 certifi = ">=2018.4.16"
 expiringdict = ">=1.1.4"
-launchdarkly-eventsource = ">=1.2.4,<2.0.0"
+launchdarkly-eventsource = ">=1.5.0,<2.0.0"
 pyRFC3339 = ">=1.0"
 semver = ">=2.10.2"
 urllib3 = ">=1.26.0,<3"
@@ -1002,6 +1086,340 @@ dynamodb = ["boto3 (>=1.9.71)"]
 redis = ["redis (>=2.10.5)"]
 test-filesource = ["pyyaml (>=5.3.1)", "watchdog (>=3.0.0)"]
 
+[[package]]
+name = "markdown-it-py"
+version = "4.0.0"
+description = "Python port of markdown-it. Markdown parsing, done right!"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
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+    {file = "markdown_it_py-4.0.0.tar.gz", hash = "sha256:cb0a2b4aa34f932c007117b194e945bd74e0ec24133ceb5bac59009cda1cb9f3"},
+]
+
+[package.dependencies]
+mdurl = ">=0.1,<1.0"
+
+[package.extras]
+benchmarking = ["psutil", "pytest", "pytest-benchmark"]
+compare = ["commonmark (>=0.9,<1.0)", "markdown (>=3.4,<4.0)", "markdown-it-pyrs", "mistletoe (>=1.0,<2.0)", "mistune (>=3.0,<4.0)", "panflute (>=2.3,<3.0)"]
+linkify = ["linkify-it-py (>=1,<3)"]
+plugins = ["mdit-py-plugins (>=0.5.0)"]
+profiling = ["gprof2dot"]
+rtd = ["ipykernel", "jupyter_sphinx", "mdit-py-plugins (>=0.5.0)", "myst-parser", "pyyaml", "sphinx", "sphinx-book-theme (>=1.0,<2.0)", "sphinx-copybutton", "sphinx-design"]
+testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions", "requests"]
+
+[[package]]
+name = "mdurl"
+version = "0.1.2"
+description = "Markdown URL utilities"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8"},
+    {file = "mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba"},
+]
+
+[[package]]
+name = "mmh3"
+version = "5.2.0"
+description = "Python extension for MurmurHash (MurmurHash3), a set of fast and robust hash functions."
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@@ -1060,21 +1478,154 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
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 [[package]]
 name = "proto-plus"
@@ -1147,7 +1698,7 @@ description = "C parser in Python"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "platform_python_implementation != \"PyPy\""
+markers = "platform_python_implementation != \"PyPy\" and implementation_name != \"PyPy\""
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+typing-inspection = ">=0.4.2"
 
 [package.extras]
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 optional = false
 python-versions = ">=3.8"
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 name = "pyrfc3339"
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+]
+
 [[package]]
 name = "pytest"
 version = "8.4.1"
@@ -1406,19 +2159,20 @@ dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "requests
 
 [[package]]
 name = "pytest-asyncio"
-version = "1.1.0"
+version = "1.3.0"
 description = "Pytest support for asyncio"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
 backports-asyncio-runner = {version = ">=1.1,<2", markers = "python_version < \"3.11\""}
-pytest = ">=8.2,<9"
+pytest = ">=8.2,<10"
+typing-extensions = {version = ">=4.12", markers = "python_version < \"3.13\""}
 
 [package.extras]
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1)"]
@@ -1426,34 +2180,34 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
 [[package]]
 name = "pytest-cov"
-version = "6.2.1"
+version = "7.0.0"
 description = "Pytest plugin for measuring coverage."
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
-coverage = {version = ">=7.5", extras = ["toml"]}
+coverage = {version = ">=7.10.6", extras = ["toml"]}
 pluggy = ">=1.2"
-pytest = ">=6.2.5"
+pytest = ">=7"
 
 [package.extras]
-testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
+testing = ["process-tests", "pytest-xdist", "virtualenv"]
 
 [[package]]
 name = "pytest-mock"
-version = "3.14.1"
+version = "3.15.1"
 description = "Thin-wrapper around the mock package for easier use with pytest"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
@@ -1494,18 +2248,19 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "realtime"
-version = "2.5.3"
+version = "2.27.2"
 description = ""
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
-typing-extensions = ">=4.14.0,<5.0.0"
+pydantic = ">=2.11.7,<3.0.0"
+typing-extensions = ">=4.14.0"
 websockets = ">=11,<16"
 
 [[package]]
@@ -1550,6 +2305,25 @@ urllib3 = ">=1.21.1,<3"
 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "rich"
+version = "14.3.2"
+description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
+optional = false
+python-versions = ">=3.8.0"
+groups = ["main"]
+files = [
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+]
+
+[package.dependencies]
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+pygments = ">=2.13.0,<3.0.0"
+
+[package.extras]
+jupyter = ["ipywidgets (>=7.5.1,<9)"]
+
 [[package]]
 name = "rsa"
 version = "4.9.1"
@@ -1567,31 +2341,30 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.12.11"
+version = "0.15.0"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
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 [[package]]
@@ -1630,6 +2403,18 @@ files = [
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 ]
 
+[[package]]
+name = "sortedcontainers"
+version = "2.4.0"
+description = "Sorted Containers -- Sorted List, Sorted Dict, Sorted Set"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
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+]
+
 [[package]]
 name = "starlette"
 version = "0.47.1"
@@ -1651,20 +2436,22 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "0.12.0"
+version = "2.27.2"
 description = "Supabase Storage client for Python."
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "storage3-0.12.0-py3-none-any.whl", hash = "sha256:1c4585693ca42243ded1512b58e54c697111e91a20916cd14783eebc37e7c87d"},
-    {file = "storage3-0.12.0.tar.gz", hash = "sha256:94243f20922d57738bf42e96b9f5582b4d166e8bf209eccf20b146909f3f71b0"},
+    {file = "storage3-2.27.2-py3-none-any.whl", hash = "sha256:e6f16e7a260729e7b1f46e9bf61746805a02e30f5e419ee1291007c432e3ec63"},
+    {file = "storage3-2.27.2.tar.gz", hash = "sha256:cb4807b7f86b4bb1272ac6fdd2f3cfd8ba577297046fa5f88557425200275af5"},
 ]
 
 [package.dependencies]
-deprecation = ">=2.1.0,<3.0.0"
+deprecation = ">=2.1.0"
 httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
-python-dateutil = ">=2.8.2,<3.0.0"
+pydantic = ">=2.11.7"
+pyiceberg = ">=0.10.0"
+yarl = ">=1.20.1"
 
 [[package]]
 name = "strenum"
@@ -1684,40 +2471,90 @@ release = ["twine"]
 test = ["pylint", "pytest", "pytest-black", "pytest-cov", "pytest-pylint"]
 
 [[package]]
-name = "supabase"
-version = "2.16.0"
-description = "Supabase client for Python."
+name = "strictyaml"
+version = "1.7.3"
+description = "Strict, typed YAML parser"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.7.0"
 groups = ["main"]
 files = [
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+    {file = "strictyaml-1.7.3-py3-none-any.whl", hash = "sha256:fb5c8a4edb43bebb765959e420f9b3978d7f1af88c80606c03fb420888f5d1c7"},
+    {file = "strictyaml-1.7.3.tar.gz", hash = "sha256:22f854a5fcab42b5ddba8030a0e4be51ca89af0267961c8d6cfa86395586c407"},
 ]
 
 [package.dependencies]
-gotrue = ">=2.11.0,<3.0.0"
-httpx = ">=0.26,<0.29"
-postgrest = ">0.19,<1.2"
-realtime = ">=2.4.0,<2.6.0"
-storage3 = ">=0.10,<0.13"
-supafunc = ">=0.9,<0.11"
+python-dateutil = ">=2.6.0"
 
 [[package]]
-name = "supafunc"
-version = "0.10.1"
-description = "Library for Supabase Functions"
+name = "supabase"
+version = "2.27.2"
+description = "Supabase client for Python."
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "supabase-2.27.2-py3-none-any.whl", hash = "sha256:d4dce00b3a418ee578017ec577c0e5be47a9a636355009c76f20ed2faa15bc54"},
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+]
+
+[package.dependencies]
+httpx = ">=0.26,<0.29"
+postgrest = "2.27.2"
+realtime = "2.27.2"
+storage3 = "2.27.2"
+supabase-auth = "2.27.2"
+supabase-functions = "2.27.2"
+yarl = ">=1.22.0"
+
+[[package]]
+name = "supabase-auth"
+version = "2.27.2"
+description = "Python Client Library for Supabase Auth"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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 ]
 
 [package.dependencies]
 httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
-strenum = ">=0.4.15,<0.5.0"
+pydantic = ">=1.10,<3"
+pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
+
+[[package]]
+name = "supabase-functions"
+version = "2.27.2"
+description = "Library for Supabase Functions"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "supabase_functions-2.27.2-py3-none-any.whl", hash = "sha256:db480efc669d0bca07605b9b6f167312af43121adcc842a111f79bea416ef754"},
+    {file = "supabase_functions-2.27.2.tar.gz", hash = "sha256:d0c8266207a94371cb3fd35ad3c7f025b78a97cf026861e04ccd35ac1775f80b"},
+]
+
+[package.dependencies]
+httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
+strenum = ">=0.4.15"
+yarl = ">=1.20.1"
+
+[[package]]
+name = "tenacity"
+version = "9.1.2"
+description = "Retry code until it succeeds"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+    {file = "tenacity-9.1.2.tar.gz", hash = "sha256:1169d376c297e7de388d18b4481760d478b0e99a777cad3a9c86e556f4b697cb"},
+]
+
+[package.extras]
+doc = ["reno", "sphinx"]
+test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
 [[package]]
 name = "tomli"
@@ -1776,14 +2613,14 @@ files = [
 
 [[package]]
 name = "typing-inspection"
-version = "0.4.1"
+version = "0.4.2"
 description = "Runtime typing introspection tools"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464"},
 ]
 
 [package.dependencies]
@@ -1809,14 +2646,14 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "uvicorn"
-version = "0.35.0"
+version = "0.40.0"
 description = "The lightning-fast ASGI server."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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+    {file = "uvicorn-0.40.0-py3-none-any.whl", hash = "sha256:c6c8f55bc8bf13eb6fa9ff87ad62308bbbc33d0b67f84293151efe87e0d5f2ee"},
+    {file = "uvicorn-0.40.0.tar.gz", hash = "sha256:839676675e87e73694518b5574fd0f24c9d97b46bea16df7b8c05ea1a51071ea"},
 ]
 
 [package.dependencies]
@@ -1906,6 +2743,151 @@ files = [
     {file = "websockets-15.0.1.tar.gz", hash = "sha256:82544de02076bafba038ce055ee6412d68da13ab47f0c60cab827346de828dee"},
 ]
 
+[[package]]
+name = "yarl"
+version = "1.22.0"
+description = "Yet another URL library"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+    {file = "yarl-1.22.0-py3-none-any.whl", hash = "sha256:1380560bdba02b6b6c90de54133c81c9f2a453dee9912fe58c1dcced1edb7cff"},
+    {file = "yarl-1.22.0.tar.gz", hash = "sha256:bebf8557577d4401ba8bd9ff33906f1376c877aa78d1fe216ad01b4d6745af71"},
+]
+
+[package.dependencies]
+idna = ">=2.0"
+multidict = ">=4.0"
+propcache = ">=0.2.1"
+
 [[package]]
 name = "zipp"
 version = "3.23.0"
@@ -1929,4 +2911,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "0c40b63c3c921846cf05ccfb4e685d4959854b29c2c302245f9832e20aac6954"
+content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"
diff --git a/autogpt_platform/autogpt_libs/pyproject.toml b/autogpt_platform/autogpt_libs/pyproject.toml
index a81b07fba6..8deb4d2169 100644
--- a/autogpt_platform/autogpt_libs/pyproject.toml
+++ b/autogpt_platform/autogpt_libs/pyproject.toml
@@ -9,25 +9,25 @@ packages = [{ include = "autogpt_libs" }]
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 colorama = "^0.4.6"
-cryptography = "^45.0"
+cryptography = "^46.0"
 expiringdict = "^1.2.2"
-fastapi = "^0.116.1"
-google-cloud-logging = "^3.12.1"
-launchdarkly-server-sdk = "^9.12.0"
-pydantic = "^2.11.7"
-pydantic-settings = "^2.10.1"
-pyjwt = { version = "^2.10.1", extras = ["crypto"] }
+fastapi = "^0.128.0"
+google-cloud-logging = "^3.13.0"
+launchdarkly-server-sdk = "^9.14.1"
+pydantic = "^2.12.5"
+pydantic-settings = "^2.12.0"
+pyjwt = { version = "^2.11.0", extras = ["crypto"] }
 redis = "^6.2.0"
-supabase = "^2.16.0"
-uvicorn = "^0.35.0"
+supabase = "^2.27.2"
+uvicorn = "^0.40.0"
 
 [tool.poetry.group.dev.dependencies]
-pyright = "^1.1.404"
+pyright = "^1.1.408"
 pytest = "^8.4.1"
-pytest-asyncio = "^1.1.0"
-pytest-mock = "^3.14.1"
-pytest-cov = "^6.2.1"
-ruff = "^0.12.11"
+pytest-asyncio = "^1.3.0"
+pytest-mock = "^3.15.1"
+pytest-cov = "^7.0.0"
+ruff = "^0.15.0"
 
 [build-system]
 requires = ["poetry-core"]
diff --git a/autogpt_platform/backend/.env.default b/autogpt_platform/backend/.env.default
index b393f13017..fa52ba812a 100644
--- a/autogpt_platform/backend/.env.default
+++ b/autogpt_platform/backend/.env.default
@@ -152,6 +152,7 @@ REPLICATE_API_KEY=
 REVID_API_KEY=
 SCREENSHOTONE_API_KEY=
 UNREAL_SPEECH_API_KEY=
+ELEVENLABS_API_KEY=
 
 # Data & Search Services
 E2B_API_KEY=
diff --git a/autogpt_platform/backend/.gitignore b/autogpt_platform/backend/.gitignore
index 9224c07d9e..6e688311a6 100644
--- a/autogpt_platform/backend/.gitignore
+++ b/autogpt_platform/backend/.gitignore
@@ -19,3 +19,6 @@ load-tests/*.json
 load-tests/*.log
 load-tests/node_modules/*
 migrations/*/rollback*.sql
+
+# Workspace files
+workspaces/
diff --git a/autogpt_platform/backend/Dockerfile b/autogpt_platform/backend/Dockerfile
index 103226d079..9bd455e490 100644
--- a/autogpt_platform/backend/Dockerfile
+++ b/autogpt_platform/backend/Dockerfile
@@ -62,10 +62,12 @@ ENV POETRY_HOME=/opt/poetry \
     DEBIAN_FRONTEND=noninteractive
 ENV PATH=/opt/poetry/bin:$PATH
 
-# Install Python without upgrading system-managed packages
+# Install Python, FFmpeg, and ImageMagick (required for video processing blocks)
 RUN apt-get update && apt-get install -y \
     python3.13 \
     python3-pip \
+    ffmpeg \
+    imagemagick \
     && rm -rf /var/lib/apt/lists/*
 
 # Copy only necessary files from builder
diff --git a/autogpt_platform/backend/backend/api/features/chat/completion_consumer.py b/autogpt_platform/backend/backend/api/features/chat/completion_consumer.py
new file mode 100644
index 0000000000..f447d46bd7
--- /dev/null
+++ b/autogpt_platform/backend/backend/api/features/chat/completion_consumer.py
@@ -0,0 +1,368 @@
+"""Redis Streams consumer for operation completion messages.
+
+This module provides a consumer (ChatCompletionConsumer) that listens for
+completion notifications (OperationCompleteMessage) from external services
+(like Agent Generator) and triggers the appropriate stream registry and
+chat service updates via process_operation_success/process_operation_failure.
+
+Why Redis Streams instead of RabbitMQ?
+--------------------------------------
+While the project typically uses RabbitMQ for async task queues (e.g., execution
+queue), Redis Streams was chosen for chat completion notifications because:
+
+1. **Unified Infrastructure**: The SSE reconnection feature already uses Redis
+   Streams (via stream_registry) for message persistence and replay. Using Redis
+   Streams for completion notifications keeps all chat streaming infrastructure
+   in one system, simplifying operations and reducing cross-system coordination.
+
+2. **Message Replay**: Redis Streams support XREAD with arbitrary message IDs,
+   allowing consumers to replay missed messages after reconnection. This aligns
+   with the SSE reconnection pattern where clients can resume from last_message_id.
+
+3. **Consumer Groups with XAUTOCLAIM**: Redis consumer groups provide automatic
+   load balancing across pods with explicit message claiming (XAUTOCLAIM) for
+   recovering from dead consumers - ideal for the completion callback pattern.
+
+4. **Lower Latency**: For real-time SSE updates, Redis (already in-memory for
+   stream_registry) provides lower latency than an additional RabbitMQ hop.
+
+5. **Atomicity with Task State**: Completion processing often needs to update
+   task metadata stored in Redis. Keeping both in Redis enables simpler
+   transactional semantics without distributed coordination.
+
+The consumer uses Redis Streams with consumer groups for reliable message
+processing across multiple platform pods, with XAUTOCLAIM for reclaiming
+stale pending messages from dead consumers.
+"""
+
+import asyncio
+import logging
+import os
+import uuid
+from typing import Any
+
+import orjson
+from prisma import Prisma
+from pydantic import BaseModel
+from redis.exceptions import ResponseError
+
+from backend.data.redis_client import get_redis_async
+
+from . import stream_registry
+from .completion_handler import process_operation_failure, process_operation_success
+from .config import ChatConfig
+
+logger = logging.getLogger(__name__)
+config = ChatConfig()
+
+
+class OperationCompleteMessage(BaseModel):
+    """Message format for operation completion notifications."""
+
+    operation_id: str
+    task_id: str
+    success: bool
+    result: dict | str | None = None
+    error: str | None = None
+
+
+class ChatCompletionConsumer:
+    """Consumer for chat operation completion messages from Redis Streams.
+
+    This consumer initializes its own Prisma client in start() to ensure
+    database operations work correctly within this async context.
+
+    Uses Redis consumer groups to allow multiple platform pods to consume
+    messages reliably with automatic redelivery on failure.
+    """
+
+    def __init__(self):
+        self._consumer_task: asyncio.Task | None = None
+        self._running = False
+        self._prisma: Prisma | None = None
+        self._consumer_name = f"consumer-{uuid.uuid4().hex[:8]}"
+
+    async def start(self) -> None:
+        """Start the completion consumer."""
+        if self._running:
+            logger.warning("Completion consumer already running")
+            return
+
+        # Create consumer group if it doesn't exist
+        try:
+            redis = await get_redis_async()
+            await redis.xgroup_create(
+                config.stream_completion_name,
+                config.stream_consumer_group,
+                id="0",
+                mkstream=True,
+            )
+            logger.info(
+                f"Created consumer group '{config.stream_consumer_group}' "
+                f"on stream '{config.stream_completion_name}'"
+            )
+        except ResponseError as e:
+            if "BUSYGROUP" in str(e):
+                logger.debug(
+                    f"Consumer group '{config.stream_consumer_group}' already exists"
+                )
+            else:
+                raise
+
+        self._running = True
+        self._consumer_task = asyncio.create_task(self._consume_messages())
+        logger.info(
+            f"Chat completion consumer started (consumer: {self._consumer_name})"
+        )
+
+    async def _ensure_prisma(self) -> Prisma:
+        """Lazily initialize Prisma client on first use."""
+        if self._prisma is None:
+            database_url = os.getenv("DATABASE_URL", "postgresql://localhost:5432")
+            self._prisma = Prisma(datasource={"url": database_url})
+            await self._prisma.connect()
+            logger.info("[COMPLETION] Consumer Prisma client connected (lazy init)")
+        return self._prisma
+
+    async def stop(self) -> None:
+        """Stop the completion consumer."""
+        self._running = False
+
+        if self._consumer_task:
+            self._consumer_task.cancel()
+            try:
+                await self._consumer_task
+            except asyncio.CancelledError:
+                pass
+            self._consumer_task = None
+
+        if self._prisma:
+            await self._prisma.disconnect()
+            self._prisma = None
+            logger.info("[COMPLETION] Consumer Prisma client disconnected")
+
+        logger.info("Chat completion consumer stopped")
+
+    async def _consume_messages(self) -> None:
+        """Main message consumption loop with retry logic."""
+        max_retries = 10
+        retry_delay = 5  # seconds
+        retry_count = 0
+        block_timeout = 5000  # milliseconds
+
+        while self._running and retry_count < max_retries:
+            try:
+                redis = await get_redis_async()
+
+                # Reset retry count on successful connection
+                retry_count = 0
+
+                while self._running:
+                    # First, claim any stale pending messages from dead consumers
+                    # Redis does NOT auto-redeliver pending messages; we must explicitly
+                    # claim them using XAUTOCLAIM
+                    try:
+                        claimed_result = await redis.xautoclaim(
+                            name=config.stream_completion_name,
+                            groupname=config.stream_consumer_group,
+                            consumername=self._consumer_name,
+                            min_idle_time=config.stream_claim_min_idle_ms,
+                            start_id="0-0",
+                            count=10,
+                        )
+                        # xautoclaim returns: (next_start_id, [(id, data), ...], [deleted_ids])
+                        if claimed_result and len(claimed_result) >= 2:
+                            claimed_entries = claimed_result[1]
+                            if claimed_entries:
+                                logger.info(
+                                    f"Claimed {len(claimed_entries)} stale pending messages"
+                                )
+                                for entry_id, data in claimed_entries:
+                                    if not self._running:
+                                        return
+                                    await self._process_entry(redis, entry_id, data)
+                    except Exception as e:
+                        logger.warning(f"XAUTOCLAIM failed (non-fatal): {e}")
+
+                    # Read new messages from the stream
+                    messages = await redis.xreadgroup(
+                        groupname=config.stream_consumer_group,
+                        consumername=self._consumer_name,
+                        streams={config.stream_completion_name: ">"},
+                        block=block_timeout,
+                        count=10,
+                    )
+
+                    if not messages:
+                        continue
+
+                    for stream_name, entries in messages:
+                        for entry_id, data in entries:
+                            if not self._running:
+                                return
+                            await self._process_entry(redis, entry_id, data)
+
+            except asyncio.CancelledError:
+                logger.info("Consumer cancelled")
+                return
+            except Exception as e:
+                retry_count += 1
+                logger.error(
+                    f"Consumer error (retry {retry_count}/{max_retries}): {e}",
+                    exc_info=True,
+                )
+                if self._running and retry_count < max_retries:
+                    await asyncio.sleep(retry_delay)
+                else:
+                    logger.error("Max retries reached, stopping consumer")
+                    return
+
+    async def _process_entry(
+        self, redis: Any, entry_id: str, data: dict[str, Any]
+    ) -> None:
+        """Process a single stream entry and acknowledge it on success.
+
+        Args:
+            redis: Redis client connection
+            entry_id: The stream entry ID
+            data: The entry data dict
+        """
+        try:
+            # Handle the message
+            message_data = data.get("data")
+            if message_data:
+                await self._handle_message(
+                    message_data.encode()
+                    if isinstance(message_data, str)
+                    else message_data
+                )
+
+            # Acknowledge the message after successful processing
+            await redis.xack(
+                config.stream_completion_name,
+                config.stream_consumer_group,
+                entry_id,
+            )
+        except Exception as e:
+            logger.error(
+                f"Error processing completion message {entry_id}: {e}",
+                exc_info=True,
+            )
+            # Message remains in pending state and will be claimed by
+            # XAUTOCLAIM after min_idle_time expires
+
+    async def _handle_message(self, body: bytes) -> None:
+        """Handle a completion message using our own Prisma client."""
+        try:
+            data = orjson.loads(body)
+            message = OperationCompleteMessage(**data)
+        except Exception as e:
+            logger.error(f"Failed to parse completion message: {e}")
+            return
+
+        logger.info(
+            f"[COMPLETION] Received completion for operation {message.operation_id} "
+            f"(task_id={message.task_id}, success={message.success})"
+        )
+
+        # Find task in registry
+        task = await stream_registry.find_task_by_operation_id(message.operation_id)
+        if task is None:
+            task = await stream_registry.get_task(message.task_id)
+
+        if task is None:
+            logger.warning(
+                f"[COMPLETION] Task not found for operation {message.operation_id} "
+                f"(task_id={message.task_id})"
+            )
+            return
+
+        logger.info(
+            f"[COMPLETION] Found task: task_id={task.task_id}, "
+            f"session_id={task.session_id}, tool_call_id={task.tool_call_id}"
+        )
+
+        # Guard against empty task fields
+        if not task.task_id or not task.session_id or not task.tool_call_id:
+            logger.error(
+                f"[COMPLETION] Task has empty critical fields! "
+                f"task_id={task.task_id!r}, session_id={task.session_id!r}, "
+                f"tool_call_id={task.tool_call_id!r}"
+            )
+            return
+
+        if message.success:
+            await self._handle_success(task, message)
+        else:
+            await self._handle_failure(task, message)
+
+    async def _handle_success(
+        self,
+        task: stream_registry.ActiveTask,
+        message: OperationCompleteMessage,
+    ) -> None:
+        """Handle successful operation completion."""
+        prisma = await self._ensure_prisma()
+        await process_operation_success(task, message.result, prisma)
+
+    async def _handle_failure(
+        self,
+        task: stream_registry.ActiveTask,
+        message: OperationCompleteMessage,
+    ) -> None:
+        """Handle failed operation completion."""
+        prisma = await self._ensure_prisma()
+        await process_operation_failure(task, message.error, prisma)
+
+
+# Module-level consumer instance
+_consumer: ChatCompletionConsumer | None = None
+
+
+async def start_completion_consumer() -> None:
+    """Start the global completion consumer."""
+    global _consumer
+    if _consumer is None:
+        _consumer = ChatCompletionConsumer()
+    await _consumer.start()
+
+
+async def stop_completion_consumer() -> None:
+    """Stop the global completion consumer."""
+    global _consumer
+    if _consumer:
+        await _consumer.stop()
+        _consumer = None
+
+
+async def publish_operation_complete(
+    operation_id: str,
+    task_id: str,
+    success: bool,
+    result: dict | str | None = None,
+    error: str | None = None,
+) -> None:
+    """Publish an operation completion message to Redis Streams.
+
+    Args:
+        operation_id: The operation ID that completed.
+        task_id: The task ID associated with the operation.
+        success: Whether the operation succeeded.
+        result: The result data (for success).
+        error: The error message (for failure).
+    """
+    message = OperationCompleteMessage(
+        operation_id=operation_id,
+        task_id=task_id,
+        success=success,
+        result=result,
+        error=error,
+    )
+
+    redis = await get_redis_async()
+    await redis.xadd(
+        config.stream_completion_name,
+        {"data": message.model_dump_json()},
+        maxlen=config.stream_max_length,
+    )
+    logger.info(f"Published completion for operation {operation_id}")
diff --git a/autogpt_platform/backend/backend/api/features/chat/completion_handler.py b/autogpt_platform/backend/backend/api/features/chat/completion_handler.py
new file mode 100644
index 0000000000..905fa2ddba
--- /dev/null
+++ b/autogpt_platform/backend/backend/api/features/chat/completion_handler.py
@@ -0,0 +1,344 @@
+"""Shared completion handling for operation success and failure.
+
+This module provides common logic for handling operation completion from both:
+- The Redis Streams consumer (completion_consumer.py)
+- The HTTP webhook endpoint (routes.py)
+"""
+
+import logging
+from typing import Any
+
+import orjson
+from prisma import Prisma
+
+from . import service as chat_service
+from . import stream_registry
+from .response_model import StreamError, StreamToolOutputAvailable
+from .tools.models import ErrorResponse
+
+logger = logging.getLogger(__name__)
+
+# Tools that produce agent_json that needs to be saved to library
+AGENT_GENERATION_TOOLS = {"create_agent", "edit_agent"}
+
+# Keys that should be stripped from agent_json when returning in error responses
+SENSITIVE_KEYS = frozenset(
+    {
+        "api_key",
+        "apikey",
+        "api_secret",
+        "password",
+        "secret",
+        "credentials",
+        "credential",
+        "token",
+        "access_token",
+        "refresh_token",
+        "private_key",
+        "privatekey",
+        "auth",
+        "authorization",
+    }
+)
+
+
+def _sanitize_agent_json(obj: Any) -> Any:
+    """Recursively sanitize agent_json by removing sensitive keys.
+
+    Args:
+        obj: The object to sanitize (dict, list, or primitive)
+
+    Returns:
+        Sanitized copy with sensitive keys removed/redacted
+    """
+    if isinstance(obj, dict):
+        return {
+            k: "[REDACTED]" if k.lower() in SENSITIVE_KEYS else _sanitize_agent_json(v)
+            for k, v in obj.items()
+        }
+    elif isinstance(obj, list):
+        return [_sanitize_agent_json(item) for item in obj]
+    else:
+        return obj
+
+
+class ToolMessageUpdateError(Exception):
+    """Raised when updating a tool message in the database fails."""
+
+    pass
+
+
+async def _update_tool_message(
+    session_id: str,
+    tool_call_id: str,
+    content: str,
+    prisma_client: Prisma | None,
+) -> None:
+    """Update tool message in database.
+
+    Args:
+        session_id: The session ID
+        tool_call_id: The tool call ID to update
+        content: The new content for the message
+        prisma_client: Optional Prisma client. If None, uses chat_service.
+
+    Raises:
+        ToolMessageUpdateError: If the database update fails. The caller should
+            handle this to avoid marking the task as completed with inconsistent state.
+    """
+    try:
+        if prisma_client:
+            # Use provided Prisma client (for consumer with its own connection)
+            updated_count = await prisma_client.chatmessage.update_many(
+                where={
+                    "sessionId": session_id,
+                    "toolCallId": tool_call_id,
+                },
+                data={"content": content},
+            )
+            # Check if any rows were updated - 0 means message not found
+            if updated_count == 0:
+                raise ToolMessageUpdateError(
+                    f"No message found with tool_call_id={tool_call_id} in session {session_id}"
+                )
+        else:
+            # Use service function (for webhook endpoint)
+            await chat_service._update_pending_operation(
+                session_id=session_id,
+                tool_call_id=tool_call_id,
+                result=content,
+            )
+    except ToolMessageUpdateError:
+        raise
+    except Exception as e:
+        logger.error(f"[COMPLETION] Failed to update tool message: {e}", exc_info=True)
+        raise ToolMessageUpdateError(
+            f"Failed to update tool message for tool_call_id={tool_call_id}: {e}"
+        ) from e
+
+
+def serialize_result(result: dict | list | str | int | float | bool | None) -> str:
+    """Serialize result to JSON string with sensible defaults.
+
+    Args:
+        result: The result to serialize. Can be a dict, list, string,
+            number, boolean, or None.
+
+    Returns:
+        JSON string representation of the result. Returns '{"status": "completed"}'
+        only when result is explicitly None.
+    """
+    if isinstance(result, str):
+        return result
+    if result is None:
+        return '{"status": "completed"}'
+    return orjson.dumps(result).decode("utf-8")
+
+
+async def _save_agent_from_result(
+    result: dict[str, Any],
+    user_id: str | None,
+    tool_name: str,
+) -> dict[str, Any]:
+    """Save agent to library if result contains agent_json.
+
+    Args:
+        result: The result dict that may contain agent_json
+        user_id: The user ID to save the agent for
+        tool_name: The tool name (create_agent or edit_agent)
+
+    Returns:
+        Updated result dict with saved agent details, or original result if no agent_json
+    """
+    if not user_id:
+        logger.warning("[COMPLETION] Cannot save agent: no user_id in task")
+        return result
+
+    agent_json = result.get("agent_json")
+    if not agent_json:
+        logger.warning(
+            f"[COMPLETION] {tool_name} completed but no agent_json in result"
+        )
+        return result
+
+    try:
+        from .tools.agent_generator import save_agent_to_library
+
+        is_update = tool_name == "edit_agent"
+        created_graph, library_agent = await save_agent_to_library(
+            agent_json, user_id, is_update=is_update
+        )
+
+        logger.info(
+            f"[COMPLETION] Saved agent '{created_graph.name}' to library "
+            f"(graph_id={created_graph.id}, library_agent_id={library_agent.id})"
+        )
+
+        # Return a response similar to AgentSavedResponse
+        return {
+            "type": "agent_saved",
+            "message": f"Agent '{created_graph.name}' has been saved to your library!",
+            "agent_id": created_graph.id,
+            "agent_name": created_graph.name,
+            "library_agent_id": library_agent.id,
+            "library_agent_link": f"/library/agents/{library_agent.id}",
+            "agent_page_link": f"/build?flowID={created_graph.id}",
+        }
+    except Exception as e:
+        logger.error(
+            f"[COMPLETION] Failed to save agent to library: {e}",
+            exc_info=True,
+        )
+        # Return error but don't fail the whole operation
+        # Sanitize agent_json to remove sensitive keys before returning
+        return {
+            "type": "error",
+            "message": f"Agent was generated but failed to save: {str(e)}",
+            "error": str(e),
+            "agent_json": _sanitize_agent_json(agent_json),
+        }
+
+
+async def process_operation_success(
+    task: stream_registry.ActiveTask,
+    result: dict | str | None,
+    prisma_client: Prisma | None = None,
+) -> None:
+    """Handle successful operation completion.
+
+    Publishes the result to the stream registry, updates the database,
+    generates LLM continuation, and marks the task as completed.
+
+    Args:
+        task: The active task that completed
+        result: The result data from the operation
+        prisma_client: Optional Prisma client for database operations.
+            If None, uses chat_service._update_pending_operation instead.
+
+    Raises:
+        ToolMessageUpdateError: If the database update fails. The task will be
+            marked as failed instead of completed to avoid inconsistent state.
+    """
+    # For agent generation tools, save the agent to library
+    if task.tool_name in AGENT_GENERATION_TOOLS and isinstance(result, dict):
+        result = await _save_agent_from_result(result, task.user_id, task.tool_name)
+
+    # Serialize result for output (only substitute default when result is exactly None)
+    result_output = result if result is not None else {"status": "completed"}
+    output_str = (
+        result_output
+        if isinstance(result_output, str)
+        else orjson.dumps(result_output).decode("utf-8")
+    )
+
+    # Publish result to stream registry
+    await stream_registry.publish_chunk(
+        task.task_id,
+        StreamToolOutputAvailable(
+            toolCallId=task.tool_call_id,
+            toolName=task.tool_name,
+            output=output_str,
+            success=True,
+        ),
+    )
+
+    # Update pending operation in database
+    # If this fails, we must not continue to mark the task as completed
+    result_str = serialize_result(result)
+    try:
+        await _update_tool_message(
+            session_id=task.session_id,
+            tool_call_id=task.tool_call_id,
+            content=result_str,
+            prisma_client=prisma_client,
+        )
+    except ToolMessageUpdateError:
+        # DB update failed - mark task as failed to avoid inconsistent state
+        logger.error(
+            f"[COMPLETION] DB update failed for task {task.task_id}, "
+            "marking as failed instead of completed"
+        )
+        await stream_registry.publish_chunk(
+            task.task_id,
+            StreamError(errorText="Failed to save operation result to database"),
+        )
+        await stream_registry.mark_task_completed(task.task_id, status="failed")
+        raise
+
+    # Generate LLM continuation with streaming
+    try:
+        await chat_service._generate_llm_continuation_with_streaming(
+            session_id=task.session_id,
+            user_id=task.user_id,
+            task_id=task.task_id,
+        )
+    except Exception as e:
+        logger.error(
+            f"[COMPLETION] Failed to generate LLM continuation: {e}",
+            exc_info=True,
+        )
+
+    # Mark task as completed and release Redis lock
+    await stream_registry.mark_task_completed(task.task_id, status="completed")
+    try:
+        await chat_service._mark_operation_completed(task.tool_call_id)
+    except Exception as e:
+        logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
+
+    logger.info(
+        f"[COMPLETION] Successfully processed completion for task {task.task_id}"
+    )
+
+
+async def process_operation_failure(
+    task: stream_registry.ActiveTask,
+    error: str | None,
+    prisma_client: Prisma | None = None,
+) -> None:
+    """Handle failed operation completion.
+
+    Publishes the error to the stream registry, updates the database with
+    the error response, and marks the task as failed.
+
+    Args:
+        task: The active task that failed
+        error: The error message from the operation
+        prisma_client: Optional Prisma client for database operations.
+            If None, uses chat_service._update_pending_operation instead.
+    """
+    error_msg = error or "Operation failed"
+
+    # Publish error to stream registry
+    await stream_registry.publish_chunk(
+        task.task_id,
+        StreamError(errorText=error_msg),
+    )
+
+    # Update pending operation with error
+    # If this fails, we still continue to mark the task as failed
+    error_response = ErrorResponse(
+        message=error_msg,
+        error=error,
+    )
+    try:
+        await _update_tool_message(
+            session_id=task.session_id,
+            tool_call_id=task.tool_call_id,
+            content=error_response.model_dump_json(),
+            prisma_client=prisma_client,
+        )
+    except ToolMessageUpdateError:
+        # DB update failed - log but continue with cleanup
+        logger.error(
+            f"[COMPLETION] DB update failed while processing failure for task {task.task_id}, "
+            "continuing with cleanup"
+        )
+
+    # Mark task as failed and release Redis lock
+    await stream_registry.mark_task_completed(task.task_id, status="failed")
+    try:
+        await chat_service._mark_operation_completed(task.tool_call_id)
+    except Exception as e:
+        logger.error(f"[COMPLETION] Failed to mark operation completed: {e}")
+
+    logger.info(f"[COMPLETION] Processed failure for task {task.task_id}: {error_msg}")
diff --git a/autogpt_platform/backend/backend/api/features/chat/config.py b/autogpt_platform/backend/backend/api/features/chat/config.py
index dba7934877..808692f97f 100644
--- a/autogpt_platform/backend/backend/api/features/chat/config.py
+++ b/autogpt_platform/backend/backend/api/features/chat/config.py
@@ -11,7 +11,7 @@ class ChatConfig(BaseSettings):
 
     # OpenAI API Configuration
     model: str = Field(
-        default="anthropic/claude-opus-4.5", description="Default model to use"
+        default="anthropic/claude-opus-4.6", description="Default model to use"
     )
     title_model: str = Field(
         default="openai/gpt-4o-mini",
@@ -44,6 +44,48 @@ class ChatConfig(BaseSettings):
         description="TTL in seconds for long-running operation tracking in Redis (safety net if pod dies)",
     )
 
+    # Stream registry configuration for SSE reconnection
+    stream_ttl: int = Field(
+        default=3600,
+        description="TTL in seconds for stream data in Redis (1 hour)",
+    )
+    stream_max_length: int = Field(
+        default=10000,
+        description="Maximum number of messages to store per stream",
+    )
+
+    # Redis Streams configuration for completion consumer
+    stream_completion_name: str = Field(
+        default="chat:completions",
+        description="Redis Stream name for operation completions",
+    )
+    stream_consumer_group: str = Field(
+        default="chat_consumers",
+        description="Consumer group name for completion stream",
+    )
+    stream_claim_min_idle_ms: int = Field(
+        default=60000,
+        description="Minimum idle time in milliseconds before claiming pending messages from dead consumers",
+    )
+
+    # Redis key prefixes for stream registry
+    task_meta_prefix: str = Field(
+        default="chat:task:meta:",
+        description="Prefix for task metadata hash keys",
+    )
+    task_stream_prefix: str = Field(
+        default="chat:stream:",
+        description="Prefix for task message stream keys",
+    )
+    task_op_prefix: str = Field(
+        default="chat:task:op:",
+        description="Prefix for operation ID to task ID mapping keys",
+    )
+    internal_api_key: str | None = Field(
+        default=None,
+        description="API key for internal webhook callbacks (env: CHAT_INTERNAL_API_KEY)",
+    )
+
     # Langfuse Prompt Management Configuration
     # Note: Langfuse credentials are in Settings().secrets (settings.py)
     langfuse_prompt_name: str = Field(
@@ -51,6 +93,12 @@ class ChatConfig(BaseSettings):
         description="Name of the prompt in Langfuse to fetch",
     )
 
+    # Extended thinking configuration for Claude models
+    thinking_enabled: bool = Field(
+        default=True,
+        description="Enable adaptive thinking for Claude models via OpenRouter",
+    )
+
     @field_validator("api_key", mode="before")
     @classmethod
     def get_api_key(cls, v):
@@ -82,6 +130,14 @@ class ChatConfig(BaseSettings):
                 v = "https://openrouter.ai/api/v1"
         return v
 
+    @field_validator("internal_api_key", mode="before")
+    @classmethod
+    def get_internal_api_key(cls, v):
+        """Get internal API key from environment if not provided."""
+        if v is None:
+            v = os.getenv("CHAT_INTERNAL_API_KEY")
+        return v
+
     # Prompt paths for different contexts
     PROMPT_PATHS: dict[str, str] = {
         "default": "prompts/chat_system.md",
diff --git a/autogpt_platform/backend/backend/api/features/chat/db.py b/autogpt_platform/backend/backend/api/features/chat/db.py
index d34b4e5b07..303ea0a698 100644
--- a/autogpt_platform/backend/backend/api/features/chat/db.py
+++ b/autogpt_platform/backend/backend/api/features/chat/db.py
@@ -45,10 +45,7 @@ async def create_chat_session(
         successfulAgentRuns=SafeJson({}),
         successfulAgentSchedules=SafeJson({}),
     )
-    return await PrismaChatSession.prisma().create(
-        data=data,
-        include={"Messages": True},
-    )
+    return await PrismaChatSession.prisma().create(data=data)
 
 
 async def update_chat_session(
diff --git a/autogpt_platform/backend/backend/api/features/chat/response_model.py b/autogpt_platform/backend/backend/api/features/chat/response_model.py
index 53a8cf3a1f..8ea0c1f97a 100644
--- a/autogpt_platform/backend/backend/api/features/chat/response_model.py
+++ b/autogpt_platform/backend/backend/api/features/chat/response_model.py
@@ -10,6 +10,8 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from backend.util.json import dumps as json_dumps
+
 
 class ResponseType(str, Enum):
     """Types of streaming responses following AI SDK protocol."""
@@ -18,6 +20,10 @@ class ResponseType(str, Enum):
     START = "start"
     FINISH = "finish"
 
+    # Step lifecycle (one LLM API call within a message)
+    START_STEP = "start-step"
+    FINISH_STEP = "finish-step"
+
     # Text streaming
     TEXT_START = "text-start"
     TEXT_DELTA = "text-delta"
@@ -52,6 +58,20 @@ class StreamStart(StreamBaseResponse):
 
     type: ResponseType = ResponseType.START
     messageId: str = Field(..., description="Unique message ID")
+    taskId: str | None = Field(
+        default=None,
+        description="Task ID for SSE reconnection. Clients can reconnect using GET /tasks/{taskId}/stream",
+    )
+
+    def to_sse(self) -> str:
+        """Convert to SSE format, excluding non-protocol fields like taskId."""
+        import json
+
+        data: dict[str, Any] = {
+            "type": self.type.value,
+            "messageId": self.messageId,
+        }
+        return f"data: {json.dumps(data)}\n\n"
 
 
 class StreamFinish(StreamBaseResponse):
@@ -60,6 +80,26 @@ class StreamFinish(StreamBaseResponse):
     type: ResponseType = ResponseType.FINISH
 
 
+class StreamStartStep(StreamBaseResponse):
+    """Start of a step (one LLM API call within a message).
+
+    The AI SDK uses this to add a step-start boundary to message.parts,
+    enabling visual separation between multiple LLM calls in a single message.
+    """
+
+    type: ResponseType = ResponseType.START_STEP
+
+
+class StreamFinishStep(StreamBaseResponse):
+    """End of a step (one LLM API call within a message).
+
+    The AI SDK uses this to reset activeTextParts and activeReasoningParts,
+    so the next LLM call in a tool-call continuation starts with clean state.
+    """
+
+    type: ResponseType = ResponseType.FINISH_STEP
+
+
 # ========== Text Streaming ==========
 
 
@@ -113,7 +153,7 @@ class StreamToolOutputAvailable(StreamBaseResponse):
     type: ResponseType = ResponseType.TOOL_OUTPUT_AVAILABLE
     toolCallId: str = Field(..., description="Tool call ID this responds to")
     output: str | dict[str, Any] = Field(..., description="Tool execution output")
-    # Additional fields for internal use (not part of AI SDK spec but useful)
+    # Keep these for internal backend use
     toolName: str | None = Field(
         default=None, description="Name of the tool that was executed"
     )
@@ -121,6 +161,17 @@ class StreamToolOutputAvailable(StreamBaseResponse):
         default=True, description="Whether the tool execution succeeded"
     )
 
+    def to_sse(self) -> str:
+        """Convert to SSE format, excluding non-spec fields."""
+        import json
+
+        data = {
+            "type": self.type.value,
+            "toolCallId": self.toolCallId,
+            "output": self.output,
+        }
+        return f"data: {json.dumps(data)}\n\n"
+
 
 # ========== Other ==========
 
@@ -144,6 +195,18 @@ class StreamError(StreamBaseResponse):
         default=None, description="Additional error details"
     )
 
+    def to_sse(self) -> str:
+        """Convert to SSE format, only emitting fields required by AI SDK protocol.
+
+        The AI SDK uses z.strictObject({type, errorText}) which rejects
+        any extra fields like `code` or `details`.
+        """
+        data = {
+            "type": self.type.value,
+            "errorText": self.errorText,
+        }
+        return f"data: {json_dumps(data)}\n\n"
+
 
 class StreamHeartbeat(StreamBaseResponse):
     """Heartbeat to keep SSE connection alive during long-running operations.
diff --git a/autogpt_platform/backend/backend/api/features/chat/routes.py b/autogpt_platform/backend/backend/api/features/chat/routes.py
index cab51543b1..c6f37569b7 100644
--- a/autogpt_platform/backend/backend/api/features/chat/routes.py
+++ b/autogpt_platform/backend/backend/api/features/chat/routes.py
@@ -1,19 +1,45 @@
 """Chat API routes for chat session management and streaming via SSE."""
 
 import logging
+import uuid as uuid_module
 from collections.abc import AsyncGenerator
 from typing import Annotated
 
 from autogpt_libs import auth
-from fastapi import APIRouter, Depends, Query, Security
+from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
 from backend.util.exceptions import NotFoundError
 
 from . import service as chat_service
+from . import stream_registry
+from .completion_handler import process_operation_failure, process_operation_success
 from .config import ChatConfig
 from .model import ChatSession, create_chat_session, get_chat_session, get_user_sessions
+from .response_model import StreamFinish, StreamHeartbeat
+from .tools.models import (
+    AgentDetailsResponse,
+    AgentOutputResponse,
+    AgentPreviewResponse,
+    AgentSavedResponse,
+    AgentsFoundResponse,
+    BlockListResponse,
+    BlockOutputResponse,
+    ClarificationNeededResponse,
+    DocPageResponse,
+    DocSearchResultsResponse,
+    ErrorResponse,
+    ExecutionStartedResponse,
+    InputValidationErrorResponse,
+    NeedLoginResponse,
+    NoResultsResponse,
+    OperationInProgressResponse,
+    OperationPendingResponse,
+    OperationStartedResponse,
+    SetupRequirementsResponse,
+    UnderstandingUpdatedResponse,
+)
 
 config = ChatConfig()
 
@@ -55,6 +81,15 @@ class CreateSessionResponse(BaseModel):
     user_id: str | None
 
 
+class ActiveStreamInfo(BaseModel):
+    """Information about an active stream for reconnection."""
+
+    task_id: str
+    last_message_id: str  # Redis Stream message ID for resumption
+    operation_id: str  # Operation ID for completion tracking
+    tool_name: str  # Name of the tool being executed
+
+
 class SessionDetailResponse(BaseModel):
     """Response model providing complete details for a chat session, including messages."""
 
@@ -63,6 +98,7 @@ class SessionDetailResponse(BaseModel):
     updated_at: str
     user_id: str | None
     messages: list[dict]
+    active_stream: ActiveStreamInfo | None = None  # Present if stream is still active
 
 
 class SessionSummaryResponse(BaseModel):
@@ -81,6 +117,14 @@ class ListSessionsResponse(BaseModel):
     total: int
 
 
+class OperationCompleteRequest(BaseModel):
+    """Request model for external completion webhook."""
+
+    success: bool
+    result: dict | str | None = None
+    error: str | None = None
+
+
 # ========== Routes ==========
 
 
@@ -166,13 +210,14 @@ async def get_session(
     Retrieve the details of a specific chat session.
 
     Looks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.
+    If there's an active stream for this session, returns the task_id for reconnection.
 
     Args:
         session_id: The unique identifier for the desired chat session.
         user_id: The optional authenticated user ID, or None for anonymous access.
 
     Returns:
-        SessionDetailResponse: Details for the requested session, or None if not found.
+        SessionDetailResponse: Details for the requested session, including active_stream info if applicable.
 
     """
     session = await get_chat_session(session_id, user_id)
@@ -180,11 +225,28 @@ async def get_session(
         raise NotFoundError(f"Session {session_id} not found.")
 
     messages = [message.model_dump() for message in session.messages]
-    logger.info(
-        f"Returning session {session_id}: "
-        f"message_count={len(messages)}, "
-        f"roles={[m.get('role') for m in messages]}"
+
+    # Check if there's an active stream for this session
+    active_stream_info = None
+    active_task, last_message_id = await stream_registry.get_active_task_for_session(
+        session_id, user_id
     )
+    if active_task:
+        # Filter out the in-progress assistant message from the session response.
+        # The client will receive the complete assistant response through the SSE
+        # stream replay instead, preventing duplicate content.
+        if messages and messages[-1].get("role") == "assistant":
+            messages = messages[:-1]
+
+        # Use "0-0" as last_message_id to replay the stream from the beginning.
+        # Since we filtered out the cached assistant message, the client needs
+        # the full stream to reconstruct the response.
+        active_stream_info = ActiveStreamInfo(
+            task_id=active_task.task_id,
+            last_message_id="0-0",
+            operation_id=active_task.operation_id,
+            tool_name=active_task.tool_name,
+        )
 
     return SessionDetailResponse(
         id=session.session_id,
@@ -192,6 +254,7 @@ async def get_session(
         updated_at=session.updated_at.isoformat(),
         user_id=session.user_id or None,
         messages=messages,
+        active_stream=active_stream_info,
     )
 
 
@@ -211,49 +274,264 @@ async def stream_chat_post(
       - Tool call UI elements (if invoked)
       - Tool execution results
 
+    The AI generation runs in a background task that continues even if the client disconnects.
+    All chunks are written to Redis for reconnection support. If the client disconnects,
+    they can reconnect using GET /tasks/{task_id}/stream to resume from where they left off.
+
     Args:
         session_id: The chat session identifier to associate with the streamed messages.
         request: Request body containing message, is_user_message, and optional context.
         user_id: Optional authenticated user ID.
     Returns:
-        StreamingResponse: SSE-formatted response chunks.
+        StreamingResponse: SSE-formatted response chunks. First chunk is a "start" event
+        containing the task_id for reconnection.
 
     """
-    session = await _validate_and_get_session(session_id, user_id)
+    import asyncio
+    import time
 
-    async def event_generator() -> AsyncGenerator[str, None]:
-        chunk_count = 0
-        first_chunk_type: str | None = None
-        async for chunk in chat_service.stream_chat_completion(
-            session_id,
-            request.message,
-            is_user_message=request.is_user_message,
-            user_id=user_id,
-            session=session,  # Pass pre-fetched session to avoid double-fetch
-            context=request.context,
-        ):
-            if chunk_count < 3:
-                logger.info(
-                    "Chat stream chunk",
-                    extra={
-                        "session_id": session_id,
-                        "chunk_type": str(chunk.type),
-                    },
-                )
-            if not first_chunk_type:
-                first_chunk_type = str(chunk.type)
-            chunk_count += 1
-            yield chunk.to_sse()
+    stream_start_time = time.perf_counter()
+    log_meta = {"component": "ChatStream", "session_id": session_id}
+    if user_id:
+        log_meta["user_id"] = user_id
+
+    logger.info(
+        f"[TIMING] stream_chat_post STARTED, session={session_id}, "
+        f"user={user_id}, message_len={len(request.message)}",
+        extra={"json_fields": log_meta},
+    )
+
+    session = await _validate_and_get_session(session_id, user_id)
+    logger.info(
+        f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "duration_ms": (time.perf_counter() - stream_start_time) * 1000,
+            }
+        },
+    )
+
+    # Create a task in the stream registry for reconnection support
+    task_id = str(uuid_module.uuid4())
+    operation_id = str(uuid_module.uuid4())
+    log_meta["task_id"] = task_id
+
+    task_create_start = time.perf_counter()
+    await stream_registry.create_task(
+        task_id=task_id,
+        session_id=session_id,
+        user_id=user_id,
+        tool_call_id="chat_stream",  # Not a tool call, but needed for the model
+        tool_name="chat",
+        operation_id=operation_id,
+    )
+    logger.info(
+        f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "duration_ms": (time.perf_counter() - task_create_start) * 1000,
+            }
+        },
+    )
+
+    # Background task that runs the AI generation independently of SSE connection
+    async def run_ai_generation():
+        import time as time_module
+
+        gen_start_time = time_module.perf_counter()
         logger.info(
-            "Chat stream completed",
-            extra={
-                "session_id": session_id,
-                "chunk_count": chunk_count,
-                "first_chunk_type": first_chunk_type,
-            },
+            f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
+            extra={"json_fields": log_meta},
         )
-        # AI SDK protocol termination
-        yield "data: [DONE]\n\n"
+        first_chunk_time, ttfc = None, None
+        chunk_count = 0
+        try:
+            async for chunk in chat_service.stream_chat_completion(
+                session_id,
+                request.message,
+                is_user_message=request.is_user_message,
+                user_id=user_id,
+                session=session,  # Pass pre-fetched session to avoid double-fetch
+                context=request.context,
+                _task_id=task_id,  # Pass task_id so service emits start with taskId for reconnection
+            ):
+                chunk_count += 1
+                if first_chunk_time is None:
+                    first_chunk_time = time_module.perf_counter()
+                    ttfc = first_chunk_time - gen_start_time
+                    logger.info(
+                        f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
+                        extra={
+                            "json_fields": {
+                                **log_meta,
+                                "chunk_type": type(chunk).__name__,
+                                "time_to_first_chunk_ms": ttfc * 1000,
+                            }
+                        },
+                    )
+                # Write to Redis (subscribers will receive via XREAD)
+                await stream_registry.publish_chunk(task_id, chunk)
+
+            gen_end_time = time_module.perf_counter()
+            total_time = (gen_end_time - gen_start_time) * 1000
+            logger.info(
+                f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
+                f"task={task_id}, session={session_id}, "
+                f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "total_time_ms": total_time,
+                        "time_to_first_chunk_ms": (
+                            ttfc * 1000 if ttfc is not None else None
+                        ),
+                        "n_chunks": chunk_count,
+                    }
+                },
+            )
+            await stream_registry.mark_task_completed(task_id, "completed")
+        except Exception as e:
+            elapsed = time_module.perf_counter() - gen_start_time
+            logger.error(
+                f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "elapsed_ms": elapsed * 1000,
+                        "error": str(e),
+                    }
+                },
+            )
+            await stream_registry.mark_task_completed(task_id, "failed")
+
+    # Start the AI generation in a background task
+    bg_task = asyncio.create_task(run_ai_generation())
+    await stream_registry.set_task_asyncio_task(task_id, bg_task)
+    setup_time = (time.perf_counter() - stream_start_time) * 1000
+    logger.info(
+        f"[TIMING] Background task started, setup={setup_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
+    )
+
+    # SSE endpoint that subscribes to the task's stream
+    async def event_generator() -> AsyncGenerator[str, None]:
+        import time as time_module
+
+        event_gen_start = time_module.perf_counter()
+        logger.info(
+            f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
+            f"user={user_id}",
+            extra={"json_fields": log_meta},
+        )
+        subscriber_queue = None
+        first_chunk_yielded = False
+        chunks_yielded = 0
+        try:
+            # Subscribe to the task stream (this replays existing messages + live updates)
+            subscriber_queue = await stream_registry.subscribe_to_task(
+                task_id=task_id,
+                user_id=user_id,
+                last_message_id="0-0",  # Get all messages from the beginning
+            )
+
+            if subscriber_queue is None:
+                yield StreamFinish().to_sse()
+                yield "data: [DONE]\n\n"
+                return
+
+            # Read from the subscriber queue and yield to SSE
+            logger.info(
+                "[TIMING] Starting to read from subscriber_queue",
+                extra={"json_fields": log_meta},
+            )
+            while True:
+                try:
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+                    chunks_yielded += 1
+
+                    if not first_chunk_yielded:
+                        first_chunk_yielded = True
+                        elapsed = time_module.perf_counter() - event_gen_start
+                        logger.info(
+                            f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
+                            f"type={type(chunk).__name__}",
+                            extra={
+                                "json_fields": {
+                                    **log_meta,
+                                    "chunk_type": type(chunk).__name__,
+                                    "elapsed_ms": elapsed * 1000,
+                                }
+                            },
+                        )
+
+                    yield chunk.to_sse()
+
+                    # Check for finish signal
+                    if isinstance(chunk, StreamFinish):
+                        total_time = time_module.perf_counter() - event_gen_start
+                        logger.info(
+                            f"[TIMING] StreamFinish received in {total_time:.2f}s; "
+                            f"n_chunks={chunks_yielded}",
+                            extra={
+                                "json_fields": {
+                                    **log_meta,
+                                    "chunks_yielded": chunks_yielded,
+                                    "total_time_ms": total_time * 1000,
+                                }
+                            },
+                        )
+                        break
+                except asyncio.TimeoutError:
+                    yield StreamHeartbeat().to_sse()
+
+        except GeneratorExit:
+            logger.info(
+                f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "chunks_yielded": chunks_yielded,
+                        "reason": "client_disconnect",
+                    }
+                },
+            )
+            pass  # Client disconnected - background task continues
+        except Exception as e:
+            elapsed = (time_module.perf_counter() - event_gen_start) * 1000
+            logger.error(
+                f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
+                extra={
+                    "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
+                },
+            )
+        finally:
+            # Unsubscribe when client disconnects or stream ends to prevent resource leak
+            if subscriber_queue is not None:
+                try:
+                    await stream_registry.unsubscribe_from_task(
+                        task_id, subscriber_queue
+                    )
+                except Exception as unsub_err:
+                    logger.error(
+                        f"Error unsubscribing from task {task_id}: {unsub_err}",
+                        exc_info=True,
+                    )
+            # AI SDK protocol termination - always yield even if unsubscribe fails
+            total_time = time_module.perf_counter() - event_gen_start
+            logger.info(
+                f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
+                f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "total_time_ms": total_time * 1000,
+                        "chunks_yielded": chunks_yielded,
+                    }
+                },
+            )
+            yield "data: [DONE]\n\n"
 
     return StreamingResponse(
         event_generator(),
@@ -270,63 +548,90 @@ async def stream_chat_post(
 @router.get(
     "/sessions/{session_id}/stream",
 )
-async def stream_chat_get(
+async def resume_session_stream(
     session_id: str,
-    message: Annotated[str, Query(min_length=1, max_length=10000)],
     user_id: str | None = Depends(auth.get_user_id),
-    is_user_message: bool = Query(default=True),
 ):
     """
-    Stream chat responses for a session (GET - legacy endpoint).
+    Resume an active stream for a session.
 
-    Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
-      - Text fragments as they are generated
-      - Tool call UI elements (if invoked)
-      - Tool execution results
+    Called by the AI SDK's ``useChat(resume: true)`` on page load.
+    Checks for an active (in-progress) task on the session and either replays
+    the full SSE stream or returns 204 No Content if nothing is running.
 
     Args:
-        session_id: The chat session identifier to associate with the streamed messages.
-        message: The user's new message to process.
+        session_id: The chat session identifier.
         user_id: Optional authenticated user ID.
-        is_user_message: Whether the message is a user message.
-    Returns:
-        StreamingResponse: SSE-formatted response chunks.
 
+    Returns:
+        StreamingResponse (SSE) when an active stream exists,
+        or 204 No Content when there is nothing to resume.
     """
-    session = await _validate_and_get_session(session_id, user_id)
+    import asyncio
+
+    active_task, _last_id = await stream_registry.get_active_task_for_session(
+        session_id, user_id
+    )
+
+    if not active_task:
+        return Response(status_code=204)
+
+    subscriber_queue = await stream_registry.subscribe_to_task(
+        task_id=active_task.task_id,
+        user_id=user_id,
+        last_message_id="0-0",  # Full replay so useChat rebuilds the message
+    )
+
+    if subscriber_queue is None:
+        return Response(status_code=204)
 
     async def event_generator() -> AsyncGenerator[str, None]:
         chunk_count = 0
         first_chunk_type: str | None = None
-        async for chunk in chat_service.stream_chat_completion(
-            session_id,
-            message,
-            is_user_message=is_user_message,
-            user_id=user_id,
-            session=session,  # Pass pre-fetched session to avoid double-fetch
-        ):
-            if chunk_count < 3:
-                logger.info(
-                    "Chat stream chunk",
-                    extra={
-                        "session_id": session_id,
-                        "chunk_type": str(chunk.type),
-                    },
+        try:
+            while True:
+                try:
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+                    if chunk_count < 3:
+                        logger.info(
+                            "Resume stream chunk",
+                            extra={
+                                "session_id": session_id,
+                                "chunk_type": str(chunk.type),
+                            },
+                        )
+                    if not first_chunk_type:
+                        first_chunk_type = str(chunk.type)
+                    chunk_count += 1
+                    yield chunk.to_sse()
+
+                    if isinstance(chunk, StreamFinish):
+                        break
+                except asyncio.TimeoutError:
+                    yield StreamHeartbeat().to_sse()
+        except GeneratorExit:
+            pass
+        except Exception as e:
+            logger.error(f"Error in resume stream for session {session_id}: {e}")
+        finally:
+            try:
+                await stream_registry.unsubscribe_from_task(
+                    active_task.task_id, subscriber_queue
                 )
-            if not first_chunk_type:
-                first_chunk_type = str(chunk.type)
-            chunk_count += 1
-            yield chunk.to_sse()
-        logger.info(
-            "Chat stream completed",
-            extra={
-                "session_id": session_id,
-                "chunk_count": chunk_count,
-                "first_chunk_type": first_chunk_type,
-            },
-        )
-        # AI SDK protocol termination
-        yield "data: [DONE]\n\n"
+            except Exception as unsub_err:
+                logger.error(
+                    f"Error unsubscribing from task {active_task.task_id}: {unsub_err}",
+                    exc_info=True,
+                )
+            logger.info(
+                "Resume stream completed",
+                extra={
+                    "session_id": session_id,
+                    "n_chunks": chunk_count,
+                    "first_chunk_type": first_chunk_type,
+                },
+            )
+            yield "data: [DONE]\n\n"
 
     return StreamingResponse(
         event_generator(),
@@ -334,8 +639,8 @@ async def stream_chat_get(
         headers={
             "Cache-Control": "no-cache",
             "Connection": "keep-alive",
-            "X-Accel-Buffering": "no",  # Disable nginx buffering
-            "x-vercel-ai-ui-message-stream": "v1",  # AI SDK protocol header
+            "X-Accel-Buffering": "no",
+            "x-vercel-ai-ui-message-stream": "v1",
         },
     )
 
@@ -366,6 +671,251 @@ async def session_assign_user(
     return {"status": "ok"}
 
 
+# ========== Task Streaming (SSE Reconnection) ==========
+
+
+@router.get(
+    "/tasks/{task_id}/stream",
+)
+async def stream_task(
+    task_id: str,
+    user_id: str | None = Depends(auth.get_user_id),
+    last_message_id: str = Query(
+        default="0-0",
+        description="Last Redis Stream message ID received (e.g., '1706540123456-0'). Use '0-0' for full replay.",
+    ),
+):
+    """
+    Reconnect to a long-running task's SSE stream.
+
+    When a long-running operation (like agent generation) starts, the client
+    receives a task_id. If the connection drops, the client can reconnect
+    using this endpoint to resume receiving updates.
+
+    Args:
+        task_id: The task ID from the operation_started response.
+        user_id: Authenticated user ID for ownership validation.
+        last_message_id: Last Redis Stream message ID received ("0-0" for full replay).
+
+    Returns:
+        StreamingResponse: SSE-formatted response chunks starting after last_message_id.
+
+    Raises:
+        HTTPException: 404 if task not found, 410 if task expired, 403 if access denied.
+    """
+    # Check task existence and expiry before subscribing
+    task, error_code = await stream_registry.get_task_with_expiry_info(task_id)
+
+    if error_code == "TASK_EXPIRED":
+        raise HTTPException(
+            status_code=410,
+            detail={
+                "code": "TASK_EXPIRED",
+                "message": "This operation has expired. Please try again.",
+            },
+        )
+
+    if error_code == "TASK_NOT_FOUND":
+        raise HTTPException(
+            status_code=404,
+            detail={
+                "code": "TASK_NOT_FOUND",
+                "message": f"Task {task_id} not found.",
+            },
+        )
+
+    # Validate ownership if task has an owner
+    if task and task.user_id and user_id != task.user_id:
+        raise HTTPException(
+            status_code=403,
+            detail={
+                "code": "ACCESS_DENIED",
+                "message": "You do not have access to this task.",
+            },
+        )
+
+    # Get subscriber queue from stream registry
+    subscriber_queue = await stream_registry.subscribe_to_task(
+        task_id=task_id,
+        user_id=user_id,
+        last_message_id=last_message_id,
+    )
+
+    if subscriber_queue is None:
+        raise HTTPException(
+            status_code=404,
+            detail={
+                "code": "TASK_NOT_FOUND",
+                "message": f"Task {task_id} not found or access denied.",
+            },
+        )
+
+    async def event_generator() -> AsyncGenerator[str, None]:
+        import asyncio
+
+        heartbeat_interval = 15.0  # Send heartbeat every 15 seconds
+        try:
+            while True:
+                try:
+                    # Wait for next chunk with timeout for heartbeats
+                    chunk = await asyncio.wait_for(
+                        subscriber_queue.get(), timeout=heartbeat_interval
+                    )
+                    yield chunk.to_sse()
+
+                    # Check for finish signal
+                    if isinstance(chunk, StreamFinish):
+                        break
+                except asyncio.TimeoutError:
+                    # Send heartbeat to keep connection alive
+                    yield StreamHeartbeat().to_sse()
+        except Exception as e:
+            logger.error(f"Error in task stream {task_id}: {e}", exc_info=True)
+        finally:
+            # Unsubscribe when client disconnects or stream ends
+            try:
+                await stream_registry.unsubscribe_from_task(task_id, subscriber_queue)
+            except Exception as unsub_err:
+                logger.error(
+                    f"Error unsubscribing from task {task_id}: {unsub_err}",
+                    exc_info=True,
+                )
+            # AI SDK protocol termination - always yield even if unsubscribe fails
+            yield "data: [DONE]\n\n"
+
+    return StreamingResponse(
+        event_generator(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",
+            "x-vercel-ai-ui-message-stream": "v1",
+        },
+    )
+
+
+@router.get(
+    "/tasks/{task_id}",
+)
+async def get_task_status(
+    task_id: str,
+    user_id: str | None = Depends(auth.get_user_id),
+) -> dict:
+    """
+    Get the status of a long-running task.
+
+    Args:
+        task_id: The task ID to check.
+        user_id: Authenticated user ID for ownership validation.
+
+    Returns:
+        dict: Task status including task_id, status, tool_name, and operation_id.
+
+    Raises:
+        NotFoundError: If task_id is not found or user doesn't have access.
+    """
+    task = await stream_registry.get_task(task_id)
+
+    if task is None:
+        raise NotFoundError(f"Task {task_id} not found.")
+
+    # Validate ownership - if task has an owner, requester must match
+    if task.user_id and user_id != task.user_id:
+        raise NotFoundError(f"Task {task_id} not found.")
+
+    return {
+        "task_id": task.task_id,
+        "session_id": task.session_id,
+        "status": task.status,
+        "tool_name": task.tool_name,
+        "operation_id": task.operation_id,
+        "created_at": task.created_at.isoformat(),
+    }
+
+
+# ========== External Completion Webhook ==========
+
+
+@router.post(
+    "/operations/{operation_id}/complete",
+    status_code=200,
+)
+async def complete_operation(
+    operation_id: str,
+    request: OperationCompleteRequest,
+    x_api_key: str | None = Header(default=None),
+) -> dict:
+    """
+    External completion webhook for long-running operations.
+
+    Called by Agent Generator (or other services) when an operation completes.
+    This triggers the stream registry to publish completion and continue LLM generation.
+
+    Args:
+        operation_id: The operation ID to complete.
+        request: Completion payload with success status and result/error.
+        x_api_key: Internal API key for authentication.
+
+    Returns:
+        dict: Status of the completion.
+
+    Raises:
+        HTTPException: If API key is invalid or operation not found.
+    """
+    # Validate internal API key - reject if not configured or invalid
+    if not config.internal_api_key:
+        logger.error(
+            "Operation complete webhook rejected: CHAT_INTERNAL_API_KEY not configured"
+        )
+        raise HTTPException(
+            status_code=503,
+            detail="Webhook not available: internal API key not configured",
+        )
+    if x_api_key != config.internal_api_key:
+        raise HTTPException(status_code=401, detail="Invalid API key")
+
+    # Find task by operation_id
+    task = await stream_registry.find_task_by_operation_id(operation_id)
+    if task is None:
+        raise HTTPException(
+            status_code=404,
+            detail=f"Operation {operation_id} not found",
+        )
+
+    logger.info(
+        f"Received completion webhook for operation {operation_id} "
+        f"(task_id={task.task_id}, success={request.success})"
+    )
+
+    if request.success:
+        await process_operation_success(task, request.result)
+    else:
+        await process_operation_failure(task, request.error)
+
+    return {"status": "ok", "task_id": task.task_id}
+
+
+# ========== Configuration ==========
+
+
+@router.get("/config/ttl", status_code=200)
+async def get_ttl_config() -> dict:
+    """
+    Get the stream TTL configuration.
+
+    Returns the Time-To-Live settings for chat streams, which determines
+    how long clients can reconnect to an active stream.
+
+    Returns:
+        dict: TTL configuration with seconds and milliseconds values.
+    """
+    return {
+        "stream_ttl_seconds": config.stream_ttl,
+        "stream_ttl_ms": config.stream_ttl * 1000,
+    }
+
+
 # ========== Health Check ==========
 
 
@@ -402,3 +952,42 @@ async def health_check() -> dict:
         "service": "chat",
         "version": "0.1.0",
     }
+
+
+# ========== Schema Export (for OpenAPI / Orval codegen) ==========
+
+ToolResponseUnion = (
+    AgentsFoundResponse
+    | NoResultsResponse
+    | AgentDetailsResponse
+    | SetupRequirementsResponse
+    | ExecutionStartedResponse
+    | NeedLoginResponse
+    | ErrorResponse
+    | InputValidationErrorResponse
+    | AgentOutputResponse
+    | UnderstandingUpdatedResponse
+    | AgentPreviewResponse
+    | AgentSavedResponse
+    | ClarificationNeededResponse
+    | BlockListResponse
+    | BlockOutputResponse
+    | DocSearchResultsResponse
+    | DocPageResponse
+    | OperationStartedResponse
+    | OperationPendingResponse
+    | OperationInProgressResponse
+)
+
+
+@router.get(
+    "/schema/tool-responses",
+    response_model=ToolResponseUnion,
+    include_in_schema=True,
+    summary="[Dummy] Tool response type export for codegen",
+    description="This endpoint is not meant to be called. It exists solely to "
+    "expose tool response models in the OpenAPI schema for frontend codegen.",
+)
+async def _tool_response_schema() -> ToolResponseUnion:  # type: ignore[return]
+    """Never called at runtime. Exists only so Orval generates TS types."""
+    raise HTTPException(status_code=501, detail="Schema-only endpoint")
diff --git a/autogpt_platform/backend/backend/api/features/chat/service.py b/autogpt_platform/backend/backend/api/features/chat/service.py
index 20216162b5..072ea88fd5 100644
--- a/autogpt_platform/backend/backend/api/features/chat/service.py
+++ b/autogpt_platform/backend/backend/api/features/chat/service.py
@@ -3,9 +3,13 @@ import logging
 import time
 from asyncio import CancelledError
 from collections.abc import AsyncGenerator
-from typing import Any
+from typing import TYPE_CHECKING, Any, cast
 
 import openai
+
+if TYPE_CHECKING:
+    from backend.util.prompt import CompressResult
+
 import orjson
 from langfuse import get_client
 from openai import (
@@ -15,7 +19,13 @@ from openai import (
     PermissionDeniedError,
     RateLimitError,
 )
-from openai.types.chat import ChatCompletionChunk, ChatCompletionToolParam
+from openai.types.chat import (
+    ChatCompletionChunk,
+    ChatCompletionMessageParam,
+    ChatCompletionStreamOptionsParam,
+    ChatCompletionSystemMessageParam,
+    ChatCompletionToolParam,
+)
 
 from backend.data.redis_client import get_redis_async
 from backend.data.understanding import (
@@ -23,9 +33,10 @@ from backend.data.understanding import (
     get_business_understanding,
 )
 from backend.util.exceptions import NotFoundError
-from backend.util.settings import Settings
+from backend.util.settings import AppEnvironment, Settings
 
 from . import db as chat_db
+from . import stream_registry
 from .config import ChatConfig
 from .model import (
     ChatMessage,
@@ -41,8 +52,10 @@ from .response_model import (
     StreamBaseResponse,
     StreamError,
     StreamFinish,
+    StreamFinishStep,
     StreamHeartbeat,
     StreamStart,
+    StreamStartStep,
     StreamTextDelta,
     StreamTextEnd,
     StreamTextStart,
@@ -211,8 +224,18 @@ async def _get_system_prompt_template(context: str) -> str:
         try:
             # cache_ttl_seconds=0 disables SDK caching to always get the latest prompt
             # Use asyncio.to_thread to avoid blocking the event loop
+            # In non-production environments, fetch the latest prompt version
+            # instead of the production-labeled version for easier testing
+            label = (
+                None
+                if settings.config.app_env == AppEnvironment.PRODUCTION
+                else "latest"
+            )
             prompt = await asyncio.to_thread(
-                langfuse.get_prompt, config.langfuse_prompt_name, cache_ttl_seconds=0
+                langfuse.get_prompt,
+                config.langfuse_prompt_name,
+                label=label,
+                cache_ttl_seconds=0,
             )
             return prompt.compile(users_information=context)
         except Exception as e:
@@ -330,6 +353,10 @@ async def stream_chat_completion(
     retry_count: int = 0,
     session: ChatSession | None = None,
     context: dict[str, str] | None = None,  # {url: str, content: str}
+    _continuation_message_id: (
+        str | None
+    ) = None,  # Internal: reuse message ID for tool call continuations
+    _task_id: str | None = None,  # Internal: task ID for SSE reconnection support
 ) -> AsyncGenerator[StreamBaseResponse, None]:
     """Main entry point for streaming chat completions with database handling.
 
@@ -350,21 +377,45 @@ async def stream_chat_completion(
         ValueError: If max_context_messages is exceeded
 
     """
+    completion_start = time.monotonic()
+
+    # Build log metadata for structured logging
+    log_meta = {"component": "ChatService", "session_id": session_id}
+    if user_id:
+        log_meta["user_id"] = user_id
+
     logger.info(
-        f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
+        f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
+        f"message_len={len(message) if message else 0}, is_user={is_user_message}",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "message_len": len(message) if message else 0,
+                "is_user_message": is_user_message,
+            }
+        },
     )
 
     # Only fetch from Redis if session not provided (initial call)
     if session is None:
+        fetch_start = time.monotonic()
         session = await get_chat_session(session_id, user_id)
+        fetch_time = (time.monotonic() - fetch_start) * 1000
         logger.info(
-            f"Fetched session from Redis: {session.session_id if session else 'None'}, "
-            f"message_count={len(session.messages) if session else 0}"
+            f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
+            f"n_messages={len(session.messages) if session else 0}",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "duration_ms": fetch_time,
+                    "n_messages": len(session.messages) if session else 0,
+                }
+            },
         )
     else:
         logger.info(
-            f"Using provided session object: {session.session_id}, "
-            f"message_count={len(session.messages)}"
+            f"[TIMING] Using provided session, messages={len(session.messages)}",
+            extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
         )
 
     if not session:
@@ -385,17 +436,25 @@ async def stream_chat_completion(
 
         # Track user message in PostHog
         if is_user_message:
+            posthog_start = time.monotonic()
             track_user_message(
                 user_id=user_id,
                 session_id=session_id,
                 message_length=len(message),
             )
+            posthog_time = (time.monotonic() - posthog_start) * 1000
+            logger.info(
+                f"[TIMING] track_user_message took {posthog_time:.1f}ms",
+                extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
+            )
 
-    logger.info(
-        f"Upserting session: {session.session_id} with user id {session.user_id}, "
-        f"message_count={len(session.messages)}"
-    )
+    upsert_start = time.monotonic()
     session = await upsert_chat_session(session)
+    upsert_time = (time.monotonic() - upsert_start) * 1000
+    logger.info(
+        f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
+    )
     assert session, "Session not found"
 
     # Generate title for new sessions on first user message (non-blocking)
@@ -433,7 +492,13 @@ async def stream_chat_completion(
             asyncio.create_task(_update_title())
 
     # Build system prompt with business understanding
+    prompt_start = time.monotonic()
     system_prompt, understanding = await _build_system_prompt(user_id)
+    prompt_time = (time.monotonic() - prompt_start) * 1000
+    logger.info(
+        f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
+    )
 
     # Initialize variables for streaming
     assistant_response = ChatMessage(
@@ -458,13 +523,27 @@ async def stream_chat_completion(
     # Generate unique IDs for AI SDK protocol
     import uuid as uuid_module
 
-    message_id = str(uuid_module.uuid4())
+    is_continuation = _continuation_message_id is not None
+    message_id = _continuation_message_id or str(uuid_module.uuid4())
     text_block_id = str(uuid_module.uuid4())
 
-    # Yield message start
-    yield StreamStart(messageId=message_id)
+    # Only yield message start for the initial call, not for continuations.
+    setup_time = (time.monotonic() - completion_start) * 1000
+    logger.info(
+        f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
+    )
+    if not is_continuation:
+        yield StreamStart(messageId=message_id, taskId=_task_id)
+
+    # Emit start-step before each LLM call (AI SDK uses this to add step boundaries)
+    yield StreamStartStep()
 
     try:
+        logger.info(
+            "[TIMING] Calling _stream_chat_chunks",
+            extra={"json_fields": log_meta},
+        )
         async for chunk in _stream_chat_chunks(
             session=session,
             tools=tools,
@@ -564,6 +643,10 @@ async def stream_chat_completion(
                     )
                 yield chunk
             elif isinstance(chunk, StreamFinish):
+                if has_done_tool_call:
+                    # Tool calls happened — close the step but don't send message-level finish.
+                    # The continuation will open a new step, and finish will come at the end.
+                    yield StreamFinishStep()
                 if not has_done_tool_call:
                     # Emit text-end before finish if we received text but haven't closed it
                     if has_received_text and not text_streaming_ended:
@@ -595,6 +678,8 @@ async def stream_chat_completion(
                             has_saved_assistant_message = True
 
                     has_yielded_end = True
+                    # Emit finish-step before finish (resets AI SDK text/reasoning state)
+                    yield StreamFinishStep()
                     yield chunk
             elif isinstance(chunk, StreamError):
                 has_yielded_error = True
@@ -607,6 +692,9 @@ async def stream_chat_completion(
                         total_tokens=chunk.totalTokens,
                     )
                 )
+            elif isinstance(chunk, StreamHeartbeat):
+                # Pass through heartbeat to keep SSE connection alive
+                yield chunk
             else:
                 logger.error(f"Unknown chunk type: {type(chunk)}", exc_info=True)
 
@@ -641,6 +729,10 @@ async def stream_chat_completion(
             logger.info(
                 f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
             )
+            # Close the current step before retrying so the recursive call's
+            # StreamStartStep doesn't produce unbalanced step events.
+            if not has_yielded_end:
+                yield StreamFinishStep()
             should_retry = True
         else:
             # Non-retryable error or max retries exceeded
@@ -676,6 +768,7 @@ async def stream_chat_completion(
                 error_response = StreamError(errorText=error_message)
                 yield error_response
             if not has_yielded_end:
+                yield StreamFinishStep()
                 yield StreamFinish()
             return
 
@@ -690,6 +783,8 @@ async def stream_chat_completion(
             retry_count=retry_count + 1,
             session=session,
             context=context,
+            _continuation_message_id=message_id,  # Reuse message ID since start was already sent
+            _task_id=_task_id,
         ):
             yield chunk
         return  # Exit after retry to avoid double-saving in finally block
@@ -759,6 +854,8 @@ async def stream_chat_completion(
             session=session,  # Pass session object to avoid Redis refetch
             context=context,
             tool_call_response=str(tool_response_messages),
+            _continuation_message_id=message_id,  # Reuse message ID to avoid duplicates
+            _task_id=_task_id,
         ):
             yield chunk
 
@@ -794,207 +891,58 @@ def _is_region_blocked_error(error: Exception) -> bool:
     return "not available in your region" in str(error).lower()
 
 
-async def _summarize_messages(
+async def _manage_context_window(
     messages: list,
     model: str,
     api_key: str | None = None,
     base_url: str | None = None,
-    timeout: float = 30.0,
-) -> str:
-    """Summarize a list of messages into concise context.
+) -> "CompressResult":
+    """
+    Manage context window using the unified compress_context function.
 
-    Uses the same model as the chat for higher quality summaries.
+    This is a thin wrapper that creates an OpenAI client for summarization
+    and delegates to the shared compression logic in prompt.py.
 
     Args:
-        messages: List of message dicts to summarize
-        model: Model to use for summarization (same as chat model)
-        api_key: API key for OpenAI client
-        base_url: Base URL for OpenAI client
-        timeout: Request timeout in seconds (default: 30.0)
+        messages: List of messages in OpenAI format
+        model: Model name for token counting and summarization
+        api_key: API key for summarization calls
+        base_url: Base URL for summarization calls
 
     Returns:
-        Summarized text
+        CompressResult with compacted messages and metadata
     """
-    # Format messages for summarization
-    conversation = []
-    for msg in messages:
-        role = msg.get("role", "")
-        content = msg.get("content", "")
-        # Include user, assistant, and tool messages (tool outputs are important context)
-        if content and role in ("user", "assistant", "tool"):
-            conversation.append(f"{role.upper()}: {content}")
-
-    conversation_text = "\n\n".join(conversation)
-
-    # Handle empty conversation
-    if not conversation_text:
-        return "No conversation history available."
-
-    # Truncate conversation to fit within summarization model's context
-    # gpt-4o-mini has 128k context, but we limit to ~25k tokens (~100k chars) for safety
-    MAX_CHARS = 100_000
-    if len(conversation_text) > MAX_CHARS:
-        conversation_text = conversation_text[:MAX_CHARS] + "\n\n[truncated]"
-
-    # Call LLM to summarize
     import openai
 
-    summarization_client = openai.AsyncOpenAI(
-        api_key=api_key, base_url=base_url, timeout=timeout
-    )
+    from backend.util.prompt import compress_context
 
-    response = await summarization_client.chat.completions.create(
-        model=model,
-        messages=[
-            {
-                "role": "system",
-                "content": (
-                    "Create a detailed summary of the conversation so far. "
-                    "This summary will be used as context when continuing the conversation.\n\n"
-                    "Before writing the summary, analyze each message chronologically to identify:\n"
-                    "- User requests and their explicit goals\n"
-                    "- Your approach and key decisions made\n"
-                    "- Technical specifics (file names, tool outputs, function signatures)\n"
-                    "- Errors encountered and resolutions applied\n\n"
-                    "You MUST include ALL of the following sections:\n\n"
-                    "## 1. Primary Request and Intent\n"
-                    "The user's explicit goals and what they are trying to accomplish.\n\n"
-                    "## 2. Key Technical Concepts\n"
-                    "Technologies, frameworks, tools, and patterns being used or discussed.\n\n"
-                    "## 3. Files and Resources Involved\n"
-                    "Specific files examined or modified, with relevant snippets and identifiers.\n\n"
-                    "## 4. Errors and Fixes\n"
-                    "Problems encountered, error messages, and their resolutions. "
-                    "Include any user feedback on fixes.\n\n"
-                    "## 5. Problem Solving\n"
-                    "Issues that have been resolved and how they were addressed.\n\n"
-                    "## 6. All User Messages\n"
-                    "A complete list of all user inputs (excluding tool outputs) to preserve their exact requests.\n\n"
-                    "## 7. Pending Tasks\n"
-                    "Work items the user explicitly requested that have not yet been completed.\n\n"
-                    "## 8. Current Work\n"
-                    "Precise description of what was being worked on most recently, including relevant context.\n\n"
-                    "## 9. Next Steps\n"
-                    "What should happen next, aligned with the user's most recent requests. "
-                    "Include verbatim quotes of recent instructions if relevant."
-                ),
-            },
-            {"role": "user", "content": f"Summarize:\n\n{conversation_text}"},
-        ],
-        max_tokens=1500,
-        temperature=0.3,
-    )
+    # Convert messages to dict format
+    messages_dict = []
+    for msg in messages:
+        if isinstance(msg, dict):
+            msg_dict = {k: v for k, v in msg.items() if v is not None}
+        else:
+            msg_dict = dict(msg)
+        messages_dict.append(msg_dict)
 
-    summary = response.choices[0].message.content
-    return summary or "No summary available."
-
-
-def _ensure_tool_pairs_intact(
-    recent_messages: list[dict],
-    all_messages: list[dict],
-    start_index: int,
-) -> list[dict]:
-    """
-    Ensure tool_call/tool_response pairs stay together after slicing.
-
-    When slicing messages for context compaction, a naive slice can separate
-    an assistant message containing tool_calls from its corresponding tool
-    response messages. This causes API validation errors (e.g., Anthropic's
-    "unexpected tool_use_id found in tool_result blocks").
-
-    This function checks for orphan tool responses in the slice and extends
-    backwards to include their corresponding assistant messages.
-
-    Args:
-        recent_messages: The sliced messages to validate
-        all_messages: The complete message list (for looking up missing assistants)
-        start_index: The index in all_messages where recent_messages begins
-
-    Returns:
-        A potentially extended list of messages with tool pairs intact
-    """
-    if not recent_messages:
-        return recent_messages
-
-    # Collect all tool_call_ids from assistant messages in the slice
-    available_tool_call_ids: set[str] = set()
-    for msg in recent_messages:
-        if msg.get("role") == "assistant" and msg.get("tool_calls"):
-            for tc in msg["tool_calls"]:
-                tc_id = tc.get("id")
-                if tc_id:
-                    available_tool_call_ids.add(tc_id)
-
-    # Find orphan tool responses (tool messages whose tool_call_id is missing)
-    orphan_tool_call_ids: set[str] = set()
-    for msg in recent_messages:
-        if msg.get("role") == "tool":
-            tc_id = msg.get("tool_call_id")
-            if tc_id and tc_id not in available_tool_call_ids:
-                orphan_tool_call_ids.add(tc_id)
-
-    if not orphan_tool_call_ids:
-        # No orphans, slice is valid
-        return recent_messages
-
-    # Find the assistant messages that contain the orphan tool_call_ids
-    # Search backwards from start_index in all_messages
-    messages_to_prepend: list[dict] = []
-    for i in range(start_index - 1, -1, -1):
-        msg = all_messages[i]
-        if msg.get("role") == "assistant" and msg.get("tool_calls"):
-            msg_tool_ids = {tc.get("id") for tc in msg["tool_calls"] if tc.get("id")}
-            if msg_tool_ids & orphan_tool_call_ids:
-                # This assistant message has tool_calls we need
-                # Also collect its contiguous tool responses that follow it
-                assistant_and_responses: list[dict] = [msg]
-
-                # Scan forward from this assistant to collect tool responses
-                for j in range(i + 1, start_index):
-                    following_msg = all_messages[j]
-                    if following_msg.get("role") == "tool":
-                        tool_id = following_msg.get("tool_call_id")
-                        if tool_id and tool_id in msg_tool_ids:
-                            assistant_and_responses.append(following_msg)
-                    else:
-                        # Stop at first non-tool message
-                        break
-
-                # Prepend the assistant and its tool responses (maintain order)
-                messages_to_prepend = assistant_and_responses + messages_to_prepend
-                # Mark these as found
-                orphan_tool_call_ids -= msg_tool_ids
-                # Also add this assistant's tool_call_ids to available set
-                available_tool_call_ids |= msg_tool_ids
-
-        if not orphan_tool_call_ids:
-            # Found all missing assistants
-            break
-
-    if orphan_tool_call_ids:
-        # Some tool_call_ids couldn't be resolved - remove those tool responses
-        # This shouldn't happen in normal operation but handles edge cases
-        logger.warning(
-            f"Could not find assistant messages for tool_call_ids: {orphan_tool_call_ids}. "
-            "Removing orphan tool responses."
-        )
-        recent_messages = [
-            msg
-            for msg in recent_messages
-            if not (
-                msg.get("role") == "tool"
-                and msg.get("tool_call_id") in orphan_tool_call_ids
+    # Only create client if api_key is provided (enables summarization)
+    # Use context manager to avoid socket leaks
+    if api_key:
+        async with openai.AsyncOpenAI(
+            api_key=api_key, base_url=base_url, timeout=30.0
+        ) as client:
+            return await compress_context(
+                messages=messages_dict,
+                model=model,
+                client=client,
             )
-        ]
-
-    if messages_to_prepend:
-        logger.info(
-            f"Extended recent messages by {len(messages_to_prepend)} to preserve "
-            f"tool_call/tool_response pairs"
+    else:
+        # No API key - use truncation-only mode
+        return await compress_context(
+            messages=messages_dict,
+            model=model,
+            client=None,
         )
-        return messages_to_prepend + recent_messages
-
-    return recent_messages
 
 
 async def _stream_chat_chunks(
@@ -1018,15 +966,24 @@ async def _stream_chat_chunks(
         SSE formatted JSON response objects
 
     """
+    import time as time_module
+
+    stream_chunks_start = time_module.perf_counter()
     model = config.model
 
-    logger.info("Starting pure chat stream")
+    # Build log metadata for structured logging
+    log_meta = {"component": "ChatService", "session_id": session.session_id}
+    if session.user_id:
+        log_meta["user_id"] = session.user_id
+
+    logger.info(
+        f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
+        f"user={session.user_id}, n_messages={len(session.messages)}",
+        extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
+    )
 
-    # Build messages with system prompt prepended
     messages = session.to_openai_messages()
     if system_prompt:
-        from openai.types.chat import ChatCompletionSystemMessageParam
-
         system_message = ChatCompletionSystemMessageParam(
             role="system",
             content=system_prompt,
@@ -1034,314 +991,44 @@ async def _stream_chat_chunks(
         messages = [system_message] + messages
 
     # Apply context window management
-    token_count = 0  # Initialize for exception handler
-    try:
-        from backend.util.prompt import estimate_token_count
+    context_start = time_module.perf_counter()
+    context_result = await _manage_context_window(
+        messages=messages,
+        model=model,
+        api_key=config.api_key,
+        base_url=config.base_url,
+    )
+    context_time = (time_module.perf_counter() - context_start) * 1000
+    logger.info(
+        f"[TIMING] _manage_context_window took {context_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": context_time}},
+    )
 
-        # Convert to dict for token counting
-        # OpenAI message types are TypedDicts, so they're already dict-like
-        messages_dict = []
-        for msg in messages:
-            # TypedDict objects are already dicts, just filter None values
-            if isinstance(msg, dict):
-                msg_dict = {k: v for k, v in msg.items() if v is not None}
-            else:
-                # Fallback for unexpected types
-                msg_dict = dict(msg)
-            messages_dict.append(msg_dict)
-
-        # Estimate tokens using appropriate tokenizer
-        # Normalize model name for token counting (tiktoken only supports OpenAI models)
-        token_count_model = model
-        if "/" in model:
-            # Strip provider prefix (e.g., "anthropic/claude-opus-4.5" -> "claude-opus-4.5")
-            token_count_model = model.split("/")[-1]
-
-        # For Claude and other non-OpenAI models, approximate with gpt-4o tokenizer
-        # Most modern LLMs have similar tokenization (~1 token per 4 chars)
-        if "claude" in token_count_model.lower() or not any(
-            known in token_count_model.lower()
-            for known in ["gpt", "o1", "chatgpt", "text-"]
-        ):
-            token_count_model = "gpt-4o"
-
-        # Attempt token counting with error handling
-        try:
-            token_count = estimate_token_count(messages_dict, model=token_count_model)
-        except Exception as token_error:
-            # If token counting fails, use gpt-4o as fallback approximation
-            logger.warning(
-                f"Token counting failed for model {token_count_model}: {token_error}. "
-                "Using gpt-4o approximation."
-            )
-            token_count = estimate_token_count(messages_dict, model="gpt-4o")
-
-        # If over threshold, summarize old messages
-        if token_count > 120_000:
-            KEEP_RECENT = 15
-
-            # Check if we have a system prompt at the start
-            has_system_prompt = (
-                len(messages) > 0 and messages[0].get("role") == "system"
-            )
-
-            # Always attempt mitigation when over limit, even with few messages
-            if messages:
-                # Split messages based on whether system prompt exists
-                # Calculate start index for the slice
-                slice_start = max(0, len(messages_dict) - KEEP_RECENT)
-                recent_messages = messages_dict[-KEEP_RECENT:]
-
-                # Ensure tool_call/tool_response pairs stay together
-                # This prevents API errors from orphan tool responses
-                recent_messages = _ensure_tool_pairs_intact(
-                    recent_messages, messages_dict, slice_start
-                )
-
-                if has_system_prompt:
-                    # Keep system prompt separate, summarize everything between system and recent
-                    system_msg = messages[0]
-                    old_messages_dict = messages_dict[1:-KEEP_RECENT]
-                else:
-                    # No system prompt, summarize everything except recent
-                    system_msg = None
-                    old_messages_dict = messages_dict[:-KEEP_RECENT]
-
-                # Summarize any non-empty old messages (no minimum threshold)
-                # If we're over the token limit, we need to compress whatever we can
-                if old_messages_dict:
-                    # Summarize old messages using the same model as chat
-                    summary_text = await _summarize_messages(
-                        old_messages_dict,
-                        model=model,
-                        api_key=config.api_key,
-                        base_url=config.base_url,
-                    )
-
-                    # Build new message list
-                    # Use assistant role (not system) to prevent privilege escalation
-                    # of user-influenced content to instruction-level authority
-                    from openai.types.chat import ChatCompletionAssistantMessageParam
-
-                    summary_msg = ChatCompletionAssistantMessageParam(
-                        role="assistant",
-                        content=(
-                            "[Previous conversation summary — for context only]: "
-                            f"{summary_text}"
-                        ),
-                    )
-
-                    # Rebuild messages based on whether we have a system prompt
-                    if has_system_prompt:
-                        # system_prompt + summary + recent_messages
-                        messages = [system_msg, summary_msg] + recent_messages
-                    else:
-                        # summary + recent_messages (no original system prompt)
-                        messages = [summary_msg] + recent_messages
-
-                    logger.info(
-                        f"Context summarized: {token_count} tokens, "
-                        f"summarized {len(old_messages_dict)} old messages, "
-                        f"kept last {KEEP_RECENT} messages"
-                    )
-
-                    # Fallback: If still over limit after summarization, progressively drop recent messages
-                    # This handles edge cases where recent messages are extremely large
-                    new_messages_dict = []
-                    for msg in messages:
-                        if isinstance(msg, dict):
-                            msg_dict = {k: v for k, v in msg.items() if v is not None}
-                        else:
-                            msg_dict = dict(msg)
-                        new_messages_dict.append(msg_dict)
-
-                    new_token_count = estimate_token_count(
-                        new_messages_dict, model=token_count_model
-                    )
-
-                    if new_token_count > 120_000:
-                        # Still over limit - progressively reduce KEEP_RECENT
-                        logger.warning(
-                            f"Still over limit after summarization: {new_token_count} tokens. "
-                            "Reducing number of recent messages kept."
-                        )
-
-                        for keep_count in [12, 10, 8, 5, 3, 2, 1, 0]:
-                            if keep_count == 0:
-                                # Try with just system prompt + summary (no recent messages)
-                                if has_system_prompt:
-                                    messages = [system_msg, summary_msg]
-                                else:
-                                    messages = [summary_msg]
-                                logger.info(
-                                    "Trying with 0 recent messages (system + summary only)"
-                                )
-                            else:
-                                # Slice from ORIGINAL recent_messages to avoid duplicating summary
-                                reduced_recent = (
-                                    recent_messages[-keep_count:]
-                                    if len(recent_messages) >= keep_count
-                                    else recent_messages
-                                )
-                                # Ensure tool pairs stay intact in the reduced slice
-                                reduced_slice_start = max(
-                                    0, len(recent_messages) - keep_count
-                                )
-                                reduced_recent = _ensure_tool_pairs_intact(
-                                    reduced_recent, recent_messages, reduced_slice_start
-                                )
-                                if has_system_prompt:
-                                    messages = [
-                                        system_msg,
-                                        summary_msg,
-                                    ] + reduced_recent
-                                else:
-                                    messages = [summary_msg] + reduced_recent
-
-                            new_messages_dict = []
-                            for msg in messages:
-                                if isinstance(msg, dict):
-                                    msg_dict = {
-                                        k: v for k, v in msg.items() if v is not None
-                                    }
-                                else:
-                                    msg_dict = dict(msg)
-                                new_messages_dict.append(msg_dict)
-
-                            new_token_count = estimate_token_count(
-                                new_messages_dict, model=token_count_model
-                            )
-
-                            if new_token_count <= 120_000:
-                                logger.info(
-                                    f"Reduced to {keep_count} recent messages, "
-                                    f"now {new_token_count} tokens"
-                                )
-                                break
-                        else:
-                            logger.error(
-                                f"Unable to reduce token count below threshold even with 0 messages. "
-                                f"Final count: {new_token_count} tokens"
-                            )
-                            # ABSOLUTE LAST RESORT: Drop system prompt
-                            # This should only happen if summary itself is massive
-                            if has_system_prompt and len(messages) > 1:
-                                messages = messages[1:]  # Drop system prompt
-                                logger.critical(
-                                    "CRITICAL: Dropped system prompt as absolute last resort. "
-                                    "Behavioral consistency may be affected."
-                                )
-                                # Yield error to user
-                                yield StreamError(
-                                    errorText=(
-                                        "Warning: System prompt dropped due to size constraints. "
-                                        "Assistant behavior may be affected."
-                                    )
-                                )
-                else:
-                    # No old messages to summarize - all messages are "recent"
-                    # Apply progressive truncation to reduce token count
-                    logger.warning(
-                        f"Token count {token_count} exceeds threshold but no old messages to summarize. "
-                        f"Applying progressive truncation to recent messages."
-                    )
-
-                    # Create a base list excluding system prompt to avoid duplication
-                    # This is the pool of messages we'll slice from in the loop
-                    # Use messages_dict for type consistency with _ensure_tool_pairs_intact
-                    base_msgs = (
-                        messages_dict[1:] if has_system_prompt else messages_dict
-                    )
-
-                    # Try progressively smaller keep counts
-                    new_token_count = token_count  # Initialize with current count
-                    for keep_count in [12, 10, 8, 5, 3, 2, 1, 0]:
-                        if keep_count == 0:
-                            # Try with just system prompt (no recent messages)
-                            if has_system_prompt:
-                                messages = [system_msg]
-                                logger.info(
-                                    "Trying with 0 recent messages (system prompt only)"
-                                )
-                            else:
-                                # No system prompt and no recent messages = empty messages list
-                                # This is invalid, skip this iteration
-                                continue
-                        else:
-                            if len(base_msgs) < keep_count:
-                                continue  # Skip if we don't have enough messages
-
-                            # Slice from base_msgs to get recent messages (without system prompt)
-                            recent_messages = base_msgs[-keep_count:]
-
-                            # Ensure tool pairs stay intact in the reduced slice
-                            reduced_slice_start = max(0, len(base_msgs) - keep_count)
-                            recent_messages = _ensure_tool_pairs_intact(
-                                recent_messages, base_msgs, reduced_slice_start
-                            )
-
-                            if has_system_prompt:
-                                messages = [system_msg] + recent_messages
-                            else:
-                                messages = recent_messages
-
-                        new_messages_dict = []
-                        for msg in messages:
-                            if msg is None:
-                                continue  # Skip None messages (type safety)
-                            if isinstance(msg, dict):
-                                msg_dict = {
-                                    k: v for k, v in msg.items() if v is not None
-                                }
-                            else:
-                                msg_dict = dict(msg)
-                            new_messages_dict.append(msg_dict)
-
-                        new_token_count = estimate_token_count(
-                            new_messages_dict, model=token_count_model
-                        )
-
-                        if new_token_count <= 120_000:
-                            logger.info(
-                                f"Reduced to {keep_count} recent messages, "
-                                f"now {new_token_count} tokens"
-                            )
-                            break
-                    else:
-                        # Even with 0 messages still over limit
-                        logger.error(
-                            f"Unable to reduce token count below threshold even with 0 messages. "
-                            f"Final count: {new_token_count} tokens. Messages may be extremely large."
-                        )
-                        # ABSOLUTE LAST RESORT: Drop system prompt
-                        if has_system_prompt and len(messages) > 1:
-                            messages = messages[1:]  # Drop system prompt
-                            logger.critical(
-                                "CRITICAL: Dropped system prompt as absolute last resort. "
-                                "Behavioral consistency may be affected."
-                            )
-                            # Yield error to user
-                            yield StreamError(
-                                errorText=(
-                                    "Warning: System prompt dropped due to size constraints. "
-                                    "Assistant behavior may be affected."
-                                )
-                            )
-
-    except Exception as e:
-        logger.error(f"Context summarization failed: {e}", exc_info=True)
-        # If we were over the token limit, yield error to user
-        # Don't silently continue with oversized messages that will fail
-        if token_count > 120_000:
+    if context_result.error:
+        if "System prompt dropped" in context_result.error:
+            # Warning only - continue with reduced context
             yield StreamError(
                 errorText=(
-                    f"Unable to manage context window (token limit exceeded: {token_count} tokens). "
-                    "Context summarization failed. Please start a new conversation."
+                    "Warning: System prompt dropped due to size constraints. "
+                    "Assistant behavior may be affected."
+                )
+            )
+        else:
+            # Any other error - abort to prevent failed LLM calls
+            yield StreamError(
+                errorText=(
+                    f"Context window management failed: {context_result.error}. "
+                    "Please start a new conversation."
                 )
             )
             yield StreamFinish()
             return
-        # Otherwise, continue with original messages (under limit)
+
+    messages = context_result.messages
+    if context_result.was_compacted:
+        logger.info(
+            f"Context compacted for streaming: {context_result.token_count} tokens"
+        )
 
     # Loop to handle tool calls and continue conversation
     while True:
@@ -1350,9 +1037,19 @@ async def _stream_chat_chunks(
 
         while retry_count <= MAX_RETRIES:
             try:
+                elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
+                retry_info = (
+                    f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
+                )
                 logger.info(
-                    f"Creating OpenAI chat completion stream..."
-                    f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
+                    f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "elapsed_ms": elapsed,
+                            "retry_count": retry_count,
+                        }
+                    },
                 )
 
                 # Build extra_body for OpenRouter tracing and PostHog analytics
@@ -1369,14 +1066,11 @@ async def _stream_chat_chunks(
                         :128
                     ]  # OpenRouter limit
 
-                # Create the stream with proper types
-                from typing import cast
-
-                from openai.types.chat import (
-                    ChatCompletionMessageParam,
-                    ChatCompletionStreamOptionsParam,
-                )
+                # Enable adaptive thinking for Anthropic models via OpenRouter
+                if config.thinking_enabled and "anthropic" in model.lower():
+                    extra_body["reasoning"] = {"enabled": True}
 
+                api_call_start = time_module.perf_counter()
                 stream = await client.chat.completions.create(
                     model=model,
                     messages=cast(list[ChatCompletionMessageParam], messages),
@@ -1386,6 +1080,11 @@ async def _stream_chat_chunks(
                     stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
                     extra_body=extra_body,
                 )
+                api_init_time = (time_module.perf_counter() - api_call_start) * 1000
+                logger.info(
+                    f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
+                    extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
+                )
 
                 # Variables to accumulate tool calls
                 tool_calls: list[dict[str, Any]] = []
@@ -1396,10 +1095,13 @@ async def _stream_chat_chunks(
 
                 # Track if we've started the text block
                 text_started = False
+                first_content_chunk = True
+                chunk_count = 0
 
                 # Process the stream
                 chunk: ChatCompletionChunk
                 async for chunk in stream:
+                    chunk_count += 1
                     if chunk.usage:
                         yield StreamUsage(
                             promptTokens=chunk.usage.prompt_tokens,
@@ -1422,6 +1124,23 @@ async def _stream_chat_chunks(
                             if not text_started and text_block_id:
                                 yield StreamTextStart(id=text_block_id)
                                 text_started = True
+                            # Log timing for first content chunk
+                            if first_content_chunk:
+                                first_content_chunk = False
+                                ttfc = (
+                                    time_module.perf_counter() - api_call_start
+                                ) * 1000
+                                logger.info(
+                                    f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
+                                    f"(since API call), n_chunks={chunk_count}",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "time_to_first_chunk_ms": ttfc,
+                                            "n_chunks": chunk_count,
+                                        }
+                                    },
+                                )
                             # Stream the text delta
                             text_response = StreamTextDelta(
                                 id=text_block_id or "",
@@ -1478,7 +1197,21 @@ async def _stream_chat_chunks(
                                         toolName=tool_calls[idx]["function"]["name"],
                                     )
                                     emitted_start_for_idx.add(idx)
-                logger.info(f"Stream complete. Finish reason: {finish_reason}")
+                stream_duration = time_module.perf_counter() - api_call_start
+                logger.info(
+                    f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
+                    f"duration={stream_duration:.2f}s, "
+                    f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "stream_duration_ms": stream_duration * 1000,
+                            "finish_reason": finish_reason,
+                            "n_chunks": chunk_count,
+                            "n_tool_calls": len(tool_calls),
+                        }
+                    },
+                )
 
                 # Yield all accumulated tool calls after the stream is complete
                 # This ensures all tool call arguments have been fully received
@@ -1498,6 +1231,12 @@ async def _stream_chat_chunks(
                         # Re-raise to trigger retry logic in the parent function
                         raise
 
+                total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
+                logger.info(
+                    f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
+                    f"session={session.session_id}, user={session.user_id}",
+                    extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
+                )
                 yield StreamFinish()
                 return
             except Exception as e:
@@ -1610,8 +1349,9 @@ async def _yield_tool_call(
             )
             return
 
-        # Generate operation ID
+        # Generate operation ID and task ID
         operation_id = str(uuid_module.uuid4())
+        task_id = str(uuid_module.uuid4())
 
         # Build a user-friendly message based on tool and arguments
         if tool_name == "create_agent":
@@ -1654,6 +1394,16 @@ async def _yield_tool_call(
 
         # Wrap session save and task creation in try-except to release lock on failure
         try:
+            # Create task in stream registry for SSE reconnection support
+            await stream_registry.create_task(
+                task_id=task_id,
+                session_id=session.session_id,
+                user_id=session.user_id,
+                tool_call_id=tool_call_id,
+                tool_name=tool_name,
+                operation_id=operation_id,
+            )
+
             # Save assistant message with tool_call FIRST (required by LLM)
             assistant_message = ChatMessage(
                 role="assistant",
@@ -1675,23 +1425,27 @@ async def _yield_tool_call(
             session.messages.append(pending_message)
             await upsert_chat_session(session)
             logger.info(
-                f"Saved pending operation {operation_id} for tool {tool_name} "
-                f"in session {session.session_id}"
+                f"Saved pending operation {operation_id} (task_id={task_id}) "
+                f"for tool {tool_name} in session {session.session_id}"
             )
 
             # Store task reference in module-level set to prevent GC before completion
-            task = asyncio.create_task(
-                _execute_long_running_tool(
+            bg_task = asyncio.create_task(
+                _execute_long_running_tool_with_streaming(
                     tool_name=tool_name,
                     parameters=arguments,
                     tool_call_id=tool_call_id,
                     operation_id=operation_id,
+                    task_id=task_id,
                     session_id=session.session_id,
                     user_id=session.user_id,
                 )
             )
-            _background_tasks.add(task)
-            task.add_done_callback(_background_tasks.discard)
+            _background_tasks.add(bg_task)
+            bg_task.add_done_callback(_background_tasks.discard)
+
+            # Associate the asyncio task with the stream registry task
+            await stream_registry.set_task_asyncio_task(task_id, bg_task)
         except Exception as e:
             # Roll back appended messages to prevent data corruption on subsequent saves
             if (
@@ -1709,6 +1463,11 @@ async def _yield_tool_call(
 
             # Release the Redis lock since the background task won't be spawned
             await _mark_operation_completed(tool_call_id)
+            # Mark stream registry task as failed if it was created
+            try:
+                await stream_registry.mark_task_completed(task_id, status="failed")
+            except Exception:
+                pass
             logger.error(
                 f"Failed to setup long-running tool {tool_name}: {e}", exc_info=True
             )
@@ -1722,6 +1481,7 @@ async def _yield_tool_call(
                 message=started_msg,
                 operation_id=operation_id,
                 tool_name=tool_name,
+                task_id=task_id,  # Include task_id for SSE reconnection
             ).model_dump_json(),
             success=True,
         )
@@ -1791,6 +1551,9 @@ async def _execute_long_running_tool(
 
     This function runs independently of the SSE connection, so the operation
     survives if the user closes their browser tab.
+
+    NOTE: This is the legacy function without stream registry support.
+    Use _execute_long_running_tool_with_streaming for new implementations.
     """
     try:
         # Load fresh session (not stale reference)
@@ -1834,10 +1597,143 @@ async def _execute_long_running_tool(
             tool_call_id=tool_call_id,
             result=error_response.model_dump_json(),
         )
+        # Generate LLM continuation so user sees explanation even for errors
+        try:
+            await _generate_llm_continuation(session_id=session_id, user_id=user_id)
+        except Exception as llm_err:
+            logger.warning(f"Failed to generate LLM continuation for error: {llm_err}")
     finally:
         await _mark_operation_completed(tool_call_id)
 
 
+async def _execute_long_running_tool_with_streaming(
+    tool_name: str,
+    parameters: dict[str, Any],
+    tool_call_id: str,
+    operation_id: str,
+    task_id: str,
+    session_id: str,
+    user_id: str | None,
+) -> None:
+    """Execute a long-running tool with stream registry support for SSE reconnection.
+
+    This function runs independently of the SSE connection, publishes progress
+    to the stream registry, and survives if the user closes their browser tab.
+    Clients can reconnect via GET /chat/tasks/{task_id}/stream to resume streaming.
+
+    If the external service returns a 202 Accepted (async), this function exits
+    early and lets the Redis Streams completion consumer handle the rest.
+    """
+    # Track whether we delegated to async processing - if so, the Redis Streams
+    # completion consumer (stream_registry / completion_consumer) will handle cleanup, not us
+    delegated_to_async = False
+
+    try:
+        # Load fresh session (not stale reference)
+        session = await get_chat_session(session_id, user_id)
+        if not session:
+            logger.error(f"Session {session_id} not found for background tool")
+            await stream_registry.mark_task_completed(task_id, status="failed")
+            return
+
+        # Pass operation_id and task_id to the tool for async processing
+        enriched_parameters = {
+            **parameters,
+            "_operation_id": operation_id,
+            "_task_id": task_id,
+        }
+
+        # Execute the actual tool
+        result = await execute_tool(
+            tool_name=tool_name,
+            parameters=enriched_parameters,
+            tool_call_id=tool_call_id,
+            user_id=user_id,
+            session=session,
+        )
+
+        # Check if the tool result indicates async processing
+        # (e.g., Agent Generator returned 202 Accepted)
+        try:
+            if isinstance(result.output, dict):
+                result_data = result.output
+            elif result.output:
+                result_data = orjson.loads(result.output)
+            else:
+                result_data = {}
+            if result_data.get("status") == "accepted":
+                logger.info(
+                    f"Tool {tool_name} delegated to async processing "
+                    f"(operation_id={operation_id}, task_id={task_id}). "
+                    f"Redis Streams completion consumer will handle the rest."
+                )
+                # Don't publish result, don't continue with LLM, and don't cleanup
+                # The Redis Streams consumer (completion_consumer) will handle
+                # everything when the external service completes via webhook
+                delegated_to_async = True
+                return
+        except (orjson.JSONDecodeError, TypeError):
+            pass  # Not JSON or not async - continue normally
+
+        # Publish tool result to stream registry
+        await stream_registry.publish_chunk(task_id, result)
+
+        # Update the pending message with result
+        result_str = (
+            result.output
+            if isinstance(result.output, str)
+            else orjson.dumps(result.output).decode("utf-8")
+        )
+        await _update_pending_operation(
+            session_id=session_id,
+            tool_call_id=tool_call_id,
+            result=result_str,
+        )
+
+        logger.info(
+            f"Background tool {tool_name} completed for session {session_id} "
+            f"(task_id={task_id})"
+        )
+
+        # Generate LLM continuation and stream chunks to registry
+        await _generate_llm_continuation_with_streaming(
+            session_id=session_id,
+            user_id=user_id,
+            task_id=task_id,
+        )
+
+        # Mark task as completed in stream registry
+        await stream_registry.mark_task_completed(task_id, status="completed")
+
+    except Exception as e:
+        logger.error(f"Background tool {tool_name} failed: {e}", exc_info=True)
+        error_response = ErrorResponse(
+            message=f"Tool {tool_name} failed: {str(e)}",
+        )
+
+        # Publish error to stream registry followed by finish event
+        await stream_registry.publish_chunk(
+            task_id,
+            StreamError(errorText=str(e)),
+        )
+        await stream_registry.publish_chunk(task_id, StreamFinishStep())
+        await stream_registry.publish_chunk(task_id, StreamFinish())
+
+        await _update_pending_operation(
+            session_id=session_id,
+            tool_call_id=tool_call_id,
+            result=error_response.model_dump_json(),
+        )
+
+        # Mark task as failed in stream registry
+        await stream_registry.mark_task_completed(task_id, status="failed")
+    finally:
+        # Only cleanup if we didn't delegate to async processing
+        # For async path, the Redis Streams completion consumer handles cleanup
+        if not delegated_to_async:
+            await _mark_operation_completed(tool_call_id)
+
+
 async def _update_pending_operation(
     session_id: str,
     tool_call_id: str,
@@ -1895,17 +1791,36 @@ async def _generate_llm_continuation(
         # Build system prompt
         system_prompt, _ = await _build_system_prompt(user_id)
 
-        # Build messages in OpenAI format
         messages = session.to_openai_messages()
         if system_prompt:
-            from openai.types.chat import ChatCompletionSystemMessageParam
-
             system_message = ChatCompletionSystemMessageParam(
                 role="system",
                 content=system_prompt,
             )
             messages = [system_message] + messages
 
+        # Apply context window management to prevent oversized requests
+        context_result = await _manage_context_window(
+            messages=messages,
+            model=config.model,
+            api_key=config.api_key,
+            base_url=config.base_url,
+        )
+
+        if context_result.error and "System prompt dropped" not in context_result.error:
+            logger.error(
+                f"Context window management failed for session {session_id}: "
+                f"{context_result.error} (tokens={context_result.token_count})"
+            )
+            return
+
+        messages = context_result.messages
+        if context_result.was_compacted:
+            logger.info(
+                f"Context compacted for LLM continuation: "
+                f"{context_result.token_count} tokens"
+            )
+
         # Build extra_body for tracing
         extra_body: dict[str, Any] = {
             "posthogProperties": {
@@ -1918,19 +1833,58 @@ async def _generate_llm_continuation(
         if session_id:
             extra_body["session_id"] = session_id[:128]
 
-        # Make non-streaming LLM call (no tools - just text response)
-        from typing import cast
+        # Enable adaptive thinking for Anthropic models via OpenRouter
+        if config.thinking_enabled and "anthropic" in config.model.lower():
+            extra_body["reasoning"] = {"enabled": True}
 
-        from openai.types.chat import ChatCompletionMessageParam
+        retry_count = 0
+        last_error: Exception | None = None
+        response = None
 
-        # No tools parameter = text-only response (no tool calls)
-        response = await client.chat.completions.create(
-            model=config.model,
-            messages=cast(list[ChatCompletionMessageParam], messages),
-            extra_body=extra_body,
-        )
+        while retry_count <= MAX_RETRIES:
+            try:
+                logger.info(
+                    f"Generating LLM continuation for session {session_id}"
+                    f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
+                )
 
-        if response.choices and response.choices[0].message.content:
+                response = await client.chat.completions.create(
+                    model=config.model,
+                    messages=cast(list[ChatCompletionMessageParam], messages),
+                    extra_body=extra_body,
+                )
+                last_error = None  # Clear any previous error on success
+                break  # Success, exit retry loop
+            except Exception as e:
+                last_error = e
+                if _is_retryable_error(e) and retry_count < MAX_RETRIES:
+                    retry_count += 1
+                    delay = min(
+                        BASE_DELAY_SECONDS * (2 ** (retry_count - 1)),
+                        MAX_DELAY_SECONDS,
+                    )
+                    logger.warning(
+                        f"Retryable error in LLM continuation: {e!s}. "
+                        f"Retrying in {delay:.1f}s (attempt {retry_count}/{MAX_RETRIES})"
+                    )
+                    await asyncio.sleep(delay)
+                    continue
+                else:
+                    # Non-retryable error - log and exit gracefully
+                    logger.error(
+                        f"Non-retryable error in LLM continuation: {e!s}",
+                        exc_info=True,
+                    )
+                    return
+
+        if last_error:
+            logger.error(
+                f"Max retries ({MAX_RETRIES}) exceeded for LLM continuation. "
+                f"Last error: {last_error!s}"
+            )
+            return
+
+        if response and response.choices and response.choices[0].message.content:
             assistant_content = response.choices[0].message.content
 
             # Reload session from DB to avoid race condition with user messages
@@ -1964,3 +1918,135 @@ async def _generate_llm_continuation(
 
     except Exception as e:
         logger.error(f"Failed to generate LLM continuation: {e}", exc_info=True)
+
+
+async def _generate_llm_continuation_with_streaming(
+    session_id: str,
+    user_id: str | None,
+    task_id: str,
+) -> None:
+    """Generate an LLM response with streaming to the stream registry.
+
+    This is called by background tasks to continue the conversation
+    after a tool result is saved. Chunks are published to the stream registry
+    so reconnecting clients can receive them.
+    """
+    import uuid as uuid_module
+
+    try:
+        # Load fresh session from DB (bypass cache to get the updated tool result)
+        await invalidate_session_cache(session_id)
+        session = await get_chat_session(session_id, user_id)
+        if not session:
+            logger.error(f"Session {session_id} not found for LLM continuation")
+            return
+
+        # Build system prompt
+        system_prompt, _ = await _build_system_prompt(user_id)
+
+        # Build messages in OpenAI format
+        messages = session.to_openai_messages()
+        if system_prompt:
+            from openai.types.chat import ChatCompletionSystemMessageParam
+
+            system_message = ChatCompletionSystemMessageParam(
+                role="system",
+                content=system_prompt,
+            )
+            messages = [system_message] + messages
+
+        # Build extra_body for tracing
+        extra_body: dict[str, Any] = {
+            "posthogProperties": {
+                "environment": settings.config.app_env.value,
+            },
+        }
+        if user_id:
+            extra_body["user"] = user_id[:128]
+            extra_body["posthogDistinctId"] = user_id
+        if session_id:
+            extra_body["session_id"] = session_id[:128]
+
+        # Enable adaptive thinking for Anthropic models via OpenRouter
+        if config.thinking_enabled and "anthropic" in config.model.lower():
+            extra_body["reasoning"] = {"enabled": True}
+
+        # Make streaming LLM call (no tools - just text response)
+        from typing import cast
+
+        from openai.types.chat import ChatCompletionMessageParam
+
+        # Generate unique IDs for AI SDK protocol
+        message_id = str(uuid_module.uuid4())
+        text_block_id = str(uuid_module.uuid4())
+
+        # Publish start event
+        await stream_registry.publish_chunk(task_id, StreamStart(messageId=message_id))
+        await stream_registry.publish_chunk(task_id, StreamStartStep())
+        await stream_registry.publish_chunk(task_id, StreamTextStart(id=text_block_id))
+
+        # Stream the response
+        stream = await client.chat.completions.create(
+            model=config.model,
+            messages=cast(list[ChatCompletionMessageParam], messages),
+            extra_body=extra_body,
+            stream=True,
+        )
+
+        assistant_content = ""
+        async for chunk in stream:
+            if chunk.choices and chunk.choices[0].delta.content:
+                delta = chunk.choices[0].delta.content
+                assistant_content += delta
+                # Publish delta to stream registry
+                await stream_registry.publish_chunk(
+                    task_id,
+                    StreamTextDelta(id=text_block_id, delta=delta),
+                )
+
+        # Publish end events
+        await stream_registry.publish_chunk(task_id, StreamTextEnd(id=text_block_id))
+        await stream_registry.publish_chunk(task_id, StreamFinishStep())
+
+        if assistant_content:
+            # Reload session from DB to avoid race condition with user messages
+            fresh_session = await get_chat_session(session_id, user_id)
+            if not fresh_session:
+                logger.error(
+                    f"Session {session_id} disappeared during LLM continuation"
+                )
+                return
+
+            # Save assistant message to database
+            assistant_message = ChatMessage(
+                role="assistant",
+                content=assistant_content,
+            )
+            fresh_session.messages.append(assistant_message)
+
+            # Save to database (not cache) to persist the response
+            await upsert_chat_session(fresh_session)
+
+            # Invalidate cache so next poll/refresh gets fresh data
+            await invalidate_session_cache(session_id)
+
+            logger.info(
+                f"Generated streaming LLM continuation for session {session_id} "
+                f"(task_id={task_id}), response length: {len(assistant_content)}"
+            )
+        else:
+            logger.warning(
+                f"Streaming LLM continuation returned empty response for {session_id}"
+            )
+
+    except Exception as e:
+        logger.error(
+            f"Failed to generate streaming LLM continuation: {e}", exc_info=True
+        )
+        # Publish error to stream registry followed by finish event
+        await stream_registry.publish_chunk(
+            task_id,
+            StreamError(errorText=f"Failed to generate response: {e}"),
+        )
+        await stream_registry.publish_chunk(task_id, StreamFinishStep())
+        await stream_registry.publish_chunk(task_id, StreamFinish())
diff --git a/autogpt_platform/backend/backend/api/features/chat/stream_registry.py b/autogpt_platform/backend/backend/api/features/chat/stream_registry.py
new file mode 100644
index 0000000000..abc34b1fc9
--- /dev/null
+++ b/autogpt_platform/backend/backend/api/features/chat/stream_registry.py
@@ -0,0 +1,967 @@
+"""Stream registry for managing reconnectable SSE streams.
+
+This module provides a registry for tracking active streaming tasks and their
+messages. It uses Redis for all state management (no in-memory state), making
+pods stateless and horizontally scalable.
+
+Architecture:
+- Redis Stream: Persists all messages for replay and real-time delivery
+- Redis Hash: Task metadata (status, session_id, etc.)
+
+Subscribers:
+1. Replay missed messages from Redis Stream (XREAD)
+2. Listen for live updates via blocking XREAD
+3. No in-memory state required on the subscribing pod
+"""
+
+import asyncio
+import logging
+from dataclasses import dataclass, field
+from datetime import datetime, timezone
+from typing import Any, Literal
+
+import orjson
+
+from backend.data.redis_client import get_redis_async
+
+from .config import ChatConfig
+from .response_model import StreamBaseResponse, StreamError, StreamFinish
+
+logger = logging.getLogger(__name__)
+config = ChatConfig()
+
+# Track background tasks for this pod (just the asyncio.Task reference, not subscribers)
+_local_tasks: dict[str, asyncio.Task] = {}
+
+# Track listener tasks per subscriber queue for cleanup
+# Maps queue id() to (task_id, asyncio.Task) for proper cleanup on unsubscribe
+_listener_tasks: dict[int, tuple[str, asyncio.Task]] = {}
+
+# Timeout for putting chunks into subscriber queues (seconds)
+# If the queue is full and doesn't drain within this time, send an overflow error
+QUEUE_PUT_TIMEOUT = 5.0
+
+# Lua script for atomic compare-and-swap status update (idempotent completion)
+# Returns 1 if status was updated, 0 if already completed/failed
+COMPLETE_TASK_SCRIPT = """
+local current = redis.call("HGET", KEYS[1], "status")
+if current == "running" then
+    redis.call("HSET", KEYS[1], "status", ARGV[1])
+    return 1
+end
+return 0
+"""
+
+
+@dataclass
+class ActiveTask:
+    """Represents an active streaming task (metadata only, no in-memory queues)."""
+
+    task_id: str
+    session_id: str
+    user_id: str | None
+    tool_call_id: str
+    tool_name: str
+    operation_id: str
+    status: Literal["running", "completed", "failed"] = "running"
+    created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
+    asyncio_task: asyncio.Task | None = None
+
+
+def _get_task_meta_key(task_id: str) -> str:
+    """Get Redis key for task metadata."""
+    return f"{config.task_meta_prefix}{task_id}"
+
+
+def _get_task_stream_key(task_id: str) -> str:
+    """Get Redis key for task message stream."""
+    return f"{config.task_stream_prefix}{task_id}"
+
+
+def _get_operation_mapping_key(operation_id: str) -> str:
+    """Get Redis key for operation_id to task_id mapping."""
+    return f"{config.task_op_prefix}{operation_id}"
+
+
+async def create_task(
+    task_id: str,
+    session_id: str,
+    user_id: str | None,
+    tool_call_id: str,
+    tool_name: str,
+    operation_id: str,
+) -> ActiveTask:
+    """Create a new streaming task in Redis.
+
+    Args:
+        task_id: Unique identifier for the task
+        session_id: Chat session ID
+        user_id: User ID (may be None for anonymous)
+        tool_call_id: Tool call ID from the LLM
+        tool_name: Name of the tool being executed
+        operation_id: Operation ID for webhook callbacks
+
+    Returns:
+        The created ActiveTask instance (metadata only)
+    """
+    import time
+
+    start_time = time.perf_counter()
+
+    # Build log metadata for structured logging
+    log_meta = {
+        "component": "StreamRegistry",
+        "task_id": task_id,
+        "session_id": session_id,
+    }
+    if user_id:
+        log_meta["user_id"] = user_id
+
+    logger.info(
+        f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}",
+        extra={"json_fields": log_meta},
+    )
+
+    task = ActiveTask(
+        task_id=task_id,
+        session_id=session_id,
+        user_id=user_id,
+        tool_call_id=tool_call_id,
+        tool_name=tool_name,
+        operation_id=operation_id,
+    )
+
+    # Store metadata in Redis
+    redis_start = time.perf_counter()
+    redis = await get_redis_async()
+    redis_time = (time.perf_counter() - redis_start) * 1000
+    logger.info(
+        f"[TIMING] get_redis_async took {redis_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": redis_time}},
+    )
+
+    meta_key = _get_task_meta_key(task_id)
+    op_key = _get_operation_mapping_key(operation_id)
+
+    hset_start = time.perf_counter()
+    await redis.hset(  # type: ignore[misc]
+        meta_key,
+        mapping={
+            "task_id": task_id,
+            "session_id": session_id,
+            "user_id": user_id or "",
+            "tool_call_id": tool_call_id,
+            "tool_name": tool_name,
+            "operation_id": operation_id,
+            "status": task.status,
+            "created_at": task.created_at.isoformat(),
+        },
+    )
+    hset_time = (time.perf_counter() - hset_start) * 1000
+    logger.info(
+        f"[TIMING] redis.hset took {hset_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": hset_time}},
+    )
+
+    await redis.expire(meta_key, config.stream_ttl)
+
+    # Create operation_id -> task_id mapping for webhook lookups
+    await redis.set(op_key, task_id, ex=config.stream_ttl)
+
+    total_time = (time.perf_counter() - start_time) * 1000
+    logger.info(
+        f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
+        extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
+    )
+
+    return task
+
+
+async def publish_chunk(
+    task_id: str,
+    chunk: StreamBaseResponse,
+) -> str:
+    """Publish a chunk to Redis Stream.
+
+    All delivery is via Redis Streams - no in-memory state.
+
+    Args:
+        task_id: Task ID to publish to
+        chunk: The stream response chunk to publish
+
+    Returns:
+        The Redis Stream message ID
+    """
+    import time
+
+    start_time = time.perf_counter()
+    chunk_type = type(chunk).__name__
+    chunk_json = chunk.model_dump_json()
+    message_id = "0-0"
+
+    # Build log metadata
+    log_meta = {
+        "component": "StreamRegistry",
+        "task_id": task_id,
+        "chunk_type": chunk_type,
+    }
+
+    try:
+        redis = await get_redis_async()
+        stream_key = _get_task_stream_key(task_id)
+
+        # Write to Redis Stream for persistence and real-time delivery
+        xadd_start = time.perf_counter()
+        raw_id = await redis.xadd(
+            stream_key,
+            {"data": chunk_json},
+            maxlen=config.stream_max_length,
+        )
+        xadd_time = (time.perf_counter() - xadd_start) * 1000
+        message_id = raw_id if isinstance(raw_id, str) else raw_id.decode()
+
+        # Set TTL on stream to match task metadata TTL
+        await redis.expire(stream_key, config.stream_ttl)
+
+        total_time = (time.perf_counter() - start_time) * 1000
+        # Only log timing for significant chunks or slow operations
+        if (
+            chunk_type
+            in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd")
+            or total_time > 50
+        ):
+            logger.info(
+                f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "total_time_ms": total_time,
+                        "xadd_time_ms": xadd_time,
+                        "message_id": message_id,
+                    }
+                },
+            )
+    except Exception as e:
+        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.error(
+            f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}",
+            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
+            exc_info=True,
+        )
+
+    return message_id
+
+
+async def subscribe_to_task(
+    task_id: str,
+    user_id: str | None,
+    last_message_id: str = "0-0",
+) -> asyncio.Queue[StreamBaseResponse] | None:
+    """Subscribe to a task's stream with replay of missed messages.
+
+    This is fully stateless - uses Redis Stream for replay and pub/sub for live updates.
+
+    Args:
+        task_id: Task ID to subscribe to
+        user_id: User ID for ownership validation
+        last_message_id: Last Redis Stream message ID received ("0-0" for full replay)
+
+    Returns:
+        An asyncio Queue that will receive stream chunks, or None if task not found
+        or user doesn't have access
+    """
+    import time
+
+    start_time = time.perf_counter()
+
+    # Build log metadata
+    log_meta = {"component": "StreamRegistry", "task_id": task_id}
+    if user_id:
+        log_meta["user_id"] = user_id
+
+    logger.info(
+        f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}",
+        extra={"json_fields": {**log_meta, "last_message_id": last_message_id}},
+    )
+
+    redis_start = time.perf_counter()
+    redis = await get_redis_async()
+    meta_key = _get_task_meta_key(task_id)
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
+    hgetall_time = (time.perf_counter() - redis_start) * 1000
+    logger.info(
+        f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}},
+    )
+
+    if not meta:
+        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.info(
+            f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "elapsed_ms": elapsed,
+                    "reason": "task_not_found",
+                }
+            },
+        )
+        return None
+
+    # Note: Redis client uses decode_responses=True, so keys are strings
+    task_status = meta.get("status", "")
+    task_user_id = meta.get("user_id", "") or None
+    log_meta["session_id"] = meta.get("session_id", "")
+
+    # Validate ownership - if task has an owner, requester must match
+    if task_user_id:
+        if user_id != task_user_id:
+            logger.warning(
+                f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "task_owner": task_user_id,
+                        "reason": "access_denied",
+                    }
+                },
+            )
+            return None
+
+    subscriber_queue: asyncio.Queue[StreamBaseResponse] = asyncio.Queue()
+    stream_key = _get_task_stream_key(task_id)
+
+    # Step 1: Replay messages from Redis Stream
+    xread_start = time.perf_counter()
+    messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
+    xread_time = (time.perf_counter() - xread_start) * 1000
+    logger.info(
+        f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "duration_ms": xread_time,
+                "task_status": task_status,
+            }
+        },
+    )
+
+    replayed_count = 0
+    replay_last_id = last_message_id
+    if messages:
+        for _stream_name, stream_messages in messages:
+            for msg_id, msg_data in stream_messages:
+                replay_last_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
+                # Note: Redis client uses decode_responses=True, so keys are strings
+                if "data" in msg_data:
+                    try:
+                        chunk_data = orjson.loads(msg_data["data"])
+                        chunk = _reconstruct_chunk(chunk_data)
+                        if chunk:
+                            await subscriber_queue.put(chunk)
+                            replayed_count += 1
+                    except Exception as e:
+                        logger.warning(f"Failed to replay message: {e}")
+
+    logger.info(
+        f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "n_messages_replayed": replayed_count,
+                "replay_last_id": replay_last_id,
+            }
+        },
+    )
+
+    # Step 2: If task is still running, start stream listener for live updates
+    if task_status == "running":
+        logger.info(
+            "[TIMING] Task still running, starting _stream_listener",
+            extra={"json_fields": {**log_meta, "task_status": task_status}},
+        )
+        listener_task = asyncio.create_task(
+            _stream_listener(task_id, subscriber_queue, replay_last_id, log_meta)
+        )
+        # Track listener task for cleanup on unsubscribe
+        _listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
+    else:
+        # Task is completed/failed - add finish marker
+        logger.info(
+            f"[TIMING] Task already {task_status}, adding StreamFinish",
+            extra={"json_fields": {**log_meta, "task_status": task_status}},
+        )
+        await subscriber_queue.put(StreamFinish())
+
+    total_time = (time.perf_counter() - start_time) * 1000
+    logger.info(
+        f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
+        f"n_messages_replayed={replayed_count}",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "total_time_ms": total_time,
+                "n_messages_replayed": replayed_count,
+            }
+        },
+    )
+    return subscriber_queue
+
+
+async def _stream_listener(
+    task_id: str,
+    subscriber_queue: asyncio.Queue[StreamBaseResponse],
+    last_replayed_id: str,
+    log_meta: dict | None = None,
+) -> None:
+    """Listen to Redis Stream for new messages using blocking XREAD.
+
+    This approach avoids the duplicate message issue that can occur with pub/sub
+    when messages are published during the gap between replay and subscription.
+
+    Args:
+        task_id: Task ID to listen for
+        subscriber_queue: Queue to deliver messages to
+        last_replayed_id: Last message ID from replay (continue from here)
+        log_meta: Structured logging metadata
+    """
+    import time
+
+    start_time = time.perf_counter()
+
+    # Use provided log_meta or build minimal one
+    if log_meta is None:
+        log_meta = {"component": "StreamRegistry", "task_id": task_id}
+
+    logger.info(
+        f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}",
+        extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}},
+    )
+
+    queue_id = id(subscriber_queue)
+    # Track the last successfully delivered message ID for recovery hints
+    last_delivered_id = last_replayed_id
+    messages_delivered = 0
+    first_message_time = None
+    xread_count = 0
+
+    try:
+        redis = await get_redis_async()
+        stream_key = _get_task_stream_key(task_id)
+        current_id = last_replayed_id
+
+        while True:
+            # Block for up to 30 seconds waiting for new messages
+            # This allows periodic checking if task is still running
+            xread_start = time.perf_counter()
+            xread_count += 1
+            messages = await redis.xread(
+                {stream_key: current_id}, block=30000, count=100
+            )
+            xread_time = (time.perf_counter() - xread_start) * 1000
+
+            if messages:
+                msg_count = sum(len(msgs) for _, msgs in messages)
+                logger.info(
+                    f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "xread_count": xread_count,
+                            "n_messages": msg_count,
+                            "duration_ms": xread_time,
+                        }
+                    },
+                )
+            elif xread_time > 1000:
+                # Only log timeouts (30s blocking)
+                logger.info(
+                    f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "xread_count": xread_count,
+                            "duration_ms": xread_time,
+                            "reason": "timeout",
+                        }
+                    },
+                )
+
+            if not messages:
+                # Timeout - check if task is still running
+                meta_key = _get_task_meta_key(task_id)
+                status = await redis.hget(meta_key, "status")  # type: ignore[misc]
+                if status and status != "running":
+                    try:
+                        await asyncio.wait_for(
+                            subscriber_queue.put(StreamFinish()),
+                            timeout=QUEUE_PUT_TIMEOUT,
+                        )
+                    except asyncio.TimeoutError:
+                        logger.warning(
+                            f"Timeout delivering finish event for task {task_id}"
+                        )
+                    break
+                continue
+
+            for _stream_name, stream_messages in messages:
+                for msg_id, msg_data in stream_messages:
+                    current_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
+
+                    if "data" not in msg_data:
+                        continue
+
+                    try:
+                        chunk_data = orjson.loads(msg_data["data"])
+                        chunk = _reconstruct_chunk(chunk_data)
+                        if chunk:
+                            try:
+                                await asyncio.wait_for(
+                                    subscriber_queue.put(chunk),
+                                    timeout=QUEUE_PUT_TIMEOUT,
+                                )
+                                # Update last delivered ID on successful delivery
+                                last_delivered_id = current_id
+                                messages_delivered += 1
+                                if first_message_time is None:
+                                    first_message_time = time.perf_counter()
+                                    elapsed = (first_message_time - start_time) * 1000
+                                    logger.info(
+                                        f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
+                                        extra={
+                                            "json_fields": {
+                                                **log_meta,
+                                                "elapsed_ms": elapsed,
+                                                "chunk_type": type(chunk).__name__,
+                                            }
+                                        },
+                                    )
+                            except asyncio.TimeoutError:
+                                logger.warning(
+                                    f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "timeout_s": QUEUE_PUT_TIMEOUT,
+                                            "reason": "queue_full",
+                                        }
+                                    },
+                                )
+                                # Send overflow error with recovery info
+                                try:
+                                    overflow_error = StreamError(
+                                        errorText="Message delivery timeout - some messages may have been missed",
+                                        code="QUEUE_OVERFLOW",
+                                        details={
+                                            "last_delivered_id": last_delivered_id,
+                                            "recovery_hint": f"Reconnect with last_message_id={last_delivered_id}",
+                                        },
+                                    )
+                                    subscriber_queue.put_nowait(overflow_error)
+                                except asyncio.QueueFull:
+                                    # Queue is completely stuck, nothing more we can do
+                                    logger.error(
+                                        f"Cannot deliver overflow error for task {task_id}, "
+                                        "queue completely blocked"
+                                    )
+
+                            # Stop listening on finish
+                            if isinstance(chunk, StreamFinish):
+                                total_time = (time.perf_counter() - start_time) * 1000
+                                logger.info(
+                                    f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "total_time_ms": total_time,
+                                            "messages_delivered": messages_delivered,
+                                        }
+                                    },
+                                )
+                                return
+                    except Exception as e:
+                        logger.warning(
+                            f"Error processing stream message: {e}",
+                            extra={"json_fields": {**log_meta, "error": str(e)}},
+                        )
+
+    except asyncio.CancelledError:
+        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.info(
+            f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "elapsed_ms": elapsed,
+                    "messages_delivered": messages_delivered,
+                    "reason": "cancelled",
+                }
+            },
+        )
+        raise  # Re-raise to propagate cancellation
+    except Exception as e:
+        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.error(
+            f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}",
+            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
+        )
+        # On error, send finish to unblock subscriber
+        try:
+            await asyncio.wait_for(
+                subscriber_queue.put(StreamFinish()),
+                timeout=QUEUE_PUT_TIMEOUT,
+            )
+        except (asyncio.TimeoutError, asyncio.QueueFull):
+            logger.warning(
+                "Could not deliver finish event after error",
+                extra={"json_fields": log_meta},
+            )
+    finally:
+        # Clean up listener task mapping on exit
+        total_time = (time.perf_counter() - start_time) * 1000
+        logger.info(
+            f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
+            f"delivered={messages_delivered}, xread_count={xread_count}",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "total_time_ms": total_time,
+                    "messages_delivered": messages_delivered,
+                    "xread_count": xread_count,
+                }
+            },
+        )
+        _listener_tasks.pop(queue_id, None)
+
+
+async def mark_task_completed(
+    task_id: str,
+    status: Literal["completed", "failed"] = "completed",
+) -> bool:
+    """Mark a task as completed and publish finish event.
+
+    This is idempotent - calling multiple times with the same task_id is safe.
+    Uses atomic compare-and-swap via Lua script to prevent race conditions.
+    Status is updated first (source of truth), then finish event is published (best-effort).
+
+    Args:
+        task_id: Task ID to mark as completed
+        status: Final status ("completed" or "failed")
+
+    Returns:
+        True if task was newly marked completed, False if already completed/failed
+    """
+    redis = await get_redis_async()
+    meta_key = _get_task_meta_key(task_id)
+
+    # Atomic compare-and-swap: only update if status is "running"
+    # This prevents race conditions when multiple callers try to complete simultaneously
+    result = await redis.eval(COMPLETE_TASK_SCRIPT, 1, meta_key, status)  # type: ignore[misc]
+
+    if result == 0:
+        logger.debug(f"Task {task_id} already completed/failed, skipping")
+        return False
+
+    # THEN publish finish event (best-effort - listeners can detect via status polling)
+    try:
+        await publish_chunk(task_id, StreamFinish())
+    except Exception as e:
+        logger.error(
+            f"Failed to publish finish event for task {task_id}: {e}. "
+            "Listeners will detect completion via status polling."
+        )
+
+    # Clean up local task reference if exists
+    _local_tasks.pop(task_id, None)
+    return True
+
+
+async def find_task_by_operation_id(operation_id: str) -> ActiveTask | None:
+    """Find a task by its operation ID.
+
+    Used by webhook callbacks to locate the task to update.
+
+    Args:
+        operation_id: Operation ID to search for
+
+    Returns:
+        ActiveTask if found, None otherwise
+    """
+    redis = await get_redis_async()
+    op_key = _get_operation_mapping_key(operation_id)
+    task_id = await redis.get(op_key)
+
+    if not task_id:
+        return None
+
+    task_id_str = task_id.decode() if isinstance(task_id, bytes) else task_id
+    return await get_task(task_id_str)
+
+
+async def get_task(task_id: str) -> ActiveTask | None:
+    """Get a task by its ID from Redis.
+
+    Args:
+        task_id: Task ID to look up
+
+    Returns:
+        ActiveTask if found, None otherwise
+    """
+    redis = await get_redis_async()
+    meta_key = _get_task_meta_key(task_id)
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
+
+    if not meta:
+        return None
+
+    # Note: Redis client uses decode_responses=True, so keys/values are strings
+    return ActiveTask(
+        task_id=meta.get("task_id", ""),
+        session_id=meta.get("session_id", ""),
+        user_id=meta.get("user_id", "") or None,
+        tool_call_id=meta.get("tool_call_id", ""),
+        tool_name=meta.get("tool_name", ""),
+        operation_id=meta.get("operation_id", ""),
+        status=meta.get("status", "running"),  # type: ignore[arg-type]
+    )
+
+
+async def get_task_with_expiry_info(
+    task_id: str,
+) -> tuple[ActiveTask | None, str | None]:
+    """Get a task by its ID with expiration detection.
+
+    Returns (task, error_code) where error_code is:
+    - None if task found
+    - "TASK_EXPIRED" if stream exists but metadata is gone (TTL expired)
+    - "TASK_NOT_FOUND" if neither exists
+
+    Args:
+        task_id: Task ID to look up
+
+    Returns:
+        Tuple of (ActiveTask or None, error_code or None)
+    """
+    redis = await get_redis_async()
+    meta_key = _get_task_meta_key(task_id)
+    stream_key = _get_task_stream_key(task_id)
+
+    meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
+
+    if not meta:
+        # Check if stream still has data (metadata expired but stream hasn't)
+        stream_len = await redis.xlen(stream_key)
+        if stream_len > 0:
+            return None, "TASK_EXPIRED"
+        return None, "TASK_NOT_FOUND"
+
+    # Note: Redis client uses decode_responses=True, so keys/values are strings
+    return (
+        ActiveTask(
+            task_id=meta.get("task_id", ""),
+            session_id=meta.get("session_id", ""),
+            user_id=meta.get("user_id", "") or None,
+            tool_call_id=meta.get("tool_call_id", ""),
+            tool_name=meta.get("tool_name", ""),
+            operation_id=meta.get("operation_id", ""),
+            status=meta.get("status", "running"),  # type: ignore[arg-type]
+        ),
+        None,
+    )
+
+
+async def get_active_task_for_session(
+    session_id: str,
+    user_id: str | None = None,
+) -> tuple[ActiveTask | None, str]:
+    """Get the active (running) task for a session, if any.
+
+    Scans Redis for tasks matching the session_id with status="running".
+
+    Args:
+        session_id: Session ID to look up
+        user_id: User ID for ownership validation (optional)
+
+    Returns:
+        Tuple of (ActiveTask if found and running, last_message_id from Redis Stream)
+    """
+
+    redis = await get_redis_async()
+
+    # Scan Redis for task metadata keys
+    cursor = 0
+    tasks_checked = 0
+
+    while True:
+        cursor, keys = await redis.scan(
+            cursor, match=f"{config.task_meta_prefix}*", count=100
+        )
+
+        for key in keys:
+            tasks_checked += 1
+            meta: dict[Any, Any] = await redis.hgetall(key)  # type: ignore[misc]
+            if not meta:
+                continue
+
+            # Note: Redis client uses decode_responses=True, so keys/values are strings
+            task_session_id = meta.get("session_id", "")
+            task_status = meta.get("status", "")
+            task_user_id = meta.get("user_id", "") or None
+            task_id = meta.get("task_id", "")
+
+            if task_session_id == session_id and task_status == "running":
+                # Validate ownership - if task has an owner, requester must match
+                if task_user_id and user_id != task_user_id:
+                    continue
+
+                # Get the last message ID from Redis Stream
+                stream_key = _get_task_stream_key(task_id)
+                last_id = "0-0"
+                try:
+                    messages = await redis.xrevrange(stream_key, count=1)
+                    if messages:
+                        msg_id = messages[0][0]
+                        last_id = msg_id if isinstance(msg_id, str) else msg_id.decode()
+                except Exception as e:
+                    logger.warning(f"Failed to get last message ID: {e}")
+
+                return (
+                    ActiveTask(
+                        task_id=task_id,
+                        session_id=task_session_id,
+                        user_id=task_user_id,
+                        tool_call_id=meta.get("tool_call_id", ""),
+                        tool_name=meta.get("tool_name", ""),
+                        operation_id=meta.get("operation_id", ""),
+                        status="running",
+                    ),
+                    last_id,
+                )
+
+        if cursor == 0:
+            break
+
+    return None, "0-0"
+
+
+def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
+    """Reconstruct a StreamBaseResponse from JSON data.
+
+    Args:
+        chunk_data: Parsed JSON data from Redis
+
+    Returns:
+        Reconstructed response object, or None if unknown type
+    """
+    from .response_model import (
+        ResponseType,
+        StreamError,
+        StreamFinish,
+        StreamFinishStep,
+        StreamHeartbeat,
+        StreamStart,
+        StreamStartStep,
+        StreamTextDelta,
+        StreamTextEnd,
+        StreamTextStart,
+        StreamToolInputAvailable,
+        StreamToolInputStart,
+        StreamToolOutputAvailable,
+        StreamUsage,
+    )
+
+    # Map response types to their corresponding classes
+    type_to_class: dict[str, type[StreamBaseResponse]] = {
+        ResponseType.START.value: StreamStart,
+        ResponseType.FINISH.value: StreamFinish,
+        ResponseType.START_STEP.value: StreamStartStep,
+        ResponseType.FINISH_STEP.value: StreamFinishStep,
+        ResponseType.TEXT_START.value: StreamTextStart,
+        ResponseType.TEXT_DELTA.value: StreamTextDelta,
+        ResponseType.TEXT_END.value: StreamTextEnd,
+        ResponseType.TOOL_INPUT_START.value: StreamToolInputStart,
+        ResponseType.TOOL_INPUT_AVAILABLE.value: StreamToolInputAvailable,
+        ResponseType.TOOL_OUTPUT_AVAILABLE.value: StreamToolOutputAvailable,
+        ResponseType.ERROR.value: StreamError,
+        ResponseType.USAGE.value: StreamUsage,
+        ResponseType.HEARTBEAT.value: StreamHeartbeat,
+    }
+
+    chunk_type = chunk_data.get("type")
+    chunk_class = type_to_class.get(chunk_type)  # type: ignore[arg-type]
+
+    if chunk_class is None:
+        logger.warning(f"Unknown chunk type: {chunk_type}")
+        return None
+
+    try:
+        return chunk_class(**chunk_data)
+    except Exception as e:
+        logger.warning(f"Failed to reconstruct chunk of type {chunk_type}: {e}")
+        return None
+
+
+async def set_task_asyncio_task(task_id: str, asyncio_task: asyncio.Task) -> None:
+    """Track the asyncio.Task for a task (local reference only).
+
+    This is just for cleanup purposes - the task state is in Redis.
+
+    Args:
+        task_id: Task ID
+        asyncio_task: The asyncio Task to track
+    """
+    _local_tasks[task_id] = asyncio_task
+
+
+async def unsubscribe_from_task(
+    task_id: str,
+    subscriber_queue: asyncio.Queue[StreamBaseResponse],
+) -> None:
+    """Clean up when a subscriber disconnects.
+
+    Cancels the XREAD-based listener task associated with this subscriber queue
+    to prevent resource leaks.
+
+    Args:
+        task_id: Task ID
+        subscriber_queue: The subscriber's queue used to look up the listener task
+    """
+    queue_id = id(subscriber_queue)
+    listener_entry = _listener_tasks.pop(queue_id, None)
+
+    if listener_entry is None:
+        logger.debug(
+            f"No listener task found for task {task_id} queue {queue_id} "
+            "(may have already completed)"
+        )
+        return
+
+    stored_task_id, listener_task = listener_entry
+
+    if stored_task_id != task_id:
+        logger.warning(
+            f"Task ID mismatch in unsubscribe: expected {task_id}, "
+            f"found {stored_task_id}"
+        )
+
+    if listener_task.done():
+        logger.debug(f"Listener task for task {task_id} already completed")
+        return
+
+    # Cancel the listener task
+    listener_task.cancel()
+
+    try:
+        # Wait for the task to be cancelled with a timeout
+        await asyncio.wait_for(listener_task, timeout=5.0)
+    except asyncio.CancelledError:
+        # Expected - the task was successfully cancelled
+        pass
+    except asyncio.TimeoutError:
+        logger.warning(
+            f"Timeout waiting for listener task cancellation for task {task_id}"
+        )
+    except Exception as e:
+        logger.error(f"Error during listener task cancellation for task {task_id}: {e}")
+
+    logger.debug(f"Successfully unsubscribed from task {task_id}")
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/__init__.py b/autogpt_platform/backend/backend/api/features/chat/tools/__init__.py
index d078860c3a..dcbc35ef37 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/__init__.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/__init__.py
@@ -10,6 +10,7 @@ from .add_understanding import AddUnderstandingTool
 from .agent_output import AgentOutputTool
 from .base import BaseTool
 from .create_agent import CreateAgentTool
+from .customize_agent import CustomizeAgentTool
 from .edit_agent import EditAgentTool
 from .find_agent import FindAgentTool
 from .find_block import FindBlockTool
@@ -34,6 +35,7 @@ logger = logging.getLogger(__name__)
 TOOL_REGISTRY: dict[str, BaseTool] = {
     "add_understanding": AddUnderstandingTool(),
     "create_agent": CreateAgentTool(),
+    "customize_agent": CustomizeAgentTool(),
     "edit_agent": EditAgentTool(),
     "find_agent": FindAgentTool(),
     "find_block": FindBlockTool(),
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/__init__.py b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/__init__.py
index 499025b7dc..4266834220 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/__init__.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/__init__.py
@@ -2,30 +2,58 @@
 
 from .core import (
     AgentGeneratorNotConfiguredError,
+    AgentJsonValidationError,
+    AgentSummary,
+    DecompositionResult,
+    DecompositionStep,
+    LibraryAgentSummary,
+    MarketplaceAgentSummary,
+    customize_template,
     decompose_goal,
+    enrich_library_agents_from_steps,
+    extract_search_terms_from_steps,
+    extract_uuids_from_text,
     generate_agent,
     generate_agent_patch,
     get_agent_as_json,
+    get_all_relevant_agents_for_generation,
+    get_library_agent_by_graph_id,
+    get_library_agent_by_id,
+    get_library_agents_for_generation,
+    graph_to_json,
     json_to_graph,
     save_agent_to_library,
+    search_marketplace_agents_for_generation,
 )
 from .errors import get_user_message_for_error
 from .service import health_check as check_external_service_health
 from .service import is_external_service_configured
 
 __all__ = [
-    # Core functions
+    "AgentGeneratorNotConfiguredError",
+    "AgentJsonValidationError",
+    "AgentSummary",
+    "DecompositionResult",
+    "DecompositionStep",
+    "LibraryAgentSummary",
+    "MarketplaceAgentSummary",
+    "check_external_service_health",
+    "customize_template",
     "decompose_goal",
+    "enrich_library_agents_from_steps",
+    "extract_search_terms_from_steps",
+    "extract_uuids_from_text",
     "generate_agent",
     "generate_agent_patch",
-    "save_agent_to_library",
     "get_agent_as_json",
-    "json_to_graph",
-    # Exceptions
-    "AgentGeneratorNotConfiguredError",
-    # Service
-    "is_external_service_configured",
-    "check_external_service_health",
-    # Error handling
+    "get_all_relevant_agents_for_generation",
+    "get_library_agent_by_graph_id",
+    "get_library_agent_by_id",
+    "get_library_agents_for_generation",
     "get_user_message_for_error",
+    "graph_to_json",
+    "is_external_service_configured",
+    "json_to_graph",
+    "save_agent_to_library",
+    "search_marketplace_agents_for_generation",
 ]
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py
index d56e33cbb0..f83ca30b5c 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py
@@ -1,13 +1,17 @@
 """Core agent generation functions."""
 
 import logging
+import re
 import uuid
-from typing import Any
+from typing import Any, NotRequired, TypedDict
 
 from backend.api.features.library import db as library_db
-from backend.data.graph import Graph, Link, Node, create_graph
+from backend.api.features.store import db as store_db
+from backend.data.graph import Graph, Link, Node, get_graph, get_store_listed_graphs
+from backend.util.exceptions import DatabaseError, NotFoundError
 
 from .service import (
+    customize_template_external,
     decompose_goal_external,
     generate_agent_external,
     generate_agent_patch_external,
@@ -17,6 +21,72 @@ from .service import (
 logger = logging.getLogger(__name__)
 
 
+class ExecutionSummary(TypedDict):
+    """Summary of a single execution for quality assessment."""
+
+    status: str
+    correctness_score: NotRequired[float]
+    activity_summary: NotRequired[str]
+
+
+class LibraryAgentSummary(TypedDict):
+    """Summary of a library agent for sub-agent composition.
+
+    Includes recent executions to help the LLM decide whether to use this agent.
+    Each execution shows status, correctness_score (0-1), and activity_summary.
+    """
+
+    graph_id: str
+    graph_version: int
+    name: str
+    description: str
+    input_schema: dict[str, Any]
+    output_schema: dict[str, Any]
+    recent_executions: NotRequired[list[ExecutionSummary]]
+
+
+class MarketplaceAgentSummary(TypedDict):
+    """Summary of a marketplace agent for sub-agent composition."""
+
+    name: str
+    description: str
+    sub_heading: str
+    creator: str
+    is_marketplace_agent: bool
+
+
+class DecompositionStep(TypedDict, total=False):
+    """A single step in decomposed instructions."""
+
+    description: str
+    action: str
+    block_name: str
+    tool: str
+    name: str
+
+
+class DecompositionResult(TypedDict, total=False):
+    """Result from decompose_goal - can be instructions, questions, or error."""
+
+    type: str
+    steps: list[DecompositionStep]
+    questions: list[dict[str, Any]]
+    error: str
+    error_type: str
+
+
+AgentSummary = LibraryAgentSummary | MarketplaceAgentSummary | dict[str, Any]
+
+
+def _to_dict_list(
+    agents: list[AgentSummary] | list[dict[str, Any]] | None,
+) -> list[dict[str, Any]] | None:
+    """Convert typed agent summaries to plain dicts for external service calls."""
+    if agents is None:
+        return None
+    return [dict(a) for a in agents]
+
+
 class AgentGeneratorNotConfiguredError(Exception):
     """Raised when the external Agent Generator service is not configured."""
 
@@ -36,15 +106,422 @@ def _check_service_configured() -> None:
         )
 
 
-async def decompose_goal(description: str, context: str = "") -> dict[str, Any] | None:
+_UUID_PATTERN = re.compile(
+    r"[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}",
+    re.IGNORECASE,
+)
+
+
+def extract_uuids_from_text(text: str) -> list[str]:
+    """Extract all UUID v4 strings from text.
+
+    Args:
+        text: Text that may contain UUIDs (e.g., user's goal description)
+
+    Returns:
+        List of unique UUIDs found in the text (lowercase)
+    """
+    matches = _UUID_PATTERN.findall(text)
+    return list({m.lower() for m in matches})
+
+
+async def get_library_agent_by_id(
+    user_id: str, agent_id: str
+) -> LibraryAgentSummary | None:
+    """Fetch a specific library agent by its ID (library agent ID or graph_id).
+
+    This function tries multiple lookup strategies:
+    1. First tries to find by graph_id (AgentGraph primary key)
+    2. If not found, tries to find by library agent ID (LibraryAgent primary key)
+
+    This handles both cases:
+    - User provides graph_id (e.g., from AgentExecutorBlock)
+    - User provides library agent ID (e.g., from library URL)
+
+    Args:
+        user_id: The user ID
+        agent_id: The ID to look up (can be graph_id or library agent ID)
+
+    Returns:
+        LibraryAgentSummary if found, None otherwise
+    """
+    try:
+        agent = await library_db.get_library_agent_by_graph_id(user_id, agent_id)
+        if agent:
+            logger.debug(f"Found library agent by graph_id: {agent.name}")
+            return LibraryAgentSummary(
+                graph_id=agent.graph_id,
+                graph_version=agent.graph_version,
+                name=agent.name,
+                description=agent.description,
+                input_schema=agent.input_schema,
+                output_schema=agent.output_schema,
+            )
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.debug(f"Could not fetch library agent by graph_id {agent_id}: {e}")
+
+    try:
+        agent = await library_db.get_library_agent(agent_id, user_id)
+        if agent:
+            logger.debug(f"Found library agent by library_id: {agent.name}")
+            return LibraryAgentSummary(
+                graph_id=agent.graph_id,
+                graph_version=agent.graph_version,
+                name=agent.name,
+                description=agent.description,
+                input_schema=agent.input_schema,
+                output_schema=agent.output_schema,
+            )
+    except NotFoundError:
+        logger.debug(f"Library agent not found by library_id: {agent_id}")
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.warning(
+            f"Could not fetch library agent by library_id {agent_id}: {e}",
+            exc_info=True,
+        )
+
+    return None
+
+
+get_library_agent_by_graph_id = get_library_agent_by_id
+
+
+async def get_library_agents_for_generation(
+    user_id: str,
+    search_query: str | None = None,
+    exclude_graph_id: str | None = None,
+    max_results: int = 15,
+) -> list[LibraryAgentSummary]:
+    """Fetch user's library agents formatted for Agent Generator.
+
+    Uses search-based fetching to return relevant agents instead of all agents.
+    This is more scalable for users with large libraries.
+
+    Includes recent_executions list to help the LLM assess agent quality:
+    - Each execution has status, correctness_score (0-1), and activity_summary
+    - This gives the LLM concrete examples of recent performance
+
+    Args:
+        user_id: The user ID
+        search_query: Optional search term to find relevant agents (user's goal/description)
+        exclude_graph_id: Optional graph ID to exclude (prevents circular references)
+        max_results: Maximum number of agents to return (default 15)
+
+    Returns:
+        List of LibraryAgentSummary with schemas and recent executions for sub-agent composition
+    """
+    try:
+        response = await library_db.list_library_agents(
+            user_id=user_id,
+            search_term=search_query,
+            page=1,
+            page_size=max_results,
+            include_executions=True,
+        )
+
+        results: list[LibraryAgentSummary] = []
+        for agent in response.agents:
+            if exclude_graph_id is not None and agent.graph_id == exclude_graph_id:
+                continue
+
+            summary = LibraryAgentSummary(
+                graph_id=agent.graph_id,
+                graph_version=agent.graph_version,
+                name=agent.name,
+                description=agent.description,
+                input_schema=agent.input_schema,
+                output_schema=agent.output_schema,
+            )
+            if agent.recent_executions:
+                exec_summaries: list[ExecutionSummary] = []
+                for ex in agent.recent_executions:
+                    exec_sum = ExecutionSummary(status=ex.status)
+                    if ex.correctness_score is not None:
+                        exec_sum["correctness_score"] = ex.correctness_score
+                    if ex.activity_summary:
+                        exec_sum["activity_summary"] = ex.activity_summary
+                    exec_summaries.append(exec_sum)
+                summary["recent_executions"] = exec_summaries
+            results.append(summary)
+        return results
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.warning(f"Failed to fetch library agents: {e}")
+        return []
+
+
+async def search_marketplace_agents_for_generation(
+    search_query: str,
+    max_results: int = 10,
+) -> list[LibraryAgentSummary]:
+    """Search marketplace agents formatted for Agent Generator.
+
+    Fetches marketplace agents and their full schemas so they can be used
+    as sub-agents in generated workflows.
+
+    Args:
+        search_query: Search term to find relevant public agents
+        max_results: Maximum number of agents to return (default 10)
+
+    Returns:
+        List of LibraryAgentSummary with full input/output schemas
+    """
+    try:
+        response = await store_db.get_store_agents(
+            search_query=search_query,
+            page=1,
+            page_size=max_results,
+        )
+
+        agents_with_graphs = [
+            agent for agent in response.agents if agent.agent_graph_id
+        ]
+
+        if not agents_with_graphs:
+            return []
+
+        graph_ids = [agent.agent_graph_id for agent in agents_with_graphs]
+        graphs = await get_store_listed_graphs(*graph_ids)
+
+        results: list[LibraryAgentSummary] = []
+        for agent in agents_with_graphs:
+            graph_id = agent.agent_graph_id
+            if graph_id and graph_id in graphs:
+                graph = graphs[graph_id]
+                results.append(
+                    LibraryAgentSummary(
+                        graph_id=graph.id,
+                        graph_version=graph.version,
+                        name=agent.agent_name,
+                        description=agent.description,
+                        input_schema=graph.input_schema,
+                        output_schema=graph.output_schema,
+                    )
+                )
+        return results
+    except Exception as e:
+        logger.warning(f"Failed to search marketplace agents: {e}")
+        return []
+
+
+async def get_all_relevant_agents_for_generation(
+    user_id: str,
+    search_query: str | None = None,
+    exclude_graph_id: str | None = None,
+    include_library: bool = True,
+    include_marketplace: bool = True,
+    max_library_results: int = 15,
+    max_marketplace_results: int = 10,
+) -> list[AgentSummary]:
+    """Fetch relevant agents from library and/or marketplace.
+
+    Searches both user's library and marketplace by default.
+    Explicitly mentioned UUIDs in the search query are always looked up.
+
+    Args:
+        user_id: The user ID
+        search_query: Search term to find relevant agents (user's goal/description)
+        exclude_graph_id: Optional graph ID to exclude (prevents circular references)
+        include_library: Whether to search user's library (default True)
+        include_marketplace: Whether to also search marketplace (default True)
+        max_library_results: Max library agents to return (default 15)
+        max_marketplace_results: Max marketplace agents to return (default 10)
+
+    Returns:
+        List of AgentSummary with full schemas (both library and marketplace agents)
+    """
+    agents: list[AgentSummary] = []
+    seen_graph_ids: set[str] = set()
+
+    if search_query:
+        mentioned_uuids = extract_uuids_from_text(search_query)
+        for graph_id in mentioned_uuids:
+            if graph_id == exclude_graph_id:
+                continue
+            agent = await get_library_agent_by_graph_id(user_id, graph_id)
+            agent_graph_id = agent.get("graph_id") if agent else None
+            if agent and agent_graph_id and agent_graph_id not in seen_graph_ids:
+                agents.append(agent)
+                seen_graph_ids.add(agent_graph_id)
+                logger.debug(
+                    f"Found explicitly mentioned agent: {agent.get('name') or 'Unknown'}"
+                )
+
+    if include_library:
+        library_agents = await get_library_agents_for_generation(
+            user_id=user_id,
+            search_query=search_query,
+            exclude_graph_id=exclude_graph_id,
+            max_results=max_library_results,
+        )
+        for agent in library_agents:
+            graph_id = agent.get("graph_id")
+            if graph_id and graph_id not in seen_graph_ids:
+                agents.append(agent)
+                seen_graph_ids.add(graph_id)
+
+    if include_marketplace and search_query:
+        marketplace_agents = await search_marketplace_agents_for_generation(
+            search_query=search_query,
+            max_results=max_marketplace_results,
+        )
+        for agent in marketplace_agents:
+            graph_id = agent.get("graph_id")
+            if graph_id and graph_id not in seen_graph_ids:
+                agents.append(agent)
+                seen_graph_ids.add(graph_id)
+
+    return agents
+
+
+def extract_search_terms_from_steps(
+    decomposition_result: DecompositionResult | dict[str, Any],
+) -> list[str]:
+    """Extract search terms from decomposed instruction steps.
+
+    Analyzes the decomposition result to extract relevant keywords
+    for additional library agent searches.
+
+    Args:
+        decomposition_result: Result from decompose_goal containing steps
+
+    Returns:
+        List of unique search terms extracted from steps
+    """
+    search_terms: list[str] = []
+
+    if decomposition_result.get("type") != "instructions":
+        return search_terms
+
+    steps = decomposition_result.get("steps", [])
+    if not steps:
+        return search_terms
+
+    step_keys: list[str] = ["description", "action", "block_name", "tool", "name"]
+
+    for step in steps:
+        for key in step_keys:
+            value = step.get(key)  # type: ignore[union-attr]
+            if isinstance(value, str) and len(value) > 3:
+                search_terms.append(value)
+
+    seen: set[str] = set()
+    unique_terms: list[str] = []
+    for term in search_terms:
+        term_lower = term.lower()
+        if term_lower not in seen:
+            seen.add(term_lower)
+            unique_terms.append(term)
+
+    return unique_terms
+
+
+async def enrich_library_agents_from_steps(
+    user_id: str,
+    decomposition_result: DecompositionResult | dict[str, Any],
+    existing_agents: list[AgentSummary] | list[dict[str, Any]],
+    exclude_graph_id: str | None = None,
+    include_marketplace: bool = True,
+    max_additional_results: int = 10,
+) -> list[AgentSummary] | list[dict[str, Any]]:
+    """Enrich library agents list with additional searches based on decomposed steps.
+
+    This implements two-phase search: after decomposition, we search for additional
+    relevant agents based on the specific steps identified.
+
+    Args:
+        user_id: The user ID
+        decomposition_result: Result from decompose_goal containing steps
+        existing_agents: Already fetched library agents from initial search
+        exclude_graph_id: Optional graph ID to exclude
+        include_marketplace: Whether to also search marketplace
+        max_additional_results: Max additional agents per search term (default 10)
+
+    Returns:
+        Combined list of library agents (existing + newly discovered)
+    """
+    search_terms = extract_search_terms_from_steps(decomposition_result)
+
+    if not search_terms:
+        return existing_agents
+
+    existing_ids: set[str] = set()
+    existing_names: set[str] = set()
+
+    for agent in existing_agents:
+        agent_name = agent.get("name")
+        if agent_name and isinstance(agent_name, str):
+            existing_names.add(agent_name.lower())
+        graph_id = agent.get("graph_id")  # type: ignore[call-overload]
+        if graph_id and isinstance(graph_id, str):
+            existing_ids.add(graph_id)
+
+    all_agents: list[AgentSummary] | list[dict[str, Any]] = list(existing_agents)
+
+    for term in search_terms[:3]:
+        try:
+            additional_agents = await get_all_relevant_agents_for_generation(
+                user_id=user_id,
+                search_query=term,
+                exclude_graph_id=exclude_graph_id,
+                include_marketplace=include_marketplace,
+                max_library_results=max_additional_results,
+                max_marketplace_results=5,
+            )
+
+            for agent in additional_agents:
+                agent_name = agent.get("name")
+                if not agent_name or not isinstance(agent_name, str):
+                    continue
+                agent_name_lower = agent_name.lower()
+
+                if agent_name_lower in existing_names:
+                    continue
+
+                graph_id = agent.get("graph_id")  # type: ignore[call-overload]
+                if graph_id and graph_id in existing_ids:
+                    continue
+
+                all_agents.append(agent)
+                existing_names.add(agent_name_lower)
+                if graph_id and isinstance(graph_id, str):
+                    existing_ids.add(graph_id)
+
+        except DatabaseError:
+            logger.error(f"Database error searching for agents with term '{term}'")
+            raise
+        except Exception as e:
+            logger.warning(
+                f"Failed to search for additional agents with term '{term}': {e}"
+            )
+
+    logger.debug(
+        f"Enriched library agents: {len(existing_agents)} initial + "
+        f"{len(all_agents) - len(existing_agents)} additional = {len(all_agents)} total"
+    )
+
+    return all_agents
+
+
+async def decompose_goal(
+    description: str,
+    context: str = "",
+    library_agents: list[AgentSummary] | None = None,
+) -> DecompositionResult | None:
     """Break down a goal into steps or return clarifying questions.
 
     Args:
         description: Natural language goal description
         context: Additional context (e.g., answers to previous questions)
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
-        Dict with either:
+        DecompositionResult with either:
         - {"type": "clarifying_questions", "questions": [...]}
         - {"type": "instructions", "steps": [...]}
         Or None on error
@@ -54,29 +531,47 @@ async def decompose_goal(description: str, context: str = "") -> dict[str, Any]
     """
     _check_service_configured()
     logger.info("Calling external Agent Generator service for decompose_goal")
-    return await decompose_goal_external(description, context)
+    result = await decompose_goal_external(
+        description, context, _to_dict_list(library_agents)
+    )
+    return result  # type: ignore[return-value]
 
 
-async def generate_agent(instructions: dict[str, Any]) -> dict[str, Any] | None:
+async def generate_agent(
+    instructions: DecompositionResult | dict[str, Any],
+    library_agents: list[AgentSummary] | list[dict[str, Any]] | None = None,
+    operation_id: str | None = None,
+    task_id: str | None = None,
+) -> dict[str, Any] | None:
     """Generate agent JSON from instructions.
 
     Args:
         instructions: Structured instructions from decompose_goal
+        library_agents: User's library agents available for sub-agent composition
+        operation_id: Operation ID for async processing (enables Redis Streams
+            completion notification)
+        task_id: Task ID for async processing (enables Redis Streams persistence
+            and SSE delivery)
 
     Returns:
-        Agent JSON dict, error dict {"type": "error", ...}, or None on error
+        Agent JSON dict, {"status": "accepted"} for async, error dict {"type": "error", ...}, or None on error
 
     Raises:
         AgentGeneratorNotConfiguredError: If the external service is not configured.
     """
     _check_service_configured()
     logger.info("Calling external Agent Generator service for generate_agent")
-    result = await generate_agent_external(instructions)
+    result = await generate_agent_external(
+        dict(instructions), _to_dict_list(library_agents), operation_id, task_id
+    )
+
+    # Don't modify async response
+    if result and result.get("status") == "accepted":
+        return result
+
     if result:
-        # Check if it's an error response - pass through as-is
         if isinstance(result, dict) and result.get("type") == "error":
             return result
-        # Ensure required fields for successful agent generation
         if "id" not in result:
             result["id"] = str(uuid.uuid4())
         if "version" not in result:
@@ -86,6 +581,12 @@ async def generate_agent(instructions: dict[str, Any]) -> dict[str, Any] | None:
     return result
 
 
+class AgentJsonValidationError(Exception):
+    """Raised when agent JSON is invalid or missing required fields."""
+
+    pass
+
+
 def json_to_graph(agent_json: dict[str, Any]) -> Graph:
     """Convert agent JSON dict to Graph model.
 
@@ -94,25 +595,55 @@ def json_to_graph(agent_json: dict[str, Any]) -> Graph:
 
     Returns:
         Graph ready for saving
+
+    Raises:
+        AgentJsonValidationError: If required fields are missing from nodes or links
     """
     nodes = []
-    for n in agent_json.get("nodes", []):
+    for idx, n in enumerate(agent_json.get("nodes", [])):
+        block_id = n.get("block_id")
+        if not block_id:
+            node_id = n.get("id", f"index_{idx}")
+            raise AgentJsonValidationError(
+                f"Node '{node_id}' is missing required field 'block_id'"
+            )
         node = Node(
             id=n.get("id", str(uuid.uuid4())),
-            block_id=n["block_id"],
+            block_id=block_id,
             input_default=n.get("input_default", {}),
             metadata=n.get("metadata", {}),
         )
         nodes.append(node)
 
     links = []
-    for link_data in agent_json.get("links", []):
+    for idx, link_data in enumerate(agent_json.get("links", [])):
+        source_id = link_data.get("source_id")
+        sink_id = link_data.get("sink_id")
+        source_name = link_data.get("source_name")
+        sink_name = link_data.get("sink_name")
+
+        missing_fields = []
+        if not source_id:
+            missing_fields.append("source_id")
+        if not sink_id:
+            missing_fields.append("sink_id")
+        if not source_name:
+            missing_fields.append("source_name")
+        if not sink_name:
+            missing_fields.append("sink_name")
+
+        if missing_fields:
+            link_id = link_data.get("id", f"index_{idx}")
+            raise AgentJsonValidationError(
+                f"Link '{link_id}' is missing required fields: {', '.join(missing_fields)}"
+            )
+
         link = Link(
             id=link_data.get("id", str(uuid.uuid4())),
-            source_id=link_data["source_id"],
-            sink_id=link_data["sink_id"],
-            source_name=link_data["source_name"],
-            sink_name=link_data["sink_name"],
+            source_id=source_id,
+            sink_id=sink_id,
+            source_name=source_name,
+            sink_name=sink_name,
             is_static=link_data.get("is_static", False),
         )
         links.append(link)
@@ -128,27 +659,6 @@ def json_to_graph(agent_json: dict[str, Any]) -> Graph:
     )
 
 
-def _reassign_node_ids(graph: Graph) -> None:
-    """Reassign all node and link IDs to new UUIDs.
-
-    This is needed when creating a new version to avoid unique constraint violations.
-    """
-    # Create mapping from old node IDs to new UUIDs
-    id_map = {node.id: str(uuid.uuid4()) for node in graph.nodes}
-
-    # Reassign node IDs
-    for node in graph.nodes:
-        node.id = id_map[node.id]
-
-    # Update link references to use new node IDs
-    for link in graph.links:
-        link.id = str(uuid.uuid4())  # Also give links new IDs
-        if link.source_id in id_map:
-            link.source_id = id_map[link.source_id]
-        if link.sink_id in id_map:
-            link.sink_id = id_map[link.sink_id]
-
-
 async def save_agent_to_library(
     agent_json: dict[str, Any], user_id: str, is_update: bool = False
 ) -> tuple[Graph, Any]:
@@ -162,63 +672,21 @@ async def save_agent_to_library(
     Returns:
         Tuple of (created Graph, LibraryAgent)
     """
-    from backend.data.graph import get_graph_all_versions
-
     graph = json_to_graph(agent_json)
-
     if is_update:
-        # For updates, keep the same graph ID but increment version
-        # and reassign node/link IDs to avoid conflicts
-        if graph.id:
-            existing_versions = await get_graph_all_versions(graph.id, user_id)
-            if existing_versions:
-                latest_version = max(v.version for v in existing_versions)
-                graph.version = latest_version + 1
-                # Reassign node IDs (but keep graph ID the same)
-                _reassign_node_ids(graph)
-                logger.info(f"Updating agent {graph.id} to version {graph.version}")
-    else:
-        # For new agents, always generate a fresh UUID to avoid collisions
-        graph.id = str(uuid.uuid4())
-        graph.version = 1
-        # Reassign all node IDs as well
-        _reassign_node_ids(graph)
-        logger.info(f"Creating new agent with ID {graph.id}")
-
-    # Save to database
-    created_graph = await create_graph(graph, user_id)
-
-    # Add to user's library (or update existing library agent)
-    library_agents = await library_db.create_library_agent(
-        graph=created_graph,
-        user_id=user_id,
-        sensitive_action_safe_mode=True,
-        create_library_agents_for_sub_graphs=False,
-    )
-
-    return created_graph, library_agents[0]
+        return await library_db.update_graph_in_library(graph, user_id)
+    return await library_db.create_graph_in_library(graph, user_id)
 
 
-async def get_agent_as_json(
-    graph_id: str, user_id: str | None
-) -> dict[str, Any] | None:
-    """Fetch an agent and convert to JSON format for editing.
+def graph_to_json(graph: Graph) -> dict[str, Any]:
+    """Convert a Graph object to JSON format for the agent generator.
 
     Args:
-        graph_id: Graph ID or library agent ID
-        user_id: User ID
+        graph: Graph object to convert
 
     Returns:
-        Agent as JSON dict or None if not found
+        Agent as JSON dict
     """
-    from backend.data.graph import get_graph
-
-    # Try to get the graph (version=None gets the active version)
-    graph = await get_graph(graph_id, version=None, user_id=user_id)
-    if not graph:
-        return None
-
-    # Convert to JSON format
     nodes = []
     for node in graph.nodes:
         nodes.append(
@@ -255,8 +723,41 @@ async def get_agent_as_json(
     }
 
 
+async def get_agent_as_json(
+    agent_id: str, user_id: str | None
+) -> dict[str, Any] | None:
+    """Fetch an agent and convert to JSON format for editing.
+
+    Args:
+        agent_id: Graph ID or library agent ID
+        user_id: User ID
+
+    Returns:
+        Agent as JSON dict or None if not found
+    """
+    graph = await get_graph(agent_id, version=None, user_id=user_id)
+
+    if not graph and user_id:
+        try:
+            library_agent = await library_db.get_library_agent(agent_id, user_id)
+            graph = await get_graph(
+                library_agent.graph_id, version=None, user_id=user_id
+            )
+        except NotFoundError:
+            pass
+
+    if not graph:
+        return None
+
+    return graph_to_json(graph)
+
+
 async def generate_agent_patch(
-    update_request: str, current_agent: dict[str, Any]
+    update_request: str,
+    current_agent: dict[str, Any],
+    library_agents: list[AgentSummary] | None = None,
+    operation_id: str | None = None,
+    task_id: str | None = None,
 ) -> dict[str, Any] | None:
     """Update an existing agent using natural language.
 
@@ -268,14 +769,57 @@ async def generate_agent_patch(
     Args:
         update_request: Natural language description of changes
         current_agent: Current agent JSON
+        library_agents: User's library agents available for sub-agent composition
+        operation_id: Operation ID for async processing (enables Redis Streams callback)
+        task_id: Task ID for async processing (enables Redis Streams callback)
 
     Returns:
         Updated agent JSON, clarifying questions dict {"type": "clarifying_questions", ...},
-        error dict {"type": "error", ...}, or None on unexpected error
+        {"status": "accepted"} for async, error dict {"type": "error", ...}, or None on error
 
     Raises:
         AgentGeneratorNotConfiguredError: If the external service is not configured.
     """
     _check_service_configured()
     logger.info("Calling external Agent Generator service for generate_agent_patch")
-    return await generate_agent_patch_external(update_request, current_agent)
+    return await generate_agent_patch_external(
+        update_request,
+        current_agent,
+        _to_dict_list(library_agents),
+        operation_id,
+        task_id,
+    )
+
+
+async def customize_template(
+    template_agent: dict[str, Any],
+    modification_request: str,
+    context: str = "",
+) -> dict[str, Any] | None:
+    """Customize a template/marketplace agent using natural language.
+
+    This is used when users want to modify a template or marketplace agent
+    to fit their specific needs before adding it to their library.
+
+    The external Agent Generator service handles:
+    - Understanding the modification request
+    - Applying changes to the template
+    - Fixing and validating the result
+
+    Args:
+        template_agent: The template agent JSON to customize
+        modification_request: Natural language description of customizations
+        context: Additional context (e.g., answers to previous questions)
+
+    Returns:
+        Customized agent JSON, clarifying questions dict {"type": "clarifying_questions", ...},
+        error dict {"type": "error", ...}, or None on unexpected error
+
+    Raises:
+        AgentGeneratorNotConfiguredError: If the external service is not configured.
+    """
+    _check_service_configured()
+    logger.info("Calling external Agent Generator service for customize_template")
+    return await customize_template_external(
+        template_agent, modification_request, context
+    )
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/errors.py b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/errors.py
index bf71a95df9..282d8cf9aa 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/errors.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/errors.py
@@ -1,11 +1,43 @@
 """Error handling utilities for agent generator."""
 
+import re
+
+
+def _sanitize_error_details(details: str) -> str:
+    """Sanitize error details to remove sensitive information.
+
+    Strips common patterns that could expose internal system info:
+    - File paths (Unix and Windows)
+    - Database connection strings
+    - URLs with credentials
+    - Stack trace internals
+
+    Args:
+        details: Raw error details string
+
+    Returns:
+        Sanitized error details safe for user display
+    """
+    sanitized = re.sub(
+        r"/[a-zA-Z0-9_./\-]+\.(py|js|ts|json|yaml|yml)", "[path]", details
+    )
+    sanitized = re.sub(r"[A-Z]:\\[a-zA-Z0-9_\\.\\-]+", "[path]", sanitized)
+    sanitized = re.sub(
+        r"(postgres|mysql|mongodb|redis)://[^\s]+", "[database_url]", sanitized
+    )
+    sanitized = re.sub(r"https?://[^:]+:[^@]+@[^\s]+", "[url]", sanitized)
+    sanitized = re.sub(r", line \d+", "", sanitized)
+    sanitized = re.sub(r'File "[^"]+",?', "", sanitized)
+
+    return sanitized.strip()
+
 
 def get_user_message_for_error(
     error_type: str,
     operation: str = "process the request",
     llm_parse_message: str | None = None,
     validation_message: str | None = None,
+    error_details: str | None = None,
 ) -> str:
     """Get a user-friendly error message based on error type.
 
@@ -19,25 +51,45 @@ def get_user_message_for_error(
             message (e.g., "analyze the goal", "generate the agent")
         llm_parse_message: Custom message for llm_parse_error type
         validation_message: Custom message for validation_error type
+        error_details: Optional additional details about the error
 
     Returns:
         User-friendly error message suitable for display to the user
     """
+    base_message = ""
+
     if error_type == "llm_parse_error":
-        return (
+        base_message = (
             llm_parse_message
             or "The AI had trouble processing this request. Please try again."
         )
     elif error_type == "validation_error":
-        return (
+        base_message = (
             validation_message
-            or "The request failed validation. Please try rephrasing."
+            or "The generated agent failed validation. "
+            "This usually happens when the agent structure doesn't match "
+            "what the platform expects. Please try simplifying your goal "
+            "or breaking it into smaller parts."
         )
     elif error_type == "patch_error":
-        return "Failed to apply the changes. Please try a different approach."
+        base_message = (
+            "Failed to apply the changes. The modification couldn't be "
+            "validated. Please try a different approach or simplify the change."
+        )
     elif error_type in ("timeout", "llm_timeout"):
-        return "The request took too long. Please try again."
+        base_message = (
+            "The request took too long to process. This can happen with "
+            "complex agents. Please try again or simplify your goal."
+        )
     elif error_type in ("rate_limit", "llm_rate_limit"):
-        return "The service is currently busy. Please try again in a moment."
+        base_message = "The service is currently busy. Please try again in a moment."
     else:
-        return f"Failed to {operation}. Please try again."
+        base_message = f"Failed to {operation}. Please try again."
+
+    if error_details:
+        details = _sanitize_error_details(error_details)
+        if len(details) > 200:
+            details = details[:200] + "..."
+        base_message += f"\n\nTechnical details: {details}"
+
+    return base_message
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/service.py b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/service.py
index 1df1faaaef..62411b4e1b 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/service.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/service.py
@@ -117,13 +117,16 @@ def _get_client() -> httpx.AsyncClient:
 
 
 async def decompose_goal_external(
-    description: str, context: str = ""
+    description: str,
+    context: str = "",
+    library_agents: list[dict[str, Any]] | None = None,
 ) -> dict[str, Any] | None:
     """Call the external service to decompose a goal.
 
     Args:
         description: Natural language goal description
         context: Additional context (e.g., answers to previous questions)
+        library_agents: User's library agents available for sub-agent composition
 
     Returns:
         Dict with either:
@@ -136,11 +139,12 @@ async def decompose_goal_external(
     """
     client = _get_client()
 
-    # Build the request payload
-    payload: dict[str, Any] = {"description": description}
     if context:
-        # The external service uses user_instruction for additional context
-        payload["user_instruction"] = context
+        description = f"{description}\n\nAdditional context from user:\n{context}"
+
+    payload: dict[str, Any] = {"description": description}
+    if library_agents:
+        payload["library_agents"] = library_agents
 
     try:
         response = await client.post("/api/decompose-description", json=payload)
@@ -207,21 +211,46 @@ async def decompose_goal_external(
 
 async def generate_agent_external(
     instructions: dict[str, Any],
+    library_agents: list[dict[str, Any]] | None = None,
+    operation_id: str | None = None,
+    task_id: str | None = None,
 ) -> dict[str, Any] | None:
     """Call the external service to generate an agent from instructions.
 
     Args:
         instructions: Structured instructions from decompose_goal
+        library_agents: User's library agents available for sub-agent composition
+        operation_id: Operation ID for async processing (enables Redis Streams callback)
+        task_id: Task ID for async processing (enables Redis Streams callback)
 
     Returns:
-        Agent JSON dict on success, or error dict {"type": "error", ...} on error
+        Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
     """
     client = _get_client()
 
+    # Build request payload
+    payload: dict[str, Any] = {"instructions": instructions}
+    if library_agents:
+        payload["library_agents"] = library_agents
+    if operation_id and task_id:
+        payload["operation_id"] = operation_id
+        payload["task_id"] = task_id
+
     try:
-        response = await client.post(
-            "/api/generate-agent", json={"instructions": instructions}
-        )
+        response = await client.post("/api/generate-agent", json=payload)
+
+        # Handle 202 Accepted for async processing
+        if response.status_code == 202:
+            logger.info(
+                f"Agent Generator accepted async request "
+                f"(operation_id={operation_id}, task_id={task_id})"
+            )
+            return {
+                "status": "accepted",
+                "operation_id": operation_id,
+                "task_id": task_id,
+            }
+
         response.raise_for_status()
         data = response.json()
 
@@ -229,8 +258,7 @@ async def generate_agent_external(
             error_msg = data.get("error", "Unknown error from Agent Generator")
             error_type = data.get("error_type", "unknown")
             logger.error(
-                f"Agent Generator generation failed: {error_msg} "
-                f"(type: {error_type})"
+                f"Agent Generator generation failed: {error_msg} (type: {error_type})"
             )
             return _create_error_response(error_msg, error_type)
 
@@ -251,27 +279,52 @@ async def generate_agent_external(
 
 
 async def generate_agent_patch_external(
-    update_request: str, current_agent: dict[str, Any]
+    update_request: str,
+    current_agent: dict[str, Any],
+    library_agents: list[dict[str, Any]] | None = None,
+    operation_id: str | None = None,
+    task_id: str | None = None,
 ) -> dict[str, Any] | None:
     """Call the external service to generate a patch for an existing agent.
 
     Args:
         update_request: Natural language description of changes
         current_agent: Current agent JSON
+        library_agents: User's library agents available for sub-agent composition
+        operation_id: Operation ID for async processing (enables Redis Streams callback)
+        task_id: Task ID for async processing (enables Redis Streams callback)
 
     Returns:
-        Updated agent JSON, clarifying questions dict, or error dict on error
+        Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
     """
     client = _get_client()
 
+    # Build request payload
+    payload: dict[str, Any] = {
+        "update_request": update_request,
+        "current_agent_json": current_agent,
+    }
+    if library_agents:
+        payload["library_agents"] = library_agents
+    if operation_id and task_id:
+        payload["operation_id"] = operation_id
+        payload["task_id"] = task_id
+
     try:
-        response = await client.post(
-            "/api/update-agent",
-            json={
-                "update_request": update_request,
-                "current_agent_json": current_agent,
-            },
-        )
+        response = await client.post("/api/update-agent", json=payload)
+
+        # Handle 202 Accepted for async processing
+        if response.status_code == 202:
+            logger.info(
+                f"Agent Generator accepted async update request "
+                f"(operation_id={operation_id}, task_id={task_id})"
+            )
+            return {
+                "status": "accepted",
+                "operation_id": operation_id,
+                "task_id": task_id,
+            }
+
         response.raise_for_status()
         data = response.json()
 
@@ -315,6 +368,77 @@ async def generate_agent_patch_external(
         return _create_error_response(error_msg, "unexpected_error")
 
 
+async def customize_template_external(
+    template_agent: dict[str, Any],
+    modification_request: str,
+    context: str = "",
+) -> dict[str, Any] | None:
+    """Call the external service to customize a template/marketplace agent.
+
+    Args:
+        template_agent: The template agent JSON to customize
+        modification_request: Natural language description of customizations
+        context: Additional context (e.g., answers to previous questions)
+
+    Returns:
+        Customized agent JSON, clarifying questions dict, or error dict on error
+    """
+    client = _get_client()
+
+    request = modification_request
+    if context:
+        request = f"{modification_request}\n\nAdditional context from user:\n{context}"
+
+    payload: dict[str, Any] = {
+        "template_agent_json": template_agent,
+        "modification_request": request,
+    }
+
+    try:
+        response = await client.post("/api/template-modification", json=payload)
+        response.raise_for_status()
+        data = response.json()
+
+        if not data.get("success"):
+            error_msg = data.get("error", "Unknown error from Agent Generator")
+            error_type = data.get("error_type", "unknown")
+            logger.error(
+                f"Agent Generator template customization failed: {error_msg} "
+                f"(type: {error_type})"
+            )
+            return _create_error_response(error_msg, error_type)
+
+        # Check if it's clarifying questions
+        if data.get("type") == "clarifying_questions":
+            return {
+                "type": "clarifying_questions",
+                "questions": data.get("questions", []),
+            }
+
+        # Check if it's an error passed through
+        if data.get("type") == "error":
+            return _create_error_response(
+                data.get("error", "Unknown error"),
+                data.get("error_type", "unknown"),
+            )
+
+        # Otherwise return the customized agent JSON
+        return data.get("agent_json")
+
+    except httpx.HTTPStatusError as e:
+        error_type, error_msg = _classify_http_error(e)
+        logger.error(error_msg)
+        return _create_error_response(error_msg, error_type)
+    except httpx.RequestError as e:
+        error_type, error_msg = _classify_request_error(e)
+        logger.error(error_msg)
+        return _create_error_response(error_msg, error_type)
+    except Exception as e:
+        error_msg = f"Unexpected error calling Agent Generator: {e}"
+        logger.error(error_msg)
+        return _create_error_response(error_msg, "unexpected_error")
+
+
 async def get_blocks_external() -> list[dict[str, Any]] | None:
     """Get available blocks from the external service.
 
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/agent_search.py b/autogpt_platform/backend/backend/api/features/chat/tools/agent_search.py
index 5fa74ba04e..61cdba1ef9 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/agent_search.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/agent_search.py
@@ -1,6 +1,7 @@
 """Shared agent search functionality for find_agent and find_library_agent tools."""
 
 import logging
+import re
 from typing import Literal
 
 from backend.api.features.library import db as library_db
@@ -19,6 +20,85 @@ logger = logging.getLogger(__name__)
 
 SearchSource = Literal["marketplace", "library"]
 
+_UUID_PATTERN = re.compile(
+    r"^[a-f0-9]{8}-[a-f0-9]{4}-4[a-f0-9]{3}-[89ab][a-f0-9]{3}-[a-f0-9]{12}$",
+    re.IGNORECASE,
+)
+
+
+def _is_uuid(text: str) -> bool:
+    """Check if text is a valid UUID v4."""
+    return bool(_UUID_PATTERN.match(text.strip()))
+
+
+async def _get_library_agent_by_id(user_id: str, agent_id: str) -> AgentInfo | None:
+    """Fetch a library agent by ID (library agent ID or graph_id).
+
+    Tries multiple lookup strategies:
+    1. First by graph_id (AgentGraph primary key)
+    2. Then by library agent ID (LibraryAgent primary key)
+
+    Args:
+        user_id: The user ID
+        agent_id: The ID to look up (can be graph_id or library agent ID)
+
+    Returns:
+        AgentInfo if found, None otherwise
+    """
+    try:
+        agent = await library_db.get_library_agent_by_graph_id(user_id, agent_id)
+        if agent:
+            logger.debug(f"Found library agent by graph_id: {agent.name}")
+            return AgentInfo(
+                id=agent.id,
+                name=agent.name,
+                description=agent.description or "",
+                source="library",
+                in_library=True,
+                creator=agent.creator_name,
+                status=agent.status.value,
+                can_access_graph=agent.can_access_graph,
+                has_external_trigger=agent.has_external_trigger,
+                new_output=agent.new_output,
+                graph_id=agent.graph_id,
+            )
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.warning(
+            f"Could not fetch library agent by graph_id {agent_id}: {e}",
+            exc_info=True,
+        )
+
+    try:
+        agent = await library_db.get_library_agent(agent_id, user_id)
+        if agent:
+            logger.debug(f"Found library agent by library_id: {agent.name}")
+            return AgentInfo(
+                id=agent.id,
+                name=agent.name,
+                description=agent.description or "",
+                source="library",
+                in_library=True,
+                creator=agent.creator_name,
+                status=agent.status.value,
+                can_access_graph=agent.can_access_graph,
+                has_external_trigger=agent.has_external_trigger,
+                new_output=agent.new_output,
+                graph_id=agent.graph_id,
+            )
+    except NotFoundError:
+        logger.debug(f"Library agent not found by library_id: {agent_id}")
+    except DatabaseError:
+        raise
+    except Exception as e:
+        logger.warning(
+            f"Could not fetch library agent by library_id {agent_id}: {e}",
+            exc_info=True,
+        )
+
+    return None
+
 
 async def search_agents(
     query: str,
@@ -69,29 +149,37 @@ async def search_agents(
                         is_featured=False,
                     )
                 )
-        else:  # library
-            logger.info(f"Searching user library for: {query}")
-            results = await library_db.list_library_agents(
-                user_id=user_id,  # type: ignore[arg-type]
-                search_term=query,
-                page_size=10,
-            )
-            for agent in results.agents:
-                agents.append(
-                    AgentInfo(
-                        id=agent.id,
-                        name=agent.name,
-                        description=agent.description or "",
-                        source="library",
-                        in_library=True,
-                        creator=agent.creator_name,
-                        status=agent.status.value,
-                        can_access_graph=agent.can_access_graph,
-                        has_external_trigger=agent.has_external_trigger,
-                        new_output=agent.new_output,
-                        graph_id=agent.graph_id,
-                    )
+        else:
+            if _is_uuid(query):
+                logger.info(f"Query looks like UUID, trying direct lookup: {query}")
+                agent = await _get_library_agent_by_id(user_id, query)  # type: ignore[arg-type]
+                if agent:
+                    agents.append(agent)
+                    logger.info(f"Found agent by direct ID lookup: {agent.name}")
+
+            if not agents:
+                logger.info(f"Searching user library for: {query}")
+                results = await library_db.list_library_agents(
+                    user_id=user_id,  # type: ignore[arg-type]
+                    search_term=query,
+                    page_size=10,
                 )
+                for agent in results.agents:
+                    agents.append(
+                        AgentInfo(
+                            id=agent.id,
+                            name=agent.name,
+                            description=agent.description or "",
+                            source="library",
+                            in_library=True,
+                            creator=agent.creator_name,
+                            status=agent.status.value,
+                            can_access_graph=agent.can_access_graph,
+                            has_external_trigger=agent.has_external_trigger,
+                            new_output=agent.new_output,
+                            graph_id=agent.graph_id,
+                        )
+                    )
         logger.info(f"Found {len(agents)} agents in {source}")
     except NotFoundError:
         pass
@@ -118,9 +206,9 @@ async def search_agents(
             ]
         )
         no_results_msg = (
-            f"No agents found matching '{query}'. Try different keywords or browse the marketplace."
+            f"No agents found matching '{query}'. Let the user know they can try different keywords or browse the marketplace. Also let them know you can create a custom agent for them based on their needs."
             if source == "marketplace"
-            else f"No agents matching '{query}' found in your library."
+            else f"No agents matching '{query}' found in your library. Let the user know you can create a custom agent for them based on their needs."
         )
         return NoResultsResponse(
             message=no_results_msg, session_id=session_id, suggestions=suggestions
@@ -136,10 +224,10 @@ async def search_agents(
     message = (
         "Now you have found some options for the user to choose from. "
         "You can add a link to a recommended agent at: /marketplace/agent/agent_id "
-        "Please ask the user if they would like to use any of these agents."
+        "Please ask the user if they would like to use any of these agents. Let the user know we can create a custom agent for them based on their needs."
         if source == "marketplace"
         else "Found agents in the user's library. You can provide a link to view an agent at: "
-        "/library/agents/{agent_id}. Use agent_output to get execution results, or run_agent to execute."
+        "/library/agents/{agent_id}. Use agent_output to get execution results, or run_agent to execute. Let the user know we can create a custom agent for them based on their needs."
     )
 
     return AgentsFoundResponse(
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py b/autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py
index 74011c7e95..7333851a5b 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py
@@ -8,7 +8,9 @@ from backend.api.features.chat.model import ChatSession
 from .agent_generator import (
     AgentGeneratorNotConfiguredError,
     decompose_goal,
+    enrich_library_agents_from_steps,
     generate_agent,
+    get_all_relevant_agents_for_generation,
     get_user_message_for_error,
     save_agent_to_library,
 )
@@ -16,6 +18,7 @@ from .base import BaseTool
 from .models import (
     AgentPreviewResponse,
     AgentSavedResponse,
+    AsyncProcessingResponse,
     ClarificationNeededResponse,
     ClarifyingQuestion,
     ErrorResponse,
@@ -96,6 +99,10 @@ class CreateAgentTool(BaseTool):
         save = kwargs.get("save", True)
         session_id = session.session_id if session else None
 
+        # Extract async processing params (passed by long-running tool handler)
+        operation_id = kwargs.get("_operation_id")
+        task_id = kwargs.get("_task_id")
+
         if not description:
             return ErrorResponse(
                 message="Please provide a description of what the agent should do.",
@@ -103,9 +110,24 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Step 1: Decompose goal into steps
+        library_agents = None
+        if user_id:
+            try:
+                library_agents = await get_all_relevant_agents_for_generation(
+                    user_id=user_id,
+                    search_query=description,
+                    include_marketplace=True,
+                )
+                logger.debug(
+                    f"Found {len(library_agents)} relevant agents for sub-agent composition"
+                )
+            except Exception as e:
+                logger.warning(f"Failed to fetch library agents: {e}")
+
         try:
-            decomposition_result = await decompose_goal(description, context)
+            decomposition_result = await decompose_goal(
+                description, context, library_agents
+            )
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
                 message=(
@@ -124,7 +146,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if the result is an error from the external service
         if decomposition_result.get("type") == "error":
             error_msg = decomposition_result.get("error", "Unknown error")
             error_type = decomposition_result.get("error_type", "unknown")
@@ -144,7 +165,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if LLM returned clarifying questions
         if decomposition_result.get("type") == "clarifying_questions":
             questions = decomposition_result.get("questions", [])
             return ClarificationNeededResponse(
@@ -163,7 +183,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check for unachievable/vague goals
         if decomposition_result.get("type") == "unachievable_goal":
             suggested = decomposition_result.get("suggested_goal", "")
             reason = decomposition_result.get("reason", "")
@@ -190,9 +209,27 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Step 2: Generate agent JSON (external service handles fixing and validation)
+        if user_id and library_agents is not None:
+            try:
+                library_agents = await enrich_library_agents_from_steps(
+                    user_id=user_id,
+                    decomposition_result=decomposition_result,
+                    existing_agents=library_agents,
+                    include_marketplace=True,
+                )
+                logger.debug(
+                    f"After enrichment: {len(library_agents)} total agents for sub-agent composition"
+                )
+            except Exception as e:
+                logger.warning(f"Failed to enrich library agents from steps: {e}")
+
         try:
-            agent_json = await generate_agent(decomposition_result)
+            agent_json = await generate_agent(
+                decomposition_result,
+                library_agents,
+                operation_id=operation_id,
+                task_id=task_id,
+            )
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
                 message=(
@@ -211,7 +248,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if the result is an error from the external service
         if isinstance(agent_json, dict) and agent_json.get("type") == "error":
             error_msg = agent_json.get("error", "Unknown error")
             error_type = agent_json.get("error_type", "unknown")
@@ -219,7 +255,12 @@ class CreateAgentTool(BaseTool):
                 error_type,
                 operation="generate the agent",
                 llm_parse_message="The AI had trouble generating the agent. Please try again or simplify your goal.",
-                validation_message="The generated agent failed validation. Please try rephrasing your goal.",
+                validation_message=(
+                    "I wasn't able to create a valid agent for this request. "
+                    "The generated workflow had some structural issues. "
+                    "Please try simplifying your goal or breaking it into smaller steps."
+                ),
+                error_details=error_msg,
             )
             return ErrorResponse(
                 message=user_message,
@@ -232,12 +273,24 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
+        # Check if Agent Generator accepted for async processing
+        if agent_json.get("status") == "accepted":
+            logger.info(
+                f"Agent generation delegated to async processing "
+                f"(operation_id={operation_id}, task_id={task_id})"
+            )
+            return AsyncProcessingResponse(
+                message="Agent generation started. You'll be notified when it's complete.",
+                operation_id=operation_id,
+                task_id=task_id,
+                session_id=session_id,
+            )
+
         agent_name = agent_json.get("name", "Generated Agent")
         agent_description = agent_json.get("description", "")
         node_count = len(agent_json.get("nodes", []))
         link_count = len(agent_json.get("links", []))
 
-        # Step 3: Preview or save
         if not save:
             return AgentPreviewResponse(
                 message=(
@@ -252,7 +305,6 @@ class CreateAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Save to library
         if not user_id:
             return ErrorResponse(
                 message="You must be logged in to save agents.",
@@ -270,7 +322,7 @@ class CreateAgentTool(BaseTool):
                 agent_id=created_graph.id,
                 agent_name=created_graph.name,
                 library_agent_id=library_agent.id,
-                library_agent_link=f"/library/{library_agent.id}",
+                library_agent_link=f"/library/agents/{library_agent.id}",
                 agent_page_link=f"/build?flowID={created_graph.id}",
                 session_id=session_id,
             )
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py b/autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py
new file mode 100644
index 0000000000..c0568bd936
--- /dev/null
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py
@@ -0,0 +1,337 @@
+"""CustomizeAgentTool - Customizes marketplace/template agents using natural language."""
+
+import logging
+from typing import Any
+
+from backend.api.features.chat.model import ChatSession
+from backend.api.features.store import db as store_db
+from backend.api.features.store.exceptions import AgentNotFoundError
+
+from .agent_generator import (
+    AgentGeneratorNotConfiguredError,
+    customize_template,
+    get_user_message_for_error,
+    graph_to_json,
+    save_agent_to_library,
+)
+from .base import BaseTool
+from .models import (
+    AgentPreviewResponse,
+    AgentSavedResponse,
+    ClarificationNeededResponse,
+    ClarifyingQuestion,
+    ErrorResponse,
+    ToolResponseBase,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class CustomizeAgentTool(BaseTool):
+    """Tool for customizing marketplace/template agents using natural language."""
+
+    @property
+    def name(self) -> str:
+        return "customize_agent"
+
+    @property
+    def description(self) -> str:
+        return (
+            "Customize a marketplace or template agent using natural language. "
+            "Takes an existing agent from the marketplace and modifies it based on "
+            "the user's requirements before adding to their library."
+        )
+
+    @property
+    def requires_auth(self) -> bool:
+        return True
+
+    @property
+    def is_long_running(self) -> bool:
+        return True
+
+    @property
+    def parameters(self) -> dict[str, Any]:
+        return {
+            "type": "object",
+            "properties": {
+                "agent_id": {
+                    "type": "string",
+                    "description": (
+                        "The marketplace agent ID in format 'creator/slug' "
+                        "(e.g., 'autogpt/newsletter-writer'). "
+                        "Get this from find_agent results."
+                    ),
+                },
+                "modifications": {
+                    "type": "string",
+                    "description": (
+                        "Natural language description of how to customize the agent. "
+                        "Be specific about what changes you want to make."
+                    ),
+                },
+                "context": {
+                    "type": "string",
+                    "description": (
+                        "Additional context or answers to previous clarifying questions."
+                    ),
+                },
+                "save": {
+                    "type": "boolean",
+                    "description": (
+                        "Whether to save the customized agent to the user's library. "
+                        "Default is true. Set to false for preview only."
+                    ),
+                    "default": True,
+                },
+            },
+            "required": ["agent_id", "modifications"],
+        }
+
+    async def _execute(
+        self,
+        user_id: str | None,
+        session: ChatSession,
+        **kwargs,
+    ) -> ToolResponseBase:
+        """Execute the customize_agent tool.
+
+        Flow:
+        1. Parse the agent ID to get creator/slug
+        2. Fetch the template agent from the marketplace
+        3. Call customize_template with the modification request
+        4. Preview or save based on the save parameter
+        """
+        agent_id = kwargs.get("agent_id", "").strip()
+        modifications = kwargs.get("modifications", "").strip()
+        context = kwargs.get("context", "")
+        save = kwargs.get("save", True)
+        session_id = session.session_id if session else None
+
+        if not agent_id:
+            return ErrorResponse(
+                message="Please provide the marketplace agent ID (e.g., 'creator/agent-name').",
+                error="missing_agent_id",
+                session_id=session_id,
+            )
+
+        if not modifications:
+            return ErrorResponse(
+                message="Please describe how you want to customize this agent.",
+                error="missing_modifications",
+                session_id=session_id,
+            )
+
+        # Parse agent_id in format "creator/slug"
+        parts = [p.strip() for p in agent_id.split("/")]
+        if len(parts) != 2 or not parts[0] or not parts[1]:
+            return ErrorResponse(
+                message=(
+                    f"Invalid agent ID format: '{agent_id}'. "
+                    "Expected format is 'creator/agent-name' "
+                    "(e.g., 'autogpt/newsletter-writer')."
+                ),
+                error="invalid_agent_id_format",
+                session_id=session_id,
+            )
+
+        creator_username, agent_slug = parts
+
+        # Fetch the marketplace agent details
+        try:
+            agent_details = await store_db.get_store_agent_details(
+                username=creator_username, agent_name=agent_slug
+            )
+        except AgentNotFoundError:
+            return ErrorResponse(
+                message=(
+                    f"Could not find marketplace agent '{agent_id}'. "
+                    "Please check the agent ID and try again."
+                ),
+                error="agent_not_found",
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.error(f"Error fetching marketplace agent {agent_id}: {e}")
+            return ErrorResponse(
+                message="Failed to fetch the marketplace agent. Please try again.",
+                error="fetch_error",
+                session_id=session_id,
+            )
+
+        if not agent_details.store_listing_version_id:
+            return ErrorResponse(
+                message=(
+                    f"The agent '{agent_id}' does not have an available version. "
+                    "Please try a different agent."
+                ),
+                error="no_version_available",
+                session_id=session_id,
+            )
+
+        # Get the full agent graph
+        try:
+            graph = await store_db.get_agent(agent_details.store_listing_version_id)
+            template_agent = graph_to_json(graph)
+        except Exception as e:
+            logger.error(f"Error fetching agent graph for {agent_id}: {e}")
+            return ErrorResponse(
+                message="Failed to fetch the agent configuration. Please try again.",
+                error="graph_fetch_error",
+                session_id=session_id,
+            )
+
+        # Call customize_template
+        try:
+            result = await customize_template(
+                template_agent=template_agent,
+                modification_request=modifications,
+                context=context,
+            )
+        except AgentGeneratorNotConfiguredError:
+            return ErrorResponse(
+                message=(
+                    "Agent customization is not available. "
+                    "The Agent Generator service is not configured."
+                ),
+                error="service_not_configured",
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.error(f"Error calling customize_template for {agent_id}: {e}")
+            return ErrorResponse(
+                message=(
+                    "Failed to customize the agent due to a service error. "
+                    "Please try again."
+                ),
+                error="customization_service_error",
+                session_id=session_id,
+            )
+
+        if result is None:
+            return ErrorResponse(
+                message=(
+                    "Failed to customize the agent. "
+                    "The agent generation service may be unavailable or timed out. "
+                    "Please try again."
+                ),
+                error="customization_failed",
+                session_id=session_id,
+            )
+
+        # Handle error response
+        if isinstance(result, dict) and result.get("type") == "error":
+            error_msg = result.get("error", "Unknown error")
+            error_type = result.get("error_type", "unknown")
+            user_message = get_user_message_for_error(
+                error_type,
+                operation="customize the agent",
+                llm_parse_message=(
+                    "The AI had trouble customizing the agent. "
+                    "Please try again or simplify your request."
+                ),
+                validation_message=(
+                    "The customized agent failed validation. "
+                    "Please try rephrasing your request."
+                ),
+                error_details=error_msg,
+            )
+            return ErrorResponse(
+                message=user_message,
+                error=f"customization_failed:{error_type}",
+                session_id=session_id,
+            )
+
+        # Handle clarifying questions
+        if isinstance(result, dict) and result.get("type") == "clarifying_questions":
+            questions = result.get("questions") or []
+            if not isinstance(questions, list):
+                logger.error(
+                    f"Unexpected clarifying questions format: {type(questions)}"
+                )
+                questions = []
+            return ClarificationNeededResponse(
+                message=(
+                    "I need some more information to customize this agent. "
+                    "Please answer the following questions:"
+                ),
+                questions=[
+                    ClarifyingQuestion(
+                        question=q.get("question", ""),
+                        keyword=q.get("keyword", ""),
+                        example=q.get("example"),
+                    )
+                    for q in questions
+                    if isinstance(q, dict)
+                ],
+                session_id=session_id,
+            )
+
+        # Result should be the customized agent JSON
+        if not isinstance(result, dict):
+            logger.error(f"Unexpected customize_template response type: {type(result)}")
+            return ErrorResponse(
+                message="Failed to customize the agent due to an unexpected response.",
+                error="unexpected_response_type",
+                session_id=session_id,
+            )
+
+        customized_agent = result
+
+        agent_name = customized_agent.get(
+            "name", f"Customized {agent_details.agent_name}"
+        )
+        agent_description = customized_agent.get("description", "")
+        nodes = customized_agent.get("nodes")
+        links = customized_agent.get("links")
+        node_count = len(nodes) if isinstance(nodes, list) else 0
+        link_count = len(links) if isinstance(links, list) else 0
+
+        if not save:
+            return AgentPreviewResponse(
+                message=(
+                    f"I've customized the agent '{agent_details.agent_name}'. "
+                    f"The customized agent has {node_count} blocks. "
+                    f"Review it and call customize_agent with save=true to save it."
+                ),
+                agent_json=customized_agent,
+                agent_name=agent_name,
+                description=agent_description,
+                node_count=node_count,
+                link_count=link_count,
+                session_id=session_id,
+            )
+
+        if not user_id:
+            return ErrorResponse(
+                message="You must be logged in to save agents.",
+                error="auth_required",
+                session_id=session_id,
+            )
+
+        # Save to user's library
+        try:
+            created_graph, library_agent = await save_agent_to_library(
+                customized_agent, user_id, is_update=False
+            )
+
+            return AgentSavedResponse(
+                message=(
+                    f"Customized agent '{created_graph.name}' "
+                    f"(based on '{agent_details.agent_name}') "
+                    f"has been saved to your library!"
+                ),
+                agent_id=created_graph.id,
+                agent_name=created_graph.name,
+                library_agent_id=library_agent.id,
+                library_agent_link=f"/library/agents/{library_agent.id}",
+                agent_page_link=f"/build?flowID={created_graph.id}",
+                session_id=session_id,
+            )
+        except Exception as e:
+            logger.error(f"Error saving customized agent: {e}")
+            return ErrorResponse(
+                message="Failed to save the customized agent. Please try again.",
+                error="save_failed",
+                session_id=session_id,
+            )
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py b/autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py
index ee8eee53ce..3ae56407a7 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py
@@ -9,6 +9,7 @@ from .agent_generator import (
     AgentGeneratorNotConfiguredError,
     generate_agent_patch,
     get_agent_as_json,
+    get_all_relevant_agents_for_generation,
     get_user_message_for_error,
     save_agent_to_library,
 )
@@ -16,6 +17,7 @@ from .base import BaseTool
 from .models import (
     AgentPreviewResponse,
     AgentSavedResponse,
+    AsyncProcessingResponse,
     ClarificationNeededResponse,
     ClarifyingQuestion,
     ErrorResponse,
@@ -103,6 +105,10 @@ class EditAgentTool(BaseTool):
         save = kwargs.get("save", True)
         session_id = session.session_id if session else None
 
+        # Extract async processing params (passed by long-running tool handler)
+        operation_id = kwargs.get("_operation_id")
+        task_id = kwargs.get("_task_id")
+
         if not agent_id:
             return ErrorResponse(
                 message="Please provide the agent ID to edit.",
@@ -117,7 +123,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Step 1: Fetch current agent
         current_agent = await get_agent_as_json(agent_id, user_id)
 
         if current_agent is None:
@@ -127,14 +132,34 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Build the update request with context
+        library_agents = None
+        if user_id:
+            try:
+                graph_id = current_agent.get("id")
+                library_agents = await get_all_relevant_agents_for_generation(
+                    user_id=user_id,
+                    search_query=changes,
+                    exclude_graph_id=graph_id,
+                    include_marketplace=True,
+                )
+                logger.debug(
+                    f"Found {len(library_agents)} relevant agents for sub-agent composition"
+                )
+            except Exception as e:
+                logger.warning(f"Failed to fetch library agents: {e}")
+
         update_request = changes
         if context:
             update_request = f"{changes}\n\nAdditional context:\n{context}"
 
-        # Step 2: Generate updated agent (external service handles fixing and validation)
         try:
-            result = await generate_agent_patch(update_request, current_agent)
+            result = await generate_agent_patch(
+                update_request,
+                current_agent,
+                library_agents,
+                operation_id=operation_id,
+                task_id=task_id,
+            )
         except AgentGeneratorNotConfiguredError:
             return ErrorResponse(
                 message=(
@@ -153,6 +178,19 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
+        # Check if Agent Generator accepted for async processing
+        if result.get("status") == "accepted":
+            logger.info(
+                f"Agent edit delegated to async processing "
+                f"(operation_id={operation_id}, task_id={task_id})"
+            )
+            return AsyncProcessingResponse(
+                message="Agent edit started. You'll be notified when it's complete.",
+                operation_id=operation_id,
+                task_id=task_id,
+                session_id=session_id,
+            )
+
         # Check if the result is an error from the external service
         if isinstance(result, dict) and result.get("type") == "error":
             error_msg = result.get("error", "Unknown error")
@@ -162,6 +200,7 @@ class EditAgentTool(BaseTool):
                 operation="generate the changes",
                 llm_parse_message="The AI had trouble generating the changes. Please try again or simplify your request.",
                 validation_message="The generated changes failed validation. Please try rephrasing your request.",
+                error_details=error_msg,
             )
             return ErrorResponse(
                 message=user_message,
@@ -175,7 +214,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Check if LLM returned clarifying questions
         if result.get("type") == "clarifying_questions":
             questions = result.get("questions", [])
             return ClarificationNeededResponse(
@@ -194,7 +232,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Result is the updated agent JSON
         updated_agent = result
 
         agent_name = updated_agent.get("name", "Updated Agent")
@@ -202,7 +239,6 @@ class EditAgentTool(BaseTool):
         node_count = len(updated_agent.get("nodes", []))
         link_count = len(updated_agent.get("links", []))
 
-        # Step 3: Preview or save
         if not save:
             return AgentPreviewResponse(
                 message=(
@@ -218,7 +254,6 @@ class EditAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-        # Save to library (creates a new version)
         if not user_id:
             return ErrorResponse(
                 message="You must be logged in to save agents.",
@@ -236,7 +271,7 @@ class EditAgentTool(BaseTool):
                 agent_id=created_graph.id,
                 agent_name=created_graph.name,
                 library_agent_id=library_agent.id,
-                library_agent_link=f"/library/{library_agent.id}",
+                library_agent_link=f"/library/agents/{library_agent.id}",
                 agent_page_link=f"/build?flowID={created_graph.id}",
                 session_id=session_id,
             )
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/find_block.py b/autogpt_platform/backend/backend/api/features/chat/tools/find_block.py
index 7ca85961f9..f55cd567e8 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/find_block.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/find_block.py
@@ -13,10 +13,32 @@ from backend.api.features.chat.tools.models import (
     NoResultsResponse,
 )
 from backend.api.features.store.hybrid_search import unified_hybrid_search
-from backend.data.block import get_block
+from backend.data.block import BlockType, get_block
 
 logger = logging.getLogger(__name__)
 
+_TARGET_RESULTS = 10
+# Over-fetch to compensate for post-hoc filtering of graph-only blocks.
+# 40 is 2x current removed; speed of query 10 vs 40 is minimial
+_OVERFETCH_PAGE_SIZE = 40
+
+# Block types that only work within graphs and cannot run standalone in CoPilot.
+COPILOT_EXCLUDED_BLOCK_TYPES = {
+    BlockType.INPUT,  # Graph interface definition - data enters via chat, not graph inputs
+    BlockType.OUTPUT,  # Graph interface definition - data exits via chat, not graph outputs
+    BlockType.WEBHOOK,  # Wait for external events - would hang forever in CoPilot
+    BlockType.WEBHOOK_MANUAL,  # Same as WEBHOOK
+    BlockType.NOTE,  # Visual annotation only - no runtime behavior
+    BlockType.HUMAN_IN_THE_LOOP,  # Pauses for human approval - CoPilot IS human-in-the-loop
+    BlockType.AGENT,  # AgentExecutorBlock requires execution_context - use run_agent tool
+}
+
+# Specific block IDs excluded from CoPilot (STANDARD type but still require graph context)
+COPILOT_EXCLUDED_BLOCK_IDS = {
+    # SmartDecisionMakerBlock - dynamically discovers downstream blocks via graph topology
+    "3b191d9f-356f-482d-8238-ba04b6d18381",
+}
+
 
 class FindBlockTool(BaseTool):
     """Tool for searching available blocks."""
@@ -88,7 +110,7 @@ class FindBlockTool(BaseTool):
                 query=query,
                 content_types=[ContentType.BLOCK],
                 page=1,
-                page_size=10,
+                page_size=_OVERFETCH_PAGE_SIZE,
             )
 
             if not results:
@@ -108,60 +130,90 @@ class FindBlockTool(BaseTool):
                 block = get_block(block_id)
 
                 # Skip disabled blocks
-                if block and not block.disabled:
-                    # Get input/output schemas
-                    input_schema = {}
-                    output_schema = {}
-                    try:
-                        input_schema = block.input_schema.jsonschema()
-                    except Exception:
-                        pass
-                    try:
-                        output_schema = block.output_schema.jsonschema()
-                    except Exception:
-                        pass
+                if not block or block.disabled:
+                    continue
 
-                    # Get categories from block instance
-                    categories = []
-                    if hasattr(block, "categories") and block.categories:
-                        categories = [cat.value for cat in block.categories]
+                # Skip blocks excluded from CoPilot (graph-only blocks)
+                if (
+                    block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
+                    or block.id in COPILOT_EXCLUDED_BLOCK_IDS
+                ):
+                    continue
 
-                    # Extract required inputs for easier use
-                    required_inputs: list[BlockInputFieldInfo] = []
-                    if input_schema:
-                        properties = input_schema.get("properties", {})
-                        required_fields = set(input_schema.get("required", []))
-                        # Get credential field names to exclude from required inputs
-                        credentials_fields = set(
-                            block.input_schema.get_credentials_fields().keys()
-                        )
-
-                        for field_name, field_schema in properties.items():
-                            # Skip credential fields - they're handled separately
-                            if field_name in credentials_fields:
-                                continue
-
-                            required_inputs.append(
-                                BlockInputFieldInfo(
-                                    name=field_name,
-                                    type=field_schema.get("type", "string"),
-                                    description=field_schema.get("description", ""),
-                                    required=field_name in required_fields,
-                                    default=field_schema.get("default"),
-                                )
-                            )
-
-                    blocks.append(
-                        BlockInfoSummary(
-                            id=block_id,
-                            name=block.name,
-                            description=block.description or "",
-                            categories=categories,
-                            input_schema=input_schema,
-                            output_schema=output_schema,
-                            required_inputs=required_inputs,
-                        )
+                # Get input/output schemas
+                input_schema = {}
+                output_schema = {}
+                try:
+                    input_schema = block.input_schema.jsonschema()
+                except Exception as e:
+                    logger.debug(
+                        "Failed to generate input schema for block %s: %s",
+                        block_id,
+                        e,
                     )
+                try:
+                    output_schema = block.output_schema.jsonschema()
+                except Exception as e:
+                    logger.debug(
+                        "Failed to generate output schema for block %s: %s",
+                        block_id,
+                        e,
+                    )
+
+                # Get categories from block instance
+                categories = []
+                if hasattr(block, "categories") and block.categories:
+                    categories = [cat.value for cat in block.categories]
+
+                # Extract required inputs for easier use
+                required_inputs: list[BlockInputFieldInfo] = []
+                if input_schema:
+                    properties = input_schema.get("properties", {})
+                    required_fields = set(input_schema.get("required", []))
+                    # Get credential field names to exclude from required inputs
+                    credentials_fields = set(
+                        block.input_schema.get_credentials_fields().keys()
+                    )
+
+                    for field_name, field_schema in properties.items():
+                        # Skip credential fields - they're handled separately
+                        if field_name in credentials_fields:
+                            continue
+
+                        required_inputs.append(
+                            BlockInputFieldInfo(
+                                name=field_name,
+                                type=field_schema.get("type", "string"),
+                                description=field_schema.get("description", ""),
+                                required=field_name in required_fields,
+                                default=field_schema.get("default"),
+                            )
+                        )
+
+                blocks.append(
+                    BlockInfoSummary(
+                        id=block_id,
+                        name=block.name,
+                        description=block.description or "",
+                        categories=categories,
+                        input_schema=input_schema,
+                        output_schema=output_schema,
+                        required_inputs=required_inputs,
+                    )
+                )
+
+                if len(blocks) >= _TARGET_RESULTS:
+                    break
+
+            if blocks and len(blocks) < _TARGET_RESULTS:
+                logger.debug(
+                    "find_block returned %d/%d results for query '%s' "
+                    "(filtered %d excluded/disabled blocks)",
+                    len(blocks),
+                    _TARGET_RESULTS,
+                    query,
+                    len(results) - len(blocks),
+                )
 
             if not blocks:
                 return NoResultsResponse(
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/find_block_test.py b/autogpt_platform/backend/backend/api/features/chat/tools/find_block_test.py
new file mode 100644
index 0000000000..0f3d4cbfa5
--- /dev/null
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/find_block_test.py
@@ -0,0 +1,139 @@
+"""Tests for block filtering in FindBlockTool."""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from backend.api.features.chat.tools.find_block import (
+    COPILOT_EXCLUDED_BLOCK_IDS,
+    COPILOT_EXCLUDED_BLOCK_TYPES,
+    FindBlockTool,
+)
+from backend.api.features.chat.tools.models import BlockListResponse
+from backend.data.block import BlockType
+
+from ._test_data import make_session
+
+_TEST_USER_ID = "test-user-find-block"
+
+
+def make_mock_block(
+    block_id: str, name: str, block_type: BlockType, disabled: bool = False
+):
+    """Create a mock block for testing."""
+    mock = MagicMock()
+    mock.id = block_id
+    mock.name = name
+    mock.description = f"{name} description"
+    mock.block_type = block_type
+    mock.disabled = disabled
+    mock.input_schema = MagicMock()
+    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
+    mock.input_schema.get_credentials_fields.return_value = {}
+    mock.output_schema = MagicMock()
+    mock.output_schema.jsonschema.return_value = {}
+    mock.categories = []
+    return mock
+
+
+class TestFindBlockFiltering:
+    """Tests for block filtering in FindBlockTool."""
+
+    def test_excluded_block_types_contains_expected_types(self):
+        """Verify COPILOT_EXCLUDED_BLOCK_TYPES contains all graph-only types."""
+        assert BlockType.INPUT in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.OUTPUT in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.WEBHOOK in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.WEBHOOK_MANUAL in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.NOTE in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.HUMAN_IN_THE_LOOP in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.AGENT in COPILOT_EXCLUDED_BLOCK_TYPES
+
+    def test_excluded_block_ids_contains_smart_decision_maker(self):
+        """Verify SmartDecisionMakerBlock is in COPILOT_EXCLUDED_BLOCK_IDS."""
+        assert "3b191d9f-356f-482d-8238-ba04b6d18381" in COPILOT_EXCLUDED_BLOCK_IDS
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_type_filtered_from_results(self):
+        """Verify blocks with excluded BlockTypes are filtered from search results."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        # Mock search returns an INPUT block (excluded) and a STANDARD block (included)
+        search_results = [
+            {"content_id": "input-block-id", "score": 0.9},
+            {"content_id": "standard-block-id", "score": 0.8},
+        ]
+
+        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
+        standard_block = make_mock_block(
+            "standard-block-id", "HTTP Request", BlockType.STANDARD
+        )
+
+        def mock_get_block(block_id):
+            return {
+                "input-block-id": input_block,
+                "standard-block-id": standard_block,
+            }.get(block_id)
+
+        with patch(
+            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
+            new_callable=AsyncMock,
+            return_value=(search_results, 2),
+        ):
+            with patch(
+                "backend.api.features.chat.tools.find_block.get_block",
+                side_effect=mock_get_block,
+            ):
+                tool = FindBlockTool()
+                response = await tool._execute(
+                    user_id=_TEST_USER_ID, session=session, query="test"
+                )
+
+        # Should only return the standard block, not the INPUT block
+        assert isinstance(response, BlockListResponse)
+        assert len(response.blocks) == 1
+        assert response.blocks[0].id == "standard-block-id"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_id_filtered_from_results(self):
+        """Verify SmartDecisionMakerBlock is filtered from search results."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
+        search_results = [
+            {"content_id": smart_decision_id, "score": 0.9},
+            {"content_id": "normal-block-id", "score": 0.8},
+        ]
+
+        # SmartDecisionMakerBlock has STANDARD type but is excluded by ID
+        smart_block = make_mock_block(
+            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
+        )
+        normal_block = make_mock_block(
+            "normal-block-id", "Normal Block", BlockType.STANDARD
+        )
+
+        def mock_get_block(block_id):
+            return {
+                smart_decision_id: smart_block,
+                "normal-block-id": normal_block,
+            }.get(block_id)
+
+        with patch(
+            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
+            new_callable=AsyncMock,
+            return_value=(search_results, 2),
+        ):
+            with patch(
+                "backend.api.features.chat.tools.find_block.get_block",
+                side_effect=mock_get_block,
+            ):
+                tool = FindBlockTool()
+                response = await tool._execute(
+                    user_id=_TEST_USER_ID, session=session, query="decision"
+                )
+
+        # Should only return normal block, not SmartDecisionMakerBlock
+        assert isinstance(response, BlockListResponse)
+        assert len(response.blocks) == 1
+        assert response.blocks[0].id == "normal-block-id"
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py b/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py
new file mode 100644
index 0000000000..cf53605ac0
--- /dev/null
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py
@@ -0,0 +1,29 @@
+"""Shared helpers for chat tools."""
+
+from typing import Any
+
+
+def get_inputs_from_schema(
+    input_schema: dict[str, Any],
+    exclude_fields: set[str] | None = None,
+) -> list[dict[str, Any]]:
+    """Extract input field info from JSON schema."""
+    if not isinstance(input_schema, dict):
+        return []
+
+    exclude = exclude_fields or set()
+    properties = input_schema.get("properties", {})
+    required = set(input_schema.get("required", []))
+
+    return [
+        {
+            "name": name,
+            "title": schema.get("title", name),
+            "type": schema.get("type", "string"),
+            "description": schema.get("description", ""),
+            "required": name in required,
+            "default": schema.get("default"),
+        }
+        for name, schema in properties.items()
+        if name not in exclude
+    ]
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/models.py b/autogpt_platform/backend/backend/api/features/chat/tools/models.py
index 49b233784e..69c8c6c684 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/models.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/models.py
@@ -38,6 +38,8 @@ class ResponseType(str, Enum):
     OPERATION_STARTED = "operation_started"
     OPERATION_PENDING = "operation_pending"
     OPERATION_IN_PROGRESS = "operation_in_progress"
+    # Input validation
+    INPUT_VALIDATION_ERROR = "input_validation_error"
 
 
 # Base response model
@@ -68,6 +70,10 @@ class AgentInfo(BaseModel):
     has_external_trigger: bool | None = None
     new_output: bool | None = None
     graph_id: str | None = None
+    inputs: dict[str, Any] | None = Field(
+        default=None,
+        description="Input schema for the agent, including field names, types, and defaults",
+    )
 
 
 class AgentsFoundResponse(ToolResponseBase):
@@ -194,6 +200,20 @@ class ErrorResponse(ToolResponseBase):
     details: dict[str, Any] | None = None
 
 
+class InputValidationErrorResponse(ToolResponseBase):
+    """Response when run_agent receives unknown input fields."""
+
+    type: ResponseType = ResponseType.INPUT_VALIDATION_ERROR
+    unrecognized_fields: list[str] = Field(
+        description="List of input field names that were not recognized"
+    )
+    inputs: dict[str, Any] = Field(
+        description="The agent's valid input schema for reference"
+    )
+    graph_id: str | None = None
+    graph_version: int | None = None
+
+
 # Agent output models
 class ExecutionOutputInfo(BaseModel):
     """Summary of a single execution's outputs."""
@@ -352,11 +372,15 @@ class OperationStartedResponse(ToolResponseBase):
 
     This is returned immediately to the client while the operation continues
     to execute. The user can close the tab and check back later.
+
+    The task_id can be used to reconnect to the SSE stream via
+    GET /chat/tasks/{task_id}/stream?last_idx=0
     """
 
     type: ResponseType = ResponseType.OPERATION_STARTED
     operation_id: str
     tool_name: str
+    task_id: str | None = None  # For SSE reconnection
 
 
 class OperationPendingResponse(ToolResponseBase):
@@ -380,3 +404,20 @@ class OperationInProgressResponse(ToolResponseBase):
 
     type: ResponseType = ResponseType.OPERATION_IN_PROGRESS
     tool_call_id: str
+
+
+class AsyncProcessingResponse(ToolResponseBase):
+    """Response when an operation has been delegated to async processing.
+
+    This is returned by tools when the external service accepts the request
+    for async processing (HTTP 202 Accepted). The Redis Streams completion
+    consumer will handle the result when the external service completes.
+
+    The status field is specifically "accepted" to allow the long-running tool
+    handler to detect this response and skip LLM continuation.
+    """
+
+    type: ResponseType = ResponseType.OPERATION_STARTED
+    status: str = "accepted"  # Must be "accepted" for detection
+    operation_id: str | None = None
+    task_id: str | None = None
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py b/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py
index a7fa65348a..a9f19bcf62 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py
@@ -24,12 +24,14 @@ from backend.util.timezone_utils import (
 )
 
 from .base import BaseTool
+from .helpers import get_inputs_from_schema
 from .models import (
     AgentDetails,
     AgentDetailsResponse,
     ErrorResponse,
     ExecutionOptions,
     ExecutionStartedResponse,
+    InputValidationErrorResponse,
     SetupInfo,
     SetupRequirementsResponse,
     ToolResponseBase,
@@ -260,7 +262,7 @@ class RunAgentTool(BaseTool):
                         ),
                         requirements={
                             "credentials": requirements_creds_list,
-                            "inputs": self._get_inputs_list(graph.input_schema),
+                            "inputs": get_inputs_from_schema(graph.input_schema),
                             "execution_modes": self._get_execution_modes(graph),
                         },
                     ),
@@ -273,6 +275,22 @@ class RunAgentTool(BaseTool):
             input_properties = graph.input_schema.get("properties", {})
             required_fields = set(graph.input_schema.get("required", []))
             provided_inputs = set(params.inputs.keys())
+            valid_fields = set(input_properties.keys())
+
+            # Check for unknown input fields
+            unrecognized_fields = provided_inputs - valid_fields
+            if unrecognized_fields:
+                return InputValidationErrorResponse(
+                    message=(
+                        f"Unknown input field(s) provided: {', '.join(sorted(unrecognized_fields))}. "
+                        f"Agent was not executed. Please use the correct field names from the schema."
+                    ),
+                    session_id=session_id,
+                    unrecognized_fields=sorted(unrecognized_fields),
+                    inputs=graph.input_schema,
+                    graph_id=graph.id,
+                    graph_version=graph.version,
+                )
 
             # If agent has inputs but none were provided AND use_defaults is not set,
             # always show what's available first so user can decide
@@ -352,22 +370,6 @@ class RunAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-    def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]:
-        """Extract inputs list from schema."""
-        inputs_list = []
-        if isinstance(input_schema, dict) and "properties" in input_schema:
-            for field_name, field_schema in input_schema["properties"].items():
-                inputs_list.append(
-                    {
-                        "name": field_name,
-                        "title": field_schema.get("title", field_name),
-                        "type": field_schema.get("type", "string"),
-                        "description": field_schema.get("description", ""),
-                        "required": field_name in input_schema.get("required", []),
-                    }
-                )
-        return inputs_list
-
     def _get_execution_modes(self, graph: GraphModel) -> list[str]:
         """Get available execution modes for the graph."""
         trigger_info = graph.trigger_setup_info
@@ -381,7 +383,7 @@ class RunAgentTool(BaseTool):
         suffix: str,
     ) -> str:
         """Build a message describing available inputs for an agent."""
-        inputs_list = self._get_inputs_list(graph.input_schema)
+        inputs_list = get_inputs_from_schema(graph.input_schema)
         required_names = [i["name"] for i in inputs_list if i["required"]]
         optional_names = [i["name"] for i in inputs_list if not i["required"]]
 
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/run_agent_test.py b/autogpt_platform/backend/backend/api/features/chat/tools/run_agent_test.py
index 404df2adb6..d5da394fa6 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/run_agent_test.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_agent_test.py
@@ -402,3 +402,42 @@ async def test_run_agent_schedule_without_name(setup_test_data):
     # Should return error about missing schedule_name
     assert result_data.get("type") == "error"
     assert "schedule_name" in result_data["message"].lower()
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_run_agent_rejects_unknown_input_fields(setup_test_data):
+    """Test that run_agent returns input_validation_error for unknown input fields."""
+    user = setup_test_data["user"]
+    store_submission = setup_test_data["store_submission"]
+
+    tool = RunAgentTool()
+    agent_marketplace_id = f"{user.email.split('@')[0]}/{store_submission.slug}"
+    session = make_session(user_id=user.id)
+
+    # Execute with unknown input field names
+    response = await tool.execute(
+        user_id=user.id,
+        session_id=str(uuid.uuid4()),
+        tool_call_id=str(uuid.uuid4()),
+        username_agent_slug=agent_marketplace_id,
+        inputs={
+            "unknown_field": "some value",
+            "another_unknown": "another value",
+        },
+        session=session,
+    )
+
+    assert response is not None
+    assert hasattr(response, "output")
+    assert isinstance(response.output, str)
+    result_data = orjson.loads(response.output)
+
+    # Should return input_validation_error type with unrecognized fields
+    assert result_data.get("type") == "input_validation_error"
+    assert "unrecognized_fields" in result_data
+    assert set(result_data["unrecognized_fields"]) == {
+        "another_unknown",
+        "unknown_field",
+    }
+    assert "inputs" in result_data  # Contains the valid schema
+    assert "Agent was not executed" in result_data["message"]
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py b/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
index a59082b399..fc4a470fdd 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
@@ -5,15 +5,22 @@ import uuid
 from collections import defaultdict
 from typing import Any
 
+from pydantic_core import PydanticUndefined
+
 from backend.api.features.chat.model import ChatSession
-from backend.data.block import get_block
+from backend.api.features.chat.tools.find_block import (
+    COPILOT_EXCLUDED_BLOCK_IDS,
+    COPILOT_EXCLUDED_BLOCK_TYPES,
+)
+from backend.data.block import AnyBlockSchema, get_block
 from backend.data.execution import ExecutionContext
-from backend.data.model import CredentialsMetaInput
+from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
 from backend.data.workspace import get_or_create_workspace
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import BlockError
 
 from .base import BaseTool
+from .helpers import get_inputs_from_schema
 from .models import (
     BlockOutputResponse,
     ErrorResponse,
@@ -22,7 +29,10 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
-from .utils import build_missing_credentials_from_field_info
+from .utils import (
+    build_missing_credentials_from_field_info,
+    match_credentials_to_requirements,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -71,65 +81,6 @@ class RunBlockTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
-    async def _check_block_credentials(
-        self,
-        user_id: str,
-        block: Any,
-    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
-        """
-        Check if user has required credentials for a block.
-
-        Returns:
-            tuple[matched_credentials, missing_credentials]
-        """
-        matched_credentials: dict[str, CredentialsMetaInput] = {}
-        missing_credentials: list[CredentialsMetaInput] = []
-
-        # Get credential field info from block's input schema
-        credentials_fields_info = block.input_schema.get_credentials_fields_info()
-
-        if not credentials_fields_info:
-            return matched_credentials, missing_credentials
-
-        # Get user's available credentials
-        creds_manager = IntegrationCredentialsManager()
-        available_creds = await creds_manager.store.get_all_creds(user_id)
-
-        for field_name, field_info in credentials_fields_info.items():
-            # field_info.provider is a frozenset of acceptable providers
-            # field_info.supported_types is a frozenset of acceptable types
-            matching_cred = next(
-                (
-                    cred
-                    for cred in available_creds
-                    if cred.provider in field_info.provider
-                    and cred.type in field_info.supported_types
-                ),
-                None,
-            )
-
-            if matching_cred:
-                matched_credentials[field_name] = CredentialsMetaInput(
-                    id=matching_cred.id,
-                    provider=matching_cred.provider,  # type: ignore
-                    type=matching_cred.type,
-                    title=matching_cred.title,
-                )
-            else:
-                # Create a placeholder for the missing credential
-                provider = next(iter(field_info.provider), "unknown")
-                cred_type = next(iter(field_info.supported_types), "api_key")
-                missing_credentials.append(
-                    CredentialsMetaInput(
-                        id=field_name,
-                        provider=provider,  # type: ignore
-                        type=cred_type,  # type: ignore
-                        title=field_name.replace("_", " ").title(),
-                    )
-                )
-
-        return matched_credentials, missing_credentials
-
     async def _execute(
         self,
         user_id: str | None,
@@ -184,12 +135,24 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
+        # Check if block is excluded from CoPilot (graph-only blocks)
+        if (
+            block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
+            or block.id in COPILOT_EXCLUDED_BLOCK_IDS
+        ):
+            return ErrorResponse(
+                message=(
+                    f"Block '{block.name}' cannot be run directly in CoPilot. "
+                    "This block is designed for use within graphs only."
+                ),
+                session_id=session_id,
+            )
+
         logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
 
-        # Check credentials
         creds_manager = IntegrationCredentialsManager()
-        matched_credentials, missing_credentials = await self._check_block_credentials(
-            user_id, block
+        matched_credentials, missing_credentials = (
+            await self._resolve_block_credentials(user_id, block, input_data)
         )
 
         if missing_credentials:
@@ -318,29 +281,75 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
-    def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
+    async def _resolve_block_credentials(
+        self,
+        user_id: str,
+        block: AnyBlockSchema,
+        input_data: dict[str, Any] | None = None,
+    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
+        """
+        Resolve credentials for a block by matching user's available credentials.
+
+        Args:
+            user_id: User ID
+            block: Block to resolve credentials for
+            input_data: Input data for the block (used to determine provider via discriminator)
+
+        Returns:
+            tuple of (matched_credentials, missing_credentials) - matched credentials
+            are used for block execution, missing ones indicate setup requirements.
+        """
+        input_data = input_data or {}
+        requirements = self._resolve_discriminated_credentials(block, input_data)
+
+        if not requirements:
+            return {}, []
+
+        return await match_credentials_to_requirements(user_id, requirements)
+
+    def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]:
         """Extract non-credential inputs from block schema."""
-        inputs_list = []
         schema = block.input_schema.jsonschema()
-        properties = schema.get("properties", {})
-        required_fields = set(schema.get("required", []))
-
-        # Get credential field names to exclude
         credentials_fields = set(block.input_schema.get_credentials_fields().keys())
+        return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
 
-        for field_name, field_schema in properties.items():
-            # Skip credential fields
-            if field_name in credentials_fields:
-                continue
+    def _resolve_discriminated_credentials(
+        self,
+        block: AnyBlockSchema,
+        input_data: dict[str, Any],
+    ) -> dict[str, CredentialsFieldInfo]:
+        """Resolve credential requirements, applying discriminator logic where needed."""
+        credentials_fields_info = block.input_schema.get_credentials_fields_info()
+        if not credentials_fields_info:
+            return {}
 
-            inputs_list.append(
-                {
-                    "name": field_name,
-                    "title": field_schema.get("title", field_name),
-                    "type": field_schema.get("type", "string"),
-                    "description": field_schema.get("description", ""),
-                    "required": field_name in required_fields,
-                }
-            )
+        resolved: dict[str, CredentialsFieldInfo] = {}
 
-        return inputs_list
+        for field_name, field_info in credentials_fields_info.items():
+            effective_field_info = field_info
+
+            if field_info.discriminator and field_info.discriminator_mapping:
+                discriminator_value = input_data.get(field_info.discriminator)
+                if discriminator_value is None:
+                    field = block.input_schema.model_fields.get(
+                        field_info.discriminator
+                    )
+                    if field and field.default is not PydanticUndefined:
+                        discriminator_value = field.default
+
+                if (
+                    discriminator_value
+                    and discriminator_value in field_info.discriminator_mapping
+                ):
+                    effective_field_info = field_info.discriminate(discriminator_value)
+                    # For host-scoped credentials, add the discriminator value
+                    # (e.g., URL) so _credential_is_for_host can match it
+                    effective_field_info.discriminator_values.add(discriminator_value)
+                    logger.debug(
+                        f"Discriminated provider for {field_name}: "
+                        f"{discriminator_value} -> {effective_field_info.provider}"
+                    )
+
+            resolved[field_name] = effective_field_info
+
+        return resolved
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/run_block_test.py b/autogpt_platform/backend/backend/api/features/chat/tools/run_block_test.py
new file mode 100644
index 0000000000..2aae45e875
--- /dev/null
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_block_test.py
@@ -0,0 +1,106 @@
+"""Tests for block execution guards in RunBlockTool."""
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from backend.api.features.chat.tools.models import ErrorResponse
+from backend.api.features.chat.tools.run_block import RunBlockTool
+from backend.data.block import BlockType
+
+from ._test_data import make_session
+
+_TEST_USER_ID = "test-user-run-block"
+
+
+def make_mock_block(
+    block_id: str, name: str, block_type: BlockType, disabled: bool = False
+):
+    """Create a mock block for testing."""
+    mock = MagicMock()
+    mock.id = block_id
+    mock.name = name
+    mock.block_type = block_type
+    mock.disabled = disabled
+    mock.input_schema = MagicMock()
+    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
+    mock.input_schema.get_credentials_fields_info.return_value = []
+    return mock
+
+
+class TestRunBlockFiltering:
+    """Tests for block execution guards in RunBlockTool."""
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_type_returns_error(self):
+        """Attempting to execute a block with excluded BlockType returns error."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
+
+        with patch(
+            "backend.api.features.chat.tools.run_block.get_block",
+            return_value=input_block,
+        ):
+            tool = RunBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                block_id="input-block-id",
+                input_data={},
+            )
+
+        assert isinstance(response, ErrorResponse)
+        assert "cannot be run directly in CoPilot" in response.message
+        assert "designed for use within graphs only" in response.message
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_id_returns_error(self):
+        """Attempting to execute SmartDecisionMakerBlock returns error."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
+        smart_block = make_mock_block(
+            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
+        )
+
+        with patch(
+            "backend.api.features.chat.tools.run_block.get_block",
+            return_value=smart_block,
+        ):
+            tool = RunBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                block_id=smart_decision_id,
+                input_data={},
+            )
+
+        assert isinstance(response, ErrorResponse)
+        assert "cannot be run directly in CoPilot" in response.message
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_non_excluded_block_passes_guard(self):
+        """Non-excluded blocks pass the filtering guard (may fail later for other reasons)."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        standard_block = make_mock_block(
+            "standard-id", "HTTP Request", BlockType.STANDARD
+        )
+
+        with patch(
+            "backend.api.features.chat.tools.run_block.get_block",
+            return_value=standard_block,
+        ):
+            tool = RunBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                block_id="standard-id",
+                input_data={},
+            )
+
+        # Should NOT be an ErrorResponse about CoPilot exclusion
+        # (may be other errors like missing credentials, but not the exclusion guard)
+        if isinstance(response, ErrorResponse):
+            assert "cannot be run directly in CoPilot" not in response.message
diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/utils.py b/autogpt_platform/backend/backend/api/features/chat/tools/utils.py
index a2ac91dc65..80a842bf36 100644
--- a/autogpt_platform/backend/backend/api/features/chat/tools/utils.py
+++ b/autogpt_platform/backend/backend/api/features/chat/tools/utils.py
@@ -6,9 +6,14 @@ from typing import Any
 from backend.api.features.library import db as library_db
 from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
-from backend.data import graph as graph_db
 from backend.data.graph import GraphModel
-from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
+from backend.data.model import (
+    Credentials,
+    CredentialsFieldInfo,
+    CredentialsMetaInput,
+    HostScopedCredentials,
+    OAuth2Credentials,
+)
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import NotFoundError
 
@@ -39,14 +44,8 @@ async def fetch_graph_from_store_slug(
         return None, None
 
     # Get the graph from store listing version
-    graph_meta = await store_db.get_available_graph(
-        store_agent.store_listing_version_id
-    )
-    graph = await graph_db.get_graph(
-        graph_id=graph_meta.id,
-        version=graph_meta.version,
-        user_id=None,  # Public access
-        include_subgraphs=True,
+    graph = await store_db.get_available_graph(
+        store_agent.store_listing_version_id, hide_nodes=False
     )
     return graph, store_agent
 
@@ -123,7 +122,7 @@ def build_missing_credentials_from_graph(
 
     return {
         field_key: _serialize_missing_credential(field_key, field_info)
-        for field_key, (field_info, _node_fields) in aggregated_fields.items()
+        for field_key, (field_info, _, _) in aggregated_fields.items()
         if field_key not in matched_keys
     }
 
@@ -225,6 +224,99 @@ async def get_or_create_library_agent(
     return library_agents[0]
 
 
+async def match_credentials_to_requirements(
+    user_id: str,
+    requirements: dict[str, CredentialsFieldInfo],
+) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
+    """
+    Match user's credentials against a dictionary of credential requirements.
+
+    This is the core matching logic shared by both graph and block credential matching.
+    """
+    matched: dict[str, CredentialsMetaInput] = {}
+    missing: list[CredentialsMetaInput] = []
+
+    if not requirements:
+        return matched, missing
+
+    available_creds = await get_user_credentials(user_id)
+
+    for field_name, field_info in requirements.items():
+        matching_cred = find_matching_credential(available_creds, field_info)
+
+        if matching_cred:
+            try:
+                matched[field_name] = create_credential_meta_from_match(matching_cred)
+            except Exception as e:
+                logger.error(
+                    f"Failed to create CredentialsMetaInput for field '{field_name}': "
+                    f"provider={matching_cred.provider}, type={matching_cred.type}, "
+                    f"credential_id={matching_cred.id}",
+                    exc_info=True,
+                )
+                provider = next(iter(field_info.provider), "unknown")
+                cred_type = next(iter(field_info.supported_types), "api_key")
+                missing.append(
+                    CredentialsMetaInput(
+                        id=field_name,
+                        provider=provider,  # type: ignore
+                        type=cred_type,  # type: ignore
+                        title=f"{field_name} (validation failed: {e})",
+                    )
+                )
+        else:
+            provider = next(iter(field_info.provider), "unknown")
+            cred_type = next(iter(field_info.supported_types), "api_key")
+            missing.append(
+                CredentialsMetaInput(
+                    id=field_name,
+                    provider=provider,  # type: ignore
+                    type=cred_type,  # type: ignore
+                    title=field_name.replace("_", " ").title(),
+                )
+            )
+
+    return matched, missing
+
+
+async def get_user_credentials(user_id: str) -> list[Credentials]:
+    """Get all available credentials for a user."""
+    creds_manager = IntegrationCredentialsManager()
+    return await creds_manager.store.get_all_creds(user_id)
+
+
+def find_matching_credential(
+    available_creds: list[Credentials],
+    field_info: CredentialsFieldInfo,
+) -> Credentials | None:
+    """Find a credential that matches the required provider, type, scopes, and host."""
+    for cred in available_creds:
+        if cred.provider not in field_info.provider:
+            continue
+        if cred.type not in field_info.supported_types:
+            continue
+        if cred.type == "oauth2" and not _credential_has_required_scopes(
+            cred, field_info
+        ):
+            continue
+        if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info):
+            continue
+        return cred
+    return None
+
+
+def create_credential_meta_from_match(
+    matching_cred: Credentials,
+) -> CredentialsMetaInput:
+    """Create a CredentialsMetaInput from a matched credential."""
+    return CredentialsMetaInput(
+        id=matching_cred.id,
+        provider=matching_cred.provider,  # type: ignore
+        type=matching_cred.type,
+        title=matching_cred.title,
+    )
+
+
 async def match_user_credentials_to_graph(
     user_id: str,
     graph: GraphModel,
@@ -264,15 +356,24 @@ async def match_user_credentials_to_graph(
     # provider is in the set of acceptable providers.
     for credential_field_name, (
         credential_requirements,
-        _node_fields,
+        _,
+        _,
     ) in aggregated_creds.items():
-        # Find first matching credential by provider and type
+        # Find first matching credential by provider, type, and scopes
         matching_cred = next(
             (
                 cred
                 for cred in available_creds
                 if cred.provider in credential_requirements.provider
                 and cred.type in credential_requirements.supported_types
+                and (
+                    cred.type != "oauth2"
+                    or _credential_has_required_scopes(cred, credential_requirements)
+                )
+                and (
+                    cred.type != "host_scoped"
+                    or _credential_is_for_host(cred, credential_requirements)
+                )
             ),
             None,
         )
@@ -296,10 +397,17 @@ async def match_user_credentials_to_graph(
                     f"{credential_field_name} (validation failed: {e})"
                 )
         else:
+            # Build a helpful error message including scope requirements
+            error_parts = [
+                f"provider in {list(credential_requirements.provider)}",
+                f"type in {list(credential_requirements.supported_types)}",
+            ]
+            if credential_requirements.required_scopes:
+                error_parts.append(
+                    f"scopes including {list(credential_requirements.required_scopes)}"
+                )
             missing_creds.append(
-                f"{credential_field_name} "
-                f"(requires provider in {list(credential_requirements.provider)}, "
-                f"type in {list(credential_requirements.supported_types)})"
+                f"{credential_field_name} (requires {', '.join(error_parts)})"
             )
 
     logger.info(
@@ -309,6 +417,33 @@ async def match_user_credentials_to_graph(
     return graph_credentials_inputs, missing_creds
 
 
+def _credential_has_required_scopes(
+    credential: OAuth2Credentials,
+    requirements: CredentialsFieldInfo,
+) -> bool:
+    """Check if an OAuth2 credential has all the scopes required by the input."""
+    # If no scopes are required, any credential matches
+    if not requirements.required_scopes:
+        return True
+    return set(credential.scopes).issuperset(requirements.required_scopes)
+
+
+def _credential_is_for_host(
+    credential: HostScopedCredentials,
+    requirements: CredentialsFieldInfo,
+) -> bool:
+    """Check if a host-scoped credential matches the host required by the input."""
+    # We need to know the host to match host-scoped credentials to.
+    # Graph.aggregate_credentials_inputs() adds the node's set URL value (if any)
+    # to discriminator_values. No discriminator_values -> no host to match against.
+    if not requirements.discriminator_values:
+        return True
+
+    # Check that credential host matches required host.
+    # Host-scoped credential inputs are grouped by host, so any item from the set works.
+    return credential.matches_url(list(requirements.discriminator_values)[0])
+
+
 async def check_user_has_required_credentials(
     user_id: str,
     required_credentials: list[CredentialsMetaInput],
diff --git a/autogpt_platform/backend/backend/api/features/library/db.py b/autogpt_platform/backend/backend/api/features/library/db.py
index 872fe66b28..32479c18a3 100644
--- a/autogpt_platform/backend/backend/api/features/library/db.py
+++ b/autogpt_platform/backend/backend/api/features/library/db.py
@@ -19,7 +19,10 @@ from backend.data.graph import GraphSettings
 from backend.data.includes import AGENT_PRESET_INCLUDE, library_agent_include
 from backend.data.model import CredentialsMetaInput
 from backend.integrations.creds_manager import IntegrationCredentialsManager
-from backend.integrations.webhooks.graph_lifecycle_hooks import on_graph_activate
+from backend.integrations.webhooks.graph_lifecycle_hooks import (
+    on_graph_activate,
+    on_graph_deactivate,
+)
 from backend.util.clients import get_scheduler_client
 from backend.util.exceptions import DatabaseError, InvalidInputError, NotFoundError
 from backend.util.json import SafeJson
@@ -39,6 +42,7 @@ async def list_library_agents(
     sort_by: library_model.LibraryAgentSort = library_model.LibraryAgentSort.UPDATED_AT,
     page: int = 1,
     page_size: int = 50,
+    include_executions: bool = False,
 ) -> library_model.LibraryAgentResponse:
     """
     Retrieves a paginated list of LibraryAgent records for a given user.
@@ -49,6 +53,9 @@ async def list_library_agents(
         sort_by: Sorting field (createdAt, updatedAt, isFavorite, isCreatedByUser).
         page: Current page (1-indexed).
         page_size: Number of items per page.
+        include_executions: Whether to include execution data for status calculation.
+            Defaults to False for performance (UI fetches status separately).
+            Set to True when accurate status/metrics are needed (e.g., agent generator).
 
     Returns:
         A LibraryAgentResponse containing the list of agents and pagination details.
@@ -76,7 +83,6 @@ async def list_library_agents(
         "isArchived": False,
     }
 
-    # Build search filter if applicable
     if search_term:
         where_clause["OR"] = [
             {
@@ -93,7 +99,6 @@ async def list_library_agents(
             },
         ]
 
-    # Determine sorting
     order_by: prisma.types.LibraryAgentOrderByInput | None = None
 
     if sort_by == library_model.LibraryAgentSort.CREATED_AT:
@@ -105,7 +110,7 @@ async def list_library_agents(
         library_agents = await prisma.models.LibraryAgent.prisma().find_many(
             where=where_clause,
             include=library_agent_include(
-                user_id, include_nodes=False, include_executions=False
+                user_id, include_nodes=False, include_executions=include_executions
             ),
             order=order_by,
             skip=(page - 1) * page_size,
@@ -369,7 +374,7 @@ async def get_library_agent_by_graph_id(
 
 
 async def add_generated_agent_image(
-    graph: graph_db.BaseGraph,
+    graph: graph_db.GraphBaseMeta,
     user_id: str,
     library_agent_id: str,
 ) -> Optional[prisma.models.LibraryAgent]:
@@ -535,6 +540,92 @@ async def update_agent_version_in_library(
     return library_model.LibraryAgent.from_db(lib)
 
 
+async def create_graph_in_library(
+    graph: graph_db.Graph,
+    user_id: str,
+) -> tuple[graph_db.GraphModel, library_model.LibraryAgent]:
+    """Create a new graph and add it to the user's library."""
+    graph.version = 1
+    graph_model = graph_db.make_graph_model(graph, user_id)
+    graph_model.reassign_ids(user_id=user_id, reassign_graph_id=True)
+
+    created_graph = await graph_db.create_graph(graph_model, user_id)
+
+    library_agents = await create_library_agent(
+        graph=created_graph,
+        user_id=user_id,
+        sensitive_action_safe_mode=True,
+        create_library_agents_for_sub_graphs=False,
+    )
+
+    if created_graph.is_active:
+        created_graph = await on_graph_activate(created_graph, user_id=user_id)
+
+    return created_graph, library_agents[0]
+
+
+async def update_graph_in_library(
+    graph: graph_db.Graph,
+    user_id: str,
+) -> tuple[graph_db.GraphModel, library_model.LibraryAgent]:
+    """Create a new version of an existing graph and update the library entry."""
+    existing_versions = await graph_db.get_graph_all_versions(graph.id, user_id)
+    current_active_version = (
+        next((v for v in existing_versions if v.is_active), None)
+        if existing_versions
+        else None
+    )
+    graph.version = (
+        max(v.version for v in existing_versions) + 1 if existing_versions else 1
+    )
+
+    graph_model = graph_db.make_graph_model(graph, user_id)
+    graph_model.reassign_ids(user_id=user_id, reassign_graph_id=False)
+
+    created_graph = await graph_db.create_graph(graph_model, user_id)
+
+    library_agent = await get_library_agent_by_graph_id(user_id, created_graph.id)
+    if not library_agent:
+        raise NotFoundError(f"Library agent not found for graph {created_graph.id}")
+
+    library_agent = await update_library_agent_version_and_settings(
+        user_id, created_graph
+    )
+
+    if created_graph.is_active:
+        created_graph = await on_graph_activate(created_graph, user_id=user_id)
+        await graph_db.set_graph_active_version(
+            graph_id=created_graph.id,
+            version=created_graph.version,
+            user_id=user_id,
+        )
+        if current_active_version:
+            await on_graph_deactivate(current_active_version, user_id=user_id)
+
+    return created_graph, library_agent
+
+
+async def update_library_agent_version_and_settings(
+    user_id: str, agent_graph: graph_db.GraphModel
+) -> library_model.LibraryAgent:
+    """Update library agent to point to new graph version and sync settings."""
+    library = await update_agent_version_in_library(
+        user_id, agent_graph.id, agent_graph.version
+    )
+    updated_settings = GraphSettings.from_graph(
+        graph=agent_graph,
+        hitl_safe_mode=library.settings.human_in_the_loop_safe_mode,
+        sensitive_action_safe_mode=library.settings.sensitive_action_safe_mode,
+    )
+    if updated_settings != library.settings:
+        library = await update_library_agent(
+            library_agent_id=library.id,
+            user_id=user_id,
+            settings=updated_settings,
+        )
+    return library
+
+
 async def update_library_agent(
     library_agent_id: str,
     user_id: str,
diff --git a/autogpt_platform/backend/backend/api/features/library/model.py b/autogpt_platform/backend/backend/api/features/library/model.py
index 14d7c7be81..c6bc0e0427 100644
--- a/autogpt_platform/backend/backend/api/features/library/model.py
+++ b/autogpt_platform/backend/backend/api/features/library/model.py
@@ -9,6 +9,7 @@ import pydantic
 from backend.data.block import BlockInput
 from backend.data.graph import GraphModel, GraphSettings, GraphTriggerInfo
 from backend.data.model import CredentialsMetaInput, is_credentials_field_name
+from backend.util.json import loads as json_loads
 from backend.util.models import Pagination
 
 if TYPE_CHECKING:
@@ -16,10 +17,10 @@ if TYPE_CHECKING:
 
 
 class LibraryAgentStatus(str, Enum):
-    COMPLETED = "COMPLETED"  # All runs completed
-    HEALTHY = "HEALTHY"  # Agent is running (not all runs have completed)
-    WAITING = "WAITING"  # Agent is queued or waiting to start
-    ERROR = "ERROR"  # Agent is in an error state
+    COMPLETED = "COMPLETED"
+    HEALTHY = "HEALTHY"
+    WAITING = "WAITING"
+    ERROR = "ERROR"
 
 
 class MarketplaceListingCreator(pydantic.BaseModel):
@@ -39,6 +40,30 @@ class MarketplaceListing(pydantic.BaseModel):
     creator: MarketplaceListingCreator
 
 
+class RecentExecution(pydantic.BaseModel):
+    """Summary of a recent execution for quality assessment.
+
+    Used by the LLM to understand the agent's recent performance with specific examples
+    rather than just aggregate statistics.
+    """
+
+    status: str
+    correctness_score: float | None = None
+    activity_summary: str | None = None
+
+
+def _parse_settings(settings: dict | str | None) -> GraphSettings:
+    """Parse settings from database, handling both dict and string formats."""
+    if settings is None:
+        return GraphSettings()
+    try:
+        if isinstance(settings, str):
+            settings = json_loads(settings)
+        return GraphSettings.model_validate(settings)
+    except Exception:
+        return GraphSettings()
+
+
 class LibraryAgent(pydantic.BaseModel):
     """
     Represents an agent in the library, including metadata for display and
@@ -48,7 +73,7 @@ class LibraryAgent(pydantic.BaseModel):
     id: str
     graph_id: str
     graph_version: int
-    owner_user_id: str  # ID of user who owns/created this agent graph
+    owner_user_id: str
 
     image_url: str | None
 
@@ -64,7 +89,7 @@ class LibraryAgent(pydantic.BaseModel):
     description: str
     instructions: str | None = None
 
-    input_schema: dict[str, Any]  # Should be BlockIOObjectSubSchema in frontend
+    input_schema: dict[str, Any]
     output_schema: dict[str, Any]
     credentials_input_schema: dict[str, Any] | None = pydantic.Field(
         description="Input schema for credentials required by the agent",
@@ -81,25 +106,19 @@ class LibraryAgent(pydantic.BaseModel):
     )
     trigger_setup_info: Optional[GraphTriggerInfo] = None
 
-    # Indicates whether there's a new output (based on recent runs)
     new_output: bool
-
-    # Whether the user can access the underlying graph
+    execution_count: int = 0
+    success_rate: float | None = None
+    avg_correctness_score: float | None = None
+    recent_executions: list[RecentExecution] = pydantic.Field(
+        default_factory=list,
+        description="List of recent executions with status, score, and summary",
+    )
     can_access_graph: bool
-
-    # Indicates if this agent is the latest version
     is_latest_version: bool
-
-    # Whether the agent is marked as favorite by the user
     is_favorite: bool
-
-    # Recommended schedule cron (from marketplace agents)
     recommended_schedule_cron: str | None = None
-
-    # User-specific settings for this library agent
     settings: GraphSettings = pydantic.Field(default_factory=GraphSettings)
-
-    # Marketplace listing information if the agent has been published
     marketplace_listing: Optional["MarketplaceListing"] = None
 
     @staticmethod
@@ -123,7 +142,6 @@ class LibraryAgent(pydantic.BaseModel):
         agent_updated_at = agent.AgentGraph.updatedAt
         lib_agent_updated_at = agent.updatedAt
 
-        # Compute updated_at as the latest between library agent and graph
         updated_at = (
             max(agent_updated_at, lib_agent_updated_at)
             if agent_updated_at
@@ -136,7 +154,6 @@ class LibraryAgent(pydantic.BaseModel):
             creator_name = agent.Creator.name or "Unknown"
             creator_image_url = agent.Creator.avatarUrl or ""
 
-        # Logic to calculate status and new_output
         week_ago = datetime.datetime.now(datetime.timezone.utc) - datetime.timedelta(
             days=7
         )
@@ -145,13 +162,55 @@ class LibraryAgent(pydantic.BaseModel):
         status = status_result.status
         new_output = status_result.new_output
 
-        # Check if user can access the graph
-        can_access_graph = agent.AgentGraph.userId == agent.userId
+        execution_count = len(executions)
+        success_rate: float | None = None
+        avg_correctness_score: float | None = None
+        if execution_count > 0:
+            success_count = sum(
+                1
+                for e in executions
+                if e.executionStatus == prisma.enums.AgentExecutionStatus.COMPLETED
+            )
+            success_rate = (success_count / execution_count) * 100
 
-        # Hard-coded to True until a method to check is implemented
+            correctness_scores = []
+            for e in executions:
+                if e.stats and isinstance(e.stats, dict):
+                    score = e.stats.get("correctness_score")
+                    if score is not None and isinstance(score, (int, float)):
+                        correctness_scores.append(float(score))
+            if correctness_scores:
+                avg_correctness_score = sum(correctness_scores) / len(
+                    correctness_scores
+                )
+
+        recent_executions: list[RecentExecution] = []
+        for e in executions:
+            exec_score: float | None = None
+            exec_summary: str | None = None
+            if e.stats and isinstance(e.stats, dict):
+                score = e.stats.get("correctness_score")
+                if score is not None and isinstance(score, (int, float)):
+                    exec_score = float(score)
+                summary = e.stats.get("activity_status")
+                if summary is not None and isinstance(summary, str):
+                    exec_summary = summary
+            exec_status = (
+                e.executionStatus.value
+                if hasattr(e.executionStatus, "value")
+                else str(e.executionStatus)
+            )
+            recent_executions.append(
+                RecentExecution(
+                    status=exec_status,
+                    correctness_score=exec_score,
+                    activity_summary=exec_summary,
+                )
+            )
+
+        can_access_graph = agent.AgentGraph.userId == agent.userId
         is_latest_version = True
 
-        # Build marketplace_listing if available
         marketplace_listing_data = None
         if store_listing and store_listing.ActiveVersion and profile:
             creator_data = MarketplaceListingCreator(
@@ -190,11 +249,15 @@ class LibraryAgent(pydantic.BaseModel):
             has_sensitive_action=graph.has_sensitive_action,
             trigger_setup_info=graph.trigger_setup_info,
             new_output=new_output,
+            execution_count=execution_count,
+            success_rate=success_rate,
+            avg_correctness_score=avg_correctness_score,
+            recent_executions=recent_executions,
             can_access_graph=can_access_graph,
             is_latest_version=is_latest_version,
             is_favorite=agent.isFavorite,
             recommended_schedule_cron=agent.AgentGraph.recommendedScheduleCron,
-            settings=GraphSettings.model_validate(agent.settings),
+            settings=_parse_settings(agent.settings),
             marketplace_listing=marketplace_listing_data,
         )
 
@@ -220,18 +283,15 @@ def _calculate_agent_status(
     if not executions:
         return AgentStatusResult(status=LibraryAgentStatus.COMPLETED, new_output=False)
 
-    # Track how many times each execution status appears
     status_counts = {status: 0 for status in prisma.enums.AgentExecutionStatus}
     new_output = False
 
     for execution in executions:
-        # Check if there's a completed run more recent than `recent_threshold`
         if execution.createdAt >= recent_threshold:
             if execution.executionStatus == prisma.enums.AgentExecutionStatus.COMPLETED:
                 new_output = True
         status_counts[execution.executionStatus] += 1
 
-    # Determine the final status based on counts
     if status_counts[prisma.enums.AgentExecutionStatus.FAILED] > 0:
         return AgentStatusResult(status=LibraryAgentStatus.ERROR, new_output=new_output)
     elif status_counts[prisma.enums.AgentExecutionStatus.QUEUED] > 0:
diff --git a/autogpt_platform/backend/backend/api/features/store/db.py b/autogpt_platform/backend/backend/api/features/store/db.py
index 956fdfa7da..87b72d6a9c 100644
--- a/autogpt_platform/backend/backend/api/features/store/db.py
+++ b/autogpt_platform/backend/backend/api/features/store/db.py
@@ -1,7 +1,7 @@
 import asyncio
 import logging
 from datetime import datetime, timezone
-from typing import Any, Literal
+from typing import Any, Literal, overload
 
 import fastapi
 import prisma.enums
@@ -11,8 +11,8 @@ import prisma.types
 
 from backend.data.db import transaction
 from backend.data.graph import (
-    GraphMeta,
     GraphModel,
+    GraphModelWithoutNodes,
     get_graph,
     get_graph_as_admin,
     get_sub_graphs,
@@ -112,6 +112,7 @@ async def get_store_agents(
                             description=agent["description"],
                             runs=agent["runs"],
                             rating=agent["rating"],
+                            agent_graph_id=agent.get("agentGraphId", ""),
                         )
                         store_agents.append(store_agent)
                     except Exception as e:
@@ -170,6 +171,7 @@ async def get_store_agents(
                         description=agent.description,
                         runs=agent.runs,
                         rating=agent.rating,
+                        agent_graph_id=agent.agentGraphId,
                     )
                     # Add to the list only if creation was successful
                     store_agents.append(store_agent)
@@ -332,7 +334,22 @@ async def get_store_agent_details(
         raise DatabaseError("Failed to fetch agent details") from e
 
 
-async def get_available_graph(store_listing_version_id: str) -> GraphMeta:
+@overload
+async def get_available_graph(
+    store_listing_version_id: str, hide_nodes: Literal[False]
+) -> GraphModel: ...
+
+
+@overload
+async def get_available_graph(
+    store_listing_version_id: str, hide_nodes: Literal[True] = True
+) -> GraphModelWithoutNodes: ...
+
+
+async def get_available_graph(
+    store_listing_version_id: str,
+    hide_nodes: bool = True,
+) -> GraphModelWithoutNodes | GraphModel:
     try:
         # Get avaialble, non-deleted store listing version
         store_listing_version = (
@@ -342,7 +359,7 @@ async def get_available_graph(store_listing_version_id: str) -> GraphMeta:
                     "isAvailable": True,
                     "isDeleted": False,
                 },
-                include={"AgentGraph": {"include": {"Nodes": True}}},
+                include={"AgentGraph": {"include": AGENT_GRAPH_INCLUDE}},
             )
         )
 
@@ -352,7 +369,9 @@ async def get_available_graph(store_listing_version_id: str) -> GraphMeta:
                 detail=f"Store listing version {store_listing_version_id} not found",
             )
 
-        return GraphModel.from_db(store_listing_version.AgentGraph).meta()
+        return (GraphModelWithoutNodes if hide_nodes else GraphModel).from_db(
+            store_listing_version.AgentGraph
+        )
 
     except Exception as e:
         logger.error(f"Error getting agent: {e}")
diff --git a/autogpt_platform/backend/backend/api/features/store/embeddings_e2e_test.py b/autogpt_platform/backend/backend/api/features/store/embeddings_e2e_test.py
index bae5b97cd6..86af457f50 100644
--- a/autogpt_platform/backend/backend/api/features/store/embeddings_e2e_test.py
+++ b/autogpt_platform/backend/backend/api/features/store/embeddings_e2e_test.py
@@ -454,6 +454,9 @@ async def test_unified_hybrid_search_pagination(
     cleanup_embeddings: list,
 ):
     """Test unified search pagination works correctly."""
+    # Use a unique search term to avoid matching other test data
+    unique_term = f"xyzpagtest{uuid.uuid4().hex[:8]}"
+
     # Create multiple items
     content_ids = []
     for i in range(5):
@@ -465,14 +468,14 @@ async def test_unified_hybrid_search_pagination(
             content_type=ContentType.BLOCK,
             content_id=content_id,
             embedding=mock_embedding,
-            searchable_text=f"pagination test item number {i}",
+            searchable_text=f"{unique_term} item number {i}",
             metadata={"index": i},
             user_id=None,
         )
 
     # Get first page
     page1_results, total1 = await unified_hybrid_search(
-        query="pagination test",
+        query=unique_term,
         content_types=[ContentType.BLOCK],
         page=1,
         page_size=2,
@@ -480,7 +483,7 @@ async def test_unified_hybrid_search_pagination(
 
     # Get second page
     page2_results, total2 = await unified_hybrid_search(
-        query="pagination test",
+        query=unique_term,
         content_types=[ContentType.BLOCK],
         page=2,
         page_size=2,
diff --git a/autogpt_platform/backend/backend/api/features/store/hybrid_search.py b/autogpt_platform/backend/backend/api/features/store/hybrid_search.py
index 8b0884bb24..b10bfbcc06 100644
--- a/autogpt_platform/backend/backend/api/features/store/hybrid_search.py
+++ b/autogpt_platform/backend/backend/api/features/store/hybrid_search.py
@@ -8,6 +8,7 @@ Includes BM25 reranking for improved lexical relevance.
 
 import logging
 import re
+import time
 from dataclasses import dataclass
 from typing import Any, Literal
 
@@ -362,7 +363,11 @@ async def unified_hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
     # Apply BM25 reranking
@@ -600,6 +605,7 @@ async def hybrid_search(
                 sa.featured,
                 sa.is_available,
                 sa.updated_at,
+                sa."agentGraphId",
                 -- Searchable text for BM25 reranking
                 COALESCE(sa.agent_name, '') || ' ' || COALESCE(sa.sub_heading, '') || ' ' || COALESCE(sa.description, '') as searchable_text,
                 -- Semantic score
@@ -659,6 +665,7 @@ async def hybrid_search(
                 featured,
                 is_available,
                 updated_at,
+                "agentGraphId",
                 searchable_text,
                 semantic_score,
                 lexical_score,
@@ -684,7 +691,11 @@ async def hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
 
@@ -716,6 +727,87 @@ async def hybrid_search_simple(
     return await hybrid_search(query=query, page=page, page_size=page_size)
 
 
+# ============================================================================
+# Diagnostics
+# ============================================================================
+
+# Rate limit: only log vector error diagnostics once per this interval
+_VECTOR_DIAG_INTERVAL_SECONDS = 60
+_last_vector_diag_time: float = 0
+
+
+async def _log_vector_error_diagnostics(error: Exception) -> None:
+    """Log diagnostic info when 'type vector does not exist' error occurs.
+
+    Note: Diagnostic queries use query_raw_with_schema which may run on a different
+    pooled connection than the one that failed. Session-level search_path can differ,
+    so these diagnostics show cluster-wide state, not necessarily the failed session.
+
+    Includes rate limiting to avoid log spam - only logs once per minute.
+    Caller should re-raise the error after calling this function.
+    """
+    global _last_vector_diag_time
+
+    # Check if this is the vector type error
+    error_str = str(error).lower()
+    if not (
+        "type" in error_str and "vector" in error_str and "does not exist" in error_str
+    ):
+        return
+
+    # Rate limit: only log once per interval
+    now = time.time()
+    if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS:
+        return
+    _last_vector_diag_time = now
+
+    try:
+        diagnostics: dict[str, object] = {}
+
+        try:
+            search_path_result = await query_raw_with_schema("SHOW search_path")
+            diagnostics["search_path"] = search_path_result
+        except Exception as e:
+            diagnostics["search_path"] = f"Error: {e}"
+
+        try:
+            schema_result = await query_raw_with_schema("SELECT current_schema()")
+            diagnostics["current_schema"] = schema_result
+        except Exception as e:
+            diagnostics["current_schema"] = f"Error: {e}"
+
+        try:
+            user_result = await query_raw_with_schema(
+                "SELECT current_user, session_user, current_database()"
+            )
+            diagnostics["user_info"] = user_result
+        except Exception as e:
+            diagnostics["user_info"] = f"Error: {e}"
+
+        try:
+            # Check pgvector extension installation (cluster-wide, stable info)
+            ext_result = await query_raw_with_schema(
+                "SELECT extname, extversion, nspname as schema "
+                "FROM pg_extension e "
+                "JOIN pg_namespace n ON e.extnamespace = n.oid "
+                "WHERE extname = 'vector'"
+            )
+            diagnostics["pgvector_extension"] = ext_result
+        except Exception as e:
+            diagnostics["pgvector_extension"] = f"Error: {e}"
+
+        logger.error(
+            f"Vector type error diagnostics:\n"
+            f"  Error: {error}\n"
+            f"  search_path: {diagnostics.get('search_path')}\n"
+            f"  current_schema: {diagnostics.get('current_schema')}\n"
+            f"  user_info: {diagnostics.get('user_info')}\n"
+            f"  pgvector_extension: {diagnostics.get('pgvector_extension')}"
+        )
+    except Exception as diag_error:
+        logger.error(f"Failed to collect vector error diagnostics: {diag_error}")
+
+
 # Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights
 # for existing code that expects the popularity parameter
 HybridSearchWeights = StoreAgentSearchWeights
diff --git a/autogpt_platform/backend/backend/api/features/store/image_gen.py b/autogpt_platform/backend/backend/api/features/store/image_gen.py
index 87b7b601df..087a7895ba 100644
--- a/autogpt_platform/backend/backend/api/features/store/image_gen.py
+++ b/autogpt_platform/backend/backend/api/features/store/image_gen.py
@@ -16,7 +16,7 @@ from backend.blocks.ideogram import (
     StyleType,
     UpscaleOption,
 )
-from backend.data.graph import BaseGraph
+from backend.data.graph import GraphBaseMeta
 from backend.data.model import CredentialsMetaInput, ProviderName
 from backend.integrations.credentials_store import ideogram_credentials
 from backend.util.request import Requests
@@ -34,14 +34,14 @@ class ImageStyle(str, Enum):
     DIGITAL_ART = "digital art"
 
 
-async def generate_agent_image(agent: BaseGraph | AgentGraph) -> io.BytesIO:
+async def generate_agent_image(agent: GraphBaseMeta | AgentGraph) -> io.BytesIO:
     if settings.config.use_agent_image_generation_v2:
         return await generate_agent_image_v2(graph=agent)
     else:
         return await generate_agent_image_v1(agent=agent)
 
 
-async def generate_agent_image_v2(graph: BaseGraph | AgentGraph) -> io.BytesIO:
+async def generate_agent_image_v2(graph: GraphBaseMeta | AgentGraph) -> io.BytesIO:
     """
     Generate an image for an agent using Ideogram model.
     Returns:
@@ -54,14 +54,17 @@ async def generate_agent_image_v2(graph: BaseGraph | AgentGraph) -> io.BytesIO:
     description = f"{name} ({graph.description})" if graph.description else name
 
     prompt = (
-        f"Create a visually striking retro-futuristic vector pop art illustration prominently featuring "
-        f'"{name}" in bold typography. The image clearly and literally depicts a {description}, '
-        f"along with recognizable objects directly associated with the primary function of a {name}. "
-        f"Ensure the imagery is concrete, intuitive, and immediately understandable, clearly conveying the "
-        f"purpose of a {name}. Maintain vibrant, limited-palette colors, sharp vector lines, geometric "
-        f"shapes, flat illustration techniques, and solid colors without gradients or shading. Preserve a "
-        f"retro-futuristic aesthetic influenced by mid-century futurism and 1960s psychedelia, "
-        f"prioritizing clear visual storytelling and thematic clarity above all else."
+        "Create a visually striking retro-futuristic vector pop art illustration "
+        f'prominently featuring "{name}" in bold typography. The image clearly and '
+        f"literally depicts a {description}, along with recognizable objects directly "
+        f"associated with the primary function of a {name}. "
+        f"Ensure the imagery is concrete, intuitive, and immediately understandable, "
+        f"clearly conveying the purpose of a {name}. "
+        "Maintain vibrant, limited-palette colors, sharp vector lines, "
+        "geometric shapes, flat illustration techniques, and solid colors "
+        "without gradients or shading. Preserve a retro-futuristic aesthetic "
+        "influenced by mid-century futurism and 1960s psychedelia, "
+        "prioritizing clear visual storytelling and thematic clarity above all else."
     )
 
     custom_colors = [
@@ -99,12 +102,12 @@ async def generate_agent_image_v2(graph: BaseGraph | AgentGraph) -> io.BytesIO:
     return io.BytesIO(response.content)
 
 
-async def generate_agent_image_v1(agent: BaseGraph | AgentGraph) -> io.BytesIO:
+async def generate_agent_image_v1(agent: GraphBaseMeta | AgentGraph) -> io.BytesIO:
     """
     Generate an image for an agent using Flux model via Replicate API.
 
     Args:
-        agent (Graph): The agent to generate an image for
+        agent (GraphBaseMeta | AgentGraph): The agent to generate an image for
 
     Returns:
         io.BytesIO: The generated image as bytes
@@ -114,7 +117,13 @@ async def generate_agent_image_v1(agent: BaseGraph | AgentGraph) -> io.BytesIO:
             raise ValueError("Missing Replicate API key in settings")
 
         # Construct prompt from agent details
-        prompt = f"Create a visually engaging app store thumbnail for the AI agent that highlights what it does in a clear and captivating way:\n- **Name**: {agent.name}\n- **Description**: {agent.description}\nFocus on showcasing its core functionality with an appealing design."
+        prompt = (
+            "Create a visually engaging app store thumbnail for the AI agent "
+            "that highlights what it does in a clear and captivating way:\n"
+            f"- **Name**: {agent.name}\n"
+            f"- **Description**: {agent.description}\n"
+            f"Focus on showcasing its core functionality with an appealing design."
+        )
 
         # Set up Replicate client
         client = ReplicateClient(api_token=settings.secrets.replicate_api_key)
diff --git a/autogpt_platform/backend/backend/api/features/store/model.py b/autogpt_platform/backend/backend/api/features/store/model.py
index a3310b96fc..d66b91807d 100644
--- a/autogpt_platform/backend/backend/api/features/store/model.py
+++ b/autogpt_platform/backend/backend/api/features/store/model.py
@@ -38,6 +38,7 @@ class StoreAgent(pydantic.BaseModel):
     description: str
     runs: int
     rating: float
+    agent_graph_id: str
 
 
 class StoreAgentsResponse(pydantic.BaseModel):
diff --git a/autogpt_platform/backend/backend/api/features/store/model_test.py b/autogpt_platform/backend/backend/api/features/store/model_test.py
index fd09a0cf77..c4109f4603 100644
--- a/autogpt_platform/backend/backend/api/features/store/model_test.py
+++ b/autogpt_platform/backend/backend/api/features/store/model_test.py
@@ -26,11 +26,13 @@ def test_store_agent():
         description="Test description",
         runs=50,
         rating=4.5,
+        agent_graph_id="test-graph-id",
     )
     assert agent.slug == "test-agent"
     assert agent.agent_name == "Test Agent"
     assert agent.runs == 50
     assert agent.rating == 4.5
+    assert agent.agent_graph_id == "test-graph-id"
 
 
 def test_store_agents_response():
@@ -46,6 +48,7 @@ def test_store_agents_response():
                 description="Test description",
                 runs=50,
                 rating=4.5,
+                agent_graph_id="test-graph-id",
             )
         ],
         pagination=store_model.Pagination(
diff --git a/autogpt_platform/backend/backend/api/features/store/routes.py b/autogpt_platform/backend/backend/api/features/store/routes.py
index 2f3c7bfb04..d93fe60f15 100644
--- a/autogpt_platform/backend/backend/api/features/store/routes.py
+++ b/autogpt_platform/backend/backend/api/features/store/routes.py
@@ -278,7 +278,7 @@ async def get_agent(
 )
 async def get_graph_meta_by_store_listing_version_id(
     store_listing_version_id: str,
-) -> backend.data.graph.GraphMeta:
+) -> backend.data.graph.GraphModelWithoutNodes:
     """
     Get Agent Graph from Store Listing Version ID.
     """
diff --git a/autogpt_platform/backend/backend/api/features/store/routes_test.py b/autogpt_platform/backend/backend/api/features/store/routes_test.py
index 36431c20ec..fcef3f845a 100644
--- a/autogpt_platform/backend/backend/api/features/store/routes_test.py
+++ b/autogpt_platform/backend/backend/api/features/store/routes_test.py
@@ -82,6 +82,7 @@ def test_get_agents_featured(
                 description="Featured agent description",
                 runs=100,
                 rating=4.5,
+                agent_graph_id="test-graph-1",
             )
         ],
         pagination=store_model.Pagination(
@@ -127,6 +128,7 @@ def test_get_agents_by_creator(
                 description="Creator agent description",
                 runs=50,
                 rating=4.0,
+                agent_graph_id="test-graph-2",
             )
         ],
         pagination=store_model.Pagination(
@@ -172,6 +174,7 @@ def test_get_agents_sorted(
                 description="Top agent description",
                 runs=1000,
                 rating=5.0,
+                agent_graph_id="test-graph-3",
             )
         ],
         pagination=store_model.Pagination(
@@ -217,6 +220,7 @@ def test_get_agents_search(
                 description="Specific search term description",
                 runs=75,
                 rating=4.2,
+                agent_graph_id="test-graph-search",
             )
         ],
         pagination=store_model.Pagination(
@@ -262,6 +266,7 @@ def test_get_agents_category(
                 description="Category agent description",
                 runs=60,
                 rating=4.1,
+                agent_graph_id="test-graph-category",
             )
         ],
         pagination=store_model.Pagination(
@@ -306,6 +311,7 @@ def test_get_agents_pagination(
                 description=f"Agent {i} description",
                 runs=i * 10,
                 rating=4.0,
+                agent_graph_id="test-graph-2",
             )
             for i in range(5)
         ],
diff --git a/autogpt_platform/backend/backend/api/features/store/test_cache_delete.py b/autogpt_platform/backend/backend/api/features/store/test_cache_delete.py
index dd9be1f4ab..298c51d47c 100644
--- a/autogpt_platform/backend/backend/api/features/store/test_cache_delete.py
+++ b/autogpt_platform/backend/backend/api/features/store/test_cache_delete.py
@@ -33,6 +33,7 @@ class TestCacheDeletion:
                     description="Test description",
                     runs=100,
                     rating=4.5,
+                    agent_graph_id="test-graph-id",
                 )
             ],
             pagination=Pagination(
diff --git a/autogpt_platform/backend/backend/api/features/v1.py b/autogpt_platform/backend/backend/api/features/v1.py
index 09d3759a65..a8610702cc 100644
--- a/autogpt_platform/backend/backend/api/features/v1.py
+++ b/autogpt_platform/backend/backend/api/features/v1.py
@@ -101,7 +101,6 @@ from backend.util.timezone_utils import (
 from backend.util.virus_scanner import scan_content_safe
 
 from .library import db as library_db
-from .library import model as library_model
 from .store.model import StoreAgentDetails
 
 
@@ -823,18 +822,16 @@ async def update_graph(
     graph: graph_db.Graph,
     user_id: Annotated[str, Security(get_user_id)],
 ) -> graph_db.GraphModel:
-    # Sanity check
     if graph.id and graph.id != graph_id:
         raise HTTPException(400, detail="Graph ID does not match ID in URI")
 
-    # Determine new version
     existing_versions = await graph_db.get_graph_all_versions(graph_id, user_id=user_id)
     if not existing_versions:
         raise HTTPException(404, detail=f"Graph #{graph_id} not found")
-    latest_version_number = max(g.version for g in existing_versions)
-    graph.version = latest_version_number + 1
 
+    graph.version = max(g.version for g in existing_versions) + 1
     current_active_version = next((v for v in existing_versions if v.is_active), None)
+
     graph = graph_db.make_graph_model(graph, user_id)
     graph.reassign_ids(user_id=user_id, reassign_graph_id=False)
     graph.validate_graph(for_run=False)
@@ -842,27 +839,23 @@ async def update_graph(
     new_graph_version = await graph_db.create_graph(graph, user_id=user_id)
 
     if new_graph_version.is_active:
-        # Keep the library agent up to date with the new active version
-        await _update_library_agent_version_and_settings(user_id, new_graph_version)
-
-        # Handle activation of the new graph first to ensure continuity
+        await library_db.update_library_agent_version_and_settings(
+            user_id, new_graph_version
+        )
         new_graph_version = await on_graph_activate(new_graph_version, user_id=user_id)
-        # Ensure new version is the only active version
         await graph_db.set_graph_active_version(
             graph_id=graph_id, version=new_graph_version.version, user_id=user_id
         )
         if current_active_version:
-            # Handle deactivation of the previously active version
             await on_graph_deactivate(current_active_version, user_id=user_id)
 
-    # Fetch new graph version *with sub-graphs* (needed for credentials input schema)
     new_graph_version_with_subgraphs = await graph_db.get_graph(
         graph_id,
         new_graph_version.version,
         user_id=user_id,
         include_subgraphs=True,
     )
-    assert new_graph_version_with_subgraphs  # make type checker happy
+    assert new_graph_version_with_subgraphs
     return new_graph_version_with_subgraphs
 
 
@@ -900,33 +893,15 @@ async def set_graph_active_version(
     )
 
     # Keep the library agent up to date with the new active version
-    await _update_library_agent_version_and_settings(user_id, new_active_graph)
+    await library_db.update_library_agent_version_and_settings(
+        user_id, new_active_graph
+    )
 
     if current_active_graph and current_active_graph.version != new_active_version:
         # Handle deactivation of the previously active version
         await on_graph_deactivate(current_active_graph, user_id=user_id)
 
 
-async def _update_library_agent_version_and_settings(
-    user_id: str, agent_graph: graph_db.GraphModel
-) -> library_model.LibraryAgent:
-    library = await library_db.update_agent_version_in_library(
-        user_id, agent_graph.id, agent_graph.version
-    )
-    updated_settings = GraphSettings.from_graph(
-        graph=agent_graph,
-        hitl_safe_mode=library.settings.human_in_the_loop_safe_mode,
-        sensitive_action_safe_mode=library.settings.sensitive_action_safe_mode,
-    )
-    if updated_settings != library.settings:
-        library = await library_db.update_library_agent(
-            library_agent_id=library.id,
-            user_id=user_id,
-            settings=updated_settings,
-        )
-    return library
-
-
 @v1_router.patch(
     path="/graphs/{graph_id}/settings",
     summary="Update graph settings",
diff --git a/autogpt_platform/backend/backend/api/rest_api.py b/autogpt_platform/backend/backend/api/rest_api.py
index b936312ce1..0eef76193e 100644
--- a/autogpt_platform/backend/backend/api/rest_api.py
+++ b/autogpt_platform/backend/backend/api/rest_api.py
@@ -40,6 +40,10 @@ import backend.data.user
 import backend.integrations.webhooks.utils
 import backend.util.service
 import backend.util.settings
+from backend.api.features.chat.completion_consumer import (
+    start_completion_consumer,
+    stop_completion_consumer,
+)
 from backend.blocks.llm import DEFAULT_LLM_MODEL
 from backend.data.model import Credentials
 from backend.integrations.providers import ProviderName
@@ -118,9 +122,21 @@ async def lifespan_context(app: fastapi.FastAPI):
     await backend.data.graph.migrate_llm_models(DEFAULT_LLM_MODEL)
     await backend.integrations.webhooks.utils.migrate_legacy_triggered_graphs()
 
+    # Start chat completion consumer for Redis Streams notifications
+    try:
+        await start_completion_consumer()
+    except Exception as e:
+        logger.warning(f"Could not start chat completion consumer: {e}")
+
     with launch_darkly_context():
         yield
 
+    # Stop chat completion consumer
+    try:
+        await stop_completion_consumer()
+    except Exception as e:
+        logger.warning(f"Error stopping chat completion consumer: {e}")
+
     try:
         await shutdown_cloud_storage_handler()
     except Exception as e:
diff --git a/autogpt_platform/backend/backend/api/ws_api.py b/autogpt_platform/backend/backend/api/ws_api.py
index b71fdb3526..e254d4b4db 100644
--- a/autogpt_platform/backend/backend/api/ws_api.py
+++ b/autogpt_platform/backend/backend/api/ws_api.py
@@ -66,18 +66,24 @@ async def event_broadcaster(manager: ConnectionManager):
     execution_bus = AsyncRedisExecutionEventBus()
     notification_bus = AsyncRedisNotificationEventBus()
 
-    async def execution_worker():
-        async for event in execution_bus.listen("*"):
-            await manager.send_execution_update(event)
+    try:
 
-    async def notification_worker():
-        async for notification in notification_bus.listen("*"):
-            await manager.send_notification(
-                user_id=notification.user_id,
-                payload=notification.payload,
-            )
+        async def execution_worker():
+            async for event in execution_bus.listen("*"):
+                await manager.send_execution_update(event)
 
-    await asyncio.gather(execution_worker(), notification_worker())
+        async def notification_worker():
+            async for notification in notification_bus.listen("*"):
+                await manager.send_notification(
+                    user_id=notification.user_id,
+                    payload=notification.payload,
+                )
+
+        await asyncio.gather(execution_worker(), notification_worker())
+    finally:
+        # Ensure PubSub connections are closed on any exit to prevent leaks
+        await execution_bus.close()
+        await notification_bus.close()
 
 
 async def authenticate_websocket(websocket: WebSocket) -> str:
diff --git a/autogpt_platform/backend/backend/blocks/elevenlabs/_auth.py b/autogpt_platform/backend/backend/blocks/elevenlabs/_auth.py
new file mode 100644
index 0000000000..b823627b43
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/elevenlabs/_auth.py
@@ -0,0 +1,28 @@
+"""ElevenLabs integration blocks - test credentials and shared utilities."""
+
+from typing import Literal
+
+from pydantic import SecretStr
+
+from backend.data.model import APIKeyCredentials, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="elevenlabs",
+    api_key=SecretStr("mock-elevenlabs-api-key"),
+    title="Mock ElevenLabs API key",
+    expires_at=None,
+)
+
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+ElevenLabsCredentials = APIKeyCredentials
+ElevenLabsCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.ELEVENLABS], Literal["api_key"]
+]
diff --git a/autogpt_platform/backend/backend/blocks/encoder_block.py b/autogpt_platform/backend/backend/blocks/encoder_block.py
new file mode 100644
index 0000000000..b60a4ae828
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/encoder_block.py
@@ -0,0 +1,77 @@
+"""Text encoding block for converting special characters to escape sequences."""
+
+import codecs
+
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.model import SchemaField
+
+
+class TextEncoderBlock(Block):
+    """
+    Encodes a string by converting special characters into escape sequences.
+
+    This block is the inverse of TextDecoderBlock. It takes text containing
+    special characters (like newlines, tabs, etc.) and converts them into
+    their escape sequence representations (e.g., newline becomes \\n).
+    """
+
+    class Input(BlockSchemaInput):
+        """Input schema for TextEncoderBlock."""
+
+        text: str = SchemaField(
+            description="A string containing special characters to be encoded",
+            placeholder="Your text with newlines and quotes to encode",
+        )
+
+    class Output(BlockSchemaOutput):
+        """Output schema for TextEncoderBlock."""
+
+        encoded_text: str = SchemaField(
+            description="The encoded text with special characters converted to escape sequences"
+        )
+        error: str = SchemaField(description="Error message if encoding fails")
+
+    def __init__(self):
+        super().__init__(
+            id="5185f32e-4b65-4ecf-8fbb-873f003f09d6",
+            description="Encodes a string by converting special characters into escape sequences",
+            categories={BlockCategory.TEXT},
+            input_schema=TextEncoderBlock.Input,
+            output_schema=TextEncoderBlock.Output,
+            test_input={
+                "text": """Hello
+World!
+This is a "quoted" string."""
+            },
+            test_output=[
+                (
+                    "encoded_text",
+                    """Hello\\nWorld!\\nThis is a "quoted" string.""",
+                )
+            ],
+        )
+
+    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        """
+        Encode the input text by converting special characters to escape sequences.
+
+        Args:
+            input_data: The input containing the text to encode.
+            **kwargs: Additional keyword arguments (unused).
+
+        Yields:
+            The encoded text with escape sequences, or an error message if encoding fails.
+        """
+        try:
+            encoded_text = codecs.encode(input_data.text, "unicode_escape").decode(
+                "utf-8"
+            )
+            yield "encoded_text", encoded_text
+        except Exception as e:
+            yield "error", f"Encoding error: {str(e)}"
diff --git a/autogpt_platform/backend/backend/blocks/exa/websets.py b/autogpt_platform/backend/backend/blocks/exa/websets.py
index 069911af66..ce623ad410 100644
--- a/autogpt_platform/backend/backend/blocks/exa/websets.py
+++ b/autogpt_platform/backend/backend/blocks/exa/websets.py
@@ -478,7 +478,7 @@ class ExaCreateOrFindWebsetBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         try:
-            webset = aexa.websets.get(id=input_data.external_id)
+            webset = await aexa.websets.get(id=input_data.external_id)
             webset_result = Webset.model_validate(webset.model_dump(by_alias=True))
 
             yield "webset", webset_result
@@ -494,7 +494,7 @@ class ExaCreateOrFindWebsetBlock(Block):
                         count=input_data.search_count,
                     )
 
-                webset = aexa.websets.create(
+                webset = await aexa.websets.create(
                     params=CreateWebsetParameters(
                         search=search_params,
                         external_id=input_data.external_id,
@@ -554,7 +554,7 @@ class ExaUpdateWebsetBlock(Block):
         if input_data.metadata is not None:
             payload["metadata"] = input_data.metadata
 
-        sdk_webset = aexa.websets.update(id=input_data.webset_id, params=payload)
+        sdk_webset = await aexa.websets.update(id=input_data.webset_id, params=payload)
 
         status_str = (
             sdk_webset.status.value
@@ -617,7 +617,7 @@ class ExaListWebsetsBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        response = aexa.websets.list(
+        response = await aexa.websets.list(
             cursor=input_data.cursor,
             limit=input_data.limit,
         )
@@ -678,7 +678,7 @@ class ExaGetWebsetBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_webset = aexa.websets.get(id=input_data.webset_id)
+        sdk_webset = await aexa.websets.get(id=input_data.webset_id)
 
         status_str = (
             sdk_webset.status.value
@@ -748,7 +748,7 @@ class ExaDeleteWebsetBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_webset = aexa.websets.delete(id=input_data.webset_id)
+        deleted_webset = await aexa.websets.delete(id=input_data.webset_id)
 
         status_str = (
             deleted_webset.status.value
@@ -798,7 +798,7 @@ class ExaCancelWebsetBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        canceled_webset = aexa.websets.cancel(id=input_data.webset_id)
+        canceled_webset = await aexa.websets.cancel(id=input_data.webset_id)
 
         status_str = (
             canceled_webset.status.value
@@ -968,7 +968,7 @@ class ExaPreviewWebsetBlock(Block):
                 entity["description"] = input_data.entity_description
             payload["entity"] = entity
 
-        sdk_preview = aexa.websets.preview(params=payload)
+        sdk_preview = await aexa.websets.preview(params=payload)
 
         preview = PreviewWebsetModel.from_sdk(sdk_preview)
 
@@ -1051,7 +1051,7 @@ class ExaWebsetStatusBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         status = (
             webset.status.value
@@ -1185,7 +1185,7 @@ class ExaWebsetSummaryBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         # Extract basic info
         webset_id = webset.id
@@ -1211,7 +1211,7 @@ class ExaWebsetSummaryBlock(Block):
         total_items = 0
 
         if input_data.include_sample_items and input_data.sample_size > 0:
-            items_response = aexa.websets.items.list(
+            items_response = await aexa.websets.items.list(
                 webset_id=input_data.webset_id, limit=input_data.sample_size
             )
             sample_items_data = [
@@ -1362,7 +1362,7 @@ class ExaWebsetReadyCheckBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         # Get webset details
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         status = (
             webset.status.value
diff --git a/autogpt_platform/backend/backend/blocks/exa/websets_enrichment.py b/autogpt_platform/backend/backend/blocks/exa/websets_enrichment.py
index 242700713a..f136b996b9 100644
--- a/autogpt_platform/backend/backend/blocks/exa/websets_enrichment.py
+++ b/autogpt_platform/backend/backend/blocks/exa/websets_enrichment.py
@@ -202,7 +202,7 @@ class ExaCreateEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_enrichment = aexa.websets.enrichments.create(
+        sdk_enrichment = await aexa.websets.enrichments.create(
             webset_id=input_data.webset_id, params=payload
         )
 
@@ -223,7 +223,7 @@ class ExaCreateEnrichmentBlock(Block):
             items_enriched = 0
 
             while time.time() - poll_start < input_data.polling_timeout:
-                current_enrich = aexa.websets.enrichments.get(
+                current_enrich = await aexa.websets.enrichments.get(
                     webset_id=input_data.webset_id, id=enrichment_id
                 )
                 current_status = (
@@ -234,7 +234,7 @@ class ExaCreateEnrichmentBlock(Block):
 
                 if current_status in ["completed", "failed", "cancelled"]:
                     # Estimate items from webset searches
-                    webset = aexa.websets.get(id=input_data.webset_id)
+                    webset = await aexa.websets.get(id=input_data.webset_id)
                     if webset.searches:
                         for search in webset.searches:
                             if search.progress:
@@ -329,7 +329,7 @@ class ExaGetEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_enrichment = aexa.websets.enrichments.get(
+        sdk_enrichment = await aexa.websets.enrichments.get(
             webset_id=input_data.webset_id, id=input_data.enrichment_id
         )
 
@@ -474,7 +474,7 @@ class ExaDeleteEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_enrichment = aexa.websets.enrichments.delete(
+        deleted_enrichment = await aexa.websets.enrichments.delete(
             webset_id=input_data.webset_id, id=input_data.enrichment_id
         )
 
@@ -525,13 +525,13 @@ class ExaCancelEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        canceled_enrichment = aexa.websets.enrichments.cancel(
+        canceled_enrichment = await aexa.websets.enrichments.cancel(
             webset_id=input_data.webset_id, id=input_data.enrichment_id
         )
 
         # Try to estimate how many items were enriched before cancellation
         items_enriched = 0
-        items_response = aexa.websets.items.list(
+        items_response = await aexa.websets.items.list(
             webset_id=input_data.webset_id, limit=100
         )
 
diff --git a/autogpt_platform/backend/backend/blocks/exa/websets_import_export.py b/autogpt_platform/backend/backend/blocks/exa/websets_import_export.py
index 9a91c7a4d0..e5a6137ed4 100644
--- a/autogpt_platform/backend/backend/blocks/exa/websets_import_export.py
+++ b/autogpt_platform/backend/backend/blocks/exa/websets_import_export.py
@@ -222,7 +222,7 @@ class ExaCreateImportBlock(Block):
     def _create_test_mock():
         """Create test mocks for the AsyncExa SDK."""
         from datetime import datetime
-        from unittest.mock import MagicMock
+        from unittest.mock import AsyncMock, MagicMock
 
         # Create mock SDK import object
         mock_import = MagicMock()
@@ -247,7 +247,7 @@ class ExaCreateImportBlock(Block):
         return {
             "_get_client": lambda *args, **kwargs: MagicMock(
                 websets=MagicMock(
-                    imports=MagicMock(create=lambda *args, **kwargs: mock_import)
+                    imports=MagicMock(create=AsyncMock(return_value=mock_import))
                 )
             )
         }
@@ -294,7 +294,7 @@ class ExaCreateImportBlock(Block):
         if input_data.metadata:
             payload["metadata"] = input_data.metadata
 
-        sdk_import = aexa.websets.imports.create(
+        sdk_import = await aexa.websets.imports.create(
             params=payload, csv_data=input_data.csv_data
         )
 
@@ -360,7 +360,7 @@ class ExaGetImportBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_import = aexa.websets.imports.get(import_id=input_data.import_id)
+        sdk_import = await aexa.websets.imports.get(import_id=input_data.import_id)
 
         import_obj = ImportModel.from_sdk(sdk_import)
 
@@ -426,7 +426,7 @@ class ExaListImportsBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        response = aexa.websets.imports.list(
+        response = await aexa.websets.imports.list(
             cursor=input_data.cursor,
             limit=input_data.limit,
         )
@@ -474,7 +474,9 @@ class ExaDeleteImportBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_import = aexa.websets.imports.delete(import_id=input_data.import_id)
+        deleted_import = await aexa.websets.imports.delete(
+            import_id=input_data.import_id
+        )
 
         yield "import_id", deleted_import.id
         yield "success", "true"
@@ -573,14 +575,14 @@ class ExaExportWebsetBlock(Block):
             }
         )
 
-        # Create mock iterator
-        mock_items = [mock_item1, mock_item2]
+        # Create async iterator for list_all
+        async def async_item_iterator(*args, **kwargs):
+            for item in [mock_item1, mock_item2]:
+                yield item
 
         return {
             "_get_client": lambda *args, **kwargs: MagicMock(
-                websets=MagicMock(
-                    items=MagicMock(list_all=lambda *args, **kwargs: iter(mock_items))
-                )
+                websets=MagicMock(items=MagicMock(list_all=async_item_iterator))
             )
         }
 
@@ -602,7 +604,7 @@ class ExaExportWebsetBlock(Block):
                 webset_id=input_data.webset_id, limit=input_data.max_items
             )
 
-            for sdk_item in item_iterator:
+            async for sdk_item in item_iterator:
                 if len(all_items) >= input_data.max_items:
                     break
 
diff --git a/autogpt_platform/backend/backend/blocks/exa/websets_items.py b/autogpt_platform/backend/backend/blocks/exa/websets_items.py
index 3c5d0d51a8..cdccb89b8d 100644
--- a/autogpt_platform/backend/backend/blocks/exa/websets_items.py
+++ b/autogpt_platform/backend/backend/blocks/exa/websets_items.py
@@ -178,7 +178,7 @@ class ExaGetWebsetItemBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_item = aexa.websets.items.get(
+        sdk_item = await aexa.websets.items.get(
             webset_id=input_data.webset_id, id=input_data.item_id
         )
 
@@ -269,7 +269,7 @@ class ExaListWebsetItemsBlock(Block):
             response = None
 
             while time.time() - start_time < input_data.wait_timeout:
-                response = aexa.websets.items.list(
+                response = await aexa.websets.items.list(
                     webset_id=input_data.webset_id,
                     cursor=input_data.cursor,
                     limit=input_data.limit,
@@ -282,13 +282,13 @@ class ExaListWebsetItemsBlock(Block):
                 interval = min(interval * 1.2, 10)
 
             if not response:
-                response = aexa.websets.items.list(
+                response = await aexa.websets.items.list(
                     webset_id=input_data.webset_id,
                     cursor=input_data.cursor,
                     limit=input_data.limit,
                 )
         else:
-            response = aexa.websets.items.list(
+            response = await aexa.websets.items.list(
                 webset_id=input_data.webset_id,
                 cursor=input_data.cursor,
                 limit=input_data.limit,
@@ -340,7 +340,7 @@ class ExaDeleteWebsetItemBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_item = aexa.websets.items.delete(
+        deleted_item = await aexa.websets.items.delete(
             webset_id=input_data.webset_id, id=input_data.item_id
         )
 
@@ -408,7 +408,7 @@ class ExaBulkWebsetItemsBlock(Block):
             webset_id=input_data.webset_id, limit=input_data.max_items
         )
 
-        for sdk_item in item_iterator:
+        async for sdk_item in item_iterator:
             if len(all_items) >= input_data.max_items:
                 break
 
@@ -475,7 +475,7 @@ class ExaWebsetItemsSummaryBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         entity_type = "unknown"
         if webset.searches:
@@ -495,7 +495,7 @@ class ExaWebsetItemsSummaryBlock(Block):
         # Get sample items if requested
         sample_items: List[WebsetItemModel] = []
         if input_data.sample_size > 0:
-            items_response = aexa.websets.items.list(
+            items_response = await aexa.websets.items.list(
                 webset_id=input_data.webset_id, limit=input_data.sample_size
             )
             # Convert to our stable models
@@ -569,7 +569,7 @@ class ExaGetNewItemsBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         # Get items starting from cursor
-        response = aexa.websets.items.list(
+        response = await aexa.websets.items.list(
             webset_id=input_data.webset_id,
             cursor=input_data.since_cursor,
             limit=input_data.max_items,
diff --git a/autogpt_platform/backend/backend/blocks/exa/websets_monitor.py b/autogpt_platform/backend/backend/blocks/exa/websets_monitor.py
index b10fd65310..8f9836965e 100644
--- a/autogpt_platform/backend/backend/blocks/exa/websets_monitor.py
+++ b/autogpt_platform/backend/backend/blocks/exa/websets_monitor.py
@@ -233,7 +233,7 @@ class ExaCreateMonitorBlock(Block):
     def _create_test_mock():
         """Create test mocks for the AsyncExa SDK."""
         from datetime import datetime
-        from unittest.mock import MagicMock
+        from unittest.mock import AsyncMock, MagicMock
 
         # Create mock SDK monitor object
         mock_monitor = MagicMock()
@@ -263,7 +263,7 @@ class ExaCreateMonitorBlock(Block):
         return {
             "_get_client": lambda *args, **kwargs: MagicMock(
                 websets=MagicMock(
-                    monitors=MagicMock(create=lambda *args, **kwargs: mock_monitor)
+                    monitors=MagicMock(create=AsyncMock(return_value=mock_monitor))
                 )
             )
         }
@@ -320,7 +320,7 @@ class ExaCreateMonitorBlock(Block):
         if input_data.metadata:
             payload["metadata"] = input_data.metadata
 
-        sdk_monitor = aexa.websets.monitors.create(params=payload)
+        sdk_monitor = await aexa.websets.monitors.create(params=payload)
 
         monitor = MonitorModel.from_sdk(sdk_monitor)
 
@@ -384,7 +384,7 @@ class ExaGetMonitorBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_monitor = aexa.websets.monitors.get(monitor_id=input_data.monitor_id)
+        sdk_monitor = await aexa.websets.monitors.get(monitor_id=input_data.monitor_id)
 
         monitor = MonitorModel.from_sdk(sdk_monitor)
 
@@ -476,7 +476,7 @@ class ExaUpdateMonitorBlock(Block):
         if input_data.metadata is not None:
             payload["metadata"] = input_data.metadata
 
-        sdk_monitor = aexa.websets.monitors.update(
+        sdk_monitor = await aexa.websets.monitors.update(
             monitor_id=input_data.monitor_id, params=payload
         )
 
@@ -522,7 +522,9 @@ class ExaDeleteMonitorBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_monitor = aexa.websets.monitors.delete(monitor_id=input_data.monitor_id)
+        deleted_monitor = await aexa.websets.monitors.delete(
+            monitor_id=input_data.monitor_id
+        )
 
         yield "monitor_id", deleted_monitor.id
         yield "success", "true"
@@ -579,7 +581,7 @@ class ExaListMonitorsBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        response = aexa.websets.monitors.list(
+        response = await aexa.websets.monitors.list(
             cursor=input_data.cursor,
             limit=input_data.limit,
             webset_id=input_data.webset_id,
diff --git a/autogpt_platform/backend/backend/blocks/exa/websets_polling.py b/autogpt_platform/backend/backend/blocks/exa/websets_polling.py
index 4aa86567b4..f4168f1446 100644
--- a/autogpt_platform/backend/backend/blocks/exa/websets_polling.py
+++ b/autogpt_platform/backend/backend/blocks/exa/websets_polling.py
@@ -121,7 +121,7 @@ class ExaWaitForWebsetBlock(Block):
                 WebsetTargetStatus.IDLE,
                 WebsetTargetStatus.ANY_COMPLETE,
             ]:
-                final_webset = aexa.websets.wait_until_idle(
+                final_webset = await aexa.websets.wait_until_idle(
                     id=input_data.webset_id,
                     timeout=input_data.timeout,
                     poll_interval=input_data.check_interval,
@@ -164,7 +164,7 @@ class ExaWaitForWebsetBlock(Block):
                 interval = input_data.check_interval
                 while time.time() - start_time < input_data.timeout:
                     # Get current webset status
-                    webset = aexa.websets.get(id=input_data.webset_id)
+                    webset = await aexa.websets.get(id=input_data.webset_id)
                     current_status = (
                         webset.status.value
                         if hasattr(webset.status, "value")
@@ -209,7 +209,7 @@ class ExaWaitForWebsetBlock(Block):
 
                 # Timeout reached
                 elapsed = time.time() - start_time
-                webset = aexa.websets.get(id=input_data.webset_id)
+                webset = await aexa.websets.get(id=input_data.webset_id)
                 final_status = (
                     webset.status.value
                     if hasattr(webset.status, "value")
@@ -345,7 +345,7 @@ class ExaWaitForSearchBlock(Block):
         try:
             while time.time() - start_time < input_data.timeout:
                 # Get current search status using SDK
-                search = aexa.websets.searches.get(
+                search = await aexa.websets.searches.get(
                     webset_id=input_data.webset_id, id=input_data.search_id
                 )
 
@@ -401,7 +401,7 @@ class ExaWaitForSearchBlock(Block):
             elapsed = time.time() - start_time
 
             # Get last known status
-            search = aexa.websets.searches.get(
+            search = await aexa.websets.searches.get(
                 webset_id=input_data.webset_id, id=input_data.search_id
             )
             final_status = (
@@ -503,7 +503,7 @@ class ExaWaitForEnrichmentBlock(Block):
         try:
             while time.time() - start_time < input_data.timeout:
                 # Get current enrichment status using SDK
-                enrichment = aexa.websets.enrichments.get(
+                enrichment = await aexa.websets.enrichments.get(
                     webset_id=input_data.webset_id, id=input_data.enrichment_id
                 )
 
@@ -548,7 +548,7 @@ class ExaWaitForEnrichmentBlock(Block):
             elapsed = time.time() - start_time
 
             # Get last known status
-            enrichment = aexa.websets.enrichments.get(
+            enrichment = await aexa.websets.enrichments.get(
                 webset_id=input_data.webset_id, id=input_data.enrichment_id
             )
             final_status = (
@@ -575,7 +575,7 @@ class ExaWaitForEnrichmentBlock(Block):
     ) -> tuple[list[SampleEnrichmentModel], int]:
         """Get sample enriched data and count."""
         # Get a few items to see enrichment results using SDK
-        response = aexa.websets.items.list(webset_id=webset_id, limit=5)
+        response = await aexa.websets.items.list(webset_id=webset_id, limit=5)
 
         sample_data: list[SampleEnrichmentModel] = []
         enriched_count = 0
diff --git a/autogpt_platform/backend/backend/blocks/exa/websets_search.py b/autogpt_platform/backend/backend/blocks/exa/websets_search.py
index ff0974f021..77184b6cdf 100644
--- a/autogpt_platform/backend/backend/blocks/exa/websets_search.py
+++ b/autogpt_platform/backend/backend/blocks/exa/websets_search.py
@@ -317,7 +317,7 @@ class ExaCreateWebsetSearchBlock(Block):
 
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_search = aexa.websets.searches.create(
+        sdk_search = await aexa.websets.searches.create(
             webset_id=input_data.webset_id, params=payload
         )
 
@@ -350,7 +350,7 @@ class ExaCreateWebsetSearchBlock(Block):
             poll_start = time.time()
 
             while time.time() - poll_start < input_data.polling_timeout:
-                current_search = aexa.websets.searches.get(
+                current_search = await aexa.websets.searches.get(
                     webset_id=input_data.webset_id, id=search_id
                 )
                 current_status = (
@@ -442,7 +442,7 @@ class ExaGetWebsetSearchBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_search = aexa.websets.searches.get(
+        sdk_search = await aexa.websets.searches.get(
             webset_id=input_data.webset_id, id=input_data.search_id
         )
 
@@ -523,7 +523,7 @@ class ExaCancelWebsetSearchBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        canceled_search = aexa.websets.searches.cancel(
+        canceled_search = await aexa.websets.searches.cancel(
             webset_id=input_data.webset_id, id=input_data.search_id
         )
 
@@ -604,7 +604,7 @@ class ExaFindOrCreateSearchBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         # Get webset to check existing searches
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         # Look for existing search with same query
         existing_search = None
@@ -636,7 +636,7 @@ class ExaFindOrCreateSearchBlock(Block):
             if input_data.entity_type != SearchEntityType.AUTO:
                 payload["entity"] = {"type": input_data.entity_type.value}
 
-            sdk_search = aexa.websets.searches.create(
+            sdk_search = await aexa.websets.searches.create(
                 webset_id=input_data.webset_id, params=payload
             )
 
diff --git a/autogpt_platform/backend/backend/blocks/human_in_the_loop.py b/autogpt_platform/backend/backend/blocks/human_in_the_loop.py
index 568ac4b33f..d31f90ec81 100644
--- a/autogpt_platform/backend/backend/blocks/human_in_the_loop.py
+++ b/autogpt_platform/backend/backend/blocks/human_in_the_loop.py
@@ -21,43 +21,71 @@ logger = logging.getLogger(__name__)
 
 class HumanInTheLoopBlock(Block):
     """
-    This block pauses execution and waits for human approval or modification of the data.
+    Pauses execution and waits for human approval or rejection of the data.
 
-    When executed, it creates a pending review entry and sets the node execution status
-    to REVIEW. The execution will remain paused until a human user either:
-    - Approves the data (with or without modifications)
-    - Rejects the data
+    When executed, this block creates a pending review entry and sets the node execution
+    status to REVIEW. The execution remains paused until a human user either approves
+    or rejects the data.
 
-    This is useful for workflows that require human validation or intervention before
-    proceeding to the next steps.
+    **How it works:**
+    - The input data is presented to a human reviewer
+    - The reviewer can approve or reject (and optionally modify the data if editable)
+    - On approval: the data flows out through the `approved_data` output pin
+    - On rejection: the data flows out through the `rejected_data` output pin
+
+    **Important:** The output pins yield the actual data itself, NOT status strings.
+    The approval/rejection decision determines WHICH output pin fires, not the value.
+    You do NOT need to compare the output to "APPROVED" or "REJECTED" - simply connect
+    downstream blocks to the appropriate output pin for each case.
+
+    **Example usage:**
+    - Connect `approved_data` → next step in your workflow (data was approved)
+    - Connect `rejected_data` → error handling or notification (data was rejected)
     """
 
     class Input(BlockSchemaInput):
-        data: Any = SchemaField(description="The data to be reviewed by a human user")
+        data: Any = SchemaField(
+            description="The data to be reviewed by a human user. "
+            "This exact data will be passed through to either approved_data or "
+            "rejected_data output based on the reviewer's decision."
+        )
         name: str = SchemaField(
-            description="A descriptive name for what this data represents",
+            description="A descriptive name for what this data represents. "
+            "This helps the reviewer understand what they are reviewing.",
         )
         editable: bool = SchemaField(
-            description="Whether the human reviewer can edit the data",
+            description="Whether the human reviewer can edit the data before "
+            "approving or rejecting it",
             default=True,
             advanced=True,
         )
 
     class Output(BlockSchemaOutput):
         approved_data: Any = SchemaField(
-            description="The data when approved (may be modified by reviewer)"
+            description="Outputs the input data when the reviewer APPROVES it. "
+            "The value is the actual data itself (not a status string like 'APPROVED'). "
+            "If the reviewer edited the data, this contains the modified version. "
+            "Connect downstream blocks here for the 'approved' workflow path."
         )
         rejected_data: Any = SchemaField(
-            description="The data when rejected (may be modified by reviewer)"
+            description="Outputs the input data when the reviewer REJECTS it. "
+            "The value is the actual data itself (not a status string like 'REJECTED'). "
+            "If the reviewer edited the data, this contains the modified version. "
+            "Connect downstream blocks here for the 'rejected' workflow path."
         )
         review_message: str = SchemaField(
-            description="Any message provided by the reviewer", default=""
+            description="Optional message provided by the reviewer explaining their "
+            "decision. Only outputs when the reviewer provides a message; "
+            "this pin does not fire if no message was given.",
+            default="",
         )
 
     def __init__(self):
         super().__init__(
             id="8b2a7b3c-6e9d-4a5f-8c1b-2e3f4a5b6c7d",
-            description="Pause execution and wait for human approval or modification of data",
+            description="Pause execution for human review. Data flows through "
+            "approved_data or rejected_data output based on the reviewer's decision. "
+            "Outputs contain the actual data, not status strings.",
             categories={BlockCategory.BASIC},
             input_schema=HumanInTheLoopBlock.Input,
             output_schema=HumanInTheLoopBlock.Output,
diff --git a/autogpt_platform/backend/backend/blocks/linear/_api.py b/autogpt_platform/backend/backend/blocks/linear/_api.py
index 477b8a209c..ea609d515a 100644
--- a/autogpt_platform/backend/backend/blocks/linear/_api.py
+++ b/autogpt_platform/backend/backend/blocks/linear/_api.py
@@ -162,8 +162,16 @@ class LinearClient:
                 "searchTerm": team_name,
             }
 
-            team_id = await self.query(query, variables)
-            return team_id["teams"]["nodes"][0]["id"]
+            result = await self.query(query, variables)
+            nodes = result["teams"]["nodes"]
+
+            if not nodes:
+                raise LinearAPIException(
+                    f"Team '{team_name}' not found. Check the team name or key and try again.",
+                    status_code=404,
+                )
+
+            return nodes[0]["id"]
         except LinearAPIException as e:
             raise e
 
@@ -240,17 +248,44 @@ class LinearClient:
         except LinearAPIException as e:
             raise e
 
-    async def try_search_issues(self, term: str) -> list[Issue]:
+    async def try_search_issues(
+        self,
+        term: str,
+        max_results: int = 10,
+        team_id: str | None = None,
+    ) -> list[Issue]:
         try:
             query = """
-                query SearchIssues($term: String!, $includeComments: Boolean!) {
-                    searchIssues(term: $term, includeComments: $includeComments) {
+                query SearchIssues(
+                    $term: String!,
+                    $first: Int,
+                    $teamId: String
+                ) {
+                    searchIssues(
+                        term: $term,
+                        first: $first,
+                        teamId: $teamId
+                    ) {
                         nodes {
                             id
                             identifier
                             title
                             description
                             priority
+                            createdAt
+                            state {
+                                id
+                                name
+                                type
+                            }
+                            project {
+                                id
+                                name
+                            }
+                            assignee {
+                                id
+                                name
+                            }
                         }
                     }
                 }
@@ -258,7 +293,8 @@ class LinearClient:
 
             variables: dict[str, Any] = {
                 "term": term,
-                "includeComments": True,
+                "first": max_results,
+                "teamId": team_id,
             }
 
             issues = await self.query(query, variables)
diff --git a/autogpt_platform/backend/backend/blocks/linear/issues.py b/autogpt_platform/backend/backend/blocks/linear/issues.py
index baac01214c..165178f8ee 100644
--- a/autogpt_platform/backend/backend/blocks/linear/issues.py
+++ b/autogpt_platform/backend/backend/blocks/linear/issues.py
@@ -17,7 +17,7 @@ from ._config import (
     LinearScope,
     linear,
 )
-from .models import CreateIssueResponse, Issue
+from .models import CreateIssueResponse, Issue, State
 
 
 class LinearCreateIssueBlock(Block):
@@ -135,9 +135,20 @@ class LinearSearchIssuesBlock(Block):
             description="Linear credentials with read permissions",
             required_scopes={LinearScope.READ},
         )
+        max_results: int = SchemaField(
+            description="Maximum number of results to return",
+            default=10,
+            ge=1,
+            le=100,
+        )
+        team_name: str | None = SchemaField(
+            description="Optional team name to filter results (e.g., 'Internal', 'Open Source')",
+            default=None,
+        )
 
     class Output(BlockSchemaOutput):
         issues: list[Issue] = SchemaField(description="List of issues")
+        error: str = SchemaField(description="Error message if the search failed")
 
     def __init__(self):
         super().__init__(
@@ -145,8 +156,11 @@ class LinearSearchIssuesBlock(Block):
             description="Searches for issues on Linear",
             input_schema=self.Input,
             output_schema=self.Output,
+            categories={BlockCategory.PRODUCTIVITY, BlockCategory.ISSUE_TRACKING},
             test_input={
                 "term": "Test issue",
+                "max_results": 10,
+                "team_name": None,
                 "credentials": TEST_CREDENTIALS_INPUT_OAUTH,
             },
             test_credentials=TEST_CREDENTIALS_OAUTH,
@@ -156,10 +170,14 @@ class LinearSearchIssuesBlock(Block):
                     [
                         Issue(
                             id="abc123",
-                            identifier="abc123",
+                            identifier="TST-123",
                             title="Test issue",
                             description="Test description",
                             priority=1,
+                            state=State(
+                                id="state1", name="In Progress", type="started"
+                            ),
+                            createdAt="2026-01-15T10:00:00.000Z",
                         )
                     ],
                 )
@@ -168,10 +186,12 @@ class LinearSearchIssuesBlock(Block):
                 "search_issues": lambda *args, **kwargs: [
                     Issue(
                         id="abc123",
-                        identifier="abc123",
+                        identifier="TST-123",
                         title="Test issue",
                         description="Test description",
                         priority=1,
+                        state=State(id="state1", name="In Progress", type="started"),
+                        createdAt="2026-01-15T10:00:00.000Z",
                     )
                 ]
             },
@@ -181,10 +201,22 @@ class LinearSearchIssuesBlock(Block):
     async def search_issues(
         credentials: OAuth2Credentials | APIKeyCredentials,
         term: str,
+        max_results: int = 10,
+        team_name: str | None = None,
     ) -> list[Issue]:
         client = LinearClient(credentials=credentials)
-        response: list[Issue] = await client.try_search_issues(term=term)
-        return response
+
+        # Resolve team name to ID if provided
+        # Raises LinearAPIException with descriptive message if team not found
+        team_id: str | None = None
+        if team_name:
+            team_id = await client.try_get_team_by_name(team_name=team_name)
+
+        return await client.try_search_issues(
+            term=term,
+            max_results=max_results,
+            team_id=team_id,
+        )
 
     async def run(
         self,
@@ -196,7 +228,10 @@ class LinearSearchIssuesBlock(Block):
         """Execute the issue search"""
         try:
             issues = await self.search_issues(
-                credentials=credentials, term=input_data.term
+                credentials=credentials,
+                term=input_data.term,
+                max_results=input_data.max_results,
+                team_name=input_data.team_name,
             )
             yield "issues", issues
         except LinearAPIException as e:
diff --git a/autogpt_platform/backend/backend/blocks/linear/models.py b/autogpt_platform/backend/backend/blocks/linear/models.py
index bfeaa13656..dd1f603459 100644
--- a/autogpt_platform/backend/backend/blocks/linear/models.py
+++ b/autogpt_platform/backend/backend/blocks/linear/models.py
@@ -36,12 +36,21 @@ class Project(BaseModel):
     content: str | None = None
 
 
+class State(BaseModel):
+    id: str
+    name: str
+    type: str | None = (
+        None  # Workflow state type (e.g., "triage", "backlog", "started", "completed", "canceled")
+    )
+
+
 class Issue(BaseModel):
     id: str
     identifier: str
     title: str
     description: str | None
     priority: int
+    state: State | None = None
     project: Project | None = None
     createdAt: str | None = None
     comments: list[Comment] | None = None
diff --git a/autogpt_platform/backend/backend/blocks/llm.py b/autogpt_platform/backend/backend/blocks/llm.py
index fdcd7f3568..7a020593d7 100644
--- a/autogpt_platform/backend/backend/blocks/llm.py
+++ b/autogpt_platform/backend/backend/blocks/llm.py
@@ -32,7 +32,7 @@ from backend.data.model import (
 from backend.integrations.providers import ProviderName
 from backend.util import json
 from backend.util.logging import TruncatedLogger
-from backend.util.prompt import compress_prompt, estimate_token_count
+from backend.util.prompt import compress_context, estimate_token_count
 from backend.util.text import TextFormatter
 
 logger = TruncatedLogger(logging.getLogger(__name__), "[LLM-Block]")
@@ -115,7 +115,7 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     CLAUDE_4_5_OPUS = "claude-opus-4-5-20251101"
     CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
     CLAUDE_4_5_HAIKU = "claude-haiku-4-5-20251001"
-    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
+    CLAUDE_4_6_OPUS = "claude-opus-4-6"
     CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
     # AI/ML API models
     AIML_API_QWEN2_5_72B = "Qwen/Qwen2.5-72B-Instruct-Turbo"
@@ -271,6 +271,9 @@ MODEL_METADATA = {
     LlmModel.CLAUDE_4_SONNET: ModelMetadata(
         "anthropic", 200000, 64000, "Claude Sonnet 4", "Anthropic", "Anthropic", 2
     ),  # claude-4-sonnet-20250514
+    LlmModel.CLAUDE_4_6_OPUS: ModelMetadata(
+        "anthropic", 200000, 128000, "Claude Opus 4.6", "Anthropic", "Anthropic", 3
+    ),  # claude-opus-4-6
     LlmModel.CLAUDE_4_5_OPUS: ModelMetadata(
         "anthropic", 200000, 64000, "Claude Opus 4.5", "Anthropic", "Anthropic", 3
     ),  # claude-opus-4-5-20251101
@@ -280,9 +283,6 @@ MODEL_METADATA = {
     LlmModel.CLAUDE_4_5_HAIKU: ModelMetadata(
         "anthropic", 200000, 64000, "Claude Haiku 4.5", "Anthropic", "Anthropic", 2
     ),  # claude-haiku-4-5-20251001
-    LlmModel.CLAUDE_3_7_SONNET: ModelMetadata(
-        "anthropic", 200000, 64000, "Claude 3.7 Sonnet", "Anthropic", "Anthropic", 2
-    ),  # claude-3-7-sonnet-20250219
     LlmModel.CLAUDE_3_HAIKU: ModelMetadata(
         "anthropic", 200000, 4096, "Claude 3 Haiku", "Anthropic", "Anthropic", 1
     ),  # claude-3-haiku-20240307
@@ -531,12 +531,12 @@ class LLMResponse(BaseModel):
 
 def convert_openai_tool_fmt_to_anthropic(
     openai_tools: list[dict] | None = None,
-) -> Iterable[ToolParam] | anthropic.NotGiven:
+) -> Iterable[ToolParam] | anthropic.Omit:
     """
     Convert OpenAI tool format to Anthropic tool format.
     """
     if not openai_tools or len(openai_tools) == 0:
-        return anthropic.NOT_GIVEN
+        return anthropic.omit
 
     anthropic_tools = []
     for tool in openai_tools:
@@ -596,10 +596,10 @@ def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
 
 def get_parallel_tool_calls_param(
     llm_model: LlmModel, parallel_tool_calls: bool | None
-):
+) -> bool | openai.Omit:
     """Get the appropriate parallel_tool_calls parameter for OpenAI-compatible APIs."""
     if llm_model.startswith("o") or parallel_tool_calls is None:
-        return openai.NOT_GIVEN
+        return openai.omit
     return parallel_tool_calls
 
 
@@ -638,11 +638,18 @@ async def llm_call(
     context_window = llm_model.context_window
 
     if compress_prompt_to_fit:
-        prompt = compress_prompt(
+        result = await compress_context(
             messages=prompt,
             target_tokens=llm_model.context_window // 2,
-            lossy_ok=True,
+            client=None,  # Truncation-only, no LLM summarization
+            reserve=0,  # Caller handles response token budget separately
         )
+        if result.error:
+            logger.warning(
+                f"Prompt compression did not meet target: {result.error}. "
+                f"Proceeding with {result.token_count} tokens."
+            )
+        prompt = result.messages
 
     # Calculate available tokens based on context window and input length
     estimated_input_tokens = estimate_token_count(prompt)
diff --git a/autogpt_platform/backend/backend/blocks/media.py b/autogpt_platform/backend/backend/blocks/media.py
deleted file mode 100644
index a8d145bc64..0000000000
--- a/autogpt_platform/backend/backend/blocks/media.py
+++ /dev/null
@@ -1,246 +0,0 @@
-import os
-import tempfile
-from typing import Optional
-
-from moviepy.audio.io.AudioFileClip import AudioFileClip
-from moviepy.video.fx.Loop import Loop
-from moviepy.video.io.VideoFileClip import VideoFileClip
-
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
-from backend.data.execution import ExecutionContext
-from backend.data.model import SchemaField
-from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
-
-
-class MediaDurationBlock(Block):
-
-    class Input(BlockSchemaInput):
-        media_in: MediaFileType = SchemaField(
-            description="Media input (URL, data URI, or local path)."
-        )
-        is_video: bool = SchemaField(
-            description="Whether the media is a video (True) or audio (False).",
-            default=True,
-        )
-
-    class Output(BlockSchemaOutput):
-        duration: float = SchemaField(
-            description="Duration of the media file (in seconds)."
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="d8b91fd4-da26-42d4-8ecb-8b196c6d84b6",
-            description="Block to get the duration of a media file.",
-            categories={BlockCategory.MULTIMEDIA},
-            input_schema=MediaDurationBlock.Input,
-            output_schema=MediaDurationBlock.Output,
-        )
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        execution_context: ExecutionContext,
-        **kwargs,
-    ) -> BlockOutput:
-        # 1) Store the input media locally
-        local_media_path = await store_media_file(
-            file=input_data.media_in,
-            execution_context=execution_context,
-            return_format="for_local_processing",
-        )
-        assert execution_context.graph_exec_id is not None
-        media_abspath = get_exec_file_path(
-            execution_context.graph_exec_id, local_media_path
-        )
-
-        # 2) Load the clip
-        if input_data.is_video:
-            clip = VideoFileClip(media_abspath)
-        else:
-            clip = AudioFileClip(media_abspath)
-
-        yield "duration", clip.duration
-
-
-class LoopVideoBlock(Block):
-    """
-    Block for looping (repeating) a video clip until a given duration or number of loops.
-    """
-
-    class Input(BlockSchemaInput):
-        video_in: MediaFileType = SchemaField(
-            description="The input video (can be a URL, data URI, or local path)."
-        )
-        # Provide EITHER a `duration` or `n_loops` or both. We'll demonstrate `duration`.
-        duration: Optional[float] = SchemaField(
-            description="Target duration (in seconds) to loop the video to. If omitted, defaults to no looping.",
-            default=None,
-            ge=0.0,
-        )
-        n_loops: Optional[int] = SchemaField(
-            description="Number of times to repeat the video. If omitted, defaults to 1 (no repeat).",
-            default=None,
-            ge=1,
-        )
-
-    class Output(BlockSchemaOutput):
-        video_out: str = SchemaField(
-            description="Looped video returned either as a relative path or a data URI."
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="8bf9eef6-5451-4213-b265-25306446e94b",
-            description="Block to loop a video to a given duration or number of repeats.",
-            categories={BlockCategory.MULTIMEDIA},
-            input_schema=LoopVideoBlock.Input,
-            output_schema=LoopVideoBlock.Output,
-        )
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        execution_context: ExecutionContext,
-        **kwargs,
-    ) -> BlockOutput:
-        assert execution_context.graph_exec_id is not None
-        assert execution_context.node_exec_id is not None
-        graph_exec_id = execution_context.graph_exec_id
-        node_exec_id = execution_context.node_exec_id
-
-        # 1) Store the input video locally
-        local_video_path = await store_media_file(
-            file=input_data.video_in,
-            execution_context=execution_context,
-            return_format="for_local_processing",
-        )
-        input_abspath = get_exec_file_path(graph_exec_id, local_video_path)
-
-        # 2) Load the clip
-        clip = VideoFileClip(input_abspath)
-
-        # 3) Apply the loop effect
-        looped_clip = clip
-        if input_data.duration:
-            # Loop until we reach the specified duration
-            looped_clip = looped_clip.with_effects([Loop(duration=input_data.duration)])
-        elif input_data.n_loops:
-            looped_clip = looped_clip.with_effects([Loop(n=input_data.n_loops)])
-        else:
-            raise ValueError("Either 'duration' or 'n_loops' must be provided.")
-
-        assert isinstance(looped_clip, VideoFileClip)
-
-        # 4) Save the looped output
-        output_filename = MediaFileType(
-            f"{node_exec_id}_looped_{os.path.basename(local_video_path)}"
-        )
-        output_abspath = get_exec_file_path(graph_exec_id, output_filename)
-
-        looped_clip = looped_clip.with_audio(clip.audio)
-        looped_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
-
-        # Return output - for_block_output returns workspace:// if available, else data URI
-        video_out = await store_media_file(
-            file=output_filename,
-            execution_context=execution_context,
-            return_format="for_block_output",
-        )
-
-        yield "video_out", video_out
-
-
-class AddAudioToVideoBlock(Block):
-    """
-    Block that adds (attaches) an audio track to an existing video.
-    Optionally scale the volume of the new track.
-    """
-
-    class Input(BlockSchemaInput):
-        video_in: MediaFileType = SchemaField(
-            description="Video input (URL, data URI, or local path)."
-        )
-        audio_in: MediaFileType = SchemaField(
-            description="Audio input (URL, data URI, or local path)."
-        )
-        volume: float = SchemaField(
-            description="Volume scale for the newly attached audio track (1.0 = original).",
-            default=1.0,
-        )
-
-    class Output(BlockSchemaOutput):
-        video_out: MediaFileType = SchemaField(
-            description="Final video (with attached audio), as a path or data URI."
-        )
-
-    def __init__(self):
-        super().__init__(
-            id="3503748d-62b6-4425-91d6-725b064af509",
-            description="Block to attach an audio file to a video file using moviepy.",
-            categories={BlockCategory.MULTIMEDIA},
-            input_schema=AddAudioToVideoBlock.Input,
-            output_schema=AddAudioToVideoBlock.Output,
-        )
-
-    async def run(
-        self,
-        input_data: Input,
-        *,
-        execution_context: ExecutionContext,
-        **kwargs,
-    ) -> BlockOutput:
-        assert execution_context.graph_exec_id is not None
-        assert execution_context.node_exec_id is not None
-        graph_exec_id = execution_context.graph_exec_id
-        node_exec_id = execution_context.node_exec_id
-
-        # 1) Store the inputs locally
-        local_video_path = await store_media_file(
-            file=input_data.video_in,
-            execution_context=execution_context,
-            return_format="for_local_processing",
-        )
-        local_audio_path = await store_media_file(
-            file=input_data.audio_in,
-            execution_context=execution_context,
-            return_format="for_local_processing",
-        )
-
-        abs_temp_dir = os.path.join(tempfile.gettempdir(), "exec_file", graph_exec_id)
-        video_abspath = os.path.join(abs_temp_dir, local_video_path)
-        audio_abspath = os.path.join(abs_temp_dir, local_audio_path)
-
-        # 2) Load video + audio with moviepy
-        video_clip = VideoFileClip(video_abspath)
-        audio_clip = AudioFileClip(audio_abspath)
-        # Optionally scale volume
-        if input_data.volume != 1.0:
-            audio_clip = audio_clip.with_volume_scaled(input_data.volume)
-
-        # 3) Attach the new audio track
-        final_clip = video_clip.with_audio(audio_clip)
-
-        # 4) Write to output file
-        output_filename = MediaFileType(
-            f"{node_exec_id}_audio_attached_{os.path.basename(local_video_path)}"
-        )
-        output_abspath = os.path.join(abs_temp_dir, output_filename)
-        final_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
-
-        # 5) Return output - for_block_output returns workspace:// if available, else data URI
-        video_out = await store_media_file(
-            file=output_filename,
-            execution_context=execution_context,
-            return_format="for_block_output",
-        )
-
-        yield "video_out", video_out
diff --git a/autogpt_platform/backend/backend/blocks/stagehand/blocks.py b/autogpt_platform/backend/backend/blocks/stagehand/blocks.py
index be1d736962..91c096ffe4 100644
--- a/autogpt_platform/backend/backend/blocks/stagehand/blocks.py
+++ b/autogpt_platform/backend/backend/blocks/stagehand/blocks.py
@@ -83,7 +83,7 @@ class StagehandRecommendedLlmModel(str, Enum):
     GPT41_MINI = "gpt-4.1-mini-2025-04-14"
 
     # Anthropic
-    CLAUDE_3_7_SONNET = "claude-3-7-sonnet-20250219"
+    CLAUDE_4_5_SONNET = "claude-sonnet-4-5-20250929"
 
     @property
     def provider_name(self) -> str:
@@ -137,7 +137,7 @@ class StagehandObserveBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -182,10 +182,7 @@ class StagehandObserveBlock(Block):
         **kwargs,
     ) -> BlockOutput:
 
-        logger.info(f"OBSERVE: Stagehand credentials: {stagehand_credentials}")
-        logger.info(
-            f"OBSERVE: Model credentials: {model_credentials} for provider {model_credentials.provider} secret: {model_credentials.api_key.get_secret_value()}"
-        )
+        logger.debug(f"OBSERVE: Using model provider {model_credentials.provider}")
 
         with disable_signal_handling():
             stagehand = Stagehand(
@@ -230,7 +227,7 @@ class StagehandActBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -282,10 +279,7 @@ class StagehandActBlock(Block):
         **kwargs,
     ) -> BlockOutput:
 
-        logger.info(f"ACT: Stagehand credentials: {stagehand_credentials}")
-        logger.info(
-            f"ACT: Model credentials: {model_credentials} for provider {model_credentials.provider} secret: {model_credentials.api_key.get_secret_value()}"
-        )
+        logger.debug(f"ACT: Using model provider {model_credentials.provider}")
 
         with disable_signal_handling():
             stagehand = Stagehand(
@@ -330,7 +324,7 @@ class StagehandExtractBlock(Block):
         model: StagehandRecommendedLlmModel = SchemaField(
             title="LLM Model",
             description="LLM to use for Stagehand (provider is inferred)",
-            default=StagehandRecommendedLlmModel.CLAUDE_3_7_SONNET,
+            default=StagehandRecommendedLlmModel.CLAUDE_4_5_SONNET,
             advanced=False,
         )
         model_credentials: AICredentials = AICredentialsField()
@@ -370,10 +364,7 @@ class StagehandExtractBlock(Block):
         **kwargs,
     ) -> BlockOutput:
 
-        logger.info(f"EXTRACT: Stagehand credentials: {stagehand_credentials}")
-        logger.info(
-            f"EXTRACT: Model credentials: {model_credentials} for provider {model_credentials.provider} secret: {model_credentials.api_key.get_secret_value()}"
-        )
+        logger.debug(f"EXTRACT: Using model provider {model_credentials.provider}")
 
         with disable_signal_handling():
             stagehand = Stagehand(
diff --git a/autogpt_platform/backend/backend/blocks/test/test_text_encoder.py b/autogpt_platform/backend/backend/blocks/test/test_text_encoder.py
new file mode 100644
index 0000000000..1e9b9fed4f
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/test/test_text_encoder.py
@@ -0,0 +1,77 @@
+import pytest
+
+from backend.blocks.encoder_block import TextEncoderBlock
+
+
+@pytest.mark.asyncio
+async def test_text_encoder_basic():
+    """Test basic encoding of newlines and special characters."""
+    block = TextEncoderBlock()
+    result = []
+    async for output in block.run(TextEncoderBlock.Input(text="Hello\nWorld")):
+        result.append(output)
+
+    assert len(result) == 1
+    assert result[0][0] == "encoded_text"
+    assert result[0][1] == "Hello\\nWorld"
+
+
+@pytest.mark.asyncio
+async def test_text_encoder_multiple_escapes():
+    """Test encoding of multiple escape sequences."""
+    block = TextEncoderBlock()
+    result = []
+    async for output in block.run(
+        TextEncoderBlock.Input(text="Line1\nLine2\tTabbed\rCarriage")
+    ):
+        result.append(output)
+
+    assert len(result) == 1
+    assert result[0][0] == "encoded_text"
+    assert "\\n" in result[0][1]
+    assert "\\t" in result[0][1]
+    assert "\\r" in result[0][1]
+
+
+@pytest.mark.asyncio
+async def test_text_encoder_unicode():
+    """Test that unicode characters are handled correctly."""
+    block = TextEncoderBlock()
+    result = []
+    async for output in block.run(TextEncoderBlock.Input(text="Hello 世界\n")):
+        result.append(output)
+
+    assert len(result) == 1
+    assert result[0][0] == "encoded_text"
+    # Unicode characters should be escaped as \uXXXX sequences
+    assert "\\n" in result[0][1]
+
+
+@pytest.mark.asyncio
+async def test_text_encoder_empty_string():
+    """Test encoding of an empty string."""
+    block = TextEncoderBlock()
+    result = []
+    async for output in block.run(TextEncoderBlock.Input(text="")):
+        result.append(output)
+
+    assert len(result) == 1
+    assert result[0][0] == "encoded_text"
+    assert result[0][1] == ""
+
+
+@pytest.mark.asyncio
+async def test_text_encoder_error_handling():
+    """Test that encoding errors are handled gracefully."""
+    from unittest.mock import patch
+
+    block = TextEncoderBlock()
+    result = []
+
+    with patch("codecs.encode", side_effect=Exception("Mocked encoding error")):
+        async for output in block.run(TextEncoderBlock.Input(text="test")):
+            result.append(output)
+
+    assert len(result) == 1
+    assert result[0][0] == "error"
+    assert "Mocked encoding error" in result[0][1]
diff --git a/autogpt_platform/backend/backend/blocks/video/__init__.py b/autogpt_platform/backend/backend/blocks/video/__init__.py
new file mode 100644
index 0000000000..4974ae8a87
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/__init__.py
@@ -0,0 +1,37 @@
+"""Video editing blocks for AutoGPT Platform.
+
+This module provides blocks for:
+- Downloading videos from URLs (YouTube, Vimeo, news sites, direct links)
+- Clipping/trimming video segments
+- Concatenating multiple videos
+- Adding text overlays
+- Adding AI-generated narration
+- Getting media duration
+- Looping videos
+- Adding audio to videos
+
+Dependencies:
+- yt-dlp: For video downloading
+- moviepy: For video editing operations
+- elevenlabs: For AI narration (optional)
+"""
+
+from backend.blocks.video.add_audio import AddAudioToVideoBlock
+from backend.blocks.video.clip import VideoClipBlock
+from backend.blocks.video.concat import VideoConcatBlock
+from backend.blocks.video.download import VideoDownloadBlock
+from backend.blocks.video.duration import MediaDurationBlock
+from backend.blocks.video.loop import LoopVideoBlock
+from backend.blocks.video.narration import VideoNarrationBlock
+from backend.blocks.video.text_overlay import VideoTextOverlayBlock
+
+__all__ = [
+    "AddAudioToVideoBlock",
+    "LoopVideoBlock",
+    "MediaDurationBlock",
+    "VideoClipBlock",
+    "VideoConcatBlock",
+    "VideoDownloadBlock",
+    "VideoNarrationBlock",
+    "VideoTextOverlayBlock",
+]
diff --git a/autogpt_platform/backend/backend/blocks/video/_utils.py b/autogpt_platform/backend/backend/blocks/video/_utils.py
new file mode 100644
index 0000000000..9ebf195078
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/_utils.py
@@ -0,0 +1,131 @@
+"""Shared utilities for video blocks."""
+
+from __future__ import annotations
+
+import logging
+import os
+import re
+import subprocess
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+# Known operation tags added by video blocks
+_VIDEO_OPS = (
+    r"(?:clip|overlay|narrated|looped|concat|audio_attached|with_audio|narration)"
+)
+
+# Matches: {node_exec_id}_{operation}_ where node_exec_id contains a UUID
+_BLOCK_PREFIX_RE = re.compile(
+    r"^[a-zA-Z0-9_-]*"
+    r"[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}"
+    r"[a-zA-Z0-9_-]*"
+    r"_" + _VIDEO_OPS + r"_"
+)
+
+# Matches: a lone {node_exec_id}_ prefix (no operation keyword, e.g. download output)
+_UUID_PREFIX_RE = re.compile(
+    r"^[a-zA-Z0-9_-]*"
+    r"[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}"
+    r"[a-zA-Z0-9_-]*_"
+)
+
+
+def extract_source_name(input_path: str, max_length: int = 50) -> str:
+    """Extract the original source filename by stripping block-generated prefixes.
+
+    Iteratively removes {node_exec_id}_{operation}_ prefixes that accumulate
+    when chaining video blocks, recovering the original human-readable name.
+
+    Safe for plain filenames (no UUID -> no stripping).
+    Falls back to "video" if everything is stripped.
+    """
+    stem = Path(input_path).stem
+
+    # Pass 1: strip {node_exec_id}_{operation}_ prefixes iteratively
+    while _BLOCK_PREFIX_RE.match(stem):
+        stem = _BLOCK_PREFIX_RE.sub("", stem, count=1)
+
+    # Pass 2: strip a lone {node_exec_id}_ prefix (e.g. from download block)
+    if _UUID_PREFIX_RE.match(stem):
+        stem = _UUID_PREFIX_RE.sub("", stem, count=1)
+
+    if not stem:
+        return "video"
+
+    return stem[:max_length]
+
+
+def get_video_codecs(output_path: str) -> tuple[str, str]:
+    """Get appropriate video and audio codecs based on output file extension.
+
+    Args:
+        output_path: Path to the output file (used to determine extension)
+
+    Returns:
+        Tuple of (video_codec, audio_codec)
+
+    Codec mappings:
+        - .mp4: H.264 + AAC (universal compatibility)
+        - .webm: VP8 + Vorbis (web streaming)
+        - .mkv: H.264 + AAC (container supports many codecs)
+        - .mov: H.264 + AAC (Apple QuickTime, widely compatible)
+        - .m4v: H.264 + AAC (Apple iTunes/devices)
+        - .avi: MPEG-4 + MP3 (legacy Windows)
+    """
+    ext = os.path.splitext(output_path)[1].lower()
+
+    codec_map: dict[str, tuple[str, str]] = {
+        ".mp4": ("libx264", "aac"),
+        ".webm": ("libvpx", "libvorbis"),
+        ".mkv": ("libx264", "aac"),
+        ".mov": ("libx264", "aac"),
+        ".m4v": ("libx264", "aac"),
+        ".avi": ("mpeg4", "libmp3lame"),
+    }
+
+    return codec_map.get(ext, ("libx264", "aac"))
+
+
+def strip_chapters_inplace(video_path: str) -> None:
+    """Strip chapter metadata from a media file in-place using ffmpeg.
+
+    MoviePy 2.x crashes with IndexError when parsing files with embedded
+    chapter metadata (https://github.com/Zulko/moviepy/issues/2419).
+    This strips chapters without re-encoding.
+
+    Args:
+        video_path: Absolute path to the media file to strip chapters from.
+    """
+    base, ext = os.path.splitext(video_path)
+    tmp_path = base + ".tmp" + ext
+    try:
+        result = subprocess.run(
+            [
+                "ffmpeg",
+                "-y",
+                "-i",
+                video_path,
+                "-map_chapters",
+                "-1",
+                "-codec",
+                "copy",
+                tmp_path,
+            ],
+            capture_output=True,
+            text=True,
+            timeout=300,
+        )
+        if result.returncode != 0:
+            logger.warning(
+                "ffmpeg chapter strip failed (rc=%d): %s",
+                result.returncode,
+                result.stderr,
+            )
+            return
+        os.replace(tmp_path, video_path)
+    except FileNotFoundError:
+        logger.warning("ffmpeg not found; skipping chapter strip")
+    finally:
+        if os.path.exists(tmp_path):
+            os.unlink(tmp_path)
diff --git a/autogpt_platform/backend/backend/blocks/video/add_audio.py b/autogpt_platform/backend/backend/blocks/video/add_audio.py
new file mode 100644
index 0000000000..ebd4ab94f2
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/add_audio.py
@@ -0,0 +1,113 @@
+"""AddAudioToVideoBlock - Attach an audio track to a video file."""
+
+from moviepy.audio.io.AudioFileClip import AudioFileClip
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.blocks.video._utils import extract_source_name, strip_chapters_inplace
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class AddAudioToVideoBlock(Block):
+    """Add (attach) an audio track to an existing video."""
+
+    class Input(BlockSchemaInput):
+        video_in: MediaFileType = SchemaField(
+            description="Video input (URL, data URI, or local path)."
+        )
+        audio_in: MediaFileType = SchemaField(
+            description="Audio input (URL, data URI, or local path)."
+        )
+        volume: float = SchemaField(
+            description="Volume scale for the newly attached audio track (1.0 = original).",
+            default=1.0,
+        )
+
+    class Output(BlockSchemaOutput):
+        video_out: MediaFileType = SchemaField(
+            description="Final video (with attached audio), as a path or data URI."
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3503748d-62b6-4425-91d6-725b064af509",
+            description="Block to attach an audio file to a video file using moviepy.",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=AddAudioToVideoBlock.Input,
+            output_schema=AddAudioToVideoBlock.Output,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        execution_context: ExecutionContext,
+        **kwargs,
+    ) -> BlockOutput:
+        assert execution_context.graph_exec_id is not None
+        assert execution_context.node_exec_id is not None
+        graph_exec_id = execution_context.graph_exec_id
+        node_exec_id = execution_context.node_exec_id
+
+        # 1) Store the inputs locally
+        local_video_path = await store_media_file(
+            file=input_data.video_in,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+        local_audio_path = await store_media_file(
+            file=input_data.audio_in,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+
+        video_abspath = get_exec_file_path(graph_exec_id, local_video_path)
+        audio_abspath = get_exec_file_path(graph_exec_id, local_audio_path)
+
+        # 2) Load video + audio with moviepy
+        strip_chapters_inplace(video_abspath)
+        strip_chapters_inplace(audio_abspath)
+        video_clip = None
+        audio_clip = None
+        final_clip = None
+        try:
+            video_clip = VideoFileClip(video_abspath)
+            audio_clip = AudioFileClip(audio_abspath)
+            # Optionally scale volume
+            if input_data.volume != 1.0:
+                audio_clip = audio_clip.with_volume_scaled(input_data.volume)
+
+            # 3) Attach the new audio track
+            final_clip = video_clip.with_audio(audio_clip)
+
+            # 4) Write to output file
+            source = extract_source_name(local_video_path)
+            output_filename = MediaFileType(f"{node_exec_id}_with_audio_{source}.mp4")
+            output_abspath = get_exec_file_path(graph_exec_id, output_filename)
+            final_clip.write_videofile(
+                output_abspath, codec="libx264", audio_codec="aac"
+            )
+        finally:
+            if final_clip:
+                final_clip.close()
+            if audio_clip:
+                audio_clip.close()
+            if video_clip:
+                video_clip.close()
+
+        # 5) Return output - for_block_output returns workspace:// if available, else data URI
+        video_out = await store_media_file(
+            file=output_filename,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+
+        yield "video_out", video_out
diff --git a/autogpt_platform/backend/backend/blocks/video/clip.py b/autogpt_platform/backend/backend/blocks/video/clip.py
new file mode 100644
index 0000000000..05deea6530
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/clip.py
@@ -0,0 +1,167 @@
+"""VideoClipBlock - Extract a segment from a video file."""
+
+from typing import Literal
+
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.blocks.video._utils import (
+    extract_source_name,
+    get_video_codecs,
+    strip_chapters_inplace,
+)
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.exceptions import BlockExecutionError
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class VideoClipBlock(Block):
+    """Extract a time segment from a video."""
+
+    class Input(BlockSchemaInput):
+        video_in: MediaFileType = SchemaField(
+            description="Input video (URL, data URI, or local path)"
+        )
+        start_time: float = SchemaField(description="Start time in seconds", ge=0.0)
+        end_time: float = SchemaField(description="End time in seconds", ge=0.0)
+        output_format: Literal["mp4", "webm", "mkv", "mov"] = SchemaField(
+            description="Output format", default="mp4", advanced=True
+        )
+
+    class Output(BlockSchemaOutput):
+        video_out: MediaFileType = SchemaField(
+            description="Clipped video file (path or data URI)"
+        )
+        duration: float = SchemaField(description="Clip duration in seconds")
+
+    def __init__(self):
+        super().__init__(
+            id="8f539119-e580-4d86-ad41-86fbcb22abb1",
+            description="Extract a time segment from a video",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "video_in": "/tmp/test.mp4",
+                "start_time": 0.0,
+                "end_time": 10.0,
+            },
+            test_output=[("video_out", str), ("duration", float)],
+            test_mock={
+                "_clip_video": lambda *args: 10.0,
+                "_store_input_video": lambda *args, **kwargs: "test.mp4",
+                "_store_output_video": lambda *args, **kwargs: "clip_test.mp4",
+            },
+        )
+
+    async def _store_input_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store input video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+
+    async def _store_output_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store output video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+
+    def _clip_video(
+        self,
+        video_abspath: str,
+        output_abspath: str,
+        start_time: float,
+        end_time: float,
+    ) -> float:
+        """Extract a clip from a video. Extracted for testability."""
+        clip = None
+        subclip = None
+        try:
+            strip_chapters_inplace(video_abspath)
+            clip = VideoFileClip(video_abspath)
+            subclip = clip.subclipped(start_time, end_time)
+            video_codec, audio_codec = get_video_codecs(output_abspath)
+            subclip.write_videofile(
+                output_abspath, codec=video_codec, audio_codec=audio_codec
+            )
+            return subclip.duration
+        finally:
+            if subclip:
+                subclip.close()
+            if clip:
+                clip.close()
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        execution_context: ExecutionContext,
+        node_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        # Validate time range
+        if input_data.end_time <= input_data.start_time:
+            raise BlockExecutionError(
+                message=f"end_time ({input_data.end_time}) must be greater than start_time ({input_data.start_time})",
+                block_name=self.name,
+                block_id=str(self.id),
+            )
+
+        try:
+            assert execution_context.graph_exec_id is not None
+
+            # Store the input video locally
+            local_video_path = await self._store_input_video(
+                execution_context, input_data.video_in
+            )
+            video_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, local_video_path
+            )
+
+            # Build output path
+            source = extract_source_name(local_video_path)
+            output_filename = MediaFileType(
+                f"{node_exec_id}_clip_{source}.{input_data.output_format}"
+            )
+            output_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, output_filename
+            )
+
+            duration = self._clip_video(
+                video_abspath,
+                output_abspath,
+                input_data.start_time,
+                input_data.end_time,
+            )
+
+            # Return as workspace path or data URI based on context
+            video_out = await self._store_output_video(
+                execution_context, output_filename
+            )
+
+            yield "video_out", video_out
+            yield "duration", duration
+
+        except BlockExecutionError:
+            raise
+        except Exception as e:
+            raise BlockExecutionError(
+                message=f"Failed to clip video: {e}",
+                block_name=self.name,
+                block_id=str(self.id),
+            ) from e
diff --git a/autogpt_platform/backend/backend/blocks/video/concat.py b/autogpt_platform/backend/backend/blocks/video/concat.py
new file mode 100644
index 0000000000..b49854fb40
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/concat.py
@@ -0,0 +1,227 @@
+"""VideoConcatBlock - Concatenate multiple video clips into one."""
+
+from typing import Literal
+
+from moviepy import concatenate_videoclips
+from moviepy.video.fx import CrossFadeIn, CrossFadeOut, FadeIn, FadeOut
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.blocks.video._utils import (
+    extract_source_name,
+    get_video_codecs,
+    strip_chapters_inplace,
+)
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.exceptions import BlockExecutionError
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class VideoConcatBlock(Block):
+    """Merge multiple video clips into one continuous video."""
+
+    class Input(BlockSchemaInput):
+        videos: list[MediaFileType] = SchemaField(
+            description="List of video files to concatenate (in order)"
+        )
+        transition: Literal["none", "crossfade", "fade_black"] = SchemaField(
+            description="Transition between clips", default="none"
+        )
+        transition_duration: int = SchemaField(
+            description="Transition duration in seconds",
+            default=1,
+            ge=0,
+            advanced=True,
+        )
+        output_format: Literal["mp4", "webm", "mkv", "mov"] = SchemaField(
+            description="Output format", default="mp4", advanced=True
+        )
+
+    class Output(BlockSchemaOutput):
+        video_out: MediaFileType = SchemaField(
+            description="Concatenated video file (path or data URI)"
+        )
+        total_duration: float = SchemaField(description="Total duration in seconds")
+
+    def __init__(self):
+        super().__init__(
+            id="9b0f531a-1118-487f-aeec-3fa63ea8900a",
+            description="Merge multiple video clips into one continuous video",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "videos": ["/tmp/a.mp4", "/tmp/b.mp4"],
+            },
+            test_output=[
+                ("video_out", str),
+                ("total_duration", float),
+            ],
+            test_mock={
+                "_concat_videos": lambda *args: 20.0,
+                "_store_input_video": lambda *args, **kwargs: "test.mp4",
+                "_store_output_video": lambda *args, **kwargs: "concat_test.mp4",
+            },
+        )
+
+    async def _store_input_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store input video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+
+    async def _store_output_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store output video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+
+    def _concat_videos(
+        self,
+        video_abspaths: list[str],
+        output_abspath: str,
+        transition: str,
+        transition_duration: int,
+    ) -> float:
+        """Concatenate videos. Extracted for testability.
+
+        Returns:
+            Total duration of the concatenated video.
+        """
+        clips = []
+        faded_clips = []
+        final = None
+        try:
+            # Load clips
+            for v in video_abspaths:
+                strip_chapters_inplace(v)
+                clips.append(VideoFileClip(v))
+
+            # Validate transition_duration against shortest clip
+            if transition in {"crossfade", "fade_black"} and transition_duration > 0:
+                min_duration = min(c.duration for c in clips)
+                if transition_duration >= min_duration:
+                    raise BlockExecutionError(
+                        message=(
+                            f"transition_duration ({transition_duration}s) must be "
+                            f"shorter than the shortest clip ({min_duration:.2f}s)"
+                        ),
+                        block_name=self.name,
+                        block_id=str(self.id),
+                    )
+
+            if transition == "crossfade":
+                for i, clip in enumerate(clips):
+                    effects = []
+                    if i > 0:
+                        effects.append(CrossFadeIn(transition_duration))
+                    if i < len(clips) - 1:
+                        effects.append(CrossFadeOut(transition_duration))
+                    if effects:
+                        clip = clip.with_effects(effects)
+                    faded_clips.append(clip)
+                final = concatenate_videoclips(
+                    faded_clips,
+                    method="compose",
+                    padding=-transition_duration,
+                )
+            elif transition == "fade_black":
+                for clip in clips:
+                    faded = clip.with_effects(
+                        [FadeIn(transition_duration), FadeOut(transition_duration)]
+                    )
+                    faded_clips.append(faded)
+                final = concatenate_videoclips(faded_clips)
+            else:
+                final = concatenate_videoclips(clips)
+
+            video_codec, audio_codec = get_video_codecs(output_abspath)
+            final.write_videofile(
+                output_abspath, codec=video_codec, audio_codec=audio_codec
+            )
+
+            return final.duration
+        finally:
+            if final:
+                final.close()
+            for clip in faded_clips:
+                clip.close()
+            for clip in clips:
+                clip.close()
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        execution_context: ExecutionContext,
+        node_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        # Validate minimum clips
+        if len(input_data.videos) < 2:
+            raise BlockExecutionError(
+                message="At least 2 videos are required for concatenation",
+                block_name=self.name,
+                block_id=str(self.id),
+            )
+
+        try:
+            assert execution_context.graph_exec_id is not None
+
+            # Store all input videos locally
+            video_abspaths = []
+            for video in input_data.videos:
+                local_path = await self._store_input_video(execution_context, video)
+                video_abspaths.append(
+                    get_exec_file_path(execution_context.graph_exec_id, local_path)
+                )
+
+            # Build output path
+            source = (
+                extract_source_name(video_abspaths[0]) if video_abspaths else "video"
+            )
+            output_filename = MediaFileType(
+                f"{node_exec_id}_concat_{source}.{input_data.output_format}"
+            )
+            output_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, output_filename
+            )
+
+            total_duration = self._concat_videos(
+                video_abspaths,
+                output_abspath,
+                input_data.transition,
+                input_data.transition_duration,
+            )
+
+            # Return as workspace path or data URI based on context
+            video_out = await self._store_output_video(
+                execution_context, output_filename
+            )
+
+            yield "video_out", video_out
+            yield "total_duration", total_duration
+
+        except BlockExecutionError:
+            raise
+        except Exception as e:
+            raise BlockExecutionError(
+                message=f"Failed to concatenate videos: {e}",
+                block_name=self.name,
+                block_id=str(self.id),
+            ) from e
diff --git a/autogpt_platform/backend/backend/blocks/video/download.py b/autogpt_platform/backend/backend/blocks/video/download.py
new file mode 100644
index 0000000000..4046d5df42
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/download.py
@@ -0,0 +1,172 @@
+"""VideoDownloadBlock - Download video from URL (YouTube, Vimeo, news sites, direct links)."""
+
+import os
+import typing
+from typing import Literal
+
+import yt_dlp
+
+if typing.TYPE_CHECKING:
+    from yt_dlp import _Params
+
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.exceptions import BlockExecutionError
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class VideoDownloadBlock(Block):
+    """Download video from URL using yt-dlp."""
+
+    class Input(BlockSchemaInput):
+        url: str = SchemaField(
+            description="URL of the video to download (YouTube, Vimeo, direct link, etc.)",
+            placeholder="https://www.youtube.com/watch?v=...",
+        )
+        quality: Literal["best", "1080p", "720p", "480p", "audio_only"] = SchemaField(
+            description="Video quality preference", default="720p"
+        )
+        output_format: Literal["mp4", "webm", "mkv"] = SchemaField(
+            description="Output video format", default="mp4", advanced=True
+        )
+
+    class Output(BlockSchemaOutput):
+        video_file: MediaFileType = SchemaField(
+            description="Downloaded video (path or data URI)"
+        )
+        duration: float = SchemaField(description="Video duration in seconds")
+        title: str = SchemaField(description="Video title from source")
+        source_url: str = SchemaField(description="Original source URL")
+
+    def __init__(self):
+        super().__init__(
+            id="c35daabb-cd60-493b-b9ad-51f1fe4b50c4",
+            description="Download video from URL (YouTube, Vimeo, news sites, direct links)",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            disabled=True,  # Disable until we can sandbox yt-dlp and handle security implications
+            test_input={
+                "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
+                "quality": "480p",
+            },
+            test_output=[
+                ("video_file", str),
+                ("duration", float),
+                ("title", str),
+                ("source_url", str),
+            ],
+            test_mock={
+                "_download_video": lambda *args: (
+                    "video.mp4",
+                    212.0,
+                    "Test Video",
+                ),
+                "_store_output_video": lambda *args, **kwargs: "video.mp4",
+            },
+        )
+
+    async def _store_output_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store output video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+
+    def _get_format_string(self, quality: str) -> str:
+        formats = {
+            "best": "bestvideo+bestaudio/best",
+            "1080p": "bestvideo[height<=1080]+bestaudio/best[height<=1080]",
+            "720p": "bestvideo[height<=720]+bestaudio/best[height<=720]",
+            "480p": "bestvideo[height<=480]+bestaudio/best[height<=480]",
+            "audio_only": "bestaudio/best",
+        }
+        return formats.get(quality, formats["720p"])
+
+    def _download_video(
+        self,
+        url: str,
+        quality: str,
+        output_format: str,
+        output_dir: str,
+        node_exec_id: str,
+    ) -> tuple[str, float, str]:
+        """Download video. Extracted for testability."""
+        output_template = os.path.join(
+            output_dir, f"{node_exec_id}_%(title).50s.%(ext)s"
+        )
+
+        ydl_opts: "_Params" = {
+            "format": f"{self._get_format_string(quality)}/best",
+            "outtmpl": output_template,
+            "merge_output_format": output_format,
+            "quiet": True,
+            "no_warnings": True,
+        }
+
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            info = ydl.extract_info(url, download=True)
+            video_path = ydl.prepare_filename(info)
+
+            # Handle format conversion in filename
+            if not video_path.endswith(f".{output_format}"):
+                video_path = video_path.rsplit(".", 1)[0] + f".{output_format}"
+
+            # Return just the filename, not the full path
+            filename = os.path.basename(video_path)
+
+            return (
+                filename,
+                info.get("duration") or 0.0,
+                info.get("title") or "Unknown",
+            )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        execution_context: ExecutionContext,
+        node_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            assert execution_context.graph_exec_id is not None
+
+            # Get the exec file directory
+            output_dir = get_exec_file_path(execution_context.graph_exec_id, "")
+            os.makedirs(output_dir, exist_ok=True)
+
+            filename, duration, title = self._download_video(
+                input_data.url,
+                input_data.quality,
+                input_data.output_format,
+                output_dir,
+                node_exec_id,
+            )
+
+            # Return as workspace path or data URI based on context
+            video_out = await self._store_output_video(
+                execution_context, MediaFileType(filename)
+            )
+
+            yield "video_file", video_out
+            yield "duration", duration
+            yield "title", title
+            yield "source_url", input_data.url
+
+        except Exception as e:
+            raise BlockExecutionError(
+                message=f"Failed to download video: {e}",
+                block_name=self.name,
+                block_id=str(self.id),
+            ) from e
diff --git a/autogpt_platform/backend/backend/blocks/video/duration.py b/autogpt_platform/backend/backend/blocks/video/duration.py
new file mode 100644
index 0000000000..9e05d35b00
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/duration.py
@@ -0,0 +1,77 @@
+"""MediaDurationBlock - Get the duration of a media file."""
+
+from moviepy.audio.io.AudioFileClip import AudioFileClip
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.blocks.video._utils import strip_chapters_inplace
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class MediaDurationBlock(Block):
+    """Get the duration of a media file (video or audio)."""
+
+    class Input(BlockSchemaInput):
+        media_in: MediaFileType = SchemaField(
+            description="Media input (URL, data URI, or local path)."
+        )
+        is_video: bool = SchemaField(
+            description="Whether the media is a video (True) or audio (False).",
+            default=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        duration: float = SchemaField(
+            description="Duration of the media file (in seconds)."
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="d8b91fd4-da26-42d4-8ecb-8b196c6d84b6",
+            description="Block to get the duration of a media file.",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=MediaDurationBlock.Input,
+            output_schema=MediaDurationBlock.Output,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        execution_context: ExecutionContext,
+        **kwargs,
+    ) -> BlockOutput:
+        # 1) Store the input media locally
+        local_media_path = await store_media_file(
+            file=input_data.media_in,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+        assert execution_context.graph_exec_id is not None
+        media_abspath = get_exec_file_path(
+            execution_context.graph_exec_id, local_media_path
+        )
+
+        # 2) Strip chapters to avoid MoviePy crash, then load the clip
+        strip_chapters_inplace(media_abspath)
+        clip = None
+        try:
+            if input_data.is_video:
+                clip = VideoFileClip(media_abspath)
+            else:
+                clip = AudioFileClip(media_abspath)
+
+            duration = clip.duration
+        finally:
+            if clip:
+                clip.close()
+
+        yield "duration", duration
diff --git a/autogpt_platform/backend/backend/blocks/video/loop.py b/autogpt_platform/backend/backend/blocks/video/loop.py
new file mode 100644
index 0000000000..461610f713
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/loop.py
@@ -0,0 +1,115 @@
+"""LoopVideoBlock - Loop a video to a given duration or number of repeats."""
+
+from typing import Optional
+
+from moviepy.video.fx.Loop import Loop
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.blocks.video._utils import extract_source_name, strip_chapters_inplace
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class LoopVideoBlock(Block):
+    """Loop (repeat) a video clip until a given duration or number of loops."""
+
+    class Input(BlockSchemaInput):
+        video_in: MediaFileType = SchemaField(
+            description="The input video (can be a URL, data URI, or local path)."
+        )
+        duration: Optional[float] = SchemaField(
+            description="Target duration (in seconds) to loop the video to. Either duration or n_loops must be provided.",
+            default=None,
+            ge=0.0,
+            le=3600.0,  # Max 1 hour to prevent disk exhaustion
+        )
+        n_loops: Optional[int] = SchemaField(
+            description="Number of times to repeat the video. Either n_loops or duration must be provided.",
+            default=None,
+            ge=1,
+            le=10,  # Max 10 loops to prevent disk exhaustion
+        )
+
+    class Output(BlockSchemaOutput):
+        video_out: MediaFileType = SchemaField(
+            description="Looped video returned either as a relative path or a data URI."
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8bf9eef6-5451-4213-b265-25306446e94b",
+            description="Block to loop a video to a given duration or number of repeats.",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=LoopVideoBlock.Input,
+            output_schema=LoopVideoBlock.Output,
+        )
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        execution_context: ExecutionContext,
+        **kwargs,
+    ) -> BlockOutput:
+        assert execution_context.graph_exec_id is not None
+        assert execution_context.node_exec_id is not None
+        graph_exec_id = execution_context.graph_exec_id
+        node_exec_id = execution_context.node_exec_id
+
+        # 1) Store the input video locally
+        local_video_path = await store_media_file(
+            file=input_data.video_in,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+        input_abspath = get_exec_file_path(graph_exec_id, local_video_path)
+
+        # 2) Load the clip
+        strip_chapters_inplace(input_abspath)
+        clip = None
+        looped_clip = None
+        try:
+            clip = VideoFileClip(input_abspath)
+
+            # 3) Apply the loop effect
+            if input_data.duration:
+                # Loop until we reach the specified duration
+                looped_clip = clip.with_effects([Loop(duration=input_data.duration)])
+            elif input_data.n_loops:
+                looped_clip = clip.with_effects([Loop(n=input_data.n_loops)])
+            else:
+                raise ValueError("Either 'duration' or 'n_loops' must be provided.")
+
+            assert isinstance(looped_clip, VideoFileClip)
+
+            # 4) Save the looped output
+            source = extract_source_name(local_video_path)
+            output_filename = MediaFileType(f"{node_exec_id}_looped_{source}.mp4")
+            output_abspath = get_exec_file_path(graph_exec_id, output_filename)
+
+            looped_clip = looped_clip.with_audio(clip.audio)
+            looped_clip.write_videofile(
+                output_abspath, codec="libx264", audio_codec="aac"
+            )
+        finally:
+            if looped_clip:
+                looped_clip.close()
+            if clip:
+                clip.close()
+
+        # Return output - for_block_output returns workspace:// if available, else data URI
+        video_out = await store_media_file(
+            file=output_filename,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+
+        yield "video_out", video_out
diff --git a/autogpt_platform/backend/backend/blocks/video/narration.py b/autogpt_platform/backend/backend/blocks/video/narration.py
new file mode 100644
index 0000000000..adf41753c8
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/narration.py
@@ -0,0 +1,267 @@
+"""VideoNarrationBlock - Generate AI voice narration and add to video."""
+
+import os
+from typing import Literal
+
+from elevenlabs import ElevenLabs
+from moviepy import CompositeAudioClip
+from moviepy.audio.io.AudioFileClip import AudioFileClip
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.blocks.elevenlabs._auth import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    ElevenLabsCredentials,
+    ElevenLabsCredentialsInput,
+)
+from backend.blocks.video._utils import (
+    extract_source_name,
+    get_video_codecs,
+    strip_chapters_inplace,
+)
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import CredentialsField, SchemaField
+from backend.util.exceptions import BlockExecutionError
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class VideoNarrationBlock(Block):
+    """Generate AI narration and add to video."""
+
+    class Input(BlockSchemaInput):
+        credentials: ElevenLabsCredentialsInput = CredentialsField(
+            description="ElevenLabs API key for voice synthesis"
+        )
+        video_in: MediaFileType = SchemaField(
+            description="Input video (URL, data URI, or local path)"
+        )
+        script: str = SchemaField(description="Narration script text")
+        voice_id: str = SchemaField(
+            description="ElevenLabs voice ID", default="21m00Tcm4TlvDq8ikWAM"  # Rachel
+        )
+        model_id: Literal[
+            "eleven_multilingual_v2",
+            "eleven_flash_v2_5",
+            "eleven_turbo_v2_5",
+            "eleven_turbo_v2",
+        ] = SchemaField(
+            description="ElevenLabs TTS model",
+            default="eleven_multilingual_v2",
+        )
+        mix_mode: Literal["replace", "mix", "ducking"] = SchemaField(
+            description="How to combine with original audio. 'ducking' applies stronger attenuation than 'mix'.",
+            default="ducking",
+        )
+        narration_volume: float = SchemaField(
+            description="Narration volume (0.0 to 2.0)",
+            default=1.0,
+            ge=0.0,
+            le=2.0,
+            advanced=True,
+        )
+        original_volume: float = SchemaField(
+            description="Original audio volume when mixing (0.0 to 1.0)",
+            default=0.3,
+            ge=0.0,
+            le=1.0,
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        video_out: MediaFileType = SchemaField(
+            description="Video with narration (path or data URI)"
+        )
+        audio_file: MediaFileType = SchemaField(
+            description="Generated audio file (path or data URI)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3d036b53-859c-4b17-9826-ca340f736e0e",
+            description="Generate AI narration and add to video",
+            categories={BlockCategory.MULTIMEDIA, BlockCategory.AI},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "video_in": "/tmp/test.mp4",
+                "script": "Hello world",
+                "credentials": TEST_CREDENTIALS_INPUT,
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("video_out", str), ("audio_file", str)],
+            test_mock={
+                "_generate_narration_audio": lambda *args: b"mock audio content",
+                "_add_narration_to_video": lambda *args: None,
+                "_store_input_video": lambda *args, **kwargs: "test.mp4",
+                "_store_output_video": lambda *args, **kwargs: "narrated_test.mp4",
+            },
+        )
+
+    async def _store_input_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store input video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+
+    async def _store_output_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store output video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+
+    def _generate_narration_audio(
+        self, api_key: str, script: str, voice_id: str, model_id: str
+    ) -> bytes:
+        """Generate narration audio via ElevenLabs API."""
+        client = ElevenLabs(api_key=api_key)
+        audio_generator = client.text_to_speech.convert(
+            voice_id=voice_id,
+            text=script,
+            model_id=model_id,
+        )
+        # The SDK returns a generator, collect all chunks
+        return b"".join(audio_generator)
+
+    def _add_narration_to_video(
+        self,
+        video_abspath: str,
+        audio_abspath: str,
+        output_abspath: str,
+        mix_mode: str,
+        narration_volume: float,
+        original_volume: float,
+    ) -> None:
+        """Add narration audio to video. Extracted for testability."""
+        video = None
+        final = None
+        narration_original = None
+        narration_scaled = None
+        original = None
+
+        try:
+            strip_chapters_inplace(video_abspath)
+            video = VideoFileClip(video_abspath)
+            narration_original = AudioFileClip(audio_abspath)
+            narration_scaled = narration_original.with_volume_scaled(narration_volume)
+            narration = narration_scaled
+
+            if mix_mode == "replace":
+                final_audio = narration
+            elif mix_mode == "mix":
+                if video.audio:
+                    original = video.audio.with_volume_scaled(original_volume)
+                    final_audio = CompositeAudioClip([original, narration])
+                else:
+                    final_audio = narration
+            else:  # ducking - apply stronger attenuation
+                if video.audio:
+                    # Ducking uses a much lower volume for original audio
+                    ducking_volume = original_volume * 0.3
+                    original = video.audio.with_volume_scaled(ducking_volume)
+                    final_audio = CompositeAudioClip([original, narration])
+                else:
+                    final_audio = narration
+
+            final = video.with_audio(final_audio)
+            video_codec, audio_codec = get_video_codecs(output_abspath)
+            final.write_videofile(
+                output_abspath, codec=video_codec, audio_codec=audio_codec
+            )
+
+        finally:
+            if original:
+                original.close()
+            if narration_scaled:
+                narration_scaled.close()
+            if narration_original:
+                narration_original.close()
+            if final:
+                final.close()
+            if video:
+                video.close()
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        credentials: ElevenLabsCredentials,
+        execution_context: ExecutionContext,
+        node_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        try:
+            assert execution_context.graph_exec_id is not None
+
+            # Store the input video locally
+            local_video_path = await self._store_input_video(
+                execution_context, input_data.video_in
+            )
+            video_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, local_video_path
+            )
+
+            # Generate narration audio via ElevenLabs
+            audio_content = self._generate_narration_audio(
+                credentials.api_key.get_secret_value(),
+                input_data.script,
+                input_data.voice_id,
+                input_data.model_id,
+            )
+
+            # Save audio to exec file path
+            audio_filename = MediaFileType(f"{node_exec_id}_narration.mp3")
+            audio_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, audio_filename
+            )
+            os.makedirs(os.path.dirname(audio_abspath), exist_ok=True)
+            with open(audio_abspath, "wb") as f:
+                f.write(audio_content)
+
+            # Add narration to video
+            source = extract_source_name(local_video_path)
+            output_filename = MediaFileType(f"{node_exec_id}_narrated_{source}.mp4")
+            output_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, output_filename
+            )
+
+            self._add_narration_to_video(
+                video_abspath,
+                audio_abspath,
+                output_abspath,
+                input_data.mix_mode,
+                input_data.narration_volume,
+                input_data.original_volume,
+            )
+
+            # Return as workspace path or data URI based on context
+            video_out = await self._store_output_video(
+                execution_context, output_filename
+            )
+            audio_out = await self._store_output_video(
+                execution_context, audio_filename
+            )
+
+            yield "video_out", video_out
+            yield "audio_file", audio_out
+
+        except Exception as e:
+            raise BlockExecutionError(
+                message=f"Failed to add narration: {e}",
+                block_name=self.name,
+                block_id=str(self.id),
+            ) from e
diff --git a/autogpt_platform/backend/backend/blocks/video/text_overlay.py b/autogpt_platform/backend/backend/blocks/video/text_overlay.py
new file mode 100644
index 0000000000..cb7cfe0420
--- /dev/null
+++ b/autogpt_platform/backend/backend/blocks/video/text_overlay.py
@@ -0,0 +1,231 @@
+"""VideoTextOverlayBlock - Add text overlay to video."""
+
+from typing import Literal
+
+from moviepy import CompositeVideoClip, TextClip
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.blocks.video._utils import (
+    extract_source_name,
+    get_video_codecs,
+    strip_chapters_inplace,
+)
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchemaInput,
+    BlockSchemaOutput,
+)
+from backend.data.execution import ExecutionContext
+from backend.data.model import SchemaField
+from backend.util.exceptions import BlockExecutionError
+from backend.util.file import MediaFileType, get_exec_file_path, store_media_file
+
+
+class VideoTextOverlayBlock(Block):
+    """Add text overlay/caption to video."""
+
+    class Input(BlockSchemaInput):
+        video_in: MediaFileType = SchemaField(
+            description="Input video (URL, data URI, or local path)"
+        )
+        text: str = SchemaField(description="Text to overlay on video")
+        position: Literal[
+            "top",
+            "center",
+            "bottom",
+            "top-left",
+            "top-right",
+            "bottom-left",
+            "bottom-right",
+        ] = SchemaField(description="Position of text on screen", default="bottom")
+        start_time: float | None = SchemaField(
+            description="When to show text (seconds). None = entire video",
+            default=None,
+            advanced=True,
+        )
+        end_time: float | None = SchemaField(
+            description="When to hide text (seconds). None = until end",
+            default=None,
+            advanced=True,
+        )
+        font_size: int = SchemaField(
+            description="Font size", default=48, ge=12, le=200, advanced=True
+        )
+        font_color: str = SchemaField(
+            description="Font color (hex or name)", default="white", advanced=True
+        )
+        bg_color: str | None = SchemaField(
+            description="Background color behind text (None for transparent)",
+            default=None,
+            advanced=True,
+        )
+
+    class Output(BlockSchemaOutput):
+        video_out: MediaFileType = SchemaField(
+            description="Video with text overlay (path or data URI)"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8ef14de6-cc90-430a-8cfa-3a003be92454",
+            description="Add text overlay/caption to video",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            disabled=True,  # Disable until we can lockdown imagemagick security policy
+            test_input={"video_in": "/tmp/test.mp4", "text": "Hello World"},
+            test_output=[("video_out", str)],
+            test_mock={
+                "_add_text_overlay": lambda *args: None,
+                "_store_input_video": lambda *args, **kwargs: "test.mp4",
+                "_store_output_video": lambda *args, **kwargs: "overlay_test.mp4",
+            },
+        )
+
+    async def _store_input_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store input video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_local_processing",
+        )
+
+    async def _store_output_video(
+        self, execution_context: ExecutionContext, file: MediaFileType
+    ) -> MediaFileType:
+        """Store output video. Extracted for testability."""
+        return await store_media_file(
+            file=file,
+            execution_context=execution_context,
+            return_format="for_block_output",
+        )
+
+    def _add_text_overlay(
+        self,
+        video_abspath: str,
+        output_abspath: str,
+        text: str,
+        position: str,
+        start_time: float | None,
+        end_time: float | None,
+        font_size: int,
+        font_color: str,
+        bg_color: str | None,
+    ) -> None:
+        """Add text overlay to video. Extracted for testability."""
+        video = None
+        final = None
+        txt_clip = None
+        try:
+            strip_chapters_inplace(video_abspath)
+            video = VideoFileClip(video_abspath)
+
+            txt_clip = TextClip(
+                text=text,
+                font_size=font_size,
+                color=font_color,
+                bg_color=bg_color,
+            )
+
+            # Position mapping
+            pos_map = {
+                "top": ("center", "top"),
+                "center": ("center", "center"),
+                "bottom": ("center", "bottom"),
+                "top-left": ("left", "top"),
+                "top-right": ("right", "top"),
+                "bottom-left": ("left", "bottom"),
+                "bottom-right": ("right", "bottom"),
+            }
+
+            txt_clip = txt_clip.with_position(pos_map[position])
+
+            # Set timing
+            start = start_time or 0
+            end = end_time or video.duration
+            duration = max(0, end - start)
+            txt_clip = txt_clip.with_start(start).with_end(end).with_duration(duration)
+
+            final = CompositeVideoClip([video, txt_clip])
+            video_codec, audio_codec = get_video_codecs(output_abspath)
+            final.write_videofile(
+                output_abspath, codec=video_codec, audio_codec=audio_codec
+            )
+
+        finally:
+            if txt_clip:
+                txt_clip.close()
+            if final:
+                final.close()
+            if video:
+                video.close()
+
+    async def run(
+        self,
+        input_data: Input,
+        *,
+        execution_context: ExecutionContext,
+        node_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        # Validate time range if both are provided
+        if (
+            input_data.start_time is not None
+            and input_data.end_time is not None
+            and input_data.end_time <= input_data.start_time
+        ):
+            raise BlockExecutionError(
+                message=f"end_time ({input_data.end_time}) must be greater than start_time ({input_data.start_time})",
+                block_name=self.name,
+                block_id=str(self.id),
+            )
+
+        try:
+            assert execution_context.graph_exec_id is not None
+
+            # Store the input video locally
+            local_video_path = await self._store_input_video(
+                execution_context, input_data.video_in
+            )
+            video_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, local_video_path
+            )
+
+            # Build output path
+            source = extract_source_name(local_video_path)
+            output_filename = MediaFileType(f"{node_exec_id}_overlay_{source}.mp4")
+            output_abspath = get_exec_file_path(
+                execution_context.graph_exec_id, output_filename
+            )
+
+            self._add_text_overlay(
+                video_abspath,
+                output_abspath,
+                input_data.text,
+                input_data.position,
+                input_data.start_time,
+                input_data.end_time,
+                input_data.font_size,
+                input_data.font_color,
+                input_data.bg_color,
+            )
+
+            # Return as workspace path or data URI based on context
+            video_out = await self._store_output_video(
+                execution_context, output_filename
+            )
+
+            yield "video_out", video_out
+
+        except BlockExecutionError:
+            raise
+        except Exception as e:
+            raise BlockExecutionError(
+                message=f"Failed to add text overlay: {e}",
+                block_name=self.name,
+                block_id=str(self.id),
+            ) from e
diff --git a/autogpt_platform/backend/backend/blocks/youtube.py b/autogpt_platform/backend/backend/blocks/youtube.py
index e79be3e99b..6d81a86b4c 100644
--- a/autogpt_platform/backend/backend/blocks/youtube.py
+++ b/autogpt_platform/backend/backend/blocks/youtube.py
@@ -165,10 +165,13 @@ class TranscribeYoutubeVideoBlock(Block):
         credentials: WebshareProxyCredentials,
         **kwargs,
     ) -> BlockOutput:
-        video_id = self.extract_video_id(input_data.youtube_url)
-        yield "video_id", video_id
+        try:
+            video_id = self.extract_video_id(input_data.youtube_url)
+            transcript = self.get_transcript(video_id, credentials)
+            transcript_text = self.format_transcript(transcript=transcript)
 
-        transcript = self.get_transcript(video_id, credentials)
-        transcript_text = self.format_transcript(transcript=transcript)
-
-        yield "transcript", transcript_text
+            # Only yield after all operations succeed
+            yield "video_id", video_id
+            yield "transcript", transcript_text
+        except Exception as e:
+            yield "error", str(e)
diff --git a/autogpt_platform/backend/backend/data/block.py b/autogpt_platform/backend/backend/data/block.py
index 8d9ecfff4c..f67134ceb3 100644
--- a/autogpt_platform/backend/backend/data/block.py
+++ b/autogpt_platform/backend/backend/data/block.py
@@ -246,7 +246,9 @@ class BlockSchema(BaseModel):
                         f"is not of type {CredentialsMetaInput.__name__}"
                     )
 
-                credentials_fields[field_name].validate_credentials_field_schema(cls)
+                CredentialsMetaInput.validate_credentials_field_schema(
+                    cls.get_field_schema(field_name), field_name
+                )
 
             elif field_name in credentials_fields:
                 raise KeyError(
@@ -873,14 +875,13 @@ def is_block_auth_configured(
 
 
 async def initialize_blocks() -> None:
-    # First, sync all provider costs to blocks
-    # Imported here to avoid circular import
     from backend.sdk.cost_integration import sync_all_provider_costs
+    from backend.util.retry import func_retry
 
     sync_all_provider_costs()
 
-    for cls in get_blocks().values():
-        block = cls()
+    @func_retry
+    async def sync_block_to_db(block: Block) -> None:
         existing_block = await AgentBlock.prisma().find_first(
             where={"OR": [{"id": block.id}, {"name": block.name}]}
         )
@@ -893,7 +894,7 @@ async def initialize_blocks() -> None:
                     outputSchema=json.dumps(block.output_schema.jsonschema()),
                 )
             )
-            continue
+            return
 
         input_schema = json.dumps(block.input_schema.jsonschema())
         output_schema = json.dumps(block.output_schema.jsonschema())
@@ -913,6 +914,25 @@ async def initialize_blocks() -> None:
                 },
             )
 
+    failed_blocks: list[str] = []
+    for cls in get_blocks().values():
+        block = cls()
+        try:
+            await sync_block_to_db(block)
+        except Exception as e:
+            logger.warning(
+                f"Failed to sync block {block.name} to database: {e}. "
+                "Block is still available in memory.",
+                exc_info=True,
+            )
+            failed_blocks.append(block.name)
+
+    if failed_blocks:
+        logger.error(
+            f"Failed to sync {len(failed_blocks)} block(s) to database: "
+            f"{', '.join(failed_blocks)}. These blocks are still available in memory."
+        )
+
 
 # Note on the return type annotation: https://github.com/microsoft/pyright/issues/10281
 def get_block(block_id: str) -> AnyBlockSchema | None:
diff --git a/autogpt_platform/backend/backend/data/block_cost_config.py b/autogpt_platform/backend/backend/data/block_cost_config.py
index 1b54ae0942..ec35afa401 100644
--- a/autogpt_platform/backend/backend/data/block_cost_config.py
+++ b/autogpt_platform/backend/backend/data/block_cost_config.py
@@ -36,12 +36,14 @@ from backend.blocks.replicate.replicate_block import ReplicateModelBlock
 from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock
 from backend.blocks.talking_head import CreateTalkingAvatarVideoBlock
 from backend.blocks.text_to_speech_block import UnrealTextToSpeechBlock
+from backend.blocks.video.narration import VideoNarrationBlock
 from backend.data.block import Block, BlockCost, BlockCostType
 from backend.integrations.credentials_store import (
     aiml_api_credentials,
     anthropic_credentials,
     apollo_credentials,
     did_credentials,
+    elevenlabs_credentials,
     enrichlayer_credentials,
     groq_credentials,
     ideogram_credentials,
@@ -78,10 +80,10 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.CLAUDE_4_1_OPUS: 21,
     LlmModel.CLAUDE_4_OPUS: 21,
     LlmModel.CLAUDE_4_SONNET: 5,
+    LlmModel.CLAUDE_4_6_OPUS: 14,
     LlmModel.CLAUDE_4_5_HAIKU: 4,
     LlmModel.CLAUDE_4_5_OPUS: 14,
     LlmModel.CLAUDE_4_5_SONNET: 9,
-    LlmModel.CLAUDE_3_7_SONNET: 5,
     LlmModel.CLAUDE_3_HAIKU: 1,
     LlmModel.AIML_API_QWEN2_5_72B: 1,
     LlmModel.AIML_API_LLAMA3_1_70B: 1,
@@ -640,4 +642,16 @@ BLOCK_COSTS: dict[Type[Block], list[BlockCost]] = {
             },
         ),
     ],
+    VideoNarrationBlock: [
+        BlockCost(
+            cost_amount=5,  # ElevenLabs TTS cost
+            cost_filter={
+                "credentials": {
+                    "id": elevenlabs_credentials.id,
+                    "provider": elevenlabs_credentials.provider,
+                    "type": elevenlabs_credentials.type,
+                }
+            },
+        )
+    ],
 }
diff --git a/autogpt_platform/backend/backend/data/credit_test.py b/autogpt_platform/backend/backend/data/credit_test.py
index 391a373b86..2b10c62882 100644
--- a/autogpt_platform/backend/backend/data/credit_test.py
+++ b/autogpt_platform/backend/backend/data/credit_test.py
@@ -134,6 +134,16 @@ async def test_block_credit_reset(server: SpinTestServer):
         month1 = datetime.now(timezone.utc).replace(month=1, day=1)
         user_credit.time_now = lambda: month1
 
+        # IMPORTANT: Set updatedAt to December of previous year to ensure it's
+        # in a different month than month1 (January). This fixes a timing bug
+        # where if the test runs in early February, 35 days ago would be January,
+        # matching the mocked month1 and preventing the refill from triggering.
+        dec_previous_year = month1.replace(year=month1.year - 1, month=12, day=15)
+        await UserBalance.prisma().update(
+            where={"userId": DEFAULT_USER_ID},
+            data={"updatedAt": dec_previous_year},
+        )
+
         # First call in month 1 should trigger refill
         balance = await user_credit.get_credits(DEFAULT_USER_ID)
         assert balance == REFILL_VALUE  # Should get 1000 credits
diff --git a/autogpt_platform/backend/backend/data/event_bus.py b/autogpt_platform/backend/backend/data/event_bus.py
index d8a1c5b729..614fb158b2 100644
--- a/autogpt_platform/backend/backend/data/event_bus.py
+++ b/autogpt_platform/backend/backend/data/event_bus.py
@@ -133,10 +133,23 @@ class RedisEventBus(BaseRedisEventBus[M], ABC):
 
 
 class AsyncRedisEventBus(BaseRedisEventBus[M], ABC):
+    def __init__(self):
+        self._pubsub: AsyncPubSub | None = None
+
     @property
     async def connection(self) -> redis.AsyncRedis:
         return await redis.get_redis_async()
 
+    async def close(self) -> None:
+        """Close the PubSub connection if it exists."""
+        if self._pubsub is not None:
+            try:
+                await self._pubsub.close()
+            except Exception:
+                logger.warning("Failed to close PubSub connection", exc_info=True)
+            finally:
+                self._pubsub = None
+
     async def publish_event(self, event: M, channel_key: str):
         """
         Publish an event to Redis. Gracefully handles connection failures
@@ -157,6 +170,7 @@ class AsyncRedisEventBus(BaseRedisEventBus[M], ABC):
             await self.connection, channel_key
         )
         assert isinstance(pubsub, AsyncPubSub)
+        self._pubsub = pubsub
 
         if "*" in channel_key:
             await pubsub.psubscribe(full_channel_name)
diff --git a/autogpt_platform/backend/backend/data/execution.py b/autogpt_platform/backend/backend/data/execution.py
index afb8c70538..def3d14fda 100644
--- a/autogpt_platform/backend/backend/data/execution.py
+++ b/autogpt_platform/backend/backend/data/execution.py
@@ -1,9 +1,8 @@
 import logging
+import queue
 from collections import defaultdict
 from datetime import datetime, timedelta, timezone
 from enum import Enum
-from multiprocessing import Manager
-from queue import Empty
 from typing import (
     TYPE_CHECKING,
     Annotated,
@@ -1200,12 +1199,16 @@ class NodeExecutionEntry(BaseModel):
 
 class ExecutionQueue(Generic[T]):
     """
-    Queue for managing the execution of agents.
-    This will be shared between different processes
+    Thread-safe queue for managing node execution within a single graph execution.
+
+    Note: Uses queue.Queue (not multiprocessing.Queue) since all access is from
+    threads within the same process. If migrating back to ProcessPoolExecutor,
+    replace with multiprocessing.Manager().Queue() for cross-process safety.
     """
 
     def __init__(self):
-        self.queue = Manager().Queue()
+        # Thread-safe queue (not multiprocessing) — see class docstring
+        self.queue: queue.Queue[T] = queue.Queue()
 
     def add(self, execution: T) -> T:
         self.queue.put(execution)
@@ -1220,7 +1223,7 @@ class ExecutionQueue(Generic[T]):
     def get_or_none(self) -> T | None:
         try:
             return self.queue.get_nowait()
-        except Empty:
+        except queue.Empty:
             return None
 
 
diff --git a/autogpt_platform/backend/backend/data/execution_queue_test.py b/autogpt_platform/backend/backend/data/execution_queue_test.py
new file mode 100644
index 0000000000..7a76adfe05
--- /dev/null
+++ b/autogpt_platform/backend/backend/data/execution_queue_test.py
@@ -0,0 +1,58 @@
+"""Tests for ExecutionQueue thread-safety."""
+
+import queue
+import threading
+
+from backend.data.execution import ExecutionQueue
+
+
+def test_execution_queue_uses_stdlib_queue():
+    """Verify ExecutionQueue uses queue.Queue (not multiprocessing)."""
+    q = ExecutionQueue()
+    assert isinstance(q.queue, queue.Queue)
+
+
+def test_basic_operations():
+    """Test add, get, empty, and get_or_none."""
+    q = ExecutionQueue()
+
+    assert q.empty() is True
+    assert q.get_or_none() is None
+
+    result = q.add("item1")
+    assert result == "item1"
+    assert q.empty() is False
+
+    item = q.get()
+    assert item == "item1"
+    assert q.empty() is True
+
+
+def test_thread_safety():
+    """Test concurrent access from multiple threads."""
+    q = ExecutionQueue()
+    results = []
+    num_items = 100
+
+    def producer():
+        for i in range(num_items):
+            q.add(f"item_{i}")
+
+    def consumer():
+        count = 0
+        while count < num_items:
+            item = q.get_or_none()
+            if item is not None:
+                results.append(item)
+                count += 1
+
+    producer_thread = threading.Thread(target=producer)
+    consumer_thread = threading.Thread(target=consumer)
+
+    producer_thread.start()
+    consumer_thread.start()
+
+    producer_thread.join(timeout=5)
+    consumer_thread.join(timeout=5)
+
+    assert len(results) == num_items
diff --git a/autogpt_platform/backend/backend/data/graph.py b/autogpt_platform/backend/backend/data/graph.py
index c1f38f81d5..2433a5d270 100644
--- a/autogpt_platform/backend/backend/data/graph.py
+++ b/autogpt_platform/backend/backend/data/graph.py
@@ -3,7 +3,7 @@ import logging
 import uuid
 from collections import defaultdict
 from datetime import datetime, timezone
-from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, cast
+from typing import TYPE_CHECKING, Annotated, Any, Literal, Optional, Self, cast
 
 from prisma.enums import SubmissionStatus
 from prisma.models import (
@@ -20,7 +20,7 @@ from prisma.types import (
     AgentNodeLinkCreateInput,
     StoreListingVersionWhereInput,
 )
-from pydantic import BaseModel, BeforeValidator, Field, create_model
+from pydantic import BaseModel, BeforeValidator, Field
 from pydantic.fields import computed_field
 
 from backend.blocks.agent import AgentExecutorBlock
@@ -30,7 +30,6 @@ from backend.data.db import prisma as db
 from backend.data.dynamic_fields import is_tool_pin, sanitize_pin_name
 from backend.data.includes import MAX_GRAPH_VERSIONS_FETCH
 from backend.data.model import (
-    CredentialsField,
     CredentialsFieldInfo,
     CredentialsMetaInput,
     is_credentials_field_name,
@@ -45,7 +44,6 @@ from .block import (
     AnyBlockSchema,
     Block,
     BlockInput,
-    BlockSchema,
     BlockType,
     EmptySchema,
     get_block,
@@ -113,10 +111,12 @@ class Link(BaseDbModel):
 
 class Node(BaseDbModel):
     block_id: str
-    input_default: BlockInput = {}  # dict[input_name, default_value]
-    metadata: dict[str, Any] = {}
-    input_links: list[Link] = []
-    output_links: list[Link] = []
+    input_default: BlockInput = Field(  # dict[input_name, default_value]
+        default_factory=dict
+    )
+    metadata: dict[str, Any] = Field(default_factory=dict)
+    input_links: list[Link] = Field(default_factory=list)
+    output_links: list[Link] = Field(default_factory=list)
 
     @property
     def credentials_optional(self) -> bool:
@@ -221,18 +221,33 @@ class NodeModel(Node):
         return result
 
 
-class BaseGraph(BaseDbModel):
+class GraphBaseMeta(BaseDbModel):
+    """
+    Shared base for `GraphMeta` and `BaseGraph`, with core graph metadata fields.
+    """
+
     version: int = 1
     is_active: bool = True
     name: str
     description: str
     instructions: str | None = None
     recommended_schedule_cron: str | None = None
-    nodes: list[Node] = []
-    links: list[Link] = []
     forked_from_id: str | None = None
     forked_from_version: int | None = None
 
+
+class BaseGraph(GraphBaseMeta):
+    """
+    Graph with nodes, links, and computed I/O schema fields.
+
+    Used to represent sub-graphs within a `Graph`. Contains the full graph
+    structure including nodes and links, plus computed fields for schemas
+    and trigger info. Does NOT include user_id or created_at (see GraphModel).
+    """
+
+    nodes: list[Node] = Field(default_factory=list)
+    links: list[Link] = Field(default_factory=list)
+
     @computed_field
     @property
     def input_schema(self) -> dict[str, Any]:
@@ -361,44 +376,79 @@ class GraphTriggerInfo(BaseModel):
 
 
 class Graph(BaseGraph):
-    sub_graphs: list[BaseGraph] = []  # Flattened sub-graphs
+    """Creatable graph model used in API create/update endpoints."""
+
+    sub_graphs: list[BaseGraph] = Field(default_factory=list)  # Flattened sub-graphs
+
+
+class GraphMeta(GraphBaseMeta):
+    """
+    Lightweight graph metadata model representing an existing graph from the database,
+    for use in listings and summaries.
+
+    Lacks `GraphModel`'s nodes, links, and expensive computed fields.
+    Use for list endpoints where full graph data is not needed and performance matters.
+    """
+
+    id: str  # type: ignore
+    version: int  # type: ignore
+    user_id: str
+    created_at: datetime
+
+    @classmethod
+    def from_db(cls, graph: "AgentGraph") -> Self:
+        return cls(
+            id=graph.id,
+            version=graph.version,
+            is_active=graph.isActive,
+            name=graph.name or "",
+            description=graph.description or "",
+            instructions=graph.instructions,
+            recommended_schedule_cron=graph.recommendedScheduleCron,
+            forked_from_id=graph.forkedFromId,
+            forked_from_version=graph.forkedFromVersion,
+            user_id=graph.userId,
+            created_at=graph.createdAt,
+        )
+
+
+class GraphModel(Graph, GraphMeta):
+    """
+    Full graph model representing an existing graph from the database.
+
+    This is the primary model for working with persisted graphs. Includes all
+    graph data (nodes, links, sub_graphs) plus user ownership and timestamps.
+    Provides computed fields (input_schema, output_schema, etc.) used during
+    set-up (frontend) and execution (backend).
+
+    Inherits from:
+    - `Graph`: provides structure (nodes, links, sub_graphs) and computed schemas
+    - `GraphMeta`: provides user_id, created_at for database records
+    """
+
+    nodes: list[NodeModel] = Field(default_factory=list)  # type: ignore
+
+    @property
+    def starting_nodes(self) -> list[NodeModel]:
+        outbound_nodes = {link.sink_id for link in self.links}
+        input_nodes = {
+            node.id for node in self.nodes if node.block.block_type == BlockType.INPUT
+        }
+        return [
+            node
+            for node in self.nodes
+            if node.id not in outbound_nodes or node.id in input_nodes
+        ]
+
+    @property
+    def webhook_input_node(self) -> NodeModel | None:  # type: ignore
+        return cast(NodeModel, super().webhook_input_node)
 
     @computed_field
     @property
     def credentials_input_schema(self) -> dict[str, Any]:
-        schema = self._credentials_input_schema.jsonschema()
-
-        # Determine which credential fields are required based on credentials_optional metadata
         graph_credentials_inputs = self.aggregate_credentials_inputs()
-        required_fields = []
 
-        # Build a map of node_id -> node for quick lookup
-        all_nodes = {node.id: node for node in self.nodes}
-        for sub_graph in self.sub_graphs:
-            for node in sub_graph.nodes:
-                all_nodes[node.id] = node
-
-        for field_key, (
-            _field_info,
-            node_field_pairs,
-        ) in graph_credentials_inputs.items():
-            # A field is required if ANY node using it has credentials_optional=False
-            is_required = False
-            for node_id, _field_name in node_field_pairs:
-                node = all_nodes.get(node_id)
-                if node and not node.credentials_optional:
-                    is_required = True
-                    break
-
-            if is_required:
-                required_fields.append(field_key)
-
-        schema["required"] = required_fields
-        return schema
-
-    @property
-    def _credentials_input_schema(self) -> type[BlockSchema]:
-        graph_credentials_inputs = self.aggregate_credentials_inputs()
         logger.debug(
             f"Combined credentials input fields for graph #{self.id} ({self.name}): "
             f"{graph_credentials_inputs}"
@@ -406,8 +456,8 @@ class Graph(BaseGraph):
 
         # Warn if same-provider credentials inputs can't be combined (= bad UX)
         graph_cred_fields = list(graph_credentials_inputs.values())
-        for i, (field, keys) in enumerate(graph_cred_fields):
-            for other_field, other_keys in list(graph_cred_fields)[i + 1 :]:
+        for i, (field, keys, _) in enumerate(graph_cred_fields):
+            for other_field, other_keys, _ in list(graph_cred_fields)[i + 1 :]:
                 if field.provider != other_field.provider:
                     continue
                 if ProviderName.HTTP in field.provider:
@@ -423,31 +473,78 @@ class Graph(BaseGraph):
                     f"keys: {keys} <> {other_keys}."
                 )
 
-        fields: dict[str, tuple[type[CredentialsMetaInput], CredentialsMetaInput]] = {
-            agg_field_key: (
-                CredentialsMetaInput[
-                    Literal[tuple(field_info.provider)],  # type: ignore
-                    Literal[tuple(field_info.supported_types)],  # type: ignore
-                ],
-                CredentialsField(
-                    required_scopes=set(field_info.required_scopes or []),
-                    discriminator=field_info.discriminator,
-                    discriminator_mapping=field_info.discriminator_mapping,
-                    discriminator_values=field_info.discriminator_values,
-                ),
-            )
-            for agg_field_key, (field_info, _) in graph_credentials_inputs.items()
-        }
+        # Build JSON schema directly to avoid expensive create_model + validation overhead
+        properties = {}
+        required_fields = []
 
-        return create_model(
-            self.name.replace(" ", "") + "CredentialsInputSchema",
-            __base__=BlockSchema,
-            **fields,  # type: ignore
-        )
+        for agg_field_key, (
+            field_info,
+            _,
+            is_required,
+        ) in graph_credentials_inputs.items():
+            providers = list(field_info.provider)
+            cred_types = list(field_info.supported_types)
+
+            field_schema: dict[str, Any] = {
+                "credentials_provider": providers,
+                "credentials_types": cred_types,
+                "type": "object",
+                "properties": {
+                    "id": {"title": "Id", "type": "string"},
+                    "title": {
+                        "anyOf": [{"type": "string"}, {"type": "null"}],
+                        "default": None,
+                        "title": "Title",
+                    },
+                    "provider": {
+                        "title": "Provider",
+                        "type": "string",
+                        **(
+                            {"enum": providers}
+                            if len(providers) > 1
+                            else {"const": providers[0]}
+                        ),
+                    },
+                    "type": {
+                        "title": "Type",
+                        "type": "string",
+                        **(
+                            {"enum": cred_types}
+                            if len(cred_types) > 1
+                            else {"const": cred_types[0]}
+                        ),
+                    },
+                },
+                "required": ["id", "provider", "type"],
+            }
+
+            # Add other (optional) field info items
+            field_schema.update(
+                field_info.model_dump(
+                    by_alias=True,
+                    exclude_defaults=True,
+                    exclude={"provider", "supported_types"},  # already included above
+                )
+            )
+
+            # Ensure field schema is well-formed
+            CredentialsMetaInput.validate_credentials_field_schema(
+                field_schema, agg_field_key
+            )
+
+            properties[agg_field_key] = field_schema
+            if is_required:
+                required_fields.append(agg_field_key)
+
+        return {
+            "type": "object",
+            "properties": properties,
+            "required": required_fields,
+        }
 
     def aggregate_credentials_inputs(
         self,
-    ) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]]]]:
+    ) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]], bool]]:
         """
         Returns:
             dict[aggregated_field_key, tuple(
@@ -455,13 +552,19 @@ class Graph(BaseGraph):
                     (now includes discriminator_values from matching nodes)
                 set[(node_id, field_name)]: Node credentials fields that are
                     compatible with this aggregated field spec
+                bool: True if the field is required (any node has credentials_optional=False)
             )]
         """
         # First collect all credential field data with input defaults
-        node_credential_data = []
+        # Track (field_info, (node_id, field_name), is_required) for each credential field
+        node_credential_data: list[tuple[CredentialsFieldInfo, tuple[str, str]]] = []
+        node_required_map: dict[str, bool] = {}  # node_id -> is_required
 
         for graph in [self] + self.sub_graphs:
             for node in graph.nodes:
+                # Track if this node requires credentials (credentials_optional=False means required)
+                node_required_map[node.id] = not node.credentials_optional
+
                 for (
                     field_name,
                     field_info,
@@ -485,37 +588,21 @@ class Graph(BaseGraph):
                     )
 
         # Combine credential field info (this will merge discriminator_values automatically)
-        return CredentialsFieldInfo.combine(*node_credential_data)
+        combined = CredentialsFieldInfo.combine(*node_credential_data)
 
-
-class GraphModel(Graph):
-    user_id: str
-    nodes: list[NodeModel] = []  # type: ignore
-
-    created_at: datetime
-
-    @property
-    def starting_nodes(self) -> list[NodeModel]:
-        outbound_nodes = {link.sink_id for link in self.links}
-        input_nodes = {
-            node.id for node in self.nodes if node.block.block_type == BlockType.INPUT
+        # Add is_required flag to each aggregated field
+        # A field is required if ANY node using it has credentials_optional=False
+        return {
+            key: (
+                field_info,
+                node_field_pairs,
+                any(
+                    node_required_map.get(node_id, True)
+                    for node_id, _ in node_field_pairs
+                ),
+            )
+            for key, (field_info, node_field_pairs) in combined.items()
         }
-        return [
-            node
-            for node in self.nodes
-            if node.id not in outbound_nodes or node.id in input_nodes
-        ]
-
-    @property
-    def webhook_input_node(self) -> NodeModel | None:  # type: ignore
-        return cast(NodeModel, super().webhook_input_node)
-
-    def meta(self) -> "GraphMeta":
-        """
-        Returns a GraphMeta object with metadata about the graph.
-        This is used to return metadata about the graph without exposing nodes and links.
-        """
-        return GraphMeta.from_graph(self)
 
     def reassign_ids(self, user_id: str, reassign_graph_id: bool = False):
         """
@@ -656,6 +743,11 @@ class GraphModel(Graph):
                 # For invalid blocks, we still raise immediately as this is a structural issue
                 raise ValueError(f"Invalid block {node.block_id} for node #{node.id}")
 
+            if block.disabled:
+                raise ValueError(
+                    f"Block {node.block_id} is disabled and cannot be used in graphs"
+                )
+
             node_input_mask = (
                 nodes_input_masks.get(node.id, {}) if nodes_input_masks else {}
             )
@@ -799,13 +891,14 @@ class GraphModel(Graph):
             if is_static_output_block(link.source_id):
                 link.is_static = True  # Each value block output should be static.
 
-    @staticmethod
-    def from_db(
+    @classmethod
+    def from_db(  # type: ignore[reportIncompatibleMethodOverride]
+        cls,
         graph: AgentGraph,
         for_export: bool = False,
         sub_graphs: list[AgentGraph] | None = None,
-    ) -> "GraphModel":
-        return GraphModel(
+    ) -> Self:
+        return cls(
             id=graph.id,
             user_id=graph.userId if not for_export else "",
             version=graph.version,
@@ -831,17 +924,28 @@ class GraphModel(Graph):
             ],
         )
 
+    def hide_nodes(self) -> "GraphModelWithoutNodes":
+        """
+        Returns a copy of the `GraphModel` with nodes, links, and sub-graphs hidden
+        (excluded from serialization). They are still present in the model instance
+        so all computed fields (e.g. `credentials_input_schema`) still work.
+        """
+        return GraphModelWithoutNodes.model_validate(self, from_attributes=True)
 
-class GraphMeta(Graph):
-    user_id: str
 
-    # Easy work-around to prevent exposing nodes and links in the API response
-    nodes: list[NodeModel] = Field(default=[], exclude=True)  # type: ignore
-    links: list[Link] = Field(default=[], exclude=True)
+class GraphModelWithoutNodes(GraphModel):
+    """
+    GraphModel variant that excludes nodes, links, and sub-graphs from serialization.
 
-    @staticmethod
-    def from_graph(graph: GraphModel) -> "GraphMeta":
-        return GraphMeta(**graph.model_dump())
+    Used in contexts like the store where exposing internal graph structure
+    is not desired. Inherits all computed fields from GraphModel but marks
+    nodes and links as excluded from JSON output.
+    """
+
+    nodes: list[NodeModel] = Field(default_factory=list, exclude=True)
+    links: list[Link] = Field(default_factory=list, exclude=True)
+
+    sub_graphs: list[BaseGraph] = Field(default_factory=list, exclude=True)
 
 
 class GraphsPaginated(BaseModel):
@@ -912,21 +1016,11 @@ async def list_graphs_paginated(
         where=where_clause,
         distinct=["id"],
         order={"version": "desc"},
-        include=AGENT_GRAPH_INCLUDE,
         skip=offset,
         take=page_size,
     )
 
-    graph_models: list[GraphMeta] = []
-    for graph in graphs:
-        try:
-            graph_meta = GraphModel.from_db(graph).meta()
-            # Trigger serialization to validate that the graph is well formed
-            graph_meta.model_dump()
-            graph_models.append(graph_meta)
-        except Exception as e:
-            logger.error(f"Error processing graph {graph.id}: {e}")
-            continue
+    graph_models = [GraphMeta.from_db(graph) for graph in graphs]
 
     return GraphsPaginated(
         graphs=graph_models,
@@ -1028,6 +1122,39 @@ async def get_graph(
     return GraphModel.from_db(graph, for_export)
 
 
+async def get_store_listed_graphs(*graph_ids: str) -> dict[str, GraphModel]:
+    """Batch-fetch multiple store-listed graphs by their IDs.
+
+    Only returns graphs that have approved store listings (publicly available).
+    Does not require permission checks since store-listed graphs are public.
+
+    Args:
+        *graph_ids: Variable number of graph IDs to fetch
+
+    Returns:
+        Dict mapping graph_id to GraphModel for graphs with approved store listings
+    """
+    if not graph_ids:
+        return {}
+
+    store_listings = await StoreListingVersion.prisma().find_many(
+        where={
+            "agentGraphId": {"in": list(graph_ids)},
+            "submissionStatus": SubmissionStatus.APPROVED,
+            "isDeleted": False,
+        },
+        include={"AgentGraph": {"include": AGENT_GRAPH_INCLUDE}},
+        distinct=["agentGraphId"],
+        order={"agentGraphVersion": "desc"},
+    )
+
+    return {
+        listing.agentGraphId: GraphModel.from_db(listing.AgentGraph)
+        for listing in store_listings
+        if listing.AgentGraph
+    }
+
+
 async def get_graph_as_admin(
     graph_id: str,
     version: int | None = None,
diff --git a/autogpt_platform/backend/backend/data/model.py b/autogpt_platform/backend/backend/data/model.py
index 2cc73f6b7b..7bdfef059b 100644
--- a/autogpt_platform/backend/backend/data/model.py
+++ b/autogpt_platform/backend/backend/data/model.py
@@ -19,7 +19,6 @@ from typing import (
     cast,
     get_args,
 )
-from urllib.parse import urlparse
 from uuid import uuid4
 
 from prisma.enums import CreditTransactionType, OnboardingStep
@@ -42,6 +41,7 @@ from typing_extensions import TypedDict
 
 from backend.integrations.providers import ProviderName
 from backend.util.json import loads as json_loads
+from backend.util.request import parse_url
 from backend.util.settings import Secrets
 
 # Type alias for any provider name (including custom ones)
@@ -163,7 +163,6 @@ class User(BaseModel):
 if TYPE_CHECKING:
     from prisma.models import User as PrismaUser
 
-    from backend.data.block import BlockSchema
 
 T = TypeVar("T")
 logger = logging.getLogger(__name__)
@@ -397,19 +396,25 @@ class HostScopedCredentials(_BaseCredentials):
     def matches_url(self, url: str) -> bool:
         """Check if this credential should be applied to the given URL."""
 
-        parsed_url = urlparse(url)
-        # Extract hostname without port
-        request_host = parsed_url.hostname
+        request_host, request_port = _extract_host_from_url(url)
+        cred_scope_host, cred_scope_port = _extract_host_from_url(self.host)
         if not request_host:
             return False
 
-        # Simple host matching - exact match or wildcard subdomain match
-        if self.host == request_host:
+        # If a port is specified in credential host, the request host port must match
+        if cred_scope_port is not None and request_port != cred_scope_port:
+            return False
+        # Non-standard ports are only allowed if explicitly specified in credential host
+        elif cred_scope_port is None and request_port not in (80, 443, None):
+            return False
+
+        # Simple host matching
+        if cred_scope_host == request_host:
             return True
 
         # Support wildcard matching (e.g., "*.example.com" matches "api.example.com")
-        if self.host.startswith("*."):
-            domain = self.host[2:]  # Remove "*."
+        if cred_scope_host.startswith("*."):
+            domain = cred_scope_host[2:]  # Remove "*."
             return request_host.endswith(f".{domain}") or request_host == domain
 
         return False
@@ -502,15 +507,13 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
     def allowed_cred_types(cls) -> tuple[CredentialsType, ...]:
         return get_args(cls.model_fields["type"].annotation)
 
-    @classmethod
-    def validate_credentials_field_schema(cls, model: type["BlockSchema"]):
+    @staticmethod
+    def validate_credentials_field_schema(
+        field_schema: dict[str, Any], field_name: str
+    ):
         """Validates the schema of a credentials input field"""
-        field_name = next(
-            name for name, type in model.get_credentials_fields().items() if type is cls
-        )
-        field_schema = model.jsonschema()["properties"][field_name]
         try:
-            schema_extra = CredentialsFieldInfo[CP, CT].model_validate(field_schema)
+            field_info = CredentialsFieldInfo[CP, CT].model_validate(field_schema)
         except ValidationError as e:
             if "Field required [type=missing" not in str(e):
                 raise
@@ -520,11 +523,11 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
                 f"{field_schema}"
             ) from e
 
-        providers = cls.allowed_providers()
+        providers = field_info.provider
         if (
             providers is not None
             and len(providers) > 1
-            and not schema_extra.discriminator
+            and not field_info.discriminator
         ):
             raise TypeError(
                 f"Multi-provider CredentialsField '{field_name}' "
@@ -551,13 +554,13 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
     )
 
 
-def _extract_host_from_url(url: str) -> str:
-    """Extract host from URL for grouping host-scoped credentials."""
+def _extract_host_from_url(url: str) -> tuple[str, int | None]:
+    """Extract host and port from URL for grouping host-scoped credentials."""
     try:
-        parsed = urlparse(url)
-        return parsed.hostname or url
+        parsed = parse_url(url)
+        return parsed.hostname or url, parsed.port
     except Exception:
-        return ""
+        return "", None
 
 
 class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
@@ -606,7 +609,7 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
                 providers = frozenset(
                     [cast(CP, "http")]
                     + [
-                        cast(CP, _extract_host_from_url(str(value)))
+                        cast(CP, parse_url(str(value)).netloc)
                         for value in field.discriminator_values
                     ]
                 )
@@ -666,10 +669,16 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
         if not (self.discriminator and self.discriminator_mapping):
             return self
 
+        try:
+            provider = self.discriminator_mapping[discriminator_value]
+        except KeyError:
+            raise ValueError(
+                f"Model '{discriminator_value}' is not supported. "
+                "It may have been deprecated. Please update your agent configuration."
+            )
+
         return CredentialsFieldInfo(
-            credentials_provider=frozenset(
-                [self.discriminator_mapping[discriminator_value]]
-            ),
+            credentials_provider=frozenset([provider]),
             credentials_types=self.supported_types,
             credentials_scopes=self.required_scopes,
             discriminator=self.discriminator,
diff --git a/autogpt_platform/backend/backend/data/model_test.py b/autogpt_platform/backend/backend/data/model_test.py
index 37ec6be82f..e8e2ddfa35 100644
--- a/autogpt_platform/backend/backend/data/model_test.py
+++ b/autogpt_platform/backend/backend/data/model_test.py
@@ -79,10 +79,23 @@ class TestHostScopedCredentials:
             headers={"Authorization": SecretStr("Bearer token")},
         )
 
-        assert creds.matches_url("http://localhost:8080/api/v1")
+        # Non-standard ports require explicit port in credential host
+        assert not creds.matches_url("http://localhost:8080/api/v1")
         assert creds.matches_url("https://localhost:443/secure/endpoint")
         assert creds.matches_url("http://localhost/simple")
 
+    def test_matches_url_with_explicit_port(self):
+        """Test URL matching with explicit port in credential host."""
+        creds = HostScopedCredentials(
+            provider="custom",
+            host="localhost:8080",
+            headers={"Authorization": SecretStr("Bearer token")},
+        )
+
+        assert creds.matches_url("http://localhost:8080/api/v1")
+        assert not creds.matches_url("http://localhost:3000/api/v1")
+        assert not creds.matches_url("http://localhost/simple")
+
     def test_empty_headers_dict(self):
         """Test HostScopedCredentials with empty headers."""
         creds = HostScopedCredentials(
@@ -128,8 +141,20 @@ class TestHostScopedCredentials:
             ("*.example.com", "https://sub.api.example.com/test", True),
             ("*.example.com", "https://example.com/test", True),
             ("*.example.com", "https://example.org/test", False),
-            ("localhost", "http://localhost:3000/test", True),
+            # Non-standard ports require explicit port in credential host
+            ("localhost", "http://localhost:3000/test", False),
+            ("localhost:3000", "http://localhost:3000/test", True),
             ("localhost", "http://127.0.0.1:3000/test", False),
+            # IPv6 addresses (frontend stores with brackets via URL.hostname)
+            ("[::1]", "http://[::1]/test", True),
+            ("[::1]", "http://[::1]:80/test", True),
+            ("[::1]", "https://[::1]:443/test", True),
+            ("[::1]", "http://[::1]:8080/test", False),  # Non-standard port
+            ("[::1]:8080", "http://[::1]:8080/test", True),
+            ("[::1]:8080", "http://[::1]:9090/test", False),
+            ("[2001:db8::1]", "http://[2001:db8::1]/path", True),
+            ("[2001:db8::1]", "https://[2001:db8::1]:443/path", True),
+            ("[2001:db8::1]", "http://[2001:db8::ff]/path", False),
         ],
     )
     def test_url_matching_parametrized(self, host: str, test_url: str, expected: bool):
diff --git a/autogpt_platform/backend/backend/data/rabbitmq.py b/autogpt_platform/backend/backend/data/rabbitmq.py
index bdf2090083..524e21748a 100644
--- a/autogpt_platform/backend/backend/data/rabbitmq.py
+++ b/autogpt_platform/backend/backend/data/rabbitmq.py
@@ -1,3 +1,4 @@
+import asyncio
 import logging
 from abc import ABC, abstractmethod
 from enum import Enum
@@ -225,6 +226,10 @@ class SyncRabbitMQ(RabbitMQBase):
 class AsyncRabbitMQ(RabbitMQBase):
     """Asynchronous RabbitMQ client"""
 
+    def __init__(self, config: RabbitMQConfig):
+        super().__init__(config)
+        self._reconnect_lock: asyncio.Lock | None = None
+
     @property
     def is_connected(self) -> bool:
         return bool(self._connection and not self._connection.is_closed)
@@ -235,7 +240,17 @@ class AsyncRabbitMQ(RabbitMQBase):
 
     @conn_retry("AsyncRabbitMQ", "Acquiring async connection")
     async def connect(self):
-        if self.is_connected:
+        if self.is_connected and self._channel and not self._channel.is_closed:
+            return
+
+        if (
+            self.is_connected
+            and self._connection
+            and (self._channel is None or self._channel.is_closed)
+        ):
+            self._channel = await self._connection.channel()
+            await self._channel.set_qos(prefetch_count=1)
+            await self.declare_infrastructure()
             return
 
         self._connection = await aio_pika.connect_robust(
@@ -291,24 +306,46 @@ class AsyncRabbitMQ(RabbitMQBase):
                     exchange, routing_key=queue.routing_key or queue.name
                 )
 
-    @func_retry
-    async def publish_message(
+    @property
+    def _lock(self) -> asyncio.Lock:
+        if self._reconnect_lock is None:
+            self._reconnect_lock = asyncio.Lock()
+        return self._reconnect_lock
+
+    async def _ensure_channel(self) -> aio_pika.abc.AbstractChannel:
+        """Get a valid channel, reconnecting if the current one is stale.
+
+        Uses a lock to prevent concurrent reconnection attempts from racing.
+        """
+        if self.is_ready:
+            return self._channel  # type: ignore  # is_ready guarantees non-None
+
+        async with self._lock:
+            # Double-check after acquiring lock
+            if self.is_ready:
+                return self._channel  # type: ignore
+
+            self._channel = None
+            await self.connect()
+
+            if self._channel is None:
+                raise RuntimeError("Channel should be established after connect")
+
+            return self._channel
+
+    async def _publish_once(
         self,
         routing_key: str,
         message: str,
         exchange: Optional[Exchange] = None,
         persistent: bool = True,
     ) -> None:
-        if not self.is_ready:
-            await self.connect()
-
-        if self._channel is None:
-            raise RuntimeError("Channel should be established after connect")
+        channel = await self._ensure_channel()
 
         if exchange:
-            exchange_obj = await self._channel.get_exchange(exchange.name)
+            exchange_obj = await channel.get_exchange(exchange.name)
         else:
-            exchange_obj = self._channel.default_exchange
+            exchange_obj = channel.default_exchange
 
         await exchange_obj.publish(
             aio_pika.Message(
@@ -322,9 +359,23 @@ class AsyncRabbitMQ(RabbitMQBase):
             routing_key=routing_key,
         )
 
+    @func_retry
+    async def publish_message(
+        self,
+        routing_key: str,
+        message: str,
+        exchange: Optional[Exchange] = None,
+        persistent: bool = True,
+    ) -> None:
+        try:
+            await self._publish_once(routing_key, message, exchange, persistent)
+        except aio_pika.exceptions.ChannelInvalidStateError:
+            logger.warning(
+                "RabbitMQ channel invalid, forcing reconnect and retrying publish"
+            )
+            async with self._lock:
+                self._channel = None
+            await self._publish_once(routing_key, message, exchange, persistent)
+
     async def get_channel(self) -> aio_pika.abc.AbstractChannel:
-        if not self.is_ready:
-            await self.connect()
-        if self._channel is None:
-            raise RuntimeError("Channel should be established after connect")
-        return self._channel
+        return await self._ensure_channel()
diff --git a/autogpt_platform/backend/backend/executor/database.py b/autogpt_platform/backend/backend/executor/database.py
index ae7474fc1d..d44439d51c 100644
--- a/autogpt_platform/backend/backend/executor/database.py
+++ b/autogpt_platform/backend/backend/executor/database.py
@@ -17,6 +17,7 @@ from backend.data.analytics import (
     get_accuracy_trends_and_alerts,
     get_marketplace_graphs_for_monitoring,
 )
+from backend.data.auth.oauth import cleanup_expired_oauth_tokens
 from backend.data.credit import UsageTransactionMetadata, get_user_credit_model
 from backend.data.execution import (
     create_graph_execution,
@@ -219,6 +220,9 @@ class DatabaseManager(AppService):
     # Onboarding
     increment_onboarding_runs = _(increment_onboarding_runs)
 
+    # OAuth
+    cleanup_expired_oauth_tokens = _(cleanup_expired_oauth_tokens)
+
     # Store
     get_store_agents = _(get_store_agents)
     get_store_agent_details = _(get_store_agent_details)
@@ -349,6 +353,9 @@ class DatabaseManagerAsyncClient(AppServiceClient):
     # Onboarding
     increment_onboarding_runs = d.increment_onboarding_runs
 
+    # OAuth
+    cleanup_expired_oauth_tokens = d.cleanup_expired_oauth_tokens
+
     # Store
     get_store_agents = d.get_store_agents
     get_store_agent_details = d.get_store_agent_details
diff --git a/autogpt_platform/backend/backend/executor/manager.py b/autogpt_platform/backend/backend/executor/manager.py
index 8362dae828..7304653811 100644
--- a/autogpt_platform/backend/backend/executor/manager.py
+++ b/autogpt_platform/backend/backend/executor/manager.py
@@ -213,6 +213,9 @@ async def execute_node(
         block_name=node_block.name,
     )
 
+    if node_block.disabled:
+        raise ValueError(f"Block {node_block.id} is disabled and cannot be executed")
+
     # Sanity check: validate the execution input.
     input_data, error = validate_exec(node, data.inputs, resolve_input=False)
     if input_data is None:
diff --git a/autogpt_platform/backend/backend/executor/scheduler.py b/autogpt_platform/backend/backend/executor/scheduler.py
index 44b77fc018..cbdc441718 100644
--- a/autogpt_platform/backend/backend/executor/scheduler.py
+++ b/autogpt_platform/backend/backend/executor/scheduler.py
@@ -24,11 +24,9 @@ from dotenv import load_dotenv
 from pydantic import BaseModel, Field, ValidationError
 from sqlalchemy import MetaData, create_engine
 
-from backend.data.auth.oauth import cleanup_expired_oauth_tokens
 from backend.data.block import BlockInput
 from backend.data.execution import GraphExecutionWithNodes
 from backend.data.model import CredentialsMetaInput
-from backend.data.onboarding import increment_onboarding_runs
 from backend.executor import utils as execution_utils
 from backend.monitoring import (
     NotificationJobArgs,
@@ -38,7 +36,11 @@ from backend.monitoring import (
     report_execution_accuracy_alerts,
     report_late_executions,
 )
-from backend.util.clients import get_database_manager_client, get_scheduler_client
+from backend.util.clients import (
+    get_database_manager_async_client,
+    get_database_manager_client,
+    get_scheduler_client,
+)
 from backend.util.cloud_storage import cleanup_expired_files_async
 from backend.util.exceptions import (
     GraphNotFoundError,
@@ -148,6 +150,7 @@ def execute_graph(**kwargs):
 async def _execute_graph(**kwargs):
     args = GraphExecutionJobArgs(**kwargs)
     start_time = asyncio.get_event_loop().time()
+    db = get_database_manager_async_client()
     try:
         logger.info(f"Executing recurring job for graph #{args.graph_id}")
         graph_exec: GraphExecutionWithNodes = await execution_utils.add_graph_execution(
@@ -157,7 +160,7 @@ async def _execute_graph(**kwargs):
             inputs=args.input_data,
             graph_credentials_inputs=args.input_credentials,
         )
-        await increment_onboarding_runs(args.user_id)
+        await db.increment_onboarding_runs(args.user_id)
         elapsed = asyncio.get_event_loop().time() - start_time
         logger.info(
             f"Graph execution started with ID {graph_exec.id} for graph {args.graph_id} "
@@ -246,8 +249,13 @@ def cleanup_expired_files():
 
 def cleanup_oauth_tokens():
     """Clean up expired OAuth tokens from the database."""
+
     # Wait for completion
-    run_async(cleanup_expired_oauth_tokens())
+    async def _cleanup():
+        db = get_database_manager_async_client()
+        return await db.cleanup_expired_oauth_tokens()
+
+    run_async(_cleanup())
 
 
 def execution_accuracy_alerts():
diff --git a/autogpt_platform/backend/backend/executor/utils.py b/autogpt_platform/backend/backend/executor/utils.py
index fa264c30a7..d26424aefc 100644
--- a/autogpt_platform/backend/backend/executor/utils.py
+++ b/autogpt_platform/backend/backend/executor/utils.py
@@ -373,7 +373,7 @@ def make_node_credentials_input_map(
     # Get aggregated credentials fields for the graph
     graph_cred_inputs = graph.aggregate_credentials_inputs()
 
-    for graph_input_name, (_, compatible_node_fields) in graph_cred_inputs.items():
+    for graph_input_name, (_, compatible_node_fields, _) in graph_cred_inputs.items():
         # Best-effort map: skip missing items
         if graph_input_name not in graph_credentials_input:
             continue
diff --git a/autogpt_platform/backend/backend/integrations/credentials_store.py b/autogpt_platform/backend/backend/integrations/credentials_store.py
index 40a6f7269c..384405b0c7 100644
--- a/autogpt_platform/backend/backend/integrations/credentials_store.py
+++ b/autogpt_platform/backend/backend/integrations/credentials_store.py
@@ -224,6 +224,14 @@ openweathermap_credentials = APIKeyCredentials(
     expires_at=None,
 )
 
+elevenlabs_credentials = APIKeyCredentials(
+    id="f4a8b6c2-3d1e-4f5a-9b8c-7d6e5f4a3b2c",
+    provider="elevenlabs",
+    api_key=SecretStr(settings.secrets.elevenlabs_api_key),
+    title="Use Credits for ElevenLabs",
+    expires_at=None,
+)
+
 DEFAULT_CREDENTIALS = [
     ollama_credentials,
     revid_credentials,
@@ -252,6 +260,7 @@ DEFAULT_CREDENTIALS = [
     v0_credentials,
     webshare_proxy_credentials,
     openweathermap_credentials,
+    elevenlabs_credentials,
 ]
 
 SYSTEM_CREDENTIAL_IDS = {cred.id for cred in DEFAULT_CREDENTIALS}
@@ -366,6 +375,8 @@ class IntegrationCredentialsStore:
             all_credentials.append(webshare_proxy_credentials)
         if settings.secrets.openweathermap_api_key:
             all_credentials.append(openweathermap_credentials)
+        if settings.secrets.elevenlabs_api_key:
+            all_credentials.append(elevenlabs_credentials)
         return all_credentials
 
     async def get_creds_by_id(
diff --git a/autogpt_platform/backend/backend/integrations/providers.py b/autogpt_platform/backend/backend/integrations/providers.py
index 3af5006ca4..8a0d6fd183 100644
--- a/autogpt_platform/backend/backend/integrations/providers.py
+++ b/autogpt_platform/backend/backend/integrations/providers.py
@@ -18,6 +18,7 @@ class ProviderName(str, Enum):
     DISCORD = "discord"
     D_ID = "d_id"
     E2B = "e2b"
+    ELEVENLABS = "elevenlabs"
     FAL = "fal"
     GITHUB = "github"
     GOOGLE = "google"
diff --git a/autogpt_platform/backend/backend/integrations/webhooks/utils_test.py b/autogpt_platform/backend/backend/integrations/webhooks/utils_test.py
new file mode 100644
index 0000000000..bc502a8e44
--- /dev/null
+++ b/autogpt_platform/backend/backend/integrations/webhooks/utils_test.py
@@ -0,0 +1,39 @@
+from urllib.parse import urlparse
+
+import fastapi
+from fastapi.routing import APIRoute
+
+from backend.api.features.integrations.router import router as integrations_router
+from backend.integrations.providers import ProviderName
+from backend.integrations.webhooks import utils as webhooks_utils
+
+
+def test_webhook_ingress_url_matches_route(monkeypatch) -> None:
+    app = fastapi.FastAPI()
+    app.include_router(integrations_router, prefix="/api/integrations")
+
+    provider = ProviderName.GITHUB
+    webhook_id = "webhook_123"
+    base_url = "https://example.com"
+
+    monkeypatch.setattr(webhooks_utils.app_config, "platform_base_url", base_url)
+
+    route = next(
+        route
+        for route in integrations_router.routes
+        if isinstance(route, APIRoute)
+        and route.path == "/{provider}/webhooks/{webhook_id}/ingress"
+        and "POST" in route.methods
+    )
+    expected_path = f"/api/integrations{route.path}".format(
+        provider=provider.value,
+        webhook_id=webhook_id,
+    )
+    actual_url = urlparse(webhooks_utils.webhook_ingress_url(provider, webhook_id))
+    expected_base = urlparse(base_url)
+
+    assert (actual_url.scheme, actual_url.netloc) == (
+        expected_base.scheme,
+        expected_base.netloc,
+    )
+    assert actual_url.path == expected_path
diff --git a/autogpt_platform/backend/backend/util/file.py b/autogpt_platform/backend/backend/util/file.py
index baa9225629..70e354a29c 100644
--- a/autogpt_platform/backend/backend/util/file.py
+++ b/autogpt_platform/backend/backend/util/file.py
@@ -8,6 +8,8 @@ from pathlib import Path
 from typing import TYPE_CHECKING, Literal
 from urllib.parse import urlparse
 
+from pydantic import BaseModel
+
 from backend.util.cloud_storage import get_cloud_storage_handler
 from backend.util.request import Requests
 from backend.util.settings import Config
@@ -17,6 +19,35 @@ from backend.util.virus_scanner import scan_content_safe
 if TYPE_CHECKING:
     from backend.data.execution import ExecutionContext
 
+
+class WorkspaceUri(BaseModel):
+    """Parsed workspace:// URI."""
+
+    file_ref: str  # File ID or path (e.g. "abc123" or "/path/to/file.txt")
+    mime_type: str | None = None  # MIME type from fragment (e.g. "video/mp4")
+    is_path: bool = False  # True if file_ref is a path (starts with "/")
+
+
+def parse_workspace_uri(uri: str) -> WorkspaceUri:
+    """Parse a workspace:// URI into its components.
+
+    Examples:
+        "workspace://abc123"            → WorkspaceUri(file_ref="abc123", mime_type=None, is_path=False)
+        "workspace://abc123#video/mp4"  → WorkspaceUri(file_ref="abc123", mime_type="video/mp4", is_path=False)
+        "workspace:///path/to/file.txt" → WorkspaceUri(file_ref="/path/to/file.txt", mime_type=None, is_path=True)
+    """
+    raw = uri.removeprefix("workspace://")
+    mime_type: str | None = None
+    if "#" in raw:
+        raw, fragment = raw.split("#", 1)
+        mime_type = fragment or None
+    return WorkspaceUri(
+        file_ref=raw,
+        mime_type=mime_type,
+        is_path=raw.startswith("/"),
+    )
+
+
 # Return format options for store_media_file
 # - "for_local_processing": Returns local file path - use with ffmpeg, MoviePy, PIL, etc.
 # - "for_external_api": Returns data URI (base64) - use when sending content to external APIs
@@ -183,22 +214,20 @@ async def store_media_file(
                 "This file type is only available in CoPilot sessions."
             )
 
-        # Parse workspace reference
-        # workspace://abc123 - by file ID
-        # workspace:///path/to/file.txt - by virtual path
-        file_ref = file[12:]  # Remove "workspace://"
+        # Parse workspace reference (strips #mimeType fragment from file ID)
+        ws = parse_workspace_uri(file)
 
-        if file_ref.startswith("/"):
-            # Path reference
-            workspace_content = await workspace_manager.read_file(file_ref)
-            file_info = await workspace_manager.get_file_info_by_path(file_ref)
+        if ws.is_path:
+            # Path reference: workspace:///path/to/file.txt
+            workspace_content = await workspace_manager.read_file(ws.file_ref)
+            file_info = await workspace_manager.get_file_info_by_path(ws.file_ref)
             filename = sanitize_filename(
                 file_info.name if file_info else f"{uuid.uuid4()}.bin"
             )
         else:
-            # ID reference
-            workspace_content = await workspace_manager.read_file_by_id(file_ref)
-            file_info = await workspace_manager.get_file_info(file_ref)
+            # ID reference: workspace://abc123 or workspace://abc123#video/mp4
+            workspace_content = await workspace_manager.read_file_by_id(ws.file_ref)
+            file_info = await workspace_manager.get_file_info(ws.file_ref)
             filename = sanitize_filename(
                 file_info.name if file_info else f"{uuid.uuid4()}.bin"
             )
@@ -313,6 +342,14 @@ async def store_media_file(
         if not target_path.is_file():
             raise ValueError(f"Local file does not exist: {target_path}")
 
+        # Virus scan the local file before any further processing
+        local_content = target_path.read_bytes()
+        if len(local_content) > MAX_FILE_SIZE_BYTES:
+            raise ValueError(
+                f"File too large: {len(local_content)} bytes > {MAX_FILE_SIZE_BYTES} bytes"
+            )
+        await scan_content_safe(local_content, filename=sanitized_file)
+
     # Return based on requested format
     if return_format == "for_local_processing":
         # Use when processing files locally with tools like ffmpeg, MoviePy, PIL
@@ -334,7 +371,21 @@ async def store_media_file(
 
         # Don't re-save if input was already from workspace
         if is_from_workspace:
-            # Return original workspace reference
+            # Return original workspace reference, ensuring MIME type fragment
+            ws = parse_workspace_uri(file)
+            if not ws.mime_type:
+                # Add MIME type fragment if missing (older refs without it)
+                try:
+                    if ws.is_path:
+                        info = await workspace_manager.get_file_info_by_path(
+                            ws.file_ref
+                        )
+                    else:
+                        info = await workspace_manager.get_file_info(ws.file_ref)
+                    if info:
+                        return MediaFileType(f"{file}#{info.mimeType}")
+                except Exception:
+                    pass
             return MediaFileType(file)
 
         # Save new content to workspace
@@ -346,7 +397,7 @@ async def store_media_file(
             filename=filename,
             overwrite=True,
         )
-        return MediaFileType(f"workspace://{file_record.id}")
+        return MediaFileType(f"workspace://{file_record.id}#{file_record.mimeType}")
 
     else:
         raise ValueError(f"Invalid return_format: {return_format}")
diff --git a/autogpt_platform/backend/backend/util/file_test.py b/autogpt_platform/backend/backend/util/file_test.py
index 9fe672d155..87c53e4305 100644
--- a/autogpt_platform/backend/backend/util/file_test.py
+++ b/autogpt_platform/backend/backend/util/file_test.py
@@ -247,3 +247,100 @@ class TestFileCloudIntegration:
                     execution_context=make_test_context(graph_exec_id=graph_exec_id),
                     return_format="for_local_processing",
                 )
+
+    @pytest.mark.asyncio
+    async def test_store_media_file_local_path_scanned(self):
+        """Test that local file paths are scanned for viruses."""
+        graph_exec_id = "test-exec-123"
+        local_file = "test_video.mp4"
+        file_content = b"fake video content"
+
+        with patch(
+            "backend.util.file.get_cloud_storage_handler"
+        ) as mock_handler_getter, patch(
+            "backend.util.file.scan_content_safe"
+        ) as mock_scan, patch(
+            "backend.util.file.Path"
+        ) as mock_path_class:
+
+            # Mock cloud storage handler - not a cloud path
+            mock_handler = MagicMock()
+            mock_handler.is_cloud_path.return_value = False
+            mock_handler_getter.return_value = mock_handler
+
+            # Mock virus scanner
+            mock_scan.return_value = None
+
+            # Mock file system operations
+            mock_base_path = MagicMock()
+            mock_target_path = MagicMock()
+            mock_resolved_path = MagicMock()
+
+            mock_path_class.return_value = mock_base_path
+            mock_base_path.mkdir = MagicMock()
+            mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
+            mock_target_path.resolve.return_value = mock_resolved_path
+            mock_resolved_path.is_relative_to.return_value = True
+            mock_resolved_path.is_file.return_value = True
+            mock_resolved_path.read_bytes.return_value = file_content
+            mock_resolved_path.relative_to.return_value = Path(local_file)
+            mock_resolved_path.name = local_file
+
+            result = await store_media_file(
+                file=MediaFileType(local_file),
+                execution_context=make_test_context(graph_exec_id=graph_exec_id),
+                return_format="for_local_processing",
+            )
+
+            # Verify virus scan was called for local file
+            mock_scan.assert_called_once_with(file_content, filename=local_file)
+
+            # Result should be the relative path
+            assert str(result) == local_file
+
+    @pytest.mark.asyncio
+    async def test_store_media_file_local_path_virus_detected(self):
+        """Test that infected local files raise VirusDetectedError."""
+        from backend.api.features.store.exceptions import VirusDetectedError
+
+        graph_exec_id = "test-exec-123"
+        local_file = "infected.exe"
+        file_content = b"malicious content"
+
+        with patch(
+            "backend.util.file.get_cloud_storage_handler"
+        ) as mock_handler_getter, patch(
+            "backend.util.file.scan_content_safe"
+        ) as mock_scan, patch(
+            "backend.util.file.Path"
+        ) as mock_path_class:
+
+            # Mock cloud storage handler - not a cloud path
+            mock_handler = MagicMock()
+            mock_handler.is_cloud_path.return_value = False
+            mock_handler_getter.return_value = mock_handler
+
+            # Mock virus scanner to detect virus
+            mock_scan.side_effect = VirusDetectedError(
+                "EICAR-Test-File", "File rejected due to virus detection"
+            )
+
+            # Mock file system operations
+            mock_base_path = MagicMock()
+            mock_target_path = MagicMock()
+            mock_resolved_path = MagicMock()
+
+            mock_path_class.return_value = mock_base_path
+            mock_base_path.mkdir = MagicMock()
+            mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
+            mock_target_path.resolve.return_value = mock_resolved_path
+            mock_resolved_path.is_relative_to.return_value = True
+            mock_resolved_path.is_file.return_value = True
+            mock_resolved_path.read_bytes.return_value = file_content
+
+            with pytest.raises(VirusDetectedError):
+                await store_media_file(
+                    file=MediaFileType(local_file),
+                    execution_context=make_test_context(graph_exec_id=graph_exec_id),
+                    return_format="for_local_processing",
+                )
diff --git a/autogpt_platform/backend/backend/util/prompt.py b/autogpt_platform/backend/backend/util/prompt.py
index 775d1c932b..3ec25dd61b 100644
--- a/autogpt_platform/backend/backend/util/prompt.py
+++ b/autogpt_platform/backend/backend/util/prompt.py
@@ -1,10 +1,19 @@
+from __future__ import annotations
+
+import logging
 from copy import deepcopy
-from typing import Any
+from dataclasses import dataclass
+from typing import TYPE_CHECKING, Any
 
 from tiktoken import encoding_for_model
 
 from backend.util import json
 
+if TYPE_CHECKING:
+    from openai import AsyncOpenAI
+
+logger = logging.getLogger(__name__)
+
 # ---------------------------------------------------------------------------#
 #  CONSTANTS                                                                 #
 # ---------------------------------------------------------------------------#
@@ -100,9 +109,17 @@ def _is_objective_message(msg: dict) -> bool:
 def _truncate_tool_message_content(msg: dict, enc, max_tokens: int) -> None:
     """
     Carefully truncate tool message content while preserving tool structure.
-    Only truncates tool_result content, leaves tool_use intact.
+    Handles both Anthropic-style (list content) and OpenAI-style (string content) tool messages.
     """
     content = msg.get("content")
+
+    # OpenAI-style tool message: role="tool" with string content
+    if msg.get("role") == "tool" and isinstance(content, str):
+        if _tok_len(content, enc) > max_tokens:
+            msg["content"] = _truncate_middle_tokens(content, enc, max_tokens)
+        return
+
+    # Anthropic-style: list content with tool_result items
     if not isinstance(content, list):
         return
 
@@ -140,141 +157,6 @@ def _truncate_middle_tokens(text: str, enc, max_tok: int) -> str:
 # ---------------------------------------------------------------------------#
 
 
-def compress_prompt(
-    messages: list[dict],
-    target_tokens: int,
-    *,
-    model: str = "gpt-4o",
-    reserve: int = 2_048,
-    start_cap: int = 8_192,
-    floor_cap: int = 128,
-    lossy_ok: bool = True,
-) -> list[dict]:
-    """
-    Shrink *messages* so that::
-
-        token_count(prompt) + reserve  ≤  target_tokens
-
-    Strategy
-    --------
-    1. **Token-aware truncation** – progressively halve a per-message cap
-       (`start_cap`, `start_cap/2`, … `floor_cap`) and apply it to the
-       *content* of every message except the first and last.  Tool shells
-       are included: we keep the envelope but shorten huge payloads.
-    2. **Middle-out deletion** – if still over the limit, delete whole
-       messages working outward from the centre, **skipping** any message
-       that contains ``tool_calls`` or has ``role == "tool"``.
-    3. **Last-chance trim** – if still too big, truncate the *first* and
-       *last* message bodies down to `floor_cap` tokens.
-    4. If the prompt is *still* too large:
-         • raise ``ValueError``      when ``lossy_ok == False`` (default)
-         • return the partially-trimmed prompt when ``lossy_ok == True``
-
-    Parameters
-    ----------
-    messages        Complete chat history (will be deep-copied).
-    model           Model name; passed to tiktoken to pick the right
-                    tokenizer (gpt-4o → 'o200k_base', others fallback).
-    target_tokens   Hard ceiling for prompt size **excluding** the model's
-                    forthcoming answer.
-    reserve         How many tokens you want to leave available for that
-                    answer (`max_tokens` in your subsequent completion call).
-    start_cap       Initial per-message truncation ceiling (tokens).
-    floor_cap       Lowest cap we'll accept before moving to deletions.
-    lossy_ok        If *True* return best-effort prompt instead of raising
-                    after all trim passes have been exhausted.
-
-    Returns
-    -------
-    list[dict]  – A *new* messages list that abides by the rules above.
-    """
-    enc = encoding_for_model(model)  # best-match tokenizer
-    msgs = deepcopy(messages)  # never mutate caller
-
-    def total_tokens() -> int:
-        """Current size of *msgs* in tokens."""
-        return sum(_msg_tokens(m, enc) for m in msgs)
-
-    original_token_count = total_tokens()
-
-    if original_token_count + reserve <= target_tokens:
-        return msgs
-
-    # ---- STEP 0 : normalise content --------------------------------------
-    # Convert non-string payloads to strings so token counting is coherent.
-    for i, m in enumerate(msgs):
-        if not isinstance(m.get("content"), str) and m.get("content") is not None:
-            if _is_tool_message(m):
-                continue
-
-            # Keep first and last messages intact (unless they're tool messages)
-            if i == 0 or i == len(msgs) - 1:
-                continue
-
-            # Reasonable 20k-char ceiling prevents pathological blobs
-            content_str = json.dumps(m["content"], separators=(",", ":"))
-            if len(content_str) > 20_000:
-                content_str = _truncate_middle_tokens(content_str, enc, 20_000)
-            m["content"] = content_str
-
-    # ---- STEP 1 : token-aware truncation ---------------------------------
-    cap = start_cap
-    while total_tokens() + reserve > target_tokens and cap >= floor_cap:
-        for m in msgs[1:-1]:  # keep first & last intact
-            if _is_tool_message(m):
-                # For tool messages, only truncate tool result content, preserve structure
-                _truncate_tool_message_content(m, enc, cap)
-                continue
-
-            if _is_objective_message(m):
-                # Never truncate objective messages - they contain the core task
-                continue
-
-            content = m.get("content") or ""
-            if _tok_len(content, enc) > cap:
-                m["content"] = _truncate_middle_tokens(content, enc, cap)
-        cap //= 2  # tighten the screw
-
-    # ---- STEP 2 : middle-out deletion -----------------------------------
-    while total_tokens() + reserve > target_tokens and len(msgs) > 2:
-        # Identify all deletable messages (not first/last, not tool messages, not objective messages)
-        deletable_indices = []
-        for i in range(1, len(msgs) - 1):  # Skip first and last
-            if not _is_tool_message(msgs[i]) and not _is_objective_message(msgs[i]):
-                deletable_indices.append(i)
-
-        if not deletable_indices:
-            break  # nothing more we can drop
-
-        # Delete from center outward - find the index closest to center
-        centre = len(msgs) // 2
-        to_delete = min(deletable_indices, key=lambda i: abs(i - centre))
-        del msgs[to_delete]
-
-    # ---- STEP 3 : final safety-net trim on first & last ------------------
-    cap = start_cap
-    while total_tokens() + reserve > target_tokens and cap >= floor_cap:
-        for idx in (0, -1):  # first and last
-            if _is_tool_message(msgs[idx]):
-                # For tool messages at first/last position, truncate tool result content only
-                _truncate_tool_message_content(msgs[idx], enc, cap)
-                continue
-
-            text = msgs[idx].get("content") or ""
-            if _tok_len(text, enc) > cap:
-                msgs[idx]["content"] = _truncate_middle_tokens(text, enc, cap)
-        cap //= 2  # tighten the screw
-
-    # ---- STEP 4 : success or fail-gracefully -----------------------------
-    if total_tokens() + reserve > target_tokens and not lossy_ok:
-        raise ValueError(
-            "compress_prompt: prompt still exceeds budget "
-            f"({total_tokens() + reserve} > {target_tokens})."
-        )
-
-    return msgs
-
-
 def estimate_token_count(
     messages: list[dict],
     *,
@@ -293,7 +175,8 @@ def estimate_token_count(
     -------
     int  – Token count.
     """
-    enc = encoding_for_model(model)  # best-match tokenizer
+    token_model = _normalize_model_for_tokenizer(model)
+    enc = encoding_for_model(token_model)
     return sum(_msg_tokens(m, enc) for m in messages)
 
 
@@ -315,6 +198,588 @@ def estimate_token_count_str(
     -------
     int  – Token count.
     """
-    enc = encoding_for_model(model)  # best-match tokenizer
+    token_model = _normalize_model_for_tokenizer(model)
+    enc = encoding_for_model(token_model)
     text = json.dumps(text) if not isinstance(text, str) else text
     return _tok_len(text, enc)
+
+
+# ---------------------------------------------------------------------------#
+#  UNIFIED CONTEXT COMPRESSION                                               #
+# ---------------------------------------------------------------------------#
+
+# Default thresholds
+DEFAULT_TOKEN_THRESHOLD = 120_000
+DEFAULT_KEEP_RECENT = 15
+
+
+@dataclass
+class CompressResult:
+    """Result of context compression."""
+
+    messages: list[dict]
+    token_count: int
+    was_compacted: bool
+    error: str | None = None
+    original_token_count: int = 0
+    messages_summarized: int = 0
+    messages_dropped: int = 0
+
+
+def _normalize_model_for_tokenizer(model: str) -> str:
+    """Normalize model name for tiktoken tokenizer selection."""
+    if "/" in model:
+        model = model.split("/")[-1]
+    if "claude" in model.lower() or not any(
+        known in model.lower() for known in ["gpt", "o1", "chatgpt", "text-"]
+    ):
+        return "gpt-4o"
+    return model
+
+
+def _extract_tool_call_ids_from_message(msg: dict) -> set[str]:
+    """
+    Extract tool_call IDs from an assistant message.
+
+    Supports both formats:
+    - OpenAI: {"role": "assistant", "tool_calls": [{"id": "..."}]}
+    - Anthropic: {"role": "assistant", "content": [{"type": "tool_use", "id": "..."}]}
+
+    Returns:
+        Set of tool_call IDs found in the message.
+    """
+    ids: set[str] = set()
+    if msg.get("role") != "assistant":
+        return ids
+
+    # OpenAI format: tool_calls array
+    if msg.get("tool_calls"):
+        for tc in msg["tool_calls"]:
+            tc_id = tc.get("id")
+            if tc_id:
+                ids.add(tc_id)
+
+    # Anthropic format: content list with tool_use blocks
+    content = msg.get("content")
+    if isinstance(content, list):
+        for block in content:
+            if isinstance(block, dict) and block.get("type") == "tool_use":
+                tc_id = block.get("id")
+                if tc_id:
+                    ids.add(tc_id)
+
+    return ids
+
+
+def _extract_tool_response_ids_from_message(msg: dict) -> set[str]:
+    """
+    Extract tool_call IDs that this message is responding to.
+
+    Supports both formats:
+    - OpenAI: {"role": "tool", "tool_call_id": "..."}
+    - Anthropic: {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "..."}]}
+
+    Returns:
+        Set of tool_call IDs this message responds to.
+    """
+    ids: set[str] = set()
+
+    # OpenAI format: role=tool with tool_call_id
+    if msg.get("role") == "tool":
+        tc_id = msg.get("tool_call_id")
+        if tc_id:
+            ids.add(tc_id)
+
+    # Anthropic format: content list with tool_result blocks
+    content = msg.get("content")
+    if isinstance(content, list):
+        for block in content:
+            if isinstance(block, dict) and block.get("type") == "tool_result":
+                tc_id = block.get("tool_use_id")
+                if tc_id:
+                    ids.add(tc_id)
+
+    return ids
+
+
+def _is_tool_response_message(msg: dict) -> bool:
+    """Check if message is a tool response (OpenAI or Anthropic format)."""
+    # OpenAI format
+    if msg.get("role") == "tool":
+        return True
+    # Anthropic format
+    content = msg.get("content")
+    if isinstance(content, list):
+        for block in content:
+            if isinstance(block, dict) and block.get("type") == "tool_result":
+                return True
+    return False
+
+
+def _remove_orphan_tool_responses(
+    messages: list[dict], orphan_ids: set[str]
+) -> list[dict]:
+    """
+    Remove tool response messages/blocks that reference orphan tool_call IDs.
+
+    Supports both OpenAI and Anthropic formats.
+    For Anthropic messages with mixed valid/orphan tool_result blocks,
+    filters out only the orphan blocks instead of dropping the entire message.
+    """
+    result = []
+    for msg in messages:
+        # OpenAI format: role=tool - drop entire message if orphan
+        if msg.get("role") == "tool":
+            tc_id = msg.get("tool_call_id")
+            if tc_id and tc_id in orphan_ids:
+                continue
+            result.append(msg)
+            continue
+
+        # Anthropic format: content list may have mixed tool_result blocks
+        content = msg.get("content")
+        if isinstance(content, list):
+            has_tool_results = any(
+                isinstance(b, dict) and b.get("type") == "tool_result" for b in content
+            )
+            if has_tool_results:
+                # Filter out orphan tool_result blocks, keep valid ones
+                filtered_content = [
+                    block
+                    for block in content
+                    if not (
+                        isinstance(block, dict)
+                        and block.get("type") == "tool_result"
+                        and block.get("tool_use_id") in orphan_ids
+                    )
+                ]
+                # Only keep message if it has remaining content
+                if filtered_content:
+                    msg = msg.copy()
+                    msg["content"] = filtered_content
+                    result.append(msg)
+                continue
+
+        result.append(msg)
+    return result
+
+
+def validate_and_remove_orphan_tool_responses(
+    messages: list[dict],
+    log_warning: bool = True,
+) -> list[dict]:
+    """
+    Validate tool_call/tool_response pairs and remove orphaned responses.
+
+    Scans messages in order, tracking all tool_call IDs. Any tool response
+    referencing an ID not seen in a preceding message is considered orphaned
+    and removed. This prevents API errors like Anthropic's "unexpected tool_use_id".
+
+    Args:
+        messages: List of messages to validate (OpenAI or Anthropic format)
+        log_warning: Whether to log a warning when orphans are found
+
+    Returns:
+        A new list with orphaned tool responses removed
+    """
+    available_ids: set[str] = set()
+    orphan_ids: set[str] = set()
+
+    for msg in messages:
+        available_ids |= _extract_tool_call_ids_from_message(msg)
+        for resp_id in _extract_tool_response_ids_from_message(msg):
+            if resp_id not in available_ids:
+                orphan_ids.add(resp_id)
+
+    if not orphan_ids:
+        return messages
+
+    if log_warning:
+        logger.warning(
+            f"Removing {len(orphan_ids)} orphan tool response(s): {orphan_ids}"
+        )
+
+    return _remove_orphan_tool_responses(messages, orphan_ids)
+
+
+def _ensure_tool_pairs_intact(
+    recent_messages: list[dict],
+    all_messages: list[dict],
+    start_index: int,
+) -> list[dict]:
+    """
+    Ensure tool_call/tool_response pairs stay together after slicing.
+
+    When slicing messages for context compaction, a naive slice can separate
+    an assistant message containing tool_calls from its corresponding tool
+    response messages. This causes API validation errors (e.g., Anthropic's
+    "unexpected tool_use_id found in tool_result blocks").
+
+    This function checks for orphan tool responses in the slice and extends
+    backwards to include their corresponding assistant messages.
+
+    Supports both formats:
+    - OpenAI: tool_calls array + role="tool" responses
+    - Anthropic: tool_use blocks + tool_result blocks
+
+    Args:
+        recent_messages: The sliced messages to validate
+        all_messages: The complete message list (for looking up missing assistants)
+        start_index: The index in all_messages where recent_messages begins
+
+    Returns:
+        A potentially extended list of messages with tool pairs intact
+    """
+    if not recent_messages:
+        return recent_messages
+
+    # Collect all tool_call_ids from assistant messages in the slice
+    available_tool_call_ids: set[str] = set()
+    for msg in recent_messages:
+        available_tool_call_ids |= _extract_tool_call_ids_from_message(msg)
+
+    # Find orphan tool responses (responses whose tool_call_id is missing)
+    orphan_tool_call_ids: set[str] = set()
+    for msg in recent_messages:
+        response_ids = _extract_tool_response_ids_from_message(msg)
+        for tc_id in response_ids:
+            if tc_id not in available_tool_call_ids:
+                orphan_tool_call_ids.add(tc_id)
+
+    if not orphan_tool_call_ids:
+        # No orphans, slice is valid
+        return recent_messages
+
+    # Find the assistant messages that contain the orphan tool_call_ids
+    # Search backwards from start_index in all_messages
+    messages_to_prepend: list[dict] = []
+    for i in range(start_index - 1, -1, -1):
+        msg = all_messages[i]
+        msg_tool_ids = _extract_tool_call_ids_from_message(msg)
+        if msg_tool_ids & orphan_tool_call_ids:
+            # This assistant message has tool_calls we need
+            # Also collect its contiguous tool responses that follow it
+            assistant_and_responses: list[dict] = [msg]
+
+            # Scan forward from this assistant to collect tool responses
+            for j in range(i + 1, start_index):
+                following_msg = all_messages[j]
+                following_response_ids = _extract_tool_response_ids_from_message(
+                    following_msg
+                )
+                if following_response_ids and following_response_ids & msg_tool_ids:
+                    assistant_and_responses.append(following_msg)
+                elif not _is_tool_response_message(following_msg):
+                    # Stop at first non-tool-response message
+                    break
+
+            # Prepend the assistant and its tool responses (maintain order)
+            messages_to_prepend = assistant_and_responses + messages_to_prepend
+            # Mark these as found
+            orphan_tool_call_ids -= msg_tool_ids
+            # Also add this assistant's tool_call_ids to available set
+            available_tool_call_ids |= msg_tool_ids
+
+        if not orphan_tool_call_ids:
+            # Found all missing assistants
+            break
+
+    if orphan_tool_call_ids:
+        # Some tool_call_ids couldn't be resolved - remove those tool responses
+        # This shouldn't happen in normal operation but handles edge cases
+        logger.warning(
+            f"Could not find assistant messages for tool_call_ids: {orphan_tool_call_ids}. "
+            "Removing orphan tool responses."
+        )
+        recent_messages = _remove_orphan_tool_responses(
+            recent_messages, orphan_tool_call_ids
+        )
+
+    if messages_to_prepend:
+        logger.info(
+            f"Extended recent messages by {len(messages_to_prepend)} to preserve "
+            f"tool_call/tool_response pairs"
+        )
+        return messages_to_prepend + recent_messages
+
+    return recent_messages
+
+
+async def _summarize_messages_llm(
+    messages: list[dict],
+    client: AsyncOpenAI,
+    model: str,
+    timeout: float = 30.0,
+) -> str:
+    """Summarize messages using an LLM."""
+    conversation = []
+    for msg in messages:
+        role = msg.get("role", "")
+        content = msg.get("content", "")
+        if content and role in ("user", "assistant", "tool"):
+            conversation.append(f"{role.upper()}: {content}")
+
+    conversation_text = "\n\n".join(conversation)
+
+    if not conversation_text:
+        return "No conversation history available."
+
+    # Limit to ~100k chars for safety
+    MAX_CHARS = 100_000
+    if len(conversation_text) > MAX_CHARS:
+        conversation_text = conversation_text[:MAX_CHARS] + "\n\n[truncated]"
+
+    response = await client.with_options(timeout=timeout).chat.completions.create(
+        model=model,
+        messages=[
+            {
+                "role": "system",
+                "content": (
+                    "Create a detailed summary of the conversation so far. "
+                    "This summary will be used as context when continuing the conversation.\n\n"
+                    "Before writing the summary, analyze each message chronologically to identify:\n"
+                    "- User requests and their explicit goals\n"
+                    "- Your approach and key decisions made\n"
+                    "- Technical specifics (file names, tool outputs, function signatures)\n"
+                    "- Errors encountered and resolutions applied\n\n"
+                    "You MUST include ALL of the following sections:\n\n"
+                    "## 1. Primary Request and Intent\n"
+                    "The user's explicit goals and what they are trying to accomplish.\n\n"
+                    "## 2. Key Technical Concepts\n"
+                    "Technologies, frameworks, tools, and patterns being used or discussed.\n\n"
+                    "## 3. Files and Resources Involved\n"
+                    "Specific files examined or modified, with relevant snippets and identifiers.\n\n"
+                    "## 4. Errors and Fixes\n"
+                    "Problems encountered, error messages, and their resolutions. "
+                    "Include any user feedback on fixes.\n\n"
+                    "## 5. Problem Solving\n"
+                    "Issues that have been resolved and how they were addressed.\n\n"
+                    "## 6. All User Messages\n"
+                    "A complete list of all user inputs (excluding tool outputs) to preserve their exact requests.\n\n"
+                    "## 7. Pending Tasks\n"
+                    "Work items the user explicitly requested that have not yet been completed.\n\n"
+                    "## 8. Current Work\n"
+                    "Precise description of what was being worked on most recently, including relevant context.\n\n"
+                    "## 9. Next Steps\n"
+                    "What should happen next, aligned with the user's most recent requests. "
+                    "Include verbatim quotes of recent instructions if relevant."
+                ),
+            },
+            {"role": "user", "content": f"Summarize:\n\n{conversation_text}"},
+        ],
+        max_tokens=1500,
+        temperature=0.3,
+    )
+
+    return response.choices[0].message.content or "No summary available."
+
+
+async def compress_context(
+    messages: list[dict],
+    target_tokens: int = DEFAULT_TOKEN_THRESHOLD,
+    *,
+    model: str = "gpt-4o",
+    client: AsyncOpenAI | None = None,
+    keep_recent: int = DEFAULT_KEEP_RECENT,
+    reserve: int = 2_048,
+    start_cap: int = 8_192,
+    floor_cap: int = 128,
+) -> CompressResult:
+    """
+    Unified context compression that combines summarization and truncation strategies.
+
+    Strategy (in order):
+    1. **LLM summarization** – If client provided, summarize old messages into a
+       single context message while keeping recent messages intact. This is the
+       primary strategy for chat service.
+    2. **Content truncation** – Progressively halve a per-message cap and truncate
+       bloated message content (tool outputs, large pastes). Preserves all messages
+       but shortens their content. Primary strategy when client=None (LLM blocks).
+    3. **Middle-out deletion** – Delete whole messages one at a time from the center
+       outward, skipping tool messages and objective messages.
+    4. **First/last trim** – Truncate first and last message content as last resort.
+
+    Parameters
+    ----------
+    messages        Complete chat history (will be deep-copied).
+    target_tokens   Hard ceiling for prompt size.
+    model           Model name for tokenization and summarization.
+    client          AsyncOpenAI client. If provided, enables LLM summarization
+                    as the first strategy. If None, skips to truncation strategies.
+    keep_recent     Number of recent messages to preserve during summarization.
+    reserve         Tokens to reserve for model response.
+    start_cap       Initial per-message truncation ceiling (tokens).
+    floor_cap       Lowest cap before moving to deletions.
+
+    Returns
+    -------
+    CompressResult with compressed messages and metadata.
+    """
+    # Guard clause for empty messages
+    if not messages:
+        return CompressResult(
+            messages=[],
+            token_count=0,
+            was_compacted=False,
+            original_token_count=0,
+        )
+
+    token_model = _normalize_model_for_tokenizer(model)
+    enc = encoding_for_model(token_model)
+    msgs = deepcopy(messages)
+
+    def total_tokens() -> int:
+        return sum(_msg_tokens(m, enc) for m in msgs)
+
+    original_count = total_tokens()
+
+    # Already under limit
+    if original_count + reserve <= target_tokens:
+        return CompressResult(
+            messages=msgs,
+            token_count=original_count,
+            was_compacted=False,
+            original_token_count=original_count,
+        )
+
+    messages_summarized = 0
+    messages_dropped = 0
+
+    # ---- STEP 1: LLM summarization (if client provided) -------------------
+    # This is the primary compression strategy for chat service.
+    # Summarize old messages while keeping recent ones intact.
+    if client is not None:
+        has_system = len(msgs) > 0 and msgs[0].get("role") == "system"
+        system_msg = msgs[0] if has_system else None
+
+        # Calculate old vs recent messages
+        if has_system:
+            if len(msgs) > keep_recent + 1:
+                old_msgs = msgs[1:-keep_recent]
+                recent_msgs = msgs[-keep_recent:]
+            else:
+                old_msgs = []
+                recent_msgs = msgs[1:] if len(msgs) > 1 else []
+        else:
+            if len(msgs) > keep_recent:
+                old_msgs = msgs[:-keep_recent]
+                recent_msgs = msgs[-keep_recent:]
+            else:
+                old_msgs = []
+                recent_msgs = msgs
+
+        # Ensure tool pairs stay intact
+        slice_start = max(0, len(msgs) - keep_recent)
+        recent_msgs = _ensure_tool_pairs_intact(recent_msgs, msgs, slice_start)
+
+        if old_msgs:
+            try:
+                summary_text = await _summarize_messages_llm(old_msgs, client, model)
+                summary_msg = {
+                    "role": "assistant",
+                    "content": f"[Previous conversation summary — for context only]: {summary_text}",
+                }
+                messages_summarized = len(old_msgs)
+
+                if has_system:
+                    msgs = [system_msg, summary_msg] + recent_msgs
+                else:
+                    msgs = [summary_msg] + recent_msgs
+
+                logger.info(
+                    f"Context summarized: {original_count} -> {total_tokens()} tokens, "
+                    f"summarized {messages_summarized} messages"
+                )
+            except Exception as e:
+                logger.warning(f"Summarization failed, continuing with truncation: {e}")
+                # Fall through to content truncation
+
+    # ---- STEP 2: Normalize content ----------------------------------------
+    # Convert non-string payloads to strings so token counting is coherent.
+    # Always run this before truncation to ensure consistent token counting.
+    for i, m in enumerate(msgs):
+        if not isinstance(m.get("content"), str) and m.get("content") is not None:
+            if _is_tool_message(m):
+                continue
+            if i == 0 or i == len(msgs) - 1:
+                continue
+            content_str = json.dumps(m["content"], separators=(",", ":"))
+            if len(content_str) > 20_000:
+                content_str = _truncate_middle_tokens(content_str, enc, 20_000)
+            m["content"] = content_str
+
+    # ---- STEP 3: Token-aware content truncation ---------------------------
+    # Progressively halve per-message cap and truncate bloated content.
+    # This preserves all messages but shortens their content.
+    cap = start_cap
+    while total_tokens() + reserve > target_tokens and cap >= floor_cap:
+        for m in msgs[1:-1]:
+            if _is_tool_message(m):
+                _truncate_tool_message_content(m, enc, cap)
+                continue
+            if _is_objective_message(m):
+                continue
+            content = m.get("content") or ""
+            if _tok_len(content, enc) > cap:
+                m["content"] = _truncate_middle_tokens(content, enc, cap)
+        cap //= 2
+
+    # ---- STEP 4: Middle-out deletion --------------------------------------
+    # Delete messages one at a time from the center outward.
+    # This is more granular than dropping all old messages at once.
+    while total_tokens() + reserve > target_tokens and len(msgs) > 2:
+        deletable: list[int] = []
+        for i in range(1, len(msgs) - 1):
+            msg = msgs[i]
+            if (
+                msg is not None
+                and not _is_tool_message(msg)
+                and not _is_objective_message(msg)
+            ):
+                deletable.append(i)
+        if not deletable:
+            break
+        centre = len(msgs) // 2
+        to_delete = min(deletable, key=lambda i: abs(i - centre))
+        del msgs[to_delete]
+        messages_dropped += 1
+
+    # ---- STEP 5: Final trim on first/last ---------------------------------
+    cap = start_cap
+    while total_tokens() + reserve > target_tokens and cap >= floor_cap:
+        for idx in (0, -1):
+            msg = msgs[idx]
+            if msg is None:
+                continue
+            if _is_tool_message(msg):
+                _truncate_tool_message_content(msg, enc, cap)
+                continue
+            text = msg.get("content") or ""
+            if _tok_len(text, enc) > cap:
+                msg["content"] = _truncate_middle_tokens(text, enc, cap)
+        cap //= 2
+
+    # Filter out any None values that may have been introduced
+    final_msgs: list[dict] = [m for m in msgs if m is not None]
+
+    # ---- STEP 6: Final tool-pair validation ---------------------------------
+    # After all compression steps, verify that every tool response has a
+    # matching tool_call in a preceding assistant message. Remove orphans
+    # to prevent API errors (e.g., Anthropic's "unexpected tool_use_id").
+    final_msgs = validate_and_remove_orphan_tool_responses(final_msgs)
+
+    final_count = sum(_msg_tokens(m, enc) for m in final_msgs)
+    error = None
+    if final_count + reserve > target_tokens:
+        error = f"Could not compress below target ({final_count + reserve} > {target_tokens})"
+        logger.warning(error)
+
+    return CompressResult(
+        messages=final_msgs,
+        token_count=final_count,
+        was_compacted=True,
+        error=error,
+        original_token_count=original_count,
+        messages_summarized=messages_summarized,
+        messages_dropped=messages_dropped,
+    )
diff --git a/autogpt_platform/backend/backend/util/prompt_test.py b/autogpt_platform/backend/backend/util/prompt_test.py
index af6b230f8f..2d4bf090b3 100644
--- a/autogpt_platform/backend/backend/util/prompt_test.py
+++ b/autogpt_platform/backend/backend/util/prompt_test.py
@@ -1,10 +1,21 @@
 """Tests for prompt utility functions, especially tool call token counting."""
 
+from unittest.mock import AsyncMock, MagicMock
+
 import pytest
 from tiktoken import encoding_for_model
 
 from backend.util import json
-from backend.util.prompt import _msg_tokens, estimate_token_count
+from backend.util.prompt import (
+    CompressResult,
+    _ensure_tool_pairs_intact,
+    _msg_tokens,
+    _normalize_model_for_tokenizer,
+    _truncate_middle_tokens,
+    _truncate_tool_message_content,
+    compress_context,
+    estimate_token_count,
+)
 
 
 class TestMsgTokens:
@@ -276,3 +287,690 @@ class TestEstimateTokenCount:
 
         assert total_tokens == expected_total
         assert total_tokens > 20  # Should be substantial
+
+
+class TestNormalizeModelForTokenizer:
+    """Test model name normalization for tiktoken."""
+
+    def test_openai_models_unchanged(self):
+        """Test that OpenAI models are returned as-is."""
+        assert _normalize_model_for_tokenizer("gpt-4o") == "gpt-4o"
+        assert _normalize_model_for_tokenizer("gpt-4") == "gpt-4"
+        assert _normalize_model_for_tokenizer("gpt-3.5-turbo") == "gpt-3.5-turbo"
+
+    def test_claude_models_normalized(self):
+        """Test that Claude models are normalized to gpt-4o."""
+        assert _normalize_model_for_tokenizer("claude-3-opus") == "gpt-4o"
+        assert _normalize_model_for_tokenizer("claude-3-sonnet") == "gpt-4o"
+        assert _normalize_model_for_tokenizer("anthropic/claude-3-haiku") == "gpt-4o"
+
+    def test_openrouter_paths_extracted(self):
+        """Test that OpenRouter model paths are handled."""
+        assert _normalize_model_for_tokenizer("openai/gpt-4o") == "gpt-4o"
+        assert _normalize_model_for_tokenizer("anthropic/claude-3-opus") == "gpt-4o"
+
+    def test_unknown_models_default_to_gpt4o(self):
+        """Test that unknown models default to gpt-4o."""
+        assert _normalize_model_for_tokenizer("some-random-model") == "gpt-4o"
+        assert _normalize_model_for_tokenizer("llama-3-70b") == "gpt-4o"
+
+
+class TestTruncateToolMessageContent:
+    """Test tool message content truncation."""
+
+    @pytest.fixture
+    def enc(self):
+        return encoding_for_model("gpt-4o")
+
+    def test_truncate_openai_tool_message(self, enc):
+        """Test truncation of OpenAI-style tool message with string content."""
+        long_content = "x" * 10000
+        msg = {"role": "tool", "tool_call_id": "call_123", "content": long_content}
+
+        _truncate_tool_message_content(msg, enc, max_tokens=100)
+
+        # Content should be truncated
+        assert len(msg["content"]) < len(long_content)
+        assert "…" in msg["content"]  # Has ellipsis marker
+
+    def test_truncate_anthropic_tool_result(self, enc):
+        """Test truncation of Anthropic-style tool_result."""
+        long_content = "y" * 10000
+        msg = {
+            "role": "user",
+            "content": [
+                {
+                    "type": "tool_result",
+                    "tool_use_id": "toolu_123",
+                    "content": long_content,
+                }
+            ],
+        }
+
+        _truncate_tool_message_content(msg, enc, max_tokens=100)
+
+        # Content should be truncated
+        result_content = msg["content"][0]["content"]
+        assert len(result_content) < len(long_content)
+        assert "…" in result_content
+
+    def test_preserve_tool_use_blocks(self, enc):
+        """Test that tool_use blocks are not truncated."""
+        msg = {
+            "role": "assistant",
+            "content": [
+                {
+                    "type": "tool_use",
+                    "id": "toolu_123",
+                    "name": "some_function",
+                    "input": {"key": "value" * 1000},  # Large input
+                }
+            ],
+        }
+
+        original = json.dumps(msg["content"][0]["input"])
+        _truncate_tool_message_content(msg, enc, max_tokens=10)
+
+        # tool_use should be unchanged
+        assert json.dumps(msg["content"][0]["input"]) == original
+
+    def test_no_truncation_when_under_limit(self, enc):
+        """Test that short content is not modified."""
+        msg = {"role": "tool", "tool_call_id": "call_123", "content": "Short content"}
+
+        original = msg["content"]
+        _truncate_tool_message_content(msg, enc, max_tokens=1000)
+
+        assert msg["content"] == original
+
+
+class TestTruncateMiddleTokens:
+    """Test middle truncation of text."""
+
+    @pytest.fixture
+    def enc(self):
+        return encoding_for_model("gpt-4o")
+
+    def test_truncates_long_text(self, enc):
+        """Test that long text is truncated with ellipsis in middle."""
+        long_text = "word " * 1000
+        result = _truncate_middle_tokens(long_text, enc, max_tok=50)
+
+        assert len(enc.encode(result)) <= 52  # Allow some slack for ellipsis
+        assert "…" in result
+        assert result.startswith("word")  # Head preserved
+        assert result.endswith("word ")  # Tail preserved
+
+    def test_preserves_short_text(self, enc):
+        """Test that short text is not modified."""
+        short_text = "Hello world"
+        result = _truncate_middle_tokens(short_text, enc, max_tok=100)
+
+        assert result == short_text
+
+
+class TestEnsureToolPairsIntact:
+    """Test tool call/response pair preservation for both OpenAI and Anthropic formats."""
+
+    # ---- OpenAI Format Tests ----
+
+    def test_openai_adds_missing_tool_call(self):
+        """Test that orphaned OpenAI tool_response gets its tool_call prepended."""
+        all_msgs = [
+            {"role": "system", "content": "You are helpful."},
+            {
+                "role": "assistant",
+                "tool_calls": [
+                    {"id": "call_1", "type": "function", "function": {"name": "f1"}}
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "result"},
+            {"role": "user", "content": "Thanks!"},
+        ]
+        # Recent messages start at index 2 (the tool response)
+        recent = [all_msgs[2], all_msgs[3]]
+        start_index = 2
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        # Should prepend the tool_call message
+        assert len(result) == 3
+        assert result[0]["role"] == "assistant"
+        assert "tool_calls" in result[0]
+
+    def test_openai_keeps_complete_pairs(self):
+        """Test that complete OpenAI pairs are unchanged."""
+        all_msgs = [
+            {"role": "system", "content": "System"},
+            {
+                "role": "assistant",
+                "tool_calls": [
+                    {"id": "call_1", "type": "function", "function": {"name": "f1"}}
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "result"},
+        ]
+        recent = all_msgs[1:]  # Include both tool_call and response
+        start_index = 1
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        assert len(result) == 2  # No messages added
+
+    def test_openai_multiple_tool_calls(self):
+        """Test multiple OpenAI tool calls in one assistant message."""
+        all_msgs = [
+            {"role": "system", "content": "System"},
+            {
+                "role": "assistant",
+                "tool_calls": [
+                    {"id": "call_1", "type": "function", "function": {"name": "f1"}},
+                    {"id": "call_2", "type": "function", "function": {"name": "f2"}},
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "result1"},
+            {"role": "tool", "tool_call_id": "call_2", "content": "result2"},
+            {"role": "user", "content": "Thanks!"},
+        ]
+        # Recent messages start at index 2 (first tool response)
+        recent = [all_msgs[2], all_msgs[3], all_msgs[4]]
+        start_index = 2
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        # Should prepend the assistant message with both tool_calls
+        assert len(result) == 4
+        assert result[0]["role"] == "assistant"
+        assert len(result[0]["tool_calls"]) == 2
+
+    # ---- Anthropic Format Tests ----
+
+    def test_anthropic_adds_missing_tool_use(self):
+        """Test that orphaned Anthropic tool_result gets its tool_use prepended."""
+        all_msgs = [
+            {"role": "system", "content": "You are helpful."},
+            {
+                "role": "assistant",
+                "content": [
+                    {
+                        "type": "tool_use",
+                        "id": "toolu_123",
+                        "name": "get_weather",
+                        "input": {"location": "SF"},
+                    }
+                ],
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_123",
+                        "content": "22°C and sunny",
+                    }
+                ],
+            },
+            {"role": "user", "content": "Thanks!"},
+        ]
+        # Recent messages start at index 2 (the tool_result)
+        recent = [all_msgs[2], all_msgs[3]]
+        start_index = 2
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        # Should prepend the tool_use message
+        assert len(result) == 3
+        assert result[0]["role"] == "assistant"
+        assert result[0]["content"][0]["type"] == "tool_use"
+
+    def test_anthropic_keeps_complete_pairs(self):
+        """Test that complete Anthropic pairs are unchanged."""
+        all_msgs = [
+            {"role": "system", "content": "System"},
+            {
+                "role": "assistant",
+                "content": [
+                    {
+                        "type": "tool_use",
+                        "id": "toolu_456",
+                        "name": "calculator",
+                        "input": {"expr": "2+2"},
+                    }
+                ],
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_456",
+                        "content": "4",
+                    }
+                ],
+            },
+        ]
+        recent = all_msgs[1:]  # Include both tool_use and result
+        start_index = 1
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        assert len(result) == 2  # No messages added
+
+    def test_anthropic_multiple_tool_uses(self):
+        """Test multiple Anthropic tool_use blocks in one message."""
+        all_msgs = [
+            {"role": "system", "content": "System"},
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "text", "text": "Let me check both..."},
+                    {
+                        "type": "tool_use",
+                        "id": "toolu_1",
+                        "name": "get_weather",
+                        "input": {"city": "NYC"},
+                    },
+                    {
+                        "type": "tool_use",
+                        "id": "toolu_2",
+                        "name": "get_weather",
+                        "input": {"city": "LA"},
+                    },
+                ],
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_1",
+                        "content": "Cold",
+                    },
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_2",
+                        "content": "Warm",
+                    },
+                ],
+            },
+            {"role": "user", "content": "Thanks!"},
+        ]
+        # Recent messages start at index 2 (tool_result)
+        recent = [all_msgs[2], all_msgs[3]]
+        start_index = 2
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        # Should prepend the assistant message with both tool_uses
+        assert len(result) == 3
+        assert result[0]["role"] == "assistant"
+        tool_use_count = sum(
+            1 for b in result[0]["content"] if b.get("type") == "tool_use"
+        )
+        assert tool_use_count == 2
+
+    # ---- Mixed/Edge Case Tests ----
+
+    def test_anthropic_with_type_message_field(self):
+        """Test Anthropic format with 'type': 'message' field (smart_decision_maker style)."""
+        all_msgs = [
+            {"role": "system", "content": "You are helpful."},
+            {
+                "role": "assistant",
+                "content": [
+                    {
+                        "type": "tool_use",
+                        "id": "toolu_abc",
+                        "name": "search",
+                        "input": {"q": "test"},
+                    }
+                ],
+            },
+            {
+                "role": "user",
+                "type": "message",  # Extra field from smart_decision_maker
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_abc",
+                        "content": "Found results",
+                    }
+                ],
+            },
+            {"role": "user", "content": "Thanks!"},
+        ]
+        # Recent messages start at index 2 (the tool_result with 'type': 'message')
+        recent = [all_msgs[2], all_msgs[3]]
+        start_index = 2
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        # Should prepend the tool_use message
+        assert len(result) == 3
+        assert result[0]["role"] == "assistant"
+        assert result[0]["content"][0]["type"] == "tool_use"
+
+    def test_handles_no_tool_messages(self):
+        """Test messages without tool calls."""
+        all_msgs = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there!"},
+        ]
+        recent = all_msgs
+        start_index = 0
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        assert result == all_msgs
+
+    def test_handles_empty_messages(self):
+        """Test empty message list."""
+        result = _ensure_tool_pairs_intact([], [], 0)
+        assert result == []
+
+    def test_mixed_text_and_tool_content(self):
+        """Test Anthropic message with mixed text and tool_use content."""
+        all_msgs = [
+            {
+                "role": "assistant",
+                "content": [
+                    {"type": "text", "text": "I'll help you with that."},
+                    {
+                        "type": "tool_use",
+                        "id": "toolu_mixed",
+                        "name": "search",
+                        "input": {"q": "test"},
+                    },
+                ],
+            },
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_mixed",
+                        "content": "Found results",
+                    }
+                ],
+            },
+            {"role": "assistant", "content": "Here are the results..."},
+        ]
+        # Start from tool_result
+        recent = [all_msgs[1], all_msgs[2]]
+        start_index = 1
+
+        result = _ensure_tool_pairs_intact(recent, all_msgs, start_index)
+
+        # Should prepend the assistant message with tool_use
+        assert len(result) == 3
+        assert result[0]["content"][0]["type"] == "text"
+        assert result[0]["content"][1]["type"] == "tool_use"
+
+
+class TestCompressContext:
+    """Test the async compress_context function."""
+
+    @pytest.mark.asyncio
+    async def test_no_compression_needed(self):
+        """Test messages under limit return without compression."""
+        messages = [
+            {"role": "system", "content": "You are helpful."},
+            {"role": "user", "content": "Hello!"},
+        ]
+
+        result = await compress_context(messages, target_tokens=100000)
+
+        assert isinstance(result, CompressResult)
+        assert result.was_compacted is False
+        assert len(result.messages) == 2
+        assert result.error is None
+
+    @pytest.mark.asyncio
+    async def test_truncation_without_client(self):
+        """Test that truncation works without LLM client."""
+        long_content = "x" * 50000
+        messages = [
+            {"role": "system", "content": "System"},
+            {"role": "user", "content": long_content},
+            {"role": "assistant", "content": "Response"},
+        ]
+
+        result = await compress_context(
+            messages, target_tokens=1000, client=None, reserve=100
+        )
+
+        assert result.was_compacted is True
+        # Should have truncated without summarization
+        assert result.messages_summarized == 0
+
+    @pytest.mark.asyncio
+    async def test_with_mocked_llm_client(self):
+        """Test summarization with mocked LLM client."""
+        # Create many messages to trigger summarization
+        messages = [{"role": "system", "content": "System prompt"}]
+        for i in range(30):
+            messages.append({"role": "user", "content": f"User message {i} " * 100})
+            messages.append(
+                {"role": "assistant", "content": f"Assistant response {i} " * 100}
+            )
+
+        # Mock the AsyncOpenAI client
+        mock_client = AsyncMock()
+        mock_response = MagicMock()
+        mock_response.choices = [MagicMock()]
+        mock_response.choices[0].message.content = "Summary of conversation"
+        mock_client.with_options.return_value.chat.completions.create = AsyncMock(
+            return_value=mock_response
+        )
+
+        result = await compress_context(
+            messages,
+            target_tokens=5000,
+            client=mock_client,
+            keep_recent=5,
+            reserve=500,
+        )
+
+        assert result.was_compacted is True
+        # Should have attempted summarization
+        assert mock_client.with_options.called or result.messages_summarized > 0
+
+    @pytest.mark.asyncio
+    async def test_preserves_tool_pairs(self):
+        """Test that tool call/response pairs stay together."""
+        messages = [
+            {"role": "system", "content": "System"},
+            {"role": "user", "content": "Do something"},
+            {
+                "role": "assistant",
+                "tool_calls": [
+                    {"id": "call_1", "type": "function", "function": {"name": "func"}}
+                ],
+            },
+            {"role": "tool", "tool_call_id": "call_1", "content": "Result " * 1000},
+            {"role": "assistant", "content": "Done!"},
+        ]
+
+        result = await compress_context(
+            messages, target_tokens=500, client=None, reserve=50
+        )
+
+        # Check that if tool response exists, its call exists too
+        tool_call_ids = set()
+        tool_response_ids = set()
+        for msg in result.messages:
+            if "tool_calls" in msg:
+                for tc in msg["tool_calls"]:
+                    tool_call_ids.add(tc["id"])
+            if msg.get("role") == "tool":
+                tool_response_ids.add(msg.get("tool_call_id"))
+
+        # All tool responses should have their calls
+        assert tool_response_ids <= tool_call_ids
+
+    @pytest.mark.asyncio
+    async def test_returns_error_when_cannot_compress(self):
+        """Test that error is returned when compression fails."""
+        # Single huge message that can't be compressed enough
+        messages = [
+            {"role": "user", "content": "x" * 100000},
+        ]
+
+        result = await compress_context(
+            messages, target_tokens=100, client=None, reserve=50
+        )
+
+        # Should have an error since we can't get below 100 tokens
+        assert result.error is not None
+        assert result.was_compacted is True
+
+    @pytest.mark.asyncio
+    async def test_empty_messages(self):
+        """Test that empty messages list returns early without error."""
+        result = await compress_context([], target_tokens=1000)
+
+        assert result.messages == []
+        assert result.token_count == 0
+        assert result.was_compacted is False
+        assert result.error is None
+
+
+class TestRemoveOrphanToolResponses:
+    """Test _remove_orphan_tool_responses helper function."""
+
+    def test_removes_openai_orphan(self):
+        """Test removal of orphan OpenAI tool response."""
+        from backend.util.prompt import _remove_orphan_tool_responses
+
+        messages = [
+            {"role": "tool", "tool_call_id": "call_orphan", "content": "result"},
+            {"role": "user", "content": "Hello"},
+        ]
+        orphan_ids = {"call_orphan"}
+
+        result = _remove_orphan_tool_responses(messages, orphan_ids)
+
+        assert len(result) == 1
+        assert result[0]["role"] == "user"
+
+    def test_keeps_valid_openai_tool(self):
+        """Test that valid OpenAI tool responses are kept."""
+        from backend.util.prompt import _remove_orphan_tool_responses
+
+        messages = [
+            {"role": "tool", "tool_call_id": "call_valid", "content": "result"},
+        ]
+        orphan_ids = {"call_other"}
+
+        result = _remove_orphan_tool_responses(messages, orphan_ids)
+
+        assert len(result) == 1
+        assert result[0]["tool_call_id"] == "call_valid"
+
+    def test_filters_anthropic_mixed_blocks(self):
+        """Test filtering individual orphan blocks from Anthropic message with mixed valid/orphan."""
+        from backend.util.prompt import _remove_orphan_tool_responses
+
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_valid",
+                        "content": "valid result",
+                    },
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_orphan",
+                        "content": "orphan result",
+                    },
+                ],
+            },
+        ]
+        orphan_ids = {"toolu_orphan"}
+
+        result = _remove_orphan_tool_responses(messages, orphan_ids)
+
+        assert len(result) == 1
+        # Should only have the valid tool_result, orphan filtered out
+        assert len(result[0]["content"]) == 1
+        assert result[0]["content"][0]["tool_use_id"] == "toolu_valid"
+
+    def test_removes_anthropic_all_orphan(self):
+        """Test removal of Anthropic message when all tool_results are orphans."""
+        from backend.util.prompt import _remove_orphan_tool_responses
+
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_orphan1",
+                        "content": "result1",
+                    },
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "toolu_orphan2",
+                        "content": "result2",
+                    },
+                ],
+            },
+        ]
+        orphan_ids = {"toolu_orphan1", "toolu_orphan2"}
+
+        result = _remove_orphan_tool_responses(messages, orphan_ids)
+
+        # Message should be completely removed since no content left
+        assert len(result) == 0
+
+    def test_preserves_non_tool_messages(self):
+        """Test that non-tool messages are preserved."""
+        from backend.util.prompt import _remove_orphan_tool_responses
+
+        messages = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there!"},
+        ]
+        orphan_ids = {"some_id"}
+
+        result = _remove_orphan_tool_responses(messages, orphan_ids)
+
+        assert result == messages
+
+
+class TestCompressResultDataclass:
+    """Test CompressResult dataclass."""
+
+    def test_default_values(self):
+        """Test default values are set correctly."""
+        result = CompressResult(
+            messages=[{"role": "user", "content": "test"}],
+            token_count=10,
+            was_compacted=False,
+        )
+
+        assert result.error is None
+        assert result.original_token_count == 0  # Defaults to 0, not None
+        assert result.messages_summarized == 0
+        assert result.messages_dropped == 0
+
+    def test_all_fields(self):
+        """Test all fields can be set."""
+        result = CompressResult(
+            messages=[{"role": "user", "content": "test"}],
+            token_count=100,
+            was_compacted=True,
+            error="Some error",
+            original_token_count=500,
+            messages_summarized=10,
+            messages_dropped=5,
+        )
+
+        assert result.token_count == 100
+        assert result.was_compacted is True
+        assert result.error == "Some error"
+        assert result.original_token_count == 500
+        assert result.messages_summarized == 10
+        assert result.messages_dropped == 5
diff --git a/autogpt_platform/backend/backend/util/request.py b/autogpt_platform/backend/backend/util/request.py
index 9744372b15..95e5ee32f7 100644
--- a/autogpt_platform/backend/backend/util/request.py
+++ b/autogpt_platform/backend/backend/util/request.py
@@ -157,12 +157,7 @@ async def validate_url(
         is_trusted: Boolean indicating if the hostname is in trusted_origins
         ip_addresses: List of IP addresses for the host; empty if the host is trusted
     """
-    # Canonicalize URL
-    url = url.strip("/ ").replace("\\", "/")
-    parsed = urlparse(url)
-    if not parsed.scheme:
-        url = f"http://{url}"
-        parsed = urlparse(url)
+    parsed = parse_url(url)
 
     # Check scheme
     if parsed.scheme not in ALLOWED_SCHEMES:
@@ -220,6 +215,17 @@ async def validate_url(
     )
 
 
+def parse_url(url: str) -> URL:
+    """Canonicalizes and parses a URL string."""
+    url = url.strip("/ ").replace("\\", "/")
+
+    # Ensure scheme is present for proper parsing
+    if not re.match(r"[a-z0-9+.\-]+://", url):
+        url = f"http://{url}"
+
+    return urlparse(url)
+
+
 def pin_url(url: URL, ip_addresses: Optional[list[str]] = None) -> URL:
     """
     Pins a URL to a specific IP address to prevent DNS rebinding attacks.
diff --git a/autogpt_platform/backend/backend/util/settings.py b/autogpt_platform/backend/backend/util/settings.py
index aa28a4c9ac..50b7428160 100644
--- a/autogpt_platform/backend/backend/util/settings.py
+++ b/autogpt_platform/backend/backend/util/settings.py
@@ -656,6 +656,7 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
     e2b_api_key: str = Field(default="", description="E2B API key")
     nvidia_api_key: str = Field(default="", description="Nvidia API key")
     mem0_api_key: str = Field(default="", description="Mem0 API key")
+    elevenlabs_api_key: str = Field(default="", description="ElevenLabs API key")
 
     linear_client_id: str = Field(default="", description="Linear client ID")
     linear_client_secret: str = Field(default="", description="Linear client secret")
diff --git a/autogpt_platform/backend/backend/util/workspace.py b/autogpt_platform/backend/backend/util/workspace.py
index a2f1a61b9e..86413b640a 100644
--- a/autogpt_platform/backend/backend/util/workspace.py
+++ b/autogpt_platform/backend/backend/util/workspace.py
@@ -22,6 +22,7 @@ from backend.data.workspace import (
     soft_delete_workspace_file,
 )
 from backend.util.settings import Config
+from backend.util.virus_scanner import scan_content_safe
 from backend.util.workspace_storage import compute_file_checksum, get_workspace_storage
 
 logger = logging.getLogger(__name__)
@@ -187,6 +188,9 @@ class WorkspaceManager:
                 f"{Config().max_file_size_mb}MB limit"
             )
 
+        # Virus scan content before persisting (defense in depth)
+        await scan_content_safe(content, filename=filename)
+
         # Determine path with session scoping
         if path is None:
             path = f"/{filename}"
diff --git a/autogpt_platform/backend/migrations/20260126120000_migrate_claude_3_7_to_4_5_sonnet/migration.sql b/autogpt_platform/backend/migrations/20260126120000_migrate_claude_3_7_to_4_5_sonnet/migration.sql
new file mode 100644
index 0000000000..5746c80820
--- /dev/null
+++ b/autogpt_platform/backend/migrations/20260126120000_migrate_claude_3_7_to_4_5_sonnet/migration.sql
@@ -0,0 +1,22 @@
+-- Migrate Claude 3.7 Sonnet to Claude 4.5 Sonnet
+-- This updates all AgentNode blocks that use the deprecated Claude 3.7 Sonnet model
+-- Anthropic is retiring claude-3-7-sonnet-20250219 on February 19, 2026
+
+-- Update AgentNode constant inputs
+UPDATE "AgentNode"
+SET    "constantInput" = JSONB_SET(
+         "constantInput"::jsonb,
+         '{model}',
+         '"claude-sonnet-4-5-20250929"'::jsonb
+       )
+WHERE  "constantInput"::jsonb->>'model' = 'claude-3-7-sonnet-20250219';
+
+-- Update AgentPreset input overrides (stored in AgentNodeExecutionInputOutput)
+UPDATE "AgentNodeExecutionInputOutput"
+SET    "data" = JSONB_SET(
+         "data"::jsonb,
+         '{model}',
+         '"claude-sonnet-4-5-20250929"'::jsonb
+       )
+WHERE  "agentPresetId" IS NOT NULL
+  AND  "data"::jsonb->>'model' = 'claude-3-7-sonnet-20250219';
diff --git a/autogpt_platform/backend/poetry.lock b/autogpt_platform/backend/poetry.lock
index 91ac358ade..53b5030da6 100644
--- a/autogpt_platform/backend/poetry.lock
+++ b/autogpt_platform/backend/poetry.lock
@@ -2,19 +2,19 @@
 
 [[package]]
 name = "aio-pika"
-version = "9.5.5"
+version = "9.5.8"
 description = "Wrapper around the aiormq for asyncio and humans"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = "<4.0,>=3.10"
 groups = ["main"]
 files = [
-    {file = "aio_pika-9.5.5-py3-none-any.whl", hash = "sha256:94e0ac3666398d6a28b0c3b530c1febf4c6d4ececb345620727cfd7bfe1c02e0"},
-    {file = "aio_pika-9.5.5.tar.gz", hash = "sha256:3d2f25838860fa7e209e21fc95555f558401f9b49a832897419489f1c9e1d6a4"},
+    {file = "aio_pika-9.5.8-py3-none-any.whl", hash = "sha256:f4c6cb8a6c5176d00f39fd7431e9702e638449bc6e86d1769ad7548b2a506a8d"},
+    {file = "aio_pika-9.5.8.tar.gz", hash = "sha256:7c36874115f522bbe7486c46d8dd711a4dbedd67c4e8a8c47efe593d01862c62"},
 ]
 
 [package.dependencies]
-aiormq = ">=6.8,<6.9"
-exceptiongroup = ">=1,<2"
+aiormq = ">=6.8,<7.0"
+exceptiongroup = {version = ">=1,<2", markers = "python_version < \"3.11\""}
 yarl = "*"
 
 [[package]]
@@ -31,29 +31,29 @@ files = [
 
 [[package]]
 name = "aiodns"
-version = "3.5.0"
+version = "3.6.1"
 description = "Simple DNS resolver for asyncio"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "aiodns-3.5.0-py3-none-any.whl", hash = "sha256:6d0404f7d5215849233f6ee44854f2bb2481adf71b336b2279016ea5990ca5c5"},
-    {file = "aiodns-3.5.0.tar.gz", hash = "sha256:11264edbab51896ecf546c18eb0dd56dff0428c6aa6d2cd87e643e07300eb310"},
+    {file = "aiodns-3.6.1-py3-none-any.whl", hash = "sha256:46233ccad25f2037903828c5d05b64590eaa756e51d12b4a5616e2defcbc98c7"},
+    {file = "aiodns-3.6.1.tar.gz", hash = "sha256:b0e9ce98718a5b8f7ca8cd16fc393163374bc2412236b91f6c851d066e3324b6"},
 ]
 
 [package.dependencies]
-pycares = ">=4.9.0"
+pycares = ">=4.9.0,<5"
 
 [[package]]
 name = "aiofiles"
-version = "24.1.0"
+version = "25.1.0"
 description = "File support for asyncio."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "aiofiles-24.1.0-py3-none-any.whl", hash = "sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5"},
-    {file = "aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c"},
+    {file = "aiofiles-25.1.0-py3-none-any.whl", hash = "sha256:abe311e527c862958650f9438e859c1fa7568a141b22abcd015e120e86a85695"},
+    {file = "aiofiles-25.1.0.tar.gz", hash = "sha256:a8d728f0a29de45dc521f18f07297428d56992a742f0cd2701ba86e44d23d5b2"},
 ]
 
 [[package]]
@@ -70,98 +70,132 @@ files = [
 
 [[package]]
 name = "aiohttp"
-version = "3.12.14"
+version = "3.13.3"
 description = "Async http client/server framework (asyncio)"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -175,18 +209,18 @@ propcache = ">=0.2.0"
 yarl = ">=1.17.0,<2.0"
 
 [package.extras]
-speedups = ["Brotli ; platform_python_implementation == \"CPython\"", "aiodns (>=3.3.0)", "brotlicffi ; platform_python_implementation != \"CPython\""]
+speedups = ["Brotli (>=1.2) ; platform_python_implementation == \"CPython\"", "aiodns (>=3.3.0)", "backports.zstd ; platform_python_implementation == \"CPython\" and python_version < \"3.14\"", "brotlicffi (>=1.2) ; platform_python_implementation != \"CPython\""]
 
 [[package]]
 name = "aiormq"
-version = "6.8.1"
+version = "6.9.2"
 description = "Pure python AMQP asynchronous client library"
 optional = false
-python-versions = "<4.0,>=3.8"
+python-versions = "<4.0,>=3.10"
 groups = ["main"]
 files = [
-    {file = "aiormq-6.8.1-py3-none-any.whl", hash = "sha256:5da896c8624193708f9409ffad0b20395010e2747f22aa4150593837f40aa017"},
-    {file = "aiormq-6.8.1.tar.gz", hash = "sha256:a964ab09634be1da1f9298ce225b310859763d5cf83ef3a7eae1a6dc6bd1da1a"},
+    {file = "aiormq-6.9.2-py3-none-any.whl", hash = "sha256:ab0f4e88e70f874b0ea344b3c41634d2484b5dc8b17cb6ae0ae7892a172ad003"},
+    {file = "aiormq-6.9.2.tar.gz", hash = "sha256:d051d46086079934d3a7157f4d8dcb856b77683c2a94aee9faa165efa6a785d3"},
 ]
 
 [package.dependencies]
@@ -209,6 +243,18 @@ files = [
 frozenlist = ">=1.1.0"
 typing-extensions = {version = ">=4.2", markers = "python_version < \"3.13\""}
 
+[[package]]
+name = "annotated-doc"
+version = "0.0.4"
+description = "Document parameters, class attributes, return types, and variables inline, with Annotated."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "annotated_doc-0.0.4-py3-none-any.whl", hash = "sha256:571ac1dc6991c450b25a9c2d84a3705e2ae7a53467b5d111c24fa8baabbed320"},
+    {file = "annotated_doc-0.0.4.tar.gz", hash = "sha256:fbcda96e87e9c92ad167c2e53839e57503ecfda18804ea28102353485033faa4"},
+]
+
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -223,19 +269,20 @@ files = [
 
 [[package]]
 name = "anthropic"
-version = "0.59.0"
+version = "0.79.0"
 description = "The official Python library for the anthropic API"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "anthropic-0.59.0-py3-none-any.whl", hash = "sha256:cbc8b3dccef66ad6435c4fa1d317e5ebb092399a4b88b33a09dc4bf3944c3183"},
-    {file = "anthropic-0.59.0.tar.gz", hash = "sha256:d710d1ef0547ebbb64b03f219e44ba078e83fc83752b96a9b22e9726b523fd8f"},
+    {file = "anthropic-0.79.0-py3-none-any.whl", hash = "sha256:04cbd473b6bbda4ca2e41dd670fe2f829a911530f01697d0a1e37321eb75f3cf"},
+    {file = "anthropic-0.79.0.tar.gz", hash = "sha256:8707aafb3b1176ed6c13e2b1c9fb3efddce90d17aee5d8b83a86c70dcdcca871"},
 ]
 
 [package.dependencies]
 anyio = ">=3.5.0,<5"
 distro = ">=1.7.0,<2"
+docstring-parser = ">=0.15,<1"
 httpx = ">=0.25.0,<1"
 jiter = ">=0.4.0,<1"
 pydantic = ">=1.9.0,<3"
@@ -243,43 +290,40 @@ sniffio = "*"
 typing-extensions = ">=4.10,<5"
 
 [package.extras]
-aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"]
+aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.9)"]
 bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
 vertex = ["google-auth[requests] (>=2,<3)"]
 
 [[package]]
 name = "anyio"
-version = "4.9.0"
-description = "High level compatibility layer for multiple asynchronous event loop implementations"
+version = "4.12.1"
+description = "High-level concurrency and networking framework on top of asyncio or Trio"
 optional = false
 python-versions = ">=3.9"
 groups = ["main", "dev"]
 files = [
-    {file = "anyio-4.9.0-py3-none-any.whl", hash = "sha256:9f76d541cad6e36af7beb62e978876f3b41e3e04f2c1fbf0884604c0a9c4d93c"},
-    {file = "anyio-4.9.0.tar.gz", hash = "sha256:673c0c244e15788651a4ff38710fea9675823028a6f08a5eda409e0c9840a028"},
+    {file = "anyio-4.12.1-py3-none-any.whl", hash = "sha256:d405828884fc140aa80a3c667b8beed277f1dfedec42ba031bd6ac3db606ab6c"},
+    {file = "anyio-4.12.1.tar.gz", hash = "sha256:41cfcc3a4c85d3f05c932da7c26d0201ac36f72abd4435ba90d0464a3ffed703"},
 ]
 
 [package.dependencies]
 exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
-sniffio = ">=1.1"
 typing_extensions = {version = ">=4.5", markers = "python_version < \"3.13\""}
 
 [package.extras]
-doc = ["Sphinx (>=8.2,<9.0)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx_rtd_theme"]
-test = ["anyio[trio]", "blockbuster (>=1.5.23)", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "trustme", "truststore (>=0.9.1) ; python_version >= \"3.10\"", "uvloop (>=0.21) ; platform_python_implementation == \"CPython\" and platform_system != \"Windows\" and python_version < \"3.14\""]
-trio = ["trio (>=0.26.1)"]
+trio = ["trio (>=0.31.0) ; python_version < \"3.10\"", "trio (>=0.32.0) ; python_version >= \"3.10\""]
 
 [[package]]
 name = "apscheduler"
-version = "3.11.1"
+version = "3.11.2"
 description = "In-process task scheduler with Cron-like capabilities"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "apscheduler-3.11.1-py3-none-any.whl", hash = "sha256:6162cb5683cb09923654fa9bdd3130c4be4bfda6ad8990971c9597ecd52965d2"},
-    {file = "apscheduler-3.11.1.tar.gz", hash = "sha256:0db77af6400c84d1747fe98a04b8b58f0080c77d11d338c4f507a9752880f221"},
+    {file = "apscheduler-3.11.2-py3-none-any.whl", hash = "sha256:ce005177f741409db4e4dd40a7431b76feb856b9dd69d57e0da49d6715bfd26d"},
+    {file = "apscheduler-3.11.2.tar.gz", hash = "sha256:2a9966b052ec805f020c8c4c3ae6e6a06e24b1bf19f2e11d91d8cca0473eef41"},
 ]
 
 [package.dependencies]
@@ -293,7 +337,7 @@ mongodb = ["pymongo (>=3.0)"]
 redis = ["redis (>=3.0)"]
 rethinkdb = ["rethinkdb (>=2.4.0)"]
 sqlalchemy = ["sqlalchemy (>=1.4)"]
-test = ["APScheduler[etcd,mongodb,redis,rethinkdb,sqlalchemy,tornado,zookeeper]", "PySide6 ; platform_python_implementation == \"CPython\" and python_version < \"3.14\"", "anyio (>=4.5.2)", "gevent ; python_version < \"3.14\"", "pytest", "pytz", "twisted ; python_version < \"3.14\""]
+test = ["APScheduler[etcd,mongodb,redis,rethinkdb,sqlalchemy,tornado,zookeeper]", "PySide6 ; platform_python_implementation == \"CPython\" and python_version < \"3.14\"", "anyio (>=4.5.2)", "gevent ; python_version < \"3.14\"", "pytest", "pytest-timeout", "pytz", "twisted ; python_version < \"3.14\""]
 tornado = ["tornado (>=4.3)"]
 twisted = ["twisted"]
 zookeeper = ["kazoo"]
@@ -313,24 +357,16 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "25.3.0"
+version = "25.4.0"
 description = "Classes Without Boilerplate"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "attrs-25.3.0-py3-none-any.whl", hash = "sha256:427318ce031701fea540783410126f03899a97ffc6f61596ad581ac2e40e3bc3"},
-    {file = "attrs-25.3.0.tar.gz", hash = "sha256:75d7cefc7fb576747b2c81b4442d4d4a1ce0900973527c011d1030fd3bf4af1b"},
+    {file = "attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373"},
+    {file = "attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11"},
 ]
 
-[package.extras]
-benchmark = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
-cov = ["cloudpickle ; platform_python_implementation == \"CPython\"", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
-dev = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pre-commit-uv", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
-docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier"]
-tests = ["cloudpickle ; platform_python_implementation == \"CPython\"", "hypothesis", "mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-xdist[psutil]"]
-tests-mypy = ["mypy (>=1.11.1) ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\"", "pytest-mypy-plugins ; platform_python_implementation == \"CPython\" and python_version >= \"3.10\""]
-
 [[package]]
 name = "audioop-lts"
 version = "0.2.2"
@@ -403,17 +439,17 @@ develop = true
 
 [package.dependencies]
 colorama = "^0.4.6"
-cryptography = "^45.0"
+cryptography = "^46.0"
 expiringdict = "^1.2.2"
-fastapi = "^0.116.1"
-google-cloud-logging = "^3.12.1"
-launchdarkly-server-sdk = "^9.12.0"
-pydantic = "^2.11.7"
-pydantic-settings = "^2.10.1"
-pyjwt = {version = "^2.10.1", extras = ["crypto"]}
+fastapi = "^0.128.0"
+google-cloud-logging = "^3.13.0"
+launchdarkly-server-sdk = "^9.14.1"
+pydantic = "^2.12.5"
+pydantic-settings = "^2.12.0"
+pyjwt = {version = "^2.11.0", extras = ["crypto"]}
 redis = "^6.2.0"
-supabase = "^2.16.0"
-uvicorn = "^0.35.0"
+supabase = "^2.27.2"
+uvicorn = "^0.40.0"
 
 [package.source]
 type = "directory"
@@ -510,14 +546,14 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "bleach"
-version = "6.2.0"
+version = "6.3.0"
 description = "An easy safelist-based HTML-sanitizing tool."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "bleach-6.2.0-py3-none-any.whl", hash = "sha256:117d9c6097a7c3d22fd578fcd8d35ff1e125df6736f554da4e432fdd63f31e5e"},
-    {file = "bleach-6.2.0.tar.gz", hash = "sha256:123e894118b8a599fd80d3ec1a6d4cc7ce4e5882b1317a7e1ba69b56e95f991f"},
+    {file = "bleach-6.3.0-py3-none-any.whl", hash = "sha256:fe10ec77c93ddf3d13a73b035abaac7a9f5e436513864ccdad516693213c65d6"},
+    {file = "bleach-6.3.0.tar.gz", hash = "sha256:6f3b91b1c0a02bb9a78b5a454c92506aa0fdf197e1d5e114d2e00c6f64306d22"},
 ]
 
 [package.dependencies]
@@ -549,40 +585,37 @@ typing-extensions = ">=4.10,<5"
 
 [[package]]
 name = "build"
-version = "1.2.2.post1"
+version = "1.4.0"
 description = "A simple, correct Python build frontend"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "build-1.2.2.post1-py3-none-any.whl", hash = "sha256:1d61c0887fa860c01971625baae8bdd338e517b836a2f70dd1f7aa3a6b2fc5b5"},
-    {file = "build-1.2.2.post1.tar.gz", hash = "sha256:b36993e92ca9375a219c99e606a122ff365a760a2d4bba0caa09bd5278b608b7"},
+    {file = "build-1.4.0-py3-none-any.whl", hash = "sha256:6a07c1b8eb6f2b311b96fcbdbce5dab5fe637ffda0fd83c9cac622e927501596"},
+    {file = "build-1.4.0.tar.gz", hash = "sha256:f1b91b925aa322be454f8330c6fb48b465da993d1e7e7e6fa35027ec49f3c936"},
 ]
 
 [package.dependencies]
 colorama = {version = "*", markers = "os_name == \"nt\""}
 importlib-metadata = {version = ">=4.6", markers = "python_full_version < \"3.10.2\""}
-packaging = ">=19.1"
+packaging = ">=24.0"
 pyproject_hooks = "*"
 tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
-docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
-test = ["build[uv,virtualenv]", "filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0) ; python_version < \"3.10\"", "setuptools (>=56.0.0) ; python_version == \"3.10\"", "setuptools (>=56.0.0) ; python_version == \"3.11\"", "setuptools (>=67.8.0) ; python_version >= \"3.12\"", "wheel (>=0.36.0)"]
-typing = ["build[uv]", "importlib-metadata (>=5.1)", "mypy (>=1.9.0,<1.10.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
 uv = ["uv (>=0.1.18)"]
-virtualenv = ["virtualenv (>=20.0.35)"]
+virtualenv = ["virtualenv (>=20.11) ; python_version < \"3.10\"", "virtualenv (>=20.17) ; python_version >= \"3.10\" and python_version < \"3.14\"", "virtualenv (>=20.31) ; python_version >= \"3.14\""]
 
 [[package]]
 name = "cachecontrol"
-version = "0.14.3"
+version = "0.14.4"
 description = "httplib2 caching for requests"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "cachecontrol-0.14.3-py3-none-any.whl", hash = "sha256:b35e44a3113f17d2a31c1e6b27b9de6d4405f84ae51baa8c1d3cc5b633010cae"},
-    {file = "cachecontrol-0.14.3.tar.gz", hash = "sha256:73e7efec4b06b20d9267b441c1f733664f989fb8688391b670ca812d70795d11"},
+    {file = "cachecontrol-0.14.4-py3-none-any.whl", hash = "sha256:b7ac014ff72ee199b5f8af1de29d60239954f223e948196fa3d84adaffc71d2b"},
+    {file = "cachecontrol-0.14.4.tar.gz", hash = "sha256:e6220afafa4c22a47dd0badb319f84475d79108100d04e26e8542ef7d3ab05a1"},
 ]
 
 [package.dependencies]
@@ -591,124 +624,142 @@ msgpack = ">=0.5.2,<2.0.0"
 requests = ">=2.16.0"
 
 [package.extras]
-dev = ["CacheControl[filecache,redis]", "build", "cherrypy", "codespell[tomli]", "furo", "mypy", "pytest", "pytest-cov", "ruff", "sphinx", "sphinx-copybutton", "tox", "types-redis", "types-requests"]
+dev = ["cachecontrol[filecache,redis]", "cheroot (>=11.1.2)", "cherrypy", "codespell", "furo", "mypy", "pytest", "pytest-cov", "ruff", "sphinx", "sphinx-copybutton", "types-redis", "types-requests"]
 filecache = ["filelock (>=3.8.0)"]
 redis = ["redis (>=2.10.5)"]
 
 [[package]]
 name = "cachetools"
-version = "5.5.2"
+version = "6.2.6"
 description = "Extensible memoizing collections and decorators"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a"},
-    {file = "cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4"},
+    {file = "cachetools-6.2.6-py3-none-any.whl", hash = "sha256:8c9717235b3c651603fff0076db52d6acbfd1b338b8ed50256092f7ce9c85bda"},
+    {file = "cachetools-6.2.6.tar.gz", hash = "sha256:16c33e1f276b9a9c0b49ab5782d901e3ad3de0dd6da9bf9bcd29ac5672f2f9e6"},
 ]
 
 [[package]]
 name = "certifi"
-version = "2025.7.14"
+version = "2026.1.4"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.7"
 groups = ["main", "dev"]
 files = [
-    {file = "certifi-2025.7.14-py3-none-any.whl", hash = "sha256:6b31f564a415d79ee77df69d757bb49a5bb53bd9f756cbbe24394ffd6fc1f4b2"},
-    {file = "certifi-2025.7.14.tar.gz", hash = "sha256:8ea99dbdfaaf2ba2f9bac77b9249ef62ec5218e7c2b2e903378ed5fccf765995"},
+    {file = "certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c"},
+    {file = "certifi-2026.1.4.tar.gz", hash = "sha256:ac726dd470482006e014ad384921ed6438c457018f4b3d204aea4281258b2120"},
 ]
 
 [[package]]
 name = "cffi"
-version = "1.17.1"
+version = "2.0.0"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
+markers = "platform_python_implementation != \"PyPy\" or sys_platform == \"darwin\""
 files = [
-    {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
-    {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
-    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_12_i686.manylinux2010_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:edae79245293e15384b51f88b00613ba9f7198016a5948b5dddf4917d4d26382"},
-    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45398b671ac6d70e67da8e4224a065cec6a93541bb7aebe1b198a61b58c7b702"},
-    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ad9413ccdeda48c5afdae7e4fa2192157e991ff761e7ab8fdd8926f40b160cc3"},
-    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5da5719280082ac6bd9aa7becb3938dc9f9cbd57fac7d2871717b1feb0902ab6"},
-    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2bb1a08b8008b281856e5971307cc386a8e9c5b625ac297e853d36da6efe9c17"},
-    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:045d61c734659cc045141be4bae381a41d89b741f795af1dd018bfb532fd0df8"},
-    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:6883e737d7d9e4899a8a695e00ec36bd4e5e4f18fabe0aca0efe0a4b44cdb13e"},
-    {file = "cffi-1.17.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:6b8b4a92e1c65048ff98cfe1f735ef8f1ceb72e3d5f0c25fdb12087a23da22be"},
-    {file = "cffi-1.17.1-cp310-cp310-win32.whl", hash = "sha256:c9c3d058ebabb74db66e431095118094d06abf53284d9c81f27300d0e0d8bc7c"},
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 ]
 
 [[package]]
@@ -843,14 +915,14 @@ rapidfuzz = ">=3.0.0,<4.0.0"
 
 [[package]]
 name = "click"
-version = "8.2.1"
+version = "8.3.1"
 description = "Composable command line interface toolkit"
 optional = false
 python-versions = ">=3.10"
 groups = ["main", "dev"]
 files = [
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 ]
 
 [package.dependencies]
@@ -899,62 +971,75 @@ pytz = ">2021.1"
 
 [[package]]
 name = "cryptography"
-version = "45.0.7"
+version = "46.0.4"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
-python-versions = "!=3.9.0,!=3.9.1,>=3.7"
+python-versions = "!=3.9.0,!=3.9.1,>=3.8"
 groups = ["main"]
 files = [
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 [package.dependencies]
-cffi = {version = ">=1.14", markers = "platform_python_implementation != \"PyPy\""}
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 ssh = ["bcrypt (>=3.1.5)"]
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 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -998,14 +1083,14 @@ packaging = "*"
 
 [[package]]
 name = "discord-py"
-version = "2.5.2"
+version = "2.6.4"
 description = "A Python wrapper for the Discord API"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
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-    {file = "discord_py-2.5.2.tar.gz", hash = "sha256:01cd362023bfea1a4a1d43f5280b5ef00cad2c7eba80098909f98bf28e578524"},
+    {file = "discord_py-2.6.4-py3-none-any.whl", hash = "sha256:2783b7fb7f8affa26847bfc025144652c294e8fe6e0f8877c67ed895749eb227"},
+    {file = "discord_py-2.6.4.tar.gz", hash = "sha256:44384920bae9b7a073df64ae9b14c8cf85f9274b5ad5d1d07bd5a67539de2da9"},
 ]
 
 [package.dependencies]
@@ -1013,11 +1098,11 @@ aiohttp = ">=3.7.4,<4"
 audioop-lts = {version = "*", markers = "python_version >= \"3.13\""}
 
 [package.extras]
-dev = ["black (==22.6)", "typing_extensions (>=4.3,<5)"]
+dev = ["ruff (==0.12)", "typing_extensions (>=4.3,<5)"]
 docs = ["imghdr-lts (==1.0.0) ; python_version >= \"3.13\"", "sphinx (==4.4.0)", "sphinx-inline-tabs (==2023.4.21)", "sphinxcontrib-applehelp (==1.0.4)", "sphinxcontrib-devhelp (==1.0.2)", "sphinxcontrib-htmlhelp (==2.0.1)", "sphinxcontrib-jsmath (==1.0.1)", "sphinxcontrib-qthelp (==1.0.3)", "sphinxcontrib-serializinghtml (==1.1.5)", "sphinxcontrib-websupport (==1.2.4)", "sphinxcontrib_trio (==1.1.2)", "typing-extensions (>=4.3,<5)"]
-speed = ["Brotli", "aiodns (>=1.1) ; sys_platform != \"win32\"", "cchardet (==2.1.7) ; python_version < \"3.10\"", "orjson (>=3.5.4)", "zstandard (>=0.23.0)"]
+speed = ["Brotli", "aiodns (>=1.1) ; sys_platform != \"win32\"", "cchardet (==2.1.7) ; python_version < \"3.10\"", "orjson (>=3.5.4)", "zstandard (>=0.23.0) ; python_version <= \"3.13\""]
 test = ["coverage[toml]", "pytest", "pytest-asyncio", "pytest-cov", "pytest-mock", "typing-extensions (>=4.3,<5)", "tzdata ; sys_platform == \"win32\""]
-voice = ["PyNaCl (>=1.3.0,<1.6)"]
+voice = ["PyNaCl (>=1.5.0,<1.6)"]
 
 [[package]]
 name = "distlib"
@@ -1045,24 +1130,41 @@ files = [
 
 [[package]]
 name = "dnspython"
-version = "2.7.0"
+version = "2.8.0"
 description = "DNS toolkit"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "dnspython-2.7.0-py3-none-any.whl", hash = "sha256:b4c34b7d10b51bcc3a5071e7b8dee77939f1e878477eeecc965e9835f63c6c86"},
-    {file = "dnspython-2.7.0.tar.gz", hash = "sha256:ce9c432eda0dc91cf618a5cedf1a4e142651196bbcd2c80e89ed5a907e5cfaf1"},
+    {file = "dnspython-2.8.0-py3-none-any.whl", hash = "sha256:01d9bbc4a2d76bf0db7c1f729812ded6d912bd318d3b1cf81d30c0f845dbf3af"},
+    {file = "dnspython-2.8.0.tar.gz", hash = "sha256:181d3c6996452cb1189c4046c61599b84a5a86e099562ffde77d26984ff26d0f"},
 ]
 
 [package.extras]
-dev = ["black (>=23.1.0)", "coverage (>=7.0)", "flake8 (>=7)", "hypercorn (>=0.16.0)", "mypy (>=1.8)", "pylint (>=3)", "pytest (>=7.4)", "pytest-cov (>=4.1.0)", "quart-trio (>=0.11.0)", "sphinx (>=7.2.0)", "sphinx-rtd-theme (>=2.0.0)", "twine (>=4.0.0)", "wheel (>=0.42.0)"]
-dnssec = ["cryptography (>=43)"]
-doh = ["h2 (>=4.1.0)", "httpcore (>=1.0.0)", "httpx (>=0.26.0)"]
-doq = ["aioquic (>=1.0.0)"]
-idna = ["idna (>=3.7)"]
-trio = ["trio (>=0.23)"]
-wmi = ["wmi (>=1.5.1)"]
+dev = ["black (>=25.1.0)", "coverage (>=7.0)", "flake8 (>=7)", "hypercorn (>=0.17.0)", "mypy (>=1.17)", "pylint (>=3)", "pytest (>=8.4)", "pytest-cov (>=6.2.0)", "quart-trio (>=0.12.0)", "sphinx (>=8.2.0)", "sphinx-rtd-theme (>=3.0.0)", "twine (>=6.1.0)", "wheel (>=0.45.0)"]
+dnssec = ["cryptography (>=45)"]
+doh = ["h2 (>=4.2.0)", "httpcore (>=1.0.0)", "httpx (>=0.28.0)"]
+doq = ["aioquic (>=1.2.0)"]
+idna = ["idna (>=3.10)"]
+trio = ["trio (>=0.30)"]
+wmi = ["wmi (>=1.5.1) ; platform_system == \"Windows\""]
+
+[[package]]
+name = "docstring-parser"
+version = "0.17.0"
+description = "Parse Python docstrings in reST, Google and Numpydoc format"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708"},
+    {file = "docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912"},
+]
+
+[package.extras]
+dev = ["pre-commit (>=2.16.0) ; python_version >= \"3.9\"", "pydoctor (>=25.4.0)", "pytest"]
+docs = ["pydoctor (>=25.4.0)"]
+test = ["pytest"]
 
 [[package]]
 name = "dulwich"
@@ -1133,14 +1235,14 @@ pgp = ["gpg"]
 
 [[package]]
 name = "e2b"
-version = "1.6.0"
+version = "1.11.1"
 description = "E2B SDK that give agents cloud environments"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "e2b-1.6.0-py3-none-any.whl", hash = "sha256:c4606ed0a3d4e45412ce81e2e8ee224b2d81b927fd8d6519a1a81437d8d4a22a"},
-    {file = "e2b-1.6.0.tar.gz", hash = "sha256:0552115ee0a18c4e5a5aa97290d4a454478c547371386cabb76e367b8e914753"},
+    {file = "e2b-1.11.1-py3-none-any.whl", hash = "sha256:1ecb123873788472731c101939a494ab852cbcce0f913df6f7ecb194ae932130"},
+    {file = "e2b-1.11.1.tar.gz", hash = "sha256:7f7b6f238208d0a23353bb0da01f91a924321b57c61b176506862cbc1493ce8c"},
 ]
 
 [package.dependencies]
@@ -1148,7 +1250,7 @@ attrs = ">=23.2.0"
 httpcore = ">=1.0.5,<2.0.0"
 httpx = ">=0.27.0,<1.0.0"
 packaging = ">=24.1"
-protobuf = ">=5.29.4,<6.0.0"
+protobuf = ">=4.21.0"
 python-dateutil = ">=2.8.2"
 typing-extensions = ">=4.1.0"
 
@@ -1169,16 +1271,39 @@ attrs = ">=21.3.0"
 e2b = ">=1.5.4,<2.0.0"
 httpx = ">=0.20.0,<1.0.0"
 
+[[package]]
+name = "elevenlabs"
+version = "1.59.0"
+description = ""
+optional = false
+python-versions = "<4.0,>=3.8"
+groups = ["main"]
+files = [
+    {file = "elevenlabs-1.59.0-py3-none-any.whl", hash = "sha256:468145db81a0bc867708b4a8619699f75583e9481b395ec1339d0b443da771ed"},
+    {file = "elevenlabs-1.59.0.tar.gz", hash = "sha256:16e735bd594e86d415dd445d249c8cc28b09996cfd627fbc10102c0a84698859"},
+]
+
+[package.dependencies]
+httpx = ">=0.21.2"
+pydantic = ">=1.9.2"
+pydantic-core = ">=2.18.2,<3.0.0"
+requests = ">=2.20"
+typing_extensions = ">=4.0.0"
+websockets = ">=11.0"
+
+[package.extras]
+pyaudio = ["pyaudio (>=0.2.14)"]
+
 [[package]]
 name = "email-validator"
-version = "2.2.0"
+version = "2.3.0"
 description = "A robust email address syntax and deliverability validation library."
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "email_validator-2.2.0-py3-none-any.whl", hash = "sha256:561977c2d73ce3611850a06fa56b414621e0c8faa9d66f2611407d87465da631"},
-    {file = "email_validator-2.2.0.tar.gz", hash = "sha256:cb690f344c617a714f22e66ae771445a1ceb46821152df8e165c5f9a364582b7"},
+    {file = "email_validator-2.3.0-py3-none-any.whl", hash = "sha256:80f13f623413e6b197ae73bb10bf4eb0908faf509ad8362c5edeb0be7fd450b4"},
+    {file = "email_validator-2.3.0.tar.gz", hash = "sha256:9fc05c37f2f6cf439ff414f8fc46d917929974a82244c20eb10231ba60c54426"},
 ]
 
 [package.dependencies]
@@ -1187,35 +1312,37 @@ idna = ">=2.0.0"
 
 [[package]]
 name = "exa-py"
-version = "1.14.20"
+version = "1.16.1"
 description = "Python SDK for Exa API."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "exa_py-1.14.20-py3-none-any.whl", hash = "sha256:e0ed9d99c3c494a0e6903e11a0f6fb773b3b23d0cd802380cf58efc97d9d332d"},
-    {file = "exa_py-1.14.20.tar.gz", hash = "sha256:423789a0635b7a4ecd5f56d6b4a0dfb01126fa45ce1e04106c0bb96b7d551ebf"},
+    {file = "exa_py-1.16.1-py3-none-any.whl", hash = "sha256:3b323ed32725b72110720306ea12da09161cfa9c8ac64797a9c0b66869741f27"},
+    {file = "exa_py-1.16.1.tar.gz", hash = "sha256:3cb371b8efd321881a8217070f16afdac5afbaa9229177f80d5c427e1a6dbd59"},
 ]
 
 [package.dependencies]
+httpcore = ">=1.0.9"
 httpx = ">=0.28.1"
 openai = ">=1.48"
 pydantic = ">=2.10.6"
+python-dotenv = ">=1.0.1"
 requests = ">=2.32.3"
 typing-extensions = ">=4.12.2"
 
 [[package]]
 name = "exceptiongroup"
-version = "1.3.0"
+version = "1.3.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 groups = ["main", "dev"]
+markers = "python_version < \"3.11\""
 files = [
-    {file = "exceptiongroup-1.3.0-py3-none-any.whl", hash = "sha256:4d111e6e0c13d0644cad6ddaa7ed0261a0b36971f6d23e7ec9b4b9097da78a10"},
-    {file = "exceptiongroup-1.3.0.tar.gz", hash = "sha256:b241f5885f560bc56a59ee63ca4c6a8bfa46ae4ad651af316d4e81817bb9fd88"},
+    {file = "exceptiongroup-1.3.1-py3-none-any.whl", hash = "sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598"},
+    {file = "exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219"},
 ]
-markers = {dev = "python_version < \"3.11\""}
 
 [package.dependencies]
 typing-extensions = {version = ">=4.6.0", markers = "python_version < \"3.13\""}
@@ -1240,14 +1367,14 @@ tests = ["coverage", "coveralls", "dill", "mock", "nose"]
 
 [[package]]
 name = "faker"
-version = "38.2.0"
+version = "38.3.0"
 description = "Faker is a Python package that generates fake data for you."
 optional = false
 python-versions = ">=3.10"
 groups = ["dev"]
 files = [
-    {file = "faker-38.2.0-py3-none-any.whl", hash = "sha256:35fe4a0a79dee0dc4103a6083ee9224941e7d3594811a50e3969e547b0d2ee65"},
-    {file = "faker-38.2.0.tar.gz", hash = "sha256:20672803db9c7cb97f9b56c18c54b915b6f1d8991f63d1d673642dc43f5ce7ab"},
+    {file = "faker-38.3.0-py3-none-any.whl", hash = "sha256:b5499b6f2d090dec9b90ded8eae6a27daed10fda3e0dba7a182bb2be8a4d4a6b"},
+    {file = "faker-38.3.0.tar.gz", hash = "sha256:4997de214510db9328ed83b9591891c66e91d7e9a903e5744e0255a68f51ac16"},
 ]
 
 [package.dependencies]
@@ -1255,51 +1382,141 @@ tzdata = "*"
 
 [[package]]
 name = "fastapi"
-version = "0.116.1"
+version = "0.128.6"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "fastapi-0.116.1-py3-none-any.whl", hash = "sha256:c46ac7c312df840f0c9e220f7964bada936781bc4e2e6eb71f1c4d7553786565"},
-    {file = "fastapi-0.116.1.tar.gz", hash = "sha256:ed52cbf946abfd70c5a0dccb24673f0670deeb517a88b3544d03c2a6bf283143"},
+    {file = "fastapi-0.128.6-py3-none-any.whl", hash = "sha256:bb1c1ef87d6086a7132d0ab60869d6f1ee67283b20fbf84ec0003bd335099509"},
+    {file = "fastapi-0.128.6.tar.gz", hash = "sha256:0cb3946557e792d731b26a42b04912f16367e3c3135ea8290f620e234f2b604f"},
 ]
 
 [package.dependencies]
-pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
-starlette = ">=0.40.0,<0.48.0"
+annotated-doc = ">=0.0.2"
+pydantic = ">=2.7.0"
+starlette = ">=0.40.0,<1.0.0"
 typing-extensions = ">=4.8.0"
+typing-inspection = ">=0.4.2"
 
 [package.extras]
-all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
-standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
-standard-no-fastapi-cloud-cli = ["email-validator (>=2.0.0)", "fastapi-cli[standard-no-fastapi-cloud-cli] (>=0.0.8)", "httpx (>=0.23.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
+all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.9.3)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=5.8.0)", "uvicorn[standard] (>=0.12.0)"]
+standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
+standard-no-fastapi-cloud-cli = ["email-validator (>=2.0.0)", "fastapi-cli[standard-no-fastapi-cloud-cli] (>=0.0.8)", "httpx (>=0.23.0,<1.0.0)", "jinja2 (>=3.1.5)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 
 [[package]]
 name = "fastjsonschema"
-version = "2.21.1"
+version = "2.21.2"
 description = "Fastest Python implementation of JSON schema"
 optional = false
 python-versions = "*"
 groups = ["main"]
 files = [
-    {file = "fastjsonschema-2.21.1-py3-none-any.whl", hash = "sha256:c9e5b7e908310918cf494a434eeb31384dd84a98b57a30bcb1f535015b554667"},
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+    {file = "fastjsonschema-2.21.2-py3-none-any.whl", hash = "sha256:1c797122d0a86c5cace2e54bf4e819c36223b552017172f32c5c024a6b77e463"},
+    {file = "fastjsonschema-2.21.2.tar.gz", hash = "sha256:b1eb43748041c880796cd077f1a07c3d94e93ae84bba5ed36800a33554ae05de"},
 ]
 
 [package.extras]
 devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
 
+[[package]]
+name = "fastuuid"
+version = "0.14.0"
+description = "Python bindings to Rust's UUID library."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "fastuuid-0.14.0-cp310-cp310-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:6e6243d40f6c793c3e2ee14c13769e341b90be5ef0c23c82fa6515a96145181a"},
+    {file = "fastuuid-0.14.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:13ec4f2c3b04271f62be2e1ce7e95ad2dd1cf97e94503a3760db739afbd48f00"},
+    {file = "fastuuid-0.14.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b2fdd48b5e4236df145a149d7125badb28e0a383372add3fbaac9a6b7a394470"},
+    {file = "fastuuid-0.14.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f74631b8322d2780ebcf2d2d75d58045c3e9378625ec51865fe0b5620800c39d"},
+    {file = "fastuuid-0.14.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:83cffc144dc93eb604b87b179837f2ce2af44871a7b323f2bfed40e8acb40ba8"},
+    {file = "fastuuid-0.14.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1a771f135ab4523eb786e95493803942a5d1fc1610915f131b363f55af53b219"},
+    {file = "fastuuid-0.14.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:4edc56b877d960b4eda2c4232f953a61490c3134da94f3c28af129fb9c62a4f6"},
+    {file = "fastuuid-0.14.0-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:bcc96ee819c282e7c09b2eed2b9bd13084e3b749fdb2faf58c318d498df2efbe"},
+    {file = "fastuuid-0.14.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:7a3c0bca61eacc1843ea97b288d6789fbad7400d16db24e36a66c28c268cfe3d"},
+    {file = "fastuuid-0.14.0-cp310-cp310-win32.whl", hash = "sha256:7f2f3efade4937fae4e77efae1af571902263de7b78a0aee1a1653795a093b2a"},
+    {file = "fastuuid-0.14.0-cp310-cp310-win_amd64.whl", hash = "sha256:ae64ba730d179f439b0736208b4c279b8bc9c089b102aec23f86512ea458c8a4"},
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 optional = false
 python-versions = ">=3.6"
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 [package.dependencies]
@@ -1307,21 +1524,16 @@ sgmllib3k = "*"
 
 [[package]]
 name = "filelock"
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+version = "3.20.3"
 description = "A platform independent file lock."
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-python-versions = ">=3.9"
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-[package.extras]
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-
 [[package]]
 name = "findpython"
 version = "0.6.3"
@@ -1339,14 +1551,14 @@ packaging = ">=20"
 
 [[package]]
 name = "firecrawl-py"
-version = "4.3.6"
+version = "4.14.0"
 description = "Python SDK for Firecrawl API"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -1377,128 +1589,154 @@ pyflakes = ">=3.4.0,<3.5.0"
 
 [[package]]
 name = "frozenlist"
-version = "1.7.0"
+version = "1.8.0"
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 python-versions = ">=3.9"
 groups = ["main"]
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 ]
 
 [[package]]
 name = "fsspec"
-version = "2025.7.0"
+version = "2026.2.0"
 description = "File-system specification"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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+    {file = "fsspec-2026.2.0-py3-none-any.whl", hash = "sha256:98de475b5cb3bd66bedd5c4679e87b4fdfe1a3bf4d707b151b3c07e58c9a2437"},
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 ]
 
 [package.extras]
@@ -1509,9 +1747,9 @@ dask = ["dask", "distributed"]
 dev = ["pre-commit", "ruff (>=0.5)"]
 doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
 dropbox = ["dropbox", "dropboxdrivefs", "requests"]
-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
+full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs (>2024.2.0)", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs (>2024.2.0)", "smbprotocol", "tqdm"]
 fuse = ["fusepy"]
-gcs = ["gcsfs"]
+gcs = ["gcsfs (>2024.2.0)"]
 git = ["pygit2"]
 github = ["requests"]
 gs = ["gcsfs"]
@@ -1520,13 +1758,13 @@ hdfs = ["pyarrow (>=1)"]
 http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
 libarchive = ["libarchive-c"]
 oci = ["ocifs"]
-s3 = ["s3fs"]
+s3 = ["s3fs (>2024.2.0)"]
 sftp = ["paramiko"]
 smb = ["smbprotocol"]
 ssh = ["paramiko"]
 test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
 test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
-test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard ; python_version < \"3.14\""]
+test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "backports-zstd ; python_version < \"3.14\"", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas (<3.0.0)", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard ; python_version < \"3.14\""]
 tqdm = ["tqdm"]
 
 [[package]]
@@ -1550,32 +1788,32 @@ pyjwt = ">=1.5.3,<3.0.0"
 
 [[package]]
 name = "gcloud-aio-storage"
-version = "9.5.0"
+version = "9.6.1"
 description = "Python Client for Google Cloud Storage"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
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-    {file = "gcloud_aio_storage-9.5.0.tar.gz", hash = "sha256:5adbb21818f1236169fea4958e14b7ace59f81262b112d080cf76030cbef5f34"},
+    {file = "gcloud_aio_storage-9.6.1-py3-none-any.whl", hash = "sha256:6881f573df586821dfd456f7ded3d94f326a82197adca15d52acc789c3621df3"},
+    {file = "gcloud_aio_storage-9.6.1.tar.gz", hash = "sha256:e3e621ab5e870d29384a0a7935ac68af12dd19caf93f1c91b0bc70f939333bfb"},
 ]
 
 [package.dependencies]
-aiofiles = ">=0.6.0,<25.0.0"
+aiofiles = ">=0.6.0,<26.0.0"
 gcloud-aio-auth = ">=5.3.0,<6.0.0"
-pyasn1-modules = ">=0.2.1,<0.4.2"
+pyasn1-modules = ">=0.2.1,<0.5.0"
 rsa = ">=3.1.4,<5.0.0"
 
 [[package]]
 name = "google-api-core"
-version = "2.25.1"
+version = "2.29.0"
 description = "Google API client core library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google_api_core-2.25.1-py3-none-any.whl", hash = "sha256:8a2a56c1fef82987a524371f99f3bd0143702fecc670c72e600c1cda6bf8dbb7"},
-    {file = "google_api_core-2.25.1.tar.gz", hash = "sha256:d2aaa0b13c78c61cb3f4282c464c046e45fbd75755683c9c525e6e8f7ed0a5e8"},
+    {file = "google_api_core-2.29.0-py3-none-any.whl", hash = "sha256:d30bc60980daa36e314b5d5a3e5958b0200cb44ca8fa1be2b614e932b75a3ea9"},
+    {file = "google_api_core-2.29.0.tar.gz", hash = "sha256:84181be0f8e6b04006df75ddfe728f24489f0af57c96a529ff7cf45bc28797f7"},
 ]
 
 [package.dependencies]
@@ -1598,20 +1836,20 @@ requests = ">=2.18.0,<3.0.0"
 
 [package.extras]
 async-rest = ["google-auth[aiohttp] (>=2.35.0,<3.0.0)"]
-grpc = ["grpcio (>=1.33.2,<2.0.0)", "grpcio (>=1.49.1,<2.0.0) ; python_version >= \"3.11\"", "grpcio-status (>=1.33.2,<2.0.0)", "grpcio-status (>=1.49.1,<2.0.0) ; python_version >= \"3.11\""]
+grpc = ["grpcio (>=1.33.2,<2.0.0)", "grpcio (>=1.49.1,<2.0.0) ; python_version >= \"3.11\"", "grpcio (>=1.75.1,<2.0.0) ; python_version >= \"3.14\"", "grpcio-status (>=1.33.2,<2.0.0)", "grpcio-status (>=1.49.1,<2.0.0) ; python_version >= \"3.11\"", "grpcio-status (>=1.75.1,<2.0.0) ; python_version >= \"3.14\""]
 grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.0)"]
 grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.177.0"
+version = "2.189.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google_api_python_client-2.177.0-py3-none-any.whl", hash = "sha256:f2f50f11105ab883eb9b6cf38ec54ea5fd4b429249f76444bec90deba5be79b3"},
-    {file = "google_api_python_client-2.177.0.tar.gz", hash = "sha256:9ffd2b57d68f5afa7e6ac64e2c440534eaa056cbb394812a62ff94723c31b50e"},
+    {file = "google_api_python_client-2.189.0-py3-none-any.whl", hash = "sha256:a258c09660a49c6159173f8bbece171278e917e104a11f0640b34751b79c8a1a"},
+    {file = "google_api_python_client-2.189.0.tar.gz", hash = "sha256:45f2d8559b5c895dde6ad3fb33de025f5cb2c197fa5862f18df7f5295a172741"},
 ]
 
 [package.dependencies]
@@ -1623,61 +1861,63 @@ uritemplate = ">=3.0.1,<5"
 
 [[package]]
 name = "google-auth"
-version = "2.40.3"
+version = "2.48.0"
+description = "Google Authentication Library"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "google_auth-2.48.0-py3-none-any.whl", hash = "sha256:2e2a537873d449434252a9632c28bfc268b0adb1e53f9fb62afc5333a975903f"},
+    {file = "google_auth-2.48.0.tar.gz", hash = "sha256:4f7e706b0cd3208a3d940a19a822c37a476ddba5450156c3e6624a71f7c841ce"},
+]
+
+[package.dependencies]
+cryptography = ">=38.0.3"
+pyasn1-modules = ">=0.2.1"
+requests = {version = ">=2.20.0,<3.0.0", optional = true, markers = "extra == \"requests\""}
+rsa = ">=3.1.4,<5"
+
+[package.extras]
+aiohttp = ["aiohttp (>=3.6.2,<4.0.0)", "requests (>=2.20.0,<3.0.0)"]
+cryptography = ["cryptography (>=38.0.3)"]
+enterprise-cert = ["pyopenssl"]
+pyjwt = ["pyjwt (>=2.0)"]
+pyopenssl = ["pyopenssl (>=20.0.0)"]
+reauth = ["pyu2f (>=0.1.5)"]
+requests = ["requests (>=2.20.0,<3.0.0)"]
+testing = ["aiohttp (<3.10.0)", "aiohttp (>=3.6.2,<4.0.0)", "aioresponses", "flask", "freezegun", "grpcio", "oauth2client", "packaging", "pyjwt (>=2.0)", "pyopenssl (<24.3.0)", "pyopenssl (>=20.0.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-localserver", "pyu2f (>=0.1.5)", "requests (>=2.20.0,<3.0.0)", "responses", "urllib3"]
+urllib3 = ["packaging", "urllib3"]
+
+[[package]]
+name = "google-auth-httplib2"
+version = "0.3.0"
+description = "Google Authentication Library: httplib2 transport"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "google_auth_httplib2-0.3.0-py3-none-any.whl", hash = "sha256:426167e5df066e3f5a0fc7ea18768c08e7296046594ce4c8c409c2457dd1f776"},
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+]
+
+[package.dependencies]
+google-auth = ">=1.32.0,<3.0.0"
+httplib2 = ">=0.19.0,<1.0.0"
+
+[[package]]
+name = "google-auth-oauthlib"
+version = "1.2.4"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google_auth-2.40.3-py2.py3-none-any.whl", hash = "sha256:1370d4593e86213563547f97a92752fc658456fe4514c809544f330fed45a7ca"},
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+    {file = "google_auth_oauthlib-1.2.4-py3-none-any.whl", hash = "sha256:0e922eea5f2baacaf8867febb782e46e7b153236c21592ed76ab3ddb77ffd772"},
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-cachetools = ">=2.0.0,<6.0"
-pyasn1-modules = ">=0.2.1"
-rsa = ">=3.1.4,<5"
-
-[package.extras]
-aiohttp = ["aiohttp (>=3.6.2,<4.0.0)", "requests (>=2.20.0,<3.0.0)"]
-enterprise-cert = ["cryptography", "pyopenssl"]
-pyjwt = ["cryptography (<39.0.0) ; python_version < \"3.8\"", "cryptography (>=38.0.3)", "pyjwt (>=2.0)"]
-pyopenssl = ["cryptography (<39.0.0) ; python_version < \"3.8\"", "cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
-reauth = ["pyu2f (>=0.1.5)"]
-requests = ["requests (>=2.20.0,<3.0.0)"]
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-urllib3 = ["packaging", "urllib3"]
-
-[[package]]
-name = "google-auth-httplib2"
-version = "0.2.0"
-description = "Google Authentication Library: httplib2 transport"
-optional = false
-python-versions = "*"
-groups = ["main"]
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-]
-
-[package.dependencies]
-google-auth = "*"
-httplib2 = ">=0.19.0"
-
-[[package]]
-name = "google-auth-oauthlib"
-version = "1.2.2"
-description = "Google Authentication Library"
-optional = false
-python-versions = ">=3.6"
-groups = ["main"]
-files = [
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-]
-
-[package.dependencies]
-google-auth = ">=2.15.0"
+google-auth = ">=2.15.0,<2.43.0 || >2.43.0,<2.44.0 || >2.44.0,<2.45.0 || >2.45.0,<3.0.0"
 requests-oauthlib = ">=0.7.0"
 
 [package.extras]
@@ -1685,19 +1925,20 @@ tool = ["click (>=6.0.0)"]
 
 [[package]]
 name = "google-cloud-appengine-logging"
-version = "1.6.2"
+version = "1.8.0"
 description = "Google Cloud Appengine Logging API client library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
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-    {file = "google_cloud_appengine_logging-1.6.2.tar.gz", hash = "sha256:4890928464c98da9eecc7bf4e0542eba2551512c0265462c10f3a3d2a6424b90"},
+    {file = "google_cloud_appengine_logging-1.8.0-py3-none-any.whl", hash = "sha256:a4ce9ce94a9fd8c89ed07fa0b06fcf9ea3642f9532a1be1a8c7b5f82c0a70ec6"},
+    {file = "google_cloud_appengine_logging-1.8.0.tar.gz", hash = "sha256:84b705a69e4109fc2f68dfe36ce3df6a34d5c3d989eee6d0ac1b024dda0ba6f5"},
 ]
 
 [package.dependencies]
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 google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0"
+grpcio = ">=1.33.2,<2.0.0"
 proto-plus = [
     {version = ">=1.22.3,<2.0.0"},
     {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
@@ -1706,14 +1947,14 @@ protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4
 
 [[package]]
 name = "google-cloud-audit-log"
-version = "0.3.2"
+version = "0.4.0"
 description = "Google Cloud Audit Protos"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
-    {file = "google_cloud_audit_log-0.3.2-py3-none-any.whl", hash = "sha256:daaedfb947a0d77f524e1bd2b560242ab4836fe1afd6b06b92f152b9658554ed"},
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+    {file = "google_cloud_audit_log-0.4.0-py3-none-any.whl", hash = "sha256:6b88e2349df45f8f4cc0993b687109b1388da1571c502dc1417efa4b66ec55e0"},
+    {file = "google_cloud_audit_log-0.4.0.tar.gz", hash = "sha256:8467d4dcca9f3e6160520c24d71592e49e874838f174762272ec10e7950b6feb"},
 ]
 
 [package.dependencies]
@@ -1722,33 +1963,33 @@ protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4
 
 [[package]]
 name = "google-cloud-core"
-version = "2.4.3"
+version = "2.5.0"
 description = "Google Cloud API client core library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
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+    {file = "google_cloud_core-2.5.0-py3-none-any.whl", hash = "sha256:67d977b41ae6c7211ee830c7912e41003ea8194bff15ae7d72fd6f51e57acabc"},
+    {file = "google_cloud_core-2.5.0.tar.gz", hash = "sha256:7c1b7ef5c92311717bd05301aa1a91ffbc565673d3b0b4163a52d8413a186963"},
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-google-auth = ">=1.25.0,<3.0dev"
+google-api-core = ">=1.31.6,<2.0.dev0 || >2.3.0,<3.0.0"
+google-auth = ">=1.25.0,<3.0.0"
 
 [package.extras]
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+grpc = ["grpcio (>=1.38.0,<2.0.0) ; python_version < \"3.14\"", "grpcio (>=1.75.1,<2.0.0) ; python_version >= \"3.14\"", "grpcio-status (>=1.38.0,<2.0.0)"]
 
 [[package]]
 name = "google-cloud-logging"
-version = "3.12.1"
+version = "3.13.0"
 description = "Stackdriver Logging API client library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
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+    {file = "google_cloud_logging-3.13.0.tar.gz", hash = "sha256:3aae0573b1a1a4f59ecdf4571f4e7881b5823bd129fe469561c1c49a7fa8a4c1"},
 ]
 
 [package.dependencies]
@@ -1768,18 +2009,18 @@ protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4
 
 [[package]]
 name = "google-cloud-storage"
-version = "3.2.0"
+version = "3.9.0"
 description = "Google Cloud Storage API client library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
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+    {file = "google_cloud_storage-3.9.0-py3-none-any.whl", hash = "sha256:2dce75a9e8b3387078cbbdad44757d410ecdb916101f8ba308abf202b6968066"},
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 ]
 
 [package.dependencies]
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+google-api-core = ">=2.27.0,<3.0.0"
 google-auth = ">=2.26.1,<3.0.0"
 google-cloud-core = ">=2.4.2,<3.0.0"
 google-crc32c = ">=1.1.3,<2.0.0"
@@ -1787,85 +2028,111 @@ google-resumable-media = ">=2.7.2,<3.0.0"
 requests = ">=2.22.0,<3.0.0"
 
 [package.extras]
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 protobuf = ["protobuf (>=3.20.2,<7.0.0)"]
+testing = ["PyYAML", "black", "brotli", "coverage", "flake8", "google-cloud-iam", "google-cloud-kms", "google-cloud-pubsub", "google-cloud-testutils", "google-cloud-testutils", "mock", "numpy", "opentelemetry-sdk", "psutil", "py-cpuinfo", "pyopenssl", "pytest", "pytest-asyncio", "pytest-benchmark", "pytest-cov", "pytest-rerunfailures", "pytest-xdist"]
 tracing = ["opentelemetry-api (>=1.1.0,<2.0.0)"]
 
 [[package]]
 name = "google-crc32c"
-version = "1.7.1"
+version = "1.8.0"
 description = "A python wrapper of the C library 'Google CRC32C'"
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 [package.dependencies]
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-
 [[package]]
 name = "gravitas-md2gdocs"
 version = "0.1.0"
@@ -1941,71 +2191,70 @@ pytest = ">=8.2.1,<9.0.0"
 
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 [package.extras]
 docs = ["Sphinx", "furo"]
-test = ["objgraph", "psutil"]
+test = ["objgraph", "psutil", "setuptools"]
 
 [[package]]
 name = "groq"
@@ -2032,14 +2281,14 @@ aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.6)"]
 
 [[package]]
 name = "grpc-google-iam-v1"
-version = "0.14.2"
+version = "0.14.3"
 description = "IAM API client library"
 optional = false
 python-versions = ">=3.7"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -2049,67 +2298,80 @@ protobuf = ">=3.20.2,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4
 
 [[package]]
 name = "grpcio"
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 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.9"
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 [package.extras]
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+protobuf = ["grpcio-tools (>=1.78.0)"]
 
 [[package]]
 name = "grpcio-status"
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 [[package]]
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 ]
 
-[package.extras]
-test = ["Cython (>=0.29.24)"]
-
 [[package]]
 name = "httpx"
 version = "0.28.1"
@@ -2322,42 +2595,39 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.34.4"
+version = "1.4.1"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
-python-versions = ">=3.8.0"
+python-versions = ">=3.9.0"
 groups = ["main"]
 files = [
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 [package.dependencies]
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 packaging = ">=20.9"
 pyyaml = ">=5.1"
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 tqdm = ">=4.42.1"
-typing-extensions = ">=3.7.4.3"
+typer-slim = "*"
+typing-extensions = ">=4.1.0"
 
 [package.extras]
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-mcp = ["aiohttp", "mcp (>=1.8.0)", "typer"]
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+mcp = ["mcp (>=1.8.0)"]
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 torch = ["safetensors[torch]", "torch"]
-typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
+typing = ["types-PyYAML", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
 
 [[package]]
 name = "hyperframe"
@@ -2373,14 +2643,14 @@ files = [
 
 [[package]]
 name = "identify"
-version = "2.6.12"
+version = "2.6.16"
 description = "File identification library for Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["dev"]
 files = [
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+    {file = "identify-2.6.16.tar.gz", hash = "sha256:846857203b5511bbe94d5a352a48ef2359532bc8f6727b5544077a0dcfb24980"},
 ]
 
 [package.extras]
@@ -2388,14 +2658,14 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
-version = "3.10"
+version = "3.11"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.8"
 groups = ["main", "dev"]
 files = [
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+    {file = "idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea"},
+    {file = "idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902"},
 ]
 
 [package.extras]
@@ -2403,14 +2673,14 @@ all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2
 
 [[package]]
 name = "imageio"
-version = "2.37.0"
-description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
+version = "2.37.2"
+description = "Read and write images and video across all major formats. Supports scientific and volumetric data."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "imageio-2.37.0-py3-none-any.whl", hash = "sha256:11efa15b87bc7871b61590326b2d635439acc321cf7f8ce996f812543ce10eed"},
-    {file = "imageio-2.37.0.tar.gz", hash = "sha256:71b57b3669666272c818497aebba2b4c5f20d5b37c81720e5e1a56d59c492996"},
+    {file = "imageio-2.37.2-py3-none-any.whl", hash = "sha256:ad9adfb20335d718c03de457358ed69f141021a333c40a53e57273d8a5bd0b9b"},
+    {file = "imageio-2.37.2.tar.gz", hash = "sha256:0212ef2727ac9caa5ca4b2c75ae89454312f440a756fcfc8ef1993e718f50f8a"},
 ]
 
 [package.dependencies]
@@ -2418,14 +2688,14 @@ numpy = "*"
 pillow = ">=8.3.2"
 
 [package.extras]
-all-plugins = ["astropy", "av", "imageio-ffmpeg", "numpy (>2)", "pillow-heif", "psutil", "rawpy", "tifffile"]
-all-plugins-pypy = ["av", "imageio-ffmpeg", "pillow-heif", "psutil", "tifffile"]
-build = ["wheel"]
+all-plugins = ["astropy", "av", "fsspec[http]", "imageio-ffmpeg", "numpy (>2)", "pillow-heif", "psutil", "rawpy", "tifffile"]
+all-plugins-pypy = ["fsspec[http]", "imageio-ffmpeg", "pillow-heif", "psutil", "tifffile"]
 dev = ["black", "flake8", "fsspec[github]", "pytest", "pytest-cov"]
 docs = ["numpydoc", "pydata-sphinx-theme", "sphinx (<6)"]
 ffmpeg = ["imageio-ffmpeg", "psutil"]
 fits = ["astropy"]
-full = ["astropy", "av", "black", "flake8", "fsspec[github]", "gdal", "imageio-ffmpeg", "itk", "numpy (>2)", "numpydoc", "pillow-heif", "psutil", "pydata-sphinx-theme", "pytest", "pytest-cov", "rawpy", "sphinx (<6)", "tifffile", "wheel"]
+freeimage = ["fsspec[http]"]
+full = ["astropy", "av", "black", "flake8", "fsspec[github,http]", "imageio-ffmpeg", "numpy (>2)", "numpydoc", "pillow-heif", "psutil", "pydata-sphinx-theme", "pytest", "pytest-cov", "rawpy", "sphinx (<6)", "tifffile"]
 gdal = ["gdal"]
 itk = ["itk"]
 linting = ["black", "flake8"]
@@ -2454,14 +2724,14 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "8.7.0"
+version = "8.7.1"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "importlib_metadata-8.7.0-py3-none-any.whl", hash = "sha256:e5dd1551894c77868a30651cef00984d50e1002d06942a7101d34870c5f02afd"},
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+    {file = "importlib_metadata-8.7.1-py3-none-any.whl", hash = "sha256:5a1f80bf1daa489495071efbb095d75a634cf28a8bc299581244063b53176151"},
+    {file = "importlib_metadata-8.7.1.tar.gz", hash = "sha256:49fef1ae6440c182052f407c8d34a68f72efc36db9ca90dc0113398f2fdde8bb"},
 ]
 
 [package.dependencies]
@@ -2471,21 +2741,21 @@ zipp = ">=3.20"
 check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
 cover = ["pytest-cov"]
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-enabler = ["pytest-enabler (>=2.2)"]
+enabler = ["pytest-enabler (>=3.4)"]
 perf = ["ipython"]
-test = ["flufl.flake8", "importlib_resources (>=1.3) ; python_version < \"3.9\"", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
-type = ["pytest-mypy"]
+test = ["flufl.flake8", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
+type = ["mypy (<1.19) ; platform_python_implementation == \"PyPy\"", "pytest-mypy (>=1.0.1)"]
 
 [[package]]
 name = "iniconfig"
-version = "2.1.0"
+version = "2.3.0"
 description = "brain-dead simple config-ini parsing"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.10"
 groups = ["main", "dev"]
 files = [
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-    {file = "iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7"},
+    {file = "iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12"},
+    {file = "iniconfig-2.3.0.tar.gz", hash = "sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730"},
 ]
 
 [[package]]
@@ -2536,33 +2806,37 @@ testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-ena
 
 [[package]]
 name = "jaraco-context"
-version = "6.0.1"
+version = "6.1.0"
 description = "Useful decorators and context managers"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "jaraco_context-6.1.0-py3-none-any.whl", hash = "sha256:a43b5ed85815223d0d3cfdb6d7ca0d2bc8946f28f30b6f3216bda070f68badda"},
+    {file = "jaraco_context-6.1.0.tar.gz", hash = "sha256:129a341b0a85a7db7879e22acd66902fda67882db771754574338898b2d5d86f"},
 ]
 
 [package.dependencies]
 "backports.tarfile" = {version = "*", markers = "python_version < \"3.12\""}
 
 [package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
+cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-test = ["portend", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
+enabler = ["pytest-enabler (>=3.4)"]
+test = ["jaraco.test (>=5.6.0)", "portend", "pytest (>=6,!=8.1.*)"]
+type = ["mypy (<1.19) ; platform_python_implementation == \"PyPy\"", "pytest-mypy (>=1.0.1)"]
 
 [[package]]
 name = "jaraco-functools"
-version = "4.2.1"
+version = "4.4.0"
 description = "Functools like those found in stdlib"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "jaraco_functools-4.2.1-py3-none-any.whl", hash = "sha256:590486285803805f4b1f99c60ca9e94ed348d4added84b74c7a12885561e524e"},
-    {file = "jaraco_functools-4.2.1.tar.gz", hash = "sha256:be634abfccabce56fa3053f8c7ebe37b682683a4ee7793670ced17bab0087353"},
+    {file = "jaraco_functools-4.4.0-py3-none-any.whl", hash = "sha256:9eec1e36f45c818d9bf307c8948eb03b2b56cd44087b3cdc989abca1f20b9176"},
+    {file = "jaraco_functools-4.4.0.tar.gz", hash = "sha256:da21933b0417b89515562656547a77b4931f98176eb173644c0d35032a33d6bb"},
 ]
 
 [package.dependencies]
@@ -2572,9 +2846,9 @@ more_itertools = "*"
 check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"cygwin\""]
 cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
+enabler = ["pytest-enabler (>=3.4)"]
 test = ["jaraco.classes", "pytest (>=6,!=8.1.*)"]
-type = ["pytest-mypy"]
+type = ["mypy (<1.19) ; platform_python_implementation == \"PyPy\"", "pytest-mypy (>=1.0.1)"]
 
 [[package]]
 name = "jeepney"
@@ -2613,89 +2887,114 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "jiter"
-version = "0.10.0"
+version = "0.13.0"
 description = "Fast iterable JSON parser."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
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 ]
 
 [[package]]
@@ -2712,21 +3011,21 @@ files = [
 
 [[package]]
 name = "jsonschema"
-version = "4.25.0"
+version = "4.26.0"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "jsonschema-4.25.0-py3-none-any.whl", hash = "sha256:24c2e8da302de79c8b9382fee3e76b355e44d2a4364bb207159ce10b517bd716"},
-    {file = "jsonschema-4.25.0.tar.gz", hash = "sha256:e63acf5c11762c0e6672ffb61482bdf57f0876684d8d249c0fe2d730d48bc55f"},
+    {file = "jsonschema-4.26.0-py3-none-any.whl", hash = "sha256:d489f15263b8d200f8387e64b4c3a75f06629559fb73deb8fdfb525f2dab50ce"},
+    {file = "jsonschema-4.26.0.tar.gz", hash = "sha256:0c26707e2efad8aa1bfc5b7ce170f3fccc2e4918ff85989ba9ffa9facb2be326"},
 ]
 
 [package.dependencies]
 attrs = ">=22.2.0"
 jsonschema-specifications = ">=2023.03.6"
 referencing = ">=0.28.4"
-rpds-py = ">=0.7.1"
+rpds-py = ">=0.25.0"
 
 [package.extras]
 format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"]
@@ -2734,14 +3033,14 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 
 [[package]]
 name = "jsonschema-specifications"
-version = "2025.4.1"
+version = "2025.9.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "jsonschema_specifications-2025.4.1-py3-none-any.whl", hash = "sha256:4653bffbd6584f7de83a67e0d620ef16900b390ddc7939d56684d6c81e33f1af"},
-    {file = "jsonschema_specifications-2025.4.1.tar.gz", hash = "sha256:630159c9f4dbea161a6a2205c3011cc4f18ff381b189fff48bb39b9bf26ae608"},
+    {file = "jsonschema_specifications-2025.9.1-py3-none-any.whl", hash = "sha256:98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe"},
+    {file = "jsonschema_specifications-2025.9.1.tar.gz", hash = "sha256:b540987f239e745613c7a9176f3edb72b832a4ac465cf02712288397832b5e8d"},
 ]
 
 [package.dependencies]
@@ -2749,14 +3048,14 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "keyring"
-version = "25.6.0"
+version = "25.7.0"
 description = "Store and access your passwords safely."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "keyring-25.6.0-py3-none-any.whl", hash = "sha256:552a3f7af126ece7ed5c89753650eec89c7eaae8617d0aa4d9ad2b75111266bd"},
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+    {file = "keyring-25.7.0-py3-none-any.whl", hash = "sha256:be4a0b195f149690c166e850609a477c532ddbfbaed96a404d4e43f8d5e2689f"},
+    {file = "keyring-25.7.0.tar.gz", hash = "sha256:fe01bd85eb3f8fb3dd0405defdeac9a5b4f6f0439edbb3149577f244a2e8245b"},
 ]
 
 [package.dependencies]
@@ -2773,20 +3072,20 @@ check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1) ; sys_platform != \"
 completion = ["shtab (>=1.1.0)"]
 cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-enabler = ["pytest-enabler (>=2.2)"]
+enabler = ["pytest-enabler (>=3.4)"]
 test = ["pyfakefs", "pytest (>=6,!=8.1.*)"]
-type = ["pygobject-stubs", "pytest-mypy", "shtab", "types-pywin32"]
+type = ["pygobject-stubs", "pytest-mypy (>=1.0.1)", "shtab", "types-pywin32"]
 
 [[package]]
 name = "langfuse"
-version = "3.11.2"
+version = "3.14.1"
 description = "A client library for accessing langfuse"
 optional = false
 python-versions = "<4.0,>=3.10"
 groups = ["main"]
 files = [
-    {file = "langfuse-3.11.2-py3-none-any.whl", hash = "sha256:84faea9f909694023cc7f0eb45696be190248c8790424f22af57ca4cd7a29f2d"},
-    {file = "langfuse-3.11.2.tar.gz", hash = "sha256:ab5f296a8056815b7288c7f25bc308a5e79f82a8634467b25daffdde99276e09"},
+    {file = "langfuse-3.14.1-py3-none-any.whl", hash = "sha256:17bed605dbfc9947cbd1738a715f6d27c1b80b6da9f2946586171958fa5820d0"},
+    {file = "langfuse-3.14.1.tar.gz", hash = "sha256:404a6104cd29353d7829aa417ec46565b04917e5599afdda96c5b0865f4bc991"},
 ]
 
 [package.dependencies]
@@ -2803,14 +3102,14 @@ wrapt = ">=1.14,<2.0"
 
 [[package]]
 name = "launchdarkly-eventsource"
-version = "1.3.0"
+version = "1.5.1"
 description = "LaunchDarkly SSE Client"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "launchdarkly_eventsource-1.3.0-py3-none-any.whl", hash = "sha256:7afecee7a0f306630e4364994e0816abbbdbaf143fe43b3428ed122fa4e0d487"},
-    {file = "launchdarkly_eventsource-1.3.0.tar.gz", hash = "sha256:5029199b2c344aee2806bbe8784965e9c0197d052d0bab7e1396a94c159f6bc8"},
+    {file = "launchdarkly_eventsource-1.5.1-py3-none-any.whl", hash = "sha256:43dfbc14a3962c9bce252320d690cdcbfda0ca00501226d517ae77e60f570d44"},
+    {file = "launchdarkly_eventsource-1.5.1.tar.gz", hash = "sha256:f122f80b36db6ea1ab20af62c82b8b2668682259b415053c94400dd6c07922a7"},
 ]
 
 [package.dependencies]
@@ -2818,20 +3117,20 @@ urllib3 = ">=1.26.0,<3"
 
 [[package]]
 name = "launchdarkly-server-sdk"
-version = "9.12.0"
+version = "9.14.1"
 description = "LaunchDarkly SDK for Python"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "launchdarkly_server_sdk-9.12.0-py3-none-any.whl", hash = "sha256:c7351e26e6b695b968d49888e967691aae60ded82d73a41a74d59d11252a1413"},
-    {file = "launchdarkly_server_sdk-9.12.0.tar.gz", hash = "sha256:219b100d7569e4f528b6028cbd2a5d61f13539f2b44ed43fc173bb4f456ee580"},
+    {file = "launchdarkly_server_sdk-9.14.1-py3-none-any.whl", hash = "sha256:a9e2bd9ecdef845cd631ae0d4334a1115e5b44257c42eb2349492be4bac7815c"},
+    {file = "launchdarkly_server_sdk-9.14.1.tar.gz", hash = "sha256:1df44baf0a0efa74d8c1dad7a00592b98bce7d19edded7f770da8dbc49922213"},
 ]
 
 [package.dependencies]
 certifi = ">=2018.4.16"
 expiringdict = ">=1.1.4"
-launchdarkly-eventsource = ">=1.2.4,<2.0.0"
+launchdarkly-eventsource = ">=1.5.0,<2.0.0"
 pyRFC3339 = ">=1.0"
 semver = ">=2.10.2"
 urllib3 = ">=1.26.0,<3"
@@ -2844,23 +3143,25 @@ test-filesource = ["pyyaml (>=5.3.1)", "watchdog (>=3.0.0)"]
 
 [[package]]
 name = "litellm"
-version = "1.74.15.post2"
+version = "1.80.0"
 description = "Library to easily interface with LLM API providers"
 optional = false
 python-versions = "!=2.7.*,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,!=3.7.*,>=3.8"
 groups = ["main"]
 files = [
-    {file = "litellm-1.74.15.post2.tar.gz", hash = "sha256:8eddb1c8a6a5a7048f8ba16e652aba23d6ca996dd87cb853c874ba375aa32479"},
+    {file = "litellm-1.80.0-py3-none-any.whl", hash = "sha256:fd0009758f4772257048d74bf79bb64318859adb4ea49a8b66fdbc718cd80b6e"},
+    {file = "litellm-1.80.0.tar.gz", hash = "sha256:eeac733eb6b226f9e5fb020f72fe13a32b3354b001dc62bcf1bc4d9b526d6231"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.10"
 click = "*"
+fastuuid = ">=0.13.0"
 httpx = ">=0.23.0"
 importlib-metadata = ">=6.8.0"
 jinja2 = ">=3.1.2,<4.0.0"
 jsonschema = ">=4.22.0,<5.0.0"
-openai = ">=1.68.2"
+openai = ">=1.99.5"
 pydantic = ">=2.5.0,<3.0.0"
 python-dotenv = ">=0.2.0"
 tiktoken = ">=0.7.0"
@@ -2868,9 +3169,9 @@ tokenizers = "*"
 
 [package.extras]
 caching = ["diskcache (>=5.6.1,<6.0.0)"]
-extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "redisvl (>=0.4.1,<0.5.0) ; python_version >= \"3.9\" and python_version < \"3.14\"", "resend (>=0.8.0,<0.9.0)"]
+extra-proxy = ["azure-identity (>=1.15.0,<2.0.0)", "azure-keyvault-secrets (>=4.8.0,<5.0.0)", "google-cloud-iam (>=2.19.1,<3.0.0)", "google-cloud-kms (>=2.21.3,<3.0.0)", "prisma (==0.11.0)", "redisvl (>=0.4.1,<0.5.0) ; python_version >= \"3.9\" and python_version < \"3.14\"", "resend (>=0.8.0,<0.9.0)"]
 mlflow = ["mlflow (>3.1.4) ; python_version >= \"3.10\""]
-proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-storage-blob (>=12.25.1,<13.0.0)", "backoff", "boto3 (==1.34.34)", "cryptography (>=43.0.1,<44.0.0)", "fastapi (>=0.115.5,<0.116.0)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=23.0.0,<24.0.0)", "litellm-enterprise (==0.1.16)", "litellm-proxy-extras (==0.2.16)", "mcp (>=1.10.0,<2.0.0) ; python_version >= \"3.10\"", "orjson (>=3.9.7,<4.0.0)", "polars (>=1.31.0,<2.0.0) ; python_version >= \"3.10\"", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rich (==13.7.1)", "rq", "uvicorn (>=0.29.0,<0.30.0)", "uvloop (>=0.21.0,<0.22.0) ; sys_platform != \"win32\"", "websockets (>=13.1.0,<14.0.0)"]
+proxy = ["PyJWT (>=2.8.0,<3.0.0)", "apscheduler (>=3.10.4,<4.0.0)", "azure-identity (>=1.15.0,<2.0.0)", "azure-storage-blob (>=12.25.1,<13.0.0)", "backoff", "boto3 (==1.36.0)", "cryptography", "fastapi (>=0.120.1)", "fastapi-sso (>=0.16.0,<0.17.0)", "gunicorn (>=23.0.0,<24.0.0)", "litellm-enterprise (==0.1.21)", "litellm-proxy-extras (==0.4.5)", "mcp (>=1.10.0,<2.0.0) ; python_version >= \"3.10\"", "orjson (>=3.9.7,<4.0.0)", "polars (>=1.31.0,<2.0.0) ; python_version >= \"3.10\"", "pynacl (>=1.5.0,<2.0.0)", "python-multipart (>=0.0.18,<0.0.19)", "pyyaml (>=6.0.1,<7.0.0)", "rich (==13.7.1)", "rq", "soundfile (>=0.12.1,<0.13.0)", "uvicorn (>=0.29.0,<0.30.0)", "uvloop (>=0.21.0,<0.22.0) ; sys_platform != \"win32\"", "websockets (>=13.1.0,<14.0.0)"]
 semantic-router = ["semantic-router ; python_version >= \"3.9\""]
 utils = ["numpydoc"]
 
@@ -2900,73 +3201,101 @@ testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions", "requests"]
 
 [[package]]
 name = "markupsafe"
-version = "3.0.2"
+version = "3.0.3"
 description = "Safely add untrusted strings to HTML/XML markup."
 optional = false
 python-versions = ">=3.9"
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+    {file = "opentelemetry_api-1.39.1.tar.gz", hash = "sha256:fbde8c80e1b937a2c61f20347e91c0c18a1940cecf012d62e65a7caf08967c9c"},
 ]
 
 [package.dependencies]
@@ -3494,50 +4023,53 @@ typing-extensions = ">=4.5.0"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-common"
-version = "1.35.0"
+version = "1.39.1"
 description = "OpenTelemetry Protobuf encoding"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "opentelemetry_exporter_otlp_proto_common-1.35.0-py3-none-any.whl", hash = "sha256:863465de697ae81279ede660f3918680b4480ef5f69dcdac04f30722ed7b74cc"},
-    {file = "opentelemetry_exporter_otlp_proto_common-1.35.0.tar.gz", hash = "sha256:6f6d8c39f629b9fa5c79ce19a2829dbd93034f8ac51243cdf40ed2196f00d7eb"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.39.1-py3-none-any.whl", hash = "sha256:08f8a5862d64cc3435105686d0216c1365dc5701f86844a8cd56597d0c764fde"},
+    {file = "opentelemetry_exporter_otlp_proto_common-1.39.1.tar.gz", hash = "sha256:763370d4737a59741c89a67b50f9e39271639ee4afc999dadfe768541c027464"},
 ]
 
 [package.dependencies]
-opentelemetry-proto = "1.35.0"
+opentelemetry-proto = "1.39.1"
 
 [[package]]
 name = "opentelemetry-exporter-otlp-proto-http"
-version = "1.35.0"
+version = "1.39.1"
 description = "OpenTelemetry Collector Protobuf over HTTP Exporter"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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-    {file = "opentelemetry_exporter_otlp_proto_http-1.35.0.tar.gz", hash = "sha256:cf940147f91b450ef5f66e9980d40eb187582eed399fa851f4a7a45bb880de79"},
+    {file = "opentelemetry_exporter_otlp_proto_http-1.39.1-py3-none-any.whl", hash = "sha256:d9f5207183dd752a412c4cd564ca8875ececba13be6e9c6c370ffb752fd59985"},
+    {file = "opentelemetry_exporter_otlp_proto_http-1.39.1.tar.gz", hash = "sha256:31bdab9745c709ce90a49a0624c2bd445d31a28ba34275951a6a362d16a0b9cb"},
 ]
 
 [package.dependencies]
 googleapis-common-protos = ">=1.52,<2.0"
 opentelemetry-api = ">=1.15,<2.0"
-opentelemetry-exporter-otlp-proto-common = "1.35.0"
-opentelemetry-proto = "1.35.0"
-opentelemetry-sdk = ">=1.35.0,<1.36.0"
+opentelemetry-exporter-otlp-proto-common = "1.39.1"
+opentelemetry-proto = "1.39.1"
+opentelemetry-sdk = ">=1.39.1,<1.40.0"
 requests = ">=2.7,<3.0"
 typing-extensions = ">=4.5.0"
 
+[package.extras]
+gcp-auth = ["opentelemetry-exporter-credential-provider-gcp (>=0.59b0)"]
+
 [[package]]
 name = "opentelemetry-proto"
-version = "1.35.0"
+version = "1.39.1"
 description = "OpenTelemetry Python Proto"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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-    {file = "opentelemetry_proto-1.35.0.tar.gz", hash = "sha256:532497341bd3e1c074def7c5b00172601b28bb83b48afc41a4b779f26eb4ee05"},
+    {file = "opentelemetry_proto-1.39.1-py3-none-any.whl", hash = "sha256:22cdc78efd3b3765d09e68bfbd010d4fc254c9818afd0b6b423387d9dee46007"},
+    {file = "opentelemetry_proto-1.39.1.tar.gz", hash = "sha256:6c8e05144fc0d3ed4d22c2289c6b126e03bcd0e6a7da0f16cedd2e1c2772e2c8"},
 ]
 
 [package.dependencies]
@@ -3545,128 +4077,119 @@ protobuf = ">=5.0,<7.0"
 
 [[package]]
 name = "opentelemetry-sdk"
-version = "1.35.0"
+version = "1.39.1"
 description = "OpenTelemetry Python SDK"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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-    {file = "opentelemetry_sdk-1.35.0.tar.gz", hash = "sha256:2a400b415ab68aaa6f04e8a6a9f6552908fb3090ae2ff78d6ae0c597ac581954"},
+    {file = "opentelemetry_sdk-1.39.1-py3-none-any.whl", hash = "sha256:4d5482c478513ecb0a5d938dcc61394e647066e0cc2676bee9f3af3f3f45f01c"},
+    {file = "opentelemetry_sdk-1.39.1.tar.gz", hash = "sha256:cf4d4563caf7bff906c9f7967e2be22d0d6b349b908be0d90fb21c8e9c995cc6"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.35.0"
-opentelemetry-semantic-conventions = "0.56b0"
+opentelemetry-api = "1.39.1"
+opentelemetry-semantic-conventions = "0.60b1"
 typing-extensions = ">=4.5.0"
 
 [[package]]
 name = "opentelemetry-semantic-conventions"
-version = "0.56b0"
+version = "0.60b1"
 description = "OpenTelemetry Semantic Conventions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "opentelemetry_semantic_conventions-0.56b0-py3-none-any.whl", hash = "sha256:df44492868fd6b482511cc43a942e7194be64e94945f572db24df2e279a001a2"},
-    {file = "opentelemetry_semantic_conventions-0.56b0.tar.gz", hash = "sha256:c114c2eacc8ff6d3908cb328c811eaf64e6d68623840be9224dc829c4fd6c2ea"},
+    {file = "opentelemetry_semantic_conventions-0.60b1-py3-none-any.whl", hash = "sha256:9fa8c8b0c110da289809292b0591220d3a7b53c1526a23021e977d68597893fb"},
+    {file = "opentelemetry_semantic_conventions-0.60b1.tar.gz", hash = "sha256:87c228b5a0669b748c76d76df6c364c369c28f1c465e50f661e39737e84bc953"},
 ]
 
 [package.dependencies]
-opentelemetry-api = "1.35.0"
+opentelemetry-api = "1.39.1"
 typing-extensions = ">=4.5.0"
 
 [[package]]
 name = "orjson"
-version = "3.11.3"
+version = "3.11.7"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 [[package]]
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+    {file = "pandas-2.3.3-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2e3ebdb170b5ef78f19bfb71b0dc5dc58775032361fa188e814959b74d726dd5"},
+    {file = "pandas-2.3.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:d051c0e065b94b7a3cea50eb1ec32e912cd96dba41647eb24104b6c6c14c5788"},
+    {file = "pandas-2.3.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:3869faf4bd07b3b66a9f462417d0ca3a9df29a9f6abd5d0d0dbab15dac7abe87"},
+    {file = "pandas-2.3.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c503ba5216814e295f40711470446bc3fd00f0faea8a086cbc688808e26f92a2"},
+    {file = "pandas-2.3.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a637c5cdfa04b6d6e2ecedcb81fc52ffb0fd78ce2ebccc9ea964df9f658de8c8"},
+    {file = "pandas-2.3.3-cp39-cp39-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:854d00d556406bffe66a4c0802f334c9ad5a96b4f1f868adf036a21b11ef13ff"},
+    {file = "pandas-2.3.3-cp39-cp39-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bf1f8a81d04ca90e32a0aceb819d34dbd378a98bf923b6398b9a3ec0bf44de29"},
+    {file = "pandas-2.3.3-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:23ebd657a4d38268c7dfbdf089fbc31ea709d82e4923c5ffd4fbd5747133ce73"},
+    {file = "pandas-2.3.3-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:5554c929ccc317d41a5e3d1234f3be588248e61f08a74dd17c9eabb535777dc9"},
+    {file = "pandas-2.3.3-cp39-cp39-win_amd64.whl", hash = "sha256:d3e28b3e83862ccf4d85ff19cf8c20b2ae7e503881711ff2d534dc8f761131aa"},
+    {file = "pandas-2.3.3.tar.gz", hash = "sha256:e05e1af93b977f7eafa636d043f9f94c7ee3ac81af99c13508215942e64c993b"},
 ]
 
 [package.dependencies]
@@ -3798,26 +4334,32 @@ files = [
 
 [[package]]
 name = "pathspec"
-version = "0.12.1"
+version = "1.0.4"
 description = "Utility library for gitignore style pattern matching of file paths."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main", "dev"]
 files = [
-    {file = "pathspec-0.12.1-py3-none-any.whl", hash = "sha256:a0d503e138a4c123b27490a4f7beda6a01c6f288df0e4a8b79c7eb0dc7b4cc08"},
-    {file = "pathspec-0.12.1.tar.gz", hash = "sha256:a482d51503a1ab33b1c67a6c3813a26953dbdc71c31dacaef9a838c4e29f5712"},
+    {file = "pathspec-1.0.4-py3-none-any.whl", hash = "sha256:fb6ae2fd4e7c921a165808a552060e722767cfa526f99ca5156ed2ce45a5c723"},
+    {file = "pathspec-1.0.4.tar.gz", hash = "sha256:0210e2ae8a21a9137c0d470578cb0e595af87edaa6ebf12ff176f14a02e0e645"},
 ]
 
+[package.extras]
+hyperscan = ["hyperscan (>=0.7)"]
+optional = ["typing-extensions (>=4)"]
+re2 = ["google-re2 (>=1.1)"]
+tests = ["pytest (>=9)", "typing-extensions (>=4.15)"]
+
 [[package]]
 name = "pbs-installer"
-version = "2025.7.12"
+version = "2025.12.17"
 description = "Installer for Python Build Standalone"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "pbs_installer-2025.7.12-py3-none-any.whl", hash = "sha256:d73414224fceb60d4a07bea97facd9acc05de792dd7becc90a7f22383e7c1cab"},
-    {file = "pbs_installer-2025.7.12.tar.gz", hash = "sha256:343b8905e1da3cd4b03b68d630086330dde1814294963b77d2664b18b5002ac6"},
+    {file = "pbs_installer-2025.12.17-py3-none-any.whl", hash = "sha256:1a899ac5af9ca4c59a7a7944ec3fcf7ad7e40d5684b12eadcfbeee7c59d44123"},
+    {file = "pbs_installer-2025.12.17.tar.gz", hash = "sha256:cf32043fadd168c17a1b18c1c3f801090281bd5c9ce101e2deb7e0e51c8279dd"},
 ]
 
 [package.dependencies]
@@ -4000,14 +4542,14 @@ grpc = ["googleapis-common-protos (>=1.66.0)", "grpcio (>=1.44.0) ; python_versi
 
 [[package]]
 name = "pinecone-plugin-assistant"
-version = "1.7.0"
+version = "1.8.0"
 description = "Assistant plugin for Pinecone SDK"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "pinecone_plugin_assistant-1.7.0-py3-none-any.whl", hash = "sha256:864cb8e7930588e6c2da97c6d44f0240969195f43fa303c5db76cbc12bf903a5"},
-    {file = "pinecone_plugin_assistant-1.7.0.tar.gz", hash = "sha256:e26e3ba10a8b71c3da0d777cff407668022e82963c4913d0ffeb6c552721e482"},
+    {file = "pinecone_plugin_assistant-1.8.0-py3-none-any.whl", hash = "sha256:71ae42c3b4478d23138cbc4fe3505db561319a826f5aff4ef2e306a25ac56686"},
+    {file = "pinecone_plugin_assistant-1.8.0.tar.gz", hash = "sha256:8e8682cff30f9bae9243b384021aba71c91f4e6ef1650e9d63ee64aab83cba87"},
 ]
 
 [package.dependencies]
@@ -4043,37 +4585,37 @@ testing = ["pytest", "pytest-cov", "wheel"]
 
 [[package]]
 name = "platformdirs"
-version = "4.3.8"
+version = "4.5.1"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main", "dev"]
 files = [
-    {file = "platformdirs-4.3.8-py3-none-any.whl", hash = "sha256:ff7059bb7eb1179e2685604f4aaf157cfd9535242bd23742eadc3c13542139b4"},
-    {file = "platformdirs-4.3.8.tar.gz", hash = "sha256:3d512d96e16bcb959a814c9f348431070822a6496326a4be0911c40b5a74c2bc"},
+    {file = "platformdirs-4.5.1-py3-none-any.whl", hash = "sha256:d03afa3963c806a9bed9d5125c8f4cb2fdaf74a55ab60e5d59b3fde758104d31"},
+    {file = "platformdirs-4.5.1.tar.gz", hash = "sha256:61d5cdcc6065745cdd94f0f878977f8de9437be93de97c1c12f853c9c0cdcbda"},
 ]
 
 [package.extras]
-docs = ["furo (>=2024.8.6)", "proselint (>=0.14)", "sphinx (>=8.1.3)", "sphinx-autodoc-typehints (>=3)"]
-test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.3.4)", "pytest-cov (>=6)", "pytest-mock (>=3.14)"]
-type = ["mypy (>=1.14.1)"]
+docs = ["furo (>=2025.9.25)", "proselint (>=0.14)", "sphinx (>=8.2.3)", "sphinx-autodoc-typehints (>=3.2)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.4.2)", "pytest-cov (>=7)", "pytest-mock (>=3.15.1)"]
+type = ["mypy (>=1.18.2)"]
 
 [[package]]
 name = "playwright"
-version = "1.54.0"
+version = "1.58.0"
 description = "A high-level API to automate web browsers"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "playwright-1.54.0-py3-none-macosx_10_13_x86_64.whl", hash = "sha256:bf3b845af744370f1bd2286c2a9536f474cc8a88dc995b72ea9a5be714c9a77d"},
-    {file = "playwright-1.54.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:780928b3ca2077aea90414b37e54edd0c4bbb57d1aafc42f7aa0b3fd2c2fac02"},
-    {file = "playwright-1.54.0-py3-none-macosx_11_0_universal2.whl", hash = "sha256:81d0b6f28843b27f288cfe438af0a12a4851de57998009a519ea84cee6fbbfb9"},
-    {file = "playwright-1.54.0-py3-none-manylinux1_x86_64.whl", hash = "sha256:09919f45cc74c64afb5432646d7fef0d19fff50990c862cb8d9b0577093f40cc"},
-    {file = "playwright-1.54.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:13ae206c55737e8e3eae51fb385d61c0312eeef31535643bb6232741b41b6fdc"},
-    {file = "playwright-1.54.0-py3-none-win32.whl", hash = "sha256:0b108622ffb6906e28566f3f31721cd57dda637d7e41c430287804ac01911f56"},
-    {file = "playwright-1.54.0-py3-none-win_amd64.whl", hash = "sha256:9e5aee9ae5ab1fdd44cd64153313a2045b136fcbcfb2541cc0a3d909132671a2"},
-    {file = "playwright-1.54.0-py3-none-win_arm64.whl", hash = "sha256:a975815971f7b8dca505c441a4c56de1aeb56a211290f8cc214eeef5524e8d75"},
+    {file = "playwright-1.58.0-py3-none-macosx_10_13_x86_64.whl", hash = "sha256:96e3204aac292ee639edbfdef6298b4be2ea0a55a16b7068df91adac077cc606"},
+    {file = "playwright-1.58.0-py3-none-macosx_11_0_arm64.whl", hash = "sha256:70c763694739d28df71ed578b9c8202bb83e8fe8fb9268c04dd13afe36301f71"},
+    {file = "playwright-1.58.0-py3-none-macosx_11_0_universal2.whl", hash = "sha256:185e0132578733d02802dfddfbbc35f42be23a45ff49ccae5081f25952238117"},
+    {file = "playwright-1.58.0-py3-none-manylinux1_x86_64.whl", hash = "sha256:c95568ba1eda83812598c1dc9be60b4406dffd60b149bc1536180ad108723d6b"},
+    {file = "playwright-1.58.0-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8f9999948f1ab541d98812de25e3a8c410776aa516d948807140aff797b4bffa"},
+    {file = "playwright-1.58.0-py3-none-win32.whl", hash = "sha256:1e03be090e75a0fabbdaeab65ce17c308c425d879fa48bb1d7986f96bfad0b99"},
+    {file = "playwright-1.58.0-py3-none-win_amd64.whl", hash = "sha256:a2bf639d0ce33b3ba38de777e08697b0d8f3dc07ab6802e4ac53fb65e3907af8"},
+    {file = "playwright-1.58.0-py3-none-win_arm64.whl", hash = "sha256:32ffe5c303901a13a0ecab91d1c3f74baf73b84f4bedbb6b935f5bc11cc98e1b"},
 ]
 
 [package.dependencies]
@@ -4098,20 +4640,20 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "poethepoet"
-version = "0.37.0"
+version = "0.41.0"
 description = "A task runner that works well with poetry and uv."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["dev"]
 files = [
-    {file = "poethepoet-0.37.0-py3-none-any.whl", hash = "sha256:861790276315abcc8df1b4bd60e28c3d48a06db273edd3092f3c94e1a46e5e22"},
-    {file = "poethepoet-0.37.0.tar.gz", hash = "sha256:73edf458707c674a079baa46802e21455bda3a7f82a408e58c31b9f4fe8e933d"},
+    {file = "poethepoet-0.41.0-py3-none-any.whl", hash = "sha256:4bab9fd8271664c5d21407e8f12827daeb6aa484dc6cc7620f0c3b4e62b42ee4"},
+    {file = "poethepoet-0.41.0.tar.gz", hash = "sha256:dcaad621dc061f6a90b17d091bebb9ca043d67bfe9bd6aa4185aea3ebf7ff3e6"},
 ]
 
 [package.dependencies]
 pastel = ">=0.2.1,<0.3.0"
-pyyaml = ">=6.0.2,<7.0"
-tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""}
+pyyaml = ">=6.0.3,<7.0"
+tomli = {version = ">=1.3.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 poetry-plugin = ["poetry (>=1.2.0,<3.0.0) ; python_version < \"4.0\""]
@@ -4166,52 +4708,53 @@ files = [
 
 [[package]]
 name = "portalocker"
-version = "2.10.1"
+version = "3.2.0"
 description = "Wraps the portalocker recipe for easy usage"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "portalocker-2.10.1-py3-none-any.whl", hash = "sha256:53a5984ebc86a025552264b459b46a2086e269b21823cb572f8f28ee759e45bf"},
-    {file = "portalocker-2.10.1.tar.gz", hash = "sha256:ef1bf844e878ab08aee7e40184156e1151f228f103aa5c6bd0724cc330960f8f"},
+    {file = "portalocker-3.2.0-py3-none-any.whl", hash = "sha256:3cdc5f565312224bc570c49337bd21428bba0ef363bbcf58b9ef4a9f11779968"},
+    {file = "portalocker-3.2.0.tar.gz", hash = "sha256:1f3002956a54a8c3730586c5c77bf18fae4149e07eaf1c29fc3faf4d5a3f89ac"},
 ]
 
 [package.dependencies]
 pywin32 = {version = ">=226", markers = "platform_system == \"Windows\""}
 
 [package.extras]
-docs = ["sphinx (>=1.7.1)"]
+docs = ["portalocker[tests]"]
 redis = ["redis"]
-tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "pytest-timeout (>=2.1.0)", "redis", "sphinx (>=6.0.0)", "types-redis"]
+tests = ["coverage-conditional-plugin (>=0.9.0)", "portalocker[redis]", "pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "pytest-rerunfailures (>=15.0)", "pytest-timeout (>=2.1.0)", "sphinx (>=6.0.0)", "types-pywin32 (>=310.0.0.20250429)", "types-redis"]
 
 [[package]]
 name = "postgrest"
-version = "1.1.1"
+version = "2.27.3"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "postgrest-1.1.1-py3-none-any.whl", hash = "sha256:98a6035ee1d14288484bfe36235942c5fb2d26af6d8120dfe3efbe007859251a"},
-    {file = "postgrest-1.1.1.tar.gz", hash = "sha256:f3bb3e8c4602775c75c844a31f565f5f3dd584df4d36d683f0b67d01a86be322"},
+    {file = "postgrest-2.27.3-py3-none-any.whl", hash = "sha256:ed79123af7127edd78d538bfe8351d277e45b1a36994a4dbf57ae27dde87a7b7"},
+    {file = "postgrest-2.27.3.tar.gz", hash = "sha256:c2e2679addfc8eaab23197bad7ddaee6cbb4cbe8c483ebd2d2e5219543037cc3"},
 ]
 
 [package.dependencies]
-deprecation = ">=2.1.0,<3.0.0"
+deprecation = ">=2.1.0"
 httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
 pydantic = ">=1.9,<3.0"
-strenum = {version = ">=0.4.9,<0.5.0", markers = "python_version < \"3.11\""}
+strenum = {version = ">=0.4.9", markers = "python_full_version < \"3.11.0\""}
+yarl = ">=1.20.1"
 
 [[package]]
 name = "posthog"
-version = "7.6.0"
+version = "7.8.3"
 description = "Integrate PostHog into any python application."
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "posthog-7.6.0-py3-none-any.whl", hash = "sha256:c4dd78cf77c4fecceb965f86066e5ac37886ef867d68ffe75a1db5d681d7d9ad"},
-    {file = "posthog-7.6.0.tar.gz", hash = "sha256:941dfd278ee427c9b14640f09b35b5bb52a71bdf028d7dbb7307e1838fd3002e"},
+    {file = "posthog-7.8.3-py3-none-any.whl", hash = "sha256:1840796e4f7e14dd91ec5fdeb939712c3383fe9e758cfcdeb0317d8f30f7b901"},
+    {file = "posthog-7.8.3.tar.gz", hash = "sha256:2b85e818bf818ac2768a890b772b7c12d4f909797226acd9327d66a319dbcf83"},
 ]
 
 [package.dependencies]
@@ -4289,14 +4832,14 @@ test = ["betamax (>=0.8,<0.9)", "pytest (>=2.7.3)", "urllib3 (==1.26.*)"]
 
 [[package]]
 name = "pre-commit"
-version = "4.4.0"
+version = "4.5.1"
 description = "A framework for managing and maintaining multi-language pre-commit hooks."
 optional = false
 python-versions = ">=3.10"
 groups = ["dev"]
 files = [
-    {file = "pre_commit-4.4.0-py2.py3-none-any.whl", hash = "sha256:b35ea52957cbf83dcc5d8ee636cbead8624e3a15fbfa61a370e42158ac8a5813"},
-    {file = "pre_commit-4.4.0.tar.gz", hash = "sha256:f0233ebab440e9f17cabbb558706eb173d19ace965c68cdce2c081042b4fab15"},
+    {file = "pre_commit-4.5.1-py2.py3-none-any.whl", hash = "sha256:3b3afd891e97337708c1674210f8eba659b52a38ea5f822ff142d10786221f77"},
+    {file = "pre_commit-4.5.1.tar.gz", hash = "sha256:eb545fcff725875197837263e977ea257a402056661f09dae08e4b149b030a61"},
 ]
 
 [package.dependencies]
@@ -4350,17 +4893,19 @@ tqdm = "*"
 
 [[package]]
 name = "prometheus-client"
-version = "0.22.1"
+version = "0.24.1"
 description = "Python client for the Prometheus monitoring system."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "prometheus_client-0.22.1-py3-none-any.whl", hash = "sha256:cca895342e308174341b2cbf99a56bef291fbc0ef7b9e5412a0f26d653ba7094"},
-    {file = "prometheus_client-0.22.1.tar.gz", hash = "sha256:190f1331e783cf21eb60bca559354e0a4d4378facecf78f5428c39b675d20d28"},
+    {file = "prometheus_client-0.24.1-py3-none-any.whl", hash = "sha256:150db128af71a5c2482b36e588fc8a6b95e498750da4b17065947c16070f4055"},
+    {file = "prometheus_client-0.24.1.tar.gz", hash = "sha256:7e0ced7fbbd40f7b84962d5d2ab6f17ef88a72504dcf7c0b40737b43b2a461f9"},
 ]
 
 [package.extras]
+aiohttp = ["aiohttp"]
+django = ["django"]
 twisted = ["twisted"]
 
 [[package]]
@@ -4381,122 +4926,146 @@ starlette = ">=0.30.0,<1.0.0"
 
 [[package]]
 name = "propcache"
-version = "0.3.2"
+version = "0.4.1"
 description = "Accelerated property cache"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "propcache-0.3.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:22d9962a358aedbb7a2e36187ff273adeaab9743373a272976d2e348d08c7770"},
-    {file = "propcache-0.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0d0fda578d1dc3f77b6b5a5dce3b9ad69a8250a891760a548df850a5e8da87f3"},
-    {file = "propcache-0.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3def3da3ac3ce41562d85db655d18ebac740cb3fa4367f11a52b3da9d03a5cc3"},
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 [package.dependencies]
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 windows-terminal = ["colorama (>=0.4.6)"]
 
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 [[package]]
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 optional = false
 python-versions = ">=3.9"
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@@ -4992,20 +5681,20 @@ cryptography = {version = ">=3.4.0", optional = true, markers = "extra == \"cryp
 
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 [[package]]
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 python-versions = ">=3.9"
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 [package.extras]
@@ -5025,26 +5714,26 @@ files = [
 
 [[package]]
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 description = "Generate and parse RFC 3339 timestamps"
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 python-versions = ">=3.7"
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 dev = ["twine (>=3.4.1)"]
 nodejs = ["nodejs-wheel-binaries"]
 
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+
 [[package]]
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+version = "8.4.2"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.9"
 groups = ["main", "dev"]
 files = [
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 [package.dependencies]
@@ -5082,19 +5865,20 @@ dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "requests
 
 [[package]]
 name = "pytest-asyncio"
-version = "1.1.0"
+version = "1.3.0"
 description = "Pytest support for asyncio"
 optional = false
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 files = [
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 ]
 
 [package.dependencies]
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-pytest = ">=8.2,<9"
+pytest = ">=8.2,<10"
+typing-extensions = {version = ">=4.12", markers = "python_version < \"3.13\""}
 
 [package.extras]
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1)"]
@@ -5135,18 +5919,18 @@ pytest = ">=3.0.0"
 
 [[package]]
 name = "pytest-watcher"
-version = "0.4.3"
+version = "0.6.3"
 description = "Automatically rerun your tests on file modifications"
 optional = false
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+python-versions = ">=3.9"
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 ]
 
 [package.dependencies]
-tomli = {version = ">=2.0.1,<3.0.0", markers = "python_version < \"3.11\""}
+tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
 watchdog = ">=2.0.0"
 
 [[package]]
@@ -5166,14 +5950,14 @@ six = ">=1.5"
 
 [[package]]
 name = "python-dotenv"
-version = "1.1.1"
+version = "1.2.1"
 description = "Read key-value pairs from a .env file and set them as environment variables"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.extras]
@@ -5181,14 +5965,14 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "python-multipart"
-version = "0.0.20"
+version = "0.0.22"
 description = "A streaming multipart parser for Python"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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 httpx = {version = ">=0.20.0", extras = ["http2"]}
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 protobuf = ">=3.20.0"
 pydantic = ">=1.10.8,<2.0.dev0 || >2.2.0"
 urllib3 = ">=1.26.14,<3"
@@ -5359,106 +6164,95 @@ dev = ["pytest"]
 
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 [[package]]
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 name = "ruff"
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+version = "0.15.0"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
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 ]
 
 [[package]]
 name = "secretstorage"
-version = "3.3.3"
+version = "3.5.0"
 description = "Python bindings to FreeDesktop.org Secret Service API"
 optional = false
-python-versions = ">=3.6"
+python-versions = ">=3.10"
 groups = ["main"]
 markers = "sys_platform == \"linux\""
 files = [
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 ]
 
 [package.dependencies]
@@ -5965,14 +6729,14 @@ files = [
 
 [[package]]
 name = "sentry-sdk"
-version = "2.44.0"
+version = "2.52.0"
 description = "Python client for Sentry (https://sentry.io)"
 optional = false
 python-versions = ">=3.6"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -6017,6 +6781,7 @@ openai = ["openai (>=1.0.0)", "tiktoken (>=0.3.0)"]
 openfeature = ["openfeature-sdk (>=0.7.1)"]
 opentelemetry = ["opentelemetry-distro (>=0.35b0)"]
 opentelemetry-experimental = ["opentelemetry-distro"]
+opentelemetry-otlp = ["opentelemetry-distro[otlp] (>=0.35b0)"]
 pure-eval = ["asttokens", "executing", "pure_eval"]
 pydantic-ai = ["pydantic-ai (>=1.0.0)"]
 pymongo = ["pymongo (>=3.1)"]
@@ -6033,14 +6798,14 @@ unleash = ["UnleashClient (>=6.0.1)"]
 
 [[package]]
 name = "setuptools"
-version = "80.9.0"
+version = "80.10.2"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.extras]
@@ -6093,81 +6858,95 @@ version = "1.3.1"
 description = "Sniff out which async library your code is running under"
 optional = false
 python-versions = ">=3.7"
-groups = ["main", "dev"]
+groups = ["main"]
 files = [
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 ]
 
+[[package]]
+name = "sortedcontainers"
+version = "2.4.0"
+description = "Sorted Containers -- Sorted List, Sorted Dict, Sorted Set"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
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+
 [[package]]
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 description = "Database Abstraction Library"
 optional = false
 python-versions = ">=3.7"
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+    {file = "sqlalchemy-2.0.46.tar.gz", hash = "sha256:cf36851ee7219c170bb0793dbc3da3e80c582e04a5437bc601bfe8c85c9216d7"},
 ]
 
 [package.dependencies]
-greenlet = {version = ">=1", markers = "python_version < \"3.14\" and (platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\")"}
+greenlet = {version = ">=1", markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\""}
 typing-extensions = ">=4.6.0"
 
 [package.extras]
@@ -6197,23 +6976,24 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "stagehand"
-version = "0.5.1"
+version = "0.5.9"
 description = "Python SDK for Stagehand"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "stagehand-0.5.1-py3-none-any.whl", hash = "sha256:97f88ef31c4b2ad448c2ef341a3cff074b83e40c60872d8f49f79c82f9249174"},
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 ]
 
 [package.dependencies]
 anthropic = ">=0.51.0"
 browserbase = ">=1.4.0"
+google-genai = ">=1.40.0"
 httpx = ">=0.24.0"
-litellm = ">=1.72.0,<1.75.0"
+litellm = ">=1.72.0,<=1.80.0"
 nest-asyncio = ">=1.6.0"
-openai = ">=1.83.0,<1.99.6"
+openai = ">=1.99.6"
 playwright = ">=1.42.1"
 pydantic = ">=1.10.0"
 python-dotenv = ">=1.0.0"
@@ -6225,14 +7005,14 @@ dev = ["black (>=23.3.0)", "isort (>=5.12.0)", "mypy (>=1.3.0)", "psutil (>=5.9.
 
 [[package]]
 name = "starlette"
-version = "0.47.1"
+version = "0.52.1"
 description = "The little ASGI library that shines."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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-    {file = "starlette-0.47.1.tar.gz", hash = "sha256:aef012dd2b6be325ffa16698f9dc533614fb1cebd593a906b90dc1025529a79b"},
+    {file = "starlette-0.52.1-py3-none-any.whl", hash = "sha256:0029d43eb3d273bc4f83a08720b4912ea4b071087a3b48db01b7c839f7954d74"},
+    {file = "starlette-0.52.1.tar.gz", hash = "sha256:834edd1b0a23167694292e94f597773bc3f89f362be6effee198165a35d62933"},
 ]
 
 [package.dependencies]
@@ -6244,20 +7024,22 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "0.12.0"
+version = "2.27.3"
 description = "Supabase Storage client for Python."
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "storage3-2.27.3-py3-none-any.whl", hash = "sha256:11a05b7da84bccabeeea12d940bca3760cf63fe6ca441868677335cfe4fdfbe0"},
+    {file = "storage3-2.27.3.tar.gz", hash = "sha256:dc1a4a010cf36d5482c5cb6c1c28fc5f00e23284342b89e4ae43b5eae8501ddb"},
 ]
 
 [package.dependencies]
-deprecation = ">=2.1.0,<3.0.0"
+deprecation = ">=2.1.0"
 httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
-python-dateutil = ">=2.8.2,<3.0.0"
+pydantic = ">=2.11.7"
+pyiceberg = ">=0.10.0"
+yarl = ">=1.20.1"
 
 [[package]]
 name = "strenum"
@@ -6276,6 +7058,21 @@ docs = ["myst-parser[linkify]", "sphinx", "sphinx-rtd-theme"]
 release = ["twine"]
 test = ["pylint", "pytest", "pytest-black", "pytest-cov", "pytest-pylint"]
 
+[[package]]
+name = "strictyaml"
+version = "1.7.3"
+description = "Strict, typed YAML parser"
+optional = false
+python-versions = ">=3.7.0"
+groups = ["main"]
+files = [
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+]
+
+[package.dependencies]
+python-dateutil = ">=2.6.0"
+
 [[package]]
 name = "stripe"
 version = "11.6.0"
@@ -6294,50 +7091,69 @@ typing-extensions = {version = ">=4.5.0", markers = "python_version >= \"3.7\""}
 
 [[package]]
 name = "supabase"
-version = "2.17.0"
+version = "2.27.3"
 description = "Supabase client for Python."
 optional = false
-python-versions = "<4.0,>=3.9"
-groups = ["main"]
-files = [
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-
-[package.dependencies]
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-httpx = ">=0.26,<0.29"
-postgrest = "1.1.1"
-realtime = "2.6.0"
-storage3 = "0.12.0"
-supafunc = "0.10.1"
-
-[[package]]
-name = "supafunc"
-version = "0.10.1"
-description = "Library for Supabase Functions"
-optional = false
-python-versions = "<4.0,>=3.9"
-groups = ["main"]
-files = [
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-
-[package.dependencies]
-httpx = {version = ">=0.26,<0.29", extras = ["http2"]}
-strenum = ">=0.4.15,<0.5.0"
-
-[[package]]
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-description = "Retry code until it succeeds"
-optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+[package.dependencies]
+httpx = ">=0.26,<0.29"
+postgrest = "2.27.3"
+realtime = "2.27.3"
+storage3 = "2.27.3"
+supabase-auth = "2.27.3"
+supabase-functions = "2.27.3"
+yarl = ">=1.22.0"
+
+[[package]]
+name = "supabase-auth"
+version = "2.27.3"
+description = "Python Client Library for Supabase Auth"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+pydantic = ">=1.10,<3"
+pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
+
+[[package]]
+name = "supabase-functions"
+version = "2.27.3"
+description = "Library for Supabase Functions"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
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+[package.dependencies]
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+strenum = ">=0.4.15"
+yarl = ">=1.20.1"
+
+[[package]]
+name = "tenacity"
+version = "9.1.4"
+description = "Retry code until it succeeds"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
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 ]
 
 [package.extras]
@@ -6346,43 +7162,69 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
 [[package]]
 name = "tiktoken"
-version = "0.9.0"
+version = "0.12.0"
 description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
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 ]
 
 [package.dependencies]
@@ -6428,102 +7270,126 @@ requests = ">=2.32.3,<3.0.0"
 
 [[package]]
 name = "tokenizers"
-version = "0.21.4"
+version = "0.22.2"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
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 ]
 
 [package.dependencies]
-huggingface-hub = ">=0.16.4,<1.0"
+huggingface-hub = ">=0.16.4,<2.0"
 
 [package.extras]
 dev = ["tokenizers[testing]"]
 docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
-testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
+testing = ["datasets", "numpy", "pytest", "pytest-asyncio", "requests", "ruff", "ty"]
 
 [[package]]
 name = "tomli"
-version = "2.2.1"
+version = "2.4.0"
 description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
 markers = "python_version < \"3.11\""
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 [[package]]
 name = "tqdm"
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 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -6538,14 +7404,14 @@ telegram = ["requests"]
 
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 [[package]]
@@ -6570,28 +7436,47 @@ async = ["aiohttp (>=3.7.3,<4)", "async-lru (>=1.0.3,<3)"]
 dev = ["coverage (>=4.4.2)", "coveralls (>=2.1.0)", "tox (>=3.21.0)"]
 test = ["urllib3 (<2)", "vcrpy (>=1.10.3)"]
 
+[[package]]
+name = "typer-slim"
+version = "0.21.1"
+description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
+optional = false
+python-versions = ">=3.9"
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@@ -6823,118 +7721,121 @@ watchmedo = ["PyYAML (>=3.10)"]
 
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 optional = ["python-socks", "wsaccel"]
-test = ["websockets"]
+test = ["pytest", "websockets"]
 
 [[package]]
 name = "websockets"
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 [package.dependencies]
@@ -7228,116 +8109,142 @@ test = ["pytest"]
 
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 ]
 
 [package.dependencies]
@@ -7347,20 +8254,42 @@ propcache = ">=0.2.1"
 
 [[package]]
 name = "youtube-transcript-api"
-version = "1.2.1"
-description = "This is an python API which allows you to get the transcripts/subtitles for a given YouTube video. It also works for automatically generated subtitles, supports translating subtitles and it does not require a headless browser, like other selenium based solutions do!"
+version = "1.2.4"
+description = "This is a python API which allows you to get the transcripts/subtitles for a given YouTube video. It also works for automatically generated subtitles, supports translating subtitles and it does not require a headless browser, like other selenium based solutions do!"
 optional = false
-python-versions = "<3.14,>=3.8"
+python-versions = "<3.15,>=3.8"
 groups = ["main"]
 files = [
-    {file = "youtube_transcript_api-1.2.1-py3-none-any.whl", hash = "sha256:4852356c8459aceab73f8f05e0f7fc4762d5f278e7e34bd6359fce7427df853b"},
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+    {file = "youtube_transcript_api-1.2.4.tar.gz", hash = "sha256:b72d0e96a335df599d67cee51d49e143cff4f45b84bcafc202ff51291603ddcd"},
 ]
 
 [package.dependencies]
 defusedxml = ">=0.7.1,<0.8.0"
 requests = "*"
 
+[[package]]
+name = "yt-dlp"
+version = "2025.12.8"
+description = "A feature-rich command-line audio/video downloader"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
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+]
+
+[package.extras]
+build = ["build", "hatchling (>=1.27.0)", "pip", "setuptools (>=71.0.2)", "wheel"]
+curl-cffi = ["curl-cffi (>=0.5.10,<0.6.dev0 || >=0.10.dev0,<0.14) ; implementation_name == \"cpython\""]
+default = ["brotli ; implementation_name == \"cpython\"", "brotlicffi ; implementation_name != \"cpython\"", "certifi", "mutagen", "pycryptodomex", "requests (>=2.32.2,<3)", "urllib3 (>=2.0.2,<3)", "websockets (>=13.0)", "yt-dlp-ejs (==0.3.2)"]
+dev = ["autopep8 (>=2.0,<3.0)", "pre-commit", "pytest (>=8.1,<9.0)", "pytest-rerunfailures (>=14.0,<15.0)", "ruff (>=0.14.0,<0.15.0)"]
+pyinstaller = ["pyinstaller (>=6.17.0)"]
+secretstorage = ["cffi", "secretstorage"]
+static-analysis = ["autopep8 (>=2.0,<3.0)", "ruff (>=0.14.0,<0.15.0)"]
+test = ["pytest (>=8.1,<9.0)", "pytest-rerunfailures (>=14.0,<15.0)"]
+
 [[package]]
 name = "zerobouncesdk"
 version = "1.1.2"
@@ -7398,118 +8327,117 @@ type = ["pytest-mypy"]
 
 [[package]]
 name = "zstandard"
-version = "0.23.0"
+version = "0.25.0"
 description = "Zstandard bindings for Python"
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+    {file = "zstandard-0.25.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:53e08b2445a6bc241261fea89d065536f00a581f02535f8122eba42db9375530"},
+    {file = "zstandard-0.25.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:1f3689581a72eaba9131b1d9bdbfe520ccd169999219b41000ede2fca5c1bfdb"},
+    {file = "zstandard-0.25.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:d8c56bb4e6c795fc77d74d8e8b80846e1fb8292fc0b5060cd8131d522974b751"},
+    {file = "zstandard-0.25.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:53f94448fe5b10ee75d246497168e5825135d54325458c4bfffbaafabcc0a577"},
+    {file = "zstandard-0.25.0-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:c2ba942c94e0691467ab901fc51b6f2085ff48f2eea77b1a48240f011e8247c7"},
+    {file = "zstandard-0.25.0-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:07b527a69c1e1c8b5ab1ab14e2afe0675614a09182213f21a0717b62027b5936"},
+    {file = "zstandard-0.25.0-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:51526324f1b23229001eb3735bc8c94f9c578b1bd9e867a0a646a3b17109f388"},
+    {file = "zstandard-0.25.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:89c4b48479a43f820b749df49cd7ba2dbc2b1b78560ecb5ab52985574fd40b27"},
+    {file = "zstandard-0.25.0-cp39-cp39-win32.whl", hash = "sha256:1cd5da4d8e8ee0e88be976c294db744773459d51bb32f707a0f166e5ad5c8649"},
+    {file = "zstandard-0.25.0-cp39-cp39-win_amd64.whl", hash = "sha256:37daddd452c0ffb65da00620afb8e17abd4adaae6ce6310702841760c2c26860"},
+    {file = "zstandard-0.25.0.tar.gz", hash = "sha256:7713e1179d162cf5c7906da876ec2ccb9c3a9dcbdffef0cc7f70c3667a205f0b"},
 ]
 
-[package.dependencies]
-cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\""}
-
 [package.extras]
-cffi = ["cffi (>=1.11)"]
+cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and python_version < \"3.14\"", "cffi (>=2.0.0b) ; platform_python_implementation != \"PyPy\" and python_version >= \"3.14\""]
 
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "ee5742dc1a9df50dfc06d4b26a1682cbb2b25cab6b79ce5625ec272f93e4f4bf"
+content-hash = "c06e96ad49388ba7a46786e9ea55ea2c1a57408e15613237b4bee40a592a12af"
diff --git a/autogpt_platform/backend/pyproject.toml b/autogpt_platform/backend/pyproject.toml
index fe263e47c0..317663ee98 100644
--- a/autogpt_platform/backend/pyproject.toml
+++ b/autogpt_platform/backend/pyproject.toml
@@ -12,15 +12,16 @@ python = ">=3.10,<3.14"
 aio-pika = "^9.5.5"
 aiohttp = "^3.10.0"
 aiodns = "^3.5.0"
-anthropic = "^0.59.0"
+anthropic = "^0.79.0"
 apscheduler = "^3.11.1"
 autogpt-libs = { path = "../autogpt_libs", develop = true }
 bleach = { extras = ["css"], version = "^6.2.0" }
 click = "^8.2.0"
-cryptography = "^45.0"
+cryptography = "^46.0"
 discord-py = "^2.5.2"
 e2b-code-interpreter = "^1.5.2"
-fastapi = "^0.116.1"
+elevenlabs = "^1.50.0"
+fastapi = "^0.128.6"
 feedparser = "^6.0.11"
 flake8 = "^7.3.0"
 google-api-python-client = "^2.177.0"
@@ -33,11 +34,11 @@ html2text = "^2024.2.26"
 jinja2 = "^3.1.6"
 jsonref = "^1.1.0"
 jsonschema = "^4.25.0"
-langfuse = "^3.11.0"
-launchdarkly-server-sdk = "^9.12.0"
+langfuse = "^3.14.1"
+launchdarkly-server-sdk = "^9.14.1"
 mem0ai = "^0.1.115"
 moviepy = "^2.1.2"
-ollama = "^0.5.1"
+ollama = "^0.6.1"
 openai = "^1.97.1"
 orjson = "^3.10.0"
 pika = "^1.3.2"
@@ -47,16 +48,16 @@ postmarker = "^1.0"
 praw = "~7.8.1"
 prisma = "^0.15.0"
 rank-bm25 = "^0.2.2"
-prometheus-client = "^0.22.1"
+prometheus-client = "^0.24.1"
 prometheus-fastapi-instrumentator = "^7.0.0"
 psutil = "^7.0.0"
 psycopg2-binary = "^2.9.10"
-pydantic = { extras = ["email"], version = "^2.11.7" }
-pydantic-settings = "^2.10.1"
+pydantic = { extras = ["email"], version = "^2.12.5" }
+pydantic-settings = "^2.12.0"
 pytest = "^8.4.1"
 pytest-asyncio = "^1.1.0"
 python-dotenv = "^1.1.1"
-python-multipart = "^0.0.20"
+python-multipart = "^0.0.22"
 redis = "^6.2.0"
 regex = "^2025.9.18"
 replicate = "^1.0.6"
@@ -64,18 +65,19 @@ sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlal
 sqlalchemy = "^2.0.40"
 strenum = "^0.4.9"
 stripe = "^11.5.0"
-supabase = "2.17.0"
-tenacity = "^9.1.2"
+supabase = "2.27.3"
+tenacity = "^9.1.4"
 todoist-api-python = "^2.1.7"
 tweepy = "^4.16.0"
-uvicorn = { extras = ["standard"], version = "^0.35.0" }
+uvicorn = { extras = ["standard"], version = "^0.40.0" }
 websockets = "^15.0"
 youtube-transcript-api = "^1.2.1"
+yt-dlp = "2025.12.08"
 zerobouncesdk = "^1.1.2"
 # NOTE: please insert new dependencies in their alphabetical location
 pytest-snapshot = "^0.9.0"
-aiofiles = "^24.1.0"
-tiktoken = "^0.9.0"
+aiofiles = "^25.1.0"
+tiktoken = "^0.12.0"
 aioclamd = "^1.0.0"
 setuptools = "^80.9.0"
 gcloud-aio-storage = "^9.5.0"
@@ -93,13 +95,13 @@ black = "^24.10.0"
 faker = "^38.2.0"
 httpx = "^0.28.1"
 isort = "^5.13.2"
-poethepoet = "^0.37.0"
+poethepoet = "^0.41.0"
 pre-commit = "^4.4.0"
 pyright = "^1.1.407"
 pytest-mock = "^3.15.1"
-pytest-watcher = "^0.4.2"
+pytest-watcher = "^0.6.3"
 requests = "^2.32.5"
-ruff = "^0.14.5"
+ruff = "^0.15.0"
 # NOTE: please insert new dependencies in their alphabetical location
 
 [build-system]
diff --git a/autogpt_platform/backend/snapshots/agts_by_creator b/autogpt_platform/backend/snapshots/agts_by_creator
index 4d6dd12920..3f2e128a0d 100644
--- a/autogpt_platform/backend/snapshots/agts_by_creator
+++ b/autogpt_platform/backend/snapshots/agts_by_creator
@@ -9,7 +9,8 @@
       "sub_heading": "Creator agent subheading",
       "description": "Creator agent description",
       "runs": 50,
-      "rating": 4.0
+      "rating": 4.0,
+      "agent_graph_id": "test-graph-2"
     }
   ],
   "pagination": {
diff --git a/autogpt_platform/backend/snapshots/agts_category b/autogpt_platform/backend/snapshots/agts_category
index f65925ead3..4d0531763c 100644
--- a/autogpt_platform/backend/snapshots/agts_category
+++ b/autogpt_platform/backend/snapshots/agts_category
@@ -9,7 +9,8 @@
       "sub_heading": "Category agent subheading",
       "description": "Category agent description",
       "runs": 60,
-      "rating": 4.1
+      "rating": 4.1,
+      "agent_graph_id": "test-graph-category"
     }
   ],
   "pagination": {
diff --git a/autogpt_platform/backend/snapshots/agts_pagination b/autogpt_platform/backend/snapshots/agts_pagination
index 82e7f5f9bf..7b946157fb 100644
--- a/autogpt_platform/backend/snapshots/agts_pagination
+++ b/autogpt_platform/backend/snapshots/agts_pagination
@@ -9,7 +9,8 @@
       "sub_heading": "Agent 0 subheading",
       "description": "Agent 0 description",
       "runs": 0,
-      "rating": 4.0
+      "rating": 4.0,
+      "agent_graph_id": "test-graph-2"
     },
     {
       "slug": "agent-1",
@@ -20,7 +21,8 @@
       "sub_heading": "Agent 1 subheading",
       "description": "Agent 1 description",
       "runs": 10,
-      "rating": 4.0
+      "rating": 4.0,
+      "agent_graph_id": "test-graph-2"
     },
     {
       "slug": "agent-2",
@@ -31,7 +33,8 @@
       "sub_heading": "Agent 2 subheading",
       "description": "Agent 2 description",
       "runs": 20,
-      "rating": 4.0
+      "rating": 4.0,
+      "agent_graph_id": "test-graph-2"
     },
     {
       "slug": "agent-3",
@@ -42,7 +45,8 @@
       "sub_heading": "Agent 3 subheading",
       "description": "Agent 3 description",
       "runs": 30,
-      "rating": 4.0
+      "rating": 4.0,
+      "agent_graph_id": "test-graph-2"
     },
     {
       "slug": "agent-4",
@@ -53,7 +57,8 @@
       "sub_heading": "Agent 4 subheading",
       "description": "Agent 4 description",
       "runs": 40,
-      "rating": 4.0
+      "rating": 4.0,
+      "agent_graph_id": "test-graph-2"
     }
   ],
   "pagination": {
diff --git a/autogpt_platform/backend/snapshots/agts_search b/autogpt_platform/backend/snapshots/agts_search
index ca3f504584..ae9cc116bc 100644
--- a/autogpt_platform/backend/snapshots/agts_search
+++ b/autogpt_platform/backend/snapshots/agts_search
@@ -9,7 +9,8 @@
       "sub_heading": "Search agent subheading",
       "description": "Specific search term description",
       "runs": 75,
-      "rating": 4.2
+      "rating": 4.2,
+      "agent_graph_id": "test-graph-search"
     }
   ],
   "pagination": {
diff --git a/autogpt_platform/backend/snapshots/agts_sorted b/autogpt_platform/backend/snapshots/agts_sorted
index cddead76a5..b182256b2c 100644
--- a/autogpt_platform/backend/snapshots/agts_sorted
+++ b/autogpt_platform/backend/snapshots/agts_sorted
@@ -9,7 +9,8 @@
       "sub_heading": "Top agent subheading",
       "description": "Top agent description",
       "runs": 1000,
-      "rating": 5.0
+      "rating": 5.0,
+      "agent_graph_id": "test-graph-3"
     }
   ],
   "pagination": {
diff --git a/autogpt_platform/backend/snapshots/feat_agts b/autogpt_platform/backend/snapshots/feat_agts
index d57996a768..4f85786434 100644
--- a/autogpt_platform/backend/snapshots/feat_agts
+++ b/autogpt_platform/backend/snapshots/feat_agts
@@ -9,7 +9,8 @@
       "sub_heading": "Featured agent subheading",
       "description": "Featured agent description",
       "runs": 100,
-      "rating": 4.5
+      "rating": 4.5,
+      "agent_graph_id": "test-graph-1"
     }
   ],
   "pagination": {
diff --git a/autogpt_platform/backend/snapshots/grph_single b/autogpt_platform/backend/snapshots/grph_single
index 1811a57ec8..7fa5783577 100644
--- a/autogpt_platform/backend/snapshots/grph_single
+++ b/autogpt_platform/backend/snapshots/grph_single
@@ -3,7 +3,6 @@
   "credentials_input_schema": {
     "properties": {},
     "required": [],
-    "title": "TestGraphCredentialsInputSchema",
     "type": "object"
   },
   "description": "A test graph",
diff --git a/autogpt_platform/backend/snapshots/grphs_all b/autogpt_platform/backend/snapshots/grphs_all
index 0b314d96f9..9ccb4a6dc8 100644
--- a/autogpt_platform/backend/snapshots/grphs_all
+++ b/autogpt_platform/backend/snapshots/grphs_all
@@ -1,34 +1,14 @@
 [
   {
-    "credentials_input_schema": {
-      "properties": {},
-      "required": [],
-      "title": "TestGraphCredentialsInputSchema",
-      "type": "object"
-    },
+    "created_at": "2025-09-04T13:37:00",
     "description": "A test graph",
     "forked_from_id": null,
     "forked_from_version": null,
-    "has_external_trigger": false,
-    "has_human_in_the_loop": false,
-    "has_sensitive_action": false,
     "id": "graph-123",
-    "input_schema": {
-      "properties": {},
-      "required": [],
-      "type": "object"
-    },
     "instructions": null,
     "is_active": true,
     "name": "Test Graph",
-    "output_schema": {
-      "properties": {},
-      "required": [],
-      "type": "object"
-    },
     "recommended_schedule_cron": null,
-    "sub_graphs": [],
-    "trigger_setup_info": null,
     "user_id": "3e53486c-cf57-477e-ba2a-cb02dc828e1a",
     "version": 1
   }
diff --git a/autogpt_platform/backend/snapshots/lib_agts_search b/autogpt_platform/backend/snapshots/lib_agts_search
index 67c307b09e..3ce8402b63 100644
--- a/autogpt_platform/backend/snapshots/lib_agts_search
+++ b/autogpt_platform/backend/snapshots/lib_agts_search
@@ -31,6 +31,10 @@
       "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
+      "execution_count": 0,
+      "success_rate": null,
+      "avg_correctness_score": null,
+      "recent_executions": [],
       "can_access_graph": true,
       "is_latest_version": true,
       "is_favorite": false,
@@ -72,6 +76,10 @@
       "has_sensitive_action": false,
       "trigger_setup_info": null,
       "new_output": false,
+      "execution_count": 0,
+      "success_rate": null,
+      "avg_correctness_score": null,
+      "recent_executions": [],
       "can_access_graph": false,
       "is_latest_version": true,
       "is_favorite": false,
diff --git a/autogpt_platform/backend/test/agent_generator/test_core_integration.py b/autogpt_platform/backend/test/agent_generator/test_core_integration.py
index bdcc24ba79..528763e751 100644
--- a/autogpt_platform/backend/test/agent_generator/test_core_integration.py
+++ b/autogpt_platform/backend/test/agent_generator/test_core_integration.py
@@ -57,7 +57,8 @@ class TestDecomposeGoal:
 
             result = await core.decompose_goal("Build a chatbot")
 
-            mock_external.assert_called_once_with("Build a chatbot", "")
+            # library_agents defaults to None
+            mock_external.assert_called_once_with("Build a chatbot", "", None)
             assert result == expected_result
 
     @pytest.mark.asyncio
@@ -74,7 +75,8 @@ class TestDecomposeGoal:
 
             await core.decompose_goal("Build a chatbot", "Use Python")
 
-            mock_external.assert_called_once_with("Build a chatbot", "Use Python")
+            # library_agents defaults to None
+            mock_external.assert_called_once_with("Build a chatbot", "Use Python", None)
 
     @pytest.mark.asyncio
     async def test_returns_none_on_service_failure(self):
@@ -109,8 +111,7 @@ class TestGenerateAgent:
             instructions = {"type": "instructions", "steps": ["Step 1"]}
             result = await core.generate_agent(instructions)
 
-            mock_external.assert_called_once_with(instructions)
-            # Result should have id, version, is_active added if not present
+            mock_external.assert_called_once_with(instructions, None, None, None)
             assert result is not None
             assert result["name"] == "Test Agent"
             assert "id" in result
@@ -174,7 +175,9 @@ class TestGenerateAgentPatch:
             current_agent = {"nodes": [], "links": []}
             result = await core.generate_agent_patch("Add a node", current_agent)
 
-            mock_external.assert_called_once_with("Add a node", current_agent)
+            mock_external.assert_called_once_with(
+                "Add a node", current_agent, None, None, None
+            )
             assert result == expected_result
 
     @pytest.mark.asyncio
diff --git a/autogpt_platform/backend/test/agent_generator/test_library_agents.py b/autogpt_platform/backend/test/agent_generator/test_library_agents.py
new file mode 100644
index 0000000000..8387339582
--- /dev/null
+++ b/autogpt_platform/backend/test/agent_generator/test_library_agents.py
@@ -0,0 +1,857 @@
+"""
+Tests for library agent fetching functionality in agent generator.
+
+This test suite verifies the search-based library agent fetching,
+including the combination of library and marketplace agents.
+"""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from backend.api.features.chat.tools.agent_generator import core
+
+
+class TestGetLibraryAgentsForGeneration:
+    """Test get_library_agents_for_generation function."""
+
+    @pytest.mark.asyncio
+    async def test_fetches_agents_with_search_term(self):
+        """Test that search_term is passed to the library db."""
+        # Create a mock agent with proper attribute values
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "agent-123"
+        mock_agent.graph_version = 1
+        mock_agent.name = "Email Agent"
+        mock_agent.description = "Sends emails"
+        mock_agent.input_schema = {"properties": {}}
+        mock_agent.output_schema = {"properties": {}}
+        mock_agent.recent_executions = []
+
+        mock_response = MagicMock()
+        mock_response.agents = [mock_agent]
+
+        with patch.object(
+            core.library_db,
+            "list_library_agents",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_list:
+            result = await core.get_library_agents_for_generation(
+                user_id="user-123",
+                search_query="send email",
+            )
+
+            mock_list.assert_called_once_with(
+                user_id="user-123",
+                search_term="send email",
+                page=1,
+                page_size=15,
+                include_executions=True,
+            )
+
+        # Verify result format
+        assert len(result) == 1
+        assert result[0]["graph_id"] == "agent-123"
+        assert result[0]["name"] == "Email Agent"
+
+    @pytest.mark.asyncio
+    async def test_excludes_specified_graph_id(self):
+        """Test that agents with excluded graph_id are filtered out."""
+        mock_response = MagicMock()
+        mock_response.agents = [
+            MagicMock(
+                graph_id="agent-123",
+                graph_version=1,
+                name="Agent 1",
+                description="First agent",
+                input_schema={},
+                output_schema={},
+                recent_executions=[],
+            ),
+            MagicMock(
+                graph_id="agent-456",
+                graph_version=1,
+                name="Agent 2",
+                description="Second agent",
+                input_schema={},
+                output_schema={},
+                recent_executions=[],
+            ),
+        ]
+
+        with patch.object(
+            core.library_db,
+            "list_library_agents",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ):
+            result = await core.get_library_agents_for_generation(
+                user_id="user-123",
+                exclude_graph_id="agent-123",
+            )
+
+        # Verify the excluded agent is not in results
+        assert len(result) == 1
+        assert result[0]["graph_id"] == "agent-456"
+
+    @pytest.mark.asyncio
+    async def test_respects_max_results(self):
+        """Test that max_results parameter limits the page_size."""
+        mock_response = MagicMock()
+        mock_response.agents = []
+
+        with patch.object(
+            core.library_db,
+            "list_library_agents",
+            new_callable=AsyncMock,
+            return_value=mock_response,
+        ) as mock_list:
+            await core.get_library_agents_for_generation(
+                user_id="user-123",
+                max_results=5,
+            )
+
+            mock_list.assert_called_once_with(
+                user_id="user-123",
+                search_term=None,
+                page=1,
+                page_size=5,
+                include_executions=True,
+            )
+
+
+class TestSearchMarketplaceAgentsForGeneration:
+    """Test search_marketplace_agents_for_generation function."""
+
+    @pytest.mark.asyncio
+    async def test_searches_marketplace_with_query(self):
+        """Test that marketplace is searched with the query."""
+        mock_response = MagicMock()
+        mock_response.agents = [
+            MagicMock(
+                agent_name="Public Agent",
+                description="A public agent",
+                sub_heading="Does something useful",
+                creator="creator-1",
+                agent_graph_id="graph-123",
+            )
+        ]
+
+        mock_graph = MagicMock()
+        mock_graph.id = "graph-123"
+        mock_graph.version = 1
+        mock_graph.input_schema = {"type": "object"}
+        mock_graph.output_schema = {"type": "object"}
+
+        with (
+            patch(
+                "backend.api.features.store.db.get_store_agents",
+                new_callable=AsyncMock,
+                return_value=mock_response,
+            ) as mock_search,
+            patch(
+                "backend.api.features.chat.tools.agent_generator.core.get_store_listed_graphs",
+                new_callable=AsyncMock,
+                return_value={"graph-123": mock_graph},
+            ),
+        ):
+            result = await core.search_marketplace_agents_for_generation(
+                search_query="automation",
+                max_results=10,
+            )
+
+            mock_search.assert_called_once_with(
+                search_query="automation",
+                page=1,
+                page_size=10,
+            )
+
+        assert len(result) == 1
+        assert result[0]["name"] == "Public Agent"
+        assert result[0]["graph_id"] == "graph-123"
+
+    @pytest.mark.asyncio
+    async def test_handles_marketplace_error_gracefully(self):
+        """Test that marketplace errors don't crash the function."""
+        with patch(
+            "backend.api.features.store.db.get_store_agents",
+            new_callable=AsyncMock,
+            side_effect=Exception("Marketplace unavailable"),
+        ):
+            result = await core.search_marketplace_agents_for_generation(
+                search_query="test"
+            )
+
+        # Should return empty list, not raise exception
+        assert result == []
+
+
+class TestGetAllRelevantAgentsForGeneration:
+    """Test get_all_relevant_agents_for_generation function."""
+
+    @pytest.mark.asyncio
+    async def test_combines_library_and_marketplace_agents(self):
+        """Test that agents from both sources are combined."""
+        library_agents = [
+            {
+                "graph_id": "lib-123",
+                "graph_version": 1,
+                "name": "Library Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        marketplace_agents = [
+            {
+                "graph_id": "market-456",
+                "graph_version": 1,
+                "name": "Market Agent",
+                "description": "From marketplace",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+                return_value=marketplace_agents,
+            ):
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query="test query",
+                    include_marketplace=True,
+                )
+
+        # Library agents should come first
+        assert len(result) == 2
+        assert result[0]["name"] == "Library Agent"
+        assert result[1]["name"] == "Market Agent"
+
+    @pytest.mark.asyncio
+    async def test_deduplicates_by_graph_id(self):
+        """Test that marketplace agents with same graph_id as library are excluded."""
+        library_agents = [
+            {
+                "graph_id": "shared-123",
+                "graph_version": 1,
+                "name": "Shared Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        marketplace_agents = [
+            {
+                "graph_id": "shared-123",  # Same graph_id, should be deduplicated
+                "graph_version": 1,
+                "name": "Shared Agent",
+                "description": "From marketplace",
+                "input_schema": {},
+                "output_schema": {},
+            },
+            {
+                "graph_id": "unique-456",
+                "graph_version": 1,
+                "name": "Unique Agent",
+                "description": "Only in marketplace",
+                "input_schema": {},
+                "output_schema": {},
+            },
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+                return_value=marketplace_agents,
+            ):
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query="test",
+                    include_marketplace=True,
+                )
+
+        # Shared Agent from marketplace should be excluded by graph_id
+        assert len(result) == 2
+        names = [a["name"] for a in result]
+        assert "Shared Agent" in names
+        assert "Unique Agent" in names
+
+    @pytest.mark.asyncio
+    async def test_skips_marketplace_when_disabled(self):
+        """Test that marketplace is not searched when include_marketplace=False."""
+        library_agents = [
+            {
+                "graph_id": "lib-123",
+                "graph_version": 1,
+                "name": "Library Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+            ) as mock_marketplace:
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query="test",
+                    include_marketplace=False,
+                )
+
+        # Marketplace should not be called
+        mock_marketplace.assert_not_called()
+        assert len(result) == 1
+
+    @pytest.mark.asyncio
+    async def test_skips_marketplace_when_no_search_query(self):
+        """Test that marketplace is not searched without a search query."""
+        library_agents = [
+            {
+                "graph_id": "lib-123",
+                "graph_version": 1,
+                "name": "Library Agent",
+                "description": "From library",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        with patch.object(
+            core,
+            "get_library_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=library_agents,
+        ):
+            with patch.object(
+                core,
+                "search_marketplace_agents_for_generation",
+                new_callable=AsyncMock,
+            ) as mock_marketplace:
+                result = await core.get_all_relevant_agents_for_generation(
+                    user_id="user-123",
+                    search_query=None,  # No search query
+                    include_marketplace=True,
+                )
+
+        # Marketplace should not be called without search query
+        mock_marketplace.assert_not_called()
+        assert len(result) == 1
+
+
+class TestExtractSearchTermsFromSteps:
+    """Test extract_search_terms_from_steps function."""
+
+    def test_extracts_terms_from_instructions_type(self):
+        """Test extraction from valid instructions decomposition result."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {
+                    "description": "Send an email notification",
+                    "block_name": "GmailSendBlock",
+                },
+                {"description": "Fetch weather data", "action": "Get weather API"},
+            ],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert "Send an email notification" in result
+        assert "GmailSendBlock" in result
+        assert "Fetch weather data" in result
+        assert "Get weather API" in result
+
+    def test_returns_empty_for_non_instructions_type(self):
+        """Test that non-instructions types return empty list."""
+        decomposition_result = {
+            "type": "clarifying_questions",
+            "questions": [{"question": "What email?"}],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert result == []
+
+    def test_deduplicates_terms_case_insensitively(self):
+        """Test that duplicate terms are removed (case-insensitive)."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "Send Email", "name": "send email"},
+                {"description": "Other task"},
+            ],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        # Should only have one "send email" variant
+        email_terms = [t for t in result if "email" in t.lower()]
+        assert len(email_terms) == 1
+
+    def test_filters_short_terms(self):
+        """Test that terms with 3 or fewer characters are filtered out."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "ab", "action": "xyz"},  # Both too short
+                {"description": "Valid term here"},
+            ],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert "ab" not in result
+        assert "xyz" not in result
+        assert "Valid term here" in result
+
+    def test_handles_empty_steps(self):
+        """Test handling of empty steps list."""
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [],
+        }
+
+        result = core.extract_search_terms_from_steps(decomposition_result)
+
+        assert result == []
+
+
+class TestEnrichLibraryAgentsFromSteps:
+    """Test enrich_library_agents_from_steps function."""
+
+    @pytest.mark.asyncio
+    async def test_enriches_with_additional_agents(self):
+        """Test that additional agents are found based on steps."""
+        existing_agents = [
+            {
+                "graph_id": "existing-123",
+                "graph_version": 1,
+                "name": "Existing Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        additional_agents = [
+            {
+                "graph_id": "new-456",
+                "graph_version": 1,
+                "name": "Email Agent",
+                "description": "For sending emails",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "Send email notification"},
+            ],
+        }
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=additional_agents,
+        ):
+            result = await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should have both existing and new agents
+        assert len(result) == 2
+        names = [a["name"] for a in result]
+        assert "Existing Agent" in names
+        assert "Email Agent" in names
+
+    @pytest.mark.asyncio
+    async def test_deduplicates_by_graph_id(self):
+        """Test that agents with same graph_id are not duplicated."""
+        existing_agents = [
+            {
+                "graph_id": "agent-123",
+                "graph_version": 1,
+                "name": "Existing Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        # Additional search returns same agent
+        additional_agents = [
+            {
+                "graph_id": "agent-123",  # Same ID
+                "graph_version": 1,
+                "name": "Existing Agent Copy",
+                "description": "Same agent different name",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [{"description": "Some action"}],
+        }
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=additional_agents,
+        ):
+            result = await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should not duplicate
+        assert len(result) == 1
+
+    @pytest.mark.asyncio
+    async def test_deduplicates_by_name(self):
+        """Test that agents with same name are not duplicated."""
+        existing_agents = [
+            {
+                "graph_id": "agent-123",
+                "graph_version": 1,
+                "name": "Email Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        # Additional search returns agent with same name but different ID
+        additional_agents = [
+            {
+                "graph_id": "agent-456",  # Different ID
+                "graph_version": 1,
+                "name": "Email Agent",  # Same name
+                "description": "Different agent same name",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [{"description": "Send email"}],
+        }
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            new_callable=AsyncMock,
+            return_value=additional_agents,
+        ):
+            result = await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should not duplicate by name
+        assert len(result) == 1
+        assert result[0].get("graph_id") == "agent-123"  # Original kept
+
+    @pytest.mark.asyncio
+    async def test_returns_existing_when_no_steps(self):
+        """Test that existing agents are returned when no search terms extracted."""
+        existing_agents = [
+            {
+                "graph_id": "existing-123",
+                "graph_version": 1,
+                "name": "Existing Agent",
+                "description": "Already fetched",
+                "input_schema": {},
+                "output_schema": {},
+            }
+        ]
+
+        decomposition_result = {
+            "type": "clarifying_questions",  # Not instructions type
+            "questions": [],
+        }
+
+        result = await core.enrich_library_agents_from_steps(
+            user_id="user-123",
+            decomposition_result=decomposition_result,
+            existing_agents=existing_agents,
+        )
+
+        # Should return existing unchanged
+        assert result == existing_agents
+
+    @pytest.mark.asyncio
+    async def test_limits_search_terms_to_three(self):
+        """Test that only first 3 search terms are used."""
+        existing_agents = []
+
+        decomposition_result = {
+            "type": "instructions",
+            "steps": [
+                {"description": "First action"},
+                {"description": "Second action"},
+                {"description": "Third action"},
+                {"description": "Fourth action"},
+                {"description": "Fifth action"},
+            ],
+        }
+
+        call_count = 0
+
+        async def mock_get_agents(*args, **kwargs):
+            nonlocal call_count
+            call_count += 1
+            return []
+
+        with patch.object(
+            core,
+            "get_all_relevant_agents_for_generation",
+            side_effect=mock_get_agents,
+        ):
+            await core.enrich_library_agents_from_steps(
+                user_id="user-123",
+                decomposition_result=decomposition_result,
+                existing_agents=existing_agents,
+            )
+
+        # Should only make 3 calls (limited to first 3 terms)
+        assert call_count == 3
+
+
+class TestExtractUuidsFromText:
+    """Test extract_uuids_from_text function."""
+
+    def test_extracts_single_uuid(self):
+        """Test extraction of a single UUID from text."""
+        text = "Use my agent 46631191-e8a8-486f-ad90-84f89738321d for this task"
+        result = core.extract_uuids_from_text(text)
+        assert len(result) == 1
+        assert "46631191-e8a8-486f-ad90-84f89738321d" in result
+
+    def test_extracts_multiple_uuids(self):
+        """Test extraction of multiple UUIDs from text."""
+        text = (
+            "Combine agents 11111111-1111-4111-8111-111111111111 "
+            "and 22222222-2222-4222-9222-222222222222"
+        )
+        result = core.extract_uuids_from_text(text)
+        assert len(result) == 2
+        assert "11111111-1111-4111-8111-111111111111" in result
+        assert "22222222-2222-4222-9222-222222222222" in result
+
+    def test_deduplicates_uuids(self):
+        """Test that duplicate UUIDs are deduplicated."""
+        text = (
+            "Use 46631191-e8a8-486f-ad90-84f89738321d twice: "
+            "46631191-e8a8-486f-ad90-84f89738321d"
+        )
+        result = core.extract_uuids_from_text(text)
+        assert len(result) == 1
+
+    def test_normalizes_to_lowercase(self):
+        """Test that UUIDs are normalized to lowercase."""
+        text = "Use 46631191-E8A8-486F-AD90-84F89738321D"
+        result = core.extract_uuids_from_text(text)
+        assert result[0] == "46631191-e8a8-486f-ad90-84f89738321d"
+
+    def test_returns_empty_for_no_uuids(self):
+        """Test that empty list is returned when no UUIDs found."""
+        text = "Create an email agent that sends notifications"
+        result = core.extract_uuids_from_text(text)
+        assert result == []
+
+    def test_ignores_invalid_uuids(self):
+        """Test that invalid UUID-like strings are ignored."""
+        text = "Not a valid UUID: 12345678-1234-1234-1234-123456789abc"
+        result = core.extract_uuids_from_text(text)
+        # UUID v4 requires specific patterns (4 in third group, 8/9/a/b in fourth)
+        assert len(result) == 0
+
+
+class TestGetLibraryAgentById:
+    """Test get_library_agent_by_id function (and its alias get_library_agent_by_graph_id)."""
+
+    @pytest.mark.asyncio
+    async def test_returns_agent_when_found_by_graph_id(self):
+        """Test that agent is returned when found by graph_id."""
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "agent-123"
+        mock_agent.graph_version = 1
+        mock_agent.name = "Test Agent"
+        mock_agent.description = "Test description"
+        mock_agent.input_schema = {"properties": {}}
+        mock_agent.output_schema = {"properties": {}}
+
+        with patch.object(
+            core.library_db,
+            "get_library_agent_by_graph_id",
+            new_callable=AsyncMock,
+            return_value=mock_agent,
+        ):
+            result = await core.get_library_agent_by_id("user-123", "agent-123")
+
+        assert result is not None
+        assert result["graph_id"] == "agent-123"
+        assert result["name"] == "Test Agent"
+
+    @pytest.mark.asyncio
+    async def test_falls_back_to_library_agent_id(self):
+        """Test that lookup falls back to library agent ID when graph_id not found."""
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "graph-456"  # Different from the lookup ID
+        mock_agent.graph_version = 1
+        mock_agent.name = "Library Agent"
+        mock_agent.description = "Found by library ID"
+        mock_agent.input_schema = {"properties": {}}
+        mock_agent.output_schema = {"properties": {}}
+
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                return_value=None,  # Not found by graph_id
+            ),
+            patch.object(
+                core.library_db,
+                "get_library_agent",
+                new_callable=AsyncMock,
+                return_value=mock_agent,  # Found by library ID
+            ),
+        ):
+            result = await core.get_library_agent_by_id("user-123", "library-id-123")
+
+        assert result is not None
+        assert result["graph_id"] == "graph-456"
+        assert result["name"] == "Library Agent"
+
+    @pytest.mark.asyncio
+    async def test_returns_none_when_not_found_by_either_method(self):
+        """Test that None is returned when agent not found by either method."""
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                return_value=None,
+            ),
+            patch.object(
+                core.library_db,
+                "get_library_agent",
+                new_callable=AsyncMock,
+                side_effect=core.NotFoundError("Not found"),
+            ),
+        ):
+            result = await core.get_library_agent_by_id("user-123", "nonexistent")
+
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_returns_none_on_exception(self):
+        """Test that None is returned when exception occurs in both lookups."""
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                side_effect=Exception("Database error"),
+            ),
+            patch.object(
+                core.library_db,
+                "get_library_agent",
+                new_callable=AsyncMock,
+                side_effect=Exception("Database error"),
+            ),
+        ):
+            result = await core.get_library_agent_by_id("user-123", "agent-123")
+
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_alias_works(self):
+        """Test that get_library_agent_by_graph_id is an alias for get_library_agent_by_id."""
+        assert core.get_library_agent_by_graph_id is core.get_library_agent_by_id
+
+
+class TestGetAllRelevantAgentsWithUuids:
+    """Test UUID extraction in get_all_relevant_agents_for_generation."""
+
+    @pytest.mark.asyncio
+    async def test_fetches_explicitly_mentioned_agents(self):
+        """Test that agents mentioned by UUID are fetched directly."""
+        mock_agent = MagicMock()
+        mock_agent.graph_id = "46631191-e8a8-486f-ad90-84f89738321d"
+        mock_agent.graph_version = 1
+        mock_agent.name = "Mentioned Agent"
+        mock_agent.description = "Explicitly mentioned"
+        mock_agent.input_schema = {}
+        mock_agent.output_schema = {}
+
+        mock_response = MagicMock()
+        mock_response.agents = []
+
+        with (
+            patch.object(
+                core.library_db,
+                "get_library_agent_by_graph_id",
+                new_callable=AsyncMock,
+                return_value=mock_agent,
+            ),
+            patch.object(
+                core.library_db,
+                "list_library_agents",
+                new_callable=AsyncMock,
+                return_value=mock_response,
+            ),
+        ):
+            result = await core.get_all_relevant_agents_for_generation(
+                user_id="user-123",
+                search_query="Use agent 46631191-e8a8-486f-ad90-84f89738321d",
+                include_marketplace=False,
+            )
+
+        assert len(result) == 1
+        assert result[0].get("graph_id") == "46631191-e8a8-486f-ad90-84f89738321d"
+        assert result[0].get("name") == "Mentioned Agent"
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])
diff --git a/autogpt_platform/backend/test/agent_generator/test_service.py b/autogpt_platform/backend/test/agent_generator/test_service.py
index fe7a1a7fdd..cc37c428c0 100644
--- a/autogpt_platform/backend/test/agent_generator/test_service.py
+++ b/autogpt_platform/backend/test/agent_generator/test_service.py
@@ -102,7 +102,7 @@ class TestDecomposeGoalExternal:
 
     @pytest.mark.asyncio
     async def test_decompose_goal_with_context(self):
-        """Test decomposition with additional context."""
+        """Test decomposition with additional context enriched into description."""
         mock_response = MagicMock()
         mock_response.json.return_value = {
             "success": True,
@@ -119,9 +119,12 @@ class TestDecomposeGoalExternal:
                 "Build a chatbot", context="Use Python"
             )
 
+        expected_description = (
+            "Build a chatbot\n\nAdditional context from user:\nUse Python"
+        )
         mock_client.post.assert_called_once_with(
             "/api/decompose-description",
-            json={"description": "Build a chatbot", "user_instruction": "Use Python"},
+            json={"description": expected_description},
         )
 
     @pytest.mark.asyncio
@@ -433,5 +436,139 @@ class TestGetBlocksExternal:
         assert result is None
 
 
+class TestLibraryAgentsPassthrough:
+    """Test that library_agents are passed correctly in all requests."""
+
+    def setup_method(self):
+        """Reset client singleton before each test."""
+        service._settings = None
+        service._client = None
+
+    @pytest.mark.asyncio
+    async def test_decompose_goal_passes_library_agents(self):
+        """Test that library_agents are included in decompose goal payload."""
+        library_agents = [
+            {
+                "graph_id": "agent-123",
+                "graph_version": 1,
+                "name": "Email Sender",
+                "description": "Sends emails",
+                "input_schema": {"properties": {"to": {"type": "string"}}},
+                "output_schema": {"properties": {"sent": {"type": "boolean"}}},
+            },
+        ]
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "type": "instructions",
+            "steps": ["Step 1"],
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.decompose_goal_external(
+                "Send an email",
+                library_agents=library_agents,
+            )
+
+        # Verify library_agents was passed in the payload
+        call_args = mock_client.post.call_args
+        assert call_args[1]["json"]["library_agents"] == library_agents
+
+    @pytest.mark.asyncio
+    async def test_generate_agent_passes_library_agents(self):
+        """Test that library_agents are included in generate agent payload."""
+        library_agents = [
+            {
+                "graph_id": "agent-456",
+                "graph_version": 2,
+                "name": "Data Fetcher",
+                "description": "Fetches data from API",
+                "input_schema": {"properties": {"url": {"type": "string"}}},
+                "output_schema": {"properties": {"data": {"type": "object"}}},
+            },
+        ]
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "agent_json": {"name": "Test Agent", "nodes": []},
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.generate_agent_external(
+                {"steps": ["Step 1"]},
+                library_agents=library_agents,
+            )
+
+        # Verify library_agents was passed in the payload
+        call_args = mock_client.post.call_args
+        assert call_args[1]["json"]["library_agents"] == library_agents
+
+    @pytest.mark.asyncio
+    async def test_generate_agent_patch_passes_library_agents(self):
+        """Test that library_agents are included in patch generation payload."""
+        library_agents = [
+            {
+                "graph_id": "agent-789",
+                "graph_version": 1,
+                "name": "Slack Notifier",
+                "description": "Sends Slack messages",
+                "input_schema": {"properties": {"message": {"type": "string"}}},
+                "output_schema": {"properties": {"success": {"type": "boolean"}}},
+            },
+        ]
+
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "agent_json": {"name": "Updated Agent", "nodes": []},
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.generate_agent_patch_external(
+                "Add error handling",
+                {"name": "Original Agent", "nodes": []},
+                library_agents=library_agents,
+            )
+
+        # Verify library_agents was passed in the payload
+        call_args = mock_client.post.call_args
+        assert call_args[1]["json"]["library_agents"] == library_agents
+
+    @pytest.mark.asyncio
+    async def test_decompose_goal_without_library_agents(self):
+        """Test that decompose goal works without library_agents."""
+        mock_response = MagicMock()
+        mock_response.json.return_value = {
+            "success": True,
+            "type": "instructions",
+            "steps": ["Step 1"],
+        }
+        mock_response.raise_for_status = MagicMock()
+
+        mock_client = AsyncMock()
+        mock_client.post.return_value = mock_response
+
+        with patch.object(service, "_get_client", return_value=mock_client):
+            await service.decompose_goal_external("Build a workflow")
+
+        # Verify library_agents was NOT passed when not provided
+        call_args = mock_client.post.call_args
+        assert "library_agents" not in call_args[1]["json"]
+
+
 if __name__ == "__main__":
     pytest.main([__file__, "-v"])
diff --git a/autogpt_platform/backend/test/e2e_test_data.py b/autogpt_platform/backend/test/e2e_test_data.py
index d7576cdad3..7288197a90 100644
--- a/autogpt_platform/backend/test/e2e_test_data.py
+++ b/autogpt_platform/backend/test/e2e_test_data.py
@@ -43,19 +43,24 @@ faker = Faker()
 # Constants for data generation limits (reduced for E2E tests)
 NUM_USERS = 15
 NUM_AGENT_BLOCKS = 30
-MIN_GRAPHS_PER_USER = 15
-MAX_GRAPHS_PER_USER = 15
+MIN_GRAPHS_PER_USER = 25
+MAX_GRAPHS_PER_USER = 25
 MIN_NODES_PER_GRAPH = 3
 MAX_NODES_PER_GRAPH = 6
 MIN_PRESETS_PER_USER = 2
 MAX_PRESETS_PER_USER = 3
-MIN_AGENTS_PER_USER = 15
-MAX_AGENTS_PER_USER = 15
+MIN_AGENTS_PER_USER = 25
+MAX_AGENTS_PER_USER = 25
 MIN_EXECUTIONS_PER_GRAPH = 2
 MAX_EXECUTIONS_PER_GRAPH = 8
 MIN_REVIEWS_PER_VERSION = 2
 MAX_REVIEWS_PER_VERSION = 5
 
+# Guaranteed minimums for marketplace tests (deterministic)
+GUARANTEED_FEATURED_AGENTS = 8
+GUARANTEED_FEATURED_CREATORS = 5
+GUARANTEED_TOP_AGENTS = 10
+
 
 def get_image():
     """Generate a consistent image URL using picsum.photos service."""
@@ -385,7 +390,7 @@ class TestDataCreator:
 
         library_agents = []
         for user in self.users:
-            num_agents = 10  # Create exactly 10 agents per user
+            num_agents = random.randint(MIN_AGENTS_PER_USER, MAX_AGENTS_PER_USER)
 
             # Get available graphs for this user
             user_graphs = [
@@ -507,14 +512,17 @@ class TestDataCreator:
             existing_profiles, min(num_creators, len(existing_profiles))
         )
 
-        # Mark about 50% of creators as featured (more for testing)
-        num_featured = max(2, int(num_creators * 0.5))
+        # Guarantee at least GUARANTEED_FEATURED_CREATORS featured creators
+        num_featured = max(GUARANTEED_FEATURED_CREATORS, int(num_creators * 0.5))
         num_featured = min(
             num_featured, len(selected_profiles)
         )  # Don't exceed available profiles
         featured_profile_ids = set(
             random.sample([p.id for p in selected_profiles], num_featured)
         )
+        print(
+            f"🎯 Creating {num_featured} featured creators (min: {GUARANTEED_FEATURED_CREATORS})"
+        )
 
         for profile in selected_profiles:
             try:
@@ -545,21 +553,25 @@ class TestDataCreator:
         return profiles
 
     async def create_test_store_submissions(self) -> List[Dict[str, Any]]:
-        """Create test store submissions using the API function."""
+        """Create test store submissions using the API function.
+
+        DETERMINISTIC: Guarantees minimum featured agents for E2E tests.
+        """
         print("Creating test store submissions...")
 
         submissions = []
         approved_submissions = []
+        featured_count = 0
+        submission_counter = 0
 
-        # Create a special test submission for test123@gmail.com
+        # Create a special test submission for test123@gmail.com (ALWAYS approved + featured)
         test_user = next(
             (user for user in self.users if user["email"] == "test123@gmail.com"), None
         )
-        if test_user:
-            # Special test data for consistent testing
+        if test_user and self.agent_graphs:
             test_submission_data = {
                 "user_id": test_user["id"],
-                "agent_id": self.agent_graphs[0]["id"],  # Use first available graph
+                "agent_id": self.agent_graphs[0]["id"],
                 "agent_version": 1,
                 "slug": "test-agent-submission",
                 "name": "Test Agent Submission",
@@ -580,37 +592,24 @@ class TestDataCreator:
                 submissions.append(test_submission.model_dump())
                 print("✅ Created special test store submission for test123@gmail.com")
 
-                # Randomly approve, reject, or leave pending the test submission
+                # ALWAYS approve and feature the test submission
                 if test_submission.store_listing_version_id:
-                    random_value = random.random()
-                    if random_value < 0.4:  # 40% chance to approve
-                        approved_submission = await review_store_submission(
-                            store_listing_version_id=test_submission.store_listing_version_id,
-                            is_approved=True,
-                            external_comments="Test submission approved",
-                            internal_comments="Auto-approved test submission",
-                            reviewer_id=test_user["id"],
-                        )
-                        approved_submissions.append(approved_submission.model_dump())
-                        print("✅ Approved test store submission")
+                    approved_submission = await review_store_submission(
+                        store_listing_version_id=test_submission.store_listing_version_id,
+                        is_approved=True,
+                        external_comments="Test submission approved",
+                        internal_comments="Auto-approved test submission",
+                        reviewer_id=test_user["id"],
+                    )
+                    approved_submissions.append(approved_submission.model_dump())
+                    print("✅ Approved test store submission")
 
-                        # Mark approved submission as featured
-                        await prisma.storelistingversion.update(
-                            where={"id": test_submission.store_listing_version_id},
-                            data={"isFeatured": True},
-                        )
-                        print("🌟 Marked test agent as FEATURED")
-                    elif random_value < 0.7:  # 30% chance to reject (40% to 70%)
-                        await review_store_submission(
-                            store_listing_version_id=test_submission.store_listing_version_id,
-                            is_approved=False,
-                            external_comments="Test submission rejected - needs improvements",
-                            internal_comments="Auto-rejected test submission for E2E testing",
-                            reviewer_id=test_user["id"],
-                        )
-                        print("❌ Rejected test store submission")
-                    else:  # 30% chance to leave pending (70% to 100%)
-                        print("⏳ Left test submission pending for review")
+                    await prisma.storelistingversion.update(
+                        where={"id": test_submission.store_listing_version_id},
+                        data={"isFeatured": True},
+                    )
+                    featured_count += 1
+                    print("🌟 Marked test agent as FEATURED")
 
             except Exception as e:
                 print(f"Error creating test store submission: {e}")
@@ -620,7 +619,6 @@ class TestDataCreator:
 
         # Create regular submissions for all users
         for user in self.users:
-            # Get available graphs for this specific user
             user_graphs = [
                 g for g in self.agent_graphs if g.get("userId") == user["id"]
             ]
@@ -631,18 +629,17 @@ class TestDataCreator:
                 )
                 continue
 
-            # Create exactly 4 store submissions per user
             for submission_index in range(4):
                 graph = random.choice(user_graphs)
+                submission_counter += 1
 
                 try:
                     print(
-                        f"Creating store submission for user {user['id']} with graph {graph['id']} (owner: {graph.get('userId')})"
+                        f"Creating store submission for user {user['id']} with graph {graph['id']}"
                     )
 
-                    # Use the API function to create store submission with correct parameters
                     submission = await create_store_submission(
-                        user_id=user["id"],  # Must match graph's userId
+                        user_id=user["id"],
                         agent_id=graph["id"],
                         agent_version=graph.get("version", 1),
                         slug=faker.slug(),
@@ -651,22 +648,24 @@ class TestDataCreator:
                         video_url=get_video_url() if random.random() < 0.3 else None,
                         image_urls=[get_image() for _ in range(3)],
                         description=faker.text(),
-                        categories=[
-                            get_category()
-                        ],  # Single category from predefined list
+                        categories=[get_category()],
                         changes_summary="Initial E2E test submission",
                     )
                     submissions.append(submission.model_dump())
                     print(f"✅ Created store submission: {submission.name}")
 
-                    # Randomly approve, reject, or leave pending the submission
                     if submission.store_listing_version_id:
-                        random_value = random.random()
-                        if random_value < 0.4:  # 40% chance to approve
-                            try:
-                                # Pick a random user as the reviewer (admin)
-                                reviewer_id = random.choice(self.users)["id"]
+                        # DETERMINISTIC: First N submissions are always approved
+                        # First GUARANTEED_FEATURED_AGENTS of those are always featured
+                        should_approve = (
+                            submission_counter <= GUARANTEED_TOP_AGENTS
+                            or random.random() < 0.4
+                        )
+                        should_feature = featured_count < GUARANTEED_FEATURED_AGENTS
 
+                        if should_approve:
+                            try:
+                                reviewer_id = random.choice(self.users)["id"]
                                 approved_submission = await review_store_submission(
                                     store_listing_version_id=submission.store_listing_version_id,
                                     is_approved=True,
@@ -681,16 +680,7 @@ class TestDataCreator:
                                     f"✅ Approved store submission: {submission.name}"
                                 )
 
-                                # Mark some agents as featured during creation (30% chance)
-                                # More likely for creators and first submissions
-                                is_creator = user["id"] in [
-                                    p.get("userId") for p in self.profiles
-                                ]
-                                feature_chance = (
-                                    0.5 if is_creator else 0.2
-                                )  # 50% for creators, 20% for others
-
-                                if random.random() < feature_chance:
+                                if should_feature:
                                     try:
                                         await prisma.storelistingversion.update(
                                             where={
@@ -698,8 +688,25 @@ class TestDataCreator:
                                             },
                                             data={"isFeatured": True},
                                         )
+                                        featured_count += 1
                                         print(
-                                            f"🌟 Marked agent as FEATURED: {submission.name}"
+                                            f"🌟 Marked agent as FEATURED ({featured_count}/{GUARANTEED_FEATURED_AGENTS}): {submission.name}"
+                                        )
+                                    except Exception as e:
+                                        print(
+                                            f"Warning: Could not mark submission as featured: {e}"
+                                        )
+                                elif random.random() < 0.2:
+                                    try:
+                                        await prisma.storelistingversion.update(
+                                            where={
+                                                "id": submission.store_listing_version_id
+                                            },
+                                            data={"isFeatured": True},
+                                        )
+                                        featured_count += 1
+                                        print(
+                                            f"🌟 Marked agent as FEATURED (bonus): {submission.name}"
                                         )
                                     except Exception as e:
                                         print(
@@ -710,11 +717,9 @@ class TestDataCreator:
                                 print(
                                     f"Warning: Could not approve submission {submission.name}: {e}"
                                 )
-                        elif random_value < 0.7:  # 30% chance to reject (40% to 70%)
+                        elif random.random() < 0.5:
                             try:
-                                # Pick a random user as the reviewer (admin)
                                 reviewer_id = random.choice(self.users)["id"]
-
                                 await review_store_submission(
                                     store_listing_version_id=submission.store_listing_version_id,
                                     is_approved=False,
@@ -729,7 +734,7 @@ class TestDataCreator:
                                 print(
                                     f"Warning: Could not reject submission {submission.name}: {e}"
                                 )
-                        else:  # 30% chance to leave pending (70% to 100%)
+                        else:
                             print(
                                 f"⏳ Left submission pending for review: {submission.name}"
                             )
@@ -743,9 +748,13 @@ class TestDataCreator:
                     traceback.print_exc()
                     continue
 
+        print("\n📊 Store Submissions Summary:")
+        print(f"   Created: {len(submissions)}")
+        print(f"   Approved: {len(approved_submissions)}")
         print(
-            f"Created {len(submissions)} store submissions, approved {len(approved_submissions)}"
+            f"   Featured: {featured_count} (guaranteed min: {GUARANTEED_FEATURED_AGENTS})"
         )
+
         self.store_submissions = submissions
         return submissions
 
@@ -825,12 +834,15 @@ class TestDataCreator:
         print(f"✅ Agent blocks available: {len(self.agent_blocks)}")
         print(f"✅ Agent graphs created: {len(self.agent_graphs)}")
         print(f"✅ Library agents created: {len(self.library_agents)}")
-        print(f"✅ Creator profiles updated: {len(self.profiles)} (some featured)")
-        print(
-            f"✅ Store submissions created: {len(self.store_submissions)} (some marked as featured during creation)"
-        )
+        print(f"✅ Creator profiles updated: {len(self.profiles)}")
+        print(f"✅ Store submissions created: {len(self.store_submissions)}")
         print(f"✅ API keys created: {len(self.api_keys)}")
         print(f"✅ Presets created: {len(self.presets)}")
+        print("\n🎯 Deterministic Guarantees:")
+        print(f"   • Featured agents: >= {GUARANTEED_FEATURED_AGENTS}")
+        print(f"   • Featured creators: >= {GUARANTEED_FEATURED_CREATORS}")
+        print(f"   • Top agents (approved): >= {GUARANTEED_TOP_AGENTS}")
+        print(f"   • Library agents per user: >= {MIN_AGENTS_PER_USER}")
         print("\n🚀 Your E2E test database is ready to use!")
 
 
diff --git a/autogpt_platform/frontend/Dockerfile b/autogpt_platform/frontend/Dockerfile
index 2b120af5e1..ab2708f1f9 100644
--- a/autogpt_platform/frontend/Dockerfile
+++ b/autogpt_platform/frontend/Dockerfile
@@ -25,8 +25,12 @@ RUN if [ -f .env.production ]; then \
       cp .env.default .env; \
     fi
 RUN pnpm run generate:api
+# Disable source-map generation in Docker builds to halve webpack memory usage.
+# Source maps are only useful when SENTRY_AUTH_TOKEN is set (Vercel deploys);
+# the Docker image never uploads them, so generating them just wastes RAM.
+ENV NEXT_PUBLIC_SOURCEMAPS="false"
 # In CI, we want NEXT_PUBLIC_PW_TEST=true during build so Next.js inlines it
-RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=4096" pnpm build; else NODE_OPTIONS="--max-old-space-size=4096" pnpm build; fi
+RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=8192" pnpm build; else NODE_OPTIONS="--max-old-space-size=8192" pnpm build; fi
 
 # Prod stage - based on NextJS reference Dockerfile https://github.com/vercel/next.js/blob/64271354533ed16da51be5dce85f0dbd15f17517/examples/with-docker/Dockerfile
 FROM node:21-alpine AS prod
diff --git a/autogpt_platform/frontend/next.config.mjs b/autogpt_platform/frontend/next.config.mjs
index bb4410039d..9bb5983801 100644
--- a/autogpt_platform/frontend/next.config.mjs
+++ b/autogpt_platform/frontend/next.config.mjs
@@ -1,8 +1,12 @@
 import { withSentryConfig } from "@sentry/nextjs";
 
+// Allow Docker builds to skip source-map generation (halves memory usage).
+// Defaults to true so Vercel/local builds are unaffected.
+const enableSourceMaps = process.env.NEXT_PUBLIC_SOURCEMAPS !== "false";
+
 /** @type {import('next').NextConfig} */
 const nextConfig = {
-  productionBrowserSourceMaps: true,
+  productionBrowserSourceMaps: enableSourceMaps,
   // Externalize OpenTelemetry packages to fix Turbopack HMR issues
   serverExternalPackages: [
     "@opentelemetry/instrumentation",
@@ -14,9 +18,37 @@ const nextConfig = {
     serverActions: {
       bodySizeLimit: "256mb",
     },
-    // Increase body size limit for API routes (file uploads) - 256MB to match backend limit
-    proxyClientMaxBodySize: "256mb",
     middlewareClientMaxBodySize: "256mb",
+    // Limit parallel webpack workers to reduce peak memory during builds.
+    cpus: 2,
+  },
+  // Work around cssnano "Invalid array length" bug in Next.js's bundled
+  // cssnano-simple comment parser when processing very large CSS chunks.
+  // CSS is still bundled correctly; gzip handles most of the size savings anyway.
+  webpack: (config, { dev }) => {
+    if (!dev) {
+      // Next.js adds CssMinimizerPlugin internally (after user config), so we
+      // can't filter it from config.plugins. Instead, intercept the webpack
+      // compilation hooks and replace the buggy plugin's tap with a no-op.
+      config.plugins.push({
+        apply(compiler) {
+          compiler.hooks.compilation.tap(
+            "DisableCssMinimizer",
+            (compilation) => {
+              compilation.hooks.processAssets.intercept({
+                register: (tap) => {
+                  if (tap.name === "CssMinimizerPlugin") {
+                    return { ...tap, fn: async () => {} };
+                  }
+                  return tap;
+                },
+              });
+            },
+          );
+        },
+      });
+    }
+    return config;
   },
   images: {
     domains: [
@@ -54,9 +86,16 @@ const nextConfig = {
   transpilePackages: ["geist"],
 };
 
-const isDevelopmentBuild = process.env.NODE_ENV !== "production";
+// Only run the Sentry webpack plugin when we can actually upload source maps
+// (i.e. on Vercel with SENTRY_AUTH_TOKEN set). The Sentry *runtime* SDK
+// (imported in app code) still captures errors without the plugin.
+// Skipping the plugin saves ~1 GB of peak memory during `next build`.
+const skipSentryPlugin =
+  process.env.NODE_ENV !== "production" ||
+  !enableSourceMaps ||
+  !process.env.SENTRY_AUTH_TOKEN;
 
-export default isDevelopmentBuild
+export default skipSentryPlugin
   ? nextConfig
   : withSentryConfig(nextConfig, {
       // For all available options, see:
@@ -96,7 +135,7 @@ export default isDevelopmentBuild
 
       // This helps Sentry with sourcemaps... https://docs.sentry.io/platforms/javascript/guides/nextjs/sourcemaps/
       sourcemaps: {
-        disable: false,
+        disable: !enableSourceMaps,
         assets: [".next/**/*.js", ".next/**/*.js.map"],
         ignore: ["**/node_modules/**"],
         deleteSourcemapsAfterUpload: false, // Source is public anyway :)
diff --git a/autogpt_platform/frontend/package.json b/autogpt_platform/frontend/package.json
index f22a182d20..5988e59c90 100644
--- a/autogpt_platform/frontend/package.json
+++ b/autogpt_platform/frontend/package.json
@@ -7,7 +7,7 @@
   },
   "scripts": {
     "dev": "pnpm run generate:api:force && next dev --turbo",
-    "build": "next build",
+    "build": "cross-env NODE_OPTIONS=--max-old-space-size=16384 next build",
     "start": "next start",
     "start:standalone": "cd .next/standalone && node server.js",
     "lint": "next lint && prettier --check .",
@@ -30,6 +30,7 @@
     "defaults"
   ],
   "dependencies": {
+    "@ai-sdk/react": "3.0.61",
     "@faker-js/faker": "10.0.0",
     "@hookform/resolvers": "5.2.2",
     "@next/third-parties": "15.4.6",
@@ -60,6 +61,10 @@
     "@rjsf/utils": "6.1.2",
     "@rjsf/validator-ajv8": "6.1.2",
     "@sentry/nextjs": "10.27.0",
+    "@streamdown/cjk": "1.0.1",
+    "@streamdown/code": "1.0.1",
+    "@streamdown/math": "1.0.1",
+    "@streamdown/mermaid": "1.0.1",
     "@supabase/ssr": "0.7.0",
     "@supabase/supabase-js": "2.78.0",
     "@tanstack/react-query": "5.90.6",
@@ -68,6 +73,7 @@
     "@vercel/analytics": "1.5.0",
     "@vercel/speed-insights": "1.2.0",
     "@xyflow/react": "12.9.2",
+    "ai": "6.0.59",
     "boring-avatars": "1.11.2",
     "class-variance-authority": "0.7.1",
     "clsx": "2.1.1",
@@ -87,7 +93,6 @@
     "launchdarkly-react-client-sdk": "3.9.0",
     "lodash": "4.17.21",
     "lucide-react": "0.552.0",
-    "moment": "2.30.1",
     "next": "15.4.10",
     "next-themes": "0.4.6",
     "nuqs": "2.7.2",
@@ -102,7 +107,7 @@
     "react-markdown": "9.0.3",
     "react-modal": "3.16.3",
     "react-shepherd": "6.1.9",
-    "react-window": "1.8.11",
+    "react-window": "2.2.0",
     "recharts": "3.3.0",
     "rehype-autolink-headings": "7.1.0",
     "rehype-highlight": "7.0.2",
@@ -112,9 +117,11 @@
     "remark-math": "6.0.0",
     "shepherd.js": "14.5.1",
     "sonner": "2.0.7",
+    "streamdown": "2.1.0",
     "tailwind-merge": "2.6.0",
     "tailwind-scrollbar": "3.1.0",
     "tailwindcss-animate": "1.0.7",
+    "use-stick-to-bottom": "1.1.2",
     "uuid": "11.1.0",
     "vaul": "1.1.2",
     "zod": "3.25.76",
@@ -140,7 +147,7 @@
     "@types/react": "18.3.17",
     "@types/react-dom": "18.3.5",
     "@types/react-modal": "3.16.3",
-    "@types/react-window": "1.8.8",
+    "@types/react-window": "2.0.0",
     "@vitejs/plugin-react": "5.1.2",
     "axe-playwright": "2.2.2",
     "chromatic": "13.3.3",
@@ -172,7 +179,8 @@
   },
   "pnpm": {
     "overrides": {
-      "@opentelemetry/instrumentation": "0.209.0"
+      "@opentelemetry/instrumentation": "0.209.0",
+      "lodash-es": "4.17.23"
     }
   },
   "packageManager": "pnpm@10.20.0+sha512.cf9998222162dd85864d0a8102e7892e7ba4ceadebbf5a31f9c2fce48dfce317a9c53b9f6464d1ef9042cba2e02ae02a9f7c143a2b438cd93c91840f0192b9dd"
diff --git a/autogpt_platform/frontend/pnpm-lock.yaml b/autogpt_platform/frontend/pnpm-lock.yaml
index db891ccf3f..468e2f312d 100644
--- a/autogpt_platform/frontend/pnpm-lock.yaml
+++ b/autogpt_platform/frontend/pnpm-lock.yaml
@@ -6,11 +6,15 @@ settings:
 
 overrides:
   '@opentelemetry/instrumentation': 0.209.0
+  lodash-es: 4.17.23
 
 importers:
 
   .:
     dependencies:
+      '@ai-sdk/react':
+        specifier: 3.0.61
+        version: 3.0.61(react@18.3.1)(zod@3.25.76)
       '@faker-js/faker':
         specifier: 10.0.0
         version: 10.0.0
@@ -101,6 +105,18 @@ importers:
       '@sentry/nextjs':
         specifier: 10.27.0
         version: 10.27.0(@opentelemetry/context-async-hooks@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.2.0(@opentelemetry/api@1.9.0))(next@15.4.10(@babel/core@7.28.5)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)(webpack@5.104.1(esbuild@0.25.12))
+      '@streamdown/cjk':
+        specifier: 1.0.1
+        version: 1.0.1(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(react@18.3.1)(unified@11.0.5)
+      '@streamdown/code':
+        specifier: 1.0.1
+        version: 1.0.1(react@18.3.1)
+      '@streamdown/math':
+        specifier: 1.0.1
+        version: 1.0.1(react@18.3.1)
+      '@streamdown/mermaid':
+        specifier: 1.0.1
+        version: 1.0.1(react@18.3.1)
       '@supabase/ssr':
         specifier: 0.7.0
         version: 0.7.0(@supabase/supabase-js@2.78.0)
@@ -125,6 +141,9 @@ importers:
       '@xyflow/react':
         specifier: 12.9.2
         version: 12.9.2(@types/react@18.3.17)(immer@11.1.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+      ai:
+        specifier: 6.0.59
+        version: 6.0.59(zod@3.25.76)
       boring-avatars:
         specifier: 1.11.2
         version: 1.11.2
@@ -182,9 +201,6 @@ importers:
       lucide-react:
         specifier: 0.552.0
         version: 0.552.0(react@18.3.1)
-      moment:
-        specifier: 2.30.1
-        version: 2.30.1
       next:
         specifier: 15.4.10
         version: 15.4.10(@babel/core@7.28.5)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
@@ -228,8 +244,8 @@ importers:
         specifier: 6.1.9
         version: 6.1.9(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(typescript@5.9.3)
       react-window:
-        specifier: 1.8.11
-        version: 1.8.11(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+        specifier: 2.2.0
+        version: 2.2.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
       recharts:
         specifier: 3.3.0
         version: 3.3.0(@types/react@18.3.17)(react-dom@18.3.1(react@18.3.1))(react-is@18.3.1)(react@18.3.1)(redux@5.0.1)
@@ -257,6 +273,9 @@ importers:
       sonner:
         specifier: 2.0.7
         version: 2.0.7(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+      streamdown:
+        specifier: 2.1.0
+        version: 2.1.0(react@18.3.1)
       tailwind-merge:
         specifier: 2.6.0
         version: 2.6.0
@@ -266,6 +285,9 @@ importers:
       tailwindcss-animate:
         specifier: 1.0.7
         version: 1.0.7(tailwindcss@3.4.17)
+      use-stick-to-bottom:
+        specifier: 1.1.2
+        version: 1.1.2(react@18.3.1)
       uuid:
         specifier: 11.1.0
         version: 11.1.0
@@ -337,8 +359,8 @@ importers:
         specifier: 3.16.3
         version: 3.16.3
       '@types/react-window':
-        specifier: 1.8.8
-        version: 1.8.8
+        specifier: 2.0.0
+        version: 2.0.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
       '@vitejs/plugin-react':
         specifier: 5.1.2
         version: 5.1.2(vite@7.3.1(@types/node@24.10.0)(jiti@2.6.1)(terser@5.44.1)(yaml@2.8.2))
@@ -417,10 +439,35 @@ packages:
   '@adobe/css-tools@4.4.4':
     resolution: {integrity: sha512-Elp+iwUx5rN5+Y8xLt5/GRoG20WGoDCQ/1Fb+1LiGtvwbDavuSk0jhD/eZdckHAuzcDzccnkv+rEjyWfRx18gg==}
 
+  '@ai-sdk/gateway@3.0.27':
+    resolution: {integrity: sha512-Pr+ApS9k6/jcR3kNltJNxo60OdYvnVU4DeRhzVtxUAYTXCHx4qO+qTMG9nNRn+El1acJnNRA//Su47srjXkT/w==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      zod: ^3.25.76 || ^4.1.8
+
+  '@ai-sdk/provider-utils@4.0.10':
+    resolution: {integrity: sha512-VeDAiCH+ZK8Xs4hb9Cw7pHlujWNL52RKe8TExOkrw6Ir1AmfajBZTb9XUdKOZO08RwQElIKA8+Ltm+Gqfo8djQ==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      zod: ^3.25.76 || ^4.1.8
+
+  '@ai-sdk/provider@3.0.5':
+    resolution: {integrity: sha512-2Xmoq6DBJqmSl80U6V9z5jJSJP7ehaJJQMy2iFUqTay06wdCqTnPVBBQbtEL8RCChenL+q5DC5H5WzU3vV3v8w==}
+    engines: {node: '>=18'}
+
+  '@ai-sdk/react@3.0.61':
+    resolution: {integrity: sha512-vCjZBnY2+TawFBXamSKt6elAt9n1MXMfcjSd9DSgT9peCJN27qNGVSXgaGNh/B3cUgeOktFfhB2GVmIqOjvmLQ==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      react: ^18 || ~19.0.1 || ~19.1.2 || ^19.2.1
+
   '@alloc/quick-lru@5.2.0':
     resolution: {integrity: sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==}
     engines: {node: '>=10'}
 
+  '@antfu/install-pkg@1.1.0':
+    resolution: {integrity: sha512-MGQsmw10ZyI+EJo45CdSER4zEb+p31LpDAFp2Z3gkSd1yqVZGi0Ebx++YTEMonJy4oChEMLsxZ64j8FH6sSqtQ==}
+
   '@apidevtools/json-schema-ref-parser@14.0.1':
     resolution: {integrity: sha512-Oc96zvmxx1fqoSEdUmfmvvb59/KDOnUoJ7s2t7bISyAn0XEz57LCCw8k2Y4Pf3mwKaZLMciESALORLgfe2frCw==}
     engines: {node: '>= 16'}
@@ -1032,6 +1079,24 @@ packages:
     resolution: {integrity: sha512-qQ5m48eI/MFLQ5PxQj4PFaprjyCTLI37ElWMmNs0K8Lk3dVeOdNpB3ks8jc7yM5CDmVC73eMVk/trk3fgmrUpA==}
     engines: {node: '>=6.9.0'}
 
+  '@braintree/sanitize-url@7.1.2':
+    resolution: {integrity: sha512-jigsZK+sMF/cuiB7sERuo9V7N9jx+dhmHHnQyDSVdpZwVutaBu7WvNYqMDLSgFgfB30n452TP3vjDAvFC973mA==}
+
+  '@chevrotain/cst-dts-gen@11.0.3':
+    resolution: {integrity: sha512-BvIKpRLeS/8UbfxXxgC33xOumsacaeCKAjAeLyOn7Pcp95HiRbrpl14S+9vaZLolnbssPIUuiUd8IvgkRyt6NQ==}
+
+  '@chevrotain/gast@11.0.3':
+    resolution: {integrity: sha512-+qNfcoNk70PyS/uxmj3li5NiECO+2YKZZQMbmjTqRI3Qchu8Hig/Q9vgkHpI3alNjr7M+a2St5pw5w5F6NL5/Q==}
+
+  '@chevrotain/regexp-to-ast@11.0.3':
+    resolution: {integrity: sha512-1fMHaBZxLFvWI067AVbGJav1eRY7N8DDvYCTwGBiE/ytKBgP8azTdgyrKyWZ9Mfh09eHWb5PgTSO8wi7U824RA==}
+
+  '@chevrotain/types@11.0.3':
+    resolution: {integrity: sha512-gsiM3G8b58kZC2HaWR50gu6Y1440cHiJ+i3JUvcp/35JchYejb2+5MVeJK0iKThYpAa/P2PYFV4hoi44HD+aHQ==}
+
+  '@chevrotain/utils@11.0.3':
+    resolution: {integrity: sha512-YslZMgtJUyuMbZ+aKvfF3x1f5liK4mWNxghFRv7jqRR9C3R3fAOGTTKvxXDa2Y1s9zSbcpuO0cAxDYsc9SrXoQ==}
+
   '@chromatic-com/storybook@4.1.2':
     resolution: {integrity: sha512-QAWGtHwib0qsP5CcO64aJCF75zpFgpKK3jNpxILzQiPK3sVo4EmnVGJVdwcZWpWrGdH8E4YkncGoitw4EXzKMg==}
     engines: {node: '>=20.0.0', yarn: '>=1.22.18'}
@@ -1486,6 +1551,12 @@ packages:
     resolution: {integrity: sha512-oT8USsTulFAA8FiBN0lA2rJqQI2lIt+HP2pdakGQXo3EviL2vqJTgpSCRwjl6mLJL158f1BVcdQUOEFGxomK3w==}
     engines: {node: '>=16.0.0'}
 
+  '@iconify/types@2.0.0':
+    resolution: {integrity: sha512-+wluvCrRhXrhyOmRDJ3q8mux9JkKy5SJ/v8ol2tu4FVjyYvtEzkc/3pK15ET6RKg4b4w4BmTk1+gsCUhf21Ykg==}
+
+  '@iconify/utils@3.1.0':
+    resolution: {integrity: sha512-Zlzem1ZXhI1iHeeERabLNzBHdOa4VhQbqAcOQaMKuTuyZCpwKbC2R4Dd0Zo3g9EAc+Y4fiarO8HIHRAth7+skw==}
+
   '@img/colour@1.0.0':
     resolution: {integrity: sha512-A5P/LfWGFSl6nsckYtjw9da+19jB8hkJ6ACTGcDfEJ0aE+l2n2El7dsVM7UVHZQ9s2lmYMWlrS21YLy2IR1LUw==}
     engines: {node: '>=18'}
@@ -1705,6 +1776,9 @@ packages:
       '@types/react': '>=16'
       react: '>=16'
 
+  '@mermaid-js/parser@0.6.3':
+    resolution: {integrity: sha512-lnjOhe7zyHjc+If7yT4zoedx2vo4sHaTmtkl1+or8BRTnCtDmcTpAjpzDSfCZrshM5bCoz0GyidzadJAH1xobA==}
+
   '@mswjs/interceptors@0.40.0':
     resolution: {integrity: sha512-EFd6cVbHsgLa6wa4RljGj6Wk75qoHxUSyc5asLyyPSyuhIcdS2Q3Phw6ImS1q+CkALthJRShiYfKANcQMuMqsQ==}
     engines: {node: '>=18'}
@@ -3019,6 +3093,12 @@ packages:
     peerDependencies:
       webpack: '>=4.40.0'
 
+  '@shikijs/core@3.21.0':
+    resolution: {integrity: sha512-AXSQu/2n1UIQekY8euBJlvFYZIw0PHY63jUzGbrOma4wPxzznJXTXkri+QcHeBNaFxiiOljKxxJkVSoB3PjbyA==}
+
+  '@shikijs/engine-javascript@3.21.0':
+    resolution: {integrity: sha512-ATwv86xlbmfD9n9gKRiwuPpWgPENAWCLwYCGz9ugTJlsO2kOzhOkvoyV/UD+tJ0uT7YRyD530x6ugNSffmvIiQ==}
+
   '@shikijs/engine-oniguruma@3.21.0':
     resolution: {integrity: sha512-OYknTCct6qiwpQDqDdf3iedRdzj6hFlOPv5hMvI+hkWfCKs5mlJ4TXziBG9nyabLwGulrUjHiCq3xCspSzErYQ==}
 
@@ -3222,6 +3302,26 @@ packages:
       typescript:
         optional: true
 
+  '@streamdown/cjk@1.0.1':
+    resolution: {integrity: sha512-ElDoEfad2u8iFzmgmEEab15N4mt19r47xeUIPJtHaHVyEF5baojamGo+xw3MywMj2qUsAY3LnTnKbrUtL5tGkg==}
+    peerDependencies:
+      react: ^18.0.0 || ^19.0.0
+
+  '@streamdown/code@1.0.1':
+    resolution: {integrity: sha512-U9LITfQ28tZYAoY922jdtw1ryg4kgRBdURopqK9hph7G2fBUwPeHthjH7SvaV0fvFv7EqjqCzARJuWUljLe9Ag==}
+    peerDependencies:
+      react: ^18.0.0 || ^19.0.0
+
+  '@streamdown/math@1.0.1':
+    resolution: {integrity: sha512-R9WdHbpERiRU7WeO7oT1aIbnLJ/jraDr89F7X9x2OM//Y8G8UMATRnLD/RUwg4VLr8Nu7QSIJ0Pa8lXd2meM4Q==}
+    peerDependencies:
+      react: ^18.0.0 || ^19.0.0
+
+  '@streamdown/mermaid@1.0.1':
+    resolution: {integrity: sha512-LVGbxYd6t1DKMCMqm3cpbfsdD4/EKpQelanOlJaBMKv83kbrl8syZJhVBsd/jka+CawhpeR9xsGQJzSJEpjoVw==}
+    peerDependencies:
+      react: ^18.0.0 || ^19.0.0
+
   '@supabase/auth-js@2.78.0':
     resolution: {integrity: sha512-cXDtu1U0LeZj/xfnFoV7yCze37TcbNo8FCxy1FpqhMbB9u9QxxDSW6pA5gm/07Ei7m260Lof4CZx67Cu6DPeig==}
 
@@ -3344,21 +3444,69 @@ packages:
   '@types/d3-array@3.2.2':
     resolution: {integrity: sha512-hOLWVbm7uRza0BYXpIIW5pxfrKe0W+D5lrFiAEYR+pb6w3N2SwSMaJbXdUfSEv+dT4MfHBLtn5js0LAWaO6otw==}
 
+  '@types/d3-axis@3.0.6':
+    resolution: {integrity: sha512-pYeijfZuBd87T0hGn0FO1vQ/cgLk6E1ALJjfkC0oJ8cbwkZl3TpgS8bVBLZN+2jjGgg38epgxb2zmoGtSfvgMw==}
+
+  '@types/d3-brush@3.0.6':
+    resolution: {integrity: sha512-nH60IZNNxEcrh6L1ZSMNA28rj27ut/2ZmI3r96Zd+1jrZD++zD3LsMIjWlvg4AYrHn/Pqz4CF3veCxGjtbqt7A==}
+
+  '@types/d3-chord@3.0.6':
+    resolution: {integrity: sha512-LFYWWd8nwfwEmTZG9PfQxd17HbNPksHBiJHaKuY1XeqscXacsS2tyoo6OdRsjf+NQYeB6XrNL3a25E3gH69lcg==}
+
   '@types/d3-color@3.1.3':
     resolution: {integrity: sha512-iO90scth9WAbmgv7ogoq57O9YpKmFBbmoEoCHDB2xMBY0+/KVrqAaCDyCE16dUspeOvIxFFRI+0sEtqDqy2b4A==}
 
+  '@types/d3-contour@3.0.6':
+    resolution: {integrity: sha512-BjzLgXGnCWjUSYGfH1cpdo41/hgdWETu4YxpezoztawmqsvCeep+8QGfiY6YbDvfgHz/DkjeIkkZVJavB4a3rg==}
+
+  '@types/d3-delaunay@6.0.4':
+    resolution: {integrity: sha512-ZMaSKu4THYCU6sV64Lhg6qjf1orxBthaC161plr5KuPHo3CNm8DTHiLw/5Eq2b6TsNP0W0iJrUOFscY6Q450Hw==}
+
+  '@types/d3-dispatch@3.0.7':
+    resolution: {integrity: sha512-5o9OIAdKkhN1QItV2oqaE5KMIiXAvDWBDPrD85e58Qlz1c1kI/J0NcqbEG88CoTwJrYe7ntUCVfeUl2UJKbWgA==}
+
   '@types/d3-drag@3.0.7':
     resolution: {integrity: sha512-HE3jVKlzU9AaMazNufooRJ5ZpWmLIoc90A37WU2JMmeq28w1FQqCZswHZ3xR+SuxYftzHq6WU6KJHvqxKzTxxQ==}
 
+  '@types/d3-dsv@3.0.7':
+    resolution: {integrity: sha512-n6QBF9/+XASqcKK6waudgL0pf/S5XHPPI8APyMLLUHd8NqouBGLsU8MgtO7NINGtPBtk9Kko/W4ea0oAspwh9g==}
+
   '@types/d3-ease@3.0.2':
     resolution: {integrity: sha512-NcV1JjO5oDzoK26oMzbILE6HW7uVXOHLQvHshBUW4UMdZGfiY6v5BeQwh9a9tCzv+CeefZQHJt5SRgK154RtiA==}
 
+  '@types/d3-fetch@3.0.7':
+    resolution: {integrity: sha512-fTAfNmxSb9SOWNB9IoG5c8Hg6R+AzUHDRlsXsDZsNp6sxAEOP0tkP3gKkNSO/qmHPoBFTxNrjDprVHDQDvo5aA==}
+
+  '@types/d3-force@3.0.10':
+    resolution: {integrity: sha512-ZYeSaCF3p73RdOKcjj+swRlZfnYpK1EbaDiYICEEp5Q6sUiqFaFQ9qgoshp5CzIyyb/yD09kD9o2zEltCexlgw==}
+
+  '@types/d3-format@3.0.4':
+    resolution: {integrity: sha512-fALi2aI6shfg7vM5KiR1wNJnZ7r6UuggVqtDA+xiEdPZQwy/trcQaHnwShLuLdta2rTymCNpxYTiMZX/e09F4g==}
+
+  '@types/d3-geo@3.1.0':
+    resolution: {integrity: sha512-856sckF0oP/diXtS4jNsiQw/UuK5fQG8l/a9VVLeSouf1/PPbBE1i1W852zVwKwYCBkFJJB7nCFTbk6UMEXBOQ==}
+
+  '@types/d3-hierarchy@3.1.7':
+    resolution: {integrity: sha512-tJFtNoYBtRtkNysX1Xq4sxtjK8YgoWUNpIiUee0/jHGRwqvzYxkq0hGVbbOGSz+JgFxxRu4K8nb3YpG3CMARtg==}
+
   '@types/d3-interpolate@3.0.4':
     resolution: {integrity: sha512-mgLPETlrpVV1YRJIglr4Ez47g7Yxjl1lj7YKsiMCb27VJH9W8NVM6Bb9d8kkpG/uAQS5AmbA48q2IAolKKo1MA==}
 
   '@types/d3-path@3.1.1':
     resolution: {integrity: sha512-VMZBYyQvbGmWyWVea0EHs/BwLgxc+MKi1zLDCONksozI4YJMcTt8ZEuIR4Sb1MMTE8MMW49v0IwI5+b7RmfWlg==}
 
+  '@types/d3-polygon@3.0.2':
+    resolution: {integrity: sha512-ZuWOtMaHCkN9xoeEMr1ubW2nGWsp4nIql+OPQRstu4ypeZ+zk3YKqQT0CXVe/PYqrKpZAi+J9mTs05TKwjXSRA==}
+
+  '@types/d3-quadtree@3.0.6':
+    resolution: {integrity: sha512-oUzyO1/Zm6rsxKRHA1vH0NEDG58HrT5icx/azi9MF1TWdtttWl0UIUsjEQBBh+SIkrpd21ZjEv7ptxWys1ncsg==}
+
+  '@types/d3-random@3.0.3':
+    resolution: {integrity: sha512-Imagg1vJ3y76Y2ea0871wpabqp613+8/r0mCLEBfdtqC7xMSfj9idOnmBYyMoULfHePJyxMAw3nWhJxzc+LFwQ==}
+
+  '@types/d3-scale-chromatic@3.1.0':
+    resolution: {integrity: sha512-iWMJgwkK7yTRmWqRB5plb1kadXyQ5Sj8V/zYlFGMUBbIPKQScw+Dku9cAAMgJG+z5GYDoMjWGLVOvjghDEFnKQ==}
+
   '@types/d3-scale@4.0.9':
     resolution: {integrity: sha512-dLmtwB8zkAeO/juAMfnV+sItKjlsw2lKdZVVy6LRr0cBmegxSABiLEpGVmSJJ8O08i4+sGR6qQtb6WtuwJdvVw==}
 
@@ -3368,6 +3516,9 @@ packages:
   '@types/d3-shape@3.1.7':
     resolution: {integrity: sha512-VLvUQ33C+3J+8p+Daf+nYSOsjB4GXp19/S/aGo60m9h1v6XaxjiT82lKVWJCfzhtuZ3yD7i/TPeC/fuKLLOSmg==}
 
+  '@types/d3-time-format@4.0.3':
+    resolution: {integrity: sha512-5xg9rC+wWL8kdDj153qZcsJ0FWiFt0J5RB6LYUNZjwSnesfblqrI/bJ1wBdJ8OQfncgbJG5+2F+qfqnqyzYxyg==}
+
   '@types/d3-time@3.0.4':
     resolution: {integrity: sha512-yuzZug1nkAAaBlBBikKZTgzCeA+k1uy4ZFwWANOfKw5z5LRhV0gNA7gNkKm7HoK+HRN0wX3EkxGk0fpbWhmB7g==}
 
@@ -3380,6 +3531,9 @@ packages:
   '@types/d3-zoom@3.0.8':
     resolution: {integrity: sha512-iqMC4/YlFCSlO8+2Ii1GGGliCAY4XdeG748w5vQUbevlbDu0zSjH/+jojorQVBK/se0j6DUFNPBGSqD3YWYnDw==}
 
+  '@types/d3@7.4.3':
+    resolution: {integrity: sha512-lZXZ9ckh5R8uiFVt8ogUNf+pIrK4EsWrx2Np75WvF/eTpJ0FMHNhjXk8CKEx/+gpHbNQyJWehbFaTvqmHWB3ww==}
+
   '@types/debug@4.1.12':
     resolution: {integrity: sha512-vIChWdVG3LG1SMxEvI/AK+FWJthlrqlTu7fbrlywTkkaONwk/UAGaULXRlf8vkzFBLVm0zkMdCquhL5aOjhXPQ==}
 
@@ -3404,6 +3558,9 @@ packages:
   '@types/estree@1.0.8':
     resolution: {integrity: sha512-dWHzHa2WqEXI/O1E9OjrocMTKJl2mSrEolh1Iomrv6U+JuNwaHXsXx9bLu5gG7BUWFIN0skIQJQ/L1rIex4X6w==}
 
+  '@types/geojson@7946.0.16':
+    resolution: {integrity: sha512-6C8nqWur3j98U6+lXDfTUWIfgvZU+EumvpHKcYjujKH7woYyLj2sUmff0tRhrqM7BohUw7Pz3ZB1jj2gW9Fvmg==}
+
   '@types/hast@3.0.4':
     resolution: {integrity: sha512-WPs+bbQw5aCj+x6laNGWLH3wviHtoCv/P3+otBhbOhJgG8qtpdAMlTCxLtsTWA7LH1Oh/bFCHsBn0TPS5m30EQ==}
 
@@ -3469,8 +3626,9 @@ packages:
   '@types/react-modal@3.16.3':
     resolution: {integrity: sha512-xXuGavyEGaFQDgBv4UVm8/ZsG+qxeQ7f77yNrW3n+1J6XAstUy5rYHeIHPh1KzsGc6IkCIdu6lQ2xWzu1jBTLg==}
 
-  '@types/react-window@1.8.8':
-    resolution: {integrity: sha512-8Ls660bHR1AUA2kuRvVG9D/4XpRC6wjAaPT9dil7Ckc76eP9TKWZwwmgfq8Q1LANX3QNDnoU4Zp48A3w+zK69Q==}
+  '@types/react-window@2.0.0':
+    resolution: {integrity: sha512-E8hMDtImEpMk1SjswSvqoSmYvk7GEtyVaTa/GJV++FdDNuMVVEzpAClyJ0nqeKYBrMkGiyH6M1+rPLM0Nu1exQ==}
+    deprecated: This is a stub types definition. react-window provides its own type definitions, so you do not need this installed.
 
   '@types/react@18.3.17':
     resolution: {integrity: sha512-opAQ5no6LqJNo9TqnxBKsgnkIYHozW9KSTlFVoSUJYh1Fl/sswkEoqIugRSm7tbh6pABtYjGAjW+GOS23j8qbw==}
@@ -3691,6 +3849,10 @@ packages:
       vue-router:
         optional: true
 
+  '@vercel/oidc@3.1.0':
+    resolution: {integrity: sha512-Fw28YZpRnA3cAHHDlkt7xQHiJ0fcL+NRcIqsocZQUSmbzeIKRpwttJjik5ZGanXP+vlA4SbTg+AbA3bP363l+w==}
+    engines: {node: '>= 20'}
+
   '@vercel/speed-insights@1.2.0':
     resolution: {integrity: sha512-y9GVzrUJ2xmgtQlzFP2KhVRoCglwfRQgjyfY607aU0hh0Un6d0OUyrJkjuAlsV18qR4zfoFPs/BiIj9YDS6Wzw==}
     peerDependencies:
@@ -3872,6 +4034,12 @@ packages:
     resolution: {integrity: sha512-MnA+YT8fwfJPgBx3m60MNqakm30XOkyIoH1y6huTQvC0PwZG7ki8NacLBcrPbNoo8vEZy7Jpuk7+jMO+CUovTQ==}
     engines: {node: '>= 14'}
 
+  ai@6.0.59:
+    resolution: {integrity: sha512-9SfCvcr4kVk4t8ZzIuyHpuL1hFYKsYMQfBSbBq3dipXPa+MphARvI8wHEjNaRqYl3JOsJbWxEBIMqHL0L92mUA==}
+    engines: {node: '>=18'}
+    peerDependencies:
+      zod: ^3.25.76 || ^4.1.8
+
   ajv-draft-04@1.0.0:
     resolution: {integrity: sha512-mv00Te6nmYbRp5DCwclxtt7yV/joXJPGS7nM+97GdxvuttCOfgI3K4U25zboyeX0O+myI8ERluxQe5wljMmVIw==}
     peerDependencies:
@@ -4226,6 +4394,14 @@ packages:
     resolution: {integrity: sha512-PAJdDJusoxnwm1VwW07VWwUN1sl7smmC3OKggvndJFadxxDRyFJBX/ggnu/KE4kQAB7a3Dp8f/YXC1FlUprWmA==}
     engines: {node: '>= 16'}
 
+  chevrotain-allstar@0.3.1:
+    resolution: {integrity: sha512-b7g+y9A0v4mxCW1qUhf3BSVPg+/NvGErk/dOkrDaHA0nQIQGAtrOjlX//9OQtRlSCy+x9rfB5N8yC71lH1nvMw==}
+    peerDependencies:
+      chevrotain: ^11.0.0
+
+  chevrotain@11.0.3:
+    resolution: {integrity: sha512-ci2iJH6LeIkvP9eJW6gpueU8cnZhv85ELY8w8WiFtNjMHA5ad6pQLaJo9mEly/9qUyCpvqX8/POVUTf18/HFdw==}
+
   chokidar@3.6.0:
     resolution: {integrity: sha512-7VT13fmjotKpGipCW9JEQAusEPE+Ei8nl6/g4FBAmIm0GOOLMua9NDDo/DWp0ZAxCr3cPq5ZpBqmPAQgDda2Pw==}
     engines: {node: '>= 8.10.0'}
@@ -4324,6 +4500,10 @@ packages:
     resolution: {integrity: sha512-NOKm8xhkzAjzFx8B2v5OAHT+u5pRQc2UCa2Vq9jYL/31o2wi9mxBA7LIFs3sV5VSC49z6pEhfbMULvShKj26WA==}
     engines: {node: '>= 6'}
 
+  commander@7.2.0:
+    resolution: {integrity: sha512-QrWXB+ZQSVPmIWIhtEO9H+gwHaMGYiF5ChvoJ+K9ZGHG/sVsa6yiesAD1GC/x46sET00Xlwo1u49RVVVzvcSkw==}
+    engines: {node: '>= 10'}
+
   commander@8.3.0:
     resolution: {integrity: sha512-OkTL9umf+He2DZkUq8f8J9of7yL6RJKI24dVITBmNfZBmri9zYZQrKkuXiKhyfPSu8tUhnVBB1iKXevvnlR4Ww==}
     engines: {node: '>= 12'}
@@ -4345,6 +4525,9 @@ packages:
     engines: {node: '>=18'}
     hasBin: true
 
+  confbox@0.1.8:
+    resolution: {integrity: sha512-RMtmw0iFkeR4YV+fUOSucriAQNb9g8zFR52MWCtl+cCZOFRNL6zeB395vPzFhEjjn4fMxXudmELnl/KF/WrK6w==}
+
   console-browserify@1.2.0:
     resolution: {integrity: sha512-ZMkYO/LkF17QvCPqM0gxw8yUzigAOZOSWSHg91FH6orS7vcEj5dVZTidN2fQ14yBSdg97RqhSNwLUXInd52OTA==}
 
@@ -4373,6 +4556,12 @@ packages:
   core-util-is@1.0.3:
     resolution: {integrity: sha512-ZQBvi1DcpJ4GDqanjucZ2Hj3wEO5pZDS89BWbkcrvdxksJorwUDDZamX9ldFkp9aw2lmBDLgkObEA4DWNJ9FYQ==}
 
+  cose-base@1.0.3:
+    resolution: {integrity: sha512-s9whTXInMSgAp/NVXVNuVxVKzGH2qck3aQlVHxDCdAEPgtMKwc4Wq6/QKhgdEdgbLSi9rBTAcPoRa6JpiG4ksg==}
+
+  cose-base@2.2.0:
+    resolution: {integrity: sha512-AzlgcsCbUMymkADOJtQm3wO9S3ltPfYOFD5033keQn9NJzIbtnZj+UdBJe7DYml/8TdbtHJW3j58SOnKhWY/5g==}
+
   cosmiconfig@7.1.0:
     resolution: {integrity: sha512-AdmX6xUzdNASswsFtmwSt7Vj8po9IuqXm0UXz7QKPuEUmPB4XyjGfaAr2PSuELMwkRMVH1EpIkX5bTZGRB3eCA==}
     engines: {node: '>=10'}
@@ -4446,14 +4635,51 @@ packages:
   csstype@3.2.3:
     resolution: {integrity: sha512-z1HGKcYy2xA8AGQfwrn0PAy+PB7X/GSj3UVJW9qKyn43xWa+gl5nXmU4qqLMRzWVLFC8KusUX8T/0kCiOYpAIQ==}
 
+  cytoscape-cose-bilkent@4.1.0:
+    resolution: {integrity: sha512-wgQlVIUJF13Quxiv5e1gstZ08rnZj2XaLHGoFMYXz7SkNfCDOOteKBE6SYRfA9WxxI/iBc3ajfDoc6hb/MRAHQ==}
+    peerDependencies:
+      cytoscape: ^3.2.0
+
+  cytoscape-fcose@2.2.0:
+    resolution: {integrity: sha512-ki1/VuRIHFCzxWNrsshHYPs6L7TvLu3DL+TyIGEsRcvVERmxokbf5Gdk7mFxZnTdiGtnA4cfSmjZJMviqSuZrQ==}
+    peerDependencies:
+      cytoscape: ^3.2.0
+
+  cytoscape@3.33.1:
+    resolution: {integrity: sha512-iJc4TwyANnOGR1OmWhsS9ayRS3s+XQ185FmuHObThD+5AeJCakAAbWv8KimMTt08xCCLNgneQwFp+JRJOr9qGQ==}
+    engines: {node: '>=0.10'}
+
+  d3-array@2.12.1:
+    resolution: {integrity: sha512-B0ErZK/66mHtEsR1TkPEEkwdy+WDesimkM5gpZr5Dsg54BiTA5RXtYW5qTLIAcekaS9xfZrzBLF/OAkB3Qn1YQ==}
+
   d3-array@3.2.4:
     resolution: {integrity: sha512-tdQAmyA18i4J7wprpYq8ClcxZy3SC31QMeByyCFyRt7BVHdREQZ5lpzoe5mFEYZUWe+oq8HBvk9JjpibyEV4Jg==}
     engines: {node: '>=12'}
 
+  d3-axis@3.0.0:
+    resolution: {integrity: sha512-IH5tgjV4jE/GhHkRV0HiVYPDtvfjHQlQfJHs0usq7M30XcSBvOotpmH1IgkcXsO/5gEQZD43B//fc7SRT5S+xw==}
+    engines: {node: '>=12'}
+
+  d3-brush@3.0.0:
+    resolution: {integrity: sha512-ALnjWlVYkXsVIGlOsuWH1+3udkYFI48Ljihfnh8FZPF2QS9o+PzGLBslO0PjzVoHLZ2KCVgAM8NVkXPJB2aNnQ==}
+    engines: {node: '>=12'}
+
+  d3-chord@3.0.1:
+    resolution: {integrity: sha512-VE5S6TNa+j8msksl7HwjxMHDM2yNK3XCkusIlpX5kwauBfXuyLAtNg9jCp/iHH61tgI4sb6R/EIMWCqEIdjT/g==}
+    engines: {node: '>=12'}
+
   d3-color@3.1.0:
     resolution: {integrity: sha512-zg/chbXyeBtMQ1LbD/WSoW2DpC3I0mpmPdW+ynRTj/x2DAWYrIY7qeZIHidozwV24m4iavr15lNwIwLxRmOxhA==}
     engines: {node: '>=12'}
 
+  d3-contour@4.0.2:
+    resolution: {integrity: sha512-4EzFTRIikzs47RGmdxbeUvLWtGedDUNkTcmzoeyg4sP/dvCexO47AaQL7VKy/gul85TOxw+IBgA8US2xwbToNA==}
+    engines: {node: '>=12'}
+
+  d3-delaunay@6.0.4:
+    resolution: {integrity: sha512-mdjtIZ1XLAM8bm/hx3WwjfHt6Sggek7qH043O8KEjDXN40xi3vx/6pYSVTwLjEgiXQTbvaouWKynLBiUZ6SK6A==}
+    engines: {node: '>=12'}
+
   d3-dispatch@3.0.1:
     resolution: {integrity: sha512-rzUyPU/S7rwUflMyLc1ETDeBj0NRuHKKAcvukozwhshr6g6c5d8zh4c2gQjY2bZ0dXeGLWc1PF174P2tVvKhfg==}
     engines: {node: '>=12'}
@@ -4462,22 +4688,65 @@ packages:
     resolution: {integrity: sha512-pWbUJLdETVA8lQNJecMxoXfH6x+mO2UQo8rSmZ+QqxcbyA3hfeprFgIT//HW2nlHChWeIIMwS2Fq+gEARkhTkg==}
     engines: {node: '>=12'}
 
+  d3-dsv@3.0.1:
+    resolution: {integrity: sha512-UG6OvdI5afDIFP9w4G0mNq50dSOsXHJaRE8arAS5o9ApWnIElp8GZw1Dun8vP8OyHOZ/QJUKUJwxiiCCnUwm+Q==}
+    engines: {node: '>=12'}
+    hasBin: true
+
   d3-ease@3.0.1:
     resolution: {integrity: sha512-wR/XK3D3XcLIZwpbvQwQ5fK+8Ykds1ip7A2Txe0yxncXSdq1L9skcG7blcedkOX+ZcgxGAmLX1FrRGbADwzi0w==}
     engines: {node: '>=12'}
 
+  d3-fetch@3.0.1:
+    resolution: {integrity: sha512-kpkQIM20n3oLVBKGg6oHrUchHM3xODkTzjMoj7aWQFq5QEM+R6E4WkzT5+tojDY7yjez8KgCBRoj4aEr99Fdqw==}
+    engines: {node: '>=12'}
+
+  d3-force@3.0.0:
+    resolution: {integrity: sha512-zxV/SsA+U4yte8051P4ECydjD/S+qeYtnaIyAs9tgHCqfguma/aAQDjo85A9Z6EKhBirHRJHXIgJUlffT4wdLg==}
+    engines: {node: '>=12'}
+
   d3-format@3.1.0:
     resolution: {integrity: sha512-YyUI6AEuY/Wpt8KWLgZHsIU86atmikuoOmCfommt0LYHiQSPjvX2AcFc38PX0CBpr2RCyZhjex+NS/LPOv6YqA==}
     engines: {node: '>=12'}
 
+  d3-geo@3.1.1:
+    resolution: {integrity: sha512-637ln3gXKXOwhalDzinUgY83KzNWZRKbYubaG+fGVuc/dxO64RRljtCTnf5ecMyE1RIdtqpkVcq0IbtU2S8j2Q==}
+    engines: {node: '>=12'}
+
+  d3-hierarchy@3.1.2:
+    resolution: {integrity: sha512-FX/9frcub54beBdugHjDCdikxThEqjnR93Qt7PvQTOHxyiNCAlvMrHhclk3cD5VeAaq9fxmfRp+CnWw9rEMBuA==}
+    engines: {node: '>=12'}
+
   d3-interpolate@3.0.1:
     resolution: {integrity: sha512-3bYs1rOD33uo8aqJfKP3JWPAibgw8Zm2+L9vBKEHJ2Rg+viTR7o5Mmv5mZcieN+FRYaAOWX5SJATX6k1PWz72g==}
     engines: {node: '>=12'}
 
+  d3-path@1.0.9:
+    resolution: {integrity: sha512-VLaYcn81dtHVTjEHd8B+pbe9yHWpXKZUC87PzoFmsFrJqgFwDe/qxfp5MlfsfM1V5E/iVt0MmEbWQ7FVIXh/bg==}
+
   d3-path@3.1.0:
     resolution: {integrity: sha512-p3KP5HCf/bvjBSSKuXid6Zqijx7wIfNW+J/maPs+iwR35at5JCbLUT0LzF1cnjbCHWhqzQTIN2Jpe8pRebIEFQ==}
     engines: {node: '>=12'}
 
+  d3-polygon@3.0.1:
+    resolution: {integrity: sha512-3vbA7vXYwfe1SYhED++fPUQlWSYTTGmFmQiany/gdbiWgU/iEyQzyymwL9SkJjFFuCS4902BSzewVGsHHmHtXg==}
+    engines: {node: '>=12'}
+
+  d3-quadtree@3.0.1:
+    resolution: {integrity: sha512-04xDrxQTDTCFwP5H6hRhsRcb9xxv2RzkcsygFzmkSIOJy3PeRJP7sNk3VRIbKXcog561P9oU0/rVH6vDROAgUw==}
+    engines: {node: '>=12'}
+
+  d3-random@3.0.1:
+    resolution: {integrity: sha512-FXMe9GfxTxqd5D6jFsQ+DJ8BJS4E/fT5mqqdjovykEB2oFbTMDVdg1MGFxfQW+FBOGoB++k8swBrgwSHT1cUXQ==}
+    engines: {node: '>=12'}
+
+  d3-sankey@0.12.3:
+    resolution: {integrity: sha512-nQhsBRmM19Ax5xEIPLMY9ZmJ/cDvd1BG3UVvt5h3WRxKg5zGRbvnteTyWAbzeSvlh3tW7ZEmq4VwR5mB3tutmQ==}
+
+  d3-scale-chromatic@3.1.0:
+    resolution: {integrity: sha512-A3s5PWiZ9YCXFye1o246KoscMWqf8BsD9eRiJ3He7C9OBaxKhAd5TFCdEx/7VbKtxxTsu//1mMJFrEt572cEyQ==}
+    engines: {node: '>=12'}
+
   d3-scale@4.0.2:
     resolution: {integrity: sha512-GZW464g1SH7ag3Y7hXjf8RoUuAFIqklOAq3MRl4OaWabTFJY9PN/E1YklhXLh+OQ3fM9yS2nOkCoS+WLZ6kvxQ==}
     engines: {node: '>=12'}
@@ -4486,6 +4755,9 @@ packages:
     resolution: {integrity: sha512-fmTRWbNMmsmWq6xJV8D19U/gw/bwrHfNXxrIN+HfZgnzqTHp9jOmKMhsTUjXOJnZOdZY9Q28y4yebKzqDKlxlQ==}
     engines: {node: '>=12'}
 
+  d3-shape@1.3.7:
+    resolution: {integrity: sha512-EUkvKjqPFUAZyOlhY5gzCxCeI0Aep04LwIRpsZ/mLFelJiUfnK56jo5JMDSE7yyP2kLSb6LtF+S5chMk7uqPqw==}
+
   d3-shape@3.2.0:
     resolution: {integrity: sha512-SaLBuwGm3MOViRq2ABk3eLoxwZELpH6zhl3FbAoJ7Vm1gofKx6El1Ib5z23NUEhF9AsGl7y+dzLe5Cw2AArGTA==}
     engines: {node: '>=12'}
@@ -4512,6 +4784,13 @@ packages:
     resolution: {integrity: sha512-b8AmV3kfQaqWAuacbPuNbL6vahnOJflOhexLzMMNLga62+/nh0JzvJ0aO/5a5MVgUFGS7Hu1P9P03o3fJkDCyw==}
     engines: {node: '>=12'}
 
+  d3@7.9.0:
+    resolution: {integrity: sha512-e1U46jVP+w7Iut8Jt8ri1YsPOvFpg46k+K8TpCb0P+zjCkjkPnV7WzfDJzMHy1LnA+wj5pLT1wjO901gLXeEhA==}
+    engines: {node: '>=12'}
+
+  dagre-d3-es@7.0.13:
+    resolution: {integrity: sha512-efEhnxpSuwpYOKRm/L5KbqoZmNNukHa/Flty4Wp62JRvgH2ojwVgPgdYyr4twpieZnyRDdIH7PY2mopX26+j2Q==}
+
   damerau-levenshtein@1.0.8:
     resolution: {integrity: sha512-sdQSFB7+llfUcQHUQO3+B8ERRj0Oa4w9POWMI/puGtuf7gFywGmkaLCElnudfTiKZV+NvHqL0ifzdrI8Ro7ESA==}
 
@@ -4537,6 +4816,9 @@ packages:
   date-fns@4.1.0:
     resolution: {integrity: sha512-Ukq0owbQXxa/U3EGtsdVBkR1w7KOQ5gIBqdH2hkvknzZPYvBxb/aa6E8L7tmjFtkwZBu3UXBbjIgPo/Ez4xaNg==}
 
+  dayjs@1.11.19:
+    resolution: {integrity: sha512-t5EcLVS6QPBNqM2z8fakk/NKel+Xzshgt8FFKAn+qwlD1pzZWxh0nVCrvFK7ZDb6XucZeF9z8C7CBWTRIVApAw==}
+
   debug@3.2.7:
     resolution: {integrity: sha512-CFjzYYAi4ThfiQvizrFQevTTXHtnCqWfe7x1AhgEscTz6ZbLbfoLRLPugTQyBth6f8ZERVUSyWHFD/7Wu4t1XQ==}
     peerDependencies:
@@ -4593,6 +4875,9 @@ packages:
     resolution: {integrity: sha512-8QmQKqEASLd5nx0U1B1okLElbUuuttJ/AnYmRXbbbGDWh6uS208EjD4Xqq/I9wK7u0v6O08XhTWnt5XtEbR6Dg==}
     engines: {node: '>= 0.4'}
 
+  delaunator@5.0.1:
+    resolution: {integrity: sha512-8nvh+XBe96aCESrGOqMp/84b13H9cdKbG5P2ejQCh4d4sK9RL4371qou9drQjMhvnPmhWl5hnmqbEE0fXr9Xnw==}
+
   dependency-graph@0.11.0:
     resolution: {integrity: sha512-JeMq7fEshyepOWDfcfHK06N3MhyPhz++vtqWhMT5O9A3K42rdsEDpfdVqjaqaAhsw6a+ZqeDvQVtD0hFHQWrzg==}
     engines: {node: '>= 0.6.0'}
@@ -4973,6 +5258,10 @@ packages:
     resolution: {integrity: sha512-mQw+2fkQbALzQ7V0MY0IqdnXNOeTtP4r0lN9z7AAawCXgqea7bDii20AYrIBrFd/Hx0M2Ocz6S111CaFkUcb0Q==}
     engines: {node: '>=0.8.x'}
 
+  eventsource-parser@3.0.6:
+    resolution: {integrity: sha512-Vo1ab+QXPzZ4tCa8SwIHJFaSzy4R6SHf7BY79rFBDf0idraZWAkYrDjDj8uWaSm3S2TK+hJ7/t1CEmZ7jXw+pg==}
+    engines: {node: '>=18.0.0'}
+
   evp_bytestokey@1.0.3:
     resolution: {integrity: sha512-/f2Go4TognH/KvCISP7OUsHn85hT9nUkxxA9BEWxFn+Oj9o8ZNLm/40hdlgSLyuOimsrTKLUMEorQexp/aPQeA==}
 
@@ -5173,6 +5462,10 @@ packages:
     resolution: {integrity: sha512-DyFP3BM/3YHTQOCUL/w0OZHR0lpKeGrxotcHWcqNEdnltqFwXVfhEBQ94eIo34AfQpo0rGki4cyIiftY06h2Fg==}
     engines: {node: 6.* || 8.* || >= 10.*}
 
+  get-east-asian-width@1.4.0:
+    resolution: {integrity: sha512-QZjmEOC+IT1uk6Rx0sX22V6uHWVwbdbxf1faPqJ1QhLdGgsRGCZoyaQBm/piRdJy/D2um6hM1UP7ZEeQ4EkP+Q==}
+    engines: {node: '>=18'}
+
   get-intrinsic@1.3.0:
     resolution: {integrity: sha512-9fSjSaos/fRIVIp+xSJlE6lfwhES7LNtKaCBIamHsjr2na1BiABJPo0mOjjz8GJDURarmCPGqaiVg5mfjb98CQ==}
     engines: {node: '>= 0.4'}
@@ -5212,11 +5505,12 @@ packages:
 
   glob@10.5.0:
     resolution: {integrity: sha512-DfXN8DfhJ7NH3Oe7cFmu3NCu1wKbkReJ8TorzSAFbSKrlNaQSKfIzqYqVY8zlbs2NLBbWpRiU52GX2PbaBVNkg==}
+    deprecated: Old versions of glob are not supported, and contain widely publicized security vulnerabilities, which have been fixed in the current version. Please update. Support for old versions may be purchased (at exorbitant rates) by contacting i@izs.me
     hasBin: true
 
   glob@7.2.3:
     resolution: {integrity: sha512-nFR0zLpU2YCaRxwoCJvL6UvCH2JFyFVIvwTLsIf21AuHlMskA1hhTdk+LlYJtOlYt9v6dvszD2BGRqBL+iQK9Q==}
-    deprecated: Glob versions prior to v9 are no longer supported
+    deprecated: Old versions of glob are not supported, and contain widely publicized security vulnerabilities, which have been fixed in the current version. Please update. Support for old versions may be purchased (at exorbitant rates) by contacting i@izs.me
 
   globals@13.24.0:
     resolution: {integrity: sha512-AhO5QUcj8llrbG09iWhPU2B204J1xnPeL8kQmVorSsy+Sjj1sk8gIyh6cUocGmH4L0UuhAJy+hJMRA4mgA4mFQ==}
@@ -5247,6 +5541,9 @@ packages:
     resolution: {integrity: sha512-DKKrynuQRne0PNpEbzuEdHlYOMksHSUI8Zc9Unei5gTsMNA2/vMpoMz/yKba50pejK56qj98qM0SjYxAKi13gQ==}
     engines: {node: ^12.22.0 || ^14.16.0 || ^16.0.0 || >=17.0.0}
 
+  hachure-fill@0.5.2:
+    resolution: {integrity: sha512-3GKBOn+m2LX9iq+JC1064cSFprJY4jL1jCXTcpnfER5HYE2l/4EfWSGzkPa/ZDBmYI0ZOEj5VHV/eKnPGkHuOg==}
+
   happy-dom@20.3.4:
     resolution: {integrity: sha512-rfbiwB6OKxZFIFQ7SRnCPB2WL9WhyXsFoTfecYgeCeFSOBxvkWLaXsdv5ehzJrfqwXQmDephAKWLRQoFoJwrew==}
     engines: {node: '>=20.0.0'}
@@ -5310,9 +5607,21 @@ packages:
   hast-util-parse-selector@4.0.0:
     resolution: {integrity: sha512-wkQCkSYoOGCRKERFWcxMVMOcYE2K1AaNLU8DXS9arxnLOUEWbOXKXiJUNzEpqZ3JOKpnha3jkFrumEjVliDe7A==}
 
+  hast-util-raw@9.1.0:
+    resolution: {integrity: sha512-Y8/SBAHkZGoNkpzqqfCldijcuUKh7/su31kEBp67cFY09Wy0mTRgtsLYsiIxMJxlu0f6AA5SUTbDR8K0rxnbUw==}
+
+  hast-util-sanitize@5.0.2:
+    resolution: {integrity: sha512-3yTWghByc50aGS7JlGhk61SPenfE/p1oaFeNwkOOyrscaOkMGrcW9+Cy/QAIOBpZxP1yqDIzFMR0+Np0i0+usg==}
+
+  hast-util-to-html@9.0.5:
+    resolution: {integrity: sha512-OguPdidb+fbHQSU4Q4ZiLKnzWo8Wwsf5bZfbvu7//a9oTYoqD/fWpe96NuHkoS9h0ccGOTe0C4NGXdtS0iObOw==}
+
   hast-util-to-jsx-runtime@2.3.6:
     resolution: {integrity: sha512-zl6s8LwNyo1P9uw+XJGvZtdFF1GdAkOg8ujOw+4Pyb76874fLps4ueHXDhXWdk6YHQ6OgUtinliG7RsYvCbbBg==}
 
+  hast-util-to-parse5@8.0.1:
+    resolution: {integrity: sha512-MlWT6Pjt4CG9lFCjiz4BH7l9wmrMkfkJYCxFwKQic8+RTZgWPuWxwAfjJElsXkex7DJjfSJsQIt931ilUgmwdA==}
+
   hast-util-to-string@3.0.1:
     resolution: {integrity: sha512-XelQVTDWvqcl3axRfI0xSeoVKzyIFPwsAGSLIsKdJKQMXDYJS4WYrBNF/8J7RdhIcFI2BOHgAifggsvsxp/3+A==}
 
@@ -5357,6 +5666,9 @@ packages:
   html-url-attributes@3.0.1:
     resolution: {integrity: sha512-ol6UPyBWqsrO6EJySPz2O7ZSr856WDrEzM5zMqp+FJJLGMW35cLYmmZnl0vztAZxRUoNZJFTCohfjuIJ8I4QBQ==}
 
+  html-void-elements@3.0.0:
+    resolution: {integrity: sha512-bEqo66MRXsUGxWHV5IP0PUiAWwoEjba4VCzg0LjFJBpchPaTfyfCKTG6bc5F8ucKec3q5y6qOdGyYTSBEvhCrg==}
+
   html-webpack-plugin@5.6.5:
     resolution: {integrity: sha512-4xynFbKNNk+WlzXeQQ+6YYsH2g7mpfPszQZUi3ovKlj+pDmngQ7vRXjrrmGROabmKwyQkcgcX5hqfOwHbFmK5g==}
     engines: {node: '>=10.13.0'}
@@ -5394,6 +5706,10 @@ packages:
     resolution: {integrity: sha512-B4FFZ6q/T2jhhksgkbEW3HBvWIfDW85snkQgawt07S7J5QXTk6BkNV+0yAeZrM5QpMAdYlocGoljn0sJ/WQkFw==}
     engines: {node: '>=10.17.0'}
 
+  iconv-lite@0.6.3:
+    resolution: {integrity: sha512-4fCk79wshMdzMp2rH06qWrJE4iolqLhCUH+OiuIgU++RB0+94NlDL81atO7GX55uUKueo0txHNtvEyI6D7WdMw==}
+    engines: {node: '>=0.10.0'}
+
   icss-utils@5.1.0:
     resolution: {integrity: sha512-soFhflCVWLfRNOPU3iv5Z9VUdT44xFRbzjLsEzSr5AQmgqPMTHdU3PMT1Cf1ssx8fLNJDA1juftYl+PUcv3MqA==}
     engines: {node: ^10 || ^12 || >= 14}
@@ -5457,6 +5773,9 @@ packages:
     resolution: {integrity: sha512-4gd7VpWNQNB4UKKCFFVcp1AVv+FMOgs9NKzjHKusc8jTMhd5eL1NqQqOpE0KzMds804/yHlglp3uxgluOqAPLw==}
     engines: {node: '>= 0.4'}
 
+  internmap@1.0.1:
+    resolution: {integrity: sha512-lDB5YccMydFBtasVtxnZ3MRBHuaoE8GKsppq+EchKL2U4nK/DmEpPHNH8MZe5HkMtpSiTSOZwfN0tzYjO/lJEw==}
+
   internmap@2.0.3:
     resolution: {integrity: sha512-5Hh7Y1wQbvY5ooGgPbDaL5iYLAPzMTUrjMulskHLH6wnv/A+1q5rgEaiuqEjB+oxGXIVZs1FF+R/KPN3ZSQYYg==}
     engines: {node: '>=12'}
@@ -5697,6 +6016,9 @@ packages:
   json-schema-traverse@1.0.0:
     resolution: {integrity: sha512-NM8/P9n3XjXhIZn1lLhkFaACTOURQXjWhV4BA/RnOv8xvgqtqpAX9IO4mRQxSx1Rlo4tqzeqb0sOlruaOy3dug==}
 
+  json-schema@0.4.0:
+    resolution: {integrity: sha512-es94M3nTIfsEPisRafak+HDLfHXnKBhV3vU5eqPcS3flIWqcxJWgXHXiey3YrpaNsanY5ei1VoYEbOzijuq9BA==}
+
   json-stable-stringify-without-jsonify@1.0.1:
     resolution: {integrity: sha512-Bdboy+l7tA3OGW6FjyFHWkP5LuByj1Tk33Ljyq0axyzdk9//JSi2u3fP1QSmd1KNwq6VOKYGlAu87CisVir6Pw==}
 
@@ -5739,9 +6061,20 @@ packages:
     resolution: {integrity: sha512-woHRUZ/iF23GBP1dkDQMh1QBad9dmr8/PAwNA54VrSOVYgI12MAcE14TqnDdQOdzyEonGzMepYnqBMYdsoAr8Q==}
     hasBin: true
 
+  katex@0.16.28:
+    resolution: {integrity: sha512-YHzO7721WbmAL6Ov1uzN/l5mY5WWWhJBSW+jq4tkfZfsxmo1hu6frS0EOswvjBUnWE6NtjEs48SFn5CQESRLZg==}
+    hasBin: true
+
   keyv@4.5.4:
     resolution: {integrity: sha512-oxVHkHR/EJf2CNXnWxRLW6mg7JyCCUcG0DtEGmL2ctUo1PNTin1PUil+r/+4r5MpVgC/fn1kjsx7mjSujKqIpw==}
 
+  khroma@2.1.0:
+    resolution: {integrity: sha512-Ls993zuzfayK269Svk9hzpeGUKob/sIgZzyHYdjQoAdQetRKpOLj+k/QQQ/6Qi0Yz65mlROrfd+Ev+1+7dz9Kw==}
+
+  langium@3.3.1:
+    resolution: {integrity: sha512-QJv/h939gDpvT+9SiLVlY7tZC3xB2qK57v0J04Sh9wpMb6MP1q8gB21L3WIo8T5P1MSMg3Ep14L7KkDCFG3y4w==}
+    engines: {node: '>=16.0.0'}
+
   language-subtag-registry@0.3.23:
     resolution: {integrity: sha512-0K65Lea881pHotoGEa5gDlMxt3pctLi2RplBb7Ezh4rRdLEOtgi7n4EwK9lamnUCkKBqaeKRVebTq6BAxSkpXQ==}
 
@@ -5761,6 +6094,12 @@ packages:
       react: ^16.6.3 || ^17.0.0 || ^18.0.0 || ^19.0.0
       react-dom: ^16.8.4 || ^17.0.0 || ^18.0.0 || ^19.0.0
 
+  layout-base@1.0.2:
+    resolution: {integrity: sha512-8h2oVEZNktL4BH2JCOI90iD1yXwL6iNW7KcCKT2QZgQJR2vbqDsldCTPRU9NifTCqHZci57XvQQ15YTu+sTYPg==}
+
+  layout-base@2.0.1:
+    resolution: {integrity: sha512-dp3s92+uNI1hWIpPGH3jK2kxE2lMjdXdr+DH8ynZHpd6PUlH6x6cbuXnoMmiNumznqaNO31xu9e79F0uuZ0JFg==}
+
   leven@3.1.0:
     resolution: {integrity: sha512-qsda+H8jTaUaN/x5vzW2rzc+8Rw4TAQ/4KjB46IwK5VH+IlVeeeje/EoZRpiXvIqjFgK84QffqPztGI3VBLG1A==}
     engines: {node: '>=6'}
@@ -5803,8 +6142,8 @@ packages:
     resolution: {integrity: sha512-gvVijfZvn7R+2qyPX8mAuKcFGDf6Nc61GdvGafQsHL0sBIxfKzA+usWn4GFC/bk+QdwPUD4kWFJLhElipq+0VA==}
     engines: {node: ^12.20.0 || ^14.13.1 || >=16.0.0}
 
-  lodash-es@4.17.22:
-    resolution: {integrity: sha512-XEawp1t0gxSi9x01glktRZ5HDy0HXqrM0x5pXQM98EaI0NxO6jVM7omDOxsuEo5UIASAnm2bRp1Jt/e0a2XU8Q==}
+  lodash-es@4.17.23:
+    resolution: {integrity: sha512-kVI48u3PZr38HdYz98UmfPnXl2DXrpdctLrFLCd3kOx1xUkOmpFPx7gCWWM5MPkL/fD8zb+Ph0QzjGFs4+hHWg==}
 
   lodash.camelcase@4.3.0:
     resolution: {integrity: sha512-TwuEnCnxbc3rAvhf/LbG7tJUDzhqXyFnv3dtzLOPgCG/hODL7WFnsbwktkD7yUV0RrreP/l1PALq/YSg6VvjlA==}
@@ -5911,6 +6250,16 @@ packages:
       react:
         optional: true
 
+  marked@16.4.2:
+    resolution: {integrity: sha512-TI3V8YYWvkVf3KJe1dRkpnjs68JUPyEa5vjKrp1XEEJUAOaQc+Qj+L1qWbPd0SJuAdQkFU0h73sXXqwDYxsiDA==}
+    engines: {node: '>= 20'}
+    hasBin: true
+
+  marked@17.0.1:
+    resolution: {integrity: sha512-boeBdiS0ghpWcSwoNm/jJBwdpFaMnZWRzjA6SkUMYb40SVaN1x7mmfGKp0jvexGcx+7y2La5zRZsYFZI6Qpypg==}
+    engines: {node: '>= 20'}
+    hasBin: true
+
   math-intrinsics@1.1.0:
     resolution: {integrity: sha512-/IXtbwEk5HTPyEwyKX6hGkYXxM9nbj64B+ilVJnC/R6B0pH5G4V3b0pVbL7DBj4tkhBAppbQUlf6F6Xl9LHu1g==}
     engines: {node: '>= 0.4'}
@@ -5976,9 +6325,6 @@ packages:
     resolution: {integrity: sha512-UERzLsxzllchadvbPs5aolHh65ISpKpM+ccLbOJ8/vvpBKmAWf+la7dXFy7Mr0ySHbdHrFv5kGFCUHHe6GFEmw==}
     engines: {node: '>= 4.0.0'}
 
-  memoize-one@5.2.1:
-    resolution: {integrity: sha512-zYiwtZUcYyXKo/np96AGZAckk+FWWsUdJ3cHGGmld7+AhvcWmQyGCYUh1hc4Q/pkOhb65dQR/pqCyK0cOaHz4Q==}
-
   merge-stream@2.0.0:
     resolution: {integrity: sha512-abv/qOcuPfk3URPfDzmZU1LKmuw8kT+0nIHvKrKgFrwifol/doWcdA4ZqsWQ8ENrFKkd67Mfpo/LovbIUsbt3w==}
 
@@ -5986,9 +6332,41 @@ packages:
     resolution: {integrity: sha512-8q7VEgMJW4J8tcfVPy8g09NcQwZdbwFEqhe/WZkoIzjn/3TGDwtOCYtXGxA3O8tPzpczCCDgv+P2P5y00ZJOOg==}
     engines: {node: '>= 8'}
 
+  mermaid@11.12.2:
+    resolution: {integrity: sha512-n34QPDPEKmaeCG4WDMGy0OT6PSyxKCfy2pJgShP+Qow2KLrvWjclwbc3yXfSIf4BanqWEhQEpngWwNp/XhZt6w==}
+
   micromark-core-commonmark@2.0.3:
     resolution: {integrity: sha512-RDBrHEMSxVFLg6xvnXmb1Ayr2WzLAWjeSATAoxwKYJV94TeNavgoIdA0a9ytzDSVzBy2YKFK+emCPOEibLeCrg==}
 
+  micromark-extension-cjk-friendly-gfm-strikethrough@1.2.3:
+    resolution: {integrity: sha512-gSPnxgHDDqXYOBvQRq6lerrq9mjDhdtKn+7XETuXjxWcL62yZEfUdA28Ml1I2vDIPfAOIKLa0h2XDSGkInGHFQ==}
+    engines: {node: '>=16'}
+    peerDependencies:
+      micromark: ^4.0.0
+      micromark-util-types: ^2.0.0
+    peerDependenciesMeta:
+      micromark-util-types:
+        optional: true
+
+  micromark-extension-cjk-friendly-util@2.1.1:
+    resolution: {integrity: sha512-egs6+12JU2yutskHY55FyR48ZiEcFOJFyk9rsiyIhcJ6IvWB6ABBqVrBw8IobqJTDZ/wdSr9eoXDPb5S2nW1bg==}
+    engines: {node: '>=16'}
+    peerDependencies:
+      micromark-util-types: '*'
+    peerDependenciesMeta:
+      micromark-util-types:
+        optional: true
+
+  micromark-extension-cjk-friendly@1.2.3:
+    resolution: {integrity: sha512-gRzVLUdjXBLX6zNPSnHGDoo+ZTp5zy+MZm0g3sv+3chPXY7l9gW+DnrcHcZh/jiPR6MjPKO4AEJNp4Aw6V9z5Q==}
+    engines: {node: '>=16'}
+    peerDependencies:
+      micromark: ^4.0.0
+      micromark-util-types: ^2.0.0
+    peerDependenciesMeta:
+      micromark-util-types:
+        optional: true
+
   micromark-extension-gfm-autolink-literal@2.1.0:
     resolution: {integrity: sha512-oOg7knzhicgQ3t4QCjCWgTmfNhvQbDDnJeVu9v81r7NltNCVmhPy1fJRX27pISafdjL+SVc4d3l48Gb6pbRypw==}
 
@@ -6121,12 +6499,12 @@ packages:
     resolution: {integrity: sha512-qOOzS1cBTWYF4BH8fVePDBOO9iptMnGUEZwNc/cMWnTV2nVLZ7VoNWEPHkYczZA0pdoA7dl6e7FL659nX9S2aw==}
     engines: {node: '>=16 || 14 >=14.17'}
 
+  mlly@1.8.0:
+    resolution: {integrity: sha512-l8D9ODSRWLe2KHJSifWGwBqpTZXIXTeo8mlKjY+E2HAakaTeNpqAyBZ8GSqLzHgw4XmHmC8whvpjJNMbFZN7/g==}
+
   module-details-from-path@1.0.4:
     resolution: {integrity: sha512-EGWKgxALGMgzvxYF1UyGTy0HXX/2vHLkw6+NvDKW2jypWbHpjQuj4UMcqQWXHERJhVGKikolT06G3bcKe4fi7w==}
 
-  moment@2.30.1:
-    resolution: {integrity: sha512-uEmtNhbDOrWPFS+hdjFCBfy9f2YoyzRpwcl+DqpC6taX21FzsTLQVbMV/W7PzNSX6x/bhC1zA3c2UQ5NzH6how==}
-
   motion-dom@12.24.8:
     resolution: {integrity: sha512-wX64WITk6gKOhaTqhsFqmIkayLAAx45SVFiMnJIxIrH5uqyrwrxjrfo8WX9Kh8CaUAixjeMn82iH0W0QT9wD5w==}
 
@@ -6341,6 +6719,12 @@ packages:
     resolution: {integrity: sha512-kbpaSSGJTWdAY5KPVeMOKXSrPtr8C8C7wodJbcsd51jRnmD+GZu8Y0VoU6Dm5Z4vWr0Ig/1NKuWRKf7j5aaYSg==}
     engines: {node: '>=6'}
 
+  oniguruma-parser@0.12.1:
+    resolution: {integrity: sha512-8Unqkvk1RYc6yq2WBYRj4hdnsAxVze8i7iPfQr8e4uSP3tRv0rpZcbGUDvxfQQcdwHt/e9PrMvGCsa8OqG9X3w==}
+
+  oniguruma-to-es@4.3.4:
+    resolution: {integrity: sha512-3VhUGN3w2eYxnTzHn+ikMI+fp/96KoRSVK9/kMTcFqj1NRDh2IhQCKvYxDnWePKRXY/AqH+Fuiyb7VHSzBjHfA==}
+
   open@8.4.2:
     resolution: {integrity: sha512-7x81NCL719oNbsq/3mh+hVrAWmFuEYUqrq/Iw3kUzH8ReypT9QQ0BLoJS7/G9k6N81XjW4qHWtjWwe/9eLy1EQ==}
     engines: {node: '>=12'}
@@ -6400,6 +6784,9 @@ packages:
   package-json-from-dist@1.0.1:
     resolution: {integrity: sha512-UEZIS3/by4OC8vL3P2dTXRETpebLI2NiI5vIrjaD/5UtrkFX/tNbwjTSRAGC/+7CAo2pIcBaRgWmcBBHcsaCIw==}
 
+  package-manager-detector@1.6.0:
+    resolution: {integrity: sha512-61A5ThoTiDG/C8s8UMZwSorAGwMJ0ERVGj2OjoW5pAalsNOg15+iQiPzrLJ4jhZ1HJzmC2PIHT2oEiH3R5fzNA==}
+
   pako@1.0.11:
     resolution: {integrity: sha512-4hLB8Py4zZce5s4yd9XzopqwVv/yGNhV1Bl8NTmCq1763HeK2+EwVTv+leGeL13Dnh2wfbqowVPXCIO0z4taYw==}
 
@@ -6436,6 +6823,9 @@ packages:
   path-browserify@1.0.1:
     resolution: {integrity: sha512-b7uo2UCUOYZcnF/3ID0lulOJi/bafxa1xPe7ZPsammBSpjSWQkjNxlt635YGS2MiR9GjvuXCtz2emr3jbsz98g==}
 
+  path-data-parser@0.1.0:
+    resolution: {integrity: sha512-NOnmBpt5Y2RWbuv0LMzsayp3lVylAHLPUTut412ZA3l+C4uw4ZVkQbjShYCQ8TCpUMdPapr4YjUqLYD6v68j+w==}
+
   path-exists@4.0.0:
     resolution: {integrity: sha512-ak9Qy5Q7jYb2Wwcey5Fpvg2KoAc/ZIhLSLOSBmRmygPsGwkVVt0fZa0qrtMz+m6tJTAHfZQ8FnmB4MG4LWy7/w==}
     engines: {node: '>=8'}
@@ -6515,6 +6905,9 @@ packages:
     resolution: {integrity: sha512-Ie9z/WINcxxLp27BKOCHGde4ITq9UklYKDzVo1nhk5sqGEXU3FpkwP5GM2voTGJkGd9B3Otl+Q4uwSOeSUtOBA==}
     engines: {node: '>=14.16'}
 
+  pkg-types@1.3.1:
+    resolution: {integrity: sha512-/Jm5M4RvtBFVkKWRu2BLUTNP8/M2a+UwuAX+ae4770q1qVGtfjG+WTCupoZixokjmHiry8uI+dlY8KXYV5HVVQ==}
+
   playwright-core@1.56.1:
     resolution: {integrity: sha512-hutraynyn31F+Bifme+Ps9Vq59hKuUCz7H1kDOcBs+2oGguKkWTU50bBWrtz34OUWmIwpBTWDxaRPXrIXkgvmQ==}
     engines: {node: '>=18'}
@@ -6525,6 +6918,12 @@ packages:
     engines: {node: '>=18'}
     hasBin: true
 
+  points-on-curve@0.2.0:
+    resolution: {integrity: sha512-0mYKnYYe9ZcqMCWhUjItv/oHjvgEsfKvnUTg8sAtnHr3GVy7rGkXCb6d5cSyqrWqL4k81b9CPg3urd+T7aop3A==}
+
+  points-on-path@0.2.1:
+    resolution: {integrity: sha512-25ClnWWuw7JbWZcgqY/gJ4FQWadKxGWk+3kR/7kD0tCaDtPPMj7oHu2ToLaVhfpnHrZzYby2w6tUA0eOIuUg8g==}
+
   pony-cause@1.1.1:
     resolution: {integrity: sha512-PxkIc/2ZpLiEzQXu5YRDOUgBlfGYBY8156HY5ZcRAwwonMk5W/MrJP2LLkG/hF7GEQzaHo2aS7ho6ZLCOvf+6g==}
     engines: {node: '>=12.0.0'}
@@ -6891,12 +7290,11 @@ packages:
       '@types/react':
         optional: true
 
-  react-window@1.8.11:
-    resolution: {integrity: sha512-+SRbUVT2scadgFSWx+R1P754xHPEqvcfSfVX10QYg6POOz+WNgkN48pS+BtZNIMGiL1HYrSEiCkwsMS15QogEQ==}
-    engines: {node: '>8.0.0'}
+  react-window@2.2.0:
+    resolution: {integrity: sha512-Y2L7yonHq6K1pQA2P98wT5QdIsEcjBTB7T8o6Mub12hH9eYppXoYu6vgClmcjlh3zfNcW2UrXiJJJqDxUY7GVw==}
     peerDependencies:
-      react: ^15.0.0 || ^16.0.0 || ^17.0.0 || ^18.0.0 || ^19.0.0
-      react-dom: ^15.0.0 || ^16.0.0 || ^17.0.0 || ^18.0.0 || ^19.0.0
+      react: ^18.0.0 || ^19.0.0
+      react-dom: ^18.0.0 || ^19.0.0
 
   react@18.3.1:
     resolution: {integrity: sha512-wS+hAgJShR0KhEvPJArfuPVN1+Hz1t0Y6n5jLrGQbkb4urgPE/0Rve+1kMB1v/oWgHgm4WIcV+i7F2pTVj+2iQ==}
@@ -6965,6 +7363,15 @@ packages:
   regex-parser@2.3.1:
     resolution: {integrity: sha512-yXLRqatcCuKtVHsWrNg0JL3l1zGfdXeEvDa0bdu4tCDQw0RpMDZsqbkyRTUnKMR0tXF627V2oEWjBEaEdqTwtQ==}
 
+  regex-recursion@6.0.2:
+    resolution: {integrity: sha512-0YCaSCq2VRIebiaUviZNs0cBz1kg5kVS2UKUfNIx8YVs1cN3AV7NTctO5FOKBA+UT2BPJIWZauYHPqJODG50cg==}
+
+  regex-utilities@2.3.0:
+    resolution: {integrity: sha512-8VhliFJAWRaUiVvREIiW2NXXTmHs4vMNnSzuJVhscgmGav3g9VDxLrQndI3dZZVVdp0ZO/5v0xmX516/7M9cng==}
+
+  regex@6.1.0:
+    resolution: {integrity: sha512-6VwtthbV4o/7+OaAF9I5L5V3llLEsoPyq9P1JVXkedTP33c7MfCG0/5NOPcSJn0TzXcG9YUrR0gQSWioew3LDg==}
+
   regexp.prototype.flags@1.5.4:
     resolution: {integrity: sha512-dYqgNSZbDwkaJ2ceRd9ojCGjBq+mOm9LmtXnAnEGyHhN/5R7iDW2TRw3h+o/jCFxus3P2LfWIIiwowAjANm7IA==}
     engines: {node: '>= 0.4'}
@@ -6983,12 +7390,21 @@ packages:
   rehype-autolink-headings@7.1.0:
     resolution: {integrity: sha512-rItO/pSdvnvsP4QRB1pmPiNHUskikqtPojZKJPPPAVx9Hj8i8TwMBhofrrAYRhYOOBZH9tgmG5lPqDLuIWPWmw==}
 
+  rehype-harden@1.1.7:
+    resolution: {integrity: sha512-j5DY0YSK2YavvNGV+qBHma15J9m0WZmRe8posT5AtKDS6TNWtMVTo6RiqF8SidfcASYz8f3k2J/1RWmq5zTXUw==}
+
   rehype-highlight@7.0.2:
     resolution: {integrity: sha512-k158pK7wdC2qL3M5NcZROZ2tR/l7zOzjxXd5VGdcfIyoijjQqpHd3JKtYSBDpDZ38UI2WJWuFAtkMDxmx5kstA==}
 
   rehype-katex@7.0.1:
     resolution: {integrity: sha512-OiM2wrZ/wuhKkigASodFoo8wimG3H12LWQaH8qSPVJn9apWKFSH3YOCtbKpBorTVw/eI7cuT21XBbvwEswbIOA==}
 
+  rehype-raw@7.0.0:
+    resolution: {integrity: sha512-/aE8hCfKlQeA8LmyeyQvQF3eBiLRGNlfBJEvWH7ivp9sBqs7TNqBL5X3v157rM4IFETqDnIOO+z5M/biZbo9Ww==}
+
+  rehype-sanitize@6.0.0:
+    resolution: {integrity: sha512-CsnhKNsyI8Tub6L4sm5ZFsme4puGfc6pYylvXo1AeqaGbjOYyzNv3qZPwvs0oMJ39eryyeOdmxwUIo94IpEhqg==}
+
   rehype-slug@6.0.0:
     resolution: {integrity: sha512-lWyvf/jwu+oS5+hL5eClVd3hNdmwM1kAC0BUvEGD19pajQMIzcNUd/k9GsfQ+FfECvX+JE+e9/btsKH0EjJT6A==}
 
@@ -6996,6 +7412,26 @@ packages:
     resolution: {integrity: sha512-G08Dxvm4iDN3MLM0EsP62EDV9IuhXPR6blNz6Utcp7zyV3tr4HVNINt6MpaRWbxoOHT3Q7YN2P+jaHX8vUbgog==}
     engines: {node: '>= 0.10'}
 
+  remark-cjk-friendly-gfm-strikethrough@1.2.3:
+    resolution: {integrity: sha512-bXfMZtsaomK6ysNN/UGRIcasQAYkC10NtPmP0oOHOV8YOhA2TXmwRXCku4qOzjIFxAPfish5+XS0eIug2PzNZA==}
+    engines: {node: '>=16'}
+    peerDependencies:
+      '@types/mdast': ^4.0.0
+      unified: ^11.0.0
+    peerDependenciesMeta:
+      '@types/mdast':
+        optional: true
+
+  remark-cjk-friendly@1.2.3:
+    resolution: {integrity: sha512-UvAgxwlNk+l9Oqgl/9MWK2eWRS7zgBW/nXX9AthV7nd/3lNejF138E7Xbmk9Zs4WjTJGs721r7fAEc7tNFoH7g==}
+    engines: {node: '>=16'}
+    peerDependencies:
+      '@types/mdast': ^4.0.0
+      unified: ^11.0.0
+    peerDependenciesMeta:
+      '@types/mdast':
+        optional: true
+
   remark-gfm@4.0.1:
     resolution: {integrity: sha512-1quofZ2RQ9EWdeN34S79+KExV1764+wCUGop5CPL1WGdD0ocPpu91lzPGbwWMECpEpd42kJGQwzRfyov9j4yNg==}
 
@@ -7011,6 +7447,9 @@ packages:
   remark-stringify@11.0.0:
     resolution: {integrity: sha512-1OSmLd3awB/t8qdoEOMazZkNsfVTeY4fTsgzcQFdXNq8ToTN4ZGwrMnlda4K6smTFKD+GRV6O48i6Z4iKgPPpw==}
 
+  remend@1.1.0:
+    resolution: {integrity: sha512-JENGyuIhTwzUfCarW43X4r9cehoqTo9QyYxfNDZSud2AmqeuWjZ5pfybasTa4q0dxTJAj5m8NB+wR+YueAFpxQ==}
+
   renderkid@3.0.0:
     resolution: {integrity: sha512-q/7VIQA8lmM1hF+jn+sFSPWGlMkSAeNYcPLmDQx2zzuiDfaLrOmumR8iaUKlenFgh0XRPIUeSPlH3A+AW3Z5pg==}
 
@@ -7069,14 +7508,23 @@ packages:
     resolution: {integrity: sha512-5Di9UC0+8h1L6ZD2d7awM7E/T4uA1fJRlx6zk/NvdCCVEoAnFqvHmCuNeIKoCeIixBX/q8uM+6ycDvF8woqosA==}
     engines: {node: '>= 0.8'}
 
+  robust-predicates@3.0.2:
+    resolution: {integrity: sha512-IXgzBWvWQwE6PrDI05OvmXUIruQTcoMDzRsOd5CDvHCVLcLHMTSYvOK5Cm46kWqlV3yAbuSpBZdJ5oP5OUoStg==}
+
   rollup@4.55.1:
     resolution: {integrity: sha512-wDv/Ht1BNHB4upNbK74s9usvl7hObDnvVzknxqY/E/O3X6rW1U1rV1aENEfJ54eFZDTNo7zv1f5N4edCluH7+A==}
     engines: {node: '>=18.0.0', npm: '>=8.0.0'}
     hasBin: true
 
+  roughjs@4.6.6:
+    resolution: {integrity: sha512-ZUz/69+SYpFN/g/lUlo2FXcIjRkSu3nDarreVdGGndHEBJ6cXPdKguS8JGxwj5HA5xIbVKSmLgr5b3AWxtRfvQ==}
+
   run-parallel@1.2.0:
     resolution: {integrity: sha512-5l4VyZR86LZ/lDxZTR6jqL8AFE2S0IFLMP26AbjsLVADxHdhB/c0GUsH+y39UfCi3dzz8OlQuPmnaJOMoDHQBA==}
 
+  rw@1.3.3:
+    resolution: {integrity: sha512-PdhdWy89SiZogBLaw42zdeqtRJ//zFd2PgQavcICDUgJT5oW10QCRKbJ6bg4r0/UY2M6BWd5tkxuGFRvCkgfHQ==}
+
   rxjs@7.8.2:
     resolution: {integrity: sha512-dhKf903U/PQZY6boNNtAGdWbG85WAbjT/1xYoZIC7FAY0yWapOBQVsVrDl58W86//e1VpMNBtRV4MaXfdMySFA==}
 
@@ -7101,6 +7549,9 @@ packages:
   safe-stable-stringify@1.1.1:
     resolution: {integrity: sha512-ERq4hUjKDbJfE4+XtZLFPCDi8Vb1JqaxAPTxWFLBx8XcAlf9Bda/ZJdVezs/NAfsMQScyIlUMx+Yeu7P7rx5jw==}
 
+  safer-buffer@2.1.2:
+    resolution: {integrity: sha512-YZo3K82SD7Riyi0E1EQPojLz7kpepnSQI9IyPbHHg1XXXevb5dJI7tpyN2ADxGcQbHG7vcyRHk0cbwqcQriUtg==}
+
   sass-loader@16.0.6:
     resolution: {integrity: sha512-sglGzId5gmlfxNs4gK2U3h7HlVRfx278YK6Ono5lwzuvi1jxig80YiuHkaDBVsYIKFhx8wN7XSCI0M2IDS/3qA==}
     engines: {node: '>= 18.12.0'}
@@ -7189,6 +7640,9 @@ packages:
     resolution: {integrity: sha512-VuvPvLG1QjNOLP7AIm2HGyfmxEIz8QdskvWOHwUcxLDibYWjLRBmCWd8LSL5FlwhBW7D/GU+3gNVC/ASxAWdxg==}
     engines: {node: 18.* || >= 20}
 
+  shiki@3.21.0:
+    resolution: {integrity: sha512-N65B/3bqL/TI2crrXr+4UivctrAGEjmsib5rPMMPpFp1xAx/w03v8WZ9RDDFYteXoEgY7qZ4HGgl5KBIu1153w==}
+
   should-equal@2.0.0:
     resolution: {integrity: sha512-ZP36TMrK9euEuWQYBig9W55WPC7uo37qzAEmbjHz4gfyuXrEUgF8cUvQVO+w+d3OMfPvSRQJ22lSm8MQJ43LTA==}
 
@@ -7304,6 +7758,11 @@ packages:
   stream-http@3.2.0:
     resolution: {integrity: sha512-Oq1bLqisTyK3TSCXpPbT4sdeYNdmyZJv1LxpEm2vu1ZhK89kSE5YXwZc3cWk0MagGaKriBh9mCFbVGtO+vY29A==}
 
+  streamdown@2.1.0:
+    resolution: {integrity: sha512-u9gWd0AmjKg1d+74P44XaPlGrMeC21oDOSIhjGNEYMAttDMzCzlJO6lpTyJ9JkSinQQF65YcK4eOd3q9iTvULw==}
+    peerDependencies:
+      react: ^18.0.0 || ^19.0.0
+
   strict-event-emitter@0.5.1:
     resolution: {integrity: sha512-vMgjE/GGEPEFnhFub6pa4FmJBRBVOLpIII2hvCZ8Kzb7K0hlHo7mQv6xYrBvCL2LtAIBwFUK8wvuJgTVSQ5MFQ==}
 
@@ -7417,6 +7876,9 @@ packages:
       babel-plugin-macros:
         optional: true
 
+  stylis@4.3.6:
+    resolution: {integrity: sha512-yQ3rwFWRfwNUY7H5vpU0wfdkNSnvnJinhF9830Swlaxl03zsOjCfmX0ugac+3LtK0lYSgwL/KXc8oYL3mG4YFQ==}
+
   sucrase@3.35.1:
     resolution: {integrity: sha512-DhuTmvZWux4H1UOnWMB3sk0sbaCVOoQZjv8u1rDoTV0HTdGem9hkAZtl4JZy8P2z4Bg0nT+YMeOFyVr4zcG5Tw==}
     engines: {node: '>=16 || 14 >=14.17'}
@@ -7438,12 +7900,20 @@ packages:
     resolution: {integrity: sha512-upi/0ZGkYgEcLeGieoz8gT74oWHA0E7JivX7aN9mAf+Tc7BQoRBvnIGHoPDw+f9TXTW4s6kGYCZJtauP6OYp7g==}
     hasBin: true
 
+  swr@2.3.8:
+    resolution: {integrity: sha512-gaCPRVoMq8WGDcWj9p4YWzCMPHzE0WNl6W8ADIx9c3JBEIdMkJGMzW+uzXvxHMltwcYACr9jP+32H8/hgwMR7w==}
+    peerDependencies:
+      react: ^16.11.0 || ^17.0.0 || ^18.0.0 || ^19.0.0
+
   symbol-tree@3.2.4:
     resolution: {integrity: sha512-9QNk5KwDF+Bvz+PyObkmSYjI5ksVUYtjW7AU22r2NKcfLJcXp96hkDWU3+XndOsUb+AQ9QhfzfCT2O+CNWT5Tw==}
 
   tailwind-merge@2.6.0:
     resolution: {integrity: sha512-P+Vu1qXfzediirmHOC3xKGAYeZtPcV9g76X+xg2FD4tYgR71ewMA35Y3sCz3zhiN/dwefRpJX0yBcgwi1fXNQA==}
 
+  tailwind-merge@3.4.0:
+    resolution: {integrity: sha512-uSaO4gnW+b3Y2aWoWfFpX62vn2sR3skfhbjsEnaBI81WD1wBLlHZe5sWf0AqjksNdYTbGBEd0UasQMT3SNV15g==}
+
   tailwind-scrollbar@3.1.0:
     resolution: {integrity: sha512-pmrtDIZeHyu2idTejfV59SbaJyvp1VRjYxAjZBH0jnyrPRo6HL1kD5Glz8VPagasqr6oAx6M05+Tuw429Z8jxg==}
     engines: {node: '>=12.13.0'}
@@ -7498,6 +7968,10 @@ packages:
   third-party-capital@1.0.20:
     resolution: {integrity: sha512-oB7yIimd8SuGptespDAZnNkzIz+NWaJCu2RMsbs4Wmp9zSDUM8Nhi3s2OOcqYuv3mN4hitXc8DVx+LyUmbUDiA==}
 
+  throttleit@2.1.0:
+    resolution: {integrity: sha512-nt6AMGKW1p/70DF/hGBdJB57B8Tspmbp5gfJ8ilhLnt7kkr2ye7hzD6NVG8GGErk2HWF34igrL2CXmNIkzKqKw==}
+    engines: {node: '>=18'}
+
   timers-browserify@2.0.12:
     resolution: {integrity: sha512-9phl76Cqm6FhSX9Xe1ZUAMLtm1BLkKj2Qd5ApyWkXzsMRaA7dgr81kf4wJmQf/hAvg8EEyJxDo3du/0KlhPiKQ==}
     engines: {node: '>=0.6.0'}
@@ -7680,6 +8154,9 @@ packages:
   uc.micro@2.1.0:
     resolution: {integrity: sha512-ARDJmphmdvUk6Glw7y9DQ2bFkKBHwQHLi2lsaH6PPmz/Ka9sFOBsBluozhDltWmnv9u/cF6Rt87znRTPV+yp/A==}
 
+  ufo@1.6.3:
+    resolution: {integrity: sha512-yDJTmhydvl5lJzBmy/hyOAA0d+aqCBuwl818haVdYCRrWV84o7YyeVm4QlVHStqNrrJSTb6jKuFAVqAFsr+K3Q==}
+
   unbox-primitive@1.1.0:
     resolution: {integrity: sha512-nWJ91DjeOkej/TA8pXQ3myruKpKEYgqvpw9lz4OPHj/NWFNluYrjbz9j01CJ8yKQd2g4jFoOkINCTW2I5LEEyw==}
     engines: {node: '>= 0.4'}
@@ -7784,6 +8261,11 @@ packages:
       '@types/react':
         optional: true
 
+  use-stick-to-bottom@1.1.2:
+    resolution: {integrity: sha512-ssUfMNvfH8a8hGLoAt5kcOsjbsVORknon2tbkECuf3EsVucFFBbyXl+Xnv3b58P8ZRuZelzO81fgb6M0eRo8cg==}
+    peerDependencies:
+      react: ^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0
+
   use-sync-external-store@1.6.0:
     resolution: {integrity: sha512-Pp6GSwGP/NrPIrxVFAIkOQeyw8lFenOHijQWkUTrDvrF4ALqylP2C/KCkeS9dpUM3KvYRQhna5vt7IL95+ZQ9w==}
     peerDependencies:
@@ -7921,6 +8403,26 @@ packages:
   vm-browserify@1.1.2:
     resolution: {integrity: sha512-2ham8XPWTONajOR0ohOKOHXkm3+gaBmGut3SRuu75xLd/RRaY6vqgh8NBYYk7+RW3u5AtzPQZG8F10LHkl0lAQ==}
 
+  vscode-jsonrpc@8.2.0:
+    resolution: {integrity: sha512-C+r0eKJUIfiDIfwJhria30+TYWPtuHJXHtI7J0YlOmKAo7ogxP20T0zxB7HZQIFhIyvoBPwWskjxrvAtfjyZfA==}
+    engines: {node: '>=14.0.0'}
+
+  vscode-languageserver-protocol@3.17.5:
+    resolution: {integrity: sha512-mb1bvRJN8SVznADSGWM9u/b07H7Ecg0I3OgXDuLdn307rl/J3A9YD6/eYOssqhecL27hK1IPZAsaqh00i/Jljg==}
+
+  vscode-languageserver-textdocument@1.0.12:
+    resolution: {integrity: sha512-cxWNPesCnQCcMPeenjKKsOCKQZ/L6Tv19DTRIGuLWe32lyzWhihGVJ/rcckZXJxfdKCFvRLS3fpBIsV/ZGX4zA==}
+
+  vscode-languageserver-types@3.17.5:
+    resolution: {integrity: sha512-Ld1VelNuX9pdF39h2Hgaeb5hEZM2Z3jUrrMgWQAu82jMtZp7p3vJT3BzToKtZI7NgQssZje5o0zryOrhQvzQAg==}
+
+  vscode-languageserver@9.0.1:
+    resolution: {integrity: sha512-woByF3PDpkHFUreUa7Hos7+pUWdeWMXRd26+ZX2A8cFx6v/JPTtd4/uN0/jB6XQHYaOlHbio03NTHCqrgG5n7g==}
+    hasBin: true
+
+  vscode-uri@3.0.8:
+    resolution: {integrity: sha512-AyFQ0EVmsOZOlAnxoFOGOq1SQDWAB7C6aqMGS23svWAllfOaxbuFvcT8D1i8z3Gyn8fraVeZNNmN6e9bxxXkKw==}
+
   w3c-xmlserializer@5.0.0:
     resolution: {integrity: sha512-o8qghlI8NZHU1lLPrpi2+Uq7abh4GGPpYANlalzWxyWteJOCsr/P+oPBA49TOLu5FTZO4d3F9MnWJfiMo4BkmA==}
     engines: {node: '>=18'}
@@ -8150,8 +8652,41 @@ snapshots:
 
   '@adobe/css-tools@4.4.4': {}
 
+  '@ai-sdk/gateway@3.0.27(zod@3.25.76)':
+    dependencies:
+      '@ai-sdk/provider': 3.0.5
+      '@ai-sdk/provider-utils': 4.0.10(zod@3.25.76)
+      '@vercel/oidc': 3.1.0
+      zod: 3.25.76
+
+  '@ai-sdk/provider-utils@4.0.10(zod@3.25.76)':
+    dependencies:
+      '@ai-sdk/provider': 3.0.5
+      '@standard-schema/spec': 1.1.0
+      eventsource-parser: 3.0.6
+      zod: 3.25.76
+
+  '@ai-sdk/provider@3.0.5':
+    dependencies:
+      json-schema: 0.4.0
+
+  '@ai-sdk/react@3.0.61(react@18.3.1)(zod@3.25.76)':
+    dependencies:
+      '@ai-sdk/provider-utils': 4.0.10(zod@3.25.76)
+      ai: 6.0.59(zod@3.25.76)
+      react: 18.3.1
+      swr: 2.3.8(react@18.3.1)
+      throttleit: 2.1.0
+    transitivePeerDependencies:
+      - zod
+
   '@alloc/quick-lru@5.2.0': {}
 
+  '@antfu/install-pkg@1.1.0':
+    dependencies:
+      package-manager-detector: 1.6.0
+      tinyexec: 1.0.2
+
   '@apidevtools/json-schema-ref-parser@14.0.1':
     dependencies:
       '@types/json-schema': 7.0.15
@@ -8965,6 +9500,25 @@ snapshots:
       '@babel/helper-string-parser': 7.27.1
       '@babel/helper-validator-identifier': 7.28.5
 
+  '@braintree/sanitize-url@7.1.2': {}
+
+  '@chevrotain/cst-dts-gen@11.0.3':
+    dependencies:
+      '@chevrotain/gast': 11.0.3
+      '@chevrotain/types': 11.0.3
+      lodash-es: 4.17.23
+
+  '@chevrotain/gast@11.0.3':
+    dependencies:
+      '@chevrotain/types': 11.0.3
+      lodash-es: 4.17.23
+
+  '@chevrotain/regexp-to-ast@11.0.3': {}
+
+  '@chevrotain/types@11.0.3': {}
+
+  '@chevrotain/utils@11.0.3': {}
+
   '@chromatic-com/storybook@4.1.2(storybook@9.1.5(@testing-library/dom@10.4.1)(msw@2.11.6(@types/node@24.10.0)(typescript@5.9.3))(prettier@3.6.2)(vite@7.3.1(@types/node@24.10.0)(jiti@2.6.1)(terser@5.44.1)(yaml@2.8.2)))':
     dependencies:
       '@neoconfetti/react': 1.0.0
@@ -9284,6 +9838,14 @@ snapshots:
     transitivePeerDependencies:
       - encoding
 
+  '@iconify/types@2.0.0': {}
+
+  '@iconify/utils@3.1.0':
+    dependencies:
+      '@antfu/install-pkg': 1.1.0
+      '@iconify/types': 2.0.0
+      mlly: 1.8.0
+
   '@img/colour@1.0.0':
     optional: true
 
@@ -9460,6 +10022,10 @@ snapshots:
       '@types/react': 18.3.17
       react: 18.3.1
 
+  '@mermaid-js/parser@0.6.3':
+    dependencies:
+      langium: 3.3.1
+
   '@mswjs/interceptors@0.40.0':
     dependencies:
       '@open-draft/deferred-promise': 2.2.0
@@ -10611,7 +11177,7 @@ snapshots:
     dependencies:
       '@rjsf/utils': 6.1.2(react@18.3.1)
       lodash: 4.17.21
-      lodash-es: 4.17.22
+      lodash-es: 4.17.23
       markdown-to-jsx: 8.0.0(react@18.3.1)
       prop-types: 15.8.1
       react: 18.3.1
@@ -10622,7 +11188,7 @@ snapshots:
       fast-uri: 3.1.0
       jsonpointer: 5.0.1
       lodash: 4.17.21
-      lodash-es: 4.17.22
+      lodash-es: 4.17.23
       react: 18.3.1
       react-is: 18.3.1
 
@@ -10632,7 +11198,7 @@ snapshots:
       ajv: 8.17.1
       ajv-formats: 2.1.1(ajv@8.17.1)
       lodash: 4.17.21
-      lodash-es: 4.17.22
+      lodash-es: 4.17.23
 
   '@rolldown/pluginutils@1.0.0-beta.53': {}
 
@@ -10939,6 +11505,19 @@ snapshots:
       - encoding
       - supports-color
 
+  '@shikijs/core@3.21.0':
+    dependencies:
+      '@shikijs/types': 3.21.0
+      '@shikijs/vscode-textmate': 10.0.2
+      '@types/hast': 3.0.4
+      hast-util-to-html: 9.0.5
+
+  '@shikijs/engine-javascript@3.21.0':
+    dependencies:
+      '@shikijs/types': 3.21.0
+      '@shikijs/vscode-textmate': 10.0.2
+      oniguruma-to-es: 4.3.4
+
   '@shikijs/engine-oniguruma@3.21.0':
     dependencies:
       '@shikijs/types': 3.21.0
@@ -11316,6 +11895,37 @@ snapshots:
     optionalDependencies:
       typescript: 5.9.3
 
+  '@streamdown/cjk@1.0.1(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(react@18.3.1)(unified@11.0.5)':
+    dependencies:
+      react: 18.3.1
+      remark-cjk-friendly: 1.2.3(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(unified@11.0.5)
+      remark-cjk-friendly-gfm-strikethrough: 1.2.3(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(unified@11.0.5)
+      unist-util-visit: 5.0.0
+    transitivePeerDependencies:
+      - '@types/mdast'
+      - micromark
+      - micromark-util-types
+      - unified
+
+  '@streamdown/code@1.0.1(react@18.3.1)':
+    dependencies:
+      react: 18.3.1
+      shiki: 3.21.0
+
+  '@streamdown/math@1.0.1(react@18.3.1)':
+    dependencies:
+      katex: 0.16.28
+      react: 18.3.1
+      rehype-katex: 7.0.1
+      remark-math: 6.0.0
+    transitivePeerDependencies:
+      - supports-color
+
+  '@streamdown/mermaid@1.0.1(react@18.3.1)':
+    dependencies:
+      mermaid: 11.12.2
+      react: 18.3.1
+
   '@supabase/auth-js@2.78.0':
     dependencies:
       '@supabase/node-fetch': 2.6.15
@@ -11478,20 +12088,63 @@ snapshots:
 
   '@types/d3-array@3.2.2': {}
 
+  '@types/d3-axis@3.0.6':
+    dependencies:
+      '@types/d3-selection': 3.0.11
+
+  '@types/d3-brush@3.0.6':
+    dependencies:
+      '@types/d3-selection': 3.0.11
+
+  '@types/d3-chord@3.0.6': {}
+
   '@types/d3-color@3.1.3': {}
 
+  '@types/d3-contour@3.0.6':
+    dependencies:
+      '@types/d3-array': 3.2.2
+      '@types/geojson': 7946.0.16
+
+  '@types/d3-delaunay@6.0.4': {}
+
+  '@types/d3-dispatch@3.0.7': {}
+
   '@types/d3-drag@3.0.7':
     dependencies:
       '@types/d3-selection': 3.0.11
 
+  '@types/d3-dsv@3.0.7': {}
+
   '@types/d3-ease@3.0.2': {}
 
+  '@types/d3-fetch@3.0.7':
+    dependencies:
+      '@types/d3-dsv': 3.0.7
+
+  '@types/d3-force@3.0.10': {}
+
+  '@types/d3-format@3.0.4': {}
+
+  '@types/d3-geo@3.1.0':
+    dependencies:
+      '@types/geojson': 7946.0.16
+
+  '@types/d3-hierarchy@3.1.7': {}
+
   '@types/d3-interpolate@3.0.4':
     dependencies:
       '@types/d3-color': 3.1.3
 
   '@types/d3-path@3.1.1': {}
 
+  '@types/d3-polygon@3.0.2': {}
+
+  '@types/d3-quadtree@3.0.6': {}
+
+  '@types/d3-random@3.0.3': {}
+
+  '@types/d3-scale-chromatic@3.1.0': {}
+
   '@types/d3-scale@4.0.9':
     dependencies:
       '@types/d3-time': 3.0.4
@@ -11502,6 +12155,8 @@ snapshots:
     dependencies:
       '@types/d3-path': 3.1.1
 
+  '@types/d3-time-format@4.0.3': {}
+
   '@types/d3-time@3.0.4': {}
 
   '@types/d3-timer@3.0.2': {}
@@ -11515,6 +12170,39 @@ snapshots:
       '@types/d3-interpolate': 3.0.4
       '@types/d3-selection': 3.0.11
 
+  '@types/d3@7.4.3':
+    dependencies:
+      '@types/d3-array': 3.2.2
+      '@types/d3-axis': 3.0.6
+      '@types/d3-brush': 3.0.6
+      '@types/d3-chord': 3.0.6
+      '@types/d3-color': 3.1.3
+      '@types/d3-contour': 3.0.6
+      '@types/d3-delaunay': 6.0.4
+      '@types/d3-dispatch': 3.0.7
+      '@types/d3-drag': 3.0.7
+      '@types/d3-dsv': 3.0.7
+      '@types/d3-ease': 3.0.2
+      '@types/d3-fetch': 3.0.7
+      '@types/d3-force': 3.0.10
+      '@types/d3-format': 3.0.4
+      '@types/d3-geo': 3.1.0
+      '@types/d3-hierarchy': 3.1.7
+      '@types/d3-interpolate': 3.0.4
+      '@types/d3-path': 3.1.1
+      '@types/d3-polygon': 3.0.2
+      '@types/d3-quadtree': 3.0.6
+      '@types/d3-random': 3.0.3
+      '@types/d3-scale': 4.0.9
+      '@types/d3-scale-chromatic': 3.1.0
+      '@types/d3-selection': 3.0.11
+      '@types/d3-shape': 3.1.7
+      '@types/d3-time': 3.0.4
+      '@types/d3-time-format': 4.0.3
+      '@types/d3-timer': 3.0.2
+      '@types/d3-transition': 3.0.9
+      '@types/d3-zoom': 3.0.8
+
   '@types/debug@4.1.12':
     dependencies:
       '@types/ms': 2.1.0
@@ -11543,6 +12231,8 @@ snapshots:
 
   '@types/estree@1.0.8': {}
 
+  '@types/geojson@7946.0.16': {}
+
   '@types/hast@3.0.4':
     dependencies:
       '@types/unist': 3.0.3
@@ -11603,9 +12293,12 @@ snapshots:
     dependencies:
       '@types/react': 18.3.17
 
-  '@types/react-window@1.8.8':
+  '@types/react-window@2.0.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)':
     dependencies:
-      '@types/react': 18.3.17
+      react-window: 2.2.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+    transitivePeerDependencies:
+      - react
+      - react-dom
 
   '@types/react@18.3.17':
     dependencies:
@@ -11796,6 +12489,8 @@ snapshots:
       next: 15.4.10(@babel/core@7.28.5)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
       react: 18.3.1
 
+  '@vercel/oidc@3.1.0': {}
+
   '@vercel/speed-insights@1.2.0(next@15.4.10(@babel/core@7.28.5)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)':
     optionalDependencies:
       next: 15.4.10(@babel/core@7.28.5)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
@@ -12023,6 +12718,14 @@ snapshots:
   agent-base@7.1.4:
     optional: true
 
+  ai@6.0.59(zod@3.25.76):
+    dependencies:
+      '@ai-sdk/gateway': 3.0.27(zod@3.25.76)
+      '@ai-sdk/provider': 3.0.5
+      '@ai-sdk/provider-utils': 4.0.10(zod@3.25.76)
+      '@opentelemetry/api': 1.9.0
+      zod: 3.25.76
+
   ajv-draft-04@1.0.0(ajv@8.17.1):
     optionalDependencies:
       ajv: 8.17.1
@@ -12411,6 +13114,20 @@ snapshots:
 
   check-error@2.1.3: {}
 
+  chevrotain-allstar@0.3.1(chevrotain@11.0.3):
+    dependencies:
+      chevrotain: 11.0.3
+      lodash-es: 4.17.23
+
+  chevrotain@11.0.3:
+    dependencies:
+      '@chevrotain/cst-dts-gen': 11.0.3
+      '@chevrotain/gast': 11.0.3
+      '@chevrotain/regexp-to-ast': 11.0.3
+      '@chevrotain/types': 11.0.3
+      '@chevrotain/utils': 11.0.3
+      lodash-es: 4.17.23
+
   chokidar@3.6.0:
     dependencies:
       anymatch: 3.1.3
@@ -12491,6 +13208,8 @@ snapshots:
 
   commander@4.1.1: {}
 
+  commander@7.2.0: {}
+
   commander@8.3.0: {}
 
   common-path-prefix@3.0.0: {}
@@ -12510,6 +13229,8 @@ snapshots:
       tree-kill: 1.2.2
       yargs: 17.7.2
 
+  confbox@0.1.8: {}
+
   console-browserify@1.2.0: {}
 
   constants-browserify@1.0.0: {}
@@ -12530,6 +13251,14 @@ snapshots:
 
   core-util-is@1.0.3: {}
 
+  cose-base@1.0.3:
+    dependencies:
+      layout-base: 1.0.2
+
+  cose-base@2.2.0:
+    dependencies:
+      layout-base: 2.0.1
+
   cosmiconfig@7.1.0:
     dependencies:
       '@types/parse-json': 4.0.2
@@ -12638,12 +13367,50 @@ snapshots:
 
   csstype@3.2.3: {}
 
+  cytoscape-cose-bilkent@4.1.0(cytoscape@3.33.1):
+    dependencies:
+      cose-base: 1.0.3
+      cytoscape: 3.33.1
+
+  cytoscape-fcose@2.2.0(cytoscape@3.33.1):
+    dependencies:
+      cose-base: 2.2.0
+      cytoscape: 3.33.1
+
+  cytoscape@3.33.1: {}
+
+  d3-array@2.12.1:
+    dependencies:
+      internmap: 1.0.1
+
   d3-array@3.2.4:
     dependencies:
       internmap: 2.0.3
 
+  d3-axis@3.0.0: {}
+
+  d3-brush@3.0.0:
+    dependencies:
+      d3-dispatch: 3.0.1
+      d3-drag: 3.0.0
+      d3-interpolate: 3.0.1
+      d3-selection: 3.0.0
+      d3-transition: 3.0.1(d3-selection@3.0.0)
+
+  d3-chord@3.0.1:
+    dependencies:
+      d3-path: 3.1.0
+
   d3-color@3.1.0: {}
 
+  d3-contour@4.0.2:
+    dependencies:
+      d3-array: 3.2.4
+
+  d3-delaunay@6.0.4:
+    dependencies:
+      delaunator: 5.0.1
+
   d3-dispatch@3.0.1: {}
 
   d3-drag@3.0.0:
@@ -12651,16 +13418,56 @@ snapshots:
       d3-dispatch: 3.0.1
       d3-selection: 3.0.0
 
+  d3-dsv@3.0.1:
+    dependencies:
+      commander: 7.2.0
+      iconv-lite: 0.6.3
+      rw: 1.3.3
+
   d3-ease@3.0.1: {}
 
+  d3-fetch@3.0.1:
+    dependencies:
+      d3-dsv: 3.0.1
+
+  d3-force@3.0.0:
+    dependencies:
+      d3-dispatch: 3.0.1
+      d3-quadtree: 3.0.1
+      d3-timer: 3.0.1
+
   d3-format@3.1.0: {}
 
+  d3-geo@3.1.1:
+    dependencies:
+      d3-array: 3.2.4
+
+  d3-hierarchy@3.1.2: {}
+
   d3-interpolate@3.0.1:
     dependencies:
       d3-color: 3.1.0
 
+  d3-path@1.0.9: {}
+
   d3-path@3.1.0: {}
 
+  d3-polygon@3.0.1: {}
+
+  d3-quadtree@3.0.1: {}
+
+  d3-random@3.0.1: {}
+
+  d3-sankey@0.12.3:
+    dependencies:
+      d3-array: 2.12.1
+      d3-shape: 1.3.7
+
+  d3-scale-chromatic@3.1.0:
+    dependencies:
+      d3-color: 3.1.0
+      d3-interpolate: 3.0.1
+
   d3-scale@4.0.2:
     dependencies:
       d3-array: 3.2.4
@@ -12671,6 +13478,10 @@ snapshots:
 
   d3-selection@3.0.0: {}
 
+  d3-shape@1.3.7:
+    dependencies:
+      d3-path: 1.0.9
+
   d3-shape@3.2.0:
     dependencies:
       d3-path: 3.1.0
@@ -12702,6 +13513,44 @@ snapshots:
       d3-selection: 3.0.0
       d3-transition: 3.0.1(d3-selection@3.0.0)
 
+  d3@7.9.0:
+    dependencies:
+      d3-array: 3.2.4
+      d3-axis: 3.0.0
+      d3-brush: 3.0.0
+      d3-chord: 3.0.1
+      d3-color: 3.1.0
+      d3-contour: 4.0.2
+      d3-delaunay: 6.0.4
+      d3-dispatch: 3.0.1
+      d3-drag: 3.0.0
+      d3-dsv: 3.0.1
+      d3-ease: 3.0.1
+      d3-fetch: 3.0.1
+      d3-force: 3.0.0
+      d3-format: 3.1.0
+      d3-geo: 3.1.1
+      d3-hierarchy: 3.1.2
+      d3-interpolate: 3.0.1
+      d3-path: 3.1.0
+      d3-polygon: 3.0.1
+      d3-quadtree: 3.0.1
+      d3-random: 3.0.1
+      d3-scale: 4.0.2
+      d3-scale-chromatic: 3.1.0
+      d3-selection: 3.0.0
+      d3-shape: 3.2.0
+      d3-time: 3.1.0
+      d3-time-format: 4.1.0
+      d3-timer: 3.0.1
+      d3-transition: 3.0.1(d3-selection@3.0.0)
+      d3-zoom: 3.0.0
+
+  dagre-d3-es@7.0.13:
+    dependencies:
+      d3: 7.9.0
+      lodash-es: 4.17.23
+
   damerau-levenshtein@1.0.8: {}
 
   data-urls@6.0.1:
@@ -12732,6 +13581,8 @@ snapshots:
 
   date-fns@4.1.0: {}
 
+  dayjs@1.11.19: {}
+
   debug@3.2.7:
     dependencies:
       ms: 2.1.3
@@ -12773,6 +13624,10 @@ snapshots:
       has-property-descriptors: 1.0.2
       object-keys: 1.1.1
 
+  delaunator@5.0.1:
+    dependencies:
+      robust-predicates: 3.0.2
+
   dependency-graph@0.11.0: {}
 
   dequal@2.0.3: {}
@@ -13347,6 +14202,8 @@ snapshots:
 
   events@3.3.0: {}
 
+  eventsource-parser@3.0.6: {}
+
   evp_bytestokey@1.0.3:
     dependencies:
       md5.js: 1.3.5
@@ -13553,6 +14410,8 @@ snapshots:
 
   get-caller-file@2.0.5: {}
 
+  get-east-asian-width@1.4.0: {}
+
   get-intrinsic@1.3.0:
     dependencies:
       call-bind-apply-helpers: 1.0.2
@@ -13643,6 +14502,8 @@ snapshots:
 
   graphql@16.12.0: {}
 
+  hachure-fill@0.5.2: {}
+
   happy-dom@20.3.4:
     dependencies:
       '@types/node': 24.10.0
@@ -13739,6 +14600,42 @@ snapshots:
     dependencies:
       '@types/hast': 3.0.4
 
+  hast-util-raw@9.1.0:
+    dependencies:
+      '@types/hast': 3.0.4
+      '@types/unist': 3.0.3
+      '@ungap/structured-clone': 1.3.0
+      hast-util-from-parse5: 8.0.3
+      hast-util-to-parse5: 8.0.1
+      html-void-elements: 3.0.0
+      mdast-util-to-hast: 13.2.1
+      parse5: 7.3.0
+      unist-util-position: 5.0.0
+      unist-util-visit: 5.0.0
+      vfile: 6.0.3
+      web-namespaces: 2.0.1
+      zwitch: 2.0.4
+
+  hast-util-sanitize@5.0.2:
+    dependencies:
+      '@types/hast': 3.0.4
+      '@ungap/structured-clone': 1.3.0
+      unist-util-position: 5.0.0
+
+  hast-util-to-html@9.0.5:
+    dependencies:
+      '@types/hast': 3.0.4
+      '@types/unist': 3.0.3
+      ccount: 2.0.1
+      comma-separated-tokens: 2.0.3
+      hast-util-whitespace: 3.0.0
+      html-void-elements: 3.0.0
+      mdast-util-to-hast: 13.2.1
+      property-information: 7.1.0
+      space-separated-tokens: 2.0.2
+      stringify-entities: 4.0.4
+      zwitch: 2.0.4
+
   hast-util-to-jsx-runtime@2.3.6:
     dependencies:
       '@types/estree': 1.0.8
@@ -13759,6 +14656,16 @@ snapshots:
     transitivePeerDependencies:
       - supports-color
 
+  hast-util-to-parse5@8.0.1:
+    dependencies:
+      '@types/hast': 3.0.4
+      comma-separated-tokens: 2.0.3
+      devlop: 1.1.0
+      property-information: 7.1.0
+      space-separated-tokens: 2.0.2
+      web-namespaces: 2.0.1
+      zwitch: 2.0.4
+
   hast-util-to-string@3.0.1:
     dependencies:
       '@types/hast': 3.0.4
@@ -13819,6 +14726,8 @@ snapshots:
 
   html-url-attributes@3.0.1: {}
 
+  html-void-elements@3.0.0: {}
+
   html-webpack-plugin@5.6.5(webpack@5.104.1(esbuild@0.25.12)):
     dependencies:
       '@types/html-minifier-terser': 6.1.0
@@ -13865,6 +14774,10 @@ snapshots:
 
   human-signals@2.1.0: {}
 
+  iconv-lite@0.6.3:
+    dependencies:
+      safer-buffer: 2.1.2
+
   icss-utils@5.1.0(postcss@8.5.6):
     dependencies:
       postcss: 8.5.6
@@ -13916,6 +14829,8 @@ snapshots:
       hasown: 2.0.2
       side-channel: 1.1.0
 
+  internmap@1.0.1: {}
+
   internmap@2.0.3: {}
 
   is-alphabetical@2.0.1: {}
@@ -14164,6 +15079,8 @@ snapshots:
 
   json-schema-traverse@1.0.0: {}
 
+  json-schema@0.4.0: {}
+
   json-stable-stringify-without-jsonify@1.0.1: {}
 
   json5@1.0.2:
@@ -14207,10 +15124,24 @@ snapshots:
     dependencies:
       commander: 8.3.0
 
+  katex@0.16.28:
+    dependencies:
+      commander: 8.3.0
+
   keyv@4.5.4:
     dependencies:
       json-buffer: 3.0.1
 
+  khroma@2.1.0: {}
+
+  langium@3.3.1:
+    dependencies:
+      chevrotain: 11.0.3
+      chevrotain-allstar: 0.3.1(chevrotain@11.0.3)
+      vscode-languageserver: 9.0.1
+      vscode-languageserver-textdocument: 1.0.12
+      vscode-uri: 3.0.8
+
   language-subtag-registry@0.3.23: {}
 
   language-tags@1.0.9:
@@ -14236,6 +15167,10 @@ snapshots:
       react: 18.3.1
       react-dom: 18.3.1(react@18.3.1)
 
+  layout-base@1.0.2: {}
+
+  layout-base@2.0.1: {}
+
   leven@3.1.0: {}
 
   levn@0.4.1:
@@ -14273,7 +15208,7 @@ snapshots:
     dependencies:
       p-locate: 6.0.0
 
-  lodash-es@4.17.22: {}
+  lodash-es@4.17.23: {}
 
   lodash.camelcase@4.3.0: {}
 
@@ -14363,6 +15298,10 @@ snapshots:
     optionalDependencies:
       react: 18.3.1
 
+  marked@16.4.2: {}
+
+  marked@17.0.1: {}
+
   math-intrinsics@1.1.0: {}
 
   md5.js@1.3.5:
@@ -14545,12 +15484,33 @@ snapshots:
     dependencies:
       fs-monkey: 1.1.0
 
-  memoize-one@5.2.1: {}
-
   merge-stream@2.0.0: {}
 
   merge2@1.4.1: {}
 
+  mermaid@11.12.2:
+    dependencies:
+      '@braintree/sanitize-url': 7.1.2
+      '@iconify/utils': 3.1.0
+      '@mermaid-js/parser': 0.6.3
+      '@types/d3': 7.4.3
+      cytoscape: 3.33.1
+      cytoscape-cose-bilkent: 4.1.0(cytoscape@3.33.1)
+      cytoscape-fcose: 2.2.0(cytoscape@3.33.1)
+      d3: 7.9.0
+      d3-sankey: 0.12.3
+      dagre-d3-es: 7.0.13
+      dayjs: 1.11.19
+      dompurify: 3.3.1
+      katex: 0.16.25
+      khroma: 2.1.0
+      lodash-es: 4.17.23
+      marked: 16.4.2
+      roughjs: 4.6.6
+      stylis: 4.3.6
+      ts-dedent: 2.2.0
+      uuid: 11.1.0
+
   micromark-core-commonmark@2.0.3:
     dependencies:
       decode-named-character-reference: 1.2.0
@@ -14570,6 +15530,38 @@ snapshots:
       micromark-util-symbol: 2.0.1
       micromark-util-types: 2.0.2
 
+  micromark-extension-cjk-friendly-gfm-strikethrough@1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2):
+    dependencies:
+      devlop: 1.1.0
+      get-east-asian-width: 1.4.0
+      micromark: 4.0.2
+      micromark-extension-cjk-friendly-util: 2.1.1(micromark-util-types@2.0.2)
+      micromark-util-character: 2.1.1
+      micromark-util-chunked: 2.0.1
+      micromark-util-resolve-all: 2.0.1
+      micromark-util-symbol: 2.0.1
+    optionalDependencies:
+      micromark-util-types: 2.0.2
+
+  micromark-extension-cjk-friendly-util@2.1.1(micromark-util-types@2.0.2):
+    dependencies:
+      get-east-asian-width: 1.4.0
+      micromark-util-character: 2.1.1
+      micromark-util-symbol: 2.0.1
+    optionalDependencies:
+      micromark-util-types: 2.0.2
+
+  micromark-extension-cjk-friendly@1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2):
+    dependencies:
+      devlop: 1.1.0
+      micromark: 4.0.2
+      micromark-extension-cjk-friendly-util: 2.1.1(micromark-util-types@2.0.2)
+      micromark-util-chunked: 2.0.1
+      micromark-util-resolve-all: 2.0.1
+      micromark-util-symbol: 2.0.1
+    optionalDependencies:
+      micromark-util-types: 2.0.2
+
   micromark-extension-gfm-autolink-literal@2.1.0:
     dependencies:
       micromark-util-character: 2.1.1
@@ -14792,9 +15784,14 @@ snapshots:
 
   minipass@7.1.2: {}
 
-  module-details-from-path@1.0.4: {}
+  mlly@1.8.0:
+    dependencies:
+      acorn: 8.15.0
+      pathe: 2.0.3
+      pkg-types: 1.3.1
+      ufo: 1.6.3
 
-  moment@2.30.1: {}
+  module-details-from-path@1.0.4: {}
 
   motion-dom@12.24.8:
     dependencies:
@@ -15051,6 +16048,14 @@ snapshots:
     dependencies:
       mimic-fn: 2.1.0
 
+  oniguruma-parser@0.12.1: {}
+
+  oniguruma-to-es@4.3.4:
+    dependencies:
+      oniguruma-parser: 0.12.1
+      regex: 6.1.0
+      regex-recursion: 6.0.2
+
   open@8.4.2:
     dependencies:
       define-lazy-prop: 2.0.0
@@ -15145,6 +16150,8 @@ snapshots:
 
   package-json-from-dist@1.0.1: {}
 
+  package-manager-detector@1.6.0: {}
+
   pako@1.0.11: {}
 
   param-case@3.0.4:
@@ -15199,6 +16206,8 @@ snapshots:
 
   path-browserify@1.0.1: {}
 
+  path-data-parser@0.1.0: {}
+
   path-exists@4.0.0: {}
 
   path-exists@5.0.0: {}
@@ -15261,6 +16270,12 @@ snapshots:
     dependencies:
       find-up: 6.3.0
 
+  pkg-types@1.3.1:
+    dependencies:
+      confbox: 0.1.8
+      mlly: 1.8.0
+      pathe: 2.0.3
+
   playwright-core@1.56.1: {}
 
   playwright@1.56.1:
@@ -15269,6 +16284,13 @@ snapshots:
     optionalDependencies:
       fsevents: 2.3.2
 
+  points-on-curve@0.2.0: {}
+
+  points-on-path@0.2.1:
+    dependencies:
+      path-data-parser: 0.1.0
+      points-on-curve: 0.2.0
+
   pony-cause@1.1.1: {}
 
   possible-typed-array-names@1.1.0: {}
@@ -15592,10 +16614,8 @@ snapshots:
     optionalDependencies:
       '@types/react': 18.3.17
 
-  react-window@1.8.11(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
+  react-window@2.2.0(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
     dependencies:
-      '@babel/runtime': 7.28.4
-      memoize-one: 5.2.1
       react: 18.3.1
       react-dom: 18.3.1(react@18.3.1)
 
@@ -15697,6 +16717,16 @@ snapshots:
 
   regex-parser@2.3.1: {}
 
+  regex-recursion@6.0.2:
+    dependencies:
+      regex-utilities: 2.3.0
+
+  regex-utilities@2.3.0: {}
+
+  regex@6.1.0:
+    dependencies:
+      regex-utilities: 2.3.0
+
   regexp.prototype.flags@1.5.4:
     dependencies:
       call-bind: 1.0.8
@@ -15730,6 +16760,10 @@ snapshots:
       unified: 11.0.5
       unist-util-visit: 5.0.0
 
+  rehype-harden@1.1.7:
+    dependencies:
+      unist-util-visit: 5.0.0
+
   rehype-highlight@7.0.2:
     dependencies:
       '@types/hast': 3.0.4
@@ -15748,6 +16782,17 @@ snapshots:
       unist-util-visit-parents: 6.0.2
       vfile: 6.0.3
 
+  rehype-raw@7.0.0:
+    dependencies:
+      '@types/hast': 3.0.4
+      hast-util-raw: 9.1.0
+      vfile: 6.0.3
+
+  rehype-sanitize@6.0.0:
+    dependencies:
+      '@types/hast': 3.0.4
+      hast-util-sanitize: 5.0.2
+
   rehype-slug@6.0.0:
     dependencies:
       '@types/hast': 3.0.4
@@ -15758,6 +16803,26 @@ snapshots:
 
   relateurl@0.2.7: {}
 
+  remark-cjk-friendly-gfm-strikethrough@1.2.3(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(unified@11.0.5):
+    dependencies:
+      micromark-extension-cjk-friendly-gfm-strikethrough: 1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2)
+      unified: 11.0.5
+    optionalDependencies:
+      '@types/mdast': 4.0.4
+    transitivePeerDependencies:
+      - micromark
+      - micromark-util-types
+
+  remark-cjk-friendly@1.2.3(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(unified@11.0.5):
+    dependencies:
+      micromark-extension-cjk-friendly: 1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2)
+      unified: 11.0.5
+    optionalDependencies:
+      '@types/mdast': 4.0.4
+    transitivePeerDependencies:
+      - micromark
+      - micromark-util-types
+
   remark-gfm@4.0.1:
     dependencies:
       '@types/mdast': 4.0.4
@@ -15801,6 +16866,8 @@ snapshots:
       mdast-util-to-markdown: 2.1.2
       unified: 11.0.5
 
+  remend@1.1.0: {}
+
   renderkid@3.0.0:
     dependencies:
       css-select: 4.3.0
@@ -15865,6 +16932,8 @@ snapshots:
       hash-base: 3.1.2
       inherits: 2.0.4
 
+  robust-predicates@3.0.2: {}
+
   rollup@4.55.1:
     dependencies:
       '@types/estree': 1.0.8
@@ -15896,10 +16965,19 @@ snapshots:
       '@rollup/rollup-win32-x64-msvc': 4.55.1
       fsevents: 2.3.3
 
+  roughjs@4.6.6:
+    dependencies:
+      hachure-fill: 0.5.2
+      path-data-parser: 0.1.0
+      points-on-curve: 0.2.0
+      points-on-path: 0.2.1
+
   run-parallel@1.2.0:
     dependencies:
       queue-microtask: 1.2.3
 
+  rw@1.3.3: {}
+
   rxjs@7.8.2:
     dependencies:
       tslib: 2.8.1
@@ -15929,6 +17007,8 @@ snapshots:
 
   safe-stable-stringify@1.1.1: {}
 
+  safer-buffer@2.1.2: {}
+
   sass-loader@16.0.6(webpack@5.104.1(esbuild@0.25.12)):
     dependencies:
       neo-async: 2.6.2
@@ -16041,6 +17121,17 @@ snapshots:
       '@scarf/scarf': 1.4.0
       deepmerge-ts: 7.1.5
 
+  shiki@3.21.0:
+    dependencies:
+      '@shikijs/core': 3.21.0
+      '@shikijs/engine-javascript': 3.21.0
+      '@shikijs/engine-oniguruma': 3.21.0
+      '@shikijs/langs': 3.21.0
+      '@shikijs/themes': 3.21.0
+      '@shikijs/types': 3.21.0
+      '@shikijs/vscode-textmate': 10.0.2
+      '@types/hast': 3.0.4
+
   should-equal@2.0.0:
     dependencies:
       should-type: 1.4.0
@@ -16180,6 +17271,26 @@ snapshots:
       readable-stream: 3.6.2
       xtend: 4.0.2
 
+  streamdown@2.1.0(react@18.3.1):
+    dependencies:
+      clsx: 2.1.1
+      hast-util-to-jsx-runtime: 2.3.6
+      html-url-attributes: 3.0.1
+      marked: 17.0.1
+      react: 18.3.1
+      rehype-harden: 1.1.7
+      rehype-raw: 7.0.0
+      rehype-sanitize: 6.0.0
+      remark-gfm: 4.0.1
+      remark-parse: 11.0.0
+      remark-rehype: 11.1.2
+      remend: 1.1.0
+      tailwind-merge: 3.4.0
+      unified: 11.0.5
+      unist-util-visit: 5.0.0
+    transitivePeerDependencies:
+      - supports-color
+
   strict-event-emitter@0.5.1: {}
 
   string-argv@0.3.2: {}
@@ -16305,6 +17416,8 @@ snapshots:
     optionalDependencies:
       '@babel/core': 7.28.5
 
+  stylis@4.3.6: {}
+
   sucrase@3.35.1:
     dependencies:
       '@jridgewell/gen-mapping': 0.3.13
@@ -16341,11 +17454,19 @@ snapshots:
     transitivePeerDependencies:
       - encoding
 
+  swr@2.3.8(react@18.3.1):
+    dependencies:
+      dequal: 2.0.3
+      react: 18.3.1
+      use-sync-external-store: 1.6.0(react@18.3.1)
+
   symbol-tree@3.2.4:
     optional: true
 
   tailwind-merge@2.6.0: {}
 
+  tailwind-merge@3.4.0: {}
+
   tailwind-scrollbar@3.1.0(tailwindcss@3.4.17):
     dependencies:
       tailwindcss: 3.4.17
@@ -16413,6 +17534,8 @@ snapshots:
 
   third-party-capital@1.0.20: {}
 
+  throttleit@2.1.0: {}
+
   timers-browserify@2.0.12:
     dependencies:
       setimmediate: 1.0.5
@@ -16575,6 +17698,8 @@ snapshots:
 
   uc.micro@2.1.0: {}
 
+  ufo@1.6.3: {}
+
   unbox-primitive@1.1.0:
     dependencies:
       call-bound: 1.0.4
@@ -16712,6 +17837,10 @@ snapshots:
     optionalDependencies:
       '@types/react': 18.3.17
 
+  use-stick-to-bottom@1.1.2(react@18.3.1):
+    dependencies:
+      react: 18.3.1
+
   use-sync-external-store@1.6.0(react@18.3.1):
     dependencies:
       react: 18.3.1
@@ -16847,6 +17976,23 @@ snapshots:
 
   vm-browserify@1.1.2: {}
 
+  vscode-jsonrpc@8.2.0: {}
+
+  vscode-languageserver-protocol@3.17.5:
+    dependencies:
+      vscode-jsonrpc: 8.2.0
+      vscode-languageserver-types: 3.17.5
+
+  vscode-languageserver-textdocument@1.0.12: {}
+
+  vscode-languageserver-types@3.17.5: {}
+
+  vscode-languageserver@9.0.1:
+    dependencies:
+      vscode-languageserver-protocol: 3.17.5
+
+  vscode-uri@3.0.8: {}
+
   w3c-xmlserializer@5.0.0:
     dependencies:
       xml-name-validator: 5.0.0
diff --git a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/AgentOnboardingCredentials.tsx b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/AgentOnboardingCredentials.tsx
index f0bb652a06..a8efa344a2 100644
--- a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/AgentOnboardingCredentials.tsx
+++ b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/AgentOnboardingCredentials.tsx
@@ -1,5 +1,5 @@
 import { CredentialsMetaInput } from "@/app/api/__generated__/models/credentialsMetaInput";
-import { GraphMeta } from "@/app/api/__generated__/models/graphMeta";
+import { GraphModel } from "@/app/api/__generated__/models/graphModel";
 import { CredentialsInput } from "@/components/contextual/CredentialsInput/CredentialsInput";
 import { useState } from "react";
 import { getSchemaDefaultCredentials } from "../../helpers";
@@ -9,7 +9,7 @@ type Credential = CredentialsMetaInput | undefined;
 type Credentials = Record<string, Credential>;
 
 type Props = {
-  agent: GraphMeta | null;
+  agent: GraphModel | null;
   siblingInputs?: Record<string, any>;
   onCredentialsChange: (
     credentials: Record<string, CredentialsMetaInput>,
diff --git a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/helpers.ts b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/helpers.ts
index 7a456d63e4..a4947015c4 100644
--- a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/helpers.ts
+++ b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/components/AgentOnboardingCredentials/helpers.ts
@@ -1,9 +1,9 @@
 import { CredentialsMetaInput } from "@/app/api/__generated__/models/credentialsMetaInput";
-import { GraphMeta } from "@/app/api/__generated__/models/graphMeta";
+import { GraphModel } from "@/app/api/__generated__/models/graphModel";
 import { BlockIOCredentialsSubSchema } from "@/lib/autogpt-server-api/types";
 
 export function getCredentialFields(
-  agent: GraphMeta | null,
+  agent: GraphModel | null,
 ): AgentCredentialsFields {
   if (!agent) return {};
 
diff --git a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/helpers.ts b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/helpers.ts
index 62f5c564ff..ff1f8d452c 100644
--- a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/helpers.ts
+++ b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/5-run/helpers.ts
@@ -3,10 +3,10 @@ import type {
   CredentialsMetaInput,
 } from "@/lib/autogpt-server-api/types";
 import type { InputValues } from "./types";
-import { GraphMeta } from "@/app/api/__generated__/models/graphMeta";
+import { GraphModel } from "@/app/api/__generated__/models/graphModel";
 
 export function computeInitialAgentInputs(
-  agent: GraphMeta | null,
+  agent: GraphModel | null,
   existingInputs?: InputValues | null,
 ): InputValues {
   const properties = agent?.input_schema?.properties || {};
@@ -29,7 +29,7 @@ export function computeInitialAgentInputs(
 }
 
 type IsRunDisabledParams = {
-  agent: GraphMeta | null;
+  agent: GraphModel | null;
   isRunning: boolean;
   agentInputs: InputValues | null | undefined;
 };
diff --git a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/page.tsx b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/page.tsx
index 70d9783ccd..246fe52826 100644
--- a/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/page.tsx
+++ b/autogpt_platform/frontend/src/app/(no-navbar)/onboarding/page.tsx
@@ -1,10 +1,9 @@
 "use client";
+import { getV1OnboardingState } from "@/app/api/__generated__/endpoints/onboarding/onboarding";
+import { getOnboardingStatus, resolveResponse } from "@/app/api/helpers";
 import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { useRouter } from "next/navigation";
 import { useEffect } from "react";
-import { resolveResponse, getOnboardingStatus } from "@/app/api/helpers";
-import { getV1OnboardingState } from "@/app/api/__generated__/endpoints/onboarding/onboarding";
-import { getHomepageRoute } from "@/lib/constants";
 
 export default function OnboardingPage() {
   const router = useRouter();
@@ -13,12 +12,10 @@ export default function OnboardingPage() {
     async function redirectToStep() {
       try {
         // Check if onboarding is enabled (also gets chat flag for redirect)
-        const { shouldShowOnboarding, isChatEnabled } =
-          await getOnboardingStatus();
-        const homepageRoute = getHomepageRoute(isChatEnabled);
+        const { shouldShowOnboarding } = await getOnboardingStatus();
 
         if (!shouldShowOnboarding) {
-          router.replace(homepageRoute);
+          router.replace("/");
           return;
         }
 
@@ -26,7 +23,7 @@ export default function OnboardingPage() {
 
         // Handle completed onboarding
         if (onboarding.completedSteps.includes("GET_RESULTS")) {
-          router.replace(homepageRoute);
+          router.replace("/");
           return;
         }
 
diff --git a/autogpt_platform/frontend/src/app/(platform)/auth/callback/route.ts b/autogpt_platform/frontend/src/app/(platform)/auth/callback/route.ts
index 15be137f63..e7e2997d0d 100644
--- a/autogpt_platform/frontend/src/app/(platform)/auth/callback/route.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/auth/callback/route.ts
@@ -1,9 +1,8 @@
-import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
-import { getHomepageRoute } from "@/lib/constants";
-import BackendAPI from "@/lib/autogpt-server-api";
-import { NextResponse } from "next/server";
-import { revalidatePath } from "next/cache";
 import { getOnboardingStatus } from "@/app/api/helpers";
+import BackendAPI from "@/lib/autogpt-server-api";
+import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
+import { revalidatePath } from "next/cache";
+import { NextResponse } from "next/server";
 
 // Handle the callback to complete the user session login
 export async function GET(request: Request) {
@@ -27,13 +26,12 @@ export async function GET(request: Request) {
         await api.createUser();
 
         // Get onboarding status from backend (includes chat flag evaluated for this user)
-        const { shouldShowOnboarding, isChatEnabled } =
-          await getOnboardingStatus();
+        const { shouldShowOnboarding } = await getOnboardingStatus();
         if (shouldShowOnboarding) {
           next = "/onboarding";
           revalidatePath("/onboarding", "layout");
         } else {
-          next = getHomepageRoute(isChatEnabled);
+          next = "/";
           revalidatePath(next, "layout");
         }
       } catch (createUserError) {
diff --git a/autogpt_platform/frontend/src/app/(platform)/auth/integrations/oauth_callback/route.ts b/autogpt_platform/frontend/src/app/(platform)/auth/integrations/oauth_callback/route.ts
index 41d05a9afb..fd67519957 100644
--- a/autogpt_platform/frontend/src/app/(platform)/auth/integrations/oauth_callback/route.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/auth/integrations/oauth_callback/route.ts
@@ -1,6 +1,17 @@
 import { OAuthPopupResultMessage } from "./types";
 import { NextResponse } from "next/server";
 
+/**
+ * Safely encode a value as JSON for embedding in a script tag.
+ * Escapes characters that could break out of the script context to prevent XSS.
+ */
+function safeJsonStringify(value: unknown): string {
+  return JSON.stringify(value)
+    .replace(/</g, "\\u003c")
+    .replace(/>/g, "\\u003e")
+    .replace(/&/g, "\\u0026");
+}
+
 // This route is intended to be used as the callback for integration OAuth flows,
 // controlled by the CredentialsInput component. The CredentialsInput opens the login
 // page in a pop-up window, which then redirects to this route to close the loop.
@@ -23,12 +34,13 @@ export async function GET(request: Request) {
   console.debug("Sending message to opener:", message);
 
   // Return a response with the message as JSON and a script to close the window
+  // Use safeJsonStringify to prevent XSS by escaping <, >, and & characters
   return new NextResponse(
     `
     <html>
       <body>
         <script>
-          window.opener.postMessage(${JSON.stringify(message)});
+          window.opener.postMessage(${safeJsonStringify(message)});
           window.close();
         </script>
       </body>
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts
index ab1af16584..e98d240215 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts
@@ -1,4 +1,4 @@
-import { debounce } from "lodash";
+import debounce from "lodash/debounce";
 import { useCallback, useEffect, useRef, useState } from "react";
 import { useBlockMenuStore } from "../../../../stores/blockMenuStore";
 import { getQueryClient } from "@/lib/react-query/queryClient";
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx
index 0f953394e6..bee0b85721 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx
@@ -70,10 +70,10 @@ export const HorizontalScroll: React.FC<HorizontalScrollAreaProps> = ({
           {children}
         </div>
         {canScrollLeft && (
-          <div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-white via-white/80 to-white/0" />
+          <div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-background via-background/80 to-background/0" />
         )}
         {canScrollRight && (
-          <div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-white via-white/80 to-white/0" />
+          <div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-background via-background/80 to-background/0" />
         )}
         {canScrollLeft && (
           <button
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/BlocksControl.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/BlocksControl.tsx
index f5451e6d4d..99b66fe1dc 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/BlocksControl.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/BlocksControl.tsx
@@ -30,6 +30,8 @@ import {
 } from "@/components/atoms/Tooltip/BaseTooltip";
 import { GraphMeta } from "@/lib/autogpt-server-api";
 import jaro from "jaro-winkler";
+import { getV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
+import { okData } from "@/app/api/helpers";
 
 type _Block = Omit<Block, "inputSchema" | "outputSchema"> & {
   uiKey?: string;
@@ -107,6 +109,8 @@ export function BlocksControl({
       .filter((b) => b.uiType !== BlockUIType.AGENT)
       .sort((a, b) => a.name.localeCompare(b.name));
 
+    // Agent blocks are created from GraphMeta which doesn't include schemas.
+    // Schemas will be fetched on-demand when the block is actually added.
     const agentBlockList = flows
       .map((flow): _Block => {
         return {
@@ -116,8 +120,9 @@ export function BlocksControl({
             `Ver.${flow.version}` +
             (flow.description ? ` | ${flow.description}` : ""),
           categories: [{ category: "AGENT", description: "" }],
-          inputSchema: flow.input_schema,
-          outputSchema: flow.output_schema,
+          // Empty schemas - will be populated when block is added
+          inputSchema: { type: "object", properties: {} },
+          outputSchema: { type: "object", properties: {} },
           staticOutput: false,
           uiType: BlockUIType.AGENT,
           costs: [],
@@ -125,8 +130,7 @@ export function BlocksControl({
           hardcodedValues: {
             graph_id: flow.id,
             graph_version: flow.version,
-            input_schema: flow.input_schema,
-            output_schema: flow.output_schema,
+            // Schemas will be fetched on-demand when block is added
           },
         };
       })
@@ -182,6 +186,37 @@ export function BlocksControl({
     setSelectedCategory(null);
   }, []);
 
+  // Handler to add a block, fetching graph data on-demand for agent blocks
+  const handleAddBlock = useCallback(
+    async (block: _Block & { notAvailable: string | null }) => {
+      if (block.notAvailable) return;
+
+      // For agent blocks, fetch the full graph to get schemas
+      if (block.uiType === BlockUIType.AGENT && block.hardcodedValues) {
+        const graphID = block.hardcodedValues.graph_id as string;
+        const graphVersion = block.hardcodedValues.graph_version as number;
+        const graphData = okData(
+          await getV1GetSpecificGraph(graphID, { version: graphVersion }),
+        );
+
+        if (graphData) {
+          addBlock(block.id, block.name, {
+            ...block.hardcodedValues,
+            input_schema: graphData.input_schema,
+            output_schema: graphData.output_schema,
+          });
+        } else {
+          // Fallback: add without schemas (will be incomplete)
+          console.error("Failed to fetch graph data for agent block");
+          addBlock(block.id, block.name, block.hardcodedValues || {});
+        }
+      } else {
+        addBlock(block.id, block.name, block.hardcodedValues || {});
+      }
+    },
+    [addBlock],
+  );
+
   // Extract unique categories from blocks
   const categories = useMemo(() => {
     return Array.from(
@@ -303,10 +338,7 @@ export function BlocksControl({
                       }),
                     );
                   }}
-                  onClick={() =>
-                    !block.notAvailable &&
-                    addBlock(block.id, block.name, block?.hardcodedValues || {})
-                  }
+                  onClick={() => handleAddBlock(block)}
                   title={block.notAvailable ?? undefined}
                 >
                   <div
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode.tsx
index 94e917a4ac..834603cc4a 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode.tsx
@@ -857,7 +857,7 @@ export const CustomNode = React.memo(
     })();
 
     const hasAdvancedFields =
-      data.inputSchema &&
+      data.inputSchema?.properties &&
       Object.entries(data.inputSchema.properties).some(([key, value]) => {
         return (
           value.advanced === true && !data.inputSchema.required?.includes(key)
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/DataTable.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/DataTable.tsx
index 4213711447..c58bdac642 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/DataTable.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/DataTable.tsx
@@ -1,6 +1,6 @@
 import { beautifyString } from "@/lib/utils";
 import { Clipboard, Maximize2 } from "lucide-react";
-import React, { useState } from "react";
+import React, { useMemo, useState } from "react";
 import { Button } from "../../../../../components/__legacy__/ui/button";
 import { ContentRenderer } from "../../../../../components/__legacy__/ui/render";
 import {
@@ -11,6 +11,12 @@ import {
   TableHeader,
   TableRow,
 } from "../../../../../components/__legacy__/ui/table";
+import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
+import {
+  globalRegistry,
+  OutputItem,
+} from "@/components/contextual/OutputRenderers";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { useToast } from "../../../../../components/molecules/Toast/use-toast";
 import ExpandableOutputDialog from "./ExpandableOutputDialog";
 
@@ -26,6 +32,9 @@ export default function DataTable({
   data,
 }: DataTableProps) {
   const { toast } = useToast();
+  const enableEnhancedOutputHandling = useGetFlag(
+    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
+  );
   const [expandedDialog, setExpandedDialog] = useState<{
     isOpen: boolean;
     execId: string;
@@ -33,6 +42,15 @@ export default function DataTable({
     data: any[];
   } | null>(null);
 
+  // Prepare renderers for each item when enhanced mode is enabled
+  const getItemRenderer = useMemo(() => {
+    if (!enableEnhancedOutputHandling) return null;
+    return (item: unknown) => {
+      const metadata: OutputMetadata = {};
+      return globalRegistry.getRenderer(item, metadata);
+    };
+  }, [enableEnhancedOutputHandling]);
+
   const copyData = (pin: string, data: string) => {
     navigator.clipboard.writeText(data).then(() => {
       toast({
@@ -102,15 +120,31 @@ export default function DataTable({
                       <Clipboard size={18} />
                     </Button>
                   </div>
-                  {value.map((item, index) => (
-                    <React.Fragment key={index}>
-                      <ContentRenderer
-                        value={item}
-                        truncateLongData={truncateLongData}
-                      />
-                      {index < value.length - 1 && ", "}
-                    </React.Fragment>
-                  ))}
+                  {value.map((item, index) => {
+                    const renderer = getItemRenderer?.(item);
+                    if (enableEnhancedOutputHandling && renderer) {
+                      const metadata: OutputMetadata = {};
+                      return (
+                        <React.Fragment key={index}>
+                          <OutputItem
+                            value={item}
+                            metadata={metadata}
+                            renderer={renderer}
+                          />
+                          {index < value.length - 1 && ", "}
+                        </React.Fragment>
+                      );
+                    }
+                    return (
+                      <React.Fragment key={index}>
+                        <ContentRenderer
+                          value={item}
+                          truncateLongData={truncateLongData}
+                        />
+                        {index < value.length - 1 && ", "}
+                      </React.Fragment>
+                    );
+                  })}
                 </div>
               </TableCell>
             </TableRow>
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/Flow/Flow.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/Flow/Flow.tsx
index a54a9ef386..67b3cad9af 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/Flow/Flow.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/Flow/Flow.tsx
@@ -29,13 +29,17 @@ import "@xyflow/react/dist/style.css";
 import { ConnectedEdge, CustomNode } from "../CustomNode/CustomNode";
 import "./flow.css";
 import {
+  BlockIORootSchema,
   BlockUIType,
   formatEdgeID,
   GraphExecutionID,
   GraphID,
   GraphMeta,
   LibraryAgent,
+  SpecialBlockID,
 } from "@/lib/autogpt-server-api";
+import { getV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
+import { okData } from "@/app/api/helpers";
 import { IncompatibilityInfo } from "../../../hooks/useSubAgentUpdate/types";
 import { Key, storage } from "@/services/storage/local-storage";
 import { findNewlyAddedBlockCoordinates, getTypeColor } from "@/lib/utils";
@@ -687,8 +691,94 @@ const FlowEditor: React.FC<{
     [getNode, updateNode, nodes],
   );
 
+  /* Shared helper to create and add a node */
+  const createAndAddNode = useCallback(
+    async (
+      blockID: string,
+      blockName: string,
+      hardcodedValues: Record<string, any>,
+      position: { x: number; y: number },
+    ): Promise<CustomNode | null> => {
+      const nodeSchema = availableBlocks.find((node) => node.id === blockID);
+      if (!nodeSchema) {
+        console.error(`Schema not found for block ID: ${blockID}`);
+        return null;
+      }
+
+      // For agent blocks, fetch the full graph to get schemas
+      let inputSchema: BlockIORootSchema = nodeSchema.inputSchema;
+      let outputSchema: BlockIORootSchema = nodeSchema.outputSchema;
+      let finalHardcodedValues = hardcodedValues;
+
+      if (blockID === SpecialBlockID.AGENT) {
+        const graphID = hardcodedValues.graph_id as string;
+        const graphVersion = hardcodedValues.graph_version as number;
+        const graphData = okData(
+          await getV1GetSpecificGraph(graphID, { version: graphVersion }),
+        );
+
+        if (graphData) {
+          inputSchema = graphData.input_schema as BlockIORootSchema;
+          outputSchema = graphData.output_schema as BlockIORootSchema;
+          finalHardcodedValues = {
+            ...hardcodedValues,
+            input_schema: graphData.input_schema,
+            output_schema: graphData.output_schema,
+          };
+        } else {
+          console.error("Failed to fetch graph data for agent block");
+        }
+      }
+
+      const newNode: CustomNode = {
+        id: nodeId.toString(),
+        type: "custom",
+        position,
+        data: {
+          blockType: blockName,
+          blockCosts: nodeSchema.costs || [],
+          title: `${blockName} ${nodeId}`,
+          description: nodeSchema.description,
+          categories: nodeSchema.categories,
+          inputSchema: inputSchema,
+          outputSchema: outputSchema,
+          hardcodedValues: finalHardcodedValues,
+          connections: [],
+          isOutputOpen: false,
+          block_id: blockID,
+          isOutputStatic: nodeSchema.staticOutput,
+          uiType: nodeSchema.uiType,
+        },
+      };
+
+      addNodes(newNode);
+      setNodeId((prevId) => prevId + 1);
+      clearNodesStatusAndOutput();
+
+      history.push({
+        type: "ADD_NODE",
+        payload: { node: { ...newNode, ...newNode.data } },
+        undo: () => deleteElements({ nodes: [{ id: newNode.id }] }),
+        redo: () => addNodes(newNode),
+      });
+
+      return newNode;
+    },
+    [
+      availableBlocks,
+      nodeId,
+      addNodes,
+      deleteElements,
+      clearNodesStatusAndOutput,
+    ],
+  );
+
   const addNode = useCallback(
-    (blockId: string, nodeType: string, hardcodedValues: any = {}) => {
+    async (
+      blockId: string,
+      nodeType: string,
+      hardcodedValues: Record<string, any> = {},
+    ) => {
       const nodeSchema = availableBlocks.find((node) => node.id === blockId);
       if (!nodeSchema) {
         console.error(`Schema not found for block ID: ${blockId}`);
@@ -707,73 +797,42 @@ const FlowEditor: React.FC<{
       // Alternative: We could also use D3 force, Intersection for this (React flow Pro examples)
 
       const { x, y } = getViewport();
-      const viewportCoordinates =
+      const position =
         nodeDimensions && Object.keys(nodeDimensions).length > 0
-          ? // we will get all the dimension of nodes, then store
-            findNewlyAddedBlockCoordinates(
+          ? findNewlyAddedBlockCoordinates(
               nodeDimensions,
               nodeSchema.uiType == BlockUIType.NOTE ? 300 : 500,
               60,
               1.0,
             )
-          : // we will get all the dimension of nodes, then store
-            {
+          : {
               x: window.innerWidth / 2 - x,
               y: window.innerHeight / 2 - y,
             };
 
-      const newNode: CustomNode = {
-        id: nodeId.toString(),
-        type: "custom",
-        position: viewportCoordinates, // Set the position to the calculated viewport center
-        data: {
-          blockType: nodeType,
-          blockCosts: nodeSchema.costs,
-          title: `${nodeType} ${nodeId}`,
-          description: nodeSchema.description,
-          categories: nodeSchema.categories,
-          inputSchema: nodeSchema.inputSchema,
-          outputSchema: nodeSchema.outputSchema,
-          hardcodedValues: hardcodedValues,
-          connections: [],
-          isOutputOpen: false,
-          block_id: blockId,
-          isOutputStatic: nodeSchema.staticOutput,
-          uiType: nodeSchema.uiType,
-        },
-      };
-
-      addNodes(newNode);
-      setNodeId((prevId) => prevId + 1);
-      clearNodesStatusAndOutput(); // Clear status and output when a new node is added
+      const newNode = await createAndAddNode(
+        blockId,
+        nodeType,
+        hardcodedValues,
+        position,
+      );
+      if (!newNode) return;
 
       setViewport(
         {
-          // Rough estimate of the dimension of the node is: 500x400px.
-          // Though we skip shifting the X, considering the block menu side-bar.
-          x: -viewportCoordinates.x * 0.8 + (window.innerWidth - 0.0) / 2,
-          y: -viewportCoordinates.y * 0.8 + (window.innerHeight - 400) / 2,
+          x: -position.x * 0.8 + (window.innerWidth - 0.0) / 2,
+          y: -position.y * 0.8 + (window.innerHeight - 400) / 2,
           zoom: 0.8,
         },
         { duration: 500 },
       );
-
-      history.push({
-        type: "ADD_NODE",
-        payload: { node: { ...newNode, ...newNode.data } },
-        undo: () => deleteElements({ nodes: [{ id: newNode.id }] }),
-        redo: () => addNodes(newNode),
-      });
     },
     [
-      nodeId,
       getViewport,
       setViewport,
       availableBlocks,
-      addNodes,
       nodeDimensions,
-      deleteElements,
-      clearNodesStatusAndOutput,
+      createAndAddNode,
     ],
   );
 
@@ -920,7 +979,7 @@ const FlowEditor: React.FC<{
   }, []);
 
   const onDrop = useCallback(
-    (event: React.DragEvent) => {
+    async (event: React.DragEvent) => {
       event.preventDefault();
 
       const blockData = event.dataTransfer.getData("application/reactflow");
@@ -935,62 +994,17 @@ const FlowEditor: React.FC<{
           y: event.clientY,
         });
 
-        // Find the block schema
-        const nodeSchema = availableBlocks.find((node) => node.id === blockId);
-        if (!nodeSchema) {
-          console.error(`Schema not found for block ID: ${blockId}`);
-          return;
-        }
-
-        // Create the new node at the drop position
-        const newNode: CustomNode = {
-          id: nodeId.toString(),
-          type: "custom",
+        await createAndAddNode(
+          blockId,
+          blockName,
+          hardcodedValues || {},
           position,
-          data: {
-            blockType: blockName,
-            blockCosts: nodeSchema.costs || [],
-            title: `${blockName} ${nodeId}`,
-            description: nodeSchema.description,
-            categories: nodeSchema.categories,
-            inputSchema: nodeSchema.inputSchema,
-            outputSchema: nodeSchema.outputSchema,
-            hardcodedValues: hardcodedValues,
-            connections: [],
-            isOutputOpen: false,
-            block_id: blockId,
-            uiType: nodeSchema.uiType,
-          },
-        };
-
-        history.push({
-          type: "ADD_NODE",
-          payload: { node: { ...newNode, ...newNode.data } },
-          undo: () => {
-            deleteElements({ nodes: [{ id: newNode.id } as any], edges: [] });
-          },
-          redo: () => {
-            addNodes([newNode]);
-          },
-        });
-        addNodes([newNode]);
-        clearNodesStatusAndOutput();
-
-        setNodeId((prevId) => prevId + 1);
+        );
       } catch (error) {
         console.error("Failed to drop block:", error);
       }
     },
-    [
-      nodeId,
-      availableBlocks,
-      nodes,
-      edges,
-      addNodes,
-      screenToFlowPosition,
-      deleteElements,
-      clearNodesStatusAndOutput,
-    ],
+    [screenToFlowPosition, createAndAddNode],
   );
 
   const buildContextValue: BuilderContextType = useMemo(
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeOutputs.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeOutputs.tsx
index d90b7d6a4c..2111db7d99 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeOutputs.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeOutputs.tsx
@@ -1,8 +1,14 @@
-import React, { useContext, useState } from "react";
+import React, { useContext, useMemo, useState } from "react";
 import { Button } from "@/components/__legacy__/ui/button";
 import { Maximize2 } from "lucide-react";
 import * as Separator from "@radix-ui/react-separator";
 import { ContentRenderer } from "@/components/__legacy__/ui/render";
+import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
+import {
+  globalRegistry,
+  OutputItem,
+} from "@/components/contextual/OutputRenderers";
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 
 import { beautifyString } from "@/lib/utils";
 
@@ -21,6 +27,9 @@ export default function NodeOutputs({
   data,
 }: NodeOutputsProps) {
   const builderContext = useContext(BuilderContext);
+  const enableEnhancedOutputHandling = useGetFlag(
+    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
+  );
 
   const [expandedDialog, setExpandedDialog] = useState<{
     isOpen: boolean;
@@ -37,6 +46,15 @@ export default function NodeOutputs({
 
   const { getNodeTitle } = builderContext;
 
+  // Prepare renderers for each item when enhanced mode is enabled
+  const getItemRenderer = useMemo(() => {
+    if (!enableEnhancedOutputHandling) return null;
+    return (item: unknown) => {
+      const metadata: OutputMetadata = {};
+      return globalRegistry.getRenderer(item, metadata);
+    };
+  }, [enableEnhancedOutputHandling]);
+
   const getBeautifiedPinName = (pin: string) => {
     if (!pin.startsWith("tools_^_")) {
       return beautifyString(pin);
@@ -87,15 +105,31 @@ export default function NodeOutputs({
           <div className="mt-2">
             <strong className="mr-2">Data:</strong>
             <div className="mt-1">
-              {dataArray.slice(0, 10).map((item, index) => (
-                <React.Fragment key={index}>
-                  <ContentRenderer
-                    value={item}
-                    truncateLongData={truncateLongData}
-                  />
-                  {index < Math.min(dataArray.length, 10) - 1 && ", "}
-                </React.Fragment>
-              ))}
+              {dataArray.slice(0, 10).map((item, index) => {
+                const renderer = getItemRenderer?.(item);
+                if (enableEnhancedOutputHandling && renderer) {
+                  const metadata: OutputMetadata = {};
+                  return (
+                    <React.Fragment key={index}>
+                      <OutputItem
+                        value={item}
+                        metadata={metadata}
+                        renderer={renderer}
+                      />
+                      {index < Math.min(dataArray.length, 10) - 1 && ", "}
+                    </React.Fragment>
+                  );
+                }
+                return (
+                  <React.Fragment key={index}>
+                    <ContentRenderer
+                      value={item}
+                      truncateLongData={truncateLongData}
+                    />
+                    {index < Math.min(dataArray.length, 10) - 1 && ", "}
+                  </React.Fragment>
+                );
+              })}
               {dataArray.length > 10 && (
                 <span style={{ color: "#888" }}>
                   <br />
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerInputUI.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerInputUI.tsx
index 15983be9f5..cb06a79683 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerInputUI.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerInputUI.tsx
@@ -4,13 +4,13 @@ import { AgentRunDraftView } from "@/app/(platform)/library/agents/[id]/componen
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import type {
   CredentialsMetaInput,
-  GraphMeta,
+  Graph,
 } from "@/lib/autogpt-server-api/types";
 
 interface RunInputDialogProps {
   isOpen: boolean;
   doClose: () => void;
-  graph: GraphMeta;
+  graph: Graph;
   doRun?: (
     inputs: Record<string, any>,
     credentialsInputs: Record<string, CredentialsMetaInput>,
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerUIWrapper.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerUIWrapper.tsx
index a9af065a5d..b1d40fb919 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerUIWrapper.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerUIWrapper.tsx
@@ -9,13 +9,13 @@ import { CustomNodeData } from "@/app/(platform)/build/components/legacy-builder
 import {
   BlockUIType,
   CredentialsMetaInput,
-  GraphMeta,
+  Graph,
 } from "@/lib/autogpt-server-api/types";
 import RunnerOutputUI, { OutputNodeInfo } from "./RunnerOutputUI";
 import { RunnerInputDialog } from "./RunnerInputUI";
 
 interface RunnerUIWrapperProps {
-  graph: GraphMeta;
+  graph: Graph;
   nodes: Node<CustomNodeData>[];
   graphExecutionError?: string | null;
   saveAndRun: (
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/helpers.ts
index aece7e9811..69593a142b 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/helpers.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/helpers.ts
@@ -1,5 +1,5 @@
 import { GraphInputSchema } from "@/lib/autogpt-server-api";
-import { GraphMetaLike, IncompatibilityInfo } from "./types";
+import { GraphLike, IncompatibilityInfo } from "./types";
 
 // Helper type for schema properties - the generated types are too loose
 type SchemaProperties = Record<string, GraphInputSchema["properties"][string]>;
@@ -36,7 +36,7 @@ export function getSchemaRequired(schema: unknown): SchemaRequired {
  */
 export function createUpdatedAgentNodeInputs(
   currentInputs: Record<string, unknown>,
-  latestSubGraphVersion: GraphMetaLike,
+  latestSubGraphVersion: GraphLike,
 ): Record<string, unknown> {
   return {
     ...currentInputs,
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/types.ts b/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/types.ts
index 83f83155db..6c115f20a3 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/types.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/types.ts
@@ -1,7 +1,11 @@
-import type { GraphMeta as LegacyGraphMeta } from "@/lib/autogpt-server-api";
+import type {
+  Graph as LegacyGraph,
+  GraphMeta as LegacyGraphMeta,
+} from "@/lib/autogpt-server-api";
+import type { GraphModel as GeneratedGraph } from "@/app/api/__generated__/models/graphModel";
 import type { GraphMeta as GeneratedGraphMeta } from "@/app/api/__generated__/models/graphMeta";
 
-export type SubAgentUpdateInfo<T extends GraphMetaLike = GraphMetaLike> = {
+export type SubAgentUpdateInfo<T extends GraphLike = GraphLike> = {
   hasUpdate: boolean;
   currentVersion: number;
   latestVersion: number;
@@ -10,7 +14,10 @@ export type SubAgentUpdateInfo<T extends GraphMetaLike = GraphMetaLike> = {
   incompatibilities: IncompatibilityInfo | null;
 };
 
-// Union type for GraphMeta that works with both legacy and new builder
+// Union type for Graph (with schemas) that works with both legacy and new builder
+export type GraphLike = LegacyGraph | GeneratedGraph;
+
+// Union type for GraphMeta (without schemas) for version detection
 export type GraphMetaLike = LegacyGraphMeta | GeneratedGraphMeta;
 
 export type IncompatibilityInfo = {
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/useSubAgentUpdate.ts b/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/useSubAgentUpdate.ts
index 315e337cd6..7ad10ea697 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/useSubAgentUpdate.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/build/hooks/useSubAgentUpdate/useSubAgentUpdate.ts
@@ -1,5 +1,11 @@
 import { useMemo } from "react";
-import { GraphInputSchema, GraphOutputSchema } from "@/lib/autogpt-server-api";
+import type {
+  GraphInputSchema,
+  GraphOutputSchema,
+} from "@/lib/autogpt-server-api";
+import type { GraphModel } from "@/app/api/__generated__/models/graphModel";
+import { useGetV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
+import { okData } from "@/app/api/helpers";
 import { getEffectiveType } from "@/lib/utils";
 import { EdgeLike, getSchemaProperties, getSchemaRequired } from "./helpers";
 import {
@@ -11,26 +17,38 @@ import {
 /**
  * Checks if a newer version of a sub-agent is available and determines compatibility
  */
-export function useSubAgentUpdate<T extends GraphMetaLike>(
+export function useSubAgentUpdate(
   nodeID: string,
   graphID: string | undefined,
   graphVersion: number | undefined,
   currentInputSchema: GraphInputSchema | undefined,
   currentOutputSchema: GraphOutputSchema | undefined,
   connections: EdgeLike[],
-  availableGraphs: T[],
-): SubAgentUpdateInfo<T> {
+  availableGraphs: GraphMetaLike[],
+): SubAgentUpdateInfo<GraphModel> {
   // Find the latest version of the same graph
-  const latestGraph = useMemo(() => {
+  const latestGraphInfo = useMemo(() => {
     if (!graphID) return null;
     return availableGraphs.find((graph) => graph.id === graphID) || null;
   }, [graphID, availableGraphs]);
 
-  // Check if there's an update available
+  // Check if there's a newer version available
   const hasUpdate = useMemo(() => {
-    if (!latestGraph || graphVersion === undefined) return false;
-    return latestGraph.version! > graphVersion;
-  }, [latestGraph, graphVersion]);
+    if (!latestGraphInfo || graphVersion === undefined) return false;
+    return latestGraphInfo.version! > graphVersion;
+  }, [latestGraphInfo, graphVersion]);
+
+  // Fetch full graph IF an update is detected
+  const { data: latestGraph } = useGetV1GetSpecificGraph(
+    graphID ?? "",
+    { version: latestGraphInfo?.version },
+    {
+      query: {
+        enabled: hasUpdate && !!graphID && !!latestGraphInfo?.version,
+        select: okData,
+      },
+    },
+  );
 
   // Get connected input and output handles for this specific node
   const connectedHandles = useMemo(() => {
@@ -152,8 +170,8 @@ export function useSubAgentUpdate<T extends GraphMetaLike>(
   return {
     hasUpdate,
     currentVersion: graphVersion || 0,
-    latestVersion: latestGraph?.version || 0,
-    latestGraph,
+    latestVersion: latestGraphInfo?.version || 0,
+    latestGraph: latestGraph || null,
     isCompatible: compatibilityResult.isCompatible,
     incompatibilities: compatibilityResult.incompatibilities,
   };
diff --git a/autogpt_platform/frontend/src/app/(platform)/build/stores/graphStore.ts b/autogpt_platform/frontend/src/app/(platform)/build/stores/graphStore.ts
index 6961884732..c1eba556d2 100644
--- a/autogpt_platform/frontend/src/app/(platform)/build/stores/graphStore.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/build/stores/graphStore.ts
@@ -18,7 +18,7 @@ interface GraphStore {
     outputSchema: Record<string, any> | null,
   ) => void;
 
-  // Available graphs; used for sub-graph updates
+  // Available graphs; used for sub-graph updated version detection
   availableSubGraphs: GraphMeta[];
   setAvailableSubGraphs: (graphs: GraphMeta[]) => void;
 
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx
new file mode 100644
index 0000000000..0d403b1a79
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx
@@ -0,0 +1,80 @@
+"use client";
+
+import { SidebarProvider } from "@/components/ui/sidebar";
+import { ChatContainer } from "./components/ChatContainer/ChatContainer";
+import { ChatSidebar } from "./components/ChatSidebar/ChatSidebar";
+import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
+import { MobileHeader } from "./components/MobileHeader/MobileHeader";
+import { ScaleLoader } from "./components/ScaleLoader/ScaleLoader";
+import { useCopilotPage } from "./useCopilotPage";
+
+export function CopilotPage() {
+  const {
+    sessionId,
+    messages,
+    status,
+    error,
+    stop,
+    createSession,
+    onSend,
+    isLoadingSession,
+    isCreatingSession,
+    isUserLoading,
+    isLoggedIn,
+    // Mobile drawer
+    isMobile,
+    isDrawerOpen,
+    sessions,
+    isLoadingSessions,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleSelectSession,
+    handleNewChat,
+  } = useCopilotPage();
+
+  if (isUserLoading || !isLoggedIn) {
+    return (
+      <div className="fixed inset-0 z-50 flex items-center justify-center bg-[#f8f8f9]">
+        <ScaleLoader className="text-neutral-400" />
+      </div>
+    );
+  }
+
+  return (
+    <SidebarProvider
+      defaultOpen={true}
+      className="h-[calc(100vh-72px)] min-h-0"
+    >
+      {!isMobile && <ChatSidebar />}
+      <div className="relative flex h-full w-full flex-col overflow-hidden bg-[#f8f8f9] px-0">
+        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
+        <div className="flex-1 overflow-hidden">
+          <ChatContainer
+            messages={messages}
+            status={status}
+            error={error}
+            sessionId={sessionId}
+            isLoadingSession={isLoadingSession}
+            isCreatingSession={isCreatingSession}
+            onCreateSession={createSession}
+            onSend={onSend}
+            onStop={stop}
+          />
+        </div>
+      </div>
+      {isMobile && (
+        <MobileDrawer
+          isOpen={isDrawerOpen}
+          sessions={sessions}
+          currentSessionId={sessionId}
+          isLoading={isLoadingSessions}
+          onSelectSession={handleSelectSession}
+          onNewChat={handleNewChat}
+          onClose={handleCloseDrawer}
+          onOpenChange={handleDrawerOpenChange}
+        />
+      )}
+    </SidebarProvider>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx
new file mode 100644
index 0000000000..5074741095
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx
@@ -0,0 +1,74 @@
+"use client";
+import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
+import { UIDataTypes, UIMessage, UITools } from "ai";
+import { LayoutGroup, motion } from "framer-motion";
+import { ChatMessagesContainer } from "../ChatMessagesContainer/ChatMessagesContainer";
+import { CopilotChatActionsProvider } from "../CopilotChatActionsProvider/CopilotChatActionsProvider";
+import { EmptySession } from "../EmptySession/EmptySession";
+
+export interface ChatContainerProps {
+  messages: UIMessage<unknown, UIDataTypes, UITools>[];
+  status: string;
+  error: Error | undefined;
+  sessionId: string | null;
+  isLoadingSession: boolean;
+  isCreatingSession: boolean;
+  onCreateSession: () => void | Promise<string>;
+  onSend: (message: string) => void | Promise<void>;
+  onStop: () => void;
+}
+export const ChatContainer = ({
+  messages,
+  status,
+  error,
+  sessionId,
+  isLoadingSession,
+  isCreatingSession,
+  onCreateSession,
+  onSend,
+  onStop,
+}: ChatContainerProps) => {
+  const inputLayoutId = "copilot-2-chat-input";
+
+  return (
+    <CopilotChatActionsProvider onSend={onSend}>
+      <LayoutGroup id="copilot-2-chat-layout">
+        <div className="flex h-full min-h-0 w-full flex-col bg-[#f8f8f9] px-2 lg:px-0">
+          {sessionId ? (
+            <div className="mx-auto flex h-full min-h-0 w-full max-w-3xl flex-col">
+              <ChatMessagesContainer
+                messages={messages}
+                status={status}
+                error={error}
+                isLoading={isLoadingSession}
+              />
+              <motion.div
+                initial={{ opacity: 0 }}
+                animate={{ opacity: 1 }}
+                transition={{ duration: 0.3 }}
+                className="relative px-3 pb-2 pt-2"
+              >
+                <div className="pointer-events-none absolute left-0 right-0 top-[-18px] z-10 h-6 bg-gradient-to-b from-transparent to-[#f8f8f9]" />
+                <ChatInput
+                  inputId="chat-input-session"
+                  onSend={onSend}
+                  disabled={status === "streaming"}
+                  isStreaming={status === "streaming"}
+                  onStop={onStop}
+                  placeholder="What else can I help with?"
+                />
+              </motion.div>
+            </div>
+          ) : (
+            <EmptySession
+              inputLayoutId={inputLayoutId}
+              isCreatingSession={isCreatingSession}
+              onCreateSession={onCreateSession}
+              onSend={onSend}
+            />
+          )}
+        </div>
+      </LayoutGroup>
+    </CopilotChatActionsProvider>
+  );
+};
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/ChatInput.tsx
similarity index 85%
rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx
rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/ChatInput.tsx
index 521f6f6320..af44232a4a 100644
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/ChatInput.tsx
@@ -6,17 +6,19 @@ import {
   MicrophoneIcon,
   StopIcon,
 } from "@phosphor-icons/react";
+import { ChangeEvent, useCallback } from "react";
 import { RecordingIndicator } from "./components/RecordingIndicator";
 import { useChatInput } from "./useChatInput";
 import { useVoiceRecording } from "./useVoiceRecording";
 
 export interface Props {
-  onSend: (message: string) => void;
+  onSend: (message: string) => void | Promise<void>;
   disabled?: boolean;
   isStreaming?: boolean;
   onStop?: () => void;
   placeholder?: string;
   className?: string;
+  inputId?: string;
 }
 
 export function ChatInput({
@@ -26,14 +28,14 @@ export function ChatInput({
   onStop,
   placeholder = "Type your message...",
   className,
+  inputId = "chat-input",
 }: Props) {
-  const inputId = "chat-input";
   const {
     value,
     setValue,
     handleKeyDown: baseHandleKeyDown,
     handleSubmit,
-    handleChange,
+    handleChange: baseHandleChange,
     hasMultipleLines,
   } = useChatInput({
     onSend,
@@ -57,8 +59,18 @@ export function ChatInput({
     isStreaming,
     value,
     baseHandleKeyDown,
+    inputId,
   });
 
+  // Block text changes when recording
+  const handleChange = useCallback(
+    (e: ChangeEvent<HTMLTextAreaElement>) => {
+      if (isRecording) return;
+      baseHandleChange(e);
+    },
+    [isRecording, baseHandleChange],
+  );
+
   return (
     <form onSubmit={handleSubmit} className={cn("relative flex-1", className)}>
       <div className="relative">
@@ -73,19 +85,20 @@ export function ChatInput({
             hasMultipleLines ? "rounded-xlarge" : "rounded-full",
           )}
         >
+          {!value && !isRecording && (
+            <div
+              className="pointer-events-none absolute inset-0 top-0.5 flex items-center justify-start pl-14 text-[1rem] text-zinc-400"
+              aria-hidden="true"
+            >
+              {isTranscribing ? "Transcribing..." : placeholder}
+            </div>
+          )}
           <textarea
             id={inputId}
             aria-label="Chat message input"
             value={value}
             onChange={handleChange}
             onKeyDown={handleKeyDown}
-            placeholder={
-              isTranscribing
-                ? "Transcribing..."
-                : isRecording
-                  ? ""
-                  : placeholder
-            }
             disabled={isInputDisabled}
             rows={1}
             className={cn(
@@ -121,13 +134,14 @@ export function ChatInput({
               size="icon"
               aria-label={isRecording ? "Stop recording" : "Start recording"}
               onClick={toggleRecording}
-              disabled={disabled || isTranscribing}
+              disabled={disabled || isTranscribing || isStreaming}
               className={cn(
                 isRecording
                   ? "animate-pulse border-red-500 bg-red-500 text-white hover:border-red-600 hover:bg-red-600"
                   : isTranscribing
                     ? "border-zinc-300 bg-zinc-100 text-zinc-400"
                     : "border-zinc-300 bg-white text-zinc-500 hover:border-zinc-400 hover:bg-zinc-50 hover:text-zinc-700",
+                isStreaming && "opacity-40",
               )}
             >
               {isTranscribing ? (
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/AudioWaveform.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/AudioWaveform.tsx
similarity index 90%
rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/AudioWaveform.tsx
rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/AudioWaveform.tsx
index 10cbb3fc9f..50414adc89 100644
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/AudioWaveform.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/AudioWaveform.tsx
@@ -38,8 +38,8 @@ export function AudioWaveform({
     // Create audio context and analyser
     const audioContext = new AudioContext();
     const analyser = audioContext.createAnalyser();
-    analyser.fftSize = 512;
-    analyser.smoothingTimeConstant = 0.8;
+    analyser.fftSize = 256;
+    analyser.smoothingTimeConstant = 0.3;
 
     // Connect the stream to the analyser
     const source = audioContext.createMediaStreamSource(stream);
@@ -73,10 +73,11 @@ export function AudioWaveform({
           maxAmplitude = Math.max(maxAmplitude, amplitude);
         }
 
-        // Map amplitude (0-128) to bar height
-        const normalized = (maxAmplitude / 128) * 255;
-        const height =
-          minBarHeight + (normalized / 255) * (maxBarHeight - minBarHeight);
+        // Normalize amplitude (0-128 range) to 0-1
+        const normalized = maxAmplitude / 128;
+        // Apply sensitivity boost (multiply by 4) and use sqrt curve to amplify quiet sounds
+        const boosted = Math.min(1, Math.sqrt(normalized) * 4);
+        const height = minBarHeight + boosted * (maxBarHeight - minBarHeight);
         newBars.push(height);
       }
 
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/RecordingIndicator.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/RecordingIndicator.tsx
similarity index 100%
rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/RecordingIndicator.tsx
rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/RecordingIndicator.tsx
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/helpers.ts
similarity index 100%
rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/helpers.ts
rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/helpers.ts
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts
similarity index 83%
rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts
rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts
index a053e6080f..64b39c3817 100644
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts
@@ -21,6 +21,7 @@ export function useChatInput({
 }: Args) {
   const [value, setValue] = useState("");
   const [hasMultipleLines, setHasMultipleLines] = useState(false);
+  const [isSending, setIsSending] = useState(false);
 
   useEffect(
     function focusOnMount() {
@@ -100,34 +101,40 @@ export function useChatInput({
     }
   }, [value, maxRows, inputId]);
 
-  const handleSend = () => {
-    if (disabled || !value.trim()) return;
-    onSend(value.trim());
-    setValue("");
-    setHasMultipleLines(false);
-    const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
-    const wrapper = document.getElementById(
-      `${inputId}-wrapper`,
-    ) as HTMLDivElement;
-    if (textarea) {
-      textarea.style.height = "auto";
+  async function handleSend() {
+    if (disabled || isSending || !value.trim()) return;
+
+    setIsSending(true);
+    try {
+      await onSend(value.trim());
+      setValue("");
+      setHasMultipleLines(false);
+      const textarea = document.getElementById(inputId) as HTMLTextAreaElement;
+      const wrapper = document.getElementById(
+        `${inputId}-wrapper`,
+      ) as HTMLDivElement;
+      if (textarea) {
+        textarea.style.height = "auto";
+      }
+      if (wrapper) {
+        wrapper.style.height = "";
+        wrapper.style.maxHeight = "";
+      }
+    } finally {
+      setIsSending(false);
     }
-    if (wrapper) {
-      wrapper.style.height = "";
-      wrapper.style.maxHeight = "";
-    }
-  };
+  }
 
   function handleKeyDown(event: KeyboardEvent<HTMLTextAreaElement>) {
     if (event.key === "Enter" && !event.shiftKey) {
       event.preventDefault();
-      handleSend();
+      void handleSend();
     }
   }
 
   function handleSubmit(e: FormEvent<HTMLFormElement>) {
     e.preventDefault();
-    handleSend();
+    void handleSend();
   }
 
   function handleChange(e: ChangeEvent<HTMLTextAreaElement>) {
@@ -142,5 +149,6 @@ export function useChatInput({
     handleSubmit,
     handleChange,
     hasMultipleLines,
+    isSending,
   };
 }
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useVoiceRecording.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts
similarity index 82%
rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useVoiceRecording.ts
rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts
index 13b625e69c..0f9ee51736 100644
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useVoiceRecording.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts
@@ -15,6 +15,7 @@ interface Args {
   isStreaming?: boolean;
   value: string;
   baseHandleKeyDown: (event: KeyboardEvent<HTMLTextAreaElement>) => void;
+  inputId?: string;
 }
 
 export function useVoiceRecording({
@@ -23,6 +24,7 @@ export function useVoiceRecording({
   isStreaming = false,
   value,
   baseHandleKeyDown,
+  inputId,
 }: Args) {
   const [isRecording, setIsRecording] = useState(false);
   const [isTranscribing, setIsTranscribing] = useState(false);
@@ -36,9 +38,13 @@ export function useVoiceRecording({
   const streamRef = useRef<MediaStream | null>(null);
   const isRecordingRef = useRef(false);
 
-  const isSupported =
-    typeof window !== "undefined" &&
-    !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia);
+  const [isSupported, setIsSupported] = useState(false);
+
+  useEffect(() => {
+    setIsSupported(
+      !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia),
+    );
+  }, []);
 
   const clearTimer = useCallback(() => {
     if (timerRef.current) {
@@ -103,7 +109,7 @@ export function useVoiceRecording({
         setIsTranscribing(false);
       }
     },
-    [handleTranscription],
+    [handleTranscription, inputId],
   );
 
   const stopRecording = useCallback(() => {
@@ -201,19 +207,44 @@ export function useVoiceRecording({
     }
   }, [error, toast]);
 
+  useEffect(() => {
+    if (!isTranscribing && inputId) {
+      const inputElement = document.getElementById(inputId);
+      if (inputElement) {
+        inputElement.focus();
+      }
+    }
+  }, [isTranscribing, inputId]);
+
   const handleKeyDown = useCallback(
     (event: KeyboardEvent<HTMLTextAreaElement>) => {
-      if (event.key === " " && !value.trim() && !isTranscribing) {
+      // Allow space to toggle recording (start when empty, stop when recording)
+      if (event.key === " " && !isTranscribing) {
+        if (isRecordingRef.current) {
+          // Stop recording on space
+          event.preventDefault();
+          stopRecording();
+          return;
+        } else if (!value.trim()) {
+          // Start recording on space when input is empty
+          event.preventDefault();
+          void startRecording();
+          return;
+        }
+      }
+      // Block all key events when recording (except space handled above)
+      if (isRecordingRef.current) {
         event.preventDefault();
-        toggleRecording();
         return;
       }
       baseHandleKeyDown(event);
     },
-    [value, isTranscribing, toggleRecording, baseHandleKeyDown],
+    [value, isTranscribing, stopRecording, startRecording, baseHandleKeyDown],
   );
 
-  const showMicButton = isSupported && !isStreaming;
+  const showMicButton = isSupported;
+  // Don't include isRecording in disabled state - we need key events to work
+  // Text input is blocked via handleKeyDown instead
   const isInputDisabled = disabled || isStreaming || isTranscribing;
 
   // Cleanup on unmount
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx
new file mode 100644
index 0000000000..fbe1c03d1d
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx
@@ -0,0 +1,294 @@
+import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
+import {
+  Conversation,
+  ConversationContent,
+  ConversationScrollButton,
+} from "@/components/ai-elements/conversation";
+import {
+  Message,
+  MessageContent,
+  MessageResponse,
+} from "@/components/ai-elements/message";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { toast } from "@/components/molecules/Toast/use-toast";
+import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
+import { useEffect, useRef, useState } from "react";
+import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
+import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
+import { FindAgentsTool } from "../../tools/FindAgents/FindAgents";
+import { FindBlocksTool } from "../../tools/FindBlocks/FindBlocks";
+import { RunAgentTool } from "../../tools/RunAgent/RunAgent";
+import { RunBlockTool } from "../../tools/RunBlock/RunBlock";
+import { SearchDocsTool } from "../../tools/SearchDocs/SearchDocs";
+import { ViewAgentOutputTool } from "../../tools/ViewAgentOutput/ViewAgentOutput";
+
+// ---------------------------------------------------------------------------
+// Workspace media support
+// ---------------------------------------------------------------------------
+
+/**
+ * Resolve workspace:// URLs in markdown text to proxy download URLs.
+ * Detects MIME type from the hash fragment (e.g. workspace://id#video/mp4)
+ * and prefixes the alt text with "video:" so the custom img component can
+ * render a <video> element instead.
+ */
+function resolveWorkspaceUrls(text: string): string {
+  return text.replace(
+    /!\[([^\]]*)\]\(workspace:\/\/([^)#\s]+)(?:#([^)\s]*))?\)/g,
+    (_match, alt: string, fileId: string, mimeHint?: string) => {
+      const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
+      const url = `/api/proxy${apiPath}`;
+      if (mimeHint?.startsWith("video/")) {
+        return `![video:${alt || "Video"}](${url})`;
+      }
+      return `![${alt || "Image"}](${url})`;
+    },
+  );
+}
+
+/**
+ * Custom img component for Streamdown that renders <video> elements
+ * for workspace video files (detected via "video:" alt-text prefix).
+ * Falls back to <video> when an <img> fails to load for workspace files.
+ */
+function WorkspaceMediaImage(props: React.JSX.IntrinsicElements["img"]) {
+  const { src, alt, ...rest } = props;
+  const [imgFailed, setImgFailed] = useState(false);
+  const isWorkspace = src?.includes("/workspace/files/") ?? false;
+
+  if (!src) return null;
+
+  if (alt?.startsWith("video:") || (imgFailed && isWorkspace)) {
+    return (
+      <span className="my-2 inline-block">
+        <video
+          controls
+          className="h-auto max-w-full rounded-md border border-zinc-200"
+          preload="metadata"
+        >
+          <source src={src} />
+          Your browser does not support the video tag.
+        </video>
+      </span>
+    );
+  }
+
+  return (
+    // eslint-disable-next-line @next/next/no-img-element
+    <img
+      src={src}
+      alt={alt || "Image"}
+      className="h-auto max-w-full rounded-md border border-zinc-200"
+      loading="lazy"
+      onError={() => {
+        if (isWorkspace) setImgFailed(true);
+      }}
+      {...rest}
+    />
+  );
+}
+
+/** Stable components override for Streamdown (avoids re-creating on every render). */
+const STREAMDOWN_COMPONENTS = { img: WorkspaceMediaImage };
+
+const THINKING_PHRASES = [
+  "Thinking...",
+  "Considering this...",
+  "Working through this...",
+  "Analyzing your request...",
+  "Reasoning...",
+  "Looking into it...",
+  "Processing your request...",
+  "Mulling this over...",
+  "Piecing it together...",
+  "On it...",
+];
+
+function getRandomPhrase() {
+  return THINKING_PHRASES[Math.floor(Math.random() * THINKING_PHRASES.length)];
+}
+
+interface ChatMessagesContainerProps {
+  messages: UIMessage<unknown, UIDataTypes, UITools>[];
+  status: string;
+  error: Error | undefined;
+  isLoading: boolean;
+}
+
+export const ChatMessagesContainer = ({
+  messages,
+  status,
+  error,
+  isLoading,
+}: ChatMessagesContainerProps) => {
+  const [thinkingPhrase, setThinkingPhrase] = useState(getRandomPhrase);
+  const lastToastTimeRef = useRef(0);
+
+  useEffect(() => {
+    if (status === "submitted") {
+      setThinkingPhrase(getRandomPhrase());
+    }
+  }, [status]);
+
+  // Show a toast when a new error occurs, debounced to avoid spam
+  useEffect(() => {
+    if (!error) return;
+    const now = Date.now();
+    if (now - lastToastTimeRef.current < 3_000) return;
+    lastToastTimeRef.current = now;
+    toast({
+      variant: "destructive",
+      title: "Something went wrong",
+      description:
+        "The assistant encountered an error. Please try sending your message again.",
+    });
+  }, [error]);
+
+  const lastMessage = messages[messages.length - 1];
+  const lastAssistantHasVisibleContent =
+    lastMessage?.role === "assistant" &&
+    lastMessage.parts.some(
+      (p) =>
+        (p.type === "text" && p.text.trim().length > 0) ||
+        p.type.startsWith("tool-"),
+    );
+
+  const showThinking =
+    status === "submitted" ||
+    (status === "streaming" && !lastAssistantHasVisibleContent);
+
+  return (
+    <Conversation className="min-h-0 flex-1">
+      <ConversationContent className="flex min-h-screen flex-1 flex-col gap-6 px-3 py-6">
+        {isLoading && messages.length === 0 && (
+          <div className="flex min-h-full flex-1 items-center justify-center">
+            <LoadingSpinner className="text-neutral-600" />
+          </div>
+        )}
+        {messages.map((message, messageIndex) => {
+          const isLastAssistant =
+            messageIndex === messages.length - 1 &&
+            message.role === "assistant";
+          const messageHasVisibleContent = message.parts.some(
+            (p) =>
+              (p.type === "text" && p.text.trim().length > 0) ||
+              p.type.startsWith("tool-"),
+          );
+
+          return (
+            <Message from={message.role} key={message.id}>
+              <MessageContent
+                className={
+                  "text-[1rem] leading-relaxed " +
+                  "group-[.is-user]:rounded-xl group-[.is-user]:bg-purple-100 group-[.is-user]:px-3 group-[.is-user]:py-2.5 group-[.is-user]:text-slate-900 group-[.is-user]:[border-bottom-right-radius:0] " +
+                  "group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900"
+                }
+              >
+                {message.parts.map((part, i) => {
+                  switch (part.type) {
+                    case "text":
+                      return (
+                        <MessageResponse
+                          key={`${message.id}-${i}`}
+                          components={STREAMDOWN_COMPONENTS}
+                        >
+                          {resolveWorkspaceUrls(part.text)}
+                        </MessageResponse>
+                      );
+                    case "tool-find_block":
+                      return (
+                        <FindBlocksTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-find_agent":
+                    case "tool-find_library_agent":
+                      return (
+                        <FindAgentsTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-search_docs":
+                    case "tool-get_doc_page":
+                      return (
+                        <SearchDocsTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-run_block":
+                      return (
+                        <RunBlockTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-run_agent":
+                    case "tool-schedule_agent":
+                      return (
+                        <RunAgentTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-create_agent":
+                      return (
+                        <CreateAgentTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-edit_agent":
+                      return (
+                        <EditAgentTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    case "tool-view_agent_output":
+                      return (
+                        <ViewAgentOutputTool
+                          key={`${message.id}-${i}`}
+                          part={part as ToolUIPart}
+                        />
+                      );
+                    default:
+                      return null;
+                  }
+                })}
+                {isLastAssistant &&
+                  !messageHasVisibleContent &&
+                  showThinking && (
+                    <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
+                      {thinkingPhrase}
+                    </span>
+                  )}
+              </MessageContent>
+            </Message>
+          );
+        })}
+        {showThinking && lastMessage?.role !== "assistant" && (
+          <Message from="assistant">
+            <MessageContent className="text-[1rem] leading-relaxed">
+              <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
+                {thinkingPhrase}
+              </span>
+            </MessageContent>
+          </Message>
+        )}
+        {error && (
+          <div className="rounded-lg bg-red-50 p-4 text-sm text-red-700">
+            <p className="font-medium">Something went wrong</p>
+            <p className="mt-1 text-red-600">
+              The assistant encountered an error. Please try sending your
+              message again.
+            </p>
+          </div>
+        )}
+      </ConversationContent>
+      <ConversationScrollButton />
+    </Conversation>
+  );
+};
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatSidebar/ChatSidebar.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatSidebar/ChatSidebar.tsx
new file mode 100644
index 0000000000..6b7398b4ba
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatSidebar/ChatSidebar.tsx
@@ -0,0 +1,188 @@
+"use client";
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
+import { Button } from "@/components/atoms/Button/Button";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { Text } from "@/components/atoms/Text/Text";
+import {
+  Sidebar,
+  SidebarContent,
+  SidebarFooter,
+  SidebarHeader,
+  SidebarTrigger,
+  useSidebar,
+} from "@/components/ui/sidebar";
+import { cn } from "@/lib/utils";
+import { PlusCircleIcon, PlusIcon } from "@phosphor-icons/react";
+import { motion } from "framer-motion";
+import { parseAsString, useQueryState } from "nuqs";
+
+export function ChatSidebar() {
+  const { state } = useSidebar();
+  const isCollapsed = state === "collapsed";
+  const [sessionId, setSessionId] = useQueryState("sessionId", parseAsString);
+
+  const { data: sessionsResponse, isLoading: isLoadingSessions } =
+    useGetV2ListSessions({ limit: 50 });
+
+  const sessions =
+    sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
+
+  function handleNewChat() {
+    setSessionId(null);
+  }
+
+  function handleSelectSession(id: string) {
+    setSessionId(id);
+  }
+
+  function formatDate(dateString: string) {
+    const date = new Date(dateString);
+    const now = new Date();
+    const diffMs = now.getTime() - date.getTime();
+    const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
+
+    if (diffDays === 0) return "Today";
+    if (diffDays === 1) return "Yesterday";
+    if (diffDays < 7) return `${diffDays} days ago`;
+
+    const day = date.getDate();
+    const ordinal =
+      day % 10 === 1 && day !== 11
+        ? "st"
+        : day % 10 === 2 && day !== 12
+          ? "nd"
+          : day % 10 === 3 && day !== 13
+            ? "rd"
+            : "th";
+    const month = date.toLocaleDateString("en-US", { month: "short" });
+    const year = date.getFullYear();
+
+    return `${day}${ordinal} ${month} ${year}`;
+  }
+
+  return (
+    <Sidebar
+      variant="inset"
+      collapsible="icon"
+      className="!top-[50px] !h-[calc(100vh-50px)] border-r border-zinc-100 px-0"
+    >
+      {isCollapsed && (
+        <SidebarHeader
+          className={cn(
+            "flex",
+            isCollapsed
+              ? "flex-row items-center justify-between gap-y-4 md:flex-col md:items-start md:justify-start"
+              : "flex-row items-center justify-between",
+          )}
+        >
+          <motion.div
+            key={isCollapsed ? "header-collapsed" : "header-expanded"}
+            className="flex flex-col items-center gap-3 pt-4"
+            initial={{ opacity: 0, filter: "blur(3px)" }}
+            animate={{ opacity: 1, filter: "blur(0px)" }}
+            transition={{ type: "spring", bounce: 0.2 }}
+          >
+            <div className="flex flex-col items-center gap-2">
+              <SidebarTrigger />
+              <Button
+                variant="ghost"
+                onClick={handleNewChat}
+                style={{ minWidth: "auto", width: "auto" }}
+              >
+                <PlusCircleIcon className="!size-5" />
+                <span className="sr-only">New Chat</span>
+              </Button>
+            </div>
+          </motion.div>
+        </SidebarHeader>
+      )}
+      <SidebarContent className="gap-4 overflow-y-auto px-4 py-4 [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+        {!isCollapsed && (
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.1 }}
+            className="flex items-center justify-between px-3"
+          >
+            <Text variant="h3" size="body-medium">
+              Your chats
+            </Text>
+            <div className="relative left-6">
+              <SidebarTrigger />
+            </div>
+          </motion.div>
+        )}
+
+        {!isCollapsed && (
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.15 }}
+            className="mt-4 flex flex-col gap-1"
+          >
+            {isLoadingSessions ? (
+              <div className="flex min-h-[30rem] items-center justify-center py-4">
+                <LoadingSpinner size="small" className="text-neutral-600" />
+              </div>
+            ) : sessions.length === 0 ? (
+              <p className="py-4 text-center text-sm text-neutral-500">
+                No conversations yet
+              </p>
+            ) : (
+              sessions.map((session) => (
+                <button
+                  key={session.id}
+                  onClick={() => handleSelectSession(session.id)}
+                  className={cn(
+                    "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+                    session.id === sessionId
+                      ? "bg-zinc-100"
+                      : "hover:bg-zinc-50",
+                  )}
+                >
+                  <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
+                    <div className="min-w-0 max-w-full">
+                      <Text
+                        variant="body"
+                        className={cn(
+                          "truncate font-normal",
+                          session.id === sessionId
+                            ? "text-zinc-600"
+                            : "text-zinc-800",
+                        )}
+                      >
+                        {session.title || `Untitled chat`}
+                      </Text>
+                    </div>
+                    <Text variant="small" className="text-neutral-400">
+                      {formatDate(session.updated_at)}
+                    </Text>
+                  </div>
+                </button>
+              ))
+            )}
+          </motion.div>
+        )}
+      </SidebarContent>
+      {!isCollapsed && sessionId && (
+        <SidebarFooter className="shrink-0 bg-zinc-50 p-3 pb-1 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+          <motion.div
+            initial={{ opacity: 0 }}
+            animate={{ opacity: 1 }}
+            transition={{ duration: 0.2, delay: 0.2 }}
+          >
+            <Button
+              variant="primary"
+              size="small"
+              onClick={handleNewChat}
+              className="w-full"
+              leftIcon={<PlusIcon className="h-4 w-4" weight="bold" />}
+            >
+              New Chat
+            </Button>
+          </motion.div>
+        </SidebarFooter>
+      )}
+    </Sidebar>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/CopilotChatActionsProvider.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/CopilotChatActionsProvider.tsx
new file mode 100644
index 0000000000..5c80348e8c
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/CopilotChatActionsProvider.tsx
@@ -0,0 +1,16 @@
+"use client";
+
+import { CopilotChatActionsContext } from "./useCopilotChatActions";
+
+interface Props {
+  onSend: (message: string) => void | Promise<void>;
+  children: React.ReactNode;
+}
+
+export function CopilotChatActionsProvider({ onSend, children }: Props) {
+  return (
+    <CopilotChatActionsContext.Provider value={{ onSend }}>
+      {children}
+    </CopilotChatActionsContext.Provider>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/useCopilotChatActions.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/useCopilotChatActions.ts
new file mode 100644
index 0000000000..31b27c0f6e
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/useCopilotChatActions.ts
@@ -0,0 +1,23 @@
+"use client";
+
+import { createContext, useContext } from "react";
+
+interface CopilotChatActions {
+  onSend: (message: string) => void | Promise<void>;
+}
+
+const CopilotChatActionsContext = createContext<CopilotChatActions | null>(
+  null,
+);
+
+export function useCopilotChatActions(): CopilotChatActions {
+  const ctx = useContext(CopilotChatActionsContext);
+  if (!ctx) {
+    throw new Error(
+      "useCopilotChatActions must be used within CopilotChatActionsProvider",
+    );
+  }
+  return ctx;
+}
+
+export { CopilotChatActionsContext };
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/CopilotShell.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/CopilotShell.tsx
deleted file mode 100644
index 3f695da5ed..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/CopilotShell.tsx
+++ /dev/null
@@ -1,99 +0,0 @@
-"use client";
-
-import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
-import { Text } from "@/components/atoms/Text/Text";
-import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
-import type { ReactNode } from "react";
-import { DesktopSidebar } from "./components/DesktopSidebar/DesktopSidebar";
-import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
-import { MobileHeader } from "./components/MobileHeader/MobileHeader";
-import { useCopilotShell } from "./useCopilotShell";
-
-interface Props {
-  children: ReactNode;
-}
-
-export function CopilotShell({ children }: Props) {
-  const {
-    isMobile,
-    isDrawerOpen,
-    isLoading,
-    isCreatingSession,
-    isLoggedIn,
-    hasActiveSession,
-    sessions,
-    currentSessionId,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-    handleNewChatClick,
-    handleSessionClick,
-    hasNextPage,
-    isFetchingNextPage,
-    fetchNextPage,
-  } = useCopilotShell();
-
-  if (!isLoggedIn) {
-    return (
-      <div className="flex h-full items-center justify-center">
-        <ChatLoader />
-      </div>
-    );
-  }
-
-  return (
-    <div
-      className="flex overflow-hidden bg-[#EFEFF0]"
-      style={{ height: `calc(100vh - ${NAVBAR_HEIGHT_PX}px)` }}
-    >
-      {!isMobile && (
-        <DesktopSidebar
-          sessions={sessions}
-          currentSessionId={currentSessionId}
-          isLoading={isLoading}
-          hasNextPage={hasNextPage}
-          isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSessionClick}
-          onFetchNextPage={fetchNextPage}
-          onNewChat={handleNewChatClick}
-          hasActiveSession={Boolean(hasActiveSession)}
-        />
-      )}
-
-      <div className="relative flex min-h-0 flex-1 flex-col">
-        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
-        <div className="flex min-h-0 flex-1 flex-col">
-          {isCreatingSession ? (
-            <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9]">
-              <div className="flex flex-col items-center gap-4">
-                <ChatLoader />
-                <Text variant="body" className="text-zinc-500">
-                  Creating your chat...
-                </Text>
-              </div>
-            </div>
-          ) : (
-            children
-          )}
-        </div>
-      </div>
-
-      {isMobile && (
-        <MobileDrawer
-          isOpen={isDrawerOpen}
-          sessions={sessions}
-          currentSessionId={currentSessionId}
-          isLoading={isLoading}
-          hasNextPage={hasNextPage}
-          isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={handleSessionClick}
-          onFetchNextPage={fetchNextPage}
-          onNewChat={handleNewChatClick}
-          onClose={handleCloseDrawer}
-          onOpenChange={handleDrawerOpenChange}
-          hasActiveSession={Boolean(hasActiveSession)}
-        />
-      )}
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/DesktopSidebar/DesktopSidebar.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/DesktopSidebar/DesktopSidebar.tsx
deleted file mode 100644
index 122a09a02f..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/DesktopSidebar/DesktopSidebar.tsx
+++ /dev/null
@@ -1,70 +0,0 @@
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { scrollbarStyles } from "@/components/styles/scrollbars";
-import { cn } from "@/lib/utils";
-import { Plus } from "@phosphor-icons/react";
-import { SessionsList } from "../SessionsList/SessionsList";
-
-interface Props {
-  sessions: SessionSummaryResponse[];
-  currentSessionId: string | null;
-  isLoading: boolean;
-  hasNextPage: boolean;
-  isFetchingNextPage: boolean;
-  onSelectSession: (sessionId: string) => void;
-  onFetchNextPage: () => void;
-  onNewChat: () => void;
-  hasActiveSession: boolean;
-}
-
-export function DesktopSidebar({
-  sessions,
-  currentSessionId,
-  isLoading,
-  hasNextPage,
-  isFetchingNextPage,
-  onSelectSession,
-  onFetchNextPage,
-  onNewChat,
-  hasActiveSession,
-}: Props) {
-  return (
-    <aside className="flex h-full w-80 flex-col border-r border-zinc-100 bg-zinc-50">
-      <div className="shrink-0 px-6 py-4">
-        <Text variant="h3" size="body-medium">
-          Your chats
-        </Text>
-      </div>
-      <div
-        className={cn(
-          "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
-          scrollbarStyles,
-        )}
-      >
-        <SessionsList
-          sessions={sessions}
-          currentSessionId={currentSessionId}
-          isLoading={isLoading}
-          hasNextPage={hasNextPage}
-          isFetchingNextPage={isFetchingNextPage}
-          onSelectSession={onSelectSession}
-          onFetchNextPage={onFetchNextPage}
-        />
-      </div>
-      {hasActiveSession && (
-        <div className="shrink-0 bg-zinc-50 p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
-          <Button
-            variant="primary"
-            size="small"
-            onClick={onNewChat}
-            className="w-full"
-            leftIcon={<Plus width="1rem" height="1rem" />}
-          >
-            New Chat
-          </Button>
-        </div>
-      )}
-    </aside>
-  );
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/MobileDrawer.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/MobileDrawer.tsx
deleted file mode 100644
index ea3b39f829..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/MobileDrawer.tsx
+++ /dev/null
@@ -1,91 +0,0 @@
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { Button } from "@/components/atoms/Button/Button";
-import { scrollbarStyles } from "@/components/styles/scrollbars";
-import { cn } from "@/lib/utils";
-import { PlusIcon, X } from "@phosphor-icons/react";
-import { Drawer } from "vaul";
-import { SessionsList } from "../SessionsList/SessionsList";
-
-interface Props {
-  isOpen: boolean;
-  sessions: SessionSummaryResponse[];
-  currentSessionId: string | null;
-  isLoading: boolean;
-  hasNextPage: boolean;
-  isFetchingNextPage: boolean;
-  onSelectSession: (sessionId: string) => void;
-  onFetchNextPage: () => void;
-  onNewChat: () => void;
-  onClose: () => void;
-  onOpenChange: (open: boolean) => void;
-  hasActiveSession: boolean;
-}
-
-export function MobileDrawer({
-  isOpen,
-  sessions,
-  currentSessionId,
-  isLoading,
-  hasNextPage,
-  isFetchingNextPage,
-  onSelectSession,
-  onFetchNextPage,
-  onNewChat,
-  onClose,
-  onOpenChange,
-  hasActiveSession,
-}: Props) {
-  return (
-    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
-      <Drawer.Portal>
-        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
-        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
-          <div className="shrink-0 border-b border-zinc-200 p-4">
-            <div className="flex items-center justify-between">
-              <Drawer.Title className="text-lg font-semibold text-zinc-800">
-                Your chats
-              </Drawer.Title>
-              <Button
-                variant="icon"
-                size="icon"
-                aria-label="Close sessions"
-                onClick={onClose}
-              >
-                <X width="1.25rem" height="1.25rem" />
-              </Button>
-            </div>
-          </div>
-          <div
-            className={cn(
-              "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
-              scrollbarStyles,
-            )}
-          >
-            <SessionsList
-              sessions={sessions}
-              currentSessionId={currentSessionId}
-              isLoading={isLoading}
-              hasNextPage={hasNextPage}
-              isFetchingNextPage={isFetchingNextPage}
-              onSelectSession={onSelectSession}
-              onFetchNextPage={onFetchNextPage}
-            />
-          </div>
-          {hasActiveSession && (
-            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
-              <Button
-                variant="primary"
-                size="small"
-                onClick={onNewChat}
-                className="w-full"
-                leftIcon={<PlusIcon width="1rem" height="1rem" />}
-              >
-                New Chat
-              </Button>
-            </div>
-          )}
-        </Drawer.Content>
-      </Drawer.Portal>
-    </Drawer.Root>
-  );
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/useMobileDrawer.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/useMobileDrawer.ts
deleted file mode 100644
index 2ef63a4422..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/useMobileDrawer.ts
+++ /dev/null
@@ -1,24 +0,0 @@
-import { useState } from "react";
-
-export function useMobileDrawer() {
-  const [isDrawerOpen, setIsDrawerOpen] = useState(false);
-
-  const handleOpenDrawer = () => {
-    setIsDrawerOpen(true);
-  };
-
-  const handleCloseDrawer = () => {
-    setIsDrawerOpen(false);
-  };
-
-  const handleDrawerOpenChange = (open: boolean) => {
-    setIsDrawerOpen(open);
-  };
-
-  return {
-    isDrawerOpen,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-  };
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/SessionsList.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/SessionsList.tsx
deleted file mode 100644
index ef63e1aff4..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/SessionsList.tsx
+++ /dev/null
@@ -1,80 +0,0 @@
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { Skeleton } from "@/components/__legacy__/ui/skeleton";
-import { Text } from "@/components/atoms/Text/Text";
-import { InfiniteList } from "@/components/molecules/InfiniteList/InfiniteList";
-import { cn } from "@/lib/utils";
-import { getSessionTitle } from "../../helpers";
-
-interface Props {
-  sessions: SessionSummaryResponse[];
-  currentSessionId: string | null;
-  isLoading: boolean;
-  hasNextPage: boolean;
-  isFetchingNextPage: boolean;
-  onSelectSession: (sessionId: string) => void;
-  onFetchNextPage: () => void;
-}
-
-export function SessionsList({
-  sessions,
-  currentSessionId,
-  isLoading,
-  hasNextPage,
-  isFetchingNextPage,
-  onSelectSession,
-  onFetchNextPage,
-}: Props) {
-  if (isLoading) {
-    return (
-      <div className="space-y-1">
-        {Array.from({ length: 5 }).map((_, i) => (
-          <div key={i} className="rounded-lg px-3 py-2.5">
-            <Skeleton className="h-5 w-full" />
-          </div>
-        ))}
-      </div>
-    );
-  }
-
-  if (sessions.length === 0) {
-    return (
-      <div className="flex h-full items-center justify-center">
-        <Text variant="body" className="text-zinc-500">
-          You don&apos;t have previous chats
-        </Text>
-      </div>
-    );
-  }
-
-  return (
-    <InfiniteList
-      items={sessions}
-      hasMore={hasNextPage}
-      isFetchingMore={isFetchingNextPage}
-      onEndReached={onFetchNextPage}
-      className="space-y-1"
-      renderItem={(session) => {
-        const isActive = session.id === currentSessionId;
-        return (
-          <button
-            onClick={() => onSelectSession(session.id)}
-            className={cn(
-              "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
-              isActive ? "bg-zinc-100" : "hover:bg-zinc-50",
-            )}
-          >
-            <Text
-              variant="body"
-              className={cn(
-                "font-normal",
-                isActive ? "text-zinc-600" : "text-zinc-800",
-              )}
-            >
-              {getSessionTitle(session)}
-            </Text>
-          </button>
-        );
-      }}
-    />
-  );
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/useSessionsPagination.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/useSessionsPagination.ts
deleted file mode 100644
index 61e3e6f37f..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/useSessionsPagination.ts
+++ /dev/null
@@ -1,91 +0,0 @@
-import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { okData } from "@/app/api/helpers";
-import { useEffect, useState } from "react";
-
-const PAGE_SIZE = 50;
-
-export interface UseSessionsPaginationArgs {
-  enabled: boolean;
-}
-
-export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
-  const [offset, setOffset] = useState(0);
-
-  const [accumulatedSessions, setAccumulatedSessions] = useState<
-    SessionSummaryResponse[]
-  >([]);
-
-  const [totalCount, setTotalCount] = useState<number | null>(null);
-
-  const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
-    { limit: PAGE_SIZE, offset },
-    {
-      query: {
-        enabled: enabled && offset >= 0,
-      },
-    },
-  );
-
-  useEffect(() => {
-    const responseData = okData(data);
-    if (responseData) {
-      const newSessions = responseData.sessions;
-      const total = responseData.total;
-      setTotalCount(total);
-
-      if (offset === 0) {
-        setAccumulatedSessions(newSessions);
-      } else {
-        setAccumulatedSessions((prev) => [...prev, ...newSessions]);
-      }
-    } else if (!enabled) {
-      setAccumulatedSessions([]);
-      setTotalCount(null);
-    }
-  }, [data, offset, enabled]);
-
-  const hasNextPage =
-    totalCount !== null && accumulatedSessions.length < totalCount;
-
-  const areAllSessionsLoaded =
-    totalCount !== null &&
-    accumulatedSessions.length >= totalCount &&
-    !isFetching &&
-    !isLoading;
-
-  useEffect(() => {
-    if (
-      hasNextPage &&
-      !isFetching &&
-      !isLoading &&
-      !isError &&
-      totalCount !== null
-    ) {
-      setOffset((prev) => prev + PAGE_SIZE);
-    }
-  }, [hasNextPage, isFetching, isLoading, isError, totalCount]);
-
-  const fetchNextPage = () => {
-    if (hasNextPage && !isFetching) {
-      setOffset((prev) => prev + PAGE_SIZE);
-    }
-  };
-
-  const reset = () => {
-    // Only reset the offset - keep existing sessions visible during refetch
-    // The effect will replace sessions when new data arrives at offset 0
-    setOffset(0);
-  };
-
-  return {
-    sessions: accumulatedSessions,
-    isLoading,
-    isFetching,
-    hasNextPage,
-    areAllSessionsLoaded,
-    totalCount,
-    fetchNextPage,
-    reset,
-  };
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/helpers.ts
deleted file mode 100644
index ef0d414edf..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/helpers.ts
+++ /dev/null
@@ -1,106 +0,0 @@
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { format, formatDistanceToNow, isToday } from "date-fns";
-
-export function convertSessionDetailToSummary(session: SessionDetailResponse) {
-  return {
-    id: session.id,
-    created_at: session.created_at,
-    updated_at: session.updated_at,
-    title: undefined,
-  };
-}
-
-export function filterVisibleSessions(sessions: SessionSummaryResponse[]) {
-  const fiveMinutesAgo = Date.now() - 5 * 60 * 1000;
-  return sessions.filter((session) => {
-    const hasBeenUpdated = session.updated_at !== session.created_at;
-
-    if (hasBeenUpdated) return true;
-
-    const isRecentlyCreated =
-      new Date(session.created_at).getTime() > fiveMinutesAgo;
-
-    return isRecentlyCreated;
-  });
-}
-
-export function getSessionTitle(session: SessionSummaryResponse) {
-  if (session.title) return session.title;
-
-  const isNewSession = session.updated_at === session.created_at;
-
-  if (isNewSession) {
-    const createdDate = new Date(session.created_at);
-    if (isToday(createdDate)) {
-      return "Today";
-    }
-    return format(createdDate, "MMM d, yyyy");
-  }
-
-  return "Untitled Chat";
-}
-
-export function getSessionUpdatedLabel(session: SessionSummaryResponse) {
-  if (!session.updated_at) return "";
-  return formatDistanceToNow(new Date(session.updated_at), { addSuffix: true });
-}
-
-export function mergeCurrentSessionIntoList(
-  accumulatedSessions: SessionSummaryResponse[],
-  currentSessionId: string | null,
-  currentSessionData: SessionDetailResponse | null | undefined,
-  recentlyCreatedSessions?: Map<string, SessionSummaryResponse>,
-) {
-  const filteredSessions: SessionSummaryResponse[] = [];
-  const addedIds = new Set<string>();
-
-  if (accumulatedSessions.length > 0) {
-    const visibleSessions = filterVisibleSessions(accumulatedSessions);
-
-    if (currentSessionId) {
-      const currentInAll = accumulatedSessions.find(
-        (s) => s.id === currentSessionId,
-      );
-      if (currentInAll) {
-        const isInVisible = visibleSessions.some(
-          (s) => s.id === currentSessionId,
-        );
-        if (!isInVisible) {
-          filteredSessions.push(currentInAll);
-          addedIds.add(currentInAll.id);
-        }
-      }
-    }
-
-    for (const session of visibleSessions) {
-      if (!addedIds.has(session.id)) {
-        filteredSessions.push(session);
-        addedIds.add(session.id);
-      }
-    }
-  }
-
-  if (currentSessionId && currentSessionData) {
-    if (!addedIds.has(currentSessionId)) {
-      const summarySession = convertSessionDetailToSummary(currentSessionData);
-      filteredSessions.unshift(summarySession);
-      addedIds.add(currentSessionId);
-    }
-  }
-
-  if (recentlyCreatedSessions) {
-    for (const [sessionId, sessionData] of recentlyCreatedSessions) {
-      if (!addedIds.has(sessionId)) {
-        filteredSessions.unshift(sessionData);
-        addedIds.add(sessionId);
-      }
-    }
-  }
-
-  return filteredSessions;
-}
-
-export function getCurrentSessionId(searchParams: URLSearchParams) {
-  return searchParams.get("sessionId");
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useCopilotShell.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useCopilotShell.ts
deleted file mode 100644
index 74fd663ab2..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useCopilotShell.ts
+++ /dev/null
@@ -1,171 +0,0 @@
-"use client";
-
-import {
-  getGetV2GetSessionQueryKey,
-  getGetV2ListSessionsQueryKey,
-  useGetV2GetSession,
-} from "@/app/api/__generated__/endpoints/chat/chat";
-import { okData } from "@/app/api/helpers";
-import { useChatStore } from "@/components/contextual/Chat/chat-store";
-import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
-import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { useQueryClient } from "@tanstack/react-query";
-import { usePathname, useSearchParams } from "next/navigation";
-import { useRef } from "react";
-import { useCopilotStore } from "../../copilot-page-store";
-import { useCopilotSessionId } from "../../useCopilotSessionId";
-import { useMobileDrawer } from "./components/MobileDrawer/useMobileDrawer";
-import { getCurrentSessionId } from "./helpers";
-import { useShellSessionList } from "./useShellSessionList";
-
-export function useCopilotShell() {
-  const pathname = usePathname();
-  const searchParams = useSearchParams();
-  const queryClient = useQueryClient();
-  const breakpoint = useBreakpoint();
-  const { isLoggedIn } = useSupabase();
-  const isMobile =
-    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
-
-  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
-
-  const isOnHomepage = pathname === "/copilot";
-  const paramSessionId = searchParams.get("sessionId");
-
-  const {
-    isDrawerOpen,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-  } = useMobileDrawer();
-
-  const paginationEnabled = !isMobile || isDrawerOpen || !!paramSessionId;
-
-  const currentSessionId = getCurrentSessionId(searchParams);
-
-  const { data: currentSessionData } = useGetV2GetSession(
-    currentSessionId || "",
-    {
-      query: {
-        enabled: !!currentSessionId,
-        select: okData,
-      },
-    },
-  );
-
-  const {
-    sessions,
-    isLoading,
-    isSessionsFetching,
-    hasNextPage,
-    fetchNextPage,
-    resetPagination,
-    recentlyCreatedSessionsRef,
-  } = useShellSessionList({
-    paginationEnabled,
-    currentSessionId,
-    currentSessionData,
-    isOnHomepage,
-    paramSessionId,
-  });
-
-  const stopStream = useChatStore((s) => s.stopStream);
-  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
-  const isStreaming = useCopilotStore((s) => s.isStreaming);
-  const isCreatingSession = useCopilotStore((s) => s.isCreatingSession);
-  const setIsSwitchingSession = useCopilotStore((s) => s.setIsSwitchingSession);
-  const openInterruptModal = useCopilotStore((s) => s.openInterruptModal);
-
-  const pendingActionRef = useRef<(() => void) | null>(null);
-
-  async function stopCurrentStream() {
-    if (!currentSessionId) return;
-
-    setIsSwitchingSession(true);
-    await new Promise<void>((resolve) => {
-      const unsubscribe = onStreamComplete((completedId) => {
-        if (completedId === currentSessionId) {
-          clearTimeout(timeout);
-          unsubscribe();
-          resolve();
-        }
-      });
-      const timeout = setTimeout(() => {
-        unsubscribe();
-        resolve();
-      }, 3000);
-      stopStream(currentSessionId);
-    });
-
-    queryClient.invalidateQueries({
-      queryKey: getGetV2GetSessionQueryKey(currentSessionId),
-    });
-    setIsSwitchingSession(false);
-  }
-
-  function selectSession(sessionId: string) {
-    if (sessionId === currentSessionId) return;
-    if (recentlyCreatedSessionsRef.current.has(sessionId)) {
-      queryClient.invalidateQueries({
-        queryKey: getGetV2GetSessionQueryKey(sessionId),
-      });
-    }
-    setUrlSessionId(sessionId, { shallow: false });
-    if (isMobile) handleCloseDrawer();
-  }
-
-  function startNewChat() {
-    resetPagination();
-    queryClient.invalidateQueries({
-      queryKey: getGetV2ListSessionsQueryKey(),
-    });
-    setUrlSessionId(null, { shallow: false });
-    if (isMobile) handleCloseDrawer();
-  }
-
-  function handleSessionClick(sessionId: string) {
-    if (sessionId === currentSessionId) return;
-
-    if (isStreaming) {
-      pendingActionRef.current = async () => {
-        await stopCurrentStream();
-        selectSession(sessionId);
-      };
-      openInterruptModal(pendingActionRef.current);
-    } else {
-      selectSession(sessionId);
-    }
-  }
-
-  function handleNewChatClick() {
-    if (isStreaming) {
-      pendingActionRef.current = async () => {
-        await stopCurrentStream();
-        startNewChat();
-      };
-      openInterruptModal(pendingActionRef.current);
-    } else {
-      startNewChat();
-    }
-  }
-
-  return {
-    isMobile,
-    isDrawerOpen,
-    isLoggedIn,
-    hasActiveSession:
-      Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
-    isLoading: isLoading || isCreatingSession,
-    isCreatingSession,
-    sessions,
-    currentSessionId: urlSessionId,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-    handleNewChatClick,
-    handleSessionClick,
-    hasNextPage,
-    isFetchingNextPage: isSessionsFetching,
-    fetchNextPage,
-  };
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useShellSessionList.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useShellSessionList.ts
deleted file mode 100644
index fb39a11096..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useShellSessionList.ts
+++ /dev/null
@@ -1,113 +0,0 @@
-import { getGetV2ListSessionsQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { useChatStore } from "@/components/contextual/Chat/chat-store";
-import { useQueryClient } from "@tanstack/react-query";
-import { useEffect, useMemo, useRef } from "react";
-import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
-import {
-  convertSessionDetailToSummary,
-  filterVisibleSessions,
-  mergeCurrentSessionIntoList,
-} from "./helpers";
-
-interface UseShellSessionListArgs {
-  paginationEnabled: boolean;
-  currentSessionId: string | null;
-  currentSessionData: SessionDetailResponse | null | undefined;
-  isOnHomepage: boolean;
-  paramSessionId: string | null;
-}
-
-export function useShellSessionList({
-  paginationEnabled,
-  currentSessionId,
-  currentSessionData,
-  isOnHomepage,
-  paramSessionId,
-}: UseShellSessionListArgs) {
-  const queryClient = useQueryClient();
-  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
-
-  const {
-    sessions: accumulatedSessions,
-    isLoading: isSessionsLoading,
-    isFetching: isSessionsFetching,
-    hasNextPage,
-    fetchNextPage,
-    reset: resetPagination,
-  } = useSessionsPagination({
-    enabled: paginationEnabled,
-  });
-
-  const recentlyCreatedSessionsRef = useRef<
-    Map<string, SessionSummaryResponse>
-  >(new Map());
-
-  useEffect(() => {
-    if (isOnHomepage && !paramSessionId) {
-      queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-    }
-  }, [isOnHomepage, paramSessionId, queryClient]);
-
-  useEffect(() => {
-    if (currentSessionId && currentSessionData) {
-      const isNewSession =
-        currentSessionData.updated_at === currentSessionData.created_at;
-      const isNotInAccumulated = !accumulatedSessions.some(
-        (s) => s.id === currentSessionId,
-      );
-      if (isNewSession || isNotInAccumulated) {
-        const summary = convertSessionDetailToSummary(currentSessionData);
-        recentlyCreatedSessionsRef.current.set(currentSessionId, summary);
-      }
-    }
-  }, [currentSessionId, currentSessionData, accumulatedSessions]);
-
-  useEffect(() => {
-    for (const sessionId of recentlyCreatedSessionsRef.current.keys()) {
-      if (accumulatedSessions.some((s) => s.id === sessionId)) {
-        recentlyCreatedSessionsRef.current.delete(sessionId);
-      }
-    }
-  }, [accumulatedSessions]);
-
-  useEffect(() => {
-    const unsubscribe = onStreamComplete(() => {
-      queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-    });
-    return unsubscribe;
-  }, [onStreamComplete, queryClient]);
-
-  const sessions = useMemo(
-    () =>
-      mergeCurrentSessionIntoList(
-        accumulatedSessions,
-        currentSessionId,
-        currentSessionData,
-        recentlyCreatedSessionsRef.current,
-      ),
-    [accumulatedSessions, currentSessionId, currentSessionData],
-  );
-
-  const visibleSessions = useMemo(
-    () => filterVisibleSessions(sessions),
-    [sessions],
-  );
-
-  const isLoading = isSessionsLoading && accumulatedSessions.length === 0;
-
-  return {
-    sessions: visibleSessions,
-    isLoading,
-    isSessionsFetching,
-    hasNextPage,
-    fetchNextPage,
-    resetPagination,
-    recentlyCreatedSessionsRef,
-  };
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/EmptySession.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/EmptySession.tsx
new file mode 100644
index 0000000000..cbbe6c570e
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/EmptySession.tsx
@@ -0,0 +1,111 @@
+"use client";
+
+import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { SpinnerGapIcon } from "@phosphor-icons/react";
+import { motion } from "framer-motion";
+import { useEffect, useState } from "react";
+import {
+  getGreetingName,
+  getInputPlaceholder,
+  getQuickActions,
+} from "./helpers";
+
+interface Props {
+  inputLayoutId: string;
+  isCreatingSession: boolean;
+  onCreateSession: () => void | Promise<string>;
+  onSend: (message: string) => void | Promise<void>;
+}
+
+export function EmptySession({
+  inputLayoutId,
+  isCreatingSession,
+  onSend,
+}: Props) {
+  const { user } = useSupabase();
+  const greetingName = getGreetingName(user);
+  const quickActions = getQuickActions();
+  const [loadingAction, setLoadingAction] = useState<string | null>(null);
+  const [inputPlaceholder, setInputPlaceholder] = useState(
+    getInputPlaceholder(),
+  );
+
+  useEffect(() => {
+    setInputPlaceholder(getInputPlaceholder(window.innerWidth));
+  }, [window.innerWidth]);
+
+  async function handleQuickActionClick(action: string) {
+    if (isCreatingSession || loadingAction) return;
+
+    setLoadingAction(action);
+    try {
+      await onSend(action);
+    } finally {
+      setLoadingAction(null);
+    }
+  }
+
+  return (
+    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-0 py-5 md:px-6 md:py-10">
+      <motion.div
+        className="w-full max-w-3xl text-center"
+        initial={{ opacity: 0 }}
+        animate={{ opacity: 1 }}
+        transition={{ duration: 0.3 }}
+      >
+        <div className="mx-auto max-w-3xl">
+          <Text variant="h3" className="mb-1 !text-[1.375rem] text-zinc-700">
+            Hey, <span className="text-violet-600">{greetingName}</span>
+          </Text>
+          <Text variant="h3" className="mb-8 !font-normal">
+            Tell me about your work — I&apos;ll find what to automate.
+          </Text>
+
+          <div className="mb-6">
+            <motion.div
+              layoutId={inputLayoutId}
+              transition={{ type: "spring", bounce: 0.2, duration: 0.65 }}
+              className="w-full px-2"
+            >
+              <ChatInput
+                inputId="chat-input-empty"
+                onSend={onSend}
+                disabled={isCreatingSession}
+                placeholder={inputPlaceholder}
+                className="w-full"
+              />
+            </motion.div>
+          </div>
+        </div>
+
+        <div className="flex flex-wrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+          {quickActions.map((action) => (
+            <Button
+              key={action}
+              type="button"
+              variant="outline"
+              size="small"
+              onClick={() => void handleQuickActionClick(action)}
+              disabled={isCreatingSession || loadingAction !== null}
+              aria-busy={loadingAction === action}
+              leftIcon={
+                loadingAction === action ? (
+                  <SpinnerGapIcon
+                    className="h-4 w-4 animate-spin"
+                    weight="bold"
+                  />
+                ) : null
+              }
+              className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
+            >
+              {action}
+            </Button>
+          ))}
+        </div>
+      </motion.div>
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/helpers.ts
new file mode 100644
index 0000000000..f6f8980fd4
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/helpers.ts
@@ -0,0 +1,38 @@
+import { User } from "@supabase/supabase-js";
+
+export function getInputPlaceholder(width?: number) {
+  if (!width) return "What's your role and what eats up most of your day?";
+
+  if (width < 500) {
+    return "I'm a chef and I hate...";
+  }
+  if (width <= 1080) {
+    return "What's your role and what eats up most of your day?";
+  }
+  return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
+}
+
+export function getQuickActions() {
+  return [
+    "I don't know where to start, just ask me stuff",
+    "I do the same thing every week and it's killing me",
+    "Help me find where I'm wasting my time",
+  ];
+}
+
+export function getGreetingName(user?: User | null) {
+  if (!user) return "there";
+  const metadata = user.user_metadata as Record<string, unknown> | undefined;
+  const fullName = metadata?.full_name;
+  const name = metadata?.name;
+  if (typeof fullName === "string" && fullName.trim()) {
+    return fullName.split(" ")[0];
+  }
+  if (typeof name === "string" && name.trim()) {
+    return name.split(" ")[0];
+  }
+  if (user.email) {
+    return user.email.split("@")[0];
+  }
+  return "there";
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/MobileDrawer/MobileDrawer.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/MobileDrawer/MobileDrawer.tsx
new file mode 100644
index 0000000000..80ccfc9c03
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/MobileDrawer/MobileDrawer.tsx
@@ -0,0 +1,140 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { PlusIcon, SpinnerGapIcon, X } from "@phosphor-icons/react";
+import { Drawer } from "vaul";
+
+interface Props {
+  isOpen: boolean;
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onNewChat: () => void;
+  onClose: () => void;
+  onOpenChange: (open: boolean) => void;
+}
+
+function formatDate(dateString: string) {
+  const date = new Date(dateString);
+  const now = new Date();
+  const diffMs = now.getTime() - date.getTime();
+  const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
+
+  if (diffDays === 0) return "Today";
+  if (diffDays === 1) return "Yesterday";
+  if (diffDays < 7) return `${diffDays} days ago`;
+
+  const day = date.getDate();
+  const ordinal =
+    day % 10 === 1 && day !== 11
+      ? "st"
+      : day % 10 === 2 && day !== 12
+        ? "nd"
+        : day % 10 === 3 && day !== 13
+          ? "rd"
+          : "th";
+  const month = date.toLocaleDateString("en-US", { month: "short" });
+  const year = date.getFullYear();
+
+  return `${day}${ordinal} ${month} ${year}`;
+}
+
+export function MobileDrawer({
+  isOpen,
+  sessions,
+  currentSessionId,
+  isLoading,
+  onSelectSession,
+  onNewChat,
+  onClose,
+  onOpenChange,
+}: Props) {
+  return (
+    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
+      <Drawer.Portal>
+        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
+        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
+          <div className="shrink-0 border-b border-zinc-200 px-4 py-2">
+            <div className="flex items-center justify-between">
+              <Drawer.Title className="text-lg font-semibold text-zinc-800">
+                Your chats
+              </Drawer.Title>
+              <Button
+                variant="icon"
+                size="icon"
+                aria-label="Close sessions"
+                onClick={onClose}
+              >
+                <X width="1rem" height="1rem" />
+              </Button>
+            </div>
+          </div>
+          <div
+            className={cn(
+              "flex min-h-0 flex-1 flex-col gap-1 overflow-y-auto px-3 py-3",
+              scrollbarStyles,
+            )}
+          >
+            {isLoading ? (
+              <div className="flex items-center justify-center py-4">
+                <SpinnerGapIcon className="h-5 w-5 animate-spin text-neutral-400" />
+              </div>
+            ) : sessions.length === 0 ? (
+              <p className="py-4 text-center text-sm text-neutral-500">
+                No conversations yet
+              </p>
+            ) : (
+              sessions.map((session) => (
+                <button
+                  key={session.id}
+                  onClick={() => onSelectSession(session.id)}
+                  className={cn(
+                    "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+                    session.id === currentSessionId
+                      ? "bg-zinc-100"
+                      : "hover:bg-zinc-50",
+                  )}
+                >
+                  <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
+                    <div className="min-w-0 max-w-full">
+                      <Text
+                        variant="body"
+                        className={cn(
+                          "truncate font-normal",
+                          session.id === currentSessionId
+                            ? "text-zinc-600"
+                            : "text-zinc-800",
+                        )}
+                      >
+                        {session.title || "Untitled chat"}
+                      </Text>
+                    </div>
+                    <Text variant="small" className="text-neutral-400">
+                      {formatDate(session.updated_at)}
+                    </Text>
+                  </div>
+                </button>
+              ))
+            )}
+          </div>
+          {currentSessionId && (
+            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+              <Button
+                variant="primary"
+                size="small"
+                onClick={onNewChat}
+                className="w-full"
+                leftIcon={<PlusIcon width="1rem" height="1rem" />}
+              >
+                New Chat
+              </Button>
+            </div>
+          )}
+        </Drawer.Content>
+      </Drawer.Portal>
+    </Drawer.Root>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileHeader/MobileHeader.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/MobileHeader/MobileHeader.tsx
similarity index 100%
rename from autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileHeader/MobileHeader.tsx
rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/MobileHeader/MobileHeader.tsx
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/MorphingTextAnimation/MorphingTextAnimation.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/MorphingTextAnimation/MorphingTextAnimation.tsx
new file mode 100644
index 0000000000..aac615bb2b
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/MorphingTextAnimation/MorphingTextAnimation.tsx
@@ -0,0 +1,54 @@
+import { cn } from "@/lib/utils";
+import { AnimatePresence, motion } from "framer-motion";
+
+interface Props {
+  text: string;
+  className?: string;
+}
+
+export function MorphingTextAnimation({ text, className }: Props) {
+  const letters = text.split("");
+
+  return (
+    <div className={cn(className)}>
+      <AnimatePresence mode="popLayout" initial={false}>
+        <motion.div key={text} className="whitespace-nowrap">
+          <motion.span className="inline-flex overflow-hidden">
+            {letters.map((char, index) => (
+              <motion.span
+                key={`${text}-${index}`}
+                initial={{
+                  opacity: 0,
+                  y: 8,
+                  rotateX: "80deg",
+                  filter: "blur(6px)",
+                }}
+                animate={{
+                  opacity: 1,
+                  y: 0,
+                  rotateX: "0deg",
+                  filter: "blur(0px)",
+                }}
+                exit={{
+                  opacity: 0,
+                  y: -8,
+                  rotateX: "-80deg",
+                  filter: "blur(6px)",
+                }}
+                style={{ willChange: "transform" }}
+                transition={{
+                  delay: 0.015 * index,
+                  type: "spring",
+                  bounce: 0.5,
+                }}
+                className="inline-block"
+              >
+                {char === " " ? "\u00A0" : char}
+              </motion.span>
+            ))}
+          </motion.span>
+        </motion.div>
+      </AnimatePresence>
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.module.css b/autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.module.css
new file mode 100644
index 0000000000..cd04402348
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.module.css
@@ -0,0 +1,69 @@
+.loader {
+  position: relative;
+  animation: rotate 1s infinite;
+}
+
+.loader::before,
+.loader::after {
+  border-radius: 50%;
+  content: "";
+  display: block;
+  /* 40% of container size */
+  height: 40%;
+  width: 40%;
+}
+
+.loader::before {
+  animation: ball1 1s infinite;
+  background-color: #a1a1aa; /* zinc-400 */
+  box-shadow: calc(var(--spacing)) 0 0 #18181b; /* zinc-900 */
+  margin-bottom: calc(var(--gap));
+}
+
+.loader::after {
+  animation: ball2 1s infinite;
+  background-color: #18181b; /* zinc-900 */
+  box-shadow: calc(var(--spacing)) 0 0 #a1a1aa; /* zinc-400 */
+}
+
+@keyframes rotate {
+  0% {
+    transform: rotate(0deg) scale(0.8);
+  }
+  50% {
+    transform: rotate(360deg) scale(1.2);
+  }
+  100% {
+    transform: rotate(720deg) scale(0.8);
+  }
+}
+
+@keyframes ball1 {
+  0% {
+    box-shadow: calc(var(--spacing)) 0 0 #18181b;
+  }
+  50% {
+    box-shadow: 0 0 0 #18181b;
+    margin-bottom: 0;
+    transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
+  }
+  100% {
+    box-shadow: calc(var(--spacing)) 0 0 #18181b;
+    margin-bottom: calc(var(--gap));
+  }
+}
+
+@keyframes ball2 {
+  0% {
+    box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
+  }
+  50% {
+    box-shadow: 0 0 0 #a1a1aa;
+    margin-top: calc(var(--ball-size) * -1);
+    transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
+  }
+  100% {
+    box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
+    margin-top: 0;
+  }
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.tsx
new file mode 100644
index 0000000000..cc47c16132
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.tsx
@@ -0,0 +1,28 @@
+import { cn } from "@/lib/utils";
+import styles from "./OrbitLoader.module.css";
+
+interface Props {
+  size?: number;
+  className?: string;
+}
+
+export function OrbitLoader({ size = 24, className }: Props) {
+  const ballSize = Math.round(size * 0.4);
+  const spacing = Math.round(size * 0.6);
+  const gap = Math.round(size * 0.2);
+
+  return (
+    <div
+      className={cn(styles.loader, className)}
+      style={
+        {
+          width: size,
+          height: size,
+          "--ball-size": `${ballSize}px`,
+          "--spacing": `${spacing}px`,
+          "--gap": `${gap}px`,
+        } as React.CSSProperties
+      }
+    />
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ProgressBar/ProgressBar.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ProgressBar/ProgressBar.tsx
new file mode 100644
index 0000000000..d251b08640
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ProgressBar/ProgressBar.tsx
@@ -0,0 +1,26 @@
+import { cn } from "@/lib/utils";
+
+interface Props {
+  value: number;
+  label?: string;
+  className?: string;
+}
+
+export function ProgressBar({ value, label, className }: Props) {
+  const clamped = Math.min(100, Math.max(0, value));
+
+  return (
+    <div className={cn("flex flex-col gap-1.5", className)}>
+      <div className="flex items-center justify-between text-xs text-neutral-500">
+        <span>{label ?? "Working on it..."}</span>
+        <span>{Math.round(clamped)}%</span>
+      </div>
+      <div className="h-2 w-full overflow-hidden rounded-full bg-neutral-200">
+        <div
+          className="h-full rounded-full bg-neutral-900 transition-[width] duration-300 ease-out"
+          style={{ width: `${clamped}%` }}
+        />
+      </div>
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.module.css b/autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.module.css
new file mode 100644
index 0000000000..77ab5ae931
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.module.css
@@ -0,0 +1,34 @@
+.loader {
+  position: relative;
+  display: inline-block;
+  flex-shrink: 0;
+}
+
+.loader::before,
+.loader::after {
+  content: "";
+  box-sizing: border-box;
+  width: 100%;
+  height: 100%;
+  border-radius: 50%;
+  background: currentColor;
+  position: absolute;
+  left: 0;
+  top: 0;
+  animation: ripple 2s linear infinite;
+}
+
+.loader::after {
+  animation-delay: 1s;
+}
+
+@keyframes ripple {
+  0% {
+    transform: scale(0);
+    opacity: 1;
+  }
+  100% {
+    transform: scale(1);
+    opacity: 0;
+  }
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.tsx
new file mode 100644
index 0000000000..599874daaa
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.tsx
@@ -0,0 +1,16 @@
+import { cn } from "@/lib/utils";
+import styles from "./PulseLoader.module.css";
+
+interface Props {
+  size?: number;
+  className?: string;
+}
+
+export function PulseLoader({ size = 24, className }: Props) {
+  return (
+    <div
+      className={cn(styles.loader, className)}
+      style={{ width: size, height: size }}
+    />
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.module.css b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.module.css
new file mode 100644
index 0000000000..3e7e71d66b
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.module.css
@@ -0,0 +1,35 @@
+.loader {
+  width: 48px;
+  height: 48px;
+  display: inline-block;
+  position: relative;
+}
+
+.loader::after,
+.loader::before {
+  content: "";
+  box-sizing: border-box;
+  width: 100%;
+  height: 100%;
+  border-radius: 50%;
+  background: currentColor;
+  position: absolute;
+  left: 0;
+  top: 0;
+  animation: animloader 2s linear infinite;
+}
+
+.loader::after {
+  animation-delay: 1s;
+}
+
+@keyframes animloader {
+  0% {
+    transform: scale(0);
+    opacity: 1;
+  }
+  100% {
+    transform: scale(1);
+    opacity: 0;
+  }
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.tsx
new file mode 100644
index 0000000000..a395b21319
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.tsx
@@ -0,0 +1,16 @@
+import { cn } from "@/lib/utils";
+import styles from "./ScaleLoader.module.css";
+
+interface Props {
+  size?: number;
+  className?: string;
+}
+
+export function ScaleLoader({ size = 48, className }: Props) {
+  return (
+    <div
+      className={cn(styles.loader, className)}
+      style={{ width: size, height: size }}
+    />
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.module.css b/autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.module.css
new file mode 100644
index 0000000000..ee456bfac4
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.module.css
@@ -0,0 +1,57 @@
+.loader {
+  position: relative;
+  display: inline-block;
+  flex-shrink: 0;
+  transform: rotateZ(45deg);
+  perspective: 1000px;
+  border-radius: 50%;
+  color: currentColor;
+}
+
+.loader::before,
+.loader::after {
+  content: "";
+  display: block;
+  position: absolute;
+  top: 0;
+  left: 0;
+  width: inherit;
+  height: inherit;
+  border-radius: 50%;
+  transform: rotateX(70deg);
+  animation: spin 1s linear infinite;
+}
+
+.loader::after {
+  color: var(--spinner-accent, #a855f7);
+  transform: rotateY(70deg);
+  animation-delay: 0.4s;
+}
+
+@keyframes spin {
+  0%,
+  100% {
+    box-shadow: 0.2em 0 0 0 currentColor;
+  }
+  12% {
+    box-shadow: 0.2em 0.2em 0 0 currentColor;
+  }
+  25% {
+    box-shadow: 0 0.2em 0 0 currentColor;
+  }
+  37% {
+    box-shadow: -0.2em 0.2em 0 0 currentColor;
+  }
+  50% {
+    box-shadow: -0.2em 0 0 0 currentColor;
+  }
+  62% {
+    box-shadow: -0.2em -0.2em 0 0 currentColor;
+  }
+  75% {
+    box-shadow: 0 -0.2em 0 0 currentColor;
+  }
+  87% {
+    box-shadow: 0.2em -0.2em 0 0 currentColor;
+  }
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.tsx
new file mode 100644
index 0000000000..d921b5f778
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.tsx
@@ -0,0 +1,16 @@
+import { cn } from "@/lib/utils";
+import styles from "./SpinnerLoader.module.css";
+
+interface Props {
+  size?: number;
+  className?: string;
+}
+
+export function SpinnerLoader({ size = 24, className }: Props) {
+  return (
+    <div
+      className={cn(styles.loader, className)}
+      style={{ width: size, height: size }}
+    />
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/AccordionContent.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/AccordionContent.tsx
new file mode 100644
index 0000000000..dab8f49257
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/AccordionContent.tsx
@@ -0,0 +1,235 @@
+import { Link } from "@/components/atoms/Link/Link";
+import { Text } from "@/components/atoms/Text/Text";
+import { cn } from "@/lib/utils";
+
+/* ------------------------------------------------------------------ */
+/*  Layout                                                            */
+/* ------------------------------------------------------------------ */
+
+export function ContentGrid({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return <div className={cn("grid gap-2", className)}>{children}</div>;
+}
+
+/* ------------------------------------------------------------------ */
+/*  Card                                                              */
+/* ------------------------------------------------------------------ */
+
+export function ContentCard({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <div
+      className={cn(
+        "min-w-0 rounded-lg bg-gradient-to-r from-purple-500/30 to-blue-500/30 p-[1px]",
+        className,
+      )}
+    >
+      <div className="rounded-lg bg-neutral-100 p-3">{children}</div>
+    </div>
+  );
+}
+
+/** Flex row with a left content area (`children`) and an optional right‑side `action`. */
+export function ContentCardHeader({
+  children,
+  action,
+  className,
+}: {
+  children: React.ReactNode;
+  action?: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <div className={cn("flex items-start justify-between gap-2", className)}>
+      <div className="min-w-0">{children}</div>
+      {action}
+    </div>
+  );
+}
+
+export function ContentCardTitle({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <Text
+      variant="body-medium"
+      className={cn("truncate text-zinc-800", className)}
+    >
+      {children}
+    </Text>
+  );
+}
+
+export function ContentCardSubtitle({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <Text
+      variant="small"
+      className={cn("mt-0.5 truncate font-mono text-zinc-800", className)}
+    >
+      {children}
+    </Text>
+  );
+}
+
+export function ContentCardDescription({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <Text variant="body" className={cn("mt-2 text-zinc-800", className)}>
+      {children}
+    </Text>
+  );
+}
+
+/* ------------------------------------------------------------------ */
+/*  Text                                                              */
+/* ------------------------------------------------------------------ */
+
+export function ContentMessage({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <Text variant="body" className={cn("text-zinc-800", className)}>
+      {children}
+    </Text>
+  );
+}
+
+export function ContentHint({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <Text variant="small" className={cn("text-neutral-500", className)}>
+      {children}
+    </Text>
+  );
+}
+
+/* ------------------------------------------------------------------ */
+/*  Code / data                                                       */
+/* ------------------------------------------------------------------ */
+
+export function ContentCodeBlock({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <pre
+      className={cn(
+        "whitespace-pre-wrap rounded-lg border bg-black p-3 text-xs text-neutral-200",
+        className,
+      )}
+    >
+      {children}
+    </pre>
+  );
+}
+
+/* ------------------------------------------------------------------ */
+/*  Inline elements                                                   */
+/* ------------------------------------------------------------------ */
+
+export function ContentBadge({
+  children,
+  className,
+}: {
+  children: React.ReactNode;
+  className?: string;
+}) {
+  return (
+    <Text
+      variant="small"
+      as="span"
+      className={cn(
+        "shrink-0 rounded-full border bg-muted px-2 py-0.5 text-[11px] text-zinc-800",
+        className,
+      )}
+    >
+      {children}
+    </Text>
+  );
+}
+
+export function ContentLink({
+  href,
+  children,
+  className,
+  ...rest
+}: Omit<React.ComponentProps<typeof Link>, "className"> & {
+  className?: string;
+}) {
+  return (
+    <Link
+      variant="primary"
+      isExternal
+      href={href}
+      className={cn("shrink-0 text-xs text-purple-500", className)}
+      {...rest}
+    >
+      {children}
+    </Link>
+  );
+}
+
+/* ------------------------------------------------------------------ */
+/*  Lists                                                             */
+/* ------------------------------------------------------------------ */
+
+export function ContentSuggestionsList({
+  items,
+  max = 5,
+  className,
+}: {
+  items: string[];
+  max?: number;
+  className?: string;
+}) {
+  if (items.length === 0) return null;
+  return (
+    <ul
+      className={cn(
+        "mt-2 list-disc space-y-1 pl-5 font-sans text-[0.75rem] leading-[1.125rem] text-zinc-800",
+        className,
+      )}
+    >
+      {items.slice(0, max).map((s) => (
+        <li key={s}>{s}</li>
+      ))}
+    </ul>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/ToolAccordion.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/ToolAccordion.tsx
new file mode 100644
index 0000000000..e53df15e6c
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/ToolAccordion.tsx
@@ -0,0 +1,102 @@
+"use client";
+
+import { cn } from "@/lib/utils";
+import { CaretDownIcon } from "@phosphor-icons/react";
+import { AnimatePresence, motion, useReducedMotion } from "framer-motion";
+import { useId } from "react";
+import { useToolAccordion } from "./useToolAccordion";
+
+interface Props {
+  icon: React.ReactNode;
+  title: React.ReactNode;
+  titleClassName?: string;
+  description?: React.ReactNode;
+  children: React.ReactNode;
+  className?: string;
+  defaultExpanded?: boolean;
+  expanded?: boolean;
+  onExpandedChange?: (expanded: boolean) => void;
+}
+
+export function ToolAccordion({
+  icon,
+  title,
+  titleClassName,
+  description,
+  children,
+  className,
+  defaultExpanded,
+  expanded,
+  onExpandedChange,
+}: Props) {
+  const shouldReduceMotion = useReducedMotion();
+  const contentId = useId();
+  const { isExpanded, toggle } = useToolAccordion({
+    expanded,
+    defaultExpanded,
+    onExpandedChange,
+  });
+
+  return (
+    <div
+      className={cn(
+        "mt-2 w-full rounded-lg border border-slate-200 bg-slate-100 px-3 py-2",
+        className,
+      )}
+    >
+      <button
+        type="button"
+        aria-expanded={isExpanded}
+        aria-controls={contentId}
+        onClick={toggle}
+        className="flex w-full items-center justify-between gap-3 py-1 text-left"
+      >
+        <div className="flex min-w-0 items-center gap-3">
+          <span className="flex shrink-0 items-center text-gray-800">
+            {icon}
+          </span>
+          <div className="min-w-0">
+            <p
+              className={cn(
+                "truncate text-sm font-medium text-gray-800",
+                titleClassName,
+              )}
+            >
+              {title}
+            </p>
+            {description && (
+              <p className="truncate text-xs text-slate-800">{description}</p>
+            )}
+          </div>
+        </div>
+        <CaretDownIcon
+          className={cn(
+            "h-4 w-4 shrink-0 text-slate-500 transition-transform",
+            isExpanded && "rotate-180",
+          )}
+          weight="bold"
+        />
+      </button>
+
+      <AnimatePresence initial={false}>
+        {isExpanded && (
+          <motion.div
+            id={contentId}
+            initial={{ height: 0, opacity: 0, filter: "blur(10px)" }}
+            animate={{ height: "auto", opacity: 1, filter: "blur(0px)" }}
+            exit={{ height: 0, opacity: 0, filter: "blur(10px)" }}
+            transition={
+              shouldReduceMotion
+                ? { duration: 0 }
+                : { type: "spring", bounce: 0.35, duration: 0.55 }
+            }
+            className="overflow-hidden"
+            style={{ willChange: "height, opacity, filter" }}
+          >
+            <div className="pb-2 pt-3">{children}</div>
+          </motion.div>
+        )}
+      </AnimatePresence>
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/useToolAccordion.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/useToolAccordion.ts
new file mode 100644
index 0000000000..bc2a177e8d
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/useToolAccordion.ts
@@ -0,0 +1,32 @@
+import { useState } from "react";
+
+interface UseToolAccordionOptions {
+  expanded?: boolean;
+  defaultExpanded?: boolean;
+  onExpandedChange?: (expanded: boolean) => void;
+}
+
+interface UseToolAccordionResult {
+  isExpanded: boolean;
+  toggle: () => void;
+}
+
+export function useToolAccordion({
+  expanded,
+  defaultExpanded = false,
+  onExpandedChange,
+}: UseToolAccordionOptions): UseToolAccordionResult {
+  const [uncontrolledExpanded, setUncontrolledExpanded] =
+    useState(defaultExpanded);
+
+  const isControlled = typeof expanded === "boolean";
+  const isExpanded = isControlled ? expanded : uncontrolledExpanded;
+
+  function toggle() {
+    const next = !isExpanded;
+    if (!isControlled) setUncontrolledExpanded(next);
+    onExpandedChange?.(next);
+  }
+
+  return { isExpanded, toggle };
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/copilot-page-store.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/copilot-page-store.ts
deleted file mode 100644
index 9fc97a14e3..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/copilot-page-store.ts
+++ /dev/null
@@ -1,56 +0,0 @@
-"use client";
-
-import { create } from "zustand";
-
-interface CopilotStoreState {
-  isStreaming: boolean;
-  isSwitchingSession: boolean;
-  isCreatingSession: boolean;
-  isInterruptModalOpen: boolean;
-  pendingAction: (() => void) | null;
-}
-
-interface CopilotStoreActions {
-  setIsStreaming: (isStreaming: boolean) => void;
-  setIsSwitchingSession: (isSwitchingSession: boolean) => void;
-  setIsCreatingSession: (isCreating: boolean) => void;
-  openInterruptModal: (onConfirm: () => void) => void;
-  confirmInterrupt: () => void;
-  cancelInterrupt: () => void;
-}
-
-type CopilotStore = CopilotStoreState & CopilotStoreActions;
-
-export const useCopilotStore = create<CopilotStore>((set, get) => ({
-  isStreaming: false,
-  isSwitchingSession: false,
-  isCreatingSession: false,
-  isInterruptModalOpen: false,
-  pendingAction: null,
-
-  setIsStreaming(isStreaming) {
-    set({ isStreaming });
-  },
-
-  setIsSwitchingSession(isSwitchingSession) {
-    set({ isSwitchingSession });
-  },
-
-  setIsCreatingSession(isCreatingSession) {
-    set({ isCreatingSession });
-  },
-
-  openInterruptModal(onConfirm) {
-    set({ isInterruptModalOpen: true, pendingAction: onConfirm });
-  },
-
-  confirmInterrupt() {
-    const { pendingAction } = get();
-    set({ isInterruptModalOpen: false, pendingAction: null });
-    if (pendingAction) pendingAction();
-  },
-
-  cancelInterrupt() {
-    set({ isInterruptModalOpen: false, pendingAction: null });
-  },
-}));
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/helpers.ts
deleted file mode 100644
index 692a5741f4..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/helpers.ts
+++ /dev/null
@@ -1,33 +0,0 @@
-import type { User } from "@supabase/supabase-js";
-
-export function getGreetingName(user?: User | null): string {
-  if (!user) return "there";
-  const metadata = user.user_metadata as Record<string, unknown> | undefined;
-  const fullName = metadata?.full_name;
-  const name = metadata?.name;
-  if (typeof fullName === "string" && fullName.trim()) {
-    return fullName.split(" ")[0];
-  }
-  if (typeof name === "string" && name.trim()) {
-    return name.split(" ")[0];
-  }
-  if (user.email) {
-    return user.email.split("@")[0];
-  }
-  return "there";
-}
-
-export function buildCopilotChatUrl(prompt: string): string {
-  const trimmed = prompt.trim();
-  if (!trimmed) return "/copilot/chat";
-  const encoded = encodeURIComponent(trimmed);
-  return `/copilot/chat?prompt=${encoded}`;
-}
-
-export function getQuickActions(): string[] {
-  return [
-    "Show me what I can automate",
-    "Design a custom workflow",
-    "Help me with content creation",
-  ];
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/helpers/convertChatSessionToUiMessages.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/helpers/convertChatSessionToUiMessages.ts
new file mode 100644
index 0000000000..a3f2bc28bf
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/helpers/convertChatSessionToUiMessages.ts
@@ -0,0 +1,128 @@
+import type { UIMessage, UIDataTypes, UITools } from "ai";
+
+interface SessionChatMessage {
+  role: string;
+  content: string | null;
+  tool_call_id: string | null;
+  tool_calls: unknown[] | null;
+}
+
+function coerceSessionChatMessages(
+  rawMessages: unknown[],
+): SessionChatMessage[] {
+  return rawMessages
+    .map((m) => {
+      if (!m || typeof m !== "object") return null;
+      const msg = m as Record<string, unknown>;
+
+      const role = typeof msg.role === "string" ? msg.role : null;
+      if (!role) return null;
+
+      return {
+        role,
+        content:
+          typeof msg.content === "string"
+            ? msg.content
+            : msg.content == null
+              ? null
+              : String(msg.content),
+        tool_call_id:
+          typeof msg.tool_call_id === "string"
+            ? msg.tool_call_id
+            : msg.tool_call_id == null
+              ? null
+              : String(msg.tool_call_id),
+        tool_calls: Array.isArray(msg.tool_calls) ? msg.tool_calls : null,
+      };
+    })
+    .filter((m): m is SessionChatMessage => m !== null);
+}
+
+function safeJsonParse(value: string): unknown {
+  try {
+    return JSON.parse(value) as unknown;
+  } catch {
+    return value;
+  }
+}
+
+function toToolInput(rawArguments: unknown): unknown {
+  if (typeof rawArguments === "string") {
+    const trimmed = rawArguments.trim();
+    return trimmed ? safeJsonParse(trimmed) : {};
+  }
+  if (rawArguments && typeof rawArguments === "object") return rawArguments;
+  return {};
+}
+
+export function convertChatSessionMessagesToUiMessages(
+  sessionId: string,
+  rawMessages: unknown[],
+): UIMessage<unknown, UIDataTypes, UITools>[] {
+  const messages = coerceSessionChatMessages(rawMessages);
+  const toolOutputsByCallId = new Map<string, unknown>();
+
+  for (const msg of messages) {
+    if (msg.role !== "tool") continue;
+    if (!msg.tool_call_id) continue;
+    if (msg.content == null) continue;
+    toolOutputsByCallId.set(msg.tool_call_id, msg.content);
+  }
+
+  const uiMessages: UIMessage<unknown, UIDataTypes, UITools>[] = [];
+
+  messages.forEach((msg, index) => {
+    if (msg.role === "tool") return;
+    if (msg.role !== "user" && msg.role !== "assistant") return;
+
+    const parts: UIMessage<unknown, UIDataTypes, UITools>["parts"] = [];
+
+    if (typeof msg.content === "string" && msg.content.trim()) {
+      parts.push({ type: "text", text: msg.content, state: "done" });
+    }
+
+    if (msg.role === "assistant" && Array.isArray(msg.tool_calls)) {
+      for (const rawToolCall of msg.tool_calls) {
+        if (!rawToolCall || typeof rawToolCall !== "object") continue;
+        const toolCall = rawToolCall as {
+          id?: unknown;
+          function?: { name?: unknown; arguments?: unknown };
+        };
+
+        const toolCallId = String(toolCall.id ?? "").trim();
+        const toolName = String(toolCall.function?.name ?? "").trim();
+        if (!toolCallId || !toolName) continue;
+
+        const input = toToolInput(toolCall.function?.arguments);
+        const output = toolOutputsByCallId.get(toolCallId);
+
+        if (output !== undefined) {
+          parts.push({
+            type: `tool-${toolName}`,
+            toolCallId,
+            state: "output-available",
+            input,
+            output: typeof output === "string" ? safeJsonParse(output) : output,
+          });
+        } else {
+          parts.push({
+            type: `tool-${toolName}`,
+            toolCallId,
+            state: "input-available",
+            input,
+          });
+        }
+      }
+    }
+
+    if (parts.length === 0) return;
+
+    uiMessages.push({
+      id: `${sessionId}-${index}`,
+      role: msg.role,
+      parts,
+    });
+  });
+
+  return uiMessages;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotSessionId.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/hooks/Untitled
similarity index 99%
rename from autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotSessionId.ts
rename to autogpt_platform/frontend/src/app/(platform)/copilot/hooks/Untitled
index 87f9b7d3ae..13769eb726 100644
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotSessionId.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/hooks/Untitled
@@ -7,4 +7,4 @@ export function useCopilotSessionId() {
   );
 
   return { urlSessionId, setUrlSessionId };
-}
+}
\ No newline at end of file
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/hooks/useAsymptoticProgress.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/hooks/useAsymptoticProgress.ts
new file mode 100644
index 0000000000..408ec74175
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/hooks/useAsymptoticProgress.ts
@@ -0,0 +1,47 @@
+import { useEffect, useRef, useState } from "react";
+
+/**
+ * Hook that returns a progress value that starts fast and slows down,
+ * asymptotically approaching but never reaching the max value.
+ *
+ * Uses a half-life formula: progress = max * (1 - 0.5^(time/halfLife))
+ * This creates a "loading bar" effect where:
+ * - 50% is reached at halfLifeSeconds
+ * - 75% is reached at 2 * halfLifeSeconds
+ * - 87.5% is reached at 3 * halfLifeSeconds
+ *
+ * @param isActive - Whether the progress should be animating
+ * @param halfLifeSeconds - Time in seconds to reach 50% progress (default: 30)
+ * @param maxProgress - Maximum progress value to approach (default: 100)
+ * @param intervalMs - Update interval in milliseconds (default: 100)
+ * @returns Current progress value (0–maxProgress)
+ */
+export function useAsymptoticProgress(
+  isActive: boolean,
+  halfLifeSeconds = 30,
+  maxProgress = 100,
+  intervalMs = 100,
+) {
+  const [progress, setProgress] = useState(0);
+  const elapsedTimeRef = useRef(0);
+
+  useEffect(() => {
+    if (!isActive) {
+      setProgress(0);
+      elapsedTimeRef.current = 0;
+      return;
+    }
+
+    const interval = setInterval(() => {
+      elapsedTimeRef.current += intervalMs / 1000;
+      const newProgress =
+        maxProgress *
+        (1 - Math.pow(0.5, elapsedTimeRef.current / halfLifeSeconds));
+      setProgress(newProgress);
+    }, intervalMs);
+
+    return () => clearInterval(interval);
+  }, [isActive, halfLifeSeconds, maxProgress, intervalMs]);
+
+  return progress;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/layout.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/layout.tsx
deleted file mode 100644
index 89cf72e2ba..0000000000
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/layout.tsx
+++ /dev/null
@@ -1,6 +0,0 @@
-import type { ReactNode } from "react";
-import { CopilotShell } from "./components/CopilotShell/CopilotShell";
-
-export default function CopilotLayout({ children }: { children: ReactNode }) {
-  return <CopilotShell>{children}</CopilotShell>;
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/page.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/page.tsx
index 104b238895..3e4a81dd51 100644
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/page.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/page.tsx
@@ -1,138 +1,13 @@
 "use client";
 
-import { Button } from "@/components/atoms/Button/Button";
-import { Skeleton } from "@/components/atoms/Skeleton/Skeleton";
-import { Text } from "@/components/atoms/Text/Text";
-import { Chat } from "@/components/contextual/Chat/Chat";
-import { ChatInput } from "@/components/contextual/Chat/components/ChatInput/ChatInput";
-import { Dialog } from "@/components/molecules/Dialog/Dialog";
-import { useCopilotStore } from "./copilot-page-store";
-import { useCopilotPage } from "./useCopilotPage";
-
-export default function CopilotPage() {
-  const { state, handlers } = useCopilotPage();
-  const isInterruptModalOpen = useCopilotStore((s) => s.isInterruptModalOpen);
-  const confirmInterrupt = useCopilotStore((s) => s.confirmInterrupt);
-  const cancelInterrupt = useCopilotStore((s) => s.cancelInterrupt);
-  const {
-    greetingName,
-    quickActions,
-    isLoading,
-    hasSession,
-    initialPrompt,
-    isReady,
-  } = state;
-  const {
-    handleQuickAction,
-    startChatWithPrompt,
-    handleSessionNotFound,
-    handleStreamingChange,
-  } = handlers;
-
-  if (!isReady) return null;
-
-  if (hasSession) {
-    return (
-      <div className="flex h-full flex-col">
-        <Chat
-          className="flex-1"
-          initialPrompt={initialPrompt}
-          onSessionNotFound={handleSessionNotFound}
-          onStreamingChange={handleStreamingChange}
-        />
-        <Dialog
-          title="Interrupt current chat?"
-          styling={{ maxWidth: 300, width: "100%" }}
-          controlled={{
-            isOpen: isInterruptModalOpen,
-            set: (open) => {
-              if (!open) cancelInterrupt();
-            },
-          }}
-          onClose={cancelInterrupt}
-        >
-          <Dialog.Content>
-            <div className="flex flex-col gap-4">
-              <Text variant="body">
-                The current chat response will be interrupted. Are you sure you
-                want to continue?
-              </Text>
-              <Dialog.Footer>
-                <Button
-                  type="button"
-                  variant="outline"
-                  onClick={cancelInterrupt}
-                >
-                  Cancel
-                </Button>
-                <Button
-                  type="button"
-                  variant="primary"
-                  onClick={confirmInterrupt}
-                >
-                  Continue
-                </Button>
-              </Dialog.Footer>
-            </div>
-          </Dialog.Content>
-        </Dialog>
-      </div>
-    );
-  }
+import { FeatureFlagPage } from "@/services/feature-flags/FeatureFlagPage";
+import { Flag } from "@/services/feature-flags/use-get-flag";
+import { CopilotPage } from "./CopilotPage";
 
+export default function Page() {
   return (
-    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-6 py-10">
-      <div className="w-full text-center">
-        {isLoading ? (
-          <div className="mx-auto max-w-2xl">
-            <Skeleton className="mx-auto mb-3 h-8 w-64" />
-            <Skeleton className="mx-auto mb-8 h-6 w-80" />
-            <div className="mb-8">
-              <Skeleton className="mx-auto h-14 w-full rounded-lg" />
-            </div>
-            <div className="flex flex-wrap items-center justify-center gap-3">
-              {Array.from({ length: 4 }).map((_, i) => (
-                <Skeleton key={i} className="h-9 w-48 rounded-md" />
-              ))}
-            </div>
-          </div>
-        ) : (
-          <>
-            <div className="mx-auto max-w-2xl">
-              <Text
-                variant="h3"
-                className="mb-3 !text-[1.375rem] text-zinc-700"
-              >
-                Hey, <span className="text-violet-600">{greetingName}</span>
-              </Text>
-              <Text variant="h3" className="mb-8 !font-normal">
-                What do you want to automate?
-              </Text>
-
-              <div className="mb-6">
-                <ChatInput
-                  onSend={startChatWithPrompt}
-                  placeholder='You can search or just ask - e.g. "create a blog post outline"'
-                />
-              </div>
-            </div>
-            <div className="flex flex-nowrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
-              {quickActions.map((action) => (
-                <Button
-                  key={action}
-                  type="button"
-                  variant="outline"
-                  size="small"
-                  onClick={() => handleQuickAction(action)}
-                  className="h-auto shrink-0 border-zinc-600 !px-4 !py-2 text-[1rem] text-zinc-600"
-                >
-                  {action}
-                </Button>
-              ))}
-            </div>
-          </>
-        )}
-      </div>
-    </div>
+    <FeatureFlagPage flag={Flag.CHAT} whenDisabled="/library">
+      <CopilotPage />
+    </FeatureFlagPage>
   );
 }
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/styleguide/page.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/styleguide/page.tsx
new file mode 100644
index 0000000000..6030665f1c
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/styleguide/page.tsx
@@ -0,0 +1,1533 @@
+"use client";
+
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import {
+  Conversation,
+  ConversationContent,
+} from "@/components/ai-elements/conversation";
+import {
+  Message,
+  MessageContent,
+  MessageResponse,
+} from "@/components/ai-elements/message";
+import { Text } from "@/components/atoms/Text/Text";
+import { CopilotChatActionsProvider } from "../components/CopilotChatActionsProvider/CopilotChatActionsProvider";
+import { CreateAgentTool } from "../tools/CreateAgent/CreateAgent";
+import { EditAgentTool } from "../tools/EditAgent/EditAgent";
+import { FindAgentsTool } from "../tools/FindAgents/FindAgents";
+import { FindBlocksTool } from "../tools/FindBlocks/FindBlocks";
+import { RunAgentTool } from "../tools/RunAgent/RunAgent";
+import { RunBlockTool } from "../tools/RunBlock/RunBlock";
+import { SearchDocsTool } from "../tools/SearchDocs/SearchDocs";
+import { ViewAgentOutputTool } from "../tools/ViewAgentOutput/ViewAgentOutput";
+
+// ---------------------------------------------------------------------------
+// Helpers
+// ---------------------------------------------------------------------------
+
+function slugify(text: string) {
+  return text
+    .toLowerCase()
+    .replace(/[^a-z0-9]+/g, "-")
+    .replace(/(^-|-$)/g, "");
+}
+
+const SECTIONS = [
+  "Messages",
+  "Tool: Find Blocks",
+  "Tool: Find Agents (Marketplace)",
+  "Tool: Find Agents (Library)",
+  "Tool: Search Docs",
+  "Tool: Get Doc Page",
+  "Tool: Run Block",
+  "Tool: Run Agent",
+  "Tool: Schedule Agent",
+  "Tool: Create Agent",
+  "Tool: Edit Agent",
+  "Tool: View Agent Output",
+  "Full Conversation Example",
+] as const;
+
+function Section({
+  title,
+  children,
+}: {
+  title: string;
+  children: React.ReactNode;
+}) {
+  return (
+    <div id={slugify(title)} className="mb-10 scroll-mt-6">
+      <h2 className="mb-4 border-b border-neutral-200 pb-2 font-mono text-xl font-semibold text-neutral-800">
+        {title}
+      </h2>
+      <div className="space-y-4">{children}</div>
+    </div>
+  );
+}
+
+function SubSection({
+  label,
+  children,
+}: {
+  label: string;
+  children: React.ReactNode;
+}) {
+  return (
+    <div className="rounded-lg border border-dashed border-blue-200 p-3">
+      <p className="mb-2 text-xs font-medium uppercase tracking-wide text-neutral-500">
+        {label}
+      </p>
+      {children}
+    </div>
+  );
+}
+
+// ---------------------------------------------------------------------------
+// Mock data factories
+// ---------------------------------------------------------------------------
+
+let _id = 0;
+function uid() {
+  return `sg-${++_id}`;
+}
+
+// ---------------------------------------------------------------------------
+// Page
+// ---------------------------------------------------------------------------
+
+export default function StyleguidePage() {
+  return (
+    <CopilotChatActionsProvider onSend={(msg) => alert(`onSend: ${msg}`)}>
+      <div className="flex h-[calc(100vh-72px)] bg-[#f8f8f9]">
+        {/* Sidebar */}
+        <nav className="sticky top-0 hidden h-full w-56 shrink-0 overflow-y-auto border-r border-neutral-200 bg-white px-3 py-6 lg:block">
+          <p className="mb-3 px-2 text-[11px] font-semibold uppercase tracking-wider text-neutral-400">
+            Sections
+          </p>
+          <ul className="space-y-0.5">
+            {SECTIONS.map((title) => (
+              <li key={title}>
+                <a
+                  href={`#${slugify(title)}`}
+                  className="block rounded-md px-2 py-1.5 text-[13px] text-neutral-600 transition-colors hover:bg-neutral-100 hover:text-neutral-900"
+                >
+                  {title.replace(/^Tool: /, "")}
+                </a>
+              </li>
+            ))}
+          </ul>
+        </nav>
+
+        {/* Content */}
+        <div className="flex-1 overflow-y-auto">
+          <div className="mx-auto max-w-3xl px-4 py-10">
+            <Text variant="h1">Copilot Styleguide</Text>
+            <p className="mb-8 text-sm text-neutral-500">
+              Static showcase of all chat message types, tool states &amp;
+              variants.
+            </p>
+
+            {/* ============================================================= */}
+            {/* MESSAGE TYPES                                                  */}
+            {/* ============================================================= */}
+
+            <Section title="Messages">
+              <SubSection label="User message">
+                <Message from="user">
+                  <MessageContent className="text-[1rem] leading-relaxed group-[.is-user]:rounded-xl group-[.is-user]:bg-purple-100 group-[.is-user]:px-3 group-[.is-user]:py-2.5 group-[.is-user]:text-slate-900 group-[.is-user]:[border-bottom-right-radius:0]">
+                    <MessageResponse>
+                      Find me an agent that can summarize YouTube videos
+                    </MessageResponse>
+                  </MessageContent>
+                </Message>
+              </SubSection>
+
+              <SubSection label="Assistant message (text)">
+                <Message from="assistant">
+                  <MessageContent className="text-[1rem] leading-relaxed group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900">
+                    <MessageResponse>
+                      I found a few agents that can help with YouTube video
+                      summarization. Let me search for the best options for you.
+                    </MessageResponse>
+                  </MessageContent>
+                </Message>
+              </SubSection>
+
+              <SubSection label="Assistant message (markdown)">
+                <Message from="assistant">
+                  <MessageContent className="text-[1rem] leading-relaxed group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900">
+                    <MessageResponse>
+                      {`Here's what I found:\n\n1. **YouTube Summarizer** — Extracts key points from any YouTube video\n2. **Video Digest** — Creates bullet-point summaries with timestamps\n\n> Both agents support videos up to 2 hours long.\n\n\`\`\`python\n# Example usage\nresult = agent.run(url="https://youtube.com/watch?v=...")\nprint(result.summary)\n\`\`\``}
+                    </MessageResponse>
+                  </MessageContent>
+                </Message>
+              </SubSection>
+
+              <SubSection label="Thinking state">
+                <Message from="assistant">
+                  <MessageContent className="text-[1rem] leading-relaxed">
+                    <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
+                      Thinking...
+                    </span>
+                  </MessageContent>
+                </Message>
+              </SubSection>
+
+              <SubSection label="Error state">
+                <div className="rounded-lg bg-red-50 p-3 text-red-600">
+                  Error: Connection timed out. Please try again.
+                </div>
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* FIND BLOCKS                                                    */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Find Blocks">
+              <SubSection label="Input streaming">
+                <FindBlocksTool
+                  part={{
+                    type: "tool-find_block",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: { query: "weather" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Input available">
+                <FindBlocksTool
+                  part={{
+                    type: "tool-find_block",
+                    toolCallId: uid(),
+                    state: "input-available",
+                    input: { query: "weather" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (with results)">
+                <FindBlocksTool
+                  part={{
+                    type: "tool-find_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { query: "weather" },
+                    output: {
+                      type: ResponseType.block_list,
+                      blocks: [
+                        {
+                          id: "block-1",
+                          name: "Get Weather",
+                          description:
+                            "Fetches current weather data for a given city using the OpenWeatherMap API.",
+                          categories: [],
+                        },
+                        {
+                          id: "block-2",
+                          name: "Weather Forecast",
+                          description:
+                            "Returns a 5-day weather forecast for any location worldwide.",
+                          categories: [],
+                        },
+                        {
+                          id: "block-3",
+                          name: "Historical Weather",
+                          description:
+                            "Retrieves historical weather data for the past 30 days.",
+                          categories: [],
+                        },
+                      ],
+                      count: 3,
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <FindBlocksTool
+                  part={{
+                    type: "tool-find_block",
+                    toolCallId: uid(),
+                    state: "output-error",
+                    input: { query: "weather" },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* FIND AGENTS (Marketplace)                                      */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Find Agents (Marketplace)">
+              <SubSection label="Input streaming">
+                <FindAgentsTool
+                  part={{
+                    type: "tool-find_agent",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: { query: "youtube summarizer" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (agents found)">
+                <FindAgentsTool
+                  part={{
+                    type: "tool-find_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { query: "youtube summarizer" },
+                    output: {
+                      type: ResponseType.agents_found,
+                      agents: [
+                        {
+                          id: "creator/youtube-summarizer",
+                          name: "YouTube Summarizer",
+                          description:
+                            "Summarizes YouTube videos into concise bullet points with key insights.",
+                          source: "marketplace",
+                        },
+                        {
+                          id: "creator/video-digest",
+                          name: "Video Digest Pro",
+                          description:
+                            "Creates detailed summaries with timestamps from any YouTube video.",
+                          source: "marketplace",
+                        },
+                      ],
+                      count: 2,
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (no results)">
+                <FindAgentsTool
+                  part={{
+                    type: "tool-find_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { query: "quantum computing simulator" },
+                    output: {
+                      type: ResponseType.no_results,
+                      message: "No agents found matching your query.",
+                      suggestions: [
+                        "Try broader search terms",
+                        "Check the marketplace for related agents",
+                      ],
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <FindAgentsTool
+                  part={{
+                    type: "tool-find_agent",
+                    toolCallId: uid(),
+                    state: "output-error",
+                    input: { query: "youtube summarizer" },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* FIND AGENTS (Library)                                          */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Find Agents (Library)">
+              <SubSection label="Input streaming">
+                <FindAgentsTool
+                  part={{
+                    type: "tool-find_library_agent",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: { query: "social media" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (agents found)">
+                <FindAgentsTool
+                  part={{
+                    type: "tool-find_library_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { query: "social media" },
+                    output: {
+                      type: ResponseType.agents_found,
+                      agents: [
+                        {
+                          id: "lib-agent-1",
+                          name: "Twitter Post Scheduler",
+                          description:
+                            "Schedules and posts tweets at optimal times for engagement.",
+                          source: "library",
+                        },
+                      ],
+                      count: 1,
+                    },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* SEARCH DOCS                                                    */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Search Docs">
+              <SubSection label="Input streaming">
+                <SearchDocsTool
+                  part={{
+                    type: "tool-search_docs",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: { query: "webhooks" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (search results)">
+                <SearchDocsTool
+                  part={{
+                    type: "tool-search_docs",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { query: "webhooks" },
+                    output: {
+                      type: ResponseType.doc_search_results,
+                      query: "webhooks",
+                      count: 2,
+                      results: [
+                        {
+                          title: "Webhook Configuration Guide",
+                          path: "platform/webhooks/configuration.md",
+                          section: "Setup",
+                          snippet:
+                            "Webhooks allow you to receive real-time notifications when events occur in your AutoGPT workspace. Configure webhook endpoints to integrate with external services.",
+                          doc_url:
+                            "https://docs.agpt.co/platform/webhooks/configuration",
+                        },
+                        {
+                          title: "Webhook Events Reference",
+                          path: "platform/webhooks/events.md",
+                          section: "Event Types",
+                          snippet:
+                            "A complete reference of all webhook event types including agent.completed, execution.started, and execution.failed events.",
+                          doc_url:
+                            "https://docs.agpt.co/platform/webhooks/events",
+                        },
+                      ],
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (no results)">
+                <SearchDocsTool
+                  part={{
+                    type: "tool-search_docs",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { query: "foobar" },
+                    output: {
+                      type: ResponseType.no_results,
+                      message: "No documentation found for this query.",
+                      suggestions: [
+                        "Try different keywords",
+                        "Check the documentation index",
+                      ],
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <SearchDocsTool
+                  part={{
+                    type: "tool-search_docs",
+                    toolCallId: uid(),
+                    state: "output-error",
+                    input: { query: "webhooks" },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* GET DOC PAGE                                                   */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Get Doc Page">
+              <SubSection label="Input streaming">
+                <SearchDocsTool
+                  part={{
+                    type: "tool-get_doc_page",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: { path: "platform/getting-started.md" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (page loaded)">
+                <SearchDocsTool
+                  part={{
+                    type: "tool-get_doc_page",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { path: "platform/getting-started.md" },
+                    output: {
+                      type: ResponseType.doc_page,
+                      title: "Getting Started with AutoGPT Platform",
+                      path: "platform/getting-started.md",
+                      content:
+                        "Welcome to AutoGPT Platform! This guide will walk you through setting up your first agent.\n\n## Prerequisites\n- An AutoGPT account\n- Basic understanding of automation workflows\n\n## Quick Start\n1. Navigate to the Builder\n2. Create a new agent\n3. Add blocks to your workflow\n4. Test and deploy",
+                      doc_url: "https://docs.agpt.co/platform/getting-started",
+                    },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* RUN BLOCK                                                      */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Run Block">
+              <SubSection label="Input streaming">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: { block_id: "weather-block-123" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Input available">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "input-available",
+                    input: {
+                      block_id: "weather-block-123",
+                      input_data: { city: "San Francisco" },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (block output)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "weather-block-123" },
+                    output: {
+                      type: ResponseType.block_output,
+                      block_id: "weather-block-123",
+                      block_name: "Get Weather",
+                      message:
+                        "Successfully fetched weather data for San Francisco.",
+                      outputs: {
+                        temperature: ["72°F"],
+                        condition: ["Partly Cloudy"],
+                        humidity: ["65%"],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (setup requirements)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "weather-block-123" },
+                    output: {
+                      type: ResponseType.setup_requirements,
+                      message:
+                        "This block requires API credentials to run. Please configure them below.",
+                      setup_info: {
+                        agent_name: "Weather Agent",
+                        requirements: {
+                          inputs: [
+                            {
+                              name: "city",
+                              title: "City",
+                              type: "string",
+                              required: true,
+                              description: "The city to get weather for",
+                            },
+                          ],
+                        },
+                        user_readiness: {
+                          missing_credentials: {
+                            openweathermap: {
+                              provider: "openweathermap",
+                              credentials_type: "api_key",
+                              title: "OpenWeatherMap API Key",
+                              description:
+                                "Required to access weather data. Get your key at openweathermap.org",
+                            },
+                          },
+                        },
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (error)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "weather-block-123" },
+                    output: {
+                      type: ResponseType.error,
+                      message: "Failed to run the block.",
+                      error: "Block execution timed out after 30 seconds.",
+                      details: {
+                        block_id: "weather-block-123",
+                        timeout_ms: 30000,
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (JSON object output — interactive viewer)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "api-block-456" },
+                    output: {
+                      type: ResponseType.block_output,
+                      block_id: "api-block-456",
+                      block_name: "API Request",
+                      message: "Successfully fetched user profile data.",
+                      outputs: {
+                        response: [
+                          {
+                            id: 42,
+                            name: "Jane Doe",
+                            email: "jane@example.com",
+                            roles: ["admin", "editor"],
+                            settings: {
+                              theme: "dark",
+                              notifications: true,
+                              language: "en",
+                            },
+                          },
+                        ],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (image URL — ImageRenderer)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "image-gen-789" },
+                    output: {
+                      type: ResponseType.block_output,
+                      block_id: "image-gen-789",
+                      block_name: "Image Generator",
+                      message: "Generated image successfully.",
+                      outputs: {
+                        image: [
+                          "https://picsum.photos/seed/styleguide/600/400",
+                        ],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (markdown text — MarkdownRenderer)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "summarizer-101" },
+                    output: {
+                      type: ResponseType.block_output,
+                      block_id: "summarizer-101",
+                      block_name: "Text Summarizer",
+                      message: "Document summarized successfully.",
+                      outputs: {
+                        summary: [
+                          "## Executive Summary\n\nThe quarterly report shows **strong growth** across all departments:\n\n- Revenue increased by *23%* compared to Q3\n- Customer satisfaction score: `4.8/5.0`\n- New user sign-ups doubled\n\n### Key Takeaways\n\n1. **Product launches** drove the majority of growth\n2. **Marketing campaigns** exceeded ROI targets\n3. **Infrastructure costs** remained flat despite scaling\n\n> Overall, this was our strongest quarter to date.\n\n| Metric | Q3 | Q4 | Change |\n|--------|-----|-----|--------|\n| Revenue | $2.1M | $2.6M | +23% |\n| Users | 10k | 20k | +100% |\n| NPS | 72 | 78 | +6 |",
+                        ],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (plain text — TextRenderer)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "translate-202" },
+                    output: {
+                      type: ResponseType.block_output,
+                      block_id: "translate-202",
+                      block_name: "Translate Text",
+                      message: "Translation completed.",
+                      outputs: {
+                        translated_text: [
+                          "Bonjour le monde! Ceci est un exemple de texte traduit du bloc de traduction.",
+                        ],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (multiple items with expand)">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { block_id: "scraper-303" },
+                    output: {
+                      type: ResponseType.block_output,
+                      block_id: "scraper-303",
+                      block_name: "Web Scraper",
+                      message: "Scraped 6 articles from the feed.",
+                      outputs: {
+                        articles: [
+                          {
+                            title: "AI Advances in 2026",
+                            url: "https://example.com/1",
+                            score: 142,
+                          },
+                          {
+                            title: "New Framework Released",
+                            url: "https://example.com/2",
+                            score: 98,
+                          },
+                          {
+                            title: "Open Source Milestone",
+                            url: "https://example.com/3",
+                            score: 87,
+                          },
+                          {
+                            title: "Cloud Computing Trends",
+                            url: "https://example.com/4",
+                            score: 76,
+                          },
+                          {
+                            title: "Developer Survey Results",
+                            url: "https://example.com/5",
+                            score: 64,
+                          },
+                          {
+                            title: "Security Best Practices",
+                            url: "https://example.com/6",
+                            score: 51,
+                          },
+                        ],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <RunBlockTool
+                  part={{
+                    type: "tool-run_block",
+                    toolCallId: uid(),
+                    state: "output-error",
+                    input: { block_id: "weather-block-123" },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* RUN AGENT                                                      */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Run Agent">
+              <SubSection label="Input streaming">
+                <RunAgentTool
+                  part={{
+                    type: "tool-run_agent",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: { username_agent_slug: "creator/my-agent" },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (execution started)">
+                <RunAgentTool
+                  part={{
+                    type: "tool-run_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { username_agent_slug: "creator/my-agent" },
+                    output: {
+                      type: ResponseType.execution_started,
+                      execution_id: "exec-abc-123-def-456",
+                      graph_name: "YouTube Summarizer",
+                      message:
+                        "Agent execution started. You can track progress in your library.",
+                      status: "running",
+                      library_agent_link: "/library/agents/lib-123",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (agent details / inputs needed)">
+                <RunAgentTool
+                  part={{
+                    type: "tool-run_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { username_agent_slug: "creator/my-agent" },
+                    output: {
+                      type: ResponseType.agent_details,
+                      agent: {
+                        name: "YouTube Summarizer",
+                        description:
+                          "Summarizes YouTube videos into key points.",
+                        inputs: [
+                          {
+                            name: "video_url",
+                            title: "Video URL",
+                            type: "string",
+                            required: true,
+                            description: "The YouTube video URL to summarize",
+                          },
+                          {
+                            name: "language",
+                            title: "Output Language",
+                            type: "string",
+                            required: false,
+                            description:
+                              "Language for the summary (default: English)",
+                          },
+                        ],
+                      },
+                      message: "This agent requires inputs to run.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (setup requirements)">
+                <RunAgentTool
+                  part={{
+                    type: "tool-run_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { username_agent_slug: "creator/my-agent" },
+                    output: {
+                      type: ResponseType.setup_requirements,
+                      message: "This agent requires additional setup.",
+                      setup_info: {
+                        agent_name: "YouTube Summarizer",
+                        requirements: {},
+                        user_readiness: {
+                          missing_credentials: {
+                            youtube_api: {
+                              provider: "youtube",
+                              credentials_type: "api_key",
+                              title: "YouTube Data API Key",
+                              description:
+                                "Required to access YouTube video data.",
+                            },
+                          },
+                        },
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (need login)">
+                <RunAgentTool
+                  part={{
+                    type: "tool-run_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { username_agent_slug: "creator/my-agent" },
+                    output: {
+                      type: ResponseType.need_login,
+                      message:
+                        "You need to sign in to run this agent. Please log in and try again.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (error)">
+                <RunAgentTool
+                  part={{
+                    type: "tool-run_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { username_agent_slug: "creator/my-agent" },
+                    output: {
+                      type: ResponseType.error,
+                      message: "Failed to start the agent.",
+                      error: "Agent not found or has been deleted.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <RunAgentTool
+                  part={{
+                    type: "tool-run_agent",
+                    toolCallId: uid(),
+                    state: "output-error",
+                    input: { username_agent_slug: "creator/my-agent" },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* SCHEDULE AGENT                                                 */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Schedule Agent">
+              <SubSection label="Input streaming (schedule)">
+                <RunAgentTool
+                  part={{
+                    type: "tool-schedule_agent",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: {
+                      username_agent_slug: "creator/daily-digest",
+                      schedule_name: "Morning Digest",
+                      cron: "0 8 * * *",
+                      timezone: "America/Los_Angeles",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (execution started — scheduled)">
+                <RunAgentTool
+                  part={{
+                    type: "tool-schedule_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: {
+                      username_agent_slug: "creator/daily-digest",
+                      schedule_name: "Morning Digest",
+                      cron: "0 8 * * *",
+                    },
+                    output: {
+                      type: ResponseType.execution_started,
+                      execution_id: "sched-abc-123",
+                      graph_name: "Daily Digest",
+                      message:
+                        "Agent scheduled successfully. It will run daily at 8:00 AM.",
+                      status: "scheduled",
+                      library_agent_link: "/library/agents/lib-456",
+                    },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* CREATE AGENT                                                   */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Create Agent">
+              <SubSection label="Input streaming">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (operation started)">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.operation_started,
+                      operation_id: "op-create-123",
+                      tool_name: "create_agent",
+                      message:
+                        "Agent creation has been started. This may take a moment.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (operation pending)">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.operation_pending,
+                      operation_id: "op-create-123",
+                      tool_name: "create_agent",
+                      message:
+                        "Agent creation is queued and will begin shortly.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (operation in progress)">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.operation_in_progress,
+                      tool_call_id: "tc-456",
+                      message:
+                        "An agent creation operation is already in progress. Please wait for it to finish.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (agent preview)">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.agent_preview,
+                      agent_name: "Email Summarizer",
+                      description:
+                        "An agent that summarizes your unread emails into a daily digest.",
+                      node_count: 4,
+                      message:
+                        "Here's a preview of the agent. Would you like me to save it?",
+                      agent_json: {
+                        name: "Email Summarizer",
+                        nodes: [
+                          { id: "1", type: "gmail_reader" },
+                          { id: "2", type: "text_summarizer" },
+                          { id: "3", type: "formatter" },
+                          { id: "4", type: "output" },
+                        ],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (agent saved)">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.agent_saved,
+                      agent_id: "agent-789",
+                      agent_name: "Email Summarizer",
+                      library_agent_id: "lib-agent-789",
+                      library_agent_link: "/library/agents/lib-agent-789",
+                      agent_page_link: "/build?agent=agent-789",
+                      message:
+                        "Agent 'Email Summarizer' has been saved to your library!",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (clarification needed)">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.clarification_needed,
+                      message:
+                        "I need a bit more information before creating this agent.",
+                      questions: [
+                        {
+                          question:
+                            "Which email provider should the agent connect to?",
+                          keyword: "email_provider",
+                          example: "Gmail, Outlook, Yahoo",
+                        },
+                        {
+                          question:
+                            "How frequently should the digest be generated?",
+                          keyword: "frequency",
+                          example: "Daily, Twice a day, Weekly",
+                        },
+                      ],
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (error)">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.error,
+                      message: "Failed to create the agent.",
+                      error:
+                        "The requested blocks are not compatible with each other.",
+                      details: {
+                        incompatible: ["gmail_reader", "slack_writer"],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <CreateAgentTool
+                  part={{
+                    type: "tool-create_agent",
+                    toolCallId: uid(),
+                    state: "output-error",
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* EDIT AGENT                                                     */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: Edit Agent">
+              <SubSection label="Input streaming">
+                <EditAgentTool
+                  part={{
+                    type: "tool-edit_agent",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (operation started)">
+                <EditAgentTool
+                  part={{
+                    type: "tool-edit_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.operation_started,
+                      operation_id: "op-edit-456",
+                      tool_name: "edit_agent",
+                      message: "Agent editing has started.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (agent preview)">
+                <EditAgentTool
+                  part={{
+                    type: "tool-edit_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.agent_preview,
+                      agent_name: "Email Summarizer v2",
+                      description:
+                        "Updated agent with improved summarization and Slack integration.",
+                      node_count: 6,
+                      message:
+                        "Here's the updated agent. Shall I save these changes?",
+                      agent_json: {
+                        name: "Email Summarizer v2",
+                        nodes: [
+                          { id: "1", type: "gmail_reader" },
+                          { id: "2", type: "text_summarizer" },
+                          { id: "3", type: "formatter" },
+                          { id: "4", type: "slack_writer" },
+                          { id: "5", type: "scheduler" },
+                          { id: "6", type: "output" },
+                        ],
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (agent saved)">
+                <EditAgentTool
+                  part={{
+                    type: "tool-edit_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.agent_saved,
+                      agent_id: "agent-789",
+                      agent_name: "Email Summarizer v2",
+                      library_agent_id: "lib-agent-789",
+                      library_agent_link: "/library/agents/lib-agent-789",
+                      agent_page_link: "/build?agent=agent-789",
+                      message:
+                        "Agent 'Email Summarizer v2' has been saved successfully!",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (clarification needed)">
+                <EditAgentTool
+                  part={{
+                    type: "tool-edit_agent",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    output: {
+                      type: ResponseType.clarification_needed,
+                      message:
+                        "I need to clarify a few things about the edits you want.",
+                      questions: [
+                        {
+                          question:
+                            "Should the Slack notification replace the email output or be in addition to it?",
+                          keyword: "notification_mode",
+                          example: "Replace, Add alongside",
+                        },
+                      ],
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <EditAgentTool
+                  part={{
+                    type: "tool-edit_agent",
+                    toolCallId: uid(),
+                    state: "output-error",
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* VIEW AGENT OUTPUT                                              */}
+            {/* ============================================================= */}
+
+            <Section title="Tool: View Agent Output">
+              <SubSection label="Input streaming">
+                <ViewAgentOutputTool
+                  part={{
+                    type: "tool-view_agent_output",
+                    toolCallId: uid(),
+                    state: "input-streaming",
+                    input: {
+                      agent_name: "YouTube Summarizer",
+                      execution_id: "exec-abc-123",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (with execution data)">
+                <ViewAgentOutputTool
+                  part={{
+                    type: "tool-view_agent_output",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: {
+                      agent_name: "YouTube Summarizer",
+                      execution_id: "exec-abc-123",
+                    },
+                    output: {
+                      type: ResponseType.agent_output,
+                      agent_id: "agent-123",
+                      agent_name: "YouTube Summarizer",
+                      message: "Here are the results from the last execution.",
+                      library_agent_link: "/library/agents/lib-agent-123",
+                      execution: {
+                        execution_id: "exec-abc-123",
+                        status: "completed",
+                        inputs_summary: {
+                          video_url: "https://youtube.com/watch?v=dQw4w9WgXcQ",
+                        },
+                        outputs: {
+                          summary: [
+                            "Key Points:\n1. Introduction to the topic\n2. Main arguments presented\n3. Conclusion and takeaways",
+                          ],
+                          keywords: ["music", "classic", "80s"],
+                        },
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (rich outputs — JSON + markdown + image)">
+                <ViewAgentOutputTool
+                  part={{
+                    type: "tool-view_agent_output",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: {
+                      agent_name: "Research Agent",
+                      execution_id: "exec-rich-456",
+                    },
+                    output: {
+                      type: ResponseType.agent_output,
+                      agent_id: "agent-456",
+                      agent_name: "Research Agent",
+                      message: "Research completed with multiple output types.",
+                      library_agent_link: "/library/agents/lib-agent-456",
+                      execution: {
+                        execution_id: "exec-rich-456",
+                        status: "completed",
+                        inputs_summary: {
+                          topic: "Artificial Intelligence in Healthcare",
+                          depth: "comprehensive",
+                          format: "report",
+                        },
+                        outputs: {
+                          report: [
+                            "## AI in Healthcare: 2026 Landscape\n\n### Key Findings\n\n- **Diagnostic accuracy** improved by 34% with AI-assisted imaging\n- Drug discovery timelines reduced from *10 years to 3 years*\n- Patient outcomes improved across `87%` of pilot programs\n\n> AI is not replacing doctors — it's augmenting their capabilities.\n\n### Adoption by Region\n\n| Region | Adoption Rate | Growth |\n|--------|--------------|--------|\n| North America | 78% | +15% |\n| Europe | 62% | +22% |\n| Asia Pacific | 71% | +31% |",
+                          ],
+                          metadata: [
+                            {
+                              sources_analyzed: 142,
+                              confidence_score: 0.94,
+                              processing_time_ms: 3420,
+                              model_version: "v2.3.1",
+                              categories: [
+                                "healthcare",
+                                "machine-learning",
+                                "diagnostics",
+                              ],
+                            },
+                          ],
+                          chart: [
+                            "https://picsum.photos/seed/chart-demo/500/300",
+                          ],
+                        },
+                      },
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (no execution selected)">
+                <ViewAgentOutputTool
+                  part={{
+                    type: "tool-view_agent_output",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { agent_name: "YouTube Summarizer" },
+                    output: {
+                      type: ResponseType.agent_output,
+                      agent_id: "agent-123",
+                      agent_name: "YouTube Summarizer",
+                      message:
+                        "Agent found but no specific execution selected.",
+                      library_agent_link: "/library/agents/lib-agent-123",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (no results)">
+                <ViewAgentOutputTool
+                  part={{
+                    type: "tool-view_agent_output",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { agent_name: "Nonexistent Agent" },
+                    output: {
+                      type: ResponseType.no_results,
+                      message:
+                        "No outputs found for this agent. It may not have been run yet.",
+                      suggestions: [
+                        "Try running the agent first",
+                        "Check the agent name is correct",
+                      ],
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output available (error)">
+                <ViewAgentOutputTool
+                  part={{
+                    type: "tool-view_agent_output",
+                    toolCallId: uid(),
+                    state: "output-available",
+                    input: { agent_name: "YouTube Summarizer" },
+                    output: {
+                      type: ResponseType.error,
+                      message: "Failed to retrieve agent output.",
+                      error: "Execution data is corrupted or unavailable.",
+                    },
+                  }}
+                />
+              </SubSection>
+
+              <SubSection label="Output error">
+                <ViewAgentOutputTool
+                  part={{
+                    type: "tool-view_agent_output",
+                    toolCallId: uid(),
+                    state: "output-error",
+                    input: { agent_name: "YouTube Summarizer" },
+                  }}
+                />
+              </SubSection>
+            </Section>
+
+            {/* ============================================================= */}
+            {/* FULL CONVERSATION EXAMPLE                                      */}
+            {/* ============================================================= */}
+
+            <Section title="Full Conversation Example">
+              <Conversation className="min-h-0 rounded-lg border bg-white">
+                <ConversationContent className="gap-6 px-3 py-6">
+                  <Message from="user">
+                    <MessageContent className="text-[1rem] leading-relaxed group-[.is-user]:rounded-xl group-[.is-user]:bg-purple-100 group-[.is-user]:px-3 group-[.is-user]:py-2.5 group-[.is-user]:text-slate-900 group-[.is-user]:[border-bottom-right-radius:0]">
+                      <MessageResponse>
+                        Find me a block that can fetch weather data
+                      </MessageResponse>
+                    </MessageContent>
+                  </Message>
+
+                  <Message from="assistant">
+                    <MessageContent className="text-[1rem] leading-relaxed group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900">
+                      <MessageResponse>
+                        Let me search for weather-related blocks for you.
+                      </MessageResponse>
+
+                      <FindBlocksTool
+                        part={{
+                          type: "tool-find_block",
+                          toolCallId: uid(),
+                          state: "output-available",
+                          input: { query: "weather" },
+                          output: {
+                            type: ResponseType.block_list,
+                            blocks: [
+                              {
+                                id: "block-1",
+                                name: "Get Weather",
+                                description:
+                                  "Fetches current weather data for a given city.",
+                                categories: [],
+                              },
+                              {
+                                id: "block-2",
+                                name: "Weather Forecast",
+                                description:
+                                  "Returns a 5-day weather forecast for any location.",
+                                categories: [],
+                              },
+                            ],
+                            count: 2,
+                          },
+                        }}
+                      />
+
+                      <MessageResponse>
+                        I found 2 blocks related to weather. The **Get Weather**
+                        block fetches current conditions, while **Weather
+                        Forecast** provides a 5-day outlook. Would you like me
+                        to run one of these?
+                      </MessageResponse>
+                    </MessageContent>
+                  </Message>
+
+                  <Message from="user">
+                    <MessageContent className="text-[1rem] leading-relaxed group-[.is-user]:rounded-xl group-[.is-user]:bg-purple-100 group-[.is-user]:px-3 group-[.is-user]:py-2.5 group-[.is-user]:text-slate-900 group-[.is-user]:[border-bottom-right-radius:0]">
+                      <MessageResponse>
+                        Yes, run the Get Weather block for San Francisco
+                      </MessageResponse>
+                    </MessageContent>
+                  </Message>
+
+                  <Message from="assistant">
+                    <MessageContent className="text-[1rem] leading-relaxed group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900">
+                      <RunBlockTool
+                        part={{
+                          type: "tool-run_block",
+                          toolCallId: uid(),
+                          state: "output-available",
+                          input: {
+                            block_id: "block-1",
+                            input_data: { city: "San Francisco" },
+                          },
+                          output: {
+                            type: ResponseType.block_output,
+                            block_id: "block-1",
+                            block_name: "Get Weather",
+                            message:
+                              "Successfully fetched weather for San Francisco.",
+                            outputs: {
+                              temperature: ["68°F"],
+                              condition: ["Foggy"],
+                              humidity: ["85%"],
+                              wind: ["12 mph W"],
+                            },
+                          },
+                        }}
+                      />
+
+                      <MessageResponse>
+                        The current weather in San Francisco is **68°F** and
+                        **Foggy** with 85% humidity and winds from the west at
+                        12 mph.
+                      </MessageResponse>
+                    </MessageContent>
+                  </Message>
+                </ConversationContent>
+              </Conversation>
+            </Section>
+          </div>
+        </div>
+      </div>
+    </CopilotChatActionsProvider>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
new file mode 100644
index 0000000000..88b1c491d7
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
@@ -0,0 +1,234 @@
+"use client";
+
+import { WarningDiamondIcon } from "@phosphor-icons/react";
+import type { ToolUIPart } from "ai";
+import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
+import {
+  ContentCardDescription,
+  ContentCodeBlock,
+  ContentGrid,
+  ContentHint,
+  ContentLink,
+  ContentMessage,
+} from "../../components/ToolAccordion/AccordionContent";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
+import {
+  ClarificationQuestionsCard,
+  ClarifyingQuestion,
+} from "./components/ClarificationQuestionsCard";
+import {
+  AccordionIcon,
+  formatMaybeJson,
+  getAnimationText,
+  getCreateAgentToolOutput,
+  isAgentPreviewOutput,
+  isAgentSavedOutput,
+  isClarificationNeededOutput,
+  isErrorOutput,
+  isOperationInProgressOutput,
+  isOperationPendingOutput,
+  isOperationStartedOutput,
+  ToolIcon,
+  truncateText,
+  type CreateAgentToolOutput,
+} from "./helpers";
+
+export interface CreateAgentToolPart {
+  type: string;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}
+
+interface Props {
+  part: CreateAgentToolPart;
+}
+
+function getAccordionMeta(output: CreateAgentToolOutput) {
+  const icon = <AccordionIcon />;
+
+  if (isAgentSavedOutput(output)) {
+    return { icon, title: output.agent_name };
+  }
+  if (isAgentPreviewOutput(output)) {
+    return {
+      icon,
+      title: output.agent_name,
+      description: `${output.node_count} block${output.node_count === 1 ? "" : "s"}`,
+    };
+  }
+  if (isClarificationNeededOutput(output)) {
+    const questions = output.questions ?? [];
+    return {
+      icon,
+      title: "Needs clarification",
+      description: `${questions.length} question${questions.length === 1 ? "" : "s"}`,
+      expanded: true,
+    };
+  }
+  if (
+    isOperationStartedOutput(output) ||
+    isOperationPendingOutput(output) ||
+    isOperationInProgressOutput(output)
+  ) {
+    return {
+      icon,
+      title: "Creating agent, this may take a few minutes. Sit back and relax.",
+    };
+  }
+  return {
+    icon: (
+      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
+    ),
+    title: "Error",
+    titleClassName: "text-red-500",
+  };
+}
+
+export function CreateAgentTool({ part }: Props) {
+  const text = getAnimationText(part);
+  const { onSend } = useCopilotChatActions();
+
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+
+  const output = getCreateAgentToolOutput(part);
+
+  const isError =
+    part.state === "output-error" || (!!output && isErrorOutput(output));
+
+  const isOperating =
+    !!output &&
+    (isOperationStartedOutput(output) ||
+      isOperationPendingOutput(output) ||
+      isOperationInProgressOutput(output));
+
+  const progress = useAsymptoticProgress(isOperating);
+
+  const hasExpandableContent =
+    part.state === "output-available" &&
+    !!output &&
+    (isOperationStartedOutput(output) ||
+      isOperationPendingOutput(output) ||
+      isOperationInProgressOutput(output) ||
+      isAgentPreviewOutput(output) ||
+      isAgentSavedOutput(output) ||
+      isClarificationNeededOutput(output) ||
+      isErrorOutput(output));
+
+  function handleClarificationAnswers(answers: Record<string, string>) {
+    const questions =
+      output && isClarificationNeededOutput(output)
+        ? (output.questions ?? [])
+        : [];
+
+    const contextMessage = questions
+      .map((q) => {
+        const answer = answers[q.keyword] || "";
+        return `> ${q.question}\n\n${answer}`;
+      })
+      .join("\n\n");
+
+    onSend(
+      `**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
+    );
+  }
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon isStreaming={isStreaming} isError={isError} />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasExpandableContent && output && (
+        <ToolAccordion {...getAccordionMeta(output)}>
+          {isOperating && (
+            <ContentGrid>
+              <ProgressBar value={progress} className="max-w-[280px]" />
+              <ContentHint>
+                This could take a few minutes, grab a coffee ☕
+              </ContentHint>
+            </ContentGrid>
+          )}
+
+          {isAgentSavedOutput(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              <div className="flex flex-wrap gap-2">
+                <ContentLink href={output.library_agent_link}>
+                  Open in library
+                </ContentLink>
+                <ContentLink href={output.agent_page_link}>
+                  Open in builder
+                </ContentLink>
+              </div>
+              <ContentCodeBlock>
+                {truncateText(
+                  formatMaybeJson({ agent_id: output.agent_id }),
+                  800,
+                )}
+              </ContentCodeBlock>
+            </ContentGrid>
+          )}
+
+          {isAgentPreviewOutput(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              {output.description?.trim() && (
+                <ContentCardDescription>
+                  {output.description}
+                </ContentCardDescription>
+              )}
+              <ContentCodeBlock>
+                {truncateText(formatMaybeJson(output.agent_json), 1600)}
+              </ContentCodeBlock>
+            </ContentGrid>
+          )}
+
+          {isClarificationNeededOutput(output) && (
+            <ClarificationQuestionsCard
+              questions={(output.questions ?? []).map((q) => {
+                const item: ClarifyingQuestion = {
+                  question: q.question,
+                  keyword: q.keyword,
+                };
+                const example =
+                  typeof q.example === "string" && q.example.trim()
+                    ? q.example.trim()
+                    : null;
+                if (example) item.example = example;
+                return item;
+              })}
+              message={output.message}
+              onSubmitAnswers={handleClarificationAnswers}
+            />
+          )}
+
+          {isErrorOutput(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              {output.error && (
+                <ContentCodeBlock>
+                  {formatMaybeJson(output.error)}
+                </ContentCodeBlock>
+              )}
+              {output.details && (
+                <ContentCodeBlock>
+                  {formatMaybeJson(output.details)}
+                </ContentCodeBlock>
+              )}
+            </ContentGrid>
+          )}
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ClarificationQuestionsWidget/ClarificationQuestionsWidget.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/ClarificationQuestionsCard.tsx
similarity index 78%
rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ClarificationQuestionsWidget/ClarificationQuestionsWidget.tsx
rename to autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/ClarificationQuestionsCard.tsx
index a3bd17dd3f..abcb04731e 100644
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ClarificationQuestionsWidget/ClarificationQuestionsWidget.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/ClarificationQuestionsCard.tsx
@@ -6,7 +6,7 @@ import { Input } from "@/components/atoms/Input/Input";
 import { Text } from "@/components/atoms/Text/Text";
 import { cn } from "@/lib/utils";
 import { CheckCircleIcon, QuestionIcon } from "@phosphor-icons/react";
-import { useState } from "react";
+import { useEffect, useRef, useState } from "react";
 
 export interface ClarifyingQuestion {
   question: string;
@@ -17,39 +17,91 @@ export interface ClarifyingQuestion {
 interface Props {
   questions: ClarifyingQuestion[];
   message: string;
+  sessionId?: string;
   onSubmitAnswers: (answers: Record<string, string>) => void;
   onCancel?: () => void;
+  isAnswered?: boolean;
   className?: string;
 }
 
-export function ClarificationQuestionsWidget({
+export function ClarificationQuestionsCard({
   questions,
   message,
+  sessionId,
   onSubmitAnswers,
   onCancel,
+  isAnswered = false,
   className,
 }: Props) {
   const [answers, setAnswers] = useState<Record<string, string>>({});
   const [isSubmitted, setIsSubmitted] = useState(false);
+  const lastSessionIdRef = useRef<string | undefined>(undefined);
+
+  useEffect(() => {
+    const storageKey = getStorageKey(sessionId);
+    if (!storageKey) {
+      setAnswers({});
+      setIsSubmitted(false);
+      lastSessionIdRef.current = sessionId;
+      return;
+    }
+
+    try {
+      const saved = localStorage.getItem(storageKey);
+      if (saved) {
+        const parsed = JSON.parse(saved) as Record<string, string>;
+        setAnswers(parsed);
+      } else {
+        setAnswers({});
+      }
+      setIsSubmitted(false);
+    } catch {
+      setAnswers({});
+      setIsSubmitted(false);
+    }
+    lastSessionIdRef.current = sessionId;
+  }, [sessionId]);
+
+  useEffect(() => {
+    if (lastSessionIdRef.current !== sessionId) {
+      return;
+    }
+    const storageKey = getStorageKey(sessionId);
+    if (!storageKey) return;
+
+    const hasAnswers = Object.values(answers).some((v) => v.trim());
+    try {
+      if (hasAnswers) {
+        localStorage.setItem(storageKey, JSON.stringify(answers));
+      } else {
+        localStorage.removeItem(storageKey);
+      }
+    } catch {}
+  }, [answers, sessionId]);
 
   function handleAnswerChange(keyword: string, value: string) {
     setAnswers((prev) => ({ ...prev, [keyword]: value }));
   }
 
   function handleSubmit() {
-    // Check if all questions are answered
     const allAnswered = questions.every((q) => answers[q.keyword]?.trim());
     if (!allAnswered) {
       return;
     }
     setIsSubmitted(true);
     onSubmitAnswers(answers);
+
+    const storageKey = getStorageKey(sessionId);
+    try {
+      if (storageKey) {
+        localStorage.removeItem(storageKey);
+      }
+    } catch {}
   }
 
   const allAnswered = questions.every((q) => answers[q.keyword]?.trim());
 
-  // Show submitted state after answers are submitted
-  if (isSubmitted) {
+  if (isAnswered || isSubmitted) {
     return (
       <div
         className={cn(
@@ -184,3 +236,8 @@ export function ClarificationQuestionsWidget({
     </div>
   );
 }
+
+function getStorageKey(sessionId?: string): string | null {
+  if (!sessionId) return null;
+  return `clarification_answers_${sessionId}`;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx
new file mode 100644
index 0000000000..bd47eac051
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx
@@ -0,0 +1,186 @@
+import type { AgentPreviewResponse } from "@/app/api/__generated__/models/agentPreviewResponse";
+import type { AgentSavedResponse } from "@/app/api/__generated__/models/agentSavedResponse";
+import type { ClarificationNeededResponse } from "@/app/api/__generated__/models/clarificationNeededResponse";
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import type { OperationInProgressResponse } from "@/app/api/__generated__/models/operationInProgressResponse";
+import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
+import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import {
+  PlusCircleIcon,
+  PlusIcon,
+  WarningDiamondIcon,
+} from "@phosphor-icons/react";
+import type { ToolUIPart } from "ai";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
+
+export type CreateAgentToolOutput =
+  | OperationStartedResponse
+  | OperationPendingResponse
+  | OperationInProgressResponse
+  | AgentPreviewResponse
+  | AgentSavedResponse
+  | ClarificationNeededResponse
+  | ErrorResponse;
+
+function parseOutput(output: unknown): CreateAgentToolOutput | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (
+      type === ResponseType.operation_started ||
+      type === ResponseType.operation_pending ||
+      type === ResponseType.operation_in_progress ||
+      type === ResponseType.agent_preview ||
+      type === ResponseType.agent_saved ||
+      type === ResponseType.clarification_needed ||
+      type === ResponseType.error
+    ) {
+      return output as CreateAgentToolOutput;
+    }
+    if ("operation_id" in output && "tool_name" in output)
+      return output as OperationStartedResponse | OperationPendingResponse;
+    if ("tool_call_id" in output) return output as OperationInProgressResponse;
+    if ("agent_json" in output && "agent_name" in output)
+      return output as AgentPreviewResponse;
+    if ("agent_id" in output && "library_agent_id" in output)
+      return output as AgentSavedResponse;
+    if ("questions" in output) return output as ClarificationNeededResponse;
+    if ("error" in output || "details" in output)
+      return output as ErrorResponse;
+  }
+  return null;
+}
+
+export function getCreateAgentToolOutput(
+  part: unknown,
+): CreateAgentToolOutput | null {
+  if (!part || typeof part !== "object") return null;
+  return parseOutput((part as { output?: unknown }).output);
+}
+
+export function isOperationStartedOutput(
+  output: CreateAgentToolOutput,
+): output is OperationStartedResponse {
+  return (
+    output.type === ResponseType.operation_started ||
+    ("operation_id" in output && "tool_name" in output)
+  );
+}
+
+export function isOperationPendingOutput(
+  output: CreateAgentToolOutput,
+): output is OperationPendingResponse {
+  return output.type === ResponseType.operation_pending;
+}
+
+export function isOperationInProgressOutput(
+  output: CreateAgentToolOutput,
+): output is OperationInProgressResponse {
+  return (
+    output.type === ResponseType.operation_in_progress ||
+    "tool_call_id" in output
+  );
+}
+
+export function isAgentPreviewOutput(
+  output: CreateAgentToolOutput,
+): output is AgentPreviewResponse {
+  return output.type === ResponseType.agent_preview || "agent_json" in output;
+}
+
+export function isAgentSavedOutput(
+  output: CreateAgentToolOutput,
+): output is AgentSavedResponse {
+  return (
+    output.type === ResponseType.agent_saved || "agent_page_link" in output
+  );
+}
+
+export function isClarificationNeededOutput(
+  output: CreateAgentToolOutput,
+): output is ClarificationNeededResponse {
+  return (
+    output.type === ResponseType.clarification_needed || "questions" in output
+  );
+}
+
+export function isErrorOutput(
+  output: CreateAgentToolOutput,
+): output is ErrorResponse {
+  return output.type === ResponseType.error || "error" in output;
+}
+
+export function getAnimationText(part: {
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}): string {
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return "Creating a new agent";
+    case "output-available": {
+      const output = parseOutput(part.output);
+      if (!output) return "Creating a new agent";
+      if (isOperationStartedOutput(output)) return "Agent creation started";
+      if (isOperationPendingOutput(output)) return "Agent creation in progress";
+      if (isOperationInProgressOutput(output))
+        return "Agent creation already in progress";
+      if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
+      if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
+      if (isClarificationNeededOutput(output)) return "Needs clarification";
+      return "Error creating agent";
+    }
+    case "output-error":
+      return "Error creating agent";
+    default:
+      return "Creating a new agent";
+  }
+}
+
+export function ToolIcon({
+  isStreaming,
+  isError,
+}: {
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  if (isError) {
+    return (
+      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
+    );
+  }
+  if (isStreaming) {
+    return <OrbitLoader size={24} />;
+  }
+  return <PlusIcon size={14} weight="regular" className="text-neutral-400" />;
+}
+
+export function AccordionIcon() {
+  return <PlusCircleIcon size={32} weight="light" />;
+}
+
+export function formatMaybeJson(value: unknown): string {
+  if (typeof value === "string") return value;
+  try {
+    return JSON.stringify(value, null, 2);
+  } catch {
+    return String(value);
+  }
+}
+
+export function truncateText(text: string, maxChars: number): string {
+  const trimmed = text.trim();
+  if (trimmed.length <= maxChars) return trimmed;
+  return `${trimmed.slice(0, maxChars).trimEnd()}…`;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx
new file mode 100644
index 0000000000..6766a5cb49
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx
@@ -0,0 +1,231 @@
+"use client";
+
+import { WarningDiamondIcon } from "@phosphor-icons/react";
+import type { ToolUIPart } from "ai";
+import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
+import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
+import {
+  ContentCardDescription,
+  ContentCodeBlock,
+  ContentGrid,
+  ContentHint,
+  ContentLink,
+  ContentMessage,
+} from "../../components/ToolAccordion/AccordionContent";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
+import {
+  ClarificationQuestionsCard,
+  ClarifyingQuestion,
+} from "../CreateAgent/components/ClarificationQuestionsCard";
+import {
+  AccordionIcon,
+  formatMaybeJson,
+  getAnimationText,
+  getEditAgentToolOutput,
+  isAgentPreviewOutput,
+  isAgentSavedOutput,
+  isClarificationNeededOutput,
+  isErrorOutput,
+  isOperationInProgressOutput,
+  isOperationPendingOutput,
+  isOperationStartedOutput,
+  ToolIcon,
+  truncateText,
+  type EditAgentToolOutput,
+} from "./helpers";
+
+export interface EditAgentToolPart {
+  type: string;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}
+
+interface Props {
+  part: EditAgentToolPart;
+}
+
+function getAccordionMeta(output: EditAgentToolOutput): {
+  icon: React.ReactNode;
+  title: string;
+  titleClassName?: string;
+  description?: string;
+} {
+  const icon = <AccordionIcon />;
+
+  if (isAgentSavedOutput(output)) {
+    return { icon, title: output.agent_name };
+  }
+  if (isAgentPreviewOutput(output)) {
+    return {
+      icon,
+      title: output.agent_name,
+      description: `${output.node_count} block${output.node_count === 1 ? "" : "s"}`,
+    };
+  }
+  if (isClarificationNeededOutput(output)) {
+    const questions = output.questions ?? [];
+    return {
+      icon,
+      title: "Needs clarification",
+      description: `${questions.length} question${questions.length === 1 ? "" : "s"}`,
+    };
+  }
+  if (
+    isOperationStartedOutput(output) ||
+    isOperationPendingOutput(output) ||
+    isOperationInProgressOutput(output)
+  ) {
+    return { icon: <OrbitLoader size={32} />, title: "Editing agent" };
+  }
+  return {
+    icon: (
+      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
+    ),
+    title: "Error",
+    titleClassName: "text-red-500",
+  };
+}
+
+export function EditAgentTool({ part }: Props) {
+  const text = getAnimationText(part);
+  const { onSend } = useCopilotChatActions();
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+
+  const output = getEditAgentToolOutput(part);
+  const isError =
+    part.state === "output-error" || (!!output && isErrorOutput(output));
+  const isOperating =
+    !!output &&
+    (isOperationStartedOutput(output) ||
+      isOperationPendingOutput(output) ||
+      isOperationInProgressOutput(output));
+  const progress = useAsymptoticProgress(isOperating);
+  const hasExpandableContent =
+    part.state === "output-available" &&
+    !!output &&
+    (isOperationStartedOutput(output) ||
+      isOperationPendingOutput(output) ||
+      isOperationInProgressOutput(output) ||
+      isAgentPreviewOutput(output) ||
+      isAgentSavedOutput(output) ||
+      isClarificationNeededOutput(output) ||
+      isErrorOutput(output));
+
+  function handleClarificationAnswers(answers: Record<string, string>) {
+    const questions =
+      output && isClarificationNeededOutput(output)
+        ? (output.questions ?? [])
+        : [];
+
+    const contextMessage = questions
+      .map((q) => {
+        const answer = answers[q.keyword] || "";
+        return `> ${q.question}\n\n${answer}`;
+      })
+      .join("\n\n");
+
+    onSend(
+      `**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with editing the agent.`,
+    );
+  }
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon isStreaming={isStreaming} isError={isError} />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasExpandableContent && output && (
+        <ToolAccordion {...getAccordionMeta(output)}>
+          {isOperating && (
+            <ContentGrid>
+              <ProgressBar value={progress} className="max-w-[280px]" />
+              <ContentHint>
+                This could take a few minutes, grab a coffee ☕
+              </ContentHint>
+            </ContentGrid>
+          )}
+
+          {isAgentSavedOutput(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              <div className="flex flex-wrap gap-2">
+                <ContentLink href={output.library_agent_link}>
+                  Open in library
+                </ContentLink>
+                <ContentLink href={output.agent_page_link}>
+                  Open in builder
+                </ContentLink>
+              </div>
+              <ContentCodeBlock>
+                {truncateText(
+                  formatMaybeJson({ agent_id: output.agent_id }),
+                  800,
+                )}
+              </ContentCodeBlock>
+            </ContentGrid>
+          )}
+
+          {isAgentPreviewOutput(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              {output.description?.trim() && (
+                <ContentCardDescription>
+                  {output.description}
+                </ContentCardDescription>
+              )}
+              <ContentCodeBlock>
+                {truncateText(formatMaybeJson(output.agent_json), 1600)}
+              </ContentCodeBlock>
+            </ContentGrid>
+          )}
+
+          {isClarificationNeededOutput(output) && (
+            <ClarificationQuestionsCard
+              questions={(output.questions ?? []).map((q) => {
+                const item: ClarifyingQuestion = {
+                  question: q.question,
+                  keyword: q.keyword,
+                };
+                const example =
+                  typeof q.example === "string" && q.example.trim()
+                    ? q.example.trim()
+                    : null;
+                if (example) item.example = example;
+                return item;
+              })}
+              message={output.message}
+              onSubmitAnswers={handleClarificationAnswers}
+            />
+          )}
+
+          {isErrorOutput(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              {output.error && (
+                <ContentCodeBlock>
+                  {formatMaybeJson(output.error)}
+                </ContentCodeBlock>
+              )}
+              {output.details && (
+                <ContentCodeBlock>
+                  {formatMaybeJson(output.details)}
+                </ContentCodeBlock>
+              )}
+            </ContentGrid>
+          )}
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/helpers.tsx
new file mode 100644
index 0000000000..a0db50cddc
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/helpers.tsx
@@ -0,0 +1,188 @@
+import type { AgentPreviewResponse } from "@/app/api/__generated__/models/agentPreviewResponse";
+import type { AgentSavedResponse } from "@/app/api/__generated__/models/agentSavedResponse";
+import type { ClarificationNeededResponse } from "@/app/api/__generated__/models/clarificationNeededResponse";
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import type { OperationInProgressResponse } from "@/app/api/__generated__/models/operationInProgressResponse";
+import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
+import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import {
+  NotePencilIcon,
+  PencilLineIcon,
+  WarningDiamondIcon,
+} from "@phosphor-icons/react";
+import type { ToolUIPart } from "ai";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
+
+export type EditAgentToolOutput =
+  | OperationStartedResponse
+  | OperationPendingResponse
+  | OperationInProgressResponse
+  | AgentPreviewResponse
+  | AgentSavedResponse
+  | ClarificationNeededResponse
+  | ErrorResponse;
+
+function parseOutput(output: unknown): EditAgentToolOutput | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (
+      type === ResponseType.operation_started ||
+      type === ResponseType.operation_pending ||
+      type === ResponseType.operation_in_progress ||
+      type === ResponseType.agent_preview ||
+      type === ResponseType.agent_saved ||
+      type === ResponseType.clarification_needed ||
+      type === ResponseType.error
+    ) {
+      return output as EditAgentToolOutput;
+    }
+    if ("operation_id" in output && "tool_name" in output)
+      return output as OperationStartedResponse | OperationPendingResponse;
+    if ("tool_call_id" in output) return output as OperationInProgressResponse;
+    if ("agent_json" in output && "agent_name" in output)
+      return output as AgentPreviewResponse;
+    if ("agent_id" in output && "library_agent_id" in output)
+      return output as AgentSavedResponse;
+    if ("questions" in output) return output as ClarificationNeededResponse;
+    if ("error" in output || "details" in output)
+      return output as ErrorResponse;
+  }
+  return null;
+}
+
+export function getEditAgentToolOutput(
+  part: unknown,
+): EditAgentToolOutput | null {
+  if (!part || typeof part !== "object") return null;
+  return parseOutput((part as { output?: unknown }).output);
+}
+
+export function isOperationStartedOutput(
+  output: EditAgentToolOutput,
+): output is OperationStartedResponse {
+  return (
+    output.type === ResponseType.operation_started ||
+    ("operation_id" in output && "tool_name" in output)
+  );
+}
+
+export function isOperationPendingOutput(
+  output: EditAgentToolOutput,
+): output is OperationPendingResponse {
+  return output.type === ResponseType.operation_pending;
+}
+
+export function isOperationInProgressOutput(
+  output: EditAgentToolOutput,
+): output is OperationInProgressResponse {
+  return (
+    output.type === ResponseType.operation_in_progress ||
+    "tool_call_id" in output
+  );
+}
+
+export function isAgentPreviewOutput(
+  output: EditAgentToolOutput,
+): output is AgentPreviewResponse {
+  return output.type === ResponseType.agent_preview || "agent_json" in output;
+}
+
+export function isAgentSavedOutput(
+  output: EditAgentToolOutput,
+): output is AgentSavedResponse {
+  return (
+    output.type === ResponseType.agent_saved || "agent_page_link" in output
+  );
+}
+
+export function isClarificationNeededOutput(
+  output: EditAgentToolOutput,
+): output is ClarificationNeededResponse {
+  return (
+    output.type === ResponseType.clarification_needed || "questions" in output
+  );
+}
+
+export function isErrorOutput(
+  output: EditAgentToolOutput,
+): output is ErrorResponse {
+  return output.type === ResponseType.error || "error" in output;
+}
+
+export function getAnimationText(part: {
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}): string {
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return "Editing the agent";
+    case "output-available": {
+      const output = parseOutput(part.output);
+      if (!output) return "Editing the agent";
+      if (isOperationStartedOutput(output)) return "Agent update started";
+      if (isOperationPendingOutput(output)) return "Agent update in progress";
+      if (isOperationInProgressOutput(output))
+        return "Agent update already in progress";
+      if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
+      if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
+      if (isClarificationNeededOutput(output)) return "Needs clarification";
+      return "Error editing agent";
+    }
+    case "output-error":
+      return "Error editing agent";
+    default:
+      return "Editing the agent";
+  }
+}
+
+export function ToolIcon({
+  isStreaming,
+  isError,
+}: {
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  if (isError) {
+    return (
+      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
+    );
+  }
+  if (isStreaming) {
+    return <OrbitLoader size={24} />;
+  }
+  return (
+    <PencilLineIcon size={14} weight="regular" className="text-neutral-400" />
+  );
+}
+
+export function AccordionIcon() {
+  return <NotePencilIcon size={32} weight="light" />;
+}
+
+export function formatMaybeJson(value: unknown): string {
+  if (typeof value === "string") return value;
+  try {
+    return JSON.stringify(value, null, 2);
+  } catch {
+    return String(value);
+  }
+}
+
+export function truncateText(text: string, maxChars: number): string {
+  const trimmed = text.trim();
+  if (trimmed.length <= maxChars) return trimmed;
+  return `${trimmed.slice(0, maxChars).trimEnd()}…`;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/FindAgents.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/FindAgents.tsx
new file mode 100644
index 0000000000..4f0068b2c5
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/FindAgents.tsx
@@ -0,0 +1,127 @@
+"use client";
+
+import { ToolUIPart } from "ai";
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import {
+  ContentBadge,
+  ContentCard,
+  ContentCardDescription,
+  ContentCardHeader,
+  ContentCardTitle,
+  ContentGrid,
+  ContentLink,
+} from "../../components/ToolAccordion/AccordionContent";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import {
+  AccordionIcon,
+  getAgentHref,
+  getAnimationText,
+  getFindAgentsOutput,
+  getSourceLabelFromToolType,
+  isAgentsFoundOutput,
+  isErrorOutput,
+  ToolIcon,
+} from "./helpers";
+
+export interface FindAgentsToolPart {
+  type: string;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}
+
+interface Props {
+  part: FindAgentsToolPart;
+}
+
+export function FindAgentsTool({ part }: Props) {
+  const text = getAnimationText(part);
+  const output = getFindAgentsOutput(part);
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+  const isError =
+    part.state === "output-error" || (!!output && isErrorOutput(output));
+
+  const query =
+    typeof part.input === "object" && part.input !== null
+      ? String((part.input as { query?: unknown }).query ?? "").trim()
+      : "";
+
+  const agentsFoundOutput =
+    part.state === "output-available" && output && isAgentsFoundOutput(output)
+      ? output
+      : null;
+
+  const hasAgents =
+    !!agentsFoundOutput &&
+    agentsFoundOutput.agents.length > 0 &&
+    (typeof agentsFoundOutput.count !== "number" ||
+      agentsFoundOutput.count > 0);
+  const totalCount = agentsFoundOutput ? agentsFoundOutput.count : 0;
+  const { source } = getSourceLabelFromToolType(part.type);
+  const scopeText =
+    source === "library"
+      ? "in your library"
+      : source === "marketplace"
+        ? "in marketplace"
+        : "";
+  const accordionDescription = `Found ${totalCount}${scopeText ? ` ${scopeText}` : ""}${
+    query ? ` for "${query}"` : ""
+  }`;
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon
+          toolType={part.type}
+          isStreaming={isStreaming}
+          isError={isError}
+        />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasAgents && agentsFoundOutput && (
+        <ToolAccordion
+          icon={<AccordionIcon toolType={part.type} />}
+          title="Agent results"
+          description={accordionDescription}
+        >
+          <ContentGrid className="sm:grid-cols-2">
+            {agentsFoundOutput.agents.map((agent) => {
+              const href = getAgentHref(agent);
+              const agentSource =
+                agent.source === "library"
+                  ? "Library"
+                  : agent.source === "marketplace"
+                    ? "Marketplace"
+                    : null;
+              return (
+                <ContentCard key={agent.id}>
+                  <ContentCardHeader
+                    action={
+                      href ? <ContentLink href={href}>Open</ContentLink> : null
+                    }
+                  >
+                    <div className="flex items-center gap-2">
+                      <ContentCardTitle>{agent.name}</ContentCardTitle>
+                      {agentSource && (
+                        <ContentBadge>{agentSource}</ContentBadge>
+                      )}
+                    </div>
+                    <ContentCardDescription className="mt-1 line-clamp-2">
+                      {agent.description}
+                    </ContentCardDescription>
+                  </ContentCardHeader>
+                </ContentCard>
+              );
+            })}
+          </ContentGrid>
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/helpers.tsx
new file mode 100644
index 0000000000..f253947953
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/helpers.tsx
@@ -0,0 +1,187 @@
+import type { AgentInfo } from "@/app/api/__generated__/models/agentInfo";
+import type { AgentsFoundResponse } from "@/app/api/__generated__/models/agentsFoundResponse";
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import type { NoResultsResponse } from "@/app/api/__generated__/models/noResultsResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import {
+  FolderOpenIcon,
+  MagnifyingGlassIcon,
+  SquaresFourIcon,
+  StorefrontIcon,
+} from "@phosphor-icons/react";
+import { ToolUIPart } from "ai";
+
+export interface FindAgentInput {
+  query: string;
+}
+
+export type FindAgentsOutput =
+  | AgentsFoundResponse
+  | NoResultsResponse
+  | ErrorResponse;
+
+export type FindAgentsToolType =
+  | "tool-find_agent"
+  | "tool-find_library_agent"
+  | (string & {});
+
+function parseOutput(output: unknown): FindAgentsOutput | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (
+      type === ResponseType.agents_found ||
+      type === ResponseType.no_results ||
+      type === ResponseType.error
+    ) {
+      return output as FindAgentsOutput;
+    }
+    if ("agents" in output && "count" in output)
+      return output as AgentsFoundResponse;
+    if ("suggestions" in output && !("error" in output))
+      return output as NoResultsResponse;
+    if ("error" in output || "details" in output)
+      return output as ErrorResponse;
+  }
+  return null;
+}
+
+export function getFindAgentsOutput(part: unknown): FindAgentsOutput | null {
+  if (!part || typeof part !== "object") return null;
+  return parseOutput((part as { output?: unknown }).output);
+}
+
+export function isAgentsFoundOutput(
+  output: FindAgentsOutput,
+): output is AgentsFoundResponse {
+  return output.type === ResponseType.agents_found || "agents" in output;
+}
+
+export function isNoResultsOutput(
+  output: FindAgentsOutput,
+): output is NoResultsResponse {
+  return (
+    output.type === ResponseType.no_results ||
+    ("suggestions" in output && !("error" in output))
+  );
+}
+
+export function isErrorOutput(
+  output: FindAgentsOutput,
+): output is ErrorResponse {
+  return output.type === ResponseType.error || "error" in output;
+}
+
+export function getSourceLabelFromToolType(toolType?: FindAgentsToolType): {
+  source: "marketplace" | "library" | "unknown";
+  label: string;
+} {
+  if (toolType === "tool-find_library_agent") {
+    return { source: "library", label: "Library" };
+  }
+  if (toolType === "tool-find_agent") {
+    return { source: "marketplace", label: "Marketplace" };
+  }
+  return { source: "unknown", label: "Agents" };
+}
+
+export function getAnimationText(part: {
+  type?: FindAgentsToolType;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}): string {
+  const { source } = getSourceLabelFromToolType(part.type);
+  const query = (part.input as FindAgentInput | undefined)?.query?.trim();
+
+  // Action phrase matching legacy ToolCallMessage
+  const actionPhrase =
+    source === "library"
+      ? "Looking for library agents"
+      : "Looking for agents in the marketplace";
+
+  const queryText = query ? ` matching "${query}"` : "";
+
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return `${actionPhrase}${queryText}`;
+
+    case "output-available": {
+      const output = parseOutput(part.output);
+      if (!output) {
+        return `${actionPhrase}${queryText}`;
+      }
+      if (isNoResultsOutput(output)) {
+        return `No agents found${queryText}`;
+      }
+      if (isAgentsFoundOutput(output)) {
+        const count = output.count ?? output.agents?.length ?? 0;
+        return `Found ${count} agent${count === 1 ? "" : "s"}${queryText}`;
+      }
+      if (isErrorOutput(output)) {
+        return `Error finding agents${queryText}`;
+      }
+      return `${actionPhrase}${queryText}`;
+    }
+
+    case "output-error":
+      return `Error finding agents${queryText}`;
+
+    default:
+      return actionPhrase;
+  }
+}
+
+export function getAgentHref(agent: AgentInfo): string | null {
+  if (agent.source === "library") {
+    return `/library/agents/${encodeURIComponent(agent.id)}`;
+  }
+
+  const [creator, slug, ...rest] = agent.id.split("/");
+  if (!creator || !slug || rest.length > 0) return null;
+  return `/marketplace/agent/${encodeURIComponent(creator)}/${encodeURIComponent(slug)}`;
+}
+
+export function ToolIcon({
+  toolType,
+  isStreaming,
+  isError,
+}: {
+  toolType?: FindAgentsToolType;
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  const { source } = getSourceLabelFromToolType(toolType);
+  const IconComponent =
+    source === "library" ? MagnifyingGlassIcon : SquaresFourIcon;
+
+  return (
+    <IconComponent
+      size={14}
+      weight="regular"
+      className={
+        isError
+          ? "text-red-500"
+          : isStreaming
+            ? "text-neutral-500"
+            : "text-neutral-400"
+      }
+    />
+  );
+}
+
+export function AccordionIcon({ toolType }: { toolType?: FindAgentsToolType }) {
+  const { source } = getSourceLabelFromToolType(toolType);
+  const IconComponent = source === "library" ? FolderOpenIcon : StorefrontIcon;
+  return <IconComponent size={32} weight="light" />;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/FindBlocks.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/FindBlocks.tsx
new file mode 100644
index 0000000000..3684a2da14
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/FindBlocks.tsx
@@ -0,0 +1,92 @@
+"use client";
+
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import {
+  ContentCard,
+  ContentCardDescription,
+  ContentCardTitle,
+} from "../../components/ToolAccordion/AccordionContent";
+import type { BlockListResponse } from "@/app/api/__generated__/models/blockListResponse";
+import type { BlockInfoSummary } from "@/app/api/__generated__/models/blockInfoSummary";
+import { ToolUIPart } from "ai";
+import { HorizontalScroll } from "@/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll";
+import {
+  AccordionIcon,
+  getAnimationText,
+  parseOutput,
+  ToolIcon,
+} from "./helpers";
+
+export interface FindBlockInput {
+  query: string;
+}
+
+export type FindBlockOutput = BlockListResponse;
+
+export interface FindBlockToolPart {
+  type: string;
+  toolName?: string;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: FindBlockInput | unknown;
+  output?: string | FindBlockOutput | unknown;
+  title?: string;
+}
+
+interface Props {
+  part: FindBlockToolPart;
+}
+
+function BlockCard({ block }: { block: BlockInfoSummary }) {
+  return (
+    <ContentCard className="w-48 shrink-0">
+      <ContentCardTitle>{block.name}</ContentCardTitle>
+      <ContentCardDescription className="mt-1 line-clamp-2">
+        {block.description}
+      </ContentCardDescription>
+    </ContentCard>
+  );
+}
+
+export function FindBlocksTool({ part }: Props) {
+  const text = getAnimationText(part);
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+  const isError = part.state === "output-error";
+
+  const parsed =
+    part.state === "output-available" ? parseOutput(part.output) : null;
+  const hasBlocks = !!parsed && parsed.blocks.length > 0;
+
+  const query = (part.input as FindBlockInput | undefined)?.query?.trim();
+  const accordionDescription = parsed
+    ? `Found ${parsed.count} block${parsed.count === 1 ? "" : "s"}${query ? ` for "${query}"` : ""}`
+    : undefined;
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon isStreaming={isStreaming} isError={isError} />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasBlocks && parsed && (
+        <ToolAccordion
+          icon={<AccordionIcon />}
+          title="Block results"
+          description={accordionDescription}
+        >
+          <HorizontalScroll dependencyList={[parsed.blocks.length]}>
+            {parsed.blocks.map((block) => (
+              <BlockCard key={block.id} block={block} />
+            ))}
+          </HorizontalScroll>
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/helpers.tsx
new file mode 100644
index 0000000000..eaebe98ea5
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/helpers.tsx
@@ -0,0 +1,75 @@
+import type { BlockListResponse } from "@/app/api/__generated__/models/blockListResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import { CubeIcon, PackageIcon } from "@phosphor-icons/react";
+import { FindBlockInput, FindBlockToolPart } from "./FindBlocks";
+
+export function parseOutput(output: unknown): BlockListResponse | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (type === ResponseType.block_list || "blocks" in output) {
+      return output as BlockListResponse;
+    }
+  }
+  return null;
+}
+
+export function getAnimationText(part: FindBlockToolPart): string {
+  const query = (part.input as FindBlockInput | undefined)?.query?.trim();
+  const queryText = query ? ` matching "${query}"` : "";
+
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return `Searching for blocks${queryText}`;
+
+    case "output-available": {
+      const parsed = parseOutput(part.output);
+      if (parsed) {
+        return `Found ${parsed.count} block${parsed.count === 1 ? "" : "s"}${queryText}`;
+      }
+      return `Searching for blocks${queryText}`;
+    }
+
+    case "output-error":
+      return `Error finding blocks${queryText}`;
+
+    default:
+      return "Searching for blocks";
+  }
+}
+
+export function ToolIcon({
+  isStreaming,
+  isError,
+}: {
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  return (
+    <PackageIcon
+      size={14}
+      weight="regular"
+      className={
+        isError
+          ? "text-red-500"
+          : isStreaming
+            ? "text-neutral-500"
+            : "text-neutral-400"
+      }
+    />
+  );
+}
+
+export function AccordionIcon() {
+  return <CubeIcon size={32} weight="light" />;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/RunAgent.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/RunAgent.tsx
new file mode 100644
index 0000000000..f16b9d2b2f
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/RunAgent.tsx
@@ -0,0 +1,86 @@
+"use client";
+
+import type { ToolUIPart } from "ai";
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import { ContentMessage } from "../../components/ToolAccordion/AccordionContent";
+import {
+  getAccordionMeta,
+  getAnimationText,
+  getRunAgentToolOutput,
+  isRunAgentAgentDetailsOutput,
+  isRunAgentErrorOutput,
+  isRunAgentExecutionStartedOutput,
+  isRunAgentNeedLoginOutput,
+  isRunAgentSetupRequirementsOutput,
+  ToolIcon,
+} from "./helpers";
+import { ExecutionStartedCard } from "./components/ExecutionStartedCard/ExecutionStartedCard";
+import { AgentDetailsCard } from "./components/AgentDetailsCard/AgentDetailsCard";
+import { SetupRequirementsCard } from "./components/SetupRequirementsCard/SetupRequirementsCard";
+import { ErrorCard } from "./components/ErrorCard/ErrorCard";
+
+export interface RunAgentToolPart {
+  type: string;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}
+
+interface Props {
+  part: RunAgentToolPart;
+}
+
+export function RunAgentTool({ part }: Props) {
+  const text = getAnimationText(part);
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+
+  const output = getRunAgentToolOutput(part);
+  const isError =
+    part.state === "output-error" ||
+    (!!output && isRunAgentErrorOutput(output));
+  const hasExpandableContent =
+    part.state === "output-available" &&
+    !!output &&
+    (isRunAgentExecutionStartedOutput(output) ||
+      isRunAgentAgentDetailsOutput(output) ||
+      isRunAgentSetupRequirementsOutput(output) ||
+      isRunAgentNeedLoginOutput(output) ||
+      isRunAgentErrorOutput(output));
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon isStreaming={isStreaming} isError={isError} />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasExpandableContent && output && (
+        <ToolAccordion {...getAccordionMeta(output)}>
+          {isRunAgentExecutionStartedOutput(output) && (
+            <ExecutionStartedCard output={output} />
+          )}
+
+          {isRunAgentAgentDetailsOutput(output) && (
+            <AgentDetailsCard output={output} />
+          )}
+
+          {isRunAgentSetupRequirementsOutput(output) && (
+            <SetupRequirementsCard output={output} />
+          )}
+
+          {isRunAgentNeedLoginOutput(output) && (
+            <ContentMessage>{output.message}</ContentMessage>
+          )}
+
+          {isRunAgentErrorOutput(output) && <ErrorCard output={output} />}
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/AgentDetailsCard.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/AgentDetailsCard.tsx
new file mode 100644
index 0000000000..f18568faec
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/AgentDetailsCard.tsx
@@ -0,0 +1,116 @@
+"use client";
+
+import type { AgentDetailsResponse } from "@/app/api/__generated__/models/agentDetailsResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { FormRenderer } from "@/components/renderers/InputRenderer/FormRenderer";
+import { AnimatePresence, motion } from "framer-motion";
+import { useState } from "react";
+import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
+import { ContentMessage } from "../../../../components/ToolAccordion/AccordionContent";
+import { buildInputSchema } from "./helpers";
+
+interface Props {
+  output: AgentDetailsResponse;
+}
+
+export function AgentDetailsCard({ output }: Props) {
+  const { onSend } = useCopilotChatActions();
+  const [showInputForm, setShowInputForm] = useState(false);
+  const [inputValues, setInputValues] = useState<Record<string, unknown>>({});
+
+  function handleRunWithExamples() {
+    onSend(
+      `Run the agent "${output.agent.name}" with placeholder/example values so I can test it.`,
+    );
+  }
+
+  function handleRunWithInputs() {
+    const nonEmpty = Object.fromEntries(
+      Object.entries(inputValues).filter(
+        ([, v]) => v !== undefined && v !== null && v !== "",
+      ),
+    );
+    onSend(
+      `Run the agent "${output.agent.name}" with these inputs: ${JSON.stringify(nonEmpty, null, 2)}`,
+    );
+    setShowInputForm(false);
+    setInputValues({});
+  }
+
+  return (
+    <div className="grid gap-2">
+      <ContentMessage>
+        Run this agent with example values or your own inputs.
+      </ContentMessage>
+
+      <div className="flex gap-2 pt-4">
+        <Button size="small" className="w-fit" onClick={handleRunWithExamples}>
+          Run with example values
+        </Button>
+        <Button
+          variant="outline"
+          size="small"
+          className="w-fit"
+          onClick={() => setShowInputForm((prev) => !prev)}
+        >
+          Run with my inputs
+        </Button>
+      </div>
+
+      <AnimatePresence initial={false}>
+        {showInputForm && buildInputSchema(output.agent.inputs) && (
+          <motion.div
+            initial={{ height: 0, opacity: 0, filter: "blur(6px)" }}
+            animate={{ height: "auto", opacity: 1, filter: "blur(0px)" }}
+            exit={{ height: 0, opacity: 0, filter: "blur(6px)" }}
+            transition={{
+              height: { type: "spring", bounce: 0.15, duration: 0.5 },
+              opacity: { duration: 0.25 },
+              filter: { duration: 0.2 },
+            }}
+            className="overflow-hidden"
+            style={{ willChange: "height, opacity, filter" }}
+          >
+            <div className="mt-4 rounded-2xl border bg-background p-3 pt-4">
+              <Text variant="body-medium">Enter your inputs</Text>
+              <FormRenderer
+                jsonSchema={buildInputSchema(output.agent.inputs)!}
+                handleChange={(v) => setInputValues(v.formData ?? {})}
+                uiSchema={{
+                  "ui:submitButtonOptions": { norender: true },
+                }}
+                initialValues={inputValues}
+                formContext={{
+                  showHandles: false,
+                  size: "small",
+                }}
+              />
+              <div className="-mt-8 flex gap-2">
+                <Button
+                  variant="primary"
+                  size="small"
+                  className="w-fit"
+                  onClick={handleRunWithInputs}
+                >
+                  Run
+                </Button>
+                <Button
+                  variant="secondary"
+                  size="small"
+                  className="w-fit"
+                  onClick={() => {
+                    setShowInputForm(false);
+                    setInputValues({});
+                  }}
+                >
+                  Cancel
+                </Button>
+              </div>
+            </div>
+          </motion.div>
+        )}
+      </AnimatePresence>
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/helpers.ts
new file mode 100644
index 0000000000..635b8d20d7
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/helpers.ts
@@ -0,0 +1,8 @@
+import type { RJSFSchema } from "@rjsf/utils";
+
+export function buildInputSchema(inputs: unknown): RJSFSchema | null {
+  if (!inputs || typeof inputs !== "object") return null;
+  const properties = inputs as RJSFSchema["properties"];
+  if (!properties || Object.keys(properties).length === 0) return null;
+  return inputs as RJSFSchema;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ErrorCard/ErrorCard.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ErrorCard/ErrorCard.tsx
new file mode 100644
index 0000000000..7990428947
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ErrorCard/ErrorCard.tsx
@@ -0,0 +1,27 @@
+"use client";
+
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import {
+  ContentCodeBlock,
+  ContentGrid,
+  ContentMessage,
+} from "../../../../components/ToolAccordion/AccordionContent";
+import { formatMaybeJson } from "../../helpers";
+
+interface Props {
+  output: ErrorResponse;
+}
+
+export function ErrorCard({ output }: Props) {
+  return (
+    <ContentGrid>
+      <ContentMessage>{output.message}</ContentMessage>
+      {output.error && (
+        <ContentCodeBlock>{formatMaybeJson(output.error)}</ContentCodeBlock>
+      )}
+      {output.details && (
+        <ContentCodeBlock>{formatMaybeJson(output.details)}</ContentCodeBlock>
+      )}
+    </ContentGrid>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ExecutionStartedCard/ExecutionStartedCard.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ExecutionStartedCard/ExecutionStartedCard.tsx
new file mode 100644
index 0000000000..f98656e5ff
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ExecutionStartedCard/ExecutionStartedCard.tsx
@@ -0,0 +1,39 @@
+"use client";
+
+import type { ExecutionStartedResponse } from "@/app/api/__generated__/models/executionStartedResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { useRouter } from "next/navigation";
+import {
+  ContentCard,
+  ContentCardDescription,
+  ContentCardSubtitle,
+  ContentCardTitle,
+  ContentGrid,
+} from "../../../../components/ToolAccordion/AccordionContent";
+
+interface Props {
+  output: ExecutionStartedResponse;
+}
+
+export function ExecutionStartedCard({ output }: Props) {
+  const router = useRouter();
+
+  return (
+    <ContentGrid>
+      <ContentCard>
+        <ContentCardTitle>Execution started</ContentCardTitle>
+        <ContentCardSubtitle>{output.execution_id}</ContentCardSubtitle>
+        <ContentCardDescription>{output.message}</ContentCardDescription>
+        {output.library_agent_link && (
+          <Button
+            size="small"
+            className="mt-3"
+            onClick={() => router.push(output.library_agent_link!)}
+          >
+            View Execution
+          </Button>
+        )}
+      </ContentCard>
+    </ContentGrid>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/SetupRequirementsCard.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/SetupRequirementsCard.tsx
new file mode 100644
index 0000000000..c6d116e62a
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/SetupRequirementsCard.tsx
@@ -0,0 +1,105 @@
+"use client";
+
+import { useState } from "react";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
+import { Button } from "@/components/atoms/Button/Button";
+import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
+import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
+import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
+import {
+  ContentBadge,
+  ContentCardDescription,
+  ContentCardTitle,
+  ContentMessage,
+} from "../../../../components/ToolAccordion/AccordionContent";
+import { coerceCredentialFields, coerceExpectedInputs } from "./helpers";
+
+interface Props {
+  output: SetupRequirementsResponse;
+}
+
+export function SetupRequirementsCard({ output }: Props) {
+  const { onSend } = useCopilotChatActions();
+
+  const [inputCredentials, setInputCredentials] = useState<
+    Record<string, CredentialsMetaInput | undefined>
+  >({});
+  const [hasSent, setHasSent] = useState(false);
+
+  const { credentialFields, requiredCredentials } = coerceCredentialFields(
+    output.setup_info.user_readiness?.missing_credentials,
+  );
+
+  const expectedInputs = coerceExpectedInputs(
+    (output.setup_info.requirements as Record<string, unknown>)?.inputs,
+  );
+
+  function handleCredentialChange(key: string, value?: CredentialsMetaInput) {
+    setInputCredentials((prev) => ({ ...prev, [key]: value }));
+  }
+
+  const isAllComplete =
+    credentialFields.length > 0 &&
+    [...requiredCredentials].every((key) => !!inputCredentials[key]);
+
+  function handleProceed() {
+    setHasSent(true);
+    onSend(
+      "I've configured the required credentials. Please check if everything is ready and proceed with running the agent.",
+    );
+  }
+
+  return (
+    <div className="grid gap-2">
+      <ContentMessage>{output.message}</ContentMessage>
+
+      {credentialFields.length > 0 && (
+        <div className="rounded-2xl border bg-background p-3">
+          <CredentialsGroupedView
+            credentialFields={credentialFields}
+            requiredCredentials={requiredCredentials}
+            inputCredentials={inputCredentials}
+            inputValues={{}}
+            onCredentialChange={handleCredentialChange}
+          />
+          {isAllComplete && !hasSent && (
+            <Button
+              variant="primary"
+              size="small"
+              className="mt-3 w-full"
+              onClick={handleProceed}
+            >
+              Proceed
+            </Button>
+          )}
+        </div>
+      )}
+
+      {expectedInputs.length > 0 && (
+        <div className="rounded-2xl border bg-background p-3">
+          <ContentCardTitle className="text-xs">
+            Expected inputs
+          </ContentCardTitle>
+          <div className="mt-2 grid gap-2">
+            {expectedInputs.map((input) => (
+              <div key={input.name} className="rounded-xl border p-2">
+                <div className="flex items-center justify-between gap-2">
+                  <ContentCardTitle className="text-xs">
+                    {input.title}
+                  </ContentCardTitle>
+                  <ContentBadge>
+                    {input.required ? "Required" : "Optional"}
+                  </ContentBadge>
+                </div>
+                <ContentCardDescription className="mt-1">
+                  {input.name} &bull; {input.type}
+                  {input.description ? ` \u2022 ${input.description}` : ""}
+                </ContentCardDescription>
+              </div>
+            ))}
+          </div>
+        </div>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/helpers.ts
new file mode 100644
index 0000000000..6bb10751f0
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/helpers.ts
@@ -0,0 +1,116 @@
+import type { CredentialField } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
+
+const VALID_CREDENTIAL_TYPES = new Set([
+  "api_key",
+  "oauth2",
+  "user_password",
+  "host_scoped",
+]);
+
+/**
+ * Transforms raw missing_credentials from SetupRequirementsResponse
+ * into CredentialField[] tuples compatible with CredentialsGroupedView.
+ *
+ * Each CredentialField is [key, schema] where schema matches
+ * BlockIOCredentialsSubSchema shape.
+ */
+export function coerceCredentialFields(rawMissingCredentials: unknown): {
+  credentialFields: CredentialField[];
+  requiredCredentials: Set<string>;
+} {
+  const missing =
+    rawMissingCredentials && typeof rawMissingCredentials === "object"
+      ? (rawMissingCredentials as Record<string, unknown>)
+      : {};
+
+  const credentialFields: CredentialField[] = [];
+  const requiredCredentials = new Set<string>();
+
+  Object.entries(missing).forEach(([key, value]) => {
+    if (!value || typeof value !== "object") return;
+    const cred = value as Record<string, unknown>;
+
+    const provider =
+      typeof cred.provider === "string" ? cred.provider.trim() : "";
+    if (!provider) return;
+
+    const types =
+      Array.isArray(cred.types) && cred.types.length > 0
+        ? cred.types
+        : typeof cred.type === "string"
+          ? [cred.type]
+          : [];
+
+    const credentialTypes = types
+      .map((t) => (typeof t === "string" ? t.trim() : ""))
+      .filter((t) => VALID_CREDENTIAL_TYPES.has(t));
+
+    if (credentialTypes.length === 0) return;
+
+    const scopes = Array.isArray(cred.scopes)
+      ? cred.scopes.filter((s): s is string => typeof s === "string")
+      : undefined;
+
+    const schema = {
+      type: "object" as const,
+      properties: {},
+      credentials_provider: [provider],
+      credentials_types: credentialTypes,
+      credentials_scopes: scopes,
+    };
+
+    credentialFields.push([key, schema]);
+    requiredCredentials.add(key);
+  });
+
+  return { credentialFields, requiredCredentials };
+}
+
+export function coerceExpectedInputs(rawInputs: unknown): Array<{
+  name: string;
+  title: string;
+  type: string;
+  description?: string;
+  required: boolean;
+}> {
+  if (!Array.isArray(rawInputs)) return [];
+  const results: Array<{
+    name: string;
+    title: string;
+    type: string;
+    description?: string;
+    required: boolean;
+  }> = [];
+
+  rawInputs.forEach((value, index) => {
+    if (!value || typeof value !== "object") return;
+    const input = value as Record<string, unknown>;
+
+    const name =
+      typeof input.name === "string" && input.name.trim()
+        ? input.name.trim()
+        : `input-${index}`;
+    const title =
+      typeof input.title === "string" && input.title.trim()
+        ? input.title.trim()
+        : name;
+    const type = typeof input.type === "string" ? input.type : "unknown";
+    const description =
+      typeof input.description === "string" && input.description.trim()
+        ? input.description.trim()
+        : undefined;
+    const required = Boolean(input.required);
+
+    const item: {
+      name: string;
+      title: string;
+      type: string;
+      description?: string;
+      required: boolean;
+    } = { name, title, type, required };
+    if (description) item.description = description;
+    results.push(item);
+  });
+
+  return results;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/helpers.tsx
new file mode 100644
index 0000000000..2b75ed9c97
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/helpers.tsx
@@ -0,0 +1,248 @@
+import type { AgentDetailsResponse } from "@/app/api/__generated__/models/agentDetailsResponse";
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import type { ExecutionStartedResponse } from "@/app/api/__generated__/models/executionStartedResponse";
+import type { NeedLoginResponse } from "@/app/api/__generated__/models/needLoginResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
+import {
+  PlayIcon,
+  RocketLaunchIcon,
+  WarningDiamondIcon,
+} from "@phosphor-icons/react";
+import type { ToolUIPart } from "ai";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
+
+export interface RunAgentInput {
+  username_agent_slug?: string;
+  library_agent_id?: string;
+  inputs?: Record<string, unknown>;
+  use_defaults?: boolean;
+  schedule_name?: string;
+  cron?: string;
+  timezone?: string;
+}
+
+export type RunAgentToolOutput =
+  | SetupRequirementsResponse
+  | ExecutionStartedResponse
+  | AgentDetailsResponse
+  | NeedLoginResponse
+  | ErrorResponse;
+
+const RUN_AGENT_OUTPUT_TYPES = new Set<string>([
+  ResponseType.setup_requirements,
+  ResponseType.execution_started,
+  ResponseType.agent_details,
+  ResponseType.need_login,
+  ResponseType.error,
+]);
+
+export function isRunAgentSetupRequirementsOutput(
+  output: RunAgentToolOutput,
+): output is SetupRequirementsResponse {
+  return (
+    output.type === ResponseType.setup_requirements ||
+    ("setup_info" in output && typeof output.setup_info === "object")
+  );
+}
+
+export function isRunAgentExecutionStartedOutput(
+  output: RunAgentToolOutput,
+): output is ExecutionStartedResponse {
+  return (
+    output.type === ResponseType.execution_started || "execution_id" in output
+  );
+}
+
+export function isRunAgentAgentDetailsOutput(
+  output: RunAgentToolOutput,
+): output is AgentDetailsResponse {
+  return output.type === ResponseType.agent_details || "agent" in output;
+}
+
+export function isRunAgentNeedLoginOutput(
+  output: RunAgentToolOutput,
+): output is NeedLoginResponse {
+  return output.type === ResponseType.need_login;
+}
+
+export function isRunAgentErrorOutput(
+  output: RunAgentToolOutput,
+): output is ErrorResponse {
+  return output.type === ResponseType.error || "error" in output;
+}
+
+function parseOutput(output: unknown): RunAgentToolOutput | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (typeof type === "string" && RUN_AGENT_OUTPUT_TYPES.has(type)) {
+      return output as RunAgentToolOutput;
+    }
+    if ("execution_id" in output) return output as ExecutionStartedResponse;
+    if ("setup_info" in output) return output as SetupRequirementsResponse;
+    if ("agent" in output) return output as AgentDetailsResponse;
+    if ("error" in output || "details" in output)
+      return output as ErrorResponse;
+    if (type === ResponseType.need_login) return output as NeedLoginResponse;
+  }
+  return null;
+}
+
+export function getRunAgentToolOutput(
+  part: unknown,
+): RunAgentToolOutput | null {
+  if (!part || typeof part !== "object") return null;
+  return parseOutput((part as { output?: unknown }).output);
+}
+
+function getAgentIdentifierText(
+  input: RunAgentInput | undefined,
+): string | null {
+  if (!input) return null;
+  const slug = input.username_agent_slug?.trim();
+  if (slug) return slug;
+  const libraryId = input.library_agent_id?.trim();
+  if (libraryId) return `Library agent ${libraryId}`;
+  return null;
+}
+
+export function getAnimationText(part: {
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}): string {
+  const input = part.input as RunAgentInput | undefined;
+  const agentIdentifier = getAgentIdentifierText(input);
+  const isSchedule = Boolean(
+    input?.schedule_name?.trim() || input?.cron?.trim(),
+  );
+  const actionPhrase = isSchedule
+    ? "Scheduling the agent to run"
+    : "Running the agent";
+  const identifierText = agentIdentifier ? ` "${agentIdentifier}"` : "";
+
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return `${actionPhrase}${identifierText}`;
+    case "output-available": {
+      const output = parseOutput(part.output);
+      if (!output) return `${actionPhrase}${identifierText}`;
+      if (isRunAgentExecutionStartedOutput(output)) {
+        return `Started "${output.graph_name}"`;
+      }
+      if (isRunAgentAgentDetailsOutput(output)) {
+        return `Agent inputs needed for "${output.agent.name}"`;
+      }
+      if (isRunAgentSetupRequirementsOutput(output)) {
+        return `Setup needed for "${output.setup_info.agent_name}"`;
+      }
+      if (isRunAgentNeedLoginOutput(output))
+        return "Sign in required to run agent";
+      return "Error running agent";
+    }
+    case "output-error":
+      return "Error running agent";
+    default:
+      return actionPhrase;
+  }
+}
+
+export function ToolIcon({
+  isStreaming,
+  isError,
+}: {
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  if (isError) {
+    return (
+      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
+    );
+  }
+  if (isStreaming) {
+    return <OrbitLoader size={24} />;
+  }
+  return <PlayIcon size={14} weight="regular" className="text-neutral-400" />;
+}
+
+export function AccordionIcon() {
+  return <RocketLaunchIcon size={28} weight="light" />;
+}
+
+export function formatMaybeJson(value: unknown): string {
+  if (typeof value === "string") return value;
+  try {
+    return JSON.stringify(value, null, 2);
+  } catch {
+    return String(value);
+  }
+}
+
+export function getAccordionMeta(output: RunAgentToolOutput): {
+  icon: React.ReactNode;
+  title: string;
+  titleClassName?: string;
+  description?: string;
+} {
+  const icon = <AccordionIcon />;
+
+  if (isRunAgentExecutionStartedOutput(output)) {
+    const statusText =
+      typeof output.status === "string" && output.status.trim()
+        ? output.status.trim()
+        : "started";
+    return {
+      icon,
+      title: output.graph_name,
+      description: `Status: ${statusText}`,
+    };
+  }
+
+  if (isRunAgentAgentDetailsOutput(output)) {
+    return {
+      icon,
+      title: output.agent.name,
+      description: "Inputs required",
+    };
+  }
+
+  if (isRunAgentSetupRequirementsOutput(output)) {
+    const missingCredsCount = Object.keys(
+      (output.setup_info.user_readiness?.missing_credentials ?? {}) as Record<
+        string,
+        unknown
+      >,
+    ).length;
+    return {
+      icon,
+      title: output.setup_info.agent_name,
+      description:
+        missingCredsCount > 0
+          ? `Missing ${missingCredsCount} credential${missingCredsCount === 1 ? "" : "s"}`
+          : output.message,
+    };
+  }
+
+  if (isRunAgentNeedLoginOutput(output)) {
+    return { icon, title: "Sign in required" };
+  }
+
+  return {
+    icon: (
+      <WarningDiamondIcon size={28} weight="light" className="text-red-500" />
+    ),
+    title: "Error",
+    titleClassName: "text-red-500",
+  };
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/RunBlock.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/RunBlock.tsx
new file mode 100644
index 0000000000..e1cb030449
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/RunBlock.tsx
@@ -0,0 +1,70 @@
+"use client";
+
+import type { ToolUIPart } from "ai";
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import { BlockOutputCard } from "./components/BlockOutputCard/BlockOutputCard";
+import { ErrorCard } from "./components/ErrorCard/ErrorCard";
+import { SetupRequirementsCard } from "./components/SetupRequirementsCard/SetupRequirementsCard";
+import {
+  getAccordionMeta,
+  getAnimationText,
+  getRunBlockToolOutput,
+  isRunBlockBlockOutput,
+  isRunBlockErrorOutput,
+  isRunBlockSetupRequirementsOutput,
+  ToolIcon,
+} from "./helpers";
+
+export interface RunBlockToolPart {
+  type: string;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}
+
+interface Props {
+  part: RunBlockToolPart;
+}
+
+export function RunBlockTool({ part }: Props) {
+  const text = getAnimationText(part);
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+
+  const output = getRunBlockToolOutput(part);
+  const isError =
+    part.state === "output-error" ||
+    (!!output && isRunBlockErrorOutput(output));
+  const hasExpandableContent =
+    part.state === "output-available" &&
+    !!output &&
+    (isRunBlockBlockOutput(output) ||
+      isRunBlockSetupRequirementsOutput(output) ||
+      isRunBlockErrorOutput(output));
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon isStreaming={isStreaming} isError={isError} />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasExpandableContent && output && (
+        <ToolAccordion {...getAccordionMeta(output)}>
+          {isRunBlockBlockOutput(output) && <BlockOutputCard output={output} />}
+
+          {isRunBlockSetupRequirementsOutput(output) && (
+            <SetupRequirementsCard output={output} />
+          )}
+
+          {isRunBlockErrorOutput(output) && <ErrorCard output={output} />}
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/BlockOutputCard/BlockOutputCard.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/BlockOutputCard/BlockOutputCard.tsx
new file mode 100644
index 0000000000..4051927653
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/BlockOutputCard/BlockOutputCard.tsx
@@ -0,0 +1,133 @@
+"use client";
+
+import React, { useState } from "react";
+import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
+import { Button } from "@/components/atoms/Button/Button";
+import type { BlockOutputResponse } from "@/app/api/__generated__/models/blockOutputResponse";
+import {
+  globalRegistry,
+  OutputItem,
+} from "@/components/contextual/OutputRenderers";
+import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
+import {
+  ContentBadge,
+  ContentCard,
+  ContentCardTitle,
+  ContentGrid,
+  ContentMessage,
+} from "../../../../components/ToolAccordion/AccordionContent";
+
+interface Props {
+  output: BlockOutputResponse;
+}
+
+const COLLAPSED_LIMIT = 3;
+
+function isWorkspaceRef(value: unknown): value is string {
+  return typeof value === "string" && value.startsWith("workspace://");
+}
+
+function resolveForRenderer(value: unknown): {
+  value: unknown;
+  metadata?: OutputMetadata;
+} {
+  if (!isWorkspaceRef(value)) return { value };
+
+  const withoutPrefix = value.replace("workspace://", "");
+  const fileId = withoutPrefix.split("#")[0];
+  const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
+  const url = `/api/proxy${apiPath}`;
+
+  const hashIndex = value.indexOf("#");
+  const mimeHint =
+    hashIndex !== -1 ? value.slice(hashIndex + 1) || undefined : undefined;
+
+  const metadata: OutputMetadata = {};
+  if (mimeHint) {
+    metadata.mimeType = mimeHint;
+    if (mimeHint.startsWith("image/")) metadata.type = "image";
+    else if (mimeHint.startsWith("video/")) metadata.type = "video";
+  }
+
+  return { value: url, metadata };
+}
+
+function RenderOutputValue({ value }: { value: unknown }) {
+  const resolved = resolveForRenderer(value);
+  const renderer = globalRegistry.getRenderer(
+    resolved.value,
+    resolved.metadata,
+  );
+
+  if (renderer) {
+    return (
+      <OutputItem
+        value={resolved.value}
+        metadata={resolved.metadata}
+        renderer={renderer}
+      />
+    );
+  }
+
+  // Fallback for audio workspace refs
+  if (
+    isWorkspaceRef(value) &&
+    resolved.metadata?.mimeType?.startsWith("audio/")
+  ) {
+    return (
+      <audio controls src={String(resolved.value)} className="mt-2 w-full" />
+    );
+  }
+
+  return null;
+}
+
+function OutputKeySection({
+  outputKey,
+  items,
+}: {
+  outputKey: string;
+  items: unknown[];
+}) {
+  const [expanded, setExpanded] = useState(false);
+  const hasMoreItems = items.length > COLLAPSED_LIMIT;
+  const visibleItems = expanded ? items : items.slice(0, COLLAPSED_LIMIT);
+
+  return (
+    <ContentCard>
+      <div className="flex items-center justify-between gap-2">
+        <ContentCardTitle className="text-xs">{outputKey}</ContentCardTitle>
+        <ContentBadge>
+          {items.length} item{items.length === 1 ? "" : "s"}
+        </ContentBadge>
+      </div>
+      <div className="mt-2">
+        {visibleItems.map((item, i) => (
+          <RenderOutputValue key={i} value={item} />
+        ))}
+      </div>
+      {hasMoreItems && (
+        <Button
+          variant="ghost"
+          size="small"
+          className="mt-1 h-auto px-0 py-0.5 text-[11px] text-muted-foreground"
+          onClick={() => setExpanded((prev) => !prev)}
+        >
+          {expanded ? "Show less" : `Show all ${items.length} items`}
+        </Button>
+      )}
+    </ContentCard>
+  );
+}
+
+export function BlockOutputCard({ output }: Props) {
+  return (
+    <ContentGrid>
+      <ContentMessage>{output.message}</ContentMessage>
+
+      {Object.entries(output.outputs ?? {}).map(([key, items]) => (
+        <OutputKeySection key={key} outputKey={key} items={items} />
+      ))}
+    </ContentGrid>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/ErrorCard/ErrorCard.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/ErrorCard/ErrorCard.tsx
new file mode 100644
index 0000000000..7990428947
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/ErrorCard/ErrorCard.tsx
@@ -0,0 +1,27 @@
+"use client";
+
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import {
+  ContentCodeBlock,
+  ContentGrid,
+  ContentMessage,
+} from "../../../../components/ToolAccordion/AccordionContent";
+import { formatMaybeJson } from "../../helpers";
+
+interface Props {
+  output: ErrorResponse;
+}
+
+export function ErrorCard({ output }: Props) {
+  return (
+    <ContentGrid>
+      <ContentMessage>{output.message}</ContentMessage>
+      {output.error && (
+        <ContentCodeBlock>{formatMaybeJson(output.error)}</ContentCodeBlock>
+      )}
+      {output.details && (
+        <ContentCodeBlock>{formatMaybeJson(output.details)}</ContentCodeBlock>
+      )}
+    </ContentGrid>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/SetupRequirementsCard.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/SetupRequirementsCard.tsx
new file mode 100644
index 0000000000..e98fea2850
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/SetupRequirementsCard.tsx
@@ -0,0 +1,197 @@
+"use client";
+
+import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
+import { FormRenderer } from "@/components/renderers/InputRenderer/FormRenderer";
+import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
+import { AnimatePresence, motion } from "framer-motion";
+import { useState } from "react";
+import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
+import {
+  ContentBadge,
+  ContentCardDescription,
+  ContentCardTitle,
+  ContentMessage,
+} from "../../../../components/ToolAccordion/AccordionContent";
+import {
+  buildExpectedInputsSchema,
+  coerceCredentialFields,
+  coerceExpectedInputs,
+} from "./helpers";
+
+interface Props {
+  output: SetupRequirementsResponse;
+}
+
+export function SetupRequirementsCard({ output }: Props) {
+  const { onSend } = useCopilotChatActions();
+
+  const [inputCredentials, setInputCredentials] = useState<
+    Record<string, CredentialsMetaInput | undefined>
+  >({});
+  const [hasSentCredentials, setHasSentCredentials] = useState(false);
+
+  const [showInputForm, setShowInputForm] = useState(false);
+  const [inputValues, setInputValues] = useState<Record<string, unknown>>({});
+
+  const { credentialFields, requiredCredentials } = coerceCredentialFields(
+    output.setup_info.user_readiness?.missing_credentials,
+  );
+
+  const expectedInputs = coerceExpectedInputs(
+    (output.setup_info.requirements as Record<string, unknown>)?.inputs,
+  );
+
+  const inputSchema = buildExpectedInputsSchema(expectedInputs);
+
+  function handleCredentialChange(key: string, value?: CredentialsMetaInput) {
+    setInputCredentials((prev) => ({ ...prev, [key]: value }));
+  }
+
+  const isAllCredentialsComplete =
+    credentialFields.length > 0 &&
+    [...requiredCredentials].every((key) => !!inputCredentials[key]);
+
+  function handleProceedCredentials() {
+    setHasSentCredentials(true);
+    onSend(
+      "I've configured the required credentials. Please re-run the block now.",
+    );
+  }
+
+  function handleRunWithInputs() {
+    const nonEmpty = Object.fromEntries(
+      Object.entries(inputValues).filter(
+        ([, v]) => v !== undefined && v !== null && v !== "",
+      ),
+    );
+    onSend(
+      `Run the block with these inputs: ${JSON.stringify(nonEmpty, null, 2)}`,
+    );
+    setShowInputForm(false);
+    setInputValues({});
+  }
+
+  return (
+    <div className="grid gap-2">
+      <ContentMessage>{output.message}</ContentMessage>
+
+      {credentialFields.length > 0 && (
+        <div className="rounded-2xl border bg-background p-3">
+          <CredentialsGroupedView
+            credentialFields={credentialFields}
+            requiredCredentials={requiredCredentials}
+            inputCredentials={inputCredentials}
+            inputValues={{}}
+            onCredentialChange={handleCredentialChange}
+          />
+          {isAllCredentialsComplete && !hasSentCredentials && (
+            <Button
+              variant="primary"
+              size="small"
+              className="mt-3 w-full"
+              onClick={handleProceedCredentials}
+            >
+              Proceed
+            </Button>
+          )}
+        </div>
+      )}
+
+      {inputSchema && (
+        <div className="flex gap-2 pt-2">
+          <Button
+            variant="outline"
+            size="small"
+            className="w-fit"
+            onClick={() => setShowInputForm((prev) => !prev)}
+          >
+            {showInputForm ? "Hide inputs" : "Fill in inputs"}
+          </Button>
+        </div>
+      )}
+
+      <AnimatePresence initial={false}>
+        {showInputForm && inputSchema && (
+          <motion.div
+            initial={{ height: 0, opacity: 0, filter: "blur(6px)" }}
+            animate={{ height: "auto", opacity: 1, filter: "blur(0px)" }}
+            exit={{ height: 0, opacity: 0, filter: "blur(6px)" }}
+            transition={{
+              height: { type: "spring", bounce: 0.15, duration: 0.5 },
+              opacity: { duration: 0.25 },
+              filter: { duration: 0.2 },
+            }}
+            className="overflow-hidden"
+            style={{ willChange: "height, opacity, filter" }}
+          >
+            <div className="rounded-2xl border bg-background p-3 pt-4">
+              <Text variant="body-medium">Block inputs</Text>
+              <FormRenderer
+                jsonSchema={inputSchema}
+                handleChange={(v) => setInputValues(v.formData ?? {})}
+                uiSchema={{
+                  "ui:submitButtonOptions": { norender: true },
+                }}
+                initialValues={inputValues}
+                formContext={{
+                  showHandles: false,
+                  size: "small",
+                }}
+              />
+              <div className="-mt-8 flex gap-2">
+                <Button
+                  variant="primary"
+                  size="small"
+                  className="w-fit"
+                  onClick={handleRunWithInputs}
+                >
+                  Run
+                </Button>
+                <Button
+                  variant="secondary"
+                  size="small"
+                  className="w-fit"
+                  onClick={() => {
+                    setShowInputForm(false);
+                    setInputValues({});
+                  }}
+                >
+                  Cancel
+                </Button>
+              </div>
+            </div>
+          </motion.div>
+        )}
+      </AnimatePresence>
+
+      {expectedInputs.length > 0 && !inputSchema && (
+        <div className="rounded-2xl border bg-background p-3">
+          <ContentCardTitle className="text-xs">
+            Expected inputs
+          </ContentCardTitle>
+          <div className="mt-2 grid gap-2">
+            {expectedInputs.map((input) => (
+              <div key={input.name} className="rounded-xl border p-2">
+                <div className="flex items-center justify-between gap-2">
+                  <ContentCardTitle className="text-xs">
+                    {input.title}
+                  </ContentCardTitle>
+                  <ContentBadge>
+                    {input.required ? "Required" : "Optional"}
+                  </ContentBadge>
+                </div>
+                <ContentCardDescription className="mt-1">
+                  {input.name} &bull; {input.type}
+                  {input.description ? ` \u2022 ${input.description}` : ""}
+                </ContentCardDescription>
+              </div>
+            ))}
+          </div>
+        </div>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/helpers.ts
new file mode 100644
index 0000000000..bacc0bac55
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/helpers.ts
@@ -0,0 +1,156 @@
+import type { CredentialField } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/helpers";
+import type { RJSFSchema } from "@rjsf/utils";
+
+const VALID_CREDENTIAL_TYPES = new Set([
+  "api_key",
+  "oauth2",
+  "user_password",
+  "host_scoped",
+]);
+
+export function coerceCredentialFields(rawMissingCredentials: unknown): {
+  credentialFields: CredentialField[];
+  requiredCredentials: Set<string>;
+} {
+  const missing =
+    rawMissingCredentials && typeof rawMissingCredentials === "object"
+      ? (rawMissingCredentials as Record<string, unknown>)
+      : {};
+
+  const credentialFields: CredentialField[] = [];
+  const requiredCredentials = new Set<string>();
+
+  Object.entries(missing).forEach(([key, value]) => {
+    if (!value || typeof value !== "object") return;
+    const cred = value as Record<string, unknown>;
+
+    const provider =
+      typeof cred.provider === "string" ? cred.provider.trim() : "";
+    if (!provider) return;
+
+    const types =
+      Array.isArray(cred.types) && cred.types.length > 0
+        ? cred.types
+        : typeof cred.type === "string"
+          ? [cred.type]
+          : [];
+
+    const credentialTypes = types
+      .map((t) => (typeof t === "string" ? t.trim() : ""))
+      .filter((t) => VALID_CREDENTIAL_TYPES.has(t));
+
+    if (credentialTypes.length === 0) return;
+
+    const scopes = Array.isArray(cred.scopes)
+      ? cred.scopes.filter((s): s is string => typeof s === "string")
+      : undefined;
+
+    const schema = {
+      type: "object" as const,
+      properties: {},
+      credentials_provider: [provider],
+      credentials_types: credentialTypes,
+      credentials_scopes: scopes,
+    };
+
+    credentialFields.push([key, schema]);
+    requiredCredentials.add(key);
+  });
+
+  return { credentialFields, requiredCredentials };
+}
+
+export function coerceExpectedInputs(rawInputs: unknown): Array<{
+  name: string;
+  title: string;
+  type: string;
+  description?: string;
+  required: boolean;
+}> {
+  if (!Array.isArray(rawInputs)) return [];
+  const results: Array<{
+    name: string;
+    title: string;
+    type: string;
+    description?: string;
+    required: boolean;
+  }> = [];
+
+  rawInputs.forEach((value, index) => {
+    if (!value || typeof value !== "object") return;
+    const input = value as Record<string, unknown>;
+
+    const name =
+      typeof input.name === "string" && input.name.trim()
+        ? input.name.trim()
+        : `input-${index}`;
+    const title =
+      typeof input.title === "string" && input.title.trim()
+        ? input.title.trim()
+        : name;
+    const type = typeof input.type === "string" ? input.type : "unknown";
+    const description =
+      typeof input.description === "string" && input.description.trim()
+        ? input.description.trim()
+        : undefined;
+    const required = Boolean(input.required);
+
+    const item: {
+      name: string;
+      title: string;
+      type: string;
+      description?: string;
+      required: boolean;
+    } = { name, title, type, required };
+    if (description) item.description = description;
+    results.push(item);
+  });
+
+  return results;
+}
+
+/**
+ * Build an RJSF schema from expected inputs so they can be rendered
+ * as a dynamic form via FormRenderer.
+ */
+export function buildExpectedInputsSchema(
+  expectedInputs: Array<{
+    name: string;
+    title: string;
+    type: string;
+    description?: string;
+    required: boolean;
+  }>,
+): RJSFSchema | null {
+  if (expectedInputs.length === 0) return null;
+
+  const TYPE_MAP: Record<string, string> = {
+    string: "string",
+    str: "string",
+    text: "string",
+    number: "number",
+    int: "integer",
+    integer: "integer",
+    float: "number",
+    boolean: "boolean",
+    bool: "boolean",
+  };
+
+  const properties: Record<string, Record<string, unknown>> = {};
+  const required: string[] = [];
+
+  for (const input of expectedInputs) {
+    properties[input.name] = {
+      type: TYPE_MAP[input.type.toLowerCase()] ?? "string",
+      title: input.title,
+      ...(input.description ? { description: input.description } : {}),
+    };
+    if (input.required) required.push(input.name);
+  }
+
+  return {
+    type: "object",
+    properties,
+    ...(required.length > 0 ? { required } : {}),
+  };
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/helpers.tsx
new file mode 100644
index 0000000000..b8625988cd
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/helpers.tsx
@@ -0,0 +1,185 @@
+import type { BlockOutputResponse } from "@/app/api/__generated__/models/blockOutputResponse";
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
+import {
+  PlayCircleIcon,
+  PlayIcon,
+  WarningDiamondIcon,
+} from "@phosphor-icons/react";
+import type { ToolUIPart } from "ai";
+import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
+
+export interface RunBlockInput {
+  block_id?: string;
+  input_data?: Record<string, unknown>;
+}
+
+export type RunBlockToolOutput =
+  | SetupRequirementsResponse
+  | BlockOutputResponse
+  | ErrorResponse;
+
+const RUN_BLOCK_OUTPUT_TYPES = new Set<string>([
+  ResponseType.setup_requirements,
+  ResponseType.block_output,
+  ResponseType.error,
+]);
+
+export function isRunBlockSetupRequirementsOutput(
+  output: RunBlockToolOutput,
+): output is SetupRequirementsResponse {
+  return (
+    output.type === ResponseType.setup_requirements ||
+    ("setup_info" in output && typeof output.setup_info === "object")
+  );
+}
+
+export function isRunBlockBlockOutput(
+  output: RunBlockToolOutput,
+): output is BlockOutputResponse {
+  return output.type === ResponseType.block_output || "block_id" in output;
+}
+
+export function isRunBlockErrorOutput(
+  output: RunBlockToolOutput,
+): output is ErrorResponse {
+  return output.type === ResponseType.error || "error" in output;
+}
+
+function parseOutput(output: unknown): RunBlockToolOutput | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (typeof type === "string" && RUN_BLOCK_OUTPUT_TYPES.has(type)) {
+      return output as RunBlockToolOutput;
+    }
+    if ("block_id" in output) return output as BlockOutputResponse;
+    if ("setup_info" in output) return output as SetupRequirementsResponse;
+    if ("error" in output || "details" in output)
+      return output as ErrorResponse;
+  }
+  return null;
+}
+
+export function getRunBlockToolOutput(
+  part: unknown,
+): RunBlockToolOutput | null {
+  if (!part || typeof part !== "object") return null;
+  return parseOutput((part as { output?: unknown }).output);
+}
+
+export function getAnimationText(part: {
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}): string {
+  const input = part.input as RunBlockInput | undefined;
+  const blockId = input?.block_id?.trim();
+  const blockText = blockId ? ` "${blockId}"` : "";
+
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return `Running the block${blockText}`;
+    case "output-available": {
+      const output = parseOutput(part.output);
+      if (!output) return `Running the block${blockText}`;
+      if (isRunBlockBlockOutput(output)) return `Ran "${output.block_name}"`;
+      if (isRunBlockSetupRequirementsOutput(output)) {
+        return `Setup needed for "${output.setup_info.agent_name}"`;
+      }
+      return "Error running block";
+    }
+    case "output-error":
+      return "Error running block";
+    default:
+      return "Running the block";
+  }
+}
+
+export function ToolIcon({
+  isStreaming,
+  isError,
+}: {
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  if (isError) {
+    return (
+      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
+    );
+  }
+  if (isStreaming) {
+    return <OrbitLoader size={24} />;
+  }
+  return <PlayIcon size={14} weight="regular" className="text-neutral-400" />;
+}
+
+export function AccordionIcon() {
+  return <PlayCircleIcon size={32} weight="light" />;
+}
+
+export function formatMaybeJson(value: unknown): string {
+  if (typeof value === "string") return value;
+  try {
+    return JSON.stringify(value, null, 2);
+  } catch {
+    return String(value);
+  }
+}
+
+export function getAccordionMeta(output: RunBlockToolOutput): {
+  icon: React.ReactNode;
+  title: string;
+  titleClassName?: string;
+  description?: string;
+} {
+  const icon = <AccordionIcon />;
+
+  if (isRunBlockBlockOutput(output)) {
+    const keys = Object.keys(output.outputs ?? {});
+    return {
+      icon,
+      title: output.block_name,
+      description:
+        keys.length > 0
+          ? `${keys.length} output key${keys.length === 1 ? "" : "s"}`
+          : output.message,
+    };
+  }
+
+  if (isRunBlockSetupRequirementsOutput(output)) {
+    const missingCredsCount = Object.keys(
+      (output.setup_info.user_readiness?.missing_credentials ?? {}) as Record<
+        string,
+        unknown
+      >,
+    ).length;
+    return {
+      icon,
+      title: output.setup_info.agent_name,
+      description:
+        missingCredsCount > 0
+          ? `Missing ${missingCredsCount} credential${missingCredsCount === 1 ? "" : "s"}`
+          : output.message,
+    };
+  }
+
+  return {
+    icon: (
+      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
+    ),
+    title: "Error",
+    titleClassName: "text-red-500",
+  };
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/SearchDocs/SearchDocs.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/SearchDocs/SearchDocs.tsx
new file mode 100644
index 0000000000..d3fb793d14
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/SearchDocs/SearchDocs.tsx
@@ -0,0 +1,186 @@
+"use client";
+
+import type { ToolUIPart } from "ai";
+import { useMemo } from "react";
+
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import {
+  ContentCard,
+  ContentCardDescription,
+  ContentCardHeader,
+  ContentCardSubtitle,
+  ContentCardTitle,
+  ContentGrid,
+  ContentLink,
+  ContentMessage,
+  ContentSuggestionsList,
+} from "../../components/ToolAccordion/AccordionContent";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import {
+  AccordionIcon,
+  getAnimationText,
+  getDocsToolOutput,
+  getDocsToolTitle,
+  getToolLabel,
+  isDocPageOutput,
+  isDocSearchResultsOutput,
+  isErrorOutput,
+  isNoResultsOutput,
+  toDocsUrl,
+  ToolIcon,
+  type DocsToolType,
+} from "./helpers";
+
+export interface DocsToolPart {
+  type: DocsToolType;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}
+
+interface Props {
+  part: DocsToolPart;
+}
+
+function truncate(text: string, maxChars: number): string {
+  const trimmed = text.trim();
+  if (trimmed.length <= maxChars) return trimmed;
+  return `${trimmed.slice(0, maxChars).trimEnd()}…`;
+}
+
+export function SearchDocsTool({ part }: Props) {
+  const output = getDocsToolOutput(part);
+  const text = getAnimationText(part);
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+  const isError =
+    part.state === "output-error" || (!!output && isErrorOutput(output));
+
+  const normalized = useMemo(() => {
+    if (!output) return null;
+    const title = getDocsToolTitle(part.type, output);
+    const label = getToolLabel(part.type);
+    return { title, label };
+  }, [output, part.type]);
+
+  const isOutputAvailable = part.state === "output-available" && !!output;
+
+  const docSearchOutput =
+    isOutputAvailable && output && isDocSearchResultsOutput(output)
+      ? output
+      : null;
+  const docPageOutput =
+    isOutputAvailable && output && isDocPageOutput(output) ? output : null;
+  const noResultsOutput =
+    isOutputAvailable && output && isNoResultsOutput(output) ? output : null;
+  const errorOutput =
+    isOutputAvailable && output && isErrorOutput(output) ? output : null;
+
+  const hasExpandableContent =
+    isOutputAvailable &&
+    ((!!docSearchOutput && docSearchOutput.count > 0) ||
+      !!docPageOutput ||
+      !!noResultsOutput ||
+      !!errorOutput);
+
+  const accordionDescription =
+    hasExpandableContent && docSearchOutput
+      ? `Found ${docSearchOutput.count} result${docSearchOutput.count === 1 ? "" : "s"} for "${docSearchOutput.query}"`
+      : hasExpandableContent && docPageOutput
+        ? docPageOutput.path
+        : hasExpandableContent && (noResultsOutput || errorOutput)
+          ? ((noResultsOutput ?? errorOutput)?.message ?? null)
+          : null;
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon
+          toolType={part.type}
+          isStreaming={isStreaming}
+          isError={isError}
+        />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasExpandableContent && normalized && (
+        <ToolAccordion
+          icon={<AccordionIcon toolType={part.type} />}
+          title={normalized.title}
+          description={accordionDescription}
+        >
+          {docSearchOutput && (
+            <ContentGrid>
+              {docSearchOutput.results.map((r) => {
+                const href = r.doc_url ?? toDocsUrl(r.path);
+                return (
+                  <ContentCard key={r.path}>
+                    <ContentCardHeader
+                      action={<ContentLink href={href}>Open</ContentLink>}
+                    >
+                      <ContentCardTitle>{r.title}</ContentCardTitle>
+                      <ContentCardSubtitle>
+                        {r.path}
+                        {r.section ? ` • ${r.section}` : ""}
+                      </ContentCardSubtitle>
+                      <ContentCardDescription>
+                        {truncate(r.snippet, 240)}
+                      </ContentCardDescription>
+                    </ContentCardHeader>
+                  </ContentCard>
+                );
+              })}
+            </ContentGrid>
+          )}
+
+          {docPageOutput && (
+            <div>
+              <ContentCardHeader
+                action={
+                  <ContentLink
+                    href={
+                      docPageOutput.doc_url ?? toDocsUrl(docPageOutput.path)
+                    }
+                  >
+                    Open
+                  </ContentLink>
+                }
+              >
+                <ContentCardTitle>{docPageOutput.title}</ContentCardTitle>
+                <ContentCardSubtitle>{docPageOutput.path}</ContentCardSubtitle>
+              </ContentCardHeader>
+              <ContentCardDescription className="whitespace-pre-wrap">
+                {truncate(docPageOutput.content, 800)}
+              </ContentCardDescription>
+            </div>
+          )}
+
+          {noResultsOutput && (
+            <div>
+              <ContentMessage>{noResultsOutput.message}</ContentMessage>
+              {noResultsOutput.suggestions &&
+                noResultsOutput.suggestions.length > 0 && (
+                  <ContentSuggestionsList items={noResultsOutput.suggestions} />
+                )}
+            </div>
+          )}
+
+          {errorOutput && (
+            <div>
+              <ContentMessage>{errorOutput.message}</ContentMessage>
+              {errorOutput.error && (
+                <ContentCardDescription>
+                  {errorOutput.error}
+                </ContentCardDescription>
+              )}
+            </div>
+          )}
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/SearchDocs/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/SearchDocs/helpers.tsx
new file mode 100644
index 0000000000..50a84edceb
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/SearchDocs/helpers.tsx
@@ -0,0 +1,215 @@
+import type { DocPageResponse } from "@/app/api/__generated__/models/docPageResponse";
+import type { DocSearchResultsResponse } from "@/app/api/__generated__/models/docSearchResultsResponse";
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import type { NoResultsResponse } from "@/app/api/__generated__/models/noResultsResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import {
+  ArticleIcon,
+  FileMagnifyingGlassIcon,
+  FileTextIcon,
+} from "@phosphor-icons/react";
+import { ToolUIPart } from "ai";
+
+export interface SearchDocsInput {
+  query: string;
+}
+
+export interface GetDocPageInput {
+  path: string;
+}
+
+export type DocsToolOutput =
+  | DocSearchResultsResponse
+  | DocPageResponse
+  | NoResultsResponse
+  | ErrorResponse;
+
+export type DocsToolType = "tool-search_docs" | "tool-get_doc_page" | string;
+
+export function getToolLabel(toolType: DocsToolType): string {
+  switch (toolType) {
+    case "tool-search_docs":
+      return "Docs";
+    case "tool-get_doc_page":
+      return "Docs page";
+    default:
+      return "Docs";
+  }
+}
+
+function parseOutput(output: unknown): DocsToolOutput | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (
+      type === ResponseType.doc_search_results ||
+      type === ResponseType.doc_page ||
+      type === ResponseType.no_results ||
+      type === ResponseType.error
+    ) {
+      return output as DocsToolOutput;
+    }
+    if ("results" in output && "query" in output)
+      return output as DocSearchResultsResponse;
+    if ("content" in output && "path" in output)
+      return output as DocPageResponse;
+    if ("suggestions" in output && !("error" in output))
+      return output as NoResultsResponse;
+    if ("error" in output || "details" in output)
+      return output as ErrorResponse;
+  }
+  return null;
+}
+
+export function getDocsToolOutput(part: unknown): DocsToolOutput | null {
+  if (!part || typeof part !== "object") return null;
+  return parseOutput((part as { output?: unknown }).output);
+}
+
+export function isDocSearchResultsOutput(
+  output: DocsToolOutput,
+): output is DocSearchResultsResponse {
+  return output.type === ResponseType.doc_search_results || "results" in output;
+}
+
+export function isDocPageOutput(
+  output: DocsToolOutput,
+): output is DocPageResponse {
+  return output.type === ResponseType.doc_page || "content" in output;
+}
+
+export function isNoResultsOutput(
+  output: DocsToolOutput,
+): output is NoResultsResponse {
+  return (
+    output.type === ResponseType.no_results ||
+    ("suggestions" in output && !("error" in output))
+  );
+}
+
+export function isErrorOutput(output: DocsToolOutput): output is ErrorResponse {
+  return output.type === ResponseType.error || "error" in output;
+}
+
+export function getDocsToolTitle(
+  toolType: DocsToolType,
+  output: DocsToolOutput,
+): string {
+  if (toolType === "tool-search_docs") {
+    if (isDocSearchResultsOutput(output)) return "Documentation results";
+    if (isNoResultsOutput(output)) return "No documentation found";
+    return "Documentation search error";
+  }
+
+  if (isDocPageOutput(output)) return "Documentation page";
+  if (isNoResultsOutput(output)) return "No documentation found";
+  return "Documentation page error";
+}
+
+export function getAnimationText(part: {
+  type: DocsToolType;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}): string {
+  switch (part.type) {
+    case "tool-search_docs": {
+      const query = (part.input as SearchDocsInput | undefined)?.query?.trim();
+      const queryText = query ? ` for "${query}"` : "";
+
+      switch (part.state) {
+        case "input-streaming":
+        case "input-available":
+          return `Searching documentation${queryText}`;
+        case "output-available": {
+          const output = parseOutput(part.output);
+          if (!output) return `Searching documentation${queryText}`;
+          if (isDocSearchResultsOutput(output)) {
+            const count = output.count ?? output.results.length;
+            return `Found ${count} result${count === 1 ? "" : "s"}${queryText}`;
+          }
+          if (isNoResultsOutput(output)) {
+            return `No results found${queryText}`;
+          }
+          return `Error searching documentation${queryText}`;
+        }
+        case "output-error":
+          return `Error searching documentation${queryText}`;
+        default:
+          return "Searching documentation";
+      }
+    }
+    case "tool-get_doc_page": {
+      const path = (part.input as GetDocPageInput | undefined)?.path?.trim();
+      const pathText = path ? ` "${path}"` : "";
+
+      switch (part.state) {
+        case "input-streaming":
+        case "input-available":
+          return `Loading documentation page${pathText}`;
+        case "output-available": {
+          const output = parseOutput(part.output);
+          if (!output) return `Loading documentation page${pathText}`;
+          if (isDocPageOutput(output)) return `Loaded "${output.title}"`;
+          if (isNoResultsOutput(output)) return "Documentation page not found";
+          return "Error loading documentation page";
+        }
+        case "output-error":
+          return "Error loading documentation page";
+        default:
+          return "Loading documentation page";
+      }
+    }
+  }
+
+  return "Processing";
+}
+
+export function ToolIcon({
+  toolType,
+  isStreaming,
+  isError,
+}: {
+  toolType: DocsToolType;
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  const IconComponent =
+    toolType === "tool-get_doc_page" ? FileTextIcon : FileMagnifyingGlassIcon;
+
+  return (
+    <IconComponent
+      size={14}
+      weight="regular"
+      className={
+        isError
+          ? "text-red-500"
+          : isStreaming
+            ? "text-neutral-500"
+            : "text-neutral-400"
+      }
+    />
+  );
+}
+
+export function AccordionIcon({ toolType }: { toolType: DocsToolType }) {
+  const IconComponent =
+    toolType === "tool-get_doc_page" ? ArticleIcon : FileTextIcon;
+  return <IconComponent size={32} weight="light" />;
+}
+
+export function toDocsUrl(path: string): string {
+  const urlPath = path.includes(".")
+    ? path.slice(0, path.lastIndexOf("."))
+    : path;
+  return `https://docs.agpt.co/${urlPath}`;
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/ViewAgentOutput/ViewAgentOutput.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/ViewAgentOutput/ViewAgentOutput.tsx
new file mode 100644
index 0000000000..e7265ac7cb
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/ViewAgentOutput/ViewAgentOutput.tsx
@@ -0,0 +1,261 @@
+"use client";
+
+import type { ToolUIPart } from "ai";
+import React from "react";
+import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
+import {
+  globalRegistry,
+  OutputItem,
+} from "@/components/contextual/OutputRenderers";
+import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
+import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
+import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import {
+  ContentBadge,
+  ContentCard,
+  ContentCardHeader,
+  ContentCardSubtitle,
+  ContentCardTitle,
+  ContentCodeBlock,
+  ContentGrid,
+  ContentLink,
+  ContentMessage,
+  ContentSuggestionsList,
+} from "../../components/ToolAccordion/AccordionContent";
+import {
+  formatMaybeJson,
+  getAnimationText,
+  getViewAgentOutputToolOutput,
+  isAgentOutputResponse,
+  isErrorResponse,
+  isNoResultsResponse,
+  AccordionIcon,
+  ToolIcon,
+  type ViewAgentOutputToolOutput,
+} from "./helpers";
+
+export interface ViewAgentOutputToolPart {
+  type: string;
+  toolCallId: string;
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}
+
+interface Props {
+  part: ViewAgentOutputToolPart;
+}
+
+function isWorkspaceRef(value: unknown): value is string {
+  return typeof value === "string" && value.startsWith("workspace://");
+}
+
+function resolveForRenderer(value: unknown): {
+  value: unknown;
+  metadata?: OutputMetadata;
+} {
+  if (!isWorkspaceRef(value)) return { value };
+
+  const withoutPrefix = value.replace("workspace://", "");
+  const fileId = withoutPrefix.split("#")[0];
+  const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
+  const url = `/api/proxy${apiPath}`;
+
+  const hashIndex = value.indexOf("#");
+  const mimeHint =
+    hashIndex !== -1 ? value.slice(hashIndex + 1) || undefined : undefined;
+
+  const metadata: OutputMetadata = {};
+  if (mimeHint) {
+    metadata.mimeType = mimeHint;
+    if (mimeHint.startsWith("image/")) metadata.type = "image";
+    else if (mimeHint.startsWith("video/")) metadata.type = "video";
+  }
+
+  return { value: url, metadata };
+}
+
+function RenderOutputValue({ value }: { value: unknown }) {
+  const resolved = resolveForRenderer(value);
+  const renderer = globalRegistry.getRenderer(
+    resolved.value,
+    resolved.metadata,
+  );
+
+  if (renderer) {
+    return (
+      <OutputItem
+        value={resolved.value}
+        metadata={resolved.metadata}
+        renderer={renderer}
+      />
+    );
+  }
+
+  // Fallback for audio workspace refs
+  if (
+    isWorkspaceRef(value) &&
+    resolved.metadata?.mimeType?.startsWith("audio/")
+  ) {
+    return (
+      <audio controls src={String(resolved.value)} className="mt-2 w-full" />
+    );
+  }
+
+  return null;
+}
+
+function getAccordionMeta(output: ViewAgentOutputToolOutput): {
+  icon: React.ReactNode;
+  title: string;
+  description?: string;
+} {
+  const icon = <AccordionIcon />;
+
+  if (isAgentOutputResponse(output)) {
+    const status = output.execution?.status;
+    return {
+      icon,
+      title: output.agent_name,
+      description: status ? `Status: ${status}` : output.message,
+    };
+  }
+  if (isNoResultsResponse(output)) {
+    return { icon, title: "No results" };
+  }
+  return { icon, title: "Error" };
+}
+
+export function ViewAgentOutputTool({ part }: Props) {
+  const text = getAnimationText(part);
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+
+  const output = getViewAgentOutputToolOutput(part);
+  const isError =
+    part.state === "output-error" || (!!output && isErrorResponse(output));
+  const hasExpandableContent =
+    part.state === "output-available" &&
+    !!output &&
+    (isAgentOutputResponse(output) ||
+      isNoResultsResponse(output) ||
+      isErrorResponse(output));
+
+  return (
+    <div className="py-2">
+      <div className="flex items-center gap-2 text-sm text-muted-foreground">
+        <ToolIcon isStreaming={isStreaming} isError={isError} />
+        <MorphingTextAnimation
+          text={text}
+          className={isError ? "text-red-500" : undefined}
+        />
+      </div>
+
+      {hasExpandableContent && output && (
+        <ToolAccordion {...getAccordionMeta(output)}>
+          {isAgentOutputResponse(output) && (
+            <ContentGrid>
+              <ContentCardHeader
+                className="gap-3"
+                action={
+                  output.library_agent_link ? (
+                    <ContentLink href={output.library_agent_link}>
+                      Open
+                    </ContentLink>
+                  ) : null
+                }
+              >
+                <ContentMessage>{output.message}</ContentMessage>
+              </ContentCardHeader>
+
+              {output.execution ? (
+                <ContentGrid>
+                  <ContentCard>
+                    <ContentCardTitle className="text-xs">
+                      Execution
+                    </ContentCardTitle>
+                    <ContentCardSubtitle className="mt-1">
+                      {output.execution.execution_id}
+                    </ContentCardSubtitle>
+                    <ContentCardSubtitle className="mt-1">
+                      Status: {output.execution.status}
+                    </ContentCardSubtitle>
+                  </ContentCard>
+
+                  {output.execution.inputs_summary && (
+                    <ContentCard>
+                      <ContentCardTitle className="text-xs">
+                        Inputs summary
+                      </ContentCardTitle>
+                      <div className="mt-2">
+                        <RenderOutputValue
+                          value={output.execution.inputs_summary}
+                        />
+                      </div>
+                    </ContentCard>
+                  )}
+
+                  {Object.entries(output.execution.outputs ?? {}).map(
+                    ([key, items]) => (
+                      <ContentCard key={key}>
+                        <div className="flex items-center justify-between gap-2">
+                          <ContentCardTitle className="text-xs">
+                            {key}
+                          </ContentCardTitle>
+                          <ContentBadge>
+                            {items.length} item
+                            {items.length === 1 ? "" : "s"}
+                          </ContentBadge>
+                        </div>
+                        <div className="mt-2">
+                          {items.slice(0, 3).map((item, i) => (
+                            <RenderOutputValue key={i} value={item} />
+                          ))}
+                        </div>
+                      </ContentCard>
+                    ),
+                  )}
+                </ContentGrid>
+              ) : (
+                <ContentCard>
+                  <ContentMessage>No execution selected.</ContentMessage>
+                  <ContentCardSubtitle className="mt-1">
+                    Try asking for a specific run or execution_id.
+                  </ContentCardSubtitle>
+                </ContentCard>
+              )}
+            </ContentGrid>
+          )}
+
+          {isNoResultsResponse(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              {output.suggestions && output.suggestions.length > 0 && (
+                <ContentSuggestionsList
+                  items={output.suggestions}
+                  className="mt-1"
+                />
+              )}
+            </ContentGrid>
+          )}
+
+          {isErrorResponse(output) && (
+            <ContentGrid>
+              <ContentMessage>{output.message}</ContentMessage>
+              {output.error && (
+                <ContentCodeBlock>
+                  {formatMaybeJson(output.error)}
+                </ContentCodeBlock>
+              )}
+              {output.details && (
+                <ContentCodeBlock>
+                  {formatMaybeJson(output.details)}
+                </ContentCodeBlock>
+              )}
+            </ContentGrid>
+          )}
+        </ToolAccordion>
+      )}
+    </div>
+  );
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/ViewAgentOutput/helpers.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/ViewAgentOutput/helpers.tsx
new file mode 100644
index 0000000000..1ff2e64ec7
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/ViewAgentOutput/helpers.tsx
@@ -0,0 +1,158 @@
+import type { AgentOutputResponse } from "@/app/api/__generated__/models/agentOutputResponse";
+import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
+import type { NoResultsResponse } from "@/app/api/__generated__/models/noResultsResponse";
+import { ResponseType } from "@/app/api/__generated__/models/responseType";
+import { EyeIcon, MonitorIcon } from "@phosphor-icons/react";
+import type { ToolUIPart } from "ai";
+
+export interface ViewAgentOutputInput {
+  agent_name?: string;
+  library_agent_id?: string;
+  store_slug?: string;
+  execution_id?: string;
+  run_time?: string;
+}
+
+export type ViewAgentOutputToolOutput =
+  | AgentOutputResponse
+  | NoResultsResponse
+  | ErrorResponse;
+
+function parseOutput(output: unknown): ViewAgentOutputToolOutput | null {
+  if (!output) return null;
+  if (typeof output === "string") {
+    const trimmed = output.trim();
+    if (!trimmed) return null;
+    try {
+      return parseOutput(JSON.parse(trimmed) as unknown);
+    } catch {
+      return null;
+    }
+  }
+  if (typeof output === "object") {
+    const type = (output as { type?: unknown }).type;
+    if (
+      type === ResponseType.agent_output ||
+      type === ResponseType.no_results ||
+      type === ResponseType.error
+    ) {
+      return output as ViewAgentOutputToolOutput;
+    }
+    if ("agent_id" in output && "agent_name" in output) {
+      return output as AgentOutputResponse;
+    }
+    if ("suggestions" in output && !("error" in output)) {
+      return output as NoResultsResponse;
+    }
+    if ("error" in output || "details" in output)
+      return output as ErrorResponse;
+  }
+  return null;
+}
+
+export function isAgentOutputResponse(
+  output: ViewAgentOutputToolOutput,
+): output is AgentOutputResponse {
+  return output.type === ResponseType.agent_output || "agent_id" in output;
+}
+
+export function isNoResultsResponse(
+  output: ViewAgentOutputToolOutput,
+): output is NoResultsResponse {
+  return (
+    output.type === ResponseType.no_results ||
+    ("suggestions" in output && !("error" in output))
+  );
+}
+
+export function isErrorResponse(
+  output: ViewAgentOutputToolOutput,
+): output is ErrorResponse {
+  return output.type === ResponseType.error || "error" in output;
+}
+
+export function getViewAgentOutputToolOutput(
+  part: unknown,
+): ViewAgentOutputToolOutput | null {
+  if (!part || typeof part !== "object") return null;
+  return parseOutput((part as { output?: unknown }).output);
+}
+
+function getAgentIdentifierText(
+  input: ViewAgentOutputInput | undefined,
+): string | null {
+  if (!input) return null;
+  const libraryId = input.library_agent_id?.trim();
+  if (libraryId) return `Library agent ${libraryId}`;
+  const slug = input.store_slug?.trim();
+  if (slug) return slug;
+  const name = input.agent_name?.trim();
+  if (name) return name;
+  return null;
+}
+
+export function getAnimationText(part: {
+  state: ToolUIPart["state"];
+  input?: unknown;
+  output?: unknown;
+}): string {
+  const input = part.input as ViewAgentOutputInput | undefined;
+  const agent = getAgentIdentifierText(input);
+  const agentText = agent ? ` "${agent}"` : "";
+
+  switch (part.state) {
+    case "input-streaming":
+    case "input-available":
+      return `Retrieving agent output${agentText}`;
+    case "output-available": {
+      const output = parseOutput(part.output);
+      if (!output) return `Retrieving agent output${agentText}`;
+      if (isAgentOutputResponse(output)) {
+        if (output.execution)
+          return `Retrieved output (${output.execution.status})`;
+        return "Retrieved agent output";
+      }
+      if (isNoResultsResponse(output)) return "No outputs found";
+      return "Error loading agent output";
+    }
+    case "output-error":
+      return "Error loading agent output";
+    default:
+      return "Retrieving agent output";
+  }
+}
+
+export function ToolIcon({
+  isStreaming,
+  isError,
+}: {
+  isStreaming?: boolean;
+  isError?: boolean;
+}) {
+  return (
+    <EyeIcon
+      size={14}
+      weight="regular"
+      className={
+        isError
+          ? "text-red-500"
+          : isStreaming
+            ? "text-neutral-500"
+            : "text-neutral-400"
+      }
+    />
+  );
+}
+
+export function AccordionIcon() {
+  return <MonitorIcon size={32} weight="light" />;
+}
+
+export function formatMaybeJson(value: unknown): string {
+  if (typeof value === "string") return value;
+  try {
+    return JSON.stringify(value, null, 2);
+  } catch {
+    return String(value);
+  }
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/useChatSession.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/useChatSession.ts
new file mode 100644
index 0000000000..ac9213e119
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/useChatSession.ts
@@ -0,0 +1,109 @@
+import {
+  getGetV2GetSessionQueryKey,
+  getGetV2ListSessionsQueryKey,
+  useGetV2GetSession,
+  usePostV2CreateSession,
+} from "@/app/api/__generated__/endpoints/chat/chat";
+import { toast } from "@/components/molecules/Toast/use-toast";
+import * as Sentry from "@sentry/nextjs";
+import { useQueryClient } from "@tanstack/react-query";
+import { parseAsString, useQueryState } from "nuqs";
+import { useEffect, useMemo, useRef } from "react";
+import { convertChatSessionMessagesToUiMessages } from "./helpers/convertChatSessionToUiMessages";
+
+export function useChatSession() {
+  const [sessionId, setSessionId] = useQueryState("sessionId", parseAsString);
+  const queryClient = useQueryClient();
+
+  const sessionQuery = useGetV2GetSession(sessionId ?? "", {
+    query: {
+      enabled: !!sessionId,
+      staleTime: Infinity,
+      refetchOnWindowFocus: false,
+      refetchOnReconnect: false,
+    },
+  });
+
+  // When the user navigates away from a session, invalidate its query cache.
+  // useChat destroys its Chat instance on id change, so messages are lost.
+  // Invalidating ensures the next visit fetches fresh data from the API
+  // instead of hydrating from stale cache that's missing recent messages.
+  const prevSessionIdRef = useRef(sessionId);
+
+  useEffect(() => {
+    const prev = prevSessionIdRef.current;
+    prevSessionIdRef.current = sessionId;
+    if (prev && prev !== sessionId) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2GetSessionQueryKey(prev),
+      });
+    }
+  }, [sessionId, queryClient]);
+
+  // Memoize so the effect in useCopilotPage doesn't infinite-loop on a new
+  // array reference every render. Re-derives only when query data changes.
+  const hydratedMessages = useMemo(() => {
+    if (sessionQuery.data?.status !== 200 || !sessionId) return undefined;
+    return convertChatSessionMessagesToUiMessages(
+      sessionId,
+      sessionQuery.data.data.messages ?? [],
+    );
+  }, [sessionQuery.data, sessionId]);
+
+  const { mutateAsync: createSessionMutation, isPending: isCreatingSession } =
+    usePostV2CreateSession({
+      mutation: {
+        onSuccess: (response) => {
+          if (response.status === 200 && response.data?.id) {
+            setSessionId(response.data.id);
+            queryClient.invalidateQueries({
+              queryKey: getGetV2ListSessionsQueryKey(),
+            });
+          }
+        },
+      },
+    });
+
+  async function createSession() {
+    if (sessionId) return sessionId;
+    try {
+      const response = await createSessionMutation();
+      if (response.status !== 200 || !response.data?.id) {
+        const error = new Error("Failed to create session");
+        Sentry.captureException(error, {
+          extra: { status: response.status },
+        });
+        toast({
+          variant: "destructive",
+          title: "Could not start a new chat session",
+          description: "Please try again.",
+        });
+        throw error;
+      }
+      return response.data.id;
+    } catch (error) {
+      if (
+        error instanceof Error &&
+        error.message === "Failed to create session"
+      ) {
+        throw error; // already handled above
+      }
+      Sentry.captureException(error);
+      toast({
+        variant: "destructive",
+        title: "Could not start a new chat session",
+        description: "Please try again.",
+      });
+      throw error;
+    }
+  }
+
+  return {
+    sessionId,
+    setSessionId,
+    hydratedMessages,
+    isLoadingSession: sessionQuery.isLoading,
+    createSession,
+    isCreatingSession,
+  };
+}
diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
index e4713cd24a..3dbba6e790 100644
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
@@ -1,154 +1,142 @@
-import {
-  getGetV2ListSessionsQueryKey,
-  postV2CreateSession,
-} from "@/app/api/__generated__/endpoints/chat/chat";
-import { useToast } from "@/components/molecules/Toast/use-toast";
-import { getHomepageRoute } from "@/lib/constants";
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
+import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { useOnboarding } from "@/providers/onboarding/onboarding-provider";
-import {
-  Flag,
-  type FlagValues,
-  useGetFlag,
-} from "@/services/feature-flags/use-get-flag";
-import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
-import * as Sentry from "@sentry/nextjs";
-import { useQueryClient } from "@tanstack/react-query";
-import { useFlags } from "launchdarkly-react-client-sdk";
-import { useRouter } from "next/navigation";
-import { useEffect } from "react";
-import { useCopilotStore } from "./copilot-page-store";
-import { getGreetingName, getQuickActions } from "./helpers";
-import { useCopilotSessionId } from "./useCopilotSessionId";
+import { useChat } from "@ai-sdk/react";
+import { DefaultChatTransport } from "ai";
+import { useEffect, useMemo, useState } from "react";
+import { useChatSession } from "./useChatSession";
 
 export function useCopilotPage() {
-  const router = useRouter();
-  const queryClient = useQueryClient();
-  const { user, isLoggedIn, isUserLoading } = useSupabase();
-  const { toast } = useToast();
-  const { completeStep } = useOnboarding();
+  const { isUserLoading, isLoggedIn } = useSupabase();
+  const [isDrawerOpen, setIsDrawerOpen] = useState(false);
+  const [pendingMessage, setPendingMessage] = useState<string | null>(null);
 
-  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
-  const setIsStreaming = useCopilotStore((s) => s.setIsStreaming);
-  const isCreating = useCopilotStore((s) => s.isCreatingSession);
-  const setIsCreating = useCopilotStore((s) => s.setIsCreatingSession);
+  const {
+    sessionId,
+    setSessionId,
+    hydratedMessages,
+    isLoadingSession,
+    createSession,
+    isCreatingSession,
+  } = useChatSession();
 
-  // Complete VISIT_COPILOT onboarding step to grant $5 welcome bonus
-  useEffect(() => {
-    if (isLoggedIn) {
-      completeStep("VISIT_COPILOT");
-    }
-  }, [completeStep, isLoggedIn]);
+  const breakpoint = useBreakpoint();
+  const isMobile =
+    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
 
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const flags = useFlags<FlagValues>();
-  const homepageRoute = getHomepageRoute(isChatEnabled);
-  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
-  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
-  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
-  const isFlagReady =
-    !isLaunchDarklyConfigured || flags[Flag.CHAT] !== undefined;
+  const transport = useMemo(
+    () =>
+      sessionId
+        ? new DefaultChatTransport({
+            api: `/api/chat/sessions/${sessionId}/stream`,
+            prepareSendMessagesRequest: ({ messages }) => {
+              const last = messages[messages.length - 1];
+              return {
+                body: {
+                  message: (
+                    last.parts?.map((p) => (p.type === "text" ? p.text : "")) ??
+                    []
+                  ).join(""),
+                  is_user_message: last.role === "user",
+                  context: null,
+                },
+              };
+            },
+          })
+        : null,
+    [sessionId],
+  );
 
-  const greetingName = getGreetingName(user);
-  const quickActions = getQuickActions();
-
-  const hasSession = Boolean(urlSessionId);
-  const initialPrompt = urlSessionId
-    ? getInitialPrompt(urlSessionId)
-    : undefined;
+  const { messages, sendMessage, stop, status, error, setMessages } = useChat({
+    id: sessionId ?? undefined,
+    transport: transport ?? undefined,
+  });
 
   useEffect(() => {
-    if (!isFlagReady) return;
-    if (isChatEnabled === false) {
-      router.replace(homepageRoute);
+    if (!hydratedMessages || hydratedMessages.length === 0) return;
+    setMessages((prev) => {
+      if (prev.length >= hydratedMessages.length) return prev;
+      return hydratedMessages;
+    });
+  }, [hydratedMessages, setMessages]);
+
+  // Clear messages when session is null
+  useEffect(() => {
+    if (!sessionId) setMessages([]);
+  }, [sessionId, setMessages]);
+
+  useEffect(() => {
+    if (!sessionId || !pendingMessage) return;
+    const msg = pendingMessage;
+    setPendingMessage(null);
+    sendMessage({ text: msg });
+  }, [sessionId, pendingMessage, sendMessage]);
+
+  async function onSend(message: string) {
+    const trimmed = message.trim();
+    if (!trimmed) return;
+
+    if (sessionId) {
+      sendMessage({ text: trimmed });
+      return;
     }
-  }, [homepageRoute, isChatEnabled, isFlagReady, router]);
 
-  async function startChatWithPrompt(prompt: string) {
-    if (!prompt?.trim()) return;
-    if (isCreating) return;
-
-    const trimmedPrompt = prompt.trim();
-    setIsCreating(true);
-
-    try {
-      const sessionResponse = await postV2CreateSession({
-        body: JSON.stringify({}),
-      });
-
-      if (sessionResponse.status !== 200 || !sessionResponse.data?.id) {
-        throw new Error("Failed to create session");
-      }
-
-      const sessionId = sessionResponse.data.id;
-      setInitialPrompt(sessionId, trimmedPrompt);
-
-      await queryClient.invalidateQueries({
-        queryKey: getGetV2ListSessionsQueryKey(),
-      });
-
-      await setUrlSessionId(sessionId, { shallow: true });
-    } catch (error) {
-      console.error("[CopilotPage] Failed to start chat:", error);
-      toast({ title: "Failed to start chat", variant: "destructive" });
-      Sentry.captureException(error);
-    } finally {
-      setIsCreating(false);
-    }
+    setPendingMessage(trimmed);
+    await createSession();
   }
 
-  function handleQuickAction(action: string) {
-    startChatWithPrompt(action);
+  const { data: sessionsResponse, isLoading: isLoadingSessions } =
+    useGetV2ListSessions(
+      { limit: 50 },
+      { query: { enabled: !isUserLoading && isLoggedIn } },
+    );
+
+  const sessions =
+    sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
+
+  function handleOpenDrawer() {
+    setIsDrawerOpen(true);
   }
 
-  function handleSessionNotFound() {
-    router.replace("/copilot");
+  function handleCloseDrawer() {
+    setIsDrawerOpen(false);
   }
 
-  function handleStreamingChange(isStreamingValue: boolean) {
-    setIsStreaming(isStreamingValue);
+  function handleDrawerOpenChange(open: boolean) {
+    setIsDrawerOpen(open);
+  }
+
+  function handleSelectSession(id: string) {
+    setSessionId(id);
+    if (isMobile) setIsDrawerOpen(false);
+  }
+
+  function handleNewChat() {
+    setSessionId(null);
+    if (isMobile) setIsDrawerOpen(false);
   }
 
   return {
-    state: {
-      greetingName,
-      quickActions,
-      isLoading: isUserLoading,
-      hasSession,
-      initialPrompt,
-      isReady: isFlagReady && isChatEnabled !== false && isLoggedIn,
-    },
-    handlers: {
-      handleQuickAction,
-      startChatWithPrompt,
-      handleSessionNotFound,
-      handleStreamingChange,
-    },
+    sessionId,
+    messages,
+    status,
+    error,
+    stop,
+    isLoadingSession,
+    isCreatingSession,
+    isUserLoading,
+    isLoggedIn,
+    createSession,
+    onSend,
+    // Mobile drawer
+    isMobile,
+    isDrawerOpen,
+    sessions,
+    isLoadingSessions,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleSelectSession,
+    handleNewChat,
   };
 }
-
-function getInitialPrompt(sessionId: string): string | undefined {
-  try {
-    const prompts = JSON.parse(
-      sessionStorage.get(SessionKey.CHAT_INITIAL_PROMPTS) || "{}",
-    );
-    return prompts[sessionId];
-  } catch {
-    return undefined;
-  }
-}
-
-function setInitialPrompt(sessionId: string, prompt: string): void {
-  try {
-    const prompts = JSON.parse(
-      sessionStorage.get(SessionKey.CHAT_INITIAL_PROMPTS) || "{}",
-    );
-    prompts[sessionId] = prompt;
-    sessionStorage.set(
-      SessionKey.CHAT_INITIAL_PROMPTS,
-      JSON.stringify(prompts),
-    );
-  } catch {
-    // Ignore storage errors
-  }
-}
diff --git a/autogpt_platform/frontend/src/app/(platform)/error/page.tsx b/autogpt_platform/frontend/src/app/(platform)/error/page.tsx
index b26ca4559b..3cf68178ad 100644
--- a/autogpt_platform/frontend/src/app/(platform)/error/page.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/error/page.tsx
@@ -1,8 +1,6 @@
 "use client";
 
 import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
-import { getHomepageRoute } from "@/lib/constants";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { useSearchParams } from "next/navigation";
 import { Suspense } from "react";
 import { getErrorDetails } from "./helpers";
@@ -11,8 +9,6 @@ function ErrorPageContent() {
   const searchParams = useSearchParams();
   const errorMessage = searchParams.get("message");
   const errorDetails = getErrorDetails(errorMessage);
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   function handleRetry() {
     // Auth-related errors should redirect to login
@@ -30,7 +26,7 @@ function ErrorPageContent() {
       }, 2000);
     } else {
       // For server/network errors, go to home
-      window.location.href = homepageRoute;
+      window.location.href = "/";
     }
   }
 
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/RunDetailHeader/RunDetailHeader.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/RunDetailHeader/RunDetailHeader.tsx
index 3d04234bb3..4e98c70de5 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/RunDetailHeader/RunDetailHeader.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/RunDetailHeader/RunDetailHeader.tsx
@@ -2,7 +2,7 @@ import { GraphExecution } from "@/app/api/__generated__/models/graphExecution";
 import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { Text } from "@/components/atoms/Text/Text";
 import { ClockClockwiseIcon } from "@phosphor-icons/react";
-import moment from "moment";
+import { formatDistanceToNow, formatDistanceStrict } from "date-fns";
 import { AGENT_LIBRARY_SECTION_PADDING_X } from "../../../helpers";
 import { RunStatusBadge } from "../SelectedRunView/components/RunStatusBadge";
 
@@ -43,7 +43,10 @@ export function RunDetailHeader({ agent, run, scheduleRecurrence }: Props) {
           {run ? (
             <div className="mt-1 flex flex-wrap items-center gap-2 gap-y-1 text-zinc-400">
               <Text variant="small" className="text-zinc-500">
-                Started {moment(run.started_at).fromNow()}
+                Started{" "}
+                {run.started_at
+                  ? formatDistanceToNow(run.started_at, { addSuffix: true })
+                  : "—"}
               </Text>
               <span className="mx-1 inline-block text-zinc-200">|</span>
               <Text variant="small" className="text-zinc-500">
@@ -62,7 +65,7 @@ export function RunDetailHeader({ agent, run, scheduleRecurrence }: Props) {
                   <span className="mx-1 inline-block text-zinc-200">|</span>
                   <Text variant="small" className="text-zinc-500">
                     Duration:{" "}
-                    {moment.duration(run.stats.duration, "seconds").humanize()}
+                    {formatDistanceStrict(0, run.stats.duration * 1000)}
                   </Text>
                 </>
               )}
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleListItem.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleListItem.tsx
index a389fb4fc8..1ad40fcef4 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleListItem.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleListItem.tsx
@@ -3,7 +3,7 @@
 import { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo";
 import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { ClockClockwiseIcon } from "@phosphor-icons/react";
-import moment from "moment";
+import { formatDistanceToNow } from "date-fns";
 import { IconWrapper } from "./IconWrapper";
 import { ScheduleActionsDropdown } from "./ScheduleActionsDropdown";
 import { SidebarItemCard } from "./SidebarItemCard";
@@ -26,7 +26,9 @@ export function ScheduleListItem({
   return (
     <SidebarItemCard
       title={schedule.name}
-      description={moment(schedule.next_run_time).fromNow()}
+      description={formatDistanceToNow(schedule.next_run_time, {
+        addSuffix: true,
+      })}
       onClick={onClick}
       selected={selected}
       icon={
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TaskListItem.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TaskListItem.tsx
index 2e2871e15e..8970e82b64 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TaskListItem.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TaskListItem.tsx
@@ -11,7 +11,7 @@ import {
   WarningCircleIcon,
   XCircleIcon,
 } from "@phosphor-icons/react";
-import moment from "moment";
+import { formatDistanceToNow } from "date-fns";
 import React from "react";
 import { IconWrapper } from "./IconWrapper";
 import { SidebarItemCard } from "./SidebarItemCard";
@@ -76,7 +76,11 @@ export function TaskListItem({
     <SidebarItemCard
       icon={statusIconMap[run.status]}
       title={title}
-      description={moment(run.started_at).fromNow()}
+      description={
+        run.started_at
+          ? formatDistanceToNow(run.started_at, { addSuffix: true })
+          : "—"
+      }
       onClick={onClick}
       selected={selected}
       actions={
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TemplateListItem.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TemplateListItem.tsx
index c970cd1522..2cc3cbe203 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TemplateListItem.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TemplateListItem.tsx
@@ -3,7 +3,7 @@
 import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { LibraryAgentPreset } from "@/app/api/__generated__/models/libraryAgentPreset";
 import { FileTextIcon } from "@phosphor-icons/react";
-import moment from "moment";
+import { formatDistanceToNow } from "date-fns";
 import { IconWrapper } from "./IconWrapper";
 import { SidebarItemCard } from "./SidebarItemCard";
 import { TemplateActionsDropdown } from "./TemplateActionsDropdown";
@@ -31,7 +31,9 @@ export function TemplateListItem({
         </IconWrapper>
       }
       title={template.name}
-      description={moment(template.updated_at).fromNow()}
+      description={formatDistanceToNow(template.updated_at, {
+        addSuffix: true,
+      })}
       onClick={onClick}
       selected={selected}
       actions={
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TriggerListItem.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TriggerListItem.tsx
index 4c399e640a..c7b0473a9b 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TriggerListItem.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TriggerListItem.tsx
@@ -3,7 +3,7 @@
 import { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
 import { LibraryAgentPreset } from "@/app/api/__generated__/models/libraryAgentPreset";
 import { LightningIcon } from "@phosphor-icons/react";
-import moment from "moment";
+import { formatDistanceToNow } from "date-fns";
 import { IconWrapper } from "./IconWrapper";
 import { SidebarItemCard } from "./SidebarItemCard";
 import { TriggerActionsDropdown } from "./TriggerActionsDropdown";
@@ -31,7 +31,7 @@ export function TriggerListItem({
         </IconWrapper>
       }
       title={trigger.name}
-      description={moment(trigger.updated_at).fromNow()}
+      description={formatDistanceToNow(trigger.updated_at, { addSuffix: true })}
       onClick={onClick}
       selected={selected}
       actions={
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-details-view.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-details-view.tsx
index f51c44c243..eb5224c958 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-details-view.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-details-view.tsx
@@ -1,5 +1,5 @@
 "use client";
-import moment from "moment";
+import { format, formatDistanceToNow, formatDistanceStrict } from "date-fns";
 import React, { useCallback, useMemo, useEffect } from "react";
 
 import {
@@ -90,13 +90,15 @@ export function AgentRunDetailsView({
       },
       {
         label: "Started",
-        value: `${moment(run.started_at).fromNow()}, ${moment(run.started_at).format("HH:mm")}`,
+        value: run.started_at
+          ? `${formatDistanceToNow(run.started_at, { addSuffix: true })}, ${format(run.started_at, "HH:mm")}`
+          : "—",
       },
       ...(run.stats
         ? [
             {
               label: "Duration",
-              value: moment.duration(run.stats.duration, "seconds").humanize(),
+              value: formatDistanceStrict(0, run.stats.duration * 1000),
             },
             { label: "Steps", value: run.stats.node_exec_count },
             { label: "Cost", value: formatCredits(run.stats.cost) },
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx
index 0147c19a5c..b0c3a6ff7b 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx
@@ -10,8 +10,8 @@ import React, {
 import {
   CredentialsMetaInput,
   CredentialsType,
+  Graph,
   GraphExecutionID,
-  GraphMeta,
   LibraryAgentPreset,
   LibraryAgentPresetID,
   LibraryAgentPresetUpdatable,
@@ -69,7 +69,7 @@ export function AgentRunDraftView({
   className,
   recommendedScheduleCron,
 }: {
-  graph: GraphMeta;
+  graph: Graph;
   agentActions?: ButtonAction[];
   recommendedScheduleCron?: string | null;
   doRun?: (
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-summary-card.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-summary-card.tsx
index 423495878b..6f7d7865bc 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-summary-card.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-summary-card.tsx
@@ -1,5 +1,5 @@
 import React from "react";
-import moment from "moment";
+import { formatDistanceToNow, isPast } from "date-fns";
 
 import { cn } from "@/lib/utils";
 
@@ -118,10 +118,10 @@ export function AgentRunSummaryCard({
         {timestamp && (
           <p
             className="mt-1 text-sm font-normal text-neutral-500"
-            title={moment(timestamp).toString()}
+            title={new Date(timestamp).toString()}
           >
-            {moment(timestamp).isBefore() ? "Ran" : "Runs in"}{" "}
-            {moment(timestamp).fromNow()}
+            {isPast(timestamp) ? "Ran" : "Runs in"}{" "}
+            {formatDistanceToNow(timestamp, { addSuffix: true })}
           </p>
         )}
       </CardContent>
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-schedule-details-view.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-schedule-details-view.tsx
index 61161088fc..30b0a82e65 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-schedule-details-view.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-schedule-details-view.tsx
@@ -2,8 +2,8 @@
 import React, { useCallback, useMemo } from "react";
 
 import {
+  Graph,
   GraphExecutionID,
-  GraphMeta,
   Schedule,
   ScheduleID,
 } from "@/lib/autogpt-server-api";
@@ -35,7 +35,7 @@ export function AgentScheduleDetailsView({
   onForcedRun,
   doDeleteSchedule,
 }: {
-  graph: GraphMeta;
+  graph: Graph;
   schedule: Schedule;
   agentActions: ButtonAction[];
   onForcedRun: (runID: GraphExecutionID) => void;
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/components/LibrarySearchBar/useLibrarySearchbar.tsx b/autogpt_platform/frontend/src/app/(platform)/library/components/LibrarySearchBar/useLibrarySearchbar.tsx
index 74b8e9874c..efeb654ed5 100644
--- a/autogpt_platform/frontend/src/app/(platform)/library/components/LibrarySearchBar/useLibrarySearchbar.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/library/components/LibrarySearchBar/useLibrarySearchbar.tsx
@@ -1,4 +1,4 @@
-import { debounce } from "lodash";
+import debounce from "lodash/debounce";
 import { useCallback, useEffect } from "react";
 
 interface Props {
diff --git a/autogpt_platform/frontend/src/app/(platform)/login/actions.ts b/autogpt_platform/frontend/src/app/(platform)/login/actions.ts
index 447a25a41d..c4867dd123 100644
--- a/autogpt_platform/frontend/src/app/(platform)/login/actions.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/login/actions.ts
@@ -1,6 +1,5 @@
 "use server";
 
-import { getHomepageRoute } from "@/lib/constants";
 import BackendAPI from "@/lib/autogpt-server-api";
 import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
 import { loginFormSchema } from "@/types/auth";
@@ -38,10 +37,8 @@ export async function login(email: string, password: string) {
     await api.createUser();
 
     // Get onboarding status from backend (includes chat flag evaluated for this user)
-    const { shouldShowOnboarding, isChatEnabled } = await getOnboardingStatus();
-    const next = shouldShowOnboarding
-      ? "/onboarding"
-      : getHomepageRoute(isChatEnabled);
+    const { shouldShowOnboarding } = await getOnboardingStatus();
+    const next = shouldShowOnboarding ? "/onboarding" : "/";
 
     return {
       success: true,
diff --git a/autogpt_platform/frontend/src/app/(platform)/login/useLoginPage.ts b/autogpt_platform/frontend/src/app/(platform)/login/useLoginPage.ts
index e64cc1858d..9b81965c31 100644
--- a/autogpt_platform/frontend/src/app/(platform)/login/useLoginPage.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/login/useLoginPage.ts
@@ -1,8 +1,6 @@
 import { useToast } from "@/components/molecules/Toast/use-toast";
-import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { environment } from "@/services/environment";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { loginFormSchema, LoginProvider } from "@/types/auth";
 import { zodResolver } from "@hookform/resolvers/zod";
 import { useRouter, useSearchParams } from "next/navigation";
@@ -22,17 +20,15 @@ export function useLoginPage() {
   const [isGoogleLoading, setIsGoogleLoading] = useState(false);
   const [showNotAllowedModal, setShowNotAllowedModal] = useState(false);
   const isCloudEnv = environment.isCloud();
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   // Get redirect destination from 'next' query parameter
   const nextUrl = searchParams.get("next");
 
   useEffect(() => {
     if (isLoggedIn && !isLoggingIn) {
-      router.push(nextUrl || homepageRoute);
+      router.push(nextUrl || "/");
     }
-  }, [homepageRoute, isLoggedIn, isLoggingIn, nextUrl, router]);
+  }, [isLoggedIn, isLoggingIn, nextUrl, router]);
 
   const form = useForm<z.infer<typeof loginFormSchema>>({
     resolver: zodResolver(loginFormSchema),
@@ -98,7 +94,7 @@ export function useLoginPage() {
       }
 
       // Prefer URL's next parameter, then use backend-determined route
-      router.replace(nextUrl || result.next || homepageRoute);
+      router.replace(nextUrl || result.next || "/");
     } catch (error) {
       toast({
         title:
diff --git a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/AgentFlowList.tsx b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/AgentFlowList.tsx
index badba61bf1..a306275f10 100644
--- a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/AgentFlowList.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/AgentFlowList.tsx
@@ -30,7 +30,7 @@ import {
   TableHeader,
   TableRow,
 } from "@/components/__legacy__/ui/table";
-import moment from "moment/moment";
+import { formatDistanceToNow } from "date-fns";
 import { DialogTitle } from "@/components/__legacy__/ui/dialog";
 import { AgentImportForm } from "./AgentImportForm";
 
@@ -161,8 +161,12 @@ export const AgentFlowList = ({
                     (!lastRun ? (
                       <TableCell />
                     ) : (
-                      <TableCell title={moment(lastRun.started_at).toString()}>
-                        {moment(lastRun.started_at).fromNow()}
+                      <TableCell title={lastRun.started_at?.toString() ?? ""}>
+                        {lastRun.started_at
+                          ? formatDistanceToNow(lastRun.started_at, {
+                              addSuffix: true,
+                            })
+                          : "—"}
                       </TableCell>
                     ))}
                 </TableRow>
diff --git a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunInfo.tsx b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunInfo.tsx
index e619c2fd3d..0fdf39e8d9 100644
--- a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunInfo.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunInfo.tsx
@@ -10,7 +10,7 @@ import Link from "next/link";
 import { Button, buttonVariants } from "@/components/__legacy__/ui/button";
 import { IconSquare } from "@/components/__legacy__/ui/icons";
 import { ExitIcon, Pencil2Icon } from "@radix-ui/react-icons";
-import moment from "moment/moment";
+import { format } from "date-fns";
 import { FlowRunStatusBadge } from "@/app/(platform)/monitoring/components/FlowRunStatusBadge";
 import { useBackendAPI } from "@/lib/autogpt-server-api/context";
 import RunnerOutputUI, {
@@ -111,11 +111,15 @@ export const FlowRunInfo: React.FC<
           </div>
           <p>
             <strong>Started:</strong>{" "}
-            {moment(execution.started_at).format("YYYY-MM-DD HH:mm:ss")}
+            {execution.started_at
+              ? format(execution.started_at, "yyyy-MM-dd HH:mm:ss")
+              : "—"}
           </p>
           <p>
             <strong>Finished:</strong>{" "}
-            {moment(execution.ended_at).format("YYYY-MM-DD HH:mm:ss")}
+            {execution.ended_at
+              ? format(execution.ended_at, "yyyy-MM-dd HH:mm:ss")
+              : "—"}
           </p>
           {execution.stats && (
             <p>
diff --git a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsList.tsx b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsList.tsx
index a99d9309b5..c4a2a40447 100644
--- a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsList.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsList.tsx
@@ -14,7 +14,7 @@ import {
   TableHeader,
   TableRow,
 } from "@/components/__legacy__/ui/table";
-import moment from "moment/moment";
+import { format } from "date-fns";
 import { FlowRunStatusBadge } from "@/app/(platform)/monitoring/components/FlowRunStatusBadge";
 import { TextRenderer } from "../../../../components/__legacy__/ui/render";
 
@@ -59,7 +59,9 @@ export const FlowRunsList: React.FC<{
                 />
               </TableCell>
               <TableCell>
-                {moment(execution.started_at).format("HH:mm")}
+                {execution.started_at
+                  ? format(execution.started_at, "HH:mm")
+                  : "—"}
               </TableCell>
               <TableCell>
                 <FlowRunStatusBadge
diff --git a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsTimeline.tsx b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsTimeline.tsx
index ee01d67234..c54209e1df 100644
--- a/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsTimeline.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/monitoring/components/FlowRunsTimeline.tsx
@@ -10,7 +10,7 @@ import {
   XAxis,
   YAxis,
 } from "recharts";
-import moment from "moment/moment";
+import { differenceInHours, format } from "date-fns";
 import { Card } from "@/components/__legacy__/ui/card";
 import { cn, hashString } from "@/lib/utils";
 import React from "react";
@@ -43,11 +43,11 @@ export const FlowRunsTimeline = ({
         ]}
         allowDataOverflow={true}
         tickFormatter={(unixTime) => {
-          const now = moment();
-          const time = moment(unixTime);
-          return now.diff(time, "hours") < 24
-            ? time.format("HH:mm")
-            : time.format("YYYY-MM-DD HH:mm");
+          const now = new Date();
+          const time = new Date(unixTime);
+          return differenceInHours(now, time) < 24
+            ? format(time, "HH:mm")
+            : format(time, "yyyy-MM-dd HH:mm");
         }}
         name="Time"
         scale="time"
@@ -79,7 +79,9 @@ export const FlowRunsTimeline = ({
                 </div>
                 <p>
                   <strong>Started:</strong>{" "}
-                  {moment(data.started_at).format("YYYY-MM-DD HH:mm:ss")}
+                  {data.started_at
+                    ? format(data.started_at, "yyyy-MM-dd HH:mm:ss")
+                    : "—"}
                 </p>
                 {data.stats && (
                   <p>
diff --git a/autogpt_platform/frontend/src/app/(platform)/signup/actions.ts b/autogpt_platform/frontend/src/app/(platform)/signup/actions.ts
index 0fbba54b8e..204482dbe9 100644
--- a/autogpt_platform/frontend/src/app/(platform)/signup/actions.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/signup/actions.ts
@@ -1,6 +1,5 @@
 "use server";
 
-import { getHomepageRoute } from "@/lib/constants";
 import { getServerSupabase } from "@/lib/supabase/server/getServerSupabase";
 import { signupFormSchema } from "@/types/auth";
 import * as Sentry from "@sentry/nextjs";
@@ -59,10 +58,8 @@ export async function signup(
     }
 
     // Get onboarding status from backend (includes chat flag evaluated for this user)
-    const { shouldShowOnboarding, isChatEnabled } = await getOnboardingStatus();
-    const next = shouldShowOnboarding
-      ? "/onboarding"
-      : getHomepageRoute(isChatEnabled);
+    const { shouldShowOnboarding } = await getOnboardingStatus();
+    const next = shouldShowOnboarding ? "/onboarding" : "/";
 
     return { success: true, next };
   } catch (err) {
diff --git a/autogpt_platform/frontend/src/app/(platform)/signup/useSignupPage.ts b/autogpt_platform/frontend/src/app/(platform)/signup/useSignupPage.ts
index 5fa8c2c159..fd78b48735 100644
--- a/autogpt_platform/frontend/src/app/(platform)/signup/useSignupPage.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/signup/useSignupPage.ts
@@ -1,8 +1,6 @@
 import { useToast } from "@/components/molecules/Toast/use-toast";
-import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { environment } from "@/services/environment";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { LoginProvider, signupFormSchema } from "@/types/auth";
 import { zodResolver } from "@hookform/resolvers/zod";
 import { useRouter, useSearchParams } from "next/navigation";
@@ -22,17 +20,15 @@ export function useSignupPage() {
   const [isGoogleLoading, setIsGoogleLoading] = useState(false);
   const [showNotAllowedModal, setShowNotAllowedModal] = useState(false);
   const isCloudEnv = environment.isCloud();
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   // Get redirect destination from 'next' query parameter
   const nextUrl = searchParams.get("next");
 
   useEffect(() => {
     if (isLoggedIn && !isSigningUp) {
-      router.push(nextUrl || homepageRoute);
+      router.push(nextUrl || "/");
     }
-  }, [homepageRoute, isLoggedIn, isSigningUp, nextUrl, router]);
+  }, [isLoggedIn, isSigningUp, nextUrl, router]);
 
   const form = useForm<z.infer<typeof signupFormSchema>>({
     resolver: zodResolver(signupFormSchema),
@@ -133,7 +129,7 @@ export function useSignupPage() {
       }
 
       // Prefer the URL's next parameter, then result.next (for onboarding), then default
-      const redirectTo = nextUrl || result.next || homepageRoute;
+      const redirectTo = nextUrl || result.next || "/";
       router.replace(redirectTo);
     } catch (error) {
       setIsLoading(false);
diff --git a/autogpt_platform/frontend/src/app/api/chat/sessions/[sessionId]/stream/route.ts b/autogpt_platform/frontend/src/app/api/chat/sessions/[sessionId]/stream/route.ts
index d63eed0ca2..bd27c77963 100644
--- a/autogpt_platform/frontend/src/app/api/chat/sessions/[sessionId]/stream/route.ts
+++ b/autogpt_platform/frontend/src/app/api/chat/sessions/[sessionId]/stream/route.ts
@@ -1,11 +1,8 @@
 import { environment } from "@/services/environment";
 import { getServerAuthToken } from "@/lib/autogpt-server-api/helpers";
 import { NextRequest } from "next/server";
+import { normalizeSSEStream, SSE_HEADERS } from "../../../sse-helpers";
 
-/**
- * SSE Proxy for chat streaming.
- * Supports POST with context (page content + URL) in the request body.
- */
 export async function POST(
   request: NextRequest,
   { params }: { params: Promise<{ sessionId: string }> },
@@ -23,17 +20,14 @@ export async function POST(
       );
     }
 
-    // Get auth token from server-side session
     const token = await getServerAuthToken();
 
-    // Build backend URL
     const backendUrl = environment.getAGPTServerBaseUrl();
     const streamUrl = new URL(
       `/api/chat/sessions/${sessionId}/stream`,
       backendUrl,
     );
 
-    // Forward request to backend with auth header
     const headers: Record<string, string> = {
       "Content-Type": "application/json",
       Accept: "text/event-stream",
@@ -63,14 +57,15 @@ export async function POST(
       });
     }
 
-    // Return the SSE stream directly
-    return new Response(response.body, {
-      headers: {
-        "Content-Type": "text/event-stream",
-        "Cache-Control": "no-cache, no-transform",
-        Connection: "keep-alive",
-        "X-Accel-Buffering": "no",
-      },
+    if (!response.body) {
+      return new Response(
+        JSON.stringify({ error: "Empty response from chat service" }),
+        { status: 502, headers: { "Content-Type": "application/json" } },
+      );
+    }
+
+    return new Response(normalizeSSEStream(response.body), {
+      headers: SSE_HEADERS,
     });
   } catch (error) {
     console.error("SSE proxy error:", error);
@@ -87,40 +82,21 @@ export async function POST(
   }
 }
 
-/**
- * Legacy GET endpoint for backward compatibility
- */
 export async function GET(
-  request: NextRequest,
+  _request: NextRequest,
   { params }: { params: Promise<{ sessionId: string }> },
 ) {
   const { sessionId } = await params;
-  const searchParams = request.nextUrl.searchParams;
-  const message = searchParams.get("message");
-  const isUserMessage = searchParams.get("is_user_message");
-
-  if (!message) {
-    return new Response("Missing message parameter", { status: 400 });
-  }
 
   try {
-    // Get auth token from server-side session
     const token = await getServerAuthToken();
 
-    // Build backend URL
     const backendUrl = environment.getAGPTServerBaseUrl();
     const streamUrl = new URL(
       `/api/chat/sessions/${sessionId}/stream`,
       backendUrl,
     );
-    streamUrl.searchParams.set("message", message);
 
-    // Pass is_user_message parameter if provided
-    if (isUserMessage !== null) {
-      streamUrl.searchParams.set("is_user_message", isUserMessage);
-    }
-
-    // Forward request to backend with auth header
     const headers: Record<string, string> = {
       Accept: "text/event-stream",
       "Cache-Control": "no-cache",
@@ -136,6 +112,10 @@ export async function GET(
       headers,
     });
 
+    if (response.status === 204) {
+      return new Response(null, { status: 204 });
+    }
+
     if (!response.ok) {
       const error = await response.text();
       return new Response(error, {
@@ -144,17 +124,18 @@ export async function GET(
       });
     }
 
-    // Return the SSE stream directly
-    return new Response(response.body, {
+    if (!response.body) {
+      return new Response(null, { status: 204 });
+    }
+
+    return new Response(normalizeSSEStream(response.body), {
       headers: {
-        "Content-Type": "text/event-stream",
-        "Cache-Control": "no-cache, no-transform",
-        Connection: "keep-alive",
-        "X-Accel-Buffering": "no",
+        ...SSE_HEADERS,
+        "x-vercel-ai-ui-message-stream": "v1",
       },
     });
   } catch (error) {
-    console.error("SSE proxy error:", error);
+    console.error("Resume stream proxy error:", error);
     return new Response(
       JSON.stringify({
         error: "Failed to connect to chat service",
diff --git a/autogpt_platform/frontend/src/app/api/chat/sse-helpers.ts b/autogpt_platform/frontend/src/app/api/chat/sse-helpers.ts
new file mode 100644
index 0000000000..a5c76cf872
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/api/chat/sse-helpers.ts
@@ -0,0 +1,72 @@
+export const SSE_HEADERS = {
+  "Content-Type": "text/event-stream",
+  "Cache-Control": "no-cache, no-transform",
+  Connection: "keep-alive",
+  "X-Accel-Buffering": "no",
+} as const;
+
+export function normalizeSSEStream(
+  input: ReadableStream<Uint8Array>,
+): ReadableStream<Uint8Array> {
+  const decoder = new TextDecoder();
+  const encoder = new TextEncoder();
+  let buffer = "";
+
+  return input.pipeThrough(
+    new TransformStream<Uint8Array, Uint8Array>({
+      transform(chunk, controller) {
+        buffer += decoder.decode(chunk, { stream: true });
+
+        const parts = buffer.split("\n\n");
+        buffer = parts.pop() ?? "";
+
+        for (const part of parts) {
+          const normalized = normalizeSSEEvent(part);
+          controller.enqueue(encoder.encode(normalized + "\n\n"));
+        }
+      },
+      flush(controller) {
+        if (buffer.trim()) {
+          const normalized = normalizeSSEEvent(buffer);
+          controller.enqueue(encoder.encode(normalized + "\n\n"));
+        }
+      },
+    }),
+  );
+}
+
+function normalizeSSEEvent(event: string): string {
+  const lines = event.split("\n");
+  const dataLines: string[] = [];
+  const otherLines: string[] = [];
+
+  for (const line of lines) {
+    if (line.startsWith("data: ")) {
+      dataLines.push(line.slice(6));
+    } else {
+      otherLines.push(line);
+    }
+  }
+
+  if (dataLines.length === 0) return event;
+
+  const dataStr = dataLines.join("\n");
+  try {
+    const parsed = JSON.parse(dataStr) as Record<string, unknown>;
+    if (parsed.type === "error") {
+      const normalized = {
+        type: "error",
+        errorText:
+          typeof parsed.errorText === "string"
+            ? parsed.errorText
+            : "An unexpected error occurred",
+      };
+      const newData = `data: ${JSON.stringify(normalized)}`;
+      return [...otherLines.filter((l) => l.length > 0), newData].join("\n");
+    }
+  } catch {
+    // Not valid JSON — pass through as-is
+  }
+
+  return event;
+}
diff --git a/autogpt_platform/frontend/src/app/api/chat/tasks/[taskId]/stream/route.ts b/autogpt_platform/frontend/src/app/api/chat/tasks/[taskId]/stream/route.ts
new file mode 100644
index 0000000000..238fdebb06
--- /dev/null
+++ b/autogpt_platform/frontend/src/app/api/chat/tasks/[taskId]/stream/route.ts
@@ -0,0 +1,64 @@
+import { environment } from "@/services/environment";
+import { getServerAuthToken } from "@/lib/autogpt-server-api/helpers";
+import { NextRequest } from "next/server";
+import { normalizeSSEStream, SSE_HEADERS } from "../../../sse-helpers";
+
+export async function GET(
+  request: NextRequest,
+  { params }: { params: Promise<{ taskId: string }> },
+) {
+  const { taskId } = await params;
+  const searchParams = request.nextUrl.searchParams;
+  const lastMessageId = searchParams.get("last_message_id") || "0-0";
+
+  try {
+    const token = await getServerAuthToken();
+
+    const backendUrl = environment.getAGPTServerBaseUrl();
+    const streamUrl = new URL(`/api/chat/tasks/${taskId}/stream`, backendUrl);
+    streamUrl.searchParams.set("last_message_id", lastMessageId);
+
+    const headers: Record<string, string> = {
+      Accept: "text/event-stream",
+      "Cache-Control": "no-cache",
+      Connection: "keep-alive",
+    };
+
+    if (token) {
+      headers["Authorization"] = `Bearer ${token}`;
+    }
+
+    const response = await fetch(streamUrl.toString(), {
+      method: "GET",
+      headers,
+    });
+
+    if (!response.ok) {
+      const error = await response.text();
+      return new Response(error, {
+        status: response.status,
+        headers: { "Content-Type": "application/json" },
+      });
+    }
+
+    if (!response.body) {
+      return new Response(null, { status: 204 });
+    }
+
+    return new Response(normalizeSSEStream(response.body), {
+      headers: SSE_HEADERS,
+    });
+  } catch (error) {
+    console.error("Task stream proxy error:", error);
+    return new Response(
+      JSON.stringify({
+        error: "Failed to connect to task stream",
+        detail: error instanceof Error ? error.message : String(error),
+      }),
+      {
+        status: 500,
+        headers: { "Content-Type": "application/json" },
+      },
+    );
+  }
+}
diff --git a/autogpt_platform/frontend/src/app/api/helpers.ts b/autogpt_platform/frontend/src/app/api/helpers.ts
index c2104d231a..226f5fa786 100644
--- a/autogpt_platform/frontend/src/app/api/helpers.ts
+++ b/autogpt_platform/frontend/src/app/api/helpers.ts
@@ -181,6 +181,5 @@ export async function getOnboardingStatus() {
   const isCompleted = onboarding.completedSteps.includes("CONGRATS");
   return {
     shouldShowOnboarding: status.is_onboarding_enabled && !isCompleted,
-    isChatEnabled: status.is_chat_enabled,
   };
 }
diff --git a/autogpt_platform/frontend/src/app/api/openapi.json b/autogpt_platform/frontend/src/app/api/openapi.json
index 6692c30e72..172419d27e 100644
--- a/autogpt_platform/frontend/src/app/api/openapi.json
+++ b/autogpt_platform/frontend/src/app/api/openapi.json
@@ -917,6 +917,28 @@
         "security": [{ "HTTPBearerJWT": [] }]
       }
     },
+    "/api/chat/config/ttl": {
+      "get": {
+        "tags": ["v2", "chat", "chat"],
+        "summary": "Get Ttl Config",
+        "description": "Get the stream TTL configuration.\n\nReturns the Time-To-Live settings for chat streams, which determines\nhow long clients can reconnect to an active stream.\n\nReturns:\n    dict: TTL configuration with seconds and milliseconds values.",
+        "operationId": "getV2GetTtlConfig",
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "additionalProperties": true,
+                  "type": "object",
+                  "title": "Response Getv2Getttlconfig"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
     "/api/chat/health": {
       "get": {
         "tags": ["v2", "chat", "chat"],
@@ -939,6 +961,115 @@
         }
       }
     },
+    "/api/chat/operations/{operation_id}/complete": {
+      "post": {
+        "tags": ["v2", "chat", "chat"],
+        "summary": "Complete Operation",
+        "description": "External completion webhook for long-running operations.\n\nCalled by Agent Generator (or other services) when an operation completes.\nThis triggers the stream registry to publish completion and continue LLM generation.\n\nArgs:\n    operation_id: The operation ID to complete.\n    request: Completion payload with success status and result/error.\n    x_api_key: Internal API key for authentication.\n\nReturns:\n    dict: Status of the completion.\n\nRaises:\n    HTTPException: If API key is invalid or operation not found.",
+        "operationId": "postV2CompleteOperation",
+        "parameters": [
+          {
+            "name": "operation_id",
+            "in": "path",
+            "required": true,
+            "schema": { "type": "string", "title": "Operation Id" }
+          },
+          {
+            "name": "x-api-key",
+            "in": "header",
+            "required": false,
+            "schema": {
+              "anyOf": [{ "type": "string" }, { "type": "null" }],
+              "title": "X-Api-Key"
+            }
+          }
+        ],
+        "requestBody": {
+          "required": true,
+          "content": {
+            "application/json": {
+              "schema": {
+                "$ref": "#/components/schemas/OperationCompleteRequest"
+              }
+            }
+          }
+        },
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "additionalProperties": true,
+                  "title": "Response Postv2Completeoperation"
+                }
+              }
+            }
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/api/chat/schema/tool-responses": {
+      "get": {
+        "tags": ["v2", "chat", "chat"],
+        "summary": "[Dummy] Tool response type export for codegen",
+        "description": "This endpoint is not meant to be called. It exists solely to expose tool response models in the OpenAPI schema for frontend codegen.",
+        "operationId": "getV2[dummy] tool response type export for codegen",
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "anyOf": [
+                    { "$ref": "#/components/schemas/AgentsFoundResponse" },
+                    { "$ref": "#/components/schemas/NoResultsResponse" },
+                    { "$ref": "#/components/schemas/AgentDetailsResponse" },
+                    {
+                      "$ref": "#/components/schemas/SetupRequirementsResponse"
+                    },
+                    { "$ref": "#/components/schemas/ExecutionStartedResponse" },
+                    { "$ref": "#/components/schemas/NeedLoginResponse" },
+                    { "$ref": "#/components/schemas/ErrorResponse" },
+                    {
+                      "$ref": "#/components/schemas/InputValidationErrorResponse"
+                    },
+                    { "$ref": "#/components/schemas/AgentOutputResponse" },
+                    {
+                      "$ref": "#/components/schemas/UnderstandingUpdatedResponse"
+                    },
+                    { "$ref": "#/components/schemas/AgentPreviewResponse" },
+                    { "$ref": "#/components/schemas/AgentSavedResponse" },
+                    {
+                      "$ref": "#/components/schemas/ClarificationNeededResponse"
+                    },
+                    { "$ref": "#/components/schemas/BlockListResponse" },
+                    { "$ref": "#/components/schemas/BlockOutputResponse" },
+                    { "$ref": "#/components/schemas/DocSearchResultsResponse" },
+                    { "$ref": "#/components/schemas/DocPageResponse" },
+                    { "$ref": "#/components/schemas/OperationStartedResponse" },
+                    { "$ref": "#/components/schemas/OperationPendingResponse" },
+                    {
+                      "$ref": "#/components/schemas/OperationInProgressResponse"
+                    }
+                  ],
+                  "title": "Response Getv2[Dummy] Tool Response Type Export For Codegen"
+                }
+              }
+            }
+          }
+        }
+      }
+    },
     "/api/chat/sessions": {
       "get": {
         "tags": ["v2", "chat", "chat"],
@@ -1022,7 +1153,7 @@
       "get": {
         "tags": ["v2", "chat", "chat"],
         "summary": "Get Session",
-        "description": "Retrieve the details of a specific chat session.\n\nLooks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.\n\nArgs:\n    session_id: The unique identifier for the desired chat session.\n    user_id: The optional authenticated user ID, or None for anonymous access.\n\nReturns:\n    SessionDetailResponse: Details for the requested session, or None if not found.",
+        "description": "Retrieve the details of a specific chat session.\n\nLooks up a chat session by ID for the given user (if authenticated) and returns all session data including messages.\nIf there's an active stream for this session, returns the task_id for reconnection.\n\nArgs:\n    session_id: The unique identifier for the desired chat session.\n    user_id: The optional authenticated user ID, or None for anonymous access.\n\nReturns:\n    SessionDetailResponse: Details for the requested session, including active_stream info if applicable.",
         "operationId": "getV2GetSession",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -1103,9 +1234,9 @@
     "/api/chat/sessions/{session_id}/stream": {
       "get": {
         "tags": ["v2", "chat", "chat"],
-        "summary": "Stream Chat Get",
-        "description": "Stream chat responses for a session (GET - legacy endpoint).\n\nStreams the AI/completion responses in real time over Server-Sent Events (SSE), including:\n  - Text fragments as they are generated\n  - Tool call UI elements (if invoked)\n  - Tool execution results\n\nArgs:\n    session_id: The chat session identifier to associate with the streamed messages.\n    message: The user's new message to process.\n    user_id: Optional authenticated user ID.\n    is_user_message: Whether the message is a user message.\nReturns:\n    StreamingResponse: SSE-formatted response chunks.",
-        "operationId": "getV2StreamChatGet",
+        "summary": "Resume Session Stream",
+        "description": "Resume an active stream for a session.\n\nCalled by the AI SDK's ``useChat(resume: true)`` on page load.\nChecks for an active (in-progress) task on the session and either replays\nthe full SSE stream or returns 204 No Content if nothing is running.\n\nArgs:\n    session_id: The chat session identifier.\n    user_id: Optional authenticated user ID.\n\nReturns:\n    StreamingResponse (SSE) when an active stream exists,\n    or 204 No Content when there is nothing to resume.",
+        "operationId": "getV2ResumeSessionStream",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
           {
@@ -1113,27 +1244,6 @@
             "in": "path",
             "required": true,
             "schema": { "type": "string", "title": "Session Id" }
-          },
-          {
-            "name": "message",
-            "in": "query",
-            "required": true,
-            "schema": {
-              "type": "string",
-              "minLength": 1,
-              "maxLength": 10000,
-              "title": "Message"
-            }
-          },
-          {
-            "name": "is_user_message",
-            "in": "query",
-            "required": false,
-            "schema": {
-              "type": "boolean",
-              "default": true,
-              "title": "Is User Message"
-            }
           }
         ],
         "responses": {
@@ -1157,7 +1267,7 @@
       "post": {
         "tags": ["v2", "chat", "chat"],
         "summary": "Stream Chat Post",
-        "description": "Stream chat responses for a session (POST with context support).\n\nStreams the AI/completion responses in real time over Server-Sent Events (SSE), including:\n  - Text fragments as they are generated\n  - Tool call UI elements (if invoked)\n  - Tool execution results\n\nArgs:\n    session_id: The chat session identifier to associate with the streamed messages.\n    request: Request body containing message, is_user_message, and optional context.\n    user_id: Optional authenticated user ID.\nReturns:\n    StreamingResponse: SSE-formatted response chunks.",
+        "description": "Stream chat responses for a session (POST with context support).\n\nStreams the AI/completion responses in real time over Server-Sent Events (SSE), including:\n  - Text fragments as they are generated\n  - Tool call UI elements (if invoked)\n  - Tool execution results\n\nThe AI generation runs in a background task that continues even if the client disconnects.\nAll chunks are written to Redis for reconnection support. If the client disconnects,\nthey can reconnect using GET /tasks/{task_id}/stream to resume from where they left off.\n\nArgs:\n    session_id: The chat session identifier to associate with the streamed messages.\n    request: Request body containing message, is_user_message, and optional context.\n    user_id: Optional authenticated user ID.\nReturns:\n    StreamingResponse: SSE-formatted response chunks. First chunk is a \"start\" event\n    containing the task_id for reconnection.",
         "operationId": "postV2StreamChatPost",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -1195,6 +1305,94 @@
         }
       }
     },
+    "/api/chat/tasks/{task_id}": {
+      "get": {
+        "tags": ["v2", "chat", "chat"],
+        "summary": "Get Task Status",
+        "description": "Get the status of a long-running task.\n\nArgs:\n    task_id: The task ID to check.\n    user_id: Authenticated user ID for ownership validation.\n\nReturns:\n    dict: Task status including task_id, status, tool_name, and operation_id.\n\nRaises:\n    NotFoundError: If task_id is not found or user doesn't have access.",
+        "operationId": "getV2GetTaskStatus",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "task_id",
+            "in": "path",
+            "required": true,
+            "schema": { "type": "string", "title": "Task Id" }
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": {
+              "application/json": {
+                "schema": {
+                  "type": "object",
+                  "additionalProperties": true,
+                  "title": "Response Getv2Gettaskstatus"
+                }
+              }
+            }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
+    "/api/chat/tasks/{task_id}/stream": {
+      "get": {
+        "tags": ["v2", "chat", "chat"],
+        "summary": "Stream Task",
+        "description": "Reconnect to a long-running task's SSE stream.\n\nWhen a long-running operation (like agent generation) starts, the client\nreceives a task_id. If the connection drops, the client can reconnect\nusing this endpoint to resume receiving updates.\n\nArgs:\n    task_id: The task ID from the operation_started response.\n    user_id: Authenticated user ID for ownership validation.\n    last_message_id: Last Redis Stream message ID received (\"0-0\" for full replay).\n\nReturns:\n    StreamingResponse: SSE-formatted response chunks starting after last_message_id.\n\nRaises:\n    HTTPException: 404 if task not found, 410 if task expired, 403 if access denied.",
+        "operationId": "getV2StreamTask",
+        "security": [{ "HTTPBearerJWT": [] }],
+        "parameters": [
+          {
+            "name": "task_id",
+            "in": "path",
+            "required": true,
+            "schema": { "type": "string", "title": "Task Id" }
+          },
+          {
+            "name": "last_message_id",
+            "in": "query",
+            "required": false,
+            "schema": {
+              "type": "string",
+              "description": "Last Redis Stream message ID received (e.g., '1706540123456-0'). Use '0-0' for full replay.",
+              "default": "0-0",
+              "title": "Last Message Id"
+            },
+            "description": "Last Redis Stream message ID received (e.g., '1706540123456-0'). Use '0-0' for full replay."
+          }
+        ],
+        "responses": {
+          "200": {
+            "description": "Successful Response",
+            "content": { "application/json": { "schema": {} } }
+          },
+          "401": {
+            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
+          },
+          "422": {
+            "description": "Validation Error",
+            "content": {
+              "application/json": {
+                "schema": { "$ref": "#/components/schemas/HTTPValidationError" }
+              }
+            }
+          }
+        }
+      }
+    },
     "/api/credits": {
       "get": {
         "tags": ["v1", "credits"],
@@ -5462,7 +5660,9 @@
             "description": "Successful Response",
             "content": {
               "application/json": {
-                "schema": { "$ref": "#/components/schemas/GraphMeta" }
+                "schema": {
+                  "$ref": "#/components/schemas/GraphModelWithoutNodes"
+                }
               }
             }
           },
@@ -6168,6 +6368,18 @@
         "title": "AccuracyTrendsResponse",
         "description": "Response model for accuracy trends and alerts."
       },
+      "ActiveStreamInfo": {
+        "properties": {
+          "task_id": { "type": "string", "title": "Task Id" },
+          "last_message_id": { "type": "string", "title": "Last Message Id" },
+          "operation_id": { "type": "string", "title": "Operation Id" },
+          "tool_name": { "type": "string", "title": "Tool Name" }
+        },
+        "type": "object",
+        "required": ["task_id", "last_message_id", "operation_id", "tool_name"],
+        "title": "ActiveStreamInfo",
+        "description": "Information about an active stream for reconnection."
+      },
       "AddUserCreditsResponse": {
         "properties": {
           "new_balance": { "type": "integer", "title": "New Balance" },
@@ -6177,6 +6389,75 @@
         "required": ["new_balance", "transaction_key"],
         "title": "AddUserCreditsResponse"
       },
+      "AgentDetails": {
+        "properties": {
+          "id": { "type": "string", "title": "Id" },
+          "name": { "type": "string", "title": "Name" },
+          "description": { "type": "string", "title": "Description" },
+          "in_library": {
+            "type": "boolean",
+            "title": "In Library",
+            "default": false
+          },
+          "inputs": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Inputs",
+            "default": {}
+          },
+          "credentials": {
+            "items": { "$ref": "#/components/schemas/CredentialsMetaInput" },
+            "type": "array",
+            "title": "Credentials",
+            "default": []
+          },
+          "execution_options": {
+            "$ref": "#/components/schemas/ExecutionOptions"
+          },
+          "trigger_info": {
+            "anyOf": [
+              { "additionalProperties": true, "type": "object" },
+              { "type": "null" }
+            ],
+            "title": "Trigger Info"
+          }
+        },
+        "type": "object",
+        "required": ["id", "name", "description"],
+        "title": "AgentDetails",
+        "description": "Detailed agent information."
+      },
+      "AgentDetailsResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "agent_details"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "agent": { "$ref": "#/components/schemas/AgentDetails" },
+          "user_authenticated": {
+            "type": "boolean",
+            "title": "User Authenticated",
+            "default": false
+          },
+          "graph_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Graph Id"
+          },
+          "graph_version": {
+            "anyOf": [{ "type": "integer" }, { "type": "null" }],
+            "title": "Graph Version"
+          }
+        },
+        "type": "object",
+        "required": ["message", "agent"],
+        "title": "AgentDetailsResponse",
+        "description": "Response for get_details action."
+      },
       "AgentExecutionStatus": {
         "type": "string",
         "enum": [
@@ -6190,6 +6471,224 @@
         ],
         "title": "AgentExecutionStatus"
       },
+      "AgentInfo": {
+        "properties": {
+          "id": { "type": "string", "title": "Id" },
+          "name": { "type": "string", "title": "Name" },
+          "description": { "type": "string", "title": "Description" },
+          "source": {
+            "type": "string",
+            "title": "Source",
+            "description": "marketplace or library"
+          },
+          "in_library": {
+            "type": "boolean",
+            "title": "In Library",
+            "default": false
+          },
+          "creator": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Creator"
+          },
+          "category": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Category"
+          },
+          "rating": {
+            "anyOf": [{ "type": "number" }, { "type": "null" }],
+            "title": "Rating"
+          },
+          "runs": {
+            "anyOf": [{ "type": "integer" }, { "type": "null" }],
+            "title": "Runs"
+          },
+          "is_featured": {
+            "anyOf": [{ "type": "boolean" }, { "type": "null" }],
+            "title": "Is Featured"
+          },
+          "status": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Status"
+          },
+          "can_access_graph": {
+            "anyOf": [{ "type": "boolean" }, { "type": "null" }],
+            "title": "Can Access Graph"
+          },
+          "has_external_trigger": {
+            "anyOf": [{ "type": "boolean" }, { "type": "null" }],
+            "title": "Has External Trigger"
+          },
+          "new_output": {
+            "anyOf": [{ "type": "boolean" }, { "type": "null" }],
+            "title": "New Output"
+          },
+          "graph_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Graph Id"
+          },
+          "inputs": {
+            "anyOf": [
+              { "additionalProperties": true, "type": "object" },
+              { "type": "null" }
+            ],
+            "title": "Inputs",
+            "description": "Input schema for the agent, including field names, types, and defaults"
+          }
+        },
+        "type": "object",
+        "required": ["id", "name", "description", "source"],
+        "title": "AgentInfo",
+        "description": "Information about an agent."
+      },
+      "AgentOutputResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "agent_output"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "agent_name": { "type": "string", "title": "Agent Name" },
+          "agent_id": { "type": "string", "title": "Agent Id" },
+          "library_agent_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Library Agent Id"
+          },
+          "library_agent_link": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Library Agent Link"
+          },
+          "execution": {
+            "anyOf": [
+              { "$ref": "#/components/schemas/ExecutionOutputInfo" },
+              { "type": "null" }
+            ]
+          },
+          "available_executions": {
+            "anyOf": [
+              {
+                "items": { "additionalProperties": true, "type": "object" },
+                "type": "array"
+              },
+              { "type": "null" }
+            ],
+            "title": "Available Executions"
+          },
+          "total_executions": {
+            "type": "integer",
+            "title": "Total Executions",
+            "default": 0
+          }
+        },
+        "type": "object",
+        "required": ["message", "agent_name", "agent_id"],
+        "title": "AgentOutputResponse",
+        "description": "Response for agent_output tool."
+      },
+      "AgentPreviewResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "agent_preview"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "agent_json": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Agent Json"
+          },
+          "agent_name": { "type": "string", "title": "Agent Name" },
+          "description": { "type": "string", "title": "Description" },
+          "node_count": { "type": "integer", "title": "Node Count" },
+          "link_count": {
+            "type": "integer",
+            "title": "Link Count",
+            "default": 0
+          }
+        },
+        "type": "object",
+        "required": [
+          "message",
+          "agent_json",
+          "agent_name",
+          "description",
+          "node_count"
+        ],
+        "title": "AgentPreviewResponse",
+        "description": "Response for previewing a generated agent before saving."
+      },
+      "AgentSavedResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "agent_saved"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "agent_id": { "type": "string", "title": "Agent Id" },
+          "agent_name": { "type": "string", "title": "Agent Name" },
+          "library_agent_id": { "type": "string", "title": "Library Agent Id" },
+          "library_agent_link": {
+            "type": "string",
+            "title": "Library Agent Link"
+          },
+          "agent_page_link": { "type": "string", "title": "Agent Page Link" }
+        },
+        "type": "object",
+        "required": [
+          "message",
+          "agent_id",
+          "agent_name",
+          "library_agent_id",
+          "library_agent_link",
+          "agent_page_link"
+        ],
+        "title": "AgentSavedResponse",
+        "description": "Response when an agent is saved to the library."
+      },
+      "AgentsFoundResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "agents_found"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "title": {
+            "type": "string",
+            "title": "Title",
+            "default": "Available Agents"
+          },
+          "agents": {
+            "items": { "$ref": "#/components/schemas/AgentInfo" },
+            "type": "array",
+            "title": "Agents"
+          },
+          "count": { "type": "integer", "title": "Count" },
+          "name": {
+            "type": "string",
+            "title": "Name",
+            "default": "agents_found"
+          }
+        },
+        "type": "object",
+        "required": ["message", "agents", "count"],
+        "title": "AgentsFoundResponse",
+        "description": "Response for find_agent tool."
+      },
       "ApiResponse": {
         "properties": {
           "answer": { "type": "string", "title": "Answer" },
@@ -6316,18 +6815,6 @@
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Recommended Schedule Cron"
           },
-          "nodes": {
-            "items": { "$ref": "#/components/schemas/Node" },
-            "type": "array",
-            "title": "Nodes",
-            "default": []
-          },
-          "links": {
-            "items": { "$ref": "#/components/schemas/Link" },
-            "type": "array",
-            "title": "Links",
-            "default": []
-          },
           "forked_from_id": {
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Forked From Id"
@@ -6335,11 +6822,22 @@
           "forked_from_version": {
             "anyOf": [{ "type": "integer" }, { "type": "null" }],
             "title": "Forked From Version"
+          },
+          "nodes": {
+            "items": { "$ref": "#/components/schemas/Node" },
+            "type": "array",
+            "title": "Nodes"
+          },
+          "links": {
+            "items": { "$ref": "#/components/schemas/Link" },
+            "type": "array",
+            "title": "Links"
           }
         },
         "type": "object",
         "required": ["name", "description"],
-        "title": "BaseGraph"
+        "title": "BaseGraph",
+        "description": "Graph with nodes, links, and computed I/O schema fields.\n\nUsed to represent sub-graphs within a `Graph`. Contains the full graph\nstructure including nodes and links, plus computed fields for schemas\nand trigger info. Does NOT include user_id or created_at (see GraphModel)."
       },
       "BaseGraph-Output": {
         "properties": {
@@ -6360,18 +6858,6 @@
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Recommended Schedule Cron"
           },
-          "nodes": {
-            "items": { "$ref": "#/components/schemas/Node" },
-            "type": "array",
-            "title": "Nodes",
-            "default": []
-          },
-          "links": {
-            "items": { "$ref": "#/components/schemas/Link" },
-            "type": "array",
-            "title": "Links",
-            "default": []
-          },
           "forked_from_id": {
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Forked From Id"
@@ -6380,6 +6866,16 @@
             "anyOf": [{ "type": "integer" }, { "type": "null" }],
             "title": "Forked From Version"
           },
+          "nodes": {
+            "items": { "$ref": "#/components/schemas/Node" },
+            "type": "array",
+            "title": "Nodes"
+          },
+          "links": {
+            "items": { "$ref": "#/components/schemas/Link" },
+            "type": "array",
+            "title": "Links"
+          },
           "input_schema": {
             "additionalProperties": true,
             "type": "object",
@@ -6426,7 +6922,8 @@
           "has_sensitive_action",
           "trigger_setup_info"
         ],
-        "title": "BaseGraph"
+        "title": "BaseGraph",
+        "description": "Graph with nodes, links, and computed I/O schema fields.\n\nUsed to represent sub-graphs within a `Graph`. Contains the full graph\nstructure including nodes and links, plus computed fields for schemas\nand trigger info. Does NOT include user_id or created_at (see GraphModel)."
       },
       "BlockCategoryResponse": {
         "properties": {
@@ -6512,6 +7009,120 @@
         ],
         "title": "BlockInfo"
       },
+      "BlockInfoSummary": {
+        "properties": {
+          "id": { "type": "string", "title": "Id" },
+          "name": { "type": "string", "title": "Name" },
+          "description": { "type": "string", "title": "Description" },
+          "categories": {
+            "items": { "type": "string" },
+            "type": "array",
+            "title": "Categories"
+          },
+          "input_schema": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Input Schema"
+          },
+          "output_schema": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Output Schema"
+          },
+          "required_inputs": {
+            "items": { "$ref": "#/components/schemas/BlockInputFieldInfo" },
+            "type": "array",
+            "title": "Required Inputs",
+            "description": "List of required input fields for this block"
+          }
+        },
+        "type": "object",
+        "required": [
+          "id",
+          "name",
+          "description",
+          "categories",
+          "input_schema",
+          "output_schema"
+        ],
+        "title": "BlockInfoSummary",
+        "description": "Summary of a block for search results."
+      },
+      "BlockInputFieldInfo": {
+        "properties": {
+          "name": { "type": "string", "title": "Name" },
+          "type": { "type": "string", "title": "Type" },
+          "description": {
+            "type": "string",
+            "title": "Description",
+            "default": ""
+          },
+          "required": {
+            "type": "boolean",
+            "title": "Required",
+            "default": false
+          },
+          "default": { "anyOf": [{}, { "type": "null" }], "title": "Default" }
+        },
+        "type": "object",
+        "required": ["name", "type"],
+        "title": "BlockInputFieldInfo",
+        "description": "Information about a block input field."
+      },
+      "BlockListResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "block_list"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "blocks": {
+            "items": { "$ref": "#/components/schemas/BlockInfoSummary" },
+            "type": "array",
+            "title": "Blocks"
+          },
+          "count": { "type": "integer", "title": "Count" },
+          "query": { "type": "string", "title": "Query" },
+          "usage_hint": {
+            "type": "string",
+            "title": "Usage Hint",
+            "default": "To execute a block, call run_block with block_id set to the block's 'id' field and input_data containing the required fields from input_schema."
+          }
+        },
+        "type": "object",
+        "required": ["message", "blocks", "count", "query"],
+        "title": "BlockListResponse",
+        "description": "Response for find_block tool."
+      },
+      "BlockOutputResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "block_output"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "block_id": { "type": "string", "title": "Block Id" },
+          "block_name": { "type": "string", "title": "Block Name" },
+          "outputs": {
+            "additionalProperties": { "items": {}, "type": "array" },
+            "type": "object",
+            "title": "Outputs"
+          },
+          "success": { "type": "boolean", "title": "Success", "default": true }
+        },
+        "type": "object",
+        "required": ["message", "block_id", "block_name", "outputs"],
+        "title": "BlockOutputResponse",
+        "description": "Response for run_block tool."
+      },
       "BlockResponse": {
         "properties": {
           "blocks": {
@@ -6758,6 +7369,42 @@
         "required": ["query", "conversation_history", "message_id"],
         "title": "ChatRequest"
       },
+      "ClarificationNeededResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "clarification_needed"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "questions": {
+            "items": { "$ref": "#/components/schemas/ClarifyingQuestion" },
+            "type": "array",
+            "title": "Questions"
+          }
+        },
+        "type": "object",
+        "required": ["message"],
+        "title": "ClarificationNeededResponse",
+        "description": "Response when the LLM needs more information from the user."
+      },
+      "ClarifyingQuestion": {
+        "properties": {
+          "question": { "type": "string", "title": "Question" },
+          "keyword": { "type": "string", "title": "Keyword" },
+          "example": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Example"
+          }
+        },
+        "type": "object",
+        "required": ["question", "keyword"],
+        "title": "ClarifyingQuestion",
+        "description": "A question that needs user clarification."
+      },
       "CountResponse": {
         "properties": {
           "all_blocks": { "type": "integer", "title": "All Blocks" },
@@ -7016,6 +7663,71 @@
         "required": ["version_counts"],
         "title": "DeleteGraphResponse"
       },
+      "DocPageResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "doc_page"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "title": { "type": "string", "title": "Title" },
+          "path": { "type": "string", "title": "Path" },
+          "content": { "type": "string", "title": "Content" },
+          "doc_url": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Doc Url"
+          }
+        },
+        "type": "object",
+        "required": ["message", "title", "path", "content"],
+        "title": "DocPageResponse",
+        "description": "Response for get_doc_page tool."
+      },
+      "DocSearchResult": {
+        "properties": {
+          "title": { "type": "string", "title": "Title" },
+          "path": { "type": "string", "title": "Path" },
+          "section": { "type": "string", "title": "Section" },
+          "snippet": { "type": "string", "title": "Snippet" },
+          "score": { "type": "number", "title": "Score" },
+          "doc_url": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Doc Url"
+          }
+        },
+        "type": "object",
+        "required": ["title", "path", "section", "snippet", "score"],
+        "title": "DocSearchResult",
+        "description": "A single documentation search result."
+      },
+      "DocSearchResultsResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "doc_search_results"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "results": {
+            "items": { "$ref": "#/components/schemas/DocSearchResult" },
+            "type": "array",
+            "title": "Results"
+          },
+          "count": { "type": "integer", "title": "Count" },
+          "query": { "type": "string", "title": "Query" }
+        },
+        "type": "object",
+        "required": ["message", "results", "count", "query"],
+        "title": "DocSearchResultsResponse",
+        "description": "Response for search_docs tool."
+      },
       "Document": {
         "properties": {
           "url": { "type": "string", "title": "Url" },
@@ -7025,6 +7737,34 @@
         "required": ["url", "relevance_score"],
         "title": "Document"
       },
+      "ErrorResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "error"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "error": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Error"
+          },
+          "details": {
+            "anyOf": [
+              { "additionalProperties": true, "type": "object" },
+              { "type": "null" }
+            ],
+            "title": "Details"
+          }
+        },
+        "type": "object",
+        "required": ["message"],
+        "title": "ErrorResponse",
+        "description": "Response for errors."
+      },
       "ExecutionAnalyticsConfig": {
         "properties": {
           "available_models": {
@@ -7201,6 +7941,85 @@
         ],
         "title": "ExecutionAnalyticsResult"
       },
+      "ExecutionOptions": {
+        "properties": {
+          "manual": { "type": "boolean", "title": "Manual", "default": true },
+          "scheduled": {
+            "type": "boolean",
+            "title": "Scheduled",
+            "default": true
+          },
+          "webhook": { "type": "boolean", "title": "Webhook", "default": false }
+        },
+        "type": "object",
+        "title": "ExecutionOptions",
+        "description": "Available execution options for an agent."
+      },
+      "ExecutionOutputInfo": {
+        "properties": {
+          "execution_id": { "type": "string", "title": "Execution Id" },
+          "status": { "type": "string", "title": "Status" },
+          "started_at": {
+            "anyOf": [
+              { "type": "string", "format": "date-time" },
+              { "type": "null" }
+            ],
+            "title": "Started At"
+          },
+          "ended_at": {
+            "anyOf": [
+              { "type": "string", "format": "date-time" },
+              { "type": "null" }
+            ],
+            "title": "Ended At"
+          },
+          "outputs": {
+            "additionalProperties": { "items": {}, "type": "array" },
+            "type": "object",
+            "title": "Outputs"
+          },
+          "inputs_summary": {
+            "anyOf": [
+              { "additionalProperties": true, "type": "object" },
+              { "type": "null" }
+            ],
+            "title": "Inputs Summary"
+          }
+        },
+        "type": "object",
+        "required": ["execution_id", "status", "outputs"],
+        "title": "ExecutionOutputInfo",
+        "description": "Summary of a single execution's outputs."
+      },
+      "ExecutionStartedResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "execution_started"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "execution_id": { "type": "string", "title": "Execution Id" },
+          "graph_id": { "type": "string", "title": "Graph Id" },
+          "graph_name": { "type": "string", "title": "Graph Name" },
+          "library_agent_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Library Agent Id"
+          },
+          "library_agent_link": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Library Agent Link"
+          },
+          "status": { "type": "string", "title": "Status", "default": "QUEUED" }
+        },
+        "type": "object",
+        "required": ["message", "execution_id", "graph_id", "graph_name"],
+        "title": "ExecutionStartedResponse",
+        "description": "Response for run/schedule actions."
+      },
       "Graph": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -7220,18 +8039,6 @@
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Recommended Schedule Cron"
           },
-          "nodes": {
-            "items": { "$ref": "#/components/schemas/Node" },
-            "type": "array",
-            "title": "Nodes",
-            "default": []
-          },
-          "links": {
-            "items": { "$ref": "#/components/schemas/Link" },
-            "type": "array",
-            "title": "Links",
-            "default": []
-          },
           "forked_from_id": {
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Forked From Id"
@@ -7240,16 +8047,26 @@
             "anyOf": [{ "type": "integer" }, { "type": "null" }],
             "title": "Forked From Version"
           },
+          "nodes": {
+            "items": { "$ref": "#/components/schemas/Node" },
+            "type": "array",
+            "title": "Nodes"
+          },
+          "links": {
+            "items": { "$ref": "#/components/schemas/Link" },
+            "type": "array",
+            "title": "Links"
+          },
           "sub_graphs": {
             "items": { "$ref": "#/components/schemas/BaseGraph-Input" },
             "type": "array",
-            "title": "Sub Graphs",
-            "default": []
+            "title": "Sub Graphs"
           }
         },
         "type": "object",
         "required": ["name", "description"],
-        "title": "Graph"
+        "title": "Graph",
+        "description": "Creatable graph model used in API create/update endpoints."
       },
       "GraphExecution": {
         "properties": {
@@ -7599,6 +8416,52 @@
         "description": "Response schema for paginated graph executions."
       },
       "GraphMeta": {
+        "properties": {
+          "id": { "type": "string", "title": "Id" },
+          "version": { "type": "integer", "title": "Version" },
+          "is_active": {
+            "type": "boolean",
+            "title": "Is Active",
+            "default": true
+          },
+          "name": { "type": "string", "title": "Name" },
+          "description": { "type": "string", "title": "Description" },
+          "instructions": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Instructions"
+          },
+          "recommended_schedule_cron": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Recommended Schedule Cron"
+          },
+          "forked_from_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Forked From Id"
+          },
+          "forked_from_version": {
+            "anyOf": [{ "type": "integer" }, { "type": "null" }],
+            "title": "Forked From Version"
+          },
+          "user_id": { "type": "string", "title": "User Id" },
+          "created_at": {
+            "type": "string",
+            "format": "date-time",
+            "title": "Created At"
+          }
+        },
+        "type": "object",
+        "required": [
+          "id",
+          "version",
+          "name",
+          "description",
+          "user_id",
+          "created_at"
+        ],
+        "title": "GraphMeta",
+        "description": "Lightweight graph metadata model representing an existing graph from the database,\nfor use in listings and summaries.\n\nLacks `GraphModel`'s nodes, links, and expensive computed fields.\nUse for list endpoints where full graph data is not needed and performance matters."
+      },
+      "GraphModel": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
           "version": { "type": "integer", "title": "Version", "default": 1 },
@@ -7625,13 +8488,27 @@
             "anyOf": [{ "type": "integer" }, { "type": "null" }],
             "title": "Forked From Version"
           },
+          "user_id": { "type": "string", "title": "User Id" },
+          "created_at": {
+            "type": "string",
+            "format": "date-time",
+            "title": "Created At"
+          },
+          "nodes": {
+            "items": { "$ref": "#/components/schemas/NodeModel" },
+            "type": "array",
+            "title": "Nodes"
+          },
+          "links": {
+            "items": { "$ref": "#/components/schemas/Link" },
+            "type": "array",
+            "title": "Links"
+          },
           "sub_graphs": {
             "items": { "$ref": "#/components/schemas/BaseGraph-Output" },
             "type": "array",
-            "title": "Sub Graphs",
-            "default": []
+            "title": "Sub Graphs"
           },
-          "user_id": { "type": "string", "title": "User Id" },
           "input_schema": {
             "additionalProperties": true,
             "type": "object",
@@ -7678,6 +8555,7 @@
           "name",
           "description",
           "user_id",
+          "created_at",
           "input_schema",
           "output_schema",
           "has_external_trigger",
@@ -7686,9 +8564,10 @@
           "trigger_setup_info",
           "credentials_input_schema"
         ],
-        "title": "GraphMeta"
+        "title": "GraphModel",
+        "description": "Full graph model representing an existing graph from the database.\n\nThis is the primary model for working with persisted graphs. Includes all\ngraph data (nodes, links, sub_graphs) plus user ownership and timestamps.\nProvides computed fields (input_schema, output_schema, etc.) used during\nset-up (frontend) and execution (backend).\n\nInherits from:\n- `Graph`: provides structure (nodes, links, sub_graphs) and computed schemas\n- `GraphMeta`: provides user_id, created_at for database records"
       },
-      "GraphModel": {
+      "GraphModelWithoutNodes": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
           "version": { "type": "integer", "title": "Version", "default": 1 },
@@ -7707,18 +8586,6 @@
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Recommended Schedule Cron"
           },
-          "nodes": {
-            "items": { "$ref": "#/components/schemas/NodeModel" },
-            "type": "array",
-            "title": "Nodes",
-            "default": []
-          },
-          "links": {
-            "items": { "$ref": "#/components/schemas/Link" },
-            "type": "array",
-            "title": "Links",
-            "default": []
-          },
           "forked_from_id": {
             "anyOf": [{ "type": "string" }, { "type": "null" }],
             "title": "Forked From Id"
@@ -7727,12 +8594,6 @@
             "anyOf": [{ "type": "integer" }, { "type": "null" }],
             "title": "Forked From Version"
           },
-          "sub_graphs": {
-            "items": { "$ref": "#/components/schemas/BaseGraph-Output" },
-            "type": "array",
-            "title": "Sub Graphs",
-            "default": []
-          },
           "user_id": { "type": "string", "title": "User Id" },
           "created_at": {
             "type": "string",
@@ -7794,7 +8655,8 @@
           "trigger_setup_info",
           "credentials_input_schema"
         ],
-        "title": "GraphModel"
+        "title": "GraphModelWithoutNodes",
+        "description": "GraphModel variant that excludes nodes, links, and sub-graphs from serialization.\n\nUsed in contexts like the store where exposing internal graph structure\nis not desired. Inherits all computed fields from GraphModel but marks\nnodes and links as excluded from JSON output."
       },
       "GraphSettings": {
         "properties": {
@@ -7909,6 +8771,43 @@
         "required": ["provider", "host"],
         "title": "HostScopedCredentials"
       },
+      "InputValidationErrorResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "input_validation_error"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "unrecognized_fields": {
+            "items": { "type": "string" },
+            "type": "array",
+            "title": "Unrecognized Fields",
+            "description": "List of input field names that were not recognized"
+          },
+          "inputs": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Inputs",
+            "description": "The agent's valid input schema for reference"
+          },
+          "graph_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Graph Id"
+          },
+          "graph_version": {
+            "anyOf": [{ "type": "integer" }, { "type": "null" }],
+            "title": "Graph Version"
+          }
+        },
+        "type": "object",
+        "required": ["message", "unrecognized_fields", "inputs"],
+        "title": "InputValidationErrorResponse",
+        "description": "Response when run_agent receives unknown input fields."
+      },
       "LibraryAgent": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -7981,6 +8880,25 @@
             ]
           },
           "new_output": { "type": "boolean", "title": "New Output" },
+          "execution_count": {
+            "type": "integer",
+            "title": "Execution Count",
+            "default": 0
+          },
+          "success_rate": {
+            "anyOf": [{ "type": "number" }, { "type": "null" }],
+            "title": "Success Rate"
+          },
+          "avg_correctness_score": {
+            "anyOf": [{ "type": "number" }, { "type": "null" }],
+            "title": "Avg Correctness Score"
+          },
+          "recent_executions": {
+            "items": { "$ref": "#/components/schemas/RecentExecution" },
+            "type": "array",
+            "title": "Recent Executions",
+            "description": "List of recent executions with status, score, and summary"
+          },
           "can_access_graph": {
             "type": "boolean",
             "title": "Can Access Graph"
@@ -8408,6 +9326,54 @@
         "required": ["agents", "pagination"],
         "title": "MyAgentsResponse"
       },
+      "NeedLoginResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "need_login"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "agent_info": {
+            "anyOf": [
+              { "additionalProperties": true, "type": "object" },
+              { "type": "null" }
+            ],
+            "title": "Agent Info"
+          }
+        },
+        "type": "object",
+        "required": ["message"],
+        "title": "NeedLoginResponse",
+        "description": "Response when login is needed."
+      },
+      "NoResultsResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "no_results"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "suggestions": {
+            "items": { "type": "string" },
+            "type": "array",
+            "title": "Suggestions",
+            "default": []
+          },
+          "name": { "type": "string", "title": "Name", "default": "no_results" }
+        },
+        "type": "object",
+        "required": ["message"],
+        "title": "NoResultsResponse",
+        "description": "Response when no agents found."
+      },
       "Node": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -8415,26 +9381,22 @@
           "input_default": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Input Default",
-            "default": {}
+            "title": "Input Default"
           },
           "metadata": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Metadata",
-            "default": {}
+            "title": "Metadata"
           },
           "input_links": {
             "items": { "$ref": "#/components/schemas/Link" },
             "type": "array",
-            "title": "Input Links",
-            "default": []
+            "title": "Input Links"
           },
           "output_links": {
             "items": { "$ref": "#/components/schemas/Link" },
             "type": "array",
-            "title": "Output Links",
-            "default": []
+            "title": "Output Links"
           }
         },
         "type": "object",
@@ -8514,26 +9476,22 @@
           "input_default": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Input Default",
-            "default": {}
+            "title": "Input Default"
           },
           "metadata": {
             "additionalProperties": true,
             "type": "object",
-            "title": "Metadata",
-            "default": {}
+            "title": "Metadata"
           },
           "input_links": {
             "items": { "$ref": "#/components/schemas/Link" },
             "type": "array",
-            "title": "Input Links",
-            "default": []
+            "title": "Input Links"
           },
           "output_links": {
             "items": { "$ref": "#/components/schemas/Link" },
             "type": "array",
-            "title": "Output Links",
-            "default": []
+            "title": "Output Links"
           },
           "graph_id": { "type": "string", "title": "Graph Id" },
           "graph_version": { "type": "integer", "title": "Graph Version" },
@@ -8804,6 +9762,87 @@
         ],
         "title": "OnboardingStep"
       },
+      "OperationCompleteRequest": {
+        "properties": {
+          "success": { "type": "boolean", "title": "Success" },
+          "result": {
+            "anyOf": [
+              { "additionalProperties": true, "type": "object" },
+              { "type": "string" },
+              { "type": "null" }
+            ],
+            "title": "Result"
+          },
+          "error": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Error"
+          }
+        },
+        "type": "object",
+        "required": ["success"],
+        "title": "OperationCompleteRequest",
+        "description": "Request model for external completion webhook."
+      },
+      "OperationInProgressResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "operation_in_progress"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "tool_call_id": { "type": "string", "title": "Tool Call Id" }
+        },
+        "type": "object",
+        "required": ["message", "tool_call_id"],
+        "title": "OperationInProgressResponse",
+        "description": "Response when an operation is already in progress.\n\nReturned for idempotency when the same tool_call_id is requested again\nwhile the background task is still running."
+      },
+      "OperationPendingResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "operation_pending"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "operation_id": { "type": "string", "title": "Operation Id" },
+          "tool_name": { "type": "string", "title": "Tool Name" }
+        },
+        "type": "object",
+        "required": ["message", "operation_id", "tool_name"],
+        "title": "OperationPendingResponse",
+        "description": "Response stored in chat history while a long-running operation is executing.\n\nThis is persisted to the database so users see a pending state when they\nrefresh before the operation completes."
+      },
+      "OperationStartedResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "operation_started"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "operation_id": { "type": "string", "title": "Operation Id" },
+          "tool_name": { "type": "string", "title": "Tool Name" },
+          "task_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Task Id"
+          }
+        },
+        "type": "object",
+        "required": ["message", "operation_id", "tool_name"],
+        "title": "OperationStartedResponse",
+        "description": "Response when a long-running operation has been started in the background.\n\nThis is returned immediately to the client while the operation continues\nto execute. The user can close the tab and check back later.\n\nThe task_id can be used to reconnect to the SSE stream via\nGET /chat/tasks/{task_id}/stream?last_idx=0"
+      },
       "Pagination": {
         "properties": {
           "total_items": {
@@ -9374,6 +10413,23 @@
         "required": ["providers", "pagination"],
         "title": "ProviderResponse"
       },
+      "RecentExecution": {
+        "properties": {
+          "status": { "type": "string", "title": "Status" },
+          "correctness_score": {
+            "anyOf": [{ "type": "number" }, { "type": "null" }],
+            "title": "Correctness Score"
+          },
+          "activity_summary": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Activity Summary"
+          }
+        },
+        "type": "object",
+        "required": ["status"],
+        "title": "RecentExecution",
+        "description": "Summary of a recent execution for quality assessment.\n\nUsed by the LLM to understand the agent's recent performance with specific examples\nrather than just aggregate statistics."
+      },
       "RefundRequest": {
         "properties": {
           "id": { "type": "string", "title": "Id" },
@@ -9418,6 +10474,38 @@
         "required": ["credit_amount"],
         "title": "RequestTopUp"
       },
+      "ResponseType": {
+        "type": "string",
+        "enum": [
+          "agents_found",
+          "agent_details",
+          "setup_requirements",
+          "execution_started",
+          "need_login",
+          "error",
+          "no_results",
+          "agent_output",
+          "understanding_updated",
+          "agent_preview",
+          "agent_saved",
+          "clarification_needed",
+          "block_list",
+          "block_output",
+          "doc_search_results",
+          "doc_page",
+          "workspace_file_list",
+          "workspace_file_content",
+          "workspace_file_metadata",
+          "workspace_file_written",
+          "workspace_file_deleted",
+          "operation_started",
+          "operation_pending",
+          "operation_in_progress",
+          "input_validation_error"
+        ],
+        "title": "ResponseType",
+        "description": "Types of tool responses."
+      },
       "ReviewItem": {
         "properties": {
           "node_exec_id": {
@@ -9642,6 +10730,12 @@
             "items": { "additionalProperties": true, "type": "object" },
             "type": "array",
             "title": "Messages"
+          },
+          "active_stream": {
+            "anyOf": [
+              { "$ref": "#/components/schemas/ActiveStreamInfo" },
+              { "type": "null" }
+            ]
           }
         },
         "type": "object",
@@ -9675,6 +10769,48 @@
         "required": ["active_graph_version"],
         "title": "SetGraphActiveVersion"
       },
+      "SetupInfo": {
+        "properties": {
+          "agent_id": { "type": "string", "title": "Agent Id" },
+          "agent_name": { "type": "string", "title": "Agent Name" },
+          "requirements": {
+            "additionalProperties": { "items": {}, "type": "array" },
+            "type": "object",
+            "title": "Requirements"
+          },
+          "user_readiness": { "$ref": "#/components/schemas/UserReadiness" }
+        },
+        "type": "object",
+        "required": ["agent_id", "agent_name"],
+        "title": "SetupInfo",
+        "description": "Complete setup information."
+      },
+      "SetupRequirementsResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "setup_requirements"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "setup_info": { "$ref": "#/components/schemas/SetupInfo" },
+          "graph_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Graph Id"
+          },
+          "graph_version": {
+            "anyOf": [{ "type": "integer" }, { "type": "null" }],
+            "title": "Graph Version"
+          }
+        },
+        "type": "object",
+        "required": ["message", "setup_info"],
+        "title": "SetupRequirementsResponse",
+        "description": "Response for validate action."
+      },
       "ShareRequest": {
         "properties": {},
         "type": "object",
@@ -9797,7 +10933,8 @@
           "sub_heading": { "type": "string", "title": "Sub Heading" },
           "description": { "type": "string", "title": "Description" },
           "runs": { "type": "integer", "title": "Runs" },
-          "rating": { "type": "number", "title": "Rating" }
+          "rating": { "type": "number", "title": "Rating" },
+          "agent_graph_id": { "type": "string", "title": "Agent Graph Id" }
         },
         "type": "object",
         "required": [
@@ -9809,7 +10946,8 @@
           "sub_heading",
           "description",
           "runs",
-          "rating"
+          "rating",
+          "agent_graph_id"
         ],
         "title": "StoreAgent"
       },
@@ -11069,6 +12207,33 @@
         "required": ["name", "graph_id", "graph_version", "trigger_config"],
         "title": "TriggeredPresetSetupRequest"
       },
+      "UnderstandingUpdatedResponse": {
+        "properties": {
+          "type": {
+            "$ref": "#/components/schemas/ResponseType",
+            "default": "understanding_updated"
+          },
+          "message": { "type": "string", "title": "Message" },
+          "session_id": {
+            "anyOf": [{ "type": "string" }, { "type": "null" }],
+            "title": "Session Id"
+          },
+          "updated_fields": {
+            "items": { "type": "string" },
+            "type": "array",
+            "title": "Updated Fields"
+          },
+          "current_understanding": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Current Understanding"
+          }
+        },
+        "type": "object",
+        "required": ["message"],
+        "title": "UnderstandingUpdatedResponse",
+        "description": "Response for add_understanding tool."
+      },
       "UnifiedSearchResponse": {
         "properties": {
           "results": {
@@ -11947,6 +13112,29 @@
         "required": ["provider", "username", "password"],
         "title": "UserPasswordCredentials"
       },
+      "UserReadiness": {
+        "properties": {
+          "has_all_credentials": {
+            "type": "boolean",
+            "title": "Has All Credentials",
+            "default": false
+          },
+          "missing_credentials": {
+            "additionalProperties": true,
+            "type": "object",
+            "title": "Missing Credentials",
+            "default": {}
+          },
+          "ready_to_run": {
+            "type": "boolean",
+            "title": "Ready To Run",
+            "default": false
+          }
+        },
+        "type": "object",
+        "title": "UserReadiness",
+        "description": "User readiness status."
+      },
       "UserTransaction": {
         "properties": {
           "transaction_key": {
@@ -12028,7 +13216,9 @@
             "title": "Location"
           },
           "msg": { "type": "string", "title": "Message" },
-          "type": { "type": "string", "title": "Error Type" }
+          "type": { "type": "string", "title": "Error Type" },
+          "input": { "title": "Input" },
+          "ctx": { "type": "object", "title": "Context" }
         },
         "type": "object",
         "required": ["loc", "msg", "type"],
diff --git a/autogpt_platform/frontend/src/app/globals.css b/autogpt_platform/frontend/src/app/globals.css
index 1f782f753b..dd1d17cde7 100644
--- a/autogpt_platform/frontend/src/app/globals.css
+++ b/autogpt_platform/frontend/src/app/globals.css
@@ -1,6 +1,7 @@
 @tailwind base;
 @tailwind components;
 @tailwind utilities;
+@source "../node_modules/streamdown/dist/*.js";
 
 @layer base {
   :root {
@@ -29,6 +30,14 @@
     --chart-3: 197 37% 24%;
     --chart-4: 43 74% 66%;
     --chart-5: 27 87% 67%;
+    --sidebar-background: 0 0% 98%;
+    --sidebar-foreground: 240 5.3% 26.1%;
+    --sidebar-primary: 240 5.9% 10%;
+    --sidebar-primary-foreground: 0 0% 98%;
+    --sidebar-accent: 240 4.8% 95.9%;
+    --sidebar-accent-foreground: 240 5.9% 10%;
+    --sidebar-border: 220 13% 91%;
+    --sidebar-ring: 217.2 91.2% 59.8%;
   }
 
   .dark {
@@ -56,6 +65,14 @@
     --chart-3: 30 80% 55%;
     --chart-4: 280 65% 60%;
     --chart-5: 340 75% 55%;
+    --sidebar-background: 240 5.9% 10%;
+    --sidebar-foreground: 240 4.8% 95.9%;
+    --sidebar-primary: 224.3 76.3% 48%;
+    --sidebar-primary-foreground: 0 0% 100%;
+    --sidebar-accent: 240 3.7% 15.9%;
+    --sidebar-accent-foreground: 240 4.8% 95.9%;
+    --sidebar-border: 240 3.7% 15.9%;
+    --sidebar-ring: 217.2 91.2% 59.8%;
   }
 
   * {
diff --git a/autogpt_platform/frontend/src/app/page.tsx b/autogpt_platform/frontend/src/app/page.tsx
index dbfab49469..ce67760eda 100644
--- a/autogpt_platform/frontend/src/app/page.tsx
+++ b/autogpt_platform/frontend/src/app/page.tsx
@@ -1,27 +1,15 @@
 "use client";
 
-import { getHomepageRoute } from "@/lib/constants";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { useRouter } from "next/navigation";
 import { useEffect } from "react";
 
 export default function Page() {
-  const isChatEnabled = useGetFlag(Flag.CHAT);
   const router = useRouter();
-  const homepageRoute = getHomepageRoute(isChatEnabled);
-  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
-  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
-  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
-  const isFlagReady =
-    !isLaunchDarklyConfigured || typeof isChatEnabled === "boolean";
 
-  useEffect(
-    function redirectToHomepage() {
-      if (!isFlagReady) return;
-      router.replace(homepageRoute);
-    },
-    [homepageRoute, isFlagReady, router],
-  );
+  useEffect(() => {
+    router.replace("/copilot");
+  }, [router]);
 
-  return null;
+  return <LoadingSpinner size="large" cover />;
 }
diff --git a/autogpt_platform/frontend/src/components/__legacy__/ui/render.tsx b/autogpt_platform/frontend/src/components/__legacy__/ui/render.tsx
index 5173326f23..b290c51809 100644
--- a/autogpt_platform/frontend/src/components/__legacy__/ui/render.tsx
+++ b/autogpt_platform/frontend/src/components/__legacy__/ui/render.tsx
@@ -22,7 +22,7 @@ const isValidVideoUrl = (url: string): boolean => {
   if (url.startsWith("data:video")) {
     return true;
   }
-  const videoExtensions = /\.(mp4|webm|ogg)$/i;
+  const videoExtensions = /\.(mp4|webm|ogg|mov|avi|mkv|m4v)$/i;
   const youtubeRegex = /^(https?:\/\/)?(www\.)?(youtube\.com|youtu\.?be)\/.+$/;
   const cleanedUrl = url.split("?")[0];
   return (
@@ -44,11 +44,29 @@ const isValidAudioUrl = (url: string): boolean => {
   if (url.startsWith("data:audio")) {
     return true;
   }
-  const audioExtensions = /\.(mp3|wav)$/i;
+  const audioExtensions = /\.(mp3|wav|ogg|m4a|aac|flac)$/i;
   const cleanedUrl = url.split("?")[0];
   return isValidMediaUri(url) && audioExtensions.test(cleanedUrl);
 };
 
+const getVideoMimeType = (url: string): string => {
+  if (url.startsWith("data:video/")) {
+    const match = url.match(/^data:(video\/[^;]+)/);
+    return match?.[1] || "video/mp4";
+  }
+  const extension = url.split("?")[0].split(".").pop()?.toLowerCase();
+  const mimeMap: Record<string, string> = {
+    mp4: "video/mp4",
+    webm: "video/webm",
+    ogg: "video/ogg",
+    mov: "video/quicktime",
+    avi: "video/x-msvideo",
+    mkv: "video/x-matroska",
+    m4v: "video/mp4",
+  };
+  return mimeMap[extension || ""] || "video/mp4";
+};
+
 const VideoRenderer: React.FC<{ videoUrl: string }> = ({ videoUrl }) => {
   const videoId = getYouTubeVideoId(videoUrl);
   return (
@@ -63,7 +81,7 @@ const VideoRenderer: React.FC<{ videoUrl: string }> = ({ videoUrl }) => {
         ></iframe>
       ) : (
         <video controls width="100%" height="315">
-          <source src={videoUrl} type="video/mp4" />
+          <source src={videoUrl} type={getVideoMimeType(videoUrl)} />
           Your browser does not support the video tag.
         </video>
       )}
diff --git a/autogpt_platform/frontend/src/components/ai-elements/conversation.tsx b/autogpt_platform/frontend/src/components/ai-elements/conversation.tsx
new file mode 100644
index 0000000000..92e940c715
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ai-elements/conversation.tsx
@@ -0,0 +1,109 @@
+"use client";
+
+import { Button } from "@/components/ui/button";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { ArrowDownIcon } from "lucide-react";
+import type { ComponentProps } from "react";
+import { useCallback } from "react";
+import { StickToBottom, useStickToBottomContext } from "use-stick-to-bottom";
+
+export type ConversationProps = ComponentProps<typeof StickToBottom>;
+
+export const Conversation = ({ className, ...props }: ConversationProps) => (
+  <StickToBottom
+    className={cn(
+      "relative flex-1 overflow-y-hidden",
+      scrollbarStyles,
+      className,
+    )}
+    initial="smooth"
+    resize="smooth"
+    role="log"
+    {...props}
+  />
+);
+
+export type ConversationContentProps = ComponentProps<
+  typeof StickToBottom.Content
+>;
+
+export const ConversationContent = ({
+  className,
+  ...props
+}: ConversationContentProps) => (
+  <StickToBottom.Content
+    className={cn("flex flex-col gap-8 p-4", className)}
+    {...props}
+  />
+);
+
+export type ConversationEmptyStateProps = ComponentProps<"div"> & {
+  title?: string;
+  description?: string;
+  icon?: React.ReactNode;
+};
+
+export const ConversationEmptyState = ({
+  className,
+  title = "No messages yet",
+  description = "Start a conversation to see messages here",
+  icon,
+  children,
+  ...props
+}: ConversationEmptyStateProps) => (
+  <div
+    className={cn(
+      "flex size-full flex-col items-center justify-center gap-3 p-8 text-center",
+      className,
+    )}
+    {...props}
+  >
+    {children ?? (
+      <>
+        {icon && (
+          <div className="text-neutral-500 dark:text-neutral-400">{icon}</div>
+        )}
+        <div className="space-y-1">
+          <h3 className="text-sm font-medium">{title}</h3>
+          {description && (
+            <p className="text-sm text-neutral-500 dark:text-neutral-400">
+              {description}
+            </p>
+          )}
+        </div>
+      </>
+    )}
+  </div>
+);
+
+export type ConversationScrollButtonProps = ComponentProps<typeof Button>;
+
+export const ConversationScrollButton = ({
+  className,
+  ...props
+}: ConversationScrollButtonProps) => {
+  const { isAtBottom, scrollToBottom } = useStickToBottomContext();
+
+  const handleScrollToBottom = useCallback(() => {
+    scrollToBottom();
+  }, [scrollToBottom]);
+
+  return (
+    !isAtBottom && (
+      <Button
+        className={cn(
+          "absolute bottom-4 left-[50%] translate-x-[-50%] rounded-full dark:bg-white dark:dark:bg-neutral-950 dark:dark:hover:bg-neutral-800 dark:hover:bg-neutral-100",
+          className,
+        )}
+        onClick={handleScrollToBottom}
+        size="icon"
+        type="button"
+        variant="outline"
+        {...props}
+      >
+        <ArrowDownIcon className="size-4" />
+      </Button>
+    )
+  );
+};
diff --git a/autogpt_platform/frontend/src/components/ai-elements/message.tsx b/autogpt_platform/frontend/src/components/ai-elements/message.tsx
new file mode 100644
index 0000000000..5cc330e57c
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ai-elements/message.tsx
@@ -0,0 +1,338 @@
+"use client";
+
+import { Button } from "@/components/ui/button";
+import { ButtonGroup, ButtonGroupText } from "@/components/ui/button-group";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipProvider,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
+import { cn } from "@/lib/utils";
+import { cjk } from "@streamdown/cjk";
+import { code } from "@streamdown/code";
+import { math } from "@streamdown/math";
+import { mermaid } from "@streamdown/mermaid";
+import type { UIMessage } from "ai";
+import { ChevronLeftIcon, ChevronRightIcon } from "lucide-react";
+import type { ComponentProps, HTMLAttributes, ReactElement } from "react";
+import { createContext, memo, useContext, useEffect, useState } from "react";
+import { Streamdown } from "streamdown";
+
+export type MessageProps = HTMLAttributes<HTMLDivElement> & {
+  from: UIMessage["role"];
+};
+
+export const Message = ({ className, from, ...props }: MessageProps) => (
+  <div
+    className={cn(
+      "group flex w-full max-w-[95%] flex-col gap-2",
+      from === "user" ? "is-user ml-auto justify-end" : "is-assistant",
+      className,
+    )}
+    {...props}
+  />
+);
+
+export type MessageContentProps = HTMLAttributes<HTMLDivElement>;
+
+export const MessageContent = ({
+  children,
+  className,
+  ...props
+}: MessageContentProps) => (
+  <div
+    className={cn(
+      "is-user:dark flex w-full min-w-0 max-w-full flex-col gap-2 overflow-hidden text-sm",
+      "group-[.is-user]:w-fit",
+      "group-[.is-user]:ml-auto group-[.is-user]:rounded-lg group-[.is-user]:bg-neutral-100 group-[.is-user]:px-4 group-[.is-user]:py-3 group-[.is-user]:text-neutral-950 dark:group-[.is-user]:bg-neutral-800 dark:group-[.is-user]:text-neutral-50",
+      "group-[.is-assistant]:text-neutral-950 dark:group-[.is-assistant]:text-neutral-50",
+      className,
+    )}
+    {...props}
+  >
+    {children}
+  </div>
+);
+
+export type MessageActionsProps = ComponentProps<"div">;
+
+export const MessageActions = ({
+  className,
+  children,
+  ...props
+}: MessageActionsProps) => (
+  <div className={cn("flex items-center gap-1", className)} {...props}>
+    {children}
+  </div>
+);
+
+export type MessageActionProps = ComponentProps<typeof Button> & {
+  tooltip?: string;
+  label?: string;
+};
+
+export const MessageAction = ({
+  tooltip,
+  children,
+  label,
+  variant = "ghost",
+  size = "icon-sm",
+  ...props
+}: MessageActionProps) => {
+  const button = (
+    <Button size={size} type="button" variant={variant} {...props}>
+      {children}
+      <span className="sr-only">{label || tooltip}</span>
+    </Button>
+  );
+
+  if (tooltip) {
+    return (
+      <TooltipProvider>
+        <Tooltip>
+          <TooltipTrigger asChild>{button}</TooltipTrigger>
+          <TooltipContent>
+            <p>{tooltip}</p>
+          </TooltipContent>
+        </Tooltip>
+      </TooltipProvider>
+    );
+  }
+
+  return button;
+};
+
+interface MessageBranchContextType {
+  currentBranch: number;
+  totalBranches: number;
+  goToPrevious: () => void;
+  goToNext: () => void;
+  branches: ReactElement[];
+  setBranches: (branches: ReactElement[]) => void;
+}
+
+const MessageBranchContext = createContext<MessageBranchContextType | null>(
+  null,
+);
+
+const useMessageBranch = () => {
+  const context = useContext(MessageBranchContext);
+
+  if (!context) {
+    throw new Error("MessageBranch components must be used within");
+  }
+
+  return context;
+};
+
+export type MessageBranchProps = HTMLAttributes<HTMLDivElement> & {
+  defaultBranch?: number;
+  onBranchChange?: (branchIndex: number) => void;
+};
+
+export const MessageBranch = ({
+  defaultBranch = 0,
+  onBranchChange,
+  className,
+  ...props
+}: MessageBranchProps) => {
+  const [currentBranch, setCurrentBranch] = useState(defaultBranch);
+  const [branches, setBranches] = useState<ReactElement[]>([]);
+
+  const handleBranchChange = (newBranch: number) => {
+    setCurrentBranch(newBranch);
+    onBranchChange?.(newBranch);
+  };
+
+  const goToPrevious = () => {
+    const newBranch =
+      currentBranch > 0 ? currentBranch - 1 : branches.length - 1;
+    handleBranchChange(newBranch);
+  };
+
+  const goToNext = () => {
+    const newBranch =
+      currentBranch < branches.length - 1 ? currentBranch + 1 : 0;
+    handleBranchChange(newBranch);
+  };
+
+  const contextValue: MessageBranchContextType = {
+    currentBranch,
+    totalBranches: branches.length,
+    goToPrevious,
+    goToNext,
+    branches,
+    setBranches,
+  };
+
+  return (
+    <MessageBranchContext.Provider value={contextValue}>
+      <div
+        className={cn("grid w-full gap-2 [&>div]:pb-0", className)}
+        {...props}
+      />
+    </MessageBranchContext.Provider>
+  );
+};
+
+export type MessageBranchContentProps = HTMLAttributes<HTMLDivElement>;
+
+export const MessageBranchContent = ({
+  children,
+  ...props
+}: MessageBranchContentProps) => {
+  const { currentBranch, setBranches, branches } = useMessageBranch();
+  const childrenArray = Array.isArray(children) ? children : [children];
+
+  // Use useEffect to update branches when they change
+  useEffect(() => {
+    if (branches.length !== childrenArray.length) {
+      setBranches(childrenArray);
+    }
+  }, [childrenArray, branches, setBranches]);
+
+  return childrenArray.map((branch, index) => (
+    <div
+      className={cn(
+        "grid gap-2 overflow-hidden [&>div]:pb-0",
+        index === currentBranch ? "block" : "hidden",
+      )}
+      key={branch.key}
+      {...props}
+    >
+      {branch}
+    </div>
+  ));
+};
+
+export type MessageBranchSelectorProps = HTMLAttributes<HTMLDivElement> & {
+  from: UIMessage["role"];
+};
+
+export const MessageBranchSelector = ({
+  className,
+  from: _from,
+  ...props
+}: MessageBranchSelectorProps) => {
+  const { totalBranches } = useMessageBranch();
+
+  // Don't render if there's only one branch
+  if (totalBranches <= 1) {
+    return null;
+  }
+
+  return (
+    <ButtonGroup
+      className={cn(
+        "[&>*:not(:first-child)]:rounded-l-md [&>*:not(:last-child)]:rounded-r-md",
+        className,
+      )}
+      orientation="horizontal"
+      {...props}
+    />
+  );
+};
+
+export type MessageBranchPreviousProps = ComponentProps<typeof Button>;
+
+export const MessageBranchPrevious = ({
+  children,
+  ...props
+}: MessageBranchPreviousProps) => {
+  const { goToPrevious, totalBranches } = useMessageBranch();
+
+  return (
+    <Button
+      aria-label="Previous branch"
+      disabled={totalBranches <= 1}
+      onClick={goToPrevious}
+      size="icon-sm"
+      type="button"
+      variant="ghost"
+      {...props}
+    >
+      {children ?? <ChevronLeftIcon size={14} />}
+    </Button>
+  );
+};
+
+export type MessageBranchNextProps = ComponentProps<typeof Button>;
+
+export const MessageBranchNext = ({
+  children,
+  ...props
+}: MessageBranchNextProps) => {
+  const { goToNext, totalBranches } = useMessageBranch();
+
+  return (
+    <Button
+      aria-label="Next branch"
+      disabled={totalBranches <= 1}
+      onClick={goToNext}
+      size="icon-sm"
+      type="button"
+      variant="ghost"
+      {...props}
+    >
+      {children ?? <ChevronRightIcon size={14} />}
+    </Button>
+  );
+};
+
+export type MessageBranchPageProps = HTMLAttributes<HTMLSpanElement>;
+
+export const MessageBranchPage = ({
+  className,
+  ...props
+}: MessageBranchPageProps) => {
+  const { currentBranch, totalBranches } = useMessageBranch();
+
+  return (
+    <ButtonGroupText
+      className={cn(
+        "border-none bg-transparent text-neutral-500 shadow-none dark:text-neutral-400",
+        className,
+      )}
+      {...props}
+    >
+      {currentBranch + 1} of {totalBranches}
+    </ButtonGroupText>
+  );
+};
+
+export type MessageResponseProps = ComponentProps<typeof Streamdown>;
+
+export const MessageResponse = memo(
+  ({ className, ...props }: MessageResponseProps) => (
+    <Streamdown
+      className={cn(
+        "size-full [&>*:first-child]:mt-0 [&>*:last-child]:mb-0 [&_pre]:!bg-white",
+        className,
+      )}
+      plugins={{ code, mermaid, math, cjk }}
+      {...props}
+    />
+  ),
+  (prevProps, nextProps) => prevProps.children === nextProps.children,
+);
+
+MessageResponse.displayName = "MessageResponse";
+
+export type MessageToolbarProps = ComponentProps<"div">;
+
+export const MessageToolbar = ({
+  className,
+  children,
+  ...props
+}: MessageToolbarProps) => (
+  <div
+    className={cn(
+      "mt-4 flex w-full items-center justify-between gap-4",
+      className,
+    )}
+    {...props}
+  >
+    {children}
+  </div>
+);
diff --git a/autogpt_platform/frontend/src/components/atoms/FileInput/FileInput.tsx b/autogpt_platform/frontend/src/components/atoms/FileInput/FileInput.tsx
index d43063b411..2677a7483b 100644
--- a/autogpt_platform/frontend/src/components/atoms/FileInput/FileInput.tsx
+++ b/autogpt_platform/frontend/src/components/atoms/FileInput/FileInput.tsx
@@ -104,7 +104,31 @@ export function FileInput(props: Props) {
     return false;
   }
 
-  const getFileLabelFromValue = (val: string) => {
+  const getFileLabelFromValue = (val: unknown): string => {
+    // Handle object format from external API: { name, type, size, data }
+    if (val && typeof val === "object") {
+      const obj = val as Record<string, unknown>;
+      if (typeof obj.name === "string") {
+        return getFileLabel(
+          obj.name,
+          typeof obj.type === "string" ? obj.type : "",
+        );
+      }
+      if (typeof obj.type === "string") {
+        const mimeParts = obj.type.split("/");
+        if (mimeParts.length > 1) {
+          return `${mimeParts[1].toUpperCase()} file`;
+        }
+        return `${obj.type} file`;
+      }
+      return "File";
+    }
+
+    // Handle string values (data URIs or file paths)
+    if (typeof val !== "string") {
+      return "File";
+    }
+
     if (val.startsWith("data:")) {
       const matches = val.match(/^data:([^;]+);/);
       if (matches?.[1]) {
diff --git a/autogpt_platform/frontend/src/components/atoms/OverflowText/OverflowText.tsx b/autogpt_platform/frontend/src/components/atoms/OverflowText/OverflowText.tsx
index efc345f79c..b118cc5aa0 100644
--- a/autogpt_platform/frontend/src/components/atoms/OverflowText/OverflowText.tsx
+++ b/autogpt_platform/frontend/src/components/atoms/OverflowText/OverflowText.tsx
@@ -77,7 +77,7 @@ export function OverflowText(props: Props) {
         "block min-w-0 overflow-hidden text-ellipsis whitespace-nowrap",
       )}
     >
-      <Text variant={variant} className={className} {...restProps}>
+      <Text variant={variant} as="span" className={className} {...restProps}>
         {value}
       </Text>
     </span>
diff --git a/autogpt_platform/frontend/src/components/atoms/Text/Text.tsx b/autogpt_platform/frontend/src/components/atoms/Text/Text.tsx
index 8bae184e5b..86c39b6436 100644
--- a/autogpt_platform/frontend/src/components/atoms/Text/Text.tsx
+++ b/autogpt_platform/frontend/src/components/atoms/Text/Text.tsx
@@ -1,4 +1,5 @@
 import React from "react";
+import { cn } from "@/lib/utils";
 import { As, Variant, variantElementMap, variants } from "./helpers";
 
 type CustomProps = {
@@ -22,7 +23,7 @@ export function Text({
 }: TextProps) {
   const variantClasses = variants[size || variant] || variants.body;
   const Element = outerAs || variantElementMap[variant];
-  const combinedClassName = `${variantClasses} ${className}`.trim();
+  const combinedClassName = cn(variantClasses, className);
 
   return React.createElement(
     Element,
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/Chat.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/Chat.tsx
deleted file mode 100644
index ada8c26231..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/Chat.tsx
+++ /dev/null
@@ -1,96 +0,0 @@
-"use client";
-
-import { useCopilotSessionId } from "@/app/(platform)/copilot/useCopilotSessionId";
-import { useCopilotStore } from "@/app/(platform)/copilot/copilot-page-store";
-import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { useEffect, useRef } from "react";
-import { ChatContainer } from "./components/ChatContainer/ChatContainer";
-import { ChatErrorState } from "./components/ChatErrorState/ChatErrorState";
-import { useChat } from "./useChat";
-
-export interface ChatProps {
-  className?: string;
-  initialPrompt?: string;
-  onSessionNotFound?: () => void;
-  onStreamingChange?: (isStreaming: boolean) => void;
-}
-
-export function Chat({
-  className,
-  initialPrompt,
-  onSessionNotFound,
-  onStreamingChange,
-}: ChatProps) {
-  const { urlSessionId } = useCopilotSessionId();
-  const hasHandledNotFoundRef = useRef(false);
-  const isSwitchingSession = useCopilotStore((s) => s.isSwitchingSession);
-  const {
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    isSessionNotFound,
-    sessionId,
-    createSession,
-    showLoader,
-    startPollingForOperation,
-  } = useChat({ urlSessionId });
-
-  useEffect(() => {
-    if (!onSessionNotFound) return;
-    if (!urlSessionId) return;
-    if (!isSessionNotFound || isLoading || isCreating) return;
-    if (hasHandledNotFoundRef.current) return;
-    hasHandledNotFoundRef.current = true;
-    onSessionNotFound();
-  }, [
-    onSessionNotFound,
-    urlSessionId,
-    isSessionNotFound,
-    isLoading,
-    isCreating,
-  ]);
-
-  const shouldShowLoader =
-    (showLoader && (isLoading || isCreating)) || isSwitchingSession;
-
-  return (
-    <div className={cn("flex h-full flex-col", className)}>
-      {/* Main Content */}
-      <main className="flex min-h-0 w-full flex-1 flex-col overflow-hidden bg-[#f8f8f9]">
-        {/* Loading State */}
-        {shouldShowLoader && (
-          <div className="flex flex-1 items-center justify-center">
-            <div className="flex flex-col items-center gap-3">
-              <LoadingSpinner size="large" className="text-neutral-400" />
-              <Text variant="body" className="text-zinc-500">
-                {isSwitchingSession
-                  ? "Switching chat..."
-                  : "Loading your chat..."}
-              </Text>
-            </div>
-          </div>
-        )}
-
-        {/* Error State */}
-        {error && !isLoading && !isSwitchingSession && (
-          <ChatErrorState error={error} onRetry={createSession} />
-        )}
-
-        {/* Session Content */}
-        {sessionId && !isLoading && !error && !isSwitchingSession && (
-          <ChatContainer
-            sessionId={sessionId}
-            initialMessages={messages}
-            initialPrompt={initialPrompt}
-            className="flex-1"
-            onStreamingChange={onStreamingChange}
-            onOperationStarted={startPollingForOperation}
-          />
-        )}
-      </main>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/chat-store.ts b/autogpt_platform/frontend/src/components/contextual/Chat/chat-store.ts
deleted file mode 100644
index 8229630e5d..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/chat-store.ts
+++ /dev/null
@@ -1,289 +0,0 @@
-"use client";
-
-import { create } from "zustand";
-import type {
-  ActiveStream,
-  StreamChunk,
-  StreamCompleteCallback,
-  StreamResult,
-  StreamStatus,
-} from "./chat-types";
-import { executeStream } from "./stream-executor";
-
-const COMPLETED_STREAM_TTL = 5 * 60 * 1000; // 5 minutes
-
-interface ChatStoreState {
-  activeStreams: Map<string, ActiveStream>;
-  completedStreams: Map<string, StreamResult>;
-  activeSessions: Set<string>;
-  streamCompleteCallbacks: Set<StreamCompleteCallback>;
-}
-
-interface ChatStoreActions {
-  startStream: (
-    sessionId: string,
-    message: string,
-    isUserMessage: boolean,
-    context?: { url: string; content: string },
-    onChunk?: (chunk: StreamChunk) => void,
-  ) => Promise<void>;
-  stopStream: (sessionId: string) => void;
-  subscribeToStream: (
-    sessionId: string,
-    onChunk: (chunk: StreamChunk) => void,
-    skipReplay?: boolean,
-  ) => () => void;
-  getStreamStatus: (sessionId: string) => StreamStatus;
-  getCompletedStream: (sessionId: string) => StreamResult | undefined;
-  clearCompletedStream: (sessionId: string) => void;
-  isStreaming: (sessionId: string) => boolean;
-  registerActiveSession: (sessionId: string) => void;
-  unregisterActiveSession: (sessionId: string) => void;
-  isSessionActive: (sessionId: string) => boolean;
-  onStreamComplete: (callback: StreamCompleteCallback) => () => void;
-}
-
-type ChatStore = ChatStoreState & ChatStoreActions;
-
-function notifyStreamComplete(
-  callbacks: Set<StreamCompleteCallback>,
-  sessionId: string,
-) {
-  for (const callback of callbacks) {
-    try {
-      callback(sessionId);
-    } catch (err) {
-      console.warn("[ChatStore] Stream complete callback error:", err);
-    }
-  }
-}
-
-function cleanupExpiredStreams(
-  completedStreams: Map<string, StreamResult>,
-): Map<string, StreamResult> {
-  const now = Date.now();
-  const cleaned = new Map(completedStreams);
-  for (const [sessionId, result] of cleaned) {
-    if (now - result.completedAt > COMPLETED_STREAM_TTL) {
-      cleaned.delete(sessionId);
-    }
-  }
-  return cleaned;
-}
-
-export const useChatStore = create<ChatStore>((set, get) => ({
-  activeStreams: new Map(),
-  completedStreams: new Map(),
-  activeSessions: new Set(),
-  streamCompleteCallbacks: new Set(),
-
-  startStream: async function startStream(
-    sessionId,
-    message,
-    isUserMessage,
-    context,
-    onChunk,
-  ) {
-    const state = get();
-    const newActiveStreams = new Map(state.activeStreams);
-    let newCompletedStreams = new Map(state.completedStreams);
-    const callbacks = state.streamCompleteCallbacks;
-
-    const existingStream = newActiveStreams.get(sessionId);
-    if (existingStream) {
-      existingStream.abortController.abort();
-      const normalizedStatus =
-        existingStream.status === "streaming"
-          ? "completed"
-          : existingStream.status;
-      const result: StreamResult = {
-        sessionId,
-        status: normalizedStatus,
-        chunks: existingStream.chunks,
-        completedAt: Date.now(),
-        error: existingStream.error,
-      };
-      newCompletedStreams.set(sessionId, result);
-      newActiveStreams.delete(sessionId);
-      newCompletedStreams = cleanupExpiredStreams(newCompletedStreams);
-      if (normalizedStatus === "completed" || normalizedStatus === "error") {
-        notifyStreamComplete(callbacks, sessionId);
-      }
-    }
-
-    const abortController = new AbortController();
-    const initialCallbacks = new Set<(chunk: StreamChunk) => void>();
-    if (onChunk) initialCallbacks.add(onChunk);
-
-    const stream: ActiveStream = {
-      sessionId,
-      abortController,
-      status: "streaming",
-      startedAt: Date.now(),
-      chunks: [],
-      onChunkCallbacks: initialCallbacks,
-    };
-
-    newActiveStreams.set(sessionId, stream);
-    set({
-      activeStreams: newActiveStreams,
-      completedStreams: newCompletedStreams,
-    });
-
-    try {
-      await executeStream(stream, message, isUserMessage, context);
-    } finally {
-      if (onChunk) stream.onChunkCallbacks.delete(onChunk);
-      if (stream.status !== "streaming") {
-        const currentState = get();
-        const finalActiveStreams = new Map(currentState.activeStreams);
-        let finalCompletedStreams = new Map(currentState.completedStreams);
-
-        const storedStream = finalActiveStreams.get(sessionId);
-        if (storedStream === stream) {
-          const result: StreamResult = {
-            sessionId,
-            status: stream.status,
-            chunks: stream.chunks,
-            completedAt: Date.now(),
-            error: stream.error,
-          };
-          finalCompletedStreams.set(sessionId, result);
-          finalActiveStreams.delete(sessionId);
-          finalCompletedStreams = cleanupExpiredStreams(finalCompletedStreams);
-          set({
-            activeStreams: finalActiveStreams,
-            completedStreams: finalCompletedStreams,
-          });
-          if (stream.status === "completed" || stream.status === "error") {
-            notifyStreamComplete(
-              currentState.streamCompleteCallbacks,
-              sessionId,
-            );
-          }
-        }
-      }
-    }
-  },
-
-  stopStream: function stopStream(sessionId) {
-    const state = get();
-    const stream = state.activeStreams.get(sessionId);
-    if (!stream) return;
-
-    stream.abortController.abort();
-    stream.status = "completed";
-
-    const newActiveStreams = new Map(state.activeStreams);
-    let newCompletedStreams = new Map(state.completedStreams);
-
-    const result: StreamResult = {
-      sessionId,
-      status: stream.status,
-      chunks: stream.chunks,
-      completedAt: Date.now(),
-      error: stream.error,
-    };
-    newCompletedStreams.set(sessionId, result);
-    newActiveStreams.delete(sessionId);
-    newCompletedStreams = cleanupExpiredStreams(newCompletedStreams);
-
-    set({
-      activeStreams: newActiveStreams,
-      completedStreams: newCompletedStreams,
-    });
-
-    notifyStreamComplete(state.streamCompleteCallbacks, sessionId);
-  },
-
-  subscribeToStream: function subscribeToStream(
-    sessionId,
-    onChunk,
-    skipReplay = false,
-  ) {
-    const state = get();
-    const stream = state.activeStreams.get(sessionId);
-
-    if (stream) {
-      if (!skipReplay) {
-        for (const chunk of stream.chunks) {
-          onChunk(chunk);
-        }
-      }
-
-      stream.onChunkCallbacks.add(onChunk);
-
-      return function unsubscribe() {
-        stream.onChunkCallbacks.delete(onChunk);
-      };
-    }
-
-    return function noop() {};
-  },
-
-  getStreamStatus: function getStreamStatus(sessionId) {
-    const { activeStreams, completedStreams } = get();
-
-    const active = activeStreams.get(sessionId);
-    if (active) return active.status;
-
-    const completed = completedStreams.get(sessionId);
-    if (completed) return completed.status;
-
-    return "idle";
-  },
-
-  getCompletedStream: function getCompletedStream(sessionId) {
-    return get().completedStreams.get(sessionId);
-  },
-
-  clearCompletedStream: function clearCompletedStream(sessionId) {
-    const state = get();
-    if (!state.completedStreams.has(sessionId)) return;
-
-    const newCompletedStreams = new Map(state.completedStreams);
-    newCompletedStreams.delete(sessionId);
-    set({ completedStreams: newCompletedStreams });
-  },
-
-  isStreaming: function isStreaming(sessionId) {
-    const stream = get().activeStreams.get(sessionId);
-    return stream?.status === "streaming";
-  },
-
-  registerActiveSession: function registerActiveSession(sessionId) {
-    const state = get();
-    if (state.activeSessions.has(sessionId)) return;
-
-    const newActiveSessions = new Set(state.activeSessions);
-    newActiveSessions.add(sessionId);
-    set({ activeSessions: newActiveSessions });
-  },
-
-  unregisterActiveSession: function unregisterActiveSession(sessionId) {
-    const state = get();
-    if (!state.activeSessions.has(sessionId)) return;
-
-    const newActiveSessions = new Set(state.activeSessions);
-    newActiveSessions.delete(sessionId);
-    set({ activeSessions: newActiveSessions });
-  },
-
-  isSessionActive: function isSessionActive(sessionId) {
-    return get().activeSessions.has(sessionId);
-  },
-
-  onStreamComplete: function onStreamComplete(callback) {
-    const state = get();
-    const newCallbacks = new Set(state.streamCompleteCallbacks);
-    newCallbacks.add(callback);
-    set({ streamCompleteCallbacks: newCallbacks });
-
-    return function unsubscribe() {
-      const currentState = get();
-      const cleanedCallbacks = new Set(currentState.streamCompleteCallbacks);
-      cleanedCallbacks.delete(callback);
-      set({ streamCompleteCallbacks: cleanedCallbacks });
-    };
-  },
-}));
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/chat-types.ts b/autogpt_platform/frontend/src/components/contextual/Chat/chat-types.ts
deleted file mode 100644
index 8c8aa7b704..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/chat-types.ts
+++ /dev/null
@@ -1,94 +0,0 @@
-import type { ToolArguments, ToolResult } from "@/types/chat";
-
-export type StreamStatus = "idle" | "streaming" | "completed" | "error";
-
-export interface StreamChunk {
-  type:
-    | "text_chunk"
-    | "text_ended"
-    | "tool_call"
-    | "tool_call_start"
-    | "tool_response"
-    | "login_needed"
-    | "need_login"
-    | "credentials_needed"
-    | "error"
-    | "usage"
-    | "stream_end";
-  timestamp?: string;
-  content?: string;
-  message?: string;
-  code?: string;
-  details?: Record<string, unknown>;
-  tool_id?: string;
-  tool_name?: string;
-  arguments?: ToolArguments;
-  result?: ToolResult;
-  success?: boolean;
-  idx?: number;
-  session_id?: string;
-  agent_info?: {
-    graph_id: string;
-    name: string;
-    trigger_type: string;
-  };
-  provider?: string;
-  provider_name?: string;
-  credential_type?: string;
-  scopes?: string[];
-  title?: string;
-  [key: string]: unknown;
-}
-
-export type VercelStreamChunk =
-  | { type: "start"; messageId: string }
-  | { type: "finish" }
-  | { type: "text-start"; id: string }
-  | { type: "text-delta"; id: string; delta: string }
-  | { type: "text-end"; id: string }
-  | { type: "tool-input-start"; toolCallId: string; toolName: string }
-  | {
-      type: "tool-input-available";
-      toolCallId: string;
-      toolName: string;
-      input: Record<string, unknown>;
-    }
-  | {
-      type: "tool-output-available";
-      toolCallId: string;
-      toolName?: string;
-      output: unknown;
-      success?: boolean;
-    }
-  | {
-      type: "usage";
-      promptTokens: number;
-      completionTokens: number;
-      totalTokens: number;
-    }
-  | {
-      type: "error";
-      errorText: string;
-      code?: string;
-      details?: Record<string, unknown>;
-    };
-
-export interface ActiveStream {
-  sessionId: string;
-  abortController: AbortController;
-  status: StreamStatus;
-  startedAt: number;
-  chunks: StreamChunk[];
-  error?: Error;
-  onChunkCallbacks: Set<(chunk: StreamChunk) => void>;
-}
-
-export interface StreamResult {
-  sessionId: string;
-  status: StreamStatus;
-  chunks: StreamChunk[];
-  completedAt: number;
-  error?: Error;
-}
-
-export type StreamCompleteCallback = (sessionId: string) => void;
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/AIChatBubble/AIChatBubble.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/AIChatBubble/AIChatBubble.tsx
deleted file mode 100644
index f5d56fcb15..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/AIChatBubble/AIChatBubble.tsx
+++ /dev/null
@@ -1,15 +0,0 @@
-import { cn } from "@/lib/utils";
-import { ReactNode } from "react";
-
-export interface AIChatBubbleProps {
-  children: ReactNode;
-  className?: string;
-}
-
-export function AIChatBubble({ children, className }: AIChatBubbleProps) {
-  return (
-    <div className={cn("text-left text-[1rem] leading-relaxed", className)}>
-      {children}
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentCarouselMessage/AgentCarouselMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentCarouselMessage/AgentCarouselMessage.tsx
deleted file mode 100644
index 582b24de5e..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentCarouselMessage/AgentCarouselMessage.tsx
+++ /dev/null
@@ -1,119 +0,0 @@
-import { Button } from "@/components/atoms/Button/Button";
-import { Card } from "@/components/atoms/Card/Card";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { ArrowRight, List, Robot } from "@phosphor-icons/react";
-import Image from "next/image";
-
-export interface Agent {
-  id: string;
-  name: string;
-  description: string;
-  version?: number;
-  image_url?: string;
-}
-
-export interface AgentCarouselMessageProps {
-  agents: Agent[];
-  totalCount?: number;
-  onSelectAgent?: (agentId: string) => void;
-  className?: string;
-}
-
-export function AgentCarouselMessage({
-  agents,
-  totalCount,
-  onSelectAgent,
-  className,
-}: AgentCarouselMessageProps) {
-  const displayCount = totalCount ?? agents.length;
-
-  return (
-    <div
-      className={cn(
-        "mx-4 my-2 flex flex-col gap-4 rounded-lg border border-purple-200 bg-purple-50 p-6",
-        className,
-      )}
-    >
-      {/* Header */}
-      <div className="flex items-center gap-3">
-        <div className="flex h-10 w-10 items-center justify-center rounded-full bg-purple-500">
-          <List size={24} weight="bold" className="text-white" />
-        </div>
-        <div>
-          <Text variant="h3" className="text-purple-900">
-            Found {displayCount} {displayCount === 1 ? "Agent" : "Agents"}
-          </Text>
-          <Text variant="small" className="text-purple-700">
-            Select an agent to view details or run it
-          </Text>
-        </div>
-      </div>
-
-      {/* Agent Cards */}
-      <div className="grid gap-3 sm:grid-cols-2">
-        {agents.map((agent) => (
-          <Card
-            key={agent.id}
-            className="border border-purple-200 bg-white p-4"
-          >
-            <div className="flex gap-3">
-              <div className="relative h-10 w-10 flex-shrink-0 overflow-hidden rounded-lg bg-purple-100">
-                {agent.image_url ? (
-                  <Image
-                    src={agent.image_url}
-                    alt={`${agent.name} preview image`}
-                    fill
-                    className="object-cover"
-                  />
-                ) : (
-                  <div className="flex h-full w-full items-center justify-center">
-                    <Robot
-                      size={20}
-                      weight="bold"
-                      className="text-purple-600"
-                    />
-                  </div>
-                )}
-              </div>
-              <div className="flex-1 space-y-2">
-                <div>
-                  <Text
-                    variant="body"
-                    className="font-semibold text-purple-900"
-                  >
-                    {agent.name}
-                  </Text>
-                  {agent.version && (
-                    <Text variant="small" className="text-purple-600">
-                      v{agent.version}
-                    </Text>
-                  )}
-                </div>
-                <Text variant="small" className="line-clamp-2 text-purple-700">
-                  {agent.description}
-                </Text>
-                {onSelectAgent && (
-                  <Button
-                    onClick={() => onSelectAgent(agent.id)}
-                    variant="ghost"
-                    className="mt-2 flex items-center gap-1 p-0 text-sm text-purple-600 hover:text-purple-800"
-                  >
-                    View details
-                    <ArrowRight size={16} weight="bold" />
-                  </Button>
-                )}
-              </div>
-            </div>
-          </Card>
-        ))}
-      </div>
-
-      {totalCount && totalCount > agents.length && (
-        <Text variant="small" className="text-center text-purple-600">
-          Showing {agents.length} of {totalCount} results
-        </Text>
-      )}
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentInputsSetup/AgentInputsSetup.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentInputsSetup/AgentInputsSetup.tsx
deleted file mode 100644
index 3ef71eca09..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentInputsSetup/AgentInputsSetup.tsx
+++ /dev/null
@@ -1,246 +0,0 @@
-"use client";
-
-import { Button } from "@/components/atoms/Button/Button";
-import { Card } from "@/components/atoms/Card/Card";
-import { Text } from "@/components/atoms/Text/Text";
-import { CredentialsInput } from "@/components/contextual/CredentialsInput/CredentialsInput";
-import { RunAgentInputs } from "@/components/contextual/RunAgentInputs/RunAgentInputs";
-
-import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent";
-import {
-  BlockIOCredentialsSubSchema,
-  BlockIOSubSchema,
-} from "@/lib/autogpt-server-api/types";
-import { cn, isEmpty } from "@/lib/utils";
-import { PlayIcon, WarningIcon } from "@phosphor-icons/react";
-import { useMemo } from "react";
-import { useAgentInputsSetup } from "./useAgentInputsSetup";
-
-type LibraryAgentInputSchemaProperties = LibraryAgent["input_schema"] extends {
-  properties: infer P;
-}
-  ? P extends Record<string, BlockIOSubSchema>
-    ? P
-    : Record<string, BlockIOSubSchema>
-  : Record<string, BlockIOSubSchema>;
-
-type LibraryAgentCredentialsInputSchemaProperties =
-  LibraryAgent["credentials_input_schema"] extends {
-    properties: infer P;
-  }
-    ? P extends Record<string, BlockIOCredentialsSubSchema>
-      ? P
-      : Record<string, BlockIOCredentialsSubSchema>
-    : Record<string, BlockIOCredentialsSubSchema>;
-
-interface Props {
-  agentName?: string;
-  inputSchema: LibraryAgentInputSchemaProperties | Record<string, any>;
-  credentialsSchema?:
-    | LibraryAgentCredentialsInputSchemaProperties
-    | Record<string, any>;
-  message: string;
-  requiredFields?: string[];
-  onRun: (
-    inputs: Record<string, any>,
-    credentials: Record<string, any>,
-  ) => void;
-  onCancel?: () => void;
-  className?: string;
-}
-
-export function AgentInputsSetup({
-  agentName,
-  inputSchema,
-  credentialsSchema,
-  message,
-  requiredFields,
-  onRun,
-  onCancel,
-  className,
-}: Props) {
-  const { inputValues, setInputValue, credentialsValues, setCredentialsValue } =
-    useAgentInputsSetup();
-
-  const inputSchemaObj = useMemo(() => {
-    if (!inputSchema) return { properties: {}, required: [] };
-    if ("properties" in inputSchema && "type" in inputSchema) {
-      return inputSchema as {
-        properties: Record<string, any>;
-        required?: string[];
-      };
-    }
-    return { properties: inputSchema as Record<string, any>, required: [] };
-  }, [inputSchema]);
-
-  const credentialsSchemaObj = useMemo(() => {
-    if (!credentialsSchema) return { properties: {}, required: [] };
-    if ("properties" in credentialsSchema && "type" in credentialsSchema) {
-      return credentialsSchema as {
-        properties: Record<string, any>;
-        required?: string[];
-      };
-    }
-    return {
-      properties: credentialsSchema as Record<string, any>,
-      required: [],
-    };
-  }, [credentialsSchema]);
-
-  const agentInputFields = useMemo(() => {
-    const properties = inputSchemaObj.properties || {};
-    return Object.fromEntries(
-      Object.entries(properties).filter(
-        ([_, subSchema]: [string, any]) => !subSchema.hidden,
-      ),
-    );
-  }, [inputSchemaObj]);
-
-  const agentCredentialsInputFields = useMemo(() => {
-    return credentialsSchemaObj.properties || {};
-  }, [credentialsSchemaObj]);
-
-  const inputFields = Object.entries(agentInputFields);
-  const credentialFields = Object.entries(agentCredentialsInputFields);
-
-  const defaultsFromSchema = useMemo(() => {
-    const defaults: Record<string, any> = {};
-    Object.entries(agentInputFields).forEach(([key, schema]) => {
-      if ("default" in schema && schema.default !== undefined) {
-        defaults[key] = schema.default;
-      }
-    });
-    return defaults;
-  }, [agentInputFields]);
-
-  const defaultsFromCredentialsSchema = useMemo(() => {
-    const defaults: Record<string, any> = {};
-    Object.entries(agentCredentialsInputFields).forEach(([key, schema]) => {
-      if ("default" in schema && schema.default !== undefined) {
-        defaults[key] = schema.default;
-      }
-    });
-    return defaults;
-  }, [agentCredentialsInputFields]);
-
-  const mergedInputValues = useMemo(() => {
-    return { ...defaultsFromSchema, ...inputValues };
-  }, [defaultsFromSchema, inputValues]);
-
-  const mergedCredentialsValues = useMemo(() => {
-    return { ...defaultsFromCredentialsSchema, ...credentialsValues };
-  }, [defaultsFromCredentialsSchema, credentialsValues]);
-
-  const allRequiredInputsAreSet = useMemo(() => {
-    const requiredInputs = new Set(
-      requiredFields || (inputSchemaObj.required as string[]) || [],
-    );
-    const nonEmptyInputs = new Set(
-      Object.keys(mergedInputValues).filter(
-        (k) => !isEmpty(mergedInputValues[k]),
-      ),
-    );
-    const missing = [...requiredInputs].filter(
-      (input) => !nonEmptyInputs.has(input),
-    );
-    return missing.length === 0;
-  }, [inputSchemaObj.required, mergedInputValues, requiredFields]);
-
-  const allCredentialsAreSet = useMemo(() => {
-    const requiredCredentials = new Set(
-      (credentialsSchemaObj.required as string[]) || [],
-    );
-    if (requiredCredentials.size === 0) {
-      return true;
-    }
-    const missing = [...requiredCredentials].filter((key) => {
-      const cred = mergedCredentialsValues[key];
-      return !cred || !cred.id;
-    });
-    return missing.length === 0;
-  }, [credentialsSchemaObj.required, mergedCredentialsValues]);
-
-  const canRun = allRequiredInputsAreSet && allCredentialsAreSet;
-
-  function handleRun() {
-    if (canRun) {
-      onRun(mergedInputValues, mergedCredentialsValues);
-    }
-  }
-
-  return (
-    <Card
-      className={cn(
-        "mx-4 my-2 overflow-hidden border-blue-200 bg-blue-50",
-        className,
-      )}
-    >
-      <div className="flex items-start gap-4 p-6">
-        <div className="flex h-12 w-12 flex-shrink-0 items-center justify-center rounded-full bg-blue-500">
-          <WarningIcon size={24} weight="bold" className="text-white" />
-        </div>
-        <div className="flex-1">
-          <Text variant="h3" className="mb-2 text-blue-900">
-            {agentName ? `Configure ${agentName}` : "Agent Configuration"}
-          </Text>
-          <Text variant="body" className="mb-4 text-blue-700">
-            {message}
-          </Text>
-
-          {inputFields.length > 0 && (
-            <div className="mb-4 space-y-4">
-              {inputFields.map(([key, inputSubSchema]) => (
-                <RunAgentInputs
-                  key={key}
-                  schema={inputSubSchema}
-                  value={inputValues[key] ?? inputSubSchema.default}
-                  placeholder={inputSubSchema.description}
-                  onChange={(value) => setInputValue(key, value)}
-                />
-              ))}
-            </div>
-          )}
-
-          {credentialFields.length > 0 && (
-            <div className="mb-4 space-y-4">
-              {credentialFields.map(([key, schema]) => {
-                const requiredCredentials = new Set(
-                  (credentialsSchemaObj.required as string[]) || [],
-                );
-                return (
-                  <CredentialsInput
-                    key={key}
-                    schema={schema}
-                    selectedCredentials={credentialsValues[key]}
-                    onSelectCredentials={(value) =>
-                      setCredentialsValue(key, value)
-                    }
-                    siblingInputs={mergedInputValues}
-                    isOptional={!requiredCredentials.has(key)}
-                  />
-                );
-              })}
-            </div>
-          )}
-
-          <div className="flex gap-2">
-            <Button
-              variant="primary"
-              size="small"
-              onClick={handleRun}
-              disabled={!canRun}
-            >
-              <PlayIcon className="mr-2 h-4 w-4" weight="bold" />
-              Run Agent
-            </Button>
-            {onCancel && (
-              <Button variant="outline" size="small" onClick={onCancel}>
-                Cancel
-              </Button>
-            )}
-          </div>
-        </div>
-      </div>
-    </Card>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentInputsSetup/useAgentInputsSetup.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentInputsSetup/useAgentInputsSetup.ts
deleted file mode 100644
index e36a3f3c5d..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/AgentInputsSetup/useAgentInputsSetup.ts
+++ /dev/null
@@ -1,38 +0,0 @@
-import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
-import { useState } from "react";
-
-export function useAgentInputsSetup() {
-  const [inputValues, setInputValues] = useState<Record<string, any>>({});
-  const [credentialsValues, setCredentialsValues] = useState<
-    Record<string, CredentialsMetaInput>
-  >({});
-
-  function setInputValue(key: string, value: any) {
-    setInputValues((prev) => ({
-      ...prev,
-      [key]: value,
-    }));
-  }
-
-  function setCredentialsValue(key: string, value?: CredentialsMetaInput) {
-    if (value) {
-      setCredentialsValues((prev) => ({
-        ...prev,
-        [key]: value,
-      }));
-    } else {
-      setCredentialsValues((prev) => {
-        const next = { ...prev };
-        delete next[key];
-        return next;
-      });
-    }
-  }
-
-  return {
-    inputValues,
-    setInputValue,
-    credentialsValues,
-    setCredentialsValue,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/AuthPromptWidget/AuthPromptWidget.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/AuthPromptWidget/AuthPromptWidget.tsx
deleted file mode 100644
index b2cf92ec56..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/AuthPromptWidget/AuthPromptWidget.tsx
+++ /dev/null
@@ -1,120 +0,0 @@
-"use client";
-
-import { Button } from "@/components/atoms/Button/Button";
-import { cn } from "@/lib/utils";
-import { ShieldIcon, SignInIcon, UserPlusIcon } from "@phosphor-icons/react";
-import { useRouter } from "next/navigation";
-
-export interface AuthPromptWidgetProps {
-  message: string;
-  sessionId: string;
-  agentInfo?: {
-    graph_id: string;
-    name: string;
-    trigger_type: string;
-  };
-  returnUrl?: string;
-  className?: string;
-}
-
-export function AuthPromptWidget({
-  message,
-  sessionId,
-  agentInfo,
-  returnUrl = "/copilot/chat",
-  className,
-}: AuthPromptWidgetProps) {
-  const router = useRouter();
-
-  function handleSignIn() {
-    if (typeof window !== "undefined") {
-      localStorage.setItem("pending_chat_session", sessionId);
-      if (agentInfo) {
-        localStorage.setItem("pending_agent_setup", JSON.stringify(agentInfo));
-      }
-    }
-    const returnUrlWithSession = `${returnUrl}?session_id=${sessionId}`;
-    const encodedReturnUrl = encodeURIComponent(returnUrlWithSession);
-    router.push(`/login?returnUrl=${encodedReturnUrl}`);
-  }
-
-  function handleSignUp() {
-    if (typeof window !== "undefined") {
-      localStorage.setItem("pending_chat_session", sessionId);
-      if (agentInfo) {
-        localStorage.setItem("pending_agent_setup", JSON.stringify(agentInfo));
-      }
-    }
-    const returnUrlWithSession = `${returnUrl}?session_id=${sessionId}`;
-    const encodedReturnUrl = encodeURIComponent(returnUrlWithSession);
-    router.push(`/signup?returnUrl=${encodedReturnUrl}`);
-  }
-
-  return (
-    <div
-      className={cn(
-        "my-4 overflow-hidden rounded-lg border border-violet-200",
-        "bg-gradient-to-br from-violet-50 to-purple-50",
-        "duration-500 animate-in fade-in-50 slide-in-from-bottom-2",
-        className,
-      )}
-    >
-      <div className="px-6 py-5">
-        <div className="mb-4 flex items-center gap-3">
-          <div className="flex h-10 w-10 items-center justify-center rounded-full bg-violet-600">
-            <ShieldIcon size={20} weight="fill" className="text-white" />
-          </div>
-          <div>
-            <h3 className="text-lg font-semibold text-neutral-900">
-              Authentication Required
-            </h3>
-            <p className="text-sm text-neutral-600">
-              Sign in to set up and manage agents
-            </p>
-          </div>
-        </div>
-
-        <div className="mb-5 rounded-md bg-white/50 p-4">
-          <p className="text-sm text-neutral-700">{message}</p>
-          {agentInfo && (
-            <div className="mt-3 text-xs text-neutral-600">
-              <p>
-                Ready to set up:{" "}
-                <span className="font-medium">{agentInfo.name}</span>
-              </p>
-              <p>
-                Type:{" "}
-                <span className="font-medium">{agentInfo.trigger_type}</span>
-              </p>
-            </div>
-          )}
-        </div>
-
-        <div className="flex gap-3">
-          <Button
-            onClick={handleSignIn}
-            variant="primary"
-            size="small"
-            className="flex-1"
-          >
-            <SignInIcon size={16} weight="bold" className="mr-2" />
-            Sign In
-          </Button>
-          <Button
-            onClick={handleSignUp}
-            variant="secondary"
-            size="small"
-            className="flex-1"
-          >
-            <UserPlusIcon size={16} weight="bold" className="mr-2" />
-            Create Account
-          </Button>
-        </div>
-
-        <div className="mt-4 text-center text-xs text-neutral-500">
-          Your chat session will be preserved after signing in
-        </div>
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/ChatContainer.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/ChatContainer.tsx
deleted file mode 100644
index dec221338a..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/ChatContainer.tsx
+++ /dev/null
@@ -1,130 +0,0 @@
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { Dialog } from "@/components/molecules/Dialog/Dialog";
-import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
-import { cn } from "@/lib/utils";
-import { GlobeHemisphereEastIcon } from "@phosphor-icons/react";
-import { useEffect } from "react";
-import { ChatInput } from "../ChatInput/ChatInput";
-import { MessageList } from "../MessageList/MessageList";
-import { useChatContainer } from "./useChatContainer";
-
-export interface ChatContainerProps {
-  sessionId: string | null;
-  initialMessages: SessionDetailResponse["messages"];
-  initialPrompt?: string;
-  className?: string;
-  onStreamingChange?: (isStreaming: boolean) => void;
-  onOperationStarted?: () => void;
-}
-
-export function ChatContainer({
-  sessionId,
-  initialMessages,
-  initialPrompt,
-  className,
-  onStreamingChange,
-  onOperationStarted,
-}: ChatContainerProps) {
-  const {
-    messages,
-    streamingChunks,
-    isStreaming,
-    stopStreaming,
-    isRegionBlockedModalOpen,
-    sendMessageWithContext,
-    handleRegionModalOpenChange,
-    handleRegionModalClose,
-  } = useChatContainer({
-    sessionId,
-    initialMessages,
-    initialPrompt,
-    onOperationStarted,
-  });
-
-  useEffect(() => {
-    onStreamingChange?.(isStreaming);
-  }, [isStreaming, onStreamingChange]);
-
-  const breakpoint = useBreakpoint();
-  const isMobile =
-    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
-
-  return (
-    <div
-      className={cn(
-        "mx-auto flex h-full min-h-0 w-full max-w-3xl flex-col bg-[#f8f8f9]",
-        className,
-      )}
-    >
-      <Dialog
-        title={
-          <div className="flex items-center gap-2">
-            <GlobeHemisphereEastIcon className="size-6" />
-            <Text
-              variant="body"
-              className="text-md font-poppins leading-none md:text-lg"
-            >
-              Service unavailable
-            </Text>
-          </div>
-        }
-        controlled={{
-          isOpen: isRegionBlockedModalOpen,
-          set: handleRegionModalOpenChange,
-        }}
-        onClose={handleRegionModalClose}
-        styling={{ maxWidth: 550, width: "100%", minWidth: "auto" }}
-      >
-        <Dialog.Content>
-          <div className="flex flex-col gap-8">
-            <Text variant="body">
-              The Autogpt AI model is not available in your region or your
-              connection is blocking it. Please try again with a different
-              connection.
-            </Text>
-            <div className="flex justify-center">
-              <Button
-                type="button"
-                variant="primary"
-                onClick={handleRegionModalClose}
-                className="w-full"
-              >
-                Got it
-              </Button>
-            </div>
-          </div>
-        </Dialog.Content>
-      </Dialog>
-      {/* Messages - Scrollable */}
-      <div className="relative flex min-h-0 flex-1 flex-col">
-        <div className="flex min-h-full flex-col justify-end">
-          <MessageList
-            messages={messages}
-            streamingChunks={streamingChunks}
-            isStreaming={isStreaming}
-            onSendMessage={sendMessageWithContext}
-            className="flex-1"
-          />
-        </div>
-      </div>
-
-      {/* Input - Fixed at bottom */}
-      <div className="relative px-3 pb-6 pt-2">
-        <div className="pointer-events-none absolute top-[-18px] z-10 h-6 w-full bg-gradient-to-b from-transparent to-[#f8f8f9]" />
-        <ChatInput
-          onSend={sendMessageWithContext}
-          disabled={isStreaming || !sessionId}
-          isStreaming={isStreaming}
-          onStop={stopStreaming}
-          placeholder={
-            isMobile
-              ? "You can search or just ask"
-              : 'You can search or just ask — e.g. "create a blog post outline"'
-          }
-        />
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/createStreamEventDispatcher.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/createStreamEventDispatcher.ts
deleted file mode 100644
index 82e9b05e88..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/createStreamEventDispatcher.ts
+++ /dev/null
@@ -1,86 +0,0 @@
-import { toast } from "sonner";
-import type { StreamChunk } from "../../chat-types";
-import type { HandlerDependencies } from "./handlers";
-import {
-  handleError,
-  handleLoginNeeded,
-  handleStreamEnd,
-  handleTextChunk,
-  handleTextEnded,
-  handleToolCallStart,
-  handleToolResponse,
-  isRegionBlockedError,
-} from "./handlers";
-
-export function createStreamEventDispatcher(
-  deps: HandlerDependencies,
-): (chunk: StreamChunk) => void {
-  return function dispatchStreamEvent(chunk: StreamChunk): void {
-    if (
-      chunk.type === "text_chunk" ||
-      chunk.type === "tool_call_start" ||
-      chunk.type === "tool_response" ||
-      chunk.type === "login_needed" ||
-      chunk.type === "need_login" ||
-      chunk.type === "error"
-    ) {
-      if (!deps.hasResponseRef.current) {
-        console.info("[ChatStream] First response chunk:", {
-          type: chunk.type,
-          sessionId: deps.sessionId,
-        });
-      }
-      deps.hasResponseRef.current = true;
-    }
-
-    switch (chunk.type) {
-      case "text_chunk":
-        handleTextChunk(chunk, deps);
-        break;
-
-      case "text_ended":
-        handleTextEnded(chunk, deps);
-        break;
-
-      case "tool_call_start":
-        handleToolCallStart(chunk, deps);
-        break;
-
-      case "tool_response":
-        handleToolResponse(chunk, deps);
-        break;
-
-      case "login_needed":
-      case "need_login":
-        handleLoginNeeded(chunk, deps);
-        break;
-
-      case "stream_end":
-        console.info("[ChatStream] Stream ended:", {
-          sessionId: deps.sessionId,
-          hasResponse: deps.hasResponseRef.current,
-          chunkCount: deps.streamingChunksRef.current.length,
-        });
-        handleStreamEnd(chunk, deps);
-        break;
-
-      case "error":
-        const isRegionBlocked = isRegionBlockedError(chunk);
-        handleError(chunk, deps);
-        // Show toast at dispatcher level to avoid circular dependencies
-        if (!isRegionBlocked) {
-          toast.error("Chat Error", {
-            description: chunk.message || chunk.content || "An error occurred",
-          });
-        }
-        break;
-
-      case "usage":
-        // TODO: Handle usage for display
-        break;
-
-      default:
-        console.warn("Unknown stream chunk type:", chunk);
-    }
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/handlers.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/handlers.ts
deleted file mode 100644
index f3cac01f96..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/handlers.ts
+++ /dev/null
@@ -1,256 +0,0 @@
-import type { Dispatch, MutableRefObject, SetStateAction } from "react";
-import { StreamChunk } from "../../useChatStream";
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-import {
-  extractCredentialsNeeded,
-  extractInputsNeeded,
-  parseToolResponse,
-} from "./helpers";
-
-function isToolCallMessage(
-  message: ChatMessageData,
-): message is Extract<ChatMessageData, { type: "tool_call" }> {
-  return message.type === "tool_call";
-}
-
-export interface HandlerDependencies {
-  setHasTextChunks: Dispatch<SetStateAction<boolean>>;
-  setStreamingChunks: Dispatch<SetStateAction<string[]>>;
-  streamingChunksRef: MutableRefObject<string[]>;
-  hasResponseRef: MutableRefObject<boolean>;
-  setMessages: Dispatch<SetStateAction<ChatMessageData[]>>;
-  setIsStreamingInitiated: Dispatch<SetStateAction<boolean>>;
-  setIsRegionBlockedModalOpen: Dispatch<SetStateAction<boolean>>;
-  sessionId: string;
-  onOperationStarted?: () => void;
-}
-
-export function isRegionBlockedError(chunk: StreamChunk): boolean {
-  if (chunk.code === "MODEL_NOT_AVAILABLE_REGION") return true;
-  const message = chunk.message || chunk.content;
-  if (typeof message !== "string") return false;
-  return message.toLowerCase().includes("not available in your region");
-}
-
-export function handleTextChunk(chunk: StreamChunk, deps: HandlerDependencies) {
-  if (!chunk.content) return;
-  deps.setHasTextChunks(true);
-  deps.setStreamingChunks((prev) => {
-    const updated = [...prev, chunk.content!];
-    deps.streamingChunksRef.current = updated;
-    return updated;
-  });
-}
-
-export function handleTextEnded(
-  _chunk: StreamChunk,
-  deps: HandlerDependencies,
-) {
-  const completedText = deps.streamingChunksRef.current.join("");
-  if (completedText.trim()) {
-    deps.setMessages((prev) => {
-      // Check if this exact message already exists to prevent duplicates
-      const exists = prev.some(
-        (msg) =>
-          msg.type === "message" &&
-          msg.role === "assistant" &&
-          msg.content === completedText,
-      );
-      if (exists) return prev;
-
-      const assistantMessage: ChatMessageData = {
-        type: "message",
-        role: "assistant",
-        content: completedText,
-        timestamp: new Date(),
-      };
-      return [...prev, assistantMessage];
-    });
-  }
-  deps.setStreamingChunks([]);
-  deps.streamingChunksRef.current = [];
-  deps.setHasTextChunks(false);
-}
-
-export function handleToolCallStart(
-  chunk: StreamChunk,
-  deps: HandlerDependencies,
-) {
-  const toolCallMessage: Extract<ChatMessageData, { type: "tool_call" }> = {
-    type: "tool_call",
-    toolId: chunk.tool_id || `tool-${Date.now()}-${chunk.idx || 0}`,
-    toolName: chunk.tool_name || "Executing",
-    arguments: chunk.arguments || {},
-    timestamp: new Date(),
-  };
-
-  function updateToolCallMessages(prev: ChatMessageData[]) {
-    const existingIndex = prev.findIndex(function findToolCallIndex(msg) {
-      return isToolCallMessage(msg) && msg.toolId === toolCallMessage.toolId;
-    });
-    if (existingIndex === -1) {
-      return [...prev, toolCallMessage];
-    }
-    const nextMessages = [...prev];
-    const existing = nextMessages[existingIndex];
-    if (!isToolCallMessage(existing)) return prev;
-    const nextArguments =
-      toolCallMessage.arguments &&
-      Object.keys(toolCallMessage.arguments).length > 0
-        ? toolCallMessage.arguments
-        : existing.arguments;
-    nextMessages[existingIndex] = {
-      ...existing,
-      toolName: toolCallMessage.toolName || existing.toolName,
-      arguments: nextArguments,
-      timestamp: toolCallMessage.timestamp,
-    };
-    return nextMessages;
-  }
-
-  deps.setMessages(updateToolCallMessages);
-}
-
-export function handleToolResponse(
-  chunk: StreamChunk,
-  deps: HandlerDependencies,
-) {
-  let toolName = chunk.tool_name || "unknown";
-  if (!chunk.tool_name || chunk.tool_name === "unknown") {
-    deps.setMessages((prev) => {
-      const matchingToolCall = [...prev]
-        .reverse()
-        .find(
-          (msg) => msg.type === "tool_call" && msg.toolId === chunk.tool_id,
-        );
-      if (matchingToolCall && matchingToolCall.type === "tool_call") {
-        toolName = matchingToolCall.toolName;
-      }
-      return prev;
-    });
-  }
-  const responseMessage = parseToolResponse(
-    chunk.result!,
-    chunk.tool_id!,
-    toolName,
-    new Date(),
-  );
-  if (!responseMessage) {
-    let parsedResult: Record<string, unknown> | null = null;
-    try {
-      parsedResult =
-        typeof chunk.result === "string"
-          ? JSON.parse(chunk.result)
-          : (chunk.result as Record<string, unknown>);
-    } catch {
-      parsedResult = null;
-    }
-    if (
-      (chunk.tool_name === "run_agent" || chunk.tool_name === "run_block") &&
-      chunk.success &&
-      parsedResult?.type === "setup_requirements"
-    ) {
-      const inputsMessage = extractInputsNeeded(parsedResult, chunk.tool_name);
-      if (inputsMessage) {
-        deps.setMessages((prev) => [...prev, inputsMessage]);
-      }
-      const credentialsMessage = extractCredentialsNeeded(
-        parsedResult,
-        chunk.tool_name,
-      );
-      if (credentialsMessage) {
-        deps.setMessages((prev) => [...prev, credentialsMessage]);
-      }
-    }
-    return;
-  }
-  // Trigger polling when operation_started is received
-  if (responseMessage.type === "operation_started") {
-    deps.onOperationStarted?.();
-  }
-
-  deps.setMessages((prev) => {
-    const toolCallIndex = prev.findIndex(
-      (msg) => msg.type === "tool_call" && msg.toolId === chunk.tool_id,
-    );
-    const hasResponse = prev.some(
-      (msg) => msg.type === "tool_response" && msg.toolId === chunk.tool_id,
-    );
-    if (hasResponse) return prev;
-    if (toolCallIndex !== -1) {
-      const newMessages = [...prev];
-      newMessages.splice(toolCallIndex + 1, 0, responseMessage);
-      return newMessages;
-    }
-    return [...prev, responseMessage];
-  });
-}
-
-export function handleLoginNeeded(
-  chunk: StreamChunk,
-  deps: HandlerDependencies,
-) {
-  const loginNeededMessage: ChatMessageData = {
-    type: "login_needed",
-    toolName: "login_needed",
-    message: chunk.message || "Please sign in to use chat and agent features",
-    sessionId: chunk.session_id || deps.sessionId,
-    agentInfo: chunk.agent_info,
-    timestamp: new Date(),
-  };
-  deps.setMessages((prev) => [...prev, loginNeededMessage]);
-}
-
-export function handleStreamEnd(
-  _chunk: StreamChunk,
-  deps: HandlerDependencies,
-) {
-  const completedContent = deps.streamingChunksRef.current.join("");
-  if (!completedContent.trim() && !deps.hasResponseRef.current) {
-    deps.setMessages((prev) => [
-      ...prev,
-      {
-        type: "message",
-        role: "assistant",
-        content: "No response received. Please try again.",
-        timestamp: new Date(),
-      },
-    ]);
-  }
-  if (completedContent.trim()) {
-    deps.setMessages((prev) => {
-      // Check if this exact message already exists to prevent duplicates
-      const exists = prev.some(
-        (msg) =>
-          msg.type === "message" &&
-          msg.role === "assistant" &&
-          msg.content === completedContent,
-      );
-      if (exists) return prev;
-
-      const assistantMessage: ChatMessageData = {
-        type: "message",
-        role: "assistant",
-        content: completedContent,
-        timestamp: new Date(),
-      };
-      return [...prev, assistantMessage];
-    });
-  }
-  deps.setStreamingChunks([]);
-  deps.streamingChunksRef.current = [];
-  deps.setHasTextChunks(false);
-  deps.setIsStreamingInitiated(false);
-}
-
-export function handleError(chunk: StreamChunk, deps: HandlerDependencies) {
-  const errorMessage = chunk.message || chunk.content || "An error occurred";
-  console.error("Stream error:", errorMessage);
-  if (isRegionBlockedError(chunk)) {
-    deps.setIsRegionBlockedModalOpen(true);
-  }
-  deps.setIsStreamingInitiated(false);
-  deps.setHasTextChunks(false);
-  deps.setStreamingChunks([]);
-  deps.streamingChunksRef.current = [];
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/helpers.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/helpers.ts
deleted file mode 100644
index e744c9bc34..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/helpers.ts
+++ /dev/null
@@ -1,606 +0,0 @@
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { SessionKey, sessionStorage } from "@/services/storage/session-storage";
-import type { ToolResult } from "@/types/chat";
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-
-export function processInitialMessages(
-  initialMessages: SessionDetailResponse["messages"],
-): ChatMessageData[] {
-  const processedMessages: ChatMessageData[] = [];
-  const toolCallMap = new Map<string, string>();
-
-  for (const msg of initialMessages) {
-    if (!isValidMessage(msg)) {
-      console.warn("Invalid message structure from backend:", msg);
-      continue;
-    }
-
-    let content = String(msg.content || "");
-    const role = String(msg.role || "assistant").toLowerCase();
-    const toolCalls = msg.tool_calls;
-    const timestamp = msg.timestamp
-      ? new Date(msg.timestamp as string)
-      : undefined;
-
-    if (role === "user") {
-      content = removePageContext(content);
-      if (!content.trim()) continue;
-      processedMessages.push({
-        type: "message",
-        role: "user",
-        content,
-        timestamp,
-      });
-      continue;
-    }
-
-    if (role === "assistant") {
-      content = content
-        .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
-        .replace(/<internal_reasoning>[\s\S]*?<\/internal_reasoning>/gi, "")
-        .trim();
-
-      if (toolCalls && isToolCallArray(toolCalls) && toolCalls.length > 0) {
-        for (const toolCall of toolCalls) {
-          const toolName = toolCall.function.name;
-          const toolId = toolCall.id;
-          toolCallMap.set(toolId, toolName);
-
-          try {
-            const args = JSON.parse(toolCall.function.arguments || "{}");
-            processedMessages.push({
-              type: "tool_call",
-              toolId,
-              toolName,
-              arguments: args,
-              timestamp,
-            });
-          } catch (err) {
-            console.warn("Failed to parse tool call arguments:", err);
-            processedMessages.push({
-              type: "tool_call",
-              toolId,
-              toolName,
-              arguments: {},
-              timestamp,
-            });
-          }
-        }
-        if (content.trim()) {
-          processedMessages.push({
-            type: "message",
-            role: "assistant",
-            content,
-            timestamp,
-          });
-        }
-      } else if (content.trim()) {
-        processedMessages.push({
-          type: "message",
-          role: "assistant",
-          content,
-          timestamp,
-        });
-      }
-      continue;
-    }
-
-    if (role === "tool") {
-      const toolCallId = (msg.tool_call_id as string) || "";
-      const toolName = toolCallMap.get(toolCallId) || "unknown";
-      const toolResponse = parseToolResponse(
-        content,
-        toolCallId,
-        toolName,
-        timestamp,
-      );
-      if (toolResponse) {
-        processedMessages.push(toolResponse);
-      }
-      continue;
-    }
-
-    if (content.trim()) {
-      processedMessages.push({
-        type: "message",
-        role: role as "user" | "assistant" | "system",
-        content,
-        timestamp,
-      });
-    }
-  }
-
-  return processedMessages;
-}
-
-export function hasSentInitialPrompt(sessionId: string): boolean {
-  try {
-    const sent = JSON.parse(
-      sessionStorage.get(SessionKey.CHAT_SENT_INITIAL_PROMPTS) || "{}",
-    );
-    return sent[sessionId] === true;
-  } catch {
-    return false;
-  }
-}
-
-export function markInitialPromptSent(sessionId: string): void {
-  try {
-    const sent = JSON.parse(
-      sessionStorage.get(SessionKey.CHAT_SENT_INITIAL_PROMPTS) || "{}",
-    );
-    sent[sessionId] = true;
-    sessionStorage.set(
-      SessionKey.CHAT_SENT_INITIAL_PROMPTS,
-      JSON.stringify(sent),
-    );
-  } catch {
-    // Ignore storage errors
-  }
-}
-
-export function removePageContext(content: string): string {
-  // Remove "Page URL: ..." pattern at start of line (case insensitive, handles various formats)
-  let cleaned = content.replace(/^\s*Page URL:\s*[^\n\r]*/gim, "");
-
-  // Find "User Message:" marker at start of line to preserve the actual user message
-  const userMessageMatch = cleaned.match(/^\s*User Message:\s*([\s\S]*)$/im);
-  if (userMessageMatch) {
-    // If we found "User Message:", extract everything after it
-    cleaned = userMessageMatch[1];
-  } else {
-    // If no "User Message:" marker, remove "Page Content:" and everything after it at start of line
-    cleaned = cleaned.replace(/^\s*Page Content:[\s\S]*$/gim, "");
-  }
-
-  // Clean up extra whitespace and newlines
-  cleaned = cleaned.replace(/\n\s*\n\s*\n+/g, "\n\n").trim();
-  return cleaned;
-}
-
-export function createUserMessage(content: string): ChatMessageData {
-  return {
-    type: "message",
-    role: "user",
-    content,
-    timestamp: new Date(),
-  };
-}
-
-export function filterAuthMessages(
-  messages: ChatMessageData[],
-): ChatMessageData[] {
-  return messages.filter(
-    (msg) => msg.type !== "credentials_needed" && msg.type !== "login_needed",
-  );
-}
-
-export function isValidMessage(msg: unknown): msg is Record<string, unknown> {
-  if (typeof msg !== "object" || msg === null) {
-    return false;
-  }
-  const m = msg as Record<string, unknown>;
-  if (typeof m.role !== "string") {
-    return false;
-  }
-  if (m.content !== undefined && typeof m.content !== "string") {
-    return false;
-  }
-  return true;
-}
-
-export function isToolCallArray(value: unknown): value is Array<{
-  id: string;
-  type: string;
-  function: { name: string; arguments: string };
-}> {
-  if (!Array.isArray(value)) {
-    return false;
-  }
-  return value.every(
-    (item) =>
-      typeof item === "object" &&
-      item !== null &&
-      "id" in item &&
-      typeof item.id === "string" &&
-      "type" in item &&
-      typeof item.type === "string" &&
-      "function" in item &&
-      typeof item.function === "object" &&
-      item.function !== null &&
-      "name" in item.function &&
-      typeof item.function.name === "string" &&
-      "arguments" in item.function &&
-      typeof item.function.arguments === "string",
-  );
-}
-
-export function isAgentArray(value: unknown): value is Array<{
-  id: string;
-  name: string;
-  description: string;
-  version?: number;
-  image_url?: string;
-}> {
-  if (!Array.isArray(value)) {
-    return false;
-  }
-  return value.every(
-    (item) =>
-      typeof item === "object" &&
-      item !== null &&
-      "id" in item &&
-      typeof item.id === "string" &&
-      "name" in item &&
-      typeof item.name === "string" &&
-      "description" in item &&
-      typeof item.description === "string" &&
-      (!("version" in item) || typeof item.version === "number") &&
-      (!("image_url" in item) || typeof item.image_url === "string"),
-  );
-}
-
-export function extractJsonFromErrorMessage(
-  message: string,
-): Record<string, unknown> | null {
-  try {
-    const start = message.indexOf("{");
-    if (start === -1) {
-      return null;
-    }
-    let depth = 0;
-    let end = -1;
-    for (let i = start; i < message.length; i++) {
-      const ch = message[i];
-      if (ch === "{") {
-        depth++;
-      } else if (ch === "}") {
-        depth--;
-        if (depth === 0) {
-          end = i;
-          break;
-        }
-      }
-    }
-    if (end === -1) {
-      return null;
-    }
-    const jsonStr = message.slice(start, end + 1);
-    return JSON.parse(jsonStr) as Record<string, unknown>;
-  } catch {
-    return null;
-  }
-}
-
-export function parseToolResponse(
-  result: ToolResult,
-  toolId: string,
-  toolName: string,
-  timestamp?: Date,
-): ChatMessageData | null {
-  let parsedResult: Record<string, unknown> | null = null;
-  try {
-    parsedResult =
-      typeof result === "string"
-        ? JSON.parse(result)
-        : (result as Record<string, unknown>);
-  } catch {
-    parsedResult = null;
-  }
-  if (parsedResult && typeof parsedResult === "object") {
-    const responseType = parsedResult.type as string | undefined;
-    if (responseType === "no_results") {
-      return {
-        type: "tool_response",
-        toolId,
-        toolName,
-        result: (parsedResult.message as string) || "No results found",
-        success: true,
-        timestamp: timestamp || new Date(),
-      };
-    }
-    if (responseType === "agent_carousel") {
-      const agentsData = parsedResult.agents;
-      if (isAgentArray(agentsData)) {
-        return {
-          type: "agent_carousel",
-          toolId,
-          toolName: "agent_carousel",
-          agents: agentsData,
-          totalCount: parsedResult.total_count as number | undefined,
-          timestamp: timestamp || new Date(),
-        };
-      } else {
-        console.warn("Invalid agents array in agent_carousel response");
-      }
-    }
-    if (responseType === "execution_started") {
-      return {
-        type: "execution_started",
-        toolId,
-        toolName: "execution_started",
-        executionId: (parsedResult.execution_id as string) || "",
-        agentName: (parsedResult.graph_name as string) || undefined,
-        message: parsedResult.message as string | undefined,
-        libraryAgentLink: parsedResult.library_agent_link as string | undefined,
-        timestamp: timestamp || new Date(),
-      };
-    }
-    if (responseType === "clarification_needed") {
-      return {
-        type: "clarification_needed",
-        toolName,
-        questions:
-          (parsedResult.questions as Array<{
-            question: string;
-            keyword: string;
-            example?: string;
-          }>) || [],
-        message:
-          (parsedResult.message as string) ||
-          "I need more information to proceed.",
-        sessionId: (parsedResult.session_id as string) || "",
-        timestamp: timestamp || new Date(),
-      };
-    }
-    if (responseType === "operation_started") {
-      return {
-        type: "operation_started",
-        toolName: (parsedResult.tool_name as string) || toolName,
-        toolId,
-        operationId: (parsedResult.operation_id as string) || "",
-        message:
-          (parsedResult.message as string) ||
-          "Operation started. You can close this tab.",
-        timestamp: timestamp || new Date(),
-      };
-    }
-    if (responseType === "operation_pending") {
-      return {
-        type: "operation_pending",
-        toolName: (parsedResult.tool_name as string) || toolName,
-        toolId,
-        operationId: (parsedResult.operation_id as string) || "",
-        message:
-          (parsedResult.message as string) ||
-          "Operation in progress. Please wait...",
-        timestamp: timestamp || new Date(),
-      };
-    }
-    if (responseType === "operation_in_progress") {
-      return {
-        type: "operation_in_progress",
-        toolName: (parsedResult.tool_name as string) || toolName,
-        toolCallId: (parsedResult.tool_call_id as string) || toolId,
-        message:
-          (parsedResult.message as string) ||
-          "Operation already in progress. Please wait...",
-        timestamp: timestamp || new Date(),
-      };
-    }
-    if (responseType === "need_login") {
-      return {
-        type: "login_needed",
-        toolName: "login_needed",
-        message:
-          (parsedResult.message as string) ||
-          "Please sign in to use chat and agent features",
-        sessionId: (parsedResult.session_id as string) || "",
-        agentInfo: parsedResult.agent_info as
-          | {
-              graph_id: string;
-              name: string;
-              trigger_type: string;
-            }
-          | undefined,
-        timestamp: timestamp || new Date(),
-      };
-    }
-    if (responseType === "setup_requirements") {
-      return null;
-    }
-    if (responseType === "understanding_updated") {
-      return {
-        type: "tool_response",
-        toolId,
-        toolName,
-        result: (parsedResult || result) as ToolResult,
-        success: true,
-        timestamp: timestamp || new Date(),
-      };
-    }
-  }
-  return {
-    type: "tool_response",
-    toolId,
-    toolName,
-    result: parsedResult ? (parsedResult as ToolResult) : result,
-    success: true,
-    timestamp: timestamp || new Date(),
-  };
-}
-
-export function isUserReadiness(
-  value: unknown,
-): value is { missing_credentials?: Record<string, unknown> } {
-  return (
-    typeof value === "object" &&
-    value !== null &&
-    (!("missing_credentials" in value) ||
-      typeof (value as any).missing_credentials === "object")
-  );
-}
-
-export function isMissingCredentials(
-  value: unknown,
-): value is Record<string, Record<string, unknown>> {
-  if (typeof value !== "object" || value === null) {
-    return false;
-  }
-  return Object.values(value).every((v) => typeof v === "object" && v !== null);
-}
-
-export function isSetupInfo(value: unknown): value is {
-  user_readiness?: Record<string, unknown>;
-  agent_name?: string;
-} {
-  return (
-    typeof value === "object" &&
-    value !== null &&
-    (!("user_readiness" in value) ||
-      typeof (value as any).user_readiness === "object") &&
-    (!("agent_name" in value) || typeof (value as any).agent_name === "string")
-  );
-}
-
-export function extractCredentialsNeeded(
-  parsedResult: Record<string, unknown>,
-  toolName: string = "run_agent",
-): ChatMessageData | null {
-  try {
-    const setupInfo = parsedResult?.setup_info as
-      | Record<string, unknown>
-      | undefined;
-    const userReadiness = setupInfo?.user_readiness as
-      | Record<string, unknown>
-      | undefined;
-    const missingCreds = userReadiness?.missing_credentials as
-      | Record<string, Record<string, unknown>>
-      | undefined;
-    if (missingCreds && Object.keys(missingCreds).length > 0) {
-      const agentName = (setupInfo?.agent_name as string) || "this block";
-      const credentials = Object.values(missingCreds).map((credInfo) => {
-        // Normalize to array at boundary - prefer 'types' array, fall back to single 'type'
-        const typesArray = credInfo.types as
-          | Array<"api_key" | "oauth2" | "user_password" | "host_scoped">
-          | undefined;
-        const singleType =
-          (credInfo.type as
-            | "api_key"
-            | "oauth2"
-            | "user_password"
-            | "host_scoped"
-            | undefined) || "api_key";
-        const credentialTypes =
-          typesArray && typesArray.length > 0 ? typesArray : [singleType];
-
-        return {
-          provider: (credInfo.provider as string) || "unknown",
-          providerName:
-            (credInfo.provider_name as string) ||
-            (credInfo.provider as string) ||
-            "Unknown Provider",
-          credentialTypes,
-          title:
-            (credInfo.title as string) ||
-            `${(credInfo.provider_name as string) || (credInfo.provider as string)} credentials`,
-          scopes: credInfo.scopes as string[] | undefined,
-        };
-      });
-      return {
-        type: "credentials_needed",
-        toolName,
-        credentials,
-        message: `To run ${agentName}, you need to add ${credentials.length === 1 ? "credentials" : `${credentials.length} credentials`}.`,
-        agentName,
-        timestamp: new Date(),
-      };
-    }
-    return null;
-  } catch (err) {
-    console.error("Failed to extract credentials from setup info:", err);
-    return null;
-  }
-}
-
-export function extractInputsNeeded(
-  parsedResult: Record<string, unknown>,
-  toolName: string = "run_agent",
-): ChatMessageData | null {
-  try {
-    const setupInfo = parsedResult?.setup_info as
-      | Record<string, unknown>
-      | undefined;
-    const requirements = setupInfo?.requirements as
-      | Record<string, unknown>
-      | undefined;
-    const inputs = requirements?.inputs as
-      | Array<Record<string, unknown>>
-      | undefined;
-    const credentials = requirements?.credentials as
-      | Array<Record<string, unknown>>
-      | undefined;
-
-    if (!inputs || inputs.length === 0) {
-      return null;
-    }
-
-    const agentName = (setupInfo?.agent_name as string) || "this agent";
-    const agentId = parsedResult?.graph_id as string | undefined;
-    const graphVersion = parsedResult?.graph_version as number | undefined;
-
-    const properties: Record<string, any> = {};
-    const requiredProps: string[] = [];
-    inputs.forEach((input) => {
-      const name = input.name as string;
-      if (name) {
-        properties[name] = {
-          title: input.name as string,
-          description: (input.description as string) || "",
-          type: (input.type as string) || "string",
-          default: input.default,
-          enum: input.options,
-          format: input.format,
-        };
-        if ((input.required as boolean) === true) {
-          requiredProps.push(name);
-        }
-      }
-    });
-
-    const inputSchema: Record<string, any> = {
-      type: "object",
-      properties,
-    };
-    if (requiredProps.length > 0) {
-      inputSchema.required = requiredProps;
-    }
-
-    const credentialsSchema: Record<string, any> = {};
-    if (credentials && credentials.length > 0) {
-      credentials.forEach((cred) => {
-        const id = cred.id as string;
-        if (id) {
-          const credentialTypes = Array.isArray(cred.types)
-            ? cred.types
-            : [(cred.type as string) || "api_key"];
-          credentialsSchema[id] = {
-            type: "object",
-            properties: {},
-            credentials_provider: [cred.provider as string],
-            credentials_types: credentialTypes,
-            credentials_scopes: cred.scopes as string[] | undefined,
-          };
-        }
-      });
-    }
-
-    return {
-      type: "inputs_needed",
-      toolName,
-      agentName,
-      agentId,
-      graphVersion,
-      inputSchema,
-      credentialsSchema:
-        Object.keys(credentialsSchema).length > 0
-          ? credentialsSchema
-          : undefined,
-      message: `Please provide the required inputs to run ${agentName}.`,
-      timestamp: new Date(),
-    };
-  } catch (err) {
-    console.error("Failed to extract inputs from setup info:", err);
-    return null;
-  }
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/useChatContainer.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/useChatContainer.ts
deleted file mode 100644
index 46f384d055..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/useChatContainer.ts
+++ /dev/null
@@ -1,306 +0,0 @@
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { useEffect, useMemo, useRef, useState } from "react";
-import { useChatStore } from "../../chat-store";
-import { toast } from "sonner";
-import { useChatStream } from "../../useChatStream";
-import { usePageContext } from "../../usePageContext";
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-import { createStreamEventDispatcher } from "./createStreamEventDispatcher";
-import {
-  createUserMessage,
-  filterAuthMessages,
-  hasSentInitialPrompt,
-  markInitialPromptSent,
-  processInitialMessages,
-} from "./helpers";
-
-// Helper to generate deduplication key for a message
-function getMessageKey(msg: ChatMessageData): string {
-  if (msg.type === "message") {
-    // Don't include timestamp - dedupe by role + content only
-    // This handles the case where local and server timestamps differ
-    // Server messages are authoritative, so duplicates from local state are filtered
-    return `msg:${msg.role}:${msg.content}`;
-  } else if (msg.type === "tool_call") {
-    return `toolcall:${msg.toolId}`;
-  } else if (msg.type === "tool_response") {
-    return `toolresponse:${(msg as any).toolId}`;
-  } else if (
-    msg.type === "operation_started" ||
-    msg.type === "operation_pending" ||
-    msg.type === "operation_in_progress"
-  ) {
-    return `op:${(msg as any).toolId || (msg as any).operationId || (msg as any).toolCallId || ""}:${msg.toolName}`;
-  } else {
-    return `${msg.type}:${JSON.stringify(msg).slice(0, 100)}`;
-  }
-}
-
-interface Args {
-  sessionId: string | null;
-  initialMessages: SessionDetailResponse["messages"];
-  initialPrompt?: string;
-  onOperationStarted?: () => void;
-}
-
-export function useChatContainer({
-  sessionId,
-  initialMessages,
-  initialPrompt,
-  onOperationStarted,
-}: Args) {
-  const [messages, setMessages] = useState<ChatMessageData[]>([]);
-  const [streamingChunks, setStreamingChunks] = useState<string[]>([]);
-  const [hasTextChunks, setHasTextChunks] = useState(false);
-  const [isStreamingInitiated, setIsStreamingInitiated] = useState(false);
-  const [isRegionBlockedModalOpen, setIsRegionBlockedModalOpen] =
-    useState(false);
-  const hasResponseRef = useRef(false);
-  const streamingChunksRef = useRef<string[]>([]);
-  const previousSessionIdRef = useRef<string | null>(null);
-  const {
-    error,
-    sendMessage: sendStreamMessage,
-    stopStreaming,
-  } = useChatStream();
-  const activeStreams = useChatStore((s) => s.activeStreams);
-  const subscribeToStream = useChatStore((s) => s.subscribeToStream);
-  const isStreaming = isStreamingInitiated || hasTextChunks;
-
-  useEffect(
-    function handleSessionChange() {
-      if (sessionId === previousSessionIdRef.current) return;
-
-      const prevSession = previousSessionIdRef.current;
-      if (prevSession) {
-        stopStreaming(prevSession);
-      }
-      previousSessionIdRef.current = sessionId;
-      setMessages([]);
-      setStreamingChunks([]);
-      streamingChunksRef.current = [];
-      setHasTextChunks(false);
-      setIsStreamingInitiated(false);
-      hasResponseRef.current = false;
-
-      if (!sessionId) return;
-
-      const activeStream = activeStreams.get(sessionId);
-      if (!activeStream || activeStream.status !== "streaming") return;
-
-      const dispatcher = createStreamEventDispatcher({
-        setHasTextChunks,
-        setStreamingChunks,
-        streamingChunksRef,
-        hasResponseRef,
-        setMessages,
-        setIsRegionBlockedModalOpen,
-        sessionId,
-        setIsStreamingInitiated,
-        onOperationStarted,
-      });
-
-      setIsStreamingInitiated(true);
-      const skipReplay = initialMessages.length > 0;
-      return subscribeToStream(sessionId, dispatcher, skipReplay);
-    },
-    [
-      sessionId,
-      stopStreaming,
-      activeStreams,
-      subscribeToStream,
-      onOperationStarted,
-    ],
-  );
-
-  // Collect toolIds from completed tool results in initialMessages
-  // Used to filter out operation messages when their results arrive
-  const completedToolIds = useMemo(() => {
-    const processedInitial = processInitialMessages(initialMessages);
-    const ids = new Set<string>();
-    for (const msg of processedInitial) {
-      if (
-        msg.type === "tool_response" ||
-        msg.type === "agent_carousel" ||
-        msg.type === "execution_started"
-      ) {
-        const toolId = (msg as any).toolId;
-        if (toolId) {
-          ids.add(toolId);
-        }
-      }
-    }
-    return ids;
-  }, [initialMessages]);
-
-  // Clean up local operation messages when their completed results arrive from polling
-  // This effect runs when completedToolIds changes (i.e., when polling brings new results)
-  useEffect(
-    function cleanupCompletedOperations() {
-      if (completedToolIds.size === 0) return;
-
-      setMessages((prev) => {
-        const filtered = prev.filter((msg) => {
-          if (
-            msg.type === "operation_started" ||
-            msg.type === "operation_pending" ||
-            msg.type === "operation_in_progress"
-          ) {
-            const toolId = (msg as any).toolId || (msg as any).toolCallId;
-            if (toolId && completedToolIds.has(toolId)) {
-              return false; // Remove - operation completed
-            }
-          }
-          return true;
-        });
-        // Only update state if something was actually filtered
-        return filtered.length === prev.length ? prev : filtered;
-      });
-    },
-    [completedToolIds],
-  );
-
-  // Combine initial messages from backend with local streaming messages,
-  // Server messages maintain correct order; only append truly new local messages
-  const allMessages = useMemo(() => {
-    const processedInitial = processInitialMessages(initialMessages);
-
-    // Build a set of keys from server messages for deduplication
-    const serverKeys = new Set<string>();
-    for (const msg of processedInitial) {
-      serverKeys.add(getMessageKey(msg));
-    }
-
-    // Filter local messages: remove duplicates and completed operation messages
-    const newLocalMessages = messages.filter((msg) => {
-      // Remove operation messages for completed tools
-      if (
-        msg.type === "operation_started" ||
-        msg.type === "operation_pending" ||
-        msg.type === "operation_in_progress"
-      ) {
-        const toolId = (msg as any).toolId || (msg as any).toolCallId;
-        if (toolId && completedToolIds.has(toolId)) {
-          return false;
-        }
-      }
-      // Remove messages that already exist in server data
-      const key = getMessageKey(msg);
-      return !serverKeys.has(key);
-    });
-
-    // Server messages first (correct order), then new local messages
-    return [...processedInitial, ...newLocalMessages];
-  }, [initialMessages, messages, completedToolIds]);
-
-  async function sendMessage(
-    content: string,
-    isUserMessage: boolean = true,
-    context?: { url: string; content: string },
-  ) {
-    if (!sessionId) {
-      console.error("[useChatContainer] Cannot send message: no session ID");
-      return;
-    }
-    setIsRegionBlockedModalOpen(false);
-    if (isUserMessage) {
-      const userMessage = createUserMessage(content);
-      setMessages((prev) => [...filterAuthMessages(prev), userMessage]);
-    } else {
-      setMessages((prev) => filterAuthMessages(prev));
-    }
-    setStreamingChunks([]);
-    streamingChunksRef.current = [];
-    setHasTextChunks(false);
-    setIsStreamingInitiated(true);
-    hasResponseRef.current = false;
-
-    const dispatcher = createStreamEventDispatcher({
-      setHasTextChunks,
-      setStreamingChunks,
-      streamingChunksRef,
-      hasResponseRef,
-      setMessages,
-      setIsRegionBlockedModalOpen,
-      sessionId,
-      setIsStreamingInitiated,
-      onOperationStarted,
-    });
-
-    try {
-      await sendStreamMessage(
-        sessionId,
-        content,
-        dispatcher,
-        isUserMessage,
-        context,
-      );
-    } catch (err) {
-      console.error("[useChatContainer] Failed to send message:", err);
-      setIsStreamingInitiated(false);
-
-      if (err instanceof Error && err.name === "AbortError") return;
-
-      const errorMessage =
-        err instanceof Error ? err.message : "Failed to send message";
-      toast.error("Failed to send message", {
-        description: errorMessage,
-      });
-    }
-  }
-
-  function handleStopStreaming() {
-    stopStreaming();
-    setStreamingChunks([]);
-    streamingChunksRef.current = [];
-    setHasTextChunks(false);
-    setIsStreamingInitiated(false);
-  }
-
-  const { capturePageContext } = usePageContext();
-  const sendMessageRef = useRef(sendMessage);
-  sendMessageRef.current = sendMessage;
-
-  useEffect(
-    function handleInitialPrompt() {
-      if (!initialPrompt || !sessionId) return;
-      if (initialMessages.length > 0) return;
-      if (hasSentInitialPrompt(sessionId)) return;
-
-      markInitialPromptSent(sessionId);
-      const context = capturePageContext();
-      sendMessageRef.current(initialPrompt, true, context);
-    },
-    [initialPrompt, sessionId, initialMessages.length, capturePageContext],
-  );
-
-  async function sendMessageWithContext(
-    content: string,
-    isUserMessage: boolean = true,
-  ) {
-    const context = capturePageContext();
-    await sendMessage(content, isUserMessage, context);
-  }
-
-  function handleRegionModalOpenChange(open: boolean) {
-    setIsRegionBlockedModalOpen(open);
-  }
-
-  function handleRegionModalClose() {
-    setIsRegionBlockedModalOpen(false);
-  }
-
-  return {
-    messages: allMessages,
-    streamingChunks,
-    isStreaming,
-    error,
-    isRegionBlockedModalOpen,
-    setIsRegionBlockedModalOpen,
-    sendMessageWithContext,
-    handleRegionModalOpenChange,
-    handleRegionModalClose,
-    sendMessage,
-    stopStreaming: handleStopStreaming,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatCredentialsSetup/ChatCredentialsSetup.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatCredentialsSetup/ChatCredentialsSetup.tsx
deleted file mode 100644
index f0dfadd1f7..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatCredentialsSetup/ChatCredentialsSetup.tsx
+++ /dev/null
@@ -1,151 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { CredentialsInput } from "@/components/contextual/CredentialsInput/CredentialsInput";
-import type { BlockIOCredentialsSubSchema } from "@/lib/autogpt-server-api";
-import { cn } from "@/lib/utils";
-import { CheckIcon, RobotIcon, WarningIcon } from "@phosphor-icons/react";
-import { useEffect, useRef } from "react";
-import { useChatCredentialsSetup } from "./useChatCredentialsSetup";
-
-export interface CredentialInfo {
-  provider: string;
-  providerName: string;
-  credentialTypes: Array<
-    "api_key" | "oauth2" | "user_password" | "host_scoped"
-  >;
-  title: string;
-  scopes?: string[];
-}
-
-interface Props {
-  credentials: CredentialInfo[];
-  agentName?: string;
-  message: string;
-  onAllCredentialsComplete: () => void;
-  onCancel: () => void;
-  className?: string;
-}
-
-function createSchemaFromCredentialInfo(
-  credential: CredentialInfo,
-): BlockIOCredentialsSubSchema {
-  return {
-    type: "object",
-    properties: {},
-    credentials_provider: [credential.provider],
-    credentials_types: credential.credentialTypes,
-    credentials_scopes: credential.scopes,
-    discriminator: undefined,
-    discriminator_mapping: undefined,
-    discriminator_values: undefined,
-  };
-}
-
-export function ChatCredentialsSetup({
-  credentials,
-  agentName: _agentName,
-  message,
-  onAllCredentialsComplete,
-  onCancel: _onCancel,
-}: Props) {
-  const { selectedCredentials, isAllComplete, handleCredentialSelect } =
-    useChatCredentialsSetup(credentials);
-
-  // Track if we've already called completion to prevent double calls
-  const hasCalledCompleteRef = useRef(false);
-
-  // Reset the completion flag when credentials change (new credential setup flow)
-  useEffect(
-    function resetCompletionFlag() {
-      hasCalledCompleteRef.current = false;
-    },
-    [credentials],
-  );
-
-  // Auto-call completion when all credentials are configured
-  useEffect(
-    function autoCompleteWhenReady() {
-      if (isAllComplete && !hasCalledCompleteRef.current) {
-        hasCalledCompleteRef.current = true;
-        onAllCredentialsComplete();
-      }
-    },
-    [isAllComplete, onAllCredentialsComplete],
-  );
-
-  return (
-    <div className="group relative flex w-full justify-start gap-3 px-4 py-3">
-      <div className="flex w-full max-w-3xl gap-3">
-        <div className="flex-shrink-0">
-          <div className="flex h-7 w-7 items-center justify-center rounded-lg bg-indigo-500">
-            <RobotIcon className="h-4 w-4 text-indigo-50" />
-          </div>
-        </div>
-
-        <div className="flex min-w-0 flex-1 flex-col">
-          <div className="group relative min-w-20 overflow-hidden rounded-xl border border-slate-100 bg-slate-50/20 px-6 py-2.5 text-sm leading-relaxed backdrop-blur-xl">
-            <div className="absolute inset-0 bg-gradient-to-br from-slate-200/20 via-slate-300/10 to-transparent" />
-            <div className="relative z-10 space-y-3 text-slate-900">
-              <div>
-                <Text variant="h4" className="mb-1 text-slate-900">
-                  Credentials Required
-                </Text>
-                <Text variant="small" className="text-slate-600">
-                  {message}
-                </Text>
-              </div>
-
-              <div className="space-y-3">
-                {credentials.map((cred, index) => {
-                  const schema = createSchemaFromCredentialInfo(cred);
-                  const isSelected = !!selectedCredentials[cred.provider];
-
-                  return (
-                    <div
-                      key={`${cred.provider}-${index}`}
-                      className={cn(
-                        "relative rounded-lg border p-3",
-                        isSelected
-                          ? "border-green-500 bg-green-50/50"
-                          : "border-slate-200 bg-white/50",
-                      )}
-                    >
-                      <div className="mb-2 flex items-center gap-2">
-                        {isSelected ? (
-                          <CheckIcon
-                            size={16}
-                            className="text-green-500"
-                            weight="bold"
-                          />
-                        ) : (
-                          <WarningIcon
-                            size={16}
-                            className="text-slate-500"
-                            weight="bold"
-                          />
-                        )}
-                        <Text
-                          variant="small"
-                          className="font-semibold text-slate-900"
-                        >
-                          {cred.providerName}
-                        </Text>
-                      </div>
-
-                      <CredentialsInput
-                        schema={schema}
-                        selectedCredentials={selectedCredentials[cred.provider]}
-                        onSelectCredentials={(credMeta) =>
-                          handleCredentialSelect(cred.provider, credMeta)
-                        }
-                      />
-                    </div>
-                  );
-                })}
-              </div>
-            </div>
-          </div>
-        </div>
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatCredentialsSetup/useChatCredentialsSetup.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatCredentialsSetup/useChatCredentialsSetup.ts
deleted file mode 100644
index 6b4b26e834..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatCredentialsSetup/useChatCredentialsSetup.ts
+++ /dev/null
@@ -1,36 +0,0 @@
-import { useState, useMemo } from "react";
-import type { CredentialInfo } from "./ChatCredentialsSetup";
-import type { CredentialsMetaInput } from "@/lib/autogpt-server-api";
-
-export function useChatCredentialsSetup(credentials: CredentialInfo[]) {
-  const [selectedCredentials, setSelectedCredentials] = useState<
-    Record<string, CredentialsMetaInput>
-  >({});
-
-  // Check if all credentials are configured
-  const isAllComplete = useMemo(
-    function checkAllComplete() {
-      if (credentials.length === 0) return false;
-      return credentials.every((cred) => selectedCredentials[cred.provider]);
-    },
-    [credentials, selectedCredentials],
-  );
-
-  function handleCredentialSelect(
-    provider: string,
-    credential?: CredentialsMetaInput,
-  ) {
-    if (credential) {
-      setSelectedCredentials((prev) => ({
-        ...prev,
-        [provider]: credential,
-      }));
-    }
-  }
-
-  return {
-    selectedCredentials,
-    isAllComplete,
-    handleCredentialSelect,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatErrorState/ChatErrorState.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatErrorState/ChatErrorState.tsx
deleted file mode 100644
index bac13d1b0c..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatErrorState/ChatErrorState.tsx
+++ /dev/null
@@ -1,30 +0,0 @@
-import React from "react";
-import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard";
-import { cn } from "@/lib/utils";
-
-export interface ChatErrorStateProps {
-  error: Error;
-  onRetry?: () => void;
-  className?: string;
-}
-
-export function ChatErrorState({
-  error,
-  onRetry,
-  className,
-}: ChatErrorStateProps) {
-  return (
-    <div
-      className={cn("flex flex-1 items-center justify-center p-6", className)}
-    >
-      <ErrorCard
-        responseError={{
-          message: error.message,
-        }}
-        context="chat session"
-        onRetry={onRetry}
-        className="max-w-md"
-      />
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatLoader/ChatLoader.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatLoader/ChatLoader.tsx
deleted file mode 100644
index 76cee8dbae..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatLoader/ChatLoader.tsx
+++ /dev/null
@@ -1,7 +0,0 @@
-export function ChatLoader() {
-  return (
-    <div className="flex items-center gap-2">
-      <div className="h-5 w-5 animate-loader rounded-full bg-black" />
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatLoadingState/ChatLoadingState.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatLoadingState/ChatLoadingState.tsx
deleted file mode 100644
index c0cdb33c50..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatLoadingState/ChatLoadingState.tsx
+++ /dev/null
@@ -1,19 +0,0 @@
-import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
-import { cn } from "@/lib/utils";
-
-export interface ChatLoadingStateProps {
-  message?: string;
-  className?: string;
-}
-
-export function ChatLoadingState({ className }: ChatLoadingStateProps) {
-  return (
-    <div
-      className={cn("flex flex-1 items-center justify-center p-6", className)}
-    >
-      <div className="flex flex-col items-center gap-4 text-center">
-        <LoadingSpinner />
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/ChatMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/ChatMessage.tsx
deleted file mode 100644
index c922d0da76..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/ChatMessage.tsx
+++ /dev/null
@@ -1,435 +0,0 @@
-"use client";
-
-import { Button } from "@/components/atoms/Button/Button";
-import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { cn } from "@/lib/utils";
-import {
-  ArrowsClockwiseIcon,
-  CheckCircleIcon,
-  CheckIcon,
-} from "@phosphor-icons/react";
-import { useRouter } from "next/navigation";
-import { useCallback, useState } from "react";
-import { AgentCarouselMessage } from "../AgentCarouselMessage/AgentCarouselMessage";
-import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
-import { AuthPromptWidget } from "../AuthPromptWidget/AuthPromptWidget";
-import { ChatCredentialsSetup } from "../ChatCredentialsSetup/ChatCredentialsSetup";
-import { ClarificationQuestionsWidget } from "../ClarificationQuestionsWidget/ClarificationQuestionsWidget";
-import { ExecutionStartedMessage } from "../ExecutionStartedMessage/ExecutionStartedMessage";
-import { PendingOperationWidget } from "../PendingOperationWidget/PendingOperationWidget";
-import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
-import { NoResultsMessage } from "../NoResultsMessage/NoResultsMessage";
-import { ToolCallMessage } from "../ToolCallMessage/ToolCallMessage";
-import { ToolResponseMessage } from "../ToolResponseMessage/ToolResponseMessage";
-import { UserChatBubble } from "../UserChatBubble/UserChatBubble";
-import { useChatMessage, type ChatMessageData } from "./useChatMessage";
-
-function stripInternalReasoning(content: string): string {
-  const cleaned = content.replace(
-    /<internal_reasoning>[\s\S]*?<\/internal_reasoning>/gi,
-    "",
-  );
-  return cleaned.replace(/\n{3,}/g, "\n\n").trim();
-}
-
-function getDisplayContent(message: ChatMessageData, isUser: boolean): string {
-  if (message.type !== "message") return "";
-  if (isUser) return message.content;
-  return stripInternalReasoning(message.content);
-}
-
-export interface ChatMessageProps {
-  message: ChatMessageData;
-  messages?: ChatMessageData[];
-  index?: number;
-  isStreaming?: boolean;
-  className?: string;
-  onDismissLogin?: () => void;
-  onDismissCredentials?: () => void;
-  onSendMessage?: (content: string, isUserMessage?: boolean) => void;
-  agentOutput?: ChatMessageData;
-  isFinalMessage?: boolean;
-}
-
-export function ChatMessage({
-  message,
-  messages = [],
-  index = -1,
-  isStreaming = false,
-  className,
-  onDismissCredentials,
-  onSendMessage,
-  agentOutput,
-  isFinalMessage = true,
-}: ChatMessageProps) {
-  const { user } = useSupabase();
-  const router = useRouter();
-  const [copied, setCopied] = useState(false);
-  const {
-    isUser,
-    isToolCall,
-    isToolResponse,
-    isLoginNeeded,
-    isCredentialsNeeded,
-    isClarificationNeeded,
-    isOperationStarted,
-    isOperationPending,
-    isOperationInProgress,
-  } = useChatMessage(message);
-  const displayContent = getDisplayContent(message, isUser);
-
-  const handleAllCredentialsComplete = useCallback(
-    function handleAllCredentialsComplete() {
-      // Send a user message that explicitly asks to retry the setup
-      // This ensures the LLM calls get_required_setup_info again and proceeds with execution
-      if (onSendMessage) {
-        onSendMessage(
-          "I've configured the required credentials. Please check if everything is ready and proceed with setting up the agent.",
-        );
-      }
-      // Optionally dismiss the credentials prompt
-      if (onDismissCredentials) {
-        onDismissCredentials();
-      }
-    },
-    [onSendMessage, onDismissCredentials],
-  );
-
-  function handleCancelCredentials() {
-    // Dismiss the credentials prompt
-    if (onDismissCredentials) {
-      onDismissCredentials();
-    }
-  }
-
-  function handleClarificationAnswers(answers: Record<string, string>) {
-    if (onSendMessage) {
-      const contextMessage = Object.entries(answers)
-        .map(([keyword, answer]) => `${keyword}: ${answer}`)
-        .join("\n");
-
-      onSendMessage(
-        `I have the answers to your questions:\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
-      );
-    }
-  }
-
-  const handleCopy = useCallback(
-    async function handleCopy() {
-      if (message.type !== "message") return;
-      if (!displayContent) return;
-
-      try {
-        await navigator.clipboard.writeText(displayContent);
-        setCopied(true);
-        setTimeout(() => setCopied(false), 2000);
-      } catch (error) {
-        console.error("Failed to copy:", error);
-      }
-    },
-    [displayContent, message],
-  );
-
-  const handleTryAgain = useCallback(() => {
-    if (message.type !== "message" || !onSendMessage) return;
-    onSendMessage(message.content, message.role === "user");
-  }, [message, onSendMessage]);
-
-  const handleViewExecution = useCallback(() => {
-    if (message.type === "execution_started" && message.libraryAgentLink) {
-      router.push(message.libraryAgentLink);
-    }
-  }, [message, router]);
-
-  // Render credentials needed messages
-  if (isCredentialsNeeded && message.type === "credentials_needed") {
-    return (
-      <ChatCredentialsSetup
-        credentials={message.credentials}
-        agentName={message.agentName}
-        message={message.message}
-        onAllCredentialsComplete={handleAllCredentialsComplete}
-        onCancel={handleCancelCredentials}
-        className={className}
-      />
-    );
-  }
-
-  if (isClarificationNeeded && message.type === "clarification_needed") {
-    return (
-      <ClarificationQuestionsWidget
-        questions={message.questions}
-        message={message.message}
-        onSubmitAnswers={handleClarificationAnswers}
-        className={className}
-      />
-    );
-  }
-
-  // Render login needed messages
-  if (isLoginNeeded && message.type === "login_needed") {
-    // If user is already logged in, show success message instead of auth prompt
-    if (user) {
-      return (
-        <div className={cn("px-4 py-2", className)}>
-          <div className="my-4 overflow-hidden rounded-lg border border-green-200 bg-gradient-to-br from-green-50 to-emerald-50">
-            <div className="px-6 py-4">
-              <div className="flex items-center gap-3">
-                <div className="flex h-10 w-10 items-center justify-center rounded-full bg-green-600">
-                  <CheckCircleIcon
-                    size={20}
-                    weight="fill"
-                    className="text-white"
-                  />
-                </div>
-                <div>
-                  <h3 className="text-lg font-semibold text-neutral-900">
-                    Successfully Authenticated
-                  </h3>
-                  <p className="text-sm text-neutral-600">
-                    You&apos;re now signed in and ready to continue
-                  </p>
-                </div>
-              </div>
-            </div>
-          </div>
-        </div>
-      );
-    }
-
-    // Show auth prompt if not logged in
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <AuthPromptWidget
-          message={message.message}
-          sessionId={message.sessionId}
-          agentInfo={message.agentInfo}
-        />
-      </div>
-    );
-  }
-
-  // Render tool call messages
-  if (isToolCall && message.type === "tool_call") {
-    // Check if this tool call is currently streaming
-    // A tool call is streaming if:
-    // 1. isStreaming is true
-    // 2. This is the last tool_call message
-    // 3. There's no tool_response for this tool call yet
-    const isToolCallStreaming =
-      isStreaming &&
-      index >= 0 &&
-      (() => {
-        // Find the last tool_call index
-        let lastToolCallIndex = -1;
-        for (let i = messages.length - 1; i >= 0; i--) {
-          if (messages[i].type === "tool_call") {
-            lastToolCallIndex = i;
-            break;
-          }
-        }
-        // Check if this is the last tool_call and there's no response yet
-        if (index === lastToolCallIndex) {
-          // Check if there's a tool_response for this tool call
-          const hasResponse = messages
-            .slice(index + 1)
-            .some(
-              (msg) =>
-                msg.type === "tool_response" && msg.toolId === message.toolId,
-            );
-          return !hasResponse;
-        }
-        return false;
-      })();
-
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <ToolCallMessage
-          toolId={message.toolId}
-          toolName={message.toolName}
-          arguments={message.arguments}
-          isStreaming={isToolCallStreaming}
-        />
-      </div>
-    );
-  }
-
-  // Render no_results messages - use dedicated component, not ToolResponseMessage
-  if (message.type === "no_results") {
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <NoResultsMessage
-          message={message.message}
-          suggestions={message.suggestions}
-        />
-      </div>
-    );
-  }
-
-  // Render agent_carousel messages - use dedicated component, not ToolResponseMessage
-  if (message.type === "agent_carousel") {
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <AgentCarouselMessage
-          agents={message.agents}
-          totalCount={message.totalCount}
-        />
-      </div>
-    );
-  }
-
-  // Render execution_started messages - use dedicated component, not ToolResponseMessage
-  if (message.type === "execution_started") {
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <ExecutionStartedMessage
-          executionId={message.executionId}
-          agentName={message.agentName}
-          message={message.message}
-          onViewExecution={
-            message.libraryAgentLink ? handleViewExecution : undefined
-          }
-        />
-      </div>
-    );
-  }
-
-  // Render operation_started messages (long-running background operations)
-  if (isOperationStarted && message.type === "operation_started") {
-    return (
-      <PendingOperationWidget
-        status="started"
-        message={message.message}
-        toolName={message.toolName}
-        className={className}
-      />
-    );
-  }
-
-  // Render operation_pending messages (operations in progress when refreshing)
-  if (isOperationPending && message.type === "operation_pending") {
-    return (
-      <PendingOperationWidget
-        status="pending"
-        message={message.message}
-        toolName={message.toolName}
-        className={className}
-      />
-    );
-  }
-
-  // Render operation_in_progress messages (duplicate request while operation running)
-  if (isOperationInProgress && message.type === "operation_in_progress") {
-    return (
-      <PendingOperationWidget
-        status="in_progress"
-        message={message.message}
-        toolName={message.toolName}
-        className={className}
-      />
-    );
-  }
-
-  // Render tool response messages (but skip agent_output if it's being rendered inside assistant message)
-  if (isToolResponse && message.type === "tool_response") {
-    return (
-      <div className={cn("px-4 py-2", className)}>
-        <ToolResponseMessage
-          toolId={message.toolId}
-          toolName={message.toolName}
-          result={message.result}
-        />
-      </div>
-    );
-  }
-
-  // Render regular chat messages
-  if (message.type === "message") {
-    return (
-      <div
-        className={cn(
-          "group relative flex w-full gap-3 px-4 py-3",
-          isUser ? "justify-end" : "justify-start",
-          className,
-        )}
-      >
-        <div className="flex w-full max-w-3xl gap-3">
-          <div
-            className={cn(
-              "flex min-w-0 flex-1 flex-col",
-              isUser && "items-end",
-            )}
-          >
-            {isUser ? (
-              <UserChatBubble>
-                <MarkdownContent content={displayContent} />
-              </UserChatBubble>
-            ) : (
-              <AIChatBubble>
-                <MarkdownContent content={displayContent} />
-                {agentOutput && agentOutput.type === "tool_response" && (
-                  <div className="mt-4">
-                    <ToolResponseMessage
-                      toolId={agentOutput.toolId}
-                      toolName={agentOutput.toolName || "Agent Output"}
-                      result={agentOutput.result}
-                    />
-                  </div>
-                )}
-              </AIChatBubble>
-            )}
-            <div
-              className={cn(
-                "flex gap-0",
-                isUser ? "justify-end" : "justify-start",
-              )}
-            >
-              {isUser && onSendMessage && (
-                <Button
-                  variant="ghost"
-                  size="icon"
-                  onClick={handleTryAgain}
-                  aria-label="Try again"
-                >
-                  <ArrowsClockwiseIcon className="size-4 text-zinc-600" />
-                </Button>
-              )}
-              {!isUser && isFinalMessage && !isStreaming && (
-                <Button
-                  variant="ghost"
-                  size="icon"
-                  onClick={handleCopy}
-                  aria-label="Copy message"
-                  className="p-1"
-                >
-                  {copied ? (
-                    <CheckIcon className="size-4 text-green-600" />
-                  ) : (
-                    <svg
-                      xmlns="http://www.w3.org/2000/svg"
-                      width="24"
-                      height="24"
-                      viewBox="0 0 24 24"
-                      fill="none"
-                      stroke="currentColor"
-                      strokeWidth="2"
-                      strokeLinecap="round"
-                      strokeLinejoin="round"
-                      className="size-3 text-zinc-600"
-                    >
-                      <rect width="14" height="14" x="8" y="8" rx="2" ry="2" />
-                      <path d="M4 16c-1.1 0-2-.9-2-2V4c0-1.1.9-2 2-2h10c1.1 0 2 .9 2 2" />
-                    </svg>
-                  )}
-                </Button>
-              )}
-            </div>
-          </div>
-        </div>
-      </div>
-    );
-  }
-
-  // Fallback for unknown message types
-  return null;
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/useChatMessage.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/useChatMessage.ts
deleted file mode 100644
index d6526c78ab..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatMessage/useChatMessage.ts
+++ /dev/null
@@ -1,156 +0,0 @@
-import type { ToolArguments, ToolResult } from "@/types/chat";
-import { formatDistanceToNow } from "date-fns";
-
-export type ChatMessageData =
-  | {
-      type: "message";
-      role: "user" | "assistant" | "system";
-      content: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "tool_call";
-      toolId: string;
-      toolName: string;
-      arguments?: ToolArguments;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "tool_response";
-      toolId: string;
-      toolName: string;
-      result: ToolResult;
-      success?: boolean;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "login_needed";
-      toolName: string;
-      message: string;
-      sessionId: string;
-      agentInfo?: {
-        graph_id: string;
-        name: string;
-        trigger_type: string;
-      };
-      timestamp?: string | Date;
-    }
-  | {
-      type: "credentials_needed";
-      toolName: string;
-      credentials: Array<{
-        provider: string;
-        providerName: string;
-        credentialTypes: Array<
-          "api_key" | "oauth2" | "user_password" | "host_scoped"
-        >;
-        title: string;
-        scopes?: string[];
-      }>;
-      message: string;
-      agentName?: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "no_results";
-      toolName: string;
-      message: string;
-      suggestions?: string[];
-      sessionId?: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "agent_carousel";
-      toolId: string;
-      toolName: string;
-      agents: Array<{
-        id: string;
-        name: string;
-        description: string;
-        version?: number;
-        image_url?: string;
-      }>;
-      totalCount?: number;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "execution_started";
-      toolId: string;
-      toolName: string;
-      executionId: string;
-      agentName?: string;
-      message?: string;
-      libraryAgentLink?: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "inputs_needed";
-      toolName: string;
-      agentName?: string;
-      agentId?: string;
-      graphVersion?: number;
-      inputSchema: Record<string, any>;
-      credentialsSchema?: Record<string, any>;
-      message: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "clarification_needed";
-      toolName: string;
-      questions: Array<{
-        question: string;
-        keyword: string;
-        example?: string;
-      }>;
-      message: string;
-      sessionId: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "operation_started";
-      toolName: string;
-      toolId: string;
-      operationId: string;
-      message: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "operation_pending";
-      toolName: string;
-      toolId: string;
-      operationId: string;
-      message: string;
-      timestamp?: string | Date;
-    }
-  | {
-      type: "operation_in_progress";
-      toolName: string;
-      toolCallId: string;
-      message: string;
-      timestamp?: string | Date;
-    };
-
-export function useChatMessage(message: ChatMessageData) {
-  const formattedTimestamp = message.timestamp
-    ? formatDistanceToNow(new Date(message.timestamp), { addSuffix: true })
-    : "Just now";
-
-  return {
-    formattedTimestamp,
-    isUser: message.type === "message" && message.role === "user",
-    isAssistant: message.type === "message" && message.role === "assistant",
-    isSystem: message.type === "message" && message.role === "system",
-    isToolCall: message.type === "tool_call",
-    isToolResponse: message.type === "tool_response",
-    isLoginNeeded: message.type === "login_needed",
-    isCredentialsNeeded: message.type === "credentials_needed",
-    isNoResults: message.type === "no_results",
-    isAgentCarousel: message.type === "agent_carousel",
-    isExecutionStarted: message.type === "execution_started",
-    isInputsNeeded: message.type === "inputs_needed",
-    isClarificationNeeded: message.type === "clarification_needed",
-    isOperationStarted: message.type === "operation_started",
-    isOperationPending: message.type === "operation_pending",
-    isOperationInProgress: message.type === "operation_in_progress",
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ExecutionStartedMessage/ExecutionStartedMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ExecutionStartedMessage/ExecutionStartedMessage.tsx
deleted file mode 100644
index 1ac3b440e0..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ExecutionStartedMessage/ExecutionStartedMessage.tsx
+++ /dev/null
@@ -1,90 +0,0 @@
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { ArrowSquareOut, CheckCircle, Play } from "@phosphor-icons/react";
-
-export interface ExecutionStartedMessageProps {
-  executionId: string;
-  agentName?: string;
-  message?: string;
-  onViewExecution?: () => void;
-  className?: string;
-}
-
-export function ExecutionStartedMessage({
-  executionId,
-  agentName,
-  message = "Agent execution started successfully",
-  onViewExecution,
-  className,
-}: ExecutionStartedMessageProps) {
-  return (
-    <div
-      className={cn(
-        "mx-4 my-2 flex flex-col gap-4 rounded-lg border border-green-200 bg-green-50 p-6",
-        className,
-      )}
-    >
-      {/* Icon & Header */}
-      <div className="flex items-start gap-4">
-        <div className="flex h-12 w-12 flex-shrink-0 items-center justify-center rounded-full bg-green-500">
-          <CheckCircle size={24} weight="bold" className="text-white" />
-        </div>
-        <div className="flex-1">
-          <Text variant="h3" className="mb-1 text-green-900">
-            Execution Started
-          </Text>
-          <Text variant="body" className="text-green-700">
-            {message}
-          </Text>
-        </div>
-      </div>
-
-      {/* Details */}
-      <div className="rounded-md bg-green-100 p-4">
-        <div className="space-y-2">
-          {agentName && (
-            <div className="flex items-center justify-between">
-              <Text variant="small" className="font-semibold text-green-900">
-                Agent:
-              </Text>
-              <Text variant="body" className="text-green-800">
-                {agentName}
-              </Text>
-            </div>
-          )}
-          <div className="flex items-center justify-between">
-            <Text variant="small" className="font-semibold text-green-900">
-              Execution ID:
-            </Text>
-            <Text variant="small" className="font-mono text-green-800">
-              {executionId.slice(0, 16)}...
-            </Text>
-          </div>
-        </div>
-      </div>
-
-      {/* Action Buttons */}
-      {onViewExecution && (
-        <div className="flex gap-3">
-          <Button
-            onClick={onViewExecution}
-            variant="primary"
-            className="flex flex-1 items-center justify-center gap-2"
-          >
-            <ArrowSquareOut size={20} weight="bold" />
-            View Execution
-          </Button>
-        </div>
-      )}
-
-      <div className="flex items-center gap-2 text-green-600">
-        <Play size={16} weight="fill" />
-        <Text variant="small">
-          Your agent is now running. You can monitor its progress in the monitor
-          page.
-        </Text>
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MarkdownContent/MarkdownContent.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/MarkdownContent/MarkdownContent.tsx
deleted file mode 100644
index 3dd5eca692..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MarkdownContent/MarkdownContent.tsx
+++ /dev/null
@@ -1,296 +0,0 @@
-"use client";
-
-import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
-import { cn } from "@/lib/utils";
-import { EyeSlash } from "@phosphor-icons/react";
-import React from "react";
-import ReactMarkdown from "react-markdown";
-import remarkGfm from "remark-gfm";
-
-interface MarkdownContentProps {
-  content: string;
-  className?: string;
-}
-
-interface CodeProps extends React.HTMLAttributes<HTMLElement> {
-  children?: React.ReactNode;
-  className?: string;
-}
-
-interface ListProps extends React.HTMLAttributes<HTMLUListElement> {
-  children?: React.ReactNode;
-  className?: string;
-}
-
-interface ListItemProps extends React.HTMLAttributes<HTMLLIElement> {
-  children?: React.ReactNode;
-  className?: string;
-}
-
-interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
-  type?: string;
-}
-
-/**
- * Converts a workspace:// URL to a proxy URL that routes through Next.js to the backend.
- * workspace://abc123 -> /api/proxy/api/workspace/files/abc123/download
- *
- * Uses the generated API URL helper and routes through the Next.js proxy
- * which handles authentication and proper backend routing.
- */
-/**
- * URL transformer for ReactMarkdown.
- * Converts workspace:// URLs to proxy URLs that route through Next.js to the backend.
- * workspace://abc123 -> /api/proxy/api/workspace/files/abc123/download
- *
- * This is needed because ReactMarkdown sanitizes URLs and only allows
- * http, https, mailto, and tel protocols by default.
- */
-function resolveWorkspaceUrl(src: string): string {
-  if (src.startsWith("workspace://")) {
-    const fileId = src.replace("workspace://", "");
-    // Use the generated API URL helper to get the correct path
-    const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
-    // Route through the Next.js proxy (same pattern as customMutator for client-side)
-    return `/api/proxy${apiPath}`;
-  }
-  return src;
-}
-
-/**
- * Check if the image URL is a workspace file (AI cannot see these yet).
- * After URL transformation, workspace files have URLs like /api/proxy/api/workspace/files/...
- */
-function isWorkspaceImage(src: string | undefined): boolean {
-  return src?.includes("/workspace/files/") ?? false;
-}
-
-/**
- * Custom image component that shows an indicator when the AI cannot see the image.
- * Note: src is already transformed by urlTransform, so workspace:// is now /api/workspace/...
- */
-function MarkdownImage(props: Record<string, unknown>) {
-  const src = props.src as string | undefined;
-  const alt = props.alt as string | undefined;
-
-  const aiCannotSee = isWorkspaceImage(src);
-
-  // If no src, show a placeholder
-  if (!src) {
-    return (
-      <span className="my-2 inline-block rounded border border-amber-200 bg-amber-50 px-2 py-1 text-sm text-amber-700">
-        [Image: {alt || "missing src"}]
-      </span>
-    );
-  }
-
-  return (
-    <span className="relative my-2 inline-block">
-      {/* eslint-disable-next-line @next/next/no-img-element */}
-      <img
-        src={src}
-        alt={alt || "Image"}
-        className="h-auto max-w-full rounded-md border border-zinc-200"
-        loading="lazy"
-      />
-      {aiCannotSee && (
-        <span
-          className="absolute bottom-2 right-2 flex items-center gap-1 rounded bg-black/70 px-2 py-1 text-xs text-white"
-          title="The AI cannot see this image"
-        >
-          <EyeSlash size={14} />
-          <span>AI cannot see this image</span>
-        </span>
-      )}
-    </span>
-  );
-}
-
-export function MarkdownContent({ content, className }: MarkdownContentProps) {
-  return (
-    <div className={cn("markdown-content", className)}>
-      <ReactMarkdown
-        skipHtml={true}
-        remarkPlugins={[remarkGfm]}
-        urlTransform={resolveWorkspaceUrl}
-        components={{
-          code: ({ children, className, ...props }: CodeProps) => {
-            const isInline = !className?.includes("language-");
-            if (isInline) {
-              return (
-                <code
-                  className="rounded bg-zinc-100 px-1.5 py-0.5 font-mono text-sm text-zinc-800"
-                  {...props}
-                >
-                  {children}
-                </code>
-              );
-            }
-            return (
-              <code className="font-mono text-sm text-zinc-100" {...props}>
-                {children}
-              </code>
-            );
-          },
-          pre: ({ children, ...props }) => (
-            <pre
-              className="my-2 overflow-x-auto rounded-md bg-zinc-900 p-3"
-              {...props}
-            >
-              {children}
-            </pre>
-          ),
-          a: ({ children, href, ...props }) => (
-            <a
-              href={href}
-              target="_blank"
-              rel="noopener noreferrer"
-              className="text-purple-600 underline decoration-1 underline-offset-2 hover:text-purple-700"
-              {...props}
-            >
-              {children}
-            </a>
-          ),
-          strong: ({ children, ...props }) => (
-            <strong className="font-semibold" {...props}>
-              {children}
-            </strong>
-          ),
-          em: ({ children, ...props }) => (
-            <em className="italic" {...props}>
-              {children}
-            </em>
-          ),
-          del: ({ children, ...props }) => (
-            <del className="line-through opacity-70" {...props}>
-              {children}
-            </del>
-          ),
-          ul: ({ children, ...props }: ListProps) => (
-            <ul
-              className={cn(
-                "my-2 space-y-1 pl-6",
-                props.className?.includes("contains-task-list")
-                  ? "list-none pl-0"
-                  : "list-disc",
-              )}
-              {...props}
-            >
-              {children}
-            </ul>
-          ),
-          ol: ({ children, ...props }) => (
-            <ol className="my-2 list-decimal space-y-1 pl-6" {...props}>
-              {children}
-            </ol>
-          ),
-          li: ({ children, ...props }: ListItemProps) => (
-            <li
-              className={cn(
-                props.className?.includes("task-list-item")
-                  ? "flex items-start"
-                  : "",
-              )}
-              {...props}
-            >
-              {children}
-            </li>
-          ),
-          input: ({ ...props }: InputProps) => {
-            if (props.type === "checkbox") {
-              return (
-                <input
-                  type="checkbox"
-                  className="mr-2 h-4 w-4 rounded border-zinc-300 text-purple-600 focus:ring-purple-500 disabled:cursor-not-allowed disabled:opacity-70"
-                  disabled
-                  {...props}
-                />
-              );
-            }
-            return <input {...props} />;
-          },
-          blockquote: ({ children, ...props }) => (
-            <blockquote
-              className="my-2 border-l-4 border-zinc-300 pl-3 italic text-zinc-700"
-              {...props}
-            >
-              {children}
-            </blockquote>
-          ),
-          h1: ({ children, ...props }) => (
-            <h1 className="my-2 text-xl font-bold text-zinc-900" {...props}>
-              {children}
-            </h1>
-          ),
-          h2: ({ children, ...props }) => (
-            <h2 className="my-2 text-lg font-semibold text-zinc-800" {...props}>
-              {children}
-            </h2>
-          ),
-          h3: ({ children, ...props }) => (
-            <h3
-              className="my-1 text-base font-semibold text-zinc-800"
-              {...props}
-            >
-              {children}
-            </h3>
-          ),
-          h4: ({ children, ...props }) => (
-            <h4 className="my-1 text-sm font-medium text-zinc-700" {...props}>
-              {children}
-            </h4>
-          ),
-          h5: ({ children, ...props }) => (
-            <h5 className="my-1 text-sm font-medium text-zinc-700" {...props}>
-              {children}
-            </h5>
-          ),
-          h6: ({ children, ...props }) => (
-            <h6 className="my-1 text-xs font-medium text-zinc-600" {...props}>
-              {children}
-            </h6>
-          ),
-          p: ({ children, ...props }) => (
-            <p className="my-2 leading-relaxed" {...props}>
-              {children}
-            </p>
-          ),
-          hr: ({ ...props }) => (
-            <hr className="my-3 border-zinc-300" {...props} />
-          ),
-          table: ({ children, ...props }) => (
-            <div className="my-2 overflow-x-auto">
-              <table
-                className="min-w-full divide-y divide-zinc-200 rounded border border-zinc-200"
-                {...props}
-              >
-                {children}
-              </table>
-            </div>
-          ),
-          th: ({ children, ...props }) => (
-            <th
-              className="bg-zinc-50 px-3 py-2 text-left text-xs font-semibold text-zinc-700"
-              {...props}
-            >
-              {children}
-            </th>
-          ),
-          td: ({ children, ...props }) => (
-            <td
-              className="border-t border-zinc-200 px-3 py-2 text-sm"
-              {...props}
-            >
-              {children}
-            </td>
-          ),
-          img: ({ src, alt, ...props }) => (
-            <MarkdownImage src={src} alt={alt} {...props} />
-          ),
-        }}
-      >
-        {content}
-      </ReactMarkdown>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageBubble/MessageBubble.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageBubble/MessageBubble.tsx
deleted file mode 100644
index 70d5d135a1..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageBubble/MessageBubble.tsx
+++ /dev/null
@@ -1,53 +0,0 @@
-import { cn } from "@/lib/utils";
-import { ReactNode } from "react";
-
-export interface MessageBubbleProps {
-  children: ReactNode;
-  variant: "user" | "assistant";
-  className?: string;
-}
-
-export function MessageBubble({
-  children,
-  variant,
-  className,
-}: MessageBubbleProps) {
-  const userTheme = {
-    bg: "bg-purple-100",
-    border: "border-purple-100",
-    text: "text-slate-900",
-  };
-
-  const assistantTheme = {
-    bg: "bg-slate-50/20",
-    border: "border-slate-100",
-    gradient: "from-slate-200/20 via-slate-300/10 to-transparent",
-    text: "text-slate-900",
-  };
-
-  const theme = variant === "user" ? userTheme : assistantTheme;
-
-  return (
-    <div
-      className={cn(
-        "group relative min-w-20 overflow-hidden rounded-xl border px-6 py-2.5 text-sm leading-relaxed backdrop-blur-xl transition-all duration-500 ease-in-out",
-        theme.bg,
-        theme.border,
-        variant === "user" && "text-right",
-        variant === "assistant" && "text-left",
-        className,
-      )}
-    >
-      {/* Gradient flare background */}
-      <div className={cn("absolute inset-0 bg-gradient-to-br")} />
-      <div
-        className={cn(
-          "relative z-10 transition-all duration-500 ease-in-out",
-          theme.text,
-        )}
-      >
-        {children}
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/MessageList.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/MessageList.tsx
deleted file mode 100644
index 84f31f9d20..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/MessageList.tsx
+++ /dev/null
@@ -1,119 +0,0 @@
-"use client";
-
-import { cn } from "@/lib/utils";
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-import { StreamingMessage } from "../StreamingMessage/StreamingMessage";
-import { ThinkingMessage } from "../ThinkingMessage/ThinkingMessage";
-import { LastToolResponse } from "./components/LastToolResponse/LastToolResponse";
-import { MessageItem } from "./components/MessageItem/MessageItem";
-import { findLastMessageIndex, shouldSkipAgentOutput } from "./helpers";
-import { useMessageList } from "./useMessageList";
-
-export interface MessageListProps {
-  messages: ChatMessageData[];
-  streamingChunks?: string[];
-  isStreaming?: boolean;
-  className?: string;
-  onStreamComplete?: () => void;
-  onSendMessage?: (content: string) => void;
-}
-
-export function MessageList({
-  messages,
-  streamingChunks = [],
-  isStreaming = false,
-  className,
-  onStreamComplete,
-  onSendMessage,
-}: MessageListProps) {
-  const { messagesEndRef, messagesContainerRef } = useMessageList({
-    messageCount: messages.length,
-    isStreaming,
-  });
-
-  /**
-   * Keeps this for debugging purposes 💆🏽
-   */
-  console.log(messages);
-
-  return (
-    <div className="relative flex min-h-0 flex-1 flex-col">
-      {/* Top fade shadow */}
-      <div className="pointer-events-none absolute top-0 z-10 h-8 w-full bg-gradient-to-b from-[#f8f8f9] to-transparent" />
-
-      <div
-        ref={messagesContainerRef}
-        className={cn(
-          "flex-1 overflow-y-auto overflow-x-hidden",
-          "scrollbar-thin scrollbar-track-transparent scrollbar-thumb-zinc-300",
-          className,
-        )}
-      >
-        <div className="mx-auto flex min-w-0 flex-col hyphens-auto break-words py-4">
-          {/* Render all persisted messages */}
-          {(() => {
-            const lastAssistantMessageIndex = findLastMessageIndex(
-              messages,
-              (msg) => msg.type === "message" && msg.role === "assistant",
-            );
-
-            const lastToolResponseIndex = findLastMessageIndex(
-              messages,
-              (msg) => msg.type === "tool_response",
-            );
-
-            return messages.map((message, index) => {
-              // Skip agent_output tool_responses that should be rendered inside assistant messages
-              if (shouldSkipAgentOutput(message, messages[index - 1])) {
-                return null;
-              }
-
-              // Render last tool_response as AIChatBubble
-              if (
-                message.type === "tool_response" &&
-                index === lastToolResponseIndex
-              ) {
-                return (
-                  <LastToolResponse
-                    key={index}
-                    message={message}
-                    prevMessage={messages[index - 1]}
-                  />
-                );
-              }
-
-              return (
-                <MessageItem
-                  key={index}
-                  message={message}
-                  messages={messages}
-                  index={index}
-                  lastAssistantMessageIndex={lastAssistantMessageIndex}
-                  isStreaming={isStreaming}
-                  onSendMessage={onSendMessage}
-                />
-              );
-            });
-          })()}
-
-          {/* Render thinking message when streaming but no chunks yet */}
-          {isStreaming && streamingChunks.length === 0 && <ThinkingMessage />}
-
-          {/* Render streaming message if active */}
-          {isStreaming && streamingChunks.length > 0 && (
-            <StreamingMessage
-              chunks={streamingChunks}
-              onComplete={onStreamComplete}
-            />
-          )}
-
-          {/* Invisible div to scroll to */}
-          <div ref={messagesEndRef} />
-        </div>
-      </div>
-
-      {/* Bottom fade shadow */}
-      <div className="pointer-events-none absolute bottom-0 z-10 h-8 w-full bg-gradient-to-t from-[#f8f8f9] to-transparent" />
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/LastToolResponse/LastToolResponse.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/LastToolResponse/LastToolResponse.tsx
deleted file mode 100644
index 15b10e5715..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/LastToolResponse/LastToolResponse.tsx
+++ /dev/null
@@ -1,27 +0,0 @@
-import type { ChatMessageData } from "../../../ChatMessage/useChatMessage";
-import { ToolResponseMessage } from "../../../ToolResponseMessage/ToolResponseMessage";
-import { shouldSkipAgentOutput } from "../../helpers";
-
-export interface LastToolResponseProps {
-  message: ChatMessageData;
-  prevMessage: ChatMessageData | undefined;
-}
-
-export function LastToolResponse({
-  message,
-  prevMessage,
-}: LastToolResponseProps) {
-  if (message.type !== "tool_response") return null;
-
-  if (shouldSkipAgentOutput(message, prevMessage)) return null;
-
-  return (
-    <div className="min-w-0 overflow-x-hidden hyphens-auto break-words px-4 py-2">
-      <ToolResponseMessage
-        toolId={message.toolId}
-        toolName={message.toolName}
-        result={message.result}
-      />
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/MessageItem.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/MessageItem.tsx
deleted file mode 100644
index d455633b66..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/MessageItem.tsx
+++ /dev/null
@@ -1,40 +0,0 @@
-import { ChatMessage } from "../../../ChatMessage/ChatMessage";
-import type { ChatMessageData } from "../../../ChatMessage/useChatMessage";
-import { useMessageItem } from "./useMessageItem";
-
-export interface MessageItemProps {
-  message: ChatMessageData;
-  messages: ChatMessageData[];
-  index: number;
-  lastAssistantMessageIndex: number;
-  isStreaming?: boolean;
-  onSendMessage?: (content: string) => void;
-}
-
-export function MessageItem({
-  message,
-  messages,
-  index,
-  lastAssistantMessageIndex,
-  isStreaming = false,
-  onSendMessage,
-}: MessageItemProps) {
-  const { messageToRender, agentOutput, isFinalMessage } = useMessageItem({
-    message,
-    messages,
-    index,
-    lastAssistantMessageIndex,
-  });
-
-  return (
-    <ChatMessage
-      message={messageToRender}
-      messages={messages}
-      index={index}
-      isStreaming={isStreaming}
-      onSendMessage={onSendMessage}
-      agentOutput={agentOutput}
-      isFinalMessage={isFinalMessage}
-    />
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/useMessageItem.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/useMessageItem.ts
deleted file mode 100644
index 65c2e02cc8..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/components/MessageItem/useMessageItem.ts
+++ /dev/null
@@ -1,62 +0,0 @@
-import type { ChatMessageData } from "../../../ChatMessage/useChatMessage";
-import { isAgentOutputResult, isToolOutputPattern } from "../../helpers";
-
-export interface UseMessageItemArgs {
-  message: ChatMessageData;
-  messages: ChatMessageData[];
-  index: number;
-  lastAssistantMessageIndex: number;
-}
-
-export function useMessageItem({
-  message,
-  messages,
-  index,
-  lastAssistantMessageIndex,
-}: UseMessageItemArgs) {
-  let agentOutput: ChatMessageData | undefined;
-  let messageToRender: ChatMessageData = message;
-
-  // Check if assistant message follows a tool_call and looks like a tool output
-  if (message.type === "message" && message.role === "assistant") {
-    const prevMessage = messages[index - 1];
-
-    // Check if next message is an agent_output tool_response to include in current assistant message
-    const nextMessage = messages[index + 1];
-    if (
-      nextMessage &&
-      nextMessage.type === "tool_response" &&
-      nextMessage.result
-    ) {
-      if (isAgentOutputResult(nextMessage.result)) {
-        agentOutput = nextMessage;
-      }
-    }
-
-    // Only convert to tool_response if it follows a tool_call AND looks like a tool output
-    if (prevMessage && prevMessage.type === "tool_call") {
-      if (isToolOutputPattern(message.content)) {
-        // Convert this message to a tool_response format for rendering
-        messageToRender = {
-          type: "tool_response",
-          toolId: prevMessage.toolId,
-          toolName: prevMessage.toolName,
-          result: message.content,
-          success: true,
-          timestamp: message.timestamp,
-        } as ChatMessageData;
-      }
-    }
-  }
-
-  const isFinalMessage =
-    messageToRender.type !== "message" ||
-    messageToRender.role !== "assistant" ||
-    index === lastAssistantMessageIndex;
-
-  return {
-    messageToRender,
-    agentOutput,
-    isFinalMessage,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/helpers.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/helpers.ts
deleted file mode 100644
index f6731c66c7..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/helpers.ts
+++ /dev/null
@@ -1,68 +0,0 @@
-import type { ChatMessageData } from "../ChatMessage/useChatMessage";
-
-export function parseToolResult(
-  result: unknown,
-): Record<string, unknown> | null {
-  try {
-    return typeof result === "string"
-      ? JSON.parse(result)
-      : (result as Record<string, unknown>);
-  } catch {
-    return null;
-  }
-}
-
-export function isAgentOutputResult(result: unknown): boolean {
-  const parsed = parseToolResult(result);
-  return parsed?.type === "agent_output";
-}
-
-export function isToolOutputPattern(content: string): boolean {
-  const normalizedContent = content.toLowerCase().trim();
-
-  return (
-    normalizedContent.startsWith("no agents found") ||
-    normalizedContent.startsWith("no results found") ||
-    normalizedContent.includes("no agents found matching") ||
-    !!normalizedContent.match(/^no \w+ found/i) ||
-    (content.length < 150 && normalizedContent.includes("try different")) ||
-    (content.length < 200 &&
-      !normalizedContent.includes("i'll") &&
-      !normalizedContent.includes("let me") &&
-      !normalizedContent.includes("i can") &&
-      !normalizedContent.includes("i will"))
-  );
-}
-
-export function formatToolResultValue(result: unknown): string {
-  return typeof result === "string"
-    ? result
-    : result
-      ? JSON.stringify(result, null, 2)
-      : "";
-}
-
-export function findLastMessageIndex(
-  messages: ChatMessageData[],
-  predicate: (msg: ChatMessageData) => boolean,
-): number {
-  for (let i = messages.length - 1; i >= 0; i--) {
-    if (predicate(messages[i])) return i;
-  }
-  return -1;
-}
-
-export function shouldSkipAgentOutput(
-  message: ChatMessageData,
-  prevMessage: ChatMessageData | undefined,
-): boolean {
-  if (message.type !== "tool_response" || !message.result) return false;
-
-  const isAgentOutput = isAgentOutputResult(message.result);
-  return (
-    isAgentOutput &&
-    !!prevMessage &&
-    prevMessage.type === "message" &&
-    prevMessage.role === "assistant"
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/useMessageList.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/useMessageList.ts
deleted file mode 100644
index 3dcc75df3c..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/MessageList/useMessageList.ts
+++ /dev/null
@@ -1,28 +0,0 @@
-import { useEffect, useRef, useCallback } from "react";
-
-interface UseMessageListArgs {
-  messageCount: number;
-  isStreaming: boolean;
-}
-
-export function useMessageList({
-  messageCount,
-  isStreaming,
-}: UseMessageListArgs) {
-  const messagesEndRef = useRef<HTMLDivElement>(null);
-  const messagesContainerRef = useRef<HTMLDivElement>(null);
-
-  const scrollToBottom = useCallback(() => {
-    messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
-  }, []);
-
-  useEffect(() => {
-    scrollToBottom();
-  }, [messageCount, isStreaming, scrollToBottom]);
-
-  return {
-    messagesEndRef,
-    messagesContainerRef,
-    scrollToBottom,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/NoResultsMessage/NoResultsMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/NoResultsMessage/NoResultsMessage.tsx
deleted file mode 100644
index b6adc8b93c..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/NoResultsMessage/NoResultsMessage.tsx
+++ /dev/null
@@ -1,64 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { MagnifyingGlass, X } from "@phosphor-icons/react";
-
-export interface NoResultsMessageProps {
-  message: string;
-  suggestions?: string[];
-  className?: string;
-}
-
-export function NoResultsMessage({
-  message,
-  suggestions = [],
-  className,
-}: NoResultsMessageProps) {
-  return (
-    <div
-      className={cn(
-        "mx-4 my-2 flex flex-col items-center gap-4 rounded-lg border border-gray-200 bg-gray-50 p-6",
-        className,
-      )}
-    >
-      {/* Icon */}
-      <div className="relative flex h-16 w-16 items-center justify-center">
-        <div className="flex h-16 w-16 items-center justify-center rounded-full bg-gray-200">
-          <MagnifyingGlass size={32} weight="bold" className="text-gray-500" />
-        </div>
-        <div className="absolute -right-1 -top-1 flex h-8 w-8 items-center justify-center rounded-full bg-gray-400">
-          <X size={20} weight="bold" className="text-white" />
-        </div>
-      </div>
-
-      {/* Content */}
-      <div className="text-center">
-        <Text variant="h3" className="mb-2 text-gray-900">
-          No Results Found
-        </Text>
-        <Text variant="body" className="text-gray-700">
-          {message}
-        </Text>
-      </div>
-
-      {/* Suggestions */}
-      {suggestions.length > 0 && (
-        <div className="w-full space-y-2">
-          <Text variant="small" className="font-semibold text-gray-900">
-            Try these suggestions:
-          </Text>
-          <ul className="space-y-1 rounded-md bg-gray-100 p-4">
-            {suggestions.map((suggestion, index) => (
-              <li
-                key={index}
-                className="flex items-start gap-2 text-sm text-gray-700"
-              >
-                <span className="mt-1 text-gray-500">•</span>
-                <span>{suggestion}</span>
-              </li>
-            ))}
-          </ul>
-        </div>
-      )}
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/PendingOperationWidget/PendingOperationWidget.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/PendingOperationWidget/PendingOperationWidget.tsx
deleted file mode 100644
index 6cfea7f327..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/PendingOperationWidget/PendingOperationWidget.tsx
+++ /dev/null
@@ -1,109 +0,0 @@
-"use client";
-
-import { Card } from "@/components/atoms/Card/Card";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import { CircleNotch, CheckCircle, XCircle } from "@phosphor-icons/react";
-
-type OperationStatus =
-  | "pending"
-  | "started"
-  | "in_progress"
-  | "completed"
-  | "error";
-
-interface Props {
-  status: OperationStatus;
-  message: string;
-  toolName?: string;
-  className?: string;
-}
-
-function getOperationTitle(toolName?: string): string {
-  if (!toolName) return "Operation";
-  // Convert tool name to human-readable format
-  // e.g., "create_agent" -> "Creating Agent", "edit_agent" -> "Editing Agent"
-  if (toolName === "create_agent") return "Creating Agent";
-  if (toolName === "edit_agent") return "Editing Agent";
-  // Default: capitalize and format tool name
-  return toolName
-    .split("_")
-    .map((word) => word.charAt(0).toUpperCase() + word.slice(1))
-    .join(" ");
-}
-
-export function PendingOperationWidget({
-  status,
-  message,
-  toolName,
-  className,
-}: Props) {
-  const isPending =
-    status === "pending" || status === "started" || status === "in_progress";
-  const isCompleted = status === "completed";
-  const isError = status === "error";
-
-  const operationTitle = getOperationTitle(toolName);
-
-  return (
-    <div
-      className={cn(
-        "group relative flex w-full justify-start gap-3 px-4 py-3",
-        className,
-      )}
-    >
-      <div className="flex w-full max-w-3xl gap-3">
-        <div className="flex-shrink-0">
-          <div
-            className={cn(
-              "flex h-7 w-7 items-center justify-center rounded-lg",
-              isPending && "bg-blue-500",
-              isCompleted && "bg-green-500",
-              isError && "bg-red-500",
-            )}
-          >
-            {isPending && (
-              <CircleNotch
-                className="h-4 w-4 animate-spin text-white"
-                weight="bold"
-              />
-            )}
-            {isCompleted && (
-              <CheckCircle className="h-4 w-4 text-white" weight="bold" />
-            )}
-            {isError && (
-              <XCircle className="h-4 w-4 text-white" weight="bold" />
-            )}
-          </div>
-        </div>
-
-        <div className="flex min-w-0 flex-1 flex-col">
-          <Card className="space-y-2 p-4">
-            <div>
-              <Text variant="h4" className="mb-1 text-slate-900">
-                {isPending && operationTitle}
-                {isCompleted && `${operationTitle} Complete`}
-                {isError && `${operationTitle} Failed`}
-              </Text>
-              <Text variant="small" className="text-slate-600">
-                {message}
-              </Text>
-            </div>
-
-            {isPending && (
-              <Text variant="small" className="italic text-slate-500">
-                Check your library in a few minutes.
-              </Text>
-            )}
-
-            {toolName && (
-              <Text variant="small" className="text-slate-400">
-                Tool: {toolName}
-              </Text>
-            )}
-          </Card>
-        </div>
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/QuickActionsWelcome/QuickActionsWelcome.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/QuickActionsWelcome/QuickActionsWelcome.tsx
deleted file mode 100644
index dd76fd9fb6..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/QuickActionsWelcome/QuickActionsWelcome.tsx
+++ /dev/null
@@ -1,94 +0,0 @@
-"use client";
-
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-
-export interface QuickActionsWelcomeProps {
-  title: string;
-  description: string;
-  actions: string[];
-  onActionClick: (action: string) => void;
-  disabled?: boolean;
-  className?: string;
-}
-
-export function QuickActionsWelcome({
-  title,
-  description,
-  actions,
-  onActionClick,
-  disabled = false,
-  className,
-}: QuickActionsWelcomeProps) {
-  return (
-    <div
-      className={cn("flex flex-1 items-center justify-center p-8", className)}
-    >
-      <div className="w-full max-w-3xl">
-        <div className="mb-12 text-center">
-          <Text
-            variant="h2"
-            className="mb-3 text-2xl font-semibold text-zinc-900"
-          >
-            {title}
-          </Text>
-          <Text variant="body" className="text-zinc-500">
-            {description}
-          </Text>
-        </div>
-        <div className="grid gap-3 sm:grid-cols-2">
-          {actions.map((action) => {
-            // Use slate theme for all cards
-            const theme = {
-              bg: "bg-slate-50/10",
-              border: "border-slate-100",
-              hoverBg: "hover:bg-slate-50/20",
-              hoverBorder: "hover:border-slate-200",
-              gradient: "from-slate-200/20 via-slate-300/10 to-transparent",
-              text: "text-slate-900",
-              hoverText: "group-hover:text-slate-900",
-            };
-
-            return (
-              <button
-                key={action}
-                onClick={() => onActionClick(action)}
-                disabled={disabled}
-                className={cn(
-                  "group relative overflow-hidden rounded-xl border p-5 text-left backdrop-blur-xl",
-                  "transition-all duration-200",
-                  theme.bg,
-                  theme.border,
-                  theme.hoverBg,
-                  theme.hoverBorder,
-                  "hover:shadow-sm",
-                  "focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-white/50 focus-visible:ring-offset-2",
-                  "disabled:cursor-not-allowed disabled:opacity-50 disabled:hover:shadow-none",
-                )}
-              >
-                {/* Gradient flare background */}
-                <div
-                  className={cn(
-                    "absolute inset-0 bg-gradient-to-br",
-                    theme.gradient,
-                  )}
-                />
-
-                <Text
-                  variant="body"
-                  className={cn(
-                    "relative z-10 font-medium",
-                    theme.text,
-                    theme.hoverText,
-                  )}
-                >
-                  {action}
-                </Text>
-              </button>
-            );
-          })}
-        </div>
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/SessionsDrawer/SessionsDrawer.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/SessionsDrawer/SessionsDrawer.tsx
deleted file mode 100644
index ee2896f1e2..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/SessionsDrawer/SessionsDrawer.tsx
+++ /dev/null
@@ -1,136 +0,0 @@
-"use client";
-
-import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
-import { Text } from "@/components/atoms/Text/Text";
-import { scrollbarStyles } from "@/components/styles/scrollbars";
-import { cn } from "@/lib/utils";
-import { X } from "@phosphor-icons/react";
-import { formatDistanceToNow } from "date-fns";
-import { Drawer } from "vaul";
-
-interface SessionsDrawerProps {
-  isOpen: boolean;
-  onClose: () => void;
-  onSelectSession: (sessionId: string) => void;
-  currentSessionId?: string | null;
-}
-
-export function SessionsDrawer({
-  isOpen,
-  onClose,
-  onSelectSession,
-  currentSessionId,
-}: SessionsDrawerProps) {
-  const { data, isLoading } = useGetV2ListSessions(
-    { limit: 100 },
-    {
-      query: {
-        enabled: isOpen,
-      },
-    },
-  );
-
-  const sessions =
-    data?.status === 200
-      ? data.data.sessions.filter((session) => {
-          // Filter out sessions without messages (sessions that were never updated)
-          // If updated_at equals created_at, the session was created but never had messages
-          return session.updated_at !== session.created_at;
-        })
-      : [];
-
-  function handleSelectSession(sessionId: string) {
-    onSelectSession(sessionId);
-    onClose();
-  }
-
-  return (
-    <Drawer.Root
-      open={isOpen}
-      onOpenChange={(open) => !open && onClose()}
-      direction="right"
-    >
-      <Drawer.Portal>
-        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
-        <Drawer.Content
-          className={cn(
-            "fixed right-0 top-0 z-[70] flex h-full w-96 flex-col border-l border-zinc-200 bg-white",
-            scrollbarStyles,
-          )}
-        >
-          <div className="shrink-0 p-4">
-            <div className="flex items-center justify-between">
-              <Drawer.Title className="text-lg font-semibold">
-                Chat Sessions
-              </Drawer.Title>
-              <button
-                aria-label="Close"
-                onClick={onClose}
-                className="flex size-8 items-center justify-center rounded hover:bg-zinc-100"
-              >
-                <X width="1.25rem" height="1.25rem" />
-              </button>
-            </div>
-          </div>
-
-          <div className="flex-1 overflow-y-auto p-4">
-            {isLoading ? (
-              <div className="flex items-center justify-center py-8">
-                <Text variant="body" className="text-zinc-500">
-                  Loading sessions...
-                </Text>
-              </div>
-            ) : sessions.length === 0 ? (
-              <div className="flex h-full items-center justify-center">
-                <Text variant="body" className="text-zinc-500">
-                  You don&apos;t have previously started chats
-                </Text>
-              </div>
-            ) : (
-              <div className="space-y-2">
-                {sessions.map((session) => {
-                  const isActive = session.id === currentSessionId;
-                  const updatedAt = session.updated_at
-                    ? formatDistanceToNow(new Date(session.updated_at), {
-                        addSuffix: true,
-                      })
-                    : "";
-
-                  return (
-                    <button
-                      key={session.id}
-                      onClick={() => handleSelectSession(session.id)}
-                      className={cn(
-                        "w-full rounded-lg border p-3 text-left transition-colors",
-                        isActive
-                          ? "border-indigo-500 bg-zinc-50"
-                          : "border-zinc-200 bg-zinc-100/50 hover:border-zinc-300 hover:bg-zinc-50",
-                      )}
-                    >
-                      <div className="flex flex-col gap-1">
-                        <Text
-                          variant="body"
-                          className={cn(
-                            "font-medium",
-                            isActive ? "text-indigo-900" : "text-zinc-900",
-                          )}
-                        >
-                          {session.title || "Untitled Chat"}
-                        </Text>
-                        <div className="flex items-center gap-2 text-xs text-zinc-500">
-                          <span>{session.id.slice(0, 8)}...</span>
-                          {updatedAt && <span>•</span>}
-                          <span>{updatedAt}</span>
-                        </div>
-                      </div>
-                    </button>
-                  );
-                })}
-              </div>
-            )}
-          </div>
-        </Drawer.Content>
-      </Drawer.Portal>
-    </Drawer.Root>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/StreamingMessage/StreamingMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/StreamingMessage/StreamingMessage.tsx
deleted file mode 100644
index 5b1f8b1617..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/StreamingMessage/StreamingMessage.tsx
+++ /dev/null
@@ -1,35 +0,0 @@
-import { cn } from "@/lib/utils";
-import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
-import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
-import { useStreamingMessage } from "./useStreamingMessage";
-
-export interface StreamingMessageProps {
-  chunks: string[];
-  className?: string;
-  onComplete?: () => void;
-}
-
-export function StreamingMessage({
-  chunks,
-  className,
-  onComplete,
-}: StreamingMessageProps) {
-  const { displayText } = useStreamingMessage({ chunks, onComplete });
-
-  return (
-    <div
-      className={cn(
-        "group relative flex w-full justify-start gap-3 px-4 py-3",
-        className,
-      )}
-    >
-      <div className="flex w-full max-w-3xl gap-3">
-        <div className="flex min-w-0 flex-1 flex-col">
-          <AIChatBubble>
-            <MarkdownContent content={displayText} />
-          </AIChatBubble>
-        </div>
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/StreamingMessage/useStreamingMessage.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/StreamingMessage/useStreamingMessage.ts
deleted file mode 100644
index 5203762151..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/StreamingMessage/useStreamingMessage.ts
+++ /dev/null
@@ -1,25 +0,0 @@
-import { useEffect, useState } from "react";
-
-interface UseStreamingMessageArgs {
-  chunks: string[];
-  onComplete?: () => void;
-}
-
-export function useStreamingMessage({
-  chunks,
-  onComplete,
-}: UseStreamingMessageArgs) {
-  const [isComplete, _setIsComplete] = useState(false);
-  const displayText = chunks.join("");
-
-  useEffect(() => {
-    if (isComplete && onComplete) {
-      onComplete();
-    }
-  }, [isComplete, onComplete]);
-
-  return {
-    displayText,
-    isComplete,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ThinkingMessage/ThinkingMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ThinkingMessage/ThinkingMessage.tsx
deleted file mode 100644
index 047c2277b0..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ThinkingMessage/ThinkingMessage.tsx
+++ /dev/null
@@ -1,70 +0,0 @@
-import { cn } from "@/lib/utils";
-import { useEffect, useRef, useState } from "react";
-import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
-
-export interface ThinkingMessageProps {
-  className?: string;
-}
-
-export function ThinkingMessage({ className }: ThinkingMessageProps) {
-  const [showSlowLoader, setShowSlowLoader] = useState(false);
-  const [showCoffeeMessage, setShowCoffeeMessage] = useState(false);
-  const timerRef = useRef<NodeJS.Timeout | null>(null);
-  const coffeeTimerRef = useRef<NodeJS.Timeout | null>(null);
-
-  useEffect(() => {
-    if (timerRef.current === null) {
-      timerRef.current = setTimeout(() => {
-        setShowSlowLoader(true);
-      }, 8000);
-    }
-
-    if (coffeeTimerRef.current === null) {
-      coffeeTimerRef.current = setTimeout(() => {
-        setShowCoffeeMessage(true);
-      }, 10000);
-    }
-
-    return () => {
-      if (timerRef.current) {
-        clearTimeout(timerRef.current);
-        timerRef.current = null;
-      }
-      if (coffeeTimerRef.current) {
-        clearTimeout(coffeeTimerRef.current);
-        coffeeTimerRef.current = null;
-      }
-    };
-  }, []);
-
-  return (
-    <div
-      className={cn(
-        "group relative flex w-full justify-start gap-3 px-4 py-3",
-        className,
-      )}
-    >
-      <div className="flex w-full max-w-3xl gap-3">
-        <div className="flex min-w-0 flex-1 flex-col">
-          <AIChatBubble>
-            <div className="transition-all duration-500 ease-in-out">
-              {showCoffeeMessage ? (
-                <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
-                  This could take a few minutes, grab a coffee ☕️
-                </span>
-              ) : showSlowLoader ? (
-                <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
-                  Taking a bit more time...
-                </span>
-              ) : (
-                <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
-                  Thinking...
-                </span>
-              )}
-            </div>
-          </AIChatBubble>
-        </div>
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolCallMessage/ToolCallMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolCallMessage/ToolCallMessage.tsx
deleted file mode 100644
index 67aa975f15..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolCallMessage/ToolCallMessage.tsx
+++ /dev/null
@@ -1,55 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import type { ToolArguments } from "@/types/chat";
-import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
-import {
-  formatToolArguments,
-  getToolActionPhrase,
-  getToolIcon,
-} from "./helpers";
-
-export interface ToolCallMessageProps {
-  toolId?: string;
-  toolName: string;
-  arguments?: ToolArguments;
-  isStreaming?: boolean;
-  className?: string;
-}
-
-export function ToolCallMessage({
-  toolName,
-  arguments: toolArguments,
-  isStreaming = false,
-  className,
-}: ToolCallMessageProps) {
-  const actionPhrase = getToolActionPhrase(toolName);
-  const argumentsText = formatToolArguments(toolName, toolArguments);
-  const displayText = `${actionPhrase}${argumentsText}`;
-  const IconComponent = getToolIcon(toolName);
-
-  return (
-    <AIChatBubble className={className}>
-      <div className="flex items-center gap-2">
-        <IconComponent
-          size={14}
-          weight={isStreaming ? "regular" : "regular"}
-          className={cn(
-            "shrink-0",
-            isStreaming ? "text-neutral-500" : "text-neutral-400",
-          )}
-        />
-        <Text
-          variant="small"
-          className={cn(
-            "text-xs",
-            isStreaming
-              ? "bg-gradient-to-r from-neutral-600 via-neutral-500 to-neutral-600 bg-[length:200%_100%] bg-clip-text text-transparent [animation:shimmer_2s_ease-in-out_infinite]"
-              : "text-neutral-500",
-          )}
-        >
-          {displayText}
-        </Text>
-      </div>
-    </AIChatBubble>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolCallMessage/helpers.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolCallMessage/helpers.ts
deleted file mode 100644
index 2f9f50b455..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolCallMessage/helpers.ts
+++ /dev/null
@@ -1,184 +0,0 @@
-import type { ToolArguments } from "@/types/chat";
-import {
-  BrainIcon,
-  EyeIcon,
-  FileMagnifyingGlassIcon,
-  FileTextIcon,
-  MagnifyingGlassIcon,
-  PackageIcon,
-  PencilLineIcon,
-  PlayIcon,
-  PlusIcon,
-  SquaresFourIcon,
-  type Icon,
-} from "@phosphor-icons/react";
-
-/**
- * Maps internal tool names to human-friendly action phrases (present continuous).
- * Used for tool call messages to indicate what action is currently happening.
- *
- * @param toolName - The internal tool name from the backend
- * @returns A human-friendly action phrase in present continuous tense
- */
-export function getToolActionPhrase(toolName: string): string {
-  const normalizedName = toolName.trim();
-  if (!normalizedName) return "Executing";
-  if (normalizedName.toLowerCase().startsWith("executing")) {
-    return normalizedName;
-  }
-  if (normalizedName.toLowerCase() === "unknown") return "Executing";
-  const toolActionPhrases: Record<string, string> = {
-    add_understanding: "Updating your business information",
-    create_agent: "Creating a new agent",
-    edit_agent: "Editing the agent",
-    find_agent: "Looking for agents in the marketplace",
-    find_block: "Searching for blocks",
-    find_library_agent: "Looking for library agents",
-    run_agent: "Running the agent",
-    run_block: "Running the block",
-    view_agent_output: "Retrieving agent output",
-    search_docs: "Searching documentation",
-    get_doc_page: "Loading documentation page",
-    agent_carousel: "Looking for agents in the marketplace",
-    execution_started: "Running the agent",
-    get_required_setup_info: "Getting setup requirements",
-    schedule_agent: "Scheduling the agent to run",
-  };
-
-  // Return mapped phrase or generate human-friendly fallback
-  return (
-    toolActionPhrases[toolName] ||
-    toolName
-      .replace(/_/g, " ")
-      .replace(/\b\w/g, (l) => l.toUpperCase())
-      .replace(/^/, "Executing ")
-  );
-}
-
-/**
- * Formats tool call arguments into user-friendly text.
- * Handles different tool types and formats their arguments nicely.
- *
- * @param toolName - The tool name
- * @param args - The tool arguments
- * @returns Formatted user-friendly text to append to action phrase
- */
-export function formatToolArguments(
-  toolName: string,
-  args: ToolArguments | undefined,
-): string {
-  if (!args || Object.keys(args).length === 0) {
-    return "";
-  }
-
-  switch (toolName) {
-    case "find_agent":
-    case "find_library_agent":
-    case "agent_carousel":
-      if (args.query) {
-        return ` matching "${args.query as string}"`;
-      }
-      break;
-
-    case "find_block":
-      if (args.query) {
-        return ` matching "${args.query as string}"`;
-      }
-      break;
-
-    case "search_docs":
-      if (args.query) {
-        return ` for "${args.query as string}"`;
-      }
-      break;
-
-    case "get_doc_page":
-      if (args.path) {
-        return ` "${args.path as string}"`;
-      }
-      break;
-
-    case "run_agent":
-      if (args.username_agent_slug) {
-        return ` "${args.username_agent_slug as string}"`;
-      }
-      if (args.library_agent_id) {
-        return ` (library agent)`;
-      }
-      break;
-
-    case "run_block":
-      if (args.block_id) {
-        return ` "${args.block_id as string}"`;
-      }
-      break;
-
-    case "view_agent_output":
-      if (args.library_agent_id) {
-        return ` (library agent)`;
-      }
-      if (args.username_agent_slug) {
-        return ` "${args.username_agent_slug as string}"`;
-      }
-      break;
-
-    case "create_agent":
-    case "edit_agent":
-      if (args.name) {
-        return ` "${args.name as string}"`;
-      }
-      break;
-
-    case "add_understanding":
-      const understandingFields = Object.entries(args)
-        .filter(
-          ([_, value]) => value !== null && value !== undefined && value !== "",
-        )
-        .map(([key, value]) => {
-          if (key === "user_name" && typeof value === "string") {
-            return `for ${value}`;
-          }
-          if (typeof value === "string") {
-            return `${key}: ${value}`;
-          }
-          if (Array.isArray(value) && value.length > 0) {
-            return `${key}: ${value.slice(0, 2).join(", ")}${value.length > 2 ? ` (+${value.length - 2} more)` : ""}`;
-          }
-          return key;
-        });
-      if (understandingFields.length > 0) {
-        return ` ${understandingFields[0]}`;
-      }
-      break;
-  }
-
-  return "";
-}
-
-/**
- * Maps tool names to their corresponding Phosphor icon components.
- *
- * @param toolName - The tool name from the backend
- * @returns The Icon component for the tool
- */
-export function getToolIcon(toolName: string): Icon {
-  const iconMap: Record<string, Icon> = {
-    add_understanding: BrainIcon,
-    create_agent: PlusIcon,
-    edit_agent: PencilLineIcon,
-    find_agent: SquaresFourIcon,
-    find_library_agent: MagnifyingGlassIcon,
-    find_block: PackageIcon,
-    run_agent: PlayIcon,
-    run_block: PlayIcon,
-    view_agent_output: EyeIcon,
-    search_docs: FileMagnifyingGlassIcon,
-    get_doc_page: FileTextIcon,
-    agent_carousel: MagnifyingGlassIcon,
-    execution_started: PlayIcon,
-    get_required_setup_info: SquaresFourIcon,
-    schedule_agent: PlayIcon,
-  };
-
-  return iconMap[toolName] || SquaresFourIcon;
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/ToolResponseMessage.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/ToolResponseMessage.tsx
deleted file mode 100644
index 27da02beb8..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/ToolResponseMessage.tsx
+++ /dev/null
@@ -1,53 +0,0 @@
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-import type { ToolResult } from "@/types/chat";
-import { WarningCircleIcon } from "@phosphor-icons/react";
-import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
-import { MarkdownContent } from "../MarkdownContent/MarkdownContent";
-import {
-  formatToolResponse,
-  getErrorMessage,
-  isErrorResponse,
-} from "./helpers";
-
-export interface ToolResponseMessageProps {
-  toolId?: string;
-  toolName: string;
-  result?: ToolResult;
-  success?: boolean;
-  className?: string;
-}
-
-export function ToolResponseMessage({
-  toolId: _toolId,
-  toolName,
-  result,
-  success: _success,
-  className,
-}: ToolResponseMessageProps) {
-  if (isErrorResponse(result)) {
-    const errorMessage = getErrorMessage(result);
-    return (
-      <AIChatBubble className={className}>
-        <div className="flex items-center gap-2">
-          <WarningCircleIcon
-            size={14}
-            weight="regular"
-            className="shrink-0 text-neutral-400"
-          />
-          <Text variant="small" className={cn("text-xs text-neutral-500")}>
-            {errorMessage}
-          </Text>
-        </div>
-      </AIChatBubble>
-    );
-  }
-
-  const formattedText = formatToolResponse(result, toolName);
-
-  return (
-    <AIChatBubble className={className}>
-      <MarkdownContent content={formattedText} />
-    </AIChatBubble>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/helpers.ts b/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/helpers.ts
deleted file mode 100644
index e886e1a28c..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ToolResponseMessage/helpers.ts
+++ /dev/null
@@ -1,392 +0,0 @@
-function stripInternalReasoning(content: string): string {
-  return content
-    .replace(/<internal_reasoning>[\s\S]*?<\/internal_reasoning>/gi, "")
-    .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
-    .replace(/\n{3,}/g, "\n\n")
-    .trim();
-}
-
-export function isErrorResponse(result: unknown): boolean {
-  if (typeof result === "string") {
-    const lower = result.toLowerCase();
-    return (
-      lower.startsWith("error:") ||
-      lower.includes("not found") ||
-      lower.includes("does not exist") ||
-      lower.includes("failed to") ||
-      lower.includes("unable to")
-    );
-  }
-  if (typeof result === "object" && result !== null) {
-    const response = result as Record<string, unknown>;
-    return response.type === "error" || response.error !== undefined;
-  }
-  return false;
-}
-
-export function getErrorMessage(result: unknown): string {
-  if (typeof result === "string") {
-    return stripInternalReasoning(result.replace(/^error:\s*/i, ""));
-  }
-  if (typeof result === "object" && result !== null) {
-    const response = result as Record<string, unknown>;
-    if (response.error) return stripInternalReasoning(String(response.error));
-    if (response.message)
-      return stripInternalReasoning(String(response.message));
-  }
-  return "An error occurred";
-}
-
-/**
- * Check if a value is a workspace file reference.
- */
-function isWorkspaceRef(value: unknown): value is string {
-  return typeof value === "string" && value.startsWith("workspace://");
-}
-
-/**
- * Check if a workspace reference appears to be an image based on common patterns.
- * Since workspace refs don't have extensions, we check the context or assume image
- * for certain block types.
- *
- * TODO: Replace keyword matching with MIME type encoded in workspace ref.
- * e.g., workspace://abc123#image/png or workspace://abc123#video/mp4
- * This would let frontend render correctly without fragile keyword matching.
- */
-function isLikelyImageRef(value: string, outputKey?: string): boolean {
-  if (!isWorkspaceRef(value)) return false;
-
-  // Check output key name for video-related hints (these are NOT images)
-  const videoKeywords = ["video", "mp4", "mov", "avi", "webm", "movie", "clip"];
-  if (outputKey) {
-    const lowerKey = outputKey.toLowerCase();
-    if (videoKeywords.some((kw) => lowerKey.includes(kw))) {
-      return false;
-    }
-  }
-
-  // Check output key name for image-related hints
-  const imageKeywords = [
-    "image",
-    "img",
-    "photo",
-    "picture",
-    "thumbnail",
-    "avatar",
-    "icon",
-    "screenshot",
-  ];
-  if (outputKey) {
-    const lowerKey = outputKey.toLowerCase();
-    if (imageKeywords.some((kw) => lowerKey.includes(kw))) {
-      return true;
-    }
-  }
-
-  // Default to treating workspace refs as potential images
-  // since that's the most common case for generated content
-  return true;
-}
-
-/**
- * Format a single output value, converting workspace refs to markdown images.
- */
-function formatOutputValue(value: unknown, outputKey?: string): string {
-  if (isWorkspaceRef(value) && isLikelyImageRef(value, outputKey)) {
-    // Format as markdown image
-    return `![${outputKey || "Generated image"}](${value})`;
-  }
-
-  if (typeof value === "string") {
-    // Check for data URIs (images)
-    if (value.startsWith("data:image/")) {
-      return `![${outputKey || "Generated image"}](${value})`;
-    }
-    return value;
-  }
-
-  if (Array.isArray(value)) {
-    return value
-      .map((item, idx) => formatOutputValue(item, `${outputKey}_${idx}`))
-      .join("\n\n");
-  }
-
-  if (typeof value === "object" && value !== null) {
-    return JSON.stringify(value, null, 2);
-  }
-
-  return String(value);
-}
-
-function getToolCompletionPhrase(toolName: string): string {
-  const toolCompletionPhrases: Record<string, string> = {
-    add_understanding: "Updated your business information",
-    create_agent: "Created the agent",
-    edit_agent: "Updated the agent",
-    find_agent: "Found agents in the marketplace",
-    find_block: "Found blocks",
-    find_library_agent: "Found library agents",
-    run_agent: "Started agent execution",
-    run_block: "Executed the block",
-    view_agent_output: "Retrieved agent output",
-    search_docs: "Found documentation",
-    get_doc_page: "Loaded documentation page",
-  };
-
-  // Return mapped phrase or generate human-friendly fallback
-  return (
-    toolCompletionPhrases[toolName] ||
-    `Completed ${toolName.replace(/_/g, " ").replace("...", "")}`
-  );
-}
-
-export function formatToolResponse(result: unknown, toolName: string): string {
-  if (typeof result === "string") {
-    const trimmed = result.trim();
-    if (trimmed.startsWith("{") && trimmed.endsWith("}")) {
-      try {
-        const parsed = JSON.parse(trimmed);
-        return formatToolResponse(parsed, toolName);
-      } catch {
-        return stripInternalReasoning(trimmed);
-      }
-    }
-    return stripInternalReasoning(result);
-  }
-
-  if (typeof result !== "object" || result === null) {
-    return String(result);
-  }
-
-  const response = result as Record<string, unknown>;
-
-  // Handle different response types
-  const responseType = response.type as string | undefined;
-
-  if (!responseType) {
-    if (response.message) {
-      return String(response.message);
-    }
-    return getToolCompletionPhrase(toolName);
-  }
-
-  switch (responseType) {
-    case "agents_found":
-      const agents = (response.agents as Array<{ name: string }>) || [];
-      const count =
-        typeof response.count === "number" && !isNaN(response.count)
-          ? response.count
-          : agents.length;
-      if (count === 0) {
-        return "No agents found matching your search.";
-      }
-      return `Found ${count} agent${count === 1 ? "" : "s"}: ${agents
-        .slice(0, 3)
-        .map((a) => a.name)
-        .join(", ")}${count > 3 ? ` and ${count - 3} more` : ""}`;
-
-    case "agent_details":
-      const agent = response.agent as { name: string; description?: string };
-      if (agent) {
-        return `Agent: ${agent.name}${agent.description ? `\n\n${agent.description}` : ""}`;
-      }
-      break;
-
-    case "block_list":
-      const blocks = (response.blocks as Array<{ name: string }>) || [];
-      const blockCount =
-        typeof response.count === "number" && !isNaN(response.count)
-          ? response.count
-          : blocks.length;
-      if (blockCount === 0) {
-        return "No blocks found matching your search.";
-      }
-      return `Found ${blockCount} block${blockCount === 1 ? "" : "s"}: ${blocks
-        .slice(0, 3)
-        .map((b) => b.name)
-        .join(", ")}${blockCount > 3 ? ` and ${blockCount - 3} more` : ""}`;
-
-    case "block_output":
-      const blockName = (response.block_name as string) || "Block";
-      const outputs = response.outputs as Record<string, unknown[]> | undefined;
-      if (outputs && Object.keys(outputs).length > 0) {
-        const formattedOutputs: string[] = [];
-
-        for (const [key, values] of Object.entries(outputs)) {
-          if (!Array.isArray(values) || values.length === 0) continue;
-
-          // Format each value in the output array
-          for (const value of values) {
-            const formatted = formatOutputValue(value, key);
-            if (formatted) {
-              formattedOutputs.push(formatted);
-            }
-          }
-        }
-
-        if (formattedOutputs.length > 0) {
-          return `${blockName} executed successfully.\n\n${formattedOutputs.join("\n\n")}`;
-        }
-        return `${blockName} executed successfully.`;
-      }
-      return `${blockName} executed successfully.`;
-
-    case "doc_search_results":
-      const docResults = (response.results as Array<{ title: string }>) || [];
-      const docCount =
-        typeof response.count === "number" && !isNaN(response.count)
-          ? response.count
-          : docResults.length;
-      if (docCount === 0) {
-        return "No documentation found matching your search.";
-      }
-      return `Found ${docCount} documentation result${docCount === 1 ? "" : "s"}: ${docResults
-        .slice(0, 3)
-        .map((r) => r.title)
-        .join(", ")}${docCount > 3 ? ` and ${docCount - 3} more` : ""}`;
-
-    case "doc_page":
-      const title = (response.title as string) || "Documentation";
-      const content = (response.content as string) || "";
-      if (content) {
-        const preview = content.substring(0, 200).trim();
-        return `${title}\n\n${preview}${content.length > 200 ? "..." : ""}`;
-      }
-      return title;
-
-    case "understanding_updated":
-      const currentUnderstanding = response.current_understanding as
-        | Record<string, unknown>
-        | undefined;
-      const fields = (response.updated_fields as string[]) || [];
-
-      if (response.message && typeof response.message === "string") {
-        let message = response.message;
-        if (currentUnderstanding) {
-          for (const [key, value] of Object.entries(currentUnderstanding)) {
-            if (value !== null && value !== undefined && value !== "") {
-              const placeholder = key;
-              const actualValue = String(value);
-              message = message.replace(
-                new RegExp(`\\b${placeholder}\\b`, "g"),
-                actualValue,
-              );
-            }
-          }
-        }
-        return message;
-      }
-
-      if (
-        currentUnderstanding &&
-        Object.keys(currentUnderstanding).length > 0
-      ) {
-        const understandingEntries = Object.entries(currentUnderstanding)
-          .filter(
-            ([_, value]) =>
-              value !== null && value !== undefined && value !== "",
-          )
-          .map(([key, value]) => {
-            if (key === "user_name" && typeof value === "string") {
-              return `Updated information for ${value}`;
-            }
-            return `${key}: ${String(value)}`;
-          });
-        if (understandingEntries.length > 0) {
-          return understandingEntries[0];
-        }
-      }
-      if (fields.length > 0) {
-        return `Updated business information: ${fields.join(", ")}`;
-      }
-      return "Updated your business information.";
-
-    case "agent_saved":
-      const agentName = (response.agent_name as string) || "Agent";
-      return `Successfully saved "${agentName}" to your library.`;
-
-    case "agent_preview":
-      const previewAgentName = (response.agent_name as string) || "Agent";
-      const nodeCount = (response.node_count as number) || 0;
-      const linkCount = (response.link_count as number) || 0;
-      const description = (response.description as string) || "";
-      let previewText = `Preview: "${previewAgentName}"`;
-      if (description) {
-        previewText += `\n\n${description}`;
-      }
-      previewText += `\n\n${nodeCount} node${nodeCount === 1 ? "" : "s"}, ${linkCount} link${linkCount === 1 ? "" : "s"}`;
-      return previewText;
-
-    case "clarification_needed":
-      const questions =
-        (response.questions as Array<{ question: string }>) || [];
-      if (questions.length === 0) {
-        return response.message
-          ? String(response.message)
-          : "I need more information to proceed.";
-      }
-      if (questions.length === 1) {
-        return questions[0].question;
-      }
-      return `I need clarification on ${questions.length} points:\n\n${questions
-        .map((q, i) => `${i + 1}. ${q.question}`)
-        .join("\n")}`;
-
-    case "agent_output":
-      if (response.message) {
-        return String(response.message);
-      }
-      const outputAgentName = (response.agent_name as string) || "Agent";
-      const execution = response.execution as
-        | {
-            status?: string;
-            outputs?: Record<string, unknown>;
-          }
-        | undefined;
-      if (execution) {
-        const status = execution.status || "completed";
-        const outputs = execution.outputs || {};
-        const outputKeys = Object.keys(outputs);
-        if (outputKeys.length > 0) {
-          return `${outputAgentName} execution ${status}. Outputs: ${outputKeys.join(", ")}`;
-        }
-        return `${outputAgentName} execution ${status}.`;
-      }
-      return `${outputAgentName} output retrieved.`;
-
-    case "execution_started":
-      const execAgentName = (response.graph_name as string) || "Agent";
-      if (response.message) {
-        return String(response.message);
-      }
-      return `Started execution of "${execAgentName}".`;
-
-    case "error":
-      const errorMsg =
-        (response.error as string) || response.message || "An error occurred";
-      return `Error: ${errorMsg}`;
-
-    case "no_results":
-      const suggestions = (response.suggestions as string[]) || [];
-      let noResultsText = (response.message as string) || "No results found.";
-      if (suggestions.length > 0) {
-        noResultsText += `\n\nSuggestions: ${suggestions.join(", ")}`;
-      }
-      return noResultsText;
-
-    default:
-      // Try to extract a message field
-      if (response.message) {
-        return String(response.message);
-      }
-      // Fallback: try to stringify nicely
-      if (Object.keys(response).length === 0) {
-        return getToolCompletionPhrase(toolName);
-      }
-      // If we have a response object but no recognized type, try to format it nicely
-      // Don't return raw JSON - return a completion phrase instead
-      return getToolCompletionPhrase(toolName);
-  }
-
-  return getToolCompletionPhrase(toolName);
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/UserChatBubble/UserChatBubble.tsx b/autogpt_platform/frontend/src/components/contextual/Chat/components/UserChatBubble/UserChatBubble.tsx
deleted file mode 100644
index 39a6cb36ad..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/components/UserChatBubble/UserChatBubble.tsx
+++ /dev/null
@@ -1,25 +0,0 @@
-import { cn } from "@/lib/utils";
-import { ReactNode } from "react";
-
-export interface UserChatBubbleProps {
-  children: ReactNode;
-  className?: string;
-}
-
-export function UserChatBubble({ children, className }: UserChatBubbleProps) {
-  return (
-    <div
-      className={cn(
-        "group relative min-w-20 overflow-hidden rounded-xl bg-purple-100 px-3 text-left text-[1rem] leading-relaxed transition-all duration-500 ease-in-out",
-        className,
-      )}
-      style={{
-        borderBottomRightRadius: 0,
-      }}
-    >
-      <div className="relative z-10 text-slate-900 transition-all duration-500 ease-in-out">
-        {children}
-      </div>
-    </div>
-  );
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/stream-executor.ts b/autogpt_platform/frontend/src/components/contextual/Chat/stream-executor.ts
deleted file mode 100644
index b0d970c286..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/stream-executor.ts
+++ /dev/null
@@ -1,142 +0,0 @@
-import type {
-  ActiveStream,
-  StreamChunk,
-  VercelStreamChunk,
-} from "./chat-types";
-import {
-  INITIAL_RETRY_DELAY,
-  MAX_RETRIES,
-  normalizeStreamChunk,
-  parseSSELine,
-} from "./stream-utils";
-
-function notifySubscribers(stream: ActiveStream, chunk: StreamChunk) {
-  stream.chunks.push(chunk);
-  for (const callback of stream.onChunkCallbacks) {
-    try {
-      callback(chunk);
-    } catch (err) {
-      console.warn("[StreamExecutor] Subscriber callback error:", err);
-    }
-  }
-}
-
-export async function executeStream(
-  stream: ActiveStream,
-  message: string,
-  isUserMessage: boolean,
-  context?: { url: string; content: string },
-  retryCount: number = 0,
-): Promise<void> {
-  const { sessionId, abortController } = stream;
-
-  try {
-    const url = `/api/chat/sessions/${sessionId}/stream`;
-    const body = JSON.stringify({
-      message,
-      is_user_message: isUserMessage,
-      context: context || null,
-    });
-
-    const response = await fetch(url, {
-      method: "POST",
-      headers: {
-        "Content-Type": "application/json",
-        Accept: "text/event-stream",
-      },
-      body,
-      signal: abortController.signal,
-    });
-
-    if (!response.ok) {
-      const errorText = await response.text();
-      throw new Error(errorText || `HTTP ${response.status}`);
-    }
-
-    if (!response.body) {
-      throw new Error("Response body is null");
-    }
-
-    const reader = response.body.getReader();
-    const decoder = new TextDecoder();
-    let buffer = "";
-
-    while (true) {
-      const { done, value } = await reader.read();
-
-      if (done) {
-        notifySubscribers(stream, { type: "stream_end" });
-        stream.status = "completed";
-        return;
-      }
-
-      buffer += decoder.decode(value, { stream: true });
-      const lines = buffer.split("\n");
-      buffer = lines.pop() || "";
-
-      for (const line of lines) {
-        const data = parseSSELine(line);
-        if (data !== null) {
-          if (data === "[DONE]") {
-            notifySubscribers(stream, { type: "stream_end" });
-            stream.status = "completed";
-            return;
-          }
-
-          try {
-            const rawChunk = JSON.parse(data) as
-              | StreamChunk
-              | VercelStreamChunk;
-            const chunk = normalizeStreamChunk(rawChunk);
-            if (!chunk) continue;
-
-            notifySubscribers(stream, chunk);
-
-            if (chunk.type === "stream_end") {
-              stream.status = "completed";
-              return;
-            }
-
-            if (chunk.type === "error") {
-              stream.status = "error";
-              stream.error = new Error(
-                chunk.message || chunk.content || "Stream error",
-              );
-              return;
-            }
-          } catch (err) {
-            console.warn("[StreamExecutor] Failed to parse SSE chunk:", err);
-          }
-        }
-      }
-    }
-  } catch (err) {
-    if (err instanceof Error && err.name === "AbortError") {
-      notifySubscribers(stream, { type: "stream_end" });
-      stream.status = "completed";
-      return;
-    }
-
-    if (retryCount < MAX_RETRIES) {
-      const retryDelay = INITIAL_RETRY_DELAY * Math.pow(2, retryCount);
-      console.log(
-        `[StreamExecutor] Retrying in ${retryDelay}ms (attempt ${retryCount + 1}/${MAX_RETRIES})`,
-      );
-      await new Promise((resolve) => setTimeout(resolve, retryDelay));
-      return executeStream(
-        stream,
-        message,
-        isUserMessage,
-        context,
-        retryCount + 1,
-      );
-    }
-
-    stream.status = "error";
-    stream.error = err instanceof Error ? err : new Error("Stream failed");
-    notifySubscribers(stream, {
-      type: "error",
-      message: stream.error.message,
-    });
-  }
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/stream-utils.ts b/autogpt_platform/frontend/src/components/contextual/Chat/stream-utils.ts
deleted file mode 100644
index 4100926e79..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/stream-utils.ts
+++ /dev/null
@@ -1,84 +0,0 @@
-import type { ToolArguments, ToolResult } from "@/types/chat";
-import type { StreamChunk, VercelStreamChunk } from "./chat-types";
-
-const LEGACY_STREAM_TYPES = new Set<StreamChunk["type"]>([
-  "text_chunk",
-  "text_ended",
-  "tool_call",
-  "tool_call_start",
-  "tool_response",
-  "login_needed",
-  "need_login",
-  "credentials_needed",
-  "error",
-  "usage",
-  "stream_end",
-]);
-
-export function isLegacyStreamChunk(
-  chunk: StreamChunk | VercelStreamChunk,
-): chunk is StreamChunk {
-  return LEGACY_STREAM_TYPES.has(chunk.type as StreamChunk["type"]);
-}
-
-export function normalizeStreamChunk(
-  chunk: StreamChunk | VercelStreamChunk,
-): StreamChunk | null {
-  if (isLegacyStreamChunk(chunk)) return chunk;
-
-  switch (chunk.type) {
-    case "text-delta":
-      return { type: "text_chunk", content: chunk.delta };
-    case "text-end":
-      return { type: "text_ended" };
-    case "tool-input-available":
-      return {
-        type: "tool_call_start",
-        tool_id: chunk.toolCallId,
-        tool_name: chunk.toolName,
-        arguments: chunk.input as ToolArguments,
-      };
-    case "tool-output-available":
-      return {
-        type: "tool_response",
-        tool_id: chunk.toolCallId,
-        tool_name: chunk.toolName,
-        result: chunk.output as ToolResult,
-        success: chunk.success ?? true,
-      };
-    case "usage":
-      return {
-        type: "usage",
-        promptTokens: chunk.promptTokens,
-        completionTokens: chunk.completionTokens,
-        totalTokens: chunk.totalTokens,
-      };
-    case "error":
-      return {
-        type: "error",
-        message: chunk.errorText,
-        code: chunk.code,
-        details: chunk.details,
-      };
-    case "finish":
-      return { type: "stream_end" };
-    case "start":
-    case "text-start":
-      return null;
-    case "tool-input-start":
-      return {
-        type: "tool_call_start",
-        tool_id: chunk.toolCallId,
-        tool_name: chunk.toolName,
-        arguments: {},
-      };
-  }
-}
-
-export const MAX_RETRIES = 3;
-export const INITIAL_RETRY_DELAY = 1000;
-
-export function parseSSELine(line: string): string | null {
-  if (line.startsWith("data: ")) return line.slice(6);
-  return null;
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/useChat.ts b/autogpt_platform/frontend/src/components/contextual/Chat/useChat.ts
deleted file mode 100644
index 124301abc4..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/useChat.ts
+++ /dev/null
@@ -1,100 +0,0 @@
-"use client";
-
-import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { useEffect, useRef, useState } from "react";
-import { useChatSession } from "./useChatSession";
-import { useChatStream } from "./useChatStream";
-
-interface UseChatArgs {
-  urlSessionId?: string | null;
-}
-
-export function useChat({ urlSessionId }: UseChatArgs = {}) {
-  const hasClaimedSessionRef = useRef(false);
-  const { user } = useSupabase();
-  const { sendMessage: sendStreamMessage } = useChatStream();
-  const [showLoader, setShowLoader] = useState(false);
-  const {
-    session,
-    sessionId: sessionIdFromHook,
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    isSessionNotFound,
-    createSession,
-    claimSession,
-    clearSession: clearSessionBase,
-    loadSession,
-    startPollingForOperation,
-  } = useChatSession({
-    urlSessionId,
-    autoCreate: false,
-  });
-
-  useEffect(
-    function autoClaimSession() {
-      if (
-        session &&
-        !session.user_id &&
-        user &&
-        !hasClaimedSessionRef.current &&
-        !isLoading &&
-        sessionIdFromHook
-      ) {
-        hasClaimedSessionRef.current = true;
-        claimSession(sessionIdFromHook)
-          .then(() => {
-            sendStreamMessage(
-              sessionIdFromHook,
-              "User has successfully logged in.",
-              () => {},
-              false,
-            ).catch(() => {});
-          })
-          .catch(() => {
-            hasClaimedSessionRef.current = false;
-          });
-      }
-    },
-    [
-      session,
-      user,
-      isLoading,
-      sessionIdFromHook,
-      claimSession,
-      sendStreamMessage,
-    ],
-  );
-
-  useEffect(
-    function showLoaderWithDelay() {
-      if (isLoading || isCreating) {
-        const timer = setTimeout(() => setShowLoader(true), 300);
-        return () => clearTimeout(timer);
-      }
-      setShowLoader(false);
-    },
-    [isLoading, isCreating],
-  );
-
-  function clearSession() {
-    clearSessionBase();
-    hasClaimedSessionRef.current = false;
-  }
-
-  return {
-    session,
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    isSessionNotFound,
-    createSession,
-    clearSession,
-    loadSession,
-    sessionId: sessionIdFromHook,
-    showLoader,
-    startPollingForOperation,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/useChatSession.ts b/autogpt_platform/frontend/src/components/contextual/Chat/useChatSession.ts
deleted file mode 100644
index 936a49936c..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/useChatSession.ts
+++ /dev/null
@@ -1,385 +0,0 @@
-import {
-  getGetV2GetSessionQueryKey,
-  getGetV2GetSessionQueryOptions,
-  getGetV2ListSessionsQueryKey,
-  postV2CreateSession,
-  useGetV2GetSession,
-  usePatchV2SessionAssignUser,
-  usePostV2CreateSession,
-} from "@/app/api/__generated__/endpoints/chat/chat";
-import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
-import { okData } from "@/app/api/helpers";
-import { isValidUUID } from "@/lib/utils";
-import { useQueryClient } from "@tanstack/react-query";
-import { useEffect, useMemo, useRef, useState } from "react";
-import { toast } from "sonner";
-
-interface UseChatSessionArgs {
-  urlSessionId?: string | null;
-  autoCreate?: boolean;
-}
-
-export function useChatSession({
-  urlSessionId,
-  autoCreate = false,
-}: UseChatSessionArgs = {}) {
-  const queryClient = useQueryClient();
-  const [sessionId, setSessionId] = useState<string | null>(null);
-  const [error, setError] = useState<Error | null>(null);
-  const justCreatedSessionIdRef = useRef<string | null>(null);
-
-  useEffect(() => {
-    if (urlSessionId) {
-      if (!isValidUUID(urlSessionId)) {
-        console.error("Invalid session ID format:", urlSessionId);
-        toast.error("Invalid session ID", {
-          description:
-            "The session ID in the URL is not valid. Starting a new session...",
-        });
-        setSessionId(null);
-        return;
-      }
-      setSessionId(urlSessionId);
-    } else if (autoCreate) {
-      setSessionId(null);
-    } else {
-      setSessionId(null);
-    }
-  }, [urlSessionId, autoCreate]);
-
-  const { isPending: isCreating, error: createError } =
-    usePostV2CreateSession();
-
-  const {
-    data: sessionData,
-    isLoading: isLoadingSession,
-    error: loadError,
-    refetch,
-  } = useGetV2GetSession(sessionId || "", {
-    query: {
-      enabled: !!sessionId,
-      select: okData,
-      staleTime: 0,
-      retry: shouldRetrySessionLoad,
-      retryDelay: getSessionRetryDelay,
-    },
-  });
-
-  const { mutateAsync: claimSessionMutation } = usePatchV2SessionAssignUser();
-
-  const session = useMemo(() => {
-    if (sessionData) return sessionData;
-
-    if (sessionId && justCreatedSessionIdRef.current === sessionId) {
-      return {
-        id: sessionId,
-        user_id: null,
-        messages: [],
-        created_at: new Date().toISOString(),
-        updated_at: new Date().toISOString(),
-      } as SessionDetailResponse;
-    }
-    return null;
-  }, [sessionData, sessionId]);
-
-  const messages = session?.messages || [];
-  const isLoading = isCreating || isLoadingSession;
-
-  useEffect(() => {
-    if (createError) {
-      setError(
-        createError instanceof Error
-          ? createError
-          : new Error("Failed to create session"),
-      );
-    } else if (loadError) {
-      setError(
-        loadError instanceof Error
-          ? loadError
-          : new Error("Failed to load session"),
-      );
-    } else {
-      setError(null);
-    }
-  }, [createError, loadError]);
-
-  // Track if we should be polling (set by external callers when they receive operation_started via SSE)
-  const [forcePolling, setForcePolling] = useState(false);
-  // Track if we've seen server acknowledge the pending operation (to avoid clearing forcePolling prematurely)
-  const hasSeenServerPendingRef = useRef(false);
-
-  // Check if there are any pending operations in the messages
-  // Must check all operation types: operation_pending, operation_started, operation_in_progress
-  const hasPendingOperationsFromServer = useMemo(() => {
-    if (!messages || messages.length === 0) return false;
-    const pendingTypes = new Set([
-      "operation_pending",
-      "operation_in_progress",
-      "operation_started",
-    ]);
-    return messages.some((msg) => {
-      if (msg.role !== "tool" || !msg.content) return false;
-      try {
-        const content =
-          typeof msg.content === "string"
-            ? JSON.parse(msg.content)
-            : msg.content;
-        return pendingTypes.has(content?.type);
-      } catch {
-        return false;
-      }
-    });
-  }, [messages]);
-
-  // Track when server has acknowledged the pending operation
-  useEffect(() => {
-    if (hasPendingOperationsFromServer) {
-      hasSeenServerPendingRef.current = true;
-    }
-  }, [hasPendingOperationsFromServer]);
-
-  // Combined: poll if server has pending ops OR if we received operation_started via SSE
-  const hasPendingOperations = hasPendingOperationsFromServer || forcePolling;
-
-  // Clear forcePolling only after server has acknowledged AND completed the operation
-  useEffect(() => {
-    if (
-      forcePolling &&
-      !hasPendingOperationsFromServer &&
-      hasSeenServerPendingRef.current
-    ) {
-      // Server acknowledged the operation and it's now complete
-      setForcePolling(false);
-      hasSeenServerPendingRef.current = false;
-    }
-  }, [forcePolling, hasPendingOperationsFromServer]);
-
-  // Function to trigger polling (called when operation_started is received via SSE)
-  function startPollingForOperation() {
-    setForcePolling(true);
-    hasSeenServerPendingRef.current = false; // Reset for new operation
-  }
-
-  // Refresh sessions list when a pending operation completes
-  // (hasPendingOperations transitions from true to false)
-  const prevHasPendingOperationsRef = useRef(hasPendingOperations);
-  useEffect(
-    function refreshSessionsListOnOperationComplete() {
-      const wasHasPending = prevHasPendingOperationsRef.current;
-      prevHasPendingOperationsRef.current = hasPendingOperations;
-
-      // Only invalidate when transitioning from pending to not pending
-      if (wasHasPending && !hasPendingOperations && sessionId) {
-        queryClient.invalidateQueries({
-          queryKey: getGetV2ListSessionsQueryKey(),
-        });
-      }
-    },
-    [hasPendingOperations, sessionId, queryClient],
-  );
-
-  // Poll for updates when there are pending operations
-  // Backoff: 2s, 4s, 6s, 8s, 10s, ... up to 30s max
-  const pollAttemptRef = useRef(0);
-  const hasPendingOperationsRef = useRef(hasPendingOperations);
-  hasPendingOperationsRef.current = hasPendingOperations;
-
-  useEffect(
-    function pollForPendingOperations() {
-      if (!sessionId || !hasPendingOperations) {
-        pollAttemptRef.current = 0;
-        return;
-      }
-
-      let cancelled = false;
-      let timeoutId: ReturnType<typeof setTimeout> | null = null;
-
-      function schedule() {
-        // 2s, 4s, 6s, 8s, 10s, ... 30s (max)
-        const delay = Math.min((pollAttemptRef.current + 1) * 2000, 30000);
-        timeoutId = setTimeout(async () => {
-          if (cancelled) return;
-          pollAttemptRef.current += 1;
-          try {
-            await refetch();
-          } catch (err) {
-            console.error("[useChatSession] Poll failed:", err);
-          } finally {
-            if (!cancelled && hasPendingOperationsRef.current) {
-              schedule();
-            }
-          }
-        }, delay);
-      }
-
-      schedule();
-
-      return () => {
-        cancelled = true;
-        if (timeoutId) clearTimeout(timeoutId);
-      };
-    },
-    [sessionId, hasPendingOperations, refetch],
-  );
-
-  async function createSession() {
-    try {
-      setError(null);
-      const response = await postV2CreateSession({
-        body: JSON.stringify({}),
-      });
-      if (response.status !== 200) {
-        throw new Error("Failed to create session");
-      }
-      const newSessionId = response.data.id;
-      setSessionId(newSessionId);
-      justCreatedSessionIdRef.current = newSessionId;
-      setTimeout(() => {
-        if (justCreatedSessionIdRef.current === newSessionId) {
-          justCreatedSessionIdRef.current = null;
-        }
-      }, 10000);
-      return newSessionId;
-    } catch (err) {
-      const error =
-        err instanceof Error ? err : new Error("Failed to create session");
-      setError(error);
-      toast.error("Failed to create chat session", {
-        description: error.message,
-      });
-      throw error;
-    }
-  }
-
-  async function loadSession(id: string) {
-    try {
-      setError(null);
-      // Invalidate the query cache for this session to force a fresh fetch
-      await queryClient.invalidateQueries({
-        queryKey: getGetV2GetSessionQueryKey(id),
-      });
-      // Set sessionId after invalidation to ensure the hook refetches
-      setSessionId(id);
-      // Force fetch with fresh data (bypass cache)
-      const queryOptions = getGetV2GetSessionQueryOptions(id, {
-        query: {
-          staleTime: 0, // Force fresh fetch
-          retry: shouldRetrySessionLoad,
-          retryDelay: getSessionRetryDelay,
-        },
-      });
-      const result = await queryClient.fetchQuery(queryOptions);
-      if (!result || ("status" in result && result.status !== 200)) {
-        console.warn("Session not found on server");
-        setSessionId(null);
-        throw new Error("Session not found");
-      }
-    } catch (err) {
-      const error =
-        err instanceof Error ? err : new Error("Failed to load session");
-      setError(error);
-      throw error;
-    }
-  }
-
-  async function refreshSession() {
-    if (!sessionId) return;
-    try {
-      setError(null);
-      await refetch();
-    } catch (err) {
-      const error =
-        err instanceof Error ? err : new Error("Failed to refresh session");
-      setError(error);
-      throw error;
-    }
-  }
-
-  async function claimSession(id: string) {
-    try {
-      setError(null);
-      await claimSessionMutation({ sessionId: id });
-      if (justCreatedSessionIdRef.current === id) {
-        justCreatedSessionIdRef.current = null;
-      }
-      await queryClient.invalidateQueries({
-        queryKey: getGetV2GetSessionQueryKey(id),
-      });
-      await refetch();
-      toast.success("Session claimed successfully", {
-        description: "Your chat history has been saved to your account",
-      });
-    } catch (err: unknown) {
-      const error =
-        err instanceof Error ? err : new Error("Failed to claim session");
-      const is404 =
-        (typeof err === "object" &&
-          err !== null &&
-          "status" in err &&
-          err.status === 404) ||
-        (typeof err === "object" &&
-          err !== null &&
-          "response" in err &&
-          typeof err.response === "object" &&
-          err.response !== null &&
-          "status" in err.response &&
-          err.response.status === 404);
-      if (!is404) {
-        setError(error);
-        toast.error("Failed to claim session", {
-          description: error.message || "Unable to claim session",
-        });
-      }
-      throw error;
-    }
-  }
-
-  function clearSession() {
-    setSessionId(null);
-    setError(null);
-    justCreatedSessionIdRef.current = null;
-  }
-
-  return {
-    session,
-    sessionId,
-    messages,
-    isLoading,
-    isCreating,
-    error,
-    isSessionNotFound: isNotFoundError(loadError),
-    hasPendingOperations,
-    createSession,
-    loadSession,
-    refreshSession,
-    claimSession,
-    clearSession,
-    startPollingForOperation,
-  };
-}
-
-function isNotFoundError(error: unknown): boolean {
-  if (!error || typeof error !== "object") return false;
-  if ("status" in error && error.status === 404) return true;
-  if (
-    "response" in error &&
-    typeof error.response === "object" &&
-    error.response !== null &&
-    "status" in error.response &&
-    error.response.status === 404
-  ) {
-    return true;
-  }
-  return false;
-}
-
-function shouldRetrySessionLoad(failureCount: number, error: unknown): boolean {
-  if (!isNotFoundError(error)) return false;
-  return failureCount <= 2;
-}
-
-function getSessionRetryDelay(attemptIndex: number): number {
-  if (attemptIndex === 0) return 3000;
-  if (attemptIndex === 1) return 5000;
-  return 0;
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/useChatStream.ts b/autogpt_platform/frontend/src/components/contextual/Chat/useChatStream.ts
deleted file mode 100644
index 5a9f637457..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/useChatStream.ts
+++ /dev/null
@@ -1,115 +0,0 @@
-"use client";
-
-import { useEffect, useRef, useState } from "react";
-import { toast } from "sonner";
-import { useChatStore } from "./chat-store";
-import type { StreamChunk } from "./chat-types";
-
-export type { StreamChunk } from "./chat-types";
-
-export function useChatStream() {
-  const [isStreaming, setIsStreaming] = useState(false);
-  const [error, setError] = useState<Error | null>(null);
-  const currentSessionIdRef = useRef<string | null>(null);
-  const onChunkCallbackRef = useRef<((chunk: StreamChunk) => void) | null>(
-    null,
-  );
-
-  const stopStream = useChatStore((s) => s.stopStream);
-  const unregisterActiveSession = useChatStore(
-    (s) => s.unregisterActiveSession,
-  );
-  const isSessionActive = useChatStore((s) => s.isSessionActive);
-  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
-  const getCompletedStream = useChatStore((s) => s.getCompletedStream);
-  const registerActiveSession = useChatStore((s) => s.registerActiveSession);
-  const startStream = useChatStore((s) => s.startStream);
-  const getStreamStatus = useChatStore((s) => s.getStreamStatus);
-
-  function stopStreaming(sessionId?: string) {
-    const targetSession = sessionId || currentSessionIdRef.current;
-    if (targetSession) {
-      stopStream(targetSession);
-      unregisterActiveSession(targetSession);
-    }
-    setIsStreaming(false);
-  }
-
-  useEffect(() => {
-    return function cleanup() {
-      const sessionId = currentSessionIdRef.current;
-      if (sessionId && !isSessionActive(sessionId)) {
-        stopStream(sessionId);
-      }
-      currentSessionIdRef.current = null;
-      onChunkCallbackRef.current = null;
-    };
-  }, []);
-
-  useEffect(() => {
-    const unsubscribe = onStreamComplete(
-      function handleStreamComplete(completedSessionId) {
-        if (completedSessionId !== currentSessionIdRef.current) return;
-
-        setIsStreaming(false);
-        const completed = getCompletedStream(completedSessionId);
-        if (completed?.error) {
-          setError(completed.error);
-        }
-        unregisterActiveSession(completedSessionId);
-      },
-    );
-
-    return unsubscribe;
-  }, []);
-
-  async function sendMessage(
-    sessionId: string,
-    message: string,
-    onChunk: (chunk: StreamChunk) => void,
-    isUserMessage: boolean = true,
-    context?: { url: string; content: string },
-  ) {
-    const previousSessionId = currentSessionIdRef.current;
-    if (previousSessionId && previousSessionId !== sessionId) {
-      stopStreaming(previousSessionId);
-    }
-
-    currentSessionIdRef.current = sessionId;
-    onChunkCallbackRef.current = onChunk;
-    setIsStreaming(true);
-    setError(null);
-
-    registerActiveSession(sessionId);
-
-    try {
-      await startStream(sessionId, message, isUserMessage, context, onChunk);
-
-      const status = getStreamStatus(sessionId);
-      if (status === "error") {
-        const completed = getCompletedStream(sessionId);
-        if (completed?.error) {
-          setError(completed.error);
-          toast.error("Connection Failed", {
-            description: "Unable to connect to chat service. Please try again.",
-          });
-          throw completed.error;
-        }
-      }
-    } catch (err) {
-      const streamError =
-        err instanceof Error ? err : new Error("Failed to start stream");
-      setError(streamError);
-      throw streamError;
-    } finally {
-      setIsStreaming(false);
-    }
-  }
-
-  return {
-    isStreaming,
-    error,
-    sendMessage,
-    stopStreaming,
-  };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/usePageContext.ts b/autogpt_platform/frontend/src/components/contextual/Chat/usePageContext.ts
deleted file mode 100644
index c567422a5c..0000000000
--- a/autogpt_platform/frontend/src/components/contextual/Chat/usePageContext.ts
+++ /dev/null
@@ -1,98 +0,0 @@
-import { useCallback } from "react";
-
-export interface PageContext {
-  url: string;
-  content: string;
-}
-
-const MAX_CONTENT_CHARS = 10000;
-
-/**
- * Hook to capture the current page context (URL + full page content)
- * Privacy-hardened: removes sensitive inputs and enforces content size limits
- */
-export function usePageContext() {
-  const capturePageContext = useCallback((): PageContext => {
-    if (typeof window === "undefined" || typeof document === "undefined") {
-      return { url: "", content: "" };
-    }
-
-    const url = window.location.href;
-
-    // Clone document to avoid modifying the original
-    const clone = document.cloneNode(true) as Document;
-
-    // Remove script, style, and noscript elements
-    const scripts = clone.querySelectorAll("script, style, noscript");
-    scripts.forEach((el) => el.remove());
-
-    // Remove sensitive elements and their content
-    const sensitiveSelectors = [
-      "input",
-      "textarea",
-      "[contenteditable]",
-      'input[type="password"]',
-      'input[type="email"]',
-      'input[type="tel"]',
-      'input[type="search"]',
-      'input[type="hidden"]',
-      "form",
-      "[data-sensitive]",
-      "[data-sensitive='true']",
-    ];
-
-    sensitiveSelectors.forEach((selector) => {
-      const elements = clone.querySelectorAll(selector);
-      elements.forEach((el) => {
-        // For form elements, remove the entire element
-        if (el.tagName === "FORM") {
-          el.remove();
-        } else {
-          // For inputs and textareas, clear their values but keep the element structure
-          if (
-            el instanceof HTMLInputElement ||
-            el instanceof HTMLTextAreaElement
-          ) {
-            el.value = "";
-            el.textContent = "";
-          } else {
-            // For other sensitive elements, remove them entirely
-            el.remove();
-          }
-        }
-      });
-    });
-
-    // Strip any remaining input values that might have been missed
-    const allInputs = clone.querySelectorAll("input, textarea");
-    allInputs.forEach((el) => {
-      if (el instanceof HTMLInputElement || el instanceof HTMLTextAreaElement) {
-        el.value = "";
-        el.textContent = "";
-      }
-    });
-
-    // Get text content from body
-    const body = clone.body;
-    const content = body?.textContent || body?.innerText || "";
-
-    // Clean up whitespace
-    let cleanedContent = content
-      .replace(/\s+/g, " ")
-      .replace(/\n\s*\n/g, "\n")
-      .trim();
-
-    // Enforce maximum content size
-    if (cleanedContent.length > MAX_CONTENT_CHARS) {
-      cleanedContent =
-        cleanedContent.substring(0, MAX_CONTENT_CHARS) + "... [truncated]";
-    }
-
-    return {
-      url,
-      content: cleanedContent,
-    };
-  }, []);
-
-  return { capturePageContext };
-}
diff --git a/autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/HotScopedCredentialsModal/HotScopedCredentialsModal.tsx b/autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/HotScopedCredentialsModal/HotScopedCredentialsModal.tsx
index 547952841b..63d2ae1ac5 100644
--- a/autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/HotScopedCredentialsModal/HotScopedCredentialsModal.tsx
+++ b/autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/HotScopedCredentialsModal/HotScopedCredentialsModal.tsx
@@ -41,7 +41,17 @@ export function HostScopedCredentialsModal({
   const currentHost = currentUrl ? getHostFromUrl(currentUrl) : "";
 
   const formSchema = z.object({
-    host: z.string().min(1, "Host is required"),
+    host: z
+      .string()
+      .min(1, "Host is required")
+      .refine((val) => !/^[a-zA-Z][a-zA-Z\d+\-.]*:\/\//.test(val), {
+        message: "Enter only the host (e.g. api.example.com), not a full URL",
+      })
+      .refine((val) => !val.includes("/"), {
+        message:
+          "Enter only the host (e.g. api.example.com), without a trailing path. " +
+          "You may specify a port (e.g. api.example.com:8080) if needed.",
+      }),
     title: z.string().optional(),
     headers: z.record(z.string()).optional(),
   });
diff --git a/autogpt_platform/frontend/src/components/contextual/CredentialsInput/helpers.ts b/autogpt_platform/frontend/src/components/contextual/CredentialsInput/helpers.ts
index ef965d5382..57653f3804 100644
--- a/autogpt_platform/frontend/src/components/contextual/CredentialsInput/helpers.ts
+++ b/autogpt_platform/frontend/src/components/contextual/CredentialsInput/helpers.ts
@@ -26,6 +26,7 @@ export const providerIcons: Partial<
   nvidia: fallbackIcon,
   discord: FaDiscord,
   d_id: fallbackIcon,
+  elevenlabs: fallbackIcon,
   google_maps: FaGoogle,
   jina: fallbackIcon,
   ideogram: fallbackIcon,
diff --git a/autogpt_platform/frontend/src/components/layout/Navbar/Navbar.tsx b/autogpt_platform/frontend/src/components/layout/Navbar/Navbar.tsx
index f4bdecd1df..ce5992b4be 100644
--- a/autogpt_platform/frontend/src/components/layout/Navbar/Navbar.tsx
+++ b/autogpt_platform/frontend/src/components/layout/Navbar/Navbar.tsx
@@ -47,7 +47,7 @@ export function Navbar() {
 
   const actualLoggedInLinks = [
     { name: "Home", href: homeHref },
-    ...(isChatEnabled === true ? [{ name: "Tasks", href: "/library" }] : []),
+    ...(isChatEnabled === true ? [{ name: "Agents", href: "/library" }] : []),
     ...loggedInLinks,
   ];
 
@@ -62,7 +62,7 @@ export function Navbar() {
           <PreviewBanner branchName={previewBranchName} />
         ) : null}
         <nav
-          className="border-zinc-[#EFEFF0] inline-flex w-full items-center border border-[#EFEFF0] bg-[#F3F4F6]/20 p-3 backdrop-blur-[26px]"
+          className="inline-flex w-full items-center border border-none bg-[#FAFAFA] p-3 backdrop-blur-[26px]"
           style={{ height: NAVBAR_HEIGHT_PX }}
         >
           {/* Left section */}
diff --git a/autogpt_platform/frontend/src/components/layout/Navbar/components/AgentActivityDropdown/components/ActivityDropdown/ActivityDropdown.tsx b/autogpt_platform/frontend/src/components/layout/Navbar/components/AgentActivityDropdown/components/ActivityDropdown/ActivityDropdown.tsx
index 263453b327..885877786f 100644
--- a/autogpt_platform/frontend/src/components/layout/Navbar/components/AgentActivityDropdown/components/ActivityDropdown/ActivityDropdown.tsx
+++ b/autogpt_platform/frontend/src/components/layout/Navbar/components/AgentActivityDropdown/components/ActivityDropdown/ActivityDropdown.tsx
@@ -4,7 +4,7 @@ import { Button } from "@/components/atoms/Button/Button";
 import { Input } from "@/components/atoms/Input/Input";
 import { Text } from "@/components/atoms/Text/Text";
 import { Bell, MagnifyingGlass, X } from "@phosphor-icons/react";
-import { FixedSizeList as List } from "react-window";
+import { List, type RowComponentProps } from "react-window";
 import { AgentExecutionWithInfo } from "../../helpers";
 import { ActivityItem } from "../ActivityItem";
 import styles from "./styles.module.css";
@@ -19,14 +19,16 @@ interface Props {
   recentFailures: AgentExecutionWithInfo[];
 }
 
-interface VirtualizedItemProps {
-  index: number;
-  style: React.CSSProperties;
-  data: AgentExecutionWithInfo[];
+interface ActivityRowProps {
+  executions: AgentExecutionWithInfo[];
 }
 
-function VirtualizedActivityItem({ index, style, data }: VirtualizedItemProps) {
-  const execution = data[index];
+function VirtualizedActivityItem({
+  index,
+  style,
+  executions,
+}: RowComponentProps<ActivityRowProps>) {
+  const execution = executions[index];
   return (
     <div style={style}>
       <ActivityItem execution={execution} />
@@ -129,14 +131,13 @@ export function ActivityDropdown({
       >
         {filteredExecutions.length > 0 ? (
           <List
-            height={listHeight}
-            width={320} // Match dropdown width (w-80 = 20rem = 320px)
-            itemCount={filteredExecutions.length}
-            itemSize={itemHeight}
-            itemData={filteredExecutions}
-          >
-            {VirtualizedActivityItem}
-          </List>
+            defaultHeight={listHeight}
+            rowCount={filteredExecutions.length}
+            rowHeight={itemHeight}
+            rowProps={{ executions: filteredExecutions }}
+            rowComponent={VirtualizedActivityItem}
+            style={{ width: 320, height: listHeight }}
+          />
         ) : (
           <div className="flex h-full flex-col items-center justify-center gap-5 pb-8 pt-6">
             <div className="mx-auto inline-flex flex-col items-center justify-center rounded-full bg-bgLightGrey p-6">
diff --git a/autogpt_platform/frontend/src/components/layout/Navbar/components/NavbarLink.tsx b/autogpt_platform/frontend/src/components/layout/Navbar/components/NavbarLink.tsx
index eab5a7352f..dff1277384 100644
--- a/autogpt_platform/frontend/src/components/layout/Navbar/components/NavbarLink.tsx
+++ b/autogpt_platform/frontend/src/components/layout/Navbar/components/NavbarLink.tsx
@@ -1,7 +1,6 @@
 "use client";
 
 import { IconLaptop } from "@/components/__legacy__/ui/icons";
-import { getHomepageRoute } from "@/lib/constants";
 import { cn } from "@/lib/utils";
 import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import { ListChecksIcon } from "@phosphor-icons/react/dist/ssr";
@@ -24,11 +23,11 @@ interface Props {
 export function NavbarLink({ name, href }: Props) {
   const pathname = usePathname();
   const isChatEnabled = useGetFlag(Flag.CHAT);
-  const homepageRoute = getHomepageRoute(isChatEnabled);
+  const expectedHomeRoute = isChatEnabled ? "/copilot" : "/library";
 
   const isActive =
-    href === homepageRoute
-      ? pathname === "/" || pathname.startsWith(homepageRoute)
+    href === expectedHomeRoute
+      ? pathname === "/" || pathname.startsWith(expectedHomeRoute)
       : pathname.includes(href);
 
   return (
diff --git a/autogpt_platform/frontend/src/components/layout/Navbar/components/Wallet/Wallet.tsx b/autogpt_platform/frontend/src/components/layout/Navbar/components/Wallet/Wallet.tsx
index 4a25c84f92..5a5bb514f3 100644
--- a/autogpt_platform/frontend/src/components/layout/Navbar/components/Wallet/Wallet.tsx
+++ b/autogpt_platform/frontend/src/components/layout/Navbar/components/Wallet/Wallet.tsx
@@ -15,7 +15,6 @@ import {
 import { cn } from "@/lib/utils";
 import { useOnboarding } from "@/providers/onboarding/onboarding-provider";
 import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-import { storage, Key as StorageKey } from "@/services/storage/local-storage";
 import { WalletIcon } from "@phosphor-icons/react";
 import { PopoverClose } from "@radix-ui/react-popover";
 import { X } from "lucide-react";
@@ -175,7 +174,6 @@ export function Wallet() {
   const [prevCredits, setPrevCredits] = useState<number | null>(credits);
   const [flash, setFlash] = useState(false);
   const [walletOpen, setWalletOpen] = useState(false);
-  const [lastSeenCredits, setLastSeenCredits] = useState<number | null>(null);
 
   const totalCount = useMemo(() => {
     return groups.reduce((acc, group) => acc + group.tasks.length, 0);
@@ -200,38 +198,6 @@ export function Wallet() {
     setCompletedCount(completed);
   }, [groups, state?.completedSteps]);
 
-  // Load last seen credits from localStorage once on mount
-  useEffect(() => {
-    const stored = storage.get(StorageKey.WALLET_LAST_SEEN_CREDITS);
-    if (stored !== undefined && stored !== null) {
-      const parsed = parseFloat(stored);
-      if (!Number.isNaN(parsed)) setLastSeenCredits(parsed);
-      else setLastSeenCredits(0);
-    } else {
-      setLastSeenCredits(0);
-    }
-  }, []);
-
-  // Auto-open once if never shown, otherwise open only when credits increase beyond last seen
-  useEffect(() => {
-    if (typeof credits !== "number") return;
-    // Open once for first-time users
-    if (state && state.walletShown === false) {
-      requestAnimationFrame(() => setWalletOpen(true));
-      // Mark as shown so it won't reopen on every reload
-      updateState({ walletShown: true });
-      return;
-    }
-    // Open if user gained more credits than last acknowledged
-    if (
-      lastSeenCredits !== null &&
-      credits > lastSeenCredits &&
-      walletOpen === false
-    ) {
-      requestAnimationFrame(() => setWalletOpen(true));
-    }
-  }, [credits, lastSeenCredits, state?.walletShown, updateState, walletOpen]);
-
   const onWalletOpen = useCallback(async () => {
     if (!state?.walletShown) {
       updateState({ walletShown: true });
@@ -324,19 +290,7 @@ export function Wallet() {
   if (credits === null || !state) return null;
 
   return (
-    <Popover
-      open={walletOpen}
-      onOpenChange={(open) => {
-        setWalletOpen(open);
-        if (!open) {
-          // Persist the latest acknowledged credits so we only auto-open on future gains
-          if (typeof credits === "number") {
-            storage.set(StorageKey.WALLET_LAST_SEEN_CREDITS, String(credits));
-            setLastSeenCredits(credits);
-          }
-        }
-      }}
-    >
+    <Popover open={walletOpen} onOpenChange={(open) => setWalletOpen(open)}>
       <PopoverTrigger asChild>
         <div className="relative inline-block">
           <button
diff --git a/autogpt_platform/frontend/src/components/renderers/InputRenderer/FormRenderer.tsx b/autogpt_platform/frontend/src/components/renderers/InputRenderer/FormRenderer.tsx
index fc388cc343..c3a20d8cd2 100644
--- a/autogpt_platform/frontend/src/components/renderers/InputRenderer/FormRenderer.tsx
+++ b/autogpt_platform/frontend/src/components/renderers/InputRenderer/FormRenderer.tsx
@@ -30,8 +30,6 @@ export const FormRenderer = ({
     return generateUiSchemaForCustomFields(preprocessedSchema, uiSchema);
   }, [preprocessedSchema, uiSchema]);
 
-  console.log("preprocessedSchema", preprocessedSchema);
-
   return (
     <div className={"mb-6 mt-4"} data-tutorial-id="input-handles">
       <Form
diff --git a/autogpt_platform/frontend/src/components/renderers/InputRenderer/base/anyof/AnyOfField.tsx b/autogpt_platform/frontend/src/components/renderers/InputRenderer/base/anyof/AnyOfField.tsx
index 6514ce9af0..0340ff03da 100644
--- a/autogpt_platform/frontend/src/components/renderers/InputRenderer/base/anyof/AnyOfField.tsx
+++ b/autogpt_platform/frontend/src/components/renderers/InputRenderer/base/anyof/AnyOfField.tsx
@@ -1,6 +1,6 @@
 import { FieldProps, getUiOptions, getWidget } from "@rjsf/utils";
 import { AnyOfFieldTitle } from "./components/AnyOfFieldTitle";
-import { isEmpty } from "lodash";
+import isEmpty from "lodash/isEmpty";
 import { useAnyOfField } from "./useAnyOfField";
 import { cleanUpHandleId, getHandleId, updateUiOption } from "../../helpers";
 import { useEdgeStore } from "@/app/(platform)/build/stores/edgeStore";
diff --git a/autogpt_platform/frontend/src/components/ui/button-group.tsx b/autogpt_platform/frontend/src/components/ui/button-group.tsx
new file mode 100644
index 0000000000..6eeace3265
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/button-group.tsx
@@ -0,0 +1,83 @@
+import { Slot } from "@radix-ui/react-slot";
+import { cva, type VariantProps } from "class-variance-authority";
+
+import { cn } from "@/lib/utils";
+import { Separator } from "@/components/ui/separator";
+
+const buttonGroupVariants = cva(
+  "flex w-fit items-stretch has-[>[data-slot=button-group]]:gap-2 [&>*]:focus-visible:relative [&>*]:focus-visible:z-10 has-[select[aria-hidden=true]:last-child]:[&>[data-slot=select-trigger]:last-of-type]:rounded-r-md [&>[data-slot=select-trigger]:not([class*='w-'])]:w-fit [&>input]:flex-1",
+  {
+    variants: {
+      orientation: {
+        horizontal:
+          "[&>*:not(:first-child)]:rounded-l-none [&>*:not(:first-child)]:border-l-0 [&>*:not(:last-child)]:rounded-r-none",
+        vertical:
+          "flex-col [&>*:not(:first-child)]:rounded-t-none [&>*:not(:first-child)]:border-t-0 [&>*:not(:last-child)]:rounded-b-none",
+      },
+    },
+    defaultVariants: {
+      orientation: "horizontal",
+    },
+  },
+);
+
+function ButtonGroup({
+  className,
+  orientation,
+  ...props
+}: React.ComponentProps<"div"> & VariantProps<typeof buttonGroupVariants>) {
+  return (
+    <div
+      role="group"
+      data-slot="button-group"
+      data-orientation={orientation}
+      className={cn(buttonGroupVariants({ orientation }), className)}
+      {...props}
+    />
+  );
+}
+
+function ButtonGroupText({
+  className,
+  asChild = false,
+  ...props
+}: React.ComponentProps<"div"> & {
+  asChild?: boolean;
+}) {
+  const Comp = asChild ? Slot : "div";
+
+  return (
+    <Comp
+      className={cn(
+        "shadow-xs flex items-center gap-2 rounded-md border border-neutral-200 bg-neutral-100 px-4 text-sm font-medium dark:border-neutral-800 dark:bg-neutral-800 [&_svg:not([class*='size-'])]:size-4 [&_svg]:pointer-events-none",
+        className,
+      )}
+      {...props}
+    />
+  );
+}
+
+function ButtonGroupSeparator({
+  className,
+  orientation = "vertical",
+  ...props
+}: React.ComponentProps<typeof Separator>) {
+  return (
+    <Separator
+      data-slot="button-group-separator"
+      orientation={orientation}
+      className={cn(
+        "relative !m-0 self-stretch bg-neutral-200 data-[orientation=vertical]:h-auto dark:bg-neutral-800",
+        className,
+      )}
+      {...props}
+    />
+  );
+}
+
+export {
+  ButtonGroup,
+  ButtonGroupSeparator,
+  ButtonGroupText,
+  buttonGroupVariants,
+};
diff --git a/autogpt_platform/frontend/src/components/ui/button.tsx b/autogpt_platform/frontend/src/components/ui/button.tsx
new file mode 100644
index 0000000000..1cd93355cf
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/button.tsx
@@ -0,0 +1,59 @@
+import * as React from "react";
+import { Slot } from "@radix-ui/react-slot";
+import { cva, type VariantProps } from "class-variance-authority";
+
+import { cn } from "@/lib/utils";
+
+const buttonVariants = cva(
+  "inline-flex items-center justify-center gap-2 whitespace-nowrap rounded-md text-sm font-medium transition-colors focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-neutral-950 disabled:pointer-events-none disabled:opacity-50 [&_svg]:pointer-events-none [&_svg]:size-4 [&_svg]:shrink-0 dark:focus-visible:ring-neutral-300",
+  {
+    variants: {
+      variant: {
+        default:
+          "bg-neutral-900 text-neutral-50 shadow hover:bg-neutral-900/90 dark:bg-neutral-50 dark:text-neutral-900 dark:hover:bg-neutral-50/90",
+        destructive:
+          "bg-red-500 text-neutral-50 shadow-sm hover:bg-red-500/90 dark:bg-red-900 dark:text-neutral-50 dark:hover:bg-red-900/90",
+        outline:
+          "border border-neutral-200 bg-white shadow-sm hover:bg-neutral-100 hover:text-neutral-900 dark:border-neutral-800 dark:bg-neutral-950 dark:hover:bg-neutral-800 dark:hover:text-neutral-50",
+        secondary:
+          "bg-neutral-100 text-neutral-900 shadow-sm hover:bg-neutral-100/80 dark:bg-neutral-800 dark:text-neutral-50 dark:hover:bg-neutral-800/80",
+        ghost:
+          "hover:bg-neutral-100 hover:text-neutral-900 dark:hover:bg-neutral-800 dark:hover:text-neutral-50",
+        link: "text-neutral-900 underline-offset-4 hover:underline dark:text-neutral-50",
+      },
+      size: {
+        default: "h-9 px-4 py-2",
+        sm: "h-8 rounded-md px-3 text-xs",
+        lg: "h-10 rounded-md px-8",
+        icon: "h-9 w-9",
+        "icon-sm": "h-8 w-8",
+      },
+    },
+    defaultVariants: {
+      variant: "default",
+      size: "default",
+    },
+  },
+);
+
+export interface ButtonProps
+  extends React.ButtonHTMLAttributes<HTMLButtonElement>,
+    VariantProps<typeof buttonVariants> {
+  asChild?: boolean;
+}
+
+const Button = React.forwardRef<HTMLButtonElement, ButtonProps>(
+  ({ className, variant, size, asChild = false, ...props }, ref) => {
+    const Comp = asChild ? Slot : "button";
+    return (
+      <Comp
+        className={cn(buttonVariants({ variant, size, className }))}
+        ref={ref}
+        {...props}
+      />
+    );
+  },
+);
+Button.displayName = "Button";
+
+export { Button, buttonVariants };
diff --git a/autogpt_platform/frontend/src/components/ui/input.tsx b/autogpt_platform/frontend/src/components/ui/input.tsx
new file mode 100644
index 0000000000..34b89469ce
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/input.tsx
@@ -0,0 +1,22 @@
+import * as React from "react";
+
+import { cn } from "@/lib/utils";
+
+const Input = React.forwardRef<HTMLInputElement, React.ComponentProps<"input">>(
+  ({ className, type, ...props }, ref) => {
+    return (
+      <input
+        type={type}
+        className={cn(
+          "flex h-9 w-full rounded-md border border-neutral-200 bg-transparent px-3 py-1 text-base shadow-sm transition-colors file:border-0 file:bg-transparent file:text-sm file:font-medium file:text-neutral-950 placeholder:text-neutral-500 focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-neutral-950 disabled:cursor-not-allowed disabled:opacity-50 dark:border-neutral-800 dark:file:text-neutral-50 dark:placeholder:text-neutral-400 dark:focus-visible:ring-neutral-300 md:text-sm",
+          className,
+        )}
+        ref={ref}
+        {...props}
+      />
+    );
+  },
+);
+Input.displayName = "Input";
+
+export { Input };
diff --git a/autogpt_platform/frontend/src/components/ui/separator.tsx b/autogpt_platform/frontend/src/components/ui/separator.tsx
new file mode 100644
index 0000000000..4b261e23c1
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/separator.tsx
@@ -0,0 +1,31 @@
+"use client";
+
+import * as React from "react";
+import * as SeparatorPrimitive from "@radix-ui/react-separator";
+
+import { cn } from "@/lib/utils";
+
+const Separator = React.forwardRef<
+  React.ElementRef<typeof SeparatorPrimitive.Root>,
+  React.ComponentPropsWithoutRef<typeof SeparatorPrimitive.Root>
+>(
+  (
+    { className, orientation = "horizontal", decorative = true, ...props },
+    ref,
+  ) => (
+    <SeparatorPrimitive.Root
+      ref={ref}
+      decorative={decorative}
+      orientation={orientation}
+      className={cn(
+        "shrink-0 bg-neutral-200 dark:bg-neutral-800",
+        orientation === "horizontal" ? "h-[1px] w-full" : "h-full w-[1px]",
+        className,
+      )}
+      {...props}
+    />
+  ),
+);
+Separator.displayName = SeparatorPrimitive.Root.displayName;
+
+export { Separator };
diff --git a/autogpt_platform/frontend/src/components/ui/sheet.tsx b/autogpt_platform/frontend/src/components/ui/sheet.tsx
new file mode 100644
index 0000000000..30ae1d3e44
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/sheet.tsx
@@ -0,0 +1,143 @@
+"use client";
+
+import * as React from "react";
+import * as SheetPrimitive from "@radix-ui/react-dialog";
+import { cva, type VariantProps } from "class-variance-authority";
+import { X } from "lucide-react";
+
+import { cn } from "@/lib/utils";
+
+const Sheet = SheetPrimitive.Root;
+
+const SheetTrigger = SheetPrimitive.Trigger;
+
+const SheetClose = SheetPrimitive.Close;
+
+const SheetPortal = SheetPrimitive.Portal;
+
+const SheetOverlay = React.forwardRef<
+  React.ElementRef<typeof SheetPrimitive.Overlay>,
+  React.ComponentPropsWithoutRef<typeof SheetPrimitive.Overlay>
+>(({ className, ...props }, ref) => (
+  <SheetPrimitive.Overlay
+    className={cn(
+      "fixed inset-0 z-50 bg-black/80 data-[state=open]:animate-in data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=open]:fade-in-0",
+      className,
+    )}
+    {...props}
+    ref={ref}
+  />
+));
+SheetOverlay.displayName = SheetPrimitive.Overlay.displayName;
+
+const sheetVariants = cva(
+  "fixed z-50 gap-4 bg-white p-6 shadow-lg transition ease-in-out data-[state=closed]:duration-300 data-[state=open]:duration-500 data-[state=open]:animate-in data-[state=closed]:animate-out dark:bg-neutral-950",
+  {
+    variants: {
+      side: {
+        top: "inset-x-0 top-0 border-b data-[state=closed]:slide-out-to-top data-[state=open]:slide-in-from-top",
+        bottom:
+          "inset-x-0 bottom-0 border-t data-[state=closed]:slide-out-to-bottom data-[state=open]:slide-in-from-bottom",
+        left: "inset-y-0 left-0 h-full w-3/4 border-r data-[state=closed]:slide-out-to-left data-[state=open]:slide-in-from-left sm:max-w-sm",
+        right:
+          "inset-y-0 right-0 h-full w-3/4 border-l data-[state=closed]:slide-out-to-right data-[state=open]:slide-in-from-right sm:max-w-sm",
+      },
+    },
+    defaultVariants: {
+      side: "right",
+    },
+  },
+);
+
+interface SheetContentProps
+  extends React.ComponentPropsWithoutRef<typeof SheetPrimitive.Content>,
+    VariantProps<typeof sheetVariants> {}
+
+const SheetContent = React.forwardRef<
+  React.ElementRef<typeof SheetPrimitive.Content>,
+  SheetContentProps
+>(({ side = "right", className, children, ...props }, ref) => (
+  <SheetPortal>
+    <SheetOverlay />
+    <SheetPrimitive.Content
+      ref={ref}
+      className={cn(sheetVariants({ side }), className)}
+      {...props}
+    >
+      <SheetPrimitive.Close className="absolute right-4 top-4 rounded-sm opacity-70 ring-offset-white transition-opacity data-[state=open]:bg-neutral-100 hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-neutral-950 focus:ring-offset-2 disabled:pointer-events-none dark:ring-offset-neutral-950 dark:data-[state=open]:bg-neutral-800 dark:focus:ring-neutral-300">
+        <X className="h-4 w-4" />
+        <span className="sr-only">Close</span>
+      </SheetPrimitive.Close>
+      {children}
+    </SheetPrimitive.Content>
+  </SheetPortal>
+));
+SheetContent.displayName = SheetPrimitive.Content.displayName;
+
+const SheetHeader = ({
+  className,
+  ...props
+}: React.HTMLAttributes<HTMLDivElement>) => (
+  <div
+    className={cn(
+      "flex flex-col space-y-2 text-center sm:text-left",
+      className,
+    )}
+    {...props}
+  />
+);
+SheetHeader.displayName = "SheetHeader";
+
+const SheetFooter = ({
+  className,
+  ...props
+}: React.HTMLAttributes<HTMLDivElement>) => (
+  <div
+    className={cn(
+      "flex flex-col-reverse sm:flex-row sm:justify-end sm:space-x-2",
+      className,
+    )}
+    {...props}
+  />
+);
+SheetFooter.displayName = "SheetFooter";
+
+const SheetTitle = React.forwardRef<
+  React.ElementRef<typeof SheetPrimitive.Title>,
+  React.ComponentPropsWithoutRef<typeof SheetPrimitive.Title>
+>(({ className, ...props }, ref) => (
+  <SheetPrimitive.Title
+    ref={ref}
+    className={cn(
+      "text-lg font-semibold text-neutral-950 dark:text-neutral-50",
+      className,
+    )}
+    {...props}
+  />
+));
+SheetTitle.displayName = SheetPrimitive.Title.displayName;
+
+const SheetDescription = React.forwardRef<
+  React.ElementRef<typeof SheetPrimitive.Description>,
+  React.ComponentPropsWithoutRef<typeof SheetPrimitive.Description>
+>(({ className, ...props }, ref) => (
+  <SheetPrimitive.Description
+    ref={ref}
+    className={cn("text-sm text-neutral-500 dark:text-neutral-400", className)}
+    {...props}
+  />
+));
+SheetDescription.displayName = SheetPrimitive.Description.displayName;
+
+export {
+  Sheet,
+  SheetPortal,
+  SheetOverlay,
+  SheetTrigger,
+  SheetClose,
+  SheetContent,
+  SheetHeader,
+  SheetFooter,
+  SheetTitle,
+  SheetDescription,
+};
diff --git a/autogpt_platform/frontend/src/components/ui/sidebar.tsx b/autogpt_platform/frontend/src/components/ui/sidebar.tsx
new file mode 100644
index 0000000000..1b6f69e27b
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/sidebar.tsx
@@ -0,0 +1,778 @@
+"use client";
+
+import { Slot } from "@radix-ui/react-slot";
+import { cva, type VariantProps } from "class-variance-authority";
+import * as React from "react";
+
+import { Button } from "@/components/ui/button";
+import { Input } from "@/components/ui/input";
+import { Separator } from "@/components/ui/separator";
+import {
+  Sheet,
+  SheetContent,
+  SheetDescription,
+  SheetHeader,
+  SheetTitle,
+} from "@/components/ui/sheet";
+import { Skeleton } from "@/components/ui/skeleton";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipProvider,
+  TooltipTrigger,
+} from "@/components/ui/tooltip";
+import { useIsMobile } from "@/hooks/use-mobile";
+import { cn } from "@/lib/utils";
+import { SidebarSimpleIcon } from "@phosphor-icons/react";
+
+const SIDEBAR_COOKIE_NAME = "sidebar_state";
+const SIDEBAR_COOKIE_MAX_AGE = 60 * 60 * 24 * 7;
+const SIDEBAR_WIDTH = "20rem";
+const SIDEBAR_WIDTH_MOBILE = "20rem";
+const SIDEBAR_WIDTH_ICON = "3rem";
+const SIDEBAR_KEYBOARD_SHORTCUT = "b";
+
+type SidebarContextProps = {
+  state: "expanded" | "collapsed";
+  open: boolean;
+  setOpen: (open: boolean) => void;
+  openMobile: boolean;
+  setOpenMobile: (open: boolean) => void;
+  isMobile: boolean;
+  toggleSidebar: () => void;
+};
+
+const SidebarContext = React.createContext<SidebarContextProps | null>(null);
+
+function useSidebar() {
+  const context = React.useContext(SidebarContext);
+  if (!context) {
+    throw new Error("useSidebar must be used within a SidebarProvider.");
+  }
+
+  return context;
+}
+
+const SidebarProvider = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div"> & {
+    defaultOpen?: boolean;
+    open?: boolean;
+    onOpenChange?: (open: boolean) => void;
+  }
+>(
+  (
+    {
+      defaultOpen = true,
+      open: openProp,
+      onOpenChange: setOpenProp,
+      className,
+      style,
+      children,
+      ...props
+    },
+    ref,
+  ) => {
+    const isMobile = useIsMobile();
+    const [openMobile, setOpenMobile] = React.useState(false);
+
+    // This is the internal state of the sidebar.
+    // We use openProp and setOpenProp for control from outside the component.
+    const [_open, _setOpen] = React.useState(defaultOpen);
+    const open = openProp ?? _open;
+    const setOpen = React.useCallback(
+      (value: boolean | ((value: boolean) => boolean)) => {
+        const openState = typeof value === "function" ? value(open) : value;
+        if (setOpenProp) {
+          setOpenProp(openState);
+        } else {
+          _setOpen(openState);
+        }
+
+        // This sets the cookie to keep the sidebar state.
+        document.cookie = `${SIDEBAR_COOKIE_NAME}=${openState}; path=/; max-age=${SIDEBAR_COOKIE_MAX_AGE}`;
+      },
+      [setOpenProp, open],
+    );
+
+    // Helper to toggle the sidebar.
+    const toggleSidebar = React.useCallback(() => {
+      return isMobile
+        ? setOpenMobile((open) => !open)
+        : setOpen((open) => !open);
+    }, [isMobile, setOpen, setOpenMobile]);
+
+    // Adds a keyboard shortcut to toggle the sidebar.
+    React.useEffect(() => {
+      const handleKeyDown = (event: KeyboardEvent) => {
+        if (
+          event.key === SIDEBAR_KEYBOARD_SHORTCUT &&
+          (event.metaKey || event.ctrlKey)
+        ) {
+          event.preventDefault();
+          toggleSidebar();
+        }
+      };
+
+      window.addEventListener("keydown", handleKeyDown);
+      return () => window.removeEventListener("keydown", handleKeyDown);
+    }, [toggleSidebar]);
+
+    // We add a state so that we can do data-state="expanded" or "collapsed".
+    // This makes it easier to style the sidebar with Tailwind classes.
+    const state = open ? "expanded" : "collapsed";
+
+    const contextValue = React.useMemo<SidebarContextProps>(
+      () => ({
+        state,
+        open,
+        setOpen,
+        isMobile,
+        openMobile,
+        setOpenMobile,
+        toggleSidebar,
+      }),
+      [
+        state,
+        open,
+        setOpen,
+        isMobile,
+        openMobile,
+        setOpenMobile,
+        toggleSidebar,
+      ],
+    );
+
+    return (
+      <SidebarContext.Provider value={contextValue}>
+        <TooltipProvider delayDuration={0}>
+          <div
+            style={
+              {
+                "--sidebar-width": SIDEBAR_WIDTH,
+                "--sidebar-width-icon": SIDEBAR_WIDTH_ICON,
+                ...style,
+              } as React.CSSProperties
+            }
+            className={cn(
+              "group/sidebar-wrapper flex min-h-svh w-full has-[[data-variant=inset]]:bg-sidebar",
+              className,
+            )}
+            ref={ref}
+            {...props}
+          >
+            {children}
+          </div>
+        </TooltipProvider>
+      </SidebarContext.Provider>
+    );
+  },
+);
+SidebarProvider.displayName = "SidebarProvider";
+
+const Sidebar = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div"> & {
+    side?: "left" | "right";
+    variant?: "sidebar" | "floating" | "inset";
+    collapsible?: "offcanvas" | "icon" | "none";
+  }
+>(
+  (
+    {
+      side = "left",
+      variant = "sidebar",
+      collapsible = "offcanvas",
+      className,
+      children,
+      ...props
+    },
+    ref,
+  ) => {
+    const { isMobile, state, openMobile, setOpenMobile } = useSidebar();
+
+    if (collapsible === "none") {
+      return (
+        <div
+          className={cn(
+            "flex h-full w-[--sidebar-width] flex-col bg-sidebar text-sidebar-foreground",
+            className,
+          )}
+          ref={ref}
+          {...props}
+        >
+          {children}
+        </div>
+      );
+    }
+
+    if (isMobile) {
+      return (
+        <Sheet open={openMobile} onOpenChange={setOpenMobile} {...props}>
+          <SheetContent
+            data-sidebar="sidebar"
+            data-mobile="true"
+            className="w-[--sidebar-width] bg-sidebar p-0 text-sidebar-foreground [&>button]:hidden"
+            style={
+              {
+                "--sidebar-width": SIDEBAR_WIDTH_MOBILE,
+              } as React.CSSProperties
+            }
+            side={side}
+          >
+            <SheetHeader className="sr-only">
+              <SheetTitle>Sidebar</SheetTitle>
+              <SheetDescription>Displays the mobile sidebar.</SheetDescription>
+            </SheetHeader>
+            <div className="flex h-full w-full flex-col">{children}</div>
+          </SheetContent>
+        </Sheet>
+      );
+    }
+
+    return (
+      <div
+        ref={ref}
+        className="group peer hidden text-sidebar-foreground md:block"
+        data-state={state}
+        data-collapsible={state === "collapsed" ? collapsible : ""}
+        data-variant={variant}
+        data-side={side}
+      >
+        {/* This is what handles the sidebar gap on desktop */}
+        <div
+          className={cn(
+            "relative w-[--sidebar-width] bg-transparent transition-[width] duration-200 ease-linear",
+            "group-data-[collapsible=offcanvas]:w-0",
+            "group-data-[side=right]:rotate-180",
+            variant === "floating" || variant === "inset"
+              ? "group-data-[collapsible=icon]:w-[calc(var(--sidebar-width-icon)_+_theme(spacing.4))]"
+              : "group-data-[collapsible=icon]:w-[--sidebar-width-icon]",
+          )}
+        />
+        <div
+          className={cn(
+            "fixed inset-y-0 z-10 hidden h-svh w-[--sidebar-width] transition-[left,right,width] duration-200 ease-linear md:flex",
+            side === "left"
+              ? "left-0 group-data-[collapsible=offcanvas]:left-[calc(var(--sidebar-width)*-1)]"
+              : "right-0 group-data-[collapsible=offcanvas]:right-[calc(var(--sidebar-width)*-1)]",
+            // Adjust the padding for floating and inset variants.
+            variant === "floating" || variant === "inset"
+              ? "p-2 group-data-[collapsible=icon]:w-[calc(var(--sidebar-width-icon)_+_theme(spacing.4)_+2px)]"
+              : "group-data-[collapsible=icon]:w-[--sidebar-width-icon] group-data-[side=left]:border-r group-data-[side=right]:border-l",
+            className,
+          )}
+          {...props}
+        >
+          <div
+            data-sidebar="sidebar"
+            className="flex h-full w-full flex-col bg-sidebar group-data-[variant=floating]:rounded-lg group-data-[variant=floating]:border group-data-[variant=floating]:border-sidebar-border group-data-[variant=floating]:shadow"
+          >
+            {children}
+          </div>
+        </div>
+      </div>
+    );
+  },
+);
+Sidebar.displayName = "Sidebar";
+
+const SidebarTrigger = React.forwardRef<
+  React.ElementRef<typeof Button>,
+  React.ComponentProps<typeof Button>
+>(({ onClick }, ref) => {
+  const { toggleSidebar } = useSidebar();
+
+  return (
+    <Button
+      ref={ref}
+      data-sidebar="trigger"
+      variant="ghost"
+      onClick={(event) => {
+        onClick?.(event);
+        toggleSidebar();
+      }}
+    >
+      <SidebarSimpleIcon className="!size-5" />
+      <span className="sr-only">Toggle Sidebar</span>
+    </Button>
+  );
+});
+SidebarTrigger.displayName = "SidebarTrigger";
+
+const SidebarRail = React.forwardRef<
+  HTMLButtonElement,
+  React.ComponentProps<"button">
+>(({ className, ...props }, ref) => {
+  const { toggleSidebar } = useSidebar();
+
+  return (
+    <button
+      ref={ref}
+      data-sidebar="rail"
+      aria-label="Toggle Sidebar"
+      tabIndex={-1}
+      onClick={toggleSidebar}
+      title="Toggle Sidebar"
+      className={cn(
+        "absolute inset-y-0 z-20 hidden w-4 -translate-x-1/2 transition-all ease-linear after:absolute after:inset-y-0 after:left-1/2 after:w-[2px] group-data-[side=left]:-right-4 group-data-[side=right]:left-0 hover:after:bg-sidebar-border sm:flex",
+        "[[data-side=left]_&]:cursor-w-resize [[data-side=right]_&]:cursor-e-resize",
+        "[[data-side=left][data-state=collapsed]_&]:cursor-e-resize [[data-side=right][data-state=collapsed]_&]:cursor-w-resize",
+        "group-data-[collapsible=offcanvas]:translate-x-0 group-data-[collapsible=offcanvas]:after:left-full group-data-[collapsible=offcanvas]:hover:bg-sidebar",
+        "[[data-side=left][data-collapsible=offcanvas]_&]:-right-2",
+        "[[data-side=right][data-collapsible=offcanvas]_&]:-left-2",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarRail.displayName = "SidebarRail";
+
+const SidebarInset = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"main">
+>(({ className, ...props }, ref) => {
+  return (
+    <main
+      ref={ref}
+      className={cn(
+        "relative flex w-full flex-1 flex-col bg-white dark:bg-neutral-950",
+        "md:peer-data-[variant=inset]:m-2 md:peer-data-[state=collapsed]:peer-data-[variant=inset]:ml-2 md:peer-data-[variant=inset]:ml-0 md:peer-data-[variant=inset]:rounded-xl md:peer-data-[variant=inset]:shadow",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarInset.displayName = "SidebarInset";
+
+const SidebarInput = React.forwardRef<
+  React.ElementRef<typeof Input>,
+  React.ComponentProps<typeof Input>
+>(({ className, ...props }, ref) => {
+  return (
+    <Input
+      ref={ref}
+      data-sidebar="input"
+      className={cn(
+        "h-8 w-full bg-white shadow-none focus-visible:ring-2 focus-visible:ring-sidebar-ring dark:bg-neutral-950",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarInput.displayName = "SidebarInput";
+
+const SidebarHeader = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div">
+>(({ className, ...props }, ref) => {
+  return (
+    <div
+      ref={ref}
+      data-sidebar="header"
+      className={cn("flex flex-col gap-2 p-2", className)}
+      {...props}
+    />
+  );
+});
+SidebarHeader.displayName = "SidebarHeader";
+
+const SidebarFooter = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div">
+>(({ className, ...props }, ref) => {
+  return (
+    <div
+      ref={ref}
+      data-sidebar="footer"
+      className={cn("flex flex-col gap-2 p-2", className)}
+      {...props}
+    />
+  );
+});
+SidebarFooter.displayName = "SidebarFooter";
+
+const SidebarSeparator = React.forwardRef<
+  React.ElementRef<typeof Separator>,
+  React.ComponentProps<typeof Separator>
+>(({ className, ...props }, ref) => {
+  return (
+    <Separator
+      ref={ref}
+      data-sidebar="separator"
+      className={cn("mx-2 w-auto bg-sidebar-border", className)}
+      {...props}
+    />
+  );
+});
+SidebarSeparator.displayName = "SidebarSeparator";
+
+const SidebarContent = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div">
+>(({ className, ...props }, ref) => {
+  return (
+    <div
+      ref={ref}
+      data-sidebar="content"
+      className={cn(
+        "flex min-h-0 flex-1 flex-col gap-2 overflow-auto group-data-[collapsible=icon]:overflow-hidden",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarContent.displayName = "SidebarContent";
+
+const SidebarGroup = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div">
+>(({ className, ...props }, ref) => {
+  return (
+    <div
+      ref={ref}
+      data-sidebar="group"
+      className={cn("relative flex w-full min-w-0 flex-col p-2", className)}
+      {...props}
+    />
+  );
+});
+SidebarGroup.displayName = "SidebarGroup";
+
+const SidebarGroupLabel = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div"> & { asChild?: boolean }
+>(({ className, asChild = false, ...props }, ref) => {
+  const Comp = asChild ? Slot : "div";
+
+  return (
+    <Comp
+      ref={ref}
+      data-sidebar="group-label"
+      className={cn(
+        "flex h-8 shrink-0 items-center rounded-md px-2 text-xs font-medium text-sidebar-foreground/70 outline-none ring-sidebar-ring transition-[margin,opacity] duration-200 ease-linear focus-visible:ring-2 [&>svg]:size-4 [&>svg]:shrink-0",
+        "group-data-[collapsible=icon]:-mt-8 group-data-[collapsible=icon]:opacity-0",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarGroupLabel.displayName = "SidebarGroupLabel";
+
+const SidebarGroupAction = React.forwardRef<
+  HTMLButtonElement,
+  React.ComponentProps<"button"> & { asChild?: boolean }
+>(({ className, asChild = false, ...props }, ref) => {
+  const Comp = asChild ? Slot : "button";
+
+  return (
+    <Comp
+      ref={ref}
+      data-sidebar="group-action"
+      className={cn(
+        "absolute right-3 top-3.5 flex aspect-square w-5 items-center justify-center rounded-md p-0 text-sidebar-foreground outline-none ring-sidebar-ring transition-transform hover:bg-sidebar-accent hover:text-sidebar-accent-foreground focus-visible:ring-2 [&>svg]:size-4 [&>svg]:shrink-0",
+        // Increases the hit area of the button on mobile.
+        "after:absolute after:-inset-2 after:md:hidden",
+        "group-data-[collapsible=icon]:hidden",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarGroupAction.displayName = "SidebarGroupAction";
+
+const SidebarGroupContent = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div">
+>(({ className, ...props }, ref) => (
+  <div
+    ref={ref}
+    data-sidebar="group-content"
+    className={cn("w-full text-sm", className)}
+    {...props}
+  />
+));
+SidebarGroupContent.displayName = "SidebarGroupContent";
+
+const SidebarMenu = React.forwardRef<
+  HTMLUListElement,
+  React.ComponentProps<"ul">
+>(({ className, ...props }, ref) => (
+  <ul
+    ref={ref}
+    data-sidebar="menu"
+    className={cn("flex w-full min-w-0 flex-col gap-1", className)}
+    {...props}
+  />
+));
+SidebarMenu.displayName = "SidebarMenu";
+
+const SidebarMenuItem = React.forwardRef<
+  HTMLLIElement,
+  React.ComponentProps<"li">
+>(({ className, ...props }, ref) => (
+  <li
+    ref={ref}
+    data-sidebar="menu-item"
+    className={cn("group/menu-item relative", className)}
+    {...props}
+  />
+));
+SidebarMenuItem.displayName = "SidebarMenuItem";
+
+const sidebarMenuButtonVariants = cva(
+  "peer/menu-button flex w-full items-center gap-2 overflow-hidden rounded-md p-2 text-left text-sm outline-none ring-sidebar-ring transition-[width,height,padding] hover:bg-sidebar-accent hover:text-sidebar-accent-foreground focus-visible:ring-2 active:bg-sidebar-accent active:text-sidebar-accent-foreground disabled:pointer-events-none disabled:opacity-50 group-has-[[data-sidebar=menu-action]]/menu-item:pr-8 aria-disabled:pointer-events-none aria-disabled:opacity-50 data-[active=true]:bg-sidebar-accent data-[active=true]:font-medium data-[active=true]:text-sidebar-accent-foreground data-[state=open]:hover:bg-sidebar-accent data-[state=open]:hover:text-sidebar-accent-foreground group-data-[collapsible=icon]:!size-8 group-data-[collapsible=icon]:!p-2 [&>span:last-child]:truncate [&>svg]:size-4 [&>svg]:shrink-0",
+  {
+    variants: {
+      variant: {
+        default: "hover:bg-sidebar-accent hover:text-sidebar-accent-foreground",
+        outline:
+          "bg-white shadow-[0_0_0_1px_hsl(var(--sidebar-border))] hover:bg-sidebar-accent hover:text-sidebar-accent-foreground hover:shadow-[0_0_0_1px_hsl(var(--sidebar-accent))] dark:bg-neutral-950",
+      },
+      size: {
+        default: "h-8 text-sm",
+        sm: "h-7 text-xs",
+        lg: "h-12 text-sm group-data-[collapsible=icon]:!p-0",
+      },
+    },
+    defaultVariants: {
+      variant: "default",
+      size: "default",
+    },
+  },
+);
+
+const SidebarMenuButton = React.forwardRef<
+  HTMLButtonElement,
+  React.ComponentProps<"button"> & {
+    asChild?: boolean;
+    isActive?: boolean;
+    tooltip?: string | React.ComponentProps<typeof TooltipContent>;
+  } & VariantProps<typeof sidebarMenuButtonVariants>
+>(
+  (
+    {
+      asChild = false,
+      isActive = false,
+      variant = "default",
+      size = "default",
+      tooltip,
+      className,
+      ...props
+    },
+    ref,
+  ) => {
+    const Comp = asChild ? Slot : "button";
+    const { isMobile, state } = useSidebar();
+
+    const button = (
+      <Comp
+        ref={ref}
+        data-sidebar="menu-button"
+        data-size={size}
+        data-active={isActive}
+        className={cn(sidebarMenuButtonVariants({ variant, size }), className)}
+        {...props}
+      />
+    );
+
+    if (!tooltip) {
+      return button;
+    }
+
+    if (typeof tooltip === "string") {
+      tooltip = {
+        children: tooltip,
+      };
+    }
+
+    return (
+      <Tooltip>
+        <TooltipTrigger asChild>{button}</TooltipTrigger>
+        <TooltipContent
+          side="right"
+          align="center"
+          hidden={state !== "collapsed" || isMobile}
+          {...tooltip}
+        />
+      </Tooltip>
+    );
+  },
+);
+SidebarMenuButton.displayName = "SidebarMenuButton";
+
+const SidebarMenuAction = React.forwardRef<
+  HTMLButtonElement,
+  React.ComponentProps<"button"> & {
+    asChild?: boolean;
+    showOnHover?: boolean;
+  }
+>(({ className, asChild = false, showOnHover = false, ...props }, ref) => {
+  const Comp = asChild ? Slot : "button";
+
+  return (
+    <Comp
+      ref={ref}
+      data-sidebar="menu-action"
+      className={cn(
+        "absolute right-1 top-1.5 flex aspect-square w-5 items-center justify-center rounded-md p-0 text-sidebar-foreground outline-none ring-sidebar-ring transition-transform peer-hover/menu-button:text-sidebar-accent-foreground hover:bg-sidebar-accent hover:text-sidebar-accent-foreground focus-visible:ring-2 [&>svg]:size-4 [&>svg]:shrink-0",
+        // Increases the hit area of the button on mobile.
+        "after:absolute after:-inset-2 after:md:hidden",
+        "peer-data-[size=sm]/menu-button:top-1",
+        "peer-data-[size=default]/menu-button:top-1.5",
+        "peer-data-[size=lg]/menu-button:top-2.5",
+        "group-data-[collapsible=icon]:hidden",
+        showOnHover &&
+          "group-focus-within/menu-item:opacity-100 group-hover/menu-item:opacity-100 data-[state=open]:opacity-100 peer-data-[active=true]/menu-button:text-sidebar-accent-foreground md:opacity-0",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarMenuAction.displayName = "SidebarMenuAction";
+
+const SidebarMenuBadge = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div">
+>(({ className, ...props }, ref) => (
+  <div
+    ref={ref}
+    data-sidebar="menu-badge"
+    className={cn(
+      "pointer-events-none absolute right-1 flex h-5 min-w-5 select-none items-center justify-center rounded-md px-1 text-xs font-medium tabular-nums text-sidebar-foreground",
+      "peer-hover/menu-button:text-sidebar-accent-foreground peer-data-[active=true]/menu-button:text-sidebar-accent-foreground",
+      "peer-data-[size=sm]/menu-button:top-1",
+      "peer-data-[size=default]/menu-button:top-1.5",
+      "peer-data-[size=lg]/menu-button:top-2.5",
+      "group-data-[collapsible=icon]:hidden",
+      className,
+    )}
+    {...props}
+  />
+));
+SidebarMenuBadge.displayName = "SidebarMenuBadge";
+
+const SidebarMenuSkeleton = React.forwardRef<
+  HTMLDivElement,
+  React.ComponentProps<"div"> & {
+    showIcon?: boolean;
+  }
+>(({ className, showIcon = false, ...props }, ref) => {
+  // Random width between 50 to 90%.
+  const width = React.useMemo(() => {
+    return `${Math.floor(Math.random() * 40) + 50}%`;
+  }, []);
+
+  return (
+    <div
+      ref={ref}
+      data-sidebar="menu-skeleton"
+      className={cn("flex h-8 items-center gap-2 rounded-md px-2", className)}
+      {...props}
+    >
+      {showIcon && (
+        <Skeleton
+          className="size-4 rounded-md"
+          data-sidebar="menu-skeleton-icon"
+        />
+      )}
+      <Skeleton
+        className="h-4 max-w-[--skeleton-width] flex-1"
+        data-sidebar="menu-skeleton-text"
+        style={
+          {
+            "--skeleton-width": width,
+          } as React.CSSProperties
+        }
+      />
+    </div>
+  );
+});
+SidebarMenuSkeleton.displayName = "SidebarMenuSkeleton";
+
+const SidebarMenuSub = React.forwardRef<
+  HTMLUListElement,
+  React.ComponentProps<"ul">
+>(({ className, ...props }, ref) => (
+  <ul
+    ref={ref}
+    data-sidebar="menu-sub"
+    className={cn(
+      "mx-3.5 flex min-w-0 translate-x-px flex-col gap-1 border-l border-sidebar-border px-2.5 py-0.5",
+      "group-data-[collapsible=icon]:hidden",
+      className,
+    )}
+    {...props}
+  />
+));
+SidebarMenuSub.displayName = "SidebarMenuSub";
+
+const SidebarMenuSubItem = React.forwardRef<
+  HTMLLIElement,
+  React.ComponentProps<"li">
+>(({ ...props }, ref) => <li ref={ref} {...props} />);
+SidebarMenuSubItem.displayName = "SidebarMenuSubItem";
+
+const SidebarMenuSubButton = React.forwardRef<
+  HTMLAnchorElement,
+  React.ComponentProps<"a"> & {
+    asChild?: boolean;
+    size?: "sm" | "md";
+    isActive?: boolean;
+  }
+>(({ asChild = false, size = "md", isActive, className, ...props }, ref) => {
+  const Comp = asChild ? Slot : "a";
+
+  return (
+    <Comp
+      ref={ref}
+      data-sidebar="menu-sub-button"
+      data-size={size}
+      data-active={isActive}
+      className={cn(
+        "flex h-7 min-w-0 -translate-x-px items-center gap-2 overflow-hidden rounded-md px-2 text-sidebar-foreground outline-none ring-sidebar-ring aria-disabled:pointer-events-none aria-disabled:opacity-50 hover:bg-sidebar-accent hover:text-sidebar-accent-foreground focus-visible:ring-2 active:bg-sidebar-accent active:text-sidebar-accent-foreground disabled:pointer-events-none disabled:opacity-50 [&>span:last-child]:truncate [&>svg]:size-4 [&>svg]:shrink-0 [&>svg]:text-sidebar-accent-foreground",
+        "data-[active=true]:bg-sidebar-accent data-[active=true]:text-sidebar-accent-foreground",
+        size === "sm" && "text-xs",
+        size === "md" && "text-sm",
+        "group-data-[collapsible=icon]:hidden",
+        className,
+      )}
+      {...props}
+    />
+  );
+});
+SidebarMenuSubButton.displayName = "SidebarMenuSubButton";
+
+export {
+  Sidebar,
+  SidebarContent,
+  SidebarFooter,
+  SidebarGroup,
+  SidebarGroupAction,
+  SidebarGroupContent,
+  SidebarGroupLabel,
+  SidebarHeader,
+  SidebarInput,
+  SidebarInset,
+  SidebarMenu,
+  SidebarMenuAction,
+  SidebarMenuBadge,
+  SidebarMenuButton,
+  SidebarMenuItem,
+  SidebarMenuSkeleton,
+  SidebarMenuSub,
+  SidebarMenuSubButton,
+  SidebarMenuSubItem,
+  SidebarProvider,
+  SidebarRail,
+  SidebarSeparator,
+  SidebarTrigger,
+  useSidebar,
+};
diff --git a/autogpt_platform/frontend/src/components/ui/skeleton.tsx b/autogpt_platform/frontend/src/components/ui/skeleton.tsx
new file mode 100644
index 0000000000..f38dd7313a
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/skeleton.tsx
@@ -0,0 +1,18 @@
+import { cn } from "@/lib/utils";
+
+function Skeleton({
+  className,
+  ...props
+}: React.HTMLAttributes<HTMLDivElement>) {
+  return (
+    <div
+      className={cn(
+        "animate-pulse rounded-md bg-neutral-900/10 dark:bg-neutral-50/10",
+        className,
+      )}
+      {...props}
+    />
+  );
+}
+
+export { Skeleton };
diff --git a/autogpt_platform/frontend/src/components/ui/tooltip.tsx b/autogpt_platform/frontend/src/components/ui/tooltip.tsx
new file mode 100644
index 0000000000..93d498e1e4
--- /dev/null
+++ b/autogpt_platform/frontend/src/components/ui/tooltip.tsx
@@ -0,0 +1,32 @@
+"use client";
+
+import * as React from "react";
+import * as TooltipPrimitive from "@radix-ui/react-tooltip";
+
+import { cn } from "@/lib/utils";
+
+const TooltipProvider = TooltipPrimitive.Provider;
+
+const Tooltip = TooltipPrimitive.Root;
+
+const TooltipTrigger = TooltipPrimitive.Trigger;
+
+const TooltipContent = React.forwardRef<
+  React.ElementRef<typeof TooltipPrimitive.Content>,
+  React.ComponentPropsWithoutRef<typeof TooltipPrimitive.Content>
+>(({ className, sideOffset = 4, ...props }, ref) => (
+  <TooltipPrimitive.Portal>
+    <TooltipPrimitive.Content
+      ref={ref}
+      sideOffset={sideOffset}
+      className={cn(
+        "z-50 origin-[--radix-tooltip-content-transform-origin] overflow-hidden rounded-md bg-neutral-900 px-3 py-1.5 text-xs text-neutral-50 animate-in fade-in-0 zoom-in-95 data-[state=closed]:animate-out data-[state=closed]:fade-out-0 data-[state=closed]:zoom-out-95 data-[side=bottom]:slide-in-from-top-2 data-[side=left]:slide-in-from-right-2 data-[side=right]:slide-in-from-left-2 data-[side=top]:slide-in-from-bottom-2 dark:bg-neutral-50 dark:text-neutral-900",
+        className,
+      )}
+      {...props}
+    />
+  </TooltipPrimitive.Portal>
+));
+TooltipContent.displayName = TooltipPrimitive.Content.displayName;
+
+export { Tooltip, TooltipTrigger, TooltipContent, TooltipProvider };
diff --git a/autogpt_platform/frontend/src/hooks/use-mobile.tsx b/autogpt_platform/frontend/src/hooks/use-mobile.tsx
new file mode 100644
index 0000000000..a93d583938
--- /dev/null
+++ b/autogpt_platform/frontend/src/hooks/use-mobile.tsx
@@ -0,0 +1,21 @@
+import * as React from "react";
+
+const MOBILE_BREAKPOINT = 768;
+
+export function useIsMobile() {
+  const [isMobile, setIsMobile] = React.useState<boolean | undefined>(
+    undefined,
+  );
+
+  React.useEffect(() => {
+    const mql = window.matchMedia(`(max-width: ${MOBILE_BREAKPOINT - 1}px)`);
+    const onChange = () => {
+      setIsMobile(window.innerWidth < MOBILE_BREAKPOINT);
+    };
+    mql.addEventListener("change", onChange);
+    setIsMobile(window.innerWidth < MOBILE_BREAKPOINT);
+    return () => mql.removeEventListener("change", onChange);
+  }, []);
+
+  return !!isMobile;
+}
diff --git a/autogpt_platform/frontend/src/hooks/useAgentGraph.tsx b/autogpt_platform/frontend/src/hooks/useAgentGraph.tsx
index 6c097c395e..d422e389dd 100644
--- a/autogpt_platform/frontend/src/hooks/useAgentGraph.tsx
+++ b/autogpt_platform/frontend/src/hooks/useAgentGraph.tsx
@@ -66,7 +66,7 @@ export default function useAgentGraph(
   >(null);
   const [xyNodes, setXYNodes] = useState<CustomNode[]>([]);
   const [xyEdges, setXYEdges] = useState<CustomEdge[]>([]);
-  const betaBlocks = useGetFlag(Flag.BETA_BLOCKS);
+  const betaBlocks = useGetFlag(Flag.BETA_BLOCKS) as string[];
 
   // Filter blocks based on beta flags
   const availableBlocks = useMemo(() => {
diff --git a/autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts b/autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts
index 74855f5e28..44fb25dbfc 100644
--- a/autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts
+++ b/autogpt_platform/frontend/src/lib/autogpt-server-api/types.ts
@@ -362,25 +362,14 @@ export type GraphMeta = {
   user_id: UserID;
   version: number;
   is_active: boolean;
+  created_at: Date;
   name: string;
   description: string;
   instructions?: string | null;
   recommended_schedule_cron: string | null;
   forked_from_id?: GraphID | null;
   forked_from_version?: number | null;
-  input_schema: GraphInputSchema;
-  output_schema: GraphOutputSchema;
-  credentials_input_schema: CredentialsInputSchema;
-} & (
-  | {
-      has_external_trigger: true;
-      trigger_setup_info: GraphTriggerInfo;
-    }
-  | {
-      has_external_trigger: false;
-      trigger_setup_info: null;
-    }
-);
+};
 
 export type GraphID = Brand<string, "GraphID">;
 
@@ -447,11 +436,22 @@ export type GraphTriggerInfo = {
 
 /* Mirror of backend/data/graph.py:Graph */
 export type Graph = GraphMeta & {
-  created_at: Date;
   nodes: Node[];
   links: Link[];
   sub_graphs: Omit<Graph, "sub_graphs">[]; // Flattened sub-graphs
-};
+  input_schema: GraphInputSchema;
+  output_schema: GraphOutputSchema;
+  credentials_input_schema: CredentialsInputSchema;
+} & (
+    | {
+        has_external_trigger: true;
+        trigger_setup_info: GraphTriggerInfo;
+      }
+    | {
+        has_external_trigger: false;
+        trigger_setup_info: null;
+      }
+  );
 
 export type GraphUpdateable = Omit<
   Graph,
diff --git a/autogpt_platform/frontend/src/lib/constants.ts b/autogpt_platform/frontend/src/lib/constants.ts
index de5aac1670..19365a56ac 100644
--- a/autogpt_platform/frontend/src/lib/constants.ts
+++ b/autogpt_platform/frontend/src/lib/constants.ts
@@ -11,10 +11,3 @@ export const API_KEY_HEADER_NAME = "X-API-Key";
 
 // Layout
 export const NAVBAR_HEIGHT_PX = 60;
-
-// Routes
-export function getHomepageRoute(isChatEnabled?: boolean | null): string {
-  if (isChatEnabled === true) return "/copilot";
-  if (isChatEnabled === false) return "/library";
-  return "/";
-}
diff --git a/autogpt_platform/frontend/src/lib/supabase/helpers.ts b/autogpt_platform/frontend/src/lib/supabase/helpers.ts
index 3fd0eacb5f..c77e43e7b4 100644
--- a/autogpt_platform/frontend/src/lib/supabase/helpers.ts
+++ b/autogpt_platform/frontend/src/lib/supabase/helpers.ts
@@ -1,4 +1,3 @@
-import { getHomepageRoute } from "@/lib/constants";
 import { environment } from "@/services/environment";
 import { Key, storage } from "@/services/storage/local-storage";
 import { type CookieOptions } from "@supabase/ssr";
@@ -7,6 +6,7 @@ import { SupabaseClient } from "@supabase/supabase-js";
 export const PROTECTED_PAGES = [
   "/auth/authorize",
   "/auth/integrations",
+  "/copilot",
   "/monitor",
   "/build",
   "/onboarding",
@@ -71,7 +71,7 @@ export function getRedirectPath(
   }
 
   if (isAdminPage(path) && userRole !== "admin") {
-    return getHomepageRoute();
+    return "/";
   }
 
   return null;
diff --git a/autogpt_platform/frontend/src/lib/supabase/middleware.ts b/autogpt_platform/frontend/src/lib/supabase/middleware.ts
index de8b867ef0..cd1f4a240e 100644
--- a/autogpt_platform/frontend/src/lib/supabase/middleware.ts
+++ b/autogpt_platform/frontend/src/lib/supabase/middleware.ts
@@ -1,4 +1,3 @@
-import { getHomepageRoute } from "@/lib/constants";
 import { environment } from "@/services/environment";
 import { createServerClient } from "@supabase/ssr";
 import { NextResponse, type NextRequest } from "next/server";
@@ -67,7 +66,7 @@ export async function updateSession(request: NextRequest) {
 
     // 2. Check if user is authenticated but lacks admin role when accessing admin pages
     if (user && userRole !== "admin" && isAdminPage(pathname)) {
-      url.pathname = getHomepageRoute();
+      url.pathname = "/";
       return NextResponse.redirect(url);
     }
 
diff --git a/autogpt_platform/frontend/src/lib/utils.ts b/autogpt_platform/frontend/src/lib/utils.ts
index d3abc56b6c..8c300dd6c9 100644
--- a/autogpt_platform/frontend/src/lib/utils.ts
+++ b/autogpt_platform/frontend/src/lib/utils.ts
@@ -1,5 +1,5 @@
 import { type ClassValue, clsx } from "clsx";
-import { isEmpty as _isEmpty } from "lodash";
+import _isEmpty from "lodash/isEmpty";
 import { twMerge } from "tailwind-merge";
 
 import { NodeDimension } from "@/app/(platform)/build/components/legacy-builder/Flow/Flow";
diff --git a/autogpt_platform/frontend/src/providers/onboarding/onboarding-provider.tsx b/autogpt_platform/frontend/src/providers/onboarding/onboarding-provider.tsx
index 1ee4b2b6db..42cb99f187 100644
--- a/autogpt_platform/frontend/src/providers/onboarding/onboarding-provider.tsx
+++ b/autogpt_platform/frontend/src/providers/onboarding/onboarding-provider.tsx
@@ -23,9 +23,7 @@ import {
   WebSocketNotification,
 } from "@/lib/autogpt-server-api";
 import { useBackendAPI } from "@/lib/autogpt-server-api/context";
-import { getHomepageRoute } from "@/lib/constants";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
 import Link from "next/link";
 import { usePathname, useRouter } from "next/navigation";
 import {
@@ -104,8 +102,6 @@ export default function OnboardingProvider({
   const pathname = usePathname();
   const router = useRouter();
   const { isLoggedIn } = useSupabase();
-  const isChatEnabled = useGetFlag(Flag.CHAT);
-  const homepageRoute = getHomepageRoute(isChatEnabled);
 
   useOnboardingTimezoneDetection();
 
@@ -150,7 +146,7 @@ export default function OnboardingProvider({
         if (isOnOnboardingRoute) {
           const enabled = await resolveResponse(getV1IsOnboardingEnabled());
           if (!enabled) {
-            router.push(homepageRoute);
+            router.push("/");
             return;
           }
         }
@@ -162,7 +158,7 @@ export default function OnboardingProvider({
           isOnOnboardingRoute &&
           shouldRedirectFromOnboarding(onboarding.completedSteps, pathname)
         ) {
-          router.push(homepageRoute);
+          router.push("/");
         }
       } catch (error) {
         console.error("Failed to initialize onboarding:", error);
@@ -177,7 +173,7 @@ export default function OnboardingProvider({
     }
 
     initializeOnboarding();
-  }, [api, homepageRoute, isOnOnboardingRoute, router, isLoggedIn, pathname]);
+  }, [api, isOnOnboardingRoute, router, isLoggedIn, pathname]);
 
   const handleOnboardingNotification = useCallback(
     (notification: WebSocketNotification) => {
diff --git a/autogpt_platform/frontend/src/services/environment/index.ts b/autogpt_platform/frontend/src/services/environment/index.ts
index f19bc417e3..0214dcb3c8 100644
--- a/autogpt_platform/frontend/src/services/environment/index.ts
+++ b/autogpt_platform/frontend/src/services/environment/index.ts
@@ -83,6 +83,10 @@ function getPostHogCredentials() {
   };
 }
 
+function getLaunchDarklyClientId() {
+  return process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
+}
+
 function isProductionBuild() {
   return process.env.NODE_ENV === "production";
 }
@@ -120,7 +124,10 @@ function isVercelPreview() {
 }
 
 function areFeatureFlagsEnabled() {
-  return process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "enabled";
+  return (
+    process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true" &&
+    Boolean(process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID)
+  );
 }
 
 function isPostHogEnabled() {
@@ -143,6 +150,7 @@ export const environment = {
   getSupabaseAnonKey,
   getPreviewStealingDev,
   getPostHogCredentials,
+  getLaunchDarklyClientId,
   // Assertions
   isServerSide,
   isClientSide,
diff --git a/autogpt_platform/frontend/src/services/feature-flags/FeatureFlagPage.tsx b/autogpt_platform/frontend/src/services/feature-flags/FeatureFlagPage.tsx
new file mode 100644
index 0000000000..eef0691de2
--- /dev/null
+++ b/autogpt_platform/frontend/src/services/feature-flags/FeatureFlagPage.tsx
@@ -0,0 +1,59 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { useLDClient } from "launchdarkly-react-client-sdk";
+import { useRouter } from "next/navigation";
+import { ReactNode, useEffect, useState } from "react";
+import { environment } from "../environment";
+import { Flag, useGetFlag } from "./use-get-flag";
+
+interface FeatureFlagRedirectProps {
+  flag: Flag;
+  whenDisabled: string;
+  children: ReactNode;
+}
+
+export function FeatureFlagPage({
+  flag,
+  whenDisabled,
+  children,
+}: FeatureFlagRedirectProps) {
+  const [isLoading, setIsLoading] = useState(true);
+  const router = useRouter();
+  const flagValue = useGetFlag(flag);
+  const ldClient = useLDClient();
+  const ldEnabled = environment.areFeatureFlagsEnabled();
+  const ldReady = Boolean(ldClient);
+  const flagEnabled = Boolean(flagValue);
+
+  useEffect(() => {
+    const initialize = async () => {
+      if (!ldEnabled) {
+        router.replace(whenDisabled);
+        setIsLoading(false);
+        return;
+      }
+
+      // Wait for LaunchDarkly to initialize when enabled to prevent race conditions
+      if (ldEnabled && !ldReady) return;
+
+      try {
+        await ldClient?.waitForInitialization();
+        if (!flagEnabled) router.replace(whenDisabled);
+      } catch (error) {
+        console.error(error);
+        router.replace(whenDisabled);
+      } finally {
+        setIsLoading(false);
+      }
+    };
+
+    initialize();
+  }, [ldReady, flagEnabled]);
+
+  return isLoading || !flagEnabled ? (
+    <LoadingSpinner size="large" cover />
+  ) : (
+    <>{children}</>
+  );
+}
diff --git a/autogpt_platform/frontend/src/services/feature-flags/FeatureFlagRedirect.tsx b/autogpt_platform/frontend/src/services/feature-flags/FeatureFlagRedirect.tsx
new file mode 100644
index 0000000000..b843b5567c
--- /dev/null
+++ b/autogpt_platform/frontend/src/services/feature-flags/FeatureFlagRedirect.tsx
@@ -0,0 +1,51 @@
+"use client";
+
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
+import { useLDClient } from "launchdarkly-react-client-sdk";
+import { useRouter } from "next/navigation";
+import { useEffect } from "react";
+import { environment } from "../environment";
+import { Flag, useGetFlag } from "./use-get-flag";
+
+interface FeatureFlagRedirectProps {
+  flag: Flag;
+  whenEnabled: string;
+  whenDisabled: string;
+}
+
+export function FeatureFlagRedirect({
+  flag,
+  whenEnabled,
+  whenDisabled,
+}: FeatureFlagRedirectProps) {
+  const router = useRouter();
+  const flagValue = useGetFlag(flag);
+  const ldEnabled = environment.areFeatureFlagsEnabled();
+  const ldClient = useLDClient();
+  const ldReady = Boolean(ldClient);
+  const flagEnabled = Boolean(flagValue);
+
+  useEffect(() => {
+    const initialize = async () => {
+      if (!ldEnabled) {
+        router.replace(whenDisabled);
+        return;
+      }
+
+      // Wait for LaunchDarkly to initialize when enabled to prevent race conditions
+      if (ldEnabled && !ldReady) return;
+
+      try {
+        await ldClient?.waitForInitialization();
+        router.replace(flagEnabled ? whenEnabled : whenDisabled);
+      } catch (error) {
+        console.error(error);
+        router.replace(whenDisabled);
+      }
+    };
+
+    initialize();
+  }, [ldReady, flagEnabled]);
+
+  return <LoadingSpinner size="large" cover />;
+}
diff --git a/autogpt_platform/frontend/src/services/feature-flags/feature-flag-provider.tsx b/autogpt_platform/frontend/src/services/feature-flags/feature-flag-provider.tsx
index 47e4bd738a..da073816ac 100644
--- a/autogpt_platform/frontend/src/services/feature-flags/feature-flag-provider.tsx
+++ b/autogpt_platform/frontend/src/services/feature-flags/feature-flag-provider.tsx
@@ -1,5 +1,6 @@
 "use client";
 
+import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import * as Sentry from "@sentry/nextjs";
 import { LDProvider } from "launchdarkly-react-client-sdk";
@@ -7,17 +8,17 @@ import type { ReactNode } from "react";
 import { useMemo } from "react";
 import { environment } from "../environment";
 
-const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
-const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
 const LAUNCHDARKLY_INIT_TIMEOUT_MS = 5000;
 
 export function LaunchDarklyProvider({ children }: { children: ReactNode }) {
   const { user, isUserLoading } = useSupabase();
-  const isCloud = environment.isCloud();
-  const isLaunchDarklyConfigured = isCloud && envEnabled && clientId;
+  const envEnabled = environment.areFeatureFlagsEnabled();
+  const clientId = environment.getLaunchDarklyClientId();
 
   const context = useMemo(() => {
-    if (isUserLoading || !user) {
+    if (isUserLoading) return;
+
+    if (!user) {
       return {
         kind: "user" as const,
         key: "anonymous",
@@ -36,15 +37,17 @@ export function LaunchDarklyProvider({ children }: { children: ReactNode }) {
     };
   }, [user, isUserLoading]);
 
-  if (!isLaunchDarklyConfigured) {
+  if (!envEnabled) {
     return <>{children}</>;
   }
 
+  if (isUserLoading) {
+    return <LoadingSpinner size="large" cover />;
+  }
+
   return (
     <LDProvider
-      // Add this key prop. It will be 'anonymous' when logged out,
-      key={context.key}
-      clientSideID={clientId}
+      clientSideID={clientId ?? ""}
       context={context}
       timeout={LAUNCHDARKLY_INIT_TIMEOUT_MS}
       reactOptions={{ useCamelCaseFlagKeys: false }}
diff --git a/autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts b/autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts
index 64b69895f3..c61fc9749d 100644
--- a/autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts
+++ b/autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts
@@ -1,6 +1,7 @@
 "use client";
 
 import { DEFAULT_SEARCH_TERMS } from "@/app/(platform)/marketplace/components/HeroSection/helpers";
+import { environment } from "@/services/environment";
 import { useFlags } from "launchdarkly-react-client-sdk";
 
 export enum Flag {
@@ -18,24 +19,9 @@ export enum Flag {
   CHAT = "chat",
 }
 
-export type FlagValues = {
-  [Flag.BETA_BLOCKS]: string[];
-  [Flag.NEW_BLOCK_MENU]: boolean;
-  [Flag.NEW_AGENT_RUNS]: boolean;
-  [Flag.GRAPH_SEARCH]: boolean;
-  [Flag.ENABLE_ENHANCED_OUTPUT_HANDLING]: boolean;
-  [Flag.NEW_FLOW_EDITOR]: boolean;
-  [Flag.BUILDER_VIEW_SWITCH]: boolean;
-  [Flag.SHARE_EXECUTION_RESULTS]: boolean;
-  [Flag.AGENT_FAVORITING]: boolean;
-  [Flag.MARKETPLACE_SEARCH_TERMS]: string[];
-  [Flag.ENABLE_PLATFORM_PAYMENT]: boolean;
-  [Flag.CHAT]: boolean;
-};
-
 const isPwMockEnabled = process.env.NEXT_PUBLIC_PW_TEST === "true";
 
-const mockFlags = {
+const defaultFlags = {
   [Flag.BETA_BLOCKS]: [],
   [Flag.NEW_BLOCK_MENU]: false,
   [Flag.NEW_AGENT_RUNS]: false,
@@ -50,17 +36,16 @@ const mockFlags = {
   [Flag.CHAT]: false,
 };
 
-export function useGetFlag<T extends Flag>(flag: T): FlagValues[T] | null {
+type FlagValues = typeof defaultFlags;
+
+export function useGetFlag<T extends Flag>(flag: T): FlagValues[T] {
   const currentFlags = useFlags<FlagValues>();
   const flagValue = currentFlags[flag];
+  const areFlagsEnabled = environment.areFeatureFlagsEnabled();
 
-  const envEnabled = process.env.NEXT_PUBLIC_LAUNCHDARKLY_ENABLED === "true";
-  const clientId = process.env.NEXT_PUBLIC_LAUNCHDARKLY_CLIENT_ID;
-  const isLaunchDarklyConfigured = envEnabled && Boolean(clientId);
-
-  if (!isLaunchDarklyConfigured || isPwMockEnabled) {
-    return mockFlags[flag];
+  if (!areFlagsEnabled || isPwMockEnabled) {
+    return defaultFlags[flag];
   }
 
-  return flagValue ?? mockFlags[flag];
+  return flagValue ?? defaultFlags[flag];
 }
diff --git a/autogpt_platform/frontend/src/tests/library.spec.ts b/autogpt_platform/frontend/src/tests/library.spec.ts
index 1972e94522..52941785e3 100644
--- a/autogpt_platform/frontend/src/tests/library.spec.ts
+++ b/autogpt_platform/frontend/src/tests/library.spec.ts
@@ -59,12 +59,13 @@ test.describe("Library", () => {
   });
 
   test("pagination works correctly", async ({ page }, testInfo) => {
-    test.setTimeout(testInfo.timeout * 3); // Increase timeout for pagination operations
+    test.setTimeout(testInfo.timeout * 3);
     await page.goto("/library");
 
+    const PAGE_SIZE = 20;
     const paginationResult = await libraryPage.testPagination();
 
-    if (paginationResult.initialCount >= 10) {
+    if (paginationResult.initialCount >= PAGE_SIZE) {
       expect(paginationResult.finalCount).toBeGreaterThanOrEqual(
         paginationResult.initialCount,
       );
@@ -133,7 +134,10 @@ test.describe("Library", () => {
     test.expect(clearedSearchValue).toBe("");
   });
 
-  test("pagination while searching works correctly", async ({ page }) => {
+  test("pagination while searching works correctly", async ({
+    page,
+  }, testInfo) => {
+    test.setTimeout(testInfo.timeout * 3);
     await page.goto("/library");
 
     const allAgents = await libraryPage.getAgents();
@@ -152,9 +156,10 @@ test.describe("Library", () => {
     );
     expect(matchingResults.length).toEqual(initialSearchResults.length);
 
+    const PAGE_SIZE = 20;
     const searchPaginationResult = await libraryPage.testPagination();
 
-    if (searchPaginationResult.initialCount >= 10) {
+    if (searchPaginationResult.initialCount >= PAGE_SIZE) {
       expect(searchPaginationResult.finalCount).toBeGreaterThanOrEqual(
         searchPaginationResult.initialCount,
       );
diff --git a/autogpt_platform/frontend/src/tests/marketplace-creator.spec.ts b/autogpt_platform/frontend/src/tests/marketplace-creator.spec.ts
index 3558f0672c..a41b652afb 100644
--- a/autogpt_platform/frontend/src/tests/marketplace-creator.spec.ts
+++ b/autogpt_platform/frontend/src/tests/marketplace-creator.spec.ts
@@ -69,9 +69,12 @@ test.describe("Marketplace Creator Page – Basic Functionality", () => {
       await marketplacePage.getFirstCreatorProfile(page);
     await firstCreatorProfile.click();
     await page.waitForURL("**/marketplace/creator/**");
+    await page.waitForLoadState("networkidle").catch(() => {});
+
     const firstAgent = page
       .locator('[data-testid="store-card"]:visible')
       .first();
+    await firstAgent.waitFor({ state: "visible", timeout: 30000 });
 
     await firstAgent.click();
     await page.waitForURL("**/marketplace/agent/**");
diff --git a/autogpt_platform/frontend/src/tests/marketplace.spec.ts b/autogpt_platform/frontend/src/tests/marketplace.spec.ts
index 774713dc82..44d89bf351 100644
--- a/autogpt_platform/frontend/src/tests/marketplace.spec.ts
+++ b/autogpt_platform/frontend/src/tests/marketplace.spec.ts
@@ -77,7 +77,6 @@ test.describe("Marketplace – Basic Functionality", () => {
 
     const firstFeaturedAgent =
       await marketplacePage.getFirstFeaturedAgent(page);
-    await firstFeaturedAgent.waitFor({ state: "visible" });
     await firstFeaturedAgent.click();
     await page.waitForURL("**/marketplace/agent/**");
     await matchesUrl(page, /\/marketplace\/agent\/.+/);
@@ -116,7 +115,15 @@ test.describe("Marketplace – Basic Functionality", () => {
     const searchTerm = page.getByText("DummyInput").first();
     await isVisible(searchTerm);
 
-    await page.waitForTimeout(10000);
+    await page.waitForLoadState("networkidle").catch(() => {});
+
+    await page
+      .waitForFunction(
+        () =>
+          document.querySelectorAll('[data-testid="store-card"]').length > 0,
+        { timeout: 15000 },
+      )
+      .catch(() => console.log("No search results appeared within timeout"));
 
     const results = await marketplacePage.getSearchResultsCount(page);
     expect(results).toBeGreaterThan(0);
diff --git a/autogpt_platform/frontend/src/tests/pages/library.page.ts b/autogpt_platform/frontend/src/tests/pages/library.page.ts
index 3a7695ec3a..03e98598b4 100644
--- a/autogpt_platform/frontend/src/tests/pages/library.page.ts
+++ b/autogpt_platform/frontend/src/tests/pages/library.page.ts
@@ -300,21 +300,27 @@ export class LibraryPage extends BasePage {
   async scrollToLoadMore(): Promise<void> {
     console.log(`scrolling to load more agents`);
 
-    // Get initial agent count
-    const initialCount = await this.getAgentCount();
-    console.log(`Initial agent count: ${initialCount}`);
+    const initialCount = await this.getAgentCountByListLength();
+    console.log(`Initial agent count (DOM cards): ${initialCount}`);
 
-    // Scroll down to trigger pagination
     await this.scrollToBottom();
 
-    // Wait for potential new agents to load
-    await this.page.waitForTimeout(2000);
+    await this.page
+      .waitForLoadState("networkidle", { timeout: 10000 })
+      .catch(() => console.log("Network idle timeout, continuing..."));
 
-    // Check if more agents loaded
-    const newCount = await this.getAgentCount();
-    console.log(`New agent count after scroll: ${newCount}`);
+    await this.page
+      .waitForFunction(
+        (prevCount) =>
+          document.querySelectorAll('[data-testid="library-agent-card"]')
+            .length > prevCount,
+        initialCount,
+        { timeout: 5000 },
+      )
+      .catch(() => {});
 
-    return;
+    const newCount = await this.getAgentCountByListLength();
+    console.log(`New agent count after scroll (DOM cards): ${newCount}`);
   }
 
   async testPagination(): Promise<{
diff --git a/autogpt_platform/frontend/src/tests/pages/marketplace.page.ts b/autogpt_platform/frontend/src/tests/pages/marketplace.page.ts
index 20f60c371a..115a7b2f12 100644
--- a/autogpt_platform/frontend/src/tests/pages/marketplace.page.ts
+++ b/autogpt_platform/frontend/src/tests/pages/marketplace.page.ts
@@ -9,6 +9,7 @@ export class MarketplacePage extends BasePage {
 
   async goto(page: Page) {
     await page.goto("/marketplace");
+    await page.waitForLoadState("networkidle").catch(() => {});
   }
 
   async getMarketplaceTitle(page: Page) {
@@ -109,16 +110,24 @@ export class MarketplacePage extends BasePage {
 
   async getFirstFeaturedAgent(page: Page) {
     const { getId } = getSelectors(page);
-    return getId("featured-store-card").first();
+    const card = getId("featured-store-card").first();
+    await card.waitFor({ state: "visible", timeout: 30000 });
+    return card;
   }
 
   async getFirstTopAgent() {
-    return this.page.locator('[data-testid="store-card"]:visible').first();
+    const card = this.page
+      .locator('[data-testid="store-card"]:visible')
+      .first();
+    await card.waitFor({ state: "visible", timeout: 30000 });
+    return card;
   }
 
   async getFirstCreatorProfile(page: Page) {
     const { getId } = getSelectors(page);
-    return getId("creator-card").first();
+    const card = getId("creator-card").first();
+    await card.waitFor({ state: "visible", timeout: 30000 });
+    return card;
   }
 
   async getSearchResultsCount(page: Page) {
diff --git a/autogpt_platform/frontend/src/tests/signin.spec.ts b/autogpt_platform/frontend/src/tests/signin.spec.ts
index 8582ce8b3a..8a852531b4 100644
--- a/autogpt_platform/frontend/src/tests/signin.spec.ts
+++ b/autogpt_platform/frontend/src/tests/signin.spec.ts
@@ -172,7 +172,7 @@ test("multi-tab logout with WebSocket cleanup", async ({ context }) => {
   await page2.close();
 });
 
-test("logged in user is redirected from /login to /library", async ({
+test("logged in user is redirected from /login to /copilot", async ({
   page,
 }) => {
   const testUser = await getTestUser();
diff --git a/autogpt_platform/frontend/tailwind.config.ts b/autogpt_platform/frontend/tailwind.config.ts
index 1adc53bdc4..85b31c72f8 100644
--- a/autogpt_platform/frontend/tailwind.config.ts
+++ b/autogpt_platform/frontend/tailwind.config.ts
@@ -65,6 +65,16 @@ const config = {
           "600": "#282828",
           "700": "#272727",
         },
+        sidebar: {
+          DEFAULT: "hsl(var(--sidebar-background))",
+          foreground: "hsl(var(--sidebar-foreground))",
+          primary: "hsl(var(--sidebar-primary))",
+          "primary-foreground": "hsl(var(--sidebar-primary-foreground))",
+          accent: "hsl(var(--sidebar-accent))",
+          "accent-foreground": "hsl(var(--sidebar-accent-foreground))",
+          border: "hsl(var(--sidebar-border))",
+          ring: "hsl(var(--sidebar-ring))",
+        },
       },
       spacing: {
         "0": "0rem",
diff --git a/docs/integrations/README.md b/docs/integrations/README.md
index 263d7e6365..a471ef3533 100644
--- a/docs/integrations/README.md
+++ b/docs/integrations/README.md
@@ -61,8 +61,7 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 | [Get List Item](block-integrations/basic.md#get-list-item) | Returns the element at the given index |
 | [Get Store Agent Details](block-integrations/system/store_operations.md#get-store-agent-details) | Get detailed information about an agent from the store |
 | [Get Weather Information](block-integrations/basic.md#get-weather-information) | Retrieves weather information for a specified location using OpenWeatherMap API |
-| [Human In The Loop](block-integrations/basic.md#human-in-the-loop) | Pause execution and wait for human approval or modification of data |
-| [Linear Search Issues](block-integrations/linear/issues.md#linear-search-issues) | Searches for issues on Linear |
+| [Human In The Loop](block-integrations/basic.md#human-in-the-loop) | Pause execution for human review |
 | [List Is Empty](block-integrations/basic.md#list-is-empty) | Checks if a list is empty |
 | [List Library Agents](block-integrations/system/library_operations.md#list-library-agents) | List all agents in your personal library |
 | [Note](block-integrations/basic.md#note) | A visual annotation block that displays a sticky note in the workflow editor for documentation and organization purposes |
@@ -193,6 +192,7 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 | [Get Current Time](block-integrations/text.md#get-current-time) | This block outputs the current time |
 | [Match Text Pattern](block-integrations/text.md#match-text-pattern) | Matches text against a regex pattern and forwards data to positive or negative output based on the match |
 | [Text Decoder](block-integrations/text.md#text-decoder) | Decodes a string containing escape sequences into actual text |
+| [Text Encoder](block-integrations/text.md#text-encoder) | Encodes a string by converting special characters into escape sequences |
 | [Text Replace](block-integrations/text.md#text-replace) | This block is used to replace a text with a new text |
 | [Text Split](block-integrations/text.md#text-split) | This block is used to split a text into a list of strings |
 | [Word Character Count](block-integrations/text.md#word-character-count) | Counts the number of words and characters in a given text |
@@ -233,6 +233,7 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 | [Stagehand Extract](block-integrations/stagehand/blocks.md#stagehand-extract) | Extract structured data from a webpage |
 | [Stagehand Observe](block-integrations/stagehand/blocks.md#stagehand-observe) | Find suggested actions for your workflows |
 | [Unreal Text To Speech](block-integrations/llm.md#unreal-text-to-speech) | Converts text to speech using the Unreal Speech API |
+| [Video Narration](block-integrations/video/narration.md#video-narration) | Generate AI narration and add to video |
 
 ## Search and Information Retrieval
 
@@ -472,9 +473,13 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 
 | Block Name | Description |
 |------------|-------------|
-| [Add Audio To Video](block-integrations/multimedia.md#add-audio-to-video) | Block to attach an audio file to a video file using moviepy |
-| [Loop Video](block-integrations/multimedia.md#loop-video) | Block to loop a video to a given duration or number of repeats |
-| [Media Duration](block-integrations/multimedia.md#media-duration) | Block to get the duration of a media file |
+| [Add Audio To Video](block-integrations/video/add_audio.md#add-audio-to-video) | Block to attach an audio file to a video file using moviepy |
+| [Loop Video](block-integrations/video/loop.md#loop-video) | Block to loop a video to a given duration or number of repeats |
+| [Media Duration](block-integrations/video/duration.md#media-duration) | Block to get the duration of a media file |
+| [Video Clip](block-integrations/video/clip.md#video-clip) | Extract a time segment from a video |
+| [Video Concat](block-integrations/video/concat.md#video-concat) | Merge multiple video clips into one continuous video |
+| [Video Download](block-integrations/video/download.md#video-download) | Download video from URL (YouTube, Vimeo, news sites, direct links) |
+| [Video Text Overlay](block-integrations/video/text_overlay.md#video-text-overlay) | Add text overlay/caption to video |
 
 ## Productivity
 
@@ -571,6 +576,7 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 | [Linear Create Comment](block-integrations/linear/comment.md#linear-create-comment) | Creates a new comment on a Linear issue |
 | [Linear Create Issue](block-integrations/linear/issues.md#linear-create-issue) | Creates a new issue on Linear |
 | [Linear Get Project Issues](block-integrations/linear/issues.md#linear-get-project-issues) | Gets issues from a Linear project filtered by status and assignee |
+| [Linear Search Issues](block-integrations/linear/issues.md#linear-search-issues) | Searches for issues on Linear |
 | [Linear Search Projects](block-integrations/linear/projects.md#linear-search-projects) | Searches for projects on Linear |
 
 ## Hardware
diff --git a/docs/integrations/SUMMARY.md b/docs/integrations/SUMMARY.md
index 9ce440ca45..f481ae2e0a 100644
--- a/docs/integrations/SUMMARY.md
+++ b/docs/integrations/SUMMARY.md
@@ -85,7 +85,6 @@
 * [LLM](block-integrations/llm.md)
 * [Logic](block-integrations/logic.md)
 * [Misc](block-integrations/misc.md)
-* [Multimedia](block-integrations/multimedia.md)
 * [Notion Create Page](block-integrations/notion/create_page.md)
 * [Notion Read Database](block-integrations/notion/read_database.md)
 * [Notion Read Page](block-integrations/notion/read_page.md)
@@ -129,5 +128,13 @@
 * [Twitter Timeline](block-integrations/twitter/timeline.md)
 * [Twitter Tweet Lookup](block-integrations/twitter/tweet_lookup.md)
 * [Twitter User Lookup](block-integrations/twitter/user_lookup.md)
+* [Video Add Audio](block-integrations/video/add_audio.md)
+* [Video Clip](block-integrations/video/clip.md)
+* [Video Concat](block-integrations/video/concat.md)
+* [Video Download](block-integrations/video/download.md)
+* [Video Duration](block-integrations/video/duration.md)
+* [Video Loop](block-integrations/video/loop.md)
+* [Video Narration](block-integrations/video/narration.md)
+* [Video Text Overlay](block-integrations/video/text_overlay.md)
 * [Wolfram LLM API](block-integrations/wolfram/llm_api.md)
 * [Zerobounce Validate Emails](block-integrations/zerobounce/validate_emails.md)
diff --git a/docs/integrations/block-integrations/basic.md b/docs/integrations/block-integrations/basic.md
index 5a73fd5a03..08def38ede 100644
--- a/docs/integrations/block-integrations/basic.md
+++ b/docs/integrations/block-integrations/basic.md
@@ -975,7 +975,7 @@ A travel planning application could use this block to provide users with current
 ## Human In The Loop
 
 ### What it is
-Pause execution and wait for human approval or modification of data
+Pause execution for human review. Data flows through approved_data or rejected_data output based on the reviewer's decision. Outputs contain the actual data, not status strings.
 
 ### How it works
 <!-- MANUAL: how_it_works -->
@@ -988,18 +988,18 @@ This enables human oversight at critical points in automated workflows, ensuring
 
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
-| data | The data to be reviewed by a human user | Data | Yes |
-| name | A descriptive name for what this data represents | str | Yes |
-| editable | Whether the human reviewer can edit the data | bool | No |
+| data | The data to be reviewed by a human user. This exact data will be passed through to either approved_data or rejected_data output based on the reviewer's decision. | Data | Yes |
+| name | A descriptive name for what this data represents. This helps the reviewer understand what they are reviewing. | str | Yes |
+| editable | Whether the human reviewer can edit the data before approving or rejecting it | bool | No |
 
 ### Outputs
 
 | Output | Description | Type |
 |--------|-------------|------|
 | error | Error message if the operation failed | str |
-| approved_data | The data when approved (may be modified by reviewer) | Approved Data |
-| rejected_data | The data when rejected (may be modified by reviewer) | Rejected Data |
-| review_message | Any message provided by the reviewer | str |
+| approved_data | Outputs the input data when the reviewer APPROVES it. The value is the actual data itself (not a status string like 'APPROVED'). If the reviewer edited the data, this contains the modified version. Connect downstream blocks here for the 'approved' workflow path. | Approved Data |
+| rejected_data | Outputs the input data when the reviewer REJECTS it. The value is the actual data itself (not a status string like 'REJECTED'). If the reviewer edited the data, this contains the modified version. Connect downstream blocks here for the 'rejected' workflow path. | Rejected Data |
+| review_message | Optional message provided by the reviewer explaining their decision. Only outputs when the reviewer provides a message; this pin does not fire if no message was given. | str |
 
 ### Possible use case
 <!-- MANUAL: use_case -->
diff --git a/docs/integrations/block-integrations/linear/issues.md b/docs/integrations/block-integrations/linear/issues.md
index 8955ba761e..fffd1a97c7 100644
--- a/docs/integrations/block-integrations/linear/issues.md
+++ b/docs/integrations/block-integrations/linear/issues.md
@@ -90,9 +90,9 @@ Searches for issues on Linear
 
 ### How it works
 <!-- MANUAL: how_it_works -->
-This block searches for issues in Linear using a text query. It searches across issue titles, descriptions, and other fields to find matching issues.
+This block searches for issues in Linear using a text query. It searches across issue titles, descriptions, and other fields to find matching issues. You can limit the number of results returned using the `max_results` parameter (default: 10, max: 100) to control token consumption and response size.
 
-Returns a list of issues matching the search term.
+Optionally filter results by team name to narrow searches to specific workspaces. If a team name is provided, the block resolves it to a team ID before searching. Returns matching issues with their state, creation date, project, and assignee information. If the search or team resolution fails, an error message is returned.
 <!-- END MANUAL -->
 
 ### Inputs
@@ -100,12 +100,14 @@ Returns a list of issues matching the search term.
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | term | Term to search for issues | str | Yes |
+| max_results | Maximum number of results to return | int | No |
+| team_name | Optional team name to filter results (e.g., 'Internal', 'Open Source') | str | No |
 
 ### Outputs
 
 | Output | Description | Type |
 |--------|-------------|------|
-| error | Error message if the operation failed | str |
+| error | Error message if the search failed | str |
 | issues | List of issues | List[Issue] |
 
 ### Possible use case
diff --git a/docs/integrations/block-integrations/llm.md b/docs/integrations/block-integrations/llm.md
index f4d69b912b..20a5147fcd 100644
--- a/docs/integrations/block-integrations/llm.md
+++ b/docs/integrations/block-integrations/llm.md
@@ -65,7 +65,7 @@ The result routes data to yes_output or no_output, enabling intelligent branchin
 | condition | A plaintext English description of the condition to evaluate | str | Yes |
 | yes_value | (Optional) Value to output if the condition is true. If not provided, input_value will be used. | Yes Value | No |
 | no_value | (Optional) Value to output if the condition is false. If not provided, input_value will be used. | No Value | No |
-| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 
 ### Outputs
 
@@ -103,7 +103,7 @@ The block sends the entire conversation history to the chosen LLM, including sys
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. | str | No |
 | messages | List of messages in the conversation. | List[Any] | Yes |
-| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
 | ollama_host | Ollama host for local  models | str | No |
 
@@ -257,7 +257,7 @@ The block formulates a prompt based on the given focus or source data, sends it
 |-------|-------------|------|----------|
 | focus | The focus of the list to generate. | str | No |
 | source_data | The data to generate the list from. | str | No |
-| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | max_retries | Maximum number of retries for generating a valid list. | int | No |
 | force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -424,7 +424,7 @@ The block sends the input prompt to a chosen LLM, along with any system prompts
 | prompt | The prompt to send to the language model. | str | Yes |
 | expected_format | Expected format of the response. If provided, the response will be validated against this format. The keys should be the expected fields in the response, and the values should be the description of the field. | Dict[str, str] | Yes |
 | list_result | Whether the response should be a list of objects in the expected format. | bool | No |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
@@ -464,7 +464,7 @@ The block sends the input prompt to a chosen LLM, processes the response, and re
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. You can use any of the {keys} from Prompt Values to fill in the prompt with values from the prompt values dictionary by putting them in curly braces. | str | Yes |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | retry | Number of times to retry the LLM call if the response does not match the expected format. | int | No |
 | prompt_values | Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}. | Dict[str, str] | No |
@@ -501,7 +501,7 @@ The block splits the input text into smaller chunks, sends each chunk to an LLM
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | text | The text to summarize. | str | Yes |
-| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | focus | The topic to focus on in the summary | str | No |
 | style | The style of the summary to generate. | "concise" \| "detailed" \| "bullet points" \| "numbered list" | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -763,7 +763,7 @@ Configure agent_mode_max_iterations to control loop behavior: 0 for single decis
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. | str | Yes |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-3-7-sonnet-20250219" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | multiple_tool_calls | Whether to allow multiple tool calls in a single response. | bool | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
diff --git a/docs/integrations/block-integrations/stagehand/blocks.md b/docs/integrations/block-integrations/stagehand/blocks.md
index dac0586fa2..cc201d092b 100644
--- a/docs/integrations/block-integrations/stagehand/blocks.md
+++ b/docs/integrations/block-integrations/stagehand/blocks.md
@@ -20,7 +20,7 @@ Configure timeouts for DOM settlement and page loading. Variables can be passed
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
-| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-3-7-sonnet-20250219" | No |
+| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
 | url | URL to navigate to. | str | Yes |
 | action | Action to perform. Suggested actions are: click, fill, type, press, scroll, select from dropdown. For multi-step actions, add an entry for each step. | List[str] | Yes |
 | variables | Variables to use in the action. Variables contains data you want the action to use. | Dict[str, str] | No |
@@ -65,7 +65,7 @@ Supports searching within iframes and configurable timeouts for dynamic content
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
-| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-3-7-sonnet-20250219" | No |
+| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
 | url | URL to navigate to. | str | Yes |
 | instruction | Natural language description of elements or actions to discover. | str | Yes |
 | iframes | Whether to search within iframes. If True, Stagehand will search for actions within iframes. | bool | No |
@@ -106,7 +106,7 @@ Use this to explore a page's interactive elements before building automated work
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | browserbase_project_id | Browserbase project ID (required if using Browserbase) | str | Yes |
-| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-3-7-sonnet-20250219" | No |
+| model | LLM to use for Stagehand (provider is inferred) | "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "claude-sonnet-4-5-20250929" | No |
 | url | URL to navigate to. | str | Yes |
 | instruction | Natural language description of elements or actions to discover. | str | Yes |
 | iframes | Whether to search within iframes. If True, Stagehand will search for actions within iframes. | bool | No |
diff --git a/docs/integrations/block-integrations/text.md b/docs/integrations/block-integrations/text.md
index e47375196c..d189aa5c3f 100644
--- a/docs/integrations/block-integrations/text.md
+++ b/docs/integrations/block-integrations/text.md
@@ -380,6 +380,42 @@ This is useful when working with data from APIs or files where escape sequences
 
 ---
 
+## Text Encoder
+
+### What it is
+Encodes a string by converting special characters into escape sequences
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The Text Encoder takes the input string and applies Python's `unicode_escape` encoding (equivalent to `codecs.encode(text, "unicode_escape").decode("utf-8")`) to transform special characters like newlines, tabs, and backslashes into their escaped forms.
+
+The block relies on the input schema to ensure the value is a string; non-string inputs are rejected by validation, and any encoding failures surface as block errors. Non-ASCII characters are emitted as `\uXXXX` sequences, which is useful for ASCII-only payloads.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| text | A string containing special characters to be encoded | str | Yes |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if encoding fails | str |
+| encoded_text | The encoded text with special characters converted to escape sequences | str |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+**JSON Payload Preparation**: Encode multiline or quoted text before embedding it in JSON string fields to ensure proper escaping.
+
+**Config/ENV Generation**: Convert template text into escaped strings for `.env` or YAML values that require special character handling.
+
+**Snapshot Fixtures**: Produce stable escaped strings for golden files or API tests where consistent text representation is needed.
+<!-- END MANUAL -->
+
+---
+
 ## Text Replace
 
 ### What it is
diff --git a/docs/integrations/block-integrations/video/add_audio.md b/docs/integrations/block-integrations/video/add_audio.md
new file mode 100644
index 0000000000..615dd747ef
--- /dev/null
+++ b/docs/integrations/block-integrations/video/add_audio.md
@@ -0,0 +1,39 @@
+# Video Add Audio
+<!-- MANUAL: file_description -->
+This block allows you to attach a separate audio track to a video file, replacing or combining with the original audio.
+<!-- END MANUAL -->
+
+## Add Audio To Video
+
+### What it is
+Block to attach an audio file to a video file using moviepy.
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses MoviePy to combine video and audio files. It loads the video and audio inputs (which can be URLs, data URIs, or local paths), optionally scales the audio volume, then writes the combined result to a new video file using H.264 video codec and AAC audio codec.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| video_in | Video input (URL, data URI, or local path). | str (file) | Yes |
+| audio_in | Audio input (URL, data URI, or local path). | str (file) | Yes |
+| volume | Volume scale for the newly attached audio track (1.0 = original). | float | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| video_out | Final video (with attached audio), as a path or data URI. | str (file) |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Adding background music to a silent screen recording
+- Replacing original audio with a voiceover or translated audio track
+- Combining AI-generated speech with stock footage
+- Adding sound effects to video content
+<!-- END MANUAL -->
+
+---
diff --git a/docs/integrations/block-integrations/video/clip.md b/docs/integrations/block-integrations/video/clip.md
new file mode 100644
index 0000000000..659ec9d9e6
--- /dev/null
+++ b/docs/integrations/block-integrations/video/clip.md
@@ -0,0 +1,41 @@
+# Video Clip
+<!-- MANUAL: file_description -->
+This block extracts a specific time segment from a video file, allowing you to trim videos to precise start and end times.
+<!-- END MANUAL -->
+
+## Video Clip
+
+### What it is
+Extract a time segment from a video
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses MoviePy's `subclipped` function to extract a portion of the video between specified start and end times. It validates that end time is greater than start time, then creates a new video file containing only the selected segment. The output is encoded with H.264 video codec and AAC audio codec, preserving both video and audio from the original clip.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| video_in | Input video (URL, data URI, or local path) | str (file) | Yes |
+| start_time | Start time in seconds | float | Yes |
+| end_time | End time in seconds | float | Yes |
+| output_format | Output format | "mp4" \| "webm" \| "mkv" \| "mov" | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| video_out | Clipped video file (path or data URI) | str (file) |
+| duration | Clip duration in seconds | float |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Extracting highlights from a longer video
+- Trimming intro/outro from recorded content
+- Creating short clips for social media from longer videos
+- Isolating specific segments for further processing in a workflow
+<!-- END MANUAL -->
+
+---
diff --git a/docs/integrations/block-integrations/video/concat.md b/docs/integrations/block-integrations/video/concat.md
new file mode 100644
index 0000000000..2a9efd3e2e
--- /dev/null
+++ b/docs/integrations/block-integrations/video/concat.md
@@ -0,0 +1,41 @@
+# Video Concat
+<!-- MANUAL: file_description -->
+This block merges multiple video clips into a single continuous video, with optional transitions between clips.
+<!-- END MANUAL -->
+
+## Video Concat
+
+### What it is
+Merge multiple video clips into one continuous video
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses MoviePy's `concatenate_videoclips` function to join multiple videos in sequence. It supports three transition modes: **none** (direct concatenation), **crossfade** (smooth blending where clips overlap), and **fade_black** (each clip fades out to black and the next fades in). At least 2 videos are required. The output is encoded with H.264 video codec and AAC audio codec.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| videos | List of video files to concatenate (in order) | List[str (file)] | Yes |
+| transition | Transition between clips | "none" \| "crossfade" \| "fade_black" | No |
+| transition_duration | Transition duration in seconds | int | No |
+| output_format | Output format | "mp4" \| "webm" \| "mkv" \| "mov" | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| video_out | Concatenated video file (path or data URI) | str (file) |
+| total_duration | Total duration in seconds | float |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Combining multiple clips into a compilation video
+- Assembling intro, main content, and outro segments
+- Creating montages from multiple source videos
+- Building video playlists or slideshows with transitions
+<!-- END MANUAL -->
+
+---
diff --git a/docs/integrations/block-integrations/video/download.md b/docs/integrations/block-integrations/video/download.md
new file mode 100644
index 0000000000..36c62e765a
--- /dev/null
+++ b/docs/integrations/block-integrations/video/download.md
@@ -0,0 +1,42 @@
+# Video Download
+<!-- MANUAL: file_description -->
+This block downloads videos from URLs, supporting a wide range of video platforms and direct links.
+<!-- END MANUAL -->
+
+## Video Download
+
+### What it is
+Download video from URL (YouTube, Vimeo, news sites, direct links)
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses yt-dlp, a powerful video downloading library that supports over 1000 websites. It accepts a URL, quality preference, and output format, then downloads the video while merging the best available video and audio streams for the selected quality. Quality options: **best** (highest available), **1080p/720p/480p** (maximum resolution at that height), **audio_only** (extracts just the audio track).
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| url | URL of the video to download (YouTube, Vimeo, direct link, etc.) | str | Yes |
+| quality | Video quality preference | "best" \| "1080p" \| "720p" \| "480p" \| "audio_only" | No |
+| output_format | Output video format | "mp4" \| "webm" \| "mkv" | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| video_file | Downloaded video (path or data URI) | str (file) |
+| duration | Video duration in seconds | float |
+| title | Video title from source | str |
+| source_url | Original source URL | str |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Downloading source videos for editing or remixing
+- Archiving video content for offline processing
+- Extracting audio from videos for transcription or podcast creation
+- Gathering video content for automated content pipelines
+<!-- END MANUAL -->
+
+---
diff --git a/docs/integrations/block-integrations/video/duration.md b/docs/integrations/block-integrations/video/duration.md
new file mode 100644
index 0000000000..31d70130b6
--- /dev/null
+++ b/docs/integrations/block-integrations/video/duration.md
@@ -0,0 +1,38 @@
+# Video Duration
+<!-- MANUAL: file_description -->
+This block retrieves the duration of video or audio files, useful for planning and conditional logic in media workflows.
+<!-- END MANUAL -->
+
+## Media Duration
+
+### What it is
+Block to get the duration of a media file.
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses MoviePy to load the media file and extract its duration property. It supports both video files (using VideoFileClip) and audio files (using AudioFileClip), determined by the `is_video` flag. The media can be provided as a URL, data URI, or local file path. The duration is returned in seconds as a floating-point number.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| media_in | Media input (URL, data URI, or local path). | str (file) | Yes |
+| is_video | Whether the media is a video (True) or audio (False). | bool | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| duration | Duration of the media file (in seconds). | float |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Checking video length before processing to avoid timeout issues
+- Calculating how many times to loop a video to reach a target duration
+- Validating that uploaded content meets length requirements
+- Building conditional workflows based on media duration
+<!-- END MANUAL -->
+
+---
diff --git a/docs/integrations/block-integrations/video/loop.md b/docs/integrations/block-integrations/video/loop.md
new file mode 100644
index 0000000000..ea90422e2e
--- /dev/null
+++ b/docs/integrations/block-integrations/video/loop.md
@@ -0,0 +1,39 @@
+# Video Loop
+<!-- MANUAL: file_description -->
+This block repeats a video to extend its duration, either to a specific length or a set number of repetitions.
+<!-- END MANUAL -->
+
+## Loop Video
+
+### What it is
+Block to loop a video to a given duration or number of repeats.
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses MoviePy's Loop effect to repeat a video clip. You can specify either a target duration (the video will repeat until reaching that length) or a number of loops (the video will repeat that many times). The Loop effect handles both video and audio looping automatically, maintaining sync. Either `duration` or `n_loops` must be provided. The output is encoded with H.264 video codec and AAC audio codec.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| video_in | The input video (can be a URL, data URI, or local path). | str (file) | Yes |
+| duration | Target duration (in seconds) to loop the video to. Either duration or n_loops must be provided. | float | No |
+| n_loops | Number of times to repeat the video. Either n_loops or duration must be provided. | int | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| video_out | Looped video returned either as a relative path or a data URI. | str (file) |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Extending a short background video to match the length of narration audio
+- Creating seamless looping content for digital signage
+- Repeating a product demo video multiple times for emphasis
+- Extending short clips to meet minimum duration requirements for platforms
+<!-- END MANUAL -->
+
+---
diff --git a/docs/integrations/block-integrations/video/narration.md b/docs/integrations/block-integrations/video/narration.md
new file mode 100644
index 0000000000..48c551e016
--- /dev/null
+++ b/docs/integrations/block-integrations/video/narration.md
@@ -0,0 +1,44 @@
+# Video Narration
+<!-- MANUAL: file_description -->
+This block generates AI voiceover narration using ElevenLabs and adds it to a video, with flexible audio mixing options.
+<!-- END MANUAL -->
+
+## Video Narration
+
+### What it is
+Generate AI narration and add to video
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses ElevenLabs text-to-speech API to generate natural-sounding narration from your script. It then combines the narration with the video using MoviePy. Three audio mixing modes are available: **replace** (completely replaces original audio), **mix** (blends narration with original audio at configurable volumes), and **ducking** (similar to mix but applies stronger attenuation to original audio, making narration more prominent). The block outputs both the final video and the generated audio file separately.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| video_in | Input video (URL, data URI, or local path) | str (file) | Yes |
+| script | Narration script text | str | Yes |
+| voice_id | ElevenLabs voice ID | str | No |
+| model_id | ElevenLabs TTS model | "eleven_multilingual_v2" \| "eleven_flash_v2_5" \| "eleven_turbo_v2_5" \| "eleven_turbo_v2" | No |
+| mix_mode | How to combine with original audio. 'ducking' applies stronger attenuation than 'mix'. | "replace" \| "mix" \| "ducking" | No |
+| narration_volume | Narration volume (0.0 to 2.0) | float | No |
+| original_volume | Original audio volume when mixing (0.0 to 1.0) | float | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| video_out | Video with narration (path or data URI) | str (file) |
+| audio_file | Generated audio file (path or data URI) | str (file) |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Adding professional voiceover to product demos or tutorials
+- Creating narrated explainer videos from screen recordings
+- Generating multi-language versions of video content
+- Adding commentary to gameplay or walkthrough videos
+<!-- END MANUAL -->
+
+---
diff --git a/docs/integrations/block-integrations/video/text_overlay.md b/docs/integrations/block-integrations/video/text_overlay.md
new file mode 100644
index 0000000000..d684abd609
--- /dev/null
+++ b/docs/integrations/block-integrations/video/text_overlay.md
@@ -0,0 +1,44 @@
+# Video Text Overlay
+<!-- MANUAL: file_description -->
+This block adds customizable text captions or titles to videos, with control over positioning, timing, and styling.
+<!-- END MANUAL -->
+
+## Video Text Overlay
+
+### What it is
+Add text overlay/caption to video
+
+### How it works
+<!-- MANUAL: how_it_works -->
+The block uses MoviePy's TextClip and CompositeVideoClip to render text onto video frames. The text is created as a separate clip with configurable font size, color, and optional background color, then composited over the video at the specified position. Timing can be controlled to show text only during specific portions of the video. Position options include center alignments (top, center, bottom) and corner positions (top-left, top-right, bottom-left, bottom-right). The output is encoded with H.264 video codec and AAC audio codec.
+<!-- END MANUAL -->
+
+### Inputs
+
+| Input | Description | Type | Required |
+|-------|-------------|------|----------|
+| video_in | Input video (URL, data URI, or local path) | str (file) | Yes |
+| text | Text to overlay on video | str | Yes |
+| position | Position of text on screen | "top" \| "center" \| "bottom" \| "top-left" \| "top-right" \| "bottom-left" \| "bottom-right" | No |
+| start_time | When to show text (seconds). None = entire video | float | No |
+| end_time | When to hide text (seconds). None = until end | float | No |
+| font_size | Font size | int | No |
+| font_color | Font color (hex or name) | str | No |
+| bg_color | Background color behind text (None for transparent) | str | No |
+
+### Outputs
+
+| Output | Description | Type |
+|--------|-------------|------|
+| error | Error message if the operation failed | str |
+| video_out | Video with text overlay (path or data URI) | str (file) |
+
+### Possible use case
+<!-- MANUAL: use_case -->
+- Adding titles or chapter headings to video content
+- Creating lower-thirds with speaker names or captions
+- Watermarking videos with branding text
+- Adding call-to-action text at specific moments in a video
+<!-- END MANUAL -->
+
+---
diff --git a/docs/platform/create-basic-agent.md b/docs/platform/create-basic-agent.md
index 7721fb9b9c..ffe654ba99 100644
--- a/docs/platform/create-basic-agent.md
+++ b/docs/platform/create-basic-agent.md
@@ -4,6 +4,28 @@
 
 This guide walks through creating a simple question-answer AI agent using AutoGPT's visual builder. This is a basic example that can be expanded into more complex agents.
 
+## **Prerequisites**
+
+### **Cloud-Hosted AutoGPT**
+If you're using the cloud-hosted version at [agpt.co](https://agpt.co), you're ready to go! AI blocks come with **built-in credits** — no API keys required to get started. If you'd prefer to use your own API keys, you can add them via **Profile → Integrations**.
+
+### **Self-Hosted (Docker)**
+If you're running AutoGPT locally with Docker, you'll need to add your own API keys to `autogpt_platform/backend/.env`:
+
+```bash
+# Create or edit backend/.env
+OPENAI_API_KEY=sk-your-key-here
+ANTHROPIC_API_KEY=sk-ant-your-key-here
+# Add other provider keys as needed
+```
+
+After adding keys, restart the services:
+```bash
+docker compose down && docker compose up -d
+```
+
+**Note:** The Calculator example below doesn't require any API credentials — it's a good way to test your setup before adding AI blocks.
+
 ## **Example Agent: Q&A (with AI)**
 
 A step-by-step guide to creating a simple Q&A agent using input and output blocks.