fix(ci): allow dependabot[bot] in Claude dependabot review workflow

The Claude Code Action rejects bot actors by default. Adding dependabot[bot]
to allowed_bots so the automated dependency review can run on Dependabot PRs.

.github/workflows/classic-frontend-ci.yml

@@ -49,7 +49,7 @@ jobs:
 
       - name: Create PR ${{ env.BUILD_BRANCH }} -> ${{ github.ref_name }}
         if: github.event_name == 'push'
-        uses: peter-evans/create-pull-request@v8
+        uses: peter-evans/create-pull-request@v7
         with:
           add-paths: classic/frontend/build/web
           base: ${{ github.ref_name }}

.github/workflows/claude-ci-failure-auto-fix.yml

@@ -22,7 +22,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         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@v8
+        uses: actions/github-script@v7
         with:
           script: |
             const run = await github.rest.actions.getWorkflowRun({

.github/workflows/claude-dependabot.yml

@@ -30,7 +30,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         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@v5
+        uses: actions/cache@v4
         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@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22"
 
@@ -91,7 +91,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         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@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/claude.yml

@@ -40,7 +40,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         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@v5
+        uses: actions/cache@v4
         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@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22"
 
@@ -107,7 +107,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         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@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.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@v6
+      uses: actions/checkout@v4
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL

.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@v6
+        uses: actions/checkout@v4
         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@v5
+        uses: actions/cache@v4
         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@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22"
 
@@ -89,7 +89,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         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@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/docs-block-sync.yml

@@ -23,7 +23,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         with:
           fetch-depth: 1
 
@@ -33,7 +33,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/docs-claude-review.yml

@@ -23,7 +23,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         with:
           fetch-depth: 0
 
@@ -33,7 +33,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/docs-enhance.yml

@@ -28,7 +28,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         with:
           fetch-depth: 1
 
@@ -38,7 +38,7 @@ jobs:
           python-version: "3.11"
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/platform-autogpt-deploy-dev.yaml

@@ -25,7 +25,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         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@v4
+        uses: peter-evans/repository-dispatch@v3
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

.github/workflows/platform-autogpt-deploy-prod.yml

@@ -17,7 +17,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         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@v4
+        uses: peter-evans/repository-dispatch@v3
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

.github/workflows/platform-backend-ci.yml

@@ -68,7 +68,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         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@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.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@v8
+        uses: actions/github-script@v7
         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@v8
+        uses: actions/github-script@v7
         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@v8
+        uses: actions/github-script@v7
         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@v4
+        uses: peter-evans/repository-dispatch@v3
         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@v8
+        uses: actions/github-script@v7
         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@v4
+        uses: peter-evans/repository-dispatch@v3
         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@v8
+        uses: actions/github-script@v7
         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@v8
+        uses: actions/github-script@v7
         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@v4
+        uses: peter-evans/repository-dispatch@v3
         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@v8
+        uses: actions/github-script@v7
         with:
           script: |
             await github.rest.issues.createComment({

.github/workflows/platform-frontend-ci.yml

@@ -31,7 +31,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
 
       - name: Check for component changes
         uses: dorny/paths-filter@v3
@@ -42,7 +42,7 @@ jobs:
               - 'autogpt_platform/frontend/src/components/**'
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -54,7 +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@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -71,10 +71,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -82,7 +82,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -107,12 +107,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         with:
           fetch-depth: 0
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -120,7 +120,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -148,12 +148,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -176,7 +176,7 @@ jobs:
         uses: docker/setup-buildx-action@v3
 
       - name: Cache Docker layers
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         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') }}
@@ -231,7 +231,7 @@ jobs:
           fi
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -277,12 +277,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -290,7 +290,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

.github/workflows/platform-fullstack-ci.yml

@@ -29,10 +29,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         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@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -56,19 +56,19 @@ jobs:
         run: pnpm install --frozen-lockfile
 
   types:
-    runs-on: big-boi
+    runs-on: ubuntu-latest
     needs: setup
     strategy:
       fail-fast: false
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v6
+        uses: actions/checkout@v4
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -85,10 +85,10 @@ jobs:
 
       - name: Run docker compose
         run: |
-          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
+          docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

.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@v6
+      - uses: actions/checkout@v4
         # with:
           # fetch-depth: 0
       - name: Set up Python

autogpt_platform/autogpt_libs/poetry.lock

@@ -99,101 +99,84 @@ files = [
 
 [[package]]
 name = "cffi"
-version = "2.0.0"
+version = "1.17.1"
 description = "Foreign Function Interface for Python calling C code."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["main"]
 markers = "platform_python_implementation != \"PyPy\""
 files = [
-    {file = "cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44"},
+    {file = "cffi-1.17.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df8b1c11f177bc2313ec4b2d46baec87a5f3e71fc8b45dab2ee7cae86d9aba14"},
-    {file = "cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49"},
+    {file = "cffi-1.17.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f2cdc858323644ab277e9bb925ad72ae0e67f69e804f4898c070998d50b1a67"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:53f77cbe57044e88bbd5ed26ac1d0514d2acf0591dd6bb02a3ae37f76811b80c"},
+    {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-2.0.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:3e837e369566884707ddaf85fc1744b47575005c0a229de3327f8f9a20f4efeb"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45398b671ac6d70e67da8e4224a065cec6a93541bb7aebe1b198a61b58c7b702"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:5eda85d6d1879e692d546a078b44251cdd08dd1cfb98dfb77b670c97cee49ea0"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ad9413ccdeda48c5afdae7e4fa2192157e991ff761e7ab8fdd8926f40b160cc3"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9332088d75dc3241c702d852d4671613136d90fa6881da7d770a483fd05248b4"},
+    {file = "cffi-1.17.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5da5719280082ac6bd9aa7becb3938dc9f9cbd57fac7d2871717b1feb0902ab6"},
-    {file = "cffi-2.0.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fc7de24befaeae77ba923797c7c87834c73648a05a4bde34b3b7e5588973a453"},
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 [package.dependencies]
@@ -448,75 +413,62 @@ toml = ["tomli ; python_full_version <= \"3.11.0a6\""]
 
 [[package]]
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 optional = false
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 [package.dependencies]
-cffi = {version = ">=2.0.0", markers = "python_full_version >= \"3.9.0\" and platform_python_implementation != \"PyPy\""}
+cffi = {version = ">=1.14", markers = "platform_python_implementation != \"PyPy\""}
-typing-extensions = {version = ">=4.13.2", markers = "python_full_version < \"3.11.0\""}
 
 [package.extras]
-docs = ["sphinx (>=5.3.0)", "sphinx-inline-tabs", "sphinx-rtd-theme (>=3.0.0)"]
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 docstest = ["pyenchant (>=3)", "readme-renderer (>=30.0)", "sphinxcontrib-spelling (>=7.3.1)"]
-nox = ["nox[uv] (>=2024.4.15)"]
+nox = ["nox (>=2024.4.15)", "nox[uv] (>=2024.3.2) ; python_full_version >= \"3.8.0\""]
-pep8test = ["check-sdist", "click (>=8.0.1)", "mypy (>=1.14)", "ruff (>=0.11.11)"]
+pep8test = ["check-sdist ; python_full_version >= \"3.8.0\"", "click (>=8.0.1)", "mypy (>=1.4)", "ruff (>=0.3.6)"]
 sdist = ["build (>=1.0.0)"]
 ssh = ["bcrypt (>=3.1.5)"]
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+test = ["certifi (>=2024)", "cryptography-vectors (==45.0.6)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -1698,7 +1650,7 @@ description = "C parser in Python"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "platform_python_implementation != \"PyPy\" and implementation_name != \"PyPy\""
+markers = "platform_python_implementation != \"PyPy\""
 files = [
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@@ -2020,14 +1972,14 @@ files = [
 
 [[package]]
 name = "pyright"
-version = "1.1.408"
+version = "1.1.404"
 description = "Command line wrapper for pyright"
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
@@ -2159,20 +2111,19 @@ dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "requests
 
 [[package]]
 name = "pytest-asyncio"
-version = "1.3.0"
+version = "1.1.0"
 description = "Pytest support for asyncio"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
 backports-asyncio-runner = {version = ">=1.1,<2", markers = "python_version < \"3.11\""}
-pytest = ">=8.2,<10"
+pytest = ">=8.2,<9"
-typing-extensions = {version = ">=4.12", markers = "python_version < \"3.13\""}
 
 [package.extras]
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1)"]
@@ -2180,34 +2131,34 @@ testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
 [[package]]
 name = "pytest-cov"
-version = "7.0.0"
+version = "6.2.1"
 description = "Pytest plugin for measuring coverage."
 optional = false
 python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
-coverage = {version = ">=7.10.6", extras = ["toml"]}
+coverage = {version = ">=7.5", extras = ["toml"]}
 pluggy = ">=1.2"
-pytest = ">=7"
+pytest = ">=6.2.5"
 
 [package.extras]
-testing = ["process-tests", "pytest-xdist", "virtualenv"]
+testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"]
 
 [[package]]
 name = "pytest-mock"
-version = "3.15.1"
+version = "3.14.1"
 description = "Thin-wrapper around the mock package for easier use with pytest"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["dev"]
 files = [
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+    {file = "pytest_mock-3.14.1.tar.gz", hash = "sha256:159e9edac4c451ce77a5cdb9fc5d1100708d2dd4ba3c3df572f14097351af80e"},
 ]
 
 [package.dependencies]
@@ -2341,30 +2292,31 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.15.0"
+version = "0.12.11"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
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 ]
 
 [[package]]
@@ -2911,4 +2863,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<4.0"
-content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d"
+content-hash = "5f15a9c9381c9a374f3d18e087c23b1f1ba8cce192d6f67463a3e3a7a18fee44"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -9,7 +9,7 @@ packages = [{ include = "autogpt_libs" }]
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 colorama = "^0.4.6"
-cryptography = "^46.0"
+cryptography = "^45.0"
 expiringdict = "^1.2.2"
 fastapi = "^0.128.0"
 google-cloud-logging = "^3.13.0"
@@ -22,12 +22,12 @@ supabase = "^2.27.2"
 uvicorn = "^0.40.0"
 
 [tool.poetry.group.dev.dependencies]
-pyright = "^1.1.408"
+pyright = "^1.1.404"
 pytest = "^8.4.1"
-pytest-asyncio = "^1.3.0"
+pytest-asyncio = "^1.1.0"
-pytest-mock = "^3.15.1"
+pytest-mock = "^3.14.1"
-pytest-cov = "^7.0.0"
+pytest-cov = "^6.2.1"
-ruff = "^0.15.0"
+ruff = "^0.12.11"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/backend/api/features/chat/config.py

@@ -93,12 +93,6 @@ 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):

autogpt_platform/backend/backend/api/features/chat/db.py

@@ -45,7 +45,10 @@ async def create_chat_session(
         successfulAgentRuns=SafeJson({}),
         successfulAgentSchedules=SafeJson({}),
     )
-    return await PrismaChatSession.prisma().create(data=data)
+    return await PrismaChatSession.prisma().create(
+        data=data,
+        include={"Messages": True},
+    )
 
 
 async def update_chat_session(

autogpt_platform/backend/backend/api/features/chat/response_model.py

@@ -18,10 +18,6 @@ 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"
@@ -61,16 +57,6 @@ class StreamStart(StreamBaseResponse):
         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):
     """End of message/stream."""
@@ -78,26 +64,6 @@ 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 ==========
 
 
@@ -151,7 +117,7 @@ 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")
-    # Keep these for internal backend use
+    # Additional fields for internal use (not part of AI SDK spec but useful)
     toolName: str | None = Field(
         default=None, description="Name of the tool that was executed"
     )
@@ -159,17 +125,6 @@ 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 ==========
 

autogpt_platform/backend/backend/api/features/chat/routes.py

@@ -6,7 +6,7 @@ from collections.abc import AsyncGenerator
 from typing import Annotated
 
 from autogpt_libs import auth
-from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
+from fastapi import APIRouter, Depends, Header, HTTPException, Query, Security
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
@@ -17,29 +17,7 @@ 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 .response_model import StreamFinish, StreamHeartbeat, StreamStart
-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()
 
@@ -288,36 +266,12 @@ async def stream_chat_post(
 
     """
     import asyncio
-    import time
-
-    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,
@@ -326,28 +280,14 @@ async def stream_chat_post(
         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(
-            f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
-            extra={"json_fields": log_meta},
-        )
-        first_chunk_time, ttfc = None, None
-        chunk_count = 0
         try:
+            # Emit a start event with task_id for reconnection
+            start_chunk = StreamStart(messageId=task_id, taskId=task_id)
+            await stream_registry.publish_chunk(task_id, start_chunk)
+
             async for chunk in chat_service.stream_chat_completion(
                 session_id,
                 request.message,
@@ -355,79 +295,25 @@ async def stream_chat_post(
                 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()
+            # Mark task as completed
-            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}",
+                f"Error in background AI generation for session {session_id}: {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(
@@ -442,70 +328,22 @@ async def stream_chat_post(
                 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:
+                    # Send heartbeat to keep connection alive
                     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"Error in SSE stream for task {task_id}: {e}")
-            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:
@@ -519,18 +357,6 @@ async def stream_chat_post(
                         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(
@@ -548,90 +374,63 @@ async def stream_chat_post(
 @router.get(
     "/sessions/{session_id}/stream",
 )
-async def resume_session_stream(
+async def stream_chat_get(
     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),
 ):
     """
-    Resume an active stream for a session.
+    Stream chat responses for a session (GET - legacy endpoint).
 
-    Called by the AI SDK's ``useChat(resume: true)`` on page load.
+    Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
-    Checks for an active (in-progress) task on the session and either replays
+      - Text fragments as they are generated
-    the full SSE stream or returns 204 No Content if nothing is running.
+      - Tool call UI elements (if invoked)
+      - Tool execution results
 
     Args:
-        session_id: The chat session identifier.
+        session_id: The chat session identifier to associate with the streamed messages.
+        message: The user's new message to process.
         user_id: Optional authenticated user ID.
-
+        is_user_message: Whether the message is a user message.
     Returns:
-        StreamingResponse (SSE) when an active stream exists,
+        StreamingResponse: SSE-formatted response chunks.
-        or 204 No Content when there is nothing to resume.
+
     """
-    import asyncio
+    session = await _validate_and_get_session(session_id, user_id)
-
-    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
-        try:
+        async for chunk in chat_service.stream_chat_completion(
-            while True:
+            session_id,
-                try:
+            message,
-                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+            is_user_message=is_user_message,
-                    if chunk_count < 3:
+            user_id=user_id,
-                        logger.info(
+            session=session,  # Pass pre-fetched session to avoid double-fetch
-                            "Resume stream chunk",
+        ):
-                            extra={
+            if chunk_count < 3:
-                                "session_id": session_id,
+                logger.info(
-                                "chunk_type": str(chunk.type),
+                    "Chat stream chunk",
-                            },
+                    extra={
-                        )
+                        "session_id": session_id,
-                    if not first_chunk_type:
+                        "chunk_type": str(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
                 )
-            except Exception as unsub_err:
+            if not first_chunk_type:
-                logger.error(
+                first_chunk_type = str(chunk.type)
-                    f"Error unsubscribing from task {active_task.task_id}: {unsub_err}",
+            chunk_count += 1
-                    exc_info=True,
+            yield chunk.to_sse()
-                )
+        logger.info(
-            logger.info(
+            "Chat stream completed",
-                "Resume stream completed",
+            extra={
-                extra={
+                "session_id": session_id,
-                    "session_id": session_id,
+                "chunk_count": chunk_count,
-                    "n_chunks": chunk_count,
+                "first_chunk_type": first_chunk_type,
-                    "first_chunk_type": first_chunk_type,
+            },
-                },
+        )
-            )
+        # AI SDK protocol termination
-            yield "data: [DONE]\n\n"
+        yield "data: [DONE]\n\n"
 
     return StreamingResponse(
         event_generator(),
@@ -639,8 +438,8 @@ async def resume_session_stream(
         headers={
             "Cache-Control": "no-cache",
             "Connection": "keep-alive",
-            "X-Accel-Buffering": "no",
+            "X-Accel-Buffering": "no",  # Disable nginx buffering
-            "x-vercel-ai-ui-message-stream": "v1",
+            "x-vercel-ai-ui-message-stream": "v1",  # AI SDK protocol header
         },
     )
 
@@ -952,42 +751,3 @@ 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")

autogpt_platform/backend/backend/api/features/chat/service.py

@@ -52,10 +52,8 @@ from .response_model import (
     StreamBaseResponse,
     StreamError,
     StreamFinish,
-    StreamFinishStep,
     StreamHeartbeat,
     StreamStart,
-    StreamStartStep,
     StreamTextDelta,
     StreamTextEnd,
     StreamTextStart,
@@ -353,10 +351,6 @@ 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.
 
@@ -377,45 +371,21 @@ 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"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
+        f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
-        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"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
+            f"Fetched session from Redis: {session.session_id if session else 'None'}, "
-            f"n_messages={len(session.messages) if session else 0}",
+            f"message_count={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"[TIMING] Using provided session, messages={len(session.messages)}",
+            f"Using provided session object: {session.session_id}, "
-            extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
+            f"message_count={len(session.messages)}"
         )
 
     if not session:
@@ -436,25 +406,17 @@ 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}},
-            )
 
-    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",
+        f"Upserting session: {session.session_id} with user id {session.user_id}, "
-        extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
+        f"message_count={len(session.messages)}"
     )
+    session = await upsert_chat_session(session)
     assert session, "Session not found"
 
     # Generate title for new sessions on first user message (non-blocking)
@@ -492,13 +454,7 @@ 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(
@@ -523,27 +479,13 @@ async def stream_chat_completion(
     # Generate unique IDs for AI SDK protocol
     import uuid as uuid_module
 
-    is_continuation = _continuation_message_id is not None
+    message_id = str(uuid_module.uuid4())
-    message_id = _continuation_message_id or str(uuid_module.uuid4())
     text_block_id = str(uuid_module.uuid4())
 
-    # Only yield message start for the initial call, not for continuations.
+    # Yield message start
-    setup_time = (time.monotonic() - completion_start) * 1000
+    yield StreamStart(messageId=message_id)
-    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,
@@ -643,10 +585,6 @@ 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:
@@ -678,8 +616,6 @@ 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
@@ -729,10 +665,6 @@ 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
@@ -768,7 +700,6 @@ async def stream_chat_completion(
                 error_response = StreamError(errorText=error_message)
                 yield error_response
             if not has_yielded_end:
-                yield StreamFinishStep()
                 yield StreamFinish()
             return
 
@@ -783,8 +714,6 @@ 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
@@ -854,8 +783,6 @@ 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
 
@@ -966,21 +893,9 @@ 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
 
-    # Build log metadata for structured logging
+    logger.info("Starting pure chat stream")
-    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)}},
-    )
 
     messages = session.to_openai_messages()
     if system_prompt:
@@ -991,18 +906,12 @@ async def _stream_chat_chunks(
         messages = [system_message] + messages
 
     # Apply context window management
-    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}},
-    )
 
     if context_result.error:
         if "System prompt dropped" in context_result.error:
@@ -1037,19 +946,9 @@ 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"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
+                    f"Creating OpenAI chat completion stream..."
-                    extra={
+                    f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
-                        "json_fields": {
-                            **log_meta,
-                            "elapsed_ms": elapsed,
-                            "retry_count": retry_count,
-                        }
-                    },
                 )
 
                 # Build extra_body for OpenRouter tracing and PostHog analytics
@@ -1066,11 +965,6 @@ async def _stream_chat_chunks(
                         :128
                     ]  # OpenRouter limit
 
-                # 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),
@@ -1080,11 +974,6 @@ 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]] = []
@@ -1095,13 +984,10 @@ 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,
@@ -1124,23 +1010,6 @@ 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 "",
@@ -1197,21 +1066,7 @@ async def _stream_chat_chunks(
                                         toolName=tool_calls[idx]["function"]["name"],
                                     )
                                     emitted_start_for_idx.add(idx)
-                stream_duration = time_module.perf_counter() - api_call_start
+                logger.info(f"Stream complete. Finish reason: {finish_reason}")
-                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
@@ -1231,12 +1086,6 @@ 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:
@@ -1716,7 +1565,6 @@ async def _execute_long_running_tool_with_streaming(
             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(
@@ -1833,10 +1681,6 @@ async def _generate_llm_continuation(
         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}
-
         retry_count = 0
         last_error: Exception | None = None
         response = None
@@ -1967,10 +1811,6 @@ async def _generate_llm_continuation_with_streaming(
         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
 
@@ -1982,7 +1822,6 @@ async def _generate_llm_continuation_with_streaming(
 
         # 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
@@ -2006,7 +1845,6 @@ async def _generate_llm_continuation_with_streaming(
 
         # 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
@@ -2048,5 +1886,4 @@ async def _generate_llm_continuation_with_streaming(
             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())

autogpt_platform/backend/backend/api/features/chat/stream_registry.py

@@ -104,24 +104,6 @@ async def create_task(
     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,
@@ -132,18 +114,10 @@ async def create_task(
     )
 
     # 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={
@@ -157,22 +131,12 @@ async def create_task(
             "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.debug(f"Created task {task_id} for session {session_id}")
-    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
 
@@ -192,60 +156,26 @@ async def publish_chunk(
     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}",
+            f"Failed to publish chunk for task {task_id}: {e}",
-            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
             exc_info=True,
         )
 
@@ -270,61 +200,24 @@ async def subscribe_to_task(
         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.debug(f"Task {task_id} not found in Redis")
-        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}",
+                f"User {user_id} denied access to task {task_id} "
-                extra={
+                f"owned by {task_user_id}"
-                    "json_fields": {
-                        **log_meta,
-                        "task_owner": task_user_id,
-                        "reason": "access_denied",
-                    }
-                },
             )
             return None
 
@@ -332,19 +225,7 @@ async def subscribe_to_task(
     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
@@ -363,48 +244,19 @@ async def subscribe_to_task(
                     except Exception as e:
                         logger.warning(f"Failed to replay message: {e}")
 
-    logger.info(
+    logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
-        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)
+            _stream_listener(task_id, subscriber_queue, replay_last_id)
         )
         # 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
 
 
@@ -412,7 +264,6 @@ 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.
 
@@ -423,27 +274,10 @@ async def _stream_listener(
         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()
@@ -453,39 +287,9 @@ async def _stream_listener(
         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
@@ -522,30 +326,10 @@ async def _stream_listener(
                                 )
                                 # 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",
+                                    f"Subscriber queue full for task {task_id}, "
-                                    extra={
+                                    f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
-                                        "json_fields": {
-                                            **log_meta,
-                                            "timeout_s": QUEUE_PUT_TIMEOUT,
-                                            "reason": "queue_full",
-                                        }
-                                    },
                                 )
                                 # Send overflow error with recovery info
                                 try:
@@ -567,44 +351,15 @@ async def _stream_listener(
 
                             # 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(
+                        logger.warning(f"Error processing stream message: {e}")
-                            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.debug(f"Stream listener cancelled for task {task_id}")
-        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"Stream listener error for task {task_id}: {e}")
-        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(
@@ -613,24 +368,10 @@ async def _stream_listener(
             )
         except (asyncio.TimeoutError, asyncio.QueueFull):
             logger.warning(
-                "Could not deliver finish event after error",
+                f"Could not deliver finish event for task {task_id} 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)
 
 
@@ -857,10 +598,8 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
         ResponseType,
         StreamError,
         StreamFinish,
-        StreamFinishStep,
         StreamHeartbeat,
         StreamStart,
-        StreamStartStep,
         StreamTextDelta,
         StreamTextEnd,
         StreamTextStart,
@@ -874,8 +613,6 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
     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,

autogpt_platform/backend/backend/api/features/chat/tools/find_block.py

@@ -13,32 +13,10 @@ 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 BlockType, get_block
+from backend.data.block import 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."""
@@ -110,7 +88,7 @@ class FindBlockTool(BaseTool):
                 query=query,
                 content_types=[ContentType.BLOCK],
                 page=1,
-                page_size=_OVERFETCH_PAGE_SIZE,
+                page_size=10,
             )
 
             if not results:
@@ -130,90 +108,60 @@ class FindBlockTool(BaseTool):
                 block = get_block(block_id)
 
                 # Skip disabled blocks
-                if not block or block.disabled:
+                if block and not block.disabled:
-                    continue
+                    # 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
 
-                # Skip blocks excluded from CoPilot (graph-only blocks)
+                    # Get categories from block instance
-                if (
+                    categories = []
-                    block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
+                    if hasattr(block, "categories") and block.categories:
-                    or block.id in COPILOT_EXCLUDED_BLOCK_IDS
+                        categories = [cat.value for cat in block.categories]
-                ):
-                    continue
 
-                # Get input/output schemas
+                    # Extract required inputs for easier use
-                input_schema = {}
+                    required_inputs: list[BlockInputFieldInfo] = []
-                output_schema = {}
+                    if input_schema:
-                try:
+                        properties = input_schema.get("properties", {})
-                    input_schema = block.input_schema.jsonschema()
+                        required_fields = set(input_schema.get("required", []))
-                except Exception as e:
+                        # Get credential field names to exclude from required inputs
-                    logger.debug(
+                        credentials_fields = set(
-                        "Failed to generate input schema for block %s: %s",
+                            block.input_schema.get_credentials_fields().keys()
-                        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(
+                        for field_name, field_schema in properties.items():
-                    BlockInfoSummary(
+                            # Skip credential fields - they're handled separately
-                        id=block_id,
+                            if field_name in credentials_fields:
-                        name=block.name,
+                                continue
-                        description=block.description or "",
+
-                        categories=categories,
+                            required_inputs.append(
-                        input_schema=input_schema,
+                                BlockInputFieldInfo(
-                        output_schema=output_schema,
+                                    name=field_name,
-                        required_inputs=required_inputs,
+                                    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(

autogpt_platform/backend/backend/api/features/chat/tools/find_block_test.py

@@ -1,139 +0,0 @@
-"""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"

autogpt_platform/backend/backend/api/features/chat/tools/helpers.py

@@ -1,29 +0,0 @@
-"""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
-    ]

autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py

@@ -24,7 +24,6 @@ from backend.util.timezone_utils import (
 )
 
 from .base import BaseTool
-from .helpers import get_inputs_from_schema
 from .models import (
     AgentDetails,
     AgentDetailsResponse,
@@ -262,7 +261,7 @@ class RunAgentTool(BaseTool):
                         ),
                         requirements={
                             "credentials": requirements_creds_list,
-                            "inputs": get_inputs_from_schema(graph.input_schema),
+                            "inputs": self._get_inputs_list(graph.input_schema),
                             "execution_modes": self._get_execution_modes(graph),
                         },
                     ),
@@ -370,6 +369,22 @@ 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
@@ -383,7 +398,7 @@ class RunAgentTool(BaseTool):
         suffix: str,
     ) -> str:
         """Build a message describing available inputs for an agent."""
-        inputs_list = get_inputs_from_schema(graph.input_schema)
+        inputs_list = self._get_inputs_list(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"]]
 

autogpt_platform/backend/backend/api/features/chat/tools/run_block.py

@@ -8,19 +8,14 @@ from typing import Any
 from pydantic_core import PydanticUndefined
 
 from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.find_block import (
+from backend.data.block import get_block
-    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 CredentialsFieldInfo, CredentialsMetaInput
+from backend.data.model import 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,
@@ -29,10 +24,7 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
-from .utils import (
+from .utils import build_missing_credentials_from_field_info
-    build_missing_credentials_from_field_info,
-    match_credentials_to_requirements,
-)
 
 logger = logging.getLogger(__name__)
 
@@ -81,6 +73,91 @@ class RunBlockTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
+    async def _check_block_credentials(
+        self,
+        user_id: str,
+        block: Any,
+        input_data: dict[str, Any] | None = None,
+    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
+        """
+        Check if user has required credentials for a block.
+
+        Args:
+            user_id: User ID
+            block: Block to check credentials for
+            input_data: Input data for the block (used to determine provider via discriminator)
+
+        Returns:
+            tuple[matched_credentials, missing_credentials]
+        """
+        matched_credentials: dict[str, CredentialsMetaInput] = {}
+        missing_credentials: list[CredentialsMetaInput] = []
+        input_data = input_data or {}
+
+        # 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():
+            effective_field_info = field_info
+            if field_info.discriminator and field_info.discriminator_mapping:
+                # Get discriminator from input, falling back to schema default
+                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)
+                    logger.debug(
+                        f"Discriminated provider for {field_name}: "
+                        f"{discriminator_value} -> {effective_field_info.provider}"
+                    )
+
+            matching_cred = next(
+                (
+                    cred
+                    for cred in available_creds
+                    if cred.provider in effective_field_info.provider
+                    and cred.type in effective_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(effective_field_info.provider), "unknown")
+                cred_type = next(iter(effective_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,
@@ -135,24 +212,11 @@ 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}")
 
         creds_manager = IntegrationCredentialsManager()
-        matched_credentials, missing_credentials = (
+        matched_credentials, missing_credentials = await self._check_block_credentials(
-            await self._resolve_block_credentials(user_id, block, input_data)
+            user_id, block, input_data
         )
 
         if missing_credentials:
@@ -281,75 +345,29 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
-    async def _resolve_block_credentials(
+    def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
-        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)
 
-    def _resolve_discriminated_credentials(
+        for field_name, field_schema in properties.items():
-        self,
+            # Skip credential fields
-        block: AnyBlockSchema,
+            if field_name in credentials_fields:
-        input_data: dict[str, Any],
+                continue
-    ) -> 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 {}
 
-        resolved: dict[str, CredentialsFieldInfo] = {}
+            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,
+                }
+            )
 
-        for field_name, field_info in credentials_fields_info.items():
+        return inputs_list
-            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

autogpt_platform/backend/backend/api/features/chat/tools/run_block_test.py

@@ -1,106 +0,0 @@
-"""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

autogpt_platform/backend/backend/api/features/chat/tools/utils.py

@@ -8,7 +8,6 @@ from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
 from backend.data.graph import GraphModel
 from backend.data.model import (
-    Credentials,
     CredentialsFieldInfo,
     CredentialsMetaInput,
     HostScopedCredentials,
@@ -224,99 +223,6 @@ 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,
@@ -425,6 +331,8 @@ def _credential_has_required_scopes(
     # If no scopes are required, any credential matches
     if not requirements.required_scopes:
         return True
+
+    # Check that credential scopes are a superset of required scopes
     return set(credential.scopes).issuperset(requirements.required_scopes)
 
 

autogpt_platform/backend/backend/api/features/store/hybrid_search.py

@@ -8,7 +8,6 @@ Includes BM25 reranking for improved lexical relevance.
 
 import logging
 import re
-import time
 from dataclasses import dataclass
 from typing import Any, Literal
 
@@ -363,11 +362,7 @@ async def unified_hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    try:
+    results = await query_raw_with_schema(sql_query, *params)
-        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
@@ -691,11 +686,7 @@ async def hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    try:
+    results = await query_raw_with_schema(sql_query, *params)
-        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
 
@@ -727,87 +718,6 @@ 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

autogpt_platform/backend/backend/blocks/llm.py

@@ -531,12 +531,12 @@ class LLMResponse(BaseModel):
 
 def convert_openai_tool_fmt_to_anthropic(
     openai_tools: list[dict] | None = None,
-) -> Iterable[ToolParam] | anthropic.Omit:
+) -> Iterable[ToolParam] | anthropic.NotGiven:
     """
     Convert OpenAI tool format to Anthropic tool format.
     """
     if not openai_tools or len(openai_tools) == 0:
-        return anthropic.omit
+        return anthropic.NOT_GIVEN
 
     anthropic_tools = []
     for tool in openai_tools:

autogpt_platform/backend/backend/data/execution_queue_test.py

@@ -3,6 +3,8 @@
 import queue
 import threading
 
+import pytest
+
 from backend.data.execution import ExecutionQueue
 
 

autogpt_platform/backend/backend/data/graph.py

@@ -743,11 +743,6 @@ class GraphModel(Graph, GraphMeta):
                 # 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 {}
             )

autogpt_platform/backend/backend/data/rabbitmq.py

@@ -1,4 +1,3 @@
-import asyncio
 import logging
 from abc import ABC, abstractmethod
 from enum import Enum
@@ -226,10 +225,6 @@ 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)
@@ -240,17 +235,7 @@ class AsyncRabbitMQ(RabbitMQBase):
 
     @conn_retry("AsyncRabbitMQ", "Acquiring async connection")
     async def connect(self):
-        if self.is_connected and self._channel and not self._channel.is_closed:
+        if self.is_connected:
-            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(
@@ -306,46 +291,24 @@ class AsyncRabbitMQ(RabbitMQBase):
                     exchange, routing_key=queue.routing_key or queue.name
                 )
 
-    @property
+    @func_retry
-    def _lock(self) -> asyncio.Lock:
+    async def publish_message(
-        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:
-        channel = await self._ensure_channel()
+        if not self.is_ready:
+            await self.connect()
+
+        if self._channel is None:
+            raise RuntimeError("Channel should be established after connect")
 
         if exchange:
-            exchange_obj = await channel.get_exchange(exchange.name)
+            exchange_obj = await self._channel.get_exchange(exchange.name)
         else:
-            exchange_obj = channel.default_exchange
+            exchange_obj = self._channel.default_exchange
 
         await exchange_obj.publish(
             aio_pika.Message(
@@ -359,23 +322,9 @@ 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:
-        return await self._ensure_channel()
+        if not self.is_ready:
+            await self.connect()
+        if self._channel is None:
+            raise RuntimeError("Channel should be established after connect")
+        return self._channel

autogpt_platform/backend/backend/executor/manager.py

@@ -213,9 +213,6 @@ 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:

autogpt_platform/backend/backend/util/file.py

@@ -342,14 +342,6 @@ 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

autogpt_platform/backend/backend/util/file_test.py

@@ -247,100 +247,3 @@ 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",
-                )

autogpt_platform/backend/poetry.lock

@@ -46,14 +46,14 @@ pycares = ">=4.9.0,<5"
 
 [[package]]
 name = "aiofiles"
-version = "25.1.0"
+version = "24.1.0"
 description = "File support for asyncio."
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "aiofiles-25.1.0-py3-none-any.whl", hash = "sha256:abe311e527c862958650f9438e859c1fa7568a141b22abcd015e120e86a85695"},
+    {file = "aiofiles-24.1.0-py3-none-any.whl", hash = "sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5"},
-    {file = "aiofiles-25.1.0.tar.gz", hash = "sha256:a8d728f0a29de45dc521f18f07297428d56992a742f0cd2701ba86e44d23d5b2"},
+    {file = "aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c"},
 ]
 
 [[package]]
@@ -269,20 +269,19 @@ files = [
 
 [[package]]
 name = "anthropic"
-version = "0.79.0"
+version = "0.59.0"
 description = "The official Python library for the anthropic API"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "anthropic-0.79.0-py3-none-any.whl", hash = "sha256:04cbd473b6bbda4ca2e41dd670fe2f829a911530f01697d0a1e37321eb75f3cf"},
+    {file = "anthropic-0.59.0-py3-none-any.whl", hash = "sha256:cbc8b3dccef66ad6435c4fa1d317e5ebb092399a4b88b33a09dc4bf3944c3183"},
-    {file = "anthropic-0.79.0.tar.gz", hash = "sha256:8707aafb3b1176ed6c13e2b1c9fb3efddce90d17aee5d8b83a86c70dcdcca871"},
+    {file = "anthropic-0.59.0.tar.gz", hash = "sha256:d710d1ef0547ebbb64b03f219e44ba078e83fc83752b96a9b22e9726b523fd8f"},
 ]
 
 [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"
@@ -290,7 +289,7 @@ sniffio = "*"
 typing-extensions = ">=4.10,<5"
 
 [package.extras]
-aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.9)"]
+aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"]
 bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
 vertex = ["google-auth[requests] (>=2,<3)"]
 
@@ -439,7 +438,7 @@ develop = true
 
 [package.dependencies]
 colorama = "^0.4.6"
-cryptography = "^46.0"
+cryptography = "^45.0"
 expiringdict = "^1.2.2"
 fastapi = "^0.128.0"
 google-cloud-logging = "^3.13.0"
@@ -971,75 +970,62 @@ pytz = ">2021.1"
 
 [[package]]
 name = "cryptography"
-version = "46.0.4"
+version = "45.0.7"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
-python-versions = "!=3.9.0,!=3.9.1,>=3.8"
+python-versions = "!=3.9.0,!=3.9.1,>=3.7"
 groups = ["main"]
 files = [
-    {file = "cryptography-46.0.4-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:281526e865ed4166009e235afadf3a4c4cba6056f99336a99efba65336fd5485"},
+    {file = "cryptography-45.0.7-cp311-abi3-macosx_10_9_universal2.whl", hash = "sha256:3be4f21c6245930688bd9e162829480de027f8bf962ede33d4f8ba7d67a00cee"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5f14fba5bf6f4390d7ff8f086c566454bff0411f6d8aa7af79c88b6f9267aecc"},
+    {file = "cryptography-45.0.7-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:67285f8a611b0ebc0857ced2081e30302909f571a46bfa7a3cc0ad303fe015c6"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:47bcd19517e6389132f76e2d5303ded6cf3f78903da2158a671be8de024f4cd0"},
+    {file = "cryptography-45.0.7-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:577470e39e60a6cd7780793202e63536026d9b8641de011ed9d8174da9ca5339"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:01df4f50f314fbe7009f54046e908d1754f19d0c6d3070df1e6268c5a4af09fa"},
+    {file = "cryptography-45.0.7-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:4bd3e5c4b9682bc112d634f2c6ccc6736ed3635fc3319ac2bb11d768cc5a00d8"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:5aa3e463596b0087b3da0dbe2b2487e9fc261d25da85754e30e3b40637d61f81"},
+    {file = "cryptography-45.0.7-cp311-abi3-manylinux_2_28_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:465ccac9d70115cd4de7186e60cfe989de73f7bb23e8a7aa45af18f7412e75bf"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:0a9ad24359fee86f131836a9ac3bffc9329e956624a2d379b613f8f8abaf5255"},
+    {file = "cryptography-45.0.7-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:16ede8a4f7929b4b7ff3642eba2bf79aa1d71f24ab6ee443935c0d269b6bc513"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_31_armv7l.whl", hash = "sha256:dc1272e25ef673efe72f2096e92ae39dea1a1a450dd44918b15351f72c5a168e"},
+    {file = "cryptography-45.0.7-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:8978132287a9d3ad6b54fcd1e08548033cc09dc6aacacb6c004c73c3eb5d3ac3"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:de0f5f4ec8711ebc555f54735d4c673fc34b65c44283895f1a08c2b49d2fd99c"},
+    {file = "cryptography-45.0.7-cp311-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:b6a0e535baec27b528cb07a119f321ac024592388c5681a5ced167ae98e9fff3"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:eeeb2e33d8dbcccc34d64651f00a98cb41b2dc69cef866771a5717e6734dfa32"},
+    {file = "cryptography-45.0.7-cp311-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:a24ee598d10befaec178efdff6054bc4d7e883f615bfbcd08126a0f4931c83a6"},
-    {file = "cryptography-46.0.4-cp311-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:3d425eacbc9aceafd2cb429e42f4e5d5633c6f873f5e567077043ef1b9bbf616"},
+    {file = "cryptography-45.0.7-cp311-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:fa26fa54c0a9384c27fcdc905a2fb7d60ac6e47d14bc2692145f2b3b1e2cfdbd"},
-    {file = "cryptography-46.0.4-cp311-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:91627ebf691d1ea3976a031b61fb7bac1ccd745afa03602275dda443e11c8de0"},
+    {file = "cryptography-45.0.7-cp311-abi3-win32.whl", hash = "sha256:bef32a5e327bd8e5af915d3416ffefdbe65ed975b646b3805be81b23580b57b8"},
-    {file = "cryptography-46.0.4-cp311-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:2d08bc22efd73e8854b0b7caff402d735b354862f1145d7be3b9c0f740fef6a0"},
+    {file = "cryptography-45.0.7-cp311-abi3-win_amd64.whl", hash = "sha256:3808e6b2e5f0b46d981c24d79648e5c25c35e59902ea4391a0dcb3e667bf7443"},
-    {file = "cryptography-46.0.4-cp311-abi3-win32.whl", hash = "sha256:82a62483daf20b8134f6e92898da70d04d0ef9a75829d732ea1018678185f4f5"},
+    {file = "cryptography-45.0.7-cp37-abi3-macosx_10_9_universal2.whl", hash = "sha256:bfb4c801f65dd61cedfc61a83732327fafbac55a47282e6f26f073ca7a41c3b2"},
-    {file = "cryptography-46.0.4-cp311-abi3-win_amd64.whl", hash = "sha256:6225d3ebe26a55dbc8ead5ad1265c0403552a63336499564675b29eb3184c09b"},
+    {file = "cryptography-45.0.7-cp37-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:81823935e2f8d476707e85a78a405953a03ef7b7b4f55f93f7c2d9680e5e0691"},
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 [package.dependencies]
-cffi = {version = ">=2.0.0", markers = "python_full_version >= \"3.9.0\" and platform_python_implementation != \"PyPy\""}
+cffi = {version = ">=1.14", markers = "platform_python_implementation != \"PyPy\""}
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 [package.extras]
-docs = ["sphinx (>=5.3.0)", "sphinx-inline-tabs", "sphinx-rtd-theme (>=3.0.0)"]
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 docstest = ["pyenchant (>=3)", "readme-renderer (>=30.0)", "sphinxcontrib-spelling (>=7.3.1)"]
-nox = ["nox[uv] (>=2024.4.15)"]
+nox = ["nox (>=2024.4.15)", "nox[uv] (>=2024.3.2) ; python_full_version >= \"3.8.0\""]
-pep8test = ["check-sdist", "click (>=8.0.1)", "mypy (>=1.14)", "ruff (>=0.11.11)"]
+pep8test = ["check-sdist ; python_full_version >= \"3.8.0\"", "click (>=8.0.1)", "mypy (>=1.4)", "ruff (>=0.3.6)"]
 sdist = ["build (>=1.0.0)"]
 ssh = ["bcrypt (>=3.1.5)"]
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+test = ["certifi (>=2024)", "cryptography-vectors (==45.0.7)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -1149,23 +1135,6 @@ 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"]
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-
-[package.extras]
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-docs = ["pydoctor (>=25.4.0)"]
-test = ["pytest"]
-
 [[package]]
 name = "dulwich"
 version = "0.22.8"
@@ -1382,14 +1351,14 @@ tzdata = "*"
 
 [[package]]
 name = "fastapi"
-version = "0.128.6"
+version = "0.128.3"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -3078,14 +3047,14 @@ type = ["pygobject-stubs", "pytest-mypy (>=1.0.1)", "shtab", "types-pywin32"]
 
 [[package]]
 name = "langfuse"
-version = "3.14.1"
+version = "3.13.0"
 description = "A client library for accessing langfuse"
 optional = false
 python-versions = "<4.0,>=3.10"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -3963,14 +3932,14 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 
 [[package]]
 name = "ollama"
-version = "0.6.1"
+version = "0.5.4"
 description = "The official Python client for Ollama."
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -4640,20 +4609,20 @@ testing = ["coverage", "pytest", "pytest-benchmark"]
 
 [[package]]
 name = "poethepoet"
-version = "0.41.0"
+version = "0.37.0"
 description = "A task runner that works well with poetry and uv."
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.9"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
 pastel = ">=0.2.1,<0.3.0"
-pyyaml = ">=6.0.3,<7.0"
+pyyaml = ">=6.0.2,<7.0"
-tomli = {version = ">=1.3.0", markers = "python_version < \"3.11\""}
+tomli = {version = ">=1.2.2", markers = "python_version < \"3.11\""}
 
 [package.extras]
 poetry-plugin = ["poetry (>=1.2.0,<3.0.0) ; python_version < \"4.0\""]
@@ -4728,14 +4697,14 @@ tests = ["coverage-conditional-plugin (>=0.9.0)", "portalocker[redis]", "pytest
 
 [[package]]
 name = "postgrest"
-version = "2.27.3"
+version = "2.27.2"
 description = "PostgREST client for Python. This library provides an ORM interface to PostgREST."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -4893,19 +4862,17 @@ tqdm = "*"
 
 [[package]]
 name = "prometheus-client"
-version = "0.24.1"
+version = "0.22.1"
 description = "Python client for the Prometheus monitoring system."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "prometheus_client-0.22.1.tar.gz", hash = "sha256:190f1331e783cf21eb60bca559354e0a4d4378facecf78f5428c39b675d20d28"},
 ]
 
 [package.extras]
-aiohttp = ["aiohttp"]
-django = ["django"]
 twisted = ["twisted"]
 
 [[package]]
@@ -5919,18 +5886,18 @@ pytest = ">=3.0.0"
 
 [[package]]
 name = "pytest-watcher"
-version = "0.6.3"
+version = "0.4.3"
 description = "Automatically rerun your tests on file modifications"
 optional = false
-python-versions = ">=3.9"
+python-versions = "<4.0.0,>=3.7.0"
 groups = ["dev"]
 files = [
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 ]
 
 [package.dependencies]
-tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
+tomli = {version = ">=2.0.1,<3.0.0", markers = "python_version < \"3.11\""}
 watchdog = ">=2.0.0"
 
 [[package]]
@@ -5965,14 +5932,14 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "python-multipart"
-version = "0.0.22"
+version = "0.0.20"
 description = "A streaming multipart parser for Python"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.8"
 groups = ["main"]
 files = [
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+    {file = "python_multipart-0.0.20.tar.gz", hash = "sha256:8dd0cab45b8e23064ae09147625994d090fa46f5b0d1e13af944c331a7fa9d13"},
 ]
 
 [[package]]
@@ -6260,14 +6227,14 @@ all = ["numpy"]
 
 [[package]]
 name = "realtime"
-version = "2.27.3"
+version = "2.27.2"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "realtime-2.27.2.tar.gz", hash = "sha256:b960a90294d2cea1b3f1275ecb89204304728e08fff1c393cc1b3150739556b3"},
 ]
 
 [package.dependencies]
@@ -6672,30 +6639,31 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "ruff"
-version = "0.15.0"
+version = "0.14.14"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
 python-versions = ">=3.7"
 groups = ["dev"]
 files = [
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-    {file = "ruff-0.15.0.tar.gz", hash = "sha256:6bdea47cdbea30d40f8f8d7d69c0854ba7c15420ec75a26f463290949d7f7e9a"},
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 ]
 
 [[package]]
@@ -7024,14 +6992,14 @@ full = ["httpx (>=0.27.0,<0.29.0)", "itsdangerous", "jinja2", "python-multipart
 
 [[package]]
 name = "storage3"
-version = "2.27.3"
+version = "2.27.2"
 description = "Supabase Storage client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "storage3-2.27.3-py3-none-any.whl", hash = "sha256:11a05b7da84bccabeeea12d940bca3760cf63fe6ca441868677335cfe4fdfbe0"},
+    {file = "storage3-2.27.2-py3-none-any.whl", hash = "sha256:e6f16e7a260729e7b1f46e9bf61746805a02e30f5e419ee1291007c432e3ec63"},
-    {file = "storage3-2.27.3.tar.gz", hash = "sha256:dc1a4a010cf36d5482c5cb6c1c28fc5f00e23284342b89e4ae43b5eae8501ddb"},
+    {file = "storage3-2.27.2.tar.gz", hash = "sha256:cb4807b7f86b4bb1272ac6fdd2f3cfd8ba577297046fa5f88557425200275af5"},
 ]
 
 [package.dependencies]
@@ -7091,35 +7059,35 @@ typing-extensions = {version = ">=4.5.0", markers = "python_version >= \"3.7\""}
 
 [[package]]
 name = "supabase"
-version = "2.27.3"
+version = "2.27.2"
 description = "Supabase client for Python."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase-2.27.3-py3-none-any.whl", hash = "sha256:082a74642fcf9954693f1ce8c251baf23e4bda26ffdbc8dcd4c99c82e60d69ff"},
+    {file = "supabase-2.27.2-py3-none-any.whl", hash = "sha256:d4dce00b3a418ee578017ec577c0e5be47a9a636355009c76f20ed2faa15bc54"},
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+    {file = "supabase-2.27.2.tar.gz", hash = "sha256:2aed40e4f3454438822442a1e94a47be6694c2c70392e7ae99b51a226d4293f7"},
 ]
 
 [package.dependencies]
 httpx = ">=0.26,<0.29"
-postgrest = "2.27.3"
+postgrest = "2.27.2"
-realtime = "2.27.3"
+realtime = "2.27.2"
-storage3 = "2.27.3"
+storage3 = "2.27.2"
-supabase-auth = "2.27.3"
+supabase-auth = "2.27.2"
-supabase-functions = "2.27.3"
+supabase-functions = "2.27.2"
 yarl = ">=1.22.0"
 
 [[package]]
 name = "supabase-auth"
-version = "2.27.3"
+version = "2.27.2"
 description = "Python Client Library for Supabase Auth"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "supabase_auth-2.27.2-py3-none-any.whl", hash = "sha256:78ec25b11314d0a9527a7205f3b1c72560dccdc11b38392f80297ef98664ee91"},
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+    {file = "supabase_auth-2.27.2.tar.gz", hash = "sha256:0f5bcc79b3677cb42e9d321f3c559070cfa40d6a29a67672cc8382fb7dc2fe97"},
 ]
 
 [package.dependencies]
@@ -7129,14 +7097,14 @@ pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 
 [[package]]
 name = "supabase-functions"
-version = "2.27.3"
+version = "2.27.2"
 description = "Library for Supabase Functions"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "supabase_functions-2.27.3-py3-none-any.whl", hash = "sha256:9d14a931d49ede1c6cf5fbfceb11c44061535ba1c3f310f15384964d86a83d9e"},
+    {file = "supabase_functions-2.27.2-py3-none-any.whl", hash = "sha256:db480efc669d0bca07605b9b6f167312af43121adcc842a111f79bea416ef754"},
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+    {file = "supabase_functions-2.27.2.tar.gz", hash = "sha256:d0c8266207a94371cb3fd35ad3c7f025b78a97cf026861e04ccd35ac1775f80b"},
 ]
 
 [package.dependencies]
@@ -7146,14 +7114,14 @@ yarl = ">=1.20.1"
 
 [[package]]
 name = "tenacity"
-version = "9.1.4"
+version = "9.1.3"
 description = "Retry code until it succeeds"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
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+    {file = "tenacity-9.1.3.tar.gz", hash = "sha256:a6724c947aa717087e2531f883bde5c9188f603f6669a9b8d54eb998e604c12a"},
 ]
 
 [package.extras]
@@ -7162,69 +7130,43 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
 [[package]]
 name = "tiktoken"
-version = "0.12.0"
+version = "0.9.0"
 description = "tiktoken is a fast BPE tokeniser for use with OpenAI's models"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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+    {file = "tiktoken-0.9.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:586c16358138b96ea804c034b8acf3f5d3f0258bd2bc3b0227af4af5d622e382"},
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 ]
 
 [package.dependencies]
@@ -8440,4 +8382,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "c06e96ad49388ba7a46786e9ea55ea2c1a57408e15613237b4bee40a592a12af"
+content-hash = "40b2c87c3c86bd10214bd30ad291cead75da5060ab894105025ee4c0a3b3828e"

autogpt_platform/backend/pyproject.toml

@@ -12,16 +12,16 @@ python = ">=3.10,<3.14"
 aio-pika = "^9.5.5"
 aiohttp = "^3.10.0"
 aiodns = "^3.5.0"
-anthropic = "^0.79.0"
+anthropic = "^0.59.0"
 apscheduler = "^3.11.1"
 autogpt-libs = { path = "../autogpt_libs", develop = true }
 bleach = { extras = ["css"], version = "^6.2.0" }
 click = "^8.2.0"
-cryptography = "^46.0"
+cryptography = "^45.0"
 discord-py = "^2.5.2"
 e2b-code-interpreter = "^1.5.2"
 elevenlabs = "^1.50.0"
-fastapi = "^0.128.6"
+fastapi = "^0.128.0"
 feedparser = "^6.0.11"
 flake8 = "^7.3.0"
 google-api-python-client = "^2.177.0"
@@ -34,11 +34,11 @@ html2text = "^2024.2.26"
 jinja2 = "^3.1.6"
 jsonref = "^1.1.0"
 jsonschema = "^4.25.0"
-langfuse = "^3.14.1"
+langfuse = "^3.11.0"
 launchdarkly-server-sdk = "^9.14.1"
 mem0ai = "^0.1.115"
 moviepy = "^2.1.2"
-ollama = "^0.6.1"
+ollama = "^0.5.1"
 openai = "^1.97.1"
 orjson = "^3.10.0"
 pika = "^1.3.2"
@@ -48,7 +48,7 @@ postmarker = "^1.0"
 praw = "~7.8.1"
 prisma = "^0.15.0"
 rank-bm25 = "^0.2.2"
-prometheus-client = "^0.24.1"
+prometheus-client = "^0.22.1"
 prometheus-fastapi-instrumentator = "^7.0.0"
 psutil = "^7.0.0"
 psycopg2-binary = "^2.9.10"
@@ -57,7 +57,7 @@ pydantic-settings = "^2.12.0"
 pytest = "^8.4.1"
 pytest-asyncio = "^1.1.0"
 python-dotenv = "^1.1.1"
-python-multipart = "^0.0.22"
+python-multipart = "^0.0.20"
 redis = "^6.2.0"
 regex = "^2025.9.18"
 replicate = "^1.0.6"
@@ -65,8 +65,8 @@ sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlal
 sqlalchemy = "^2.0.40"
 strenum = "^0.4.9"
 stripe = "^11.5.0"
-supabase = "2.27.3"
+supabase = "2.27.2"
-tenacity = "^9.1.4"
+tenacity = "^9.1.2"
 todoist-api-python = "^2.1.7"
 tweepy = "^4.16.0"
 uvicorn = { extras = ["standard"], version = "^0.40.0" }
@@ -76,8 +76,8 @@ yt-dlp = "2025.12.08"
 zerobouncesdk = "^1.1.2"
 # NOTE: please insert new dependencies in their alphabetical location
 pytest-snapshot = "^0.9.0"
-aiofiles = "^25.1.0"
+aiofiles = "^24.1.0"
-tiktoken = "^0.12.0"
+tiktoken = "^0.9.0"
 aioclamd = "^1.0.0"
 setuptools = "^80.9.0"
 gcloud-aio-storage = "^9.5.0"
@@ -95,13 +95,13 @@ black = "^24.10.0"
 faker = "^38.2.0"
 httpx = "^0.28.1"
 isort = "^5.13.2"
-poethepoet = "^0.41.0"
+poethepoet = "^0.37.0"
 pre-commit = "^4.4.0"
 pyright = "^1.1.407"
 pytest-mock = "^3.15.1"
-pytest-watcher = "^0.6.3"
+pytest-watcher = "^0.4.2"
 requests = "^2.32.5"
-ruff = "^0.15.0"
+ruff = "^0.14.5"
 # NOTE: please insert new dependencies in their alphabetical location
 
 [build-system]

autogpt_platform/frontend/Dockerfile

@@ -25,12 +25,8 @@ 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 [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=8192" pnpm build; else NODE_OPTIONS="--max-old-space-size=8192" pnpm build; fi
+RUN if [ "$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
 
 # 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

autogpt_platform/frontend/next.config.mjs

@@ -1,12 +1,8 @@
 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: enableSourceMaps,
+  productionBrowserSourceMaps: true,
   // Externalize OpenTelemetry packages to fix Turbopack HMR issues
   serverExternalPackages: [
     "@opentelemetry/instrumentation",
@@ -18,37 +14,9 @@ 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: [
@@ -86,16 +54,9 @@ const nextConfig = {
   transpilePackages: ["geist"],
 };
 
-// Only run the Sentry webpack plugin when we can actually upload source maps
+const isDevelopmentBuild = process.env.NODE_ENV !== "production";
-// (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 skipSentryPlugin
+export default isDevelopmentBuild
   ? nextConfig
   : withSentryConfig(nextConfig, {
       // For all available options, see:
@@ -135,7 +96,7 @@ export default skipSentryPlugin
 
       // This helps Sentry with sourcemaps... https://docs.sentry.io/platforms/javascript/guides/nextjs/sourcemaps/
       sourcemaps: {
-        disable: !enableSourceMaps,
+        disable: false,
         assets: [".next/**/*.js", ".next/**/*.js.map"],
         ignore: ["**/node_modules/**"],
         deleteSourcemapsAfterUpload: false, // Source is public anyway :)

autogpt_platform/frontend/package.json

@@ -7,7 +7,7 @@
   },
   "scripts": {
     "dev": "pnpm run generate:api:force && next dev --turbo",
-    "build": "cross-env NODE_OPTIONS=--max-old-space-size=16384 next build",
+    "build": "next build",
     "start": "next start",
     "start:standalone": "cd .next/standalone && node server.js",
     "lint": "next lint && prettier --check .",
@@ -30,7 +30,6 @@
     "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",
@@ -61,10 +60,6 @@
     "@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",
@@ -73,7 +68,6 @@
     "@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",
@@ -93,6 +87,7 @@
     "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",
@@ -107,7 +102,7 @@
     "react-markdown": "9.0.3",
     "react-modal": "3.16.3",
     "react-shepherd": "6.1.9",
-    "react-window": "2.2.0",
+    "react-window": "1.8.11",
     "recharts": "3.3.0",
     "rehype-autolink-headings": "7.1.0",
     "rehype-highlight": "7.0.2",
@@ -117,11 +112,9 @@
     "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",
@@ -147,7 +140,7 @@
     "@types/react": "18.3.17",
     "@types/react-dom": "18.3.5",
     "@types/react-modal": "3.16.3",
-    "@types/react-window": "2.0.0",
+    "@types/react-window": "1.8.8",
     "@vitejs/plugin-react": "5.1.2",
     "axe-playwright": "2.2.2",
     "chromatic": "13.3.3",
@@ -179,8 +172,7 @@
   },
   "pnpm": {
     "overrides": {
-      "@opentelemetry/instrumentation": "0.209.0",
+      "@opentelemetry/instrumentation": "0.209.0"
-      "lodash-es": "4.17.23"
     }
   },
   "packageManager": "pnpm@10.20.0+sha512.cf9998222162dd85864d0a8102e7892e7ba4ceadebbf5a31f9c2fce48dfce317a9c53b9f6464d1ef9042cba2e02ae02a9f7c143a2b438cd93c91840f0192b9dd"

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts

@@ -1,4 +1,4 @@
-import debounce from "lodash/debounce";
+import { debounce } from "lodash";
 import { useCallback, useEffect, useRef, useState } from "react";
 import { useBlockMenuStore } from "../../../../stores/blockMenuStore";
 import { getQueryClient } from "@/lib/react-query/queryClient";

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-background via-background/80 to-background/0" />
+          <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" />
         )}
         {canScrollRight && (
-          <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" />
+          <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" />
         )}
         {canScrollLeft && (
           <button

autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx

@@ -1,80 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx

@@ -1,74 +0,0 @@
-"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>
-  );
-};

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx

@@ -1,274 +0,0 @@
-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 { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
-import { useEffect, 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);
-
-  useEffect(() => {
-    if (status === "submitted") {
-      setThinkingPhrase(getRandomPhrase());
-    }
-  }, [status]);
-
-  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-3 text-red-600">
-            Error: {error.message}
-          </div>
-        )}
-      </ConversationContent>
-      <ConversationScrollButton />
-    </Conversation>
-  );
-};

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatSidebar/ChatSidebar.tsx

@@ -1,188 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/CopilotChatActionsProvider.tsx

@@ -1,16 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotChatActionsProvider/useCopilotChatActions.ts

@@ -1,23 +0,0 @@
-"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 };

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/CopilotShell.tsx

@@ -0,0 +1,99 @@
+"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>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/DesktopSidebar/DesktopSidebar.tsx

@@ -0,0 +1,70 @@
+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>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/MobileDrawer.tsx

@@ -0,0 +1,91 @@
+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>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/MobileDrawer/useMobileDrawer.ts

@@ -0,0 +1,24 @@
+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,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/SessionsList.tsx

@@ -0,0 +1,80 @@
+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>
+        );
+      }}
+    />
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/components/SessionsList/useSessionsPagination.ts

@@ -0,0 +1,91 @@
+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,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/helpers.ts

@@ -0,0 +1,106 @@
+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");
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useCopilotShell.ts

@@ -0,0 +1,124 @@
+"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 { 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 isCreatingSession = useCopilotStore((s) => s.isCreatingSession);
+
+  function handleSessionClick(sessionId: string) {
+    if (sessionId === currentSessionId) return;
+
+    // Stop current stream - SSE reconnection allows resuming later
+    if (currentSessionId) {
+      stopStream(currentSessionId);
+    }
+
+    if (recentlyCreatedSessionsRef.current.has(sessionId)) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2GetSessionQueryKey(sessionId),
+      });
+    }
+    setUrlSessionId(sessionId, { shallow: false });
+    if (isMobile) handleCloseDrawer();
+  }
+
+  function handleNewChatClick() {
+    // Stop current stream - SSE reconnection allows resuming later
+    if (currentSessionId) {
+      stopStream(currentSessionId);
+    }
+
+    resetPagination();
+    queryClient.invalidateQueries({
+      queryKey: getGetV2ListSessionsQueryKey(),
+    });
+    setUrlSessionId(null, { shallow: false });
+    if (isMobile) handleCloseDrawer();
+  }
+
+  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,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/CopilotShell/useShellSessionList.ts

@@ -0,0 +1,113 @@
+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,
+  };
+}

autogpt_platform/frontend/src/app/(platform)/copilot/components/EmptySession/EmptySession.tsx

@@ -1,111 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/MobileDrawer/MobileDrawer.tsx

@@ -1,140 +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 { 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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/MorphingTextAnimation/MorphingTextAnimation.tsx

@@ -1,54 +0,0 @@
-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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.module.css

@@ -1,69 +0,0 @@
-.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;
-  }
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/OrbitLoader/OrbitLoader.tsx

@@ -1,28 +0,0 @@
-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
-      }
-    />
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ProgressBar/ProgressBar.tsx

@@ -1,26 +0,0 @@
-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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.module.css

@@ -1,34 +0,0 @@
-.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;
-  }
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/PulseLoader/PulseLoader.tsx

@@ -1,16 +0,0 @@
-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 }}
-    />
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.module.css

@@ -1,35 +0,0 @@
-.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;
-  }
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ScaleLoader/ScaleLoader.tsx

@@ -1,16 +0,0 @@
-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 }}
-    />
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.module.css

@@ -1,57 +0,0 @@
-.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;
-  }
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/SpinnerLoader/SpinnerLoader.tsx

@@ -1,16 +0,0 @@
-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 }}
-    />
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/AccordionContent.tsx

@@ -1,235 +0,0 @@
-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(
-        "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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/ToolAccordion.tsx

@@ -1,102 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolAccordion/useToolAccordion.ts

@@ -1,32 +0,0 @@
-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 };
-}

autogpt_platform/frontend/src/app/(platform)/copilot/copilot-page-store.ts

@@ -0,0 +1,56 @@
+"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 });
+  },
+}));

autogpt_platform/frontend/src/app/(platform)/copilot/helpers.ts

@@ -1,26 +1,6 @@
-import { User } from "@supabase/supabase-js";
+import type { User } from "@supabase/supabase-js";
 
-export function getInputPlaceholder(width?: number) {
+export function getGreetingName(user?: User | null): string {
-  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;
@@ -36,3 +16,30 @@ export function getGreetingName(user?: User | null) {
   }
   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 [
+    "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 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...'";
+}

autogpt_platform/frontend/src/app/(platform)/copilot/helpers/convertChatSessionToUiMessages.ts

@@ -1,128 +0,0 @@
-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;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/layout.tsx

@@ -0,0 +1,13 @@
+"use client";
+import { FeatureFlagPage } from "@/services/feature-flags/FeatureFlagPage";
+import { Flag } from "@/services/feature-flags/use-get-flag";
+import { type ReactNode } from "react";
+import { CopilotShell } from "./components/CopilotShell/CopilotShell";
+
+export default function CopilotLayout({ children }: { children: ReactNode }) {
+  return (
+    <FeatureFlagPage flag={Flag.CHAT} whenDisabled="/library">
+      <CopilotShell>{children}</CopilotShell>
+    </FeatureFlagPage>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/page.tsx

@@ -1,13 +1,149 @@
 "use client";
 
-import { FeatureFlagPage } from "@/services/feature-flags/FeatureFlagPage";
+import { Button } from "@/components/atoms/Button/Button";
-import { Flag } from "@/services/feature-flags/use-get-flag";
+import { Skeleton } from "@/components/atoms/Skeleton/Skeleton";
-import { CopilotPage } from "./CopilotPage";
+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 { useEffect, useState } from "react";
+import { useCopilotStore } from "./copilot-page-store";
+import { getInputPlaceholder } from "./helpers";
+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 [inputPlaceholder, setInputPlaceholder] = useState(
+    getInputPlaceholder(),
+  );
+
+  useEffect(() => {
+    const handleResize = () => {
+      setInputPlaceholder(getInputPlaceholder(window.innerWidth));
+    };
+
+    handleResize();
+
+    window.addEventListener("resize", handleResize);
+    return () => window.removeEventListener("resize", handleResize);
+  }, []);
+
+  const { greetingName, quickActions, isLoading, hasSession, initialPrompt } =
+    state;
+
+  const {
+    handleQuickAction,
+    startChatWithPrompt,
+    handleSessionNotFound,
+    handleStreamingChange,
+  } = handlers;
+
+  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>
+    );
+  }
 
-export default function Page() {
   return (
-    <FeatureFlagPage flag={Flag.CHAT} whenDisabled="/library">
+    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-3 py-5 md:px-6 md:py-10">
-      <CopilotPage />
+      <div className="w-full text-center">
-    </FeatureFlagPage>
+        {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-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">
+                <ChatInput
+                  onSend={startChatWithPrompt}
+                  placeholder={inputPlaceholder}
+                />
+              </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={() => handleQuickAction(action)}
+                  className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
+                >
+                  {action}
+                </Button>
+              ))}
+            </div>
+          </>
+        )}
+      </div>
+    </div>
   );
 }

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx

@@ -1,235 +0,0 @@
-"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 "./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: <OrbitLoader size={32} />,
-      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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx

@@ -1,186 +0,0 @@
-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()}…`;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx

@@ -1,231 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/helpers.tsx

@@ -1,188 +0,0 @@
-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()}…`;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/FindAgents.tsx

@@ -1,127 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindAgents/helpers.tsx

@@ -1,187 +0,0 @@
-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" />;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/FindBlocks.tsx

@@ -1,92 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/FindBlocks/helpers.tsx

@@ -1,75 +0,0 @@
-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" />;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/RunAgent.tsx

@@ -1,86 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/AgentDetailsCard.tsx

@@ -1,116 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/AgentDetailsCard/helpers.ts

@@ -1,8 +0,0 @@
-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;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ErrorCard/ErrorCard.tsx

@@ -1,27 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/ExecutionStartedCard/ExecutionStartedCard.tsx

@@ -1,39 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/SetupRequirementsCard.tsx

@@ -1,105 +0,0 @@
-"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>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/helpers.ts

@@ -1,116 +0,0 @@
-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;
-}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/helpers.tsx

@@ -1,248 +0,0 @@
-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: <OrbitLoader size={28} className="text-neutral-700" />,
-      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",
-  };
-}