Merge branch 'dev' into abhimanyuyadav/secrt-1938-remove-old-builder-code-and-unused-shared-components

(#12081)

### Changes 🏗️

This PR completes the migration from the legacy builder to the new Flow
editor by removing all legacy code and feature flags.

**Removed:**
- Old builder view toggle functionality (`BuilderViewTabs.tsx`)
- Legacy debug panel (`RightSidebar.tsx`)
- Feature flags: `NEW_FLOW_EDITOR` and `BUILDER_VIEW_SWITCH`
- `useBuilderView` hook and related view-switching logic

**Updated:**
- Simplified `build/page.tsx` to always render the new Flow editor
- Added CSS styling (`flow.css`) to properly render Phosphor icons in
React Flow handles

**Tests:**
- Skipped e2e test suite in `build.spec.ts` (legacy builder tests)
- Follow-up PR (#12082) will add new e2e tests for the Flow editor

### Checklist 📋

#### For code changes:

- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
    - [x] Create a new flow and verify it loads correctly
    - [x] Add nodes and connections to verify basic functionality works
    - [x] Verify that node handles render correctly with the new CSS
- [x] Check that the UI is clean without the old debug panel or view
toggles

#### For configuration changes:

- [x] `.env.default` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes

.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@v7
+        uses: peter-evans/create-pull-request@v8
         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@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.event.workflow_run.head_branch }}
           fetch-depth: 0
@@ -42,7 +42,7 @@ jobs:
 
       - name: Get CI failure details
         id: failure_details
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const run = await github.rest.actions.getWorkflowRun({

.github/workflows/claude-dependabot.yml

@@ -30,7 +30,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -41,7 +41,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -78,7 +78,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22"
 
@@ -91,7 +91,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -124,7 +124,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes
@@ -309,6 +309,7 @@ jobs:
         uses: anthropics/claude-code-action@v1
         with:
           claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }}
+          allowed_bots: "dependabot[bot]"
           claude_args: |
             --allowedTools "Bash(npm:*),Bash(pnpm:*),Bash(poetry:*),Bash(git:*),Edit,Replace,NotebookEditCell,mcp__github_inline_comment__create_inline_comment,Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*)"
           prompt: |

.github/workflows/claude.yml

@@ -40,7 +40,7 @@ jobs:
       actions: read # Required for CI access
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 1
 
@@ -57,7 +57,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -94,7 +94,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22"
 
@@ -107,7 +107,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -140,7 +140,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

.github/workflows/codeql.yml

@@ -58,7 +58,7 @@ jobs:
         # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
     steps:
     - name: Checkout repository
-      uses: actions/checkout@v4
+      uses: actions/checkout@v6
 
     # Initializes the CodeQL tools for scanning.
     - name: Initialize CodeQL

.github/workflows/copilot-setup-steps.yml

@@ -27,7 +27,7 @@ jobs:
     # If you do not check out your code, Copilot will do this for you.
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true
@@ -39,7 +39,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -76,7 +76,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22"
 
@@ -89,7 +89,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -132,7 +132,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

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

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

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

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

.github/workflows/docs-enhance.yml

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

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

@@ -25,7 +25,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.event.inputs.git_ref || github.ref_name }}
 
@@ -52,7 +52,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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

@@ -17,7 +17,7 @@ jobs:
 
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ github.ref_name || 'master' }}
 
@@ -45,7 +45,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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

@@ -68,7 +68,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
           submodules: true
@@ -88,7 +88,7 @@ jobs:
         run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}

.github/workflows/platform-dev-deploy-event-dispatcher.yml

@@ -17,7 +17,7 @@ jobs:
       - name: Check comment permissions and deployment status
         id: check_status
         if: github.event_name == 'issue_comment' && github.event.issue.pull_request
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const commentBody = context.payload.comment.body.trim();
@@ -55,7 +55,7 @@ jobs:
 
       - name: Post permission denied comment
         if: steps.check_status.outputs.permission_denied == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -68,7 +68,7 @@ jobs:
       - name: Get PR details for deployment
         id: pr_details
         if: steps.check_status.outputs.should_deploy == 'true' || steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const pr = await github.rest.pulls.get({
@@ -82,7 +82,7 @@ jobs:
           
       - name: Dispatch Deploy Event
         if: steps.check_status.outputs.should_deploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -98,7 +98,7 @@ jobs:
 
       - name: Post deploy success comment
         if: steps.check_status.outputs.should_deploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -110,7 +110,7 @@ jobs:
 
       - name: Dispatch Undeploy Event (from comment)
         if: steps.check_status.outputs.should_undeploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -126,7 +126,7 @@ jobs:
 
       - name: Post undeploy success comment
         if: steps.check_status.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({
@@ -139,7 +139,7 @@ jobs:
       - name: Check deployment status on PR close
         id: check_pr_close
         if: github.event_name == 'pull_request' && github.event.action == 'closed'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             const comments = await github.rest.issues.listComments({
@@ -168,7 +168,7 @@ jobs:
           github.event_name == 'pull_request' &&
           github.event.action == 'closed' &&
           steps.check_pr_close.outputs.should_undeploy == 'true'
-        uses: peter-evans/repository-dispatch@v3
+        uses: peter-evans/repository-dispatch@v4
         with:
           token: ${{ secrets.DISPATCH_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
@@ -187,7 +187,7 @@ jobs:
           github.event_name == 'pull_request' &&
           github.event.action == 'closed' &&
           steps.check_pr_close.outputs.should_undeploy == 'true'
-        uses: actions/github-script@v7
+        uses: actions/github-script@v8
         with:
           script: |
             await github.rest.issues.createComment({

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

@@ -31,7 +31,7 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - 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@v4
+        uses: actions/setup-node@v6
         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@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -71,10 +71,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -82,7 +82,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -107,12 +107,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           fetch-depth: 0
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -120,7 +120,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -148,12 +148,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -176,7 +176,7 @@ jobs:
         uses: docker/setup-buildx-action@v3
 
       - name: Cache Docker layers
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: /tmp/.buildx-cache
           key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
@@ -231,7 +231,7 @@ jobs:
           fi
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -277,12 +277,12 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -290,7 +290,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

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

@@ -29,10 +29,10 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -44,7 +44,7 @@ jobs:
         run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
 
       - name: Cache dependencies
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -56,19 +56,19 @@ jobs:
         run: pnpm install --frozen-lockfile
 
   types:
-    runs-on: ubuntu-latest
+    runs-on: big-boi
     needs: setup
     strategy:
       fail-fast: false
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v4
+        uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
 
@@ -85,10 +85,10 @@ jobs:
 
       - name: Run docker compose
         run: |
-          docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
+          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
 
       - name: Restore dependencies cache
-        uses: actions/cache@v4
+        uses: actions/cache@v5
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

.github/workflows/repo-workflow-checker.yml

@@ -11,7 +11,7 @@ jobs:
     steps:
       # - name: Wait some time for all actions to start
       #   run: sleep 30
-      - uses: actions/checkout@v4
+      - uses: actions/checkout@v6
         # with:
           # fetch-depth: 0
       - name: Set up Python

autogpt_platform/autogpt_libs/pyproject.toml

@@ -9,25 +9,25 @@ packages = [{ include = "autogpt_libs" }]
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
 colorama = "^0.4.6"
-cryptography = "^45.0"
+cryptography = "^46.0"
 expiringdict = "^1.2.2"
-fastapi = "^0.116.1"
-google-cloud-logging = "^3.12.1"
-launchdarkly-server-sdk = "^9.12.0"
-pydantic = "^2.11.7"
-pydantic-settings = "^2.10.1"
-pyjwt = { version = "^2.10.1", extras = ["crypto"] }
+fastapi = "^0.128.0"
+google-cloud-logging = "^3.13.0"
+launchdarkly-server-sdk = "^9.14.1"
+pydantic = "^2.12.5"
+pydantic-settings = "^2.12.0"
+pyjwt = { version = "^2.11.0", extras = ["crypto"] }
 redis = "^6.2.0"
-supabase = "^2.16.0"
-uvicorn = "^0.35.0"
+supabase = "^2.27.2"
+uvicorn = "^0.40.0"
 
 [tool.poetry.group.dev.dependencies]
-pyright = "^1.1.404"
+pyright = "^1.1.408"
 pytest = "^8.4.1"
-pytest-asyncio = "^1.1.0"
-pytest-mock = "^3.14.1"
-pytest-cov = "^6.2.1"
-ruff = "^0.12.11"
+pytest-asyncio = "^1.3.0"
+pytest-mock = "^3.15.1"
+pytest-cov = "^7.0.0"
+ruff = "^0.15.0"
 
 [build-system]
 requires = ["poetry-core"]

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

@@ -93,6 +93,12 @@ class ChatConfig(BaseSettings):
         description="Name of the prompt in Langfuse to fetch",
     )
 
+    # Extended thinking configuration for Claude models
+    thinking_enabled: bool = Field(
+        default=True,
+        description="Enable adaptive thinking for Claude models via OpenRouter",
+    )
+
     @field_validator("api_key", mode="before")
     @classmethod
     def get_api_key(cls, v):

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

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

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

@@ -2,7 +2,7 @@ import asyncio
 import logging
 import uuid
 from datetime import UTC, datetime
-from typing import Any
+from typing import Any, cast
 from weakref import WeakValueDictionary
 
 from openai.types.chat import (
@@ -104,6 +104,26 @@ class ChatSession(BaseModel):
     successful_agent_runs: dict[str, int] = {}
     successful_agent_schedules: dict[str, int] = {}
 
+    def add_tool_call_to_current_turn(self, tool_call: dict) -> None:
+        """Attach a tool_call to the current turn's assistant message.
+
+        Searches backwards for the most recent assistant message (stopping at
+        any user message boundary). If found, appends the tool_call to it.
+        Otherwise creates a new assistant message with the tool_call.
+        """
+        for msg in reversed(self.messages):
+            if msg.role == "user":
+                break
+            if msg.role == "assistant":
+                if not msg.tool_calls:
+                    msg.tool_calls = []
+                msg.tool_calls.append(tool_call)
+                return
+
+        self.messages.append(
+            ChatMessage(role="assistant", content="", tool_calls=[tool_call])
+        )
+
     @staticmethod
     def new(user_id: str) -> "ChatSession":
         return ChatSession(
@@ -172,6 +192,47 @@ class ChatSession(BaseModel):
             successful_agent_schedules=successful_agent_schedules,
         )
 
+    @staticmethod
+    def _merge_consecutive_assistant_messages(
+        messages: list[ChatCompletionMessageParam],
+    ) -> list[ChatCompletionMessageParam]:
+        """Merge consecutive assistant messages into single messages.
+
+        Long-running tool flows can create split assistant messages: one with
+        text content and another with tool_calls. Anthropic's API requires
+        tool_result blocks to reference a tool_use in the immediately preceding
+        assistant message, so these splits cause 400 errors via OpenRouter.
+        """
+        if len(messages) < 2:
+            return messages
+
+        result: list[ChatCompletionMessageParam] = [messages[0]]
+        for msg in messages[1:]:
+            prev = result[-1]
+            if prev.get("role") != "assistant" or msg.get("role") != "assistant":
+                result.append(msg)
+                continue
+
+            prev = cast(ChatCompletionAssistantMessageParam, prev)
+            curr = cast(ChatCompletionAssistantMessageParam, msg)
+
+            curr_content = curr.get("content") or ""
+            if curr_content:
+                prev_content = prev.get("content") or ""
+                prev["content"] = (
+                    f"{prev_content}\n{curr_content}" if prev_content else curr_content
+                )
+
+            curr_tool_calls = curr.get("tool_calls")
+            if curr_tool_calls:
+                prev_tool_calls = prev.get("tool_calls")
+                prev["tool_calls"] = (
+                    list(prev_tool_calls) + list(curr_tool_calls)
+                    if prev_tool_calls
+                    else list(curr_tool_calls)
+                )
+        return result
+
     def to_openai_messages(self) -> list[ChatCompletionMessageParam]:
         messages = []
         for message in self.messages:
@@ -258,7 +319,7 @@ class ChatSession(BaseModel):
                         name=message.name or "",
                     )
                 )
-        return messages
+        return self._merge_consecutive_assistant_messages(messages)
 
 
 async def _get_session_from_cache(session_id: str) -> ChatSession | None:

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

@@ -1,4 +1,16 @@
+from typing import cast
+
 import pytest
+from openai.types.chat import (
+    ChatCompletionAssistantMessageParam,
+    ChatCompletionMessageParam,
+    ChatCompletionToolMessageParam,
+    ChatCompletionUserMessageParam,
+)
+from openai.types.chat.chat_completion_message_tool_call_param import (
+    ChatCompletionMessageToolCallParam,
+    Function,
+)
 
 from .model import (
     ChatMessage,
@@ -117,3 +129,205 @@ async def test_chatsession_db_storage(setup_test_user, test_user_id):
                 loaded.tool_calls is not None
             ), f"Tool calls missing for {orig.role} message"
             assert len(orig.tool_calls) == len(loaded.tool_calls)
+
+
+# --------------------------------------------------------------------------- #
+#  _merge_consecutive_assistant_messages                                       #
+# --------------------------------------------------------------------------- #
+
+_tc = ChatCompletionMessageToolCallParam(
+    id="tc1", type="function", function=Function(name="do_stuff", arguments="{}")
+)
+_tc2 = ChatCompletionMessageToolCallParam(
+    id="tc2", type="function", function=Function(name="other", arguments="{}")
+)
+
+
+def test_merge_noop_when_no_consecutive_assistants():
+    """Messages without consecutive assistants are returned unchanged."""
+    msgs = [
+        ChatCompletionUserMessageParam(role="user", content="hi"),
+        ChatCompletionAssistantMessageParam(role="assistant", content="hello"),
+        ChatCompletionUserMessageParam(role="user", content="bye"),
+    ]
+    merged = ChatSession._merge_consecutive_assistant_messages(msgs)
+    assert len(merged) == 3
+    assert [m["role"] for m in merged] == ["user", "assistant", "user"]
+
+
+def test_merge_splits_text_and_tool_calls():
+    """The exact bug scenario: text-only assistant followed by tool_calls-only assistant."""
+    msgs = [
+        ChatCompletionUserMessageParam(role="user", content="build agent"),
+        ChatCompletionAssistantMessageParam(
+            role="assistant", content="Let me build that"
+        ),
+        ChatCompletionAssistantMessageParam(
+            role="assistant", content="", tool_calls=[_tc]
+        ),
+        ChatCompletionToolMessageParam(role="tool", content="ok", tool_call_id="tc1"),
+    ]
+    merged = ChatSession._merge_consecutive_assistant_messages(msgs)
+
+    assert len(merged) == 3
+    assert merged[0]["role"] == "user"
+    assert merged[2]["role"] == "tool"
+    a = cast(ChatCompletionAssistantMessageParam, merged[1])
+    assert a["role"] == "assistant"
+    assert a.get("content") == "Let me build that"
+    assert a.get("tool_calls") == [_tc]
+
+
+def test_merge_combines_tool_calls_from_both():
+    """Both consecutive assistants have tool_calls — they get merged."""
+    msgs: list[ChatCompletionAssistantMessageParam] = [
+        ChatCompletionAssistantMessageParam(
+            role="assistant", content="text", tool_calls=[_tc]
+        ),
+        ChatCompletionAssistantMessageParam(
+            role="assistant", content="", tool_calls=[_tc2]
+        ),
+    ]
+    merged = ChatSession._merge_consecutive_assistant_messages(msgs)  # type: ignore[arg-type]
+
+    assert len(merged) == 1
+    a = cast(ChatCompletionAssistantMessageParam, merged[0])
+    assert a.get("tool_calls") == [_tc, _tc2]
+    assert a.get("content") == "text"
+
+
+def test_merge_three_consecutive_assistants():
+    """Three consecutive assistants collapse into one."""
+    msgs: list[ChatCompletionAssistantMessageParam] = [
+        ChatCompletionAssistantMessageParam(role="assistant", content="a"),
+        ChatCompletionAssistantMessageParam(role="assistant", content="b"),
+        ChatCompletionAssistantMessageParam(
+            role="assistant", content="", tool_calls=[_tc]
+        ),
+    ]
+    merged = ChatSession._merge_consecutive_assistant_messages(msgs)  # type: ignore[arg-type]
+
+    assert len(merged) == 1
+    a = cast(ChatCompletionAssistantMessageParam, merged[0])
+    assert a.get("content") == "a\nb"
+    assert a.get("tool_calls") == [_tc]
+
+
+def test_merge_empty_and_single_message():
+    """Edge cases: empty list and single message."""
+    assert ChatSession._merge_consecutive_assistant_messages([]) == []
+
+    single: list[ChatCompletionMessageParam] = [
+        ChatCompletionUserMessageParam(role="user", content="hi")
+    ]
+    assert ChatSession._merge_consecutive_assistant_messages(single) == single
+
+
+# --------------------------------------------------------------------------- #
+#  add_tool_call_to_current_turn                                               #
+# --------------------------------------------------------------------------- #
+
+_raw_tc = {
+    "id": "tc1",
+    "type": "function",
+    "function": {"name": "f", "arguments": "{}"},
+}
+_raw_tc2 = {
+    "id": "tc2",
+    "type": "function",
+    "function": {"name": "g", "arguments": "{}"},
+}
+
+
+def test_add_tool_call_appends_to_existing_assistant():
+    """When the last assistant is from the current turn, tool_call is added to it."""
+    session = ChatSession.new(user_id="u")
+    session.messages = [
+        ChatMessage(role="user", content="hi"),
+        ChatMessage(role="assistant", content="working on it"),
+    ]
+    session.add_tool_call_to_current_turn(_raw_tc)
+
+    assert len(session.messages) == 2  # no new message created
+    assert session.messages[1].tool_calls == [_raw_tc]
+
+
+def test_add_tool_call_creates_assistant_when_none_exists():
+    """When there's no current-turn assistant, a new one is created."""
+    session = ChatSession.new(user_id="u")
+    session.messages = [
+        ChatMessage(role="user", content="hi"),
+    ]
+    session.add_tool_call_to_current_turn(_raw_tc)
+
+    assert len(session.messages) == 2
+    assert session.messages[1].role == "assistant"
+    assert session.messages[1].tool_calls == [_raw_tc]
+
+
+def test_add_tool_call_does_not_cross_user_boundary():
+    """A user message acts as a boundary — previous assistant is not modified."""
+    session = ChatSession.new(user_id="u")
+    session.messages = [
+        ChatMessage(role="assistant", content="old turn"),
+        ChatMessage(role="user", content="new message"),
+    ]
+    session.add_tool_call_to_current_turn(_raw_tc)
+
+    assert len(session.messages) == 3  # new assistant was created
+    assert session.messages[0].tool_calls is None  # old assistant untouched
+    assert session.messages[2].role == "assistant"
+    assert session.messages[2].tool_calls == [_raw_tc]
+
+
+def test_add_tool_call_multiple_times():
+    """Multiple long-running tool calls accumulate on the same assistant."""
+    session = ChatSession.new(user_id="u")
+    session.messages = [
+        ChatMessage(role="user", content="hi"),
+        ChatMessage(role="assistant", content="doing stuff"),
+    ]
+    session.add_tool_call_to_current_turn(_raw_tc)
+    # Simulate a pending tool result in between (like _yield_tool_call does)
+    session.messages.append(
+        ChatMessage(role="tool", content="pending", tool_call_id="tc1")
+    )
+    session.add_tool_call_to_current_turn(_raw_tc2)
+
+    assert len(session.messages) == 3  # user, assistant, tool — no extra assistant
+    assert session.messages[1].tool_calls == [_raw_tc, _raw_tc2]
+
+
+def test_to_openai_messages_merges_split_assistants():
+    """End-to-end: session with split assistants produces valid OpenAI messages."""
+    session = ChatSession.new(user_id="u")
+    session.messages = [
+        ChatMessage(role="user", content="build agent"),
+        ChatMessage(role="assistant", content="Let me build that"),
+        ChatMessage(
+            role="assistant",
+            content="",
+            tool_calls=[
+                {
+                    "id": "tc1",
+                    "type": "function",
+                    "function": {"name": "create_agent", "arguments": "{}"},
+                }
+            ],
+        ),
+        ChatMessage(role="tool", content="done", tool_call_id="tc1"),
+        ChatMessage(role="assistant", content="Saved!"),
+        ChatMessage(role="user", content="show me an example run"),
+    ]
+    openai_msgs = session.to_openai_messages()
+
+    # The two consecutive assistants at index 1,2 should be merged
+    roles = [m["role"] for m in openai_msgs]
+    assert roles == ["user", "assistant", "tool", "assistant", "user"]
+
+    # The merged assistant should have both content and tool_calls
+    merged = cast(ChatCompletionAssistantMessageParam, openai_msgs[1])
+    assert merged.get("content") == "Let me build that"
+    tc_list = merged.get("tool_calls")
+    assert tc_list is not None and len(list(tc_list)) == 1
+    assert list(tc_list)[0]["id"] == "tc1"

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

@@ -10,6 +10,8 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
+from backend.util.json import dumps as json_dumps
+
 
 class ResponseType(str, Enum):
     """Types of streaming responses following AI SDK protocol."""
@@ -18,6 +20,10 @@ class ResponseType(str, Enum):
     START = "start"
     FINISH = "finish"
 
+    # Step lifecycle (one LLM API call within a message)
+    START_STEP = "start-step"
+    FINISH_STEP = "finish-step"
+
     # Text streaming
     TEXT_START = "text-start"
     TEXT_DELTA = "text-delta"
@@ -57,6 +63,16 @@ 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."""
@@ -64,6 +80,26 @@ class StreamFinish(StreamBaseResponse):
     type: ResponseType = ResponseType.FINISH
 
 
+class StreamStartStep(StreamBaseResponse):
+    """Start of a step (one LLM API call within a message).
+
+    The AI SDK uses this to add a step-start boundary to message.parts,
+    enabling visual separation between multiple LLM calls in a single message.
+    """
+
+    type: ResponseType = ResponseType.START_STEP
+
+
+class StreamFinishStep(StreamBaseResponse):
+    """End of a step (one LLM API call within a message).
+
+    The AI SDK uses this to reset activeTextParts and activeReasoningParts,
+    so the next LLM call in a tool-call continuation starts with clean state.
+    """
+
+    type: ResponseType = ResponseType.FINISH_STEP
+
+
 # ========== Text Streaming ==========
 
 
@@ -117,7 +153,7 @@ class StreamToolOutputAvailable(StreamBaseResponse):
     type: ResponseType = ResponseType.TOOL_OUTPUT_AVAILABLE
     toolCallId: str = Field(..., description="Tool call ID this responds to")
     output: str | dict[str, Any] = Field(..., description="Tool execution output")
-    # Additional fields for internal use (not part of AI SDK spec but useful)
+    # Keep these for internal backend use
     toolName: str | None = Field(
         default=None, description="Name of the tool that was executed"
     )
@@ -125,6 +161,17 @@ class StreamToolOutputAvailable(StreamBaseResponse):
         default=True, description="Whether the tool execution succeeded"
     )
 
+    def to_sse(self) -> str:
+        """Convert to SSE format, excluding non-spec fields."""
+        import json
+
+        data = {
+            "type": self.type.value,
+            "toolCallId": self.toolCallId,
+            "output": self.output,
+        }
+        return f"data: {json.dumps(data)}\n\n"
+
 
 # ========== Other ==========
 
@@ -148,6 +195,18 @@ class StreamError(StreamBaseResponse):
         default=None, description="Additional error details"
     )
 
+    def to_sse(self) -> str:
+        """Convert to SSE format, only emitting fields required by AI SDK protocol.
+
+        The AI SDK uses z.strictObject({type, errorText}) which rejects
+        any extra fields like `code` or `details`.
+        """
+        data = {
+            "type": self.type.value,
+            "errorText": self.errorText,
+        }
+        return f"data: {json_dumps(data)}\n\n"
+
 
 class StreamHeartbeat(StreamBaseResponse):
     """Heartbeat to keep SSE connection alive during long-running operations.

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, Security
+from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
@@ -17,7 +17,29 @@ 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, StreamStart
+from .response_model import StreamFinish, StreamHeartbeat
+from .tools.models import (
+    AgentDetailsResponse,
+    AgentOutputResponse,
+    AgentPreviewResponse,
+    AgentSavedResponse,
+    AgentsFoundResponse,
+    BlockListResponse,
+    BlockOutputResponse,
+    ClarificationNeededResponse,
+    DocPageResponse,
+    DocSearchResultsResponse,
+    ErrorResponse,
+    ExecutionStartedResponse,
+    InputValidationErrorResponse,
+    NeedLoginResponse,
+    NoResultsResponse,
+    OperationInProgressResponse,
+    OperationPendingResponse,
+    OperationStartedResponse,
+    SetupRequirementsResponse,
+    UnderstandingUpdatedResponse,
+)
 
 config = ChatConfig()
 
@@ -266,12 +288,36 @@ 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,
@@ -280,14 +326,28 @@ 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():
-        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)
+        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:
             async for chunk in chat_service.stream_chat_completion(
                 session_id,
                 request.message,
@@ -295,25 +355,79 @@ 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)
 
-            # Mark task as completed
+            gen_end_time = time_module.perf_counter()
+            total_time = (gen_end_time - gen_start_time) * 1000
+            logger.info(
+                f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
+                f"task={task_id}, session={session_id}, "
+                f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "total_time_ms": total_time,
+                        "time_to_first_chunk_ms": (
+                            ttfc * 1000 if ttfc is not None else None
+                        ),
+                        "n_chunks": chunk_count,
+                    }
+                },
+            )
             await stream_registry.mark_task_completed(task_id, "completed")
         except Exception as e:
+            elapsed = time_module.perf_counter() - gen_start_time
             logger.error(
-                f"Error in background AI generation for session {session_id}: {e}"
+                f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "elapsed_ms": elapsed * 1000,
+                        "error": str(e),
+                    }
+                },
             )
             await stream_registry.mark_task_completed(task_id, "failed")
 
     # Start the AI generation in a background task
     bg_task = asyncio.create_task(run_ai_generation())
     await stream_registry.set_task_asyncio_task(task_id, bg_task)
+    setup_time = (time.perf_counter() - stream_start_time) * 1000
+    logger.info(
+        f"[TIMING] Background task started, setup={setup_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
+    )
 
     # SSE endpoint that subscribes to the task's stream
     async def event_generator() -> AsyncGenerator[str, None]:
+        import time as time_module
+
+        event_gen_start = time_module.perf_counter()
+        logger.info(
+            f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
+            f"user={user_id}",
+            extra={"json_fields": log_meta},
+        )
         subscriber_queue = None
+        first_chunk_yielded = False
+        chunks_yielded = 0
         try:
             # Subscribe to the task stream (this replays existing messages + live updates)
             subscriber_queue = await stream_registry.subscribe_to_task(
@@ -328,22 +442,70 @@ 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:
-            logger.error(f"Error in SSE stream for task {task_id}: {e}")
+            elapsed = (time_module.perf_counter() - event_gen_start) * 1000
+            logger.error(
+                f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
+                extra={
+                    "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
+                },
+            )
         finally:
             # Unsubscribe when client disconnects or stream ends to prevent resource leak
             if subscriber_queue is not None:
@@ -357,6 +519,18 @@ 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(
@@ -374,63 +548,90 @@ async def stream_chat_post(
 @router.get(
     "/sessions/{session_id}/stream",
 )
-async def stream_chat_get(
+async def resume_session_stream(
     session_id: str,
-    message: Annotated[str, Query(min_length=1, max_length=10000)],
     user_id: str | None = Depends(auth.get_user_id),
-    is_user_message: bool = Query(default=True),
 ):
     """
-    Stream chat responses for a session (GET - legacy endpoint).
+    Resume an active stream for a session.
 
-    Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
-      - Text fragments as they are generated
-      - Tool call UI elements (if invoked)
-      - Tool execution results
+    Called by the AI SDK's ``useChat(resume: true)`` on page load.
+    Checks for an active (in-progress) task on the session and either replays
+    the full SSE stream or returns 204 No Content if nothing is running.
 
     Args:
-        session_id: The chat session identifier to associate with the streamed messages.
-        message: The user's new message to process.
+        session_id: The chat session identifier.
         user_id: Optional authenticated user ID.
-        is_user_message: Whether the message is a user message.
-    Returns:
-        StreamingResponse: SSE-formatted response chunks.
 
+    Returns:
+        StreamingResponse (SSE) when an active stream exists,
+        or 204 No Content when there is nothing to resume.
     """
-    session = await _validate_and_get_session(session_id, user_id)
+    import asyncio
+
+    active_task, _last_id = await stream_registry.get_active_task_for_session(
+        session_id, user_id
+    )
+
+    if not active_task:
+        return Response(status_code=204)
+
+    subscriber_queue = await stream_registry.subscribe_to_task(
+        task_id=active_task.task_id,
+        user_id=user_id,
+        last_message_id="0-0",  # Full replay so useChat rebuilds the message
+    )
+
+    if subscriber_queue is None:
+        return Response(status_code=204)
 
     async def event_generator() -> AsyncGenerator[str, None]:
         chunk_count = 0
         first_chunk_type: str | None = None
-        async for chunk in chat_service.stream_chat_completion(
-            session_id,
-            message,
-            is_user_message=is_user_message,
-            user_id=user_id,
-            session=session,  # Pass pre-fetched session to avoid double-fetch
-        ):
-            if chunk_count < 3:
-                logger.info(
-                    "Chat stream chunk",
-                    extra={
-                        "session_id": session_id,
-                        "chunk_type": str(chunk.type),
-                    },
+        try:
+            while True:
+                try:
+                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+                    if chunk_count < 3:
+                        logger.info(
+                            "Resume stream chunk",
+                            extra={
+                                "session_id": session_id,
+                                "chunk_type": str(chunk.type),
+                            },
+                        )
+                    if not first_chunk_type:
+                        first_chunk_type = str(chunk.type)
+                    chunk_count += 1
+                    yield chunk.to_sse()
+
+                    if isinstance(chunk, StreamFinish):
+                        break
+                except asyncio.TimeoutError:
+                    yield StreamHeartbeat().to_sse()
+        except GeneratorExit:
+            pass
+        except Exception as e:
+            logger.error(f"Error in resume stream for session {session_id}: {e}")
+        finally:
+            try:
+                await stream_registry.unsubscribe_from_task(
+                    active_task.task_id, subscriber_queue
                 )
-            if not first_chunk_type:
-                first_chunk_type = str(chunk.type)
-            chunk_count += 1
-            yield chunk.to_sse()
-        logger.info(
-            "Chat stream completed",
-            extra={
-                "session_id": session_id,
-                "chunk_count": chunk_count,
-                "first_chunk_type": first_chunk_type,
-            },
-        )
-        # AI SDK protocol termination
-        yield "data: [DONE]\n\n"
+            except Exception as unsub_err:
+                logger.error(
+                    f"Error unsubscribing from task {active_task.task_id}: {unsub_err}",
+                    exc_info=True,
+                )
+            logger.info(
+                "Resume stream completed",
+                extra={
+                    "session_id": session_id,
+                    "n_chunks": chunk_count,
+                    "first_chunk_type": first_chunk_type,
+                },
+            )
+            yield "data: [DONE]\n\n"
 
     return StreamingResponse(
         event_generator(),
@@ -438,8 +639,8 @@ async def stream_chat_get(
         headers={
             "Cache-Control": "no-cache",
             "Connection": "keep-alive",
-            "X-Accel-Buffering": "no",  # Disable nginx buffering
-            "x-vercel-ai-ui-message-stream": "v1",  # AI SDK protocol header
+            "X-Accel-Buffering": "no",
+            "x-vercel-ai-ui-message-stream": "v1",
         },
     )
 
@@ -751,3 +952,42 @@ async def health_check() -> dict:
         "service": "chat",
         "version": "0.1.0",
     }
+
+
+# ========== Schema Export (for OpenAPI / Orval codegen) ==========
+
+ToolResponseUnion = (
+    AgentsFoundResponse
+    | NoResultsResponse
+    | AgentDetailsResponse
+    | SetupRequirementsResponse
+    | ExecutionStartedResponse
+    | NeedLoginResponse
+    | ErrorResponse
+    | InputValidationErrorResponse
+    | AgentOutputResponse
+    | UnderstandingUpdatedResponse
+    | AgentPreviewResponse
+    | AgentSavedResponse
+    | ClarificationNeededResponse
+    | BlockListResponse
+    | BlockOutputResponse
+    | DocSearchResultsResponse
+    | DocPageResponse
+    | OperationStartedResponse
+    | OperationPendingResponse
+    | OperationInProgressResponse
+)
+
+
+@router.get(
+    "/schema/tool-responses",
+    response_model=ToolResponseUnion,
+    include_in_schema=True,
+    summary="[Dummy] Tool response type export for codegen",
+    description="This endpoint is not meant to be called. It exists solely to "
+    "expose tool response models in the OpenAPI schema for frontend codegen.",
+)
+async def _tool_response_schema() -> ToolResponseUnion:  # type: ignore[return]
+    """Never called at runtime. Exists only so Orval generates TS types."""
+    raise HTTPException(status_code=501, detail="Schema-only endpoint")

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

@@ -52,8 +52,10 @@ from .response_model import (
     StreamBaseResponse,
     StreamError,
     StreamFinish,
+    StreamFinishStep,
     StreamHeartbeat,
     StreamStart,
+    StreamStartStep,
     StreamTextDelta,
     StreamTextEnd,
     StreamTextStart,
@@ -351,6 +353,10 @@ async def stream_chat_completion(
     retry_count: int = 0,
     session: ChatSession | None = None,
     context: dict[str, str] | None = None,  # {url: str, content: str}
+    _continuation_message_id: (
+        str | None
+    ) = None,  # Internal: reuse message ID for tool call continuations
+    _task_id: str | None = None,  # Internal: task ID for SSE reconnection support
 ) -> AsyncGenerator[StreamBaseResponse, None]:
     """Main entry point for streaming chat completions with database handling.
 
@@ -371,21 +377,45 @@ async def stream_chat_completion(
         ValueError: If max_context_messages is exceeded
 
     """
+    completion_start = time.monotonic()
+
+    # Build log metadata for structured logging
+    log_meta = {"component": "ChatService", "session_id": session_id}
+    if user_id:
+        log_meta["user_id"] = user_id
+
     logger.info(
-        f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
+        f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
+        f"message_len={len(message) if message else 0}, is_user={is_user_message}",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "message_len": len(message) if message else 0,
+                "is_user_message": is_user_message,
+            }
+        },
     )
 
     # Only fetch from Redis if session not provided (initial call)
     if session is None:
+        fetch_start = time.monotonic()
         session = await get_chat_session(session_id, user_id)
+        fetch_time = (time.monotonic() - fetch_start) * 1000
         logger.info(
-            f"Fetched session from Redis: {session.session_id if session else 'None'}, "
-            f"message_count={len(session.messages) if session else 0}"
+            f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
+            f"n_messages={len(session.messages) if session else 0}",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "duration_ms": fetch_time,
+                    "n_messages": len(session.messages) if session else 0,
+                }
+            },
         )
     else:
         logger.info(
-            f"Using provided session object: {session.session_id}, "
-            f"message_count={len(session.messages)}"
+            f"[TIMING] Using provided session, messages={len(session.messages)}",
+            extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
         )
 
     if not session:
@@ -406,17 +436,25 @@ async def stream_chat_completion(
 
         # Track user message in PostHog
         if is_user_message:
+            posthog_start = time.monotonic()
             track_user_message(
                 user_id=user_id,
                 session_id=session_id,
                 message_length=len(message),
             )
+            posthog_time = (time.monotonic() - posthog_start) * 1000
+            logger.info(
+                f"[TIMING] track_user_message took {posthog_time:.1f}ms",
+                extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
+            )
 
-    logger.info(
-        f"Upserting session: {session.session_id} with user id {session.user_id}, "
-        f"message_count={len(session.messages)}"
-    )
+    upsert_start = time.monotonic()
     session = await upsert_chat_session(session)
+    upsert_time = (time.monotonic() - upsert_start) * 1000
+    logger.info(
+        f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
+    )
     assert session, "Session not found"
 
     # Generate title for new sessions on first user message (non-blocking)
@@ -454,7 +492,13 @@ async def stream_chat_completion(
             asyncio.create_task(_update_title())
 
     # Build system prompt with business understanding
+    prompt_start = time.monotonic()
     system_prompt, understanding = await _build_system_prompt(user_id)
+    prompt_time = (time.monotonic() - prompt_start) * 1000
+    logger.info(
+        f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
+    )
 
     # Initialize variables for streaming
     assistant_response = ChatMessage(
@@ -479,13 +523,27 @@ async def stream_chat_completion(
     # Generate unique IDs for AI SDK protocol
     import uuid as uuid_module
 
-    message_id = str(uuid_module.uuid4())
+    is_continuation = _continuation_message_id is not None
+    message_id = _continuation_message_id or str(uuid_module.uuid4())
     text_block_id = str(uuid_module.uuid4())
 
-    # Yield message start
-    yield StreamStart(messageId=message_id)
+    # Only yield message start for the initial call, not for continuations.
+    setup_time = (time.monotonic() - completion_start) * 1000
+    logger.info(
+        f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
+    )
+    if not is_continuation:
+        yield StreamStart(messageId=message_id, taskId=_task_id)
+
+    # Emit start-step before each LLM call (AI SDK uses this to add step boundaries)
+    yield StreamStartStep()
 
     try:
+        logger.info(
+            "[TIMING] Calling _stream_chat_chunks",
+            extra={"json_fields": log_meta},
+        )
         async for chunk in _stream_chat_chunks(
             session=session,
             tools=tools,
@@ -585,6 +643,10 @@ async def stream_chat_completion(
                     )
                 yield chunk
             elif isinstance(chunk, StreamFinish):
+                if has_done_tool_call:
+                    # Tool calls happened — close the step but don't send message-level finish.
+                    # The continuation will open a new step, and finish will come at the end.
+                    yield StreamFinishStep()
                 if not has_done_tool_call:
                     # Emit text-end before finish if we received text but haven't closed it
                     if has_received_text and not text_streaming_ended:
@@ -616,6 +678,8 @@ async def stream_chat_completion(
                             has_saved_assistant_message = True
 
                     has_yielded_end = True
+                    # Emit finish-step before finish (resets AI SDK text/reasoning state)
+                    yield StreamFinishStep()
                     yield chunk
             elif isinstance(chunk, StreamError):
                 has_yielded_error = True
@@ -665,6 +729,10 @@ async def stream_chat_completion(
             logger.info(
                 f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
             )
+            # Close the current step before retrying so the recursive call's
+            # StreamStartStep doesn't produce unbalanced step events.
+            if not has_yielded_end:
+                yield StreamFinishStep()
             should_retry = True
         else:
             # Non-retryable error or max retries exceeded
@@ -700,6 +768,7 @@ async def stream_chat_completion(
                 error_response = StreamError(errorText=error_message)
                 yield error_response
             if not has_yielded_end:
+                yield StreamFinishStep()
                 yield StreamFinish()
             return
 
@@ -714,6 +783,8 @@ async def stream_chat_completion(
             retry_count=retry_count + 1,
             session=session,
             context=context,
+            _continuation_message_id=message_id,  # Reuse message ID since start was already sent
+            _task_id=_task_id,
         ):
             yield chunk
         return  # Exit after retry to avoid double-saving in finally block
@@ -729,9 +800,13 @@ async def stream_chat_completion(
         # Build the messages list in the correct order
         messages_to_save: list[ChatMessage] = []
 
-        # Add assistant message with tool_calls if any
+        # Add assistant message with tool_calls if any.
+        # Use extend (not assign) to preserve tool_calls already added by
+        # _yield_tool_call for long-running tools.
         if accumulated_tool_calls:
-            assistant_response.tool_calls = accumulated_tool_calls
+            if not assistant_response.tool_calls:
+                assistant_response.tool_calls = []
+            assistant_response.tool_calls.extend(accumulated_tool_calls)
             logger.info(
                 f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
             )
@@ -783,6 +858,8 @@ async def stream_chat_completion(
             session=session,  # Pass session object to avoid Redis refetch
             context=context,
             tool_call_response=str(tool_response_messages),
+            _continuation_message_id=message_id,  # Reuse message ID to avoid duplicates
+            _task_id=_task_id,
         ):
             yield chunk
 
@@ -893,9 +970,21 @@ async def _stream_chat_chunks(
         SSE formatted JSON response objects
 
     """
+    import time as time_module
+
+    stream_chunks_start = time_module.perf_counter()
     model = config.model
 
-    logger.info("Starting pure chat stream")
+    # Build log metadata for structured logging
+    log_meta = {"component": "ChatService", "session_id": session.session_id}
+    if session.user_id:
+        log_meta["user_id"] = session.user_id
+
+    logger.info(
+        f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
+        f"user={session.user_id}, n_messages={len(session.messages)}",
+        extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
+    )
 
     messages = session.to_openai_messages()
     if system_prompt:
@@ -906,12 +995,18 @@ 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:
@@ -946,9 +1041,19 @@ async def _stream_chat_chunks(
 
         while retry_count <= MAX_RETRIES:
             try:
+                elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
+                retry_info = (
+                    f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
+                )
                 logger.info(
-                    f"Creating OpenAI chat completion stream..."
-                    f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
+                    f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "elapsed_ms": elapsed,
+                            "retry_count": retry_count,
+                        }
+                    },
                 )
 
                 # Build extra_body for OpenRouter tracing and PostHog analytics
@@ -965,6 +1070,11 @@ 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),
@@ -974,6 +1084,11 @@ async def _stream_chat_chunks(
                     stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
                     extra_body=extra_body,
                 )
+                api_init_time = (time_module.perf_counter() - api_call_start) * 1000
+                logger.info(
+                    f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
+                    extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
+                )
 
                 # Variables to accumulate tool calls
                 tool_calls: list[dict[str, Any]] = []
@@ -984,10 +1099,13 @@ async def _stream_chat_chunks(
 
                 # Track if we've started the text block
                 text_started = False
+                first_content_chunk = True
+                chunk_count = 0
 
                 # Process the stream
                 chunk: ChatCompletionChunk
                 async for chunk in stream:
+                    chunk_count += 1
                     if chunk.usage:
                         yield StreamUsage(
                             promptTokens=chunk.usage.prompt_tokens,
@@ -1010,6 +1128,23 @@ async def _stream_chat_chunks(
                             if not text_started and text_block_id:
                                 yield StreamTextStart(id=text_block_id)
                                 text_started = True
+                            # Log timing for first content chunk
+                            if first_content_chunk:
+                                first_content_chunk = False
+                                ttfc = (
+                                    time_module.perf_counter() - api_call_start
+                                ) * 1000
+                                logger.info(
+                                    f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
+                                    f"(since API call), n_chunks={chunk_count}",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "time_to_first_chunk_ms": ttfc,
+                                            "n_chunks": chunk_count,
+                                        }
+                                    },
+                                )
                             # Stream the text delta
                             text_response = StreamTextDelta(
                                 id=text_block_id or "",
@@ -1066,7 +1201,21 @@ async def _stream_chat_chunks(
                                         toolName=tool_calls[idx]["function"]["name"],
                                     )
                                     emitted_start_for_idx.add(idx)
-                logger.info(f"Stream complete. Finish reason: {finish_reason}")
+                stream_duration = time_module.perf_counter() - api_call_start
+                logger.info(
+                    f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
+                    f"duration={stream_duration:.2f}s, "
+                    f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "stream_duration_ms": stream_duration * 1000,
+                            "finish_reason": finish_reason,
+                            "n_chunks": chunk_count,
+                            "n_tool_calls": len(tool_calls),
+                        }
+                    },
+                )
 
                 # Yield all accumulated tool calls after the stream is complete
                 # This ensures all tool call arguments have been fully received
@@ -1086,6 +1235,12 @@ async def _stream_chat_chunks(
                         # Re-raise to trigger retry logic in the parent function
                         raise
 
+                total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
+                logger.info(
+                    f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
+                    f"session={session.session_id}, user={session.user_id}",
+                    extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
+                )
                 yield StreamFinish()
                 return
             except Exception as e:
@@ -1253,13 +1408,9 @@ async def _yield_tool_call(
                 operation_id=operation_id,
             )
 
-            # Save assistant message with tool_call FIRST (required by LLM)
-            assistant_message = ChatMessage(
-                role="assistant",
-                content="",
-                tool_calls=[tool_calls[yield_idx]],
-            )
-            session.messages.append(assistant_message)
+            # Attach the tool_call to the current turn's assistant message
+            # (or create one if this is a tool-only response with no text).
+            session.add_tool_call_to_current_turn(tool_calls[yield_idx])
 
             # Then save pending tool result
             pending_message = ChatMessage(
@@ -1565,6 +1716,7 @@ 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(
@@ -1681,6 +1833,10 @@ 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
@@ -1811,6 +1967,10 @@ 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
 
@@ -1822,6 +1982,7 @@ 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
@@ -1845,6 +2006,7 @@ 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
@@ -1886,4 +2048,5 @@ 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

@@ -104,6 +104,24 @@ 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,
@@ -114,10 +132,18 @@ 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={
@@ -131,12 +157,22 @@ 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)
 
-    logger.debug(f"Created task {task_id} for session {session_id}")
+    total_time = (time.perf_counter() - start_time) * 1000
+    logger.info(
+        f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
+        extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
+    )
 
     return task
 
@@ -156,26 +192,60 @@ 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"Failed to publish chunk for task {task_id}: {e}",
+            f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}",
+            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
             exc_info=True,
         )
 
@@ -200,24 +270,61 @@ 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:
-        logger.debug(f"Task {task_id} not found in Redis")
+        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.info(
+            f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "elapsed_ms": elapsed,
+                    "reason": "task_not_found",
+                }
+            },
+        )
         return None
 
     # Note: Redis client uses decode_responses=True, so keys are strings
     task_status = meta.get("status", "")
     task_user_id = meta.get("user_id", "") or None
+    log_meta["session_id"] = meta.get("session_id", "")
 
     # Validate ownership - if task has an owner, requester must match
     if task_user_id:
         if user_id != task_user_id:
             logger.warning(
-                f"User {user_id} denied access to task {task_id} "
-                f"owned by {task_user_id}"
+                f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "task_owner": task_user_id,
+                        "reason": "access_denied",
+                    }
+                },
             )
             return None
 
@@ -225,7 +332,19 @@ 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
@@ -244,19 +363,48 @@ async def subscribe_to_task(
                     except Exception as e:
                         logger.warning(f"Failed to replay message: {e}")
 
-    logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
+    logger.info(
+        f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "n_messages_replayed": replayed_count,
+                "replay_last_id": replay_last_id,
+            }
+        },
+    )
 
     # Step 2: If task is still running, start stream listener for live updates
     if task_status == "running":
+        logger.info(
+            "[TIMING] Task still running, starting _stream_listener",
+            extra={"json_fields": {**log_meta, "task_status": task_status}},
+        )
         listener_task = asyncio.create_task(
-            _stream_listener(task_id, subscriber_queue, replay_last_id)
+            _stream_listener(task_id, subscriber_queue, replay_last_id, log_meta)
         )
         # Track listener task for cleanup on unsubscribe
         _listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
     else:
         # Task is completed/failed - add finish marker
+        logger.info(
+            f"[TIMING] Task already {task_status}, adding StreamFinish",
+            extra={"json_fields": {**log_meta, "task_status": task_status}},
+        )
         await subscriber_queue.put(StreamFinish())
 
+    total_time = (time.perf_counter() - start_time) * 1000
+    logger.info(
+        f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
+        f"n_messages_replayed={replayed_count}",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "total_time_ms": total_time,
+                "n_messages_replayed": replayed_count,
+            }
+        },
+    )
     return subscriber_queue
 
 
@@ -264,6 +412,7 @@ 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.
 
@@ -274,10 +423,27 @@ 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()
@@ -287,9 +453,39 @@ 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
@@ -326,10 +522,30 @@ 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"Subscriber queue full for task {task_id}, "
-                                    f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
+                                    f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "timeout_s": QUEUE_PUT_TIMEOUT,
+                                            "reason": "queue_full",
+                                        }
+                                    },
                                 )
                                 # Send overflow error with recovery info
                                 try:
@@ -351,15 +567,44 @@ 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(f"Error processing stream message: {e}")
+                        logger.warning(
+                            f"Error processing stream message: {e}",
+                            extra={"json_fields": {**log_meta, "error": str(e)}},
+                        )
 
     except asyncio.CancelledError:
-        logger.debug(f"Stream listener cancelled for task {task_id}")
+        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.info(
+            f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "elapsed_ms": elapsed,
+                    "messages_delivered": messages_delivered,
+                    "reason": "cancelled",
+                }
+            },
+        )
         raise  # Re-raise to propagate cancellation
     except Exception as e:
-        logger.error(f"Stream listener error for task {task_id}: {e}")
+        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.error(
+            f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}",
+            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
+        )
         # On error, send finish to unblock subscriber
         try:
             await asyncio.wait_for(
@@ -368,10 +613,24 @@ async def _stream_listener(
             )
         except (asyncio.TimeoutError, asyncio.QueueFull):
             logger.warning(
-                f"Could not deliver finish event for task {task_id} after error"
+                "Could not deliver finish event after error",
+                extra={"json_fields": log_meta},
             )
     finally:
         # Clean up listener task mapping on exit
+        total_time = (time.perf_counter() - start_time) * 1000
+        logger.info(
+            f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
+            f"delivered={messages_delivered}, xread_count={xread_count}",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "total_time_ms": total_time,
+                    "messages_delivered": messages_delivered,
+                    "xread_count": xread_count,
+                }
+            },
+        )
         _listener_tasks.pop(queue_id, None)
 
 
@@ -598,8 +857,10 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
         ResponseType,
         StreamError,
         StreamFinish,
+        StreamFinishStep,
         StreamHeartbeat,
         StreamStart,
+        StreamStartStep,
         StreamTextDelta,
         StreamTextEnd,
         StreamTextStart,
@@ -613,6 +874,8 @@ 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

@@ -13,10 +13,32 @@ from backend.api.features.chat.tools.models import (
     NoResultsResponse,
 )
 from backend.api.features.store.hybrid_search import unified_hybrid_search
-from backend.data.block import get_block
+from backend.data.block import BlockType, get_block
 
 logger = logging.getLogger(__name__)
 
+_TARGET_RESULTS = 10
+# Over-fetch to compensate for post-hoc filtering of graph-only blocks.
+# 40 is 2x current removed; speed of query 10 vs 40 is minimial
+_OVERFETCH_PAGE_SIZE = 40
+
+# Block types that only work within graphs and cannot run standalone in CoPilot.
+COPILOT_EXCLUDED_BLOCK_TYPES = {
+    BlockType.INPUT,  # Graph interface definition - data enters via chat, not graph inputs
+    BlockType.OUTPUT,  # Graph interface definition - data exits via chat, not graph outputs
+    BlockType.WEBHOOK,  # Wait for external events - would hang forever in CoPilot
+    BlockType.WEBHOOK_MANUAL,  # Same as WEBHOOK
+    BlockType.NOTE,  # Visual annotation only - no runtime behavior
+    BlockType.HUMAN_IN_THE_LOOP,  # Pauses for human approval - CoPilot IS human-in-the-loop
+    BlockType.AGENT,  # AgentExecutorBlock requires execution_context - use run_agent tool
+}
+
+# Specific block IDs excluded from CoPilot (STANDARD type but still require graph context)
+COPILOT_EXCLUDED_BLOCK_IDS = {
+    # SmartDecisionMakerBlock - dynamically discovers downstream blocks via graph topology
+    "3b191d9f-356f-482d-8238-ba04b6d18381",
+}
+
 
 class FindBlockTool(BaseTool):
     """Tool for searching available blocks."""
@@ -88,7 +110,7 @@ class FindBlockTool(BaseTool):
                 query=query,
                 content_types=[ContentType.BLOCK],
                 page=1,
-                page_size=10,
+                page_size=_OVERFETCH_PAGE_SIZE,
             )
 
             if not results:
@@ -108,60 +130,90 @@ class FindBlockTool(BaseTool):
                 block = get_block(block_id)
 
                 # Skip disabled blocks
-                if block and not block.disabled:
-                    # Get input/output schemas
-                    input_schema = {}
-                    output_schema = {}
-                    try:
-                        input_schema = block.input_schema.jsonschema()
-                    except Exception:
-                        pass
-                    try:
-                        output_schema = block.output_schema.jsonschema()
-                    except Exception:
-                        pass
+                if not block or block.disabled:
+                    continue
 
-                    # Get categories from block instance
-                    categories = []
-                    if hasattr(block, "categories") and block.categories:
-                        categories = [cat.value for cat in block.categories]
+                # Skip blocks excluded from CoPilot (graph-only blocks)
+                if (
+                    block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
+                    or block.id in COPILOT_EXCLUDED_BLOCK_IDS
+                ):
+                    continue
 
-                    # Extract required inputs for easier use
-                    required_inputs: list[BlockInputFieldInfo] = []
-                    if input_schema:
-                        properties = input_schema.get("properties", {})
-                        required_fields = set(input_schema.get("required", []))
-                        # Get credential field names to exclude from required inputs
-                        credentials_fields = set(
-                            block.input_schema.get_credentials_fields().keys()
-                        )
-
-                        for field_name, field_schema in properties.items():
-                            # Skip credential fields - they're handled separately
-                            if field_name in credentials_fields:
-                                continue
-
-                            required_inputs.append(
-                                BlockInputFieldInfo(
-                                    name=field_name,
-                                    type=field_schema.get("type", "string"),
-                                    description=field_schema.get("description", ""),
-                                    required=field_name in required_fields,
-                                    default=field_schema.get("default"),
-                                )
-                            )
-
-                    blocks.append(
-                        BlockInfoSummary(
-                            id=block_id,
-                            name=block.name,
-                            description=block.description or "",
-                            categories=categories,
-                            input_schema=input_schema,
-                            output_schema=output_schema,
-                            required_inputs=required_inputs,
-                        )
+                # Get input/output schemas
+                input_schema = {}
+                output_schema = {}
+                try:
+                    input_schema = block.input_schema.jsonschema()
+                except Exception as e:
+                    logger.debug(
+                        "Failed to generate input schema for block %s: %s",
+                        block_id,
+                        e,
                     )
+                try:
+                    output_schema = block.output_schema.jsonschema()
+                except Exception as e:
+                    logger.debug(
+                        "Failed to generate output schema for block %s: %s",
+                        block_id,
+                        e,
+                    )
+
+                # Get categories from block instance
+                categories = []
+                if hasattr(block, "categories") and block.categories:
+                    categories = [cat.value for cat in block.categories]
+
+                # Extract required inputs for easier use
+                required_inputs: list[BlockInputFieldInfo] = []
+                if input_schema:
+                    properties = input_schema.get("properties", {})
+                    required_fields = set(input_schema.get("required", []))
+                    # Get credential field names to exclude from required inputs
+                    credentials_fields = set(
+                        block.input_schema.get_credentials_fields().keys()
+                    )
+
+                    for field_name, field_schema in properties.items():
+                        # Skip credential fields - they're handled separately
+                        if field_name in credentials_fields:
+                            continue
+
+                        required_inputs.append(
+                            BlockInputFieldInfo(
+                                name=field_name,
+                                type=field_schema.get("type", "string"),
+                                description=field_schema.get("description", ""),
+                                required=field_name in required_fields,
+                                default=field_schema.get("default"),
+                            )
+                        )
+
+                blocks.append(
+                    BlockInfoSummary(
+                        id=block_id,
+                        name=block.name,
+                        description=block.description or "",
+                        categories=categories,
+                        input_schema=input_schema,
+                        output_schema=output_schema,
+                        required_inputs=required_inputs,
+                    )
+                )
+
+                if len(blocks) >= _TARGET_RESULTS:
+                    break
+
+            if blocks and len(blocks) < _TARGET_RESULTS:
+                logger.debug(
+                    "find_block returned %d/%d results for query '%s' "
+                    "(filtered %d excluded/disabled blocks)",
+                    len(blocks),
+                    _TARGET_RESULTS,
+                    query,
+                    len(results) - len(blocks),
+                )
 
             if not blocks:
                 return NoResultsResponse(

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

@@ -0,0 +1,139 @@
+"""Tests for block filtering in FindBlockTool."""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from backend.api.features.chat.tools.find_block import (
+    COPILOT_EXCLUDED_BLOCK_IDS,
+    COPILOT_EXCLUDED_BLOCK_TYPES,
+    FindBlockTool,
+)
+from backend.api.features.chat.tools.models import BlockListResponse
+from backend.data.block import BlockType
+
+from ._test_data import make_session
+
+_TEST_USER_ID = "test-user-find-block"
+
+
+def make_mock_block(
+    block_id: str, name: str, block_type: BlockType, disabled: bool = False
+):
+    """Create a mock block for testing."""
+    mock = MagicMock()
+    mock.id = block_id
+    mock.name = name
+    mock.description = f"{name} description"
+    mock.block_type = block_type
+    mock.disabled = disabled
+    mock.input_schema = MagicMock()
+    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
+    mock.input_schema.get_credentials_fields.return_value = {}
+    mock.output_schema = MagicMock()
+    mock.output_schema.jsonschema.return_value = {}
+    mock.categories = []
+    return mock
+
+
+class TestFindBlockFiltering:
+    """Tests for block filtering in FindBlockTool."""
+
+    def test_excluded_block_types_contains_expected_types(self):
+        """Verify COPILOT_EXCLUDED_BLOCK_TYPES contains all graph-only types."""
+        assert BlockType.INPUT in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.OUTPUT in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.WEBHOOK in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.WEBHOOK_MANUAL in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.NOTE in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.HUMAN_IN_THE_LOOP in COPILOT_EXCLUDED_BLOCK_TYPES
+        assert BlockType.AGENT in COPILOT_EXCLUDED_BLOCK_TYPES
+
+    def test_excluded_block_ids_contains_smart_decision_maker(self):
+        """Verify SmartDecisionMakerBlock is in COPILOT_EXCLUDED_BLOCK_IDS."""
+        assert "3b191d9f-356f-482d-8238-ba04b6d18381" in COPILOT_EXCLUDED_BLOCK_IDS
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_type_filtered_from_results(self):
+        """Verify blocks with excluded BlockTypes are filtered from search results."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        # Mock search returns an INPUT block (excluded) and a STANDARD block (included)
+        search_results = [
+            {"content_id": "input-block-id", "score": 0.9},
+            {"content_id": "standard-block-id", "score": 0.8},
+        ]
+
+        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
+        standard_block = make_mock_block(
+            "standard-block-id", "HTTP Request", BlockType.STANDARD
+        )
+
+        def mock_get_block(block_id):
+            return {
+                "input-block-id": input_block,
+                "standard-block-id": standard_block,
+            }.get(block_id)
+
+        with patch(
+            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
+            new_callable=AsyncMock,
+            return_value=(search_results, 2),
+        ):
+            with patch(
+                "backend.api.features.chat.tools.find_block.get_block",
+                side_effect=mock_get_block,
+            ):
+                tool = FindBlockTool()
+                response = await tool._execute(
+                    user_id=_TEST_USER_ID, session=session, query="test"
+                )
+
+        # Should only return the standard block, not the INPUT block
+        assert isinstance(response, BlockListResponse)
+        assert len(response.blocks) == 1
+        assert response.blocks[0].id == "standard-block-id"
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_id_filtered_from_results(self):
+        """Verify SmartDecisionMakerBlock is filtered from search results."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
+        search_results = [
+            {"content_id": smart_decision_id, "score": 0.9},
+            {"content_id": "normal-block-id", "score": 0.8},
+        ]
+
+        # SmartDecisionMakerBlock has STANDARD type but is excluded by ID
+        smart_block = make_mock_block(
+            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
+        )
+        normal_block = make_mock_block(
+            "normal-block-id", "Normal Block", BlockType.STANDARD
+        )
+
+        def mock_get_block(block_id):
+            return {
+                smart_decision_id: smart_block,
+                "normal-block-id": normal_block,
+            }.get(block_id)
+
+        with patch(
+            "backend.api.features.chat.tools.find_block.unified_hybrid_search",
+            new_callable=AsyncMock,
+            return_value=(search_results, 2),
+        ):
+            with patch(
+                "backend.api.features.chat.tools.find_block.get_block",
+                side_effect=mock_get_block,
+            ):
+                tool = FindBlockTool()
+                response = await tool._execute(
+                    user_id=_TEST_USER_ID, session=session, query="decision"
+                )
+
+        # Should only return normal block, not SmartDecisionMakerBlock
+        assert isinstance(response, BlockListResponse)
+        assert len(response.blocks) == 1
+        assert response.blocks[0].id == "normal-block-id"

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

@@ -0,0 +1,29 @@
+"""Shared helpers for chat tools."""
+
+from typing import Any
+
+
+def get_inputs_from_schema(
+    input_schema: dict[str, Any],
+    exclude_fields: set[str] | None = None,
+) -> list[dict[str, Any]]:
+    """Extract input field info from JSON schema."""
+    if not isinstance(input_schema, dict):
+        return []
+
+    exclude = exclude_fields or set()
+    properties = input_schema.get("properties", {})
+    required = set(input_schema.get("required", []))
+
+    return [
+        {
+            "name": name,
+            "title": schema.get("title", name),
+            "type": schema.get("type", "string"),
+            "description": schema.get("description", ""),
+            "required": name in required,
+            "default": schema.get("default"),
+        }
+        for name, schema in properties.items()
+        if name not in exclude
+    ]

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

@@ -24,6 +24,7 @@ from backend.util.timezone_utils import (
 )
 
 from .base import BaseTool
+from .helpers import get_inputs_from_schema
 from .models import (
     AgentDetails,
     AgentDetailsResponse,
@@ -261,7 +262,7 @@ class RunAgentTool(BaseTool):
                         ),
                         requirements={
                             "credentials": requirements_creds_list,
-                            "inputs": self._get_inputs_list(graph.input_schema),
+                            "inputs": get_inputs_from_schema(graph.input_schema),
                             "execution_modes": self._get_execution_modes(graph),
                         },
                     ),
@@ -369,22 +370,6 @@ class RunAgentTool(BaseTool):
                 session_id=session_id,
             )
 
-    def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]:
-        """Extract inputs list from schema."""
-        inputs_list = []
-        if isinstance(input_schema, dict) and "properties" in input_schema:
-            for field_name, field_schema in input_schema["properties"].items():
-                inputs_list.append(
-                    {
-                        "name": field_name,
-                        "title": field_schema.get("title", field_name),
-                        "type": field_schema.get("type", "string"),
-                        "description": field_schema.get("description", ""),
-                        "required": field_name in input_schema.get("required", []),
-                    }
-                )
-        return inputs_list
-
     def _get_execution_modes(self, graph: GraphModel) -> list[str]:
         """Get available execution modes for the graph."""
         trigger_info = graph.trigger_setup_info
@@ -398,7 +383,7 @@ class RunAgentTool(BaseTool):
         suffix: str,
     ) -> str:
         """Build a message describing available inputs for an agent."""
-        inputs_list = self._get_inputs_list(graph.input_schema)
+        inputs_list = get_inputs_from_schema(graph.input_schema)
         required_names = [i["name"] for i in inputs_list if i["required"]]
         optional_names = [i["name"] for i in inputs_list if not i["required"]]
 

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

@@ -8,14 +8,19 @@ from typing import Any
 from pydantic_core import PydanticUndefined
 
 from backend.api.features.chat.model import ChatSession
-from backend.data.block import get_block
+from backend.api.features.chat.tools.find_block import (
+    COPILOT_EXCLUDED_BLOCK_IDS,
+    COPILOT_EXCLUDED_BLOCK_TYPES,
+)
+from backend.data.block import AnyBlockSchema, get_block
 from backend.data.execution import ExecutionContext
-from backend.data.model import CredentialsMetaInput
+from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
 from backend.data.workspace import get_or_create_workspace
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import BlockError
 
 from .base import BaseTool
+from .helpers import get_inputs_from_schema
 from .models import (
     BlockOutputResponse,
     ErrorResponse,
@@ -24,7 +29,10 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
-from .utils import build_missing_credentials_from_field_info
+from .utils import (
+    build_missing_credentials_from_field_info,
+    match_credentials_to_requirements,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -73,91 +81,6 @@ 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,
@@ -212,11 +135,24 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
+        # Check if block is excluded from CoPilot (graph-only blocks)
+        if (
+            block.block_type in COPILOT_EXCLUDED_BLOCK_TYPES
+            or block.id in COPILOT_EXCLUDED_BLOCK_IDS
+        ):
+            return ErrorResponse(
+                message=(
+                    f"Block '{block.name}' cannot be run directly in CoPilot. "
+                    "This block is designed for use within graphs only."
+                ),
+                session_id=session_id,
+            )
+
         logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
 
         creds_manager = IntegrationCredentialsManager()
-        matched_credentials, missing_credentials = await self._check_block_credentials(
-            user_id, block, input_data
+        matched_credentials, missing_credentials = (
+            await self._resolve_block_credentials(user_id, block, input_data)
         )
 
         if missing_credentials:
@@ -345,29 +281,75 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
-    def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
+    async def _resolve_block_credentials(
+        self,
+        user_id: str,
+        block: AnyBlockSchema,
+        input_data: dict[str, Any] | None = None,
+    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
+        """
+        Resolve credentials for a block by matching user's available credentials.
+
+        Args:
+            user_id: User ID
+            block: Block to resolve credentials for
+            input_data: Input data for the block (used to determine provider via discriminator)
+
+        Returns:
+            tuple of (matched_credentials, missing_credentials) - matched credentials
+            are used for block execution, missing ones indicate setup requirements.
+        """
+        input_data = input_data or {}
+        requirements = self._resolve_discriminated_credentials(block, input_data)
+
+        if not requirements:
+            return {}, []
+
+        return await match_credentials_to_requirements(user_id, requirements)
+
+    def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]:
         """Extract non-credential inputs from block schema."""
-        inputs_list = []
         schema = block.input_schema.jsonschema()
-        properties = schema.get("properties", {})
-        required_fields = set(schema.get("required", []))
-
-        # Get credential field names to exclude
         credentials_fields = set(block.input_schema.get_credentials_fields().keys())
+        return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
 
-        for field_name, field_schema in properties.items():
-            # Skip credential fields
-            if field_name in credentials_fields:
-                continue
+    def _resolve_discriminated_credentials(
+        self,
+        block: AnyBlockSchema,
+        input_data: dict[str, Any],
+    ) -> dict[str, CredentialsFieldInfo]:
+        """Resolve credential requirements, applying discriminator logic where needed."""
+        credentials_fields_info = block.input_schema.get_credentials_fields_info()
+        if not credentials_fields_info:
+            return {}
 
-            inputs_list.append(
-                {
-                    "name": field_name,
-                    "title": field_schema.get("title", field_name),
-                    "type": field_schema.get("type", "string"),
-                    "description": field_schema.get("description", ""),
-                    "required": field_name in required_fields,
-                }
-            )
+        resolved: dict[str, CredentialsFieldInfo] = {}
 
-        return inputs_list
+        for field_name, field_info in credentials_fields_info.items():
+            effective_field_info = field_info
+
+            if field_info.discriminator and field_info.discriminator_mapping:
+                discriminator_value = input_data.get(field_info.discriminator)
+                if discriminator_value is None:
+                    field = block.input_schema.model_fields.get(
+                        field_info.discriminator
+                    )
+                    if field and field.default is not PydanticUndefined:
+                        discriminator_value = field.default
+
+                if (
+                    discriminator_value
+                    and discriminator_value in field_info.discriminator_mapping
+                ):
+                    effective_field_info = field_info.discriminate(discriminator_value)
+                    # For host-scoped credentials, add the discriminator value
+                    # (e.g., URL) so _credential_is_for_host can match it
+                    effective_field_info.discriminator_values.add(discriminator_value)
+                    logger.debug(
+                        f"Discriminated provider for {field_name}: "
+                        f"{discriminator_value} -> {effective_field_info.provider}"
+                    )
+
+            resolved[field_name] = effective_field_info
+
+        return resolved

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

@@ -0,0 +1,106 @@
+"""Tests for block execution guards in RunBlockTool."""
+
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+from backend.api.features.chat.tools.models import ErrorResponse
+from backend.api.features.chat.tools.run_block import RunBlockTool
+from backend.data.block import BlockType
+
+from ._test_data import make_session
+
+_TEST_USER_ID = "test-user-run-block"
+
+
+def make_mock_block(
+    block_id: str, name: str, block_type: BlockType, disabled: bool = False
+):
+    """Create a mock block for testing."""
+    mock = MagicMock()
+    mock.id = block_id
+    mock.name = name
+    mock.block_type = block_type
+    mock.disabled = disabled
+    mock.input_schema = MagicMock()
+    mock.input_schema.jsonschema.return_value = {"properties": {}, "required": []}
+    mock.input_schema.get_credentials_fields_info.return_value = []
+    return mock
+
+
+class TestRunBlockFiltering:
+    """Tests for block execution guards in RunBlockTool."""
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_type_returns_error(self):
+        """Attempting to execute a block with excluded BlockType returns error."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        input_block = make_mock_block("input-block-id", "Input Block", BlockType.INPUT)
+
+        with patch(
+            "backend.api.features.chat.tools.run_block.get_block",
+            return_value=input_block,
+        ):
+            tool = RunBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                block_id="input-block-id",
+                input_data={},
+            )
+
+        assert isinstance(response, ErrorResponse)
+        assert "cannot be run directly in CoPilot" in response.message
+        assert "designed for use within graphs only" in response.message
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_excluded_block_id_returns_error(self):
+        """Attempting to execute SmartDecisionMakerBlock returns error."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        smart_decision_id = "3b191d9f-356f-482d-8238-ba04b6d18381"
+        smart_block = make_mock_block(
+            smart_decision_id, "Smart Decision Maker", BlockType.STANDARD
+        )
+
+        with patch(
+            "backend.api.features.chat.tools.run_block.get_block",
+            return_value=smart_block,
+        ):
+            tool = RunBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                block_id=smart_decision_id,
+                input_data={},
+            )
+
+        assert isinstance(response, ErrorResponse)
+        assert "cannot be run directly in CoPilot" in response.message
+
+    @pytest.mark.asyncio(loop_scope="session")
+    async def test_non_excluded_block_passes_guard(self):
+        """Non-excluded blocks pass the filtering guard (may fail later for other reasons)."""
+        session = make_session(user_id=_TEST_USER_ID)
+
+        standard_block = make_mock_block(
+            "standard-id", "HTTP Request", BlockType.STANDARD
+        )
+
+        with patch(
+            "backend.api.features.chat.tools.run_block.get_block",
+            return_value=standard_block,
+        ):
+            tool = RunBlockTool()
+            response = await tool._execute(
+                user_id=_TEST_USER_ID,
+                session=session,
+                block_id="standard-id",
+                input_data={},
+            )
+
+        # Should NOT be an ErrorResponse about CoPilot exclusion
+        # (may be other errors like missing credentials, but not the exclusion guard)
+        if isinstance(response, ErrorResponse):
+            assert "cannot be run directly in CoPilot" not in response.message

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

@@ -8,6 +8,7 @@ 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,
@@ -223,6 +224,99 @@ async def get_or_create_library_agent(
     return library_agents[0]
 
 
+async def match_credentials_to_requirements(
+    user_id: str,
+    requirements: dict[str, CredentialsFieldInfo],
+) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
+    """
+    Match user's credentials against a dictionary of credential requirements.
+
+    This is the core matching logic shared by both graph and block credential matching.
+    """
+    matched: dict[str, CredentialsMetaInput] = {}
+    missing: list[CredentialsMetaInput] = []
+
+    if not requirements:
+        return matched, missing
+
+    available_creds = await get_user_credentials(user_id)
+
+    for field_name, field_info in requirements.items():
+        matching_cred = find_matching_credential(available_creds, field_info)
+
+        if matching_cred:
+            try:
+                matched[field_name] = create_credential_meta_from_match(matching_cred)
+            except Exception as e:
+                logger.error(
+                    f"Failed to create CredentialsMetaInput for field '{field_name}': "
+                    f"provider={matching_cred.provider}, type={matching_cred.type}, "
+                    f"credential_id={matching_cred.id}",
+                    exc_info=True,
+                )
+                provider = next(iter(field_info.provider), "unknown")
+                cred_type = next(iter(field_info.supported_types), "api_key")
+                missing.append(
+                    CredentialsMetaInput(
+                        id=field_name,
+                        provider=provider,  # type: ignore
+                        type=cred_type,  # type: ignore
+                        title=f"{field_name} (validation failed: {e})",
+                    )
+                )
+        else:
+            provider = next(iter(field_info.provider), "unknown")
+            cred_type = next(iter(field_info.supported_types), "api_key")
+            missing.append(
+                CredentialsMetaInput(
+                    id=field_name,
+                    provider=provider,  # type: ignore
+                    type=cred_type,  # type: ignore
+                    title=field_name.replace("_", " ").title(),
+                )
+            )
+
+    return matched, missing
+
+
+async def get_user_credentials(user_id: str) -> list[Credentials]:
+    """Get all available credentials for a user."""
+    creds_manager = IntegrationCredentialsManager()
+    return await creds_manager.store.get_all_creds(user_id)
+
+
+def find_matching_credential(
+    available_creds: list[Credentials],
+    field_info: CredentialsFieldInfo,
+) -> Credentials | None:
+    """Find a credential that matches the required provider, type, scopes, and host."""
+    for cred in available_creds:
+        if cred.provider not in field_info.provider:
+            continue
+        if cred.type not in field_info.supported_types:
+            continue
+        if cred.type == "oauth2" and not _credential_has_required_scopes(
+            cred, field_info
+        ):
+            continue
+        if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info):
+            continue
+        return cred
+    return None
+
+
+def create_credential_meta_from_match(
+    matching_cred: Credentials,
+) -> CredentialsMetaInput:
+    """Create a CredentialsMetaInput from a matched credential."""
+    return CredentialsMetaInput(
+        id=matching_cred.id,
+        provider=matching_cred.provider,  # type: ignore
+        type=matching_cred.type,
+        title=matching_cred.title,
+    )
+
+
 async def match_user_credentials_to_graph(
     user_id: str,
     graph: GraphModel,
@@ -331,8 +425,6 @@ 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

@@ -8,6 +8,7 @@ Includes BM25 reranking for improved lexical relevance.
 
 import logging
 import re
+import time
 from dataclasses import dataclass
 from typing import Any, Literal
 
@@ -362,7 +363,11 @@ async def unified_hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
     # Apply BM25 reranking
@@ -686,7 +691,11 @@ async def hybrid_search(
         LIMIT {limit_param} OFFSET {offset_param}
     """
 
-    results = await query_raw_with_schema(sql_query, *params)
+    try:
+        results = await query_raw_with_schema(sql_query, *params)
+    except Exception as e:
+        await _log_vector_error_diagnostics(e)
+        raise
 
     total = results[0]["total_count"] if results else 0
 
@@ -718,6 +727,87 @@ async def hybrid_search_simple(
     return await hybrid_search(query=query, page=page, page_size=page_size)
 
 
+# ============================================================================
+# Diagnostics
+# ============================================================================
+
+# Rate limit: only log vector error diagnostics once per this interval
+_VECTOR_DIAG_INTERVAL_SECONDS = 60
+_last_vector_diag_time: float = 0
+
+
+async def _log_vector_error_diagnostics(error: Exception) -> None:
+    """Log diagnostic info when 'type vector does not exist' error occurs.
+
+    Note: Diagnostic queries use query_raw_with_schema which may run on a different
+    pooled connection than the one that failed. Session-level search_path can differ,
+    so these diagnostics show cluster-wide state, not necessarily the failed session.
+
+    Includes rate limiting to avoid log spam - only logs once per minute.
+    Caller should re-raise the error after calling this function.
+    """
+    global _last_vector_diag_time
+
+    # Check if this is the vector type error
+    error_str = str(error).lower()
+    if not (
+        "type" in error_str and "vector" in error_str and "does not exist" in error_str
+    ):
+        return
+
+    # Rate limit: only log once per interval
+    now = time.time()
+    if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS:
+        return
+    _last_vector_diag_time = now
+
+    try:
+        diagnostics: dict[str, object] = {}
+
+        try:
+            search_path_result = await query_raw_with_schema("SHOW search_path")
+            diagnostics["search_path"] = search_path_result
+        except Exception as e:
+            diagnostics["search_path"] = f"Error: {e}"
+
+        try:
+            schema_result = await query_raw_with_schema("SELECT current_schema()")
+            diagnostics["current_schema"] = schema_result
+        except Exception as e:
+            diagnostics["current_schema"] = f"Error: {e}"
+
+        try:
+            user_result = await query_raw_with_schema(
+                "SELECT current_user, session_user, current_database()"
+            )
+            diagnostics["user_info"] = user_result
+        except Exception as e:
+            diagnostics["user_info"] = f"Error: {e}"
+
+        try:
+            # Check pgvector extension installation (cluster-wide, stable info)
+            ext_result = await query_raw_with_schema(
+                "SELECT extname, extversion, nspname as schema "
+                "FROM pg_extension e "
+                "JOIN pg_namespace n ON e.extnamespace = n.oid "
+                "WHERE extname = 'vector'"
+            )
+            diagnostics["pgvector_extension"] = ext_result
+        except Exception as e:
+            diagnostics["pgvector_extension"] = f"Error: {e}"
+
+        logger.error(
+            f"Vector type error diagnostics:\n"
+            f"  Error: {error}\n"
+            f"  search_path: {diagnostics.get('search_path')}\n"
+            f"  current_schema: {diagnostics.get('current_schema')}\n"
+            f"  user_info: {diagnostics.get('user_info')}\n"
+            f"  pgvector_extension: {diagnostics.get('pgvector_extension')}"
+        )
+    except Exception as diag_error:
+        logger.error(f"Failed to collect vector error diagnostics: {diag_error}")
+
+
 # Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights
 # for existing code that expects the popularity parameter
 HybridSearchWeights = StoreAgentSearchWeights

autogpt_platform/backend/backend/blocks/exa/websets.py

@@ -478,7 +478,7 @@ class ExaCreateOrFindWebsetBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         try:
-            webset = aexa.websets.get(id=input_data.external_id)
+            webset = await aexa.websets.get(id=input_data.external_id)
             webset_result = Webset.model_validate(webset.model_dump(by_alias=True))
 
             yield "webset", webset_result
@@ -494,7 +494,7 @@ class ExaCreateOrFindWebsetBlock(Block):
                         count=input_data.search_count,
                     )
 
-                webset = aexa.websets.create(
+                webset = await aexa.websets.create(
                     params=CreateWebsetParameters(
                         search=search_params,
                         external_id=input_data.external_id,
@@ -554,7 +554,7 @@ class ExaUpdateWebsetBlock(Block):
         if input_data.metadata is not None:
             payload["metadata"] = input_data.metadata
 
-        sdk_webset = aexa.websets.update(id=input_data.webset_id, params=payload)
+        sdk_webset = await aexa.websets.update(id=input_data.webset_id, params=payload)
 
         status_str = (
             sdk_webset.status.value
@@ -617,7 +617,7 @@ class ExaListWebsetsBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        response = aexa.websets.list(
+        response = await aexa.websets.list(
             cursor=input_data.cursor,
             limit=input_data.limit,
         )
@@ -678,7 +678,7 @@ class ExaGetWebsetBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_webset = aexa.websets.get(id=input_data.webset_id)
+        sdk_webset = await aexa.websets.get(id=input_data.webset_id)
 
         status_str = (
             sdk_webset.status.value
@@ -748,7 +748,7 @@ class ExaDeleteWebsetBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_webset = aexa.websets.delete(id=input_data.webset_id)
+        deleted_webset = await aexa.websets.delete(id=input_data.webset_id)
 
         status_str = (
             deleted_webset.status.value
@@ -798,7 +798,7 @@ class ExaCancelWebsetBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        canceled_webset = aexa.websets.cancel(id=input_data.webset_id)
+        canceled_webset = await aexa.websets.cancel(id=input_data.webset_id)
 
         status_str = (
             canceled_webset.status.value
@@ -968,7 +968,7 @@ class ExaPreviewWebsetBlock(Block):
                 entity["description"] = input_data.entity_description
             payload["entity"] = entity
 
-        sdk_preview = aexa.websets.preview(params=payload)
+        sdk_preview = await aexa.websets.preview(params=payload)
 
         preview = PreviewWebsetModel.from_sdk(sdk_preview)
 
@@ -1051,7 +1051,7 @@ class ExaWebsetStatusBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         status = (
             webset.status.value
@@ -1185,7 +1185,7 @@ class ExaWebsetSummaryBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         # Extract basic info
         webset_id = webset.id
@@ -1211,7 +1211,7 @@ class ExaWebsetSummaryBlock(Block):
         total_items = 0
 
         if input_data.include_sample_items and input_data.sample_size > 0:
-            items_response = aexa.websets.items.list(
+            items_response = await aexa.websets.items.list(
                 webset_id=input_data.webset_id, limit=input_data.sample_size
             )
             sample_items_data = [
@@ -1362,7 +1362,7 @@ class ExaWebsetReadyCheckBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         # Get webset details
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         status = (
             webset.status.value

autogpt_platform/backend/backend/blocks/exa/websets_enrichment.py

@@ -202,7 +202,7 @@ class ExaCreateEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_enrichment = aexa.websets.enrichments.create(
+        sdk_enrichment = await aexa.websets.enrichments.create(
             webset_id=input_data.webset_id, params=payload
         )
 
@@ -223,7 +223,7 @@ class ExaCreateEnrichmentBlock(Block):
             items_enriched = 0
 
             while time.time() - poll_start < input_data.polling_timeout:
-                current_enrich = aexa.websets.enrichments.get(
+                current_enrich = await aexa.websets.enrichments.get(
                     webset_id=input_data.webset_id, id=enrichment_id
                 )
                 current_status = (
@@ -234,7 +234,7 @@ class ExaCreateEnrichmentBlock(Block):
 
                 if current_status in ["completed", "failed", "cancelled"]:
                     # Estimate items from webset searches
-                    webset = aexa.websets.get(id=input_data.webset_id)
+                    webset = await aexa.websets.get(id=input_data.webset_id)
                     if webset.searches:
                         for search in webset.searches:
                             if search.progress:
@@ -329,7 +329,7 @@ class ExaGetEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_enrichment = aexa.websets.enrichments.get(
+        sdk_enrichment = await aexa.websets.enrichments.get(
             webset_id=input_data.webset_id, id=input_data.enrichment_id
         )
 
@@ -474,7 +474,7 @@ class ExaDeleteEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_enrichment = aexa.websets.enrichments.delete(
+        deleted_enrichment = await aexa.websets.enrichments.delete(
             webset_id=input_data.webset_id, id=input_data.enrichment_id
         )
 
@@ -525,13 +525,13 @@ class ExaCancelEnrichmentBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        canceled_enrichment = aexa.websets.enrichments.cancel(
+        canceled_enrichment = await aexa.websets.enrichments.cancel(
             webset_id=input_data.webset_id, id=input_data.enrichment_id
         )
 
         # Try to estimate how many items were enriched before cancellation
         items_enriched = 0
-        items_response = aexa.websets.items.list(
+        items_response = await aexa.websets.items.list(
             webset_id=input_data.webset_id, limit=100
         )
 

autogpt_platform/backend/backend/blocks/exa/websets_import_export.py

@@ -222,7 +222,7 @@ class ExaCreateImportBlock(Block):
     def _create_test_mock():
         """Create test mocks for the AsyncExa SDK."""
         from datetime import datetime
-        from unittest.mock import MagicMock
+        from unittest.mock import AsyncMock, MagicMock
 
         # Create mock SDK import object
         mock_import = MagicMock()
@@ -247,7 +247,7 @@ class ExaCreateImportBlock(Block):
         return {
             "_get_client": lambda *args, **kwargs: MagicMock(
                 websets=MagicMock(
-                    imports=MagicMock(create=lambda *args, **kwargs: mock_import)
+                    imports=MagicMock(create=AsyncMock(return_value=mock_import))
                 )
             )
         }
@@ -294,7 +294,7 @@ class ExaCreateImportBlock(Block):
         if input_data.metadata:
             payload["metadata"] = input_data.metadata
 
-        sdk_import = aexa.websets.imports.create(
+        sdk_import = await aexa.websets.imports.create(
             params=payload, csv_data=input_data.csv_data
         )
 
@@ -360,7 +360,7 @@ class ExaGetImportBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_import = aexa.websets.imports.get(import_id=input_data.import_id)
+        sdk_import = await aexa.websets.imports.get(import_id=input_data.import_id)
 
         import_obj = ImportModel.from_sdk(sdk_import)
 
@@ -426,7 +426,7 @@ class ExaListImportsBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        response = aexa.websets.imports.list(
+        response = await aexa.websets.imports.list(
             cursor=input_data.cursor,
             limit=input_data.limit,
         )
@@ -474,7 +474,9 @@ class ExaDeleteImportBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_import = aexa.websets.imports.delete(import_id=input_data.import_id)
+        deleted_import = await aexa.websets.imports.delete(
+            import_id=input_data.import_id
+        )
 
         yield "import_id", deleted_import.id
         yield "success", "true"
@@ -573,14 +575,14 @@ class ExaExportWebsetBlock(Block):
             }
         )
 
-        # Create mock iterator
-        mock_items = [mock_item1, mock_item2]
+        # Create async iterator for list_all
+        async def async_item_iterator(*args, **kwargs):
+            for item in [mock_item1, mock_item2]:
+                yield item
 
         return {
             "_get_client": lambda *args, **kwargs: MagicMock(
-                websets=MagicMock(
-                    items=MagicMock(list_all=lambda *args, **kwargs: iter(mock_items))
-                )
+                websets=MagicMock(items=MagicMock(list_all=async_item_iterator))
             )
         }
 
@@ -602,7 +604,7 @@ class ExaExportWebsetBlock(Block):
                 webset_id=input_data.webset_id, limit=input_data.max_items
             )
 
-            for sdk_item in item_iterator:
+            async for sdk_item in item_iterator:
                 if len(all_items) >= input_data.max_items:
                     break
 

autogpt_platform/backend/backend/blocks/exa/websets_items.py

@@ -178,7 +178,7 @@ class ExaGetWebsetItemBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_item = aexa.websets.items.get(
+        sdk_item = await aexa.websets.items.get(
             webset_id=input_data.webset_id, id=input_data.item_id
         )
 
@@ -269,7 +269,7 @@ class ExaListWebsetItemsBlock(Block):
             response = None
 
             while time.time() - start_time < input_data.wait_timeout:
-                response = aexa.websets.items.list(
+                response = await aexa.websets.items.list(
                     webset_id=input_data.webset_id,
                     cursor=input_data.cursor,
                     limit=input_data.limit,
@@ -282,13 +282,13 @@ class ExaListWebsetItemsBlock(Block):
                 interval = min(interval * 1.2, 10)
 
             if not response:
-                response = aexa.websets.items.list(
+                response = await aexa.websets.items.list(
                     webset_id=input_data.webset_id,
                     cursor=input_data.cursor,
                     limit=input_data.limit,
                 )
         else:
-            response = aexa.websets.items.list(
+            response = await aexa.websets.items.list(
                 webset_id=input_data.webset_id,
                 cursor=input_data.cursor,
                 limit=input_data.limit,
@@ -340,7 +340,7 @@ class ExaDeleteWebsetItemBlock(Block):
     ) -> BlockOutput:
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_item = aexa.websets.items.delete(
+        deleted_item = await aexa.websets.items.delete(
             webset_id=input_data.webset_id, id=input_data.item_id
         )
 
@@ -408,7 +408,7 @@ class ExaBulkWebsetItemsBlock(Block):
             webset_id=input_data.webset_id, limit=input_data.max_items
         )
 
-        for sdk_item in item_iterator:
+        async for sdk_item in item_iterator:
             if len(all_items) >= input_data.max_items:
                 break
 
@@ -475,7 +475,7 @@ class ExaWebsetItemsSummaryBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         entity_type = "unknown"
         if webset.searches:
@@ -495,7 +495,7 @@ class ExaWebsetItemsSummaryBlock(Block):
         # Get sample items if requested
         sample_items: List[WebsetItemModel] = []
         if input_data.sample_size > 0:
-            items_response = aexa.websets.items.list(
+            items_response = await aexa.websets.items.list(
                 webset_id=input_data.webset_id, limit=input_data.sample_size
             )
             # Convert to our stable models
@@ -569,7 +569,7 @@ class ExaGetNewItemsBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         # Get items starting from cursor
-        response = aexa.websets.items.list(
+        response = await aexa.websets.items.list(
             webset_id=input_data.webset_id,
             cursor=input_data.since_cursor,
             limit=input_data.max_items,

autogpt_platform/backend/backend/blocks/exa/websets_monitor.py

@@ -233,7 +233,7 @@ class ExaCreateMonitorBlock(Block):
     def _create_test_mock():
         """Create test mocks for the AsyncExa SDK."""
         from datetime import datetime
-        from unittest.mock import MagicMock
+        from unittest.mock import AsyncMock, MagicMock
 
         # Create mock SDK monitor object
         mock_monitor = MagicMock()
@@ -263,7 +263,7 @@ class ExaCreateMonitorBlock(Block):
         return {
             "_get_client": lambda *args, **kwargs: MagicMock(
                 websets=MagicMock(
-                    monitors=MagicMock(create=lambda *args, **kwargs: mock_monitor)
+                    monitors=MagicMock(create=AsyncMock(return_value=mock_monitor))
                 )
             )
         }
@@ -320,7 +320,7 @@ class ExaCreateMonitorBlock(Block):
         if input_data.metadata:
             payload["metadata"] = input_data.metadata
 
-        sdk_monitor = aexa.websets.monitors.create(params=payload)
+        sdk_monitor = await aexa.websets.monitors.create(params=payload)
 
         monitor = MonitorModel.from_sdk(sdk_monitor)
 
@@ -384,7 +384,7 @@ class ExaGetMonitorBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_monitor = aexa.websets.monitors.get(monitor_id=input_data.monitor_id)
+        sdk_monitor = await aexa.websets.monitors.get(monitor_id=input_data.monitor_id)
 
         monitor = MonitorModel.from_sdk(sdk_monitor)
 
@@ -476,7 +476,7 @@ class ExaUpdateMonitorBlock(Block):
         if input_data.metadata is not None:
             payload["metadata"] = input_data.metadata
 
-        sdk_monitor = aexa.websets.monitors.update(
+        sdk_monitor = await aexa.websets.monitors.update(
             monitor_id=input_data.monitor_id, params=payload
         )
 
@@ -522,7 +522,9 @@ class ExaDeleteMonitorBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_monitor = aexa.websets.monitors.delete(monitor_id=input_data.monitor_id)
+        deleted_monitor = await aexa.websets.monitors.delete(
+            monitor_id=input_data.monitor_id
+        )
 
         yield "monitor_id", deleted_monitor.id
         yield "success", "true"
@@ -579,7 +581,7 @@ class ExaListMonitorsBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        response = aexa.websets.monitors.list(
+        response = await aexa.websets.monitors.list(
             cursor=input_data.cursor,
             limit=input_data.limit,
             webset_id=input_data.webset_id,

autogpt_platform/backend/backend/blocks/exa/websets_polling.py

@@ -121,7 +121,7 @@ class ExaWaitForWebsetBlock(Block):
                 WebsetTargetStatus.IDLE,
                 WebsetTargetStatus.ANY_COMPLETE,
             ]:
-                final_webset = aexa.websets.wait_until_idle(
+                final_webset = await aexa.websets.wait_until_idle(
                     id=input_data.webset_id,
                     timeout=input_data.timeout,
                     poll_interval=input_data.check_interval,
@@ -164,7 +164,7 @@ class ExaWaitForWebsetBlock(Block):
                 interval = input_data.check_interval
                 while time.time() - start_time < input_data.timeout:
                     # Get current webset status
-                    webset = aexa.websets.get(id=input_data.webset_id)
+                    webset = await aexa.websets.get(id=input_data.webset_id)
                     current_status = (
                         webset.status.value
                         if hasattr(webset.status, "value")
@@ -209,7 +209,7 @@ class ExaWaitForWebsetBlock(Block):
 
                 # Timeout reached
                 elapsed = time.time() - start_time
-                webset = aexa.websets.get(id=input_data.webset_id)
+                webset = await aexa.websets.get(id=input_data.webset_id)
                 final_status = (
                     webset.status.value
                     if hasattr(webset.status, "value")
@@ -345,7 +345,7 @@ class ExaWaitForSearchBlock(Block):
         try:
             while time.time() - start_time < input_data.timeout:
                 # Get current search status using SDK
-                search = aexa.websets.searches.get(
+                search = await aexa.websets.searches.get(
                     webset_id=input_data.webset_id, id=input_data.search_id
                 )
 
@@ -401,7 +401,7 @@ class ExaWaitForSearchBlock(Block):
             elapsed = time.time() - start_time
 
             # Get last known status
-            search = aexa.websets.searches.get(
+            search = await aexa.websets.searches.get(
                 webset_id=input_data.webset_id, id=input_data.search_id
             )
             final_status = (
@@ -503,7 +503,7 @@ class ExaWaitForEnrichmentBlock(Block):
         try:
             while time.time() - start_time < input_data.timeout:
                 # Get current enrichment status using SDK
-                enrichment = aexa.websets.enrichments.get(
+                enrichment = await aexa.websets.enrichments.get(
                     webset_id=input_data.webset_id, id=input_data.enrichment_id
                 )
 
@@ -548,7 +548,7 @@ class ExaWaitForEnrichmentBlock(Block):
             elapsed = time.time() - start_time
 
             # Get last known status
-            enrichment = aexa.websets.enrichments.get(
+            enrichment = await aexa.websets.enrichments.get(
                 webset_id=input_data.webset_id, id=input_data.enrichment_id
             )
             final_status = (
@@ -575,7 +575,7 @@ class ExaWaitForEnrichmentBlock(Block):
     ) -> tuple[list[SampleEnrichmentModel], int]:
         """Get sample enriched data and count."""
         # Get a few items to see enrichment results using SDK
-        response = aexa.websets.items.list(webset_id=webset_id, limit=5)
+        response = await aexa.websets.items.list(webset_id=webset_id, limit=5)
 
         sample_data: list[SampleEnrichmentModel] = []
         enriched_count = 0

autogpt_platform/backend/backend/blocks/exa/websets_search.py

@@ -317,7 +317,7 @@ class ExaCreateWebsetSearchBlock(Block):
 
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_search = aexa.websets.searches.create(
+        sdk_search = await aexa.websets.searches.create(
             webset_id=input_data.webset_id, params=payload
         )
 
@@ -350,7 +350,7 @@ class ExaCreateWebsetSearchBlock(Block):
             poll_start = time.time()
 
             while time.time() - poll_start < input_data.polling_timeout:
-                current_search = aexa.websets.searches.get(
+                current_search = await aexa.websets.searches.get(
                     webset_id=input_data.webset_id, id=search_id
                 )
                 current_status = (
@@ -442,7 +442,7 @@ class ExaGetWebsetSearchBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        sdk_search = aexa.websets.searches.get(
+        sdk_search = await aexa.websets.searches.get(
             webset_id=input_data.webset_id, id=input_data.search_id
         )
 
@@ -523,7 +523,7 @@ class ExaCancelWebsetSearchBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        canceled_search = aexa.websets.searches.cancel(
+        canceled_search = await aexa.websets.searches.cancel(
             webset_id=input_data.webset_id, id=input_data.search_id
         )
 
@@ -604,7 +604,7 @@ class ExaFindOrCreateSearchBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         # Get webset to check existing searches
-        webset = aexa.websets.get(id=input_data.webset_id)
+        webset = await aexa.websets.get(id=input_data.webset_id)
 
         # Look for existing search with same query
         existing_search = None
@@ -636,7 +636,7 @@ class ExaFindOrCreateSearchBlock(Block):
             if input_data.entity_type != SearchEntityType.AUTO:
                 payload["entity"] = {"type": input_data.entity_type.value}
 
-            sdk_search = aexa.websets.searches.create(
+            sdk_search = await aexa.websets.searches.create(
                 webset_id=input_data.webset_id, params=payload
             )
 

autogpt_platform/backend/backend/blocks/human_in_the_loop.py

@@ -21,43 +21,71 @@ logger = logging.getLogger(__name__)
 
 class HumanInTheLoopBlock(Block):
     """
-    This block pauses execution and waits for human approval or modification of the data.
+    Pauses execution and waits for human approval or rejection of the data.
 
-    When executed, it creates a pending review entry and sets the node execution status
-    to REVIEW. The execution will remain paused until a human user either:
-    - Approves the data (with or without modifications)
-    - Rejects the data
+    When executed, this block creates a pending review entry and sets the node execution
+    status to REVIEW. The execution remains paused until a human user either approves
+    or rejects the data.
 
-    This is useful for workflows that require human validation or intervention before
-    proceeding to the next steps.
+    **How it works:**
+    - The input data is presented to a human reviewer
+    - The reviewer can approve or reject (and optionally modify the data if editable)
+    - On approval: the data flows out through the `approved_data` output pin
+    - On rejection: the data flows out through the `rejected_data` output pin
+
+    **Important:** The output pins yield the actual data itself, NOT status strings.
+    The approval/rejection decision determines WHICH output pin fires, not the value.
+    You do NOT need to compare the output to "APPROVED" or "REJECTED" - simply connect
+    downstream blocks to the appropriate output pin for each case.
+
+    **Example usage:**
+    - Connect `approved_data` → next step in your workflow (data was approved)
+    - Connect `rejected_data` → error handling or notification (data was rejected)
     """
 
     class Input(BlockSchemaInput):
-        data: Any = SchemaField(description="The data to be reviewed by a human user")
+        data: Any = SchemaField(
+            description="The data to be reviewed by a human user. "
+            "This exact data will be passed through to either approved_data or "
+            "rejected_data output based on the reviewer's decision."
+        )
         name: str = SchemaField(
-            description="A descriptive name for what this data represents",
+            description="A descriptive name for what this data represents. "
+            "This helps the reviewer understand what they are reviewing.",
         )
         editable: bool = SchemaField(
-            description="Whether the human reviewer can edit the data",
+            description="Whether the human reviewer can edit the data before "
+            "approving or rejecting it",
             default=True,
             advanced=True,
         )
 
     class Output(BlockSchemaOutput):
         approved_data: Any = SchemaField(
-            description="The data when approved (may be modified by reviewer)"
+            description="Outputs the input data when the reviewer APPROVES it. "
+            "The value is the actual data itself (not a status string like 'APPROVED'). "
+            "If the reviewer edited the data, this contains the modified version. "
+            "Connect downstream blocks here for the 'approved' workflow path."
         )
         rejected_data: Any = SchemaField(
-            description="The data when rejected (may be modified by reviewer)"
+            description="Outputs the input data when the reviewer REJECTS it. "
+            "The value is the actual data itself (not a status string like 'REJECTED'). "
+            "If the reviewer edited the data, this contains the modified version. "
+            "Connect downstream blocks here for the 'rejected' workflow path."
         )
         review_message: str = SchemaField(
-            description="Any message provided by the reviewer", default=""
+            description="Optional message provided by the reviewer explaining their "
+            "decision. Only outputs when the reviewer provides a message; "
+            "this pin does not fire if no message was given.",
+            default="",
         )
 
     def __init__(self):
         super().__init__(
             id="8b2a7b3c-6e9d-4a5f-8c1b-2e3f4a5b6c7d",
-            description="Pause execution and wait for human approval or modification of data",
+            description="Pause execution for human review. Data flows through "
+            "approved_data or rejected_data output based on the reviewer's decision. "
+            "Outputs contain the actual data, not status strings.",
             categories={BlockCategory.BASIC},
             input_schema=HumanInTheLoopBlock.Input,
             output_schema=HumanInTheLoopBlock.Output,

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.NotGiven:
+) -> Iterable[ToolParam] | anthropic.Omit:
     """
     Convert OpenAI tool format to Anthropic tool format.
     """
     if not openai_tools or len(openai_tools) == 0:
-        return anthropic.NOT_GIVEN
+        return anthropic.omit
 
     anthropic_tools = []
     for tool in openai_tools:
@@ -596,10 +596,10 @@ def extract_openai_tool_calls(response) -> list[ToolContentBlock] | None:
 
 def get_parallel_tool_calls_param(
     llm_model: LlmModel, parallel_tool_calls: bool | None
-):
+) -> bool | openai.Omit:
     """Get the appropriate parallel_tool_calls parameter for OpenAI-compatible APIs."""
     if llm_model.startswith("o") or parallel_tool_calls is None:
-        return openai.NOT_GIVEN
+        return openai.omit
     return parallel_tool_calls
 
 

autogpt_platform/backend/backend/data/execution.py

@@ -1,9 +1,8 @@
 import logging
+import queue
 from collections import defaultdict
 from datetime import datetime, timedelta, timezone
 from enum import Enum
-from multiprocessing import Manager
-from queue import Empty
 from typing import (
     TYPE_CHECKING,
     Annotated,
@@ -1200,12 +1199,16 @@ class NodeExecutionEntry(BaseModel):
 
 class ExecutionQueue(Generic[T]):
     """
-    Queue for managing the execution of agents.
-    This will be shared between different processes
+    Thread-safe queue for managing node execution within a single graph execution.
+
+    Note: Uses queue.Queue (not multiprocessing.Queue) since all access is from
+    threads within the same process. If migrating back to ProcessPoolExecutor,
+    replace with multiprocessing.Manager().Queue() for cross-process safety.
     """
 
     def __init__(self):
-        self.queue = Manager().Queue()
+        # Thread-safe queue (not multiprocessing) — see class docstring
+        self.queue: queue.Queue[T] = queue.Queue()
 
     def add(self, execution: T) -> T:
         self.queue.put(execution)
@@ -1220,7 +1223,7 @@ class ExecutionQueue(Generic[T]):
     def get_or_none(self) -> T | None:
         try:
             return self.queue.get_nowait()
-        except Empty:
+        except queue.Empty:
             return None
 
 

autogpt_platform/backend/backend/data/execution_queue_test.py

@@ -0,0 +1,58 @@
+"""Tests for ExecutionQueue thread-safety."""
+
+import queue
+import threading
+
+from backend.data.execution import ExecutionQueue
+
+
+def test_execution_queue_uses_stdlib_queue():
+    """Verify ExecutionQueue uses queue.Queue (not multiprocessing)."""
+    q = ExecutionQueue()
+    assert isinstance(q.queue, queue.Queue)
+
+
+def test_basic_operations():
+    """Test add, get, empty, and get_or_none."""
+    q = ExecutionQueue()
+
+    assert q.empty() is True
+    assert q.get_or_none() is None
+
+    result = q.add("item1")
+    assert result == "item1"
+    assert q.empty() is False
+
+    item = q.get()
+    assert item == "item1"
+    assert q.empty() is True
+
+
+def test_thread_safety():
+    """Test concurrent access from multiple threads."""
+    q = ExecutionQueue()
+    results = []
+    num_items = 100
+
+    def producer():
+        for i in range(num_items):
+            q.add(f"item_{i}")
+
+    def consumer():
+        count = 0
+        while count < num_items:
+            item = q.get_or_none()
+            if item is not None:
+                results.append(item)
+                count += 1
+
+    producer_thread = threading.Thread(target=producer)
+    consumer_thread = threading.Thread(target=consumer)
+
+    producer_thread.start()
+    consumer_thread.start()
+
+    producer_thread.join(timeout=5)
+    consumer_thread.join(timeout=5)
+
+    assert len(results) == num_items

autogpt_platform/backend/backend/data/graph.py

@@ -743,6 +743,11 @@ 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

@@ -1,3 +1,4 @@
+import asyncio
 import logging
 from abc import ABC, abstractmethod
 from enum import Enum
@@ -225,6 +226,10 @@ class SyncRabbitMQ(RabbitMQBase):
 class AsyncRabbitMQ(RabbitMQBase):
     """Asynchronous RabbitMQ client"""
 
+    def __init__(self, config: RabbitMQConfig):
+        super().__init__(config)
+        self._reconnect_lock: asyncio.Lock | None = None
+
     @property
     def is_connected(self) -> bool:
         return bool(self._connection and not self._connection.is_closed)
@@ -235,7 +240,17 @@ class AsyncRabbitMQ(RabbitMQBase):
 
     @conn_retry("AsyncRabbitMQ", "Acquiring async connection")
     async def connect(self):
-        if self.is_connected:
+        if self.is_connected and self._channel and not self._channel.is_closed:
+            return
+
+        if (
+            self.is_connected
+            and self._connection
+            and (self._channel is None or self._channel.is_closed)
+        ):
+            self._channel = await self._connection.channel()
+            await self._channel.set_qos(prefetch_count=1)
+            await self.declare_infrastructure()
             return
 
         self._connection = await aio_pika.connect_robust(
@@ -291,24 +306,46 @@ class AsyncRabbitMQ(RabbitMQBase):
                     exchange, routing_key=queue.routing_key or queue.name
                 )
 
-    @func_retry
-    async def publish_message(
+    @property
+    def _lock(self) -> asyncio.Lock:
+        if self._reconnect_lock is None:
+            self._reconnect_lock = asyncio.Lock()
+        return self._reconnect_lock
+
+    async def _ensure_channel(self) -> aio_pika.abc.AbstractChannel:
+        """Get a valid channel, reconnecting if the current one is stale.
+
+        Uses a lock to prevent concurrent reconnection attempts from racing.
+        """
+        if self.is_ready:
+            return self._channel  # type: ignore  # is_ready guarantees non-None
+
+        async with self._lock:
+            # Double-check after acquiring lock
+            if self.is_ready:
+                return self._channel  # type: ignore
+
+            self._channel = None
+            await self.connect()
+
+            if self._channel is None:
+                raise RuntimeError("Channel should be established after connect")
+
+            return self._channel
+
+    async def _publish_once(
         self,
         routing_key: str,
         message: str,
         exchange: Optional[Exchange] = None,
         persistent: bool = True,
     ) -> None:
-        if not self.is_ready:
-            await self.connect()
-
-        if self._channel is None:
-            raise RuntimeError("Channel should be established after connect")
+        channel = await self._ensure_channel()
 
         if exchange:
-            exchange_obj = await self._channel.get_exchange(exchange.name)
+            exchange_obj = await channel.get_exchange(exchange.name)
         else:
-            exchange_obj = self._channel.default_exchange
+            exchange_obj = channel.default_exchange
 
         await exchange_obj.publish(
             aio_pika.Message(
@@ -322,9 +359,23 @@ class AsyncRabbitMQ(RabbitMQBase):
             routing_key=routing_key,
         )
 
+    @func_retry
+    async def publish_message(
+        self,
+        routing_key: str,
+        message: str,
+        exchange: Optional[Exchange] = None,
+        persistent: bool = True,
+    ) -> None:
+        try:
+            await self._publish_once(routing_key, message, exchange, persistent)
+        except aio_pika.exceptions.ChannelInvalidStateError:
+            logger.warning(
+                "RabbitMQ channel invalid, forcing reconnect and retrying publish"
+            )
+            async with self._lock:
+                self._channel = None
+            await self._publish_once(routing_key, message, exchange, persistent)
+
     async def get_channel(self) -> aio_pika.abc.AbstractChannel:
-        if not self.is_ready:
-            await self.connect()
-        if self._channel is None:
-            raise RuntimeError("Channel should be established after connect")
-        return self._channel
+        return await self._ensure_channel()

autogpt_platform/backend/backend/executor/manager.py

@@ -213,6 +213,9 @@ async def execute_node(
         block_name=node_block.name,
     )
 
+    if node_block.disabled:
+        raise ValueError(f"Block {node_block.id} is disabled and cannot be executed")
+
     # Sanity check: validate the execution input.
     input_data, error = validate_exec(node, data.inputs, resolve_input=False)
     if input_data is None:

autogpt_platform/backend/backend/util/file.py

@@ -342,6 +342,14 @@ async def store_media_file(
         if not target_path.is_file():
             raise ValueError(f"Local file does not exist: {target_path}")
 
+        # Virus scan the local file before any further processing
+        local_content = target_path.read_bytes()
+        if len(local_content) > MAX_FILE_SIZE_BYTES:
+            raise ValueError(
+                f"File too large: {len(local_content)} bytes > {MAX_FILE_SIZE_BYTES} bytes"
+            )
+        await scan_content_safe(local_content, filename=sanitized_file)
+
     # Return based on requested format
     if return_format == "for_local_processing":
         # Use when processing files locally with tools like ffmpeg, MoviePy, PIL

autogpt_platform/backend/backend/util/file_test.py

@@ -247,3 +247,100 @@ class TestFileCloudIntegration:
                     execution_context=make_test_context(graph_exec_id=graph_exec_id),
                     return_format="for_local_processing",
                 )
+
+    @pytest.mark.asyncio
+    async def test_store_media_file_local_path_scanned(self):
+        """Test that local file paths are scanned for viruses."""
+        graph_exec_id = "test-exec-123"
+        local_file = "test_video.mp4"
+        file_content = b"fake video content"
+
+        with patch(
+            "backend.util.file.get_cloud_storage_handler"
+        ) as mock_handler_getter, patch(
+            "backend.util.file.scan_content_safe"
+        ) as mock_scan, patch(
+            "backend.util.file.Path"
+        ) as mock_path_class:
+
+            # Mock cloud storage handler - not a cloud path
+            mock_handler = MagicMock()
+            mock_handler.is_cloud_path.return_value = False
+            mock_handler_getter.return_value = mock_handler
+
+            # Mock virus scanner
+            mock_scan.return_value = None
+
+            # Mock file system operations
+            mock_base_path = MagicMock()
+            mock_target_path = MagicMock()
+            mock_resolved_path = MagicMock()
+
+            mock_path_class.return_value = mock_base_path
+            mock_base_path.mkdir = MagicMock()
+            mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
+            mock_target_path.resolve.return_value = mock_resolved_path
+            mock_resolved_path.is_relative_to.return_value = True
+            mock_resolved_path.is_file.return_value = True
+            mock_resolved_path.read_bytes.return_value = file_content
+            mock_resolved_path.relative_to.return_value = Path(local_file)
+            mock_resolved_path.name = local_file
+
+            result = await store_media_file(
+                file=MediaFileType(local_file),
+                execution_context=make_test_context(graph_exec_id=graph_exec_id),
+                return_format="for_local_processing",
+            )
+
+            # Verify virus scan was called for local file
+            mock_scan.assert_called_once_with(file_content, filename=local_file)
+
+            # Result should be the relative path
+            assert str(result) == local_file
+
+    @pytest.mark.asyncio
+    async def test_store_media_file_local_path_virus_detected(self):
+        """Test that infected local files raise VirusDetectedError."""
+        from backend.api.features.store.exceptions import VirusDetectedError
+
+        graph_exec_id = "test-exec-123"
+        local_file = "infected.exe"
+        file_content = b"malicious content"
+
+        with patch(
+            "backend.util.file.get_cloud_storage_handler"
+        ) as mock_handler_getter, patch(
+            "backend.util.file.scan_content_safe"
+        ) as mock_scan, patch(
+            "backend.util.file.Path"
+        ) as mock_path_class:
+
+            # Mock cloud storage handler - not a cloud path
+            mock_handler = MagicMock()
+            mock_handler.is_cloud_path.return_value = False
+            mock_handler_getter.return_value = mock_handler
+
+            # Mock virus scanner to detect virus
+            mock_scan.side_effect = VirusDetectedError(
+                "EICAR-Test-File", "File rejected due to virus detection"
+            )
+
+            # Mock file system operations
+            mock_base_path = MagicMock()
+            mock_target_path = MagicMock()
+            mock_resolved_path = MagicMock()
+
+            mock_path_class.return_value = mock_base_path
+            mock_base_path.mkdir = MagicMock()
+            mock_base_path.__truediv__ = MagicMock(return_value=mock_target_path)
+            mock_target_path.resolve.return_value = mock_resolved_path
+            mock_resolved_path.is_relative_to.return_value = True
+            mock_resolved_path.is_file.return_value = True
+            mock_resolved_path.read_bytes.return_value = file_content
+
+            with pytest.raises(VirusDetectedError):
+                await store_media_file(
+                    file=MediaFileType(local_file),
+                    execution_context=make_test_context(graph_exec_id=graph_exec_id),
+                    return_format="for_local_processing",
+                )

autogpt_platform/backend/backend/util/prompt.py

@@ -364,6 +364,44 @@ def _remove_orphan_tool_responses(
     return result
 
 
+def validate_and_remove_orphan_tool_responses(
+    messages: list[dict],
+    log_warning: bool = True,
+) -> list[dict]:
+    """
+    Validate tool_call/tool_response pairs and remove orphaned responses.
+
+    Scans messages in order, tracking all tool_call IDs. Any tool response
+    referencing an ID not seen in a preceding message is considered orphaned
+    and removed. This prevents API errors like Anthropic's "unexpected tool_use_id".
+
+    Args:
+        messages: List of messages to validate (OpenAI or Anthropic format)
+        log_warning: Whether to log a warning when orphans are found
+
+    Returns:
+        A new list with orphaned tool responses removed
+    """
+    available_ids: set[str] = set()
+    orphan_ids: set[str] = set()
+
+    for msg in messages:
+        available_ids |= _extract_tool_call_ids_from_message(msg)
+        for resp_id in _extract_tool_response_ids_from_message(msg):
+            if resp_id not in available_ids:
+                orphan_ids.add(resp_id)
+
+    if not orphan_ids:
+        return messages
+
+    if log_warning:
+        logger.warning(
+            f"Removing {len(orphan_ids)} orphan tool response(s): {orphan_ids}"
+        )
+
+    return _remove_orphan_tool_responses(messages, orphan_ids)
+
+
 def _ensure_tool_pairs_intact(
     recent_messages: list[dict],
     all_messages: list[dict],
@@ -723,6 +761,13 @@ async def compress_context(
 
     # Filter out any None values that may have been introduced
     final_msgs: list[dict] = [m for m in msgs if m is not None]
+
+    # ---- STEP 6: Final tool-pair validation ---------------------------------
+    # After all compression steps, verify that every tool response has a
+    # matching tool_call in a preceding assistant message. Remove orphans
+    # to prevent API errors (e.g., Anthropic's "unexpected tool_use_id").
+    final_msgs = validate_and_remove_orphan_tool_responses(final_msgs)
+
     final_count = sum(_msg_tokens(m, enc) for m in final_msgs)
     error = None
     if final_count + reserve > target_tokens:

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 = "^0.59.0"
+anthropic = "^0.79.0"
 apscheduler = "^3.11.1"
 autogpt-libs = { path = "../autogpt_libs", develop = true }
 bleach = { extras = ["css"], version = "^6.2.0" }
 click = "^8.2.0"
-cryptography = "^45.0"
+cryptography = "^46.0"
 discord-py = "^2.5.2"
 e2b-code-interpreter = "^1.5.2"
 elevenlabs = "^1.50.0"
-fastapi = "^0.116.1"
+fastapi = "^0.128.6"
 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 = "^3.11.0"
-launchdarkly-server-sdk = "^9.12.0"
+langfuse = "^3.14.1"
+launchdarkly-server-sdk = "^9.14.1"
 mem0ai = "^0.1.115"
 moviepy = "^2.1.2"
-ollama = "^0.5.1"
+ollama = "^0.6.1"
 openai = "^1.97.1"
 orjson = "^3.10.0"
 pika = "^1.3.2"
@@ -48,16 +48,16 @@ postmarker = "^1.0"
 praw = "~7.8.1"
 prisma = "^0.15.0"
 rank-bm25 = "^0.2.2"
-prometheus-client = "^0.22.1"
+prometheus-client = "^0.24.1"
 prometheus-fastapi-instrumentator = "^7.0.0"
 psutil = "^7.0.0"
 psycopg2-binary = "^2.9.10"
-pydantic = { extras = ["email"], version = "^2.11.7" }
-pydantic-settings = "^2.10.1"
+pydantic = { extras = ["email"], version = "^2.12.5" }
+pydantic-settings = "^2.12.0"
 pytest = "^8.4.1"
 pytest-asyncio = "^1.1.0"
 python-dotenv = "^1.1.1"
-python-multipart = "^0.0.20"
+python-multipart = "^0.0.22"
 redis = "^6.2.0"
 regex = "^2025.9.18"
 replicate = "^1.0.6"
@@ -65,19 +65,19 @@ sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlal
 sqlalchemy = "^2.0.40"
 strenum = "^0.4.9"
 stripe = "^11.5.0"
-supabase = "2.17.0"
-tenacity = "^9.1.2"
+supabase = "2.27.3"
+tenacity = "^9.1.4"
 todoist-api-python = "^2.1.7"
 tweepy = "^4.16.0"
-uvicorn = { extras = ["standard"], version = "^0.35.0" }
+uvicorn = { extras = ["standard"], version = "^0.40.0" }
 websockets = "^15.0"
 youtube-transcript-api = "^1.2.1"
 yt-dlp = "2025.12.08"
 zerobouncesdk = "^1.1.2"
 # NOTE: please insert new dependencies in their alphabetical location
 pytest-snapshot = "^0.9.0"
-aiofiles = "^24.1.0"
-tiktoken = "^0.9.0"
+aiofiles = "^25.1.0"
+tiktoken = "^0.12.0"
 aioclamd = "^1.0.0"
 setuptools = "^80.9.0"
 gcloud-aio-storage = "^9.5.0"
@@ -95,13 +95,13 @@ black = "^24.10.0"
 faker = "^38.2.0"
 httpx = "^0.28.1"
 isort = "^5.13.2"
-poethepoet = "^0.37.0"
+poethepoet = "^0.41.0"
 pre-commit = "^4.4.0"
 pyright = "^1.1.407"
 pytest-mock = "^3.15.1"
-pytest-watcher = "^0.4.2"
+pytest-watcher = "^0.6.3"
 requests = "^2.32.5"
-ruff = "^0.14.5"
+ruff = "^0.15.0"
 # NOTE: please insert new dependencies in their alphabetical location
 
 [build-system]

autogpt_platform/frontend/Dockerfile

@@ -25,8 +25,12 @@ RUN if [ -f .env.production ]; then \
       cp .env.default .env; \
     fi
 RUN pnpm run generate:api
+# Disable source-map generation in Docker builds to halve webpack memory usage.
+# Source maps are only useful when SENTRY_AUTH_TOKEN is set (Vercel deploys);
+# the Docker image never uploads them, so generating them just wastes RAM.
+ENV NEXT_PUBLIC_SOURCEMAPS="false"
 # In CI, we want NEXT_PUBLIC_PW_TEST=true during build so Next.js inlines it
-RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=4096" pnpm build; else NODE_OPTIONS="--max-old-space-size=4096" pnpm build; fi
+RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=8192" pnpm build; else NODE_OPTIONS="--max-old-space-size=8192" pnpm build; fi
 
 # Prod stage - based on NextJS reference Dockerfile https://github.com/vercel/next.js/blob/64271354533ed16da51be5dce85f0dbd15f17517/examples/with-docker/Dockerfile
 FROM node:21-alpine AS prod

autogpt_platform/frontend/next.config.mjs

@@ -1,8 +1,12 @@
 import { withSentryConfig } from "@sentry/nextjs";
 
+// Allow Docker builds to skip source-map generation (halves memory usage).
+// Defaults to true so Vercel/local builds are unaffected.
+const enableSourceMaps = process.env.NEXT_PUBLIC_SOURCEMAPS !== "false";
+
 /** @type {import('next').NextConfig} */
 const nextConfig = {
-  productionBrowserSourceMaps: true,
+  productionBrowserSourceMaps: enableSourceMaps,
   // Externalize OpenTelemetry packages to fix Turbopack HMR issues
   serverExternalPackages: [
     "@opentelemetry/instrumentation",
@@ -14,9 +18,37 @@ const nextConfig = {
     serverActions: {
       bodySizeLimit: "256mb",
     },
-    // Increase body size limit for API routes (file uploads) - 256MB to match backend limit
-    proxyClientMaxBodySize: "256mb",
     middlewareClientMaxBodySize: "256mb",
+    // Limit parallel webpack workers to reduce peak memory during builds.
+    cpus: 2,
+  },
+  // Work around cssnano "Invalid array length" bug in Next.js's bundled
+  // cssnano-simple comment parser when processing very large CSS chunks.
+  // CSS is still bundled correctly; gzip handles most of the size savings anyway.
+  webpack: (config, { dev }) => {
+    if (!dev) {
+      // Next.js adds CssMinimizerPlugin internally (after user config), so we
+      // can't filter it from config.plugins. Instead, intercept the webpack
+      // compilation hooks and replace the buggy plugin's tap with a no-op.
+      config.plugins.push({
+        apply(compiler) {
+          compiler.hooks.compilation.tap(
+            "DisableCssMinimizer",
+            (compilation) => {
+              compilation.hooks.processAssets.intercept({
+                register: (tap) => {
+                  if (tap.name === "CssMinimizerPlugin") {
+                    return { ...tap, fn: async () => {} };
+                  }
+                  return tap;
+                },
+              });
+            },
+          );
+        },
+      });
+    }
+    return config;
   },
   images: {
     domains: [
@@ -54,9 +86,16 @@ const nextConfig = {
   transpilePackages: ["geist"],
 };
 
-const isDevelopmentBuild = process.env.NODE_ENV !== "production";
+// Only run the Sentry webpack plugin when we can actually upload source maps
+// (i.e. on Vercel with SENTRY_AUTH_TOKEN set). The Sentry *runtime* SDK
+// (imported in app code) still captures errors without the plugin.
+// Skipping the plugin saves ~1 GB of peak memory during `next build`.
+const skipSentryPlugin =
+  process.env.NODE_ENV !== "production" ||
+  !enableSourceMaps ||
+  !process.env.SENTRY_AUTH_TOKEN;
 
-export default isDevelopmentBuild
+export default skipSentryPlugin
   ? nextConfig
   : withSentryConfig(nextConfig, {
       // For all available options, see:
@@ -96,7 +135,7 @@ export default isDevelopmentBuild
 
       // This helps Sentry with sourcemaps... https://docs.sentry.io/platforms/javascript/guides/nextjs/sourcemaps/
       sourcemaps: {
-        disable: false,
+        disable: !enableSourceMaps,
         assets: [".next/**/*.js", ".next/**/*.js.map"],
         ignore: ["**/node_modules/**"],
         deleteSourcemapsAfterUpload: false, // Source is public anyway :)

autogpt_platform/frontend/package.json

@@ -7,7 +7,7 @@
   },
   "scripts": {
     "dev": "pnpm run generate:api:force && next dev --turbo",
-    "build": "next build",
+    "build": "cross-env NODE_OPTIONS=--max-old-space-size=16384 next build",
     "start": "next start",
     "start:standalone": "cd .next/standalone && node server.js",
     "lint": "next lint && prettier --check .",
@@ -30,6 +30,7 @@
     "defaults"
   ],
   "dependencies": {
+    "@ai-sdk/react": "3.0.61",
     "@faker-js/faker": "10.0.0",
     "@hookform/resolvers": "5.2.2",
     "@next/third-parties": "15.4.6",
@@ -60,6 +61,10 @@
     "@rjsf/utils": "6.1.2",
     "@rjsf/validator-ajv8": "6.1.2",
     "@sentry/nextjs": "10.27.0",
+    "@streamdown/cjk": "1.0.1",
+    "@streamdown/code": "1.0.1",
+    "@streamdown/math": "1.0.1",
+    "@streamdown/mermaid": "1.0.1",
     "@supabase/ssr": "0.7.0",
     "@supabase/supabase-js": "2.78.0",
     "@tanstack/react-query": "5.90.6",
@@ -68,6 +73,7 @@
     "@vercel/analytics": "1.5.0",
     "@vercel/speed-insights": "1.2.0",
     "@xyflow/react": "12.9.2",
+    "ai": "6.0.59",
     "boring-avatars": "1.11.2",
     "class-variance-authority": "0.7.1",
     "clsx": "2.1.1",
@@ -87,7 +93,6 @@
     "launchdarkly-react-client-sdk": "3.9.0",
     "lodash": "4.17.21",
     "lucide-react": "0.552.0",
-    "moment": "2.30.1",
     "next": "15.4.10",
     "next-themes": "0.4.6",
     "nuqs": "2.7.2",
@@ -102,7 +107,7 @@
     "react-markdown": "9.0.3",
     "react-modal": "3.16.3",
     "react-shepherd": "6.1.9",
-    "react-window": "1.8.11",
+    "react-window": "2.2.0",
     "recharts": "3.3.0",
     "rehype-autolink-headings": "7.1.0",
     "rehype-highlight": "7.0.2",
@@ -112,9 +117,11 @@
     "remark-math": "6.0.0",
     "shepherd.js": "14.5.1",
     "sonner": "2.0.7",
+    "streamdown": "2.1.0",
     "tailwind-merge": "2.6.0",
     "tailwind-scrollbar": "3.1.0",
     "tailwindcss-animate": "1.0.7",
+    "use-stick-to-bottom": "1.1.2",
     "uuid": "11.1.0",
     "vaul": "1.1.2",
     "zod": "3.25.76",
@@ -140,7 +147,7 @@
     "@types/react": "18.3.17",
     "@types/react-dom": "18.3.5",
     "@types/react-modal": "3.16.3",
-    "@types/react-window": "1.8.8",
+    "@types/react-window": "2.0.0",
     "@vitejs/plugin-react": "5.1.2",
     "axe-playwright": "2.2.2",
     "chromatic": "13.3.3",
@@ -172,7 +179,8 @@
   },
   "pnpm": {
     "overrides": {
-      "@opentelemetry/instrumentation": "0.209.0"
+      "@opentelemetry/instrumentation": "0.209.0",
+      "lodash-es": "4.17.23"
     }
   },
   "packageManager": "pnpm@10.20.0+sha512.cf9998222162dd85864d0a8102e7892e7ba4ceadebbf5a31f9c2fce48dfce317a9c53b9f6464d1ef9042cba2e02ae02a9f7c143a2b438cd93c91840f0192b9dd"

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderViewTabs/BuilderViewTabs.tsx

@@ -1,31 +0,0 @@
-"use client";
-
-import { Tabs, TabsList, TabsTrigger } from "@/components/__legacy__/ui/tabs";
-
-export type BuilderView = "old" | "new";
-
-export function BuilderViewTabs({
-  value,
-  onChange,
-}: {
-  value: BuilderView;
-  onChange: (value: BuilderView) => void;
-}) {
-  return (
-    <div className="pointer-events-auto fixed right-4 top-20 z-50">
-      <Tabs
-        value={value}
-        onValueChange={(v: string) => onChange(v as BuilderView)}
-      >
-        <TabsList className="w-fit bg-zinc-900">
-          <TabsTrigger value="old" className="text-gray-100">
-            Old
-          </TabsTrigger>
-          <TabsTrigger value="new" className="text-gray-100">
-            New
-          </TabsTrigger>
-        </TabsList>
-      </Tabs>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/Flow.tsx

@@ -23,6 +23,9 @@ import { useCopyPaste } from "./useCopyPaste";
 import { useFlow } from "./useFlow";
 import { useFlowRealtime } from "./useFlowRealtime";
 
+import "@xyflow/react/dist/style.css";
+import "./flow.css";
+
 export const Flow = () => {
   const [{ flowID, flowExecutionID }] = useQueryStates({
     flowID: parseAsString,

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/Flow/flow.css

@@ -0,0 +1,9 @@
+/* Reset default xyflow handle styles so custom Phosphor icon handles render correctly */
+.react-flow__handle {
+  background: transparent;
+  width: auto;
+  height: auto;
+  border: 0;
+  position: relative;
+  transform: none;
+}

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

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

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx

@@ -70,10 +70,10 @@ export const HorizontalScroll: React.FC<HorizontalScrollAreaProps> = ({
           {children}
         </div>
         {canScrollLeft && (
-          <div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-white via-white/80 to-white/0" />
+          <div className="pointer-events-none absolute inset-y-0 left-0 w-8 bg-gradient-to-r from-background via-background/80 to-background/0" />
         )}
         {canScrollRight && (
-          <div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-white via-white/80 to-white/0" />
+          <div className="pointer-events-none absolute inset-y-0 right-0 w-8 bg-gradient-to-l from-background via-background/80 to-background/0" />
         )}
         {canScrollLeft && (
           <button

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewControlPanel.tsx

@@ -1,100 +1,30 @@
-// import { Separator } from "@/components/__legacy__/ui/separator";
 import { cn } from "@/lib/utils";
 import React, { memo } from "react";
 import { BlockMenu } from "./NewBlockMenu/BlockMenu/BlockMenu";
 import { useNewControlPanel } from "./useNewControlPanel";
-// import { NewSaveControl } from "../SaveControl/NewSaveControl";
-import { GraphExecutionID } from "@/lib/autogpt-server-api";
-// import { ControlPanelButton } from "../ControlPanelButton";
-// import { GraphSearchMenu } from "../GraphMenu/GraphMenu";
 import { Separator } from "@/components/__legacy__/ui/separator";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-import { CustomNode } from "../FlowEditor/nodes/CustomNode/CustomNode";
 import { NewSaveControl } from "./NewSaveControl/NewSaveControl";
 import { UndoRedoButtons } from "./UndoRedoButtons";
 
-export type Control = {
-  icon: React.ReactNode;
-  label: string;
-  disabled?: boolean;
-  onClick: () => void;
-};
+export const NewControlPanel = memo(() => {
+  useNewControlPanel({});
 
-export type NewControlPanelProps = {
-  flowExecutionID?: GraphExecutionID | undefined;
-  visualizeBeads?: "no" | "static" | "animate";
-  pinSavePopover?: boolean;
-  pinBlocksPopover?: boolean;
-  nodes?: CustomNode[];
-  onNodeSelect?: (nodeId: string) => void;
-  onNodeHover?: (nodeId: string) => void;
-};
-export const NewControlPanel = memo(
-  ({
-    flowExecutionID: _flowExecutionID,
-    visualizeBeads: _visualizeBeads,
-    pinSavePopover: _pinSavePopover,
-    pinBlocksPopover: _pinBlocksPopover,
-    nodes: _nodes,
-    onNodeSelect: _onNodeSelect,
-    onNodeHover: _onNodeHover,
-  }: NewControlPanelProps) => {
-    const _isGraphSearchEnabled = useGetFlag(Flag.GRAPH_SEARCH);
-
-    const {
-      // agentDescription,
-      // setAgentDescription,
-      // saveAgent,
-      // agentName,
-      // setAgentName,
-      // savedAgent,
-      // isSaving,
-      // isRunning,
-      // isStopping,
-    } = useNewControlPanel({});
-
-    return (
-      <section
-        className={cn(
-          "absolute left-4 top-10 z-10 overflow-hidden rounded-[1rem] border-none bg-white p-0 shadow-[0_1px_5px_0_rgba(0,0,0,0.1)]",
-        )}
-      >
-        <div className="flex flex-col items-center justify-center rounded-[1rem] p-0">
-          <BlockMenu />
-          {/* <Separator className="text-[#E1E1E1]" />
-        {isGraphSearchEnabled && (
-          <>
-            <GraphSearchMenu
-              nodes={nodes}
-              blockMenuSelected={blockMenuSelected}
-              setBlockMenuSelected={setBlockMenuSelected}
-              onNodeSelect={onNodeSelect}
-              onNodeHover={onNodeHover}
-            />
-            <Separator className="text-[#E1E1E1]" />
-          </>
-        )}
-        {controls.map((control, index) => (
-          <ControlPanelButton
-            key={index}
-            onClick={() => control.onClick()}
-            data-id={`control-button-${index}`}
-            data-testid={`blocks-control-${control.label.toLowerCase()}-button`}
-            disabled={control.disabled || false}
-            className="rounded-none"
-          >
-            {control.icon}
-          </ControlPanelButton>
-        ))} */}
-          <Separator className="text-[#E1E1E1]" />
-          <NewSaveControl />
-          <Separator className="text-[#E1E1E1]" />
-          <UndoRedoButtons />
-        </div>
-      </section>
-    );
-  },
-);
+  return (
+    <section
+      className={cn(
+        "absolute left-4 top-10 z-10 overflow-hidden rounded-[1rem] border-none bg-white p-0 shadow-[0_1px_5px_0_rgba(0,0,0,0.1)]",
+      )}
+    >
+      <div className="flex flex-col items-center justify-center rounded-[1rem] p-0">
+        <BlockMenu />
+        <Separator className="text-[#E1E1E1]" />
+        <NewSaveControl />
+        <Separator className="text-[#E1E1E1]" />
+        <UndoRedoButtons />
+      </div>
+    </section>
+  );
+});
 
 export default NewControlPanel;
 

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewSearchGraph/GraphMenu/GraphMenu.tsx

@@ -1,4 +1,4 @@
-import { CustomNode } from "@/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode";
+import { CustomNode } from "../../../FlowEditor/nodes/CustomNode/CustomNode";
 import {
   Popover,
   PopoverContent,

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewSearchGraph/GraphMenu/useGraphMenu.ts

@@ -1,5 +1,5 @@
 import { useGraphSearch } from "../GraphMenuSearchBar/useGraphMenuSearchBar";
-import { CustomNode } from "@/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode";
+import { CustomNode } from "../../../FlowEditor/nodes/CustomNode/CustomNode";
 
 interface UseGraphMenuProps {
   nodes: CustomNode[];

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewSearchGraph/GraphMenuContent/GraphContent.tsx

@@ -1,7 +1,7 @@
 import React from "react";
 import { Separator } from "@/components/__legacy__/ui/separator";
 import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
-import { beautifyString, getPrimaryCategoryColor } from "@/lib/utils";
+import { beautifyString, categoryColorMap } from "@/lib/utils";
 import { SearchableNode } from "../GraphMenuSearchBar/useGraphMenuSearchBar";
 import { TextRenderer } from "@/components/__legacy__/ui/render";
 import {
@@ -73,14 +73,12 @@ export const GraphSearchContent: React.FC<GraphSearchContentProps> = ({
               }
 
               const nodeTitle =
-                node.data?.metadata?.customized_name ||
-                beautifyString(node.data?.blockType || "").replace(
-                  / Block$/,
-                  "",
-                );
-              const nodeType = beautifyString(
-                node.data?.blockType || "",
-              ).replace(/ Block$/, "");
+                (node.data?.metadata?.customized_name as string) ||
+                beautifyString(node.data?.title || "").replace(/ Block$/, "");
+              const nodeType = beautifyString(node.data?.title || "").replace(
+                / Block$/,
+                "",
+              );
 
               return (
                 <TooltipProvider key={node.id}>
@@ -100,7 +98,13 @@ export const GraphSearchContent: React.FC<GraphSearchContentProps> = ({
                         onMouseLeave={() => onNodeHover?.(null)}
                       >
                         <div
-                          className={`h-full w-3 rounded-l-[7px] ${getPrimaryCategoryColor(node.data?.categories)}`}
+                          className={`h-full w-3 rounded-l-[7px] ${
+                            (node.data?.categories?.[0]?.category &&
+                              categoryColorMap[
+                                node.data.categories[0].category
+                              ]) ||
+                            "bg-gray-300 dark:bg-slate-700"
+                          }`}
                         />
                         <div className="mx-3 flex flex-1 items-center justify-between">
                           <div className="mr-2 min-w-0">
@@ -129,9 +133,10 @@ export const GraphSearchContent: React.FC<GraphSearchContentProps> = ({
                         <div className="font-semibold">
                           Node Type: {nodeType}
                         </div>
-                        {node.data?.metadata?.customized_name && (
+                        {!!node.data?.metadata?.customized_name && (
                           <div className="text-xs text-gray-500">
-                            Custom Name: {node.data.metadata.customized_name}
+                            Custom Name:{" "}
+                            {String(node.data.metadata.customized_name)}
                           </div>
                         )}
                       </div>

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewSearchGraph/GraphMenuSearchBar/useGraphMenuSearchBar.tsx

@@ -1,5 +1,5 @@
 import { useState, useMemo, useDeferredValue } from "react";
-import { CustomNode } from "@/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode";
+import { CustomNode } from "../../../FlowEditor/nodes/CustomNode/CustomNode";
 import { beautifyString } from "@/lib/utils";
 import jaro from "jaro-winkler";
 
@@ -67,10 +67,10 @@ function calculateNodeScore(
   const nodeTitle = (node.data?.title || "").toLowerCase(); // This includes the ID
   const nodeId = (node.id || "").toLowerCase();
   const nodeDescription = (node.data?.description || "").toLowerCase();
-  const blockType = (node.data?.blockType || "").toLowerCase();
+  const blockType = (node.data?.title || "").toLowerCase();
   const beautifiedBlockType = beautifyString(blockType).toLowerCase();
-  const customizedName = (
-    node.data?.metadata?.customized_name || ""
+  const customizedName = String(
+    node.data?.metadata?.customized_name || "",
   ).toLowerCase();
 
   // Get input and output names with defensive checks

autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/useNewControlPanel.ts

@@ -1,54 +1,18 @@
-import { GraphID } from "@/lib/autogpt-server-api";
-import { useSearchParams } from "next/navigation";
 import { useState } from "react";
 
 export interface NewControlPanelProps {
-  // flowExecutionID: GraphExecutionID | undefined;
   visualizeBeads?: "no" | "static" | "animate";
 }
 
 export const useNewControlPanel = ({
-  // flowExecutionID,
   visualizeBeads: _visualizeBeads,
 }: NewControlPanelProps) => {
   const [blockMenuSelected, setBlockMenuSelected] = useState<
     "save" | "block" | "search" | ""
   >("");
-  const query = useSearchParams();
-  const _graphVersion = query.get("flowVersion");
-  const _graphVersionParsed = _graphVersion
-    ? parseInt(_graphVersion)
-    : undefined;
-
-  const _flowID = (query.get("flowID") as GraphID | null) ?? undefined;
-  // const {
-  //   agentDescription,
-  //   setAgentDescription,
-  //   saveAgent,
-  //   agentName,
-  //   setAgentName,
-  //   savedAgent,
-  //   isSaving,
-  //   isRunning,
-  //   isStopping,
-  // } = useAgentGraph(
-  //   flowID,
-  //   graphVersion,
-  //   flowExecutionID,
-  //   visualizeBeads !== "no",
-  // );
 
   return {
     blockMenuSelected,
     setBlockMenuSelected,
-    // agentDescription,
-    // setAgentDescription,
-    // saveAgent,
-    // agentName,
-    // setAgentName,
-    // savedAgent,
-    // isSaving,
-    // isRunning,
-    // isStopping,
   };
 };

autogpt_platform/frontend/src/app/(platform)/build/components/RIghtSidebar.tsx

@@ -1,83 +0,0 @@
-import { useMemo } from "react";
-
-import { Link } from "@/app/api/__generated__/models/link";
-import { useEdgeStore } from "../stores/edgeStore";
-import { useNodeStore } from "../stores/nodeStore";
-import { scrollbarStyles } from "@/components/styles/scrollbars";
-import { cn } from "@/lib/utils";
-import { customEdgeToLink } from "./helper";
-
-export const RightSidebar = () => {
-  const edges = useEdgeStore((s) => s.edges);
-  const nodes = useNodeStore((s) => s.nodes);
-
-  const backendLinks: Link[] = useMemo(
-    () => edges.map(customEdgeToLink),
-    [edges],
-  );
-
-  return (
-    <div
-      className={cn(
-        "flex h-full w-full flex-col border-l border-slate-200 bg-white p-4 dark:border-slate-700 dark:bg-slate-900",
-        scrollbarStyles,
-      )}
-    >
-      <div className="mb-4">
-        <h2 className="text-lg font-semibold text-slate-800 dark:text-slate-200">
-          Graph Debug Panel
-        </h2>
-      </div>
-
-      <div className="flex-1 overflow-y-auto">
-        <h3 className="mb-2 text-sm font-semibold text-slate-700 dark:text-slate-200">
-          Nodes ({nodes.length})
-        </h3>
-        <div className="mb-6 space-y-3">
-          {nodes.map((n) => (
-            <div
-              key={n.id}
-              className="rounded border p-2 text-xs dark:border-slate-700"
-            >
-              <div className="mb-1 font-medium">
-                #{n.id} {n.data?.title ? `– ${n.data.title}` : ""}
-              </div>
-              <div className="text-slate-500 dark:text-slate-400">
-                hardcodedValues
-              </div>
-              <pre className="mt-1 max-h-40 overflow-auto rounded bg-slate-50 p-2 dark:bg-slate-800">
-                {JSON.stringify(n.data?.hardcodedValues ?? {}, null, 2)}
-              </pre>
-            </div>
-          ))}
-        </div>
-
-        <h3 className="mb-2 text-sm font-semibold text-slate-700 dark:text-slate-200">
-          Links ({backendLinks.length})
-        </h3>
-        <div className="mb-6 space-y-3">
-          {backendLinks.map((l) => (
-            <div
-              key={l.id}
-              className="rounded border p-2 text-xs dark:border-slate-700"
-            >
-              <div className="font-medium">
-                {l.source_id}[{l.source_name}] → {l.sink_id}[{l.sink_name}]
-              </div>
-              <div className="mt-1 text-slate-500 dark:text-slate-400">
-                edge.id: {l.id}
-              </div>
-            </div>
-          ))}
-        </div>
-
-        <h4 className="mb-2 text-xs font-semibold text-slate-600 dark:text-slate-300">
-          Backend Links JSON
-        </h4>
-        <pre className="max-h-64 overflow-auto rounded bg-slate-50 p-2 text-[11px] dark:bg-slate-800">
-          {JSON.stringify(backendLinks, null, 2)}
-        </pre>
-      </div>
-    </div>
-  );
-};

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/BlocksControl.tsx

@@ -1,443 +0,0 @@
-import React, { useCallback, useMemo, useState, useDeferredValue } from "react";
-import { Card, CardContent, CardHeader } from "@/components/__legacy__/ui/card";
-import { Label } from "@/components/__legacy__/ui/label";
-import { Button } from "@/components/__legacy__/ui/button";
-import { Input } from "@/components/__legacy__/ui/input";
-import { TextRenderer } from "@/components/__legacy__/ui/render";
-import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
-import { CustomNode } from "@/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode";
-import { beautifyString } from "@/lib/utils";
-import {
-  Popover,
-  PopoverContent,
-  PopoverTrigger,
-} from "@/components/__legacy__/ui/popover";
-import {
-  Block,
-  BlockIORootSchema,
-  BlockUIType,
-  GraphInputSchema,
-  GraphOutputSchema,
-  SpecialBlockID,
-} from "@/lib/autogpt-server-api";
-import { MagnifyingGlassIcon, PlusIcon } from "@radix-ui/react-icons";
-import { IconToyBrick } from "@/components/__legacy__/ui/icons";
-import { getPrimaryCategoryColor } from "@/lib/utils";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipTrigger,
-} from "@/components/atoms/Tooltip/BaseTooltip";
-import { GraphMeta } from "@/lib/autogpt-server-api";
-import jaro from "jaro-winkler";
-import { getV1GetSpecificGraph } from "@/app/api/__generated__/endpoints/graphs/graphs";
-import { okData } from "@/app/api/helpers";
-
-type _Block = Omit<Block, "inputSchema" | "outputSchema"> & {
-  uiKey?: string;
-  inputSchema: BlockIORootSchema | GraphInputSchema;
-  outputSchema: BlockIORootSchema | GraphOutputSchema;
-  hardcodedValues?: Record<string, any>;
-  _cached?: {
-    blockName: string;
-    beautifiedName: string;
-    description: string;
-  };
-};
-
-// Hook to preprocess blocks with cached expensive operations
-const useSearchableBlocks = (blocks: _Block[]): _Block[] => {
-  return useMemo(
-    () =>
-      blocks.map((block) => {
-        if (!block._cached) {
-          block._cached = {
-            blockName: block.name.toLowerCase(),
-            beautifiedName: beautifyString(block.name).toLowerCase(),
-            description: block.description.toLowerCase(),
-          };
-        }
-        return block;
-      }),
-    [blocks],
-  );
-};
-
-interface BlocksControlProps {
-  blocks: _Block[];
-  addBlock: (
-    id: string,
-    name: string,
-    hardcodedValues: Record<string, any>,
-  ) => void;
-  pinBlocksPopover: boolean;
-  flows: GraphMeta[];
-  nodes: CustomNode[];
-}
-
-/**
- * A React functional component that displays a control for managing blocks.
- *
- * @component
- * @param {Object} BlocksControlProps - The properties for the BlocksControl component.
- * @param {Block[]} BlocksControlProps.blocks - An array of blocks to be displayed and filtered.
- * @param {(id: string, name: string) => void} BlocksControlProps.addBlock - A function to call when a block is added.
- * @returns The rendered BlocksControl component.
- */
-export function BlocksControl({
-  blocks: _blocks,
-  addBlock,
-  pinBlocksPopover,
-  flows,
-  nodes,
-}: BlocksControlProps) {
-  const [searchQuery, setSearchQuery] = useState("");
-  const deferredSearchQuery = useDeferredValue(searchQuery);
-  const [selectedCategory, setSelectedCategory] = useState<string | null>(null);
-
-  const blocks = useSearchableBlocks(_blocks);
-
-  const graphHasWebhookNodes = nodes.some((n) =>
-    [BlockUIType.WEBHOOK, BlockUIType.WEBHOOK_MANUAL].includes(n.data.uiType),
-  );
-  const graphHasInputNodes = nodes.some(
-    (n) => n.data.uiType == BlockUIType.INPUT,
-  );
-
-  const filteredAvailableBlocks = useMemo(() => {
-    const blockList = blocks
-      .filter((b) => b.uiType !== BlockUIType.AGENT)
-      .sort((a, b) => a.name.localeCompare(b.name));
-
-    // Agent blocks are created from GraphMeta which doesn't include schemas.
-    // Schemas will be fetched on-demand when the block is actually added.
-    const agentBlockList = flows
-      .map((flow): _Block => {
-        return {
-          id: SpecialBlockID.AGENT,
-          name: flow.name,
-          description:
-            `Ver.${flow.version}` +
-            (flow.description ? ` | ${flow.description}` : ""),
-          categories: [{ category: "AGENT", description: "" }],
-          // Empty schemas - will be populated when block is added
-          inputSchema: { type: "object", properties: {} },
-          outputSchema: { type: "object", properties: {} },
-          staticOutput: false,
-          uiType: BlockUIType.AGENT,
-          costs: [],
-          uiKey: flow.id,
-          hardcodedValues: {
-            graph_id: flow.id,
-            graph_version: flow.version,
-            // Schemas will be fetched on-demand when block is added
-          },
-        };
-      })
-      .map(
-        (agentBlock): _Block => ({
-          ...agentBlock,
-          _cached: {
-            blockName: agentBlock.name.toLowerCase(),
-            beautifiedName: beautifyString(agentBlock.name).toLowerCase(),
-            description: agentBlock.description.toLowerCase(),
-          },
-        }),
-      );
-
-    return blockList
-      .concat(agentBlockList)
-      .map((block) => ({
-        block,
-        score: blockScoreForQuery(block, deferredSearchQuery),
-      }))
-      .filter(
-        ({ block, score }) =>
-          score > 0 &&
-          (!selectedCategory ||
-            block.categories.some((cat) => cat.category === selectedCategory)),
-      )
-      .sort((a, b) => b.score - a.score)
-      .map(({ block }) => ({
-        ...block,
-        notAvailable:
-          (block.uiType == BlockUIType.WEBHOOK &&
-            graphHasWebhookNodes &&
-            "Agents can only have one webhook-triggered block") ||
-          (block.uiType == BlockUIType.WEBHOOK &&
-            graphHasInputNodes &&
-            "Webhook-triggered blocks can't be used together with input blocks") ||
-          (block.uiType == BlockUIType.INPUT &&
-            graphHasWebhookNodes &&
-            "Input blocks can't be used together with a webhook-triggered block") ||
-          null,
-      }));
-  }, [
-    blocks,
-    flows,
-    selectedCategory,
-    deferredSearchQuery,
-    graphHasInputNodes,
-    graphHasWebhookNodes,
-  ]);
-
-  const resetFilters = useCallback(() => {
-    setSearchQuery("");
-    setSelectedCategory(null);
-  }, []);
-
-  // Handler to add a block, fetching graph data on-demand for agent blocks
-  const handleAddBlock = useCallback(
-    async (block: _Block & { notAvailable: string | null }) => {
-      if (block.notAvailable) return;
-
-      // For agent blocks, fetch the full graph to get schemas
-      if (block.uiType === BlockUIType.AGENT && block.hardcodedValues) {
-        const graphID = block.hardcodedValues.graph_id as string;
-        const graphVersion = block.hardcodedValues.graph_version as number;
-        const graphData = okData(
-          await getV1GetSpecificGraph(graphID, { version: graphVersion }),
-        );
-
-        if (graphData) {
-          addBlock(block.id, block.name, {
-            ...block.hardcodedValues,
-            input_schema: graphData.input_schema,
-            output_schema: graphData.output_schema,
-          });
-        } else {
-          // Fallback: add without schemas (will be incomplete)
-          console.error("Failed to fetch graph data for agent block");
-          addBlock(block.id, block.name, block.hardcodedValues || {});
-        }
-      } else {
-        addBlock(block.id, block.name, block.hardcodedValues || {});
-      }
-    },
-    [addBlock],
-  );
-
-  // Extract unique categories from blocks
-  const categories = useMemo(() => {
-    return Array.from(
-      new Set([
-        null,
-        ...blocks
-          .flatMap((block) => block.categories.map((cat) => cat.category))
-          .sort(),
-      ]),
-    );
-  }, [blocks]);
-
-  return (
-    <Popover
-      open={pinBlocksPopover ? true : undefined}
-      onOpenChange={(open) => open || resetFilters()}
-    >
-      <Tooltip delayDuration={500}>
-        <TooltipTrigger asChild>
-          <PopoverTrigger asChild>
-            <Button
-              variant="ghost"
-              size="icon"
-              data-id="blocks-control-popover-trigger"
-              data-testid="blocks-control-blocks-button"
-              name="Blocks"
-              className="dark:hover:bg-slate-800"
-            >
-              <IconToyBrick />
-            </Button>
-          </PopoverTrigger>
-        </TooltipTrigger>
-        <TooltipContent side="right">Blocks</TooltipContent>
-      </Tooltip>
-      <PopoverContent
-        side="right"
-        sideOffset={22}
-        align="start"
-        className="absolute -top-3 w-[17rem] rounded-xl border-none p-0 shadow-none md:w-[30rem]"
-        data-id="blocks-control-popover-content"
-      >
-        <Card className="p-3 pb-0 dark:bg-slate-900">
-          <CardHeader className="flex flex-col gap-x-8 gap-y-1 p-3 px-2">
-            <div className="items-center justify-between">
-              <Label
-                htmlFor="search-blocks"
-                className="whitespace-nowrap text-base font-bold text-black dark:text-white 2xl:text-xl"
-                data-id="blocks-control-label"
-                data-testid="blocks-control-blocks-label"
-              >
-                Blocks
-              </Label>
-            </div>
-            <div className="relative flex items-center">
-              <MagnifyingGlassIcon className="absolute m-2 h-5 w-5 text-gray-500 dark:text-gray-400" />
-              <Input
-                id="search-blocks"
-                type="text"
-                placeholder="Search blocks"
-                value={searchQuery}
-                onChange={(e) => setSearchQuery(e.target.value)}
-                className="rounded-lg px-8 py-5 dark:bg-slate-800 dark:text-white"
-                data-id="blocks-control-search-input"
-                autoComplete="off"
-              />
-            </div>
-            <div
-              className="mt-2 flex flex-wrap gap-2"
-              data-testid="blocks-categories-list"
-            >
-              {categories.map((category) => {
-                const color = getPrimaryCategoryColor([
-                  { category: category || "All", description: "" },
-                ]);
-                const colorClass =
-                  selectedCategory === category ? `${color}` : "";
-                return (
-                  <div
-                    key={category}
-                    data-testid="blocks-category"
-                    role="button"
-                    className={`cursor-pointer rounded-xl border px-2 py-2 text-xs font-medium dark:border-slate-700 dark:text-white ${colorClass}`}
-                    onClick={() =>
-                      setSelectedCategory(
-                        selectedCategory === category ? null : category,
-                      )
-                    }
-                  >
-                    {beautifyString((category || "All").toLowerCase())}
-                  </div>
-                );
-              })}
-            </div>
-          </CardHeader>
-          <CardContent className="overflow-scroll border-t border-t-gray-200 p-0 dark:border-t-slate-700">
-            <ScrollArea
-              className="h-[60vh] w-full"
-              data-id="blocks-control-scroll-area"
-            >
-              {filteredAvailableBlocks.map((block) => (
-                <Card
-                  key={block.uiKey || block.id}
-                  className={`m-2 my-4 flex h-20 shadow-none dark:border-slate-700 dark:bg-slate-800 dark:text-slate-100 dark:hover:bg-slate-700 ${
-                    block.notAvailable
-                      ? "cursor-not-allowed opacity-50"
-                      : "cursor-move hover:shadow-lg"
-                  }`}
-                  data-id={`block-card-${block.id}`}
-                  draggable={!block.notAvailable}
-                  onDragStart={(e) => {
-                    if (block.notAvailable) return;
-                    e.dataTransfer.effectAllowed = "copy";
-                    e.dataTransfer.setData(
-                      "application/reactflow",
-                      JSON.stringify({
-                        blockId: block.id,
-                        blockName: block.name,
-                        hardcodedValues: block?.hardcodedValues || {},
-                      }),
-                    );
-                  }}
-                  onClick={() => handleAddBlock(block)}
-                  title={block.notAvailable ?? undefined}
-                >
-                  <div
-                    className={`-ml-px h-full w-3 rounded-l-xl ${getPrimaryCategoryColor(block.categories)}`}
-                  ></div>
-
-                  <div className="mx-3 flex flex-1 items-center justify-between">
-                    <div className="mr-2 min-w-0">
-                      <span
-                        className="block truncate pb-1 text-sm font-semibold dark:text-white"
-                        data-id={`block-name-${block.id}`}
-                        data-type={block.uiType}
-                        data-testid={`block-name-${block.id}`}
-                      >
-                        <TextRenderer
-                          value={beautifyString(block.name).replace(
-                            / Block$/,
-                            "",
-                          )}
-                          truncateLengthLimit={45}
-                        />
-                      </span>
-                      <span
-                        className="block break-all text-xs font-normal text-gray-500 dark:text-gray-400"
-                        data-testid={`block-description-${block.id}`}
-                      >
-                        <TextRenderer
-                          value={block.description}
-                          truncateLengthLimit={165}
-                        />
-                      </span>
-                    </div>
-                    <div
-                      className="flex flex-shrink-0 items-center gap-1"
-                      data-id={`block-tooltip-${block.id}`}
-                      data-testid={`block-add`}
-                    >
-                      <PlusIcon className="h-6 w-6 rounded-lg bg-gray-200 stroke-black stroke-[0.5px] p-1 dark:bg-gray-700 dark:stroke-white" />
-                    </div>
-                  </div>
-                </Card>
-              ))}
-            </ScrollArea>
-          </CardContent>
-        </Card>
-      </PopoverContent>
-    </Popover>
-  );
-}
-
-/**
- * Evaluates how well a block matches the search query and returns a relevance score.
- * The scoring algorithm works as follows:
- * - Returns 1 if no query (all blocks match equally)
- * - Normalized query for case-insensitive matching
- * - Returns 3 for exact substring matches in block name (highest priority)
- * - Returns 2 when all query words appear in the block name (regardless of order)
- * - Returns 1.X for blocks with names similar to query using Jaro-Winkler distance (X is similarity score)
- * - Returns 0.5 when all query words appear in the block description (lowest priority)
- * - Returns 0 for no match
- *
- * Higher scores will appear first in search results.
- */
-function blockScoreForQuery(block: _Block, query: string): number {
-  if (!query) return 1;
-  const normalizedQuery = query.toLowerCase().trim();
-  const queryWords = normalizedQuery.split(/\s+/);
-
-  // Use cached values for performance
-  const { blockName, beautifiedName, description } = block._cached!;
-
-  // 1. Exact match in name (highest priority)
-  if (
-    blockName.includes(normalizedQuery) ||
-    beautifiedName.includes(normalizedQuery)
-  ) {
-    return 3;
-  }
-
-  // 2. All query words in name (regardless of order)
-  const allWordsInName = queryWords.every(
-    (word) => blockName.includes(word) || beautifiedName.includes(word),
-  );
-  if (allWordsInName) return 2;
-
-  // 3. Similarity with name (Jaro-Winkler)
-  const similarityThreshold = 0.65;
-  const nameSimilarity = jaro(blockName, normalizedQuery);
-  const beautifiedSimilarity = jaro(beautifiedName, normalizedQuery);
-  const maxSimilarity = Math.max(nameSimilarity, beautifiedSimilarity);
-  if (maxSimilarity > similarityThreshold) {
-    return 1 + maxSimilarity; // Score between 1 and 2
-  }
-
-  // 4. All query words in description (lower priority)
-  const allWordsInDescription = queryWords.every((word) =>
-    description.includes(word),
-  );
-  if (allWordsInDescription) return 0.5;
-
-  return 0;
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/BuildActionBar.tsx

@@ -1,119 +0,0 @@
-import React from "react";
-import { cn } from "@/lib/utils";
-import { Button } from "@/components/__legacy__/ui/button";
-import { LogOut } from "lucide-react";
-import { ClockIcon, WarningIcon } from "@phosphor-icons/react";
-import { IconPlay, IconSquare } from "@/components/__legacy__/ui/icons";
-
-interface Props {
-  onClickAgentOutputs?: () => void;
-  onClickRunAgent?: () => void;
-  onClickStopRun: () => void;
-  onClickScheduleButton?: () => void;
-  isRunning: boolean;
-  isDisabled: boolean;
-  className?: string;
-  resolutionModeActive?: boolean;
-}
-
-export const BuildActionBar: React.FC<Props> = ({
-  onClickAgentOutputs,
-  onClickRunAgent,
-  onClickStopRun,
-  onClickScheduleButton,
-  isRunning,
-  isDisabled,
-  className,
-  resolutionModeActive = false,
-}) => {
-  const buttonClasses =
-    "flex items-center gap-2 text-sm font-medium md:text-lg";
-
-  // Show resolution mode message instead of action buttons
-  if (resolutionModeActive) {
-    return (
-      <div
-        className={cn(
-          "flex w-fit select-none items-center justify-center p-4",
-          className,
-        )}
-      >
-        <div className="flex items-center gap-3 rounded-lg border border-amber-300 bg-amber-50 px-4 py-3 dark:border-amber-700 dark:bg-amber-900/30">
-          <WarningIcon className="size-5 text-amber-600 dark:text-amber-400" />
-          <span className="text-sm font-medium text-amber-800 dark:text-amber-200">
-            Remove incompatible connections to continue
-          </span>
-        </div>
-      </div>
-    );
-  }
-
-  return (
-    <div
-      className={cn(
-        "flex w-fit select-none items-center justify-center p-4",
-        className,
-      )}
-    >
-      <div className="flex gap-1 md:gap-4">
-        {onClickAgentOutputs && (
-          <Button
-            className={buttonClasses}
-            variant="outline"
-            size="primary"
-            onClick={onClickAgentOutputs}
-            title="View agent outputs"
-          >
-            <LogOut className="hidden size-5 md:flex" /> Agent Outputs
-          </Button>
-        )}
-
-        {!isRunning ? (
-          <Button
-            className={cn(
-              buttonClasses,
-              onClickRunAgent && isDisabled
-                ? "cursor-default opacity-50 hover:bg-accent"
-                : "",
-            )}
-            variant="accent"
-            size="primary"
-            onClick={onClickRunAgent}
-            disabled={!onClickRunAgent}
-            title="Run the agent"
-            aria-label="Run the agent"
-            data-testid="primary-action-run-agent"
-            data-tutorial-id="primary-action-run-agent"
-          >
-            <IconPlay /> Run
-          </Button>
-        ) : (
-          <Button
-            className={buttonClasses}
-            variant="destructive"
-            size="primary"
-            onClick={onClickStopRun}
-            title="Stop the agent"
-            data-id="primary-action-stop-agent"
-          >
-            <IconSquare /> Stop
-          </Button>
-        )}
-
-        {onClickScheduleButton && (
-          <Button
-            className={buttonClasses}
-            variant="outline"
-            size="primary"
-            onClick={onClickScheduleButton}
-            title="Set up a run schedule for the agent"
-            data-id="primary-action-schedule-agent"
-          >
-            <ClockIcon className="hidden h-5 w-5 md:flex" />
-            Schedule Run
-          </Button>
-        )}
-      </div>
-    </div>
-  );
-};

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/ConnectionLine.tsx

@@ -1,33 +0,0 @@
-import {
-  BaseEdge,
-  ConnectionLineComponentProps,
-  Node,
-  getBezierPath,
-  Position,
-} from "@xyflow/react";
-
-export default function ConnectionLine<NodeType extends Node>({
-  fromPosition,
-  fromHandle,
-  fromX,
-  fromY,
-  toPosition,
-  toX,
-  toY,
-}: ConnectionLineComponentProps<NodeType>) {
-  const sourceX =
-    fromPosition === Position.Right
-      ? fromX + ((fromHandle?.width ?? 0) / 2 - 5)
-      : fromX - ((fromHandle?.width ?? 0) / 2 - 5);
-
-  const [path] = getBezierPath({
-    sourceX: sourceX,
-    sourceY: fromY,
-    sourcePosition: fromPosition,
-    targetX: toX,
-    targetY: toY,
-    targetPosition: toPosition,
-  });
-
-  return <BaseEdge path={path} style={{ strokeWidth: 2, stroke: "#555" }} />;
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/ControlPanel.tsx

@@ -1,86 +0,0 @@
-import { Card, CardContent } from "@/components/__legacy__/ui/card";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipTrigger,
-} from "@/components/atoms/Tooltip/BaseTooltip";
-import { Button } from "@/components/__legacy__/ui/button";
-import { Separator } from "@/components/__legacy__/ui/separator";
-import { cn } from "@/lib/utils";
-import React from "react";
-
-/**
- * Represents a control element for the ControlPanel Component.
- * @type {Object} Control
- * @property {React.ReactNode} icon - The icon of the control from lucide-react https://lucide.dev/icons/
- * @property {string} label - The label of the control, to be leveraged by ToolTip.
- * @property {onclick} onClick - The function to be executed when the control is clicked.
- */
-export type Control = {
-  icon: React.ReactNode;
-  label: string;
-  disabled?: boolean;
-  onClick: () => void;
-};
-
-interface ControlPanelProps {
-  controls: Control[];
-  topChildren?: React.ReactNode;
-  botChildren?: React.ReactNode;
-  className?: string;
-}
-
-/**
- * ControlPanel component displays a panel with controls as icons.tsx with the ability to take in children.
- * @param {Object} ControlPanelProps - The properties of the control panel component.
- * @param {Array} ControlPanelProps.controls - An array of control objects representing actions to be preformed.
- * @param {Array} ControlPanelProps.children - The child components of the control panel.
- * @param {string} ControlPanelProps.className - Additional CSS class names for the control panel.
- * @returns The rendered control panel component.
- */
-export const ControlPanel = ({
-  controls,
-  topChildren,
-  botChildren,
-  className,
-}: ControlPanelProps) => {
-  return (
-    <Card className={cn("m-4 mt-24 w-14 dark:bg-slate-900", className)}>
-      <CardContent className="p-0">
-        <div className="flex flex-col items-center gap-3 rounded-xl py-3">
-          {topChildren}
-          <Separator className="dark:bg-slate-700" />
-          {controls.map((control, index) => (
-            <Tooltip key={index} delayDuration={500}>
-              <TooltipTrigger asChild>
-                <div>
-                  <Button
-                    variant="ghost"
-                    size="icon"
-                    onClick={() => control.onClick()}
-                    data-id={`control-button-${index}`}
-                    data-testid={`blocks-control-${control.label.toLowerCase()}-button`}
-                    disabled={control.disabled || false}
-                    className="dark:bg-slate-900 dark:text-slate-100 dark:hover:bg-slate-800"
-                  >
-                    {control.icon}
-                    <span className="sr-only">{control.label}</span>
-                  </Button>
-                </div>
-              </TooltipTrigger>
-              <TooltipContent
-                side="right"
-                className="dark:bg-slate-800 dark:text-slate-100"
-              >
-                {control.label}
-              </TooltipContent>
-            </Tooltip>
-          ))}
-          <Separator className="dark:bg-slate-700" />
-          {botChildren}
-        </div>
-      </CardContent>
-    </Card>
-  );
-};
-export default ControlPanel;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomEdge/CustomEdge.tsx

@@ -1,240 +0,0 @@
-import React, {
-  useCallback,
-  useContext,
-  useEffect,
-  useState,
-  useRef,
-} from "react";
-import {
-  BaseEdge,
-  EdgeLabelRenderer,
-  EdgeProps,
-  useReactFlow,
-  XYPosition,
-  Edge,
-  Node,
-} from "@xyflow/react";
-import "./customedge.css";
-import { X } from "lucide-react";
-import { BuilderContext } from "../Flow/Flow";
-import { NodeExecutionResult } from "@/lib/autogpt-server-api";
-import { useCustomEdge } from "./useCustomEdge";
-
-export type CustomEdgeData = {
-  edgeColor: string;
-  sourcePos?: XYPosition;
-  isStatic?: boolean;
-  beadUp: number;
-  beadDown: number;
-  beadData?: Map<string, NodeExecutionResult["status"]>;
-};
-
-type Bead = {
-  t: number;
-  targetT: number;
-  startTime: number;
-};
-
-export type CustomEdge = Edge<CustomEdgeData, "custom">;
-
-export function CustomEdge({
-  id,
-  data,
-  selected,
-  sourceX,
-  sourceY,
-  targetX,
-  targetY,
-  markerEnd,
-}: EdgeProps<CustomEdge>) {
-  const [beads, setBeads] = useState<{
-    beads: Bead[];
-    created: number;
-    destroyed: number;
-  }>({ beads: [], created: 0, destroyed: 0 });
-  const beadsRef = useRef(beads);
-  const { svgPath, length, getPointForT, getTForDistance } = useCustomEdge(
-    sourceX - 5,
-    sourceY - 5,
-    targetX + 3,
-    targetY - 5,
-  );
-  const { deleteElements } = useReactFlow<Node, CustomEdge>();
-  const builderContext = useContext(BuilderContext);
-  const { visualizeBeads } = builderContext ?? {
-    visualizeBeads: "no",
-  };
-
-  // Check if this edge is broken (during resolution mode)
-  const isBroken =
-    builderContext?.resolutionMode?.active &&
-    builderContext?.resolutionMode?.brokenEdgeIds?.includes(id);
-
-  const onEdgeRemoveClick = () => {
-    deleteElements({ edges: [{ id }] });
-  };
-
-  const animationDuration = 500; // Duration in milliseconds for bead to travel the curve
-  const beadDiameter = 12;
-  const deltaTime = 16;
-
-  const setTargetPositions = useCallback(
-    (beads: Bead[]) => {
-      const distanceBetween = Math.min(
-        (length - beadDiameter) / (beads.length + 1),
-        beadDiameter,
-      );
-
-      return beads.map((bead, index) => {
-        const distanceFromEnd = beadDiameter * 1.35;
-        const targetPosition = distanceBetween * index + distanceFromEnd;
-        const t = getTForDistance(-targetPosition);
-
-        return {
-          ...bead,
-          t: visualizeBeads === "animate" ? bead.t : t,
-          targetT: t,
-        } as Bead;
-      });
-    },
-    [getTForDistance, length, visualizeBeads],
-  );
-
-  beadsRef.current = beads;
-  useEffect(() => {
-    const beadUp: number = data?.beadUp ?? 0;
-    const beadDown: number = data?.beadDown ?? 0;
-
-    if (
-      beadUp === 0 &&
-      beadDown === 0 &&
-      (beads.created > 0 || beads.destroyed > 0)
-    ) {
-      setBeads({ beads: [], created: 0, destroyed: 0 });
-      return;
-    }
-
-    // Add beads
-    if (beadUp > beads.created) {
-      setBeads(({ beads, created, destroyed }) => {
-        const newBeads = [];
-        for (let i = 0; i < beadUp - created; i++) {
-          newBeads.push({ t: 0, targetT: 0, startTime: Date.now() });
-        }
-
-        const b = setTargetPositions([...beads, ...newBeads]);
-        return { beads: b, created: beadUp, destroyed };
-      });
-    }
-
-    // Animate and remove beads
-    const interval = setInterval(
-      ({ current: beads }) => {
-        // If there are no beads visible or moving, stop re-rendering
-        if (
-          (beadUp === beads.created && beads.created === beads.destroyed) ||
-          beads.beads.every((bead) => bead.t >= bead.targetT)
-        ) {
-          clearInterval(interval);
-          return;
-        }
-
-        setBeads(({ beads, created, destroyed }) => {
-          let destroyedCount = 0;
-
-          const newBeads = beads
-            .map((bead) => {
-              const progressIncrement = deltaTime / animationDuration;
-              const t = Math.min(
-                bead.t + bead.targetT * progressIncrement,
-                bead.targetT,
-              );
-
-              return { ...bead, t };
-            })
-            .filter((bead, index) => {
-              const removeCount = beadDown - destroyed;
-              if (bead.t >= bead.targetT && index < removeCount) {
-                destroyedCount++;
-                return false;
-              }
-              return true;
-            });
-
-          return {
-            beads: setTargetPositions(newBeads),
-            created,
-            destroyed: destroyed + destroyedCount,
-          };
-        });
-      },
-      deltaTime,
-      beadsRef,
-    );
-
-    return () => clearInterval(interval);
-  }, [data?.beadUp, data?.beadDown, setTargetPositions, visualizeBeads]);
-
-  const middle = getPointForT(0.5);
-
-  // Determine edge color - red for broken edges
-  const baseColor = data?.edgeColor ?? "#555555";
-  const edgeColor = isBroken ? "#ef4444" : baseColor;
-  // Add opacity to hex color (99 = 60% opacity, 80 = 50% opacity)
-  const strokeColor = isBroken
-    ? `${edgeColor}99`
-    : selected
-      ? edgeColor
-      : `${edgeColor}80`;
-
-  return (
-    <>
-      <BaseEdge
-        path={svgPath}
-        markerEnd={markerEnd}
-        style={{
-          stroke: strokeColor,
-          strokeWidth: data?.isStatic ? 2.5 : 2,
-          strokeDasharray: data?.isStatic ? "5 3" : undefined,
-        }}
-        className="data-sentry-unmask transition-all duration-200"
-      />
-      <path
-        d={svgPath}
-        fill="none"
-        strokeOpacity={0}
-        strokeWidth={20}
-        className="data-sentry-unmask react-flow__edge-interaction"
-      />
-      <EdgeLabelRenderer>
-        <div
-          style={{
-            position: "absolute",
-            transform: `translate(-50%, -50%) translate(${middle.x}px,${middle.y}px)`,
-            pointerEvents: "all",
-          }}
-          className="edge-label-renderer"
-        >
-          <button
-            className="edge-label-button opacity-0 transition-opacity duration-200 hover:opacity-100"
-            onClick={onEdgeRemoveClick}
-          >
-            <X className="size-4" />
-          </button>
-        </div>
-      </EdgeLabelRenderer>
-      {beads.beads.map((bead, index) => {
-        const pos = getPointForT(bead.t);
-        return (
-          <circle
-            key={index}
-            cx={pos.x}
-            cy={pos.y}
-            r={beadDiameter / 2} // Bead radius
-            fill={data?.edgeColor ?? "#555555"}
-          />
-        );
-      })}
-    </>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomEdge/customedge.css

@@ -1,48 +0,0 @@
-.edge-label-renderer {
-  position: absolute;
-  pointer-events: all;
-}
-
-.edge-label-button {
-  width: 20px;
-  height: 20px;
-  background: #eee;
-  border: 1px solid #fff;
-  cursor: pointer;
-  border-radius: 50%;
-  display: flex;
-  justify-content: center;
-  align-items: center;
-  padding: 0;
-  color: #555;
-  opacity: 0;
-  transition:
-    opacity 0.2s ease-in-out,
-    background-color 0.2s ease-in-out;
-}
-
-.edge-label-button.visible {
-  opacity: 1;
-}
-
-.edge-label-button:hover {
-  box-shadow: 0 0 6px 2px rgba(0, 0, 0, 0.08);
-  background: #f0f0f0;
-}
-
-.edge-label-button svg {
-  width: 14px;
-  height: 14px;
-}
-
-.react-flow__edge-interaction {
-  cursor: pointer;
-}
-
-.react-flow__edges > svg:has(> g.selected) {
-  z-index: 10 !important;
-}
-
-.react-flow__edgelabel-renderer {
-  z-index: 11 !important;
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomEdge/useCustomEdge.ts

@@ -1,157 +0,0 @@
-import { useCallback, useMemo } from "react";
-
-type XYPosition = {
-  x: number;
-  y: number;
-};
-
-export type BezierPath = {
-  sourcePosition: XYPosition;
-  control1: XYPosition;
-  control2: XYPosition;
-  targetPosition: XYPosition;
-};
-
-export function useCustomEdge(
-  sourceX: number,
-  sourceY: number,
-  targetX: number,
-  targetY: number,
-) {
-  const path: BezierPath = useMemo(() => {
-    const xDifference = Math.abs(sourceX - targetX);
-    const yDifference = Math.abs(sourceY - targetY);
-    const xControlDistance =
-      sourceX < targetX ? 64 : Math.max(xDifference / 2, 64);
-    const yControlDistance = yDifference < 128 && sourceX > targetX ? -64 : 0;
-
-    return {
-      sourcePosition: { x: sourceX, y: sourceY },
-      control1: {
-        x: sourceX + xControlDistance,
-        y: sourceY + yControlDistance,
-      },
-      control2: {
-        x: targetX - xControlDistance,
-        y: targetY + yControlDistance,
-      },
-      targetPosition: { x: targetX, y: targetY },
-    };
-  }, [sourceX, sourceY, targetX, targetY]);
-
-  const svgPath = useMemo(
-    () =>
-      `M ${path.sourcePosition.x} ${path.sourcePosition.y} ` +
-      `C ${path.control1.x} ${path.control1.y} ${path.control2.x} ${path.control2.y} ` +
-      `${path.targetPosition.x}, ${path.targetPosition.y}`,
-    [path],
-  );
-
-  const getPointForT = useCallback(
-    (t: number) => {
-      // Bezier formula: (1-t)^3 * p0 + 3*(1-t)^2*t*p1 + 3*(1-t)*t^2*p2 + t^3*p3
-      const x =
-        Math.pow(1 - t, 3) * path.sourcePosition.x +
-        3 * Math.pow(1 - t, 2) * t * path.control1.x +
-        3 * (1 - t) * Math.pow(t, 2) * path.control2.x +
-        Math.pow(t, 3) * path.targetPosition.x;
-
-      const y =
-        Math.pow(1 - t, 3) * path.sourcePosition.y +
-        3 * Math.pow(1 - t, 2) * t * path.control1.y +
-        3 * (1 - t) * Math.pow(t, 2) * path.control2.y +
-        Math.pow(t, 3) * path.targetPosition.y;
-
-      return { x, y };
-    },
-    [path],
-  );
-
-  const getArcLength = useCallback(
-    (t: number, samples: number = 100) => {
-      let length = 0;
-      let prevPoint = getPointForT(0);
-
-      for (let i = 1; i <= samples; i++) {
-        const currT = (i / samples) * t;
-        const currPoint = getPointForT(currT);
-        length += Math.sqrt(
-          Math.pow(currPoint.x - prevPoint.x, 2) +
-            Math.pow(currPoint.y - prevPoint.y, 2),
-        );
-        prevPoint = currPoint;
-      }
-
-      return length;
-    },
-    [getPointForT],
-  );
-
-  const length = useMemo(() => {
-    return getArcLength(1);
-  }, [getArcLength]);
-
-  const getBezierDerivative = useCallback(
-    (t: number) => {
-      const mt = 1 - t;
-      const x =
-        3 *
-        (mt * mt * (path.control1.x - path.sourcePosition.x) +
-          2 * mt * t * (path.control2.x - path.control1.x) +
-          t * t * (path.targetPosition.x - path.control2.x));
-      const y =
-        3 *
-        (mt * mt * (path.control1.y - path.sourcePosition.y) +
-          2 * mt * t * (path.control2.y - path.control1.y) +
-          t * t * (path.targetPosition.y - path.control2.y));
-      return { x, y };
-    },
-    [path],
-  );
-
-  const getTForDistance = useCallback(
-    (distance: number, epsilon: number = 0.0001) => {
-      if (distance < 0) {
-        distance = length + distance; // If distance is negative, calculate from the end of the curve
-      }
-
-      let t = distance / getArcLength(1);
-      let prevT = 0;
-
-      while (Math.abs(t - prevT) > epsilon) {
-        prevT = t;
-        const length = getArcLength(t);
-        const derivative = Math.sqrt(
-          Math.pow(getBezierDerivative(t).x, 2) +
-            Math.pow(getBezierDerivative(t).y, 2),
-        );
-        t -= (length - distance) / derivative;
-        t = Math.max(0, Math.min(1, t)); // Clamp t between 0 and 1
-      }
-
-      return t;
-    },
-    [getArcLength, getBezierDerivative, length],
-  );
-
-  const getPointAtDistance = useCallback(
-    (distance: number) => {
-      if (distance < 0) {
-        distance = length + distance; // If distance is negative, calculate from the end of the curve
-      }
-
-      const t = getTForDistance(distance);
-      return getPointForT(t);
-    },
-    [getTForDistance, getPointForT, length],
-  );
-
-  return {
-    path,
-    svgPath,
-    length,
-    getPointForT,
-    getTForDistance,
-    getPointAtDistance,
-  };
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/IncompatibilityDialog.tsx

@@ -1,244 +0,0 @@
-import React from "react";
-import {
-  Dialog,
-  DialogContent,
-  DialogDescription,
-  DialogFooter,
-  DialogHeader,
-  DialogTitle,
-} from "@/components/__legacy__/ui/dialog";
-import { Button } from "@/components/__legacy__/ui/button";
-import { AlertTriangle, XCircle, PlusCircle } from "lucide-react";
-import { IncompatibilityInfo } from "../../../hooks/useSubAgentUpdate/types";
-import { beautifyString } from "@/lib/utils";
-import { Alert, AlertDescription } from "@/components/molecules/Alert/Alert";
-
-interface IncompatibilityDialogProps {
-  isOpen: boolean;
-  onClose: () => void;
-  onConfirm: () => void;
-  currentVersion: number;
-  latestVersion: number;
-  agentName: string;
-  incompatibilities: IncompatibilityInfo;
-}
-
-export const IncompatibilityDialog: React.FC<IncompatibilityDialogProps> = ({
-  isOpen,
-  onClose,
-  onConfirm,
-  currentVersion,
-  latestVersion,
-  agentName,
-  incompatibilities,
-}) => {
-  const hasMissingInputs = incompatibilities.missingInputs.length > 0;
-  const hasMissingOutputs = incompatibilities.missingOutputs.length > 0;
-  const hasNewInputs = incompatibilities.newInputs.length > 0;
-  const hasNewOutputs = incompatibilities.newOutputs.length > 0;
-  const hasNewRequired = incompatibilities.newRequiredInputs.length > 0;
-  const hasTypeMismatches = incompatibilities.inputTypeMismatches.length > 0;
-
-  const hasInputChanges = hasMissingInputs || hasNewInputs;
-  const hasOutputChanges = hasMissingOutputs || hasNewOutputs;
-
-  return (
-    <Dialog open={isOpen} onOpenChange={(open) => !open && onClose()}>
-      <DialogContent className="max-w-lg">
-        <DialogHeader>
-          <DialogTitle className="flex items-center gap-2">
-            <AlertTriangle className="h-5 w-5 text-amber-500" />
-            Incompatible Update
-          </DialogTitle>
-          <DialogDescription>
-            Updating <strong>{beautifyString(agentName)}</strong> from v
-            {currentVersion} to v{latestVersion} will break some connections.
-          </DialogDescription>
-        </DialogHeader>
-
-        <div className="space-y-4 py-2">
-          {/* Input changes - two column layout */}
-          {hasInputChanges && (
-            <TwoColumnSection
-              title="Input Changes"
-              leftIcon={<XCircle className="h-4 w-4 text-red-500" />}
-              leftTitle="Removed"
-              leftItems={incompatibilities.missingInputs}
-              rightIcon={<PlusCircle className="h-4 w-4 text-green-500" />}
-              rightTitle="Added"
-              rightItems={incompatibilities.newInputs}
-            />
-          )}
-
-          {/* Output changes - two column layout */}
-          {hasOutputChanges && (
-            <TwoColumnSection
-              title="Output Changes"
-              leftIcon={<XCircle className="h-4 w-4 text-red-500" />}
-              leftTitle="Removed"
-              leftItems={incompatibilities.missingOutputs}
-              rightIcon={<PlusCircle className="h-4 w-4 text-green-500" />}
-              rightTitle="Added"
-              rightItems={incompatibilities.newOutputs}
-            />
-          )}
-
-          {hasTypeMismatches && (
-            <SingleColumnSection
-              icon={<XCircle className="h-4 w-4 text-red-500" />}
-              title="Type Changed"
-              description="These connected inputs have a different type:"
-              items={incompatibilities.inputTypeMismatches.map(
-                (m) => `${m.name} (${m.oldType} → ${m.newType})`,
-              )}
-            />
-          )}
-
-          {hasNewRequired && (
-            <SingleColumnSection
-              icon={<PlusCircle className="h-4 w-4 text-amber-500" />}
-              title="New Required Inputs"
-              description="These inputs are now required:"
-              items={incompatibilities.newRequiredInputs}
-            />
-          )}
-        </div>
-
-        <Alert variant="warning">
-          <AlertDescription>
-            If you proceed, you&apos;ll need to remove the broken connections
-            before you can save or run your agent.
-          </AlertDescription>
-        </Alert>
-
-        <DialogFooter className="gap-2 sm:gap-0">
-          <Button variant="outline" onClick={onClose}>
-            Cancel
-          </Button>
-          <Button
-            variant="destructive"
-            onClick={onConfirm}
-            className="bg-amber-600 hover:bg-amber-700"
-          >
-            Update Anyway
-          </Button>
-        </DialogFooter>
-      </DialogContent>
-    </Dialog>
-  );
-};
-
-interface TwoColumnSectionProps {
-  title: string;
-  leftIcon: React.ReactNode;
-  leftTitle: string;
-  leftItems: string[];
-  rightIcon: React.ReactNode;
-  rightTitle: string;
-  rightItems: string[];
-}
-
-const TwoColumnSection: React.FC<TwoColumnSectionProps> = ({
-  title,
-  leftIcon,
-  leftTitle,
-  leftItems,
-  rightIcon,
-  rightTitle,
-  rightItems,
-}) => (
-  <div className="rounded-md border border-gray-200 p-3 dark:border-gray-700">
-    <span className="font-medium">{title}</span>
-    <div className="mt-2 grid grid-cols-2 items-start gap-4">
-      {/* Left column - Breaking changes */}
-      <div className="min-w-0">
-        <div className="flex items-center gap-1.5 text-sm text-gray-500 dark:text-gray-400">
-          {leftIcon}
-          <span>{leftTitle}</span>
-        </div>
-        <ul className="mt-1.5 space-y-1">
-          {leftItems.length > 0 ? (
-            leftItems.map((item) => (
-              <li
-                key={item}
-                className="text-sm text-gray-700 dark:text-gray-300"
-              >
-                <code className="rounded bg-red-50 px-1 py-0.5 font-mono text-xs text-red-700 dark:bg-red-900/30 dark:text-red-300">
-                  {item}
-                </code>
-              </li>
-            ))
-          ) : (
-            <li className="text-sm italic text-gray-400 dark:text-gray-500">
-              None
-            </li>
-          )}
-        </ul>
-      </div>
-
-      {/* Right column - Possible solutions */}
-      <div className="min-w-0">
-        <div className="flex items-center gap-1.5 text-sm text-gray-500 dark:text-gray-400">
-          {rightIcon}
-          <span>{rightTitle}</span>
-        </div>
-        <ul className="mt-1.5 space-y-1">
-          {rightItems.length > 0 ? (
-            rightItems.map((item) => (
-              <li
-                key={item}
-                className="text-sm text-gray-700 dark:text-gray-300"
-              >
-                <code className="rounded bg-green-50 px-1 py-0.5 font-mono text-xs text-green-700 dark:bg-green-900/30 dark:text-green-300">
-                  {item}
-                </code>
-              </li>
-            ))
-          ) : (
-            <li className="text-sm italic text-gray-400 dark:text-gray-500">
-              None
-            </li>
-          )}
-        </ul>
-      </div>
-    </div>
-  </div>
-);
-
-interface SingleColumnSectionProps {
-  icon: React.ReactNode;
-  title: string;
-  description: string;
-  items: string[];
-}
-
-const SingleColumnSection: React.FC<SingleColumnSectionProps> = ({
-  icon,
-  title,
-  description,
-  items,
-}) => (
-  <div className="rounded-md border border-gray-200 p-3 dark:border-gray-700">
-    <div className="flex items-center gap-2">
-      {icon}
-      <span className="font-medium">{title}</span>
-    </div>
-    <p className="mt-1 text-sm text-gray-500 dark:text-gray-400">
-      {description}
-    </p>
-    <ul className="mt-2 space-y-1">
-      {items.map((item) => (
-        <li
-          key={item}
-          className="ml-4 list-disc text-sm text-gray-700 dark:text-gray-300"
-        >
-          <code className="rounded bg-gray-100 px-1 py-0.5 font-mono text-xs dark:bg-gray-800">
-            {item}
-          </code>
-        </li>
-      ))}
-    </ul>
-  </div>
-);
-
-export default IncompatibilityDialog;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/SubAgentUpdateBar.tsx

@@ -1,130 +0,0 @@
-import React from "react";
-import { Button } from "@/components/__legacy__/ui/button";
-import { ArrowUp, AlertTriangle, Info } from "lucide-react";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipTrigger,
-} from "@/components/atoms/Tooltip/BaseTooltip";
-import { IncompatibilityInfo } from "../../../hooks/useSubAgentUpdate/types";
-import { cn } from "@/lib/utils";
-
-interface SubAgentUpdateBarProps {
-  currentVersion: number;
-  latestVersion: number;
-  isCompatible: boolean;
-  incompatibilities: IncompatibilityInfo | null;
-  onUpdate: () => void;
-  isInResolutionMode?: boolean;
-}
-
-export const SubAgentUpdateBar: React.FC<SubAgentUpdateBarProps> = ({
-  currentVersion,
-  latestVersion,
-  isCompatible,
-  incompatibilities,
-  onUpdate,
-  isInResolutionMode = false,
-}) => {
-  if (isInResolutionMode) {
-    return <ResolutionModeBar incompatibilities={incompatibilities} />;
-  }
-
-  return (
-    <div className="flex items-center justify-between gap-2 rounded-t-lg bg-blue-50 px-3 py-2 dark:bg-blue-900/30">
-      <div className="flex items-center gap-2">
-        <ArrowUp className="h-4 w-4 text-blue-600 dark:text-blue-400" />
-        <span className="text-sm text-blue-700 dark:text-blue-300">
-          Update available (v{currentVersion} → v{latestVersion})
-        </span>
-        {!isCompatible && (
-          <Tooltip>
-            <TooltipTrigger asChild>
-              <AlertTriangle className="h-4 w-4 text-amber-500" />
-            </TooltipTrigger>
-            <TooltipContent className="max-w-xs">
-              <p className="font-medium">Incompatible changes detected</p>
-              <p className="text-xs text-gray-400">
-                Click Update to see details
-              </p>
-            </TooltipContent>
-          </Tooltip>
-        )}
-      </div>
-      <Button
-        size="sm"
-        variant={isCompatible ? "default" : "outline"}
-        onClick={onUpdate}
-        className={cn(
-          "h-7 text-xs",
-          !isCompatible && "border-amber-500 text-amber-600 hover:bg-amber-50",
-        )}
-      >
-        Update
-      </Button>
-    </div>
-  );
-};
-
-interface ResolutionModeBarProps {
-  incompatibilities: IncompatibilityInfo | null;
-}
-
-const ResolutionModeBar: React.FC<ResolutionModeBarProps> = ({
-  incompatibilities,
-}) => {
-  const formatIncompatibilities = () => {
-    if (!incompatibilities) return "No incompatibilities";
-
-    const items: string[] = [];
-
-    if (incompatibilities.missingInputs.length > 0) {
-      items.push(
-        `Missing inputs: ${incompatibilities.missingInputs.join(", ")}`,
-      );
-    }
-    if (incompatibilities.missingOutputs.length > 0) {
-      items.push(
-        `Missing outputs: ${incompatibilities.missingOutputs.join(", ")}`,
-      );
-    }
-    if (incompatibilities.newRequiredInputs.length > 0) {
-      items.push(
-        `New required inputs: ${incompatibilities.newRequiredInputs.join(", ")}`,
-      );
-    }
-    if (incompatibilities.inputTypeMismatches.length > 0) {
-      const mismatches = incompatibilities.inputTypeMismatches
-        .map((m) => `${m.name} (${m.oldType} → ${m.newType})`)
-        .join(", ");
-      items.push(`Type changed: ${mismatches}`);
-    }
-
-    return items.join("\n");
-  };
-
-  return (
-    <div className="flex items-center justify-between gap-2 rounded-t-lg bg-amber-50 px-3 py-2 dark:bg-amber-900/30">
-      <div className="flex items-center gap-2">
-        <AlertTriangle className="h-4 w-4 text-amber-600 dark:text-amber-400" />
-        <span className="text-sm text-amber-700 dark:text-amber-300">
-          Remove incompatible connections
-        </span>
-        <Tooltip>
-          <TooltipTrigger asChild>
-            <Info className="h-4 w-4 cursor-help text-amber-500" />
-          </TooltipTrigger>
-          <TooltipContent className="max-w-sm whitespace-pre-line">
-            <p className="font-medium">Incompatible changes:</p>
-            <p className="mt-1 text-xs">{formatIncompatibilities()}</p>
-            <p className="mt-2 text-xs text-gray-400">
-              Delete the red connections to continue
-            </p>
-          </TooltipContent>
-        </Tooltip>
-      </div>
-    </div>
-  );
-};
-
-export default SubAgentUpdateBar;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/CustomNode/customnode.css

@@ -1,131 +0,0 @@
-.custom-node {
-  color: #000000;
-  box-sizing: border-box;
-  transition: border-color 0.3s ease-in-out;
-}
-
-.custom-node .custom-switch {
-  padding: 0.5rem 1.25rem;
-  display: flex;
-  align-items: center;
-  justify-content: space-between;
-}
-
-.error-message {
-  color: #d9534f;
-  font-size: 13px;
-  padding-left: 0.5rem;
-}
-
-/* Existing styles */
-.handle-container {
-  display: flex;
-  position: relative;
-  margin-bottom: 0px;
-  padding: 5px;
-  min-height: 44px;
-  height: 100%;
-}
-
-.react-flow__handle {
-  background: transparent;
-  width: auto;
-  height: auto;
-  border: 0;
-  position: relative;
-  transform: none;
-}
-
-.border-error {
-  border: 1px solid #d9534f;
-}
-
-.select-input {
-  width: 100%;
-  padding: 5px;
-  border-radius: 4px;
-  border: 1px solid #000;
-  background: #fff;
-  color: #000;
-}
-
-.radio-label {
-  display: block;
-  margin: 5px 0;
-  color: #000;
-}
-
-.number-input {
-  width: 100%;
-  padding: 5px;
-  border-radius: 4px;
-  background: #fff;
-  color: #000;
-}
-
-.array-item-container {
-  display: flex;
-  align-items: center;
-  margin-bottom: 5px;
-}
-
-.array-item-input {
-  flex-grow: 1;
-  padding: 5px;
-  border-radius: 4px;
-  border: 1px solid #000;
-  background: #fff;
-  color: #000;
-}
-
-.array-item-remove {
-  background: #d9534f;
-  border: none;
-  color: white;
-  cursor: pointer;
-  margin-left: 5px;
-  border-radius: 4px;
-  padding: 5px 10px;
-}
-
-.array-item-add {
-  background: #5bc0de;
-  border: none;
-  color: white;
-  cursor: pointer;
-  border-radius: 4px;
-  padding: 5px 10px;
-  margin-top: 5px;
-}
-
-.error-message {
-  color: #d9534f;
-  font-size: 13px;
-  margin-top: 5px;
-  margin-left: 5px;
-}
-
-/* Styles for node states */
-.completed {
-  border-color: #27ae60; /* Green border for completed nodes */
-}
-
-.running {
-  border-color: #f39c12; /* Orange border for running nodes */
-}
-
-.failed {
-  border-color: #c0392b; /* Red border for failed nodes */
-}
-
-.incomplete {
-  border-color: #9f14ab; /* Pink border for incomplete nodes */
-}
-
-.queued {
-  border-color: #25e6e6; /* Cyan border for queued nodes */
-}
-
-.custom-switch {
-  padding-left: 2px;
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/DataTable.tsx

@@ -1,166 +0,0 @@
-import { beautifyString } from "@/lib/utils";
-import { Clipboard, Maximize2 } from "lucide-react";
-import React, { useMemo, useState } from "react";
-import { Button } from "../../../../../components/__legacy__/ui/button";
-import { ContentRenderer } from "../../../../../components/__legacy__/ui/render";
-import {
-  Table,
-  TableBody,
-  TableCell,
-  TableHead,
-  TableHeader,
-  TableRow,
-} from "../../../../../components/__legacy__/ui/table";
-import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
-import {
-  globalRegistry,
-  OutputItem,
-} from "@/components/contextual/OutputRenderers";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-import { useToast } from "../../../../../components/molecules/Toast/use-toast";
-import ExpandableOutputDialog from "./ExpandableOutputDialog";
-
-type DataTableProps = {
-  title?: string;
-  truncateLongData?: boolean;
-  data: { [key: string]: Array<any> };
-};
-
-export default function DataTable({
-  title,
-  truncateLongData,
-  data,
-}: DataTableProps) {
-  const { toast } = useToast();
-  const enableEnhancedOutputHandling = useGetFlag(
-    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
-  );
-  const [expandedDialog, setExpandedDialog] = useState<{
-    isOpen: boolean;
-    execId: string;
-    pinName: string;
-    data: any[];
-  } | null>(null);
-
-  // Prepare renderers for each item when enhanced mode is enabled
-  const getItemRenderer = useMemo(() => {
-    if (!enableEnhancedOutputHandling) return null;
-    return (item: unknown) => {
-      const metadata: OutputMetadata = {};
-      return globalRegistry.getRenderer(item, metadata);
-    };
-  }, [enableEnhancedOutputHandling]);
-
-  const copyData = (pin: string, data: string) => {
-    navigator.clipboard.writeText(data).then(() => {
-      toast({
-        title: `"${pin}" data copied to clipboard!`,
-        duration: 2000,
-      });
-    });
-  };
-
-  const openExpandedView = (pinName: string, pinData: any[]) => {
-    setExpandedDialog({
-      isOpen: true,
-      execId: title || "Unknown Execution",
-      pinName,
-      data: pinData,
-    });
-  };
-
-  const closeExpandedView = () => {
-    setExpandedDialog(null);
-  };
-
-  return (
-    <>
-      {title && <strong className="mt-2 flex justify-center">{title}</strong>}
-      <Table className="cursor-default select-text">
-        <TableHeader>
-          <TableRow>
-            <TableHead>Pin</TableHead>
-            <TableHead>Data</TableHead>
-          </TableRow>
-        </TableHeader>
-        <TableBody>
-          {Object.entries(data).map(([key, value]) => (
-            <TableRow className="group" key={key}>
-              <TableCell className="cursor-text">
-                {beautifyString(key)}
-              </TableCell>
-              <TableCell className="cursor-text">
-                <div className="flex min-h-9 items-center whitespace-pre-wrap">
-                  <div className="absolute right-1 top-auto m-1 hidden gap-1 group-hover:flex">
-                    <Button
-                      variant="outline"
-                      size="icon"
-                      onClick={() => openExpandedView(key, value)}
-                      title="Expand Full View"
-                    >
-                      <Maximize2 size={18} />
-                    </Button>
-                    <Button
-                      variant="outline"
-                      size="icon"
-                      onClick={() =>
-                        copyData(
-                          beautifyString(key),
-                          value
-                            .map((i) =>
-                              typeof i === "object"
-                                ? JSON.stringify(i, null, 2)
-                                : String(i),
-                            )
-                            .join(", "),
-                        )
-                      }
-                      title="Copy Data"
-                    >
-                      <Clipboard size={18} />
-                    </Button>
-                  </div>
-                  {value.map((item, index) => {
-                    const renderer = getItemRenderer?.(item);
-                    if (enableEnhancedOutputHandling && renderer) {
-                      const metadata: OutputMetadata = {};
-                      return (
-                        <React.Fragment key={index}>
-                          <OutputItem
-                            value={item}
-                            metadata={metadata}
-                            renderer={renderer}
-                          />
-                          {index < value.length - 1 && ", "}
-                        </React.Fragment>
-                      );
-                    }
-                    return (
-                      <React.Fragment key={index}>
-                        <ContentRenderer
-                          value={item}
-                          truncateLongData={truncateLongData}
-                        />
-                        {index < value.length - 1 && ", "}
-                      </React.Fragment>
-                    );
-                  })}
-                </div>
-              </TableCell>
-            </TableRow>
-          ))}
-        </TableBody>
-      </Table>
-
-      {expandedDialog && (
-        <ExpandableOutputDialog
-          isOpen={expandedDialog.isOpen}
-          onClose={closeExpandedView}
-          execId={expandedDialog.execId}
-          pinName={expandedDialog.pinName}
-          data={expandedDialog.data}
-        />
-      )}
-    </>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/ExpandableOutputDialog.tsx

@@ -1,269 +0,0 @@
-import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
-import {
-  globalRegistry,
-  OutputActions,
-  OutputItem,
-} from "@/components/contextual/OutputRenderers";
-import { Dialog } from "@/components/molecules/Dialog/Dialog";
-import { beautifyString } from "@/lib/utils";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-import { Clipboard, Maximize2 } from "lucide-react";
-import React, { FC, useMemo, useState } from "react";
-import { Button } from "../../../../../components/__legacy__/ui/button";
-import { ContentRenderer } from "../../../../../components/__legacy__/ui/render";
-import { ScrollArea } from "../../../../../components/__legacy__/ui/scroll-area";
-import { Separator } from "../../../../../components/__legacy__/ui/separator";
-import { Switch } from "../../../../../components/atoms/Switch/Switch";
-import { useToast } from "../../../../../components/molecules/Toast/use-toast";
-
-interface ExpandableOutputDialogProps {
-  isOpen: boolean;
-  onClose: () => void;
-  execId: string;
-  pinName: string;
-  data: any[];
-}
-
-const ExpandableOutputDialog: FC<ExpandableOutputDialogProps> = ({
-  isOpen,
-  onClose,
-  execId,
-  pinName,
-  data,
-}) => {
-  const { toast } = useToast();
-  const enableEnhancedOutputHandling = useGetFlag(
-    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
-  );
-  const [useEnhancedRenderer, setUseEnhancedRenderer] = useState(false);
-
-  // Prepare items for the enhanced renderer system
-  const outputItems = useMemo(() => {
-    if (!data || !useEnhancedRenderer) return [];
-
-    const items: Array<{
-      key: string;
-      label: string;
-      value: unknown;
-      metadata?: OutputMetadata;
-      renderer: any;
-    }> = [];
-
-    data.forEach((value, index) => {
-      const metadata: OutputMetadata = {};
-
-      // Extract metadata from the value if it's an object
-      if (
-        typeof value === "object" &&
-        value !== null &&
-        !React.isValidElement(value)
-      ) {
-        const objValue = value as any;
-        if (objValue.type) metadata.type = objValue.type;
-        if (objValue.mimeType) metadata.mimeType = objValue.mimeType;
-        if (objValue.filename) metadata.filename = objValue.filename;
-        if (objValue.language) metadata.language = objValue.language;
-      }
-
-      const renderer = globalRegistry.getRenderer(value, metadata);
-      if (renderer) {
-        items.push({
-          key: `item-${index}`,
-          label: index === 0 ? beautifyString(pinName) : "",
-          value,
-          metadata,
-          renderer,
-        });
-      } else {
-        // Fallback to text renderer
-        const textRenderer = globalRegistry
-          .getAllRenderers()
-          .find((r) => r.name === "TextRenderer");
-        if (textRenderer) {
-          items.push({
-            key: `item-${index}`,
-            label: index === 0 ? beautifyString(pinName) : "",
-            value:
-              typeof value === "string"
-                ? value
-                : JSON.stringify(value, null, 2),
-            metadata,
-            renderer: textRenderer,
-          });
-        }
-      }
-    });
-
-    return items;
-  }, [data, useEnhancedRenderer, pinName]);
-
-  const copyData = () => {
-    const formattedData = data
-      .map((item) =>
-        typeof item === "object" ? JSON.stringify(item, null, 2) : String(item),
-      )
-      .join("\n\n");
-
-    navigator.clipboard.writeText(formattedData).then(() => {
-      toast({
-        title: `"${beautifyString(pinName)}" data copied to clipboard!`,
-        duration: 2000,
-      });
-    });
-  };
-
-  return (
-    <Dialog
-      title={
-        <div className="flex items-center justify-between pr-8">
-          <div className="flex items-center gap-2">
-            <Maximize2 size={20} />
-            Full Output Preview
-          </div>
-          {enableEnhancedOutputHandling && (
-            <div className="flex items-center gap-3">
-              <label
-                htmlFor="enhanced-rendering-toggle"
-                className="cursor-pointer select-none text-sm font-normal text-gray-600"
-              >
-                Enhanced Rendering
-              </label>
-              <Switch
-                id="enhanced-rendering-toggle"
-                checked={useEnhancedRenderer}
-                onCheckedChange={setUseEnhancedRenderer}
-              />
-            </div>
-          )}
-        </div>
-      }
-      controlled={{
-        isOpen,
-        set: (open) => {
-          if (!open) onClose();
-        },
-      }}
-      onClose={onClose}
-      styling={{
-        maxWidth: "56rem",
-        width: "90vw",
-        height: "90vh",
-      }}
-    >
-      <Dialog.Content>
-        <div className="flex h-full flex-col">
-          <div className="pb-4">
-            <p className="text-sm text-zinc-600">
-              Execution ID: <span className="font-mono text-xs">{execId}</span>
-              <br />
-              Pin:{" "}
-              <span className="font-semibold">{beautifyString(pinName)}</span>
-            </p>
-          </div>
-
-          <div className="flex flex-1 flex-col overflow-hidden">
-            {useEnhancedRenderer && outputItems.length > 0 && (
-              <div className="border-b px-4 py-2">
-                <OutputActions
-                  items={outputItems.map((item) => ({
-                    value: item.value,
-                    metadata: item.metadata,
-                    renderer: item.renderer,
-                  }))}
-                />
-              </div>
-            )}
-            <ScrollArea className="h-full">
-              <div className="p-4">
-                {data.length > 0 ? (
-                  useEnhancedRenderer ? (
-                    <div className="space-y-4">
-                      {outputItems.map((item) => (
-                        <OutputItem
-                          key={item.key}
-                          value={item.value}
-                          metadata={item.metadata}
-                          renderer={item.renderer}
-                          label={item.label}
-                        />
-                      ))}
-                    </div>
-                  ) : (
-                    <div className="space-y-4">
-                      {data.map((item, index) => (
-                        <div
-                          key={index}
-                          className="rounded-lg border bg-gray-50 p-4"
-                        >
-                          <div className="mb-2 flex items-center justify-between">
-                            <span className="text-sm font-medium text-gray-600">
-                              Item {index + 1} of {data.length}
-                            </span>
-                            <Button
-                              variant="outline"
-                              size="sm"
-                              onClick={() => {
-                                const itemData =
-                                  typeof item === "object"
-                                    ? JSON.stringify(item, null, 2)
-                                    : String(item);
-                                navigator.clipboard
-                                  .writeText(itemData)
-                                  .then(() => {
-                                    toast({
-                                      title: `Item ${index + 1} copied to clipboard!`,
-                                      duration: 2000,
-                                    });
-                                  });
-                              }}
-                              className="flex items-center gap-1"
-                            >
-                              <Clipboard size={14} />
-                              Copy Item
-                            </Button>
-                          </div>
-                          <Separator className="mb-3" />
-                          <div className="whitespace-pre-wrap break-words font-mono text-sm">
-                            <ContentRenderer
-                              value={item}
-                              truncateLongData={false}
-                            />
-                          </div>
-                        </div>
-                      ))}
-                    </div>
-                  )
-                ) : (
-                  <div className="py-8 text-center text-gray-500">
-                    No data available
-                  </div>
-                )}
-              </div>
-            </ScrollArea>
-          </div>
-
-          <Dialog.Footer className="flex justify-between">
-            <div className="text-sm text-gray-600">
-              {data.length} item{data.length !== 1 ? "s" : ""} total
-            </div>
-            <div className="flex gap-2">
-              {!useEnhancedRenderer && (
-                <Button
-                  variant="outline"
-                  onClick={copyData}
-                  className="flex items-center gap-1"
-                >
-                  <Clipboard size={16} />
-                  Copy All
-                </Button>
-              )}
-              <Button onClick={onClose}>Close</Button>
-            </div>
-          </Dialog.Footer>
-        </div>
-      </Dialog.Content>
-    </Dialog>
-  );
-};
-
-export default ExpandableOutputDialog;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/Flow/flow.css

@@ -1,103 +0,0 @@
-/* flow.css or index.css */
-
-body {
-  font-family:
-    -apple-system, BlinkMacSystemFont, "Segoe UI", "Roboto", "Oxygen", "Ubuntu",
-    "Cantarell", "Fira Sans", "Droid Sans", "Helvetica Neue", sans-serif;
-}
-
-code {
-  font-family:
-    source-code-pro, Menlo, Monaco, Consolas, "Courier New", monospace;
-}
-
-.modal {
-  position: absolute;
-  top: 50%;
-  left: 50%;
-  right: auto;
-  bottom: auto;
-  margin-right: -50%;
-  transform: translate(-50%, -50%);
-  background: #ffffff;
-  padding: 20px;
-  border: 1px solid #ccc;
-  border-radius: 4px;
-  color: #000000;
-}
-
-.overlay {
-  position: fixed;
-  top: 0;
-  left: 0;
-  right: 0;
-  bottom: 0;
-  background-color: rgba(0, 0, 0, 0.75);
-}
-
-.modal h2 {
-  margin-top: 0;
-}
-
-.modal button {
-  margin-right: 10px;
-}
-
-.modal form {
-  display: flex;
-  flex-direction: column;
-}
-
-.modal form div {
-  margin-bottom: 15px;
-}
-
-.sidebar {
-  position: fixed;
-  top: 0;
-  left: -600px;
-  width: 350px;
-  height: calc(100vh - 68px); /* Full height minus top offset */
-  background-color: #ffffff;
-  color: #000000;
-  padding: 20px;
-  transition: left 0.3s ease;
-  z-index: 1000;
-  overflow-y: auto;
-  margin-top: 68px; /* Margin to push content below the top fixed area */
-}
-
-.sidebar.open {
-  left: 0;
-}
-
-.sidebar h3 {
-  margin: 0 0 10px;
-}
-
-.sidebar input {
-  margin: 0 0 10px;
-}
-
-.sidebarNodeRowStyle {
-  display: flex;
-  justify-content: space-between;
-  align-items: center;
-  background-color: #e2e2e2;
-  padding: 10px;
-  margin-bottom: 10px;
-  border-radius: 10px;
-  cursor: grab;
-}
-
-.sidebarNodeRowStyle.dragging {
-  opacity: 0.5;
-}
-
-.flow-container {
-  position: absolute;
-  top: 0;
-  left: 0;
-  width: 100vw;
-  height: 100vh;
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/GraphSearchControl.tsx

@@ -1,82 +0,0 @@
-import React from "react";
-import {
-  Popover,
-  PopoverContent,
-  PopoverTrigger,
-} from "@/components/__legacy__/ui/popover";
-import { Button } from "@/components/atoms/Button/Button";
-import { MagnifyingGlassIcon } from "@radix-ui/react-icons";
-import { CustomNode } from "@/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode";
-import { GraphSearchContent } from "../NewControlPanel/NewSearchGraph/GraphMenuContent/GraphContent";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipTrigger,
-} from "@/components/atoms/Tooltip/BaseTooltip";
-import { useGraphMenu } from "../NewControlPanel/NewSearchGraph/GraphMenu/useGraphMenu";
-
-interface GraphSearchControlProps {
-  nodes: CustomNode[];
-  onNodeSelect: (nodeId: string) => void;
-  onNodeHover?: (nodeId: string | null) => void;
-}
-
-export function GraphSearchControl({
-  nodes,
-  onNodeSelect,
-  onNodeHover,
-}: GraphSearchControlProps) {
-  // Use the same hook as GraphSearchMenu for consistency
-  const {
-    open,
-    searchQuery,
-    setSearchQuery,
-    filteredNodes,
-    handleNodeSelect,
-    handleOpenChange,
-  } = useGraphMenu({
-    nodes,
-    blockMenuSelected: "", // We don't need to track this in the old control panel
-    setBlockMenuSelected: () => {}, // Not needed in this context
-    onNodeSelect,
-  });
-
-  return (
-    <Popover open={open} onOpenChange={handleOpenChange}>
-      <Tooltip delayDuration={500}>
-        <TooltipTrigger asChild>
-          <PopoverTrigger asChild>
-            <Button
-              variant="ghost"
-              size="icon"
-              data-id="graph-search-control-trigger"
-              data-testid="graph-search-control-button"
-              name="Search"
-              className="dark:hover:bg-slate-800"
-            >
-              <MagnifyingGlassIcon className="h-5 w-5" />
-            </Button>
-          </PopoverTrigger>
-        </TooltipTrigger>
-        <TooltipContent side="right">Search Graph</TooltipContent>
-      </Tooltip>
-
-      <PopoverContent
-        side="right"
-        sideOffset={22}
-        align="start"
-        alignOffset={-50} // Offset upward to align with control panel top
-        className="absolute -top-3 w-[17rem] rounded-xl border-none p-0 shadow-none md:w-[30rem]"
-        data-id="graph-search-popover-content"
-      >
-        <GraphSearchContent
-          searchQuery={searchQuery}
-          onSearchChange={setSearchQuery}
-          filteredNodes={filteredNodes}
-          onNodeSelect={handleNodeSelect}
-          onNodeHover={onNodeHover}
-        />
-      </PopoverContent>
-    </Popover>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/InputModalComponent.tsx

@@ -1,107 +0,0 @@
-import React, { FC, useEffect, useState } from "react";
-import { Button } from "../../../../../components/__legacy__/ui/button";
-import { Textarea } from "../../../../../components/__legacy__/ui/textarea";
-import { Maximize2, Minimize2, Clipboard } from "lucide-react";
-import { createPortal } from "react-dom";
-import { toast } from "../../../../../components/molecules/Toast/use-toast";
-
-interface ModalProps {
-  isOpen: boolean;
-  onClose: () => void;
-  onSave: (value: string) => void;
-  title?: string;
-  defaultValue: string;
-}
-
-const InputModalComponent: FC<ModalProps> = ({
-  isOpen,
-  onClose,
-  onSave,
-  title,
-  defaultValue,
-}) => {
-  const [tempValue, setTempValue] = useState(defaultValue);
-  const [isMaximized, setIsMaximized] = useState(false);
-
-  useEffect(() => {
-    if (isOpen) {
-      setTempValue(defaultValue);
-      setIsMaximized(false);
-    }
-  }, [isOpen, defaultValue]);
-
-  const handleSave = () => {
-    onSave(tempValue);
-    onClose();
-  };
-
-  const toggleSize = () => {
-    setIsMaximized(!isMaximized);
-  };
-
-  const copyValue = () => {
-    navigator.clipboard.writeText(tempValue).then(() => {
-      toast({
-        title: "Input value copied to clipboard!",
-        duration: 2000,
-      });
-    });
-  };
-
-  if (!isOpen) {
-    return null;
-  }
-
-  const modalContent = (
-    <div
-      id="modal-content"
-      className={`fixed rounded-lg border-[1.5px] bg-white p-5 ${
-        isMaximized ? "inset-[128px] flex flex-col" : `w-[90%] max-w-[800px]`
-      }`}
-    >
-      <h2 className="mb-4 text-center text-lg font-semibold">
-        {title || "Enter input text"}
-      </h2>
-      <div className="nowheel relative flex-grow">
-        <Textarea
-          className="h-full min-h-[200px] w-full resize-none"
-          value={tempValue}
-          onChange={(e) => setTempValue(e.target.value)}
-        />
-        <div className="absolute bottom-2 right-2 flex space-x-2">
-          <Button onClick={copyValue} size="icon" variant="outline">
-            <Clipboard size={18} />
-          </Button>
-          <Button onClick={toggleSize} size="icon" variant="outline">
-            {isMaximized ? <Minimize2 size={18} /> : <Maximize2 size={18} />}
-          </Button>
-        </div>
-      </div>
-      <div className="mt-4 flex justify-end space-x-2">
-        <Button onClick={onClose} variant="outline">
-          Cancel
-        </Button>
-        <Button onClick={handleSave}>Save</Button>
-      </div>
-    </div>
-  );
-
-  return (
-    <>
-      {isMaximized ? (
-        createPortal(
-          <div className="fixed inset-0 flex items-center justify-center bg-white bg-opacity-60">
-            {modalContent}
-          </div>,
-          document.body,
-        )
-      ) : (
-        <div className="nodrag fixed inset-0 flex items-center justify-center bg-white bg-opacity-60">
-          {modalContent}
-        </div>
-      )}
-    </>
-  );
-};
-
-export default InputModalComponent;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeHandle.tsx

@@ -1,163 +0,0 @@
-import { BlockIOSubSchema } from "@/lib/autogpt-server-api/types";
-import {
-  cn,
-  beautifyString,
-  getTypeBgColor,
-  getTypeTextColor,
-  getEffectiveType,
-} from "@/lib/utils";
-import { FC, memo, useCallback } from "react";
-import { Handle, Position } from "@xyflow/react";
-import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip";
-
-type HandleProps = {
-  keyName: string;
-  schema: BlockIOSubSchema;
-  isConnected: boolean;
-  isRequired?: boolean;
-  side: "left" | "right";
-  title?: string;
-  className?: string;
-  isBroken?: boolean;
-};
-
-// Move the constant out of the component to avoid re-creation on every render.
-const TYPE_NAME: Record<string, string> = {
-  string: "text",
-  number: "number",
-  integer: "integer",
-  boolean: "true/false",
-  object: "object",
-  array: "list",
-  null: "null",
-};
-
-// Extract and memoize the Dot component so that it doesn't re-render unnecessarily.
-const Dot: FC<{ isConnected: boolean; type?: string; isBroken?: boolean }> =
-  memo(({ isConnected, type, isBroken }) => {
-    const color = isBroken
-      ? "border-red-500 bg-red-100 dark:bg-red-900/30"
-      : isConnected
-        ? getTypeBgColor(type || "any")
-        : "border-gray-300 dark:border-gray-600";
-    return (
-      <div
-        className={cn(
-          "m-1 h-4 w-4 rounded-full border-2 bg-white transition-colors duration-100 group-hover:bg-gray-300 dark:bg-slate-800 dark:group-hover:bg-gray-700",
-          color,
-          isBroken && "opacity-50",
-        )}
-      />
-    );
-  });
-Dot.displayName = "Dot";
-
-const NodeHandle: FC<HandleProps> = ({
-  keyName,
-  schema,
-  isConnected,
-  isRequired,
-  side,
-  title,
-  className,
-  isBroken = false,
-}) => {
-  // Extract effective type from schema (handles anyOf/oneOf/allOf wrappers)
-  const effectiveType = getEffectiveType(schema);
-
-  const typeClass = `text-sm ${getTypeTextColor(effectiveType || "any")} ${
-    side === "left" ? "text-left" : "text-right"
-  }`;
-
-  const label = (
-    <div className={cn("flex flex-grow flex-row", isBroken && "opacity-50")}>
-      <span
-        className={cn(
-          "data-sentry-unmask text-m green flex items-end pr-2 text-gray-900 dark:text-gray-100",
-          className,
-          isBroken && "text-red-500 line-through",
-        )}
-      >
-        {title || schema.title || beautifyString(keyName.toLowerCase())}
-        {isRequired ? "*" : ""}
-      </span>
-      <span
-        className={cn(
-          `${typeClass} data-sentry-unmask flex items-end`,
-          isBroken && "text-red-400",
-        )}
-      >
-        ({TYPE_NAME[effectiveType as keyof typeof TYPE_NAME] || "any"})
-      </span>
-    </div>
-  );
-
-  // Use a native HTML onContextMenu handler instead of wrapping a large node with a Radix ContextMenu trigger.
-  const handleContextMenu = useCallback(
-    (e: React.MouseEvent<HTMLDivElement>) => {
-      e.preventDefault();
-      // Optionally, you can trigger a custom, lightweight context menu here.
-    },
-    [],
-  );
-
-  if (side === "left") {
-    return (
-      <div
-        key={keyName}
-        className={cn("handle-container", isBroken && "pointer-events-none")}
-        onContextMenu={handleContextMenu}
-      >
-        <Handle
-          type="target"
-          data-testid={`input-handle-${keyName}`}
-          position={Position.Left}
-          id={keyName}
-          className={cn("group -ml-[38px]", isBroken && "cursor-not-allowed")}
-          isConnectable={!isBroken}
-        >
-          <div className="pointer-events-none flex items-center">
-            <Dot
-              isConnected={isConnected}
-              type={effectiveType}
-              isBroken={isBroken}
-            />
-            {label}
-          </div>
-        </Handle>
-        <InformationTooltip description={schema.description} />
-      </div>
-    );
-  } else {
-    return (
-      <div
-        key={keyName}
-        className={cn(
-          "handle-container justify-end",
-          isBroken && "pointer-events-none",
-        )}
-        onContextMenu={handleContextMenu}
-      >
-        <Handle
-          type="source"
-          data-testid={`output-handle-${keyName}`}
-          position={Position.Right}
-          id={keyName}
-          className={cn("group -mr-[38px]", isBroken && "cursor-not-allowed")}
-          isConnectable={!isBroken}
-        >
-          <div className="pointer-events-none flex items-center">
-            {label}
-            <Dot
-              isConnected={isConnected}
-              type={effectiveType}
-              isBroken={isBroken}
-            />
-          </div>
-        </Handle>
-      </div>
-    );
-  }
-};
-
-export default memo(NodeHandle);

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeOutputs.tsx

@@ -1,158 +0,0 @@
-import React, { useContext, useMemo, useState } from "react";
-import { Button } from "@/components/__legacy__/ui/button";
-import { Maximize2 } from "lucide-react";
-import * as Separator from "@radix-ui/react-separator";
-import { ContentRenderer } from "@/components/__legacy__/ui/render";
-import type { OutputMetadata } from "@/components/contextual/OutputRenderers";
-import {
-  globalRegistry,
-  OutputItem,
-} from "@/components/contextual/OutputRenderers";
-import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
-
-import { beautifyString } from "@/lib/utils";
-
-import { BuilderContext } from "./Flow/Flow";
-import ExpandableOutputDialog from "./ExpandableOutputDialog";
-
-type NodeOutputsProps = {
-  title?: string;
-  truncateLongData?: boolean;
-  data: { [key: string]: Array<any> };
-};
-
-export default function NodeOutputs({
-  title,
-  truncateLongData,
-  data,
-}: NodeOutputsProps) {
-  const builderContext = useContext(BuilderContext);
-  const enableEnhancedOutputHandling = useGetFlag(
-    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
-  );
-
-  const [expandedDialog, setExpandedDialog] = useState<{
-    isOpen: boolean;
-    execId: string;
-    pinName: string;
-    data: any[];
-  } | null>(null);
-
-  if (!builderContext) {
-    throw new Error(
-      "BuilderContext consumer must be inside FlowEditor component",
-    );
-  }
-
-  const { getNodeTitle } = builderContext;
-
-  // Prepare renderers for each item when enhanced mode is enabled
-  const getItemRenderer = useMemo(() => {
-    if (!enableEnhancedOutputHandling) return null;
-    return (item: unknown) => {
-      const metadata: OutputMetadata = {};
-      return globalRegistry.getRenderer(item, metadata);
-    };
-  }, [enableEnhancedOutputHandling]);
-
-  const getBeautifiedPinName = (pin: string) => {
-    if (!pin.startsWith("tools_^_")) {
-      return beautifyString(pin);
-    }
-    // Special handling for tool pins: replace node ID with node title
-    const toolNodeID = pin.slice(8).split("_~_")[0]; // tools_^_{node_id}_~_{field}
-    const toolNodeTitle = getNodeTitle(toolNodeID);
-    return toolNodeTitle
-      ? beautifyString(pin.replace(toolNodeID, toolNodeTitle))
-      : beautifyString(pin);
-  };
-
-  const openExpandedView = (pinName: string, pinData: any[]) => {
-    setExpandedDialog({
-      isOpen: true,
-      execId: title || "Node Output",
-      pinName,
-      data: pinData,
-    });
-  };
-
-  const closeExpandedView = () => {
-    setExpandedDialog(null);
-  };
-  return (
-    <div className="m-4 space-y-4">
-      {title && <strong className="mt-2flex">{title}</strong>}
-      {Object.entries(data).map(([pin, dataArray]) => (
-        <div key={pin} className="group">
-          <div className="flex items-center justify-between">
-            <div className="flex items-center">
-              <strong className="mr-2">Pin:</strong>
-              <span>{getBeautifiedPinName(pin)}</span>
-            </div>
-            {(truncateLongData || dataArray.length > 10) && (
-              <Button
-                variant="outline"
-                size="sm"
-                onClick={() => openExpandedView(pin, dataArray)}
-                className="hidden items-center gap-1 group-hover:flex"
-                title="Expand Full View"
-              >
-                <Maximize2 size={14} />
-                Expand
-              </Button>
-            )}
-          </div>
-          <div className="mt-2">
-            <strong className="mr-2">Data:</strong>
-            <div className="mt-1">
-              {dataArray.slice(0, 10).map((item, index) => {
-                const renderer = getItemRenderer?.(item);
-                if (enableEnhancedOutputHandling && renderer) {
-                  const metadata: OutputMetadata = {};
-                  return (
-                    <React.Fragment key={index}>
-                      <OutputItem
-                        value={item}
-                        metadata={metadata}
-                        renderer={renderer}
-                      />
-                      {index < Math.min(dataArray.length, 10) - 1 && ", "}
-                    </React.Fragment>
-                  );
-                }
-                return (
-                  <React.Fragment key={index}>
-                    <ContentRenderer
-                      value={item}
-                      truncateLongData={truncateLongData}
-                    />
-                    {index < Math.min(dataArray.length, 10) - 1 && ", "}
-                  </React.Fragment>
-                );
-              })}
-              {dataArray.length > 10 && (
-                <span style={{ color: "#888" }}>
-                  <br />
-                  <b>⋮</b>
-                  <br />
-                  <span>and {dataArray.length - 10} more</span>
-                </span>
-              )}
-            </div>
-            <Separator.Root className="my-4 h-[1px] bg-gray-300" />
-          </div>
-        </div>
-      ))}
-
-      {expandedDialog && (
-        <ExpandableOutputDialog
-          isOpen={expandedDialog.isOpen}
-          onClose={closeExpandedView}
-          execId={expandedDialog.execId}
-          pinName={expandedDialog.pinName}
-          data={expandedDialog.data}
-        />
-      )}
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/NodeTableInput.tsx

@@ -1,205 +0,0 @@
-import { FC, useCallback, useEffect, useState } from "react";
-
-import NodeHandle from "@/app/(platform)/build/components/legacy-builder/NodeHandle";
-import type {
-  BlockIOTableSubSchema,
-  TableCellValue,
-  TableRow,
-} from "@/lib/autogpt-server-api/types";
-import type { ConnectedEdge } from "./CustomNode/CustomNode";
-import { cn } from "@/lib/utils";
-import { PlusIcon, XIcon } from "@phosphor-icons/react";
-import { Button } from "@/components/atoms/Button/Button";
-import { Input } from "@/components/atoms/Input/Input";
-
-interface NodeTableInputProps {
-  /** Unique identifier for the node in the builder graph */
-  nodeId: string;
-  /** Key identifier for this specific input field within the node */
-  selfKey: string;
-  /** Schema definition for the table structure */
-  schema: BlockIOTableSubSchema;
-  /** Column headers for the table */
-  headers: string[];
-  /** Initial row data for the table */
-  rows?: TableRow[];
-  /** Validation errors mapped by field key */
-  errors: { [key: string]: string | undefined };
-  /** Graph connections between nodes in the builder */
-  connections: ConnectedEdge[];
-  /** Callback when table data changes */
-  handleInputChange: (key: string, value: TableRow[]) => void;
-  /** Callback when input field is clicked (for builder selection) */
-  handleInputClick: (key: string) => void;
-  /** Additional CSS classes */
-  className?: string;
-  /** Display name for the input field */
-  displayName?: string;
-}
-
-/**
- * Table input component for the workflow builder interface.
- *
- * This component is specifically designed for use in the agent builder where users
- * design workflows with connected nodes. It includes graph connection capabilities
- * via NodeHandle and is tightly integrated with the builder's state management.
- *
- * @warning Do NOT use this component in runtime/execution contexts (like RunAgentInputs).
- * For runtime table inputs, use a simpler implementation without builder-specific features.
- *
- * @example
- * ```tsx
- * <NodeTableInput
- *   nodeId="node-123"
- *   selfKey="table_data"
- *   schema={tableSchema}
- *   headers={["Name", "Value"]}
- *   rows={existingData}
- *   connections={graphConnections}
- *   handleInputChange={handleChange}
- *   handleInputClick={handleClick}
- *   errors={{}}
- * />
- * ```
- *
- * @see Used exclusively in: `/app/(platform)/build/components/legacy-builder/NodeInputs.tsx`
- */
-export const NodeTableInput: FC<NodeTableInputProps> = ({
-  nodeId,
-  selfKey,
-  schema,
-  headers,
-  rows = [],
-  errors,
-  connections,
-  handleInputChange,
-  handleInputClick: _handleInputClick,
-  className,
-  displayName,
-}) => {
-  const [tableData, setTableData] = useState<TableRow[]>(rows);
-
-  // Sync with parent state when rows change
-  useEffect(() => {
-    setTableData(rows);
-  }, [rows]);
-
-  const isConnected = (key: string) =>
-    connections.some((c) => c.targetHandle === key && c.target === nodeId);
-
-  const updateTableData = useCallback(
-    (newData: TableRow[]) => {
-      setTableData(newData);
-      handleInputChange(selfKey, newData);
-    },
-    [selfKey, handleInputChange],
-  );
-
-  const updateCell = (
-    rowIndex: number,
-    header: string,
-    value: TableCellValue,
-  ) => {
-    const newData = [...tableData];
-    if (!newData[rowIndex]) {
-      newData[rowIndex] = {};
-    }
-    newData[rowIndex][header] = value;
-    updateTableData(newData);
-  };
-
-  const addRow = () => {
-    if (!headers || headers.length === 0) {
-      return;
-    }
-    const newRow: TableRow = {};
-    headers.forEach((header) => {
-      newRow[header] = "";
-    });
-    updateTableData([...tableData, newRow]);
-  };
-
-  const removeRow = (index: number) => {
-    const newData = tableData.filter((_, i) => i !== index);
-    updateTableData(newData);
-  };
-
-  return (
-    <div className={cn("w-full space-y-2", className)}>
-      <NodeHandle
-        title={displayName || selfKey}
-        keyName={selfKey}
-        schema={schema}
-        isConnected={isConnected(selfKey)}
-        isRequired={false}
-        side="left"
-      />
-
-      {!isConnected(selfKey) && (
-        <div className="nodrag overflow-x-auto">
-          <table className="w-full border-collapse">
-            <thead>
-              <tr>
-                {headers.map((header, index) => (
-                  <th
-                    key={index}
-                    className="border border-gray-300 bg-gray-100 px-2 py-1 text-left text-sm font-medium dark:border-gray-600 dark:bg-gray-800"
-                  >
-                    {header}
-                  </th>
-                ))}
-                <th className="w-10"></th>
-              </tr>
-            </thead>
-            <tbody>
-              {tableData.map((row, rowIndex) => (
-                <tr key={rowIndex}>
-                  {headers.map((header, colIndex) => (
-                    <td
-                      key={colIndex}
-                      className="border border-gray-300 p-1 dark:border-gray-600"
-                    >
-                      <Input
-                        id={`${selfKey}-${rowIndex}-${header}`}
-                        label={header}
-                        type="text"
-                        value={String(row[header] || "")}
-                        onChange={(e) =>
-                          updateCell(rowIndex, header, e.target.value)
-                        }
-                        className="h-8 w-full"
-                        placeholder={`Enter ${header}`}
-                      />
-                    </td>
-                  ))}
-                  <td className="p-1">
-                    <Button
-                      variant="ghost"
-                      size="small"
-                      onClick={() => removeRow(rowIndex)}
-                      className="h-8 w-8 p-0"
-                    >
-                      <XIcon />
-                    </Button>
-                  </td>
-                </tr>
-              ))}
-            </tbody>
-          </table>
-
-          <Button
-            className="mt-2 bg-gray-200 font-normal text-black hover:text-white dark:bg-gray-700 dark:text-white dark:hover:bg-gray-600"
-            onClick={addRow}
-            size="small"
-          >
-            <PlusIcon className="mr-2" /> Add Row
-          </Button>
-        </div>
-      )}
-
-      {errors[selfKey] && (
-        <span className="text-sm text-red-500">{errors[selfKey]}</span>
-      )}
-    </div>
-  );
-};

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/OttoChatWidget.tsx

@@ -1,311 +0,0 @@
-"use client";
-
-import React, { useEffect, useState, useRef } from "react";
-import ReactMarkdown from "react-markdown";
-
-import type { GraphID } from "@/lib/autogpt-server-api/types";
-import { askOtto } from "@/app/(platform)/build/actions";
-import { cn } from "@/lib/utils";
-import { environment } from "@/services/environment";
-
-interface Message {
-  type: "user" | "assistant";
-  content: string;
-}
-
-export default function OttoChatWidget({
-  graphID,
-  className,
-}: {
-  graphID?: GraphID;
-  className?: string;
-}): React.ReactNode {
-  const [isOpen, setIsOpen] = useState(false);
-  const [messages, setMessages] = useState<Message[]>([]);
-  const [inputValue, setInputValue] = useState("");
-  const [isProcessing, setIsProcessing] = useState(false);
-  const [includeGraphData, setIncludeGraphData] = useState(false);
-  const messagesEndRef = useRef<HTMLDivElement>(null);
-
-  useEffect(() => {
-    // Add welcome message when component mounts
-    if (messages.length === 0) {
-      setMessages([
-        {
-          type: "assistant",
-          content: "Hello, I am Otto! Ask me anything about AutoGPT!",
-        },
-      ]);
-    }
-  }, [messages.length]);
-
-  useEffect(() => {
-    // Scroll to bottom whenever messages change
-    messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
-  }, [messages]);
-
-  const handleSubmit = async (e: React.FormEvent) => {
-    e.preventDefault();
-    if (!inputValue.trim() || isProcessing) return;
-
-    const userMessage = inputValue.trim();
-    setInputValue("");
-    setIsProcessing(true);
-
-    // Add user message to chat
-    setMessages((prev) => [...prev, { type: "user", content: userMessage }]);
-
-    // Add temporary processing message
-    setMessages((prev) => [
-      ...prev,
-      { type: "assistant", content: "Processing your question..." },
-    ]);
-
-    const conversationHistory = messages.reduce<
-      { query: string; response: string }[]
-    >((acc, msg, i, arr) => {
-      if (
-        msg.type === "user" &&
-        i + 1 < arr.length &&
-        arr[i + 1].type === "assistant" &&
-        arr[i + 1].content !== "Processing your question..."
-      ) {
-        acc.push({
-          query: msg.content,
-          response: arr[i + 1].content,
-        });
-      }
-      return acc;
-    }, []);
-
-    try {
-      const data = await askOtto(
-        userMessage,
-        conversationHistory,
-        includeGraphData,
-        graphID,
-      );
-
-      // Check if the response contains an error
-      if ("error" in data && data.error === true) {
-        // Handle different error types
-        let errorMessage =
-          "Sorry, there was an error processing your message. Please try again.";
-
-        if (data.answer === "Authentication required") {
-          errorMessage = "Please sign in to use the chat feature.";
-        } else if (data.answer === "Failed to connect to Otto service") {
-          errorMessage =
-            "Otto service is currently unavailable. Please try again later.";
-        } else if (data.answer.includes("timed out")) {
-          errorMessage = "Request timed out. Please try again later.";
-        }
-
-        // Remove processing message and add error message
-        setMessages((prev) => [
-          ...prev.slice(0, -1),
-          { type: "assistant", content: errorMessage },
-        ]);
-      } else {
-        // Remove processing message and add actual response
-        setMessages((prev) => [
-          ...prev.slice(0, -1),
-          { type: "assistant", content: data.answer },
-        ]);
-      }
-    } catch (error) {
-      console.error("Unexpected error in chat widget:", error);
-      setMessages((prev) => [
-        ...prev.slice(0, -1),
-        {
-          type: "assistant",
-          content:
-            "An unexpected error occurred. Please refresh the page and try again.",
-        },
-      ]);
-    } finally {
-      setIsProcessing(false);
-      setIncludeGraphData(false);
-    }
-  };
-
-  // Don't render the chat widget if we're not on the build page or in local mode
-  if (environment.isLocal()) {
-    return null;
-  }
-
-  if (!isOpen) {
-    return (
-      <div className={className}>
-        <button
-          onClick={() => setIsOpen(true)}
-          className="inline-flex h-14 w-14 items-center justify-center whitespace-nowrap rounded-2xl bg-[rgba(65,65,64,1)] text-neutral-50 shadow transition-colors hover:bg-neutral-900/90 focus-visible:outline-none focus-visible:ring-1 focus-visible:ring-neutral-950 disabled:pointer-events-none disabled:opacity-50 dark:bg-neutral-50 dark:text-neutral-900 dark:hover:bg-neutral-50/90 dark:focus-visible:ring-neutral-300"
-          aria-label="Open chat widget"
-        >
-          <svg
-            viewBox="0 0 24 24"
-            className="h-6 w-6"
-            stroke="currentColor"
-            strokeWidth="2"
-            fill="none"
-            strokeLinecap="round"
-            strokeLinejoin="round"
-          >
-            <path d="M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z" />
-          </svg>
-        </button>
-      </div>
-    );
-  }
-
-  return (
-    <div
-      className={cn(
-        "flex h-[600px] w-[600px] flex-col rounded-lg border bg-background shadow-xl",
-        className,
-        "z-40",
-      )}
-    >
-      {/* Header */}
-      <div className="flex items-center justify-between border-b p-4">
-        <h2 className="font-semibold">Otto Assistant</h2>
-        <button
-          onClick={() => setIsOpen(false)}
-          className="text-muted-foreground transition-colors hover:text-foreground"
-          aria-label="Close chat"
-        >
-          <svg
-            viewBox="0 0 24 24"
-            className="h-5 w-5"
-            stroke="currentColor"
-            strokeWidth="2"
-            fill="none"
-            strokeLinecap="round"
-            strokeLinejoin="round"
-          >
-            <line x1="18" y1="6" x2="6" y2="18" />
-            <line x1="6" y1="6" x2="18" y2="18" />
-          </svg>
-        </button>
-      </div>
-
-      {/* Messages */}
-      <div className="flex-1 space-y-4 overflow-y-auto p-4">
-        {messages.map((message, index) => (
-          <div
-            key={index}
-            className={`flex ${message.type === "user" ? "justify-end" : "justify-start"}`}
-          >
-            <div
-              className={`max-w-[80%] rounded-lg p-3 ${
-                message.type === "user"
-                  ? "ml-4 bg-black text-white"
-                  : "mr-4 bg-[#8b5cf6] text-white"
-              }`}
-            >
-              {message.type === "user" ? (
-                message.content
-              ) : (
-                <ReactMarkdown
-                  className="prose prose-sm dark:prose-invert max-w-none"
-                  components={{
-                    p: ({ children }) => (
-                      <p className="mb-2 last:mb-0">{children}</p>
-                    ),
-                    code(props) {
-                      const { children, className, node: _, ...rest } = props;
-                      const match = /language-(\w+)/.exec(className || "");
-                      return match ? (
-                        <pre className="overflow-x-auto rounded-md bg-muted-foreground/20 p-3">
-                          <code className="font-mono text-sm" {...rest}>
-                            {children}
-                          </code>
-                        </pre>
-                      ) : (
-                        <code
-                          className="rounded-md bg-muted-foreground/20 px-1 py-0.5 font-mono text-sm"
-                          {...rest}
-                        >
-                          {children}
-                        </code>
-                      );
-                    },
-                    ul: ({ children }) => (
-                      <ul className="mb-2 list-disc pl-4 last:mb-0">
-                        {children}
-                      </ul>
-                    ),
-                    ol: ({ children }) => (
-                      <ol className="mb-2 list-decimal pl-4 last:mb-0">
-                        {children}
-                      </ol>
-                    ),
-                    li: ({ children }) => (
-                      <li className="mb-1 last:mb-0">{children}</li>
-                    ),
-                  }}
-                >
-                  {message.content}
-                </ReactMarkdown>
-              )}
-            </div>
-          </div>
-        ))}
-        <div ref={messagesEndRef} />
-      </div>
-
-      {/* Input */}
-      <form onSubmit={handleSubmit} className="border-t p-4">
-        <div className="flex flex-col gap-2">
-          <div className="flex gap-2">
-            <input
-              type="text"
-              value={inputValue}
-              onChange={(e) => setInputValue(e.target.value)}
-              placeholder="Type your message..."
-              className="flex-1 rounded-md border bg-background px-3 py-2 focus:outline-none focus:ring-2 focus:ring-primary"
-              disabled={isProcessing}
-            />
-            <button
-              type="submit"
-              disabled={isProcessing}
-              className="rounded-md bg-primary px-4 py-2 text-primary-foreground transition-colors hover:bg-primary/90 disabled:opacity-50"
-            >
-              Send
-            </button>
-          </div>
-          {graphID && (
-            <button
-              type="button"
-              onClick={() => {
-                setIncludeGraphData((prev) => !prev);
-              }}
-              className={`flex items-center gap-2 rounded border px-2 py-1.5 text-sm transition-all duration-200 ${
-                includeGraphData
-                  ? "border-primary/30 bg-primary/10 text-primary hover:shadow-[0_0_10px_3px_rgba(139,92,246,0.3)]"
-                  : "border-transparent bg-muted text-muted-foreground hover:bg-muted/80 hover:shadow-[0_0_10px_3px_rgba(139,92,246,0.15)]"
-              }`}
-            >
-              <svg
-                viewBox="0 0 24 24"
-                className="h-4 w-4"
-                stroke="currentColor"
-                strokeWidth="2"
-                fill="none"
-                strokeLinecap="round"
-                strokeLinejoin="round"
-              >
-                <rect x="3" y="3" width="18" height="18" rx="2" ry="2" />
-                <circle cx="8.5" cy="8.5" r="1.5" />
-                <polyline points="21 15 16 10 5 21" />
-              </svg>
-              {includeGraphData
-                ? "Graph data will be included"
-                : "Include graph data"}
-            </button>
-          )}
-        </div>
-      </form>
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/OutputModalComponent.tsx

@@ -1,50 +0,0 @@
-import React, { FC } from "react";
-import { Button } from "../../../../../components/__legacy__/ui/button";
-import { NodeExecutionResult } from "@/lib/autogpt-server-api/types";
-import DataTable from "./DataTable";
-import { Separator } from "@/components/__legacy__/ui/separator";
-
-interface OutputModalProps {
-  isOpen: boolean;
-  onClose: () => void;
-  executionResults: {
-    execId: string;
-    data: NodeExecutionResult["output_data"];
-  }[];
-}
-
-const OutputModalComponent: FC<OutputModalProps> = ({
-  isOpen,
-  onClose,
-  executionResults,
-}) => {
-  if (!isOpen) {
-    return null;
-  }
-
-  return (
-    <div className="nodrag nowheel fixed inset-0 flex items-center justify-center bg-white bg-opacity-60">
-      <div className="w-[500px] max-w-[90%] rounded-lg border-[1.5px] bg-white p-5">
-        <strong>Output Data History</strong>
-        <div className="my-2 max-h-[384px] flex-grow overflow-y-auto rounded-md p-2">
-          {executionResults.map((data, i) => (
-            <>
-              <DataTable
-                key={i}
-                title={data.execId}
-                data={data.data}
-                truncateLongData={true}
-              />
-              <Separator />
-            </>
-          ))}
-        </div>
-        <div className="mt-2.5 flex justify-end gap-2.5">
-          <Button onClick={onClose}>Close</Button>
-        </div>
-      </div>
-    </div>
-  );
-};
-
-export default OutputModalComponent;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerInputUI.tsx

@@ -1,96 +0,0 @@
-import { useCallback } from "react";
-
-import { AgentRunDraftView } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view";
-import { Dialog } from "@/components/molecules/Dialog/Dialog";
-import type {
-  CredentialsMetaInput,
-  Graph,
-} from "@/lib/autogpt-server-api/types";
-
-interface RunInputDialogProps {
-  isOpen: boolean;
-  doClose: () => void;
-  graph: Graph;
-  doRun?: (
-    inputs: Record<string, any>,
-    credentialsInputs: Record<string, CredentialsMetaInput>,
-  ) => Promise<void> | void;
-  doCreateSchedule?: (
-    cronExpression: string,
-    scheduleName: string,
-    inputs: Record<string, any>,
-    credentialsInputs: Record<string, CredentialsMetaInput>,
-  ) => Promise<void> | void;
-}
-
-export function RunnerInputDialog({
-  isOpen,
-  doClose,
-  graph,
-  doRun,
-  doCreateSchedule,
-}: RunInputDialogProps) {
-  const handleRun = useCallback(
-    doRun
-      ? async (
-          inputs: Record<string, any>,
-          credentials_inputs: Record<string, CredentialsMetaInput>,
-        ) => {
-          await doRun(inputs, credentials_inputs);
-          doClose();
-        }
-      : async () => {},
-    [doRun, doClose],
-  );
-
-  const handleSchedule = useCallback(
-    doCreateSchedule
-      ? async (
-          cronExpression: string,
-          scheduleName: string,
-          inputs: Record<string, any>,
-          credentialsInputs: Record<string, CredentialsMetaInput>,
-        ) => {
-          await doCreateSchedule(
-            cronExpression,
-            scheduleName,
-            inputs,
-            credentialsInputs,
-          );
-          doClose();
-        }
-      : async () => {},
-    [doCreateSchedule, doClose],
-  );
-
-  return (
-    <Dialog
-      title="Run your agent"
-      controlled={{
-        isOpen,
-        set: (open) => {
-          if (!open) doClose();
-        },
-      }}
-      onClose={doClose}
-      styling={{
-        maxWidth: "56rem",
-        width: "90vw",
-      }}
-    >
-      <Dialog.Content>
-        <div className="flex flex-col p-10">
-          <p className="mt-2 text-sm text-zinc-600">{graph.name}</p>
-          <AgentRunDraftView
-            className="p-0"
-            graph={graph}
-            doRun={doRun ? handleRun : undefined}
-            onRun={doRun ? undefined : doClose}
-            doCreateSchedule={doCreateSchedule ? handleSchedule : undefined}
-            onCreateSchedule={doCreateSchedule ? undefined : doClose}
-          />
-        </div>
-      </Dialog.Content>
-    </Dialog>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerOutputUI.tsx

@@ -1,156 +0,0 @@
-import React from "react";
-import {
-  Sheet,
-  SheetContent,
-  SheetHeader,
-  SheetTitle,
-  SheetDescription,
-} from "@/components/__legacy__/ui/sheet";
-import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
-import { Label } from "@/components/__legacy__/ui/label";
-import { Textarea } from "@/components/__legacy__/ui/textarea";
-import { Button } from "@/components/__legacy__/ui/button";
-import { Clipboard } from "lucide-react";
-import { useToast } from "@/components/molecules/Toast/use-toast";
-
-export type OutputNodeInfo = {
-  metadata: {
-    name: string;
-    description: string;
-  };
-  result?: any;
-};
-
-interface OutputModalProps {
-  isOpen: boolean;
-  doClose: () => void;
-  outputs: OutputNodeInfo[];
-  graphExecutionError?: string | null;
-}
-
-const formatOutput = (output: any): string => {
-  if (typeof output === "object") {
-    try {
-      if (
-        Array.isArray(output) &&
-        output.every((item) => typeof item === "string")
-      ) {
-        return output.join("\n").replace(/\\n/g, "\n");
-      }
-      return JSON.stringify(output, null, 2);
-    } catch (error) {
-      return `Error formatting output: ${(error as Error).message}`;
-    }
-  }
-  if (typeof output === "string") {
-    return output.replace(/\\n/g, "\n");
-  }
-  return String(output);
-};
-
-export function RunnerOutputUI({
-  isOpen,
-  doClose,
-  outputs,
-  graphExecutionError,
-}: OutputModalProps) {
-  const { toast } = useToast();
-
-  const copyOutput = (name: string, output: any) => {
-    const formattedOutput = formatOutput(output);
-    navigator.clipboard.writeText(formattedOutput).then(() => {
-      toast({
-        title: `"${name}" output copied to clipboard!`,
-        duration: 2000,
-      });
-    });
-  };
-
-  const adjustTextareaHeight = (textarea: HTMLTextAreaElement) => {
-    textarea.style.height = "auto";
-    textarea.style.height = `${textarea.scrollHeight}px`;
-  };
-
-  return (
-    <Sheet open={isOpen} onOpenChange={doClose}>
-      <SheetContent
-        side="right"
-        className="flex h-full w-full flex-col overflow-hidden sm:max-w-[600px]"
-      >
-        <SheetHeader className="px-2 py-2">
-          <SheetTitle className="text-xl">Run Outputs</SheetTitle>
-          <SheetDescription className="mt-1 text-sm">
-            View the outputs from your agent run.
-          </SheetDescription>
-        </SheetHeader>
-        <div className="flex-grow overflow-y-auto px-2 py-2">
-          <ScrollArea className="h-full overflow-auto pr-4">
-            <div className="space-y-4">
-              {graphExecutionError && (
-                <div className="rounded-md border border-red-200 bg-red-50 p-3 dark:border-red-800 dark:bg-red-900/20">
-                  <p className="text-sm text-red-800 dark:text-red-200">
-                    <strong>Error:</strong> {graphExecutionError}
-                  </p>
-                </div>
-              )}
-              {outputs && outputs.length > 0 ? (
-                outputs.map((output, i) => (
-                  <div key={i} className="space-y-1">
-                    <Label className="text-base font-semibold">
-                      {output.metadata.name || "Unnamed Output"}
-                    </Label>
-
-                    {output.metadata.description && (
-                      <Label className="block text-sm text-gray-600">
-                        {output.metadata.description}
-                      </Label>
-                    )}
-
-                    <div className="group relative rounded-md bg-gray-100 p-2">
-                      <Button
-                        className="absolute right-1 top-1 z-10 m-1 hidden p-2 group-hover:block"
-                        variant="outline"
-                        size="icon"
-                        onClick={() =>
-                          copyOutput(
-                            output.metadata.name || "Unnamed Output",
-                            output.result,
-                          )
-                        }
-                        title="Copy Output"
-                      >
-                        <Clipboard size={18} />
-                      </Button>
-                      <Textarea
-                        readOnly
-                        value={formatOutput(output.result ?? "No output yet")}
-                        className="w-full resize-none whitespace-pre-wrap break-words border-none bg-transparent text-sm"
-                        style={{
-                          height: "auto",
-                          minHeight: "2.5rem",
-                          maxHeight: "400px",
-                        }}
-                        ref={(el) => {
-                          if (el) {
-                            adjustTextareaHeight(el);
-                            if (el.scrollHeight > 400) {
-                              el.style.height = "400px";
-                            }
-                          }
-                        }}
-                      />
-                    </div>
-                  </div>
-                ))
-              ) : (
-                <p>No output blocks available.</p>
-              )}
-            </div>
-          </ScrollArea>
-        </div>
-      </SheetContent>
-    </Sheet>
-  );
-}
-
-export default RunnerOutputUI;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/RunnerUIWrapper.tsx

@@ -1,117 +0,0 @@
-import React, {
-  useState,
-  forwardRef,
-  useImperativeHandle,
-  useMemo,
-} from "react";
-import { Node } from "@xyflow/react";
-import { CustomNodeData } from "@/app/(platform)/build/components/legacy-builder/CustomNode/CustomNode";
-import {
-  BlockUIType,
-  CredentialsMetaInput,
-  Graph,
-} from "@/lib/autogpt-server-api/types";
-import RunnerOutputUI, { OutputNodeInfo } from "./RunnerOutputUI";
-import { RunnerInputDialog } from "./RunnerInputUI";
-
-interface RunnerUIWrapperProps {
-  graph: Graph;
-  nodes: Node<CustomNodeData>[];
-  graphExecutionError?: string | null;
-  saveAndRun: (
-    inputs: Record<string, any>,
-    credentialsInputs: Record<string, CredentialsMetaInput>,
-  ) => void;
-  createRunSchedule: (
-    cronExpression: string,
-    scheduleName: string,
-    inputs: Record<string, any>,
-    credentialsInputs: Record<string, CredentialsMetaInput>,
-  ) => Promise<void>;
-}
-
-export interface RunnerUIWrapperRef {
-  openRunInputDialog: () => void;
-  openRunnerOutput: () => void;
-  runOrOpenInput: () => void;
-}
-
-const RunnerUIWrapper = forwardRef<RunnerUIWrapperRef, RunnerUIWrapperProps>(
-  (
-    { graph, nodes, graphExecutionError, saveAndRun, createRunSchedule },
-    ref,
-  ) => {
-    const [isRunInputDialogOpen, setIsRunInputDialogOpen] = useState(false);
-    const [isRunnerOutputOpen, setIsRunnerOutputOpen] = useState(false);
-
-    const graphInputs = graph.input_schema.properties;
-
-    const graphOutputs = useMemo((): OutputNodeInfo[] => {
-      const outputNodes = nodes.filter(
-        (node) => node.data.uiType === BlockUIType.OUTPUT,
-      );
-
-      return outputNodes.map(
-        (node) =>
-          ({
-            metadata: {
-              name: node.data.hardcodedValues.name || "Output",
-              description:
-                node.data.hardcodedValues.description ||
-                "Output from the agent",
-            },
-            result:
-              (node.data.executionResults as any)
-                ?.map((result: any) => result?.data?.output)
-                .join("\n--\n") || "No output yet",
-          }) satisfies OutputNodeInfo,
-      );
-    }, [nodes]);
-
-    const openRunInputDialog = () => setIsRunInputDialogOpen(true);
-    const openRunnerOutput = () => setIsRunnerOutputOpen(true);
-
-    const runOrOpenInput = () => {
-      if (
-        Object.keys(graphInputs).length > 0 ||
-        Object.keys(graph.credentials_input_schema.properties).length > 0
-      ) {
-        openRunInputDialog();
-      } else {
-        saveAndRun({}, {});
-      }
-    };
-
-    useImperativeHandle(
-      ref,
-      () =>
-        ({
-          openRunInputDialog,
-          openRunnerOutput,
-          runOrOpenInput,
-        }) satisfies RunnerUIWrapperRef,
-    );
-
-    return (
-      <>
-        <RunnerInputDialog
-          isOpen={isRunInputDialogOpen}
-          doClose={() => setIsRunInputDialogOpen(false)}
-          graph={graph}
-          doRun={saveAndRun}
-          doCreateSchedule={createRunSchedule}
-        />
-        <RunnerOutputUI
-          isOpen={isRunnerOutputOpen}
-          doClose={() => setIsRunnerOutputOpen(false)}
-          outputs={graphOutputs}
-          graphExecutionError={graphExecutionError}
-        />
-      </>
-    );
-  },
-);
-
-RunnerUIWrapper.displayName = "RunnerUIWrapper";
-
-export default RunnerUIWrapper;

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/SaveControl.tsx

@@ -1,217 +0,0 @@
-import React, { useEffect, useState } from "react";
-import {
-  Popover,
-  PopoverContent,
-  PopoverTrigger,
-} from "@/components/__legacy__/ui/popover";
-import { Card, CardContent, CardFooter } from "@/components/__legacy__/ui/card";
-import { Input } from "@/components/__legacy__/ui/input";
-import { Button } from "@/components/__legacy__/ui/button";
-import { GraphMeta } from "@/lib/autogpt-server-api";
-import { Label } from "@/components/__legacy__/ui/label";
-import { IconSave } from "@/components/__legacy__/ui/icons";
-import {
-  Tooltip,
-  TooltipContent,
-  TooltipTrigger,
-} from "@/components/atoms/Tooltip/BaseTooltip";
-import { useToast } from "@/components/molecules/Toast/use-toast";
-import { useQueryClient } from "@tanstack/react-query";
-import { getGetV2ListMySubmissionsQueryKey } from "@/app/api/__generated__/endpoints/store/store";
-import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
-import { humanizeCronExpression } from "@/lib/cron-expression-utils";
-import { CalendarClockIcon } from "lucide-react";
-
-interface SaveControlProps {
-  agentMeta: GraphMeta | null;
-  agentName: string;
-  agentDescription: string;
-  agentRecommendedScheduleCron: string;
-  canSave: boolean;
-  onSave: () => Promise<void>;
-  onNameChange: (name: string) => void;
-  onDescriptionChange: (description: string) => void;
-  onRecommendedScheduleCronChange: (cron: string) => void;
-  pinSavePopover: boolean;
-}
-
-/**
- * A SaveControl component to be used within the ControlPanel. It allows the user to save the agent.
- * @param {Object} SaveControlProps - The properties of the SaveControl component.
- * @param {GraphMeta | null} SaveControlProps.agentMeta - The agent's metadata, or null if creating a new agent.
- * @param {string} SaveControlProps.agentName - The agent's name.
- * @param {string} SaveControlProps.agentDescription - The agent's description.
- * @param {boolean} SaveControlProps.canSave - Whether the button to save the agent should be enabled.
- * @param {() => void} SaveControlProps.onSave - Function to save the agent.
- * @param {(name: string) => void} SaveControlProps.onNameChange - Function to handle name changes.
- * @param {(description: string) => void} SaveControlProps.onDescriptionChange - Function to handle description changes.
- * @returns The SaveControl component.
- */
-export const SaveControl = ({
-  agentMeta,
-  canSave,
-  onSave,
-  agentName,
-  onNameChange,
-  agentDescription,
-  onDescriptionChange,
-  agentRecommendedScheduleCron,
-  onRecommendedScheduleCronChange,
-  pinSavePopover,
-}: SaveControlProps) => {
-  /**
-   * Note for improvement:
-   * At the moment we are leveraging onDescriptionChange and onNameChange to handle the changes in the description and name of the agent.
-   * We should migrate this to be handled with form controls and a form library.
-   */
-
-  const { toast } = useToast();
-  const queryClient = useQueryClient();
-  const [cronScheduleDialogOpen, setCronScheduleDialogOpen] = useState(false);
-
-  const handleScheduleChange = (cronExpression: string) => {
-    onRecommendedScheduleCronChange(cronExpression);
-  };
-
-  useEffect(() => {
-    const handleKeyDown = async (event: KeyboardEvent) => {
-      if ((event.ctrlKey || event.metaKey) && event.key === "s") {
-        event.preventDefault(); // Stop the browser default action
-        await onSave(); // Call your save function
-        queryClient.invalidateQueries({
-          queryKey: getGetV2ListMySubmissionsQueryKey(),
-        });
-        toast({
-          duration: 2000,
-          title: "All changes saved successfully!",
-        });
-      }
-    };
-
-    window.addEventListener("keydown", handleKeyDown);
-
-    return () => {
-      window.removeEventListener("keydown", handleKeyDown);
-    };
-  }, [onSave, toast]);
-
-  return (
-    <Popover open={pinSavePopover ? true : undefined}>
-      <Tooltip delayDuration={500}>
-        <TooltipTrigger asChild>
-          <PopoverTrigger asChild>
-            <Button
-              variant="ghost"
-              size="icon"
-              data-id="save-control-popover-trigger"
-              data-testid="blocks-control-save-button"
-              name="Save"
-            >
-              <IconSave className="dark:text-gray-300" />
-            </Button>
-          </PopoverTrigger>
-        </TooltipTrigger>
-        <TooltipContent side="right">Save</TooltipContent>
-      </Tooltip>
-      <PopoverContent
-        side="right"
-        sideOffset={15}
-        align="start"
-        data-id="save-control-popover-content"
-        className="w-96 max-w-[400px]"
-      >
-        <Card className="border-none shadow-none dark:bg-slate-900">
-          <CardContent className="p-4">
-            <div className="space-y-3">
-              <div>
-                <Label htmlFor="name" className="dark:text-gray-300">
-                  Name
-                </Label>
-                <Input
-                  id="name"
-                  placeholder="Enter your agent name"
-                  value={agentName}
-                  onChange={(e) => onNameChange(e.target.value)}
-                  data-id="save-control-name-input"
-                  data-testid="save-control-name-input"
-                  maxLength={100}
-                  className="mt-1"
-                />
-              </div>
-
-              <div>
-                <Label htmlFor="description" className="dark:text-gray-300">
-                  Description
-                </Label>
-                <Input
-                  id="description"
-                  placeholder="Your agent description"
-                  value={agentDescription}
-                  onChange={(e) => onDescriptionChange(e.target.value)}
-                  data-id="save-control-description-input"
-                  data-testid="save-control-description-input"
-                  maxLength={500}
-                  className="mt-1"
-                />
-              </div>
-
-              <div>
-                <Label className="dark:text-gray-300">
-                  Recommended Schedule
-                </Label>
-                <Button
-                  variant="outline"
-                  onClick={() => setCronScheduleDialogOpen(true)}
-                  className="mt-1 w-full min-w-0 justify-start text-sm"
-                  data-id="save-control-recommended-schedule-button"
-                  data-testid="save-control-recommended-schedule-button"
-                >
-                  <CalendarClockIcon className="mr-2 h-4 w-4 flex-shrink-0" />
-                  <span className="min-w-0 flex-1 truncate">
-                    {agentRecommendedScheduleCron
-                      ? humanizeCronExpression(agentRecommendedScheduleCron)
-                      : "Set schedule"}
-                  </span>
-                </Button>
-              </div>
-
-              {agentMeta?.version && (
-                <div>
-                  <Label htmlFor="version" className="dark:text-gray-300">
-                    Version
-                  </Label>
-                  <Input
-                    id="version"
-                    placeholder="Version"
-                    value={agentMeta?.version || "-"}
-                    disabled
-                    data-testid="save-control-version-output"
-                    className="mt-1"
-                  />
-                </div>
-              )}
-            </div>
-          </CardContent>
-          <CardFooter className="flex flex-col items-stretch gap-2">
-            <Button
-              className="w-full dark:bg-slate-700 dark:text-slate-100 dark:hover:bg-slate-800"
-              onClick={onSave}
-              data-id="save-control-save-agent"
-              data-testid="save-control-save-agent-button"
-              disabled={!canSave}
-            >
-              Save Agent
-            </Button>
-          </CardFooter>
-        </Card>
-      </PopoverContent>
-      <CronExpressionDialog
-        open={cronScheduleDialogOpen}
-        setOpen={setCronScheduleDialogOpen}
-        onSubmit={handleScheduleChange}
-        defaultCronExpression={agentRecommendedScheduleCron}
-        title="Recommended Schedule"
-      />
-    </Popover>
-  );
-};

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/history.ts

@@ -1,95 +0,0 @@
-import { CustomNodeData } from "./CustomNode/CustomNode";
-import { CustomEdgeData } from "./CustomEdge/CustomEdge";
-import { Edge } from "@xyflow/react";
-
-type ActionType =
-  | "ADD_NODE"
-  | "DELETE_NODE"
-  | "ADD_EDGE"
-  | "DELETE_EDGE"
-  | "UPDATE_NODE"
-  | "MOVE_NODE"
-  | "UPDATE_INPUT"
-  | "UPDATE_NODE_POSITION";
-
-type AddNodePayload = { node: CustomNodeData };
-type DeleteNodePayload = { nodeId: string };
-type AddEdgePayload = { edge: Edge<CustomEdgeData> };
-type DeleteEdgePayload = { edgeId: string };
-type UpdateNodePayload = { nodeId: string; newData: Partial<CustomNodeData> };
-type MoveNodePayload = { nodeId: string; position: { x: number; y: number } };
-type UpdateInputPayload = {
-  nodeId: string;
-  oldValues: { [key: string]: any };
-  newValues: { [key: string]: any };
-};
-type UpdateNodePositionPayload = {
-  nodeId: string;
-  oldPosition: { x: number; y: number };
-  newPosition: { x: number; y: number };
-};
-
-type ActionPayload =
-  | AddNodePayload
-  | DeleteNodePayload
-  | AddEdgePayload
-  | DeleteEdgePayload
-  | UpdateNodePayload
-  | MoveNodePayload
-  | UpdateInputPayload
-  | UpdateNodePositionPayload;
-
-type Action = {
-  type: ActionType;
-  payload: ActionPayload;
-  undo: () => void;
-  redo: () => void;
-};
-
-class History {
-  private past: Action[] = [];
-  private future: Action[] = [];
-
-  push(action: Action) {
-    this.past.push(action);
-    this.future = [];
-  }
-
-  undo() {
-    const action = this.past.pop();
-    if (action) {
-      action.undo();
-      this.future.push(action);
-    }
-  }
-
-  redo() {
-    const action = this.future.pop();
-    if (action) {
-      action.redo();
-      this.past.push(action);
-    }
-  }
-
-  canUndo(): boolean {
-    return this.past.length > 0;
-  }
-
-  canRedo(): boolean {
-    return this.future.length > 0;
-  }
-
-  clear() {
-    this.past = [];
-    this.future = [];
-  }
-
-  getHistoryState() {
-    return {
-      past: [...this.past],
-      future: [...this.future],
-    };
-  }
-}
-
-export const history = new History();

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/tutorial.ts

@@ -1,569 +0,0 @@
-import Shepherd from "shepherd.js";
-import "shepherd.js/dist/css/shepherd.css";
-import { Key, storage } from "@/services/storage/local-storage";
-import { analytics } from "@/services/analytics";
-
-export const startTutorial = (
-  emptyNodeList: (forceEmpty: boolean) => boolean,
-  setPinBlocksPopover: (value: boolean) => void,
-  setPinSavePopover: (value: boolean) => void,
-) => {
-  const tour = new Shepherd.Tour({
-    useModalOverlay: true,
-    defaultStepOptions: {
-      cancelIcon: { enabled: true },
-      scrollTo: { behavior: "smooth", block: "center" },
-    },
-  });
-
-  // CSS classes for disabling and highlighting blocks
-  const disableClass = "disable-blocks";
-  const highlightClass = "highlight-block";
-  let isConnecting = false;
-
-  // Helper function to disable all blocks except the target block
-  const disableOtherBlocks = (targetBlockSelector: string) => {
-    document.querySelectorAll('[data-id^="block-card-"]').forEach((block) => {
-      block.classList.toggle(disableClass, !block.matches(targetBlockSelector));
-      block.classList.toggle(
-        highlightClass,
-        block.matches(targetBlockSelector),
-      );
-    });
-  };
-
-  // Helper function to enable all blocks
-  const enableAllBlocks = () => {
-    document.querySelectorAll('[data-id^="block-card-"]').forEach((block) => {
-      block.classList.remove(disableClass, highlightClass);
-    });
-  };
-
-  // Inject CSS for disabling and highlighting blocks
-  const injectStyles = () => {
-    const style = document.createElement("style");
-    style.textContent = `
-            .${disableClass} {
-                pointer-events: none;
-                opacity: 0.5;
-            }
-            .${highlightClass} {
-                background-color: #ffeb3b;
-                border: 2px solid #fbc02d;
-                transition: background-color 0.3s, border-color 0.3s;
-            }
-        `;
-    document.head.appendChild(style);
-  };
-
-  // Helper function to check if an element is present in the DOM
-  const waitForElement = (selector: string): Promise<void> => {
-    return new Promise((resolve) => {
-      const checkElement = () => {
-        if (document.querySelector(selector)) {
-          resolve();
-        } else {
-          setTimeout(checkElement, 10);
-        }
-      };
-      checkElement();
-    });
-  };
-
-  // Function to detect the correct connection and advance the tour
-  const detectConnection = () => {
-    const checkForConnection = () => {
-      const correctConnection = document.querySelector(
-        '[data-testid^="rf__edge-"]',
-      );
-      if (correctConnection) {
-        tour.show("press-run-again");
-      } else {
-        setTimeout(checkForConnection, 100);
-      }
-    };
-
-    checkForConnection();
-  };
-
-  // Define state management functions to handle connection state
-  function startConnecting() {
-    isConnecting = true;
-  }
-
-  function stopConnecting() {
-    isConnecting = false;
-  }
-
-  // Reset connection state when revisiting the step
-  function resetConnectionState() {
-    stopConnecting();
-  }
-
-  // Event handlers for mouse down and up to manage connection state
-  function handleMouseDown() {
-    startConnecting();
-    setTimeout(() => {
-      if (isConnecting) {
-        tour.next();
-      }
-    }, 100);
-  }
-  // Event handler for mouse up to check if the connection was successful
-  function handleMouseUp(event: { target: any }) {
-    const target = event.target;
-    const validConnectionPoint = document.querySelector(
-      '[data-testid^="rf__node-"]:nth-child(2) [data-id$="-a-target"]',
-    );
-
-    if (validConnectionPoint && !validConnectionPoint.contains(target)) {
-      setTimeout(() => {
-        if (!document.querySelector('[data-testid^="rf__edge-"]')) {
-          stopConnecting();
-          tour.show("connect-blocks-output");
-        }
-      }, 200);
-    } else {
-      stopConnecting();
-    }
-  }
-
-  // Define the fitViewToScreen function
-  const fitViewToScreen = () => {
-    const fitViewButton = document.querySelector(
-      ".react-flow__controls-fitview",
-    ) as HTMLButtonElement;
-    if (fitViewButton) {
-      fitViewButton.click();
-    }
-  };
-
-  injectStyles();
-
-  const warningText = emptyNodeList(false)
-    ? ""
-    : "<br/><br/><b>Caution: Clicking next will start a tutorial and will clear the current flow.</b>";
-
-  tour.addStep({
-    id: "starting-step",
-    title: "Welcome to the Tutorial",
-    text: `This is the AutoGPT builder! ${warningText}`,
-    buttons: [
-      {
-        text: "Skip Tutorial",
-        action: () => {
-          tour.cancel(); // Ends the tour
-          storage.set(Key.SHEPHERD_TOUR, "skipped"); // Set the tutorial as skipped in local storage
-        },
-        classes: "shepherd-button-secondary", // Optionally add a class for styling the skip button differently
-      },
-      {
-        text: "Next",
-        action: () => {
-          emptyNodeList(true);
-          tour.next();
-        },
-      },
-    ],
-  });
-
-  tour.addStep({
-    id: "open-block-step",
-    title: "Open Blocks Menu",
-    text: "Please click the block button to open the blocks menu.",
-    attachTo: {
-      element: '[data-id="blocks-control-popover-trigger"]',
-      on: "right",
-    },
-    advanceOn: {
-      selector: '[data-id="blocks-control-popover-trigger"]',
-      event: "click",
-    },
-    buttons: [],
-  });
-
-  tour.addStep({
-    id: "scroll-block-menu",
-    title: "Scroll Down or Search",
-    text: 'Scroll down or search in the blocks menu for the "Calculator Block" and press the block to add it.',
-    attachTo: {
-      element: '[data-id="blocks-control-popover-content"]',
-      on: "right",
-    },
-    buttons: [],
-    beforeShowPromise: () =>
-      waitForElement('[data-id="blocks-control-popover-content"]').then(() => {
-        disableOtherBlocks(
-          '[data-id="block-card-b1ab9b19-67a6-406d-abf5-2dba76d00c79"]',
-        );
-      }),
-    advanceOn: {
-      selector: '[data-id="block-card-b1ab9b19-67a6-406d-abf5-2dba76d00c79"]',
-      event: "click",
-    },
-    when: {
-      show: () => setPinBlocksPopover(true),
-      hide: enableAllBlocks,
-    },
-  });
-
-  tour.addStep({
-    id: "focus-new-block",
-    title: "New Block",
-    text: "This is the Calculator Block! Let's go over how it works.",
-    attachTo: { element: `[data-id="custom-node-1"]`, on: "left" },
-    beforeShowPromise: () => waitForElement('[data-id="custom-node-1"]'),
-    buttons: [
-      {
-        text: "Next",
-        action: tour.next,
-      },
-    ],
-    when: {
-      show: () => {
-        setPinBlocksPopover(false);
-        setTimeout(() => {
-          fitViewToScreen();
-        }, 100);
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "input-to-block",
-    title: "Input to the Block",
-    text: "This is the input pin for the block. You can input the output of other blocks here; this block takes numbers as input.",
-    attachTo: { element: '[data-nodeid="1"]', on: "left" },
-    buttons: [
-      {
-        text: "Back",
-        action: tour.back,
-      },
-      {
-        text: "Next",
-        action: tour.next,
-      },
-    ],
-  });
-
-  tour.addStep({
-    id: "output-from-block",
-    title: "Output from the Block",
-    text: "This is the output pin for the block. You can connect this to another block to pass the output along.",
-    attachTo: { element: '[data-handlepos="right"]', on: "right" },
-    buttons: [
-      {
-        text: "Back",
-        action: tour.back,
-      },
-      {
-        text: "Next",
-        action: tour.next,
-      },
-    ],
-  });
-
-  tour.addStep({
-    id: "select-operation-and-input",
-    title: "Select Operation and Input Numbers",
-    text: "Select any mathematical operation you'd like to perform, and enter numbers in both input fields.",
-    attachTo: { element: '[data-id="input-handles"]', on: "right" },
-    buttons: [
-      {
-        text: "Back",
-        action: tour.back,
-      },
-      {
-        text: "Next",
-        action: tour.next,
-      },
-    ],
-  });
-
-  tour.addStep({
-    id: "press-initial-save-button",
-    title: "Press Save",
-    text: "First we need to save the flow before we can run it!",
-    attachTo: {
-      element: '[data-id="save-control-popover-trigger"]',
-      on: "left",
-    },
-    advanceOn: {
-      selector: '[data-id="save-control-popover-trigger"]',
-      event: "click",
-    },
-    buttons: [
-      {
-        text: "Back",
-        action: tour.back,
-      },
-    ],
-    when: {
-      hide: () => setPinSavePopover(true),
-    },
-  });
-
-  tour.addStep({
-    id: "save-agent-details",
-    title: "Save the Agent",
-    text: "Enter a name for your agent, add an optional description, and then click 'Save agent' to save your flow.",
-    attachTo: {
-      element: '[data-id="save-control-popover-content"]',
-      on: "top",
-    },
-    buttons: [],
-    beforeShowPromise: () =>
-      waitForElement('[data-id="save-control-popover-content"]'),
-    advanceOn: {
-      selector: '[data-id="save-control-save-agent"]',
-      event: "click",
-    },
-    when: {
-      hide: () => setPinSavePopover(false),
-    },
-  });
-
-  tour.addStep({
-    id: "press-run",
-    title: "Press Run",
-    text: "Start your first flow by pressing the Run button!",
-    attachTo: {
-      element: '[data-tutorial-id="primary-action-run-agent"]',
-      on: "top",
-    },
-    advanceOn: {
-      selector: '[data-tutorial-id="primary-action-run-agent"]',
-      event: "click",
-    },
-    buttons: [],
-    beforeShowPromise: () =>
-      waitForElement('[data-tutorial-id="primary-action-run-agent"]'),
-    when: {
-      hide: () => {
-        setTimeout(() => {
-          fitViewToScreen();
-        }, 500);
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "wait-for-processing",
-    title: "Processing",
-    text: "Let's wait for the block to finish being processed...",
-    attachTo: {
-      element: '[data-id^="badge-"][data-id$="-QUEUED"]',
-      on: "bottom",
-    },
-    buttons: [],
-    beforeShowPromise: () =>
-      waitForElement('[data-id^="badge-"][data-id$="-QUEUED"]').then(
-        fitViewToScreen,
-      ),
-    when: {
-      show: () => {
-        waitForElement('[data-id^="badge-"][data-id$="-COMPLETED"]').then(
-          () => {
-            tour.next();
-          },
-        );
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "check-output",
-    title: "Check the Output",
-    text: "Check here to see the output of the block after running the flow.",
-    attachTo: { element: '[data-id="latest-output"]', on: "top" },
-    beforeShowPromise: () =>
-      new Promise((resolve) => {
-        setTimeout(() => {
-          waitForElement('[data-id="latest-output"]').then(resolve);
-        }, 100);
-      }),
-    buttons: [
-      {
-        text: "Next",
-        action: tour.next,
-      },
-    ],
-    when: {
-      show: () => {
-        fitViewToScreen();
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "copy-paste-block",
-    title: "Copy and Paste the Block",
-    text: "Let’s duplicate this block. Click and hold the block with your mouse, then press Ctrl+C (Cmd+C on Mac) to copy and Ctrl+V (Cmd+V on Mac) to paste.",
-    attachTo: { element: '[data-testid^="rf__node-"]', on: "top" },
-    buttons: [
-      {
-        text: "Back",
-        action: tour.back,
-      },
-    ],
-    when: {
-      show: () => {
-        fitViewToScreen();
-        waitForElement('[data-testid^="rf__node-"]:nth-child(2)').then(() => {
-          tour.next();
-        });
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "focus-second-block",
-    title: "Focus on the New Block",
-    text: "This is your copied Calculator Block. Now, let’s move it to the side of the first block.",
-    attachTo: { element: '[data-testid^="rf__node-"]:nth-child(2)', on: "top" },
-    beforeShowPromise: () =>
-      waitForElement('[data-testid^="rf__node-"]:nth-child(2)'),
-    buttons: [
-      {
-        text: "Next",
-        action: tour.next,
-      },
-    ],
-  });
-
-  tour.addStep({
-    id: "connect-blocks-output",
-    title: "Connect the Blocks: Output",
-    text: "Now, let's connect the output of the first Calculator Block to the input of the second Calculator Block. Drag from the output pin of the first block to the input pin (A) of the second block.",
-    attachTo: {
-      element:
-        '[data-testid^="rf__node-"]:first-child [data-id$="-result-source"]',
-      on: "bottom",
-    },
-
-    buttons: [
-      {
-        text: "Back",
-        action: tour.back,
-      },
-    ],
-    beforeShowPromise: () => {
-      return waitForElement(
-        '[data-testid^="rf__node-"]:first-child [data-id$="-result-source"]',
-      );
-    },
-    when: {
-      show: () => {
-        fitViewToScreen();
-        resetConnectionState(); // Reset state when revisiting this step
-        tour.modal.show();
-        const outputPin = document.querySelector(
-          '[data-testid^="rf__node-"]:first-child [data-id$="-result-source"]',
-        );
-        if (outputPin) {
-          outputPin.addEventListener("mousedown", handleMouseDown);
-        }
-      },
-      hide: () => {
-        const outputPin = document.querySelector(
-          '[data-testid^="rf__node-"]:first-child [data-id$="-result-source"]',
-        );
-        if (outputPin) {
-          outputPin.removeEventListener("mousedown", handleMouseDown);
-        }
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "connect-blocks-input",
-    title: "Connect the Blocks: Input",
-    text: "Now, connect the output to the input pin of the second block (A).",
-    attachTo: {
-      element: '[data-testid^="rf__node-"]:nth-child(2) [data-id$="-a-target"]',
-      on: "top",
-    },
-    buttons: [],
-    beforeShowPromise: () => {
-      return waitForElement(
-        '[data-testid^="rf__node-"]:nth-child(2) [data-id$="-a-target"]',
-      ).then(() => {
-        detectConnection();
-      });
-    },
-    when: {
-      show: () => {
-        tour.modal.show();
-        document.addEventListener("mouseup", handleMouseUp, true);
-      },
-      hide: () => {
-        tour.modal.hide();
-        document.removeEventListener("mouseup", handleMouseUp, true);
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "press-run-again",
-    title: "Press Run Again",
-    text: "Now, press the Run button again to execute the flow with the new Calculator Block added!",
-    attachTo: {
-      element: '[data-tutorial-id="primary-action-run-agent"]',
-      on: "top",
-    },
-    advanceOn: {
-      selector: '[data-tutorial-id="primary-action-run-agent"]',
-      event: "click",
-    },
-    buttons: [],
-    beforeShowPromise: () =>
-      waitForElement('[data-tutorial-id="primary-action-run-agent"]'),
-    when: {
-      hide: () => {
-        setTimeout(() => {
-          fitViewToScreen();
-        }, 500);
-      },
-    },
-  });
-
-  tour.addStep({
-    id: "congratulations",
-    title: "Congratulations!",
-    text: "You have successfully created your first flow. Watch for the outputs in the blocks!",
-    beforeShowPromise: () => waitForElement('[data-id="latest-output"]'),
-    when: {
-      show: () => tour.modal.hide(),
-    },
-    buttons: [
-      {
-        text: "Finish",
-        action: tour.complete,
-      },
-    ],
-  });
-
-  // Unpin blocks and save menu when the tour is completed or canceled
-  tour.on("complete", () => {
-    setPinBlocksPopover(false);
-    setPinSavePopover(false);
-    storage.set(Key.SHEPHERD_TOUR, "completed"); // Optionally mark the tutorial as completed
-  });
-
-  for (const step of tour.steps) {
-    step.on("show", () => {
-      "use client";
-      console.debug("sendTutorialStep");
-
-      analytics.sendGAEvent("event", "tutorial_step_shown", { value: step.id });
-    });
-  }
-
-  tour.on("cancel", () => {
-    setPinBlocksPopover(false);
-    setPinSavePopover(false);
-    storage.set(Key.SHEPHERD_TOUR, "canceled"); // Optionally mark the tutorial as canceled
-  });
-
-  tour.start();
-};

autogpt_platform/frontend/src/app/(platform)/build/components/legacy-builder/useCopyPaste.ts

@@ -1,142 +0,0 @@
-import { useCallback } from "react";
-import { Node, Edge, useReactFlow } from "@xyflow/react";
-import { Key, storage } from "@/services/storage/local-storage";
-import { ConnectedEdge } from "./CustomNode/CustomNode";
-
-interface CopyableData {
-  nodes: Node[];
-  edges: Edge[];
-}
-
-export function useCopyPaste(getNextNodeId: () => string) {
-  const { setNodes, addEdges, getNodes, getEdges, getViewport } =
-    useReactFlow();
-
-  const handleCopyPaste = useCallback(
-    (event: KeyboardEvent) => {
-      if (event.ctrlKey || event.metaKey) {
-        if (event.key === "c" || event.key === "C") {
-          const selectedNodes = getNodes().filter((node) => node.selected);
-          const selectedNodeIds = new Set(selectedNodes.map((node) => node.id));
-
-          // Only copy edges where both source and target nodes are selected
-          const selectedEdges = getEdges().filter(
-            (edge) =>
-              edge.selected &&
-              selectedNodeIds.has(edge.source) &&
-              selectedNodeIds.has(edge.target),
-          );
-
-          const copiedData: CopyableData = {
-            nodes: selectedNodes.map((node) => ({
-              ...node,
-              data: {
-                ...node.data,
-                connections: node.data.connections || [], // Preserve connections
-              },
-            })),
-            edges: selectedEdges,
-          };
-
-          storage.set(Key.COPIED_FLOW_DATA, JSON.stringify(copiedData));
-        }
-        if (event.key === "v" || event.key === "V") {
-          const copiedDataString = storage.get(Key.COPIED_FLOW_DATA);
-          if (copiedDataString) {
-            const copiedData = JSON.parse(copiedDataString) as CopyableData;
-            const oldToNewIdMap: Record<string, string> = {};
-
-            // Get fresh viewport values at paste time to ensure correct positioning
-            const { x, y, zoom } = getViewport();
-            const viewportCenter = {
-              x: (window.innerWidth / 2 - x) / zoom,
-              y: (window.innerHeight / 2 - y) / zoom,
-            };
-
-            let minX = Infinity,
-              minY = Infinity,
-              maxX = -Infinity,
-              maxY = -Infinity;
-            copiedData.nodes.forEach((node: Node) => {
-              minX = Math.min(minX, node.position.x);
-              minY = Math.min(minY, node.position.y);
-              maxX = Math.max(maxX, node.position.x);
-              maxY = Math.max(maxY, node.position.y);
-            });
-
-            const offsetX = viewportCenter.x - (minX + maxX) / 2;
-            const offsetY = viewportCenter.y - (minY + maxY) / 2;
-
-            const pastedNodes = copiedData.nodes.map((node: Node) => {
-              const newNodeId = getNextNodeId();
-              oldToNewIdMap[node.id] = newNodeId;
-              return {
-                ...node,
-                id: newNodeId, // Generate unique ID for the pasted node
-                selected: true, // Select the pasted nodes so they're visible
-                position: {
-                  x: node.position.x + offsetX,
-                  y: node.position.y + offsetY,
-                },
-                data: {
-                  ...node.data,
-                  backend_id: undefined, // Clear backend_id so the new node.id is used when saving
-                  connections: node.data.connections || [], // Preserve connections
-                  status: undefined,
-                  executionResults: undefined,
-                },
-              };
-            });
-
-            const pastedEdges = copiedData.edges.map((edge) => {
-              const newSourceId = oldToNewIdMap[edge.source] ?? edge.source;
-              const newTargetId = oldToNewIdMap[edge.target] ?? edge.target;
-              return {
-                ...edge,
-                id: `${newSourceId}_${edge.sourceHandle}_${newTargetId}_${edge.targetHandle}_${Date.now()}`,
-                source: newSourceId,
-                target: newTargetId,
-              };
-            });
-
-            setNodes((existingNodes) => [
-              ...existingNodes.map((node) => ({ ...node, selected: false })),
-              ...pastedNodes,
-            ]);
-            addEdges(pastedEdges);
-
-            setNodes((nodes) => {
-              return nodes.map((node) => {
-                const nodeConnections = getEdges()
-                  .filter(
-                    (edge: Edge) =>
-                      edge.source === node.id || edge.target === node.id,
-                  )
-                  .map(
-                    (edge: Edge): ConnectedEdge => ({
-                      id: edge.id,
-                      source: edge.source,
-                      target: edge.target,
-                      sourceHandle: edge.sourceHandle!,
-                      targetHandle: edge.targetHandle!,
-                    }),
-                  );
-
-                return {
-                  ...node,
-                  data: {
-                    ...node.data,
-                    connections: nodeConnections,
-                  },
-                };
-              });
-            });
-          }
-        }
-      }
-    },
-    [setNodes, addEdges, getNodes, getEdges, getNextNodeId, getViewport],
-  );
-
-  return handleCopyPaste;
-}

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

@@ -1,64 +1,13 @@
 "use client";
-
-import FlowEditor from "@/app/(platform)/build/components/legacy-builder/Flow/Flow";
-import { useOnboarding } from "@/providers/onboarding/onboarding-provider";
-// import LoadingBox from "@/components/__legacy__/ui/loading";
-import { GraphID } from "@/lib/autogpt-server-api/types";
 import { ReactFlowProvider } from "@xyflow/react";
-import { useSearchParams } from "next/navigation";
-import { useEffect } from "react";
-import { BuilderViewTabs } from "./components/BuilderViewTabs/BuilderViewTabs";
 import { Flow } from "./components/FlowEditor/Flow/Flow";
-import { useBuilderView } from "./useBuilderView";
-
-function BuilderContent() {
-  const query = useSearchParams();
-  const { completeStep } = useOnboarding();
-
-  useEffect(() => {
-    completeStep("BUILDER_OPEN");
-  }, [completeStep]);
-
-  const _graphVersion = query.get("flowVersion");
-  const graphVersion = _graphVersion ? parseInt(_graphVersion) : undefined;
-  return (
-    <FlowEditor
-      className="flex h-full w-full"
-      flowID={(query.get("flowID") as GraphID | null) ?? undefined}
-      flowVersion={graphVersion}
-    />
-  );
-}
 
 export default function BuilderPage() {
-  const {
-    isSwitchEnabled,
-    selectedView,
-    setSelectedView,
-    isNewFlowEditorEnabled,
-  } = useBuilderView();
-
-  // Switch is temporary, we will remove it once our new flow editor is ready
-  if (isSwitchEnabled) {
-    return (
-      <div className="relative h-full w-full">
-        <BuilderViewTabs value={selectedView} onChange={setSelectedView} />
-        {selectedView === "new" ? (
-          <ReactFlowProvider>
-            <Flow />
-          </ReactFlowProvider>
-        ) : (
-          <BuilderContent />
-        )}
-      </div>
-    );
-  }
-
-  return isNewFlowEditorEnabled ? (
-    <ReactFlowProvider>
-      <Flow />
-    </ReactFlowProvider>
-  ) : (
-    <BuilderContent />
+  return (
+    <div className="relative h-full w-full">
+      <ReactFlowProvider>
+        <Flow />
+      </ReactFlowProvider>
+    </div>
   );
 }