Update manager.py

Addresses review feedback on #12004:
- Added AutoCredentialFieldInfo dataclass and parse_auto_credential_field()
  helper to executor/utils.py
- Updated _acquire_auto_credentials in manager.py to use shared helper
- Updated _validate_node_input_credentials in utils.py to use shared helper

This consolidates the duplicate logic for parsing GoogleDriveFileField-style
auto-credential fields, making manager.py less cluttered while ensuring
consistent validation/acquisition behavior.

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

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

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

@@ -42,7 +42,7 @@ jobs:
 
       - name: Get CI failure details
         id: failure_details
-        uses: actions/github-script@v8
+        uses: actions/github-script@v7
         with:
           script: |
             const run = await github.rest.actions.getWorkflowRun({

.github/workflows/claude-dependabot.yml

@@ -41,7 +41,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -78,7 +78,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22"
 
@@ -91,7 +91,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -124,7 +124,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes
@@ -309,7 +309,6 @@ 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

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

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

@@ -39,7 +39,7 @@ jobs:
           python-version: "3.11"  # Use standard version matching CI
 
       - name: Set up Python dependency cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.cache/pypoetry
           key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
@@ -76,7 +76,7 @@ jobs:
 
       # Frontend Node.js/pnpm setup (mirrors platform-frontend-ci.yml)
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22"
 
@@ -89,7 +89,7 @@ jobs:
           echo "PNPM_HOME=$HOME/.pnpm-store" >> $GITHUB_ENV
 
       - name: Cache frontend dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}
@@ -132,7 +132,7 @@ jobs:
       # Phase 1: Cache and load Docker images for faster setup
       - name: Set up Docker image cache
         id: docker-cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/docker-cache
           # Use a versioned key for cache invalidation when image list changes

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

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

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

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

.github/workflows/docs-enhance.yml

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

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

@@ -52,7 +52,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v4
+        uses: peter-evans/repository-dispatch@v3
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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

@@ -45,7 +45,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Trigger deploy workflow
-        uses: peter-evans/repository-dispatch@v4
+        uses: peter-evans/repository-dispatch@v3
         with:
           token: ${{ secrets.DEPLOY_TOKEN }}
           repository: Significant-Gravitas/AutoGPT_cloud_infrastructure

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

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

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

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

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

@@ -42,7 +42,7 @@ jobs:
               - 'autogpt_platform/frontend/src/components/**'
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -54,7 +54,7 @@ jobs:
         run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
 
       - name: Cache dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -74,7 +74,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -82,7 +82,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -112,7 +112,7 @@ jobs:
           fetch-depth: 0
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -120,7 +120,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -153,7 +153,7 @@ jobs:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -176,7 +176,7 @@ jobs:
         uses: docker/setup-buildx-action@v3
 
       - name: Cache Docker layers
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: /tmp/.buildx-cache
           key: ${{ runner.os }}-buildx-frontend-test-${{ hashFiles('autogpt_platform/docker-compose.yml', 'autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/pyproject.toml', 'autogpt_platform/backend/poetry.lock') }}
@@ -231,7 +231,7 @@ jobs:
           fi
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}
@@ -282,7 +282,7 @@ jobs:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -290,7 +290,7 @@ jobs:
         run: corepack enable
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

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

@@ -32,7 +32,7 @@ jobs:
         uses: actions/checkout@v4
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -44,7 +44,7 @@ jobs:
         run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
 
       - name: Cache dependencies
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ steps.cache-key.outputs.key }}
@@ -56,7 +56,7 @@ jobs:
         run: pnpm install --frozen-lockfile
 
   types:
-    runs-on: big-boi
+    runs-on: ubuntu-latest
     needs: setup
     strategy:
       fail-fast: false
@@ -68,7 +68,7 @@ jobs:
           submodules: recursive
 
       - name: Set up Node.js
-        uses: actions/setup-node@v6
+        uses: actions/setup-node@v4
         with:
           node-version: "22.18.0"
 
@@ -85,10 +85,10 @@ jobs:
 
       - name: Run docker compose
         run: |
-          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
+          docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d
 
       - name: Restore dependencies cache
-        uses: actions/cache@v5
+        uses: actions/cache@v4
         with:
           path: ~/.pnpm-store
           key: ${{ needs.setup.outputs.cache-key }}

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 = "^46.0"
+cryptography = "^45.0"
 expiringdict = "^1.2.2"
-fastapi = "^0.128.0"
+fastapi = "^0.116.1"
-google-cloud-logging = "^3.13.0"
+google-cloud-logging = "^3.12.1"
-launchdarkly-server-sdk = "^9.15.0"
+launchdarkly-server-sdk = "^9.12.0"
-pydantic = "^2.12.5"
+pydantic = "^2.11.7"
-pydantic-settings = "^2.12.0"
+pydantic-settings = "^2.10.1"
-pyjwt = { version = "^2.11.0", extras = ["crypto"] }
+pyjwt = { version = "^2.10.1", extras = ["crypto"] }
-redis = "^7.1.1"
+redis = "^6.2.0"
-supabase = "^2.28.0"
+supabase = "^2.16.0"
-uvicorn = "^0.40.0"
+uvicorn = "^0.35.0"
 
 [tool.poetry.group.dev.dependencies]
-pyright = "^1.1.408"
+pyright = "^1.1.404"
-pytest = "^9.0.2"
+pytest = "^8.4.1"
-pytest-asyncio = "^1.3.0"
+pytest-asyncio = "^1.1.0"
-pytest-mock = "^3.15.1"
+pytest-mock = "^3.14.1"
-pytest-cov = "^7.0.0"
+pytest-cov = "^6.2.1"
-ruff = "^0.15.0"
+ruff = "^0.12.11"
 
 [build-system]
 requires = ["poetry-core"]

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

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

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

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

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

@@ -18,10 +18,6 @@ class ResponseType(str, Enum):
     START = "start"
     FINISH = "finish"
 
-    # Step lifecycle (one LLM API call within a message)
-    START_STEP = "start-step"
-    FINISH_STEP = "finish-step"
-
     # Text streaming
     TEXT_START = "text-start"
     TEXT_DELTA = "text-delta"
@@ -61,16 +57,6 @@ class StreamStart(StreamBaseResponse):
         description="Task ID for SSE reconnection. Clients can reconnect using GET /tasks/{taskId}/stream",
     )
 
-    def to_sse(self) -> str:
-        """Convert to SSE format, excluding non-protocol fields like taskId."""
-        import json
-
-        data: dict[str, Any] = {
-            "type": self.type.value,
-            "messageId": self.messageId,
-        }
-        return f"data: {json.dumps(data)}\n\n"
-
 
 class StreamFinish(StreamBaseResponse):
     """End of message/stream."""
@@ -78,26 +64,6 @@ class StreamFinish(StreamBaseResponse):
     type: ResponseType = ResponseType.FINISH
 
 
-class StreamStartStep(StreamBaseResponse):
-    """Start of a step (one LLM API call within a message).
-
-    The AI SDK uses this to add a step-start boundary to message.parts,
-    enabling visual separation between multiple LLM calls in a single message.
-    """
-
-    type: ResponseType = ResponseType.START_STEP
-
-
-class StreamFinishStep(StreamBaseResponse):
-    """End of a step (one LLM API call within a message).
-
-    The AI SDK uses this to reset activeTextParts and activeReasoningParts,
-    so the next LLM call in a tool-call continuation starts with clean state.
-    """
-
-    type: ResponseType = ResponseType.FINISH_STEP
-
-
 # ========== Text Streaming ==========
 
 
@@ -151,7 +117,7 @@ class StreamToolOutputAvailable(StreamBaseResponse):
     type: ResponseType = ResponseType.TOOL_OUTPUT_AVAILABLE
     toolCallId: str = Field(..., description="Tool call ID this responds to")
     output: str | dict[str, Any] = Field(..., description="Tool execution output")
-    # Keep these for internal backend use
+    # Additional fields for internal use (not part of AI SDK spec but useful)
     toolName: str | None = Field(
         default=None, description="Name of the tool that was executed"
     )
@@ -159,17 +125,6 @@ class StreamToolOutputAvailable(StreamBaseResponse):
         default=True, description="Whether the tool execution succeeded"
     )
 
-    def to_sse(self) -> str:
-        """Convert to SSE format, excluding non-spec fields."""
-        import json
-
-        data = {
-            "type": self.type.value,
-            "toolCallId": self.toolCallId,
-            "output": self.output,
-        }
-        return f"data: {json.dumps(data)}\n\n"
-
 
 # ========== Other ==========
 

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

@@ -6,7 +6,7 @@ from collections.abc import AsyncGenerator
 from typing import Annotated
 
 from autogpt_libs import auth
-from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security
+from fastapi import APIRouter, Depends, Header, HTTPException, Query, Security
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
@@ -17,29 +17,7 @@ from . import stream_registry
 from .completion_handler import process_operation_failure, process_operation_success
 from .config import ChatConfig
 from .model import ChatSession, create_chat_session, get_chat_session, get_user_sessions
-from .response_model import StreamFinish, StreamHeartbeat
+from .response_model import StreamFinish, StreamHeartbeat, StreamStart
-from .tools.models import (
-    AgentDetailsResponse,
-    AgentOutputResponse,
-    AgentPreviewResponse,
-    AgentSavedResponse,
-    AgentsFoundResponse,
-    BlockListResponse,
-    BlockOutputResponse,
-    ClarificationNeededResponse,
-    DocPageResponse,
-    DocSearchResultsResponse,
-    ErrorResponse,
-    ExecutionStartedResponse,
-    InputValidationErrorResponse,
-    NeedLoginResponse,
-    NoResultsResponse,
-    OperationInProgressResponse,
-    OperationPendingResponse,
-    OperationStartedResponse,
-    SetupRequirementsResponse,
-    UnderstandingUpdatedResponse,
-)
 
 config = ChatConfig()
 
@@ -288,36 +266,12 @@ async def stream_chat_post(
 
     """
     import asyncio
-    import time
-
-    stream_start_time = time.perf_counter()
-    log_meta = {"component": "ChatStream", "session_id": session_id}
-    if user_id:
-        log_meta["user_id"] = user_id
-
-    logger.info(
-        f"[TIMING] stream_chat_post STARTED, session={session_id}, "
-        f"user={user_id}, message_len={len(request.message)}",
-        extra={"json_fields": log_meta},
-    )
 
     session = await _validate_and_get_session(session_id, user_id)
-    logger.info(
-        f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
-        extra={
-            "json_fields": {
-                **log_meta,
-                "duration_ms": (time.perf_counter() - stream_start_time) * 1000,
-            }
-        },
-    )
 
     # Create a task in the stream registry for reconnection support
     task_id = str(uuid_module.uuid4())
     operation_id = str(uuid_module.uuid4())
-    log_meta["task_id"] = task_id
-
-    task_create_start = time.perf_counter()
     await stream_registry.create_task(
         task_id=task_id,
         session_id=session_id,
@@ -326,28 +280,14 @@ async def stream_chat_post(
         tool_name="chat",
         operation_id=operation_id,
     )
-    logger.info(
-        f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
-        extra={
-            "json_fields": {
-                **log_meta,
-                "duration_ms": (time.perf_counter() - task_create_start) * 1000,
-            }
-        },
-    )
 
     # Background task that runs the AI generation independently of SSE connection
     async def run_ai_generation():
-        import time as time_module
-
-        gen_start_time = time_module.perf_counter()
-        logger.info(
-            f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
-            extra={"json_fields": log_meta},
-        )
-        first_chunk_time, ttfc = None, None
-        chunk_count = 0
         try:
+            # Emit a start event with task_id for reconnection
+            start_chunk = StreamStart(messageId=task_id, taskId=task_id)
+            await stream_registry.publish_chunk(task_id, start_chunk)
+
             async for chunk in chat_service.stream_chat_completion(
                 session_id,
                 request.message,
@@ -355,79 +295,25 @@ async def stream_chat_post(
                 user_id=user_id,
                 session=session,  # Pass pre-fetched session to avoid double-fetch
                 context=request.context,
-                _task_id=task_id,  # Pass task_id so service emits start with taskId for reconnection
             ):
-                chunk_count += 1
-                if first_chunk_time is None:
-                    first_chunk_time = time_module.perf_counter()
-                    ttfc = first_chunk_time - gen_start_time
-                    logger.info(
-                        f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
-                        extra={
-                            "json_fields": {
-                                **log_meta,
-                                "chunk_type": type(chunk).__name__,
-                                "time_to_first_chunk_ms": ttfc * 1000,
-                            }
-                        },
-                    )
                 # Write to Redis (subscribers will receive via XREAD)
                 await stream_registry.publish_chunk(task_id, chunk)
 
-            gen_end_time = time_module.perf_counter()
+            # Mark task as completed
-            total_time = (gen_end_time - gen_start_time) * 1000
-            logger.info(
-                f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
-                f"task={task_id}, session={session_id}, "
-                f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "total_time_ms": total_time,
-                        "time_to_first_chunk_ms": (
-                            ttfc * 1000 if ttfc is not None else None
-                        ),
-                        "n_chunks": chunk_count,
-                    }
-                },
-            )
             await stream_registry.mark_task_completed(task_id, "completed")
         except Exception as e:
-            elapsed = time_module.perf_counter() - gen_start_time
             logger.error(
-                f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
+                f"Error in background AI generation for session {session_id}: {e}"
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "elapsed_ms": elapsed * 1000,
-                        "error": str(e),
-                    }
-                },
             )
             await stream_registry.mark_task_completed(task_id, "failed")
 
     # Start the AI generation in a background task
     bg_task = asyncio.create_task(run_ai_generation())
     await stream_registry.set_task_asyncio_task(task_id, bg_task)
-    setup_time = (time.perf_counter() - stream_start_time) * 1000
-    logger.info(
-        f"[TIMING] Background task started, setup={setup_time:.1f}ms",
-        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
-    )
 
     # SSE endpoint that subscribes to the task's stream
     async def event_generator() -> AsyncGenerator[str, None]:
-        import time as time_module
-
-        event_gen_start = time_module.perf_counter()
-        logger.info(
-            f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
-            f"user={user_id}",
-            extra={"json_fields": log_meta},
-        )
         subscriber_queue = None
-        first_chunk_yielded = False
-        chunks_yielded = 0
         try:
             # Subscribe to the task stream (this replays existing messages + live updates)
             subscriber_queue = await stream_registry.subscribe_to_task(
@@ -442,70 +328,22 @@ async def stream_chat_post(
                 return
 
             # Read from the subscriber queue and yield to SSE
-            logger.info(
-                "[TIMING] Starting to read from subscriber_queue",
-                extra={"json_fields": log_meta},
-            )
             while True:
                 try:
                     chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
-                    chunks_yielded += 1
-
-                    if not first_chunk_yielded:
-                        first_chunk_yielded = True
-                        elapsed = time_module.perf_counter() - event_gen_start
-                        logger.info(
-                            f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
-                            f"type={type(chunk).__name__}",
-                            extra={
-                                "json_fields": {
-                                    **log_meta,
-                                    "chunk_type": type(chunk).__name__,
-                                    "elapsed_ms": elapsed * 1000,
-                                }
-                            },
-                        )
-
                     yield chunk.to_sse()
 
                     # Check for finish signal
                     if isinstance(chunk, StreamFinish):
-                        total_time = time_module.perf_counter() - event_gen_start
-                        logger.info(
-                            f"[TIMING] StreamFinish received in {total_time:.2f}s; "
-                            f"n_chunks={chunks_yielded}",
-                            extra={
-                                "json_fields": {
-                                    **log_meta,
-                                    "chunks_yielded": chunks_yielded,
-                                    "total_time_ms": total_time * 1000,
-                                }
-                            },
-                        )
                         break
                 except asyncio.TimeoutError:
+                    # Send heartbeat to keep connection alive
                     yield StreamHeartbeat().to_sse()
 
         except GeneratorExit:
-            logger.info(
-                f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "chunks_yielded": chunks_yielded,
-                        "reason": "client_disconnect",
-                    }
-                },
-            )
             pass  # Client disconnected - background task continues
         except Exception as e:
-            elapsed = (time_module.perf_counter() - event_gen_start) * 1000
+            logger.error(f"Error in SSE stream for task {task_id}: {e}")
-            logger.error(
-                f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
-                extra={
-                    "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
-                },
-            )
         finally:
             # Unsubscribe when client disconnects or stream ends to prevent resource leak
             if subscriber_queue is not None:
@@ -519,18 +357,6 @@ async def stream_chat_post(
                         exc_info=True,
                     )
             # AI SDK protocol termination - always yield even if unsubscribe fails
-            total_time = time_module.perf_counter() - event_gen_start
-            logger.info(
-                f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
-                f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "total_time_ms": total_time * 1000,
-                        "chunks_yielded": chunks_yielded,
-                    }
-                },
-            )
             yield "data: [DONE]\n\n"
 
     return StreamingResponse(
@@ -548,90 +374,63 @@ async def stream_chat_post(
 @router.get(
     "/sessions/{session_id}/stream",
 )
-async def resume_session_stream(
+async def stream_chat_get(
     session_id: str,
+    message: Annotated[str, Query(min_length=1, max_length=10000)],
     user_id: str | None = Depends(auth.get_user_id),
+    is_user_message: bool = Query(default=True),
 ):
     """
-    Resume an active stream for a session.
+    Stream chat responses for a session (GET - legacy endpoint).
 
-    Called by the AI SDK's ``useChat(resume: true)`` on page load.
+    Streams the AI/completion responses in real time over Server-Sent Events (SSE), including:
-    Checks for an active (in-progress) task on the session and either replays
+      - Text fragments as they are generated
-    the full SSE stream or returns 204 No Content if nothing is running.
+      - Tool call UI elements (if invoked)
+      - Tool execution results
 
     Args:
-        session_id: The chat session identifier.
+        session_id: The chat session identifier to associate with the streamed messages.
+        message: The user's new message to process.
         user_id: Optional authenticated user ID.
-
+        is_user_message: Whether the message is a user message.
     Returns:
-        StreamingResponse (SSE) when an active stream exists,
+        StreamingResponse: SSE-formatted response chunks.
-        or 204 No Content when there is nothing to resume.
+
     """
-    import asyncio
+    session = await _validate_and_get_session(session_id, user_id)
-
-    active_task, _last_id = await stream_registry.get_active_task_for_session(
-        session_id, user_id
-    )
-
-    if not active_task:
-        return Response(status_code=204)
-
-    subscriber_queue = await stream_registry.subscribe_to_task(
-        task_id=active_task.task_id,
-        user_id=user_id,
-        last_message_id="0-0",  # Full replay so useChat rebuilds the message
-    )
-
-    if subscriber_queue is None:
-        return Response(status_code=204)
 
     async def event_generator() -> AsyncGenerator[str, None]:
         chunk_count = 0
         first_chunk_type: str | None = None
-        try:
+        async for chunk in chat_service.stream_chat_completion(
-            while True:
+            session_id,
-                try:
+            message,
-                    chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+            is_user_message=is_user_message,
-                    if chunk_count < 3:
+            user_id=user_id,
-                        logger.info(
+            session=session,  # Pass pre-fetched session to avoid double-fetch
-                            "Resume stream chunk",
+        ):
-                            extra={
+            if chunk_count < 3:
-                                "session_id": session_id,
+                logger.info(
-                                "chunk_type": str(chunk.type),
+                    "Chat stream chunk",
-                            },
+                    extra={
-                        )
+                        "session_id": session_id,
-                    if not first_chunk_type:
+                        "chunk_type": str(chunk.type),
-                        first_chunk_type = str(chunk.type)
+                    },
-                    chunk_count += 1
-                    yield chunk.to_sse()
-
-                    if isinstance(chunk, StreamFinish):
-                        break
-                except asyncio.TimeoutError:
-                    yield StreamHeartbeat().to_sse()
-        except GeneratorExit:
-            pass
-        except Exception as e:
-            logger.error(f"Error in resume stream for session {session_id}: {e}")
-        finally:
-            try:
-                await stream_registry.unsubscribe_from_task(
-                    active_task.task_id, subscriber_queue
                 )
-            except Exception as unsub_err:
+            if not first_chunk_type:
-                logger.error(
+                first_chunk_type = str(chunk.type)
-                    f"Error unsubscribing from task {active_task.task_id}: {unsub_err}",
+            chunk_count += 1
-                    exc_info=True,
+            yield chunk.to_sse()
-                )
+        logger.info(
-            logger.info(
+            "Chat stream completed",
-                "Resume stream completed",
+            extra={
-                extra={
+                "session_id": session_id,
-                    "session_id": session_id,
+                "chunk_count": chunk_count,
-                    "n_chunks": chunk_count,
+                "first_chunk_type": first_chunk_type,
-                    "first_chunk_type": first_chunk_type,
+            },
-                },
+        )
-            )
+        # AI SDK protocol termination
-            yield "data: [DONE]\n\n"
+        yield "data: [DONE]\n\n"
 
     return StreamingResponse(
         event_generator(),
@@ -639,8 +438,8 @@ async def resume_session_stream(
         headers={
             "Cache-Control": "no-cache",
             "Connection": "keep-alive",
-            "X-Accel-Buffering": "no",
+            "X-Accel-Buffering": "no",  # Disable nginx buffering
-            "x-vercel-ai-ui-message-stream": "v1",
+            "x-vercel-ai-ui-message-stream": "v1",  # AI SDK protocol header
         },
     )
 
@@ -952,42 +751,3 @@ async def health_check() -> dict:
         "service": "chat",
         "version": "0.1.0",
     }
-
-
-# ========== Schema Export (for OpenAPI / Orval codegen) ==========
-
-ToolResponseUnion = (
-    AgentsFoundResponse
-    | NoResultsResponse
-    | AgentDetailsResponse
-    | SetupRequirementsResponse
-    | ExecutionStartedResponse
-    | NeedLoginResponse
-    | ErrorResponse
-    | InputValidationErrorResponse
-    | AgentOutputResponse
-    | UnderstandingUpdatedResponse
-    | AgentPreviewResponse
-    | AgentSavedResponse
-    | ClarificationNeededResponse
-    | BlockListResponse
-    | BlockOutputResponse
-    | DocSearchResultsResponse
-    | DocPageResponse
-    | OperationStartedResponse
-    | OperationPendingResponse
-    | OperationInProgressResponse
-)
-
-
-@router.get(
-    "/schema/tool-responses",
-    response_model=ToolResponseUnion,
-    include_in_schema=True,
-    summary="[Dummy] Tool response type export for codegen",
-    description="This endpoint is not meant to be called. It exists solely to "
-    "expose tool response models in the OpenAPI schema for frontend codegen.",
-)
-async def _tool_response_schema() -> ToolResponseUnion:  # type: ignore[return]
-    """Never called at runtime. Exists only so Orval generates TS types."""
-    raise HTTPException(status_code=501, detail="Schema-only endpoint")

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

@@ -52,10 +52,8 @@ from .response_model import (
     StreamBaseResponse,
     StreamError,
     StreamFinish,
-    StreamFinishStep,
     StreamHeartbeat,
     StreamStart,
-    StreamStartStep,
     StreamTextDelta,
     StreamTextEnd,
     StreamTextStart,
@@ -353,10 +351,6 @@ async def stream_chat_completion(
     retry_count: int = 0,
     session: ChatSession | None = None,
     context: dict[str, str] | None = None,  # {url: str, content: str}
-    _continuation_message_id: (
-        str | None
-    ) = None,  # Internal: reuse message ID for tool call continuations
-    _task_id: str | None = None,  # Internal: task ID for SSE reconnection support
 ) -> AsyncGenerator[StreamBaseResponse, None]:
     """Main entry point for streaming chat completions with database handling.
 
@@ -377,45 +371,21 @@ async def stream_chat_completion(
         ValueError: If max_context_messages is exceeded
 
     """
-    completion_start = time.monotonic()
-
-    # Build log metadata for structured logging
-    log_meta = {"component": "ChatService", "session_id": session_id}
-    if user_id:
-        log_meta["user_id"] = user_id
-
     logger.info(
-        f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
+        f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
-        f"message_len={len(message) if message else 0}, is_user={is_user_message}",
-        extra={
-            "json_fields": {
-                **log_meta,
-                "message_len": len(message) if message else 0,
-                "is_user_message": is_user_message,
-            }
-        },
     )
 
     # Only fetch from Redis if session not provided (initial call)
     if session is None:
-        fetch_start = time.monotonic()
         session = await get_chat_session(session_id, user_id)
-        fetch_time = (time.monotonic() - fetch_start) * 1000
         logger.info(
-            f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
+            f"Fetched session from Redis: {session.session_id if session else 'None'}, "
-            f"n_messages={len(session.messages) if session else 0}",
+            f"message_count={len(session.messages) if session else 0}"
-            extra={
-                "json_fields": {
-                    **log_meta,
-                    "duration_ms": fetch_time,
-                    "n_messages": len(session.messages) if session else 0,
-                }
-            },
         )
     else:
         logger.info(
-            f"[TIMING] Using provided session, messages={len(session.messages)}",
+            f"Using provided session object: {session.session_id}, "
-            extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
+            f"message_count={len(session.messages)}"
         )
 
     if not session:
@@ -436,25 +406,17 @@ async def stream_chat_completion(
 
         # Track user message in PostHog
         if is_user_message:
-            posthog_start = time.monotonic()
             track_user_message(
                 user_id=user_id,
                 session_id=session_id,
                 message_length=len(message),
             )
-            posthog_time = (time.monotonic() - posthog_start) * 1000
-            logger.info(
-                f"[TIMING] track_user_message took {posthog_time:.1f}ms",
-                extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
-            )
 
-    upsert_start = time.monotonic()
-    session = await upsert_chat_session(session)
-    upsert_time = (time.monotonic() - upsert_start) * 1000
     logger.info(
-        f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
+        f"Upserting session: {session.session_id} with user id {session.user_id}, "
-        extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
+        f"message_count={len(session.messages)}"
     )
+    session = await upsert_chat_session(session)
     assert session, "Session not found"
 
     # Generate title for new sessions on first user message (non-blocking)
@@ -492,13 +454,7 @@ async def stream_chat_completion(
             asyncio.create_task(_update_title())
 
     # Build system prompt with business understanding
-    prompt_start = time.monotonic()
     system_prompt, understanding = await _build_system_prompt(user_id)
-    prompt_time = (time.monotonic() - prompt_start) * 1000
-    logger.info(
-        f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
-        extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
-    )
 
     # Initialize variables for streaming
     assistant_response = ChatMessage(
@@ -523,27 +479,13 @@ async def stream_chat_completion(
     # Generate unique IDs for AI SDK protocol
     import uuid as uuid_module
 
-    is_continuation = _continuation_message_id is not None
+    message_id = str(uuid_module.uuid4())
-    message_id = _continuation_message_id or str(uuid_module.uuid4())
     text_block_id = str(uuid_module.uuid4())
 
-    # Only yield message start for the initial call, not for continuations.
+    # Yield message start
-    setup_time = (time.monotonic() - completion_start) * 1000
+    yield StreamStart(messageId=message_id)
-    logger.info(
-        f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
-        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
-    )
-    if not is_continuation:
-        yield StreamStart(messageId=message_id, taskId=_task_id)
-
-    # Emit start-step before each LLM call (AI SDK uses this to add step boundaries)
-    yield StreamStartStep()
 
     try:
-        logger.info(
-            "[TIMING] Calling _stream_chat_chunks",
-            extra={"json_fields": log_meta},
-        )
         async for chunk in _stream_chat_chunks(
             session=session,
             tools=tools,
@@ -643,10 +585,6 @@ async def stream_chat_completion(
                     )
                 yield chunk
             elif isinstance(chunk, StreamFinish):
-                if has_done_tool_call:
-                    # Tool calls happened — close the step but don't send message-level finish.
-                    # The continuation will open a new step, and finish will come at the end.
-                    yield StreamFinishStep()
                 if not has_done_tool_call:
                     # Emit text-end before finish if we received text but haven't closed it
                     if has_received_text and not text_streaming_ended:
@@ -678,8 +616,6 @@ async def stream_chat_completion(
                             has_saved_assistant_message = True
 
                     has_yielded_end = True
-                    # Emit finish-step before finish (resets AI SDK text/reasoning state)
-                    yield StreamFinishStep()
                     yield chunk
             elif isinstance(chunk, StreamError):
                 has_yielded_error = True
@@ -729,10 +665,6 @@ async def stream_chat_completion(
             logger.info(
                 f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}"
             )
-            # Close the current step before retrying so the recursive call's
-            # StreamStartStep doesn't produce unbalanced step events.
-            if not has_yielded_end:
-                yield StreamFinishStep()
             should_retry = True
         else:
             # Non-retryable error or max retries exceeded
@@ -768,7 +700,6 @@ async def stream_chat_completion(
                 error_response = StreamError(errorText=error_message)
                 yield error_response
             if not has_yielded_end:
-                yield StreamFinishStep()
                 yield StreamFinish()
             return
 
@@ -783,8 +714,6 @@ async def stream_chat_completion(
             retry_count=retry_count + 1,
             session=session,
             context=context,
-            _continuation_message_id=message_id,  # Reuse message ID since start was already sent
-            _task_id=_task_id,
         ):
             yield chunk
         return  # Exit after retry to avoid double-saving in finally block
@@ -854,8 +783,6 @@ async def stream_chat_completion(
             session=session,  # Pass session object to avoid Redis refetch
             context=context,
             tool_call_response=str(tool_response_messages),
-            _continuation_message_id=message_id,  # Reuse message ID to avoid duplicates
-            _task_id=_task_id,
         ):
             yield chunk
 
@@ -966,21 +893,9 @@ async def _stream_chat_chunks(
         SSE formatted JSON response objects
 
     """
-    import time as time_module
-
-    stream_chunks_start = time_module.perf_counter()
     model = config.model
 
-    # Build log metadata for structured logging
+    logger.info("Starting pure chat stream")
-    log_meta = {"component": "ChatService", "session_id": session.session_id}
-    if session.user_id:
-        log_meta["user_id"] = session.user_id
-
-    logger.info(
-        f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
-        f"user={session.user_id}, n_messages={len(session.messages)}",
-        extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
-    )
 
     messages = session.to_openai_messages()
     if system_prompt:
@@ -991,18 +906,12 @@ async def _stream_chat_chunks(
         messages = [system_message] + messages
 
     # Apply context window management
-    context_start = time_module.perf_counter()
     context_result = await _manage_context_window(
         messages=messages,
         model=model,
         api_key=config.api_key,
         base_url=config.base_url,
     )
-    context_time = (time_module.perf_counter() - context_start) * 1000
-    logger.info(
-        f"[TIMING] _manage_context_window took {context_time:.1f}ms",
-        extra={"json_fields": {**log_meta, "duration_ms": context_time}},
-    )
 
     if context_result.error:
         if "System prompt dropped" in context_result.error:
@@ -1037,19 +946,9 @@ async def _stream_chat_chunks(
 
         while retry_count <= MAX_RETRIES:
             try:
-                elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
-                retry_info = (
-                    f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
-                )
                 logger.info(
-                    f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
+                    f"Creating OpenAI chat completion stream..."
-                    extra={
+                    f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
-                        "json_fields": {
-                            **log_meta,
-                            "elapsed_ms": elapsed,
-                            "retry_count": retry_count,
-                        }
-                    },
                 )
 
                 # Build extra_body for OpenRouter tracing and PostHog analytics
@@ -1066,11 +965,6 @@ async def _stream_chat_chunks(
                         :128
                     ]  # OpenRouter limit
 
-                # Enable adaptive thinking for Anthropic models via OpenRouter
-                if config.thinking_enabled and "anthropic" in model.lower():
-                    extra_body["reasoning"] = {"enabled": True}
-
-                api_call_start = time_module.perf_counter()
                 stream = await client.chat.completions.create(
                     model=model,
                     messages=cast(list[ChatCompletionMessageParam], messages),
@@ -1080,11 +974,6 @@ async def _stream_chat_chunks(
                     stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
                     extra_body=extra_body,
                 )
-                api_init_time = (time_module.perf_counter() - api_call_start) * 1000
-                logger.info(
-                    f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
-                    extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
-                )
 
                 # Variables to accumulate tool calls
                 tool_calls: list[dict[str, Any]] = []
@@ -1095,13 +984,10 @@ async def _stream_chat_chunks(
 
                 # Track if we've started the text block
                 text_started = False
-                first_content_chunk = True
-                chunk_count = 0
 
                 # Process the stream
                 chunk: ChatCompletionChunk
                 async for chunk in stream:
-                    chunk_count += 1
                     if chunk.usage:
                         yield StreamUsage(
                             promptTokens=chunk.usage.prompt_tokens,
@@ -1124,23 +1010,6 @@ async def _stream_chat_chunks(
                             if not text_started and text_block_id:
                                 yield StreamTextStart(id=text_block_id)
                                 text_started = True
-                            # Log timing for first content chunk
-                            if first_content_chunk:
-                                first_content_chunk = False
-                                ttfc = (
-                                    time_module.perf_counter() - api_call_start
-                                ) * 1000
-                                logger.info(
-                                    f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
-                                    f"(since API call), n_chunks={chunk_count}",
-                                    extra={
-                                        "json_fields": {
-                                            **log_meta,
-                                            "time_to_first_chunk_ms": ttfc,
-                                            "n_chunks": chunk_count,
-                                        }
-                                    },
-                                )
                             # Stream the text delta
                             text_response = StreamTextDelta(
                                 id=text_block_id or "",
@@ -1197,21 +1066,7 @@ async def _stream_chat_chunks(
                                         toolName=tool_calls[idx]["function"]["name"],
                                     )
                                     emitted_start_for_idx.add(idx)
-                stream_duration = time_module.perf_counter() - api_call_start
+                logger.info(f"Stream complete. Finish reason: {finish_reason}")
-                logger.info(
-                    f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
-                    f"duration={stream_duration:.2f}s, "
-                    f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
-                    extra={
-                        "json_fields": {
-                            **log_meta,
-                            "stream_duration_ms": stream_duration * 1000,
-                            "finish_reason": finish_reason,
-                            "n_chunks": chunk_count,
-                            "n_tool_calls": len(tool_calls),
-                        }
-                    },
-                )
 
                 # Yield all accumulated tool calls after the stream is complete
                 # This ensures all tool call arguments have been fully received
@@ -1231,12 +1086,6 @@ async def _stream_chat_chunks(
                         # Re-raise to trigger retry logic in the parent function
                         raise
 
-                total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
-                logger.info(
-                    f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
-                    f"session={session.session_id}, user={session.user_id}",
-                    extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
-                )
                 yield StreamFinish()
                 return
             except Exception as e:
@@ -1716,7 +1565,6 @@ async def _execute_long_running_tool_with_streaming(
             task_id,
             StreamError(errorText=str(e)),
         )
-        await stream_registry.publish_chunk(task_id, StreamFinishStep())
         await stream_registry.publish_chunk(task_id, StreamFinish())
 
         await _update_pending_operation(
@@ -1833,10 +1681,6 @@ async def _generate_llm_continuation(
         if session_id:
             extra_body["session_id"] = session_id[:128]
 
-        # Enable adaptive thinking for Anthropic models via OpenRouter
-        if config.thinking_enabled and "anthropic" in config.model.lower():
-            extra_body["reasoning"] = {"enabled": True}
-
         retry_count = 0
         last_error: Exception | None = None
         response = None
@@ -1967,10 +1811,6 @@ async def _generate_llm_continuation_with_streaming(
         if session_id:
             extra_body["session_id"] = session_id[:128]
 
-        # Enable adaptive thinking for Anthropic models via OpenRouter
-        if config.thinking_enabled and "anthropic" in config.model.lower():
-            extra_body["reasoning"] = {"enabled": True}
-
         # Make streaming LLM call (no tools - just text response)
         from typing import cast
 
@@ -1982,7 +1822,6 @@ async def _generate_llm_continuation_with_streaming(
 
         # Publish start event
         await stream_registry.publish_chunk(task_id, StreamStart(messageId=message_id))
-        await stream_registry.publish_chunk(task_id, StreamStartStep())
         await stream_registry.publish_chunk(task_id, StreamTextStart(id=text_block_id))
 
         # Stream the response
@@ -2006,7 +1845,6 @@ async def _generate_llm_continuation_with_streaming(
 
         # Publish end events
         await stream_registry.publish_chunk(task_id, StreamTextEnd(id=text_block_id))
-        await stream_registry.publish_chunk(task_id, StreamFinishStep())
 
         if assistant_content:
             # Reload session from DB to avoid race condition with user messages
@@ -2048,5 +1886,4 @@ async def _generate_llm_continuation_with_streaming(
             task_id,
             StreamError(errorText=f"Failed to generate response: {e}"),
         )
-        await stream_registry.publish_chunk(task_id, StreamFinishStep())
         await stream_registry.publish_chunk(task_id, StreamFinish())

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

@@ -104,24 +104,6 @@ async def create_task(
     Returns:
         The created ActiveTask instance (metadata only)
     """
-    import time
-
-    start_time = time.perf_counter()
-
-    # Build log metadata for structured logging
-    log_meta = {
-        "component": "StreamRegistry",
-        "task_id": task_id,
-        "session_id": session_id,
-    }
-    if user_id:
-        log_meta["user_id"] = user_id
-
-    logger.info(
-        f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}",
-        extra={"json_fields": log_meta},
-    )
-
     task = ActiveTask(
         task_id=task_id,
         session_id=session_id,
@@ -132,18 +114,10 @@ async def create_task(
     )
 
     # Store metadata in Redis
-    redis_start = time.perf_counter()
     redis = await get_redis_async()
-    redis_time = (time.perf_counter() - redis_start) * 1000
-    logger.info(
-        f"[TIMING] get_redis_async took {redis_time:.1f}ms",
-        extra={"json_fields": {**log_meta, "duration_ms": redis_time}},
-    )
-
     meta_key = _get_task_meta_key(task_id)
     op_key = _get_operation_mapping_key(operation_id)
 
-    hset_start = time.perf_counter()
     await redis.hset(  # type: ignore[misc]
         meta_key,
         mapping={
@@ -157,22 +131,12 @@ async def create_task(
             "created_at": task.created_at.isoformat(),
         },
     )
-    hset_time = (time.perf_counter() - hset_start) * 1000
-    logger.info(
-        f"[TIMING] redis.hset took {hset_time:.1f}ms",
-        extra={"json_fields": {**log_meta, "duration_ms": hset_time}},
-    )
-
     await redis.expire(meta_key, config.stream_ttl)
 
     # Create operation_id -> task_id mapping for webhook lookups
     await redis.set(op_key, task_id, ex=config.stream_ttl)
 
-    total_time = (time.perf_counter() - start_time) * 1000
+    logger.debug(f"Created task {task_id} for session {session_id}")
-    logger.info(
-        f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
-        extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
-    )
 
     return task
 
@@ -192,60 +156,26 @@ async def publish_chunk(
     Returns:
         The Redis Stream message ID
     """
-    import time
-
-    start_time = time.perf_counter()
-    chunk_type = type(chunk).__name__
     chunk_json = chunk.model_dump_json()
     message_id = "0-0"
 
-    # Build log metadata
-    log_meta = {
-        "component": "StreamRegistry",
-        "task_id": task_id,
-        "chunk_type": chunk_type,
-    }
-
     try:
         redis = await get_redis_async()
         stream_key = _get_task_stream_key(task_id)
 
         # Write to Redis Stream for persistence and real-time delivery
-        xadd_start = time.perf_counter()
         raw_id = await redis.xadd(
             stream_key,
             {"data": chunk_json},
             maxlen=config.stream_max_length,
         )
-        xadd_time = (time.perf_counter() - xadd_start) * 1000
         message_id = raw_id if isinstance(raw_id, str) else raw_id.decode()
 
         # Set TTL on stream to match task metadata TTL
         await redis.expire(stream_key, config.stream_ttl)
-
-        total_time = (time.perf_counter() - start_time) * 1000
-        # Only log timing for significant chunks or slow operations
-        if (
-            chunk_type
-            in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd")
-            or total_time > 50
-        ):
-            logger.info(
-                f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)",
-                extra={
-                    "json_fields": {
-                        **log_meta,
-                        "total_time_ms": total_time,
-                        "xadd_time_ms": xadd_time,
-                        "message_id": message_id,
-                    }
-                },
-            )
     except Exception as e:
-        elapsed = (time.perf_counter() - start_time) * 1000
         logger.error(
-            f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}",
+            f"Failed to publish chunk for task {task_id}: {e}",
-            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
             exc_info=True,
         )
 
@@ -270,61 +200,24 @@ async def subscribe_to_task(
         An asyncio Queue that will receive stream chunks, or None if task not found
         or user doesn't have access
     """
-    import time
-
-    start_time = time.perf_counter()
-
-    # Build log metadata
-    log_meta = {"component": "StreamRegistry", "task_id": task_id}
-    if user_id:
-        log_meta["user_id"] = user_id
-
-    logger.info(
-        f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}",
-        extra={"json_fields": {**log_meta, "last_message_id": last_message_id}},
-    )
-
-    redis_start = time.perf_counter()
     redis = await get_redis_async()
     meta_key = _get_task_meta_key(task_id)
     meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
-    hgetall_time = (time.perf_counter() - redis_start) * 1000
-    logger.info(
-        f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
-        extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}},
-    )
 
     if not meta:
-        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.debug(f"Task {task_id} not found in Redis")
-        logger.info(
-            f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
-            extra={
-                "json_fields": {
-                    **log_meta,
-                    "elapsed_ms": elapsed,
-                    "reason": "task_not_found",
-                }
-            },
-        )
         return None
 
     # Note: Redis client uses decode_responses=True, so keys are strings
     task_status = meta.get("status", "")
     task_user_id = meta.get("user_id", "") or None
-    log_meta["session_id"] = meta.get("session_id", "")
 
     # Validate ownership - if task has an owner, requester must match
     if task_user_id:
         if user_id != task_user_id:
             logger.warning(
-                f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}",
+                f"User {user_id} denied access to task {task_id} "
-                extra={
+                f"owned by {task_user_id}"
-                    "json_fields": {
-                        **log_meta,
-                        "task_owner": task_user_id,
-                        "reason": "access_denied",
-                    }
-                },
             )
             return None
 
@@ -332,19 +225,7 @@ async def subscribe_to_task(
     stream_key = _get_task_stream_key(task_id)
 
     # Step 1: Replay messages from Redis Stream
-    xread_start = time.perf_counter()
     messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
-    xread_time = (time.perf_counter() - xread_start) * 1000
-    logger.info(
-        f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}",
-        extra={
-            "json_fields": {
-                **log_meta,
-                "duration_ms": xread_time,
-                "task_status": task_status,
-            }
-        },
-    )
 
     replayed_count = 0
     replay_last_id = last_message_id
@@ -363,48 +244,19 @@ async def subscribe_to_task(
                     except Exception as e:
                         logger.warning(f"Failed to replay message: {e}")
 
-    logger.info(
+    logger.debug(f"Task {task_id}: replayed {replayed_count} messages")
-        f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
-        extra={
-            "json_fields": {
-                **log_meta,
-                "n_messages_replayed": replayed_count,
-                "replay_last_id": replay_last_id,
-            }
-        },
-    )
 
     # Step 2: If task is still running, start stream listener for live updates
     if task_status == "running":
-        logger.info(
-            "[TIMING] Task still running, starting _stream_listener",
-            extra={"json_fields": {**log_meta, "task_status": task_status}},
-        )
         listener_task = asyncio.create_task(
-            _stream_listener(task_id, subscriber_queue, replay_last_id, log_meta)
+            _stream_listener(task_id, subscriber_queue, replay_last_id)
         )
         # Track listener task for cleanup on unsubscribe
         _listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
     else:
         # Task is completed/failed - add finish marker
-        logger.info(
-            f"[TIMING] Task already {task_status}, adding StreamFinish",
-            extra={"json_fields": {**log_meta, "task_status": task_status}},
-        )
         await subscriber_queue.put(StreamFinish())
 
-    total_time = (time.perf_counter() - start_time) * 1000
-    logger.info(
-        f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
-        f"n_messages_replayed={replayed_count}",
-        extra={
-            "json_fields": {
-                **log_meta,
-                "total_time_ms": total_time,
-                "n_messages_replayed": replayed_count,
-            }
-        },
-    )
     return subscriber_queue
 
 
@@ -412,7 +264,6 @@ async def _stream_listener(
     task_id: str,
     subscriber_queue: asyncio.Queue[StreamBaseResponse],
     last_replayed_id: str,
-    log_meta: dict | None = None,
 ) -> None:
     """Listen to Redis Stream for new messages using blocking XREAD.
 
@@ -423,27 +274,10 @@ async def _stream_listener(
         task_id: Task ID to listen for
         subscriber_queue: Queue to deliver messages to
         last_replayed_id: Last message ID from replay (continue from here)
-        log_meta: Structured logging metadata
     """
-    import time
-
-    start_time = time.perf_counter()
-
-    # Use provided log_meta or build minimal one
-    if log_meta is None:
-        log_meta = {"component": "StreamRegistry", "task_id": task_id}
-
-    logger.info(
-        f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}",
-        extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}},
-    )
-
     queue_id = id(subscriber_queue)
     # Track the last successfully delivered message ID for recovery hints
     last_delivered_id = last_replayed_id
-    messages_delivered = 0
-    first_message_time = None
-    xread_count = 0
 
     try:
         redis = await get_redis_async()
@@ -453,39 +287,9 @@ async def _stream_listener(
         while True:
             # Block for up to 30 seconds waiting for new messages
             # This allows periodic checking if task is still running
-            xread_start = time.perf_counter()
-            xread_count += 1
             messages = await redis.xread(
                 {stream_key: current_id}, block=30000, count=100
             )
-            xread_time = (time.perf_counter() - xread_start) * 1000
-
-            if messages:
-                msg_count = sum(len(msgs) for _, msgs in messages)
-                logger.info(
-                    f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms",
-                    extra={
-                        "json_fields": {
-                            **log_meta,
-                            "xread_count": xread_count,
-                            "n_messages": msg_count,
-                            "duration_ms": xread_time,
-                        }
-                    },
-                )
-            elif xread_time > 1000:
-                # Only log timeouts (30s blocking)
-                logger.info(
-                    f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms",
-                    extra={
-                        "json_fields": {
-                            **log_meta,
-                            "xread_count": xread_count,
-                            "duration_ms": xread_time,
-                            "reason": "timeout",
-                        }
-                    },
-                )
 
             if not messages:
                 # Timeout - check if task is still running
@@ -522,30 +326,10 @@ async def _stream_listener(
                                 )
                                 # Update last delivered ID on successful delivery
                                 last_delivered_id = current_id
-                                messages_delivered += 1
-                                if first_message_time is None:
-                                    first_message_time = time.perf_counter()
-                                    elapsed = (first_message_time - start_time) * 1000
-                                    logger.info(
-                                        f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
-                                        extra={
-                                            "json_fields": {
-                                                **log_meta,
-                                                "elapsed_ms": elapsed,
-                                                "chunk_type": type(chunk).__name__,
-                                            }
-                                        },
-                                    )
                             except asyncio.TimeoutError:
                                 logger.warning(
-                                    f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s",
+                                    f"Subscriber queue full for task {task_id}, "
-                                    extra={
+                                    f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s"
-                                        "json_fields": {
-                                            **log_meta,
-                                            "timeout_s": QUEUE_PUT_TIMEOUT,
-                                            "reason": "queue_full",
-                                        }
-                                    },
                                 )
                                 # Send overflow error with recovery info
                                 try:
@@ -567,44 +351,15 @@ async def _stream_listener(
 
                             # Stop listening on finish
                             if isinstance(chunk, StreamFinish):
-                                total_time = (time.perf_counter() - start_time) * 1000
-                                logger.info(
-                                    f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}",
-                                    extra={
-                                        "json_fields": {
-                                            **log_meta,
-                                            "total_time_ms": total_time,
-                                            "messages_delivered": messages_delivered,
-                                        }
-                                    },
-                                )
                                 return
                     except Exception as e:
-                        logger.warning(
+                        logger.warning(f"Error processing stream message: {e}")
-                            f"Error processing stream message: {e}",
-                            extra={"json_fields": {**log_meta, "error": str(e)}},
-                        )
 
     except asyncio.CancelledError:
-        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.debug(f"Stream listener cancelled for task {task_id}")
-        logger.info(
-            f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
-            extra={
-                "json_fields": {
-                    **log_meta,
-                    "elapsed_ms": elapsed,
-                    "messages_delivered": messages_delivered,
-                    "reason": "cancelled",
-                }
-            },
-        )
         raise  # Re-raise to propagate cancellation
     except Exception as e:
-        elapsed = (time.perf_counter() - start_time) * 1000
+        logger.error(f"Stream listener error for task {task_id}: {e}")
-        logger.error(
-            f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}",
-            extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}},
-        )
         # On error, send finish to unblock subscriber
         try:
             await asyncio.wait_for(
@@ -613,24 +368,10 @@ async def _stream_listener(
             )
         except (asyncio.TimeoutError, asyncio.QueueFull):
             logger.warning(
-                "Could not deliver finish event after error",
+                f"Could not deliver finish event for task {task_id} after error"
-                extra={"json_fields": log_meta},
             )
     finally:
         # Clean up listener task mapping on exit
-        total_time = (time.perf_counter() - start_time) * 1000
-        logger.info(
-            f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
-            f"delivered={messages_delivered}, xread_count={xread_count}",
-            extra={
-                "json_fields": {
-                    **log_meta,
-                    "total_time_ms": total_time,
-                    "messages_delivered": messages_delivered,
-                    "xread_count": xread_count,
-                }
-            },
-        )
         _listener_tasks.pop(queue_id, None)
 
 
@@ -857,10 +598,8 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
         ResponseType,
         StreamError,
         StreamFinish,
-        StreamFinishStep,
         StreamHeartbeat,
         StreamStart,
-        StreamStartStep,
         StreamTextDelta,
         StreamTextEnd,
         StreamTextStart,
@@ -874,8 +613,6 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None:
     type_to_class: dict[str, type[StreamBaseResponse]] = {
         ResponseType.START.value: StreamStart,
         ResponseType.FINISH.value: StreamFinish,
-        ResponseType.START_STEP.value: StreamStartStep,
-        ResponseType.FINISH_STEP.value: StreamFinishStep,
         ResponseType.TEXT_START.value: StreamTextStart,
         ResponseType.TEXT_DELTA.value: StreamTextDelta,
         ResponseType.TEXT_END.value: StreamTextEnd,

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

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

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

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

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

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

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

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

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

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

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

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

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

@@ -8,7 +8,6 @@ from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
 from backend.data.graph import GraphModel
 from backend.data.model import (
-    Credentials,
     CredentialsFieldInfo,
     CredentialsMetaInput,
     HostScopedCredentials,
@@ -118,7 +117,7 @@ def build_missing_credentials_from_graph(
     preserving all supported credential types for each field.
     """
     matched_keys = set(matched_credentials.keys()) if matched_credentials else set()
-    aggregated_fields = graph.aggregate_credentials_inputs()
+    aggregated_fields = graph.regular_credentials_inputs
 
     return {
         field_key: _serialize_missing_credential(field_key, field_info)
@@ -224,99 +223,6 @@ async def get_or_create_library_agent(
     return library_agents[0]
 
 
-async def match_credentials_to_requirements(
-    user_id: str,
-    requirements: dict[str, CredentialsFieldInfo],
-) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
-    """
-    Match user's credentials against a dictionary of credential requirements.
-
-    This is the core matching logic shared by both graph and block credential matching.
-    """
-    matched: dict[str, CredentialsMetaInput] = {}
-    missing: list[CredentialsMetaInput] = []
-
-    if not requirements:
-        return matched, missing
-
-    available_creds = await get_user_credentials(user_id)
-
-    for field_name, field_info in requirements.items():
-        matching_cred = find_matching_credential(available_creds, field_info)
-
-        if matching_cred:
-            try:
-                matched[field_name] = create_credential_meta_from_match(matching_cred)
-            except Exception as e:
-                logger.error(
-                    f"Failed to create CredentialsMetaInput for field '{field_name}': "
-                    f"provider={matching_cred.provider}, type={matching_cred.type}, "
-                    f"credential_id={matching_cred.id}",
-                    exc_info=True,
-                )
-                provider = next(iter(field_info.provider), "unknown")
-                cred_type = next(iter(field_info.supported_types), "api_key")
-                missing.append(
-                    CredentialsMetaInput(
-                        id=field_name,
-                        provider=provider,  # type: ignore
-                        type=cred_type,  # type: ignore
-                        title=f"{field_name} (validation failed: {e})",
-                    )
-                )
-        else:
-            provider = next(iter(field_info.provider), "unknown")
-            cred_type = next(iter(field_info.supported_types), "api_key")
-            missing.append(
-                CredentialsMetaInput(
-                    id=field_name,
-                    provider=provider,  # type: ignore
-                    type=cred_type,  # type: ignore
-                    title=field_name.replace("_", " ").title(),
-                )
-            )
-
-    return matched, missing
-
-
-async def get_user_credentials(user_id: str) -> list[Credentials]:
-    """Get all available credentials for a user."""
-    creds_manager = IntegrationCredentialsManager()
-    return await creds_manager.store.get_all_creds(user_id)
-
-
-def find_matching_credential(
-    available_creds: list[Credentials],
-    field_info: CredentialsFieldInfo,
-) -> Credentials | None:
-    """Find a credential that matches the required provider, type, scopes, and host."""
-    for cred in available_creds:
-        if cred.provider not in field_info.provider:
-            continue
-        if cred.type not in field_info.supported_types:
-            continue
-        if cred.type == "oauth2" and not _credential_has_required_scopes(
-            cred, field_info
-        ):
-            continue
-        if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info):
-            continue
-        return cred
-    return None
-
-
-def create_credential_meta_from_match(
-    matching_cred: Credentials,
-) -> CredentialsMetaInput:
-    """Create a CredentialsMetaInput from a matched credential."""
-    return CredentialsMetaInput(
-        id=matching_cred.id,
-        provider=matching_cred.provider,  # type: ignore
-        type=matching_cred.type,
-        title=matching_cred.title,
-    )
-
-
 async def match_user_credentials_to_graph(
     user_id: str,
     graph: GraphModel,
@@ -338,7 +244,7 @@ async def match_user_credentials_to_graph(
     missing_creds: list[str] = []
 
     # Get aggregated credentials requirements from the graph
-    aggregated_creds = graph.aggregate_credentials_inputs()
+    aggregated_creds = graph.regular_credentials_inputs
     logger.debug(
         f"Matching credentials for graph {graph.id}: {len(aggregated_creds)} required"
     )
@@ -425,6 +331,8 @@ def _credential_has_required_scopes(
     # If no scopes are required, any credential matches
     if not requirements.required_scopes:
         return True
+
+    # Check that credential scopes are a superset of required scopes
     return set(credential.scopes).issuperset(requirements.required_scopes)
 
 

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

@@ -0,0 +1,78 @@
+"""Tests for chat tools utility functions."""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from backend.data.model import CredentialsFieldInfo
+
+
+def _make_regular_field() -> CredentialsFieldInfo:
+    return CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["github"],
+            "credentials_types": ["api_key"],
+            "is_auto_credential": False,
+        },
+        by_alias=True,
+    )
+
+
+def test_build_missing_credentials_excludes_auto_creds():
+    """
+    build_missing_credentials_from_graph() should use regular_credentials_inputs
+    and thus exclude auto_credentials from the "missing" set.
+    """
+    from backend.api.features.chat.tools.utils import (
+        build_missing_credentials_from_graph,
+    )
+
+    regular_field = _make_regular_field()
+
+    mock_graph = MagicMock()
+    # regular_credentials_inputs should only return the non-auto field
+    mock_graph.regular_credentials_inputs = {
+        "github_api_key": (regular_field, {("node-1", "credentials")}, True),
+    }
+
+    result = build_missing_credentials_from_graph(mock_graph, matched_credentials=None)
+
+    # Should include the regular credential
+    assert "github_api_key" in result
+    # Should NOT include the auto_credential (not in regular_credentials_inputs)
+    assert "google_oauth2" not in result
+
+
+@pytest.mark.asyncio
+async def test_match_user_credentials_excludes_auto_creds():
+    """
+    match_user_credentials_to_graph() should use regular_credentials_inputs
+    and thus exclude auto_credentials from matching.
+    """
+    from backend.api.features.chat.tools.utils import match_user_credentials_to_graph
+
+    regular_field = _make_regular_field()
+
+    mock_graph = MagicMock()
+    mock_graph.id = "test-graph"
+    # regular_credentials_inputs returns only non-auto fields
+    mock_graph.regular_credentials_inputs = {
+        "github_api_key": (regular_field, {("node-1", "credentials")}, True),
+    }
+
+    # Mock the credentials manager to return no credentials
+    with patch(
+        "backend.api.features.chat.tools.utils.IntegrationCredentialsManager"
+    ) as MockCredsMgr:
+        mock_store = AsyncMock()
+        mock_store.get_all_creds.return_value = []
+        MockCredsMgr.return_value.store = mock_store
+
+        matched, missing = await match_user_credentials_to_graph(
+            user_id="test-user", graph=mock_graph
+        )
+
+    # No credentials available, so github should be missing
+    assert len(matched) == 0
+    assert len(missing) == 1
+    assert "github_api_key" in missing[0]

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

@@ -1103,7 +1103,7 @@ async def create_preset_from_graph_execution(
             raise NotFoundError(
                 f"Graph #{graph_execution.graph_id} not found or accessible"
             )
-        elif len(graph.aggregate_credentials_inputs()) > 0:
+        elif len(graph.regular_credentials_inputs) > 0:
             raise ValueError(
                 f"Graph execution #{graph_exec_id} can't be turned into a preset "
                 "because it was run before this feature existed "

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

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

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

@@ -478,7 +478,7 @@ class ExaCreateOrFindWebsetBlock(Block):
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
         try:
-            webset = await aexa.websets.get(id=input_data.external_id)
+            webset = 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 = await aexa.websets.create(
+                webset = 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 = await aexa.websets.update(id=input_data.webset_id, params=payload)
+        sdk_webset = 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 = await aexa.websets.list(
+        response = 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 = await aexa.websets.get(id=input_data.webset_id)
+        sdk_webset = 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 = await aexa.websets.delete(id=input_data.webset_id)
+        deleted_webset = 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 = await aexa.websets.cancel(id=input_data.webset_id)
+        canceled_webset = 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 = await aexa.websets.preview(params=payload)
+        sdk_preview = 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 = await aexa.websets.get(id=input_data.webset_id)
+        webset = 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 = await aexa.websets.get(id=input_data.webset_id)
+        webset = 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 = await aexa.websets.items.list(
+            items_response = 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 = await aexa.websets.get(id=input_data.webset_id)
+        webset = 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 = await aexa.websets.enrichments.create(
+        sdk_enrichment = 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 = await aexa.websets.enrichments.get(
+                current_enrich = 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 = await aexa.websets.get(id=input_data.webset_id)
+                    webset = 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 = await aexa.websets.enrichments.get(
+        sdk_enrichment = 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 = await aexa.websets.enrichments.delete(
+        deleted_enrichment = 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 = await aexa.websets.enrichments.cancel(
+        canceled_enrichment = 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 = await aexa.websets.items.list(
+        items_response = 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 AsyncMock, MagicMock
+        from unittest.mock import 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=AsyncMock(return_value=mock_import))
+                    imports=MagicMock(create=lambda *args, **kwargs: mock_import)
                 )
             )
         }
@@ -294,7 +294,7 @@ class ExaCreateImportBlock(Block):
         if input_data.metadata:
             payload["metadata"] = input_data.metadata
 
-        sdk_import = await aexa.websets.imports.create(
+        sdk_import = 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 = await aexa.websets.imports.get(import_id=input_data.import_id)
+        sdk_import = 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 = await aexa.websets.imports.list(
+        response = aexa.websets.imports.list(
             cursor=input_data.cursor,
             limit=input_data.limit,
         )
@@ -474,9 +474,7 @@ class ExaDeleteImportBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_import = await aexa.websets.imports.delete(
+        deleted_import = aexa.websets.imports.delete(import_id=input_data.import_id)
-            import_id=input_data.import_id
-        )
 
         yield "import_id", deleted_import.id
         yield "success", "true"
@@ -575,14 +573,14 @@ class ExaExportWebsetBlock(Block):
             }
         )
 
-        # Create async iterator for list_all
+        # Create mock iterator
-        async def async_item_iterator(*args, **kwargs):
+        mock_items = [mock_item1, mock_item2]
-            for item in [mock_item1, mock_item2]:
-                yield item
 
         return {
             "_get_client": lambda *args, **kwargs: MagicMock(
-                websets=MagicMock(items=MagicMock(list_all=async_item_iterator))
+                websets=MagicMock(
+                    items=MagicMock(list_all=lambda *args, **kwargs: iter(mock_items))
+                )
             )
         }
 
@@ -604,7 +602,7 @@ class ExaExportWebsetBlock(Block):
                 webset_id=input_data.webset_id, limit=input_data.max_items
             )
 
-            async for sdk_item in item_iterator:
+            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 = await aexa.websets.items.get(
+        sdk_item = 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 = await aexa.websets.items.list(
+                response = 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 = await aexa.websets.items.list(
+                response = aexa.websets.items.list(
                     webset_id=input_data.webset_id,
                     cursor=input_data.cursor,
                     limit=input_data.limit,
                 )
         else:
-            response = await aexa.websets.items.list(
+            response = 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 = await aexa.websets.items.delete(
+        deleted_item = 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
         )
 
-        async for sdk_item in item_iterator:
+        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 = await aexa.websets.get(id=input_data.webset_id)
+        webset = 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 = await aexa.websets.items.list(
+            items_response = 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 = await aexa.websets.items.list(
+        response = 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 AsyncMock, MagicMock
+        from unittest.mock import 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=AsyncMock(return_value=mock_monitor))
+                    monitors=MagicMock(create=lambda *args, **kwargs: mock_monitor)
                 )
             )
         }
@@ -320,7 +320,7 @@ class ExaCreateMonitorBlock(Block):
         if input_data.metadata:
             payload["metadata"] = input_data.metadata
 
-        sdk_monitor = await aexa.websets.monitors.create(params=payload)
+        sdk_monitor = 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 = await aexa.websets.monitors.get(monitor_id=input_data.monitor_id)
+        sdk_monitor = 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 = await aexa.websets.monitors.update(
+        sdk_monitor = aexa.websets.monitors.update(
             monitor_id=input_data.monitor_id, params=payload
         )
 
@@ -522,9 +522,7 @@ class ExaDeleteMonitorBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        deleted_monitor = await aexa.websets.monitors.delete(
+        deleted_monitor = aexa.websets.monitors.delete(monitor_id=input_data.monitor_id)
-            monitor_id=input_data.monitor_id
-        )
 
         yield "monitor_id", deleted_monitor.id
         yield "success", "true"
@@ -581,7 +579,7 @@ class ExaListMonitorsBlock(Block):
         # Use AsyncExa SDK
         aexa = AsyncExa(api_key=credentials.api_key.get_secret_value())
 
-        response = await aexa.websets.monitors.list(
+        response = 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 = await aexa.websets.wait_until_idle(
+                final_webset = 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 = await aexa.websets.get(id=input_data.webset_id)
+                    webset = 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 = await aexa.websets.get(id=input_data.webset_id)
+                webset = 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 = await aexa.websets.searches.get(
+                search = 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 = await aexa.websets.searches.get(
+            search = 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 = await aexa.websets.enrichments.get(
+                enrichment = 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 = await aexa.websets.enrichments.get(
+            enrichment = 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 = await aexa.websets.items.list(webset_id=webset_id, limit=5)
+        response = 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 = await aexa.websets.searches.create(
+        sdk_search = 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 = await aexa.websets.searches.get(
+                current_search = 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 = await aexa.websets.searches.get(
+        sdk_search = 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 = await aexa.websets.searches.cancel(
+        canceled_search = 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 = await aexa.websets.get(id=input_data.webset_id)
+        webset = 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 = await aexa.websets.searches.create(
+            sdk_search = aexa.websets.searches.create(
                 webset_id=input_data.webset_id, params=payload
             )
 

autogpt_platform/backend/backend/blocks/llm.py

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

autogpt_platform/backend/backend/data/block.py

@@ -319,6 +319,8 @@ class BlockSchema(BaseModel):
                 "credentials_provider": [config.get("provider", "google")],
                 "credentials_types": [config.get("type", "oauth2")],
                 "credentials_scopes": config.get("scopes"),
+                "is_auto_credential": True,
+                "input_field_name": info["field_name"],
             }
             result[kwarg_name] = CredentialsFieldInfo.model_validate(
                 auto_schema, by_alias=True

autogpt_platform/backend/backend/data/execution.py

@@ -1,8 +1,9 @@
 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,
@@ -1199,16 +1200,12 @@ class NodeExecutionEntry(BaseModel):
 
 class ExecutionQueue(Generic[T]):
     """
-    Thread-safe queue for managing node execution within a single graph execution.
+    Queue for managing the execution of agents.
-
+    This will be shared between different processes
-    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):
-        # Thread-safe queue (not multiprocessing) — see class docstring
+        self.queue = Manager().Queue()
-        self.queue: queue.Queue[T] = queue.Queue()
 
     def add(self, execution: T) -> T:
         self.queue.put(execution)
@@ -1223,7 +1220,7 @@ class ExecutionQueue(Generic[T]):
     def get_or_none(self) -> T | None:
         try:
             return self.queue.get_nowait()
-        except queue.Empty:
+        except Empty:
             return None
 
 

autogpt_platform/backend/backend/data/execution_queue_test.py

@@ -1,58 +0,0 @@
-"""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

@@ -447,8 +447,7 @@ class GraphModel(Graph, GraphMeta):
     @computed_field
     @property
     def credentials_input_schema(self) -> dict[str, Any]:
-        graph_credentials_inputs = self.aggregate_credentials_inputs()
+        graph_credentials_inputs = self.regular_credentials_inputs
-
         logger.debug(
             f"Combined credentials input fields for graph #{self.id} ({self.name}): "
             f"{graph_credentials_inputs}"
@@ -604,6 +603,28 @@ class GraphModel(Graph, GraphMeta):
             for key, (field_info, node_field_pairs) in combined.items()
         }
 
+    @property
+    def regular_credentials_inputs(
+        self,
+    ) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]], bool]]:
+        """Credentials that need explicit user mapping (CredentialsMetaInput fields)."""
+        return {
+            k: v
+            for k, v in self.aggregate_credentials_inputs().items()
+            if not v[0].is_auto_credential
+        }
+
+    @property
+    def auto_credentials_inputs(
+        self,
+    ) -> dict[str, tuple[CredentialsFieldInfo, set[tuple[str, str]], bool]]:
+        """Credentials embedded in file fields (_credentials_id), resolved at execution time."""
+        return {
+            k: v
+            for k, v in self.aggregate_credentials_inputs().items()
+            if v[0].is_auto_credential
+        }
+
     def reassign_ids(self, user_id: str, reassign_graph_id: bool = False):
         """
         Reassigns all IDs in the graph to new UUIDs.
@@ -654,6 +675,16 @@ class GraphModel(Graph, GraphMeta):
             ) and graph_id in graph_id_map:
                 node.input_default["graph_id"] = graph_id_map[graph_id]
 
+        # Clear auto-credentials references (e.g., _credentials_id in
+        # GoogleDriveFile fields) so the new user must re-authenticate
+        # with their own account
+        for node in graph.nodes:
+            if not node.input_default:
+                continue
+            for key, value in node.input_default.items():
+                if isinstance(value, dict) and "_credentials_id" in value:
+                    del value["_credentials_id"]
+
     def validate_graph(
         self,
         for_run: bool = False,

autogpt_platform/backend/backend/data/graph_test.py

@@ -463,3 +463,329 @@ def test_node_credentials_optional_with_other_metadata():
     assert node.credentials_optional is True
     assert node.metadata["position"] == {"x": 100, "y": 200}
     assert node.metadata["customized_name"] == "My Custom Node"
+
+
+# ============================================================================
+# Tests for CredentialsFieldInfo.combine() field propagation
+def test_combine_preserves_is_auto_credential_flag():
+    """
+    CredentialsFieldInfo.combine() must propagate is_auto_credential and
+    input_field_name to the combined result. Regression test for reviewer
+    finding that combine() dropped these fields.
+    """
+    from backend.data.model import CredentialsFieldInfo
+
+    auto_field = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["google"],
+            "credentials_types": ["oauth2"],
+            "credentials_scopes": ["drive.readonly"],
+            "is_auto_credential": True,
+            "input_field_name": "spreadsheet",
+        },
+        by_alias=True,
+    )
+
+    # combine() takes *args of (field_info, key) tuples
+    combined = CredentialsFieldInfo.combine(
+        (auto_field, ("node-1", "credentials")),
+        (auto_field, ("node-2", "credentials")),
+    )
+
+    assert len(combined) == 1
+    group_key = next(iter(combined))
+    combined_info, combined_keys = combined[group_key]
+
+    assert combined_info.is_auto_credential is True
+    assert combined_info.input_field_name == "spreadsheet"
+    assert combined_keys == {("node-1", "credentials"), ("node-2", "credentials")}
+
+
+def test_combine_preserves_regular_credential_defaults():
+    """Regular credentials should have is_auto_credential=False after combine()."""
+    from backend.data.model import CredentialsFieldInfo
+
+    regular_field = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["github"],
+            "credentials_types": ["api_key"],
+            "is_auto_credential": False,
+        },
+        by_alias=True,
+    )
+
+    combined = CredentialsFieldInfo.combine(
+        (regular_field, ("node-1", "credentials")),
+    )
+
+    group_key = next(iter(combined))
+    combined_info, _ = combined[group_key]
+
+    assert combined_info.is_auto_credential is False
+    assert combined_info.input_field_name is None
+
+
+# ============================================================================
+# Tests for _reassign_ids credential clearing (Fix 3: SECRT-1772)
+
+
+def test_reassign_ids_clears_credentials_id():
+    """
+    [SECRT-1772] _reassign_ids should clear _credentials_id from
+    GoogleDriveFile-style input_default fields so forked agents
+    don't retain the original creator's credential references.
+    """
+    from backend.data.graph import GraphModel
+
+    node = Node(
+        id="node-1",
+        block_id=StoreValueBlock().id,
+        input_default={
+            "spreadsheet": {
+                "_credentials_id": "original-cred-id",
+                "id": "file-123",
+                "name": "test.xlsx",
+                "mimeType": "application/vnd.google-apps.spreadsheet",
+                "url": "https://docs.google.com/spreadsheets/d/file-123",
+            },
+        },
+    )
+
+    graph = Graph(
+        id="test-graph",
+        name="Test",
+        description="Test",
+        nodes=[node],
+        links=[],
+    )
+
+    GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
+
+    # _credentials_id key should be removed (not set to None) so that
+    # _acquire_auto_credentials correctly errors instead of treating it as chained data
+    assert "_credentials_id" not in graph.nodes[0].input_default["spreadsheet"]
+
+
+def test_reassign_ids_preserves_non_credential_fields():
+    """
+    Regression guard: _reassign_ids should NOT modify non-credential fields
+    like name, mimeType, id, url.
+    """
+    from backend.data.graph import GraphModel
+
+    node = Node(
+        id="node-1",
+        block_id=StoreValueBlock().id,
+        input_default={
+            "spreadsheet": {
+                "_credentials_id": "cred-abc",
+                "id": "file-123",
+                "name": "test.xlsx",
+                "mimeType": "application/vnd.google-apps.spreadsheet",
+                "url": "https://docs.google.com/spreadsheets/d/file-123",
+            },
+        },
+    )
+
+    graph = Graph(
+        id="test-graph",
+        name="Test",
+        description="Test",
+        nodes=[node],
+        links=[],
+    )
+
+    GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
+
+    field = graph.nodes[0].input_default["spreadsheet"]
+    assert field["id"] == "file-123"
+    assert field["name"] == "test.xlsx"
+    assert field["mimeType"] == "application/vnd.google-apps.spreadsheet"
+    assert field["url"] == "https://docs.google.com/spreadsheets/d/file-123"
+
+
+def test_reassign_ids_handles_no_credentials():
+    """
+    Regression guard: _reassign_ids should not error when input_default
+    has no dict fields with _credentials_id.
+    """
+    from backend.data.graph import GraphModel
+
+    node = Node(
+        id="node-1",
+        block_id=StoreValueBlock().id,
+        input_default={
+            "input": "some value",
+            "another_input": 42,
+        },
+    )
+
+    graph = Graph(
+        id="test-graph",
+        name="Test",
+        description="Test",
+        nodes=[node],
+        links=[],
+    )
+
+    GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
+
+    # Should not error, fields unchanged
+    assert graph.nodes[0].input_default["input"] == "some value"
+    assert graph.nodes[0].input_default["another_input"] == 42
+
+
+def test_reassign_ids_handles_multiple_credential_fields():
+    """
+    [SECRT-1772] When a node has multiple dict fields with _credentials_id,
+    ALL of them should be cleared.
+    """
+    from backend.data.graph import GraphModel
+
+    node = Node(
+        id="node-1",
+        block_id=StoreValueBlock().id,
+        input_default={
+            "spreadsheet": {
+                "_credentials_id": "cred-1",
+                "id": "file-1",
+                "name": "file1.xlsx",
+            },
+            "doc_file": {
+                "_credentials_id": "cred-2",
+                "id": "file-2",
+                "name": "file2.docx",
+            },
+            "plain_input": "not a dict",
+        },
+    )
+
+    graph = Graph(
+        id="test-graph",
+        name="Test",
+        description="Test",
+        nodes=[node],
+        links=[],
+    )
+
+    GraphModel._reassign_ids(graph, user_id="new-user", graph_id_map={})
+
+    assert "_credentials_id" not in graph.nodes[0].input_default["spreadsheet"]
+    assert "_credentials_id" not in graph.nodes[0].input_default["doc_file"]
+    assert graph.nodes[0].input_default["plain_input"] == "not a dict"
+
+
+# ============================================================================
+# Tests for discriminate() field propagation
+def test_discriminate_preserves_is_auto_credential_flag():
+    """
+    CredentialsFieldInfo.discriminate() must propagate is_auto_credential and
+    input_field_name to the discriminated result. Regression test for
+    discriminate() dropping these fields (same class of bug as combine()).
+    """
+    from backend.data.model import CredentialsFieldInfo
+
+    auto_field = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["google", "openai"],
+            "credentials_types": ["oauth2"],
+            "credentials_scopes": ["drive.readonly"],
+            "is_auto_credential": True,
+            "input_field_name": "spreadsheet",
+            "discriminator": "model",
+            "discriminator_mapping": {"gpt-4": "openai", "gemini": "google"},
+        },
+        by_alias=True,
+    )
+
+    discriminated = auto_field.discriminate("gemini")
+
+    assert discriminated.is_auto_credential is True
+    assert discriminated.input_field_name == "spreadsheet"
+    assert discriminated.provider == frozenset(["google"])
+
+
+def test_discriminate_preserves_regular_credential_defaults():
+    """Regular credentials should have is_auto_credential=False after discriminate()."""
+    from backend.data.model import CredentialsFieldInfo
+
+    regular_field = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["google", "openai"],
+            "credentials_types": ["api_key"],
+            "is_auto_credential": False,
+            "discriminator": "model",
+            "discriminator_mapping": {"gpt-4": "openai", "gemini": "google"},
+        },
+        by_alias=True,
+    )
+
+    discriminated = regular_field.discriminate("gpt-4")
+
+    assert discriminated.is_auto_credential is False
+    assert discriminated.input_field_name is None
+    assert discriminated.provider == frozenset(["openai"])
+
+
+# ============================================================================
+# Tests for credentials_input_schema excluding auto_credentials
+def test_credentials_input_schema_excludes_auto_creds():
+    """
+    GraphModel.credentials_input_schema should exclude auto_credentials
+    (is_auto_credential=True) from the schema. Auto_credentials are
+    transparently resolved at execution time via file picker data.
+    """
+    from datetime import datetime, timezone
+    from unittest.mock import PropertyMock, patch
+
+    from backend.data.graph import GraphModel, NodeModel
+    from backend.data.model import CredentialsFieldInfo
+
+    regular_field_info = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["github"],
+            "credentials_types": ["api_key"],
+            "is_auto_credential": False,
+        },
+        by_alias=True,
+    )
+
+    graph = GraphModel(
+        id="test-graph",
+        version=1,
+        name="Test",
+        description="Test",
+        user_id="test-user",
+        created_at=datetime.now(timezone.utc),
+        nodes=[
+            NodeModel(
+                id="node-1",
+                block_id=StoreValueBlock().id,
+                input_default={},
+                graph_id="test-graph",
+                graph_version=1,
+            ),
+        ],
+        links=[],
+    )
+
+    # Mock regular_credentials_inputs to return only the non-auto field (3-tuple)
+    regular_only = {
+        "github_credentials": (
+            regular_field_info,
+            {("node-1", "credentials")},
+            True,
+        ),
+    }
+
+    with patch.object(
+        type(graph),
+        "regular_credentials_inputs",
+        new_callable=PropertyMock,
+        return_value=regular_only,
+    ):
+        schema = graph.credentials_input_schema
+        field_names = set(schema.get("properties", {}).keys())
+        # Should include regular credential but NOT auto_credential
+        assert "github_credentials" in field_names
+        assert "google_credentials" not in field_names

autogpt_platform/backend/backend/data/model.py

@@ -571,6 +571,8 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
     discriminator: Optional[str] = None
     discriminator_mapping: Optional[dict[str, CP]] = None
     discriminator_values: set[Any] = Field(default_factory=set)
+    is_auto_credential: bool = False
+    input_field_name: Optional[str] = None
 
     @classmethod
     def combine(
@@ -651,6 +653,9 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
                 + "_credentials"
             )
 
+            # Propagate is_auto_credential from the combined field.
+            # All fields in a group should share the same is_auto_credential
+            # value since auto and regular credentials serve different purposes.
             result[group_key] = (
                 CredentialsFieldInfo[CP, CT](
                     credentials_provider=combined.provider,
@@ -659,6 +664,8 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
                     discriminator=combined.discriminator,
                     discriminator_mapping=combined.discriminator_mapping,
                     discriminator_values=set(all_discriminator_values),
+                    is_auto_credential=combined.is_auto_credential,
+                    input_field_name=combined.input_field_name,
                 ),
                 combined_keys,
             )
@@ -684,6 +691,8 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
             discriminator=self.discriminator,
             discriminator_mapping=self.discriminator_mapping,
             discriminator_values=self.discriminator_values,
+            is_auto_credential=self.is_auto_credential,
+            input_field_name=self.input_field_name,
         )
 
 

autogpt_platform/backend/backend/data/rabbitmq.py

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

autogpt_platform/backend/backend/executor/manager.py

@@ -92,6 +92,7 @@ from .utils import (
     block_usage_cost,
     create_execution_queue_config,
     execution_usage_cost,
+    parse_auto_credential_field,
     validate_exec,
 )
 
@@ -172,6 +173,60 @@ def execute_graph(
 T = TypeVar("T")
 
 
+async def _acquire_auto_credentials(
+    input_model: type[BlockSchema],
+    input_data: dict[str, Any],
+    creds_manager: "IntegrationCredentialsManager",
+    user_id: str,
+) -> tuple[dict[str, Any], list[AsyncRedisLock]]:
+    """
+    Resolve auto_credentials from GoogleDriveFileField-style inputs.
+
+    Returns:
+        (extra_exec_kwargs, locks): kwargs to inject into block execution, and
+        credential locks to release after execution completes.
+    """
+    extra_exec_kwargs: dict[str, Any] = {}
+    locks: list[AsyncRedisLock] = []
+
+    # NOTE: If a block ever has multiple auto-credential fields, a ValueError
+    # on a later field will strand locks acquired for earlier fields. They'll
+    # auto-expire via Redis TTL, but add a try/except to release partial locks
+    # if that becomes a real scenario.
+    for kwarg_name, info in input_model.get_auto_credentials_fields().items():
+        field_name = info["field_name"]
+        field_data = input_data.get(field_name)
+
+        parsed = parse_auto_credential_field(
+            field_name=field_name,
+            info=info,
+            field_data=field_data,
+            field_present_in_input=field_name in input_data,
+        )
+
+        if parsed.error:
+            raise ValueError(parsed.error)
+
+        if parsed.cred_id:
+            # Credential ID provided - acquire credentials
+            try:
+                credentials, lock = await creds_manager.acquire(user_id, parsed.cred_id)
+                locks.append(lock)
+                extra_exec_kwargs[kwarg_name] = credentials
+            except ValueError:
+                raise ValueError(
+                    f"{parsed.provider.capitalize()} credentials for "
+                    f"'{parsed.file_name}' in field '{parsed.field_name}' are not "
+                    f"available in your account. "
+                    f"This can happen if the agent was created by another "
+                    f"user or the credentials were deleted. "
+                    f"Please open the agent in the builder and re-select "
+                    f"the file to authenticate with your own account."
+                )
+
+    return extra_exec_kwargs, locks
+
+
 async def execute_node(
     node: Node,
     data: NodeExecutionEntry,
@@ -271,41 +326,14 @@ async def execute_node(
         extra_exec_kwargs[field_name] = credentials
 
     # Handle auto-generated credentials (e.g., from GoogleDriveFileInput)
-    for kwarg_name, info in input_model.get_auto_credentials_fields().items():
+    auto_extra_kwargs, auto_locks = await _acquire_auto_credentials(
-        field_name = info["field_name"]
+        input_model=input_model,
-        field_data = input_data.get(field_name)
+        input_data=input_data,
-        if field_data and isinstance(field_data, dict):
+        creds_manager=creds_manager,
-            # Check if _credentials_id key exists in the field data
+        user_id=user_id,
-            if "_credentials_id" in field_data:
+    )
-                cred_id = field_data["_credentials_id"]
+    extra_exec_kwargs.update(auto_extra_kwargs)
-                if cred_id:
+    creds_locks.extend(auto_locks)
-                    # Credential ID provided - acquire credentials
-                    provider = info.get("config", {}).get(
-                        "provider", "external service"
-                    )
-                    file_name = field_data.get("name", "selected file")
-                    try:
-                        credentials, lock = await creds_manager.acquire(
-                            user_id, cred_id
-                        )
-                        creds_locks.append(lock)
-                        extra_exec_kwargs[kwarg_name] = credentials
-                    except ValueError:
-                        # Credential was deleted or doesn't exist
-                        raise ValueError(
-                            f"Authentication expired for '{file_name}' in field '{field_name}'. "
-                            f"The saved {provider.capitalize()} credentials no longer exist. "
-                            f"Please re-select the file to re-authenticate."
-                        )
-                # else: _credentials_id is explicitly None, skip credentials (for chained data)
-            else:
-                # _credentials_id key missing entirely - this is an error
-                provider = info.get("config", {}).get("provider", "external service")
-                file_name = field_data.get("name", "selected file")
-                raise ValueError(
-                    f"Authentication missing for '{file_name}' in field '{field_name}'. "
-                    f"Please re-select the file to authenticate with {provider.capitalize()}."
-                )
 
     output_size = 0
 

autogpt_platform/backend/backend/executor/manager_auto_credentials_test.py

@@ -0,0 +1,320 @@
+"""
+Tests for auto_credentials handling in execute_node().
+
+These test the _acquire_auto_credentials() helper function extracted from
+execute_node() (manager.py lines 273-308).
+"""
+
+import pytest
+from pytest_mock import MockerFixture
+
+
+@pytest.fixture
+def google_drive_file_data():
+    return {
+        "valid": {
+            "_credentials_id": "cred-id-123",
+            "id": "file-123",
+            "name": "test.xlsx",
+            "mimeType": "application/vnd.google-apps.spreadsheet",
+        },
+        "chained": {
+            "_credentials_id": None,
+            "id": "file-456",
+            "name": "chained.xlsx",
+            "mimeType": "application/vnd.google-apps.spreadsheet",
+        },
+        "missing_key": {
+            "id": "file-789",
+            "name": "bad.xlsx",
+            "mimeType": "application/vnd.google-apps.spreadsheet",
+        },
+    }
+
+
+@pytest.fixture
+def mock_input_model(mocker: MockerFixture):
+    """Create a mock input model with get_auto_credentials_fields() returning one field."""
+    input_model = mocker.MagicMock()
+    input_model.get_auto_credentials_fields.return_value = {
+        "credentials": {
+            "field_name": "spreadsheet",
+            "config": {
+                "provider": "google",
+                "type": "oauth2",
+                "scopes": ["https://www.googleapis.com/auth/drive.readonly"],
+            },
+        }
+    }
+    return input_model
+
+
+@pytest.fixture
+def mock_creds_manager(mocker: MockerFixture):
+    manager = mocker.AsyncMock()
+    mock_lock = mocker.AsyncMock()
+    mock_creds = mocker.MagicMock()
+    mock_creds.id = "cred-id-123"
+    mock_creds.provider = "google"
+    manager.acquire.return_value = (mock_creds, mock_lock)
+    return manager, mock_creds, mock_lock
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_happy_path(
+    mocker: MockerFixture,
+    google_drive_file_data,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """When field_data has a valid _credentials_id, credentials should be acquired."""
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, mock_creds, mock_lock = mock_creds_manager
+    input_data = {"spreadsheet": google_drive_file_data["valid"]}
+
+    extra_kwargs, locks = await _acquire_auto_credentials(
+        input_model=mock_input_model,
+        input_data=input_data,
+        creds_manager=manager,
+        user_id="user-1",
+    )
+
+    manager.acquire.assert_called_once_with("user-1", "cred-id-123")
+    assert extra_kwargs["credentials"] == mock_creds
+    assert mock_lock in locks
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_field_none_static_raises(
+    mocker: MockerFixture,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """
+    [THE BUG FIX TEST — OPEN-2895]
+    When field_data is None and the key IS in input_data (user didn't select a file),
+    should raise ValueError instead of silently skipping.
+    """
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, _, _ = mock_creds_manager
+    # Key is present but value is None = user didn't select a file
+    input_data = {"spreadsheet": None}
+
+    with pytest.raises(ValueError, match="No file selected"):
+        await _acquire_auto_credentials(
+            input_model=mock_input_model,
+            input_data=input_data,
+            creds_manager=manager,
+            user_id="user-1",
+        )
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_field_absent_skips(
+    mocker: MockerFixture,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """
+    When the field key is NOT in input_data at all (upstream connection),
+    should skip without error.
+    """
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, _, _ = mock_creds_manager
+    # Key not present = connected from upstream block
+    input_data = {}
+
+    extra_kwargs, locks = await _acquire_auto_credentials(
+        input_model=mock_input_model,
+        input_data=input_data,
+        creds_manager=manager,
+        user_id="user-1",
+    )
+
+    manager.acquire.assert_not_called()
+    assert "credentials" not in extra_kwargs
+    assert locks == []
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_chained_cred_id_none(
+    mocker: MockerFixture,
+    google_drive_file_data,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """
+    When _credentials_id is explicitly None (chained data from upstream),
+    should skip credential acquisition.
+    """
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, _, _ = mock_creds_manager
+    input_data = {"spreadsheet": google_drive_file_data["chained"]}
+
+    extra_kwargs, locks = await _acquire_auto_credentials(
+        input_model=mock_input_model,
+        input_data=input_data,
+        creds_manager=manager,
+        user_id="user-1",
+    )
+
+    manager.acquire.assert_not_called()
+    assert "credentials" not in extra_kwargs
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_missing_cred_id_key_raises(
+    mocker: MockerFixture,
+    google_drive_file_data,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """
+    When _credentials_id key is missing entirely from field_data dict,
+    should raise ValueError.
+    """
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, _, _ = mock_creds_manager
+    input_data = {"spreadsheet": google_drive_file_data["missing_key"]}
+
+    with pytest.raises(ValueError, match="Authentication missing"):
+        await _acquire_auto_credentials(
+            input_model=mock_input_model,
+            input_data=input_data,
+            creds_manager=manager,
+            user_id="user-1",
+        )
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_ownership_mismatch_error(
+    mocker: MockerFixture,
+    google_drive_file_data,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """
+    [SECRT-1772] When acquire() raises ValueError (credential belongs to another user),
+    the error message should mention 'not available' (not 'expired').
+    """
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, _, _ = mock_creds_manager
+    manager.acquire.side_effect = ValueError(
+        "Credentials #cred-id-123 for user #user-2 not found"
+    )
+    input_data = {"spreadsheet": google_drive_file_data["valid"]}
+
+    with pytest.raises(ValueError, match="not available in your account"):
+        await _acquire_auto_credentials(
+            input_model=mock_input_model,
+            input_data=input_data,
+            creds_manager=manager,
+            user_id="user-2",
+        )
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_deleted_credential_error(
+    mocker: MockerFixture,
+    google_drive_file_data,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """
+    [SECRT-1772] When acquire() raises ValueError (credential was deleted),
+    the error message should mention 'not available' (not 'expired').
+    """
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, _, _ = mock_creds_manager
+    manager.acquire.side_effect = ValueError(
+        "Credentials #cred-id-123 for user #user-1 not found"
+    )
+    input_data = {"spreadsheet": google_drive_file_data["valid"]}
+
+    with pytest.raises(ValueError, match="not available in your account"):
+        await _acquire_auto_credentials(
+            input_model=mock_input_model,
+            input_data=input_data,
+            creds_manager=manager,
+            user_id="user-1",
+        )
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_lock_appended(
+    mocker: MockerFixture,
+    google_drive_file_data,
+    mock_input_model,
+    mock_creds_manager,
+):
+    """Lock from acquire() should be included in returned locks list."""
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, _, mock_lock = mock_creds_manager
+    input_data = {"spreadsheet": google_drive_file_data["valid"]}
+
+    extra_kwargs, locks = await _acquire_auto_credentials(
+        input_model=mock_input_model,
+        input_data=input_data,
+        creds_manager=manager,
+        user_id="user-1",
+    )
+
+    assert len(locks) == 1
+    assert locks[0] is mock_lock
+
+
+@pytest.mark.asyncio
+async def test_auto_credentials_multiple_fields(
+    mocker: MockerFixture,
+    mock_creds_manager,
+):
+    """When there are multiple auto_credentials fields, only valid ones should acquire."""
+    from backend.executor.manager import _acquire_auto_credentials
+
+    manager, mock_creds, mock_lock = mock_creds_manager
+
+    input_model = mocker.MagicMock()
+    input_model.get_auto_credentials_fields.return_value = {
+        "credentials": {
+            "field_name": "spreadsheet",
+            "config": {"provider": "google", "type": "oauth2"},
+        },
+        "credentials2": {
+            "field_name": "doc_file",
+            "config": {"provider": "google", "type": "oauth2"},
+        },
+    }
+
+    input_data = {
+        "spreadsheet": {
+            "_credentials_id": "cred-id-123",
+            "id": "file-1",
+            "name": "file1.xlsx",
+        },
+        "doc_file": {
+            "_credentials_id": None,
+            "id": "file-2",
+            "name": "chained.doc",
+        },
+    }
+
+    extra_kwargs, locks = await _acquire_auto_credentials(
+        input_model=input_model,
+        input_data=input_data,
+        creds_manager=manager,
+        user_id="user-1",
+    )
+
+    # Only the first field should have acquired credentials
+    manager.acquire.assert_called_once_with("user-1", "cred-id-123")
+    assert "credentials" in extra_kwargs
+    assert "credentials2" not in extra_kwargs
+    assert len(locks) == 1

autogpt_platform/backend/backend/executor/utils.py

@@ -4,7 +4,7 @@ import threading
 import time
 from collections import defaultdict
 from concurrent.futures import Future
-from typing import Mapping, Optional, cast
+from typing import Any, Mapping, Optional, cast
 
 from pydantic import BaseModel, JsonValue, ValidationError
 
@@ -55,6 +55,87 @@ from backend.util.type import convert
 config = Config()
 logger = TruncatedLogger(logging.getLogger(__name__), prefix="[GraphExecutorUtil]")
 
+# ============ Auto-Credentials Helpers ============ #
+
+
+class AutoCredentialFieldInfo(BaseModel):
+    """Parsed info from an auto-credential field (e.g., GoogleDriveFileField)."""
+
+    cred_id: str | None
+    """The credential ID to use, or None if not provided."""
+    provider: str
+    """The provider name (e.g., 'google')."""
+    file_name: str
+    """The display name for error messages."""
+    field_name: str
+    """The original field name in the schema."""
+    error: str | None = None
+    """Validation error message, if any."""
+
+
+def parse_auto_credential_field(
+    field_name: str,
+    info: dict,
+    field_data: Any,
+    *,
+    field_present_in_input: bool = True,
+) -> AutoCredentialFieldInfo:
+    """
+    Parse auto-credential field data and extract credential info.
+
+    This is shared logic used by both credential acquisition (manager.py)
+    and credential validation (utils.py).
+
+    Args:
+        field_name: The name of the field in the schema
+        info: The auto_credentials field info from get_auto_credentials_fields()
+        field_data: The actual field data from input
+        field_present_in_input: Whether the field key exists in input_data
+
+    Returns:
+        AutoCredentialFieldInfo with parsed data and any validation errors
+    """
+    provider = info.get("config", {}).get("provider", "external service")
+    file_name = (
+        field_data.get("name", "selected file")
+        if isinstance(field_data, dict)
+        else "selected file"
+    )
+
+    result = AutoCredentialFieldInfo(
+        cred_id=None,
+        provider=provider,
+        file_name=file_name,
+        field_name=field_name,
+    )
+
+    if field_data and isinstance(field_data, dict):
+        if "_credentials_id" not in field_data:
+            # Key removed (e.g., on fork) — needs re-auth
+            result.error = (
+                f"Authentication missing for '{file_name}' in field "
+                f"'{field_name}'. Please re-select the file to authenticate "
+                f"with {provider.capitalize()}."
+            )
+        else:
+            cred_id = field_data.get("_credentials_id")
+            if cred_id:
+                result.cred_id = cred_id
+            # else: _credentials_id is explicitly None, skip (chained data)
+    elif field_data is None and not field_present_in_input:
+        # Field not in input_data at all = connected from upstream block, skip
+        pass
+    elif field_present_in_input:
+        # field_data is None/empty but key IS in input_data = user didn't select
+        result.error = (
+            f"No file selected for '{field_name}'. "
+            f"Please select a file to provide "
+            f"{provider.capitalize()} authentication."
+        )
+
+    return result
+
+
 # ============ Resource Helpers ============ #
 
 
@@ -259,7 +340,8 @@ async def _validate_node_input_credentials(
 
         # Find any fields of type CredentialsMetaInput
         credentials_fields = block.input_schema.get_credentials_fields()
-        if not credentials_fields:
+        auto_credentials_fields = block.input_schema.get_auto_credentials_fields()
+        if not credentials_fields and not auto_credentials_fields:
             continue
 
         # Track if any credential field is missing for this node
@@ -339,6 +421,52 @@ async def _validate_node_input_credentials(
                 ] = "Invalid credentials: type/provider mismatch"
                 continue
 
+        # Validate auto-credentials (GoogleDriveFileField-based)
+        # These have _credentials_id embedded in the file field data
+        if auto_credentials_fields:
+            for _kwarg_name, info in auto_credentials_fields.items():
+                field_name = info["field_name"]
+                # Check input_default and nodes_input_masks for the field value
+                field_value = node.input_default.get(field_name)
+                if nodes_input_masks and node.id in nodes_input_masks:
+                    field_value = nodes_input_masks[node.id].get(
+                        field_name, field_value
+                    )
+
+                # Use shared helper to parse the field
+                parsed = parse_auto_credential_field(
+                    field_name=field_name,
+                    info=info,
+                    field_data=field_value,
+                    field_present_in_input=True,  # For validation, assume present
+                )
+
+                if parsed.error:
+                    has_missing_credentials = True
+                    credential_errors[node.id][field_name] = parsed.error
+                    continue
+
+                if parsed.cred_id:
+                    # Validate that credentials exist and are accessible
+                    try:
+                        creds_store = get_integration_credentials_store()
+                        creds = await creds_store.get_creds_by_id(
+                            user_id, parsed.cred_id
+                        )
+                    except Exception as e:
+                        has_missing_credentials = True
+                        credential_errors[node.id][
+                            field_name
+                        ] = f"Credentials not available: {e}"
+                        continue
+                    if not creds:
+                        has_missing_credentials = True
+                        credential_errors[node.id][field_name] = (
+                            "The saved credentials are not available "
+                            "for your account. Please re-select the file to "
+                            "authenticate with your own account."
+                        )
+
         # If node has optional credentials and any are missing, mark for skipping
         # But only if there are no other errors for this node
         if (
@@ -370,8 +498,9 @@ def make_node_credentials_input_map(
     """
     result: dict[str, dict[str, JsonValue]] = {}
 
-    # Get aggregated credentials fields for the graph
+    # Only map regular credentials (not auto_credentials, which are resolved
-    graph_cred_inputs = graph.aggregate_credentials_inputs()
+    # at execution time from _credentials_id in file field data)
+    graph_cred_inputs = graph.regular_credentials_inputs
 
     for graph_input_name, (_, compatible_node_fields, _) in graph_cred_inputs.items():
         # Best-effort map: skip missing items

autogpt_platform/backend/backend/executor/utils_test.py

@@ -907,3 +907,335 @@ async def test_stop_graph_execution_cascades_to_child_with_reviews(
 
     # Verify both parent and child status updates
     assert mock_execution_db.update_graph_execution_stats.call_count >= 1
+
+
+# ============================================================================
+# Tests for auto_credentials validation in _validate_node_input_credentials
+# (Fix 3: SECRT-1772 + Fix 4: Path 4)
+# ============================================================================
+
+
+@pytest.mark.asyncio
+async def test_validate_node_input_credentials_auto_creds_valid(
+    mocker: MockerFixture,
+):
+    """
+    [SECRT-1772] When a node has auto_credentials with a valid _credentials_id
+    that exists in the store, validation should pass without errors.
+    """
+    from backend.executor.utils import _validate_node_input_credentials
+
+    mock_node = mocker.MagicMock()
+    mock_node.id = "node-with-auto-creds"
+    mock_node.credentials_optional = False
+    mock_node.input_default = {
+        "spreadsheet": {
+            "_credentials_id": "valid-cred-id",
+            "id": "file-123",
+            "name": "test.xlsx",
+        }
+    }
+
+    mock_block = mocker.MagicMock()
+    # No regular credentials fields
+    mock_block.input_schema.get_credentials_fields.return_value = {}
+    # Has auto_credentials fields
+    mock_block.input_schema.get_auto_credentials_fields.return_value = {
+        "credentials": {
+            "field_name": "spreadsheet",
+            "config": {"provider": "google", "type": "oauth2"},
+        }
+    }
+    mock_node.block = mock_block
+
+    mock_graph = mocker.MagicMock()
+    mock_graph.nodes = [mock_node]
+
+    # Mock the credentials store to return valid credentials
+    mock_store = mocker.MagicMock()
+    mock_creds = mocker.MagicMock()
+    mock_creds.id = "valid-cred-id"
+    mock_store.get_creds_by_id = mocker.AsyncMock(return_value=mock_creds)
+    mocker.patch(
+        "backend.executor.utils.get_integration_credentials_store",
+        return_value=mock_store,
+    )
+
+    errors, nodes_to_skip = await _validate_node_input_credentials(
+        graph=mock_graph,
+        user_id="test-user",
+        nodes_input_masks=None,
+    )
+
+    assert mock_node.id not in errors
+    assert mock_node.id not in nodes_to_skip
+
+
+@pytest.mark.asyncio
+async def test_validate_node_input_credentials_auto_creds_missing(
+    mocker: MockerFixture,
+):
+    """
+    [SECRT-1772] When a node has auto_credentials with a _credentials_id
+    that doesn't exist for the current user, validation should report an error.
+    """
+    from backend.executor.utils import _validate_node_input_credentials
+
+    mock_node = mocker.MagicMock()
+    mock_node.id = "node-with-bad-auto-creds"
+    mock_node.credentials_optional = False
+    mock_node.input_default = {
+        "spreadsheet": {
+            "_credentials_id": "other-users-cred-id",
+            "id": "file-123",
+            "name": "test.xlsx",
+        }
+    }
+
+    mock_block = mocker.MagicMock()
+    mock_block.input_schema.get_credentials_fields.return_value = {}
+    mock_block.input_schema.get_auto_credentials_fields.return_value = {
+        "credentials": {
+            "field_name": "spreadsheet",
+            "config": {"provider": "google", "type": "oauth2"},
+        }
+    }
+    mock_node.block = mock_block
+
+    mock_graph = mocker.MagicMock()
+    mock_graph.nodes = [mock_node]
+
+    # Mock the credentials store to return None (cred not found for this user)
+    mock_store = mocker.MagicMock()
+    mock_store.get_creds_by_id = mocker.AsyncMock(return_value=None)
+    mocker.patch(
+        "backend.executor.utils.get_integration_credentials_store",
+        return_value=mock_store,
+    )
+
+    errors, nodes_to_skip = await _validate_node_input_credentials(
+        graph=mock_graph,
+        user_id="different-user",
+        nodes_input_masks=None,
+    )
+
+    assert mock_node.id in errors
+    assert "spreadsheet" in errors[mock_node.id]
+    assert "not available" in errors[mock_node.id]["spreadsheet"].lower()
+
+
+@pytest.mark.asyncio
+async def test_validate_node_input_credentials_both_regular_and_auto(
+    mocker: MockerFixture,
+):
+    """
+    [SECRT-1772] A node that has BOTH regular credentials AND auto_credentials
+    should have both validated.
+    """
+    from backend.executor.utils import _validate_node_input_credentials
+
+    mock_node = mocker.MagicMock()
+    mock_node.id = "node-with-both-creds"
+    mock_node.credentials_optional = False
+    mock_node.input_default = {
+        "credentials": {
+            "id": "regular-cred-id",
+            "provider": "github",
+            "type": "api_key",
+        },
+        "spreadsheet": {
+            "_credentials_id": "auto-cred-id",
+            "id": "file-123",
+            "name": "test.xlsx",
+        },
+    }
+
+    mock_credentials_field_type = mocker.MagicMock()
+    mock_credentials_meta = mocker.MagicMock()
+    mock_credentials_meta.id = "regular-cred-id"
+    mock_credentials_meta.provider = "github"
+    mock_credentials_meta.type = "api_key"
+    mock_credentials_field_type.model_validate.return_value = mock_credentials_meta
+
+    mock_block = mocker.MagicMock()
+    # Regular credentials field
+    mock_block.input_schema.get_credentials_fields.return_value = {
+        "credentials": mock_credentials_field_type,
+    }
+    # Auto-credentials field
+    mock_block.input_schema.get_auto_credentials_fields.return_value = {
+        "auto_credentials": {
+            "field_name": "spreadsheet",
+            "config": {"provider": "google", "type": "oauth2"},
+        }
+    }
+    mock_node.block = mock_block
+
+    mock_graph = mocker.MagicMock()
+    mock_graph.nodes = [mock_node]
+
+    # Mock the credentials store to return valid credentials for both
+    mock_store = mocker.MagicMock()
+    mock_regular_creds = mocker.MagicMock()
+    mock_regular_creds.id = "regular-cred-id"
+    mock_regular_creds.provider = "github"
+    mock_regular_creds.type = "api_key"
+
+    mock_auto_creds = mocker.MagicMock()
+    mock_auto_creds.id = "auto-cred-id"
+
+    def get_creds_side_effect(user_id, cred_id):
+        if cred_id == "regular-cred-id":
+            return mock_regular_creds
+        elif cred_id == "auto-cred-id":
+            return mock_auto_creds
+        return None
+
+    mock_store.get_creds_by_id = mocker.AsyncMock(side_effect=get_creds_side_effect)
+    mocker.patch(
+        "backend.executor.utils.get_integration_credentials_store",
+        return_value=mock_store,
+    )
+
+    errors, nodes_to_skip = await _validate_node_input_credentials(
+        graph=mock_graph,
+        user_id="test-user",
+        nodes_input_masks=None,
+    )
+
+    # Both should validate successfully - no errors
+    assert mock_node.id not in errors
+    assert mock_node.id not in nodes_to_skip
+
+
+@pytest.mark.asyncio
+async def test_validate_node_input_credentials_auto_creds_skipped_when_none(
+    mocker: MockerFixture,
+):
+    """
+    When a node has auto_credentials but the field value has _credentials_id=None
+    (e.g., from upstream connection), validation should skip it without error.
+    """
+    from backend.executor.utils import _validate_node_input_credentials
+
+    mock_node = mocker.MagicMock()
+    mock_node.id = "node-with-chained-auto-creds"
+    mock_node.credentials_optional = False
+    mock_node.input_default = {
+        "spreadsheet": {
+            "_credentials_id": None,
+            "id": "file-123",
+            "name": "test.xlsx",
+        }
+    }
+
+    mock_block = mocker.MagicMock()
+    mock_block.input_schema.get_credentials_fields.return_value = {}
+    mock_block.input_schema.get_auto_credentials_fields.return_value = {
+        "credentials": {
+            "field_name": "spreadsheet",
+            "config": {"provider": "google", "type": "oauth2"},
+        }
+    }
+    mock_node.block = mock_block
+
+    mock_graph = mocker.MagicMock()
+    mock_graph.nodes = [mock_node]
+
+    errors, nodes_to_skip = await _validate_node_input_credentials(
+        graph=mock_graph,
+        user_id="test-user",
+        nodes_input_masks=None,
+    )
+
+    # No error - chained data with None cred_id is valid
+    assert mock_node.id not in errors
+
+
+# ============================================================================
+# Tests for CredentialsFieldInfo auto_credential tag (Fix 4: Path 4)
+# ============================================================================
+
+
+def test_credentials_field_info_auto_credential_tag():
+    """
+    [Path 4] CredentialsFieldInfo should support is_auto_credential and
+    input_field_name fields for distinguishing auto from regular credentials.
+    """
+    from backend.data.model import CredentialsFieldInfo
+
+    # Regular credential should have is_auto_credential=False by default
+    regular = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["github"],
+            "credentials_types": ["api_key"],
+        },
+        by_alias=True,
+    )
+    assert regular.is_auto_credential is False
+    assert regular.input_field_name is None
+
+    # Auto credential should have is_auto_credential=True
+    auto = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["google"],
+            "credentials_types": ["oauth2"],
+            "is_auto_credential": True,
+            "input_field_name": "spreadsheet",
+        },
+        by_alias=True,
+    )
+    assert auto.is_auto_credential is True
+    assert auto.input_field_name == "spreadsheet"
+
+
+def test_make_node_credentials_input_map_excludes_auto_creds(
+    mocker: MockerFixture,
+):
+    """
+    [Path 4] make_node_credentials_input_map should only include regular credentials,
+    not auto_credentials (which are resolved at execution time).
+    """
+    from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
+    from backend.executor.utils import make_node_credentials_input_map
+    from backend.integrations.providers import ProviderName
+
+    # Create a mock graph with aggregate_credentials_inputs that returns
+    # both regular and auto credentials
+    mock_graph = mocker.MagicMock()
+
+    regular_field_info = CredentialsFieldInfo.model_validate(
+        {
+            "credentials_provider": ["github"],
+            "credentials_types": ["api_key"],
+            "is_auto_credential": False,
+        },
+        by_alias=True,
+    )
+
+    # Mock regular_credentials_inputs property (auto_credentials are excluded)
+    mock_graph.regular_credentials_inputs = {
+        "github_creds": (regular_field_info, {("node-1", "credentials")}, True),
+    }
+
+    graph_credentials_input = {
+        "github_creds": CredentialsMetaInput(
+            id="cred-123",
+            provider=ProviderName("github"),
+            type="api_key",
+        ),
+    }
+
+    result = make_node_credentials_input_map(mock_graph, graph_credentials_input)
+
+    # Regular credentials should be mapped
+    assert "node-1" in result
+    assert "credentials" in result["node-1"]
+
+    # Auto credentials should NOT appear in the result
+    # (they would have been mapped to the kwarg_name "credentials" not "spreadsheet")
+    for node_id, fields in result.items():
+        for field_name, value in fields.items():
+            # Verify no auto-credential phantom entries
+            if isinstance(value, dict):
+                assert "_credentials_id" not in value

autogpt_platform/backend/backend/util/file.py

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

autogpt_platform/backend/backend/util/file_test.py

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

autogpt_platform/backend/pyproject.toml

@@ -11,17 +11,17 @@ packages = [{ include = "backend", format = "sdist" }]
 python = ">=3.10,<3.14"
 aio-pika = "^9.5.5"
 aiohttp = "^3.10.0"
-aiodns = "^4.0.0"
+aiodns = "^3.5.0"
-anthropic = "^0.79.0"
+anthropic = "^0.59.0"
 apscheduler = "^3.11.1"
 autogpt-libs = { path = "../autogpt_libs", develop = true }
 bleach = { extras = ["css"], version = "^6.2.0" }
 click = "^8.2.0"
-cryptography = "^46.0"
+cryptography = "^45.0"
 discord-py = "^2.5.2"
-e2b-code-interpreter = "^2.4.1"
+e2b-code-interpreter = "^1.5.2"
 elevenlabs = "^1.50.0"
-fastapi = "^0.128.6"
+fastapi = "^0.116.1"
 feedparser = "^6.0.11"
 flake8 = "^7.3.0"
 google-api-python-client = "^2.177.0"
@@ -29,16 +29,16 @@ google-auth-oauthlib = "^1.2.2"
 google-cloud-storage = "^3.2.0"
 googlemaps = "^4.10.0"
 gravitasml = "^0.1.4"
-groq = "^1.0.0"
+groq = "^0.30.0"
 html2text = "^2024.2.26"
 jinja2 = "^3.1.6"
 jsonref = "^1.1.0"
 jsonschema = "^4.25.0"
-langfuse = "^3.14.1"
+langfuse = "^3.11.0"
-launchdarkly-server-sdk = "^9.14.1"
+launchdarkly-server-sdk = "^9.12.0"
 mem0ai = "^0.1.115"
 moviepy = "^2.1.2"
-ollama = "^0.6.1"
+ollama = "^0.5.1"
 openai = "^1.97.1"
 orjson = "^3.10.0"
 pika = "^1.3.2"
@@ -48,36 +48,36 @@ postmarker = "^1.0"
 praw = "~7.8.1"
 prisma = "^0.15.0"
 rank-bm25 = "^0.2.2"
-prometheus-client = "^0.24.1"
+prometheus-client = "^0.22.1"
 prometheus-fastapi-instrumentator = "^7.0.0"
 psutil = "^7.0.0"
 psycopg2-binary = "^2.9.10"
-pydantic = { extras = ["email"], version = "^2.12.5" }
+pydantic = { extras = ["email"], version = "^2.11.7" }
-pydantic-settings = "^2.12.0"
+pydantic-settings = "^2.10.1"
 pytest = "^8.4.1"
 pytest-asyncio = "^1.1.0"
 python-dotenv = "^1.1.1"
-python-multipart = "^0.0.22"
+python-multipart = "^0.0.20"
-redis = "^7.1.1"
+redis = "^6.2.0"
 regex = "^2025.9.18"
 replicate = "^1.0.6"
 sentry-sdk = {extras = ["anthropic", "fastapi", "launchdarkly", "openai", "sqlalchemy"], version = "^2.44.0"}
 sqlalchemy = "^2.0.40"
 strenum = "^0.4.9"
 stripe = "^11.5.0"
-supabase = "2.28.0"
+supabase = "2.17.0"
-tenacity = "^9.1.4"
+tenacity = "^9.1.2"
-todoist-api-python = "^3.2.1"
+todoist-api-python = "^2.1.7"
 tweepy = "^4.16.0"
-uvicorn = { extras = ["standard"], version = "^0.40.0" }
+uvicorn = { extras = ["standard"], version = "^0.35.0" }
 websockets = "^15.0"
 youtube-transcript-api = "^1.2.1"
-yt-dlp = "2026.2.4"
+yt-dlp = "2025.12.08"
 zerobouncesdk = "^1.1.2"
 # NOTE: please insert new dependencies in their alphabetical location
 pytest-snapshot = "^0.9.0"
-aiofiles = "^25.1.0"
+aiofiles = "^24.1.0"
-tiktoken = "^0.12.0"
+tiktoken = "^0.9.0"
 aioclamd = "^1.0.0"
 setuptools = "^80.9.0"
 gcloud-aio-storage = "^9.5.0"
@@ -85,7 +85,7 @@ pandas = "^2.3.1"
 firecrawl-py = "^4.3.6"
 exa-py = "^1.14.20"
 croniter = "^6.0.0"
-stagehand = "^3.5.0"
+stagehand = "^0.5.1"
 gravitas-md2gdocs = "^0.1.0"
 posthog = "^7.6.0"
 
@@ -94,14 +94,14 @@ aiohappyeyeballs = "^2.6.1"
 black = "^24.10.0"
 faker = "^38.2.0"
 httpx = "^0.28.1"
-isort = "^7.0.0"
+isort = "^5.13.2"
-poethepoet = "^0.41.0"
+poethepoet = "^0.37.0"
 pre-commit = "^4.4.0"
 pyright = "^1.1.407"
 pytest-mock = "^3.15.1"
-pytest-watcher = "^0.6.3"
+pytest-watcher = "^0.4.2"
 requests = "^2.32.5"
-ruff = "^0.15.0"
+ruff = "^0.14.5"
 # NOTE: please insert new dependencies in their alphabetical location
 
 [build-system]

autogpt_platform/frontend/Dockerfile

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

autogpt_platform/frontend/next.config.mjs

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

autogpt_platform/frontend/package.json

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

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

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

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

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

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

@@ -1,80 +0,0 @@
-"use client";
-
-import { SidebarProvider } from "@/components/ui/sidebar";
-import { ChatContainer } from "./components/ChatContainer/ChatContainer";
-import { ChatSidebar } from "./components/ChatSidebar/ChatSidebar";
-import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
-import { MobileHeader } from "./components/MobileHeader/MobileHeader";
-import { ScaleLoader } from "./components/ScaleLoader/ScaleLoader";
-import { useCopilotPage } from "./useCopilotPage";
-
-export function CopilotPage() {
-  const {
-    sessionId,
-    messages,
-    status,
-    error,
-    stop,
-    createSession,
-    onSend,
-    isLoadingSession,
-    isCreatingSession,
-    isUserLoading,
-    isLoggedIn,
-    // Mobile drawer
-    isMobile,
-    isDrawerOpen,
-    sessions,
-    isLoadingSessions,
-    handleOpenDrawer,
-    handleCloseDrawer,
-    handleDrawerOpenChange,
-    handleSelectSession,
-    handleNewChat,
-  } = useCopilotPage();
-
-  if (isUserLoading || !isLoggedIn) {
-    return (
-      <div className="fixed inset-0 z-50 flex items-center justify-center bg-[#f8f8f9]">
-        <ScaleLoader className="text-neutral-400" />
-      </div>
-    );
-  }
-
-  return (
-    <SidebarProvider
-      defaultOpen={true}
-      className="h-[calc(100vh-72px)] min-h-0"
-    >
-      {!isMobile && <ChatSidebar />}
-      <div className="relative flex h-full w-full flex-col overflow-hidden bg-[#f8f8f9] px-0">
-        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
-        <div className="flex-1 overflow-hidden">
-          <ChatContainer
-            messages={messages}
-            status={status}
-            error={error}
-            sessionId={sessionId}
-            isLoadingSession={isLoadingSession}
-            isCreatingSession={isCreatingSession}
-            onCreateSession={createSession}
-            onSend={onSend}
-            onStop={stop}
-          />
-        </div>
-      </div>
-      {isMobile && (
-        <MobileDrawer
-          isOpen={isDrawerOpen}
-          sessions={sessions}
-          currentSessionId={sessionId}
-          isLoading={isLoadingSessions}
-          onSelectSession={handleSelectSession}
-          onNewChat={handleNewChat}
-          onClose={handleCloseDrawer}
-          onOpenChange={handleDrawerOpenChange}
-        />
-      )}
-    </SidebarProvider>
-  );
-}

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

@@ -1,74 +0,0 @@
-"use client";
-import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
-import { UIDataTypes, UIMessage, UITools } from "ai";
-import { LayoutGroup, motion } from "framer-motion";
-import { ChatMessagesContainer } from "../ChatMessagesContainer/ChatMessagesContainer";
-import { CopilotChatActionsProvider } from "../CopilotChatActionsProvider/CopilotChatActionsProvider";
-import { EmptySession } from "../EmptySession/EmptySession";
-
-export interface ChatContainerProps {
-  messages: UIMessage<unknown, UIDataTypes, UITools>[];
-  status: string;
-  error: Error | undefined;
-  sessionId: string | null;
-  isLoadingSession: boolean;
-  isCreatingSession: boolean;
-  onCreateSession: () => void | Promise<string>;
-  onSend: (message: string) => void | Promise<void>;
-  onStop: () => void;
-}
-export const ChatContainer = ({
-  messages,
-  status,
-  error,
-  sessionId,
-  isLoadingSession,
-  isCreatingSession,
-  onCreateSession,
-  onSend,
-  onStop,
-}: ChatContainerProps) => {
-  const inputLayoutId = "copilot-2-chat-input";
-
-  return (
-    <CopilotChatActionsProvider onSend={onSend}>
-      <LayoutGroup id="copilot-2-chat-layout">
-        <div className="flex h-full min-h-0 w-full flex-col bg-[#f8f8f9] px-2 lg:px-0">
-          {sessionId ? (
-            <div className="mx-auto flex h-full min-h-0 w-full max-w-3xl flex-col">
-              <ChatMessagesContainer
-                messages={messages}
-                status={status}
-                error={error}
-                isLoading={isLoadingSession}
-              />
-              <motion.div
-                initial={{ opacity: 0 }}
-                animate={{ opacity: 1 }}
-                transition={{ duration: 0.3 }}
-                className="relative px-3 pb-2 pt-2"
-              >
-                <div className="pointer-events-none absolute left-0 right-0 top-[-18px] z-10 h-6 bg-gradient-to-b from-transparent to-[#f8f8f9]" />
-                <ChatInput
-                  inputId="chat-input-session"
-                  onSend={onSend}
-                  disabled={status === "streaming"}
-                  isStreaming={status === "streaming"}
-                  onStop={onStop}
-                  placeholder="What else can I help with?"
-                />
-              </motion.div>
-            </div>
-          ) : (
-            <EmptySession
-              inputLayoutId={inputLayoutId}
-              isCreatingSession={isCreatingSession}
-              onCreateSession={onCreateSession}
-              onSend={onSend}
-            />
-          )}
-        </div>
-      </LayoutGroup>
-    </CopilotChatActionsProvider>
-  );
-};

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

@@ -1,274 +0,0 @@
-import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace";
-import {
-  Conversation,
-  ConversationContent,
-  ConversationScrollButton,
-} from "@/components/ai-elements/conversation";
-import {
-  Message,
-  MessageContent,
-  MessageResponse,
-} from "@/components/ai-elements/message";
-import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
-import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
-import { useEffect, useState } from "react";
-import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
-import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
-import { FindAgentsTool } from "../../tools/FindAgents/FindAgents";
-import { FindBlocksTool } from "../../tools/FindBlocks/FindBlocks";
-import { RunAgentTool } from "../../tools/RunAgent/RunAgent";
-import { RunBlockTool } from "../../tools/RunBlock/RunBlock";
-import { SearchDocsTool } from "../../tools/SearchDocs/SearchDocs";
-import { ViewAgentOutputTool } from "../../tools/ViewAgentOutput/ViewAgentOutput";
-
-// ---------------------------------------------------------------------------
-// Workspace media support
-// ---------------------------------------------------------------------------
-
-/**
- * Resolve workspace:// URLs in markdown text to proxy download URLs.
- * Detects MIME type from the hash fragment (e.g. workspace://id#video/mp4)
- * and prefixes the alt text with "video:" so the custom img component can
- * render a <video> element instead.
- */
-function resolveWorkspaceUrls(text: string): string {
-  return text.replace(
-    /!\[([^\]]*)\]\(workspace:\/\/([^)#\s]+)(?:#([^)\s]*))?\)/g,
-    (_match, alt: string, fileId: string, mimeHint?: string) => {
-      const apiPath = getGetWorkspaceDownloadFileByIdUrl(fileId);
-      const url = `/api/proxy${apiPath}`;
-      if (mimeHint?.startsWith("video/")) {
-        return `![video:${alt || "Video"}](${url})`;
-      }
-      return `![${alt || "Image"}](${url})`;
-    },
-  );
-}
-
-/**
- * Custom img component for Streamdown that renders <video> elements
- * for workspace video files (detected via "video:" alt-text prefix).
- * Falls back to <video> when an <img> fails to load for workspace files.
- */
-function WorkspaceMediaImage(props: React.JSX.IntrinsicElements["img"]) {
-  const { src, alt, ...rest } = props;
-  const [imgFailed, setImgFailed] = useState(false);
-  const isWorkspace = src?.includes("/workspace/files/") ?? false;
-
-  if (!src) return null;
-
-  if (alt?.startsWith("video:") || (imgFailed && isWorkspace)) {
-    return (
-      <span className="my-2 inline-block">
-        <video
-          controls
-          className="h-auto max-w-full rounded-md border border-zinc-200"
-          preload="metadata"
-        >
-          <source src={src} />
-          Your browser does not support the video tag.
-        </video>
-      </span>
-    );
-  }
-
-  return (
-    // eslint-disable-next-line @next/next/no-img-element
-    <img
-      src={src}
-      alt={alt || "Image"}
-      className="h-auto max-w-full rounded-md border border-zinc-200"
-      loading="lazy"
-      onError={() => {
-        if (isWorkspace) setImgFailed(true);
-      }}
-      {...rest}
-    />
-  );
-}
-
-/** Stable components override for Streamdown (avoids re-creating on every render). */
-const STREAMDOWN_COMPONENTS = { img: WorkspaceMediaImage };
-
-const THINKING_PHRASES = [
-  "Thinking...",
-  "Considering this...",
-  "Working through this...",
-  "Analyzing your request...",
-  "Reasoning...",
-  "Looking into it...",
-  "Processing your request...",
-  "Mulling this over...",
-  "Piecing it together...",
-  "On it...",
-];
-
-function getRandomPhrase() {
-  return THINKING_PHRASES[Math.floor(Math.random() * THINKING_PHRASES.length)];
-}
-
-interface ChatMessagesContainerProps {
-  messages: UIMessage<unknown, UIDataTypes, UITools>[];
-  status: string;
-  error: Error | undefined;
-  isLoading: boolean;
-}
-
-export const ChatMessagesContainer = ({
-  messages,
-  status,
-  error,
-  isLoading,
-}: ChatMessagesContainerProps) => {
-  const [thinkingPhrase, setThinkingPhrase] = useState(getRandomPhrase);
-
-  useEffect(() => {
-    if (status === "submitted") {
-      setThinkingPhrase(getRandomPhrase());
-    }
-  }, [status]);
-
-  const lastMessage = messages[messages.length - 1];
-  const lastAssistantHasVisibleContent =
-    lastMessage?.role === "assistant" &&
-    lastMessage.parts.some(
-      (p) =>
-        (p.type === "text" && p.text.trim().length > 0) ||
-        p.type.startsWith("tool-"),
-    );
-
-  const showThinking =
-    status === "submitted" ||
-    (status === "streaming" && !lastAssistantHasVisibleContent);
-
-  return (
-    <Conversation className="min-h-0 flex-1">
-      <ConversationContent className="flex min-h-screen flex-1 flex-col gap-6 px-3 py-6">
-        {isLoading && messages.length === 0 && (
-          <div className="flex min-h-full flex-1 items-center justify-center">
-            <LoadingSpinner className="text-neutral-600" />
-          </div>
-        )}
-        {messages.map((message, messageIndex) => {
-          const isLastAssistant =
-            messageIndex === messages.length - 1 &&
-            message.role === "assistant";
-          const messageHasVisibleContent = message.parts.some(
-            (p) =>
-              (p.type === "text" && p.text.trim().length > 0) ||
-              p.type.startsWith("tool-"),
-          );
-
-          return (
-            <Message from={message.role} key={message.id}>
-              <MessageContent
-                className={
-                  "text-[1rem] leading-relaxed " +
-                  "group-[.is-user]:rounded-xl group-[.is-user]:bg-purple-100 group-[.is-user]:px-3 group-[.is-user]:py-2.5 group-[.is-user]:text-slate-900 group-[.is-user]:[border-bottom-right-radius:0] " +
-                  "group-[.is-assistant]:bg-transparent group-[.is-assistant]:text-slate-900"
-                }
-              >
-                {message.parts.map((part, i) => {
-                  switch (part.type) {
-                    case "text":
-                      return (
-                        <MessageResponse
-                          key={`${message.id}-${i}`}
-                          components={STREAMDOWN_COMPONENTS}
-                        >
-                          {resolveWorkspaceUrls(part.text)}
-                        </MessageResponse>
-                      );
-                    case "tool-find_block":
-                      return (
-                        <FindBlocksTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-find_agent":
-                    case "tool-find_library_agent":
-                      return (
-                        <FindAgentsTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-search_docs":
-                    case "tool-get_doc_page":
-                      return (
-                        <SearchDocsTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-run_block":
-                      return (
-                        <RunBlockTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-run_agent":
-                    case "tool-schedule_agent":
-                      return (
-                        <RunAgentTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-create_agent":
-                      return (
-                        <CreateAgentTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-edit_agent":
-                      return (
-                        <EditAgentTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-view_agent_output":
-                      return (
-                        <ViewAgentOutputTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    default:
-                      return null;
-                  }
-                })}
-                {isLastAssistant &&
-                  !messageHasVisibleContent &&
-                  showThinking && (
-                    <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
-                      {thinkingPhrase}
-                    </span>
-                  )}
-              </MessageContent>
-            </Message>
-          );
-        })}
-        {showThinking && lastMessage?.role !== "assistant" && (
-          <Message from="assistant">
-            <MessageContent className="text-[1rem] leading-relaxed">
-              <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
-                {thinkingPhrase}
-              </span>
-            </MessageContent>
-          </Message>
-        )}
-        {error && (
-          <div className="rounded-lg bg-red-50 p-3 text-red-600">
-            Error: {error.message}
-          </div>
-        )}
-      </ConversationContent>
-      <ConversationScrollButton />
-    </Conversation>
-  );
-};

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

@@ -1,188 +0,0 @@
-"use client";
-import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
-import { Button } from "@/components/atoms/Button/Button";
-import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner";
-import { Text } from "@/components/atoms/Text/Text";
-import {
-  Sidebar,
-  SidebarContent,
-  SidebarFooter,
-  SidebarHeader,
-  SidebarTrigger,
-  useSidebar,
-} from "@/components/ui/sidebar";
-import { cn } from "@/lib/utils";
-import { PlusCircleIcon, PlusIcon } from "@phosphor-icons/react";
-import { motion } from "framer-motion";
-import { parseAsString, useQueryState } from "nuqs";
-
-export function ChatSidebar() {
-  const { state } = useSidebar();
-  const isCollapsed = state === "collapsed";
-  const [sessionId, setSessionId] = useQueryState("sessionId", parseAsString);
-
-  const { data: sessionsResponse, isLoading: isLoadingSessions } =
-    useGetV2ListSessions({ limit: 50 });
-
-  const sessions =
-    sessionsResponse?.status === 200 ? sessionsResponse.data.sessions : [];
-
-  function handleNewChat() {
-    setSessionId(null);
-  }
-
-  function handleSelectSession(id: string) {
-    setSessionId(id);
-  }
-
-  function formatDate(dateString: string) {
-    const date = new Date(dateString);
-    const now = new Date();
-    const diffMs = now.getTime() - date.getTime();
-    const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
-
-    if (diffDays === 0) return "Today";
-    if (diffDays === 1) return "Yesterday";
-    if (diffDays < 7) return `${diffDays} days ago`;
-
-    const day = date.getDate();
-    const ordinal =
-      day % 10 === 1 && day !== 11
-        ? "st"
-        : day % 10 === 2 && day !== 12
-          ? "nd"
-          : day % 10 === 3 && day !== 13
-            ? "rd"
-            : "th";
-    const month = date.toLocaleDateString("en-US", { month: "short" });
-    const year = date.getFullYear();
-
-    return `${day}${ordinal} ${month} ${year}`;
-  }
-
-  return (
-    <Sidebar
-      variant="inset"
-      collapsible="icon"
-      className="!top-[50px] !h-[calc(100vh-50px)] border-r border-zinc-100 px-0"
-    >
-      {isCollapsed && (
-        <SidebarHeader
-          className={cn(
-            "flex",
-            isCollapsed
-              ? "flex-row items-center justify-between gap-y-4 md:flex-col md:items-start md:justify-start"
-              : "flex-row items-center justify-between",
-          )}
-        >
-          <motion.div
-            key={isCollapsed ? "header-collapsed" : "header-expanded"}
-            className="flex flex-col items-center gap-3 pt-4"
-            initial={{ opacity: 0, filter: "blur(3px)" }}
-            animate={{ opacity: 1, filter: "blur(0px)" }}
-            transition={{ type: "spring", bounce: 0.2 }}
-          >
-            <div className="flex flex-col items-center gap-2">
-              <SidebarTrigger />
-              <Button
-                variant="ghost"
-                onClick={handleNewChat}
-                style={{ minWidth: "auto", width: "auto" }}
-              >
-                <PlusCircleIcon className="!size-5" />
-                <span className="sr-only">New Chat</span>
-              </Button>
-            </div>
-          </motion.div>
-        </SidebarHeader>
-      )}
-      <SidebarContent className="gap-4 overflow-y-auto px-4 py-4 [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
-        {!isCollapsed && (
-          <motion.div
-            initial={{ opacity: 0 }}
-            animate={{ opacity: 1 }}
-            transition={{ duration: 0.2, delay: 0.1 }}
-            className="flex items-center justify-between px-3"
-          >
-            <Text variant="h3" size="body-medium">
-              Your chats
-            </Text>
-            <div className="relative left-6">
-              <SidebarTrigger />
-            </div>
-          </motion.div>
-        )}
-
-        {!isCollapsed && (
-          <motion.div
-            initial={{ opacity: 0 }}
-            animate={{ opacity: 1 }}
-            transition={{ duration: 0.2, delay: 0.15 }}
-            className="mt-4 flex flex-col gap-1"
-          >
-            {isLoadingSessions ? (
-              <div className="flex min-h-[30rem] items-center justify-center py-4">
-                <LoadingSpinner size="small" className="text-neutral-600" />
-              </div>
-            ) : sessions.length === 0 ? (
-              <p className="py-4 text-center text-sm text-neutral-500">
-                No conversations yet
-              </p>
-            ) : (
-              sessions.map((session) => (
-                <button
-                  key={session.id}
-                  onClick={() => handleSelectSession(session.id)}
-                  className={cn(
-                    "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
-                    session.id === sessionId
-                      ? "bg-zinc-100"
-                      : "hover:bg-zinc-50",
-                  )}
-                >
-                  <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
-                    <div className="min-w-0 max-w-full">
-                      <Text
-                        variant="body"
-                        className={cn(
-                          "truncate font-normal",
-                          session.id === sessionId
-                            ? "text-zinc-600"
-                            : "text-zinc-800",
-                        )}
-                      >
-                        {session.title || `Untitled chat`}
-                      </Text>
-                    </div>
-                    <Text variant="small" className="text-neutral-400">
-                      {formatDate(session.updated_at)}
-                    </Text>
-                  </div>
-                </button>
-              ))
-            )}
-          </motion.div>
-        )}
-      </SidebarContent>
-      {!isCollapsed && sessionId && (
-        <SidebarFooter className="shrink-0 bg-zinc-50 p-3 pb-1 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
-          <motion.div
-            initial={{ opacity: 0 }}
-            animate={{ opacity: 1 }}
-            transition={{ duration: 0.2, delay: 0.2 }}
-          >
-            <Button
-              variant="primary"
-              size="small"
-              onClick={handleNewChat}
-              className="w-full"
-              leftIcon={<PlusIcon className="h-4 w-4" weight="bold" />}
-            >
-              New Chat
-            </Button>
-          </motion.div>
-        </SidebarFooter>
-      )}
-    </Sidebar>
-  );
-}

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

@@ -1,16 +0,0 @@
-"use client";
-
-import { CopilotChatActionsContext } from "./useCopilotChatActions";
-
-interface Props {
-  onSend: (message: string) => void | Promise<void>;
-  children: React.ReactNode;
-}
-
-export function CopilotChatActionsProvider({ onSend, children }: Props) {
-  return (
-    <CopilotChatActionsContext.Provider value={{ onSend }}>
-      {children}
-    </CopilotChatActionsContext.Provider>
-  );
-}

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

@@ -1,23 +0,0 @@
-"use client";
-
-import { createContext, useContext } from "react";
-
-interface CopilotChatActions {
-  onSend: (message: string) => void | Promise<void>;
-}
-
-const CopilotChatActionsContext = createContext<CopilotChatActions | null>(
-  null,
-);
-
-export function useCopilotChatActions(): CopilotChatActions {
-  const ctx = useContext(CopilotChatActionsContext);
-  if (!ctx) {
-    throw new Error(
-      "useCopilotChatActions must be used within CopilotChatActionsProvider",
-    );
-  }
-  return ctx;
-}
-
-export { CopilotChatActionsContext };

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

@@ -0,0 +1,99 @@
+"use client";
+
+import { ChatLoader } from "@/components/contextual/Chat/components/ChatLoader/ChatLoader";
+import { Text } from "@/components/atoms/Text/Text";
+import { NAVBAR_HEIGHT_PX } from "@/lib/constants";
+import type { ReactNode } from "react";
+import { DesktopSidebar } from "./components/DesktopSidebar/DesktopSidebar";
+import { MobileDrawer } from "./components/MobileDrawer/MobileDrawer";
+import { MobileHeader } from "./components/MobileHeader/MobileHeader";
+import { useCopilotShell } from "./useCopilotShell";
+
+interface Props {
+  children: ReactNode;
+}
+
+export function CopilotShell({ children }: Props) {
+  const {
+    isMobile,
+    isDrawerOpen,
+    isLoading,
+    isCreatingSession,
+    isLoggedIn,
+    hasActiveSession,
+    sessions,
+    currentSessionId,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleNewChatClick,
+    handleSessionClick,
+    hasNextPage,
+    isFetchingNextPage,
+    fetchNextPage,
+  } = useCopilotShell();
+
+  if (!isLoggedIn) {
+    return (
+      <div className="flex h-full items-center justify-center">
+        <ChatLoader />
+      </div>
+    );
+  }
+
+  return (
+    <div
+      className="flex overflow-hidden bg-[#EFEFF0]"
+      style={{ height: `calc(100vh - ${NAVBAR_HEIGHT_PX}px)` }}
+    >
+      {!isMobile && (
+        <DesktopSidebar
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={handleSessionClick}
+          onFetchNextPage={fetchNextPage}
+          onNewChat={handleNewChatClick}
+          hasActiveSession={Boolean(hasActiveSession)}
+        />
+      )}
+
+      <div className="relative flex min-h-0 flex-1 flex-col">
+        {isMobile && <MobileHeader onOpenDrawer={handleOpenDrawer} />}
+        <div className="flex min-h-0 flex-1 flex-col">
+          {isCreatingSession ? (
+            <div className="flex h-full flex-1 flex-col items-center justify-center bg-[#f8f8f9]">
+              <div className="flex flex-col items-center gap-4">
+                <ChatLoader />
+                <Text variant="body" className="text-zinc-500">
+                  Creating your chat...
+                </Text>
+              </div>
+            </div>
+          ) : (
+            children
+          )}
+        </div>
+      </div>
+
+      {isMobile && (
+        <MobileDrawer
+          isOpen={isDrawerOpen}
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={handleSessionClick}
+          onFetchNextPage={fetchNextPage}
+          onNewChat={handleNewChatClick}
+          onClose={handleCloseDrawer}
+          onOpenChange={handleDrawerOpenChange}
+          hasActiveSession={Boolean(hasActiveSession)}
+        />
+      )}
+    </div>
+  );
+}

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

@@ -0,0 +1,70 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { Plus } from "@phosphor-icons/react";
+import { SessionsList } from "../SessionsList/SessionsList";
+
+interface Props {
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+  onNewChat: () => void;
+  hasActiveSession: boolean;
+}
+
+export function DesktopSidebar({
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+  onNewChat,
+  hasActiveSession,
+}: Props) {
+  return (
+    <aside className="flex h-full w-80 flex-col border-r border-zinc-100 bg-zinc-50">
+      <div className="shrink-0 px-6 py-4">
+        <Text variant="h3" size="body-medium">
+          Your chats
+        </Text>
+      </div>
+      <div
+        className={cn(
+          "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
+          scrollbarStyles,
+        )}
+      >
+        <SessionsList
+          sessions={sessions}
+          currentSessionId={currentSessionId}
+          isLoading={isLoading}
+          hasNextPage={hasNextPage}
+          isFetchingNextPage={isFetchingNextPage}
+          onSelectSession={onSelectSession}
+          onFetchNextPage={onFetchNextPage}
+        />
+      </div>
+      {hasActiveSession && (
+        <div className="shrink-0 bg-zinc-50 p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+          <Button
+            variant="primary"
+            size="small"
+            onClick={onNewChat}
+            className="w-full"
+            leftIcon={<Plus width="1rem" height="1rem" />}
+          >
+            New Chat
+          </Button>
+        </div>
+      )}
+    </aside>
+  );
+}

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

@@ -0,0 +1,91 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { scrollbarStyles } from "@/components/styles/scrollbars";
+import { cn } from "@/lib/utils";
+import { PlusIcon, X } from "@phosphor-icons/react";
+import { Drawer } from "vaul";
+import { SessionsList } from "../SessionsList/SessionsList";
+
+interface Props {
+  isOpen: boolean;
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+  onNewChat: () => void;
+  onClose: () => void;
+  onOpenChange: (open: boolean) => void;
+  hasActiveSession: boolean;
+}
+
+export function MobileDrawer({
+  isOpen,
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+  onNewChat,
+  onClose,
+  onOpenChange,
+  hasActiveSession,
+}: Props) {
+  return (
+    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
+      <Drawer.Portal>
+        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
+        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
+          <div className="shrink-0 border-b border-zinc-200 p-4">
+            <div className="flex items-center justify-between">
+              <Drawer.Title className="text-lg font-semibold text-zinc-800">
+                Your chats
+              </Drawer.Title>
+              <Button
+                variant="icon"
+                size="icon"
+                aria-label="Close sessions"
+                onClick={onClose}
+              >
+                <X width="1.25rem" height="1.25rem" />
+              </Button>
+            </div>
+          </div>
+          <div
+            className={cn(
+              "flex min-h-0 flex-1 flex-col overflow-y-auto px-3 py-3",
+              scrollbarStyles,
+            )}
+          >
+            <SessionsList
+              sessions={sessions}
+              currentSessionId={currentSessionId}
+              isLoading={isLoading}
+              hasNextPage={hasNextPage}
+              isFetchingNextPage={isFetchingNextPage}
+              onSelectSession={onSelectSession}
+              onFetchNextPage={onFetchNextPage}
+            />
+          </div>
+          {hasActiveSession && (
+            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
+              <Button
+                variant="primary"
+                size="small"
+                onClick={onNewChat}
+                className="w-full"
+                leftIcon={<PlusIcon width="1rem" height="1rem" />}
+              >
+                New Chat
+              </Button>
+            </div>
+          )}
+        </Drawer.Content>
+      </Drawer.Portal>
+    </Drawer.Root>
+  );
+}

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

@@ -0,0 +1,24 @@
+import { useState } from "react";
+
+export function useMobileDrawer() {
+  const [isDrawerOpen, setIsDrawerOpen] = useState(false);
+
+  const handleOpenDrawer = () => {
+    setIsDrawerOpen(true);
+  };
+
+  const handleCloseDrawer = () => {
+    setIsDrawerOpen(false);
+  };
+
+  const handleDrawerOpenChange = (open: boolean) => {
+    setIsDrawerOpen(open);
+  };
+
+  return {
+    isDrawerOpen,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+  };
+}

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

@@ -0,0 +1,80 @@
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { Skeleton } from "@/components/__legacy__/ui/skeleton";
+import { Text } from "@/components/atoms/Text/Text";
+import { InfiniteList } from "@/components/molecules/InfiniteList/InfiniteList";
+import { cn } from "@/lib/utils";
+import { getSessionTitle } from "../../helpers";
+
+interface Props {
+  sessions: SessionSummaryResponse[];
+  currentSessionId: string | null;
+  isLoading: boolean;
+  hasNextPage: boolean;
+  isFetchingNextPage: boolean;
+  onSelectSession: (sessionId: string) => void;
+  onFetchNextPage: () => void;
+}
+
+export function SessionsList({
+  sessions,
+  currentSessionId,
+  isLoading,
+  hasNextPage,
+  isFetchingNextPage,
+  onSelectSession,
+  onFetchNextPage,
+}: Props) {
+  if (isLoading) {
+    return (
+      <div className="space-y-1">
+        {Array.from({ length: 5 }).map((_, i) => (
+          <div key={i} className="rounded-lg px-3 py-2.5">
+            <Skeleton className="h-5 w-full" />
+          </div>
+        ))}
+      </div>
+    );
+  }
+
+  if (sessions.length === 0) {
+    return (
+      <div className="flex h-full items-center justify-center">
+        <Text variant="body" className="text-zinc-500">
+          You don&apos;t have previous chats
+        </Text>
+      </div>
+    );
+  }
+
+  return (
+    <InfiniteList
+      items={sessions}
+      hasMore={hasNextPage}
+      isFetchingMore={isFetchingNextPage}
+      onEndReached={onFetchNextPage}
+      className="space-y-1"
+      renderItem={(session) => {
+        const isActive = session.id === currentSessionId;
+        return (
+          <button
+            onClick={() => onSelectSession(session.id)}
+            className={cn(
+              "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
+              isActive ? "bg-zinc-100" : "hover:bg-zinc-50",
+            )}
+          >
+            <Text
+              variant="body"
+              className={cn(
+                "font-normal",
+                isActive ? "text-zinc-600" : "text-zinc-800",
+              )}
+            >
+              {getSessionTitle(session)}
+            </Text>
+          </button>
+        );
+      }}
+    />
+  );
+}

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

@@ -0,0 +1,91 @@
+import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { okData } from "@/app/api/helpers";
+import { useEffect, useState } from "react";
+
+const PAGE_SIZE = 50;
+
+export interface UseSessionsPaginationArgs {
+  enabled: boolean;
+}
+
+export function useSessionsPagination({ enabled }: UseSessionsPaginationArgs) {
+  const [offset, setOffset] = useState(0);
+
+  const [accumulatedSessions, setAccumulatedSessions] = useState<
+    SessionSummaryResponse[]
+  >([]);
+
+  const [totalCount, setTotalCount] = useState<number | null>(null);
+
+  const { data, isLoading, isFetching, isError } = useGetV2ListSessions(
+    { limit: PAGE_SIZE, offset },
+    {
+      query: {
+        enabled: enabled && offset >= 0,
+      },
+    },
+  );
+
+  useEffect(() => {
+    const responseData = okData(data);
+    if (responseData) {
+      const newSessions = responseData.sessions;
+      const total = responseData.total;
+      setTotalCount(total);
+
+      if (offset === 0) {
+        setAccumulatedSessions(newSessions);
+      } else {
+        setAccumulatedSessions((prev) => [...prev, ...newSessions]);
+      }
+    } else if (!enabled) {
+      setAccumulatedSessions([]);
+      setTotalCount(null);
+    }
+  }, [data, offset, enabled]);
+
+  const hasNextPage =
+    totalCount !== null && accumulatedSessions.length < totalCount;
+
+  const areAllSessionsLoaded =
+    totalCount !== null &&
+    accumulatedSessions.length >= totalCount &&
+    !isFetching &&
+    !isLoading;
+
+  useEffect(() => {
+    if (
+      hasNextPage &&
+      !isFetching &&
+      !isLoading &&
+      !isError &&
+      totalCount !== null
+    ) {
+      setOffset((prev) => prev + PAGE_SIZE);
+    }
+  }, [hasNextPage, isFetching, isLoading, isError, totalCount]);
+
+  const fetchNextPage = () => {
+    if (hasNextPage && !isFetching) {
+      setOffset((prev) => prev + PAGE_SIZE);
+    }
+  };
+
+  const reset = () => {
+    // Only reset the offset - keep existing sessions visible during refetch
+    // The effect will replace sessions when new data arrives at offset 0
+    setOffset(0);
+  };
+
+  return {
+    sessions: accumulatedSessions,
+    isLoading,
+    isFetching,
+    hasNextPage,
+    areAllSessionsLoaded,
+    totalCount,
+    fetchNextPage,
+    reset,
+  };
+}

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

@@ -0,0 +1,106 @@
+import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { format, formatDistanceToNow, isToday } from "date-fns";
+
+export function convertSessionDetailToSummary(session: SessionDetailResponse) {
+  return {
+    id: session.id,
+    created_at: session.created_at,
+    updated_at: session.updated_at,
+    title: undefined,
+  };
+}
+
+export function filterVisibleSessions(sessions: SessionSummaryResponse[]) {
+  const fiveMinutesAgo = Date.now() - 5 * 60 * 1000;
+  return sessions.filter((session) => {
+    const hasBeenUpdated = session.updated_at !== session.created_at;
+
+    if (hasBeenUpdated) return true;
+
+    const isRecentlyCreated =
+      new Date(session.created_at).getTime() > fiveMinutesAgo;
+
+    return isRecentlyCreated;
+  });
+}
+
+export function getSessionTitle(session: SessionSummaryResponse) {
+  if (session.title) return session.title;
+
+  const isNewSession = session.updated_at === session.created_at;
+
+  if (isNewSession) {
+    const createdDate = new Date(session.created_at);
+    if (isToday(createdDate)) {
+      return "Today";
+    }
+    return format(createdDate, "MMM d, yyyy");
+  }
+
+  return "Untitled Chat";
+}
+
+export function getSessionUpdatedLabel(session: SessionSummaryResponse) {
+  if (!session.updated_at) return "";
+  return formatDistanceToNow(new Date(session.updated_at), { addSuffix: true });
+}
+
+export function mergeCurrentSessionIntoList(
+  accumulatedSessions: SessionSummaryResponse[],
+  currentSessionId: string | null,
+  currentSessionData: SessionDetailResponse | null | undefined,
+  recentlyCreatedSessions?: Map<string, SessionSummaryResponse>,
+) {
+  const filteredSessions: SessionSummaryResponse[] = [];
+  const addedIds = new Set<string>();
+
+  if (accumulatedSessions.length > 0) {
+    const visibleSessions = filterVisibleSessions(accumulatedSessions);
+
+    if (currentSessionId) {
+      const currentInAll = accumulatedSessions.find(
+        (s) => s.id === currentSessionId,
+      );
+      if (currentInAll) {
+        const isInVisible = visibleSessions.some(
+          (s) => s.id === currentSessionId,
+        );
+        if (!isInVisible) {
+          filteredSessions.push(currentInAll);
+          addedIds.add(currentInAll.id);
+        }
+      }
+    }
+
+    for (const session of visibleSessions) {
+      if (!addedIds.has(session.id)) {
+        filteredSessions.push(session);
+        addedIds.add(session.id);
+      }
+    }
+  }
+
+  if (currentSessionId && currentSessionData) {
+    if (!addedIds.has(currentSessionId)) {
+      const summarySession = convertSessionDetailToSummary(currentSessionData);
+      filteredSessions.unshift(summarySession);
+      addedIds.add(currentSessionId);
+    }
+  }
+
+  if (recentlyCreatedSessions) {
+    for (const [sessionId, sessionData] of recentlyCreatedSessions) {
+      if (!addedIds.has(sessionId)) {
+        filteredSessions.unshift(sessionData);
+        addedIds.add(sessionId);
+      }
+    }
+  }
+
+  return filteredSessions;
+}
+
+export function getCurrentSessionId(searchParams: URLSearchParams) {
+  return searchParams.get("sessionId");
+}

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

@@ -0,0 +1,124 @@
+"use client";
+
+import {
+  getGetV2GetSessionQueryKey,
+  getGetV2ListSessionsQueryKey,
+  useGetV2GetSession,
+} from "@/app/api/__generated__/endpoints/chat/chat";
+import { okData } from "@/app/api/helpers";
+import { useChatStore } from "@/components/contextual/Chat/chat-store";
+import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
+import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
+import { useQueryClient } from "@tanstack/react-query";
+import { usePathname, useSearchParams } from "next/navigation";
+import { useCopilotStore } from "../../copilot-page-store";
+import { useCopilotSessionId } from "../../useCopilotSessionId";
+import { useMobileDrawer } from "./components/MobileDrawer/useMobileDrawer";
+import { getCurrentSessionId } from "./helpers";
+import { useShellSessionList } from "./useShellSessionList";
+
+export function useCopilotShell() {
+  const pathname = usePathname();
+  const searchParams = useSearchParams();
+  const queryClient = useQueryClient();
+  const breakpoint = useBreakpoint();
+  const { isLoggedIn } = useSupabase();
+  const isMobile =
+    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
+
+  const { urlSessionId, setUrlSessionId } = useCopilotSessionId();
+
+  const isOnHomepage = pathname === "/copilot";
+  const paramSessionId = searchParams.get("sessionId");
+
+  const {
+    isDrawerOpen,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+  } = useMobileDrawer();
+
+  const paginationEnabled = !isMobile || isDrawerOpen || !!paramSessionId;
+
+  const currentSessionId = getCurrentSessionId(searchParams);
+
+  const { data: currentSessionData } = useGetV2GetSession(
+    currentSessionId || "",
+    {
+      query: {
+        enabled: !!currentSessionId,
+        select: okData,
+      },
+    },
+  );
+
+  const {
+    sessions,
+    isLoading,
+    isSessionsFetching,
+    hasNextPage,
+    fetchNextPage,
+    resetPagination,
+    recentlyCreatedSessionsRef,
+  } = useShellSessionList({
+    paginationEnabled,
+    currentSessionId,
+    currentSessionData,
+    isOnHomepage,
+    paramSessionId,
+  });
+
+  const stopStream = useChatStore((s) => s.stopStream);
+  const isCreatingSession = useCopilotStore((s) => s.isCreatingSession);
+
+  function handleSessionClick(sessionId: string) {
+    if (sessionId === currentSessionId) return;
+
+    // Stop current stream - SSE reconnection allows resuming later
+    if (currentSessionId) {
+      stopStream(currentSessionId);
+    }
+
+    if (recentlyCreatedSessionsRef.current.has(sessionId)) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2GetSessionQueryKey(sessionId),
+      });
+    }
+    setUrlSessionId(sessionId, { shallow: false });
+    if (isMobile) handleCloseDrawer();
+  }
+
+  function handleNewChatClick() {
+    // Stop current stream - SSE reconnection allows resuming later
+    if (currentSessionId) {
+      stopStream(currentSessionId);
+    }
+
+    resetPagination();
+    queryClient.invalidateQueries({
+      queryKey: getGetV2ListSessionsQueryKey(),
+    });
+    setUrlSessionId(null, { shallow: false });
+    if (isMobile) handleCloseDrawer();
+  }
+
+  return {
+    isMobile,
+    isDrawerOpen,
+    isLoggedIn,
+    hasActiveSession:
+      Boolean(currentSessionId) && (!isOnHomepage || Boolean(paramSessionId)),
+    isLoading: isLoading || isCreatingSession,
+    isCreatingSession,
+    sessions,
+    currentSessionId: urlSessionId,
+    handleOpenDrawer,
+    handleCloseDrawer,
+    handleDrawerOpenChange,
+    handleNewChatClick,
+    handleSessionClick,
+    hasNextPage,
+    isFetchingNextPage: isSessionsFetching,
+    fetchNextPage,
+  };
+}

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

@@ -0,0 +1,113 @@
+import { getGetV2ListSessionsQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
+import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessionDetailResponse";
+import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
+import { useChatStore } from "@/components/contextual/Chat/chat-store";
+import { useQueryClient } from "@tanstack/react-query";
+import { useEffect, useMemo, useRef } from "react";
+import { useSessionsPagination } from "./components/SessionsList/useSessionsPagination";
+import {
+  convertSessionDetailToSummary,
+  filterVisibleSessions,
+  mergeCurrentSessionIntoList,
+} from "./helpers";
+
+interface UseShellSessionListArgs {
+  paginationEnabled: boolean;
+  currentSessionId: string | null;
+  currentSessionData: SessionDetailResponse | null | undefined;
+  isOnHomepage: boolean;
+  paramSessionId: string | null;
+}
+
+export function useShellSessionList({
+  paginationEnabled,
+  currentSessionId,
+  currentSessionData,
+  isOnHomepage,
+  paramSessionId,
+}: UseShellSessionListArgs) {
+  const queryClient = useQueryClient();
+  const onStreamComplete = useChatStore((s) => s.onStreamComplete);
+
+  const {
+    sessions: accumulatedSessions,
+    isLoading: isSessionsLoading,
+    isFetching: isSessionsFetching,
+    hasNextPage,
+    fetchNextPage,
+    reset: resetPagination,
+  } = useSessionsPagination({
+    enabled: paginationEnabled,
+  });
+
+  const recentlyCreatedSessionsRef = useRef<
+    Map<string, SessionSummaryResponse>
+  >(new Map());
+
+  useEffect(() => {
+    if (isOnHomepage && !paramSessionId) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey(),
+      });
+    }
+  }, [isOnHomepage, paramSessionId, queryClient]);
+
+  useEffect(() => {
+    if (currentSessionId && currentSessionData) {
+      const isNewSession =
+        currentSessionData.updated_at === currentSessionData.created_at;
+      const isNotInAccumulated = !accumulatedSessions.some(
+        (s) => s.id === currentSessionId,
+      );
+      if (isNewSession || isNotInAccumulated) {
+        const summary = convertSessionDetailToSummary(currentSessionData);
+        recentlyCreatedSessionsRef.current.set(currentSessionId, summary);
+      }
+    }
+  }, [currentSessionId, currentSessionData, accumulatedSessions]);
+
+  useEffect(() => {
+    for (const sessionId of recentlyCreatedSessionsRef.current.keys()) {
+      if (accumulatedSessions.some((s) => s.id === sessionId)) {
+        recentlyCreatedSessionsRef.current.delete(sessionId);
+      }
+    }
+  }, [accumulatedSessions]);
+
+  useEffect(() => {
+    const unsubscribe = onStreamComplete(() => {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2ListSessionsQueryKey(),
+      });
+    });
+    return unsubscribe;
+  }, [onStreamComplete, queryClient]);
+
+  const sessions = useMemo(
+    () =>
+      mergeCurrentSessionIntoList(
+        accumulatedSessions,
+        currentSessionId,
+        currentSessionData,
+        recentlyCreatedSessionsRef.current,
+      ),
+    [accumulatedSessions, currentSessionId, currentSessionData],
+  );
+
+  const visibleSessions = useMemo(
+    () => filterVisibleSessions(sessions),
+    [sessions],
+  );
+
+  const isLoading = isSessionsLoading && accumulatedSessions.length === 0;
+
+  return {
+    sessions: visibleSessions,
+    isLoading,
+    isSessionsFetching,
+    hasNextPage,
+    fetchNextPage,
+    resetPagination,
+    recentlyCreatedSessionsRef,
+  };
+}

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

@@ -1,111 +0,0 @@
-"use client";
-
-import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
-import { SpinnerGapIcon } from "@phosphor-icons/react";
-import { motion } from "framer-motion";
-import { useEffect, useState } from "react";
-import {
-  getGreetingName,
-  getInputPlaceholder,
-  getQuickActions,
-} from "./helpers";
-
-interface Props {
-  inputLayoutId: string;
-  isCreatingSession: boolean;
-  onCreateSession: () => void | Promise<string>;
-  onSend: (message: string) => void | Promise<void>;
-}
-
-export function EmptySession({
-  inputLayoutId,
-  isCreatingSession,
-  onSend,
-}: Props) {
-  const { user } = useSupabase();
-  const greetingName = getGreetingName(user);
-  const quickActions = getQuickActions();
-  const [loadingAction, setLoadingAction] = useState<string | null>(null);
-  const [inputPlaceholder, setInputPlaceholder] = useState(
-    getInputPlaceholder(),
-  );
-
-  useEffect(() => {
-    setInputPlaceholder(getInputPlaceholder(window.innerWidth));
-  }, [window.innerWidth]);
-
-  async function handleQuickActionClick(action: string) {
-    if (isCreatingSession || loadingAction) return;
-
-    setLoadingAction(action);
-    try {
-      await onSend(action);
-    } finally {
-      setLoadingAction(null);
-    }
-  }
-
-  return (
-    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-0 py-5 md:px-6 md:py-10">
-      <motion.div
-        className="w-full max-w-3xl text-center"
-        initial={{ opacity: 0 }}
-        animate={{ opacity: 1 }}
-        transition={{ duration: 0.3 }}
-      >
-        <div className="mx-auto max-w-3xl">
-          <Text variant="h3" className="mb-1 !text-[1.375rem] text-zinc-700">
-            Hey, <span className="text-violet-600">{greetingName}</span>
-          </Text>
-          <Text variant="h3" className="mb-8 !font-normal">
-            Tell me about your work — I&apos;ll find what to automate.
-          </Text>
-
-          <div className="mb-6">
-            <motion.div
-              layoutId={inputLayoutId}
-              transition={{ type: "spring", bounce: 0.2, duration: 0.65 }}
-              className="w-full px-2"
-            >
-              <ChatInput
-                inputId="chat-input-empty"
-                onSend={onSend}
-                disabled={isCreatingSession}
-                placeholder={inputPlaceholder}
-                className="w-full"
-              />
-            </motion.div>
-          </div>
-        </div>
-
-        <div className="flex flex-wrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
-          {quickActions.map((action) => (
-            <Button
-              key={action}
-              type="button"
-              variant="outline"
-              size="small"
-              onClick={() => void handleQuickActionClick(action)}
-              disabled={isCreatingSession || loadingAction !== null}
-              aria-busy={loadingAction === action}
-              leftIcon={
-                loadingAction === action ? (
-                  <SpinnerGapIcon
-                    className="h-4 w-4 animate-spin"
-                    weight="bold"
-                  />
-                ) : null
-              }
-              className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
-            >
-              {action}
-            </Button>
-          ))}
-        </div>
-      </motion.div>
-    </div>
-  );
-}

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

@@ -1,140 +0,0 @@
-import type { SessionSummaryResponse } from "@/app/api/__generated__/models/sessionSummaryResponse";
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { scrollbarStyles } from "@/components/styles/scrollbars";
-import { cn } from "@/lib/utils";
-import { PlusIcon, SpinnerGapIcon, X } from "@phosphor-icons/react";
-import { Drawer } from "vaul";
-
-interface Props {
-  isOpen: boolean;
-  sessions: SessionSummaryResponse[];
-  currentSessionId: string | null;
-  isLoading: boolean;
-  onSelectSession: (sessionId: string) => void;
-  onNewChat: () => void;
-  onClose: () => void;
-  onOpenChange: (open: boolean) => void;
-}
-
-function formatDate(dateString: string) {
-  const date = new Date(dateString);
-  const now = new Date();
-  const diffMs = now.getTime() - date.getTime();
-  const diffDays = Math.floor(diffMs / (1000 * 60 * 60 * 24));
-
-  if (diffDays === 0) return "Today";
-  if (diffDays === 1) return "Yesterday";
-  if (diffDays < 7) return `${diffDays} days ago`;
-
-  const day = date.getDate();
-  const ordinal =
-    day % 10 === 1 && day !== 11
-      ? "st"
-      : day % 10 === 2 && day !== 12
-        ? "nd"
-        : day % 10 === 3 && day !== 13
-          ? "rd"
-          : "th";
-  const month = date.toLocaleDateString("en-US", { month: "short" });
-  const year = date.getFullYear();
-
-  return `${day}${ordinal} ${month} ${year}`;
-}
-
-export function MobileDrawer({
-  isOpen,
-  sessions,
-  currentSessionId,
-  isLoading,
-  onSelectSession,
-  onNewChat,
-  onClose,
-  onOpenChange,
-}: Props) {
-  return (
-    <Drawer.Root open={isOpen} onOpenChange={onOpenChange} direction="left">
-      <Drawer.Portal>
-        <Drawer.Overlay className="fixed inset-0 z-[60] bg-black/10 backdrop-blur-sm" />
-        <Drawer.Content className="fixed left-0 top-0 z-[70] flex h-full w-80 flex-col border-r border-zinc-200 bg-zinc-50">
-          <div className="shrink-0 border-b border-zinc-200 px-4 py-2">
-            <div className="flex items-center justify-between">
-              <Drawer.Title className="text-lg font-semibold text-zinc-800">
-                Your chats
-              </Drawer.Title>
-              <Button
-                variant="icon"
-                size="icon"
-                aria-label="Close sessions"
-                onClick={onClose}
-              >
-                <X width="1rem" height="1rem" />
-              </Button>
-            </div>
-          </div>
-          <div
-            className={cn(
-              "flex min-h-0 flex-1 flex-col gap-1 overflow-y-auto px-3 py-3",
-              scrollbarStyles,
-            )}
-          >
-            {isLoading ? (
-              <div className="flex items-center justify-center py-4">
-                <SpinnerGapIcon className="h-5 w-5 animate-spin text-neutral-400" />
-              </div>
-            ) : sessions.length === 0 ? (
-              <p className="py-4 text-center text-sm text-neutral-500">
-                No conversations yet
-              </p>
-            ) : (
-              sessions.map((session) => (
-                <button
-                  key={session.id}
-                  onClick={() => onSelectSession(session.id)}
-                  className={cn(
-                    "w-full rounded-lg px-3 py-2.5 text-left transition-colors",
-                    session.id === currentSessionId
-                      ? "bg-zinc-100"
-                      : "hover:bg-zinc-50",
-                  )}
-                >
-                  <div className="flex min-w-0 max-w-full flex-col overflow-hidden">
-                    <div className="min-w-0 max-w-full">
-                      <Text
-                        variant="body"
-                        className={cn(
-                          "truncate font-normal",
-                          session.id === currentSessionId
-                            ? "text-zinc-600"
-                            : "text-zinc-800",
-                        )}
-                      >
-                        {session.title || "Untitled chat"}
-                      </Text>
-                    </div>
-                    <Text variant="small" className="text-neutral-400">
-                      {formatDate(session.updated_at)}
-                    </Text>
-                  </div>
-                </button>
-              ))
-            )}
-          </div>
-          {currentSessionId && (
-            <div className="shrink-0 bg-white p-3 shadow-[0_-4px_6px_-1px_rgba(0,0,0,0.05)]">
-              <Button
-                variant="primary"
-                size="small"
-                onClick={onNewChat}
-                className="w-full"
-                leftIcon={<PlusIcon width="1rem" height="1rem" />}
-              >
-                New Chat
-              </Button>
-            </div>
-          )}
-        </Drawer.Content>
-      </Drawer.Portal>
-    </Drawer.Root>
-  );
-}

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

@@ -1,54 +0,0 @@
-import { cn } from "@/lib/utils";
-import { AnimatePresence, motion } from "framer-motion";
-
-interface Props {
-  text: string;
-  className?: string;
-}
-
-export function MorphingTextAnimation({ text, className }: Props) {
-  const letters = text.split("");
-
-  return (
-    <div className={cn(className)}>
-      <AnimatePresence mode="popLayout" initial={false}>
-        <motion.div key={text} className="whitespace-nowrap">
-          <motion.span className="inline-flex overflow-hidden">
-            {letters.map((char, index) => (
-              <motion.span
-                key={`${text}-${index}`}
-                initial={{
-                  opacity: 0,
-                  y: 8,
-                  rotateX: "80deg",
-                  filter: "blur(6px)",
-                }}
-                animate={{
-                  opacity: 1,
-                  y: 0,
-                  rotateX: "0deg",
-                  filter: "blur(0px)",
-                }}
-                exit={{
-                  opacity: 0,
-                  y: -8,
-                  rotateX: "-80deg",
-                  filter: "blur(6px)",
-                }}
-                style={{ willChange: "transform" }}
-                transition={{
-                  delay: 0.015 * index,
-                  type: "spring",
-                  bounce: 0.5,
-                }}
-                className="inline-block"
-              >
-                {char === " " ? "\u00A0" : char}
-              </motion.span>
-            ))}
-          </motion.span>
-        </motion.div>
-      </AnimatePresence>
-    </div>
-  );
-}

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

@@ -1,69 +0,0 @@
-.loader {
-  position: relative;
-  animation: rotate 1s infinite;
-}
-
-.loader::before,
-.loader::after {
-  border-radius: 50%;
-  content: "";
-  display: block;
-  /* 40% of container size */
-  height: 40%;
-  width: 40%;
-}
-
-.loader::before {
-  animation: ball1 1s infinite;
-  background-color: #a1a1aa; /* zinc-400 */
-  box-shadow: calc(var(--spacing)) 0 0 #18181b; /* zinc-900 */
-  margin-bottom: calc(var(--gap));
-}
-
-.loader::after {
-  animation: ball2 1s infinite;
-  background-color: #18181b; /* zinc-900 */
-  box-shadow: calc(var(--spacing)) 0 0 #a1a1aa; /* zinc-400 */
-}
-
-@keyframes rotate {
-  0% {
-    transform: rotate(0deg) scale(0.8);
-  }
-  50% {
-    transform: rotate(360deg) scale(1.2);
-  }
-  100% {
-    transform: rotate(720deg) scale(0.8);
-  }
-}
-
-@keyframes ball1 {
-  0% {
-    box-shadow: calc(var(--spacing)) 0 0 #18181b;
-  }
-  50% {
-    box-shadow: 0 0 0 #18181b;
-    margin-bottom: 0;
-    transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
-  }
-  100% {
-    box-shadow: calc(var(--spacing)) 0 0 #18181b;
-    margin-bottom: calc(var(--gap));
-  }
-}
-
-@keyframes ball2 {
-  0% {
-    box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
-  }
-  50% {
-    box-shadow: 0 0 0 #a1a1aa;
-    margin-top: calc(var(--ball-size) * -1);
-    transform: translate(calc(var(--spacing) / 2), calc(var(--spacing) / 2));
-  }
-  100% {
-    box-shadow: calc(var(--spacing)) 0 0 #a1a1aa;
-    margin-top: 0;
-  }
-}

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

@@ -1,28 +0,0 @@
-import { cn } from "@/lib/utils";
-import styles from "./OrbitLoader.module.css";
-
-interface Props {
-  size?: number;
-  className?: string;
-}
-
-export function OrbitLoader({ size = 24, className }: Props) {
-  const ballSize = Math.round(size * 0.4);
-  const spacing = Math.round(size * 0.6);
-  const gap = Math.round(size * 0.2);
-
-  return (
-    <div
-      className={cn(styles.loader, className)}
-      style={
-        {
-          width: size,
-          height: size,
-          "--ball-size": `${ballSize}px`,
-          "--spacing": `${spacing}px`,
-          "--gap": `${gap}px`,
-        } as React.CSSProperties
-      }
-    />
-  );
-}

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

@@ -1,26 +0,0 @@
-import { cn } from "@/lib/utils";
-
-interface Props {
-  value: number;
-  label?: string;
-  className?: string;
-}
-
-export function ProgressBar({ value, label, className }: Props) {
-  const clamped = Math.min(100, Math.max(0, value));
-
-  return (
-    <div className={cn("flex flex-col gap-1.5", className)}>
-      <div className="flex items-center justify-between text-xs text-neutral-500">
-        <span>{label ?? "Working on it..."}</span>
-        <span>{Math.round(clamped)}%</span>
-      </div>
-      <div className="h-2 w-full overflow-hidden rounded-full bg-neutral-200">
-        <div
-          className="h-full rounded-full bg-neutral-900 transition-[width] duration-300 ease-out"
-          style={{ width: `${clamped}%` }}
-        />
-      </div>
-    </div>
-  );
-}

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

@@ -1,34 +0,0 @@
-.loader {
-  position: relative;
-  display: inline-block;
-  flex-shrink: 0;
-}
-
-.loader::before,
-.loader::after {
-  content: "";
-  box-sizing: border-box;
-  width: 100%;
-  height: 100%;
-  border-radius: 50%;
-  background: currentColor;
-  position: absolute;
-  left: 0;
-  top: 0;
-  animation: ripple 2s linear infinite;
-}
-
-.loader::after {
-  animation-delay: 1s;
-}
-
-@keyframes ripple {
-  0% {
-    transform: scale(0);
-    opacity: 1;
-  }
-  100% {
-    transform: scale(1);
-    opacity: 0;
-  }
-}

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

@@ -1,16 +0,0 @@
-import { cn } from "@/lib/utils";
-import styles from "./PulseLoader.module.css";
-
-interface Props {
-  size?: number;
-  className?: string;
-}
-
-export function PulseLoader({ size = 24, className }: Props) {
-  return (
-    <div
-      className={cn(styles.loader, className)}
-      style={{ width: size, height: size }}
-    />
-  );
-}

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

@@ -1,35 +0,0 @@
-.loader {
-  width: 48px;
-  height: 48px;
-  display: inline-block;
-  position: relative;
-}
-
-.loader::after,
-.loader::before {
-  content: "";
-  box-sizing: border-box;
-  width: 100%;
-  height: 100%;
-  border-radius: 50%;
-  background: currentColor;
-  position: absolute;
-  left: 0;
-  top: 0;
-  animation: animloader 2s linear infinite;
-}
-
-.loader::after {
-  animation-delay: 1s;
-}
-
-@keyframes animloader {
-  0% {
-    transform: scale(0);
-    opacity: 1;
-  }
-  100% {
-    transform: scale(1);
-    opacity: 0;
-  }
-}

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

@@ -1,16 +0,0 @@
-import { cn } from "@/lib/utils";
-import styles from "./ScaleLoader.module.css";
-
-interface Props {
-  size?: number;
-  className?: string;
-}
-
-export function ScaleLoader({ size = 48, className }: Props) {
-  return (
-    <div
-      className={cn(styles.loader, className)}
-      style={{ width: size, height: size }}
-    />
-  );
-}

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

@@ -1,57 +0,0 @@
-.loader {
-  position: relative;
-  display: inline-block;
-  flex-shrink: 0;
-  transform: rotateZ(45deg);
-  perspective: 1000px;
-  border-radius: 50%;
-  color: currentColor;
-}
-
-.loader::before,
-.loader::after {
-  content: "";
-  display: block;
-  position: absolute;
-  top: 0;
-  left: 0;
-  width: inherit;
-  height: inherit;
-  border-radius: 50%;
-  transform: rotateX(70deg);
-  animation: spin 1s linear infinite;
-}
-
-.loader::after {
-  color: var(--spinner-accent, #a855f7);
-  transform: rotateY(70deg);
-  animation-delay: 0.4s;
-}
-
-@keyframes spin {
-  0%,
-  100% {
-    box-shadow: 0.2em 0 0 0 currentColor;
-  }
-  12% {
-    box-shadow: 0.2em 0.2em 0 0 currentColor;
-  }
-  25% {
-    box-shadow: 0 0.2em 0 0 currentColor;
-  }
-  37% {
-    box-shadow: -0.2em 0.2em 0 0 currentColor;
-  }
-  50% {
-    box-shadow: -0.2em 0 0 0 currentColor;
-  }
-  62% {
-    box-shadow: -0.2em -0.2em 0 0 currentColor;
-  }
-  75% {
-    box-shadow: 0 -0.2em 0 0 currentColor;
-  }
-  87% {
-    box-shadow: 0.2em -0.2em 0 0 currentColor;
-  }
-}

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

@@ -1,16 +0,0 @@
-import { cn } from "@/lib/utils";
-import styles from "./SpinnerLoader.module.css";
-
-interface Props {
-  size?: number;
-  className?: string;
-}
-
-export function SpinnerLoader({ size = 24, className }: Props) {
-  return (
-    <div
-      className={cn(styles.loader, className)}
-      style={{ width: size, height: size }}
-    />
-  );
-}

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

@@ -1,235 +0,0 @@
-import { Link } from "@/components/atoms/Link/Link";
-import { Text } from "@/components/atoms/Text/Text";
-import { cn } from "@/lib/utils";
-
-/* ------------------------------------------------------------------ */
-/*  Layout                                                            */
-/* ------------------------------------------------------------------ */
-
-export function ContentGrid({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return <div className={cn("grid gap-2", className)}>{children}</div>;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Card                                                              */
-/* ------------------------------------------------------------------ */
-
-export function ContentCard({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <div
-      className={cn(
-        "rounded-lg bg-gradient-to-r from-purple-500/30 to-blue-500/30 p-[1px]",
-        className,
-      )}
-    >
-      <div className="rounded-lg bg-neutral-100 p-3">{children}</div>
-    </div>
-  );
-}
-
-/** Flex row with a left content area (`children`) and an optional right‑side `action`. */
-export function ContentCardHeader({
-  children,
-  action,
-  className,
-}: {
-  children: React.ReactNode;
-  action?: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <div className={cn("flex items-start justify-between gap-2", className)}>
-      <div className="min-w-0">{children}</div>
-      {action}
-    </div>
-  );
-}
-
-export function ContentCardTitle({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <Text
-      variant="body-medium"
-      className={cn("truncate text-zinc-800", className)}
-    >
-      {children}
-    </Text>
-  );
-}
-
-export function ContentCardSubtitle({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <Text
-      variant="small"
-      className={cn("mt-0.5 truncate font-mono text-zinc-800", className)}
-    >
-      {children}
-    </Text>
-  );
-}
-
-export function ContentCardDescription({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <Text variant="body" className={cn("mt-2 text-zinc-800", className)}>
-      {children}
-    </Text>
-  );
-}
-
-/* ------------------------------------------------------------------ */
-/*  Text                                                              */
-/* ------------------------------------------------------------------ */
-
-export function ContentMessage({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <Text variant="body" className={cn("text-zinc-800", className)}>
-      {children}
-    </Text>
-  );
-}
-
-export function ContentHint({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <Text variant="small" className={cn("text-neutral-500", className)}>
-      {children}
-    </Text>
-  );
-}
-
-/* ------------------------------------------------------------------ */
-/*  Code / data                                                       */
-/* ------------------------------------------------------------------ */
-
-export function ContentCodeBlock({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <pre
-      className={cn(
-        "whitespace-pre-wrap rounded-lg border bg-black p-3 text-xs text-neutral-200",
-        className,
-      )}
-    >
-      {children}
-    </pre>
-  );
-}
-
-/* ------------------------------------------------------------------ */
-/*  Inline elements                                                   */
-/* ------------------------------------------------------------------ */
-
-export function ContentBadge({
-  children,
-  className,
-}: {
-  children: React.ReactNode;
-  className?: string;
-}) {
-  return (
-    <Text
-      variant="small"
-      as="span"
-      className={cn(
-        "shrink-0 rounded-full border bg-muted px-2 py-0.5 text-[11px] text-zinc-800",
-        className,
-      )}
-    >
-      {children}
-    </Text>
-  );
-}
-
-export function ContentLink({
-  href,
-  children,
-  className,
-  ...rest
-}: Omit<React.ComponentProps<typeof Link>, "className"> & {
-  className?: string;
-}) {
-  return (
-    <Link
-      variant="primary"
-      isExternal
-      href={href}
-      className={cn("shrink-0 text-xs text-purple-500", className)}
-      {...rest}
-    >
-      {children}
-    </Link>
-  );
-}
-
-/* ------------------------------------------------------------------ */
-/*  Lists                                                             */
-/* ------------------------------------------------------------------ */
-
-export function ContentSuggestionsList({
-  items,
-  max = 5,
-  className,
-}: {
-  items: string[];
-  max?: number;
-  className?: string;
-}) {
-  if (items.length === 0) return null;
-  return (
-    <ul
-      className={cn(
-        "mt-2 list-disc space-y-1 pl-5 font-sans text-[0.75rem] leading-[1.125rem] text-zinc-800",
-        className,
-      )}
-    >
-      {items.slice(0, max).map((s) => (
-        <li key={s}>{s}</li>
-      ))}
-    </ul>
-  );
-}

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

@@ -1,102 +0,0 @@
-"use client";
-
-import { cn } from "@/lib/utils";
-import { CaretDownIcon } from "@phosphor-icons/react";
-import { AnimatePresence, motion, useReducedMotion } from "framer-motion";
-import { useId } from "react";
-import { useToolAccordion } from "./useToolAccordion";
-
-interface Props {
-  icon: React.ReactNode;
-  title: React.ReactNode;
-  titleClassName?: string;
-  description?: React.ReactNode;
-  children: React.ReactNode;
-  className?: string;
-  defaultExpanded?: boolean;
-  expanded?: boolean;
-  onExpandedChange?: (expanded: boolean) => void;
-}
-
-export function ToolAccordion({
-  icon,
-  title,
-  titleClassName,
-  description,
-  children,
-  className,
-  defaultExpanded,
-  expanded,
-  onExpandedChange,
-}: Props) {
-  const shouldReduceMotion = useReducedMotion();
-  const contentId = useId();
-  const { isExpanded, toggle } = useToolAccordion({
-    expanded,
-    defaultExpanded,
-    onExpandedChange,
-  });
-
-  return (
-    <div
-      className={cn(
-        "mt-2 w-full rounded-lg border border-slate-200 bg-slate-100 px-3 py-2",
-        className,
-      )}
-    >
-      <button
-        type="button"
-        aria-expanded={isExpanded}
-        aria-controls={contentId}
-        onClick={toggle}
-        className="flex w-full items-center justify-between gap-3 py-1 text-left"
-      >
-        <div className="flex min-w-0 items-center gap-3">
-          <span className="flex shrink-0 items-center text-gray-800">
-            {icon}
-          </span>
-          <div className="min-w-0">
-            <p
-              className={cn(
-                "truncate text-sm font-medium text-gray-800",
-                titleClassName,
-              )}
-            >
-              {title}
-            </p>
-            {description && (
-              <p className="truncate text-xs text-slate-800">{description}</p>
-            )}
-          </div>
-        </div>
-        <CaretDownIcon
-          className={cn(
-            "h-4 w-4 shrink-0 text-slate-500 transition-transform",
-            isExpanded && "rotate-180",
-          )}
-          weight="bold"
-        />
-      </button>
-
-      <AnimatePresence initial={false}>
-        {isExpanded && (
-          <motion.div
-            id={contentId}
-            initial={{ height: 0, opacity: 0, filter: "blur(10px)" }}
-            animate={{ height: "auto", opacity: 1, filter: "blur(0px)" }}
-            exit={{ height: 0, opacity: 0, filter: "blur(10px)" }}
-            transition={
-              shouldReduceMotion
-                ? { duration: 0 }
-                : { type: "spring", bounce: 0.35, duration: 0.55 }
-            }
-            className="overflow-hidden"
-            style={{ willChange: "height, opacity, filter" }}
-          >
-            <div className="pb-2 pt-3">{children}</div>
-          </motion.div>
-        )}
-      </AnimatePresence>
-    </div>
-  );
-}

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

@@ -1,32 +0,0 @@
-import { useState } from "react";
-
-interface UseToolAccordionOptions {
-  expanded?: boolean;
-  defaultExpanded?: boolean;
-  onExpandedChange?: (expanded: boolean) => void;
-}
-
-interface UseToolAccordionResult {
-  isExpanded: boolean;
-  toggle: () => void;
-}
-
-export function useToolAccordion({
-  expanded,
-  defaultExpanded = false,
-  onExpandedChange,
-}: UseToolAccordionOptions): UseToolAccordionResult {
-  const [uncontrolledExpanded, setUncontrolledExpanded] =
-    useState(defaultExpanded);
-
-  const isControlled = typeof expanded === "boolean";
-  const isExpanded = isControlled ? expanded : uncontrolledExpanded;
-
-  function toggle() {
-    const next = !isExpanded;
-    if (!isControlled) setUncontrolledExpanded(next);
-    onExpandedChange?.(next);
-  }
-
-  return { isExpanded, toggle };
-}

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

@@ -0,0 +1,56 @@
+"use client";
+
+import { create } from "zustand";
+
+interface CopilotStoreState {
+  isStreaming: boolean;
+  isSwitchingSession: boolean;
+  isCreatingSession: boolean;
+  isInterruptModalOpen: boolean;
+  pendingAction: (() => void) | null;
+}
+
+interface CopilotStoreActions {
+  setIsStreaming: (isStreaming: boolean) => void;
+  setIsSwitchingSession: (isSwitchingSession: boolean) => void;
+  setIsCreatingSession: (isCreating: boolean) => void;
+  openInterruptModal: (onConfirm: () => void) => void;
+  confirmInterrupt: () => void;
+  cancelInterrupt: () => void;
+}
+
+type CopilotStore = CopilotStoreState & CopilotStoreActions;
+
+export const useCopilotStore = create<CopilotStore>((set, get) => ({
+  isStreaming: false,
+  isSwitchingSession: false,
+  isCreatingSession: false,
+  isInterruptModalOpen: false,
+  pendingAction: null,
+
+  setIsStreaming(isStreaming) {
+    set({ isStreaming });
+  },
+
+  setIsSwitchingSession(isSwitchingSession) {
+    set({ isSwitchingSession });
+  },
+
+  setIsCreatingSession(isCreatingSession) {
+    set({ isCreatingSession });
+  },
+
+  openInterruptModal(onConfirm) {
+    set({ isInterruptModalOpen: true, pendingAction: onConfirm });
+  },
+
+  confirmInterrupt() {
+    const { pendingAction } = get();
+    set({ isInterruptModalOpen: false, pendingAction: null });
+    if (pendingAction) pendingAction();
+  },
+
+  cancelInterrupt() {
+    set({ isInterruptModalOpen: false, pendingAction: null });
+  },
+}));

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

@@ -1,26 +1,6 @@
-import { User } from "@supabase/supabase-js";
+import type { User } from "@supabase/supabase-js";
 
-export function getInputPlaceholder(width?: number) {
+export function getGreetingName(user?: User | null): string {
-  if (!width) return "What's your role and what eats up most of your day?";
-
-  if (width < 500) {
-    return "I'm a chef and I hate...";
-  }
-  if (width <= 1080) {
-    return "What's your role and what eats up most of your day?";
-  }
-  return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
-}
-
-export function getQuickActions() {
-  return [
-    "I don't know where to start, just ask me stuff",
-    "I do the same thing every week and it's killing me",
-    "Help me find where I'm wasting my time",
-  ];
-}
-
-export function getGreetingName(user?: User | null) {
   if (!user) return "there";
   const metadata = user.user_metadata as Record<string, unknown> | undefined;
   const fullName = metadata?.full_name;
@@ -36,3 +16,30 @@ export function getGreetingName(user?: User | null) {
   }
   return "there";
 }
+
+export function buildCopilotChatUrl(prompt: string): string {
+  const trimmed = prompt.trim();
+  if (!trimmed) return "/copilot/chat";
+  const encoded = encodeURIComponent(trimmed);
+  return `/copilot/chat?prompt=${encoded}`;
+}
+
+export function getQuickActions(): string[] {
+  return [
+    "I don't know where to start, just ask me stuff",
+    "I do the same thing every week and it's killing me",
+    "Help me find where I'm wasting my time",
+  ];
+}
+
+export function getInputPlaceholder(width?: number) {
+  if (!width) return "What's your role and what eats up most of your day?";
+
+  if (width < 500) {
+    return "I'm a chef and I hate...";
+  }
+  if (width <= 1080) {
+    return "What's your role and what eats up most of your day?";
+  }
+  return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
+}

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

@@ -1,128 +0,0 @@
-import type { UIMessage, UIDataTypes, UITools } from "ai";
-
-interface SessionChatMessage {
-  role: string;
-  content: string | null;
-  tool_call_id: string | null;
-  tool_calls: unknown[] | null;
-}
-
-function coerceSessionChatMessages(
-  rawMessages: unknown[],
-): SessionChatMessage[] {
-  return rawMessages
-    .map((m) => {
-      if (!m || typeof m !== "object") return null;
-      const msg = m as Record<string, unknown>;
-
-      const role = typeof msg.role === "string" ? msg.role : null;
-      if (!role) return null;
-
-      return {
-        role,
-        content:
-          typeof msg.content === "string"
-            ? msg.content
-            : msg.content == null
-              ? null
-              : String(msg.content),
-        tool_call_id:
-          typeof msg.tool_call_id === "string"
-            ? msg.tool_call_id
-            : msg.tool_call_id == null
-              ? null
-              : String(msg.tool_call_id),
-        tool_calls: Array.isArray(msg.tool_calls) ? msg.tool_calls : null,
-      };
-    })
-    .filter((m): m is SessionChatMessage => m !== null);
-}
-
-function safeJsonParse(value: string): unknown {
-  try {
-    return JSON.parse(value) as unknown;
-  } catch {
-    return value;
-  }
-}
-
-function toToolInput(rawArguments: unknown): unknown {
-  if (typeof rawArguments === "string") {
-    const trimmed = rawArguments.trim();
-    return trimmed ? safeJsonParse(trimmed) : {};
-  }
-  if (rawArguments && typeof rawArguments === "object") return rawArguments;
-  return {};
-}
-
-export function convertChatSessionMessagesToUiMessages(
-  sessionId: string,
-  rawMessages: unknown[],
-): UIMessage<unknown, UIDataTypes, UITools>[] {
-  const messages = coerceSessionChatMessages(rawMessages);
-  const toolOutputsByCallId = new Map<string, unknown>();
-
-  for (const msg of messages) {
-    if (msg.role !== "tool") continue;
-    if (!msg.tool_call_id) continue;
-    if (msg.content == null) continue;
-    toolOutputsByCallId.set(msg.tool_call_id, msg.content);
-  }
-
-  const uiMessages: UIMessage<unknown, UIDataTypes, UITools>[] = [];
-
-  messages.forEach((msg, index) => {
-    if (msg.role === "tool") return;
-    if (msg.role !== "user" && msg.role !== "assistant") return;
-
-    const parts: UIMessage<unknown, UIDataTypes, UITools>["parts"] = [];
-
-    if (typeof msg.content === "string" && msg.content.trim()) {
-      parts.push({ type: "text", text: msg.content, state: "done" });
-    }
-
-    if (msg.role === "assistant" && Array.isArray(msg.tool_calls)) {
-      for (const rawToolCall of msg.tool_calls) {
-        if (!rawToolCall || typeof rawToolCall !== "object") continue;
-        const toolCall = rawToolCall as {
-          id?: unknown;
-          function?: { name?: unknown; arguments?: unknown };
-        };
-
-        const toolCallId = String(toolCall.id ?? "").trim();
-        const toolName = String(toolCall.function?.name ?? "").trim();
-        if (!toolCallId || !toolName) continue;
-
-        const input = toToolInput(toolCall.function?.arguments);
-        const output = toolOutputsByCallId.get(toolCallId);
-
-        if (output !== undefined) {
-          parts.push({
-            type: `tool-${toolName}`,
-            toolCallId,
-            state: "output-available",
-            input,
-            output: typeof output === "string" ? safeJsonParse(output) : output,
-          });
-        } else {
-          parts.push({
-            type: `tool-${toolName}`,
-            toolCallId,
-            state: "input-available",
-            input,
-          });
-        }
-      }
-    }
-
-    if (parts.length === 0) return;
-
-    uiMessages.push({
-      id: `${sessionId}-${index}`,
-      role: msg.role,
-      parts,
-    });
-  });
-
-  return uiMessages;
-}

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

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

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

@@ -1,13 +1,149 @@
 "use client";
 
-import { FeatureFlagPage } from "@/services/feature-flags/FeatureFlagPage";
+import { Button } from "@/components/atoms/Button/Button";
-import { Flag } from "@/services/feature-flags/use-get-flag";
+import { Skeleton } from "@/components/atoms/Skeleton/Skeleton";
-import { CopilotPage } from "./CopilotPage";
+import { Text } from "@/components/atoms/Text/Text";
+import { Chat } from "@/components/contextual/Chat/Chat";
+import { ChatInput } from "@/components/contextual/Chat/components/ChatInput/ChatInput";
+import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { useEffect, useState } from "react";
+import { useCopilotStore } from "./copilot-page-store";
+import { getInputPlaceholder } from "./helpers";
+import { useCopilotPage } from "./useCopilotPage";
+
+export default function CopilotPage() {
+  const { state, handlers } = useCopilotPage();
+  const isInterruptModalOpen = useCopilotStore((s) => s.isInterruptModalOpen);
+  const confirmInterrupt = useCopilotStore((s) => s.confirmInterrupt);
+  const cancelInterrupt = useCopilotStore((s) => s.cancelInterrupt);
+
+  const [inputPlaceholder, setInputPlaceholder] = useState(
+    getInputPlaceholder(),
+  );
+
+  useEffect(() => {
+    const handleResize = () => {
+      setInputPlaceholder(getInputPlaceholder(window.innerWidth));
+    };
+
+    handleResize();
+
+    window.addEventListener("resize", handleResize);
+    return () => window.removeEventListener("resize", handleResize);
+  }, []);
+
+  const { greetingName, quickActions, isLoading, hasSession, initialPrompt } =
+    state;
+
+  const {
+    handleQuickAction,
+    startChatWithPrompt,
+    handleSessionNotFound,
+    handleStreamingChange,
+  } = handlers;
+
+  if (hasSession) {
+    return (
+      <div className="flex h-full flex-col">
+        <Chat
+          className="flex-1"
+          initialPrompt={initialPrompt}
+          onSessionNotFound={handleSessionNotFound}
+          onStreamingChange={handleStreamingChange}
+        />
+        <Dialog
+          title="Interrupt current chat?"
+          styling={{ maxWidth: 300, width: "100%" }}
+          controlled={{
+            isOpen: isInterruptModalOpen,
+            set: (open) => {
+              if (!open) cancelInterrupt();
+            },
+          }}
+          onClose={cancelInterrupt}
+        >
+          <Dialog.Content>
+            <div className="flex flex-col gap-4">
+              <Text variant="body">
+                The current chat response will be interrupted. Are you sure you
+                want to continue?
+              </Text>
+              <Dialog.Footer>
+                <Button
+                  type="button"
+                  variant="outline"
+                  onClick={cancelInterrupt}
+                >
+                  Cancel
+                </Button>
+                <Button
+                  type="button"
+                  variant="primary"
+                  onClick={confirmInterrupt}
+                >
+                  Continue
+                </Button>
+              </Dialog.Footer>
+            </div>
+          </Dialog.Content>
+        </Dialog>
+      </div>
+    );
+  }
 
-export default function Page() {
   return (
-    <FeatureFlagPage flag={Flag.CHAT} whenDisabled="/library">
+    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-3 py-5 md:px-6 md:py-10">
-      <CopilotPage />
+      <div className="w-full text-center">
-    </FeatureFlagPage>
+        {isLoading ? (
+          <div className="mx-auto max-w-2xl">
+            <Skeleton className="mx-auto mb-3 h-8 w-64" />
+            <Skeleton className="mx-auto mb-8 h-6 w-80" />
+            <div className="mb-8">
+              <Skeleton className="mx-auto h-14 w-full rounded-lg" />
+            </div>
+            <div className="flex flex-wrap items-center justify-center gap-3">
+              {Array.from({ length: 4 }).map((_, i) => (
+                <Skeleton key={i} className="h-9 w-48 rounded-md" />
+              ))}
+            </div>
+          </div>
+        ) : (
+          <>
+            <div className="mx-auto max-w-3xl">
+              <Text
+                variant="h3"
+                className="mb-1 !text-[1.375rem] text-zinc-700"
+              >
+                Hey, <span className="text-violet-600">{greetingName}</span>
+              </Text>
+              <Text variant="h3" className="mb-8 !font-normal">
+                Tell me about your work — I&apos;ll find what to automate.
+              </Text>
+
+              <div className="mb-6">
+                <ChatInput
+                  onSend={startChatWithPrompt}
+                  placeholder={inputPlaceholder}
+                />
+              </div>
+            </div>
+            <div className="flex flex-wrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+              {quickActions.map((action) => (
+                <Button
+                  key={action}
+                  type="button"
+                  variant="outline"
+                  size="small"
+                  onClick={() => handleQuickAction(action)}
+                  className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
+                >
+                  {action}
+                </Button>
+              ))}
+            </div>
+          </>
+        )}
+      </div>
+    </div>
   );
 }

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

@@ -1,235 +0,0 @@
-"use client";
-
-import { WarningDiamondIcon } from "@phosphor-icons/react";
-import type { ToolUIPart } from "ai";
-import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
-import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
-import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
-import {
-  ContentCardDescription,
-  ContentCodeBlock,
-  ContentGrid,
-  ContentHint,
-  ContentLink,
-  ContentMessage,
-} from "../../components/ToolAccordion/AccordionContent";
-import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
-import {
-  ClarificationQuestionsCard,
-  ClarifyingQuestion,
-} from "./components/ClarificationQuestionsCard";
-import {
-  AccordionIcon,
-  formatMaybeJson,
-  getAnimationText,
-  getCreateAgentToolOutput,
-  isAgentPreviewOutput,
-  isAgentSavedOutput,
-  isClarificationNeededOutput,
-  isErrorOutput,
-  isOperationInProgressOutput,
-  isOperationPendingOutput,
-  isOperationStartedOutput,
-  ToolIcon,
-  truncateText,
-  type CreateAgentToolOutput,
-} from "./helpers";
-
-export interface CreateAgentToolPart {
-  type: string;
-  toolCallId: string;
-  state: ToolUIPart["state"];
-  input?: unknown;
-  output?: unknown;
-}
-
-interface Props {
-  part: CreateAgentToolPart;
-}
-
-function getAccordionMeta(output: CreateAgentToolOutput) {
-  const icon = <AccordionIcon />;
-
-  if (isAgentSavedOutput(output)) {
-    return { icon, title: output.agent_name };
-  }
-  if (isAgentPreviewOutput(output)) {
-    return {
-      icon,
-      title: output.agent_name,
-      description: `${output.node_count} block${output.node_count === 1 ? "" : "s"}`,
-    };
-  }
-  if (isClarificationNeededOutput(output)) {
-    const questions = output.questions ?? [];
-    return {
-      icon,
-      title: "Needs clarification",
-      description: `${questions.length} question${questions.length === 1 ? "" : "s"}`,
-      expanded: true,
-    };
-  }
-  if (
-    isOperationStartedOutput(output) ||
-    isOperationPendingOutput(output) ||
-    isOperationInProgressOutput(output)
-  ) {
-    return {
-      icon: <OrbitLoader size={32} />,
-      title: "Creating agent, this may take a few minutes. Sit back and relax.",
-    };
-  }
-  return {
-    icon: (
-      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
-    ),
-    title: "Error",
-    titleClassName: "text-red-500",
-  };
-}
-
-export function CreateAgentTool({ part }: Props) {
-  const text = getAnimationText(part);
-  const { onSend } = useCopilotChatActions();
-
-  const isStreaming =
-    part.state === "input-streaming" || part.state === "input-available";
-
-  const output = getCreateAgentToolOutput(part);
-
-  const isError =
-    part.state === "output-error" || (!!output && isErrorOutput(output));
-
-  const isOperating =
-    !!output &&
-    (isOperationStartedOutput(output) ||
-      isOperationPendingOutput(output) ||
-      isOperationInProgressOutput(output));
-
-  const progress = useAsymptoticProgress(isOperating);
-
-  const hasExpandableContent =
-    part.state === "output-available" &&
-    !!output &&
-    (isOperationStartedOutput(output) ||
-      isOperationPendingOutput(output) ||
-      isOperationInProgressOutput(output) ||
-      isAgentPreviewOutput(output) ||
-      isAgentSavedOutput(output) ||
-      isClarificationNeededOutput(output) ||
-      isErrorOutput(output));
-
-  function handleClarificationAnswers(answers: Record<string, string>) {
-    const questions =
-      output && isClarificationNeededOutput(output)
-        ? (output.questions ?? [])
-        : [];
-
-    const contextMessage = questions
-      .map((q) => {
-        const answer = answers[q.keyword] || "";
-        return `> ${q.question}\n\n${answer}`;
-      })
-      .join("\n\n");
-
-    onSend(
-      `**Here are my answers:**\n\n${contextMessage}\n\nPlease proceed with creating the agent.`,
-    );
-  }
-
-  return (
-    <div className="py-2">
-      <div className="flex items-center gap-2 text-sm text-muted-foreground">
-        <ToolIcon isStreaming={isStreaming} isError={isError} />
-        <MorphingTextAnimation
-          text={text}
-          className={isError ? "text-red-500" : undefined}
-        />
-      </div>
-
-      {hasExpandableContent && output && (
-        <ToolAccordion {...getAccordionMeta(output)}>
-          {isOperating && (
-            <ContentGrid>
-              <ProgressBar value={progress} className="max-w-[280px]" />
-              <ContentHint>
-                This could take a few minutes, grab a coffee ☕
-              </ContentHint>
-            </ContentGrid>
-          )}
-
-          {isAgentSavedOutput(output) && (
-            <ContentGrid>
-              <ContentMessage>{output.message}</ContentMessage>
-              <div className="flex flex-wrap gap-2">
-                <ContentLink href={output.library_agent_link}>
-                  Open in library
-                </ContentLink>
-                <ContentLink href={output.agent_page_link}>
-                  Open in builder
-                </ContentLink>
-              </div>
-              <ContentCodeBlock>
-                {truncateText(
-                  formatMaybeJson({ agent_id: output.agent_id }),
-                  800,
-                )}
-              </ContentCodeBlock>
-            </ContentGrid>
-          )}
-
-          {isAgentPreviewOutput(output) && (
-            <ContentGrid>
-              <ContentMessage>{output.message}</ContentMessage>
-              {output.description?.trim() && (
-                <ContentCardDescription>
-                  {output.description}
-                </ContentCardDescription>
-              )}
-              <ContentCodeBlock>
-                {truncateText(formatMaybeJson(output.agent_json), 1600)}
-              </ContentCodeBlock>
-            </ContentGrid>
-          )}
-
-          {isClarificationNeededOutput(output) && (
-            <ClarificationQuestionsCard
-              questions={(output.questions ?? []).map((q) => {
-                const item: ClarifyingQuestion = {
-                  question: q.question,
-                  keyword: q.keyword,
-                };
-                const example =
-                  typeof q.example === "string" && q.example.trim()
-                    ? q.example.trim()
-                    : null;
-                if (example) item.example = example;
-                return item;
-              })}
-              message={output.message}
-              onSubmitAnswers={handleClarificationAnswers}
-            />
-          )}
-
-          {isErrorOutput(output) && (
-            <ContentGrid>
-              <ContentMessage>{output.message}</ContentMessage>
-              {output.error && (
-                <ContentCodeBlock>
-                  {formatMaybeJson(output.error)}
-                </ContentCodeBlock>
-              )}
-              {output.details && (
-                <ContentCodeBlock>
-                  {formatMaybeJson(output.details)}
-                </ContentCodeBlock>
-              )}
-            </ContentGrid>
-          )}
-        </ToolAccordion>
-      )}
-    </div>
-  );
-}

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

@@ -1,186 +0,0 @@
-import type { AgentPreviewResponse } from "@/app/api/__generated__/models/agentPreviewResponse";
-import type { AgentSavedResponse } from "@/app/api/__generated__/models/agentSavedResponse";
-import type { ClarificationNeededResponse } from "@/app/api/__generated__/models/clarificationNeededResponse";
-import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
-import type { OperationInProgressResponse } from "@/app/api/__generated__/models/operationInProgressResponse";
-import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
-import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
-import { ResponseType } from "@/app/api/__generated__/models/responseType";
-import {
-  PlusCircleIcon,
-  PlusIcon,
-  WarningDiamondIcon,
-} from "@phosphor-icons/react";
-import type { ToolUIPart } from "ai";
-import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
-
-export type CreateAgentToolOutput =
-  | OperationStartedResponse
-  | OperationPendingResponse
-  | OperationInProgressResponse
-  | AgentPreviewResponse
-  | AgentSavedResponse
-  | ClarificationNeededResponse
-  | ErrorResponse;
-
-function parseOutput(output: unknown): CreateAgentToolOutput | null {
-  if (!output) return null;
-  if (typeof output === "string") {
-    const trimmed = output.trim();
-    if (!trimmed) return null;
-    try {
-      return parseOutput(JSON.parse(trimmed) as unknown);
-    } catch {
-      return null;
-    }
-  }
-  if (typeof output === "object") {
-    const type = (output as { type?: unknown }).type;
-    if (
-      type === ResponseType.operation_started ||
-      type === ResponseType.operation_pending ||
-      type === ResponseType.operation_in_progress ||
-      type === ResponseType.agent_preview ||
-      type === ResponseType.agent_saved ||
-      type === ResponseType.clarification_needed ||
-      type === ResponseType.error
-    ) {
-      return output as CreateAgentToolOutput;
-    }
-    if ("operation_id" in output && "tool_name" in output)
-      return output as OperationStartedResponse | OperationPendingResponse;
-    if ("tool_call_id" in output) return output as OperationInProgressResponse;
-    if ("agent_json" in output && "agent_name" in output)
-      return output as AgentPreviewResponse;
-    if ("agent_id" in output && "library_agent_id" in output)
-      return output as AgentSavedResponse;
-    if ("questions" in output) return output as ClarificationNeededResponse;
-    if ("error" in output || "details" in output)
-      return output as ErrorResponse;
-  }
-  return null;
-}
-
-export function getCreateAgentToolOutput(
-  part: unknown,
-): CreateAgentToolOutput | null {
-  if (!part || typeof part !== "object") return null;
-  return parseOutput((part as { output?: unknown }).output);
-}
-
-export function isOperationStartedOutput(
-  output: CreateAgentToolOutput,
-): output is OperationStartedResponse {
-  return (
-    output.type === ResponseType.operation_started ||
-    ("operation_id" in output && "tool_name" in output)
-  );
-}
-
-export function isOperationPendingOutput(
-  output: CreateAgentToolOutput,
-): output is OperationPendingResponse {
-  return output.type === ResponseType.operation_pending;
-}
-
-export function isOperationInProgressOutput(
-  output: CreateAgentToolOutput,
-): output is OperationInProgressResponse {
-  return (
-    output.type === ResponseType.operation_in_progress ||
-    "tool_call_id" in output
-  );
-}
-
-export function isAgentPreviewOutput(
-  output: CreateAgentToolOutput,
-): output is AgentPreviewResponse {
-  return output.type === ResponseType.agent_preview || "agent_json" in output;
-}
-
-export function isAgentSavedOutput(
-  output: CreateAgentToolOutput,
-): output is AgentSavedResponse {
-  return (
-    output.type === ResponseType.agent_saved || "agent_page_link" in output
-  );
-}
-
-export function isClarificationNeededOutput(
-  output: CreateAgentToolOutput,
-): output is ClarificationNeededResponse {
-  return (
-    output.type === ResponseType.clarification_needed || "questions" in output
-  );
-}
-
-export function isErrorOutput(
-  output: CreateAgentToolOutput,
-): output is ErrorResponse {
-  return output.type === ResponseType.error || "error" in output;
-}
-
-export function getAnimationText(part: {
-  state: ToolUIPart["state"];
-  input?: unknown;
-  output?: unknown;
-}): string {
-  switch (part.state) {
-    case "input-streaming":
-    case "input-available":
-      return "Creating a new agent";
-    case "output-available": {
-      const output = parseOutput(part.output);
-      if (!output) return "Creating a new agent";
-      if (isOperationStartedOutput(output)) return "Agent creation started";
-      if (isOperationPendingOutput(output)) return "Agent creation in progress";
-      if (isOperationInProgressOutput(output))
-        return "Agent creation already in progress";
-      if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
-      if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
-      if (isClarificationNeededOutput(output)) return "Needs clarification";
-      return "Error creating agent";
-    }
-    case "output-error":
-      return "Error creating agent";
-    default:
-      return "Creating a new agent";
-  }
-}
-
-export function ToolIcon({
-  isStreaming,
-  isError,
-}: {
-  isStreaming?: boolean;
-  isError?: boolean;
-}) {
-  if (isError) {
-    return (
-      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
-    );
-  }
-  if (isStreaming) {
-    return <OrbitLoader size={24} />;
-  }
-  return <PlusIcon size={14} weight="regular" className="text-neutral-400" />;
-}
-
-export function AccordionIcon() {
-  return <PlusCircleIcon size={32} weight="light" />;
-}
-
-export function formatMaybeJson(value: unknown): string {
-  if (typeof value === "string") return value;
-  try {
-    return JSON.stringify(value, null, 2);
-  } catch {
-    return String(value);
-  }
-}
-
-export function truncateText(text: string, maxChars: number): string {
-  const trimmed = text.trim();
-  if (trimmed.length <= maxChars) return trimmed;
-  return `${trimmed.slice(0, maxChars).trimEnd()}…`;
-}