fix(copilot): stream timeout, long-running tool polling, and CreateAgent UI refresh (#12070)

Agent generation completes on the backend but the UI does not
update/refresh to show the result.

### Changes 🏗️

![Uploading Screenshot 2026-02-13 at 00.44.54.png…]()


- **Stream start timeout (12s):** If the backend doesn't begin streaming
within 12 seconds of submitting a message, the stream is aborted and a
destructive toast is shown to the user.
- **Long-running tool polling:** Added `useLongRunningToolPolling` hook
that polls the session endpoint every 1.5s while a tool output is in an
operating state (`operation_started` / `operation_pending` /
`operation_in_progress`). When the backend completes, messages are
refreshed so the UI reflects the final result.
- **CreateAgent UI improvements:** Replaced the orbit loader / progress
bar with a mini-game, added expanded accordion for saved agents, and
improved the saved-agent card with image, icons, and links that open in
new tabs.
- **Backend tweaks:** Added `image_url` to `CreateAgentToolOutput`,
minor model/service updates for the dummy agent generator.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Send a message and verify the stream starts within 12s or a toast
appears
- [x] Trigger agent creation and verify the UI updates when the backend
completes
- [x] Verify the saved-agent card renders correctly with image, links,
and icons

---------

Co-authored-by: Otto <otto@agpt.co>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

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

@@ -12,7 +12,6 @@ from .base import BaseTool
 from .create_agent import CreateAgentTool
 from .customize_agent import CustomizeAgentTool
 from .edit_agent import EditAgentTool
-from .feature_requests import CreateFeatureRequestTool, SearchFeatureRequestsTool
 from .find_agent import FindAgentTool
 from .find_block import FindBlockTool
 from .find_library_agent import FindLibraryAgentTool
@@ -46,9 +45,6 @@ TOOL_REGISTRY: dict[str, BaseTool] = {
     "view_agent_output": AgentOutputTool(),
     "search_docs": SearchDocsTool(),
     "get_doc_page": GetDocPageTool(),
-    # Feature request tools
-    "search_feature_requests": SearchFeatureRequestsTool(),
-    "create_feature_request": CreateFeatureRequestTool(),
     # Workspace tools for CoPilot file operations
     "list_workspace_files": ListWorkspaceFilesTool(),
     "read_workspace_file": ReadWorkspaceFileTool(),

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/dummy.py

@@ -0,0 +1,154 @@
+"""Dummy Agent Generator for testing.
+
+Returns mock responses matching the format expected from the external service.
+Enable via AGENTGENERATOR_USE_DUMMY=true in settings.
+
+WARNING: This is for testing only. Do not use in production.
+"""
+
+import asyncio
+import logging
+import uuid
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+# Dummy decomposition result (instructions type)
+DUMMY_DECOMPOSITION_RESULT: dict[str, Any] = {
+    "type": "instructions",
+    "steps": [
+        {
+            "description": "Get input from user",
+            "action": "input",
+            "block_name": "AgentInputBlock",
+        },
+        {
+            "description": "Process the input",
+            "action": "process",
+            "block_name": "TextFormatterBlock",
+        },
+        {
+            "description": "Return output to user",
+            "action": "output",
+            "block_name": "AgentOutputBlock",
+        },
+    ],
+}
+
+# Block IDs from backend/blocks/io.py
+AGENT_INPUT_BLOCK_ID = "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b"
+AGENT_OUTPUT_BLOCK_ID = "363ae599-353e-4804-937e-b2ee3cef3da4"
+
+
+def _generate_dummy_agent_json() -> dict[str, Any]:
+    """Generate a minimal valid agent JSON for testing."""
+    input_node_id = str(uuid.uuid4())
+    output_node_id = str(uuid.uuid4())
+
+    return {
+        "id": str(uuid.uuid4()),
+        "version": 1,
+        "is_active": True,
+        "name": "Dummy Test Agent",
+        "description": "A dummy agent generated for testing purposes",
+        "nodes": [
+            {
+                "id": input_node_id,
+                "block_id": AGENT_INPUT_BLOCK_ID,
+                "input_default": {
+                    "name": "input",
+                    "title": "Input",
+                    "description": "Enter your input",
+                    "placeholder_values": [],
+                },
+                "metadata": {"position": {"x": 0, "y": 0}},
+            },
+            {
+                "id": output_node_id,
+                "block_id": AGENT_OUTPUT_BLOCK_ID,
+                "input_default": {
+                    "name": "output",
+                    "title": "Output",
+                    "description": "Agent output",
+                    "format": "{output}",
+                },
+                "metadata": {"position": {"x": 400, "y": 0}},
+            },
+        ],
+        "links": [
+            {
+                "id": str(uuid.uuid4()),
+                "source_id": input_node_id,
+                "sink_id": output_node_id,
+                "source_name": "result",
+                "sink_name": "value",
+                "is_static": False,
+            },
+        ],
+    }
+
+
+async def decompose_goal_dummy(
+    description: str,
+    context: str = "",
+    library_agents: list[dict[str, Any]] | None = None,
+) -> dict[str, Any]:
+    """Return dummy decomposition result."""
+    logger.info("Using dummy agent generator for decompose_goal")
+    return DUMMY_DECOMPOSITION_RESULT.copy()
+
+
+async def generate_agent_dummy(
+    instructions: dict[str, Any],
+    library_agents: list[dict[str, Any]] | None = None,
+    operation_id: str | None = None,
+    task_id: str | None = None,
+) -> dict[str, Any]:
+    """Return dummy agent JSON after a simulated delay."""
+    logger.info("Using dummy agent generator for generate_agent (30s delay)")
+    await asyncio.sleep(30)
+    return _generate_dummy_agent_json()
+
+
+async def generate_agent_patch_dummy(
+    update_request: str,
+    current_agent: dict[str, Any],
+    library_agents: list[dict[str, Any]] | None = None,
+    operation_id: str | None = None,
+    task_id: str | None = None,
+) -> dict[str, Any]:
+    """Return dummy patched agent (returns the current agent with updated description)."""
+    logger.info("Using dummy agent generator for generate_agent_patch")
+    patched = current_agent.copy()
+    patched["description"] = (
+        f"{current_agent.get('description', '')} (updated: {update_request})"
+    )
+    return patched
+
+
+async def customize_template_dummy(
+    template_agent: dict[str, Any],
+    modification_request: str,
+    context: str = "",
+) -> dict[str, Any]:
+    """Return dummy customized template (returns template with updated description)."""
+    logger.info("Using dummy agent generator for customize_template")
+    customized = template_agent.copy()
+    customized["description"] = (
+        f"{template_agent.get('description', '')} (customized: {modification_request})"
+    )
+    return customized
+
+
+async def get_blocks_dummy() -> list[dict[str, Any]]:
+    """Return dummy blocks list."""
+    logger.info("Using dummy agent generator for get_blocks")
+    return [
+        {"id": AGENT_INPUT_BLOCK_ID, "name": "AgentInputBlock"},
+        {"id": AGENT_OUTPUT_BLOCK_ID, "name": "AgentOutputBlock"},
+    ]
+
+
+async def health_check_dummy() -> bool:
+    """Always returns healthy for dummy service."""
+    return True

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

@@ -12,8 +12,19 @@ import httpx
 
 from backend.util.settings import Settings
 
+from .dummy import (
+    customize_template_dummy,
+    decompose_goal_dummy,
+    generate_agent_dummy,
+    generate_agent_patch_dummy,
+    get_blocks_dummy,
+    health_check_dummy,
+)
+
 logger = logging.getLogger(__name__)
 
+_dummy_mode_warned = False
+
 
 def _create_error_response(
     error_message: str,
@@ -90,10 +101,26 @@ def _get_settings() -> Settings:
     return _settings
 
 
-def is_external_service_configured() -> bool:
-    """Check if external Agent Generator service is configured."""
+def _is_dummy_mode() -> bool:
+    """Check if dummy mode is enabled for testing."""
+    global _dummy_mode_warned
     settings = _get_settings()
-    return bool(settings.config.agentgenerator_host)
+    is_dummy = bool(settings.config.agentgenerator_use_dummy)
+    if is_dummy and not _dummy_mode_warned:
+        logger.warning(
+            "Agent Generator running in DUMMY MODE - returning mock responses. "
+            "Do not use in production!"
+        )
+        _dummy_mode_warned = True
+    return is_dummy
+
+
+def is_external_service_configured() -> bool:
+    """Check if external Agent Generator service is configured (or dummy mode)."""
+    settings = _get_settings()
+    return bool(settings.config.agentgenerator_host) or bool(
+        settings.config.agentgenerator_use_dummy
+    )
 
 
 def _get_base_url() -> str:
@@ -137,6 +164,9 @@ async def decompose_goal_external(
         - {"type": "error", "error": "...", "error_type": "..."} on error
         Or None on unexpected error
     """
+    if _is_dummy_mode():
+        return await decompose_goal_dummy(description, context, library_agents)
+
     client = _get_client()
 
     if context:
@@ -226,6 +256,11 @@ async def generate_agent_external(
     Returns:
         Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
     """
+    if _is_dummy_mode():
+        return await generate_agent_dummy(
+            instructions, library_agents, operation_id, task_id
+        )
+
     client = _get_client()
 
     # Build request payload
@@ -297,6 +332,11 @@ async def generate_agent_patch_external(
     Returns:
         Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
     """
+    if _is_dummy_mode():
+        return await generate_agent_patch_dummy(
+            update_request, current_agent, library_agents, operation_id, task_id
+        )
+
     client = _get_client()
 
     # Build request payload
@@ -383,6 +423,11 @@ async def customize_template_external(
     Returns:
         Customized agent JSON, clarifying questions dict, or error dict on error
     """
+    if _is_dummy_mode():
+        return await customize_template_dummy(
+            template_agent, modification_request, context
+        )
+
     client = _get_client()
 
     request = modification_request
@@ -445,6 +490,9 @@ async def get_blocks_external() -> list[dict[str, Any]] | None:
     Returns:
         List of block info dicts or None on error
     """
+    if _is_dummy_mode():
+        return await get_blocks_dummy()
+
     client = _get_client()
 
     try:
@@ -478,6 +526,9 @@ async def health_check() -> bool:
     if not is_external_service_configured():
         return False
 
+    if _is_dummy_mode():
+        return await health_check_dummy()
+
     client = _get_client()
 
     try:

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

@@ -1,369 +0,0 @@
-"""Feature request tools - search and create feature requests via Linear."""
-
-import logging
-from typing import Any
-
-from pydantic import SecretStr
-
-from backend.api.features.chat.model import ChatSession
-from backend.api.features.chat.tools.base import BaseTool
-from backend.api.features.chat.tools.models import (
-    ErrorResponse,
-    FeatureRequestCreatedResponse,
-    FeatureRequestInfo,
-    FeatureRequestSearchResponse,
-    NoResultsResponse,
-    ToolResponseBase,
-)
-from backend.blocks.linear._api import LinearClient
-from backend.data.model import APIKeyCredentials
-from backend.util.settings import Settings
-
-logger = logging.getLogger(__name__)
-
-# Target project and team IDs in our Linear workspace
-FEATURE_REQUEST_PROJECT_ID = "13f066f3-f639-4a67-aaa3-31483ebdf8cd"
-TEAM_ID = "557fd3d5-087e-43a9-83e3-476c8313ce49"
-
-MAX_SEARCH_RESULTS = 10
-
-# GraphQL queries/mutations
-SEARCH_ISSUES_QUERY = """
-query SearchFeatureRequests($term: String!, $filter: IssueFilter, $first: Int) {
-  searchIssues(term: $term, filter: $filter, first: $first) {
-    nodes {
-      id
-      identifier
-      title
-      description
-    }
-  }
-}
-"""
-
-CUSTOMER_UPSERT_MUTATION = """
-mutation CustomerUpsert($input: CustomerUpsertInput!) {
-  customerUpsert(input: $input) {
-    success
-    customer {
-      id
-      name
-      externalIds
-    }
-  }
-}
-"""
-
-ISSUE_CREATE_MUTATION = """
-mutation IssueCreate($input: IssueCreateInput!) {
-  issueCreate(input: $input) {
-    success
-    issue {
-      id
-      identifier
-      title
-      url
-    }
-  }
-}
-"""
-
-CUSTOMER_NEED_CREATE_MUTATION = """
-mutation CustomerNeedCreate($input: CustomerNeedCreateInput!) {
-  customerNeedCreate(input: $input) {
-    success
-    need {
-      id
-      body
-      customer {
-        id
-        name
-      }
-      issue {
-        id
-        identifier
-        title
-        url
-      }
-    }
-  }
-}
-"""
-
-
-_settings: Settings | None = None
-
-
-def _get_settings() -> Settings:
-    global _settings
-    if _settings is None:
-        _settings = Settings()
-    return _settings
-
-
-def _get_linear_client() -> LinearClient:
-    """Create a Linear client using the system API key from settings."""
-    api_key = _get_settings().secrets.linear_api_key
-    if not api_key:
-        raise RuntimeError("LINEAR_API_KEY secret is not configured")
-    credentials = APIKeyCredentials(
-        id="system-linear",
-        provider="linear",
-        api_key=SecretStr(api_key),
-        title="System Linear API Key",
-    )
-    return LinearClient(credentials=credentials)
-
-
-class SearchFeatureRequestsTool(BaseTool):
-    """Tool for searching existing feature requests in Linear."""
-
-    @property
-    def name(self) -> str:
-        return "search_feature_requests"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Search existing feature requests to check if a similar request "
-            "already exists before creating a new one. Returns matching feature "
-            "requests with their ID, title, and description."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "query": {
-                    "type": "string",
-                    "description": "Search term to find matching feature requests.",
-                },
-            },
-            "required": ["query"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        query = kwargs.get("query", "").strip()
-        session_id = session.session_id if session else None
-
-        if not query:
-            return ErrorResponse(
-                message="Please provide a search query.",
-                error="Missing query parameter",
-                session_id=session_id,
-            )
-
-        client = _get_linear_client()
-        data = await client.query(
-            SEARCH_ISSUES_QUERY,
-            {
-                "term": query,
-                "filter": {
-                    "project": {"id": {"eq": FEATURE_REQUEST_PROJECT_ID}},
-                },
-                "first": MAX_SEARCH_RESULTS,
-            },
-        )
-
-        nodes = data.get("searchIssues", {}).get("nodes", [])
-
-        if not nodes:
-            return NoResultsResponse(
-                message=f"No feature requests found matching '{query}'.",
-                suggestions=[
-                    "Try different keywords",
-                    "Use broader search terms",
-                    "You can create a new feature request if none exists",
-                ],
-                session_id=session_id,
-            )
-
-        results = [
-            FeatureRequestInfo(
-                id=node["id"],
-                identifier=node["identifier"],
-                title=node["title"],
-                description=node.get("description"),
-            )
-            for node in nodes
-        ]
-
-        return FeatureRequestSearchResponse(
-            message=f"Found {len(results)} feature request(s) matching '{query}'.",
-            results=results,
-            count=len(results),
-            query=query,
-            session_id=session_id,
-        )
-
-
-class CreateFeatureRequestTool(BaseTool):
-    """Tool for creating feature requests (or adding needs to existing ones)."""
-
-    @property
-    def name(self) -> str:
-        return "create_feature_request"
-
-    @property
-    def description(self) -> str:
-        return (
-            "Create a new feature request or add a customer need to an existing one. "
-            "Always search first with search_feature_requests to avoid duplicates. "
-            "If a matching request exists, pass its ID as existing_issue_id to add "
-            "the user's need to it instead of creating a duplicate."
-        )
-
-    @property
-    def parameters(self) -> dict[str, Any]:
-        return {
-            "type": "object",
-            "properties": {
-                "title": {
-                    "type": "string",
-                    "description": "Title for the feature request.",
-                },
-                "description": {
-                    "type": "string",
-                    "description": "Detailed description of what the user wants and why.",
-                },
-                "existing_issue_id": {
-                    "type": "string",
-                    "description": (
-                        "If adding a need to an existing feature request, "
-                        "provide its Linear issue ID (from search results). "
-                        "Omit to create a new feature request."
-                    ),
-                },
-            },
-            "required": ["title", "description"],
-        }
-
-    @property
-    def requires_auth(self) -> bool:
-        return True
-
-    async def _find_or_create_customer(
-        self, client: LinearClient, user_id: str
-    ) -> dict:
-        """Find existing customer by user_id or create a new one via upsert."""
-        data = await client.mutate(
-            CUSTOMER_UPSERT_MUTATION,
-            {
-                "input": {
-                    "name": user_id,
-                    "externalId": user_id,
-                },
-            },
-        )
-        result = data.get("customerUpsert", {})
-        if not result.get("success"):
-            raise RuntimeError(f"Failed to upsert customer: {data}")
-        return result["customer"]
-
-    async def _execute(
-        self,
-        user_id: str | None,
-        session: ChatSession,
-        **kwargs,
-    ) -> ToolResponseBase:
-        title = kwargs.get("title", "").strip()
-        description = kwargs.get("description", "").strip()
-        existing_issue_id = kwargs.get("existing_issue_id")
-        session_id = session.session_id if session else None
-
-        if not title or not description:
-            return ErrorResponse(
-                message="Both title and description are required.",
-                error="Missing required parameters",
-                session_id=session_id,
-            )
-
-        if not user_id:
-            return ErrorResponse(
-                message="Authentication required to create feature requests.",
-                error="Missing user_id",
-                session_id=session_id,
-            )
-
-        client = _get_linear_client()
-
-        # Step 1: Find or create customer for this user
-        customer = await self._find_or_create_customer(client, user_id)
-        customer_id = customer["id"]
-        customer_name = customer["name"]
-
-        # Step 2: Create or reuse issue
-        if existing_issue_id:
-            # Add need to existing issue - we still need the issue details for response
-            is_new_issue = False
-            issue_id = existing_issue_id
-        else:
-            # Create new issue in the feature requests project
-            data = await client.mutate(
-                ISSUE_CREATE_MUTATION,
-                {
-                    "input": {
-                        "title": title,
-                        "description": description,
-                        "teamId": TEAM_ID,
-                        "projectId": FEATURE_REQUEST_PROJECT_ID,
-                    },
-                },
-            )
-            result = data.get("issueCreate", {})
-            if not result.get("success"):
-                return ErrorResponse(
-                    message="Failed to create feature request issue.",
-                    error=str(data),
-                    session_id=session_id,
-                )
-            issue = result["issue"]
-            issue_id = issue["id"]
-            is_new_issue = True
-
-        # Step 3: Create customer need on the issue
-        data = await client.mutate(
-            CUSTOMER_NEED_CREATE_MUTATION,
-            {
-                "input": {
-                    "customerId": customer_id,
-                    "issueId": issue_id,
-                    "body": description,
-                    "priority": 0,
-                },
-            },
-        )
-        need_result = data.get("customerNeedCreate", {})
-        if not need_result.get("success"):
-            return ErrorResponse(
-                message="Failed to attach customer need to the feature request.",
-                error=str(data),
-                session_id=session_id,
-            )
-
-        need = need_result["need"]
-        issue_info = need["issue"]
-
-        return FeatureRequestCreatedResponse(
-            message=(
-                f"{'Created new feature request' if is_new_issue else 'Added your request to existing feature request'} "
-                f"[{issue_info['identifier']}] {issue_info['title']}."
-            ),
-            issue_id=issue_info["id"],
-            issue_identifier=issue_info["identifier"],
-            issue_title=issue_info["title"],
-            issue_url=issue_info.get("url", ""),
-            is_new_issue=is_new_issue,
-            customer_name=customer_name,
-            session_id=session_id,
-        )

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

@@ -40,9 +40,6 @@ class ResponseType(str, Enum):
     OPERATION_IN_PROGRESS = "operation_in_progress"
     # Input validation
     INPUT_VALIDATION_ERROR = "input_validation_error"
-    # Feature request types
-    FEATURE_REQUEST_SEARCH = "feature_request_search"
-    FEATURE_REQUEST_CREATED = "feature_request_created"
 
 
 # Base response model
@@ -424,34 +421,3 @@ class AsyncProcessingResponse(ToolResponseBase):
     status: str = "accepted"  # Must be "accepted" for detection
     operation_id: str | None = None
     task_id: str | None = None
-
-
-# Feature request models
-class FeatureRequestInfo(BaseModel):
-    """Information about a feature request issue."""
-
-    id: str
-    identifier: str
-    title: str
-    description: str | None = None
-
-
-class FeatureRequestSearchResponse(ToolResponseBase):
-    """Response for search_feature_requests tool."""
-
-    type: ResponseType = ResponseType.FEATURE_REQUEST_SEARCH
-    results: list[FeatureRequestInfo]
-    count: int
-    query: str
-
-
-class FeatureRequestCreatedResponse(ToolResponseBase):
-    """Response for create_feature_request tool."""
-
-    type: ResponseType = ResponseType.FEATURE_REQUEST_CREATED
-    issue_id: str
-    issue_identifier: str
-    issue_title: str
-    issue_url: str
-    is_new_issue: bool  # False if added to existing
-    customer_name: str

autogpt_platform/backend/backend/blocks/claude_code.py

@@ -1,10 +1,10 @@
 import json
 import shlex
 import uuid
-from typing import Literal, Optional
+from typing import TYPE_CHECKING, Literal, Optional
 
 from e2b import AsyncSandbox as BaseAsyncSandbox
-from pydantic import BaseModel, SecretStr
+from pydantic import SecretStr
 
 from backend.blocks._base import (
     Block,
@@ -20,6 +20,13 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.sandbox_files import (
+    SandboxFileOutput,
+    extract_and_store_sandbox_files,
+)
+
+if TYPE_CHECKING:
+    from backend.executor.utils import ExecutionContext
 
 
 class ClaudeCodeExecutionError(Exception):
@@ -174,22 +181,15 @@ class ClaudeCodeBlock(Block):
             advanced=True,
         )
 
-    class FileOutput(BaseModel):
-        """A file extracted from the sandbox."""
-
-        path: str
-        relative_path: str  # Path relative to working directory (for GitHub, etc.)
-        name: str
-        content: str
-
     class Output(BlockSchemaOutput):
         response: str = SchemaField(
             description="The output/response from Claude Code execution"
         )
-        files: list["ClaudeCodeBlock.FileOutput"] = SchemaField(
+        files: list[SandboxFileOutput] = SchemaField(
             description=(
                 "List of text files created/modified by Claude Code during this execution. "
-                "Each file has 'path', 'relative_path', 'name', and 'content' fields."
+                "Each file has 'path', 'relative_path', 'name', 'content', and 'workspace_ref' fields. "
+                "workspace_ref contains a workspace:// URI if the file was stored to workspace."
             )
         )
         conversation_history: str = SchemaField(
@@ -252,6 +252,7 @@ class ClaudeCodeBlock(Block):
                             "relative_path": "index.html",
                             "name": "index.html",
                             "content": "<html>Hello World</html>",
+                            "workspace_ref": None,
                         }
                     ],
                 ),
@@ -267,11 +268,12 @@ class ClaudeCodeBlock(Block):
                 "execute_claude_code": lambda *args, **kwargs: (
                     "Created index.html with hello world content",  # response
                     [
-                        ClaudeCodeBlock.FileOutput(
+                        SandboxFileOutput(
                             path="/home/user/index.html",
                             relative_path="index.html",
                             name="index.html",
                             content="<html>Hello World</html>",
+                            workspace_ref=None,
                         )
                     ],  # files
                     "User: Create a hello world HTML file\n"
@@ -294,7 +296,8 @@ class ClaudeCodeBlock(Block):
         existing_sandbox_id: str,
         conversation_history: str,
         dispose_sandbox: bool,
-    ) -> tuple[str, list["ClaudeCodeBlock.FileOutput"], str, str, str]:
+        execution_context: "ExecutionContext",
+    ) -> tuple[str, list[SandboxFileOutput], str, str, str]:
         """
         Execute Claude Code in an E2B sandbox.
 
@@ -449,14 +452,18 @@ class ClaudeCodeBlock(Block):
                 else:
                     new_conversation_history = turn_entry
 
-            # Extract files created/modified during this run
-            files = await self._extract_files(
-                sandbox, working_directory, start_timestamp
+            # Extract files created/modified during this run and store to workspace
+            sandbox_files = await extract_and_store_sandbox_files(
+                sandbox=sandbox,
+                working_directory=working_directory,
+                execution_context=execution_context,
+                since_timestamp=start_timestamp,
+                text_only=True,
             )
 
             return (
                 response,
-                files,
+                sandbox_files,  # Already SandboxFileOutput objects
                 new_conversation_history,
                 current_session_id,
                 sandbox_id,
@@ -471,140 +478,6 @@ class ClaudeCodeBlock(Block):
             if dispose_sandbox and sandbox:
                 await sandbox.kill()
 
-    async def _extract_files(
-        self,
-        sandbox: BaseAsyncSandbox,
-        working_directory: str,
-        since_timestamp: str | None = None,
-    ) -> list["ClaudeCodeBlock.FileOutput"]:
-        """
-        Extract text files created/modified during this Claude Code execution.
-
-        Args:
-            sandbox: The E2B sandbox instance
-            working_directory: Directory to search for files
-            since_timestamp: ISO timestamp - only return files modified after this time
-
-        Returns:
-            List of FileOutput objects with path, relative_path, name, and content
-        """
-        files: list[ClaudeCodeBlock.FileOutput] = []
-
-        # Text file extensions we can safely read as text
-        text_extensions = {
-            ".txt",
-            ".md",
-            ".html",
-            ".htm",
-            ".css",
-            ".js",
-            ".ts",
-            ".jsx",
-            ".tsx",
-            ".json",
-            ".xml",
-            ".yaml",
-            ".yml",
-            ".toml",
-            ".ini",
-            ".cfg",
-            ".conf",
-            ".py",
-            ".rb",
-            ".php",
-            ".java",
-            ".c",
-            ".cpp",
-            ".h",
-            ".hpp",
-            ".cs",
-            ".go",
-            ".rs",
-            ".swift",
-            ".kt",
-            ".scala",
-            ".sh",
-            ".bash",
-            ".zsh",
-            ".sql",
-            ".graphql",
-            ".env",
-            ".gitignore",
-            ".dockerfile",
-            "Dockerfile",
-            ".vue",
-            ".svelte",
-            ".astro",
-            ".mdx",
-            ".rst",
-            ".tex",
-            ".csv",
-            ".log",
-        }
-
-        try:
-            # List files recursively using find command
-            # Exclude node_modules and .git directories, but allow hidden files
-            # like .env and .gitignore (they're filtered by text_extensions later)
-            # Filter by timestamp to only get files created/modified during this run
-            safe_working_dir = shlex.quote(working_directory)
-            timestamp_filter = ""
-            if since_timestamp:
-                timestamp_filter = f"-newermt {shlex.quote(since_timestamp)} "
-            find_result = await sandbox.commands.run(
-                f"find {safe_working_dir} -type f "
-                f"{timestamp_filter}"
-                f"-not -path '*/node_modules/*' "
-                f"-not -path '*/.git/*' "
-                f"2>/dev/null"
-            )
-
-            if find_result.stdout:
-                for file_path in find_result.stdout.strip().split("\n"):
-                    if not file_path:
-                        continue
-
-                    # Check if it's a text file we can read
-                    is_text = any(
-                        file_path.endswith(ext) for ext in text_extensions
-                    ) or file_path.endswith("Dockerfile")
-
-                    if is_text:
-                        try:
-                            content = await sandbox.files.read(file_path)
-                            # Handle bytes or string
-                            if isinstance(content, bytes):
-                                content = content.decode("utf-8", errors="replace")
-
-                            # Extract filename from path
-                            file_name = file_path.split("/")[-1]
-
-                            # Calculate relative path by stripping working directory
-                            relative_path = file_path
-                            if file_path.startswith(working_directory):
-                                relative_path = file_path[len(working_directory) :]
-                                # Remove leading slash if present
-                                if relative_path.startswith("/"):
-                                    relative_path = relative_path[1:]
-
-                            files.append(
-                                ClaudeCodeBlock.FileOutput(
-                                    path=file_path,
-                                    relative_path=relative_path,
-                                    name=file_name,
-                                    content=content,
-                                )
-                            )
-                        except Exception:
-                            # Skip files that can't be read
-                            pass
-
-        except Exception:
-            # If file extraction fails, return empty results
-            pass
-
-        return files
-
     def _escape_prompt(self, prompt: str) -> str:
         """Escape the prompt for safe shell execution."""
         # Use single quotes and escape any single quotes in the prompt
@@ -617,6 +490,7 @@ class ClaudeCodeBlock(Block):
         *,
         e2b_credentials: APIKeyCredentials,
         anthropic_credentials: APIKeyCredentials,
+        execution_context: "ExecutionContext",
         **kwargs,
     ) -> BlockOutput:
         try:
@@ -637,6 +511,7 @@ class ClaudeCodeBlock(Block):
                 existing_sandbox_id=input_data.sandbox_id,
                 conversation_history=input_data.conversation_history,
                 dispose_sandbox=input_data.dispose_sandbox,
+                execution_context=execution_context,
             )
 
             yield "response", response

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Any, Literal, Optional
+from typing import TYPE_CHECKING, Any, Literal, Optional
 
 from e2b_code_interpreter import AsyncSandbox
 from e2b_code_interpreter import Result as E2BExecutionResult
@@ -20,6 +20,13 @@ from backend.data.model import (
     SchemaField,
 )
 from backend.integrations.providers import ProviderName
+from backend.util.sandbox_files import (
+    SandboxFileOutput,
+    extract_and_store_sandbox_files,
+)
+
+if TYPE_CHECKING:
+    from backend.executor.utils import ExecutionContext
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -85,6 +92,9 @@ class CodeExecutionResult(MainCodeExecutionResult):
 class BaseE2BExecutorMixin:
     """Shared implementation methods for E2B executor blocks."""
 
+    # Default working directory in E2B sandboxes
+    WORKING_DIR = "/home/user"
+
     async def execute_code(
         self,
         api_key: str,
@@ -95,14 +105,21 @@ class BaseE2BExecutorMixin:
         timeout: Optional[int] = None,
         sandbox_id: Optional[str] = None,
         dispose_sandbox: bool = False,
+        execution_context: Optional["ExecutionContext"] = None,
+        extract_files: bool = False,
     ):
         """
         Unified code execution method that handles all three use cases:
         1. Create new sandbox and execute (ExecuteCodeBlock)
         2. Create new sandbox, execute, and return sandbox_id (InstantiateCodeSandboxBlock)
         3. Connect to existing sandbox and execute (ExecuteCodeStepBlock)
+
+        Args:
+            extract_files: If True and execution_context provided, extract files
+                           created/modified during execution and store to workspace.
         """  # noqa
         sandbox = None
+        files: list[SandboxFileOutput] = []
         try:
             if sandbox_id:
                 # Connect to existing sandbox (ExecuteCodeStepBlock case)
@@ -118,6 +135,12 @@ class BaseE2BExecutorMixin:
                     for cmd in setup_commands:
                         await sandbox.commands.run(cmd)
 
+            # Capture timestamp before execution to scope file extraction
+            start_timestamp = None
+            if extract_files:
+                ts_result = await sandbox.commands.run("date -u +%Y-%m-%dT%H:%M:%S")
+                start_timestamp = ts_result.stdout.strip() if ts_result.stdout else None
+
             # Execute the code
             execution = await sandbox.run_code(
                 code,
@@ -133,7 +156,24 @@ class BaseE2BExecutorMixin:
             stdout_logs = "".join(execution.logs.stdout)
             stderr_logs = "".join(execution.logs.stderr)
 
-            return results, text_output, stdout_logs, stderr_logs, sandbox.sandbox_id
+            # Extract files created/modified during this execution
+            if extract_files and execution_context:
+                files = await extract_and_store_sandbox_files(
+                    sandbox=sandbox,
+                    working_directory=self.WORKING_DIR,
+                    execution_context=execution_context,
+                    since_timestamp=start_timestamp,
+                    text_only=False,  # Include binary files too
+                )
+
+            return (
+                results,
+                text_output,
+                stdout_logs,
+                stderr_logs,
+                sandbox.sandbox_id,
+                files,
+            )
         finally:
             # Dispose of sandbox if requested to reduce usage costs
             if dispose_sandbox and sandbox:
@@ -238,6 +278,12 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
             description="Standard output logs from execution"
         )
         stderr_logs: str = SchemaField(description="Standard error logs from execution")
+        files: list[SandboxFileOutput] = SchemaField(
+            description=(
+                "Files created or modified during execution. "
+                "Each file has path, name, content, and workspace_ref (if stored)."
+            ),
+        )
 
     def __init__(self):
         super().__init__(
@@ -259,23 +305,30 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
                 ("results", []),
                 ("response", "Hello World"),
                 ("stdout_logs", "Hello World\n"),
+                ("files", []),
             ],
             test_mock={
-                "execute_code": lambda api_key, code, language, template_id, setup_commands, timeout, dispose_sandbox: (  # noqa
+                "execute_code": lambda api_key, code, language, template_id, setup_commands, timeout, dispose_sandbox, execution_context, extract_files: (  # noqa
                     [],  # results
                     "Hello World",  # text_output
                     "Hello World\n",  # stdout_logs
                     "",  # stderr_logs
                     "sandbox_id",  # sandbox_id
+                    [],  # files
                 ),
             },
         )
 
     async def run(
-        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+        self,
+        input_data: Input,
+        *,
+        credentials: APIKeyCredentials,
+        execution_context: "ExecutionContext",
+        **kwargs,
     ) -> BlockOutput:
         try:
-            results, text_output, stdout, stderr, _ = await self.execute_code(
+            results, text_output, stdout, stderr, _, files = await self.execute_code(
                 api_key=credentials.api_key.get_secret_value(),
                 code=input_data.code,
                 language=input_data.language,
@@ -283,6 +336,8 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
                 setup_commands=input_data.setup_commands,
                 timeout=input_data.timeout,
                 dispose_sandbox=input_data.dispose_sandbox,
+                execution_context=execution_context,
+                extract_files=True,
             )
 
             # Determine result object shape & filter out empty formats
@@ -296,6 +351,8 @@ class ExecuteCodeBlock(Block, BaseE2BExecutorMixin):
                 yield "stdout_logs", stdout
             if stderr:
                 yield "stderr_logs", stderr
+            # Always yield files (empty list if none)
+            yield "files", [f.model_dump() for f in files]
         except Exception as e:
             yield "error", str(e)
 
@@ -393,6 +450,7 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
                     "Hello World\n",  # stdout_logs
                     "",  # stderr_logs
                     "sandbox_id",  # sandbox_id
+                    [],  # files
                 ),
             },
         )
@@ -401,7 +459,7 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            _, text_output, stdout, stderr, sandbox_id = await self.execute_code(
+            _, text_output, stdout, stderr, sandbox_id, _ = await self.execute_code(
                 api_key=credentials.api_key.get_secret_value(),
                 code=input_data.setup_code,
                 language=input_data.language,
@@ -500,6 +558,7 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
                     "Hello World\n",  # stdout_logs
                     "",  # stderr_logs
                     sandbox_id,  # sandbox_id
+                    [],  # files
                 ),
             },
         )
@@ -508,7 +567,7 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
         self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            results, text_output, stdout, stderr, _ = await self.execute_code(
+            results, text_output, stdout, stderr, _, _ = await self.execute_code(
                 api_key=credentials.api_key.get_secret_value(),
                 code=input_data.step_code,
                 language=input_data.language,

autogpt_platform/backend/backend/util/sandbox_files.py

@@ -0,0 +1,288 @@
+"""
+Shared utilities for extracting and storing files from E2B sandboxes.
+
+This module provides common file extraction and workspace storage functionality
+for blocks that run code in E2B sandboxes (Claude Code, Code Executor, etc.).
+"""
+
+import base64
+import logging
+import mimetypes
+import shlex
+from dataclasses import dataclass
+from typing import TYPE_CHECKING
+
+from pydantic import BaseModel
+
+from backend.util.file import store_media_file
+from backend.util.type import MediaFileType
+
+if TYPE_CHECKING:
+    from e2b import AsyncSandbox as BaseAsyncSandbox
+
+    from backend.executor.utils import ExecutionContext
+
+logger = logging.getLogger(__name__)
+
+# Text file extensions that can be safely read and stored as text
+TEXT_EXTENSIONS = {
+    ".txt",
+    ".md",
+    ".html",
+    ".htm",
+    ".css",
+    ".js",
+    ".ts",
+    ".jsx",
+    ".tsx",
+    ".json",
+    ".xml",
+    ".yaml",
+    ".yml",
+    ".toml",
+    ".ini",
+    ".cfg",
+    ".conf",
+    ".py",
+    ".rb",
+    ".php",
+    ".java",
+    ".c",
+    ".cpp",
+    ".h",
+    ".hpp",
+    ".cs",
+    ".go",
+    ".rs",
+    ".swift",
+    ".kt",
+    ".scala",
+    ".sh",
+    ".bash",
+    ".zsh",
+    ".sql",
+    ".graphql",
+    ".env",
+    ".gitignore",
+    ".dockerfile",
+    "Dockerfile",
+    ".vue",
+    ".svelte",
+    ".astro",
+    ".mdx",
+    ".rst",
+    ".tex",
+    ".csv",
+    ".log",
+}
+
+
+class SandboxFileOutput(BaseModel):
+    """A file extracted from a sandbox and optionally stored in workspace."""
+
+    path: str
+    """Full path in the sandbox."""
+
+    relative_path: str
+    """Path relative to the working directory."""
+
+    name: str
+    """Filename only."""
+
+    content: str
+    """File content as text (for backward compatibility)."""
+
+    workspace_ref: str | None = None
+    """Workspace reference (workspace://{id}#mime) if stored, None otherwise."""
+
+
+@dataclass
+class ExtractedFile:
+    """Internal representation of an extracted file before storage."""
+
+    path: str
+    relative_path: str
+    name: str
+    content: bytes
+    is_text: bool
+
+
+async def extract_sandbox_files(
+    sandbox: "BaseAsyncSandbox",
+    working_directory: str,
+    since_timestamp: str | None = None,
+    text_only: bool = True,
+) -> list[ExtractedFile]:
+    """
+    Extract files from an E2B sandbox.
+
+    Args:
+        sandbox: The E2B sandbox instance
+        working_directory: Directory to search for files
+        since_timestamp: ISO timestamp - only return files modified after this time
+        text_only: If True, only extract text files (default). If False, extract all files.
+
+    Returns:
+        List of ExtractedFile objects with path, content, and metadata
+    """
+    files: list[ExtractedFile] = []
+
+    try:
+        # Build find command
+        safe_working_dir = shlex.quote(working_directory)
+        timestamp_filter = ""
+        if since_timestamp:
+            timestamp_filter = f"-newermt {shlex.quote(since_timestamp)} "
+
+        find_result = await sandbox.commands.run(
+            f"find {safe_working_dir} -type f "
+            f"{timestamp_filter}"
+            f"-not -path '*/node_modules/*' "
+            f"-not -path '*/.git/*' "
+            f"2>/dev/null"
+        )
+
+        if not find_result.stdout:
+            return files
+
+        for file_path in find_result.stdout.strip().split("\n"):
+            if not file_path:
+                continue
+
+            # Check if it's a text file
+            is_text = any(file_path.endswith(ext) for ext in TEXT_EXTENSIONS)
+
+            # Skip non-text files if text_only mode
+            if text_only and not is_text:
+                continue
+
+            try:
+                # Read file content as bytes
+                content = await sandbox.files.read(file_path, format="bytes")
+                if isinstance(content, str):
+                    content = content.encode("utf-8")
+                elif isinstance(content, bytearray):
+                    content = bytes(content)
+
+                # Extract filename from path
+                file_name = file_path.split("/")[-1]
+
+                # Calculate relative path
+                relative_path = file_path
+                if file_path.startswith(working_directory):
+                    relative_path = file_path[len(working_directory) :]
+                    if relative_path.startswith("/"):
+                        relative_path = relative_path[1:]
+
+                files.append(
+                    ExtractedFile(
+                        path=file_path,
+                        relative_path=relative_path,
+                        name=file_name,
+                        content=content,
+                        is_text=is_text,
+                    )
+                )
+            except Exception as e:
+                logger.debug(f"Failed to read file {file_path}: {e}")
+                continue
+
+    except Exception as e:
+        logger.warning(f"File extraction failed: {e}")
+
+    return files
+
+
+async def store_sandbox_files(
+    extracted_files: list[ExtractedFile],
+    execution_context: "ExecutionContext",
+) -> list[SandboxFileOutput]:
+    """
+    Store extracted sandbox files to workspace and return output objects.
+
+    Args:
+        extracted_files: List of files extracted from sandbox
+        execution_context: Execution context for workspace storage
+
+    Returns:
+        List of SandboxFileOutput objects with workspace refs
+    """
+    outputs: list[SandboxFileOutput] = []
+
+    for file in extracted_files:
+        # Decode content for text files (for backward compat content field)
+        if file.is_text:
+            try:
+                content_str = file.content.decode("utf-8", errors="replace")
+            except Exception:
+                content_str = ""
+        else:
+            content_str = f"[Binary file: {len(file.content)} bytes]"
+
+        # Build data URI (needed for storage and as binary fallback)
+        mime_type = mimetypes.guess_type(file.name)[0] or "application/octet-stream"
+        data_uri = f"data:{mime_type};base64,{base64.b64encode(file.content).decode()}"
+
+        # Try to store in workspace
+        workspace_ref: str | None = None
+        try:
+            result = await store_media_file(
+                file=MediaFileType(data_uri),
+                execution_context=execution_context,
+                return_format="for_block_output",
+            )
+            if result.startswith("workspace://"):
+                workspace_ref = result
+            elif not file.is_text:
+                # Non-workspace context (graph execution): store_media_file
+                # returned a data URI — use it as content so binary data isn't lost.
+                content_str = result
+        except Exception as e:
+            logger.warning(f"Failed to store file {file.name} to workspace: {e}")
+            # For binary files, fall back to data URI to prevent data loss
+            if not file.is_text:
+                content_str = data_uri
+
+        outputs.append(
+            SandboxFileOutput(
+                path=file.path,
+                relative_path=file.relative_path,
+                name=file.name,
+                content=content_str,
+                workspace_ref=workspace_ref,
+            )
+        )
+
+    return outputs
+
+
+async def extract_and_store_sandbox_files(
+    sandbox: "BaseAsyncSandbox",
+    working_directory: str,
+    execution_context: "ExecutionContext",
+    since_timestamp: str | None = None,
+    text_only: bool = True,
+) -> list[SandboxFileOutput]:
+    """
+    Extract files from sandbox and store them in workspace.
+
+    This is the main entry point combining extraction and storage.
+
+    Args:
+        sandbox: The E2B sandbox instance
+        working_directory: Directory to search for files
+        execution_context: Execution context for workspace storage
+        since_timestamp: ISO timestamp - only return files modified after this time
+        text_only: If True, only extract text files
+
+    Returns:
+        List of SandboxFileOutput objects with content and workspace refs
+    """
+    extracted = await extract_sandbox_files(
+        sandbox=sandbox,
+        working_directory=working_directory,
+        since_timestamp=since_timestamp,
+        text_only=text_only,
+    )
+
+    return await store_sandbox_files(extracted, execution_context)

autogpt_platform/backend/backend/util/settings.py

@@ -368,6 +368,10 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         default=600,
         description="The timeout in seconds for Agent Generator service requests (includes retries for rate limits)",
     )
+    agentgenerator_use_dummy: bool = Field(
+        default=False,
+        description="Use dummy agent generator responses for testing (bypasses external service)",
+    )
 
     enable_example_blocks: bool = Field(
         default=False,
@@ -658,9 +662,6 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
     mem0_api_key: str = Field(default="", description="Mem0 API key")
     elevenlabs_api_key: str = Field(default="", description="ElevenLabs API key")
 
-    linear_api_key: str = Field(
-        default="", description="Linear API key for system-level operations"
-    )
     linear_client_id: str = Field(default="", description="Linear client ID")
     linear_client_secret: str = Field(default="", description="Linear client secret")
 

autogpt_platform/backend/test/agent_generator/test_service.py

@@ -25,6 +25,7 @@ class TestServiceConfiguration:
         """Test that external service is not configured when host is empty."""
         mock_settings = MagicMock()
         mock_settings.config.agentgenerator_host = ""
+        mock_settings.config.agentgenerator_use_dummy = False
 
         with patch.object(service, "_get_settings", return_value=mock_settings):
             assert service.is_external_service_configured() is False

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

@@ -15,10 +15,6 @@ import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
 import { useEffect, useRef, useState } from "react";
 import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
 import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
-import {
-  CreateFeatureRequestTool,
-  SearchFeatureRequestsTool,
-} from "../../tools/FeatureRequests/FeatureRequests";
 import { FindAgentsTool } from "../../tools/FindAgents/FindAgents";
 import { FindBlocksTool } from "../../tools/FindBlocks/FindBlocks";
 import { RunAgentTool } from "../../tools/RunAgent/RunAgent";
@@ -258,20 +254,6 @@ export const ChatMessagesContainer = ({
                           part={part as ToolUIPart}
                         />
                       );
-                    case "tool-search_feature_requests":
-                      return (
-                        <SearchFeatureRequestsTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
-                    case "tool-create_feature_request":
-                      return (
-                        <CreateFeatureRequestTool
-                          key={`${message.id}-${i}`}
-                          part={part as ToolUIPart}
-                        />
-                      );
                     default:
                       return null;
                   }

autogpt_platform/frontend/src/app/(platform)/copilot/hooks/Untitled

@@ -1,10 +0,0 @@
-import { parseAsString, useQueryState } from "nuqs";
-
-export function useCopilotSessionId() {
-  const [urlSessionId, setUrlSessionId] = useQueryState(
-    "sessionId",
-    parseAsString,
-  );
-
-  return { urlSessionId, setUrlSessionId };
-}

autogpt_platform/frontend/src/app/(platform)/copilot/hooks/useLongRunningToolPolling.ts

@@ -0,0 +1,126 @@
+import { getGetV2GetSessionQueryKey } from "@/app/api/__generated__/endpoints/chat/chat";
+import { useQueryClient } from "@tanstack/react-query";
+import type { UIDataTypes, UIMessage, UITools } from "ai";
+import { useCallback, useEffect, useRef } from "react";
+import { convertChatSessionMessagesToUiMessages } from "../helpers/convertChatSessionToUiMessages";
+
+const OPERATING_TYPES = new Set([
+  "operation_started",
+  "operation_pending",
+  "operation_in_progress",
+]);
+
+const POLL_INTERVAL_MS = 1_500;
+
+/**
+ * Detects whether any message contains a tool part whose output indicates
+ * a long-running operation is still in progress.
+ */
+function hasOperatingTool(
+  messages: UIMessage<unknown, UIDataTypes, UITools>[],
+) {
+  for (const msg of messages) {
+    for (const part of msg.parts) {
+      if (!part.type.startsWith("tool-")) continue;
+      const toolPart = part as { output?: unknown };
+      if (!toolPart.output) continue;
+      const output =
+        typeof toolPart.output === "string"
+          ? safeParse(toolPart.output)
+          : toolPart.output;
+      if (
+        output &&
+        typeof output === "object" &&
+        "type" in output &&
+        OPERATING_TYPES.has((output as { type: string }).type)
+      ) {
+        return true;
+      }
+    }
+  }
+  return false;
+}
+
+function safeParse(value: string): unknown {
+  try {
+    return JSON.parse(value);
+  } catch {
+    return null;
+  }
+}
+
+/**
+ * Polls the session endpoint while any tool is in an "operating" state
+ * (operation_started / operation_pending / operation_in_progress).
+ *
+ * When the session data shows the tool output has changed (e.g. to
+ * agent_saved), it calls `setMessages` with the updated messages.
+ */
+export function useLongRunningToolPolling(
+  sessionId: string | null,
+  messages: UIMessage<unknown, UIDataTypes, UITools>[],
+  setMessages: (
+    updater: (
+      prev: UIMessage<unknown, UIDataTypes, UITools>[],
+    ) => UIMessage<unknown, UIDataTypes, UITools>[],
+  ) => void,
+) {
+  const queryClient = useQueryClient();
+  const intervalRef = useRef<ReturnType<typeof setInterval> | null>(null);
+
+  const stopPolling = useCallback(() => {
+    if (intervalRef.current) {
+      clearInterval(intervalRef.current);
+      intervalRef.current = null;
+    }
+  }, []);
+
+  const poll = useCallback(async () => {
+    if (!sessionId) return;
+
+    // Invalidate the query cache so the next fetch gets fresh data
+    await queryClient.invalidateQueries({
+      queryKey: getGetV2GetSessionQueryKey(sessionId),
+    });
+
+    // Fetch fresh session data
+    const data = queryClient.getQueryData<{
+      status: number;
+      data: { messages?: unknown[] };
+    }>(getGetV2GetSessionQueryKey(sessionId));
+
+    if (data?.status !== 200 || !data.data.messages) return;
+
+    const freshMessages = convertChatSessionMessagesToUiMessages(
+      sessionId,
+      data.data.messages,
+    );
+
+    if (!freshMessages || freshMessages.length === 0) return;
+
+    // Update when the long-running tool completed
+    if (!hasOperatingTool(freshMessages)) {
+      setMessages(() => freshMessages);
+      stopPolling();
+    }
+  }, [sessionId, queryClient, setMessages, stopPolling]);
+
+  useEffect(() => {
+    const shouldPoll = hasOperatingTool(messages);
+
+    // Always clear any previous interval first so we never leak timers
+    // when the effect re-runs due to dependency changes (e.g. messages
+    // updating as the LLM streams text after the tool call).
+    stopPolling();
+
+    if (shouldPoll && sessionId) {
+      intervalRef.current = setInterval(() => {
+        poll();
+      }, POLL_INTERVAL_MS);
+    }
+
+    return () => {
+      stopPolling();
+    };
+  }, [messages, sessionId, poll, stopPolling]);
+}

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

@@ -14,10 +14,6 @@ import { Text } from "@/components/atoms/Text/Text";
 import { CopilotChatActionsProvider } from "../components/CopilotChatActionsProvider/CopilotChatActionsProvider";
 import { CreateAgentTool } from "../tools/CreateAgent/CreateAgent";
 import { EditAgentTool } from "../tools/EditAgent/EditAgent";
-import {
-  CreateFeatureRequestTool,
-  SearchFeatureRequestsTool,
-} from "../tools/FeatureRequests/FeatureRequests";
 import { FindAgentsTool } from "../tools/FindAgents/FindAgents";
 import { FindBlocksTool } from "../tools/FindBlocks/FindBlocks";
 import { RunAgentTool } from "../tools/RunAgent/RunAgent";
@@ -49,8 +45,6 @@ const SECTIONS = [
   "Tool: Create Agent",
   "Tool: Edit Agent",
   "Tool: View Agent Output",
-  "Tool: Search Feature Requests",
-  "Tool: Create Feature Request",
   "Full Conversation Example",
 ] as const;
 
@@ -1427,235 +1421,6 @@ export default function StyleguidePage() {
               </SubSection>
             </Section>
 
-            {/* ============================================================= */}
-            {/* SEARCH FEATURE REQUESTS                                        */}
-            {/* ============================================================= */}
-
-            <Section title="Tool: Search Feature Requests">
-              <SubSection label="Input streaming">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "input-streaming",
-                    input: { query: "dark mode" },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Input available">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "input-available",
-                    input: { query: "dark mode" },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (with results)">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { query: "dark mode" },
-                    output: {
-                      type: "feature_request_search",
-                      message:
-                        'Found 2 feature request(s) matching "dark mode".',
-                      query: "dark mode",
-                      count: 2,
-                      results: [
-                        {
-                          id: "fr-001",
-                          identifier: "INT-42",
-                          title: "Add dark mode to the platform",
-                          description:
-                            "Users have requested a dark mode option for the builder and copilot interfaces to reduce eye strain during long sessions.",
-                        },
-                        {
-                          id: "fr-002",
-                          identifier: "INT-87",
-                          title: "Dark theme for agent output viewer",
-                          description:
-                            "Specifically requesting dark theme support for the agent output/execution viewer panel.",
-                        },
-                      ],
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (no results)">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { query: "teleportation" },
-                    output: {
-                      type: "no_results",
-                      message:
-                        "No feature requests found matching 'teleportation'.",
-                      suggestions: [
-                        "Try different keywords",
-                        "Use broader search terms",
-                        "You can create a new feature request if none exists",
-                      ],
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (error)">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { query: "dark mode" },
-                    output: {
-                      type: "error",
-                      message: "Failed to search feature requests.",
-                      error: "LINEAR_API_KEY environment variable is not set",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output error">
-                <SearchFeatureRequestsTool
-                  part={{
-                    type: "tool-search_feature_requests",
-                    toolCallId: uid(),
-                    state: "output-error",
-                    input: { query: "dark mode" },
-                  }}
-                />
-              </SubSection>
-            </Section>
-
-            {/* ============================================================= */}
-            {/* CREATE FEATURE REQUEST                                         */}
-            {/* ============================================================= */}
-
-            <Section title="Tool: Create Feature Request">
-              <SubSection label="Input streaming">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "input-streaming",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode for the platform.",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Input available">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "input-available",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode for the platform.",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (new issue created)">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode for the platform.",
-                    },
-                    output: {
-                      type: "feature_request_created",
-                      message:
-                        "Created new feature request [INT-105] Add dark mode.",
-                      issue_id: "issue-new-123",
-                      issue_identifier: "INT-105",
-                      issue_title: "Add dark mode",
-                      issue_url:
-                        "https://linear.app/autogpt/issue/INT-105/add-dark-mode",
-                      is_new_issue: true,
-                      customer_name: "user-abc-123",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (added to existing issue)">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: {
-                      title: "Dark mode support",
-                      description:
-                        "Please add dark mode, it would help with long sessions.",
-                      existing_issue_id: "fr-001",
-                    },
-                    output: {
-                      type: "feature_request_created",
-                      message:
-                        "Added your request to existing feature request [INT-42] Add dark mode to the platform.",
-                      issue_id: "fr-001",
-                      issue_identifier: "INT-42",
-                      issue_title: "Add dark mode to the platform",
-                      issue_url:
-                        "https://linear.app/autogpt/issue/INT-42/add-dark-mode-to-the-platform",
-                      is_new_issue: false,
-                      customer_name: "user-xyz-789",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output available (error)">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: {
-                      title: "Add dark mode",
-                      description: "I would love dark mode.",
-                    },
-                    output: {
-                      type: "error",
-                      message:
-                        "Failed to attach customer need to the feature request.",
-                      error: "Linear API request failed (500): Internal error",
-                    },
-                  }}
-                />
-              </SubSection>
-
-              <SubSection label="Output error">
-                <CreateFeatureRequestTool
-                  part={{
-                    type: "tool-create_feature_request",
-                    toolCallId: uid(),
-                    state: "output-error",
-                    input: { title: "Add dark mode" },
-                  }}
-                />
-              </SubSection>
-            </Section>
-
             {/* ============================================================= */}
             {/* FULL CONVERSATION EXAMPLE                                      */}
             {/* ============================================================= */}

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

@@ -1,24 +1,30 @@
 "use client";
 
-import { WarningDiamondIcon } from "@phosphor-icons/react";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import {
+  BookOpenIcon,
+  CheckFatIcon,
+  PencilSimpleIcon,
+  WarningDiamondIcon,
+} from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
+import NextLink from "next/link";
 import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import { ProgressBar } from "../../components/ProgressBar/ProgressBar";
 import {
   ContentCardDescription,
   ContentCodeBlock,
   ContentGrid,
   ContentHint,
-  ContentLink,
   ContentMessage,
 } from "../../components/ToolAccordion/AccordionContent";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import { useAsymptoticProgress } from "../../hooks/useAsymptoticProgress";
 import {
   ClarificationQuestionsCard,
   ClarifyingQuestion,
 } from "./components/ClarificationQuestionsCard";
+import { MiniGame } from "./components/MiniGame/MiniGame";
 import {
   AccordionIcon,
   formatMaybeJson,
@@ -52,7 +58,7 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
   const icon = <AccordionIcon />;
 
   if (isAgentSavedOutput(output)) {
-    return { icon, title: output.agent_name };
+    return { icon, title: output.agent_name, expanded: true };
   }
   if (isAgentPreviewOutput(output)) {
     return {
@@ -78,6 +84,7 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
     return {
       icon,
       title: "Creating agent, this may take a few minutes. Sit back and relax.",
+      expanded: true,
     };
   }
   return {
@@ -107,8 +114,6 @@ export function CreateAgentTool({ part }: Props) {
       isOperationPendingOutput(output) ||
       isOperationInProgressOutput(output));
 
-  const progress = useAsymptoticProgress(isOperating);
-
   const hasExpandableContent =
     part.state === "output-available" &&
     !!output &&
@@ -152,31 +157,53 @@ export function CreateAgentTool({ part }: Props) {
         <ToolAccordion {...getAccordionMeta(output)}>
           {isOperating && (
             <ContentGrid>
-              <ProgressBar value={progress} className="max-w-[280px]" />
+              <MiniGame />
               <ContentHint>
-                This could take a few minutes, grab a coffee ☕
+                This could take a few minutes — play while you wait!
               </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 className="rounded-xl border border-border/60 bg-card p-4 shadow-sm">
+              <div className="flex items-baseline gap-2">
+                <CheckFatIcon
+                  size={18}
+                  weight="regular"
+                  className="relative top-1 text-green-500"
+                />
+                <Text
+                  variant="body-medium"
+                  className="text-blacks mb-2 text-[16px]"
+                >
+                  {output.message}
+                </Text>
               </div>
-              <ContentCodeBlock>
-                {truncateText(
-                  formatMaybeJson({ agent_id: output.agent_id }),
-                  800,
-                )}
-              </ContentCodeBlock>
-            </ContentGrid>
+              <div className="mt-3 flex flex-wrap gap-4">
+                <Button variant="outline" size="small">
+                  <NextLink
+                    href={output.library_agent_link}
+                    className="inline-flex items-center gap-1.5"
+                    target="_blank"
+                    rel="noopener noreferrer"
+                  >
+                    <BookOpenIcon size={14} weight="regular" />
+                    Open in library
+                  </NextLink>
+                </Button>
+                <Button variant="outline" size="small">
+                  <NextLink
+                    href={output.agent_page_link}
+                    target="_blank"
+                    rel="noopener noreferrer"
+                    className="inline-flex items-center gap-1.5"
+                  >
+                    <PencilSimpleIcon size={14} weight="regular" />
+                    Open in builder
+                  </NextLink>
+                </Button>
+              </div>
+            </div>
           )}
 
           {isAgentPreviewOutput(output) && (

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

@@ -0,0 +1,21 @@
+"use client";
+
+import { useMiniGame } from "./useMiniGame";
+
+export function MiniGame() {
+  const { canvasRef } = useMiniGame();
+
+  return (
+    <div
+      className="w-full overflow-hidden rounded-md bg-background text-foreground"
+      style={{ border: "1px solid #d17fff" }}
+    >
+      <canvas
+        ref={canvasRef}
+        tabIndex={0}
+        className="block w-full outline-none"
+        style={{ imageRendering: "pixelated" }}
+      />
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/useMiniGame.ts

@@ -0,0 +1,579 @@
+import { useEffect, useRef } from "react";
+
+/* ------------------------------------------------------------------ */
+/*  Constants                                                         */
+/* ------------------------------------------------------------------ */
+
+const CANVAS_HEIGHT = 150;
+const GRAVITY = 0.55;
+const JUMP_FORCE = -9.5;
+const BASE_SPEED = 3;
+const SPEED_INCREMENT = 0.0008;
+const SPAWN_MIN = 70;
+const SPAWN_MAX = 130;
+const CHAR_SIZE = 18;
+const CHAR_X = 50;
+const GROUND_PAD = 20;
+const STORAGE_KEY = "copilot-minigame-highscore";
+
+// Colors
+const COLOR_BG = "#E8EAF6";
+const COLOR_CHAR = "#263238";
+const COLOR_BOSS = "#F50057";
+
+// Boss
+const BOSS_SIZE = 36;
+const BOSS_ENTER_SPEED = 2;
+const BOSS_LEAVE_SPEED = 3;
+const BOSS_SHOOT_COOLDOWN = 90;
+const BOSS_SHOTS_TO_EVADE = 5;
+const BOSS_INTERVAL = 20; // every N score
+const PROJ_SPEED = 4.5;
+const PROJ_SIZE = 12;
+
+/* ------------------------------------------------------------------ */
+/*  Types                                                             */
+/* ------------------------------------------------------------------ */
+
+interface Obstacle {
+  x: number;
+  width: number;
+  height: number;
+  scored: boolean;
+}
+
+interface Projectile {
+  x: number;
+  y: number;
+  speed: number;
+  evaded: boolean;
+  type: "low" | "high";
+}
+
+interface BossState {
+  phase: "inactive" | "entering" | "fighting" | "leaving";
+  x: number;
+  targetX: number;
+  shotsEvaded: number;
+  cooldown: number;
+  projectiles: Projectile[];
+  bob: number;
+}
+
+interface GameState {
+  charY: number;
+  vy: number;
+  obstacles: Obstacle[];
+  score: number;
+  highScore: number;
+  speed: number;
+  frame: number;
+  nextSpawn: number;
+  running: boolean;
+  over: boolean;
+  groundY: number;
+  boss: BossState;
+  bossThreshold: number;
+}
+
+/* ------------------------------------------------------------------ */
+/*  Helpers                                                           */
+/* ------------------------------------------------------------------ */
+
+function randInt(min: number, max: number) {
+  return Math.floor(Math.random() * (max - min + 1)) + min;
+}
+
+function readHighScore(): number {
+  try {
+    return parseInt(localStorage.getItem(STORAGE_KEY) || "0", 10) || 0;
+  } catch {
+    return 0;
+  }
+}
+
+function writeHighScore(score: number) {
+  try {
+    localStorage.setItem(STORAGE_KEY, String(score));
+  } catch {
+    /* noop */
+  }
+}
+
+function makeBoss(): BossState {
+  return {
+    phase: "inactive",
+    x: 0,
+    targetX: 0,
+    shotsEvaded: 0,
+    cooldown: 0,
+    projectiles: [],
+    bob: 0,
+  };
+}
+
+function makeState(groundY: number): GameState {
+  return {
+    charY: groundY - CHAR_SIZE,
+    vy: 0,
+    obstacles: [],
+    score: 0,
+    highScore: readHighScore(),
+    speed: BASE_SPEED,
+    frame: 0,
+    nextSpawn: randInt(SPAWN_MIN, SPAWN_MAX),
+    running: false,
+    over: false,
+    groundY,
+    boss: makeBoss(),
+    bossThreshold: BOSS_INTERVAL,
+  };
+}
+
+function gameOver(s: GameState) {
+  s.running = false;
+  s.over = true;
+  if (s.score > s.highScore) {
+    s.highScore = s.score;
+    writeHighScore(s.score);
+  }
+}
+
+/* ------------------------------------------------------------------ */
+/*  Projectile collision — shared between fighting & leaving phases   */
+/* ------------------------------------------------------------------ */
+
+/** Returns true if the player died. */
+function tickProjectiles(s: GameState): boolean {
+  const boss = s.boss;
+
+  for (const p of boss.projectiles) {
+    p.x -= p.speed;
+
+    if (!p.evaded && p.x + PROJ_SIZE < CHAR_X) {
+      p.evaded = true;
+      boss.shotsEvaded++;
+    }
+
+    // Collision
+    if (
+      !p.evaded &&
+      CHAR_X + CHAR_SIZE > p.x &&
+      CHAR_X < p.x + PROJ_SIZE &&
+      s.charY + CHAR_SIZE > p.y &&
+      s.charY < p.y + PROJ_SIZE
+    ) {
+      gameOver(s);
+      return true;
+    }
+  }
+
+  boss.projectiles = boss.projectiles.filter((p) => p.x + PROJ_SIZE > -20);
+  return false;
+}
+
+/* ------------------------------------------------------------------ */
+/*  Update                                                            */
+/* ------------------------------------------------------------------ */
+
+function update(s: GameState, canvasWidth: number) {
+  if (!s.running) return;
+
+  s.frame++;
+
+  // Speed only ramps during regular play
+  if (s.boss.phase === "inactive") {
+    s.speed = BASE_SPEED + s.frame * SPEED_INCREMENT;
+  }
+
+  // ---- Character physics (always active) ---- //
+  s.vy += GRAVITY;
+  s.charY += s.vy;
+  if (s.charY + CHAR_SIZE >= s.groundY) {
+    s.charY = s.groundY - CHAR_SIZE;
+    s.vy = 0;
+  }
+
+  // ---- Trigger boss ---- //
+  if (s.boss.phase === "inactive" && s.score >= s.bossThreshold) {
+    s.boss.phase = "entering";
+    s.boss.x = canvasWidth + 10;
+    s.boss.targetX = canvasWidth - BOSS_SIZE - 40;
+    s.boss.shotsEvaded = 0;
+    s.boss.cooldown = BOSS_SHOOT_COOLDOWN;
+    s.boss.projectiles = [];
+    s.obstacles = [];
+  }
+
+  // ---- Boss: entering ---- //
+  if (s.boss.phase === "entering") {
+    s.boss.bob = Math.sin(s.frame * 0.05) * 3;
+    s.boss.x -= BOSS_ENTER_SPEED;
+    if (s.boss.x <= s.boss.targetX) {
+      s.boss.x = s.boss.targetX;
+      s.boss.phase = "fighting";
+    }
+    return; // no obstacles while entering
+  }
+
+  // ---- Boss: fighting ---- //
+  if (s.boss.phase === "fighting") {
+    s.boss.bob = Math.sin(s.frame * 0.05) * 3;
+
+    // Shoot
+    s.boss.cooldown--;
+    if (s.boss.cooldown <= 0) {
+      const isLow = Math.random() < 0.5;
+      s.boss.projectiles.push({
+        x: s.boss.x - PROJ_SIZE,
+        y: isLow ? s.groundY - 14 : s.groundY - 70,
+        speed: PROJ_SPEED,
+        evaded: false,
+        type: isLow ? "low" : "high",
+      });
+      s.boss.cooldown = BOSS_SHOOT_COOLDOWN;
+    }
+
+    if (tickProjectiles(s)) return;
+
+    // Boss defeated?
+    if (s.boss.shotsEvaded >= BOSS_SHOTS_TO_EVADE) {
+      s.boss.phase = "leaving";
+      s.score += 5; // bonus
+      s.bossThreshold = s.score + BOSS_INTERVAL;
+    }
+    return;
+  }
+
+  // ---- Boss: leaving ---- //
+  if (s.boss.phase === "leaving") {
+    s.boss.bob = Math.sin(s.frame * 0.05) * 3;
+    s.boss.x += BOSS_LEAVE_SPEED;
+
+    // Still check in-flight projectiles
+    if (tickProjectiles(s)) return;
+
+    if (s.boss.x > canvasWidth + 50) {
+      s.boss = makeBoss();
+      s.nextSpawn = s.frame + randInt(SPAWN_MIN / 2, SPAWN_MAX / 2);
+    }
+    return;
+  }
+
+  // ---- Regular obstacle play ---- //
+  if (s.frame >= s.nextSpawn) {
+    s.obstacles.push({
+      x: canvasWidth + 10,
+      width: randInt(10, 16),
+      height: randInt(20, 48),
+      scored: false,
+    });
+    s.nextSpawn = s.frame + randInt(SPAWN_MIN, SPAWN_MAX);
+  }
+
+  for (const o of s.obstacles) {
+    o.x -= s.speed;
+    if (!o.scored && o.x + o.width < CHAR_X) {
+      o.scored = true;
+      s.score++;
+    }
+  }
+
+  s.obstacles = s.obstacles.filter((o) => o.x + o.width > -20);
+
+  for (const o of s.obstacles) {
+    const oY = s.groundY - o.height;
+    if (
+      CHAR_X + CHAR_SIZE > o.x &&
+      CHAR_X < o.x + o.width &&
+      s.charY + CHAR_SIZE > oY
+    ) {
+      gameOver(s);
+      return;
+    }
+  }
+}
+
+/* ------------------------------------------------------------------ */
+/*  Drawing                                                           */
+/* ------------------------------------------------------------------ */
+
+function drawBoss(ctx: CanvasRenderingContext2D, s: GameState, bg: string) {
+  const bx = s.boss.x;
+  const by = s.groundY - BOSS_SIZE + s.boss.bob;
+
+  // Body
+  ctx.save();
+  ctx.fillStyle = COLOR_BOSS;
+  ctx.globalAlpha = 0.9;
+  ctx.beginPath();
+  ctx.roundRect(bx, by, BOSS_SIZE, BOSS_SIZE, 4);
+  ctx.fill();
+  ctx.restore();
+
+  // Eyes
+  ctx.save();
+  ctx.fillStyle = bg;
+  const eyeY = by + 13;
+  ctx.beginPath();
+  ctx.arc(bx + 10, eyeY, 4, 0, Math.PI * 2);
+  ctx.fill();
+  ctx.beginPath();
+  ctx.arc(bx + 26, eyeY, 4, 0, Math.PI * 2);
+  ctx.fill();
+  ctx.restore();
+
+  // Angry eyebrows
+  ctx.save();
+  ctx.strokeStyle = bg;
+  ctx.lineWidth = 2;
+  ctx.beginPath();
+  ctx.moveTo(bx + 5, eyeY - 7);
+  ctx.lineTo(bx + 14, eyeY - 4);
+  ctx.stroke();
+  ctx.beginPath();
+  ctx.moveTo(bx + 31, eyeY - 7);
+  ctx.lineTo(bx + 22, eyeY - 4);
+  ctx.stroke();
+  ctx.restore();
+
+  // Zigzag mouth
+  ctx.save();
+  ctx.strokeStyle = bg;
+  ctx.lineWidth = 1.5;
+  ctx.beginPath();
+  ctx.moveTo(bx + 10, by + 27);
+  ctx.lineTo(bx + 14, by + 24);
+  ctx.lineTo(bx + 18, by + 27);
+  ctx.lineTo(bx + 22, by + 24);
+  ctx.lineTo(bx + 26, by + 27);
+  ctx.stroke();
+  ctx.restore();
+}
+
+function drawProjectiles(ctx: CanvasRenderingContext2D, boss: BossState) {
+  ctx.save();
+  ctx.fillStyle = COLOR_BOSS;
+  ctx.globalAlpha = 0.8;
+  for (const p of boss.projectiles) {
+    if (p.evaded) continue;
+    ctx.beginPath();
+    ctx.arc(
+      p.x + PROJ_SIZE / 2,
+      p.y + PROJ_SIZE / 2,
+      PROJ_SIZE / 2,
+      0,
+      Math.PI * 2,
+    );
+    ctx.fill();
+  }
+  ctx.restore();
+}
+
+function draw(
+  ctx: CanvasRenderingContext2D,
+  s: GameState,
+  w: number,
+  h: number,
+  fg: string,
+  started: boolean,
+) {
+  ctx.fillStyle = COLOR_BG;
+  ctx.fillRect(0, 0, w, h);
+
+  // Ground
+  ctx.save();
+  ctx.strokeStyle = fg;
+  ctx.globalAlpha = 0.15;
+  ctx.setLineDash([4, 4]);
+  ctx.beginPath();
+  ctx.moveTo(0, s.groundY);
+  ctx.lineTo(w, s.groundY);
+  ctx.stroke();
+  ctx.restore();
+
+  // Character
+  ctx.save();
+  ctx.fillStyle = COLOR_CHAR;
+  ctx.globalAlpha = 0.85;
+  ctx.beginPath();
+  ctx.roundRect(CHAR_X, s.charY, CHAR_SIZE, CHAR_SIZE, 3);
+  ctx.fill();
+  ctx.restore();
+
+  // Eyes
+  ctx.save();
+  ctx.fillStyle = COLOR_BG;
+  ctx.beginPath();
+  ctx.arc(CHAR_X + 6, s.charY + 7, 2.5, 0, Math.PI * 2);
+  ctx.fill();
+  ctx.beginPath();
+  ctx.arc(CHAR_X + 12, s.charY + 7, 2.5, 0, Math.PI * 2);
+  ctx.fill();
+  ctx.restore();
+
+  // Obstacles
+  ctx.save();
+  ctx.fillStyle = fg;
+  ctx.globalAlpha = 0.55;
+  for (const o of s.obstacles) {
+    ctx.fillRect(o.x, s.groundY - o.height, o.width, o.height);
+  }
+  ctx.restore();
+
+  // Boss + projectiles
+  if (s.boss.phase !== "inactive") {
+    drawBoss(ctx, s, COLOR_BG);
+    drawProjectiles(ctx, s.boss);
+  }
+
+  // Score HUD
+  ctx.save();
+  ctx.fillStyle = fg;
+  ctx.globalAlpha = 0.5;
+  ctx.font = "bold 11px monospace";
+  ctx.textAlign = "right";
+  ctx.fillText(`Score: ${s.score}`, w - 12, 20);
+  ctx.fillText(`Best: ${s.highScore}`, w - 12, 34);
+  if (s.boss.phase === "fighting") {
+    ctx.fillText(
+      `Evade: ${s.boss.shotsEvaded}/${BOSS_SHOTS_TO_EVADE}`,
+      w - 12,
+      48,
+    );
+  }
+  ctx.restore();
+
+  // Prompts
+  if (!started && !s.running && !s.over) {
+    ctx.save();
+    ctx.fillStyle = fg;
+    ctx.globalAlpha = 0.5;
+    ctx.font = "12px sans-serif";
+    ctx.textAlign = "center";
+    ctx.fillText("Click or press Space to play while you wait", w / 2, h / 2);
+    ctx.restore();
+  }
+
+  if (s.over) {
+    ctx.save();
+    ctx.fillStyle = fg;
+    ctx.globalAlpha = 0.7;
+    ctx.font = "bold 13px sans-serif";
+    ctx.textAlign = "center";
+    ctx.fillText("Game Over", w / 2, h / 2 - 8);
+    ctx.font = "11px sans-serif";
+    ctx.fillText("Click or Space to restart", w / 2, h / 2 + 10);
+    ctx.restore();
+  }
+}
+
+/* ------------------------------------------------------------------ */
+/*  Hook                                                              */
+/* ------------------------------------------------------------------ */
+
+export function useMiniGame() {
+  const canvasRef = useRef<HTMLCanvasElement>(null);
+  const stateRef = useRef<GameState | null>(null);
+  const rafRef = useRef(0);
+  const startedRef = useRef(false);
+
+  useEffect(() => {
+    const canvas = canvasRef.current;
+    if (!canvas) return;
+
+    const container = canvas.parentElement;
+    if (container) {
+      canvas.width = container.clientWidth;
+      canvas.height = CANVAS_HEIGHT;
+    }
+
+    const groundY = canvas.height - GROUND_PAD;
+    stateRef.current = makeState(groundY);
+
+    const style = getComputedStyle(canvas);
+    let fg = style.color || "#71717a";
+
+    // -------------------------------------------------------------- //
+    //  Jump                                                           //
+    // -------------------------------------------------------------- //
+    function jump() {
+      const s = stateRef.current;
+      if (!s) return;
+
+      if (s.over) {
+        const hs = s.highScore;
+        const gy = s.groundY;
+        stateRef.current = makeState(gy);
+        stateRef.current.highScore = hs;
+        stateRef.current.running = true;
+        startedRef.current = true;
+        return;
+      }
+
+      if (!s.running) {
+        s.running = true;
+        startedRef.current = true;
+        return;
+      }
+
+      // Only jump when on the ground
+      if (s.charY + CHAR_SIZE >= s.groundY) {
+        s.vy = JUMP_FORCE;
+      }
+    }
+
+    function onKey(e: KeyboardEvent) {
+      if (e.code === "Space" || e.key === " ") {
+        e.preventDefault();
+        jump();
+      }
+    }
+
+    function onClick() {
+      canvas?.focus();
+      jump();
+    }
+
+    // -------------------------------------------------------------- //
+    //  Loop                                                           //
+    // -------------------------------------------------------------- //
+    function loop() {
+      const s = stateRef.current;
+      if (!canvas || !s) return;
+      const ctx = canvas.getContext("2d");
+      if (!ctx) return;
+
+      update(s, canvas.width);
+      draw(ctx, s, canvas.width, canvas.height, fg, startedRef.current);
+      rafRef.current = requestAnimationFrame(loop);
+    }
+
+    rafRef.current = requestAnimationFrame(loop);
+
+    canvas.addEventListener("click", onClick);
+    canvas.addEventListener("keydown", onKey);
+
+    const observer = new ResizeObserver((entries) => {
+      for (const entry of entries) {
+        canvas.width = entry.contentRect.width;
+        canvas.height = CANVAS_HEIGHT;
+        if (stateRef.current) {
+          stateRef.current.groundY = canvas.height - GROUND_PAD;
+        }
+        const cs = getComputedStyle(canvas);
+        fg = cs.color || fg;
+      }
+    });
+    if (container) observer.observe(container);
+
+    return () => {
+      cancelAnimationFrame(rafRef.current);
+      canvas.removeEventListener("click", onClick);
+      canvas.removeEventListener("keydown", onKey);
+      observer.disconnect();
+    };
+  }, []);
+
+  return { canvasRef };
+}

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

@@ -1,240 +0,0 @@
-"use client";
-
-import type { ToolUIPart } from "ai";
-import { useMemo } from "react";
-
-import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import {
-  ContentBadge,
-  ContentCard,
-  ContentCardDescription,
-  ContentCardHeader,
-  ContentCardTitle,
-  ContentGrid,
-  ContentLink,
-  ContentMessage,
-  ContentSuggestionsList,
-} from "../../components/ToolAccordion/AccordionContent";
-import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import {
-  AccordionIcon,
-  getAccordionTitle,
-  getAnimationText,
-  getFeatureRequestOutput,
-  isCreatedOutput,
-  isErrorOutput,
-  isNoResultsOutput,
-  isSearchResultsOutput,
-  ToolIcon,
-  type FeatureRequestToolType,
-} from "./helpers";
-
-export interface FeatureRequestToolPart {
-  type: FeatureRequestToolType;
-  toolCallId: string;
-  state: ToolUIPart["state"];
-  input?: unknown;
-  output?: unknown;
-}
-
-interface Props {
-  part: FeatureRequestToolPart;
-}
-
-function truncate(text: string, maxChars: number): string {
-  const trimmed = text.trim();
-  if (trimmed.length <= maxChars) return trimmed;
-  return `${trimmed.slice(0, maxChars).trimEnd()}…`;
-}
-
-export function SearchFeatureRequestsTool({ part }: Props) {
-  const output = getFeatureRequestOutput(part);
-  const text = getAnimationText(part);
-  const isStreaming =
-    part.state === "input-streaming" || part.state === "input-available";
-  const isError =
-    part.state === "output-error" || (!!output && isErrorOutput(output));
-
-  const normalized = useMemo(() => {
-    if (!output) return null;
-    return { title: getAccordionTitle(part.type, output) };
-  }, [output, part.type]);
-
-  const isOutputAvailable = part.state === "output-available" && !!output;
-
-  const searchOutput =
-    isOutputAvailable && output && isSearchResultsOutput(output)
-      ? output
-      : null;
-  const noResultsOutput =
-    isOutputAvailable && output && isNoResultsOutput(output) ? output : null;
-  const errorOutput =
-    isOutputAvailable && output && isErrorOutput(output) ? output : null;
-
-  const hasExpandableContent =
-    isOutputAvailable &&
-    ((!!searchOutput && searchOutput.count > 0) ||
-      !!noResultsOutput ||
-      !!errorOutput);
-
-  const accordionDescription =
-    hasExpandableContent && searchOutput
-      ? `Found ${searchOutput.count} result${searchOutput.count === 1 ? "" : "s"} for "${searchOutput.query}"`
-      : hasExpandableContent && (noResultsOutput || errorOutput)
-        ? ((noResultsOutput ?? errorOutput)?.message ?? null)
-        : null;
-
-  return (
-    <div className="py-2">
-      <div className="flex items-center gap-2 text-sm text-muted-foreground">
-        <ToolIcon
-          toolType={part.type}
-          isStreaming={isStreaming}
-          isError={isError}
-        />
-        <MorphingTextAnimation
-          text={text}
-          className={isError ? "text-red-500" : undefined}
-        />
-      </div>
-
-      {hasExpandableContent && normalized && (
-        <ToolAccordion
-          icon={<AccordionIcon toolType={part.type} />}
-          title={normalized.title}
-          description={accordionDescription}
-        >
-          {searchOutput && (
-            <ContentGrid>
-              {searchOutput.results.map((r) => (
-                <ContentCard key={r.id}>
-                  <ContentCardHeader>
-                    <ContentCardTitle>
-                      {r.identifier} — {r.title}
-                    </ContentCardTitle>
-                  </ContentCardHeader>
-                  {r.description && (
-                    <ContentCardDescription>
-                      {truncate(r.description, 200)}
-                    </ContentCardDescription>
-                  )}
-                </ContentCard>
-              ))}
-            </ContentGrid>
-          )}
-
-          {noResultsOutput && (
-            <div>
-              <ContentMessage>{noResultsOutput.message}</ContentMessage>
-              {noResultsOutput.suggestions &&
-                noResultsOutput.suggestions.length > 0 && (
-                  <ContentSuggestionsList items={noResultsOutput.suggestions} />
-                )}
-            </div>
-          )}
-
-          {errorOutput && (
-            <div>
-              <ContentMessage>{errorOutput.message}</ContentMessage>
-              {errorOutput.error && (
-                <ContentCardDescription>
-                  {errorOutput.error}
-                </ContentCardDescription>
-              )}
-            </div>
-          )}
-        </ToolAccordion>
-      )}
-    </div>
-  );
-}
-
-export function CreateFeatureRequestTool({ part }: Props) {
-  const output = getFeatureRequestOutput(part);
-  const text = getAnimationText(part);
-  const isStreaming =
-    part.state === "input-streaming" || part.state === "input-available";
-  const isError =
-    part.state === "output-error" || (!!output && isErrorOutput(output));
-
-  const normalized = useMemo(() => {
-    if (!output) return null;
-    return { title: getAccordionTitle(part.type, output) };
-  }, [output, part.type]);
-
-  const isOutputAvailable = part.state === "output-available" && !!output;
-
-  const createdOutput =
-    isOutputAvailable && output && isCreatedOutput(output) ? output : null;
-  const errorOutput =
-    isOutputAvailable && output && isErrorOutput(output) ? output : null;
-
-  const hasExpandableContent =
-    isOutputAvailable && (!!createdOutput || !!errorOutput);
-
-  const accordionDescription =
-    hasExpandableContent && createdOutput
-      ? `${createdOutput.issue_identifier} — ${createdOutput.issue_title}`
-      : hasExpandableContent && errorOutput
-        ? errorOutput.message
-        : null;
-
-  return (
-    <div className="py-2">
-      <div className="flex items-center gap-2 text-sm text-muted-foreground">
-        <ToolIcon
-          toolType={part.type}
-          isStreaming={isStreaming}
-          isError={isError}
-        />
-        <MorphingTextAnimation
-          text={text}
-          className={isError ? "text-red-500" : undefined}
-        />
-      </div>
-
-      {hasExpandableContent && normalized && (
-        <ToolAccordion
-          icon={<AccordionIcon toolType={part.type} />}
-          title={normalized.title}
-          description={accordionDescription}
-        >
-          {createdOutput && (
-            <ContentCard>
-              <ContentCardHeader
-                action={
-                  createdOutput.issue_url ? (
-                    <ContentLink href={createdOutput.issue_url}>
-                      View
-                    </ContentLink>
-                  ) : undefined
-                }
-              >
-                <ContentCardTitle>
-                  {createdOutput.issue_identifier} — {createdOutput.issue_title}
-                </ContentCardTitle>
-              </ContentCardHeader>
-              <div className="mt-2 flex items-center gap-2">
-                <ContentBadge>
-                  {createdOutput.is_new_issue ? "New" : "Existing"}
-                </ContentBadge>
-              </div>
-              <ContentMessage>{createdOutput.message}</ContentMessage>
-            </ContentCard>
-          )}
-
-          {errorOutput && (
-            <div>
-              <ContentMessage>{errorOutput.message}</ContentMessage>
-              {errorOutput.error && (
-                <ContentCardDescription>
-                  {errorOutput.error}
-                </ContentCardDescription>
-              )}
-            </div>
-          )}
-        </ToolAccordion>
-      )}
-    </div>
-  );
-}

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

@@ -1,271 +0,0 @@
-import {
-  CheckCircleIcon,
-  LightbulbIcon,
-  MagnifyingGlassIcon,
-  PlusCircleIcon,
-} from "@phosphor-icons/react";
-import type { ToolUIPart } from "ai";
-
-/* ------------------------------------------------------------------ */
-/*  Types (local until API client is regenerated)                      */
-/* ------------------------------------------------------------------ */
-
-interface FeatureRequestInfo {
-  id: string;
-  identifier: string;
-  title: string;
-  description?: string | null;
-}
-
-export interface FeatureRequestSearchResponse {
-  type: "feature_request_search";
-  message: string;
-  results: FeatureRequestInfo[];
-  count: number;
-  query: string;
-}
-
-export interface FeatureRequestCreatedResponse {
-  type: "feature_request_created";
-  message: string;
-  issue_id: string;
-  issue_identifier: string;
-  issue_title: string;
-  issue_url: string;
-  is_new_issue: boolean;
-  customer_name: string;
-}
-
-interface NoResultsResponse {
-  type: "no_results";
-  message: string;
-  suggestions?: string[];
-}
-
-interface ErrorResponse {
-  type: "error";
-  message: string;
-  error?: string;
-}
-
-export type FeatureRequestOutput =
-  | FeatureRequestSearchResponse
-  | FeatureRequestCreatedResponse
-  | NoResultsResponse
-  | ErrorResponse;
-
-export type FeatureRequestToolType =
-  | "tool-search_feature_requests"
-  | "tool-create_feature_request"
-  | string;
-
-/* ------------------------------------------------------------------ */
-/*  Output parsing                                                     */
-/* ------------------------------------------------------------------ */
-
-function parseOutput(output: unknown): FeatureRequestOutput | 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 === "feature_request_search" ||
-      type === "feature_request_created" ||
-      type === "no_results" ||
-      type === "error"
-    ) {
-      return output as FeatureRequestOutput;
-    }
-    // Fallback structural checks
-    if ("results" in output && "query" in output)
-      return output as FeatureRequestSearchResponse;
-    if ("issue_identifier" in output)
-      return output as FeatureRequestCreatedResponse;
-    if ("suggestions" in output && !("error" in output))
-      return output as NoResultsResponse;
-    if ("error" in output || "details" in output)
-      return output as ErrorResponse;
-  }
-  return null;
-}
-
-export function getFeatureRequestOutput(
-  part: unknown,
-): FeatureRequestOutput | null {
-  if (!part || typeof part !== "object") return null;
-  return parseOutput((part as { output?: unknown }).output);
-}
-
-/* ------------------------------------------------------------------ */
-/*  Type guards                                                        */
-/* ------------------------------------------------------------------ */
-
-export function isSearchResultsOutput(
-  output: FeatureRequestOutput,
-): output is FeatureRequestSearchResponse {
-  return (
-    output.type === "feature_request_search" ||
-    ("results" in output && "query" in output)
-  );
-}
-
-export function isCreatedOutput(
-  output: FeatureRequestOutput,
-): output is FeatureRequestCreatedResponse {
-  return (
-    output.type === "feature_request_created" || "issue_identifier" in output
-  );
-}
-
-export function isNoResultsOutput(
-  output: FeatureRequestOutput,
-): output is NoResultsResponse {
-  return (
-    output.type === "no_results" ||
-    ("suggestions" in output && !("error" in output))
-  );
-}
-
-export function isErrorOutput(
-  output: FeatureRequestOutput,
-): output is ErrorResponse {
-  return output.type === "error" || "error" in output;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Accordion metadata                                                 */
-/* ------------------------------------------------------------------ */
-
-export function getAccordionTitle(
-  toolType: FeatureRequestToolType,
-  output: FeatureRequestOutput,
-): string {
-  if (toolType === "tool-search_feature_requests") {
-    if (isSearchResultsOutput(output)) return "Feature requests";
-    if (isNoResultsOutput(output)) return "No feature requests found";
-    return "Feature request search error";
-  }
-  if (isCreatedOutput(output)) {
-    return output.is_new_issue
-      ? "Feature request created"
-      : "Added to feature request";
-  }
-  if (isErrorOutput(output)) return "Feature request error";
-  return "Feature request";
-}
-
-/* ------------------------------------------------------------------ */
-/*  Animation text                                                     */
-/* ------------------------------------------------------------------ */
-
-interface AnimationPart {
-  type: FeatureRequestToolType;
-  state: ToolUIPart["state"];
-  input?: unknown;
-  output?: unknown;
-}
-
-export function getAnimationText(part: AnimationPart): string {
-  if (part.type === "tool-search_feature_requests") {
-    const query = (part.input as { query?: string } | undefined)?.query?.trim();
-    const queryText = query ? ` for "${query}"` : "";
-
-    switch (part.state) {
-      case "input-streaming":
-      case "input-available":
-        return `Searching feature requests${queryText}`;
-      case "output-available": {
-        const output = parseOutput(part.output);
-        if (!output) return `Searching feature requests${queryText}`;
-        if (isSearchResultsOutput(output)) {
-          return `Found ${output.count} feature request${output.count === 1 ? "" : "s"}${queryText}`;
-        }
-        if (isNoResultsOutput(output))
-          return `No feature requests found${queryText}`;
-        return `Error searching feature requests${queryText}`;
-      }
-      case "output-error":
-        return `Error searching feature requests${queryText}`;
-      default:
-        return "Searching feature requests";
-    }
-  }
-
-  // create_feature_request
-  const title = (part.input as { title?: string } | undefined)?.title?.trim();
-  const titleText = title ? ` "${title}"` : "";
-
-  switch (part.state) {
-    case "input-streaming":
-    case "input-available":
-      return `Creating feature request${titleText}`;
-    case "output-available": {
-      const output = parseOutput(part.output);
-      if (!output) return `Creating feature request${titleText}`;
-      if (isCreatedOutput(output)) {
-        return output.is_new_issue
-          ? `Created ${output.issue_identifier}`
-          : `Added to ${output.issue_identifier}`;
-      }
-      if (isErrorOutput(output)) return "Error creating feature request";
-      return `Created feature request${titleText}`;
-    }
-    case "output-error":
-      return "Error creating feature request";
-    default:
-      return "Creating feature request";
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Icons                                                              */
-/* ------------------------------------------------------------------ */
-
-export function ToolIcon({
-  toolType,
-  isStreaming,
-  isError,
-}: {
-  toolType: FeatureRequestToolType;
-  isStreaming?: boolean;
-  isError?: boolean;
-}) {
-  const IconComponent =
-    toolType === "tool-create_feature_request"
-      ? PlusCircleIcon
-      : MagnifyingGlassIcon;
-
-  return (
-    <IconComponent
-      size={14}
-      weight="regular"
-      className={
-        isError
-          ? "text-red-500"
-          : isStreaming
-            ? "text-neutral-500"
-            : "text-neutral-400"
-      }
-    />
-  );
-}
-
-export function AccordionIcon({
-  toolType,
-}: {
-  toolType: FeatureRequestToolType;
-}) {
-  const IconComponent =
-    toolType === "tool-create_feature_request"
-      ? CheckCircleIcon
-      : LightbulbIcon;
-  return <IconComponent size={32} weight="light" />;
-}

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

@@ -1,10 +1,14 @@
 import { useGetV2ListSessions } from "@/app/api/__generated__/endpoints/chat/chat";
+import { toast } from "@/components/molecules/Toast/use-toast";
 import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { useSupabase } from "@/lib/supabase/hooks/useSupabase";
 import { useChat } from "@ai-sdk/react";
 import { DefaultChatTransport } from "ai";
-import { useEffect, useMemo, useState } from "react";
+import { useEffect, useMemo, useRef, useState } from "react";
 import { useChatSession } from "./useChatSession";
+import { useLongRunningToolPolling } from "./hooks/useLongRunningToolPolling";
+
+const STREAM_START_TIMEOUT_MS = 12_000;
 
 export function useCopilotPage() {
   const { isUserLoading, isLoggedIn } = useSupabase();
@@ -52,6 +56,24 @@ export function useCopilotPage() {
     transport: transport ?? undefined,
   });
 
+  // Abort the stream if the backend doesn't start sending data within 12s.
+  const stopRef = useRef(stop);
+  stopRef.current = stop;
+  useEffect(() => {
+    if (status !== "submitted") return;
+
+    const timer = setTimeout(() => {
+      stopRef.current();
+      toast({
+        title: "Stream timed out",
+        description: "The server took too long to respond. Please try again.",
+        variant: "destructive",
+      });
+    }, STREAM_START_TIMEOUT_MS);
+
+    return () => clearTimeout(timer);
+  }, [status]);
+
   useEffect(() => {
     if (!hydratedMessages || hydratedMessages.length === 0) return;
     setMessages((prev) => {
@@ -60,6 +82,11 @@ export function useCopilotPage() {
     });
   }, [hydratedMessages, setMessages]);
 
+  // Poll session endpoint when a long-running tool (create_agent, edit_agent)
+  // is in progress. When the backend completes, the session data will contain
+  // the final tool output — this hook detects the change and updates messages.
+  useLongRunningToolPolling(sessionId, messages, setMessages);
+
   // Clear messages when session is null
   useEffect(() => {
     if (!sessionId) setMessages([]);

autogpt_platform/frontend/src/app/api/openapi.json

@@ -10495,9 +10495,7 @@
           "operation_started",
           "operation_pending",
           "operation_in_progress",
-          "input_validation_error",
-          "feature_request_search",
-          "feature_request_created"
+          "input_validation_error"
         ],
         "title": "ResponseType",
         "description": "Types of tool responses."

docs/integrations/block-integrations/llm.md

@@ -563,7 +563,7 @@ The block supports conversation continuation through three mechanisms:
 |--------|-------------|------|
 | error | Error message if execution failed | str |
 | response | The output/response from Claude Code execution | str |
-| files | List of text files created/modified by Claude Code during this execution. Each file has 'path', 'relative_path', 'name', and 'content' fields. | List[FileOutput] |
+| files | List of text files created/modified by Claude Code during this execution. Each file has 'path', 'relative_path', 'name', 'content', and 'workspace_ref' fields. workspace_ref contains a workspace:// URI if the file was stored to workspace. | List[SandboxFileOutput] |
 | conversation_history | Full conversation history including this turn. Pass this to conversation_history input to continue on a fresh sandbox if the previous sandbox timed out. | str |
 | session_id | Session ID for this conversation. Pass this back along with sandbox_id to continue the conversation. | str |
 | sandbox_id | ID of the sandbox instance. Pass this back along with session_id to continue the conversation. This is None if dispose_sandbox was True (sandbox was disposed). | str |

docs/integrations/block-integrations/misc.md

@@ -215,6 +215,7 @@ The sandbox includes pip and npm pre-installed. Set timeout to limit execution t
 | response | Text output (if any) of the main execution result | str |
 | stdout_logs | Standard output logs from execution | str |
 | stderr_logs | Standard error logs from execution | str |
+| files | Files created or modified during execution. Each file has path, name, content, and workspace_ref (if stored). | List[SandboxFileOutput] |
 
 ### Possible use case
 <!-- MANUAL: use_case -->