delted test script

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

@@ -12,6 +12,7 @@ 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
@@ -45,6 +46,9 @@ 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

@@ -1,154 +0,0 @@
-"""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

@@ -12,19 +12,8 @@ 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,
@@ -101,26 +90,10 @@ def _get_settings() -> Settings:
     return _settings
 
 
-def _is_dummy_mode() -> bool:
-    """Check if dummy mode is enabled for testing."""
-    global _dummy_mode_warned
-    settings = _get_settings()
-    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)."""
+    """Check if external Agent Generator service is configured."""
     settings = _get_settings()
-    return bool(settings.config.agentgenerator_host) or bool(
-        settings.config.agentgenerator_use_dummy
-    )
+    return bool(settings.config.agentgenerator_host)
 
 
 def _get_base_url() -> str:
@@ -164,9 +137,6 @@ 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:
@@ -256,11 +226,6 @@ 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
@@ -332,11 +297,6 @@ 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
@@ -423,11 +383,6 @@ 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
@@ -490,9 +445,6 @@ 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:
@@ -526,9 +478,6 @@ 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

@@ -0,0 +1,369 @@
+"""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

@@ -40,6 +40,9 @@ 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
@@ -421,3 +424,34 @@ 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 TYPE_CHECKING, Literal, Optional
+from typing import Literal, Optional
 
 from e2b import AsyncSandbox as BaseAsyncSandbox
-from pydantic import SecretStr
+from pydantic import BaseModel, SecretStr
 
 from backend.blocks._base import (
     Block,
@@ -20,13 +20,6 @@ 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):
@@ -181,15 +174,22 @@ 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[SandboxFileOutput] = SchemaField(
+        files: list["ClaudeCodeBlock.FileOutput"] = SchemaField(
             description=(
                 "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."
+                "Each file has 'path', 'relative_path', 'name', and 'content' fields."
             )
         )
         conversation_history: str = SchemaField(
@@ -252,7 +252,6 @@ class ClaudeCodeBlock(Block):
                             "relative_path": "index.html",
                             "name": "index.html",
                             "content": "<html>Hello World</html>",
-                            "workspace_ref": None,
                         }
                     ],
                 ),
@@ -268,12 +267,11 @@ class ClaudeCodeBlock(Block):
                 "execute_claude_code": lambda *args, **kwargs: (
                     "Created index.html with hello world content",  # response
                     [
-                        SandboxFileOutput(
+                        ClaudeCodeBlock.FileOutput(
                             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"
@@ -296,8 +294,7 @@ class ClaudeCodeBlock(Block):
         existing_sandbox_id: str,
         conversation_history: str,
         dispose_sandbox: bool,
-        execution_context: "ExecutionContext",
-    ) -> tuple[str, list[SandboxFileOutput], str, str, str]:
+    ) -> tuple[str, list["ClaudeCodeBlock.FileOutput"], str, str, str]:
         """
         Execute Claude Code in an E2B sandbox.
 
@@ -452,18 +449,14 @@ class ClaudeCodeBlock(Block):
                 else:
                     new_conversation_history = turn_entry
 
-            # 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,
+            # Extract files created/modified during this run
+            files = await self._extract_files(
+                sandbox, working_directory, start_timestamp
             )
 
             return (
                 response,
-                sandbox_files,  # Already SandboxFileOutput objects
+                files,
                 new_conversation_history,
                 current_session_id,
                 sandbox_id,
@@ -478,6 +471,140 @@ 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
@@ -490,7 +617,6 @@ class ClaudeCodeBlock(Block):
         *,
         e2b_credentials: APIKeyCredentials,
         anthropic_credentials: APIKeyCredentials,
-        execution_context: "ExecutionContext",
         **kwargs,
     ) -> BlockOutput:
         try:
@@ -511,7 +637,6 @@ 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 TYPE_CHECKING, Any, Literal, Optional
+from typing import Any, Literal, Optional
 
 from e2b_code_interpreter import AsyncSandbox
 from e2b_code_interpreter import Result as E2BExecutionResult
@@ -20,13 +20,6 @@ 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",
@@ -92,9 +85,6 @@ 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,
@@ -105,21 +95,14 @@ 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)
@@ -135,12 +118,6 @@ 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,
@@ -156,24 +133,7 @@ class BaseE2BExecutorMixin:
             stdout_logs = "".join(execution.logs.stdout)
             stderr_logs = "".join(execution.logs.stderr)
 
-            # 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,
-            )
+            return results, text_output, stdout_logs, stderr_logs, sandbox.sandbox_id
         finally:
             # Dispose of sandbox if requested to reduce usage costs
             if dispose_sandbox and sandbox:
@@ -278,12 +238,6 @@ 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__(
@@ -305,30 +259,23 @@ 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, execution_context, extract_files: (  # noqa
+                "execute_code": lambda api_key, code, language, template_id, setup_commands, timeout, dispose_sandbox: (  # 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,
-        execution_context: "ExecutionContext",
-        **kwargs,
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
     ) -> BlockOutput:
         try:
-            results, text_output, stdout, stderr, _, files = await self.execute_code(
+            results, text_output, stdout, stderr, _ = await self.execute_code(
                 api_key=credentials.api_key.get_secret_value(),
                 code=input_data.code,
                 language=input_data.language,
@@ -336,8 +283,6 @@ 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
@@ -351,8 +296,6 @@ 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)
 
@@ -450,7 +393,6 @@ class InstantiateCodeSandboxBlock(Block, BaseE2BExecutorMixin):
                     "Hello World\n",  # stdout_logs
                     "",  # stderr_logs
                     "sandbox_id",  # sandbox_id
-                    [],  # files
                 ),
             },
         )
@@ -459,7 +401,7 @@ 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,
@@ -558,7 +500,6 @@ class ExecuteCodeStepBlock(Block, BaseE2BExecutorMixin):
                     "Hello World\n",  # stdout_logs
                     "",  # stderr_logs
                     sandbox_id,  # sandbox_id
-                    [],  # files
                 ),
             },
         )
@@ -567,7 +508,7 @@ 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

@@ -1,288 +0,0 @@
-"""
-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

@@ -368,10 +368,6 @@ 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,
@@ -662,6 +658,9 @@ 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

@@ -25,7 +25,6 @@ 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/instrumentation-client.ts

@@ -22,11 +22,6 @@ Sentry.init({
 
   enabled: shouldEnable,
 
-  // Suppress cross-origin stylesheet errors from Sentry Replay (rrweb)
-  // serializing DOM snapshots with cross-origin stylesheets
-  // (e.g., from browser extensions or CDN-loaded CSS)
-  ignoreErrors: [/Not allowed to access cross-origin stylesheet/],
-
   // Add optional integrations for additional features
   integrations: [
     Sentry.captureConsoleIntegration(),

autogpt_platform/frontend/src/app/(platform)/build/components/BuilderActions/components/RunGraph/useRunGraph.ts

@@ -4,7 +4,7 @@ import {
 } from "@/app/api/__generated__/endpoints/graphs/graphs";
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { parseAsInteger, parseAsString, useQueryStates } from "nuqs";
-import { GraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
+import { GraphExecutionMeta } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/use-agent-runs";
 import { useGraphStore } from "@/app/(platform)/build/stores/graphStore";
 import { useShallow } from "zustand/react/shallow";
 import { useEffect, useState } from "react";

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

@@ -1,6 +1,6 @@
 import { useCallback } from "react";
 
-import { AgentRunDraftView } from "@/app/(platform)/build/components/legacy-builder/agent-run-draft-view";
+import { AgentRunDraftView } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import type {
   CredentialsMetaInput,

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

@@ -18,7 +18,7 @@ import {
 import { useToast } from "@/components/molecules/Toast/use-toast";
 import { useQueryClient } from "@tanstack/react-query";
 import { getGetV2ListMySubmissionsQueryKey } from "@/app/api/__generated__/endpoints/store/store";
-import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
+import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
 import { humanizeCronExpression } from "@/lib/cron-expression-utils";
 import { CalendarClockIcon } from "lucide-react";
 

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

@@ -15,6 +15,10 @@ 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";
@@ -254,6 +258,20 @@ 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

@@ -0,0 +1,10 @@
+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

@@ -1,126 +0,0 @@
-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

@@ -14,6 +14,10 @@ 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";
@@ -45,6 +49,8 @@ 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;
 
@@ -1421,6 +1427,235 @@ 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

@@ -1,30 +1,24 @@
 "use client";
 
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import {
-  BookOpenIcon,
-  CheckFatIcon,
-  PencilSimpleIcon,
-  WarningDiamondIcon,
-} from "@phosphor-icons/react";
+import { 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,
@@ -58,7 +52,7 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
   const icon = <AccordionIcon />;
 
   if (isAgentSavedOutput(output)) {
-    return { icon, title: output.agent_name, expanded: true };
+    return { icon, title: output.agent_name };
   }
   if (isAgentPreviewOutput(output)) {
     return {
@@ -84,7 +78,6 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
     return {
       icon,
       title: "Creating agent, this may take a few minutes. Sit back and relax.",
-      expanded: true,
     };
   }
   return {
@@ -114,6 +107,8 @@ export function CreateAgentTool({ part }: Props) {
       isOperationPendingOutput(output) ||
       isOperationInProgressOutput(output));
 
+  const progress = useAsymptoticProgress(isOperating);
+
   const hasExpandableContent =
     part.state === "output-available" &&
     !!output &&
@@ -157,53 +152,31 @@ export function CreateAgentTool({ part }: Props) {
         <ToolAccordion {...getAccordionMeta(output)}>
           {isOperating && (
             <ContentGrid>
-              <MiniGame />
+              <ProgressBar value={progress} className="max-w-[280px]" />
               <ContentHint>
-                This could take a few minutes — play while you wait!
+                This could take a few minutes, grab a coffee ☕
               </ContentHint>
             </ContentGrid>
           )}
 
           {isAgentSavedOutput(output) && (
-            <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>
+            <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>
-              <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>
+              <ContentCodeBlock>
+                {truncateText(
+                  formatMaybeJson({ agent_id: output.agent_id }),
+                  800,
+                )}
+              </ContentCodeBlock>
+            </ContentGrid>
           )}
 
           {isAgentPreviewOutput(output) && (

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

@@ -1,21 +0,0 @@
-"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

@@ -1,579 +0,0 @@
-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

@@ -0,0 +1,240 @@
+"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

@@ -0,0 +1,271 @@
+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

@@ -1,14 +1,10 @@
 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, useRef, useState } from "react";
+import { useEffect, useMemo, 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();
@@ -56,24 +52,6 @@ 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) => {
@@ -82,11 +60,6 @@ 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/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/ScheduleListItem.tsx

@@ -29,7 +29,6 @@ export function ScheduleListItem({
       description={formatDistanceToNow(schedule.next_run_time, {
         addSuffix: true,
       })}
-      descriptionTitle={new Date(schedule.next_run_time).toString()}
       onClick={onClick}
       selected={selected}
       icon={

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/SidebarItemCard.tsx

@@ -7,7 +7,6 @@ import React from "react";
 interface Props {
   title: string;
   description?: string;
-  descriptionTitle?: string;
   icon?: React.ReactNode;
   selected?: boolean;
   onClick?: () => void;
@@ -17,7 +16,6 @@ interface Props {
 export function SidebarItemCard({
   title,
   description,
-  descriptionTitle,
   icon,
   selected,
   onClick,
@@ -40,11 +38,7 @@ export function SidebarItemCard({
           >
             {title}
           </Text>
-          <Text
-            variant="body"
-            className="leading-tight !text-zinc-500"
-            title={descriptionTitle}
-          >
+          <Text variant="body" className="leading-tight !text-zinc-500">
             {description}
           </Text>
         </div>

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/sidebar/SidebarRunsList/components/TaskListItem.tsx

@@ -81,9 +81,6 @@ export function TaskListItem({
           ? formatDistanceToNow(run.started_at, { addSuffix: true })
           : "—"
       }
-      descriptionTitle={
-        run.started_at ? new Date(run.started_at).toString() : undefined
-      }
       onClick={onClick}
       selected={selected}
       actions={

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView.tsx

@@ -0,0 +1,631 @@
+"use client";
+import { useParams, useRouter } from "next/navigation";
+import { useQueryState } from "nuqs";
+import React, {
+  useCallback,
+  useEffect,
+  useMemo,
+  useRef,
+  useState,
+} from "react";
+
+import {
+  Graph,
+  GraphExecution,
+  GraphExecutionID,
+  GraphExecutionMeta,
+  GraphID,
+  LibraryAgent,
+  LibraryAgentID,
+  LibraryAgentPreset,
+  LibraryAgentPresetID,
+  Schedule,
+  ScheduleID,
+} from "@/lib/autogpt-server-api";
+import { useBackendAPI } from "@/lib/autogpt-server-api/context";
+import { exportAsJSONFile } from "@/lib/utils";
+
+import DeleteConfirmDialog from "@/components/__legacy__/delete-confirm-dialog";
+import type { ButtonAction } from "@/components/__legacy__/types";
+import { Button } from "@/components/__legacy__/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/__legacy__/ui/dialog";
+import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
+import {
+  useToast,
+  useToastOnFail,
+} from "@/components/molecules/Toast/use-toast";
+import { AgentRunDetailsView } from "./components/agent-run-details-view";
+import { AgentRunDraftView } from "./components/agent-run-draft-view";
+import { CreatePresetDialog } from "./components/create-preset-dialog";
+import { useAgentRunsInfinite } from "./use-agent-runs";
+import { AgentRunsSelectorList } from "./components/agent-runs-selector-list";
+import { AgentScheduleDetailsView } from "./components/agent-schedule-details-view";
+
+export function OldAgentLibraryView() {
+  const { id: agentID }: { id: LibraryAgentID } = useParams();
+  const [executionId, setExecutionId] = useQueryState("executionId");
+  const toastOnFail = useToastOnFail();
+  const { toast } = useToast();
+  const router = useRouter();
+  const api = useBackendAPI();
+
+  // ============================ STATE =============================
+
+  const [graph, setGraph] = useState<Graph | null>(null); // Graph version corresponding to LibraryAgent
+  const [agent, setAgent] = useState<LibraryAgent | null>(null);
+  const agentRunsQuery = useAgentRunsInfinite(graph?.id); // only runs once graph.id is known
+  const agentRuns = agentRunsQuery.agentRuns;
+  const [agentPresets, setAgentPresets] = useState<LibraryAgentPreset[]>([]);
+  const [schedules, setSchedules] = useState<Schedule[]>([]);
+  const [selectedView, selectView] = useState<
+    | { type: "run"; id?: GraphExecutionID }
+    | { type: "preset"; id: LibraryAgentPresetID }
+    | { type: "schedule"; id: ScheduleID }
+  >({ type: "run" });
+  const [selectedRun, setSelectedRun] = useState<
+    GraphExecution | GraphExecutionMeta | null
+  >(null);
+  const selectedSchedule =
+    selectedView.type == "schedule"
+      ? schedules.find((s) => s.id == selectedView.id)
+      : null;
+  const [isFirstLoad, setIsFirstLoad] = useState<boolean>(true);
+  const [agentDeleteDialogOpen, setAgentDeleteDialogOpen] =
+    useState<boolean>(false);
+  const [confirmingDeleteAgentRun, setConfirmingDeleteAgentRun] =
+    useState<GraphExecutionMeta | null>(null);
+  const [confirmingDeleteAgentPreset, setConfirmingDeleteAgentPreset] =
+    useState<LibraryAgentPresetID | null>(null);
+  const [copyAgentDialogOpen, setCopyAgentDialogOpen] = useState(false);
+  const [creatingPresetFromExecutionID, setCreatingPresetFromExecutionID] =
+    useState<GraphExecutionID | null>(null);
+
+  // Set page title with agent name
+  useEffect(() => {
+    if (agent) {
+      document.title = `${agent.name} - Library - AutoGPT Platform`;
+    }
+  }, [agent]);
+
+  const openRunDraftView = useCallback(() => {
+    selectView({ type: "run" });
+  }, []);
+
+  const selectRun = useCallback((id: GraphExecutionID) => {
+    selectView({ type: "run", id });
+  }, []);
+
+  const selectPreset = useCallback((id: LibraryAgentPresetID) => {
+    selectView({ type: "preset", id });
+  }, []);
+
+  const selectSchedule = useCallback((id: ScheduleID) => {
+    selectView({ type: "schedule", id });
+  }, []);
+
+  const graphVersions = useRef<Record<number, Graph>>({});
+  const loadingGraphVersions = useRef<Record<number, Promise<Graph>>>({});
+  const getGraphVersion = useCallback(
+    async (graphID: GraphID, version: number) => {
+      if (version in graphVersions.current)
+        return graphVersions.current[version];
+      if (version in loadingGraphVersions.current)
+        return loadingGraphVersions.current[version];
+
+      const pendingGraph = api.getGraph(graphID, version).then((graph) => {
+        graphVersions.current[version] = graph;
+        return graph;
+      });
+      // Cache promise as well to avoid duplicate requests
+      loadingGraphVersions.current[version] = pendingGraph;
+      return pendingGraph;
+    },
+    [api, graphVersions, loadingGraphVersions],
+  );
+
+  const lastRefresh = useRef<number>(0);
+  const refreshPageData = useCallback(() => {
+    if (Date.now() - lastRefresh.current < 2e3) return; // 2 second debounce
+    lastRefresh.current = Date.now();
+
+    api.getLibraryAgent(agentID).then((agent) => {
+      setAgent(agent);
+
+      getGraphVersion(agent.graph_id, agent.graph_version).then(
+        (_graph) =>
+          (graph && graph.version == _graph.version) || setGraph(_graph),
+      );
+      Promise.all([
+        agentRunsQuery.refetchRuns(),
+        api.listLibraryAgentPresets({
+          graph_id: agent.graph_id,
+          page_size: 100,
+        }),
+      ]).then(([runsQueryResult, presets]) => {
+        setAgentPresets(presets.presets);
+
+        const newestAgentRunsResponse = runsQueryResult.data?.pages[0];
+        if (!newestAgentRunsResponse || newestAgentRunsResponse.status != 200)
+          return;
+        const newestAgentRuns = newestAgentRunsResponse.data.executions;
+        // Preload the corresponding graph versions for the latest 10 runs
+        new Set(
+          newestAgentRuns.slice(0, 10).map((run) => run.graph_version),
+        ).forEach((version) => getGraphVersion(agent.graph_id, version));
+      });
+    });
+  }, [api, agentID, getGraphVersion, graph]);
+
+  // On first load: select the latest run
+  useEffect(() => {
+    // Only for first load or first execution
+    if (selectedView.id || !isFirstLoad) return;
+    if (agentRuns.length == 0 && agentPresets.length == 0) return;
+
+    setIsFirstLoad(false);
+    if (agentRuns.length > 0) {
+      // select latest run
+      const latestRun = agentRuns.reduce((latest, current) => {
+        if (!latest.started_at && !current.started_at) return latest;
+        if (!latest.started_at) return current;
+        if (!current.started_at) return latest;
+        return latest.started_at > current.started_at ? latest : current;
+      }, agentRuns[0]);
+      selectRun(latestRun.id as GraphExecutionID);
+    } else {
+      // select top preset
+      const latestPreset = agentPresets.toSorted(
+        (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
+      )[0];
+      selectPreset(latestPreset.id);
+    }
+  }, [
+    isFirstLoad,
+    selectedView.id,
+    agentRuns,
+    agentPresets,
+    selectRun,
+    selectPreset,
+  ]);
+
+  useEffect(() => {
+    if (executionId) {
+      selectRun(executionId as GraphExecutionID);
+      setExecutionId(null);
+    }
+  }, [executionId, selectRun, setExecutionId]);
+
+  // Initial load
+  useEffect(() => {
+    refreshPageData();
+
+    // Show a toast when the WebSocket connection disconnects
+    let connectionToast: ReturnType<typeof toast> | null = null;
+    const cancelDisconnectHandler = api.onWebSocketDisconnect(() => {
+      connectionToast ??= toast({
+        title: "Connection to server was lost",
+        variant: "destructive",
+        description: (
+          <div className="flex items-center">
+            Trying to reconnect...
+            <LoadingSpinner className="ml-1.5 size-3.5" />
+          </div>
+        ),
+        duration: Infinity,
+        dismissable: true,
+      });
+    });
+    const cancelConnectHandler = api.onWebSocketConnect(() => {
+      if (connectionToast)
+        connectionToast.update({
+          id: connectionToast.id,
+          title: "✅ Connection re-established",
+          variant: "default",
+          description: (
+            <div className="flex items-center">
+              Refreshing data...
+              <LoadingSpinner className="ml-1.5 size-3.5" />
+            </div>
+          ),
+          duration: 2000,
+          dismissable: true,
+        });
+      connectionToast = null;
+    });
+    return () => {
+      cancelDisconnectHandler();
+      cancelConnectHandler();
+    };
+  }, []);
+
+  // Subscribe to WebSocket updates for agent runs
+  useEffect(() => {
+    if (!agent?.graph_id) return;
+
+    return api.onWebSocketConnect(() => {
+      refreshPageData(); // Sync up on (re)connect
+
+      // Subscribe to all executions for this agent
+      api.subscribeToGraphExecutions(agent.graph_id);
+    });
+  }, [api, agent?.graph_id, refreshPageData]);
+
+  // Handle execution updates
+  useEffect(() => {
+    const detachExecUpdateHandler = api.onWebSocketMessage(
+      "graph_execution_event",
+      (data) => {
+        if (data.graph_id != agent?.graph_id) return;
+
+        agentRunsQuery.upsertAgentRun(data);
+        if (data.id === selectedView.id) {
+          // Update currently viewed run
+          setSelectedRun(data);
+        }
+      },
+    );
+
+    return () => {
+      detachExecUpdateHandler();
+    };
+  }, [api, agent?.graph_id, selectedView.id]);
+
+  // Pre-load selectedRun based on selectedView
+  useEffect(() => {
+    if (selectedView.type != "run" || !selectedView.id) return;
+
+    const newSelectedRun = agentRuns.find((run) => run.id == selectedView.id);
+    if (selectedView.id !== selectedRun?.id) {
+      // Pull partial data from "cache" while waiting for the rest to load
+      setSelectedRun((newSelectedRun as GraphExecutionMeta) ?? null);
+    }
+  }, [api, selectedView, agentRuns, selectedRun?.id]);
+
+  // Load selectedRun based on selectedView; refresh on agent refresh
+  useEffect(() => {
+    if (selectedView.type != "run" || !selectedView.id || !agent) return;
+
+    api
+      .getGraphExecutionInfo(agent.graph_id, selectedView.id)
+      .then(async (run) => {
+        // Ensure corresponding graph version is available before rendering I/O
+        await getGraphVersion(run.graph_id, run.graph_version);
+        setSelectedRun(run);
+      });
+  }, [api, selectedView, agent, getGraphVersion]);
+
+  const fetchSchedules = useCallback(async () => {
+    if (!agent) return;
+
+    setSchedules(await api.listGraphExecutionSchedules(agent.graph_id));
+  }, [api, agent?.graph_id]);
+
+  useEffect(() => {
+    fetchSchedules();
+  }, [fetchSchedules]);
+
+  // =========================== ACTIONS ============================
+
+  const deleteRun = useCallback(
+    async (run: GraphExecutionMeta) => {
+      if (run.status == "RUNNING" || run.status == "QUEUED") {
+        await api.stopGraphExecution(run.graph_id, run.id);
+      }
+      await api.deleteGraphExecution(run.id);
+
+      setConfirmingDeleteAgentRun(null);
+      if (selectedView.type == "run" && selectedView.id == run.id) {
+        openRunDraftView();
+      }
+      agentRunsQuery.removeAgentRun(run.id);
+    },
+    [api, selectedView, openRunDraftView],
+  );
+
+  const deletePreset = useCallback(
+    async (presetID: LibraryAgentPresetID) => {
+      await api.deleteLibraryAgentPreset(presetID);
+
+      setConfirmingDeleteAgentPreset(null);
+      if (selectedView.type == "preset" && selectedView.id == presetID) {
+        openRunDraftView();
+      }
+      setAgentPresets((presets) => presets.filter((p) => p.id !== presetID));
+    },
+    [api, selectedView, openRunDraftView],
+  );
+
+  const deleteSchedule = useCallback(
+    async (scheduleID: ScheduleID) => {
+      const removedSchedule =
+        await api.deleteGraphExecutionSchedule(scheduleID);
+
+      setSchedules((schedules) => {
+        const newSchedules = schedules.filter(
+          (s) => s.id !== removedSchedule.id,
+        );
+        if (
+          selectedView.type == "schedule" &&
+          selectedView.id == removedSchedule.id
+        ) {
+          if (newSchedules.length > 0) {
+            // Select next schedule if available
+            selectSchedule(newSchedules[0].id);
+          } else {
+            // Reset to draft view if current schedule was deleted
+            openRunDraftView();
+          }
+        }
+        return newSchedules;
+      });
+      openRunDraftView();
+    },
+    [schedules, api],
+  );
+
+  const handleCreatePresetFromRun = useCallback(
+    async (name: string, description: string) => {
+      if (!creatingPresetFromExecutionID) return;
+
+      await api
+        .createLibraryAgentPreset({
+          name,
+          description,
+          graph_execution_id: creatingPresetFromExecutionID,
+        })
+        .then((preset) => {
+          setAgentPresets((prev) => [...prev, preset]);
+          selectPreset(preset.id);
+          setCreatingPresetFromExecutionID(null);
+        })
+        .catch(toastOnFail("create a preset"));
+    },
+    [api, creatingPresetFromExecutionID, selectPreset, toast],
+  );
+
+  const downloadGraph = useCallback(
+    async () =>
+      agent &&
+      // Export sanitized graph from backend
+      api
+        .getGraph(agent.graph_id, agent.graph_version, true)
+        .then((graph) =>
+          exportAsJSONFile(graph, `${graph.name}_v${graph.version}.json`),
+        ),
+    [api, agent],
+  );
+
+  const copyAgent = useCallback(async () => {
+    setCopyAgentDialogOpen(false);
+    api
+      .forkLibraryAgent(agentID)
+      .then((newAgent) => {
+        router.push(`/library/agents/${newAgent.id}`);
+      })
+      .catch((error) => {
+        console.error("Error copying agent:", error);
+        toast({
+          title: "Error copying agent",
+          description: `An error occurred while copying the agent: ${error.message}`,
+          variant: "destructive",
+        });
+      });
+  }, [agentID, api, router, toast]);
+
+  const agentActions: ButtonAction[] = useMemo(
+    () => [
+      {
+        label: "Customize agent",
+        href: `/build?flowID=${agent?.graph_id}&flowVersion=${agent?.graph_version}`,
+        disabled: !agent?.can_access_graph,
+      },
+      { label: "Export agent to file", callback: downloadGraph },
+      ...(!agent?.can_access_graph
+        ? [
+            {
+              label: "Edit a copy",
+              callback: () => setCopyAgentDialogOpen(true),
+            },
+          ]
+        : []),
+      {
+        label: "Delete agent",
+        callback: () => setAgentDeleteDialogOpen(true),
+      },
+    ],
+    [agent, downloadGraph],
+  );
+
+  const runGraph =
+    graphVersions.current[selectedRun?.graph_version ?? 0] ?? graph;
+
+  const onCreateSchedule = useCallback(
+    (schedule: Schedule) => {
+      setSchedules((prev) => [...prev, schedule]);
+      selectSchedule(schedule.id);
+    },
+    [selectView],
+  );
+
+  const onCreatePreset = useCallback(
+    (preset: LibraryAgentPreset) => {
+      setAgentPresets((prev) => [...prev, preset]);
+      selectPreset(preset.id);
+    },
+    [selectPreset],
+  );
+
+  const onUpdatePreset = useCallback(
+    (updated: LibraryAgentPreset) => {
+      setAgentPresets((prev) =>
+        prev.map((p) => (p.id === updated.id ? updated : p)),
+      );
+      selectPreset(updated.id);
+    },
+    [selectPreset],
+  );
+
+  if (!agent || !graph) {
+    return <LoadingBox className="h-[90vh]" />;
+  }
+
+  return (
+    <div className="container justify-stretch p-0 pt-16 lg:flex">
+      {/* Sidebar w/ list of runs */}
+      {/* TODO: render this below header in sm and md layouts */}
+      <AgentRunsSelectorList
+        className="agpt-div w-full border-b pb-2 lg:w-auto lg:border-b-0 lg:border-r lg:pb-0"
+        agent={agent}
+        agentRunsQuery={agentRunsQuery}
+        agentPresets={agentPresets}
+        schedules={schedules}
+        selectedView={selectedView}
+        onSelectRun={selectRun}
+        onSelectPreset={selectPreset}
+        onSelectSchedule={selectSchedule}
+        onSelectDraftNewRun={openRunDraftView}
+        doDeleteRun={setConfirmingDeleteAgentRun}
+        doDeletePreset={setConfirmingDeleteAgentPreset}
+        doDeleteSchedule={deleteSchedule}
+        doCreatePresetFromRun={setCreatingPresetFromExecutionID}
+      />
+
+      <div className="flex-1">
+        {/* Header */}
+        <div className="agpt-div w-full border-b">
+          <h1
+            data-testid="agent-title"
+            className="font-poppins text-3xl font-medium"
+          >
+            {
+              agent.name /* TODO: use dynamic/custom run title - https://github.com/Significant-Gravitas/AutoGPT/issues/9184 */
+            }
+          </h1>
+        </div>
+
+        {/* Run / Schedule views */}
+        {(selectedView.type == "run" && selectedView.id ? (
+          selectedRun && runGraph ? (
+            <AgentRunDetailsView
+              agent={agent}
+              graph={runGraph}
+              run={selectedRun}
+              agentActions={agentActions}
+              onRun={selectRun}
+              doDeleteRun={() => setConfirmingDeleteAgentRun(selectedRun)}
+              doCreatePresetFromRun={() =>
+                setCreatingPresetFromExecutionID(selectedRun.id)
+              }
+            />
+          ) : null
+        ) : selectedView.type == "run" ? (
+          /* Draft new runs / Create new presets */
+          <AgentRunDraftView
+            graph={graph}
+            onRun={selectRun}
+            onCreateSchedule={onCreateSchedule}
+            onCreatePreset={onCreatePreset}
+            agentActions={agentActions}
+            recommendedScheduleCron={agent?.recommended_schedule_cron || null}
+          />
+        ) : selectedView.type == "preset" ? (
+          /* Edit & update presets */
+          <AgentRunDraftView
+            graph={graph}
+            agentPreset={
+              agentPresets.find((preset) => preset.id == selectedView.id)!
+            }
+            onRun={selectRun}
+            recommendedScheduleCron={agent?.recommended_schedule_cron || null}
+            onCreateSchedule={onCreateSchedule}
+            onUpdatePreset={onUpdatePreset}
+            doDeletePreset={setConfirmingDeleteAgentPreset}
+            agentActions={agentActions}
+          />
+        ) : selectedView.type == "schedule" ? (
+          selectedSchedule &&
+          graph && (
+            <AgentScheduleDetailsView
+              graph={graph}
+              schedule={selectedSchedule}
+              // agent={agent}
+              agentActions={agentActions}
+              onForcedRun={selectRun}
+              doDeleteSchedule={deleteSchedule}
+            />
+          )
+        ) : null) || <LoadingBox className="h-[70vh]" />}
+
+        <DeleteConfirmDialog
+          entityType="agent"
+          open={agentDeleteDialogOpen}
+          onOpenChange={setAgentDeleteDialogOpen}
+          onDoDelete={() =>
+            agent &&
+            api.deleteLibraryAgent(agent.id).then(() => router.push("/library"))
+          }
+        />
+
+        <DeleteConfirmDialog
+          entityType="agent run"
+          open={!!confirmingDeleteAgentRun}
+          onOpenChange={(open) => !open && setConfirmingDeleteAgentRun(null)}
+          onDoDelete={() =>
+            confirmingDeleteAgentRun && deleteRun(confirmingDeleteAgentRun)
+          }
+        />
+        <DeleteConfirmDialog
+          entityType={agent.has_external_trigger ? "trigger" : "agent preset"}
+          open={!!confirmingDeleteAgentPreset}
+          onOpenChange={(open) => !open && setConfirmingDeleteAgentPreset(null)}
+          onDoDelete={() =>
+            confirmingDeleteAgentPreset &&
+            deletePreset(confirmingDeleteAgentPreset)
+          }
+        />
+        {/* Copy agent confirmation dialog */}
+        <Dialog
+          onOpenChange={setCopyAgentDialogOpen}
+          open={copyAgentDialogOpen}
+        >
+          <DialogContent>
+            <DialogHeader>
+              <DialogTitle>You&apos;re making an editable copy</DialogTitle>
+              <DialogDescription className="pt-2">
+                The original Marketplace agent stays the same and cannot be
+                edited. We&apos;ll save a new version of this agent to your
+                Library. From there, you can customize it however you&apos;d
+                like by clicking &quot;Customize agent&quot; — this will open
+                the builder where you can see and modify the inner workings.
+              </DialogDescription>
+            </DialogHeader>
+            <DialogFooter className="justify-end">
+              <Button
+                type="button"
+                variant="outline"
+                onClick={() => setCopyAgentDialogOpen(false)}
+              >
+                Cancel
+              </Button>
+              <Button type="button" onClick={copyAgent}>
+                Continue
+              </Button>
+            </DialogFooter>
+          </DialogContent>
+        </Dialog>
+        <CreatePresetDialog
+          open={!!creatingPresetFromExecutionID}
+          onOpenChange={() => setCreatingPresetFromExecutionID(null)}
+          onConfirm={handleCreatePresetFromRun}
+        />
+      </div>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-details-view.tsx

@@ -0,0 +1,445 @@
+"use client";
+import { format, formatDistanceToNow, formatDistanceStrict } from "date-fns";
+import React, { useCallback, useMemo, useEffect } from "react";
+
+import {
+  Graph,
+  GraphExecution,
+  GraphExecutionID,
+  GraphExecutionMeta,
+  LibraryAgent,
+} from "@/lib/autogpt-server-api";
+import { useBackendAPI } from "@/lib/autogpt-server-api/context";
+
+import ActionButtonGroup from "@/components/__legacy__/action-button-group";
+import type { ButtonAction } from "@/components/__legacy__/types";
+import {
+  Card,
+  CardContent,
+  CardHeader,
+  CardTitle,
+} from "@/components/__legacy__/ui/card";
+import {
+  IconRefresh,
+  IconSquare,
+  IconCircleAlert,
+} from "@/components/__legacy__/ui/icons";
+import { Input } from "@/components/__legacy__/ui/input";
+import LoadingBox from "@/components/__legacy__/ui/loading";
+import {
+  Tooltip,
+  TooltipContent,
+  TooltipProvider,
+  TooltipTrigger,
+} from "@/components/atoms/Tooltip/BaseTooltip";
+import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
+
+import { AgentRunStatus, agentRunStatusMap } from "./agent-run-status-chip";
+import useCredits from "@/hooks/useCredits";
+import { AgentRunOutputView } from "./agent-run-output-view";
+import { analytics } from "@/services/analytics";
+import { PendingReviewsList } from "@/components/organisms/PendingReviewsList/PendingReviewsList";
+import { usePendingReviewsForExecution } from "@/hooks/usePendingReviews";
+
+export function AgentRunDetailsView({
+  agent,
+  graph,
+  run,
+  agentActions,
+  onRun,
+  doDeleteRun,
+  doCreatePresetFromRun,
+}: {
+  agent: LibraryAgent;
+  graph: Graph;
+  run: GraphExecution | GraphExecutionMeta;
+  agentActions: ButtonAction[];
+  onRun: (runID: GraphExecutionID) => void;
+  doDeleteRun: () => void;
+  doCreatePresetFromRun: () => void;
+}): React.ReactNode {
+  const api = useBackendAPI();
+  const { formatCredits } = useCredits();
+
+  const runStatus: AgentRunStatus = useMemo(
+    () => agentRunStatusMap[run.status],
+    [run],
+  );
+
+  const {
+    pendingReviews,
+    isLoading: reviewsLoading,
+    refetch: refetchReviews,
+  } = usePendingReviewsForExecution(run.id);
+
+  const toastOnFail = useToastOnFail();
+
+  // Refetch pending reviews when execution status changes to REVIEW
+  useEffect(() => {
+    if (runStatus === "review" && run.id) {
+      refetchReviews();
+    }
+  }, [runStatus, run.id, refetchReviews]);
+
+  const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
+    if (!run) return [];
+    return [
+      {
+        label: "Status",
+        value: runStatus.charAt(0).toUpperCase() + runStatus.slice(1),
+      },
+      {
+        label: "Started",
+        value: run.started_at
+          ? `${formatDistanceToNow(run.started_at, { addSuffix: true })}, ${format(run.started_at, "HH:mm")}`
+          : "—",
+      },
+      ...(run.stats
+        ? [
+            {
+              label: "Duration",
+              value: formatDistanceStrict(0, run.stats.duration * 1000),
+            },
+            { label: "Steps", value: run.stats.node_exec_count },
+            { label: "Cost", value: formatCredits(run.stats.cost) },
+          ]
+        : []),
+    ];
+  }, [run, runStatus, formatCredits]);
+
+  const agentRunInputs:
+    | Record<
+        string,
+        {
+          title?: string;
+          /* type: BlockIOSubType; */
+          value: string | number | undefined;
+        }
+      >
+    | undefined = useMemo(() => {
+    if (!run.inputs) return undefined;
+    // TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
+
+    // Add type info from agent input schema
+    return Object.fromEntries(
+      Object.entries(run.inputs).map(([k, v]) => [
+        k,
+        {
+          title: graph.input_schema.properties[k]?.title,
+          // type: graph.input_schema.properties[k].type, // TODO: implement typed graph inputs
+          value: typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
+        },
+      ]),
+    );
+  }, [graph, run]);
+
+  const runAgain = useCallback(() => {
+    if (
+      !run.inputs ||
+      !(graph.credentials_input_schema?.required ?? []).every(
+        (k) => k in (run.credential_inputs ?? {}),
+      )
+    )
+      return;
+
+    if (run.preset_id) {
+      return api
+        .executeLibraryAgentPreset(
+          run.preset_id,
+          run.inputs!,
+          run.credential_inputs!,
+        )
+        .then(({ id }) => {
+          analytics.sendDatafastEvent("run_agent", {
+            name: graph.name,
+            id: graph.id,
+          });
+          onRun(id);
+        })
+        .catch(toastOnFail("execute agent preset"));
+    }
+
+    return api
+      .executeGraph(
+        graph.id,
+        graph.version,
+        run.inputs!,
+        run.credential_inputs!,
+        "library",
+      )
+      .then(({ id }) => {
+        analytics.sendDatafastEvent("run_agent", {
+          name: graph.name,
+          id: graph.id,
+        });
+        onRun(id);
+      })
+      .catch(toastOnFail("execute agent"));
+  }, [api, graph, run, onRun, toastOnFail]);
+
+  const stopRun = useCallback(
+    () => api.stopGraphExecution(graph.id, run.id),
+    [api, graph.id, run.id],
+  );
+
+  const agentRunOutputs:
+    | Record<
+        string,
+        {
+          title?: string;
+          /* type: BlockIOSubType; */
+          values: Array<React.ReactNode>;
+        }
+      >
+    | null
+    | undefined = useMemo(() => {
+    if (!("outputs" in run)) return undefined;
+    if (!["running", "success", "failed", "stopped"].includes(runStatus))
+      return null;
+
+    // Add type info from agent input schema
+    return Object.fromEntries(
+      Object.entries(run.outputs).map(([k, vv]) => [
+        k,
+        {
+          title: graph.output_schema.properties[k].title,
+          /* type: agent.output_schema.properties[k].type */
+          values: vv.map((v) =>
+            typeof v == "object" ? JSON.stringify(v, undefined, 2) : v,
+          ),
+        },
+      ]),
+    );
+  }, [graph, run, runStatus]);
+
+  const runActions: ButtonAction[] = useMemo(
+    () => [
+      ...(["running", "queued"].includes(runStatus)
+        ? ([
+            {
+              label: (
+                <>
+                  <IconSquare className="mr-2 size-4" />
+                  Stop run
+                </>
+              ),
+              variant: "secondary",
+              callback: stopRun,
+            },
+          ] satisfies ButtonAction[])
+        : []),
+      ...(["success", "failed", "stopped"].includes(runStatus) &&
+      !graph.has_external_trigger &&
+      (graph.credentials_input_schema?.required ?? []).every(
+        (k) => k in (run.credential_inputs ?? {}),
+      )
+        ? [
+            {
+              label: (
+                <>
+                  <IconRefresh className="mr-2 size-4" />
+                  Run again
+                </>
+              ),
+              callback: runAgain,
+              dataTestId: "run-again-button",
+            },
+          ]
+        : []),
+      ...(agent.can_access_graph
+        ? [
+            {
+              label: "Open run in builder",
+              href: `/build?flowID=${run.graph_id}&flowVersion=${run.graph_version}&flowExecutionID=${run.id}`,
+            },
+          ]
+        : []),
+      { label: "Create preset from run", callback: doCreatePresetFromRun },
+      { label: "Delete run", variant: "secondary", callback: doDeleteRun },
+    ],
+    [
+      runStatus,
+      runAgain,
+      stopRun,
+      doDeleteRun,
+      doCreatePresetFromRun,
+      graph.has_external_trigger,
+      graph.credentials_input_schema?.required,
+      agent.can_access_graph,
+      run.graph_id,
+      run.graph_version,
+      run.id,
+    ],
+  );
+
+  return (
+    <div className="agpt-div flex gap-6">
+      <div className="flex flex-1 flex-col gap-4">
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Info</CardTitle>
+          </CardHeader>
+
+          <CardContent>
+            <div className="flex justify-stretch gap-4">
+              {infoStats.map(({ label, value }) => (
+                <div key={label} className="flex-1">
+                  <p className="text-sm font-medium text-black">{label}</p>
+                  <p className="text-sm text-neutral-600">{value}</p>
+                </div>
+              ))}
+            </div>
+            {run.status === "FAILED" && (
+              <div className="mt-4 rounded-md border border-red-200 bg-red-50 p-3 dark:border-red-800 dark:bg-red-900/20">
+                <p className="text-sm text-red-800 dark:text-red-200">
+                  <strong>Error:</strong>{" "}
+                  {run.stats?.error ||
+                    "The execution failed due to an internal error. You can re-run the agent to retry."}
+                </p>
+              </div>
+            )}
+          </CardContent>
+        </Card>
+
+        {/* Smart Agent Execution Summary */}
+        {run.stats?.activity_status && (
+          <Card className="agpt-box">
+            <CardHeader>
+              <CardTitle className="flex items-center gap-2 font-poppins text-lg">
+                Task Summary
+                <TooltipProvider>
+                  <Tooltip>
+                    <TooltipTrigger asChild>
+                      <IconCircleAlert className="size-4 cursor-help text-neutral-500 hover:text-neutral-700" />
+                    </TooltipTrigger>
+                    <TooltipContent>
+                      <p className="max-w-xs">
+                        This AI-generated summary describes how the agent
+                        handled your task. It’s an experimental feature and may
+                        occasionally be inaccurate.
+                      </p>
+                    </TooltipContent>
+                  </Tooltip>
+                </TooltipProvider>
+              </CardTitle>
+            </CardHeader>
+            <CardContent className="space-y-4">
+              <p className="text-sm leading-relaxed text-neutral-700">
+                {run.stats.activity_status}
+              </p>
+
+              {/* Correctness Score */}
+              {typeof run.stats.correctness_score === "number" && (
+                <div className="flex items-center gap-3 rounded-lg bg-neutral-50 p-3">
+                  <div className="flex items-center gap-2">
+                    <span className="text-sm font-medium text-neutral-600">
+                      Success Estimate:
+                    </span>
+                    <div className="flex items-center gap-2">
+                      <div className="relative h-2 w-16 overflow-hidden rounded-full bg-neutral-200">
+                        <div
+                          className={`h-full transition-all ${
+                            run.stats.correctness_score >= 0.8
+                              ? "bg-green-500"
+                              : run.stats.correctness_score >= 0.6
+                                ? "bg-yellow-500"
+                                : run.stats.correctness_score >= 0.4
+                                  ? "bg-orange-500"
+                                  : "bg-red-500"
+                          }`}
+                          style={{
+                            width: `${Math.round(run.stats.correctness_score * 100)}%`,
+                          }}
+                        />
+                      </div>
+                      <span className="text-sm font-medium">
+                        {Math.round(run.stats.correctness_score * 100)}%
+                      </span>
+                    </div>
+                  </div>
+                  <TooltipProvider>
+                    <Tooltip>
+                      <TooltipTrigger asChild>
+                        <IconCircleAlert className="size-4 cursor-help text-neutral-400 hover:text-neutral-600" />
+                      </TooltipTrigger>
+                      <TooltipContent>
+                        <p className="max-w-xs">
+                          AI-generated estimate of how well this execution
+                          achieved its intended purpose. This score indicates
+                          {run.stats.correctness_score >= 0.8
+                            ? " the agent was highly successful."
+                            : run.stats.correctness_score >= 0.6
+                              ? " the agent was mostly successful with minor issues."
+                              : run.stats.correctness_score >= 0.4
+                                ? " the agent was partially successful with some gaps."
+                                : " the agent had limited success with significant issues."}
+                        </p>
+                      </TooltipContent>
+                    </Tooltip>
+                  </TooltipProvider>
+                </div>
+              )}
+            </CardContent>
+          </Card>
+        )}
+
+        {agentRunOutputs !== null && (
+          <AgentRunOutputView agentRunOutputs={agentRunOutputs} />
+        )}
+
+        {/* Pending Reviews Section */}
+        {runStatus === "review" && (
+          <Card className="agpt-box">
+            <CardHeader>
+              <CardTitle className="font-poppins text-lg">
+                Pending Reviews ({pendingReviews.length})
+              </CardTitle>
+            </CardHeader>
+            <CardContent>
+              {reviewsLoading ? (
+                <LoadingBox spinnerSize={12} className="h-24" />
+              ) : pendingReviews.length > 0 ? (
+                <PendingReviewsList
+                  reviews={pendingReviews}
+                  onReviewComplete={refetchReviews}
+                  emptyMessage="No pending reviews for this execution"
+                />
+              ) : (
+                <div className="py-4 text-neutral-600">
+                  No pending reviews for this execution
+                </div>
+              )}
+            </CardContent>
+          </Card>
+        )}
+
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Input</CardTitle>
+          </CardHeader>
+          <CardContent className="flex flex-col gap-4">
+            {agentRunInputs !== undefined ? (
+              Object.entries(agentRunInputs).map(([key, { title, value }]) => (
+                <div key={key} className="flex flex-col gap-1.5">
+                  <label className="text-sm font-medium">{title || key}</label>
+                  <Input value={value} className="rounded-full" disabled />
+                </div>
+              ))
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      </div>
+
+      {/* Run / Agent Actions */}
+      <aside className="w-48 xl:w-56">
+        <div className="flex flex-col gap-8">
+          <ActionButtonGroup title="Run actions" actions={runActions} />
+
+          <ActionButtonGroup title="Agent actions" actions={agentActions} />
+        </div>
+      </aside>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx

@@ -20,7 +20,7 @@ import {
 import { useBackendAPI } from "@/lib/autogpt-server-api/context";
 
 import { RunAgentInputs } from "@/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs";
-import { ScheduleTaskDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
+import { ScheduleTaskDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
 import ActionButtonGroup from "@/components/__legacy__/action-button-group";
 import type { ButtonAction } from "@/components/__legacy__/types";
 import {
@@ -53,10 +53,7 @@ import { ClockIcon, CopyIcon, InfoIcon } from "@phosphor-icons/react";
 import { CalendarClockIcon, Trash2Icon } from "lucide-react";
 
 import { analytics } from "@/services/analytics";
-import {
-  AgentStatus,
-  AgentStatusChip,
-} from "@/app/(platform)/build/components/legacy-builder/agent-status-chip";
+import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
 
 export function AgentRunDraftView({
   graph,

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-output-view.tsx

@@ -0,0 +1,178 @@
+"use client";
+
+import { Flag, useGetFlag } from "@/services/feature-flags/use-get-flag";
+import React, { useMemo } from "react";
+
+import {
+  Card,
+  CardContent,
+  CardHeader,
+  CardTitle,
+} from "@/components/__legacy__/ui/card";
+
+import LoadingBox from "@/components/__legacy__/ui/loading";
+import type { OutputMetadata } from "../../../../../../../../components/contextual/OutputRenderers";
+import {
+  globalRegistry,
+  OutputActions,
+  OutputItem,
+} from "../../../../../../../../components/contextual/OutputRenderers";
+
+export function AgentRunOutputView({
+  agentRunOutputs,
+}: {
+  agentRunOutputs:
+    | Record<
+        string,
+        {
+          title?: string;
+          /* type: BlockIOSubType; */
+          values: Array<React.ReactNode>;
+        }
+      >
+    | undefined;
+}) {
+  const enableEnhancedOutputHandling = useGetFlag(
+    Flag.ENABLE_ENHANCED_OUTPUT_HANDLING,
+  );
+
+  // Prepare items for the renderer system
+  const outputItems = useMemo(() => {
+    if (!agentRunOutputs) return [];
+
+    const items: Array<{
+      key: string;
+      label: string;
+      value: unknown;
+      metadata?: OutputMetadata;
+      renderer: any;
+    }> = [];
+
+    Object.entries(agentRunOutputs).forEach(([key, { title, values }]) => {
+      values.forEach((value, index) => {
+        // Enhanced metadata extraction
+        const metadata: OutputMetadata = {};
+
+        // Type guard to safely access properties
+        if (
+          typeof value === "object" &&
+          value !== null &&
+          !React.isValidElement(value)
+        ) {
+          const objValue = value as any;
+          if (objValue.type) metadata.type = objValue.type;
+          if (objValue.mimeType) metadata.mimeType = objValue.mimeType;
+          if (objValue.filename) metadata.filename = objValue.filename;
+        }
+
+        const renderer = globalRegistry.getRenderer(value, metadata);
+        if (renderer) {
+          items.push({
+            key: `${key}-${index}`,
+            label: index === 0 ? title || key : "",
+            value,
+            metadata,
+            renderer,
+          });
+        } else {
+          const textRenderer = globalRegistry
+            .getAllRenderers()
+            .find((r) => r.name === "TextRenderer");
+          if (textRenderer) {
+            items.push({
+              key: `${key}-${index}`,
+              label: index === 0 ? title || key : "",
+              value: JSON.stringify(value, null, 2),
+              metadata,
+              renderer: textRenderer,
+            });
+          }
+        }
+      });
+    });
+
+    return items;
+  }, [agentRunOutputs]);
+
+  return (
+    <>
+      {enableEnhancedOutputHandling ? (
+        <Card className="agpt-box" style={{ maxWidth: "950px" }}>
+          <CardHeader>
+            <div className="flex items-center justify-between">
+              <CardTitle className="font-poppins text-lg">Output</CardTitle>
+              {outputItems.length > 0 && (
+                <OutputActions
+                  items={outputItems.map((item) => ({
+                    value: item.value,
+                    metadata: item.metadata,
+                    renderer: item.renderer,
+                  }))}
+                />
+              )}
+            </div>
+          </CardHeader>
+
+          <CardContent
+            className="flex flex-col gap-4"
+            style={{ maxWidth: "660px" }}
+          >
+            {agentRunOutputs !== undefined ? (
+              outputItems.length > 0 ? (
+                outputItems.map((item) => (
+                  <OutputItem
+                    key={item.key}
+                    value={item.value}
+                    metadata={item.metadata}
+                    renderer={item.renderer}
+                    label={item.label}
+                  />
+                ))
+              ) : (
+                <p className="text-sm text-muted-foreground">
+                  No outputs to display
+                </p>
+              )
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      ) : (
+        <Card className="agpt-box" style={{ maxWidth: "950px" }}>
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Output</CardTitle>
+          </CardHeader>
+
+          <CardContent
+            className="flex flex-col gap-4"
+            style={{ maxWidth: "660px" }}
+          >
+            {agentRunOutputs !== undefined ? (
+              Object.entries(agentRunOutputs).map(
+                ([key, { title, values }]) => (
+                  <div key={key} className="flex flex-col gap-1.5">
+                    <label className="text-sm font-medium">
+                      {title || key}
+                    </label>
+                    {values.map((value, i) => (
+                      <p
+                        className="resize-none overflow-x-auto whitespace-pre-wrap break-words border-none text-sm text-neutral-700 disabled:cursor-not-allowed"
+                        key={i}
+                      >
+                        {value}
+                      </p>
+                    ))}
+                    {/* TODO: pretty type-dependent rendering */}
+                  </div>
+                ),
+              )
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      )}
+    </>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-status-chip.tsx

@@ -0,0 +1,68 @@
+import React from "react";
+
+import { Badge } from "@/components/__legacy__/ui/badge";
+
+import { GraphExecutionMeta } from "@/lib/autogpt-server-api/types";
+
+export type AgentRunStatus =
+  | "success"
+  | "failed"
+  | "queued"
+  | "running"
+  | "stopped"
+  | "scheduled"
+  | "draft"
+  | "review";
+
+export const agentRunStatusMap: Record<
+  GraphExecutionMeta["status"],
+  AgentRunStatus
+> = {
+  INCOMPLETE: "draft",
+  COMPLETED: "success",
+  FAILED: "failed",
+  QUEUED: "queued",
+  RUNNING: "running",
+  TERMINATED: "stopped",
+  REVIEW: "review",
+};
+
+const statusData: Record<
+  AgentRunStatus,
+  { label: string; variant: keyof typeof statusStyles }
+> = {
+  success: { label: "Success", variant: "success" },
+  running: { label: "Running", variant: "info" },
+  failed: { label: "Failed", variant: "destructive" },
+  queued: { label: "Queued", variant: "warning" },
+  draft: { label: "Draft", variant: "secondary" },
+  stopped: { label: "Stopped", variant: "secondary" },
+  scheduled: { label: "Scheduled", variant: "secondary" },
+  review: { label: "In Review", variant: "warning" },
+};
+
+const statusStyles = {
+  success:
+    "bg-green-100 text-green-800 hover:bg-green-100 hover:text-green-800",
+  destructive: "bg-red-100 text-red-800 hover:bg-red-100 hover:text-red-800",
+  warning:
+    "bg-yellow-100 text-yellow-800 hover:bg-yellow-100 hover:text-yellow-800",
+  info: "bg-blue-100 text-blue-800 hover:bg-blue-100 hover:text-blue-800",
+  secondary:
+    "bg-slate-100 text-slate-800 hover:bg-slate-100 hover:text-slate-800",
+};
+
+export function AgentRunStatusChip({
+  status,
+}: {
+  status: AgentRunStatus;
+}): React.ReactElement {
+  return (
+    <Badge
+      variant="secondary"
+      className={`text-xs font-medium ${statusStyles[statusData[status]?.variant]} rounded-[45px] px-[9px] py-[3px]`}
+    >
+      {statusData[status]?.label}
+    </Badge>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-summary-card.tsx

@@ -0,0 +1,130 @@
+import React from "react";
+import { formatDistanceToNow, isPast } from "date-fns";
+
+import { cn } from "@/lib/utils";
+
+import { Link2Icon, Link2OffIcon, MoreVertical } from "lucide-react";
+import { Card, CardContent } from "@/components/__legacy__/ui/card";
+import { Button } from "@/components/__legacy__/ui/button";
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuTrigger,
+} from "@/components/__legacy__/ui/dropdown-menu";
+
+import { AgentStatus, AgentStatusChip } from "./agent-status-chip";
+import { AgentRunStatus, AgentRunStatusChip } from "./agent-run-status-chip";
+import { PushPinSimpleIcon } from "@phosphor-icons/react";
+
+export type AgentRunSummaryProps = (
+  | {
+      type: "run";
+      status: AgentRunStatus;
+    }
+  | {
+      type: "preset";
+      status?: undefined;
+    }
+  | {
+      type: "preset.triggered";
+      status: AgentStatus;
+    }
+  | {
+      type: "schedule";
+      status: "scheduled";
+    }
+) & {
+  title: string;
+  timestamp?: number | Date;
+  selected?: boolean;
+  onClick?: () => void;
+  // onRename: () => void;
+  onDelete: () => void;
+  onPinAsPreset?: () => void;
+  className?: string;
+};
+
+export function AgentRunSummaryCard({
+  type,
+  status,
+  title,
+  timestamp,
+  selected = false,
+  onClick,
+  // onRename,
+  onDelete,
+  onPinAsPreset,
+  className,
+}: AgentRunSummaryProps): React.ReactElement {
+  return (
+    <Card
+      className={cn(
+        "agpt-rounded-card cursor-pointer border-zinc-300",
+        selected ? "agpt-card-selected" : "",
+        className,
+      )}
+      onClick={onClick}
+    >
+      <CardContent className="relative p-2.5 lg:p-4">
+        {(type == "run" || type == "schedule") && (
+          <AgentRunStatusChip status={status} />
+        )}
+        {type == "preset" && (
+          <div className="flex items-center text-sm font-medium text-neutral-700">
+            <PushPinSimpleIcon className="mr-1 size-4 text-foreground" /> Preset
+          </div>
+        )}
+        {type == "preset.triggered" && (
+          <div className="flex items-center justify-between">
+            <AgentStatusChip status={status} />
+
+            <div className="flex items-center text-sm font-medium text-neutral-700">
+              {status == "inactive" ? (
+                <Link2OffIcon className="mr-1 size-4 text-foreground" />
+              ) : (
+                <Link2Icon className="mr-1 size-4 text-foreground" />
+              )}{" "}
+              Trigger
+            </div>
+          </div>
+        )}
+
+        <div className="mt-5 flex items-center justify-between">
+          <h3 className="truncate pr-2 text-base font-medium text-neutral-900">
+            {title}
+          </h3>
+
+          <DropdownMenu>
+            <DropdownMenuTrigger asChild>
+              <Button variant="ghost" className="h-5 w-5 p-0">
+                <MoreVertical className="h-5 w-5" />
+              </Button>
+            </DropdownMenuTrigger>
+            <DropdownMenuContent>
+              {onPinAsPreset && (
+                <DropdownMenuItem onClick={onPinAsPreset}>
+                  Pin as a preset
+                </DropdownMenuItem>
+              )}
+
+              {/* <DropdownMenuItem onClick={onRename}>Rename</DropdownMenuItem> */}
+
+              <DropdownMenuItem onClick={onDelete}>Delete</DropdownMenuItem>
+            </DropdownMenuContent>
+          </DropdownMenu>
+        </div>
+
+        {timestamp && (
+          <p
+            className="mt-1 text-sm font-normal text-neutral-500"
+            title={new Date(timestamp).toString()}
+          >
+            {isPast(timestamp) ? "Ran" : "Runs in"}{" "}
+            {formatDistanceToNow(timestamp, { addSuffix: true })}
+          </p>
+        )}
+      </CardContent>
+    </Card>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-runs-selector-list.tsx

@@ -0,0 +1,237 @@
+"use client";
+import { Plus } from "lucide-react";
+import React, { useEffect, useState } from "react";
+
+import {
+  GraphExecutionID,
+  GraphExecutionMeta,
+  LibraryAgent,
+  LibraryAgentPreset,
+  LibraryAgentPresetID,
+  Schedule,
+  ScheduleID,
+} from "@/lib/autogpt-server-api";
+import { cn } from "@/lib/utils";
+
+import { Badge } from "@/components/__legacy__/ui/badge";
+import { Button } from "@/components/atoms/Button/Button";
+import LoadingBox, { LoadingSpinner } from "@/components/__legacy__/ui/loading";
+import { Separator } from "@/components/__legacy__/ui/separator";
+import { ScrollArea } from "@/components/__legacy__/ui/scroll-area";
+import { InfiniteScroll } from "@/components/contextual/InfiniteScroll/InfiniteScroll";
+import { AgentRunsQuery } from "../use-agent-runs";
+import { agentRunStatusMap } from "./agent-run-status-chip";
+import { AgentRunSummaryCard } from "./agent-run-summary-card";
+
+interface AgentRunsSelectorListProps {
+  agent: LibraryAgent;
+  agentRunsQuery: AgentRunsQuery;
+  agentPresets: LibraryAgentPreset[];
+  schedules: Schedule[];
+  selectedView: { type: "run" | "preset" | "schedule"; id?: string };
+  allowDraftNewRun?: boolean;
+  onSelectRun: (id: GraphExecutionID) => void;
+  onSelectPreset: (preset: LibraryAgentPresetID) => void;
+  onSelectSchedule: (id: ScheduleID) => void;
+  onSelectDraftNewRun: () => void;
+  doDeleteRun: (id: GraphExecutionMeta) => void;
+  doDeletePreset: (id: LibraryAgentPresetID) => void;
+  doDeleteSchedule: (id: ScheduleID) => void;
+  doCreatePresetFromRun?: (id: GraphExecutionID) => void;
+  className?: string;
+}
+
+export function AgentRunsSelectorList({
+  agent,
+  agentRunsQuery: {
+    agentRuns,
+    agentRunCount,
+    agentRunsLoading,
+    hasMoreRuns,
+    fetchMoreRuns,
+    isFetchingMoreRuns,
+  },
+  agentPresets,
+  schedules,
+  selectedView,
+  allowDraftNewRun = true,
+  onSelectRun,
+  onSelectPreset,
+  onSelectSchedule,
+  onSelectDraftNewRun,
+  doDeleteRun,
+  doDeletePreset,
+  doDeleteSchedule,
+  doCreatePresetFromRun,
+  className,
+}: AgentRunsSelectorListProps): React.ReactElement {
+  const [activeListTab, setActiveListTab] = useState<"runs" | "scheduled">(
+    "runs",
+  );
+
+  useEffect(() => {
+    if (selectedView.type === "schedule") {
+      setActiveListTab("scheduled");
+    } else {
+      setActiveListTab("runs");
+    }
+  }, [selectedView]);
+
+  const listItemClasses = "h-28 w-72 lg:w-full lg:h-32";
+
+  return (
+    <aside className={cn("flex flex-col gap-4", className)}>
+      {allowDraftNewRun ? (
+        <Button
+          className={"mb-4 hidden lg:flex"}
+          onClick={onSelectDraftNewRun}
+          leftIcon={<Plus className="h-6 w-6" />}
+        >
+          New {agent.has_external_trigger ? "trigger" : "run"}
+        </Button>
+      ) : null}
+
+      <div className="flex gap-2">
+        <Badge
+          variant={activeListTab === "runs" ? "secondary" : "outline"}
+          className="cursor-pointer gap-2 rounded-full text-base"
+          onClick={() => setActiveListTab("runs")}
+        >
+          <span>Runs</span>
+          <span className="text-neutral-600">
+            {agentRunCount ?? <LoadingSpinner className="size-4" />}
+          </span>
+        </Badge>
+
+        <Badge
+          variant={activeListTab === "scheduled" ? "secondary" : "outline"}
+          className="cursor-pointer gap-2 rounded-full text-base"
+          onClick={() => setActiveListTab("scheduled")}
+        >
+          <span>Scheduled</span>
+          <span className="text-neutral-600">{schedules.length}</span>
+        </Badge>
+      </div>
+
+      {/* Runs / Schedules list */}
+      {agentRunsLoading && activeListTab === "runs" ? (
+        <LoadingBox className="h-28 w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80" />
+      ) : (
+        <ScrollArea
+          className="w-full lg:h-[calc(100vh-300px)] lg:w-72 xl:w-80"
+          orientation={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
+        >
+          <InfiniteScroll
+            direction={window.innerWidth >= 1024 ? "vertical" : "horizontal"}
+            hasNextPage={hasMoreRuns}
+            fetchNextPage={fetchMoreRuns}
+            isFetchingNextPage={isFetchingMoreRuns}
+          >
+            <div className="flex items-center gap-2 lg:flex-col">
+              {/* New Run button - only in small layouts */}
+              {allowDraftNewRun && (
+                <Button
+                  size="large"
+                  className={
+                    "flex h-12 w-40 items-center gap-2 py-6 lg:hidden " +
+                    (selectedView.type == "run" && !selectedView.id
+                      ? "agpt-card-selected text-accent"
+                      : "")
+                  }
+                  onClick={onSelectDraftNewRun}
+                  leftIcon={<Plus className="h-6 w-6" />}
+                >
+                  New {agent.has_external_trigger ? "trigger" : "run"}
+                </Button>
+              )}
+
+              {activeListTab === "runs" ? (
+                <>
+                  {agentPresets
+                    .filter((preset) => preset.webhook) // Triggers
+                    .toSorted(
+                      (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
+                    )
+                    .map((preset) => (
+                      <AgentRunSummaryCard
+                        className={cn(listItemClasses, "lg:h-auto")}
+                        key={preset.id}
+                        type="preset.triggered"
+                        status={preset.is_active ? "active" : "inactive"}
+                        title={preset.name}
+                        // timestamp={preset.last_run_time} // TODO: implement this
+                        selected={selectedView.id === preset.id}
+                        onClick={() => onSelectPreset(preset.id)}
+                        onDelete={() => doDeletePreset(preset.id)}
+                      />
+                    ))}
+                  {agentPresets
+                    .filter((preset) => !preset.webhook) // Presets
+                    .toSorted(
+                      (a, b) => b.updated_at.getTime() - a.updated_at.getTime(),
+                    )
+                    .map((preset) => (
+                      <AgentRunSummaryCard
+                        className={cn(listItemClasses, "lg:h-auto")}
+                        key={preset.id}
+                        type="preset"
+                        title={preset.name}
+                        // timestamp={preset.last_run_time} // TODO: implement this
+                        selected={selectedView.id === preset.id}
+                        onClick={() => onSelectPreset(preset.id)}
+                        onDelete={() => doDeletePreset(preset.id)}
+                      />
+                    ))}
+                  {agentPresets.length > 0 && <Separator className="my-1" />}
+                  {agentRuns
+                    .toSorted((a, b) => {
+                      const aTime = a.started_at?.getTime() ?? 0;
+                      const bTime = b.started_at?.getTime() ?? 0;
+                      return bTime - aTime;
+                    })
+                    .map((run) => (
+                      <AgentRunSummaryCard
+                        className={listItemClasses}
+                        key={run.id}
+                        type="run"
+                        status={agentRunStatusMap[run.status]}
+                        title={
+                          (run.preset_id
+                            ? agentPresets.find((p) => p.id == run.preset_id)
+                                ?.name
+                            : null) ?? agent.name
+                        }
+                        timestamp={run.started_at ?? undefined}
+                        selected={selectedView.id === run.id}
+                        onClick={() => onSelectRun(run.id)}
+                        onDelete={() => doDeleteRun(run as GraphExecutionMeta)}
+                        onPinAsPreset={
+                          doCreatePresetFromRun
+                            ? () => doCreatePresetFromRun(run.id)
+                            : undefined
+                        }
+                      />
+                    ))}
+                </>
+              ) : (
+                schedules.map((schedule) => (
+                  <AgentRunSummaryCard
+                    className={listItemClasses}
+                    key={schedule.id}
+                    type="schedule"
+                    status="scheduled" // TODO: implement active/inactive status for schedules
+                    title={schedule.name}
+                    timestamp={schedule.next_run_time}
+                    selected={selectedView.id === schedule.id}
+                    onClick={() => onSelectSchedule(schedule.id)}
+                    onDelete={() => doDeleteSchedule(schedule.id)}
+                  />
+                ))
+              )}
+            </div>
+          </InfiniteScroll>
+        </ScrollArea>
+      )}
+    </aside>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-schedule-details-view.tsx

@@ -0,0 +1,180 @@
+"use client";
+import React, { useCallback, useMemo } from "react";
+
+import {
+  Graph,
+  GraphExecutionID,
+  Schedule,
+  ScheduleID,
+} from "@/lib/autogpt-server-api";
+import { useBackendAPI } from "@/lib/autogpt-server-api/context";
+
+import ActionButtonGroup from "@/components/__legacy__/action-button-group";
+import type { ButtonAction } from "@/components/__legacy__/types";
+import {
+  Card,
+  CardContent,
+  CardHeader,
+  CardTitle,
+} from "@/components/__legacy__/ui/card";
+import { IconCross } from "@/components/__legacy__/ui/icons";
+import { Input } from "@/components/__legacy__/ui/input";
+import LoadingBox from "@/components/__legacy__/ui/loading";
+import { useToastOnFail } from "@/components/molecules/Toast/use-toast";
+import { humanizeCronExpression } from "@/lib/cron-expression-utils";
+import { formatScheduleTime } from "@/lib/timezone-utils";
+import { useUserTimezone } from "@/lib/hooks/useUserTimezone";
+import { PlayIcon } from "lucide-react";
+
+import { AgentRunStatus } from "./agent-run-status-chip";
+
+export function AgentScheduleDetailsView({
+  graph,
+  schedule,
+  agentActions,
+  onForcedRun,
+  doDeleteSchedule,
+}: {
+  graph: Graph;
+  schedule: Schedule;
+  agentActions: ButtonAction[];
+  onForcedRun: (runID: GraphExecutionID) => void;
+  doDeleteSchedule: (scheduleID: ScheduleID) => void;
+}): React.ReactNode {
+  const api = useBackendAPI();
+
+  const selectedRunStatus: AgentRunStatus = "scheduled";
+
+  const toastOnFail = useToastOnFail();
+
+  // Get user's timezone for displaying schedule times
+  const userTimezone = useUserTimezone();
+
+  const infoStats: { label: string; value: React.ReactNode }[] = useMemo(() => {
+    return [
+      {
+        label: "Status",
+        value:
+          selectedRunStatus.charAt(0).toUpperCase() +
+          selectedRunStatus.slice(1),
+      },
+      {
+        label: "Schedule",
+        value: humanizeCronExpression(schedule.cron),
+      },
+      {
+        label: "Next run",
+        value: formatScheduleTime(schedule.next_run_time, userTimezone),
+      },
+    ];
+  }, [schedule, selectedRunStatus, userTimezone]);
+
+  const agentRunInputs: Record<
+    string,
+    { title?: string; /* type: BlockIOSubType; */ value: any }
+  > = useMemo(() => {
+    // TODO: show (link to) preset - https://github.com/Significant-Gravitas/AutoGPT/issues/9168
+
+    // Add type info from agent input schema
+    return Object.fromEntries(
+      Object.entries(schedule.input_data).map(([k, v]) => [
+        k,
+        {
+          title: graph.input_schema.properties[k].title,
+          /* TODO: type: agent.input_schema.properties[k].type */
+          value: v,
+        },
+      ]),
+    );
+  }, [graph, schedule]);
+
+  const runNow = useCallback(
+    () =>
+      api
+        .executeGraph(
+          graph.id,
+          graph.version,
+          schedule.input_data,
+          schedule.input_credentials,
+          "library",
+        )
+        .then((run) => onForcedRun(run.id))
+        .catch(toastOnFail("execute agent")),
+    [api, graph, schedule, onForcedRun, toastOnFail],
+  );
+
+  const runActions: ButtonAction[] = useMemo(
+    () => [
+      {
+        label: (
+          <>
+            <PlayIcon className="mr-2 size-4" />
+            Run now
+          </>
+        ),
+        callback: runNow,
+      },
+      {
+        label: (
+          <>
+            <IconCross className="mr-2 size-4 px-0.5" />
+            Delete schedule
+          </>
+        ),
+        callback: () => doDeleteSchedule(schedule.id),
+        variant: "destructive",
+      },
+    ],
+    [runNow],
+  );
+
+  return (
+    <div className="agpt-div flex gap-6">
+      <div className="flex flex-1 flex-col gap-4">
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Info</CardTitle>
+          </CardHeader>
+
+          <CardContent>
+            <div className="flex justify-stretch gap-4">
+              {infoStats.map(({ label, value }) => (
+                <div key={label} className="flex-1">
+                  <p className="text-sm font-medium text-black">{label}</p>
+                  <p className="text-sm text-neutral-600">{value}</p>
+                </div>
+              ))}
+            </div>
+          </CardContent>
+        </Card>
+
+        <Card className="agpt-box">
+          <CardHeader>
+            <CardTitle className="font-poppins text-lg">Input</CardTitle>
+          </CardHeader>
+          <CardContent className="flex flex-col gap-4">
+            {agentRunInputs !== undefined ? (
+              Object.entries(agentRunInputs).map(([key, { title, value }]) => (
+                <div key={key} className="flex flex-col gap-1.5">
+                  <label className="text-sm font-medium">{title || key}</label>
+                  <Input value={value} className="rounded-full" disabled />
+                </div>
+              ))
+            ) : (
+              <LoadingBox spinnerSize={12} className="h-24" />
+            )}
+          </CardContent>
+        </Card>
+      </div>
+
+      {/* Run / Agent Actions */}
+      <aside className="w-48 xl:w-56">
+        <div className="flex flex-col gap-8">
+          <ActionButtonGroup title="Run actions" actions={runActions} />
+
+          <ActionButtonGroup title="Agent actions" actions={agentActions} />
+        </div>
+      </aside>
+    </div>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/create-preset-dialog.tsx

@@ -0,0 +1,100 @@
+"use client";
+
+import React, { useState } from "react";
+import { Button } from "@/components/__legacy__/ui/button";
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from "@/components/__legacy__/ui/dialog";
+import { Input } from "@/components/__legacy__/ui/input";
+import { Textarea } from "@/components/__legacy__/ui/textarea";
+
+interface CreatePresetDialogProps {
+  open: boolean;
+  onOpenChange: (open: boolean) => void;
+  onConfirm: (name: string, description: string) => Promise<void> | void;
+}
+
+export function CreatePresetDialog({
+  open,
+  onOpenChange,
+  onConfirm,
+}: CreatePresetDialogProps) {
+  const [name, setName] = useState("");
+  const [description, setDescription] = useState("");
+
+  const handleSubmit = async () => {
+    if (name.trim()) {
+      await onConfirm(name.trim(), description.trim());
+      setName("");
+      setDescription("");
+      onOpenChange(false);
+    }
+  };
+
+  const handleCancel = () => {
+    setName("");
+    setDescription("");
+    onOpenChange(false);
+  };
+
+  const handleKeyDown = (e: React.KeyboardEvent) => {
+    if (e.key === "Enter" && (e.metaKey || e.ctrlKey)) {
+      e.preventDefault();
+      handleSubmit();
+    }
+  };
+
+  return (
+    <Dialog open={open} onOpenChange={onOpenChange}>
+      <DialogContent className="sm:max-w-[425px]">
+        <DialogHeader>
+          <DialogTitle>Create Preset</DialogTitle>
+          <DialogDescription>
+            Give your preset a name and description to help identify it later.
+          </DialogDescription>
+        </DialogHeader>
+        <div className="grid gap-4 py-4">
+          <div className="grid gap-2">
+            <label htmlFor="preset-name" className="text-sm font-medium">
+              Name *
+            </label>
+            <Input
+              id="preset-name"
+              placeholder="Enter preset name"
+              value={name}
+              onChange={(e) => setName(e.target.value)}
+              onKeyDown={handleKeyDown}
+              autoFocus
+            />
+          </div>
+          <div className="grid gap-2">
+            <label htmlFor="preset-description" className="text-sm font-medium">
+              Description
+            </label>
+            <Textarea
+              id="preset-description"
+              placeholder="Optional description"
+              value={description}
+              onChange={(e) => setDescription(e.target.value)}
+              onKeyDown={handleKeyDown}
+              rows={3}
+            />
+          </div>
+        </div>
+        <DialogFooter>
+          <Button variant="outline" onClick={handleCancel}>
+            Cancel
+          </Button>
+          <Button onClick={handleSubmit} disabled={!name.trim()}>
+            Create Preset
+          </Button>
+        </DialogFooter>
+      </DialogContent>
+    </Dialog>
+  );
+}

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog.tsx

@@ -2,7 +2,7 @@ import { useEffect, useState } from "react";
 import { Input } from "@/components/__legacy__/ui/input";
 import { Button } from "@/components/__legacy__/ui/button";
 import { useToast } from "@/components/molecules/Toast/use-toast";
-import { CronScheduler } from "@/components/contextual/CronScheduler/cron-scheduler";
+import { CronScheduler } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
 import { getTimezoneDisplayName } from "@/lib/timezone-utils";
 import { useUserTimezone } from "@/lib/hooks/useUserTimezone";

autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/use-agent-runs.ts

@@ -0,0 +1,210 @@
+import {
+  GraphExecutionMeta as LegacyGraphExecutionMeta,
+  GraphID,
+  GraphExecutionID,
+} from "@/lib/autogpt-server-api";
+import { getQueryClient } from "@/lib/react-query/queryClient";
+import {
+  getPaginatedTotalCount,
+  getPaginationNextPageNumber,
+  unpaginate,
+} from "@/app/api/helpers";
+import {
+  getV1ListGraphExecutionsResponse,
+  getV1ListGraphExecutionsResponse200,
+  useGetV1ListGraphExecutionsInfinite,
+} from "@/app/api/__generated__/endpoints/graphs/graphs";
+import { GraphExecutionsPaginated } from "@/app/api/__generated__/models/graphExecutionsPaginated";
+import { GraphExecutionMeta as RawGraphExecutionMeta } from "@/app/api/__generated__/models/graphExecutionMeta";
+
+export type GraphExecutionMeta = Omit<
+  RawGraphExecutionMeta,
+  "id" | "user_id" | "graph_id" | "preset_id" | "stats"
+> &
+  Pick<
+    LegacyGraphExecutionMeta,
+    "id" | "user_id" | "graph_id" | "preset_id" | "stats"
+  >;
+
+/** Hook to fetch runs for a specific graph, with support for infinite scroll.
+ *
+ * @param graphID - The ID of the graph to fetch agent runs for. This parameter is
+ *                  optional in the sense that the hook doesn't run unless it is passed.
+ *                  This way, it can be used in components where the graph ID is not
+ *                  immediately available.
+ */
+export const useAgentRunsInfinite = (graphID?: GraphID) => {
+  const queryClient = getQueryClient();
+  const {
+    data: queryResults,
+    refetch: refetchRuns,
+    isPending: agentRunsLoading,
+    isRefetching: agentRunsReloading,
+    hasNextPage: hasMoreRuns,
+    fetchNextPage: fetchMoreRuns,
+    isFetchingNextPage: isFetchingMoreRuns,
+    queryKey,
+  } = useGetV1ListGraphExecutionsInfinite(
+    graphID!,
+    { page: 1, page_size: 20 },
+    {
+      query: {
+        getNextPageParam: getPaginationNextPageNumber,
+
+        // Prevent query from running if graphID is not available (yet)
+        ...(!graphID
+          ? {
+              enabled: false,
+              queryFn: () =>
+                // Fake empty response if graphID is not available (yet)
+                Promise.resolve({
+                  status: 200,
+                  data: {
+                    executions: [],
+                    pagination: {
+                      current_page: 1,
+                      page_size: 20,
+                      total_items: 0,
+                      total_pages: 0,
+                    },
+                  },
+                  headers: new Headers(),
+                } satisfies getV1ListGraphExecutionsResponse),
+            }
+          : {}),
+      },
+    },
+    queryClient,
+  );
+
+  const agentRuns = queryResults ? unpaginate(queryResults, "executions") : [];
+  const agentRunCount = getPaginatedTotalCount(queryResults);
+
+  const upsertAgentRun = (newAgentRun: GraphExecutionMeta) => {
+    queryClient.setQueryData(
+      queryKey,
+      (currentQueryData: typeof queryResults) => {
+        if (!currentQueryData?.pages || agentRunCount === undefined)
+          return currentQueryData;
+
+        const exists = currentQueryData.pages.some((page) => {
+          if (page.status !== 200) return false;
+
+          const response = page.data;
+          return response.executions.some((run) => run.id === newAgentRun.id);
+        });
+        if (exists) {
+          // If the run already exists, we update it
+          return {
+            ...currentQueryData,
+            pages: currentQueryData.pages.map((page) => {
+              if (page.status !== 200) return page;
+              const response = page.data;
+              const executions = response.executions;
+
+              const index = executions.findIndex(
+                (run) => run.id === newAgentRun.id,
+              );
+              if (index === -1) return page;
+
+              const newExecutions = [...executions];
+              newExecutions[index] = newAgentRun;
+
+              return {
+                ...page,
+                data: {
+                  ...response,
+                  executions: newExecutions,
+                },
+              } satisfies getV1ListGraphExecutionsResponse;
+            }),
+          };
+        }
+
+        // If the run does not exist, we add it to the first page
+        const page = currentQueryData
+          .pages[0] as getV1ListGraphExecutionsResponse200 & {
+          headers: Headers;
+        };
+        const updatedExecutions = [newAgentRun, ...page.data.executions];
+        const updatedPage = {
+          ...page,
+          data: {
+            ...page.data,
+            executions: updatedExecutions,
+          },
+        } satisfies getV1ListGraphExecutionsResponse;
+        const updatedPages = [updatedPage, ...currentQueryData.pages.slice(1)];
+        return {
+          ...currentQueryData,
+          pages: updatedPages.map(
+            // Increment the total runs count in the pagination info of all pages
+            (page) =>
+              page.status === 200
+                ? {
+                    ...page,
+                    data: {
+                      ...page.data,
+                      pagination: {
+                        ...page.data.pagination,
+                        total_items: agentRunCount + 1,
+                      },
+                    },
+                  }
+                : page,
+          ),
+        };
+      },
+    );
+  };
+
+  const removeAgentRun = (runID: GraphExecutionID) => {
+    queryClient.setQueryData(
+      [queryKey, { page: 1, page_size: 20 }],
+      (currentQueryData: typeof queryResults) => {
+        if (!currentQueryData?.pages) return currentQueryData;
+
+        let found = false;
+        return {
+          ...currentQueryData,
+          pages: currentQueryData.pages.map((page) => {
+            const response = page.data as GraphExecutionsPaginated;
+            const filteredExecutions = response.executions.filter(
+              (run) => run.id !== runID,
+            );
+            if (filteredExecutions.length < response.executions.length) {
+              found = true;
+            }
+
+            return {
+              ...page,
+              data: {
+                ...response,
+                executions: filteredExecutions,
+                pagination: {
+                  ...response.pagination,
+                  total_items:
+                    response.pagination.total_items - (found ? 1 : 0),
+                },
+              },
+            };
+          }),
+        };
+      },
+    );
+  };
+
+  return {
+    agentRuns: agentRuns as GraphExecutionMeta[],
+    refetchRuns,
+    agentRunCount,
+    agentRunsLoading: agentRunsLoading || agentRunsReloading,
+    hasMoreRuns,
+    fetchMoreRuns,
+    isFetchingMoreRuns,
+    upsertAgentRun,
+    removeAgentRun,
+  };
+};
+
+export type AgentRunsQuery = ReturnType<typeof useAgentRunsInfinite>;

autogpt_platform/frontend/src/app/(platform)/library/legacy/[id]/page.tsx

@@ -0,0 +1,7 @@
+"use client";
+
+import { OldAgentLibraryView } from "../../agents/[id]/components/OldAgentLibraryView/OldAgentLibraryView";
+
+export default function OldAgentLibraryPage() {
+  return <OldAgentLibraryView />;
+}

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

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

autogpt_platform/frontend/src/app/globals.css

@@ -180,14 +180,3 @@ body[data-google-picker-open="true"] [data-dialog-content] {
   z-index: 1 !important;
   pointer-events: none !important;
 }
-
-/* CoPilot chat table styling — remove left/right borders, increase padding */
-[data-streamdown="table-wrapper"] table {
-  border-left: none;
-  border-right: none;
-}
-
-[data-streamdown="table-wrapper"] th,
-[data-streamdown="table-wrapper"] td {
-  padding: 0.875rem 1rem; /* py-3.5 px-4 */
-}

autogpt_platform/frontend/src/components/contextual/OutputRenderers/renderers/MarkdownRenderer.tsx

@@ -226,7 +226,7 @@ function renderMarkdown(
           table: ({ children, ...props }) => (
             <div className="my-4 overflow-x-auto">
               <table
-                className="min-w-full divide-y divide-gray-200 border-y border-gray-200 dark:divide-gray-700 dark:border-gray-700"
+                className="min-w-full divide-y divide-gray-200 rounded-lg border border-gray-200 dark:divide-gray-700 dark:border-gray-700"
                 {...props}
               >
                 {children}
@@ -235,7 +235,7 @@ function renderMarkdown(
           ),
           th: ({ children, ...props }) => (
             <th
-              className="bg-gray-50 px-4 py-3.5 text-left text-xs font-semibold uppercase tracking-wider text-gray-700 dark:bg-gray-800 dark:text-gray-300"
+              className="bg-gray-50 px-4 py-3 text-left text-xs font-semibold uppercase tracking-wider text-gray-700 dark:bg-gray-800 dark:text-gray-300"
               {...props}
             >
               {children}
@@ -243,7 +243,7 @@ function renderMarkdown(
           ),
           td: ({ children, ...props }) => (
             <td
-              className="border-t border-gray-200 px-4 py-3.5 text-sm text-gray-600 dark:border-gray-700 dark:text-gray-400"
+              className="border-t border-gray-200 px-4 py-3 text-sm text-gray-600 dark:border-gray-700 dark:text-gray-400"
               {...props}
             >
               {children}

autogpt_platform/frontend/src/components/contextual/PublishAgentModal/components/AgentInfoStep/AgentInfoStep.tsx

@@ -1,6 +1,6 @@
 "use client";
 
-import { CronExpressionDialog } from "@/components/contextual/CronScheduler/cron-scheduler-dialog";
+import { CronExpressionDialog } from "@/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/cron-scheduler-dialog";
 import { Form, FormField } from "@/components/__legacy__/ui/form";
 import { Button } from "@/components/atoms/Button/Button";
 import { Input } from "@/components/atoms/Input/Input";

autogpt_platform/frontend/src/services/feature-flags/use-get-flag.ts

@@ -7,6 +7,7 @@ import { useFlags } from "launchdarkly-react-client-sdk";
 export enum Flag {
   BETA_BLOCKS = "beta-blocks",
   NEW_BLOCK_MENU = "new-block-menu",
+  NEW_AGENT_RUNS = "new-agent-runs",
   GRAPH_SEARCH = "graph-search",
   ENABLE_ENHANCED_OUTPUT_HANDLING = "enable-enhanced-output-handling",
   SHARE_EXECUTION_RESULTS = "share-execution-results",
@@ -21,6 +22,7 @@ const isPwMockEnabled = process.env.NEXT_PUBLIC_PW_TEST === "true";
 const defaultFlags = {
   [Flag.BETA_BLOCKS]: [],
   [Flag.NEW_BLOCK_MENU]: false,
+  [Flag.NEW_AGENT_RUNS]: false,
   [Flag.GRAPH_SEARCH]: false,
   [Flag.ENABLE_ENHANCED_OUTPUT_HANDLING]: false,
   [Flag.SHARE_EXECUTION_RESULTS]: false,

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', 'content', and 'workspace_ref' fields. workspace_ref contains a workspace:// URI if the file was stored to workspace. | List[SandboxFileOutput] |
+| 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] |
 | 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

@@ -215,7 +215,6 @@ 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 -->