fix: address review feedback

- Close Redis event bus connection in finally block (fixes connection leak)
- Handle race condition: re-check DB after subscribing to pubsub
- Handle REVIEW status (human-in-the-loop) as a stop-waiting state
- Handle TERMINATED explicitly in run_agent instead of falling into else-branch
- Include REVIEW in queryable statuses when waiting

autogpt_platform/backend/backend/copilot/executor/manager.py

@@ -4,6 +4,7 @@ This module contains the CoPilotExecutor class that consumes chat tasks from
 RabbitMQ and processes them using a thread pool, following the graph executor pattern.
 """
 
+import asyncio
 import logging
 import os
 import threading
@@ -163,23 +164,21 @@ class CoPilotExecutor(AppProcess):
                 self._cancel_thread, self.cancel_client, "[cleanup][cancel]"
             )
 
-        # Clean up worker threads (closes per-loop workspace storage sessions)
+        # Shutdown executor
         if self._executor:
-            from .processor import cleanup_worker
-
-            logger.info(f"[cleanup {pid}] Cleaning up workers...")
-            futures = []
-            for _ in range(self._executor._max_workers):
-                futures.append(self._executor.submit(cleanup_worker))
-            for f in futures:
-                try:
-                    f.result(timeout=10)
-                except Exception as e:
-                    logger.warning(f"[cleanup {pid}] Worker cleanup error: {e}")
-
             logger.info(f"[cleanup {pid}] Shutting down executor...")
             self._executor.shutdown(wait=False)
 
+        # Close async resources (workspace storage aiohttp session, etc.)
+        try:
+            from backend.util.workspace_storage import shutdown_workspace_storage
+
+            loop = asyncio.new_event_loop()
+            loop.run_until_complete(shutdown_workspace_storage())
+            loop.close()
+        except Exception as e:
+            logger.warning(f"[cleanup {pid}] Error closing workspace storage: {e}")
+
         # Release any remaining locks
         for task_id, lock in list(self._task_locks.items()):
             try:

autogpt_platform/backend/backend/copilot/executor/processor.py

@@ -60,18 +60,6 @@ def init_worker():
     _tls.processor.on_executor_start()
 
 
-def cleanup_worker():
-    """Clean up the processor for the current worker thread.
-
-    Should be called before the worker thread's event loop is destroyed so
-    that event-loop-bound resources (e.g. ``aiohttp.ClientSession``) are
-    closed on the correct loop.
-    """
-    processor: CoPilotProcessor | None = getattr(_tls, "processor", None)
-    if processor is not None:
-        processor.cleanup()
-
-
 # ============ Processor Class ============ #
 
 
@@ -110,28 +98,6 @@ class CoPilotProcessor:
 
         logger.info(f"[CoPilotExecutor] Worker {self.tid} started")
 
-    def cleanup(self):
-        """Clean up event-loop-bound resources before the loop is destroyed.
-
-        Shuts down the workspace storage instance that belongs to this
-        worker's event loop, ensuring ``aiohttp.ClientSession.close()``
-        runs on the same loop that created the session.
-        """
-        from backend.util.workspace_storage import shutdown_workspace_storage
-
-        try:
-            future = asyncio.run_coroutine_threadsafe(
-                shutdown_workspace_storage(), self.execution_loop
-            )
-            future.result(timeout=5)
-        except Exception as e:
-            logger.warning(f"[CoPilotExecutor] Worker {self.tid} cleanup error: {e}")
-
-        # Stop the event loop
-        self.execution_loop.call_soon_threadsafe(self.execution_loop.stop)
-        self.execution_thread.join(timeout=5)
-        logger.info(f"[CoPilotExecutor] Worker {self.tid} cleaned up")
-
     @error_logged(swallow=False)
     def execute(
         self,

autogpt_platform/backend/backend/copilot/sdk/response_adapter.py

@@ -53,7 +53,6 @@ class SDKResponseAdapter:
         self.has_started_text = False
         self.has_ended_text = False
         self.current_tool_calls: dict[str, dict[str, str]] = {}
-        self.resolved_tool_calls: set[str] = set()
         self.task_id: str | None = None
         self.step_open = False
 
@@ -75,10 +74,6 @@ class SDKResponseAdapter:
                 self.step_open = True
 
         elif isinstance(sdk_message, AssistantMessage):
-            # Flush any SDK built-in tool calls that didn't get a UserMessage
-            # result (e.g. WebSearch, Read handled internally by the CLI).
-            self._flush_unresolved_tool_calls(responses)
-
             # After tool results, the SDK sends a new AssistantMessage for the
             # next LLM turn. Open a new step if the previous one was closed.
             if not self.step_open:
@@ -116,8 +111,6 @@ class SDKResponseAdapter:
             # UserMessage carries tool results back from tool execution.
             content = sdk_message.content
             blocks = content if isinstance(content, list) else []
-            resolved_in_blocks: set[str] = set()
-
             for block in blocks:
                 if isinstance(block, ToolResultBlock) and block.tool_use_id:
                     tool_info = self.current_tool_calls.get(block.tool_use_id, {})
@@ -139,37 +132,6 @@ class SDKResponseAdapter:
                             success=not (block.is_error or False),
                         )
                     )
-                    resolved_in_blocks.add(block.tool_use_id)
-
-            # Handle SDK built-in tool results carried via parent_tool_use_id
-            # instead of (or in addition to) ToolResultBlock content.
-            parent_id = sdk_message.parent_tool_use_id
-            if parent_id and parent_id not in resolved_in_blocks:
-                tool_info = self.current_tool_calls.get(parent_id, {})
-                tool_name = tool_info.get("name", "unknown")
-
-                # Try stashed output first (from PostToolUse hook),
-                # then tool_use_result dict, then string content.
-                output = pop_pending_tool_output(tool_name)
-                if not output:
-                    tur = sdk_message.tool_use_result
-                    if tur is not None:
-                        output = _extract_tool_use_result(tur)
-                if not output and isinstance(content, str) and content.strip():
-                    output = content.strip()
-
-                if output:
-                    responses.append(
-                        StreamToolOutputAvailable(
-                            toolCallId=parent_id,
-                            toolName=tool_name,
-                            output=output,
-                            success=True,
-                        )
-                    )
-                    resolved_in_blocks.add(parent_id)
-
-            self.resolved_tool_calls.update(resolved_in_blocks)
 
             # Close the current step after tool results — the next
             # AssistantMessage will open a new step for the continuation.
@@ -178,7 +140,6 @@ class SDKResponseAdapter:
                 self.step_open = False
 
         elif isinstance(sdk_message, ResultMessage):
-            self._flush_unresolved_tool_calls(responses)
             self._end_text_if_open(responses)
             # Close the step before finishing.
             if self.step_open:
@@ -188,7 +149,7 @@ class SDKResponseAdapter:
             if sdk_message.subtype == "success":
                 responses.append(StreamFinish())
             elif sdk_message.subtype in ("error", "error_during_execution"):
-                error_msg = sdk_message.result or "Unknown error"
+                error_msg = getattr(sdk_message, "result", None) or "Unknown error"
                 responses.append(
                     StreamError(errorText=str(error_msg), code="sdk_error")
                 )
@@ -219,59 +180,6 @@ class SDKResponseAdapter:
             responses.append(StreamTextEnd(id=self.text_block_id))
             self.has_ended_text = True
 
-    def _flush_unresolved_tool_calls(self, responses: list[StreamBaseResponse]) -> None:
-        """Emit outputs for tool calls that didn't receive a UserMessage result.
-
-        SDK built-in tools (WebSearch, Read, etc.) may be executed by the CLI
-        internally without surfacing a separate ``UserMessage`` with
-        ``ToolResultBlock`` content.  The ``PostToolUse`` hook stashes their
-        output, which we pop and emit here before the next ``AssistantMessage``
-        starts.
-        """
-        flushed = False
-        for tool_id, tool_info in self.current_tool_calls.items():
-            if tool_id in self.resolved_tool_calls:
-                continue
-            tool_name = tool_info.get("name", "unknown")
-            output = pop_pending_tool_output(tool_name)
-            if output is not None:
-                responses.append(
-                    StreamToolOutputAvailable(
-                        toolCallId=tool_id,
-                        toolName=tool_name,
-                        output=output,
-                        success=True,
-                    )
-                )
-                self.resolved_tool_calls.add(tool_id)
-                flushed = True
-                logger.debug(
-                    f"Flushed pending output for built-in tool {tool_name} "
-                    f"(call {tool_id})"
-                )
-            else:
-                # No output available — emit an empty output so the frontend
-                # transitions the tool from input-available to output-available
-                # (stops the spinner).
-                responses.append(
-                    StreamToolOutputAvailable(
-                        toolCallId=tool_id,
-                        toolName=tool_name,
-                        output="",
-                        success=True,
-                    )
-                )
-                self.resolved_tool_calls.add(tool_id)
-                flushed = True
-                logger.debug(
-                    f"Flushed empty output for unresolved tool {tool_name} "
-                    f"(call {tool_id})"
-                )
-
-        if flushed and self.step_open:
-            responses.append(StreamFinishStep())
-            self.step_open = False
-
 
 def _extract_tool_output(content: str | list[dict[str, str]] | None) -> str:
     """Extract a string output from a ToolResultBlock's content field."""
@@ -291,30 +199,3 @@ def _extract_tool_output(content: str | list[dict[str, str]] | None) -> str:
         return json.dumps(content)
     except (TypeError, ValueError):
         return str(content)
-
-
-def _extract_tool_use_result(result: object) -> str:
-    """Extract a string from a UserMessage's ``tool_use_result`` dict.
-
-    SDK built-in tools may store their result in ``tool_use_result``
-    instead of (or in addition to) ``ToolResultBlock`` content blocks.
-    """
-    if isinstance(result, str):
-        return result
-    if isinstance(result, dict):
-        # Try common result keys
-        for key in ("content", "text", "output", "stdout", "result"):
-            val = result.get(key)
-            if isinstance(val, str) and val:
-                return val
-        # Fall back to JSON serialization of the whole dict
-        try:
-            return json.dumps(result)
-        except (TypeError, ValueError):
-            return str(result)
-    if result is None:
-        return ""
-    try:
-        return json.dumps(result)
-    except (TypeError, ValueError):
-        return str(result)

autogpt_platform/backend/backend/copilot/sdk/security_hooks.py

@@ -16,7 +16,6 @@ from .tool_adapter import (
     DANGEROUS_PATTERNS,
     MCP_TOOL_PREFIX,
     WORKSPACE_SCOPED_TOOLS,
-    stash_pending_tool_output,
 )
 
 logger = logging.getLogger(__name__)
@@ -225,25 +224,10 @@ def create_security_hooks(
             tool_use_id: str | None,
             context: HookContext,
         ) -> SyncHookJSONOutput:
-            """Log successful tool executions and stash SDK built-in tool outputs.
-
-            MCP tools stash their output in ``_execute_tool_sync`` before the
-            SDK can truncate it.  SDK built-in tools (WebSearch, Read, etc.)
-            are executed by the CLI internally — this hook captures their
-            output so the response adapter can forward it to the frontend.
-            """
+            """Log successful tool executions for observability."""
             _ = context
             tool_name = cast(str, input_data.get("tool_name", ""))
             logger.debug(f"[SDK] Tool success: {tool_name}, tool_use_id={tool_use_id}")
-
-            # Stash output for SDK built-in tools so the response adapter can
-            # emit StreamToolOutputAvailable even when the CLI doesn't surface
-            # a separate UserMessage with ToolResultBlock content.
-            if not tool_name.startswith(MCP_TOOL_PREFIX):
-                tool_response = input_data.get("tool_response")
-                if tool_response is not None:
-                    stash_pending_tool_output(tool_name, tool_response)
-
             return cast(SyncHookJSONOutput, {})
 
         async def post_tool_failure_hook(

autogpt_platform/backend/backend/copilot/sdk/service.py

@@ -47,7 +47,6 @@ from .tool_adapter import (
     set_execution_context,
 )
 from .transcript import (
-    cleanup_cli_project_dir,
     download_transcript,
     read_transcript_file,
     upload_transcript,
@@ -87,12 +86,9 @@ _SDK_TOOL_SUPPLEMENT = """
   for shell commands — it runs in a network-isolated sandbox.
 - **Shared workspace**: The SDK Read/Write tools and `bash_exec` share the
   same working directory. Files created by one are readable by the other.
-- **IMPORTANT — File persistence**: Your working directory is **ephemeral** —
-  files are lost between turns. When you create or modify important files
-  (code, configs, outputs), you MUST save them using `write_workspace_file`
-  so they persist. Use `read_workspace_file` and `list_workspace_files` to
-  access files saved in previous turns. If a "Files from previous turns"
-  section is present above, those files are available via `read_workspace_file`.
+  These files are **ephemeral** — they exist only for the current session.
+- **Persistent storage**: Use `write_workspace_file` / `read_workspace_file`
+  for files that should persist across sessions (stored in cloud storage).
 - Long-running tools (create_agent, edit_agent, etc.) are handled
   asynchronously.  You will receive an immediate response; the actual result
   is delivered to the user via a background stream.
@@ -272,28 +268,48 @@ def _make_sdk_cwd(session_id: str) -> str:
 
 
 def _cleanup_sdk_tool_results(cwd: str) -> None:
-    """Remove SDK session artifacts for a specific working directory.
+    """Remove SDK tool-result files for a specific session working directory.
 
-    Cleans up:
-    - ``~/.claude/projects/<encoded-cwd>/`` — CLI session transcripts and
-      tool-result files.  Each SDK turn uses a unique cwd, so this directory
-      is safe to remove entirely.
-    - ``/tmp/copilot-<session>/`` — the ephemeral working directory.
+    The SDK creates tool-result files under ~/.claude/projects/<encoded-cwd>/tool-results/.
+    We clean only the specific cwd's results to avoid race conditions between
+    concurrent sessions.
 
-    Security: *cwd* MUST be created by ``_make_sdk_cwd()`` which sanitizes
-    the session_id.
+    Security: cwd MUST be created by _make_sdk_cwd() which sanitizes session_id.
     """
     import shutil
 
+    # Validate cwd is under the expected prefix
     normalized = os.path.normpath(cwd)
     if not normalized.startswith(_SDK_CWD_PREFIX):
         logger.warning(f"[SDK] Rejecting cleanup for path outside workspace: {cwd}")
         return
 
-    # Clean the CLI's project directory (transcripts + tool-results).
-    cleanup_cli_project_dir(cwd)
+    # SDK encodes the cwd path by replacing '/' with '-'
+    encoded_cwd = normalized.replace("/", "-")
 
-    # Clean up the temp cwd directory itself.
+    # Construct the project directory path (known-safe home expansion)
+    claude_projects = os.path.expanduser("~/.claude/projects")
+    project_dir = os.path.join(claude_projects, encoded_cwd)
+
+    # Security check 3: Validate project_dir is under ~/.claude/projects
+    project_dir = os.path.normpath(project_dir)
+    if not project_dir.startswith(claude_projects):
+        logger.warning(
+            f"[SDK] Rejecting cleanup for escaped project path: {project_dir}"
+        )
+        return
+
+    results_dir = os.path.join(project_dir, "tool-results")
+    if os.path.isdir(results_dir):
+        for filename in os.listdir(results_dir):
+            file_path = os.path.join(results_dir, filename)
+            try:
+                if os.path.isfile(file_path):
+                    os.remove(file_path)
+            except OSError:
+                pass
+
+    # Also clean up the temp cwd directory itself
     try:
         shutil.rmtree(normalized, ignore_errors=True)
     except OSError:
@@ -503,7 +519,6 @@ async def stream_chat_completion_sdk(
             def _on_stop(transcript_path: str, sdk_session_id: str) -> None:
                 captured_transcript.path = transcript_path
                 captured_transcript.sdk_session_id = sdk_session_id
-                logger.debug(f"[SDK] Stop hook: path={transcript_path!r}")
 
             security_hooks = create_security_hooks(
                 user_id,
@@ -515,20 +530,18 @@ async def stream_chat_completion_sdk(
             # --- Resume strategy: download transcript from bucket ---
             resume_file: str | None = None
             use_resume = False
-            transcript_msg_count = 0  # watermark: session.messages length at upload
 
             if config.claude_agent_use_resume and user_id and len(session.messages) > 1:
-                dl = await download_transcript(user_id, session_id)
-                if dl and validate_transcript(dl.content):
+                transcript_content = await download_transcript(user_id, session_id)
+                if transcript_content and validate_transcript(transcript_content):
                     resume_file = write_transcript_to_tempfile(
-                        dl.content, session_id, sdk_cwd
+                        transcript_content, session_id, sdk_cwd
                     )
                     if resume_file:
                         use_resume = True
-                        transcript_msg_count = dl.message_count
-                        logger.debug(
-                            f"[SDK] Using --resume ({len(dl.content)}B, "
-                            f"msg_count={transcript_msg_count})"
+                        logger.info(
+                            f"[SDK] Using --resume with transcript "
+                            f"({len(transcript_content)} bytes)"
                         )
 
             sdk_options_kwargs: dict[str, Any] = {
@@ -569,35 +582,11 @@ async def stream_chat_completion_sdk(
                 # Build query: with --resume the CLI already has full
                 # context, so we only send the new message.  Without
                 # resume, compress history into a context prefix.
-                #
-                # Hybrid mode: if the transcript is stale (upload missed
-                # some turns), compress only the gap and prepend it so
-                # the agent has transcript context + missed turns.
                 query_message = current_message
-                current_msg_count = len(session.messages)
-
-                if use_resume and transcript_msg_count > 0:
-                    # Transcript covers messages[0..M-1].  Current session
-                    # has N messages (last one is the new user msg).
-                    # Gap = messages[M .. N-2] (everything between upload
-                    # and the current turn).
-                    if transcript_msg_count < current_msg_count - 1:
-                        gap = session.messages[transcript_msg_count:-1]
-                        gap_context = _format_conversation_context(gap)
-                        if gap_context:
-                            logger.info(
-                                f"[SDK] Transcript stale: covers {transcript_msg_count} "
-                                f"of {current_msg_count} messages, compressing "
-                                f"{len(gap)} missed messages"
-                            )
-                            query_message = (
-                                f"{gap_context}\n\n"
-                                f"Now, the user says:\n{current_message}"
-                            )
-                elif not use_resume and current_msg_count > 1:
+                if not use_resume and len(session.messages) > 1:
                     logger.warning(
                         f"[SDK] Using compression fallback for session "
-                        f"{session_id} ({current_msg_count} messages) — "
+                        f"{session_id} ({len(session.messages)} messages) — "
                         f"no transcript available for --resume"
                     )
                     compressed = await _compress_conversation_history(session)
@@ -608,10 +597,10 @@ async def stream_chat_completion_sdk(
                             f"Now, the user says:\n{current_message}"
                         )
 
-                logger.debug(
-                    f"[SDK] Sending query ({len(session.messages)} msgs, "
-                    f"resume={use_resume})"
+                logger.info(
+                    f"[SDK] Sending query ({len(session.messages)} msgs in session)"
                 )
+                logger.debug(f"[SDK] Query preview: {current_message[:80]!r}")
                 await client.query(query_message, session_id=session_id)
 
                 assistant_response = ChatMessage(role="assistant", content="")
@@ -692,27 +681,25 @@ async def stream_chat_completion_sdk(
                 ) and not has_appended_assistant:
                     session.messages.append(assistant_response)
 
-            # --- Upload transcript for next-turn --resume ---
-            # After async with the SDK task group has exited, so the Stop
-            # hook has already fired and the CLI has been SIGTERMed.  The
-            # CLI uses appendFileSync, so all writes are safely on disk.
-            if config.claude_agent_use_resume and user_id:
-                # With --resume the CLI appends to the resume file (most
-                # complete).  Otherwise use the Stop hook path.
-                if use_resume and resume_file:
-                    raw_transcript = read_transcript_file(resume_file)
-                elif captured_transcript.path:
+                # --- Capture transcript while CLI is still alive ---
+                # Must happen INSIDE async with: close() sends SIGTERM
+                # which kills the CLI before it can flush the JSONL.
+                if (
+                    config.claude_agent_use_resume
+                    and user_id
+                    and captured_transcript.available
+                ):
+                    # Give CLI time to flush JSONL writes before we read
+                    await asyncio.sleep(0.5)
                     raw_transcript = read_transcript_file(captured_transcript.path)
-                else:
-                    raw_transcript = None
-
-                if raw_transcript:
-                    await _try_upload_transcript(
-                        user_id,
-                        session_id,
-                        raw_transcript,
-                        message_count=len(session.messages),
-                    )
+                    if raw_transcript:
+                        task = asyncio.create_task(
+                            _upload_transcript_bg(user_id, session_id, raw_transcript)
+                        )
+                        _background_tasks.add(task)
+                        task.add_done_callback(_background_tasks.discard)
+                    else:
+                        logger.debug("[SDK] Stop hook fired but transcript not usable")
 
         except ImportError:
             raise RuntimeError(
@@ -744,31 +731,14 @@ async def stream_chat_completion_sdk(
             _cleanup_sdk_tool_results(sdk_cwd)
 
 
-async def _try_upload_transcript(
-    user_id: str,
-    session_id: str,
-    raw_content: str,
-    message_count: int = 0,
-) -> bool:
-    """Strip progress entries and upload transcript (with timeout).
-
-    Returns True if the upload completed without error.
-    """
+async def _upload_transcript_bg(
+    user_id: str, session_id: str, raw_content: str
+) -> None:
+    """Background task to strip progress entries and upload transcript."""
     try:
-        async with asyncio.timeout(30):
-            await upload_transcript(
-                user_id, session_id, raw_content, message_count=message_count
-            )
-        return True
-    except asyncio.TimeoutError:
-        logger.warning(f"[SDK] Transcript upload timed out for {session_id}")
-        return False
+        await upload_transcript(user_id, session_id, raw_content)
     except Exception as e:
-        logger.error(
-            f"[SDK] Failed to upload transcript for {session_id}: {e}",
-            exc_info=True,
-        )
-        return False
+        logger.error(f"[SDK] Failed to upload transcript for {session_id}: {e}")
 
 
 async def _update_title_async(

autogpt_platform/backend/backend/copilot/sdk/tool_adapter.py

@@ -103,31 +103,6 @@ def pop_pending_tool_output(tool_name: str) -> str | None:
     return pending.pop(tool_name, None)
 
 
-def stash_pending_tool_output(tool_name: str, output: Any) -> None:
-    """Stash tool output for later retrieval by the response adapter.
-
-    Used by the PostToolUse hook to capture SDK built-in tool outputs
-    (WebSearch, Read, etc.) that aren't available through the MCP stash
-    mechanism in ``_execute_tool_sync``.
-
-    Does NOT overwrite an existing stash entry — MCP tools stash in
-    ``_execute_tool_sync`` first with the guaranteed-full output.
-    """
-    pending = _pending_tool_outputs.get(None)
-    if pending is None:
-        return
-    # Don't overwrite MCP tool stash (which has the guaranteed-full output)
-    if tool_name in pending:
-        return
-    if isinstance(output, str):
-        pending[tool_name] = output
-    else:
-        try:
-            pending[tool_name] = json.dumps(output)
-        except (TypeError, ValueError):
-            pending[tool_name] = str(output)
-
-
 async def _execute_tool_sync(
     base_tool: BaseTool,
     user_id: str | None,
@@ -152,54 +127,12 @@ async def _execute_tool_sync(
     if pending is not None:
         pending[base_tool.name] = text
 
-    content_blocks: list[dict[str, str]] = [{"type": "text", "text": text}]
-
-    # If the tool result contains inline image data, add an MCP image block
-    # so Claude can "see" the image (e.g. read_workspace_file on a small PNG).
-    image_block = _extract_image_block(text)
-    if image_block:
-        content_blocks.append(image_block)
-
     return {
-        "content": content_blocks,
+        "content": [{"type": "text", "text": text}],
         "isError": not result.success,
     }
 
 
-# MIME types that Claude can process as image content blocks.
-_SUPPORTED_IMAGE_TYPES = frozenset(
-    {"image/png", "image/jpeg", "image/gif", "image/webp"}
-)
-
-
-def _extract_image_block(text: str) -> dict[str, str] | None:
-    """Extract an MCP image content block from a tool result JSON string.
-
-    Detects workspace file responses with ``content_base64`` and an image
-    MIME type, returning an MCP-format image block that allows Claude to
-    "see" the image.  Returns ``None`` if the result is not an inline image.
-    """
-    try:
-        data = json.loads(text)
-    except (json.JSONDecodeError, TypeError):
-        return None
-
-    if not isinstance(data, dict):
-        return None
-
-    mime_type = data.get("mime_type", "")
-    base64_content = data.get("content_base64", "")
-
-    if mime_type in _SUPPORTED_IMAGE_TYPES and base64_content:
-        return {
-            "type": "image",
-            "data": base64_content,
-            "mimeType": mime_type,
-        }
-
-    return None
-
-
 def _mcp_error(message: str) -> dict[str, Any]:
     return {
         "content": [
@@ -378,29 +311,14 @@ def create_copilot_mcp_server():
 # which provides kernel-level network isolation via unshare --net.
 # Task allows spawning sub-agents (rate-limited by security hooks).
 # WebSearch uses Brave Search via Anthropic's API — safe, no SSRF risk.
-# TodoWrite manages the task checklist shown in the UI — no security concern.
-_SDK_BUILTIN_TOOLS = [
-    "Read",
-    "Write",
-    "Edit",
-    "Glob",
-    "Grep",
-    "Task",
-    "WebSearch",
-    "TodoWrite",
-]
+_SDK_BUILTIN_TOOLS = ["Read", "Write", "Edit", "Glob", "Grep", "Task", "WebSearch"]
 
 # SDK built-in tools that must be explicitly blocked.
 # Bash: dangerous — agent uses mcp__copilot__bash_exec with kernel-level
 #   network isolation (unshare --net) instead.
 # WebFetch: SSRF risk — can reach internal network (localhost, 10.x, etc.).
 #   Agent uses the SSRF-protected mcp__copilot__web_fetch tool instead.
-# AskUserQuestion: interactive CLI tool — no terminal in copilot context.
-SDK_DISALLOWED_TOOLS = [
-    "Bash",
-    "WebFetch",
-    "AskUserQuestion",
-]
+SDK_DISALLOWED_TOOLS = ["Bash", "WebFetch"]
 
 # Tools that are blocked entirely in security hooks (defence-in-depth).
 # Includes SDK_DISALLOWED_TOOLS plus common aliases/synonyms.

autogpt_platform/backend/backend/copilot/sdk/transcript.py

@@ -14,8 +14,6 @@ import json
 import logging
 import os
 import re
-import time
-from dataclasses import dataclass
 
 logger = logging.getLogger(__name__)
 
@@ -33,16 +31,6 @@ STRIPPABLE_TYPES = frozenset(
     {"progress", "file-history-snapshot", "queue-operation", "summary", "pr-link"}
 )
 
-
-@dataclass
-class TranscriptDownload:
-    """Result of downloading a transcript with its metadata."""
-
-    content: str
-    message_count: int = 0  # session.messages length when uploaded
-    uploaded_at: float = 0.0  # epoch timestamp of upload
-
-
 # Workspace storage constants — deterministic path from session_id.
 TRANSCRIPT_STORAGE_PREFIX = "chat-transcripts"
 
@@ -131,19 +119,23 @@ def read_transcript_file(transcript_path: str) -> str | None:
             content = f.read()
 
         if not content.strip():
+            logger.debug(f"[Transcript] Empty file: {transcript_path}")
             return None
 
         lines = content.strip().split("\n")
         if len(lines) < 3:
             # Raw files with ≤2 lines are metadata-only
             # (queue-operation + file-history-snapshot, no conversation).
+            logger.debug(
+                f"[Transcript] Too few lines ({len(lines)}): {transcript_path}"
+            )
             return None
 
         # Quick structural validation — parse first and last lines.
         json.loads(lines[0])
         json.loads(lines[-1])
 
-        logger.debug(
+        logger.info(
             f"[Transcript] Read {len(lines)} lines, "
             f"{len(content)} bytes from {transcript_path}"
         )
@@ -168,39 +160,6 @@ def _sanitize_id(raw_id: str, max_len: int = 36) -> str:
 _SAFE_CWD_PREFIX = os.path.realpath("/tmp/copilot-")
 
 
-def _encode_cwd_for_cli(cwd: str) -> str:
-    """Encode a working directory path the same way the Claude CLI does.
-
-    The CLI replaces all non-alphanumeric characters with ``-``.
-    """
-    return re.sub(r"[^a-zA-Z0-9]", "-", os.path.realpath(cwd))
-
-
-def cleanup_cli_project_dir(sdk_cwd: str) -> None:
-    """Remove the CLI's project directory for a specific working directory.
-
-    The CLI stores session data under ``~/.claude/projects/<encoded_cwd>/``.
-    Each SDK turn uses a unique ``sdk_cwd``, so the project directory is
-    safe to remove entirely after the transcript has been uploaded.
-    """
-    import shutil
-
-    cwd_encoded = _encode_cwd_for_cli(sdk_cwd)
-    config_dir = os.environ.get("CLAUDE_CONFIG_DIR") or os.path.expanduser("~/.claude")
-    projects_base = os.path.realpath(os.path.join(config_dir, "projects"))
-    project_dir = os.path.realpath(os.path.join(projects_base, cwd_encoded))
-
-    if not project_dir.startswith(projects_base + os.sep):
-        logger.warning(
-            f"[Transcript] Cleanup path escaped projects base: {project_dir}"
-        )
-        return
-
-    if os.path.isdir(project_dir):
-        shutil.rmtree(project_dir, ignore_errors=True)
-        logger.debug(f"[Transcript] Cleaned up CLI project dir: {project_dir}")
-
-
 def write_transcript_to_tempfile(
     transcript_content: str,
     session_id: str,
@@ -232,7 +191,7 @@ def write_transcript_to_tempfile(
         with open(jsonl_path, "w") as f:
             f.write(transcript_content)
 
-        logger.debug(f"[Transcript] Wrote resume file: {jsonl_path}")
+        logger.info(f"[Transcript] Wrote resume file: {jsonl_path}")
         return jsonl_path
 
     except OSError as e:
@@ -289,15 +248,6 @@ def _storage_path_parts(user_id: str, session_id: str) -> tuple[str, str, str]:
     )
 
 
-def _meta_storage_path_parts(user_id: str, session_id: str) -> tuple[str, str, str]:
-    """Return (workspace_id, file_id, filename) for a session's transcript metadata."""
-    return (
-        TRANSCRIPT_STORAGE_PREFIX,
-        _sanitize_id(user_id),
-        f"{_sanitize_id(session_id)}.meta.json",
-    )
-
-
 def _build_storage_path(user_id: str, session_id: str, backend: object) -> str:
     """Build the full storage path string that ``retrieve()`` expects.
 
@@ -318,30 +268,21 @@ def _build_storage_path(user_id: str, session_id: str, backend: object) -> str:
         return f"local://{wid}/{fid}/{fname}"
 
 
-async def upload_transcript(
-    user_id: str,
-    session_id: str,
-    content: str,
-    message_count: int = 0,
-) -> None:
+async def upload_transcript(user_id: str, session_id: str, content: str) -> None:
     """Strip progress entries and upload transcript to bucket storage.
 
     Safety: only overwrites when the new (stripped) transcript is larger than
     what is already stored.  Since JSONL is append-only, the latest transcript
     is always the longest.  This prevents a slow/stale background task from
     clobbering a newer upload from a concurrent turn.
-
-    Args:
-        message_count: ``len(session.messages)`` at upload time — used by
-            the next turn to detect staleness and compress only the gap.
     """
     from backend.util.workspace_storage import get_workspace_storage
 
     stripped = strip_progress_entries(content)
     if not validate_transcript(stripped):
         logger.warning(
-            f"[Transcript] Skipping upload — stripped content not valid "
-            f"for session {session_id}"
+            f"[Transcript] Skipping upload — stripped content is not a valid "
+            f"transcript for session {session_id}"
         )
         return
 
@@ -355,9 +296,10 @@ async def upload_transcript(
     try:
         existing = await storage.retrieve(path)
         if len(existing) >= new_size:
-            logger.debug(
-                f"[Transcript] Skipping upload — existing ({len(existing)}B) "
-                f">= new ({new_size}B) for session {session_id}"
+            logger.info(
+                f"[Transcript] Skipping upload — existing transcript "
+                f"({len(existing)}B) >= new ({new_size}B) for session "
+                f"{session_id}"
             )
             return
     except (FileNotFoundError, Exception):
@@ -369,32 +311,16 @@ async def upload_transcript(
         filename=fname,
         content=encoded,
     )
-
-    # Store metadata alongside the transcript so the next turn can detect
-    # staleness and only compress the gap instead of the full history.
-    meta = {"message_count": message_count, "uploaded_at": time.time()}
-    mwid, mfid, mfname = _meta_storage_path_parts(user_id, session_id)
-    await storage.store(
-        workspace_id=mwid,
-        file_id=mfid,
-        filename=mfname,
-        content=json.dumps(meta).encode("utf-8"),
-    )
-
     logger.info(
-        f"[Transcript] Uploaded {new_size}B "
-        f"(stripped from {len(content)}B, msg_count={message_count}) "
-        f"for session {session_id}"
+        f"[Transcript] Uploaded {new_size} bytes "
+        f"(stripped from {len(content)}) for session {session_id}"
     )
 
 
-async def download_transcript(
-    user_id: str, session_id: str
-) -> TranscriptDownload | None:
-    """Download transcript and metadata from bucket storage.
+async def download_transcript(user_id: str, session_id: str) -> str | None:
+    """Download transcript from bucket storage.
 
-    Returns a ``TranscriptDownload`` with the JSONL content and the
-    ``message_count`` watermark from the upload, or ``None`` if not found.
+    Returns the JSONL content string, or ``None`` if not found.
     """
     from backend.util.workspace_storage import get_workspace_storage
 
@@ -404,6 +330,10 @@ async def download_transcript(
     try:
         data = await storage.retrieve(path)
         content = data.decode("utf-8")
+        logger.info(
+            f"[Transcript] Downloaded {len(content)} bytes for session {session_id}"
+        )
+        return content
     except FileNotFoundError:
         logger.debug(f"[Transcript] No transcript in storage for {session_id}")
         return None
@@ -411,36 +341,6 @@ async def download_transcript(
         logger.warning(f"[Transcript] Failed to download transcript: {e}")
         return None
 
-    # Try to load metadata (best-effort — old transcripts won't have it)
-    message_count = 0
-    uploaded_at = 0.0
-    try:
-        from backend.util.workspace_storage import GCSWorkspaceStorage
-
-        mwid, mfid, mfname = _meta_storage_path_parts(user_id, session_id)
-        if isinstance(storage, GCSWorkspaceStorage):
-            blob = f"workspaces/{mwid}/{mfid}/{mfname}"
-            meta_path = f"gcs://{storage.bucket_name}/{blob}"
-        else:
-            meta_path = f"local://{mwid}/{mfid}/{mfname}"
-
-        meta_data = await storage.retrieve(meta_path)
-        meta = json.loads(meta_data.decode("utf-8"))
-        message_count = meta.get("message_count", 0)
-        uploaded_at = meta.get("uploaded_at", 0.0)
-    except (FileNotFoundError, json.JSONDecodeError, Exception):
-        pass  # No metadata — treat as unknown (msg_count=0 → always fill gap)
-
-    logger.debug(
-        f"[Transcript] Downloaded {len(content)}B "
-        f"(msg_count={message_count}) for session {session_id}"
-    )
-    return TranscriptDownload(
-        content=content,
-        message_count=message_count,
-        uploaded_at=uploaded_at,
-    )
-
 
 async def delete_transcript(user_id: str, session_id: str) -> None:
     """Delete transcript from bucket storage (e.g. after resume failure)."""

autogpt_platform/backend/backend/copilot/service.py

@@ -387,7 +387,7 @@ async def stream_chat_completion(
     if user_id:
         log_meta["user_id"] = user_id
 
-    logger.debug(
+    logger.info(
         f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, "
         f"message_len={len(message) if message else 0}, is_user={is_user_message}",
         extra={
@@ -404,7 +404,7 @@ async def stream_chat_completion(
         fetch_start = time.monotonic()
         session = await get_chat_session(session_id, user_id)
         fetch_time = (time.monotonic() - fetch_start) * 1000
-        logger.debug(
+        logger.info(
             f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
             f"n_messages={len(session.messages) if session else 0}",
             extra={
@@ -416,7 +416,7 @@ async def stream_chat_completion(
             },
         )
     else:
-        logger.debug(
+        logger.info(
             f"[TIMING] Using provided session, messages={len(session.messages)}",
             extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
         )
@@ -450,7 +450,7 @@ async def stream_chat_completion(
                 message_length=len(message),
             )
             posthog_time = (time.monotonic() - posthog_start) * 1000
-            logger.debug(
+            logger.info(
                 f"[TIMING] track_user_message took {posthog_time:.1f}ms",
                 extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
             )
@@ -458,7 +458,7 @@ async def stream_chat_completion(
     upsert_start = time.monotonic()
     session = await upsert_chat_session(session)
     upsert_time = (time.monotonic() - upsert_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
     )
@@ -503,7 +503,7 @@ async def stream_chat_completion(
     prompt_start = time.monotonic()
     system_prompt, understanding = await _build_system_prompt(user_id)
     prompt_time = (time.monotonic() - prompt_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
     )
@@ -537,7 +537,7 @@ async def stream_chat_completion(
 
     # Only yield message start for the initial call, not for continuations.
     setup_time = (time.monotonic() - completion_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
         extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
     )
@@ -548,7 +548,7 @@ async def stream_chat_completion(
     yield StreamStartStep()
 
     try:
-        logger.debug(
+        logger.info(
             "[TIMING] Calling _stream_chat_chunks",
             extra={"json_fields": log_meta},
         )
@@ -988,7 +988,7 @@ async def _stream_chat_chunks(
     if session.user_id:
         log_meta["user_id"] = session.user_id
 
-    logger.debug(
+    logger.info(
         f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
         f"user={session.user_id}, n_messages={len(session.messages)}",
         extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
@@ -1011,7 +1011,7 @@ async def _stream_chat_chunks(
         base_url=config.base_url,
     )
     context_time = (time_module.perf_counter() - context_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] _manage_context_window took {context_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": context_time}},
     )
@@ -1053,7 +1053,7 @@ async def _stream_chat_chunks(
                 retry_info = (
                     f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
                 )
-                logger.debug(
+                logger.info(
                     f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
                     extra={
                         "json_fields": {
@@ -1093,7 +1093,7 @@ async def _stream_chat_chunks(
                     extra_body=extra_body,
                 )
                 api_init_time = (time_module.perf_counter() - api_call_start) * 1000
-                logger.debug(
+                logger.info(
                     f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
                     extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
                 )
@@ -1142,7 +1142,7 @@ async def _stream_chat_chunks(
                                 ttfc = (
                                     time_module.perf_counter() - api_call_start
                                 ) * 1000
-                                logger.debug(
+                                logger.info(
                                     f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
                                     f"(since API call), n_chunks={chunk_count}",
                                     extra={
@@ -1210,7 +1210,7 @@ async def _stream_chat_chunks(
                                     )
                                     emitted_start_for_idx.add(idx)
                 stream_duration = time_module.perf_counter() - api_call_start
-                logger.debug(
+                logger.info(
                     f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
                     f"duration={stream_duration:.2f}s, "
                     f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
@@ -1244,7 +1244,7 @@ async def _stream_chat_chunks(
                         raise
 
                 total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
-                logger.debug(
+                logger.info(
                     f"[TIMING] _stream_chat_chunks COMPLETED in {total_time / 1000:.1f}s; "
                     f"session={session.session_id}, user={session.user_id}",
                     extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
@@ -1494,8 +1494,8 @@ async def _yield_tool_call(
             # Mark stream registry task as failed if it was created
             try:
                 await stream_registry.mark_task_completed(task_id, status="failed")
-            except Exception as mark_err:
-                logger.warning(f"Failed to mark task {task_id} as failed: {mark_err}")
+            except Exception:
+                pass
             logger.error(
                 f"Failed to setup long-running tool {tool_name}: {e}", exc_info=True
             )

autogpt_platform/backend/backend/copilot/service_test.py

@@ -143,7 +143,7 @@ async def test_sdk_resume_multi_turn(setup_test_user, test_user_id):
         "Transcript was not uploaded to bucket after turn 1 — "
         "Stop hook may not have fired or transcript was too small"
     )
-    logger.info(f"Turn 1 transcript uploaded: {len(transcript.content)} bytes")
+    logger.info(f"Turn 1 transcript uploaded: {len(transcript)} bytes")
 
     # Reload session for turn 2
     session = await get_chat_session(session.session_id, test_user_id)

autogpt_platform/backend/backend/copilot/stream_registry.py

@@ -117,7 +117,7 @@ async def create_task(
     if user_id:
         log_meta["user_id"] = user_id
 
-    logger.debug(
+    logger.info(
         f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}",
         extra={"json_fields": log_meta},
     )
@@ -135,7 +135,7 @@ async def create_task(
     redis_start = time.perf_counter()
     redis = await get_redis_async()
     redis_time = (time.perf_counter() - redis_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] get_redis_async took {redis_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": redis_time}},
     )
@@ -158,7 +158,7 @@ async def create_task(
         },
     )
     hset_time = (time.perf_counter() - hset_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] redis.hset took {hset_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": hset_time}},
     )
@@ -169,7 +169,7 @@ async def create_task(
     await redis.set(op_key, task_id, ex=config.stream_ttl)
 
     total_time = (time.perf_counter() - start_time) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}",
         extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
     )
@@ -230,7 +230,7 @@ async def publish_chunk(
             in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd")
             or total_time > 50
         ):
-            logger.debug(
+            logger.info(
                 f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)",
                 extra={
                     "json_fields": {
@@ -279,7 +279,7 @@ async def subscribe_to_task(
     if user_id:
         log_meta["user_id"] = user_id
 
-    logger.debug(
+    logger.info(
         f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}",
         extra={"json_fields": {**log_meta, "last_message_id": last_message_id}},
     )
@@ -289,14 +289,14 @@ async def subscribe_to_task(
     meta_key = _get_task_meta_key(task_id)
     meta: dict[Any, Any] = await redis.hgetall(meta_key)  # type: ignore[misc]
     hgetall_time = (time.perf_counter() - redis_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}},
     )
 
     if not meta:
         elapsed = (time.perf_counter() - start_time) * 1000
-        logger.debug(
+        logger.info(
             f"[TIMING] Task not found in Redis after {elapsed:.1f}ms",
             extra={
                 "json_fields": {
@@ -335,7 +335,7 @@ async def subscribe_to_task(
     xread_start = time.perf_counter()
     messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000)
     xread_time = (time.perf_counter() - xread_start) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}",
         extra={
             "json_fields": {
@@ -363,7 +363,7 @@ async def subscribe_to_task(
                     except Exception as e:
                         logger.warning(f"Failed to replay message: {e}")
 
-    logger.debug(
+    logger.info(
         f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}",
         extra={
             "json_fields": {
@@ -376,7 +376,7 @@ async def subscribe_to_task(
 
     # Step 2: If task is still running, start stream listener for live updates
     if task_status == "running":
-        logger.debug(
+        logger.info(
             "[TIMING] Task still running, starting _stream_listener",
             extra={"json_fields": {**log_meta, "task_status": task_status}},
         )
@@ -387,14 +387,14 @@ async def subscribe_to_task(
         _listener_tasks[id(subscriber_queue)] = (task_id, listener_task)
     else:
         # Task is completed/failed - add finish marker
-        logger.debug(
+        logger.info(
             f"[TIMING] Task already {task_status}, adding StreamFinish",
             extra={"json_fields": {**log_meta, "task_status": task_status}},
         )
         await subscriber_queue.put(StreamFinish())
 
     total_time = (time.perf_counter() - start_time) * 1000
-    logger.debug(
+    logger.info(
         f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, "
         f"n_messages_replayed={replayed_count}",
         extra={
@@ -433,7 +433,7 @@ async def _stream_listener(
     if log_meta is None:
         log_meta = {"component": "StreamRegistry", "task_id": task_id}
 
-    logger.debug(
+    logger.info(
         f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}",
         extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}},
     )
@@ -462,7 +462,7 @@ async def _stream_listener(
 
             if messages:
                 msg_count = sum(len(msgs) for _, msgs in messages)
-                logger.debug(
+                logger.info(
                     f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms",
                     extra={
                         "json_fields": {
@@ -475,7 +475,7 @@ async def _stream_listener(
                 )
             elif xread_time > 1000:
                 # Only log timeouts (30s blocking)
-                logger.debug(
+                logger.info(
                     f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms",
                     extra={
                         "json_fields": {
@@ -526,7 +526,7 @@ async def _stream_listener(
                                 if first_message_time is None:
                                     first_message_time = time.perf_counter()
                                     elapsed = (first_message_time - start_time) * 1000
-                                    logger.debug(
+                                    logger.info(
                                         f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}",
                                         extra={
                                             "json_fields": {
@@ -568,7 +568,7 @@ async def _stream_listener(
                             # Stop listening on finish
                             if isinstance(chunk, StreamFinish):
                                 total_time = (time.perf_counter() - start_time) * 1000
-                                logger.debug(
+                                logger.info(
                                     f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}",
                                     extra={
                                         "json_fields": {
@@ -587,7 +587,7 @@ async def _stream_listener(
 
     except asyncio.CancelledError:
         elapsed = (time.perf_counter() - start_time) * 1000
-        logger.debug(
+        logger.info(
             f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}",
             extra={
                 "json_fields": {
@@ -619,7 +619,7 @@ async def _stream_listener(
     finally:
         # Clean up listener task mapping on exit
         total_time = (time.perf_counter() - start_time) * 1000
-        logger.debug(
+        logger.info(
             f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
             f"delivered={messages_delivered}, xread_count={xread_count}",
             extra={
@@ -829,13 +829,10 @@ async def get_active_task_for_session(
                             )
                             await mark_task_completed(task_id, "failed")
                             continue
-                    except (ValueError, TypeError) as exc:
-                        logger.warning(
-                            f"[TASK_LOOKUP] Failed to parse created_at "
-                            f"for task {task_id[:8]}...: {exc}"
-                        )
+                    except (ValueError, TypeError):
+                        pass
 
-                logger.debug(
+                logger.info(
                     f"[TASK_LOOKUP] Found running task {task_id[:8]}... for session {session_id[:8]}..."
                 )
 

autogpt_platform/backend/backend/copilot/tools/agent_output.py

@@ -5,7 +5,7 @@ import re
 from datetime import datetime, timedelta, timezone
 from typing import Any
 
-from pydantic import BaseModel, field_validator
+from pydantic import BaseModel, Field, field_validator
 
 from backend.api.features.library.model import LibraryAgent
 from backend.copilot.model import ChatSession
@@ -13,6 +13,7 @@ from backend.data.db_accessors import execution_db, library_db
 from backend.data.execution import ExecutionStatus, GraphExecution, GraphExecutionMeta
 
 from .base import BaseTool
+from .execution_utils import TERMINAL_STATUSES, wait_for_execution
 from .models import (
     AgentOutputResponse,
     ErrorResponse,
@@ -33,6 +34,7 @@ class AgentOutputInput(BaseModel):
     store_slug: str = ""
     execution_id: str = ""
     run_time: str = "latest"
+    wait_if_running: int = Field(default=0, ge=0, le=300)
 
     @field_validator(
         "agent_name",
@@ -116,6 +118,11 @@ class AgentOutputTool(BaseTool):
         Select which run to retrieve using:
         - execution_id: Specific execution ID
         - run_time: 'latest' (default), 'yesterday', 'last week', or ISO date 'YYYY-MM-DD'
+
+        Wait for completion (optional):
+        - wait_if_running: Max seconds to wait if execution is still running (0-300).
+          If the execution is running/queued, waits up to this many seconds for completion.
+          Returns current status on timeout. If already finished, returns immediately.
         """
 
     @property
@@ -145,6 +152,13 @@ class AgentOutputTool(BaseTool):
                         "Time filter: 'latest', 'yesterday', 'last week', or 'YYYY-MM-DD'"
                     ),
                 },
+                "wait_if_running": {
+                    "type": "integer",
+                    "description": (
+                        "Max seconds to wait if execution is still running (0-300). "
+                        "If running, waits for completion. Returns current state on timeout."
+                    ),
+                },
             },
             "required": [],
         }
@@ -224,10 +238,14 @@ class AgentOutputTool(BaseTool):
         execution_id: str | None,
         time_start: datetime | None,
         time_end: datetime | None,
+        include_running: bool = False,
     ) -> tuple[GraphExecution | None, list[GraphExecutionMeta], str | None]:
         """
         Fetch execution(s) based on filters.
         Returns (single_execution, available_executions_meta, error_message).
+
+        Args:
+            include_running: If True, also look for running/queued executions (for waiting)
         """
         exec_db = execution_db()
 
@@ -242,11 +260,23 @@ class AgentOutputTool(BaseTool):
                 return None, [], f"Execution '{execution_id}' not found"
             return execution, [], None
 
-        # Get completed executions with time filters
+        # Determine which statuses to query
+        statuses = [ExecutionStatus.COMPLETED]
+        if include_running:
+            statuses.extend(
+                [
+                    ExecutionStatus.RUNNING,
+                    ExecutionStatus.QUEUED,
+                    ExecutionStatus.INCOMPLETE,
+                    ExecutionStatus.REVIEW,
+                ]
+            )
+
+        # Get executions with time filters
         executions = await exec_db.get_graph_executions(
             graph_id=graph_id,
             user_id=user_id,
-            statuses=[ExecutionStatus.COMPLETED],
+            statuses=statuses,
             created_time_gte=time_start,
             created_time_lte=time_end,
             limit=10,
@@ -313,10 +343,33 @@ class AgentOutputTool(BaseTool):
                 for e in available_executions[:5]
             ]
 
-        message = f"Found execution outputs for agent '{agent.name}'"
+        # Build appropriate message based on execution status
+        if execution.status == ExecutionStatus.COMPLETED:
+            message = f"Found execution outputs for agent '{agent.name}'"
+        elif execution.status == ExecutionStatus.FAILED:
+            message = f"Execution for agent '{agent.name}' failed"
+        elif execution.status == ExecutionStatus.TERMINATED:
+            message = f"Execution for agent '{agent.name}' was terminated"
+        elif execution.status == ExecutionStatus.REVIEW:
+            message = (
+                f"Execution for agent '{agent.name}' is awaiting human review. "
+                "The user needs to approve it before it can continue."
+            )
+        elif execution.status in (
+            ExecutionStatus.RUNNING,
+            ExecutionStatus.QUEUED,
+            ExecutionStatus.INCOMPLETE,
+        ):
+            message = (
+                f"Execution for agent '{agent.name}' is still {execution.status.value}. "
+                "Results may be incomplete. Use wait_if_running to wait for completion."
+            )
+        else:
+            message = f"Found execution for agent '{agent.name}' (status: {execution.status.value})"
+
         if len(available_executions) > 1:
             message += (
-                f". Showing latest of {len(available_executions)} matching executions."
+                f" Showing latest of {len(available_executions)} matching executions."
             )
 
         return AgentOutputResponse(
@@ -431,13 +484,17 @@ class AgentOutputTool(BaseTool):
         # Parse time expression
         time_start, time_end = parse_time_expression(input_data.run_time)
 
-        # Fetch execution(s)
+        # Check if we should wait for running executions
+        wait_timeout = input_data.wait_if_running
+
+        # Fetch execution(s) - include running if we're going to wait
         execution, available_executions, exec_error = await self._get_execution(
             user_id=user_id,
             graph_id=agent.graph_id,
             execution_id=input_data.execution_id or None,
             time_start=time_start,
             time_end=time_end,
+            include_running=wait_timeout > 0,
         )
 
         if exec_error:
@@ -446,4 +503,17 @@ class AgentOutputTool(BaseTool):
                 session_id=session_id,
             )
 
+        # If we have an execution that's still running and we should wait
+        if execution and wait_timeout > 0 and execution.status not in TERMINAL_STATUSES:
+            logger.info(
+                f"Execution {execution.id} is {execution.status}, "
+                f"waiting up to {wait_timeout}s for completion"
+            )
+            execution = await wait_for_execution(
+                user_id=user_id,
+                graph_id=agent.graph_id,
+                execution_id=execution.id,
+                timeout_seconds=wait_timeout,
+            )
+
         return self._build_response(agent, execution, available_executions, session_id)

autogpt_platform/backend/backend/copilot/tools/execution_utils.py

@@ -0,0 +1,169 @@
+"""Shared utilities for execution waiting and status handling."""
+
+import asyncio
+import logging
+from typing import Any
+
+from backend.data.db_accessors import execution_db
+from backend.data.execution import (
+    AsyncRedisExecutionEventBus,
+    ExecutionStatus,
+    GraphExecution,
+    GraphExecutionEvent,
+)
+
+logger = logging.getLogger(__name__)
+
+# Terminal statuses that indicate execution is complete
+TERMINAL_STATUSES = frozenset(
+    {
+        ExecutionStatus.COMPLETED,
+        ExecutionStatus.FAILED,
+        ExecutionStatus.TERMINATED,
+    }
+)
+
+# Statuses where execution is paused but not finished (e.g. human-in-the-loop)
+PAUSED_STATUSES = frozenset(
+    {
+        ExecutionStatus.REVIEW,
+    }
+)
+
+# Statuses that mean "stop waiting" (terminal or paused)
+STOP_WAITING_STATUSES = TERMINAL_STATUSES | PAUSED_STATUSES
+
+
+async def wait_for_execution(
+    user_id: str,
+    graph_id: str,
+    execution_id: str,
+    timeout_seconds: int,
+) -> GraphExecution | None:
+    """
+    Wait for an execution to reach a terminal or paused status using Redis pubsub.
+
+    Handles the race condition between checking status and subscribing by
+    re-checking the DB after the subscription is established.
+
+    Args:
+        user_id: User ID
+        graph_id: Graph ID
+        execution_id: Execution ID to wait for
+        timeout_seconds: Max seconds to wait
+
+    Returns:
+        The execution with current status, or None if not found
+    """
+    exec_db = execution_db()
+
+    # Quick check — maybe it's already done
+    execution = await exec_db.get_graph_execution(
+        user_id=user_id,
+        execution_id=execution_id,
+        include_node_executions=False,
+    )
+    if not execution:
+        return None
+
+    if execution.status in STOP_WAITING_STATUSES:
+        logger.debug(
+            f"Execution {execution_id} already in stop-waiting state: "
+            f"{execution.status}"
+        )
+        return execution
+
+    logger.info(
+        f"Waiting up to {timeout_seconds}s for execution {execution_id} "
+        f"(current status: {execution.status})"
+    )
+
+    event_bus = AsyncRedisExecutionEventBus()
+    channel_key = f"{user_id}/{graph_id}/{execution_id}"
+
+    try:
+        result = await asyncio.wait_for(
+            _subscribe_and_wait(
+                event_bus, channel_key, user_id, execution_id, exec_db
+            ),
+            timeout=timeout_seconds,
+        )
+        return result
+    except asyncio.TimeoutError:
+        logger.info(f"Timeout waiting for execution {execution_id}")
+    except Exception as e:
+        logger.error(f"Error waiting for execution: {e}", exc_info=True)
+    finally:
+        await event_bus.close()
+
+    # Return current state on timeout/error
+    return await exec_db.get_graph_execution(
+        user_id=user_id,
+        execution_id=execution_id,
+        include_node_executions=False,
+    )
+
+
+async def _subscribe_and_wait(
+    event_bus: AsyncRedisExecutionEventBus,
+    channel_key: str,
+    user_id: str,
+    execution_id: str,
+    exec_db: Any,
+) -> GraphExecution | None:
+    """
+    Subscribe to execution events and wait for a terminal/paused status.
+
+    To avoid the race condition where the execution completes between the
+    initial DB check and the Redis subscription, we:
+    1. Start listening (which subscribes internally)
+    2. Re-check the DB after subscription is active
+    3. If still running, wait for pubsub events
+    """
+    listen_iter = event_bus.listen_events(channel_key).__aiter__()
+
+    # Start a background task to consume pubsub events
+    result_event: GraphExecutionEvent | None = None
+    done = asyncio.Event()
+
+    async def _consume():
+        nonlocal result_event
+        async for event in listen_iter:
+            if isinstance(event, GraphExecutionEvent):
+                logger.debug(f"Received execution update: {event.status}")
+                if event.status in STOP_WAITING_STATUSES:
+                    result_event = event
+                    done.set()
+                    return
+
+    consume_task = asyncio.create_task(_consume())
+
+    # Give the subscription a moment to establish, then re-check DB
+    await asyncio.sleep(0.1)
+
+    execution = await exec_db.get_graph_execution(
+        user_id=user_id,
+        execution_id=execution_id,
+        include_node_executions=False,
+    )
+    if execution and execution.status in STOP_WAITING_STATUSES:
+        consume_task.cancel()
+        return execution
+
+    # Wait for the pubsub consumer to find a terminal event
+    await done.wait()
+    consume_task.cancel()
+
+    # Fetch full execution
+    return await exec_db.get_graph_execution(
+        user_id=user_id,
+        execution_id=execution_id,
+        include_node_executions=False,
+    )
+
+
+def get_execution_outputs(execution: GraphExecution | None) -> dict[str, Any] | None:
+    """Extract outputs from an execution, or return None."""
+    if execution is None:
+        return None
+    return execution.outputs

autogpt_platform/backend/backend/copilot/tools/feature_requests.py

@@ -33,6 +33,7 @@ query SearchFeatureRequests($term: String!, $filter: IssueFilter, $first: Int) {
       id
       identifier
       title
+      description
     }
   }
 }
@@ -204,6 +205,7 @@ class SearchFeatureRequestsTool(BaseTool):
                     id=node["id"],
                     identifier=node["identifier"],
                     title=node["title"],
+                    description=node.get("description"),
                 )
                 for node in nodes
             ]
@@ -237,11 +239,7 @@ class CreateFeatureRequestTool(BaseTool):
             "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. "
-            "IMPORTANT: Never include personally identifiable information (PII) in "
-            "the title or description — no names, emails, phone numbers, company "
-            "names, or other identifying details. Write titles and descriptions in "
-            "generic, feature-focused language."
+            "the user's need to it instead of creating a duplicate."
         )
 
     @property
@@ -251,20 +249,11 @@ class CreateFeatureRequestTool(BaseTool):
             "properties": {
                 "title": {
                     "type": "string",
-                    "description": (
-                        "Title for the feature request. Must be generic and "
-                        "feature-focused — do not include any user names, emails, "
-                        "company names, or other PII."
-                    ),
+                    "description": "Title for the feature request.",
                 },
                 "description": {
                     "type": "string",
-                    "description": (
-                        "Detailed description of what the user wants and why. "
-                        "Must not contain any personally identifiable information "
-                        "(PII) — describe the feature need generically without "
-                        "referencing specific users, companies, or contact details."
-                    ),
+                    "description": "Detailed description of what the user wants and why.",
                 },
                 "existing_issue_id": {
                     "type": "string",

autogpt_platform/backend/backend/copilot/tools/feature_requests_test.py

@@ -117,11 +117,13 @@ class TestSearchFeatureRequestsTool:
                 "id": "id-1",
                 "identifier": "FR-1",
                 "title": "Dark mode",
+                "description": "Add dark mode support",
             },
             {
                 "id": "id-2",
                 "identifier": "FR-2",
                 "title": "Dark theme",
+                "description": None,
             },
         ]
         patcher, _ = _mock_linear_config(query_return=_search_response(nodes))

autogpt_platform/backend/backend/copilot/tools/models.py

@@ -486,6 +486,7 @@ class FeatureRequestInfo(BaseModel):
     id: str
     identifier: str
     title: str
+    description: str | None = None
 
 
 class FeatureRequestSearchResponse(ToolResponseBase):

autogpt_platform/backend/backend/copilot/tools/run_agent.py

@@ -9,6 +9,7 @@ from backend.copilot.config import ChatConfig
 from backend.copilot.model import ChatSession
 from backend.copilot.tracking import track_agent_run_success, track_agent_scheduled
 from backend.data.db_accessors import graph_db, library_db, user_db
+from backend.data.execution import ExecutionStatus
 from backend.data.graph import GraphModel
 from backend.data.model import CredentialsMetaInput
 from backend.executor import utils as execution_utils
@@ -24,6 +25,7 @@ from .helpers import get_inputs_from_schema
 from .models import (
     AgentDetails,
     AgentDetailsResponse,
+    AgentOutputResponse,
     ErrorResponse,
     ExecutionOptions,
     ExecutionStartedResponse,
@@ -33,6 +35,7 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
+from .execution_utils import get_execution_outputs, wait_for_execution
 from .utils import (
     build_missing_credentials_from_graph,
     extract_credentials_from_schema,
@@ -66,6 +69,7 @@ class RunAgentInput(BaseModel):
     schedule_name: str = ""
     cron: str = ""
     timezone: str = "UTC"
+    wait_for_result: int = Field(default=0, ge=0, le=300)
 
     @field_validator(
         "username_agent_slug",
@@ -147,6 +151,14 @@ class RunAgentTool(BaseTool):
                     "type": "string",
                     "description": "IANA timezone for schedule (default: UTC)",
                 },
+                "wait_for_result": {
+                    "type": "integer",
+                    "description": (
+                        "Max seconds to wait for execution to complete (0-300). "
+                        "If >0, blocks until the execution finishes or times out. "
+                        "Returns execution outputs when complete."
+                    ),
+                },
             },
             "required": [],
         }
@@ -341,6 +353,7 @@ class RunAgentTool(BaseTool):
                     graph=graph,
                     graph_credentials=graph_credentials,
                     inputs=params.inputs,
+                    wait_for_result=params.wait_for_result,
                 )
 
         except NotFoundError as e:
@@ -424,8 +437,9 @@ class RunAgentTool(BaseTool):
         graph: GraphModel,
         graph_credentials: dict[str, CredentialsMetaInput],
         inputs: dict[str, Any],
+        wait_for_result: int = 0,
     ) -> ToolResponseBase:
-        """Execute an agent immediately."""
+        """Execute an agent immediately, optionally waiting for completion."""
         session_id = session.session_id
 
         # Check rate limits
@@ -462,6 +476,78 @@ class RunAgentTool(BaseTool):
         )
 
         library_agent_link = f"/library/agents/{library_agent.id}"
+
+        # If wait_for_result is requested, wait for execution to complete
+        if wait_for_result > 0:
+            logger.info(
+                f"Waiting up to {wait_for_result}s for execution {execution.id}"
+            )
+            completed = await wait_for_execution(
+                user_id=user_id,
+                graph_id=library_agent.graph_id,
+                execution_id=execution.id,
+                timeout_seconds=wait_for_result,
+            )
+
+            if completed and completed.status == ExecutionStatus.COMPLETED:
+                outputs = get_execution_outputs(completed)
+                return AgentOutputResponse(
+                    message=(
+                        f"Agent '{library_agent.name}' completed successfully. "
+                        f"View at {library_agent_link}."
+                    ),
+                    session_id=session_id,
+                    execution_id=execution.id,
+                    graph_id=library_agent.graph_id,
+                    graph_name=library_agent.name,
+                    outputs=outputs or {},
+                )
+            elif completed and completed.status == ExecutionStatus.FAILED:
+                return ErrorResponse(
+                    message=(
+                        f"Agent '{library_agent.name}' execution failed. "
+                        f"View details at {library_agent_link}."
+                    ),
+                    session_id=session_id,
+                )
+            elif completed and completed.status == ExecutionStatus.TERMINATED:
+                return ErrorResponse(
+                    message=(
+                        f"Agent '{library_agent.name}' execution was terminated. "
+                        f"View details at {library_agent_link}."
+                    ),
+                    session_id=session_id,
+                )
+            elif completed and completed.status == ExecutionStatus.REVIEW:
+                return ExecutionStartedResponse(
+                    message=(
+                        f"Agent '{library_agent.name}' is awaiting human review. "
+                        f"Check at {library_agent_link}."
+                    ),
+                    session_id=session_id,
+                    execution_id=execution.id,
+                    graph_id=library_agent.graph_id,
+                    graph_name=library_agent.name,
+                    library_agent_id=library_agent.id,
+                    library_agent_link=library_agent_link,
+                )
+            else:
+                status = completed.status.value if completed else "unknown"
+                return ExecutionStartedResponse(
+                    message=(
+                        f"Agent '{library_agent.name}' is still {status} after "
+                        f"{wait_for_result}s. Check results later at "
+                        f"{library_agent_link}. "
+                        f"Use view_agent_output with wait_if_running to check again."
+                    ),
+                    session_id=session_id,
+                    execution_id=execution.id,
+                    graph_id=library_agent.graph_id,
+                    graph_name=library_agent.name,
+                    library_agent_id=library_agent.id,
+                    library_agent_link=library_agent_link,
+                )
+
         return ExecutionStartedResponse(
             message=(
                 f"Agent '{library_agent.name}' execution started successfully. "

autogpt_platform/backend/backend/data/db_manager.py

@@ -93,15 +93,7 @@ from backend.data.user import (
     get_user_notification_preference,
     update_user_integrations,
 )
-from backend.data.workspace import (
-    count_workspace_files,
-    create_workspace_file,
-    get_or_create_workspace,
-    get_workspace_file,
-    get_workspace_file_by_path,
-    list_workspace_files,
-    soft_delete_workspace_file,
-)
+from backend.data.workspace import get_or_create_workspace
 from backend.util.service import (
     AppService,
     AppServiceClient,
@@ -282,13 +274,7 @@ class DatabaseManager(AppService):
     get_user_execution_summary_data = _(get_user_execution_summary_data)
 
     # ============ Workspace ============ #
-    count_workspace_files = _(count_workspace_files)
-    create_workspace_file = _(create_workspace_file)
     get_or_create_workspace = _(get_or_create_workspace)
-    get_workspace_file = _(get_workspace_file)
-    get_workspace_file_by_path = _(get_workspace_file_by_path)
-    list_workspace_files = _(list_workspace_files)
-    soft_delete_workspace_file = _(soft_delete_workspace_file)
 
     # ============ Understanding ============ #
     get_business_understanding = _(get_business_understanding)
@@ -452,13 +438,7 @@ class DatabaseManagerAsyncClient(AppServiceClient):
     get_user_execution_summary_data = d.get_user_execution_summary_data
 
     # ============ Workspace ============ #
-    count_workspace_files = d.count_workspace_files
-    create_workspace_file = d.create_workspace_file
     get_or_create_workspace = d.get_or_create_workspace
-    get_workspace_file = d.get_workspace_file
-    get_workspace_file_by_path = d.get_workspace_file_by_path
-    list_workspace_files = d.list_workspace_files
-    soft_delete_workspace_file = d.soft_delete_workspace_file
 
     # ============ Understanding ============ #
     get_business_understanding = d.get_business_understanding

autogpt_platform/backend/backend/data/workspace.py

@@ -164,23 +164,21 @@ async def create_workspace_file(
 
 async def get_workspace_file(
     file_id: str,
-    workspace_id: str,
+    workspace_id: Optional[str] = None,
 ) -> Optional[WorkspaceFile]:
     """
     Get a workspace file by ID.
 
     Args:
         file_id: The file ID
-        workspace_id: Workspace ID for scoping (required)
+        workspace_id: Optional workspace ID for validation
 
     Returns:
         WorkspaceFile instance or None
     """
-    where_clause: UserWorkspaceFileWhereInput = {
-        "id": file_id,
-        "isDeleted": False,
-        "workspaceId": workspace_id,
-    }
+    where_clause: dict = {"id": file_id, "isDeleted": False}
+    if workspace_id:
+        where_clause["workspaceId"] = workspace_id
 
     file = await UserWorkspaceFile.prisma().find_first(where=where_clause)
     return WorkspaceFile.from_db(file) if file else None
@@ -270,7 +268,7 @@ async def count_workspace_files(
     Returns:
         Number of files
     """
-    where_clause: UserWorkspaceFileWhereInput = {"workspaceId": workspace_id}
+    where_clause: dict = {"workspaceId": workspace_id}
     if not include_deleted:
         where_clause["isDeleted"] = False
 
@@ -285,7 +283,7 @@ async def count_workspace_files(
 
 async def soft_delete_workspace_file(
     file_id: str,
-    workspace_id: str,
+    workspace_id: Optional[str] = None,
 ) -> Optional[WorkspaceFile]:
     """
     Soft-delete a workspace file.
@@ -295,7 +293,7 @@ async def soft_delete_workspace_file(
 
     Args:
         file_id: The file ID
-        workspace_id: Workspace ID for scoping (required)
+        workspace_id: Optional workspace ID for validation
 
     Returns:
         Updated WorkspaceFile instance or None if not found

autogpt_platform/backend/backend/util/service.py

@@ -28,7 +28,7 @@ from typing import (
 import httpx
 import uvicorn
 from fastapi import FastAPI, Request, responses
-from prisma.errors import DataError, UniqueViolationError
+from prisma.errors import DataError
 from pydantic import BaseModel, TypeAdapter, create_model
 
 import backend.util.exceptions as exceptions
@@ -201,7 +201,6 @@ EXCEPTION_MAPPING = {
         UnhealthyServiceError,
         HTTPClientError,
         HTTPServerError,
-        UniqueViolationError,
         *[
             ErrorType
             for _, ErrorType in inspect.getmembers(exceptions)
@@ -417,9 +416,6 @@ class AppService(BaseAppService, ABC):
         self.fastapi_app.add_exception_handler(
             DataError, self._handle_internal_http_error(400)
         )
-        self.fastapi_app.add_exception_handler(
-            UniqueViolationError, self._handle_internal_http_error(400)
-        )
         self.fastapi_app.add_exception_handler(
             Exception, self._handle_internal_http_error(500)
         )
@@ -482,7 +478,6 @@ def get_service_client(
                 # Don't retry these specific exceptions that won't be fixed by retrying
                 ValueError,  # Invalid input/parameters
                 DataError,  # Prisma data integrity errors (foreign key, unique constraints)
-                UniqueViolationError,  # Unique constraint violations
                 KeyError,  # Missing required data
                 TypeError,  # Wrong data types
                 AttributeError,  # Missing attributes

autogpt_platform/backend/backend/util/workspace.py

@@ -12,8 +12,15 @@ from typing import Optional
 
 from prisma.errors import UniqueViolationError
 
-from backend.data.db_accessors import workspace_db
-from backend.data.workspace import WorkspaceFile
+from backend.data.workspace import (
+    WorkspaceFile,
+    count_workspace_files,
+    create_workspace_file,
+    get_workspace_file,
+    get_workspace_file_by_path,
+    list_workspace_files,
+    soft_delete_workspace_file,
+)
 from backend.util.settings import Config
 from backend.util.virus_scanner import scan_content_safe
 from backend.util.workspace_storage import compute_file_checksum, get_workspace_storage
@@ -118,9 +125,8 @@ class WorkspaceManager:
         Raises:
             FileNotFoundError: If file doesn't exist
         """
-        db = workspace_db()
         resolved_path = self._resolve_path(path)
-        file = await db.get_workspace_file_by_path(self.workspace_id, resolved_path)
+        file = await get_workspace_file_by_path(self.workspace_id, resolved_path)
         if file is None:
             raise FileNotFoundError(f"File not found at path: {resolved_path}")
 
@@ -140,8 +146,7 @@ class WorkspaceManager:
         Raises:
             FileNotFoundError: If file doesn't exist
         """
-        db = workspace_db()
-        file = await db.get_workspace_file(file_id, self.workspace_id)
+        file = await get_workspace_file(file_id, self.workspace_id)
         if file is None:
             raise FileNotFoundError(f"File not found: {file_id}")
 
@@ -199,10 +204,8 @@ class WorkspaceManager:
         # For overwrite=True, we let the write proceed and handle via UniqueViolationError
         # This ensures the new file is written to storage BEFORE the old one is deleted,
         # preventing data loss if the new write fails
-        db = workspace_db()
-
         if not overwrite:
-            existing = await db.get_workspace_file_by_path(self.workspace_id, path)
+            existing = await get_workspace_file_by_path(self.workspace_id, path)
             if existing is not None:
                 raise ValueError(f"File already exists at path: {path}")
 
@@ -229,7 +232,7 @@ class WorkspaceManager:
         # Create database record - handle race condition where another request
         # created a file at the same path between our check and create
         try:
-            file = await db.create_workspace_file(
+            file = await create_workspace_file(
                 workspace_id=self.workspace_id,
                 file_id=file_id,
                 name=filename,
@@ -243,12 +246,12 @@ class WorkspaceManager:
             # Race condition: another request created a file at this path
             if overwrite:
                 # Re-fetch and delete the conflicting file, then retry
-                existing = await db.get_workspace_file_by_path(self.workspace_id, path)
+                existing = await get_workspace_file_by_path(self.workspace_id, path)
                 if existing:
                     await self.delete_file(existing.id)
                 # Retry the create - if this also fails, clean up storage file
                 try:
-                    file = await db.create_workspace_file(
+                    file = await create_workspace_file(
                         workspace_id=self.workspace_id,
                         file_id=file_id,
                         name=filename,
@@ -311,9 +314,8 @@ class WorkspaceManager:
             List of WorkspaceFile instances
         """
         effective_path = self._get_effective_path(path, include_all_sessions)
-        db = workspace_db()
 
-        return await db.list_workspace_files(
+        return await list_workspace_files(
             workspace_id=self.workspace_id,
             path_prefix=effective_path,
             limit=limit,
@@ -330,8 +332,7 @@ class WorkspaceManager:
         Returns:
             True if deleted, False if not found
         """
-        db = workspace_db()
-        file = await db.get_workspace_file(file_id, self.workspace_id)
+        file = await get_workspace_file(file_id, self.workspace_id)
         if file is None:
             return False
 
@@ -344,7 +345,7 @@ class WorkspaceManager:
             # Continue with database soft-delete even if storage delete fails
 
         # Soft-delete database record
-        result = await db.soft_delete_workspace_file(file_id, self.workspace_id)
+        result = await soft_delete_workspace_file(file_id, self.workspace_id)
         return result is not None
 
     async def get_download_url(self, file_id: str, expires_in: int = 3600) -> str:
@@ -361,8 +362,7 @@ class WorkspaceManager:
         Raises:
             FileNotFoundError: If file doesn't exist
         """
-        db = workspace_db()
-        file = await db.get_workspace_file(file_id, self.workspace_id)
+        file = await get_workspace_file(file_id, self.workspace_id)
         if file is None:
             raise FileNotFoundError(f"File not found: {file_id}")
 
@@ -379,8 +379,7 @@ class WorkspaceManager:
         Returns:
             WorkspaceFile instance or None
         """
-        db = workspace_db()
-        return await db.get_workspace_file(file_id, self.workspace_id)
+        return await get_workspace_file(file_id, self.workspace_id)
 
     async def get_file_info_by_path(self, path: str) -> Optional[WorkspaceFile]:
         """
@@ -395,9 +394,8 @@ class WorkspaceManager:
         Returns:
             WorkspaceFile instance or None
         """
-        db = workspace_db()
         resolved_path = self._resolve_path(path)
-        return await db.get_workspace_file_by_path(self.workspace_id, resolved_path)
+        return await get_workspace_file_by_path(self.workspace_id, resolved_path)
 
     async def get_file_count(
         self,
@@ -419,8 +417,7 @@ class WorkspaceManager:
             Number of files
         """
         effective_path = self._get_effective_path(path, include_all_sessions)
-        db = workspace_db()
 
-        return await db.count_workspace_files(
+        return await count_workspace_files(
             self.workspace_id, path_prefix=effective_path
         )

autogpt_platform/backend/backend/util/workspace_storage.py

@@ -93,14 +93,7 @@ class WorkspaceStorageBackend(ABC):
 
 
 class GCSWorkspaceStorage(WorkspaceStorageBackend):
-    """Google Cloud Storage implementation for workspace storage.
-
-    Each instance owns a single ``aiohttp.ClientSession`` and GCS async
-    client.  Because ``ClientSession`` is bound to the event loop on which it
-    was created, callers that run on separate loops (e.g. copilot executor
-    worker threads) **must** obtain their own ``GCSWorkspaceStorage`` instance
-    via :func:`get_workspace_storage` which is event-loop-aware.
-    """
+    """Google Cloud Storage implementation for workspace storage."""
 
     def __init__(self, bucket_name: str):
         self.bucket_name = bucket_name
@@ -344,73 +337,60 @@ class LocalWorkspaceStorage(WorkspaceStorageBackend):
             raise ValueError(f"Invalid storage path format: {storage_path}")
 
 
-# ---------------------------------------------------------------------------
-# Storage instance management
-# ---------------------------------------------------------------------------
-# ``aiohttp.ClientSession`` is bound to the event loop where it is created.
-# The copilot executor runs each worker in its own thread with a dedicated
-# event loop, so a single global ``GCSWorkspaceStorage`` instance would break.
-#
-# For **local storage** a single shared instance is fine (no async I/O).
-# For **GCS storage** we keep one instance *per event loop* so every loop
-# gets its own ``ClientSession``.
-# ---------------------------------------------------------------------------
-
-_local_storage: Optional[LocalWorkspaceStorage] = None
-_gcs_storages: dict[int, GCSWorkspaceStorage] = {}
+# Global storage backend instance
+_workspace_storage: Optional[WorkspaceStorageBackend] = None
 _storage_lock = asyncio.Lock()
 
 
 async def get_workspace_storage() -> WorkspaceStorageBackend:
-    """Return a workspace storage backend for the **current** event loop.
-
-    * Local storage → single shared instance (no event-loop affinity).
-    * GCS storage   → one instance per event loop to avoid cross-loop
-      ``aiohttp`` errors.
     """
-    global _local_storage
+    Get the workspace storage backend instance.
 
-    config = Config()
+    Uses GCS if media_gcs_bucket_name is configured, otherwise uses local storage.
+    """
+    global _workspace_storage
 
-    # --- Local storage (shared) ---
-    if not config.media_gcs_bucket_name:
-        if _local_storage is None:
-            storage_dir = (
-                config.workspace_storage_dir if config.workspace_storage_dir else None
-            )
-            logger.info(f"Using local workspace storage: {storage_dir or 'default'}")
-            _local_storage = LocalWorkspaceStorage(storage_dir)
-        return _local_storage
+    if _workspace_storage is None:
+        async with _storage_lock:
+            if _workspace_storage is None:
+                config = Config()
 
-    # --- GCS storage (per event loop) ---
-    loop_id = id(asyncio.get_running_loop())
-    if loop_id not in _gcs_storages:
-        logger.info(
-            f"Creating GCS workspace storage for loop {loop_id}: "
-            f"{config.media_gcs_bucket_name}"
-        )
-        _gcs_storages[loop_id] = GCSWorkspaceStorage(config.media_gcs_bucket_name)
-    return _gcs_storages[loop_id]
+                if config.media_gcs_bucket_name:
+                    logger.info(
+                        f"Using GCS workspace storage: {config.media_gcs_bucket_name}"
+                    )
+                    _workspace_storage = GCSWorkspaceStorage(
+                        config.media_gcs_bucket_name
+                    )
+                else:
+                    storage_dir = (
+                        config.workspace_storage_dir
+                        if config.workspace_storage_dir
+                        else None
+                    )
+                    logger.info(
+                        f"Using local workspace storage: {storage_dir or 'default'}"
+                    )
+                    _workspace_storage = LocalWorkspaceStorage(storage_dir)
+
+    return _workspace_storage
 
 
 async def shutdown_workspace_storage() -> None:
-    """Shut down workspace storage for the **current** event loop.
-
-    Closes the ``aiohttp`` session owned by the current loop's GCS instance.
-    Each worker thread should call this on its own loop before the loop is
-    destroyed.  The REST API lifespan hook calls it for the main server loop.
     """
-    global _local_storage
+    Properly shutdown the global workspace storage backend.
 
-    loop_id = id(asyncio.get_running_loop())
-    storage = _gcs_storages.pop(loop_id, None)
-    if storage is not None:
-        await storage.close()
+    Closes aiohttp sessions and other resources for GCS backend.
+    Should be called during application shutdown.
+    """
+    global _workspace_storage
 
-    # Clear local storage only when the last GCS instance is gone
-    # (i.e. full shutdown, not just a single worker stopping).
-    if not _gcs_storages:
-        _local_storage = None
+    if _workspace_storage is not None:
+        async with _storage_lock:
+            if _workspace_storage is not None:
+                if isinstance(_workspace_storage, GCSWorkspaceStorage):
+                    await _workspace_storage.close()
+                _workspace_storage = None
 
 
 def compute_file_checksum(content: bytes) -> str:

autogpt_platform/frontend/src/app/(platform)/build/components/FlowEditor/nodes/CustomNode/components/NodeAdvancedToggle.tsx

@@ -1,39 +1,21 @@
 import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
-import { Button } from "@/components/atoms/Button/Button";
+import { Switch } from "@/components/atoms/Switch/Switch";
 import { Text } from "@/components/atoms/Text/Text";
-import { CaretDownIcon } from "@phosphor-icons/react";
 
-type Props = {
-  nodeId: string;
-};
-
-export function NodeAdvancedToggle({ nodeId }: Props) {
+export const NodeAdvancedToggle = ({ nodeId }: { nodeId: string }) => {
   const showAdvanced = useNodeStore(
     (state) => state.nodeAdvancedStates[nodeId] || false,
   );
   const setShowAdvanced = useNodeStore((state) => state.setShowAdvanced);
   return (
-    <div className="flex items-center justify-start gap-2 bg-white px-5 pb-3.5">
-      <Button
-        variant="ghost"
-        className="h-fit min-w-0 p-0 hover:border-transparent hover:bg-transparent"
-        onClick={() => setShowAdvanced(nodeId, !showAdvanced)}
-        aria-expanded={showAdvanced}
-      >
-        <Text
-          variant="body"
-          as="span"
-          className="flex items-center gap-2 !font-semibold text-slate-700"
-        >
-          Advanced{" "}
-          <CaretDownIcon
-            size={16}
-            weight="bold"
-            className={`transition-transform ${showAdvanced ? "rotate-180" : ""}`}
-            aria-hidden
-          />
-        </Text>
-      </Button>
+    <div className="flex items-center justify-between gap-2 rounded-b-xlarge border-t border-zinc-200 bg-white px-5 py-3.5">
+      <Text variant="body" className="font-medium text-slate-700">
+        Advanced
+      </Text>
+      <Switch
+        onCheckedChange={(checked) => setShowAdvanced(nodeId, checked)}
+        checked={showAdvanced}
+      />
     </div>
   );
-}
+};

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

@@ -1,695 +1,63 @@
 "use client";
 
 import { ToolUIPart } from "ai";
-import {
-  CheckCircleIcon,
-  CircleDashedIcon,
-  CircleIcon,
-  FileIcon,
-  FilesIcon,
-  GearIcon,
-  GlobeIcon,
-  ListChecksIcon,
-  MagnifyingGlassIcon,
-  PencilSimpleIcon,
-  TerminalIcon,
-  TrashIcon,
-  WarningDiamondIcon,
-} from "@phosphor-icons/react";
+import { GearIcon } from "@phosphor-icons/react";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import {
-  ContentCodeBlock,
-  ContentMessage,
-} from "../../components/ToolAccordion/AccordionContent";
-import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 
 interface Props {
   part: ToolUIPart;
 }
 
-/* ------------------------------------------------------------------ */
-/*  Tool name helpers                                                  */
-/* ------------------------------------------------------------------ */
-
 function extractToolName(part: ToolUIPart): string {
+  // ToolUIPart.type is "tool-{name}", extract the name portion.
   return part.type.replace(/^tool-/, "");
 }
 
 function formatToolName(name: string): string {
+  // "search_docs" → "Search docs", "Read" → "Read"
   return name.replace(/_/g, " ").replace(/^\w/, (c) => c.toUpperCase());
 }
 
-/* ------------------------------------------------------------------ */
-/*  Tool categorization                                                */
-/* ------------------------------------------------------------------ */
-
-type ToolCategory =
-  | "bash"
-  | "web"
-  | "file-read"
-  | "file-write"
-  | "file-delete"
-  | "file-list"
-  | "search"
-  | "edit"
-  | "todo"
-  | "other";
-
-function getToolCategory(toolName: string): ToolCategory {
-  switch (toolName) {
-    case "bash_exec":
-      return "bash";
-    case "web_fetch":
-    case "WebSearch":
-    case "WebFetch":
-      return "web";
-    case "read_workspace_file":
-    case "Read":
-      return "file-read";
-    case "write_workspace_file":
-    case "Write":
-      return "file-write";
-    case "delete_workspace_file":
-      return "file-delete";
-    case "list_workspace_files":
-    case "Glob":
-      return "file-list";
-    case "Grep":
-      return "search";
-    case "Edit":
-      return "edit";
-    case "TodoWrite":
-      return "todo";
-    default:
-      return "other";
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Tool icon                                                          */
-/* ------------------------------------------------------------------ */
-
-function ToolIcon({
-  category,
-  isStreaming,
-  isError,
-}: {
-  category: ToolCategory;
-  isStreaming: boolean;
-  isError: boolean;
-}) {
-  if (isError) {
-    return (
-      <WarningDiamondIcon size={14} weight="regular" className="text-red-500" />
-    );
-  }
-  if (isStreaming) {
-    return <OrbitLoader size={20} />;
-  }
-
-  const iconClass = "text-neutral-400";
-  switch (category) {
-    case "bash":
-      return <TerminalIcon size={14} weight="regular" className={iconClass} />;
-    case "web":
-      return <GlobeIcon size={14} weight="regular" className={iconClass} />;
-    case "file-read":
-      return <FileIcon size={14} weight="regular" className={iconClass} />;
-    case "file-write":
-      return <FileIcon size={14} weight="regular" className={iconClass} />;
-    case "file-delete":
-      return <TrashIcon size={14} weight="regular" className={iconClass} />;
-    case "file-list":
-      return <FilesIcon size={14} weight="regular" className={iconClass} />;
-    case "search":
-      return (
-        <MagnifyingGlassIcon size={14} weight="regular" className={iconClass} />
-      );
-    case "edit":
-      return (
-        <PencilSimpleIcon size={14} weight="regular" className={iconClass} />
-      );
-    case "todo":
-      return (
-        <ListChecksIcon size={14} weight="regular" className={iconClass} />
-      );
-    default:
-      return <GearIcon size={14} weight="regular" className={iconClass} />;
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Accordion icon (larger, for the accordion header)                  */
-/* ------------------------------------------------------------------ */
-
-function AccordionIcon({ category }: { category: ToolCategory }) {
-  switch (category) {
-    case "bash":
-      return <TerminalIcon size={32} weight="light" />;
-    case "web":
-      return <GlobeIcon size={32} weight="light" />;
-    case "file-read":
-    case "file-write":
-      return <FileIcon size={32} weight="light" />;
-    case "file-delete":
-      return <TrashIcon size={32} weight="light" />;
-    case "file-list":
-      return <FilesIcon size={32} weight="light" />;
-    case "search":
-      return <MagnifyingGlassIcon size={32} weight="light" />;
-    case "edit":
-      return <PencilSimpleIcon size={32} weight="light" />;
-    case "todo":
-      return <ListChecksIcon size={32} weight="light" />;
-    default:
-      return <GearIcon size={32} weight="light" />;
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Input extraction                                                   */
-/* ------------------------------------------------------------------ */
-
-function getInputSummary(toolName: string, input: unknown): string | null {
-  if (!input || typeof input !== "object") return null;
-  const inp = input as Record<string, unknown>;
-
-  switch (toolName) {
-    case "bash_exec":
-      return typeof inp.command === "string" ? inp.command : null;
-    case "web_fetch":
-    case "WebFetch":
-      return typeof inp.url === "string" ? inp.url : null;
-    case "WebSearch":
-      return typeof inp.query === "string" ? inp.query : null;
-    case "read_workspace_file":
-    case "Read":
-      return (
-        (typeof inp.file_path === "string" ? inp.file_path : null) ??
-        (typeof inp.path === "string" ? inp.path : null)
-      );
-    case "write_workspace_file":
-    case "Write":
-      return (
-        (typeof inp.file_path === "string" ? inp.file_path : null) ??
-        (typeof inp.path === "string" ? inp.path : null)
-      );
-    case "delete_workspace_file":
-      return typeof inp.file_path === "string" ? inp.file_path : null;
-    case "Glob":
-      return typeof inp.pattern === "string" ? inp.pattern : null;
-    case "Grep":
-      return typeof inp.pattern === "string" ? inp.pattern : null;
-    case "Edit":
-      return typeof inp.file_path === "string" ? inp.file_path : null;
-    case "TodoWrite": {
-      // Extract the in-progress task name for the status line
-      const todos = Array.isArray(inp.todos) ? inp.todos : [];
-      const active = todos.find(
-        (t: Record<string, unknown>) => t.status === "in_progress",
-      );
-      if (active && typeof active.activeForm === "string")
-        return active.activeForm;
-      if (active && typeof active.content === "string") return active.content;
-      return null;
-    }
-    default:
-      return null;
-  }
-}
-
-function truncate(text: string, maxLen: number): string {
-  if (text.length <= maxLen) return text;
-  return text.slice(0, maxLen).trimEnd() + "…";
-}
-
-/* ------------------------------------------------------------------ */
-/*  Animation text                                                     */
-/* ------------------------------------------------------------------ */
-
-function getAnimationText(part: ToolUIPart, category: ToolCategory): string {
-  const toolName = extractToolName(part);
-  const summary = getInputSummary(toolName, part.input);
-  const shortSummary = summary ? truncate(summary, 60) : null;
+function getAnimationText(part: ToolUIPart): string {
+  const label = formatToolName(extractToolName(part));
 
   switch (part.state) {
     case "input-streaming":
-    case "input-available": {
-      switch (category) {
-        case "bash":
-          return shortSummary ? `Running: ${shortSummary}` : "Running command…";
-        case "web":
-          if (toolName === "WebSearch") {
-            return shortSummary
-              ? `Searching "${shortSummary}"`
-              : "Searching the web…";
-          }
-          return shortSummary
-            ? `Fetching ${shortSummary}`
-            : "Fetching web content…";
-        case "file-read":
-          return shortSummary ? `Reading ${shortSummary}` : "Reading file…";
-        case "file-write":
-          return shortSummary ? `Writing ${shortSummary}` : "Writing file…";
-        case "file-delete":
-          return shortSummary ? `Deleting ${shortSummary}` : "Deleting file…";
-        case "file-list":
-          return shortSummary ? `Listing ${shortSummary}` : "Listing files…";
-        case "search":
-          return shortSummary
-            ? `Searching for "${shortSummary}"`
-            : "Searching…";
-        case "edit":
-          return shortSummary ? `Editing ${shortSummary}` : "Editing file…";
-        case "todo":
-          return shortSummary ? `${shortSummary}` : "Updating task list…";
-        default:
-          return `Running ${formatToolName(toolName)}…`;
-      }
-    }
-    case "output-available": {
-      switch (category) {
-        case "bash": {
-          const exitCode = getExitCode(part.output);
-          if (exitCode !== null && exitCode !== 0) {
-            return `Command exited with code ${exitCode}`;
-          }
-          return shortSummary ? `Ran: ${shortSummary}` : "Command completed";
-        }
-        case "web":
-          if (toolName === "WebSearch") {
-            return shortSummary
-              ? `Searched "${shortSummary}"`
-              : "Web search completed";
-          }
-          return shortSummary
-            ? `Fetched ${shortSummary}`
-            : "Fetched web content";
-        case "file-read":
-          return shortSummary ? `Read ${shortSummary}` : "File read completed";
-        case "file-write":
-          return shortSummary ? `Wrote ${shortSummary}` : "File written";
-        case "file-delete":
-          return shortSummary ? `Deleted ${shortSummary}` : "File deleted";
-        case "file-list":
-          return "Listed files";
-        case "search":
-          return shortSummary
-            ? `Searched for "${shortSummary}"`
-            : "Search completed";
-        case "edit":
-          return shortSummary ? `Edited ${shortSummary}` : "Edit completed";
-        case "todo":
-          return "Updated task list";
-        default:
-          return `${formatToolName(toolName)} completed`;
-      }
-    }
-    case "output-error": {
-      switch (category) {
-        case "bash":
-          return "Command failed";
-        case "web":
-          return toolName === "WebSearch" ? "Search failed" : "Fetch failed";
-        default:
-          return `${formatToolName(toolName)} failed`;
-      }
-    }
+    case "input-available":
+      return `Running ${label}…`;
+    case "output-available":
+      return `${label} completed`;
+    case "output-error":
+      return `${label} failed`;
     default:
-      return `Running ${formatToolName(toolName)}…`;
+      return `Running ${label}…`;
   }
 }
 
-/* ------------------------------------------------------------------ */
-/*  Output parsing helpers                                             */
-/* ------------------------------------------------------------------ */
-
-function parseOutput(output: unknown): Record<string, unknown> | null {
-  if (!output) return null;
-  if (typeof output === "object") return output as Record<string, unknown>;
-  if (typeof output === "string") {
-    const trimmed = output.trim();
-    if (!trimmed) return null;
-    try {
-      const parsed = JSON.parse(trimmed);
-      if (typeof parsed === "object" && parsed !== null) return parsed;
-    } catch {
-      // Return as a message wrapper for plain text output
-      return { _raw: trimmed };
-    }
-  }
-  return null;
-}
-
-/**
- * Extract text from MCP-style content blocks.
- * SDK built-in tools (WebSearch, etc.) may return `{content: [{type:"text", text:"..."}]}`.
- */
-function extractMcpText(output: Record<string, unknown>): string | null {
-  if (Array.isArray(output.content)) {
-    const texts = (output.content as Array<Record<string, unknown>>)
-      .filter((b) => b.type === "text" && typeof b.text === "string")
-      .map((b) => b.text as string);
-    if (texts.length > 0) return texts.join("\n");
-  }
-  return null;
-}
-
-function getExitCode(output: unknown): number | null {
-  const parsed = parseOutput(output);
-  if (!parsed) return null;
-  if (typeof parsed.exit_code === "number") return parsed.exit_code;
-  return null;
-}
-
-function getStringField(
-  obj: Record<string, unknown>,
-  ...keys: string[]
-): string | null {
-  for (const key of keys) {
-    if (typeof obj[key] === "string" && obj[key].length > 0)
-      return obj[key] as string;
-  }
-  return null;
-}
-
-/* ------------------------------------------------------------------ */
-/*  Accordion content per tool category                                */
-/* ------------------------------------------------------------------ */
-
-interface AccordionData {
-  title: string;
-  description?: string;
-  content: React.ReactNode;
-}
-
-function getBashAccordionData(
-  input: unknown,
-  output: Record<string, unknown>,
-): AccordionData {
-  const inp = (input && typeof input === "object" ? input : {}) as Record<
-    string,
-    unknown
-  >;
-  const command = typeof inp.command === "string" ? inp.command : "Command";
-
-  const stdout = getStringField(output, "stdout");
-  const stderr = getStringField(output, "stderr");
-  const exitCode =
-    typeof output.exit_code === "number" ? output.exit_code : null;
-  const timedOut = output.timed_out === true;
-  const message = getStringField(output, "message");
-
-  const title = timedOut
-    ? "Command timed out"
-    : exitCode !== null && exitCode !== 0
-      ? `Command failed (exit ${exitCode})`
-      : "Command output";
-
-  return {
-    title,
-    description: truncate(command, 80),
-    content: (
-      <div className="space-y-2">
-        {stdout && (
-          <div>
-            <p className="mb-1 text-xs font-medium text-slate-500">stdout</p>
-            <ContentCodeBlock>{truncate(stdout, 2000)}</ContentCodeBlock>
-          </div>
-        )}
-        {stderr && (
-          <div>
-            <p className="mb-1 text-xs font-medium text-slate-500">stderr</p>
-            <ContentCodeBlock>{truncate(stderr, 1000)}</ContentCodeBlock>
-          </div>
-        )}
-        {!stdout && !stderr && message && (
-          <ContentMessage>{message}</ContentMessage>
-        )}
-      </div>
-    ),
-  };
-}
-
-function getWebAccordionData(
-  input: unknown,
-  output: Record<string, unknown>,
-): AccordionData {
-  const inp = (input && typeof input === "object" ? input : {}) as Record<
-    string,
-    unknown
-  >;
-  const url =
-    getStringField(inp as Record<string, unknown>, "url", "query") ??
-    "Web content";
-
-  // Try direct string fields first, then MCP content blocks, then raw JSON
-  let content = getStringField(output, "content", "text", "_raw");
-  if (!content) content = extractMcpText(output);
-  if (!content) {
-    // Fallback: render the raw JSON so the accordion isn't empty
-    try {
-      const raw = JSON.stringify(output, null, 2);
-      if (raw !== "{}") content = raw;
-    } catch {
-      /* empty */
-    }
-  }
-
-  const statusCode =
-    typeof output.status_code === "number" ? output.status_code : null;
-  const message = getStringField(output, "message");
-
-  return {
-    title: statusCode ? `Response (${statusCode})` : "Search results",
-    description: truncate(url, 80),
-    content: content ? (
-      <ContentCodeBlock>{truncate(content, 2000)}</ContentCodeBlock>
-    ) : message ? (
-      <ContentMessage>{message}</ContentMessage>
-    ) : null,
-  };
-}
-
-function getFileAccordionData(
-  input: unknown,
-  output: Record<string, unknown>,
-): AccordionData {
-  const inp = (input && typeof input === "object" ? input : {}) as Record<
-    string,
-    unknown
-  >;
-  const filePath =
-    getStringField(
-      inp as Record<string, unknown>,
-      "file_path",
-      "path",
-      "pattern",
-    ) ?? "File";
-  const content = getStringField(output, "content", "text", "_raw");
-  const message = getStringField(output, "message");
-  // For Glob/list results, try to show file list
-  const files = Array.isArray(output.files) ? (output.files as string[]) : null;
-
-  return {
-    title: message ?? "File output",
-    description: truncate(filePath, 80),
-    content: (
-      <div className="space-y-2">
-        {content && (
-          <ContentCodeBlock>{truncate(content, 2000)}</ContentCodeBlock>
-        )}
-        {files && files.length > 0 && (
-          <ContentCodeBlock>{files.join("\n")}</ContentCodeBlock>
-        )}
-        {!content && !files && message && (
-          <ContentMessage>{message}</ContentMessage>
-        )}
-      </div>
-    ),
-  };
-}
-
-interface TodoItem {
-  content: string;
-  status: "pending" | "in_progress" | "completed";
-  activeForm?: string;
-}
-
-function getTodoAccordionData(input: unknown): AccordionData {
-  const inp = (input && typeof input === "object" ? input : {}) as Record<
-    string,
-    unknown
-  >;
-  const todos: TodoItem[] = Array.isArray(inp.todos)
-    ? inp.todos.filter(
-        (t: unknown): t is TodoItem =>
-          typeof t === "object" &&
-          t !== null &&
-          typeof (t as TodoItem).content === "string",
-      )
-    : [];
-
-  const completed = todos.filter((t) => t.status === "completed").length;
-  const total = todos.length;
-
-  return {
-    title: "Task list",
-    description: `${completed}/${total} completed`,
-    content: (
-      <div className="space-y-1 py-1">
-        {todos.map((todo, i) => (
-          <div key={i} className="flex items-start gap-2 text-xs">
-            <span className="mt-0.5 flex-shrink-0">
-              {todo.status === "completed" ? (
-                <CheckCircleIcon
-                  size={14}
-                  weight="fill"
-                  className="text-green-500"
-                />
-              ) : todo.status === "in_progress" ? (
-                <CircleDashedIcon
-                  size={14}
-                  weight="bold"
-                  className="text-blue-500"
-                />
-              ) : (
-                <CircleIcon
-                  size={14}
-                  weight="regular"
-                  className="text-neutral-400"
-                />
-              )}
-            </span>
-            <span
-              className={
-                todo.status === "completed"
-                  ? "text-muted-foreground line-through"
-                  : todo.status === "in_progress"
-                    ? "font-medium text-foreground"
-                    : "text-muted-foreground"
-              }
-            >
-              {todo.content}
-            </span>
-          </div>
-        ))}
-      </div>
-    ),
-  };
-}
-
-function getDefaultAccordionData(
-  output: Record<string, unknown>,
-): AccordionData {
-  const message = getStringField(output, "message");
-  const raw = output._raw;
-  const mcpText = extractMcpText(output);
-
-  let displayContent: string;
-  if (typeof raw === "string") {
-    displayContent = raw;
-  } else if (mcpText) {
-    displayContent = mcpText;
-  } else if (message) {
-    displayContent = message;
-  } else {
-    try {
-      displayContent = JSON.stringify(output, null, 2);
-    } catch {
-      displayContent = String(output);
-    }
-  }
-
-  return {
-    title: "Output",
-    description: message ?? undefined,
-    content: (
-      <ContentCodeBlock>{truncate(displayContent, 2000)}</ContentCodeBlock>
-    ),
-  };
-}
-
-function getAccordionData(
-  category: ToolCategory,
-  input: unknown,
-  output: Record<string, unknown>,
-): AccordionData {
-  switch (category) {
-    case "bash":
-      return getBashAccordionData(input, output);
-    case "web":
-      return getWebAccordionData(input, output);
-    case "file-read":
-    case "file-write":
-    case "file-delete":
-    case "file-list":
-    case "search":
-    case "edit":
-      return getFileAccordionData(input, output);
-    case "todo":
-      return getTodoAccordionData(input);
-    default:
-      return getDefaultAccordionData(output);
-  }
-}
-
-/* ------------------------------------------------------------------ */
-/*  Component                                                          */
-/* ------------------------------------------------------------------ */
-
 export function GenericTool({ part }: Props) {
-  const toolName = extractToolName(part);
-  const category = getToolCategory(toolName);
   const isStreaming =
     part.state === "input-streaming" || part.state === "input-available";
   const isError = part.state === "output-error";
-  const text = getAnimationText(part, category);
-
-  const output = parseOutput(part.output);
-  const hasOutput =
-    part.state === "output-available" &&
-    !!output &&
-    Object.keys(output).length > 0;
-  const hasError = isError && !!output;
-
-  // TodoWrite: always show accordion from input (the todo list lives in input)
-  const hasTodoInput =
-    category === "todo" &&
-    part.input &&
-    typeof part.input === "object" &&
-    Array.isArray((part.input as Record<string, unknown>).todos);
-
-  const showAccordion = hasOutput || hasError || hasTodoInput;
-  const accordionData = showAccordion
-    ? getAccordionData(category, part.input, output ?? {})
-    : null;
 
   return (
     <div className="py-2">
       <div className="flex items-center gap-2 text-sm text-muted-foreground">
-        <ToolIcon
-          category={category}
-          isStreaming={isStreaming}
-          isError={isError}
+        <GearIcon
+          size={14}
+          weight="regular"
+          className={
+            isError
+              ? "text-red-500"
+              : isStreaming
+                ? "animate-spin text-neutral-500"
+                : "text-neutral-400"
+          }
         />
         <MorphingTextAnimation
-          text={text}
+          text={getAnimationText(part)}
           className={isError ? "text-red-500" : undefined}
         />
       </div>
-
-      {showAccordion && accordionData ? (
-        <ToolAccordion
-          icon={<AccordionIcon category={category} />}
-          title={accordionData.title}
-          description={accordionData.description}
-          titleClassName={isError ? "text-red-500" : undefined}
-        >
-          {accordionData.content}
-        </ToolAccordion>
-      ) : null}
     </div>
   );
 }

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

@@ -80,12 +80,6 @@ export function useCopilotPage() {
                 },
               };
             },
-            // Resume: GET goes to the same URL as POST (backend uses
-            // method to distinguish).  Override the default formula which
-            // would append /{chatId}/stream to the existing path.
-            prepareReconnectToStreamRequest: () => ({
-              api: `/api/chat/sessions/${sessionId}/stream`,
-            }),
           })
         : null,
     [sessionId],
@@ -94,7 +88,6 @@ export function useCopilotPage() {
   const { messages, sendMessage, stop, status, error, setMessages } = useChat({
     id: sessionId ?? undefined,
     transport: transport ?? undefined,
-    resume: true,
   });
 
   // Abort the stream if the backend doesn't start sending data within 12s.