feat(copilot): stream resume, transcript staleness detection, WebSearch display

- Enable `resume: true` on `useChat` with `prepareReconnectToStreamRequest`
  so page refresh reconnects to active backend streams via Redis replay
- Add `message_count` watermark + timestamp metadata to transcript uploads;
  on download, detect staleness and compress only the gap instead of the
  full history (hybrid: transcript via --resume + compressed missed turns)
- Fix WebSearch accordion showing empty by extracting text from MCP-style
  content blocks (`extractMcpText`) with raw JSON fallback
- Revert over-blocking: only `AskUserQuestion` added to SDK_DISALLOWED_TOOLS
  (removed EnterPlanMode, ExitPlanMode, Skill, NotebookEdit)
- Add defensive TodoItem filter per coderabbit review
- Fix service_test for TranscriptDownload return type change

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

@@ -50,7 +50,6 @@ from backend.copilot.tools.models import (
     OperationPendingResponse,
     OperationStartedResponse,
     SetupRequirementsResponse,
-    SuggestedGoalResponse,
     UnderstandingUpdatedResponse,
 )
 from backend.copilot.tracking import track_user_message
@@ -985,7 +984,6 @@ ToolResponseUnion = (
     | AgentPreviewResponse
     | AgentSavedResponse
     | ClarificationNeededResponse
-    | SuggestedGoalResponse
     | BlockListResponse
     | BlockDetailsResponse
     | BlockOutputResponse

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

@@ -4,7 +4,6 @@ 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
@@ -164,21 +163,23 @@ class CoPilotExecutor(AppProcess):
                 self._cancel_thread, self.cancel_client, "[cleanup][cancel]"
             )
 
-        # Shutdown executor
+        # Clean up worker threads (closes per-loop workspace storage sessions)
         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

@@ -60,6 +60,18 @@ 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 ============ #
 
 
@@ -98,6 +110,28 @@ 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

@@ -53,6 +53,7 @@ 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
 
@@ -74,6 +75,10 @@ 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:
@@ -111,6 +116,8 @@ 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, {})
@@ -132,6 +139,37 @@ 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.
@@ -140,6 +178,7 @@ 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:
@@ -149,7 +188,7 @@ class SDKResponseAdapter:
             if sdk_message.subtype == "success":
                 responses.append(StreamFinish())
             elif sdk_message.subtype in ("error", "error_during_execution"):
-                error_msg = getattr(sdk_message, "result", None) or "Unknown error"
+                error_msg = sdk_message.result or "Unknown error"
                 responses.append(
                     StreamError(errorText=str(error_msg), code="sdk_error")
                 )
@@ -180,6 +219,59 @@ 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."""
@@ -199,3 +291,30 @@ 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

@@ -16,6 +16,7 @@ from .tool_adapter import (
     DANGEROUS_PATTERNS,
     MCP_TOOL_PREFIX,
     WORKSPACE_SCOPED_TOOLS,
+    stash_pending_tool_output,
 )
 
 logger = logging.getLogger(__name__)
@@ -224,10 +225,25 @@ def create_security_hooks(
             tool_use_id: str | None,
             context: HookContext,
         ) -> SyncHookJSONOutput:
-            """Log successful tool executions for observability."""
+            """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.
+            """
             _ = 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

@@ -47,6 +47,7 @@ from .tool_adapter import (
     set_execution_context,
 )
 from .transcript import (
+    cleanup_cli_project_dir,
     download_transcript,
     read_transcript_file,
     upload_transcript,
@@ -86,9 +87,12 @@ _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.
-  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).
+- **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`.
 - 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.
@@ -268,48 +272,28 @@ def _make_sdk_cwd(session_id: str) -> str:
 
 
 def _cleanup_sdk_tool_results(cwd: str) -> None:
-    """Remove SDK tool-result files for a specific session working directory.
+    """Remove SDK session artifacts for a specific 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.
+    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.
 
-    Security: cwd MUST be created by _make_sdk_cwd() which sanitizes session_id.
+    Security: *cwd* MUST be created by ``_make_sdk_cwd()`` which sanitizes
+    the 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
 
-    # SDK encodes the cwd path by replacing '/' with '-'
-    encoded_cwd = normalized.replace("/", "-")
+    # Clean the CLI's project directory (transcripts + tool-results).
+    cleanup_cli_project_dir(cwd)
 
-    # 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
+    # Clean up the temp cwd directory itself.
     try:
         shutil.rmtree(normalized, ignore_errors=True)
     except OSError:
@@ -519,6 +503,7 @@ 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,
@@ -530,18 +515,20 @@ 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:
-                transcript_content = await download_transcript(user_id, session_id)
-                if transcript_content and validate_transcript(transcript_content):
+                dl = await download_transcript(user_id, session_id)
+                if dl and validate_transcript(dl.content):
                     resume_file = write_transcript_to_tempfile(
-                        transcript_content, session_id, sdk_cwd
+                        dl.content, session_id, sdk_cwd
                     )
                     if resume_file:
                         use_resume = True
-                        logger.info(
-                            f"[SDK] Using --resume with transcript "
-                            f"({len(transcript_content)} bytes)"
+                        transcript_msg_count = dl.message_count
+                        logger.debug(
+                            f"[SDK] Using --resume ({len(dl.content)}B, "
+                            f"msg_count={transcript_msg_count})"
                         )
 
             sdk_options_kwargs: dict[str, Any] = {
@@ -582,11 +569,35 @@ 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
-                if not use_resume and len(session.messages) > 1:
+                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:
                     logger.warning(
                         f"[SDK] Using compression fallback for session "
-                        f"{session_id} ({len(session.messages)} messages) — "
+                        f"{session_id} ({current_msg_count} messages) — "
                         f"no transcript available for --resume"
                     )
                     compressed = await _compress_conversation_history(session)
@@ -597,10 +608,10 @@ async def stream_chat_completion_sdk(
                             f"Now, the user says:\n{current_message}"
                         )
 
-                logger.info(
-                    f"[SDK] Sending query ({len(session.messages)} msgs in session)"
+                logger.debug(
+                    f"[SDK] Sending query ({len(session.messages)} msgs, "
+                    f"resume={use_resume})"
                 )
-                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="")
@@ -681,25 +692,27 @@ async def stream_chat_completion_sdk(
                 ) and not has_appended_assistant:
                     session.messages.append(assistant_response)
 
-                # --- 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)
+            # --- 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:
                     raw_transcript = read_transcript_file(captured_transcript.path)
-                    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")
+                else:
+                    raw_transcript = None
+
+                if raw_transcript:
+                    await _try_upload_transcript(
+                        user_id,
+                        session_id,
+                        raw_transcript,
+                        message_count=len(session.messages),
+                    )
 
         except ImportError:
             raise RuntimeError(
@@ -731,14 +744,31 @@ async def stream_chat_completion_sdk(
             _cleanup_sdk_tool_results(sdk_cwd)
 
 
-async def _upload_transcript_bg(
-    user_id: str, session_id: str, raw_content: str
-) -> None:
-    """Background task to strip progress entries and upload transcript."""
+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.
+    """
     try:
-        await upload_transcript(user_id, session_id, raw_content)
+        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
     except Exception as e:
-        logger.error(f"[SDK] Failed to upload transcript for {session_id}: {e}")
+        logger.error(
+            f"[SDK] Failed to upload transcript for {session_id}: {e}",
+            exc_info=True,
+        )
+        return False
 
 
 async def _update_title_async(

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

@@ -103,6 +103,31 @@ 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,
@@ -127,12 +152,54 @@ 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": [{"type": "text", "text": text}],
+        "content": content_blocks,
         "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": [
@@ -311,14 +378,29 @@ 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.
-_SDK_BUILTIN_TOOLS = ["Read", "Write", "Edit", "Glob", "Grep", "Task", "WebSearch"]
+# TodoWrite manages the task checklist shown in the UI — no security concern.
+_SDK_BUILTIN_TOOLS = [
+    "Read",
+    "Write",
+    "Edit",
+    "Glob",
+    "Grep",
+    "Task",
+    "WebSearch",
+    "TodoWrite",
+]
 
 # 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.
-SDK_DISALLOWED_TOOLS = ["Bash", "WebFetch"]
+# AskUserQuestion: interactive CLI tool — no terminal in copilot context.
+SDK_DISALLOWED_TOOLS = [
+    "Bash",
+    "WebFetch",
+    "AskUserQuestion",
+]
 
 # 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

@@ -14,6 +14,8 @@ import json
 import logging
 import os
 import re
+import time
+from dataclasses import dataclass
 
 logger = logging.getLogger(__name__)
 
@@ -31,6 +33,16 @@ 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"
 
@@ -119,23 +131,19 @@ 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.info(
+        logger.debug(
             f"[Transcript] Read {len(lines)} lines, "
             f"{len(content)} bytes from {transcript_path}"
         )
@@ -160,6 +168,39 @@ 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,
@@ -191,7 +232,7 @@ def write_transcript_to_tempfile(
         with open(jsonl_path, "w") as f:
             f.write(transcript_content)
 
-        logger.info(f"[Transcript] Wrote resume file: {jsonl_path}")
+        logger.debug(f"[Transcript] Wrote resume file: {jsonl_path}")
         return jsonl_path
 
     except OSError as e:
@@ -248,6 +289,15 @@ 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.
 
@@ -268,21 +318,30 @@ 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) -> None:
+async def upload_transcript(
+    user_id: str,
+    session_id: str,
+    content: str,
+    message_count: int = 0,
+) -> 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 is not a valid "
-            f"transcript for session {session_id}"
+            f"[Transcript] Skipping upload — stripped content not valid "
+            f"for session {session_id}"
         )
         return
 
@@ -296,10 +355,9 @@ async def upload_transcript(user_id: str, session_id: str, content: str) -> None
     try:
         existing = await storage.retrieve(path)
         if len(existing) >= new_size:
-            logger.info(
-                f"[Transcript] Skipping upload — existing transcript "
-                f"({len(existing)}B) >= new ({new_size}B) for session "
-                f"{session_id}"
+            logger.debug(
+                f"[Transcript] Skipping upload — existing ({len(existing)}B) "
+                f">= new ({new_size}B) for session {session_id}"
             )
             return
     except (FileNotFoundError, Exception):
@@ -311,16 +369,32 @@ async def upload_transcript(user_id: str, session_id: str, content: str) -> None
         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} bytes "
-        f"(stripped from {len(content)}) for session {session_id}"
+        f"[Transcript] Uploaded {new_size}B "
+        f"(stripped from {len(content)}B, msg_count={message_count}) "
+        f"for session {session_id}"
     )
 
 
-async def download_transcript(user_id: str, session_id: str) -> str | None:
-    """Download transcript from bucket storage.
+async def download_transcript(
+    user_id: str, session_id: str
+) -> TranscriptDownload | None:
+    """Download transcript and metadata from bucket storage.
 
-    Returns the JSONL content string, or ``None`` if not found.
+    Returns a ``TranscriptDownload`` with the JSONL content and the
+    ``message_count`` watermark from the upload, or ``None`` if not found.
     """
     from backend.util.workspace_storage import get_workspace_storage
 
@@ -330,10 +404,6 @@ async def download_transcript(user_id: str, session_id: str) -> str | None:
     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
@@ -341,6 +411,36 @@ async def download_transcript(user_id: str, session_id: str) -> str | None:
         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

@@ -118,8 +118,6 @@ Adapt flexibly to the conversation context. Not every interaction requires all s
    - Find reusable components with `find_block`
    - Create custom solutions with `create_agent` if nothing suitable exists
    - Modify existing library agents with `edit_agent`
-   - **When `create_agent` returns `suggested_goal`**: Present the suggestion to the user and ask "Would you like me to proceed with this refined goal?" If they accept, call `create_agent` again with the suggested goal.
-   - **When `create_agent` returns `clarifying_questions`**: After the user answers, call `create_agent` again with the original description AND the answers in the `context` parameter.
 
 5. **Execute**: Run automations immediately, schedule them, or set up webhooks using `run_agent`. Test specific components with `run_block`.
 
@@ -166,11 +164,6 @@ Adapt flexibly to the conversation context. Not every interaction requires all s
 - Use `add_understanding` to capture valuable business context
 - When tool calls fail, try alternative approaches
 
-**Handle Feedback Loops:**
-- When a tool returns a suggested alternative (like a refined goal), present it clearly and ask the user for confirmation before proceeding
-- When clarifying questions are answered, immediately re-call the tool with the accumulated context
-- Don't ask redundant questions if the user has already provided context in the conversation
-
 ## CRITICAL REMINDER
 
 You are NOT a chatbot. You are NOT documentation. You are a partner who helps busy business owners get value quickly by showing proof through working automations. Bias toward action over explanation."""
@@ -394,7 +387,7 @@ async def stream_chat_completion(
     if user_id:
         log_meta["user_id"] = user_id
 
-    logger.info(
+    logger.debug(
         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={
@@ -411,7 +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.info(
+        logger.debug(
             f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
             f"n_messages={len(session.messages) if session else 0}",
             extra={
@@ -423,7 +416,7 @@ async def stream_chat_completion(
             },
         )
     else:
-        logger.info(
+        logger.debug(
             f"[TIMING] Using provided session, messages={len(session.messages)}",
             extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
         )
@@ -457,7 +450,7 @@ async def stream_chat_completion(
                 message_length=len(message),
             )
             posthog_time = (time.monotonic() - posthog_start) * 1000
-            logger.info(
+            logger.debug(
                 f"[TIMING] track_user_message took {posthog_time:.1f}ms",
                 extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
             )
@@ -465,7 +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.info(
+    logger.debug(
         f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
     )
@@ -510,7 +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.info(
+    logger.debug(
         f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
     )
@@ -544,7 +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.info(
+    logger.debug(
         f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
         extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
     )
@@ -555,7 +548,7 @@ async def stream_chat_completion(
     yield StreamStartStep()
 
     try:
-        logger.info(
+        logger.debug(
             "[TIMING] Calling _stream_chat_chunks",
             extra={"json_fields": log_meta},
         )
@@ -995,7 +988,7 @@ async def _stream_chat_chunks(
     if session.user_id:
         log_meta["user_id"] = session.user_id
 
-    logger.info(
+    logger.debug(
         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)}},
@@ -1018,7 +1011,7 @@ async def _stream_chat_chunks(
         base_url=config.base_url,
     )
     context_time = (time_module.perf_counter() - context_start) * 1000
-    logger.info(
+    logger.debug(
         f"[TIMING] _manage_context_window took {context_time:.1f}ms",
         extra={"json_fields": {**log_meta, "duration_ms": context_time}},
     )
@@ -1060,7 +1053,7 @@ async def _stream_chat_chunks(
                 retry_info = (
                     f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
                 )
-                logger.info(
+                logger.debug(
                     f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
                     extra={
                         "json_fields": {
@@ -1100,7 +1093,7 @@ async def _stream_chat_chunks(
                     extra_body=extra_body,
                 )
                 api_init_time = (time_module.perf_counter() - api_call_start) * 1000
-                logger.info(
+                logger.debug(
                     f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
                     extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
                 )
@@ -1149,7 +1142,7 @@ async def _stream_chat_chunks(
                                 ttfc = (
                                     time_module.perf_counter() - api_call_start
                                 ) * 1000
-                                logger.info(
+                                logger.debug(
                                     f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
                                     f"(since API call), n_chunks={chunk_count}",
                                     extra={
@@ -1217,7 +1210,7 @@ async def _stream_chat_chunks(
                                     )
                                     emitted_start_for_idx.add(idx)
                 stream_duration = time_module.perf_counter() - api_call_start
-                logger.info(
+                logger.debug(
                     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)}",
@@ -1251,7 +1244,7 @@ async def _stream_chat_chunks(
                         raise
 
                 total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
-                logger.info(
+                logger.debug(
                     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}},
@@ -1501,8 +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:
-                pass
+            except Exception as mark_err:
+                logger.warning(f"Failed to mark task {task_id} as failed: {mark_err}")
             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)} bytes")
+    logger.info(f"Turn 1 transcript uploaded: {len(transcript.content)} 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.info(
+    logger.debug(
         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.info(
+    logger.debug(
         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.info(
+    logger.debug(
         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.info(
+    logger.debug(
         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.info(
+            logger.debug(
                 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.info(
+    logger.debug(
         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.info(
+    logger.debug(
         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.info(
+        logger.debug(
             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.info(
+    logger.debug(
         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.info(
+    logger.debug(
         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.info(
+        logger.debug(
             "[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.info(
+        logger.debug(
             f"[TIMING] Task already {task_status}, adding StreamFinish",
             extra={"json_fields": {**log_meta, "task_status": task_status}},
         )
         await subscriber_queue.put(StreamFinish())
 
     total_time = (time.perf_counter() - start_time) * 1000
-    logger.info(
+    logger.debug(
         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.info(
+    logger.debug(
         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.info(
+                logger.debug(
                     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.info(
+                logger.debug(
                     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.info(
+                                    logger.debug(
                                         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.info(
+                                logger.debug(
                                     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.info(
+        logger.debug(
             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.info(
+        logger.debug(
             f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, "
             f"delivered={messages_delivered}, xread_count={xread_count}",
             extra={
@@ -829,10 +829,13 @@ async def get_active_task_for_session(
                             )
                             await mark_task_completed(task_id, "failed")
                             continue
-                    except (ValueError, TypeError):
-                        pass
+                    except (ValueError, TypeError) as exc:
+                        logger.warning(
+                            f"[TASK_LOOKUP] Failed to parse created_at "
+                            f"for task {task_id[:8]}...: {exc}"
+                        )
 
-                logger.info(
+                logger.debug(
                     f"[TASK_LOOKUP] Found running task {task_id[:8]}... for session {session_id[:8]}..."
                 )
 

autogpt_platform/backend/backend/copilot/tools/create_agent.py

@@ -22,7 +22,6 @@ from .models import (
     ClarificationNeededResponse,
     ClarifyingQuestion,
     ErrorResponse,
-    SuggestedGoalResponse,
     ToolResponseBase,
 )
 
@@ -187,28 +186,26 @@ class CreateAgentTool(BaseTool):
         if decomposition_result.get("type") == "unachievable_goal":
             suggested = decomposition_result.get("suggested_goal", "")
             reason = decomposition_result.get("reason", "")
-            return SuggestedGoalResponse(
+            return ErrorResponse(
                 message=(
-                    f"This goal cannot be accomplished with the available blocks. {reason}"
+                    f"This goal cannot be accomplished with the available blocks. "
+                    f"{reason} "
+                    f"Suggestion: {suggested}"
                 ),
-                suggested_goal=suggested,
-                reason=reason,
-                original_goal=description,
-                goal_type="unachievable",
+                error="unachievable_goal",
+                details={"suggested_goal": suggested, "reason": reason},
                 session_id=session_id,
             )
 
         if decomposition_result.get("type") == "vague_goal":
             suggested = decomposition_result.get("suggested_goal", "")
-            reason = decomposition_result.get(
-                "reason", "The goal needs more specific details"
-            )
-            return SuggestedGoalResponse(
-                message="The goal is too vague to create a specific workflow.",
-                suggested_goal=suggested,
-                reason=reason,
-                original_goal=description,
-                goal_type="vague",
+            return ErrorResponse(
+                message=(
+                    f"The goal is too vague to create a specific workflow. "
+                    f"Suggestion: {suggested}"
+                ),
+                error="vague_goal",
+                details={"suggested_goal": suggested},
                 session_id=session_id,
             )
 

autogpt_platform/backend/backend/copilot/tools/create_agent_test.py

@@ -1,142 +0,0 @@
-"""Tests for CreateAgentTool response types."""
-
-from unittest.mock import AsyncMock, patch
-
-import pytest
-
-from backend.copilot.tools.create_agent import CreateAgentTool
-from backend.copilot.tools.models import (
-    ClarificationNeededResponse,
-    ErrorResponse,
-    SuggestedGoalResponse,
-)
-
-from ._test_data import make_session
-
-_TEST_USER_ID = "test-user-create-agent"
-
-
-@pytest.fixture
-def tool():
-    return CreateAgentTool()
-
-
-@pytest.fixture
-def session():
-    return make_session(_TEST_USER_ID)
-
-
-@pytest.mark.asyncio
-async def test_missing_description_returns_error(tool, session):
-    """Missing description returns ErrorResponse."""
-    result = await tool._execute(user_id=_TEST_USER_ID, session=session, description="")
-    assert isinstance(result, ErrorResponse)
-    assert result.error == "Missing description parameter"
-
-
-@pytest.mark.asyncio
-async def test_vague_goal_returns_suggested_goal_response(tool, session):
-    """vague_goal decomposition result returns SuggestedGoalResponse, not ErrorResponse."""
-    vague_result = {
-        "type": "vague_goal",
-        "suggested_goal": "Monitor Twitter mentions for a specific keyword and send a daily digest email",
-    }
-
-    with (
-        patch(
-            "backend.copilot.tools.create_agent.get_all_relevant_agents_for_generation",
-            new_callable=AsyncMock,
-            return_value=[],
-        ),
-        patch(
-            "backend.copilot.tools.create_agent.decompose_goal",
-            new_callable=AsyncMock,
-            return_value=vague_result,
-        ),
-    ):
-        result = await tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            description="monitor social media",
-        )
-
-    assert isinstance(result, SuggestedGoalResponse)
-    assert result.goal_type == "vague"
-    assert result.suggested_goal == vague_result["suggested_goal"]
-    assert result.original_goal == "monitor social media"
-    assert result.reason == "The goal needs more specific details"
-    assert not isinstance(result, ErrorResponse)
-
-
-@pytest.mark.asyncio
-async def test_unachievable_goal_returns_suggested_goal_response(tool, session):
-    """unachievable_goal decomposition result returns SuggestedGoalResponse, not ErrorResponse."""
-    unachievable_result = {
-        "type": "unachievable_goal",
-        "suggested_goal": "Summarize the latest news articles on a topic and send them by email",
-        "reason": "There are no blocks for mind-reading.",
-    }
-
-    with (
-        patch(
-            "backend.copilot.tools.create_agent.get_all_relevant_agents_for_generation",
-            new_callable=AsyncMock,
-            return_value=[],
-        ),
-        patch(
-            "backend.copilot.tools.create_agent.decompose_goal",
-            new_callable=AsyncMock,
-            return_value=unachievable_result,
-        ),
-    ):
-        result = await tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            description="read my mind",
-        )
-
-    assert isinstance(result, SuggestedGoalResponse)
-    assert result.goal_type == "unachievable"
-    assert result.suggested_goal == unachievable_result["suggested_goal"]
-    assert result.original_goal == "read my mind"
-    assert result.reason == unachievable_result["reason"]
-    assert not isinstance(result, ErrorResponse)
-
-
-@pytest.mark.asyncio
-async def test_clarifying_questions_returns_clarification_needed_response(
-    tool, session
-):
-    """clarifying_questions decomposition result returns ClarificationNeededResponse."""
-    clarifying_result = {
-        "type": "clarifying_questions",
-        "questions": [
-            {
-                "question": "What platform should be monitored?",
-                "keyword": "platform",
-                "example": "Twitter, Reddit",
-            }
-        ],
-    }
-
-    with (
-        patch(
-            "backend.copilot.tools.create_agent.get_all_relevant_agents_for_generation",
-            new_callable=AsyncMock,
-            return_value=[],
-        ),
-        patch(
-            "backend.copilot.tools.create_agent.decompose_goal",
-            new_callable=AsyncMock,
-            return_value=clarifying_result,
-        ),
-    ):
-        result = await tool._execute(
-            user_id=_TEST_USER_ID,
-            session=session,
-            description="monitor social media and alert me",
-        )
-
-    assert isinstance(result, ClarificationNeededResponse)
-    assert len(result.questions) == 1
-    assert result.questions[0].keyword == "platform"

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

@@ -33,7 +33,6 @@ query SearchFeatureRequests($term: String!, $filter: IssueFilter, $first: Int) {
       id
       identifier
       title
-      description
     }
   }
 }
@@ -205,7 +204,6 @@ class SearchFeatureRequestsTool(BaseTool):
                     id=node["id"],
                     identifier=node["identifier"],
                     title=node["title"],
-                    description=node.get("description"),
                 )
                 for node in nodes
             ]
@@ -239,7 +237,11 @@ 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."
+            "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."
         )
 
     @property
@@ -249,11 +251,20 @@ class CreateFeatureRequestTool(BaseTool):
             "properties": {
                 "title": {
                     "type": "string",
-                    "description": "Title for the feature request.",
+                    "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": {
                     "type": "string",
-                    "description": "Detailed description of what the user wants and why.",
+                    "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."
+                    ),
                 },
                 "existing_issue_id": {
                     "type": "string",

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

@@ -117,13 +117,11 @@ 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

@@ -2,7 +2,7 @@
 
 from datetime import datetime
 from enum import Enum
-from typing import Any, Literal
+from typing import Any
 
 from pydantic import BaseModel, Field
 
@@ -50,8 +50,6 @@ class ResponseType(str, Enum):
     # Feature request types
     FEATURE_REQUEST_SEARCH = "feature_request_search"
     FEATURE_REQUEST_CREATED = "feature_request_created"
-    # Goal refinement
-    SUGGESTED_GOAL = "suggested_goal"
 
 
 # Base response model
@@ -298,22 +296,6 @@ class ClarificationNeededResponse(ToolResponseBase):
     questions: list[ClarifyingQuestion] = Field(default_factory=list)
 
 
-class SuggestedGoalResponse(ToolResponseBase):
-    """Response when the goal needs refinement with a suggested alternative."""
-
-    type: ResponseType = ResponseType.SUGGESTED_GOAL
-    suggested_goal: str = Field(description="The suggested alternative goal")
-    reason: str = Field(
-        default="", description="Why the original goal needs refinement"
-    )
-    original_goal: str = Field(
-        default="", description="The user's original goal for context"
-    )
-    goal_type: Literal["vague", "unachievable"] = Field(
-        default="vague", description="Type: 'vague' or 'unachievable'"
-    )
-
-
 # Documentation search models
 class DocSearchResult(BaseModel):
     """A single documentation search result."""
@@ -504,7 +486,6 @@ class FeatureRequestInfo(BaseModel):
     id: str
     identifier: str
     title: str
-    description: str | None = None
 
 
 class FeatureRequestSearchResponse(ToolResponseBase):

autogpt_platform/backend/backend/data/db_manager.py

@@ -93,7 +93,15 @@ from backend.data.user import (
     get_user_notification_preference,
     update_user_integrations,
 )
-from backend.data.workspace import get_or_create_workspace
+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.util.service import (
     AppService,
     AppServiceClient,
@@ -274,7 +282,13 @@ 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)
@@ -438,7 +452,13 @@ 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

@@ -164,21 +164,23 @@ async def create_workspace_file(
 
 async def get_workspace_file(
     file_id: str,
-    workspace_id: Optional[str] = None,
+    workspace_id: str,
 ) -> Optional[WorkspaceFile]:
     """
     Get a workspace file by ID.
 
     Args:
         file_id: The file ID
-        workspace_id: Optional workspace ID for validation
+        workspace_id: Workspace ID for scoping (required)
 
     Returns:
         WorkspaceFile instance or None
     """
-    where_clause: dict = {"id": file_id, "isDeleted": False}
-    if workspace_id:
-        where_clause["workspaceId"] = workspace_id
+    where_clause: UserWorkspaceFileWhereInput = {
+        "id": file_id,
+        "isDeleted": False,
+        "workspaceId": workspace_id,
+    }
 
     file = await UserWorkspaceFile.prisma().find_first(where=where_clause)
     return WorkspaceFile.from_db(file) if file else None
@@ -268,7 +270,7 @@ async def count_workspace_files(
     Returns:
         Number of files
     """
-    where_clause: dict = {"workspaceId": workspace_id}
+    where_clause: UserWorkspaceFileWhereInput = {"workspaceId": workspace_id}
     if not include_deleted:
         where_clause["isDeleted"] = False
 
@@ -283,7 +285,7 @@ async def count_workspace_files(
 
 async def soft_delete_workspace_file(
     file_id: str,
-    workspace_id: Optional[str] = None,
+    workspace_id: str,
 ) -> Optional[WorkspaceFile]:
     """
     Soft-delete a workspace file.
@@ -293,7 +295,7 @@ async def soft_delete_workspace_file(
 
     Args:
         file_id: The file ID
-        workspace_id: Optional workspace ID for validation
+        workspace_id: Workspace ID for scoping (required)
 
     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
+from prisma.errors import DataError, UniqueViolationError
 from pydantic import BaseModel, TypeAdapter, create_model
 
 import backend.util.exceptions as exceptions
@@ -201,6 +201,7 @@ EXCEPTION_MAPPING = {
         UnhealthyServiceError,
         HTTPClientError,
         HTTPServerError,
+        UniqueViolationError,
         *[
             ErrorType
             for _, ErrorType in inspect.getmembers(exceptions)
@@ -416,6 +417,9 @@ 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)
         )
@@ -478,6 +482,7 @@ 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

@@ -12,15 +12,8 @@ from typing import Optional
 
 from prisma.errors import UniqueViolationError
 
-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.data.db_accessors import workspace_db
+from backend.data.workspace import WorkspaceFile
 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
@@ -125,8 +118,9 @@ class WorkspaceManager:
         Raises:
             FileNotFoundError: If file doesn't exist
         """
+        db = workspace_db()
         resolved_path = self._resolve_path(path)
-        file = await get_workspace_file_by_path(self.workspace_id, resolved_path)
+        file = await db.get_workspace_file_by_path(self.workspace_id, resolved_path)
         if file is None:
             raise FileNotFoundError(f"File not found at path: {resolved_path}")
 
@@ -146,7 +140,8 @@ class WorkspaceManager:
         Raises:
             FileNotFoundError: If file doesn't exist
         """
-        file = await get_workspace_file(file_id, self.workspace_id)
+        db = workspace_db()
+        file = await db.get_workspace_file(file_id, self.workspace_id)
         if file is None:
             raise FileNotFoundError(f"File not found: {file_id}")
 
@@ -204,8 +199,10 @@ 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 get_workspace_file_by_path(self.workspace_id, path)
+            existing = await db.get_workspace_file_by_path(self.workspace_id, path)
             if existing is not None:
                 raise ValueError(f"File already exists at path: {path}")
 
@@ -232,7 +229,7 @@ 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 create_workspace_file(
+            file = await db.create_workspace_file(
                 workspace_id=self.workspace_id,
                 file_id=file_id,
                 name=filename,
@@ -246,12 +243,12 @@ 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 get_workspace_file_by_path(self.workspace_id, path)
+                existing = await db.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 create_workspace_file(
+                    file = await db.create_workspace_file(
                         workspace_id=self.workspace_id,
                         file_id=file_id,
                         name=filename,
@@ -314,8 +311,9 @@ class WorkspaceManager:
             List of WorkspaceFile instances
         """
         effective_path = self._get_effective_path(path, include_all_sessions)
+        db = workspace_db()
 
-        return await list_workspace_files(
+        return await db.list_workspace_files(
             workspace_id=self.workspace_id,
             path_prefix=effective_path,
             limit=limit,
@@ -332,7 +330,8 @@ class WorkspaceManager:
         Returns:
             True if deleted, False if not found
         """
-        file = await get_workspace_file(file_id, self.workspace_id)
+        db = workspace_db()
+        file = await db.get_workspace_file(file_id, self.workspace_id)
         if file is None:
             return False
 
@@ -345,7 +344,7 @@ class WorkspaceManager:
             # Continue with database soft-delete even if storage delete fails
 
         # Soft-delete database record
-        result = await soft_delete_workspace_file(file_id, self.workspace_id)
+        result = await db.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:
@@ -362,7 +361,8 @@ class WorkspaceManager:
         Raises:
             FileNotFoundError: If file doesn't exist
         """
-        file = await get_workspace_file(file_id, self.workspace_id)
+        db = workspace_db()
+        file = await db.get_workspace_file(file_id, self.workspace_id)
         if file is None:
             raise FileNotFoundError(f"File not found: {file_id}")
 
@@ -379,7 +379,8 @@ class WorkspaceManager:
         Returns:
             WorkspaceFile instance or None
         """
-        return await get_workspace_file(file_id, self.workspace_id)
+        db = workspace_db()
+        return await db.get_workspace_file(file_id, self.workspace_id)
 
     async def get_file_info_by_path(self, path: str) -> Optional[WorkspaceFile]:
         """
@@ -394,8 +395,9 @@ class WorkspaceManager:
         Returns:
             WorkspaceFile instance or None
         """
+        db = workspace_db()
         resolved_path = self._resolve_path(path)
-        return await get_workspace_file_by_path(self.workspace_id, resolved_path)
+        return await db.get_workspace_file_by_path(self.workspace_id, resolved_path)
 
     async def get_file_count(
         self,
@@ -417,7 +419,8 @@ class WorkspaceManager:
             Number of files
         """
         effective_path = self._get_effective_path(path, include_all_sessions)
+        db = workspace_db()
 
-        return await count_workspace_files(
+        return await db.count_workspace_files(
             self.workspace_id, path_prefix=effective_path
         )

autogpt_platform/backend/backend/util/workspace_storage.py

@@ -93,7 +93,14 @@ class WorkspaceStorageBackend(ABC):
 
 
 class GCSWorkspaceStorage(WorkspaceStorageBackend):
-    """Google Cloud Storage implementation for workspace storage."""
+    """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.
+    """
 
     def __init__(self, bucket_name: str):
         self.bucket_name = bucket_name
@@ -337,60 +344,73 @@ class LocalWorkspaceStorage(WorkspaceStorageBackend):
             raise ValueError(f"Invalid storage path format: {storage_path}")
 
 
-# Global storage backend instance
-_workspace_storage: Optional[WorkspaceStorageBackend] = None
+# ---------------------------------------------------------------------------
+# 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] = {}
 _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.
     """
-    Get the workspace storage backend instance.
+    global _local_storage
 
-    Uses GCS if media_gcs_bucket_name is configured, otherwise uses local storage.
-    """
-    global _workspace_storage
+    config = Config()
 
-    if _workspace_storage is None:
-        async with _storage_lock:
-            if _workspace_storage is None:
-                config = Config()
+    # --- 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 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
+    # --- 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]
 
 
 async def shutdown_workspace_storage() -> None:
-    """
-    Properly shutdown the global workspace storage backend.
+    """Shut down workspace storage for the **current** event loop.
 
-    Closes aiohttp sessions and other resources for GCS backend.
-    Should be called during application shutdown.
+    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 _workspace_storage
+    global _local_storage
 
-    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
+    loop_id = id(asyncio.get_running_loop())
+    storage = _gcs_storages.pop(loop_id, None)
+    if storage is not None:
+        await storage.close()
+
+    # 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
 
 
 def compute_file_checksum(content: bytes) -> str:

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

@@ -1,21 +1,39 @@
 import { useNodeStore } from "@/app/(platform)/build/stores/nodeStore";
-import { Switch } from "@/components/atoms/Switch/Switch";
+import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
+import { CaretDownIcon } from "@phosphor-icons/react";
 
-export const NodeAdvancedToggle = ({ nodeId }: { nodeId: string }) => {
+type Props = {
+  nodeId: string;
+};
+
+export function NodeAdvancedToggle({ nodeId }: Props) {
   const showAdvanced = useNodeStore(
     (state) => state.nodeAdvancedStates[nodeId] || false,
   );
   const setShowAdvanced = useNodeStore((state) => state.setShowAdvanced);
   return (
-    <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 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>
   );
-};
+}

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

@@ -26,7 +26,6 @@ import {
 } from "./components/ClarificationQuestionsCard";
 import sparklesImg from "./components/MiniGame/assets/sparkles.png";
 import { MiniGame } from "./components/MiniGame/MiniGame";
-import { SuggestedGoalCard } from "./components/SuggestedGoalCard";
 import {
   AccordionIcon,
   formatMaybeJson,
@@ -39,7 +38,6 @@ import {
   isOperationInProgressOutput,
   isOperationPendingOutput,
   isOperationStartedOutput,
-  isSuggestedGoalOutput,
   ToolIcon,
   truncateText,
   type CreateAgentToolOutput,
@@ -79,13 +77,6 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
       expanded: true,
     };
   }
-  if (isSuggestedGoalOutput(output)) {
-    return {
-      icon,
-      title: "Goal needs refinement",
-      expanded: true,
-    };
-  }
   if (
     isOperationStartedOutput(output) ||
     isOperationPendingOutput(output) ||
@@ -134,13 +125,8 @@ export function CreateAgentTool({ part }: Props) {
       isAgentPreviewOutput(output) ||
       isAgentSavedOutput(output) ||
       isClarificationNeededOutput(output) ||
-      isSuggestedGoalOutput(output) ||
       isErrorOutput(output));
 
-  function handleUseSuggestedGoal(goal: string) {
-    onSend(`Please create an agent with this goal: ${goal}`);
-  }
-
   function handleClarificationAnswers(answers: Record<string, string>) {
     const questions =
       output && isClarificationNeededOutput(output)
@@ -259,16 +245,6 @@ export function CreateAgentTool({ part }: Props) {
             />
           )}
 
-          {isSuggestedGoalOutput(output) && (
-            <SuggestedGoalCard
-              message={output.message}
-              suggestedGoal={output.suggested_goal}
-              reason={output.reason}
-              goalType={output.goal_type ?? "vague"}
-              onUseSuggestedGoal={handleUseSuggestedGoal}
-            />
-          )}
-
           {isErrorOutput(output) && (
             <ContentGrid>
               <ContentMessage>{output.message}</ContentMessage>
@@ -282,22 +258,6 @@ export function CreateAgentTool({ part }: Props) {
                   {formatMaybeJson(output.details)}
                 </ContentCodeBlock>
               )}
-              <div className="flex gap-2">
-                <Button
-                  variant="outline"
-                  size="small"
-                  onClick={() => onSend("Please try creating the agent again.")}
-                >
-                  Try again
-                </Button>
-                <Button
-                  variant="outline"
-                  size="small"
-                  onClick={() => onSend("Can you help me simplify this goal?")}
-                >
-                  Simplify goal
-                </Button>
-              </div>
             </ContentGrid>
           )}
         </ToolAccordion>

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

@@ -1,63 +0,0 @@
-"use client";
-
-import { Button } from "@/components/atoms/Button/Button";
-import { Text } from "@/components/atoms/Text/Text";
-import { ArrowRightIcon, LightbulbIcon } from "@phosphor-icons/react";
-
-interface Props {
-  message: string;
-  suggestedGoal: string;
-  reason?: string;
-  goalType: string;
-  onUseSuggestedGoal: (goal: string) => void;
-}
-
-export function SuggestedGoalCard({
-  message,
-  suggestedGoal,
-  reason,
-  goalType,
-  onUseSuggestedGoal,
-}: Props) {
-  return (
-    <div className="rounded-xl border border-amber-200 bg-amber-50/50 p-4">
-      <div className="flex items-start gap-3">
-        <LightbulbIcon
-          size={20}
-          weight="fill"
-          className="mt-0.5 text-amber-600"
-        />
-        <div className="flex-1 space-y-3">
-          <div>
-            <Text variant="body-medium" className="font-medium text-slate-900">
-              {goalType === "unachievable"
-                ? "Goal cannot be accomplished"
-                : "Goal needs more detail"}
-            </Text>
-            <Text variant="small" className="text-slate-600">
-              {reason || message}
-            </Text>
-          </div>
-
-          <div className="rounded-lg border border-amber-300 bg-white p-3">
-            <Text variant="small" className="mb-1 font-semibold text-amber-800">
-              Suggested alternative:
-            </Text>
-            <Text variant="body-medium" className="text-slate-900">
-              {suggestedGoal}
-            </Text>
-          </div>
-
-          <Button
-            onClick={() => onUseSuggestedGoal(suggestedGoal)}
-            variant="primary"
-          >
-            <span className="inline-flex items-center gap-1.5">
-              Use this goal <ArrowRightIcon size={14} weight="bold" />
-            </span>
-          </Button>
-        </div>
-      </div>
-    </div>
-  );
-}

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

@@ -6,7 +6,6 @@ import type { OperationInProgressResponse } from "@/app/api/__generated__/models
 import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
 import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
 import { ResponseType } from "@/app/api/__generated__/models/responseType";
-import type { SuggestedGoalResponse } from "@/app/api/__generated__/models/suggestedGoalResponse";
 import {
   PlusCircleIcon,
   PlusIcon,
@@ -22,7 +21,6 @@ export type CreateAgentToolOutput =
   | AgentPreviewResponse
   | AgentSavedResponse
   | ClarificationNeededResponse
-  | SuggestedGoalResponse
   | ErrorResponse;
 
 function parseOutput(output: unknown): CreateAgentToolOutput | null {
@@ -45,7 +43,6 @@ function parseOutput(output: unknown): CreateAgentToolOutput | null {
       type === ResponseType.agent_preview ||
       type === ResponseType.agent_saved ||
       type === ResponseType.clarification_needed ||
-      type === ResponseType.suggested_goal ||
       type === ResponseType.error
     ) {
       return output as CreateAgentToolOutput;
@@ -58,7 +55,6 @@ function parseOutput(output: unknown): CreateAgentToolOutput | null {
     if ("agent_id" in output && "library_agent_id" in output)
       return output as AgentSavedResponse;
     if ("questions" in output) return output as ClarificationNeededResponse;
-    if ("suggested_goal" in output) return output as SuggestedGoalResponse;
     if ("error" in output || "details" in output)
       return output as ErrorResponse;
   }
@@ -118,14 +114,6 @@ export function isClarificationNeededOutput(
   );
 }
 
-export function isSuggestedGoalOutput(
-  output: CreateAgentToolOutput,
-): output is SuggestedGoalResponse {
-  return (
-    output.type === ResponseType.suggested_goal || "suggested_goal" in output
-  );
-}
-
 export function isErrorOutput(
   output: CreateAgentToolOutput,
 ): output is ErrorResponse {
@@ -151,7 +139,6 @@ export function getAnimationText(part: {
       if (isAgentSavedOutput(output)) return `Saved ${output.agent_name}`;
       if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
       if (isClarificationNeededOutput(output)) return "Needs clarification";
-      if (isSuggestedGoalOutput(output)) return "Goal needs refinement";
       return "Error creating agent";
     }
     case "output-error":

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

@@ -1,63 +1,695 @@
 "use client";
 
 import { ToolUIPart } from "ai";
-import { GearIcon } from "@phosphor-icons/react";
+import {
+  CheckCircleIcon,
+  CircleDashedIcon,
+  CircleIcon,
+  FileIcon,
+  FilesIcon,
+  GearIcon,
+  GlobeIcon,
+  ListChecksIcon,
+  MagnifyingGlassIcon,
+  PencilSimpleIcon,
+  TerminalIcon,
+  TrashIcon,
+  WarningDiamondIcon,
+} 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());
 }
 
-function getAnimationText(part: ToolUIPart): string {
-  const label = formatToolName(extractToolName(part));
+/* ------------------------------------------------------------------ */
+/*  Tool categorization                                                */
+/* ------------------------------------------------------------------ */
 
-  switch (part.state) {
-    case "input-streaming":
-    case "input-available":
-      return `Running ${label}…`;
-    case "output-available":
-      return `${label} completed`;
-    case "output-error":
-      return `${label} failed`;
+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 `Running ${label}…`;
+      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;
+
+  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`;
+      }
+    }
+    default:
+      return `Running ${formatToolName(toolName)}…`;
+  }
+}
+
+/* ------------------------------------------------------------------ */
+/*  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">
-        <GearIcon
-          size={14}
-          weight="regular"
-          className={
-            isError
-              ? "text-red-500"
-              : isStreaming
-                ? "animate-spin text-neutral-500"
-                : "text-neutral-400"
-          }
+        <ToolIcon
+          category={category}
+          isStreaming={isStreaming}
+          isError={isError}
         />
         <MorphingTextAnimation
-          text={getAnimationText(part)}
+          text={text}
           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

@@ -80,6 +80,12 @@ 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],
@@ -88,6 +94,7 @@ 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.

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

@@ -1052,7 +1052,6 @@
                     {
                       "$ref": "#/components/schemas/ClarificationNeededResponse"
                     },
-                    { "$ref": "#/components/schemas/SuggestedGoalResponse" },
                     { "$ref": "#/components/schemas/BlockListResponse" },
                     { "$ref": "#/components/schemas/BlockDetailsResponse" },
                     { "$ref": "#/components/schemas/BlockOutputResponse" },
@@ -10797,8 +10796,7 @@
           "bash_exec",
           "operation_status",
           "feature_request_search",
-          "feature_request_created",
-          "suggested_goal"
+          "feature_request_created"
         ],
         "title": "ResponseType",
         "description": "Types of tool responses."
@@ -11679,47 +11677,6 @@
         "enum": ["DRAFT", "PENDING", "APPROVED", "REJECTED"],
         "title": "SubmissionStatus"
       },
-      "SuggestedGoalResponse": {
-        "properties": {
-          "type": {
-            "$ref": "#/components/schemas/ResponseType",
-            "default": "suggested_goal"
-          },
-          "message": { "type": "string", "title": "Message" },
-          "session_id": {
-            "anyOf": [{ "type": "string" }, { "type": "null" }],
-            "title": "Session Id"
-          },
-          "suggested_goal": {
-            "type": "string",
-            "title": "Suggested Goal",
-            "description": "The suggested alternative goal"
-          },
-          "reason": {
-            "type": "string",
-            "title": "Reason",
-            "description": "Why the original goal needs refinement",
-            "default": ""
-          },
-          "original_goal": {
-            "type": "string",
-            "title": "Original Goal",
-            "description": "The user's original goal for context",
-            "default": ""
-          },
-          "goal_type": {
-            "type": "string",
-            "enum": ["vague", "unachievable"],
-            "title": "Goal Type",
-            "description": "Type: 'vague' or 'unachievable'",
-            "default": "vague"
-          }
-        },
-        "type": "object",
-        "required": ["message", "suggested_goal"],
-        "title": "SuggestedGoalResponse",
-        "description": "Response when the goal needs refinement with a suggested alternative."
-      },
       "SuggestionsResponse": {
         "properties": {
           "otto_suggestions": {