chore(backend/deps): bump e2b-code-interpreter

Bumps [e2b-code-interpreter](https://github.com/e2b-dev/code-interpreter) from 1.5.2 to 2.4.1.
- [Release notes](https://github.com/e2b-dev/code-interpreter/releases)
- [Commits](https://github.com/e2b-dev/code-interpreter/compare/@e2b/code-interpreter-python@1.5.2...@e2b/code-interpreter-python@2.4.1)

---
updated-dependencies:
- dependency-name: e2b-code-interpreter
  dependency-version: 2.4.1
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>

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

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

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

@@ -266,12 +266,38 @@ async def stream_chat_post(
 
     """
     import asyncio
+    import time
+
+    stream_start_time = time.perf_counter()
+
+    # Base log metadata (task_id added after creation)
+    log_meta = {"component": "ChatStream", "session_id": session_id}
+    if user_id:
+        log_meta["user_id"] = user_id
+
+    logger.info(
+        f"[TIMING] stream_chat_post STARTED, session={session_id}, "
+        f"user={user_id}, message_len={len(request.message)}",
+        extra={"json_fields": log_meta},
+    )
 
     session = await _validate_and_get_session(session_id, user_id)
+    logger.info(
+        f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "duration_ms": (time.perf_counter() - stream_start_time) * 1000,
+            }
+        },
+    )
 
     # Create a task in the stream registry for reconnection support
     task_id = str(uuid_module.uuid4())
     operation_id = str(uuid_module.uuid4())
+    log_meta["task_id"] = task_id
+
+    task_create_start = time.perf_counter()
     await stream_registry.create_task(
         task_id=task_id,
         session_id=session_id,
@@ -280,14 +306,46 @@ async def stream_chat_post(
         tool_name="chat",
         operation_id=operation_id,
     )
+    logger.info(
+        f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms",
+        extra={
+            "json_fields": {
+                **log_meta,
+                "duration_ms": (time.perf_counter() - task_create_start) * 1000,
+            }
+        },
+    )
 
     # Background task that runs the AI generation independently of SSE connection
     async def run_ai_generation():
+        import time as time_module
+
+        gen_start_time = time_module.perf_counter()
+        logger.info(
+            f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}",
+            extra={"json_fields": log_meta},
+        )
+        first_chunk_time, ttfc = None, None
+        chunk_count = 0
         try:
             # Emit a start event with task_id for reconnection
             start_chunk = StreamStart(messageId=task_id, taskId=task_id)
             await stream_registry.publish_chunk(task_id, start_chunk)
+            logger.info(
+                f"[TIMING] StreamStart published at {(time_module.perf_counter() - gen_start_time)*1000:.1f}ms",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "elapsed_ms": (time_module.perf_counter() - gen_start_time)
+                        * 1000,
+                    }
+                },
+            )
 
+            logger.info(
+                "[TIMING] Calling stream_chat_completion",
+                extra={"json_fields": log_meta},
+            )
             async for chunk in chat_service.stream_chat_completion(
                 session_id,
                 request.message,
@@ -296,54 +354,202 @@ async def stream_chat_post(
                 session=session,  # Pass pre-fetched session to avoid double-fetch
                 context=request.context,
             ):
+                chunk_count += 1
+                if first_chunk_time is None:
+                    first_chunk_time = time_module.perf_counter()
+                    ttfc = first_chunk_time - gen_start_time
+                    logger.info(
+                        f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}",
+                        extra={
+                            "json_fields": {
+                                **log_meta,
+                                "chunk_type": type(chunk).__name__,
+                                "time_to_first_chunk_ms": ttfc * 1000,
+                            }
+                        },
+                    )
                 # Write to Redis (subscribers will receive via XREAD)
                 await stream_registry.publish_chunk(task_id, chunk)
 
-            # Mark task as completed
+            gen_end_time = time_module.perf_counter()
+            total_time = (gen_end_time - gen_start_time) * 1000
+            logger.info(
+                f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; "
+                f"task={task_id}, session={session_id}, "
+                f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "total_time_ms": total_time,
+                        "time_to_first_chunk_ms": (
+                            ttfc * 1000 if ttfc is not None else None
+                        ),
+                        "n_chunks": chunk_count,
+                    }
+                },
+            )
+
             await stream_registry.mark_task_completed(task_id, "completed")
         except Exception as e:
+            elapsed = time_module.perf_counter() - gen_start_time
             logger.error(
-                f"Error in background AI generation for session {session_id}: {e}"
+                f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "elapsed_ms": elapsed * 1000,
+                        "error": str(e),
+                    }
+                },
             )
             await stream_registry.mark_task_completed(task_id, "failed")
 
     # Start the AI generation in a background task
     bg_task = asyncio.create_task(run_ai_generation())
     await stream_registry.set_task_asyncio_task(task_id, bg_task)
+    setup_time = (time.perf_counter() - stream_start_time) * 1000
+    logger.info(
+        f"[TIMING] Background task started, setup={setup_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
+    )
 
     # SSE endpoint that subscribes to the task's stream
     async def event_generator() -> AsyncGenerator[str, None]:
+        import time as time_module
+
+        event_gen_start = time_module.perf_counter()
+        logger.info(
+            f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, "
+            f"user={user_id}",
+            extra={"json_fields": log_meta},
+        )
         subscriber_queue = None
+        first_chunk_yielded = False
+        chunks_yielded = 0
         try:
             # Subscribe to the task stream (this replays existing messages + live updates)
+            subscribe_start = time_module.perf_counter()
+            logger.info(
+                "[TIMING] Calling subscribe_to_task",
+                extra={"json_fields": log_meta},
+            )
             subscriber_queue = await stream_registry.subscribe_to_task(
                 task_id=task_id,
                 user_id=user_id,
                 last_message_id="0-0",  # Get all messages from the beginning
             )
+            subscribe_time = (time_module.perf_counter() - subscribe_start) * 1000
+            logger.info(
+                f"[TIMING] subscribe_to_task completed in {subscribe_time:.1f}ms, "
+                f"queue_ok={subscriber_queue is not None}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "duration_ms": subscribe_time,
+                        "queue_obtained": subscriber_queue is not None,
+                    }
+                },
+            )
 
             if subscriber_queue is None:
+                logger.info(
+                    "[TIMING] subscriber_queue is None, yielding finish",
+                    extra={"json_fields": log_meta},
+                )
                 yield StreamFinish().to_sse()
                 yield "data: [DONE]\n\n"
                 return
 
             # Read from the subscriber queue and yield to SSE
+            logger.info(
+                "[TIMING] Starting to read from subscriber_queue",
+                extra={"json_fields": log_meta},
+            )
             while True:
                 try:
+                    queue_wait_start = time_module.perf_counter()
                     chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0)
+                    queue_wait_time = (
+                        time_module.perf_counter() - queue_wait_start
+                    ) * 1000
+                    chunks_yielded += 1
+
+                    if not first_chunk_yielded:
+                        first_chunk_yielded = True
+                        elapsed = time_module.perf_counter() - event_gen_start
+                        logger.info(
+                            f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, "
+                            f"type={type(chunk).__name__}, "
+                            f"wait={queue_wait_time:.1f}ms",
+                            extra={
+                                "json_fields": {
+                                    **log_meta,
+                                    "chunk_type": type(chunk).__name__,
+                                    "elapsed_ms": elapsed * 1000,
+                                    "queue_wait_ms": queue_wait_time,
+                                }
+                            },
+                        )
+                    elif chunks_yielded % 50 == 0:
+                        logger.info(
+                            f"[TIMING] Chunk #{chunks_yielded}, "
+                            f"type={type(chunk).__name__}",
+                            extra={
+                                "json_fields": {
+                                    **log_meta,
+                                    "chunk_number": chunks_yielded,
+                                    "chunk_type": type(chunk).__name__,
+                                }
+                            },
+                        )
+
                     yield chunk.to_sse()
 
                     # Check for finish signal
                     if isinstance(chunk, StreamFinish):
+                        total_time = time_module.perf_counter() - event_gen_start
+                        logger.info(
+                            f"[TIMING] StreamFinish received in {total_time:.2f}s; "
+                            f"n_chunks={chunks_yielded}",
+                            extra={
+                                "json_fields": {
+                                    **log_meta,
+                                    "chunks_yielded": chunks_yielded,
+                                    "total_time_ms": total_time * 1000,
+                                }
+                            },
+                        )
                         break
                 except asyncio.TimeoutError:
                     # Send heartbeat to keep connection alive
+                    logger.info(
+                        f"[TIMING] Heartbeat timeout, chunks_so_far={chunks_yielded}",
+                        extra={
+                            "json_fields": {**log_meta, "chunks_so_far": chunks_yielded}
+                        },
+                    )
                     yield StreamHeartbeat().to_sse()
 
         except GeneratorExit:
+            logger.info(
+                f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "chunks_yielded": chunks_yielded,
+                        "reason": "client_disconnect",
+                    }
+                },
+            )
             pass  # Client disconnected - background task continues
         except Exception as e:
-            logger.error(f"Error in SSE stream for task {task_id}: {e}")
+            elapsed = (time_module.perf_counter() - event_gen_start) * 1000
+            logger.error(
+                f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}",
+                extra={
+                    "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}
+                },
+            )
         finally:
             # Unsubscribe when client disconnects or stream ends to prevent resource leak
             if subscriber_queue is not None:
@@ -357,6 +563,18 @@ async def stream_chat_post(
                         exc_info=True,
                     )
             # AI SDK protocol termination - always yield even if unsubscribe fails
+            total_time = time_module.perf_counter() - event_gen_start
+            logger.info(
+                f"[TIMING] event_generator FINISHED in {total_time:.2f}s; "
+                f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}",
+                extra={
+                    "json_fields": {
+                        **log_meta,
+                        "total_time_ms": total_time * 1000,
+                        "chunks_yielded": chunks_yielded,
+                    }
+                },
+            )
             yield "data: [DONE]\n\n"
 
     return StreamingResponse(
@@ -425,7 +643,7 @@ async def stream_chat_get(
             "Chat stream completed",
             extra={
                 "session_id": session_id,
-                "chunk_count": chunk_count,
+                "n_chunks": chunk_count,
                 "first_chunk_type": first_chunk_type,
             },
         )

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

@@ -371,21 +371,45 @@ async def stream_chat_completion(
         ValueError: If max_context_messages is exceeded
 
     """
+    completion_start = time.monotonic()
+
+    # Build log metadata for structured logging
+    log_meta = {"component": "ChatService", "session_id": session_id}
+    if user_id:
+        log_meta["user_id"] = user_id
+
     logger.info(
-        f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}"
+        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={
+            "json_fields": {
+                **log_meta,
+                "message_len": len(message) if message else 0,
+                "is_user_message": is_user_message,
+            }
+        },
     )
 
     # Only fetch from Redis if session not provided (initial call)
     if session is None:
+        fetch_start = time.monotonic()
         session = await get_chat_session(session_id, user_id)
+        fetch_time = (time.monotonic() - fetch_start) * 1000
         logger.info(
-            f"Fetched session from Redis: {session.session_id if session else 'None'}, "
-            f"message_count={len(session.messages) if session else 0}"
+            f"[TIMING] get_chat_session took {fetch_time:.1f}ms, "
+            f"n_messages={len(session.messages) if session else 0}",
+            extra={
+                "json_fields": {
+                    **log_meta,
+                    "duration_ms": fetch_time,
+                    "n_messages": len(session.messages) if session else 0,
+                }
+            },
         )
     else:
         logger.info(
-            f"Using provided session object: {session.session_id}, "
-            f"message_count={len(session.messages)}"
+            f"[TIMING] Using provided session, messages={len(session.messages)}",
+            extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
         )
 
     if not session:
@@ -406,17 +430,25 @@ async def stream_chat_completion(
 
         # Track user message in PostHog
         if is_user_message:
+            posthog_start = time.monotonic()
             track_user_message(
                 user_id=user_id,
                 session_id=session_id,
                 message_length=len(message),
             )
+            posthog_time = (time.monotonic() - posthog_start) * 1000
+            logger.info(
+                f"[TIMING] track_user_message took {posthog_time:.1f}ms",
+                extra={"json_fields": {**log_meta, "duration_ms": posthog_time}},
+            )
 
-    logger.info(
-        f"Upserting session: {session.session_id} with user id {session.user_id}, "
-        f"message_count={len(session.messages)}"
-    )
+    upsert_start = time.monotonic()
     session = await upsert_chat_session(session)
+    upsert_time = (time.monotonic() - upsert_start) * 1000
+    logger.info(
+        f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": upsert_time}},
+    )
     assert session, "Session not found"
 
     # Generate title for new sessions on first user message (non-blocking)
@@ -454,7 +486,13 @@ async def stream_chat_completion(
             asyncio.create_task(_update_title())
 
     # Build system prompt with business understanding
+    prompt_start = time.monotonic()
     system_prompt, understanding = await _build_system_prompt(user_id)
+    prompt_time = (time.monotonic() - prompt_start) * 1000
+    logger.info(
+        f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": prompt_time}},
+    )
 
     # Initialize variables for streaming
     assistant_response = ChatMessage(
@@ -483,9 +521,18 @@ async def stream_chat_completion(
     text_block_id = str(uuid_module.uuid4())
 
     # Yield message start
+    setup_time = (time.monotonic() - completion_start) * 1000
+    logger.info(
+        f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}},
+    )
     yield StreamStart(messageId=message_id)
 
     try:
+        logger.info(
+            "[TIMING] Calling _stream_chat_chunks",
+            extra={"json_fields": log_meta},
+        )
         async for chunk in _stream_chat_chunks(
             session=session,
             tools=tools,
@@ -893,9 +940,21 @@ async def _stream_chat_chunks(
         SSE formatted JSON response objects
 
     """
+    import time as time_module
+
+    stream_chunks_start = time_module.perf_counter()
     model = config.model
 
-    logger.info("Starting pure chat stream")
+    # Build log metadata for structured logging
+    log_meta = {"component": "ChatService", "session_id": session.session_id}
+    if session.user_id:
+        log_meta["user_id"] = session.user_id
+
+    logger.info(
+        f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, "
+        f"user={session.user_id}, n_messages={len(session.messages)}",
+        extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}},
+    )
 
     messages = session.to_openai_messages()
     if system_prompt:
@@ -906,12 +965,18 @@ async def _stream_chat_chunks(
         messages = [system_message] + messages
 
     # Apply context window management
+    context_start = time_module.perf_counter()
     context_result = await _manage_context_window(
         messages=messages,
         model=model,
         api_key=config.api_key,
         base_url=config.base_url,
     )
+    context_time = (time_module.perf_counter() - context_start) * 1000
+    logger.info(
+        f"[TIMING] _manage_context_window took {context_time:.1f}ms",
+        extra={"json_fields": {**log_meta, "duration_ms": context_time}},
+    )
 
     if context_result.error:
         if "System prompt dropped" in context_result.error:
@@ -946,9 +1011,19 @@ async def _stream_chat_chunks(
 
         while retry_count <= MAX_RETRIES:
             try:
+                elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000
+                retry_info = (
+                    f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else ""
+                )
                 logger.info(
-                    f"Creating OpenAI chat completion stream..."
-                    f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}"
+                    f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "elapsed_ms": elapsed,
+                            "retry_count": retry_count,
+                        }
+                    },
                 )
 
                 # Build extra_body for OpenRouter tracing and PostHog analytics
@@ -965,6 +1040,7 @@ async def _stream_chat_chunks(
                         :128
                     ]  # OpenRouter limit
 
+                api_call_start = time_module.perf_counter()
                 stream = await client.chat.completions.create(
                     model=model,
                     messages=cast(list[ChatCompletionMessageParam], messages),
@@ -974,6 +1050,11 @@ async def _stream_chat_chunks(
                     stream_options=ChatCompletionStreamOptionsParam(include_usage=True),
                     extra_body=extra_body,
                 )
+                api_init_time = (time_module.perf_counter() - api_call_start) * 1000
+                logger.info(
+                    f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms",
+                    extra={"json_fields": {**log_meta, "duration_ms": api_init_time}},
+                )
 
                 # Variables to accumulate tool calls
                 tool_calls: list[dict[str, Any]] = []
@@ -984,10 +1065,13 @@ async def _stream_chat_chunks(
 
                 # Track if we've started the text block
                 text_started = False
+                first_content_chunk = True
+                chunk_count = 0
 
                 # Process the stream
                 chunk: ChatCompletionChunk
                 async for chunk in stream:
+                    chunk_count += 1
                     if chunk.usage:
                         yield StreamUsage(
                             promptTokens=chunk.usage.prompt_tokens,
@@ -1010,6 +1094,23 @@ async def _stream_chat_chunks(
                             if not text_started and text_block_id:
                                 yield StreamTextStart(id=text_block_id)
                                 text_started = True
+                            # Log timing for first content chunk
+                            if first_content_chunk:
+                                first_content_chunk = False
+                                ttfc = (
+                                    time_module.perf_counter() - api_call_start
+                                ) * 1000
+                                logger.info(
+                                    f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms "
+                                    f"(since API call), n_chunks={chunk_count}",
+                                    extra={
+                                        "json_fields": {
+                                            **log_meta,
+                                            "time_to_first_chunk_ms": ttfc,
+                                            "n_chunks": chunk_count,
+                                        }
+                                    },
+                                )
                             # Stream the text delta
                             text_response = StreamTextDelta(
                                 id=text_block_id or "",
@@ -1066,7 +1167,21 @@ async def _stream_chat_chunks(
                                         toolName=tool_calls[idx]["function"]["name"],
                                     )
                                     emitted_start_for_idx.add(idx)
-                logger.info(f"Stream complete. Finish reason: {finish_reason}")
+                stream_duration = time_module.perf_counter() - api_call_start
+                logger.info(
+                    f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, "
+                    f"duration={stream_duration:.2f}s, "
+                    f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}",
+                    extra={
+                        "json_fields": {
+                            **log_meta,
+                            "stream_duration_ms": stream_duration * 1000,
+                            "finish_reason": finish_reason,
+                            "n_chunks": chunk_count,
+                            "n_tool_calls": len(tool_calls),
+                        }
+                    },
+                )
 
                 # Yield all accumulated tool calls after the stream is complete
                 # This ensures all tool call arguments have been fully received
@@ -1086,6 +1201,12 @@ async def _stream_chat_chunks(
                         # Re-raise to trigger retry logic in the parent function
                         raise
 
+                total_time = (time_module.perf_counter() - stream_chunks_start) * 1000
+                logger.info(
+                    f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; "
+                    f"session={session.session_id}, user={session.user_id}",
+                    extra={"json_fields": {**log_meta, "total_time_ms": total_time}},
+                )
                 yield StreamFinish()
                 return
             except Exception as e:

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

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

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

@@ -1,251 +0,0 @@
-"""
-Detect and save embedded binary data in block outputs.
-
-Scans stdout_logs and other string outputs for embedded base64 patterns,
-saves detected binary content to workspace, and replaces the base64 with
-workspace:// references. This reduces LLM output token usage by ~97% for
-file generation tasks.
-
-Primary use case: ExecuteCodeBlock prints base64 to stdout, which appears
-in stdout_logs. Without this processor, the LLM would re-type the entire
-base64 string when saving files.
-"""
-
-import base64
-import binascii
-import hashlib
-import logging
-import re
-import uuid
-from typing import Any, Optional
-
-from backend.util.file import sanitize_filename
-from backend.util.virus_scanner import scan_content_safe
-from backend.util.workspace import WorkspaceManager
-
-logger = logging.getLogger(__name__)
-
-# Minimum decoded size to process (filters out small base64 strings)
-MIN_DECODED_SIZE = 1024  # 1KB
-
-# Pattern to find base64 chunks in text (at least 100 chars to be worth checking)
-# Matches continuous base64 characters (with optional whitespace for line wrapping),
-# optionally ending with = padding
-EMBEDDED_BASE64_PATTERN = re.compile(r"[A-Za-z0-9+/\s]{100,}={0,2}")
-
-# Magic numbers for binary file detection
-MAGIC_SIGNATURES = [
-    (b"\x89PNG\r\n\x1a\n", "png"),
-    (b"\xff\xd8\xff", "jpg"),
-    (b"%PDF-", "pdf"),
-    (b"GIF87a", "gif"),
-    (b"GIF89a", "gif"),
-    (b"RIFF", "webp"),  # Also check content[8:12] == b'WEBP'
-]
-
-
-async def process_binary_outputs(
-    outputs: dict[str, list[Any]],
-    workspace_manager: WorkspaceManager,
-    block_name: str,
-) -> dict[str, list[Any]]:
-    """
-    Scan all string values in outputs for embedded base64 binary content.
-    Save detected binaries to workspace and replace with references.
-
-    Args:
-        outputs: Block execution outputs (dict of output_name -> list of values)
-        workspace_manager: WorkspaceManager instance with session scoping
-        block_name: Name of the block (used in generated filenames)
-
-    Returns:
-        Processed outputs with embedded base64 replaced by workspace references
-    """
-    cache: dict[str, str] = {}  # content_hash -> workspace_ref
-
-    processed: dict[str, list[Any]] = {}
-    for name, items in outputs.items():
-        processed_items = []
-        for item in items:
-            processed_items.append(
-                await _process_value(item, workspace_manager, block_name, cache)
-            )
-        processed[name] = processed_items
-    return processed
-
-
-async def _process_value(
-    value: Any,
-    wm: WorkspaceManager,
-    block: str,
-    cache: dict[str, str],
-) -> Any:
-    """Recursively process a value, detecting embedded base64 in strings."""
-    if isinstance(value, dict):
-        result = {}
-        for k, v in value.items():
-            result[k] = await _process_value(v, wm, block, cache)
-        return result
-    if isinstance(value, list):
-        return [await _process_value(v, wm, block, cache) for v in value]
-    if isinstance(value, str) and len(value) > MIN_DECODED_SIZE:
-        return await _extract_and_replace_base64(value, wm, block, cache)
-    return value
-
-
-async def _extract_and_replace_base64(
-    text: str,
-    wm: WorkspaceManager,
-    block: str,
-    cache: dict[str, str],
-) -> str:
-    """
-    Find embedded base64 in text, save binaries, replace with references.
-
-    Scans for base64 patterns, validates each as binary via magic numbers,
-    saves valid binaries to workspace, and replaces the base64 portion
-    (plus any surrounding markers) with the workspace reference.
-    """
-    result = text
-    offset = 0
-
-    for match in EMBEDDED_BASE64_PATTERN.finditer(text):
-        b64_str = match.group(0)
-
-        # Try to decode and validate
-        detection = _decode_and_validate(b64_str)
-        if detection is None:
-            continue
-
-        content, ext = detection
-
-        # Save to workspace
-        ref = await _save_binary(content, ext, wm, block, cache)
-        if ref is None:
-            continue
-
-        # Calculate replacement bounds (include surrounding markers if present)
-        start, end = match.start(), match.end()
-        start, end = _expand_to_markers(text, start, end)
-
-        # Apply replacement with offset adjustment
-        adj_start = start + offset
-        adj_end = end + offset
-        result = result[:adj_start] + ref + result[adj_end:]
-        offset += len(ref) - (end - start)
-
-    return result
-
-
-def _decode_and_validate(b64_str: str) -> Optional[tuple[bytes, str]]:
-    """
-    Decode base64 and validate it's a known binary format.
-
-    Tries multiple 4-byte aligned offsets to handle cases where marker text
-    (e.g., "START" from "PDF_BASE64_START") bleeds into the regex match.
-    Base64 works in 4-char chunks, so we only check aligned offsets.
-
-    Returns (content, extension) if valid binary, None otherwise.
-    """
-    # Strip whitespace for RFC 2045 line-wrapped base64
-    normalized = re.sub(r"\s+", "", b64_str)
-
-    # Try offsets 0, 4, 8, ... up to 32 chars (handles markers up to ~24 chars)
-    # This handles cases like "STARTJVBERi0..." where "START" bleeds into match
-    for char_offset in range(0, min(33, len(normalized)), 4):
-        candidate = normalized[char_offset:]
-
-        try:
-            content = base64.b64decode(candidate, validate=True)
-        except (ValueError, binascii.Error):
-            continue
-
-        # Must meet minimum size
-        if len(content) < MIN_DECODED_SIZE:
-            continue
-
-        # Check magic numbers
-        for magic, ext in MAGIC_SIGNATURES:
-            if content.startswith(magic):
-                # Special case for WebP: RIFF container, verify "WEBP" at offset 8
-                if magic == b"RIFF":
-                    if len(content) < 12 or content[8:12] != b"WEBP":
-                        continue
-                return content, ext
-
-    return None
-
-
-def _expand_to_markers(text: str, start: int, end: int) -> tuple[int, int]:
-    """
-    Expand replacement bounds to include surrounding markers if present.
-
-    Handles patterns like:
-    - ---BASE64_START---\\n{base64}\\n---BASE64_END---
-    - [BASE64]{base64}[/BASE64]
-    - Or just the raw base64
-    """
-    # Common marker patterns to strip (order matters - check longer patterns first)
-    start_markers = [
-        "PDF_BASE64_START",
-        "---BASE64_START---\n",
-        "---BASE64_START---",
-        "[BASE64]\n",
-        "[BASE64]",
-    ]
-    end_markers = [
-        "PDF_BASE64_END",
-        "\n---BASE64_END---",
-        "---BASE64_END---",
-        "\n[/BASE64]",
-        "[/BASE64]",
-    ]
-
-    # Check for start markers
-    for marker in start_markers:
-        marker_start = start - len(marker)
-        if marker_start >= 0 and text[marker_start:start] == marker:
-            start = marker_start
-            break
-
-    # Check for end markers
-    for marker in end_markers:
-        marker_end = end + len(marker)
-        if marker_end <= len(text) and text[end:marker_end] == marker:
-            end = marker_end
-            break
-
-    return start, end
-
-
-async def _save_binary(
-    content: bytes,
-    ext: str,
-    wm: WorkspaceManager,
-    block: str,
-    cache: dict[str, str],
-) -> Optional[str]:
-    """
-    Save binary content to workspace with deduplication.
-
-    Returns workspace://file-id reference, or None on failure.
-    """
-    content_hash = hashlib.sha256(content).hexdigest()
-
-    if content_hash in cache:
-        return cache[content_hash]
-
-    try:
-        safe_block = sanitize_filename(block)[:20].lower()
-        filename = f"{safe_block}_{uuid.uuid4().hex[:12]}.{ext}"
-
-        # Scan for viruses before saving
-        await scan_content_safe(content, filename=filename)
-
-        file = await wm.write_file(content, filename)
-        ref = f"workspace://{file.id}"
-        cache[content_hash] = ref
-        return ref
-    except Exception as e:
-        logger.warning("Failed to save binary output: %s", e)
-        return None

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

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

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

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

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

@@ -12,16 +12,15 @@ from backend.api.features.chat.tools.find_block import (
     COPILOT_EXCLUDED_BLOCK_IDS,
     COPILOT_EXCLUDED_BLOCK_TYPES,
 )
-from backend.data.block import get_block
+from backend.data.block import AnyBlockSchema, get_block
 from backend.data.execution import ExecutionContext
-from backend.data.model import CredentialsMetaInput
+from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
 from backend.data.workspace import get_or_create_workspace
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import BlockError
-from backend.util.workspace import WorkspaceManager
 
 from .base import BaseTool
-from .binary_output_processor import process_binary_outputs
+from .helpers import get_inputs_from_schema
 from .models import (
     BlockOutputResponse,
     ErrorResponse,
@@ -30,7 +29,10 @@ from .models import (
     ToolResponseBase,
     UserReadiness,
 )
-from .utils import build_missing_credentials_from_field_info
+from .utils import (
+    build_missing_credentials_from_field_info,
+    match_credentials_to_requirements,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -79,91 +81,6 @@ class RunBlockTool(BaseTool):
     def requires_auth(self) -> bool:
         return True
 
-    async def _check_block_credentials(
-        self,
-        user_id: str,
-        block: Any,
-        input_data: dict[str, Any] | None = None,
-    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
-        """
-        Check if user has required credentials for a block.
-
-        Args:
-            user_id: User ID
-            block: Block to check credentials for
-            input_data: Input data for the block (used to determine provider via discriminator)
-
-        Returns:
-            tuple[matched_credentials, missing_credentials]
-        """
-        matched_credentials: dict[str, CredentialsMetaInput] = {}
-        missing_credentials: list[CredentialsMetaInput] = []
-        input_data = input_data or {}
-
-        # Get credential field info from block's input schema
-        credentials_fields_info = block.input_schema.get_credentials_fields_info()
-
-        if not credentials_fields_info:
-            return matched_credentials, missing_credentials
-
-        # Get user's available credentials
-        creds_manager = IntegrationCredentialsManager()
-        available_creds = await creds_manager.store.get_all_creds(user_id)
-
-        for field_name, field_info in credentials_fields_info.items():
-            effective_field_info = field_info
-            if field_info.discriminator and field_info.discriminator_mapping:
-                # Get discriminator from input, falling back to schema default
-                discriminator_value = input_data.get(field_info.discriminator)
-                if discriminator_value is None:
-                    field = block.input_schema.model_fields.get(
-                        field_info.discriminator
-                    )
-                    if field and field.default is not PydanticUndefined:
-                        discriminator_value = field.default
-
-                if (
-                    discriminator_value
-                    and discriminator_value in field_info.discriminator_mapping
-                ):
-                    effective_field_info = field_info.discriminate(discriminator_value)
-                    logger.debug(
-                        f"Discriminated provider for {field_name}: "
-                        f"{discriminator_value} -> {effective_field_info.provider}"
-                    )
-
-            matching_cred = next(
-                (
-                    cred
-                    for cred in available_creds
-                    if cred.provider in effective_field_info.provider
-                    and cred.type in effective_field_info.supported_types
-                ),
-                None,
-            )
-
-            if matching_cred:
-                matched_credentials[field_name] = CredentialsMetaInput(
-                    id=matching_cred.id,
-                    provider=matching_cred.provider,  # type: ignore
-                    type=matching_cred.type,
-                    title=matching_cred.title,
-                )
-            else:
-                # Create a placeholder for the missing credential
-                provider = next(iter(effective_field_info.provider), "unknown")
-                cred_type = next(iter(effective_field_info.supported_types), "api_key")
-                missing_credentials.append(
-                    CredentialsMetaInput(
-                        id=field_name,
-                        provider=provider,  # type: ignore
-                        type=cred_type,  # type: ignore
-                        title=field_name.replace("_", " ").title(),
-                    )
-                )
-
-        return matched_credentials, missing_credentials
-
     async def _execute(
         self,
         user_id: str | None,
@@ -234,8 +151,8 @@ class RunBlockTool(BaseTool):
         logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}")
 
         creds_manager = IntegrationCredentialsManager()
-        matched_credentials, missing_credentials = await self._check_block_credentials(
-            user_id, block, input_data
+        matched_credentials, missing_credentials = (
+            await self._resolve_block_credentials(user_id, block, input_data)
         )
 
         if missing_credentials:
@@ -340,16 +257,6 @@ class RunBlockTool(BaseTool):
             ):
                 outputs[output_name].append(output_data)
 
-            # Post-process outputs to save binary content to workspace
-            workspace_manager = WorkspaceManager(
-                user_id=user_id,
-                workspace_id=workspace.id,
-                session_id=session.session_id,
-            )
-            outputs = await process_binary_outputs(
-                dict(outputs), workspace_manager, block.name
-            )
-
             return BlockOutputResponse(
                 message=f"Block '{block.name}' executed successfully",
                 block_id=block_id,
@@ -374,29 +281,75 @@ class RunBlockTool(BaseTool):
                 session_id=session_id,
             )
 
-    def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]:
+    async def _resolve_block_credentials(
+        self,
+        user_id: str,
+        block: AnyBlockSchema,
+        input_data: dict[str, Any] | None = None,
+    ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]:
+        """
+        Resolve credentials for a block by matching user's available credentials.
+
+        Args:
+            user_id: User ID
+            block: Block to resolve credentials for
+            input_data: Input data for the block (used to determine provider via discriminator)
+
+        Returns:
+            tuple of (matched_credentials, missing_credentials) - matched credentials
+            are used for block execution, missing ones indicate setup requirements.
+        """
+        input_data = input_data or {}
+        requirements = self._resolve_discriminated_credentials(block, input_data)
+
+        if not requirements:
+            return {}, []
+
+        return await match_credentials_to_requirements(user_id, requirements)
+
+    def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]:
         """Extract non-credential inputs from block schema."""
-        inputs_list = []
         schema = block.input_schema.jsonschema()
-        properties = schema.get("properties", {})
-        required_fields = set(schema.get("required", []))
-
-        # Get credential field names to exclude
         credentials_fields = set(block.input_schema.get_credentials_fields().keys())
+        return get_inputs_from_schema(schema, exclude_fields=credentials_fields)
 
-        for field_name, field_schema in properties.items():
-            # Skip credential fields
-            if field_name in credentials_fields:
-                continue
+    def _resolve_discriminated_credentials(
+        self,
+        block: AnyBlockSchema,
+        input_data: dict[str, Any],
+    ) -> dict[str, CredentialsFieldInfo]:
+        """Resolve credential requirements, applying discriminator logic where needed."""
+        credentials_fields_info = block.input_schema.get_credentials_fields_info()
+        if not credentials_fields_info:
+            return {}
 
-            inputs_list.append(
-                {
-                    "name": field_name,
-                    "title": field_schema.get("title", field_name),
-                    "type": field_schema.get("type", "string"),
-                    "description": field_schema.get("description", ""),
-                    "required": field_name in required_fields,
-                }
-            )
+        resolved: dict[str, CredentialsFieldInfo] = {}
 
-        return inputs_list
+        for field_name, field_info in credentials_fields_info.items():
+            effective_field_info = field_info
+
+            if field_info.discriminator and field_info.discriminator_mapping:
+                discriminator_value = input_data.get(field_info.discriminator)
+                if discriminator_value is None:
+                    field = block.input_schema.model_fields.get(
+                        field_info.discriminator
+                    )
+                    if field and field.default is not PydanticUndefined:
+                        discriminator_value = field.default
+
+                if (
+                    discriminator_value
+                    and discriminator_value in field_info.discriminator_mapping
+                ):
+                    effective_field_info = field_info.discriminate(discriminator_value)
+                    # For host-scoped credentials, add the discriminator value
+                    # (e.g., URL) so _credential_is_for_host can match it
+                    effective_field_info.discriminator_values.add(discriminator_value)
+                    logger.debug(
+                        f"Discriminated provider for {field_name}: "
+                        f"{discriminator_value} -> {effective_field_info.provider}"
+                    )
+
+            resolved[field_name] = effective_field_info
+
+        return resolved

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

@@ -1,518 +0,0 @@
-"""Tests for embedded binary detection in block outputs."""
-
-import base64
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-
-from .binary_output_processor import (
-    _decode_and_validate,
-    _expand_to_markers,
-    process_binary_outputs,
-)
-
-
-@pytest.fixture
-def mock_workspace_manager():
-    """Create a mock workspace manager that returns predictable file IDs."""
-    wm = MagicMock()
-
-    async def mock_write_file(content, filename):
-        file = MagicMock()
-        file.id = f"file-{filename[:10]}"
-        return file
-
-    wm.write_file = AsyncMock(side_effect=mock_write_file)
-    return wm
-
-
-def _make_pdf_base64(size: int = 2000) -> str:
-    """Create a valid PDF base64 string of specified size."""
-    pdf_content = b"%PDF-1.4 " + b"x" * size
-    return base64.b64encode(pdf_content).decode()
-
-
-def _make_png_base64(size: int = 2000) -> str:
-    """Create a valid PNG base64 string of specified size."""
-    png_content = b"\x89PNG\r\n\x1a\n" + b"\x00" * size
-    return base64.b64encode(png_content).decode()
-
-
-# =============================================================================
-# Decode and Validate Tests
-# =============================================================================
-
-
-class TestDecodeAndValidate:
-    """Tests for _decode_and_validate function."""
-
-    def test_detects_pdf_magic_number(self):
-        """Should detect valid PDF by magic number."""
-        pdf_b64 = _make_pdf_base64()
-        result = _decode_and_validate(pdf_b64)
-        assert result is not None
-        content, ext = result
-        assert ext == "pdf"
-        assert content.startswith(b"%PDF-")
-
-    def test_detects_png_magic_number(self):
-        """Should detect valid PNG by magic number."""
-        png_b64 = _make_png_base64()
-        result = _decode_and_validate(png_b64)
-        assert result is not None
-        content, ext = result
-        assert ext == "png"
-
-    def test_detects_jpeg_magic_number(self):
-        """Should detect valid JPEG by magic number."""
-        jpeg_content = b"\xff\xd8\xff\xe0" + b"\x00" * 2000
-        jpeg_b64 = base64.b64encode(jpeg_content).decode()
-        result = _decode_and_validate(jpeg_b64)
-        assert result is not None
-        _, ext = result
-        assert ext == "jpg"
-
-    def test_detects_gif_magic_number(self):
-        """Should detect valid GIF by magic number."""
-        gif_content = b"GIF89a" + b"\x00" * 2000
-        gif_b64 = base64.b64encode(gif_content).decode()
-        result = _decode_and_validate(gif_b64)
-        assert result is not None
-        _, ext = result
-        assert ext == "gif"
-
-    def test_detects_webp_magic_number(self):
-        """Should detect valid WebP by magic number."""
-        webp_content = b"RIFF\x00\x00\x00\x00WEBP" + b"\x00" * 2000
-        webp_b64 = base64.b64encode(webp_content).decode()
-        result = _decode_and_validate(webp_b64)
-        assert result is not None
-        _, ext = result
-        assert ext == "webp"
-
-    def test_rejects_small_content(self):
-        """Should reject content smaller than threshold."""
-        small_pdf = b"%PDF-1.4 small"
-        small_b64 = base64.b64encode(small_pdf).decode()
-        result = _decode_and_validate(small_b64)
-        assert result is None
-
-    def test_rejects_no_magic_number(self):
-        """Should reject content without recognized magic number."""
-        random_content = b"This is just random text" * 100
-        random_b64 = base64.b64encode(random_content).decode()
-        result = _decode_and_validate(random_b64)
-        assert result is None
-
-    def test_rejects_invalid_base64(self):
-        """Should reject invalid base64."""
-        result = _decode_and_validate("not-valid-base64!!!")
-        assert result is None
-
-    def test_rejects_riff_without_webp(self):
-        """Should reject RIFF files that aren't WebP (e.g., WAV)."""
-        wav_content = b"RIFF\x00\x00\x00\x00WAVE" + b"\x00" * 2000
-        wav_b64 = base64.b64encode(wav_content).decode()
-        result = _decode_and_validate(wav_b64)
-        assert result is None
-
-    def test_handles_line_wrapped_base64(self):
-        """Should handle RFC 2045 line-wrapped base64."""
-        pdf_content = b"%PDF-1.4 " + b"x" * 2000
-        pdf_b64 = base64.b64encode(pdf_content).decode()
-        # Simulate line wrapping at 76 chars
-        wrapped = "\n".join(pdf_b64[i : i + 76] for i in range(0, len(pdf_b64), 76))
-        result = _decode_and_validate(wrapped)
-        assert result is not None
-        content, ext = result
-        assert ext == "pdf"
-        assert content == pdf_content
-
-
-# =============================================================================
-# Marker Expansion Tests
-# =============================================================================
-
-
-class TestExpandToMarkers:
-    """Tests for _expand_to_markers function."""
-
-    def test_expands_base64_start_end_markers(self):
-        """Should expand to include ---BASE64_START--- and ---BASE64_END---."""
-        text = "prefix\n---BASE64_START---\nABCDEF\n---BASE64_END---\nsuffix"
-        # Base64 "ABCDEF" is at position 26-32
-        start, end = _expand_to_markers(text, 26, 32)
-        assert text[start:end] == "---BASE64_START---\nABCDEF\n---BASE64_END---"
-
-    def test_expands_bracket_markers(self):
-        """Should expand to include [BASE64] and [/BASE64] markers."""
-        text = "prefix[BASE64]ABCDEF[/BASE64]suffix"
-        # Base64 is at position 14-20
-        start, end = _expand_to_markers(text, 14, 20)
-        assert text[start:end] == "[BASE64]ABCDEF[/BASE64]"
-
-    def test_no_expansion_without_markers(self):
-        """Should not expand if no markers present."""
-        text = "prefix ABCDEF suffix"
-        start, end = _expand_to_markers(text, 7, 13)
-        assert start == 7
-        assert end == 13
-
-
-# =============================================================================
-# Process Binary Outputs Tests
-# =============================================================================
-
-
-@pytest.fixture
-def mock_scan():
-    """Patch virus scanner for tests."""
-    with patch(
-        "backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
-        new_callable=AsyncMock,
-    ) as mock:
-        yield mock
-
-
-class TestProcessBinaryOutputs:
-    """Tests for process_binary_outputs function."""
-
-    @pytest.mark.asyncio
-    async def test_detects_embedded_pdf_in_stdout_logs(
-        self, mock_workspace_manager, mock_scan
-    ):
-        """Should detect and replace embedded PDF in stdout_logs."""
-        pdf_b64 = _make_pdf_base64()
-        stdout = f"PDF generated!\n---BASE64_START---\n{pdf_b64}\n---BASE64_END---\n"
-
-        outputs = {"stdout_logs": [stdout]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "ExecuteCodeBlock"
-        )
-
-        # Should contain workspace reference, not base64
-        assert "workspace://" in result["stdout_logs"][0]
-        assert pdf_b64 not in result["stdout_logs"][0]
-        assert "PDF generated!" in result["stdout_logs"][0]
-        mock_workspace_manager.write_file.assert_called_once()
-
-    @pytest.mark.asyncio
-    async def test_detects_embedded_png_without_markers(
-        self, mock_workspace_manager, mock_scan
-    ):
-        """Should detect embedded PNG even without markers."""
-        png_b64 = _make_png_base64()
-        stdout = f"Image created: {png_b64} done"
-
-        outputs = {"stdout_logs": [stdout]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "ExecuteCodeBlock"
-        )
-
-        assert "workspace://" in result["stdout_logs"][0]
-        assert "Image created:" in result["stdout_logs"][0]
-        assert "done" in result["stdout_logs"][0]
-
-    @pytest.mark.asyncio
-    async def test_preserves_small_strings(self, mock_workspace_manager, mock_scan):
-        """Should not process small strings."""
-        outputs = {"stdout_logs": ["small output"]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "TestBlock"
-        )
-
-        assert result["stdout_logs"][0] == "small output"
-        mock_workspace_manager.write_file.assert_not_called()
-
-    @pytest.mark.asyncio
-    async def test_preserves_non_binary_large_strings(
-        self, mock_workspace_manager, mock_scan
-    ):
-        """Should preserve large strings that don't contain valid binary."""
-        large_text = "A" * 5000  # Large string - decodes to nulls, no magic number
-
-        outputs = {"stdout_logs": [large_text]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "TestBlock"
-        )
-
-        assert result["stdout_logs"][0] == large_text
-        mock_workspace_manager.write_file.assert_not_called()
-
-    @pytest.mark.asyncio
-    async def test_deduplicates_identical_content(
-        self, mock_workspace_manager, mock_scan
-    ):
-        """Should save identical content only once."""
-        pdf_b64 = _make_pdf_base64()
-        stdout1 = f"First: {pdf_b64}"
-        stdout2 = f"Second: {pdf_b64}"
-
-        outputs = {"stdout_logs": [stdout1, stdout2]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "TestBlock"
-        )
-
-        # Both should have references
-        assert "workspace://" in result["stdout_logs"][0]
-        assert "workspace://" in result["stdout_logs"][1]
-        # But only one write
-        assert mock_workspace_manager.write_file.call_count == 1
-
-    @pytest.mark.asyncio
-    async def test_handles_multiple_binaries_in_one_string(
-        self, mock_workspace_manager, mock_scan
-    ):
-        """Should handle multiple embedded binaries in a single string."""
-        pdf_b64 = _make_pdf_base64()
-        png_b64 = _make_png_base64()
-        stdout = f"PDF: {pdf_b64}\nPNG: {png_b64}"
-
-        outputs = {"stdout_logs": [stdout]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "TestBlock"
-        )
-
-        # Should have two workspace references
-        assert result["stdout_logs"][0].count("workspace://") == 2
-        assert mock_workspace_manager.write_file.call_count == 2
-
-    @pytest.mark.asyncio
-    async def test_processes_nested_structures(self, mock_workspace_manager, mock_scan):
-        """Should recursively process nested dicts and lists."""
-        pdf_b64 = _make_pdf_base64()
-
-        outputs = {"result": [{"nested": {"deep": f"data: {pdf_b64}"}}]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "TestBlock"
-        )
-
-        assert "workspace://" in result["result"][0]["nested"]["deep"]
-
-    @pytest.mark.asyncio
-    async def test_graceful_degradation_on_save_failure(
-        self, mock_workspace_manager, mock_scan
-    ):
-        """Should preserve original on save failure."""
-        mock_workspace_manager.write_file = AsyncMock(
-            side_effect=Exception("Storage error")
-        )
-
-        pdf_b64 = _make_pdf_base64()
-        stdout = f"PDF: {pdf_b64}"
-
-        outputs = {"stdout_logs": [stdout]}
-
-        result = await process_binary_outputs(
-            outputs, mock_workspace_manager, "TestBlock"
-        )
-
-        # Should keep original since save failed
-        assert pdf_b64 in result["stdout_logs"][0]
-
-
-# =============================================================================
-# Offset Loop Tests (handling marker bleed-in)
-# =============================================================================
-
-
-class TestOffsetLoopHandling:
-    """Tests for the offset-aligned decoding that handles marker bleed-in."""
-
-    def test_handles_4char_aligned_prefix(self):
-        """Should detect base64 when a 4-char aligned prefix bleeds into match.
-
-        When 'TEST' (4 chars, aligned) bleeds in, offset 4 finds valid base64.
-        """
-        pdf_content = b"%PDF-1.4 " + b"x" * 2000
-        pdf_b64 = base64.b64encode(pdf_content).decode()
-        # 4-char prefix (aligned)
-        with_prefix = f"TEST{pdf_b64}"
-
-        result = _decode_and_validate(with_prefix)
-        assert result is not None
-        content, ext = result
-        assert ext == "pdf"
-        assert content == pdf_content
-
-    def test_handles_8char_aligned_prefix(self):
-        """Should detect base64 when an 8-char prefix bleeds into match."""
-        pdf_content = b"%PDF-1.4 " + b"x" * 2000
-        pdf_b64 = base64.b64encode(pdf_content).decode()
-        # 8-char prefix (aligned)
-        with_prefix = f"TESTTEST{pdf_b64}"
-
-        result = _decode_and_validate(with_prefix)
-        assert result is not None
-        content, ext = result
-        assert ext == "pdf"
-
-    def test_handles_misaligned_prefix(self):
-        """Should handle misaligned prefix by finding a valid aligned offset.
-
-        'START' is 5 chars (misaligned). The loop tries offsets 0, 4, 8...
-        Since characters 0-4 include 'START' which is invalid base64 on its own,
-        we need the full PDF base64 to eventually decode correctly at some offset.
-        """
-        pdf_content = b"%PDF-1.4 " + b"x" * 2000
-        pdf_b64 = base64.b64encode(pdf_content).decode()
-        # 5-char prefix - misaligned, but offset 4 should start mid-'START'
-        # and offset 8 will be past the prefix
-        with_prefix = f"START{pdf_b64}"
-
-        result = _decode_and_validate(with_prefix)
-        # Should find valid PDF at some offset (8 in this case)
-        assert result is not None
-        _, ext = result
-        assert ext == "pdf"
-
-    def test_handles_pdf_base64_start_marker_bleed(self):
-        """Should handle PDF_BASE64_START marker bleeding into regex match.
-
-        This is the real-world case: regex matches 'STARTJVBERi0...' because
-        'START' chars are in the base64 alphabet. Offset loop skips past it.
-        PDF_BASE64_START is 16 chars (4-aligned), so offset 16 finds valid base64.
-        """
-        pdf_content = b"%PDF-1.4 " + b"x" * 2000
-        pdf_b64 = base64.b64encode(pdf_content).decode()
-        # Simulate regex capturing 'PDF_BASE64_START' + base64 together
-        # This happens when there's no delimiter between marker and content
-        with_full_marker = f"PDF_BASE64_START{pdf_b64}"
-
-        result = _decode_and_validate(with_full_marker)
-        assert result is not None
-        _, ext = result
-        assert ext == "pdf"
-
-    def test_clean_base64_works_at_offset_zero(self):
-        """Should detect clean base64 at offset 0 without issues."""
-        pdf_content = b"%PDF-1.4 " + b"x" * 2000
-        pdf_b64 = base64.b64encode(pdf_content).decode()
-
-        result = _decode_and_validate(pdf_b64)
-        assert result is not None
-        content, ext = result
-        assert ext == "pdf"
-        assert content == pdf_content
-
-
-# =============================================================================
-# PDF Marker Tests
-# =============================================================================
-
-
-class TestPdfMarkerExpansion:
-    """Tests for PDF_BASE64_START/END marker handling."""
-
-    def test_expands_pdf_base64_start_marker(self):
-        """Should expand to include PDF_BASE64_START marker."""
-        text = "prefixPDF_BASE64_STARTABCDEF"
-        # Base64 'ABCDEF' is at position 22-28
-        start, end = _expand_to_markers(text, 22, 28)
-        assert text[start:end] == "PDF_BASE64_STARTABCDEF"
-
-    def test_expands_pdf_base64_end_marker(self):
-        """Should expand to include PDF_BASE64_END marker."""
-        text = "ABCDEFPDF_BASE64_ENDsuffix"
-        # Base64 'ABCDEF' is at position 0-6
-        start, end = _expand_to_markers(text, 0, 6)
-        assert text[start:end] == "ABCDEFPDF_BASE64_END"
-
-    def test_expands_both_pdf_markers(self):
-        """Should expand to include both PDF_BASE64_START and END."""
-        text = "xPDF_BASE64_STARTABCDEFPDF_BASE64_ENDy"
-        # Base64 'ABCDEF' is at position 17-23
-        start, end = _expand_to_markers(text, 17, 23)
-        assert text[start:end] == "PDF_BASE64_STARTABCDEFPDF_BASE64_END"
-
-    def test_partial_marker_not_expanded(self):
-        """Should not expand if only partial marker present."""
-        text = "BASE64_STARTABCDEF"  # Missing 'PDF_' prefix
-        start, end = _expand_to_markers(text, 12, 18)
-        # Should not expand since it's not the full marker
-        assert start == 12
-        assert end == 18
-
-    @pytest.mark.asyncio
-    async def test_full_pipeline_with_pdf_markers(self, mock_workspace_manager):
-        """Test full pipeline with PDF_BASE64_START/END markers."""
-        pdf_b64 = _make_pdf_base64()
-        stdout = f"Output: PDF_BASE64_START{pdf_b64}PDF_BASE64_END done"
-
-        outputs = {"stdout_logs": [stdout]}
-
-        with patch(
-            "backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
-            new_callable=AsyncMock,
-        ):
-            result = await process_binary_outputs(
-                outputs, mock_workspace_manager, "TestBlock"
-            )
-
-        # Should have workspace reference
-        assert "workspace://" in result["stdout_logs"][0]
-        # Markers should be consumed along with base64
-        assert "PDF_BASE64_START" not in result["stdout_logs"][0]
-        assert "PDF_BASE64_END" not in result["stdout_logs"][0]
-        # Surrounding text preserved
-        assert "Output:" in result["stdout_logs"][0]
-        assert "done" in result["stdout_logs"][0]
-
-
-# =============================================================================
-# Virus Scanning Tests
-# =============================================================================
-
-
-class TestVirusScanning:
-    """Tests for virus scanning integration."""
-
-    @pytest.mark.asyncio
-    async def test_calls_virus_scanner_before_save(self, mock_workspace_manager):
-        """Should call scan_content_safe before writing file."""
-        pdf_b64 = _make_pdf_base64()
-        stdout = f"PDF: {pdf_b64}"
-        outputs = {"stdout_logs": [stdout]}
-
-        with patch(
-            "backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
-            new_callable=AsyncMock,
-        ) as mock_scan:
-            result = await process_binary_outputs(
-                outputs, mock_workspace_manager, "TestBlock"
-            )
-
-            # Verify scanner was called
-            mock_scan.assert_called_once()
-            # Verify file was written after scan
-            mock_workspace_manager.write_file.assert_called_once()
-            # Verify result has workspace reference
-            assert "workspace://" in result["stdout_logs"][0]
-
-    @pytest.mark.asyncio
-    async def test_virus_scan_failure_preserves_original(self, mock_workspace_manager):
-        """Should preserve original if virus scan fails."""
-        pdf_b64 = _make_pdf_base64()
-        stdout = f"PDF: {pdf_b64}"
-        outputs = {"stdout_logs": [stdout]}
-
-        with patch(
-            "backend.api.features.chat.tools.binary_output_processor.scan_content_safe",
-            new_callable=AsyncMock,
-            side_effect=Exception("Virus detected"),
-        ):
-            result = await process_binary_outputs(
-                outputs, mock_workspace_manager, "TestBlock"
-            )
-
-            # Should keep original since scan failed
-            assert pdf_b64 in result["stdout_logs"][0]
-            # File should not have been written
-            mock_workspace_manager.write_file.assert_not_called()

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

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

autogpt_platform/backend/backend/data/rabbitmq.py

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

autogpt_platform/backend/poetry.lock

@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 2.1.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.2.1 and should not be changed by hand.
 
 [[package]]
 name = "aio-pika"
@@ -374,7 +374,7 @@ description = "LTS Port of Python audioop"
 optional = false
 python-versions = ">=3.13"
 groups = ["main"]
-markers = "python_version >= \"3.13\""
+markers = "python_version == \"3.13\""
 files = [
     {file = "audioop_lts-0.2.2-cp313-abi3-macosx_10_13_universal2.whl", hash = "sha256:fd3d4602dc64914d462924a08c1a9816435a2155d74f325853c1f1ac3b2d9800"},
     {file = "audioop_lts-0.2.2-cp313-abi3-macosx_10_13_x86_64.whl", hash = "sha256:550c114a8df0aafe9a05442a1162dfc8fec37e9af1d625ae6060fed6e756f303"},
@@ -474,7 +474,7 @@ description = "Backport of asyncio.Runner, a context manager that controls event
 optional = false
 python-versions = "<3.11,>=3.8"
 groups = ["main"]
-markers = "python_version < \"3.11\""
+markers = "python_version == \"3.10\""
 files = [
     {file = "backports_asyncio_runner-1.2.0-py3-none-any.whl", hash = "sha256:0da0a936a8aeb554eccb426dc55af3ba63bcdc69fa1a600b5bb305413a4477b5"},
     {file = "backports_asyncio_runner-1.2.0.tar.gz", hash = "sha256:a5aa7b2b7d8f8bfcaa2b57313f70792df84e32a2a746f585213373f900b42162"},
@@ -487,7 +487,7 @@ description = "Backport of CPython tarfile module"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "python_version <= \"3.11\""
+markers = "python_version < \"3.12\""
 files = [
     {file = "backports.tarfile-1.2.0-py3-none-any.whl", hash = "sha256:77e284d754527b01fb1e6fa8a1afe577858ebe4e9dad8919e34c862cb399bc34"},
     {file = "backports_tarfile-1.2.0.tar.gz", hash = "sha256:d75e02c268746e1b8144c278978b6e98e85de6ad16f8e4b0844a154557eca991"},
@@ -563,6 +563,18 @@ webencodings = "*"
 [package.extras]
 css = ["tinycss2 (>=1.1.0,<1.5)"]
 
+[[package]]
+name = "bracex"
+version = "2.6"
+description = "Bash style brace expander."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "bracex-2.6-py3-none-any.whl", hash = "sha256:0b0049264e7340b3ec782b5cb99beb325f36c3782a32e36e876452fd49a09952"},
+    {file = "bracex-2.6.tar.gz", hash = "sha256:98f1347cd77e22ee8d967a30ad4e310b233f7754dbf31ff3fceb76145ba47dc7"},
+]
+
 [[package]]
 name = "browserbase"
 version = "1.4.0"
@@ -659,7 +671,6 @@ description = "Foreign Function Interface for Python calling C code."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
-markers = "platform_python_implementation != \"PyPy\" or sys_platform == \"darwin\""
 files = [
     {file = "cffi-2.0.0-cp310-cp310-macosx_10_13_x86_64.whl", hash = "sha256:0cf2d91ecc3fcc0625c2c530fe004f82c110405f101548512cce44322fa8ac44"},
     {file = "cffi-2.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f73b96c41e3b2adedc34a7356e64c8eb96e03a3782b535e043a986276ce12a49"},
@@ -1149,6 +1160,18 @@ idna = ["idna (>=3.10)"]
 trio = ["trio (>=0.30)"]
 wmi = ["wmi (>=1.5.1) ; platform_system == \"Windows\""]
 
+[[package]]
+name = "dockerfile-parse"
+version = "2.0.1"
+description = "Python library for Dockerfile manipulation"
+optional = false
+python-versions = ">=3.6"
+groups = ["main"]
+files = [
+    {file = "dockerfile-parse-2.0.1.tar.gz", hash = "sha256:3184ccdc513221983e503ac00e1aa504a2aa8f84e5de673c46b0b6eee99ec7bc"},
+    {file = "dockerfile_parse-2.0.1-py2.py3-none-any.whl", hash = "sha256:bdffd126d2eb26acf1066acb54cb2e336682e1d72b974a40894fac76a4df17f6"},
+]
+
 [[package]]
 name = "docstring-parser"
 version = "0.17.0"
@@ -1235,40 +1258,43 @@ pgp = ["gpg"]
 
 [[package]]
 name = "e2b"
-version = "1.11.1"
+version = "2.13.2"
 description = "E2B SDK that give agents cloud environments"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = "<4.0,>=3.10"
 groups = ["main"]
 files = [
-    {file = "e2b-1.11.1-py3-none-any.whl", hash = "sha256:1ecb123873788472731c101939a494ab852cbcce0f913df6f7ecb194ae932130"},
-    {file = "e2b-1.11.1.tar.gz", hash = "sha256:7f7b6f238208d0a23353bb0da01f91a924321b57c61b176506862cbc1493ce8c"},
+    {file = "e2b-2.13.2-py3-none-any.whl", hash = "sha256:d91d5293bc0dd1917c72a6e6b35e86513607be2666a14ae18c57b921e7864de4"},
+    {file = "e2b-2.13.2.tar.gz", hash = "sha256:c0e81a3920091874fdf73c0b8f376b28766212db9f1cea5d8bd56a2e95d2436c"},
 ]
 
 [package.dependencies]
 attrs = ">=23.2.0"
+dockerfile-parse = ">=2.0.1,<3.0.0"
 httpcore = ">=1.0.5,<2.0.0"
 httpx = ">=0.27.0,<1.0.0"
 packaging = ">=24.1"
 protobuf = ">=4.21.0"
 python-dateutil = ">=2.8.2"
+rich = ">=14.0.0"
 typing-extensions = ">=4.1.0"
+wcmatch = ">=10.1,<11.0"
 
 [[package]]
 name = "e2b-code-interpreter"
-version = "1.5.2"
+version = "2.4.1"
 description = "E2B Code Interpreter - Stateful code execution"
 optional = false
 python-versions = "<4.0,>=3.9"
 groups = ["main"]
 files = [
-    {file = "e2b_code_interpreter-1.5.2-py3-none-any.whl", hash = "sha256:5c3188d8f25226b28fef4b255447cc6a4c36afb748bdd5180b45be486d5169f3"},
-    {file = "e2b_code_interpreter-1.5.2.tar.gz", hash = "sha256:3bd6ea70596290e85aaf0a2f19f28bf37a5e73d13086f5e6a0080bb591c5a547"},
+    {file = "e2b_code_interpreter-2.4.1-py3-none-any.whl", hash = "sha256:15d35f025b4a15033e119f2e12e7ac65657ad2b5a013fa9149e74581fbee778a"},
+    {file = "e2b_code_interpreter-2.4.1.tar.gz", hash = "sha256:4b15014ee0d0dfcdc3072e1f409cbb87ca48f48d53d75629b7257e5513b9e7dd"},
 ]
 
 [package.dependencies]
 attrs = ">=21.3.0"
-e2b = ">=1.5.4,<2.0.0"
+e2b = ">=2.7.0,<3.0.0"
 httpx = ">=0.20.0,<1.0.0"
 
 [[package]]
@@ -1338,7 +1364,7 @@ description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 groups = ["main", "dev"]
-markers = "python_version < \"3.11\""
+markers = "python_version == \"3.10\""
 files = [
     {file = "exceptiongroup-1.3.1-py3-none-any.whl", hash = "sha256:a7a39a3bd276781e98394987d3a5701d0c4edffb633bb7a5144577f82c773598"},
     {file = "exceptiongroup-1.3.1.tar.gz", hash = "sha256:8b412432c6055b0b7d14c310000ae93352ed6754f70fa8f7c34141f91c4e3219"},
@@ -1820,16 +1846,16 @@ files = [
 google-auth = ">=2.14.1,<3.0.0"
 googleapis-common-protos = ">=1.56.2,<2.0.0"
 grpcio = [
-    {version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""},
     {version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""},
 ]
 grpcio-status = [
-    {version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""},
     {version = ">=1.49.1,<2.0.0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""},
+    {version = ">=1.33.2,<2.0.0", optional = true, markers = "extra == \"grpc\""},
 ]
 proto-plus = [
-    {version = ">=1.22.3,<2.0.0"},
     {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
+    {version = ">=1.22.3,<2.0.0"},
 ]
 protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 requests = ">=2.18.0,<3.0.0"
@@ -1940,8 +1966,8 @@ google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0", extras
 google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0"
 grpcio = ">=1.33.2,<2.0.0"
 proto-plus = [
-    {version = ">=1.22.3,<2.0.0"},
     {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
+    {version = ">=1.22.3,<2.0.0"},
 ]
 protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
@@ -2001,9 +2027,9 @@ google-cloud-core = ">=2.0.0,<3.0.0"
 grpc-google-iam-v1 = ">=0.12.4,<1.0.0"
 opentelemetry-api = ">=1.9.0"
 proto-plus = [
-    {version = ">=1.22.0,<2.0.0"},
-    {version = ">=1.22.2,<2.0.0", markers = "python_version >= \"3.11\""},
     {version = ">=1.25.0,<2.0.0", markers = "python_version >= \"3.13\""},
+    {version = ">=1.22.2,<2.0.0", markers = "python_version >= \"3.11\" and python_version < \"3.13\""},
+    {version = ">=1.22.0,<2.0.0", markers = "python_version < \"3.11\""},
 ]
 protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
@@ -3802,7 +3828,7 @@ description = "Fundamental package for array computing in Python"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
-markers = "python_version < \"3.11\""
+markers = "python_version == \"3.10\""
 files = [
     {file = "numpy-2.2.6-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:b412caa66f72040e6d268491a59f2c43bf03eb6c96dd8f0307829feb7fa2b6fb"},
     {file = "numpy-2.2.6-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8e41fd67c52b86603a91c1a505ebaef50b3314de0213461c7a6e99c9a3beff90"},
@@ -4287,9 +4313,9 @@ files = [
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
-    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
     {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
+    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -4532,8 +4558,8 @@ pinecone-plugin-interface = ">=0.0.7,<0.0.8"
 python-dateutil = ">=2.5.3"
 typing-extensions = ">=3.7.4"
 urllib3 = [
-    {version = ">=1.26.0", markers = "python_version >= \"3.8\" and python_version < \"3.12\""},
     {version = ">=1.26.5", markers = "python_version >= \"3.12\" and python_version < \"4.0\""},
+    {version = ">=1.26.0", markers = "python_version >= \"3.8\" and python_version < \"3.12\""},
 ]
 
 [package.extras]
@@ -5361,7 +5387,7 @@ description = "C parser in Python"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
-markers = "(platform_python_implementation != \"PyPy\" or sys_platform == \"darwin\") and implementation_name != \"PyPy\""
+markers = "implementation_name != \"PyPy\""
 files = [
     {file = "pycparser-3.0-py3-none-any.whl", hash = "sha256:b727414169a36b7d524c1c3e31839a521725078d7b2ff038656844266160a992"},
     {file = "pycparser-3.0.tar.gz", hash = "sha256:600f49d217304a5902ac3c37e1281c9fe94e4d0489de643a9504c5cdfdfc6b29"},
@@ -6130,10 +6156,10 @@ files = [
 grpcio = ">=1.41.0"
 httpx = {version = ">=0.20.0", extras = ["http2"]}
 numpy = [
-    {version = ">=1.21,<2.3.0", markers = "python_version == \"3.10\""},
-    {version = ">=1.21", markers = "python_version == \"3.11\""},
     {version = ">=2.1.0", markers = "python_version == \"3.13\""},
+    {version = ">=1.21", markers = "python_version == \"3.11\""},
     {version = ">=1.26", markers = "python_version == \"3.12\""},
+    {version = ">=1.21,<2.3.0", markers = "python_version == \"3.10\""},
 ]
 portalocker = ">=2.7.0,<4.0"
 protobuf = ">=3.20.0"
@@ -7317,7 +7343,7 @@ description = "A lil' TOML parser"
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
-markers = "python_version < \"3.11\""
+markers = "python_version == \"3.10\""
 files = [
     {file = "tomli-2.4.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b5ef256a3fd497d4973c11bf142e9ed78b150d36f5773f1ca6088c230ffc5867"},
     {file = "tomli-2.4.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5572e41282d5268eb09a697c89a7bee84fae66511f87533a6f88bd2f7b652da9"},
@@ -7841,6 +7867,21 @@ files = [
 [package.dependencies]
 anyio = ">=3.0.0"
 
+[[package]]
+name = "wcmatch"
+version = "10.1"
+description = "Wildcard/glob file name matcher."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "wcmatch-10.1-py3-none-any.whl", hash = "sha256:5848ace7dbb0476e5e55ab63c6bbd529745089343427caa5537f230cc01beb8a"},
+    {file = "wcmatch-10.1.tar.gz", hash = "sha256:f11f94208c8c8484a16f4f48638a85d771d9513f4ab3f37595978801cb9465af"},
+]
+
+[package.dependencies]
+bracex = ">=2.1.1"
+
 [[package]]
 name = "webencodings"
 version = "0.5.1"
@@ -8440,4 +8481,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.14"
-content-hash = "14686ee0e2dc446a75d0db145b08dc410dc31c357e25085bb0f9b0174711c4b1"
+content-hash = "f1f229017d133bab1cb5b787a93f8d6d652c2712e07d4966358e725a57e35e80"

autogpt_platform/backend/pyproject.toml

@@ -19,7 +19,7 @@ bleach = { extras = ["css"], version = "^6.2.0" }
 click = "^8.2.0"
 cryptography = "^46.0"
 discord-py = "^2.5.2"
-e2b-code-interpreter = "^1.5.2"
+e2b-code-interpreter = "^2.4.1"
 elevenlabs = "^1.50.0"
 fastapi = "^0.128.5"
 feedparser = "^6.0.11"

autogpt_platform/frontend/src/components/atoms/FileInput/FileInput.tsx

@@ -104,7 +104,31 @@ export function FileInput(props: Props) {
     return false;
   }
 
-  const getFileLabelFromValue = (val: string) => {
+  const getFileLabelFromValue = (val: unknown): string => {
+    // Handle object format from external API: { name, type, size, data }
+    if (val && typeof val === "object") {
+      const obj = val as Record<string, unknown>;
+      if (typeof obj.name === "string") {
+        return getFileLabel(
+          obj.name,
+          typeof obj.type === "string" ? obj.type : "",
+        );
+      }
+      if (typeof obj.type === "string") {
+        const mimeParts = obj.type.split("/");
+        if (mimeParts.length > 1) {
+          return `${mimeParts[1].toUpperCase()} file`;
+        }
+        return `${obj.type} file`;
+      }
+      return "File";
+    }
+
+    // Handle string values (data URIs or file paths)
+    if (typeof val !== "string") {
+      return "File";
+    }
+
     if (val.startsWith("data:")) {
       const matches = val.match(/^data:([^;]+);/);
       if (matches?.[1]) {