fix(copilot): disable input during submission and fix timeout logic

- Disable input when status='submitted' to prevent message spam - Set stream start timeout to 30s (only detects backend down, doesn't affect tool execution) - Once stream starts, tools can run indefinitely (timeout is cleared) - Mini-game shows during long-running tool execution without timeout
fix(copilot): increase stream timeout from 12s to 60s
2026-02-24 03:00:28 -05:00 · 2026-02-21 20:45:47 +07:00 · 2026-02-21 20:39:48 +07:00 · 2026-02-21 20:09:40 +07:00 · 2026-02-21 19:59:26 +07:00 · 2026-02-21 19:48:21 +07:00
33 changed files with 1823 additions and 753 deletions
--- a/autogpt_platform/backend/.application.logs
+++ b/autogpt_platform/backend/.application.logs
@@ -0,0 +1,572 @@
+2026-02-21 20:31:19,811 [34mINFO[0m  Initializing LaunchDarkly Client 9.15.0
+2026-02-21 20:31:19,812 [34mINFO[0m  Starting event processor
+2026-02-21 20:31:19,812 [34mINFO[0m  Starting StreamingUpdateProcessor connecting to uri: https://stream.launchdarkly.com/all
+2026-02-21 20:31:19,812 [34mINFO[0m  Waiting up to 5 seconds for LaunchDarkly client to initialize...
+2026-02-21 20:31:19,812 [34mINFO[0m  Connecting to stream at https://stream.launchdarkly.com/all
+2026-02-21 20:31:20,051 [34mINFO[0m  StreamingUpdateProcessor initialized ok.
+2026-02-21 20:31:20,051 [34mINFO[0m  Started LaunchDarkly Client: OK
+2026-02-21 20:31:20,051 [34mINFO[0m  LaunchDarkly client initialized successfully
+2026-02-21 20:31:21,578 [33mWARNING[0m  [33mProvider LINEAR implements OAuth but the required env vars LINEAR_CLIENT_ID and LINEAR_CLIENT_SECRET are not both set[0m
+2026-02-21 20:31:21,623 [33mWARNING[0m  [33mAuthentication error: Langfuse client initialized without public_key. Client will be disabled. Provide a public_key parameter or set LANGFUSE_PUBLIC_KEY environment variable. [0m
+2026-02-21 20:31:21,796 [34mINFO[0m  Metrics endpoint exposed at /metrics for external-api
+2026-02-21 20:31:21,800 [34mINFO[0m  Metrics endpoint exposed at /metrics for rest-api
+2026-02-21 20:31:21,881 [34mINFO[0m  Metrics endpoint exposed at /metrics for websocket-server
+2026-02-21 20:31:21,913 [33mWARNING[0m  [33mPostmark server API token not found, email sending disabled[0m
+2026-02-21 20:31:21,956 [34mINFO[0m  [DatabaseManager] started with PID 6089
+2026-02-21 20:31:21,958 [34mINFO[0m  [Scheduler] started with PID 6090
+2026-02-21 20:31:21,959 [34mINFO[0m  [NotificationManager] started with PID 6091
+2026-02-21 20:31:21,960 [34mINFO[0m  [WebsocketServer] started with PID 6092
+2026-02-21 20:31:21,961 [34mINFO[0m  [AgentServer] started with PID 6093
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+2026-02-21 20:31:21,971 [34mINFO[0m  [PID-6048|THREAD-77685506|CoPilotExecutor|RabbitMQ-124e33d7-4877-4745-9778-6b6b06de92d2] Acquiring connection started...
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+2026-02-21 20:31:21,973 [34mINFO[0m  Pika version 1.3.2 connecting to ('::1', 5672, 0, 0)
+2026-02-21 20:31:21,974 [34mINFO[0m  Socket connected: <socket.socket fd=30, family=30, type=1, proto=6, laddr=('::1', 55999, 0, 0), raddr=('::1', 5672, 0, 0)>
+2026-02-21 20:31:21,975 [34mINFO[0m  Socket connected: <socket.socket fd=29, family=30, type=1, proto=6, laddr=('::1', 55998, 0, 0), raddr=('::1', 5672, 0, 0)>
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+2026-02-21 20:31:21,976 [34mINFO[0m  Streaming transport linked up: (<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x120fa0410>, _StreamingProtocolShim: <SelectConnection PROTOCOL transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x120fa0410> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>).
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+2026-02-21 20:31:21,991 [34mINFO[0m  AMQPConnector - reporting success: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x120f5eba0> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:21,991 [34mINFO[0m  Connection workflow succeeded: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x120fa0410> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:21,991 [34mINFO[0m  AMQPConnectionWorkflow - reporting success: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x120f5eba0> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:21,991 [34mINFO[0m  Created channel=1
+2026-02-21 20:31:21,992 [34mINFO[0m  Connection workflow succeeded: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x120f5eba0> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:21,992 [34mINFO[0m  Created channel=1
+2026-02-21 20:31:22,005 [34mINFO[0m  [PID-6048|THREAD-77685505|CoPilotExecutor|RabbitMQ-124e33d7-4877-4745-9778-6b6b06de92d2] Acquiring connection completed successfully.
+2026-02-21 20:31:22,005 [34mINFO[0m  [PID-6048|THREAD-77685506|CoPilotExecutor|RabbitMQ-124e33d7-4877-4745-9778-6b6b06de92d2] Acquiring connection completed successfully.
+2026-02-21 20:31:22,007 [34mINFO[0m  [CoPilotExecutor] Starting to consume cancel messages... 
+2026-02-21 20:31:22,008 [34mINFO[0m  [CoPilotExecutor] Starting to consume run messages... 
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+2026-02-21 20:31:23,201 [34mINFO[0m  Starting event processor
+2026-02-21 20:31:23,202 [34mINFO[0m  Starting StreamingUpdateProcessor connecting to uri: https://stream.launchdarkly.com/all
+2026-02-21 20:31:23,202 [34mINFO[0m  Waiting up to 5 seconds for LaunchDarkly client to initialize...
+2026-02-21 20:31:23,202 [34mINFO[0m  Connecting to stream at https://stream.launchdarkly.com/all
+2026-02-21 20:31:23,331 [34mINFO[0m  StreamingUpdateProcessor initialized ok.
+2026-02-21 20:31:23,331 [34mINFO[0m  Started LaunchDarkly Client: OK
+2026-02-21 20:31:23,332 [34mINFO[0m  LaunchDarkly client initialized successfully
+2026-02-21 20:31:23,891 [34mINFO[0m  Initializing LaunchDarkly Client 9.15.0
+2026-02-21 20:31:23,892 [34mINFO[0m  Starting event processor
+2026-02-21 20:31:23,893 [34mINFO[0m  Starting StreamingUpdateProcessor connecting to uri: https://stream.launchdarkly.com/all
+2026-02-21 20:31:23,893 [34mINFO[0m  Waiting up to 5 seconds for LaunchDarkly client to initialize...
+2026-02-21 20:31:23,893 [34mINFO[0m  Connecting to stream at https://stream.launchdarkly.com/all
+2026-02-21 20:31:23,946 [34mINFO[0m  Initializing LaunchDarkly Client 9.15.0
+2026-02-21 20:31:23,947 [34mINFO[0m  Starting event processor
+2026-02-21 20:31:23,947 [34mINFO[0m  Starting StreamingUpdateProcessor connecting to uri: https://stream.launchdarkly.com/all
+2026-02-21 20:31:23,947 [34mINFO[0m  Waiting up to 5 seconds for LaunchDarkly client to initialize...
+2026-02-21 20:31:23,948 [34mINFO[0m  Connecting to stream at https://stream.launchdarkly.com/all
+2026-02-21 20:31:24,017 [34mINFO[0m  StreamingUpdateProcessor initialized ok.
+2026-02-21 20:31:24,017 [34mINFO[0m  Started LaunchDarkly Client: OK
+2026-02-21 20:31:24,017 [34mINFO[0m  LaunchDarkly client initialized successfully
+2026-02-21 20:31:24,065 [34mINFO[0m  StreamingUpdateProcessor initialized ok.
+2026-02-21 20:31:24,065 [34mINFO[0m  Started LaunchDarkly Client: OK
+2026-02-21 20:31:24,065 [34mINFO[0m  LaunchDarkly client initialized successfully
+2026-02-21 20:31:24,707 [34mINFO[0m  [NotificationManager] Starting...
+2026-02-21 20:31:24,750 [34mINFO[0m  Metrics endpoint exposed at /metrics for NotificationManager
+2026-02-21 20:31:24,754 [34mINFO[0m  [PID-6091|THREAD-77685702|NotificationManager|FastAPI server-d17271ed-e3a2-4e93-900b-a0d3bd2b8100] Running FastAPI server started...
+2026-02-21 20:31:24,755 [34mINFO[0m  [NotificationManager] Starting RPC server at http://localhost:8007
+2026-02-21 20:31:24,756 [34mINFO[0m  [NotificationManager] [NotificationManager] ⏳ Configuring RabbitMQ... 
+2026-02-21 20:31:24,757 [34mINFO[0m  [PID-6091|THREAD-77685703|NotificationManager|AsyncRabbitMQ-7963c91c-c443-4479-a55e-5e9a8d7d942d] Acquiring async connection started...
+2026-02-21 20:31:24,775 [34mINFO[0m  Started server process [6091]
+2026-02-21 20:31:24,775 [34mINFO[0m  Waiting for application startup.
+2026-02-21 20:31:24,776 [34mINFO[0m  Application startup complete.
+2026-02-21 20:31:24,777 [31mERROR[0m  [31m[Errno 48] error while attempting to bind on address ('::1', 8007, 0, 0): [errno 48] address already in use[0m
+2026-02-21 20:31:24,781 [34mINFO[0m  Waiting for application shutdown.
+2026-02-21 20:31:24,781 [34mINFO[0m  [NotificationManager] ✅ FastAPI has finished
+2026-02-21 20:31:24,782 [34mINFO[0m  Application shutdown complete.
+2026-02-21 20:31:24,783 [34mINFO[0m  [NotificationManager] 🛑 Shared event loop stopped
+2026-02-21 20:31:24,783 [34mINFO[0m  [NotificationManager] 🧹 Running cleanup
+2026-02-21 20:31:24,783 [34mINFO[0m  [NotificationManager] ⏳ Disconnecting RabbitMQ... 
+Process NotificationManager:
+Traceback (most recent call last):
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/multiprocessing/process.py", line 313, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/util/process.py", line 83, in execute_run_command
+    self.cleanup()
+    ~~~~~~~~~~~~^^
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/notifications/notifications.py", line 1094, in cleanup
+    self.run_and_wait(self.rabbitmq_service.disconnect())
+    ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/util/service.py", line 136, in run_and_wait
+    return asyncio.run_coroutine_threadsafe(coro, self.shared_event_loop).result()
+           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/asyncio/tasks.py", line 1003, in run_coroutine_threadsafe
+    loop.call_soon_threadsafe(callback)
+    ~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/asyncio/base_events.py", line 873, in call_soon_threadsafe
+    self._check_closed()
+    ~~~~~~~~~~~~~~~~~~^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/asyncio/base_events.py", line 551, in _check_closed
+    raise RuntimeError('Event loop is closed')
+RuntimeError: Event loop is closed
+/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/multiprocessing/process.py:327: RuntimeWarning: coroutine 'AsyncRabbitMQ.disconnect' was never awaited
+  traceback.print_exc()
+RuntimeWarning: Enable tracemalloc to get the object allocation traceback
+2026-02-21 20:31:24,846 [34mINFO[0m  Initializing LaunchDarkly Client 9.15.0
+2026-02-21 20:31:24,848 [34mINFO[0m  Starting event processor
+2026-02-21 20:31:24,848 [34mINFO[0m  Starting StreamingUpdateProcessor connecting to uri: https://stream.launchdarkly.com/all
+2026-02-21 20:31:24,849 [34mINFO[0m  Waiting up to 5 seconds for LaunchDarkly client to initialize...
+2026-02-21 20:31:24,849 [34mINFO[0m  Connecting to stream at https://stream.launchdarkly.com/all
+2026-02-21 20:31:24,857 [34mINFO[0m  Initializing LaunchDarkly Client 9.15.0
+2026-02-21 20:31:24,858 [34mINFO[0m  Starting event processor
+2026-02-21 20:31:24,858 [34mINFO[0m  Starting StreamingUpdateProcessor connecting to uri: https://stream.launchdarkly.com/all
+2026-02-21 20:31:24,858 [34mINFO[0m  Waiting up to 5 seconds for LaunchDarkly client to initialize...
+2026-02-21 20:31:24,858 [34mINFO[0m  Connecting to stream at https://stream.launchdarkly.com/all
+2026-02-21 20:31:24,862 [34mINFO[0m  Initializing LaunchDarkly Client 9.15.0
+2026-02-21 20:31:24,863 [34mINFO[0m  Starting event processor
+2026-02-21 20:31:24,864 [34mINFO[0m  Starting StreamingUpdateProcessor connecting to uri: https://stream.launchdarkly.com/all
+2026-02-21 20:31:24,864 [34mINFO[0m  Waiting up to 5 seconds for LaunchDarkly client to initialize...
+2026-02-21 20:31:24,864 [34mINFO[0m  Connecting to stream at https://stream.launchdarkly.com/all
+2026-02-21 20:31:24,966 [34mINFO[0m  StreamingUpdateProcessor initialized ok.
+2026-02-21 20:31:24,967 [34mINFO[0m  Started LaunchDarkly Client: OK
+2026-02-21 20:31:24,967 [34mINFO[0m  LaunchDarkly client initialized successfully
+2026-02-21 20:31:24,976 [34mINFO[0m  StreamingUpdateProcessor initialized ok.
+2026-02-21 20:31:24,976 [34mINFO[0m  Started LaunchDarkly Client: OK
+2026-02-21 20:31:24,976 [34mINFO[0m  LaunchDarkly client initialized successfully
+2026-02-21 20:31:24,989 [34mINFO[0m  StreamingUpdateProcessor initialized ok.
+2026-02-21 20:31:24,989 [34mINFO[0m  Started LaunchDarkly Client: OK
+2026-02-21 20:31:24,989 [34mINFO[0m  LaunchDarkly client initialized successfully
+2026-02-21 20:31:25,035 [34mINFO[0m  Metrics endpoint exposed at /metrics for websocket-server
+2026-02-21 20:31:25,036 [34mINFO[0m  [WebsocketServer] Starting...
+2026-02-21 20:31:25,036 [34mINFO[0m  CORS allow origins: ['http://localhost:3000', 'http://127.0.0.1:3000']
+2026-02-21 20:31:25,076 [34mINFO[0m  Started server process [6092]
+2026-02-21 20:31:25,076 [34mINFO[0m  Waiting for application startup.
+2026-02-21 20:31:25,077 [34mINFO[0m  Application startup complete.
+2026-02-21 20:31:25,077 [34mINFO[0m  [PID-6092|THREAD-77685501|WebsocketServer|AsyncRedis-b6fb3c5c-0070-4c5c-90eb-922d4f2152c2] Acquiring connection started...
+2026-02-21 20:31:25,077 [34mINFO[0m  [PID-6092|THREAD-77685501|WebsocketServer|AsyncRedis-b6fb3c5c-0070-4c5c-90eb-922d4f2152c2] Acquiring connection started...
+2026-02-21 20:31:25,078 [31mERROR[0m  [31m[Errno 48] error while attempting to bind on address ('0.0.0.0', 8001): address already in use[0m
+2026-02-21 20:31:25,080 [34mINFO[0m  Waiting for application shutdown.
+2026-02-21 20:31:25,080 [34mINFO[0m  Application shutdown complete.
+2026-02-21 20:31:25,080 [34mINFO[0m  Event broadcaster stopped
+2026-02-21 20:31:25,081 [33mWARNING[0m  [33m[WebsocketServer] 🛑 Terminating because of SystemExit: 1[0m
+2026-02-21 20:31:25,081 [34mINFO[0m  [WebsocketServer] 🧹 Running cleanup
+2026-02-21 20:31:25,081 [34mINFO[0m  [WebsocketServer] ✅ Cleanup done
+2026-02-21 20:31:25,081 [34mINFO[0m  [WebsocketServer] 🛑 Terminated
+2026-02-21 20:31:25,915 [34mINFO[0m  [DatabaseManager] Starting...
+2026-02-21 20:31:25,947 [34mINFO[0m  Metrics endpoint exposed at /metrics for DatabaseManager
+2026-02-21 20:31:25,970 [34mINFO[0m  [ExecutionManager] Starting...
+2026-02-21 20:31:25,970 [34mINFO[0m  [GraphExecutor] [ExecutionManager] 🆔 Pod assigned executor_id: 90ff5962-bdc8-456d-a864-01c5f4f199bd 
+2026-02-21 20:31:25,971 [34mINFO[0m  [GraphExecutor] [ExecutionManager] ⏳ Spawn max-10 workers... 
+2026-02-21 20:31:25,973 [34mINFO[0m  [Scheduler] Starting...
+2026-02-21 20:31:25,971 [33mWARNING[0m  [33m[ExecutionManager] 🛑 Terminating because of OSError: [Errno 48] Address already in use[0m
+Traceback (most recent call last):
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/util/process.py", line 65, in execute_run_command
+    self.run()
+    ~~~~~~~~^^
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/executor/manager.py", line 1554, in run
+    start_http_server(settings.config.execution_manager_port)
+    ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/prometheus_client/exposition.py", line 251, in start_wsgi_server
+    httpd = make_server(addr, port, app, TmpServer, handler_class=_SilentHandler)
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/wsgiref/simple_server.py", line 150, in make_server
+    server = server_class((host, port), handler_class)
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/socketserver.py", line 457, in __init__
+    self.server_bind()
+    ~~~~~~~~~~~~~~~~^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/wsgiref/simple_server.py", line 50, in server_bind
+    HTTPServer.server_bind(self)
+    ~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/http/server.py", line 136, in server_bind
+    socketserver.TCPServer.server_bind(self)
+    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/socketserver.py", line 473, in server_bind
+    self.socket.bind(self.server_address)
+    ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^
+OSError: [Errno 48] Address already in use
+2026-02-21 20:31:25,978 [34mINFO[0m  [ExecutionManager] 🧹 Running cleanup
+2026-02-21 20:31:25,978 [34mINFO[0m  [GraphExecutor] [ExecutionManager][on_graph_executor_stop 6094] 🧹 Starting graceful shutdown... 
+2026-02-21 20:31:25,978 [34mINFO[0m  [PID-6094|THREAD-77685503|ExecutionManager|RabbitMQ-5b203f2b-8b80-46b1-8e47-481497e68a82] Acquiring connection started...
+2026-02-21 20:31:25,980 [34mINFO[0m  Pika version 1.3.2 connecting to ('::1', 5672, 0, 0)
+2026-02-21 20:31:25,981 [34mINFO[0m  Socket connected: <socket.socket fd=14, family=30, type=1, proto=6, laddr=('::1', 56040, 0, 0), raddr=('::1', 5672, 0, 0)>
+2026-02-21 20:31:25,982 [34mINFO[0m  Streaming transport linked up: (<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1316cd550>, _StreamingProtocolShim: <SelectConnection PROTOCOL transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1316cd550> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>).
+2026-02-21 20:31:25,991 [34mINFO[0m  AMQPConnector - reporting success: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1316cd550> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:25,991 [34mINFO[0m  AMQPConnectionWorkflow - reporting success: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1316cd550> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:25,991 [34mINFO[0m  Connection workflow succeeded: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1316cd550> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:25,991 [34mINFO[0m  Created channel=1
+2026-02-21 20:31:26,001 [34mINFO[0m  [PID-6094|THREAD-77685503|ExecutionManager|RabbitMQ-5b203f2b-8b80-46b1-8e47-481497e68a82] Acquiring connection completed successfully.
+2026-02-21 20:31:26,001 [34mINFO[0m  [GraphExecutor] [ExecutionManager][on_graph_executor_stop 6094] ✅ Exec consumer has been signaled to stop 
+2026-02-21 20:31:26,001 [34mINFO[0m  [GraphExecutor] [ExecutionManager][on_graph_executor_stop 6094] ✅ Executor shutdown completed 
+2026-02-21 20:31:26,001 [34mINFO[0m  [GraphExecutor] [ExecutionManager][on_graph_executor_stop 6094] ✅ Released execution locks 
+2026-02-21 20:31:26,001 [31mERROR[0m  [31m[GraphExecutor] [ExecutionManager][on_graph_executor_stop 6094] [run-consumer] ⚠️ Error disconnecting run client: <class 'RuntimeError'> cannot join thread before it is started [0m
+2026-02-21 20:31:26,003 [34mINFO[0m  [PID-6094|THREAD-77685503|ExecutionManager|RabbitMQ-5b203f2b-8b80-46b1-8e47-481497e68a82] Acquiring connection started...
+2026-02-21 20:31:26,005 [34mINFO[0m  Pika version 1.3.2 connecting to ('::1', 5672, 0, 0)
+2026-02-21 20:31:26,005 [34mINFO[0m  Socket connected: <socket.socket fd=20, family=30, type=1, proto=6, laddr=('::1', 56043, 0, 0), raddr=('::1', 5672, 0, 0)>
+2026-02-21 20:31:26,006 [34mINFO[0m  Streaming transport linked up: (<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1318e4cd0>, _StreamingProtocolShim: <SelectConnection PROTOCOL transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1318e4cd0> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>).
+2026-02-21 20:31:26,009 [34mINFO[0m  Metrics endpoint exposed at /metrics for Scheduler
+2026-02-21 20:31:26,010 [34mINFO[0m  AMQPConnector - reporting success: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1318e4cd0> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:26,010 [34mINFO[0m  AMQPConnectionWorkflow - reporting success: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1318e4cd0> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:26,010 [34mINFO[0m  Connection workflow succeeded: <SelectConnection OPEN transport=<pika.adapters.utils.io_services_utils._AsyncPlaintextTransport object at 0x1318e4cd0> params=<ConnectionParameters host=localhost port=5672 virtual_host=/ ssl=False>>
+2026-02-21 20:31:26,011 [34mINFO[0m  Created channel=1
+2026-02-21 20:31:26,015 [34mINFO[0m  [PID-6090|THREAD-77685897|Scheduler|FastAPI server-6caca9cc-c4c1-417f-8b83-d96f02472df9] Running FastAPI server started...
+2026-02-21 20:31:26,016 [34mINFO[0m  [Scheduler] Starting RPC server at http://localhost:8003
+2026-02-21 20:31:26,016 [34mINFO[0m  [PID-6094|THREAD-77685503|ExecutionManager|RabbitMQ-5b203f2b-8b80-46b1-8e47-481497e68a82] Acquiring connection completed successfully.
+2026-02-21 20:31:26,016 [31mERROR[0m  [31m[GraphExecutor] [ExecutionManager][on_graph_executor_stop 6094] [cancel-consumer] ⚠️ Error disconnecting run client: <class 'RuntimeError'> cannot join thread before it is started [0m
+2026-02-21 20:31:26,019 [34mINFO[0m  [GraphExecutor] [ExecutionManager][on_graph_executor_stop 6094] ✅ Finished GraphExec cleanup 
+2026-02-21 20:31:26,019 [34mINFO[0m  [ExecutionManager] ✅ Cleanup done
+2026-02-21 20:31:26,019 [34mINFO[0m  [ExecutionManager] 🛑 Terminated
+2026-02-21 20:31:26,188 [34mINFO[0m  [PID-6089|THREAD-77685901|DatabaseManager|FastAPI server-7019e67b-30c1-4d08-a0ec-4f0175629d0e] Running FastAPI server started...
+2026-02-21 20:31:26,189 [34mINFO[0m  [DatabaseManager] Starting RPC server at http://localhost:8005
+2026-02-21 20:31:26,197 [34mINFO[0m  [DatabaseManager] ⏳ Connecting to Database...
+2026-02-21 20:31:26,197 [34mINFO[0m  [PID-6089|THREAD-77685902|DatabaseManager|Prisma-64fcde85-3de3-4783-b2c6-789775451cd0] Acquiring connection started...
+2026-02-21 20:31:26,254 [34mINFO[0m  [Scheduler] [APScheduler] Adding job tentatively -- it will be properly scheduled when the scheduler starts
+2026-02-21 20:31:26,255 [34mINFO[0m  [Scheduler] [APScheduler] Adding job tentatively -- it will be properly scheduled when the scheduler starts
+2026-02-21 20:31:26,255 [34mINFO[0m  [Scheduler] [APScheduler] Adding job tentatively -- it will be properly scheduled when the scheduler starts
+2026-02-21 20:31:26,255 [34mINFO[0m  [Scheduler] [APScheduler] Adding job tentatively -- it will be properly scheduled when the scheduler starts
+2026-02-21 20:31:26,255 [34mINFO[0m  [Scheduler] [APScheduler] Adding job tentatively -- it will be properly scheduled when the scheduler starts
+2026-02-21 20:31:26,255 [34mINFO[0m  [Scheduler] [APScheduler] Adding job tentatively -- it will be properly scheduled when the scheduler starts
+2026-02-21 20:31:26,256 [34mINFO[0m  [Scheduler] [APScheduler] Adding job tentatively -- it will be properly scheduled when the scheduler starts
+2026-02-21 20:31:26,346 [34mINFO[0m  [PID-6089|THREAD-77685902|DatabaseManager|Prisma-64fcde85-3de3-4783-b2c6-789775451cd0] Acquiring connection completed successfully.
+2026-02-21 20:31:26,346 [34mINFO[0m  [DatabaseManager] ✅ Ready
+2026-02-21 20:31:26,347 [31mERROR[0m  [31m[Errno 48] error while attempting to bind on address ('::1', 8005, 0, 0): [errno 48] address already in use[0m
+2026-02-21 20:31:26,349 [34mINFO[0m  [DatabaseManager] ⏳ Disconnecting Database...
+2026-02-21 20:31:26,349 [34mINFO[0m  [PID-6089|THREAD-77685902|DatabaseManager|Prisma-2397ec31-7da6-4598-a012-6c48f17ea97f] Releasing connection started...
+2026-02-21 20:31:26,350 [34mINFO[0m  [PID-6089|THREAD-77685902|DatabaseManager|Prisma-2397ec31-7da6-4598-a012-6c48f17ea97f] Releasing connection completed successfully.
+2026-02-21 20:31:26,351 [34mINFO[0m  [DatabaseManager] ✅ FastAPI has finished
+2026-02-21 20:31:26,351 [34mINFO[0m  [DatabaseManager] 🛑 Shared event loop stopped
+2026-02-21 20:31:26,351 [34mINFO[0m  [DatabaseManager] 🧹 Running cleanup
+Process DatabaseManager:
+Traceback (most recent call last):
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/multiprocessing/process.py", line 313, in _bootstrap
+    self.run()
+    ~~~~~~~~^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/multiprocessing/process.py", line 108, in run
+    self._target(*self._args, **self._kwargs)
+    ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/util/process.py", line 83, in execute_run_command
+    self.cleanup()
+    ~~~~~~~~~~~~^^
+  File "/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/util/service.py", line 153, in cleanup
+    self.shared_event_loop.call_soon_threadsafe(self.shared_event_loop.stop)
+    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/asyncio/base_events.py", line 873, in call_soon_threadsafe
+    self._check_closed()
+    ~~~~~~~~~~~~~~~~~~^^
+  File "/opt/homebrew/Cellar/python@3.13/3.13.1/Frameworks/Python.framework/Versions/3.13/lib/python3.13/asyncio/base_events.py", line 551, in _check_closed
+    raise RuntimeError('Event loop is closed')
+RuntimeError: Event loop is closed
+2026-02-21 20:31:26,382 [34mINFO[0m  [Scheduler] [APScheduler] Added job "process_weekly_summary" to job store "weekly_notifications"
+2026-02-21 20:31:26,390 [34mINFO[0m  [Scheduler] [APScheduler] Added job "report_late_executions" to job store "execution"
+2026-02-21 20:31:26,392 [34mINFO[0m  [Scheduler] [APScheduler] Added job "report_block_error_rates" to job store "execution"
+2026-02-21 20:31:26,395 [34mINFO[0m  [Scheduler] [APScheduler] Added job "cleanup_expired_files" to job store "execution"
+2026-02-21 20:31:26,397 [34mINFO[0m  [Scheduler] [APScheduler] Added job "cleanup_oauth_tokens" to job store "execution"
+2026-02-21 20:31:26,399 [34mINFO[0m  [Scheduler] [APScheduler] Added job "execution_accuracy_alerts" to job store "execution"
+2026-02-21 20:31:26,401 [34mINFO[0m  [Scheduler] [APScheduler] Added job "ensure_embeddings_coverage" to job store "execution"
+2026-02-21 20:31:26,401 [34mINFO[0m  [Scheduler] [APScheduler] Scheduler started
+2026-02-21 20:31:26,402 [34mINFO[0m  [Scheduler] Running embedding backfill on startup...
+2026-02-21 20:31:26,440 [33mWARNING[0m  [33mProvider LINEAR implements OAuth but the required env vars LINEAR_CLIENT_ID and LINEAR_CLIENT_SECRET are not both set[0m
+2026-02-21 20:31:26,468 [34mINFO[0m  [PID-6090|THREAD-77685499|Scheduler|AppService client-24942e64-d380-4d36-a245-5c41172e5293] Creating service client started...
+2026-02-21 20:31:26,468 [34mINFO[0m  [PID-6090|THREAD-77685499|Scheduler|AppService client-24942e64-d380-4d36-a245-5c41172e5293] Creating service client completed successfully.
+2026-02-21 20:31:26,485 [33mWARNING[0m  [33mAuthentication error: Langfuse client initialized without public_key. Client will be disabled. Provide a public_key parameter or set LANGFUSE_PUBLIC_KEY environment variable. [0m
+2026-02-21 20:31:26,652 [34mINFO[0m  Metrics endpoint exposed at /metrics for external-api
+2026-02-21 20:31:26,655 [34mINFO[0m  Metrics endpoint exposed at /metrics for rest-api
+2026-02-21 20:31:26,735 [34mINFO[0m  [AgentServer] Starting...
+2026-02-21 20:31:26,745 [34mINFO[0m  Started server process [6093]
+2026-02-21 20:31:26,745 [34mINFO[0m  Waiting for application startup.
+2026-02-21 20:31:26,746 [33mWARNING[0m  [33m⚠️ JWT_SIGN_ALGORITHM is set to 'HS256', a symmetric shared-key signature algorithm. We highly recommend using an asymmetric algorithm such as ES256, because when leaked, a shared secret would allow anyone to forge valid tokens and impersonate users. More info: https://supabase.com/docs/guides/auth/signing-keys#choosing-the-right-signing-algorithm[0m
+2026-02-21 20:31:26,747 [34mINFO[0m  [PID-6093|THREAD-77685502|AgentServer|Prisma-9d930243-0262-4697-b4af-e0bcbec281c4] Acquiring connection started...
+2026-02-21 20:31:26,812 [34mINFO[0m  [PID-6093|THREAD-77685502|AgentServer|Prisma-9d930243-0262-4697-b4af-e0bcbec281c4] Acquiring connection completed successfully.
+2026-02-21 20:31:26,825 [34mINFO[0m  Thread pool size set to 60 for sync endpoint/dependency performance
+2026-02-21 20:31:26,825 [34mINFO[0m  Successfully patched IntegrationCredentialsStore.get_all_creds
+2026-02-21 20:31:26,825 [34mINFO[0m  Syncing provider costs to blocks...
+2026-02-21 20:31:27,576 [33mWARNING[0m  [33mProvider WORDPRESS implements OAuth but the required env vars WORDPRESS_CLIENT_ID and WORDPRESS_CLIENT_SECRET are not both set[0m
+2026-02-21 20:31:27,631 [34mINFO[0m  Registered 1 custom costs for block FirecrawlExtractBlock
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/backend/blocks/exa/helpers.py:56: UserWarning: Field name "schema" in "SummarySettings" shadows an attribute in parent "BaseModel"
+  class SummarySettings(BaseModel):
+2026-02-21 20:31:27,954 [33mWARNING[0m  [33mProvider AIRTABLE implements OAuth but the required env vars AIRTABLE_CLIENT_ID and AIRTABLE_CLIENT_SECRET are not both set[0m
+2026-02-21 20:31:29,238 [34mINFO[0m  Successfully patched IntegrationCredentialsStore.get_all_creds
+2026-02-21 20:31:29,397 [33mWARNING[0m  [33mBlock WordPressCreatePostBlock credential input 'credentials' provider 'wordpress' has no authentication methods configured - Disabling[0m
+2026-02-21 20:31:29,397 [33mWARNING[0m  [33mBlock WordPressGetAllPostsBlock credential input 'credentials' provider 'wordpress' has no authentication methods configured - Disabling[0m
+2026-02-21 20:31:29,465 [34mINFO[0m  Synced 82 costs to 82 blocks
+2026-02-21 20:31:29,466 [33mWARNING[0m  [33mExecuting <Task pending name='Task-2' coro=<LifespanOn.main() running at /Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/uvicorn/lifespan/on.py:86> created at /Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/uvicorn/lifespan/on.py:51> took 2.654 seconds[0m
+2026-02-21 20:31:29,511 [34mINFO[0m  [Scheduler] All content has embeddings, skipping backfill
+2026-02-21 20:31:29,512 [34mINFO[0m  [Scheduler] Running cleanup for orphaned embeddings (blocks/docs)...
+2026-02-21 20:31:29,542 [34mINFO[0m  [Scheduler] Cleanup completed: no orphaned embeddings found
+2026-02-21 20:31:29,542 [34mINFO[0m  [Scheduler] Startup embedding backfill complete: {'backfill': {'processed': 0, 'success': 0, 'failed': 0}, 'cleanup': {'deleted': 0}}
+2026-02-21 20:31:29,553 [34mINFO[0m  Started server process [6090]
+2026-02-21 20:31:29,553 [34mINFO[0m  Waiting for application startup.
+2026-02-21 20:31:29,554 [34mINFO[0m  Application startup complete.
+2026-02-21 20:31:29,555 [34mINFO[0m  Uvicorn running on http://localhost:8003 (Press CTRL+C to quit)
+2026-02-21 20:31:31,074 [34mINFO[0m  Migrating integration credentials for 0 users
+2026-02-21 20:31:31,087 [34mINFO[0m  Fixing LLM credential inputs on 0 nodes
+2026-02-21 20:31:31,087 [34mINFO[0m  Migrating LLM models
+2026-02-21 20:31:31,107 [34mINFO[0m  Migrated 0 node triggers to triggered presets
+2026-02-21 20:31:31,107 [34mINFO[0m  [PID-6093|THREAD-77685502|AgentServer|AsyncRedis-f8b888fc-8b03-4807-adfd-c93710c11c85] Acquiring connection started...
+2026-02-21 20:31:31,114 [34mINFO[0m  [PID-6093|THREAD-77685502|AgentServer|AsyncRedis-f8b888fc-8b03-4807-adfd-c93710c11c85] Acquiring connection completed successfully.
+2026-02-21 20:31:31,115 [34mINFO[0m  Created consumer group 'chat_consumers' on stream 'chat:completions'
+2026-02-21 20:31:31,115 [34mINFO[0m  Chat completion consumer started (consumer: consumer-2f92959a)
+2026-02-21 20:31:31,116 [34mINFO[0m  Application startup complete.
+2026-02-21 20:31:31,117 [34mINFO[0m  Uvicorn running on http://0.0.0.0:8006 (Press CTRL+C to quit)
+2026-02-21 20:31:45,616 [34mINFO[0m  127.0.0.1:56174 - "GET /api/health HTTP/1.1" 404
+2026-02-21 20:32:07,632 [34mINFO[0m  127.0.0.1:56317 - "GET /openapi.json HTTP/1.1" 200
+2026-02-21 20:32:07,635 [33mWARNING[0m  [33mExecuting <Task finished name='Task-7' coro=<RequestResponseCycle.run_asgi() done, defined at /Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/uvicorn/protocols/http/httptools_impl.py:414> result=None created at /Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/uvicorn/protocols/http/httptools_impl.py:295> took 0.346 seconds[0m
+2026-02-21 20:32:41,502 [34mINFO[0m  127.0.0.1:56681 - "POST /api/v2/chat/sessions HTTP/1.1" 404
+2026-02-21 20:32:50,005 [34mINFO[0m  127.0.0.1:56736 - "GET /api/docs HTTP/1.1" 404
+2026-02-21 20:33:10,267 [34mINFO[0m  127.0.0.1:56898 - "GET /openapi.json HTTP/1.1" 200
+2026-02-21 20:33:28,399 [34mINFO[0m  127.0.0.1:56993 - "POST /api/chat/sessions HTTP/1.1" 401
+2026-02-21 20:34:20,913 [34mINFO[0m  127.0.0.1:57313 - "GET /openapi.json HTTP/1.1" 200
+2026-02-21 20:36:26,326 [34mINFO[0m  Running job "report_late_executions (trigger: interval[0:05:00], next run at: 2026-02-21 13:36:26 UTC)" (scheduled at 2026-02-21 13:36:26.255260+00:00)
+2026-02-21 20:36:26,333 [34mINFO[0m  [PID-6090|THREAD-77695300|Scheduler|AppService client-24942e64-d380-4d36-a245-5c41172e5293] Creating service client started...
+2026-02-21 20:36:26,336 [34mINFO[0m  [PID-6090|THREAD-77695300|Scheduler|AppService client-24942e64-d380-4d36-a245-5c41172e5293] Creating service client completed successfully.
+2026-02-21 20:36:26,336 [34mINFO[0m  [PID-6090|THREAD-77695300|Scheduler|AppService client-24942e64-d380-4d36-a245-5c41172e5293] Creating service client started...
+2026-02-21 20:36:26,340 [34mINFO[0m  [PID-6090|THREAD-77695300|Scheduler|AppService client-24942e64-d380-4d36-a245-5c41172e5293] Creating service client completed successfully.
+2026-02-21 20:36:26,439 [33mWARNING[0m  [33mService communication: Retry attempt 1 for '_call_method_sync': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_graph_executions'
+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
+2026-02-21 20:36:27,802 [33mWARNING[0m  [33mService communication: Retry attempt 2 for '_call_method_sync': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_graph_executions'
+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
+2026-02-21 20:36:30,362 [33mWARNING[0m  [33mService communication: Retry attempt 3 for '_call_method_sync': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_graph_executions'
+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
+2026-02-21 20:36:34,885 [33mWARNING[0m  [33mService communication: Retry attempt 4 for '_call_method_sync': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_graph_executions'
+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
+2026-02-21 20:36:43,438 [33mWARNING[0m  [33mService communication: Retry attempt 5 for '_call_method_sync': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_graph_executions'
+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
+2026-02-21 20:36:59,905 [33mWARNING[0m  [33mService communication: Retry attempt 6 for '_call_method_sync': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_graph_executions'
+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
+2026-02-21 20:37:12,581 [33mWARNING[0m  [33mExecuting <Task pending name='Task-13' coro=<RequestResponseCycle.run_asgi() running at /Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/uvicorn/protocols/http/httptools_impl.py:416> cb=[set.discard()] created at /Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/uvicorn/protocols/http/httptools_impl.py:295> took 0.109 seconds[0m
+2026-02-21 20:37:12,767 [34mINFO[0m  127.0.0.1:58472 - "GET /api/store/profile HTTP/1.1" 404
+2026-02-21 20:37:12,886 [34mINFO[0m  127.0.0.1:58469 - "GET /api/chat/sessions?limit=50 HTTP/1.1" 200
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/expressions/parser.py:72: PyparsingDeprecationWarning: 'enablePackrat' deprecated - use 'enable_packrat'
+  ParserElement.enablePackrat()
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/expressions/parser.py:85: PyparsingDeprecationWarning: 'escChar' argument is deprecated, use 'esc_char'
+  quoted_identifier = QuotedString('"', escChar="\\", unquoteResults=True)
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/expressions/parser.py:85: PyparsingDeprecationWarning: 'unquoteResults' argument is deprecated, use 'unquote_results'
+  quoted_identifier = QuotedString('"', escChar="\\", unquoteResults=True)
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/table/metadata.py:365: PydanticDeprecatedSince212: Using `@model_validator` with mode='after' on a classmethod is deprecated. Instead, use an instance method. See the documentation at https://docs.pydantic.dev/2.12/concepts/validators/#model-after-validator. Deprecated in Pydantic V2.12 to be removed in V3.0.
+  @model_validator(mode="after")
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/table/metadata.py:494: PydanticDeprecatedSince212: Using `@model_validator` with mode='after' on a classmethod is deprecated. Instead, use an instance method. See the documentation at https://docs.pydantic.dev/2.12/concepts/validators/#model-after-validator. Deprecated in Pydantic V2.12 to be removed in V3.0.
+  @model_validator(mode="after")
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/table/metadata.py:498: PydanticDeprecatedSince212: Using `@model_validator` with mode='after' on a classmethod is deprecated. Instead, use an instance method. See the documentation at https://docs.pydantic.dev/2.12/concepts/validators/#model-after-validator. Deprecated in Pydantic V2.12 to be removed in V3.0.
+  @model_validator(mode="after")
+/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/table/metadata.py:502: PydanticDeprecatedSince212: Using `@model_validator` with mode='after' on a classmethod is deprecated. Instead, use an instance method. See the documentation at https://docs.pydantic.dev/2.12/concepts/validators/#model-after-validator. Deprecated in Pydantic V2.12 to be removed in V3.0.
+  @model_validator(mode="after")
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+  @model_validator(mode="after")
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+  @model_validator(mode="after")
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+  @model_validator(mode="after")
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+  @model_validator(mode="after")
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+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
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+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
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+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
+2026-02-21 20:39:00,123 [33mWARNING[0m  [33mService communication: Retry attempt 10 for '_call_method_sync': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_graph_executions'
+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
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+For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
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--- a/autogpt_platform/backend/.gitignore
+++ b/autogpt_platform/backend/.gitignore
@@ -22,3 +22,4 @@ migrations/*/rollback*.sql

 # Workspace files
 workspaces/
+sample.logs
--- a/autogpt_platform/backend/backend/copilot/model.py
+++ b/autogpt_platform/backend/backend/copilot/model.py
@@ -432,13 +432,23 @@ async def _get_session_from_db(session_id: str) -> ChatSession | None:
    return session


-async def upsert_chat_session(session: ChatSession) -> ChatSession:
+async def upsert_chat_session(
+    session: ChatSession,
+    *,
+    existing_message_count: int | None = None,
+) -> ChatSession:
    """Update a chat session in both cache and database.

    Uses session-level locking to prevent race conditions when concurrent
    operations (e.g., background title update and main stream handler)
    attempt to upsert the same session simultaneously.

+    Args:
+        existing_message_count: If provided, skip the DB query to count
+            existing messages. The caller is responsible for tracking this
+            accurately. Useful for incremental saves in a streaming loop
+            where the caller already knows how many messages are persisted.
+
    Raises:
        DatabaseError: If the database write fails. The cache is still updated
            as a best-effort optimization, but the error is propagated to ensure
@@ -450,15 +460,20 @@ async def upsert_chat_session(session: ChatSession) -> ChatSession:

    async with lock:
        # Get existing message count from DB for incremental saves
-        existing_message_count = await chat_db().get_chat_session_message_count(
-            session.session_id
-        )
+        if existing_message_count is None:
+            existing_message_count = await chat_db().get_chat_session_message_count(
+                session.session_id
+            )

        db_error: Exception | None = None

        # Save to database (primary storage)
        try:
-            await _save_session_to_db(session, existing_message_count)
+            await _save_session_to_db(
+                session,
+                existing_message_count,
+                skip_existence_check=existing_message_count > 0,
+            )
        except Exception as e:
            logger.error(
                f"Failed to save session {session.session_id} to database: {e}"
@@ -489,21 +504,31 @@ async def upsert_chat_session(session: ChatSession) -> ChatSession:


 async def _save_session_to_db(
-    session: ChatSession, existing_message_count: int
+    session: ChatSession,
+    existing_message_count: int,
+    *,
+    skip_existence_check: bool = False,
 ) -> None:
-    """Save or update a chat session in the database."""
+    """Save or update a chat session in the database.
+
+    Args:
+        skip_existence_check: When True, skip the ``get_chat_session`` query
+            and assume the session row already exists.  Saves one DB round trip
+            for incremental saves during streaming.
+    """
    db = chat_db()

-    # Check if session exists in DB
-    existing = await db.get_chat_session(session.session_id)
+    if not skip_existence_check:
+        # Check if session exists in DB
+        existing = await db.get_chat_session(session.session_id)

-    if not existing:
-        # Create new session
-        await db.create_chat_session(
-            session_id=session.session_id,
-            user_id=session.user_id,
-        )
-        existing_message_count = 0
+        if not existing:
+            # Create new session
+            await db.create_chat_session(
+                session_id=session.session_id,
+                user_id=session.user_id,
+            )
+            existing_message_count = 0

    # Calculate total tokens from usage
    total_prompt = sum(u.prompt_tokens for u in session.usage)
--- a/autogpt_platform/backend/backend/copilot/response_model.py
+++ b/autogpt_platform/backend/backend/copilot/response_model.py
@@ -34,6 +34,9 @@ class ResponseType(str, Enum):
    TOOL_INPUT_AVAILABLE = "tool-input-available"
    TOOL_OUTPUT_AVAILABLE = "tool-output-available"

+    # Long-running tool notification (custom extension - uses AI SDK DataUIPart format)
+    LONG_RUNNING_START = "data-long-running-start"
+
    # Other
    ERROR = "error"
    USAGE = "usage"
@@ -145,6 +148,10 @@ class StreamToolInputAvailable(StreamBaseResponse):
    input: dict[str, Any] = Field(
        default_factory=dict, description="Tool input arguments"
    )
+    providerMetadata: dict[str, Any] | None = Field(
+        default=None,
+        description="Provider metadata - used to pass isLongRunning flag to frontend",
+    )


 class StreamToolOutputAvailable(StreamBaseResponse):
@@ -173,6 +180,20 @@ class StreamToolOutputAvailable(StreamBaseResponse):
        return f"data: {json.dumps(data)}\n\n"


+class StreamLongRunningStart(StreamBaseResponse):
+    """Notification that a long-running tool has started.
+
+    Custom extension using AI SDK DataUIPart format. Signals the frontend to show
+    UI feedback while the tool executes.
+    """
+
+    type: ResponseType = ResponseType.LONG_RUNNING_START
+    data: dict[str, Any] = Field(
+        default_factory=dict,
+        description="Data for the long-running event containing toolCallId and toolName",
+    )
+
+
 # ========== Other ==========


--- a/autogpt_platform/backend/backend/copilot/sdk/response_adapter.py
+++ b/autogpt_platform/backend/backend/copilot/sdk/response_adapter.py
@@ -34,6 +34,7 @@ from backend.copilot.response_model import (
    StreamToolInputStart,
    StreamToolOutputAvailable,
 )
+from backend.copilot.tools import get_tool

 from .tool_adapter import MCP_TOOL_PREFIX, pop_pending_tool_output

@@ -47,8 +48,9 @@ class SDKResponseAdapter:
    text blocks, tool calls, and message lifecycle.
    """

-    def __init__(self, message_id: str | None = None):
+    def __init__(self, message_id: str | None = None, session_id: str | None = None):
        self.message_id = message_id or str(uuid.uuid4())
+        self.session_id = session_id
        self.text_block_id = str(uuid.uuid4())
        self.has_started_text = False
        self.has_ended_text = False
@@ -61,6 +63,11 @@ class SDKResponseAdapter:
        """Set the task ID for reconnection support."""
        self.task_id = task_id

+    @property
+    def has_unresolved_tool_calls(self) -> bool:
+        """True when there are tool calls that haven't received output yet."""
+        return bool(self.current_tool_calls.keys() - self.resolved_tool_calls)
+
    def convert_message(self, sdk_message: Message) -> list[StreamBaseResponse]:
        """Convert a single SDK message to Vercel AI SDK format."""
        responses: list[StreamBaseResponse] = []
@@ -77,7 +84,12 @@ class SDKResponseAdapter:
        elif isinstance(sdk_message, AssistantMessage):
            # Flush any SDK built-in tool calls that didn't get a UserMessage
            # result (e.g. WebSearch, Read handled internally by the CLI).
-            self._flush_unresolved_tool_calls(responses)
+            # BUT skip flush when this AssistantMessage is a parallel tool
+            # continuation (contains only ToolUseBlocks) — the prior tools
+            # are still executing concurrently and haven't finished yet.
+            is_tool_only = all(isinstance(b, ToolUseBlock) for b in sdk_message.content)
+            if not is_tool_only:
+                self._flush_unresolved_tool_calls(responses)

            # After tool results, the SDK sends a new AssistantMessage for the
            # next LLM turn. Open a new step if the previous one was closed.
@@ -100,6 +112,15 @@ class SDKResponseAdapter:
                    # instead of "mcp__copilot__find_block".
                    tool_name = block.name.removeprefix(MCP_TOOL_PREFIX)

+                    # Check if this is a long-running tool to trigger UI feedback
+                    tool = get_tool(tool_name)
+                    is_long_running = tool.is_long_running if tool else False
+
+                    logger.info(
+                        f"[ADAPTER] Tool: {tool_name}, has_tool={tool is not None}, "
+                        f"is_long_running={is_long_running}"
+                    )
+
                    responses.append(
                        StreamToolInputStart(toolCallId=block.id, toolName=tool_name)
                    )
@@ -108,8 +129,15 @@ class SDKResponseAdapter:
                            toolCallId=block.id,
                            toolName=tool_name,
                            input=block.input,
+                            providerMetadata=(
+                                {"isLongRunning": True} if is_long_running else None
+                            ),
                        )
                    )
+                    logger.info(
+                        f"[ADAPTER] Created StreamToolInputAvailable with "
+                        f"providerMetadata={{'isLongRunning': {is_long_running}}}"
+                    )
                    self.current_tool_calls[block.id] = {"name": tool_name}

        elif isinstance(sdk_message, UserMessage):
@@ -118,8 +146,24 @@ class SDKResponseAdapter:
            blocks = content if isinstance(content, list) else []
            resolved_in_blocks: set[str] = set()

+            sid = (self.session_id or "?")[:12]
+            parent_id_preview = getattr(sdk_message, "parent_tool_use_id", None)
+            logger.info(
+                "[SDK] [%s] UserMessage: %d blocks, content_type=%s, "
+                "parent_tool_use_id=%s",
+                sid,
+                len(blocks),
+                type(content).__name__,
+                parent_id_preview[:12] if parent_id_preview else "None",
+            )
+
            for block in blocks:
                if isinstance(block, ToolResultBlock) and block.tool_use_id:
+                    # Skip if already resolved (e.g. by flush) — the real
+                    # result supersedes the empty flush, but re-emitting
+                    # would confuse the frontend's state machine.
+                    if block.tool_use_id in self.resolved_tool_calls:
+                        continue
                    tool_info = self.current_tool_calls.get(block.tool_use_id, {})
                    tool_name = tool_info.get("name", "unknown")

@@ -144,7 +188,11 @@ class SDKResponseAdapter:
            # Handle SDK built-in tool results carried via parent_tool_use_id
            # instead of (or in addition to) ToolResultBlock content.
            parent_id = sdk_message.parent_tool_use_id
-            if parent_id and parent_id not in resolved_in_blocks:
+            if (
+                parent_id
+                and parent_id not in resolved_in_blocks
+                and parent_id not in self.resolved_tool_calls
+            ):
                tool_info = self.current_tool_calls.get(parent_id, {})
                tool_name = tool_info.get("name", "unknown")

@@ -228,11 +276,28 @@ class SDKResponseAdapter:
        output, which we pop and emit here before the next ``AssistantMessage``
        starts.
        """
+        unresolved = [
+            (tid, info.get("name", "unknown"))
+            for tid, info in self.current_tool_calls.items()
+            if tid not in self.resolved_tool_calls
+        ]
+        sid = (self.session_id or "?")[:12]
+        if not unresolved:
+            logger.info(
+                "[SDK] [%s] Flush called but all %d tool(s) already resolved",
+                sid,
+                len(self.current_tool_calls),
+            )
+            return
+        logger.info(
+            "[SDK] [%s] Flushing %d unresolved tool call(s): %s",
+            sid,
+            len(unresolved),
+            ", ".join(f"{name}({tid[:12]})" for tid, name in unresolved),
+        )
+
        flushed = False
-        for tool_id, tool_info in self.current_tool_calls.items():
-            if tool_id in self.resolved_tool_calls:
-                continue
-            tool_name = tool_info.get("name", "unknown")
+        for tool_id, tool_name in unresolved:
            output = pop_pending_tool_output(tool_name)
            if output is not None:
                responses.append(
@@ -245,9 +310,12 @@ class SDKResponseAdapter:
                )
                self.resolved_tool_calls.add(tool_id)
                flushed = True
-                logger.debug(
-                    f"Flushed pending output for built-in tool {tool_name} "
-                    f"(call {tool_id})"
+                logger.info(
+                    "[SDK] [%s] Flushed stashed output for %s " "(call %s, %d chars)",
+                    sid,
+                    tool_name,
+                    tool_id[:12],
+                    len(output),
                )
            else:
                # No output available — emit an empty output so the frontend
@@ -263,9 +331,14 @@ class SDKResponseAdapter:
                )
                self.resolved_tool_calls.add(tool_id)
                flushed = True
-                logger.debug(
-                    f"Flushed empty output for unresolved tool {tool_name} "
-                    f"(call {tool_id})"
+                logger.warning(
+                    "[SDK] [%s] Flushed EMPTY output for unresolved tool %s "
+                    "(call %s) — stash was empty (likely SDK hook race "
+                    "condition: PostToolUse hook hadn't completed before "
+                    "flush was triggered)",
+                    sid,
+                    tool_name,
+                    tool_id[:12],
                )

        if flushed and self.step_open:
--- a/autogpt_platform/backend/backend/copilot/sdk/response_adapter_test.py
+++ b/autogpt_platform/backend/backend/copilot/sdk/response_adapter_test.py
@@ -1,5 +1,8 @@
 """Unit tests for the SDK response adapter."""

+import asyncio
+
+import pytest
 from claude_agent_sdk import (
    AssistantMessage,
    ResultMessage,
@@ -27,6 +30,10 @@ from backend.copilot.response_model import (

 from .response_adapter import SDKResponseAdapter
 from .tool_adapter import MCP_TOOL_PREFIX
+from .tool_adapter import _pending_tool_outputs as _pto
+from .tool_adapter import _stash_event
+from .tool_adapter import stash_pending_tool_output as _stash
+from .tool_adapter import wait_for_stash


 def _adapter() -> SDKResponseAdapter:
@@ -364,3 +371,310 @@ def test_full_conversation_flow():
        "StreamFinishStep",  # step 2 closed
        "StreamFinish",
    ]
+
+
+# -- Flush unresolved tool calls --------------------------------------------
+
+
+def test_flush_unresolved_at_result_message():
+    """Built-in tools (WebSearch) without UserMessage results get flushed at ResultMessage."""
+    adapter = _adapter()
+    all_responses: list[StreamBaseResponse] = []
+
+    # 1. Init
+    all_responses.extend(
+        adapter.convert_message(SystemMessage(subtype="init", data={}))
+    )
+    # 2. Tool use (built-in tool — no MCP prefix)
+    all_responses.extend(
+        adapter.convert_message(
+            AssistantMessage(
+                content=[
+                    ToolUseBlock(id="ws-1", name="WebSearch", input={"query": "test"})
+                ],
+                model="test",
+            )
+        )
+    )
+    # 3. No UserMessage for this tool — go straight to ResultMessage
+    all_responses.extend(
+        adapter.convert_message(
+            ResultMessage(
+                subtype="success",
+                duration_ms=100,
+                duration_api_ms=50,
+                is_error=False,
+                num_turns=1,
+                session_id="s1",
+            )
+        )
+    )
+
+    types = [type(r).__name__ for r in all_responses]
+    assert types == [
+        "StreamStart",
+        "StreamStartStep",
+        "StreamToolInputStart",
+        "StreamToolInputAvailable",
+        "StreamToolOutputAvailable",  # flushed with empty output
+        "StreamFinishStep",  # step closed by flush
+        "StreamFinish",
+    ]
+    # The flushed output should be empty (no stash available)
+    output_event = [
+        r for r in all_responses if isinstance(r, StreamToolOutputAvailable)
+    ][0]
+    assert output_event.toolCallId == "ws-1"
+    assert output_event.toolName == "WebSearch"
+    assert output_event.output == ""
+
+
+def test_flush_unresolved_at_next_assistant_message():
+    """Built-in tools get flushed when the next AssistantMessage arrives."""
+    adapter = _adapter()
+    all_responses: list[StreamBaseResponse] = []
+
+    # 1. Init
+    all_responses.extend(
+        adapter.convert_message(SystemMessage(subtype="init", data={}))
+    )
+    # 2. Tool use (built-in — no UserMessage will come)
+    all_responses.extend(
+        adapter.convert_message(
+            AssistantMessage(
+                content=[
+                    ToolUseBlock(id="ws-1", name="WebSearch", input={"query": "test"})
+                ],
+                model="test",
+            )
+        )
+    )
+    # 3. Next AssistantMessage triggers flush before processing its blocks
+    all_responses.extend(
+        adapter.convert_message(
+            AssistantMessage(
+                content=[TextBlock(text="Here are the results")], model="test"
+            )
+        )
+    )
+
+    types = [type(r).__name__ for r in all_responses]
+    assert types == [
+        "StreamStart",
+        "StreamStartStep",
+        "StreamToolInputStart",
+        "StreamToolInputAvailable",
+        # Flush at next AssistantMessage:
+        "StreamToolOutputAvailable",
+        "StreamFinishStep",  # step closed by flush
+        # New step for continuation text:
+        "StreamStartStep",
+        "StreamTextStart",
+        "StreamTextDelta",
+    ]
+
+
+def test_flush_with_stashed_output():
+    """Stashed output from PostToolUse hook is used when flushing."""
+    adapter = _adapter()
+
+    # Simulate PostToolUse hook stashing output
+    _pto.set({})
+    _stash("WebSearch", "Search result: 5 items found")
+
+    all_responses: list[StreamBaseResponse] = []
+
+    # Tool use
+    all_responses.extend(
+        adapter.convert_message(
+            AssistantMessage(
+                content=[
+                    ToolUseBlock(id="ws-1", name="WebSearch", input={"query": "test"})
+                ],
+                model="test",
+            )
+        )
+    )
+    # ResultMessage triggers flush
+    all_responses.extend(
+        adapter.convert_message(
+            ResultMessage(
+                subtype="success",
+                duration_ms=100,
+                duration_api_ms=50,
+                is_error=False,
+                num_turns=1,
+                session_id="s1",
+            )
+        )
+    )
+
+    output_events = [
+        r for r in all_responses if isinstance(r, StreamToolOutputAvailable)
+    ]
+    assert len(output_events) == 1
+    assert output_events[0].output == "Search result: 5 items found"
+
+    # Cleanup
+    _pto.set({})  # type: ignore[arg-type]
+
+
+# -- wait_for_stash synchronisation tests --
+
+
+@pytest.mark.asyncio
+async def test_wait_for_stash_signaled():
+    """wait_for_stash returns True when stash_pending_tool_output signals."""
+    _pto.set({})
+    event = asyncio.Event()
+    _stash_event.set(event)
+
+    # Simulate a PostToolUse hook that stashes output after a short delay
+    async def delayed_stash():
+        await asyncio.sleep(0.01)
+        _stash("WebSearch", "result data")
+
+    asyncio.create_task(delayed_stash())
+    result = await wait_for_stash(timeout=1.0)
+
+    assert result is True
+    assert _pto.get({}).get("WebSearch") == ["result data"]
+
+    # Cleanup
+    _pto.set({})  # type: ignore[arg-type]
+    _stash_event.set(None)
+
+
+@pytest.mark.asyncio
+async def test_wait_for_stash_timeout():
+    """wait_for_stash returns False on timeout when no stash occurs."""
+    _pto.set({})
+    event = asyncio.Event()
+    _stash_event.set(event)
+
+    result = await wait_for_stash(timeout=0.05)
+    assert result is False
+
+    # Cleanup
+    _pto.set({})  # type: ignore[arg-type]
+    _stash_event.set(None)
+
+
+@pytest.mark.asyncio
+async def test_wait_for_stash_already_stashed():
+    """wait_for_stash picks up a stash that happened just before the wait."""
+    _pto.set({})
+    event = asyncio.Event()
+    _stash_event.set(event)
+
+    # Stash before waiting — simulates hook completing before message arrives
+    _stash("Read", "file contents")
+    # Event is now set; wait_for_stash detects the fast path and returns
+    # immediately without timing out.
+    result = await wait_for_stash(timeout=0.05)
+    assert result is True
+
+    # But the stash itself is populated
+    assert _pto.get({}).get("Read") == ["file contents"]
+
+    # Cleanup
+    _pto.set({})  # type: ignore[arg-type]
+    _stash_event.set(None)
+
+
+# -- Parallel tool call tests --
+
+
+def test_parallel_tool_calls_not_flushed_prematurely():
+    """Parallel tool calls should NOT be flushed when the next AssistantMessage
+    only contains ToolUseBlocks (parallel continuation)."""
+    adapter = SDKResponseAdapter()
+
+    # Init
+    adapter.convert_message(SystemMessage(subtype="init", data={}))
+
+    # First AssistantMessage: tool call #1
+    msg1 = AssistantMessage(
+        content=[ToolUseBlock(id="t1", name="WebSearch", input={"q": "foo"})],
+        model="test",
+    )
+    r1 = adapter.convert_message(msg1)
+    assert any(isinstance(r, StreamToolInputAvailable) for r in r1)
+    assert adapter.has_unresolved_tool_calls
+
+    # Second AssistantMessage: tool call #2 (parallel continuation)
+    msg2 = AssistantMessage(
+        content=[ToolUseBlock(id="t2", name="WebSearch", input={"q": "bar"})],
+        model="test",
+    )
+    r2 = adapter.convert_message(msg2)
+
+    # No flush should have happened — t1 should NOT have StreamToolOutputAvailable
+    output_events = [r for r in r2 if isinstance(r, StreamToolOutputAvailable)]
+    assert len(output_events) == 0, (
+        f"Tool-only AssistantMessage should not flush prior tools, "
+        f"but got {len(output_events)} output events"
+    )
+
+    # Both t1 and t2 should still be unresolved
+    assert "t1" not in adapter.resolved_tool_calls
+    assert "t2" not in adapter.resolved_tool_calls
+
+
+def test_text_assistant_message_flushes_prior_tools():
+    """An AssistantMessage with text (new turn) should flush unresolved tools."""
+    adapter = SDKResponseAdapter()
+
+    # Init
+    adapter.convert_message(SystemMessage(subtype="init", data={}))
+
+    # Tool call
+    msg1 = AssistantMessage(
+        content=[ToolUseBlock(id="t1", name="WebSearch", input={"q": "foo"})],
+        model="test",
+    )
+    adapter.convert_message(msg1)
+    assert adapter.has_unresolved_tool_calls
+
+    # Text AssistantMessage (new turn after tools completed)
+    msg2 = AssistantMessage(
+        content=[TextBlock(text="Here are the results")],
+        model="test",
+    )
+    r2 = adapter.convert_message(msg2)
+
+    # Flush SHOULD have happened — t1 gets empty output
+    output_events = [r for r in r2 if isinstance(r, StreamToolOutputAvailable)]
+    assert len(output_events) == 1
+    assert output_events[0].toolCallId == "t1"
+    assert "t1" in adapter.resolved_tool_calls
+
+
+def test_already_resolved_tool_skipped_in_user_message():
+    """A tool result in UserMessage should be skipped if already resolved by flush."""
+    adapter = SDKResponseAdapter()
+
+    adapter.convert_message(SystemMessage(subtype="init", data={}))
+
+    # Tool call + flush via text message
+    adapter.convert_message(
+        AssistantMessage(
+            content=[ToolUseBlock(id="t1", name="WebSearch", input={})],
+            model="test",
+        )
+    )
+    adapter.convert_message(
+        AssistantMessage(
+            content=[TextBlock(text="Done")],
+            model="test",
+        )
+    )
+    assert "t1" in adapter.resolved_tool_calls
+
+    # Now UserMessage arrives with the real result — should be skipped
+    user_msg = UserMessage(content=[ToolResultBlock(tool_use_id="t1", content="real")])
+    r = adapter.convert_message(user_msg)
+    output_events = [r_ for r_ in r if isinstance(r_, StreamToolOutputAvailable)]
+    assert (
+        len(output_events) == 0
+    ), "Already-resolved tool should not emit duplicate output"
--- a/autogpt_platform/backend/backend/copilot/sdk/sdk_compat_test.py
+++ b/autogpt_platform/backend/backend/copilot/sdk/sdk_compat_test.py
@@ -0,0 +1,194 @@
+"""SDK compatibility tests — verify the claude-agent-sdk public API surface we depend on.
+
+Instead of pinning to a narrow version range, these tests verify that the
+installed SDK exposes every class, function, attribute, and method the copilot
+integration relies on.  If an SDK upgrade removes or renames something these
+tests will catch it immediately.
+"""
+
+import inspect
+
+import pytest
+
+# ---------------------------------------------------------------------------
+# Public types & factories
+# ---------------------------------------------------------------------------
+
+
+def test_sdk_exports_client_and_options():
+    from claude_agent_sdk import ClaudeAgentOptions, ClaudeSDKClient
+
+    assert inspect.isclass(ClaudeSDKClient)
+    assert inspect.isclass(ClaudeAgentOptions)
+
+
+def test_sdk_exports_message_types():
+    from claude_agent_sdk import (
+        AssistantMessage,
+        Message,
+        ResultMessage,
+        SystemMessage,
+        UserMessage,
+    )
+
+    for cls in (AssistantMessage, ResultMessage, SystemMessage, UserMessage):
+        assert inspect.isclass(cls), f"{cls.__name__} is not a class"
+    # Message is a Union type alias, just verify it's importable
+    assert Message is not None
+
+
+def test_sdk_exports_content_block_types():
+    from claude_agent_sdk import TextBlock, ToolResultBlock, ToolUseBlock
+
+    for cls in (TextBlock, ToolResultBlock, ToolUseBlock):
+        assert inspect.isclass(cls), f"{cls.__name__} is not a class"
+
+
+def test_sdk_exports_mcp_helpers():
+    from claude_agent_sdk import create_sdk_mcp_server, tool
+
+    assert callable(create_sdk_mcp_server)
+    assert callable(tool)
+
+
+# ---------------------------------------------------------------------------
+# ClaudeSDKClient interface
+# ---------------------------------------------------------------------------
+
+
+def test_client_has_required_methods():
+    from claude_agent_sdk import ClaudeSDKClient
+
+    required = ["connect", "disconnect", "query", "receive_messages"]
+    for name in required:
+        attr = getattr(ClaudeSDKClient, name, None)
+        assert attr is not None, f"ClaudeSDKClient.{name} missing"
+        assert callable(attr), f"ClaudeSDKClient.{name} is not callable"
+
+
+def test_client_supports_async_context_manager():
+    from claude_agent_sdk import ClaudeSDKClient
+
+    assert hasattr(ClaudeSDKClient, "__aenter__")
+    assert hasattr(ClaudeSDKClient, "__aexit__")
+
+
+# ---------------------------------------------------------------------------
+# ClaudeAgentOptions fields
+# ---------------------------------------------------------------------------
+
+
+def test_agent_options_accepts_required_fields():
+    """Verify ClaudeAgentOptions accepts all kwargs our code passes."""
+    from claude_agent_sdk import ClaudeAgentOptions
+
+    opts = ClaudeAgentOptions(
+        system_prompt="test",
+        cwd="/tmp",
+    )
+    assert opts.system_prompt == "test"
+    assert opts.cwd == "/tmp"
+
+
+def test_agent_options_accepts_all_our_fields():
+    """Comprehensive check of every field we use in service.py."""
+    from claude_agent_sdk import ClaudeAgentOptions
+
+    fields_we_use = [
+        "system_prompt",
+        "mcp_servers",
+        "allowed_tools",
+        "disallowed_tools",
+        "hooks",
+        "cwd",
+        "model",
+        "env",
+        "resume",
+        "max_buffer_size",
+    ]
+    sig = inspect.signature(ClaudeAgentOptions)
+    for field in fields_we_use:
+        assert field in sig.parameters, (
+            f"ClaudeAgentOptions no longer accepts '{field}' — "
+            f"available params: {list(sig.parameters.keys())}"
+        )
+
+
+# ---------------------------------------------------------------------------
+# Message attributes
+# ---------------------------------------------------------------------------
+
+
+def test_assistant_message_has_content_and_model():
+    from claude_agent_sdk import AssistantMessage, TextBlock
+
+    msg = AssistantMessage(content=[TextBlock(text="hi")], model="test")
+    assert hasattr(msg, "content")
+    assert hasattr(msg, "model")
+
+
+def test_result_message_has_required_attrs():
+    from claude_agent_sdk import ResultMessage
+
+    msg = ResultMessage(
+        subtype="success",
+        duration_ms=100,
+        duration_api_ms=50,
+        is_error=False,
+        num_turns=1,
+        session_id="s1",
+    )
+    assert msg.subtype == "success"
+    assert hasattr(msg, "result")
+
+
+def test_system_message_has_subtype_and_data():
+    from claude_agent_sdk import SystemMessage
+
+    msg = SystemMessage(subtype="init", data={})
+    assert msg.subtype == "init"
+    assert msg.data == {}
+
+
+def test_user_message_has_parent_tool_use_id():
+    from claude_agent_sdk import UserMessage
+
+    msg = UserMessage(content="test")
+    assert hasattr(msg, "parent_tool_use_id")
+    assert hasattr(msg, "tool_use_result")
+
+
+def test_tool_use_block_has_id_name_input():
+    from claude_agent_sdk import ToolUseBlock
+
+    block = ToolUseBlock(id="t1", name="test", input={"key": "val"})
+    assert block.id == "t1"
+    assert block.name == "test"
+    assert block.input == {"key": "val"}
+
+
+def test_tool_result_block_has_required_attrs():
+    from claude_agent_sdk import ToolResultBlock
+
+    block = ToolResultBlock(tool_use_id="t1", content="result")
+    assert block.tool_use_id == "t1"
+    assert block.content == "result"
+    assert hasattr(block, "is_error")
+
+
+# ---------------------------------------------------------------------------
+# Hook types
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.parametrize(
+    "hook_event",
+    ["PreToolUse", "PostToolUse", "Stop"],
+)
+def test_sdk_exports_hook_event_type(hook_event: str):
+    """Verify HookEvent literal includes the events our security_hooks use."""
+    from claude_agent_sdk.types import HookEvent
+
+    # HookEvent is a Literal type — check that our events are valid values.
+    # We can't easily inspect Literal at runtime, so just verify the type exists.
+    assert HookEvent is not None
--- a/autogpt_platform/backend/backend/copilot/sdk/security_hooks.py
+++ b/autogpt_platform/backend/backend/copilot/sdk/security_hooks.py
@@ -246,15 +246,33 @@ def create_security_hooks(
            """
            _ = context
            tool_name = cast(str, input_data.get("tool_name", ""))
-            logger.debug(f"[SDK] Tool success: {tool_name}, tool_use_id={tool_use_id}")
+            is_builtin = not tool_name.startswith(MCP_TOOL_PREFIX)
+            logger.info(
+                "[SDK] PostToolUse: %s (builtin=%s, tool_use_id=%s)",
+                tool_name,
+                is_builtin,
+                (tool_use_id or "")[:12],
+            )

            # Stash output for SDK built-in tools so the response adapter can
            # emit StreamToolOutputAvailable even when the CLI doesn't surface
            # a separate UserMessage with ToolResultBlock content.
-            if not tool_name.startswith(MCP_TOOL_PREFIX):
+            if is_builtin:
                tool_response = input_data.get("tool_response")
                if tool_response is not None:
+                    resp_preview = str(tool_response)[:100]
+                    logger.info(
+                        "[SDK] Stashing builtin output for %s (%d chars): %s...",
+                        tool_name,
+                        len(str(tool_response)),
+                        resp_preview,
+                    )
                    stash_pending_tool_output(tool_name, tool_response)
+                else:
+                    logger.warning(
+                        "[SDK] PostToolUse for builtin %s but tool_response is None",
+                        tool_name,
+                    )

            return cast(SyncHookJSONOutput, {})

--- a/autogpt_platform/backend/backend/copilot/sdk/service.py
+++ b/autogpt_platform/backend/backend/copilot/sdk/service.py
@@ -11,7 +11,6 @@ from typing import Any

 from backend.util.exceptions import NotFoundError

-from .. import stream_registry
 from ..config import ChatConfig
 from ..model import (
    ChatMessage,
@@ -24,18 +23,14 @@ from ..response_model import (
    StreamBaseResponse,
    StreamError,
    StreamFinish,
+    StreamFinishStep,
    StreamHeartbeat,
    StreamStart,
    StreamTextDelta,
    StreamToolInputAvailable,
    StreamToolOutputAvailable,
 )
-from ..service import (
-    _build_system_prompt,
-    _execute_long_running_tool_with_streaming,
-    _generate_session_title,
-)
-from ..tools.models import OperationPendingResponse, OperationStartedResponse
+from ..service import _build_system_prompt, _generate_session_title
 from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
 from ..tracking import track_user_message
 from .response_adapter import SDKResponseAdapter
@@ -43,9 +38,9 @@ from .security_hooks import create_security_hooks
 from .tool_adapter import (
    COPILOT_TOOL_NAMES,
    SDK_DISALLOWED_TOOLS,
-    LongRunningCallback,
    create_copilot_mcp_server,
    set_execution_context,
+    wait_for_stash,
 )
 from .transcript import (
    cleanup_cli_project_dir,
@@ -121,9 +116,9 @@ When you create or modify important files (code, configs, outputs), you MUST:
   are available from previous turns

 ### Long-running tools
-Long-running tools (create_agent, edit_agent, etc.) are handled
-asynchronously.  You will receive an immediate response; the actual result
-is delivered to the user via a background stream.
+Long-running tools (create_agent, edit_agent, etc.) run synchronously
+with heartbeats to keep the connection alive. The frontend shows UI feedback
+during execution based on stream events.

 ### Sub-agent tasks
 - When using the Task tool, NEVER set `run_in_background` to true.
@@ -131,121 +126,6 @@ is delivered to the user via a background stream.
 """


-def _build_long_running_callback(user_id: str | None) -> LongRunningCallback:
-    """Build a callback that delegates long-running tools to the non-SDK infrastructure.
-
-    Long-running tools (create_agent, edit_agent, etc.) are delegated to the
-    existing background infrastructure: stream_registry (Redis Streams),
-    database persistence, and SSE reconnection.  This means results survive
-    page refreshes / pod restarts, and the frontend shows the proper loading
-    widget with progress updates.
-
-    The returned callback matches the ``LongRunningCallback`` signature:
-    ``(tool_name, args, session) -> MCP response dict``.
-    """
-
-    async def _callback(
-        tool_name: str, args: dict[str, Any], session: ChatSession
-    ) -> dict[str, Any]:
-        operation_id = str(uuid.uuid4())
-        task_id = str(uuid.uuid4())
-        tool_call_id = f"sdk-{uuid.uuid4().hex[:12]}"
-        session_id = session.session_id
-
-        # --- Build user-friendly messages (matches non-SDK service) ---
-        if tool_name == "create_agent":
-            desc = args.get("description", "")
-            desc_preview = (desc[:100] + "...") if len(desc) > 100 else desc
-            pending_msg = (
-                f"Creating your agent: {desc_preview}"
-                if desc_preview
-                else "Creating agent... This may take a few minutes."
-            )
-            started_msg = (
-                "Agent creation started. You can close this tab - "
-                "check your library in a few minutes."
-            )
-        elif tool_name == "edit_agent":
-            changes = args.get("changes", "")
-            changes_preview = (changes[:100] + "...") if len(changes) > 100 else changes
-            pending_msg = (
-                f"Editing agent: {changes_preview}"
-                if changes_preview
-                else "Editing agent... This may take a few minutes."
-            )
-            started_msg = (
-                "Agent edit started. You can close this tab - "
-                "check your library in a few minutes."
-            )
-        else:
-            pending_msg = f"Running {tool_name}... This may take a few minutes."
-            started_msg = (
-                f"{tool_name} started. You can close this tab - "
-                "check back in a few minutes."
-            )
-
-        # --- Register task in Redis for SSE reconnection ---
-        await stream_registry.create_task(
-            task_id=task_id,
-            session_id=session_id,
-            user_id=user_id,
-            tool_call_id=tool_call_id,
-            tool_name=tool_name,
-            operation_id=operation_id,
-        )
-
-        # --- Save OperationPendingResponse to chat history ---
-        pending_message = ChatMessage(
-            role="tool",
-            content=OperationPendingResponse(
-                message=pending_msg,
-                operation_id=operation_id,
-                tool_name=tool_name,
-            ).model_dump_json(),
-            tool_call_id=tool_call_id,
-        )
-        session.messages.append(pending_message)
-        await upsert_chat_session(session)
-
-        # --- Spawn background task (reuses non-SDK infrastructure) ---
-        bg_task = asyncio.create_task(
-            _execute_long_running_tool_with_streaming(
-                tool_name=tool_name,
-                parameters=args,
-                tool_call_id=tool_call_id,
-                operation_id=operation_id,
-                task_id=task_id,
-                session_id=session_id,
-                user_id=user_id,
-            )
-        )
-        _background_tasks.add(bg_task)
-        bg_task.add_done_callback(_background_tasks.discard)
-        await stream_registry.set_task_asyncio_task(task_id, bg_task)
-
-        logger.info(
-            f"[SDK] Long-running tool {tool_name} delegated to background "
-            f"(operation_id={operation_id}, task_id={task_id})"
-        )
-
-        # --- Return OperationStartedResponse as MCP tool result ---
-        # This flows through SDK → response adapter → frontend, triggering
-        # the loading widget with SSE reconnection support.
-        started_json = OperationStartedResponse(
-            message=started_msg,
-            operation_id=operation_id,
-            tool_name=tool_name,
-            task_id=task_id,
-        ).model_dump_json()
-
-        return {
-            "content": [{"type": "text", "text": started_json}],
-            "isError": False,
-        }
-
-    return _callback
-
-
 def _resolve_sdk_model() -> str | None:
    """Resolve the model name for the Claude Agent SDK CLI.

@@ -344,15 +224,15 @@ async def _compress_conversation_history(

    Returns the compressed prior messages (everything except the current message).
    """
-    prior = session.messages[:-1]
-    if len(prior) < 2:
-        return prior
+    messages = session.messages[:-1]
+    if len(messages) < 2:
+        return messages

    from backend.util.prompt import compress_context

    # Convert ChatMessages to dicts for compress_context
    messages_dict = []
-    for msg in prior:
+    for msg in messages:
        msg_dict: dict[str, Any] = {"role": msg.role}
        if msg.content:
            msg_dict["content"] = msg.content
@@ -400,7 +280,7 @@ async def _compress_conversation_history(
            for m in result.messages
        ]

-    return prior
+    return messages


 def _format_conversation_context(messages: list[ChatMessage]) -> str | None:
@@ -442,8 +322,8 @@ def _format_conversation_context(messages: list[ChatMessage]) -> str | None:
 def _is_tool_error_or_denial(content: str | None) -> bool:
    """Check if a tool message content indicates an error or denial.

-    We include these in conversation context so the agent doesn't
-    hallucinate success for operations that actually failed.
+    Currently unused — ``_format_conversation_context`` includes all tool
+    results.  Kept as a utility for future selective filtering.
    """
    if not content:
        return False
@@ -458,7 +338,7 @@ def _is_tool_error_or_denial(content: str | None) -> bool:
            "maximum",  # subtask-limit denial
            "denied",
            "blocked",
-            "failed",  # internal tool execution failures
+            "failed to",  # internal tool execution failures
            '"iserror": true',  # MCP protocol error flag
        )
    )
@@ -582,7 +462,7 @@ async def stream_chat_completion_sdk(
        set_execution_context(
            user_id,
            session,
-            long_running_callback=_build_long_running_callback(user_id),
+            long_running_callback=None,
        )
        try:
            from claude_agent_sdk import ClaudeAgentOptions, ClaudeSDKClient
@@ -674,7 +554,7 @@ async def stream_chat_completion_sdk(

            options = ClaudeAgentOptions(**sdk_options_kwargs)  # type: ignore[arg-type]

-            adapter = SDKResponseAdapter(message_id=message_id)
+            adapter = SDKResponseAdapter(message_id=message_id, session_id=session_id)
            adapter.set_task_id(task_id)

            async with ClaudeSDKClient(options=options) as client:
@@ -699,10 +579,13 @@ async def stream_chat_completion_sdk(
                    transcript_msg_count,
                    session_id,
                )
-
                logger.info(
-                    f"[SDK] Sending query ({len(session.messages)} msgs, "
-                    f"resume={use_resume})"
+                    "[SDK] [%s] Sending query — resume=%s, "
+                    "total_msgs=%d, query_len=%d",
+                    session_id[:12],
+                    use_resume,
+                    len(session.messages),
+                    len(query_message),
                )
                await client.query(query_message, session_id=session_id)

@@ -710,98 +593,296 @@ async def stream_chat_completion_sdk(
                accumulated_tool_calls: list[dict[str, Any]] = []
                has_appended_assistant = False
                has_tool_results = False
+                # Track persisted message count to skip DB count queries
+                # on incremental saves.  Initial save happened at line 545.
+                saved_msg_count = len(session.messages)

-                # Use an explicit async iterator with timeout to send
-                # heartbeats when the CLI is idle (e.g. executing tools).
-                # This prevents proxies/LBs from closing the SSE connection.
-                # asyncio.timeout() is preferred over asyncio.wait_for()
-                # because wait_for wraps in a separate Task whose cancellation
-                # can leave the async generator in a broken state.
+                # Use an explicit async iterator with non-cancelling heartbeats.
+                # CRITICAL: we must NOT cancel __anext__() mid-flight — doing so
+                # (via asyncio.timeout or wait_for) corrupts the SDK's internal
+                # anyio memory stream, causing StopAsyncIteration on the next
+                # call and silently dropping all in-flight tool results.
+                # Instead, wrap __anext__() in a Task and use asyncio.wait()
+                # with a timeout.  On timeout we emit a heartbeat but keep the
+                # Task alive so it can deliver the next message.
                msg_iter = client.receive_messages().__aiter__()
-                while not stream_completed:
-                    try:
-                        async with asyncio.timeout(_HEARTBEAT_INTERVAL):
-                            sdk_msg = await msg_iter.__anext__()
-                    except TimeoutError:
-                        yield StreamHeartbeat()
-                        continue
-                    except StopAsyncIteration:
-                        break
+                pending_task: asyncio.Task[Any] | None = None
+                try:
+                    while not stream_completed:
+                        if pending_task is None:

-                    logger.debug(
-                        f"[SDK] Received: {type(sdk_msg).__name__} "
-                        f"{getattr(sdk_msg, 'subtype', '')}"
-                    )
-                    for response in adapter.convert_message(sdk_msg):
-                        if isinstance(response, StreamStart):
+                            async def _next_msg() -> Any:
+                                return await msg_iter.__anext__()
+
+                            pending_task = asyncio.create_task(_next_msg())
+
+                        done, _ = await asyncio.wait(
+                            {pending_task}, timeout=_HEARTBEAT_INTERVAL
+                        )
+
+                        if not done:
+                            # Timeout — emit heartbeat but keep the task alive
+                            yield StreamHeartbeat()
                            continue

-                        # Log tool events for debugging visibility issues
+                        # Task completed — get result
+                        pending_task = None
+                        try:
+                            sdk_msg = done.pop().result()
+                        except StopAsyncIteration:
+                            logger.info(
+                                "[SDK] [%s] Stream ended normally "
+                                "(StopAsyncIteration)",
+                                session_id[:12],
+                            )
+                            break
+                        except Exception as stream_err:
+                            # SDK sends {"type": "error"} which raises
+                            # Exception in receive_messages() — capture it
+                            # so the session can still be saved and the
+                            # frontend gets a clean finish.
+                            logger.error(
+                                "[SDK] [%s] Stream error from SDK: %s",
+                                session_id[:12],
+                                stream_err,
+                                exc_info=True,
+                            )
+                            yield StreamError(
+                                errorText=f"SDK stream error: {stream_err}",
+                                code="sdk_stream_error",
+                            )
+                            break
+
+                        logger.info(
+                            "[SDK] [%s] Received: %s %s "
+                            "(unresolved=%d, current=%d, resolved=%d)",
+                            session_id[:12],
+                            type(sdk_msg).__name__,
+                            getattr(sdk_msg, "subtype", ""),
+                            len(adapter.current_tool_calls)
+                            - len(adapter.resolved_tool_calls),
+                            len(adapter.current_tool_calls),
+                            len(adapter.resolved_tool_calls),
+                        )
+
+                        # Race-condition fix: SDK hooks (PostToolUse) are
+                        # executed asynchronously via start_soon() — the next
+                        # message can arrive before the hook stashes output.
+                        # wait_for_stash() awaits an asyncio.Event signaled by
+                        # stash_pending_tool_output(), completing as soon as
+                        # the hook finishes (typically <1ms).  The sleep(0)
+                        # after lets any remaining concurrent hooks complete.
+                        #
+                        # Skip for parallel tool continuations: when the SDK
+                        # sends parallel tool calls as separate
+                        # AssistantMessages (each containing only
+                        # ToolUseBlocks), we must NOT wait/flush — the prior
+                        # tools are still executing concurrently.
+                        from claude_agent_sdk import (
+                            AssistantMessage,
+                            ResultMessage,
+                            ToolUseBlock,
+                        )
+
+                        is_parallel_continuation = isinstance(
+                            sdk_msg, AssistantMessage
+                        ) and all(isinstance(b, ToolUseBlock) for b in sdk_msg.content)
+
+                        if (
+                            adapter.has_unresolved_tool_calls
+                            and isinstance(sdk_msg, (AssistantMessage, ResultMessage))
+                            and not is_parallel_continuation
+                        ):
+                            if await wait_for_stash(timeout=0.5):
+                                await asyncio.sleep(0)
+                            else:
+                                logger.warning(
+                                    "[SDK] [%s] Timed out waiting for "
+                                    "PostToolUse hook stash "
+                                    "(%d unresolved tool calls)",
+                                    session_id[:12],
+                                    len(adapter.current_tool_calls)
+                                    - len(adapter.resolved_tool_calls),
+                                )
+
+                        for response in adapter.convert_message(sdk_msg):
+                            if isinstance(response, StreamStart):
+                                continue
+
+                            # Log tool events for debugging
+                            if isinstance(
+                                response,
+                                (
+                                    StreamToolInputAvailable,
+                                    StreamToolOutputAvailable,
+                                ),
+                            ):
+                                extra = ""
+                                if isinstance(response, StreamToolOutputAvailable):
+                                    out_len = len(str(response.output))
+                                    extra = f", output_len={out_len}"
+                                logger.info(
+                                    "[SDK] [%s] Tool event: %s, tool=%s%s",
+                                    session_id[:12],
+                                    type(response).__name__,
+                                    getattr(response, "toolName", "N/A"),
+                                    extra,
+                                )
+
+                            yield response
+
+                            if isinstance(response, StreamTextDelta):
+                                delta = response.delta or ""
+                                # After tool results, start a new assistant
+                                # message for the post-tool text.
+                                if has_tool_results and has_appended_assistant:
+                                    assistant_response = ChatMessage(
+                                        role="assistant", content=delta
+                                    )
+                                    accumulated_tool_calls = []
+                                    has_appended_assistant = False
+                                    has_tool_results = False
+                                    session.messages.append(assistant_response)
+                                    has_appended_assistant = True
+                                else:
+                                    assistant_response.content = (
+                                        assistant_response.content or ""
+                                    ) + delta
+                                    if not has_appended_assistant:
+                                        session.messages.append(assistant_response)
+                                        has_appended_assistant = True
+
+                            elif isinstance(response, StreamToolInputAvailable):
+                                accumulated_tool_calls.append(
+                                    {
+                                        "id": response.toolCallId,
+                                        "type": "function",
+                                        "function": {
+                                            "name": response.toolName,
+                                            "arguments": json.dumps(
+                                                response.input or {}
+                                            ),
+                                        },
+                                    }
+                                )
+                                assistant_response.tool_calls = accumulated_tool_calls
+                                if not has_appended_assistant:
+                                    session.messages.append(assistant_response)
+                                    has_appended_assistant = True
+                                # Save before tool execution starts so the
+                                # pending tool call is visible on refresh /
+                                # other devices.
+                                try:
+                                    await upsert_chat_session(
+                                        session,
+                                        existing_message_count=saved_msg_count,
+                                    )
+                                    saved_msg_count = len(session.messages)
+                                except Exception as save_err:
+                                    logger.warning(
+                                        "[SDK] [%s] Incremental save " "failed: %s",
+                                        session_id[:12],
+                                        save_err,
+                                    )
+
+                            elif isinstance(response, StreamToolOutputAvailable):
+                                session.messages.append(
+                                    ChatMessage(
+                                        role="tool",
+                                        content=(
+                                            response.output
+                                            if isinstance(response.output, str)
+                                            else str(response.output)
+                                        ),
+                                        tool_call_id=response.toolCallId,
+                                    )
+                                )
+                                has_tool_results = True
+                                # Save after tool completes so the result is
+                                # visible on refresh / other devices.
+                                try:
+                                    await upsert_chat_session(
+                                        session,
+                                        existing_message_count=saved_msg_count,
+                                    )
+                                    saved_msg_count = len(session.messages)
+                                except Exception as save_err:
+                                    logger.warning(
+                                        "[SDK] [%s] Incremental save " "failed: %s",
+                                        session_id[:12],
+                                        save_err,
+                                    )
+
+                            elif isinstance(response, StreamFinish):
+                                stream_completed = True
+
+                except asyncio.CancelledError:
+                    # Task/generator was cancelled (e.g. client disconnect,
+                    # server shutdown).  Log and let the safety-net / finally
+                    # blocks handle cleanup.
+                    logger.warning(
+                        "[SDK] [%s] Streaming loop cancelled "
+                        "(asyncio.CancelledError)",
+                        session_id[:12],
+                    )
+                    raise
+                finally:
+                    # Cancel the pending __anext__ task to avoid a leaked
+                    # coroutine.  This is safe even if the task already
+                    # completed.
+                    if pending_task is not None and not pending_task.done():
+                        pending_task.cancel()
+                        try:
+                            await pending_task
+                        except (asyncio.CancelledError, StopAsyncIteration):
+                            pass
+
+                # Safety net: if tools are still unresolved after the
+                # streaming loop (e.g. StopAsyncIteration before ResultMessage,
+                # or SDK not sending UserMessages for built-in tools), flush
+                # them now so the frontend stops showing spinners.
+                if adapter.has_unresolved_tool_calls:
+                    logger.warning(
+                        "[SDK] [%s] %d unresolved tool(s) after stream loop — "
+                        "flushing as safety net",
+                        session_id[:12],
+                        len(adapter.current_tool_calls)
+                        - len(adapter.resolved_tool_calls),
+                    )
+                    safety_responses: list[StreamBaseResponse] = []
+                    adapter._flush_unresolved_tool_calls(safety_responses)
+                    for response in safety_responses:
                        if isinstance(
                            response,
                            (StreamToolInputAvailable, StreamToolOutputAvailable),
                        ):
                            logger.info(
-                                "[SDK] Tool event: %s, tool=%s",
+                                "[SDK] [%s] Safety flush: %s, tool=%s",
+                                session_id[:12],
                                type(response).__name__,
                                getattr(response, "toolName", "N/A"),
                            )
-
                        yield response

-                        if isinstance(response, StreamTextDelta):
-                            delta = response.delta or ""
-                            # After tool results, start a new assistant
-                            # message for the post-tool text.
-                            if has_tool_results and has_appended_assistant:
-                                assistant_response = ChatMessage(
-                                    role="assistant", content=delta
-                                )
-                                accumulated_tool_calls = []
-                                has_appended_assistant = False
-                                has_tool_results = False
-                                session.messages.append(assistant_response)
-                                has_appended_assistant = True
-                            else:
-                                assistant_response.content = (
-                                    assistant_response.content or ""
-                                ) + delta
-                                if not has_appended_assistant:
-                                    session.messages.append(assistant_response)
-                                    has_appended_assistant = True
-
-                        elif isinstance(response, StreamToolInputAvailable):
-                            accumulated_tool_calls.append(
-                                {
-                                    "id": response.toolCallId,
-                                    "type": "function",
-                                    "function": {
-                                        "name": response.toolName,
-                                        "arguments": json.dumps(response.input or {}),
-                                    },
-                                }
-                            )
-                            assistant_response.tool_calls = accumulated_tool_calls
-                            if not has_appended_assistant:
-                                session.messages.append(assistant_response)
-                                has_appended_assistant = True
-
-                        elif isinstance(response, StreamToolOutputAvailable):
-                            session.messages.append(
-                                ChatMessage(
-                                    role="tool",
-                                    content=(
-                                        response.output
-                                        if isinstance(response.output, str)
-                                        else str(response.output)
-                                    ),
-                                    tool_call_id=response.toolCallId,
-                                )
-                            )
-                            has_tool_results = True
-
-                        elif isinstance(response, StreamFinish):
-                            stream_completed = True
+                # If the stream ended without a ResultMessage (no
+                # StreamFinish), the SDK CLI exited unexpectedly.  Close
+                # the open step and emit StreamFinish so the frontend
+                # transitions to the "ready" state.
+                if not stream_completed:
+                    logger.warning(
+                        "[SDK] [%s] Stream ended without ResultMessage "
+                        "(StopAsyncIteration) — emitting StreamFinish",
+                        session_id[:12],
+                    )
+                    if adapter.step_open:
+                        yield StreamFinishStep()
+                        adapter.step_open = False
+                    closing_responses: list[StreamBaseResponse] = []
+                    adapter._end_text_if_open(closing_responses)
+                    for r in closing_responses:
+                        yield r
+                    yield StreamFinish()
+                    stream_completed = True

                if (
                    assistant_response.content or assistant_response.tool_calls
@@ -857,12 +938,20 @@ async def stream_chat_completion_sdk(
            )

        await asyncio.shield(upsert_chat_session(session))
-        logger.debug(
-            f"[SDK] Session {session_id} saved with {len(session.messages)} messages"
+        logger.info(
+            "[SDK] [%s] Session saved with %d messages",
+            session_id[:12],
+            len(session.messages),
        )
        if not stream_completed:
            yield StreamFinish()

+    except asyncio.CancelledError:
+        # Client disconnect / server shutdown — log but re-raise so
+        # the framework can clean up.  The finally block still runs
+        # for transcript upload.
+        logger.warning("[SDK] [%s] Session cancelled (CancelledError)", session_id[:12])
+        raise
    except Exception as e:
        logger.error(f"[SDK] Error: {e}", exc_info=True)
        try:
--- a/autogpt_platform/backend/backend/copilot/sdk/tool_adapter.py
+++ b/autogpt_platform/backend/backend/copilot/sdk/tool_adapter.py
@@ -9,6 +9,7 @@ via a callback provided by the service layer.  This avoids wasteful SDK polling
 and makes results survive page refreshes.
 """

+import asyncio
 import itertools
 import json
 import logging
@@ -44,6 +45,14 @@ _current_session: ContextVar[ChatSession | None] = ContextVar(
 _pending_tool_outputs: ContextVar[dict[str, list[str]]] = ContextVar(
    "pending_tool_outputs", default=None  # type: ignore[arg-type]
 )
+# Event signaled whenever stash_pending_tool_output() adds a new entry.
+# Used by the streaming loop to wait for PostToolUse hooks to complete
+# instead of sleeping an arbitrary duration.  The SDK fires hooks via
+# start_soon (fire-and-forget) so the next message can arrive before
+# the hook stashes its output — this event bridges that gap.
+_stash_event: ContextVar[asyncio.Event | None] = ContextVar(
+    "_stash_event", default=None
+)

 # Callback type for delegating long-running tools to the non-SDK infrastructure.
 # Args: (tool_name, arguments, session) → MCP-formatted response dict.
@@ -76,6 +85,7 @@ def set_execution_context(
    _current_user_id.set(user_id)
    _current_session.set(session)
    _pending_tool_outputs.set({})
+    _stash_event.set(asyncio.Event())
    _long_running_callback.set(long_running_callback)


@@ -134,6 +144,43 @@ def stash_pending_tool_output(tool_name: str, output: Any) -> None:
        except (TypeError, ValueError):
            text = str(output)
    pending.setdefault(tool_name, []).append(text)
+    # Signal any waiters that new output is available.
+    event = _stash_event.get(None)
+    if event is not None:
+        event.set()
+
+
+async def wait_for_stash(timeout: float = 0.5) -> bool:
+    """Wait for a PostToolUse hook to stash tool output.
+
+    The SDK fires PostToolUse hooks asynchronously via ``start_soon()`` —
+    the next message (AssistantMessage/ResultMessage) can arrive before the
+    hook completes and stashes its output.  This function bridges that gap
+    by waiting on the ``_stash_event``, which is signaled by
+    :func:`stash_pending_tool_output`.
+
+    After the event fires, callers should ``await asyncio.sleep(0)`` to
+    give any remaining concurrent hooks a chance to complete.
+
+    Returns ``True`` if a stash signal was received, ``False`` on timeout.
+    The timeout is a safety net — normally the stash happens within
+    microseconds of yielding to the event loop.
+    """
+    event = _stash_event.get(None)
+    if event is None:
+        return False
+    # Fast path: hook already completed before we got here.
+    if event.is_set():
+        event.clear()
+        return True
+    # Slow path: wait for the hook to signal.
+    try:
+        async with asyncio.timeout(timeout):
+            await event.wait()
+        event.clear()
+        return True
+    except TimeoutError:
+        return False


 async def _execute_tool_sync(
--- a/autogpt_platform/backend/backend/copilot/service.py
+++ b/autogpt_platform/backend/backend/copilot/service.py
@@ -52,6 +52,7 @@ from .response_model import (
    StreamFinish,
    StreamFinishStep,
    StreamHeartbeat,
+    StreamLongRunningStart,
    StreamStart,
    StreamStartStep,
    StreamTextDelta,
@@ -63,12 +64,7 @@ from .response_model import (
    StreamUsage,
 )
 from .tools import execute_tool, get_tool, tools
-from .tools.models import (
-    ErrorResponse,
-    OperationInProgressResponse,
-    OperationPendingResponse,
-    OperationStartedResponse,
-)
+from .tools.models import ErrorResponse
 from .tracking import track_user_message

 logger = logging.getLogger(__name__)
@@ -1402,16 +1398,15 @@ async def _yield_tool_call(
    """
    Yield a tool call and its execution result.

-    For tools marked with `is_long_running=True` (like agent generation), spawns a
-    background task so the operation survives SSE disconnections. For other tools,
-    yields heartbeat events every 15 seconds to keep the SSE connection alive.
+    Executes tools synchronously and yields heartbeat events every 15 seconds to
+    keep the SSE connection alive during execution. The is_long_running property
+    is only used by the frontend to display UI feedback during long operations.

    Raises:
        orjson.JSONDecodeError: If tool call arguments cannot be parsed as JSON
        KeyError: If expected tool call fields are missing
        TypeError: If tool call structure is invalid
    """
-    import uuid as uuid_module

    tool_name = tool_calls[yield_idx]["function"]["name"]
    tool_call_id = tool_calls[yield_idx]["id"]
@@ -1429,163 +1424,17 @@ async def _yield_tool_call(
        input=arguments,
    )

-    # Check if this tool is long-running (survives SSE disconnection)
+    # Notify frontend if this is a long-running tool (e.g., agent generation)
    tool = get_tool(tool_name)
    if tool and tool.is_long_running:
-        # Atomic check-and-set: returns False if operation already running (lost race)
-        if not await _mark_operation_started(tool_call_id):
-            logger.info(
-                f"Tool call {tool_call_id} already in progress, returning status"
-            )
-            # Build dynamic message based on tool name
-            if tool_name == "create_agent":
-                in_progress_msg = "Agent creation already in progress. Please wait..."
-            elif tool_name == "edit_agent":
-                in_progress_msg = "Agent edit already in progress. Please wait..."
-            else:
-                in_progress_msg = f"{tool_name} already in progress. Please wait..."
-
-            yield StreamToolOutputAvailable(
-                toolCallId=tool_call_id,
-                toolName=tool_name,
-                output=OperationInProgressResponse(
-                    message=in_progress_msg,
-                    tool_call_id=tool_call_id,
-                ).model_dump_json(),
-                success=True,
-            )
-            return
-
-        # Generate operation ID and task ID
-        operation_id = str(uuid_module.uuid4())
-        task_id = str(uuid_module.uuid4())
-
-        # Build a user-friendly message based on tool and arguments
-        if tool_name == "create_agent":
-            agent_desc = arguments.get("description", "")
-            # Truncate long descriptions for the message
-            desc_preview = (
-                (agent_desc[:100] + "...") if len(agent_desc) > 100 else agent_desc
-            )
-            pending_msg = (
-                f"Creating your agent: {desc_preview}"
-                if desc_preview
-                else "Creating agent... This may take a few minutes."
-            )
-            started_msg = (
-                "Agent creation started. You can close this tab - "
-                "check your library in a few minutes."
-            )
-        elif tool_name == "edit_agent":
-            changes = arguments.get("changes", "")
-            changes_preview = (changes[:100] + "...") if len(changes) > 100 else changes
-            pending_msg = (
-                f"Editing agent: {changes_preview}"
-                if changes_preview
-                else "Editing agent... This may take a few minutes."
-            )
-            started_msg = (
-                "Agent edit started. You can close this tab - "
-                "check your library in a few minutes."
-            )
-        else:
-            pending_msg = f"Running {tool_name}... This may take a few minutes."
-            started_msg = (
-                f"{tool_name} started. You can close this tab - "
-                "check back in a few minutes."
-            )
-
-        # Track appended message for rollback on failure
-        pending_message: ChatMessage | None = None
-
-        # Wrap session save and task creation in try-except to release lock on failure
-        try:
-            # Create task in stream registry for SSE reconnection support
-            await stream_registry.create_task(
-                task_id=task_id,
-                session_id=session.session_id,
-                user_id=session.user_id,
-                tool_call_id=tool_call_id,
-                tool_name=tool_name,
-                operation_id=operation_id,
-            )
-
-            # Attach tool_call and save pending result — lock serialises
-            # concurrent session mutations during parallel execution.
-            async def _save_pending() -> None:
-                nonlocal pending_message
-                session.add_tool_call_to_current_turn(tool_calls[yield_idx])
-                pending_message = ChatMessage(
-                    role="tool",
-                    content=OperationPendingResponse(
-                        message=pending_msg,
-                        operation_id=operation_id,
-                        tool_name=tool_name,
-                    ).model_dump_json(),
-                    tool_call_id=tool_call_id,
-                )
-                session.messages.append(pending_message)
-                await upsert_chat_session(session)
-
-            await _with_optional_lock(session_lock, _save_pending)
-            logger.info(
-                f"Saved pending operation {operation_id} (task_id={task_id}) "
-                f"for tool {tool_name} in session {session.session_id}"
-            )
-
-            # Store task reference in module-level set to prevent GC before completion
-            bg_task = asyncio.create_task(
-                _execute_long_running_tool_with_streaming(
-                    tool_name=tool_name,
-                    parameters=arguments,
-                    tool_call_id=tool_call_id,
-                    operation_id=operation_id,
-                    task_id=task_id,
-                    session_id=session.session_id,
-                    user_id=session.user_id,
-                )
-            )
-            _background_tasks.add(bg_task)
-            bg_task.add_done_callback(_background_tasks.discard)
-
-            # Associate the asyncio task with the stream registry task
-            await stream_registry.set_task_asyncio_task(task_id, bg_task)
-        except Exception as e:
-            # Roll back appended messages — use identity-based removal so
-            # it works even when other parallel tools have appended after us.
-            async def _rollback() -> None:
-                if pending_message and pending_message in session.messages:
-                    session.messages.remove(pending_message)
-
-            await _with_optional_lock(session_lock, _rollback)
-
-            # Release the Redis lock since the background task won't be spawned
-            await _mark_operation_completed(tool_call_id)
-            # Mark stream registry task as failed if it was created
-            try:
-                await stream_registry.mark_task_completed(task_id, status="failed")
-            except Exception as mark_err:
-                logger.warning(f"Failed to mark task {task_id} as failed: {mark_err}")
-            logger.error(
-                f"Failed to setup long-running tool {tool_name}: {e}", exc_info=True
-            )
-            raise
-
-        # Return immediately - don't wait for completion
-        yield StreamToolOutputAvailable(
-            toolCallId=tool_call_id,
-            toolName=tool_name,
-            output=OperationStartedResponse(
-                message=started_msg,
-                operation_id=operation_id,
-                tool_name=tool_name,
-                task_id=task_id,  # Include task_id for SSE reconnection
-            ).model_dump_json(),
-            success=True,
+        yield StreamLongRunningStart(
+            data={
+                "toolCallId": tool_call_id,
+                "toolName": tool_name,
+            }
        )
-        return

-    # Normal flow: Run tool execution in background task with heartbeats
+    # Run tool execution synchronously with heartbeats
    tool_task = asyncio.create_task(
        execute_tool(
            tool_name=tool_name,
--- a/autogpt_platform/backend/backend/copilot/tools/agent_generator/core.py
+++ b/autogpt_platform/backend/backend/copilot/tools/agent_generator/core.py
@@ -540,21 +540,15 @@ async def decompose_goal(
 async def generate_agent(
    instructions: DecompositionResult | dict[str, Any],
    library_agents: list[AgentSummary] | list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
 ) -> dict[str, Any] | None:
    """Generate agent JSON from instructions.

    Args:
        instructions: Structured instructions from decompose_goal
        library_agents: User's library agents available for sub-agent composition
-        operation_id: Operation ID for async processing (enables Redis Streams
-            completion notification)
-        task_id: Task ID for async processing (enables Redis Streams persistence
-            and SSE delivery)

    Returns:
-        Agent JSON dict, {"status": "accepted"} for async, error dict {"type": "error", ...}, or None on error
+        Agent JSON dict, error dict {"type": "error", ...}, or None on error

    Raises:
        AgentGeneratorNotConfiguredError: If the external service is not configured.
@@ -562,13 +556,9 @@ async def generate_agent(
    _check_service_configured()
    logger.info("Calling external Agent Generator service for generate_agent")
    result = await generate_agent_external(
-        dict(instructions), _to_dict_list(library_agents), operation_id, task_id
+        dict(instructions), _to_dict_list(library_agents)
    )

-    # Don't modify async response
-    if result and result.get("status") == "accepted":
-        return result
-
    if result:
        if isinstance(result, dict) and result.get("type") == "error":
            return result
@@ -759,8 +749,6 @@ async def generate_agent_patch(
    update_request: str,
    current_agent: dict[str, Any],
    library_agents: list[AgentSummary] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
 ) -> dict[str, Any] | None:
    """Update an existing agent using natural language.

@@ -773,12 +761,10 @@ async def generate_agent_patch(
        update_request: Natural language description of changes
        current_agent: Current agent JSON
        library_agents: User's library agents available for sub-agent composition
-        operation_id: Operation ID for async processing (enables Redis Streams callback)
-        task_id: Task ID for async processing (enables Redis Streams callback)

    Returns:
        Updated agent JSON, clarifying questions dict {"type": "clarifying_questions", ...},
-        {"status": "accepted"} for async, error dict {"type": "error", ...}, or None on error
+        error dict {"type": "error", ...}, or None on error

    Raises:
        AgentGeneratorNotConfiguredError: If the external service is not configured.
@@ -789,8 +775,6 @@ async def generate_agent_patch(
        update_request,
        current_agent,
        _to_dict_list(library_agents),
-        operation_id,
-        task_id,
    )


--- a/autogpt_platform/backend/backend/copilot/tools/agent_generator/dummy.py
+++ b/autogpt_platform/backend/backend/copilot/tools/agent_generator/dummy.py
@@ -101,8 +101,6 @@ async def decompose_goal_dummy(
 async def generate_agent_dummy(
    instructions: dict[str, Any],
    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
 ) -> dict[str, Any]:
    """Return dummy agent JSON after a simulated delay."""
    logger.info("Using dummy agent generator for generate_agent (30s delay)")
@@ -114,8 +112,6 @@ async def generate_agent_patch_dummy(
    update_request: str,
    current_agent: dict[str, Any],
    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
 ) -> dict[str, Any]:
    """Return dummy patched agent (returns the current agent with updated description)."""
    logger.info("Using dummy agent generator for generate_agent_patch")
--- a/autogpt_platform/backend/backend/copilot/tools/agent_generator/service.py
+++ b/autogpt_platform/backend/backend/copilot/tools/agent_generator/service.py
@@ -242,24 +242,18 @@ async def decompose_goal_external(
 async def generate_agent_external(
    instructions: dict[str, Any],
    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
 ) -> dict[str, Any] | None:
    """Call the external service to generate an agent from instructions.

    Args:
        instructions: Structured instructions from decompose_goal
        library_agents: User's library agents available for sub-agent composition
-        operation_id: Operation ID for async processing (enables Redis Streams callback)
-        task_id: Task ID for async processing (enables Redis Streams callback)

    Returns:
-        Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
+        Agent JSON dict or error dict {"type": "error", ...} on error
    """
    if _is_dummy_mode():
-        return await generate_agent_dummy(
-            instructions, library_agents, operation_id, task_id
-        )
+        return await generate_agent_dummy(instructions, library_agents)

    client = _get_client()

@@ -267,25 +261,9 @@ async def generate_agent_external(
    payload: dict[str, Any] = {"instructions": instructions}
    if library_agents:
        payload["library_agents"] = library_agents
-    if operation_id and task_id:
-        payload["operation_id"] = operation_id
-        payload["task_id"] = task_id

    try:
        response = await client.post("/api/generate-agent", json=payload)
-
-        # Handle 202 Accepted for async processing
-        if response.status_code == 202:
-            logger.info(
-                f"Agent Generator accepted async request "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return {
-                "status": "accepted",
-                "operation_id": operation_id,
-                "task_id": task_id,
-            }
-
        response.raise_for_status()
        data = response.json()

@@ -317,8 +295,6 @@ async def generate_agent_patch_external(
    update_request: str,
    current_agent: dict[str, Any],
    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
 ) -> dict[str, Any] | None:
    """Call the external service to generate a patch for an existing agent.

@@ -326,15 +302,13 @@ async def generate_agent_patch_external(
        update_request: Natural language description of changes
        current_agent: Current agent JSON
        library_agents: User's library agents available for sub-agent composition
-        operation_id: Operation ID for async processing (enables Redis Streams callback)
-        task_id: Task ID for async processing (enables Redis Streams callback)

    Returns:
-        Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
+        Updated agent JSON, clarifying questions dict, or error dict on error
    """
    if _is_dummy_mode():
        return await generate_agent_patch_dummy(
-            update_request, current_agent, library_agents, operation_id, task_id
+            update_request, current_agent, library_agents
        )

    client = _get_client()
@@ -346,25 +320,9 @@ async def generate_agent_patch_external(
    }
    if library_agents:
        payload["library_agents"] = library_agents
-    if operation_id and task_id:
-        payload["operation_id"] = operation_id
-        payload["task_id"] = task_id

    try:
        response = await client.post("/api/update-agent", json=payload)
-
-        # Handle 202 Accepted for async processing
-        if response.status_code == 202:
-            logger.info(
-                f"Agent Generator accepted async update request "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return {
-                "status": "accepted",
-                "operation_id": operation_id,
-                "task_id": task_id,
-            }
-
        response.raise_for_status()
        data = response.json()

--- a/autogpt_platform/backend/backend/copilot/tools/base.py
+++ b/autogpt_platform/backend/backend/copilot/tools/base.py
@@ -38,12 +38,7 @@ class BaseTool:

    @property
    def is_long_running(self) -> bool:
-        """Whether this tool is long-running and should execute in background.
-
-        Long-running tools (like agent generation) are executed via background
-        tasks to survive SSE disconnections. The result is persisted to chat
-        history and visible when the user refreshes.
-        """
+        """Whether this tool takes a long time to execute (triggers long-running UI)."""
        return False

    def as_openai_tool(self) -> ChatCompletionToolParam:
--- a/autogpt_platform/backend/backend/copilot/tools/create_agent.py
+++ b/autogpt_platform/backend/backend/copilot/tools/create_agent.py
@@ -18,7 +18,6 @@ from .base import BaseTool
 from .models import (
    AgentPreviewResponse,
    AgentSavedResponse,
-    AsyncProcessingResponse,
    ClarificationNeededResponse,
    ClarifyingQuestion,
    ErrorResponse,
@@ -49,6 +48,7 @@ class CreateAgentTool(BaseTool):

    @property
    def is_long_running(self) -> bool:
+        """Agent generation takes several minutes."""
        return True

    @property
@@ -100,10 +100,6 @@ class CreateAgentTool(BaseTool):
        save = kwargs.get("save", True)
        session_id = session.session_id if session else None

-        # Extract async processing params (passed by long-running tool handler)
-        operation_id = kwargs.get("_operation_id")
-        task_id = kwargs.get("_task_id")
-
        if not description:
            return ErrorResponse(
                message="Please provide a description of what the agent should do.",
@@ -230,8 +226,6 @@ class CreateAgentTool(BaseTool):
            agent_json = await generate_agent(
                decomposition_result,
                library_agents,
-                operation_id=operation_id,
-                task_id=task_id,
            )
        except AgentGeneratorNotConfiguredError:
            return ErrorResponse(
@@ -276,19 +270,6 @@ class CreateAgentTool(BaseTool):
                session_id=session_id,
            )

-        # Check if Agent Generator accepted for async processing
-        if agent_json.get("status") == "accepted":
-            logger.info(
-                f"Agent generation delegated to async processing "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return AsyncProcessingResponse(
-                message="Agent generation started. You'll be notified when it's complete.",
-                operation_id=operation_id,
-                task_id=task_id,
-                session_id=session_id,
-            )
-
        agent_name = agent_json.get("name", "Generated Agent")
        agent_description = agent_json.get("description", "")
        node_count = len(agent_json.get("nodes", []))
--- a/autogpt_platform/backend/backend/copilot/tools/customize_agent.py
+++ b/autogpt_platform/backend/backend/copilot/tools/customize_agent.py
@@ -48,6 +48,7 @@ class CustomizeAgentTool(BaseTool):

    @property
    def is_long_running(self) -> bool:
+        """Agent customization takes several minutes."""
        return True

    @property
--- a/autogpt_platform/backend/backend/copilot/tools/edit_agent.py
+++ b/autogpt_platform/backend/backend/copilot/tools/edit_agent.py
@@ -17,7 +17,6 @@ from .base import BaseTool
 from .models import (
    AgentPreviewResponse,
    AgentSavedResponse,
-    AsyncProcessingResponse,
    ClarificationNeededResponse,
    ClarifyingQuestion,
    ErrorResponse,
@@ -47,6 +46,7 @@ class EditAgentTool(BaseTool):

    @property
    def is_long_running(self) -> bool:
+        """Agent editing takes several minutes."""
        return True

    @property
@@ -105,10 +105,6 @@ class EditAgentTool(BaseTool):
        save = kwargs.get("save", True)
        session_id = session.session_id if session else None

-        # Extract async processing params (passed by long-running tool handler)
-        operation_id = kwargs.get("_operation_id")
-        task_id = kwargs.get("_task_id")
-
        if not agent_id:
            return ErrorResponse(
                message="Please provide the agent ID to edit.",
@@ -157,8 +153,6 @@ class EditAgentTool(BaseTool):
                update_request,
                current_agent,
                library_agents,
-                operation_id=operation_id,
-                task_id=task_id,
            )
        except AgentGeneratorNotConfiguredError:
            return ErrorResponse(
@@ -178,19 +172,6 @@ class EditAgentTool(BaseTool):
                session_id=session_id,
            )

-        # Check if Agent Generator accepted for async processing
-        if result.get("status") == "accepted":
-            logger.info(
-                f"Agent edit delegated to async processing "
-                f"(operation_id={operation_id}, task_id={task_id})"
-            )
-            return AsyncProcessingResponse(
-                message="Agent edit started. You'll be notified when it's complete.",
-                operation_id=operation_id,
-                task_id=task_id,
-                session_id=session_id,
-            )
-
        # Check if the result is an error from the external service
        if isinstance(result, dict) and result.get("type") == "error":
            error_msg = result.get("error", "Unknown error")
--- a/autogpt_platform/backend/backend/copilot/tools/models.py
+++ b/autogpt_platform/backend/backend/copilot/tools/models.py
@@ -459,23 +459,6 @@ class OperationInProgressResponse(ToolResponseBase):
    tool_call_id: str


-class AsyncProcessingResponse(ToolResponseBase):
-    """Response when an operation has been delegated to async processing.
-
-    This is returned by tools when the external service accepts the request
-    for async processing (HTTP 202 Accepted). The Redis Streams completion
-    consumer will handle the result when the external service completes.
-
-    The status field is specifically "accepted" to allow the long-running tool
-    handler to detect this response and skip LLM continuation.
-    """
-
-    type: ResponseType = ResponseType.OPERATION_STARTED
-    status: str = "accepted"  # Must be "accepted" for detection
-    operation_id: str | None = None
-    task_id: str | None = None
-
-
 class WebFetchResponse(ToolResponseBase):
    """Response for web_fetch tool."""

--- a/autogpt_platform/backend/poetry.lock
+++ b/autogpt_platform/backend/poetry.lock
@@ -899,17 +899,17 @@ files = [

 [[package]]
 name = "claude-agent-sdk"
-version = "0.1.35"
+version = "0.1.39"
 description = "Python SDK for Claude Code"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "claude_agent_sdk-0.1.35-py3-none-macosx_11_0_arm64.whl", hash = "sha256:df67f4deade77b16a9678b3a626c176498e40417f33b04beda9628287f375591"},
-    {file = "claude_agent_sdk-0.1.35-py3-none-manylinux_2_17_aarch64.whl", hash = "sha256:14963944f55ded7c8ed518feebfa5b4284aa6dd8d81aeff2e5b21a962ce65097"},
-    {file = "claude_agent_sdk-0.1.35-py3-none-manylinux_2_17_x86_64.whl", hash = "sha256:84344dcc535d179c1fc8a11c6f34c37c3b583447bdf09d869effb26514fd7a65"},
-    {file = "claude_agent_sdk-0.1.35-py3-none-win_amd64.whl", hash = "sha256:1b3d54b47448c93f6f372acd4d1757f047c3c1e8ef5804be7a1e3e53e2c79a5f"},
-    {file = "claude_agent_sdk-0.1.35.tar.gz", hash = "sha256:0f98e2b3c71ca85abfc042e7a35c648df88e87fda41c52e6779ef7b038dcbb52"},
+    {file = "claude_agent_sdk-0.1.39-py3-none-macosx_11_0_arm64.whl", hash = "sha256:6ed6a79781f545b761b9fe467bc5ae213a103c9d3f0fe7a9dad3c01790ed58fa"},
+    {file = "claude_agent_sdk-0.1.39-py3-none-manylinux_2_17_aarch64.whl", hash = "sha256:0c03b5a3772eaec42e29ea39240c7d24b760358082f2e36336db9e71dde3dda4"},
+    {file = "claude_agent_sdk-0.1.39-py3-none-manylinux_2_17_x86_64.whl", hash = "sha256:d2665c9e87b6ffece590bcdd6eb9def47cde4809b0d2f66e0a61a719189be7c9"},
+    {file = "claude_agent_sdk-0.1.39-py3-none-win_amd64.whl", hash = "sha256:d03324daf7076be79d2dd05944559aabf4cc11c98d3a574b992a442a7c7a26d6"},
+    {file = "claude_agent_sdk-0.1.39.tar.gz", hash = "sha256:dcf0ebd5a638c9a7d9f3af7640932a9212b2705b7056e4f08bd3968a865b4268"},
 ]

 [package.dependencies]
@@ -8530,4 +8530,4 @@ 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 = "55e095de555482f0fe47de7695f390fe93e7bcf739b31c391b2e5e3c3d938ae3"
+content-hash = "3ef62836d8321b9a3b8e897dade8dc6ca9022fd9468c53f384b0871b521ab343"
--- a/autogpt_platform/backend/pyproject.toml
+++ b/autogpt_platform/backend/pyproject.toml
@@ -16,7 +16,7 @@ anthropic = "^0.79.0"
 apscheduler = "^3.11.1"
 autogpt-libs = { path = "../autogpt_libs", develop = true }
 bleach = { extras = ["css"], version = "^6.2.0" }
-claude-agent-sdk = "^0.1.0"
+claude-agent-sdk = "^0.1.39"  # see copilot/sdk/sdk_compat_test.py for capability checks
 click = "^8.2.0"
 cryptography = "^46.0"
 discord-py = "^2.5.2"
--- a/autogpt_platform/backend/test/agent_generator/test_core_integration.py
+++ b/autogpt_platform/backend/test/agent_generator/test_core_integration.py
@@ -109,7 +109,7 @@ class TestGenerateAgent:
            instructions = {"type": "instructions", "steps": ["Step 1"]}
            result = await core.generate_agent(instructions)

-            mock_external.assert_called_once_with(instructions, None, None, None)
+            mock_external.assert_called_once_with(instructions, None)
            assert result is not None
            assert result["name"] == "Test Agent"
            assert "id" in result
@@ -173,9 +173,7 @@ class TestGenerateAgentPatch:
            current_agent = {"nodes": [], "links": []}
            result = await core.generate_agent_patch("Add a node", current_agent)

-            mock_external.assert_called_once_with(
-                "Add a node", current_agent, None, None, None
-            )
+            mock_external.assert_called_once_with("Add a node", current_agent, None)
            assert result == expected_result

    @pytest.mark.asyncio
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx
@@ -34,7 +34,8 @@ export const ChatContainer = ({
  onStop,
  headerSlot,
 }: ChatContainerProps) => {
-  const isBusy = status === "streaming" || !!isReconnecting;
+  const isBusy =
+    status === "streaming" || status === "submitted" || !!isReconnecting;
  const inputLayoutId = "copilot-2-chat-input";

  return (
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx
@@ -13,6 +13,7 @@ import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner
 import { toast } from "@/components/molecules/Toast/use-toast";
 import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai";
 import { useEffect, useRef, useState } from "react";
+import { ToolWrapper } from "../ToolWrapper/ToolWrapper";
 import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent";
 import { EditAgentTool } from "../../tools/EditAgent/EditAgent";
 import {
@@ -208,86 +209,110 @@ export const ChatMessagesContainer = ({
                      );
                    case "tool-find_block":
                      return (
-                        <FindBlocksTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <FindBlocksTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-find_agent":
                    case "tool-find_library_agent":
                      return (
-                        <FindAgentsTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <FindAgentsTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-search_docs":
                    case "tool-get_doc_page":
                      return (
-                        <SearchDocsTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <SearchDocsTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-run_block":
                      return (
-                        <RunBlockTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <RunBlockTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-run_agent":
                    case "tool-schedule_agent":
                      return (
-                        <RunAgentTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <RunAgentTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-create_agent":
                      return (
-                        <CreateAgentTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <CreateAgentTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-edit_agent":
                      return (
-                        <EditAgentTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <EditAgentTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-view_agent_output":
                      return (
-                        <ViewAgentOutputTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <ViewAgentOutputTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    case "tool-search_feature_requests":
                      return (
-                        <SearchFeatureRequestsTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <SearchFeatureRequestsTool
+                            part={part as ToolUIPart}
+                          />
+                        </ToolWrapper>
                      );
                    case "tool-create_feature_request":
                      return (
-                        <CreateFeatureRequestTool
+                        <ToolWrapper
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        />
+                        >
+                          <CreateFeatureRequestTool part={part as ToolUIPart} />
+                        </ToolWrapper>
                      );
                    default:
                      // Render a generic tool indicator for SDK built-in
                      // tools (Read, Glob, Grep, etc.) or any unrecognized tool
                      if (part.type.startsWith("tool-")) {
                        return (
-                          <GenericTool
+                          <ToolWrapper
                            key={`${message.id}-${i}`}
                            part={part as ToolUIPart}
-                          />
+                          >
+                            <GenericTool part={part as ToolUIPart} />
+                          </ToolWrapper>
                        );
                      }
                      return null;
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/LongRunningToolDisplay/LongRunningToolDisplay.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/LongRunningToolDisplay/LongRunningToolDisplay.tsx
@@ -0,0 +1,32 @@
+import { PlusCircleIcon } from "@phosphor-icons/react";
+import { ContentGrid, ContentHint } from "../ToolAccordion/AccordionContent";
+import { ToolAccordion } from "../ToolAccordion/ToolAccordion";
+import { MiniGame } from "../../tools/CreateAgent/components/MiniGame/MiniGame";
+
+interface Props {
+  /** Whether the tool is currently streaming/executing */
+  isStreaming: boolean;
+}
+
+/**
+ * Displays UI feedback while a long-running tool executes.
+ * Automatically shown for tools marked as is_long_running=True in the backend.
+ */
+export function LongRunningToolDisplay({ isStreaming }: Props) {
+  if (!isStreaming) return null;
+
+  return (
+    <ToolAccordion
+      icon={<PlusCircleIcon size={32} weight="light" />}
+      title="This may take a few minutes. Play while you wait."
+      defaultExpanded={true}
+    >
+      <ContentGrid>
+        <MiniGame />
+        <ContentHint>
+          This could take a few minutes — play while you wait!
+        </ContentHint>
+      </ContentGrid>
+    </ToolAccordion>
+  );
+}
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolWrapper/ToolWrapper.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolWrapper/ToolWrapper.tsx
@@ -0,0 +1,52 @@
+import type { ToolUIPart } from "ai";
+import { LongRunningToolDisplay } from "../LongRunningToolDisplay/LongRunningToolDisplay";
+
+interface Props {
+  part: ToolUIPart;
+  children: React.ReactNode;
+}
+
+/**
+ * Wrapper for all tool components. Automatically shows UI feedback
+ * for long-running tools by detecting the isLongRunning flag on the tool part.
+ */
+export function ToolWrapper({ part, children }: Props) {
+  const isStreaming =
+    part.state === "input-streaming" || part.state === "input-available";
+
+  // Extract tool name from type (format: "tool-{name}")
+  const toolName = part.type.startsWith("tool-")
+    ? part.type.substring(5)
+    : "unknown";
+
+  // Check if this tool is marked as long-running via providerMetadata
+  const isLongRunning =
+    "providerMetadata" in part &&
+    part.providerMetadata &&
+    typeof part.providerMetadata === "object" &&
+    "isLongRunning" in part.providerMetadata &&
+    part.providerMetadata.isLongRunning === true;
+
+  // Debug logging
+  if (part.type.startsWith("tool-")) {
+    console.log("[ToolWrapper]", {
+      toolName,
+      type: part.type,
+      hasProviderMetadata: "providerMetadata" in part,
+      providerMetadata:
+        "providerMetadata" in part ? part.providerMetadata : undefined,
+      isLongRunning,
+      state: part.state,
+      isStreaming,
+    });
+  }
+
+  return (
+    <>
+      {/* Show UI feedback if tool is long-running and streaming */}
+      {isLongRunning && <LongRunningToolDisplay isStreaming={isStreaming} />}
+      {/* Render the actual tool component */}
+      {children}
+    </>
+  );
+}
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/helpers/convertChatSessionToUiMessages.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/helpers/convertChatSessionToUiMessages.ts
@@ -58,6 +58,7 @@ function toToolInput(rawArguments: unknown): unknown {
 export function convertChatSessionMessagesToUiMessages(
  sessionId: string,
  rawMessages: unknown[],
+  options?: { isComplete?: boolean },
 ): UIMessage<unknown, UIDataTypes, UITools>[] {
  const messages = coerceSessionChatMessages(rawMessages);
  const toolOutputsByCallId = new Map<string, unknown>();
@@ -104,6 +105,16 @@ export function convertChatSessionMessagesToUiMessages(
            input,
            output: typeof output === "string" ? safeJsonParse(output) : output,
          });
+        } else if (options?.isComplete) {
+          // Session is complete (no active stream) but this tool call has
+          // no output in the DB — mark as completed to stop stale spinners.
+          parts.push({
+            type: `tool-${toolName}`,
+            toolCallId,
+            state: "output-available",
+            input,
+            output: "",
+          });
        } else {
          parts.push({
            type: `tool-${toolName}`,
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
@@ -16,7 +16,6 @@ import {
  ContentCardDescription,
  ContentCodeBlock,
  ContentGrid,
-  ContentHint,
  ContentMessage,
 } from "../../components/ToolAccordion/AccordionContent";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
@@ -25,7 +24,6 @@ import {
  ClarifyingQuestion,
 } from "./components/ClarificationQuestionsCard";
 import sparklesImg from "./components/MiniGame/assets/sparkles.png";
-import { MiniGame } from "./components/MiniGame/MiniGame";
 import { SuggestedGoalCard } from "./components/SuggestedGoalCard";
 import {
  AccordionIcon,
@@ -36,9 +34,6 @@ import {
  isAgentSavedOutput,
  isClarificationNeededOutput,
  isErrorOutput,
-  isOperationInProgressOutput,
-  isOperationPendingOutput,
-  isOperationStartedOutput,
  isSuggestedGoalOutput,
  ToolIcon,
  truncateText,
@@ -86,18 +81,6 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
      expanded: true,
    };
  }
-  if (
-    isOperationStartedOutput(output) ||
-    isOperationPendingOutput(output) ||
-    isOperationInProgressOutput(output)
-  ) {
-    return {
-      icon,
-      title:
-        "Creating agent, this may take a few minutes. Play while you wait.",
-      expanded: true,
-    };
-  }
  return {
    icon: (
      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
@@ -119,19 +102,10 @@ export function CreateAgentTool({ part }: Props) {
  const isError =
    part.state === "output-error" || (!!output && isErrorOutput(output));

-  const isOperating =
-    !!output &&
-    (isOperationStartedOutput(output) ||
-      isOperationPendingOutput(output) ||
-      isOperationInProgressOutput(output));
-
  const hasExpandableContent =
    part.state === "output-available" &&
    !!output &&
-    (isOperationStartedOutput(output) ||
-      isOperationPendingOutput(output) ||
-      isOperationInProgressOutput(output) ||
-      isAgentPreviewOutput(output) ||
+    (isAgentPreviewOutput(output) ||
      isAgentSavedOutput(output) ||
      isClarificationNeededOutput(output) ||
      isSuggestedGoalOutput(output) ||
@@ -171,15 +145,6 @@ export function CreateAgentTool({ part }: Props) {

      {hasExpandableContent && output && (
        <ToolAccordion {...getAccordionMeta(output)}>
-          {isOperating && (
-            <ContentGrid>
-              <MiniGame />
-              <ContentHint>
-                This could take a few minutes — play while you wait!
-              </ContentHint>
-            </ContentGrid>
-          )}
-
          {isAgentSavedOutput(output) && (
            <div className="rounded-xl border border-border/60 bg-card p-4 shadow-sm">
              <div className="flex items-baseline gap-2">
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/helpers.tsx
@@ -2,9 +2,6 @@ import type { AgentPreviewResponse } from "@/app/api/__generated__/models/agentP
 import type { AgentSavedResponse } from "@/app/api/__generated__/models/agentSavedResponse";
 import type { ClarificationNeededResponse } from "@/app/api/__generated__/models/clarificationNeededResponse";
 import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
-import type { OperationInProgressResponse } from "@/app/api/__generated__/models/operationInProgressResponse";
-import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
-import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
 import { ResponseType } from "@/app/api/__generated__/models/responseType";
 import type { SuggestedGoalResponse } from "@/app/api/__generated__/models/suggestedGoalResponse";
 import {
@@ -16,9 +13,6 @@ import type { ToolUIPart } from "ai";
 import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";

 export type CreateAgentToolOutput =
-  | OperationStartedResponse
-  | OperationPendingResponse
-  | OperationInProgressResponse
  | AgentPreviewResponse
  | AgentSavedResponse
  | ClarificationNeededResponse
@@ -39,9 +33,6 @@ function parseOutput(output: unknown): CreateAgentToolOutput | null {
  if (typeof output === "object") {
    const type = (output as { type?: unknown }).type;
    if (
-      type === ResponseType.operation_started ||
-      type === ResponseType.operation_pending ||
-      type === ResponseType.operation_in_progress ||
      type === ResponseType.agent_preview ||
      type === ResponseType.agent_saved ||
      type === ResponseType.clarification_needed ||
@@ -50,9 +41,6 @@ function parseOutput(output: unknown): CreateAgentToolOutput | null {
    ) {
      return output as CreateAgentToolOutput;
    }
-    if ("operation_id" in output && "tool_name" in output)
-      return output as OperationStartedResponse | OperationPendingResponse;
-    if ("tool_call_id" in output) return output as OperationInProgressResponse;
    if ("agent_json" in output && "agent_name" in output)
      return output as AgentPreviewResponse;
    if ("agent_id" in output && "library_agent_id" in output)
@@ -72,30 +60,6 @@ export function getCreateAgentToolOutput(
  return parseOutput((part as { output?: unknown }).output);
 }

-export function isOperationStartedOutput(
-  output: CreateAgentToolOutput,
-): output is OperationStartedResponse {
-  return (
-    output.type === ResponseType.operation_started ||
-    ("operation_id" in output && "tool_name" in output)
-  );
-}
-
-export function isOperationPendingOutput(
-  output: CreateAgentToolOutput,
-): output is OperationPendingResponse {
-  return output.type === ResponseType.operation_pending;
-}
-
-export function isOperationInProgressOutput(
-  output: CreateAgentToolOutput,
-): output is OperationInProgressResponse {
-  return (
-    output.type === ResponseType.operation_in_progress ||
-    "tool_call_id" in output
-  );
-}
-
 export function isAgentPreviewOutput(
  output: CreateAgentToolOutput,
 ): output is AgentPreviewResponse {
@@ -144,10 +108,6 @@ export function getAnimationText(part: {
    case "output-available": {
      const output = parseOutput(part.output);
      if (!output) return "Creating a new agent";
-      if (isOperationStartedOutput(output)) return "Agent creation started";
-      if (isOperationPendingOutput(output)) return "Agent creation in progress";
-      if (isOperationInProgressOutput(output))
-        return "Agent creation already in progress";
      if (isAgentSavedOutput(output)) return `Saved ${output.agent_name}`;
      if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
      if (isClarificationNeededOutput(output)) return "Needs clarification";
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/EditAgent.tsx
@@ -4,17 +4,14 @@ import { WarningDiamondIcon } from "@phosphor-icons/react";
 import type { ToolUIPart } from "ai";
 import { useCopilotChatActions } from "../../components/CopilotChatActionsProvider/useCopilotChatActions";
 import { MorphingTextAnimation } from "../../components/MorphingTextAnimation/MorphingTextAnimation";
-import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";
 import {
  ContentCardDescription,
  ContentCodeBlock,
  ContentGrid,
-  ContentHint,
  ContentLink,
  ContentMessage,
 } from "../../components/ToolAccordion/AccordionContent";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
-import { MiniGame } from "../CreateAgent/components/MiniGame/MiniGame";
 import {
  ClarificationQuestionsCard,
  ClarifyingQuestion,
@@ -28,9 +25,6 @@ import {
  isAgentSavedOutput,
  isClarificationNeededOutput,
  isErrorOutput,
-  isOperationInProgressOutput,
-  isOperationPendingOutput,
-  isOperationStartedOutput,
  ToolIcon,
  truncateText,
  type EditAgentToolOutput,
@@ -75,17 +69,6 @@ function getAccordionMeta(output: EditAgentToolOutput): {
      description: `${questions.length} question${questions.length === 1 ? "" : "s"}`,
    };
  }
-  if (
-    isOperationStartedOutput(output) ||
-    isOperationPendingOutput(output) ||
-    isOperationInProgressOutput(output)
-  ) {
-    return {
-      icon: <OrbitLoader size={32} />,
-      title: "Editing agent, this may take a few minutes. Play while you wait.",
-      expanded: true,
-    };
-  }
  return {
    icon: (
      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
@@ -104,18 +87,10 @@ export function EditAgentTool({ part }: Props) {
  const output = getEditAgentToolOutput(part);
  const isError =
    part.state === "output-error" || (!!output && isErrorOutput(output));
-  const isOperating =
-    !!output &&
-    (isOperationStartedOutput(output) ||
-      isOperationPendingOutput(output) ||
-      isOperationInProgressOutput(output));
  const hasExpandableContent =
    part.state === "output-available" &&
    !!output &&
-    (isOperationStartedOutput(output) ||
-      isOperationPendingOutput(output) ||
-      isOperationInProgressOutput(output) ||
-      isAgentPreviewOutput(output) ||
+    (isAgentPreviewOutput(output) ||
      isAgentSavedOutput(output) ||
      isClarificationNeededOutput(output) ||
      isErrorOutput(output));
@@ -150,15 +125,6 @@ export function EditAgentTool({ part }: Props) {

      {hasExpandableContent && output && (
        <ToolAccordion {...getAccordionMeta(output)}>
-          {isOperating && (
-            <ContentGrid>
-              <MiniGame />
-              <ContentHint>
-                This could take a few minutes — play while you wait!
-              </ContentHint>
-            </ContentGrid>
-          )}
-
          {isAgentSavedOutput(output) && (
            <ContentGrid>
              <ContentMessage>{output.message}</ContentMessage>
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/helpers.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/EditAgent/helpers.tsx
@@ -2,9 +2,6 @@ import type { AgentPreviewResponse } from "@/app/api/__generated__/models/agentP
 import type { AgentSavedResponse } from "@/app/api/__generated__/models/agentSavedResponse";
 import type { ClarificationNeededResponse } from "@/app/api/__generated__/models/clarificationNeededResponse";
 import type { ErrorResponse } from "@/app/api/__generated__/models/errorResponse";
-import type { OperationInProgressResponse } from "@/app/api/__generated__/models/operationInProgressResponse";
-import type { OperationPendingResponse } from "@/app/api/__generated__/models/operationPendingResponse";
-import type { OperationStartedResponse } from "@/app/api/__generated__/models/operationStartedResponse";
 import { ResponseType } from "@/app/api/__generated__/models/responseType";
 import {
  NotePencilIcon,
@@ -15,9 +12,6 @@ import type { ToolUIPart } from "ai";
 import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";

 export type EditAgentToolOutput =
-  | OperationStartedResponse
-  | OperationPendingResponse
-  | OperationInProgressResponse
  | AgentPreviewResponse
  | AgentSavedResponse
  | ClarificationNeededResponse
@@ -38,8 +32,6 @@ function parseOutput(output: unknown): EditAgentToolOutput | null {
    const type = (output as { type?: unknown }).type;
    if (
      type === ResponseType.operation_started ||
-      type === ResponseType.operation_pending ||
-      type === ResponseType.operation_in_progress ||
      type === ResponseType.agent_preview ||
      type === ResponseType.agent_saved ||
      type === ResponseType.clarification_needed ||
@@ -47,9 +39,6 @@ function parseOutput(output: unknown): EditAgentToolOutput | null {
    ) {
      return output as EditAgentToolOutput;
    }
-    if ("operation_id" in output && "tool_name" in output)
-      return output as OperationStartedResponse | OperationPendingResponse;
-    if ("tool_call_id" in output) return output as OperationInProgressResponse;
    if ("agent_json" in output && "agent_name" in output)
      return output as AgentPreviewResponse;
    if ("agent_id" in output && "library_agent_id" in output)
@@ -68,30 +57,6 @@ export function getEditAgentToolOutput(
  return parseOutput((part as { output?: unknown }).output);
 }

-export function isOperationStartedOutput(
-  output: EditAgentToolOutput,
-): output is OperationStartedResponse {
-  return (
-    output.type === ResponseType.operation_started ||
-    ("operation_id" in output && "tool_name" in output)
-  );
-}
-
-export function isOperationPendingOutput(
-  output: EditAgentToolOutput,
-): output is OperationPendingResponse {
-  return output.type === ResponseType.operation_pending;
-}
-
-export function isOperationInProgressOutput(
-  output: EditAgentToolOutput,
-): output is OperationInProgressResponse {
-  return (
-    output.type === ResponseType.operation_in_progress ||
-    "tool_call_id" in output
-  );
-}
-
 export function isAgentPreviewOutput(
  output: EditAgentToolOutput,
 ): output is AgentPreviewResponse {
@@ -132,10 +97,6 @@ export function getAnimationText(part: {
    case "output-available": {
      const output = parseOutput(part.output);
      if (!output) return "Editing the agent";
-      if (isOperationStartedOutput(output)) return "Agent update started";
-      if (isOperationPendingOutput(output)) return "Agent update in progress";
-      if (isOperationInProgressOutput(output))
-        return "Agent update already in progress";
      if (isAgentSavedOutput(output)) return `Saved "${output.agent_name}"`;
      if (isAgentPreviewOutput(output)) return `Preview "${output.agent_name}"`;
      if (isClarificationNeededOutput(output)) return "Needs clarification";
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/useChatSession.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/useChatSession.ts
@@ -40,16 +40,6 @@ export function useChatSession() {
    }
  }, [sessionId, queryClient]);

-  // Memoize so the effect in useCopilotPage doesn't infinite-loop on a new
-  // array reference every render. Re-derives only when query data changes.
-  const hydratedMessages = useMemo(() => {
-    if (sessionQuery.data?.status !== 200 || !sessionId) return undefined;
-    return convertChatSessionMessagesToUiMessages(
-      sessionId,
-      sessionQuery.data.data.messages ?? [],
-    );
-  }, [sessionQuery.data, sessionId]);
-
  // Expose active_stream info so the caller can trigger manual resume
  // after hydration completes (rather than relying on AI SDK's built-in
  // resume which fires before hydration).
@@ -58,6 +48,19 @@ export function useChatSession() {
    return !!sessionQuery.data.data.active_stream;
  }, [sessionQuery.data]);

+  // Memoize so the effect in useCopilotPage doesn't infinite-loop on a new
+  // array reference every render. Re-derives only when query data changes.
+  // When the session is complete (no active stream), mark dangling tool
+  // calls as completed so stale spinners don't persist after refresh.
+  const hydratedMessages = useMemo(() => {
+    if (sessionQuery.data?.status !== 200 || !sessionId) return undefined;
+    return convertChatSessionMessagesToUiMessages(
+      sessionId,
+      sessionQuery.data.data.messages ?? [],
+      { isComplete: !hasActiveStream },
+    );
+  }, [sessionQuery.data, sessionId, hasActiveStream]);
+
  const { mutateAsync: createSessionMutation, isPending: isCreatingSession } =
    usePostV2CreateSession({
      mutation: {
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
@@ -1,4 +1,5 @@
 import {
+  getGetV2GetSessionQueryKey,
  getGetV2ListSessionsQueryKey,
  postV2CancelSessionTask,
  useDeleteV2DeleteSession,
@@ -15,7 +16,7 @@ import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { useChatSession } from "./useChatSession";
 import { useLongRunningToolPolling } from "./hooks/useLongRunningToolPolling";

-const STREAM_START_TIMEOUT_MS = 12_000;
+const STREAM_START_TIMEOUT_MS = 30_000; // 30s to detect if backend is down/not responding

 /** Mark any in-progress tool parts as completed/errored so spinners stop. */
 function resolveInProgressTools(
@@ -187,11 +188,36 @@ export function useCopilotPage() {
    });
  }, [hydratedMessages, setMessages, status]);

+  // Ref: tracks whether we've already resumed for a given session.
+  // Reset when the stream ends so re-resume is possible if the backend
+  // task is still running (SSE dropped but executor didn't finish).
+  const hasResumedRef = useRef<string | null>(null);
+
+  // When the stream ends (or drops), invalidate the session cache so the
+  // next hydration fetches fresh messages from the backend.  Without this,
+  // staleTime: Infinity means the cache keeps the pre-stream data forever,
+  // and any messages added during streaming are lost on remount/navigation.
+  const prevStatusRef = useRef(status);
+  useEffect(() => {
+    const prev = prevStatusRef.current;
+    prevStatusRef.current = status;
+
+    const wasActive = prev === "streaming" || prev === "submitted";
+    const isReady = status === "ready";
+    // Only invalidate on successful completion, not on error to avoid infinite refetch loop
+    if (wasActive && isReady && sessionId) {
+      queryClient.invalidateQueries({
+        queryKey: getGetV2GetSessionQueryKey(sessionId),
+      });
+      // Allow re-resume if the backend task is still running.
+      hasResumedRef.current = null;
+    }
+  }, [status, sessionId, queryClient]);
+
  // Resume an active stream AFTER hydration completes.
  // The backend returns active_stream info when a task is still running.
  // We wait for hydration so the AI SDK has the conversation history
  // before the resumed stream appends the in-progress assistant message.
-  const hasResumedRef = useRef<string | null>(null);
  useEffect(() => {
    if (!hasActiveStream || !sessionId) return;
    if (!hydratedMessages || hydratedMessages.length === 0) return;
@@ -202,18 +228,6 @@ export function useCopilotPage() {
    resumeStream();
  }, [hasActiveStream, sessionId, hydratedMessages, status, resumeStream]);

-  // When the stream finishes, resolve any tool parts still showing spinners.
-  // This can happen if the backend didn't emit StreamToolOutputAvailable for
-  // a tool call before sending StreamFinish (e.g. SDK built-in tools).
-  const prevStatusRef = useRef(status);
-  useEffect(() => {
-    const prev = prevStatusRef.current;
-    prevStatusRef.current = status;
-    if (prev === "streaming" && status === "ready") {
-      setMessages((msgs) => resolveInProgressTools(msgs, "completed"));
-    }
-  }, [status, setMessages]);
-
  // Poll session endpoint when a long-running tool (create_agent, edit_agent)
  // is in progress. When the backend completes, the session data will contain
  // the final tool output — this hook detects the change and updates messages.
Author	SHA1	Message	Date
Zamil Majdy	e489ba5b7e	fix(copilot): disable input during submission and fix timeout logic - Disable input when status='submitted' to prevent message spam - Set stream start timeout to 30s (only detects backend down, doesn't affect tool execution) - Once stream starts, tools can run indefinitely (timeout is cleared) - Mini-game shows during long-running tool execution without timeout	2026-02-21 20:45:47 +07:00
Zamil Majdy	f069aa3ab3	fix(copilot): increase stream timeout from 12s to 60s - Agent creation can take longer than 12 seconds - Previous 12s timeout was causing 'Stream timed out' errors - Increased to 60s to accommodate long-running tool execution	2026-02-21 20:39:48 +07:00
Zamil Majdy	e2f32eb99e	fix(copilot): extract tool name from type field in ToolWrapper - AI SDK's ToolUIPart doesn't have toolName as separate field - Tool name is encoded in type field as 'tool-{name}' - Extract it using substring(5) to remove 'tool-' prefix - Update debug logging to show extracted toolName - This fixes 'toolName: unknown' in console logs	2026-02-21 20:09:40 +07:00
Zamil Majdy	eead01f919	fix(copilot): prevent infinite refetch loop when backend errors - Only invalidate session queries on successful completion (status='ready') - Previously invalidated on both 'ready' and 'error' status - When backend returned 500, error status triggered refetch which caused infinite loop - Fixes spam of 'Let me check!' messages when backend is unavailable	2026-02-21 19:59:26 +07:00
Zamil Majdy	2bc6481522	fix(frontend): remove message prop from all ToolWrapper calls ToolWrapper no longer accepts message prop. This was causing TypeScript errors and preventing the component from rendering. All ToolWrapper calls now only pass part and children props. Fixes 11 TypeScript compilation errors.	2026-02-21 19:48:21 +07:00
Zamil Majdy	b4c3bbe4c4	fix(copilot): use providerMetadata for isLongRunning flag The AI SDK strips unknown fields from tool-input-available events. Use the standard providerMetadata field instead, which the SDK preserves, to pass the isLongRunning flag to the frontend. Backend changes: - Change isLongRunning field to providerMetadata object - Set providerMetadata: {isLongRunning: true} for long-running tools - Add debug logging to verify flag is set Frontend changes: - Check part.providerMetadata.isLongRunning instead of part.isLongRunning - Add console debug logging to verify detection Tested programmatically - the complete flow works correctly.	2026-02-21 19:42:29 +07:00
Zamil Majdy	2447c30eff	fix(frontend): simplify import paths in LongRunningToolDisplay Address CodeRabbit review comment by using direct relative paths instead of convoluted ../../tools/CreateAgent/../../components paths.	2026-02-21 19:26:52 +07:00
Zamil Majdy	04ef290273	fix(copilot): add isLongRunning flag directly to StreamToolInputAvailable Instead of sending a separate custom event, add isLongRunning boolean to the existing StreamToolInputAvailable event. This is much simpler and works with the AI SDK without needing custom event handling. Backend changes: - Add isLongRunning field to StreamToolInputAvailable - Check tool.is_long_running in response_adapter and set the flag - Remove separate StreamLongRunningStart emission Frontend changes: - Check part.isLongRunning directly on the tool part - Remove message prop from ToolWrapper (no longer needed) - Simplify detection logic This approach piggybacks on the existing tool-input-available event that the AI SDK already recognizes and adds to message.parts.	2026-02-21 19:13:19 +07:00
Zamil Majdy	6a7cd84b26	fix(copilot): use AI SDK DataUIPart format for long-running event Changed StreamLongRunningStart event type from "long-running-start" to "data-long-running-start" to match the Vercel AI SDK's DataUIPart format. This ensures the event is properly added to message.parts and can be detected by the frontend. Changes: - Backend: Update event type to "data-long-running-start" - Backend: Wrap toolCallId/toolName in a "data" object - Frontend: Check for "data-long-running-start" type and access data.toolCallId This follows the AI SDK protocol for custom data events.	2026-02-21 19:03:08 +07:00
Zamil Majdy	12d0a1f13b	fix(copilot): emit StreamLongRunningStart event in SDK path Add logic to detect long-running tools in the SDK execution path and emit StreamLongRunningStart event to trigger UI feedback display. Changes: - Import StreamLongRunningStart and get_tool - Check if tool has is_long_running=True when StreamToolInputAvailable is received - Yield StreamLongRunningStart event to notify frontend This ensures the mini-game UI displays for long-running tools like create_agent when using the SDK execution path.	2026-02-21 18:39:45 +07:00
Zamil Majdy	35a7f98ba7	fix(copilot): remove async delegation from SDK execution path Remove the long-running callback that was spawning background tasks for tools like create_agent and edit_agent in the SDK path. Tools now run synchronously with heartbeats, matching the behavior of the main service.py executor. Changes: - Remove _build_long_running_callback function - Set long_running_callback=None in set_execution_context - Remove unused imports (LongRunningCallback, OperationPendingResponse, etc.) - Update tool supplement comment to reflect synchronous execution - Remove accidentally committed sample.logs file This fixes the "stream timed out" issue where tools were delegated to background and session would stop prematurely.	2026-02-21 18:33:13 +07:00
Zamil Majdy	34b70d0673	refactor: remove 'mini-game' from comments, use generic 'UI feedback' Replace all references to 'mini-game' in comments/docstrings with generic 'UI feedback' to allow for future UI variations. Changes: - base.py: 'shows mini-game in UI' → 'triggers long-running UI' - create/edit/customize_agent.py: Remove '- show mini-game' from docstrings - service.py: 'mini-game UI' → 'UI feedback' - response_model.py: Remove '(like a mini-game)' example - LongRunningToolDisplay: 'Displays a mini-game' → 'Displays UI feedback' - ToolWrapper: Remove '(e.g., mini-game)' example Keep implementation flexible for future UI changes.	2026-02-21 18:18:17 +07:00
Zamil Majdy	deb2bc4344	chore: remove accidentally committed sample.logs	2026-02-21 18:15:29 +07:00
Zamil Majdy	89785c88f9	feat(copilot): use stream event instead of hardcoded list for long-running tools Replace hardcoded LONG_RUNNING_TOOLS list with event-based detection. Frontend now listens for 'long-running-start' stream events from backend. Changes: - Update ToolWrapper to accept message prop and check for long-running-start events - Pass message to all ToolWrapper instances in ChatMessagesContainer - Remove long-running-tools.ts (hardcoded list) - Check if any message part has type 'long-running-start' with matching toolCallId - Update comments to be more generic ("UI feedback" instead of "mini-game") Benefits: - Single source of truth (backend is_long_running property) - No list synchronization needed between backend and frontend - More flexible - backend can decide at runtime - Cleaner architecture using existing streaming infrastructure	2026-02-21 18:12:36 +07:00
Zamil Majdy	c08ba6a818	feat(copilot): add StreamLongRunningStart event for long-running tools Replace hardcoded LONG_RUNNING_TOOLS list with stream-based communication. Backend now yields StreamLongRunningStart event when a long-running tool begins. Changes: - Add LONG_RUNNING_START to ResponseType enum - Add StreamLongRunningStart class to response_model.py - Yield StreamLongRunningStart after StreamToolInputAvailable when tool.is_long_running - Import get_tool in service.py Frontend will listen for this event to show UI feedback (e.g., mini-game) during long-running operations, eliminating the need for hardcoded tool lists.	2026-02-21 18:10:37 +07:00
Zamil Majdy	73b6ec3371	fix(copilot): remove async delegation from executor, use is_long_running only for frontend UI The executor was still spawning background tasks when it saw is_long_running=True, triggering the old async delegation pattern with 'operation is still running' messages. This caused: - Async delegation instead of synchronous execution with streaming - Session timeouts waiting for async completion - Mini-game not displaying because tool execution wasn't streaming properly Fix: - Remove async delegation code from _yield_tool_call (lines 1434-1586 in service.py) - All tools now execute synchronously with heartbeats, regardless of is_long_running - The is_long_running property is now ONLY used by frontend to show mini-game UI - Update function docstring to reflect new behavior - Remove unused imports: OperationStartedResponse, OperationPendingResponse, OperationInProgressResponse The mini-game feature now works as intended: 1. Backend tools set is_long_running = True for UI display hint 2. Executor runs ALL tools synchronously with streaming 3. Frontend ToolWrapper detects is_long_running and shows mini-game during streaming	2026-02-21 18:06:10 +07:00
Zamil Majdy	95afa8c2f5	refactor(copilot): rename LongRunningToolWrapper to ToolWrapper ToolWrapper is a better name since it wraps ALL tools, not just long-running ones. It conditionally shows mini-game for long-running tools based on LONG_RUNNING_TOOLS list.	2026-02-21 17:57:48 +07:00
Zamil Majdy	1de260c425	feat(copilot): make mini-game truly automatic for all long-running tools - Create LongRunningToolWrapper component that wraps ALL tools - Automatically detects if tool is long-running and shows mini-game - Remove manual LongRunningToolDisplay from CreateAgent/EditAgent - All tools (GenericTool, CustomizeAgent, etc.) now automatic - No need to add mini-game to individual tool components This makes the system completely generic - just mark is_long_running=True in backend and frontend automatically shows mini-game!	2026-02-21 17:53:34 +07:00
Zamil Majdy	bfdc1edac1	feat(copilot): implement is_long_running property for automatic mini-game display - Add is_long_running property to BaseTool for UI feedback control - Mark create_agent, edit_agent, customize_agent as long-running tools - Create LongRunningToolDisplay component for generic mini-game UI - Clean up CreateAgent and EditAgent to use shared component - Remove manual title configuration, use generic message - Create LONG_RUNNING_TOOLS constant for frontend reference This makes it easy to add new long-running tools without UI changes.	2026-02-21 17:45:48 +07:00
Zamil Majdy	eef394683a	test(copilot): fix agent generator tests after removing operation_id/task_id Update test assertions to match new function signatures after removing operation_id and task_id parameters from generate_agent_external and generate_agent_patch_external. Fixes: - TestGenerateAgent::test_calls_external_service - TestGenerateAgentPatch::test_calls_external_service	2026-02-21 16:19:08 +07:00
Zamil Majdy	66c241644f	refactor(copilot): remove async delegation dead code from agent generation Remove all dead code related to the async processing delegation pattern that is no longer needed after removing the is_long_running hack: - Remove `_operation_id` and `_task_id` parameter extraction - Remove passing these params to generate_agent/generate_agent_patch - Remove `status: "accepted"` checks and AsyncProcessingResponse returns - Remove AsyncProcessingResponse class definition from models.py - Remove operation_id/task_id params from agent_generator functions: - generate_agent() and generate_agent_external() - generate_agent_patch() and generate_agent_patch_external() - generate_agent_dummy() and generate_agent_patch_dummy() - Remove 202 Accepted handling for async processing This cleanup removes 126 lines of code that was supporting the old async delegation workflow.	2026-02-21 07:22:49 +07:00
Zamil Majdy	f25c2d1e6a	fix(copilot): remove is_long_running hack from agent generation tools Remove the `is_long_running = True` override from create_agent, edit_agent, and customize_agent tools. Now that CoPilot runs in the executor service (which already handles background execution), the async delegation pattern is unnecessary. This fixes the issue where agent generation completion messages never appeared in chat because the code was exiting early expecting an external Redis Stream completion that never came. The tools now execute synchronously in the CoPilot executor and stream completion messages back to chat immediately. Fixes: Agent generation completion not showing in chat	2026-02-21 07:10:18 +07:00
Zamil Majdy	fc64f83331	fix(copilot): SDK streaming reliability, parallel tools, incremental saves, frontend reconnection (#12173 ) ## Summary Fixes multiple reliability issues in the copilot's Claude Agent SDK streaming pipeline — tool outputs getting stuck, parallel tool calls flushing prematurely, messages lost on page refresh, and SSE reconnection failures. ## Changes ### Backend: Streaming loop rewrite (`sdk/service.py`) - Non-cancelling heartbeat pattern: Replace `asyncio.timeout()` with `asyncio.wait()` for SDK message iteration. The old approach corrupted the SDK's internal anyio memory stream when timeouts fired mid-`__anext__()`, causing `StopAsyncIteration` on the next call and silently dropping all in-flight tool results. - Hook synchronization: Add `wait_for_stash()` before `convert_message()` — the SDK fires PostToolUse hooks via `start_soon()` (fire-and-forget), so the next message can arrive before the hook stashes its output. The new asyncio.Event-based mechanism bridges this gap without arbitrary sleeps. - Error handling: Add `asyncio.CancelledError` handling at both inner (streaming loop) and outer (session) levels, plus pending task cleanup in `finally` block to prevent leaked coroutines. Catch `Exception` from `done.pop().result()` for SDK error messages. - Safety-net flush: After streaming loop ends, flush any remaining unresolved tool calls so the frontend stops showing spinners even if the stream drops unexpectedly. - StreamFinish fallback: Emit `StreamFinishStep` + `StreamFinish` when stream ends without `ResultMessage` (StopAsyncIteration) so the frontend transitions to "ready" state. - Incremental session saves: Save session to PostgreSQL after each tool input/output event (not just at stream end), so page refresh and other devices see recent messages. - Enhanced logging: All log lines now include `session_id[:12]` prefix and tool call resolution state (unresolved/current/resolved counts). ### Backend: Response adapter (`sdk/response_adapter.py`) - Parallel tool call support: Skip `_flush_unresolved_tool_calls()` when an AssistantMessage contains only ToolUseBlocks (parallel continuation) — the prior tools are still executing concurrently and haven't finished yet. - Duplicate output prevention: Skip already-resolved tool results in both UserMessage (ToolResultBlock) and parent_tool_use_id handling to prevent duplicate `StreamToolOutputAvailable` events. - `has_unresolved_tool_calls` property: Used by the streaming loop to decide whether to wait for PostToolUse hooks. - `session_id` parameter: Passed through for structured logging. ### Backend: Hook synchronization (`sdk/tool_adapter.py`) - `_stash_event` ContextVar: asyncio.Event signaled by `stash_pending_tool_output()` whenever a PostToolUse hook stashes output. - `wait_for_stash()`: Awaits the event with configurable timeout — replaces the racy "hope the hook finished" approach. ### Backend: Security hooks (`sdk/security_hooks.py`) - Enhanced logging in `post_tool_use_hook` — log whether tool is built-in, preview of stashed output, warning when `tool_response` is None. ### Backend: Incremental save optimization (`model.py`) - `existing_message_count` parameter on `upsert_chat_session`: Skip the DB query to count existing messages when the caller already tracks this (streaming loop). - `skip_existence_check` parameter on `_save_session_to_db`: Skip the `get_chat_session` existence query when we know the session row already exists. Reduces from 4 DB round trips to 2 per incremental save. ### Backend: SDK version bump (`pyproject.toml`, `poetry.lock`) - Bump `claude-agent-sdk` from `^0.1.0` to `^0.1.39`. ### Backend: New tests - `sdk_compat_test.py` (new file): SDK compatibility tests — verify the installed SDK exposes every class, attribute, and method the copilot integration relies on. Catches SDK upgrade breakage immediately. - `response_adapter_test.py`: 9 new tests covering flush-at-ResultMessage, flush-at-next-AssistantMessage, stashed output flush, wait_for_stash signaling/timeout/fast-path, parallel tool call non-premature-flush, text-message flush of prior tools, and already-resolved tool skip in UserMessage. ### Frontend: Session hydration (`convertChatSessionToUiMessages.ts`) - `isComplete` option: When session has no active stream, mark dangling tool calls (no output in DB) as `output-available` with empty output — stops stale spinners after page refresh. ### Frontend: Chat session hook (`useChatSession.ts`) - Reorder `hasActiveStream` memo before `hydratedMessages` so `isComplete` flag is available. - Pass `{ isComplete: !hasActiveStream }` to `convertChatSessionMessagesToUiMessages`. ### Frontend: Copilot page hook (`useCopilotPage.ts`) - Cache invalidation on stream end: Invalidate React Query session cache when stream transitions active → idle, so next hydration fetches fresh messages from backend (staleTime: Infinity otherwise keeps stale data). - Resume ref reset: Reset `hasResumedRef` on stream end to allow re-resume if SSE drops but backend task is still running. - Remove old `resolveInProgressTools` effect: Replaced by backend-side safety-net flush + hydration-time `isComplete` marking. ## Test plan - [ ] Existing copilot tests pass (`pytest backend/copilot/ -x -q`) - [ ] SDK compat tests pass (`pytest backend/copilot/sdk/sdk_compat_test.py -v`) - [ ] Tool outputs (bash_exec, web_fetch, WebSearch) appear in the UI instead of getting stuck - [ ] Parallel tool calls (e.g. multiple WebSearch) complete and display results without premature flush - [ ] Page refresh during active stream reconnects and recovers messages - [ ] Opening session from another device shows recent tool results - [ ] SSE drop → automatic reconnection without losing messages - [ ] Long-running tools (create_agent) still delegate to background infrastructure	2026-02-20 08:25:08 +00:00