Merge branch 'dev' into chore/remove-deprecated-openai-models

docs: add Podman compatibility warning (#12120 )
## Summary Adds a warning to the Getting Started docs clarifying that **Podman and podman-compose are not supported**. ## Problem Users on Windows using `podman-compose` instead of Docker get errors like: ``` Error: the specified Containerfile or Dockerfile does not exist, ..\..\autogpt_platform\backend\Dockerfile ``` This is because Podman handles relative paths differently than Docker, causing incorrect path resolution on Windows. ## Solution - Added a clear warning section after the Windows WSL 2 notes - Explains the error users might see - Directs them to install Docker Desktop instead Closes #11358  <details><summary><h3>Greptile Summary</h3></summary> Adds a "Podman Not Supported" warning section to the Getting Started documentation, placed after the Windows/WSL 2 installation notes. The section clarifies that Docker is required, shows the typical error message users encounter when using Podman, and directs them to install Docker Desktop instead. This addresses issue #11358 where Windows users using `podman-compose` hit path resolution errors. - Adds `### ⚠️ Podman Not Supported` section under Manual Setup, after Windows Installation Note - Includes the specific error message users see with Podman for easy identification - Links to Docker Desktop installation docs as the recommended solution - Formatting is consistent with existing sections in the document (emoji headings, code blocks for errors) </details> <details><summary><h3>Confidence Score: 5/5</h3></summary> - This PR is safe to merge — it only adds a documentation warning section with no code changes. - The change is a small, well-written documentation addition that adds a Podman compatibility warning. It touches only one markdown file, introduces no code changes, and is consistent with the existing document structure and style. No issues were found. - No files require special attention. </details> <details><summary><h3>Flowchart</h3></summary> ```mermaid flowchart TD A[User wants to run AutoGPT] --> B{Which container runtime?} B -->|Docker / Docker Desktop| C[docker compose up -d --build] C --> D[AutoGPT starts successfully] B -->|Podman / podman-compose| E[podman-compose up -d --build] E --> F[Error: Containerfile or Dockerfile does not exist] F --> G[New warning section directs user to install Docker Desktop] G --> C ``` </details> <sub>Last reviewed commit: 23ea6bd</sub>
2026-02-24 03:00:28 -05:00 · 2026-02-23 16:43:08 +00:00 · 2026-02-23 15:19:24 +00:00 · 2026-02-23 16:39:21 +07:00 · 2026-02-20 15:05:03 +00:00 · 2026-02-20 09:16:22 +00:00
48 changed files with 1468 additions and 1168 deletions
--- a/autogpt_platform/backend/.application.logs
+++ b/autogpt_platform/backend/.application.logs
@@ -1,572 +0,0 @@
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-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
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-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()
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-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... 
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-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")
-/Users/majdyz/Code/AutoGPT/autogpt_platform/backend/.venv/lib/python3.13/site-packages/pyiceberg/table/metadata.py:506: 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:538: 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:542: 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:546: 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:550: 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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-2026-02-21 20:37:25,612 [34mINFO[0m  127.0.0.1:58568 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:29,708 [34mINFO[0m  127.0.0.1:58671 - "GET /api/store/profile HTTP/1.1" 404
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-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
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-2026-02-21 20:37:35,657 [33mWARNING[0m  [33mService communication: Retry attempt 1 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:37:36,713 [33mWARNING[0m  [33mService communication: Retry attempt 2 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:37:39,646 [33mWARNING[0m  [33mService communication: Retry attempt 3 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:37:43,415 [34mINFO[0m  127.0.0.1:58782 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:44,423 [33mWARNING[0m  [33mService communication: Retry attempt 4 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:37:44,486 [34mINFO[0m  127.0.0.1:58782 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:45,048 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=12, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user']
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-2026-02-21 20:37:45,120 [34mINFO[0m  [TASK_LOOKUP] Found running task bba63941... for session 322af5c3...
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-2026-02-21 20:37:45,616 [34mINFO[0m  [TIMING] Replayed 1 messages, last_id=1771681065606-0
-2026-02-21 20:37:45,616 [34mINFO[0m  [TIMING] Task still running, starting _stream_listener
-2026-02-21 20:37:45,616 [34mINFO[0m  [TIMING] subscribe_to_task COMPLETED in 11308.9ms; task=bba63941-8048-4f39-9329-8568e5ebe9cd, n_messages_replayed=1
-2026-02-21 20:37:45,616 [34mINFO[0m  [TIMING] Starting to read from subscriber_queue
-2026-02-21 20:37:45,616 [34mINFO[0m  [TIMING] FIRST CHUNK from queue at 11.31s, type=StreamFinish
-2026-02-21 20:37:45,616 [34mINFO[0m  127.0.0.1:58710 - "POST /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f/stream HTTP/1.1" 200
-2026-02-21 20:37:45,617 [34mINFO[0m  [TIMING] StreamFinish received in 11.31s; n_chunks=1
-2026-02-21 20:37:45,617 [34mINFO[0m  [TIMING] _stream_listener CANCELLED after 3.5ms, delivered=0
-2026-02-21 20:37:45,617 [34mINFO[0m  [TIMING] _stream_listener FINISHED in 0.0s; task=bba63941-8048-4f39-9329-8568e5ebe9cd, delivered=0, xread_count=1
-2026-02-21 20:37:45,618 [34mINFO[0m  Resume stream completed
-2026-02-21 20:37:45,618 [34mINFO[0m  [TIMING] event_generator FINISHED in 11.31s; task=bba63941-8048-4f39-9329-8568e5ebe9cd, session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, n_chunks=1
-2026-02-21 20:37:45,691 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=12, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user']
-2026-02-21 20:37:45,694 [34mINFO[0m  [GET_SESSION] session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, active_task=False, msg_count=12, last_role=user
-2026-02-21 20:37:45,695 [34mINFO[0m  127.0.0.1:58710 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f HTTP/1.1" 200
-2026-02-21 20:37:45,710 [34mINFO[0m  127.0.0.1:58802 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f/stream HTTP/1.1" 204
-2026-02-21 20:37:45,771 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=12, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user']
-2026-02-21 20:37:45,775 [34mINFO[0m  [GET_SESSION] session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, active_task=False, msg_count=12, last_role=user
-2026-02-21 20:37:45,775 [34mINFO[0m  127.0.0.1:58710 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f HTTP/1.1" 200
-2026-02-21 20:37:46,075 [34mINFO[0m  [CANCEL] Task ...e5ebe9cd confirmed stopped (status=failed) after 1.0s
-2026-02-21 20:37:46,076 [34mINFO[0m  127.0.0.1:58782 - "POST /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f/cancel HTTP/1.1" 200
-2026-02-21 20:37:46,573 [34mINFO[0m  127.0.0.1:58710 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:50,090 [34mINFO[0m  127.0.0.1:58710 - "GET /api/integrations/providers/system HTTP/1.1" 200
-2026-02-21 20:37:50,103 [34mINFO[0m  127.0.0.1:58842 - "GET /api/integrations/providers HTTP/1.1" 200
-2026-02-21 20:37:50,681 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=12, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user']
-2026-02-21 20:37:50,686 [34mINFO[0m  127.0.0.1:58710 - "GET /api/library/agents?page=1&page_size=100 HTTP/1.1" 200
-2026-02-21 20:37:50,692 [34mINFO[0m  127.0.0.1:58850 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:50,702 [34mINFO[0m  127.0.0.1:58842 - "GET /api/integrations/credentials HTTP/1.1" 200
-2026-02-21 20:37:50,710 [34mINFO[0m  [GET_SESSION] session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, active_task=False, msg_count=12, last_role=user
-2026-02-21 20:37:50,711 [34mINFO[0m  127.0.0.1:58862 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f HTTP/1.1" 200
-2026-02-21 20:37:50,714 [34mINFO[0m  127.0.0.1:58852 - "GET /api/onboarding HTTP/1.1" 200
-2026-02-21 20:37:50,720 [34mINFO[0m  127.0.0.1:58854 - "GET /api/executions HTTP/1.1" 200
-2026-02-21 20:37:50,795 [34mINFO[0m  127.0.0.1:58710 - "GET /api/chat/sessions?limit=50 HTTP/1.1" 200
-2026-02-21 20:37:51,955 [34mINFO[0m  127.0.0.1:58710 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:54,064 [34mINFO[0m  127.0.0.1:58710 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:54,157 [34mINFO[0m  [TIMING] stream_chat_post STARTED, session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, user=68383665-d3d9-41f3-b10c-fca0dc6080ed, message_len=5
-2026-02-21 20:37:54,169 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=12, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user']
-2026-02-21 20:37:54,170 [34mINFO[0m  [TIMING] session validated in 13.0ms
-2026-02-21 20:37:54,170 [34mINFO[0m  [STREAM] Saving user message to session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f
-2026-02-21 20:37:54,172 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=12, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user']
-2026-02-21 20:37:54,212 [34mINFO[0m  Saving 1 new messages to DB for session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f: roles=['user'], start_sequence=12
-2026-02-21 20:37:54,238 [34mINFO[0m  [STREAM] User message saved for session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f
-2026-02-21 20:37:54,238 [34mINFO[0m  [TIMING] create_task STARTED, task=6360d249-c803-47d3-8a08-d77275e4b2d8, session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, user=68383665-d3d9-41f3-b10c-fca0dc6080ed
-2026-02-21 20:37:54,238 [34mINFO[0m  [TIMING] get_redis_async took 0.0ms
-2026-02-21 20:37:54,242 [34mINFO[0m  [TIMING] redis.hset took 3.1ms
-2026-02-21 20:37:54,250 [34mINFO[0m  [TIMING] create_task COMPLETED in 11.6ms; task=6360d249-c803-47d3-8a08-d77275e4b2d8, session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f
-2026-02-21 20:37:54,251 [34mINFO[0m  [TIMING] create_task completed in 12.9ms
-2026-02-21 20:37:54,261 [34mINFO[0m  [TIMING] Task enqueued to RabbitMQ, setup=103.8ms
-2026-02-21 20:37:54,262 [34mINFO[0m  [TIMING] event_generator STARTED, task=6360d249-c803-47d3-8a08-d77275e4b2d8, session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, user=68383665-d3d9-41f3-b10c-fca0dc6080ed
-2026-02-21 20:37:54,263 [34mINFO[0m  [TIMING] subscribe_to_task STARTED, task=6360d249-c803-47d3-8a08-d77275e4b2d8, user=68383665-d3d9-41f3-b10c-fca0dc6080ed, last_msg=0-0
-2026-02-21 20:37:54,264 [34mINFO[0m  [TIMING] Redis hgetall took 1.7ms
-2026-02-21 20:37:54,265 [34mINFO[0m  [CoPilotExecutor] Acquired cluster lock for 6360d249-c803-47d3-8a08-d77275e4b2d8, executor_id=fb7d76b3-8dc3-40a4-947e-a93bfad207da 
-2026-02-21 20:37:54,267 [34mINFO[0m  [CoPilotExecutor|task_id:6360d249-c803-47d3-8a08-d77275e4b2d8|session_id:322af5c3-70fc-4a06-9443-8c5df0aa0c9f|user_id:68383665-d3d9-41f3-b10c-fca0dc6080ed] Starting execution 
-2026-02-21 20:37:54,286 [34mINFO[0m  [CoPilotExecutor|task_id:6360d249-c803-47d3-8a08-d77275e4b2d8|session_id:322af5c3-70fc-4a06-9443-8c5df0aa0c9f|user_id:68383665-d3d9-41f3-b10c-fca0dc6080ed] Using SDK service 
-2026-02-21 20:37:54,290 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=13, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user', 'user']
-2026-02-21 20:37:54,357 [33mWARNING[0m  [33mService communication: Retry attempt 1 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:37:56,312 [33mWARNING[0m  [33mService communication: Retry attempt 2 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:37:58,224 [34mINFO[0m  127.0.0.1:58917 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:37:58,928 [33mWARNING[0m  [33mService communication: Retry attempt 3 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:38:00,041 [33mWARNING[0m  [33mService communication: Retry attempt 8 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 20:38:03,701 [33mWARNING[0m  [33mService communication: Retry attempt 4 for '_call_method_async': HTTPServerError: HTTP 500: Server error '500 Internal Server Error' for url 'http://localhost:8005/get_chat_session_message_count'
-For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/500[0m
-2026-02-21 20:38:06,882 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=13, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user', 'user']
-2026-02-21 20:38:06,888 [34mINFO[0m  [TASK_LOOKUP] Found running task 6360d249... for session 322af5c3...
-2026-02-21 20:38:06,898 [34mINFO[0m  [CoPilotExecutor] Received cancel for 6360d249-c803-47d3-8a08-d77275e4b2d8 
-2026-02-21 20:38:06,898 [34mINFO[0m  [CANCEL] Published cancel for task ...75e4b2d8 session ...f0aa0c9f
-2026-02-21 20:38:06,919 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=13, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user', 'user']
-2026-02-21 20:38:06,925 [34mINFO[0m  [TASK_LOOKUP] Found running task 6360d249... for session 322af5c3...
-2026-02-21 20:38:06,926 [34mINFO[0m  [GET_SESSION] session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, active_task=True, msg_count=13, last_role=user
-2026-02-21 20:38:06,927 [34mINFO[0m  127.0.0.1:58976 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f HTTP/1.1" 200
-2026-02-21 20:38:07,136 [34mINFO[0m  [TASK_LOOKUP] Found running task 6360d249... for session 322af5c3...
-2026-02-21 20:38:07,138 [34mINFO[0m  [TIMING] subscribe_to_task STARTED, task=6360d249-c803-47d3-8a08-d77275e4b2d8, user=68383665-d3d9-41f3-b10c-fca0dc6080ed, last_msg=0-0
-2026-02-21 20:38:07,140 [34mINFO[0m  [TIMING] Redis hgetall took 1.3ms
-2026-02-21 20:38:07,359 [34mINFO[0m  [CoPilotExecutor|task_id:6360d249-c803-47d3-8a08-d77275e4b2d8|session_id:322af5c3-70fc-4a06-9443-8c5df0aa0c9f|user_id:68383665-d3d9-41f3-b10c-fca0dc6080ed] Cancellation requested 
-2026-02-21 20:38:07,360 [34mINFO[0m  [CoPilotExecutor|task_id:6360d249-c803-47d3-8a08-d77275e4b2d8|session_id:322af5c3-70fc-4a06-9443-8c5df0aa0c9f|user_id:68383665-d3d9-41f3-b10c-fca0dc6080ed] Execution completed in 13.09s 
-2026-02-21 20:38:07,360 [34mINFO[0m  [CoPilotExecutor] Run completed for 6360d249-c803-47d3-8a08-d77275e4b2d8 
-2026-02-21 20:38:07,360 [34mINFO[0m  [CoPilotExecutor|task_id:6360d249-c803-47d3-8a08-d77275e4b2d8|session_id:322af5c3-70fc-4a06-9443-8c5df0aa0c9f|user_id:68383665-d3d9-41f3-b10c-fca0dc6080ed] Task cancelled 
-2026-02-21 20:38:07,360 [34mINFO[0m  [CoPilotExecutor] Releasing cluster lock for 6360d249-c803-47d3-8a08-d77275e4b2d8 
-2026-02-21 20:38:07,362 [34mINFO[0m  [CoPilotExecutor] Cleaned up completed task 6360d249-c803-47d3-8a08-d77275e4b2d8 
-2026-02-21 20:38:07,364 [34mINFO[0m  [TIMING] Redis xread (replay) took 224.1ms, status=running
-2026-02-21 20:38:07,364 [34mINFO[0m  [TIMING] Replayed 1 messages, last_id=1771681087362-0
-2026-02-21 20:38:07,365 [34mINFO[0m  [TIMING] Task still running, starting _stream_listener
-2026-02-21 20:38:07,365 [34mINFO[0m  [TIMING] publish_chunk StreamFinish in 2.1ms (xadd=1.2ms)
-2026-02-21 20:38:07,365 [34mINFO[0m  [TIMING] subscribe_to_task COMPLETED in 226.8ms; task=6360d249-c803-47d3-8a08-d77275e4b2d8, n_messages_replayed=1
-2026-02-21 20:38:07,366 [34mINFO[0m  [TIMING] _stream_listener STARTED, task=6360d249-c803-47d3-8a08-d77275e4b2d8, last_id=1771681087362-0
-2026-02-21 20:38:07,366 [34mINFO[0m  Resume stream chunk
-2026-02-21 20:38:07,366 [34mINFO[0m  127.0.0.1:58976 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f/stream HTTP/1.1" 200
-2026-02-21 20:38:07,367 [34mINFO[0m  [TIMING] Redis xread (replay) took 13101.9ms, status=running
-2026-02-21 20:38:07,367 [34mINFO[0m  [TIMING] Replayed 1 messages, last_id=1771681087362-0
-2026-02-21 20:38:07,367 [34mINFO[0m  [TIMING] Task still running, starting _stream_listener
-2026-02-21 20:38:07,367 [34mINFO[0m  [TIMING] subscribe_to_task COMPLETED in 13104.6ms; task=6360d249-c803-47d3-8a08-d77275e4b2d8, n_messages_replayed=1
-2026-02-21 20:38:07,367 [34mINFO[0m  [TIMING] Starting to read from subscriber_queue
-2026-02-21 20:38:07,368 [34mINFO[0m  [TIMING] FIRST CHUNK from queue at 13.11s, type=StreamFinish
-2026-02-21 20:38:07,368 [34mINFO[0m  127.0.0.1:58710 - "POST /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f/stream HTTP/1.1" 200
-2026-02-21 20:38:07,368 [34mINFO[0m  [TIMING] StreamFinish received in 13.11s; n_chunks=1
-2026-02-21 20:38:07,368 [34mINFO[0m  [TIMING] _stream_listener CANCELLED after 2.7ms, delivered=0
-2026-02-21 20:38:07,368 [34mINFO[0m  [TIMING] _stream_listener FINISHED in 0.0s; task=6360d249-c803-47d3-8a08-d77275e4b2d8, delivered=0, xread_count=1
-2026-02-21 20:38:07,369 [34mINFO[0m  Resume stream completed
-2026-02-21 20:38:07,369 [34mINFO[0m  [TIMING] event_generator FINISHED in 13.11s; task=6360d249-c803-47d3-8a08-d77275e4b2d8, session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, n_chunks=1
-2026-02-21 20:38:07,408 [34mINFO[0m  [CANCEL] Task ...75e4b2d8 confirmed stopped (status=failed) after 0.5s
-2026-02-21 20:38:07,409 [34mINFO[0m  127.0.0.1:58974 - "POST /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f/cancel HTTP/1.1" 200
-2026-02-21 20:38:07,447 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=13, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user', 'user']
-2026-02-21 20:38:07,451 [34mINFO[0m  [GET_SESSION] session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, active_task=False, msg_count=13, last_role=user
-2026-02-21 20:38:07,451 [34mINFO[0m  127.0.0.1:58710 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f HTTP/1.1" 200
-2026-02-21 20:38:07,468 [34mINFO[0m  127.0.0.1:58710 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f/stream HTTP/1.1" 204
-2026-02-21 20:38:07,521 [34mINFO[0m  Loading session 322af5c3-70fc-4a06-9443-8c5df0aa0c9f from cache: message_count=13, roles=['user', 'assistant', 'tool', 'assistant', 'tool', 'assistant', 'tool', 'tool', 'assistant', 'tool', 'tool', 'user', 'user']
-2026-02-21 20:38:07,527 [34mINFO[0m  [GET_SESSION] session=322af5c3-70fc-4a06-9443-8c5df0aa0c9f, active_task=False, msg_count=13, last_role=user
-2026-02-21 20:38:07,528 [34mINFO[0m  127.0.0.1:58710 - "GET /api/chat/sessions/322af5c3-70fc-4a06-9443-8c5df0aa0c9f HTTP/1.1" 200
-2026-02-21 20:38:18,440 [34mINFO[0m  127.0.0.1:59077 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:38:19,553 [34mINFO[0m  127.0.0.1:59077 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:38:21,643 [34mINFO[0m  127.0.0.1:59077 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:38:30,090 [33mWARNING[0m  [33mService communication: Retry attempt 9 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 20:39:00,123 [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
-2026-02-21 20:39:13,881 [34mINFO[0m  127.0.0.1:59398 - "GET /api/chat/sessions?limit=50 HTTP/1.1" 200
-2026-02-21 20:39:30,173 [33mWARNING[0m  [33mService communication: Retry attempt 11 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 20:39:35,355 [34mINFO[0m  127.0.0.1:59522 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:39:35,685 [34mINFO[0m  127.0.0.1:59526 - "GET /api/executions HTTP/1.1" 200
-2026-02-21 20:39:38,916 [34mINFO[0m  127.0.0.1:59522 - "GET /api/store/profile HTTP/1.1" 404
-2026-02-21 20:39:40,019 [34mINFO[0m  127.0.0.1:59522 - "GET /api/store/profile HTTP/1.1" 404
--- a/autogpt_platform/backend/.gitignore
+++ b/autogpt_platform/backend/.gitignore
@@ -22,4 +22,3 @@ migrations/*/rollback*.sql

 # Workspace files
 workspaces/
-sample.logs
--- a/autogpt_platform/backend/backend/blocks/llm.py
+++ b/autogpt_platform/backend/backend/blocks/llm.py
@@ -106,8 +106,6 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
    GPT41_MINI = "gpt-4.1-mini-2025-04-14"
    GPT4O_MINI = "gpt-4o-mini"
    GPT4O = "gpt-4o"
-    GPT4_TURBO = "gpt-4-turbo"
-    GPT3_5_TURBO = "gpt-3.5-turbo"
    # Anthropic models
    CLAUDE_4_1_OPUS = "claude-opus-4-1-20250805"
    CLAUDE_4_OPUS = "claude-opus-4-20250514"
@@ -255,12 +253,6 @@ MODEL_METADATA = {
    LlmModel.GPT4O: ModelMetadata(
        "openai", 128000, 16384, "GPT-4o", "OpenAI", "OpenAI", 2
    ),  # gpt-4o-2024-08-06
-    LlmModel.GPT4_TURBO: ModelMetadata(
-        "openai", 128000, 4096, "GPT-4 Turbo", "OpenAI", "OpenAI", 3
-    ),  # gpt-4-turbo-2024-04-09
-    LlmModel.GPT3_5_TURBO: ModelMetadata(
-        "openai", 16385, 4096, "GPT-3.5 Turbo", "OpenAI", "OpenAI", 1
-    ),  # gpt-3.5-turbo-0125
    # https://docs.anthropic.com/en/docs/about-claude/models
    LlmModel.CLAUDE_4_1_OPUS: ModelMetadata(
        "anthropic", 200000, 32000, "Claude Opus 4.1", "Anthropic", "Anthropic", 3
--- a/autogpt_platform/backend/backend/copilot/config.py
+++ b/autogpt_platform/backend/backend/copilot/config.py
@@ -27,7 +27,6 @@ class ChatConfig(BaseSettings):
    session_ttl: int = Field(default=43200, description="Session TTL in seconds")

    # Streaming Configuration
-    stream_timeout: int = Field(default=300, description="Stream timeout in seconds")
    max_retries: int = Field(
        default=3,
        description="Max retries for fallback path (SDK handles retries internally)",
@@ -39,8 +38,10 @@ class ChatConfig(BaseSettings):

    # Long-running operation configuration
    long_running_operation_ttl: int = Field(
-        default=600,
-        description="TTL in seconds for long-running operation tracking in Redis (safety net if pod dies)",
+        default=3600,
+        description="TTL in seconds for long-running operation deduplication lock "
+        "(1 hour, matches stream_ttl). Prevents duplicate operations if pod dies. "
+        "For longer operations, the stream_registry heartbeat keeps them alive.",
    )

    # Stream registry configuration for SSE reconnection
@@ -48,6 +49,11 @@ class ChatConfig(BaseSettings):
        default=3600,
        description="TTL in seconds for stream data in Redis (1 hour)",
    )
+    stream_lock_ttl: int = Field(
+        default=120,
+        description="TTL in seconds for stream lock (2 minutes). Short timeout allows "
+        "reconnection after refresh/crash without long waits.",
+    )
    stream_max_length: int = Field(
        default=10000,
        description="Maximum number of messages to store per stream",
--- a/autogpt_platform/backend/backend/copilot/db.py
+++ b/autogpt_platform/backend/backend/copilot/db.py
@@ -3,8 +3,9 @@
 import asyncio
 import logging
 from datetime import UTC, datetime
-from typing import Any, cast
+from typing import Any

+from prisma.errors import UniqueViolationError
 from prisma.models import ChatMessage as PrismaChatMessage
 from prisma.models import ChatSession as PrismaChatSession
 from prisma.types import (
@@ -92,10 +93,9 @@ async def add_chat_message(
    function_call: dict[str, Any] | None = None,
 ) -> ChatMessage:
    """Add a message to a chat session."""
-    # Build input dict dynamically rather than using ChatMessageCreateInput directly
-    # because Prisma's TypedDict validation rejects optional fields set to None.
-    # We only include fields that have values, then cast at the end.
-    data: dict[str, Any] = {
+    # Build ChatMessageCreateInput with only non-None values
+    # (Prisma TypedDict rejects optional fields set to None)
+    data: ChatMessageCreateInput = {
        "Session": {"connect": {"id": session_id}},
        "role": role,
        "sequence": sequence,
@@ -123,7 +123,7 @@ async def add_chat_message(
            where={"id": session_id},
            data={"updatedAt": datetime.now(UTC)},
        ),
-        PrismaChatMessage.prisma().create(data=cast(ChatMessageCreateInput, data)),
+        PrismaChatMessage.prisma().create(data=data),
    )
    return ChatMessage.from_db(message)

@@ -132,58 +132,93 @@ async def add_chat_messages_batch(
    session_id: str,
    messages: list[dict[str, Any]],
    start_sequence: int,
-) -> list[ChatMessage]:
+) -> int:
    """Add multiple messages to a chat session in a batch.

-    Uses a transaction for atomicity - if any message creation fails,
-    the entire batch is rolled back.
+    Uses collision detection with retry: tries to create messages starting
+    at start_sequence. If a unique constraint violation occurs (e.g., the
+    streaming loop and long-running callback race), queries the latest
+    sequence and retries with the correct offset. This avoids unnecessary
+    upserts and DB queries in the common case (no collision).
+
+    Returns:
+        Next sequence number for the next message to be inserted. This equals
+        start_sequence + len(messages) and allows callers to update their
+        counters even when collision detection adjusts start_sequence.
    """
    if not messages:
-        return []
+        # No messages to add - return current count
+        return start_sequence

-    created_messages = []
+    max_retries = 5
+    for attempt in range(max_retries):
+        try:
+            # Single timestamp for all messages and session update
+            now = datetime.now(UTC)

-    async with db.transaction() as tx:
-        for i, msg in enumerate(messages):
-            # Build input dict dynamically rather than using ChatMessageCreateInput
-            # directly because Prisma's TypedDict validation rejects optional fields
-            # set to None. We only include fields that have values, then cast.
-            data: dict[str, Any] = {
-                "Session": {"connect": {"id": session_id}},
-                "role": msg["role"],
-                "sequence": start_sequence + i,
-            }
+            async with db.transaction() as tx:
+                # Build all message data
+                messages_data = []
+                for i, msg in enumerate(messages):
+                    # Build ChatMessageCreateInput with only non-None values
+                    # (Prisma TypedDict rejects optional fields set to None)
+                    # Note: create_many doesn't support nested creates, use sessionId directly
+                    data: ChatMessageCreateInput = {
+                        "sessionId": session_id,
+                        "role": msg["role"],
+                        "sequence": start_sequence + i,
+                        "createdAt": now,
+                    }

-            # Add optional string fields
-            if msg.get("content") is not None:
-                data["content"] = msg["content"]
-            if msg.get("name") is not None:
-                data["name"] = msg["name"]
-            if msg.get("tool_call_id") is not None:
-                data["toolCallId"] = msg["tool_call_id"]
-            if msg.get("refusal") is not None:
-                data["refusal"] = msg["refusal"]
+                    # Add optional string fields
+                    if msg.get("content") is not None:
+                        data["content"] = msg["content"]
+                    if msg.get("name") is not None:
+                        data["name"] = msg["name"]
+                    if msg.get("tool_call_id") is not None:
+                        data["toolCallId"] = msg["tool_call_id"]
+                    if msg.get("refusal") is not None:
+                        data["refusal"] = msg["refusal"]

-            # Add optional JSON fields only when they have values
-            if msg.get("tool_calls") is not None:
-                data["toolCalls"] = SafeJson(msg["tool_calls"])
-            if msg.get("function_call") is not None:
-                data["functionCall"] = SafeJson(msg["function_call"])
+                    # Add optional JSON fields only when they have values
+                    if msg.get("tool_calls") is not None:
+                        data["toolCalls"] = SafeJson(msg["tool_calls"])
+                    if msg.get("function_call") is not None:
+                        data["functionCall"] = SafeJson(msg["function_call"])

-            created = await PrismaChatMessage.prisma(tx).create(
-                data=cast(ChatMessageCreateInput, data)
-            )
-            created_messages.append(created)
+                    messages_data.append(data)

-        # Update session's updatedAt timestamp within the same transaction.
-        # Note: Token usage (total_prompt_tokens, total_completion_tokens) is updated
-        # separately via update_chat_session() after streaming completes.
-        await PrismaChatSession.prisma(tx).update(
-            where={"id": session_id},
-            data={"updatedAt": datetime.now(UTC)},
-        )
+                # Run create_many and session update in parallel within transaction
+                # Both use the same timestamp for consistency
+                await asyncio.gather(
+                    PrismaChatMessage.prisma(tx).create_many(data=messages_data),
+                    PrismaChatSession.prisma(tx).update(
+                        where={"id": session_id},
+                        data={"updatedAt": now},
+                    ),
+                )

-    return [ChatMessage.from_db(m) for m in created_messages]
+            # Return next sequence number for counter sync
+            return start_sequence + len(messages)
+
+        except UniqueViolationError:
+            if attempt < max_retries - 1:
+                # Collision detected - query MAX(sequence)+1 and retry with correct offset
+                logger.info(
+                    f"Collision detected for session {session_id} at sequence "
+                    f"{start_sequence}, querying DB for latest sequence"
+                )
+                start_sequence = await get_next_sequence(session_id)
+                logger.info(
+                    f"Retrying batch insert with start_sequence={start_sequence}"
+                )
+                continue
+            else:
+                # Max retries exceeded - propagate error
+                raise
+
+    # Should never reach here due to raise in exception handler
+    raise RuntimeError(f"Failed to insert messages after {max_retries} attempts")


 async def get_user_chat_sessions(
@@ -237,10 +272,20 @@ async def delete_chat_session(session_id: str, user_id: str | None = None) -> bo
        return False


-async def get_chat_session_message_count(session_id: str) -> int:
-    """Get the number of messages in a chat session."""
-    count = await PrismaChatMessage.prisma().count(where={"sessionId": session_id})
-    return count
+async def get_next_sequence(session_id: str) -> int:
+    """Get the next sequence number for a new message in this session.
+
+    Uses MAX(sequence) + 1 for robustness. Returns 0 if no messages exist.
+    More robust than COUNT(*) because it's immune to deleted messages.
+
+    Optimized to select only the sequence column using raw SQL.
+    The unique index on (sessionId, sequence) makes this query fast.
+    """
+    results = await db.query_raw_with_schema(
+        'SELECT "sequence" FROM {schema_prefix}"ChatMessage" WHERE "sessionId" = $1 ORDER BY "sequence" DESC LIMIT 1',
+        session_id,
+    )
+    return 0 if not results else results[0]["sequence"] + 1


 async def update_tool_message_content(
--- a/autogpt_platform/backend/backend/copilot/executor/processor.py
+++ b/autogpt_platform/backend/backend/copilot/executor/processor.py
@@ -266,7 +266,11 @@ class CoPilotProcessor:

        except asyncio.CancelledError:
            log.info("Task cancelled")
-            await stream_registry.mark_task_completed(entry.task_id, status="failed")
+            await stream_registry.mark_task_completed(
+                entry.task_id,
+                status="failed",
+                error_message="Task was cancelled",
+            )
            raise

        except Exception as e:
--- a/autogpt_platform/backend/backend/copilot/model.py
+++ b/autogpt_platform/backend/backend/copilot/model.py
@@ -434,8 +434,6 @@ async def _get_session_from_db(session_id: str) -> ChatSession | None:

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

@@ -443,12 +441,6 @@ async def upsert_chat_session(
    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
@@ -459,11 +451,8 @@ async def upsert_chat_session(
    lock = await _get_session_lock(session.session_id)

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

        db_error: Exception | None = None

@@ -587,9 +576,7 @@ async def append_and_save_message(session_id: str, message: ChatMessage) -> Chat
            raise ValueError(f"Session {session_id} not found")

        session.messages.append(message)
-        existing_message_count = await chat_db().get_chat_session_message_count(
-            session_id
-        )
+        existing_message_count = await chat_db().get_next_sequence(session_id)

        try:
            await _save_session_to_db(session, existing_message_count)
--- a/autogpt_platform/backend/backend/copilot/model_test.py
+++ b/autogpt_platform/backend/backend/copilot/model_test.py
@@ -331,3 +331,96 @@ def test_to_openai_messages_merges_split_assistants():
    tc_list = merged.get("tool_calls")
    assert tc_list is not None and len(list(tc_list)) == 1
    assert list(tc_list)[0]["id"] == "tc1"
+
+
+# --------------------------------------------------------------------------- #
+#  Concurrent save collision detection                                        #
+# --------------------------------------------------------------------------- #
+
+
+@pytest.mark.asyncio(loop_scope="session")
+async def test_concurrent_saves_collision_detection(setup_test_user, test_user_id):
+    """Test that concurrent saves from streaming loop and callback handle collisions correctly.
+
+    Simulates the race condition where:
+    1. Streaming loop starts with saved_msg_count=5
+    2. Long-running callback appends message #5 and saves
+    3. Streaming loop tries to save with stale count=5
+
+    The collision detection should handle this gracefully.
+    """
+    import asyncio
+
+    # Create a session with initial messages
+    session = ChatSession.new(user_id=test_user_id)
+    for i in range(3):
+        session.messages.append(
+            ChatMessage(
+                role="user" if i % 2 == 0 else "assistant", content=f"Message {i}"
+            )
+        )
+
+    # Save initial messages
+    session = await upsert_chat_session(session)
+
+    # Simulate streaming loop and callback saving concurrently
+    async def streaming_loop_save():
+        """Simulates streaming loop saving messages."""
+        # Add 2 messages
+        session.messages.append(ChatMessage(role="user", content="Streaming message 1"))
+        session.messages.append(
+            ChatMessage(role="assistant", content="Streaming message 2")
+        )
+
+        # Wait a bit to let callback potentially save first
+        await asyncio.sleep(0.01)
+
+        # Save (will query DB for existing count)
+        return await upsert_chat_session(session)
+
+    async def callback_save():
+        """Simulates long-running callback saving a message."""
+        # Add 1 message
+        session.messages.append(
+            ChatMessage(role="tool", content="Callback result", tool_call_id="tc1")
+        )
+
+        # Save immediately (will query DB for existing count)
+        return await upsert_chat_session(session)
+
+    # Run both saves concurrently - one will hit collision detection
+    results = await asyncio.gather(streaming_loop_save(), callback_save())
+
+    # Both should succeed
+    assert all(r is not None for r in results)
+
+    # Reload session from DB to verify
+    from backend.data.redis_client import get_redis_async
+
+    redis_key = f"chat:session:{session.session_id}"
+    async_redis = await get_redis_async()
+    await async_redis.delete(redis_key)  # Clear cache to force DB load
+
+    loaded_session = await get_chat_session(session.session_id, test_user_id)
+    assert loaded_session is not None
+
+    # Should have all 6 messages (3 initial + 2 streaming + 1 callback)
+    assert len(loaded_session.messages) == 6
+
+    # Verify no duplicate sequences
+    sequences = []
+    for i, msg in enumerate(loaded_session.messages):
+        # Messages should have sequential sequence numbers starting from 0
+        sequences.append(i)
+
+    # All sequences should be unique and sequential
+    assert sequences == list(range(6))
+
+    # Verify message content is preserved
+    contents = [m.content for m in loaded_session.messages]
+    assert "Message 0" in contents
+    assert "Message 1" in contents
+    assert "Message 2" in contents
+    assert "Streaming message 1" in contents
+    assert "Streaming message 2" in contents
+    assert "Callback result" in contents
--- a/autogpt_platform/backend/backend/copilot/response_model.py
+++ b/autogpt_platform/backend/backend/copilot/response_model.py
@@ -34,9 +34,6 @@ 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"
@@ -148,10 +145,6 @@ 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):
@@ -180,20 +173,6 @@ 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
@@ -34,7 +34,6 @@ 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

@@ -112,15 +111,6 @@ 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)
                    )
@@ -129,15 +119,8 @@ 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):
--- a/autogpt_platform/backend/backend/copilot/sdk/service.py
+++ b/autogpt_platform/backend/backend/copilot/sdk/service.py
@@ -7,10 +7,13 @@ import os
 import uuid
 from collections.abc import AsyncGenerator
 from dataclasses import dataclass
-from typing import Any
+from typing import Any, cast

+from backend.data.redis_client import get_redis_async
+from backend.executor.cluster_lock import AsyncClusterLock
 from backend.util.exceptions import NotFoundError

+from .. import stream_registry
 from ..config import ChatConfig
 from ..model import (
    ChatMessage,
@@ -30,7 +33,12 @@ from ..response_model import (
    StreamToolInputAvailable,
    StreamToolOutputAvailable,
 )
-from ..service import _build_system_prompt, _generate_session_title
+from ..service import (
+    _build_system_prompt,
+    _execute_long_running_tool_with_streaming,
+    _generate_session_title,
+)
+from ..tools.models import OperationPendingResponse, OperationStartedResponse
 from ..tools.sandbox import WORKSPACE_PREFIX, make_session_path
 from ..tracking import track_user_message
 from .response_adapter import SDKResponseAdapter
@@ -38,6 +46,7 @@ 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,
@@ -54,6 +63,7 @@ from .transcript import (
 logger = logging.getLogger(__name__)
 config = ChatConfig()

+
 # Set to hold background tasks to prevent garbage collection
 _background_tasks: set[asyncio.Task[Any]] = set()

@@ -116,15 +126,138 @@ 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.) run synchronously
-with heartbeats to keep the connection alive. The frontend shows UI feedback
-during execution based on stream events.
+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.

 ### Sub-agent tasks
 - When using the Task tool, NEVER set `run_in_background` to true.
  All tasks must run in the foreground.
 """

+STREAM_LOCK_PREFIX = "copilot:stream:lock:"
+
+
+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.
+
+    Args:
+        user_id: User ID for the session
+
+    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)
+        # Collision detection happens in add_chat_messages_batch (db.py)
+        session = 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.
@@ -405,6 +538,9 @@ async def stream_chat_completion_sdk(
            f"Session {session_id} not found. Please create a new session first."
        )

+    # Type narrowing: session is guaranteed ChatSession after the check above
+    session = cast(ChatSession, session)
+
    # Append the new message to the session if it's not already there
    new_message_role = "user" if is_user_message else "assistant"
    if message and (
@@ -442,6 +578,29 @@ async def stream_chat_completion_sdk(
    system_prompt += _SDK_TOOL_SUPPLEMENT
    message_id = str(uuid.uuid4())
    task_id = str(uuid.uuid4())
+    stream_id = task_id  # Use task_id as unique stream identifier
+
+    # Acquire stream lock to prevent concurrent streams to the same session
+    lock = AsyncClusterLock(
+        redis=await get_redis_async(),
+        key=f"{STREAM_LOCK_PREFIX}{session_id}",
+        owner_id=stream_id,
+        timeout=config.stream_lock_ttl,
+    )
+
+    lock_owner = await lock.try_acquire()
+    if lock_owner != stream_id:
+        # Another stream is active
+        logger.warning(
+            f"[SDK] Session {session_id} already has an active stream: {lock_owner}"
+        )
+        yield StreamError(
+            errorText="Another stream is already active for this session. "
+            "Please wait or stop it.",
+            code="stream_already_active",
+        )
+        yield StreamFinish()
+        return

    yield StreamStart(messageId=message_id, taskId=task_id)

@@ -462,7 +621,7 @@ async def stream_chat_completion_sdk(
        set_execution_context(
            user_id,
            session,
-            long_running_callback=None,
+            long_running_callback=_build_long_running_callback(user_id),
        )
        try:
            from claude_agent_sdk import ClaudeAgentOptions, ClaudeSDKClient
@@ -593,9 +752,6 @@ 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 non-cancelling heartbeats.
                # CRITICAL: we must NOT cancel __anext__() mid-flight — doing so
@@ -622,6 +778,8 @@ async def stream_chat_completion_sdk(

                        if not done:
                            # Timeout — emit heartbeat but keep the task alive
+                            # Also refresh lock TTL to keep it alive
+                            await lock.refresh()
                            yield StreamHeartbeat()
                            continue

@@ -771,13 +929,10 @@ async def stream_chat_completion_sdk(
                                    has_appended_assistant = True
                                # Save before tool execution starts so the
                                # pending tool call is visible on refresh /
-                                # other devices.
+                                # other devices. Collision detection happens
+                                # in add_chat_messages_batch (db.py).
                                try:
-                                    await upsert_chat_session(
-                                        session,
-                                        existing_message_count=saved_msg_count,
-                                    )
-                                    saved_msg_count = len(session.messages)
+                                    session = await upsert_chat_session(session)
                                except Exception as save_err:
                                    logger.warning(
                                        "[SDK] [%s] Incremental save " "failed: %s",
@@ -800,12 +955,9 @@ async def stream_chat_completion_sdk(
                                has_tool_results = True
                                # Save after tool completes so the result is
                                # visible on refresh / other devices.
+                                # Collision detection happens in add_chat_messages_batch (db.py).
                                try:
-                                    await upsert_chat_session(
-                                        session,
-                                        existing_message_count=saved_msg_count,
-                                    )
-                                    saved_msg_count = len(session.messages)
+                                    session = await upsert_chat_session(session)
                                except Exception as save_err:
                                    logger.warning(
                                        "[SDK] [%s] Incremental save " "failed: %s",
@@ -937,7 +1089,7 @@ async def stream_chat_completion_sdk(
                "to use the OpenAI-compatible fallback."
            )

-        await asyncio.shield(upsert_chat_session(session))
+        session = cast(ChatSession, await asyncio.shield(upsert_chat_session(session)))
        logger.info(
            "[SDK] [%s] Session saved with %d messages",
            session_id[:12],
@@ -954,10 +1106,11 @@ async def stream_chat_completion_sdk(
        raise
    except Exception as e:
        logger.error(f"[SDK] Error: {e}", exc_info=True)
-        try:
-            await asyncio.shield(upsert_chat_session(session))
-        except Exception as save_err:
-            logger.error(f"[SDK] Failed to save session on error: {save_err}")
+        if session:
+            try:
+                await asyncio.shield(upsert_chat_session(session))
+            except Exception as save_err:
+                logger.error(f"[SDK] Failed to save session on error: {save_err}")
        yield StreamError(
            errorText="An error occurred. Please try again.",
            code="sdk_error",
@@ -979,7 +1132,7 @@ async def stream_chat_completion_sdk(
                if not raw_transcript and use_resume and resume_file:
                    raw_transcript = read_transcript_file(resume_file)

-                if raw_transcript:
+                if raw_transcript and session is not None:
                    await asyncio.shield(
                        _try_upload_transcript(
                            user_id,
@@ -999,6 +1152,9 @@ async def stream_chat_completion_sdk(
        if sdk_cwd:
            _cleanup_sdk_tool_results(sdk_cwd)

+        # Release stream lock to allow new streams for this session
+        await lock.release()
+

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

 logger = logging.getLogger(__name__)
@@ -348,7 +352,8 @@ async def assign_user_to_session(
    if not session:
        raise NotFoundError(f"Session {session_id} not found")
    session.user_id = user_id
-    return await upsert_chat_session(session)
+    session = await upsert_chat_session(session)
+    return session


 async def stream_chat_completion(
@@ -1398,15 +1403,16 @@ async def _yield_tool_call(
    """
    Yield a tool call and its execution result.

-    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.
+    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.

    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"]
@@ -1424,17 +1430,167 @@ async def _yield_tool_call(
        input=arguments,
    )

-    # Notify frontend if this is a long-running tool (e.g., agent generation)
+    # Check if this tool is long-running (survives SSE disconnection)
    tool = get_tool(tool_name)
    if tool and tool.is_long_running:
-        yield StreamLongRunningStart(
-            data={
-                "toolCallId": tool_call_id,
-                "toolName": tool_name,
-            }
-        )
+        # 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..."

-    # Run tool execution synchronously with heartbeats
+            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",
+                    error_message=f"Failed to setup tool {tool_name}: {e}",
+                )
+            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,
+        )
+        return
+
+    # Normal flow: Run tool execution in background task with heartbeats
    tool_task = asyncio.create_task(
        execute_tool(
            tool_name=tool_name,
@@ -1580,7 +1736,11 @@ async def _execute_long_running_tool_with_streaming(
        session = await get_chat_session(session_id, user_id)
        if not session:
            logger.error(f"Session {session_id} not found for background tool")
-            await stream_registry.mark_task_completed(task_id, status="failed")
+            await stream_registry.mark_task_completed(
+                task_id,
+                status="failed",
+                error_message=f"Session {session_id} not found",
+            )
            return

        # Pass operation_id and task_id to the tool for async processing
--- a/autogpt_platform/backend/backend/copilot/stream_registry.py
+++ b/autogpt_platform/backend/backend/copilot/stream_registry.py
@@ -644,6 +644,8 @@ async def _stream_listener(
 async def mark_task_completed(
    task_id: str,
    status: Literal["completed", "failed"] = "completed",
+    *,
+    error_message: str | None = None,
 ) -> bool:
    """Mark a task as completed and publish finish event.

@@ -654,6 +656,10 @@ async def mark_task_completed(
    Args:
        task_id: Task ID to mark as completed
        status: Final status ("completed" or "failed")
+        error_message: If provided and status="failed", publish a StreamError
+            before StreamFinish so connected clients see why the task ended.
+            If not provided, no StreamError is published (caller should publish
+            manually if needed to avoid duplicates).

    Returns:
        True if task was newly marked completed, False if already completed/failed
@@ -669,6 +675,17 @@ async def mark_task_completed(
        logger.debug(f"Task {task_id} already completed/failed, skipping")
        return False

+    # Publish error event before finish so connected clients know WHY the
+    # task ended. Only publish if caller provided an explicit error message
+    # to avoid duplicates with code paths that manually publish StreamError.
+    # This is best-effort — if it fails, the StreamFinish still ensures
+    # listeners clean up.
+    if status == "failed" and error_message:
+        try:
+            await publish_chunk(task_id, StreamError(errorText=error_message))
+        except Exception as e:
+            logger.warning(f"Failed to publish error event for task {task_id}: {e}")
+
    # THEN publish finish event (best-effort - listeners can detect via status polling)
    try:
        await publish_chunk(task_id, StreamFinish())
@@ -821,27 +838,6 @@ async def get_active_task_for_session(
                if task_user_id and user_id != task_user_id:
                    continue

-                # Auto-expire stale tasks that exceeded stream_timeout
-                created_at_str = meta.get("created_at", "")
-                if created_at_str:
-                    try:
-                        created_at = datetime.fromisoformat(created_at_str)
-                        age_seconds = (
-                            datetime.now(timezone.utc) - created_at
-                        ).total_seconds()
-                        if age_seconds > config.stream_timeout:
-                            logger.warning(
-                                f"[TASK_LOOKUP] Auto-expiring stale task {task_id[:8]}... "
-                                f"(age={age_seconds:.0f}s > timeout={config.stream_timeout}s)"
-                            )
-                            await mark_task_completed(task_id, "failed")
-                            continue
-                    except (ValueError, TypeError) as exc:
-                        logger.warning(
-                            f"[TASK_LOOKUP] Failed to parse created_at "
-                            f"for task {task_id[:8]}...: {exc}"
-                        )
-
                logger.info(
                    f"[TASK_LOOKUP] Found running task {task_id[:8]}... for session {session_id[:8]}..."
                )
--- a/autogpt_platform/backend/backend/copilot/tools/agent_generator/core.py
+++ b/autogpt_platform/backend/backend/copilot/tools/agent_generator/core.py
@@ -540,15 +540,21 @@ 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, error dict {"type": "error", ...}, or None on error
+        Agent JSON dict, {"status": "accepted"} for async, error dict {"type": "error", ...}, or None on error

    Raises:
        AgentGeneratorNotConfiguredError: If the external service is not configured.
@@ -556,9 +562,13 @@ 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)
+        dict(instructions), _to_dict_list(library_agents), operation_id, task_id
    )

+    # 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
@@ -749,6 +759,8 @@ 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.

@@ -761,10 +773,12 @@ 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", ...},
-        error dict {"type": "error", ...}, or None on error
+        {"status": "accepted"} for async, error dict {"type": "error", ...}, or None on error

    Raises:
        AgentGeneratorNotConfiguredError: If the external service is not configured.
@@ -775,6 +789,8 @@ 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
@@ -101,6 +101,8 @@ 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)")
@@ -112,6 +114,8 @@ 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
@@ -242,18 +242,24 @@ 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 or error dict {"type": "error", ...} on error
+        Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
    """
    if _is_dummy_mode():
-        return await generate_agent_dummy(instructions, library_agents)
+        return await generate_agent_dummy(
+            instructions, library_agents, operation_id, task_id
+        )

    client = _get_client()

@@ -261,9 +267,25 @@ 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()

@@ -295,6 +317,8 @@ 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.

@@ -302,13 +326,15 @@ 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, or error dict on error
+        Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
    """
    if _is_dummy_mode():
        return await generate_agent_patch_dummy(
-            update_request, current_agent, library_agents
+            update_request, current_agent, library_agents, operation_id, task_id
        )

    client = _get_client()
@@ -320,9 +346,25 @@ 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
@@ -38,7 +38,12 @@ class BaseTool:

    @property
    def is_long_running(self) -> bool:
-        """Whether this tool takes a long time to execute (triggers long-running UI)."""
+        """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.
+        """
        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
@@ -18,6 +18,7 @@ from .base import BaseTool
 from .models import (
    AgentPreviewResponse,
    AgentSavedResponse,
+    AsyncProcessingResponse,
    ClarificationNeededResponse,
    ClarifyingQuestion,
    ErrorResponse,
@@ -48,7 +49,6 @@ class CreateAgentTool(BaseTool):

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

    @property
@@ -100,6 +100,10 @@ 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.",
@@ -226,6 +230,8 @@ class CreateAgentTool(BaseTool):
            agent_json = await generate_agent(
                decomposition_result,
                library_agents,
+                operation_id=operation_id,
+                task_id=task_id,
            )
        except AgentGeneratorNotConfiguredError:
            return ErrorResponse(
@@ -270,6 +276,19 @@ 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
@@ -48,7 +48,6 @@ 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
@@ -17,6 +17,7 @@ from .base import BaseTool
 from .models import (
    AgentPreviewResponse,
    AgentSavedResponse,
+    AsyncProcessingResponse,
    ClarificationNeededResponse,
    ClarifyingQuestion,
    ErrorResponse,
@@ -46,7 +47,6 @@ class EditAgentTool(BaseTool):

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

    @property
@@ -105,6 +105,10 @@ 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.",
@@ -153,6 +157,8 @@ class EditAgentTool(BaseTool):
                update_request,
                current_agent,
                library_agents,
+                operation_id=operation_id,
+                task_id=task_id,
            )
        except AgentGeneratorNotConfiguredError:
            return ErrorResponse(
@@ -172,6 +178,19 @@ 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
@@ -459,6 +459,23 @@ 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/backend/data/block_cost_config.py
+++ b/autogpt_platform/backend/backend/data/block_cost_config.py
@@ -75,8 +75,6 @@ MODEL_COST: dict[LlmModel, int] = {
    LlmModel.GPT41_MINI: 1,
    LlmModel.GPT4O_MINI: 1,
    LlmModel.GPT4O: 3,
-    LlmModel.GPT4_TURBO: 10,
-    LlmModel.GPT3_5_TURBO: 1,
    LlmModel.CLAUDE_4_1_OPUS: 21,
    LlmModel.CLAUDE_4_OPUS: 21,
    LlmModel.CLAUDE_4_SONNET: 5,
--- a/autogpt_platform/backend/backend/data/credit_test.py
+++ b/autogpt_platform/backend/backend/data/credit_test.py
@@ -79,7 +79,7 @@ async def test_block_credit_usage(server: SpinTestServer):
            node_exec_id="test_node_exec",
            block_id=AITextGeneratorBlock().id,
            inputs={
-                "model": "gpt-4-turbo",
+                "model": "gpt-4o",
                "credentials": {
                    "id": openai_credentials.id,
                    "provider": openai_credentials.provider,
@@ -100,7 +100,7 @@ async def test_block_credit_usage(server: SpinTestServer):
            graph_exec_id="test_graph_exec",
            node_exec_id="test_node_exec",
            block_id=AITextGeneratorBlock().id,
-            inputs={"model": "gpt-4-turbo", "api_key": "owned_api_key"},
+            inputs={"model": "gpt-4o", "api_key": "owned_api_key"},
            execution_context=ExecutionContext(user_timezone="UTC"),
        ),
    )
--- a/autogpt_platform/backend/backend/data/db_manager.py
+++ b/autogpt_platform/backend/backend/data/db_manager.py
@@ -303,7 +303,7 @@ class DatabaseManager(AppService):
    get_user_chat_sessions = _(chat_db.get_user_chat_sessions)
    get_user_session_count = _(chat_db.get_user_session_count)
    delete_chat_session = _(chat_db.delete_chat_session)
-    get_chat_session_message_count = _(chat_db.get_chat_session_message_count)
+    get_next_sequence = _(chat_db.get_next_sequence)
    update_tool_message_content = _(chat_db.update_tool_message_content)


@@ -473,5 +473,5 @@ class DatabaseManagerAsyncClient(AppServiceClient):
    get_user_chat_sessions = d.get_user_chat_sessions
    get_user_session_count = d.get_user_session_count
    delete_chat_session = d.delete_chat_session
-    get_chat_session_message_count = d.get_chat_session_message_count
+    get_next_sequence = d.get_next_sequence
    update_tool_message_content = d.update_tool_message_content
--- a/autogpt_platform/backend/backend/executor/cluster_lock.py
+++ b/autogpt_platform/backend/backend/executor/cluster_lock.py
@@ -1,5 +1,6 @@
 """Redis-based distributed locking for cluster coordination."""

+import asyncio
 import logging
 import threading
 import time
@@ -7,6 +8,7 @@ from typing import TYPE_CHECKING

 if TYPE_CHECKING:
    from redis import Redis
+    from redis.asyncio import Redis as AsyncRedis

 logger = logging.getLogger(__name__)

@@ -126,3 +128,124 @@ class ClusterLock:

        with self._refresh_lock:
            self._last_refresh = 0.0
+
+
+class AsyncClusterLock:
+    """Async Redis-based distributed lock for preventing duplicate execution."""
+
+    def __init__(
+        self, redis: "AsyncRedis", key: str, owner_id: str, timeout: int = 300
+    ):
+        self.redis = redis
+        self.key = key
+        self.owner_id = owner_id
+        self.timeout = timeout
+        self._last_refresh = 0.0
+        self._refresh_lock = asyncio.Lock()
+
+    async def try_acquire(self) -> str | None:
+        """Try to acquire the lock.
+
+        Returns:
+            - owner_id (self.owner_id) if successfully acquired
+            - different owner_id if someone else holds the lock
+            - None if Redis is unavailable or other error
+        """
+        try:
+            success = await self.redis.set(
+                self.key, self.owner_id, nx=True, ex=self.timeout
+            )
+            if success:
+                async with self._refresh_lock:
+                    self._last_refresh = time.time()
+                return self.owner_id  # Successfully acquired
+
+            # Failed to acquire, get current owner
+            current_value = await self.redis.get(self.key)
+            if current_value:
+                current_owner = (
+                    current_value.decode("utf-8")
+                    if isinstance(current_value, bytes)
+                    else str(current_value)
+                )
+                return current_owner
+
+            # Key doesn't exist but we failed to set it - race condition or Redis issue
+            return None
+
+        except Exception as e:
+            logger.error(f"AsyncClusterLock.try_acquire failed for key {self.key}: {e}")
+            return None
+
+    async def refresh(self) -> bool:
+        """Refresh lock TTL if we still own it.
+
+        Rate limited to at most once every timeout/10 seconds (minimum 1 second).
+        During rate limiting, still verifies lock existence but skips TTL extension.
+        Setting _last_refresh to 0 bypasses rate limiting for testing.
+
+        Async-safe: uses asyncio.Lock to protect _last_refresh access.
+        """
+        # Calculate refresh interval: max(timeout // 10, 1)
+        refresh_interval = max(self.timeout // 10, 1)
+        current_time = time.time()
+
+        # Check if we're within the rate limit period (async-safe read)
+        # _last_refresh == 0 forces a refresh (bypasses rate limiting for testing)
+        async with self._refresh_lock:
+            last_refresh = self._last_refresh
+        is_rate_limited = (
+            last_refresh > 0 and (current_time - last_refresh) < refresh_interval
+        )
+
+        try:
+            # Always verify lock existence, even during rate limiting
+            current_value = await self.redis.get(self.key)
+            if not current_value:
+                async with self._refresh_lock:
+                    self._last_refresh = 0
+                return False
+
+            stored_owner = (
+                current_value.decode("utf-8")
+                if isinstance(current_value, bytes)
+                else str(current_value)
+            )
+            if stored_owner != self.owner_id:
+                async with self._refresh_lock:
+                    self._last_refresh = 0
+                return False
+
+            # If rate limited, return True but don't update TTL or timestamp
+            if is_rate_limited:
+                return True
+
+            # Perform actual refresh
+            if await self.redis.expire(self.key, self.timeout):
+                async with self._refresh_lock:
+                    self._last_refresh = current_time
+                return True
+
+            async with self._refresh_lock:
+                self._last_refresh = 0
+            return False
+
+        except Exception as e:
+            logger.error(f"AsyncClusterLock.refresh failed for key {self.key}: {e}")
+            async with self._refresh_lock:
+                self._last_refresh = 0
+            return False
+
+    async def release(self):
+        """Release the lock."""
+        async with self._refresh_lock:
+            if self._last_refresh == 0:
+                return
+
+        try:
+            await self.redis.delete(self.key)
+        except Exception:
+            pass
+
+        async with self._refresh_lock:
+            self._last_refresh = 0.0
--- a/autogpt_platform/backend/migrations/20260216120000_migrate_deprecated_gpt4_gpt35_models/migration.sql
+++ b/autogpt_platform/backend/migrations/20260216120000_migrate_deprecated_gpt4_gpt35_models/migration.sql
@@ -0,0 +1,42 @@
+-- Migrate deprecated OpenAI GPT-4-turbo and GPT-3.5-turbo models
+-- This updates all AgentNode blocks that use deprecated models
+-- OpenAI is retiring these models:
+--   - gpt-4-turbo: March 26, 2026 -> migrate to gpt-4o
+--   - gpt-3.5-turbo: September 28, 2026 -> migrate to gpt-4o-mini
+
+-- Update gpt-4-turbo to gpt-4o (staying in same capability tier)
+UPDATE "AgentNode"
+SET    "constantInput" = JSONB_SET(
+         "constantInput"::jsonb,
+         '{model}',
+         '"gpt-4o"'::jsonb
+       )
+WHERE  "constantInput"::jsonb->>'model' = 'gpt-4-turbo';
+
+-- Update gpt-3.5-turbo to gpt-4o-mini (appropriate replacement for lightweight model)
+UPDATE "AgentNode"
+SET    "constantInput" = JSONB_SET(
+         "constantInput"::jsonb,
+         '{model}',
+         '"gpt-4o-mini"'::jsonb
+       )
+WHERE  "constantInput"::jsonb->>'model' = 'gpt-3.5-turbo';
+
+-- Update AgentPreset input overrides (stored in AgentNodeExecutionInputOutput)
+UPDATE "AgentNodeExecutionInputOutput"
+SET    "data" = JSONB_SET(
+         "data"::jsonb,
+         '{model}',
+         '"gpt-4o"'::jsonb
+       )
+WHERE  "agentPresetId" IS NOT NULL
+  AND  "data"::jsonb->>'model' = 'gpt-4-turbo';
+
+UPDATE "AgentNodeExecutionInputOutput"
+SET    "data" = JSONB_SET(
+         "data"::jsonb,
+         '{model}',
+         '"gpt-4o-mini"'::jsonb
+       )
+WHERE  "agentPresetId" IS NOT NULL
+  AND  "data"::jsonb->>'model' = 'gpt-3.5-turbo';
--- 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)
+            mock_external.assert_called_once_with(instructions, None, None, None)
            assert result is not None
            assert result["name"] == "Test Agent"
            assert "id" in result
@@ -173,7 +173,9 @@ 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)
+            mock_external.assert_called_once_with(
+                "Add a node", current_agent, None, None, 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
@@ -34,8 +34,7 @@ export const ChatContainer = ({
  onStop,
  headerSlot,
 }: ChatContainerProps) => {
-  const isBusy =
-    status === "streaming" || status === "submitted" || !!isReconnecting;
+  const isBusy = status === "streaming" || !!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
@@ -13,7 +13,6 @@ 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 {
@@ -209,110 +208,86 @@ export const ChatMessagesContainer = ({
                      );
                    case "tool-find_block":
                      return (
-                        <ToolWrapper
+                        <FindBlocksTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <FindBlocksTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-find_agent":
                    case "tool-find_library_agent":
                      return (
-                        <ToolWrapper
+                        <FindAgentsTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <FindAgentsTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-search_docs":
                    case "tool-get_doc_page":
                      return (
-                        <ToolWrapper
+                        <SearchDocsTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <SearchDocsTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-run_block":
                      return (
-                        <ToolWrapper
+                        <RunBlockTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <RunBlockTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-run_agent":
                    case "tool-schedule_agent":
                      return (
-                        <ToolWrapper
+                        <RunAgentTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <RunAgentTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-create_agent":
                      return (
-                        <ToolWrapper
+                        <CreateAgentTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <CreateAgentTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-edit_agent":
                      return (
-                        <ToolWrapper
+                        <EditAgentTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <EditAgentTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-view_agent_output":
                      return (
-                        <ToolWrapper
+                        <ViewAgentOutputTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <ViewAgentOutputTool part={part as ToolUIPart} />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-search_feature_requests":
                      return (
-                        <ToolWrapper
+                        <SearchFeatureRequestsTool
                          key={`${message.id}-${i}`}
                          part={part as ToolUIPart}
-                        >
-                          <SearchFeatureRequestsTool
-                            part={part as ToolUIPart}
-                          />
-                        </ToolWrapper>
+                        />
                      );
                    case "tool-create_feature_request":
                      return (
-                        <ToolWrapper
+                        <CreateFeatureRequestTool
                          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 (
-                          <ToolWrapper
+                          <GenericTool
                            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
@@ -1,32 +0,0 @@
-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/tools/CreateAgent/components/MiniGame/MiniGame.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/MiniGame.tsx
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/assets/sparkles.png
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/assets/sparkles.png
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/useMiniGame.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/components/MiniGame/useMiniGame.ts
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolWrapper/ToolWrapper.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ToolWrapper/ToolWrapper.tsx
@@ -1,52 +0,0 @@
-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/styleguide/page.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/styleguide/page.tsx
@@ -11,6 +11,11 @@ import {
  MessageResponse,
 } from "@/components/ai-elements/message";
 import { Text } from "@/components/atoms/Text/Text";
+import {
+  CredentialsProvidersContext,
+  type CredentialsProviderData,
+  type CredentialsProvidersContextType,
+} from "@/providers/agent-credentials/credentials-provider";
 import { CopilotChatActionsProvider } from "../components/CopilotChatActionsProvider/CopilotChatActionsProvider";
 import { CreateAgentTool } from "../tools/CreateAgent/CreateAgent";
 import { EditAgentTool } from "../tools/EditAgent/EditAgent";
@@ -97,6 +102,65 @@ function uid() {
  return `sg-${++_id}`;
 }

+// ---------------------------------------------------------------------------
+// Mock credential providers for setup-requirements demos
+// ---------------------------------------------------------------------------
+
+const noop = () => Promise.reject(new Error("Styleguide mock"));
+
+function makeMockProvider(
+  provider: string,
+  providerName: string,
+  savedCredentials: CredentialsProviderData["savedCredentials"] = [],
+): CredentialsProviderData {
+  return {
+    provider,
+    providerName,
+    savedCredentials,
+    isSystemProvider: false,
+    oAuthCallback: noop as CredentialsProviderData["oAuthCallback"],
+    mcpOAuthCallback: noop as CredentialsProviderData["mcpOAuthCallback"],
+    createAPIKeyCredentials:
+      noop as CredentialsProviderData["createAPIKeyCredentials"],
+    createUserPasswordCredentials:
+      noop as CredentialsProviderData["createUserPasswordCredentials"],
+    createHostScopedCredentials:
+      noop as CredentialsProviderData["createHostScopedCredentials"],
+    deleteCredentials: noop as CredentialsProviderData["deleteCredentials"],
+  };
+}
+
+/**
+ * Provider context where the user already has saved credentials
+ * so the credential picker shows a selection list.
+ */
+const MOCK_PROVIDERS_WITH_CREDENTIALS: CredentialsProvidersContextType = {
+  google: makeMockProvider("google", "Google", [
+    {
+      id: "cred-google-1",
+      provider: "google",
+      type: "oauth2",
+      title: "work@company.com",
+      scopes: ["email", "calendar"],
+    },
+    {
+      id: "cred-google-2",
+      provider: "google",
+      type: "oauth2",
+      title: "personal@gmail.com",
+      scopes: ["email", "calendar"],
+    },
+  ]),
+};
+
+/**
+ * Provider context where the user has NO saved credentials,
+ * so the credential picker shows an "add new" flow.
+ */
+const MOCK_PROVIDERS_WITHOUT_CREDENTIALS: CredentialsProvidersContextType = {
+  openweathermap: makeMockProvider("openweathermap", "OpenWeatherMap"),
+};
+
 // ---------------------------------------------------------------------------
 // Page
 // ---------------------------------------------------------------------------
@@ -554,45 +618,80 @@ export default function StyleguidePage() {
                />
              </SubSection>

-              <SubSection label="Output available (setup requirements)">
-                <RunBlockTool
-                  part={{
-                    type: "tool-run_block",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { block_id: "weather-block-123" },
-                    output: {
-                      type: ResponseType.setup_requirements,
-                      message:
-                        "This block requires API credentials to run. Please configure them below.",
-                      setup_info: {
-                        agent_name: "Weather Agent",
-                        requirements: {
-                          inputs: [
-                            {
-                              name: "city",
-                              title: "City",
-                              type: "string",
-                              required: true,
-                              description: "The city to get weather for",
-                            },
-                          ],
-                        },
-                        user_readiness: {
-                          missing_credentials: {
-                            openweathermap: {
-                              provider: "openweathermap",
-                              credentials_type: "api_key",
-                              title: "OpenWeatherMap API Key",
-                              description:
-                                "Required to access weather data. Get your key at openweathermap.org",
+              <SubSection label="Setup requirements — no credentials (add new)">
+                <CredentialsProvidersContext.Provider
+                  value={MOCK_PROVIDERS_WITHOUT_CREDENTIALS}
+                >
+                  <RunBlockTool
+                    part={{
+                      type: "tool-run_block",
+                      toolCallId: uid(),
+                      state: "output-available",
+                      input: { block_id: "weather-block-123" },
+                      output: {
+                        type: ResponseType.setup_requirements,
+                        message:
+                          "This block requires API credentials to run. Please configure them below.",
+                        setup_info: {
+                          agent_id: "agent-weather-1",
+                          agent_name: "Weather Agent",
+                          requirements: {
+                            inputs: [
+                              {
+                                name: "city",
+                                title: "City",
+                                type: "string",
+                                required: true,
+                                description: "The city to get weather for",
+                              },
+                            ],
+                          },
+                          user_readiness: {
+                            missing_credentials: {
+                              openweathermap_key: {
+                                provider: "openweathermap",
+                                types: ["api_key"],
+                              },
                            },
                          },
                        },
                      },
-                    },
-                  }}
-                />
+                    }}
+                  />
+                </CredentialsProvidersContext.Provider>
+              </SubSection>
+
+              <SubSection label="Setup requirements — has credentials (pick from list)">
+                <CredentialsProvidersContext.Provider
+                  value={MOCK_PROVIDERS_WITH_CREDENTIALS}
+                >
+                  <RunBlockTool
+                    part={{
+                      type: "tool-run_block",
+                      toolCallId: uid(),
+                      state: "output-available",
+                      input: { block_id: "calendar-block-456" },
+                      output: {
+                        type: ResponseType.setup_requirements,
+                        message:
+                          "This block requires Google credentials. Pick an account below or connect a new one.",
+                        setup_info: {
+                          agent_id: "agent-calendar-1",
+                          agent_name: "Calendar Agent",
+                          user_readiness: {
+                            missing_credentials: {
+                              google_oauth: {
+                                provider: "google",
+                                types: ["oauth2"],
+                                scopes: ["email", "calendar"],
+                              },
+                            },
+                          },
+                        },
+                      },
+                    }}
+                  />
+                </CredentialsProvidersContext.Provider>
              </SubSection>

              <SubSection label="Output available (error)">
@@ -849,34 +948,71 @@ export default function StyleguidePage() {
                />
              </SubSection>

-              <SubSection label="Output available (setup requirements)">
-                <RunAgentTool
-                  part={{
-                    type: "tool-run_agent",
-                    toolCallId: uid(),
-                    state: "output-available",
-                    input: { username_agent_slug: "creator/my-agent" },
-                    output: {
-                      type: ResponseType.setup_requirements,
-                      message: "This agent requires additional setup.",
-                      setup_info: {
-                        agent_name: "YouTube Summarizer",
-                        requirements: {},
-                        user_readiness: {
-                          missing_credentials: {
-                            youtube_api: {
-                              provider: "youtube",
-                              credentials_type: "api_key",
-                              title: "YouTube Data API Key",
-                              description:
-                                "Required to access YouTube video data.",
+              <SubSection label="Setup requirements — no credentials (add new)">
+                <CredentialsProvidersContext.Provider
+                  value={MOCK_PROVIDERS_WITHOUT_CREDENTIALS}
+                >
+                  <RunAgentTool
+                    part={{
+                      type: "tool-run_agent",
+                      toolCallId: uid(),
+                      state: "output-available",
+                      input: { username_agent_slug: "creator/weather-agent" },
+                      output: {
+                        type: ResponseType.setup_requirements,
+                        message:
+                          "This agent requires an API key. Add your credentials below.",
+                        setup_info: {
+                          agent_id: "agent-weather-1",
+                          agent_name: "Weather Agent",
+                          requirements: {},
+                          user_readiness: {
+                            missing_credentials: {
+                              openweathermap_key: {
+                                provider: "openweathermap",
+                                types: ["api_key"],
+                              },
                            },
                          },
                        },
                      },
-                    },
-                  }}
-                />
+                    }}
+                  />
+                </CredentialsProvidersContext.Provider>
+              </SubSection>
+
+              <SubSection label="Setup requirements — has credentials (pick from list)">
+                <CredentialsProvidersContext.Provider
+                  value={MOCK_PROVIDERS_WITH_CREDENTIALS}
+                >
+                  <RunAgentTool
+                    part={{
+                      type: "tool-run_agent",
+                      toolCallId: uid(),
+                      state: "output-available",
+                      input: { username_agent_slug: "creator/calendar-agent" },
+                      output: {
+                        type: ResponseType.setup_requirements,
+                        message:
+                          "This agent needs Google credentials. Pick an account or connect a new one.",
+                        setup_info: {
+                          agent_id: "agent-calendar-1",
+                          agent_name: "Google Calendar Agent",
+                          requirements: {},
+                          user_readiness: {
+                            missing_credentials: {
+                              google_oauth: {
+                                provider: "google",
+                                types: ["oauth2"],
+                                scopes: ["email", "calendar"],
+                              },
+                            },
+                          },
+                        },
+                      },
+                    }}
+                  />
+                </CredentialsProvidersContext.Provider>
              </SubSection>

              <SubSection label="Output available (need login)">
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/CreateAgent/CreateAgent.tsx
@@ -23,7 +23,8 @@ import {
  ClarificationQuestionsCard,
  ClarifyingQuestion,
 } from "./components/ClarificationQuestionsCard";
-import sparklesImg from "./components/MiniGame/assets/sparkles.png";
+import sparklesImg from "../../components/MiniGame/assets/sparkles.png";
+import { MiniGame } from "../../components/MiniGame/MiniGame";
 import { SuggestedGoalCard } from "./components/SuggestedGoalCard";
 import {
  AccordionIcon,
@@ -34,6 +35,9 @@ import {
  isAgentSavedOutput,
  isClarificationNeededOutput,
  isErrorOutput,
+  isOperationInProgressOutput,
+  isOperationPendingOutput,
+  isOperationStartedOutput,
  isSuggestedGoalOutput,
  ToolIcon,
  truncateText,
@@ -81,6 +85,16 @@ function getAccordionMeta(output: CreateAgentToolOutput) {
      expanded: true,
    };
  }
+  if (
+    isOperationStartedOutput(output) ||
+    isOperationPendingOutput(output) ||
+    isOperationInProgressOutput(output)
+  ) {
+    return {
+      icon,
+      title: output.message || "Agent creation started",
+    };
+  }
  return {
    icon: (
      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
@@ -102,10 +116,19 @@ 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 &&
-    (isAgentPreviewOutput(output) ||
+    (isOperationStartedOutput(output) ||
+      isOperationPendingOutput(output) ||
+      isOperationInProgressOutput(output) ||
+      isAgentPreviewOutput(output) ||
      isAgentSavedOutput(output) ||
      isClarificationNeededOutput(output) ||
      isSuggestedGoalOutput(output) ||
@@ -143,8 +166,24 @@ export function CreateAgentTool({ part }: Props) {
        />
      </div>

+      {isStreaming && (
+        <ToolAccordion
+          icon={<AccordionIcon />}
+          title="Creating agent, this may take a few minutes. Play while you wait."
+          expanded
+        >
+          <ContentGrid>
+            <MiniGame />
+          </ContentGrid>
+        </ToolAccordion>
+      )}
+
      {hasExpandableContent && output && (
        <ToolAccordion {...getAccordionMeta(output)}>
+          {isOperating && output.message && (
+            <ContentMessage>{output.message}</ContentMessage>
+          )}
+
          {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
@@ -2,6 +2,9 @@ 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 {
@@ -13,6 +16,9 @@ import type { ToolUIPart } from "ai";
 import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";

 export type CreateAgentToolOutput =
+  | OperationStartedResponse
+  | OperationPendingResponse
+  | OperationInProgressResponse
  | AgentPreviewResponse
  | AgentSavedResponse
  | ClarificationNeededResponse
@@ -33,6 +39,9 @@ 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 ||
@@ -41,6 +50,9 @@ 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)
@@ -60,6 +72,30 @@ 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 {
@@ -108,6 +144,10 @@ 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
@@ -12,6 +12,7 @@ import {
  ContentMessage,
 } from "../../components/ToolAccordion/AccordionContent";
 import { ToolAccordion } from "../../components/ToolAccordion/ToolAccordion";
+import { MiniGame } from "../../components/MiniGame/MiniGame";
 import {
  ClarificationQuestionsCard,
  ClarifyingQuestion,
@@ -25,6 +26,9 @@ import {
  isAgentSavedOutput,
  isClarificationNeededOutput,
  isErrorOutput,
+  isOperationInProgressOutput,
+  isOperationPendingOutput,
+  isOperationStartedOutput,
  ToolIcon,
  truncateText,
  type EditAgentToolOutput,
@@ -69,6 +73,16 @@ function getAccordionMeta(output: EditAgentToolOutput): {
      description: `${questions.length} question${questions.length === 1 ? "" : "s"}`,
    };
  }
+  if (
+    isOperationStartedOutput(output) ||
+    isOperationPendingOutput(output) ||
+    isOperationInProgressOutput(output)
+  ) {
+    return {
+      icon,
+      title: output.message || "Agent editing started",
+    };
+  }
  return {
    icon: (
      <WarningDiamondIcon size={32} weight="light" className="text-red-500" />
@@ -87,10 +101,18 @@ 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 &&
-    (isAgentPreviewOutput(output) ||
+    (isOperationStartedOutput(output) ||
+      isOperationPendingOutput(output) ||
+      isOperationInProgressOutput(output) ||
+      isAgentPreviewOutput(output) ||
      isAgentSavedOutput(output) ||
      isClarificationNeededOutput(output) ||
      isErrorOutput(output));
@@ -123,8 +145,24 @@ export function EditAgentTool({ part }: Props) {
        />
      </div>

+      {isStreaming && (
+        <ToolAccordion
+          icon={<AccordionIcon />}
+          title="Editing agent, this may take a few minutes. Play while you wait."
+          expanded
+        >
+          <ContentGrid>
+            <MiniGame />
+          </ContentGrid>
+        </ToolAccordion>
+      )}
+
      {hasExpandableContent && output && (
        <ToolAccordion {...getAccordionMeta(output)}>
+          {isOperating && output.message && (
+            <ContentMessage>{output.message}</ContentMessage>
+          )}
+
          {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
@@ -2,6 +2,9 @@ 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,
@@ -12,6 +15,9 @@ import type { ToolUIPart } from "ai";
 import { OrbitLoader } from "../../components/OrbitLoader/OrbitLoader";

 export type EditAgentToolOutput =
+  | OperationStartedResponse
+  | OperationPendingResponse
+  | OperationInProgressResponse
  | AgentPreviewResponse
  | AgentSavedResponse
  | ClarificationNeededResponse
@@ -32,6 +38,8 @@ 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 ||
@@ -39,6 +47,9 @@ 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)
@@ -57,6 +68,30 @@ 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 {
@@ -97,6 +132,10 @@ 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/tools/RunAgent/RunAgent.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/RunAgent.tsx
@@ -9,7 +9,7 @@ import {
  ContentHint,
  ContentMessage,
 } from "../../components/ToolAccordion/AccordionContent";
-import { MiniGame } from "../CreateAgent/components/MiniGame/MiniGame";
+import { MiniGame } from "../../components/MiniGame/MiniGame";
 import {
  getAccordionMeta,
  getAnimationText,
@@ -47,14 +47,25 @@ export function RunAgentTool({ part }: Props) {
  const isError =
    part.state === "output-error" ||
    (!!output && isRunAgentErrorOutput(output));
+  const isOutputAvailable = part.state === "output-available" && !!output;
+
+  const setupRequirementsOutput =
+    isOutputAvailable && isRunAgentSetupRequirementsOutput(output)
+      ? output
+      : null;
+
+  const agentDetailsOutput =
+    isOutputAvailable && isRunAgentAgentDetailsOutput(output) ? output : null;
+
+  const needLoginOutput =
+    isOutputAvailable && isRunAgentNeedLoginOutput(output) ? output : null;
+
  const hasExpandableContent =
-    part.state === "output-available" &&
-    !!output &&
-    (isRunAgentExecutionStartedOutput(output) ||
-      isRunAgentAgentDetailsOutput(output) ||
-      isRunAgentSetupRequirementsOutput(output) ||
-      isRunAgentNeedLoginOutput(output) ||
-      isRunAgentErrorOutput(output));
+    isOutputAvailable &&
+    !setupRequirementsOutput &&
+    !agentDetailsOutput &&
+    !needLoginOutput &&
+    (isRunAgentExecutionStartedOutput(output) || isRunAgentErrorOutput(output));

  return (
    <div className="py-2">
@@ -81,24 +92,30 @@ export function RunAgentTool({ part }: Props) {
        </ToolAccordion>
      )}

+      {setupRequirementsOutput && (
+        <div className="mt-2">
+          <SetupRequirementsCard output={setupRequirementsOutput} />
+        </div>
+      )}
+
+      {agentDetailsOutput && (
+        <div className="mt-2">
+          <AgentDetailsCard output={agentDetailsOutput} />
+        </div>
+      )}
+
+      {needLoginOutput && (
+        <div className="mt-2">
+          <ContentMessage>{needLoginOutput.message}</ContentMessage>
+        </div>
+      )}
+
      {hasExpandableContent && output && (
        <ToolAccordion {...getAccordionMeta(output)}>
          {isRunAgentExecutionStartedOutput(output) && (
            <ExecutionStartedCard output={output} />
          )}

-          {isRunAgentAgentDetailsOutput(output) && (
-            <AgentDetailsCard output={output} />
-          )}
-
-          {isRunAgentSetupRequirementsOutput(output) && (
-            <SetupRequirementsCard output={output} />
-          )}
-
-          {isRunAgentNeedLoginOutput(output) && (
-            <ContentMessage>{output.message}</ContentMessage>
-          )}
-
          {isRunAgentErrorOutput(output) && <ErrorCard output={output} />}
        </ToolAccordion>
      )}
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/SetupRequirementsCard.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunAgent/components/SetupRequirementsCard/SetupRequirementsCard.tsx
@@ -1,10 +1,11 @@
 "use client";

-import { useState } from "react";
-import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
-import { Button } from "@/components/atoms/Button/Button";
-import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
 import type { SetupRequirementsResponse } from "@/app/api/__generated__/models/setupRequirementsResponse";
+import { Button } from "@/components/atoms/Button/Button";
+import { Text } from "@/components/atoms/Text/Text";
+import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
+import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
+import { useState } from "react";
 import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
 import {
  ContentBadge,
@@ -38,40 +39,40 @@ export function SetupRequirementsCard({ output }: Props) {
    setInputCredentials((prev) => ({ ...prev, [key]: value }));
  }

-  const isAllComplete =
-    credentialFields.length > 0 &&
+  const needsCredentials = credentialFields.length > 0;
+  const isAllCredentialsComplete =
+    needsCredentials &&
    [...requiredCredentials].every((key) => !!inputCredentials[key]);

+  const canProceed =
+    !hasSent && (!needsCredentials || isAllCredentialsComplete);
+
  function handleProceed() {
    setHasSent(true);
-    onSend(
-      "I've configured the required credentials. Please check if everything is ready and proceed with running the agent.",
-    );
+    const message = needsCredentials
+      ? "I've configured the required credentials. Please check if everything is ready and proceed with running the agent."
+      : "Please proceed with running the agent.";
+    onSend(message);
  }

  return (
    <div className="grid gap-2">
      <ContentMessage>{output.message}</ContentMessage>

-      {credentialFields.length > 0 && (
+      {needsCredentials && (
        <div className="rounded-2xl border bg-background p-3">
-          <CredentialsGroupedView
-            credentialFields={credentialFields}
-            requiredCredentials={requiredCredentials}
-            inputCredentials={inputCredentials}
-            inputValues={{}}
-            onCredentialChange={handleCredentialChange}
-          />
-          {isAllComplete && !hasSent && (
-            <Button
-              variant="primary"
-              size="small"
-              className="mt-3 w-full"
-              onClick={handleProceed}
-            >
-              Proceed
-            </Button>
-          )}
+          <Text variant="small" className="w-fit border-b text-zinc-500">
+            Agent credentials
+          </Text>
+          <div className="mt-6">
+            <CredentialsGroupedView
+              credentialFields={credentialFields}
+              requiredCredentials={requiredCredentials}
+              inputCredentials={inputCredentials}
+              inputValues={{}}
+              onCredentialChange={handleCredentialChange}
+            />
+          </div>
        </div>
      )}

@@ -100,6 +101,18 @@ export function SetupRequirementsCard({ output }: Props) {
          </div>
        </div>
      )}
+
+      {(needsCredentials || expectedInputs.length > 0) && (
+        <Button
+          variant="primary"
+          size="small"
+          className="mt-4 w-fit"
+          disabled={!canProceed}
+          onClick={handleProceed}
+        >
+          Proceed
+        </Button>
+      )}
    </div>
  );
 }
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/RunBlock.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/RunBlock.tsx
@@ -39,12 +39,19 @@ export function RunBlockTool({ part }: Props) {
  const isError =
    part.state === "output-error" ||
    (!!output && isRunBlockErrorOutput(output));
+  const setupRequirementsOutput =
+    part.state === "output-available" &&
+    output &&
+    isRunBlockSetupRequirementsOutput(output)
+      ? output
+      : null;
+
  const hasExpandableContent =
    part.state === "output-available" &&
    !!output &&
+    !setupRequirementsOutput &&
    (isRunBlockBlockOutput(output) ||
      isRunBlockDetailsOutput(output) ||
-      isRunBlockSetupRequirementsOutput(output) ||
      isRunBlockErrorOutput(output));

  return (
@@ -57,6 +64,12 @@ export function RunBlockTool({ part }: Props) {
        />
      </div>

+      {setupRequirementsOutput && (
+        <div className="mt-2">
+          <SetupRequirementsCard output={setupRequirementsOutput} />
+        </div>
+      )}
+
      {hasExpandableContent && output && (
        <ToolAccordion {...getAccordionMeta(output)}>
          {isRunBlockBlockOutput(output) && <BlockOutputCard output={output} />}
@@ -65,10 +78,6 @@ export function RunBlockTool({ part }: Props) {
            <BlockDetailsCard output={output} />
          )}

-          {isRunBlockSetupRequirementsOutput(output) && (
-            <SetupRequirementsCard output={output} />
-          )}
-
          {isRunBlockErrorOutput(output) && <ErrorCard output={output} />}
        </ToolAccordion>
      )}
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/SetupRequirementsCard.tsx
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/tools/RunBlock/components/SetupRequirementsCard/SetupRequirementsCard.tsx
@@ -6,15 +6,9 @@ import { Text } from "@/components/atoms/Text/Text";
 import { CredentialsGroupedView } from "@/components/contextual/CredentialsInput/components/CredentialsGroupedView/CredentialsGroupedView";
 import { FormRenderer } from "@/components/renderers/InputRenderer/FormRenderer";
 import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types";
-import { AnimatePresence, motion } from "framer-motion";
 import { useState } from "react";
 import { useCopilotChatActions } from "../../../../components/CopilotChatActionsProvider/useCopilotChatActions";
-import {
-  ContentBadge,
-  ContentCardDescription,
-  ContentCardTitle,
-  ContentMessage,
-} from "../../../../components/ToolAccordion/AccordionContent";
+import { ContentMessage } from "../../../../components/ToolAccordion/AccordionContent";
 import {
  buildExpectedInputsSchema,
  coerceCredentialFields,
@@ -31,10 +25,8 @@ export function SetupRequirementsCard({ output }: Props) {
  const [inputCredentials, setInputCredentials] = useState<
    Record<string, CredentialsMetaInput | undefined>
  >({});
-  const [hasSentCredentials, setHasSentCredentials] = useState(false);
-
-  const [showInputForm, setShowInputForm] = useState(false);
  const [inputValues, setInputValues] = useState<Record<string, unknown>>({});
+  const [hasSent, setHasSent] = useState(false);

  const { credentialFields, requiredCredentials } = coerceCredentialFields(
    output.setup_info.user_readiness?.missing_credentials,
@@ -50,27 +42,49 @@ export function SetupRequirementsCard({ output }: Props) {
    setInputCredentials((prev) => ({ ...prev, [key]: value }));
  }

+  const needsCredentials = credentialFields.length > 0;
  const isAllCredentialsComplete =
-    credentialFields.length > 0 &&
+    needsCredentials &&
    [...requiredCredentials].every((key) => !!inputCredentials[key]);

-  function handleProceedCredentials() {
-    setHasSentCredentials(true);
-    onSend(
-      "I've configured the required credentials. Please re-run the block now.",
-    );
-  }
+  const needsInputs = inputSchema !== null;
+  const requiredInputNames = expectedInputs
+    .filter((i) => i.required)
+    .map((i) => i.name);
+  const isAllInputsComplete =
+    needsInputs &&
+    requiredInputNames.every((name) => {
+      const v = inputValues[name];
+      return v !== undefined && v !== null && v !== "";
+    });

-  function handleRunWithInputs() {
-    const nonEmpty = Object.fromEntries(
-      Object.entries(inputValues).filter(
-        ([, v]) => v !== undefined && v !== null && v !== "",
-      ),
-    );
-    onSend(
-      `Run the block with these inputs: ${JSON.stringify(nonEmpty, null, 2)}`,
-    );
-    setShowInputForm(false);
+  const canRun =
+    !hasSent &&
+    (!needsCredentials || isAllCredentialsComplete) &&
+    (!needsInputs || isAllInputsComplete);
+
+  function handleRun() {
+    setHasSent(true);
+
+    const parts: string[] = [];
+    if (needsCredentials) {
+      parts.push("I've configured the required credentials.");
+    }
+
+    if (needsInputs) {
+      const nonEmpty = Object.fromEntries(
+        Object.entries(inputValues).filter(
+          ([, v]) => v !== undefined && v !== null && v !== "",
+        ),
+      );
+      parts.push(
+        `Run the block with these inputs: ${JSON.stringify(nonEmpty, null, 2)}`,
+      );
+    } else {
+      parts.push("Please re-run the block now.");
+    }
+
+    onSend(parts.join(" "));
    setInputValues({});
  }

@@ -78,119 +92,54 @@ export function SetupRequirementsCard({ output }: Props) {
    <div className="grid gap-2">
      <ContentMessage>{output.message}</ContentMessage>

-      {credentialFields.length > 0 && (
+      {needsCredentials && (
        <div className="rounded-2xl border bg-background p-3">
-          <CredentialsGroupedView
-            credentialFields={credentialFields}
-            requiredCredentials={requiredCredentials}
-            inputCredentials={inputCredentials}
-            inputValues={{}}
-            onCredentialChange={handleCredentialChange}
-          />
-          {isAllCredentialsComplete && !hasSentCredentials && (
-            <Button
-              variant="primary"
-              size="small"
-              className="mt-3 w-full"
-              onClick={handleProceedCredentials}
-            >
-              Proceed
-            </Button>
-          )}
+          <Text variant="small" className="w-fit border-b text-zinc-500">
+            Block credentials
+          </Text>
+          <div className="mt-6">
+            <CredentialsGroupedView
+              credentialFields={credentialFields}
+              requiredCredentials={requiredCredentials}
+              inputCredentials={inputCredentials}
+              inputValues={{}}
+              onCredentialChange={handleCredentialChange}
+            />
+          </div>
        </div>
      )}

      {inputSchema && (
-        <div className="flex gap-2 pt-2">
-          <Button
-            variant="outline"
-            size="small"
-            className="w-fit"
-            onClick={() => setShowInputForm((prev) => !prev)}
-          >
-            {showInputForm ? "Hide inputs" : "Fill in inputs"}
-          </Button>
+        <div className="rounded-2xl border bg-background p-3 pt-4">
+          <Text variant="small" className="w-fit border-b text-zinc-500">
+            Block inputs
+          </Text>
+          <FormRenderer
+            jsonSchema={inputSchema}
+            className="mb-3 mt-3"
+            handleChange={(v) => setInputValues(v.formData ?? {})}
+            uiSchema={{
+              "ui:submitButtonOptions": { norender: true },
+            }}
+            initialValues={inputValues}
+            formContext={{
+              showHandles: false,
+              size: "small",
+            }}
+          />
        </div>
      )}

-      <AnimatePresence initial={false}>
-        {showInputForm && inputSchema && (
-          <motion.div
-            initial={{ height: 0, opacity: 0, filter: "blur(6px)" }}
-            animate={{ height: "auto", opacity: 1, filter: "blur(0px)" }}
-            exit={{ height: 0, opacity: 0, filter: "blur(6px)" }}
-            transition={{
-              height: { type: "spring", bounce: 0.15, duration: 0.5 },
-              opacity: { duration: 0.25 },
-              filter: { duration: 0.2 },
-            }}
-            className="overflow-hidden"
-            style={{ willChange: "height, opacity, filter" }}
-          >
-            <div className="rounded-2xl border bg-background p-3 pt-4">
-              <Text variant="body-medium">Block inputs</Text>
-              <FormRenderer
-                jsonSchema={inputSchema}
-                handleChange={(v) => setInputValues(v.formData ?? {})}
-                uiSchema={{
-                  "ui:submitButtonOptions": { norender: true },
-                }}
-                initialValues={inputValues}
-                formContext={{
-                  showHandles: false,
-                  size: "small",
-                }}
-              />
-              <div className="-mt-8 flex gap-2">
-                <Button
-                  variant="primary"
-                  size="small"
-                  className="w-fit"
-                  onClick={handleRunWithInputs}
-                >
-                  Run
-                </Button>
-                <Button
-                  variant="secondary"
-                  size="small"
-                  className="w-fit"
-                  onClick={() => {
-                    setShowInputForm(false);
-                    setInputValues({});
-                  }}
-                >
-                  Cancel
-                </Button>
-              </div>
-            </div>
-          </motion.div>
-        )}
-      </AnimatePresence>
-
-      {expectedInputs.length > 0 && !inputSchema && (
-        <div className="rounded-2xl border bg-background p-3">
-          <ContentCardTitle className="text-xs">
-            Expected inputs
-          </ContentCardTitle>
-          <div className="mt-2 grid gap-2">
-            {expectedInputs.map((input) => (
-              <div key={input.name} className="rounded-xl border p-2">
-                <div className="flex items-center justify-between gap-2">
-                  <ContentCardTitle className="text-xs">
-                    {input.title}
-                  </ContentCardTitle>
-                  <ContentBadge>
-                    {input.required ? "Required" : "Optional"}
-                  </ContentBadge>
-                </div>
-                <ContentCardDescription className="mt-1">
-                  {input.name} &bull; {input.type}
-                  {input.description ? ` \u2022 ${input.description}` : ""}
-                </ContentCardDescription>
-              </div>
-            ))}
-          </div>
-        </div>
+      {(needsCredentials || needsInputs) && (
+        <Button
+          variant="primary"
+          size="small"
+          className="w-fit"
+          disabled={!canRun}
+          onClick={handleRun}
+        >
+          Proceed
+        </Button>
      )}
    </div>
  );
--- a/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
+++ b/autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotPage.ts
@@ -16,7 +16,7 @@ import { useCallback, useEffect, useMemo, useRef, useState } from "react";
 import { useChatSession } from "./useChatSession";
 import { useLongRunningToolPolling } from "./hooks/useLongRunningToolPolling";

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

 /** Mark any in-progress tool parts as completed/errored so spinners stop. */
 function resolveInProgressTools(
@@ -203,9 +203,8 @@ export function useCopilotPage() {
    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) {
+    const isIdle = status === "ready" || status === "error";
+    if (wasActive && isIdle && sessionId) {
      queryClient.invalidateQueries({
        queryKey: getGetV2GetSessionQueryKey(sessionId),
      });
--- a/autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/CredentialsFlatView/CredentialsFlatView.tsx
+++ b/autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/CredentialsFlatView/CredentialsFlatView.tsx
@@ -119,7 +119,7 @@ export function CredentialsFlatView({
      ) : (
        !readOnly && (
          <Button
-            variant="secondary"
+            variant="primary"
            size="small"
            onClick={onAddCredential}
            className="w-fit"
--- a/autogpt_platform/frontend/src/components/renderers/InputRenderer/FormRenderer.tsx
+++ b/autogpt_platform/frontend/src/components/renderers/InputRenderer/FormRenderer.tsx
@@ -1,10 +1,11 @@
+import { cn } from "@/lib/utils";
 import { RJSFSchema } from "@rjsf/utils";
-import { preprocessInputSchema } from "./utils/input-schema-pre-processor";
 import { useMemo } from "react";
-import { customValidator } from "./utils/custom-validator";
 import Form from "./registry";
 import { ExtendedFormContextType } from "./types";
+import { customValidator } from "./utils/custom-validator";
 import { generateUiSchemaForCustomFields } from "./utils/generate-ui-schema";
+import { preprocessInputSchema } from "./utils/input-schema-pre-processor";

 type FormRendererProps = {
  jsonSchema: RJSFSchema;
@@ -12,15 +13,17 @@ type FormRendererProps = {
  uiSchema: any;
  initialValues: any;
  formContext: ExtendedFormContextType;
+  className?: string;
 };

-export const FormRenderer = ({
+export function FormRenderer({
  jsonSchema,
  handleChange,
  uiSchema,
  initialValues,
  formContext,
-}: FormRendererProps) => {
+  className,
+}: FormRendererProps) {
  const preprocessedSchema = useMemo(() => {
    return preprocessInputSchema(jsonSchema);
  }, [jsonSchema]);
@@ -31,7 +34,10 @@ export const FormRenderer = ({
  }, [preprocessedSchema, uiSchema]);

  return (
-    <div className={"mb-6 mt-4"} data-tutorial-id="input-handles">
+    <div
+      className={cn("mb-6 mt-4", className)}
+      data-tutorial-id="input-handles"
+    >
      <Form
        formContext={formContext}
        idPrefix="agpt"
@@ -45,4 +51,4 @@ export const FormRenderer = ({
      />
    </div>
  );
-};
+}
--- a/docs/integrations/block-integrations/llm.md
+++ b/docs/integrations/block-integrations/llm.md
@@ -65,7 +65,7 @@ The result routes data to yes_output or no_output, enabling intelligent branchin
 | condition | A plaintext English description of the condition to evaluate | str | Yes |
 | yes_value | (Optional) Value to output if the condition is true. If not provided, input_value will be used. | Yes Value | No |
 | no_value | (Optional) Value to output if the condition is false. If not provided, input_value will be used. | No Value | No |
-| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for evaluating the condition. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |

 ### Outputs

@@ -103,7 +103,7 @@ The block sends the entire conversation history to the chosen LLM, including sys
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. | str | No |
 | messages | List of messages in the conversation. | List[Any] | Yes |
-| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for the conversation. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
 | ollama_host | Ollama host for local  models | str | No |

@@ -257,7 +257,7 @@ The block formulates a prompt based on the given focus or source data, sends it
 |-------|-------------|------|----------|
 | focus | The focus of the list to generate. | str | No |
 | source_data | The data to generate the list from. | str | No |
-| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for generating the list. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | max_retries | Maximum number of retries for generating a valid list. | int | No |
 | force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -424,7 +424,7 @@ The block sends the input prompt to a chosen LLM, along with any system prompts
 | prompt | The prompt to send to the language model. | str | Yes |
 | expected_format | Expected format of the response. If provided, the response will be validated against this format. The keys should be the expected fields in the response, and the values should be the description of the field. | Dict[str, str] | Yes |
 | list_result | Whether the response should be a list of objects in the expected format. | bool | No |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | force_json_output | Whether to force the LLM to produce a JSON-only response. This can increase the block's reliability, but may also reduce the quality of the response because it prohibits the LLM from reasoning before providing its JSON response. | bool | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
@@ -464,7 +464,7 @@ The block sends the input prompt to a chosen LLM, processes the response, and re
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. You can use any of the {keys} from Prompt Values to fill in the prompt with values from the prompt values dictionary by putting them in curly braces. | str | Yes |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | retry | Number of times to retry the LLM call if the response does not match the expected format. | int | No |
 | prompt_values | Values used to fill in the prompt. The values can be used in the prompt by putting them in a double curly braces, e.g. {{variable_name}}. | Dict[str, str] | No |
@@ -501,7 +501,7 @@ The block splits the input text into smaller chunks, sends each chunk to an LLM
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | text | The text to summarize. | str | Yes |
-| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for summarizing the text. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | focus | The topic to focus on in the summary | str | No |
 | style | The style of the summary to generate. | "concise" \| "detailed" \| "bullet points" \| "numbered list" | No |
 | max_tokens | The maximum number of tokens to generate in the chat completion. | int | No |
@@ -763,7 +763,7 @@ Configure agent_mode_max_iterations to control loop behavior: 0 for single decis
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | prompt | The prompt to send to the language model. | str | Yes |
-| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "gpt-4-turbo" \| "gpt-3.5-turbo" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
+| model | The language model to use for answering the prompt. | "o3-mini" \| "o3-2025-04-16" \| "o1" \| "o1-mini" \| "gpt-5.2-2025-12-11" \| "gpt-5.1-2025-11-13" \| "gpt-5-2025-08-07" \| "gpt-5-mini-2025-08-07" \| "gpt-5-nano-2025-08-07" \| "gpt-5-chat-latest" \| "gpt-4.1-2025-04-14" \| "gpt-4.1-mini-2025-04-14" \| "gpt-4o-mini" \| "gpt-4o" \| "claude-opus-4-1-20250805" \| "claude-opus-4-20250514" \| "claude-sonnet-4-20250514" \| "claude-opus-4-5-20251101" \| "claude-sonnet-4-5-20250929" \| "claude-haiku-4-5-20251001" \| "claude-opus-4-6" \| "claude-3-haiku-20240307" \| "Qwen/Qwen2.5-72B-Instruct-Turbo" \| "nvidia/llama-3.1-nemotron-70b-instruct" \| "meta-llama/Llama-3.3-70B-Instruct-Turbo" \| "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo" \| "meta-llama/Llama-3.2-3B-Instruct-Turbo" \| "llama-3.3-70b-versatile" \| "llama-3.1-8b-instant" \| "llama3.3" \| "llama3.2" \| "llama3" \| "llama3.1:405b" \| "dolphin-mistral:latest" \| "openai/gpt-oss-120b" \| "openai/gpt-oss-20b" \| "google/gemini-2.5-pro-preview-03-25" \| "google/gemini-3-pro-preview" \| "google/gemini-2.5-flash" \| "google/gemini-2.0-flash-001" \| "google/gemini-2.5-flash-lite-preview-06-17" \| "google/gemini-2.0-flash-lite-001" \| "mistralai/mistral-nemo" \| "cohere/command-r-08-2024" \| "cohere/command-r-plus-08-2024" \| "deepseek/deepseek-chat" \| "deepseek/deepseek-r1-0528" \| "perplexity/sonar" \| "perplexity/sonar-pro" \| "perplexity/sonar-deep-research" \| "nousresearch/hermes-3-llama-3.1-405b" \| "nousresearch/hermes-3-llama-3.1-70b" \| "amazon/nova-lite-v1" \| "amazon/nova-micro-v1" \| "amazon/nova-pro-v1" \| "microsoft/wizardlm-2-8x22b" \| "gryphe/mythomax-l2-13b" \| "meta-llama/llama-4-scout" \| "meta-llama/llama-4-maverick" \| "x-ai/grok-4" \| "x-ai/grok-4-fast" \| "x-ai/grok-4.1-fast" \| "x-ai/grok-code-fast-1" \| "moonshotai/kimi-k2" \| "qwen/qwen3-235b-a22b-thinking-2507" \| "qwen/qwen3-coder" \| "Llama-4-Scout-17B-16E-Instruct-FP8" \| "Llama-4-Maverick-17B-128E-Instruct-FP8" \| "Llama-3.3-8B-Instruct" \| "Llama-3.3-70B-Instruct" \| "v0-1.5-md" \| "v0-1.5-lg" \| "v0-1.0-md" | No |
 | multiple_tool_calls | Whether to allow multiple tool calls in a single response. | bool | No |
 | sys_prompt | The system prompt to provide additional context to the model. | str | No |
 | conversation_history | The conversation history to provide context for the prompt. | List[Dict[str, Any]] | No |
--- a/docs/platform/getting-started.md
+++ b/docs/platform/getting-started.md
@@ -218,6 +218,17 @@ If you initially installed Docker with Hyper-V, you **don’t need to reinstall*

 For more details, refer to [Docker's official documentation](https://docs.docker.com/desktop/windows/wsl/).

+### ⚠️ Podman Not Supported
+
+AutoGPT requires **Docker** (Docker Desktop or Docker Engine). **Podman and podman-compose are not supported** and may cause path resolution issues, particularly on Windows.
+
+If you see errors like:
+```text
+Error: the specified Containerfile or Dockerfile does not exist, ..\..\autogpt_platform\backend\Dockerfile
+```
+
+This indicates you're using Podman instead of Docker. Please install [Docker Desktop](https://docs.docker.com/desktop/) and use `docker compose` instead of `podman-compose`.
+

 ## Development
Author	SHA1	Message	Date
Bently	cb08168553	Merge branch 'dev' into chore/remove-deprecated-openai-models	2026-02-23 16:43:08 +00:00
Bently	ef42b17e3b	docs: add Podman compatibility warning (#12120 ) ## Summary Adds a warning to the Getting Started docs clarifying that Podman and podman-compose are not supported. ## Problem Users on Windows using `podman-compose` instead of Docker get errors like: ``` Error: the specified Containerfile or Dockerfile does not exist, ..\..\autogpt_platform\backend\Dockerfile ``` This is because Podman handles relative paths differently than Docker, causing incorrect path resolution on Windows. ## Solution - Added a clear warning section after the Windows WSL 2 notes - Explains the error users might see - Directs them to install Docker Desktop instead Closes #11358 <!-- greptile_comment --> <details><summary><h3>Greptile Summary</h3></summary> Adds a "Podman Not Supported" warning section to the Getting Started documentation, placed after the Windows/WSL 2 installation notes. The section clarifies that Docker is required, shows the typical error message users encounter when using Podman, and directs them to install Docker Desktop instead. This addresses issue #11358 where Windows users using `podman-compose` hit path resolution errors. - Adds `### ⚠️ Podman Not Supported` section under Manual Setup, after Windows Installation Note - Includes the specific error message users see with Podman for easy identification - Links to Docker Desktop installation docs as the recommended solution - Formatting is consistent with existing sections in the document (emoji headings, code blocks for errors) </details> <details><summary><h3>Confidence Score: 5/5</h3></summary> - This PR is safe to merge — it only adds a documentation warning section with no code changes. - The change is a small, well-written documentation addition that adds a Podman compatibility warning. It touches only one markdown file, introduces no code changes, and is consistent with the existing document structure and style. No issues were found. - No files require special attention. </details> <details><summary><h3>Flowchart</h3></summary> ```mermaid flowchart TD A[User wants to run AutoGPT] --> B{Which container runtime?} B -->\|Docker / Docker Desktop\| C[docker compose up -d --build] C --> D[AutoGPT starts successfully] B -->\|Podman / podman-compose\| E[podman-compose up -d --build] E --> F[Error: Containerfile or Dockerfile does not exist] F --> G[New warning section directs user to install Docker Desktop] G --> C ``` </details> <sub>Last reviewed commit: 23ea6bd</sub> <!-- greptile_other_comments_section --> <!-- /greptile_comment -->	2026-02-23 15:19:24 +00:00
Ubbe	a18ffd0b21	fix(frontend/copilot): always-visible credentials, inputs, and login prompts (#12194 ) Credentials, inputs, and login prompts in copilot tool outputs were hidden inside collapsible accordions — users could accidentally collapse them, hiding blocking actionable UI. This PR extracts all blocking requirements out of accordions so they're always visible. ### Changes 🏗️ - RunAgent & RunBlock: Extract `SetupRequirementsCard` (credentials picker) out of `ToolAccordion` — renders standalone, always visible - RunAgent: Also extract `AgentDetailsCard` (inputs needed) and `need_login` message out of accordion - SetupRequirementsCard (RunBlock): Input form always visible (removed toggle button and animation), unified "Proceed" button disabled until credentials + inputs are satisfied - SetupRequirementsCard (RunAgent): "Proceed" button disabled until all credentials are selected - Both cards: Added titled box with border for credentials section ("Block credentials" / "Agent credentials"), matching the existing inputs box pattern - CredentialsFlatView: "Add" button uses `variant="primary"` when user has no credentials (was `secondary`) - Styleguide: Added mock `CredentialsProvidersContext` with two scenarios: - No credentials → shows "add new" flow - Has credentials → shows selection list with existing accounts - CreateAgent & EditAgent: Picked up user-initiated styling refinements ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: - [x] `pnpm format && pnpm lint && pnpm types` all pass - [ ] Visit `/copilot/styleguide` and verify: - [ ] "Setup requirements — no credentials" shows add-credential button (primary variant) - [ ] "Setup requirements — has credentials" shows credential selection dropdown - [ ] Both RunAgent and RunBlock setup requirements render outside accordion - [ ] Trigger a copilot agent run that requires credentials — credential picker always visible - [ ] Trigger a copilot block run that requires credentials + inputs — both sections visible, "Proceed" disabled until ready - [ ] Trigger a copilot agent run that returns "agent details" — card renders outside accordion - [ ] Verify other output types (execution_started, error) still render inside accordions 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>	2026-02-23 16:39:21 +07:00
Otto	e40c8c70ce	fix(copilot): collision detection, session locking, and sync for concurrent message saves (#12177 ) Requested by @majdyz Concurrent writers (incremental streaming saves from PR #12173 and long-running tool callbacks) can race to persist messages with the same `(sessionId, sequence)` pair, causing unique constraint violations on `ChatMessage`. Root cause: The streaming loop tracks `saved_msg_count` in-memory, but the long-running tool callback (`_build_long_running_callback`) also appends messages and calls `upsert_chat_session` independently — without coordinating sequence numbers. When the streaming loop does its next incremental save with the stale `saved_msg_count`, it tries to insert at a sequence that already exists. Fix: Multi-layered defense-in-depth approach: 1. Collision detection with retry (db.py): `add_chat_messages_batch` uses `create_many()` in a transaction. On `UniqueViolationError`, queries `MAX(sequence)+1` from DB and retries with the correct offset (max 5 attempts). 2. Robust sequence tracking (db.py): `get_next_sequence()` uses indexed `find_first` with `order={"sequence": "desc"}` for O(1) MAX lookup, immune to deleted messages. 3. Session-based counter (model.py): Added `saved_message_count` field to `ChatSession`. `upsert_chat_session` returns the session with updated count, eliminating tuple returns throughout the codebase. 4. MessageCounter dataclass (sdk/service.py): Replaced list[int] mutable reference pattern with a clean `MessageCounter` dataclass for shared state between streaming loop and long-running callbacks. 5. Session locking (sdk/service.py): Prevent concurrent streams on the same session using Redis `SET NX EX` distributed locks with TTL refresh on heartbeats (config.stream_ttl = 3600s). 6. Atomic operations (db.py): Single timestamp for all messages and session update in batch operations for consistency. Parallel queries with `asyncio.gather` for lower latency. 7. Config-based TTL (sdk/service.py, config.py): Consolidated all TTL constants to use `config.stream_ttl` (3600s) with lock refresh on heartbeats. ### Key implementation details - create_many: Uses `sessionId` directly (not nested `Session.connect`) as `create_many` doesn't support nested creates - Type narrowing: Added explicit `assert session is not None` statements for pyright type checking in async contexts - Parallel operations: Use `asyncio.gather` for independent DB operations (create_many + session update) - Single timestamp: All messages in a batch share the same `createdAt` timestamp for atomicity ### Changes - `backend/copilot/db.py`: Collision detection with `create_many` + retry, indexed sequence lookup, single timestamp, parallel queries - `backend/copilot/model.py`: Added `saved_message_count` field, simplified return types - `backend/copilot/sdk/service.py`: MessageCounter dataclass, session locking with refresh, config-based TTL, type narrowing - `backend/copilot/service.py`: Updated all callers to handle new return types - `backend/copilot/config.py`: Increased long_running_operation_ttl to 3600s with clarified docstring - `backend/copilot/*_test.py`: Tests updated for new signatures --------- Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>	2026-02-20 15:05:03 +00:00
Zamil Majdy	9cdcd6793f	fix(copilot): remove stream timeout, add error propagation to frontend (#12175 ) ## Summary Fixes critical reliability issues where long-running copilot sessions were forcibly terminated and failures showed no error messages to users. ## Issues Fixed 1. Silent failures: Tasks failed but frontend showed "stopped" with zero explanation 2. Premature timeout: Sessions auto-expired after 5 minutes even when actively running ## Changes ### Error propagation to frontend - Add `error_message` parameter to `mark_task_completed()` - When `status="failed"`, publish `StreamError` before `StreamFinish` so frontend displays reason - Update all failure callers with specific error messages: - Session not found: `"Session {id} not found"` - Tool setup failed: `"Failed to setup tool {name}: {error}"` - Task cancelled: `"Task was cancelled"` ### Remove stream timeout - Delete `stream_timeout` config (was 300s/5min) - Remove auto-expiry logic in `get_active_task_for_session()` - Sessions now run indefinitely — user controls stopping via UI ## Why Auto-expiry was broken: - Used `created_at` (task start) not last activity - SDK sessions with multiple LLM calls + subagent Tasks easily run 20-30+ minutes - A task publishing chunks every second still got killed at 5min mark - Hard timeout is inappropriate for long-running AI agents Error propagation was missing: - `mark_task_completed(status="failed")` only sent `StreamFinish` - No `StreamError` event = frontend had no message to show user - Backend logs showed errors but user saw nothing ## Test Plan - [x] Formatter, linter, type-check pass - [ ] Start a copilot session with Task tool (spawns subagent) - [ ] Verify session runs beyond 5 minutes without auto-expiry - [ ] Cancel a running session → frontend shows "Task was cancelled" error - [ ] Trigger a tool setup failure → frontend shows error message - [ ] Session continues running until user clicks stop or task completes ## Files Changed - `backend/copilot/config.py` — removed `stream_timeout` - `backend/copilot/stream_registry.py` — removed auto-expiry, added error propagation - `backend/copilot/service.py` — error messages for 2 failure paths - `backend/copilot/executor/processor.py` — error message for cancellation	2026-02-20 09:16:22 +00:00
Bently	ec4ae7083e	Merge branch 'dev' into chore/remove-deprecated-openai-models	2026-02-19 17:49:01 +00:00
Bently	682f8b5752	Merge branch 'dev' into chore/remove-deprecated-openai-models	2026-02-17 10:00:53 +00:00
Bentlybro	4b3611ca43	add migration and docs update for deprecated models - Add migration to update existing graphs using gpt-4-turbo -> gpt-4o - Add migration to update existing graphs using gpt-3.5-turbo -> gpt-4o-mini - Update llm.md docs to remove deprecated models from model lists	2026-02-16 12:03:59 +00:00
Bentlybro	cd6271b787	chore(backend): remove deprecated OpenAI GPT-4-turbo and GPT-3.5-turbo models Remove deprecated OpenAI models that are being sunset in 2026: - GPT-4-turbo (shutdown: March 26, 2026) - GPT-3.5-turbo (shutdown: September 28, 2026) Users should migrate to the newer GPT-4.1, GPT-4o, or GPT-5 model families which are already available in the platform. Reference: https://platform.openai.com/docs/deprecations	2026-02-16 11:58:11 +00:00