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fix: prevent worker death during document upload by using run_coroutine_threadsafe (#21158)
* fix: prevent worker death during document upload by using run_coroutine_threadsafe Replace asyncio.run() with asyncio.run_coroutine_threadsafe() in save_docs_to_vector_db() to prevent uvicorn worker health check failures. The issue: asyncio.run() creates a new event loop and blocks the thread completely, preventing the worker from responding to health checks during long-running embedding operations (>5 seconds default timeout). The fix: Schedule the async embedding work on the main event loop using run_coroutine_threadsafe(). This keeps the main loop responsive to health check pings while the sync caller waits for the result. Changes: - main.py: Store main event loop reference in app.state.main_loop at startup - retrieval.py: Use run_coroutine_threadsafe() instead of asyncio.run() https://claude.ai/code/session_01UQSYvSTkXb57sFb7M85Kcw * add env var --------- Co-authored-by: Claude <noreply@anthropic.com>
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@@ -591,6 +591,10 @@ https://github.com/open-webui/open-webui
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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# Store reference to main event loop for sync->async calls (e.g., embedding generation)
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# This allows sync functions to schedule work on the main loop without blocking health checks
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app.state.main_loop = asyncio.get_running_loop()
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app.state.instance_id = INSTANCE_ID
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start_logger()
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@@ -1590,14 +1590,20 @@ def save_docs_to_vector_db(
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enable_async=request.app.state.config.ENABLE_ASYNC_EMBEDDING,
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)
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# Run async embedding in sync context
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embeddings = asyncio.run(
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# Run async embedding in sync context using the main event loop
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# This allows the main loop to stay responsive to health checks during long operations
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embedding_timeout_str = os.environ.get("RAG_EMBEDDING_TIMEOUT")
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embedding_timeout = int(embedding_timeout_str) if embedding_timeout_str else None
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future = asyncio.run_coroutine_threadsafe(
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embedding_function(
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list(map(lambda x: x.replace("\n", " "), texts)),
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prefix=RAG_EMBEDDING_CONTENT_PREFIX,
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user=user,
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)
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),
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request.app.state.main_loop,
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)
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embeddings = future.result(timeout=embedding_timeout)
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log.info(f"embeddings generated {len(embeddings)} for {len(texts)} items")
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items = [
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