After building our standalone Python agent in Post #27, Post #28 wraps our reasoning loop inside an asynchronous FastAPI microservice with Server-Sent Events (SSE) streaming.
Why FastAPI for AI Agents?
FastAPI leverages native ASGI async/await to prevent thread blocking during slow I/O waits (such as GitHub REST API calls or vector database queries). Because FastAPI is built natively around Pydantic, your agent tool input schemas double as FastAPI request validation bodies.
Streaming SSE via StreamingResponse
Using Python generator functions (async def agent_event_stream()), you can yield custom W3C-compliant SSE frames (event: tool-start, event: text-delta, event: done) directly through FastAPI's StreamingResponse with media_type='text/event-stream' and anti-buffering headers.
Read the full tutorial with complete Python source code on my blog: https://zahidhasantonmoy.vercel.app/blog/fastapi-ai-agent-backend-streaming-python
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