Async FastAPI
Building high-concurrency Python APIs with FastAPI and asyncio.
Definition
Async FastAPI refers to building FastAPI route handlers with `async def` instead of `def`, allowing Python's event loop to handle other requests while waiting for I/O (database queries, HTTP calls to LLM APIs, Redis operations). A single async worker can handle hundreds of concurrent connections.
Why it matters for AI APIs
LLM API calls take 1–30 seconds. If your FastAPI app uses sync handlers, each pending LLM call blocks a thread, limiting your server to a handful of concurrent requests. Async allows a single process to handle thousands of concurrent LLM requests without extra servers.
In FastAPI AI Kit
Every route handler in the kit is `async def`. Database access uses SQLAlchemy 2.0 async. LLM calls use async HTTP clients (httpx). Redis calls use aioredis. Background tasks use Celery, not threads. The result is a server that handles burst LLM traffic without resource exhaustion.