Type-hinted async endpoints with auto validation and docs—the default for ML APIs.
A web framework where the function signature IS the API contract — types give you validation, docs and editor support for free.
It's the default way to put a Python model behind an HTTP endpoint, and it's async-native, which matters for LLM calls.
FastAPI is an async Python web framework where you declare endpoints ('path operations') as type-hinted functions. From the hints it validates and parses requests via Pydantic and auto-generates OpenAPI/Swagger docs. Depends() provides dependency injection, and it runs on ASGI/uvicorn for concurrent I/O—making it the default choice for serving ML models.
FastAPI builds a web API from type hints. You write a path operation—an async def decorated with @app.post—and annotate its parameters, using a Pydantic model for the body. FastAPI then validates every request automatically, returns a 422 on bad input, and generates interactive OpenAPI docs for free. Depends() injects shared resources like a DB session or a loaded model, and because it's ASGI-based on uvicorn it handles I/O concurrently. That combination of speed, typing, and free docs is why it's the go-to for ML model serving.
Learn FastAPI in 3 Minutes | Python FastAPI Tutorial For Beginners (Hands-on Tutorials) — LimeGuru, 3:53