Great—but then one ought to be able to performantly use that same runner equally well from FastAPI, Starlette, Quart (ASGI port of Flask), or any other ASGI framework. You’ve decided to build a convenient integration with Starlette instead of the others, but it’s weird to frame this as an argument that other frameworks are ill suited for this domain.
That’s is true, it would be more accurate to say FastAPI (or any ASGI) framework along is not enough for ML model serving, you need batching and runner for performance. And some additional Ml focused features for integration with other ML tools
