python-gunicorn-uvicorn VS uvicorn

As a note there is also a gunicorn uvicorn image, but in general you're better of just using uvicorn and launching multiple images rather than having gunicorn and uvicorn in one container.

The multi-py project has a cross platform gunicorn container that works with Intel and Arm out of the box.

https://github.com/multi-py/python-gunicorn

There's also a uvicorn one there for people who want the async features.

https://github.com/multi-py/python-uvicorn

And a container that combines both (although it's often better to just use uvicorn and add more containers to your API to scale up).

https://github.com/multi-py/python-gunicorn-uvicorn

FastAPI & Uvicorn

This tells Heroku to run uvicorn, which is a web server implementation in Python.

FastAPI uses Uvicorn, an ASGI (Asynchronous Server Gateway Interface) web server implementation for Python.

Now, let’s run our FastAPI application using Uvicorn: uvicorn main:app --reload

Uvicorn + Starlette 8k requests/s

I switched to Hypercorn because Uvicorn currently supports HTTP/1.1 and WebSockets as mentioned at https://www.uvicorn.org

This will set up Chroma and run it as a server with uvicorn, making port 8000 accessible outside the net docker network. The command also mounts a persistent docker volume for Chroma's database, found at chroma/chroma from your project's root.

There's an open discussion under the Uvicorn repository and we prepared a repository for Reproduction GitHub Repo

FastAPI is a popular Python Web framework that developers use to create RESTful APIs. It is based on Pydantic and Python-type hints that assist in the serialization, deserialization, and validation of data. In this tutorial, we will use FastAPI to create a simple "Hello World" application. We test and run the application locally. FastAPI requires a ASGI server to run the application production such as Uvicorn.

- [3] https://github.com/encode/uvicorn/issues/527