FastAPI Lab

This is a demo project used to show how to serve ML models with FastAPI in the 2021 edition of the Software Engineering for AI-enabled Systems course (University of Bari, Italy - Dept. of Computer Science).

The scripts in this project are freely inspired by the Made with ML tutorial: "APIs for Machine Learning".

Project setup

Install all project requirements with pip:

pip install -r requirements.txt

Launch the server

We'll be using Uvicorn, a fast ASGI server (it can run asynchronous code in a single process) to launch our application. Use the following command to start the server:

uvicorn app.api:app \
    --host 0.0.0.0 \
    --port 5000 \
    --reload \
    --reload-dir app \
    --reload-dir models

In detail:

• uvicorn app.api:app is the location of app (app directory > api.py script > app object);
• --reload makes the server reload every time we update;
• --reload-dir app makes it only reload on updates to the app/ directory;
• --reload-dir models makes it also reload on updates to the models/ directory;

Observation. If we want to manage multiple uvicorn workers to enable parallelism in our application, we can use Gunicorn in conjunction with Uvicorn.

Try the API

We can now test that the application is working. These are some of the possibilities:

• visit localhost:5000

• use curl

  curl -X GET http://localhost:5000/

• access the API programmatically, e.g.:

  import json
  import requests
  
  response = requests.get("http://localhost:5000/")
  print (json.loads(response.text))

• use an external tool like Postman, which lets you execute and manage tests that can be saved and shared with others.

Accessing the documentation

We can access the Swagger UI for our documentation by going to the /docs endpoint. Alternatively, the documentation generated via Redoc is accessible at the /redoc endpoint.

Requests to try

Virginica (2)

{
  "sepal_length": 6.4,
  "sepal_width": 2.8,
  "petal_length": 5.6,
  "petal_width": 2.1
}

Setosa (0)

{
  "sepal_length": 5.7,
  "sepal_width": 3.8,
  "petal_length": 1.7,
  "petal_width": 0.3
}