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FastAPI Inference API

This is a simple FastAPI application with a single inference endpoint. The application is containerized using Docker.

Table of Contents

  1. Installation
  2. Usage
  3. API Endpoints

Installation

First, you need to install Docker. The installation process varies depending on your operating system. You can find the detailed instructions on the official Docker documentation.

Once Docker is installed, navigate to the directory containing the repository. You can then build your Docker image using the following command:

docker build -f environments/Dockerfile.api -t my-fastapi-app .

Replace my-fastapi-app with the name you want for your Docker image.

Usage

After the Docker image is built, you can run your FastAPI application in a Docker container using the following command:

docker run -p 8000:8000 my-fastapi-app

This command will start a Docker container with your FastAPI application, and the application will be available at http://localhost/inference.

Remember to replace my-fastapi-app with the name you used for your Docker image.

Alternatively, you can build the regular Docker image from the environments/Dockerfile and run the FastAPI application using the following commands:

poetry install --with api
uvicorn api.api:app

Test the Inference Endpoint

To use the inference endpoint, you can send a POST request with an base64-encoded image file. We prepared the script api_sample_request.py to help you test the endpoint. You can run the script using the following command:

bash api_sample_request.py path/to/image.ext

For example, you can run the following command to test the endpoint with the images from our README in imgs/ catalogue:

bash api_sample_request.py imgs/4Q91mZx8dyJfTkuBOokf--4--ojjjo.jpg

API Endpoints

The application has the following endpoint:

  • POST /inference: Accepts a JSON body and returns it back in the response.