Building an Open AI plugin with Codespaces

☁️ To deploy your app on Azure using Azure Developer CLI and Container Apps, see the demo-azd branch.

This is a sample repo for developing OpenAI plugin using the FastAPI framework. There are two main parts of the repo:

• Code to help setup development environment for FastAPI framework
• Code for the FastAPI app

📦 Code to help setup development environment

Create a Codespaces by clicking <> Code -> Codespaces -> Create codespaces on {branch}, and a containerized development environment will be set up for you on the cloud based on the contents of the following files.

.devcontainer

The .devcontainer folder contains files for defining a containerized development environment, specific to building this FastAPI app. It's set up in a way that makes it easy for you to use with GitHub Codespaces as well: launch a Codespace using this template, and you're ready to start developing! Learn more about devcontainers here.

.vscode

The .vscode folder contains:

• json.code-snippets file that helps to quickly write the manifest file for the OpenAI plugin. (✨ Tip: Type manifest-openai, press enter to accept the template, and tab through the fields to quickly generate the manifest)
• settings.json file that helps to validate the manifest file (ai-plugin.json) against this schema.
• launch.json file that helps to customize Run and Debug.

💻 Code for the FastAPI app

If you have access to GitHub Copilot, try it out to help you write code faster. To test the app, run uvicorn main:app in the integrated terminal, or press F5, and debug CRUD operations at .../docs.

• main.py is the code for the API plugin. (✨ Tip: Generate the code using Copilot. The following is an example prompt to use in the Copilot chat view.)

  Write a simple TODO app using FastAPI, that lets the user add TODOs, list their TODOs, list specific TODOs, and delete TODOs, ensuring that the app stores todo_id for each todo item. 
  
  Assume that a docker container is running for Redis, running and accessible at host "redis" and port 6379 as specified in the docker-compose.yml file. Make use of the Redis container for persisting data from the TODO app.
  
  Include a __main__ section which will run this app using uvicorn. The Python module where I save this code will be called main.py.
  
  Mount static files in the .well-known directory to the path /.well-known, which should at minimum contain ai-plugin.json that serves (as JSON).

• openapi.yaml is a specification that dictates how to define the schema of the API.
• ai-plugin.json is a JSON manifest file that defines relevant metadata for the plugin. Learn more in the OpenAI docs.

💬 Register the app on ChatGPT

• Go to PORT and set visibility of port 8000 to public
• Copy the link and paste it on ChatGPT plugin