Visual Studio Code's Copilot Chat architecture enables extension authors to integrate with the GitHub Copilot Chat experience. A chat extension is a VS Code extension that uses the Chat extension API by contributing a Chat participant. Chat participants are domain experts that can answer user queries within a specific domain.

The Language Model API enables you to use the Language Model and integrate AI-powered features and natural language processing in your Visual Studio Code extension.

When an extension uses the Chat or the Language Model API, we call it a GitHub Copilot Extension, since GitHub Copilot is the provider of the Chat and the Language Model experience.

This GitHub Copilot Extension sample shows:

• How to contribute a simple chat participant to the GitHub Copilot Chat view. (@cat, simple.ts)
• How to use the Language Model API to request access to the Language Model.
• How to use the @vscode/chat-extension-utils library to easily create a chat participant that uses tools. (@catTools, chatUtilsSample.ts)
• How to contribute a more sophisticated chat participant that uses the LanguageModelTool API to contribute and invoke tools. (@tool, toolParticipant.ts)

Documentation can be found here:

• https://code.visualstudio.com/api/extension-guides/chat
• https://code.visualstudio.com/api/extension-guides/language-model

• Run npm install in terminal to install dependencies
• Run the Run Extension target in the Debug View. This will:
  • Start a task npm: watch to compile the code
  • Run the extension in a new VS Code window
  • You will see the @cat chat participant show in the GitHub Copilot Chat view

This sample shows two different ways to build a chat participant in VS Code:

See simple.ts for an example of a simple chat participant that makes requests and responds to user queries. It shows how you can create chat participants with or without the @vscode/prompt-tsx library.

See toolParticipant.ts for an example of a chat participant that invokes tools, either dynamically or using the toolReferences that are attached to the request. This is a more advanced example that shows how you can use the @vscode/prompt-tsx library to implement the LLM tool calling flow and tries to implement all the features of the chat API.