claude-code-router/CLAUDE.md

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Commands

• Build the project:

  npm run build
  

• Start the router server:

  ccr start
  

• Stop the router server:

  ccr stop
  

• Check the server status:

  ccr status
  

• Run Claude Code through the router:

  ccr code "<your prompt>"
  

• Release a new version:

  npm run release
  

Architecture

This project is a TypeScript-based router for Claude Code requests. It allows routing requests to different large language models (LLMs) from various providers based on custom rules.

• Entry Point: The main command-line interface logic is in src/cli.ts. It handles parsing commands like start, stop, and code.
• Server: The ccr start command launches a server that listens for requests from Claude Code. The server logic is initiated from src/index.ts.
• Configuration: The router is configured via a JSON file located at ~/.claude-code-router/config.json. This file defines API providers, routing rules, and custom transformers. An example can be found in config.example.json.
• Routing: The core routing logic determines which LLM provider and model to use for a given request. It supports default routes for different scenarios (default, background, think, longContext, webSearch) and can be extended with a custom JavaScript router file. The router logic is likely in src/utils/router.ts.
• Providers and Transformers: The application supports multiple LLM providers. Transformers adapt the request and response formats for different provider APIs.
• Claude Code Integration: When a user runs ccr code, the command is forwarded to the running router service. The service then processes the request, applies routing rules, and sends it to the configured LLM. If the service isn't running, ccr code will attempt to start it automatically.
• Dependencies: The project is built with esbuild. It has a key local dependency @musistudio/llms, which probably contains the core logic for interacting with different LLM APIs.
• @musistudio/llms is implemented based on fastify and exposes fastify's hook and middleware interfaces, allowing direct use of server.addHook.
• 无论如何你都不能自动提交git