CoDoc: AI-Powered Technical Wiki Code Documentation

This project is a continuation of The-Pocket/Tutorial-Codebase-Knowledge

🆕 Key Features of CoDoc

• AI-Powered Documentation Generation:
  • Automatically analyze codebases and generate comprehensive technical wiki documents.
• Customizable Output:
  • Define inclusions, exclusions, and language preferences for tailored documentation.
• Flexible Integration:
  • Supports any git repository or local directory for codebase analysis.
• OpenAI-Compatible Model Support:
  • Easily configure your own API endpoint and model (OpenAI, Azure, local, etc.) for AI processing.

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🚀 Getting Started

We are using uv as the package manager and virtual environment manager, but you can just use python, pip and venv if you prefer.

1. Clone this repository

Optionally create a virtual environment using uv venv and activate it

2. Install dependencies:

   uv pip install -r requirements.txt

3. Set up your LLM provider Edit utils/call_llm.py or set the following environment variables:

   OPENAI_API_KEY=your_api_key
   OPENAI_API_BASE=your_api_base
   OPENAI_MODEL=your_model
   

4. Generate codebase documentation:

   # Analyze a GitHub repository to generate documentation
   uv run main.py --repo https://github.com/username/repo
   
   # You can also specify additional options:
   uv run main.py --repo https://github.com/username/repo --include "*.py" "*.js" --exclude "tests/*" --max-size 50000
   
   # Or, analyze a local directory to generate documentation
   uv run main.py --dir /path/to/your/codebase --include "*.py" --exclude "*test*"
   
   # Or, generate documentation in Chinese
   uv run main.py --repo https://github.com/username/repo --language "Chinese"

   • --repo or --dir: Specify either a GitHub repo URL or a local directory path (required, mutually exclusive)
   • -n, --name: Project name (optional, derived from URL/directory if omitted)
   • -t, --token: GitHub token (or set GITHUB_TOKEN environment variable)
   • -o, --output: Output directory (default: ./output)
   • -i, --include: Files to include (e.g., "*.py" "*.js")
   • -e, --exclude: Files to exclude (e.g., "tests/*" "docs/*")
   • -s, --max-size: Maximum file size in bytes (default: 100KB)
   • --language: Language for the generated tutorial (default: "english")

The application will crawl the repository, analyze the codebase structure, generate technical wiki code documentation in the specified language, and save the output in the specified directory (default: ./output).

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🙏 Credits

• Original project: The-Pocket/Tutorial-Codebase-Knowledge