grawl 0.1.0

Generate repository documentation for LLMs

Grawl

A CLI tool that clones GitHub repositories and generates comprehensive documentation for LLMs using OpenAI's agents framework.

Features

• Clone GitHub repositories to a local directory
• Analyze repository structure and content
• Generate comprehensive documentation optimized for LLMs
• Identify important files and components
• Filter out binary and irrelevant files

Installation

From PyPI (Recommended)

pip install grawl

From Source

# Clone the repository
git clone https://github.com/kacppian/grawl.git
cd grawl

# Create a virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install in development mode
pip install -e .

Configuration

Before using Grawl, you need to set your OpenAI API key:

export OPENAI_API_KEY='your-api-key'

On Windows:

set OPENAI_API_KEY=your-api-key

Usage

Command Line Interface

# Get help
grawl --help

# Generate documentation for a GitHub repository
grawl generate https://github.com/username/repository

# Specify a custom output path for documentation
grawl generate https://github.com/username/repository --output custom_path.txt

How it works

Grawl uses OpenAI's agents framework to:

1. Clone the specified GitHub repository to .grawl/repositories/<repo_name>
2. Analyze the repository structure and content
3. Generate comprehensive documentation in .grawl/generated/<repo_name>.txt

The documentation includes:

• Repository overview
• Architecture and components
• Key functionality
• API documentation
• Dependencies
• Usage examples
• Development guidelines

Development

Setup Development Environment

# Clone the repository
git clone https://github.com/kacppian/grawl.git
cd grawl

# Create a virtual environment
python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

# Install development dependencies
pip install -e ".[dev]"

Running Tests

pytest

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Requirements

• Python 3.10+
• OpenAI API key