RepoMaster is an AI agent designed to transform GitHub repositories into an executable toolbox for autonomous task-solving. It targets developers and researchers seeking to leverage the vast open-source ecosystem for complex coding and real-world problems, offering an alternative to proprietary solutions by automating the discovery and integration of relevant code.

How It Works

RepoMaster operates by taking a natural language task description and orchestrating a multi-step AI-driven process. It first analyzes the task, then autonomously discovers relevant GitHub repositories and tools, and finally executes them intelligently to achieve the desired outcome. This approach aims to seamlessly integrate open-source projects into a cohesive workflow, enabling users to harness collective code intelligence.

Quick Start & Requirements

Installation involves cloning the repository and installing dependencies via pip:

git clone https://github.com/QuantaAlpha/RepoMaster.git
cd RepoMaster
pip install -r requirements.txt

Configuration requires setting API keys for primary AI providers (OpenAI required) and external services like Serper (for search) and Jina (for web extraction). Optional keys for other AI providers (Anthropic, DeepSeek, Gemini) can also be configured. The project can be launched via a web interface (python launcher.py --mode frontend) or a command-line interface (python launcher.py --mode backend --backend-mode unified). A comprehensive User Guide is available for advanced usage.

Highlighted Details

• Transforms GitHub repositories into an AI-powered toolbox for autonomous task execution.
• Demonstrates capabilities with a neural style transfer case study, showing autonomous tool discovery and execution.
• Part of a broader ecosystem including GitTaskBench (benchmark suite) and SE-Agent (self-evolution framework).
• Offers a YouTube demo showcasing the end-to-end autonomous execution process.

Maintenance & Community

RepoMaster is developed by QuantaAlpha, a team founded by academics from institutions including Tsinghua University and Peking University, focusing on agent research. Contributions are welcomed via bug reports and feature requests. Further details and contact information are available on their Team Homepage.

Licensing & Compatibility

The README does not explicitly state the project's license. Users should verify licensing terms before integration, especially for commercial or closed-source applications.

Limitations & Caveats

The project relies heavily on external API keys, which incur costs. Specific limitations regarding supported task types, performance benchmarks, or potential integration challenges with diverse repositories are not detailed in the README.