Moonshot
Moonshot is a simple and modular tool developed by the AI Verify Foundation to evaluate and red-team any LLM (Large Language Model) application. It combines benchmarking and red-teaming to assist AI developers, compliance teams, and AI system owners in assessing the performance and safety of LLMs.
Key Features
- Access to AI Systems: Easily connect to popular LLMs from providers like OpenAI, Anthropic, and HuggingFace.
- Benchmarking: Utilize a variety of benchmarks to measure LLM performance in capability, quality, and trust & safety.
- Red Teaming: Conduct adversarial testing to identify vulnerabilities in AI systems with user-friendly interfaces.
- Customizability: Create custom model connectors, cookbooks, and recipes to tailor evaluations to specific needs.
- Automated Testing: Leverage automated red-teaming tools to scale testing efforts efficiently.
Benefits
- Comprehensive Evaluation: Moonshot provides a holistic approach to testing LLM applications, ensuring thorough assessments.
- User-Friendly Interfaces: With both a Web UI and an interactive CLI, users can easily navigate and utilize the tool.
- Community-Driven: Collaborate with a community of developers and researchers to enhance the tool's capabilities and benchmarks.
Highlights
- Developed by the AI Verify Foundation, Moonshot is one of the first tools to integrate benchmarking and red-teaming for LLMs.
- Supports Python 3.11 and offers installation through various methods, including pip and Git.
- Licensed under Apache Software License 2.0, promoting open-source collaboration.