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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Moonshot - A simple and modular tool to evaluate and red-team any LLM application.
| Date | Stars |
|---|---|
| 2026-07-31 | 341 |
| 2026-08-11 | 345 |
| 2026-08-18 | 347 |
| 2026-08-19 | 347 |
| 2026-08-23 | 348 |
| 2026-08-30 | 347 |
| 2026-09-03 | 348 |
| 2026-09-05 | 348 |
| 2026-09-08 | 349 |
| 2026-09-09 | 349 |
| 2026-09-10 | 350 |
| 2026-09-13 | 351 |
| 2026-09-18 | 352 |
| 2026-09-20 | 352 |
Today
— stars today
This week
+1 stars this week
This month
+5 stars this month
Momentum
0.0
growth rate 0.29%/day
<div align="center">
**Version 0.7.6**
A simple and modular tool to evaluate any LLM-based AI systems.
[](https://www.python.org/downloads/release/python-3111/)
</div>
## 🎯 Motivation
Developed by the [AI Verify Foundation](https://aiverifyfoundation.sg/), [Moonshot](https://aiverifyfoundation.sg/project-moonshot/) is a tool to bring Benchmarking and Red-Teaming together to help AI developers, compliance teams evaluate LLM-based Apps and LLMs.
</br>
## 🚀 Why Moonshot
In the rapidly evolving landscape of Generative AI, ensuring safety, reliability, and performance of LLM applications is paramount. Moonshot addresses this critical need by providing a unified platform for:
- <b>Benchmark Tests:</b> Systematically test LLM Apps or LLMs across critical trust & safety risks using a wide array of open-source benchmark dataset and metrics, including guided workflows to implement <b>IMDA's Starter Kit for LLM-based App Testing</b>.
- <b>Red Team Attacks:</b> Proactively identify vulnerabilities and potential misuse scenarios in your LLM applications through streamlined adversarial prompting.
</br>
## 🔑 Key Features
- <b>User-friendly Interfaces:</b> Interact with Moonshot via an intuitive Web UI for visual insights, and an interactive Command Line Interface (CLI) for quick operations.
- <b>Comprehensive Benchmarking:</b>
- [View list of available datasets available](https://aiverify-foundation.github.io/moonshot/resources/datasets/)
- Test for <b>Performance</b> (e.g., accuracy, BLEU)
- Ensure <b>Trust & Safety</b> e.g., bias, toxicity, hallucination)
- Utilize built-in workflow to implement IMDA's Starter Kit for LLM-based App Testing. [View available pre-built Cookbooks](https://aiverify-foundation.github.io/moonshot/resources/cookbooks/)
- <b>Powerful Red-Teaming:</b>
- [View list of available attack modules](https://aiverify-foundation.github.io/moonshot/resources/attack_modules/)
- Simplify adversarial prompt generation using algorithmic strategies or generative LLM to uncover potential misuse.
- Leverage prompt templates, context strategies, and automated attack modules.
- <b>Customizable Recipes:</b> Build your own benchmark tests with custom datasets (input-target pairs), prompt templates (optional), evaluation metric, and grading scales. [View available pre-built Recipes](https://aiverify-foundation.github.io/moonshot/resources/recipes/)
- <b>Insightful Reporting:</b> Use our HTML reports with interactive charts for clear visualization of test results, and download detailed raw JSON results for deeper programmatic analysis.
- <b>Extensible & Modular:</b> Designed for easy extension and integration with new LLM applications, benchmarks, and attack techniques.
</br>
# Getting Started
Moonshot can be used through several interfaces:
- User-friendly Web UI - [Web UI User Guide](https://aiverify-foundation.github.io/moonshot/user_guide/web_ui/web_ui_guide/)
- Interactive Command Line Interface - [CLI User Guide](https://aiverify-foundation.github.io/moonshot/user_guide/cli/connecting_endpoints/)
- Seamless Integration into your MLOps workflow via Moonshot Library APIs or Moonshot Web APIs - [Notebook Examples](https://github.com/aiverify-foundation/moonshot/tree/main/examples/jupyter-notebook), [Web API Docs](https://aiverify-foundation.github.io/moonshot/api_reference/web_api_swagger/)
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## 💻 Let's Go!
This section will guide you through getting Moonshot up and running.
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### ✅ Prerequisites
1. <b>Python:</b> [Version 3.11](https://www.python.org/downloads/) is required.
2. <b>Git Version Control:</b> [Git](https://github.com/git-guides/install-git) is essential for cloning the repository.
3. <b>(Optional) Virtual Environment:</b> Highly recommended to manage dependencies.
```
# Create a virtual environmenExcerpt of 9,302 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:992df3e57aec3496, llm:Repository topics: benchmarking, evaluation-framework, llm, red-teaming, trustworthy-ai; description: 'Moonshot - A simple and modular tool to evaluate and red-team any LLM application.'
matched fp:992df3e57aec3496, llm:Repository topics: benchmarking, evaluation-framework, llm, red-teaming, trustworthy-ai; description: 'Moonshot - A simple and modular tool to evaluate and red-team any LLM application.'
matched fp:992df3e57aec3496, llm:Repository topics: benchmarking, evaluation-framework, llm, red-teaming, trustworthy-ai; description: 'Moonshot - A simple and modular tool to evaluate and red-team any LLM application.'