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https://github.com/aiverify-foundation/moonshot

Moonshot - A simple and modular tool to evaluate and red-team any LLM application.
https://github.com/aiverify-foundation/moonshot

benchmarking evaluation-framework llm red-teaming trustworthy-ai

Last synced: 2 months ago
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Moonshot - A simple and modular tool to evaluate and red-team any LLM application.

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README 

          



![Moonshot Logo](https://github.com/aiverify-foundation/moonshot/raw/main/misc/aiverify-moonshot-logo.png)



**Version 0.7.6**



A simple and modular tool to evaluate any LLM-based AI systems.



[![Python 3.11](https://img.shields.io/badge/python-3.11-green)](https://www.python.org/downloads/release/python-3111/)






## 🎯 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.



## 🚀 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:

- Benchmark Tests: 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 IMDA's Starter Kit for LLM-based App Testing.

- Red Team Attacks: Proactively identify vulnerabilities and potential misuse scenarios in your LLM applications through streamlined adversarial prompting.



## 🔑 Key Features



- User-friendly Interfaces: Interact with Moonshot via an intuitive Web UI for visual insights, and an interactive Command Line Interface (CLI) for quick operations.

- Comprehensive Benchmarking:

  - [View list of available datasets available](https://aiverify-foundation.github.io/moonshot/resources/datasets/)

  - Test for Performance (e.g., accuracy, BLEU)

  - Ensure Trust & Safety 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/)

- Powerful Red-Teaming:

  - [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.

- Customizable Recipes: 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/)

- Insightful Reporting: Use our HTML reports with interactive charts for clear visualization of test results, and download detailed raw JSON results for deeper programmatic analysis.

- Extensible & Modular: Designed for easy extension and integration with new LLM applications, benchmarks, and attack techniques.



# 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/)



## 💻 Let's Go!



This section will guide you through getting Moonshot up and running.



### ✅ Prerequisites

1. Python: [Version 3.11](https://www.python.org/downloads/) is required. 



2. Git Version Control: [Git](https://github.com/git-guides/install-git) is essential for cloning the repository.



3. (Optional) Virtual Environment: Highly recommended to manage dependencies.



    ```

    # Create a virtual environment

    python -m venv venv



    # Activate the virtual environment

    source venv/bin/activate

    ```

4. If you plan to install our Web UI, you will also need [Node.js version 20.11.1 LTS](https://nodejs.org/en/blog/release/v20.11.1) and above



### ⬇️ Installation



You can install Moonshot in various ways depending on your needs



1. Using `pip` (Recommended for most users)



```

# Install Project Moonshot's Python Library, which includes Moonshot's full functionalities (Library APIs, CLI and Web APIs)

pip install "aiverify-moonshot[all]"



# Clone and install test assets and Web UI

python -m moonshot -i moonshot-data -i moonshot-ui

```

⚠️ You will need to have test assets from [moonshot-data](https://github.com/aiverify-foundation/moonshot-data) before you can run any tests.



🖼️ If you plan to install our Web UI, you will also need [moonshot-ui](https://github.com/aiverify-foundation/moonshot-ui)



Check out our [Installation Guide](https://aiverify-foundation.github.io/moonshot/getting_started/quick_install/) for more details.



2. From Source Code (For developers and contributors)



```

# To install from source code (Full functionalities)

git clone git@github.com:aiverify-foundation/moonshot.git

cd moonshot

pip install -r requirements.txt

```

If you have installation issues, please take a look at the [Troubleshooting Guide](https://aiverify-foundation.github.io/moonshot/faq/).



Other installation options

Here's a summary of other installation commands available:



```

# To install Moonshot library APIs only

pip install aiverify-moonshot



# To install Moonshot library APIs and Web APIs only

pip install "aiverify-moonshot[web-api]"



# To install Moonshot library APIs and CLI only

pip install "aiverify-moonshot[cli]"

```

Check out our [Installation Guide](https://aiverify-foundation.github.io/moonshot/getting_started/quick_install/) for more details.



### 🏃‍♀️ Run Moonshot



#### Running the Web UI

```

python -m moonshot web

```

Open [http://localhost:3000/](http://localhost:3000/) in a browser and you should see this homepage:



![Moonshot UI Home](https://github.com/aiverify-foundation/moonshot/raw/main/misc/ui-homepage.png)



Refer to this [guide](https://aiverify-foundation.github.io/moonshot/user_guide/web_ui/moonshot_interface/homepage/) to discover the rich features available in Moonshot Web UI



#### Running the Interactive CLI

```

python -m moonshot cli interactive

```

![Moonshot cli](https://github.com/aiverify-foundation/moonshot/raw/main/misc/cli-homepage.png)



Refer to this [Command List](https://aiverify-foundation.github.io/moonshot/user_guide/cli/cli_command_list/) to discover the list of CLI commands for Moonshot



# 📚 Documentation & User Guides



For detailed information on configuring, using, and extending Moonshot, please refer to our comprehensive documentation:



#### Guides for Moonshot Web UI

- [Getting Started with Moonshot Web UI](https://aiverify-foundation.github.io/moonshot/user_guide/web_ui/web_ui_guide/)

- [Creating Your Custom Cookbook via Moonshot Web UI](https://aiverify-foundation.github.io/moonshot/tutorial/web-ui/create_cookbook/)

- [Creating Your Custom Connector Endpoint via Moonshot Web UI](https://aiverify-foundation.github.io/moonshot/tutorial/web-ui/create_endpoint/)

- [Running Benchmark Test on Moonshot Web UI](https://aiverify-foundation.github.io/moonshot/getting_started/first_test/)

- [Running Red Teaming on Moonshot Web UI](https://aiverify-foundation.github.io/moonshot/tutorial/web-ui/redteam/)



#### Guides for Moonshot Interactive CLI

- [Getting Started with Moonshot Interactive CLI](https://aiverify-foundation.github.io/moonshot/user_guide/cli/connecting_endpoints/)

- [Creating Your Custom Benchmark Tests for Your RAG Apps via Moonshot Interactive CLI](https://aiverify-foundation.github.io/moonshot/tutorial/cli/create_benchmark_tests/)

- [Creating Your Custom Connector Endpoint via Moonshot Interactive CLI](https://aiverify-foundation.github.io/moonshot/tutorial/cli/create_endpoint/)

- [Running Benchmark Test on Moonshot Interactive CLI](https://aiverify-foundation.github.io/moonshot/tutorial/cli/run_benchmark_tests/)

- [Running Red Teaming on Moonshot Interactive CLI](https://aiverify-foundation.github.io/moonshot/tutorial/cli/run_red_teaming/)



#### For Users Interested in trying Out Moonshot using Jupyter Notebook

- [Moonshot Library Python Notebook Examples](https://github.com/aiverify-foundation/moonshot/tree/main/examples/jupyter-notebook)



#### 



## 🤝 Contribution



Moonshot is an open-source project, and we welcome contributions from the community! Whether fixing a bug, adding a new feature, improving documentation, or suggesting an enhancement, your efforts are highly valued.



Please refer to our [Contributor Guide](https://aiverify-foundation.github.io/moonshot/contributing/) for details on how to get started.



## ✨ Project Status



Moonshot is currently in beta. We are actively developing new features, improving existing ones, and enhancing stability. We encourage you to try it out and provide feedback!



## 📜 License



Moonshot is released under the [Apache Software License 2.0](https://www.apache.org/licenses/LICENSE-2.0.txt)