For notes on running a fork under windows see MyNote.MD.
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This project provides a graphical user interface (GUI) application for testing local Large Language Models (LLMs) within the context of Obsidian or similar note-taking and personal knowledge management systems.
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It aims to facilitate the evaluation of LLMs' performance on tasks relevant to knowledge management, note-taking, and productivity.
- Local LLM Integration: Connect to local LLM servers for privacy-focused, offline testing.
- Customizable Tests: Easily modify or add new test questions to suit your specific needs.
- Interactive GUI: Conduct tests and review results through a user-friendly interface.
- Performance Metrics: Track and analyze the performance of your LLM with built-in scoring and feedback mechanisms.
- Add a screenshot of the GUI to the README.
- Add a GIF of the GUI in action to the README.
- Add a section on how to contribute to the project.
- Add a section on how to add new test questions.
- Python 3.6 or higher.
- A local LLM server or access to an LLM API (e.g., OpenAI's GPT models).
- An environment capable of running PyQt6 applications.
- Clone the Repository:
git clone https://github.com/systemsculpt/obsidian_llm_testing
cd obsidian_llm_testing
- Set Up a Virtual Environment (optional but recommended):
python3 -m venv .venv
source .venv/bin/activate
- Install Dependencies:
pip install -r requirements.txt
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Edit the Configuration File: Modify
config.yaml
to set up your LLM server URL, API key (if needed), and other preferences like font size and window size. -
Prepare Your Test Questions: Edit
LLM_Test.md
to include your custom questions. Follow the format provided in the file for consistency.
- Launch the GUI application by running:
python main.py
- The GUI will start, and you can begin testing by following the on-screen instructions.
- Connect to Your LLM Server: Use the "Reload API Connection" button to connect to your LLM server.
- Generate Answers: Select a question and use the "Generate Answer" button to get responses from your LLM.
- Evaluate Responses: Mark answers as "Pass" or "Fail" based on their relevance and accuracy.
- Review Results: The application automatically calculates and displays performance metrics.
- Adding New Questions: You can add new questions directly to the
LLM_Test.md
file. Ensure you follow the existing format for compatibility. - Changing the GUI Appearance: Modify settings in
config.yaml
to adjust the font size, window size, and other UI elements.
Contributions to improve the application or add new features are welcome. Please follow these steps:
- Fork the Repository: Create your own fork of the project.
- Make Your Changes: Implement your improvements or new features.
- Test Your Changes: Ensure your changes work as expected, especially with Obsidian.
- Submit a Pull Request: Create a PR against the main project with a clear description of your changes.
Thank you for contributing to the Obsidian LLM Testing GUI project!