Skip to main content

williamtoolbox: William Toolbox

Project description

William Toolbox 🧰

William Toolbox is an open-source project designed to simplify the management of byzerllm models and auto-cder.RAG (Retrieval-Augmented Generation) systems. It provides a user-friendly interface for deploying, monitoring, and controlling various AI models and RAG setups.

This project is powered by auto-coder.chat. You can check how we develop this project by reading yamls in directory auto-coder-actions.

image

飞书文档链接: https://uelng8wukz.feishu.cn/wiki/R7mswlEn2iROu4kbUezcRyJAnSf?fromScene=spaceOverview

🌟 Features

  • 🤖 Model Management: Deploy, start, stop, and monitor AI models
  • 📚 RAG System Management: Create and control RAG setups
  • 🖥️ User-friendly Web Interface: Easy-to-use dashboard for all operations
  • 🔄 Real-time Status Updates: Monitor the status of your models and RAGs
  • 🛠️ Flexible Configuration: Customize model and RAG parameters

🚀 Getting Started

Prerequisites

  • Python 3.9+

Installation

pip install -U williamtoolbox

Running the Application

  1. Create a work directory and cd into it:

    mkdir william-toolbox && cd william-toolbox
    
  2. Start the backend server:

    william.toolbox.backend
    
  3. Start the frontend server:

    william.toolbox.frontend
    
  4. Open your browser and navigate to http://localhost:8006

📖 Usage

  1. Adding a Model: Click on "Add Model" and fill in the required information.
  2. Managing Models: Use the model list to start, stop, or check the status of your models.
  3. Creating a RAG: Click on "Add RAG" and provide the necessary details.
  4. Managing RAGs: Control and monitor your RAG systems from the RAG list.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgements

  • Thanks to all contributors who have helped shape William Toolbox.
  • Special thanks to the open-source community for providing the tools and libraries that make this project possible.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

williamtoolbox-0.0.15.tar.gz (2.4 MB view details)

Uploaded Source

Built Distribution

williamtoolbox-0.0.15-py3-none-any.whl (27.0 MB view details)

Uploaded Python 3

File details

Details for the file williamtoolbox-0.0.15.tar.gz.

File metadata

  • Download URL: williamtoolbox-0.0.15.tar.gz
  • Upload date:
  • Size: 2.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.11

File hashes

Hashes for williamtoolbox-0.0.15.tar.gz
Algorithm Hash digest
SHA256 d8ec71a4f6a952917fe3d13ea0f431ef356a8381901a2ad2099eda7dce02405d
MD5 e6b36c8d099e28e0a9dd724a6692632a
BLAKE2b-256 5bb03c7a76814b7cb3f10158960076231ac3444be5d5502d35072eb050b21326

See more details on using hashes here.

File details

Details for the file williamtoolbox-0.0.15-py3-none-any.whl.

File metadata

File hashes

Hashes for williamtoolbox-0.0.15-py3-none-any.whl
Algorithm Hash digest
SHA256 ba74e33e1b8ca1944b8eb6260f75e70a88cfc6da85a0bb26fdec503f5c143819
MD5 9d6f635bba75fd46cc26bcaaf533e239
BLAKE2b-256 323cba6c4b8f33589166e09dc78444e721ae6dabec23f23413cbbe9619b0ba02

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page