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-0.0.9.tar.gz (2.4 MB view details)

Uploaded Source

Built Distribution

williamtoolbox-0.0.9-py3-none-any.whl (15.0 MB view details)

Uploaded Python 3

File details

Details for the file williamtoolbox-0.0.9.tar.gz.

File metadata

  • Download URL: williamtoolbox-0.0.9.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-0.0.9.tar.gz
Algorithm Hash digest
SHA256 a0602e273bf140b16dd99fd43e1a0a12c633f615902980f2ddb142fcf2cce574
MD5 f504d2e26f1942f6d16b5c4f626f976e
BLAKE2b-256 d4f5a4cb85be10f3eb6f16293800f8fe46c6c0cd042395a956cfc590ab2ecf7d

See more details on using hashes here.

File details

Details for the file williamtoolbox-0.0.9-py3-none-any.whl.

File metadata

File hashes

Hashes for williamtoolbox-0.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 1bc92fe6dce1317509492ae0451b524640fd461c49be4b267b6eb15fbcd6009d
MD5 1078c6f4bb86832c599c9c86b034ceaa
BLAKE2b-256 45925d89b00d07d887ed43f4d061a5e71fe274a824d74d0ead6d944d6363acd0

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