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-0.0.59.tar.gz (3.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

williamtoolbox-0.0.59-py3-none-any.whl (3.2 MB view details)

Uploaded Python 3

File details

Details for the file williamtoolbox-0.0.59.tar.gz.

File metadata

  • Download URL: williamtoolbox-0.0.59.tar.gz
  • Upload date:
  • Size: 3.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.11

File hashes

Hashes for williamtoolbox-0.0.59.tar.gz
Algorithm Hash digest
SHA256 f2538e4fa05672d8e93913e1c6449eeb99a0446b8996abbcdc4aa09ea5dac81d
MD5 6812b5fb2d4196368f25f3cef95131f3
BLAKE2b-256 0ac7efbc15ae0cdf2a430087de0a45c7776efe4cc96042e3e299a7369c822005

See more details on using hashes here.

File details

Details for the file williamtoolbox-0.0.59-py3-none-any.whl.

File metadata

File hashes

Hashes for williamtoolbox-0.0.59-py3-none-any.whl
Algorithm Hash digest
SHA256 7034cad5c2b302a97c6be4dae962841b4d12f92f81e389a138bec5f399919b72
MD5 47fb7285ac4b5549a41d132d513cb402
BLAKE2b-256 6b23354f138865a55ed9ba46d51009e20596a8c663c27cd14963214a4395f6e8

See more details on using hashes here.

Supported by

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