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-0.0.32.tar.gz (3.0 MB view details)

Uploaded Source

Built Distribution

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

williamtoolbox-0.0.32-py3-none-any.whl (70.4 MB view details)

Uploaded Python 3

File details

Details for the file williamtoolbox-0.0.32.tar.gz.

File metadata

  • Download URL: williamtoolbox-0.0.32.tar.gz
  • Upload date:
  • Size: 3.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.11

File hashes

Hashes for williamtoolbox-0.0.32.tar.gz
Algorithm Hash digest
SHA256 a80d7e8347da26112f4727f0f020180104e9585511d9ddefbdea92cb7cb852d1
MD5 9e45a2db1cc3b9b875fcb2755be48e10
BLAKE2b-256 3b3fb8676f0ecb50d8b360c1978b7a6ffe5c1cba9fabee3fa5bdbb9a1d9040c3

See more details on using hashes here.

File details

Details for the file williamtoolbox-0.0.32-py3-none-any.whl.

File metadata

File hashes

Hashes for williamtoolbox-0.0.32-py3-none-any.whl
Algorithm Hash digest
SHA256 ab9184e3859e4c5a64b3c2a3619a7bfd035f08ff130e4f5d4ba4a2af421da037
MD5 9bbc6d19070523d82870e462eb970491
BLAKE2b-256 34c33d7a7fd8dcbf99d7b784ed5df8ab209b7b3652a91216ec43cf1a3205526f

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