/JARVIS

JARVIS, a system to connect LLMs with ML community

MIT LicenseMIT

JARVIS

This project is under construction and we will have all the code ready soon.

Overview

Language serves as an interface for LLMs to connect numerous AI models for solving complicated AI tasks!

See our paper: HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in HuggingFace

HuggingGPT is a collaborative system that consists of an LLM as the controller and numerous expert models as collaborative executors (from HuggingFace Hub). The workflow of HuggingGPT consists of four stages:

  • Task Planning: Using ChatGPT to analyze the requests of users to understand their intention, and disassemble them into possible solvable sub-tasks.
  • Model Selection: Based on the sub-tasks, ChatGPT invoke the corresponding models hosted on HuggingFace.
  • Task Execution: Executing each invoked model and returning the results to ChatGPT.
  • Response Generation: Finally, using ChatGPT to integrate the prediction of all models, and generate response.

Quick Start

First replace openai.key in server/config.yaml with your personal key. Then run the following commands:

For server:

# setup env
cd server
conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch 
pip install git+https://github.com/huggingface/diffusers.git
pip install git+https://github.com/huggingface/transformers
pip install -r requirements.txt

# download models
cd models
sh download.sh

# run server
cd ..
python bot_server.py
python model_server.py

For web:

cd web
npm install
npm run dev

Work in progress...

Screenshots

Citation

You can cite HuggingGPT as follows:

@article{shen2023hugginggpt,
    title={HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in HuggingFace},
    author={Shen, Yongliang and Song, Kaitao and Tan, Xu and Li, Dongsheng and Lu, Weiming and Zhuang, Yueting},
    journal={arXiv preprint arXiv:2303.17580},
    year={2023}
}

Acknowledgement