This repository contains an implementation of the SELF-DISCOVER framework as described in the paper "Self-Discover: Large Language Models Self-Compose Reasoning Structures" by Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng. SELF-DISCOVER enables Large Language Models (LLMs) to autonomously discover and compose reasoning structures to tackle complex reasoning tasks, significantly enhancing their performance on challenging benchmarks.
set your together.ai API key as an enviroment variable TOGETHER_API_KEY or your groq API key as an enviroment variable GROQ_API_KEY.
Run the main pythons script main.py. Use -v to see the thinking process.
I welcome contributions to improve this implementation! Please feel free to submit issues or pull requests with enhancements, bug fixes, or suggestions.
The idea is based on the paper "Self-Discover: Large Language Models Self-Compose Reasoning Structures" by Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng.
@article{zhou2024selfdiscover,
title={Self-Discover: Large Language Models Self-Compose Reasoning Structures},
author={Zhou, Pei and Pujara, Jay and Ren, Xiang and Chen, Xinyun and Cheng, Heng-Tze and Le, Quoc V. and Chi, Ed H. and Zhou, Denny and Mishra, Swaroop and Zheng, Huaixiu Steven},
journal={ArXiv},
volume={abs/2402.03620},
year={2024},
url={https://arxiv.org/abs/2402.03620}
}
The implementation is based on https://github.com/catid/self-discover