| # Open-o1 | |
| It thinks like o1 | |
| ## TODO | |
| [ ] Add fallback llms | |
| [ ] Better error handling | |
| [ ] Add Tools (web, math, code) | |
| [ ] Make cli | |
| ## What it does | |
| - It takes a prompt , thinks, thinks again, critics itself, then returns answer | |
| ## Installation | |
| ```bash | |
| git clone https://github.com/tikendraw/open-o1.git | |
| cd open-o1 | |
| streamlit run app.py | |
| ``` | |
| HAVE FUN. | |
| ## Helpful Papers | |
| 1. To Cot or not to Cot? CHAIN-OF-THOUGHT HELPS MAINLY ON MATH AND SYMBOLIC REASONING | |
| 2. The Impact of Reasoning Step Length on Large Language Models | |
| 3. Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters [2212.10001](https://arxiv.org/abs/2212.10001) | |
| ```bibtex | |
| @misc{wang2023understandingchainofthoughtpromptingempirical, | |
| title={Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters}, | |
| author={Boshi Wang and Sewon Min and Xiang Deng and Jiaming Shen and You Wu and Luke Zettlemoyer and Huan Sun}, | |
| year={2023}, | |
| eprint={2212.10001}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL}, | |
| url={https://arxiv.org/abs/2212.10001}, | |
| } | |
| ``` |