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- input_config.json +1 -1
README.md
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#
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## TODO
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[ ]
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[ ] Add Tools (web, math, code)
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[ ] Make cli
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## What it does
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- It takes a prompt , thinks, thinks again, critics itself, then returns answer
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## Installation
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cd open-o1
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pip install -r requirements.txt
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streamlit run app.py
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```
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HAVE FUN.
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# Open-o1
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It thinks like o1
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## TODO
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[ ] Add fallback llms
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[ ] Better error handling
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[ ] Add Tools (web, math, code)
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[ ] Make cli
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## What it does
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- It takes a prompt , thinks, thinks again, critics itself, then returns answer
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## Installation
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cd open-o1
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streamlit run app.py
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```
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HAVE FUN.
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## Helpful Papers
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1. To Cot or not to Cot? CHAIN-OF-THOUGHT HELPS MAINLY ON MATH AND SYMBOLIC REASONING
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2. The Impact of Reasoning Step Length on Large Language Models
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3. Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters [2212.10001](https://arxiv.org/abs/2212.10001)
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```bibtex
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@misc{wang2023understandingchainofthoughtpromptingempirical,
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title={Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters},
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author={Boshi Wang and Sewon Min and Xiang Deng and Jiaming Shen and You Wu and Luke Zettlemoyer and Huan Sun},
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year={2023},
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eprint={2212.10001},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2212.10001},
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}
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```
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input_config.json
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"max_steps": 3,
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"temperature": 0.2,
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"timeout": 30.0,
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"sleeptime":
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"force_max_steps": true
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}
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"max_steps": 3,
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"temperature": 0.2,
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"timeout": 30.0,
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"sleeptime": 0.0,
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"force_max_steps": true
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}
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