https://github.com/kyegomez/eaot

The open source implementation of "Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers"
https://github.com/kyegomez/eaot

artificial-intelligence gpt4 llama llama2 machine-learning prompt-engineering prompting

Last synced: 11 months ago
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The open source implementation of "Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers"

• Host: GitHub
• URL: https://github.com/kyegomez/eaot
• Owner: kyegomez
• License: mit
• Created: 2023-09-21T02:40:42.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2024-03-11T22:25:47.000Z (over 2 years ago)
• Last Synced: 2025-07-19T21:39:28.367Z (12 months ago)
• Topics: artificial-intelligence, gpt4, llama, llama2, machine-learning, prompt-engineering, prompting
• Language: Makefile
• Homepage: https://discord.gg/qUtxnK2NMf
• Size: 2.15 MB
• Stars: 19
• Watchers: 3
• Forks: 5
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Contributing: docs/contributing.md
  • Funding: .github/FUNDING.yml
  • License: LICENSE
  • Roadmap: docs/roadmap.md

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README

          
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# Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Agora's open source implementation of the paper: Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers

[PAPER LINK](https://arxiv.org/pdf/2309.08532.pdf)

## Installation

`pip install eaot``

# Citation

```BibTeX

@misc{2309.08532,

Author = {Qingyan Guo and Rui Wang and Junliang Guo and Bei Li and Kaitao Song and Xu Tan and Guoqing Liu and Jiang Bian and Yujiu Yang},

Title = {Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers},

Year = {2023},

Eprint = {arXiv:2309.08532},

}

```