Metadata-Version: 2.1
Name: eaot
Version: 0.0.1
Summary: Paper - Pytorch
Home-page: https://github.com/kyegomez/eaot
License: MIT
Keywords: artificial intelligence,deep learning,optimizers,Prompt Engineering
Author: Kye Gomez
Author-email: kye@apac.ai
Requires-Python: >=3.6,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Project-URL: Repository, https://github.com/kyegomez/eaot
Description-Content-Type: text/markdown

[![Multi-Modality](agorabanner.png)](https://discord.gg/qUtxnK2NMf)

# 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

You can install the package using pip

# 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},
}
```
