Auto-Precise-Prompts

Automated LLM-based Prompt Engineering for Structured Data Processing

Created by Praneeth Vadlapati (@prane-eth)

Note

Please star ⭐ the repository to show your support.

Why Auto-Precise-Prompts?

LLMs are powerful tools for processing text. Structured data processing using LLMs requires precise prompts. Prompt Engineering and testing require workforce for manual efforts, and require more time, resources, and budget.
The project uses automated methods to generate and test prompts, to automate the Prompt Engineering process for structured data processing using LLMs.

📄 Research Paper

A published research paper is available at NAJER

📑 Citation

To use my paper for reference, please cite it as below:

@article{vadlapati2024autopreciseprompts,
	title={{AutoPrecisePrompts: Automated LLM-based Prompt Engineering for Structured Data Processing}},
	journal={{North American Journal of Engineering and Research}},
	volume={5},
	number={1},
	year={2024},
	month={Jan},
	author={{Praneeth Vadlapati}},
	url={https://najer.org/najer/article/view/83}
}

🚀 Quick Start

pip install -r requirements.txt
cp .env.example .env

Now, edit the .env file and add your values.
Run the file Auto-Precise-Prompts.ipynb

💻 More Projects

For more projects, open the profile: @Pro-GenAI

🛠️ Contributing

Contributions are welcome! Feel free to create an issue for any bug reports or suggestions.
To contribute, star ⭐ the repository and create an Issue. If I can't solve it, I will allow anyone to create a pull request.

🪪 License

Copyright (c) 2024 Praneeth Vadlapati
Please refer to the LICENSE file for more information.

⚠️ Disclaimer

The code is not intended for use in production environments. This code is for educational and research purposes only.

No author is responsible for any misuse or damage caused by this code. Use it at your own risk. The code is provided as is without any guarantees or warranty.

📧 Contact

For personal queries, please find my contact details here: linktr.ee/prane.eth