Chemist AI Agent for Developing Materials Datasets with Natural Language Prompts
Project description
Eunomia
AI Agent Chemist for Developing Materials Datasets
Iterative-Chain-of-Verification (CoV)
Eunomia employs a chain-of-verification process iteratively to minimize the likelihood of hallucination, as well as integrating chemistry-informed knowledge into decision-making and action-taking plannings of the LLM.
Live App
https://eunomia.streamlit.app/
Example 1: Molecular Targets and Peptide Sequences
Example 2: Water Stable Metal-organic Frameworks
Example 3: Thermal Conductivity of Metal-organic Frameworks
Installation
pip install materials-eunomia
or you can clone the source code and install in developer mode:
git clone https://github.com/AI4ChemS/Eunomia.git && cd Eunomia
pip install -e .
You need to have a valid OPENAI API key. If you are on a windows machine you can add OPENAI_API_KEY in your Environment Variables. For linux systems set the key by adding this line to ~/.bashrc:
export OPENAI_API_KEY=your_api_key_here
Confirm correct installation by running the unittests:
cd tests && python -m unittest discover
Applying Other LLMs
Eunomia uses openAI's gpt-4 by default but you can use other LLMs for driving the agent as well. Check out this notebook for examples.
Citation
For more details checkout preprint and if you are using our methodology, please consider citing us using the citation below:
@misc{ansari2023agentbased,
title={Agent-based Learning of Materials Datasets from Scientific Literature},
author={Mehrad Ansari and Seyed Mohamad Moosavi},
year={2023},
eprint={2312.11690},
archivePrefix={arXiv},
primaryClass={cs.AI}
}
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