ChemAgent

This code repo contains ChemAgent implementation for the paper "Tooling or Not Tooling? The Impact of Tools on Language Agents for Chemistry Problem Solving".

Installation

API Keys

To use the backbone LLMs (GPT-4o and Claude-3.5-Sonnet) and some tools, you need to obtain the API keys first. Please follow the links in api_keys.py to get your keys and insert your keys there.

Environment Setup

conda create -n chemagent python=3.9
pip install -r requirements.txt

# Manually install Uni-Core, following https://github.com/dptech-corp/Uni-Core

Usage

cd to the python_server folder, run:

./start_jupyter_server.sh 8888

Then cd back to the project root folder, and use the following commands to query ChemAgent:

from api_keys import api_keys
from chemagent import ChemAgent

agent = ChemAgent(model='gpt-4o-2024-08-06', api_keys=api_keys)

query = "What is the molecular weight the chemical compound Caffeine."
final_answer, tool_use_chain, conversation, conversation_with_icl = agent.run(query)

You could play the agent in the Jupyter notebook playground.ipynb.

Citation

If our paper or related resources prove valuable to your research, we kindly ask for citation. Please feel free to contact us with any inquiries.

@article{yu2024chemagent,
    title={Tooling or Not Tooling? The Impact of Tools on Language Agents for Chemistry Problem Solving},
    author={Botao Yu and Frazier N. Baker and Ziru Chen and Garrett Herb and Boyu Gou and Daniel Adu-Ampratwum and Xia Ning and Huan Sun},
    journal={arXiv preprint arXiv:2411.07228},
    year={2024}
}