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Eunomia

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Chemist AI Agent for Developing Materials Datasets with Natural Language Prompts

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최종 버전 다운로드 (.zip)

- - test.yml
- case-study-3-ground-truth.csv
- conf.py
- contributing.rst
- history.rst
- index.rst
- installation.rst
- make.bat
- Makefile
- readme.rst
- usage.rst
- - __init__.py
  - docs.py
- __init__.py
- agents.py
- eunomia.py
- general.py
- parser.py
- prompts.py
- tools.py
- Applying_other_LLMs.ipynb
- chemical_structure.ipynb
- Extracting_materials_information.ipynb
- other_application.ipynb
- - test_docs.csv
  - test_docs.md
  - test_docs.pdf
  - test_docs.txt
  - test_vector_store.pkl
- __init__.py
- test_docs.py
- test_eunomia.py
- test_tools.py
.editorconfig
.gitignore
.travis.yml
LICENSE
MANIFEST.in
README.md
requirements.txt
setup.cfg
setup.py
tox.ini

// repository documentation

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# Eunomia
AI Agent Chemist for Developing Materials Datasets

![TOC](https://github.com/AI4ChemS/Eunomia/assets/51170839/9fa4d4a7-4997-4a8a-9483-8bea6911b131)

## 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.

![cov_with_flow](https://github.com/AI4ChemS/Eunomia/assets/51170839/2db06b6f-327c-462d-a2c5-7d69737f9ce9)

Live App
--------
[https://eunomia.streamlit.app/](https://eunomia.streamlit.app/)

Example 1: Molecular Targets and Peptide Sequences
--------

[VEGFR example](https://github.com/AI4ChemS/Eunomia/assets/51170839/26350a96-e7ba-47ad-90e0-4b388d58223d)

Example 2: Water Stable Metal-organic Frameworks
--------

[Water stability example](https://github.com/AI4ChemS/Eunomia/assets/51170839/ccd89e31-e7b4-49e8-b90f-c420438e751d)

Example 3: Thermal Conductivity of Metal-organic Frameworks
--------

[Thermal conductivity example](https://github.com/AI4ChemS/Eunomia/assets/51170839/d12afb51-669c-4a3f-b9be-171bec830915)

Installation
--------

```bash
pip install materials-eunomia
```

or you can clone the source code and install in developer mode:

```bash
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`:

```bash
export OPENAI_API_KEY=your_api_key_here
```

Confirm correct installation by running the unittests:

```bash
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](https://github.com/AI4ChemS/Eunomia/blob/main/examples/Applying_other_LLMs.ipynb) for examples.

Citation
--------

For more details checkout [paper](https://pubs.rsc.org/en/content/articlehtml/2024/dd/d4dd00252k) and if you are using our methodology, please consider citing us using the citation below:

```bibtex
@article{ansari2024agent,
  title={Agent-based learning of materials datasets from scientific literature},
  author={Ansari, Mehrad Gholizadeh and Moosavi, Seyed Mohamad},
  journal={Digital Discovery},
  year={2024},
  publisher={Royal Society of Chemistry}
}
```