Welcome to our project submission for the LLMs for Chemistry and Materials Science Heckatlon that took place on March 29th, 2023.
Our project aims to create a simplified knowledge graph from article abstacts to discover concepts and relevant articles. During the hackathon, we were able to design a web application that automatically extracts entities and relationships from material-science abstracts using a pre-defined schema.. You can find our video submission here: https://twitter.com/DCirci/status/1641486022709059585?s=20.
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Clone the repo
git clone https://github.com/github_username/repo_name.git
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Install the packages
pip install -r requirements.txt
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Specify authentication details in config.py
openai_api_key = "openai_api_key" neo4j_uri = "neo4j_uri" neo4j_username = "neo4j_username" neo4j_password = "neo4j_password"
Get Neo4j credentials by first creating a user account, and then creating a free instance. On creation of an instance, you will be prompted to download authentication details containing uri, username and password.
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Run
streamlit run app.py
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To view and interact with the results on Neo4j Browser, you will be asked to authenticate with your credentials again (see config.py)
We are still working on developing our project and would greatly appreciate your feedback and contributions.
This project is licensed under the MIT License. See the LICENSE file for details.
If you have any questions or comments, feel free to reach out to us at [email protected].
Thank you for taking the time to check out our project!