Welcome to the python-chebai Wiki, a comprehensive guide to understanding and utilizing ChEB-AI, a tool designed to automate semantic classification within the ChEBI (Chemical Entities of Biological Interest) ontology. This wiki aims to provide users with detailed insights into ChEBai's functionalities, data management, model architectures, and configuration setups.

Python-Chebai is library developed for Chebifier, a tool engineered to automate semantic classification within the ChEBI ontology using AI techniques. ChEBI serves as a vast ontology for biologically relevant chemistry, interconnecting chemical structures with meaningful biological and chemical categories. Utilizing a neuro-symbolic AI approach, Python-Chebai harnesses the ontology's structure to facilitate a learning system that continuously adapts and learns from expanding data, contributing significantly to data-driven chemical knowledge discovery.

The tool is built using the Pytorch lightning framework. To learn more about the framework please refer to the official pytorch lightning documentation: Pytorch Ligtning Docs

For quick setup and usage instructions, please refer to the README.