BaranziniLab/KG_RAG
Empower Large Language Models (LLM) using Knowledge Graph based Retrieval-Augmented Generation (KG-RAG) for knowledge intensive tasks
This project helps biomedical researchers or clinicians get precise, accurate answers to questions about diseases and related biomedical concepts. You input a question, and it combines a large language model's general knowledge with specific, verified facts from a biomedical knowledge graph. The output is a highly informed, contextually accurate response that avoids common inaccuracies of standalone AI models.
938 stars. No commits in the last 6 months.
Use this if you need accurate, fact-checked answers to complex questions about diseases, drugs, genes, or other biomedical entities, reducing the risk of misinformation from general AI models.
Not ideal if your queries extend beyond diseases or the biomedical domain, as it is currently optimized for disease-related questions.
Stars
938
Forks
111
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Nov 09, 2024
Commits (30d)
0
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