graphrag and biomedical-graphrag
GraphRAG is a general-purpose graph-based RAG framework by Microsoft, while the biomedical variant is a specialized implementation built on top of it for domain-specific biomedical research applications, making them framework-and-domain-adaptation ecosystem siblings.
About graphrag
microsoft/graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
Extracts knowledge graphs from unstructured text using LLMs, then uses those graph structures to improve retrieval and reasoning for private data. Implements a data indexing pipeline that transforms narrative documents into entity-relationship graphs, enabling more contextual and discovery-oriented query responses compared to standard vector retrieval. Supports prompt tuning workflows and integrates with major LLM providers through a configuration-driven architecture.
About biomedical-graphrag
benitomartin/biomedical-graphrag
A comprehensive GraphRAG (Graph Retrieval-Augmented Generation) system designed for biomedical research
Combines Neo4j knowledge graphs with Qdrant vector embeddings for hybrid biomedical retrieval, ingesting PubMed papers, gene data, and citation networks into a specialized schema covering papers, authors, institutions, genes, and MeSH terms. LLM-powered tool selection routes queries to semantic search or graph traversal, while async processing handles high-volume data collection from external biomedical APIs.
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