GraphRAG-SDK and biomedical-graphrag
The GraphRAG SDK is a general-purpose framework for building graph-based RAG applications at scale, while the biomedical implementation is a specialized domain application built on top of similar GraphRAG principles, making them complementary rather than competing solutions.
About GraphRAG-SDK
FalkorDB/GraphRAG-SDK
Build fast and accurate GenAI apps with GraphRAG SDK at scale.
Combines knowledge graphs, ontology extraction, and LLM inference via LiteLLM to enable GraphRAG workflows—automatically structuring unstructured data into queryable graphs stored in FalkorDB. Supports multi-vendor LLM deployment (OpenAI, Google, Azure, Ollama) and provides both ontology auto-detection from sources and chat-based query interfaces for knowledge graph traversal and augmented generation.
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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