Rethinking RAG: How GraphRAG Improves Multi-Hop Reasoning!

Traditional RAG pipelines rely on vector search to pull relevant text chunks and then feed those chunks to an LLM to generate answers. GraphRAG takes this a step further by extracting entities and relationships