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    Advanced Architecture ️RAG Techniques

    Microsoft GraphRAG

    Microsoft GraphRAG is an advanced Retrieval-Augmented Generation (RAG) system that integrates knowledge graphs to improve the performance of large language models (LLMs). Developed by Microsoft Research, GraphRAG addresses limitations in traditional RAG approaches by using LLM-generated knowledge graphs to enhance document analysis and improve response quality.

    Traditional RAG systems often struggle with complex queries that require synthesizing information from disparate sources. GraphRAG aims to: Connect related information across datasets. Enhance understanding of semantic concepts. Improve performance on global sensemaking tasks.

    About this tutorial

    This hands-on Jupyter notebook is part of RAG Techniques, a free open-source repository by Nir Diamant covering rag techniques with runnable code examples and detailed explanations.

    Free and open-sourceRunnable Jupyter notebookActive community support
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    The book that extends this repo: 22 RAG techniques with the intuition behind each, side-by-side comparisons of when each wins (and quietly fails), and original illustrations.

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