Microsoft Reactor

In this presentation, you'll gain an understanding of GraphRAG, a technique that enhances document analysis and question-and-answer performance by leveraging large language models (LLMs) to create knowledge graphs. We'll explore how GraphRAG builds upon Retrieval-Augmented Generation (RAG) by using knowledge graphs instead of vector similarity for retrieval. You'll learn how to set up the environment, prepare data, and implement GraphRAG using LangChain, with practical code examples. Additionally, we'll explore some advanced features and customization options available in LangChain to optimize and tailor GraphRAG to your specific needs.

Presented by John Alexander, Content Developer and Apurva Mody, Principal Program Manager

** Part of RAGHack, a free global hackathon to develop RAG applications. Join at https://aka.ms/raghack **