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Now available: GraphRAG with MongoDB Atlas and LangChain. 🔍 If you are building retrieval-augmented generation (RAG) systems that require reasoning over complex relationships, GraphRAG offers a graph-based alternative to traditional vector search. This integration enables: 1. Entity and relationship extraction via LLMs to create a knowledge graph in MongoDB Atlas 2. Graph traversal during query time to retrieve connected context and improve response accuracy In this tutorial, we apply GraphRAG
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YouTubeARCTutorials
Go developers, this one’s for you! MongoDB just launched a powerful new integration with LangChainGo, making it easier than ever to build Go applications powered by LLMs. With Atlas Vector Search, you can quickly find semantically similar documents to power RAG applications in Go—all while keeping your operational and vector data in one place. Ready to build smarter AI applications? Check out our blog and tutorial to get started today! https://mongodb.social/6188FrZVO | MongoDB
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