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This video tutorial demonstrates how to communicate with graph databases using an Intelligent Agent with Retrieval Augmentation Generation (RAG). Learn how to implement a RAG system using LangChain and Neo4j over the course of 49 minutes. Explore key components including the Neo4j Graph integration that wraps the Python driver for simplified database interaction, the CypherQAChain that translates natural language into Cypher queries, and Neo4jVector which provides vector integration capabilities. Discover how to integrate Neo4j with LangChain via GraphsipperQAChain, implement Neo4j vector integration for LangChain documents, and utilize the MCP Context Protocol. The tutorial shows how to use the MCP client and server integrated with Anthropic's Claude Desktop application to connect to a Neo4J graph database and query it using natural language. Note that the notebook and code are available only for paying subscribers by contacting mlengineerchannel@gmail.com.
