GRAPH-RAG PROJECT COOKBOOK

Graph-RAG Project Cookbook Subtitle: Practical Recipes for Building Knowledge Graph-Powered LLM Systems in Real-World ApplicationsUnlock the next evolution of Retrieval-Augmented Generation with Graph-RAG — the powerful fusion of knowledge graphs and large language models that delivers more accurate, explainable, and intelligent AI systems.Traditional RAG relies on vector similarity alone and often falls short when handling complex relationships, multi-hop reasoning, or enterprise-scale knowledge. Graph-RAG overcomes these limitations by combining structured graph databases with vector search, enabling deep relational reasoning, hierarchical summarization, and agentic workflows that go far beyond isolated text chunks.This practical, project-driven cookbook takes you step-by-step from foundational concepts to production-ready implementations. Through reusable Python recipes, real-world architectures, and detailed workflows using LangChain, LangGraph, and Neo4j, you will learn how to:Design and build high-quality knowledge graphs from raw documentsExtract entities and relationships with schema-guided LLM pipelinesCreate hybrid retrieval systems that combine semantic search with graph traversalImplement multi-step reasoning, question answering, and intelligent summarizationBuild persistent graph-memory agents capable of complex decision-making and task automationDeploy, scale, monitor, and secure Graph-RAG systems in cloud environmentsWhether you are a developer experimenting with advanced RAG techniques, a data scientist building enterprise knowledge platforms, or an AI engineer creating agentic applications, this book provides the hands-on guidance and best practices you need to succeed.Inside you will find complete end-to-end projects, production notes, optimization strategies, and code examples that translate directly into real-world solutions. Move beyond basic RAG and master the art of turning interconnected data into actionable intelligence with Graph-RAG.Perfect for anyone ready to build the next generation of knowledge-powered AI systems.