GraphRAG: Building an Intelligent Research Assistant with Knowledge Graphs
English | June 2, 2026 | ASIN: B0H3QXVSY4 | 804 pages | Epub | 9.09 MB
Build a Complete AI Research Assistant That Runs 100% Locally - No API Costs, No Cloud, No SubscriptionsWhat if your documents could answer questions about themselves - not just find keywords, but explain how ideas connect across hundreds of pages?Traditional search finds documents. Traditional RAG retrieves paragraphs. But neither can answer: "How is Dr. Martinez connected to the CRISPR-Adapt project through her collaborators?" - because that answer lives across multiple documents and requires understanding relationships.GraphRAG changes that.This book teaches you to build a complete Graph-based Retrieval Augmented Generation system from scratch. You will transform unstructured documents (PDFs, Word files, text) into a queryable knowledge graph, then answer complex multi-hop questions by combining vector search with graph-based reasoning.Everything runs locally on your machine. Zero cloud costs. Zero API fees. Your data never leaves your computer.What you will build across 11 hands-on chapters:* A document processing pipeline that extracts entities and relationships using a local LLM* A Neo4j knowledge graph with vector embeddings for hybrid search* Two query modes - LLM-First for flexible exploration and Graph-First for precise, low-hallucination answers* A contradiction-handling system that stores all versions of facts transparently* A web interface that makes your system accessible to non-technical users* A production-ready pipeline tested with 1,000+ documentsThe tech stack: Python, Neo4j, Ollama, Qwen2.5, and nomic-embed-text - all free, all open-source.This book is for you if:* You are a software developer, data engineer, or AI practitioner* You can write intermediate Python and use the Linux command line* You have been frustrated by AI systems that find documents but cannot explain connections* You want to build real AI systems, not just call cloud APIsNo prior experience with graph databases, Neo4j, or LLMs is required. This book teaches you everything from installation to production deployment.By the end, you will have a working system that processes thousands of documents and answers complex questions with citations, reasoning paths, and 98% accuracy - all running on your own hardware at $0/month.