Rain Born

Essential GraphRAG

Upgrade your RAG applications with the power of knowledge graphs. Retrieval Augmented Generation (RAG) is a great way to harness the power of generative AI for information not contained in a LLM’s training data and to avoid depending on LLM for factual information. However, RAG only works when you can quickly identify and supply the most relevant context to your LLM. Essential GraphRAG shows you how to use knowledge graphs to model your RAG data and deliver better performance, accuracy, traceability, and completeness. Inside Essential GraphRAG you’ll learn: • The benefits of using Knowledge Graphs in a RAG system • How to implement a GraphRAG system from scratch • The process of building a fully working production RAG system • Constructing knowledge graphs using LLMs • Evaluating performance of a RAG pipeline Essential GraphRAG is a practical guide to empowering LLMs with RAG. You’ll learn to deliver vector similarity-based approaches to find relevant information, as well as work with semantic layers, deliver agentic RAG, and generate Cypher statements to retrieve data from a knowledge graph. About the technology A Retrieval Augmented Generation (RAG) system automatically selects and supplies domain-specific context to an LLM, radically improving its ability to generate accurate, hallucination-free responses. The GraphRAG pattern employs a knowledge graph to structure the RAG’s input, taking advantage of existing relationships in the data to generate rich, relevant prompts. About the book Essential GraphRAG shows you how to build and deploy a production-quality GraphRAG system. You’ll learn to extract structured knowledge from text and how to combine vector-based and graph-based retrieval methods. The book is rich in practical examples, from building a vector similarity search retrieval tool and an Agentic RAG application, to evaluating performance and accuracy, and more. What's inside • Embeddings, vector similarity search, and hybrid search • Turning natural language into Cypher database queries • Microsoft’s GraphRAG pipeline • Agentic RAG About the reader For readers with intermediate Python skills and some experience with a graph database like Neo4j. About the author The author of Manning’s Graph Algorithms for Data Science and a contributor to LangChain and LlamaIndex, Tomaž Bratanic has extensive experience with graphs, machine learning, and generative AI. Oskar Hane leads the Generative AI engineering team at Neo4j. Table of Contents 1 Improving LLM accuracy 2 Vector similarity search and hybrid search 3 Advanced vector retrieval strategies 4 Generating Cypher queries from natural language questions 5 Agentic RAG 6 Constructing knowledge graphs with LLMs 7 Microsoft’s GraphRAG implementation 8 RAG application evaluation A The Neo4j environment Get a free eBook (PDF or ePub) from Manning as well as access to the online liveBook format (and its AI assistant that will answer your questions in any language) when you purchase the print book.

Midworld

Born was a child of the rain forest that covered Midworld, part of the primitive society that the peaceful jungle planet had sustained for hundreds of years. He was wise in the ways of his world, and he knew well the precarious natural balance that governed all things.Then one day the aliens came. Giants. They knew nothing of the Upper or Lower Hell ? and they cared less. Born had risked his life to save them, to guide them through the myriad tangled boughs, past unseen, unsuspected dangers lurking in the underbrush. But worse than their ignorance of how to survive, the aliens had plans for Midworld, plans that could utterly destroy the globe-spanning forest that his people called home.As the days passed, Born realized his mistake. And as he had once hunted only to live, he knew now that he would be forced to live only to kill...

The Ruling Races of Prehistoric Times in India, Southwestern Asia, and Southern Europe: The primitive village. The early history of India ... Astronomical myths. History of the rule of the Kushite-Semite races. First coming of the fire-worshipping Heracleidae to Greece