A comprehensive guide to building cutting-edge Generative AI applications using Neo4j's knowledge graphs and vector search capabilities Key Features Design vector search and recommendation systems with LLMs using Neo4j GenAI, Haystack, Spring AI, and LangChain4j Apply best practices for graph exploration, modeling, reasoning, and performance optimization Build and consume Neo4j knowledge graphs and deploy your GenAI apps to Google Cloud Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionEmbark on ...
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A comprehensive guide to building cutting-edge Generative AI applications using Neo4j's knowledge graphs and vector search capabilities Key Features Design vector search and recommendation systems with LLMs using Neo4j GenAI, Haystack, Spring AI, and LangChain4j Apply best practices for graph exploration, modeling, reasoning, and performance optimization Build and consume Neo4j knowledge graphs and deploy your GenAI apps to Google Cloud Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionEmbark on an expert-led journey into building LLM-powered applications using Retrieval-Augmented Generation (RAG) and Neo4j knowledge graphs. Written by Ravindranatha Anthapu, Principal Consultant at Neo4j, and Siddhant Agrawal, a Google Developer Expert in GenAI, this comprehensive guide serves as the starting point for developers exploring alternatives to LangChain, covering frameworks like Haystack, Spring AI, and LangChain4j. As LLMs reshape how businesses interact with customers, this book helps you to develop intelligent applications using RAG architecture and knowledge graphs, with a strong focus on overcoming one of AI's most persistent challenges-mitigating hallucinations. You'll also learn how to model and construct Neo4j knowledge graphs with Cypher to enhance LLM responses. Through real-world use cases like vector-powered search and personalized recommendations, the authors help you build hands-on experience with Neo4j GenAI integrations across Haystack and Spring AI. Supported by access to a companion GitHub repository, you'll work through code-heavy examples to confidently build and deploy GenAI apps on Google Cloud. By the end of this book, you'll have the skills to ground LLMs with RAG and Neo4j, optimize graph performance, and strategically select the right cloud platform for your GenAI applications.What you will learn Design, populate, and integrate a Neo4j knowledge graph with RAG Model data for knowledge graphs Enhance knowledge exploration with AI-powered search Maintain and monitor your AI search application with Haystack Leverage LangChain4j and Spring AI for recommendations and personalization Deploy your application on Google Cloud Platform Who this book is forThis book is for database developers and data scientists who want to learn and use knowledge graphs using Neo4j and its vector search capabilities to build intelligent search and recommendation systems. To get started, working knowledge of Python and Java is essential. Familiarity with Neo4j, the Cypher query language, and fundamental concepts of databases will come in handy.
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Add this copy of Building Neo4j-Powered Applications with LLMs: Create to cart. $71.02, new condition, Sold by Booksplease rated 4.0 out of 5 stars, ships from Southport, MERSEYSIDE, UNITED KINGDOM, published 2025 by Packt Publishing Limited.
