01968nam a22002297a 4500 20260727150424.0 260727s2025 |||||||| |||| 00| 0 eng d 9781836206231 PK-LaUMT 005.74 ANT-B Anthapu, Ravindranatha 14262 Building Neo4j-powered applications with LLMs : create LLM-driven search and recommendations : applications with Haystack, LangChain4j, and Sprin AI / Ravindranatha Anthapu Birmingham : Packt Publishing Ltd., 2025 xxiv, 283 p. Expert insight Index present 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 Description Embark 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 is your starting point for exploring alternatives to LangChain, covering frameworks such as Haystack, Spring AI, and LangChain4j. As LLMs (large language models) reshape how businesses interact with customers, this book helps you develop intelligent applications using RAG architecture and knowledge graphs, with a strong focus on overcoming one of AI's most persistent challenges--mitigating hallucinations. Eng Neo4J (computer file) 13417 Database design 4777 BK 141675 141675 0 0 0 0 01 01 2026-07-27 0 005.74 ANT-B 153671 2026-07-27 15:04:36 2026-07-27 BK