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Building Neo4j-Powered Applications with LLMs

You're reading from   Building Neo4j-Powered Applications with LLMs Create LLM-driven search and recommendations applications with Haystack, LangChain4j, and Spring AI

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Product type Paperback
Published in Jun 2025
Publisher Packt
ISBN-13 9781836206231
Length 312 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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Ravindranatha Anthapu Ravindranatha Anthapu
Author Profile Icon Ravindranatha Anthapu
Ravindranatha Anthapu
Siddhant Agarwal Siddhant Agarwal
Author Profile Icon Siddhant Agarwal
Siddhant Agarwal
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Toc

Table of Contents (20) Chapters Close

Preface 1. Part: 1 Introducing RAG and Knowledge Graphs for LLM Grounding 2. Introducing LLMs, RAGs, and Neo4j Knowledge Graphs FREE CHAPTER 3. Demystifying RAG 4. Building a Foundational Understanding of Knowledge Graph for Intelligent Applications 5. Part 2: Integrating Haystack with Neo4j: A Practical Guide to Building AI-Powered Search 6. Building Your Neo4j Graph with Movies Dataset 7. Implementing Powerful Search Functionalities with Neo4j and Haystack 8. Exploring Advanced Knowledge Graph Capabilities with Neo4j 9. Part 3: Building an Intelligent Recommendation System with Neo4j, Spring AI, and LangChain4j 10. Introducing the Neo4j Spring AI and LangChain4j Frameworks for Building Recommendation Systems 11. Constructing a Recommendation Graph with H&M Personalization Dataset 12. Integrating LangChain4j and Spring AI with Neo4j 13. Creating an Intelligent Recommendation System 14. Part 4: Deploying Your GenAI Application in the Cloud 15. Choosing the Right Cloud Platform for GenAI Applications 16. Deploying Your Application on the Google Cloud 17. Epilogue 18. Other Books You May Enjoy
19. Index

Index

A

Accelerate 13

advanced Cypher techniques, complex graph structures

nested queries 93

pattern matching, with path patterns 91

procedural logic 92

subqueries 92

variable-length relationships 90

advanced vector search

Haystack, connecting to Neo4j 102

AI-powered search system

alerts, setting up for critical issues 132

best practices, for maintaining and monitoring 131

logging strategy, implementing 132

Neo4j and Haystack performance, monitoring 131

regular maintenance routine,
establishing 132

AI services

by cloud providers 233, 234

reference link 143

application

containerizing, with Docker 254, 255

articles

filtering, by characteristics 223-227

filtering, that belong to other
communities 219-227

AuraDB

reference link 38

AuraDB Free 86

data, importing into 87-89

instance, setting up 86

AuraDS

reference link 38

AWS

reference link, for security and
compliance...

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