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

Product type Paperback

Published in Jun 2025

Publisher Packt

ISBN-13 9781836206231

Length 312 pages

Edition 1st Edition

Languages

Cypher

Tools

Cypher Query

Concepts

GPT/LLMs

Authors (2):

Ravindranatha Anthapu

Siddhant Agarwal

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Table of Contents (20) Chapters

Preface

1. Part: 1 Introducing RAG and Knowledge Graphs for LLM Grounding

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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

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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

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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

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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

Technical requirements

Before diving into this chapter, ensure that your development environment is set up with the necessary technologies and tools. Also, your Neo4j instance should be loaded with the data from Ch4 and embeddings from Ch5. Here are the technical requirements for this chapter:

Neo4j (v5.x or higher): You will need Neo4j installed and running on your local machine or server. You can download it from https://neo4j.com/download/.
Haystack (v1.x): We will be using the Haystack framework for integrating AI-powered search capabilities. Make sure to install Haystack by following the instructions at https://docs.haystack.deepset.ai/docs/installation.
Python (v3.8 or higher): Ensure that you have Python installed. You can download it from https://www.python.org/downloads/.
OpenAI API key: To successfully generate embeddings using GPT-based models, you will need an OpenAI API key:
- Obtain the API Key by signing up for an account at OpenAI...

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

Table of Contents (20) Chapters

Technical requirements

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Authors (2)

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