Mastering GraphRAG with Neo4j

Description

In this workshop, you will learn about the neo4j-graphrag Python open-source package and how it can be used to build Retrieval-Augmented Generation (RAG) applications. You will also learn how to integrate Neo4j with generative AI models to enhance graph-powered applications and AI solutions.

Abstract

Join us for an intensive hands-on workshop where you'll dive deep into building GraphRAG applications using Neo4j. This workshop will cover everything from setting up your development environment to implementing advanced RAG patterns using graph databases. You'll learn practical techniques for enhancing your AI applications with graph-powered context and reasoning capabilities.

Key Takeaways

• Master the neo4j-graphrag Python package for building RAG applications
• Learn how to integrate Neo4j with generative AI models
• Understand graph-based approaches to enhance RAG systems
• Implement practical solutions for graph-powered AI applications
• Gain hands-on experience with real-world GraphRAG implementations

Prerequisites

• Basic understanding of Python
• Familiarity with RAG concepts
• Basic knowledge of graph databases (helpful but not required)

Required Materials

• Laptop with Python 3.8+ installed
• Neo4j account (free tier available)
• GitHub account for accessing workshop materials