Introduction to GraphRAG Workshop
In this 60 minute workshop, you will learn about GraphRAG, a technique that combines graph databases with generative AI to improve the quality of LLM-generated content.
We will explore the terms Retrieval-Augmented Generation (RAG) and Context Engineering, and how GraphRAG can be used in both scenarios.
The workshop is aimed at Generative AI practitioners who are familiar with vector-based Retrieval-Augmented Generation (RAG) and would like to understand how the approach of GraphRAG can improve the quality of LLM-generated content.
What you will learn
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What GraphRAG is and how it can improve the quality of LLM-generated content
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The common graph shapes used in GraphRAG
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How to extract structure from unstructured data and store it in a Knowledge Graph
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How to use relationships to provide additional context to vector-based semantic search
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How to convert natural language queries into Cypher queries
Prerequisites
Before taking this workshop, you should have:
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An understanding of Generative AI and Large Language Models (LLMs)
Duration
1 hour
Get Support
If you find yourself stuck at any stage then our friendly community will be happy to help. You can reach out for help on the Neo4j Community Site, or head over to the Neo4j Discord server for real-time discussions.
Feedback
If you have any comments or feedback on this course you can email us on graphacademy@neo4j.com.