Introduction to GraphRAG

In this module, you will learn the fundamentals you need to start building. Your environment is already set up, so from here on the focus is on graphs themselves.

By the end of this module, you will:

• Understand why graphs make LLMsiGo to glossary for large language model (opens in a new tab)A model trained on text to predict the next token, and so to generate language. more accurate
• Know the building blocks of a Neo4j graph (nodesiFull definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties., relationshipsiFull definition for relationship (opens in a new tab)A named, directed connection between two nodes. Every relationship has a type, a start node and an end node., propertiesiFull definition for property (opens in a new tab)A named value stored on a node or a relationship.)
• Have designed a graph data modeliFull definition for data model (opens in a new tab)The labels, relationship types and properties chosen to represent a domain. for your own use case
• Be able to write basic CypheriFull definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it. queries to create and query data