Vector Indexes

In the last lesson, you learned about embeddingsInformation represented as a numerical vector, positioned so that similar information sits close together., vectors and their role in RAGFetching relevant context from an external data source as additional context to inform a language model's response..

In this lesson, you will learn how to use a vector indexA structure over a vector property. The database searches it to find the vectors nearest a given one, rather than comparing every vector stored. in Neo4j to compare embeddings to find similar data.