Basic Retriever

Alternative Names

• Naive Retriever
• Baseline RAG
• Typical RAG

Required Graph Shape

Lexical Graph

Description

The user question is embedded using the same embedder that has been used before to create the chunk embeddings. A vector similarity search is executed on the chunk embeddings to retrieve k (number previously configured by developer / user) most similar chunks.

Usage

This pattern is useful if the user asks for specific information about a topic that exists in one or more (but not too many) chunks. The question should not require complex aggregations or knowledge about the whole dataset. Since the pattern only contains a vector similarity search it is easy to understand, implement and get started with.

Further reading

• Advanced Retriever Techniques to Improve Your RAGs (Damian Gil, April 2024)
• Implementing advanced RAG strategies with Neo4j (November 2023)

Existing Implementations

• Langchain Retrievers: Vector store-backed retriever
• Langchain: Neo4jVector

Example Implementations

• Langchain Templates: Neo4j Advanced RAG