Retrieval Process

The retrieval process in Retrieval-Augmented Generation (RAG) involves finding relevant information from a large dataset or knowledge base to support the generation of accurate, context-aware responses. When a query is received, the system first converts it into a vector (embedding) and uses this vector to search a database of pre-indexed embeddings, identifying the most similar or relevant data points. Techniques like approximate nearest neighbor (ANN) search are often used to speed up this process.

Visit the following resources to learn more:

• @article@What is Retrieval-Augmented Generation (RAG)?
• @article@What Is Retrieval-Augmented Generation, aka RAG?