Contextual Retrieval

Contextual retrieval is the process of identifying and retrieving relevant information from a knowledge base or document corpus based on the specific context of a user's query. This step is crucial in RAG systems, as it ensures that the AI model has access to the most pertinent information when generating responses.

The retrieval process typically involves converting both the query and documents into vector representations using embeddings, allowing for efficient similarity search. The retrieved documents are then used to provide context for the language model, enabling it to generate more accurate and relevant responses.