Do you know what RAG (Retrieval-Augmented Generation) is?

RAG (Retrieval-Augmented Generation) is an approach in natural language processing that combines generative models (such as language models) with a mechanism for searching and retrieving relevant information from external data sources.

The idea is that instead of relying solely on the knowledge embedded in the model, the system first searches for relevant documents or facts in a database, and then uses this information to generate a more accurate and justified response.

Example of application:

• Question-answering systems, where the model first retrieves suitable texts from a knowledge base, and then formulates an answer based on them.

This improves the quality and relevance of answers, especially when the knowledge base is regularly updated.