RAG

Retrieval-Augmented Generation (RAG) is an innovative AI framework designed to enhance the performance of large language models (LLMs) by integrating external information into their generative processes. This approach addresses several limitations inherent in traditional LLMs, such as outdated knowledge and inaccuracies in generated responses. Overview of RAG RAG combines the generative capabilities of LLMs with…