What is RAG?
RAG is an architectural pattern in generative AI designed to enhance the accuracy and relevance of responses generated by Large Language Models (LLMs). It works by retrieving external data from a vector database at the time a prompt is issued. This approach helps prevent hallucinations, which are inaccuracies or fabrications that LLMs might produce when they lack sufficient context or information.
RAG is an architectural pattern in generative AI designed to enhance the accuracy and relevance of responses generated by Large Language Models (LLMs). It works by retrieving external data from a vector database at the time a prompt is issued. This approach helps prevent hallucinations, which are inaccuracies or fabrications that LLMs might produce when they lack sufficient context or information.