Retrieval-Augmented Generation (RAG) models are transforming the landscape of artificial intelligence by combining data retrieval and generative capabilities to provide contextually relevant and real-time answers. By addressing the limitations of traditional AI models, which struggle with up-to-date information and memory constraints, RAG models offer more accurate, personalized, and adaptable responses. Their growing popularity is driven…