In the landscape of natural language processing, the concept of Retrieval-Augmented Generation (RAG) has emerged as a groundbreaking approach with the potential to revolutionize the way machines interact with and understand human language. RAG is a unique fusion of two powerful techniques - retrieval and generation - that synergize to
