One approach to answering user inquiries with LLMs and reference material is called Retrieval Augmentation Generation, RAG for short. While RAG can serve in a multitude of question/answering scenarios, it can fall short in certain situations. A common challenge in conversation-based applications that leverages Large Language Models is constraining responses to a valid set of […]