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Retrieval Augmented Generation (RAG) is a technique that enables LLMs to retrieve and integrate information from external sources, such as structured databases or documents, to provide more nuanced and specialized responses. This makes it easier to create LLM-based applications that are tailored to specific industries or use cases. Additionally, RAG can help improve the accuracy and relevance of LLM-generated content.