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Explore the integration of Large Language Models (LLMs) with LangChain for document-based question answering using Retrieval-Augmented Generation (RAG) in this 10-minute video. Learn about the retrieval, augmentation, and generation phases of RAG, understanding how this technique enhances model accuracy by leveraging external data. Discover the strengths of combining information retrieval systems with generative capabilities to produce precise answers based on specific document content. Gain insights into RAG's limitations when dealing with common knowledge already comprehended by the foundational model. Access accompanying code on GitHub to further your understanding of this powerful AI technique for document analysis and natural language processing.