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Retrieval Augmented Generation (RAG) is a popular technique to get LLMs to answer questions based off your own knowledge base. "Agentic RAG" adds planning, tool use, and reflection to a RAG flow. In this session, we'll extend our most popular open-source RAG solution with a reflection step, prompting the LLM to realize whether it needs to repeat the retrieval in order to improve the answer quality.

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