How to Create a RAG Agent with Reflection

What if your AI agent could think twice before answering, catching mistakes and refining its responses on the fly? That’s the promise of integrating reflection steps into Retrieval-Augmented Generation (RAG) systems. While RAG is already a fantastic option—combining the power of external knowledge retrieval with language model generation—it’s not without its flaws. Irrelevant documents, misleading […]
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