7 Agentic RAG System Architectures to Build AI Agents VIEMIND Tech Consulting · Follow 5 min read · Just now https://viemind.ai 7 Agentic RAG System Architectures Self-reflective RAG Self-reflective RAG (Retrieval-Augmented Generation) is an advanced approach in natural language processing (NLP) that combines the capabilities of retrieval-based methods with generative models while adding an additional layer of self-reflection and logical reasoning. For instance, self-reflective RAG helps in retrieval, re-writing questions, discarding irrelevant or hallucinated documents and re-try retrieval. In short, it was introduced to capture the idea of using an LLM to self-correct poor-quality retrieval and/or generations Speculative RAG Speculative RAG is a smart framework designed to make large language models (LLMs) both faster and more accurate when answering questions. It does this by splitting the work between two […]
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