构建AI代理的7种代理性RAG系统架构
For me, 2024 has been a year when I was not just using LLMs for content generation but also understanding their internal working. In this quest to learn about LLMs, RAG and more, I discovered the potential of AI Agents—autonomous systems capable of executing tasks and making decisions with minimal human intervention. Going back to 2023, Retrieval-Augmented Generation (RAG) was in the limelight, and 2024 advanced with Agentic RAG workflows, driving innovation across industries. Looking ahead, 2025 is set to be the “Year of AI Agents,” where autonomous systems will revolutionize productivity and reshape industries, unlocking unprecedented possibilities with the Agentic RAG Systems.
对我来说，2024年不仅是使用LLMs进行内容生成的一年，也是理解其内部工作原理的一年。在学习LLMs、RAG等的过程中，我发现了AI代理的潜力——能够以最少的人类干预执行任务和做出决策的自主系统。回到2023年，检索增强生成（RAG）备受关注，而2024年随着Agentic RAG工作流程的推进，推动了各行业的创新。展望未来，2025年将成为“AI代理之年”，自主系统将革新生产力并重塑行业，利用Agentic RAG系统解锁前所未有的可能性。
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These workflows, powered by autonomous AI agents capable of complex decision-making and task execution, enhance productivity and reshape how individuals and organisations tackle problems. The shift from static tools to dynamic, agent-driven processes has unlocked unprecedented efficiencies, laying the groundwork for an even more innovative 2025. Today, we will talk about the types of Agentic RAG systems. In this guide, we will go through the architecture of types of Agentic RAG and more.
这些由能够进行复杂决策和任务执行的自主AI代理驱动的工作流程，提高了生产力并重塑了个人和组织解决问题的方式。从静态工具到动态、代理驱动的流程的转变解锁了前所未有的效率，为更加创新的2025奠定了基础。今天，我们将讨论Agentic RAG系统的类型。在本指南中，我们将介绍Agentic RAG类型的架构等内容。
To simply understand Agentic RAG, let’s dissect the term: It is the amalgamation of RAG + AI Agents. If you don’t know these terms, don’t worry! We will be diving into them shortly.
为了简单理解 Agentic RAG，让我们剖析这个术语：它是 RAG + AI Agents 的结合。如果你不懂这些术语，不用担心！我们很快就会深入探讨它们。
Now, I will shed light on both RAG and Agentic AI systems (AI Agents)
现在，我将阐明 RAG 和 Agentic AI 系统（AI Agents）
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RAG is a framework designed to enhance the performance of generativ...