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标签：RAG

RAG（检索增强生成）是一种结合信息检索与大语言模型的AI技术。本专栏涵盖知识库构建、向量搜索与提示工程，为开发者提供高效落地方案。

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如何系统学习AI工程？2026年最全资源推荐（含ML理论到RAG）

AI Insight

This document compiles the most helpful resources for understanding AI engineering, covering ML theory, foundation models, evaluation, prompt engineering, RAG, finetuning, dataset engineering, inference optimization, and architecture. It includes papers, case studies, blog posts, and tools referenced in the book 'AI Engineering'. 原文翻译：本文档汇集了理解AI工程最有用的资源，涵盖ML理论、基础模型、评估、提示工程、RAG、微调、数据集工程、推理优化和架构。包括《AI工程》一书中引用的论文、案例研究、博客文章和工具。

AI大模型2026/4/24

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如何构建本地混合RAG系统？ONNX与Foundry Local离线AI助手实现

AI Insight

This article presents a local hybrid RAG pattern combining lexical retrieval, ONNX-based semantic embeddings, and Foundry Local chat model for offline AI assistants. It covers architecture, implementation, and best practices for graceful degradation when semantic path fails. 原文翻译：本文介绍了一种本地混合RAG模式，结合词法检索、基于ONNX的语义嵌入和Foundry Local聊天模型，用于离线AI助手。涵盖架构、实现和最佳实践，确保语义路径不可用时优雅降级。

AI大模型2026/4/24

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RAG-Anything 如何实现多模态文档处理？2026年安装配置指南

AI Insight

RAG-Anything is a lightweight RAG system based on LightRAG, designed for multimodal document processing (PDF, images, tables, formulas, etc.). It provides end-to-end parsing, multimodal understanding, knowledge graph indexing, and modal-aware retrieval. This article covers installation, configuration, and usage examples with SiliconFlow platform. 原文翻译： RAG-Anything 是基于 LightRAG 的轻量级 RAG 系统，专为多模态文档（PDF、图片、表格、公式等）处理而设计。它提供端到端解析、多模态理解、知识图谱索引和模态感知检索。本文涵盖安装、配置以及使用硅基流动平台的示例。

AI大模型2026/4/24

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RAG-Anything是什么？香港大学开源全能RAG框架如何提升大模型性能？

AI Insight

RAG-Anything is an all-in-one RAG framework developed by HKUDS at the University of Hong Kong, open-sourced on GitHub. It aims to enhance LLM performance by integrating retrieval and generation, addressing hallucination and knowledge lag issues. 原文翻译：RAG-Anything是由香港大学HKUDS团队开发的全能型RAG框架，已在GitHub开源。它通过整合检索与生成技术，旨在提升大语言模型性能，解决幻觉和知识滞后问题。

AI大模型2026/4/24

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