从零开始用 Python 和 Ollama 实现简单 RAG 系统

AI 摘要

Hugging Face 博客发布了一篇教程，作者 ngxson 从零开始用 Python 和 ollama 实现一个简单的 RAG（检索增强生成）系统。文章解释了 RAG 的两个核心组件（检索模型和语言模型），并演示了如何通过嵌入模型、向量数据库和聊天机器人构建系统，使用 cat-facts 数据集作为示例。该教程旨在帮助读者理解 RAG 的基本原理和实现方法。

正文节选

Recently, Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm in the field of AI and Large Language Models (LLMs). RAG combines information retrieval with text generation to enhance language models' performance by incorporating external knowledge sources. This approach has shown promising results in various applications, such as question answering, dialogue systems, and content generation. In this blog post, we'll explore RAG and build a simple RAG system from scratch using P

发布时间：—

抓取时间：2026-08-03 01:40

来源机构：Hugging Face