# NanGePlus/RagLangChainTest

<https://repo.masters-masters.com/en/repos/NanGePlus/RagLangChainTest>

[Home](https://repo.masters-masters.com/en) › [NanGePlus](https://repo.masters-masters.com/en/owners/NanGePlus) › [RagLangChainTest](https://repo.masters-masters.com/en/repos/NanGePlus/RagLangChainTest)

NanGePlus/RagLangChainTest has 353 stars on GitHub. Its RepoMasters card: Alpha tier. 在本项目中模拟健康档案私有知识库构建和检索全流程，通过一份代码实现了同时支持多种大模型（如OpenAI、阿里通义千问等）的RAG（检索增强生成）功…

| Field | Value |
| --- | --- |
| Owner | [NanGePlus](https://repo.masters-masters.com/en/owners/NanGePlus) |
| Stars | 353 |
| Forks | 71 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | None |
| Created | 2024 |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [NanGePlus/RagLangChainTest](https://github.com/NanGePlus/RagLangChainTest) |

## Repository

在本项目中模拟健康档案私有知识库构建和检索全流程，通过一份代码实现了同时支持多种大模型（如OpenAI、阿里通义千问等）的RAG（检索增强生成）功能:(1)离线步骤:文档加载-\>文档切分-\>向量化-\>灌入向量数据库；在线步骤:获取用户问题-\>用户问题向量化-\>检索向量数据库-\>将检索结果和用户问题填入prompt模版-\>用最终的prompt调用LLM-\>由LLM生成回复

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.