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Docs: add data search update OneAPI guide and wechat (#607)
* Docs:update OneAPI guide * Docs:update use-cases weachat * Docs:add data search
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--- | ||
title: '知识库搜索参数' | ||
description: '知识库搜索原理' | ||
icon: 'language' | ||
draft: false | ||
toc: true | ||
weight: 106 | ||
--- | ||
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在知识库搜索的方式上,FastGPT提供了三种方式,分别为“语义检索”“增强语义检索”“混合检索”。 | ||
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![](/imgs/data_search1.png) | ||
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## 语义检索 | ||
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语义检索就是向量检索,同时把用户的问题和知识库内容向量化,然后通过“语义相关度匹配”的方式从知识库中查找到匹配的知识点。 | ||
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优点: | ||
- 相近语义理解 | ||
- 跨多语言理解(例如输入中文问题匹配英文知识点) | ||
- 多模态理解(文本,图片,音视频等) | ||
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## 增强语义检索 | ||
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在语义检索的基础上,增强“语义相关度匹配”并在搜索结束后进行 Rerank(重排)。 | ||
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Rerank(重排):把检索结果按“与用户问题语义”相关性,从高到低排序,简单的说就是把最匹配用户问题的检索结果排在前面。 | ||
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## 混合检索(推荐) | ||
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在向量检索的同时进行全文检索,并把两项检索的结果混合一起重排,以便选中匹配用户问题的最佳结果。 | ||
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全文检索:理解为全文关键词检索,通过关键词查询知识库,并返回包含关键词的文本片段。 | ||
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优点: | ||
- 精确匹配(姓名,编号,ID等) | ||
- 少量关键词匹配(当用户问题字数过少时向量检索效果非常不好) | ||
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混合检索结合了向量检索和全文检索的优点,并且对查询结果进行了重排,大大提高了命中率,推荐使用。 |
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BATCH_UPDATE_INTERVAL=60 | ||
``` | ||
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## 使用步骤 | ||
## One API使用步骤 | ||
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### 1. 登录 One API | ||
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