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import { CodeGroup } from '@/app/components/develop/code.tsx'
import { Row, Col, Properties, Property, Heading, SubProperty, PropertyInstruction, Paragraph } from '@/app/components/develop/md.tsx'
# 知识库 API
<div>
### 鉴权
Dify Service API 使用 `API-Key` 进行鉴权。
建议开发者把 `API-Key` 放在后端存储,而非分享或者放在客户端存储,以免 `API-Key` 泄露,导致财产损失。
所有 API 请求都应在 **`Authorization`** HTTP Header 中包含您的 `API-Key`,如下所示:
<CodeGroup title="Code">
```javascript
Authorization: Bearer {API_KEY}
```
</CodeGroup>
</div>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/document/create-by-text'
method='POST'
title='通过文本创建文档'
name='#create-by-text'
/>
<Row>
<Col>
此接口基于已存在知识库,在此知识库的基础上通过文本创建新的文档
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
</Properties>
### Request Body
<Properties>
<Property name='name' type='string' key='name'>
文档名称
</Property>
<Property name='text' type='string' key='text'>
文档内容
</Property>
<Property name='doc_type' type='string' key='doc_type'>
文档类型(选填)
- <code>book</code> 图书 Book
- <code>web_page</code> 网页 Web page
- <code>paper</code> 学术论文/文章 Academic paper/article
- <code>social_media_post</code> 社交媒体帖子 Social media post
- <code>wikipedia_entry</code> 维基百科条目 Wikipedia entry
- <code>personal_document</code> 个人文档 Personal document
- <code>business_document</code> 商业文档 Business document
- <code>im_chat_log</code> 即时通讯记录 Chat log
- <code>synced_from_notion</code> Notion同步文档 Notion document
- <code>synced_from_github</code> GitHub同步文档 GitHub document
- <code>others</code> 其他文档类型 Other document types
</Property>
<Property name='doc_metadata' type='object' key='doc_metadata'>
文档元数据(如提供文档类型则必填)。字段因文档类型而异:
针对图书 For <code>book</code>:
- <code>title</code> 书名 Book title
- <code>language</code> 图书语言 Book language
- <code>author</code> 作者 Book author
- <code>publisher</code> 出版社 Publisher name
- <code>publication_date</code> 出版日期 Publication date
- <code>isbn</code> ISBN号码 ISBN number
- <code>category</code> 图书分类 Book category
针对网页 For <code>web_page</code>:
- <code>title</code> 页面标题 Page title
- <code>url</code> 页面网址 Page URL
- <code>language</code> 页面语言 Page language
- <code>publish_date</code> 发布日期 Publish date
- <code>author/publisher</code> 作者/发布者 Author or publisher
- <code>topic/keywords</code> 主题/关键词 Topic or keywords
- <code>description</code> 页面描述 Page description
请查看 [api/services/dataset_service.py](https://github.com/langgenius/dify/blob/main/api/services/dataset_service.py#L475) 了解各文档类型所需字段的详细信息。
针对"其他"类型文档接受任何有效的JSON对象
</Property>
<Property name='indexing_technique' type='string' key='indexing_technique'>
索引方式
- <code>high_quality</code> 高质量:使用 embedding 模型进行嵌入,构建为向量数据库索引
- <code>economy</code> 经济:使用 keyword table index 的倒排索引进行构建
</Property>
<Property name='doc_form' type='string' key='doc_form'>
索引内容的形式
- <code>text_model</code> text 文档直接 embedding经济模式默认为该模式
- <code>hierarchical_model</code> parent-child 模式
- <code>qa_model</code> Q&A 模式:为分片文档生成 Q&A 对,然后对问题进行 embedding
</Property>
<Property name='doc_language' type='string' key='doc_language'>
在 Q&A 模式下,指定文档的语言,例如:<code>English</code>、<code>Chinese</code>
</Property>
<Property name='process_rule' type='object' key='process_rule'>
处理规则
- <code>mode</code> (string) 清洗、分段模式 automatic 自动 / custom 自定义
- <code>rules</code> (object) 自定义规则(自动模式下,该字段为空)
- <code>pre_processing_rules</code> (array[object]) 预处理规则
- <code>id</code> (string) 预处理规则的唯一标识符
- 枚举:
- <code>remove_extra_spaces</code> 替换连续空格、换行符、制表符
- <code>remove_urls_emails</code> 删除 URL、电子邮件地址
- <code>enabled</code> (bool) 是否选中该规则,不传入文档 ID 时代表默认值
- <code>segmentation</code> (object) 分段规则
- <code>separator</code> 自定义分段标识符,目前仅允许设置一个分隔符。默认为 <code>\n</code>
- <code>max_tokens</code> 最大长度token默认为 1000
- <code>parent_mode</code> 父分段的召回模式 <code>full-doc</code> 全文召回 / <code>paragraph</code> 段落召回
- <code>subchunk_segmentation</code> (object) 子分段规则
- <code>separator</code> 分段标识符,目前仅允许设置一个分隔符。默认为 <code>***</code>
- <code>max_tokens</code> 最大长度 (token) 需要校验小于父级的长度
- <code>chunk_overlap</code> 分段重叠指的是在对数据进行分段时,段与段之间存在一定的重叠部分(选填)
</Property>
<PropertyInstruction>当知识库未设置任何参数的时候,首次上传需要提供以下参数,未提供则使用默认选项:</PropertyInstruction>
<Property name='retrieval_model' type='object' key='retrieval_model'>
检索模式
- <code>search_method</code> (string) 检索方法
- <code>hybrid_search</code> 混合检索
- <code>semantic_search</code> 语义检索
- <code>full_text_search</code> 全文检索
- <code>reranking_enable</code> (bool) 是否开启rerank
- <code>reranking_model</code> (object) Rerank 模型配置
- <code>reranking_provider_name</code> (string) Rerank 模型的提供商
- <code>reranking_model_name</code> (string) Rerank 模型的名称
- <code>top_k</code> (int) 召回条数
- <code>score_threshold_enabled</code> (bool)是否开启召回分数限制
- <code>score_threshold</code> (float) 召回分数限制
</Property>
<Property name='embedding_model' type='string' key='embedding_model'>
Embedding 模型名称
</Property>
<Property name='embedding_model_provider' type='string' key='embedding_model_provider'>
Embedding 模型供应商
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets/{dataset_id}/document/create-by-text"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/document/create-by-text' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{"name": "text","text": "text","indexing_technique": "high_quality","process_rule": {"mode": "automatic"}}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/document/create-by-text' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json' \
--data-raw '{
"name": "text",
"text": "text",
"indexing_technique": "high_quality",
"process_rule": {
"mode": "automatic"
}
}'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"document": {
"id": "",
"position": 1,
"data_source_type": "upload_file",
"data_source_info": {
"upload_file_id": ""
},
"dataset_process_rule_id": "",
"name": "text.txt",
"created_from": "api",
"created_by": "",
"created_at": 1695690280,
"tokens": 0,
"indexing_status": "waiting",
"error": null,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"archived": false,
"display_status": "queuing",
"word_count": 0,
"hit_count": 0,
"doc_form": "text_model"
},
"batch": ""
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/document/create-by-file'
method='POST'
title='通过文件创建文档 '
name='#create-by-file'
/>
<Row>
<Col>
此接口基于已存在知识库,在此知识库的基础上通过文件创建新的文档
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
</Properties>
### Request Body
<Properties>
<Property name='data' type='multipart/form-data json string' key='data'>
- <code>original_document_id</code> 源文档 ID选填
- 用于重新上传文档或修改文档清洗、分段配置,缺失的信息从源文档复制
- 源文档不可为归档的文档
- 当传入 <code>original_document_id</code> 时,代表文档进行更新操作,<code>process_rule</code> 为可填项目,不填默认使用源文档的分段方式
- 未传入 <code>original_document_id</code> 时,代表文档进行新增操作,<code>process_rule</code> 为必填
- <code>indexing_technique</code> 索引方式
- <code>high_quality</code> 高质量:使用 embedding 模型进行嵌入,构建为向量数据库索引
- <code>economy</code> 经济:使用 keyword table index 的倒排索引进行构建
- <code>doc_form</code> 索引内容的形式
- <code>text_model</code> text 文档直接 embedding经济模式默认为该模式
- <code>hierarchical_model</code> parent-child 模式
- <code>qa_model</code> Q&A 模式:为分片文档生成 Q&A 对,然后对问题进行 embedding
- <code>doc_type</code> 文档类型选填Type of document (optional)
- <code>book</code> 图书
文档记录一本书籍或出版物
- <code>web_page</code> 网页
网页内容的文档记录
- <code>paper</code> 学术论文/文章
学术论文或研究文章的记录
- <code>social_media_post</code> 社交媒体帖子
社交媒体上的帖子内容
- <code>wikipedia_entry</code> 维基百科条目
维基百科的词条内容
- <code>personal_document</code> 个人文档
个人相关的文档记录
- <code>business_document</code> 商业文档
商业相关的文档记录
- <code>im_chat_log</code> 即时通讯记录
即时通讯的聊天记录
- <code>synced_from_notion</code> Notion同步文档
从Notion同步的文档内容
- <code>synced_from_github</code> GitHub同步文档
从GitHub同步的文档内容
- <code>others</code> 其他文档类型
其他未列出的文档类型
- <code>doc_metadata</code> 文档元数据(如提供文档类型则必填
字段因文档类型而异
针对图书类型 For <code>book</code>:
- <code>title</code> 书名
书籍的标题
- <code>language</code> 图书语言
书籍的语言
- <code>author</code> 作者
书籍的作者
- <code>publisher</code> 出版社
出版社的名称
- <code>publication_date</code> 出版日期
书籍的出版日期
- <code>isbn</code> ISBN号码
书籍的ISBN编号
- <code>category</code> 图书分类
书籍的分类类别
针对网页类型 For <code>web_page</code>:
- <code>title</code> 页面标题
网页的标题
- <code>url</code> 页面网址
网页的URL地址
- <code>language</code> 页面语言
网页的语言
- <code>publish_date</code> 发布日期
网页的发布日期
- <code>author/publisher</code> 作者/发布者
网页的作者或发布者
- <code>topic/keywords</code> 主题/关键词
网页的主题或关键词
- <code>description</code> 页面描述
网页的描述信息
请查看 [api/services/dataset_service.py](https://github.com/langgenius/dify/blob/main/api/services/dataset_service.py#L475) 了解各文档类型所需字段的详细信息。
针对"其他"类型文档接受任何有效的JSON对象
- <code>doc_language</code> 在 Q&A 模式下,指定文档的语言,例如:<code>English</code>、<code>Chinese</code>
- <code>process_rule</code> 处理规则
- <code>mode</code> (string) 清洗、分段模式 automatic 自动 / custom 自定义
- <code>rules</code> (object) 自定义规则(自动模式下,该字段为空)
- <code>pre_processing_rules</code> (array[object]) 预处理规则
- <code>id</code> (string) 预处理规则的唯一标识符
- 枚举:
- <code>remove_extra_spaces</code> 替换连续空格、换行符、制表符
- <code>remove_urls_emails</code> 删除 URL、电子邮件地址
- <code>enabled</code> (bool) 是否选中该规则,不传入文档 ID 时代表默认值
- <code>segmentation</code> (object) 分段规则
- <code>separator</code> 自定义分段标识符,目前仅允许设置一个分隔符。默认为 \n
- <code>max_tokens</code> 最大长度token默认为 1000
- <code>parent_mode</code> 父分段的召回模式 <code>full-doc</code> 全文召回 / <code>paragraph</code> 段落召回
- <code>subchunk_segmentation</code> (object) 子分段规则
- <code>separator</code> 分段标识符,目前仅允许设置一个分隔符。默认为 <code>***</code>
- <code>max_tokens</code> 最大长度 (token) 需要校验小于父级的长度
- <code>chunk_overlap</code> 分段重叠指的是在对数据进行分段时,段与段之间存在一定的重叠部分(选填)
</Property>
<Property name='file' type='multipart/form-data' key='file'>
需要上传的文件。
</Property>
<PropertyInstruction>当知识库未设置任何参数的时候,首次上传需要提供以下参数,未提供则使用默认选项:</PropertyInstruction>
<Property name='retrieval_model' type='object' key='retrieval_model'>
检索模式
- <code>search_method</code> (string) 检索方法
- <code>hybrid_search</code> 混合检索
- <code>semantic_search</code> 语义检索
- <code>full_text_search</code> 全文检索
- <code>reranking_enable</code> (bool) 是否开启rerank
- <code>reranking_model</code> (object) Rerank 模型配置
- <code>reranking_provider_name</code> (string) Rerank 模型的提供商
- <code>reranking_model_name</code> (string) Rerank 模型的名称
- <code>top_k</code> (int) 召回条数
- <code>score_threshold_enabled</code> (bool)是否开启召回分数限制
- <code>score_threshold</code> (float) 召回分数限制
</Property>
<Property name='embedding_model' type='string' key='embedding_model'>
Embedding 模型名称
</Property>
<Property name='embedding_model_provider' type='string' key='embedding_model_provider'>
Embedding 模型供应商
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets/{dataset_id}/document/create-by-file"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/document/create-by-file' \\\n--header 'Authorization: Bearer {api_key}' \\\n--form 'data="{"indexing_technique":"high_quality","process_rule":{"rules":{"pre_processing_rules":[{"id":"remove_extra_spaces","enabled":true},{"id":"remove_urls_emails","enabled":true}],"segmentation":{"separator":"###","max_tokens":500}},"mode":"custom"}}";type=text/plain' \\\n--form 'file=@"/path/to/file"'`}
>
```bash {{ title: 'cURL' }}
curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/document/create-by-file' \
--header 'Authorization: Bearer {api_key}' \
--form 'data="{\"name\":\"Dify\",\"indexing_technique\":\"high_quality\",\"process_rule\":{\"rules\":{\"pre_processing_rules\":[{\"id\":\"remove_extra_spaces\",\"enabled\":true},{\"id\":\"remove_urls_emails\",\"enabled\":true}],\"segmentation\":{\"separator\":\"###\",\"max_tokens\":500}},\"mode\":\"custom\"}}";type=text/plain' \
--form 'file=@"/path/to/file"'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"document": {
"id": "",
"position": 1,
"data_source_type": "upload_file",
"data_source_info": {
"upload_file_id": ""
},
"dataset_process_rule_id": "",
"name": "Dify.txt",
"created_from": "api",
"created_by": "",
"created_at": 1695308667,
"tokens": 0,
"indexing_status": "waiting",
"error": null,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"archived": false,
"display_status": "queuing",
"word_count": 0,
"hit_count": 0,
"doc_form": "text_model"
},
"batch": ""
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets'
method='POST'
title='创建空知识库'
name='#create_empty_dataset'
/>
<Row>
<Col>
### Request Body
<Properties>
<Property name='name' type='string' key='name'>
知识库名称(必填)
</Property>
<Property name='description' type='string' key='description'>
知识库描述(选填)
</Property>
<Property name='indexing_technique' type='string' key='indexing_technique'>
索引模式(选填,建议填写)
- <code>high_quality</code> 高质量
- <code>economy</code> 经济
</Property>
<Property name='permission' type='string' key='permission'>
权限(选填,默认 only_me
- <code>only_me</code> 仅自己
- <code>all_team_members</code> 所有团队成员
- <code>partial_members</code> 部分团队成员
</Property>
<Property name='provider' type='string' key='provider'>
Provider选填默认 vendor
- <code>vendor</code> 上传文件
- <code>external</code> 外部知识库
</Property>
<Property name='external_knowledge_api_id' type='str' key='external_knowledge_api_id'>
外部知识库 API_ID选填
</Property>
<Property name='external_knowledge_id' type='str' key='external_knowledge_id'>
外部知识库 ID选填
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{"name": "name", "permission": "only_me"}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request POST '${props.apiBaseUrl}/datasets' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json' \
--data-raw '{
"name": "name",
"permission": "only_me"
}'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"id": "",
"name": "name",
"description": null,
"provider": "vendor",
"permission": "only_me",
"data_source_type": null,
"indexing_technique": null,
"app_count": 0,
"document_count": 0,
"word_count": 0,
"created_by": "",
"created_at": 1695636173,
"updated_by": "",
"updated_at": 1695636173,
"embedding_model": null,
"embedding_model_provider": null,
"embedding_available": null
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets'
method='GET'
title='知识库列表'
name='#dataset_list'
/>
<Row>
<Col>
### Query
<Properties>
<Property name='page' type='string' key='page'>
页码
</Property>
<Property name='limit' type='string' key='limit'>
返回条数,默认 20范围 1-100
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="GET"
label="/datasets"
targetCode={`curl --location --request GET '${props.apiBaseUrl}/datasets?page=1&limit=20' \\\n--header 'Authorization: Bearer {api_key}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request GET '${props.apiBaseUrl}/datasets?page=1&limit=20' \
--header 'Authorization: Bearer {api_key}'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"data": [
{
"id": "",
"name": "知识库名称",
"description": "描述信息",
"permission": "only_me",
"data_source_type": "upload_file",
"indexing_technique": "",
"app_count": 2,
"document_count": 10,
"word_count": 1200,
"created_by": "",
"created_at": "",
"updated_by": "",
"updated_at": ""
},
...
],
"has_more": true,
"limit": 20,
"total": 50,
"page": 1
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}'
method='DELETE'
title='删除知识库'
name='#delete_dataset'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="DELETE"
label="/datasets/{dataset_id}"
targetCode={`curl --location --request DELETE '${props.apiBaseUrl}/datasets/{dataset_id}' \\\n--header 'Authorization: Bearer {api_key}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request DELETE '${props.apiBaseUrl}/datasets/{dataset_id}' \
--header 'Authorization: Bearer {api_key}'
```
</CodeGroup>
<CodeGroup title="Response">
```text {{ title: 'Response' }}
204 No Content
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}/update-by-text'
method='POST'
title='通过文本更新文档'
name='#update-by-text'
/>
<Row>
<Col>
此接口基于已存在知识库,在此知识库的基础上通过文本更新文档
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
</Properties>
### Request Body
<Properties>
<Property name='name' type='string' key='name'>
文档名称(选填)
</Property>
<Property name='text' type='string' key='text'>
文档内容(选填)
</Property>
<Property name='doc_type' type='string' key='doc_type'>
文档类型(选填)
- <code>book</code> 图书 Book
- <code>web_page</code> 网页 Web page
- <code>paper</code> 学术论文/文章 Academic paper/article
- <code>social_media_post</code> 社交媒体帖子 Social media post
- <code>wikipedia_entry</code> 维基百科条目 Wikipedia entry
- <code>personal_document</code> 个人文档 Personal document
- <code>business_document</code> 商业文档 Business document
- <code>im_chat_log</code> 即时通讯记录 Chat log
- <code>synced_from_notion</code> Notion同步文档 Notion document
- <code>synced_from_github</code> GitHub同步文档 GitHub document
- <code>others</code> 其他文档类型 Other document types
</Property>
<Property name='doc_metadata' type='object' key='doc_metadata'>
文档元数据(如提供文档类型则必填)。字段因文档类型而异:
针对图书 For <code>book</code>:
- <code>title</code> 书名 Book title
- <code>language</code> 图书语言 Book language
- <code>author</code> 作者 Book author
- <code>publisher</code> 出版社 Publisher name
- <code>publication_date</code> 出版日期 Publication date
- <code>isbn</code> ISBN号码 ISBN number
- <code>category</code> 图书分类 Book category
针对网页 For <code>web_page</code>:
- <code>title</code> 页面标题 Page title
- <code>url</code> 页面网址 Page URL
- <code>language</code> 页面语言 Page language
- <code>publish_date</code> 发布日期 Publish date
- <code>author/publisher</code> 作者/发布者 Author or publisher
- <code>topic/keywords</code> 主题/关键词 Topic or keywords
- <code>description</code> 页面描述 Page description
请查看 [api/services/dataset_service.py](https://github.com/langgenius/dify/blob/main/api/services/dataset_service.py#L475) 了解各文档类型所需字段的详细信息。
针对"其他"类型文档接受任何有效的JSON对象
</Property>
<Property name='process_rule' type='object' key='process_rule'>
处理规则(选填)
- <code>mode</code> (string) 清洗、分段模式 automatic 自动 / custom 自定义
- <code>rules</code> (object) 自定义规则(自动模式下,该字段为空)
- <code>pre_processing_rules</code> (array[object]) 预处理规则
- <code>id</code> (string) 预处理规则的唯一标识符
- 枚举:
- <code>remove_extra_spaces</code> 替换连续空格、换行符、制表符
- <code>remove_urls_emails</code> 删除 URL、电子邮件地址
- <code>enabled</code> (bool) 是否选中该规则,不传入文档 ID 时代表默认值
- <code>segmentation</code> (object) 分段规则
- <code>separator</code> 自定义分段标识符,目前仅允许设置一个分隔符。默认为 \n
- <code>max_tokens</code> 最大长度token默认为 1000
- <code>parent_mode</code> 父分段的召回模式 <code>full-doc</code> 全文召回 / <code>paragraph</code> 段落召回
- <code>subchunk_segmentation</code> (object) 子分段规则
- <code>separator</code> 分段标识符,目前仅允许设置一个分隔符。默认为 <code>***</code>
- <code>max_tokens</code> 最大长度 (token) 需要校验小于父级的长度
- <code>chunk_overlap</code> 分段重叠指的是在对数据进行分段时,段与段之间存在一定的重叠部分(选填)
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets/{dataset_id}/documents/{document_id}/update-by-text"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/update-by-text' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{"name": "name","text": "text"}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/update-by-text' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json' \
--data-raw '{
"name": "name",
"text": "text"
}'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"document": {
"id": "",
"position": 1,
"data_source_type": "upload_file",
"data_source_info": {
"upload_file_id": ""
},
"dataset_process_rule_id": "",
"name": "name.txt",
"created_from": "api",
"created_by": "",
"created_at": 1695308667,
"tokens": 0,
"indexing_status": "waiting",
"error": null,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"archived": false,
"display_status": "queuing",
"word_count": 0,
"hit_count": 0,
"doc_form": "text_model"
},
"batch": ""
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}/update-by-file'
method='POST'
title='通过文件更新文档'
name='#update-by-file'
/>
<Row>
<Col>
此接口基于已存在知识库,在此知识库的基础上通过文件更新文档的操作。
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
</Properties>
### Request Body
<Properties>
<Property name='name' type='string' key='name'>
文档名称(选填)
</Property>
<Property name='file' type='multipart/form-data' key='file'>
需要上传的文件
</Property>
<Property name='process_rule' type='object' key='process_rule'>
处理规则(选填)
- <code>mode</code> (string) 清洗、分段模式 automatic 自动 / custom 自定义
- <code>rules</code> (object) 自定义规则(自动模式下,该字段为空)
- <code>pre_processing_rules</code> (array[object]) 预处理规则
- <code>id</code> (string) 预处理规则的唯一标识符
- 枚举:
- <code>remove_extra_spaces</code> 替换连续空格、换行符、制表符
- <code>remove_urls_emails</code> 删除 URL、电子邮件地址
- <code>enabled</code> (bool) 是否选中该规则,不传入文档 ID 时代表默认值
- <code>segmentation</code> (object) 分段规则
- <code>separator</code> 自定义分段标识符,目前仅允许设置一个分隔符。默认为 \n
- <code>max_tokens</code> 最大长度token默认为 1000
- <code>parent_mode</code> 父分段的召回模式 <code>full-doc</code> 全文召回 / <code>paragraph</code> 段落召回
- <code>subchunk_segmentation</code> (object) 子分段规则
- <code>separator</code> 分段标识符,目前仅允许设置一个分隔符。默认为 <code>***</code>
- <code>max_tokens</code> 最大长度 (token) 需要校验小于父级的长度
- <code>chunk_overlap</code> 分段重叠指的是在对数据进行分段时,段与段之间存在一定的重叠部分(选填)
- <code>doc_type</code> 文档类型选填Type of document (optional)
- <code>book</code> 图书
文档记录一本书籍或出版物
- <code>web_page</code> 网页
网页内容的文档记录
- <code>paper</code> 学术论文/文章
学术论文或研究文章的记录
- <code>social_media_post</code> 社交媒体帖子
社交媒体上的帖子内容
- <code>wikipedia_entry</code> 维基百科条目
维基百科的词条内容
- <code>personal_document</code> 个人文档
个人相关的文档记录
- <code>business_document</code> 商业文档
商业相关的文档记录
- <code>im_chat_log</code> 即时通讯记录
即时通讯的聊天记录
- <code>synced_from_notion</code> Notion同步文档
从Notion同步的文档内容
- <code>synced_from_github</code> GitHub同步文档
从GitHub同步的文档内容
- <code>others</code> 其他文档类型
其他未列出的文档类型
- <code>doc_metadata</code> 文档元数据(如提供文档类型则必填
字段因文档类型而异
针对图书类型 For <code>book</code>:
- <code>title</code> 书名
书籍的标题
- <code>language</code> 图书语言
书籍的语言
- <code>author</code> 作者
书籍的作者
- <code>publisher</code> 出版社
出版社的名称
- <code>publication_date</code> 出版日期
书籍的出版日期
- <code>isbn</code> ISBN号码
书籍的ISBN编号
- <code>category</code> 图书分类
书籍的分类类别
针对网页类型 For <code>web_page</code>:
- <code>title</code> 页面标题
网页的标题
- <code>url</code> 页面网址
网页的URL地址
- <code>language</code> 页面语言
网页的语言
- <code>publish_date</code> 发布日期
网页的发布日期
- <code>author/publisher</code> 作者/发布者
网页的作者或发布者
- <code>topic/keywords</code> 主题/关键词
网页的主题或关键词
- <code>description</code> 页面描述
网页的描述信息
请查看 [api/services/dataset_service.py](https://github.com/langgenius/dify/blob/main/api/services/dataset_service.py#L475) 了解各文档类型所需字段的详细信息。
针对"其他"类型文档接受任何有效的JSON对象
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets/{dataset_id}/documents/{document_id}/update-by-file"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/update-by-file' \\\n--header 'Authorization: Bearer {api_key}' \\\n--form 'data="{"name":"Dify","indexing_technique":"high_quality","process_rule":{"rules":{"pre_processing_rules":[{"id":"remove_extra_spaces","enabled":true},{"id":"remove_urls_emails","enabled":true}],"segmentation":{"separator":"###","max_tokens":500}},"mode":"custom"}}";type=text/plain' \\\n--form 'file=@"/path/to/file"'`}
>
```bash {{ title: 'cURL' }}
curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/update-by-file' \
--header 'Authorization: Bearer {api_key}' \
--form 'data="{\"name\":\"Dify\",\"indexing_technique\":\"high_quality\",\"process_rule\":{\"rules\":{\"pre_processing_rules\":[{\"id\":\"remove_extra_spaces\",\"enabled\":true},{\"id\":\"remove_urls_emails\",\"enabled\":true}],\"segmentation\":{\"separator\":\"###\",\"max_tokens\":500}},\"mode\":\"custom\"}}";type=text/plain' \
--form 'file=@"/path/to/file"'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"document": {
"id": "",
"position": 1,
"data_source_type": "upload_file",
"data_source_info": {
"upload_file_id": ""
},
"dataset_process_rule_id": "",
"name": "Dify.txt",
"created_from": "api",
"created_by": "",
"created_at": 1695308667,
"tokens": 0,
"indexing_status": "waiting",
"error": null,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"archived": false,
"display_status": "queuing",
"word_count": 0,
"hit_count": 0,
"doc_form": "text_model"
},
"batch": "20230921150427533684"
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{batch}/indexing-status'
method='GET'
title='获取文档嵌入状态(进度)'
name='#indexing_status'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='batch' type='string' key='batch'>
上传文档的批次号
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="GET"
label="/datasets/{dataset_id}/documents/{batch}/indexing-status"
targetCode={`curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{batch}/indexing-status' \\\n--header 'Authorization: Bearer {api_key}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{batch}/indexing-status' \
--header 'Authorization: Bearer {api_key}' \
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"data":[{
"id": "",
"indexing_status": "indexing",
"processing_started_at": 1681623462.0,
"parsing_completed_at": 1681623462.0,
"cleaning_completed_at": 1681623462.0,
"splitting_completed_at": 1681623462.0,
"completed_at": null,
"paused_at": null,
"error": null,
"stopped_at": null,
"completed_segments": 24,
"total_segments": 100
}]
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}'
method='DELETE'
title='删除文档'
name='#delete_document'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="DELETE"
label="/datasets/{dataset_id}/documents/{document_id}"
targetCode={`curl --location --request DELETE '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \\\n--header 'Authorization: Bearer {api_key}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request DELETE '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}' \
--header 'Authorization: Bearer {api_key}' \
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"result": "success"
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents'
method='GET'
title='知识库文档列表'
name='#dataset_document_list'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
</Properties>
### Query
<Properties>
<Property name='keyword' type='string' key='keyword'>
搜索关键词,可选,目前仅搜索文档名称
</Property>
<Property name='page' type='string' key='page'>
页码,可选
</Property>
<Property name='limit' type='string' key='limit'>
返回条数,可选,默认 20范围 1-100
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="GET"
label="/datasets/{dataset_id}/documents"
targetCode={`curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents' \\\n--header 'Authorization: Bearer {api_key}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents' \
--header 'Authorization: Bearer {api_key}' \
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"data": [
{
"id": "",
"position": 1,
"data_source_type": "file_upload",
"data_source_info": null,
"dataset_process_rule_id": null,
"name": "dify",
"created_from": "",
"created_by": "",
"created_at": 1681623639,
"tokens": 0,
"indexing_status": "waiting",
"error": null,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"archived": false
},
],
"has_more": false,
"limit": 20,
"total": 9,
"page": 1
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}/segments'
method='POST'
title='新增分段'
name='#create_new_segment'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
</Properties>
### Request Body
<Properties>
<Property name='segments' type='object list' key='segments'>
- <code>content</code> (text) 文本内容/问题内容,必填
- <code>answer</code> (text) 答案内容,非必填,如果知识库的模式为 Q&A 模式则传值
- <code>keywords</code> (list) 关键字,非必填
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets/{dataset_id}/documents/{document_id}/segments"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json' \\\n--data-raw '{"segments": [{"content": "1","answer": "1","keywords": ["a"]}]}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json' \
--data-raw '{
"segments": [
{
"content": "1",
"answer": "1",
"keywords": ["a"]
}
]
}'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"data": [{
"id": "",
"position": 1,
"document_id": "",
"content": "1",
"answer": "1",
"word_count": 25,
"tokens": 0,
"keywords": [
"a"
],
"index_node_id": "",
"index_node_hash": "",
"hit_count": 0,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"status": "completed",
"created_by": "",
"created_at": 1695312007,
"indexing_at": 1695312007,
"completed_at": 1695312007,
"error": null,
"stopped_at": null
}],
"doc_form": "text_model"
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}/segments'
method='GET'
title='查询文档分段'
name='#get_segment'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
</Properties>
### Query
<Properties>
<Property name='keyword' type='string' key='keyword'>
搜索关键词,可选
</Property>
<Property name='status' type='string' key='status'>
搜索状态completed
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="GET"
label="/datasets/{dataset_id}/documents/{document_id}/segments"
targetCode={`curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json'`}
>
```bash {{ title: 'cURL' }}
curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"data": [{
"id": "",
"position": 1,
"document_id": "",
"content": "1",
"answer": "1",
"word_count": 25,
"tokens": 0,
"keywords": [
"a"
],
"index_node_id": "",
"index_node_hash": "",
"hit_count": 0,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"status": "completed",
"created_by": "",
"created_at": 1695312007,
"indexing_at": 1695312007,
"completed_at": 1695312007,
"error": null,
"stopped_at": null
}],
"doc_form": "text_model"
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}'
method='DELETE'
title='删除文档分段'
name='#delete_segment'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
<Property name='segment_id' type='string' key='segment_id'>
文档分段ID
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="DELETE"
label="/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}"
targetCode={`curl --location --request DELETE '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json'`}
>
```bash {{ title: 'cURL' }}
curl --location --request DELETE '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"result": "success"
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}'
method='POST'
title='更新文档分段'
name='#update_segment'
/>
<Row>
<Col>
### POST
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
<Property name='segment_id' type='string' key='segment_id'>
文档分段ID
</Property>
</Properties>
### Request Body
<Properties>
<Property name='segment' type='object' key='segment'>
- <code>content</code> (text) 文本内容/问题内容,必填
- <code>answer</code> (text) 答案内容,非必填,如果知识库的模式为 Q&A 模式则传值
- <code>keywords</code> (list) 关键字,非必填
- <code>enabled</code> (bool) false/true非必填
- <code>regenerate_child_chunks</code> (bool) 是否重新生成子分段,非必填
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json'\\\n--data-raw '{\"segment\": {\"content\": \"1\",\"answer\": \"1\", \"keywords\": [\"a\"], \"enabled\": false}}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/segments/{segment_id}' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json' \
--data-raw '{
"segment": {
"content": "1",
"answer": "1",
"keywords": ["a"],
"enabled": false
}
}'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"data": [{
"id": "",
"position": 1,
"document_id": "",
"content": "1",
"answer": "1",
"word_count": 25,
"tokens": 0,
"keywords": [
"a"
],
"index_node_id": "",
"index_node_hash": "",
"hit_count": 0,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"status": "completed",
"created_by": "",
"created_at": 1695312007,
"indexing_at": 1695312007,
"completed_at": 1695312007,
"error": null,
"stopped_at": null
}],
"doc_form": "text_model"
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/documents/{document_id}/upload-file'
method='GET'
title='获取上传文件'
name='#get_upload_file'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
<Property name='document_id' type='string' key='document_id'>
文档 ID
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="GET"
label="/datasets/{dataset_id}/documents/{document_id}/upload-file"
targetCode={`curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/upload-file' \\\n--header 'Authorization: Bearer {api_key}' \\\n--header 'Content-Type: application/json'`}
>
```bash {{ title: 'cURL' }}
curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/documents/{document_id}/upload-file' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"id": "file_id",
"name": "file_name",
"size": 1024,
"extension": "txt",
"url": "preview_url",
"download_url": "download_url",
"mime_type": "text/plain",
"created_by": "user_id",
"created_at": 1728734540,
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Heading
url='/datasets/{dataset_id}/retrieve'
method='POST'
title='检索知识库'
name='#dataset_retrieval'
/>
<Row>
<Col>
### Path
<Properties>
<Property name='dataset_id' type='string' key='dataset_id'>
知识库 ID
</Property>
</Properties>
### Request Body
<Properties>
<Property name='query' type='string' key='query'>
检索关键词
</Property>
<Property name='retrieval_model' type='object' key='retrieval_model'>
检索参数(选填,如不填,按照默认方式召回)
- <code>search_method</code> (text) 检索方法:以下三个关键字之一,必填
- <code>keyword_search</code> 关键字检索
- <code>semantic_search</code> 语义检索
- <code>full_text_search</code> 全文检索
- <code>hybrid_search</code> 混合检索
- <code>reranking_enable</code> (bool) 是否启用 Reranking非必填如果检索模式为 semantic_search 模式或者 hybrid_search 则传值
- <code>reranking_mode</code> (object) Rerank 模型配置,非必填,如果启用了 reranking 则传值
- <code>reranking_provider_name</code> (string) Rerank 模型提供商
- <code>reranking_model_name</code> (string) Rerank 模型名称
- <code>weights</code> (float) 混合检索模式下语意检索的权重设置
- <code>top_k</code> (integer) 返回结果数量,非必填
- <code>score_threshold_enabled</code> (bool) 是否开启 score 阈值
- <code>score_threshold</code> (float) Score 阈值
</Property>
<Property name='external_retrieval_model' type='object' key='external_retrieval_model'>
未启用字段
</Property>
</Properties>
</Col>
<Col sticky>
<CodeGroup
title="Request"
tag="POST"
label="/datasets/{dataset_id}/retrieve"
targetCode={`curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/retrieve' \\\n--header 'Authorization: Bearer {api_key}'\\\n--header 'Content-Type: application/json'\\\n--data-raw '{
"query": "test",
"retrieval_model": {
"search_method": "keyword_search",
"reranking_enable": false,
"reranking_mode": null,
"reranking_model": {
"reranking_provider_name": "",
"reranking_model_name": ""
},
"weights": null,
"top_k": 1,
"score_threshold_enabled": false,
"score_threshold": null
}
}'`}
>
```bash {{ title: 'cURL' }}
curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/retrieve' \
--header 'Authorization: Bearer {api_key}' \
--header 'Content-Type: application/json' \
--data-raw '{
"query": "test",
"retrieval_model": {
"search_method": "keyword_search",
"reranking_enable": false,
"reranking_mode": null,
"reranking_model": {
"reranking_provider_name": "",
"reranking_model_name": ""
},
"weights": null,
"top_k": 2,
"score_threshold_enabled": false,
"score_threshold": null
}
}'
```
</CodeGroup>
<CodeGroup title="Response">
```json {{ title: 'Response' }}
{
"query": {
"content": "test"
},
"records": [
{
"segment": {
"id": "7fa6f24f-8679-48b3-bc9d-bdf28d73f218",
"position": 1,
"document_id": "a8c6c36f-9f5d-4d7a-8472-f5d7b75d71d2",
"content": "Operation guide",
"answer": null,
"word_count": 847,
"tokens": 280,
"keywords": [
"install",
"java",
"base",
"scripts",
"jdk",
"manual",
"internal",
"opens",
"add",
"vmoptions"
],
"index_node_id": "39dd8443-d960-45a8-bb46-7275ad7fbc8e",
"index_node_hash": "0189157697b3c6a418ccf8264a09699f25858975578f3467c76d6bfc94df1d73",
"hit_count": 0,
"enabled": true,
"disabled_at": null,
"disabled_by": null,
"status": "completed",
"created_by": "dbcb1ab5-90c8-41a7-8b78-73b235eb6f6f",
"created_at": 1728734540,
"indexing_at": 1728734552,
"completed_at": 1728734584,
"error": null,
"stopped_at": null,
"document": {
"id": "a8c6c36f-9f5d-4d7a-8472-f5d7b75d71d2",
"data_source_type": "upload_file",
"name": "readme.txt",
"doc_type": null
}
},
"score": 3.730463140527718e-05,
"tsne_position": null
}
]
}
```
</CodeGroup>
</Col>
</Row>
<hr className='ml-0 mr-0' />
<Row>
<Col>
### 错误信息
<Properties>
<Property name='code' type='string' key='code'>
返回的错误代码
</Property>
</Properties>
<Properties>
<Property name='status' type='number' key='status'>
返回的错误状态
</Property>
</Properties>
<Properties>
<Property name='message' type='string' key='message'>
返回的错误信息
</Property>
</Properties>
</Col>
<Col>
<CodeGroup title="Example">
```json {{ title: 'Response' }}
{
"code": "no_file_uploaded",
"message": "Please upload your file.",
"status": 400
}
```
</CodeGroup>
</Col>
</Row>
<table className="max-w-auto border-collapse border border-slate-400" style={{ maxWidth: 'none', width: 'auto' }}>
<thead style={{ background: '#f9fafc' }}>
<tr>
<th className="p-2 border border-slate-300">code</th>
<th className="p-2 border border-slate-300">status</th>
<th className="p-2 border border-slate-300">message</th>
</tr>
</thead>
<tbody>
<tr>
<td className="p-2 border border-slate-300">no_file_uploaded</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">Please upload your file.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">too_many_files</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">Only one file is allowed.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">file_too_large</td>
<td className="p-2 border border-slate-300">413</td>
<td className="p-2 border border-slate-300">File size exceeded.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">unsupported_file_type</td>
<td className="p-2 border border-slate-300">415</td>
<td className="p-2 border border-slate-300">File type not allowed.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">high_quality_dataset_only</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">Current operation only supports 'high-quality' datasets.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">dataset_not_initialized</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">The dataset is still being initialized or indexing. Please wait a moment.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">archived_document_immutable</td>
<td className="p-2 border border-slate-300">403</td>
<td className="p-2 border border-slate-300">The archived document is not editable.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">dataset_name_duplicate</td>
<td className="p-2 border border-slate-300">409</td>
<td className="p-2 border border-slate-300">The dataset name already exists. Please modify your dataset name.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">invalid_action</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">Invalid action.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">document_already_finished</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">The document has been processed. Please refresh the page or go to the document details.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">document_indexing</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">The document is being processed and cannot be edited.</td>
</tr>
<tr>
<td className="p-2 border border-slate-300">invalid_metadata</td>
<td className="p-2 border border-slate-300">400</td>
<td className="p-2 border border-slate-300">The metadata content is incorrect. Please check and verify.</td>
</tr>
</tbody>
</table>
<div className="pb-4" />