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Author SHA1 Message Date
f22c22a635 记录个人部署的过程
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Build FastGPT images in Personal warehouse / build-fastgpt-images (push) Has been cancelled
2025-06-09 15:23:09 +08:00
yangxin
59b7c608fd 更改一下systemTitle
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2025-06-06 21:10:06 +08:00
180 changed files with 1394 additions and 3346 deletions

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@ -1,5 +1,5 @@
---
title: 'V4.9.1(包含升级脚本)'
title: 'V4.9.1'
description: 'FastGPT V4.9.1 更新说明'
icon: 'upgrade'
draft: false

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@ -7,28 +7,11 @@ toc: true
weight: 789
---
## 执行升级脚本
该脚本仅需商业版用户执行。
从任意终端,发起 1 个 HTTP 请求。其中 {{rootkey}} 替换成环境变量里的 `rootkey`{{host}} 替换成**FastGPT 域名**。
```bash
curl --location --request POST 'https://{{host}}/api/admin/initv4911' \
--header 'rootkey: {{rootkey}}' \
--header 'Content-Type: application/json'
```
**脚本功能**
1. 移动第三方知识库 API 配置。
## 🚀 新增内容
1. 商业版支持图片知识库。
2. 工作流中增加节点搜索功能。
3. 工作流中,子流程版本控制,可选择“保持最新版本”,无需手动更新。
4. 增加更多审计操作日志。
1. 工作流中增加节点搜索功能。
2. 工作流中,子流程版本控制,可选择“保持最新版本”,无需手动更新。
## ⚙️ 优化

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@ -1,5 +1,5 @@
---
title: 'V4.9.4(包含升级脚本)'
title: 'V4.9.4'
description: 'FastGPT V4.9.4 更新说明'
icon: 'upgrade'
draft: false

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@ -1,161 +0,0 @@
---
title: '第三方知识库开发'
description: '本节详细介绍如何在FastGPT上自己接入第三方知识库'
icon: 'language'
draft: false
toc: true
weight: 410
---
目前,互联网上拥有各种各样的文档库,例如飞书,语雀等等。 FastGPT 的不同用户可能使用的文档库不同,目前 FastGPT 内置了飞书、语雀文档库,如果需要接入其他文档库,可以参考本节内容。
## 统一的接口规范
为了实现对不同文档库的统一接入FastGPT 对第三方文档库进行了接口的规范,共包含 4 个接口内容,可以[查看 API 文件库接口](/docs/guide/knowledge_base/api_datase)。
所有内置的文档库,都是基于标准的 API 文件库进行扩展。可以参考`FastGPT/packages/service/core/dataset/apiDataset/yuqueDataset/api.ts`中的代码,进行其他文档库的扩展。一共需要完成 4 个接口开发:
1. 获取文件列表
2. 获取文件内容/文件链接
3. 获取原文预览地址
4. 获取文件详情信息
## 开始一个第三方文件库
为了方便讲解,这里以添加飞书知识库为例。
### 1. 添加第三方文档库参数
首先,要进入 FastGPT 项目路径下的`FastGPT\packages\global\core\dataset\apiDataset.d.ts`文件,添加第三方文档库 Server 类型。例如,语雀文档中,需要提供`userId``token`两个字段作为鉴权信息。
```ts
export type YuqueServer = {
userId: string;
token?: string;
basePath?: string;
};
```
{{% alert icon="🤖 " context="success" %}}
如果文档库有`根目录`选择的功能,需要设置添加一个字段`basePath`
{{% /alert %}}
### 2. 创建 Hook 文件
每个第三方文档库都会采用 Hook 的方式来实现一套 API 接口的维护Hook 里包含 4 个函数需要完成。
- 在`FastGPT\packages\service\core\dataset\apiDataset\`下创建一个文档库的文件夹,然后在文件夹下创建一个`api.ts`文件
- 在`api.ts`文件中,需要完成 4 个函数的定义,分别是:
- `listFiles`:获取文件列表
- `getFileContent`:获取文件内容/文件链接
- `getFileDetail`:获取文件详情信息
- `getFilePreviewUrl`:获取原文预览地址
### 3. 数据库添加配置字段
- 在`packages/service/core/dataset/schema.ts` 中添加第三方文档库的配置字段,类型统一设置成`Object`
- 在`FastGPT/packages/global/core/dataset/type.d.ts`中添加第三方文档库配置字段的数据类型,类型设置为第一步创建的参数。
![](/imgs/thirddataset-7.png)
{{% alert icon="🤖 " context="success" %}}
`schema.ts`文件修改后,需要重新启动 FastGPT 项目才会生效。
{{% /alert %}}
### 4. 添加知识库类型
`projects/app/src/web/core/dataset/constants.ts`中,添加自己的知识库类型
```TS
export const datasetTypeCourseMap: Record<`${DatasetTypeEnum}`, string> = {
[DatasetTypeEnum.folder]: '',
[DatasetTypeEnum.dataset]: '',
[DatasetTypeEnum.apiDataset]: '/docs/guide/knowledge_base/api_dataset/',
[DatasetTypeEnum.websiteDataset]: '/docs/guide/knowledge_base/websync/',
[DatasetTypeEnum.feishuShare]: '/docs/guide/knowledge_base/lark_share_dataset/',
[DatasetTypeEnum.feishuKnowledge]: '/docs/guide/knowledge_base/lark_knowledge_dataset/',
[DatasetTypeEnum.yuque]: '/docs/guide/knowledge_base/yuque_dataset/',
[DatasetTypeEnum.externalFile]: ''
};
```
{{% alert icon="🤖 " context="success" %}}
在 datasetTypeCourseMap 中添加自己的知识库类型,`' '`内是相应的文档说明,如果有的话,可以添加。
文档添加在`FastGPT\docSite\content\zh-cn\docs\guide\knowledge_base\`
{{% /alert %}}
## 添加前端
`FastGPT\packages\web\i18n\zh-CN\dataset.json`,`FastGPT\packages\web\i18n\en\dataset.json``FastGPT\packages\web\i18n\zh-Hant\dataset.json`中添加自己的 I18n 翻译,以中文翻译为例,大体需要如下几个内容:
![](/imgs/thirddataset-24.png)
`FastGPT\packages\web\components\common\Icon\icons\core\dataset\`添加自己的知识库图标,一共是两个,分为`Outline``Color`,分别是有颜色的和无色的,具体看如下图片。
![](/imgs/thirddataset-10.png)
`FastGPT\packages\web\components\common\Icon\constants.ts`文件中,添加自己的图标。 `import` 是图标的存放路径。
![](/imgs/thirddataset-9.png)
`FastGPT\packages\global\core\dataset\constants.ts`文件中,添加自己的知识库类型。
![](/imgs/thirddataset-8.png)
{{% alert icon="🤖 " context="success" %}}
`label`内容是自己之前通过 i18n 翻译添加的知识库名称的
`icon`是自己之前添加的 Icon , I18n 的添加看最后清单。
{{% /alert %}}
`FastGPT\projects\app\src\pages\dataset\list\index.tsx`文件下,添加如下内容。这个文件负责的是知识库列表页的`新建`按钮点击后的菜单,只有在该文件添加知识库后,才能创建知识库。
![](/imgs/thirddataset-12.png)
`FastGPT\projects\app\src\pageComponents\dataset\detail\Info\index.tsx`文件下,添加如下内容。
![](/imgs/thirddataset-18.png)
`FastGPT\projects\app\src\pageComponents\dataset\list\CreateModal.tsx`文件下,添加如下内容。
| | |
| --- | --- |
| ![](/imgs/thirddataset-19.png) | ![](/imgs/thirddataset-20.png) |
`FastGPT\projects\app\src\pageComponents\dataset\list\SideTag.tsx`文件下,添加如下内容。
![](/imgs/thirddataset-21.png)
`FastGPT\projects\app\src\web\core\dataset\context\datasetPageContext.tsx`文件下,添加如下内容。
![](/imgs/thirddataset-23.png)
## 添加配置表单
`FastGPT\projects\app\src\pageComponents\dataset\ApiDatasetForm.tsx`文件下,添加自己如下内容。这个文件负责的是创建知识库页的字段填写。
| | | |
| --- | --- | --- |
| ![](/imgs/thirddataset-13.png) | ![](/imgs/thirddataset-14.png) | ![](/imgs/thirddataset-15.png) |
代码中添加的两个组件是对根目录选择的渲染,对应设计的 api 的 getfiledetail 方法,如果你的文件不支持,你可以不引用。
```
{renderBaseUrlSelector()} //这是对`Base URL`字段的渲染
{renderDirectoryModal()} //点击`选择`后出现的`选择根目录`窗口,见图
```
| | |
| --- | --- |
| ![](/imgs/thirddataset-16.png) | ![](/imgs/thirddataset-17.png) |
如果知识库需要支持根目录,还需要在`ApiDatasetForm`文件中添加相关内容。
## 添加杂项
最后,需要在很多文件里添加`server`类型,这里由于文件过多,且不大,不一一列举文件的清单。只提供方法:使用自己编程工具的全局搜索功能,搜索`YuqueServer``yuqueServer`。在搜索到的文件中,逐一添加自己的知识库类型。
## 提示
建议知识库创建完成后,完整测试一遍知识库的功能,以确定有无漏洞,如果你的知识库添加有问题,且无法在文档找到对应的文件解决,一定是杂项没有添加完全,建议重复一次全局搜索`YuqueServer``yuqueServer`,检查是否有地方没有加上自己的类型。

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@ -6,8 +6,7 @@ export const fileImgs = [
{ suffix: '(doc|docs)', src: 'file/fill/doc' },
{ suffix: 'txt', src: 'file/fill/txt' },
{ suffix: 'md', src: 'file/fill/markdown' },
{ suffix: 'html', src: 'file/fill/html' },
{ suffix: '(jpg|jpeg|png|gif|bmp|webp|svg|ico|tiff|tif)', src: 'image' }
{ suffix: 'html', src: 'file/fill/html' }
// { suffix: '.', src: '/imgs/files/file.svg' }
];

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@ -2,5 +2,4 @@ export type AuthFrequencyLimitProps = {
eventId: string;
maxAmount: number;
expiredTime: Date;
num?: number;
};

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@ -34,7 +34,7 @@ export const valToStr = (val: any) => {
};
// replace {{variable}} to value
export function replaceVariable(text: any, obj: Record<string, string | number | undefined>) {
export function replaceVariable(text: any, obj: Record<string, string | number>) {
if (typeof text !== 'string') return text;
for (const key in obj) {

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@ -1,9 +1,4 @@
import type {
ChunkSettingsType,
DatasetDataIndexItemType,
DatasetDataFieldType,
DatasetSchemaType
} from './type';
import type { ChunkSettingsType, DatasetDataIndexItemType, DatasetSchemaType } from './type';
import type {
DatasetCollectionTypeEnum,
DatasetCollectionDataProcessModeEnum,
@ -12,14 +7,12 @@ import type {
ChunkTriggerConfigTypeEnum,
ParagraphChunkAIModeEnum
} from './constants';
import type { ParentIdType } from '../../common/parentFolder/type';
import type { LLMModelItemType } from '../ai/model.d';
import type { ParentIdType } from 'common/parentFolder/type';
/* ================= dataset ===================== */
export type DatasetUpdateBody = {
id: string;
apiDatasetServer?: DatasetSchemaType['apiDatasetServer'];
parentId?: ParentIdType;
name?: string;
avatar?: string;
@ -31,6 +24,9 @@ export type DatasetUpdateBody = {
websiteConfig?: DatasetSchemaType['websiteConfig'];
externalReadUrl?: DatasetSchemaType['externalReadUrl'];
defaultPermission?: DatasetSchemaType['defaultPermission'];
apiServer?: DatasetSchemaType['apiServer'];
yuqueServer?: DatasetSchemaType['yuqueServer'];
feishuServer?: DatasetSchemaType['feishuServer'];
chunkSettings?: DatasetSchemaType['chunkSettings'];
// sync schedule
@ -104,9 +100,6 @@ export type ExternalFileCreateDatasetCollectionParams = ApiCreateDatasetCollecti
externalFileUrl: string;
filename?: string;
};
export type ImageCreateDatasetCollectionParams = ApiCreateDatasetCollectionParams & {
collectionName: string;
};
/* ================= tag ===================== */
export type CreateDatasetCollectionTagParams = {
@ -132,9 +125,8 @@ export type PgSearchRawType = {
score: number;
};
export type PushDatasetDataChunkProps = {
q?: string;
a?: string;
imageId?: string;
q: string; // embedding content
a?: string; // bonus content
chunkIndex?: number;
indexes?: Omit<DatasetDataIndexItemType, 'dataId'>[];
};

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@ -1,5 +1,5 @@
import { RequireOnlyOne } from '../../../common/type/utils';
import type { ParentIdType } from '../../../common/parentFolder/type';
import { RequireOnlyOne } from '../../common/type/utils';
import type { ParentIdType } from '../../common/parentFolder/type.d';
export type APIFileItem = {
id: string;
@ -28,12 +28,6 @@ export type YuqueServer = {
basePath?: string;
};
export type ApiDatasetServerType = {
apiServer?: APIFileServer;
feishuServer?: FeishuServer;
yuqueServer?: YuqueServer;
};
// Api dataset api
export type APIFileListResponse = APIFileItem[];

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@ -1,31 +0,0 @@
import type { ApiDatasetServerType } from './type';
export const filterApiDatasetServerPublicData = (apiDatasetServer?: ApiDatasetServerType) => {
if (!apiDatasetServer) return undefined;
const { apiServer, yuqueServer, feishuServer } = apiDatasetServer;
return {
apiServer: apiServer
? {
baseUrl: apiServer.baseUrl,
authorization: '',
basePath: apiServer.basePath
}
: undefined,
yuqueServer: yuqueServer
? {
userId: yuqueServer.userId,
token: '',
basePath: yuqueServer.basePath
}
: undefined,
feishuServer: feishuServer
? {
appId: feishuServer.appId,
appSecret: '',
folderToken: feishuServer.folderToken
}
: undefined
};
};

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@ -6,80 +6,45 @@ export enum DatasetTypeEnum {
dataset = 'dataset',
websiteDataset = 'websiteDataset', // depp link
externalFile = 'externalFile',
apiDataset = 'apiDataset',
feishu = 'feishu',
yuque = 'yuque'
}
// @ts-ignore
export const ApiDatasetTypeMap: Record<
`${DatasetTypeEnum}`,
{
icon: string;
avatar: string;
label: any;
collectionLabel: string;
courseUrl?: string;
}
> = {
[DatasetTypeEnum.apiDataset]: {
icon: 'core/dataset/externalDatasetOutline',
avatar: 'core/dataset/externalDatasetColor',
label: i18nT('dataset:api_file'),
collectionLabel: i18nT('common:File'),
courseUrl: '/docs/guide/knowledge_base/api_dataset/'
},
[DatasetTypeEnum.feishu]: {
icon: 'core/dataset/feishuDatasetOutline',
avatar: 'core/dataset/feishuDatasetColor',
label: i18nT('dataset:feishu_dataset'),
collectionLabel: i18nT('common:File'),
courseUrl: '/docs/guide/knowledge_base/lark_dataset/'
},
[DatasetTypeEnum.yuque]: {
icon: 'core/dataset/yuqueDatasetOutline',
avatar: 'core/dataset/yuqueDatasetColor',
label: i18nT('dataset:yuque_dataset'),
collectionLabel: i18nT('common:File'),
courseUrl: '/docs/guide/knowledge_base/yuque_dataset/'
}
};
export const DatasetTypeMap: Record<
`${DatasetTypeEnum}`,
{
icon: string;
avatar: string;
label: any;
collectionLabel: string;
courseUrl?: string;
}
> = {
...ApiDatasetTypeMap,
export const DatasetTypeMap = {
[DatasetTypeEnum.folder]: {
icon: 'common/folderFill',
avatar: 'common/folderFill',
label: i18nT('dataset:folder_dataset'),
collectionLabel: i18nT('common:Folder')
},
[DatasetTypeEnum.dataset]: {
icon: 'core/dataset/commonDatasetOutline',
avatar: 'core/dataset/commonDatasetColor',
label: i18nT('dataset:common_dataset'),
collectionLabel: i18nT('common:File')
},
[DatasetTypeEnum.websiteDataset]: {
icon: 'core/dataset/websiteDatasetOutline',
avatar: 'core/dataset/websiteDatasetColor',
label: i18nT('dataset:website_dataset'),
collectionLabel: i18nT('common:Website'),
courseUrl: '/docs/guide/knowledge_base/websync/'
collectionLabel: i18nT('common:Website')
},
[DatasetTypeEnum.externalFile]: {
icon: 'core/dataset/externalDatasetOutline',
avatar: 'core/dataset/externalDatasetColor',
label: i18nT('dataset:external_file'),
collectionLabel: i18nT('common:File')
},
[DatasetTypeEnum.apiDataset]: {
icon: 'core/dataset/externalDatasetOutline',
label: i18nT('dataset:api_file'),
collectionLabel: i18nT('common:File')
},
[DatasetTypeEnum.feishu]: {
icon: 'core/dataset/feishuDatasetOutline',
label: i18nT('dataset:feishu_dataset'),
collectionLabel: i18nT('common:File')
},
[DatasetTypeEnum.yuque]: {
icon: 'core/dataset/yuqueDatasetOutline',
label: i18nT('dataset:yuque_dataset'),
collectionLabel: i18nT('common:File')
}
};
@ -112,8 +77,7 @@ export enum DatasetCollectionTypeEnum {
file = 'file',
link = 'link', // one link
externalFile = 'externalFile',
apiFile = 'apiFile',
images = 'images'
apiFile = 'apiFile'
}
export const DatasetCollectionTypeMap = {
[DatasetCollectionTypeEnum.folder]: {
@ -133,9 +97,6 @@ export const DatasetCollectionTypeMap = {
},
[DatasetCollectionTypeEnum.apiFile]: {
name: i18nT('common:core.dataset.apiFile')
},
[DatasetCollectionTypeEnum.images]: {
name: i18nT('dataset:core.dataset.Image collection')
}
};
@ -159,7 +120,6 @@ export const DatasetCollectionSyncResultMap = {
export enum DatasetCollectionDataProcessModeEnum {
chunk = 'chunk',
qa = 'qa',
imageParse = 'imageParse',
backup = 'backup',
auto = 'auto' // abandon
@ -173,10 +133,6 @@ export const DatasetCollectionDataProcessModeMap = {
label: i18nT('common:core.dataset.training.QA mode'),
tooltip: i18nT('common:core.dataset.import.QA Import Tip')
},
[DatasetCollectionDataProcessModeEnum.imageParse]: {
label: i18nT('dataset:training.Image mode'),
tooltip: i18nT('common:core.dataset.import.Chunk Split Tip')
},
[DatasetCollectionDataProcessModeEnum.backup]: {
label: i18nT('dataset:backup_mode'),
tooltip: i18nT('dataset:backup_mode')
@ -216,16 +172,14 @@ export enum ImportDataSourceEnum {
fileCustom = 'fileCustom',
externalFile = 'externalFile',
apiDataset = 'apiDataset',
reTraining = 'reTraining',
imageDataset = 'imageDataset'
reTraining = 'reTraining'
}
export enum TrainingModeEnum {
chunk = 'chunk',
qa = 'qa',
auto = 'auto',
image = 'image',
imageParse = 'imageParse'
image = 'image'
}
/* ------------ search -------------- */

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@ -8,19 +8,17 @@ export type CreateDatasetDataProps = {
chunkIndex?: number;
q: string;
a?: string;
imageId?: string;
indexes?: Omit<DatasetDataIndexItemType, 'dataId'>[];
};
export type UpdateDatasetDataProps = {
dataId: string;
q: string;
q?: string;
a?: string;
indexes?: (Omit<DatasetDataIndexItemType, 'dataId'> & {
dataId?: string; // pg data id
})[];
imageId?: string;
};
export type PatchIndexesProps =

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@ -1,13 +0,0 @@
export type DatasetImageSchema = {
_id: string;
teamId: string;
datasetId: string;
collectionId?: string;
name: string;
contentType: string;
size: number;
metadata?: Record<string, any>;
expiredTime?: Date;
createdAt: Date;
updatedAt: Date;
};

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@ -13,15 +13,9 @@ import type {
ChunkTriggerConfigTypeEnum
} from './constants';
import type { DatasetPermission } from '../../support/permission/dataset/controller';
import type {
ApiDatasetServerType,
APIFileServer,
FeishuServer,
YuqueServer
} from './apiDataset/type';
import type { APIFileServer, FeishuServer, YuqueServer } from './apiDataset';
import type { SourceMemberType } from 'support/user/type';
import type { DatasetDataIndexTypeEnum } from './data/constants';
import type { ParentIdType } from 'common/parentFolder/type';
export type ChunkSettingsType = {
trainingType?: DatasetCollectionDataProcessModeEnum;
@ -55,7 +49,7 @@ export type ChunkSettingsType = {
export type DatasetSchemaType = {
_id: string;
parentId: ParentIdType;
parentId?: string;
userId: string;
teamId: string;
tmbId: string;
@ -78,16 +72,14 @@ export type DatasetSchemaType = {
chunkSettings?: ChunkSettingsType;
inheritPermission: boolean;
apiDatasetServer?: ApiDatasetServerType;
apiServer?: APIFileServer;
feishuServer?: FeishuServer;
yuqueServer?: YuqueServer;
// abandon
autoSync?: boolean;
externalReadUrl?: string;
defaultPermission?: number;
apiServer?: APIFileServer;
feishuServer?: FeishuServer;
yuqueServer?: YuqueServer;
};
export type DatasetCollectionSchemaType = ChunkSettingsType & {
@ -140,13 +132,7 @@ export type DatasetDataIndexItemType = {
dataId: string; // pg data id
text: string;
};
export type DatasetDataFieldType = {
q: string; // large chunks or question
a?: string; // answer or custom content
imageId?: string;
};
export type DatasetDataSchemaType = DatasetDataFieldType & {
export type DatasetDataSchemaType = {
_id: string;
userId: string;
teamId: string;
@ -155,9 +141,13 @@ export type DatasetDataSchemaType = DatasetDataFieldType & {
collectionId: string;
chunkIndex: number;
updateTime: Date;
history?: (DatasetDataFieldType & {
q: string; // large chunks or question
a: string; // answer or custom content
history?: {
q: string;
a: string;
updateTime: Date;
})[];
}[];
forbid?: boolean;
fullTextToken: string;
indexes: DatasetDataIndexItemType[];
@ -189,7 +179,6 @@ export type DatasetTrainingSchemaType = {
dataId?: string;
q: string;
a: string;
imageId?: string;
chunkIndex: number;
indexSize?: number;
weight: number;
@ -255,18 +244,20 @@ export type DatasetCollectionItemType = CollectionWithDatasetType & {
};
/* ================= data ===================== */
export type DatasetDataItemType = DatasetDataFieldType & {
export type DatasetDataItemType = {
id: string;
teamId: string;
datasetId: string;
imagePreivewUrl?: string;
updateTime: Date;
collectionId: string;
sourceName: string;
sourceId?: string;
q: string;
a: string;
chunkIndex: number;
indexes: DatasetDataIndexItemType[];
isOwner: boolean;
// permission: DatasetPermission;
};
/* --------------- file ---------------------- */
@ -293,14 +284,3 @@ export type SearchDataResponseItemType = Omit<
score: { type: `${SearchScoreTypeEnum}`; value: number; index: number }[];
// score: number;
};
export type DatasetCiteItemType = {
_id: string;
q: string;
a?: string;
imagePreivewUrl?: string;
history?: DatasetDataSchemaType['history'];
updateTime: DatasetDataSchemaType['updateTime'];
index: DatasetDataSchemaType['chunkIndex'];
updated?: boolean;
};

View File

@ -2,15 +2,10 @@ import { TrainingModeEnum, DatasetCollectionTypeEnum } from './constants';
import { getFileIcon } from '../../common/file/icon';
import { strIsLink } from '../../common/string/tools';
export function getCollectionIcon({
type = DatasetCollectionTypeEnum.file,
name = '',
sourceId
}: {
type?: DatasetCollectionTypeEnum;
name?: string;
sourceId?: string;
}) {
export function getCollectionIcon(
type: DatasetCollectionTypeEnum = DatasetCollectionTypeEnum.file,
name = ''
) {
if (type === DatasetCollectionTypeEnum.folder) {
return 'common/folderFill';
}
@ -20,10 +15,7 @@ export function getCollectionIcon({
if (type === DatasetCollectionTypeEnum.virtual) {
return 'file/fill/manual';
}
if (type === DatasetCollectionTypeEnum.images) {
return 'core/dataset/imageFill';
}
return getSourceNameIcon({ sourceName: name, sourceId });
return getFileIcon(name);
}
export function getSourceNameIcon({
sourceName,

View File

@ -1,8 +1,5 @@
import type {
ApiDatasetDetailResponse,
FeishuServer,
YuqueServer
} from '@fastgpt/global/core/dataset/apiDataset/type';
import type { ApiDatasetDetailResponse } from '@fastgpt/global/core/dataset/apiDataset';
import { FeishuServer, YuqueServer } from '@fastgpt/global/core/dataset/apiDataset';
import type {
DeepRagSearchProps,
SearchDatasetDataResponse

View File

@ -142,26 +142,23 @@ export const updateRawTextBufferExpiredTime = async ({
};
export const clearExpiredRawTextBufferCron = async () => {
const gridBucket = getGridBucket();
const clearExpiredRawTextBuffer = async () => {
addLog.debug('Clear expired raw text buffer start');
const gridBucket = getGridBucket();
const data = await MongoRawTextBufferSchema.find(
{
'metadata.expiredTime': { $lt: new Date() }
},
'_id'
).lean();
return retryFn(async () => {
const data = await MongoRawTextBufferSchema.find(
{
'metadata.expiredTime': { $lt: new Date() }
},
'_id'
).lean();
for (const item of data) {
try {
for (const item of data) {
await gridBucket.delete(item._id);
} catch (error) {
addLog.error('Delete expired raw text buffer error', error);
}
}
addLog.debug('Clear expired raw text buffer end');
addLog.debug('Clear expired raw text buffer end');
});
};
setCron('*/10 * * * *', async () => {

View File

@ -7,13 +7,12 @@ import { MongoChatFileSchema, MongoDatasetFileSchema } from './schema';
import { detectFileEncoding, detectFileEncodingByPath } from '@fastgpt/global/common/file/tools';
import { CommonErrEnum } from '@fastgpt/global/common/error/code/common';
import { readRawContentByFileBuffer } from '../read/utils';
import { computeGridFsChunSize, gridFsStream2Buffer, stream2Encoding } from './utils';
import { gridFsStream2Buffer, stream2Encoding } from './utils';
import { addLog } from '../../system/log';
import { parseFileExtensionFromUrl } from '@fastgpt/global/common/string/tools';
import { Readable } from 'stream';
import { addRawTextBuffer, getRawTextBuffer } from '../../buffer/rawText/controller';
import { addMinutes } from 'date-fns';
import { retryFn } from '@fastgpt/global/common/system/utils';
export function getGFSCollection(bucket: `${BucketNameEnum}`) {
MongoDatasetFileSchema;
@ -65,7 +64,23 @@ export async function uploadFile({
// create a gridfs bucket
const bucket = getGridBucket(bucketName);
const chunkSizeBytes = computeGridFsChunSize(stats.size);
const fileSize = stats.size;
// 单块大小:尽可能大,但不超过 14MB不小于512KB
const chunkSizeBytes = (() => {
// 计算理想块大小:文件大小 ÷ 目标块数(10)。 并且每个块需要小于 14MB
const idealChunkSize = Math.min(Math.ceil(fileSize / 10), 14 * 1024 * 1024);
// 确保块大小至少为512KB
const minChunkSize = 512 * 1024; // 512KB
// 取理想块大小和最小块大小中的较大值
let chunkSize = Math.max(idealChunkSize, minChunkSize);
// 将块大小向上取整到最接近的64KB的倍数使其更整齐
chunkSize = Math.ceil(chunkSize / (64 * 1024)) * (64 * 1024);
return chunkSize;
})();
const stream = bucket.openUploadStream(filename, {
metadata,
@ -158,18 +173,24 @@ export async function getFileById({
export async function delFileByFileIdList({
bucketName,
fileIdList
fileIdList,
retry = 3
}: {
bucketName: `${BucketNameEnum}`;
fileIdList: string[];
retry?: number;
}): Promise<any> {
return retryFn(async () => {
try {
const bucket = getGridBucket(bucketName);
for await (const fileId of fileIdList) {
await bucket.delete(new Types.ObjectId(fileId));
}
});
} catch (error) {
if (retry > 0) {
return delFileByFileIdList({ bucketName, fileIdList, retry: retry - 1 });
}
}
}
export async function getDownloadStream({

View File

@ -105,20 +105,3 @@ export const stream2Encoding = async (stream: NodeJS.ReadableStream) => {
stream: copyStream
};
};
// 单块大小:尽可能大,但不超过 14MB不小于512KB
export const computeGridFsChunSize = (fileSize: number) => {
// 计算理想块大小:文件大小 ÷ 目标块数(10)。 并且每个块需要小于 14MB
const idealChunkSize = Math.min(Math.ceil(fileSize / 10), 14 * 1024 * 1024);
// 确保块大小至少为512KB
const minChunkSize = 512 * 1024; // 512KB
// 取理想块大小和最小块大小中的较大值
let chunkSize = Math.max(idealChunkSize, minChunkSize);
// 将块大小向上取整到最接近的64KB的倍数使其更整齐
chunkSize = Math.ceil(chunkSize / (64 * 1024)) * (64 * 1024);
return chunkSize;
};

View File

@ -22,7 +22,7 @@ export const getUploadModel = ({ maxSize = 500 }: { maxSize?: number }) => {
maxSize *= 1024 * 1024;
class UploadModel {
uploaderSingle = multer({
uploader = multer({
limits: {
fieldSize: maxSize
},
@ -41,7 +41,8 @@ export const getUploadModel = ({ maxSize = 500 }: { maxSize?: number }) => {
}
})
}).single('file');
async getUploadFile<T = any>(
async doUpload<T = any>(
req: NextApiRequest,
res: NextApiResponse,
originBucketName?: `${BucketNameEnum}`
@ -53,7 +54,7 @@ export const getUploadModel = ({ maxSize = 500 }: { maxSize?: number }) => {
bucketName?: `${BucketNameEnum}`;
}>((resolve, reject) => {
// @ts-ignore
this.uploaderSingle(req, res, (error) => {
this.uploader(req, res, (error) => {
if (error) {
return reject(error);
}
@ -93,58 +94,6 @@ export const getUploadModel = ({ maxSize = 500 }: { maxSize?: number }) => {
});
});
}
uploaderMultiple = multer({
limits: {
fieldSize: maxSize
},
preservePath: true,
storage: multer.diskStorage({
// destination: (_req, _file, cb) => {
// cb(null, tmpFileDirPath);
// },
filename: (req, file, cb) => {
if (!file?.originalname) {
cb(new Error('File not found'), '');
} else {
const { ext } = path.parse(decodeURIComponent(file.originalname));
cb(null, `${getNanoid()}${ext}`);
}
}
})
}).array('file', global.feConfigs?.uploadFileMaxSize);
async getUploadFiles<T = any>(req: NextApiRequest, res: NextApiResponse) {
return new Promise<{
files: FileType[];
data: T;
}>((resolve, reject) => {
// @ts-ignore
this.uploaderMultiple(req, res, (error) => {
if (error) {
console.log(error);
return reject(error);
}
// @ts-ignore
const files = req.files as FileType[];
resolve({
files: files.map((file) => ({
...file,
originalname: decodeURIComponent(file.originalname)
})),
data: (() => {
if (!req.body?.data) return {};
try {
return JSON.parse(req.body.data);
} catch (error) {
return {};
}
})()
});
});
});
}
}
return new UploadModel();

View File

@ -4,8 +4,7 @@ import { MongoFrequencyLimit } from './schema';
export const authFrequencyLimit = async ({
eventId,
maxAmount,
expiredTime,
num = 1
expiredTime
}: AuthFrequencyLimitProps) => {
try {
// 对应 eventId 的 account+1, 不存在的话,则创建一个
@ -15,7 +14,7 @@ export const authFrequencyLimit = async ({
expiredTime: { $gte: new Date() }
},
{
$inc: { amount: num },
$inc: { amount: 1 },
// If not exist, set the expiredTime
$setOnInsert: { expiredTime }
},

View File

@ -6,9 +6,7 @@ export enum TimerIdEnum {
updateStandardPlan = 'updateStandardPlan',
scheduleTriggerApp = 'scheduleTriggerApp',
notification = 'notification',
clearExpiredRawTextBuffer = 'clearExpiredRawTextBuffer',
clearExpiredDatasetImage = 'clearExpiredDatasetImage'
clearExpiredRawTextBuffer = 'clearExpiredRawTextBuffer'
}
export enum LockNotificationEnum {

View File

@ -20,10 +20,6 @@ export const getVlmModel = (model?: string) => {
?.find((item) => item.model === model || item.name === model);
};
export const getVlmModelList = () => {
return Array.from(global.llmModelMap.values())?.filter((item) => item.vision) || [];
};
export const getDefaultEmbeddingModel = () => global?.systemDefaultModel.embedding!;
export const getEmbeddingModel = (model?: string) => {
if (!model) return getDefaultEmbeddingModel();

View File

@ -3,11 +3,12 @@ import type {
ApiFileReadContentResponse,
APIFileReadResponse,
ApiDatasetDetailResponse,
APIFileServer
} from '@fastgpt/global/core/dataset/apiDataset/type';
APIFileServer,
APIFileItem
} from '@fastgpt/global/core/dataset/apiDataset';
import axios, { type Method } from 'axios';
import { addLog } from '../../../../common/system/log';
import { readFileRawTextByUrl } from '../../read';
import { addLog } from '../../../common/system/log';
import { readFileRawTextByUrl } from '../read';
import { type ParentIdType } from '@fastgpt/global/common/parentFolder/type';
import { type RequireOnlyOne } from '@fastgpt/global/common/type/utils';

View File

@ -1,10 +1,18 @@
import { useApiDatasetRequest } from './custom/api';
import { useYuqueDatasetRequest } from './yuqueDataset/api';
import { useFeishuDatasetRequest } from './feishuDataset/api';
import type { ApiDatasetServerType } from '@fastgpt/global/core/dataset/apiDataset/type';
import type {
APIFileServer,
YuqueServer,
FeishuServer
} from '@fastgpt/global/core/dataset/apiDataset';
import { useApiDatasetRequest } from './api';
import { useYuqueDatasetRequest } from '../yuqueDataset/api';
import { useFeishuDatasetRequest } from '../feishuDataset/api';
export const getApiDatasetRequest = async (apiDatasetServer?: ApiDatasetServerType) => {
const { apiServer, yuqueServer, feishuServer } = apiDatasetServer || {};
export const getApiDatasetRequest = async (data: {
apiServer?: APIFileServer;
yuqueServer?: YuqueServer;
feishuServer?: FeishuServer;
}) => {
const { apiServer, yuqueServer, feishuServer } = data;
if (apiServer) {
return useApiDatasetRequest({ apiServer });

View File

@ -5,10 +5,9 @@ import {
} from '@fastgpt/global/core/dataset/constants';
import type { CreateDatasetCollectionParams } from '@fastgpt/global/core/dataset/api.d';
import { MongoDatasetCollection } from './schema';
import type {
DatasetCollectionSchemaType,
DatasetDataFieldType,
DatasetSchemaType
import {
type DatasetCollectionSchemaType,
type DatasetSchemaType
} from '@fastgpt/global/core/dataset/type';
import { MongoDatasetTraining } from '../training/schema';
import { MongoDatasetData } from '../data/schema';
@ -16,7 +15,7 @@ import { delImgByRelatedId } from '../../../common/file/image/controller';
import { deleteDatasetDataVector } from '../../../common/vectorDB/controller';
import { delFileByFileIdList } from '../../../common/file/gridfs/controller';
import { BucketNameEnum } from '@fastgpt/global/common/file/constants';
import type { ClientSession } from '../../../common/mongo';
import { type ClientSession } from '../../../common/mongo';
import { createOrGetCollectionTags } from './utils';
import { rawText2Chunks } from '../read';
import { checkDatasetLimit } from '../../../support/permission/teamLimit';
@ -39,25 +38,20 @@ import {
getLLMMaxChunkSize
} from '@fastgpt/global/core/dataset/training/utils';
import { DatasetDataIndexTypeEnum } from '@fastgpt/global/core/dataset/data/constants';
import { deleteDatasetImage } from '../image/controller';
import { clearCollectionImages, removeDatasetImageExpiredTime } from '../image/utils';
export const createCollectionAndInsertData = async ({
dataset,
rawText,
relatedId,
imageIds,
createCollectionParams,
backupParse = false,
billId,
session
}: {
dataset: DatasetSchemaType;
rawText?: string;
rawText: string;
relatedId?: string;
imageIds?: string[];
createCollectionParams: CreateOneCollectionParams;
backupParse?: boolean;
billId?: string;
@ -75,13 +69,13 @@ export const createCollectionAndInsertData = async ({
// Set default params
const trainingType =
createCollectionParams.trainingType || DatasetCollectionDataProcessModeEnum.chunk;
const chunkSize = computeChunkSize({
...createCollectionParams,
trainingType,
llmModel: getLLMModel(dataset.agentModel)
});
const chunkSplitter = computeChunkSplitter(createCollectionParams);
const paragraphChunkDeep = computeParagraphChunkDeep(createCollectionParams);
const trainingMode = getTrainingModeByCollection({
trainingType: trainingType,
autoIndexes: createCollectionParams.autoIndexes,
imageIndex: createCollectionParams.imageIndex
});
if (
trainingType === DatasetCollectionDataProcessModeEnum.qa ||
@ -96,60 +90,35 @@ export const createCollectionAndInsertData = async ({
delete createCollectionParams.qaPrompt;
}
// 1. split chunks or create image chunks
const {
chunks,
chunkSize
}: {
chunks: Array<{
q?: string;
a?: string; // answer or custom content
imageId?: string;
indexes?: string[];
}>;
chunkSize?: number;
} = (() => {
if (rawText) {
const chunkSize = computeChunkSize({
...createCollectionParams,
trainingType,
llmModel: getLLMModel(dataset.agentModel)
});
// Process text chunks
const chunks = rawText2Chunks({
rawText,
chunkTriggerType: createCollectionParams.chunkTriggerType,
chunkTriggerMinSize: createCollectionParams.chunkTriggerMinSize,
chunkSize,
paragraphChunkDeep,
paragraphChunkMinSize: createCollectionParams.paragraphChunkMinSize,
maxSize: getLLMMaxChunkSize(getLLMModel(dataset.agentModel)),
overlapRatio: trainingType === DatasetCollectionDataProcessModeEnum.chunk ? 0.2 : 0,
customReg: chunkSplitter ? [chunkSplitter] : [],
backupParse
});
return { chunks, chunkSize };
}
if (imageIds) {
// Process image chunks
const chunks = imageIds.map((imageId: string) => ({
imageId,
indexes: []
}));
return { chunks };
}
throw new Error('Either rawText or imageIdList must be provided');
})();
// 1. split chunks
const chunks = rawText2Chunks({
rawText,
chunkTriggerType: createCollectionParams.chunkTriggerType,
chunkTriggerMinSize: createCollectionParams.chunkTriggerMinSize,
chunkSize,
paragraphChunkDeep,
paragraphChunkMinSize: createCollectionParams.paragraphChunkMinSize,
maxSize: getLLMMaxChunkSize(getLLMModel(dataset.agentModel)),
overlapRatio: trainingType === DatasetCollectionDataProcessModeEnum.chunk ? 0.2 : 0,
customReg: chunkSplitter ? [chunkSplitter] : [],
backupParse
});
// 2. auth limit
await checkDatasetLimit({
teamId,
insertLen: predictDataLimitLength(trainingMode, chunks)
insertLen: predictDataLimitLength(
getTrainingModeByCollection({
trainingType: trainingType,
autoIndexes: createCollectionParams.autoIndexes,
imageIndex: createCollectionParams.imageIndex
}),
chunks
)
});
const fn = async (session: ClientSession) => {
// 3. Create collection
// 3. create collection
const { _id: collectionId } = await createOneCollection({
...createCollectionParams,
trainingType,
@ -157,8 +126,8 @@ export const createCollectionAndInsertData = async ({
chunkSize,
chunkSplitter,
hashRawText: rawText ? hashStr(rawText) : undefined,
rawTextLength: rawText?.length,
hashRawText: hashStr(rawText),
rawTextLength: rawText.length,
nextSyncTime: (() => {
// ignore auto collections sync for website datasets
if (!dataset.autoSync && dataset.type === DatasetTypeEnum.websiteDataset) return undefined;
@ -200,7 +169,11 @@ export const createCollectionAndInsertData = async ({
vectorModel: dataset.vectorModel,
vlmModel: dataset.vlmModel,
indexSize: createCollectionParams.indexSize,
mode: trainingMode,
mode: getTrainingModeByCollection({
trainingType: trainingType,
autoIndexes: createCollectionParams.autoIndexes,
imageIndex: createCollectionParams.imageIndex
}),
prompt: createCollectionParams.qaPrompt,
billId: traingBillId,
data: chunks.map((item, index) => ({
@ -214,12 +187,7 @@ export const createCollectionAndInsertData = async ({
session
});
// 6. Remove images ttl index
await removeDatasetImageExpiredTime({
ids: imageIds,
collectionId,
session
});
// 6. remove related image ttl
if (relatedId) {
await MongoImage.updateMany(
{
@ -239,7 +207,7 @@ export const createCollectionAndInsertData = async ({
}
return {
collectionId: String(collectionId),
collectionId,
insertResults
};
};
@ -320,20 +288,17 @@ export const delCollectionRelatedSource = async ({
.map((item) => item?.metadata?.relatedImgId || '')
.filter(Boolean);
// Delete files and images in parallel
await Promise.all([
// Delete files
delFileByFileIdList({
bucketName: BucketNameEnum.dataset,
fileIdList
}),
// Delete images
delImgByRelatedId({
teamId,
relateIds: relatedImageIds,
session
})
]);
// Delete files
await delFileByFileIdList({
bucketName: BucketNameEnum.dataset,
fileIdList
});
// Delete images
await delImgByRelatedId({
teamId,
relateIds: relatedImageIds,
session
});
};
/**
* delete collection and it related data
@ -378,16 +343,16 @@ export async function delCollection({
datasetId: { $in: datasetIds },
collectionId: { $in: collectionIds }
}),
// Delete dataset_images
clearCollectionImages(collectionIds),
// Delete images if needed
...(delImg
? collections
.map((item) => item?.metadata?.relatedImgId || '')
.filter(Boolean)
.map((imageId) => deleteDatasetImage(imageId))
? [
delImgByRelatedId({
teamId,
relateIds: collections
.map((item) => item?.metadata?.relatedImgId || '')
.filter(Boolean)
})
]
: []),
// Delete files if needed
...(delFile
? [
delFileByFileIdList({

View File

@ -1,9 +1,11 @@
import { MongoDatasetCollection } from './schema';
import type { ClientSession } from '../../../common/mongo';
import { type ClientSession } from '../../../common/mongo';
import { MongoDatasetCollectionTags } from '../tag/schema';
import { readFromSecondary } from '../../../common/mongo/utils';
import type { CollectionWithDatasetType } from '@fastgpt/global/core/dataset/type';
import { DatasetCollectionSchemaType } from '@fastgpt/global/core/dataset/type';
import {
type CollectionWithDatasetType,
type DatasetCollectionSchemaType
} from '@fastgpt/global/core/dataset/type';
import {
DatasetCollectionDataProcessModeEnum,
DatasetCollectionSyncResultEnum,
@ -157,7 +159,9 @@ export const syncCollection = async (collection: CollectionWithDatasetType) => {
return {
type: DatasetSourceReadTypeEnum.apiFile,
sourceId,
apiDatasetServer: dataset.apiDatasetServer
apiServer: dataset.apiServer,
feishuServer: dataset.feishuServer,
yuqueServer: dataset.yuqueServer
};
})();
@ -229,37 +233,18 @@ export const syncCollection = async (collection: CollectionWithDatasetType) => {
QA: 独立进程
Chunk: Image Index -> Auto index -> chunk index
*/
export const getTrainingModeByCollection = ({
trainingType,
autoIndexes,
imageIndex
}: {
trainingType: DatasetCollectionDataProcessModeEnum;
autoIndexes?: boolean;
imageIndex?: boolean;
export const getTrainingModeByCollection = (collection: {
trainingType: DatasetCollectionSchemaType['trainingType'];
autoIndexes?: DatasetCollectionSchemaType['autoIndexes'];
imageIndex?: DatasetCollectionSchemaType['imageIndex'];
}) => {
if (
trainingType === DatasetCollectionDataProcessModeEnum.imageParse &&
global.feConfigs?.isPlus
) {
return TrainingModeEnum.imageParse;
}
if (trainingType === DatasetCollectionDataProcessModeEnum.qa) {
if (collection.trainingType === DatasetCollectionDataProcessModeEnum.qa) {
return TrainingModeEnum.qa;
}
if (
trainingType === DatasetCollectionDataProcessModeEnum.chunk &&
imageIndex &&
global.feConfigs?.isPlus
) {
if (collection.imageIndex && global.feConfigs?.isPlus) {
return TrainingModeEnum.image;
}
if (
trainingType === DatasetCollectionDataProcessModeEnum.chunk &&
autoIndexes &&
global.feConfigs?.isPlus
) {
if (collection.autoIndexes && global.feConfigs?.isPlus) {
return TrainingModeEnum.auto;
}
return TrainingModeEnum.chunk;

View File

@ -9,7 +9,6 @@ import { deleteDatasetDataVector } from '../../common/vectorDB/controller';
import { MongoDatasetDataText } from './data/dataTextSchema';
import { DatasetErrEnum } from '@fastgpt/global/common/error/code/dataset';
import { retryFn } from '@fastgpt/global/common/system/utils';
import { clearDatasetImages } from './image/utils';
/* ============= dataset ========== */
/* find all datasetId by top datasetId */
@ -103,10 +102,8 @@ export async function delDatasetRelevantData({
}),
//delete dataset_datas
MongoDatasetData.deleteMany({ teamId, datasetId: { $in: datasetIds } }),
// Delete collection image and file
// Delete Image and file
delCollectionRelatedSource({ collections }),
// Delete dataset Image
clearDatasetImages(datasetIds),
// Delete vector data
deleteDatasetDataVector({ teamId, datasetIds })
]);

View File

@ -1,56 +0,0 @@
import { getDatasetImagePreviewUrl } from '../image/utils';
import type { DatasetCiteItemType, DatasetDataSchemaType } from '@fastgpt/global/core/dataset/type';
export const formatDatasetDataValue = ({
q,
a,
imageId,
teamId,
datasetId
}: {
q: string;
a?: string;
imageId?: string;
teamId: string;
datasetId: string;
}): {
q: string;
a?: string;
imagePreivewUrl?: string;
} => {
if (!imageId) {
return {
q,
a
};
}
const previewUrl = getDatasetImagePreviewUrl({
imageId,
teamId,
datasetId,
expiredMinutes: 60 * 24 * 7 // 7 days
});
return {
q: `![${q.replaceAll('\n', '\\n')}](${previewUrl})`,
a,
imagePreivewUrl: previewUrl
};
};
export const getFormatDatasetCiteList = (list: DatasetDataSchemaType[]) => {
return list.map<DatasetCiteItemType>((item) => ({
_id: item._id,
...formatDatasetDataValue({
teamId: item.teamId,
datasetId: item.datasetId,
q: item.q,
a: item.a,
imageId: item.imageId
}),
history: item.history,
updateTime: item.updateTime,
index: item.chunkIndex
}));
};

View File

@ -37,7 +37,8 @@ const DatasetDataSchema = new Schema({
required: true
},
a: {
type: String
type: String,
default: ''
},
history: {
type: [
@ -73,9 +74,6 @@ const DatasetDataSchema = new Schema({
default: []
},
imageId: {
type: String
},
updateTime: {
type: Date,
default: () => new Date()

View File

@ -3,10 +3,10 @@ import type {
ApiFileReadContentResponse,
ApiDatasetDetailResponse,
FeishuServer
} from '@fastgpt/global/core/dataset/apiDataset/type';
} from '@fastgpt/global/core/dataset/apiDataset';
import { type ParentIdType } from '@fastgpt/global/common/parentFolder/type';
import axios, { type Method } from 'axios';
import { addLog } from '../../../../common/system/log';
import { addLog } from '../../../common/system/log';
type ResponseDataType = {
success: boolean;

View File

@ -1,166 +0,0 @@
import { addMinutes } from 'date-fns';
import { bucketName, MongoDatasetImageSchema } from './schema';
import { connectionMongo, Types } from '../../../common/mongo';
import fs from 'fs';
import type { FileType } from '../../../common/file/multer';
import fsp from 'fs/promises';
import { computeGridFsChunSize } from '../../../common/file/gridfs/utils';
import { setCron } from '../../../common/system/cron';
import { checkTimerLock } from '../../../common/system/timerLock/utils';
import { TimerIdEnum } from '../../../common/system/timerLock/constants';
import { addLog } from '../../../common/system/log';
const getGridBucket = () => {
return new connectionMongo.mongo.GridFSBucket(connectionMongo.connection.db!, {
bucketName: bucketName
});
};
export const createDatasetImage = async ({
teamId,
datasetId,
file,
expiredTime = addMinutes(new Date(), 30)
}: {
teamId: string;
datasetId: string;
file: FileType;
expiredTime?: Date;
}): Promise<{ imageId: string; previewUrl: string }> => {
const path = file.path;
const gridBucket = getGridBucket();
const metadata = {
teamId: String(teamId),
datasetId: String(datasetId),
expiredTime
};
const stats = await fsp.stat(path);
if (!stats.isFile()) return Promise.reject(`${path} is not a file`);
const readStream = fs.createReadStream(path, {
highWaterMark: 256 * 1024
});
const chunkSizeBytes = computeGridFsChunSize(stats.size);
const stream = gridBucket.openUploadStream(file.originalname, {
metadata,
contentType: file.mimetype,
chunkSizeBytes
});
// save to gridfs
await new Promise((resolve, reject) => {
readStream
.pipe(stream as any)
.on('finish', resolve)
.on('error', reject);
});
return {
imageId: String(stream.id),
previewUrl: ''
};
};
export const getDatasetImageReadData = async (imageId: string) => {
// Get file metadata to get contentType
const fileInfo = await MongoDatasetImageSchema.findOne({
_id: new Types.ObjectId(imageId)
}).lean();
if (!fileInfo) {
return Promise.reject('Image not found');
}
const gridBucket = getGridBucket();
return {
stream: gridBucket.openDownloadStream(new Types.ObjectId(imageId)),
fileInfo
};
};
export const getDatasetImageBase64 = async (imageId: string) => {
// Get file metadata to get contentType
const fileInfo = await MongoDatasetImageSchema.findOne({
_id: new Types.ObjectId(imageId)
}).lean();
if (!fileInfo) {
return Promise.reject('Image not found');
}
// Get image stream from GridFS
const { stream } = await getDatasetImageReadData(imageId);
// Convert stream to buffer
const chunks: Buffer[] = [];
return new Promise<string>((resolve, reject) => {
stream.on('data', (chunk: Buffer) => {
chunks.push(chunk);
});
stream.on('end', () => {
// Combine all chunks into a single buffer
const buffer = Buffer.concat(chunks);
// Convert buffer to base64 string
const base64 = buffer.toString('base64');
const dataUrl = `data:${fileInfo.contentType || 'image/jpeg'};base64,${base64}`;
resolve(dataUrl);
});
stream.on('error', reject);
});
};
export const deleteDatasetImage = async (imageId: string) => {
const gridBucket = getGridBucket();
try {
await gridBucket.delete(new Types.ObjectId(imageId));
} catch (error: any) {
const msg = error?.message;
if (msg.includes('File not found')) {
addLog.warn('Delete dataset image error', error);
return;
} else {
return Promise.reject(error);
}
}
};
export const clearExpiredDatasetImageCron = async () => {
const gridBucket = getGridBucket();
const clearExpiredDatasetImages = async () => {
addLog.debug('Clear expired dataset image start');
const data = await MongoDatasetImageSchema.find(
{
'metadata.expiredTime': { $lt: new Date() }
},
'_id'
).lean();
for (const item of data) {
try {
await gridBucket.delete(item._id);
} catch (error) {
addLog.error('Delete expired dataset image error', error);
}
}
addLog.debug('Clear expired dataset image end');
};
setCron('*/10 * * * *', async () => {
if (
await checkTimerLock({
timerId: TimerIdEnum.clearExpiredDatasetImage,
lockMinuted: 9
})
) {
try {
await clearExpiredDatasetImages();
} catch (error) {
addLog.error('clearExpiredDatasetImageCron error', error);
}
}
});
};

View File

@ -1,36 +0,0 @@
import type { Types } from '../../../common/mongo';
import { getMongoModel, Schema } from '../../../common/mongo';
export const bucketName = 'dataset_image';
const MongoDatasetImage = new Schema({
length: { type: Number, required: true },
chunkSize: { type: Number, required: true },
uploadDate: { type: Date, required: true },
filename: { type: String, required: true },
contentType: { type: String, required: true },
metadata: {
teamId: { type: String, required: true },
datasetId: { type: String, required: true },
collectionId: { type: String },
expiredTime: { type: Date, required: true }
}
});
MongoDatasetImage.index({ 'metadata.datasetId': 'hashed' });
MongoDatasetImage.index({ 'metadata.collectionId': 'hashed' });
MongoDatasetImage.index({ 'metadata.expiredTime': -1 });
export const MongoDatasetImageSchema = getMongoModel<{
_id: Types.ObjectId;
length: number;
chunkSize: number;
uploadDate: Date;
filename: string;
contentType: string;
metadata: {
teamId: string;
datasetId: string;
collectionId: string;
expiredTime: Date;
};
}>(`${bucketName}.files`, MongoDatasetImage);

View File

@ -1,101 +0,0 @@
import { ERROR_ENUM } from '@fastgpt/global/common/error/errorCode';
import { Types, type ClientSession } from '../../../common/mongo';
import { deleteDatasetImage } from './controller';
import { MongoDatasetImageSchema } from './schema';
import { addMinutes } from 'date-fns';
import jwt from 'jsonwebtoken';
export const removeDatasetImageExpiredTime = async ({
ids = [],
collectionId,
session
}: {
ids?: string[];
collectionId: string;
session?: ClientSession;
}) => {
if (ids.length === 0) return;
return MongoDatasetImageSchema.updateMany(
{
_id: {
$in: ids
.filter((id) => Types.ObjectId.isValid(id))
.map((id) => (typeof id === 'string' ? new Types.ObjectId(id) : id))
}
},
{
$unset: { 'metadata.expiredTime': '' },
$set: {
'metadata.collectionId': String(collectionId)
}
},
{ session }
);
};
export const getDatasetImagePreviewUrl = ({
imageId,
teamId,
datasetId,
expiredMinutes
}: {
imageId: string;
teamId: string;
datasetId: string;
expiredMinutes: number;
}) => {
const expiredTime = Math.floor(addMinutes(new Date(), expiredMinutes).getTime() / 1000);
const key = (process.env.FILE_TOKEN_KEY as string) ?? 'filetoken';
const token = jwt.sign(
{
teamId: String(teamId),
datasetId: String(datasetId),
exp: expiredTime
},
key
);
return `/api/core/dataset/image/${imageId}?token=${token}`;
};
export const authDatasetImagePreviewUrl = (token?: string) =>
new Promise<{
teamId: string;
datasetId: string;
}>((resolve, reject) => {
if (!token) {
return reject(ERROR_ENUM.unAuthFile);
}
const key = (process.env.FILE_TOKEN_KEY as string) ?? 'filetoken';
jwt.verify(token, key, (err, decoded: any) => {
if (err || !decoded?.teamId || !decoded?.datasetId) {
reject(ERROR_ENUM.unAuthFile);
return;
}
resolve({
teamId: decoded.teamId,
datasetId: decoded.datasetId
});
});
});
export const clearDatasetImages = async (datasetIds: string[]) => {
const images = await MongoDatasetImageSchema.find(
{
'metadata.datasetId': { $in: datasetIds.map((item) => String(item)) }
},
'_id'
).lean();
await Promise.all(images.map((image) => deleteDatasetImage(String(image._id))));
};
export const clearCollectionImages = async (collectionIds: string[]) => {
const images = await MongoDatasetImageSchema.find(
{
'metadata.collectionId': { $in: collectionIds.map((item) => String(item)) }
},
'_id'
).lean();
await Promise.all(images.map((image) => deleteDatasetImage(String(image._id))));
};

View File

@ -9,9 +9,13 @@ import { type TextSplitProps, splitText2Chunks } from '@fastgpt/global/common/st
import axios from 'axios';
import { readRawContentByFileBuffer } from '../../common/file/read/utils';
import { parseFileExtensionFromUrl } from '@fastgpt/global/common/string/tools';
import {
type APIFileServer,
type FeishuServer,
type YuqueServer
} from '@fastgpt/global/core/dataset/apiDataset';
import { getApiDatasetRequest } from './apiDataset';
import Papa from 'papaparse';
import type { ApiDatasetServerType } from '@fastgpt/global/core/dataset/apiDataset/type';
export const readFileRawTextByUrl = async ({
teamId,
@ -65,7 +69,9 @@ export const readDatasetSourceRawText = async ({
sourceId,
selector,
externalFileId,
apiDatasetServer,
apiServer,
feishuServer,
yuqueServer,
customPdfParse,
getFormatText
}: {
@ -78,7 +84,9 @@ export const readDatasetSourceRawText = async ({
selector?: string; // link selector
externalFileId?: string; // external file dataset
apiDatasetServer?: ApiDatasetServerType; // api dataset
apiServer?: APIFileServer; // api dataset
feishuServer?: FeishuServer; // feishu dataset
yuqueServer?: YuqueServer; // yuque dataset
}): Promise<{
title?: string;
rawText: string;
@ -120,7 +128,9 @@ export const readDatasetSourceRawText = async ({
};
} else if (type === DatasetSourceReadTypeEnum.apiFile) {
const { title, rawText } = await readApiServerFileContent({
apiDatasetServer,
apiServer,
feishuServer,
yuqueServer,
apiFileId: sourceId,
teamId,
tmbId
@ -137,13 +147,17 @@ export const readDatasetSourceRawText = async ({
};
export const readApiServerFileContent = async ({
apiDatasetServer,
apiServer,
feishuServer,
yuqueServer,
apiFileId,
teamId,
tmbId,
customPdfParse
}: {
apiDatasetServer?: ApiDatasetServerType;
apiServer?: APIFileServer;
feishuServer?: FeishuServer;
yuqueServer?: YuqueServer;
apiFileId: string;
teamId: string;
tmbId: string;
@ -152,7 +166,13 @@ export const readApiServerFileContent = async ({
title?: string;
rawText: string;
}> => {
return (await getApiDatasetRequest(apiDatasetServer)).getFileContent({
return (
await getApiDatasetRequest({
apiServer,
yuqueServer,
feishuServer
})
).getFileContent({
teamId,
tmbId,
apiFileId,
@ -166,11 +186,9 @@ export const rawText2Chunks = ({
chunkTriggerMinSize = 1000,
backupParse,
chunkSize = 512,
imageIdList,
...splitProps
}: {
rawText: string;
imageIdList?: string[];
chunkTriggerType?: ChunkTriggerConfigTypeEnum;
chunkTriggerMinSize?: number; // maxSize from agent model, not store
@ -181,7 +199,6 @@ export const rawText2Chunks = ({
q: string;
a: string;
indexes?: string[];
imageIdList?: string[];
}[] => {
const parseDatasetBackup2Chunks = (rawText: string) => {
const csvArr = Papa.parse(rawText).data as string[][];
@ -192,8 +209,7 @@ export const rawText2Chunks = ({
.map((item) => ({
q: item[0] || '',
a: item[1] || '',
indexes: item.slice(2),
imageIdList
indexes: item.slice(2)
}))
.filter((item) => item.q || item.a);
@ -215,8 +231,7 @@ export const rawText2Chunks = ({
return [
{
q: rawText,
a: '',
imageIdList
a: ''
}
];
}
@ -225,7 +240,7 @@ export const rawText2Chunks = ({
if (chunkTriggerType !== ChunkTriggerConfigTypeEnum.forceChunk) {
const textLength = rawText.trim().length;
if (textLength < chunkTriggerMinSize) {
return [{ q: rawText, a: '', imageIdList }];
return [{ q: rawText, a: '' }];
}
}
@ -238,7 +253,6 @@ export const rawText2Chunks = ({
return chunks.map((item) => ({
q: item,
a: '',
indexes: [],
imageIdList
indexes: []
}));
};

View File

@ -127,16 +127,14 @@ const DatasetSchema = new Schema({
type: Boolean,
default: true
},
apiDatasetServer: Object,
apiServer: Object,
feishuServer: Object,
yuqueServer: Object,
// abandoned
autoSync: Boolean,
externalReadUrl: String,
defaultPermission: Number,
apiServer: Object,
feishuServer: Object,
yuqueServer: Object
defaultPermission: Number
});
try {

View File

@ -28,7 +28,6 @@ import type { NodeInputKeyEnum } from '@fastgpt/global/core/workflow/constants';
import { datasetSearchQueryExtension } from './utils';
import type { RerankModelItemType } from '@fastgpt/global/core/ai/model.d';
import { addLog } from '../../../common/system/log';
import { formatDatasetDataValue } from '../data/controller';
export type SearchDatasetDataProps = {
histories: ChatItemType[];
@ -176,12 +175,6 @@ export async function searchDatasetData(
collectionFilterMatch
} = props;
// Constants data
const datasetDataSelectField =
'_id datasetId collectionId updateTime q a imageId chunkIndex indexes';
const datsaetCollectionSelectField =
'_id name fileId rawLink apiFileId externalFileId externalFileUrl';
/* init params */
searchMode = DatasetSearchModeMap[searchMode] ? searchMode : DatasetSearchModeEnum.embedding;
usingReRank = usingReRank && !!getDefaultRerankModel();
@ -470,14 +463,14 @@ export async function searchDatasetData(
collectionId: { $in: collectionIdList },
'indexes.dataId': { $in: results.map((item) => item.id?.trim()) }
},
datasetDataSelectField,
'_id datasetId collectionId updateTime q a chunkIndex indexes',
{ ...readFromSecondary }
).lean(),
MongoDatasetCollection.find(
{
_id: { $in: collectionIdList }
},
datsaetCollectionSelectField,
'_id name fileId rawLink apiFileId externalFileId externalFileUrl',
{ ...readFromSecondary }
).lean()
]);
@ -501,13 +494,8 @@ export async function searchDatasetData(
const result: SearchDataResponseItemType = {
id: String(data._id),
updateTime: data.updateTime,
...formatDatasetDataValue({
teamId,
datasetId: data.datasetId,
q: data.q,
a: data.a,
imageId: data.imageId
}),
q: data.q,
a: data.a,
chunkIndex: data.chunkIndex,
datasetId: String(data.datasetId),
collectionId: String(data.collectionId),
@ -609,14 +597,14 @@ export async function searchDatasetData(
{
_id: { $in: searchResults.map((item) => item.dataId) }
},
datasetDataSelectField,
'_id datasetId collectionId updateTime q a chunkIndex indexes',
{ ...readFromSecondary }
).lean(),
MongoDatasetCollection.find(
{
_id: { $in: searchResults.map((item) => item.collectionId) }
},
datsaetCollectionSelectField,
'_id name fileId rawLink apiFileId externalFileId externalFileUrl',
{ ...readFromSecondary }
).lean()
]);
@ -642,13 +630,8 @@ export async function searchDatasetData(
datasetId: String(data.datasetId),
collectionId: String(data.collectionId),
updateTime: data.updateTime,
...formatDatasetDataValue({
teamId,
datasetId: data.datasetId,
q: data.q,
a: data.a,
imageId: data.imageId
}),
q: data.q,
a: data.a,
chunkIndex: data.chunkIndex,
indexes: data.indexes,
...getCollectionSourceData(collection),

View File

@ -12,7 +12,10 @@ import { getCollectionWithDataset } from '../controller';
import { mongoSessionRun } from '../../../common/mongo/sessionRun';
import { type PushDataToTrainingQueueProps } from '@fastgpt/global/core/dataset/training/type';
import { i18nT } from '../../../../web/i18n/utils';
import { getLLMMaxChunkSize } from '../../../../global/core/dataset/training/utils';
import {
getLLMDefaultChunkSize,
getLLMMaxChunkSize
} from '../../../../global/core/dataset/training/utils';
export const lockTrainingDataByTeamId = async (teamId: string): Promise<any> => {
try {
@ -62,7 +65,7 @@ export async function pushDataListToTrainingQueue({
const getImageChunkMode = (data: PushDatasetDataChunkProps, mode: TrainingModeEnum) => {
if (mode !== TrainingModeEnum.image) return mode;
// 检查内容中,是否包含 ![](xxx) 的图片格式
const text = (data.q || '') + (data.a || '');
const text = data.q + data.a || '';
const regex = /!\[\]\((.*?)\)/g;
const match = text.match(regex);
if (match) {
@ -79,6 +82,9 @@ export async function pushDataListToTrainingQueue({
if (!agentModelData) {
return Promise.reject(i18nT('common:error_llm_not_config'));
}
if (mode === TrainingModeEnum.chunk || mode === TrainingModeEnum.auto) {
prompt = undefined;
}
const { model, maxToken, weight } = await (async () => {
if (mode === TrainingModeEnum.chunk) {
@ -95,7 +101,7 @@ export async function pushDataListToTrainingQueue({
weight: 0
};
}
if (mode === TrainingModeEnum.image || mode === TrainingModeEnum.imageParse) {
if (mode === TrainingModeEnum.image) {
const vllmModelData = getVlmModel(vlmModel);
if (!vllmModelData) {
return Promise.reject(i18nT('common:error_vlm_not_config'));
@ -111,9 +117,11 @@ export async function pushDataListToTrainingQueue({
})();
// filter repeat or equal content
const set = new Set();
const filterResult: Record<string, PushDatasetDataChunkProps[]> = {
success: [],
overToken: [],
repeat: [],
error: []
};
@ -132,7 +140,7 @@ export async function pushDataListToTrainingQueue({
.filter(Boolean);
// filter repeat content
if (!item.imageId && !item.q) {
if (!item.q) {
filterResult.error.push(item);
return;
}
@ -145,26 +153,32 @@ export async function pushDataListToTrainingQueue({
return;
}
filterResult.success.push(item);
if (set.has(text)) {
filterResult.repeat.push(item);
} else {
filterResult.success.push(item);
set.add(text);
}
});
// insert data to db
const insertLen = filterResult.success.length;
const failedDocuments: PushDatasetDataChunkProps[] = [];
// 使用 insertMany 批量插入
const batchSize = 500;
const batchSize = 200;
const insertData = async (startIndex: number, session: ClientSession) => {
const list = filterResult.success.slice(startIndex, startIndex + batchSize);
if (list.length === 0) return;
try {
const result = await MongoDatasetTraining.insertMany(
await MongoDatasetTraining.insertMany(
list.map((item) => ({
teamId,
tmbId,
datasetId: datasetId,
collectionId: collectionId,
datasetId,
collectionId,
billId,
mode: getImageChunkMode(item, mode),
prompt,
@ -175,25 +189,25 @@ export async function pushDataListToTrainingQueue({
indexSize,
weight: weight ?? 0,
indexes: item.indexes,
retryCount: 5,
...(item.imageId ? { imageId: item.imageId } : {})
retryCount: 5
})),
{
session,
ordered: false,
rawResult: true,
includeResultMetadata: false // 进一步减少返回数据
ordered: true
}
);
if (result.insertedCount !== list.length) {
return Promise.reject(`Insert data error, ${JSON.stringify(result)}`);
}
} catch (error: any) {
addLog.error(`Insert error`, error);
return Promise.reject(error);
// 如果有错误,将失败的文档添加到失败列表中
error.writeErrors?.forEach((writeError: any) => {
failedDocuments.push(data[writeError.index]);
});
console.log('failed', failedDocuments);
}
// 对于失败的文档,尝试单独插入
await MongoDatasetTraining.create(failedDocuments, { session });
return insertData(startIndex + batchSize, session);
};
@ -208,6 +222,7 @@ export async function pushDataListToTrainingQueue({
delete filterResult.success;
return {
insertLen
insertLen,
...filterResult
};
}

View File

@ -99,9 +99,6 @@ const TrainingDataSchema = new Schema({
],
default: []
},
imageId: {
type: String
},
errorMsg: String
});

View File

@ -3,9 +3,9 @@ import type {
ApiFileReadContentResponse,
YuqueServer,
ApiDatasetDetailResponse
} from '@fastgpt/global/core/dataset/apiDataset/type';
} from '@fastgpt/global/core/dataset/apiDataset';
import axios, { type Method } from 'axios';
import { addLog } from '../../../../common/system/log';
import { addLog } from '../../../common/system/log';
import { type ParentIdType } from '@fastgpt/global/common/parentFolder/type';
type ResponseDataType = {
@ -105,6 +105,7 @@ export const useYuqueDatasetRequest = ({ yuqueServer }: { yuqueServer: YuqueServ
if (!parentId) {
if (yuqueServer.basePath) parentId = yuqueServer.basePath;
}
let files: APIFileItem[] = [];
if (!parentId) {

View File

@ -358,7 +358,7 @@ async function filterDatasetQuote({
return replaceVariable(quoteTemplate, {
id: item.id,
q: item.q,
a: item.a || '',
a: item.a,
updateTime: formatTime2YMDHM(item.updateTime),
source: item.sourceName,
sourceId: String(item.sourceId || ''),

View File

@ -16,7 +16,6 @@ import { type AuthModeType, type AuthResponseType } from '../type';
import { DatasetTypeEnum } from '@fastgpt/global/core/dataset/constants';
import { type ParentIdType } from '@fastgpt/global/common/parentFolder/type';
import { DatasetDefaultPermissionVal } from '@fastgpt/global/support/permission/dataset/constant';
import { getDatasetImagePreviewUrl } from '../../../core/dataset/image/utils';
export const authDatasetByTmbId = async ({
tmbId,
@ -268,15 +267,6 @@ export async function authDatasetData({
updateTime: datasetData.updateTime,
q: datasetData.q,
a: datasetData.a,
imageId: datasetData.imageId,
imagePreivewUrl: datasetData.imageId
? getDatasetImagePreviewUrl({
imageId: datasetData.imageId,
teamId: datasetData.teamId,
datasetId: datasetData.datasetId,
expiredMinutes: 30
})
: undefined,
chunkIndex: datasetData.chunkIndex,
indexes: datasetData.indexes,
datasetId: String(datasetData.datasetId),

View File

@ -1,7 +1,7 @@
import { getWorkerController, WorkerNameEnum } from './utils';
export const preLoadWorker = async () => {
const max = Math.min(Number(global.systemEnv?.tokenWorkers || 30), 100);
const max = Number(global.systemEnv?.tokenWorkers || 30);
const workerController = getWorkerController({
name: WorkerNameEnum.countGptMessagesTokens,
maxReservedThreads: max

View File

@ -220,11 +220,9 @@ export const iconPaths = {
import('./icons/core/dataset/feishuDatasetOutline.svg'),
'core/dataset/fileCollection': () => import('./icons/core/dataset/fileCollection.svg'),
'core/dataset/fullTextRecall': () => import('./icons/core/dataset/fullTextRecall.svg'),
'core/dataset/imageFill': () => import('./icons/core/dataset/imageFill.svg'),
'core/dataset/manualCollection': () => import('./icons/core/dataset/manualCollection.svg'),
'core/dataset/mixedRecall': () => import('./icons/core/dataset/mixedRecall.svg'),
'core/dataset/modeEmbedding': () => import('./icons/core/dataset/modeEmbedding.svg'),
'core/dataset/otherDataset': () => import('./icons/core/dataset/otherDataset.svg'),
'core/dataset/questionExtension': () => import('./icons/core/dataset/questionExtension.svg'),
'core/dataset/rerank': () => import('./icons/core/dataset/rerank.svg'),
'core/dataset/searchfilter': () => import('./icons/core/dataset/searchfilter.svg'),
@ -232,6 +230,7 @@ export const iconPaths = {
'core/dataset/tableCollection': () => import('./icons/core/dataset/tableCollection.svg'),
'core/dataset/tag': () => import('./icons/core/dataset/tag.svg'),
'core/dataset/websiteDataset': () => import('./icons/core/dataset/websiteDataset.svg'),
'core/dataset/otherDataset': () => import('./icons/core/dataset/otherDataset.svg'),
'core/dataset/websiteDatasetColor': () => import('./icons/core/dataset/websiteDatasetColor.svg'),
'core/dataset/websiteDatasetOutline': () =>
import('./icons/core/dataset/websiteDatasetOutline.svg'),
@ -380,12 +379,10 @@ export const iconPaths = {
fullScreen: () => import('./icons/fullScreen.svg'),
help: () => import('./icons/help.svg'),
history: () => import('./icons/history.svg'),
image: () => import('./icons/image.svg'),
infoRounded: () => import('./icons/infoRounded.svg'),
kbTest: () => import('./icons/kbTest.svg'),
key: () => import('./icons/key.svg'),
keyPrimary: () => import('./icons/keyPrimary.svg'),
loading: () => import('./icons/loading.svg'),
menu: () => import('./icons/menu.svg'),
minus: () => import('./icons/minus.svg'),
'modal/AddClb': () => import('./icons/modal/AddClb.svg'),

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@ -1,3 +0,0 @@
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@ -1,331 +0,0 @@
import React, { useMemo, useRef, useState } from 'react';
import {
Box,
Flex,
type MenuItemProps,
type PlacementWithLogical,
type AvatarProps,
type BoxProps,
type DividerProps
} from '@chakra-ui/react';
import MyDivider from '../MyDivider';
import type { IconNameType } from '../Icon/type';
import { useSystem } from '../../../hooks/useSystem';
import Avatar from '../Avatar';
import MyPopover from '../MyPopover';
export type MenuItemType = 'primary' | 'danger' | 'gray' | 'grayBg';
export type MenuSizeType = 'sm' | 'md' | 'xs' | 'mini';
export type MenuItemData = {
label?: string;
children: Array<{
isActive?: boolean;
type?: MenuItemType;
icon?: IconNameType | string;
label: string | React.ReactNode;
description?: string;
onClick?: () => any;
menuItemStyles?: MenuItemProps;
menuList?: MenuItemData[];
}>;
};
export type Props = {
label?: string;
width?: number | string;
offset?: [number, number];
Trigger: React.ReactNode;
trigger?: 'hover' | 'click';
size?: MenuSizeType;
placement?: PlacementWithLogical;
hasArrow?: boolean;
onClose?: () => void;
menuList: MenuItemData[];
};
const typeMapStyle: Record<MenuItemType, { styles: MenuItemProps; iconColor?: string }> = {
primary: {
styles: {
_hover: {
backgroundColor: 'primary.50',
color: 'primary.600'
},
_focus: {
backgroundColor: 'primary.50',
color: 'primary.600'
},
_active: {
backgroundColor: 'primary.50',
color: 'primary.600'
}
},
iconColor: 'myGray.600'
},
gray: {
styles: {
_hover: {
backgroundColor: 'myGray.05',
color: 'primary.600'
},
_focus: {
backgroundColor: 'myGray.05',
color: 'primary.600'
},
_active: {
backgroundColor: 'myGray.05',
color: 'primary.600'
}
},
iconColor: 'myGray.400'
},
grayBg: {
styles: {
_hover: {
backgroundColor: 'myGray.05',
color: 'primary.600'
},
_focus: {
backgroundColor: 'myGray.05',
color: 'primary.600'
},
_active: {
backgroundColor: 'myGray.05',
color: 'primary.600'
}
},
iconColor: 'myGray.600'
},
danger: {
styles: {
color: 'red.600',
_hover: {
background: 'red.1'
},
_focus: {
background: 'red.1'
},
_active: {
background: 'red.1'
}
},
iconColor: 'red.600'
}
};
const sizeMapStyle: Record<
MenuSizeType,
{
iconStyle: AvatarProps;
labelStyle: BoxProps;
dividerStyle: DividerProps;
menuItemStyle: MenuItemProps;
}
> = {
mini: {
iconStyle: {
w: '14px'
},
labelStyle: {
fontSize: 'mini'
},
dividerStyle: {
my: 0.5
},
menuItemStyle: {
py: 1.5,
px: 2
}
},
xs: {
iconStyle: {
w: '14px'
},
labelStyle: {
fontSize: 'sm'
},
dividerStyle: {
my: 0.5
},
menuItemStyle: {
py: 1.5,
px: 2
}
},
sm: {
iconStyle: {
w: '1rem'
},
labelStyle: {
fontSize: 'sm'
},
dividerStyle: {
my: 1
},
menuItemStyle: {
py: 2,
px: 3,
_notLast: {
mb: 0.5
}
}
},
md: {
iconStyle: {
w: '2rem',
borderRadius: '6px'
},
labelStyle: {
fontSize: 'sm'
},
dividerStyle: {
my: 1
},
menuItemStyle: {
py: 2,
px: 3,
_notLast: {
mb: 0.5
}
}
}
};
const MenuItem = ({
item,
size,
onClose
}: {
item: MenuItemData['children'][number];
size: MenuSizeType;
onClose: () => void;
}) => {
return (
<Box
px={3}
py={2}
cursor="pointer"
borderRadius="md"
_hover={{
bg: 'primary.50',
color: 'primary.600'
}}
onClick={(e) => {
if (item.onClick) {
item.onClick();
}
if (!item.menuList) {
onClose();
}
}}
>
<Flex alignItems="center" w="100%">
{!!item.icon && (
<Avatar
src={item.icon as any}
mr={2}
{...sizeMapStyle[size].iconStyle}
color={item.isActive ? 'inherit' : typeMapStyle[item.type || 'primary'].iconColor}
/>
)}
<Box flex="1">
<Box
color={item.description ? 'myGray.900' : 'inherit'}
{...sizeMapStyle[size].labelStyle}
>
{item.label}
</Box>
{item.description && (
<Box color={'myGray.500'} fontSize={'mini'}>
{item.description}
</Box>
)}
</Box>
</Flex>
</Box>
);
};
const MultipleMenu = (props: Props) => {
const {
width = 'auto',
trigger = 'hover',
size = 'sm',
offset,
Trigger,
menuList,
hasArrow = false,
placement = 'bottom-start'
} = props;
const { isPc } = useSystem();
const formatTrigger = !isPc ? 'click' : trigger;
return (
<MyPopover
placement={placement}
offset={offset}
hasArrow={hasArrow}
trigger={formatTrigger}
w={width}
zIndex={999}
closeOnBlur={false}
autoFocus={false}
Trigger={Trigger}
>
{({ onClose }) => {
const onCloseFn = () => {
onClose();
props?.onClose?.();
};
return (
<Box
bg="white"
maxW="300px"
p="6px"
border={'1px solid #fff'}
boxShadow={'3'}
borderRadius={'md'}
>
{menuList.map((group, i) => (
<Box key={i}>
{i !== 0 && <MyDivider h={'1.5px'} {...sizeMapStyle[size].dividerStyle} />}
{group.label && (
<Box fontSize="sm" px={3} py={1} color="myGray.500">
{group.label}
</Box>
)}
{group.children.map((item, index) => {
return (
<Box key={index}>
{item.menuList ? (
<MultipleMenu
{...props}
placement={'left'}
trigger={'hover'}
menuList={item.menuList}
onClose={onCloseFn}
Trigger={
<Box>
<MenuItem item={item} size={size} onClose={onCloseFn} />
</Box>
}
hasArrow
/>
) : (
<MenuItem item={item} size={size} onClose={onCloseFn} />
)}
</Box>
);
})}
</Box>
))}
</Box>
);
}}
</MyPopover>
);
};
export default React.memo(MultipleMenu);

View File

@ -1,4 +1,4 @@
import React, { useCallback, useMemo, useRef, useState } from 'react';
import React, { useMemo, useRef, useState } from 'react';
import {
Menu,
MenuList,
@ -18,20 +18,9 @@ import { useSystem } from '../../../hooks/useSystem';
import Avatar from '../Avatar';
export type MenuItemType = 'primary' | 'danger' | 'gray' | 'grayBg';
export type MenuSizeType = 'sm' | 'md' | 'xs' | 'mini';
export type MenuItemData = {
label?: string;
children: Array<{
isActive?: boolean;
type?: MenuItemType;
icon?: IconNameType | string;
label: string | React.ReactNode;
description?: string;
onClick?: () => any;
menuItemStyles?: MenuItemProps;
}>;
};
export type Props = {
width?: number | string;
offset?: [number, number];
@ -40,7 +29,18 @@ export type Props = {
size?: MenuSizeType;
placement?: PlacementWithLogical;
menuList: MenuItemData[];
menuList: {
label?: string;
children: {
isActive?: boolean;
type?: MenuItemType;
icon?: IconNameType | string;
label: string | React.ReactNode;
description?: string;
onClick?: () => any;
menuItemStyles?: MenuItemProps;
}[];
}[];
};
const typeMapStyle: Record<MenuItemType, { styles: MenuItemProps; iconColor?: string }> = {

View File

@ -43,11 +43,11 @@ const MyPopover = ({
initialFocusRef={firstFieldRef}
onOpen={() => {
onOpen();
onOpenFunc?.();
onOpenFunc && onOpenFunc();
}}
onClose={() => {
onClose();
onCloseFunc?.();
onCloseFunc && onCloseFunc();
}}
placement={placement}
offset={offset}

View File

@ -6,7 +6,6 @@
"accept": "accept",
"action": "operate",
"assign_permission": "Permission change",
"audit_log": "audit",
"change_department_name": "Department Editor",
"change_member_name": "Member name change",
"change_member_name_self": "Change member name",
@ -33,13 +32,6 @@
"create_invoice": "Issuing invoices",
"create_org": "Create organization",
"create_sub_org": "Create sub-organization",
"dataset.api_file": "API Import",
"dataset.common_dataset": "Dataset",
"dataset.external_file": "External File",
"dataset.feishu_dataset": "Feishu Spreadsheet",
"dataset.folder_dataset": "Folder",
"dataset.website_dataset": "Website Sync",
"dataset.yuque_dataset": "Yuque Knowledge Base",
"delete": "delete",
"delete_api_key": "Delete the API key",
"delete_app": "Delete the workbench application",
@ -54,7 +46,6 @@
"delete_from_team": "Move out of the team",
"delete_group": "Delete a group",
"delete_org": "Delete organization",
"department": "department",
"edit_info": "Edit information",
"edit_member": "Edit user",
"edit_member_tip": "Name",
@ -145,12 +136,16 @@
"login": "Log in",
"manage_member": "Managing members",
"member": "member",
"department": "department",
"update": "update",
"save_and_publish": "save and publish",
"member_group": "Belonging to member group",
"move_app": "App location movement",
"move_dataset": "Mobile Knowledge Base",
"move_member": "Move member",
"move_org": "Move organization",
"notification_recieve": "Team notification reception",
"operation_log": "log",
"org": "organization",
"org_description": "Organization description",
"org_name": "Organization name",
@ -174,7 +169,6 @@
"restore_tip_title": "Recovery confirmation",
"retain_admin_permissions": "Keep administrator rights",
"retrain_collection": "Retrain the set",
"save_and_publish": "save and publish",
"search_log": "Search log",
"search_member": "Search for members",
"search_member_group_name": "Search member/group name",
@ -196,8 +190,14 @@
"type.Tool": "Tool",
"type.Tool set": "Toolset",
"type.Workflow bot": "Workflow",
"dataset.folder_dataset": "Folder",
"dataset.common_dataset": "Dataset",
"dataset.website_dataset": "Website Sync",
"dataset.external_file": "External File",
"dataset.api_file": "API Import",
"dataset.feishu_dataset": "Feishu Spreadsheet",
"dataset.yuque_dataset": "Yuque Knowledge Base",
"unlimited": "Unlimited",
"update": "update",
"update_api_key": "Update API key",
"update_app_collaborator": "Apply permission changes",
"update_app_info": "Application information modification",
@ -213,4 +213,4 @@
"user_team_leave_team": "Leave the team",
"user_team_leave_team_failed": "Failure to leave the team",
"waiting": "To be accepted"
}
}

View File

@ -71,13 +71,13 @@
"response_embedding_model_tokens": "Vector Model Tokens",
"response_hybrid_weight": "Embedding : Full text = {{emb}} : {{text}}",
"response_rerank_tokens": "Rearrange Model Tokens",
"search_results": "Search results",
"select": "Select",
"select_file": "Upload File",
"select_file_img": "Upload file / image",
"select_img": "Upload Image",
"source_cronJob": "Scheduled execution",
"stream_output": "Stream Output",
"to_dataset": "Go to the Knowledge Base",
"unsupported_file_type": "Unsupported file types",
"upload": "Upload",
"variable_invisable_in_share": "Custom variables are not visible in login-free links",

View File

@ -180,7 +180,7 @@
"code_error.user_error.balance_not_enough": "Insufficient Account Balance",
"code_error.user_error.bin_visitor_guest": "You Are Currently a Guest, Unauthorized to Operate",
"code_error.user_error.un_auth_user": "User Not Found",
"comfirm_import": "Confirm import",
"comfirm_import": "comfirm_import",
"comfirm_leave_page": "Confirm to Leave This Page?",
"comfirn_create": "Confirm Creation",
"commercial_function_tip": "Please Upgrade to the Commercial Version to Use This Feature: https://doc.fastgpt.cn/docs/commercial/intro/",
@ -403,6 +403,7 @@
"core.chat.response.module model": "Model",
"core.chat.response.module name": "Model Name",
"core.chat.response.module query": "Question/Search Term",
"core.chat.response.module quoteList": "Quote Content",
"core.chat.response.module similarity": "Similarity",
"core.chat.response.module temperature": "Temperature",
"core.chat.response.module time": "Run Time",
@ -433,6 +434,7 @@
"core.dataset.Text collection": "Text Dataset",
"core.dataset.apiFile": "API File",
"core.dataset.collection.Click top config website": "Click to Configure Website",
"core.dataset.collection.Collection name": "Dataset Name",
"core.dataset.collection.Collection raw text": "Dataset Content",
"core.dataset.collection.Empty Tip": "The Dataset is Empty",
"core.dataset.collection.QA Prompt": "QA Split Prompt",
@ -449,6 +451,7 @@
"core.dataset.collection.metadata.metadata": "Metadata",
"core.dataset.collection.metadata.read source": "View Original Content",
"core.dataset.collection.metadata.source": "Data Source",
"core.dataset.collection.metadata.source name": "Source Name",
"core.dataset.collection.metadata.source size": "Source Size",
"core.dataset.collection.status.active": "Ready",
"core.dataset.collection.status.error": "Error",
@ -740,7 +743,7 @@
"core.workflow.value": "Value",
"core.workflow.variable": "Variable",
"create": "Create",
"create_failed": "Create failed",
"create_failed": "Creation Failed",
"create_success": "Created Successfully",
"create_time": "Creation Time",
"cron_job_run_app": "Scheduled Task",
@ -785,6 +788,7 @@
"dataset.dataset_name": "Dataset Name",
"dataset.deleteFolderTips": "Confirm to Delete This Folder and All Its Contained Datasets? Data Cannot Be Recovered After Deletion, Please Confirm!",
"dataset.test.noResult": "No Search Results",
"dataset_data_import_q_placeholder": "Up to {{maxToken}} words.",
"dataset_data_input_a": "Answer",
"dataset_data_input_chunk": "Chunk",
"dataset_data_input_chunk_content": "Chunk",
@ -798,6 +802,7 @@
"delete_success": "Deleted Successfully",
"delete_warning": "Deletion Warning",
"embedding_model_not_config": "No index model is detected",
"error.Create failed": "Create failed",
"error.code_error": "Verification code error",
"error.fileNotFound": "File not found~",
"error.inheritPermissionError": "Inherit permission Error",
@ -1203,7 +1208,6 @@
"templateTags.Writing": "Writing",
"template_market": "Template Market",
"textarea_variable_picker_tip": "Enter \"/\" to select a variable",
"to_dataset": "To dataset",
"ui.textarea.Magnifying": "Magnifying",
"un_used": "Unused",
"unauth_token": "The certificate has expired, please log in again",

View File

@ -28,21 +28,16 @@
"collection.training_type": "Chunk type",
"collection_data_count": "Data amount",
"collection_metadata_custom_pdf_parse": "PDF enhancement analysis",
"collection_name": "Collection name",
"collection_not_support_retraining": "This collection type does not support retuning parameters",
"collection_not_support_sync": "This collection does not support synchronization",
"collection_sync": "Sync data",
"collection_sync_confirm_tip": "Confirm to start synchronizing data? \nThe system will pull the latest data for comparison. If the contents are different, a new collection will be created and the old collection will be deleted. Please confirm!",
"collection_tags": "Collection Tags",
"common.dataset.data.Input Error Tip": "[Image Dataset] Process error:",
"common.error.unKnow": "Unknown error",
"common_dataset": "General Dataset",
"common_dataset_desc": "Building a knowledge base by importing files, web page links, or manual entry",
"condition": "condition",
"config_sync_schedule": "Configure scheduled synchronization",
"confirm_import_images": "Total {{num}} | Confirm create",
"confirm_to_rebuild_embedding_tip": "Are you sure you want to switch the index for the Dataset?\nSwitching the index is a significant operation that requires re-indexing all data in your Dataset, which may take a long time. Please ensure your account has sufficient remaining points.\n\nAdditionally, you need to update the applications that use this Dataset to avoid conflicts with other indexed model Datasets.",
"core.dataset.Image collection": "Image dataset",
"core.dataset.import.Adjust parameters": "Adjust parameters",
"custom_data_process_params": "Custom",
"custom_data_process_params_desc": "Customize data processing rules",
@ -95,7 +90,6 @@
"image_auto_parse": "Automatic image indexing",
"image_auto_parse_tips": "Call VLM to automatically label the pictures in the document and generate additional search indexes",
"image_training_queue": "Queue of image processing",
"images_creating": "Creating",
"immediate_sync": "Immediate Synchronization",
"import.Auto mode Estimated Price Tips": "The text understanding model needs to be called, which requires more points: {{price}} points/1K tokens",
"import.Embedding Estimated Price Tips": "Only use the index model and consume a small amount of AI points: {{price}} points/1K tokens",
@ -110,8 +104,6 @@
"index_size": "Index size",
"index_size_tips": "When vectorized, the system will automatically further segment the blocks according to this size.",
"input_required_field_to_select_baseurl": "Please enter the required information first",
"insert_images": "Added pictures",
"insert_images_success": "The new picture is successfully added, and you need to wait for the training to be completed before it will be displayed.",
"is_open_schedule": "Enable scheduled synchronization",
"keep_image": "Keep the picture",
"loading": "Loading...",
@ -143,7 +135,6 @@
"process.Image_Index": "Image index generation",
"process.Is_Ready": "Ready",
"process.Is_Ready_Count": "{{count}} Group is ready",
"process.Parse_Image": "Image analysis",
"process.Parsing": "Parsing",
"process.Vectorizing": "Index vectorization",
"process.Waiting": "Queue",
@ -188,19 +179,13 @@
"training.Error": "{{count}} Group exception",
"training.Normal": "Normal",
"training_mode": "Chunk mode",
"training_queue_tip": "Training queue status",
"training_ready": "{{count}} Group",
"uploading_progress": "Uploading: {{num}}%",
"vector_model_max_tokens_tip": "Each chunk of data has a maximum length of 3000 tokens",
"vector_training_queue": "Vector training queue",
"vllm_model": "Image understanding model",
"vlm_model_required_tooltip": "A Vision Language Model is required to create image collections",
"vlm_model_required_warning": "Image datasets require a Vision Language Model (VLM) to be configured. Please add a model that supports image understanding in the model configuration first.",
"waiting_for_training": "Waiting for training",
"website_dataset": "Website Sync",
"website_dataset_desc": "Build knowledge base by crawling web page data in batches",
"website_info": "Website Information",
"yuque_dataset": "Yuque Knowledge Base",
"yuque_dataset_config": "Configure Yuque Knowledge Base",
"yuque_dataset_desc": "Build knowledge base using Yuque documents by configuring document permissions, documents will not be stored twice"
"yuque_dataset": "Yuque Dataset",
"yuque_dataset_config": "Yuque Dataset Config",
"yuque_dataset_desc": "Can build a dataset using Yuque documents by configuring permissions, without secondary storage"
}

View File

@ -1,32 +1,9 @@
{
"Action": "Please select the image to upload",
"All images import failed": "All pictures failed to import",
"Dataset_ID_not_found": "The dataset ID does not exist",
"Failed_to_get_token": "Failed to obtain the token",
"Image_ID_copied": "Copy ID",
"Image_Preview": "Picture preview",
"Image_dataset_requires_VLM_model_to_be_configured": "The image dataset needs to be configured with the image understanding model (VLM) to be used. Please add a model that supports image understanding in the model configuration first.",
"Image_does_not_belong_to_current_team": "The picture does not belong to the current team",
"Image_file_does_not_exist": "The picture does not exist",
"Loading_image": "Loading the picture...",
"Loading_image failed": "Preview loading failed",
"Only_support_uploading_one_image": "Only support uploading one image",
"Please select the image to upload": "Please select the image to upload",
"Please select the image to upload select the image to upload": "",
"Please wait for all files to upload": "Please wait for all files to be uploaded to complete",
"bucket_chat": "Conversation Files",
"bucket_file": "Dataset Documents",
"click_to_view_raw_source": "Click to View Original Source",
"common.dataset_data_input_image_support_format": "Support .jpg, .jpeg, .png, .gif, .webp formats",
"delete_image": "Delete pictures",
"file_name": "Filename",
"file_size": "Filesize",
"image": "picture",
"image_collection": "Picture collection",
"image_description": "Image description",
"image_description_tip": "Please enter the description of the picture",
"please_upload_image_first": "Please upload the picture first",
"reached_max_file_count": "Maximum file count reached",
"release_the_mouse_to_upload_the_file": "Release Mouse to Upload File",
"select_and_drag_file_tip": "Click or Drag Files Here to Upload",
"select_file_amount_limit": "You can select up to {{max}} files",
@ -35,9 +12,7 @@
"support_file_type": "Supports {{fileType}} file types",
"support_max_count": "Supports up to {{maxCount}} files",
"support_max_size": "Maximum file size is {{maxSize}}",
"total_files": "Total {{selectFiles.length}} files",
"upload_error_description": "Only multiple files or a single folder can be uploaded at a time",
"upload_failed": "Upload Failed",
"upload_file_error": "Please upload pictures",
"uploading": "Uploading..."
}
"reached_max_file_count": "Maximum file count reached",
"upload_error_description": "Only multiple files or a single folder can be uploaded at a time"
}

View File

@ -6,7 +6,6 @@
"accept": "接受",
"action": "操作",
"assign_permission": "权限变更",
"audit_log": "审计",
"change_department_name": "部门编辑",
"change_member_name": "成员改名",
"change_member_name_self": "变更成员名",
@ -34,13 +33,6 @@
"create_invoice": "开发票",
"create_org": "创建部门",
"create_sub_org": "创建子部门",
"dataset.api_file": "API导入",
"dataset.common_dataset": "知识库",
"dataset.external_file": "外部文件",
"dataset.feishu_dataset": "飞书多维表格",
"dataset.folder_dataset": "文件夹",
"dataset.website_dataset": "网站同步",
"dataset.yuque_dataset": "语雀知识库",
"delete": "删除",
"delete_api_key": "删除api密钥",
"delete_app": "删除工作台应用",
@ -55,7 +47,6 @@
"delete_from_team": "移出团队",
"delete_group": "删除群组",
"delete_org": "删除部门",
"department": "部门",
"edit_info": "编辑信息",
"edit_member": "编辑用户",
"edit_member_tip": "成员名",
@ -147,12 +138,16 @@
"login": "登录",
"manage_member": "管理成员",
"member": "成员",
"department": "部门",
"update": "更新",
"save_and_publish": "保存并发布",
"member_group": "所属群组",
"move_app": "应用位置移动",
"move_dataset": "移动知识库",
"move_member": "移动成员",
"move_org": "移动部门",
"notification_recieve": "团队通知接收",
"operation_log": "日志",
"org": "部门",
"org_description": "介绍",
"org_name": "部门名称",
@ -176,7 +171,6 @@
"restore_tip_title": "恢复确认",
"retain_admin_permissions": "保留管理员权限",
"retrain_collection": "重新训练集合",
"save_and_publish": "保存并发布",
"search_log": "搜索日志",
"search_member": "搜索成员",
"search_member_group_name": "搜索成员/群组名称",
@ -198,8 +192,14 @@
"type.Tool": "工具",
"type.Tool set": "工具集",
"type.Workflow bot": "工作流",
"dataset.folder_dataset": "文件夹",
"dataset.common_dataset": "知识库",
"dataset.website_dataset": "网站同步",
"dataset.external_file": "外部文件",
"dataset.api_file": "API导入",
"dataset.feishu_dataset": "飞书多维表格",
"dataset.yuque_dataset": "语雀知识库",
"unlimited": "无限制",
"update": "更新",
"update_api_key": "更新api密钥",
"update_app_collaborator": "应用权限更改",
"update_app_info": "应用信息修改",
@ -215,4 +215,4 @@
"user_team_leave_team": "离开团队",
"user_team_leave_team_failed": "离开团队失败",
"waiting": "待接受"
}
}

View File

@ -71,13 +71,13 @@
"response_embedding_model_tokens": "向量模型 Tokens",
"response_hybrid_weight": "语义检索 : 全文检索 = {{emb}} : {{text}}",
"response_rerank_tokens": "重排模型 Tokens",
"search_results": "搜索结果",
"select": "选择",
"select_file": "上传文件",
"select_file_img": "上传文件/图片",
"select_img": "上传图片",
"source_cronJob": "定时执行",
"stream_output": "流输出",
"to_dataset": "前往知识库",
"unsupported_file_type": "不支持的文件类型",
"upload": "上传",
"variable_invisable_in_share": "自定义变量在免登录链接中不可见",

View File

@ -403,6 +403,7 @@
"core.chat.response.module model": "模型",
"core.chat.response.module name": "模型名",
"core.chat.response.module query": "问题/检索词",
"core.chat.response.module quoteList": "引用内容",
"core.chat.response.module similarity": "相似度",
"core.chat.response.module temperature": "温度",
"core.chat.response.module time": "运行时长",
@ -433,6 +434,7 @@
"core.dataset.Text collection": "文本数据集",
"core.dataset.apiFile": "API 文件",
"core.dataset.collection.Click top config website": "点击配置网站",
"core.dataset.collection.Collection name": "数据集名称",
"core.dataset.collection.Collection raw text": "数据集内容",
"core.dataset.collection.Empty Tip": "数据集空空如也",
"core.dataset.collection.QA Prompt": "QA 拆分引导词",
@ -449,6 +451,7 @@
"core.dataset.collection.metadata.metadata": "元数据",
"core.dataset.collection.metadata.read source": "查看原始内容",
"core.dataset.collection.metadata.source": "数据来源",
"core.dataset.collection.metadata.source name": "来源名",
"core.dataset.collection.metadata.source size": "来源大小",
"core.dataset.collection.status.active": "已就绪",
"core.dataset.collection.status.error": "训练异常",
@ -740,7 +743,7 @@
"core.workflow.value": "值",
"core.workflow.variable": "变量",
"create": "去创建",
"create_failed": "创建失败",
"create_failed": "创建异常",
"create_success": "创建成功",
"create_time": "创建时间",
"cron_job_run_app": "定时任务",
@ -785,6 +788,7 @@
"dataset.dataset_name": "知识库名称",
"dataset.deleteFolderTips": "确认删除该文件夹及其包含的所有知识库?删除后数据无法恢复,请确认!",
"dataset.test.noResult": "搜索结果为空",
"dataset_data_import_q_placeholder": "最多 {{maxToken}} 字。",
"dataset_data_input_a": "答案",
"dataset_data_input_chunk": "常规模式",
"dataset_data_input_chunk_content": "内容",
@ -798,6 +802,7 @@
"delete_success": "删除成功",
"delete_warning": "删除警告",
"embedding_model_not_config": "检测到没有可用的索引模型",
"error.Create failed": "创建失败",
"error.code_error": "验证码错误",
"error.fileNotFound": "文件找不到了~",
"error.inheritPermissionError": "权限继承错误",
@ -1203,7 +1208,6 @@
"templateTags.Writing": "文本创作",
"template_market": "模板市场",
"textarea_variable_picker_tip": "输入\"/\"可选择变量",
"to_dataset": "前往知识库",
"ui.textarea.Magnifying": "放大",
"un_used": "未使用",
"unauth_token": "凭证已过期,请重新登录",

View File

@ -28,21 +28,16 @@
"collection.training_type": "处理模式",
"collection_data_count": "数据量",
"collection_metadata_custom_pdf_parse": "PDF增强解析",
"collection_name": "数据集名称",
"collection_not_support_retraining": "该集合类型不支持重新调整参数",
"collection_not_support_sync": "该集合不支持同步",
"collection_sync": "立即同步",
"collection_sync_confirm_tip": "确认开始同步数据?系统将会拉取最新数据进行比较,如果内容不相同,则会创建一个新的集合并删除旧的集合,请确认!",
"collection_tags": "集合标签",
"common.dataset.data.Input Error Tip": "[图片数据集] 处理过程错误:",
"common.error.unKnow": "未知错误",
"common_dataset": "通用知识库",
"common_dataset_desc": "通过导入文件、网页链接或手动录入形式构建知识库",
"condition": "条件",
"config_sync_schedule": "配置定时同步",
"confirm_import_images": "共 {{num}} 张图片 | 确认创建",
"confirm_to_rebuild_embedding_tip": "确认为知识库切换索引?\n切换索引是一个非常重量的操作需要对您知识库内所有数据进行重新索引时间可能较长请确保账号内剩余积分充足。\n\n此外你还需要注意修改选择该知识库的应用避免它们与其他索引模型知识库混用。",
"core.dataset.Image collection": "图片数据集",
"core.dataset.import.Adjust parameters": "调整参数",
"custom_data_process_params": "自定义",
"custom_data_process_params_desc": "自定义设置数据处理规则",
@ -95,7 +90,6 @@
"image_auto_parse": "图片自动索引",
"image_auto_parse_tips": "调用 VLM 自动标注文档里的图片,并生成额外的检索索引",
"image_training_queue": "图片处理排队",
"images_creating": "正在创建",
"immediate_sync": "立即同步",
"import.Auto mode Estimated Price Tips": "需调用文本理解模型需要消耗较多AI 积分:{{price}} 积分/1K tokens",
"import.Embedding Estimated Price Tips": "仅使用索引模型,消耗少量 AI 积分:{{price}} 积分/1K tokens",
@ -110,8 +104,6 @@
"index_size": "索引大小",
"index_size_tips": "向量化时内容的长度,系统会自动按该大小对分块进行进一步的分割。",
"input_required_field_to_select_baseurl": "请先输入必填信息",
"insert_images": "新增图片",
"insert_images_success": "新增图片成功,需等待训练完成才会展示",
"is_open_schedule": "启用定时同步",
"keep_image": "保留图片",
"loading": "加载中...",
@ -143,7 +135,6 @@
"process.Image_Index": "图片索引生成",
"process.Is_Ready": "已就绪",
"process.Is_Ready_Count": "{{count}} 组已就绪",
"process.Parse_Image": "图片解析中",
"process.Parsing": "内容解析中",
"process.Vectorizing": "索引向量化",
"process.Waiting": "排队中",
@ -185,14 +176,11 @@
"the_knowledge_base_has_indexes_that_are_being_trained_or_being_rebuilt": "知识库有训练中或正在重建的索引",
"total_num_files": "共 {{total}} 个文件",
"training.Error": "{{count}} 组异常",
"training.Image mode": "图片处理",
"training.Normal": "正常",
"training_mode": "处理方式",
"training_ready": "{{count}} 组",
"uploading_progress": "上传中: {{num}}%",
"vector_model_max_tokens_tip": "每个分块数据,最大长度为 3000 tokens",
"vllm_model": "图片理解模型",
"vlm_model_required_warning": "需要图片理解模型",
"website_dataset": "Web 站点同步",
"website_dataset_desc": "通过爬虫,批量爬取网页数据构建知识库",
"website_info": "网站信息",

View File

@ -1,33 +1,9 @@
{
"Action": "请选择要上传的图片",
"All images import failed": "所有图片导入失败",
"Dataset_ID_not_found": "数据集ID不存在",
"Failed_to_get_token": "获取令牌失败",
"Image_ID_copied": "已复制ID",
"Image_Preview": "图片预览",
"Image_dataset_requires_VLM_model_to_be_configured": "图片数据集需要配置图片理解模型(VLM)才能使用,请先在模型配置中添加支持图片理解的模型",
"Image_does_not_belong_to_current_team": "图片不属于当前团队",
"Image_file_does_not_exist": "图片不存在",
"Loading_image": "加载图片中...",
"Loading_image failed": "预览加载失败",
"Only_support_uploading_one_image": "仅支持上传一张图片",
"image_description_tip": "请输入图片的描述内容",
"Please select the image to upload": "请选择要上传的图片",
"Please wait for all files to upload": "请等待所有文件上传完成",
"bucket_chat": "对话文件",
"bucket_file": "知识库文件",
"click_to_view_raw_source": "点击查看来源",
"common.Some images failed to process": "部分图片处理失败",
"common.dataset_data_input_image_support_format": "支持 .jpg, .jpeg, .png, .gif, .webp 格式",
"count.core.dataset.collection.Create Success": "成功导入 {{count}} 张图片",
"delete_image": "删除图片",
"file_name": "文件名",
"file_size": "文件大小",
"image": "图片",
"image_collection": "图片集合",
"image_description": "图片描述",
"please_upload_image_first": "请先上传图片",
"reached_max_file_count": "已达到最大文件数量",
"release_the_mouse_to_upload_the_file": "松开鼠标上传文件",
"select_and_drag_file_tip": "点击或拖动文件到此处上传",
"select_file_amount_limit": "最多选择 {{max}} 个文件",
@ -36,9 +12,7 @@
"support_file_type": "支持 {{fileType}} 类型文件",
"support_max_count": "最多支持 {{maxCount}} 个文件",
"support_max_size": "单个文件最大 {{maxSize}}",
"total_files": "共{{selectFiles.length}}个文件",
"upload_error_description": "单次只支持上传多个文件或者一个文件夹",
"upload_failed": "上传异常",
"upload_file_error": "请上传图片",
"uploading": "正在上传..."
}
"reached_max_file_count": "已达到最大文件数量",
"upload_error_description": "单次只支持上传多个文件或者一个文件夹"
}

View File

@ -6,7 +6,6 @@
"accept": "接受",
"action": "操作",
"assign_permission": "權限變更",
"audit_log": "審計",
"change_department_name": "部門編輯",
"change_member_name": "成員改名",
"change_member_name_self": "變更成員名",
@ -33,13 +32,6 @@
"create_invoice": "開發票",
"create_org": "建立部門",
"create_sub_org": "建立子部門",
"dataset.api_file": "API 匯入",
"dataset.common_dataset": "知識庫",
"dataset.external_file": "外部文件",
"dataset.feishu_dataset": "飛書多維表格",
"dataset.folder_dataset": "資料夾",
"dataset.website_dataset": "網站同步",
"dataset.yuque_dataset": "語雀知識庫",
"delete": "刪除",
"delete_api_key": "刪除api密鑰",
"delete_app": "刪除工作台應用",
@ -54,7 +46,6 @@
"delete_from_team": "移出團隊",
"delete_group": "刪除群組",
"delete_org": "刪除部門",
"department": "部門",
"edit_info": "編輯訊息",
"edit_member": "編輯使用者",
"edit_member_tip": "成員名",
@ -145,12 +136,16 @@
"login": "登入",
"manage_member": "管理成員",
"member": "成員",
"department": "部門",
"update": "更新",
"save_and_publish": "儲存並發布",
"member_group": "所屬成員組",
"move_app": "應用位置移動",
"move_dataset": "移動知識庫",
"move_member": "移動成員",
"move_org": "行動部門",
"notification_recieve": "團隊通知接收",
"operation_log": "紀錄",
"org": "組織",
"org_description": "介紹",
"org_name": "部門名稱",
@ -174,7 +169,6 @@
"restore_tip_title": "恢復確認",
"retain_admin_permissions": "保留管理員權限",
"retrain_collection": "重新訓練集合",
"save_and_publish": "儲存並發布",
"search_log": "搜索日誌",
"search_member": "搜索成員",
"search_member_group_name": "搜尋成員/群組名稱",
@ -196,8 +190,14 @@
"type.Tool": "工具",
"type.Tool set": "工具集",
"type.Workflow bot": "工作流程",
"dataset.folder_dataset": "資料夾",
"dataset.common_dataset": "知識庫",
"dataset.website_dataset": "網站同步",
"dataset.external_file": "外部文件",
"dataset.api_file": "API 匯入",
"dataset.feishu_dataset": "飛書多維表格",
"dataset.yuque_dataset": "語雀知識庫",
"unlimited": "無限制",
"update": "更新",
"update_api_key": "更新api密鑰",
"update_app_collaborator": "應用權限更改",
"update_app_info": "應用信息修改",
@ -213,4 +213,4 @@
"user_team_leave_team": "離開團隊",
"user_team_leave_team_failed": "離開團隊失敗",
"waiting": "待接受"
}
}

View File

@ -71,13 +71,13 @@
"response_embedding_model_tokens": "向量模型 Tokens",
"response_hybrid_weight": "語義檢索 : 全文檢索 = {{emb}} : {{text}}",
"response_rerank_tokens": "重排模型 Tokens",
"search_results": "搜索結果",
"select": "選取",
"select_file": "上傳檔案",
"select_file_img": "上傳檔案 / 圖片",
"select_img": "上傳圖片",
"source_cronJob": "定時執行",
"stream_output": "串流輸出",
"to_dataset": "前往知識庫",
"unsupported_file_type": "不支援的檔案類型",
"upload": "上傳",
"variable_invisable_in_share": "自定義變數在免登入連結中不可見",

View File

@ -403,6 +403,7 @@
"core.chat.response.module model": "模型",
"core.chat.response.module name": "模型名稱",
"core.chat.response.module query": "問題/搜尋詞",
"core.chat.response.module quoteList": "引用內容",
"core.chat.response.module similarity": "相似度",
"core.chat.response.module temperature": "溫度",
"core.chat.response.module time": "執行時長",
@ -433,6 +434,7 @@
"core.dataset.Text collection": "文字資料集",
"core.dataset.apiFile": "API 檔案",
"core.dataset.collection.Click top config website": "點選設定網站",
"core.dataset.collection.Collection name": "資料集名稱",
"core.dataset.collection.Collection raw text": "資料集內容",
"core.dataset.collection.Empty Tip": "資料集是空的",
"core.dataset.collection.QA Prompt": "問答拆分提示詞",
@ -449,6 +451,7 @@
"core.dataset.collection.metadata.metadata": "中繼資料",
"core.dataset.collection.metadata.read source": "檢視原始內容",
"core.dataset.collection.metadata.source": "資料來源",
"core.dataset.collection.metadata.source name": "來源名稱",
"core.dataset.collection.metadata.source size": "來源大小",
"core.dataset.collection.status.active": "已就緒",
"core.dataset.collection.status.error": "訓練異常",
@ -552,7 +555,7 @@
"core.dataset.training.Agent queue": "問答訓練排隊中",
"core.dataset.training.Auto mode": "補充索引",
"core.dataset.training.Auto mode Tip": "透過子索引以及呼叫模型產生相關問題與摘要,來增加資料區塊的語意豐富度,更有利於檢索。需要消耗更多的儲存空間並增加 AI 呼叫次數。",
"core.dataset.training.Chunk mode": "分塊存",
"core.dataset.training.Chunk mode": "分塊",
"core.dataset.training.Full": "預計 20 分鐘以上",
"core.dataset.training.Leisure": "閒置",
"core.dataset.training.QA mode": "問答對提取",
@ -785,6 +788,7 @@
"dataset.dataset_name": "知識庫名稱",
"dataset.deleteFolderTips": "確認刪除此資料夾及其包含的所有知識庫?刪除後資料無法復原,請確認!",
"dataset.test.noResult": "搜尋結果為空",
"dataset_data_import_q_placeholder": "最多 {{maxToken}} 字。",
"dataset_data_input_a": "答案",
"dataset_data_input_chunk": "常規模式",
"dataset_data_input_chunk_content": "內容",
@ -798,6 +802,7 @@
"delete_success": "刪除成功",
"delete_warning": "刪除警告",
"embedding_model_not_config": "偵測到沒有可用的索引模型",
"error.Create failed": "建立失敗",
"error.code_error": "驗證碼錯誤",
"error.fileNotFound": "找不到檔案",
"error.inheritPermissionError": "繼承權限錯誤",
@ -1203,7 +1208,6 @@
"templateTags.Writing": "文字創作",
"template_market": "模板市場",
"textarea_variable_picker_tip": "輸入「/」以選擇變數",
"to_dataset": "前往知識庫",
"ui.textarea.Magnifying": "放大",
"un_used": "未使用",
"unauth_token": "憑證已過期,請重新登入",

View File

@ -26,21 +26,16 @@
"collection.training_type": "處理模式",
"collection_data_count": "資料量",
"collection_metadata_custom_pdf_parse": "PDF 增強解析",
"collection_name": "數據集名稱",
"collection_not_support_retraining": "此集合類型不支援重新調整參數",
"collection_not_support_sync": "該集合不支援同步",
"collection_sync": "立即同步",
"collection_sync_confirm_tip": "確認開始同步資料?\n系統將會拉取最新資料進行比較如果內容不相同則會建立一個新的集合並刪除舊的集合請確認",
"collection_tags": "集合標籤",
"common.dataset.data.Input Error Tip": "[圖片數據集] 處理過程錯誤:",
"common.error.unKnow": "未知錯誤",
"common_dataset": "通用資料集",
"common_dataset_desc": "通過導入文件、網頁鏈接或手動錄入形式構建知識庫",
"condition": "條件",
"config_sync_schedule": "設定定時同步",
"confirm_import_images": "共 {{num}} 張圖片 | 確認創建",
"confirm_to_rebuild_embedding_tip": "確定要為資料集切換索引嗎?\n切換索引是一個重要的操作需要對您資料集內所有資料重新建立索引可能需要較長時間請確保帳號內剩餘點數充足。\n\n此外您還需要注意修改使用此資料集的應用程式避免與其他索引模型資料集混用。",
"core.dataset.Image collection": "圖片數據集",
"core.dataset.import.Adjust parameters": "調整參數",
"custom_data_process_params": "自訂",
"custom_data_process_params_desc": "自訂資料處理規則",
@ -93,7 +88,6 @@
"image_auto_parse": "圖片自動索引",
"image_auto_parse_tips": "呼叫 VLM 自動標註文件裡的圖片,並生成額外的檢索索引",
"image_training_queue": "圖片處理排隊",
"images_creating": "正在創建",
"immediate_sync": "立即同步",
"import.Auto mode Estimated Price Tips": "需呼叫文字理解模型,將消耗較多 AI 點數:{{price}} 點數 / 1K tokens",
"import.Embedding Estimated Price Tips": "僅使用索引模型,消耗少量 AI 點數:{{price}} 點數 / 1K tokens",
@ -108,8 +102,6 @@
"index_size": "索引大小",
"index_size_tips": "向量化時內容的長度,系統會自動按該大小對分塊進行進一步的分割。",
"input_required_field_to_select_baseurl": "請先輸入必填信息",
"insert_images": "新增圖片",
"insert_images_success": "新增圖片成功,需等待訓練完成才會展示",
"is_open_schedule": "啟用定時同步",
"keep_image": "保留圖片",
"loading": "加載中...",
@ -141,7 +133,6 @@
"process.Image_Index": "圖片索引生成",
"process.Is_Ready": "已就緒",
"process.Is_Ready_Count": "{{count}} 組已就緒",
"process.Parse_Image": "圖片解析中",
"process.Parsing": "內容解析中",
"process.Vectorizing": "索引向量化",
"process.Waiting": "排隊中",
@ -183,13 +174,11 @@
"the_knowledge_base_has_indexes_that_are_being_trained_or_being_rebuilt": "資料集有索引正在訓練或重建中",
"total_num_files": "共 {{total}} 個文件",
"training.Error": "{{count}} 組異常",
"training.Image mode": "圖片處理",
"training.Normal": "正常",
"training_mode": "分段模式",
"training_ready": "{{count}} 組",
"vector_model_max_tokens_tip": "每個分塊資料,最大長度為 3000 tokens",
"vllm_model": "圖片理解模型",
"vlm_model_required_warning": "需要圖片理解模型",
"website_dataset": "網站同步",
"website_dataset_desc": "通過爬蟲,批量爬取網頁數據構建知識庫",
"website_info": "網站資訊",

View File

@ -1,31 +1,9 @@
{
"Action": "請選擇要上傳的圖片",
"All images import failed": "所有圖片導入失敗",
"Dataset_ID_not_found": "數據集ID不存在",
"Failed_to_get_token": "獲取令牌失敗",
"Image_ID_copied": "已復制ID",
"Image_Preview": "圖片預覽",
"Image_dataset_requires_VLM_model_to_be_configured": "圖片數據集需要配置圖片理解模型(VLM)才能使用,請先在模型配置中添加支持圖片理解的模型",
"Image_does_not_belong_to_current_team": "圖片不屬於當前團隊",
"Image_file_does_not_exist": "圖片不存在",
"Loading_image": "加載圖片中...",
"Loading_image_failed": "預覽加載失敗",
"Only_support_uploading_one_image": "僅支持上傳一張圖片",
"image_description_tip": "請輸入圖片的描述內容",
"Please select the image to upload": "請選擇要上傳的圖片",
"Please select the image to upload select the image to upload": "",
"Please wait for all files to upload": "請等待所有文件上傳完成",
"bucket_chat": "對話檔案",
"bucket_file": "知識庫檔案",
"click_to_view_raw_source": "點選檢視原始來源",
"dataset_data_input_image_support_format": "支持 .jpg, .jpeg, .png, .gif, .webp 格式",
"delete_image": "刪除圖片",
"file_name": "檔案名稱",
"file_size": "檔案大小",
"image": "圖片",
"image_collection": "圖片集合",
"please_upload_image_first": "請先上傳圖片",
"reached_max_file_count": "已達檔案數量上限",
"release_the_mouse_to_upload_the_file": "放開滑鼠以上傳檔案",
"select_and_drag_file_tip": "點選或拖曳檔案至此處上傳",
"select_file_amount_limit": "最多可選擇 {{max}} 個檔案",
@ -34,9 +12,7 @@
"support_file_type": "支援 {{fileType}} 格式的檔案",
"support_max_count": "最多可支援 {{maxCount}} 個檔案",
"support_max_size": "單一檔案大小上限為 {{maxSize}}",
"total_files": "共{{selectFiles.length}}個文件",
"upload_error_description": "單次僅支援上傳多個檔案或一個資料夾",
"upload_failed": "上傳失敗",
"upload_file_error": "請上傳圖片",
"uploading": "正在上傳..."
}
"reached_max_file_count": "已達檔案數量上限",
"upload_error_description": "單次僅支援上傳多個檔案或一個資料夾"
}

View File

@ -85,10 +85,10 @@ RUN chown -R nextjs:nodejs /app/data
ENV NODE_ENV=production
ENV NEXT_TELEMETRY_DISABLED=1
ENV PORT=3000
ENV PORT=3001
ENV NEXT_PUBLIC_BASE_URL=$base_url
EXPOSE 3000
EXPOSE 3001
USER nextjs

View File

@ -2,7 +2,9 @@
{
"feConfigs": {
"lafEnv": "https://laf.dev", // laf https://laf.run ,laf使 Laf openapi laf
"mcpServerProxyEndpoint": "" // mcp server http://localhost:3005
"mcpServerProxyEndpoint": "", // mcp server http://localhost:3005
"show_git":false,
"system_Title":"Test"
},
"systemEnv": {
"vectorMaxProcess": 10, // 线

View File

@ -0,0 +1,38 @@
version: '3.3'
services:
martin-gpt:
image: martingpt:v4.8.1 # 个人构建的镜像
container_name: martin-fastgpt
ports:
- '3001:3001'
networks:
- q00k04kgc8wk4k8okwog8owc_fastgpt
restart: always
environment:
- FE_DOMAIN=
- DEFAULT_ROOT_PSW=Pllh@123
- 'AIPROXY_API_ENDPOINT=http://aiproxy:3000'
- AIPROXY_API_TOKEN=aiproxy
- DB_MAX_LINK=30
- TOKEN_KEY=any
- ROOT_KEY=root_key
- FILE_TOKEN_KEY=filetoken
- 'MONGODB_URI=mongodb://myusername:mypassword@mongo:27017/fastgpt?authSource=admin'
- 'PG_URL=postgresql://username:password@pg:5432/postgres'
- 'REDIS_URL=redis://default:mypassword@redis:6379'
- 'SANDBOX_URL=http://sandbox:3000'
- LOG_LEVEL=info
- STORE_LOG_LEVEL=warn
- WORKFLOW_MAX_RUN_TIMES=1000
- WORKFLOW_MAX_LOOP_TIMES=100
- ALLOWED_ORIGINS=
- USE_IP_LIMIT=false
- CHAT_FILE_EXPIRE_TIME=7
volumes:
- '/data/martingpt/config.json:/app/data/config.json'
networks:
q00k04kgc8wk4k8okwog8owc_fastgpt:
external: true # 声明使用外部网络

View File

@ -3,9 +3,9 @@
"version": "4.9.10",
"private": false,
"scripts": {
"dev": "next dev",
"dev": "next dev -p 3001",
"build": "next build",
"start": "next start",
"start": "next start -p 3001",
"lint": "next lint"
},
"dependencies": {

View File

@ -3,28 +3,38 @@ import { Skeleton, type ImageProps } from '@chakra-ui/react';
import CustomImage from '@fastgpt/web/components/common/Image/MyImage';
export const MyImage = (props: ImageProps) => {
const [isLoading, setIsLoading] = useState(true);
const [succeed, setSucceed] = useState(false);
return (
<CustomImage
title={'Preview image'}
display={'inline-block'}
borderRadius={'md'}
alt={''}
fallbackSrc={'/imgs/errImg.png'}
fallbackStrategy={'onError'}
cursor={succeed ? 'pointer' : 'default'}
objectFit={'contain'}
loading={'lazy'}
onLoad={() => {
setSucceed(true);
}}
onClick={() => {
if (!succeed) return;
window.open(props.src, '_blank');
}}
{...props}
/>
<Skeleton
minH="100px"
isLoaded={!isLoading}
fadeDuration={2}
display={'flex'}
justifyContent={'center'}
my={1}
>
<CustomImage
display={'inline-block'}
borderRadius={'md'}
alt={''}
fallbackSrc={'/imgs/errImg.png'}
fallbackStrategy={'onError'}
cursor={succeed ? 'pointer' : 'default'}
objectFit={'contain'}
loading={'lazy'}
onLoad={() => {
setIsLoading(false);
setSucceed(true);
}}
onError={() => setIsLoading(false)}
onClick={() => {
if (!succeed) return;
window.open(props.src, '_blank');
}}
{...props}
/>
</Skeleton>
);
};

View File

@ -18,7 +18,7 @@ const NextHead = ({ title, icon, desc }: { title?: string; icon?: string; desc?:
name="viewport"
content="width=device-width,initial-scale=1.0,maximum-scale=1.0,minimum-scale=1.0,user-scalable=no, viewport-fit=cover"
/>
<meta httpEquiv="Content-Security-Policy" content="img-src * data: blob:;" />
<meta httpEquiv="Content-Security-Policy" content="img-src * data:;" />
{desc && <meta name="description" content={desc} />}
{icon && <link rel="icon" href={formatIcon} />}
</Head>

View File

@ -240,7 +240,7 @@ const LexiconConfigModal = ({ appId, onClose }: { appId: string; onClose: () =>
onSuccess() {
setNewData(undefined);
},
errorToast: t('common:create_failed')
errorToast: t('common:error.Create failed')
}
);

View File

@ -57,12 +57,11 @@ const QuoteList = React.memo(function QuoteList({
return {
...item,
q: currentFilterItem?.q || '',
a: currentFilterItem?.a || '',
imagePreivewUrl: currentFilterItem?.imagePreivewUrl
a: currentFilterItem?.a || ''
};
}
return { ...item, q: item.q || '' };
return { ...item, q: item.q || '', a: item.a || '' };
});
return processedData.sort((a, b) => {
@ -88,7 +87,6 @@ const QuoteList = React.memo(function QuoteList({
<QuoteItem
quoteItem={item}
canViewSource={showRawSource}
canEditData={showRouteToDatasetDetail}
canEditDataset={showRouteToDatasetDetail}
{...RawSourceBoxProps}
/>

View File

@ -81,9 +81,7 @@ const ResponseTags = ({
.map((item) => ({
sourceName: item.sourceName,
sourceId: item.sourceId,
icon: item.imageId
? 'core/dataset/imageFill'
: getSourceNameIcon({ sourceId: item.sourceId, sourceName: item.sourceName }),
icon: getSourceNameIcon({ sourceId: item.sourceId, sourceName: item.sourceName }),
collectionId: item.collectionId,
datasetId: item.datasetId
}));

View File

@ -300,7 +300,7 @@ export const WholeResponseContent = ({
<Row label={t('chat:query_extension_result')} value={`${activeModule?.extensionResult}`} />
{activeModule.quoteList && activeModule.quoteList.length > 0 && (
<Row
label={t('chat:search_results')}
label={t('common:core.chat.response.module quoteList')}
rawDom={<QuoteList chatItemDataId={dataId} rawSearch={activeModule.quoteList} />}
/>
)}

View File

@ -8,11 +8,7 @@ import { useTranslation } from 'next-i18next';
import MyTooltip from '@fastgpt/web/components/common/MyTooltip';
import dynamic from 'next/dynamic';
import MyBox from '@fastgpt/web/components/common/MyBox';
import {
DatasetCollectionTypeEnum,
SearchScoreTypeEnum,
SearchScoreTypeMap
} from '@fastgpt/global/core/dataset/constants';
import { SearchScoreTypeEnum, SearchScoreTypeMap } from '@fastgpt/global/core/dataset/constants';
import type { readCollectionSourceBody } from '@/pages/api/core/dataset/collection/read';
import Markdown from '@/components/Markdown';
@ -92,13 +88,11 @@ export const formatScore = (score: ScoreItemType[]) => {
const QuoteItem = ({
quoteItem,
canViewSource,
canEditData,
canEditDataset,
...RawSourceBoxProps
}: {
quoteItem: SearchDataResponseItemType;
canViewSource?: boolean;
canEditData?: boolean;
canEditDataset?: boolean;
} & Omit<readCollectionSourceBody, 'collectionId'>) => {
const { t } = useTranslation();
@ -212,7 +206,7 @@ const QuoteItem = ({
{...RawSourceBoxProps}
/>
<Box flex={1} />
{quoteItem.id && canEditData && (
{quoteItem.id && canEditDataset && (
<MyTooltip label={t('common:core.dataset.data.Edit')}>
<Box
className="hover-data"
@ -244,13 +238,12 @@ const QuoteItem = ({
<Link
as={NextLink}
className="hover-data"
display={'flex'}
alignItems={'center'}
visibility={'hidden'}
alignItems={'center'}
color={'primary.500'}
href={`/dataset/detail?datasetId=${quoteItem.datasetId}&currentTab=dataCard&collectionId=${quoteItem.collectionId}`}
>
{t('common:to_dataset')}
{t('chat:to_dataset')}
<MyIcon name={'common/rightArrowLight'} w={'10px'} />
</Link>
)}

View File

@ -3,22 +3,20 @@ import { Box, type BoxProps } from '@chakra-ui/react';
import MyTooltip from '@fastgpt/web/components/common/MyTooltip';
import { useTranslation } from 'next-i18next';
import { getCollectionSourceAndOpen } from '@/web/core/dataset/hooks/readCollectionSource';
import { getCollectionIcon } from '@fastgpt/global/core/dataset/utils';
import { getSourceNameIcon } from '@fastgpt/global/core/dataset/utils';
import MyIcon from '@fastgpt/web/components/common/Icon';
import type { readCollectionSourceBody } from '@/pages/api/core/dataset/collection/read';
import type { DatasetCollectionTypeEnum } from '@fastgpt/global/core/dataset/constants';
type Props = BoxProps &
readCollectionSourceBody & {
collectionType?: DatasetCollectionTypeEnum;
sourceName?: string;
collectionId: string;
sourceId?: string;
canView?: boolean;
};
const RawSourceBox = ({
sourceId,
collectionType,
sourceName = '',
canView = true,
@ -37,10 +35,7 @@ const RawSourceBox = ({
const canPreview = !!sourceId && canView;
const icon = useMemo(
() => getCollectionIcon({ type: collectionType, sourceId, name: sourceName }),
[collectionType, sourceId, sourceName]
);
const icon = useMemo(() => getSourceNameIcon({ sourceId, sourceName }), [sourceId, sourceName]);
const read = getCollectionSourceAndOpen({
collectionId,
appId,

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