feat: sync api collection will refresh title;perf: invite link ux (#4237)

* update queue

* feat: sync api collection will refresh title

* sync collection

* remove lock

* perf: invite link ux
This commit is contained in:
Archer
2025-03-19 21:03:21 +08:00
committed by archer
parent 73451dbc64
commit 87e90c37bd
44 changed files with 368 additions and 327 deletions

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@@ -12,10 +12,14 @@ weight: 799
1. 知识库分块增加自定义分隔符预设值,同时支持自定义换行符分割。
2. 外部变量改名:自定义变量。 并且支持在测试时调试,在分享链接中,该变量直接隐藏。
3. 集合同步时,支持同步修改标题。
## ⚙️ 优化
1. 导出对话日志时,支持导出成员名。
2. 邀请链接交互。
3. 无 SSL 证书时复制失败,会提示弹窗用于手动复制。
## 🐛 修复
1. 飞书和语雀知识库无法同步。

View File

@@ -124,6 +124,7 @@ curl --location --request GET '{{baseURL}}/v1/file/content?id=xx' \
"success": true,
"message": "",
"data": {
"title": "文档标题",
"content": "FastGPT 是一个基于 LLM 大语言模型的知识库问答系统,提供开箱即用的数据处理、模型调用等能力。同时可以通过 Flow 可视化进行工作流编排,从而实现复杂的问答场景!\n",
"previewUrl": "xxxx"
}
@@ -131,10 +132,13 @@ curl --location --request GET '{{baseURL}}/v1/file/content?id=xx' \
```
{{% alert icon=" " context="success" %}}
二选一返回,如果同时返回则 content 优先级更高。
- title - 文件标题。
- content - 文件内容,直接拿来用。
- previewUrl - 文件链接,系统会请求该地址获取文件内容。
`content``previewUrl`二选一返回,如果同时返回则 `content` 优先级更高,返回 `previewUrl`时,则会访问该链接进行文档内容读取。
{{% /alert %}}
{{< /markdownify >}}

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@@ -56,7 +56,7 @@ export const replaceSensitiveText = (text: string) => {
};
/* Make sure the first letter is definitely lowercase */
export const getNanoid = (size = 12) => {
export const getNanoid = (size = 16) => {
const firstChar = customAlphabet('abcdefghijklmnopqrstuvwxyz', 1)();
if (size === 1) return firstChar;

View File

@@ -1,3 +1,5 @@
import { RequireOnlyOne } from '../../common/type/utils';
export type APIFileItem = {
id: string;
parentId: string | null;
@@ -15,9 +17,9 @@ export type APIFileServer = {
export type APIFileListResponse = APIFileItem[];
export type APIFileContentResponse = {
content?: string;
previewUrl?: string;
export type ApiFileReadContentResponse = {
title?: string;
rawText: string;
};
export type APIFileReadResponse = {

View File

@@ -16,3 +16,7 @@ export const getCollectionSourceData = (collection?: DatasetCollectionSchemaType
export const checkCollectionIsFolder = (type: DatasetCollectionTypeEnum) => {
return type === DatasetCollectionTypeEnum.folder || type === DatasetCollectionTypeEnum.virtual;
};
export const collectionCanSync = (type: DatasetCollectionTypeEnum) => {
return [DatasetCollectionTypeEnum.link, DatasetCollectionTypeEnum.apiFile].includes(type);
};

View File

@@ -13,38 +13,38 @@ export enum DatasetTypeEnum {
export const DatasetTypeMap = {
[DatasetTypeEnum.folder]: {
icon: 'common/folderFill',
label: 'folder_dataset',
collectionLabel: 'common.Folder'
label: i18nT('dataset:folder_dataset'),
collectionLabel: i18nT('common:Folder')
},
[DatasetTypeEnum.dataset]: {
icon: 'core/dataset/commonDatasetOutline',
label: 'common_dataset',
collectionLabel: 'common.File'
label: i18nT('dataset:common_dataset'),
collectionLabel: i18nT('common:common.File')
},
[DatasetTypeEnum.websiteDataset]: {
icon: 'core/dataset/websiteDatasetOutline',
label: 'website_dataset',
collectionLabel: 'common.Website'
label: i18nT('dataset:website_dataset'),
collectionLabel: i18nT('common:common.Website')
},
[DatasetTypeEnum.externalFile]: {
icon: 'core/dataset/externalDatasetOutline',
label: 'external_file',
collectionLabel: 'common.File'
label: i18nT('dataset:external_file'),
collectionLabel: i18nT('common:common.File')
},
[DatasetTypeEnum.apiDataset]: {
icon: 'core/dataset/externalDatasetOutline',
label: 'api_file',
collectionLabel: 'common.File'
label: i18nT('dataset:api_file'),
collectionLabel: i18nT('common:common.File')
},
[DatasetTypeEnum.feishu]: {
icon: 'core/dataset/feishuDatasetOutline',
label: 'feishu_dataset',
collectionLabel: 'common.File'
label: i18nT('dataset:feishu_dataset'),
collectionLabel: i18nT('common:common.File')
},
[DatasetTypeEnum.yuque]: {
icon: 'core/dataset/yuqueDatasetOutline',
label: 'yuque_dataset',
collectionLabel: 'common.File'
label: i18nT('dataset:yuque_dataset'),
collectionLabel: i18nT('common:common.File')
}
};

View File

@@ -1,6 +1,6 @@
import type {
APIFileContentResponse,
APIFileListResponse,
ApiFileReadContentResponse,
APIFileReadResponse,
APIFileServer
} from '@fastgpt/global/core/dataset/apiDataset';
@@ -8,6 +8,7 @@ import axios, { Method } from 'axios';
import { addLog } from '../../../common/system/log';
import { readFileRawTextByUrl } from '../read';
import { ParentIdType } from '@fastgpt/global/common/parentFolder/type';
import { RequireOnlyOne } from '@fastgpt/global/common/type/utils';
type ResponseDataType = {
success: boolean;
@@ -118,17 +119,24 @@ export const useApiDatasetRequest = ({ apiServer }: { apiServer: APIFileServer }
tmbId: string;
apiFileId: string;
customPdfParse?: boolean;
}) => {
const data = await request<APIFileContentResponse>(
`/v1/file/content`,
{ id: apiFileId },
'GET'
);
}): Promise<ApiFileReadContentResponse> => {
const data = await request<
{
title?: string;
} & RequireOnlyOne<{
content: string;
previewUrl: string;
}>
>(`/v1/file/content`, { id: apiFileId }, 'GET');
const title = data.title;
const content = data.content;
const previewUrl = data.previewUrl;
if (content) {
return content;
return {
title,
rawText: content
};
}
if (previewUrl) {
const rawText = await readFileRawTextByUrl({
@@ -138,7 +146,10 @@ export const useApiDatasetRequest = ({ apiServer }: { apiServer: APIFileServer }
relatedId: apiFileId,
customPdfParse
});
return rawText;
return {
title,
rawText
};
}
return Promise.reject('Invalid content type: content or previewUrl is required');
};

View File

@@ -11,7 +11,6 @@ import {
DatasetCollectionSyncResultEnum,
DatasetCollectionTypeEnum,
DatasetSourceReadTypeEnum,
DatasetTypeEnum,
TrainingModeEnum
} from '@fastgpt/global/core/dataset/constants';
import { DatasetErrEnum } from '@fastgpt/global/common/error/code/dataset';
@@ -19,6 +18,7 @@ import { readDatasetSourceRawText } from '../read';
import { hashStr } from '@fastgpt/global/common/string/tools';
import { mongoSessionRun } from '../../../common/mongo/sessionRun';
import { createCollectionAndInsertData, delCollection } from './controller';
import { collectionCanSync } from '@fastgpt/global/core/dataset/collection/utils';
/**
* get all collection by top collectionId
@@ -137,10 +137,7 @@ export const collectionTagsToTagLabel = async ({
export const syncCollection = async (collection: CollectionWithDatasetType) => {
const dataset = collection.dataset;
if (
collection.type !== DatasetCollectionTypeEnum.link &&
dataset.type !== DatasetTypeEnum.apiDataset
) {
if (!collectionCanSync(collection.type)) {
return Promise.reject(DatasetErrEnum.notSupportSync);
}
@@ -155,15 +152,20 @@ export const syncCollection = async (collection: CollectionWithDatasetType) => {
};
}
if (!collection.apiFileId) return Promise.reject('apiFileId is missing');
if (!dataset.apiServer) return Promise.reject('apiServer not found');
const sourceId = collection.apiFileId;
if (!sourceId) return Promise.reject('apiFileId is missing');
return {
type: DatasetSourceReadTypeEnum.apiFile,
sourceId: collection.apiFileId,
apiServer: dataset.apiServer
sourceId,
apiServer: dataset.apiServer,
feishuServer: dataset.feishuServer,
yuqueServer: dataset.yuqueServer
};
})();
const rawText = await readDatasetSourceRawText({
const { title, rawText } = await readDatasetSourceRawText({
teamId: collection.teamId,
tmbId: collection.tmbId,
...sourceReadType
@@ -196,7 +198,7 @@ export const syncCollection = async (collection: CollectionWithDatasetType) => {
createCollectionParams: {
teamId: collection.teamId,
tmbId: collection.tmbId,
name: collection.name,
name: title || collection.name,
datasetId: collection.datasetId,
parentId: collection.parentId,
type: collection.type,

View File

@@ -79,9 +79,12 @@ export const readDatasetSourceRawText = async ({
apiServer?: APIFileServer; // api dataset
feishuServer?: FeishuServer; // feishu dataset
yuqueServer?: YuqueServer; // yuque dataset
}): Promise<string> => {
}): Promise<{
title?: string;
rawText: string;
}> => {
if (type === DatasetSourceReadTypeEnum.fileLocal) {
const { rawText } = await readFileContentFromMongo({
const { filename, rawText } = await readFileContentFromMongo({
teamId,
tmbId,
bucketName: BucketNameEnum.dataset,
@@ -89,14 +92,20 @@ export const readDatasetSourceRawText = async ({
isQAImport,
customPdfParse
});
return rawText;
return {
title: filename,
rawText
};
} else if (type === DatasetSourceReadTypeEnum.link) {
const result = await urlsFetch({
urlList: [sourceId],
selector
});
return result[0]?.content || '';
return {
title: result[0]?.title,
rawText: result[0]?.content || ''
};
} else if (type === DatasetSourceReadTypeEnum.externalFile) {
if (!externalFileId) return Promise.reject('FileId not found');
const rawText = await readFileRawTextByUrl({
@@ -106,9 +115,11 @@ export const readDatasetSourceRawText = async ({
relatedId: externalFileId,
customPdfParse
});
return rawText;
return {
rawText
};
} else if (type === DatasetSourceReadTypeEnum.apiFile) {
const rawText = await readApiServerFileContent({
const { title, rawText } = await readApiServerFileContent({
apiServer,
feishuServer,
yuqueServer,
@@ -116,9 +127,15 @@ export const readDatasetSourceRawText = async ({
teamId,
tmbId
});
return rawText;
return {
title,
rawText
};
}
return '';
return {
title: '',
rawText: ''
};
};
export const readApiServerFileContent = async ({
@@ -137,7 +154,10 @@ export const readApiServerFileContent = async ({
teamId: string;
tmbId: string;
customPdfParse?: boolean;
}) => {
}): Promise<{
title?: string;
rawText: string;
}> => {
if (apiServer) {
return useApiDatasetRequest({ apiServer }).getFileContent({
teamId,
@@ -148,7 +168,10 @@ export const readApiServerFileContent = async ({
}
if (feishuServer || yuqueServer) {
return POST<string>(`/core/dataset/systemApiDataset`, {
return POST<{
title?: string;
rawText: string;
}>(`/core/dataset/systemApiDataset`, {
type: 'content',
feishuServer,
yuqueServer,

View File

@@ -1,52 +0,0 @@
import { TeamCollectionName } from '@fastgpt/global/support/user/team/constant';
import { connectionMongo, getMongoModel } from '../../../../common/mongo';
import { InvitationSchemaType } from './type';
import { randomUUID } from 'crypto';
const { Schema } = connectionMongo;
export const InvitationCollectionName = 'team_invitation_links';
const InvitationSchema = new Schema({
linkId: {
type: String,
required: true,
unique: true,
default: () => randomUUID()
},
teamId: {
type: Schema.Types.ObjectId,
ref: TeamCollectionName,
required: true
},
usedTimesLimit: {
type: Number,
default: 1,
enum: [1, -1]
},
forbidden: Boolean,
expires: Date,
description: String,
members: {
type: [String],
default: []
}
});
InvitationSchema.virtual('team', {
ref: TeamCollectionName,
localField: 'teamId',
foreignField: '_id',
justOne: true
});
try {
InvitationSchema.index({ teamId: 1 });
InvitationSchema.index({ expires: 1 }, { expireAfterSeconds: 30 * 24 * 60 * 60 });
} catch (error) {
console.log(error);
}
export const MongoInvitationLink = getMongoModel<InvitationSchemaType>(
InvitationCollectionName,
InvitationSchema
);

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@@ -0,0 +1,8 @@
import zustandNpm from 'zustand';
export * from 'zustand';
export * from 'zustand/middleware';
export * from 'zustand/middleware/immer';
export * from 'zustand';
export default zustandNpm;

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@@ -3,6 +3,11 @@ import { useToast } from './useToast';
import { useCallback } from 'react';
import { hasHttps } from '../common/system/utils';
import { isProduction } from '@fastgpt/global/common/system/constants';
import MyModal from '../components/common/MyModal';
import React from 'react';
import { Box, ModalBody } from '@chakra-ui/react';
import Tag from '../components/common/Tag';
import { useCommonStore } from '../store/useCommonStore';
/**
* copy text data
@@ -10,43 +15,15 @@ import { isProduction } from '@fastgpt/global/common/system/constants';
export const useCopyData = () => {
const { t } = useTranslation();
const { toast } = useToast();
const { setCopyContent } = useCommonStore();
const copyData = useCallback(
async (
data: string,
title: string | null = t('common:common.Copy Successful'),
duration = 1000
) => {
async (data: string, title = t('common:common.Copy Successful'), duration = 1000) => {
data = data.trim();
try {
if ((hasHttps() || !isProduction) && navigator.clipboard) {
await navigator.clipboard.writeText(data);
} else {
throw new Error('');
}
} catch (error) {
// console.log(error);
const textarea = document.createElement('textarea');
textarea.value = data;
textarea.style.position = 'absolute';
textarea.style.opacity = '0';
document.body.appendChild(textarea);
textarea.select();
const res = document.execCommand('copy');
document.body.removeChild(textarea);
if (!res) {
return toast({
title: t('common:common.Copy_failed'),
status: 'error',
duration
});
}
}
if (title) {
toast({
title,
@@ -54,6 +31,12 @@ export const useCopyData = () => {
duration
});
}
} else {
throw new Error('');
}
} catch (error) {
setCopyContent(data);
}
},
[t, toast]
);
@@ -62,3 +45,29 @@ export const useCopyData = () => {
copyData
};
};
export const ManualCopyModal = () => {
const { t } = useTranslation();
const { copyContent, setCopyContent } = useCommonStore();
return (
<MyModal
isOpen={!!copyContent}
iconSrc="copy"
iconColor="primary.600"
title={t('common:common.Copy')}
maxW={['90vw', '500px']}
w={'100%'}
onClose={() => setCopyContent(undefined)}
>
<ModalBody>
<Tag w={'100%'} colorSchema="blue">
{t('common:can_copy_content_tip')}
</Tag>
<Box mt={3} borderRadius={'md'} p={3} border={'base'} userSelect={'all'}>
{copyContent}
</Box>
</ModalBody>
</MyModal>
);
};

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@@ -21,7 +21,7 @@
"edit_member_tip": "username",
"edit_info": "Edit information",
"edit_org_info": "Edit organization information",
"expires": "Expiration",
"expires": "Expiration time",
"forbid_hint": "After forbidden, this invitation link will become invalid. This action is irreversible. Are you sure you want to deactivate?",
"forbid_success": "Forbid success",
"forbidden": "Forbidden",

View File

@@ -37,6 +37,7 @@
"add_new_param": "Add new param",
"app.templateMarket.templateTags.Writing": "Writing",
"back": "Back",
"can_copy_content_tip": "It is not possible to copy automatically using the browser, please manually copy the following content",
"chose_condition": "Choose Condition",
"chosen": "Chosen",
"classification": "Classification",
@@ -128,7 +129,6 @@
"common.Continue_Adding": "Continue adding",
"common.Copy": "Copy",
"common.Copy Successful": "Copied Successfully",
"common.Copy_failed": "Copy Failed, Please Copy Manually",
"common.Create Failed": "Creation Failed",
"common.Create Success": "Created Successfully",
"common.Create Time": "Creation Time",
@@ -645,11 +645,11 @@
"core.dataset.training.Auto mode": "Auto index",
"core.dataset.training.Auto mode Tip": "Increase the semantic richness of data blocks by generating related questions and summaries through sub-indexes and calling models, making it more conducive to retrieval. Requires more storage space and increases AI call times.",
"core.dataset.training.Chunk mode": "Chunk",
"core.dataset.training.Full": "Estimated Over 5 Minutes",
"core.dataset.training.Full": "It is expected to be more than 20 minutes",
"core.dataset.training.Leisure": "Idle",
"core.dataset.training.QA mode": "QA",
"core.dataset.training.Vector queue": "Index Queue",
"core.dataset.training.Waiting": "Estimated 5 Minutes",
"core.dataset.training.Waiting": "Estimated 20 minutes",
"core.dataset.training.Website Sync": "Website Sync",
"core.dataset.training.tag": "Queue Status",
"core.dataset.website.Base Url": "Base URL",

View File

@@ -5,6 +5,7 @@
"api_url": "API Url",
"auto_indexes": "Automatically generate supplementary indexes",
"auto_indexes_tips": "Additional index generation is performed through large models to improve semantic richness and improve retrieval accuracy.",
"auto_training_queue": "Enhanced index queueing",
"chunk_max_tokens": "max_tokens",
"close_auto_sync": "Are you sure you want to turn off automatic sync?",
"collection.Create update time": "Creation/Update Time",
@@ -56,6 +57,7 @@
"ideal_chunk_length_tips": "Segment according to the end symbol and combine multiple segments into one block. This value determines the estimated size of the block, if there is any fluctuation.",
"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",
"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",
"import_confirm": "Confirm upload",

View File

@@ -24,7 +24,7 @@
"edit_member_tip": "用户名",
"edit_info": "编辑信息",
"edit_org_info": "编辑部门信息",
"expires": "有效期",
"expires": "过期时间",
"export_members": "导出成员",
"forbid_hint": "停用后,该邀请链接将失效。 该操作不可撤销,是否确认停用?",
"forbid_success": "停用成功",

View File

@@ -41,6 +41,7 @@
"app.templateMarket.templateTags.Web_search": "联网搜索",
"app.templateMarket.templateTags.Writing": "文本创作",
"back": "返回",
"can_copy_content_tip": "无法使用浏览器自动复制,请手动复制下面内容",
"chose_condition": "选择条件",
"chosen": "已选",
"classification": "分类",
@@ -132,7 +133,6 @@
"common.Continue_Adding": "继续添加",
"common.Copy": "复制",
"common.Copy Successful": "复制成功",
"common.Copy_failed": "复制失败,请手动复制",
"common.Create Failed": "创建异常",
"common.Create Success": "创建成功",
"common.Create Time": "创建时间",
@@ -648,11 +648,11 @@
"core.dataset.training.Auto mode": "补充索引",
"core.dataset.training.Auto mode Tip": "通过子索引以及调用模型生成相关问题与摘要,来增加数据块的语义丰富度,更利于检索。需要消耗更多的存储空间和增加 AI 调用次数。",
"core.dataset.training.Chunk mode": "直接分块",
"core.dataset.training.Full": "预计 5 分钟以上",
"core.dataset.training.Full": "预计 20 分钟以上",
"core.dataset.training.Leisure": "空闲",
"core.dataset.training.QA mode": "问答对提取",
"core.dataset.training.Vector queue": "索引排队",
"core.dataset.training.Waiting": "预计 5 分钟",
"core.dataset.training.Waiting": "预计 20 分钟",
"core.dataset.training.Website Sync": "Web 站点同步",
"core.dataset.training.tag": "排队情况",
"core.dataset.website.Base Url": "根地址",

View File

@@ -5,6 +5,7 @@
"api_url": "接口地址",
"auto_indexes": "自动生成补充索引",
"auto_indexes_tips": "通过大模型进行额外索引生成,提高语义丰富度,提高检索的精度。",
"auto_training_queue": "增强索引排队",
"chunk_max_tokens": "分块上限",
"close_auto_sync": "确认关闭自动同步功能?",
"collection.Create update time": "创建/更新时间",
@@ -56,6 +57,7 @@
"ideal_chunk_length_tips": "按结束符号进行分段,并将多个分段组成一个分块,该值决定了分块的预估大小,如果会有上下浮动。",
"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",
"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",
"import_confirm": "确认上传",

View File

@@ -21,7 +21,7 @@
"edit_member_tip": "使用者名稱",
"edit_info": "編輯訊息",
"edit_org_info": "編輯部門資訊",
"expires": "有效期",
"expires": "過期時間",
"forbid_hint": "停用後,該邀請連結將失效。 該操作不可撤銷,是否確認停用?",
"forbid_success": "停用成功",
"forbidden": "停用",

View File

@@ -37,6 +37,7 @@
"add_new_param": "新增參數",
"app.templateMarket.templateTags.Writing": "文字創作",
"back": "返回",
"can_copy_content_tip": "無法使用瀏覽器自動複製,請手動複製下面內容",
"chose_condition": "選擇條件",
"chosen": "已選擇",
"classification": "分類",
@@ -127,7 +128,6 @@
"common.Continue_Adding": "繼續新增",
"common.Copy": "複製",
"common.Copy Successful": "複製成功",
"common.Copy_failed": "複製失敗,請手動複製",
"common.Create Failed": "建立失敗",
"common.Create Success": "建立成功",
"common.Create Time": "建立時間",
@@ -644,11 +644,11 @@
"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": "直接分块",
"core.dataset.training.Full": "預計超過 5 分鐘",
"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",
"core.dataset.training.Vector queue": "索引排隊中",
"core.dataset.training.Waiting": "預計 5 分鐘",
"core.dataset.training.Waiting": "預計 20 分鐘",
"core.dataset.training.Website Sync": "網站同步",
"core.dataset.training.tag": "排隊狀況",
"core.dataset.website.Base Url": "根網址",

View File

@@ -5,6 +5,7 @@
"api_url": "介面位址",
"auto_indexes": "自動生成補充索引",
"auto_indexes_tips": "通過大模型進行額外索引生成,提高語義豐富度,提高檢索的精度。",
"auto_training_queue": "增強索引排隊",
"chunk_max_tokens": "分塊上限",
"close_auto_sync": "確認關閉自動同步功能?",
"collection.Create update time": "建立/更新時間",
@@ -56,6 +57,7 @@
"ideal_chunk_length_tips": "依結束符號進行分段,並將多個分段組成一個分塊,此值決定了分塊的預估大小,可能會有上下浮動。",
"image_auto_parse": "圖片自動索引",
"image_auto_parse_tips": "調用 VLM 自動標註文檔裡的圖片,並生成額外的檢索索引",
"image_training_queue": "圖片處理排隊",
"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",
"import_confirm": "確認上傳",

View File

@@ -34,7 +34,8 @@
"react-hook-form": "7.43.1",
"react-i18next": "14.1.2",
"react-photo-view": "^1.2.6",
"use-context-selector": "^1.4.4"
"use-context-selector": "^1.4.4",
"zustand": "^4.3.5"
},
"devDependencies": {
"@types/js-cookie": "^3.0.5",

View File

@@ -0,0 +1,25 @@
import { create, devtools, persist, immer } from '../common/zustand';
type State = {
copyContent?: string;
setCopyContent: (val?: string) => void;
};
export const useCommonStore = create<State>()(
devtools(
persist(
immer((set, get) => ({
copyContent: undefined,
setCopyContent(val) {
set((state) => {
state.copyContent = val;
});
}
})),
{
name: 'commonStore',
partialize: (state) => ({})
}
)
)
);

6
pnpm-lock.yaml generated
View File

@@ -398,6 +398,9 @@ importers:
use-context-selector:
specifier: ^1.4.4
version: 1.4.4(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(scheduler@0.23.2)
zustand:
specifier: ^4.3.5
version: 4.5.6(@types/react@18.3.1)(immer@9.0.21)(react@18.3.1)
devDependencies:
'@types/js-cookie':
specifier: ^3.0.5
@@ -588,9 +591,6 @@ importers:
use-context-selector:
specifier: ^1.4.4
version: 1.4.4(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(scheduler@0.23.2)
zustand:
specifier: ^4.3.5
version: 4.5.6(@types/react@18.3.1)(immer@9.0.21)(react@18.3.1)
devDependencies:
'@svgr/webpack':
specifier: ^6.5.1

View File

@@ -64,8 +64,7 @@
"request-ip": "^3.3.0",
"sass": "^1.58.3",
"use-context-selector": "^1.4.4",
"@node-rs/jieba": "2.0.1",
"zustand": "^4.3.5"
"@node-rs/jieba": "2.0.1"
},
"devDependencies": {
"@svgr/webpack": "^6.5.1",

View File

@@ -22,6 +22,9 @@ const NotSufficientModal = dynamic(() => import('@/components/support/wallet/Not
const SystemMsgModal = dynamic(() => import('@/components/support/user/inform/SystemMsgModal'));
const ImportantInform = dynamic(() => import('@/components/support/user/inform/ImportantInform'));
const UpdateContact = dynamic(() => import('@/components/support/user/inform/UpdateContactModal'));
const ManualCopyModal = dynamic(() =>
import('@fastgpt/web/hooks/useCopyData').then((mod) => mod.ManualCopyModal)
);
const pcUnShowLayoutRoute: Record<string, boolean> = {
'/': true,
@@ -162,6 +165,7 @@ const Layout = ({ children }: { children: JSX.Element }) => {
</>
)}
<ManualCopyModal />
<Loading loading={loading} zIndex={999999} />
</>
);

View File

@@ -48,15 +48,6 @@ export type InsertOneDatasetDataProps = PushDatasetDataChunkProps & {
collectionId: string;
};
export type GetTrainingQueueProps = {
vectorModel: string;
agentModel: string;
};
export type GetTrainingQueueResponse = {
vectorTrainingCount: number;
agentTrainingCount: number;
};
/* -------------- search ---------------- */
export type SearchTestProps = {
datasetId: string;

View File

@@ -22,7 +22,13 @@ import { useRequest2 } from '@fastgpt/web/hooks/useRequest';
import { useTranslation } from 'next-i18next';
import { useForm } from 'react-hook-form';
function CreateInvitationModal({ onClose }: { onClose: (linkId?: string) => void }) {
function CreateInvitationModal({
onSuccess,
onClose
}: {
onSuccess: (linkId: string) => void;
onClose: () => void;
}) {
const { t } = useTranslation();
const expiresOptions: Array<{ label: string; value: InvitationLinkExpiresType }> = [
{ label: t('account_team:30mins'), value: '30m' }, // 30 mins
@@ -43,12 +49,11 @@ function CreateInvitationModal({ onClose }: { onClose: (linkId?: string) => void
const { runAsync: createInvitationLink, loading } = useRequest2(postCreateInvitationLink, {
manual: true,
successToast: t('common:common.Create Success'),
errorToast: t('common:common.Create Failed'),
onSuccess: (data) => {
onClose(data);
},
onFinally: () => onClose()
onSuccess(data);
onClose();
}
});
return (

View File

@@ -35,15 +35,7 @@ import { useCallback } from 'react';
const CreateInvitationModal = dynamic(() => import('./CreateInvitationModal'));
const InviteModal = ({
teamId,
onClose,
onSuccess
}: {
teamId: string;
onClose: () => void;
onSuccess: () => void;
}) => {
const InviteModal = ({ onClose }: { onClose: () => void }) => {
const { t } = useTranslation();
const {
@@ -57,10 +49,10 @@ const InviteModal = ({
const { isOpen: isOpenCreate, onOpen: onOpenCreate, onClose: onCloseCreate } = useDisclosure();
const isLoading = isLoadingLink;
const { copyData } = useCopyData();
const { userInfo } = useUserStore();
const { feConfigs } = useSystemStore();
const onCopy = useCallback(
(linkId: string) => {
const url = location.origin + `/account/team?invitelinkid=${linkId}`;
@@ -76,7 +68,7 @@ const InviteModal = ({
})
);
},
[copyData]
[copyData, feConfigs?.systemTitle, t, userInfo?.team.memberName, userInfo?.team.teamName]
);
const { runAsync: onForbid, loading: forbiding } = useRequest2(putForbidInvitationLink, {
@@ -131,13 +123,7 @@ const InviteModal = ({
<Td maxW="200px" minW="100px">
{item.description}
</Td>
<Td>
{isForbidden ? (
<Tag colorSchema="gray">{t('account_team:has_forbidden')}</Tag>
) : (
format(new Date(item.expires), 'yyyy-MM-dd HH:mm')
)}
</Td>
<Td>{format(new Date(item.expires), 'yyyy-MM-dd HH:mm')}</Td>
<Td>
{item.usedTimesLimit === -1
? t('account_team:unlimited')
@@ -153,7 +139,6 @@ const InviteModal = ({
cursor="pointer"
_hover={{ bg: 'myGray.100' }}
p="1.5"
w="fit-content"
>
<AvatarGroup max={3} avatars={item.members.map((i) => i.avatar)} />
</Box>
@@ -162,7 +147,7 @@ const InviteModal = ({
closeOnBlur={true}
>
{() => (
<Box py="4" maxH="200px" w="fit-content">
<Box py="4" maxH="200px">
<Flex mx="4" justifyContent="center" alignItems={'center'}>
<Box>{t('account_team:has_invited')}</Box>
<Box
@@ -175,15 +160,16 @@ const InviteModal = ({
{item.members.length}
</Box>
</Flex>
<Divider my="2" mx="4" />
<Divider my="2" />
<Grid
w="fit-content"
mt="2"
gridRowGap="4"
mt="4"
gap={4}
gridTemplateColumns="1fr 1fr"
overflow="auto"
alignItems="center"
mx="4"
maxH={'250px'}
>
{item.members.map((member) => (
<Box key={member.tmbId} justifySelf="start">
@@ -197,7 +183,9 @@ const InviteModal = ({
)}
</Td>
<Td>
{!isForbidden && (
{isForbidden ? (
<Tag colorSchema="red">{t('account_team:has_forbidden')}</Tag>
) : (
<>
<Button
size="sm"
@@ -261,17 +249,11 @@ const InviteModal = ({
</ModalFooter>
{isOpenCreate && (
<CreateInvitationModal
onClose={(linkId?: string) =>
Promise.all([
onCloseCreate(),
refetchInvitationLinkList(),
(() => {
if (linkId) {
onSuccess={(linkId) => {
refetchInvitationLinkList();
onCopy(linkId);
}
})()
])
}
}}
onClose={onCloseCreate}
/>
)}
</MyModal>

View File

@@ -29,7 +29,6 @@ import {
DatasetCollectionTypeEnum,
DatasetStatusEnum,
DatasetCollectionSyncResultMap,
DatasetTypeEnum,
DatasetCollectionDataProcessModeMap
} from '@fastgpt/global/core/dataset/constants';
import { getCollectionIcon } from '@fastgpt/global/core/dataset/utils';
@@ -45,7 +44,10 @@ import { CollectionPageContext } from './Context';
import { DatasetPageContext } from '@/web/core/dataset/context/datasetPageContext';
import { formatTime2YMDHM } from '@fastgpt/global/common/string/time';
import MyTag from '@fastgpt/web/components/common/Tag/index';
import { checkCollectionIsFolder } from '@fastgpt/global/core/dataset/collection/utils';
import {
checkCollectionIsFolder,
collectionCanSync
} from '@fastgpt/global/core/dataset/collection/utils';
import { useFolderDrag } from '@/components/common/folder/useFolderDrag';
import TagsPopOver from './TagsPopOver';
import { useSystemStore } from '@/web/common/system/useSystemStore';
@@ -315,8 +317,7 @@ const CollectionCard = () => {
menuList={[
{
children: [
...(collection.type === DatasetCollectionTypeEnum.link ||
datasetDetail.type === DatasetTypeEnum.apiDataset
...(collectionCanSync(collection.type)
? [
{
label: (

View File

@@ -1,4 +1,4 @@
import React, { useCallback } from 'react';
import React, { useCallback, useMemo } from 'react';
import { useTranslation } from 'next-i18next';
import { Box, Flex, IconButton, useTheme, Progress } from '@chakra-ui/react';
import MyIcon from '@fastgpt/web/components/common/Icon';
@@ -9,6 +9,8 @@ import LightRowTabs from '@fastgpt/web/components/common/Tabs/LightRowTabs';
import { useSystem } from '@fastgpt/web/hooks/useSystem';
import MyPopover from '@fastgpt/web/components/common/MyPopover';
import ParentPaths from '@/components/common/ParentPaths';
import { getTrainingQueueLen } from '@/web/core/dataset/api';
import { useRequest2 } from '@fastgpt/web/hooks/useRequest';
export enum TabEnum {
dataCard = 'dataCard',
@@ -24,8 +26,68 @@ const NavBar = ({ currentTab }: { currentTab: TabEnum }) => {
const router = useRouter();
const query = router.query;
const { isPc } = useSystem();
const { datasetDetail, vectorTrainingMap, agentTrainingMap, rebuildingCount, paths } =
useContextSelector(DatasetPageContext, (v) => v);
const { datasetDetail, rebuildingCount, paths } = useContextSelector(
DatasetPageContext,
(v) => v
);
// global queue
const {
data: {
vectorTrainingCount = 0,
qaTrainingCount = 0,
autoTrainingCount = 0,
imageTrainingCount = 0
} = {}
} = useRequest2(getTrainingQueueLen, {
manual: false,
retryInterval: 10000
});
const { vectorTrainingMap, qaTrainingMap, autoTrainingMap, imageTrainingMap } = useMemo(() => {
const vectorTrainingMap = (() => {
if (vectorTrainingCount < 1000)
return {
colorSchema: 'green',
tip: t('common:core.dataset.training.Leisure')
};
if (vectorTrainingCount < 20000)
return {
colorSchema: 'yellow',
tip: t('common:core.dataset.training.Waiting')
};
return {
colorSchema: 'red',
tip: t('common:core.dataset.training.Full')
};
})();
const countLLMMap = (count: number) => {
if (count < 100)
return {
colorSchema: 'green',
tip: t('common:core.dataset.training.Leisure')
};
if (count < 1000)
return {
colorSchema: 'yellow',
tip: t('common:core.dataset.training.Waiting')
};
return {
colorSchema: 'red',
tip: t('common:core.dataset.training.Full')
};
};
const qaTrainingMap = countLLMMap(qaTrainingCount);
const autoTrainingMap = countLLMMap(autoTrainingCount);
const imageTrainingMap = countLLMMap(imageTrainingCount);
return {
vectorTrainingMap,
qaTrainingMap,
autoTrainingMap,
imageTrainingMap
};
}, [qaTrainingCount, autoTrainingCount, imageTrainingCount, vectorTrainingCount, t]);
const tabList = [
{
@@ -172,12 +234,38 @@ const NavBar = ({ currentTab }: { currentTab: TabEnum }) => {
)}
<Box mb={3}>
<Box fontSize={'sm'} pb={1}>
{t('common:core.dataset.training.Agent queue')}({agentTrainingMap.tip})
{t('common:core.dataset.training.Agent queue')}({qaTrainingMap.tip})
</Box>
<Progress
value={100}
size={'xs'}
colorScheme={agentTrainingMap.colorSchema}
colorScheme={qaTrainingMap.colorSchema}
borderRadius={'md'}
isAnimated
hasStripe
/>
</Box>
<Box mb={3}>
<Box fontSize={'sm'} pb={1}>
{t('dataset:auto_training_queue')}({autoTrainingMap.tip})
</Box>
<Progress
value={100}
size={'xs'}
colorScheme={autoTrainingMap.colorSchema}
borderRadius={'md'}
isAnimated
hasStripe
/>
</Box>
<Box mb={3}>
<Box fontSize={'sm'} pb={1}>
{t('dataset:image_training_queue')}({imageTrainingMap.tip})
</Box>
<Progress
value={100}
size={'xs'}
colorScheme={imageTrainingMap.colorSchema}
borderRadius={'md'}
isAnimated
hasStripe

View File

@@ -41,7 +41,7 @@ async function handler(req: NextApiRequest): CreateCollectionResponse {
return Promise.reject(DatasetErrEnum.sameApiCollection);
}
const content = await readApiServerFileContent({
const { title, rawText } = await readApiServerFileContent({
apiServer,
feishuServer,
yuqueServer,
@@ -53,14 +53,14 @@ async function handler(req: NextApiRequest): CreateCollectionResponse {
const { collectionId, insertResults } = await createCollectionAndInsertData({
dataset,
rawText: content,
rawText,
relatedId: apiFileId,
createCollectionParams: {
...body,
teamId,
tmbId,
type: DatasetCollectionTypeEnum.apiFile,
name,
name: title || name,
apiFileId,
metadata: {
relatedImgId: apiFileId

View File

@@ -77,7 +77,7 @@ async function handler(
return Promise.reject(i18nT('dataset:collection_not_support_retraining'));
})();
const rawText = await readDatasetSourceRawText({
const { title, rawText } = await readDatasetSourceRawText({
teamId,
tmbId,
customPdfParse,
@@ -100,7 +100,7 @@ async function handler(
teamId: collection.teamId,
tmbId: collection.tmbId,
datasetId: collection.dataset._id,
name: collection.name,
name: title || collection.name,
type: collection.type,
customPdfParse,

View File

@@ -82,7 +82,7 @@ async function handler(
};
})();
const rawText = await readDatasetSourceRawText({
const { rawText } = await readDatasetSourceRawText({
teamId,
tmbId,
type,

View File

@@ -1,27 +1,31 @@
import type { NextApiRequest } from 'next';
import { MongoDatasetTraining } from '@fastgpt/service/core/dataset/training/schema';
import { authCert } from '@fastgpt/service/support/permission/auth/common';
import { GetTrainingQueueProps } from '@/global/core/dataset/api';
import { NextAPI } from '@/service/middleware/entry';
import { readFromSecondary } from '@fastgpt/service/common/mongo/utils';
import { TrainingModeEnum } from '@fastgpt/global/core/dataset/constants';
export type GetQueueLenResponse = {
vectorTrainingCount: number;
qaTrainingCount: number;
autoTrainingCount: number;
imageTrainingCount: number;
};
async function handler(req: NextApiRequest) {
await authCert({ req, authToken: true });
const { vectorModel, agentModel } = req.query as GetTrainingQueueProps;
// get queue data
// 分别统计 model = vectorModel和agentModel的数量
const data = await MongoDatasetTraining.aggregate(
[
{
$match: {
lockTime: { $lt: new Date('2040/1/1') },
$or: [{ model: { $eq: vectorModel } }, { model: { $eq: agentModel } }]
lockTime: { $lt: new Date('2040/1/1') }
}
},
{
$group: {
_id: '$model',
_id: '$mode',
count: { $sum: 1 }
}
}
@@ -31,12 +35,16 @@ async function handler(req: NextApiRequest) {
}
);
const vectorTrainingCount = data.find((item) => item._id === vectorModel)?.count || 0;
const agentTrainingCount = data.find((item) => item._id === agentModel)?.count || 0;
const vectorTrainingCount = data.find((item) => item._id === TrainingModeEnum.chunk)?.count || 0;
const qaTrainingCount = data.find((item) => item._id === TrainingModeEnum.qa)?.count || 0;
const autoTrainingCount = data.find((item) => item._id === TrainingModeEnum.auto)?.count || 0;
const imageTrainingCount = data.find((item) => item._id === TrainingModeEnum.image)?.count || 0;
return {
vectorTrainingCount,
agentTrainingCount
qaTrainingCount,
autoTrainingCount,
imageTrainingCount
};
}

View File

@@ -1,6 +1,4 @@
import { create } from 'zustand';
import { devtools, persist } from 'zustand/middleware';
import { immer } from 'zustand/middleware/immer';
import { create, devtools, persist, immer } from '@fastgpt/web/common/zustand';
import axios from 'axios';
import { OAuthEnum } from '@fastgpt/global/support/user/constant';
import type {

View File

@@ -1,6 +1,4 @@
import { create } from 'zustand';
import { createJSONStorage, devtools, persist } from 'zustand/middleware';
import { immer } from 'zustand/middleware/immer';
import { create, createJSONStorage, devtools, persist, immer } from '@fastgpt/web/common/zustand';
import { getNanoid } from '@fastgpt/global/common/string/tools';
import { OutLinkChatAuthProps } from '@fastgpt/global/support/permission/chat';
import { ChatSourceEnum } from '@fastgpt/global/core/chat/constants';

View File

@@ -1,6 +1,4 @@
import { create } from 'zustand';
import { devtools, persist } from 'zustand/middleware';
import { immer } from 'zustand/middleware/immer';
import { create, devtools, persist, immer } from '@fastgpt/web/common/zustand';
type State = {
localUId?: string;

View File

@@ -27,12 +27,7 @@ import type {
TextCreateDatasetCollectionParams,
UpdateDatasetCollectionTagParams
} from '@fastgpt/global/core/dataset/api.d';
import type {
GetTrainingQueueProps,
GetTrainingQueueResponse,
SearchTestProps,
SearchTestResponse
} from '@/global/core/dataset/api.d';
import type { SearchTestProps, SearchTestResponse } from '@/global/core/dataset/api.d';
import type { CreateDatasetParams, InsertOneDatasetDataProps } from '@/global/core/dataset/api.d';
import type { DatasetCollectionItemType } from '@fastgpt/global/core/dataset/type';
import { DatasetCollectionSyncResultEnum } from '@fastgpt/global/core/dataset/constants';
@@ -67,6 +62,7 @@ import type {
} from '@/pages/api/core/dataset/apiDataset/listExistId';
import type { GetQuoteDataResponse } from '@/pages/api/core/dataset/data/getQuoteData';
import type { GetQuotePermissionResponse } from '@/pages/api/core/dataset/data/getPermission';
import type { GetQueueLenResponse } from '@/pages/api/core/dataset/training/getQueueLen';
/* ======================== dataset ======================= */
export const getDatasets = (data: GetDatasetListBody) =>
@@ -215,8 +211,8 @@ export const postRebuildEmbedding = (data: rebuildEmbeddingBody) =>
POST(`/core/dataset/training/rebuildEmbedding`, data);
/* get length of system training queue */
export const getTrainingQueueLen = (data: GetTrainingQueueProps) =>
GET<GetTrainingQueueResponse>(`/core/dataset/training/getQueueLen`, data);
export const getTrainingQueueLen = () =>
GET<GetQueueLenResponse>(`/core/dataset/training/getQueueLen`);
export const getDatasetTrainingQueue = (datasetId: string) =>
GET<getDatasetTrainingQueueResponse>(`/core/dataset/training/getDatasetTrainingQueue`, {
datasetId

View File

@@ -1,5 +1,5 @@
import { useQuery } from '@tanstack/react-query';
import { Dispatch, ReactNode, SetStateAction, useMemo, useState } from 'react';
import { Dispatch, ReactNode, SetStateAction, useState } from 'react';
import { useTranslation } from 'next-i18next';
import { createContext } from 'use-context-selector';
import {
@@ -8,7 +8,6 @@ import {
getDatasetCollectionTags,
getDatasetPaths,
getDatasetTrainingQueue,
getTrainingQueueLen,
postCreateDatasetCollectionTag,
putDatasetById
} from '../api';
@@ -37,28 +36,13 @@ type DatasetPageContextType = {
setSearchTagKey: Dispatch<SetStateAction<string>>;
paths: ParentTreePathItemType[];
refetchPaths: () => void;
vectorTrainingMap: {
colorSchema: string;
tip: string;
};
agentTrainingMap: {
colorSchema: string;
tip: string;
};
rebuildingCount: number;
trainingCount: number;
refetchDatasetTraining: () => void;
};
export const DatasetPageContext = createContext<DatasetPageContextType>({
vectorTrainingMap: {
colorSchema: '',
tip: ''
},
agentTrainingMap: {
colorSchema: '',
tip: ''
},
rebuildingCount: 0,
trainingCount: 0,
refetchDatasetTraining: function (): void {
@@ -191,57 +175,6 @@ export const DatasetPageContextProvider = ({
}
);
// global queue
const { data: { vectorTrainingCount = 0, agentTrainingCount = 0 } = {} } = useQuery(
['getTrainingQueueLen'],
() =>
getTrainingQueueLen({
vectorModel: datasetDetail.vectorModel.model,
agentModel: datasetDetail.agentModel.model
}),
{
refetchInterval: 10000
}
);
const { vectorTrainingMap, agentTrainingMap } = useMemo(() => {
const vectorTrainingMap = (() => {
if (vectorTrainingCount < 1000)
return {
colorSchema: 'green',
tip: t('common:core.dataset.training.Leisure')
};
if (vectorTrainingCount < 10000)
return {
colorSchema: 'yellow',
tip: t('common:core.dataset.training.Waiting')
};
return {
colorSchema: 'red',
tip: t('common:core.dataset.training.Full')
};
})();
const agentTrainingMap = (() => {
if (agentTrainingCount < 100)
return {
colorSchema: 'green',
tip: t('common:core.dataset.training.Leisure')
};
if (agentTrainingCount < 1000)
return {
colorSchema: 'yellow',
tip: t('common:core.dataset.training.Waiting')
};
return {
colorSchema: 'red',
tip: t('common:core.dataset.training.Full')
};
})();
return {
vectorTrainingMap,
agentTrainingMap
};
}, [agentTrainingCount, t, vectorTrainingCount]);
// training and rebuild queue
const { data: { rebuildingCount = 0, trainingCount = 0 } = {}, refetch: refetchDatasetTraining } =
useQuery(['getDatasetTrainingQueue'], () => getDatasetTrainingQueue(datasetId), {
@@ -273,8 +206,7 @@ export const DatasetPageContextProvider = ({
updateDataset,
paths,
refetchPaths,
vectorTrainingMap,
agentTrainingMap,
rebuildingCount,
trainingCount,
refetchDatasetTraining,

View File

@@ -1,6 +1,4 @@
import { create } from 'zustand';
import { devtools, persist } from 'zustand/middleware';
import { immer } from 'zustand/middleware/immer';
import { create, devtools, persist, immer } from '@fastgpt/web/common/zustand';
import type { DatasetListItemType } from '@fastgpt/global/core/dataset/type.d';
import { getDatasets } from '@/web/core/dataset/api';

View File

@@ -1,6 +1,4 @@
import { create } from 'zustand';
import { devtools } from 'zustand/middleware';
import { immer } from 'zustand/middleware/immer';
import { create, devtools, immer } from '@fastgpt/web/common/zustand';
export type MarkDataStore = {
dataId: string;

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@@ -1,6 +1,5 @@
import { create } from 'zustand';
import { devtools, persist } from 'zustand/middleware';
import { immer } from 'zustand/middleware/immer';
import { create, devtools, persist, immer } from '@fastgpt/web/common/zustand';
import type { SearchDataResponseItemType } from '@fastgpt/global/core/dataset/type';
import { DatasetSearchModeEnum } from '@fastgpt/global/core/dataset/constants';

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@@ -1,3 +1,5 @@
import { create, devtools, persist, immer } from '@fastgpt/web/common/zustand';
import type { UserUpdateParams } from '@/types/user';
import { useSystemStore } from '@/web/common/system/useSystemStore';
import { getTokenLogin, putUserInfo } from '@/web/support/user/api';
@@ -5,9 +7,6 @@ import type { MemberGroupListType } from '@fastgpt/global/support/permission/mem
import type { OrgType } from '@fastgpt/global/support/user/team/org/type';
import type { UserType } from '@fastgpt/global/support/user/type.d';
import type { FeTeamPlanStatusType } from '@fastgpt/global/support/wallet/sub/type';
import { create } from 'zustand';
import { devtools, persist } from 'zustand/middleware';
import { immer } from 'zustand/middleware/immer';
import { getTeamPlanStatus } from './team/api';
import { getGroupList } from './team/group/api';
import { getOrgList } from './team/org/api';