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* update: Add type * fix: update import statement for NextApiRequest type * fix: update imports to use type for LexicalEditor and EditorState * Refactor imports to use 'import type' for type-only imports across multiple files - Updated imports in various components and API files to use 'import type' for better clarity and to optimize TypeScript's type checking. - Ensured consistent usage of type imports in files related to chat, dataset, workflow, and user management. - Improved code readability and maintainability by distinguishing between value and type imports. * refactor: remove old ESLint configuration and add new rules - Deleted the old ESLint configuration file from the app project. - Added a new ESLint configuration file with updated rules and settings. - Changed imports to use type-only imports in various files for better clarity and performance. - Updated TypeScript configuration to remove unnecessary options. - Added an ESLint ignore file to exclude build and dependency directories from linting. * fix: update imports to use 'import type' for type-only imports in schema files
252 lines
6.8 KiB
TypeScript
252 lines
6.8 KiB
TypeScript
import { MongoDatasetCollection } from './schema';
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import { type ClientSession } from '../../../common/mongo';
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import { MongoDatasetCollectionTags } from '../tag/schema';
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import { readFromSecondary } from '../../../common/mongo/utils';
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import {
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type CollectionWithDatasetType,
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type DatasetCollectionSchemaType
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} from '@fastgpt/global/core/dataset/type';
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import {
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DatasetCollectionDataProcessModeEnum,
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DatasetCollectionSyncResultEnum,
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DatasetCollectionTypeEnum,
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DatasetSourceReadTypeEnum,
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TrainingModeEnum
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} from '@fastgpt/global/core/dataset/constants';
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import { DatasetErrEnum } from '@fastgpt/global/common/error/code/dataset';
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import { readDatasetSourceRawText } from '../read';
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import { hashStr } from '@fastgpt/global/common/string/tools';
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import { mongoSessionRun } from '../../../common/mongo/sessionRun';
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import { createCollectionAndInsertData, delCollection } from './controller';
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import { collectionCanSync } from '@fastgpt/global/core/dataset/collection/utils';
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/**
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* get all collection by top collectionId
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*/
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export async function findCollectionAndChild({
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teamId,
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datasetId,
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collectionId,
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fields = '_id parentId name metadata'
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}: {
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teamId: string;
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datasetId: string;
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collectionId: string;
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fields?: string;
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}) {
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async function find(id: string) {
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// find children
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const children = await MongoDatasetCollection.find(
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{ teamId, datasetId, parentId: id },
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fields
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).lean();
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let collections = children;
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for (const child of children) {
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const grandChildrenIds = await find(child._id);
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collections = collections.concat(grandChildrenIds);
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}
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return collections;
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}
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const [collection, childCollections] = await Promise.all([
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MongoDatasetCollection.findById(collectionId, fields).lean(),
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find(collectionId)
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]);
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if (!collection) {
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return Promise.reject('Collection not found');
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}
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return [collection, ...childCollections];
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}
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export function getCollectionUpdateTime({ name, time }: { time?: Date; name: string }) {
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if (time) return time;
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if (name.startsWith('手动') || ['manual', 'mark'].includes(name)) return new Date('2999/9/9');
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return new Date();
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}
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export const createOrGetCollectionTags = async ({
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tags,
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datasetId,
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teamId,
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session
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}: {
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tags?: string[];
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datasetId: string;
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teamId: string;
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session?: ClientSession;
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}) => {
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if (!tags) return undefined;
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if (tags.length === 0) return [];
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const existingTags = await MongoDatasetCollectionTags.find(
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{
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teamId,
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datasetId,
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tag: { $in: tags }
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},
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undefined,
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{ session }
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).lean();
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const existingTagContents = existingTags.map((tag) => tag.tag);
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const newTagContents = tags.filter((tag) => !existingTagContents.includes(tag));
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const newTags = await MongoDatasetCollectionTags.insertMany(
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newTagContents.map((tagContent) => ({
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teamId,
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datasetId,
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tag: tagContent
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})),
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{ session, ordered: true }
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);
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return [...existingTags.map((tag) => tag._id), ...newTags.map((tag) => tag._id)];
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};
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export const collectionTagsToTagLabel = async ({
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datasetId,
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tags
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}: {
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datasetId: string;
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tags?: string[];
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}) => {
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if (!tags) return undefined;
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if (tags.length === 0) return;
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// Get all the tags
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const collectionTags = await MongoDatasetCollectionTags.find({ datasetId }, undefined, {
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...readFromSecondary
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}).lean();
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const tagsMap = new Map<string, string>();
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collectionTags.forEach((tag) => {
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tagsMap.set(String(tag._id), tag.tag);
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});
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return tags
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.map((tag) => {
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return tagsMap.get(tag) || '';
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})
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.filter(Boolean);
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};
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export const syncCollection = async (collection: CollectionWithDatasetType) => {
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const dataset = collection.dataset;
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if (!collectionCanSync(collection.type)) {
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return Promise.reject(DatasetErrEnum.notSupportSync);
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}
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// Get new text
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const sourceReadType = await (async () => {
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if (collection.type === DatasetCollectionTypeEnum.link) {
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if (!collection.rawLink) return Promise.reject('rawLink is missing');
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return {
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type: DatasetSourceReadTypeEnum.link,
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sourceId: collection.rawLink,
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selector: collection.metadata?.webPageSelector
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};
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}
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const sourceId = collection.apiFileId;
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if (!sourceId) return Promise.reject('apiFileId is missing');
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return {
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type: DatasetSourceReadTypeEnum.apiFile,
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sourceId,
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apiServer: dataset.apiServer,
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feishuServer: dataset.feishuServer,
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yuqueServer: dataset.yuqueServer
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};
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})();
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const { title, rawText } = await readDatasetSourceRawText({
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teamId: collection.teamId,
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tmbId: collection.tmbId,
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...sourceReadType
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});
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if (!rawText) {
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return DatasetCollectionSyncResultEnum.failed;
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}
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// Check if the original text is the same: skip if same
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const hashRawText = hashStr(rawText);
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if (collection.hashRawText && hashRawText === collection.hashRawText) {
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return DatasetCollectionSyncResultEnum.sameRaw;
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}
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await mongoSessionRun(async (session) => {
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// Delete old collection
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await delCollection({
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collections: [collection],
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delImg: false,
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delFile: false,
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session
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});
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// Create new collection
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await createCollectionAndInsertData({
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session,
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dataset,
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rawText: rawText,
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createCollectionParams: {
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teamId: collection.teamId,
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tmbId: collection.tmbId,
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name: title || collection.name,
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datasetId: collection.datasetId,
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parentId: collection.parentId,
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type: collection.type,
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trainingType: collection.trainingType,
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chunkSize: collection.chunkSize,
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chunkSplitter: collection.chunkSplitter,
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qaPrompt: collection.qaPrompt,
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fileId: collection.fileId,
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rawLink: collection.rawLink,
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externalFileId: collection.externalFileId,
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externalFileUrl: collection.externalFileUrl,
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apiFileId: collection.apiFileId,
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hashRawText,
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rawTextLength: rawText.length,
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metadata: collection.metadata,
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tags: collection.tags,
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createTime: collection.createTime,
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updateTime: new Date()
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}
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});
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});
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return DatasetCollectionSyncResultEnum.success;
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};
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/*
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QA: 独立进程
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Chunk: Image Index -> Auto index -> chunk index
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*/
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export const getTrainingModeByCollection = (collection: {
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trainingType: DatasetCollectionSchemaType['trainingType'];
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autoIndexes?: DatasetCollectionSchemaType['autoIndexes'];
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imageIndex?: DatasetCollectionSchemaType['imageIndex'];
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}) => {
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if (collection.trainingType === DatasetCollectionDataProcessModeEnum.qa) {
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return TrainingModeEnum.qa;
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}
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if (collection.imageIndex && global.feConfigs?.isPlus) {
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return TrainingModeEnum.image;
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}
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if (collection.autoIndexes && global.feConfigs?.isPlus) {
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return TrainingModeEnum.auto;
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}
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return TrainingModeEnum.chunk;
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};
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