FastGPT/packages/service/core/dataset/collection/utils.ts

import { MongoDatasetCollection } from './schema';
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 {
  DatasetCollectionDataProcessModeEnum,
  DatasetCollectionSyncResultEnum,
  DatasetCollectionTypeEnum,
  DatasetSourceReadTypeEnum,
  TrainingModeEnum
} from '@fastgpt/global/core/dataset/constants';
import { DatasetErrEnum } from '@fastgpt/global/common/error/code/dataset';
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
 */
export async function findCollectionAndChild({
  teamId,
  datasetId,
  collectionId,
  fields = '_id parentId name metadata'
}: {
  teamId: string;
  datasetId: string;
  collectionId: string;
  fields?: string;
}) {
  async function find(id: string) {
    // find children
    const children = await MongoDatasetCollection.find(
      { teamId, datasetId, parentId: id },
      fields
    ).lean();

    let collections = children;

    for (const child of children) {
      const grandChildrenIds = await find(child._id);
      collections = collections.concat(grandChildrenIds);
    }

    return collections;
  }
  const [collection, childCollections] = await Promise.all([
    MongoDatasetCollection.findById(collectionId, fields).lean(),
    find(collectionId)
  ]);

  if (!collection) {
    return Promise.reject('Collection not found');
  }

  return [collection, ...childCollections];
}

export function getCollectionUpdateTime({ name, time }: { time?: Date; name: string }) {
  if (time) return time;
  if (name.startsWith('手动') || ['manual', 'mark'].includes(name)) return new Date('2999/9/9');
  return new Date();
}

export const createOrGetCollectionTags = async ({
  tags,
  datasetId,
  teamId,
  session
}: {
  tags?: string[];
  datasetId: string;
  teamId: string;
  session?: ClientSession;
}) => {
  if (!tags) return undefined;

  if (tags.length === 0) return [];

  const existingTags = await MongoDatasetCollectionTags.find(
    {
      teamId,
      datasetId,
      tag: { $in: tags }
    },
    undefined,
    { session }
  ).lean();

  const existingTagContents = existingTags.map((tag) => tag.tag);
  const newTagContents = tags.filter((tag) => !existingTagContents.includes(tag));

  const newTags = await MongoDatasetCollectionTags.insertMany(
    newTagContents.map((tagContent) => ({
      teamId,
      datasetId,
      tag: tagContent
    })),
    { session, ordered: true }
  );

  return [...existingTags.map((tag) => tag._id), ...newTags.map((tag) => tag._id)];
};

export const collectionTagsToTagLabel = async ({
  datasetId,
  tags
}: {
  datasetId: string;
  tags?: string[];
}) => {
  if (!tags) return undefined;
  if (tags.length === 0) return;

  // Get all the tags
  const collectionTags = await MongoDatasetCollectionTags.find({ datasetId }, undefined, {
    ...readFromSecondary
  }).lean();
  const tagsMap = new Map<string, string>();
  collectionTags.forEach((tag) => {
    tagsMap.set(String(tag._id), tag.tag);
  });

  return tags
    .map((tag) => {
      return tagsMap.get(tag) || '';
    })
    .filter(Boolean);
};

export const syncCollection = async (collection: CollectionWithDatasetType) => {
  const dataset = collection.dataset;

  if (!collectionCanSync(collection.type)) {
    return Promise.reject(DatasetErrEnum.notSupportSync);
  }

  // Get new text
  const sourceReadType = await (async () => {
    if (collection.type === DatasetCollectionTypeEnum.link) {
      if (!collection.rawLink) return Promise.reject('rawLink is missing');
      return {
        type: DatasetSourceReadTypeEnum.link,
        sourceId: collection.rawLink,
        selector: collection.metadata?.webPageSelector
      };
    }

    const sourceId = collection.apiFileId;

    if (!sourceId) return Promise.reject('apiFileId is missing');

    return {
      type: DatasetSourceReadTypeEnum.apiFile,
      sourceId,
      apiDatasetServer: dataset.apiDatasetServer
    };
  })();

  const { title, rawText } = await readDatasetSourceRawText({
    teamId: collection.teamId,
    tmbId: collection.tmbId,
    ...sourceReadType
  });

  if (!rawText) {
    return DatasetCollectionSyncResultEnum.failed;
  }

  // Check if the original text is the same: skip if same
  const hashRawText = hashStr(rawText);
  if (collection.hashRawText && hashRawText === collection.hashRawText) {
    return DatasetCollectionSyncResultEnum.sameRaw;
  }

  await mongoSessionRun(async (session) => {
    // Delete old collection
    await delCollection({
      collections: [collection],
      delImg: false,
      delFile: false,
      session
    });

    // Create new collection
    await createCollectionAndInsertData({
      session,
      dataset,
      rawText: rawText,
      createCollectionParams: {
        ...collection,
        name: title || collection.name,
        updateTime: new Date()
      }
    });
  });

  return DatasetCollectionSyncResultEnum.success;
};

/* 
  QA: 独立进程
  Chunk: Image Index -> Auto index -> chunk index
*/
export const getTrainingModeByCollection = ({
  trainingType,
  autoIndexes,
  imageIndex
}: {
  trainingType: DatasetCollectionDataProcessModeEnum;
  autoIndexes?: boolean;
  imageIndex?: boolean;
}) => {
  if (
    trainingType === DatasetCollectionDataProcessModeEnum.imageParse &&
    global.feConfigs?.isPlus
  ) {
    return TrainingModeEnum.imageParse;
  }

  if (trainingType === DatasetCollectionDataProcessModeEnum.qa) {
    return TrainingModeEnum.qa;
  }
  if (
    trainingType === DatasetCollectionDataProcessModeEnum.chunk &&
    imageIndex &&
    global.feConfigs?.isPlus
  ) {
    return TrainingModeEnum.image;
  }
  if (
    trainingType === DatasetCollectionDataProcessModeEnum.chunk &&
    autoIndexes &&
    global.feConfigs?.isPlus
  ) {
    return TrainingModeEnum.auto;
  }
  return TrainingModeEnum.chunk;
};