Files
FastGPT/packages/service/core/dataset/collection/controller.ts
Archer 21288d1736 Feat: pptx and xlsx loader (#1118)
* perf: plan tip

* perf: upload size controller

* feat: add image ttl index

* feat: new upload file ux

* remove file

* feat: support read pptx

* feat: support xlsx

* fix: rerank docker flie
2024-04-01 19:01:26 +08:00

172 lines
3.8 KiB
TypeScript

import {
TrainingModeEnum,
DatasetCollectionTypeEnum
} from '@fastgpt/global/core/dataset/constants';
import type { CreateDatasetCollectionParams } from '@fastgpt/global/core/dataset/api.d';
import { MongoDatasetCollection } from './schema';
import {
CollectionWithDatasetType,
DatasetCollectionSchemaType
} from '@fastgpt/global/core/dataset/type';
import { MongoDatasetTraining } from '../training/schema';
import { MongoDatasetData } from '../data/schema';
import { delImgByRelatedId } from '../../../common/file/image/controller';
import { deleteDatasetDataVector } from '../../../common/vectorStore/controller';
import { delFileByFileIdList } from '../../../common/file/gridfs/controller';
import { BucketNameEnum } from '@fastgpt/global/common/file/constants';
import { ClientSession } from '../../../common/mongo';
export async function createOneCollection({
teamId,
tmbId,
name,
parentId,
datasetId,
type,
trainingType = TrainingModeEnum.chunk,
chunkSize = 512,
chunkSplitter,
qaPrompt,
fileId,
rawLink,
hashRawText,
rawTextLength,
metadata = {},
session,
...props
}: CreateDatasetCollectionParams & {
teamId: string;
tmbId: string;
[key: string]: any;
session?: ClientSession;
}) {
const [collection] = await MongoDatasetCollection.create(
[
{
...props,
teamId,
tmbId,
parentId: parentId || null,
datasetId,
name,
type,
trainingType,
chunkSize,
chunkSplitter,
qaPrompt,
fileId,
rawLink,
rawTextLength,
hashRawText,
metadata
}
],
{ session }
);
// create default collection
if (type === DatasetCollectionTypeEnum.folder) {
await createDefaultCollection({
datasetId,
parentId: collection._id,
teamId,
tmbId,
session
});
}
return collection;
}
// create default collection
export function createDefaultCollection({
name = '手动录入',
datasetId,
parentId,
teamId,
tmbId,
session
}: {
name?: '手动录入' | '手动标注';
datasetId: string;
parentId?: string;
teamId: string;
tmbId: string;
session?: ClientSession;
}) {
return MongoDatasetCollection.create(
[
{
name,
teamId,
tmbId,
datasetId,
parentId,
type: DatasetCollectionTypeEnum.virtual,
trainingType: TrainingModeEnum.chunk,
chunkSize: 0,
updateTime: new Date('2099')
}
],
{ session }
);
}
/**
* delete collection and it related data
*/
export async function delCollectionAndRelatedSources({
collections,
session
}: {
collections: (CollectionWithDatasetType | DatasetCollectionSchemaType)[];
session: ClientSession;
}) {
if (collections.length === 0) return;
const teamId = collections[0].teamId;
if (!teamId) return Promise.reject('teamId is not exist');
const collectionIds = collections.map((item) => String(item._id));
const fileIdList = collections.map((item) => item?.fileId || '').filter(Boolean);
const relatedImageIds = collections
.map((item) => item?.metadata?.relatedImgId || '')
.filter(Boolean);
// delete training data
await MongoDatasetTraining.deleteMany({
teamId,
collectionId: { $in: collectionIds }
});
// delete dataset.datas
await MongoDatasetData.deleteMany({ teamId, collectionId: { $in: collectionIds } }, { session });
// delete imgs
await delImgByRelatedId({
teamId,
relateIds: relatedImageIds,
session
});
// delete collections
await MongoDatasetCollection.deleteMany(
{
_id: { $in: collectionIds }
},
{ session }
);
// no session delete: delete files, vector data
await deleteDatasetDataVector({ teamId, collectionIds });
await delFileByFileIdList({
bucketName: BucketNameEnum.dataset,
fileIdList
});
}