Files
FastGPT/packages/service/core/dataset/training/schema.ts
Archer c30f069f2f V4.9.11 feature (#4969)
* Feat: Images dataset collection (#4941)

* New pic (#4858)

* 更新数据集相关类型,添加图像文件ID和预览URL支持;优化数据集导入功能,新增图像数据集处理组件;修复部分国际化文本;更新文件上传逻辑以支持新功能。

* 与原先代码的差别

* 新增 V4.9.10 更新说明,支持 PG 设置`systemEnv.hnswMaxScanTuples`参数,优化 LLM stream 调用超时,修复全文检索多知识库排序问题。同时更新数据集索引,移除 datasetId 字段以简化查询。

* 更换成fileId_image逻辑,并增加训练队列匹配的逻辑

* 新增图片集合判断逻辑,优化预览URL生成流程,确保仅在数据集为图片集合时生成预览URL,并添加相关日志输出以便调试。

* Refactor Docker Compose configuration to comment out exposed ports for production environments, update image versions for pgvector, fastgpt, and mcp_server, and enhance Redis service with a health check. Additionally, standardize dataset collection labels in constants and improve internationalization strings across multiple languages.

* Enhance TrainingStates component by adding internationalization support for the imageParse training mode and update defaultCounts to include imageParse mode in trainingDetail API.

* Enhance dataset import context by adding additional steps for image dataset import process and improve internationalization strings for modal buttons in the useEditTitle hook.

* Update DatasetImportContext to conditionally render MyStep component based on data source type, improving the import process for non-image datasets.

* Refactor image dataset handling by improving internationalization strings, enhancing error messages, and streamlining the preview URL generation process.

* 图片上传到新建的 dataset_collection_images 表,逻辑跟随更改

* 修改了除了controller的其他部分问题

* 把图片数据集的逻辑整合到controller里面

* 补充i18n

* 补充i18n

* resolve评论:主要是上传逻辑的更改和组件复用

* 图片名称的图标显示

* 修改编译报错的命名问题

* 删除不需要的collectionid部分

* 多余文件的处理和改动一个删除按钮

* 除了loading和统一的imageId,其他都resolve掉的

* 处理图标报错

* 复用了MyPhotoView并采用全部替换的方式将imageFileId变成imageId

* 去除不必要文件修改

* 报错和字段修改

* 增加上传成功后删除临时文件的逻辑以及回退一些修改

* 删除path字段,将图片保存到gridfs内,并修改增删等操作的代码

* 修正编译错误

---------

Co-authored-by: archer <545436317@qq.com>

* perf: image dataset

* feat: insert image

* perf: image icon

* fix: training state

---------

Co-authored-by: Zhuangzai fa <143257420+ctrlz526@users.noreply.github.com>

* fix: ts (#4948)

* Thirddatasetmd (#4942)

* add thirddataset.md

* fix thirddataset.md

* fix

* delete wrong png

---------

Co-authored-by: dreamer6680 <146868355@qq.com>

* perf: api dataset code

* perf: log

* add secondary.tsx (#4946)

* add secondary.tsx

* fix

---------

Co-authored-by: dreamer6680 <146868355@qq.com>

* perf: multiple menu

* perf: i18n

* feat: parse queue (#4960)

* feat: parse queue

* feat: sync parse queue

* fix thirddataset.md (#4962)

* fix thirddataset-4.png (#4963)

* feat: Dataset template import (#4934)

* 模版导入部分除了文档还没写

* 修复模版导入的 build 错误

* Document production

* compress pictures

* Change some constants to variables

---------

Co-authored-by: Archer <545436317@qq.com>

* perf: template import

* doc

* llm pargraph

* bocha tool

* fix: del collection

---------

Co-authored-by: Zhuangzai fa <143257420+ctrlz526@users.noreply.github.com>
Co-authored-by: dreamer6680 <1468683855@qq.com>
Co-authored-by: dreamer6680 <146868355@qq.com>
2025-06-06 14:48:44 +08:00

124 lines
2.8 KiB
TypeScript

/* 模型的知识库 */
import { connectionMongo, getMongoModel } from '../../../common/mongo';
const { Schema } = connectionMongo;
import { type DatasetTrainingSchemaType } from '@fastgpt/global/core/dataset/type';
import { TrainingModeEnum } from '@fastgpt/global/core/dataset/constants';
import { DatasetColCollectionName } from '../collection/schema';
import { DatasetCollectionName } from '../schema';
import {
TeamCollectionName,
TeamMemberCollectionName
} from '@fastgpt/global/support/user/team/constant';
import { DatasetDataIndexTypeEnum } from '@fastgpt/global/core/dataset/data/constants';
export const DatasetTrainingCollectionName = 'dataset_trainings';
const TrainingDataSchema = new Schema({
teamId: {
type: Schema.Types.ObjectId,
ref: TeamCollectionName,
required: true
},
tmbId: {
type: Schema.Types.ObjectId,
ref: TeamMemberCollectionName,
required: true
},
datasetId: {
type: Schema.Types.ObjectId,
required: true
},
collectionId: {
type: Schema.Types.ObjectId,
ref: DatasetColCollectionName,
required: true
},
billId: String,
mode: {
type: String,
enum: Object.values(TrainingModeEnum),
required: true
},
expireAt: {
// It will be deleted after 7 days
type: Date,
default: () => new Date()
},
lockTime: {
type: Date,
default: () => new Date('2000/1/1')
},
retryCount: {
type: Number,
default: 5
},
model: String,
prompt: String,
q: {
type: String,
default: ''
},
a: {
type: String,
default: ''
},
imageId: String,
chunkIndex: {
type: Number,
default: 0
},
indexSize: Number,
weight: {
type: Number,
default: 0
},
dataId: Schema.Types.ObjectId,
indexes: {
type: [
{
type: {
type: String,
enum: Object.values(DatasetDataIndexTypeEnum)
},
text: {
type: String,
required: true
}
}
],
default: []
},
errorMsg: String
});
TrainingDataSchema.virtual('dataset', {
ref: DatasetCollectionName,
localField: 'datasetId',
foreignField: '_id',
justOne: true
});
TrainingDataSchema.virtual('collection', {
ref: DatasetColCollectionName,
localField: 'collectionId',
foreignField: '_id',
justOne: true
});
try {
// lock training data(teamId); delete training data
TrainingDataSchema.index({ teamId: 1, datasetId: 1 });
// get training data and sort
TrainingDataSchema.index({ mode: 1, retryCount: 1, lockTime: 1, weight: -1 });
TrainingDataSchema.index({ expireAt: 1 }, { expireAfterSeconds: 7 * 24 * 60 * 60 }); // 7 days
} catch (error) {
console.log(error);
}
export const MongoDatasetTraining = getMongoModel<DatasetTrainingSchemaType>(
DatasetTrainingCollectionName,
TrainingDataSchema
);