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* 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>
258 lines
6.4 KiB
TypeScript
258 lines
6.4 KiB
TypeScript
import { Types, connectionMongo, ReadPreference } from '../../mongo';
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import type { BucketNameEnum } from '@fastgpt/global/common/file/constants';
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import fsp from 'fs/promises';
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import fs from 'fs';
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import { type DatasetFileSchema } from '@fastgpt/global/core/dataset/type';
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import { MongoChatFileSchema, MongoDatasetFileSchema } from './schema';
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import { detectFileEncoding, detectFileEncodingByPath } from '@fastgpt/global/common/file/tools';
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import { CommonErrEnum } from '@fastgpt/global/common/error/code/common';
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import { readRawContentByFileBuffer } from '../read/utils';
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import { computeGridFsChunSize, gridFsStream2Buffer, stream2Encoding } from './utils';
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import { addLog } from '../../system/log';
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import { parseFileExtensionFromUrl } from '@fastgpt/global/common/string/tools';
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import { Readable } from 'stream';
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import { addRawTextBuffer, getRawTextBuffer } from '../../buffer/rawText/controller';
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import { addMinutes } from 'date-fns';
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import { retryFn } from '@fastgpt/global/common/system/utils';
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export function getGFSCollection(bucket: `${BucketNameEnum}`) {
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MongoDatasetFileSchema;
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MongoChatFileSchema;
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return connectionMongo.connection.db!.collection(`${bucket}.files`);
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}
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export function getGridBucket(bucket: `${BucketNameEnum}`) {
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return new connectionMongo.mongo.GridFSBucket(connectionMongo.connection.db!, {
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bucketName: bucket,
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// @ts-ignore
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readPreference: ReadPreference.SECONDARY_PREFERRED // Read from secondary node
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});
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}
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/* crud file */
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export async function uploadFile({
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bucketName,
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teamId,
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uid,
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path,
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filename,
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contentType,
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metadata = {}
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}: {
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bucketName: `${BucketNameEnum}`;
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teamId: string;
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uid: string; // tmbId / outLinkUId
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path: string;
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filename: string;
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contentType?: string;
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metadata?: Record<string, any>;
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}) {
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if (!path) return Promise.reject(`filePath is empty`);
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if (!filename) return Promise.reject(`filename is empty`);
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const stats = await fsp.stat(path);
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if (!stats.isFile()) return Promise.reject(`${path} is not a file`);
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const readStream = fs.createReadStream(path, {
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highWaterMark: 256 * 1024
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});
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// Add default metadata
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metadata.teamId = teamId;
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metadata.uid = uid;
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metadata.encoding = await detectFileEncodingByPath(path);
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// create a gridfs bucket
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const bucket = getGridBucket(bucketName);
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const chunkSizeBytes = computeGridFsChunSize(stats.size);
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const stream = bucket.openUploadStream(filename, {
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metadata,
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contentType,
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chunkSizeBytes
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});
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// save to gridfs
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await new Promise((resolve, reject) => {
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readStream
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.pipe(stream as any)
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.on('finish', resolve)
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.on('error', reject);
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});
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return String(stream.id);
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}
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export async function uploadFileFromBase64Img({
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bucketName,
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teamId,
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tmbId,
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base64,
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filename,
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metadata = {}
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}: {
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bucketName: `${BucketNameEnum}`;
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teamId: string;
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tmbId: string;
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base64: string;
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filename: string;
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metadata?: Record<string, any>;
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}) {
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if (!base64) return Promise.reject(`filePath is empty`);
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if (!filename) return Promise.reject(`filename is empty`);
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const base64Data = base64.split(',')[1];
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const contentType = base64.split(',')?.[0]?.split?.(':')?.[1];
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const buffer = Buffer.from(base64Data, 'base64');
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const readableStream = new Readable({
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read() {
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this.push(buffer);
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this.push(null);
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}
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});
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const { stream: readStream, encoding } = await stream2Encoding(readableStream);
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// Add default metadata
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metadata.teamId = teamId;
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metadata.tmbId = tmbId;
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metadata.encoding = encoding;
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// create a gridfs bucket
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const bucket = getGridBucket(bucketName);
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const stream = bucket.openUploadStream(filename, {
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metadata,
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contentType
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});
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// save to gridfs
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await new Promise((resolve, reject) => {
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readStream
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.pipe(stream as any)
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.on('finish', resolve)
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.on('error', reject);
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});
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return String(stream.id);
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}
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export async function getFileById({
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bucketName,
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fileId
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}: {
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bucketName: `${BucketNameEnum}`;
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fileId: string;
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}) {
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const db = getGFSCollection(bucketName);
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const file = await db.findOne<DatasetFileSchema>({
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_id: new Types.ObjectId(fileId)
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});
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// if (!file) {
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// return Promise.reject('File not found');
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// }
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return file || undefined;
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}
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export async function delFileByFileIdList({
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bucketName,
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fileIdList
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}: {
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bucketName: `${BucketNameEnum}`;
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fileIdList: string[];
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}): Promise<any> {
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return retryFn(async () => {
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const bucket = getGridBucket(bucketName);
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for await (const fileId of fileIdList) {
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await bucket.delete(new Types.ObjectId(fileId));
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}
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});
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}
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export async function getDownloadStream({
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bucketName,
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fileId
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}: {
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bucketName: `${BucketNameEnum}`;
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fileId: string;
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}) {
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const bucket = getGridBucket(bucketName);
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return bucket.openDownloadStream(new Types.ObjectId(fileId));
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}
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export const readFileContentFromMongo = async ({
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teamId,
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tmbId,
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bucketName,
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fileId,
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customPdfParse = false,
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getFormatText
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}: {
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teamId: string;
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tmbId: string;
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bucketName: `${BucketNameEnum}`;
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fileId: string;
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customPdfParse?: boolean;
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getFormatText?: boolean; // 数据类型都尽可能转化成 markdown 格式
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}): Promise<{
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rawText: string;
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filename: string;
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}> => {
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const bufferId = `${String(fileId)}-${customPdfParse}`;
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// read buffer
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const fileBuffer = await getRawTextBuffer(bufferId);
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if (fileBuffer) {
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return {
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rawText: fileBuffer.text,
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filename: fileBuffer?.sourceName
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};
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}
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const [file, fileStream] = await Promise.all([
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getFileById({ bucketName, fileId }),
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getDownloadStream({ bucketName, fileId })
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]);
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if (!file) {
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return Promise.reject(CommonErrEnum.fileNotFound);
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}
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const extension = parseFileExtensionFromUrl(file?.filename);
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const start = Date.now();
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const fileBuffers = await gridFsStream2Buffer(fileStream);
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addLog.debug('get file buffer', { time: Date.now() - start });
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const encoding = file?.metadata?.encoding || detectFileEncoding(fileBuffers);
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// Get raw text
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const { rawText } = await readRawContentByFileBuffer({
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customPdfParse,
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getFormatText,
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extension,
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teamId,
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tmbId,
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buffer: fileBuffers,
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encoding,
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metadata: {
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relatedId: fileId
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}
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});
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// Add buffer
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addRawTextBuffer({
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sourceId: bufferId,
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sourceName: file.filename,
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text: rawText,
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expiredTime: addMinutes(new Date(), 20)
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});
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return {
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rawText,
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filename: file.filename
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};
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};
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