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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>
125 lines
3.5 KiB
TypeScript
125 lines
3.5 KiB
TypeScript
import { detectFileEncoding } from '@fastgpt/global/common/file/tools';
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import { PassThrough } from 'stream';
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import { getGridBucket } from './controller';
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import { type BucketNameEnum } from '@fastgpt/global/common/file/constants';
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import { retryFn } from '@fastgpt/global/common/system/utils';
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export const createFileFromText = async ({
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bucket,
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filename,
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text,
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metadata
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}: {
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bucket: `${BucketNameEnum}`;
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filename: string;
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text: string;
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metadata: Record<string, any>;
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}) => {
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const gridBucket = getGridBucket(bucket);
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const buffer = Buffer.from(text);
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const fileSize = buffer.length;
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// 单块大小:尽可能大,但不超过 14MB,不小于128KB
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const chunkSizeBytes = (() => {
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// 计算理想块大小:文件大小 ÷ 目标块数(10)。 并且每个块需要小于 14MB
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const idealChunkSize = Math.min(Math.ceil(fileSize / 10), 14 * 1024 * 1024);
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// 确保块大小至少为128KB
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const minChunkSize = 128 * 1024; // 128KB
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// 取理想块大小和最小块大小中的较大值
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let chunkSize = Math.max(idealChunkSize, minChunkSize);
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// 将块大小向上取整到最接近的64KB的倍数,使其更整齐
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chunkSize = Math.ceil(chunkSize / (64 * 1024)) * (64 * 1024);
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return chunkSize;
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})();
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const uploadStream = gridBucket.openUploadStream(filename, {
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metadata,
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chunkSizeBytes
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});
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return retryFn(async () => {
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return new Promise<{ fileId: string }>((resolve, reject) => {
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uploadStream.end(buffer);
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uploadStream.on('finish', () => {
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resolve({ fileId: String(uploadStream.id) });
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});
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uploadStream.on('error', reject);
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});
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});
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};
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export const gridFsStream2Buffer = (stream: NodeJS.ReadableStream) => {
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return new Promise<Buffer>((resolve, reject) => {
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const chunks: Uint8Array[] = [];
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stream.on('data', (chunk) => {
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chunks.push(chunk);
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});
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stream.on('end', () => {
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const resultBuffer = Buffer.concat(chunks); // 一次性拼接
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resolve(resultBuffer);
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});
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stream.on('error', (err) => {
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reject(err);
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});
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});
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};
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export const stream2Encoding = async (stream: NodeJS.ReadableStream) => {
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const copyStream = stream.pipe(new PassThrough());
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/* get encoding */
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const buffer = await (() => {
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return new Promise<Buffer>((resolve, reject) => {
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const chunks: Uint8Array[] = [];
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let totalLength = 0;
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stream.on('data', (chunk) => {
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if (totalLength < 200) {
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chunks.push(chunk);
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totalLength += chunk.length;
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if (totalLength >= 200) {
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resolve(Buffer.concat(chunks));
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}
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}
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});
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stream.on('end', () => {
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resolve(Buffer.concat(chunks));
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});
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stream.on('error', (err) => {
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reject(err);
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});
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});
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})();
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const enc = detectFileEncoding(buffer);
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return {
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encoding: enc,
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stream: copyStream
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};
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};
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// 单块大小:尽可能大,但不超过 14MB,不小于512KB
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export const computeGridFsChunSize = (fileSize: number) => {
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// 计算理想块大小:文件大小 ÷ 目标块数(10)。 并且每个块需要小于 14MB
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const idealChunkSize = Math.min(Math.ceil(fileSize / 10), 14 * 1024 * 1024);
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// 确保块大小至少为512KB
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const minChunkSize = 512 * 1024; // 512KB
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// 取理想块大小和最小块大小中的较大值
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let chunkSize = Math.max(idealChunkSize, minChunkSize);
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// 将块大小向上取整到最接近的64KB的倍数,使其更整齐
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chunkSize = Math.ceil(chunkSize / (64 * 1024)) * (64 * 1024);
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return chunkSize;
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};
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