Files
FastGPT/packages/service/common/buffer/rawText/controller.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

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TypeScript
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import { retryFn } from '@fastgpt/global/common/system/utils';
import { connectionMongo } from '../../mongo';
import { MongoRawTextBufferSchema, bucketName } from './schema';
import { addLog } from '../../system/log';
import { setCron } from '../../system/cron';
import { checkTimerLock } from '../../system/timerLock/utils';
import { TimerIdEnum } from '../../system/timerLock/constants';
const getGridBucket = () => {
return new connectionMongo.mongo.GridFSBucket(connectionMongo.connection.db!, {
bucketName: bucketName
});
};
export const addRawTextBuffer = async ({
sourceId,
sourceName,
text,
expiredTime
}: {
sourceId: string;
sourceName: string;
text: string;
expiredTime: Date;
}) => {
const gridBucket = getGridBucket();
const metadata = {
sourceId,
sourceName,
expiredTime
};
const buffer = Buffer.from(text);
const fileSize = buffer.length;
// 单块大小:尽可能大,但不超过 14MB不小于128KB
const chunkSizeBytes = (() => {
// 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
const idealChunkSize = Math.min(Math.ceil(fileSize / 10), 14 * 1024 * 1024);
// 确保块大小至少为128KB
const minChunkSize = 128 * 1024; // 128KB
// 取理想块大小和最小块大小中的较大值
let chunkSize = Math.max(idealChunkSize, minChunkSize);
// 将块大小向上取整到最接近的64KB的倍数使其更整齐
chunkSize = Math.ceil(chunkSize / (64 * 1024)) * (64 * 1024);
return chunkSize;
})();
const uploadStream = gridBucket.openUploadStream(sourceId, {
metadata,
chunkSizeBytes
});
return retryFn(async () => {
return new Promise((resolve, reject) => {
uploadStream.end(buffer);
uploadStream.on('finish', () => {
resolve(uploadStream.id);
});
uploadStream.on('error', (error) => {
addLog.error('addRawTextBuffer error', error);
resolve('');
});
});
});
};
export const getRawTextBuffer = async (sourceId: string) => {
const gridBucket = getGridBucket();
return retryFn(async () => {
const bufferData = await MongoRawTextBufferSchema.findOne(
{
'metadata.sourceId': sourceId
},
'_id metadata'
).lean();
if (!bufferData) {
return null;
}
// Read file content
const downloadStream = gridBucket.openDownloadStream(bufferData._id);
const chunks: Buffer[] = [];
return new Promise<{
text: string;
sourceName: string;
} | null>((resolve, reject) => {
downloadStream.on('data', (chunk) => {
chunks.push(chunk);
});
downloadStream.on('end', () => {
const buffer = Buffer.concat(chunks);
const text = buffer.toString('utf8');
resolve({
text,
sourceName: bufferData.metadata?.sourceName || ''
});
});
downloadStream.on('error', (error) => {
addLog.error('getRawTextBuffer error', error);
resolve(null);
});
});
});
};
export const deleteRawTextBuffer = async (sourceId: string): Promise<boolean> => {
const gridBucket = getGridBucket();
return retryFn(async () => {
const buffer = await MongoRawTextBufferSchema.findOne({ 'metadata.sourceId': sourceId });
if (!buffer) {
return false;
}
await gridBucket.delete(buffer._id);
return true;
});
};
export const updateRawTextBufferExpiredTime = async ({
sourceId,
expiredTime
}: {
sourceId: string;
expiredTime: Date;
}) => {
return retryFn(async () => {
return MongoRawTextBufferSchema.updateOne(
{ 'metadata.sourceId': sourceId },
{ $set: { 'metadata.expiredTime': expiredTime } }
);
});
};
export const clearExpiredRawTextBufferCron = async () => {
const gridBucket = getGridBucket();
const clearExpiredRawTextBuffer = async () => {
addLog.debug('Clear expired raw text buffer start');
const data = await MongoRawTextBufferSchema.find(
{
'metadata.expiredTime': { $lt: new Date() }
},
'_id'
).lean();
for (const item of data) {
try {
await gridBucket.delete(item._id);
} catch (error) {
addLog.error('Delete expired raw text buffer error', error);
}
}
addLog.debug('Clear expired raw text buffer end');
};
setCron('*/10 * * * *', async () => {
if (
await checkTimerLock({
timerId: TimerIdEnum.clearExpiredRawTextBuffer,
lockMinuted: 9
})
) {
try {
await clearExpiredRawTextBuffer();
} catch (error) {
addLog.error('clearExpiredRawTextBufferCron error', error);
}
}
});
};