feat: text collecion auto save for a txt file (#4924)

packages/global/core/dataset/utils.ts

@@ -40,5 +40,6 @@ export function getSourceNameIcon({
 export const predictDataLimitLength = (mode: TrainingModeEnum, data: any[]) => {
   if (mode === TrainingModeEnum.qa) return data.length * 20;
   if (mode === TrainingModeEnum.auto) return data.length * 5;
+  if (mode === TrainingModeEnum.image) return data.length * 2;
   return data.length;
 };

packages/service/common/file/gridfs/controller.ts

@@ -223,7 +223,7 @@ export const readFileContentFromMongo = async ({
   rawText: string;
   filename: string;
 }> => {
-  const bufferId = `${fileId}-${customPdfParse}`;
+  const bufferId = `${String(fileId)}-${customPdfParse}`;
   // read buffer
   const fileBuffer = await getRawTextBuffer(bufferId);
   if (fileBuffer) {

packages/service/common/file/gridfs/utils.ts

@@ -1,5 +1,57 @@
 import { detectFileEncoding } from '@fastgpt/global/common/file/tools';
 import { PassThrough } from 'stream';
+import { getGridBucket } from './controller';
+import { type BucketNameEnum } from '@fastgpt/global/common/file/constants';
+import { retryFn } from '@fastgpt/global/common/system/utils';
+
+export const createFileFromText = async ({
+  bucket,
+  filename,
+  text,
+  metadata
+}: {
+  bucket: `${BucketNameEnum}`;
+  filename: string;
+  text: string;
+  metadata: Record<string, any>;
+}) => {
+  const gridBucket = getGridBucket(bucket);
+
+  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(filename, {
+    metadata,
+    chunkSizeBytes
+  });
+
+  return retryFn(async () => {
+    return new Promise<{ fileId: string }>((resolve, reject) => {
+      uploadStream.end(buffer);
+      uploadStream.on('finish', () => {
+        resolve({ fileId: String(uploadStream.id) });
+      });
+      uploadStream.on('error', reject);
+    });
+  });
+};
 
 export const gridFsStream2Buffer = (stream: NodeJS.ReadableStream) => {
   return new Promise<Buffer>((resolve, reject) => {

projects/app/src/pageComponents/dataset/detail/Import/diffSource/FileCustomText.tsx

@@ -49,7 +49,7 @@ const CustomTextInput = () => {
           createStatus: 'waiting',
           rawText: data.value,
           sourceName: data.name,
-          icon: 'file/fill/manual'
+          icon: 'file/fill/txt'
         }
       ]);
       goToNext();

projects/app/src/pages/api/core/dataset/collection/create/text.ts

@@ -6,6 +6,7 @@ import { DatasetCollectionTypeEnum } from '@fastgpt/global/core/dataset/constant
 import { NextAPI } from '@/service/middleware/entry';
 import { WritePermissionVal } from '@fastgpt/global/support/permission/constant';
 import { type CreateCollectionResponse } from '@/global/core/dataset/api';
+import { createFileFromText } from '@fastgpt/service/common/file/gridfs/utils';
 
 async function handler(req: NextApiRequest): CreateCollectionResponse {
   const { name, text, ...body } = req.body as TextCreateDatasetCollectionParams;
@@ -18,6 +19,18 @@ async function handler(req: NextApiRequest): CreateCollectionResponse {
     per: WritePermissionVal
   });
 
+  // 1. Create file from text
+  const filename = `${name}.txt`;
+  const { fileId } = await createFileFromText({
+    bucket: 'dataset',
+    filename,
+    text,
+    metadata: {
+      teamId,
+      uid: tmbId
+    }
+  });
+
   const { collectionId, insertResults } = await createCollectionAndInsertData({
     dataset,
     rawText: text,
@@ -25,9 +38,9 @@ async function handler(req: NextApiRequest): CreateCollectionResponse {
       ...body,
       teamId,
       tmbId,
-      type: DatasetCollectionTypeEnum.virtual,
-
-      name
+      type: DatasetCollectionTypeEnum.file,
+      fileId,
+      name: filename
     }
   });
 

projects/app/src/service/core/dataset/queues/generateQA.ts

@@ -2,7 +2,7 @@ import { MongoDatasetTraining } from '@fastgpt/service/core/dataset/training/sch
 import { pushQAUsage } from '@/service/support/wallet/usage/push';
 import { TrainingModeEnum } from '@fastgpt/global/core/dataset/constants';
 import { createChatCompletion } from '@fastgpt/service/core/ai/config';
-import type { ChatCompletionMessageParam, StreamChatType } from '@fastgpt/global/core/ai/type.d';
+import type { ChatCompletionMessageParam } from '@fastgpt/global/core/ai/type.d';
 import { addLog } from '@fastgpt/service/common/system/log';
 import { splitText2Chunks } from '@fastgpt/global/common/string/textSplitter';
 import { replaceVariable } from '@fastgpt/global/common/string/tools';

projects/app/src/service/core/dataset/queues/utils.ts

@@ -1,6 +1,6 @@
 import { TeamErrEnum } from '@fastgpt/global/common/error/code/team';
 import { checkTeamAIPoints } from '@fastgpt/service/support/permission/teamLimit';
-import { sendOneInform } from '../support/user/inform/api';
+import { sendOneInform } from '../../../support/user/inform/api';
 import { lockTrainingDataByTeamId } from '@fastgpt/service/core/dataset/training/controller';
 import { InformLevelEnum } from '@fastgpt/global/support/user/inform/constants';
 
@@ -18,7 +18,7 @@ export const checkTeamAiPointsAndLock = async (teamId: string) => {
           templateParam: {},
           teamId
         });
-        console.log('余额不足，暂停【向量】生成任务');
+        console.log('余额不足，暂停训练生成任务');
         await lockTrainingDataByTeamId(teamId);
       } catch (error) {}
     }

projects/app/src/service/core/dataset/training/utils.ts

@@ -1,5 +1,5 @@
-import { generateQA } from '@/service/events/generateQA';
-import { generateVector } from '@/service/events/generateVector';
+import { generateQA } from '@/service/core/dataset/queues/generateQA';
+import { generateVector } from '@/service/core/dataset/queues/generateVector';
 import { TrainingModeEnum } from '@fastgpt/global/core/dataset/constants';
 import { type DatasetTrainingSchemaType } from '@fastgpt/global/core/dataset/type';
 import { MongoDatasetTraining } from '@fastgpt/service/core/dataset/training/schema';