perf: random queue

src/pages/api/openapi/kb/pushData.ts

@@ -7,6 +7,7 @@ import { authKb } from '@/service/utils/auth';
 import { withNextCors } from '@/service/utils/tools';
 import { TrainingModeEnum } from '@/constants/plugin';
 import { startQueue } from '@/service/utils/tools';
+import { PgClient } from '@/service/pg';
 
 export type Props = {
   kbId: string;
@@ -60,10 +61,23 @@ export async function pushDataToKb({
     return {};
   }
 
-  // 去重
   // 过滤重复的 qa 内容
+  const set = new Set();
+  const filterData: {
+    a: string;
+    q: string;
+  }[] = [];
+
+  data.forEach((item) => {
+    const text = item.q + item.a;
+    if (!set.has(text)) {
+      filterData.push(item);
+      set.add(text);
+    }
+  });
+  // 数据库去重
   // const searchRes = await Promise.allSettled(
-  //   dataItems.map(async ({ q, a = '' }) => {
+  //   data.map(async ({ q, a = '' }) => {
   //     if (!q) {
   //       return Promise.reject('q为空');
   //     }

src/service/events/generateQA.ts

@@ -10,6 +10,10 @@ import { pushDataToKb } from '@/pages/api/openapi/kb/pushData';
 import { TrainingModeEnum } from '@/constants/plugin';
 import { ERROR_ENUM } from '../errorCode';
 
+const reduceQueue = () => {
+  global.qaQueueLen = global.qaQueueLen > 0 ? global.qaQueueLen - 1 : 0;
+};
+
 export async function generateQA(): Promise<any> {
   const maxProcess = Number(process.env.QA_MAX_PROCESS || 10);
 
@@ -20,11 +24,34 @@ export async function generateQA(): Promise<any> {
   let userId = '';
 
   try {
-    // 找出一个需要生成的 dataItem (4分钟锁)
+    const match = {
+      mode: TrainingModeEnum.qa,
+      lockTime: { $lte: new Date(Date.now() - 4 * 60 * 1000) }
+    };
+    // random get task
+    const agree = await TrainingData.aggregate([
+      {
+        $match: match
+      },
+      { $sample: { size: 1 } },
+      {
+        $project: {
+          _id: 1
+        }
+      }
+    ]);
+
+    // no task
+    if (agree.length === 0) {
+      reduceQueue();
+      global.qaQueueLen <= 0 && console.log(`没有需要【QA】的数据, ${global.qaQueueLen}`);
+      return;
+    }
+
     const data = await TrainingData.findOneAndUpdate(
       {
-        mode: TrainingModeEnum.qa,
+        _id: agree[0]._id,
-        lockTime: { $lte: new Date(Date.now() - 2 * 60 * 1000) }
+        ...match
       },
       {
         lockTime: new Date()
@@ -37,11 +64,10 @@ export async function generateQA(): Promise<any> {
       q: 1
     });
 
-    /* 无待生成的任务 */
+    // task preemption
     if (!data) {
-      global.qaQueueLen--;
+      reduceQueue();
-      !global.qaQueueLen && console.log(`没有需要【QA】的数据`);
+      return generateQA();
-      return;
     }
 
     trainingId = data._id;
@@ -123,10 +149,10 @@ A2:
 
     console.log('生成QA成功，time:', `${(Date.now() - startTime) / 1000}s`);
 
-    global.qaQueueLen--;
+    reduceQueue();
     generateQA();
   } catch (err: any) {
-    global.qaQueueLen--;
+    reduceQueue();
     // log
     if (err?.response) {
       console.log('openai error: 生成QA错误');

src/service/events/generateVector.ts

@@ -1,10 +1,14 @@
 import { openaiError2 } from '../errorCode';
-import { insertKbItem, PgClient } from '@/service/pg';
+import { insertKbItem } from '@/service/pg';
 import { openaiEmbedding } from '@/pages/api/openapi/plugin/openaiEmbedding';
 import { TrainingData } from '../models/trainingData';
 import { ERROR_ENUM } from '../errorCode';
 import { TrainingModeEnum } from '@/constants/plugin';
 
+const reduceQueue = () => {
+  global.vectorQueueLen = global.vectorQueueLen > 0 ? global.vectorQueueLen - 1 : 0;
+};
+
 /* 索引生成队列。每导入一次，就是一个单独的线程 */
 export async function generateVector(): Promise<any> {
   const maxProcess = Number(process.env.VECTOR_MAX_PROCESS || 10);
@@ -16,10 +20,34 @@ export async function generateVector(): Promise<any> {
   let userId = '';
 
   try {
+    const match = {
+      mode: TrainingModeEnum.index,
+      lockTime: { $lte: new Date(Date.now() - 2 * 60 * 1000) }
+    };
+    // random get task
+    const agree = await TrainingData.aggregate([
+      {
+        $match: match
+      },
+      { $sample: { size: 1 } },
+      {
+        $project: {
+          _id: 1
+        }
+      }
+    ]);
+
+    // no task
+    if (agree.length === 0) {
+      reduceQueue();
+      global.vectorQueueLen <= 0 && console.log(`没有需要【索引】的数据, ${global.vectorQueueLen}`);
+      return;
+    }
+
     const data = await TrainingData.findOneAndUpdate(
       {
-        mode: TrainingModeEnum.index,
+        _id: agree[0]._id,
-        lockTime: { $lte: new Date(Date.now() - 2 * 60 * 1000) }
+        ...match
       },
       {
         lockTime: new Date()
@@ -32,11 +60,10 @@ export async function generateVector(): Promise<any> {
       a: 1
     });
 
-    /* 无待生成的任务 */
+    // task preemption
     if (!data) {
-      global.vectorQueueLen--;
+      reduceQueue();
-      !global.vectorQueueLen && console.log(`没有需要【索引】的数据`);
+      return generateVector();
-      return;
     }
 
     trainingId = data._id;
@@ -72,10 +99,10 @@ export async function generateVector(): Promise<any> {
     await TrainingData.findByIdAndDelete(data._id);
     console.log(`生成向量成功: ${data._id}`);
 
-    global.vectorQueueLen--;
+    reduceQueue();
     generateVector();
   } catch (err: any) {
-    global.vectorQueueLen--;
+    reduceQueue();
     // log
     if (err?.response) {
       console.log('openai error: 生成向量错误');