feat: config vector model and qa model

client/src/service/events/generateQA.ts

@@ -1,5 +1,5 @@
 import { TrainingData } from '@/service/mongo';
-import { pushSplitDataBill } from '@/service/events/pushBill';
+import { pushQABill } from '@/service/events/pushBill';
 import { pushDataToKb } from '@/pages/api/openapi/kb/pushData';
 import { TrainingModeEnum } from '@/constants/plugin';
 import { ERROR_ENUM } from '../errorCode';
@@ -60,14 +60,13 @@ export async function generateQA(): Promise<any> {
     // 请求 chatgpt 获取回答
     const response = await Promise.all(
       [data.q].map((text) => {
-        const modelTokenLimit =
-          chatModels.find((item) => item.model === data.model)?.contextMaxToken || 16000;
+        const modelTokenLimit = global.qaModel.maxToken || 16000;
         const messages: ChatCompletionRequestMessage[] = [
           {
             role: 'system',
-            content: `你是出题人.
-${data.prompt || '我会发送一段长文本'}.
-从中提取出 25 个问题和答案. 答案详细完整. 按下面格式返回: 
+            content: `你是出题人，${
+              data.prompt || '我会发送一段长文本'
+            }，请从中提取出 25 个问题和答案. 答案详细完整，并按下面格式返回: 
 Q1:
 A1:
 Q2:
@@ -88,7 +87,7 @@ A2:
         return chatAPI
           .createChatCompletion(
             {
-              model: data.model,
+              model: global.qaModel.model,
               temperature: 0.8,
               messages,
               stream: false,
@@ -106,10 +105,9 @@ A2:
             const result = formatSplitText(answer || ''); // 格式化后的QA对
             console.log(`split result length: `, result.length);
             // 计费
-            pushSplitDataBill({
+            pushQABill({
               userId: data.userId,
               totalTokens,
-              model: data.model,
               appName: 'QA 拆分'
             });
             return {
@@ -135,7 +133,6 @@ A2:
         source: data.source
       })),
       userId,
-      model: global.vectorModels[0].model,
       mode: TrainingModeEnum.index
     });