perf: 知识库优化

src/pages/api/chat/chatGpt.ts

@@ -40,6 +40,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     }
 
     await connectToDatabase();
+    let startTime = Date.now();
 
     const { chat, userApiKey, systemKey, userId } = await authChat(chatId, authorization);
 
@@ -81,7 +82,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
     // 获取 chatAPI
     const chatAPI = getOpenAIApi(userApiKey || systemKey);
-    let startTime = Date.now();
     // 发出请求
     const chatResponse = await chatAPI.createChatCompletion(
       {

src/pages/api/chat/vectorGpt.ts

@@ -48,6 +48,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
     await connectToDatabase();
     const redis = await connectRedis();
+    let startTime = Date.now();
 
     const { chat, userApiKey, systemKey, userId } = await authChat(chatId, authorization);
 
@@ -83,17 +84,22 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     const redisData: any[] = await redis.sendCommand([
       'FT.SEARCH',
       `idx:${VecModelDataIndex}`,
-      `@modelId:{${String(chat.modelId._id)}} @vector:[VECTOR_RANGE 0.2 $blob]`,
+      `@modelId:{${String(
+        chat.modelId._id
+      )}} @vector:[VECTOR_RANGE 0.15 $blob]=>{$YIELD_DISTANCE_AS: score}`,
       // `@modelId:{${String(chat.modelId._id)}}=>[KNN 10 @vector $blob AS score]`,
       'RETURN',
       '1',
       'dataId',
-      // 'SORTBY',
-      // 'score',
+      'SORTBY',
+      'score',
       'PARAMS',
       '2',
       'blob',
       binary,
+      'LIMIT',
+      '0',
+      '20',
       'DIALECT',
       '2'
     ]);
@@ -117,8 +123,13 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
         [2, 4, 6, 8, 10, 12, 14, 16, 18, 20].map((i) => {
           if (!redisData[i] || !redisData[i][1]) return '';
           return ModelData.findById(redisData[i][1])
-            .select('text')
-            .then((res) => res?.text || '');
+            .select('text q')
+            .then((res) => {
+              if (!res) return '';
+              const questions = res.q.map((item) => item.text).join(' ');
+              const answer = res.text;
+              return `${questions} ${answer}`;
+            });
         })
       )
     ).filter((item) => item);
@@ -128,7 +139,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
     prompts.unshift({
       obj: 'SYSTEM',
-      value: `请根据下面的知识回答问题： ${systemPrompt}`
+      value: `根据下面的知识回答问题： ${systemPrompt}`
     });
 
     // 控制在 tokens 数量，防止超出
@@ -150,7 +161,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     // 计算温度
     const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
 
-    let startTime = Date.now();
     // 发出请求
     const chatResponse = await chatAPI.createChatCompletion(
       {

src/pages/api/model/data/getSplitData.ts

@@ -0,0 +1,35 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { jsonRes } from '@/service/response';
+import { connectToDatabase, SplitData, Model } from '@/service/mongo';
+import { authToken } from '@/service/utils/tools';
+
+/* 拆分数据成QA */
+export default async function handler(req: NextApiRequest, res: NextApiResponse) {
+  try {
+    const { modelId } = req.query as { modelId: string };
+    if (!modelId) {
+      throw new Error('参数错误');
+    }
+    await connectToDatabase();
+
+    const { authorization } = req.headers;
+
+    const userId = await authToken(authorization);
+
+    // 找到长度大于0的数据
+    const data = await SplitData.find({
+      userId,
+      modelId,
+      textList: { $exists: true, $not: { $size: 0 } }
+    });
+
+    jsonRes(res, {
+      data
+    });
+  } catch (err) {
+    jsonRes(res, {
+      code: 500,
+      error: err
+    });
+  }
+}

src/pages/api/model/data/splitData.ts

@@ -53,7 +53,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       textList
     });
 
-    // generateQA();
+    generateQA();
 
     jsonRes(res, {
       data: { chunks, replaceText }