perf: pg

src/pages/api/chat/vectorGpt.ts

@@ -66,14 +66,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
     const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
       fields: ['id', 'q', 'a'],
+      where: [['model_id', model._id], 'AND', `vector <=> '[${promptVector}]' < ${similarity}`],
       order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
-      where: [
-        ['model_id', model._id],
-        'AND',
-        ['user_id', userId],
-        'AND',
-        `vector <=> '[${promptVector}]' < ${similarity}`
-      ],
       limit: 30
     });
 
@@ -97,8 +91,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       });
     } else {
       // 有匹配情况下，添加知识库内容。
-      // 系统提示词过滤，最多 2500 tokens
-      const systemPrompt = systemPromptFilter(formatRedisPrompt, 2500);
+      // 系统提示词过滤，最多 2000 tokens
+      const systemPrompt = systemPromptFilter(formatRedisPrompt, 2000);
 
       prompts.unshift({
         obj: 'SYSTEM',

src/pages/api/openapi/chat/lafGpt.ts

@@ -163,8 +163,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
 
     const formatRedisPrompt: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
 
-    // textArr 筛选，最多 3000 tokens
-    const systemPrompt = systemPromptFilter(formatRedisPrompt, 3000);
+    // textArr 筛选，最多 2500 tokens
+    const systemPrompt = systemPromptFilter(formatRedisPrompt, 2500);
 
     prompts.unshift({
       obj: 'SYSTEM',

src/pages/api/openapi/chat/vectorGpt.ts

@@ -80,14 +80,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     const similarity = ModelVectorSearchModeMap[model.search.mode]?.similarity || 0.22;
     const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
       fields: ['id', 'q', 'a'],
+      where: [['model_id', model._id], 'AND', `vector <=> '[${promptVector}]' < ${similarity}`],
       order: [{ field: 'vector', mode: `<=> '[${promptVector}]'` }],
-      where: [
-        ['model_id', model._id],
-        'AND',
-        ['user_id', userId],
-        'AND',
-        `vector <=> '[${promptVector}]' < ${similarity}`
-      ],
       limit: 30
     });
 
@@ -116,8 +110,8 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       });
     } else {
       // 有匹配或者低匹配度模式情况下，添加知识库内容。
-      // 系统提示词过滤，最多 2500 tokens
-      const systemPrompt = systemPromptFilter(formatRedisPrompt, 2500);
+      // 系统提示词过滤，最多 2000 tokens
+      const systemPrompt = systemPromptFilter(formatRedisPrompt, 2000);
 
       prompts.unshift({
         obj: 'SYSTEM',

src/service/events/pushBill.ts

@@ -23,7 +23,9 @@ export const pushChatBill = async ({
     // 计算 token 数量
     const tokens = Math.floor(encode(text).length * 0.75);
 
-    console.log(`chat generate success. text len: ${text.length}. token len: ${tokens}`);
+    console.log(
+      `chat generate success. text len: ${text.length}. token len: ${tokens}. pay:${isPay}`
+    );
 
     if (isPay) {
       await connectToDatabase();
@@ -79,7 +81,9 @@ export const pushSplitDataBill = async ({
   let billId;
 
   try {
-    console.log(`splitData generate success. text len: ${text.length}. token len: ${tokenLen}`);
+    console.log(
+      `splitData generate success. text len: ${text.length}. token len: ${tokenLen}. pay:${isPay}`
+    );
 
     if (isPay) {
       try {
@@ -130,7 +134,9 @@ export const pushGenerateVectorBill = async ({
   let billId;
 
   try {
-    console.log(`vector generate success. text len: ${text.length}. token len: ${tokenLen}`);
+    console.log(
+      `vector generate success. text len: ${text.length}. token len: ${tokenLen}. pay:${isPay}`
+    );
 
     if (isPay) {
       try {

src/service/mongo.ts

@@ -16,7 +16,7 @@ export async function connectToDatabase(): Promise<void> {
     mongoose.set('strictQuery', true);
     global.mongodb = await mongoose.connect(process.env.MONGODB_URI as string, {
       bufferCommands: true,
-      dbName: process.env.NODE_ENV === 'development' ? 'doc_gpt_test' : 'doc_gpt',
+      dbName: process.env.MONGODB_NAME,
       maxPoolSize: 5,
       minPoolSize: 1,
       maxConnecting: 5

src/service/redis.ts

-import { createClient } from 'redis';
-import { customAlphabet } from 'nanoid';
-const nanoid = customAlphabet('abcdefghijklmnopqrstuvwxyz1234567890', 10);
-
-export const connectRedis = async () => {
-  // 断开了，重连
-  if (global.redisClient && !global.redisClient.isOpen) {
-    await global.redisClient.disconnect();
-  } else if (global.redisClient) {
-    // 没断开，不再连接
-    return global.redisClient;
-  }
-
-  try {
-    global.redisClient = createClient({
-      url: process.env.REDIS_URL
-    });
-
-    global.redisClient.on('error', (err) => {
-      console.log('Redis Client Error', err);
-      global.redisClient = null;
-    });
-    global.redisClient.on('end', () => {
-      global.redisClient = null;
-    });
-    global.redisClient.on('ready', () => {
-      console.log('redis connected');
-    });
-
-    await global.redisClient.connect();
-
-    await global.redisClient.SELECT(0);
-
-    return global.redisClient;
-  } catch (error) {
-    console.log(error, '==');
-    global.redisClient = null;
-    return Promise.reject('redis 连接失败');
-  }
-};
-
-export const getKey = (prefix = '') => {
-  return `${prefix}:${nanoid()}`;
-};