perf: model framwork

src/constants/model.ts

@@ -2,33 +2,34 @@ import type { ModelSchema } from '@/types/mongoSchema';
 
 export const embeddingModel = 'text-embedding-ada-002';
 
-export enum ChatModelEnum {
+export enum OpenAiChatEnum {
   'GPT35' = 'gpt-3.5-turbo',
   'GPT4' = 'gpt-4',
   'GPT432k' = 'gpt-4-32k'
 }
-export const ChatModelMap = {
-  // ui name
-  [ChatModelEnum.GPT35]: 'ChatGpt',
-  [ChatModelEnum.GPT4]: 'Gpt4',
-  [ChatModelEnum.GPT432k]: 'Gpt4-32k'
-};
 
-export type ChatModelConstantType = {
-  chatModel: `${ChatModelEnum}`;
-  contextMaxToken: number;
-  maxTemperature: number;
-  price: number; // 多少钱 / 1token，单位: 0.00001元
-};
+export type ChatModelType = `${OpenAiChatEnum}`;
 
-export const modelList: ChatModelConstantType[] = [
-  {
-    chatModel: ChatModelEnum.GPT35,
+export const ChatModelMap = {
+  [OpenAiChatEnum.GPT35]: {
+    name: 'ChatGpt',
     contextMaxToken: 4096,
     maxTemperature: 1.5,
     price: 3
+  },
+  [OpenAiChatEnum.GPT4]: {
+    name: 'Gpt4',
+    contextMaxToken: 8000,
+    maxTemperature: 1.5,
+    price: 30
+  },
+  [OpenAiChatEnum.GPT432k]: {
+    name: 'Gpt4-32k',
+    contextMaxToken: 8000,
+    maxTemperature: 1.5,
+    price: 30
   }
-];
+};
 
 export enum ModelStatusEnum {
   running = 'running',
@@ -106,7 +107,7 @@ export const defaultModel: ModelSchema = {
     searchMode: ModelVectorSearchModeEnum.hightSimilarity,
     systemPrompt: '',
     temperature: 0,
-    chatModel: ChatModelEnum.GPT35
+    chatModel: OpenAiChatEnum.GPT35
   },
   share: {
     isShare: false,

src/pages/api/chat/chat.ts

@@ -5,7 +5,7 @@ import { axiosConfig, openaiChatFilter } from '@/service/utils/tools';
 import { ChatItemSimpleType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import { modelList, ModelVectorSearchModeMap } from '@/constants/model';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
 import { gpt35StreamResponse } from '@/service/utils/openai';
 import { searchKb_openai } from '@/service/tools/searchKb';
@@ -47,10 +47,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       authorization
     });
 
-    const modelConstantsData = modelList.find((item) => item.chatModel === model.chat.chatModel);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
 
     // 读取对话内容
     const prompts = [...content, prompt];
@@ -61,7 +58,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
         apiKey: userApiKey || systemKey,
         isPay: !userApiKey,
         text: prompt.value,
-        similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22,
+        similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
         model,
         userId
       });

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

 import type { NextApiRequest, NextApiResponse } from 'next';
 import { connectToDatabase } from '@/service/mongo';
 import { getOpenAIApi, authOpenApiKey, authModel } from '@/service/utils/auth';
-import { axiosConfig, openaiChatFilter, systemPromptFilter } from '@/service/utils/tools';
+import { axiosConfig, openaiChatFilter } from '@/service/utils/tools';
 import { ChatItemSimpleType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import { modelList, ModelVectorSearchModeMap, ModelVectorSearchModeEnum } from '@/constants/model';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
 import { gpt35StreamResponse } from '@/service/utils/openai';
 import { searchKb_openai } from '@/service/tools/searchKb';
@@ -58,10 +58,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       modelId
     });
 
-    const modelConstantsData = modelList.find((item) => item.chatModel === model.chat.chatModel);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
 
     // 使用了知识库搜索
     if (model.chat.useKb) {

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

@@ -5,7 +5,7 @@ import { axiosConfig, openaiChatFilter } from '@/service/utils/tools';
 import { ChatItemSimpleType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import { modelList } from '@/constants/model';
+import { ChatModelMap } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
 import { gpt35StreamResponse } from '@/service/utils/openai';
 
@@ -60,10 +60,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('无权使用该模型');
     }
 
-    const modelConstantsData = modelList.find((item) => item.chatModel === model.chat.chatModel);
-    if (!modelConstantsData) {
-      throw new Error('模型加载异常');
-    }
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
 
     // 如果有系统提示词，自动插入
     if (model.chat.systemPrompt) {

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

 import type { NextApiRequest, NextApiResponse } from 'next';
 import { connectToDatabase, Model } from '@/service/mongo';
 import { getOpenAIApi, authOpenApiKey } from '@/service/utils/auth';
-import { axiosConfig, openaiChatFilter, systemPromptFilter } from '@/service/utils/tools';
+import { axiosConfig, openaiChatFilter } from '@/service/utils/tools';
 import { ChatItemSimpleType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import { modelList, ModelVectorSearchModeMap, ChatModelEnum } from '@/constants/model';
+import { ChatModelMap, ModelVectorSearchModeMap, OpenAiChatEnum } from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
 import { gpt35StreamResponse } from '@/service/utils/openai';
 import { searchKb_openai } from '@/service/tools/searchKb';
@@ -53,10 +53,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('找不到模型');
     }
 
-    const modelConstantsData = modelList.find((item) => item.chatModel === model.chat.chatModel);
-    if (!modelConstantsData) {
-      throw new Error('model is undefined');
-    }
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
 
     console.log('laf gpt start');
 
@@ -66,7 +63,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
     // 请求一次 chatgpt 拆解需求
     const promptResponse = await chatAPI.createChatCompletion(
       {
-        model: ChatModelEnum.GPT35,
+        model: OpenAiChatEnum.GPT35,
         temperature: 0,
         frequency_penalty: 0.5, // 越大，重复内容越少
         presence_penalty: -0.5, // 越大，越容易出现新内容

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

 import type { NextApiRequest, NextApiResponse } from 'next';
 import { connectToDatabase, Model } from '@/service/mongo';
-import { axiosConfig, systemPromptFilter, openaiChatFilter } from '@/service/utils/tools';
+import { axiosConfig, openaiChatFilter } from '@/service/utils/tools';
 import { getOpenAIApi, authOpenApiKey } from '@/service/utils/auth';
 import { ChatItemSimpleType } from '@/types/chat';
 import { jsonRes } from '@/service/response';
 import { PassThrough } from 'stream';
-import { modelList, ModelVectorSearchModeMap, ModelVectorSearchModeEnum } from '@/constants/model';
+import {
+  ChatModelMap,
+  ModelVectorSearchModeMap,
+  ModelVectorSearchModeEnum
+} from '@/constants/model';
 import { pushChatBill } from '@/service/events/pushBill';
 import { gpt35StreamResponse } from '@/service/utils/openai';
 import { searchKb_openai } from '@/service/tools/searchKb';
@@ -62,10 +66,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
       throw new Error('无权使用该模型');
     }
 
-    const modelConstantsData = modelList.find((item) => item.chatModel === model.chat.chatModel);
-    if (!modelConstantsData) {
-      throw new Error('模型初始化异常');
-    }
+    const modelConstantsData = ChatModelMap[model.chat.chatModel];
 
     // 获取向量匹配到的提示词
     const { code, searchPrompt } = await searchKb_openai({

src/pages/chat/index.tsx

@@ -27,7 +27,7 @@ import {
 import { useToast } from '@/hooks/useToast';
 import { useScreen } from '@/hooks/useScreen';
 import { useQuery } from '@tanstack/react-query';
-import { ChatModelEnum } from '@/constants/model';
+import { OpenAiChatEnum } from '@/constants/model';
 import dynamic from 'next/dynamic';
 import { useGlobalStore } from '@/store/global';
 import { useCopyData } from '@/utils/tools';
@@ -69,7 +69,7 @@ const Chat = ({ modelId, chatId }: { modelId: string; chatId: string }) => {
     name: '',
     avatar: '/icon/logo.png',
     intro: '',
-    chatModel: ChatModelEnum.GPT35,
+    chatModel: OpenAiChatEnum.GPT35,
     history: []
   }); // 聊天框整体数据
 

src/pages/model/detail/components/ModelEditForm.tsx

@@ -21,7 +21,7 @@ import {
 import { QuestionOutlineIcon } from '@chakra-ui/icons';
 import type { ModelSchema } from '@/types/mongoSchema';
 import { UseFormReturn } from 'react-hook-form';
-import { ChatModelMap, modelList, ModelVectorSearchModeMap } from '@/constants/model';
+import { ChatModelMap, ModelVectorSearchModeMap } from '@/constants/model';
 import { formatPrice } from '@/utils/user';
 import { useConfirm } from '@/hooks/useConfirm';
 import { useSelectFile } from '@/hooks/useSelectFile';
@@ -110,17 +110,14 @@ const ModelEditForm = ({
           <Box flex={'0 0 80px'} w={0}>
             对话模型:
           </Box>
-          <Box>{ChatModelMap[getValues('chat.chatModel')]}</Box>
+          <Box>{ChatModelMap[getValues('chat.chatModel')].name}</Box>
         </Flex>
         <Flex alignItems={'center'} mt={5}>
           <Box flex={'0 0 80px'} w={0}>
             价格:
           </Box>
           <Box>
-            {formatPrice(
-              modelList.find((item) => item.chatModel === getValues('chat.chatModel'))?.price || 0,
-              1000
-            )}
+            {formatPrice(ChatModelMap[getValues('chat.chatModel')].price, 1000)}
             元/1K tokens(包括上下文和回答)
           </Box>
         </Flex>

src/pages/model/detail/index.tsx

@@ -5,7 +5,7 @@ import type { ModelSchema } from '@/types/mongoSchema';
 import { Card, Box, Flex, Button, Tag, Grid } from '@chakra-ui/react';
 import { useToast } from '@/hooks/useToast';
 import { useForm } from 'react-hook-form';
-import { formatModelStatus, modelList, defaultModel } from '@/constants/model';
+import { formatModelStatus, defaultModel } from '@/constants/model';
 import { useGlobalStore } from '@/store/global';
 import { useScreen } from '@/hooks/useScreen';
 import { useQuery } from '@tanstack/react-query';

src/pages/model/list/components/ModelPhoneList.tsx

@@ -43,7 +43,7 @@ const ModelPhoneList = ({
           </Flex>
           <Flex mt={5}>
             <Box flex={'0 0 100px'}>对话模型: </Box>
-            <Box color={'blackAlpha.500'}>{ChatModelMap[model.chat.chatModel]}</Box>
+            <Box color={'blackAlpha.500'}>{ChatModelMap[model.chat.chatModel].name}</Box>
           </Flex>
           <Flex mt={5}>
             <Box flex={'0 0 100px'}>模型温度: </Box>

src/pages/model/list/components/ModelTable.tsx

@@ -36,7 +36,7 @@ const ModelTable = ({
       key: 'service',
       render: (model: ModelSchema) => (
         <Box fontWeight={'bold'} whiteSpace={'pre-wrap'} maxW={'200px'}>
-          {ChatModelMap[model.chat.chatModel]}
+          {ChatModelMap[model.chat.chatModel].name}
         </Box>
       )
     },

src/pages/number/components/PayModal.tsx

@@ -85,25 +85,6 @@ const PayModal = ({ onClose }: { onClose: () => void }) => {
           <ModalBody py={0}>
             {!payId && (
               <>
-                {/* 价格表 */}
-                {/* <TableContainer mb={4}>
-                  <Table>
-                    <Thead>
-                      <Tr>
-                        <Th>模型类型</Th>
-                        <Th>价格(元/1K tokens，包含所有上下文)</Th>
-                      </Tr>
-                    </Thead>
-                    <Tbody>
-                      {modelList.map((item, i) => (
-                        <Tr key={item.model}>
-                          <Td>{item.name}</Td>
-                          <Td>{formatPrice(item.price, 1000)}</Td>
-                        </Tr>
-                      ))}
-                    </Tbody>
-                  </Table>
-                </TableContainer> */}
                 <Grid gridTemplateColumns={'repeat(4,1fr)'} gridGap={5} mb={4}>
                   {[5, 10, 20, 50].map((item) => (
                     <Button

src/service/events/generateQA.ts

@@ -3,7 +3,7 @@ import { getOpenAIApi } from '@/service/utils/auth';
 import { axiosConfig } from '@/service/utils/tools';
 import { getOpenApiKey } from '../utils/openai';
 import type { ChatCompletionRequestMessage } from 'openai';
-import { ChatModelEnum } from '@/constants/model';
+import { OpenAiChatEnum } from '@/constants/model';
 import { pushSplitDataBill } from '@/service/events/pushBill';
 import { generateVector } from './generateVector';
 import { openaiError2 } from '../errorCode';
@@ -88,7 +88,7 @@ A2:
         chatAPI
           .createChatCompletion(
             {
-              model: ChatModelEnum.GPT35,
+              model: OpenAiChatEnum.GPT35,
               temperature: 0.8,
               n: 1,
               messages: [

src/service/events/pushBill.ts

 import { connectToDatabase, Bill, User } from '../mongo';
-import { modelList, ChatModelEnum, embeddingModel } from '@/constants/model';
+import { ChatModelMap, OpenAiChatEnum, ChatModelType, embeddingModel } from '@/constants/model';
 import { BillTypeEnum } from '@/constants/user';
 import { countChatTokens } from '@/utils/tools';
 
@@ -11,7 +11,7 @@ export const pushChatBill = async ({
   messages
 }: {
   isPay: boolean;
-  chatModel: `${ChatModelEnum}`;
+  chatModel: ChatModelType;
   userId: string;
   chatId?: '' | string;
   messages: { role: 'system' | 'user' | 'assistant'; content: string }[];
@@ -30,10 +30,8 @@ export const pushChatBill = async ({
     if (isPay) {
       await connectToDatabase();
 
-      // 获取模型单价格
-      const modelItem = modelList.find((item) => item.chatModel === chatModel);
       // 计算价格
-      const unitPrice = modelItem?.price || 5;
+      const unitPrice = ChatModelMap[chatModel]?.price || 5;
       const price = unitPrice * tokens;
 
       try {
@@ -88,8 +86,7 @@ export const pushSplitDataBill = async ({
     if (isPay) {
       try {
         // 获取模型单价格, 都是用 gpt35 拆分
-        const modelItem = modelList.find((item) => item.chatModel === ChatModelEnum.GPT35);
-        const unitPrice = modelItem?.price || 3;
+        const unitPrice = ChatModelMap[OpenAiChatEnum.GPT35]?.price || 3;
         // 计算价格
         const price = unitPrice * tokenLen;
 
@@ -97,7 +94,7 @@ export const pushSplitDataBill = async ({
         const res = await Bill.create({
           userId,
           type,
-          modelName: ChatModelEnum.GPT35,
+          modelName: OpenAiChatEnum.GPT35,
           textLen: text.length,
           tokenLen,
           price

src/service/models/model.ts

@@ -4,7 +4,7 @@ import {
   ModelVectorSearchModeMap,
   ModelVectorSearchModeEnum,
   ChatModelMap,
-  ChatModelEnum
+  OpenAiChatEnum
 } from '@/constants/model';
 
 const ModelSchema = new Schema({
@@ -57,7 +57,7 @@ const ModelSchema = new Schema({
       // 聊天时使用的模型
       type: String,
       enum: Object.keys(ChatModelMap),
-      default: ChatModelEnum.GPT35
+      default: OpenAiChatEnum.GPT35
     }
   },
   share: {

src/service/tools/searchKb.ts

 import { openaiCreateEmbedding } from '../utils/openai';
 import { PgClient } from '@/service/pg';
-import { ModelDataStatusEnum, ModelVectorSearchModeEnum } from '@/constants/model';
+import { ModelDataStatusEnum, ModelVectorSearchModeEnum, ChatModelMap } from '@/constants/model';
 import { ModelSchema } from '@/types/mongoSchema';
 import { systemPromptFilter } from '../utils/tools';
 
@@ -9,9 +9,9 @@ import { systemPromptFilter } from '../utils/tools';
  */
 export const searchKb_openai = async ({
   apiKey,
-  isPay,
+  isPay = true,
   text,
-  similarity,
+  similarity = 0.2,
   model,
   userId
 }: {
@@ -20,7 +20,7 @@ export const searchKb_openai = async ({
   text: string;
   model: ModelSchema;
   userId: string;
-  similarity: number;
+  similarity?: number;
 }): Promise<{
   code: 200 | 201;
   searchPrompt?: {
@@ -28,6 +28,8 @@ export const searchKb_openai = async ({
     value: string;
   };
 }> => {
+  const modelConstantsData = ChatModelMap[model.chat.chatModel];
+
   // 获取提示词的向量
   const { vector: promptVector } = await openaiCreateEmbedding({
     isPay,
@@ -78,11 +80,11 @@ export const searchKb_openai = async ({
   }
 
   // 有匹配情况下，system 添加知识库内容。
-  // 系统提示词过滤，最多 2500 tokens
+  // 系统提示词过滤，最多 65% tokens
   const filterSystemPrompt = systemPromptFilter({
     model: model.chat.chatModel,
     prompts: systemPrompts,
-    maxTokens: 2500
+    maxTokens: Math.floor(modelConstantsData.contextMaxToken * 0.65)
   });
 
   return {

src/service/utils/tools.ts

@@ -3,7 +3,7 @@ import jwt from 'jsonwebtoken';
 import { ChatItemSimpleType } from '@/types/chat';
 import { countChatTokens, sliceTextByToken } from '@/utils/tools';
 import { ChatCompletionRequestMessageRoleEnum, ChatCompletionRequestMessage } from 'openai';
-import { ChatModelEnum } from '@/constants/model';
+import type { ChatModelType } from '@/constants/model';
 
 /* 密码加密 */
 export const hashPassword = (psw: string) => {
@@ -44,7 +44,7 @@ export const openaiChatFilter = ({
   prompts,
   maxTokens
 }: {
-  model: `${ChatModelEnum}`;
+  model: ChatModelType;
   prompts: ChatItemSimpleType[];
   maxTokens: number;
 }) => {

src/types/mongoSchema.d.ts

@@ -3,7 +3,7 @@ import {
   ModelStatusEnum,
   ModelNameEnum,
   ModelVectorSearchModeEnum,
-  ChatModelEnum
+  ChatModelType
 } from '@/constants/model';
 import type { DataType } from './data';
 
@@ -41,7 +41,7 @@ export interface ModelSchema {
     searchMode: `${ModelVectorSearchModeEnum}`;
     systemPrompt: string;
     temperature: number;
-    chatModel: `${ChatModelEnum}`; // 聊天时用的模型，训练后就是训练的模型
+    chatModel: ChatModelType; // 聊天时用的模型，训练后就是训练的模型
   };
   share: {
     isShare: boolean;

src/utils/tools.ts

@@ -2,7 +2,7 @@ import crypto from 'crypto';
 import { useToast } from '@/hooks/useToast';
 import { encoding_for_model, type Tiktoken } from '@dqbd/tiktoken';
 import Graphemer from 'graphemer';
-import { ChatModelEnum } from '@/constants/model';
+import type { ChatModelType } from '@/constants/model';
 
 const textDecoder = new TextDecoder();
 const graphemer = new Graphemer();
@@ -130,7 +130,7 @@ export const countChatTokens = ({
   model = 'gpt-3.5-turbo',
   messages
 }: {
-  model?: `${ChatModelEnum}`;
+  model?: ChatModelType;
   messages: { role: 'system' | 'user' | 'assistant'; content: string }[];
 }) => {
   const text = getChatGPTEncodingText(messages, model);
@@ -142,7 +142,7 @@ export const sliceTextByToken = ({
   text,
   length
 }: {
-  model?: `${ChatModelEnum}`;
+  model?: ChatModelType;
   text: string;
   length: number;
 }) => {