145 lines
4.5 KiB
TypeScript
145 lines
4.5 KiB
TypeScript
import type { NextApiRequest, NextApiResponse } from 'next';
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import { createParser, ParsedEvent, ReconnectInterval } from 'eventsource-parser';
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import { connectToDatabase } from '@/service/mongo';
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import { getOpenAIApi, authChat } from '@/service/utils/chat';
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import { httpsAgent } from '@/service/utils/tools';
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import { ChatCompletionRequestMessage, ChatCompletionRequestMessageRoleEnum } from 'openai';
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import { ChatItemType } from '@/types/chat';
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import { jsonRes } from '@/service/response';
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import type { ModelSchema } from '@/types/mongoSchema';
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import { PassThrough } from 'stream';
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import { modelList } from '@/constants/model';
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import { pushBill } from '@/service/events/bill';
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/* 发送提示词 */
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export default async function handler(req: NextApiRequest, res: NextApiResponse) {
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const { chatId, prompt } = req.body as {
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prompt: ChatItemType;
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chatId: string;
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};
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const { authorization } = req.headers;
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try {
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if (!chatId || !prompt) {
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throw new Error('缺少参数');
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}
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await connectToDatabase();
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const { chat, userApiKey, systemKey, userId } = await authChat(chatId, authorization);
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const model: ModelSchema = chat.modelId;
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// 读取对话内容
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const prompts = [...chat.content, prompt];
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// 上下文长度过滤
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const maxContext = model.security.contextMaxLen;
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const filterPrompts =
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prompts.length > maxContext ? prompts.slice(prompts.length - maxContext) : prompts;
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// 格式化文本内容
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const map = {
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Human: ChatCompletionRequestMessageRoleEnum.User,
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AI: ChatCompletionRequestMessageRoleEnum.Assistant,
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SYSTEM: ChatCompletionRequestMessageRoleEnum.System
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};
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const formatPrompts: ChatCompletionRequestMessage[] = filterPrompts.map(
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(item: ChatItemType) => ({
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role: map[item.obj],
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content: item.value
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})
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);
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// 如果有系统提示词，自动插入
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if (model.systemPrompt) {
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formatPrompts.unshift({
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role: 'system',
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content: model.systemPrompt
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});
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}
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// 计算温度
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const modelConstantsData = modelList.find((item) => item.model === model.service.modelName);
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if (!modelConstantsData) {
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throw new Error('模型异常');
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}
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const temperature = modelConstantsData.maxTemperature * (model.temperature / 10);
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// 获取 chatAPI
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const chatAPI = getOpenAIApi(userApiKey || systemKey);
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let startTime = Date.now();
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// 发出请求
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const chatResponse = await chatAPI.createChatCompletion(
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{
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model: model.service.chatModel,
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temperature: temperature,
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// max_tokens: modelConstantsData.maxToken,
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messages: formatPrompts,
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stream: true
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},
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{
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timeout: 40000,
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responseType: 'stream',
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httpsAgent
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}
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);
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console.log('api response time:', `time: ${(Date.now() - startTime) / 1000}s`);
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// 创建响应流
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res.setHeader('Content-Type', 'text/event-stream;charset-utf-8');
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res.setHeader('Access-Control-Allow-Origin', '*');
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res.setHeader('X-Accel-Buffering', 'no');
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res.setHeader('Cache-Control', 'no-cache, no-transform');
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let responseContent = '';
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const pass = new PassThrough();
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pass.pipe(res);
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const onParse = async (event: ParsedEvent | ReconnectInterval) => {
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if (event.type !== 'event') return;
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const data = event.data;
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if (data === '[DONE]') return;
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try {
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const json = JSON.parse(data);
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const content: string = json?.choices?.[0].delta.content || '';
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if (!content) return;
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responseContent += content;
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// console.log('content:', content)
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pass.push(content.replace(/\n/g, '<br/>'));
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} catch (error) {
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error;
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}
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};
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const decoder = new TextDecoder();
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try {
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for await (const chunk of chatResponse.data as any) {
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const parser = createParser(onParse);
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parser.feed(decoder.decode(chunk));
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}
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} catch (error) {
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console.log('pipe error', error);
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}
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pass.push(null);
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const promptsLen = formatPrompts.reduce((sum, item) => sum + item.content.length, 0);
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console.log(`responseLen: ${responseContent.length}`, `promptLen: ${promptsLen}`);
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// 只有使用平台的 key 才计费
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!userApiKey &&
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pushBill({
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modelName: model.service.modelName,
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userId,
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chatId,
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textLen: promptsLen + responseContent.length
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});
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} catch (err: any) {
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res.status(500);
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jsonRes(res, {
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code: 500,
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error: err
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});
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}
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}
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