1、nestjs中引用esm插件

nestjs是使用commonjs规范进行开发，但是目前市场上很多插件是使用module的形式进行开发，所以遇到引用问题时，建议开发都绕过去，使用功能差不多的插件，但是如果遇到绕不过去的情况，那可以使用以下的方法进行引用

import { ConfigService } from '@nestjs/config';import { Injectable } from '@nestjs/common';import { FailException } from '@app/exceptions/fail.exception';import { ErrorCode } from '@app/constants/error.constant';export const importDynamic = new Function(  'modulePath',  'return import(modulePath)',);@Injectable()export class ChatService {  private chatGpt: any;  public constructor(private readonly configService: ConfigService) {}  private async initInstance(): Promise<void> {    if (!this.chatGpt) {      const { ChatGPTAPI } = await importDynamic('chatgpt');      this.chatGpt = new ChatGPTAPI({        apiKey: this.configService.get('chat.apiKey'),      });    }  }  public async getChatResponse() {    try {      if (!this.chatGpt) await this.initInstance();      const res = await this.chatGpt.sendMessage('用js生成一个计算器');      return res;    } catch (err) {      console.log(err);      throw new FailException(ErrorCode.SERVER_ERROR);    }  }}

2、nestjs中实现流的转发以及接口转发

import { Response } from 'express';import { lastValueFrom } from 'rxjs';import { HttpService } from '@nestjs/axios';import { IncomingHttpHeaders } from 'http';import { Controller, Post, Body, Headers, Res } from '@nestjs/common';import { DChatParam } from './chat.dto';import { ChatService } from './chat.service';import { pipeline } from 'stream';@Controller('chat')export class ChatController {  public constructor(    private readonly chatService: ChatService,    private readonly httpService: HttpService,  ) {}  // 基本的数据接口转发  @Post('parse')  public async chatParser(    @Headers() headers: IncomingHttpHeaders,    @Body() body: Record<string, string | boolean | number>,    // @Res() response: Response,  ) {    const response = this.httpService.post(      'https://api.openai.com/v1/chat/completions',      {        model: 'gpt-3.5-turbo',        messages: [{ role: 'user', content: '你好啊' }],      },      {        headers: {          'Content-Type': 'application/json',          Authorization:            'Bearer sk-************',        },      },    );    const res = await lastValueFrom(response);    return res.data;  }  @Post('stream')  public async streamRes(@Body() body: any, @Res() response: Response) {    const response$ = this.httpService.post(      'https://api.openai.com/v1/chat/completions',      {        model: 'gpt-3.5-turbo',        messages: [{ role: 'user', content: '你好' }],        stream: true,      },      {        headers: {          Authorization:            'Bearer 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',          'Content-Type': 'application/json',        },      },    );    const { data, headers } = await lastValueFrom(response$);    // 将响应头设置到当前请求的头部    if (headers) {      Object.keys(headers).forEach((key) => {        response.setHeader(key, headers[key]);      });    }    // 管道流处理    const stream = data;    await new Promise((resolve, reject) => {      pipeline(stream, response, (err) => {        if (err) {          reject(err);        } else {          resolve('');        }      });    });  }}