npm install dotenv openai chalk

// index.js 
// 导入所需的库import dotenv from "dotenv";import { Configuration, OpenAIApi } from "openai";import readline from "readline";import chalk from "chalk";
// Load environment variablesdotenv.config();
// Initialize the OpenAI API clientconst openai = new OpenAIApi(  new Configuration({ apiKey: process.env.OPENAI_API_KEY }));
// Create a readline interface for user inputconst rl = readline.createInterface({  input: process.stdin,  output: process.stdout});
// Define an array to store the conversation messagesconst GPTMessages = [];
// Set the model name; replace with other model names if neededconst modelName = "gpt⑷"; // "gpt⑶.5-turbo"
// Define an async function to call the GPT APIconst GPT = async (message) => {  // Call the GPT API with the model, messages, and max tokens  const response = await openai.createChatCompletion({    model: modelName,    messages: message,    max_tokens: 100,  });
  // Return the response content and the total number of tokens used  return {    content: response.data.choices[0].message.content,    tokensUsed: response.data.usage.total_tokens,  };};
// Define a function to ask the user a question and handle their inputconst askUserQuestion = (role) => {  // Set the prompt text based on the role (system or user)  const prompt = role === "system" ? "Enter system message: " : "Enter your question: ";
  // Ask the user a question and process their input  rl.question(prompt, async (userInput) => {    // Add the user's input to the GPTMessages array    GPTMessages.push({ role: role, content: userInput });
    // If the input is a system message, ask the user for their question    if (role === "system") {      askUserQuestion("user");    } else {      // Call the GPT function with the current conversation messages      const assistantResponse = await GPT(GPTMessages);
      // Add the assistant's response to the GPTMessages array      GPTMessages.push({ role: "assistant", content: assistantResponse.content });
      // Display the assistant's response and the number of tokens used      console.log(chalk.yellow("-----"));      console.log(chalk.green("Assistant: "), assistantResponse.content);      console.log(chalk.cyan("Tokens used: "), assistantResponse.tokensUsed);
      // Ask the user another question      askUserQuestion("user");    }  });};
// Display the model name and begin the conversationconsole.log(`### I'm ${chalk.blue(modelName.toUpperCase())}. ####`);askUserQuestion("system");