How can i add two line breaks(\n\n) at the start of every message response recieved from openai under the resume category?
Code:
const fs = require("fs");
const { Configuration, OpenAIApi } = require("openai");
let Chatgpt = {};

const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY,
});

const openai = new OpenAIApi(configuration);

function sleep(ms) {
  return new Promise((resolve) => {
    setTimeout(resolve, ms);
  });
}

Chatgpt.botreplyfirst = async(req, res) => {
  
  let data=req.body;
  let message = data.message;
  let category_key = data.category_key;
  let tone = data.tone;
  let replyIn = data.replyIn;
  let formality = data.formality;
  let promptfilter = data.promptfilter;
  let promtmessage = "";
  let promtvalue = 0;
  let userToken = 0;
  let purchaseTime =0;
  if(promptfilter == "1"){
    promptfilter ="Please fix grammer and punctuations {explain the mistakes at the end}"
  }
  if(promptfilter == "2"){
    promptfilter ="Provide improvement in phrases that enhance clarity"
  }
  if(promptfilter == "3"){
    promptfilter ="Improve my writing style and provide stylistic suggestions and examples"
  }
  if(promptfilter == "4"){
    promptfilter ="Assist me with choosing the right word"
  }
  if(promptfilter == "5"){
    promptfilter ="Offer sentence structure suggestions along {with examples}"
  }
  return new Promise(async (resolve, reject) => {
    try {
  if(!message){
    reject("Message is required");
    return;
  }
  if(!tone){
    tone = "Confident"
  }
  if(!replyIn){
    replyIn = "American English"
  }
  if(!formality){
    formality ="Formal"
  }
  if(!promptfilter){
    promptfilter =" "
  }else{
  //  promptfilter = promptfilter+' and '
   promptfilter = '['+promptfilter+']'
  }

  if(!category_key){
    reject("category_key required");
      return;
  }
  let userId = req.authUser ? req.authUser.userId : 0;
    if (!userId) {
      reject("login required");
      return;
    }


  let userdata = await UserModel.findOne({ _id: userId }).lean().exec();    
  let categorydata = await CategoryModel.findOne({ categorykey: category_key }).lean().exec();    
  
  if(category_key == 'social_media'){
    promtmessage = 'someprompt'
  }
  if(category_key == 'email'){

    promtmessage = `someprompt`
     
  if(category_key == 'messages'){
    promtmessage = `someprompt`
  }  
  if(category_key == 'general'){
    promtmessage = 'someprompt'
  }
  if(category_key == 'meeting_minute'){
    promtmessage = 'someprompt'
  }
  if(category_key == 'resume'){
    promtmessage = `someprompt`
  }
  if(category_key == 'report'){
    promtmessage = 'someprompt'
  }
  
  if(userdata.promptToken != undefined){
    promtvalue = userdata.promptToken 
  }

      const response = await openai.createChatCompletion({
        model: "gpt-3.5-turbo",
        messages: [{"role": "system", "content": "You are a helpful assistant your name is tamara."}, {role: "user", content: promtmessage}],
      });
      console.log("promtmessage:-",response)
      await UserModel.findOneAndUpdate(
        { _id: userId },
        {
          $set: {
            promptToken:response.data.usage.prompt_tokens+promtvalue,
            updatedAt: new Date()
          }
        },
        { new: true },
      );
    let findCase={user_id:userId};
    let historydataresp = await HistoryModel.find(findCase).sort({_id:-1}).limit(2)
    let chatgpt = historydataresp[0]
    let user = historydataresp[1]
      const data = {
        userMessage: {
          _id:  user._doc._id,
          message: user._doc.message,
          message_from: "user",
          createdAt:user._doc.createdAt,
          isLike: user._doc.isLike,
          isDisLike:  user._doc.isDisLike,
          isSave: user._doc.isSave,
          translator: user._doc.translator,
          user: {
            _id: userId,
            name:userdata.name,
            avatar: userdata.profilePicture,
          },
        },
        chatGPTMessage: {
          _id: chatgpt._doc._id,
          message: chatgpt._doc.message,
          message_from: "chatgpt",
          createdAt: chatgpt._doc.createdAt,
          isLike: chatgpt._doc.isLike,
          isDisLike:  chatgpt._doc.isDisLike,
          isSave: chatgpt._doc.isSave,
          translator: chatgpt._doc.translator,
          user: {
            _id: categorydata._id,
            name: categorydata.name,
            avatar: null,
          },
        }
        
      }
      resolve(data)

    } 
  });
};

Chatgpt.botreply = (req, res) => {
  return new Promise(async (resolve, reject) => {
    try {
      const response = await openai.createChatCompletion({
        model: "gpt-3.5-turbo",
        messages: [{"role": "system", "content": "You are a helpful assistant your name is tamara."}, {role: "user", content: req.body.message}],
      });
      resolve(response.data.choices[0].text)
    } catch(error) {
      // Consider adjusting the error handling logic for your use case
      if (error.response) {
        console.error(error.response.status, error.response.data);
        reject(error.response)
      } else {
        console.error(`Error with OpenAI API request: ${error.message}`);
        reject('An error occurred during your request.')
      }
    }
  });
};

Chatgpt.categories = (req) => {
  return new Promise((resolve, reject) => {
    let findCase={visibility:true};

    CategoryModel.find(findCase, function (err, response) {
      if (err) {

        reject(err);
      } else {

        if (response.length > 0) {
          resolve(response)
        }else{
          reject("not found!!")
        }
      }
     });
  });
};