const Promise = require('promise');

//
// API Key For OpenAI
// **Add your Vectara API Key and Customer ID to MY SECRETS (Left Panel)**
//
let VECTARA_API_KEY = null;
let CUSTOMER_ID = null;
let channel = "docs-pubnub-ai-response";
function getVectaraKey() {
   // Use cached key
   if (VECTARA_API_KEY && CUSTOMER_ID) {
       return new Promise(resolve => resolve(VECTARA_API_KEY));
   }
   // Fetch key from vault
   return vault.get("VECTARA_API_KEY").then(apikey => {
       return vault.get("CUSTOMER_ID").then(customer_id => {
            VECTARA_API_KEY = apikey;
            CUSTOMER_ID = customer_id;
           return new Promise(resolve => resolve(VECTARA_API_KEY));
       });
   });
}

//
// Import Modules
//
const xhr = require('xhr');
const vault = require('vault');
const pubnub = require('pubnub');

//
// Main
//
export default (request) => {
   // Input data for Vectara
   let message = request.message.text;
   let signalMessage = { message: { type: "typing_on" }, channel: channel };
   return pubnub.signal(signalMessage).then((_) => {
       return getVectaraKey().then(_ => {
           return vectara(message).then(response => {
               return pubnub.publish({
                   channel: channel,
                   message: {
                       id: "PubNubAI",
                       type: "default",
                       text: response
                   },
               }).then((publishResponse) => {
                   console.log(publishResponse);
                   message = { message: { type: "typing_off" }, channel: channel };
                   return pubnub.signal(message).then((signalOffResponse) => {
                       console.log(signalOffResponse);
                       return request.ok();
                   });
               }).catch((err) => {
                   console.error(err);
               });
           });
       });
   });
};

//
// API Call to Vectara asking the AI a question
//
async function vectara(question) {
   console.log("SENDING REQUEST TO VECTARA");
   const url = "https://api.vectara.io/v1/query";
   const body = JSON.stringify({
       "query": [
           {
           "query": question,
           "start": 0,
           "numResults": 10,
           "contextConfig": {
               "charsBefore": 0,
               "charsAfter": 0,
               "sentencesBefore": 2,
               "sentencesAfter": 2,
               "startTag": "<b>",
               "endTag": "</b>"
           },
           "corpusKey": [
               {
               "customerId": CUSTOMER_ID,
               "corpusId": 1,
               "semantics": "DEFAULT",
               "dim": [
                   {
                   "name": "string",
                   "weight": 0
                   }
               ],
               "lexicalInterpolationConfig": {
                   "lambda": 0.025
               }
               }
           ],
           "rerankingConfig": {
               "rerankerId": 272725717
           },
           "summary": [
               {
               "summarizerPromptName": "",
               "maxSummarizedResults": 5,
               "responseLang": "eng",
               "summarizerPromptId": 1,
               "debug": false,
               "responseChars": 0
               }
           ]
           }
       ]
   });

   const http_options = {
       'method': 'POST',
       'timeout': 20000,
       'headers': {
           'Content-Type': 'application/json',
           'customer-id': CUSTOMER_ID,
           'x-api-key': VECTARA_API_KEY
        },
       'body': body
   };

   xhr.timeout = 100000;

   // Send API Request to OpenAI GPT Model
   const response = await xhr.fetch(url, http_options).then(res => res.json());

   // Parse the response and get the summary
   const summary = response.responseSet[0].summary[0].text;

   return summary;
}

const pubnub = new PubNub({
   publishKey: process.env.NEXT_PUBLIC_PUBLISH_KEY!,
   subscribeKey: process.env.NEXT_PUBLIC_SUBSCRIBE_KEY!,
   userId: "You",
 });

 const publishChannel = "docs-pubnub-ai";

 const sendMessage = (message: string) => {
   if (message) {
     pubnub.publish({
         channel: publishChannel, message: {
           text: message
       }});
   }
 };