Build a Hamilton Song Recommendation SMS Bot with Machine Learning

const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
const WhichX = require("whichx");
exports.handler = async function(context, event, callback) {
        let twiml = new Twilio.twiml.MessagingResponse();
        const key = context.AZURE_KEY_HAMILFILM;
        const endpoint = context.AZURE_ENDPOINT_HAMILFILM;
        const textAnalyticsClient = new TextAnalyticsClient(endpoint,  new AzureKeyCredential(key));
        const input = [
            event.Body
        ];
        const songs = {
	"non-stop": {
		desc: "You work a lot. You work too hard and do not sleep much, but it is how you get ahead. Keep pushing forward, maybe take some risks.",
		link: "youtube.com/watch?v=_YHVPNOHySk"
	},
	"wait for it": {
		desc: "Lost, doubtful, confused, maybe sad or down, and you do not know what to do? Good things take time. You will get praise, recognition, and validation soon. If you're doubting yourself, just keep going. You are inimitable, an original.",
		link: "youtube.com/watch?v=ulsLI029rH0"
	},
	"schuyler sisters": {
		desc: "Girl power! Queens. Sisters. You are empowered and thus empower others. Keep your siblings and friends close. You may be looking for a significant other, a friend, a peer, or a general mind at work.",
		link: "youtube.com/watch?v=UeqKF_NF1Qs"
	},
	"dear theodosia": {
		desc: "You get teary over your kid or your pet like when your dog is sleeping. They are cute, young, innocent, and have their whole lives ahead of them, which you will make better.",
		link: "youtube.com/watch?v=TKpJjdKcjeo"
	},
	"story of tonight": {
		desc: "You may be emotional over what you, your friends, and your family will do in the future. The night is still young. You can all do so much and change the world!",
		link: "youtube.com/watch?v=3vqwrepaMR0"
	},
	"my shot": {
		desc: "You may be confused or unsure. Life is tough but you are tougher. All you need is one chance, one shot, and you do not know what to do right now. Well here is the inspiration and motivation you need to accomplish anything.",
		link: "youtube.com/watch?v=Ic7NqP_YGlg"
	},
	"alexander hamilton": {
		desc: "You save time by reading summaries. You do not get the hype over Alexander Hamilton or know the story. Hamilton may be new to you. This song will sum it up succinctly for you and you'll learn some history too.",
		link: "youtube.com/watch?v=VhinPd5RRJw"
	},
    };
    
    const sentimentResult = await textAnalyticsClient.analyzeSentiment(input);
    let sentiment, pos, neg, neutral, max;
    
    sentimentResult.forEach(document => {
        console.log(`ID: ${document.id}`);
        console.log(`Document Sentiment: ${document.sentiment}`);
        console.log(`Positive: ${document.confidenceScores.positive.toFixed(2)} Negative: ${document.confidenceScores.negative.toFixed(2)} Neutral: ${document.confidenceScores.neutral.toFixed(2)}`);
        document.sentences.forEach(sentence => {
            sentiment = sentence.sentiment;
            console.log(`Sentence sentiment: ${sentiment}`);
            pos = sentence.confidenceScores.positive.toFixed(2);
            neg = sentence.confidenceScores.negative.toFixed(2);
            neutral = sentence.confidenceScores.neutral.toFixed(2);
            var obj = {"positive": pos, "negative": neg, "neutral": neutral};
            max = Object.keys(obj).reduce((a, b) => obj[a] > obj[b] ? a : b);
        });
    });
   
    //Build our Bayesian model
    var whichfw = new WhichX();
     whichfw.addLabels(["non-stop", "wait for it", "schuyler sisters", "dear theodosia", "story of tonight", "my shot", "alexander hamilton"]);
    Object.keys(songs).forEach((s) => { whichfw.addData(s.toLowerCase(), songs[s].desc) } );
    const song = whichfw.classify(event.Body); 
    const reasonWhySong = songs[song].desc;
    const link = songs[song].link;
    twiml.message(`You seem to be feeling ${max}. ${reasonWhySong} We recommend listening to ${song} right now: ${link}`);
    callback(null, twiml);
};

const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
const WhichX = require("whichx");

exports.handler = async function(context, event, callback) {
        let twiml = new Twilio.twiml.MessagingResponse();
        const key = context.AZURE_KEY_HAMILFILM;
        const endpoint = context.AZURE_ENDPOINT_HAMILFILM;
        const textAnalyticsClient = new TextAnalyticsClient(endpoint,  new AzureKeyCredential(key));
        const input = [
            event.Body
        ];

const songs = {
    "non-stop": {
		desc: "You work a lot. You work too hard and do not sleep much, but it is how you get ahead. Keep pushing forward, maybe take some risks.",
		link: "youtube.com/watch?v=_YHVPNOHySk"
	},
        //complete songs object code on GitHub: https://github.com/elizabethsiegle/hamilton_song_recommender_azure_cog_services/blob/master/index.js
        ...
};

const sentimentResult = await textAnalyticsClient.analyzeSentiment(input);
let sentiment, pos, neg, neutral, max;

sentimentResult.forEach(document => {
        console.log(`ID: ${document.id}`);
        console.log(`Document Sentiment: ${document.sentiment}`);
        console.log(`Positive: ${document.confidenceScores.positive.toFixed(2)} Negative: ${document.confidenceScores.negative.toFixed(2)} Neutral: ${document.confidenceScores.neutral.toFixed(2)}`);
        document.sentences.forEach(sentence => {
            sentiment = sentence.sentiment;
            console.log(`Sentence sentiment: ${sentiment}`);
            pos = sentence.confidenceScores.positive.toFixed(2);
            neg = sentence.confidenceScores.negative.toFixed(2);
            neutral = sentence.confidenceScores.neutral.toFixed(2);
            var obj = {"positive": pos, "negative": neg, "neutral": neutral};
            max = Object.keys(obj).reduce((a, b) => obj[a] > obj[b] ? a : b);
        });
    });

 //Build our Bayesian model
    var whichfw = new WhichX();
    whichfw.addLabels(["non-stop", "wait for it", "schuyler sisters", "dear theodosia", "story of tonight", "my shot", "alexander hamilton"]);
    Object.keys(songs).forEach((s) => { whichfw.addData(s.toLowerCase(), songs[s].desc) } );
    const song = whichfw.classify(event.Body); 
    const reasonWhySong = songs[song].desc;
    const link = songs[song].link;
    twiml.message(`You seem to be feeling ${max}. ${reasonWhySong} We recommend listening to ${song} right now: ${link}`);
    callback(null, twiml);
};