IBM Watson Salesforce Visual Recognition

In this Blog, I am going to explain how to Integrate Salesforce and IBM Watson Image Recognition.  Visual Recognition allows users to understand the contents of an image or video frame, answering the question: “What is in this image?” and “Are there similar images?” etc. The IBM Watson Visual Recognition service uses deep learning algorithms to analyze images for scenes, objects, faces, and other content. The response includes keywords that provide information about the content.A set of built-in classes provides highly accurate results without training. You can train custom classifiers to create specialized classes. You can also create custom collections of your own images, and then upload an image to search the collection for similar images. In this blog, we are going to use default classifiers to classify an image and then detect faces in an image. You can also preview a live version of this application. Some of the major highlights include

Object determination — Classification of things in the image
Face detection — Detect human faces, including estimation of age & gender
Text extraction — Extract text contained in the image
Celebrity identifier — Identity of the person if your image includes a public figure

1. Setup API Key for IBM Watson Visual Recognition

  1. Register for IBM Bluemix with US South or your preferred region.
  2. Log in to the IBM Bluemix.
  3. Select Create app, to start with the new applet
  4. Find Watson on Services tab
  5. On Watson services, select Visual Recognition API
  6. Click on Create to get started.
  7. On Service credentials, select on credential-1 and copy the API-key
    Once you get the API key you are completed with Bluemix console setup now we will turn to Salesforce.

2. Salesforce Setup

I am considering the case is having an image which we will use for Image Recognition. So let’s set up two new fields on the case as shown below. Upload_Image_URL__c – URL(255)
Image__c  formula   HYPERLINK( Upload_Image_URL__c ,IMAGE( Upload_Image_URL__c , “Case Image”))

3. Train a Custom Classifier

So not too much worried at this stage on the  Custom Classifier and trying to emphasize the out of the box default classifier with IBM Waston. You can consider to implement the custom classifier based on the business logic and wanted to implement your own image classification that fits your model like a product catalog.

4.Remote Site Settings

Add the Image Recognition services under Remote Site settings.

5.Recognition Image

Here is the simple visualforce page that shows how we can classify the images as shown below. You will get the result of each image with a prediction score and Classification. You can now use the class with the highest score in your application to label your image.

6. Code Walkthrough

Here is the code walkthrough for the apex controller. The below code is shown the simple way to build the endpoint URL of image Recognition services.

 public String buildImageRecognizationURL(String imageURL ,String API_KEY ){
        String baseURL = 'https://gateway-a.watsonplatform.net/visual-recognition/api/v3/classify?api_key='+API_KEY+'&url='+imageURL+'&version=2016-05-20';
        return baseURL ;
    }

the below code is making an API call to Watson services along with the image URL

 HttpRequest req = new HttpRequest();
        String baseURL = buildImageRecognizationURL(c.Upload_Image_URL__c, '9c1be84069f7af00896771d0dfd8b1bb4c822d5b');
        req.setEndpoint(baseURL);
        req.setMethod('POST');
        Http http = new Http();
        HTTPResponse res = http.send(req);

Below Code is used to for parsing the JSON response data to show it the page

 public list<Classification> parseJson(String jsonRes){
        list<Classification> classif = new list<Classification>() ;
        Map<String, Object> m =(Map<String, Object>)JSON.deserializeUntyped(jsonRes);
        List<Object> a = (List<Object>)m.get('images');
        Map<String, Object> a2 =(Map<String, Object>)a[0];
        List<Object> a33 = (List<Object> )a2.get('classifiers') ; 
        Map<String, Object> a444 =(Map<String, Object>)a33[0];
        List<Object> a555= (List<Object>)a444.get('classes');
        for(Object o :a555){
            Map<String, Object> classiObj =(Map<String, Object>)o;
            Classification cNew = new Classification(); 
            for(String ss : classiObj.keySet()){
                if(ss=='class'){
                    cNew.classificaions = (String)classiObj.get(ss) ;
                }
                if(ss=='score'){
                    cNew.percentage = (Decimal)classiObj.get(ss) ;
                }
            }
            classif.add(cNew);
        }
        return classif;
    }
    
    public class Classification {
        public String classificaions {get;set;}
        public Decimal percentage {get;set;}
    }

Here is corresponding visualforce page code

 <div class="slds-scope">
        <table class="slds-table slds-table_bordered slds-table_cell-buffer">
            <thead>
                <tr class="slds-text-title_caps" style="padding: 0.5rem; color: rgb(51, 135, 133);">
                    <th scope="col">
                        <div class="slds-truncate" title="Classification"><b>Classification</b></div>
                    </th>
                    <th scope="col">
                        <div class="slds-truncate" title="prediction %"><b>prediction %</b></div>
                    </th>
                </tr> </thead>
            <tbody>
                <apex:repeat value="{!fetchClassifications}" var="cls">
                    
                    <tr>
                        <th scope="row" data-label="Classification">
                            <div class="slds-truncate" > {!cls.classificaions}</div>
                        </th>
                        <td data-label="prediction %">
                            <div class="slds-truncate">
                                {!cls.percentage}%
                            </div>
                        </td>
                        
                        
                    </tr>
                    
                </apex:repeat>
            </tbody>
        </table>

Github Repo is here below

https://github.com/rajamohanvakati/Watson-Image-Recognition

Customer Tone Analyze from Live Agent Chat

In this blog, I am going to explain how to understand the customer tone from the live agent chat and this post is an extended version of my post about customer tone. IBM Watson has different tone analyzer services like from the text, email, and customer engagement.
You can use live agent transcript for tone analysis. simple live agent chat is looking as shown below

the result of the analysis will look as shown below.

The code is here for the same is shown here below.

public class IBMWatsonToneChatAnalyzer {
    
    Private String caseId {get;set;}
    public Case c{get;set;}
    public String jsonData{get;set;}
    public ToneAnalysis tones {get;set;}
    public IBMWatsonToneChatAnalyzer(ApexPages.StandardController con){
        caseId = con.getId() ; 
        c =[Select Id , Subject,Description from Case where id=:caseId] ;
        callWatsonToneAnalyser(c);
    }
    
    public  void callWatsonToneAnalyser(Case c) {
        HttpRequest req = new HttpRequest();
        req.setEndpoint('callout:Bluemix_Tone_Analyser/v3/tone_chat?version=2016-05-18');
        req.setMethod('POST');
        req.setHeader('Content-Type', 'application/json');
        req.setBody(stringToJSON(c));
        Http http = new Http();
        HTTPResponse res = http.send(req);
        jsonData = res.getBody();
        tones =  (ToneAnalysis) JSON.deserialize(res.getBody(), ToneAnalysis.class);
        
    }
    
    private static String stringToJSON(Case c) {
        LiveChatTranscript trans = [Select Id , Body from LiveChatTranscript where CaseId =:c.Id ];
        String body =trans.Body;
        return     buildJson(body);
    }
    
    public static String buildJson(String body){
        List<String> strSplite = body.Split('<p align="center">') ;
        String againSpl = strSplite[3];
        String spl2 = againSpl.Split('</p>')[0];
        String agentName = spl2.Split('Agent')[1] ; 
        String toMakeJson = strSplite[3].replace('Agent','') ;
        String temp = strSplite[3].replace('Agent','');
        List<String> spliteBodsy = temp.Split(agentName) ; 
        //System.debug('spliteBodsy'+spliteBodsy);     
        JSONGenerator gen = JSON.createGenerator(true);
        gen.writeStartObject();
        gen.writeFieldName('utterances');
        gen.writeStartArray();
        for (integer i = 0; i <spliteBodsy.size(); i++){
            String res = spliteBodsy[i]; 
            List<String> restem =res.Split('Visitor') ; 
            If(restem.size()>1){
                gen.writeStartObject();
                gen.writeStringField('text', res.Split('Visitor')[1]);
                gen.writeStringField('user', 'customer');
                gen.writeEndObject();
                gen.writeStartObject();
                gen.writeStringField('text', res.Split('Visitor')[0]);
                gen.writeStringField('user', 'agent');
                gen.writeEndObject();
                
            }
        }
        gen.writeEndArray();
        gen.writeEndObject();
        
        String pretty = gen.getAsString();
        System.debug('pretty'+pretty);
        return pretty ;
        
    } 
    
    public class Tones {
        public Double score{get;set;}
        public String tone_id{get;set;}
        public String tone_name{get;set;}
    }
    
    public class ToneAnalysis {
        public List<Utterances_tone> utterances_tone{get;set;}
    }
    
    public class Utterances_tone {
        public Integer utterance_id{get;set;}
        public String utterance_text{get;set;}
        public List<Tones> tones{get;set;}
    }
    
    public class Tones_Z {
    }
    
    
    public static ToneAnalysis parse(String json) {
        return (ToneAnalysis) System.JSON.deserialize(json, ToneAnalysis.class);
    }
    
}

The below is the visualforce page for the same.

<apex:page standardController="Case" extensions="IBMWatsonToneChatAnalyzer" showHeader="false"  standardStylesheets="false" sidebar="false" applyHtmlTag="false" applyBodyTag="false" docType="html-5.0">
    <html xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" lang="en">
        <head>
            <meta charset="utf-8" />
            <meta http-equiv="x-ua-compatible" content="ie=edge" />
            <title>Image Recognization with Watson </title>
            <meta name="viewport" content="width=device-width, initial-scale=1" />
            <apex:slds />
            
        </head>
        <body>
            
            <div class="slds-scope">
                <div class="demo-only" style="padding: 0.5rem; background: rgb(51, 135, 133);">
                    <div class="slds-text-color_inverse-weak slds-text-heading_large slds-text-align_center"> Case Tone Analyzer </div>
                </div>
            </div>
            <div class="slds-scope">
                <div class="slds-grid">
                    <apex:repeat value="{!tones.utterances_tone}" var="cls">
                        <div class="slds-col">
                            <apex:repeat value="{!cls.tones}" var="cls1">
                                <div class="slds-page-header color-background-error-dark">
                                    <div class="slds-media__body">
                                        <p class="slds-text-body_small slds-line-height_reset">{!cls1.tone_name}</p>
                                        <p class="slds-text-body_small slds-line-height_reset">
                                            {!cls1.score}  
                                        </p>
                                    </div>
                                </div>
                            </apex:repeat>
                        </div>
                        
                    </apex:repeat>
                    
                </div>
            </div>
        </body>
    </html>
</apex:page>

 

 

 

 

 

 

Understand Customer Feeling from Case With IBM Watson

In this post, we are going to see how to use IBM Watson tone analyzer services understand the customer emotional, social, and language tones from the case descriptions. You can use IBM Waston services in many ways like understand the customer tone from Analyzing text marketing campaigns, Understanding the lead interested level, understand customer happiness from the case is few use cases. Let’s assume the case is coming from the web to lead with case subject and Description about the case . This post we are going to Predict whether they are happy, sad, confident, and more from the description an the subject.

What is Watson Tone Analyzer?

The IBM Watson Tone Analyzer service uses linguistic analysis to detect emotional, social, and language tones in written text. The service can analyze tone at both the document and sentence levels. You can use the service to understand how your written communications are perceived and then to improve the tone of your communications. Businesses can use the service to learn the tone of their customers’ communications and to respond to each customer appropriately or to understand and improve their customer conversations in general.You submit JSON, plain text, or HTML input that contains your written content to the service. The service returns JSON results that report the tone of your input. You can use these results to improve the perception and effectiveness of your communications, ensuring that your writing conveys the tone and style that you want for your intended audience. The following diagram shows the basic flow of calls to the service.

Submit content to the Tone Analyzer service and use the results to improve your communications.

1. Create Waston Service

To get started, one can just create an IBM login at https://console.ng.bluemix.net and create a service called “Tone Analyzer” as shown below.

Select the Service click on create a service to receive your credentials which are required to make an API call from the salesforce.

 

2. Create Named Credential in Salesforce

Create a named credential in Salesforce with the Tone Analyzer service credentials which you got them from the first step and you can use those in call out to IBM Watson services.

3. Simple Visualforce page.

That’s all. Here is the below Sample visualforce page that displays the customer emotions based on the case subject and description. The page shows the complete custom tone in different areas of the Emotions and Language styles and Social Tendencies.

4.Code Walkthrough

Here is the below piece of code that prepares the Json file to send the HTTP request to Watson services.

    JSONGenerator generator = JSON.createGenerator(true);
        generator.writeStartObject();
        generator.writeStringField('text', c.Subject+''+c.Description);
        generator.writeEndObject();

Below piece of code shows how to make the Http Call to IBM Watson tone services. We are using the Named Credentials with call out.

 HttpRequest req = new HttpRequest();
        req.setEndpoint('callout:Bluemix_Tone_Analyser/v3/tone?version=2016-05-18');
        req.setMethod('POST');
        req.setHeader('Content-Type', 'application/json');
        req.setBody(stringToJSON(c));
        Http http = new Http();
        HTTPResponse res = http.send(req);
        jsonData = res.getBody();

 

Below Piece of code is for the JSON parsing.

public Class ToneAnalysis {
        public DocumentTone document_tone {get; set;} 
    }
    
    public Class DocumentTone {
        public  List<ToneCategory> tone_categories {get; set;}
    }
    
    public Class ToneCategory {
        public  List<Tone> tones {get; set;}
        public  String category_id {get; set;}
        public  String category_name {get; set;}
    }
    
    public Class Tone {
        public  Double  score {get; set;}
        public  String tone_id {get; set;}
        public  String tone_name {get; set;}
    }

Here is the visual force page the show the result.

<div class="slds-scope">
                <div class="demo-only" style="padding: 0.5rem; background: rgb(51, 135, 133);">
                    <div class="slds-text-color_inverse-weak slds-text-heading_large slds-text-align_center"> Case Tone Analyzer </div>
                </div>
            </div>
            <div class="slds-scope">
                <div class="slds-grid">
                    <div class="slds-col">
                        <div class="slds-page-header">
                            <div class="slds-media__body">
                                <h1 class="slds-page-header__title slds-truncate slds-align-middle">Emotion</h1>
                                <p class="slds-text-body_small slds-line-height_reset">
                                    &lt; .5 = not likely present <br/> &gt; .5 = likely present <br/> &gt; .75 = very likely present <br/>
                                </p>
                            </div>
                        </div>
                    </div>
                    <div class="slds-col">
                        <div class="slds-page-header">
                            <div class="slds-media__body">
                                <h1 class="slds-page-header__title slds-truncate slds-align-middle">Language Style</h1>
                                <p class="slds-text-body_small slds-line-height_reset">
                                    &lt; .5 = not likely present <br/> &gt; .5 = likely present <br/> &gt; .75 = very likely present <br/>
                                </p>
                            </div>
                        </div>
                    </div>
                    <div class="slds-col">
                        <div class="slds-page-header">
                            <div class="slds-media__body">
                                <h1 class="slds-page-header__title slds-truncate slds-align-middle">Social Tendencies</h1>
                                <p class="slds-text-body_small slds-line-height_reset">
                                    &lt; .5 = not likely present <br/> &gt; .5 = likely present <br/> &gt; .75 = very likely present <br/>
                                </p>
                            </div>
                        </div>
                    </div>
                </div>
            </div>
            <div class="slds-scope">
                <div class="slds-grid">
                    
                    <apex:repeat value="{!tones.document_tone.tone_categories}" var="cls">
                        <div class="slds-col">
                            <apex:repeat value="{!cls.tones}" var="cls1">
                                <div class="slds-page-header color-background-error-dark">
                                    <div class="slds-media__body">
                                        <p class="slds-text-body_small slds-line-height_reset">{!cls1.tone_name}</p>
                                        <p class="slds-text-body_small slds-line-height_reset">
                                            {!cls1.score}  
                                        </p>
                                    </div>
                                </div>
                            </apex:repeat>
                        </div>
                        
                    </apex:repeat>
                    
                </div>
            </div>

Here is the complete code

https://github.com/rajamohanvakati/Watson-Tone-Analyzer-

5.Conclusion

If you’d like help identifying how your customers are feeling, IBM Watson tone analyzer will help you to understand.

 

 

 

Salesforce Contact Personality Insights with Watson

1. Introduction

In this blog, I am going to explain how to use contact personality insight by using contact twitter handler to Predict personality characteristics by using the twitter timeline. but you can leverage the Personality Insights other aspects based on the user profile information or Facebook post or even you can use Salesforce chatter post it self to understand.

2.What is Personality Insight?

Personality Insights extracts and analyzes a spectrum of personality attributes to help discover actionable insights about people and entities, and in turn guides end users to highly personalized interactions. The IBM Watson Personality Insights service provides an API that enables applications to derive insights from social media, enterprise data, or other digital communications. The service uses linguistic analytics to infer individuals’ intrinsic personality characteristics, including Big Five, Needs, and Values, from digital communications such as email, text messages, tweets, and forum posts.The service can automatically infer, from potentially noisy social media, portraits of individuals that reflect their personality characteristics. It can also determine individuals’ consumption preferences, which indicate their likelihood to prefer various products, services, and activities.As a core service of the IBM Watson platform, the Personality Insights service can help businesses understand their customers at a deeper level. It can help businesses learn their clients’ preferences, improve customer satisfaction, and strengthen client relations. Businesses can use these insights to improve client acquisition, retention, and engagement, and to guide highly personalized engagements and interactions to better tailor their products, services, campaigns, and communications for individual clients.

3. Create a custom field on Contact

Create a new text field on the contact twitter_handler__c text of 255 on contact object. we will use this to store the contact twitter handler.  We are going to see the personality insight sunburst Chart which contains all the insights of the contacts

4. Making API calls to twitter / Connected App in twitter.

Go to https://apps.twitter.com/ and create an app from the twitter. After this, you are going to get the OAuth details which we will make an API call to the twitter timeline. Here is the below code which we will use to make an API call to twitter

 String oauthVersion = '1.0';
        String oauthConsumerKey = 'dEa7ZayYR6gnvdMMMDHhSXwX';        
        String oauthConsumerSecret = '0lQeueBZgm1cGIQIwEgaOveEN3JYEsNDRr9gWeVo1Cmovme9Z';
        String baseUrl = 'https://api.twitter.com';
        String oauthSignatureMethod = 'HMAC-SHA1';
        String strTwitterId = twitterHandler;
        String pictureURL = '';
        String twitterAcct = twitterHandler;
        String keyencoded = EncodingUtil.urlEncode(oauthConsumerKey, 'UTF-8');
        String secretkeyencoded = EncodingUtil.urlEncode(oauthConsumerSecret, 'UTF-8');
        //Create Final Key String
        String sFinal = keyencoded + ':' + secretkeyencoded;
        //Convert to Blob
        Blob headerValue = Blob.valueOf(sFinal);
        //Build Request
        HttpRequest req = new HttpRequest();
        req.setEndpoint('https://api.twitter.com/oauth2/token');
        req.setMethod('POST');
        //Add Auth Header
        String authorizationHeader = 'Basic ' + EncodingUtil.base64Encode(headerValue);
        req.setHeader('Authorization', authorizationHeader);
        req.setBody('grant_type=client_credentials');
        Http http = new Http();
        HTTPResponse res = http.send(req);
        String responseBody = res.getBody();
        String stoken;
        JSONParser parser = JSON.createParser(res.getBody());
        while (parser.nextToken() != null) 
        {
            if (parser.getCurrentToken() == JSONToken.FIELD_NAME && parser.getText() == 'access_token')
            {
                parser.nextToken();
                stoken = parser.getText();
            }
        }
        HttpRequest req2 = new HttpRequest();
        String endpoint90 = 'https://api.twitter.com/1.1/statuses/user_timeline.json?screen_name='+ twitterAcct + '&count=240' ;
        req2.setEndpoint(endpoint90);
        req2.setMethod('GET');
        String authorizationHeader2 = 'Bearer ' + stoken;
        req2.setHeader('Authorization', authorizationHeader2);
        Http http2 = new Http();
        HTTPResponse res2 = http2.send(req2);
        String sBody2 = res2.getBody();
        String responseBody2 = res2.getBody();
        JSONParser parser2 = JSON.createParser(res2.getBody());
        System.JSONToken token;
        List<TwitterResponse> twitterResponse = (List<TwitterResponse>)JSON.deserialize( res2.getBody() , List<TwitterResponse>.class);

5. Create a Services in IBM Watson console.

Go to IBM Watson console and create a new Personality  insight services and obtain the service credentials

Click on Create and Get the Service Credentials as shown below

6. Created Named Credential in Salesforce

Create a named credential in Salesforce with the IBM Watson personality insight API authentication which we will use for call out with Watson Personality services.

7. Finally, Visualforce Page and Controller to make API call

Here is the apex controller that calls IBM Watson personality services.

public class IBMWatsonPersonalTwitter {
    Private String userIds {get;set;}
    public Contact c{get;set;}
    public String jsonData{get;set;}
    public JSON2Apex apexCls{get;set;} 
    public IBMWatsonPersonalTwitter(ApexPages.StandardController con){
        userIds = con.getId() ; 
        c =[Select Id , Name,Twitter_Name__c from Contact where id=:userIds] ;
        callWatsonToneAnalyser(c);
        apexCls = parse(jsonData);
    }
    public static String createAuthHeader(String username, String password){
        Blob headerValue = Blob.valueOf(username + ':' + password);
        String authorizationHeader = 'Basic ' + EncodingUtil.base64Encode(headerValue);
        return authorizationHeader;
    }
    public  void callWatsonToneAnalyser(Contact c) {
        HttpRequest req = new HttpRequest();
        req.setEndpoint('callout:IBM_Watson_Personality_Insight/v3/profile?version=2016-10-20&consumption_preferences=true&raw_scores=true');
        req.setHeader('Content-Type', 'application/json');
        req.setBody(stringToJSON(c.Twitter_Name__c));
        req.setMethod('POST');
        Http http = new Http();
        HTTPResponse res = http.send(req);
        jsonData = res.getBody();
    }
    
    private String stringToJSON(String  userTweets) {
        List<TwitterResponse> responce = TwitterHandler.getTwitterDetails(userTweets);
        List<ContentItemsJSON.contentItem> contentItems =  new List<ContentItemsJSON.contentItem>();
        for(TwitterResponse tweet : responce){
            ContentItemsJSON.contentItem contentItem = new ContentItemsJSON.contentItem();
            contentItem.id = tweet.id_str;
            contentItem.userid = userTweets;
            contentItem.sourceid = 'twitter';
            contentItem.created = (Integer)Datetime.now().getTime();
            contentItem.updated = (Integer)Datetime.now().getTime();
            contentItem.contenttype = 'text/plain';
            contentItem.charset = 'UTF-8';
            contentItem.language = 'en-us';
            contentItem.content = tweet.text;
            contentItem.parentid = '';
            contentItem.reply = false;
            contentItem.forward = false;
            contentItems.add(contentItem);
        }
        
        
        
        JSONGenerator generator = JSON.createGenerator(true);
        generator.writeStartObject();
        generator.writeObjectField('contentItems', contentItems);
        generator.writeEndObject();
        String body = generator.getAsString();
        jsonData = body;
        System.debug('body'+body);
        
        
        return body;
        //  return TwitterHandler.getTwitterDetails(c.Twitter_Name__c);
    }
    //
    // Generated by JSON2Apex http://json2apex.herokuapp.com/
    //
    
    
    
    public class Consumption_preferences {
        public String consumption_preference_id;
        public String name;
        public Double score;
    }
    
    public class JSON2Apex {
        public Integer word_count;
        public String processed_language;
        public List<Personality> personality{get;set;}
        public List<Children> needs;
        public List<Children> values;
        public List<Behavior> behavior{get;set;}
        public List<Consumption_preferences_Z> consumption_preferences{get;set;}
        public List<Warnings> warnings;
    }
    
    public class Consumption_preferences_Z {
        public String consumption_preference_category_id;
        public String name;
        public List<Consumption_preferences> consumption_preferences;
    }
    
    public class Personality {
        public String trait_id;
        public String name{get;set;}
        public String category{get;set;}
        public Double percentile{get;set;}
        public Double raw_score{get;set;}
        public List<Children> children;
    }
    
    public class Children {
        public String trait_id;
        public String name;
        public String category;
        public Double percentile;
        public Double raw_score;
    }
    
    public class Behavior {
        public String trait_id {get;set;}
        public String name {get;set;}
        public String category {get;set;}
        public Double percentage {get;set;}
    }
    
    public class Warnings {
    }
    
    
    public static JSON2Apex parse(String json) {
        return (JSON2Apex) System.JSON.deserialize(json, JSON2Apex.class);
    }
    
    
}

This is the visualforce page

<apex:page standardController="Contact" extensions="IBMWatsonPersonalTwitter" sidebar="false" showHeader="false">
    <head>
        
        https://code.jquery.com/jquery-2.2.0.min.js
        https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.17/d3.min.js
        https://unpkg.com/personality-sunburst-chart@2.0.4/dist/index.js
        https://d3js.org/d3-color.v1.min.js
        <link href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.5/css/bootstrap.min.css" rel="stylesheet" />
        <style>
            #profile pre {
            max-height: 400px;
            }
            #textSummary {
            font-size: 1.2em;
            }
        </style>
    </head>
    <body>
        
        <div class="container">
            <div class="row">
                <div class="col-sm-6 col-xs-12">
                    <div id="sunburstChart"></div>
                </div>
            </div>
        </div>
        
        <script>
        $(document).ready(function(){
            
            var chart = new PersonalitySunburstChart({
                'selector':'#sunburstChart',
                'version': 'v3'
            });
            
            // Render the sunburst chart for a personality profile (version as specified in creating the chart)
            // and optionally a profile photo.  The photo will be inserted into the center of the sunburst chart.
            chart.show({!jsonData});
        });
        </script>
        
    </body>
    
</apex:page>

You can find the complete code in this GitHub URL https://github.com/rajamohanvakati/Personality-Insights-