Einstein Sentiment Wrappers

EinsteinSentimentAction.cls

public with sharing class EinsteinSentimentAction {

    public class Request {
        @InvocableVariable
        public String recordId;
        @InvocableVariable
        public String document;
        @InvocableVariable
        public String modelId;
    }
    
    public class Prediction {
        @InvocableVariable
        public double positive;
        @InvocableVariable
        public double negative;
        @InvocableVariable
        public double neutral;
    }

    @InvocableMethod(label='Classify the given text and optionally updates the given record with the results.')
    public static List<EinsteinSentimentAction.Prediction> analyze(List<EinsteinSentimentAction.Request> requests) {
        // TODO: Bulkify!
        EinsteinSentimentAction.Request request = requests[0];
        // Switch to async? 
        if(!System.isQueueable() && request.recordId!=null) { // TODO: Maybe put this in the callers hands as a param?
            System.enqueueJob(new AsyncCallback(requests));
            return null;            
        }
        // Call Einstein API and update record (if provided)
		Sentiment.Prediction prediction = 
		  new Sentiment().getSentiment(
		      new VisionController().getAccessToken(), 
		      request.document, 
		      request.modelId);
        // Update record?
        if(request.recordId!=null) {
            Id recordToUpdateId = (Id) request.recordId;
            SObject recordToUpdate = recordToUpdateId.getSObjectType().newSObject(recordToUpdateId);
            recordToUpdate.put('SentimentPositive__c', prediction.positive);
            recordToUpdate.put('SentimentNegative__c', prediction.negative);
            recordToUpdate.put('SentimentNeutral__c', prediction.neutral);
            update recordToUpdate;
        }
        // Return prediction for Flow use cases
        EinsteinSentimentAction.Prediction response = new EinsteinSentimentAction.Prediction();
        response.positive = prediction.positive;
        response.negative = prediction.negative;
        response.neutral = prediction.neutral;                        		      
        return new List<EinsteinSentimentAction.Prediction> { response };
    }
    
    // Class re-enters above method in an async context
    public class AsyncCallback implements Queueable, Database.AllowsCallouts  {
        private List<EinsteinSentimentAction.Request> requests;        
        public AsyncCallback(List<EinsteinSentimentAction.Request> requests) {
            this.requests = requests;
        }                
        public void execute(QueueableContext context) {
            EinsteinSentimentAction.analyze(requests);
        }         
    } 
}

Sentiment.cls

public class Sentiment {
    
    public Prediction getSentiment(String token, String document, String modelId) {
        // Instantiate a new http object
        Http h = new Http();    
        // Instantiate a new HTTP request
        HttpRequest req = new HttpRequest();            
        // HTTP Header
        req.setEndpoint('https://api.einstein.ai/v2/language/sentiment');
        req.setHeader('Authorization', 'Bearer ' + token);
        req.setHeader('Cache-Control', 'no-cache');        
        req.setHeader('Connection', 'keep-alive');
        req.setHeader('Content-Type', HttpFormBuilder.GetContentType()); 
        // HTTP Body
        string form64 = '';
        form64 += HttpFormBuilder.WriteBoundary();
        form64 += HttpFormBuilder.WriteBodyParameter('modelId', EncodingUtil.urlEncode(modelId==null ? 'CommunitySentiment' : modelId, 'UTF-8'));
        form64 += HttpFormBuilder.WriteBoundary();
        form64 += HttpFormBuilder.WriteBodyParameter('document', document);
        form64 += HttpFormBuilder.WriteBoundary(HttpFormBuilder.EndingType.CrLf);
        blob formBlob = EncodingUtil.base64Decode(form64);
        string contentLength = string.valueOf(formBlob.size());
        req.setBodyAsBlob(formBlob);
        // HTTP Header
        req.setHeader('Content-Length', contentLength);                
        req.setMethod('POST');        
        // Send the request and parse response
        HttpResponse res = h.send(req); 
        if(res.getStatusCode() == 200) {
	        Response resp = (Response) JSON.deserializeStrict(res.getBody().replace('object', 'object_x'), Response.class);
	        Prediction prediction = new Prediction();
	        for(Probability prob : resp.probabilities) {
                if(prob.label.equals('positive')) {
                    prediction.positive = prob.probability;
                } else if(prob.label.equals('negative')) {
                    prediction.negative = prob.probability;
                } else if(prob.label.equals('neutral')) {
                    prediction.neutral = prob.probability;
                }               
	        }
	        return prediction;
        }        
        // TODO: Error handling
        return null;
    }
    
    public class Prediction {
        public double positive;
        public double negative;
        public double neutral;
    }
    
    public class Response {
         public List<Probability> probabilities;
         public String object_x;
    }
    
    public class Probability {
        public String label;
        public Double probability;
    }
}