With MAKEPLUS you can
decode emotions in every interaction

// Initialize MAKEPLUS SDK
import { MakeplusClient } from '@makeplus/sdk';

const client = new MakeplusClient({
    apiKey: 'YOUR_API_KEY',
    region: 'us-west-2'
});

// Analyze voice stream in real-time
const voiceStream = await client.createVoiceStream();

voiceStream.on('emotion', (data) => {
    console.log('Detected emotions:', data.emotions);
    console.log('Confidence score:', data.confidence);
    console.log('Dominant emotion:', data.primary);
});

// Analyze video feed
const videoAnalysis = await client.analyzeVideo({
    source: videoElement,
    fps: 30,
    resolution: '720p'
});

videoAnalysis.on('frame', (result) => {
    updateEmotionDisplay(result.faces[0].emotions);
});

# Initialize MAKEPLUS SDK
from makeplus import Client
import asyncio

client = Client(
    api_key='YOUR_API_KEY',
    region='us-west-2'
)

# Analyze audio file for emotions
async def analyze_audio(file_path):
    result = await client.analyze_audio(
        file=file_path,
        model='advanced-v2',
        include_timeline=True
    )
    
    for segment in result.timeline:
        print(f"Time: {segment.start}s - {segment.end}s")
        print(f"Emotions: {segment.emotions}")
        print(f"Stress Level: {segment.stress_level}")

# Real-time stream processing
stream = client.create_stream()
await stream.connect()

async for emotion_data in stream:
    process_emotion(emotion_data)

// Initialize MAKEPLUS SDK
import com.makeplus.sdk.MakeplusClient;
import com.makeplus.sdk.models.*;

public class EmotionAnalyzer {
    private MakeplusClient client;
    
    public EmotionAnalyzer() {
        client = new MakeplusClient()
            .withApiKey("YOUR_API_KEY")
            .withRegion("us-west-2")
            .build();
    }
    
    // Analyze customer call
    public EmotionResult analyzeCall(AudioStream stream) {
        EmotionAnalysis analysis = client.createAnalysis()
            .withSource(stream)
            .withModel(Model.ADVANCED_V2)
            .withRealTime(true)
            .start();
        
        analysis.onEmotionDetected(emotion -> {
            System.out.println("Emotion: " + emotion.getType());
            System.out.println("Confidence: " + emotion.getConfidence());
        });
        
        return analysis.getResult();
    }
}

// Initialize MAKEPLUS SDK
using Makeplus.SDK;
using Makeplus.SDK.Models;

var client = new MakeplusClient(
    apiKey: "YOUR_API_KEY",
    region: "us-west-2"
);

// Analyze video conference
var videoAnalyzer = await client.CreateVideoAnalyzer();

videoAnalyzer.OnEmotionDetected += (sender, e) =>
{
    Console.WriteLine($"Participant {e.ParticipantId}");
    Console.WriteLine($"Emotions: {e.Emotions}");
    Console.WriteLine($"Engagement: {e.EngagementScore}");
};

// Batch process recordings
var batchResult = await client.BatchAnalyze(
    files: recordingFiles,
    options: new AnalysisOptions 
    {
        IncludeTranscript = true,
        GenerateReport = true,
        EmotionGranularity = Granularity.Detailed
    }
);