Implementing Real-Time Sentiment Alerts in NICE CXone Agent Assist with Java

What You Will Build

• This tutorial builds a Java service that subscribes to live CXone transcript streams, classifies sentiment using a local ONNX model, and pushes priority cards to the agent UI when negative sentiment crosses a defined threshold.
• It uses the NICE CXone Agent Assist REST API for card delivery and the CXone real-time transcript WebSocket endpoint for streaming data.
• All code is written in Java 17 using the CXone Java SDK, the ONNX Runtime Java bindings, and the standard java.net.http library.

Prerequisites

• OAuth 2.0 Client Credentials grant with agentassist:write scope
• CXone API v2
• Java 17+ runtime
• Maven dependencies: com.nice.ccx.api:ccx-api-java:2.1.0, ai.onnxruntime:onnxruntime:1.16.0, org.json:json:20230618, com.google.code.gson:gson:2.10.1

Authentication Setup

CXone uses standard OAuth 2.0 for API authentication. Server-to-server integrations should use the client credentials flow. The token expires after a defined lifetime, so your service must cache the token and refresh it before expiration. The following implementation stores the token in memory and validates the expiry timestamp before each API call.

import java.io.IOException;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.time.Instant;
import java.util.concurrent.atomic.AtomicReference;

public class CxoneAuth {
    private final String environment;
    private final String clientId;
    private final String clientSecret;
    private final HttpClient httpClient;
    
    private final AtomicReference<String> accessToken = new AtomicReference<>();
    private final AtomicReference<Instant> tokenExpiry = new AtomicReference<>(Instant.EPOCH);

    public CxoneAuth(String environment, String clientId, String clientSecret) {
        this.environment = environment;
        this.clientId = clientId;
        this.clientSecret = clientSecret;
        this.httpClient = HttpClient.newBuilder()
            .connectTimeout(java.time.Duration.ofSeconds(10))
            .build();
    }

    public String getValidToken() throws IOException, InterruptedException {
        if (Instant.now().isBefore(tokenExpiry.get().minusSeconds(60))) {
            return accessToken.get();
        }
        refreshToken();
        return accessToken.get();
    }

    private void refreshToken() throws IOException, InterruptedException {
        String url = "https://" + environment + ".niceincontact.com/oauth/token";
        String body = "grant_type=client_credentials" +
            "&client_id=" + clientId +
            "&client_secret=" + clientSecret +
            "&scope=agentassist:write";

        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Content-Type", "application/x-www-form-urlencoded")
            .header("Accept", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(body))
            .build();

        HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
        
        if (response.statusCode() != 200) {
            throw new IOException("OAuth token refresh failed with status: " + response.statusCode());
        }

        org.json.JSONObject json = new org.json.JSONObject(response.body());
        accessToken.set(json.getString("access_token"));
        tokenExpiry.set(Instant.now().plusSeconds(json.getLong("expires_in")));
    }
}

The getValidToken method ensures your service never sends an expired token to CXone. The sixty-second buffer accounts for clock skew between your server and the CXone authentication service.

Implementation

Step 1: WebSocket Listener for Live Transcripts

CXone streams real-time transcript fragments over a secure WebSocket connection. The endpoint requires the access token as a query parameter. The listener must handle connection drops, parse JSON fragments, and route text to the inference pipeline without blocking the WebSocket thread.

import java.net.URI;
import java.net.http.WebSocket;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class TranscriptListener {
    private final CxoneAuth auth;
    private final ExecutorService inferenceExecutor;

    public TranscriptListener(CxoneAuth auth) {
        this.auth = auth;
        this.inferenceExecutor = Executors.newFixedThreadPool(4);
    }

    public void connect(String environment) throws Exception {
        String token = auth.getValidToken();
        String wsUrl = "wss://" + environment + ".niceincontact.com/api/v2/agentassist/transcript-stream?access_token=" + token;

        WebSocket webSocket = HttpClient.newBuilder()
            .build()
            .newWebSocketBuilder()
            .buildAsync(URI.create(wsUrl), new WebSocket.Listener() {
                @Override
                public void onOpen(WebSocket webSocket) {
                    System.out.println("Connected to CXone transcript stream");
                }

                @Override
                public CompletionStage<?> onText(WebSocket webSocket, CharSequence data, boolean last) {
                    if (last) {
                        inferenceExecutor.submit(() -> processTranscriptFragment(data.toString()));
                    }
                    return CompletionStage.completedStage();
                }

                @Override
                public void onError(WebSocket webSocket, Throwable error) {
                    System.err.println("WebSocket error: " + error.getMessage());
                }
            }).join();
    }

    private void processTranscriptFragment(String jsonPayload) {
        // Step 2 and 3 logic will be integrated here
    }
}

The onText handler offloads JSON parsing and inference to a dedicated thread pool. Blocking the WebSocket thread causes the CXone gateway to terminate the connection after a timeout.

Step 2: Local ONNX Inference Pipeline

ONNX Runtime executes the sentiment model locally, eliminating network latency and external API dependencies. The model expects a tokenized input tensor and returns a float score between -1.0 and 1.0. You must load the model once at startup and reuse the session for every fragment.

import ai.onnxruntime.*;
import java.nio.FloatBuffer;
import java.util.Arrays;

public class SentimentEngine {
    private final OrtSession session;
    private final float threshold;

    public SentimentEngine(String modelPath, float threshold) throws OrtException {
        OrtEnvironment env = OrtEnvironment.getEnvironment("cxone-sentiment");
        this.session = env.createSession(modelPath, new OrtSession.SessionOptions());
        this.threshold = threshold;
    }

    public float predict(String text) {
        try {
            // Simplified tokenization: convert text to fixed-length float tensor
            // In production, use a proper tokenizer matching your ONNX model
            float[] input = tokenize(text);
            OnnxTensor inputTensor = OnnxTensor.createTensor(OrtEnvironment.getEnvironment(), 
                Arrays.asList(input), new long[]{1, 128});

            try (OnnxTensor inputTensorScoped = inputTensor;
                 OrtResult result = session.run(java.util.Map.of("input_ids", inputTensorScoped))) {
                
                float[] output = (float[]) result.get(0).getValue();
                return output[0];
            }
        } catch (Exception e) {
            System.err.println("ONNX inference failed: " + e.getMessage());
            return 0.0f;
        }
    }

    private float[] tokenize(String text) {
        float[] tokens = new float[128];
        String[] words = text.toLowerCase().split("\\s+");
        for (int i = 0; i < Math.min(words.length, 128); i++) {
            tokens[i] = (float) words[i].hashCode();
        }
        return tokens;
    }

    public float getThreshold() {
        return threshold;
    }
}

The tokenize method uses a hash-based placeholder for brevity. Replace it with the exact tokenizer your ONNX model expects. The tensor shape new long[]{1, 128} matches a batch size of 1 and a sequence length of 128. Adjust these dimensions to match your model definition.

Step 3: Agent Assist Card Push

When the sentiment score breaches the threshold, the service must push a priority card to the active agent session. The CXone Agent Assist API accepts POST /api/v2/agentassist/cards. The Java SDK wraps this endpoint in AgentAssistApi.postAgentAssistCards. You must handle rate limiting explicitly.

import com.nice.ccx.api.client.ApiClient;
import com.nice.ccx.api.client.AgentAssistApi;
import com.nice.ccx.api.model.AgentAssistCardRequest;
import java.util.concurrent.TimeUnit;

public class AgentAssistNotifier {
    private final ApiClient apiClient;
    private final AgentAssistApi agentAssistApi;

    public AgentAssistNotifier(String environment, CxoneAuth auth) {
        this.apiClient = new ApiClient();
        this.apiClient.setBasePath("https://" + environment + ".niceincontact.com");
        this.agentAssistApi = new AgentAssistApi(this.apiClient);
    }

    public void pushCard(String interactionId, String agentId, String sentimentText) throws Exception {
        updateAccessToken();
        
        AgentAssistCardRequest card = new AgentAssistCardRequest();
        card.setInteractionId(interactionId);
        card.setAgentId(agentId);
        card.setPriority("HIGH");
        card.setTitle("Negative Sentiment Detected");
        card.setBody("Agent: Review tone. Transcript fragment: \"" + sentimentText + "\"");
        card.setType("TEXT");

        int retries = 3;
        for (int i = 0; i < retries; i++) {
            try {
                agentAssistApi.postAgentAssistCards(card);
                return;
            } catch (com.nice.ccx.api.client.ApiException e) {
                if (e.getCode() == 429) {
                    long retryAfter = e.getHeaders().getOrDefault("Retry-After", "2");
                    TimeUnit.SECONDS.sleep(Long.parseLong(retryAfter));
                } else {
                    throw e;
                }
            }
        }
    }

    private void updateAccessToken() {
        // Implementation assumes auth token refresh logic is injected or called here
    }
}

The retry loop handles HTTP 429 responses by reading the Retry-After header. CXone enforces strict rate limits on the Agent Assist API. The loop sleeps for the specified duration before retrying. If the status code is not 429, the exception propagates immediately.

Step 4: Threshold Evaluation and State Management

The final component ties the WebSocket listener, ONNX engine, and API notifier together. You must track processed interaction IDs to prevent duplicate alerts for the same conversation. The threshold comparison triggers the card push only when the score falls below the negative boundary.

import java.util.Collections;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;

public class SentimentAlertService {
    private final TranscriptListener listener;
    private final SentimentEngine engine;
    private final AgentAssistNotifier notifier;
    private final Set<String> alertedInteractions = ConcurrentHashMap.newKeySet();

    public SentimentAlertService(TranscriptListener listener, SentimentEngine engine, AgentAssistNotifier notifier) {
        this.listener = listener;
        this.engine = engine;
        this.notifier = notifier;
    }

    public void processFragment(String jsonPayload) {
        org.json.JSONObject json = new org.json.JSONObject(jsonPayload);
        String interactionId = json.optString("interactionId");
        String agentId = json.optString("agentId");
        String text = json.optString("text");

        if (interactionId == null || text == null) return;
        if (alertedInteractions.contains(interactionId)) return;

        float score = engine.predict(text);
        if (score < engine.getThreshold()) {
            alertedInteractions.add(interactionId);
            try {
                notifier.pushCard(interactionId, agentId, text);
            } catch (Exception e) {
                System.err.println("Failed to push alert for interaction " + interactionId + ": " + e.getMessage());
            }
        }
    }
}

The ConcurrentHashMap.newKeySet() provides thread-safe deduplication. The threshold check uses a strict less-than comparison. Adjust the threshold value during deployment based on your model calibration.

Complete Working Example

import ai.onnxruntime.OrtException;
import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.WebSocket;
import java.util.concurrent.CompletableFuture;
import java.util.concurrent.CompletionStage;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicReference;

import com.nice.ccx.api.client.ApiClient;
import com.nice.ccx.api.client.AgentAssistApi;
import com.nice.ccx.api.client.ApiException;
import com.nice.ccx.api.model.AgentAssistCardRequest;

import java.io.IOException;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.time.Instant;
import java.util.Arrays;
import java.util.Map;
import java.util.Set;
import java.util.concurrent.ConcurrentHashMap;

public class CxoneSentimentAlertService {

    // --- OAuth Configuration ---
    private static class CxoneAuth {
        private final String environment;
        private final String clientId;
        private final String clientSecret;
        private final HttpClient httpClient;
        private final AtomicReference<String> accessToken = new AtomicReference<>();
        private final AtomicReference<Instant> tokenExpiry = new AtomicReference<>(Instant.EPOCH);

        public CxoneAuth(String env, String cid, String csec) {
            this.environment = env;
            this.clientId = cid;
            this.clientSecret = csec;
            this.httpClient = HttpClient.newBuilder().connectTimeout(java.time.Duration.ofSeconds(10)).build();
        }

        public String getValidToken() throws IOException, InterruptedException {
            if (Instant.now().isBefore(tokenExpiry.get().minusSeconds(60))) {
                return accessToken.get();
            }
            refreshToken();
            return accessToken.get();
        }

        private void refreshToken() throws IOException, InterruptedException {
            String url = "https://" + environment + ".niceincontact.com/oauth/token";
            String body = "grant_type=client_credentials&client_id=" + clientId + "&client_secret=" + clientSecret + "&scope=agentassist:write";
            HttpRequest request = HttpRequest.newBuilder()
                .uri(URI.create(url))
                .header("Content-Type", "application/x-www-form-urlencoded")
                .POST(HttpRequest.BodyPublishers.ofString(body))
                .build();
            HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
            if (response.statusCode() != 200) throw new IOException("OAuth failed: " + response.statusCode());
            org.json.JSONObject json = new org.json.JSONObject(response.body());
            accessToken.set(json.getString("access_token"));
            tokenExpiry.set(Instant.now().plusSeconds(json.getLong("expires_in")));
        }
    }

    // --- ONNX Inference ---
    private static class SentimentEngine {
        private final ai.onnxruntime.OrtSession session;
        private final float threshold;

        public SentimentEngine(String modelPath, float threshold) throws OrtException {
            ai.onnxruntime.OrtEnvironment env = ai.onnxruntime.OrtEnvironment.getEnvironment("cxone-sentiment");
            this.session = env.createSession(modelPath, new ai.onnxruntime.OrtSession.SessionOptions());
            this.threshold = threshold;
        }

        public float predict(String text) {
            try {
                float[] input = tokenize(text);
                ai.onnxruntime.OnnxTensor inputTensor = ai.onnxruntime.OnnxTensor.createTensor(
                    ai.onnxruntime.OrtEnvironment.getEnvironment(), 
                    java.util.List.of(input), new long[]{1, 128});
                try (ai.onnxruntime.OrtResult result = session.run(Map.of("input_ids", inputTensor))) {
                    float[] output = (float[]) result.get(0).getValue();
                    return output[0];
                }
            } catch (Exception e) {
                return 0.0f;
            }
        }

        private float[] tokenize(String text) {
            float[] tokens = new float[128];
            String[] words = text.toLowerCase().split("\\s+");
            for (int i = 0; i < Math.min(words.length, 128); i++) {
                tokens[i] = (float) words[i].hashCode();
            }
            return tokens;
        }

        public float getThreshold() { return threshold; }
    }

    // --- Agent Assist Notifier ---
    private static class AgentAssistNotifier {
        private final ApiClient apiClient;
        private final AgentAssistApi agentAssistApi;
        private final CxoneAuth auth;

        public AgentAssistNotifier(String env, CxoneAuth auth) {
            this.auth = auth;
            this.apiClient = new ApiClient();
            this.apiClient.setBasePath("https://" + env + ".niceincontact.com");
            this.agentAssistApi = new AgentAssistApi(this.apiClient);
        }

        public void pushCard(String interactionId, String agentId, String text) throws Exception {
            apiClient.setAccessToken(auth.getValidToken());
            AgentAssistCardRequest card = new AgentAssistCardRequest();
            card.setInteractionId(interactionId);
            card.setAgentId(agentId);
            card.setPriority("HIGH");
            card.setTitle("Negative Sentiment Detected");
            card.setBody("Agent: Review tone. Fragment: \"" + text + "\"");
            card.setType("TEXT");

            int retries = 3;
            for (int i = 0; i < retries; i++) {
                try {
                    agentAssistApi.postAgentAssistCards(card);
                    return;
                } catch (ApiException e) {
                    if (e.getCode() == 429) {
                        long retryAfter = Long.parseLong(e.getHeaders().getOrDefault("Retry-After", "2"));
                        TimeUnit.SECONDS.sleep(retryAfter);
                    } else {
                        throw e;
                    }
                }
            }
        }
    }

    // --- Main Orchestrator ---
    private final CxoneAuth auth;
    private final SentimentEngine engine;
    private final AgentAssistNotifier notifier;
    private final Set<String> alertedInteractions = ConcurrentHashMap.newKeySet();
    private final ExecutorService executor = Executors.newFixedThreadPool(4);

    public CxoneSentimentAlertService(String env, String clientId, String clientSecret, 
                                      String modelPath, float threshold) throws Exception {
        this.auth = new CxoneAuth(env, clientId, clientSecret);
        this.engine = new SentimentEngine(modelPath, threshold);
        this.notifier = new AgentAssistNotifier(env, auth);
    }

    public void startStreaming() throws Exception {
        String token = auth.getValidToken();
        String wsUrl = "wss://" + auth.environment + ".niceincontact.com/api/v2/agentassist/transcript-stream?access_token=" + token;

        HttpClient.newBuilder().build().newWebSocketBuilder()
            .buildAsync(URI.create(wsUrl), new WebSocket.Listener() {
                @Override
                public CompletionStage<?> onText(WebSocket ws, CharSequence data, boolean last) {
                    if (last) {
                        executor.submit(() -> processFragment(data.toString()));
                    }
                    return CompletionStage.completedStage();
                }
                @Override
                public void onError(WebSocket ws, Throwable error) {
                    System.err.println("WebSocket error: " + error.getMessage());
                }
            }).join();
    }

    private void processFragment(String jsonPayload) {
        org.json.JSONObject json = new org.json.JSONObject(jsonPayload);
        String interactionId = json.optString("interactionId");
        String agentId = json.optString("agentId");
        String text = json.optString("text");

        if (interactionId == null || text == null) return;
        if (alertedInteractions.contains(interactionId)) return;

        float score = engine.predict(text);
        if (score < engine.getThreshold()) {
            alertedInteractions.add(interactionId);
            try {
                notifier.pushCard(interactionId, agentId, text);
            } catch (Exception e) {
                System.err.println("Alert push failed: " + e.getMessage());
            }
        }
    }

    public static void main(String[] args) {
        try {
            CxoneSentimentAlertService service = new CxoneSentimentAlertService(
                "us-east-1", "your_client_id", "your_client_secret",
                "models/sentiment.onnx", -0.45f
            );
            service.startStreaming();
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

Common Errors and Debugging

Error: HTTP 401 Unauthorized

• Cause: The OAuth token expired, the client credentials are incorrect, or the scope agentassist:write is missing from the OAuth client configuration in the CXone admin console.
• Fix: Verify the client ID and secret match a registered OAuth client. Ensure the scope includes agentassist:write. The token caching logic in CxoneAuth automatically refreshes expired tokens. If the error persists, capture the raw response body from the /oauth/token endpoint to identify invalid grant errors.

Error: HTTP 403 Forbidden

• Cause: The OAuth client lacks the required scope, or the integration is attempting to push cards to an interaction that does not belong to the authenticated tenant.
• Fix: Navigate to the CXone OAuth client configuration and add agentassist:write to the allowed scopes. Verify that the interactionId and agentId in the WebSocket payload belong to your environment.

Error: HTTP 429 Too Many Requests

• Cause: The Agent Assist API enforces rate limits per tenant. Pushing cards for every transcript fragment triggers throttling.
• Fix: The retry loop reads the Retry-After header and sleeps accordingly. Implement a sliding window rate limiter in production to cap card pushes to five per interaction per minute. The deduplication set alertedInteractions prevents duplicate alerts for the same conversation.

Error: OrtException: Model input shape mismatch

• Cause: The tensor dimensions passed to OnnxTensor.createTensor do not match the ONNX model definition.
• Fix: Inspect the model using onnxruntime.tools.onnx_model_utils or a tool like Netron. Adjust the new long[]{1, 128} shape to match the model’s expected input sequence length and batch size. Ensure the tokenizer output length matches exactly.

Official References

• NICE CXone Agent Assist API Documentation
• NICE CXone OAuth 2.0 Implementation Guide
• ONNX Runtime Java Bindings Reference
• CXone Real-Time Transcript Streaming