Injecting Genesys Cloud Agent Assist Prompts with Java

What You Will Build

• A Java service that constructs, validates, and injects real-time agent assist prompts via the Genesys Cloud Agent Assist API.
• The service scores prompt relevance, delivers suggestions through a prioritized WebSocket queue, tracks engagement metrics, and generates structured audit logs.
• All code is written in Java 17+ using the official Genesys Cloud Java SDK and standard JRE networking libraries.

Prerequisites

• Genesys Cloud OAuth Client (Confidential type) with scopes: agentassist:prompt:create, interaction:read, analytics:read, notifications:register
• Genesys Cloud Java SDK genesyscloud-java-sdk v1.0.0+
• Java 17 or later
• External dependencies: javax.websocket-api v1.1, com.google.code.gson:gson v2.10.1
• Network access to api.mypurecloud.com and your WebSocket endpoint

Authentication Setup

Genesys Cloud requires OAuth 2.0 Client Credentials flow for service-to-service API access. The following code initializes the SDK client, fetches an access token, and implements token caching with automatic refresh.

import com.mypurecloud.sdk.v2.auth.ClientCredentialsFlow;
import com.mypurecloud.sdk.v2.auth.PureCloudAuth;
import com.mypurecloud.sdk.v2.client.PureCloudPlatformClientV2;
import com.mypurecloud.sdk.v2.api.OAuthApi;
import com.mypurecloud.sdk.v2.model.TokenResponse;

import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;

public class GenesysAuthManager {
    private static final String BASE_URL = "https://api.mypurecloud.com";
    private static final String CLIENT_ID = System.getenv("GENESYS_CLIENT_ID");
    private static final String CLIENT_SECRET = System.getenv("GENESYS_CLIENT_SECRET");
    private static final String[] SCOPES = {"agentassist:prompt:create", "interaction:read", "analytics:read"};

    private final PureCloudPlatformClientV2 client;
    private final OAuthApi oAuthApi;
    private final ConcurrentHashMap<String, String> tokenCache = new ConcurrentHashMap<>();
    private final AtomicLong tokenExpiry = new AtomicLong(0);

    public GenesysAuthManager() {
        this.client = PureCloudPlatformClientV2.defaultClient();
        this.client.setBasePath(BASE_URL);
        this.oAuthApi = new OAuthApi(client);
    }

    public PureCloudPlatformClientV2 getClient() {
        ensureValidToken();
        return client;
    }

    private void ensureValidToken() {
        long now = System.currentTimeMillis();
        if (tokenExpiry.get() > now) {
            return;
        }

        synchronized (this) {
            if (tokenExpiry.get() > now) {
                return;
            }
            try {
                ClientCredentialsFlow flow = new ClientCredentialsFlow(CLIENT_ID, CLIENT_SECRET, SCOPES);
                TokenResponse tokenResponse = oAuthApi.postOAuthTokenClientCredentials(
                    flow.getGrantType(),
                    flow.getScope(),
                    flow.getClientId(),
                    flow.getClientSecret()
                );
                
                String accessToken = tokenResponse.getAccessToken();
                long expiresIn = tokenResponse.getExpiresIn() * 1000;
                
                tokenCache.put("access_token", accessToken);
                tokenExpiry.set(now + expiresIn - 5000); // Refresh 5 seconds early
                client.getConfiguration().getOAuth().setAccessToken(accessToken);
            } catch (Exception e) {
                throw new RuntimeException("OAuth token acquisition failed", e);
            }
        }
    }
}

Implementation

Step 1: Constructing and Validating Prompt Injection Payloads

The Genesys Cloud Agent Assist API accepts prompt injection requests via POST /api/v2/agentassist/interactions/{interactionId}/prompts. You must construct a payload containing the knowledge base reference, query context, and trigger conditions. This step validates the payload against a simulated context window limit and enforces a response latency threshold before injection.

import com.mypurecloud.sdk.v2.api.AgentassistApi;
import com.mypurecloud.sdk.v2.model.AgentassistPrompt;
import com.mypurecloud.sdk.v2.model.AgentassistPromptResponse;
import com.mypurecloud.sdk.v2.client.PureCloudPlatformClientV2;

import java.time.Instant;
import java.util.List;
import java.util.Map;

public class PromptInjector {
    private final AgentassistApi agentassistApi;
    private static final int MAX_CONTEXT_TOKENS = 4096;
    private static final long MAX_LATENCY_MS = 800;

    public PromptInjector(PureCloudPlatformClientV2 client) {
        this.agentassistApi = new AgentassistApi(client);
    }

    public AgentassistPromptResponse injectPrompt(String interactionId, String query, String knowledgeBaseId, List<String> triggers) {
        long startTime = Instant.now().toEpochMilli();

        // Validate context window simulation (character count proxy for tokens)
        if (query.length() > MAX_CONTEXT_TOKENS) {
            throw new IllegalArgumentException("Query exceeds context window limit");
        }

        // Build payload
        AgentassistPrompt payload = new AgentassistPrompt();
        payload.setKnowledgeBaseId(knowledgeBaseId);
        payload.setQuery(query);
        payload.setTriggerConditions(triggers);
        payload.setMetadata(Map.of("source", "java-injector", "timestamp", Instant.now().toString()));

        try {
            AgentassistPromptResponse response = agentassistApi.createInteractionPrompt(interactionId, payload);
            long latency = Instant.now().toEpochMilli() - startTime;

            if (latency > MAX_LATENCY_MS) {
                // Log warning but proceed; Genesys Cloud accepts the prompt asynchronously
                System.out.printf("WARNING: Prompt injection latency %dms exceeds threshold %dms%n", latency, MAX_LATENCY_MS);
            }

            return response;
        } catch (Exception e) {
            throw new RuntimeException("Prompt injection failed for interaction: " + interactionId, e);
        }
    }
}

Step 2: Relevance Scoring and Confidence Threshold Filtering

Agent assist prompts must be ranked before delivery. This step implements cosine similarity for semantic scoring and applies a confidence threshold to filter low-value suggestions. The scoring function accepts embedding vectors and returns a normalized relevance score.

import java.util.List;
import java.util.stream.Collectors;

public class RelevanceScorer {
    private static final double CONFIDENCE_THRESHOLD = 0.75;

    public record ScoredPrompt(String promptId, String text, double score) {}

    public static List<ScoredPrompt> filterByConfidence(List<ScoredPrompt> candidates) {
        return candidates.stream()
                .filter(p -> p.score() >= CONFIDENCE_THRESHOLD)
                .sorted((a, b) -> Double.compare(b.score(), a.score()))
                .collect(Collectors.toList());
    }

    public static double cosineSimilarity(double[] vectorA, double[] vectorB) {
        if (vectorA.length != vectorB.length) {
            throw new IllegalArgumentException("Vector dimensions must match");
        }

        double dotProduct = 0.0;
        double magnitudeA = 0.0;
        double magnitudeB = 0.0;

        for (int i = 0; i < vectorA.length; i++) {
            dotProduct += vectorA[i] * vectorB[i];
            magnitudeA += vectorA[i] * vectorA[i];
            magnitudeB += vectorB[i] * vectorB[i];
        }

        double magProduct = Math.sqrt(magnitudeA) * Math.sqrt(magnitudeB);
        return (magProduct == 0.0) ? 0.0 : dotProduct / magProduct;
    }
}

Step 3: Priority Queuing and WebSocket Push Delivery

Real-time agent desktops require ordered prompt delivery. This step implements a PriorityBlockingQueue that orders prompts by relevance score and urgency. A WebSocket endpoint broadcasts queued prompts to connected agent sessions.

import javax.websocket.*;
import javax.websocket.server.ServerEndpoint;
import java.io.IOException;
import java.util.concurrent.*;

@ServerEndpoint("/ws/agent-assist")
public class AssistWebSocketEndpoint {
    private static final PriorityBlockingQueue<RelevanceScorer.ScoredPrompt> promptQueue = new PriorityBlockingQueue<>(
        (a, b) -> Double.compare(b.score(), a.score())
    );
    private static final ConcurrentHashMap<String, Session> connectedAgents = new ConcurrentHashMap<>();

    @OnOpen
    public void onOpen(Session session) {
        connectedAgents.put(session.getId(), session);
        System.out.println("Agent connected: " + session.getId());
    }

    @OnClose
    public void onClose(Session session) {
        connectedAgents.remove(session.getId());
        System.out.println("Agent disconnected: " + session.getId());
    }

    public static void enqueuePrompt(RelevanceScorer.ScoredPrompt prompt) {
        promptQueue.offer(prompt);
        deliverNextPrompt();
    }

    private static void deliverNextPrompt() {
        RelevanceScorer.ScoredPrompt prompt = promptQueue.poll();
        if (prompt == null) {
            return;
        }

        for (Session session : connectedAgents.values()) {
            try {
                if (session.isOpen()) {
                    session.getBasicRemote().sendText(prompt.text());
                }
            } catch (IOException e) {
                System.err.println("WebSocket delivery failed for session: " + session.getId());
            }
        }
    }
}

Step 4: Metrics Tracking, Webhook Sync, and Audit Logging

You must track retrieval latency, click-through rates, and synchronize engagement data with external training platforms. This step implements a metrics tracker, sends webhook callbacks to an external coaching system, and generates structured JSON audit logs.

import com.google.gson.Gson;
import com.google.gson.GsonBuilder;

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.*;
import java.util.concurrent.ConcurrentHashMap;

public class AssistMetricsManager {
    private final HttpClient httpClient;
    private final Gson gson;
    private final String trainingWebhookUrl;
    private final Map<String, List<Long>> latencyTracker = new ConcurrentHashMap<>();
    private final Map<String, Integer> clickThroughTracker = new ConcurrentHashMap<>();

    public AssistMetricsManager(String trainingWebhookUrl) {
        this.httpClient = HttpClient.newHttpClient();
        this.trainingWebhookUrl = trainingWebhookUrl;
        this.gson = new GsonBuilder().setPrettyPrinting().create();
    }

    public void recordLatency(String interactionId, long latencyMs) {
        latencyTracker.computeIfAbsent(interactionId, k -> new ArrayList<>()).add(latencyMs);
    }

    public void recordClick(String promptId) {
        clickThroughTracker.merge(promptId, 1, Integer::sum);
    }

    public void syncMetricsToTrainingPlatform(String agentId, Map<String, Object> metrics) {
        String payload = gson.toJson(Map.of(
            "event", "agent_assist_engagement",
            "agentId", agentId,
            "timestamp", Instant.now().toString(),
            "metrics", metrics
        ));

        HttpRequest request = HttpRequest.newBuilder()
                .uri(URI.create(trainingWebhookUrl))
                .header("Content-Type", "application/json")
                .POST(HttpRequest.BodyPublishers.ofString(payload))
                .build();

        try {
            HttpResponse<String> response = httpClient.send(request, HttpResponse.BodyHandlers.ofString());
            if (response.statusCode() != 200 && response.statusCode() != 204) {
                System.err.println("Webhook sync failed with status: " + response.statusCode());
            }
        } catch (Exception e) {
            System.err.println("Webhook delivery exception: " + e.getMessage());
        }
    }

    public String generateAuditLog(String interactionId, String promptId, String action, long latencyMs) {
        Map<String, Object> auditEntry = Map.of(
            "auditId", UUID.randomUUID().toString(),
            "interactionId", interactionId,
            "promptId", promptId,
            "action", action,
            "latencyMs", latencyMs,
            "timestamp", Instant.now().toString(),
            "system", "genesys-agent-assist-injector"
        );
        return gson.toJson(auditEntry);
    }
}

Complete Working Example

The following module combines authentication, payload construction, relevance scoring, WebSocket delivery, and metrics tracking into a single executable service. Replace environment variables with your Genesys Cloud credentials.

import com.mypurecloud.sdk.v2.client.PureCloudPlatformClientV2;

import java.util.List;
import java.util.Map;
import java.util.concurrent.*;

public class AgentAssistService {
    private final PromptInjector injector;
    private final AssistMetricsManager metricsManager;
    private final ScheduledExecutorService scheduler = Executors.newScheduledThreadPool(2);

    public AgentAssistService(String trainingWebhookUrl) {
        GenesysAuthManager authManager = new GenesysAuthManager();
        PureCloudPlatformClientV2 client = authManager.getClient();
        
        this.injector = new PromptInjector(client);
        this.metricsManager = new AssistMetricsManager(trainingWebhookUrl);
    }

    public void processInteraction(String interactionId, String agentQuery, String knowledgeBaseId, List<String> triggers) {
        try {
            // 1. Inject prompt via Genesys Cloud API
            var response = injector.injectPrompt(interactionId, agentQuery, knowledgeBaseId, triggers);
            String promptId = response.getId();
            long latency = response.getCreatedAt() != null ? 
                System.currentTimeMillis() - response.getCreatedAt().toInstant().toEpochMilli() : 0;

            // 2. Simulate semantic scoring (replace with actual embedding service in production)
            double[] queryVector = new double[]{0.8, 0.1, 0.3};
            double[] kbVector = new double[]{0.7, 0.2, 0.4};
            double score = RelevanceScorer.cosineSimilarity(queryVector, kbVector);
            
            var scoredPrompt = new RelevanceScorer.ScoredPrompt(promptId, response.getQuery(), score);
            List<RelevanceScorer.ScoredPrompt> filtered = RelevanceScorer.filterByConfidence(List.of(scoredPrompt));

            // 3. Deliver via WebSocket priority queue
            if (!filtered.isEmpty()) {
                AssistWebSocketEndpoint.enqueuePrompt(filtered.get(0));
            }

            // 4. Record metrics and audit
            metricsManager.recordLatency(interactionId, latency);
            String auditLog = metricsManager.generateAuditLog(interactionId, promptId, "INJECT", latency);
            System.out.println("AUDIT: " + auditLog);

            // 5. Schedule webhook sync for training platform
            scheduler.schedule(() -> {
                metricsManager.syncMetricsToTrainingPlatform(
                    "AGENT_" + interactionId.substring(0, 8),
                    Map.of("latencyMs", latency, "score", score, "promptId", promptId)
                );
            }, 2, TimeUnit.SECONDS);

        } catch (Exception e) {
            System.err.println("Processing failed for interaction: " + interactionId + " | Error: " + e.getMessage());
        }
    }

    public static void main(String[] args) {
        if (System.getenv("GENESYS_CLIENT_ID") == null || System.getenv("GENESYS_CLIENT_SECRET") == null) {
            System.err.println("Missing GENESYS_CLIENT_ID or GENESYS_CLIENT_SECRET environment variables");
            System.exit(1);
        }

        AgentAssistService service = new AgentAssistService("https://training-platform.example.com/webhooks/assist-metrics");
        
        // Simulate incoming interaction
        service.processInteraction(
            "INTERACTION-ABC-123",
            "How do I reset a customer's temporary access code?",
            "KB-ENTERPRISE-001",
            List.of("auth_failure", "password_reset")
        );
    }
}

Common Errors & Debugging

Error: HTTP 401 Unauthorized

• Cause: OAuth token expired, missing scopes, or incorrect client credentials.
• Fix: Verify GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET. Ensure the OAuth client has agentassist:prompt:create assigned. The GenesysAuthManager automatically refreshes tokens, but network timeouts during refresh will cause 401 responses. Add retry logic with exponential backoff.
• Code Fix: Wrap API calls in a retry loop that catches 401 and triggers ensureValidToken().

Error: HTTP 403 Forbidden

• Cause: The OAuth client lacks required scopes or the interaction ID belongs to a different Genesys Cloud organization.
• Fix: Confirm the client has agentassist:prompt:create and interaction:read. Verify the interactionId matches the authenticated tenant.

Error: HTTP 429 Too Many Requests

• Cause: Rate limit exceeded on the Agent Assist API endpoint. Genesys Cloud enforces per-client and per-tenant limits.
• Fix: Implement exponential backoff with jitter. The following snippet demonstrates retry logic for 429 responses.

private <T> T executeWithRetry(Runnable action, int maxRetries) throws Exception {
    int attempt = 0;
    while (attempt < maxRetries) {
        try {
            action.run();
            return null;
        } catch (Exception e) {
            attempt++;
            if (attempt >= maxRetries || !e.getMessage().contains("429")) {
                throw e;
            }
            long delay = (long) Math.pow(2, attempt) * 1000 + ThreadLocalRandom.current().nextInt(500);
            Thread.sleep(delay);
        }
    }
    throw new RuntimeException("Max retries exceeded for 429");
}

Error: HTTP 400 Bad Request

• Cause: Payload schema mismatch, missing required fields, or context window exceeded.
• Fix: Validate query length against MAX_CONTEXT_TOKENS. Ensure knowledgeBaseId exists and is accessible. Check trigger conditions against allowed values in your Genesys Cloud instance.

Error: WebSocket Connection Refused

• Cause: Agent desktop client not running, firewall blocking port, or incorrect endpoint path.
• Fix: Verify the WebSocket server is deployed and accessible. Ensure the agent desktop registers to /ws/agent-assist. Check server logs for handshake failures.

Official References

• Genesys Cloud Agent Assist API Documentation
• Genesys Cloud Java SDK Reference
• Genesys Cloud OAuth 2.0 Client Credentials Flow
• Genesys Cloud Notifications and Webhook Configuration