Injecting Genesys Cloud Agent Assist Manual Suggestions via Java SDK

What You Will Build

• A production-ready Java utility that programmatically injects custom suggestions into active Genesys Cloud Agent Assist sessions.
• This implementation uses the Genesys Cloud Agent Assist API (POST /api/v2/agentassist/sessions/{sessionId}/suggestions) and the official Java SDK.
• The code is written in Java 17+ using the mypurecloud.api.client SDK, java.net.http.HttpClient, and structured logging for audit compliance.

Prerequisites

• OAuth Client: Confidential client with agentassist:inject:suggestion, agentassist:read, and user:read scopes.
• SDK: com.mypurecloud.api.client:client version 110.0.0 or later.
• Runtime: Java 17+ with standard library modules.
• External Dependencies: com.fasterxml.jackson.core:jackson-databind, org.slf4j:slf4j-api, com.google.guava:guava (for retry utilities).

Authentication Setup

Genesys Cloud requires OAuth 2.0 Client Credentials flow for server-to-server API calls. The Java SDK provides a built-in ClientCredentialsProvider that handles initial token acquisition and automatic refresh before expiration. You must configure the ApiClient instance with your environment base URL, client ID, client secret, and required scopes.

import com.mypurecloud.api.client.ApiClient;
import com.mypurecloud.api.client.auth.oauth.ClientCredentialsProvider;
import com.mypurecloud.api.client.AgentassistApi;
import com.mypurecloud.api.client.UsersApi;
import java.util.Set;

public class GenesysAuthSetup {
    public static AgentassistApi buildAgentassistApi(String clientId, String clientSecret, String environmentUrl) throws Exception {
        ApiClient apiClient = new ApiClient();
        apiClient.setBasePath(environmentUrl);
        
        ClientCredentialsProvider credentialsProvider = new ClientCredentialsProvider(
                apiClient,
                clientId,
                clientSecret,
                Set.of("agentassist:inject:suggestion", "agentassist:read", "user:read")
        );
        
        apiClient.setAuth(credentialsProvider);
        return new AgentassistApi(apiClient);
    }

    public static UsersApi buildUsersApi(String clientId, String clientSecret, String environmentUrl) throws Exception {
        ApiClient apiClient = new ApiClient();
        apiClient.setBasePath(environmentUrl);
        
        ClientCredentialsProvider credentialsProvider = new ClientCredentialsProvider(
                apiClient,
                clientId,
                clientSecret,
                Set.of("user:read")
        );
        
        apiClient.setAuth(credentialsProvider);
        return new UsersApi(apiClient);
    }
}

OAuth Scope Requirement: agentassist:inject:suggestion is mandatory for the injection endpoint. The SDK will throw a 401 Unauthorized exception if the scope is missing or expired. The ClientCredentialsProvider automatically calls /api/v2/oauth/token when the access token nears expiration.

Implementation

Step 1: Session Validation & Agent Role Checking

Before injecting suggestions, you must verify that the target session belongs to an authorized agent. Genesys Cloud restricts manual injection to active sessions associated with users holding specific roles. This step retrieves the current user context and validates role membership using the Users API.

import com.mypurecloud.api.client.ApiException;
import com.mypurecloud.api.client.model.User;
import com.mypurecloud.api.client.model.UserRoles;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;

public class RoleValidator {
    private final UsersApi usersApi;

    public RoleValidator(UsersApi usersApi) {
        this.usersApi = usersApi;
    }

    public boolean isAuthorizedInjector(String userId) throws ApiException {
        User user = usersApi.getUsersUser(userId);
        UserRoles roles = user.getRoles();
        if (roles == null) {
            return false;
        }

        List<String> roleNames = roles.getRoles().stream()
                .map(r -> r.getName())
                .collect(Collectors.toList());

        Set<String> authorizedRoles = Set.of("Agent", "Supervisor", "Admin", "AgentAssistAdmin");
        return roleNames.stream().anyMatch(authorizedRoles::contains);
    }
}

Endpoint Used: GET /api/v2/users/{userId}
Required Scope: user:read
Error Handling: The SDK throws ApiException with HTTP status codes. A 404 indicates an invalid user ID. A 403 indicates missing user:read scope. The code catches and wraps these exceptions for upstream handling.

Step 2: Payload Construction & Schema Validation

The injection payload must conform to the assist engine constraints. Genesys Cloud enforces a maximum of 50 suggestions per inject request. Each suggestion requires a valid title, description, URI, category, and priority directive. This step validates the input matrix against engine limits and constructs the SDK model objects.

import com.mypurecloud.api.client.model.Suggestion;
import com.mypurecloud.api.client.model.InjectSuggestionsRequest;
import com.fasterxml.jackson.databind.ObjectMapper;
import java.net.URI;
import java.util.ArrayList;
import java.util.List;
import java.util.regex.Pattern;

public class SuggestionPayloadBuilder {
    private static final int MAX_SUGGESTIONS = 50;
    private static final Pattern URI_PATTERN = Pattern.compile("^https?://");
    private static final Set<String> VALID_PRIORITIES = Set.of("low", "medium", "high");
    private final ObjectMapper mapper = new ObjectMapper();

    public InjectSuggestionsRequest buildPayload(List<SuggestionInput> inputs) throws IllegalArgumentException {
        if (inputs.size() > MAX_SUGGESTIONS) {
            throw new IllegalArgumentException("Suggestion count exceeds engine limit of " + MAX_SUGGESTIONS);
        }

        List<Suggestion> suggestions = new ArrayList<>();
        for (SuggestionInput input : inputs) {
            if (!URI_PATTERN.matcher(input.getUri()).matches()) {
                throw new IllegalArgumentException("Invalid URI format: " + input.getUri());
            }
            if (!VALID_PRIORITIES.contains(input.getPriority())) {
                throw new IllegalArgumentException("Invalid priority directive: " + input.getPriority());
            }

            Suggestion suggestion = new Suggestion();
            suggestion.setTitle(input.getTitle());
            suggestion.setDescription(input.getDescription());
            suggestion.setUri(input.getUri());
            suggestion.setCategory(input.getCategory());
            suggestion.setPriority(input.getPriority());
            suggestion.setSource("ManualInjection");
            suggestions.add(suggestion);
        }

        InjectSuggestionsRequest request = new InjectSuggestionsRequest();
        request.setSuggestions(suggestions);
        return request;
    }

    // Record class for input matrix
    public record SuggestionInput(String title, String description, String uri, String category, String priority) {}
}

Schema Constraints: The assist engine rejects payloads exceeding 50 items. Invalid URIs or unsupported priority values cause a 400 Bad Request. The builder enforces these rules before SDK serialization.

Step 3: Content Policy Verification Pipeline

Before injection, you must filter content against organizational policies to prevent information overload or compliance violations. This pipeline checks for blocked keywords, enforces category whitelisting, and verifies that the suggestion content aligns with the current assist context.

import java.util.List;
import java.util.Set;
import java.util.regex.Pattern;
import java.util.stream.Collectors;

public class ContentPolicyPipeline {
    private final Set<String> blockedKeywords;
    private final Set<String> allowedCategories;
    private final Pattern sensitiveDataPattern;

    public ContentPolicyPipeline(Set<String> blockedKeywords, Set<String> allowedCategories) {
        this.blockedKeywords = blockedKeywords;
        this.allowedCategories = allowedCategories;
        this.sensitiveDataPattern = Pattern.compile("\\b\\d{3}-\\d{2}-\\d{4}\\b|\\b\\d{16}\\b"); // SSN or Card patterns
    }

    public List<SuggestionPayloadBuilder.SuggestionInput> validateAndFilter(List<SuggestionPayloadBuilder.SuggestionInput> inputs) {
        return inputs.stream().filter(input -> {
            if (!allowedCategories.contains(input.category())) {
                return false;
            }
            String content = input.title() + " " + input.description();
            boolean containsBlocked = blockedKeywords.stream().anyMatch(content::contains);
            boolean containsSensitive = sensitiveDataPattern.matcher(content).find();
            return !containsBlocked && !containsSensitive;
        }).collect(Collectors.toList());
    }
}

Policy Enforcement: The pipeline runs synchronously before API submission. It filters out non-compliant items and returns a clean matrix. Empty results after filtering trigger an early exit to prevent unnecessary API calls.

Step 4: Atomic POST Injection with Latency Tracking & 429 Retry

The injection occurs via a single atomic POST operation. This step wraps the SDK call with latency measurement, exponential backoff for rate limits, and structured audit logging. The Genesys Cloud API returns a 200 OK with an InjectSuggestionsResponse containing the injected suggestion IDs.

import com.mypurecloud.api.client.AgentassistApi;
import com.mypurecloud.api.client.ApiException;
import com.mypurecloud.api.client.model.InjectSuggestionsResponse;
import com.google.common.util.concurrent.RateLimiter;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.time.Instant;
import java.util.concurrent.TimeUnit;

public class InjectionExecutor {
    private static final Logger log = LoggerFactory.getLogger(InjectionExecutor.class);
    private final AgentassistApi api;
    private final int maxRetries = 3;

    public InjectionExecutor(AgentassistApi api) {
        this.api = api;
    }

    public InjectSuggestionsResponse execute(String sessionId, InjectSuggestionsRequest request) throws Exception {
        Instant start = Instant.now();
        int attempt = 0;
        ApiException lastException = null;

        while (attempt < maxRetries) {
            try {
                InjectSuggestionsResponse response = api.postAgentassistSessionsSessionIdSuggestions(sessionId, request);
                
                long latencyMs = java.time.Duration.between(start, Instant.now()).toMillis();
                logAuditSuccess(sessionId, request.getSuggestions().size(), latencyMs, response);
                return response;
            } catch (ApiException e) {
                lastException = e;
                if (e.getCode() == 429 && attempt < maxRetries - 1) {
                    long waitMs = (long) Math.pow(2, attempt) * 1000;
                    log.warn("Rate limited (429). Retrying in {} ms...", waitMs);
                    Thread.sleep(waitMs);
                    attempt++;
                } else {
                    logAuditFailure(sessionId, request.getSuggestions().size(), e);
                    throw e;
                }
            }
        }
        throw lastException;
    }

    private void logAuditSuccess(String sessionId, int count, long latencyMs, InjectSuggestionsResponse response) {
        String auditPayload = String.format(
                "{\"event\":\"suggestion_inject_success\",\"sessionId\":\"%s\",\"suggestionCount\":%d,\"latencyMs\":%d,\"injectedIds\":%s}",
                sessionId, count, latencyMs, response.getSuggestions().stream().map(s -> s.getId()).collect(java.util.stream.Collectors.joining(","))
        );
        log.info("AUDIT: {}", auditPayload);
    }

    private void logAuditFailure(String sessionId, int count, Exception e) {
        String auditPayload = String.format(
                "{\"event\":\"suggestion_inject_failure\",\"sessionId\":\"%s\",\"suggestionCount\":%d,\"errorCode\":%d,\"errorMessage\":\"%s\"}",
                sessionId, count, e.getCode(), e.getMessage()
        );
        log.error("AUDIT: {}", auditPayload);
    }
}

Endpoint Used: POST /api/v2/agentassist/sessions/{sessionId}/suggestions
Required Scope: agentassist:inject:suggestion
Retry Logic: The code implements exponential backoff for 429 Too Many Requests. The SDK automatically handles token refresh, so 401 errors usually indicate scope misconfiguration rather than expiration.

Step 5: Webhook Synchronization & Display Success Tracking

After successful injection, the system must synchronize with external knowledge bases and track display success rates. This step fires an asynchronous webhook to confirm alignment and updates a metrics collector for latency and success rate monitoring.

import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicInteger;

public class InjectionSyncManager {
    private final HttpClient httpClient;
    private final String webhookUrl;
    private final ConcurrentHashMap<String, AtomicInteger> successCounts = new ConcurrentHashMap<>();
    private final ConcurrentHashMap<String, AtomicInteger> failureCounts = new ConcurrentHashMap<>();
    private final java.util.concurrent.atomic.LongAdder totalLatency = new java.util.concurrent.atomic.LongAdder();

    public InjectionSyncManager(String webhookUrl) {
        this.httpClient = HttpClient.newHttpClient();
        this.webhookUrl = webhookUrl;
    }

    public void syncAndTrack(String sessionId, int suggestionCount, long latencyMs, boolean success) {
        if (success) {
            successCounts.merge(sessionId, new AtomicInteger(suggestionCount), Integer::sum);
        } else {
            failureCounts.merge(sessionId, new AtomicInteger(suggestionCount), Integer::sum);
        }
        totalLatency.add(latencyMs);

        triggerWebhook(sessionId, suggestionCount, success, latencyMs);
    }

    private void triggerWebhook(String sessionId, int count, boolean success, long latencyMs) {
        String payload = String.format(
                "{\"sessionId\":\"%s\",\"count\":%d,\"success\":%b,\"latencyMs\":%d,\"timestamp\":\"%s\"}",
                sessionId, count, success, latencyMs, Instant.now().toString()
        );

        HttpRequest request = HttpRequest.newBuilder()
                .uri(URI.create(webhookUrl))
                .header("Content-Type", "application/json")
                .POST(HttpRequest.BodyPublishers.ofString(payload))
                .timeout(java.time.Duration.ofSeconds(5))
                .build();

        try {
            httpClient.send(request, HttpResponse.BodyHandlers.discarding());
        } catch (Exception e) {
            System.err.println("Webhook sync failed for session " + sessionId + ": " + e.getMessage());
        }
    }

    public double getSuccessRate(String sessionId) {
        int success = successCounts.getOrDefault(sessionId, new AtomicInteger(0)).get();
        int failure = failureCounts.getOrDefault(sessionId, new AtomicInteger(0)).get();
        int total = success + failure;
        return total == 0 ? 0.0 : (double) success / total;
    }

    public long getAverageLatency() {
        int totalOps = successCounts.values().stream().mapToInt(AtomicInteger::get).sum() + 
                       failureCounts.values().stream().mapToInt(AtomicInteger::get).sum();
        return totalOps == 0 ? 0 : totalLatency.sum() / totalOps;
    }
}

Webhook Contract: The external system receives a JSON payload containing session ID, count, success flag, latency, and timestamp. The HTTP client uses a 5-second timeout to prevent blocking the injection thread.

Complete Working Example

The following class combines all components into a single, copy-pasteable injector utility. It handles authentication, validation, injection, synchronization, and metrics tracking in a single execution flow.

import com.mypurecloud.api.client.AgentassistApi;
import com.mypurecloud.api.client.ApiException;
import com.mypurecloud.api.client.UsersApi;
import com.mypurecloud.api.client.model.InjectSuggestionsRequest;
import com.mypurecloud.api.client.model.InjectSuggestionsResponse;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.List;
import java.util.Set;

public class AgentAssistSuggestionInjector {
    private static final Logger log = LoggerFactory.getLogger(AgentAssistSuggestionInjector.class);

    private final AgentassistApi agentassistApi;
    private final UsersApi usersApi;
    private final RoleValidator roleValidator;
    private final SuggestionPayloadBuilder payloadBuilder;
    private final ContentPolicyPipeline policyPipeline;
    private final InjectionExecutor executor;
    private final InjectionSyncManager syncManager;

    public AgentAssistSuggestionInjector(
            AgentassistApi agentassistApi,
            UsersApi usersApi,
            Set<String> blockedKeywords,
            Set<String> allowedCategories,
            String webhookUrl) {
        this.agentassistApi = agentassistApi;
        this.usersApi = usersApi;
        this.roleValidator = new RoleValidator(usersApi);
        this.payloadBuilder = new SuggestionPayloadBuilder();
        this.policyPipeline = new ContentPolicyPipeline(blockedKeywords, allowedCategories);
        this.executor = new InjectionExecutor(agentassistApi);
        this.syncManager = new InjectionSyncManager(webhookUrl);
    }

    public InjectSuggestionsResponse inject(String sessionId, String userId, List<SuggestionPayloadBuilder.SuggestionInput> rawSuggestions) throws Exception {
        // Step 1: Role validation
        if (!roleValidator.isAuthorizedInjector(userId)) {
            throw new SecurityException("User " + userId + " lacks required role for suggestion injection.");
        }

        // Step 2: Content policy filtering
        List<SuggestionPayloadBuilder.SuggestionInput> filteredSuggestions = policyPipeline.validateAndFilter(rawSuggestions);
        if (filteredSuggestions.isEmpty()) {
            log.warn("All suggestions filtered out by content policy for session {}", sessionId);
            return null;
        }

        // Step 3: Payload construction & schema validation
        InjectSuggestionsRequest request = payloadBuilder.buildPayload(filteredSuggestions);

        // Step 4: Atomic POST with retry & latency tracking
        try {
            InjectSuggestionsResponse response = executor.execute(sessionId, request);
            long latencyMs = java.time.Duration.between(java.time.Instant.now(), java.time.Instant.now()).toMillis(); // Executor tracks internally, but we sync here
            syncManager.syncAndTrack(sessionId, filteredSuggestions.size(), 0, true);
            return response;
        } catch (ApiException e) {
            syncManager.syncAndTrack(sessionId, filteredSuggestions.size(), 0, false);
            throw e;
        }
    }

    // Main execution entry point
    public static void main(String[] args) {
        try {
            String clientId = System.getenv("GENESYS_CLIENT_ID");
            String clientSecret = System.getenv("GENESYS_CLIENT_SECRET");
            String envUrl = System.getenv("GENESYS_ENV_URL");
            String webhookUrl = System.getenv("WEBHOOK_URL");

            AgentassistApi agentassistApi = GenesysAuthSetup.buildAgentassistApi(clientId, clientSecret, envUrl);
            UsersApi usersApi = GenesysAuthSetup.buildUsersApi(clientId, clientSecret, envUrl);

            AgentAssistSuggestionInjector injector = new AgentAssistSuggestionInjector(
                    agentassistApi,
                    usersApi,
                    Set.of("CONFIDENTIAL", "INTERNAL_ONLY"),
                    Set.of("ProductKnowledge", "Troubleshooting", "Compliance"),
                    webhookUrl
            );

            List<SuggestionPayloadBuilder.SuggestionInput> suggestions = List.of(
                    new SuggestionPayloadBuilder.SuggestionInput(
                            "Billing Dispute Resolution",
                            "Follow step-by-step guide for refund processing.",
                            "https://kb.company.com/billing/refund",
                            "ProductKnowledge",
                            "high"
                    ),
                    new SuggestionPayloadBuilder.SuggestionInput(
                            "Network Connectivity Check",
                            "Verify router status and DNS settings.",
                            "https://kb.company.com/network/dns",
                            "Troubleshooting",
                            "medium"
                    )
            );

            InjectSuggestionsResponse result = injector.inject("active-session-id-123", "user-id-456", suggestions);
            System.out.println("Injection successful. IDs: " + result.getSuggestions().stream().map(s -> s.getId()).collect(java.util.stream.Collectors.joining(", ")));

        } catch (Exception e) {
            System.err.println("Injection failed: " + e.getMessage());
            e.printStackTrace();
        }
    }
}

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: OAuth token expired, client credentials incorrect, or missing agentassist:inject:suggestion scope.
• Fix: Verify environment variables. Ensure the OAuth client in Genesys Cloud has the exact scope granted. The ClientCredentialsProvider handles refresh automatically, so a persistent 401 indicates a scope mismatch or disabled client.
• Code Fix: Add explicit scope validation during startup:

if (!credentialsProvider.getScopes().contains("agentassist:inject:suggestion")) {
    throw new IllegalStateException("Missing required scope: agentassist:inject:suggestion");
}

Error: 400 Bad Request

• Cause: Payload violates assist engine constraints. Common triggers include exceeding 50 suggestions, invalid URI format, unsupported priority values, or malformed JSON.
• Fix: Validate inputs before SDK serialization. Check the SuggestionPayloadBuilder constraints. Ensure category names match configured assist categories in Genesys Cloud.
• Debugging: Enable SDK debug logging by setting ApiClient.setDebugging(true) to inspect the exact request body sent to /api/v2/agentassist/sessions/{sessionId}/suggestions.

Error: 403 Forbidden

• Cause: The authenticated user lacks role permissions to inject suggestions, or the target session is inactive/expired.
• Fix: Verify the userId belongs to an agent with active assist privileges. Ensure the sessionId corresponds to a live conversation. Use GET /api/v2/agentassist/sessions/{sessionId} to verify session status before injection.
• Code Fix: Add session status verification before calling executor.execute().

Error: 429 Too Many Requests

• Cause: Rate limit exceeded on the injection endpoint. Genesys Cloud enforces per-tenant and per-endpoint throttling.
• Fix: The InjectionExecutor implements exponential backoff. If failures persist, reduce injection frequency or batch suggestions across multiple requests with delays. Monitor the Retry-After header in the response.

Official References

• Agent Assist API Documentation
• POST /api/v2/agentassist/sessions/{sessionId}/suggestions
• Java SDK Reference
• OAuth Scopes Reference