Triggering Genesys Cloud Language Identification Jobs via the Transcription API with TypeScript

What You Will Build

You will build a TypeScript module that programmatically submits language identification transcription jobs to Genesys Cloud by constructing strict payloads, validating recording metadata, and enforcing organizational concurrency limits. You will implement atomic POST operations with exponential backoff, queue prioritization logic, and webhook synchronization for external analytics. The code will expose a reusable triggerer class that tracks latency, success rates, and generates structured audit logs for governance compliance.

Prerequisites

• OAuth client credentials flow with scopes: recording:read, recording:transcribe
• Genesys Cloud REST API v2
• Node.js 18+ with TypeScript 5+
• External dependencies: axios, uuid, dotenv

Authentication Setup

The Transcription API requires a bearer token obtained via the Genesys Cloud OAuth 2.0 server. The following function fetches and caches the token with automatic expiration handling. The required scopes are recording:read and recording:transcribe.

import axios, { AxiosInstance } from 'axios';

interface TokenResponse {
  access_token: string;
  expires_in: number;
  token_type: string;
}

class TokenManager {
  private token: string | null = null;
  private expiry: number = 0;
  private client: AxiosInstance;

  constructor(private environment: string, private clientId: string, private clientSecret: string) {
    this.client = axios.create({ baseURL: `https://${environment}.mygen.com` });
  }

  async getToken(): Promise<string> {
    if (this.token && Date.now() < this.expiry) {
      return this.token;
    }

    const formData = new URLSearchParams({
      grant_type: 'client_credentials',
      client_id: this.clientId,
      client_secret: this.clientSecret
    });

    const response = await this.client.post<TokenResponse>('/oauth/token', formData, {
      headers: { 'Content-Type': 'application/x-www-form-urlencoded' }
    });

    this.token = response.data.access_token;
    this.expiry = Date.now() + (response.data.expires_in * 1000) - 5000;
    return this.token;
  }
}

Implementation

Step 1: Construct Trigger Payloads with Recording References and Language Models

The Transcription API expects a TranscriptionCreateRequest payload. Language identification jobs require the languageModel field set to auto and the features array to include languageIdentification. You must attach a callbackUri to receive completion events. The following interface enforces schema constraints before submission.

import { v4 as uuidv4 } from 'uuid';

export interface TranscriptionTriggerConfig {
  recordingId: string;
  callbackUri: string;
  languageModel: 'auto' | string;
  queuePriority: 'HIGH' | 'NORMAL' | 'LOW';
  customTags?: Record<string, string>;
}

export interface TranscriptionPayload {
  recordingId: string;
  languageModel: string;
  callbackUri: string;
  name: string;
  queuePriority: string;
  features: string[];
  metadata: Record<string, string>;
}

function buildTranscriptionPayload(config: TranscriptionTriggerConfig): TranscriptionPayload {
  const payload: TranscriptionPayload = {
    recordingId: config.recordingId,
    languageModel: config.languageModel,
    callbackUri: config.callbackUri,
    name: `lang-id-job-${uuidv4().slice(0, 8)}`,
    queuePriority: config.queuePriority,
    features: ['languageIdentification'],
    metadata: {
      source: 'automated-triggerer',
      timestamp: new Date().toISOString(),
      ...config.customTags
    }
  };

  return payload;
}

Step 2: Validate Audio Formats and Enforce Concurrent Job Limits

Genesys Cloud rejects transcription jobs for unsupported audio formats or sample rates. You must fetch the recording metadata and verify compatibility. You must also query active jobs to prevent exceeding the organizational concurrency limit. The following functions implement these validation pipelines.

interface RecordingMetadata {
  format: string;
  sampleRate: number;
  duration: number;
}

const SUPPORTED_FORMATS = ['wav', 'mp3', 'aac', 'ogg', 'flac'];
const SUPPORTED_SAMPLE_RATES = [8000, 16000, 44100, 48000];
const MAX_CONCURRENT_JOBS = 100;

async function validateRecordingFormat(client: AxiosInstance, recordingId: string): Promise<RecordingMetadata> {
  const response = await client.get<RecordingMetadata>(`/api/v2/recorder/recordings/${recordingId}`);
  const meta = response.data;

  if (!SUPPORTED_FORMATS.includes(meta.format.toLowerCase())) {
    throw new Error(`Unsupported recording format: ${meta.format}`);
  }

  if (!SUPPORTED_SAMPLE_RATES.includes(meta.sampleRate)) {
    throw new Error(`Unsupported sample rate: ${meta.sampleRate} Hz`);
  }

  return meta;
}

async function checkConcurrentJobLimit(client: AxiosInstance): Promise<boolean> {
  const response = await client.get('/api/v2/recorder/transcriptions', {
    params: { status: 'RUNNING', pageSize: 1 }
  });

  const totalCount = response.headers['x-total-count'] ? parseInt(response.headers['x-total-count'], 10) : 0;
  return totalCount < MAX_CONCURRENT_JOBS;
}

Step 3: Execute Atomic POST Operations with Queue Prioritization and Retry Logic

Job submission must be atomic. The API returns 429 Too Many Requests during scaling events. The following function implements exponential backoff with jitter and automatic queue prioritization based on recording duration.

async function submitTranscriptionJob(
  client: AxiosInstance,
  payload: TranscriptionPayload,
  recordingDuration: number
): Promise<string> {
  payload.queuePriority = recordingDuration > 300 ? 'LOW' : 'HIGH';

  const maxRetries = 3;
  let attempt = 0;

  while (attempt < maxRetries) {
    try {
      const response = await client.post('/api/v2/recorder/transcriptions', payload);
      return response.data.id;
    } catch (error: any) {
      if (error.response?.status === 429) {
        const delay = Math.pow(2, attempt) * 1000 + Math.random() * 500;
        await new Promise(resolve => setTimeout(resolve, delay));
        attempt++;
      } else {
        throw error;
      }
    }
  }

  throw new Error('Max retries exceeded for transcription job submission');
}

Step 4: Synchronize Completion Events and Track Trigger Metrics

The callbackUri directive receives a TranscriptionCompletedEvent when the job finishes. You must parse the event, synchronize it with external analytics, and update trigger metrics. The following handler demonstrates webhook processing and latency tracking.

interface WebhookPayload {
  id: string;
  status: string;
  languageModel: string;
  createdTime: string;
  completedTime: string;
}

interface TriggerMetrics {
  totalAttempts: number;
  successfulSubmissions: number;
  averageLatencyMs: number;
  latencies: number[];
}

class MetricsTracker {
  private metrics: TriggerMetrics = {
    totalAttempts: 0,
    successfulSubmissions: 0,
    averageLatencyMs: 0,
    latencies: []
  };

  recordSubmission(latencyMs: number, success: boolean) {
    this.metrics.totalAttempts++;
    if (success) {
      this.metrics.successfulSubmissions++;
      this.metrics.latencies.push(latencyMs);
      this.metrics.averageLatencyMs = this.metrics.latencies.reduce((a, b) => a + b, 0) / this.metrics.latencies.length;
    }
  }

  getMetrics() { return { ...this.metrics }; }
}

async function handleWebhookSync(payload: WebhookPayload, analyticsEndpoint: string) {
  const syncEvent = {
    jobId: payload.id,
    status: payload.status,
    language: payload.languageModel,
    processingTimeMs: new Date(payload.completedTime).getTime() - new Date(payload.createdTime).getTime(),
    syncedAt: new Date().toISOString()
  };

  await axios.post(analyticsEndpoint, syncEvent, {
    headers: { 'Content-Type': 'application/json' }
  });
}

Step 5: Generate Audit Logs and Expose the Triggerer Interface

Governance requires immutable audit trails. The following class consolidates authentication, validation, submission, metrics, and logging into a single triggerer interface.

class TranscriptionJobTriggerer {
  private tokenManager: TokenManager;
  private apiClient: AxiosInstance;
  private metrics: MetricsTracker;
  private auditLog: Array<Record<string, any>> = [];

  constructor(environment: string, clientId: string, clientSecret: string) {
    this.tokenManager = new TokenManager(environment, clientId, clientSecret);
    this.apiClient = axios.create({ baseURL: `https://${environment}.mygen.com` });
    this.metrics = new MetricsTracker();
  }

  private async getAuthenticatedClient(): Promise<AxiosInstance> {
    const token = await this.tokenManager.getToken();
    const client = this.apiClient.defaults.headers;
    client.common.Authorization = `Bearer ${token}`;
    client.common['Content-Type'] = 'application/json';
    return this.apiClient;
  }

  async trigger(config: TranscriptionTriggerConfig, analyticsEndpoint: string): Promise<string> {
    const startTime = Date.now();
    const authClient = await this.getAuthenticatedClient();

    const limitCheck = await checkConcurrentJobLimit(authClient);
    if (!limitCheck) {
      throw new Error('Concurrent job limit reached. Queue is full.');
    }

    const recordingMeta = await validateRecordingFormat(authClient, config.recordingId);
    const payload = buildTranscriptionPayload(config);

    const jobId = await submitTranscriptionJob(authClient, payload, recordingMeta.duration);
    const latency = Date.now() - startTime;

    this.metrics.recordSubmission(latency, true);
    this.auditLog.push({
      action: 'JOB_TRIGGERED',
      jobId,
      recordingId: config.recordingId,
      languageModel: config.languageModel,
      queuePriority: payload.queuePriority,
      latencyMs: latency,
      timestamp: new Date().toISOString()
    });

    return jobId;
  }

  getAuditLog() { return [...this.auditLog]; }
  getMetrics() { return this.metrics.getMetrics(); }
}

Complete Working Example

The following script integrates all components. Replace the environment variables with your credentials before execution.

import 'dotenv/config';
import { TranscriptionJobTriggerer } from './triggerer';
import { TranscriptionTriggerConfig } from './payloads';

async function main() {
  const environment = process.env.GENESYS_ENV || 'us-east-1';
  const clientId = process.env.GENESYS_CLIENT_ID!;
  const clientSecret = process.env.GENESYS_CLIENT_SECRET!;
  const recordingId = process.env.TARGET_RECORDING_ID!;
  const callbackUri = process.env.WEBHOOK_CALLBACK_URI!;
  const analyticsEndpoint = process.env.ANALYTICS_ENDPOINT!;

  const triggerer = new TranscriptionJobTriggerer(environment, clientId, clientSecret);

  const config: TranscriptionTriggerConfig = {
    recordingId,
    callbackUri,
    languageModel: 'auto',
    queuePriority: 'NORMAL',
    customTags: {
      team: 'support',
      campaign: 'q4-scaling'
    }
  };

  try {
    console.log('Initiating language identification job trigger...');
    const jobId = await triggerer.trigger(config, analyticsEndpoint);
    console.log(`Job submitted successfully. ID: ${jobId}`);
    console.log('Metrics:', triggerer.getMetrics());
    console.log('Audit Log:', JSON.stringify(triggerer.getAuditLog(), null, 2));
  } catch (error: any) {
    console.error('Trigger failed:', error.response?.data || error.message);
    process.exit(1);
  }
}

main();

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: Expired OAuth token or invalid client credentials. The TokenManager automatically refreshes tokens, but initial fetch failures indicate misconfigured client_id or client_secret.
• Fix: Verify credentials in Genesys Cloud Admin. Ensure the grant_type matches client_credentials. Check that the token request includes Content-Type: application/x-www-form-urlencoded.

Error: 400 Bad Request

• Cause: Payload schema mismatch or unsupported languageModel. The Transcription API rejects jobs with missing recordingId or invalid callbackUri formats.
• Fix: Validate the TranscriptionPayload interface against the official schema. Ensure callbackUri uses HTTPS and returns a 200 OK immediately upon receipt. Verify languageModel is set to auto for identification jobs.

Error: 403 Forbidden

• Cause: Missing OAuth scopes. The client lacks recording:read or recording:transcribe.
• Fix: Navigate to the OAuth client configuration in Genesys Cloud. Add both scopes to the client. Regenerate credentials if you modified an existing client.

Error: 429 Too Many Requests

• Cause: Rate limit cascade during peak transcription scaling. The API throttles submissions to protect backend queues.
• Fix: The submitTranscriptionJob function implements exponential backoff with jitter. If failures persist, reduce batch submission frequency or implement a local queue with a rate limiter like p-limit.

Official References

• Transcription API Documentation
• OAuth 2.0 Client Credentials Flow
• Recording Metadata Endpoint
• TypeScript SDK Reference