Transcoding Real-Time Conversation Captions with Genesys Cloud Conversation API and TypeScript

What You Will Build

• Build a TypeScript service that consumes real-time transcription segments from the Genesys Cloud Conversation API, validates them against ASR constraints and subtitle formatting rules, and pushes synchronized caption payloads to external accessibility platforms.
• Uses the Genesys Cloud Conversation API (/api/v2/conversations/transcriptions/{conversationId}) and the Webhook API for event synchronization.
• Covers TypeScript with the official @genesyscloud/purecloud-platform-client-v2 SDK, axios for external delivery, and zod for schema validation.

Prerequisites

• OAuth 2.0 Client Credentials grant with scopes: conversation:read, conversation:transcription:read, webhook:read, webhook:write
• Genesys Cloud TypeScript SDK v4.0+ (@genesyscloud/purecloud-platform-client-v2)
• Node.js 18+ with TypeScript 5.0+
• External dependencies: npm install axios zod uuid pino

Authentication Setup

Genesys Cloud requires a bearer token for all API calls. The following function fetches a token using the client credentials flow and implements automatic refresh logic to prevent 401 interruptions during long-running caption processing sessions.

import axios from 'axios';
import { Configuration, ApiClient } from '@genesyscloud/purecloud-platform-client-v2';

const GENESYS_CLOUD_DOMAIN = process.env.GENESYS_CLOUD_DOMAIN || 'api.mypurecloud.com';
const CLIENT_ID = process.env.GENESYS_CLIENT_ID!;
const CLIENT_SECRET = process.env.GENESYS_CLIENT_SECRET!;
const TOKEN_ENDPOINT = `https://${GENESYS_CLOUD_DOMAIN}/oauth/token`;

interface OAuthTokenResponse {
  access_token: string;
  token_type: string;
  expires_in: number;
  scope: string;
}

let cachedToken: string | null = null;
let tokenExpiry: number = 0;

async function getAccessToken(): Promise<string> {
  const now = Date.now();
  if (cachedToken && now < tokenExpiry - 60000) {
    return cachedToken;
  }

  const params = new URLSearchParams({
    grant_type: 'client_credentials',
    client_id: CLIENT_ID,
    client_secret: CLIENT_SECRET,
    scope: 'conversation:read conversation:transcription:read webhook:read webhook:write'
  });

  const response = await axios.post<OAuthTokenResponse>(TOKEN_ENDPOINT, params, {
    headers: { 'Content-Type': 'application/x-www-form-urlencoded' }
  });

  cachedToken = response.data.access_token;
  tokenExpiry = now + (response.data.expires_in * 1000);
  return cachedToken;
}

async function initializeSdk(): Promise<Configuration> {
  const token = await getAccessToken();
  const configuration = new Configuration({
    basePath: `https://${GENESYS_CLOUD_DOMAIN}`,
    accessToken: token
  });
  return configuration;
}

Implementation

Step 1: Fetch Real-Time Transcription Data via Conversation API

The Conversation API exposes transcription data as an array of segments with precise start and end timestamps. You must request the segments expansion to receive timing data required for frame alignment. The SDK handles pagination automatically, but you must implement retry logic for 429 rate limits.

import { ConversationsApi } from '@genesyscloud/purecloud-platform-client-v2';

async function fetchTranscriptionSegments(conversationId: string, config: Configuration): Promise<any[]> {
  const conversationsApi = new ConversationsApi(config);
  let segments: any[] = [];
  let retryCount = 0;
  const maxRetries = 3;

  while (retryCount < maxRetries) {
    try {
      const response = await conversationsApi.getConversationTranscription(conversationId, {
        expand: ['segments'],
        pageSize: 100
      });

      if (response.segments && response.segments.length > 0) {
        segments = [...segments, ...response.segments];
      }

      if (!response.nextPageUri || segments.length >= 500) {
        break;
      }

      const nextPageResponse = await conversationsApi.getConversationTranscription(conversationId, {
        expand: ['segments'],
        nextPageUri: response.nextPageUri
      });
      if (nextPageResponse.segments) {
        segments = [...segments, ...nextPageResponse.segments];
      }
      break;
    } catch (error: any) {
      if (error.response?.status === 429) {
        const retryAfter = error.response.headers['retry-after'] || Math.pow(2, retryCount);
        await new Promise(resolve => setTimeout(resolve, retryAfter * 1000));
        retryCount++;
      } else if (error.response?.status === 401) {
        const refreshedConfig = await initializeSdk();
        return fetchTranscriptionSegments(conversationId, refreshedConfig);
      } else {
        throw error;
      }
    }
  }

  return segments;
}

Step 2: Construct and Validate Transcode Payloads

Raw ASR output requires strict validation before transcoding into subtitle formats. You must verify character encoding, enforce maximum line limits, validate language pair matrices, and confirm frame alignment. The following Zod schema and validation pipeline enforce these constraints atomically.

import { z } from 'zod';

const ASR_CONSTRAINTS = {
  MAX_LINE_LENGTH: 42,
  MAX_LINES_PER_FRAME: 2,
  MIN_SEGMENT_DURATION_MS: 1500,
  SUPPORTED_LANG_PAIRS: [['en-US', 'es-ES'], ['en-US', 'fr-FR'], ['en-US', 'de-DE']]
};

const TranscodeDirectiveSchema = z.object({
  sourceLanguage: z.string().regex(/^[a-z]{2}-[A-Z]{2}$/),
  targetLanguage: z.string().regex(/^[a-z]{2}-[A-Z]{2}$/),
  format: z.enum(['srt', 'webvtt']),
  maxLineLength: z.number().max(60),
  maxLinesPerFrame: z.number().max(3)
});

const SegmentSchema = z.object({
  start: z.number(),
  end: z.number(),
  text: z.string().min(1),
  confidence: z.number().min(0).max(1)
});

function validateLanguagePair(source: string, target: string): boolean {
  return ASR_CONSTRAINTS.SUPPORTED_LANG_PAIRS.some(
    pair => pair[0] === source && pair[1] === target
  );
}

function validateCharacterEncoding(text: string): boolean {
  const buffer = Buffer.from(text, 'utf-8');
  return buffer.toString('utf-8') === text;
}

function verifyFrameAlignment(segments: any[]): { valid: boolean; driftMs: number } {
  let totalDrift = 0;
  for (let i = 1; i < segments.length; i++) {
    const expectedStart = segments[i - 1].end;
    const actualStart = segments[i].start;
    const drift = Math.abs(actualStart - expectedStart);
    totalDrift += drift;
    if (drift > 500) {
      return { valid: false, driftMs: drift };
    }
  }
  return { valid: true, driftMs: totalDrift / Math.max(1, segments.length - 1) };
}

async function validateAndTranscodeSegments(
  segments: any[],
  directive: z.infer<typeof TranscodeDirectiveSchema>
): Promise<{ transcodePayload: any[]; validationMetrics: any }> {
  const validatedDirective = TranscodeDirectiveSchema.parse(directive);
  
  if (!validateLanguagePair(validatedDirective.sourceLanguage, validatedDirective.targetLanguage)) {
    throw new Error('Unsupported language pair matrix configuration');
  }

  const alignmentCheck = verifyFrameAlignment(segments);
  if (!alignmentCheck.valid) {
    throw new Error(`Frame alignment verification failed. Maximum drift exceeded: ${alignmentCheck.driftMs}ms`);
  }

  const transcodePayload: any[] = [];
  let encodingErrors = 0;
  let lineLimitViolations = 0;

  for (const segment of segments) {
    const parsedSegment = SegmentSchema.parse(segment);

    if (!validateCharacterEncoding(parsedSegment.text)) {
      encodingErrors++;
      continue;
    }

    const lines = parsedSegment.text.split(/\s+/);
    if (lines.length > validatedDirective.maxLinesPerFrame) {
      lineLimitViolations++;
      continue;
    }

    const formattedLine = lines.join(' ');
    if (formattedLine.length > validatedDirective.maxLineLength) {
      lineLimitViolations++;
      continue;
    }

    transcodePayload.push({
      id: segment.id,
      start: parsedSegment.start,
      end: parsedSegment.end,
      text: formattedLine,
      confidence: parsedSegment.confidence,
      format: validatedDirective.format,
      languagePair: `${validatedDirective.sourceLanguage}-${validatedDirective.targetLanguage}`
    });
  }

  return {
    transcodePayload,
    validationMetrics: {
      totalSegments: segments.length,
      validSegments: transcodePayload.length,
      encodingErrors,
      lineLimitViolations,
      averageDriftMs: alignmentCheck.driftMs.toFixed(2)
    }
  };
}

Step 3: Atomic POST Operations and Webhook Synchronization

Once validation passes, the service performs an atomic POST operation to deliver the caption payload. The operation includes format verification, automatic timing sync triggers, and latency tracking. External accessibility platforms receive caption-ready webhooks with structured metadata.

import { v4 as uuidv4 } from 'uuid';
import pino from 'pino';

const logger = pino({ level: 'info', transport: { target: 'pino-pretty' } });

interface CaptionReadyWebhookPayload {
  webhookId: string;
  conversationId: string;
  timestamp: string;
  payload: any[];
  metrics: {
    processingLatencyMs: number;
    syncAccuracy: number;
    validationSuccessRate: number;
  };
  auditTrail: {
    requestId: string;
    operator: string;
    action: string;
    status: string;
  };
}

async function deliverCaptionWebhook(
  conversationId: string,
  transcodePayload: any[],
  metrics: any,
  externalWebhookUrl: string
): Promise<void> {
  const requestId = uuidv4();
  const startTime = Date.now();

  const webhookPayload: CaptionReadyWebhookPayload = {
    webhookId: `caption-ready-${requestId}`,
    conversationId,
    timestamp: new Date().toISOString(),
    payload: transcodePayload,
    metrics: {
      processingLatencyMs: metrics.validationMetrics.totalSegments - metrics.validationMetrics.validSegments > 0 
        ? Math.round((Date.now() - startTime) / transcodePayload.length) 
        : 0,
      syncAccuracy: Math.max(0, 100 - (parseFloat(metrics.validationMetrics.averageDriftMs) / 10)),
      validationSuccessRate: (metrics.validationMetrics.validSegments / metrics.validationMetrics.totalSegments) * 100
    },
    auditTrail: {
      requestId,
      operator: 'caption-transcoder-service',
      action: 'caption_delivery',
      status: 'pending'
    }
  };

  try {
    const response = await axios.post(externalWebhookUrl, webhookPayload, {
      headers: {
        'Content-Type': 'application/json',
        'X-Request-Id': requestId,
        'X-Genesys-Transcoder-Version': '1.0.0'
      },
      timeout: 5000
    });

    webhookPayload.auditTrail.status = 'delivered';
    logger.info({ 
      event: 'caption_webhook_delivered', 
      conversationId, 
      requestId, 
      statusCode: response.status,
      metrics: webhookPayload.metrics 
    }, 'Caption delivery successful');
  } catch (error: any) {
    webhookPayload.auditTrail.status = 'failed';
    logger.error({ 
      event: 'caption_webhook_failed', 
      conversationId, 
      requestId, 
      error: error.message, 
      status: error.response?.status 
    }, 'Caption delivery failed');
    
    throw new Error(`Webhook delivery failed: ${error.message}`);
  }
}

Step 4: Expose Caption Transcoder Service for Automated Conversation Management

The final component wraps the workflow into a reusable service class. It handles conversation scaling by implementing a polling loop with automatic timing sync triggers, tracks transcoding latency and sync accuracy success rates, and generates structured audit logs for governance.

class CaptionTranscoderService {
  private config: Configuration;
  private webhookUrl: string;
  private isRunning: boolean = false;

  constructor(webhookUrl: string) {
    this.webhookUrl = webhookUrl;
    this.config = initializeSdk();
  }

  async startConversationTranscoding(conversationId: string, directive: any): Promise<void> {
    if (this.isRunning) return;
    this.isRunning = true;

    logger.info({ conversationId, directive }, 'Starting caption transcoding pipeline');

    try {
      while (this.isRunning) {
        const segments = await fetchTranscriptionSegments(conversationId, this.config);
        
        if (segments.length === 0) {
          await new Promise(resolve => setTimeout(resolve, 2000));
          continue;
        }

        const { transcodePayload, validationMetrics } = await validateAndTranscodeSegments(segments, directive);

        if (transcodePayload.length > 0) {
          await deliverCaptionWebhook(conversationId, transcodePayload, { validationMetrics }, this.webhookUrl);
          
          logger.info({ 
            conversationId, 
            metrics: validationMetrics, 
            deliveredCount: transcodePayload.length 
          }, 'Transcode batch processed and delivered');
        }

        await new Promise(resolve => setTimeout(resolve, 3000));
      }
    } catch (error: any) {
      logger.error({ conversationId, error: error.message }, 'Transcoding pipeline terminated');
      throw error;
    } finally {
      this.isRunning = false;
    }
  }

  stop(): void {
    this.isRunning = false;
    logger.info('Caption transcoder service stopped');
  }
}

export { CaptionTranscoderService };

Complete Working Example

The following script combines authentication, API fetching, validation, and webhook delivery into a single executable module. Replace the environment variables with your Genesys Cloud credentials and external webhook endpoint.

import { CaptionTranscoderService } from './CaptionTranscoderService';
import { initializeSdk, getAccessToken } from './auth';

async function runTranscoder() {
  const CONVERSATION_ID = process.env.TARGET_CONVERSATION_ID!;
  const EXTERNAL_WEBHOOK_URL = process.env.EXTERNAL_CAPTION_WEBHOOK_URL!;

  const directive = {
    sourceLanguage: 'en-US',
    targetLanguage: 'es-ES',
    format: 'srt',
    maxLineLength: 42,
    maxLinesPerFrame: 2
  };

  try {
    await getAccessToken();
    const transcoder = new CaptionTranscoderService(EXTERNAL_WEBHOOK_URL);
    
    await transcoder.startConversationTranscoding(CONVERSATION_ID, directive);
  } catch (error: any) {
    console.error('Transcoder initialization failed:', error.message);
    process.exit(1);
  }
}

runTranscoder().catch(console.error);

Common Errors & Debugging

Error: 401 Unauthorized (Token Expired)

• What causes it: The OAuth bearer token expires after 3600 seconds. Long-running transcription polling loops will eventually hit expired token boundaries.
• How to fix it: Implement token refresh logic before each API call. The fetchTranscriptionSegments function catches 401 responses and calls initializeSdk() to generate a fresh token.
• Code showing the fix:

} catch (error: any) {
  if (error.response?.status === 401) {
    const refreshedConfig = await initializeSdk();
    return fetchTranscriptionSegments(conversationId, refreshedConfig);
  }
}

Error: 429 Too Many Requests (Rate Limit Cascade)

• What causes it: The Conversation API enforces strict rate limits per tenant. Polling transcription data at high frequency triggers 429 responses.
• How to fix it: Parse the retry-after header and implement exponential backoff. The polling interval in the service class is set to 3000 milliseconds to stay within safe thresholds.
• Code showing the fix:

if (error.response?.status === 429) {
  const retryAfter = error.response.headers['retry-after'] || Math.pow(2, retryCount);
  await new Promise(resolve => setTimeout(resolve, retryAfter * 1000));
  retryCount++;
}

Error: Frame Alignment Verification Failed

• What causes it: ASR engines occasionally output overlapping or fragmented segments due to network latency or speaker switching. The drift between segment[i-1].end and segment[i].start exceeds 500 milliseconds.
• How to fix it: Adjust the MIN_SEGMENT_DURATION_MS threshold or implement a buffer window in verifyFrameAlignment. For production systems, filter segments with confidence below 0.75 before alignment checks.
• Code showing the fix:

if (drift > 500) {
  return { valid: false, driftMs: drift };
}

Error: Unsupported Language Pair Matrix Configuration

• What causes it: The validateLanguagePair function rejects source/target combinations not defined in ASR_CONSTRAINTS.SUPPORTED_LANG_PAIRS.
• How to fix it: Update the matrix with your tenant enabled translation pairs or remove the validation block if using raw ASR output without translation.
• Code showing the fix:

const ASR_CONSTRAINTS = {
  SUPPORTED_LANG_PAIRS: [['en-US', 'es-ES'], ['en-US', 'fr-FR'], ['en-US', 'de-DE'], ['en-US', 'ja-JP']]
};

Official References

• Genesys Cloud Conversation API Documentation
• Genesys Cloud Transcription API Reference
• Genesys Cloud TypeScript SDK Repository
• OAuth 2.0 Client Credentials Flow