Processing Genesys Cloud Media Transcriptions via API with Python

What You Will Build

A Python service that submits media transcription jobs to Genesys Cloud, receives asynchronous webhook callbacks upon completion, normalizes and redacts transcription text, synchronizes results to an external search index, tracks processing metrics, and generates compliance audit logs. This tutorial uses the Genesys Cloud Python SDK and FastAPI for webhook handling. The implementation covers Python 3.9+.

Prerequisites

• OAuth 2.0 client credentials grant with scopes: quality:transcription, webhook:write, webhook:read
• Genesys Cloud Python SDK version 2.100.0 or higher
• Python 3.9+ runtime
• External dependencies: fastapi>=0.100.0, uvicorn>=0.23.0, elasticsearch>=8.0.0, python-dotenv>=1.0.0, requests>=2.31.0
• Access to an Elasticsearch or OpenSearch cluster for search synchronization
• Valid media ID from Genesys Cloud conversations or recordings API

Authentication Setup

The Genesys Cloud Python SDK handles OAuth token acquisition and refresh automatically when initialized with client credentials. You must provide your organization region, client ID, and client secret. The SDK caches tokens in memory and refreshes them before expiration.

import os
from genesyscloud.purecloud_platform_client import PureCloudPlatformClientV2

def initialize_genesys_client() -> PureCloudPlatformClientV2:
    """Initialize the Genesys Cloud platform client with OAuth credentials."""
    client = PureCloudPlatformClientV2()
    client.set_config_property(
        'region', os.getenv('GENESYS_REGION', 'mypurecloud.com')
    )
    client.set_config_property(
        'auth_url', f'https://api.{os.getenv("GENESYS_REGION", "mypurecloud.com")}/oauth/token'
    )
    
    # Configure OAuth client credentials
    client.set_config_property('client_id', os.getenv('GENESYS_CLIENT_ID'))
    client.set_config_property('client_secret', os.getenv('GENESYS_CLIENT_SECRET'))
    
    # Authenticate and cache token
    client.login_client_credential()
    return client

The authentication flow performs a POST to /api/v2/oauth/token with grant_type=client_credentials and the required scopes. The SDK stores the access_token and refresh_token internally. Token expiration triggers automatic refresh before the next API call.

Implementation

Step 1: Validate Media Attributes and Construct Transcription Payloads

Genesys Cloud enforces strict media limits: maximum duration of 240 minutes, maximum file size of 2 GB, and supported codecs including PCM, G.711, OPUS, and MP3. You must validate attributes before submission to avoid 400 Bad Request responses. The transcription payload requires explicit configuration for language models, profanity filtering, and speaker diarization.

import re
import time
from typing import Dict, Any
from genesyscloud.purecloud_platform_client import PureCloudPlatformClientV2
from genesyscloud.quality_api import TranscriptionApi
from genesyscloud.models.create_transcription_request import CreateTranscriptionRequest

SUPPORTED_CODECS = {'L16', 'G711MU', 'G711A', 'OPUS', 'MP3'}
MAX_DURATION_SECONDS = 14400  # 240 minutes
MAX_FILE_SIZE_BYTES = 2 * 1024 * 1024 * 1024  # 2 GB

def validate_media_attributes(media: Dict[str, Any]) -> bool:
    """Validate media duration, size, and codec against Genesys Cloud limits."""
    duration = media.get('duration', 0)
    file_size = media.get('size', 0)
    codec = media.get('codec', '').upper()
    
    if duration > MAX_DURATION_SECONDS:
        raise ValueError(f'Media duration {duration}s exceeds maximum {MAX_DURATION_SECONDS}s')
    if file_size > MAX_FILE_SIZE_BYTES:
        raise ValueError(f'Media size {file_size} bytes exceeds maximum {MAX_FILE_SIZE_BYTES} bytes')
    if codec not in SUPPORTED_CODECS:
        raise ValueError(f'Unsupported codec: {codec}. Supported: {SUPPORTED_CODECS}')
    
    return True

def build_transcription_payload(media_id: str, language: str = 'en-US') -> CreateTranscriptionRequest:
    """Construct a transcription request with language model, profanity filter, and diarization."""
    payload = CreateTranscriptionRequest(
        media_id=media_id,
        language=language,
        profanity_filter='on',
        diarization=True,
        language_model='default',
        custom_vocabulary_ids=[]
    )
    return payload

The POST /api/v2/quality/transcriptions endpoint expects the CreateTranscriptionRequest object. The SDK serializes it to JSON with fields mediaId, language, profanityFilter, diarization, and languageModel. The profanity filter replaces explicit content with asterisks. Diarization separates speaker turns in the output.

Step 2: Submit Transcription Jobs and Handle Webhook Callbacks

Transcription jobs run asynchronously. You submit the job and register a webhook listener for the quality.transcription.completed event. The webhook payload contains the transcription ID, but you must verify completion status by polling the API before processing results. This prevents race conditions where the webhook fires before finalization.

import logging
import hmac
import hashlib
from fastapi import FastAPI, Request, HTTPException
from genesyscloud.quality_api import TranscriptionApi

app = FastAPI()
logger = logging.getLogger('transcription_processor')

async def handle_transcription_webhook(request: Request, client: PureCloudPlatformClientV2):
    """Process webhook callback and verify transcription completion status."""
    body = await request.json()
    transcription_id = body.get('transcriptionId')
    event_type = body.get('type')
    
    if event_type != 'quality.transcription.completed':
        raise HTTPException(status_code=400, detail='Unsupported webhook event type')
    
    # Verify webhook signature if configured
    signature = request.headers.get('X-Genesys-Signature', '')
    secret = os.getenv('GENESYS_WEBHOOK_SECRET', '')
    if secret and not verify_webhook_signature(body, signature, secret):
        raise HTTPException(status_code=401, detail='Invalid webhook signature')
    
    # Fetch and verify transcription status
    transcription_api = TranscriptionApi(client)
    try:
        transcription_response = transcription_api.get_quality_transcription(transcription_id)
        status = transcription_response.status
        
        if status != 'completed':
            logger.warning(f'Transcription {transcription_id} status is {status}, skipping processing')
            return {'status': 'skipped', 'reason': 'not_completed'}
            
        return {'status': 'verified', 'transcription_id': transcription_id}
    except Exception as e:
        logger.error(f'Failed to fetch transcription {transcription_id}: {str(e)}')
        raise HTTPException(status_code=502, detail='Transcription API fetch failed')

def verify_webhook_signature(payload: dict, signature: str, secret: str) -> bool:
    """Verify HMAC-SHA256 signature of webhook payload."""
    payload_bytes = str(payload).encode('utf-8')
    expected = hmac.new(secret.encode('utf-8'), payload_bytes, hashlib.sha256).hexdigest()
    return hmac.compare_digest(signature, expected)

The webhook handler receives JSON from Genesys Cloud. The GET /api/v2/quality/transcriptions/{id} call returns the full transcription object. You must check the status field. Valid statuses include queued, processing, completed, and failed. Only completed triggers downstream processing. The SDK automatically handles 429 rate limits with exponential backoff when set_config_property('retry_on_rate_limit', True) is enabled.

Step 3: Post-Process Text, Sync to Search, and Generate Audit Logs

After verification, you extract utterances, normalize timestamps, redact sensitive patterns, track accuracy and latency, sync to Elasticsearch, and write audit logs. Genesys Cloud returns confidence scores per utterance. You calculate average confidence and processing duration for quality assurance metrics.

import json
import re
from datetime import datetime, timezone
from elasticsearch import Elasticsearch
from typing import List, Dict, Any

PII_PATTERNS = {
    'credit_card': r'\b(?:\d[ -]*?){13,16}\b',
    'ssn': r'\b\d{3}[- ]?\d{2}[- ]?\d{4}\b',
    'phone': r'\b(?:\+?1[-.\s]?)?\(?[0-9]{3}\)?[-.\s]?[0-9]{3}[-.\s]?[0-9]{4}\b'
}

def normalize_timestamps(utterances: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """Convert ISO 8601 timestamps to epoch seconds for search indexing."""
    normalized = []
    for utterance in utterances:
        start = datetime.fromisoformat(utterance['start']).replace(tzinfo=timezone.utc).timestamp()
        end = datetime.fromisoformat(utterance['end']).replace(tzinfo=timezone.utc).timestamp()
        normalized.append({
            'speaker': utterance.get('speaker', 'unknown'),
            'text': utterance['text'],
            'start_epoch': start,
            'end_epoch': end,
            'confidence': utterance.get('confidence', 0.0)
        })
    return normalized

def redact_sensitive_information(text: str) -> str:
    """Apply regex patterns to redact PII from transcription text."""
    redacted = text
    for pii_type, pattern in PII_PATTERNS.items():
        redacted = re.sub(pattern, f'[REDACTED_{pii_type.upper()}]', redacted)
    return redacted

def calculate_quality_metrics(utterances: List[Dict[str, Any]], processing_time: float) -> Dict[str, Any]:
    """Calculate average confidence and processing latency."""
    confidences = [u.get('confidence', 0.0) for u in utterances if u.get('confidence') is not None]
    avg_confidence = sum(confidences) / len(confidences) if confidences else 0.0
    return {
        'average_confidence': round(avg_confidence, 4),
        'processing_latency_seconds': round(processing_time, 3),
        'utterance_count': len(utterances)
    }

def sync_to_search_index(es_client: Elasticsearch, index_name: str, doc_id: str, data: Dict[str, Any]) -> bool:
    """Synchronize transcription results to Elasticsearch."""
    try:
        es_client.index(index=index_name, id=doc_id, body=data)
        return True
    except Exception as e:
        logger.error(f'Failed to sync to search index: {str(e)}')
        return False

def write_audit_log(transcription_id: str, metrics: Dict[str, Any], redacted_count: int) -> None:
    """Generate structured audit log for compliance reporting."""
    audit_entry = {
        'timestamp': datetime.now(timezone.utc).isoformat(),
        'transcription_id': transcription_id,
        'metrics': metrics,
        'redacted_entities': redacted_count,
        'compliance_status': 'processed',
        'data_retention_policy': 'standard'
    }
    with open('audit_logs.jsonl', 'a') as f:
        f.write(json.dumps(audit_entry) + '\n')

The post-processing pipeline normalizes timestamps to epoch format for efficient range queries in Elasticsearch. PII redaction uses compiled regex patterns. The quality metrics track average confidence scores and processing latency. The audit log writes structured JSON lines for compliance tracking. You must handle Elasticsearch connection timeouts and file write permissions in production.

Complete Working Example

The following FastAPI application integrates authentication, validation, webhook handling, post-processing, search synchronization, and audit logging into a single deployable service.

import os
import time
import logging
import json
from fastapi import FastAPI, Request, HTTPException
from genesyscloud.purecloud_platform_client import PureCloudPlatformClientV2
from genesyscloud.quality_api import TranscriptionApi
from elasticsearch import Elasticsearch
from typing import Dict, Any

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger('transcription_processor')
app = FastAPI()

# Initialize clients
genesys_client = PureCloudPlatformClientV2()
genesys_client.set_config_property('region', os.getenv('GENESYS_REGION', 'mypurecloud.com'))
genesys_client.set_config_property('client_id', os.getenv('GENESYS_CLIENT_ID'))
genesys_client.set_config_property('client_secret', os.getenv('GENESYS_CLIENT_SECRET'))
genesys_client.set_config_property('retry_on_rate_limit', True)
genesys_client.login_client_credential()

es_client = Elasticsearch(
    hosts=[os.getenv('ELASTICSEARCH_HOST', 'http://localhost:9200')],
    basic_auth=(os.getenv('ES_USER', 'elastic'), os.getenv('ES_PASS', '')),
    verify_certs=False
)

def validate_media_attributes(media: Dict[str, Any]) -> bool:
    supported_codecs = {'L16', 'G711MU', 'G711A', 'OPUS', 'MP3'}
    if media.get('duration', 0) > 14400:
        raise ValueError('Media duration exceeds 240 minutes')
    if media.get('size', 0) > 2147483648:
        raise ValueError('Media size exceeds 2 GB')
    if media.get('codec', '').upper() not in supported_codecs:
        raise ValueError('Unsupported codec')
    return True

@app.post('/webhook/transcription')
async def handle_transcription_webhook(request: Request):
    body = await request.json()
    transcription_id = body.get('transcriptionId')
    
    transcription_api = TranscriptionApi(genesys_client)
    transcription_response = transcription_api.get_quality_transcription(transcription_id)
    
    if transcription_response.status != 'completed':
        return {'status': 'pending'}
    
    start_time = time.time()
    utterances = transcription_response.utterances or []
    normalized = []
    redacted_total = 0
    
    pii_patterns = {
        'credit_card': r'\b(?:\d[ -]*?){13,16}\b',
        'ssn': r'\b\d{3}[- ]?\d{2}[- ]?\d{4}\b',
        'phone': r'\b(?:\+?1[-.\s]?)?\(?[0-9]{3}\)?[-.\s]?[0-9]{3}[-.\s]?[0-9]{4}\b'
    }
    
    for u in utterances:
        from datetime import datetime, timezone
        start_epoch = datetime.fromisoformat(u['start']).replace(tzinfo=timezone.utc).timestamp()
        end_epoch = datetime.fromisoformat(u['end']).replace(tzinfo=timezone.utc).timestamp()
        
        original_text = u['text']
        clean_text = original_text
        for pii_type, pattern in pii_patterns.items():
            matches = re.findall(pattern, clean_text)
            redacted_total += len(matches)
            clean_text = re.sub(pattern, f'[REDACTED_{pii_type.upper()}]', clean_text)
        
        normalized.append({
            'speaker': u.get('speaker', 'unknown'),
            'text': clean_text,
            'start_epoch': start_epoch,
            'end_epoch': end_epoch,
            'confidence': u.get('confidence', 0.0)
        })
    
    processing_time = time.time() - start_time
    confidences = [u.get('confidence', 0.0) for u in utterances if u.get('confidence') is not None]
    avg_confidence = sum(confidences) / len(confidences) if confidences else 0.0
    
    search_doc = {
        'transcription_id': transcription_id,
        'utterances': normalized,
        'metrics': {
            'average_confidence': round(avg_confidence, 4),
            'processing_latency_seconds': round(processing_time, 3),
            'utterance_count': len(normalized)
        },
        'indexed_at': datetime.now(timezone.utc).isoformat()
    }
    
    try:
        es_client.index(index='genesys_transcriptions', id=transcription_id, body=search_doc)
    except Exception as e:
        logger.error(f'Index sync failed: {str(e)}')
    
    audit_entry = {
        'timestamp': datetime.now(timezone.utc).isoformat(),
        'transcription_id': transcription_id,
        'redacted_entities': redacted_total,
        'average_confidence': round(avg_confidence, 4),
        'processing_latency_seconds': round(processing_time, 3)
    }
    with open('audit_logs.jsonl', 'a') as f:
        f.write(json.dumps(audit_entry) + '\n')
    
    return {'status': 'completed', 'redacted_count': redacted_total, 'confidence': round(avg_confidence, 4)}

@app.post('/submit-transcription')
async def submit_transcription(media_id: str, language: str = 'en-US'):
    transcription_api = TranscriptionApi(genesys_client)
    payload = {
        'mediaId': media_id,
        'language': language,
        'profanityFilter': 'on',
        'diarization': True,
        'languageModel': 'default'
    }
    try:
        result = transcription_api.post_quality_transcriptions(body=payload)
        return {'transcription_id': result.id, 'status': 'queued'}
    except Exception as e:
        raise HTTPException(status_code=500, detail=f'Transcription submission failed: {str(e)}')

Run the service with uvicorn main:app --host 0.0.0.0 --port 8000. The /submit-transcription endpoint accepts a media ID and queues the job. The /webhook/transcription endpoint processes completed jobs, applies post-processing, syncs to Elasticsearch, and writes audit logs.

Common Errors & Debugging

Error: 401 Unauthorized - Invalid or Expired Token

• Cause: OAuth token expired or client credentials mismatch.
• Fix: Verify GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET environment variables. Ensure the SDK is initialized with login_client_credential(). The SDK refreshes tokens automatically, but network restrictions may block /api/v2/oauth/token.
• Code: Add explicit token refresh before API calls if operating in isolated environments: genesys_client.login_client_credential()

Error: 400 Bad Request - Invalid Media Attributes

• Cause: Media duration exceeds 240 minutes, file size exceeds 2 GB, or codec is unsupported.
• Fix: Validate media attributes before submission. Check the GET /api/v2/quality/transcriptions response for detailed error messages.
• Code: Implement validate_media_attributes() function before calling post_quality_transcriptions().

Error: 429 Too Many Requests - Rate Limit Exceeded

• Cause: Exceeding Genesys Cloud API rate limits (typically 1000 requests per minute per client).
• Fix: Enable SDK retry logic with set_config_property('retry_on_rate_limit', True). Implement exponential backoff for bulk submissions.
• Code: The SDK handles retries automatically. Monitor X-RateLimit-Remaining headers in raw HTTP responses.

Error: 502 Bad Gateway - Transcription API Fetch Failed

• Cause: Webhook fires before transcription finalization or network timeout during GET /api/v2/quality/transcriptions/{id}.
• Fix: Implement retry logic with status verification. Check transcription status before processing.
• Code: Wrap the fetch call in a try-except block and return {'status': 'pending'} if the response is not completed.

Official References

• Genesys Cloud Quality Transcriptions API
• Genesys Cloud Python SDK Documentation
• Genesys Cloud Webhooks API
• OAuth 2.0 Client Credentials Flow