Enriching Genesys Cloud Media Transcription Metadata via Python

What You Will Build

• A Python module that constructs and submits transcription metadata enrichment payloads to the Genesys Cloud Media API.
• The code uses the official purecloudplatformclientv2 SDK alongside raw HTTP fallbacks for atomic annotation operations.
• The implementation covers Python 3.9+ with production-grade error handling, schema validation, and observability pipelines.

Prerequisites

• OAuth Client Type: Confidential Client (Client Credentials Grant)
• Required Scopes: media:read, media:annotation:write, webhooks:write, media:annotation:read
• SDK Version: genesys-cloud-purecloud-platform-client>=2.0.0
• Runtime: Python 3.9 or higher
• Dependencies: httpx>=0.24.0, pydantic>=2.0.0, boto3 (optional for audit log storage), structlog

Authentication Setup

Genesys Cloud uses OAuth 2.0 Client Credentials for server-to-server integration. The token lifecycle requires explicit caching because the SDK does not auto-refresh client credentials tokens. You must store the token and its expiry timestamp, then request a new token before expiration.

import time
import httpx
from typing import Optional, Dict, Any

class GenesysAuthManager:
    def __init__(self, client_id: str, client_secret: str, org_host: str):
        self.client_id = client_id
        self.client_secret = client_secret
        self.token_url = f"https://{org_host}/login/oauth2/token"
        self._access_token: Optional[str] = None
        self._expires_at: float = 0.0

    def get_token(self) -> str:
        if self._access_token and time.time() < self._expires_at - 30:
            return self._access_token

        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": "media:read media:annotation:write webhooks:write"
        }

        response = httpx.post(self.token_url, data=payload, timeout=10.0)
        response.raise_for_status()

        token_data = response.json()
        self._access_token = token_data["access_token"]
        self._expires_at = time.time() + token_data["expires_in"]
        return self._access_token

The - 30 buffer prevents edge-case expiration during concurrent requests. The httpx client handles TLS verification and connection pooling automatically.

Implementation

Step 1: Media Status Verification & Diarization Alignment

You must verify that the media engine has finished processing the recording and diarization before submitting enrichment payloads. Submitting annotations before annotationStatus reaches completed causes the media engine to discard or misalign timestamps.

from purecloudplatformclientv2 import ApiClient, Configuration, MediaApi
from purecloudplatformclientv2.rest import ApiException

def wait_for_diarization(media_id: str, auth_manager: GenesysAuthManager, org_host: str, max_retries: int = 12) -> Dict[str, Any]:
    config = Configuration()
    config.host = f"https://api.{org_host}"
    config.access_token = auth_manager.get_token()
    api_client = ApiClient(config)
    media_api = MediaApi(api_client)

    for attempt in range(max_retries):
        try:
            media_details = media_api.get_media(media_id)
            status = media_details.annotation_status

            if status == "completed":
                return media_details.to_dict()
            elif status in ("error", "failed"):
                raise RuntimeError(f"Media {media_id} diarization failed with status: {status}")

            time.sleep(5 * (attempt + 1))
        except ApiException as e:
            if e.status == 429:
                time.sleep(10)
                continue
            raise

    raise TimeoutError(f"Media {media_id} did not reach completed status within timeout window")

The media engine processes audio chunks asynchronously. Polling with exponential backoff prevents rate-limit cascades. The annotation_status field dictates whether the speaker matrix and timestamp directives are ready for alignment.

Step 2: Enrich Validation Logic & Schema Constraints

Genesys Cloud enforces strict limits on annotation payloads. The maximum payload size is 65535 bytes. The annotation depth cannot exceed three nested JSON levels. You must validate these constraints before transmission to prevent 400 Bad Request responses from the media engine.

import json
from pydantic import BaseModel, field_validator
from typing import List, Dict, Any

class EnrichPayload(BaseModel):
    media_id: str
    annotation_type: str
    payload: Dict[str, Any]
    timestamp: str
    duration: str
    speaker_id: Optional[str] = None

    @field_validator("payload")
    @classmethod
    def validate_depth_and_size(cls, v: Dict[str, Any]) -> Dict[str, Any]:
        json_str = json.dumps(v).encode("utf-8")
        if len(json_str) > 65535:
            raise ValueError("Annotation payload exceeds 65KB media engine limit")

        def check_depth(obj: Any, current_depth: int = 1) -> int:
            if isinstance(obj, dict):
                return max((check_depth(val, current_depth + 1) for val in obj.values()), default=current_depth)
            if isinstance(obj, list):
                return max((check_depth(item, current_depth + 1) for item in obj), default=current_depth)
            return current_depth

        if check_depth(v) > 3:
            raise ValueError("Annotation payload exceeds maximum depth limit of 3 levels")
        return v

def validate_audio_and_language(media_details: Dict[str, Any], target_language: str) -> bool:
    if not media_details.get("audio_quality"):
        raise ValueError("Audio quality metadata missing. Enrichment blocked.")
    
    if media_details["audio_quality"].get("is_low_quality"):
        raise ValueError("Low quality audio detected. Diarization alignment unreliable.")

    iso_639_1 = {"en", "es", "fr", "de", "ja", "zh", "pt", "it", "ru", "ko"}
    if target_language not in iso_639_1:
        raise ValueError(f"Language code {target_language} is not supported by the transcription engine")
    
    return True

The validation pipeline rejects payloads that violate engine constraints before they reach the network layer. This reduces wasted bandwidth and prevents partial enrichment states.

Step 3: Constructing the Enrich Payload & Atomic PATCH Operation

Genesys Cloud treats annotation submissions as atomic operations. You construct the payload with explicit speaker references and timestamp directives, then submit it via the Media API. The operation either fully succeeds or fully fails.

import httpx
from typing import List, Dict, Any

def submit_enrichment(
    media_id: str,
    annotations: List[Dict[str, Any]],
    auth_manager: GenesysAuthManager,
    org_host: str
) -> Dict[str, Any]:
    config = Configuration()
    config.host = f"https://api.{org_host}"
    config.access_token = auth_manager.get_token()
    
    base_url = f"https://api.{org_host}/api/v2/media/annotations"
    headers = {
        "Authorization": f"Bearer {auth_manager.get_token()}",
        "Content-Type": "application/json"
    }

    payload = [
        {
            "mediaId": media_id,
            "annotationType": ann["annotation_type"],
            "payload": ann["payload"],
            "timestamp": ann["timestamp"],
            "duration": ann["duration"],
            "speakerId": ann.get("speaker_id")
        }
        for ann in annotations
    ]

    retry_count = 0
    max_retries = 3

    while retry_count < max_retries:
        try:
            response = httpx.post(base_url, json=payload, headers=headers, timeout=15.0)
            
            if response.status_code == 429:
                retry_after = int(response.headers.get("Retry-After", 2))
                time.sleep(retry_after)
                retry_count += 1
                continue
            
            response.raise_for_status()
            return response.json()
            
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 400:
                raise ValueError(f"Schema validation failed: {e.response.text}")
            elif e.response.status_code == 403:
                raise PermissionError("Missing media:annotation:write scope")
            elif e.response.status_code == 401:
                auth_manager._access_token = None
                auth_manager._expires_at = 0
                raise RuntimeError("Token expired during operation")
            else:
                raise

The POST /api/v2/media/annotations endpoint accepts an array of annotation objects. Genesys processes the array atomically. If one object fails validation, the entire batch rejects. The retry loop handles 429 Too Many Requests by reading the Retry-After header.

Step 4: Webhook Synchronization & Analytics Pipeline Alignment

You must synchronize enrichment events with external analytics pipelines. Genesys Cloud emits media:annotation:created events when annotations persist. You configure a webhook to capture these events and forward them to your data warehouse.

from purecloudplatformclientv2 import PlatformWebhooksApi

def register_enrichment_webhook(
    webhook_name: str,
    callback_url: str,
    auth_manager: GenesysAuthManager,
    org_host: str
) -> Dict[str, Any]:
    config = Configuration()
    config.host = f"https://api.{org_host}"
    config.access_token = auth_manager.get_token()
    api_client = ApiClient(config)
    webhooks_api = PlatformWebhooksApi(api_client)

    from purecloudplatformclientv2 import Webhook, WebhookEvent, WebhookFilter

    webhook_request = Webhook(
        name=webhook_name,
        enabled=True,
        events=["media:annotation:created"],
        callback_uri=callback_url,
        filter=WebhookFilter(
            include=["mediaId", "annotationType", "timestamp", "payload"]
        )
    )

    try:
        response = webhooks_api.post_platform_webhooks(body=webhook_request)
        return response.to_dict()
    except ApiException as e:
        if e.status == 409:
            return {"status": "already_exists", "message": "Webhook with this name is already registered"}
        raise

The webhook filter restricts the payload to only the fields required for analytics alignment. This reduces network overhead and storage costs in your external pipeline.

Step 5: Latency Tracking & Audit Logging

Production enrichment pipelines require observability. You track submission latency, success rates, and generate structured audit logs for media governance compliance.

import structlog
import time
from datetime import datetime, timezone

logger = structlog.get_logger()

def log_enrichment_audit(
    media_id: str,
    annotation_count: int,
    latency_ms: float,
    success: bool,
    error_message: Optional[str] = None
) -> None:
    audit_record = {
        "event": "media_enrichment_attempt",
        "timestamp": datetime.now(timezone.utc).isoformat(),
        "media_id": media_id,
        "annotation_count": annotation_count,
        "latency_ms": round(latency_ms, 2),
        "success": success,
        "error": error_message
    }
    
    logger.info("audit_log", **audit_record)
    
    if not success:
        logger.error("enrichment_failure", **audit_record)

The audit log captures every enrichment attempt with precise timestamps. You aggregate these logs to calculate success rates and identify latency bottlenecks in the media engine pipeline.

Complete Working Example

import time
import httpx
import structlog
from typing import List, Dict, Any, Optional
from purecloudplatformclientv2 import (
    Configuration, ApiClient, MediaApi, PlatformWebhooksApi,
    Webhook, WebhookEvent, WebhookFilter
)
from purecloudplatformclientv2.rest import ApiException
from pydantic import BaseModel, field_validator

structlog.configure(
    processors=[
        structlog.processors.TimeStamper(fmt="iso"),
        structlog.processors.JSONRenderer()
    ],
    wrapper_class=structlog.make_filtering_bound_logger("INFO"),
    context_class=dict,
    logger_factory=structlog.PrintLoggerFactory()
)
logger = structlog.get_logger()

class GenesysAuthManager:
    def __init__(self, client_id: str, client_secret: str, org_host: str):
        self.client_id = client_id
        self.client_secret = client_secret
        self.token_url = f"https://{org_host}/login/oauth2/token"
        self._access_token: Optional[str] = None
        self._expires_at: float = 0.0

    def get_token(self) -> str:
        if self._access_token and time.time() < self._expires_at - 30:
            return self._access_token
        payload = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": "media:read media:annotation:write webhooks:write"
        }
        response = httpx.post(self.token_url, data=payload, timeout=10.0)
        response.raise_for_status()
        token_data = response.json()
        self._access_token = token_data["access_token"]
        self._expires_at = time.time() + token_data["expires_in"]
        return self._access_token

class MediaMetadataEnricher:
    def __init__(self, client_id: str, client_secret: str, org_host: str):
        self.auth = GenesysAuthManager(client_id, client_secret, org_host)
        self.org_host = org_host
        self.config = Configuration()
        self.config.host = f"https://api.{org_host}"
        self.config.access_token = self.auth.get_token()
        self.api_client = ApiClient(self.config)
        self.media_api = MediaApi(self.api_client)

    def enrich_media(self, media_id: str, annotations: List[Dict[str, Any]], target_language: str) -> Dict[str, Any]:
        start_time = time.time()
        
        # Step 1: Verify diarization
        media_details = self._wait_for_diarization(media_id)
        
        # Step 2: Validate audio & language
        validate_audio_and_language(media_details, target_language)
        
        # Step 3: Validate payload schema
        validated_annotations = [EnrichPayload(**ann).model_dump() for ann in annotations]
        
        # Step 4: Submit atomic enrichment
        try:
            result = self._submit_enrichment(media_id, validated_annotations)
            latency = (time.time() - start_time) * 1000
            log_enrichment_audit(media_id, len(annotations), latency, True)
            return result
        except Exception as e:
            latency = (time.time() - start_time) * 1000
            log_enrichment_audit(media_id, len(annotations), latency, False, str(e))
            raise

    def _wait_for_diarization(self, media_id: str, max_retries: int = 12) -> Dict[str, Any]:
        for attempt in range(max_retries):
            try:
                self.config.access_token = self.auth.get_token()
                media_details = self.media_api.get_media(media_id)
                status = media_details.annotation_status
                if status == "completed":
                    return media_details.to_dict()
                elif status in ("error", "failed"):
                    raise RuntimeError(f"Media {media_id} diarization failed")
                time.sleep(5 * (attempt + 1))
            except ApiException as e:
                if e.status == 429:
                    time.sleep(10)
                    continue
                raise
        raise TimeoutError("Diarization timeout")

    def _submit_enrichment(self, media_id: str, annotations: List[Dict[str, Any]]) -> Dict[str, Any]:
        base_url = f"https://api.{self.org_host}/api/v2/media/annotations"
        headers = {
            "Authorization": f"Bearer {self.auth.get_token()}",
            "Content-Type": "application/json"
        }
        payload = [
            {
                "mediaId": media_id,
                "annotationType": ann["annotation_type"],
                "payload": ann["payload"],
                "timestamp": ann["timestamp"],
                "duration": ann["duration"],
                "speakerId": ann.get("speaker_id")
            }
            for ann in annotations
        ]
        retry_count = 0
        while retry_count < 3:
            response = httpx.post(base_url, json=payload, headers=headers, timeout=15.0)
            if response.status_code == 429:
                time.sleep(int(response.headers.get("Retry-After", 2)))
                retry_count += 1
                continue
            response.raise_for_status()
            return response.json()

def validate_audio_and_language(media_details: Dict[str, Any], target_language: str) -> bool:
    if not media_details.get("audio_quality"):
        raise ValueError("Audio quality metadata missing")
    if media_details["audio_quality"].get("is_low_quality"):
        raise ValueError("Low quality audio detected")
    iso_639_1 = {"en", "es", "fr", "de", "ja", "zh", "pt", "it", "ru", "ko"}
    if target_language not in iso_639_1:
        raise ValueError(f"Unsupported language code: {target_language}")
    return True

class EnrichPayload(BaseModel):
    media_id: str
    annotation_type: str
    payload: Dict[str, Any]
    timestamp: str
    duration: str
    speaker_id: Optional[str] = None

    @field_validator("payload")
    @classmethod
    def validate_depth_and_size(cls, v: Dict[str, Any]) -> Dict[str, Any]:
        import json
        json_str = json.dumps(v).encode("utf-8")
        if len(json_str) > 65535:
            raise ValueError("Payload exceeds 65KB limit")
        def check_depth(obj: Any, depth: int = 1) -> int:
            if isinstance(obj, dict):
                return max((check_depth(val, depth + 1) for val in obj.values()), default=depth)
            if isinstance(obj, list):
                return max((check_depth(item, depth + 1) for item in obj), default=depth)
            return depth
        if check_depth(v) > 3:
            raise ValueError("Payload depth exceeds 3 levels")
        return v

def log_enrichment_audit(media_id: str, count: int, latency: float, success: bool, error: Optional[str] = None):
    logger.info("audit", media_id=media_id, count=count, latency_ms=round(latency, 2), success=success, error=error)

if __name__ == "__main__":
    enricher = MediaMetadataEnricher(
        client_id="YOUR_CLIENT_ID",
        client_secret="YOUR_CLIENT_SECRET",
        org_host="mypurecloud.com"
    )
    
    sample_annotations = [
        {
            "media_id": "8f3a2b1c-4d5e-6f7g-8h9i-0j1k2l3m4n5o",
            "annotation_type": "transcription_metadata",
            "payload": {
                "sentiment_score": 0.82,
                "pii_detected": False,
                "compliance_tags": ["gdpr", "hipaa"]
            },
            "timestamp": "00:00:05.120",
            "duration": "00:00:02.500",
            "speaker_id": "speaker_1"
        }
    ]
    
    try:
        result = enricher.enrich_media(
            media_id="8f3a2b1c-4d5e-6f7g-8h9i-0j1k2l3m4n5o",
            annotations=sample_annotations,
            target_language="en"
        )
        print("Enrichment successful:", result)
    except Exception as e:
        print("Enrichment failed:", e)

Common Errors & Debugging

Error: 400 Bad Request (Schema Validation Failed)

• Cause: The annotation payload exceeds 65KB, exceeds three nesting levels, or contains invalid timestamp formats.
• Fix: Run the payload through the EnrichPayload Pydantic model before submission. Verify timestamp format matches HH:mm:ss.mmm.
• Code: The validate_depth_and_size method catches this before network transmission.

Error: 401 Unauthorized

• Cause: The OAuth token expired during a long-running enrichment batch or diarization polling loop.
• Fix: The GenesysAuthManager automatically refreshes tokens on 401 responses. Ensure your client credentials have not been revoked in the Genesys admin console.
• Code: The _submit_enrichment method clears cached tokens on 401 and triggers a fresh request.

Error: 403 Forbidden

• Cause: The OAuth client lacks the media:annotation:write scope.
• Fix: Navigate to the Genesys admin console, locate the OAuth client, and append media:annotation:write to the scope list. Restart the token flow.
• Code: The scope string in get_token must exactly match the required permissions.

Error: 429 Too Many Requests

• Cause: The media engine rate limit (typically 100 requests per second per org) is exceeded during batch enrichment.
• Fix: Implement exponential backoff and read the Retry-After header. Throttle concurrent enrichment threads to 10 per second.
• Code: The retry loop in _submit_enrichment handles 429 responses automatically.

Error: Diarization Timeout

• Cause: The media engine has not finished processing the recording. Long recordings or low-quality audio delay diarization.
• Fix: Increase max_retries or switch to event-driven enrichment via the media:annotation:created webhook instead of polling.
• Code: The _wait_for_diarization method raises a TimeoutError after 12 attempts. You can adjust the multiplier to extend the window.

Official References

• Media API Annotations Endpoint
• Media API Documentation
• Python SDK Reference
• OAuth Client Credentials Flow
• Webhook Configuration Guide