Poll Genesys Cloud Media Transcription Jobs with Python SDK
What You Will Build
- A production-ready polling engine that tracks Genesys Cloud transcription job status, applies exponential backoff, validates responses against media engine constraints, triggers webhooks on state changes, and generates structured audit logs.
- This solution uses the Genesys Cloud Media API (
/api/v2/media/recordings) and the official Python SDK (genesyscloud). - The implementation covers Python 3.9+ with type hints, robust error classification, and metrics tracking.
Prerequisites
- OAuth 2.0 client credentials application with the
media:viewscope - Genesys Cloud Python SDK version 2.0+ (
pip install genesyscloud requests) - Python 3.9 or higher
- Access to a Genesys Cloud environment with Media recording and transcription enabled
- A valid recording ID that has an active or pending transcription job
Authentication Setup
Genesys Cloud APIs require OAuth 2.0 bearer tokens. The Media API enforces strict scope validation. You must request the media:view scope to access recording and transcription metadata. The following token manager implements client credentials flow with automatic expiry tracking and safe refresh logic.
import time
import logging
import requests
from typing import Optional
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
class TokenManager:
def __init__(self, client_id: str, client_secret: str, region: str = "us-east-1"):
self.client_id = client_id
self.client_secret = client_secret
self.region = region
self.token_url = f"https://api.{region}.mypurecloud.com/oauth/token"
self.access_token: Optional[str] = None
self.token_expiry: float = 0.0
def get_token(self) -> str:
# Refresh token if expiry is within 60 seconds to prevent mid-request 401 errors
if time.time() < self.token_expiry - 60:
return self.access_token or ""
payload = {
"grant_type": "client_credentials",
"client_id": self.client_id,
"client_secret": self.client_secret
}
headers = {"Content-Type": "application/x-www-form-urlencoded"}
response = requests.post(self.token_url, data=payload, headers=headers)
response.raise_for_status()
data = response.json()
self.access_token = data["access_token"]
self.token_expiry = time.time() + data["expires_in"]
logger.info("OAuth token refreshed successfully.")
return self.access_token
The token manager caches the bearer token and calculates the absolute expiry timestamp. It refreshes the token sixty seconds before expiration to avoid race conditions during active polling loops. The media:view scope is implicitly granted based on the OAuth client configuration in the Genesys Cloud admin console.
Implementation
Step 1: Construct Poll Configuration and Validate Against Media Engine Constraints
Polling transcription jobs requires a structured directive that defines job references, status transitions, interval boundaries, and retry limits. The Media engine imposes constraints to prevent resource exhaustion. You must validate these parameters before initiating the polling loop.
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict
class TranscriptionStatus(str, Enum):
PROCESSING = "processing"
COMPLETED = "completed"
FAILED = "failed"
ERROR = "error"
@dataclass
class PollConfig:
job_id: str
base_interval: float = 5.0
max_retries: int = 40
max_backoff: float = 60.0
webhook_url: str = "https://example.com/status-webhook"
status_matrix: Dict[TranscriptionStatus, str] = field(default_factory=lambda: {
TranscriptionStatus.PROCESSING: "continue",
TranscriptionStatus.COMPLETED: "terminate_success",
TranscriptionStatus.FAILED: "terminate_error",
TranscriptionStatus.ERROR: "terminate_error"
})
def validate(self) -> bool:
if self.base_interval < 2.0:
raise ValueError("Base interval must be at least 2.0 seconds to respect media engine constraints.")
if self.max_retries < 1 or self.max_retries > 100:
raise ValueError("Max retries must be between 1 and 100 to prevent polling failure.")
if not self.webhook_url.startswith(("http://", "https://")):
raise ValueError("Webhook URL must be a valid HTTP or HTTPS endpoint.")
return True
The PollConfig dataclass encapsulates the poll payload structure. The base_interval enforces a minimum delay between requests to align with Genesys Cloud rate limiting policies. The max_retries caps the polling loop to prevent indefinite execution. The status_matrix maps expected transcription states to execution directives. Validation runs before the first request to fail fast on misconfigured parameters.
Step 2: Execute Atomic GET Operations with Format Verification
The Media API exposes transcription status through the recording resource. You must expand the transcription object to retrieve progress metrics and state flags. The SDK performs an atomic GET request to /api/v2/media/recordings/{id}. Format verification ensures the response matches the expected schema before processing.
from genesyscloud.platform_client_v2 import PureCloudPlatformClientV2
from genesyscloud.api.media import MediaApi
from genesyscloud.model import MediaRecording
class MediaTranscriptionPoller:
def __init__(self, config: PollConfig, token_manager: TokenManager, region: str = "us-east-1"):
self.config = config
self.token_manager = token_manager
self.region = region
self.client = PureCloudPlatformClientV2(region=self.region)
self.media_api = MediaApi(self.client)
self.metrics = {
"total_polls": 0,
"successful_polls": 0,
"failed_polls": 0,
"total_latency_ms": 0.0,
"backoff_triggers": 0
}
self.audit_log: list[dict] = []
def _log_audit(self, event: str, details: dict):
entry = {
"timestamp": time.time(),
"job_id": self.config.job_id,
"event": event,
"details": details
}
self.audit_log.append(entry)
logger.info(f"AUDIT: {event} | {details}")
def _verify_response_format(self, recording: MediaRecording) -> bool:
if recording is None:
raise ValueError("Null response object received from Media API.")
if not hasattr(recording, 'transcription') or recording.transcription is None:
raise ValueError("Schema mismatch: transcription object missing from recording payload.")
if not hasattr(recording.transcription, 'status'):
raise ValueError("Schema mismatch: transcription status field missing.")
return True
The _verify_response_format method inspects the deserialized SDK model. Genesys Cloud returns a MediaRecording object that contains a nested transcription model. If the transcription object is absent, the response violates the expected schema, and the poller raises an exception immediately. This prevents downstream logic from operating on incomplete data.
Step 3: Implement Exponential Backoff and Error Classification Pipelines
Transcription jobs transition through multiple states. The poller must classify error codes, track completion percentages, and apply exponential backoff when the Media engine returns throttling signals. The following method orchestrates the polling loop, handles HTTP status codes, and calculates backoff intervals.
def poll_job(self) -> dict:
self.config.validate()
self._log_audit("polling_started", {"retries_limit": self.config.max_retries})
current_interval = self.config.base_interval
retry_count = 0
last_status = None
while retry_count < self.config.max_retries:
start_time = time.perf_counter()
self.metrics["total_polls"] += 1
try:
token = self.token_manager.get_token()
self.client.set_access_token(token)
# Atomic GET operation with expand parameter
recording, response = self.media_api.get_media_recording(
self.config.job_id,
expand=["transcription"],
_return_http_data_only=False
)
latency_ms = (time.perf_counter() - start_time) * 1000
self.metrics["total_latency_ms"] += latency_ms
# Format verification pipeline
self._verify_response_format(recording)
current_status = recording.status.lower()
transcription_status = recording.transcription.status.lower()
progress = getattr(recording.transcription, 'progress', 0) or 0
self._log_audit("status_checked", {
"recording_status": current_status,
"transcription_status": transcription_status,
"progress_percent": progress,
"latency_ms": round(latency_ms, 2)
})
# Error code classification verification pipeline
if current_status in ["failed", "error"] or transcription_status in ["failed", "error"]:
self.metrics["failed_polls"] += 1
self._trigger_webhook(current_status, {"job_id": self.config.job_id, "error": True})
return {"status": "failed", "recording": recording.to_dict(), "metrics": self.metrics}
# Completion percentage checking
if current_status == "completed" or transcription_status == "completed":
self.metrics["successful_polls"] += 1
self._trigger_webhook("completed", {"job_id": self.config.job_id, "progress": 100})
return {"status": "completed", "recording": recording.to_dict(), "metrics": self.metrics}
# State transition tracking
if last_status != current_status:
self._log_audit("status_changed", {"from": last_status, "to": current_status})
last_status = current_status
# Reset interval on successful GET to avoid compounding backoff on healthy requests
current_interval = self.config.base_interval
except Exception as e:
latency_ms = (time.perf_counter() - start_time) * 1000
self.metrics["total_latency_ms"] += latency_ms
error_code = getattr(e, 'status_code', None)
# Automatic exponential backoff triggers for 429 and 5xx
if error_code == 429 or (error_code and 500 <= error_code < 600):
self.metrics["backoff_triggers"] += 1
retry_after = getattr(e, 'headers', {}).get('Retry-After', current_interval)
wait_time = min(float(retry_after) * (2 ** retry_count), self.config.max_backoff)
logger.warning(f"Rate limited or server error {error_code}. Backing off for {wait_time:.2f}s")
time.sleep(wait_time)
else:
logger.error(f"Unexpected error during poll: {e}")
self.metrics["failed_polls"] += 1
raise
finally:
retry_count += 1
# Continue polling if not terminated and within retry limits
if retry_count < self.config.max_retries and current_status not in ["completed", "failed", "error"]:
wait_time = min(current_interval * (2 ** retry_count), self.config.max_backoff)
time.sleep(wait_time)
current_interval = wait_time
self._log_audit("polling_exhausted", {"max_retries": self.config.max_retries})
return {"status": "timeout", "recording": None, "metrics": self.metrics}
The loop executes atomic GET requests and measures latency using time.perf_counter(). When the API returns a 429 Too Many Requests or a 5xx server error, the poller extracts the Retry-After header, applies an exponential multiplier based on the retry count, and caps the delay at max_backoff. This prevents cascading failures during Media scaling events. The completion percentage check evaluates the progress field on the transcription object. Error classification routes failed jobs to immediate termination while preserving audit trails.
Step 4: Synchronize Webhooks, Track Metrics, and Generate Audit Logs
External systems require synchronized status updates. The poller dispatches HTTP POST requests to a configured webhook endpoint whenever the transcription state changes. Metrics tracking calculates success rates and average latency. Audit logs persist every polling event for governance and debugging.
def _trigger_webhook(self, status: str, payload: dict):
try:
headers = {"Content-Type": "application/json", "X-Poll-Source": "media-transcription-poller"}
response = requests.post(self.config.webhook_url, json=payload, headers=headers, timeout=10)
response.raise_for_status()
except requests.RequestException as e:
logger.error(f"Webhook delivery failed: {e}")
self._log_audit("webhook_sent", {"status": status, "url": self.config.webhook_url})
def get_metrics_summary(self) -> dict:
total = self.metrics["total_polls"]
success_rate = (self.metrics["successful_polls"] / total * 100) if total > 0 else 0
avg_latency = (self.metrics["total_latency_ms"] / total) if total > 0 else 0
return {
"success_rate_percent": round(success_rate, 2),
"average_latency_ms": round(avg_latency, 2),
"backoff_triggers": self.metrics["backoff_triggers"],
"audit_entries": len(self.audit_log)
}
The webhook dispatcher uses a ten-second timeout to prevent blocking the main polling thread. It attaches a custom header for routing identification. The metrics summary calculates the completion success rate and average request latency. Governance requirements are satisfied through the structured audit_log list, which records timestamps, job identifiers, and state transitions for every poll cycle.
Complete Working Example
The following script combines all components into a single executable module. Replace the placeholder credentials and recording ID before execution.
import time
import logging
import requests
from typing import Optional
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# --- Token Manager ---
class TokenManager:
def __init__(self, client_id: str, client_secret: str, region: str = "us-east-1"):
self.client_id = client_id
self.client_secret = client_secret
self.region = region
self.token_url = f"https://api.{region}.mypurecloud.com/oauth/token"
self.access_token: Optional[str] = None
self.token_expiry: float = 0.0
def get_token(self) -> str:
if time.time() < self.token_expiry - 60:
return self.access_token or ""
payload = {
"grant_type": "client_credentials",
"client_id": self.client_id,
"client_secret": self.client_secret
}
headers = {"Content-Type": "application/x-www-form-urlencoded"}
response = requests.post(self.token_url, data=payload, headers=headers)
response.raise_for_status()
data = response.json()
self.access_token = data["access_token"]
self.token_expiry = time.time() + data["expires_in"]
return self.access_token
# --- Poll Configuration ---
class TranscriptionStatus(str, Enum):
PROCESSING = "processing"
COMPLETED = "completed"
FAILED = "failed"
ERROR = "error"
@dataclass
class PollConfig:
job_id: str
base_interval: float = 5.0
max_retries: int = 40
max_backoff: float = 60.0
webhook_url: str = "https://example.com/status-webhook"
status_matrix: Dict[TranscriptionStatus, str] = field(default_factory=lambda: {
TranscriptionStatus.PROCESSING: "continue",
TranscriptionStatus.COMPLETED: "terminate_success",
TranscriptionStatus.FAILED: "terminate_error",
TranscriptionStatus.ERROR: "terminate_error"
})
def validate(self) -> bool:
if self.base_interval < 2.0:
raise ValueError("Base interval must be at least 2.0 seconds to respect media engine constraints.")
if self.max_retries < 1 or self.max_retries > 100:
raise ValueError("Max retries must be between 1 and 100 to prevent polling failure.")
if not self.webhook_url.startswith(("http://", "https://")):
raise ValueError("Webhook URL must be a valid HTTP or HTTPS endpoint.")
return True
# --- Poller Implementation ---
from genesyscloud.platform_client_v2 import PureCloudPlatformClientV2
from genesyscloud.api.media import MediaApi
from genesyscloud.model import MediaRecording
class MediaTranscriptionPoller:
def __init__(self, config: PollConfig, token_manager: TokenManager, region: str = "us-east-1"):
self.config = config
self.token_manager = token_manager
self.region = region
self.client = PureCloudPlatformClientV2(region=self.region)
self.media_api = MediaApi(self.client)
self.metrics = {
"total_polls": 0,
"successful_polls": 0,
"failed_polls": 0,
"total_latency_ms": 0.0,
"backoff_triggers": 0
}
self.audit_log: list[dict] = []
def _log_audit(self, event: str, details: dict):
entry = {
"timestamp": time.time(),
"job_id": self.config.job_id,
"event": event,
"details": details
}
self.audit_log.append(entry)
logger.info(f"AUDIT: {event} | {details}")
def _verify_response_format(self, recording: MediaRecording) -> bool:
if recording is None:
raise ValueError("Null response object received from Media API.")
if not hasattr(recording, 'transcription') or recording.transcription is None:
raise ValueError("Schema mismatch: transcription object missing from recording payload.")
if not hasattr(recording.transcription, 'status'):
raise ValueError("Schema mismatch: transcription status field missing.")
return True
def _trigger_webhook(self, status: str, payload: dict):
try:
headers = {"Content-Type": "application/json", "X-Poll-Source": "media-transcription-poller"}
response = requests.post(self.config.webhook_url, json=payload, headers=headers, timeout=10)
response.raise_for_status()
except requests.RequestException as e:
logger.error(f"Webhook delivery failed: {e}")
self._log_audit("webhook_sent", {"status": status, "url": self.config.webhook_url})
def poll_job(self) -> dict:
self.config.validate()
self._log_audit("polling_started", {"retries_limit": self.config.max_retries})
current_interval = self.config.base_interval
retry_count = 0
last_status = None
while retry_count < self.config.max_retries:
start_time = time.perf_counter()
self.metrics["total_polls"] += 1
try:
token = self.token_manager.get_token()
self.client.set_access_token(token)
recording, response = self.media_api.get_media_recording(
self.config.job_id,
expand=["transcription"],
_return_http_data_only=False
)
latency_ms = (time.perf_counter() - start_time) * 1000
self.metrics["total_latency_ms"] += latency_ms
self._verify_response_format(recording)
current_status = recording.status.lower()
transcription_status = recording.transcription.status.lower()
progress = getattr(recording.transcription, 'progress', 0) or 0
self._log_audit("status_checked", {
"recording_status": current_status,
"transcription_status": transcription_status,
"progress_percent": progress,
"latency_ms": round(latency_ms, 2)
})
if current_status in ["failed", "error"] or transcription_status in ["failed", "error"]:
self.metrics["failed_polls"] += 1
self._trigger_webhook(current_status, {"job_id": self.config.job_id, "error": True})
return {"status": "failed", "recording": recording.to_dict(), "metrics": self.metrics}
if current_status == "completed" or transcription_status == "completed":
self.metrics["successful_polls"] += 1
self._trigger_webhook("completed", {"job_id": self.config.job_id, "progress": 100})
return {"status": "completed", "recording": recording.to_dict(), "metrics": self.metrics}
if last_status != current_status:
self._log_audit("status_changed", {"from": last_status, "to": current_status})
last_status = current_status
current_interval = self.config.base_interval
except Exception as e:
latency_ms = (time.perf_counter() - start_time) * 1000
self.metrics["total_latency_ms"] += latency_ms
error_code = getattr(e, 'status_code', None)
if error_code == 429 or (error_code and 500 <= error_code < 600):
self.metrics["backoff_triggers"] += 1
retry_after = getattr(e, 'headers', {}).get('Retry-After', current_interval)
wait_time = min(float(retry_after) * (2 ** retry_count), self.config.max_backoff)
logger.warning(f"Rate limited or server error {error_code}. Backing off for {wait_time:.2f}s")
time.sleep(wait_time)
else:
logger.error(f"Unexpected error during poll: {e}")
self.metrics["failed_polls"] += 1
raise
finally:
retry_count += 1
if retry_count < self.config.max_retries and current_status not in ["completed", "failed", "error"]:
wait_time = min(current_interval * (2 ** retry_count), self.config.max_backoff)
time.sleep(wait_time)
current_interval = wait_time
self._log_audit("polling_exhausted", {"max_retries": self.config.max_retries})
return {"status": "timeout", "recording": None, "metrics": self.metrics}
def get_metrics_summary(self) -> dict:
total = self.metrics["total_polls"]
success_rate = (self.metrics["successful_polls"] / total * 100) if total > 0 else 0
avg_latency = (self.metrics["total_latency_ms"] / total) if total > 0 else 0
return {
"success_rate_percent": round(success_rate, 2),
"average_latency_ms": round(avg_latency, 2),
"backoff_triggers": self.metrics["backoff_triggers"],
"audit_entries": len(self.audit_log)
}
# --- Execution ---
if __name__ == "__main__":
OAUTH_CLIENT_ID = "your-client-id"
OAUTH_CLIENT_SECRET = "your-client-secret"
RECORDING_ID = "your-recording-id"
REGION = "us-east-1"
token_mgr = TokenManager(OAUTH_CLIENT_ID, OAUTH_CLIENT_SECRET, REGION)
config = PollConfig(job_id=RECORDING_ID, base_interval=5.0, max_retries=40)
poller = MediaTranscriptionPoller(config, token_mgr, REGION)
result = poller.poll_job()
print(f"Final Status: {result['status']}")
print(f"Metrics: {poller.get_metrics_summary()}")
Common Errors & Debugging
Error: 401 Unauthorized
- Cause: The OAuth token has expired, the client credentials are incorrect, or the
media:viewscope is missing from the OAuth application configuration. - Fix: Verify the client ID and secret in the Genesys Cloud admin console. Ensure the OAuth application has the
media:viewscope assigned. Check that the token manager refreshes the token before expiry. - Code Fix: The
TokenManagerautomatically refreshes tokens sixty seconds before expiration. If you encounter repeated 401 errors, log the token expiry timestamp and verify network connectivity to the OAuth endpoint.
Error: 403 Forbidden
- Cause: The authenticated user or service account lacks permission to access the specific recording, or the recording belongs to a different Genesys Cloud organization.
- Fix: Assign the
Media Recording Viewerrole to the OAuth application or service user. Verify the recording ID matches the target environment. - Code Fix: Wrap the SDK call in a try-except block that catches
genesyscloud.api_exception.ApiExceptionwith status code 403 and logs the recording ID for audit review.
Error: 429 Too Many Requests
- Cause: The polling frequency exceeds the Media API rate limit, or concurrent pollers are targeting the same resource.
- Fix: Increase the
base_intervalinPollConfig. The implementation automatically parses theRetry-Afterheader and applies exponential backoff. - Code Fix: The
poll_jobmethod detects 429 responses, extracts the retry delay, and sleeps before the next iteration. Monitor thebackoff_triggersmetric to adjust intervals if throttling occurs frequently.
Error: Schema Mismatch (Transcription Object Missing)
- Cause: The recording does not have an active transcription job, or the
expand=["transcription"]parameter was omitted. - Fix: Ensure the recording was created with transcription enabled. Always pass
expand=["transcription"]to theget_media_recordingmethod. - Code Fix: The
_verify_response_formatmethod explicitly checks for the presence of thetranscriptionattribute and raises a descriptive error if absent.