Requesting Genesys Cloud Media Transcription Jobs via REST API with Python

What You Will Build

• A Python module that validates audio media constraints, constructs transcription requests with language matrices and PII redaction policies, and initiates atomic transcription jobs against Genesys Cloud.
• This tutorial uses the Genesys Cloud Media API (/api/v2/media/transcriptions) and OAuth 2.0 client credentials authentication.
• The implementation is written in Python 3.10+ using httpx for HTTP operations, pydantic for schema validation, and structured logging for audit compliance.

Prerequisites

• OAuth client type: Confidential client registered in Genesys Cloud with media:transcription:write and media:media:read scopes.
• API version: Genesys Cloud REST API v2.
• Runtime: Python 3.10 or higher.
• External dependencies: httpx>=0.27.0, pydantic>=2.6.0, python-dotenv>=1.0.0, fastapi>=0.110.0, uvicorn>=0.29.0.

Authentication Setup

Genesys Cloud uses a standard OAuth 2.0 client credentials flow. The token endpoint is /api/v2/oauth/token. Tokens expire after one hour, so production code must cache the token and validate expiration before reuse. The following function handles token acquisition with automatic caching and scope enforcement.

import os
import time
import httpx
from typing import Optional
from dotenv import load_dotenv

load_dotenv()

GENESYS_BASE_URL = os.getenv("GENESYS_BASE_URL", "https://api.mypurecloud.com")
OAUTH_TOKEN_URL = f"{GENESYS_BASE_URL}/api/v2/oauth/token"
CLIENT_ID = os.getenv("GENESYS_CLIENT_ID")
CLIENT_SECRET = os.getenv("GENESYS_CLIENT_SECRET")
REQUIRED_SCOPES = ["media:transcription:write", "media:media:read"]

class TokenCache:
    def __init__(self):
        self._token: Optional[str] = None
        self._expires_at: float = 0.0

    def is_valid(self) -> bool:
        return self._token is not None and time.time() < self._expires_at - 60

    def store(self, token: str, expires_in: int):
        self._token = token
        self._expires_at = time.time() + expires_in

    def get(self) -> Optional[str]:
        return self._token

token_cache = TokenCache()

def fetch_oauth_token() -> str:
    if token_cache.is_valid():
        return token_cache.get()

    response = httpx.post(
        OAUTH_TOKEN_URL,
        data={
            "grant_type": "client_credentials",
            "client_id": CLIENT_ID,
            "client_secret": CLIENT_SECRET,
            "scope": " ".join(REQUIRED_SCOPES)
        },
        headers={"Content-Type": "application/x-www-form-urlencoded"}
    )
    response.raise_for_status()
    payload = response.json()
    
    token_cache.store(payload["access_token"], payload["expires_in"])
    return payload["access_token"]

The fetch_oauth_token function validates the cached token against an expiration buffer of sixty seconds. This prevents edge-case failures where a token expires mid-request. The scope parameter is space-delimited as required by the Genesys OAuth specification.

Implementation

Step 1: Media Validation and Codec Verification

Genesys Cloud rejects transcription jobs if the media format is unsupported or exceeds plan-based duration limits. You must verify the media asset before submission. The /api/v2/media/{mediaId} endpoint returns format, codec, and duration metadata.

from pydantic import BaseModel, Field
from typing import List
import logging

logger = logging.getLogger("transcription_audit")
logging.basicConfig(level=logging.INFO, format="%(asctime)s | %(levelname)s | %(message)s")

class MediaConstraint(BaseModel):
    allowed_codecs: List[str] = Field(default=["pcm", "mp3", "opus", "vorbis", "webm"])
    max_duration_seconds: int = Field(default=1800, description="Standard plan limit")

def validate_media(media_id: str, constraints: MediaConstraint) -> bool:
    token = fetch_oauth_token()
    response = httpx.get(
        f"{GENESYS_BASE_URL}/api/v2/media/{media_id}",
        headers={"Authorization": f"Bearer {token}"}
    )
    
    if response.status_code == 404:
        logger.error("Media asset not found: %s", media_id)
        return False
    response.raise_for_status()
    
    media_data = response.json()
    duration = media_data.get("duration", 0)
    codec = media_data.get("codec", "").lower()
    format_type = media_data.get("format", "").lower()
    
    if duration > constraints.max_duration_seconds:
        logger.warning("Media duration %s exceeds limit %s", duration, constraints.max_duration_seconds)
        return False
        
    if codec not in constraints.allowed_codecs:
        logger.warning("Unsupported codec %s for media %s", codec, media_id)
        return False
        
    logger.info("Media validation passed: %s [%s/%s]", media_id, format_type, codec)
    return True

The validation function checks three critical attributes. Duration limits prevent queue rejection. Codec verification ensures the media contains decodable audio streams. Format validation confirms container compatibility. You must adjust max_duration_seconds if your Genesys Cloud plan supports extended transcription windows.

Step 2: Construct Transcription Payload with Language Matrix and Redaction

The transcription request payload requires a media identifier, a language list, and an optional redaction policy. Language matrices allow fallback processing when primary language detection fails. Redaction policies reference pre-configured PII rules in Genesys Cloud.

from typing import Optional

class TranscriptionPayload(BaseModel):
    media_id: str
    languages: List[str]
    redaction_policy_id: Optional[str] = None
    webhook_uri: Optional[str] = None
    enable_speaker_identification: bool = True

    def to_request_body(self) -> dict:
        body: dict = {
            "mediaId": self.media_id,
            "languages": self.languages
        }
        
        if self.redaction_policy_id:
            body["redactionPolicyId"] = self.redaction_policy_id
            
        if self.webhook_uri:
            body["webhooks"] = [
                {
                    "uri": self.webhook_uri,
                    "events": ["transcription.completed", "transcription.failed"]
                }
            ]
            
        body["settings"] = {
            "enableSpeakerIdentification": self.enable_speaker_identification
        }
        
        return body

The to_request_body method constructs the exact JSON structure expected by /api/v2/media/transcriptions. The languages array accepts ISO 639-1 codes with region suffixes. Genesys processes the first language as primary and attempts fallback detection for subsequent entries. The redactionPolicyId must reference an active policy created in the Genesys Cloud admin console under Conversations > Transcription > Redaction Policies.

Step 3: Atomic Job Initiation with Rate Limit Handling

Transcription jobs are initiated via an atomic POST operation. Genesys Cloud enforces strict rate limits on media endpoints. The following function implements exponential backoff for 429 responses and validates the 202 Accepted response.

import json
import time

def initiate_transcription(payload: TranscriptionPayload) -> str:
    token = fetch_oauth_token()
    headers = {
        "Authorization": f"Bearer {token}",
        "Content-Type": "application/json"
    }
    
    max_retries = 3
    retry_delay = 2.0
    
    for attempt in range(max_retries):
        response = httpx.post(
            f"{GENESYS_BASE_URL}/api/v2/media/transcriptions",
            headers=headers,
            json=payload.to_request_body()
        )
        
        if response.status_code == 429:
            retry_after = float(response.headers.get("Retry-After", retry_delay))
            logger.warning("Rate limited. Retrying in %s seconds (attempt %s/%s)", retry_after, attempt + 1, max_retries)
            time.sleep(retry_after)
            retry_delay *= 2
            continue
            
        if response.status_code == 400:
            logger.error("Bad request payload: %s", response.text)
            raise ValueError("Invalid transcription payload structure")
            
        if response.status_code == 403:
            logger.error("Forbidden. Verify OAuth scopes include media:transcription:write")
            raise PermissionError("Insufficient API permissions")
            
        response.raise_for_status()
        
        result = response.json()
        transcription_id = result.get("transcriptionId")
        logger.info("Transcription job initiated: %s", transcription_id)
        return transcription_id
        
    raise RuntimeError("Max retries exceeded due to rate limiting")

The POST operation returns a transcriptionId immediately. The actual transcription runs asynchronously. The retry loop respects the Retry-After header when present. A 400 response typically indicates an invalid mediaId, unsupported language code, or malformed webhook URI. A 403 response indicates missing OAuth scopes.

Step 4: Webhook Callback Handler for Search Indexing and Latency Tracking

Genesys Cloud delivers transcription results via HTTP POST to the configured webhook URI. The handler must parse the event payload, calculate processing latency, extract confidence metrics, and synchronize results with external systems.

from datetime import datetime, timezone

def process_webhook_event(payload: dict) -> None:
    event_type = payload.get("eventType")
    data = payload.get("data", {})
    transcription_id = data.get("transcriptionId")
    status = data.get("status")
    
    if event_type != "transcription.completed" and event_type != "transcription.failed":
        return
        
    result = data.get("result", {})
    media_id = result.get("mediaId")
    completed_at = datetime.fromisoformat(data.get("completedAt", datetime.now(timezone.utc).isoformat())).timestamp()
    started_at = datetime.fromisoformat(data.get("startedAt", completed_at)).timestamp()
    latency_seconds = completed_at - started_at
    
    confidence_scores = []
    transcripts = result.get("transcripts", [])
    for segment in transcripts:
        conf = segment.get("confidence", 0.0)
        confidence_scores.append(conf)
        
    avg_confidence = sum(confidence_scores) / len(confidence_scores) if confidence_scores else 0.0
    
    audit_record = {
        "transcriptionId": transcription_id,
        "mediaId": media_id,
        "status": status,
        "latencySeconds": latency_seconds,
        "averageConfidence": avg_confidence,
        "processedAt": datetime.now(timezone.utc).isoformat(),
        "redacted": result.get("redacted", False)
    }
    
    logger.info("Audit log: %s", json.dumps(audit_record))
    
    if status == "completed" and transcripts:
        index_search_documents(transcription_id, media_id, transcripts)
    else:
        logger.warning("Transcription failed or returned empty results: %s", transcription_id)

def index_search_documents(transcription_id: str, media_id: str, transcripts: list) -> None:
    # Simulated external search indexer synchronization
    document_payload = {
        "id": transcription_id,
        "mediaReference": media_id,
        "content": " ".join(t.get("text", "") for t in transcripts),
        "confidence": transcripts[0].get("confidence", 0.0),
        "indexedAt": datetime.now(timezone.utc).isoformat()
    }
    logger.info("Pushing to search index: %s", json.dumps(document_payload))

The webhook handler calculates latency using startedAt and completedAt timestamps provided by Genesys Cloud. Confidence scores are extracted from each transcript segment. The index_search_documents function demonstrates how to transform transcription output into a searchable document format. Production systems should implement idempotency checks using transcriptionId to prevent duplicate indexing.

Step 5: Automated Transcription Requester Class

The following class encapsulates validation, payload construction, job initiation, and audit logging into a single reusable component.

class TranscriptionRequester:
    def __init__(self, webhook_uri: str, max_duration: int = 1800):
        self.webhook_uri = webhook_uri
        self.constraints = MediaConstraint(max_duration_seconds=max_duration)
        
    def request_transcription(self, media_id: str, languages: List[str], redaction_policy_id: Optional[str] = None) -> str:
        if not validate_media(media_id, self.constraints):
            raise ValueError("Media validation failed")
            
        payload = TranscriptionPayload(
            media_id=media_id,
            languages=languages,
            redaction_policy_id=redaction_policy_id,
            webhook_uri=self.webhook_uri
        )
        
        return initiate_transcription(payload)

This requester enforces media constraints before submission, constructs the payload with webhook routing, and returns the job identifier for downstream tracking. You can instantiate this class in batch processors or event-driven pipelines.

Complete Working Example

The following script demonstrates end-to-end usage. It loads environment variables, initializes the requester, submits a transcription job, and provides a FastAPI webhook endpoint for callback synchronization.

import httpx
import uvicorn
from fastapi import FastAPI, Request
import json

app = FastAPI()

REQUESTER = TranscriptionRequester(
    webhook_uri="https://your-domain.com/api/webhooks/genesys-transcription",
    max_duration=2400
)

@app.post("/api/webhooks/genesys-transcription")
async def webhook_receiver(request: Request):
    payload = await request.json()
    process_webhook_event(payload)
    return {"status": "accepted"}

if __name__ == "__main__":
    import sys
    
    if len(sys.argv) > 1 and sys.argv[1] == "run":
        uvicorn.run(app, host="0.0.0.0", port=8000)
    else:
        # Example execution path
        try:
            job_id = REQUESTER.request_transcription(
                media_id="a1b2c3d4-e5f6-7890-abcd-ef1234567890",
                languages=["en-US", "es-ES"],
                redaction_policy_id="redaction-policy-uuid-123"
            )
            print(f"Job submitted: {job_id}")
        except Exception as e:
            print(f"Submission failed: {e}")

Run the script with python transcription_requester.py run to start the webhook server. Execute the submission logic by removing the if __name__ guard or triggering it via an external orchestrator. Replace placeholder identifiers with valid Genesys Cloud media IDs and policy UUIDs.

Common Errors & Debugging

Error: 400 Bad Request

• Cause: Invalid mediaId, unsupported language code, malformed webhook URI, or missing redaction policy UUID.
• Fix: Verify the media ID exists via GET /api/v2/media/{mediaId}. Ensure language codes follow BCP 47 format. Validate webhook URIs use HTTPS and accept POST requests. Confirm redaction policies are active in Genesys Cloud.
• Code Fix: Add payload schema validation using Pydantic before submission. Log the exact response.text from the API to identify the missing field.

Error: 403 Forbidden

• Cause: OAuth token lacks media:transcription:write scope, or the client ID is restricted to read-only operations.
• Fix: Regenerate the OAuth token with the correct scope string. Verify client permissions in Genesys Cloud under Administration > Security > Applications.
• Code Fix: The fetch_oauth_token function already requests both required scopes. If the error persists, check for tenant-level API restrictions.

Error: 429 Too Many Requests

• Cause: Exceeding the media transcription endpoint rate limit (typically 10 requests per second per tenant).
• Fix: Implement exponential backoff. Distribute submissions across multiple seconds using a queue.
• Code Fix: The initiate_transcription function includes a retry loop with Retry-After header parsing. Increase max_retries or add a message queue for batch processing.

Error: Webhook Delivery Failures

• Cause: Target server returns non-2xx status, TLS handshake failure, or timeout exceeding Genesys Cloud delivery window.
• Fix: Ensure the webhook endpoint responds with 200 or 204 within two seconds. Use asynchronous processing for heavy indexing tasks. Verify TLS 1.2 compliance.
• Code Fix: The FastAPI handler returns {"status": "accepted"} immediately. Offload search indexing and audit logging to background tasks or message brokers.

Official References

• Media Transcriptions API Documentation
• OAuth 2.0 Client Credentials Flow
• Genesys Cloud Python SDK
• Webhook Event Schemas
• Redaction Policy Configuration