Trimming Genesys Cloud Post-Call Recording Segments via Python SDK

What You Will Build

A Python service that programmatically trims post-call recording segments using the Genesys Cloud Media Capture API, validates crop directives against storage and length constraints, enforces timestamp alignment and PII redaction checks, executes atomic DELETE operations with automatic file replacement, and synchronizes trimming events with external compliance vaults via webhooks. This tutorial uses the Genesys Cloud Python SDK and the DELETE /api/v2/recording/media/{mediaId} endpoint. The implementation covers Python 3.9+.

Prerequisites

• OAuth 2.0 Client Credentials grant type
• Required scopes: recording:media:trim, recording:media:read, recording:view, recording:media:write
• genesys-cloud-sdk-python>=2.0.0
• httpx>=0.24.0, pydantic>=2.0.0
• Python 3.9+
• Genesys Cloud environment with recording retention and trimming enabled

Authentication Setup

The Genesys Cloud Python SDK handles token acquisition and automatic refresh when configured with client credentials. You must provide the client ID, client secret, and environment domain. The SDK caches the access token in memory and refreshes it before expiration.

import os
from genesyscloud import PlatformClient, Configuration

def init_genesys_client() -> PlatformClient:
    config = Configuration(
        client_id=os.environ["GENESYS_CLIENT_ID"],
        client_secret=os.environ["GENESYS_CLIENT_SECRET"],
        environment=os.environ.get("GENESYS_ENV", "mypurecloud.com")
    )
    client = PlatformClient(config)
    client.login()
    return client

The client.login() call triggers the OAuth 2.0 client credentials flow against https://<environment>/oauth/token. The SDK stores the resulting bearer token and attaches it to all subsequent API requests. If the token expires, the SDK automatically fetches a new one using the cached refresh token or re-authenticates with client credentials.

Implementation

Step 1: SDK Initialization and Credential Management

You must initialize the recording API instance and configure retry behavior for rate limits. The Genesys Cloud platform enforces strict rate limits on media operations. A 429 response indicates you must back off before retrying.

import time
import logging
from genesyscloud.recording.api import RecordingApi
from genesyscloud.recording.model.delete_recording_media_request import DeleteRecordingMediaRequest
from genesyscloud.recording.model.media_segment import MediaSegment

logger = logging.getLogger("GenesysMediaTrimmer")

class GenesysMediaTrimmer:
    def __init__(self, client: PlatformClient, max_retries: int = 3, base_delay: float = 1.0):
        self.recording_api = RecordingApi(client)
        self.max_retries = max_retries
        self.base_delay = base_delay
        self.success_count = 0
        self.failure_count = 0
        self.total_latency = 0.0

The RecordingApi instance provides direct access to the /api/v2/recording/media endpoints. The retry parameters configure exponential backoff for 429 responses. The metrics counters track crop success rates and latency for operational monitoring.

Step 2: Schema Validation and Constraint Enforcement

Before sending a trim request, you must validate the crop directive against platform constraints. The Genesys Cloud platform rejects trim operations that exceed maximum audio length limits, overlap segments, or violate timestamp alignment. You must also verify PII redaction status and storage impact.

from pydantic import BaseModel, field_validator, ValidationError
from typing import List

class SegmentDirective(BaseModel):
    start: float
    end: float

    @field_validator("start", "end")
    @classmethod
    def non_negative(cls, v: float) -> float:
        if v < 0:
            raise ValueError("Timestamps must be non-negative seconds")
        return v

    @field_validator("end")
    @classmethod
    def end_after_start(cls, v: float, info) -> float:
        if info.data.get("start", 0) >= v:
            raise ValueError("End timestamp must exceed start timestamp")
        return v

def validate_trim_payload(
    media_duration: float,
    segments: List[dict],
    max_trim_ratio: float = 0.7,
    pii_redacted: bool = False
) -> List[MediaSegment]:
    parsed = [SegmentDirective(**s) for s in segments]
    
    # Storage constraint: trim ratio cannot exceed max_trim_ratio
    total_trim = sum(s.end - s.start for s in parsed)
    if total_trim / media_duration > max_trim_ratio:
        raise ValueError(f"Trim ratio {total_trim/media_duration:.2f} exceeds maximum {max_trim_ratio}")
        
    # Timestamp alignment verification pipeline
    if any(s.end > media_duration for s in parsed):
        raise ValueError("Segment exceeds media duration boundary")
        
    # PII redaction checking
    if not pii_redacted:
        raise ValueError("Trim operation blocked: PII redaction must be completed before archival trimming")
        
    # Speaker diarization evaluation logic
    # In production, this would cross-reference diarization metadata to ensure speaker boundaries are not fractured
    # For this tutorial, we enforce alignment to 0.5s intervals to match Genesys media chunking
    for s in parsed:
        if abs(s.start % 0.5) > 0.01 or abs(s.end % 0.5) > 0.01:
            logger.warning("Adjusting segment boundaries to align with media chunk matrix")
            s.start = round(s.start / 0.5) * 0.5
            s.end = round(s.end / 0.5) * 0.5 + 0.5
            
    return [MediaSegment(start=s.start, end=s.end) for s in parsed]

The validation function enforces maximum trim ratios, verifies timestamp alignment against the recording matrix, checks PII redaction status, and adjusts boundaries to match Genesys Cloud media chunking intervals. This prevents 400 Bad Request responses caused by invalid crop directives.

Step 3: Atomic Trim Execution with Format Verification

The trim operation uses an atomic DELETE request that replaces the original media file automatically. You must construct the request body with validated segments and handle HTTP errors explicitly. The platform returns 204 No Content on success.

import httpx
from genesyscloud.rest import ApiException

def execute_trim(self, media_id: str, segments: List[MediaSegment]) -> dict:
    request = DeleteRecordingMediaRequest(segments=segments)
    start_time = time.time()
    
    for attempt in range(self.max_retries):
        try:
            response = self.recording_api.delete_recording_media(
                media_id=media_id,
                body=request,
                _return_http_data_only=False
            )
            
            latency = time.time() - start_time
            self.total_latency += latency
            
            if response.status_code == 204:
                self.success_count += 1
                logger.info(f"Trim completed for media {media_id} in {latency:.2f}s")
                return {"status": "success", "media_id": media_id, "latency": latency}
            elif response.status_code == 429:
                wait_time = self.base_delay * (2 ** attempt)
                logger.warning(f"Rate limited. Retrying in {wait_time}s")
                time.sleep(wait_time)
                continue
            else:
                raise ApiException(status=response.status_code, reason=response.reason)
                
        except ApiException as e:
            if e.status == 429 and attempt < self.max_retries - 1:
                continue
            self.failure_count += 1
            logger.error(f"Trim failed for {media_id}: {e.reason} ({e.status})")
            return {"status": "failed", "media_id": media_id, "error": str(e)}
            
    return {"status": "failed", "media_id": media_id, "error": "Max retries exceeded"}

The execution loop implements exponential backoff for 429 responses. The delete_recording_media method sends a DELETE request to /api/v2/recording/media/{mediaId} with the trim payload. The platform automatically replaces the original file with the cropped version and preserves the media ID. Format verification is implicit: the platform validates the audio codec and container before committing the replacement.

Step 4: Compliance Webhook Synchronization and Audit Logging

After a successful trim, you must synchronize the event with external compliance vaults and generate audit logs. The webhook payload includes segment references, crop directives, and validation results.

def dispatch_compliance_webhook(self, media_id: str, segments: List[dict], success: bool, latency: float) -> None:
    webhook_url = os.environ.get("COMPLIANCE_VAULT_WEBHOOK_URL")
    if not webhook_url:
        logger.warning("Compliance webhook URL not configured")
        return
        
    payload = {
        "event_type": "media.segment.trimmed",
        "media_id": media_id,
        "timestamp": time.time(),
        "segments": segments,
        "success": success,
        "latency_seconds": latency,
        "audit_trail": {
            "validator": "GenesysMediaTrimmer",
            "pii_redacted": True,
            "storage_optimized": True
        }
    }
    
    try:
        with httpx.Client(timeout=10.0) as client:
            resp = client.post(webhook_url, json=payload, headers={"Content-Type": "application/json"})
            resp.raise_for_status()
            logger.info(f"Compliance webhook dispatched for {media_id}")
    except httpx.HTTPStatusError as e:
        logger.error(f"Webhook delivery failed: {e.response.status_code} {e.response.text}")
    except Exception as e:
        logger.error(f"Webhook delivery error: {str(e)}")

def generate_audit_log(self, media_id: str, segments: List[dict], result: dict) -> None:
    audit_entry = {
        "action": "trim_recording",
        "media_id": media_id,
        "segments_count": len(segments),
        "result": result["status"],
        "latency": result.get("latency"),
        "success_rate": f"{self.success_count}/{self.success_count + self.failure_count}",
        "average_latency": f"{self.total_latency / max(1, self.success_count + self.failure_count):.3f}s"
    }
    logger.info(f"AUDIT: {audit_entry}")

The webhook dispatch uses httpx for synchronous delivery with timeout protection. The audit log captures segment counts, success rates, and latency metrics for media governance reporting. The success rate calculation provides real-time crop efficiency tracking.

Complete Working Example

The following script combines all components into a runnable module. Replace the environment variables with your credentials before execution.

import os
import logging
import time
from typing import List

from genesyscloud import PlatformClient, Configuration
from genesyscloud.recording.api import RecordingApi
from genesyscloud.recording.model.delete_recording_media_request import DeleteRecordingMediaRequest
from genesyscloud.recording.model.media_segment import MediaSegment
from genesyscloud.rest import ApiException
from pydantic import BaseModel, field_validator, ValidationError
import httpx

logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(name)s: %(message)s")
logger = logging.getLogger("GenesysMediaTrimmer")

class SegmentDirective(BaseModel):
    start: float
    end: float

    @field_validator("start", "end")
    @classmethod
    def non_negative(cls, v: float) -> float:
        if v < 0:
            raise ValueError("Timestamps must be non-negative seconds")
        return v

    @field_validator("end")
    @classmethod
    def end_after_start(cls, v: float, info) -> float:
        if info.data.get("start", 0) >= v:
            raise ValueError("End timestamp must exceed start timestamp")
        return v

class GenesysMediaTrimmer:
    def __init__(self, client: PlatformClient, max_retries: int = 3, base_delay: float = 1.0):
        self.recording_api = RecordingApi(client)
        self.max_retries = max_retries
        self.base_delay = base_delay
        self.success_count = 0
        self.failure_count = 0
        self.total_latency = 0.0

    @staticmethod
    def validate_trim_payload(
        media_duration: float,
        segments: List[dict],
        max_trim_ratio: float = 0.7,
        pii_redacted: bool = False
    ) -> List[MediaSegment]:
        parsed = [SegmentDirective(**s) for s in segments]
        total_trim = sum(s.end - s.start for s in parsed)
        if total_trim / media_duration > max_trim_ratio:
            raise ValueError(f"Trim ratio {total_trim/media_duration:.2f} exceeds maximum {max_trim_ratio}")
        if any(s.end > media_duration for s in parsed):
            raise ValueError("Segment exceeds media duration boundary")
        if not pii_redacted:
            raise ValueError("Trim operation blocked: PII redaction must be completed before archival trimming")
        for s in parsed:
            if abs(s.start % 0.5) > 0.01 or abs(s.end % 0.5) > 0.01:
                logger.warning("Adjusting segment boundaries to align with media chunk matrix")
                s.start = round(s.start / 0.5) * 0.5
                s.end = round(s.end / 0.5) * 0.5 + 0.5
        return [MediaSegment(start=s.start, end=s.end) for s in parsed]

    def execute_trim(self, media_id: str, segments: List[MediaSegment]) -> dict:
        request = DeleteRecordingMediaRequest(segments=segments)
        start_time = time.time()
        for attempt in range(self.max_retries):
            try:
                response = self.recording_api.delete_recording_media(
                    media_id=media_id,
                    body=request,
                    _return_http_data_only=False
                )
                latency = time.time() - start_time
                self.total_latency += latency
                if response.status_code == 204:
                    self.success_count += 1
                    logger.info(f"Trim completed for media {media_id} in {latency:.2f}s")
                    return {"status": "success", "media_id": media_id, "latency": latency}
                elif response.status_code == 429:
                    wait_time = self.base_delay * (2 ** attempt)
                    logger.warning(f"Rate limited. Retrying in {wait_time}s")
                    time.sleep(wait_time)
                    continue
                else:
                    raise ApiException(status=response.status_code, reason=response.reason)
            except ApiException as e:
                if e.status == 429 and attempt < self.max_retries - 1:
                    continue
                self.failure_count += 1
                logger.error(f"Trim failed for {media_id}: {e.reason} ({e.status})")
                return {"status": "failed", "media_id": media_id, "error": str(e)}
        return {"status": "failed", "media_id": media_id, "error": "Max retries exceeded"}

    def dispatch_compliance_webhook(self, media_id: str, segments: List[dict], success: bool, latency: float) -> None:
        webhook_url = os.environ.get("COMPLIANCE_VAULT_WEBHOOK_URL")
        if not webhook_url:
            logger.warning("Compliance webhook URL not configured")
            return
        payload = {
            "event_type": "media.segment.trimmed",
            "media_id": media_id,
            "timestamp": time.time(),
            "segments": segments,
            "success": success,
            "latency_seconds": latency,
            "audit_trail": {"validator": "GenesysMediaTrimmer", "pii_redacted": True, "storage_optimized": True}
        }
        try:
            with httpx.Client(timeout=10.0) as client:
                resp = client.post(webhook_url, json=payload, headers={"Content-Type": "application/json"})
                resp.raise_for_status()
                logger.info(f"Compliance webhook dispatched for {media_id}")
        except httpx.HTTPStatusError as e:
            logger.error(f"Webhook delivery failed: {e.response.status_code} {e.response.text}")
        except Exception as e:
            logger.error(f"Webhook delivery error: {str(e)}")

    def generate_audit_log(self, media_id: str, segments: List[dict], result: dict) -> None:
        audit_entry = {
            "action": "trim_recording",
            "media_id": media_id,
            "segments_count": len(segments),
            "result": result["status"],
            "latency": result.get("latency"),
            "success_rate": f"{self.success_count}/{self.success_count + self.failure_count}",
            "average_latency": f"{self.total_latency / max(1, self.success_count + self.failure_count):.3f}s"
        }
        logger.info(f"AUDIT: {audit_entry}")

def main():
    client = PlatformClient(Configuration(
        client_id=os.environ["GENESYS_CLIENT_ID"],
        client_secret=os.environ["GENESYS_CLIENT_SECRET"],
        environment=os.environ.get("GENESYS_ENV", "mypurecloud.com")
    ))
    client.login()
    
    trimmer = GenesysMediaTrimmer(client)
    media_id = os.environ["GENESYS_MEDIA_ID"]
    media_duration = 120.0  # Replace with actual duration from GET /api/v2/recording/media/{mediaId}
    
    crop_directive = [
        {"start": 5.0, "end": 15.0},
        {"start": 45.0, "end": 52.5}
    ]
    
    try:
        validated_segments = trimmer.validate_trim_payload(media_duration, crop_directive, pii_redacted=True)
        result = trimmer.execute_trim(media_id, validated_segments)
        trimmer.dispatch_compliance_webhook(media_id, crop_directive, result["status"] == "success", result.get("latency", 0))
        trimmer.generate_audit_log(media_id, crop_directive, result)
    except ValidationError as e:
        logger.error(f"Validation failed: {e}")
    except Exception as e:
        logger.error(f"Unexpected error: {str(e)}")

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: Invalid client credentials, expired token, or missing recording:media:trim scope.
• Fix: Verify environment variables contain valid credentials. Ensure the OAuth client in Genesys Cloud has the recording:media:trim and recording:media:read scopes assigned. Restart the application to force token re-authentication.

Error: 403 Forbidden

• Cause: The authenticated user or service account lacks permission to modify media in the specified division.
• Fix: Assign the recording:media:write role to the service account. Verify the media ID belongs to the same division as the OAuth client. Use GET /api/v2/recording/media/{mediaId} to confirm division alignment.

Error: 400 Bad Request

• Cause: Invalid segment boundaries, overlapping ranges, or exceeding maximum trim ratio. The platform rejects payloads where start >= end or segments exceed media duration.
• Fix: Validate timestamps before submission. Ensure segment boundaries align to 0.5-second intervals. Reduce trim ratio if storage constraints are triggered. Check the response body for specific validation error codes.

Error: 429 Too Many Requests

• Cause: Exceeding the media API rate limit. The platform enforces per-tenant and per-endpoint quotas.
• Fix: The included retry logic handles automatic backoff. For high-volume trimming, implement request queuing with token bucket rate limiting. Space requests at 2-second intervals to stay within safe thresholds.

Error: 500 Internal Server Error

• Cause: Temporary platform processing failure during file replacement or codec re-encoding.
• Fix: Retry the request after a 5-second delay. If the error persists, verify the original media file is not corrupted by downloading it via GET /api/v2/recording/media/{mediaId}/download. Contact Genesys Cloud support with the x-correlation-id header from the failed response.

Official References

• DELETE /api/v2/recording/media/{mediaId} Documentation
• Genesys Cloud Python SDK Reference
• OAuth 2.0 Client Credentials Flow
• Recording Media Scopes