Retrieving Genesys Cloud Archived Media Transcripts via Archiving API with Python SDK

What You Will Build

This tutorial builds a Python module that queries Genesys Cloud archived conversations, retrieves transcripts with explicit language and diarization configurations, validates payload schemas against storage constraints, verifies timestamp alignment, and exports structured results with audit logging and external callback integration. The implementation uses the Genesys Cloud Archiving API and the official genesyscloud Python SDK. The code runs in Python 3.10 or higher.

Prerequisites

• OAuth2 confidential client with scope: archive:read
• Genesys Cloud Python SDK: genesyscloud>=2.2.0
• Runtime: Python 3.10+
• External dependencies: httpx>=0.25.0, pydantic>=2.0.0, structlog>=23.0.0
• Network access to Genesys Cloud API endpoints

Authentication Setup

The Genesys Cloud API requires OAuth2 bearer tokens. For server-to-server integrations, use the client credentials grant. The following example fetches a token and caches it with automatic refresh logic using httpx.

import httpx
import time
from typing import Optional

class GenesysAuthManager:
    def __init__(self, base_url: str, client_id: str, client_secret: str, scope: str = "archive:read"):
        self.base_url = base_url.rstrip("/")
        self.client_id = client_id
        self.client_secret = client_secret
        self.scope = scope
        self.token: Optional[str] = None
        self.expires_at: float = 0.0

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

        url = f"{self.base_url}/api/v2/oauth/token"
        headers = {"Content-Type": "application/x-www-form-urlencoded"}
        data = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": self.scope
        }

        with httpx.Client(timeout=15.0) as client:
            response = client.post(url, headers=headers, data=data)
            response.raise_for_status()
            payload = response.json()

        self.token = payload["access_token"]
        self.expires_at = time.time() + payload["expires_in"]
        return self.token

Implementation

Step 1: Initialize Platform Client and Configure OAuth

The genesyscloud SDK requires a PlatformClient instance. Attach the authentication manager to handle token resolution automatically.

from genesyscloud.platform_client import PlatformClient
from genesyscloud.archivemanagement_api import ArchivemanagementApi

def create_archivemanagement_client(auth: GenesysAuthManager) -> ArchivemanagementApi:
    platform = PlatformClient(auth.get_token, auth.base_url)
    platform.set_oauth_client_id(auth.client_id)
    platform.set_oauth_client_secret(auth.client_secret)
    return ArchivemanagementApi(platform)

Step 2: Query Archive Identifiers with Schema Validation

Before retrieving transcripts, query the archiving engine for conversation IDs. The query payload must respect storage engine constraints, including maximum payload size and retention windows. The SDK uses ConversationDetailQueryRequest.

from genesyscloud.archivemanagement_api.models import ConversationDetailQueryRequest
from datetime import datetime, timedelta

def build_archive_query_request(
    start_time: datetime,
    end_time: datetime,
    max_results: int = 50
) -> ConversationDetailQueryRequest:
    # Storage engine constraint: date range must not exceed 30 days
    if (end_time - start_time).days > 30:
        raise ValueError("Query date range exceeds storage engine constraint of 30 days.")

    # Max transcription length limit validation occurs at retrieval, but we cap query size
    if max_results > 100:
        raise ValueError("Query limit exceeds maximum allowed batch size of 100.")

    query_body = ConversationDetailQueryRequest(
        size=max_results,
        date_range_query={
            "from": start_time.isoformat() + "Z",
            "to": end_time.isoformat() + "Z"
        },
        query_type="conversation",
        transcript_config={
            "language": "en",
            "diarization": True,
            "speaker_identification": True
        }
    )
    return query_body

Step 3: Retrieve Transcripts with Diarization and Alignment Directives

The retrieval endpoint executes an atomic GET operation. You must pass the archive ID and validate the response format. The SDK handles serialization, but you must verify diarization triggers and segment alignment directives in the returned payload.

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

def retrieve_archive_with_retry(
    api_client: ArchivemanagementApi,
    archive_id: str,
    max_retries: int = 3
) -> Dict[str, Any]:
    for attempt in range(1, max_retries + 1):
        try:
            # Atomic GET: /api/v2/archivemanagement/details/{id}
            response = api_client.get_archivemanagement_details(
                id=archive_id,
                transcript_config={
                    "language": "en",
                    "diarization": True,
                    "speaker_identification": True
                }
            )
            return response.to_dict()
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 429:
                wait_time = 2 ** attempt
                time.sleep(wait_time)
                continue
            elif e.response.status_code in (401, 403):
                raise PermissionError(f"Authentication or authorization failed: {e.response.status_code}")
            elif e.response.status_code == 404:
                raise FileNotFoundError(f"Archive ID {archive_id} not found.")
            raise
        except Exception as e:
            raise RuntimeError(f"Unexpected retrieval error on attempt {attempt}: {e}")
    raise RuntimeError("Max retries exceeded for 429 rate limit.")

Step 4: Validate Codec Compatibility and Timestamp Synchronization

Transcripts must align with media segments. Validate codec compatibility and verify that transcript start/end timestamps fall within media boundaries. This prevents playback drift during archiving scaling.

def validate_transcript_alignment(details: Dict[str, Any]) -> Dict[str, Any]:
    validation_report = {
        "valid": True,
        "codec_compatible": True,
        "timestamps_synced": True,
        "drift_detected": False,
        "errors": []
    }

    media_list = details.get("media", [])
    transcripts = details.get("transcripts", [])

    if not media_list:
        validation_report["valid"] = False
        validation_report["errors"].append("No media segments found in archive.")
        return validation_report

    # Codec compatibility check
    supported_codecs = {"pcmu", "pcma", "opus", "g729", "l16"}
    for media in media_list:
        codec = media.get("codec", "").lower()
        if codec and codec not in supported_codecs:
            validation_report["codec_compatible"] = False
            validation_report["errors"].append(f"Unsupported codec: {codec}")

    # Timestamp synchronization verification pipeline
    for transcript in transcripts:
        start = transcript.get("start")
        end = transcript.get("end")
        speaker = transcript.get("speaker")

        if start is None or end is None:
            validation_report["timestamps_synced"] = False
            validation_report["errors"].append("Missing start or end timestamp in transcript segment.")
            continue

        if end <= start:
            validation_report["timestamps_synced"] = False
            validation_report["errors"].append(f"Invalid timestamp range: start={start}, end={end}")

        # Segment alignment directive validation
        if not speaker:
            validation_report["drift_detected"] = True
            validation_report["errors"].append("Speaker diarization failed to assign speaker label.")

    validation_report["valid"] = not validation_report["errors"]
    return validation_report

Step 5: Process Results with Callback Handlers and Audit Logging

Implement a retrieval pipeline that tracks latency, calculates transcription accuracy rates, generates audit logs, and triggers external search indexing callbacks.

import structlog
import json
from typing import Callable, Optional
from datetime import datetime

logger = structlog.get_logger()

class TranscriptRetriever:
    def __init__(
        self,
        api_client: ArchivemanagementApi,
        search_index_callback: Optional[Callable[[Dict[str, Any]], None]] = None
    ):
        self.api_client = api_client
        self.search_index_callback = search_index_callback
        self.audit_log: List[Dict[str, Any]] = []
        self.latency_metrics: List[float] = []
        self.accuracy_metrics: List[float] = []

    def process_archive(self, archive_id: str) -> Dict[str, Any]:
        start_time = time.time()
        logger.info("archive_retrieval_started", archive_id=archive_id)

        details = retrieve_archive_with_retry(self.api_client, archive_id)
        validation = validate_transcript_alignment(details)

        latency = time.time() - start_time
        self.latency_metrics.append(latency)

        # Extract transcripts and compute accuracy rate (based on confidence field if present)
        transcripts = details.get("transcripts", [])
        confidence_scores = [t.get("confidence", 0.0) for t in transcripts if "confidence" in t]
        avg_accuracy = sum(confidence_scores) / len(confidence_scores) if confidence_scores else 0.0
        self.accuracy_metrics.append(avg_accuracy)

        audit_entry = {
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "archive_id": archive_id,
            "status": "success" if validation["valid"] else "validation_failed",
            "latency_ms": round(latency * 1000, 2),
            "transcript_count": len(transcripts),
            "avg_confidence": round(avg_accuracy, 4),
            "validation": validation
        }
        self.audit_log.append(audit_entry)
        logger.info("archive_retrieval_completed", archive_id=archive_id, latency_ms=audit_entry["latency_ms"])

        # Trigger external search indexing callback
        if self.search_index_callback:
            self.search_index_callback({
                "archive_id": archive_id,
                "transcripts": transcripts,
                "metadata": details.get("conversation", {}),
                "validation": validation
            })

        return {
            "archive_id": archive_id,
            "transcripts": transcripts,
            "validation": validation,
            "audit": audit_entry
        }

Complete Working Example

The following script combines all components into a production-ready module. Replace the placeholder credentials and run the script against your Genesys Cloud environment.

import httpx
import time
import structlog
from typing import Callable, Optional, Dict, Any, List
from datetime import datetime, timedelta
from genesyscloud.platform_client import PlatformClient
from genesyscloud.archivemanagement_api import ArchivemanagementApi
from genesyscloud.archivemanagement_api.models import ConversationDetailQueryRequest

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(),
    cache_logger_on_first_use=True
)
logger = structlog.get_logger()

class GenesysAuthManager:
    def __init__(self, base_url: str, client_id: str, client_secret: str, scope: str = "archive:read"):
        self.base_url = base_url.rstrip("/")
        self.client_id = client_id
        self.client_secret = client_secret
        self.scope = scope
        self.token: Optional[str] = None
        self.expires_at: float = 0.0

    def get_token(self) -> str:
        if self.token and time.time() < self.expires_at - 30:
            return self.token
        url = f"{self.base_url}/api/v2/oauth/token"
        headers = {"Content-Type": "application/x-www-form-urlencoded"}
        data = {
            "grant_type": "client_credentials",
            "client_id": self.client_id,
            "client_secret": self.client_secret,
            "scope": self.scope
        }
        with httpx.Client(timeout=15.0) as client:
            response = client.post(url, headers=headers, data=data)
            response.raise_for_status()
            payload = response.json()
        self.token = payload["access_token"]
        self.expires_at = time.time() + payload["expires_in"]
        return self.token

def create_archivemanagement_client(auth: GenesysAuthManager) -> ArchivemanagementApi:
    platform = PlatformClient(auth.get_token, auth.base_url)
    platform.set_oauth_client_id(auth.client_id)
    platform.set_oauth_client_secret(auth.client_secret)
    return ArchivemanagementApi(platform)

def build_archive_query_request(start_time: datetime, end_time: datetime, max_results: int = 50) -> ConversationDetailQueryRequest:
    if (end_time - start_time).days > 30:
        raise ValueError("Query date range exceeds storage engine constraint of 30 days.")
    if max_results > 100:
        raise ValueError("Query limit exceeds maximum allowed batch size of 100.")
    return ConversationDetailQueryRequest(
        size=max_results,
        date_range_query={"from": start_time.isoformat() + "Z", "to": end_time.isoformat() + "Z"},
        query_type="conversation",
        transcript_config={"language": "en", "diarization": True, "speaker_identification": True}
    )

def retrieve_archive_with_retry(api_client: ArchivemanagementApi, archive_id: str, max_retries: int = 3) -> Dict[str, Any]:
    for attempt in range(1, max_retries + 1):
        try:
            response = api_client.get_archivemanagement_details(
                id=archive_id,
                transcript_config={"language": "en", "diarization": True, "speaker_identification": True}
            )
            return response.to_dict()
        except httpx.HTTPStatusError as e:
            if e.response.status_code == 429:
                time.sleep(2 ** attempt)
                continue
            elif e.response.status_code in (401, 403):
                raise PermissionError(f"Authentication or authorization failed: {e.response.status_code}")
            elif e.response.status_code == 404:
                raise FileNotFoundError(f"Archive ID {archive_id} not found.")
            raise
        except Exception as e:
            raise RuntimeError(f"Unexpected retrieval error on attempt {attempt}: {e}")
    raise RuntimeError("Max retries exceeded for 429 rate limit.")

def validate_transcript_alignment(details: Dict[str, Any]) -> Dict[str, Any]:
    validation_report = {"valid": True, "codec_compatible": True, "timestamps_synced": True, "drift_detected": False, "errors": []}
    media_list = details.get("media", [])
    transcripts = details.get("transcripts", [])
    if not media_list:
        validation_report["valid"] = False
        validation_report["errors"].append("No media segments found in archive.")
        return validation_report
    supported_codecs = {"pcmu", "pcma", "opus", "g729", "l16"}
    for media in media_list:
        codec = media.get("codec", "").lower()
        if codec and codec not in supported_codecs:
            validation_report["codec_compatible"] = False
            validation_report["errors"].append(f"Unsupported codec: {codec}")
    for transcript in transcripts:
        start = transcript.get("start")
        end = transcript.get("end")
        speaker = transcript.get("speaker")
        if start is None or end is None:
            validation_report["timestamps_synced"] = False
            validation_report["errors"].append("Missing start or end timestamp in transcript segment.")
            continue
        if end <= start:
            validation_report["timestamps_synced"] = False
            validation_report["errors"].append(f"Invalid timestamp range: start={start}, end={end}")
        if not speaker:
            validation_report["drift_detected"] = True
            validation_report["errors"].append("Speaker diarization failed to assign speaker label.")
    validation_report["valid"] = not validation_report["errors"]
    return validation_report

class TranscriptRetriever:
    def __init__(self, api_client: ArchivemanagementApi, search_index_callback: Optional[Callable[[Dict[str, Any]], None]] = None):
        self.api_client = api_client
        self.search_index_callback = search_index_callback
        self.audit_log: List[Dict[str, Any]] = []
        self.latency_metrics: List[float] = []
        self.accuracy_metrics: List[float] = []

    def process_archive(self, archive_id: str) -> Dict[str, Any]:
        start_time = time.time()
        logger.info("archive_retrieval_started", archive_id=archive_id)
        details = retrieve_archive_with_retry(self.api_client, archive_id)
        validation = validate_transcript_alignment(details)
        latency = time.time() - start_time
        self.latency_metrics.append(latency)
        transcripts = details.get("transcripts", [])
        confidence_scores = [t.get("confidence", 0.0) for t in transcripts if "confidence" in t]
        avg_accuracy = sum(confidence_scores) / len(confidence_scores) if confidence_scores else 0.0
        self.accuracy_metrics.append(avg_accuracy)
        audit_entry = {
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "archive_id": archive_id,
            "status": "success" if validation["valid"] else "validation_failed",
            "latency_ms": round(latency * 1000, 2),
            "transcript_count": len(transcripts),
            "avg_confidence": round(avg_accuracy, 4),
            "validation": validation
        }
        self.audit_log.append(audit_entry)
        logger.info("archive_retrieval_completed", archive_id=archive_id, latency_ms=audit_entry["latency_ms"])
        if self.search_index_callback:
            self.search_index_callback({"archive_id": archive_id, "transcripts": transcripts, "metadata": details.get("conversation", {}), "validation": validation})
        return {"archive_id": archive_id, "transcripts": transcripts, "validation": validation, "audit": audit_entry}

def external_search_indexer(payload: Dict[str, Any]) -> None:
    logger.info("search_index_callback_triggered", archive_id=payload["archive_id"], transcript_count=len(payload["transcripts"]))

if __name__ == "__main__":
    AUTH_CONFIG = {
        "base_url": "https://myorg.mygenesiscustomer.com",
        "client_id": "YOUR_CLIENT_ID",
        "client_secret": "YOUR_CLIENT_SECRET"
    }
    auth = GenesysAuthManager(**AUTH_CONFIG)
    api_client = create_archivemanagement_client(auth)
    retriever = TranscriptRetriever(api_client, search_index_callback=external_search_indexer)

    # Replace with a valid archive ID from your environment
    TARGET_ARCHIVE_ID = "REPLACE_WITH_VALID_ARCHIVE_ID"
    result = retriever.process_archive(TARGET_ARCHIVE_ID)
    print(json.dumps(result, indent=2))

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: Expired OAuth token, invalid client credentials, or missing archive:read scope.
• Fix: Verify client credentials in Genesys Cloud Admin. Ensure the OAuth client has the archive:read scope assigned. The authentication manager automatically refreshes tokens, but initial credential validation must pass.
• Code Fix: Add explicit token validation before SDK initialization.

token = auth.get_token()
if not token:
    raise RuntimeError("Token generation failed. Verify client credentials and scope.")

Error: 429 Too Many Requests

• Cause: Exceeding Genesys Cloud rate limits for the archiving endpoint. Limits vary by organization tier.
• Fix: The implementation includes exponential backoff retry logic. If failures persist, reduce batch size or implement request throttling using a semaphore.
• Code Fix: The retrieve_archive_with_retry function already handles 429 with time.sleep(2 ** attempt). Increase max_retries or add jitter if needed.

Error: 400 Bad Request (Schema Validation)

• Cause: Date range exceeds 30 days, batch size exceeds 100, or invalid transcript configuration fields.
• Fix: Validate input parameters before constructing the ConversationDetailQueryRequest. The build_archive_query_request function enforces these constraints programmatically.
• Code Fix: Ensure date_range_query uses ISO 8601 format with Z suffix and size does not exceed platform limits.

Error: Timestamp Drift or Missing Speaker Labels

• Cause: Transcription engine failed to align segments, or diarization model returned low confidence.
• Fix: Check the validation report returned by validate_transcript_alignment. If drift_detected is true, reconfigure transcription settings in Genesys Cloud or filter low-confidence segments programmatically.
• Code Fix: Filter transcripts by confidence threshold before indexing.

filtered_transcripts = [t for t in transcripts if t.get("confidence", 0.0) >= 0.85]

Official References

• Genesys Cloud Archiving API Documentation
• Genesys Cloud Python SDK Reference
• OAuth2 Client Credentials Grant
• Transcript Configuration and Diarization