Creating Genesys Cloud Follow-Up Tasks via Task Management API with Python

What You Will Build

• You will build a Python module that creates follow-up tasks in Genesys Cloud using atomic HTTP POST operations to the Task Management API, triggered by Agent Assist context events.
• The code uses the Genesys Cloud REST API (/api/v2/taskmanagement/queues/{queueId}/tasks) with explicit payload construction, schema validation, duplicate prevention, and webhook synchronization.
• This tutorial covers Python 3.9+ using the requests library with type hints, production-ready error handling, and observability hooks.

Prerequisites

• OAuth Client Credentials flow with taskmanagement:task:write, routing:queue:read, user:read, and routing:user:read scopes.
• Genesys Cloud API v2.
• Python 3.9+ runtime.
• External dependencies: pip install requests python-dotenv

Authentication Setup

Genesys Cloud uses OAuth 2.0 Client Credentials for server-to-server integrations. The token must be cached and refreshed before expiration to prevent 401 failures during task creation pipelines.

import requests
import time
import json
from typing import Optional
from dataclasses import dataclass

@dataclass
class TokenCache:
    access_token: str
    expires_at: float

class GenesysAuth:
    def __init__(self, base_url: str, client_id: str, client_secret: str):
        self.base_url = base_url.rstrip("/")
        self.client_id = client_id
        self.client_secret = client_secret
        self._cache: Optional[TokenCache] = None

    def get_token(self) -> str:
        if self._cache and time.time() < self._cache.expires_at - 60:
            return self._cache.access_token

        url = f"{self.base_url}/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": "taskmanagement:task:write routing:queue:read user:read routing:user:read"
        }

        response = requests.post(url, headers=headers, data=data)
        response.raise_for_status()
        payload = response.json()

        self._cache = TokenCache(
            access_token=payload["access_token"],
            expires_at=time.time() + payload["expires_in"]
        )
        return self._cache.access_token

Implementation

Step 1: Assignee Validity Verification and Queue Capacity Check

Before creating a task, you must verify that the target assignee exists, is active, and is in an available routing status. Genesys Cloud rejects tasks routed to inactive or offline users. You also validate queue routing configuration to prevent workload constraint violations.

class TaskValidator:
    def __init__(self, auth: GenesysAuth):
        self.auth = auth
        self.session = requests.Session()

    def _make_request(self, method: str, path: str, **kwargs) -> requests.Response:
        url = f"{self.auth.base_url}{path}"
        headers = {"Authorization": f"Bearer {self.auth.get_token()}", "Content-Type": "application/json"}
        kwargs.setdefault("headers", headers)
        return self.session.request(method, url, **kwargs)

    def validate_assignee(self, user_id: str) -> bool:
        """Verify user exists and is available for routing."""
        user_resp = self._make_request("GET", f"/api/v2/users/{user_id}")
        if user_resp.status_code == 404:
            return False

        status_resp = self._make_request("GET", f"/api/v2/users/{user_id}/routing/status")
        if status_resp.status_code != 200:
            return False

        status_data = status_resp.json()
        return status_data.get("routingStatus") == "available"

    def validate_queue_capacity(self, queue_id: str) -> bool:
        """Check if queue is enabled and accepting tasks."""
        queue_resp = self._make_request("GET", f"/api/v2/routing/queues/{queue_id}")
        if queue_resp.status_code != 200:
            return False
        
        queue_data = queue_resp.json()
        return queue_data.get("enabled", False) is True

Step 2: Payload Construction with Priority, Due Date, and Custom Attributes

Genesys Cloud Task Management expects specific schema fields. The task-ref maps to externalId, detail-matrix maps to customData, and priority ranges from 1 (highest) to 500 (lowest). Due dates must be in ISO 8601 format and cannot exceed configured SLA windows.

from datetime import datetime, timedelta
from typing import Any, Dict

def build_task_payload(
    external_id: str,
    queue_id: str,
    assignee_id: str,
    priority_score: int,
    due_date: datetime,
    detail_matrix: Dict[str, Any],
    max_duration_hours: int = 24
) -> Dict[str, Any]:
    """Construct validated task creation payload."""
    # Priority normalization: Genesys accepts 1-500
    priority = max(1, min(500, priority_score))
    
    # Due date validation against max duration
    creation_time = datetime.utcnow()
    max_due = creation_time + timedelta(hours=max_duration_hours)
    if due_date > max_due:
        due_date = max_due
    
    # Detail matrix flattening for customData
    custom_data = {k: str(v) for k, v in detail_matrix.items()}
    
    payload = {
        "externalId": external_id,
        "routingData": {
            "queueId": queue_id,
            "assigneeId": assignee_id,
            "priority": priority,
            "dueDate": due_date.isoformat() + "Z"
        },
        "customData": custom_data,
        "type": "task",
        "source": {
            "type": "api",
            "id": "agent-assist-trigger"
        }
    }
    return payload

Step 3: Duplicate Checking, Atomic Creation, and Retry Logic

You must prevent duplicate tasks by searching existing tasks using the externalId. The creation operation uses exponential backoff for 429 responses and validates the HTTP 201 response. Pagination is handled for the search endpoint.

import logging
import uuid
from typing import Tuple

logger = logging.getLogger("genesys_task_creator")

class TaskCreator:
    def __init__(self, auth: GenesysAuth, validator: TaskValidator):
        self.auth = auth
        self.validator = validator
        self.session = requests.Session()

    def _check_duplicate(self, external_id: str, queue_id: str) -> bool:
        """Search for existing task by externalId. Returns True if exists."""
        url = f"{self.auth.base_url}/api/v2/taskmanagement/tasks/search"
        headers = {
            "Authorization": f"Bearer {self.auth.get_token()}",
            "Content-Type": "application/json"
        }
        
        query = {
            "query": f'externalId == "{external_id}" AND routingData.queueId == "{queue_id}"',
            "pageSize": 20
        }
        
        while query.get("pageSize"):
            resp = self.session.post(url, headers=headers, json=query)
            resp.raise_for_status()
            data = resp.json()
            
            if data.get("entities") and len(data["entities"]) > 0:
                return True
            
            if data.get("nextPage"):
                query = {"nextPage": data["nextPage"], "pageSize": 20}
            else:
                break
        return False

    def create_task(
        self,
        external_id: str,
        queue_id: str,
        assignee_id: str,
        priority_score: int,
        due_date: datetime,
        detail_matrix: Dict[str, Any],
        max_retries: int = 3
    ) -> Tuple[bool, Dict[str, Any]]:
        """Atomic task creation with validation, duplicate check, and retry logic."""
        # Validation pipeline
        if not self.validator.validate_assignee(assignee_id):
            logger.warning("Assignee %s is not available", assignee_id)
            return False, {"error": "assignee_unavailable"}
            
        if not self.validator.validate_queue_capacity(queue_id):
            logger.warning("Queue %s is not accepting tasks", queue_id)
            return False, {"error": "queue_disabled"}
            
        if self._check_duplicate(external_id, queue_id):
            logger.info("Duplicate task detected: %s", external_id)
            return False, {"error": "duplicate_task"}
        
        payload = build_task_payload(
            external_id, queue_id, assignee_id, priority_score, due_date, detail_matrix
        )
        
        url = f"{self.auth.base_url}/api/v2/taskmanagement/queues/{queue_id}/tasks"
        headers = {
            "Authorization": f"Bearer {self.auth.get_token()}",
            "Content-Type": "application/json",
            "Idempotency-Key": str(uuid.uuid4())
        }
        
        for attempt in range(max_retries + 1):
            start_time = time.time()
            try:
                resp = self.session.post(url, headers=headers, json=payload)
                latency = time.time() - start_time
                
                if resp.status_code == 201:
                    logger.info("Task created successfully in %.3fs", latency)
                    return True, resp.json()
                elif resp.status_code == 429:
                    wait_time = min(2 ** attempt, 30)
                    logger.warning("Rate limited. Retrying in %ds", wait_time)
                    time.sleep(wait_time)
                    continue
                elif resp.status_code == 409:
                    return False, {"error": "duplicate_task_conflict"}
                elif resp.status_code == 422:
                    return False, {"error": "validation_failed", "details": resp.text}
                else:
                    resp.raise_for_status()
                    
            except requests.exceptions.RequestException as e:
                logger.error("HTTP request failed: %s", str(e))
                return False, {"error": "network_failure", "details": str(e)}
                
        return False, {"error": "max_retries_exceeded"}

Step 4: Webhook Synchronization, Audit Logging, and Metrics Tracking

After creation, you synchronize with an external task manager via outbound webhook, record audit logs, and track latency and success rates for operational governance.

class TaskOrchestrator:
    def __init__(self, creator: TaskCreator, webhook_url: str):
        self.creator = creator
        self.webhook_url = webhook_url
        self.success_count = 0
        self.failure_count = 0
        self.total_latency = 0.0

    def _sync_external_manager(self, task_data: Dict[str, Any], status: str) -> None:
        """Push task event to external manager via webhook."""
        payload = {
            "eventType": "task.created" if status == "success" else "task.failed",
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "taskId": task_data.get("id", "unknown"),
            "externalId": task_data.get("externalId", "unknown"),
            "status": status
        }
        try:
            requests.post(self.webhook_url, json=payload, timeout=5)
        except requests.exceptions.RequestException:
            logger.warning("Webhook sync failed for task %s", payload["taskId"])

    def _log_audit(self, external_id: str, result: bool, latency: float, details: Dict) -> None:
        """Write structured audit log for governance."""
        audit_entry = {
            "timestamp": datetime.utcnow().isoformat() + "Z",
            "action": "create_follow_up_task",
            "externalId": external_id,
            "success": result,
            "latency_ms": round(latency * 1000, 2),
            "details": details
        }
        logger.info("AUDIT: %s", json.dumps(audit_entry))

    def execute_workflow(
        self,
        external_id: str,
        queue_id: str,
        assignee_id: str,
        priority_score: int,
        due_date: datetime,
        detail_matrix: Dict[str, Any]
    ) -> Dict[str, Any]:
        start = time.time()
        success, result = self.creator.create_task(
            external_id, queue_id, assignee_id, priority_score, due_date, detail_matrix
        )
        latency = time.time() - start
        
        if success:
            self.success_count += 1
            self._sync_external_manager(result, "success")
            self._log_audit(external_id, True, latency, {"taskId": result.get("id")})
        else:
            self.failure_count += 1
            self._sync_external_manager({"externalId": external_id}, "failed")
            self._log_audit(external_id, False, latency, result)
            
        self.total_latency += latency
        return {"success": success, "result": result, "latency": latency}

Complete Working Example

The following script combines authentication, validation, creation, and observability into a single executable module. Replace the placeholder credentials with your Genesys Cloud tenant values.

import os
import sys
from datetime import datetime, timedelta

def main():
    # Configuration
    BASE_URL = os.getenv("GENESYS_BASE_URL", "https://api.mypurecloud.com")
    CLIENT_ID = os.getenv("GENESYS_CLIENT_ID")
    CLIENT_SECRET = os.getenv("GENESYS_CLIENT_SECRET")
    WEBHOOK_URL = os.getenv("EXTERNAL_WEBHOOK_URL", "https://hooks.example.com/genesys-sync")
    
    if not CLIENT_ID or not CLIENT_SECRET:
        print("ERROR: GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET must be set")
        sys.exit(1)
        
    logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(name)s: %(message)s")
    
    # Initialize components
    auth = GenesysAuth(BASE_URL, CLIENT_ID, CLIENT_SECRET)
    validator = TaskValidator(auth)
    creator = TaskCreator(auth, validator)
    orchestrator = TaskOrchestrator(creator, WEBHOOK_URL)
    
    # Task parameters
    external_id = f"AA-FOLLOWUP-{datetime.utcnow().strftime('%Y%m%d%H%M%S')}"
    queue_id = "your-queue-id-here"
    assignee_id = "your-assignee-user-id-here"
    priority_score = 150
    due_date = datetime.utcnow() + timedelta(hours=4)
    detail_matrix = {
        "conversationId": "conv-8821a",
        "agentAssistPromptId": "prompt-knowledge-12",
        "customerSegment": "enterprise",
        "resolutionCategory": "billing-dispute"
    }
    
    # Execute creation pipeline
    outcome = orchestrator.execute_workflow(
        external_id=external_id,
        queue_id=queue_id,
        assignee_id=assignee_id,
        priority_score=priority_score,
        due_date=due_date,
        detail_matrix=detail_matrix
    )
    
    print(json.dumps(outcome, indent=2, default=str))

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The OAuth token expired or was never generated. The get_token method caches tokens but does not automatically refresh during long-running batches.
• Fix: Ensure auth.get_token() is called before each API call. The provided implementation checks expiration with a 60-second safety buffer. If you run batch jobs, add a manual refresh trigger every 10 minutes.

Error: 403 Forbidden

• Cause: The OAuth client lacks required scopes. Task creation requires taskmanagement:task:write. Assignee validation requires user:read and routing:user:read.
• Fix: Update the client credentials application in the Genesys Cloud admin console. Add the missing scopes and regenerate the client secret if the client was created before scope updates.

Error: 409 Conflict

• Cause: A task with the same externalId already exists in the target queue. Genesys Cloud enforces uniqueness per queue for external identifiers.
• Fix: The _check_duplicate method queries the search API before posting. If you receive 409 despite the check, another process created the task concurrently. Implement database-level locking or use the Idempotency-Key header consistently.

Error: 422 Unprocessable Entity

• Cause: Invalid payload schema. Common triggers include priority outside 1-500, dueDate in the past, or assigneeId mismatching the queue member list.
• Fix: The build_task_payload function clamps priority and caps due dates. Verify that the assignee is added to the queue member list in Genesys Cloud routing settings.

Error: 429 Too Many Requests

• Cause: Exceeded Genesys Cloud API rate limits (typically 20 requests per second per client for task endpoints).
• Fix: The create_task method implements exponential backoff with a 30-second maximum wait. For high-volume pipelines, implement a token bucket rate limiter before calling the API.

Official References

• Task Management API Documentation
• OAuth 2.0 Client Credentials Flow
• Routing Queue and User Status APIs
• Python SDK Reference