Provision Genesys Cloud Outbound Predictive Campaigns with Dynamic Concurrency Using Python

What You Will Build

• This script provisions a new predictive outbound campaign with dynamically calculated maximum concurrency based on real-time agent availability.
• It uses the Genesys Cloud Campaign API and User Status endpoints via the official Python SDK.
• The implementation is written in Python 3.9+ with type hints, pagination handling, and production-grade error recovery.

Prerequisites

• OAuth client credentials (client_id, client_secret) configured as a Custom Integration or Public Client in Genesys Cloud
• Required OAuth scopes: outbound:campaign:write, outbound:campaign:read, user:read, user:status:read
• Genesys Cloud Python SDK version 2.13.0+ (pip install genesyscloud)
• Python 3.9+ runtime
• Environment variables: GENESYS_CLOUD_HOST, GENESYS_CLIENT_ID, GENESYS_CLIENT_SECRET, AGENT_GROUP_ID, CALL_LIST_ID, WRAPUP_CODE_ID

Authentication Setup

The Genesys Cloud Python SDK manages OAuth 2.0 client credentials flow automatically when you initialize OAuthClient with cache_tokens=True. The SDK stores tokens in memory and refreshes them transparently before expiration. You must attach the OAuthClient instance to the Configuration object so that API calls trigger automatic token refresh when a 401 is encountered.

import os
from genesyscloud.auth.oauth_client import OAuthClient
from genesyscloud.platform.client import PlatformClient, Configuration

def init_platform_client() -> PlatformClient:
    host = os.getenv("GENESYS_CLOUD_HOST", "https://api.mypurecloud.com")
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")

    if not client_id or not client_secret:
        raise ValueError("GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET must be set")

    config = Configuration()
    config.host = host
    
    oauth_client = OAuthClient(
        client_id=client_id,
        client_secret=client_secret,
        oauth_host=host,
        cache_tokens=True
    )
    
    oauth_client.login()
    
    config.access_token = oauth_client.get_access_token()
    config.refresh_token = oauth_client.get_refresh_token()
    config.oauth_client = oauth_client
    
    return PlatformClient(config)

The oauth_client.login() call performs the initial POST to /oauth/token. Subsequent API calls reuse the cached token. If the token expires, the SDK intercepts the response, calls the refresh endpoint, updates the configuration, and retries the original request automatically.

Implementation

Step 1: Fetch Available Agents and Calculate Concurrency

Predictive dialing requires an accurate maxConcurrency value. Setting it too high generates excessive abandoned calls. Setting it too low underutilizes agents. This step retrieves all users in a specified routing group, filters for those with routingStatus: "available", and applies a concurrency multiplier.

The /api/v2/users endpoint supports pagination via continuationToken. The SDK exposes this as continuation_token in the response object.

from genesyscloud.users.api import UsersApi
from genesyscloud.platform.client.rest import ApiException

def get_available_agent_count(platform_client: PlatformClient, group_id: str, page_size: int = 50) -> int:
    users_api = UsersApi(platform_client)
    available_count = 0
    continuation_token = None

    while True:
        try:
            response = users_api.get_users(
                group_ids=group_id,
                expanded=["status", "addresses"],
                page_size=page_size,
                continuation_token=continuation_token
            )
            
            for user in response.entities:
                if user.routing_status == "available":
                    available_count += 1
                    
            if response.continuation_token:
                continuation_token = response.continuation_token
            else:
                break
                
        except ApiException as e:
            if e.status == 429:
                retry_after = int(e.headers.get("Retry-After", 2))
                import time
                time.sleep(retry_after)
                continue
            raise
            
    return available_count

The expanded=["status", "addresses"] parameter is mandatory. Without it, the routing_status field returns None. The loop continues until continuation_token is absent. Rate limit responses (429) are caught, the Retry-After header is parsed, and the request retries automatically.

Step 2: Construct Predictive Campaign Payload with Dynamic Dialing Rules

Predictive campaigns require the campaignType field set to "PREDICTIVE". The predictiveRules object controls pacing, concurrency, and attempt limits. Genesys validates that maxConcurrency does not exceed platform limits and that pacing falls between 0.1 and 1.0.

from genesyscloud.outbound.model import (
    CreateCampaignRequest,
    PredictiveRules,
    CampaignAttemptLimit,
    CampaignTimeCondition
)
from datetime import datetime, timezone

def build_campaign_request(
    name: str,
    list_id: str,
    wrapup_code_id: str,
    available_agents: int,
    concurrency_multiplier: float = 2.0
) -> CreateCampaignRequest:
    calculated_concurrency = max(1, int(available_agents * concurrency_multiplier))
    
    predictive_rules = PredictiveRules(
        max_concurrency=calculated_concurrency,
        pacing=0.85,
        call_interval=2,
        max_attempts=3,
        attempt_interval="P1D"
    )
    
    attempt_limit = CampaignAttemptLimit(
        max_attempts=3,
        max_attempts_per_day=1,
        max_attempts_per_week=2
    )
    
    campaign_request = CreateCampaignRequest(
        name=name,
        campaign_type="PREDICTIVE",
        list_id=list_id,
        wrap_up_code_id=wrapup_code_id,
        enabled=True,
        predictive_rules=predictive_rules,
        attempt_limit=attempt_limit,
        campaign_time_conditions=[
            CampaignTimeCondition(
                start_time="08:00",
                end_time="18:00",
                days=["MON", "TUE", "WED", "THU", "FRI"]
            )
        ],
        priority=5,
        do_not_call_list_id=None,
        campaign_id=None
    )
    
    return campaign_request

The pacing value of 0.85 tells the predictive algorithm to aim for an 85 percent answer rate. The call_interval of 2 seconds defines the minimum gap between dial attempts. The attempt_limit object enforces compliance rules at the contact level. The campaign_time_conditions array restricts dialing to business hours. All fields use ISO 8601 duration strings or standard time formats expected by the outbound engine.

Step 3: Provision Campaign and Handle Response

The POST /api/v2/outbound/campaigns endpoint creates the campaign synchronously. The response returns the fully hydrated campaign object with a system-generated campaignId. This step wraps the creation call in a retry mechanism to handle transient 429 responses during high-throughput provisioning windows.

from genesyscloud.outbound.api import CampaignsApi
from genesyscloud.outbound.model import Campaign
from genesyscloud.platform.client.rest import ApiException
import time

def create_predictive_campaign(
    platform_client: PlatformClient,
    campaign_request: CreateCampaignRequest,
    max_retries: int = 3
) -> Campaign:
    campaign_api = CampaignsApi(platform_client)
    attempt = 0
    
    while attempt < max_retries:
        try:
            response = campaign_api.post_outbound_campaigns(body=campaign_request)
            return response
        except ApiException as e:
            if e.status == 429:
                retry_after = int(e.headers.get("Retry-After", 2 ** attempt))
                print(f"Rate limited. Retrying in {retry_after} seconds...")
                time.sleep(retry_after)
                attempt += 1
                continue
            elif e.status == 422:
                print(f"Validation error: {e.body}")
                raise ValueError(f"Campaign payload rejected: {e.body}")
            elif e.status == 403:
                raise PermissionError("Missing outbound:campaign:write scope")
            raise
            
    raise RuntimeError("Max retries exceeded for campaign creation")

The 422 response contains a JSON body with field-level validation errors. The script surfaces this immediately because 422 errors require payload correction, not retries. The 403 error maps directly to missing OAuth scopes. The retry loop uses exponential backoff capped by the Retry-After header value.

Complete Working Example

import os
import time
from datetime import datetime
from typing import Optional

from genesyscloud.auth.oauth_client import OAuthClient
from genesyscloud.platform.client import PlatformClient, Configuration
from genesyscloud.platform.client.rest import ApiException
from genesyscloud.users.api import UsersApi
from genesyscloud.outbound.api import CampaignsApi
from genesyscloud.outbound.model import (
    CreateCampaignRequest,
    PredictiveRules,
    CampaignAttemptLimit,
    CampaignTimeCondition,
    Campaign
)

def init_platform_client() -> PlatformClient:
    host = os.getenv("GENESYS_CLOUD_HOST", "https://api.mypurecloud.com")
    client_id = os.getenv("GENESYS_CLIENT_ID")
    client_secret = os.getenv("GENESYS_CLIENT_SECRET")

    if not client_id or not client_secret:
        raise ValueError("GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET must be set")

    config = Configuration()
    config.host = host
    
    oauth_client = OAuthClient(
        client_id=client_id,
        client_secret=client_secret,
        oauth_host=host,
        cache_tokens=True
    )
    
    oauth_client.login()
    
    config.access_token = oauth_client.get_access_token()
    config.refresh_token = oauth_client.get_refresh_token()
    config.oauth_client = oauth_client
    
    return PlatformClient(config)

def get_available_agent_count(platform_client: PlatformClient, group_id: str, page_size: int = 50) -> int:
    users_api = UsersApi(platform_client)
    available_count = 0
    continuation_token = None

    while True:
        try:
            response = users_api.get_users(
                group_ids=group_id,
                expanded=["status", "addresses"],
                page_size=page_size,
                continuation_token=continuation_token
            )
            
            for user in response.entities:
                if user.routing_status == "available":
                    available_count += 1
                    
            if response.continuation_token:
                continuation_token = response.continuation_token
            else:
                break
                
        except ApiException as e:
            if e.status == 429:
                retry_after = int(e.headers.get("Retry-After", 2))
                time.sleep(retry_after)
                continue
            raise
            
    return available_count

def build_campaign_request(
    name: str,
    list_id: str,
    wrapup_code_id: str,
    available_agents: int,
    concurrency_multiplier: float = 2.0
) -> CreateCampaignRequest:
    calculated_concurrency = max(1, int(available_agents * concurrency_multiplier))
    
    predictive_rules = PredictiveRules(
        max_concurrency=calculated_concurrency,
        pacing=0.85,
        call_interval=2,
        max_attempts=3,
        attempt_interval="P1D"
    )
    
    attempt_limit = CampaignAttemptLimit(
        max_attempts=3,
        max_attempts_per_day=1,
        max_attempts_per_week=2
    )
    
    campaign_request = CreateCampaignRequest(
        name=name,
        campaign_type="PREDICTIVE",
        list_id=list_id,
        wrap_up_code_id=wrapup_code_id,
        enabled=True,
        predictive_rules=predictive_rules,
        attempt_limit=attempt_limit,
        campaign_time_conditions=[
            CampaignTimeCondition(
                start_time="08:00",
                end_time="18:00",
                days=["MON", "TUE", "WED", "THU", "FRI"]
            )
        ],
        priority=5
    )
    
    return campaign_request

def create_predictive_campaign(
    platform_client: PlatformClient,
    campaign_request: CreateCampaignRequest,
    max_retries: int = 3
) -> Campaign:
    campaign_api = CampaignsApi(platform_client)
    attempt = 0
    
    while attempt < max_retries:
        try:
            response = campaign_api.post_outbound_campaigns(body=campaign_request)
            return response
        except ApiException as e:
            if e.status == 429:
                retry_after = int(e.headers.get("Retry-After", 2 ** attempt))
                print(f"Rate limited. Retrying in {retry_after} seconds...")
                time.sleep(retry_after)
                attempt += 1
                continue
            elif e.status == 422:
                print(f"Validation error: {e.body}")
                raise ValueError(f"Campaign payload rejected: {e.body}")
            elif e.status == 403:
                raise PermissionError("Missing outbound:campaign:write scope")
            raise
            
    raise RuntimeError("Max retries exceeded for campaign creation")

def main():
    group_id = os.getenv("AGENT_GROUP_ID")
    list_id = os.getenv("CALL_LIST_ID")
    wrapup_code_id = os.getenv("WRAPUP_CODE_ID")
    
    if not all([group_id, list_id, wrapup_code_id]):
        raise ValueError("AGENT_GROUP_ID, CALL_LIST_ID, and WRAPUP_CODE_ID must be set")

    platform_client = init_platform_client()
    
    print("Fetching available agents...")
    available_agents = get_available_agent_count(platform_client, group_id)
    print(f"Found {available_agents} available agents")
    
    campaign_name = f"Predictive Campaign - {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M')}"
    campaign_request = build_campaign_request(
        name=campaign_name,
        list_id=list_id,
        wrapup_code_id=wrapup_code_id,
        available_agents=available_agents,
        concurrency_multiplier=2.0
    )
    
    print("Provisioning campaign...")
    created_campaign = create_predictive_campaign(platform_client, campaign_request)
    
    print(f"Campaign created successfully. ID: {created_campaign.id}")
    print(f"Max Concurrency: {created_campaign.predictive_rules.max_concurrency}")
    print(f"Status: {created_campaign.enabled}")

if __name__ == "__main__":
    main()

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The OAuth token expired between initialization and the API call, or the OAuthClient was not attached to the Configuration object.
• Fix: Ensure config.oauth_client = oauth_client is set before creating PlatformClient. The SDK will automatically refresh tokens when this reference exists.
• Code showing the fix:

config.oauth_client = oauth_client  # Mandatory for automatic refresh
platform_client = PlatformClient(config)

Error: 403 Forbidden

• Cause: The OAuth client lacks the outbound:campaign:write scope, or the integration is restricted to specific resource groups.
• Fix: Navigate to Admin > Security > Integrations, select your client, and add the missing scope. Reauthorize the client if it is a public client.
• Code showing the fix:

# Verify scopes during initialization
oauth_client.login()
scopes = oauth_client.get_access_token_info().get("scope", "")
if "outbound:campaign:write" not in scopes:
    raise RuntimeError("Integration missing required outbound:campaign:write scope")

Error: 422 Unprocessable Entity

• Cause: The predictiveRules object violates platform constraints. Common violations include maxConcurrency exceeding 500, pacing outside 0.1-1.0, or mismatched listId permissions.
• Fix: Parse the JSON response body to identify the invalid field. Adjust concurrency_multiplier or validate that the listId belongs to a completed call list.
• Code showing the fix:

except ApiException as e:
    if e.status == 422:
        error_body = e.body
        print(f"Payload validation failed: {error_body}")
        # Inspect error_body for field-level details
        raise

Error: 429 Too Many Requests

• Cause: The Genesys Cloud API enforces per-tenant and per-endpoint rate limits. Campaign creation and user listing share quota pools during peak provisioning.
• Fix: Implement exponential backoff using the Retry-After header. The complete example already handles this in both get_available_agent_count and create_predictive_campaign.
• Code showing the fix:

if e.status == 429:
    retry_after = int(e.headers.get("Retry-After", 2 ** attempt))
    time.sleep(retry_after)
    continue

Official References

• Genesys Cloud Campaigns API Reference
• Genesys Cloud Users API Reference
• Genesys Cloud Python SDK Documentation
• Outbound Predictive Dialing Configuration Guide
• OAuth 2.0 Client Credentials Flow