How come this setting causes the API token to expire prematurely despite configuring a long-lived grant? I am refactoring our CI/CD pipeline to use Genesys Cloud’s OAuth2 client credentials flow instead of storing static API keys. The goal is to generate a fresh, short-lived access token on demand, but I need a long-lived refresh token or a specific grant type that persists across pipeline runs without manual intervention.
I am using the Python SDK genesyscloud version 2.4.0 within a GitHub Actions runner (ubuntu-latest). My current implementation requests the full_platform scope with a custom grant type. Here is the relevant snippet:
from genesyscloud.auth import get_auth_settings, login_api_token
auth_settings = get_auth_settings(
environment='mycompany',
client_id=os.getenv('GC_CLIENT_ID'),
client_secret=os.getenv('GC_CLIENT_SECRET'),
grant_type='client_credentials' # Trying to force persistence
)
try:
login_api_token(auth_settings)
except Exception as e:
print(f"Auth failed: {e}")
The initial POST to /api/v2/oauth/token succeeds with a 200 OK. However, the returned JSON payload contains an expires_in value of 3600 seconds. When the next workflow step triggers 10 minutes later, the token is invalid, and I get a 401 Unauthorized on subsequent calls to /api/v2/architect/data/actions.
I have verified the client credentials are correct. I assumed client_credentials would provide a longer window or a refresh token mechanism, but the response lacks a refresh_token field entirely. I have tried adding offline_access to the scope list, but the API returns a 400 Bad Request with "error_description": "Invalid scope".
Is there a specific API parameter or SDK method I am missing to generate a token that survives beyond the hour? Or is the client_credentials flow strictly ephemeral? I need a programmatic way to keep the pipeline authenticated without rotating secrets manually.
Have you tried aligning your OAuth client configuration with the specific grant type requirements? The client credentials flow does not issue refresh tokens by design. It only provides access tokens with a fixed lifetime (usually 1 hour). This is why your pipeline fails after that window.
- Switch to the authorization code flow with PKCE if you need persistence. This grants a refresh token.
- Ensure your OAuth client has the
client_credentials grant type enabled if you stick to the current method.
- Use the
PureCloudPlatformClientV2 SDK to handle token refresh automatically, but note it cannot refresh client credentials tokens.
Here is the correct SDK initialization for client credentials:
from genesyscloud import PureCloudPlatformClientV2
client = PureCloudPlatformClientV2(
client_id="your_client_id",
client_secret="your_client_secret",
environment="mypurecloud.com"
)
If you need long-lived access, you must store the refresh token from an initial auth code exchange. The current setup is architecturally incompatible with your goal. Check your OAuth client settings in Admin > Security > OAuth Clients.
This looks like a fundamental misunderstanding of the OAuth2 spec implementation in Genesys Cloud. The suggestion above regarding PKCE is correct for human users, but it adds unnecessary friction to a CI/CD pipeline. You do not need a refresh token for a non-interactive service.
Cause: The client_credentials flow is designed for machine-to-machine authentication. It intentionally does not issue refresh tokens. Your pipeline is failing because it expects persistence beyond the standard 1-hour access token lifetime. Storing refresh tokens in GitHub Actions secrets is a security anti-pattern and violates the principle of least privilege for service accounts.
Solution: Implement a token caching mechanism within your pipeline or use the SDK’s built-in token management. The genesyscloud Python SDK handles token expiration automatically if configured correctly. Do not try to extend the token lifetime. Instead, request a new token when the old one expires.
Here is how to configure the PureCloudPlatformClientV2 in Python to handle this transparently:
from purecloudplatformclientv2 import Configuration, PlatformApiClient
# Configure OAuth with client credentials
config = Configuration(
base_url='https://api.mypurecloud.com',
client_id='YOUR_CLIENT_ID',
client_secret='YOUR_CLIENT_SECRET'
)
# Initialize the API client
# The SDK will automatically fetch a new token when the current one expires
platform_client = PlatformApiClient(config)
# Use the client for your API calls
# No manual token refresh logic is required here
analytics_client = platform_client.analytics_api
response = analytics_client.post_analytics_conversations_details_query(...)
If you are using raw requests, implement a simple retry wrapper that catches 401 Unauthorized and re-authenticates. For CI/CD, I recommend using a shared secret stored in GitHub Secrets rather than rotating tokens manually. Focus on idempotent API calls.
# Client Credentials flow does not issue refresh tokens.
# Implement a simple token cache with TTL in your CI/CD workflow.
token = platformClient.auth.login_client_credentials(
client_id=os.environ['GC_CLIENT_ID'],
client_secret=os.environ['GC_CLIENT_SECRET'],
scope=['admin:agent:write', 'admin:organization:read']
)
Make sure you cache the access token locally with a one-hour TTL instead of requesting a refresh token that does not exist. The client credentials flow is stateless by design, so your pipeline must handle the token lifecycle explicitly.
TL;DR: Cache the token.
The easiest way to fix this is to implement a TTL-based cache in your pipeline. The client_credentials flow does not issue refresh tokens. My Python SDK wrapper handles this automatically with a @token_cache decorator.
@token_cache(ttl=3600)
def get_access_token():
return platformClient.get_oauth_client().get_token(...)
This prevents repeated API calls and expiry errors.