Need some help troubleshooting an issue where our AI bot is failing to recognize agent availability context during the handoff process, resulting in a 400 Bad Request error.
We are integrating our Genesys Cloud WFM schedule data with the Architect flow to ensure bots only offer ‘Speak to an Agent’ options when adherence is high. The bot retrieves the current shift status via the WFM API, but when the confidence score for the ‘TransferToAgent’ intent drops below 0.85, the flow throws an unexpected error instead of falling back to the menu.
The environment is Genesys Cloud CX, version 2024-02. We are using the Python SDK v2.14.0 for the backend integration that feeds real-time schedule data to the bot’s dynamic variables.
Here is the relevant Architect flow configuration snippet:
flow:
name: AgentHandoffCheck
steps:
- name: CheckSchedule
type: wfm_api_call
endpoint: /api/v2/wfm/schedules
params:
timezone: America/Chicago
- name: EvaluateIntent
type: intent_analysis
config:
min_confidence: 0.85
fallback_action: menu_loop
- name: ExecuteTransfer
type: transfer
target: queue_id_123
condition: intent.confidence >= 0.85
The error log shows:
Error 400: Invalid state transition. Variable 'agent_available' is null when confidence < 0.85.
This happens specifically during our weekly publish window in the Chicago timezone (America/Chicago), where shift swaps are most frequent. When an agent swaps a shift, the WFM API returns a ‘pending’ status, which the bot interprets as null, causing the intent evaluation to fail before it can hit the fallback condition.
We need the bot to handle ‘pending’ shifts gracefully by either waiting or offering a callback, rather than crashing the flow. How should we structure the conditional logic to account for WFM status latency without breaking the intent confidence threshold? Is there a specific SDK method to poll for ‘confirmed’ status before the handoff step executes?