Root Causes Fixed:
1. BatchForecastResponse schema mismatch in forecasting service
- Changed 'batch_id' to 'id' (required field name)
- Changed 'products_processed' to 'total_products'
- Changed 'success' to 'status' with "completed" value
- Changed 'message' to 'error_message'
- Added all required fields: batch_name, completed_products, failed_products,
requested_at, completed_at, processing_time_ms, forecasts
- This was causing "11 validation errors for BatchForecastResponse"
which made the forecast service return None, triggering saga failure
2. Missing pandas dependency in orchestrator service
- Added pandas==2.2.2 and numpy==1.26.4 to requirements.txt
- Fixes "No module named 'pandas'" warning when loading AI enhancement
These issues prevented the orchestrator from completing Step 3 (generate_forecasts)
in the daily workflow, causing the entire saga to fail and compensate.
