Fix forecasting clone endpoint for demo sessions

Fixed two critical issues preventing forecast data from being cloned:

1. **Missing batch_name field**: The fixture uses `batch_id` but the
   PredictionBatch model requires `batch_name` (NOT NULL constraint).
   Added field mapping to handle batch_id -> batch_name conversion.

2. **UUID type mismatch**: The fixture's `product_id` is a string but
   the Forecast model expects `inventory_product_id` as UUID type.
   Added conversion from string to UUID.

3. **Field mappings added**:
   - batch_id -> batch_name
   - total_forecasts -> total_products
   - created_at -> requested_at (fallback)
   - Calculated completed_products from status

These fixes enable the forecasting service to successfully clone all
28 forecasts from the fixture file, unlocking demand forecasting
AI insights in demo sessions.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

services/forecasting/app/api/internal_demo.py

@@ -244,7 +244,12 @@ async def clone_demo_data(
             
             # Create forecast
             # Map product_id to inventory_product_id if needed
-            inventory_product_id = forecast_data.get('inventory_product_id') or forecast_data.get('product_id')
+            inventory_product_id_str = forecast_data.get('inventory_product_id') or forecast_data.get('product_id')
+            # Convert to UUID if it's a string
+            if isinstance(inventory_product_id_str, str):
+                inventory_product_id = uuid.UUID(inventory_product_id_str)
+            else:
+                inventory_product_id = inventory_product_id_str
 
             # Map predicted_quantity to predicted_demand if needed
             predicted_demand = forecast_data.get('predicted_demand') or forecast_data.get('predicted_quantity')
@@ -317,43 +322,31 @@ async def clone_demo_data(
                     detail=f"Invalid UUID format in batch data: {str(e)}"
                 )
             
-            # Transform dates using proper parse_date_field function
-            for date_field in ['requested_at', 'completed_at']:
-                if date_field in batch_data:
-                    try:
-                        parsed_date = parse_date_field(
-                            batch_data[date_field],
-                            session_time,
-                            date_field
-                        )
-                        if parsed_date:
-                            batch_data[date_field] = parsed_date
-                        else:
-                            # If parsing fails, use session_time as fallback
-                            batch_data[date_field] = session_time
-                            logger.warning("Using fallback date for failed parsing",
-                                         date_field=date_field,
-                                         original_value=batch_data[date_field])
-                    except Exception as e:
-                        logger.warning("Failed to parse date, using fallback",
-                                     date_field=date_field,
-                                     date_value=batch_data[date_field],
-                                     error=str(e))
-                        batch_data[date_field] = session_time
-            
             # Create prediction batch
+            # Handle field mapping: batch_id -> batch_name, total_forecasts -> total_products
+            batch_name = batch_data.get('batch_name') or batch_data.get('batch_id') or f"Batch-{transformed_id}"
+            total_products = batch_data.get('total_products') or batch_data.get('total_forecasts') or 0
+            completed_products = batch_data.get('completed_products') or (total_products if batch_data.get('status') == 'COMPLETED' else 0)
+
+            # Parse dates (handle created_at or prediction_date for requested_at)
+            requested_at_raw = batch_data.get('requested_at') or batch_data.get('created_at') or batch_data.get('prediction_date')
+            requested_at = parse_date_field(requested_at_raw, session_time, 'requested_at') if requested_at_raw else session_time
+
+            completed_at_raw = batch_data.get('completed_at')
+            completed_at = parse_date_field(completed_at_raw, session_time, 'completed_at') if completed_at_raw else None
+
             new_batch = PredictionBatch(
                 id=transformed_id,
                 tenant_id=virtual_uuid,
-                batch_name=batch_data.get('batch_name'),
-                requested_at=batch_data.get('requested_at'),
-                completed_at=batch_data.get('completed_at'),
-                status=batch_data.get('status'),
-                total_products=batch_data.get('total_products'),
-                completed_products=batch_data.get('completed_products'),
-                failed_products=batch_data.get('failed_products'),
-                forecast_days=batch_data.get('forecast_days'),
-                business_type=batch_data.get('business_type'),
+                batch_name=batch_name,
+                requested_at=requested_at,
+                completed_at=completed_at,
+                status=batch_data.get('status', 'completed'),
+                total_products=total_products,
+                completed_products=completed_products,
+                failed_products=batch_data.get('failed_products', 0),
+                forecast_days=batch_data.get('forecast_days', 7),
+                business_type=batch_data.get('business_type', 'individual'),
                 error_message=batch_data.get('error_message'),
                 processing_time_ms=batch_data.get('processing_time_ms'),
                 cancelled_by=batch_data.get('cancelled_by')