feat: Complete backend i18n implementation with error codes and demo data

Demo Seed Scripts:
- Updated seed_demo_purchase_orders.py to use structured reasoning_data
  * Imports create_po_reasoning_low_stock and create_po_reasoning_supplier_contract
  * Generates reasoning_data with product names, stock levels, and consequences
  * Removed deprecated reasoning/consequence TEXT fields
- Updated seed_demo_batches.py to use structured reasoning_data
  * Imports create_batch_reasoning_forecast_demand and create_batch_reasoning_regular_schedule
  * Generates intelligent reasoning based on batch priority and AI assistance
  * Adds reasoning_data to all production batches

Backend Services - Error Code Implementation:
- Updated safety_stock_calculator.py with error codes
  * Replaced "Lead time or demand std dev is zero or negative" with ERROR:LEAD_TIME_INVALID
  * Replaced "Insufficient historical demand data" with ERROR:INSUFFICIENT_DATA
- Updated replenishment_planning_service.py with error codes
  * Replaced "Insufficient data for safety stock calculation" with ERROR:INSUFFICIENT_DATA
  * Frontend can now translate error codes using i18n

Demo data will now display with translatable reasoning in EN/ES/EU languages.
Backend services return error codes that frontend translates for user's language.

services/production/scripts/demo/seed_demo_batches.py

@@ -25,6 +25,10 @@ import structlog
 
 from app.models.production import ProductionBatch, ProductionStatus, ProductionPriority, ProcessStage
 
+# Import reasoning helper functions for i18n support
+sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent))
+from shared.schemas.reasoning_types import create_batch_reasoning_forecast_demand, create_batch_reasoning_regular_schedule
+
 # Configure logging
 logger = structlog.get_logger()
 
@@ -161,6 +165,29 @@ async def seed_batches_for_tenant(
             # For La Espiga, append tenant suffix to make batch number unique
             batch_number = batch_data["batch_number"] + "-LE"
 
+        # Generate structured reasoning_data for i18n support
+        reasoning_data = None
+        try:
+            # Use forecast demand reasoning for most batches
+            if batch_data.get("is_ai_assisted") or priority in [ProductionPriority.HIGH, ProductionPriority.URGENT]:
+                reasoning_data = create_batch_reasoning_forecast_demand(
+                    product_name=batch_data["product_name"],
+                    predicted_demand=batch_data["planned_quantity"],
+                    current_stock=int(batch_data["planned_quantity"] * 0.3),  # Demo: assume 30% current stock
+                    production_needed=batch_data["planned_quantity"],
+                    target_date=planned_start.date().isoformat(),
+                    confidence_score=0.85 if batch_data.get("is_ai_assisted") else 0.75
+                )
+            else:
+                # Regular schedule reasoning for standard batches
+                reasoning_data = create_batch_reasoning_regular_schedule(
+                    product_name=batch_data["product_name"],
+                    schedule_frequency="daily",
+                    batch_size=batch_data["planned_quantity"]
+                )
+        except Exception as e:
+            logger.warning(f"Failed to generate reasoning_data for batch {batch_number}: {e}")
+
         # Create production batch
         batch = ProductionBatch(
             id=batch_id,
@@ -197,6 +224,7 @@ async def seed_batches_for_tenant(
             waste_defect_type=batch_data.get("waste_defect_type"),
             production_notes=batch_data.get("production_notes"),
             quality_notes=batch_data.get("quality_notes"),
+            reasoning_data=reasoning_data,  # Structured reasoning for i18n support
             created_at=BASE_REFERENCE_DATE,
             updated_at=BASE_REFERENCE_DATE,
             completed_at=completed_at