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.
2025-11-07 18:40:44 +00:00
parent 28136cf198
commit ed7db4d4f2
4 changed files with 70 additions and 29 deletions
--- a/services/procurement/app/services/replenishment_planning_service.py
+++ b/services/procurement/app/services/replenishment_planning_service.py
@@ -373,7 +373,7 @@ class ReplenishmentPlanningService:
                lead_time_days=req.lead_time_days,
                calculation_method='none',
                confidence='low',
-                reasoning='Insufficient data for safety stock calculation'
+                reasoning='ERROR:INSUFFICIENT_DATA'  # Error code for i18n translation
            )

    def _adjust_for_shelf_life(
--- a/services/procurement/app/services/safety_stock_calculator.py
+++ b/services/procurement/app/services/safety_stock_calculator.py
@@ -108,7 +108,7 @@ class SafetyStockCalculator:
                lead_time_days=lead_time_days,
                calculation_method='zero_due_to_invalid_inputs',
                confidence='low',
-                reasoning='Lead time or demand std dev is zero or negative'
+                reasoning='ERROR:LEAD_TIME_INVALID'  # Error code for i18n translation
            )

        # Safety Stock = Z × σ × √L
@@ -160,7 +160,7 @@ class SafetyStockCalculator:
                lead_time_days=lead_time_days,
                calculation_method='insufficient_data',
                confidence='low',
-                reasoning='Insufficient historical demand data (need at least 2 data points)'
+                reasoning='ERROR:INSUFFICIENT_DATA'  # Error code for i18n translation
            )

        # Calculate standard deviation
--- a/services/procurement/scripts/demo/seed_demo_purchase_orders.py
+++ b/services/procurement/scripts/demo/seed_demo_purchase_orders.py
@@ -34,6 +34,13 @@ from app.models.purchase_order import (
    PurchaseOrder, PurchaseOrderItem, PurchaseOrderStatus
 )

+# 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_po_reasoning_low_stock,
+    create_po_reasoning_supplier_contract
+)
+
 # Configure logging
 logger = structlog.get_logger()

@@ -116,31 +123,39 @@ async def create_purchase_order(

    # Generate reasoning for JTBD dashboard (if columns exist after migration)
    days_until_delivery = (required_delivery - created_at).days
-    reasoning_text = None
-    reasoning_json = None
-    consequence_text = None
+
+    # Generate structured reasoning_data for i18n support
+    reasoning_data = None

    try:
-        # Try to set reasoning fields (will work after migration)
+        # Get product names from items
+        product_names = [item.product_name for item in items if hasattr(item, 'product_name')]
+        if not product_names:
+            product_names = [f"Product {i+1}" for i in range(len(items))]
+
        if status == PurchaseOrderStatus.pending_approval:
-            reasoning_text = f"Low stock detected for {supplier.name} items. Current inventory projected to run out in {days_until_delivery + 2} days."
-            consequence_text = f"Stock-out risk in {days_until_delivery + 2} days if not approved. Production may be impacted."
-            reasoning_json = {
-                "trigger": "low_stock",
-                "urgency_score": 75 if days_until_delivery < 5 else 50,
-                "days_remaining": days_until_delivery + 2,
-                "supplier_trust_score": supplier.trust_score
-            }
+            # Low stock detection reasoning
+            days_until_stockout = days_until_delivery + 2
+            reasoning_data = create_po_reasoning_low_stock(
+                supplier_name=supplier.name,
+                product_names=product_names,
+                current_stock=random.uniform(20, 50),  # Demo: low stock
+                required_stock=random.uniform(100, 200),  # Demo: needed stock
+                days_until_stockout=days_until_stockout,
+                threshold_percentage=20,
+                affected_products=product_names[:2] if len(product_names) > 1 else product_names,
+                estimated_lost_orders=random.randint(5, 15) if days_until_stockout <= 3 else None
+            )
        elif auto_approved:
-            reasoning_text = f"Auto-approved based on supplier trust score ({supplier.trust_score:.0%}) and amount within threshold (€{subtotal:.2f})."
-            reasoning_json = {
-                "trigger": "auto_approval",
-                "trust_score": supplier.trust_score,
-                "amount": float(subtotal),
-                "threshold": 500.0
-            }
-    except Exception:
-        # Columns don't exist yet, that's ok
+            # Supplier contract/auto-approval reasoning
+            reasoning_data = create_po_reasoning_supplier_contract(
+                supplier_name=supplier.name,
+                product_names=product_names,
+                contract_terms=f"Auto-approval threshold: €500",
+                trust_score=float(supplier.trust_score) if hasattr(supplier, 'trust_score') else 0.85
+            )
+    except Exception as e:
+        logger.warning(f"Failed to generate reasoning_data: {e}")
        pass

    # Create PO
@@ -165,12 +180,10 @@ async def create_purchase_order(
        updated_by=SYSTEM_USER_ID
    )

-    # Set reasoning fields if they exist (after migration)
-    if reasoning_text:
+    # Set structured reasoning_data for i18n support
+    if reasoning_data:
        try:
-            po.reasoning = reasoning_text
-            po.consequence = consequence_text
-            po.reasoning_data = reasoning_json
+            po.reasoning_data = reasoning_data
        except Exception:
            pass  # Columns don't exist yet

--- a/services/production/scripts/demo/seed_demo_batches.py
+++ b/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