New enterprise feature

services/forecasting/scripts/demo/seed_demo_forecasts.py

@@ -34,8 +34,7 @@ from shared.utils.demo_dates import BASE_REFERENCE_DATE
 # Configure logging
 logger = structlog.get_logger()
 
-DEMO_TENANT_SAN_PABLO = uuid.UUID("a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6")  # Individual bakery
-DEMO_TENANT_LA_ESPIGA = uuid.UUID("b2c3d4e5-f6a7-48b9-c0d1-e2f3a4b5c6d7")  # Central bakery
+DEMO_TENANT_PROFESSIONAL = uuid.UUID("a1b2c3d4-e5f6-47a8-b9c0-d1e2f3a4b5c6")  # Individual bakery
 
 # Day of week mapping
 DAYS_OF_WEEK = {
@@ -413,24 +412,15 @@ async def seed_all(db: AsyncSession):
     results = []
 
     # Seed San Pablo (Individual Bakery)
-    result_san_pablo = await generate_forecasts_for_tenant(
+    # Seed Professional Bakery (merged from San Pablo + La Espiga)
+    result_professional = await generate_forecasts_for_tenant(
         db,
-        DEMO_TENANT_SAN_PABLO,
-        "San Pablo - Individual Bakery",
+        DEMO_TENANT_PROFESSIONAL,
+        "Professional Bakery",
         "individual_bakery",
         config
     )
-    results.append(result_san_pablo)
-
-    # Seed La Espiga (Central Bakery)
-    result_la_espiga = await generate_forecasts_for_tenant(
-        db,
-        DEMO_TENANT_LA_ESPIGA,
-        "La Espiga - Central Bakery",
-        "central_bakery",
-        config
-    )
-    results.append(result_la_espiga)
+    results.append(result_professional)
 
     total_forecasts = sum(r["forecasts_created"] for r in results)
     total_batches = sum(r["batches_created"] for r in results)

services/forecasting/scripts/demo/seed_demo_forecasts_retail.py

@@ -0,0 +1,167 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Demo Retail Forecasting Seeding Script for Forecasting Service
+Creates store-level demand forecasts for child retail outlets
+
+This script populates child retail tenants with AI-generated demand forecasts.
+
+Usage:
+    python /app/scripts/demo/seed_demo_forecasts_retail.py
+
+Environment Variables Required:
+    FORECASTING_DATABASE_URL - PostgreSQL connection string
+    DEMO_MODE - Set to 'production' for production seeding
+"""
+
+import asyncio
+import uuid
+import sys
+import os
+import random
+from datetime import datetime, timezone, timedelta
+from pathlib import Path
+from decimal import Decimal
+
+# Add app to path
+sys.path.insert(0, str(Path(__file__).parent.parent.parent))
+# Add shared to path
+sys.path.insert(0, str(Path(__file__).parent.parent.parent.parent.parent))
+
+from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine
+from sqlalchemy.orm import sessionmaker
+from sqlalchemy import select
+import structlog
+
+from shared.utils.demo_dates import BASE_REFERENCE_DATE
+from app.models import Forecast, PredictionBatch
+
+structlog.configure(
+    processors=[
+        structlog.stdlib.add_log_level,
+        structlog.processors.TimeStamper(fmt="iso"),
+        structlog.dev.ConsoleRenderer()
+    ]
+)
+
+logger = structlog.get_logger()
+
+# Fixed Demo Tenant IDs
+DEMO_TENANT_CHILD_1 = uuid.UUID("d4e5f6a7-b8c9-40d1-e2f3-a4b5c6d7e8f9")  # Madrid Centro
+DEMO_TENANT_CHILD_2 = uuid.UUID("e5f6a7b8-c9d0-41e2-f3a4-b5c6d7e8f9a0")  # Barcelona Gràcia
+DEMO_TENANT_CHILD_3 = uuid.UUID("f6a7b8c9-d0e1-42f3-a4b5-c6d7e8f9a0b1")  # Valencia Ruzafa
+
+# Product IDs
+PRODUCT_IDS = {
+    "PRO-BAG-001": "20000000-0000-0000-0000-000000000001",
+    "PRO-CRO-001": "20000000-0000-0000-0000-000000000002",
+    "PRO-PUE-001": "20000000-0000-0000-0000-000000000003",
+    "PRO-NAP-001": "20000000-0000-0000-0000-000000000004",
+}
+
+# Retail forecasting patterns
+RETAIL_FORECASTS = [
+    (DEMO_TENANT_CHILD_1, "Madrid Centro", {"PRO-BAG-001": 120, "PRO-CRO-001": 80, "PRO-PUE-001": 35, "PRO-NAP-001": 60}),
+    (DEMO_TENANT_CHILD_2, "Barcelona Gràcia", {"PRO-BAG-001": 90, "PRO-CRO-001": 60, "PRO-PUE-001": 25, "PRO-NAP-001": 45}),
+    (DEMO_TENANT_CHILD_3, "Valencia Ruzafa", {"PRO-BAG-001": 70, "PRO-CRO-001": 45, "PRO-PUE-001": 20, "PRO-NAP-001": 35})
+]
+
+
+async def seed_forecasts_for_retail_tenant(db: AsyncSession, tenant_id: uuid.UUID, tenant_name: str, base_forecasts: dict):
+    """Seed forecasts for a retail tenant"""
+    logger.info(f"Seeding forecasts for: {tenant_name}", tenant_id=str(tenant_id))
+
+    created = 0
+    # Create 7 days of forecasts
+    for days_ahead in range(1, 8):
+        forecast_date = BASE_REFERENCE_DATE + timedelta(days=days_ahead)
+
+        for sku, base_qty in base_forecasts.items():
+            base_product_id = uuid.UUID(PRODUCT_IDS[sku])
+            tenant_int = int(tenant_id.hex, 16)
+            product_id = uuid.UUID(int=tenant_int ^ int(base_product_id.hex, 16))
+
+            # Weekend boost
+            is_weekend = forecast_date.weekday() in [5, 6]
+            day_of_week = forecast_date.weekday()
+            multiplier = random.uniform(1.3, 1.5) if is_weekend else random.uniform(0.9, 1.1)
+            forecasted_quantity = int(base_qty * multiplier)
+
+            forecast = Forecast(
+                id=uuid.uuid4(),
+                tenant_id=tenant_id,
+                inventory_product_id=product_id,
+                product_name=sku,
+                location=tenant_name,
+                forecast_date=forecast_date,
+                created_at=BASE_REFERENCE_DATE,
+                predicted_demand=float(forecasted_quantity),
+                confidence_lower=float(int(forecasted_quantity * 0.85)),
+                confidence_upper=float(int(forecasted_quantity * 1.15)),
+                confidence_level=0.90,
+                model_id="retail_forecast_model",
+                model_version="retail_v1.0",
+                algorithm="prophet_retail",
+                business_type="retail_outlet",
+                day_of_week=day_of_week,
+                is_holiday=False,
+                is_weekend=is_weekend,
+                weather_temperature=random.uniform(10.0, 25.0),
+                weather_precipitation=random.uniform(0.0, 5.0) if random.random() < 0.3 else 0.0,
+                weather_description="Clear" if random.random() > 0.3 else "Rainy",
+                traffic_volume=random.randint(50, 200) if is_weekend else random.randint(30, 120),
+                processing_time_ms=random.randint(50, 200),
+                features_used={"historical_sales": True, "weather": True, "day_of_week": True}
+            )
+
+            db.add(forecast)
+            created += 1
+
+    await db.commit()
+    logger.info(f"Created {created} forecasts for {tenant_name}")
+    return {"tenant_id": str(tenant_id), "forecasts_created": created}
+
+
+async def seed_all(db: AsyncSession):
+    """Seed all retail forecasts"""
+    logger.info("=" * 80)
+    logger.info("📈 Starting Demo Retail Forecasting Seeding")
+    logger.info("=" * 80)
+
+    results = []
+    for tenant_id, tenant_name, base_forecasts in RETAIL_FORECASTS:
+        result = await seed_forecasts_for_retail_tenant(db, tenant_id, f"{tenant_name} (Retail)", base_forecasts)
+        results.append(result)
+
+    total = sum(r["forecasts_created"] for r in results)
+    logger.info(f"✅ Total forecasts created: {total}")
+    return {"total_forecasts": total, "results": results}
+
+
+async def main():
+    database_url = os.getenv("FORECASTING_DATABASE_URL") or os.getenv("DATABASE_URL")
+    if not database_url:
+        logger.error("❌ DATABASE_URL not set")
+        return 1
+
+    if database_url.startswith("postgresql://"):
+        database_url = database_url.replace("postgresql://", "postgresql+asyncpg://", 1)
+
+    engine = create_async_engine(database_url, echo=False, pool_pre_ping=True)
+    async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
+
+    try:
+        async with async_session() as session:
+            await seed_all(session)
+            logger.info("🎉 Retail forecasting seed completed!")
+            return 0
+    except Exception as e:
+        logger.error(f"❌ Seed failed: {e}", exc_info=True)
+        return 1
+    finally:
+        await engine.dispose()
+
+
+if __name__ == "__main__":
+    exit_code = asyncio.run(main())
+    sys.exit(exit_code)