Imporve the predicciones page

2025-09-20 22:11:05 +02:00
parent abe7cf2444
commit 38d314e28d
14 changed files with 1659 additions and 364 deletions
--- a/services/forecasting/app/services/forecasting_service.py
+++ b/services/forecasting/app/services/forecasting_service.py
@@ -345,7 +345,101 @@ class EnhancedForecastingService:
                        inventory_product_id=request.inventory_product_id,
                        processing_time=processing_time)
            raise
-    
+
+    async def generate_multi_day_forecast(
+        self,
+        tenant_id: str,
+        request: ForecastRequest
+    ) -> Dict[str, Any]:
+        """
+        Generate multiple daily forecasts for the specified period.
+        """
+        start_time = datetime.utcnow()
+        forecasts = []
+
+        try:
+            logger.info("Generating multi-day forecast",
+                       tenant_id=tenant_id,
+                       inventory_product_id=request.inventory_product_id,
+                       forecast_days=request.forecast_days,
+                       start_date=request.forecast_date.isoformat())
+
+            # Generate a forecast for each day
+            for day_offset in range(request.forecast_days):
+                # Calculate the forecast date for this day
+                current_date = request.forecast_date
+                if isinstance(current_date, str):
+                    from dateutil.parser import parse
+                    current_date = parse(current_date).date()
+
+                if day_offset > 0:
+                    from datetime import timedelta
+                    current_date = current_date + timedelta(days=day_offset)
+
+                # Create a new request for this specific day
+                daily_request = ForecastRequest(
+                    inventory_product_id=request.inventory_product_id,
+                    forecast_date=current_date,
+                    forecast_days=1,  # Single day for each iteration
+                    location=request.location,
+                    confidence_level=request.confidence_level
+                )
+
+                # Generate forecast for this day
+                daily_forecast = await self.generate_forecast(tenant_id, daily_request)
+                forecasts.append(daily_forecast)
+
+            # Calculate summary statistics
+            total_demand = sum(f.predicted_demand for f in forecasts)
+            avg_confidence = sum(f.confidence_level for f in forecasts) / len(forecasts)
+            processing_time = int((datetime.utcnow() - start_time).total_seconds() * 1000)
+
+            # Convert forecasts to dictionary format for the response
+            forecast_dicts = []
+            for forecast in forecasts:
+                forecast_dicts.append({
+                    "id": forecast.id,
+                    "tenant_id": forecast.tenant_id,
+                    "inventory_product_id": forecast.inventory_product_id,
+                    "location": forecast.location,
+                    "forecast_date": forecast.forecast_date.isoformat() if hasattr(forecast.forecast_date, 'isoformat') else str(forecast.forecast_date),
+                    "predicted_demand": forecast.predicted_demand,
+                    "confidence_lower": forecast.confidence_lower,
+                    "confidence_upper": forecast.confidence_upper,
+                    "confidence_level": forecast.confidence_level,
+                    "model_id": forecast.model_id,
+                    "model_version": forecast.model_version,
+                    "algorithm": forecast.algorithm,
+                    "business_type": forecast.business_type,
+                    "is_holiday": forecast.is_holiday,
+                    "is_weekend": forecast.is_weekend,
+                    "day_of_week": forecast.day_of_week,
+                    "weather_temperature": forecast.weather_temperature,
+                    "weather_precipitation": forecast.weather_precipitation,
+                    "weather_description": forecast.weather_description,
+                    "traffic_volume": forecast.traffic_volume,
+                    "created_at": forecast.created_at.isoformat() if hasattr(forecast.created_at, 'isoformat') else str(forecast.created_at),
+                    "processing_time_ms": forecast.processing_time_ms,
+                    "features_used": forecast.features_used
+                })
+
+            return {
+                "tenant_id": tenant_id,
+                "inventory_product_id": request.inventory_product_id,
+                "forecast_start_date": request.forecast_date.isoformat() if hasattr(request.forecast_date, 'isoformat') else str(request.forecast_date),
+                "forecast_days": request.forecast_days,
+                "forecasts": forecast_dicts,
+                "total_predicted_demand": total_demand,
+                "average_confidence_level": avg_confidence,
+                "processing_time_ms": processing_time
+            }
+
+        except Exception as e:
+            logger.error("Multi-day forecast generation failed",
+                        tenant_id=tenant_id,
+                        error=str(e))
+            raise
+
    async def get_forecast_history(
        self,
        tenant_id: str,