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Start fixing forecast service 16

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This commit is contained in:
Urtzi Alfaro
2025-07-30 08:13:32 +02:00
parent 1d05e125a5
commit e5c3375d53
4 changed files with 101 additions and 36 deletions
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107
services/forecasting/app/services/forecasting_service.py
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@@ -89,16 +89,39 @@ class ForecastingService:
prediction=adjusted_prediction['prediction'])
return ForecastResponse(
id=forecast.id,
forecast_date=forecast.forecast_date,
id=str(forecast.id),
tenant_id=str(forecast.tenant_id),
product_name=forecast.product_name,
predicted_quantity=forecast.predicted_quantity,
location=forecast.location,
forecast_date=forecast.forecast_date,
# Predictions
predicted_demand=forecast.predicted_demand,
confidence_lower=forecast.confidence_lower,
confidence_upper=forecast.confidence_upper,
confidence_level=forecast.confidence_level,
lower_bound=forecast.lower_bound,
upper_bound=forecast.upper_bound,
model_id=forecast.model_id,
# Model info
model_id=str(forecast.model_id),
model_version=forecast.model_version,
algorithm=forecast.algorithm,
# Context
business_type=forecast.business_type,
is_holiday=forecast.is_holiday,
is_weekend=forecast.is_weekend,
day_of_week=forecast.day_of_week,
# External factors
weather_temperature=forecast.weather_temperature,
weather_precipitation=forecast.weather_precipitation,
weather_description=forecast.weather_description,
traffic_volume=forecast.traffic_volume,
# Metadata
created_at=forecast.created_at,
external_factors=forecast.external_factors
processing_time_ms=forecast.processing_time_ms,
features_used=forecast.features_used
)
except Exception as e:
@@ -171,7 +194,7 @@ class ForecastingService:
await self._add_weather_features_with_fallbacks(features, tenant_id)
# Add traffic data with fallbacks
# await self._add_traffic_features_with_fallbacks(features, tenant_id)
await self._add_traffic_features_with_fallbacks(features, tenant_id)
return features
@@ -248,23 +271,23 @@ class ForecastingService:
) -> None:
"""Add traffic features with fallbacks"""
try:
traffic_data = await self.data_client.get_traffic_data(
tenant_id=tenant_id,
latitude=40.4168,
longitude=-3.7038
)
if traffic_data:
features.update({
"traffic_volume": traffic_data.get("traffic_volume", 100),
"pedestrian_count": traffic_data.get("pedestrian_count", 50),
})
logger.info("Traffic data acquired successfully", tenant_id=tenant_id)
return
# try:
# traffic_data = await self.data_client.get_traffic_data(
# tenant_id=tenant_id,
# latitude=40.4168,
# longitude=-3.7038
# )
#
# if traffic_data:
# features.update({
# "traffic_volume": traffic_data.get("traffic_volume", 100),
# "pedestrian_count": traffic_data.get("pedestrian_count", 50),
# })
# logger.info("Traffic data acquired successfully", tenant_id=tenant_id)
# return
except Exception as e:
logger.warning("Traffic data acquisition failed", error=str(e))
# except Exception as e:
# logger.warning("Traffic data acquisition failed", error=str(e))
# Fallback: Use typical values based on day of week
day_of_week = features["day_of_week"]
@@ -273,6 +296,7 @@ class ForecastingService:
features.update({
"traffic_volume": int(100 * weekend_factor),
"pedestrian_count": int(50 * weekend_factor),
"congestion_level": 1
})
logger.warning("Using default traffic values", tenant_id=tenant_id)
@@ -398,15 +422,36 @@ class ForecastingService:
forecast = Forecast(
tenant_id=tenant_id,
forecast_date=request.forecast_date,
product_name=request.product_name,
predicted_quantity=prediction["prediction"],
location=request.location,
forecast_date=request.forecast_date,
# Predictions
predicted_demand=prediction['prediction'],
confidence_lower=prediction['lower_bound'],
confidence_upper=prediction['upper_bound'],
confidence_level=request.confidence_level,
lower_bound=prediction["lower_bound"],
upper_bound=prediction["upper_bound"],
model_id=model_data["model_id"],
external_factors=features,
created_at=datetime.utcnow()
# Model info
model_id=model_data['model_id'],
model_version=model_data.get('version', '1.0'),
algorithm=model_data.get('algorithm', 'prophet'),
# Context
business_type=features.get('business_type', 'individual'),
is_holiday=features.get('is_holiday', False),
is_weekend=features.get('is_weekend', False),
day_of_week=features.get('day_of_week', 0),
# External factors
weather_temperature=features.get('temperature'),
weather_precipitation=features.get('precipitation'),
weather_description=features.get('weather_description'),
traffic_volume=features.get('traffic_volume'),
# Metadata
processing_time_ms=int((datetime.now() - start_time).total_seconds() * 1000),
features_used=features
)
db.add(forecast)