Update src/components/model_risk_predictor.py

src/components/model_risk_predictor.py

@@ -72,7 +72,7 @@ def predict_risk(region: str, days: int = 5, origin=None, destination=None,
 
        
         rule_risk = calculate_rule_based_risk(region, days, incidents or [])
-        logger.info(f"Rule-based risk for {region}: {rule_risk:.3f}")
+        
 
      
         ml_risk = 0.40  
@@ -93,29 +93,25 @@ def predict_risk(region: str, days: int = 5, origin=None, destination=None,
                 )
 
                 ml_risk = float(risk_model.predict_proba(test_features)[0, 1])
-                logger.info(f"ML model risk for {region}: {ml_risk:.3f}")
+                
             except Exception as e:
-                logger.warning(f"ML prediction failed: {e}")
+              
                 ml_risk = 0.40
 
  
         if incidents and len(incidents) > 0:
             final_risk = (ml_risk * 0.40) + (rule_risk * 0.60)
-            logger.info(
-                f"Hybrid risk (with incidents): ML={ml_risk:.3f}*0.4 + Rule={rule_risk:.3f}*0.6 = {final_risk:.3f}"
-            )
+            
         else:
             final_risk = (ml_risk * 0.70) + (rule_risk * 0.30)
-            logger.info(
-                f"Hybrid risk (no incidents): ML={ml_risk:.3f}*0.7 + Rule={rule_risk:.3f}*0.3 = {final_risk:.3f}"
-            )
+            
 
   
         final_risk = float(np.clip(final_risk, 0.0, 1.0))
         return round(final_risk, 2)
 
     except Exception as e:
-        logger.error(f"Error in predict_risk: {e}", exc_info=True)
+        
         return 0.50