Update label files

models/label.py

@@ -152,7 +152,7 @@ class BatchPredictionResponse(BaseModel):
     predictions: List[PredictionResponse]
     total_processed: int = Field(..., description="Number of processed items")
     summary: Dict[str, float] = Field(
-        ...,
+        default_factory=dict,
         description="Summary statistics of the batch prediction"
     )
 

routes/label.py

@@ -112,13 +112,38 @@ async def batch_predict_kpa(request: BatchPredictionRequest):
                     )
                 )
 
+        # CALCULER LE SUMMARY
+        successful_predictions = [r for r in results if r.prediction != -1]
+        
+        if successful_predictions:
+            total_apparie = sum(1 for r in successful_predictions if r.prediction == 1)
+            total_non_apparie = sum(1 for r in successful_predictions if r.prediction == 0)
+            average_confidence = sum(r.confidence for r in successful_predictions) / len(successful_predictions)
+            
+            summary = {
+                "total_apparie": total_apparie,
+                "total_non_apparie": total_non_apparie,
+                "average_confidence": round(average_confidence, 4),
+                "successful_predictions": len(successful_predictions),
+                "failed_predictions": len(results) - len(successful_predictions)
+            }
+        else:
+            summary = {
+                "total_apparie": 0,
+                "total_non_apparie": 0,
+                "average_confidence": 0.0,
+                "successful_predictions": 0,
+                "failed_predictions": len(results)
+            }
+
         logger.info(f"Batch KPA prediction completed — {len(results)} items processed")
 
         return BatchPredictionResponse(
             predictions=results,
-            total_processed=len(results)
+            total_processed=len(results),
+            summary=summary
         )
 
     except Exception as e:
         logger.error(f"Batch KPA prediction error: {str(e)}")
-        raise HTTPException(status_code=500, detail=f"Batch prediction failed: {str(e)}")
+        raise HTTPException(status_code=500, detail=f"Batch prediction failed: {str(e)}")