changed all predictions class

main.py

@@ -103,6 +103,11 @@ class DiseaseInfo(BaseModel):
         return v
 
 
+class PredictionItem(BaseModel):
+    confidence: float
+    label: str
+    confidence_level: str
+
 class PredictionResponse(BaseModel):
     success: bool
     predicted_class: str
@@ -110,7 +115,7 @@ class PredictionResponse(BaseModel):
     clean_class_name: str = Field(description="Human-readable class name")
     confidence: float
     confidence_level: str = Field(description="High/Medium/Low confidence level")
-    all_predictions: Dict[str, float] = Field(description="Top 5 predictions with confidence scores")
+    all_predictions: list[PredictionItem] = Field(description="Top 5 predictions with confidence scores")
     disease_info: DiseaseInfo
     recommendations: List[str] = Field(description="Action recommendations based on prediction")
     message: str
@@ -456,18 +461,19 @@ def predict_image(image_bytes: bytes) -> PredictionResponse:
 
         # Top 5 predictions
         top_indices = np.argsort(predictions[0])[-5:][::-1]
-        all_predictions = {}
+        all_predictions = []
 
         for idx in top_indices:
             class_str = str(idx)
             class_confidence = float(predictions[0][idx])
             class_info = disease_guide.get(class_str, None)
             readable_name = clean_class_name(class_str, class_info)
-            all_predictions[class_str] = {
+
+            all_predictions.append({
                 "confidence": round(class_confidence, 4),
                 "label": readable_name,
                 "confidence_level": get_confidence_level(class_confidence)
-            }
+            })
 
         # Generate recommendations
         recommendations = get_recommendations(predicted_class, confidence, disease_info)
@@ -484,7 +490,6 @@ def predict_image(image_bytes: bytes) -> PredictionResponse:
             label=class_id,
             confidence=round(confidence, 4),
             confidence_level=confidence_level,
-            predictions=all_predictions,
             disease_info=disease_info,
             recommendations=recommendations
         )