Update main.py

main.py

@@ -3,6 +3,7 @@ from fastapi.responses import JSONResponse
 import tensorflow as tf
 import numpy as np
 import os
+import requests
 from tensorflow.keras.models import load_model
 from tensorflow.keras.preprocessing import image
 from tensorflow.keras.layers import Layer, Conv2D, Softmax, Concatenate
@@ -114,7 +115,7 @@ async def predict_plant_disease(plant_name: str, file: UploadFile = File(...)):
         file (UploadFile): The image file uploaded by the user.
 
     Returns:
-        JSON response with the predicted class.
+        JSON response with the predicted class and additional details from an external API.
     """
     # Ensure the plant name is valid
     if plant_name not in loaded_models:
@@ -137,9 +138,20 @@ async def predict_plant_disease(plant_name: str, file: UploadFile = File(...)):
 
         # Make prediction
         prediction = model.predict(img_array)
-        predicted_class = plant_disease_dict[plant_name][np.argmax(prediction)]
-
-        return JSONResponse(content={"plant": plant_name, "predicted_disease": predicted_class})
+        class_label = plant_disease_dict[plant_name][np.argmax(prediction)]
+
+        # Fetch additional data from external API
+        try:
+            response = requests.get(f"https://navpan2-sarva-ai-back.hf.space/kotlinback/{class_label}")
+            external_data = response.json() if response.status_code == 200 else {"error": "Failed to fetch external data"}
+        except Exception as e:
+            external_data = {"error": str(e)}
+
+        return JSONResponse(content={
+            "plant": plant_name,
+            "predicted_disease": class_label,
+            "external_data": external_data
+        })
     finally:
         # Clean up temporary file
         os.remove(temp_path)