Update app.py

app.py

@@ -3,9 +3,9 @@ from transformers import AutoImageProcessor, AutoModelForImageClassification
 from PIL import Image
 import torch
 import numpy as np
-import json
 import logging
 import requests
+import os
 
 # Configure Logging
 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
@@ -21,26 +21,27 @@ except Exception as e:
     raise RuntimeError("Failed to load the model. Please check the logs for details.")
 
 # Gemini API Key (Replace with your actual key)
-GEMINI_API_KEY = "AIzaSyCiRL0ES-zsJGJYsY03xmpwqcggDGcL2Fk"  # <-- Replace with your actual API key
+GEMINI_API_KEY = os.getenv("AIzaSyCiRL0ES-zsJGJYsY03xmpwqcggDGcL2Fk", "AIzaSyCiRL0ES-zsJGJYsY03xmpwqcggDGcL2Fk")
 
 # Function to Get AI-Powered Treatment Suggestions
 def get_treatment_suggestions(disease_name):
     url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateText?key={GEMINI_API_KEY}"
     headers = {"Content-Type": "application/json"}
     data = {
-        "prompt": f"Provide detailed organic and chemical treatment options, including dosage and preventive care, for {disease_name} in crops.",
+        "prompt": { "text": f"Provide detailed organic and chemical treatment options, including dosage and preventive care, for {disease_name} in crops." },
         "temperature": 0.7,
-        "max_tokens": 250
+        "candidate_count": 1
     }
-    
+
     try:
         response = requests.post(url, headers=headers, json=data)
         if response.status_code == 200:
             result = response.json()
-            treatment = result.get("candidates", [{}])[0].get("output", "No treatment suggestions found.")
+            treatment = result.get("candidates", [{}])[0].get("content", "No treatment suggestions found.")
             return treatment
         else:
-            return f"API Error: {response.status_code} - {response.text}"
+            logging.error(f"API Error: {response.status_code} - {response.text}")
+            return f"API Error: {response.status_code}"
     except Exception as e:
         logging.error(f"Error fetching treatment suggestions: {str(e)}")
         return "Error retrieving treatment details."