Update app.py

app.py

@@ -1,7 +1,70 @@
+import os
+import json
+import gradio as gr
+import requests
+import logging
+import base64
+from PIL import Image
+from io import BytesIO
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Get API key from environment variables
+PLANT_ID_API_KEY = os.getenv("PLANT_ID_API_KEY")
+
+if not PLANT_ID_API_KEY:
+    raise ValueError("❌ API Key is missing! Set PLANT_ID_API_KEY in Hugging Face Secrets.")
+
+# Configure Logging
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
+
+# Plant.id API URL
+PLANT_ID_URL = "https://api.plant.id/v2/health_assessment"
+
+# Function to analyze plant health using Plant.id API
+def analyze_plant_health(image):
+    try:
+        # Convert image to bytes & encode in Base64
+        buffered = BytesIO()
+        image.save(buffered, format="JPEG")
+        img_base64 = base64.b64encode(buffered.getvalue()).decode()
+
+        # Send request to Plant.id API
+        headers = {"Content-Type": "application/json"}
+        payload = {
+            "images": [f"data:image/jpeg;base64,{img_base64}"],
+            "organs": ["leaf"],
+            "api_key": PLANT_ID_API_KEY
+        }
+
+        response = requests.post(PLANT_ID_URL, headers=headers, json=payload)
+
+        if response.status_code != 200:
+            return f"❌ API Error: {response.text}"
+
+        data = response.json()
+
+        if "health_assessment" not in data or not data["health_assessment"].get("diseases"):
+            return "✅ No disease detected! Your plant looks healthy. 🌿"
+
+        assessment = data["health_assessment"]
+        disease_info = assessment["diseases"][0]
+        predicted_disease = disease_info.get("name", "Unknown Disease")
+        treatment = disease_info.get("treatment", "No treatment suggestions available.")
+
+        return f"""
+        🌱 **Predicted Disease:** {predicted_disease}  
+        💊 **Treatment:** {treatment}  
+        """
+
+    except Exception as e:
+        logging.error(f"Prediction failed: {str(e)}")
+        return f"❌ Error: {str(e)}"
+
 # Launch Gradio App
 if __name__ == "__main__":
-    import gradio as gr
-
     iface = gr.Interface(
         fn=analyze_plant_health,
         inputs=gr.Image(type="pil", label="📸 Upload or Capture a Plant Image"),