Update app.py

app.py

@@ -1,77 +1,5 @@
 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__":
-    iface = gr.Interface(
-        fn=analyze_plant_health,
-        inputs=gr.Image(type="pil", label="📸 Upload or Capture a Plant Image"),
-        outputs=gr.Textbox(label="🔍 Diagnosis & Treatment"),
-        title="🌿 AI-Powered Plant Disease Detector",
-        description="📷 Upload an image of a plant leaf to detect diseases and get treatment suggestions.",
-        allow_flagging="never"
-    )
-
-    iface.launch()
+print(f"🔍 API Key: {os.getenv('PLANT_ID_API_KEY')}")