app.py

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("bW56klawyFv1jspkrbj3GBhmueOznSQIR3FQJFNawEuTjmVjeH")

if not PLANT_ID_API_KEY:
    raise ValueError("❌ API Key is missing! Set PLANT_ID_API_KEY in Hugging Face Secrets or .env file.")

# 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)}"

# Gradio Interface with Improved UI
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 from Plant.id API.  
    ✅ Supports **multiple plant species**  
    ✅ Instant **AI-powered analysis**  
    ✅ Get **organic & chemical treatment suggestions**  
    """,
    theme="compact",
    allow_flagging="never",
)

# **Ensure this part runs correctly in Hugging Face Spaces**
if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=7860)