app.py

import gradio as gr
from PIL import Image
from model import predict

def predict_crop(image, crop_name):
    if image is None or not crop_name:
        return {"error": "Image and crop_name are required"}

    prediction, confidence = predict(image, crop_name)

    return {
        "prediction": prediction,
        "confidence": confidence
    }

gr.Interface(
    fn=predict_crop,
    inputs=[
        gr.Image(type="pil"),
        gr.Textbox(label="Crop Name (banana, tomato, rice)")
    ],
    outputs="json",
    api_name="/predict_crop",
    title="LeafBuddy Crop Disease Detection"
).launch()