import gradio as gr
from model.predictor import LBWPredictor
from utils.preprocess import clean_input

predictor = LBWPredictor("model/lbw_model.joblib")

def predict_interface(**kwargs):
    features = clean_input(kwargs)
    return predictor.predict(features)

with gr.Blocks() as demo:
    gr.Markdown("# GullyDRS: LBW Predictor 🏏")
    inputs = [
        gr.Number(label="Ball Speed (km/h)", value=130),
        gr.Number(label="Impact X", value=0.25),
        gr.Number(label="Impact Y", value=0.5),
        gr.Number(label="Stump Height", value=0.71)
    ]
    btn = gr.Button("Predict LBW")
    output = gr.Textbox(label="Decision")

    btn.click(predict_interface, inputs=inputs, outputs=output)

demo.launch()