app.py

import gradio as gr
import pandas as pd
from joblib import load

def predict_bodymass(FlipperLength):
    model = load("penguin_predictor.jb")

    # Create DataFrame from input
    data = {
        "FlipperLength": [FlipperLength]
    }
    xin = pd.DataFrame(data)
    
    bodymass = model.predict(xin)
    return bodymass[0]

iface = gr.Interface(
    fn=predict_bodymass,
    inputs=[
        gr.inputs.Number(
            label="Flipper Length (mm)",
            min_value=0,
            max_value=500,
            default=0
        )
    ],
    outputs=gr.outputs.Textbox(label="Body Mass"),
    title="PENGUIN REGRESSION"
)

if __name__ == "__main__":
    iface.launch()