app.py

import gradio as gr
import joblib
import numpy as np

# ✅ Load the model correctly using joblib
model = joblib.load("log_reg_model.pkl")

# Define prediction function
def predict_sleep(step: float, hour: float):
    input_data = np.array([[step, hour]])
    prediction = model.predict(input_data)[0]
    return "Sleep Onset" if prediction == 1 else "Wakeup"

# Gradio interface
iface = gr.Interface(
    fn=predict_sleep,
    inputs=[
        gr.Number(label="Step Count"),
        gr.Number(label="Hour (0–23)")
    ],
    outputs=gr.Text(label="Prediction"),
    title="Sleep Prediction (Onset/Wakeup)",
    description="Enter step count and hour to predict whether it's sleep onset or wakeup."
)

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