Update app.py

app.py

@@ -1,21 +1,20 @@
 import streamlit as st
+import joblib
 import numpy as np
-import joblib  # use joblib instead of pickle
 
-# Load model with joblib
-model = joblib.load("log_reg_model.pkl")
+# Load your model
+model = joblib.load("log_reg_model.pkl")  # or "log_reg_model.pkl"
 
-st.title("AI Sleep State Detection")
-st.markdown("Enter **angle** and **enmo** to predict the sleep state:")
+# Streamlit App UI
+st.title("AI Sleep State Detector")
+st.write("Predict sleep state (`onset` or `wakeup`) using step count and hour.")
 
-angle = st.number_input("Angle", min_value=0.0, max_value=360.0, step=0.1)
-enmo = st.number_input("ENMO", min_value=0.0, max_value=2.0, step=0.01)
+# Input Features
+step = st.number_input("Step count:", min_value=0, max_value=10000, value=0)
+hour = st.slider("Hour of day (0–23):", min_value=0, max_value=23, value=0)
 
-if st.button("Detect Sleep State"):
-    input_data = np.array([[angle, enmo]])
+# Predict Button
+if st.button("Predict Sleep State"):
+    input_data = np.array([[step, hour]])
     prediction = model.predict(input_data)[0]
-
-    if prediction == 0:
-        st.success("Sleep State: **Wakeup**")
-    else:
-        st.success("Sleep State: **Onset**")
+    st.success(f"Predicted Sleep State: **{prediction}**")