Update src/app.py

src/app.py

@@ -3,9 +3,7 @@ import joblib
 import numpy as np
 import pandas as pd
 
-# ----------------------------
-# Load Saved Model & Encoders
-# ----------------------------
+# Load model and encoders
 try:
     model = joblib.load("src/best_stroke_model_1.pkl")
     x_num_scaler = joblib.load("src/x_num_scaler_1.pkl")
@@ -15,16 +13,12 @@ except Exception as e:
     st.error(f"Failed to load model or encoders: {e}")
     st.stop()
 
-# ----------------------------
-# Streamlit Layout
-# ----------------------------
+# Streamlit layout
 st.set_page_config(page_title="Stroke Prediction App", page_icon="🧠", layout="centered")
 st.title("🧠 Stroke Prediction App")
 st.write("Fill in the details below to check the risk of stroke.")
 
-# ----------------------------
-# Input Fields
-# ----------------------------
+# Input fields
 gender = st.selectbox("Gender", ["Male", "Female", "Other"])
 age = st.number_input("Age", min_value=1, max_value=120, value=30)
 hypertension = st.selectbox("Hypertension (0=No, 1=Yes)", [0, 1])
@@ -34,9 +28,7 @@ avg_glucose_level = st.number_input("Average Glucose Level", min_value=50.0, max
 bmi = st.number_input("BMI", min_value=10.0, max_value=50.0, value=22.0)
 smoking_status = st.selectbox("Smoking Status", ["never smoked", "formerly smoked", "smokes", "Unknown"])
 
-# ----------------------------
-# Prediction Button
-# ----------------------------
+# Prediction button
 if st.button("Predict"):
     input_df = pd.DataFrame([[gender, age, hypertension, heart_disease, work_type, avg_glucose_level, bmi, smoking_status]],
                             columns=["gender", "age", "hypertension", "heart_disease", "work_type", "avg_glucose_level", "bmi", "smoking_status"])