src/streamlit_app.py

import streamlit as st
import pandas as pd
import joblib
import os

# ======================
# LOAD MODEL
# ======================
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
model = joblib.load(os.path.join(BASE_DIR, "heart_model.pkl"))

# ======================
# PAGE CONFIG
# ======================
st.set_page_config(
    page_title="Heart Disease Prediction",
    page_icon="❤️",
    layout="centered"
)

st.title("❤️ Heart Disease Prediction")
st.write("Predict the risk of heart disease based on patient data")

# ======================
# SIDEBAR INPUTS
# ======================
st.sidebar.header("Patient Information")

age = st.sidebar.slider("Age", 20, 100, 50)
sex = st.sidebar.selectbox("Sex", ["Female", "Male"])
sex = 0 if sex == "Female" else 1
cp = st.sidebar.slider("Chest Pain Type (cp)", 0, 3, 1)
trestbps = st.sidebar.number_input("Resting Blood Pressure", 80, 200, 120)
chol = st.sidebar.number_input("Cholesterol", 100, 600, 200)
fbs = st.sidebar.selectbox("Fasting Blood Sugar > 120 mg/dl", [0, 1])
thalach = st.sidebar.number_input("Max Heart Rate Achieved", 60, 220, 150)
exang = st.sidebar.selectbox("Exercise Induced Angina", [0, 1])
oldpeak = st.sidebar.slider("ST Depression (oldpeak)", 0.0, 6.0, 1.0)

# ======================
# DATAFRAME
# ======================
input_df = pd.DataFrame({
    "age": [age],
    "sex": [sex],
    "cp": [cp],
    "trestbps": [trestbps],
    "chol": [chol],
    "fbs": [fbs],
    "thalach": [thalach],
    "exang": [exang],
    "oldpeak": [oldpeak]
})

st.subheader("Patient Data")
st.write(input_df)

# ======================
# PREDICTION
# ======================
if st.button("Predict"):

    prediction = model.predict(input_df)[0]
    probability = model.predict_proba(input_df)[0][1]

    st.subheader("Result")

    if prediction == 1:
        st.error(f"⚠️ High Risk of Heart Disease ({probability:.2%})")
    else:
        st.success(f"✅ Low Risk of Heart Disease ({1 - probability:.2%})")