# app.py

import streamlit as st
import pandas as pd
from tensorflow.keras.models import load_model

# -----------------------------
# 1️⃣ Model Yükleme
# -----------------------------
model = load_model("src/model.keras")

# -----------------------------
# 2️⃣ Streamlit Başlığı
# -----------------------------
st.title("Diabetes Prediction App")
st.write("Input your health data to predict diabetes probability.")

# -----------------------------
# 3️⃣ Kullanıcı Sayısal Girdileri
# -----------------------------
age = st.number_input("Age", min_value=1, max_value=120, value=30)
bmi = st.number_input("BMI", min_value=10.0, max_value=60.0, value=25.0)
systolic_bp = st.number_input("Systolic BP", min_value=80, max_value=200, value=120)
diastolic_bp = st.number_input("Diastolic BP", min_value=50, max_value=150, value=80)
physical_activity = st.number_input("Physical Activity (minutes/week)", min_value=0, max_value=1000, value=60)
screen_time = st.number_input("Screen Time (hours/day)", min_value=0, max_value=24, value=4)
ldl = st.number_input("LDL Cholesterol", min_value=50, max_value=300, value=120)
hdl = st.number_input("HDL Cholesterol", min_value=20, max_value=100, value=50)

# -----------------------------
# 4️⃣ Input DataFrame
# -----------------------------
input_df = pd.DataFrame([[
    age, bmi, systolic_bp, diastolic_bp, physical_activity, screen_time, ldl, hdl
]],
columns=[
    'age','bmi','systolic_bp','diastolic_bp','physical_activity_minutes_per_week',
    'screen_time_hours_per_day','ldl_cholesterol','hdl_cholesterol'
])

# -----------------------------
# 5️⃣ Opsiyonel Feature Engineering
# -----------------------------
input_df['cholesterol_ratio'] = input_df['ldl_cholesterol'] / (input_df['hdl_cholesterol'] + 1e-5)
input_df['activity_screen_ratio'] = input_df['physical_activity_minutes_per_week'] / (input_df['screen_time_hours_per_day'] + 1)

# -----------------------------
# 6️⃣ Tahmin
# -----------------------------
prediction = model.predict(input_df)[0][0]

# -----------------------------
# 7️⃣ Tahmin Sonucu Gösterimi
# -----------------------------
st.subheader("Prediction")
st.write(f"Predicted probability of diabetes: **{prediction:.2f}**")