import streamlit as st
import joblib
import numpy as np

with open("src/taxi_linear", "rb") as f:
    model = joblib.load(f)
with open("src/X_scaler", "rb") as f:
    scaler = joblib.load(f)


st.title(":orange[Taxi] Fare Estimation :taxi:")

passengers = st.number_input("Passengers : ", min_value=1, max_value=6, step=1)
distance = st.number_input("Distance : ", min_value=0.1, max_value=100.0, step=1.0)
tips = st.number_input("Tips : ", min_value=0.1, max_value=50.0, step=1.0)
tolls = st.number_input("Tolls : ", min_value=1, max_value=15, step=1)

if st.button("Estimate"):
    model_input = np.array([[passengers, distance, tips, tolls]])
    model_input = scaler.transform(model_input)
    prediction  = model.predict(model_input)
    formatted_pred = round(prediction[0], 2)
    st.write(f"Your Fare : {formatted_pred}")