import pandas as pd
import pickle
import numpy as np
import streamlit as st
import gdown
import os

# File IDs
model_id = "1HSQTjJ_hvBBmVJmYUmrkq5T7ubpfDwzF"
top_country_id = "1aLkaAqfrs3GcrMvZcuyQ0NjFhAhrdIlR"

model_url = f"https://drive.google.com/uc?id={model_id}"
top_country_url = f"https://drive.google.com/uc?id={top_country_id}"


@st.cache_resource
def load_model():
    model_path = "best_rf_model.pkl"
    if not os.path.exists(model_path):
        gdown.download(model_url, model_path, quiet=False)
    with open(model_path, "rb") as f:
        return pickle.load(f)


@st.cache_resource
def load_top_country():
    country_path = "top_country.pkl"
    if not os.path.exists(country_path):
        gdown.download(top_country_url, country_path, quiet=False)
    with open(country_path, "rb") as f:
        return pickle.load(f)


model = load_model()
top_country = load_top_country()

st.set_page_config(page_title="Hotel Booking Prediction", layout="wide")

st.markdown(
    """
<div style="
    background-color: white;
    padding: 50px;
    border-radius: 20px;
    box-shadow: 0 4px 20px rgba(0,0,0,0.1);
    max-width: 800px;
    margin: auto;
    text-align: center;
">
    <h1 style="font-size:60px; font-weight:bold; color:black; margin-bottom:20px;">
        Hotel Booking Prediction
    </h1>
    <p style="font-size:20px; color:gray; margin-bottom:30px;">
        Welcome to Hotel Booking Prediction System
    </p>
    <p style="font-size:15px; color:black;">
        Fill in the form below to predict hotel booking!
    </p>
</div>
""",
    unsafe_allow_html=True,
)

st.write("")
st.write("")

with st.form(key="hotel_bookings"):
    col1, col2 = st.columns(2)

    with col1:
        name = st.selectbox("Hotel Type", ("city_hotel", "resort_hotel"), index=0)
        lead = st.number_input(
            "Lead Time",
            min_value=0,
            max_value=600,
            value=0,
            step=1,
            help="jarak antar waktu booking dan check-in",
        )
        arrival_year = st.selectbox("Arrival Year", ("2015", "2016", "2017"), index=0)
        arrival_month = st.selectbox(
            "Arrival Months",
            (
                "January",
                "February",
                "March",
                "April",
                "May",
                "June",
                "July",
                "August",
                "September",
                "October",
                "November",
                "December",
            ),
            index=0,
        )

    with col2:
        arrival_week = st.number_input(
            "Arrival Weeks",
            min_value=1,
            max_value=52,
            value=1,
            step=1,
            help="minggu kedatangan",
        )
        arrival_day = st.number_input(
            "Arrival Days",
            min_value=1,
            max_value=31,
            value=1,
            step=1,
            help="tanggal kedatangan",
        )

    submitted = st.form_submit_button("Predict", use_container_width=True)

    if submitted:
        # Prepare data for prediction
        data = {
            "hotel": name,
            "lead_time": lead,
            "arrival_date_year": int(arrival_year),
            "arrival_date_month": arrival_month,
            "arrival_date_week_number": arrival_week,
            "arrival_date_day_of_month": arrival_day,
        }

        df = pd.DataFrame([data])

        try:
            prediction = model.predict(df)

            st.success("Prediction Complete!")

            if prediction[0] == 1:
                st.error("⚠️ This booking is likely to be CANCELLED")
            else:
                st.success("✅ This booking is likely to be CONFIRMED")

        except Exception as e:
            st.error(f"Error making prediction: {str(e)}")