app.py

import pickle
from pathlib import Path

import pandas as pd
import streamlit as st


MODEL_PATH = Path(__file__).with_name("ufo-model.pkl")
COUNTRIES = ["Australia", "Canada", "Germany", "UK", "US"]
FEATURE_COLUMNS = ["Seconds", "Latitude", "Longitude"]


@st.cache_resource
def load_model():
    with MODEL_PATH.open("rb") as model_file:
        return pickle.load(model_file)


st.set_page_config(page_title="UFO Predictor", layout="centered")
st.title("UFO Country Predictor")
st.write("Predict the likely reporting country from sighting duration and coordinates.")

seconds = st.number_input("Seconds", min_value=1.0, max_value=60.0, value=10.0)
latitude = st.number_input("Latitude", value=44.0)
longitude = st.number_input("Longitude", value=-12.0)

if st.button("Predict"):
    model = load_model()
    features = pd.DataFrame(
        [[seconds, latitude, longitude]],
        columns=FEATURE_COLUMNS,
    )
    class_id = int(model.predict(features)[0])
    st.success(f"Likely country: {COUNTRIES[class_id]}")
    st.caption(f"Class id: {class_id}")