import streamlit as st
import plotly.express as px
from model.predictor import predict_footprint
from utils.reducer import suggest_reduction

st.set_page_config(page_title="GreenPrint AI 🌱", layout="centered")

# Custom CSS for green button
st.markdown("""
    <style>
    div.stButton > button:first-child {
        background-color: #4CAF50;
        color: white;
        border: none;
        padding: 8px 20px;
        border-radius: 8px;
        font-size: 16px;
        transition: 0.3s;
    }
    div.stButton > button:first-child:hover {
        background-color: #45a049;
        color: white;
        border: none;
    }
    </style>
""", unsafe_allow_html=True)


st.markdown("""
    <h1 style='text-align: center; white-space: nowrap; overflow-x: auto; font-size: 2.2rem;'>
        🌿 GreenPrint AI: Carbon Footprint Detector
    </h1>
""", unsafe_allow_html=True)

# Emission factors (same as used in dataset creation)
EMISSION_FACTORS = {
    "Car Travel": 0.2,                    # kg CO₂ per km
    "Electricity": 0.5,                   # kg CO₂ per unit (kWh)
    "Meat Consumption": 27 / 7,           # Assuming avg 1 kg per 7 meals
    "Flights": 250                        # kg CO₂ per flight
}

# User Input
with st.form("activity_form"):
    car_km = st.number_input("🚗 Car travel per week (km)", 0, 1000, 50)
    electricity = st.number_input("💡 Electricity usage per month (units)", 0, 1000, 200)
    meat = st.number_input("🍖 Meat meals per week", 0, 21, 7)
    flights = st.number_input("✈️ Flights per year", 0, 20, 1)

    submitted = st.form_submit_button("Calculate")

if submitted:
    user_input = {
        "car_km_per_week": car_km,
        "electricity_units_per_month": electricity,
        "meat_meals_per_week": meat,
        "flights_per_year": flights
    }

    result = predict_footprint(user_input)
    st.success(f"Estimated Annual Carbon Footprint: **{result:.2f} kg CO₂**")

    # Activity-wise contribution calculation
    yearly_values = {
        "Car Travel": car_km * 52 * EMISSION_FACTORS["Car Travel"],
        "Electricity": electricity * 12 * EMISSION_FACTORS["Electricity"],
        "Meat Consumption": meat * 52 * EMISSION_FACTORS["Meat Consumption"],
        "Flights": flights * EMISSION_FACTORS["Flights"]
    }

    # Pie chart with green shades and percent labels
    st.markdown("### 🧾 Activity-wise Contribution to Your Footprint")

    green_colors = ['#006400', '#228B22', '#32CD32', '#7CFC00']  # dark to light green
    fig = px.pie(
        names=yearly_values.keys(),
        values=yearly_values.values(),
        title="Your Carbon Footprint Breakdown",
        color_discrete_sequence=green_colors,
        hole=0.3
    )
    fig.update_traces(textinfo='label+percent', textfont_size=16)

    st.plotly_chart(fig, use_container_width=True)

    st.markdown("---")
    st.subheader("♻️ Suggestions to Reduce Your Footprint")
    for tip in suggest_reduction(user_input):
        st.markdown(f"- {tip}")

    st.markdown("---")
    st.markdown("<div style='text-align:center;'>Made with 💚 by Parishri</div>", unsafe_allow_html=True)