app.py

import os
import requests
import streamlit as st
import pandas as pd
from scraper import scrape_tariffs
from groq import Groq

# Initialize Groq client
client = Groq(api_key=os.environ.get('GroqApi'))

# Streamlit App: ⚡ EnergyGuru_PowerCalc: AI-Driven Bill & Carbon Footprint Tracker
st.title("⚡ EnergyGuru_PowerCalc: AI-Driven Bill & Carbon Footprint Tracker")
st.sidebar.header("⚙️ User Input")

# Tariff URLs for scraping
tariff_urls = {
    "IESCO": "https://iesco.com.pk/index.php/customer-services/tariff-guide",
    "FESCO": "https://fesco.com.pk/tariff",
    "HESCO": "http://www.hesco.gov.pk/htmls/tariffs.htm",
    "KE": "https://www.ke.com.pk/customer-services/tariff-structure/",
    "LESCO": "https://www.lesco.gov.pk/ElectricityTariffs",
    "PESCO": "https://pesconlinebill.pk/pesco-tariff/",
    "QESCO": "http://qesco.com.pk/Tariffs.aspx",
    "TESCO": "https://tesco.gov.pk/index.php/electricity-traiff",
}

# Predefined appliances and their power in watts
appliances = {
    "LED Bulb (10W)": 10,
    "Ceiling Fan (75W)": 75,
    "Refrigerator (150W)": 150,
    "Air Conditioner (1.5 Ton, 1500W)": 1500,
    "Washing Machine (500W)": 500,
    "Television (100W)": 100,
    "Laptop (65W)": 65,
    "Iron (1000W)": 1000,
    "Microwave Oven (1200W)": 1200,
    "Water Heater (2000W)": 2000,
}

def scrape_data():
    """
    Scrapes tariff data from the provided URLs.
    """
    st.info("🔄 Scraping tariff data... Please wait.")
    scrape_tariffs(list(tariff_urls.values()))
    st.success("✅ Tariff data scraping complete.")

def calculate_carbon_footprint(monthly_energy_kwh):
    """
    Calculates the carbon footprint based on energy consumption in kWh.
    """
    carbon_emission_factor = 0.75  # kg CO2 per kWh
    return monthly_energy_kwh * carbon_emission_factor

# Sidebar: Scrape Tariff Data
if st.sidebar.button("Scrape Tariff Data"):
    scrape_data()

# Sidebar: Tariff Selection
st.sidebar.subheader("💡 Select Tariff")
try:
    tariff_data = pd.read_csv("data/tariffs.csv")
    tariff_types = tariff_data["category"].unique()
    selected_tariff = st.sidebar.selectbox("Select your tariff category:", tariff_types)
    rate_per_kwh = tariff_data[tariff_data["category"] == selected_tariff]["rate"].iloc[0]
    st.sidebar.write(f"Rate per kWh: **{rate_per_kwh} PKR**")
except FileNotFoundError:
    st.sidebar.error("⚠️ Tariff data not found. Please scrape the data first.")
    rate_per_kwh = 0

# Sidebar: User Inputs for Appliances
st.sidebar.subheader("🏠 Add Appliances")
selected_appliance = st.sidebar.selectbox("Select an appliance:", list(appliances.keys()))
appliance_power = appliances[selected_appliance]
appliance_quantity = st.sidebar.number_input(
    "Enter quantity:", min_value=1, max_value=10, value=1
)
usage_hours = st.sidebar.number_input(
    "Enter usage hours per day:", min_value=1, max_value=24, value=5
)

# Add appliance details to the main list
if "appliance_list" not in st.session_state:
    st.session_state["appliance_list"] = []

if st.sidebar.button("Add Appliance"):
    st.session_state["appliance_list"].append(
        {
            "appliance": selected_appliance,
            "power": appliance_power,
            "quantity": appliance_quantity,
            "hours": usage_hours,
        }
    )

# Display the list of added appliances
st.subheader("📋 Added Appliances")
if st.session_state["appliance_list"]:
    for idx, appliance in enumerate(st.session_state["appliance_list"], start=1):
        st.write(
            f"{idx}. **{appliance['appliance']}** - "
            f"{appliance['power']}W, {appliance['quantity']} unit(s), "
            f"{appliance['hours']} hours/day"
        )

# Electricity Bill and Carbon Footprint Calculation
if st.session_state["appliance_list"] and rate_per_kwh > 0:
    total_daily_energy_kwh = sum(
        (appliance["power"] * appliance["quantity"] * appliance["hours"]) / 1000
        for appliance in st.session_state["appliance_list"]
    )
    monthly_energy_kwh = total_daily_energy_kwh * 30  # Assume 30 days in a month
    bill_amount = monthly_energy_kwh * rate_per_kwh  # Dynamic tariff rate
    carbon_footprint = calculate_carbon_footprint(monthly_energy_kwh)

    st.subheader("💵 Electricity Bill & 🌍 Carbon Footprint")
    st.write(f"💵 **Estimated Electricity Bill**: **{bill_amount:.2f} PKR**")
    st.write(f"🌍 **Estimated Carbon Footprint**: **{carbon_footprint:.2f} kg CO2 per month**")

    # Generate Groq-based advice to reduce carbon footprint
    appliance_names = [appliance["appliance"] for appliance in st.session_state["appliance_list"]]
    appliance_list_str = ", ".join(appliance_names)

    chat_completion = client.chat.completions.create(
        messages=[{
            "role": "user",
            "content": (
                f"Provide exactly 3 to 4 short, one-line tips to reduce the carbon footprint caused "
                f"by the usage of the following appliances: {appliance_list_str}. The tips should be "
                f"practical and relevant to these appliances only."
            )
        }],
        model="llama3-8b-8192",
    )

    advice = chat_completion.choices[0].message.content
    st.subheader("💡 Tips to Reduce Carbon Footprint")
    st.write(advice)
else:
    st.info("ℹ️ Add appliances to calculate the electricity bill and carbon footprint.")

# Footer
st.markdown("---")
st.markdown(
    "<div style='text-align: center; padding: 10px;'>"
    "Designed by EnergyGuru - Powered by AI Driven Tracker<br>"
    "</div>",
    unsafe_allow_html=True
)