Create app.py

app.py

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+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
+)