app.py

import streamlit as st
import os
from transformers import RagTokenizer, RagRetriever, RagSequenceForGeneration
import pandas as pd
import matplotlib.pyplot as plt

# Streamlit App
st.title("SustainaBot: Solar Energy Advisor")
st.sidebar.header("User Input")

# Input for Groq API Key
GROQ_API_KEY = "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"
client = Groq(api_key = GROQ_API_KEY)

# Initialize the RAG components
tokenizer = RagTokenizer.from_pretrained("facebook/rag-token-nq")
retriever = RagRetriever.from_pretrained("facebook/rag-token-nq")
model = RagSequenceForGeneration.from_pretrained("facebook/rag-token-nq")

# Helper function for energy demand calculation
def calculate_energy(appliances):
    total_energy = 0
    total_power = 0
    for app, details in appliances.items():
        total_energy += details['quantity'] * details['wattage'] * details['hours'] / 1000  # Energy in kWh
        total_power += details['quantity'] * details['wattage']  # Power in Watts
    return total_energy, total_power

# Predefined appliances with their default wattage
predefined_appliances = {
    "Select Appliance": 0,  # Default placeholder
    "LED Light": 10,
    "Air Conditioner": 2000,
    "Refrigerator": 150,
    "Washing Machine": 500,
    "Fan": 75,
    "Laptop": 50,
    "Television": 100,
    "Microwave Oven": 1000,
    "Electric Water Heater": 1500,
    "Dishwasher": 1200,
    "Coffee Maker": 800,
    "Toaster": 1200,
    "Hair Dryer": 1500,
    "Electric Kettle": 1500,
    "Oven": 2000,
    "Vacuum Cleaner": 1000,
    "Iron": 1200,
    "Blender": 300,
    "Clothes Dryer": 1800,
    "Space Heater": 1500,
    "Dehumidifier": 700,
    "Freezer": 400,
    "Electric Grill": 1200,
    "Sewing Machine": 100,
    "Projector": 300,
    "Gaming Console": 200,
    "Electric Fan Heater": 1500
}

if "appliances" not in st.session_state:
    st.session_state.appliances = {}

# Function to reset appliance state
def reset_appliances():
    st.session_state.appliances = {}

# Add appliance inputs dynamically
appliance_count = len(st.session_state.appliances)
for i in range(appliance_count):
    with st.sidebar.expander(f"Appliance {i+1} Details"):
        app_name = st.selectbox(f"Appliance {i+1} Name", options=list(predefined_appliances.keys()), key=f"app{i}_name")
        quantity = st.number_input(f"Quantity of {app_name}", min_value=1, step=1, key=f"app{i}_quantity", value=1)
        wattage = predefined_appliances.get(app_name, 0)  # Default wattage
        hours = st.number_input(f"Hours used per day", min_value=1, step=1, key=f"app{i}_hours", value=1)
        power = quantity * wattage
        st.write(f"**Total Power (Watts):** {power} W")
        if app_name and app_name != "Select Appliance":
            st.session_state.appliances[app_name] = {"quantity": quantity, "wattage": wattage, "hours": hours}

# Button to add more appliances
if st.sidebar.button("Add Appliance"):
    st.session_state.appliances[f"Appliance {len(st.session_state.appliances) + 1}"] = {"quantity": 1, "wattage": 0, "hours": 0}

# Button to reset appliances
if st.sidebar.button("Reset Appliances"):
    reset_appliances()

# Input for location and budget
location = st.sidebar.text_input("Enter your Location (City, Country)")
budget = st.sidebar.number_input("Enter your Budget for Solar System (in USD)", min_value=100, step=10)

if st.sidebar.button("Submit"):
    # Calculate energy demand
    daily_energy, total_power = calculate_energy(st.session_state.appliances)
    st.write(f"### Total Daily Energy Demand: {daily_energy:.2f} kWh")
    st.write(f"### Total Power Demand: {total_power:.2f} W")

    # RAG model interaction
    prompt = f"Provide solar recommendations for a location: {location}, daily energy: {daily_energy:.2f} kWh, budget: {budget} USD."

    # Tokenizing and retrieval process
    inputs = tokenizer(prompt, return_tensors="pt")
    question_input = inputs['input_ids']
    doc_scores, docs = retriever(question_input)

    # Generating the response
    generated_output = model.generate(input_ids=question_input, context_input_ids=docs[0]['text'])
    answer = tokenizer.decode(generated_output[0], skip_special_tokens=True)

    st.write("### Solar Recommendations")
    st.write(answer)

    # Display potential savings and pricing (same as before)
    savings = daily_energy * 30 * 0.2  # Assuming $0.2/kWh savings
    st.write(f"By switching to solar, you could save approximately **${savings:.2f} per month!**")

    # Approximate Pricing Section
    st.write("### Solar Installation Prices")
    st.write("""
    - **1 kW System:** Approx. PKR 120,000 - 150,000
    - **3 kW System:** Approx. PKR 350,000 - 400,000
    - **5 kW System:** Approx. PKR 600,000 - 700,000
    - **10 kW System:** Approx. PKR 1,200,000 - 1,500,000
    """)

    # Visualization
    st.write("### Appliance Breakdown")
    if st.session_state.appliances:
        appliance_data = pd.DataFrame([
            {"Appliance": k, "Quantity": v['quantity'], "Daily Energy (kWh)": v['quantity'] * v['wattage'] * v['hours'] / 1000, "Power (W)": v['quantity'] * v['wattage']}
            for k, v in st.session_state.appliances.items()
        ])
        st.table(appliance_data)

        # Bar chart for visualization
        st.write("### Energy Consumption by Appliance")
        fig, ax = plt.subplots()
        ax.bar(appliance_data["Appliance"], appliance_data["Daily Energy (kWh)"], color='skyblue')
        ax.set_xlabel("Appliances")
        ax.set_ylabel("Daily Energy (kWh)")
        ax.set_title("Energy Consumption Breakdown")
        plt.xticks(rotation=45, ha="right")
        st.pyplot(fig)

        # Highlight the most energy-consuming appliance
        max_energy_app = appliance_data.loc[appliance_data["Daily Energy (kWh)"].idxmax()]
        st.write(f"**Most Energy-Consuming Appliance:** {max_energy_app['Appliance']} consuming {max_energy_app['Daily Energy (kWh)']:.2f} kWh daily.")