Create app.py

app.py

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+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.")