Update app.py

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 import os
 from groq import Groq
 import pandas as pd
+import matplotlib.pyplot as plt
 
 # Set the API Key (ensure the key is properly stored as an environment variable)
 GROQ_API_KEY = "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"
@@ -10,9 +11,11 @@ client = Groq(api_key=GROQ_API_KEY)
 # 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
-    return total_energy
+        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 = {
@@ -68,6 +71,8 @@ for i in range(appliance_count):
         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}
 
@@ -79,13 +84,15 @@ if st.sidebar.button("Add Appliance"):
 if st.sidebar.button("Reset Appliances"):
     reset_appliances()
 
-location = st.sidebar.text_input("Enter your Location")
-budget = st.sidebar.number_input("Enter your Budget (in USD)", min_value=100, step=10)
+# 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 = calculate_energy(st.session_state.appliances)
+    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")
 
     # Interact with the Groq API
     prompt = f"Provide solar recommendations for a location: {location}, daily energy: {daily_energy:.2f} kWh, budget: {budget} USD."
@@ -96,7 +103,7 @@ if st.sidebar.button("Submit"):
         )
         answer = response.choices[0].message.content
         st.write("### Recommendations")
-        st.button(answer)
+        st.write(answer)
     except Exception as e:
         st.error(f"Error with Groq API: {e}")
 
@@ -114,11 +121,27 @@ if st.sidebar.button("Submit"):
     - **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}
-        for k, v in st.session_state.appliances.items()
-    ])
-    st.table(appliance_data)
+    # 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.")
+
+