Update app.py

app.py

@@ -2,9 +2,9 @@ import streamlit as st
 import pandas as pd
 import plotly.express as px
 
-# Add custom CSS for the background
+# Add custom CSS for the app background and text styling
 def add_background():
-    background_url = "https://huggingface.co/spaces/ZainMalik0925/GreenLensAI_LCA/resolve/main/BCK2.jpg"
+    background_url = "https://huggingface.co/spaces/ZainMalik0925/GreenLensAI_LCA/resolve/main/BCK1.jpg"
     css = f"""
     <style>
     .stApp {{
@@ -17,6 +17,7 @@ def add_background():
         background-color: rgba(27, 27, 27, 0.7); /* 70% Opaque Black Background */
         padding: 10px;
         border-radius: 5px;
+        margin-bottom: 15px;
         color: white;
     }}
     </style>
@@ -91,7 +92,7 @@ def calculate_footprints(weight, composition, lifecycle_inputs):
 # Sidebar inputs
 def get_inputs(prefix):
     weight = st.sidebar.number_input(f"{prefix} Product Weight (kg)", min_value=0.0, value=0.0, step=0.01, key=f"{prefix}_weight")
-    st.sidebar.markdown(f"<h3 style='color: white;'>{prefix} Material Composition (%)</h3>", unsafe_allow_html=True)
+    st.sidebar.markdown(f"<h3 style='color: black;'>{prefix} Material Composition (%)</h3>", unsafe_allow_html=True)
     cotton = st.sidebar.number_input("Conventional Cotton (%)", 0, 100, 0, step=1, key=f"{prefix}_cotton")
     polyester = st.sidebar.number_input("Polyester (%)", 0, 100, 0, step=1, key=f"{prefix}_polyester")
     nylon = st.sidebar.number_input("Nylon 6 (%)", 0, 100, 0, step=1, key=f"{prefix}_nylon")
@@ -158,6 +159,21 @@ if fiber_impact_data and transport_impact_data and washing_impact_data:
         </div>
         """, unsafe_allow_html=True)
 
+        # Bar chart comparison
+        comparison_data = pd.DataFrame({
+            "Footprint Type": ["Water (kL)", "Energy (MJ)", "Carbon (kg CO2e)"],
+            "Assessment 1": [water1, energy1, carbon1],
+            "Assessment 2": [water2, energy2, carbon2],
+        })
+        fig = px.bar(
+            comparison_data.melt(id_vars="Footprint Type", var_name="Assessment", value_name="Value"),
+            x="Footprint Type",
+            y="Value",
+            color_discrete_sequence=["white"],
+            title="Comparison of Assessments"
+        )
+        st.plotly_chart(style_figure(fig))
+
     else:
         # Input for a single assessment
         weight, composition, lifecycle = get_inputs("Single")
@@ -172,3 +188,13 @@ if fiber_impact_data and transport_impact_data and washing_impact_data:
         <p>- **Carbon Footprint**: {carbon:.2f} kg CO2e</p>
         </div>
         """, unsafe_allow_html=True)
+
+        # Bar chart for single assessment
+        result_data = pd.DataFrame({
+            "Footprint Type": ["Water (kL)", "Energy (MJ)", "Carbon (kg CO2e)"],
+            "Value": [water, energy, carbon]
+        })
+        fig = px.bar(result_data, x="Footprint Type", y="Value", title="Single Assessment Footprint Breakdown")
+        st.plotly_chart(style_figure(fig))
+else:
+    st.error("Failed to load dataset.")