Update app.py

app.py

@@ -13,6 +13,11 @@ st.set_page_config(
 # --- Custom CSS ---
 st.markdown("""
 <style>
+    /* Force Global Sans-Serif Font */
+    html, body, [class*="css"], .stMarkdown {
+        font-family: 'Inter', 'Segoe UI', Roboto, Helvetica, Arial, sans-serif !important;
+    }
+    
     /* Set Global Font */
     html, body, [class*="css"]  {
         font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;
@@ -72,16 +77,17 @@ st.markdown("""
 
 # --- Title ---
 st.title("🌍 The Climate Cost of the AI Race ⛽️")
-st.markdown("""
-**What will the US emissions of AI be in 2030?** Model the variables below, focused on the efficiency of Natural Gas deployment.
-""")
 
 st.divider()
 
 # --- Sidebar Inputs ---
+st.sidebar.markdown("""
+**What will the US emissions of AI be in 2030?** Model the variables below, focused on the efficiency of Natural Gas deployment.
+""")
 st.sidebar.header("⚙️ Scenario Settings")
 st.sidebar.markdown("---")
 
+
 # 1. AI Power Demand
 st.sidebar.markdown('<p class="sidebar-question">1. How much power will AI require in 2030?</p>', unsafe_allow_html=True)
 ai_demand_gw = st.sidebar.number_input(
@@ -102,7 +108,6 @@ gas_share = st.sidebar.slider(
     min_value=0, max_value=100, value=90, step=5,
     label_visibility="collapsed"
 )
-st.sidebar.caption(f"Selected: **{gas_share}%**")
 
 with st.sidebar.expander("More on Energy Mix"):
     st.markdown("""
@@ -113,6 +118,7 @@ with st.sidebar.expander("More on Energy Mix"):
     While solar prices have dropped ~88% since 2009, it faces physical limits:
     * **Land Use:** 2 GW of solar requires a land area roughly the size of Manhattan.
     * **Uptime:** Solar requires battery backup for 24/7 reliability, adding complexity for off-grid "island" data centers.
+      
       [Source](https://open.substack.com/pub/semianalysis/p/how-ai-labs-are-solving-the-power)
     """)
 
@@ -125,7 +131,6 @@ turbine_eff_percent = st.sidebar.slider(
     min_value=35, max_value=60, value=45, step=1,
     label_visibility="collapsed"
 )
-st.sidebar.caption(f"Selected: **{turbine_eff_percent}%**")
 
 with st.sidebar.expander("More on Turbine Tech"):
     st.markdown("""
@@ -134,6 +139,7 @@ with st.sidebar.expander("More on Turbine Tech"):
     * **Aeroderivative (35-40%):** Modified jet engines (e.g., GE LM2500). They are less efficient but fast to deploy. Companies like xAI use them to bypass grid delays.
     * **Reciprocating Engines (40-50%):** Modular internal combustion engines (e.g., Wärtsilä). They offer higher efficiency than aeroderivatives and handle partial loads well.
     * **Combined Cycle (50-60%):** The gold standard for efficiency, using waste heat to drive a steam turbine. However, they take 36-60 months to build, making them too slow for the current AI race.
+      
       [Source](https://open.substack.com/pub/semianalysis/p/how-ai-labs-are-solving-the-power)
     """)
 
@@ -211,14 +217,29 @@ fig1.add_trace(go.Bar(
 ))
 
 fig1.update_layout(
-    yaxis_title="Emissions (Million tCO2e)",
+    height=650,  # Increased height
+    font=dict(size=18), # Global font scale
+    title=dict(
+        text="Can we hit the 50% reduction target?",
+        font=dict(size=24) # Explicit title size
+    ),
+    yaxis=dict(
+        title="Emissions (Million tCO2e)",
+        titlefont=dict(size=20),
+        tickfont=dict(size=16)
+    ),
+    xaxis=dict(
+        tickfont=dict(size=16)
+    ),
     barmode='stack',
-    font=dict(
-        size=16,
+    legend=dict(
+        orientation="h",
+        y=-0.2,
+        x=0.5,
+        xanchor='center',
+        font=dict(size=18) # Larger legend text
     ),
-    legend=dict(orientation="h", y=1.1, x=0.5, xanchor='center'),
-    height=500,
-    margin=dict(l=40, r=40, t=40, b=40),
+    margin=dict(l=50, r=50, t=80, b=50),
     hovermode="x unified"
 )