Fix: use_column_width for older Streamlit on HF

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

app.py

@@ -101,7 +101,7 @@ selected_product = st.sidebar.selectbox(
 config = products[selected_product]
 
 if "image_url" in products[selected_product].get("product", {}):
-    st.sidebar.image(products[selected_product]["product"]["image_url"], use_container_width=True)
+    st.sidebar.image(products[selected_product]["product"]["image_url"], use_column_width=True)
 
 st.sidebar.markdown("---")
 st.sidebar.header("View")
@@ -490,7 +490,7 @@ if selected_view == "Strategy":
             xaxis_title="Months", yaxis_title="Cumulative Profit (NOK)",
             showlegend=False, yaxis=dict(separatethousands=True),
         )
-        st.plotly_chart(fig_be, use_container_width=True)
+        st.plotly_chart(fig_be, use_column_width=True)
 
     st.markdown("---")
 
@@ -543,7 +543,7 @@ if selected_view == "Strategy":
         yaxis_title="NOK", showlegend=False,
         yaxis=dict(separatethousands=True),
     )
-    st.plotly_chart(fig_rc, use_container_width=True)
+    st.plotly_chart(fig_rc, use_column_width=True)
 
     mfg_share = s_mfg_cost / reuse_cycles if reuse_cycles > 0 else s_mfg_cost
     st.caption(f"Blended cost breakdown: Mfg share {sfmt(mfg_share)} + logistics {sfmt(logistics_per_cycle)} + repair {sfmt(repair_per_cycle)} = **{sfmt(blended_cost_per_product)} NOK** per product per cycle")
@@ -622,7 +622,7 @@ if selected_view == "Strategy":
                 xaxis_title="Months", yaxis_title="Cumulative Profit (NOK)",
                 showlegend=False, yaxis=dict(separatethousands=True),
             )
-            st.plotly_chart(fig_trajectory, use_container_width=True)
+            st.plotly_chart(fig_trajectory, use_column_width=True)
 
             final_profit = cumulative_profit[-1]
             st.caption(f"5-year projection with {sfmt(fleet_needed)} unit fleet. Final cumulative profit: **{sfmt(final_profit)} NOK**")
@@ -662,7 +662,7 @@ if selected_view == "Strategy":
         yaxis=dict(separatethousands=True, rangemode="tozero"),
         legend=dict(orientation="h", yanchor="bottom", y=1.02),
     )
-    st.plotly_chart(fig_fleet, use_container_width=True)
+    st.plotly_chart(fig_fleet, use_column_width=True)
     savings = customers_served[-1] - portfolio_size
     st.caption(f"{sfmt(portfolio_size)} products serve **{sfmt(customers_served[-1])} families** over {reuse_cycles} cycles — **{sfmt(savings)} fewer products** manufactured vs linear model.")
 
@@ -705,7 +705,7 @@ elif selected_view == "Design":
     )
     fig_grades.update_traces(texttemplate='%{text:.0f}%', textposition='outside')
     fig_grades.update_layout(showlegend=False, yaxis_title="% of Returns")
-    st.plotly_chart(fig_grades, use_container_width=True)
+    st.plotly_chart(fig_grades, use_column_width=True)
 
     st.info(f"**Design insight:** Reducing repair rate from {grade_b_pct:.0%} to {max(5, grade_b_pct*100-10):.0f}% would save €{(grade_b_pct - max(0.05, grade_b_pct-0.10)) * refurb_b:.0f} per returned product.")
 
@@ -758,7 +758,7 @@ elif selected_view == "Design":
         yaxis_title="Material Composition (%)", yaxis_range=[0, 120],
         legend=dict(orientation="h", yanchor="bottom", y=1.02),
     )
-    st.plotly_chart(fig_materials, use_container_width=True)
+    st.plotly_chart(fig_materials, use_column_width=True)
 
     final_original = lifecycle_df.iloc[-1]["Original Material %"]
     final_new = lifecycle_df.iloc[-1]["New Parts Added %"]
@@ -805,7 +805,7 @@ elif selected_view == "Logistics":
         )
         fig_grades.update_traces(texttemplate='%{text:.0f}%', textposition='outside')
         fig_grades.update_layout(showlegend=False, yaxis_title="% of Returns")
-        st.plotly_chart(fig_grades, use_container_width=True)
+        st.plotly_chart(fig_grades, use_column_width=True)
 
     with grade_col2:
         st.subheader("Cost per Cycle")
@@ -827,7 +827,7 @@ elif selected_view == "Logistics":
         fig_cycle.add_trace(go.Bar(name="Logistics", x=df_cycle_costs["Cycle"], y=df_cycle_costs["Logistics"],
                                    marker_color=COLORS["secondary"], text=[f"€{v:.0f}" for v in df_cycle_costs["Logistics"]], textposition="inside"))
         fig_cycle.update_layout(barmode="stack", yaxis_title="Cost (EUR)", legend=dict(orientation="h", yanchor="bottom", y=1.02))
-        st.plotly_chart(fig_cycle, use_container_width=True)
+        st.plotly_chart(fig_cycle, use_column_width=True)
 
     st.markdown(f"**Key insight:** Cycle 1 costs **€{new_unit_cost:.0f}**. Cycles 2+ cost **€{refurb_unit_cost:.0f}** ({(1-refurb_unit_cost/new_unit_cost)*100:.0f}% reduction)")
 
@@ -875,7 +875,7 @@ elif selected_view == "Logistics":
         xaxis_title="",
         legend=dict(orientation="h", yanchor="bottom", y=1.02),
     )
-    st.plotly_chart(fig_products, use_container_width=True)
+    st.plotly_chart(fig_products, use_column_width=True)
 
     final_in_service = lifecycle_df.iloc[-1]["Products in Service"]
     final_lost = lifecycle_df.iloc[-1]["Products Lost"]
@@ -974,7 +974,7 @@ elif selected_view == "Sourcing":
                 totals={"marker": {"color": COLORS["info"]}},
             ))
             fig_waterfall.update_layout(title=f"Manufacturing Cost: €{mfg_cost:.0f}", yaxis_title="EUR", showlegend=False)
-            st.plotly_chart(fig_waterfall, use_container_width=True)
+            st.plotly_chart(fig_waterfall, use_column_width=True)
 
         with cost_col2:
             st.subheader("Bill of Materials")
@@ -982,7 +982,7 @@ elif selected_view == "Sourcing":
             st.dataframe(mat_df.style.format({
                 "Weight (kg)": "{:.1f}", "Cost/kg": "€{:.2f}",
                 "Total Cost": "€{:.2f}", "Recycled %": "{:.0f}%",
-            }), use_container_width=True, hide_index=True)
+            }), use_column_width=True, hide_index=True)
 
         # Summary
         recyclable_weight = sum(m["Weight (kg)"] for m in material_data if m["Recyclable"] == "Yes")
@@ -1092,7 +1092,7 @@ elif selected_view == "Market":
     ))
     fig_customer.update_layout(title="Customer Cost vs Retail Price", xaxis_title="Monthly Lease Price (EUR)",
                                yaxis_title="Total Customer Cost (EUR)")
-    st.plotly_chart(fig_customer, use_container_width=True)
+    st.plotly_chart(fig_customer, use_column_width=True)
 
     if retail_price > 0 and total_lease_cost < retail_price:
         st.success(f"At €{lease_price}/mo, customers **save €{retail_price - total_lease_cost}** ({(retail_price - total_lease_cost)/retail_price*100:.0f}% less than buying)")