Update app.py

app.py

@@ -52,6 +52,21 @@ st.markdown("""
 </style>
 """, unsafe_allow_html=True)
 
+# CSS to make sticky headers work correctly by overriding Streamlit's overflow property
+st.markdown("""
+<style>
+/* This targets the main content area */
+.main .block-container {
+    overflow: unset !important;
+}
+
+/* This targets the vertical block that holds all your elements */
+div[data-testid="stVerticalBlock"] {
+    overflow: unset !important;
+}
+</style>
+""", unsafe_allow_html=True)
+
 # Hide uploader helper text ("Drag and drop file here", limits, etc.)
 st.markdown("""
 <style>
@@ -118,7 +133,7 @@ def add_password_gate() -> None:
 
     st.sidebar.markdown(f"""
         <div class="centered-container">
-            <img src="{inline_logo('logo.png')}" style="width: 100px; height: auto; object-fit: contain;">
+            <img src="{inline_logo('logo.png')}" style="width: 200px; height: auto; object-fit: contain;">
             <div style='font-weight:800;font-size:1.2rem; margin-top: 10px;'>ST_GeoMech_UCS</div>
             <div style='color:#667085;'>Smart Thinking • Secure Access</div>
         </div>
@@ -409,7 +424,7 @@ st.session_state.setdefault("dev_preview",False)
 # =========================
 st.sidebar.markdown(f"""
     <div class="centered-container">
-        <img src="{inline_logo('logo.png')}" style="width: 100px; height: auto; object-fit: contain;">
+        <img src="{inline_logo('logo.png')}" style="width: 200px; height: auto; object-fit: contain;">
         <div style='font-weight:800;font-size:1.2rem;'>ST_GeoMech_UCS</div>
         <div style='color:#667085;'>Real-Time UCS Tracking While Drilling</div>
     </div>
@@ -653,11 +668,11 @@ if st.session_state.app_step == "predict":
             table = pd.DataFrame({
                 "Metric": ["# points","Pred min","Pred max","Pred mean","Pred std","OOR %"],
                 "Value":  [sv["n"],
-                           round(sv["pred_min"],2),
-                           round(sv["pred_max"],2),
-                           round(sv["pred_mean"],2),
-                           round(sv["pred_std"],2),
-                           f'{sv["oor"]:.1f}%']
+                            round(sv["pred_min"],2),
+                            round(sv["pred_max"],2),
+                            round(sv["pred_mean"],2),
+                            round(sv["pred_std"],2),
+                            f'{sv["oor"]:.1f}%']
             })
             st.success("Predictions ready ✓")
             df_centered_rounded(table, hide_index=True)