Update app.py

app.py

@@ -196,9 +196,9 @@ def df_centered_rounded(df: pd.DataFrame, hide_index=True):
     numcols = out.select_dtypes(include=[np.number]).columns
     styler = (
         out.style
-           .format({c: "{:.2f}" for c in numcols})
-           .set_properties(**{"text-align": "center"})
-           .set_table_styles(TABLE_CENTER_CSS)
+            .format({c: "{:.2f}" for c in numcols})
+            .set_properties(**{"text-align": "center"})
+            .set_table_styles(TABLE_CENTER_CSS)
     )
     st.dataframe(styler, use_container_width=True, hide_index=hide_index)
 
@@ -352,7 +352,6 @@ except AttributeError:
             return wrapper
         return deco
 
-@dialog("Preview data")
 def preview_modal(book: dict[str, pd.DataFrame]):
     if not book:
         st.info("No data loaded yet."); return
@@ -418,6 +417,7 @@ st.session_state.setdefault("dev_file_name","")
 st.session_state.setdefault("dev_file_bytes",b"")
 st.session_state.setdefault("dev_file_loaded",False)
 st.session_state.setdefault("dev_preview",False)
+st.session_state.setdefault("show_preview_modal", False) # New state variable
 
 # =========================
 # Branding in Sidebar
@@ -489,7 +489,7 @@ if st.session_state.app_step == "dev":
             st.sidebar.caption(f"**Data loaded:** {st.session_state.dev_file_name} • {df0.shape[0]} rows × {df0.shape[1]} cols")
 
     if st.sidebar.button("Preview data", use_container_width=True, disabled=not st.session_state.dev_file_loaded):
-        preview_modal(read_book_bytes(st.session_state.dev_file_bytes))
+        st.session_state.show_preview_modal = True  # Set state to show modal
         st.session_state.dev_preview = True
 
     run = st.sidebar.button("Run Model", type="primary", use_container_width=True)
@@ -566,7 +566,7 @@ if st.session_state.app_step == "validate":
             df0 = next(iter(book.values()))
             st.sidebar.caption(f"**Data loaded:** {up.name} • {df0.shape[0]} rows × {df0.shape[1]} cols")
     if st.sidebar.button("Preview data", use_container_width=True, disabled=(up is None)):
-        preview_modal(read_book_bytes(up.getvalue()))
+        st.session_state.show_preview_modal = True  # Set state to show modal
     go_btn = st.sidebar.button("Predict", type="primary", use_container_width=True)
     if st.sidebar.button("⬅ Back to Case Building", use_container_width=True): st.session_state.app_step="dev"; st.rerun()
     if st.sidebar.button("Proceed to Prediction ▶", use_container_width=True): st.session_state.app_step="predict"; st.rerun()
@@ -607,7 +607,7 @@ if st.session_state.app_step == "validate":
         with col_cross:
             st.pyplot(
                 cross_plot_static(st.session_state.results["Validate"][TARGET],
-                                  st.session_state.results["Validate"]["UCS_Pred"]),
+                                     st.session_state.results["Validate"]["UCS_Pred"]),
                 use_container_width=True
             )
         with col_track:
@@ -634,7 +634,7 @@ if st.session_state.app_step == "predict":
             df0 = next(iter(book.values()))
             st.sidebar.caption(f"**Data loaded:** {up.name} • {df0.shape[0]} rows × {df0.shape[1]} cols")
     if st.sidebar.button("Preview data", use_container_width=True, disabled=(up is None)):
-        preview_modal(read_book_bytes(up.getvalue()))
+        st.session_state.show_preview_modal = True  # Set state to show modal
     go_btn = st.sidebar.button("Predict", type="primary", use_container_width=True)
     if st.sidebar.button("⬅ Back to Case Building", use_container_width=True): st.session_state.app_step="dev"; st.rerun()
 
@@ -668,11 +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)
@@ -683,6 +683,47 @@ if st.session_state.app_step == "predict":
                 use_container_width=True, config={"displayModeBar": False, "scrollZoom": True}
             )
 
+# =========================
+# Run preview modal after all other elements
+# =========================
+if st.session_state.show_preview_modal:
+    # Get the correct book based on the current app step
+    book_to_preview = {}
+    if st.session_state.app_step == "dev":
+        book_to_preview = read_book_bytes(st.session_state.dev_file_bytes)
+    elif st.session_state.app_step in ["validate", "predict"] and up is not None:
+        book_to_preview = read_book_bytes(up.getvalue())
+    
+    # Use a try-except block to handle cases where 'up' might be None
+    # and the logic tries to access its attributes.
+    try:
+        if st.session_state.app_step == "validate" and up is not None:
+             book_to_preview = read_book_bytes(up.getvalue())
+        elif st.session_state.app_step == "predict" and up is not None:
+             book_to_preview = read_book_bytes(up.getvalue())
+    except NameError:
+        book_to_preview = {}
+
+    with st.expander("Preview data", expanded=True):
+        if not book_to_preview:
+            st.info("No data loaded yet.")
+        else:
+            names = list(book_to_preview.keys())
+            tabs = st.tabs(names)
+            for t, name in zip(tabs, names):
+                with t:
+                    df = book_to_preview[name]
+                    t1, t2 = st.tabs(["Tracks", "Summary"])
+                    with t1:
+                        st.pyplot(preview_tracks(df, FEATURES), use_container_width=True)
+                    with t2:
+                        tbl = (df[FEATURES]
+                                .agg(['min','max','mean','std'])
+                                .T.rename(columns={"min":"Min","max":"Max","mean":"Mean","std":"Std"}))
+                        df_centered_rounded(tbl.reset_index(names="Feature"))
+    # Reset the state variable after the modal is displayed
+    st.session_state.show_preview_modal = False
+    
 # =========================
 # Footer
 # =========================