Update app.py

app.py

@@ -323,6 +323,7 @@ st.plotly_chart(fig, use_container_width=True)
 
 st.caption(f"{len(df_final)} line(s) aggregated." if not df_final.empty else "No data.")
 
+
 # ================== Dynamic Stage Summaries (only if student answered that week) ==================
 import re
 import unicodedata
@@ -554,82 +555,72 @@ if mongo_uri and student_choice != "(All)" and source_choice != "(All)":
             for q in (summary.get("notable_quotes") or [])[:3]:
                 st.markdown(f"> {q}")
 # # ------------------- Output (Tabs) -------------------
-# tab_radar, tab_analyses = st.tabs(["📈 Radar", "📝 Analyses"])
-
-# with tab_radar:
-#     # plot the radar (uses df_plot, avg_label already computed above)
-#     fig = plot_radar(df_plot, grouped, chart_title, avg_label=avg_label)
-#     st.plotly_chart(fig, use_container_width=True)
-#     st.caption(f"{len(df_final)} line(s) aggregated." if not df_final.empty else "No data.")
-
-#     # Dynamic stage summary panel (only if a specific student + source selected,
-#     # and only if they actually answered that week)
-#     if mongo_uri and student_choice != "(All)" and source_choice != "(All)":
-#         # Map the selected source (e.g., 'onboarding_responses') to stage (e.g., 'onboarding')
-#         stage = SOURCE_TO_STAGE.get(source_choice.strip())
-#         if stage:
-#             # summaries collection name (adjust if needed)
-#             summaries_coll_name = "summaries_IFE_2025"
-
-#             summary = fetch_student_stage_summary(
-#                 mongo_uri, db_name, summaries_coll_name, coll_name,
-#                 student=student_choice, stage=stage
-#             )
-#             if summary:
-#                 st.markdown("---")
-#                 st.subheader(f"Summary — {student_choice} ({stage.replace('_', ' ').title()})")
-
-#                 c1, c2 = st.columns(2)
-#                 with c1:
-#                     st.markdown(f"**Most Consistent:** {summary.get('most_consistent') or '—'}")
-#                     st.markdown(f"**Most Developed:** {summary.get('most_developed') or '—'}")
-#                 with c2:
-#                     strengths = summary.get("top_strengths") or []
-#                     st.markdown("**Top Strengths:** " + (", ".join(strengths) if strengths else "—"))
-
-#                 st.markdown("**Notable Quotes:**")
-#                 for q in (summary.get("notable_quotes") or [])[:3]:
-#                     st.markdown(f"> {q}")
-
-# with tab_analyses:
-#     st.subheader("Student Analysis (Markdown)")
-
-#     # Use the folder you defined at top (ANALYSES_DIR), or expose it in the sidebar if you prefer.
-#     idx = _build_analysis_index(ANALYSES_DIR)
-
-#     if student_choice == "(All)":
-#         st.info("Pick a specific student on the left to view their analysis.")
-#         # (Optional) show what's available so you can browse:
-#         if idx:
-#             st.caption("Available analyses:")
-#             st.write(", ".join(sorted({name.title() for name in idx.keys()})))
-#     else:
-#         # Normalize the selected student name to match filenames
-#         norm = _normalize_name(student_choice)
-#         path = idx.get(norm)
-
-#         # If exact match not found, try simple underscore variant
-#         if not path:
-#             alt = student_choice.replace(" ", "_")
-#             path = idx.get(_normalize_name(alt))
-
-#         if path:
-#             md = _load_markdown(path)
-#             if md.strip():
-#                 st.markdown(md, unsafe_allow_html=False)
-#                 # Optional download button
-#                 with open(path, "rb") as f:
-#                     st.download_button(
-#                         "Download analysis (.md)", f,
-#                         file_name=os.path.basename(path), mime="text/markdown"
-#                     )
-#             else:
-#                 st.warning("Analysis file found but empty.")
-#         else:
-#             st.warning(f"No analysis found for **{student_choice}** in `{ANALYSES_DIR}` yet.")
-#             if idx:
-#                 st.caption("Available analyses:")
-#                 st.write(", ".join(sorted({name.title() for name in idx.keys()})))
+tab_radar, tab_analyses = st.tabs(["📈 Radar", "📝 Analyses"])
+
+with tab_radar:
+    # Recompute a local copy for the tab (prevents reusing the same figure object)
+    df_plot_local = df_final.copy()
+    avg_label_local = None
+
+    if not df_plot_local.empty:
+        cols = list(SKILL_GROUPS.keys()) if grouped else SKILLS
+        show_cohort_avg = st.toggle("Show cohort average (all students)", value=True, key="toggle_avg_radar")
+        if show_cohort_avg:
+            avg_vals = df_plot_local[cols].mean()
+            avg_row = {"label": "Average (All Students)"}
+            avg_row.update({k: float(avg_vals[k]) for k in cols})
+            df_plot_local = pd.concat([df_plot_local, pd.DataFrame([avg_row])], ignore_index=True)
+            avg_label_local = "Average (All Students)"
+
+    # Build a fresh figure for the tab or copy if you already built one above:
+    fig_tab = plot_radar(df_plot_local, grouped, chart_title, avg_label=avg_label_local)
+    # fig_tab = go.Figure(fig)  # <- alternative if you already computed `fig` above
+
+    # Unique key to avoid Plotly id collisions on reruns/tab switches
+    key_suffix = f"{student_choice}|{source_choice}|{int(grouped)}|{int(overlay_sources)}"
+    st.plotly_chart(fig_tab, use_container_width=True, key=f"radar_tab_{key_suffix}")
+
+    st.caption(f"{len(df_final)} line(s) aggregated." if not df_final.empty else "No data.")
+
+with tab_analyses:
+    st.subheader("Student Analysis (Markdown)")
+
+    # Use the folder you defined at top (ANALYSES_DIR), or expose it in the sidebar if you prefer.
+    idx = _build_analysis_index(ANALYSES_DIR)
+
+    if student_choice == "(All)":
+        st.info("Pick a specific student on the left to view their analysis.")
+        # (Optional) show what's available so you can browse:
+        if idx:
+            st.caption("Available analyses:")
+            st.write(", ".join(sorted({name.title() for name in idx.keys()})))
+    else:
+        # Normalize the selected student name to match filenames
+        norm = _normalize_name(student_choice)
+        path = idx.get(norm)
+
+        # If exact match not found, try simple underscore variant
+        if not path:
+            alt = student_choice.replace(" ", "_")
+            path = idx.get(_normalize_name(alt))
+
+        if path:
+            md = _load_markdown(path)
+            if md.strip():
+                st.markdown(md, unsafe_allow_html=False)
+                # Optional download button
+                with open(path, "rb") as f:
+                    st.download_button(
+                        "Download analysis (.md)", f,
+                        file_name=os.path.basename(path), mime="text/markdown"
+                    )
+            else:
+                st.warning("Analysis file found but empty.")
+        else:
+            st.warning(f"No analysis found for **{student_choice}** in `{ANALYSES_DIR}` yet.")
+            if idx:
+                st.caption("Available analyses:")
+                st.write(", ".join(sorted({name.title() for name in idx.keys()})))