Update app.py

app.py

@@ -529,107 +529,107 @@ def fetch_student_stage_summary(
         "notable_quotes": notable_quotes,
     }
 
-# # ---------- Render the summary panel dynamically ----------
-# if mongo_uri and student_choice != "(All)" and source_choice != "(All)":
-#     stage = SOURCE_TO_STAGE.get(source_choice.strip())
-#     if stage:
-#         # set to your actual summaries collection name
-#         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}")
-# ------------------- 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()})))
+# ---------- Render the summary panel dynamically ----------
+if mongo_uri and student_choice != "(All)" and source_choice != "(All)":
+    stage = SOURCE_TO_STAGE.get(source_choice.strip())
+    if stage:
+        # set to your actual summaries collection name
+        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}")
+# # ------------------- 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()})))