Update app.py

app.py

@@ -178,6 +178,39 @@ def mongo_get_likert_grouped(uri: str, db: str, coll: str, student: str, stage:
         return {g: _norm_01(avg.get(g)) for g in SKILL_GROUPS.keys()}
     except Exception:
         return {}
+        
+# ---- Analyses (Markdown) helpers ----
+ANALYSES_DIR = os.getenv("ANALYSES_DIR", "student_analyses")  # folder in your HF Space
+
+def _normalize_name(s: str) -> str:
+    # Lower, remove non-alphanumerics, collapse spaces/underscores
+    import re, unicodedata
+    s = unicodedata.normalize("NFKC", s or "").strip().lower()
+    s = re.sub(r"[^\w\s]", "", s)
+    s = re.sub(r"[\s_]+", " ", s).strip()
+    return s
+
+@st.cache_data(show_spinner=False)
+def _build_analysis_index(analyses_dir: str) -> dict:
+    """Return dict: normalized_name -> file_path for *.md under analyses_dir."""
+    import os, glob
+    index = {}
+    if not os.path.isdir(analyses_dir):
+        return index
+    for path in glob.glob(os.path.join(analyses_dir, "*.md")):
+        base = os.path.splitext(os.path.basename(path))[0]  # "Student_Name"
+        # accept both "Student Name" and "Student_Name" as same
+        norm = _normalize_name(base.replace("_", " "))
+        index[norm] = path
+    return index
+
+@st.cache_data(show_spinner=False)
+def _load_markdown(path: str) -> str:
+    try:
+        with open(path, "r", encoding="utf-8") as f:
+            return f.read()
+    except Exception:
+        return ""
 
 # ------------------- UI -------------------
 st.title("📊 Student Skill Radar")
@@ -199,6 +232,8 @@ with st.sidebar:
     overlay_sources = st.toggle("Overlay all sources when '(All)' selected", value=False)
     chart_title = st.text_input("Chart title", value="")
 
+
+
 # start_str = start_dt.strftime("%Y-%m-%d") if isinstance(start_dt, date) else None
 # end_str = end_dt.strftime("%Y-%m-%d") if isinstance(end_dt, date) else None
 
@@ -494,30 +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}")
+# # ---------- 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()})))