Update app.py

app.py

@@ -178,7 +178,7 @@ def _load_snapshot(path=SNAPSHOT_PATH):
 
 # ---------- Init retrieval engines ----------
 init_retriever()
-_session_rag = SessionRAG()  # in-memory only; embeddings load lazily upon first use
+_session_rag = SessionRAG()  # in-memory; supports artifacts (CSV columns)
 
 # ---------- Executive pre-compute (MDSi block) ----------
 def _mdsi_block():
@@ -207,23 +207,37 @@ def clarityops_reply(user_msg, history, tz, uploaded_files_paths):
             ans = "I am ClarityOps, your strategic decision making AI partner."
             return history + [(user_msg, ans)]
 
+        # ---------- Ingest uploads: now returns chunks + artifacts ----------
         if uploaded_files_paths:
-            items = extract_text_from_files(uploaded_files_paths)
-            if items:
-                _session_rag.add_docs(items)
-                log_event("uploads_added", None, {"count": len(items)})
-
+            ing = extract_text_from_files(uploaded_files_paths)
+            chunks = ing.get("chunks", []) if isinstance(ing, dict) else (ing or [])
+            artifacts = ing.get("artifacts", []) if isinstance(ing, dict) else []
+            if chunks:
+                _session_rag.add_docs(chunks)
+            if artifacts:
+                _session_rag.register_artifacts(artifacts)
+            log_event("uploads_added", None, {"chunks": len(chunks), "artifacts": len(artifacts)})
+
+        # ---------- Deterministic CSV "columns/headers" handler ----------
+        if re.search(r"\b(columns?|headers?)\b", (safe_in or "").lower()):
+            cols = _session_rag.get_latest_csv_columns()
+            if cols:
+                return history + [(user_msg, "Here are the column names from your most recent CSV upload:\n\n- " + "\n- ".join(cols))]
+
+        # Retrieve from session uploads (text chunks)
         session_snips = "\n---\n".join(_session_rag.retrieve(
             "diabetes screening Indigenous Métis mobile program cost throughput outcomes logistics bed flow staffing discharge forecast",
             k=6
         ))
 
+        # Load daily snapshot + policies + computed ops numbers
         snapshot = _load_snapshot()
         policy_context = retrieve_context(
             "mobile diabetes screening Indigenous community outreach logistics referral pathways cultural safety data governance cost effectiveness outcomes bed management discharge acceleration ambulance offload"
         )
         computed = compute_operational_numbers(snapshot)
 
+        # Exec scenario detect (MDSi)
         user_lower = (safe_in or "").lower()
         mdsi_extra = _mdsi_block() if ("diabetes" in user_lower or "mdsi" in user_lower or "mobile screening" in user_lower) else ""