Update src/streamlit_app.py

src/streamlit_app.py

@@ -655,6 +655,13 @@ with tabs[4]:
                     else:
                         recs.append(f"`{r['Feature']}` neutral for `{target}`")
                 st.write("\n".join(recs))
+                # --- Persist key results for Smart Advisor tab ---
+                st.session_state["recs"] = recs
+                st.session_state["final_r2"] = final_r2
+                st.session_state["use_case"] = use_case
+                st.session_state["target"] = target
+                st.session_state["last_automl_ts"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
 
                 # --- Hugging Face Router Chat API (OpenAI-Compatible Format) ---
                 import requests, textwrap
@@ -766,6 +773,15 @@ with tabs[8]:
 # ----- Smart Advisor tab (Role-based Insights)
 with tabs[9]:
     st.subheader(" Smart Advisor — Role-Based Insights")
+    if "last_automl_ts" in st.session_state:
+        st.caption(f" Model baseline last trained: {st.session_state['last_automl_ts']}")
+
+    # --- Load persisted results from AutoML tab ---
+    recs = st.session_state.get("recs", [])
+    final_r2 = st.session_state.get("final_r2", 0)
+    use_case = st.session_state.get("use_case", "N/A")
+    target = st.session_state.get("target", "N/A")
+
 
     # -------------------------
     # 1. Role hierarchy and descriptions
@@ -891,10 +907,12 @@ with tabs[9]:
     role = st.selectbox("Select Your Role", list(roles.keys()), index=10)
     st.caption(f" Context: {roles[role]}")
 
-    if "recs" not in locals() or not isinstance(recs, list) or not recs:
+    if not recs:
         st.warning("Please run the AutoML + SHAP step first to generate recommendations.")
     else:
-        if st.button("Generate Role-Based Advisory"):
+        generate_clicked = st.button("Generate Role-Based Advisory")
+        if generate_clicked and not st.session_state.get("hf_ran_once", False):
+            st.session_state["hf_ran_once"] = True
             HF_TOKEN = os.getenv("HF_TOKEN")
             if not HF_TOKEN:
                 st.error("HF_TOKEN not found. Please set it as an environment variable or in secrets.toml.")
@@ -949,7 +967,7 @@ with tabs[9]:
                 }
 
                 with st.spinner(f"Generating role-based advisory for {role}..."):
-                    resp = requests.post(API_URL, headers=headers, json=payload, timeout=90)
+                    resp = requests.post(API_URL, headers=headers, json=payload, timeout=120)
                     if resp.status_code == 200:
                         data = resp.json()
                         msg = (
@@ -961,6 +979,12 @@ with tabs[9]:
                         if msg:
                             st.markdown(f"### Advisory for {role}")
                             st.info(msg)
+                            st.session_state["last_advisory_msg"] = msg
+                            st.session_state["last_role"] = role
+                            # --- Timestamp the advisory ---
+                            st.session_state["last_advisory_ts"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+                            st.caption(f"🕒 Last updated: {st.session_state['last_advisory_ts']}")
+
                             # ---- Dynamic Data-Driven Highlights ----
                             if role in ["Chief General Manager – PP&C", "Plant Head", "Process Optimization Head (PP&C)"]:
                                 st.markdown("#### 🔍 Shift Highlights — Data-Driven Summary")
@@ -1018,7 +1042,7 @@ with tabs[9]:
                         
                                     # 6️⃣ Optional: Link to SHAP recs for validation
                                     if isinstance(recs, list) and recs:
-                                        st.markdown("#### 🧭 Cross-Verification with SHAP Insights")
+                                        st.markdown("####  Cross-Verification with SHAP Insights")
                                         matches = [r for r in recs if any(k in r for k in ["furnace", "energy", "yield", "slag", "power"])]
                                         if matches:
                                             st.info("Aligned SHAP Recommendations:\n\n- " + "\n- ".join(matches))
@@ -1031,6 +1055,15 @@ with tabs[9]:
                             st.warning(f"Empty response.\nRaw: {data}")
                     else:
                         st.error(f"HF API error {resp.status_code}: {resp.text}")
+    # --- Display last advisory if available ---
+    if "last_advisory_msg" in st.session_state:
+        st.markdown(f"### Last Advisory ({st.session_state.get('last_role', 'N/A')})")
+        st.info(st.session_state["last_advisory_msg"])
+        if "last_advisory_ts" in st.session_state:
+            st.caption(f"Last updated: {st.session_state['last_advisory_ts']}")
+        if "last_automl_ts" in st.session_state:
+            st.caption(f"Model baseline last run at: {st.session_state['last_automl_ts']}")
+
 
     # -------------------------
     # 4. Optional role-based KPIs