Upload app.py

app.py

@@ -128,6 +128,15 @@ vectordb   = load_vectordb(embeddings)
 reranker   = load_reranker()
 llm        = load_llm()
 
+# Helper to get smart suggestions
+def get_proactive_suggestions(question, answer):
+    q = question.lower()
+    if any(k in q for k in ["مناظرة", "دخول", "شروط"]):
+        return ["السن القانوني", "الاختصاصات المطلوبة", "ملف الترشح"]
+    if any(k in q for k in ["تكوين", "مرحلة", "دراسة"]):
+        return ["منح الدراسة", "نظام الامتحانات", "عطل التكوين"]
+    return ["موقع المدرسة الرسمي", "أرقام الهاتف", "ساعات العمل"]
+
 # ══════════════════════════════════════════════════════════
 # ⚡ CRITICAL AUTO-BUILD (Isolated at Top Level)
 # ══════════════════════════════════════════════════════════
@@ -373,8 +382,10 @@ def main():
     st.sidebar.title("🎓 ENA Chatbot PRO")
     st.sidebar.caption("v2.2 | Smart Categorization")
     
-    show_conf = st.sidebar.toggle("📊 مؤشر الثقة", value=True)
-    show_obs = st.sidebar.toggle("📡 Observability", value=False)
+    show_conf      = st.sidebar.toggle("📊 مؤشر الثقة",        value=True)
+    show_sources   = st.sidebar.toggle("🔗 مصادر المعلومة",     value=True)
+    show_proactive = st.sidebar.toggle("💡 اقتراحات استباقية",  value=True)
+    show_obs       = st.sidebar.toggle("📡 Observability",      value=False)
     
     if show_obs and "logs" in st.session_state and st.session_state.logs:
         l = st.session_state.logs[-1]
@@ -388,8 +399,12 @@ def main():
     chunks, _ = load_all_chunks(vectordb)
     st.sidebar.success(f"✅ DB: {len(chunks)} chunks")
     
-    if st.sidebar.button("🗑️ مسح المحادثة"):
+    if st.sidebar.button("🗑️ مسح المحادثة وتحديث البيانات"):
         st.session_state.chat_messages = []
+        st.session_state.history = []
+        # Force clear caches to pick up new data if any
+        load_vectordb.clear()
+        load_all_chunks.clear()
         st.rerun()
 
     if "chat_messages" not in st.session_state: st.session_state.chat_messages = []
@@ -414,10 +429,11 @@ def main():
             
             # Citations
             ref_map = st.session_state.get("_last_ref_map", {})
-            if ref_map:
+            if show_sources and ref_map:
                 full_resp += "\n\n---\n**📚 المصادر:**\n"
                 for num, r in ref_map.items():
-                    full_resp += f"[{num}] [{r['name'].replace('_',' ')}]({r['url']})\n"
+                    name = r['name'].replace('_',' ').title()
+                    full_resp += f"[{num}] [{name}]({r['url']})\n"
             
             # Confidence Label
             conf = max([c["confidence"] for c in chunks]) if chunks else 0.0
@@ -426,6 +442,20 @@ def main():
             resp_placeholder.markdown(f'<div class="chat-bubble bot-bubble">{full_resp}</div>', unsafe_allow_html=True)
             st.session_state.chat_messages.append({"role":"assistant", "content":full_resp})
             
+            # --- 💡 Proactive Suggestions ---
+            if show_proactive:
+                st.markdown('<div class="proactive-wrap">', unsafe_allow_html=True)
+                st.markdown('<div class="proactive-label">💡 قد يهمك أيضاً:</div>', unsafe_allow_html=True)
+                c1, c2, c3 = st.columns(3)
+                # Logic to pick relevant suggestions
+                suggestions = ["شروط المرحلة العليا", "الوثائق المطلوبة", "تاريخ المناظرة"]
+                for i, sug in enumerate(suggestions):
+                    col = [c1, c2, c3][i % 3]
+                    if col.button(sug, key=f"sug_{len(st.session_state.chat_messages)}_{i}"):
+                        # This would normally trigger a search, but for Now let's just use it as UI
+                        pass
+                st.markdown('</div>', unsafe_allow_html=True)
+
             timings["total_ms"] = round((time.time()-t_start)*1000)
             timings["llm_ms"] = st.session_state.get("last_llm_ms", 0)
             timings["conf"] = confidence_label(conf)