Update app.py

app.py

@@ -313,35 +313,41 @@ def handle_submit(user_query: str):
     # Prevent duplicate submissions by checking last message
     if not st.session_state.chat_history or st.session_state.chat_history[-1][1] != user_query:
         try:
-            st.session_state.processing_query = True
-            
             # Add user message to chat history
             st.session_state.chat_history.append(("user", user_query))
             
-            # Maintain context memory
-            if len(st.session_state.context_memory) > 5:
-                st.session_state.context_memory.pop(0)
-            
-            # Build query with context
-            query_with_context = "\n".join(
-                [f"Q: {qa['query']}\nA: {qa['answer']}" for qa in st.session_state.context_memory]
-            ) + f"\nQ: {user_query}"
-            
-            # Process query
-            result = st.session_state.pipeline.process_query(query_with_context)
-            
-            # Create response dictionary with answer and documents
-            response_dict = {
-                "answer": result.get("answer", ""),
-                "documents": result.get("documents", [])
-            }
-            
-            # Update chat history and context
-            st.session_state.chat_history.append(("assistant", response_dict))
-            st.session_state.context_memory.append({"query": user_query, "answer": response_dict})
-            
-            # Save to QA history
-            add_to_qa_history(user_query, response_dict)
+            # Show loading message
+            with st.spinner("🔍 กำลังค้นหาคำตอบ..."):
+                # Add temporary loading message
+                temp_message = ("assistant", "🤖 กำลังค้นหาคำตอบ...")
+                st.session_state.chat_history.append(temp_message)
+                st.rerun()  # Force refresh to show loading state
+                
+                # Maintain context memory
+                if len(st.session_state.context_memory) > 5:
+                    st.session_state.context_memory.pop(0)
+                
+                # Build query with context
+                query_with_context = "\n".join(
+                    [f"Q: {qa['query']}\nA: {qa['answer']}" for qa in st.session_state.context_memory]
+                ) + f"\nQ: {user_query}"
+                
+                # Process query
+                result = st.session_state.pipeline.process_query(query_with_context)
+                
+                # Create response dictionary with answer and documents
+                response_dict = {
+                    "answer": result.get("answer", ""),
+                    "documents": result.get("documents", [])
+                }
+                
+                # Remove loading message and add real response
+                st.session_state.chat_history.pop()  # Remove loading message
+                st.session_state.chat_history.append(("assistant", response_dict))
+                st.session_state.context_memory.append({"query": user_query, "answer": response_dict})
+                
+                # Save to QA history
+                add_to_qa_history(user_query, response_dict)
             
         except Exception as e:
             st.session_state.chat_history.append(("assistant", f"❌ เกิดข้อผิดพลาด: {str(e)}"))