Issue fix

app.py

@@ -135,31 +135,31 @@ if prompt := st.chat_input("Ask a follow-up question..."):
         st.markdown(prompt)
 
     with st.chat_message("assistant"):
-        with st.spinner("Thinking..."):
-            # Convert messages to LangChain format
-            chat_history = []
-            for msg in st.session_state.messages[:-1]:  # Exclude the current prompt
-                if msg["role"] == "user":
-                    chat_history.append(HumanMessage(content=msg["content"]))
-                else:
-                    chat_history.append(AIMessage(content=msg["content"]))
-
-            # Get response
-            response = llm.invoke([HumanMessage(content=prompt)] + chat_history)
-            assistant_response = response.content
-
-            st.markdown(assistant_response)
-            st.session_state.messages.append({"role": "assistant", "content": assistant_response})
         # with st.spinner("Thinking..."):
-        #     if len(st.session_state.messages) > 1:
-        #         response = llm.invoke([{"role": m["role"], "content": m["content"]} for m in st.session_state.messages])
-        #     else:
-        #         response = rag_chain.invoke(prompt)
-        #         response = response['result']
-        #
-        #     st.markdown(response)
-        #     st.session_state.messages.append({"role": "assistant", "content": response})
-        #
+            # Convert messages to LangChain format
+            # chat_history = []
+            # for msg in st.session_state.messages[:-1]:  # Exclude the current prompt
+            #     if msg["role"] == "user":
+            #         chat_history.append(HumanMessage(content=msg["content"]))
+            #     else:
+            #         chat_history.append(AIMessage(content=msg["content"]))
+            #
+            # # Get response
+            # response = llm.invoke([HumanMessage(content=prompt)] + chat_history)
+            # assistant_response = response.content
+            #
+            # st.markdown(assistant_response)
+            # st.session_state.messages.append({"role": "assistant", "content": assistant_response})
+        with st.spinner("Thinking..."):
+            if len(st.session_state.messages) > 1:
+                response = llm.invoke([{"role": m["role"], "content": m["content"]} for m in st.session_state.messages])
+                response = response['result']
+            else:
+                response = rag_chain.invoke(prompt)
+                response = response['result']
+
+            st.markdown(response)
+            st.session_state.messages.append({"role": "assistant", "content": response})
 
 if st.session_state.messages and st.button("📄 Download Chat as PDF"):
     pdf_file = export_chat_to_pdf(st.session_state.messages)