Update Chat_with_pdf_LLM.py

Chat_with_pdf_LLM.py

@@ -40,27 +40,32 @@ def LLM_pdf(model_name = 'google/flan-t5-large'):
       if 'past' not in st.session_state:
           st.session_state['past'] = []
       # print(st.session_state['generated'],st.session_state['past'])
+
+      chat_placeholder = st.empty()
       
       # show user input
-      user_question = st.text_input("Ask a question about your PDF:")
-      if user_question:
-        docs = knowledge_base.similarity_search(user_question)
-        
-        llm = HuggingFaceHub(repo_id=model_name, model_kwargs={"temperature":5,
-                                                      "max_length":64})
-        chain = load_qa_chain(llm, chain_type="stuff")
-        response = chain.run(input_documents=docs,question=user_question)
-           
-        #st.write(response)
-          
-        # # append user_input and output to state
-        st.session_state.past.append(user_question)
-        st.session_state.generated.append(response)
+      with st.container():
+          input_placeholder = st.empty()
+          user_question = input_placeholder.text_input("Ask a question about your PDF:")
+          if user_question:
+            docs = knowledge_base.similarity_search(user_question)
+            
+            llm = HuggingFaceHub(repo_id=model_name, model_kwargs={"temperature":5,
+                                                          "max_length":64})
+            chain = load_qa_chain(llm, chain_type="stuff")
+            response = chain.run(input_documents=docs,question=user_question)
+               
+            #st.write(response)
           
-      # If responses have been generated by the model
-      if st.session_state['generated']:
-        # Reverse iteration through the list
-        for i in range(len(st.session_state['generated'])-1, -1, -1):
-            # message from streamlit_chat
-            message(st.session_state['past'][::-1][i], is_user=True, key=str(i) + '_user')
-            message(st.session_state['generated'][::-1][i], key=str(i))
+            # append user_input and output to state
+            st.session_state.past.append(user_question)
+            st.session_state.generated.append(response)
+              
+      with chat_placeholder.container():    
+          # If responses have been generated by the model
+          if st.session_state['generated']:
+            # Reverse iteration through the list
+            for i in range(len(st.session_state['generated'])-1, -1, -1):
+                # message from streamlit_chat
+                message(st.session_state['past'][::-1][i], is_user=True, key=str(i) + '_user')
+                message(st.session_state['generated'][::-1][i], key=str(i))