Update app.py

app.py

@@ -103,8 +103,7 @@ def initialize_LLM(llm_option, vector_db):
 def format_chat_history(chat_history):
     formatted_chat_history = []
     for user_message, bot_message in chat_history:
-        formatted_chat_history.append(f"User: {user_message}")
-        formatted_chat_history.append(f"Assistant: {bot_message}")
+        formatted_chat_history.append(f"User: {user_message}\nAssistant: {bot_message}\n")
     return formatted_chat_history
 
 def conversation(qa_chain, message, history):
@@ -127,6 +126,11 @@ def conversation(qa_chain, message, history):
         st.error(f"Error in conversation: {e}")
         return qa_chain, history, "", []
 
+def download_history(chat_history):
+    formatted_chat_history = format_chat_history(chat_history)
+    history_text = "\n".join(formatted_chat_history)
+    st.download_button(label="Download Chat History", data=history_text, file_name="chat_history.txt", mime="text/plain")
+
 def main():
     st.sidebar.title("PDF Chatbot")
 
@@ -146,6 +150,9 @@ def main():
     if 'qa_chain' not in st.session_state:
         st.session_state['qa_chain'] = None
 
+    if 'chat_history' not in st.session_state:
+        st.session_state['chat_history'] = []
+
     st.sidebar.markdown("### Select Large Language Model (LLM)")
     llm_option = st.sidebar.radio("Available LLMs", list_llm_simple)
 
@@ -158,20 +165,26 @@ def main():
     st.title("Chat with your Document")
 
     if st.session_state['qa_chain']:
-        history = []
         message = st.text_input("Ask a question")
 
         if st.button("Submit"):
             with st.spinner("Generating response..."):
-                qa_chain, history, response_answer, sources = conversation(st.session_state['qa_chain'], message, history)
+                qa_chain, chat_history, response_answer, sources = conversation(st.session_state['qa_chain'], message, st.session_state['chat_history'])
                 st.session_state['qa_chain'] = qa_chain
+                st.session_state['chat_history'] = chat_history
 
                 st.markdown("### Chatbot Response")
-                st.write(response_answer)
+
+                # Display the chat history in a chat-like interface
+                for i, (user_msg, bot_msg) in enumerate(st.session_state['chat_history']):
+                    st.markdown(f"**User:** {user_msg}")
+                    st.markdown(f"**Assistant:** {bot_msg}")
 
                 with st.expander("Relevant context from the source document"):
                     for source in sources:
                         st.text_area(f"Source - Page {source['page']}", value=source["content"], height=100)
 
+                download_history(st.session_state['chat_history'])
+
 if __name__ == "__main__":
     main()