Update app.py

app.py

@@ -162,6 +162,55 @@ def add_paper_buttons_and_links():
 
 add_paper_buttons_and_links()
 
+def process_user_input(user_question):
+    response = st.session_state.conversation({'question': user_question})
+    st.session_state.chat_history = response['chat_history']
+
+    for i, message in enumerate(st.session_state.chat_history):
+        template = user_template if i % 2 == 0 else bot_template
+        st.write(template.replace("{{MSG}}", message.content), unsafe_allow_html=True)
+
+        # Save file output from PDF query results
+        filename = generate_filename(user_question, 'txt')
+        create_file(filename, user_question, message.content, should_save)
+
+        # New functionality to create expanders and buttons
+        create_expanders_and_buttons(message.content)
+
+def create_expanders_and_buttons(content):
+    # Split the content into sections based on headers
+    sections = content.split("\n\n")
+    for section in sections:
+        lines = section.split("\n")
+        if len(lines) > 1 and ":" in lines[0]:  # Check for header and details
+            header = lines[0].replace(":", "").strip()
+            detail = " ".join(lines[1:]).strip()
+
+            with st.expander(header, expanded=False):
+                if st.button(f"Explore {header}"):
+                    expanded_outline = "Expand on the feature: " + detail
+                    chat_with_model(expanded_outline, header)
+
+
+
+def process_user_input_old(user_question):
+    response = st.session_state.conversation({'question': user_question})
+    st.session_state.chat_history = response['chat_history']
+    for i, message in enumerate(st.session_state.chat_history):
+        template = user_template if i % 2 == 0 else bot_template
+        st.write(template.replace("{{MSG}}", message.content), unsafe_allow_html=True)
+        # Save file output from PDF query results
+        filename = generate_filename(user_question, 'txt')
+        #create_file(filename, user_question, message.content)
+        response = message.content
+        user_prompt = user_question
+        create_file(filename, user_prompt, response, should_save)       
+        #st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
+
+
+
+
+
 
 def generate_filename_old(prompt, file_type):
     central = pytz.timezone('US/Central')
@@ -473,20 +522,6 @@ def get_chain(vectorstore):
     memory = ConversationBufferMemory(memory_key='chat_history', return_messages=True)
     return ConversationalRetrievalChain.from_llm(llm=llm, retriever=vectorstore.as_retriever(), memory=memory)
 
-def process_user_input(user_question):
-    response = st.session_state.conversation({'question': user_question})
-    st.session_state.chat_history = response['chat_history']
-    for i, message in enumerate(st.session_state.chat_history):
-        template = user_template if i % 2 == 0 else bot_template
-        st.write(template.replace("{{MSG}}", message.content), unsafe_allow_html=True)
-        # Save file output from PDF query results
-        filename = generate_filename(user_question, 'txt')
-        #create_file(filename, user_question, message.content)
-        response = message.content
-        user_prompt = user_question
-        create_file(filename, user_prompt, response, should_save)       
-        #st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
-
 def divide_prompt(prompt, max_length):
     words = prompt.split()
     chunks = []