Update st_app.py

st_app.py

@@ -3,24 +3,13 @@ import sys
 import re
 
 import streamlit as st
-from streamlit_pills import pills
-from streamlit_feedback import streamlit_feedback
-
-from utils import thumbs_feedback, escape_dollars_outside_latex, send_amplitude_data
 
 from vectara_agentic.agent import AgentStatusType
-from agent import initialize_agent, get_agent_config
+from agent import initialize_agent
+from config import get_agent_config
 
 initial_prompt = "How can I help you today?"
 
-def show_example_questions():        
-    if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:            
-        selected_example = pills("Queries to Try:", st.session_state.example_messages, index=None)
-        if selected_example:
-            st.session_state.ex_prompt = selected_example
-            st.session_state.first_turn = False
-            return True
-    return False
 
 def format_log_msg(log_msg: str):
     max_log_msg_size = 500
@@ -68,50 +57,19 @@ async def launch_bot():
         cfg = get_agent_config()
         st.session_state.cfg = cfg
         st.session_state.ex_prompt = None
-        example_messages = [example.strip() for example in cfg.examples.split(";")] if cfg.examples else []
-        st.session_state.example_messages = [em for em in example_messages if len(em)>0]
         reset()
 
     cfg = st.session_state.cfg
+    print(f'Configuration: {cfg}')
 
     # left side content
-    with st.sidebar:
-        image = Image.open('Vectara-logo.png')
-        st.image(image, width=175)
-        st.markdown(f"## {cfg['demo_welcome']}")
-        st.markdown(f"{cfg['demo_description']}")
-
-        st.markdown("\n\n")
-        bc1, bc2 = st.columns([1, 1])
-        with bc1:
-            if st.button('Start Over'):
-                reset()
-                st.rerun()
-        with bc2:
-            if st.button('Show Logs'):
-                show_modal()
-
-        st.divider()
-        st.markdown(
-            "## How this works?\n"
-            "This app was built with [Vectara](https://vectara.com).\n\n"
-            "It demonstrates the use of Agentic RAG functionality with Vectara"
-        )
-
-    if "messages" not in st.session_state.keys():
-        reset()
 
     # Display chat messages
     for message in st.session_state.messages:
+        print(f'Message: {message}')
         with st.chat_message(message["role"], avatar=message["avatar"]):
             st.write(message["content"])
 
-    example_container = st.empty()
-    with example_container:
-        if show_example_questions():
-            example_container.empty()
-            st.session_state.first_turn = False
-            st.rerun()
 
     # User-provided prompt
     if st.session_state.ex_prompt:
@@ -133,32 +91,16 @@ async def launch_bot():
         with st.chat_message("assistant", avatar='🤖'):
             st.session_state.status = st.status('Processing...', expanded=False)
             res = st.session_state.agent.chat(st.session_state.prompt)
-            res = escape_dollars_outside_latex(res)
+            #res = escape_dollars_outside_latex(res)
+            res = str(res)
             message = {"role": "assistant", "content": res, "avatar": '🤖'}
             st.session_state.messages.append(message)
             st.markdown(res)
 
-        send_amplitude_data(
-            user_query=st.session_state.messages[-2]["content"], 
-            bot_response=st.session_state.messages[-1]["content"],
-            demo_name=cfg['demo_name']
-        )
 
         st.session_state.ex_prompt = None
         st.session_state.prompt = None
         st.session_state.first_turn = False
         st.rerun()
 
-    # Record user feedback
-    if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != initial_prompt):
-        if "feedback_key" not in st.session_state:
-            st.session_state.feedback_key = 0
-        streamlit_feedback(
-            feedback_type="thumbs", on_submit=thumbs_feedback, key=str(st.session_state.feedback_key),
-            kwargs={"user_query": st.session_state.messages[-2]["content"],
-                    "bot_response": st.session_state.messages[-1]["content"],
-                    "demo_name": cfg["demo_name"]}
-            )
-
-
-    sys.stdout.flush()
+    sys.stdout.flush()