import streamlit as st
import torch
import uuid
import nest_asyncio
import asyncio
import os
#import omegaConf

torch.classes.__path__ = []

# Setup for HTTP API Calls
if 'device_id' not in st.session_state:
    st.session_state.device_id = str(uuid.uuid4())

if "feedback_key" not in st.session_state:
    st.session_state.feedback_key = 0

#corpus_keys = 'first.last'
cfg = {"title": "SBS MMMMMMMMAAAAAAAAAAAPPPPPPPPPPP"}

def launch_bot():
    def reset():
        for i in range(100):
            st.write(f"This is scrollable content line {i}")    
        #st.session_state.messages = [{"role": "assistant", "content": "How may I help you?", "avatar": '🤖'}]
        st.session_state.ex_prompt = None
        st.session_state.first_turn = True


    def generate_response(question):
        response = vq.submit_query(question, languages[st.session_state.language])
        return response
    
    def generate_streaming_response(question):
        response = vq.submit_query_streaming(question, languages[st.session_state.language])
        return response
    
    def show_example_questions():        
        if len(st.session_state.example_messages) > 0 and st.session_state.first_turn:            
            selected_example = pills("Questions 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

    if 'cfg' not in st.session_state:
        yield
        #corpus_keys = str(os.environ["first, last"]).split(',')
        #cfg = {title: "SBS MMMMMMMMAAAAAAAAAAAPPPPPPPPPPP",}
        #cfg = "SBS MMMMAPPPPEEERR", # omegaConf.create({
        #    'corpus_keys': corpus_keys,
        #    'api_key': str(os.environ['api_key']),
        #    'title': os.environ['title'],
        #    'source_data_desc': os.environ['source_data_desc'],
        #    'streaming': isTrue(os.environ.get('streaming', False)),
        #    'prompt_name': os.environ.get('prompt_name', None),
        #    'examples': os.environ.get('examples', None),
        #    'language': 'English'
        #})
        #st.session_state.cfg = cfg
        #st.session_state.ex_prompt = None
        #st.session_state.first_turn = True
        #st.session_state.language = cfg.language
        #example_messages = [example.strip() for example in cfg.examples.split(",")]
        #st.session_state.example_messages = [em for em in example_messages if len(em)>0][:max_examples]
        
        #st.session_state.vq = VectaraQuery(cfg.api_key, cfg.corpus_keys, cfg.prompt_name)

    #cfg = st.session_state.cfg
    #vq = st.session_state.vq
    st.set_page_config(page_title="SSSSSSSSBBBBBBBBBSSSSSSSSSSS", layout="wide")

    # left side content
    with st.sidebar:
        #image = Image.open('Vectara-logo.png')
        #st.image(image, width=175)
        st.markdown(f"## About\n\n")
                    #f"This demo uses outside RAG to ask questions about {cfg.source_data_desc}\n")
        
        #cfg.language = st.selectbox('Language:', languages.keys())
        #if st.session_state.language != cfg.language:
        #    st.session_state.language = cfg.language
        #    reset()
        #    st.rerun()

        st.markdown("\n")
        bc1, _ = st.columns([1, 1])
        with bc1:
            if st.button('Start Over'):
                reset()
                st.rerun()

        st.markdown("---")
        st.markdown(
            "## Temporary test demo only\n"
        )       

    st.markdown(f"<center> <h2> Header Demo Test: {'SSSSSSSSSSSBBBBBBBBBBBBSSSSSSSSSS'} </h2> </center>", unsafe_allow_html=True)

    if "messages" not in st.session_state.keys():
        reset()
                
    # Display chat messages
    for message in st.session_state.messages:
        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.rerun()

    # select prompt from example question or user provided input
    if st.session_state.ex_prompt:
        prompt = st.session_state.ex_prompt
    else:
        prompt = st.chat_input()
    if prompt:
        st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑‍💻'})
        with st.chat_message("user", avatar="🧑‍💻"):
            st.write(prompt)
        st.session_state.ex_prompt = None
        
    if (st.session_state.messages[-1]["role"] == "assistant") & (st.session_state.messages[-1]["content"] != "How may I help you?"):
        streamlit_feedback(feedback_type="thumbs", on_submit = thumbs_feedback, key = st.session_state.feedback_key,
                                      kwargs = {"user_query": st.session_state.messages[-2]["content"],
                                                "chat_response": st.session_state.messages[-1]["content"],
                                                "demo_name": "SSSSSSSSSSSBBBBBBBBBBBBBBSSSSSSSSSSSS",
                                                "response_language": st.session_state.language})
    
     
if __name__ == "__main__":
    #st.set_page_config(page_title="Sticky toolbar test", layout="wide")
    nest_asyncio.apply()
    asyncio.run(launch_bot())

for i in range(100):
    st.write(f"This is scrollable content line {i}")