# python -m streamlit run app.py
import streamlit as st
from rag import RAG
import re
import logging

@st.cache_resource
def init_rag():
    llm_url = 'http://127.0.0.1:8080/completion'
    # embed_model_name = 'intfloat/multilingual-e5-large'
    embed_model_name = 'dangvantuan/sentence-camembert-large'
    collection_name = 'cera'
    chromadb_path = './chromadb'
    rag = RAG(llm_url, embed_model_name, collection_name, chromadb_path, mulitlingual_e5=False)
    return rag

rag = init_rag()

st.title("CERA Chat")

if st.sidebar.button("Nouvelle conversation"):
    st.session_state.messages = []
    rag.reset_history()

if "messages" not in st.session_state:
    st.session_state.messages = []

for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

if prompt := st.chat_input("Comment puis-je vous aider ?"):
    st.session_state.messages.append({"role": "user", "content": prompt})
    with st.chat_message("user"):
        st.markdown(prompt)

    with st.chat_message("assistant"):
        message_placeholder = st.empty()
        full_response = ""
        for response in rag.chat(prompt):
            full_response += response
            message_placeholder.markdown(full_response + "▌")
        message_placeholder.markdown(full_response)
        # url_pattern = r"URL :\n(https?://[^\s]+)"
        # urls = re.findall(url_pattern, rag.chat_history[-1]['assistant'])
        # markdown_urls = "\n".join([f"- {url}" for url in urls])
        # logging.info(f"URLs: \n{markdown_urls}")
        # message_placeholder.markdown(markdown_urls)

    st.session_state.messages.append({"role": "assistant", "content": full_response})