import streamlit as st
from langchain_core.messages import AIMessage, HumanMessage
from langchain_community.document_loaders import WebBaseLoader


def get_response(user_input):
    return "I dont know"

def get_vector_store_from_url(url):
    loader = WebBaseLoader(url)
    documents = loader.load()
    return documents

# app config
st.set_page_config(page_title= "Chat with Websites", page_icon="🤖")
st.title("Chat with Websites")


if "chat_history" not in st.session_state:
    st.session_state.chat_history = [ 
    AIMessage(content = "Hello, I am a bot. How can I help you"),
]


#sidebar
with st.sidebar:
    st.header("Settings")
    website_url = st.text_input("Website URL")
    openai_apikey = st.text_input("Enter your OpenAI API key")

if (website_url is None or website_url == "") or (openai_apikey is None or openai_apikey == ""):
    st.info("Please ensure if website URL and Open AI api key are entered")
    

else:

    documents = get_vector_store_from_url(website_url)
    with st.sidebar:
        st.write(documents)
    
    #user_input
    user_query = st.chat_input("Type your message here...")
    if user_query is not None and user_query !="":
        response = get_response(user_query)
        st.session_state.chat_history .append(HumanMessage(content=user_query))
        st.session_state.chat_history .append(AIMessageMessage(content=response))
        
                
    #conversation
    for message in st.session_state.chat_history:
        if isinstance(message, AIMessage): # checking if the messsage is the instance of an AI message
            with st.chat_message("AI"):
                st.write(message.content)
        elif isinstance(message, HumanMessage): # checking if the messsage is the instance of a Human
            with st.chat_message("Human"):
                st.write(message.content)