#this is one is using FALCON-7B
from langchain import HuggingFaceHub, LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.chat_models import ChatOpenAI
from langchain.chains import ConversationalRetrievalChain
from langchain.document_loaders.csv_loader import CSVLoader
from langchain.vectorstores import FAISS
import tempfile 
from streamlit_chat import message
import streamlit as st

import os 
import re
import sys
import pandas as pd

def extract_text_from_html(html):
    cleanr = re.compile('<.*?>')
    cleantext = re.sub(cleanr, '', html)
    return cleantext.strip()

def conversational_chat(query):    
    output = llm_chain.predict(human_input=query)
    return extract_text_from_html(output)


user_api_key = st.sidebar.text_input(
    label="#### Your HuggingFace API key 👇",
    placeholder="Paste your HuggingGace API key, sk-",
    type="password")

if user_api_key is not None and user_api_key.strip() != "":
    # huggingfacehub_api_token = os.environ[user_api_key]

    #setting up the LLM 
    repo_id = "tiiuae/falcon-7b-instruct"
    template = """

    Your custon promp
    {history}
    Me:{human_input}
    Jack:
    """
    prompt = PromptTemplate(
        input_variables=["history", "human_input"],
        template=template
    )
    llm_chain = LLMChain(
        llm=HuggingFaceHub(huggingfacehub_api_token=user_api_key, repo_id="tiiuae/falcon-7b-instruct", model_kwargs={"temperature": 0.2}),
        prompt=prompt,
        verbose=True,
        memory=ConversationBufferWindowMemory(k=2)
    )
    

    if 'history' not in st.session_state:
        st.session_state['history'] = []

    if 'generated' not in st.session_state:
        st.session_state['generated'] = ["Hello ! Ask me anything about " + " 🤗"]

    if 'past' not in st.session_state:
        st.session_state['past'] = ["Hey ! 👋"]
        
    #container for the chat history
    response_container = st.container()
    #container for the user's text input
    container = st.container()

    with container:
        with st.form(key='my_form', clear_on_submit=True):
            
            user_input = st.text_input("Query:", placeholder="Lets talk about something General", key='input')
            submit_button = st.form_submit_button(label='Send')
            
        if submit_button and user_input:
            output = conversational_chat(user_input)
            
            st.session_state['past'].append(user_input)
            st.session_state['generated'].append(output)
    
    if st.session_state['generated']:
        with response_container:
            for i in range(len(st.session_state['generated'])):
                message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
                message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")

else:
    st.text("Please enter your HuggingFace API key above.")