# https://ai-brewery.medium.com/conversational-chatbot-using-transformers-and-streamlit-73d621afde9
import streamlit as st
import torch
import transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

@st.cache(hash_funcs=
    {transformers.models.gpt2.tokenization_gpt2_fast.GPT2TokenizerFast: hash}, 
    suppress_st_warning=True, allow_output_mutation=True)

def load_data():    
    tokenizer = AutoTokenizer.from_pretrained("DeepPavlov/rubert-base-cased")
    model = AutoModelForCausalLM.from_pretrained("DeepPavlov/rubert-base-cased")
    return tokenizer, model

tokenizer, model = load_data()

st.write("Welcome to the Chatbot. I am still learning, please be patient")
input = st.text_input('User:')
if 'count' not in st.session_state or st.session_state.count == 6:
    st.session_state.count = 0 
    st.session_state.chat_history_ids = None
    st.session_state.old_response = ''
else:
    st.session_state.count += 1


new_user_input_ids = tokenizer.encode(input + tokenizer.eos_token, return_tensors='pt')

bot_input_ids = torch.cat([st.session_state.chat_history_ids, new_user_input_ids], dim=-1) if st.session_state.count > 1 else new_user_input_ids

st.session_state.chat_history_ids = model.generate(bot_input_ids, max_length=5000, pad_token_id=tokenizer.eos_token_id)

response = tokenizer.decode(st.session_state.chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)

if st.session_state.old_response == response:
    bot_input_ids = new_user_input_ids
    
    st.session_state.chat_history_ids = model.generate(bot_input_ids, max_length=5000, pad_token_id=tokenizer.eos_token_id)
    response = tokenizer.decode(st.session_state.chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)

st.write(f"Chatbot: {response}")
st.session_state.old_response = response