import streamlit as st
from streamlit_chat import message
from transformers import AutoTokenizer, AutoModelForCausalLM

# Initialize the model_name key in the st.session_state dictionary
if 'model_name' not in st.session_state:
    st.session_state['model_name'] = "microsoft/DialoGPT-medium"

# Define the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(st.session_state['model_name'])
model = AutoModelForCausalLM.from_pretrained(st.session_state['model_name'])

if 'conversation' not in st.session_state:
    st.session_state['conversation'] = None
if 'messages' not in st.session_state:
    st.session_state['messages'] = []

# Setting page title and header
st.set_page_config(page_title="Chat GPT Clone", page_icon=":robot_face:")
st.markdown("<h1 style='text-align: center;'>💻 ChatterBot</h1>", unsafe_allow_html=True)
st.subheader("How Can I Help You Today? 🤖")

st.sidebar.title("😎🗝️")
st.session_state['model_name'] = st.sidebar.text_input("Hugging Face Model Name", value="microsoft/DialoGPT-medium")
summarise_button = st.sidebar.button("Summarise the conversation", key="summarise")
st.sidebar.image('./chatbot.jpg', width=300, use_column_width=True)
if summarise_button:
    summarise_placeholder = st.sidebar.write("Nice chatting with you my friend ❤️:\n\n" + st.session_state['conversation'])

def get_response(userInput):

    if st.session_state['conversation'] is None:
        st.session_state['conversation'] = ""

    input_ids = tokenizer.encode(userInput + tokenizer.eos_token, return_tensors="pt")
    outputs = model.generate(input_ids, max_length=1024)
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    st.session_state['conversation'] += "\n" + response

    return response

response_container = st.container()
# Here we will have a container for user input text box
container = st.container()

with container:
    with st.form(key='my_form', clear_on_submit=True):
        user_input = st.text_area("Your question goes here:", key='input', height=100)
        submit_button = st.form_submit_button(label='Send')

        if submit_button:
            st.session_state['messages'].append(user_input)
            model_response = get_response(user_input)
            st.session_state['messages'].append(model_response)

            with response_container:
                for i in range(len(st.session_state['messages'])):
                    if (i % 2) == 0:
                        message(st.session_state['messages'][i], is_user=True, key=str(i) + '_user')
                    else:
                        message(st.session_state['messages'][i], key=str(i) + '_AI')