import streamlit as st
from app_models.rubert_MODEL import classify_text
from app_models.bag_of_words_MODEL import predict
from app_models.lstm_MODEL import predict_review

class_prefix =  'This review is likely...'

def run():
    st.title("Movie Review Classification")
    st.write("This page will compare three models: Bag of Words/TF-IDF, LSTM, and BERT.")
    
    # Example placeholder for user input
    user_input = st.text_area("")
    
    # Placeholder buttons for model selection
    if st.button('Classify with BoW/TF-IDF'):
        st.write(f'{class_prefix}{predict(user_input)}')
    if st.button('Classify with LSTM'):
        st.write(f'{class_prefix}{predict_review(user_input)}')
    if st.button('Classify with ruBERT'):
        st.write(f'{class_prefix}{classify_text(user_input)}')