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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)}') |