import streamlit as st
import nltk

@st.cache_resource
def setup_nltk():
    resources = [
        ('corpora/stopwords', 'stopwords'),
        ('corpora/wordnet', 'wordnet'),
        ('corpora/omw-1.4', 'omw-1.4'),
        ('tokenizers/punkt_tab', 'punkt_tab'),
        ('taggers/averaged_perceptron_tagger_eng', 'averaged_perceptron_tagger_eng')
    ]
    for resource_path, package_name in resources:
        try:
            nltk.data.find(resource_path)
        except LookupError:
            nltk.download(package_name)
            
setup_nltk()

main_page = st.Page("pages/main.py", title="Home", icon="🏠")
topic_model = st.Page("pages/topic.py", title="Topic Modeling", icon="🌐")
modeling = st.Page("pages/model.py", title='Predictive Modeling', icon='🎱')
user = st.Page("pages/user.py", title='User Page', icon="👤")

pg = st.navigation({"Pages": [main_page, topic_model, modeling, user]})

pg.run()