pages/02_Initial_Topic_Modeling.py

import streamlit as st
import streamlit.components.v1 as components

st.title("Topic Modeling")

def introduction():
    st.title("Research & Methodology")
    st.markdown("LDA as Baseline: "
    "Describe the use of Latent Dirichlet Allocation as a baseline for comparison and understanding.")
    st.markdown("Process Flow: Step-by-step breakdown of the analysis process, from data gathering to insights extraction.")

    # Display the LDA visualization HTML file
    components.html(open('lda_visualization.html', 'r').read(), height=800)


def lda_page():
    st.title("Insights & Findings of Latent Dirichlet Allocation (LDA) Model")
    st.markdown("Priliminary Results: findings, notebooks, documentation")
    st.markdown("Visualizations including pyLDAvis: ")
    st.markdown("Key Trends: ")

sidebar_pages = ["Introduction", "Latent Dirichlet Allocation"]
def main():
    st.sidebar.title("Navigation")
    page = st.sidebar.selectbox("Select a page:", sidebar_pages)

    if page == "Introduction":
        introduction()
    elif page == "Latent Dirichlet Allocation":
        lda_page()

if __name__ == "__main__":
    main()