import streamlit as st
from apps.utils import read_markdown
from streamlit_tensorboard import st_tensorboard

def app(state):
    st.info("Welcome to our Multilingual-VQA demo. Please use the navigation sidebar to move to our demo, or scroll below to read all about our project. 🤗")
    st.write(read_markdown("intro.md"))
    st.write("## Methodology")
    st.write(read_markdown("pretraining.md"))
    st.image(
        "./misc/article/Multilingual-VQA.png",
        caption="Masked LM model for Image-text Pretraining.",
    )
    st.write("**Training Logs**")
    st_tensorboard(logdir='./logs/pretrain_logs', port=6006)

    st.write(read_markdown("finetuning.md"))
    st.write("**Training Logs**")
    st_tensorboard(logdir='./logs/finetune_logs', port=6007)

    st.write(read_markdown("challenges.md"))
    st.write(read_markdown("limitations.md"))
    st.write(read_markdown("social_impact.md"))
    st.write(read_markdown("references.md"))
    st.write(read_markdown("checkpoints.md"))
    st.write(read_markdown("acknowledgements.md"))