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

from st_on_hover_tabs import on_hover_tabs

from app.pages import *

import json

# if __name__ == "__main__":
st.set_page_config(
    page_title="Leaderboard", page_icon=":chart_with_upwards_trend:", layout="wide"
)

st.header("SeaEval Leaderboard")
st.markdown('<style>' + open('./style/sidebar_style.css').read() + '</style>', unsafe_allow_html=True)

with st.sidebar:
    tabs = on_hover_tabs(tabName=['Dashboard', 
                                  'Cross-Lingual Consistency', 
                                  'Cultural Reasoning', 
                                  'General Reasoning', 
                                  'FLORES-Translation', 
                                  'Emotion', 
                                  'Dialogue', 
                                  'Fundamental NLP Tasks',
                                  ],
                            iconName=['dashboard', 'filter_1', 'filter_2', 'filter_3', 'filter_4', 
                                    'filter_5', 'filter_6', 'filter_7'], 
                            styles = {
                                'navtab': {
                                    'font-size': '12px',
                                    'transition': '0.1s',
                                    'text-transform': 'none',
                                },
                                'iconStyle':{
                                    'font-size': '18px',
                                },
                            },
                            default_choice=0
                            )
    

if tabs =='Dashboard':
    dashboard()

elif tabs == 'Cross-Lingual Consistency':
    cross_lingual_consistency()

elif tabs == 'Cultural Reasoning':
    cultural_reasoning()

elif tabs == 'General Reasoning':
    general_reasoning()

elif tabs == 'FLORES-Translation':
    flores()

elif tabs == 'Emotion':
    emotion()

elif tabs == 'Dialogue':
    dialogue()

elif tabs == 'Fundamental NLP Tasks':
    fundamental_nlp_tasks()