import streamlit as st
from app.draw_diagram import *

def dashboard():

    with st.container():
        st.title("AudioBench")
   
        st.markdown("""
            [gh]: https://github.com/AudioLLMs/AudioBench
            [![GitHub watchers](https://img.shields.io/github/watchers/AudioLLMs/AudioBench?style=social)][gh]
            [![GitHub Repo stars](https://img.shields.io/github/stars/AudioLLMs/AudioBench?style=social)][gh]
            """)

    audio_url = "https://arxiv.org/abs/2406.16020"

    st.divider()
    st.markdown("#### [AudioBench](%s)" % audio_url)
    st.markdown("##### :dizzy: A comprehensive evaluation benchmark designed for general instruction-following audiolanguage models")
    st.markdown('''

                
                ''')

    with st.container():
        left_co, center_co, right_co = st.columns([0.5,1, 0.5])
        with center_co:
            st.image("./style/audio_overview.png", 
                     caption="Overview of the datasets in AudioBench.", 
                     use_column_width = True)
        
        st.markdown('''

                
                ''')
        
        st.markdown("###### :dart: Our Benchmark includes: ")
        cols = st.columns(10)
        cols[1].metric(label="Tasks", value="8", delta="Tasks", delta_color="off")
        cols[2].metric(label="Datasets", value="26", delta="Datasets", delta_color="off")
        cols[3].metric(label="Test On", value="4", delta="Models", delta_color="off")

        # st.markdown("###### :dart: Supported Models and Datasets: ")
        
        # sup = pd.DataFrame(
        #         {"Dataset": "LibriSpeech-Clean", 
        #          "Category": st.selectbox('category', ['Speech Understanding']),
        #          "Task": st.selectbox('task', ['Automatic Speech Recognition']),
        #          "Metrics": st.selectbox('metrics', ['WER']),
        #          "Status":True}
        # )
        
        # st.data_editor(sup, num_rows="dynamic")



    st.divider()
    with st.container():
        st.markdown("##### Citations")

        st.markdown('''
                    :round_pushpin: AudioBench Paper \n
                        @article{wang2024audiobench,
                            title={AudioBench: A Universal Benchmark for Audio Large Language Models},
                            author={Wang, Bin and Zou, Xunlong and Lin, Geyu and Sun, Shuo and Liu, Zhuohan and Zhang, Wenyu and Liu, Zhengyuan and Aw, AiTi and Chen, Nancy F},
                            journal={arXiv preprint arXiv:2406.16020},
                            year={2024}
                            }
                    ''')

def speech_understanding():
    st.title("Speech Understanding")
    
    filters_levelone = ['ASR', 'SQA', 'SI']
    sort_leveltwo = []
    
    left, center, _, middle,right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
    
    with left:
        filter_1 = st.selectbox('Select Category', filters_levelone)
    
    with middle:
        if filter_1 == filters_levelone[0]:
            sort_leveltwo = ['LibriSpeech-Test-Clean', 'LibriSpeech-Test-Other', 'Common-Voice-15-En-Test', 'Peoples-Speech-Test',
                            'GigaSpeech-Test', 'Tedlium3-Test','Tedlium3-Longform-Test', 'Earning-21-Test', 'Earning-22-Test']
        elif filter_1 == filters_levelone[1]:
            sort_leveltwo = ['CN-College-Listen-Test', 'SLUE-P2-SQA5-Test', 'DREAM-TTS-Test', 'Public-SG-SpeechQA-Test']
        
        elif filter_1 == filters_levelone[2]:
            sort_leveltwo = ['OpenHermes-Audio-Test', 'ALPACA-Audio-Test']
        
        sort = st.selectbox("Sort Dataset", sort_leveltwo)
    
    with right:
        sorted = st.selectbox('by', ['Ascending', 'Descending'])

    if filter_1 or sort or sorted:
        draw('su',filter_1, sort, sorted)
    else:
        draw('su', 'ASR', 'LibriSpeech-Test-Clean', 'Descending')


def audio_scene_understanding():
    st.title("Audio Scence Understanding")

    filters_levelone = ['AQA', 'AC']
    sort_leveltwo = []
    
    left, center, _, middle,right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
    
    with left:
        filter_1 = st.selectbox('Select Category', filters_levelone)
    
    with middle:
        if filter_1 == filters_levelone[0]:
            sort_leveltwo = ['Clotho-AQA-Test', 'WavCaps-QA-Test', 'AudioCaps-QA-Test']
        elif filter_1 == filters_levelone[1]:
            sort_leveltwo = ['WavCaps-Test', 'AudioCaps-Test']
        
        sort = st.selectbox("Sort Dataset", sort_leveltwo)
    
    with right:
        sorted = st.selectbox('by', ['Ascending', 'Descending'])

    if filter_1 or sort or sorted:
        draw('asu',filter_1, sort, sorted)
    else:
        draw('asu', 'AQA', 'Clotho-AQA-Test', 'Descending')


def voice_understanding():
    st.title("Voice Understanding")

    filters_levelone = ['ER', 'AR', 'GR']
    sort_leveltwo = []
    
    left, center, _, middle,right = st.columns([0.2, 0.2, 0.2, 0.2 ,0.2])
    
    with left:
        filter_1 = st.selectbox('Select Category', filters_levelone)
    
    with middle:
        if filter_1 == filters_levelone[0]:
            sort_leveltwo = ['IEMOCAP-Emotion-Test', 'MELD-Sentiment-Test', 'MELD-Emotion-Test']
        
        elif filter_1 == filters_levelone[1]:
            sort_leveltwo = ['VoxCeleb1-Accent-Test']
        
        elif filter_1 == filters_levelone[2]:
            sort_leveltwo = ['VoxCeleb1-Gender-Test', 'IEMOCAP-Gender-Test']
        
        sort = st.selectbox("Sort Dataset", sort_leveltwo)
    
    with right:
        sorted = st.selectbox('by', ['Ascending', 'Descending'])

    if filter_1 or sort or sorted:
        draw('vu',filter_1, sort, sorted)
    else:
        draw('vu', 'ER', 'IEMOCAP-Emotion-Test', 'Descending')