import gradio as gr
from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
import pandas as pd
import logging
from apscheduler.schedulers.background import BackgroundScheduler

from src.envs import API, REPO_ID, TOKEN

from utils import get_data, submit, refresh


def restart_space():
    refresh()
    API.restart_space(repo_id=REPO_ID)


dimensions = ['Audience', 'Keyword', 'Format', 'Language', 'Length', 'Source']

display_columns = [
    "Rank", "Model", "WISE", "SICR", "nDCG@10(Original)", "nDCG@10(Instructed)",
    "nDCG@10(Reversely Instructed)", "MRR@1(Original)", "MRR@1(Instructed)",
    "MRR@1(Reversely Instructed)"
]

data_type = ["number", "markdown", "number", "number", "number", "number", "number", "number", "number", "number"]

css = """
table > thead {
    white-space: normal
}

table {
    --cell-width-1: 250px
}

table > tbody > tr > td:nth-child(2) > div {
    overflow-x: auto
}

.filter-checkbox-group {
    max-width: max-content;
}

.fixed-height-table {
    height: 100px;
    overflow-y: scroll;
}

"""

# create Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# 🤗 InfoSearch Benchmark Leaderboard")
    with gr.Tabs() as tabs:
        with gr.TabItem("🏅 InfoSearch Benchmark"):
            for dimension in dimensions:
                with gr.Tab(dimension):
                    data = get_data(f"{dimension}")
                    gr.Dataframe(data,
                                 headers=display_columns,
                                 datatype=data_type,
                                 interactive=False, elem_classes=["fixed-height-table"])
        with gr.TabItem("🚀 Submit here!"):
            gr.Markdown("✉️✨ Submit your model here.")
            file_upload = gr.File(label="Upload your JSON file")
            submit_button = gr.Button("Submit")
            submission_result = gr.Markdown()
            submit_button.click(submit, file_upload, submission_result)

logging.basicConfig()
logging.getLogger('apscheduler').setLevel(logging.DEBUG)

scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", seconds=3600)
scheduler.start()
demo.queue(default_concurrency_limit=40).launch()