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

from src.about import (
    CITATION_BUTTON_LABEL,
    CITATION_BUTTON_TEXT,
    INTRODUCTION_TEXT,
    LLM_BENCHMARKS_TEXT,
    TITLE,
)
from src.display.css_html_js import custom_css
from src.display.utils import (
    BENCHMARK_COLS,
    COLS,
    EVAL_COLS,
    EVAL_TYPES,
    AutoEvalColumn,
    ModelType,
    fields,
    WeightType,
    Precision,
)
from src.envs import API, EVAL_RESULTS_PATH_CDM, EVAL_RESULTS_PATH_CDM_FI, REPO_ID, RESULTS_REPO_CDM, RESULTS_REPO_CDM_FI, TOKEN
from src.populate import get_leaderboard_df


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


### Space initialisation
try:
    print(EVAL_RESULTS_PATH_CDM)
    snapshot_download(
        repo_id=RESULTS_REPO_CDM,
        local_dir=EVAL_RESULTS_PATH_CDM,
        repo_type="dataset",
        tqdm_class=None,
        etag_timeout=30,
        token=TOKEN,
    )
except Exception:
    restart_space()

try:
    print(EVAL_RESULTS_PATH_CDM_FI)
    snapshot_download(
        repo_id=RESULTS_REPO_CDM_FI,
        local_dir=EVAL_RESULTS_PATH_CDM_FI,
        repo_type="dataset",
        tqdm_class=None,
        etag_timeout=30,
        token=TOKEN,
    )
except Exception:
    restart_space()


LEADERBOARD_DF_CDM = get_leaderboard_df(EVAL_RESULTS_PATH_CDM, COLS, BENCHMARK_COLS)
LEADERBOARD_DF_CDM_FI = get_leaderboard_df(EVAL_RESULTS_PATH_CDM_FI, COLS, BENCHMARK_COLS)

def init_leaderboard(dataframe):
    if dataframe is None or dataframe.empty:
        raise ValueError("Leaderboard DataFrame is empty or None.")
    return Leaderboard(
        value=dataframe,
        datatype=[c.type for c in fields(AutoEvalColumn)],
        select_columns=SelectColumns(
            default_selection=[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default],
            cant_deselect=[c.name for c in fields(AutoEvalColumn) if c.never_hidden],
            label="Select Columns to Display:",
        ),
        search_columns=[AutoEvalColumn.model.name],
        # hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden],
        # filter_columns=[
            # ColumnFilter(AutoEvalColumn.model_type.name, type="checkboxgroup", label="Model types"),
            # ColumnFilter(AutoEvalColumn.precision.name, type="checkboxgroup", label="Precision"),
            # ColumnFilter(
            #     AutoEvalColumn.seq_length.name,
            #     type="checkboxgroup",
            #     label="Sequence Lengths",
            # )
            # ColumnFilter(AutoEvalColumn.still_on_hub.name, type="boolean", label="Deleted/incomplete", default=True),
        # ],
        # bool_checkboxgroup_label="Hide models",
        interactive=False,
    )


demo = gr.Blocks(css=custom_css)
with demo:
    gr.HTML(TITLE)
    gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")

    with gr.Tabs(elem_classes="tab-buttons") as tabs:
        with gr.TabItem("MIMIC CDM", elem_id="llm-benchmark-tab-table", id=0):
            leaderboard = init_leaderboard(LEADERBOARD_DF_CDM)

        with gr.TabItem("MIMIC CDM FI", elem_id="llm-benchmark-tab-table", id=1):
            leaderboard = init_leaderboard(LEADERBOARD_DF_CDM_FI)

        with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
            gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")

    with gr.Row():
        with gr.Accordion("📙 Citation", open=False):
            citation_button = gr.Textbox(
                value=CITATION_BUTTON_TEXT,
                label=CITATION_BUTTON_LABEL,
                lines=20,
                elem_id="citation-button",
                show_copy_button=True,
            )

scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", seconds=1800)
scheduler.start()
demo.queue(default_concurrency_limit=40).launch(share=True)