import gradio as gr
from gradio_leaderboard import Leaderboard, SelectColumns

from apscheduler.schedulers.background import BackgroundScheduler
from huggingface_hub import snapshot_download

from src.about import (
    CITATION_BUTTON_LABEL,
    CITATION_BUTTON_TEXT,
    EVALUATION_QUEUE_TEXT,
    INTRODUCTION_TEXT,
    BENCHMARKS_TEXT,
    TITLE,
)
from src.display.css_html_js import custom_css
from src.display.utils import (
    COLS,
    AutoEvalColumn,
    fields
)
from src.envs import API, EVAL_RESULTS_PATH, REPO_ID, RESULTS_REPO, TOKEN
from src.populate import get_leaderboard_df
from src.submission.submit import add_new_eval


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

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


LEADERBOARD_DF = get_leaderboard_df(EVAL_RESULTS_PATH, 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.result_name.name,AutoEvalColumn.eval_name.name],
        hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden],
        filter_columns=[],
        bool_checkboxgroup_label="Hide models",
        interactive=False,
    )



def greet_user(profile: gr.OAuthProfile | None):
    if profile is None:
        return "⚠️ You are not logged in."
    return f"👋 Hello, **{profile.username}**!"


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("🏅 GridNet-HD Benchmark", elem_id="benchmark-tab-table", id=0):
            leaderboard = init_leaderboard(LEADERBOARD_DF)

            def reload_leaderboard():
                # Reload dataframe
                print("reload_leaderboard")
                df = get_leaderboard_df(EVAL_RESULTS_PATH, COLS)
                return df
            # Load on app start or page refresh
            demo.load(
                fn=reload_leaderboard,
                inputs=[],
                outputs=[leaderboard]
            )

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


        with gr.TabItem("🚀 Submit here! ", elem_id="benchmark-tab-table", id=3):
            with gr.Column():
                with gr.Row():
                    gr.Markdown(EVALUATION_QUEUE_TEXT, elem_classes="markdown-text")

            with gr.Row():
                gr.Markdown("# ✉️✨ Submit your result here!", elem_classes="markdown-text")
            with gr.Row():
                gr.LoginButton()

            with gr.Row():
                with gr.Column():
                    greeting = gr.Markdown()
                    demo.load(fn=greet_user, inputs=None, outputs=greeting)
                    # user_name_textbox = gr.Textbox(label="User name")
                    result_name_textbox = gr.Textbox(label="Result name")
                    npz_files_input = gr.File(label="Upload NPZ files", file_types=[".npz"], file_count="multiple")
                    remap = gr.Checkbox(label="Remap classes : check it if you upload original classes (evaluation will only be done on mapped classes.)", value=False)

            submit_button = gr.Button("Submit Eval")
            submission_result = gr.Markdown()
            submit_button.click(
                add_new_eval,
                [
                    # user_name_textbox,
                    result_name_textbox,
                    npz_files_input,
                    remap
                ],
                submission_result,
            )


    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()