import gradio as gr
import pandas as pd

import constants
from utils import display, eval_requests

#
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#

# Load leaderboard data
leaderboard_df = pd.read_csv("leaderboard.csv")

# Get already evaluated or requested models
evaluated_models = leaderboard_df["model"].tolist()
requested_models = eval_requests.get_requested_models()

# Format the dataframe
for col in leaderboard_df.columns:
    if col == "model":
        leaderboard_df[col] = leaderboard_df[col].apply(lambda x: x.replace(x, display.make_clickable_model(x)))
    else:
        leaderboard_df[col] = leaderboard_df[col].apply(display.round_numbers)
leaderboard_df.rename(
                columns={"Average WER": "Average WER ⬇️", "RTF (1e-3)": "RTF (1e-3) ⬇️"},
                inplace=True,
            )
leaderboard_df.sort_values(by='Average WER ⬇️', inplace=True)

with gr.Blocks() as leaderboard_app:

    gr.HTML(constants.BANNER, elem_id="constants.banner")
    gr.Markdown(constants.INTRODUCTION_TEXT, elem_classes="markdown-text")

    with gr.Tabs(elem_classes="tab-buttons") as tabs:

        with gr.TabItem("🏅 Leaderboard", elem_id="od-benchmark-tab-table", id=0):
            leaderboard_table = gr.components.Dataframe(
                                    value=leaderboard_df,
                                    datatype=constants.COLUMN_DTYPES_LIST,
                                    elem_id="leaderboard-table",
                                    interactive=False,
                                    visible=True,
                                )

        with gr.TabItem("📈 Metrics", elem_id="od-benchmark-tab-table", id=1):
            gr.Markdown(constants.METRICS_TAB_TEXT, elem_classes="markdown-text")

        with gr.TabItem("✉️ Request a model here!", elem_id="od-benchmark-tab-table", id=2):
            with gr.Column():
                gr.Markdown("# ✉️ Request results for a new model here!", elem_classes="markdown-text")
                gr.Markdown("In case of multiple requests, wait the restart of the Space after each of them to ensure a correct submission.", elem_classes="markdown-text")
            with gr.Column():
                with gr.Column():
                    model_id = gr.Textbox(label="Model ID (user_name/model_name)")
                with gr.Column():
                    md_submission_result = gr.Markdown()
                    btn_submitt = gr.Button(value="🚀 Request")
                    btn_submitt.click(
                            fn=lambda model_id: eval_requests.request_model(model_id, evaluated_models, requested_models),
                            inputs=[model_id],      # inputs: List of gradio.components
                            outputs=md_submission_result,
                        )

        with gr.TabItem("☢️ Evaluate", elem_id="od-benchmark-tab-table", id=3):
            with gr.Column():
                gr.Markdown("For admins only.", elem_classes="markdown-text")
            with gr.Column():
                md_submission_result = gr.Markdown()
                btn_submitt = gr.Button(value="RUN EVALUATION")
                # btn_submitt.click(eval_requests.request_model, [model_id], md_submission_result)
    
    with gr.Row():
        with gr.Accordion("📙 Citation", open=False):
            gr.Textbox(
                value=constants.CITATION_TEXT, lines=7,
                label="Copy the BibTeX snippet to cite this source",
                elem_id="citation-button",
                show_label=True,
                show_copy_button=True,
            )

leaderboard_app.launch(allowed_paths=["banner.png"])