# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.

# %% auto 0
__all__ = ['block', 'get_submissions']

# %% app.ipynb 0
import gradio as gr
import pandas as pd
from huggingface_hub import list_models

# %% app.ipynb 1
def get_submissions(category):
    submissions = list_models(filter=["dreambooth-hackathon", category], full=True)
    leaderboard_models = []

    for submission in submissions:
        # user, model, likes
        leaderboard_models.append(
            (
                submission.id.split("/")[0],
                submission.id.split("/")[-1],
                submission.likes,
            )
        )

    df = pd.DataFrame(data=leaderboard_models, columns=["User", "Model", "Likes"])
    df.sort_values(by=["Likes"], ascending=False, inplace=True)
    df.insert(0, "Rank", list(range(1, len(df) + 1)))
    return df

# %% app.ipynb 2
block = gr.Blocks()

with block:
    gr.Markdown("hi")
    with gr.Tabs():
        with gr.TabItem("Animal"):
            with gr.Row():
                animal_data = gr.outputs.Dataframe(type="pandas")
            with gr.Row():
                data_run = gr.Button("Refresh")
                data_run.click(
                    get_submissions, inputs=gr.Variable("Animal"), outputs=animal_data
                )
        with gr.TabItem("Science"):
            with gr.Row():
                science_data = gr.outputs.Dataframe(type="pandas")
            with gr.Row():
                data_run = gr.Button("Refresh")
                data_run.click(
                    get_submissions, inputs=gr.Variable("Animal"), outputs=science_data
                )
        with gr.TabItem("Food"):
            with gr.Row():
                food_data = gr.outputs.Dataframe(type="pandas")
            with gr.Row():
                data_run = gr.Button("Refresh")
                data_run.click(
                    get_submissions, inputs=gr.Variable("Food"), outputs=food_data
                )
        with gr.TabItem("Landscape"):
            with gr.Row():
                landscape_data = gr.outputs.Dataframe(type="pandas")
            with gr.Row():
                data_run = gr.Button("Refresh")
                data_run.click(
                    get_submissions, inputs=gr.Variable("Landscape"), outputs=data
                )
        with gr.TabItem("Wilcard"):
            with gr.Row():
                wildcard_data = gr.outputs.Dataframe(type="pandas")
            with gr.Row():
                data_run = gr.Button("Refresh")
                data_run.click(
                    get_submissions,
                    inputs=gr.Variable("Wildcard"),
                    outputs=wildcard_data,
                )

    block.load(get_submissions, inputs=gr.Variable("animal"), outputs=animal_data)
    block.load(get_submissions, inputs=gr.Variable("science"), outputs=science_data)
    block.load(get_submissions, inputs=gr.Variable("food"), outputs=food_data)
    block.load(get_submissions, inputs=gr.Variable("landscape"), outputs=landscape_data)
    block.load(get_submissions, inputs=gr.Variable("wildcard"), outputs=wildcard_data)


block.launch()