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import gradio as gr | |
import pandas as pd | |
import os | |
from apscheduler.schedulers.background import BackgroundScheduler | |
from huggingface_hub import HfApi | |
from uploads import add_new_eval | |
from utils import LEADERBOARD_PATH, CORPORA, load_data, DEFAULT_COLUMNS, DEFAULT_COLUMN_LABELS | |
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results." | |
api = HfApi() | |
TOKEN = os.environ.get("TOKEN", None) | |
def restart_space(): | |
api.restart_space(repo_id=LEADERBOARD_PATH, token=TOKEN) | |
demo = gr.Blocks() | |
with demo: | |
with open("asset/p1.md", 'r') as f: | |
gr.Markdown(f.read()) | |
with gr.Row(): | |
with gr.Accordion("π Citation", open=False): | |
with open("asset/citation_button_text.txt", 'r') as f: | |
citation_button = gr.Textbox( | |
value=f.read(), | |
label="Copy the following snippet to cite these results:", | |
elem_id="citation-button", | |
show_copy_button=True, | |
) | |
with gr.Tabs(): | |
with gr.TabItem("Leaderboard"): | |
with gr.Row(): | |
corpus_dropdown = gr.Dropdown( | |
choices=CORPORA, | |
label="π Select corpus", | |
value=CORPORA[0], | |
) | |
leaderboard_table = gr.components.Dataframe( | |
value=load_data(CORPORA[0]), | |
interactive=True, | |
visible=True, | |
) | |
corpus_dropdown.change( | |
load_data, | |
inputs=[corpus_dropdown], | |
outputs=leaderboard_table | |
) | |
with gr.Accordion("Submit a new model for evaluation"): | |
with gr.Row(): | |
with gr.Column(): | |
corpus_radio = gr.Radio(['news', 'books'], value="llama", label="Corpus") | |
organization_textbox = gr.Textbox(label="Organization") | |
mail_textbox = gr.Textbox(label="Contact email") | |
with gr.Column(): | |
file_output = gr.File() | |
submit_button = gr.Button("Submit Eval") | |
submission_result = gr.Markdown() | |
submit_button.click( | |
add_new_eval, | |
[ | |
corpus_radio, | |
organization_textbox, | |
mail_textbox, | |
file_output | |
], | |
submission_result, | |
) | |
with open(f"asset/p2.md", 'r') as f: | |
gr.Markdown(f.read()) | |
scheduler = BackgroundScheduler() | |
scheduler.add_job(restart_space, "interval", seconds=3600) | |
scheduler.start() | |
demo.launch(debug=True) | |