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Running
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CPU Upgrade
File size: 4,219 Bytes
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import os
import gradio as gr
from apscheduler.schedulers.background import BackgroundScheduler
from dabstep_benchmark.content import TITLE, INTRODUCTION_TEXT, SUBMISSION_TEXT, CITATION_BUTTON_TEXT, CITATION_BUTTON_LABEL
from dabstep_benchmark.leaderboard import *
def restart_space():
HF_API.restart_space(repo_id=HF_LEADERBOARD)
# Helper function to update both tables
def update_tables():
leaderboard_df = generate_leaderboard_df()
validated = leaderboard_df[leaderboard_df["validated"] == True].drop(columns=["validated"])
unvalidated = leaderboard_df[leaderboard_df["validated"] == False].drop(columns=["validated"])
return validated, unvalidated
if __name__ == "__main__":
os.makedirs("data/task_scores", exist_ok=True)
refresh(only_leaderboard=False)
demo = gr.Blocks()
with demo:
gr.Markdown(TITLE)
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
# Generate initial leaderboard data
validated, unvalidated = update_tables()
with gr.Tab("Validated"):
verified_table = gr.Dataframe(
value=validated,
datatype=["markdown", "str", "str", "str", "markdown", "str", "str", "str"],
interactive=False,
column_widths=["20%"],
wrap=True,
)
with gr.Tab("Unvalidated"):
unverified_table = gr.Dataframe(
value=unvalidated,
datatype=["markdown", "str", "str", "str", "markdown", "str", "str", "str"],
interactive=False,
column_widths=["20%"],
wrap=True,
)
# create a Gradio event listener that runs when the page is loaded to populate the dataframe
demo.load(update_tables, inputs=None, outputs=[verified_table, unverified_table])
refresh_button = gr.Button("Refresh")
refresh_button.click(
refresh,
inputs=[
gr.Checkbox(value=True, visible=False)
],
outputs=[
verified_table, unverified_table
],
)
with gr.Row():
with gr.Accordion("📙 Citation", open=False):
citation_button = gr.Textbox(
value=CITATION_BUTTON_TEXT,
label=CITATION_BUTTON_LABEL,
lines=len(CITATION_BUTTON_TEXT.split("\n")),
elem_id="citation-button",
) # .style(show_copy_button=True)
with gr.Accordion("Submit new agent answers for evaluation"):
with gr.Row():
gr.Markdown(SUBMISSION_TEXT, elem_classes="markdown-text")
with gr.Row():
with gr.Column():
split = gr.Radio(["all"], value="all", label="Split", visible=False)
agent_name_textbox = gr.Textbox(label="Agent name")
model_family_textbox = gr.Textbox(label="Model family")
system_prompt_textbox = gr.Textbox(label="System prompt example")
repo_url_textbox = gr.Textbox(label="Repo URL with agent code")
with gr.Column():
organisation = gr.Textbox(label="Organisation")
mail = gr.Textbox(
label="Contact email (will be stored privately, & used if there is an issue with your submission)")
file_output = gr.File()
with gr.Row():
gr.LoginButton()
submit_button = gr.Button("Submit answers")
submission_result = gr.Markdown()
submit_button.click(
process_submission,
[
split,
agent_name_textbox,
model_family_textbox,
repo_url_textbox,
file_output,
organisation,
mail
],
submission_result,
)
scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", seconds=3600*24)
scheduler.start()
demo.launch(debug=True)
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