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import gradio as gr
from lb_info import load_results, BUILD_L1_DF
from desc import (
LEADERBOARD_INTRODUCTION,
LEADERBOARD_MD,
CITATION_BUTTON_TEXT,
CITATION_BUTTON_LABEL,
CINEPILE_ABOUT_MD,
)
from urllib.request import urlopen
def filter_df(fields):
# Use set operations to avoid duplicates
headers = (
[
"Model",
"Params (B)",
"Average Accuracy",
]
+ fields
+ [
"Average Rank",
]
)
# Remove duplicates in headers by keeping the earliest entry
headers = list(dict.fromkeys(headers))
return table[headers]
with gr.Blocks(theme=gr.themes.Soft()) as demo:
struct = load_results()
results = struct
# Build leaderboard DataFrame for CinePile data
table, check_box = BUILD_L1_DF(results)
N_MODELS = len(table)
UP_TS = "20th October 2024" # Replace with actual timestamp
gr.Markdown(LEADERBOARD_INTRODUCTION.format(N_MODELS, UP_TS))
with gr.Tabs(elem_classes="tab-buttons") as tabs:
# First Tab: CinePile Leaderboard
with gr.TabItem("CinePile Leaderboard", elem_id="main"):
gr.Markdown(LEADERBOARD_MD)
# Checkbox for selecting question categories
checkbox_group = gr.CheckboxGroup(
choices=check_box["question_categories"],
label="Question Categories",
interactive=True,
)
# DataFrame component for displaying the leaderboard
data_component = gr.DataFrame(
value=table[check_box["essential"]],
datatype=[check_box["type_map"][x] for x in check_box["essential"]],
interactive=False,
visible=True,
)
# Update the table when checkbox changes
checkbox_group.change(
fn=filter_df, inputs=checkbox_group, outputs=data_component
)
# Second Tab: About
with gr.TabItem("About CinePile", elem_id="about"):
gr.Markdown(urlopen(CINEPILE_ABOUT_MD).read().decode())
# Add citation support under "About"
with gr.Row():
with gr.Accordion("Citation", open=False):
citation_button = gr.Textbox(
value=CITATION_BUTTON_TEXT,
label=CITATION_BUTTON_LABEL,
elem_id="citation-button",
)
demo.launch()