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import gradio as gr
import os
from apscheduler.schedulers.background import BackgroundScheduler
from huggingface_hub import HfApi
from datetime import datetime, timedelta
from src.assets.text_content import TITLE, INTRODUCTION_TEXT, CLEMSCORE_TEXT, MULTIMODAL_NAME, TEXT_NAME, HF_REPO
from src.leaderboard_utils import query_search, get_github_data
from src.plot_utils import split_models, plotly_plot, get_plot_df, update_open_models, update_closed_models
from src.plot_utils import reset_show_all, reset_show_names, reset_show_legend, reset_mobile_view
from src.version_utils import get_versions_data
"""
CONSTANTS
"""
# For restarting the gradio application every 24 Hrs
TIME = 43200 # in seconds # Reload will not work locally - requires HFToken # The app launches locally as expected - only without the reload utility
# For Leaderboard table
dataframe_height = 800 # Height of the table in pixels # Set on average considering all possible devices
"""
AUTO RESTART HF SPACE
"""
HF_TOKEN = os.environ.get("H4_TOKEN", None)
api = HfApi()
def restart_space():
api.restart_space(repo_id=HF_REPO, token=HF_TOKEN)
"""
GITHUB UTILS
"""
github_data = get_github_data()
multimodal_leaderboard = github_data["multimodal"][0] # Get multimodal leaderboard for its available latest version.
# Show only First 4 columns for the leaderboards
multimodal_leaderboard = multimodal_leaderboard.iloc[:, :4]
print(f"Showing the following columns for the multimodal leaderboard: {multimodal_leaderboard.columns}")
"""
VERSIONS UTILS
"""
versions_data = get_versions_data()
latest_version = versions_data['latest'] # Always show latest version in text-only benchmark
last_updated_date = versions_data['date']
version_names = list(versions_data.keys())
version_names = [v for v in version_names if v.startswith("v")] # Remove "latest" and "date" keys
global version_df
version_df = versions_data[latest_version]
def select_version_df(name):
return versions_data[name]
"""
MAIN APPLICATION
"""
hf_app = gr.Blocks()
with hf_app:
gr.HTML(TITLE)
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
with gr.Tabs(elem_classes="tab-buttons") as tabs:
"""
####################### SECOND TAB - MULTIMODAL LEADERBOARD #######################
"""
with gr.TabItem(MULTIMODAL_NAME, elem_id="mm-llm-benchmark-tab-table", id=1):
with gr.Row():
mm_search_bar = gr.Textbox(
placeholder=" 🔍 Search for models - separate multiple queries with `;` and press ENTER...",
show_label=False,
elem_id="search-bar",
)
mm_leaderboard_table = gr.Dataframe(
value=multimodal_leaderboard,
elem_id="mm-leaderboard-table",
interactive=False,
visible=True,
height=dataframe_height
)
# Show information about the clemscore and last updated date below the table
gr.HTML(CLEMSCORE_TEXT)
gr.HTML(f"Last updated - {github_data['date']}")
# Add a dummy leaderboard to handle search queries in leaderboard_table
# This will show a temporary leaderboard based on the searched value
mm_dummy_leaderboard_table = gr.Dataframe(
value=multimodal_leaderboard,
elem_id="mm-leaderboard-table-dummy",
interactive=False,
visible=False
)
# Action after submitting a query to the search bar
mm_search_bar.submit(
query_search,
[mm_dummy_leaderboard_table, mm_search_bar],
mm_leaderboard_table,
queue=True
)
"""
####################### THIRD TAB - PLOTS - %PLAYED V/S QUALITY SCORE #######################
"""
with gr.TabItem("📈 Plots", elem_id="plots", id=2):
"""
Accordion Groups to select individual models - Hidden by default
"""
with gr.Accordion("Select Open-weight Models 🌐", open=False):
open_models_selection = update_open_models()
clear_button_1 = gr.ClearButton(open_models_selection)
with gr.Accordion("Select Commercial Models 💰", open=False):
closed_models_selection = update_closed_models()
clear_button_2 = gr.ClearButton(closed_models_selection)
"""
Checkbox group to control the layout of the plot
"""
with gr.Row():
with gr.Column():
show_all = gr.CheckboxGroup(
["Select All Models"],
label="Show plot for all models 🤖",
value=[],
elem_id="value-select-3",
interactive=True,
)
with gr.Column():
show_names = gr.CheckboxGroup(
["Show Names"],
label="Show names of models on the plot 🏷️",
value=[],
elem_id="value-select-4",
interactive=True,
)
with gr.Column():
show_legend = gr.CheckboxGroup(
["Show Legend"],
label="Show legend on the plot 💡",
value=[],
elem_id="value-select-5",
interactive=True,
)
with gr.Column():
mobile_view = gr.CheckboxGroup(
["Mobile View"],
label="View plot on smaller screens 📱",
value=[],
elem_id="value-select-6",
interactive=True,
)
"""
PLOT BLOCK
"""
# Create a dummy DataFrame as an input to the plotly_plot function.
# Uses this data to plot the %played v/s quality score
with gr.Row():
dummy_plot_df = gr.DataFrame(
value=get_plot_df(),
visible=False
)
with gr.Row():
with gr.Column():
# Output block for the plot
plot_output = gr.Plot()
"""
PLOT CHANGE ACTIONS
Toggle 'Select All Models' based on the values in Accordion checkbox groups
"""
open_models_selection.change(
plotly_plot,
[dummy_plot_df, open_models_selection, closed_models_selection, show_all, show_names, show_legend,
mobile_view],
[plot_output],
queue=True
)
closed_models_selection.change(
plotly_plot,
[dummy_plot_df, open_models_selection, closed_models_selection, show_all, show_names, show_legend,
mobile_view],
[plot_output],
queue=True
)
show_all.change(
plotly_plot,
[dummy_plot_df, open_models_selection, closed_models_selection, show_all, show_names, show_legend,
mobile_view],
[plot_output],
queue=True
)
show_names.change(
plotly_plot,
[dummy_plot_df, open_models_selection, closed_models_selection, show_all, show_names, show_legend,
mobile_view],
[plot_output],
queue=True
)
show_legend.change(
plotly_plot,
[dummy_plot_df, open_models_selection, closed_models_selection, show_all, show_names, show_legend,
mobile_view],
[plot_output],
queue=True
)
mobile_view.change(
plotly_plot,
[dummy_plot_df, open_models_selection, closed_models_selection, show_all, show_names, show_legend,
mobile_view],
[plot_output],
queue=True
)
open_models_selection.change(
reset_show_all,
outputs=[show_all],
queue=True
)
closed_models_selection.change(
reset_show_all,
outputs=[show_all],
queue=True
)
"""
####################### FOURTH TAB - VERSIONS AND DETAILS #######################
"""
with gr.TabItem("🔄 Versions and Details", elem_id="versions-details-tab", id=3):
with gr.Row():
version_select = gr.Dropdown(
version_names, label="Select Version 🕹️", value=latest_version
)
with gr.Row():
search_bar_prev = gr.Textbox(
placeholder=" 🔍 Search for models - separate multiple queries with `;` and press ENTER...",
show_label=False,
elem_id="search-bar-3",
)
prev_table = gr.Dataframe(
value=version_df,
elem_id="version-leaderboard-table",
interactive=False,
visible=True,
height=dataframe_height
)
dummy_prev_table = gr.Dataframe(
value=version_df,
elem_id="version-dummy-leaderboard-table",
interactive=False,
visible=False
)
gr.HTML(CLEMSCORE_TEXT)
gr.HTML(f"Last updated - {last_updated_date}")
search_bar_prev.submit(
query_search,
[dummy_prev_table, search_bar_prev],
prev_table,
queue=True
)
version_select.change(
select_version_df,
[version_select],
prev_table,
queue=True
)
# Update Dummy Leaderboard, when changing versions
version_select.change(
select_version_df,
[version_select],
dummy_prev_table,
queue=True
)
hf_app.load()
hf_app.queue()
# Add scheduler to auto-restart the HF space at every TIME interval and update every component each time
scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, 'interval', seconds=TIME)
scheduler.start()
# Log current start time and scheduled restart time
print(datetime.now())
print(f"Scheduled restart at {datetime.now() + timedelta(seconds=TIME)}")
hf_app.launch()
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