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import gradio as gr
import pandas as pd
from about import (
INTRODUCTION_TEXT,
TITLE,
)
from apscheduler.schedulers.background import BackgroundScheduler
from display.css_html_js import custom_css
from display.utils import (
COLS,
TYPES,
AutoEvalColumn,
fields,
)
from parser import update_leaderboard_table
from populate import get_leaderboard_df
from settings import (
get_settings,
)
settings = get_settings()
def filter_table(
hidden_df: pd.DataFrame,
columns: list,
show_deleted: bool,
query: str,
) -> pd.DataFrame:
filtered_df = filter_models(hidden_df, show_deleted)
filtered_df = filter_queries(query, filtered_df)
df = select_columns(filtered_df, columns)
return df
def search_table(df: pd.DataFrame, query: str) -> pd.DataFrame:
return df[(df[AutoEvalColumn.model.name].str.contains(query, case=False))]
def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
always_here_cols = [
AutoEvalColumn.model.name.lower(),
]
s = [c for c in COLS if c in df.columns and c in columns]
filtered_df = df[always_here_cols + s]
return filtered_df
def filter_queries(query: str, filtered_df: pd.DataFrame) -> pd.DataFrame:
final_df = []
if query != "":
queries = [q.strip() for q in query.split(";")]
for _q in queries:
_q = _q.strip()
if _q != "":
temp_filtered_df = search_table(filtered_df, _q)
if len(temp_filtered_df) > 0:
final_df.append(temp_filtered_df)
if len(final_df) > 0:
filtered_df = pd.concat(final_df)
filtered_df = filtered_df.drop_duplicates(
subset=[
AutoEvalColumn.model.name,
]
)
return filtered_df
def filter_models(
df: pd.DataFrame,
show_deleted: bool,
) -> pd.DataFrame:
if show_deleted:
filtered_df = df
else:
filtered_df = df[df[AutoEvalColumn.is_private.name]]
return filtered_df
def get_leaderboard() -> gr.TabItem:
with gr.TabItem("π
Encodechka", elem_id="llm-benchmark-tab-table", id=0) as leaderboard_tab:
with gr.Row():
with gr.Column():
with gr.Row():
search_bar = gr.Textbox(
placeholder=" π Search for your model (separate multiple queries with `;`) "
"and press ENTER...",
show_label=False,
elem_id="search-bar",
)
with gr.Row():
shown_columns = gr.CheckboxGroup(
choices=[c.name for c in fields(AutoEvalColumn) if not c.hidden and not c.never_hidden],
value=[
c.name
for c in fields(AutoEvalColumn)
if c.displayed_by_default and not c.hidden and not c.never_hidden
],
label="Select columns to show",
elem_id="column-select",
interactive=True,
)
with gr.Row():
private_models_visibility = gr.Checkbox(
value=True,
label="Show private models",
interactive=True,
)
leaderboard_table = gr.Dataframe(
value=get_leaderboard_df(),
headers=[c.name for c in fields(AutoEvalColumn) if c.never_hidden] + shown_columns.value,
datatype=TYPES,
elem_id="leaderboard-table",
interactive=False,
visible=True,
)
hidden_leaderboard_table_for_search = gr.Dataframe(
value=get_leaderboard_df(),
headers=COLS,
datatype=TYPES,
visible=False,
)
search_bar.submit(
filter_table,
[
hidden_leaderboard_table_for_search,
shown_columns,
private_models_visibility,
search_bar,
],
leaderboard_table,
)
for selector in [
shown_columns,
private_models_visibility,
]:
selector.change(
filter_table,
[
hidden_leaderboard_table_for_search,
shown_columns,
private_models_visibility,
search_bar,
],
leaderboard_table,
queue=True,
)
return leaderboard_tab
def build_app() -> gr.Blocks:
with gr.Blocks(css=custom_css) as app:
gr.HTML(TITLE)
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
get_leaderboard()
return app
def main():
update_leaderboard_table()
app = build_app()
scheduler = BackgroundScheduler()
scheduler.add_job(update_leaderboard_table, "interval", days=1)
scheduler.start()
app.queue(default_concurrency_limit=40).launch()
if __name__ == "__main__":
main()
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