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import gradio as gr
from src.leaderboard import BGB_COLUMN_MAPPING, get_bgb_leaderboard_df, get_leaderboard_df
from src.llm_perf import get_eval_df, get_llm_perf_df
def select_columns_fn(machine, columns, search, llm_perf_df=None):
if llm_perf_df is None:
llm_perf_df = get_llm_perf_df(machine=machine)
selected_leaderboard_df = get_leaderboard_df(llm_perf_df)
selected_leaderboard_df = selected_leaderboard_df[
selected_leaderboard_df["Model πŸ€—"].str.contains(search, case=False)
]
selected_leaderboard_df = selected_leaderboard_df[columns]
return selected_leaderboard_df
def select_columns_bgb_fn(machine, columns, search, type_checkboxes, param_slider, eval_df=None):
if eval_df is None:
eval_df = get_eval_df(machine)
selected_leaderboard_df = get_bgb_leaderboard_df(eval_df)
selected_leaderboard_df = selected_leaderboard_df[
selected_leaderboard_df["Model πŸ€—"].str.contains(search, case=False)
]
print(param_slider)
import pdb
pdb.set_trace()
columns = ["Model πŸ€—"] + columns + type_checkboxes
return selected_leaderboard_df[columns]
def create_select_callback(
# fixed
machine_textbox,
# interactive
columns_checkboxes,
search_bar,
type_checkboxes,
param_slider,
# outputs
leaderboard_table,
):
columns_checkboxes.change(
fn=select_columns_bgb_fn,
inputs=[machine_textbox, columns_checkboxes, search_bar, type_checkboxes, param_slider],
outputs=[leaderboard_table],
)
search_bar.change(
fn=select_columns_bgb_fn,
inputs=[machine_textbox, columns_checkboxes, search_bar, type_checkboxes, param_slider],
outputs=[leaderboard_table],
)