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import asyncio
import gradio as gr
import pandas as pd
import src.constants as constants
from src.hub import glob, load_jsonlines_file
def update_task_description_component(task):
base_description = constants.TASK_DESCRIPTIONS.get(task, "")
additional_info = "A higher score is a better score."
description = f"{base_description}\n\n{additional_info}" if base_description else additional_info
return gr.Textbox(
description,
label="Task Description",
lines=6,
visible=True,
)
def update_subtasks_component(task, profile: gr.OAuthProfile | None):
visible_login_btn = True if task == "leaderboard_gpqa" else False
subtasks = None if task == "leaderboard_gpqa" and not profile else constants.SUBTASKS.get(task)
return (
gr.LoginButton(size="sm", visible=visible_login_btn),
gr.Radio(
choices=subtasks,
info="Evaluation subtasks to be loaded",
value=None,
),
)
def update_load_details_component(model_id, subtask):
if model_id and subtask:
return gr.Button("Load Details", interactive=True)
else:
return gr.Button("Load Details", interactive=False)
def fetch_details_paths(model_id, subtask):
model_name_sanitized = model_id.replace("/", "__")
dataset_id = constants.DETAILS_DATASET_ID.format(model_name_sanitized=model_name_sanitized)
filename = constants.DETAILS_FILENAME.format(subtask=subtask)
path = f"{dataset_id}/**/{filename}"
return glob(path)
async def load_details_dataframe(model_id, subtask):
if not model_id or not subtask:
return
paths = await asyncio.to_thread(fetch_details_paths, model_id, subtask)
if not paths:
return
path = max(paths)
data = await load_jsonlines_file(path)
df = pd.json_normalize(data)
# Keep model_name:
df["model_name"] = model_id
return df.sort_values("doc_id").set_index("doc_id", drop=False).set_index("model_name", append=True)
async def load_details(model_ids, subtask):
dfs = await asyncio.gather(*[load_details_dataframe(model_id, subtask) for model_id in model_ids])
if dfs:
return pd.concat(dfs)
def display_details(df, sample_idx, show_only_differences):
if df is None:
return
df = df.loc[df.index.levels[0][sample_idx]]
df = df.T.rename_axis(columns=None)
# Style
# - Option: Show only differences
any_difference = pd.Series(False, index=df.index)
if show_only_differences:
any_difference = df.ne(df.iloc[:, 0], axis=0).any(axis=1)
return (
df.style.format(escape="html", na_rep="")
# .hide(axis="index")
# Hide non-different rows
.hide([row for row in df.index if show_only_differences and not any_difference[row]])
# Fix overflow
.set_table_styles(
[
{
"selector": "td",
"props": [("overflow-wrap", "break-word"), ("max-width", "1px")],
},
{
"selector": ".col_heading",
"props": [("width", f"{100 / len(df.columns)}%")],
},
]
)
.to_html()
)
def update_sample_idx_component(df):
if df is None:
return
maximum = len(df) - 1
return gr.Number(
label="Sample Index",
info="Index of the sample to be displayed",
value=0,
minimum=0,
maximum=maximum,
visible=True,
)
def clear_details():
# model_ids, details_dataframe, details_task, subtask, load_details_btn, sample_idx
return (
gr.Dropdown(value=[]),
None,
None,
None,
gr.Button("Load Details", interactive=False),
gr.Number(label="Sample Index", info="Index of the sample to be displayed", value=0, minimum=0, visible=False),
)
def display_loading_message_for_details():
return "<h3 style='text-align: center;'>Loading...</h3>"
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