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import gradio as gr
from gradio_leaderboard import Leaderboard, ColumnFilter, SelectColumns
import pandas as pd
from apscheduler.schedulers.background import BackgroundScheduler
from huggingface_hub import snapshot_download
# from fastchat.serve.monitor.monitor import build_leaderboard_tab, build_basic_stats_tab, basic_component_values, leader_component_values
from src.about import (
CITATION_BUTTON_LABEL,
CITATION_BUTTON_TEXT,
EVALUATION_QUEUE_TEXT,
INTRODUCTION_TEXT,
LLM_BENCHMARKS_TEXT,
TITLE,
)
from src.display.css_html_js import custom_css
from src.display.utils import (
BENCHMARK_COLS,
COLS,
EVAL_COLS,
EVAL_TYPES,
AutoEvalColumn,
fields,
)
from src.envs import (
API,
EVAL_DETAILED_RESULTS_PATH,
EVAL_RESULTS_PATH,
EVAL_DETAILED_RESULTS_REPO,
REPO_ID,
RESULTS_REPO,
TOKEN,
)
from src.populate import get_leaderboard_df
def restart_space():
API.restart_space(repo_id=REPO_ID)
### Space initialisation
try:
print(EVAL_DETAILED_RESULTS_REPO)
snapshot_download(
repo_id=EVAL_DETAILED_RESULTS_REPO,
local_dir=EVAL_DETAILED_RESULTS_PATH,
repo_type="dataset",
tqdm_class=None,
etag_timeout=30,
token=TOKEN,
)
except Exception:
restart_space()
try:
print(EVAL_RESULTS_PATH)
snapshot_download(
repo_id=RESULTS_REPO,
local_dir=EVAL_RESULTS_PATH,
repo_type="dataset",
tqdm_class=None,
etag_timeout=30,
token=TOKEN,
)
except Exception:
restart_space()
LEADERBOARD_DF, SUBSETS = get_leaderboard_df(RESULTS_REPO)
def init_leaderboard(dataframes, subsets):
subsets = list(subsets)
with gr.Row():
selected_subset = gr.Dropdown(choices=subsets, label="Select Dataset Subset", value=subsets[-1])
# with gr.Row():
# datatype = [c.type for c in fields(AutoEvalColumn)]
# dataframe = gr.Dataframe(dataframes, datatype=datatype, type="pandas")
return Leaderboard(
value=dataframes,
datatype=[c.type for c in fields(AutoEvalColumn)],
select_columns=SelectColumns(
default_selection=[c.name for c in fields(AutoEvalColumn) if c.displayed_by_default],
cant_deselect=[c.name for c in fields(AutoEvalColumn) if c.never_hidden],
label="Select Columns to Display:",
),
search_columns=[AutoEvalColumn.model.name],
hide_columns=[c.name for c in fields(AutoEvalColumn) if c.hidden],
filter_columns=[
ColumnFilter(
column=AutoEvalColumn.dataset_version.name,
choices=subsets,
default=subsets[-1],
)
# gr.Dropdown(choices=subsets, label="Select Dataset Subset", value=subsets[-1])
],
interactive=False,
)
demo = gr.Blocks(css=custom_css)
with demo:
gr.HTML(TITLE)
gr.Markdown(INTRODUCTION_TEXT, elem_classes="markdown-text")
with gr.Tabs(elem_classes="tab-buttons") as tabs:
with gr.TabItem("🏅 LiveBench Results", elem_id="llm-benchmark-tab-table", id=0):
init_leaderboard(LEADERBOARD_DF, SUBSETS)
with gr.TabItem("📝 About", elem_id="llm-benchmark-tab-table", id=2):
gr.Markdown(LLM_BENCHMARKS_TEXT, elem_classes="markdown-text")
# with gr.Row():
# with gr.Accordion("📙 Citation", open=False):
# citation_button = gr.Textbox(
# value=CITATION_BUTTON_TEXT,
# label=CITATION_BUTTON_LABEL,
# lines=20,
# elem_id="citation-button",
# show_copy_button=True,
# )
scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", seconds=1800)
scheduler.start()
demo.queue(default_concurrency_limit=40).launch()
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