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import os
import gradio as gr
from apscheduler.schedulers.background import BackgroundScheduler
from huggingface_hub import HfFileSystem, HfApi
from src.assets.text_content import INTRODUCTION_TEXT, TITLE
from src.load_from_hub import load_from_hub
RESULTS_REPO = os.environ.get("RESULTS_REPO", "datasets/vlsp-2023-vllm/vllms-leaderboard")
HIDDEN_TOKEN = os.environ.get("HIDDEN_TOKEN")
api = HfApi(token=HIDDEN_TOKEN)
fs = HfFileSystem(token=HIDDEN_TOKEN)
def restart_space():
api.restart_space(repo_id="vlsp-2023-vllm/VLLMs-Leaderboard", token=HIDDEN_TOKEN)
demo = gr.Blocks()
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("Public test", elem_id="llm-benchmark-tab-table", id=0):
leaderboard_df = load_from_hub(fs, RESULTS_REPO, is_private=False)
with gr.Column():
with gr.Row():
search_bar = gr.Textbox(
placeholder=" 🔍 Search for your model and press ENTER...",
show_label=False,
elem_id="search-bar",
)
with gr.Row():
leaderboard_table = gr.components.Dataframe(
value=leaderboard_df,
)
with gr.TabItem("Private test", elem_id="llm-benchmark-tab-table", id=1):
leaderboard_df = load_from_hub(fs, RESULTS_REPO, is_private=True)
with gr.Column():
with gr.Row():
search_bar = gr.Textbox(
placeholder=" 🔍 Search for your model and press ENTER...",
show_label=False,
elem_id="search-bar",
)
with gr.Row():
leaderboard_table = gr.components.Dataframe(
value=leaderboard_df,
)
scheduler = BackgroundScheduler()
scheduler.add_job(restart_space, "interval", seconds=1800)
scheduler.start()
demo.launch() |