import subprocess import gradio as gr from apscheduler.schedulers.background import BackgroundScheduler from huggingface_hub import snapshot_download from src.pages.about import show_about_page from src.pages.submit import show_submit_page from src.pages.result_table import show_result_page from src.about import ( CITATION_BUTTON_LABEL, CITATION_BUTTON_TEXT, INTRODUCTION_TEXT, TITLE, ) from src.display.css_html_js import custom_css from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, QUEUE_REPO, REPO_ID, RESULTS_REPO, TOKEN from watch_leaderboard import watch_submit_queue def restart_space(): API.restart_space(repo_id=REPO_ID) try: print(EVAL_REQUESTS_PATH) snapshot_download( repo_id=QUEUE_REPO, local_dir=EVAL_REQUESTS_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() 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: show_result_page(root_path="MC", title="📝 Exam", index=0) show_result_page( root_path="LLM", title="🤖 LLM-as-a-Judge", index=1, extra=lambda: gr.Markdown( "* Gemini result is only reported in MT-Bench because the other benchmark was mistakenly classified as unsafe" ), ) show_result_page(root_path="NLU", title="🕵️ NLU", index=2) show_result_page(root_path="NLG", title="🖊️ NLG", index=3) show_about_page(index=4) show_submit_page(index=5) with gr.Column(): with gr.Accordion("📙 Citation", open=False): citation_button = gr.Textbox( value=CITATION_BUTTON_TEXT, label=CITATION_BUTTON_LABEL, lines=8, elem_id="citation-button", show_copy_button=True, ) scheduler = BackgroundScheduler() scheduler.add_job(watch_submit_queue, "interval", seconds=3500) scheduler.add_job(restart_space, "interval", seconds=3600) scheduler.start() demo.queue(default_concurrency_limit=40).launch()