backend / app.py
meg-huggingface
Inference endpoints and parallelism.
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from apscheduler.schedulers.background import BackgroundScheduler
from src.logging import configure_root_logger
configure_root_logger()
from functools import partial
import gradio as gr
import main_backend_toxicity
from src.display.log_visualizer import log_file_to_html_string
from src.display.css_html_js import dark_mode_gradio_js
from src.envs import REFRESH_RATE, REPO_ID, QUEUE_REPO, RESULTS_REPO
from src.logging import setup_logger, log_file
logger = setup_logger(__name__)
intro_md = f"""
# Intro
This is a visual for the auto evaluator.
"""
links_md = f"""
# Important links
| Description | Link |
|-----------------|------|
| Leaderboard | [{REPO_ID}](https://huggingface.co/spaces/{REPO_ID}) |
| Queue Repo | [{QUEUE_REPO}](https://huggingface.co/datasets/{QUEUE_REPO}) |
| Results Repo | [{RESULTS_REPO}](https://huggingface.co/datasets/{RESULTS_REPO}) |
"""
def auto_eval():
logger.info("Triggering Auto Eval")
main_backend_toxicity.run_auto_eval()
reverse_order_checkbox = gr.Checkbox(label="Reverse Order", value=True)
with gr.Blocks(js=dark_mode_gradio_js) as backend_ui:
gr.Markdown(intro_md)
with gr.Tab("Application"):
output_html = gr.HTML(partial(log_file_to_html_string,
reverse=reverse_order_checkbox), every=10)
with gr.Row():
download_button = gr.DownloadButton("Download Log File",
value=log_file)
with gr.Accordion('Log View Configuration', open=False):
reverse_order_checkbox.render()
# Add a button that when pressed, triggers run_auto_eval
button = gr.Button("Manually Run Evaluation")
gr.Markdown(links_md)
# This will run the eval before fully loading the UI,
# and the UI will error out if it takes longer than 30 seconds.
# Changing to use BackgroundScheduler instead.
# dummy = gr.Markdown(main_backend_toxicity.run_auto_eval(), every=REFRESH_RATE, visible=False)
button.click(fn=auto_eval, inputs=[], outputs=[])
if __name__ == '__main__':
scheduler = BackgroundScheduler()
scheduler.add_job(auto_eval, "interval", seconds=REFRESH_RATE)
scheduler.start()
backend_ui.queue(default_concurrency_limit=40).launch(server_name="0.0.0.0",
show_error=True,
server_port=7860)