app.py

#!/usr/bin/env python

import datetime

import gradio as gr
import pandas as pd
from apscheduler.schedulers.background import BackgroundScheduler
from gradio_calendar import Calendar

from papers import PaperList, get_df

DESCRIPTION = "# Papers Leaderboard\nExplore the latest papers and filter by date, title, or abstract keywords."
FOOT_NOTE = "Community: https://discord.gg/openfreeai"

paper_list = PaperList(get_df())

def update_paper_list() -> None:
    global paper_list
    paper_list = PaperList(get_df())

scheduler = BackgroundScheduler()
scheduler.add_job(func=update_paper_list, trigger="cron", hour="*", timezone="UTC", misfire_grace_time=60)
scheduler.start()

def update_df() -> gr.Dataframe:
    return gr.Dataframe(value=paper_list.df_prettified)

def update_num_papers(df: pd.DataFrame) -> str:
    return f"{len(df)} / {len(paper_list.df_raw)}"

def search(
    start_date: datetime.datetime,
    end_date: datetime.datetime,
    search_title: str,
    search_abstract: str,
    max_num_to_retrieve: int,
) -> pd.DataFrame:
    return paper_list.search(start_date, end_date, search_title, search_abstract, max_num_to_retrieve)

# ------------------------------------------------------------------
# CSS
# ------------------------------------------------------------------
css = """
body {
  margin: 0;
  padding: 0;
  background: linear-gradient(135deg, #eef2ff 0%, #fdfdfd 100%);
  font-family: "Helvetica Neue", Arial, sans-serif;
}
#hero-section {
  background: linear-gradient(135deg, #3b82f6 0%, #9333ea 100%);
  padding: 2rem;
  border-radius: 0.5rem;
  margin-bottom: 1rem;
  color: white;
}
#hero-section h1 {
  font-size: 2.2rem;
  margin-bottom: 0.5rem;
}
.search-container {
  background-color: #ffffffdd;
  backdrop-filter: blur(6px);
  border-radius: 0.75rem;
  padding: 1rem 1.5rem;
  box-shadow: 0 3px 5px rgba(0,0,0,0.1);
  margin-bottom: 1rem;
}
.card {
  background-color: #fff;
  border-radius: 0.75rem;
  padding: 1.5rem;
  box-shadow: 0 2px 5px rgba(0, 0, 0, 0.1);
  margin-bottom: 1rem;
}
#table table {
  border-collapse: collapse;
  width: 100%;
  background: #fafafa;
}
#table th, #table td {
  border: 1px solid #e5e7eb;
  padding: 0.5rem;
  text-align: left;
}
#table thead {
  background-color: #f3f4f6;
  font-weight: 600;
}
.footer {
  color: #6b7280;
  font-size: 0.9rem;
  text-align: center;
  margin-top: 2rem;
}
"""

with gr.Blocks(css=css) as demo:
    # Hero 섹션
    gr.HTML(
        """
        <div id="hero-section">
          <h1>Papers Leaderboard</h1>
          <p>Explore the latest papers and filter by date, title, or abstract keywords.</p>
        </div>
        """
    )

    # Search & Filter 헤더 및 외부 링크
    gr.Markdown(
        "[Exp] AI‑Powered Research Impact Predictor ↗](https://huggingface.co/spaces/VIDraft/PapersImpact)",
        elem_classes="search-container"
    )

    # 검색 입력
    with gr.Group():
        search_title = gr.Textbox(label="Search title")
        with gr.Row():
            with gr.Column(scale=4):
                search_abstract = gr.Textbox(
                    label="Search abstract",
                    info="Search within abstracts (may not be fully accurate).",
                )
            with gr.Column(scale=1):
                max_num_to_retrieve = gr.Slider(
                    label="Max number to retrieve",
                    info="Applies only to abstract-based searching",
                    minimum=1,
                    maximum=len(paper_list.df_raw),
                    step=1,
                    value=100,
                )
        with gr.Row():
            start_date = Calendar(label="Start date", type="datetime", value="2023-05-05")
            end_date = Calendar(label="End date", type="datetime")

    # 결과: 통계 및 테이블
    with gr.Group(elem_id="results-section"):
        with gr.Group(elem_classes="card"):
            num_papers = gr.Textbox(
                label="Number of papers",
                value=update_num_papers(paper_list.df_raw),
                interactive=False
            )
        df = gr.Dataframe(
            value=paper_list.df_prettified,
            datatype=paper_list.column_datatype,
            type="pandas",
            interactive=False,
            max_height=800,
            elem_id="table",
            column_widths=["10%", "10%", "60%", "10%", "5%", "5%"],
            wrap=True,
        )

    gr.Markdown(FOOT_NOTE, elem_classes="footer")

    # 이벤트 연결
    gr.on(
        triggers=[start_date.change, end_date.change, search_title.submit, search_abstract.submit],
        fn=search,
        inputs=[start_date, end_date, search_title, search_abstract, max_num_to_retrieve],
        outputs=df,
        api_name=False,
    ).then(
        fn=update_num_papers,
        inputs=df,
        outputs=num_papers,
        queue=False,
        api_name=False,
    )

    demo.load(
        fn=update_df,
        outputs=df,
        queue=False,
        api_name=False,
    ).then(
        fn=update_num_papers,
        inputs=df,
        outputs=num_papers,
        queue=False,
        api_name=False,
    )

if __name__ == "__main__":
    demo.queue(api_open=False).launch(show_api=False)