app.py

import gradio as gr
import pandas as pd
import plotly.express as px
from datetime import datetime, timedelta
import requests
from io import BytesIO

def create_trend_chart(space_id, daily_ranks_df):
    if space_id is None or daily_ranks_df.empty:
        return None
    
    try:
        space_data = daily_ranks_df[daily_ranks_df['id'] == space_id].copy()
        if space_data.empty:
            return None
        
        space_data = space_data.sort_values('date')
        
        fig = px.line(
            space_data,
            x='date',
            y='rank',
            title=f'Daily Rank Trend for {space_id}',
            labels={'date': 'Date', 'rank': 'Rank'},
            markers=True
        )
        
        fig.update_layout(
            height=500,
            xaxis_title="Date",
            yaxis_title="Rank",
            yaxis=dict(
                range=[100, 1],
                tickmode='linear',
                tick0=1,
                dtick=10
            ),
            hovermode='x unified',
            plot_bgcolor='white',
            paper_bgcolor='white',
            showlegend=False,
            margin=dict(t=50, r=20, b=40, l=40)
        )
        
        fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='lightgray')
        fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='lightgray')
        
        fig.update_traces(
            line_color='#2563eb',
            line_width=2,
            marker=dict(size=8, color='#2563eb')
        )
        
        return fig
    except Exception as e:
        print(f"Error creating chart: {e}")
        return None

def create_space_card(space_info):
    return f"""
    <div class="space-card" 
         data-space-id="{space_info['id']}"
         style="
        border: 1px solid #e5e7eb;
        border-radius: 8px;
        padding: 16px;
        margin: 8px;
        background-color: white;
        box-shadow: 0 1px 3px rgba(0,0,0,0.1);
        display: inline-block;
        width: 250px;
        vertical-align: top;
        cursor: pointer;
        transition: all 0.2s;
    "
    onmouseover="this.style.transform='translateY(-2px)';this.style.boxShadow='0 4px 6px rgba(0,0,0,0.1)';"
    onmouseout="this.style.transform='none';this.style.boxShadow='0 1px 3px rgba(0,0,0,0.1)';"
    >
        <div style="font-size: 1.2em; font-weight: bold; margin-bottom: 8px;">
            #{int(space_info['rank'])}
        </div>
        <div style="margin-bottom: 8px;">
            <a href="https://huggingface.co/spaces/{space_info['id']}" 
               target="_blank" 
               style="color: #2563eb; text-decoration: none;"
               onclick="event.stopPropagation();">
                {space_info['id']} 
                <span style="font-size: 0.8em;">↗</span>
            </a>
        </div>
        <div style="color: #666;">
            Score: {space_info['trendingScore']:.2f}
        </div>
    </div>
    """

def update_display(selection):
    global daily_ranks_df
    
    if not selection:
        return None, gr.HTML(value="<div style='text-align: center; padding: 20px; color: #666;'>Select a space to view details</div>")
    
    try:
        space_id = selection
        
        latest_data = daily_ranks_df[
            daily_ranks_df['id'] == space_id
        ].sort_values('date').iloc[-1]
        
        info_text = f"""
        <div style="padding: 16px; background-color: white; border-radius: 8px; box-shadow: 0 1px 3px rgba(0,0,0,0.1);">
            <h3 style="margin: 0 0 12px 0;">Space Details</h3>
            <p style="margin: 4px 0;"><strong>ID:</strong> {space_id}</p>
            <p style="margin: 4px 0;"><strong>Current Rank:</strong> {int(latest_data['rank'])}</p>
            <p style="margin: 4px 0;"><strong>Trending Score:</strong> {latest_data['trendingScore']:.2f}</p>
            <p style="margin: 4px 0;"><strong>Created At:</strong> {latest_data['createdAt'].strftime('%Y-%m-%d')}</p>
            <p style="margin: 12px 0 0 0;">
                <a href="https://huggingface.co/spaces/{space_id}" 
                   target="_blank" 
                   style="color: #2563eb; text-decoration: none;">
                    View Space ↗
                </a>
            </p>
        </div>
        """
        
        chart = create_trend_chart(space_id, daily_ranks_df)
        
        return chart, gr.HTML(value=info_text)
        
    except Exception as e:
        print(f"Error in update_display: {e}")
        return None, gr.HTML(value=f"<div style='color: red;'>Error processing data: {str(e)}</div>")

def load_and_process_data():
    try:
        url = "https://huggingface.co/datasets/cfahlgren1/hub-stats/resolve/main/spaces.parquet"
        response = requests.get(url)
        df = pd.read_parquet(BytesIO(response.content))
        
        # 30일치 데이터 준비
        thirty_days_ago = datetime.now() - timedelta(days=30)
        df['createdAt'] = pd.to_datetime(df['createdAt'])
        df = df[df['createdAt'] >= thirty_days_ago].copy()
        
        # 날짜별 데이터 처리
        dates = pd.date_range(start=thirty_days_ago, end=datetime.now(), freq='D')
        daily_ranks = []
        
        for date in dates:
            # 해당 날짜의 데이터 추출
            date_data = df[df['createdAt'].dt.date <= date.date()].copy()
            
            # trendingScore가 같은 경우 id로 정렬하여 유니크한 순위 보장
            date_data = date_data.sort_values(['trendingScore', 'id'], ascending=[False, True])
            
            # 순위 계산
            date_data['rank'] = range(1, len(date_data) + 1)
            date_data['date'] = date.date()
            
            # 필요한 컬럼만 선택
            daily_ranks.append(
                date_data[['id', 'date', 'rank', 'trendingScore', 'createdAt']]
            )
        
        # 전체 데이터 병합
        daily_ranks_df = pd.concat(daily_ranks, ignore_index=True)
        
        # 최신 날짜의 top 100 추출
        latest_date = daily_ranks_df['date'].max()
        top_100_spaces = daily_ranks_df[
            (daily_ranks_df['date'] == latest_date) &
            (daily_ranks_df['rank'] <= 100)
        ].sort_values('rank').copy()
        
        return daily_ranks_df, top_100_spaces
    except Exception as e:
        print(f"Error loading data: {e}")
        return pd.DataFrame(), pd.DataFrame()

# 데이터 로드
print("Loading initial data...")
daily_ranks_df, top_100_spaces = load_and_process_data()
print("Data loaded successfully!")

# Gradio 인터페이스 생성
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("""
    # HF Space Ranking Tracker
    
    Track, analyze, and discover trending AI applications in the Hugging Face ecosystem. Our service continuously monitors and ranks all Spaces over a 30-day period, providing detailed analytics and daily ranking changes for the top 100 performers.
    
    ### What We Track
    - Daily ranking changes for all Hugging Face Spaces
    - Comprehensive trending scores based on 30-day activity
    - Detailed performance metrics for top 100 Spaces
    - Historical ranking data with daily granularity
    
    ### Key Features
    - **Real-time Rankings**: Stay updated with daily rank changes
    - **Interactive Visualizations**: Track ranking trajectories over time
    - **Trend Analysis**: Identify emerging popular AI applications
    - **Direct Access**: Quick links to explore trending Spaces
    - **Performance Metrics**: Detailed trending scores and statistics
    """)
    
    with gr.Tabs():
        with gr.Tab("Dashboard"):
            with gr.Row():
                trend_plot = gr.Plot(
                    label="Daily Rank Trend",
                    container=True
                )
            
            with gr.Row():
                info_box = gr.HTML(
                    value="<div style='text-align: center; padding: 20px; color: #666;'>Select a space to view details</div>"
                )
            
            with gr.Row():
                space_grid = gr.HTML(
                    value="<div style='display: flex; flex-wrap: wrap; gap: 16px; justify-content: center;'>" +
                          "".join([create_space_card(row) for _, row in top_100_spaces.iterrows()]) +
                          "</div>"
                )
                
                space_selection = gr.Radio(
                    choices=[row['id'] for _, row in top_100_spaces.iterrows()],
                    value=None,
                    visible=False
                )
        
        with gr.Tab("About"):
            gr.Markdown("""
            ### Why Use HF Space Ranking Tracker?
            - Discover trending AI demos and applications
            - Monitor your Space's performance and popularity
            - Identify emerging trends in the AI community
            - Make data-driven decisions about your AI projects
            - Stay ahead of the curve in AI application development
            
            Our dashboard provides a comprehensive view of the Hugging Face Spaces ecosystem, helping developers, researchers, and enthusiasts track and understand the dynamics of popular AI applications. Whether you're monitoring your own Space's performance or discovering new trending applications, HF Space Ranking Tracker offers the insights you need.
            
            Experience the pulse of the AI community through our daily updated rankings and discover what's making waves in the world of practical AI applications.
            """)
    
    # JavaScript를 통한 카드 클릭 이벤트 처리
    space_grid.click(
        fn=lambda: None,
        inputs=[],
        outputs=[],
        _js="""
        function() {
            document.addEventListener('click', function(e) {
                if (e.target.closest('.space-card')) {
                    const spaceId = e.target.closest('.space-card').dataset.spaceId;
                    document.querySelector(`input[type="radio"][value="${spaceId}"]`).click();
                }
            });
        }
        """
    )
    
    space_selection.change(
        fn=update_display,
        inputs=[space_selection],
        outputs=[trend_plot, info_box]
    )

if __name__ == "__main__":
    demo.launch(share=True)