Update app.py

app.py

@@ -1,49 +1,45 @@
+import gradio as gr
 import requests
 import pandas as pd
 import matplotlib.pyplot as plt
 import seaborn as sns
 from datetime import datetime, timedelta
-import numpy as np
-import streamlit as st
 import plotly.graph_objects as go
-import plotly.express as px
-from PIL import Image
-import io
-import base64
-
-# 페이지 설정
-st.set_page_config(layout="wide", page_title="HuggingFace Spaces Trending Analysis")
-
-# 스타일 적용
-st.markdown("""
-    <style>
-    .main {
-        background-color: #f5f5f5;
-    }
-    .stButton>button {
-        background-color: #ff4b4b;
-        color: white;
-        border-radius: 5px;
-    }
-    .trending-card {
-        padding: 20px;
-        border-radius: 10px;
-        background-color: white;
-        box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-        margin: 10px 0;
-    }
-    </style>
-    """, unsafe_allow_html=True)
-
-# 타이틀
-st.title("🤗 HuggingFace Spaces Trending Analysis")
+import numpy as np
+import json
 
 # 관심 스페이스 URL 리스트와 정보
 target_spaces = {
     "ginipick/FLUXllama": "https://huggingface.co/spaces/ginipick/FLUXllama",
     "ginipick/SORA-3D": "https://huggingface.co/spaces/ginipick/SORA-3D",
     "fantaxy/Sound-AI-SFX": "https://huggingface.co/spaces/fantaxy/Sound-AI-SFX",
-    # ... [나머지 스페이스들도 동일한 형식으로 추가]
+    "fantos/flx8lora": "https://huggingface.co/spaces/fantos/flx8lora",
+    "ginigen/Canvas": "https://huggingface.co/spaces/ginigen/Canvas",
+    "fantaxy/erotica": "https://huggingface.co/spaces/fantaxy/erotica",
+    "ginipick/time-machine": "https://huggingface.co/spaces/ginipick/time-machine",
+    "aiqcamp/FLUX-VisionReply": "https://huggingface.co/spaces/aiqcamp/FLUX-VisionReply",
+    "openfree/Tetris-Game": "https://huggingface.co/spaces/openfree/Tetris-Game",
+    "openfree/everychat": "https://huggingface.co/spaces/openfree/everychat",
+    "VIDraft/mouse1": "https://huggingface.co/spaces/VIDraft/mouse1",
+    "kolaslab/alpha-go": "https://huggingface.co/spaces/kolaslab/alpha-go",
+    "ginipick/text3d": "https://huggingface.co/spaces/ginipick/text3d",
+    "openfree/trending-board": "https://huggingface.co/spaces/openfree/trending-board",
+    "cutechicken/tankwar": "https://huggingface.co/spaces/cutechicken/tankwar",
+    "openfree/game-jewel": "https://huggingface.co/spaces/openfree/game-jewel",
+    "VIDraft/mouse-chat": "https://huggingface.co/spaces/VIDraft/mouse-chat",
+    "ginipick/AccDiffusion": "https://huggingface.co/spaces/ginipick/AccDiffusion",
+    "aiqtech/Particle-Accelerator-Simulation": "https://huggingface.co/spaces/aiqtech/Particle-Accelerator-Simulation",
+    "openfree/GiniGEN": "https://huggingface.co/spaces/openfree/GiniGEN",
+    "kolaslab/3DAudio-Spectrum-Analyzer": "https://huggingface.co/spaces/kolaslab/3DAudio-Spectrum-Analyzer",
+    "openfree/trending-news-24": "https://huggingface.co/spaces/openfree/trending-news-24",
+    "ginipick/Realtime-FLUX": "https://huggingface.co/spaces/ginipick/Realtime-FLUX",
+    "VIDraft/prime-number": "https://huggingface.co/spaces/VIDraft/prime-number",
+    "kolaslab/zombie-game": "https://huggingface.co/spaces/kolaslab/zombie-game",
+    "fantos/miro-game": "https://huggingface.co/spaces/fantos/miro-game",
+    "kolaslab/shooting": "https://huggingface.co/spaces/kolaslab/shooting",
+    "VIDraft/Mouse-Hackathon": "https://huggingface.co/spaces/VIDraft/Mouse-Hackathon",
+    "upstage/open-ko-llm-leaderboard": "https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard",
+    "LGAI-EXAONE/EXAONE-3.5-Instruct-Demo": "https://huggingface.co/spaces/LGAI-EXAONE/EXAONE-3.5-Instruct-Demo",
     "NCSOFT/VARCO_Arena": "https://huggingface.co/spaces/NCSOFT/VARCO_Arena"
 }
 
@@ -60,9 +56,7 @@ def get_space_rank(spaces, space_id):
             return idx
     return None
 
-# 데이터 수집
-@st.cache_data
-def fetch_trending_data():
+def fetch_and_analyze_data():
     start_date = datetime(2023, 12, 1)
     end_date = datetime(2023, 12, 31)
     dates = [(start_date + timedelta(days=x)).strftime('%Y-%m-%d') 
@@ -71,107 +65,119 @@ def fetch_trending_data():
     trending_data = {}
     target_space_ranks = {space: [] for space in target_spaces.keys()}
     
-    with st.spinner('데이터를 불러오는 중...'):
-        for date in dates:
-            spaces = get_trending_spaces(date)
-            if spaces:
-                trending_data[date] = spaces
-                for space_id in target_spaces.keys():
-                    rank = get_space_rank(spaces, space_id)
-                    target_space_ranks[space_id].append(rank)
+    for date in dates:
+        spaces = get_trending_spaces(date)
+        if spaces:
+            trending_data[date] = spaces
+            for space_id in target_spaces.keys():
+                rank = get_space_rank(spaces, space_id)
+                target_space_ranks[space_id].append(rank)
     
     return trending_data, target_space_ranks, dates
 
-trending_data, target_space_ranks, dates = fetch_trending_data()
-
-# 시각화
-st.header("📈 Trending Rank Changes")
-
-# Plotly를 사용한 인터랙티브 그래프
-fig = go.Figure()
-
-for space_id, ranks in target_space_ranks.items():
-    fig.add_trace(go.Scatter(
-        x=dates,
-        y=ranks,
-        name=space_id,
-        mode='lines+markers',
-        hovertemplate=
-        '<b>Date</b>: %{x}<br>' +
-        '<b>Rank</b>: %{y}<br>' +
-        '<b>Space</b>: ' + space_id
-    ))
-
-fig.update_layout(
-    title='Trending Ranks Over Time',
-    xaxis_title='Date',
-    yaxis_title='Rank',
-    yaxis_autorange='reversed',
-    height=800,
-    template='plotly_white',
-    hovermode='x unified'
-)
-
-st.plotly_chart(fig, use_container_width=True)
-
-# 최신 순위 정보 출력
-st.header("🏆 Latest Rankings")
-
-latest_date = max(trending_data.keys())
-latest_spaces = trending_data[latest_date]
-
-cols = st.columns(3)
-col_idx = 0
-
-for space_id, url in target_spaces.items():
-    rank = get_space_rank(latest_spaces, space_id)
-    if rank:
-        space_info = next((s for s in latest_spaces if s['id'] == space_id), None)
-        if space_info:
-            with cols[col_idx % 3]:
-                with st.container():
-                    st.markdown(f"""
-                    <div class="trending-card">
-                        <h3>#{rank} - {space_id}</h3>
-                        <p>👍 Likes: {space_info.get('likes', 'N/A')}</p>
-                        <p>📝 {space_info.get('title', 'N/A')}</p>
-                        <p>{space_info.get('description', 'N/A')[:100]}...</p>
-                        <a href="{url}" target="_blank">Visit Space 🔗</a>
-                    </div>
-                    """, unsafe_allow_html=True)
-            col_idx += 1
-
-# 다운로드 기능
-st.header("📊 Download Data")
+def create_trend_plot(trending_data, target_space_ranks, dates):
+    fig = go.Figure()
+    
+    for space_id, ranks in target_space_ranks.items():
+        fig.add_trace(go.Scatter(
+            x=dates,
+            y=ranks,
+            name=space_id,
+            mode='lines+markers'
+        ))
+    
+    fig.update_layout(
+        title='Trending Ranks Over Time',
+        xaxis_title='Date',
+        yaxis_title='Rank',
+        yaxis_autorange='reversed',
+        height=800
+    )
+    
+    return fig
 
-# DataFrame 생성
-df_data = []
-for date in dates:
-    spaces = trending_data.get(date, [])
-    for space_id in target_spaces.keys():
-        rank = get_space_rank(spaces, space_id)
+def create_space_info_html(trending_data):
+    latest_date = max(trending_data.keys())
+    latest_spaces = trending_data[latest_date]
+    
+    html_content = "<div style='padding: 20px;'>"
+    html_content += f"<h2>Latest Rankings ({latest_date})</h2>"
+    
+    for space_id, url in target_spaces.items():
+        rank = get_space_rank(latest_spaces, space_id)
         if rank:
-            space_info = next((s for s in spaces if s['id'] == space_id), None)
+            space_info = next((s for s in latest_spaces if s['id'] == space_id), None)
             if space_info:
-                df_data.append({
-                    'Date': date,
-                    'Space ID': space_id,
-                    'Rank': rank,
-                    'Likes': space_info.get('likes', 'N/A'),
-                    'Title': space_info.get('title', 'N/A'),
-                    'URL': target_spaces[space_id]
-                })
-
-df = pd.DataFrame(df_data)
+                html_content += f"""
+                <div style='margin: 20px 0; padding: 15px; border: 1px solid #ddd; border-radius: 8px;'>
+                    <h3>#{rank} - {space_id}</h3>
+                    <p>👍 Likes: {space_info.get('likes', 'N/A')}</p>
+                    <p>📝 {space_info.get('title', 'N/A')}</p>
+                    <p>{space_info.get('description', 'N/A')[:100]}...</p>
+                    <a href='{url}' target='_blank' style='color: blue;'>Visit Space 🔗</a>
+                </div>
+                """
+    
+    html_content += "</div>"
+    return html_content
+
+def export_data(trending_data, dates):
+    df_data = []
+    for date in dates:
+        spaces = trending_data.get(date, [])
+        for space_id in target_spaces.keys():
+            rank = get_space_rank(spaces, space_id)
+            if rank:
+                space_info = next((s for s in spaces if s['id'] == space_id), None)
+                if space_info:
+                    df_data.append({
+                        'Date': date,
+                        'Space ID': space_id,
+                        'Rank': rank,
+                        'Likes': space_info.get('likes', 'N/A'),
+                        'Title': space_info.get('title', 'N/A'),
+                        'URL': target_spaces[space_id]
+                    })
+    
+    df = pd.DataFrame(df_data)
+    return df
 
-# CSV 다운로드 버튼
-csv = df.to_csv(index=False)
-b64 = base64.b64encode(csv.encode()).decode()
-href = f'<a href="data:file/csv;base64,{b64}" download="trending_data.csv">Download CSV File</a>'
-st.markdown(href, unsafe_allow_html=True)
+def main_interface():
+    trending_data, target_space_ranks, dates = fetch_and_analyze_data()
+    
+    # 트렌드 플롯 생성
+    plot = create_trend_plot(trending_data, target_space_ranks, dates)
+    
+    # 스페이스 정보 HTML 생성
+    space_info = create_space_info_html(trending_data)
+    
+    # 데이터 익스포트
+    df = export_data(trending_data, dates)
+    
+    return plot, space_info, df
 
-# 푸터
-st.markdown("""
----
-Made with ❤️ using Streamlit and HuggingFace API
-""")
+# Gradio 인터페이스 생성
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 🤗 HuggingFace Spaces Trending Analysis")
+    
+    with gr.Tab("Trending Analysis"):
+        plot_output = gr.Plot()
+        info_output = gr.HTML()
+    
+    with gr.Tab("Export Data"):
+        df_output = gr.DataFrame()
+    
+    refresh_btn = gr.Button("Refresh Data")
+    refresh_btn.click(
+        main_interface,
+        outputs=[plot_output, info_output, df_output]
+    )
+    
+    # 초기 데이터 로드
+    plot, info, df = main_interface()
+    plot_output.update(value=plot)
+    info_output.update(value=info)
+    df_output.update(value=df)
+
+# Gradio 앱 실행
+demo.launch()