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Running
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 plotly.graph_objects as go | |
import numpy as np | |
import json | |
# κ΄μ¬ μ€νμ΄μ€ URL 리μ€νΈμ μ 보 | |
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", | |
"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" | |
} | |
def get_trending_spaces(date): | |
url = f"https://huggingface.co/api/spaces/trending?date={date}&limit=300" | |
response = requests.get(url) | |
if response.status_code == 200: | |
return response.json() | |
return None | |
def get_space_rank(spaces, space_id): | |
for idx, space in enumerate(spaces, 1): | |
if space.get('id', '') == space_id: | |
return idx | |
return None | |
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') | |
for x in range((end_date - start_date).days + 1)] | |
trending_data = {} | |
target_space_ranks = {space: [] for space in target_spaces.keys()} | |
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 | |
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 | |
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 latest_spaces if s['id'] == space_id), None) | |
if space_info: | |
html_content += f""" | |
<div style='margin: 20px 0; padding: 15px; border: 1px solid #ddd; border-radius: 8px;'> | |
<h3>#{rank} - {space_id}</h3> | |
<p>π Likes: {space_info.get('likes', 'N/A')}</p> | |
<p>π {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 π</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 | |
def main_interface(): | |
trending_data, target_space_ranks, dates = fetch_and_analyze_data() | |
# νΈλ λ νλ‘― μμ± | |
plot = create_trend_plot(trending_data, target_space_ranks, dates) | |
# μ€νμ΄μ€ μ 보 HTML μμ± | |
space_info = create_space_info_html(trending_data) | |
# λ°μ΄ν° μ΅μ€ν¬νΈ | |
df = export_data(trending_data, dates) | |
return plot, space_info, df | |
# Gradio μΈν°νμ΄μ€ μμ± | |
with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
gr.Markdown("# π€ 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] | |
) | |
# μ΄κΈ° λ°μ΄ν° λ‘λ | |
plot, info, df = main_interface() | |
plot_output.update(value=plot) | |
info_output.update(value=info) | |
df_output.update(value=df) | |
# Gradio μ± μ€ν | |
demo.launch() |