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import gradio as gr |
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import requests |
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import pandas as pd |
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import matplotlib.pyplot as plt |
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import seaborn as sns |
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from datetime import datetime, timedelta |
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import plotly.graph_objects as go |
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import numpy as np |
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import json |
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target_spaces = { |
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"ginipick/FLUXllama": "https://huggingface.co/spaces/ginipick/FLUXllama", |
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"ginipick/SORA-3D": "https://huggingface.co/spaces/ginipick/SORA-3D", |
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"fantaxy/Sound-AI-SFX": "https://huggingface.co/spaces/fantaxy/Sound-AI-SFX", |
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"fantos/flx8lora": "https://huggingface.co/spaces/fantos/flx8lora", |
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"ginigen/Canvas": "https://huggingface.co/spaces/ginigen/Canvas", |
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"fantaxy/erotica": "https://huggingface.co/spaces/fantaxy/erotica", |
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"ginipick/time-machine": "https://huggingface.co/spaces/ginipick/time-machine", |
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"aiqcamp/FLUX-VisionReply": "https://huggingface.co/spaces/aiqcamp/FLUX-VisionReply", |
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"openfree/Tetris-Game": "https://huggingface.co/spaces/openfree/Tetris-Game", |
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"openfree/everychat": "https://huggingface.co/spaces/openfree/everychat", |
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"VIDraft/mouse1": "https://huggingface.co/spaces/VIDraft/mouse1", |
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"kolaslab/alpha-go": "https://huggingface.co/spaces/kolaslab/alpha-go", |
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"ginipick/text3d": "https://huggingface.co/spaces/ginipick/text3d", |
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"openfree/trending-board": "https://huggingface.co/spaces/openfree/trending-board", |
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"cutechicken/tankwar": "https://huggingface.co/spaces/cutechicken/tankwar", |
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"openfree/game-jewel": "https://huggingface.co/spaces/openfree/game-jewel", |
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"VIDraft/mouse-chat": "https://huggingface.co/spaces/VIDraft/mouse-chat", |
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"ginipick/AccDiffusion": "https://huggingface.co/spaces/ginipick/AccDiffusion", |
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"aiqtech/Particle-Accelerator-Simulation": "https://huggingface.co/spaces/aiqtech/Particle-Accelerator-Simulation", |
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"openfree/GiniGEN": "https://huggingface.co/spaces/openfree/GiniGEN", |
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"kolaslab/3DAudio-Spectrum-Analyzer": "https://huggingface.co/spaces/kolaslab/3DAudio-Spectrum-Analyzer", |
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"openfree/trending-news-24": "https://huggingface.co/spaces/openfree/trending-news-24", |
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"ginipick/Realtime-FLUX": "https://huggingface.co/spaces/ginipick/Realtime-FLUX", |
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"VIDraft/prime-number": "https://huggingface.co/spaces/VIDraft/prime-number", |
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"kolaslab/zombie-game": "https://huggingface.co/spaces/kolaslab/zombie-game", |
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"fantos/miro-game": "https://huggingface.co/spaces/fantos/miro-game", |
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"kolaslab/shooting": "https://huggingface.co/spaces/kolaslab/shooting", |
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"VIDraft/Mouse-Hackathon": "https://huggingface.co/spaces/VIDraft/Mouse-Hackathon", |
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"upstage/open-ko-llm-leaderboard": "https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard", |
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"LGAI-EXAONE/EXAONE-3.5-Instruct-Demo": "https://huggingface.co/spaces/LGAI-EXAONE/EXAONE-3.5-Instruct-Demo", |
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"NCSOFT/VARCO_Arena": "https://huggingface.co/spaces/NCSOFT/VARCO_Arena" |
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} |
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def get_trending_spaces(date): |
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url = f"https://huggingface.co/api/spaces/trending?date={date}&limit=300" |
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response = requests.get(url) |
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if response.status_code == 200: |
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return response.json() |
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return None |
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def get_space_rank(spaces, space_id): |
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for idx, space in enumerate(spaces, 1): |
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if space.get('id', '') == space_id: |
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return idx |
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return None |
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def fetch_and_analyze_data(): |
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start_date = datetime(2023, 12, 1) |
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end_date = datetime(2023, 12, 31) |
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dates = [(start_date + timedelta(days=x)).strftime('%Y-%m-%d') |
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for x in range((end_date - start_date).days + 1)] |
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trending_data = {} |
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target_space_ranks = {space: [] for space in target_spaces.keys()} |
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for date in dates: |
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spaces = get_trending_spaces(date) |
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if spaces: |
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trending_data[date] = spaces |
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for space_id in target_spaces.keys(): |
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rank = get_space_rank(spaces, space_id) |
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target_space_ranks[space_id].append(rank) |
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return trending_data, target_space_ranks, dates |
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def create_trend_plot(trending_data, target_space_ranks, dates): |
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fig = go.Figure() |
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for space_id, ranks in target_space_ranks.items(): |
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fig.add_trace(go.Scatter( |
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x=dates, |
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y=ranks, |
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name=space_id, |
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mode='lines+markers' |
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)) |
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fig.update_layout( |
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title='Trending Ranks Over Time', |
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xaxis_title='Date', |
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yaxis_title='Rank', |
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yaxis_autorange='reversed', |
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height=800 |
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) |
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return fig |
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def create_space_info_html(trending_data): |
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latest_date = max(trending_data.keys()) |
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latest_spaces = trending_data[latest_date] |
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html_content = "<div style='padding: 20px;'>" |
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html_content += f"<h2>Latest Rankings ({latest_date})</h2>" |
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for space_id, url in target_spaces.items(): |
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rank = get_space_rank(latest_spaces, space_id) |
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if rank: |
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space_info = next((s for s in latest_spaces if s['id'] == space_id), None) |
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if space_info: |
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html_content += f""" |
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<div style='margin: 20px 0; padding: 15px; border: 1px solid #ddd; border-radius: 8px;'> |
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<h3>#{rank} - {space_id}</h3> |
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<p>π Likes: {space_info.get('likes', 'N/A')}</p> |
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<p>π {space_info.get('title', 'N/A')}</p> |
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<p>{space_info.get('description', 'N/A')[:100]}...</p> |
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<a href='{url}' target='_blank' style='color: blue;'>Visit Space π</a> |
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</div> |
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""" |
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html_content += "</div>" |
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return html_content |
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def export_data(trending_data, dates): |
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df_data = [] |
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for date in dates: |
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spaces = trending_data.get(date, []) |
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for space_id in target_spaces.keys(): |
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rank = get_space_rank(spaces, space_id) |
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if rank: |
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space_info = next((s for s in spaces if s['id'] == space_id), None) |
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if space_info: |
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df_data.append({ |
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'Date': date, |
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'Space ID': space_id, |
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'Rank': rank, |
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'Likes': space_info.get('likes', 'N/A'), |
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'Title': space_info.get('title', 'N/A'), |
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'URL': target_spaces[space_id] |
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}) |
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df = pd.DataFrame(df_data) |
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return df |
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def main_interface(): |
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trending_data, target_space_ranks, dates = fetch_and_analyze_data() |
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plot = create_trend_plot(trending_data, target_space_ranks, dates) |
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space_info = create_space_info_html(trending_data) |
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df = export_data(trending_data, dates) |
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return plot, space_info, df |
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with gr.Blocks(theme=gr.themes.Soft()) as demo: |
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gr.Markdown("# π€ HuggingFace Spaces Trending Analysis") |
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with gr.Tab("Trending Analysis"): |
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plot_output = gr.Plot() |
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info_output = gr.HTML() |
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with gr.Tab("Export Data"): |
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df_output = gr.DataFrame() |
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refresh_btn = gr.Button("Refresh Data") |
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refresh_btn.click( |
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main_interface, |
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outputs=[plot_output, info_output, df_output] |
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) |
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plot, info, df = main_interface() |
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plot_output.update(value=plot) |
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info_output.update(value=info) |
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df_output.update(value=df) |
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demo.launch() |
