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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 plotly.graph_objects as go |
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from datetime import datetime |
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import os |
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HF_TOKEN = os.getenv("HF_TOKEN") |
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target_models = { |
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"openfree/flux-lora-korea-palace": "https://huggingface.co/openfree/flux-lora-korea-palace", |
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"seawolf2357/hanbok": "https://huggingface.co/seawolf2357/hanbok", |
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"LGAI-EXAONE/EXAONE-3.5-32B-Instruct": "https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-32B-Instruct", |
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"LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct": "https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct", |
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"LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct": "https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct", |
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"ginipick/flux-lora-eric-cat": "https://huggingface.co/ginipick/flux-lora-eric-cat", |
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"seawolf2357/flux-lora-car-rolls-royce": "https://huggingface.co/seawolf2357/flux-lora-car-rolls-royce" |
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} |
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def get_models_data(progress=gr.Progress()): |
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"""λͺ¨λΈ λ°μ΄ν° κ°μ Έμ€κΈ°""" |
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url = "https://huggingface.co/api/models/sort/trending" |
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params = { |
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'limit': 1000, |
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'full': 'true' |
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} |
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try: |
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progress(0, desc="Fetching models data...") |
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response = requests.get(url, params=params) |
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response.raise_for_status() |
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all_models = response.json() |
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model_ranks = {model['id']: idx + 1 for idx, model in enumerate(all_models)} |
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models = [] |
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for model in all_models: |
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if model.get('id', '') in target_models: |
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model['rank'] = model_ranks.get(model['id'], 'N/A') |
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models.append(model) |
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models.sort(key=lambda x: x['rank']) |
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progress(0.3, desc="Creating visualization...") |
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fig = go.Figure() |
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ids = [model['id'] for model in models] |
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ranks = [model['rank'] for model in models] |
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likes = [model.get('likes', 0) for model in models] |
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y_values = [1001 - r for r in ranks] |
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fig.add_trace(go.Bar( |
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x=ids, |
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y=y_values, |
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text=[f"Rank: {r}<br>Likes: {l}" for r, l in zip(ranks, likes)], |
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textposition='auto', |
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marker_color='rgb(158,202,225)', |
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opacity=0.8 |
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)) |
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fig.update_layout( |
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title={ |
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'text': 'Hugging Face Models Trending Rankings', |
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'y':0.95, |
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'x':0.5, |
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'xanchor': 'center', |
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'yanchor': 'top' |
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}, |
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xaxis_title='Model ID', |
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yaxis_title='Rank', |
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yaxis=dict( |
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ticktext=[str(i) for i in range(1, 1001, 50)], |
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tickvals=[1001 - i for i in range(1, 1001, 50)], |
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range=[0, 1000] |
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), |
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height=800, |
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showlegend=False, |
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template='plotly_white', |
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xaxis_tickangle=-45 |
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) |
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progress(0.6, desc="Creating model cards...") |
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html_content = """ |
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<div style='padding: 20px; background: #f5f5f5;'> |
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<h2 style='color: #2c3e50;'>Models Trending Rankings</h2> |
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<div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'> |
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""" |
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for model in models: |
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model_id = model.get('id', '') |
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rank = model.get('rank', 'N/A') |
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likes = model.get('likes', 0) |
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downloads = model.get('downloads', 0) |
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html_content += f""" |
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<div style=' |
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background: white; |
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padding: 20px; |
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border-radius: 10px; |
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box-shadow: 0 2px 4px rgba(0,0,0,0.1); |
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transition: transform 0.2s; |
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'> |
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<h3 style='color: #34495e;'>Rank #{rank} - {model_id}</h3> |
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<p style='color: #7f8c8d;'>π Likes: {likes}</p> |
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<p style='color: #7f8c8d;'>β¬οΈ Downloads: {downloads}</p> |
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<a href='{target_models[model_id]}' |
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target='_blank' |
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style=' |
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display: inline-block; |
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padding: 8px 16px; |
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background: #3498db; |
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color: white; |
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text-decoration: none; |
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border-radius: 5px; |
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transition: background 0.3s; |
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'> |
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Visit Model π |
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</a> |
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</div> |
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""" |
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html_content += "</div></div>" |
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df = pd.DataFrame([{ |
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'Rank': model.get('rank', 'N/A'), |
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'Model ID': model.get('id', ''), |
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'Likes': model.get('likes', 'N/A'), |
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'Downloads': model.get('downloads', 'N/A'), |
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'URL': target_models[model.get('id', '')] |
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} for model in models]) |
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progress(1.0, desc="Complete!") |
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return fig, html_content, df |
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except Exception as e: |
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error_html = f'<div style="color: red; padding: 20px;">Error: {str(e)}</div>' |
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error_plot = create_error_plot() |
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return error_plot, error_html, pd.DataFrame() |
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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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|
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def get_spaces_data(sort_type="trending", progress=gr.Progress()): |
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"""μ€νμ΄μ€ λ°μ΄ν° κ°μ Έμ€κΈ° (trending λλ modes)""" |
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url = f"https://huggingface.co/api/spaces" |
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params = { |
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'full': 'true', |
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'limit': 300 |
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} |
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if sort_type == "modes": |
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params['sort'] = 'likes' |
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try: |
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progress(0, desc=f"Fetching {sort_type} spaces data...") |
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response = requests.get(url, params=params) |
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response.raise_for_status() |
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all_spaces = response.json() |
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space_ranks = {space['id']: idx + 1 for idx, space in enumerate(all_spaces)} |
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spaces = [] |
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for space in all_spaces: |
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if space.get('id', '') in target_spaces: |
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space['rank'] = space_ranks.get(space['id'], 'N/A') |
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spaces.append(space) |
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spaces.sort(key=lambda x: x['rank']) |
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progress(0.3, desc="Creating visualization...") |
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fig = go.Figure() |
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ids = [space['id'] for space in spaces] |
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ranks = [space['rank'] for space in spaces] |
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likes = [space.get('likes', 0) for space in spaces] |
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y_values = [301 - r for r in ranks] |
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fig.add_trace(go.Bar( |
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x=ids, |
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y=y_values, |
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text=[f"Rank: {r}<br>Likes: {l}" for r, l in zip(ranks, likes)], |
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textposition='auto', |
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marker_color='rgb(158,202,225)', |
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opacity=0.8 |
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)) |
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fig.update_layout( |
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title={ |
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'text': f'Hugging Face Spaces {sort_type.title()} Rankings (Top 300)', |
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'y':0.95, |
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'x':0.5, |
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'xanchor': 'center', |
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'yanchor': 'top' |
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}, |
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xaxis_title='Space ID', |
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yaxis_title='Rank', |
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yaxis=dict( |
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ticktext=[str(i) for i in range(1, 301, 20)], |
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tickvals=[301 - i for i in range(1, 301, 20)], |
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range=[0, 300] |
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), |
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height=800, |
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showlegend=False, |
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template='plotly_white', |
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xaxis_tickangle=-45 |
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) |
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progress(0.6, desc="Creating space cards...") |
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html_content = f""" |
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<div style='padding: 20px; background: #f5f5f5;'> |
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<h2 style='color: #2c3e50;'>{sort_type.title()} Rankings</h2> |
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<div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'> |
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""" |
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for space in spaces: |
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space_id = space.get('id', '') |
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rank = space.get('rank', 'N/A') |
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likes = space.get('likes', 0) |
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title = space.get('title', 'No Title') |
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description = space.get('description', 'No Description')[:100] |
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|
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html_content += f""" |
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<div style=' |
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background: white; |
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padding: 20px; |
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border-radius: 10px; |
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box-shadow: 0 2px 4px rgba(0,0,0,0.1); |
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transition: transform 0.2s; |
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'> |
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<h3 style='color: #34495e;'>Rank #{rank} - {space_id}</h3> |
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<p style='color: #7f8c8d;'>π Likes: {likes}</p> |
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<p style='color: #2c3e50;'>{title}</p> |
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<p style='color: #7f8c8d; font-size: 0.9em;'>{description}...</p> |
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<a href='{target_spaces[space_id]}' |
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target='_blank' |
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style=' |
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display: inline-block; |
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padding: 8px 16px; |
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background: #3498db; |
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color: white; |
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text-decoration: none; |
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border-radius: 5px; |
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transition: background 0.3s; |
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'> |
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Visit Space π |
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</a> |
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</div> |
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""" |
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html_content += "</div></div>" |
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|
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df = pd.DataFrame([{ |
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'Rank': space.get('rank', 'N/A'), |
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'Space ID': space.get('id', ''), |
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'Likes': space.get('likes', 'N/A'), |
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'Title': space.get('title', 'N/A'), |
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'URL': target_spaces[space.get('id', '')] |
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} for space in spaces]) |
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progress(1.0, desc="Complete!") |
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return fig, html_content, df |
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except Exception as e: |
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error_html = f'<div style="color: red; padding: 20px;">Error: {str(e)}</div>' |
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error_plot = create_error_plot() |
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return error_plot, error_html, pd.DataFrame() |
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def create_trend_visualization(spaces_data): |
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if not spaces_data: |
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return create_error_plot() |
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fig = go.Figure() |
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ranks = [] |
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for idx, space in enumerate(spaces_data, 1): |
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space_id = space.get('id', '') |
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if space_id in target_spaces: |
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ranks.append({ |
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'id': space_id, |
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'rank': idx, |
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'likes': space.get('likes', 0), |
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'title': space.get('title', 'N/A'), |
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'views': space.get('views', 0) |
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}) |
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|
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if not ranks: |
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return create_error_plot() |
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|
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ranks.sort(key=lambda x: x['rank']) |
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|
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ids = [r['id'] for r in ranks] |
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rank_values = [r['rank'] for r in ranks] |
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likes = [r['likes'] for r in ranks] |
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views = [r['views'] for r in ranks] |
|
|
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|
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fig.add_trace(go.Bar( |
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x=ids, |
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y=rank_values, |
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text=[f"Rank: {r}<br>Likes: {l}<br>Views: {v}" for r, l, v in zip(rank_values, likes, views)], |
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textposition='auto', |
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marker_color='rgb(158,202,225)', |
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opacity=0.8 |
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)) |
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|
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fig.update_layout( |
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title={ |
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'text': 'Current Trending Ranks (All Target Spaces)', |
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'y':0.95, |
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'x':0.5, |
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'xanchor': 'center', |
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'yanchor': 'top' |
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}, |
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xaxis_title='Space ID', |
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yaxis_title='Trending Rank', |
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yaxis_autorange='reversed', |
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height=800, |
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showlegend=False, |
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template='plotly_white', |
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xaxis_tickangle=-45 |
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) |
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return fig |
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|
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def get_trending_spaces_without_token(): |
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try: |
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url = "https://huggingface.co/api/spaces" |
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params = { |
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'sort': 'likes', |
|
'direction': -1, |
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'limit': 1000, |
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'full': 'true' |
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} |
|
|
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response = requests.get(url, params=params) |
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|
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if response.status_code == 200: |
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return response.json() |
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else: |
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print(f"API μμ² μ€ν¨ (ν ν° μμ): {response.status_code}") |
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print(f"Response: {response.text}") |
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return None |
|
except Exception as e: |
|
print(f"API νΈμΆ μ€ μλ¬ λ°μ (ν ν° μμ): {str(e)}") |
|
return None |
|
|
|
|
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if not HF_TOKEN: |
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get_trending_spaces = get_trending_spaces_without_token |
|
|
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|
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def create_error_plot(): |
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fig = go.Figure() |
|
fig.add_annotation( |
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text="λ°μ΄ν°λ₯Ό λΆλ¬μ¬ μ μμ΅λλ€.\n(API μΈμ¦μ΄ νμν©λλ€)", |
|
xref="paper", |
|
yref="paper", |
|
x=0.5, |
|
y=0.5, |
|
showarrow=False, |
|
font=dict(size=20) |
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) |
|
fig.update_layout( |
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title="Error Loading Data", |
|
height=400 |
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) |
|
return fig |
|
|
|
|
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def create_space_info_html(spaces_data): |
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if not spaces_data: |
|
return "<div style='padding: 20px;'><h2>λ°μ΄ν°λ₯Ό λΆλ¬μ€λλ° μ€ν¨νμ΅λλ€.</h2></div>" |
|
|
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html_content = """ |
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<div style='padding: 20px;'> |
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<h2 style='color: #2c3e50;'>Current Trending Rankings</h2> |
|
<div style='display: grid; grid-template-columns: repeat(auto-fill, minmax(300px, 1fr)); gap: 20px;'> |
|
""" |
|
|
|
|
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for space_id in target_spaces.keys(): |
|
space_info = next((s for s in spaces_data if s.get('id') == space_id), None) |
|
if space_info: |
|
rank = next((idx for idx, s in enumerate(spaces_data, 1) if s.get('id') == space_id), 'N/A') |
|
html_content += f""" |
|
<div style=' |
|
background: white; |
|
padding: 20px; |
|
border-radius: 10px; |
|
box-shadow: 0 2px 4px rgba(0,0,0,0.1); |
|
transition: transform 0.2s; |
|
'> |
|
<h3 style='color: #34495e;'>#{rank} - {space_id}</h3> |
|
<p style='color: #7f8c8d;'>π Likes: {space_info.get('likes', 'N/A')}</p> |
|
<p style='color: #7f8c8d;'>π Views: {space_info.get('views', 'N/A')}</p> |
|
<p style='color: #2c3e50;'>{space_info.get('title', 'N/A')}</p> |
|
<p style='color: #7f8c8d; font-size: 0.9em;'>{space_info.get('description', 'N/A')[:100]}...</p> |
|
<a href='{target_spaces[space_id]}' |
|
target='_blank' |
|
style=' |
|
display: inline-block; |
|
padding: 8px 16px; |
|
background: #3498db; |
|
color: white; |
|
text-decoration: none; |
|
border-radius: 5px; |
|
transition: background 0.3s; |
|
'> |
|
Visit Space π |
|
</a> |
|
</div> |
|
""" |
|
else: |
|
html_content += f""" |
|
<div style=' |
|
background: #f8f9fa; |
|
padding: 20px; |
|
border-radius: 10px; |
|
box-shadow: 0 2px 4px rgba(0,0,0,0.1); |
|
'> |
|
<h3 style='color: #34495e;'>{space_id}</h3> |
|
<p style='color: #7f8c8d;'>Not in trending</p> |
|
<a href='{target_spaces[space_id]}' |
|
target='_blank' |
|
style=' |
|
display: inline-block; |
|
padding: 8px 16px; |
|
background: #95a5a6; |
|
color: white; |
|
text-decoration: none; |
|
border-radius: 5px; |
|
'> |
|
Visit Space π |
|
</a> |
|
</div> |
|
""" |
|
|
|
html_content += "</div></div>" |
|
return html_content |
|
|
|
def create_data_table(spaces_data): |
|
if not spaces_data: |
|
return pd.DataFrame() |
|
|
|
rows = [] |
|
for idx, space in enumerate(spaces_data, 1): |
|
space_id = space.get('id', '') |
|
if space_id in target_spaces: |
|
rows.append({ |
|
'Rank': idx, |
|
'Space ID': space_id, |
|
'Likes': space.get('likes', 'N/A'), |
|
'Title': space.get('title', 'N/A'), |
|
'URL': target_spaces[space_id] |
|
}) |
|
|
|
return pd.DataFrame(rows) |
|
|
|
def refresh_data(): |
|
spaces_data = get_trending_spaces() |
|
if spaces_data: |
|
plot = create_trend_visualization(spaces_data) |
|
info = create_space_info_html(spaces_data) |
|
df = create_data_table(spaces_data) |
|
return plot, info, df |
|
else: |
|
return create_error_plot(), "<div>API μΈμ¦μ΄ νμν©λλ€.</div>", pd.DataFrame() |
|
|
|
|
|
with gr.Blocks(theme=gr.themes.Soft()) as demo: |
|
gr.Markdown(""" |
|
# π€ HuggingFace Rankings Analysis |
|
μ€μκ°μΌλ‘ Hugging Faceμ Spacesμ Models μμλ₯Ό λΆμν©λλ€. |
|
""") |
|
|
|
with gr.Tab("Spaces Trending"): |
|
trending_plot = gr.Plot() |
|
trending_info = gr.HTML() |
|
trending_df = gr.DataFrame() |
|
|
|
with gr.Tab("Models Trending"): |
|
models_plot = gr.Plot() |
|
models_info = gr.HTML() |
|
models_df = gr.DataFrame() |
|
|
|
refresh_btn = gr.Button("π Refresh Data", variant="primary") |
|
|
|
def refresh_all_data(): |
|
trending_results = get_spaces_data("trending") |
|
models_results = get_models_data() |
|
return [*trending_results, *models_results] |
|
|
|
refresh_btn.click( |
|
refresh_all_data, |
|
outputs=[ |
|
trending_plot, trending_info, trending_df, |
|
models_plot, models_info, models_df |
|
] |
|
) |
|
|
|
|
|
trending_results = get_spaces_data("trending") |
|
models_results = get_models_data() |
|
|
|
trending_plot.value, trending_info.value, trending_df.value = trending_results |
|
models_plot.value, models_info.value, models_df.value = models_results |
|
|
|
|
|
demo.launch( |
|
server_name="0.0.0.0", |
|
server_port=7860, |
|
share=False |
|
) |