Create app.py

app.py

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+# GRADIO HF SPACE
+import gradio as gr
+import requests
+import pandas as pd
+from datetime import datetime, timedelta
+import urllib.parse
+
+def get_hf_models_by_category():
+    """
+    Fetch top 3 models from each Hugging Face category ranked by likes7d
+    """
+    # Hugging Face API endpoint
+    api_url = "https://huggingface.co/api/models"
+    
+    # Common model categories on Hugging Face
+    categories = [
+        "text-generation",
+        "text-classification", 
+        "token-classification",
+        "question-answering",
+        "fill-mask",
+        "summarization",
+        "translation",
+        "text2text-generation",
+        "image-classification",
+        "object-detection",
+        "image-segmentation",
+        "text-to-image",
+        "image-to-text",
+        "automatic-speech-recognition",
+        "audio-classification",
+        "text-to-speech",
+        "audio-to-audio",
+        "voice-activity-detection",
+        "depth-estimation",
+        "image-feature-extraction",
+        "other"
+    ]
+    
+    results = {}
+    
+    for category in categories:
+        try:
+            # Fetch models for this category, sorted by likes in the last 7 days
+            params = {
+                "pipeline_tag": category,
+                "sort": "likes7d",
+                "direction": -1,
+                "limit": 3,
+                "full": True  # Get full model info including downloads
+            }
+            
+            response = requests.get(api_url, params=params, timeout=10)
+            
+            if response.status_code == 200:
+                models = response.json()
+                category_models = []
+                
+                for model in models:
+                    # Try different field names for model ID
+                    model_id = model.get("id") or model.get("modelId") or model.get("_id", "Unknown")
+                    
+                    # Get likes (might be in different fields)
+                    likes = (model.get("likes") or 
+                            model.get("likesRecent") or 
+                            model.get("likes7d") or 0)
+                    
+                    # Get downloads (different possible field names)
+                    downloads = (model.get("downloads") or 
+                               model.get("downloadsAllTime") or 
+                               model.get("downloads_all_time") or 
+                               model.get("downloads_last_month", 0))
+                    
+                    # Get last modified date
+                    last_modified = (model.get("lastModified") or 
+                                   model.get("last_modified") or 
+                                   model.get("createdAt") or 
+                                   model.get("updatedAt") or "Unknown")
+                    
+                    model_info = {
+                        "name": model_id,
+                        "likes": likes,
+                        "downloads": downloads,
+                        "updated": last_modified,
+                        "url": f"https://huggingface.co/{model_id}"
+                    }
+                    category_models.append(model_info)
+                
+                if category_models:  # Only add if we found models
+                    results[category] = category_models
+                    
+        except Exception as e:
+            print(f"Error fetching {category}: {str(e)}")
+            continue
+    
+    return results
+
+def format_number(num):
+    """Format large numbers in a readable way"""
+    if num >= 1000000:
+        return f"{num/1000000:.1f}M"
+    elif num >= 1000:
+        return f"{num/1000:.1f}k"
+    else:
+        return str(num)
+
+def format_date(date_str):
+    """Format date string to be more readable"""
+    if date_str == "Unknown" or not date_str:
+        return "Unknown"
+    try:
+        # Parse the ISO date string and format it
+        if "T" in date_str:
+            date_obj = datetime.fromisoformat(date_str.replace("Z", "+00:00"))
+            return date_obj.strftime("%Y-%m-%d")
+        else:
+            return date_str[:10]  # Just take the date part
+    except:
+        return "Unknown"
+
+def format_model_display(models_data):
+    """
+    Format the models data into a nice display format
+    """
+    if not models_data:
+        return "No models found or API unavailable."
+    
+    html_content = """
+    <div style="font-family: Arial, sans-serif; max-width: 1200px; margin: 0 auto;">
+        <h1 style="text-align: center; color: #ff6b6b; margin-bottom: 30px;">
+            🤗 Top 3 Hugging Face Models by Category (Last 7 Days)
+        </h1>
+    """
+    
+    for category, models in models_data.items():
+        if not models:
+            continue
+            
+        # Format category name
+        category_display = category.replace("-", " ").title()
+        
+        html_content += f"""
+        <div style="margin-bottom: 40px; border: 2px solid #f0f0f0; border-radius: 10px; padding: 20px; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white;">
+            <h2 style="margin-top: 0; text-align: center; font-size: 24px; text-shadow: 2px 2px 4px rgba(0,0,0,0.3);">
+                🏆 {category_display}
+            </h2>
+            <div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(380px, 1fr)); gap: 20px; margin-top: 20px;">
+        """
+        
+        for i, model in enumerate(models[:3], 1):
+            medal = "🥇" if i == 1 else "🥈" if i == 2 else "🥉"
+            
+            # Format the numbers and date
+            likes_formatted = format_number(model['likes'])
+            downloads_formatted = format_number(model['downloads'])
+            date_formatted = format_date(model['updated'])
+            author = model['name'].split("/")[0]
+            model_name = model['name'].split("/")[-1]
+            model_normal_name = model_name.replace("-", " ").title()
+            # Create YouTube search URL
+            youtube_search_query = urllib.parse.quote(f"{model_normal_name} {author} AI")
+            youtube_url = f"https://www.youtube.com/results?search_query={youtube_search_query}"
+            
+            html_content += f"""
+                <div style="background: rgba(255,255,255,0.95); color: #333; padding: 20px; border-radius: 8px; box-shadow: 0 4px 6px rgba(0,0,0,0.1); display: flex; flex-direction: column; height: 100%;">
+                    <div style="display: flex; align-items: center; margin-bottom: 15px;">
+                        <span style="font-size: 24px; margin-right: 10px;">{medal}</span>
+                        <h3 style="margin: 0; font-size: 16px; color: #2d3748;">#{i}</h3>
+                    </div>
+                    
+                    <h4 style="margin: 0 0 15px 0; font-size: 18px; color: #2b6cb0; word-break: break-word; line-height: 1.3; flex-grow: 1;">
+                        <a href="{model['url']}" target="_blank" style="text-decoration: none; color: #2b6cb0;">
+                            {model['name']}
+                        </a>
+                    </h4>
+                    
+                    <div style="display: grid; grid-template-columns: 1fr 1fr 1fr; gap: 8px; margin-bottom: 15px;">
+                        <div style="text-align: center; padding: 8px; background: #f7fafc; border-radius: 6px;">
+                            <div style="font-size: 16px; margin-bottom: 2px;">❤️</div>
+                            <div style="font-size: 12px; color: #4a5568; font-weight: bold;">Likes</div>
+                            <div style="background: #e53e3e; color: white; padding: 2px 6px; border-radius: 12px; font-size: 11px; margin-top: 4px; display: inline-block;">
+                                {likes_formatted}
+                            </div>
+                        </div>
+                        
+                        <div style="text-align: center; padding: 8px; background: #f7fafc; border-radius: 6px;">
+                            <div style="font-size: 16px; margin-bottom: 2px;">📥</div>
+                            <div style="font-size: 12px; color: #4a5568; font-weight: bold;">Downloads</div>
+                            <div style="background: #38a169; color: white; padding: 2px 6px; border-radius: 12px; font-size: 11px; margin-top: 4px; display: inline-block;">
+                                {downloads_formatted}
+                            </div>
+                        </div>
+                        
+                        <div style="text-align: center; padding: 8px; background: #f7fafc; border-radius: 6px;">
+                            <div style="font-size: 16px; margin-bottom: 2px;">🕒</div>
+                            <div style="font-size: 12px; color: #4a5568; font-weight: bold;">Updated</div>
+                            <div style="background: #3182ce; color: white; padding: 2px 6px; border-radius: 12px; font-size: 11px; margin-top: 4px; display: inline-block;">
+                                {date_formatted}
+                            </div>
+                        </div>
+                    </div>
+                    
+                    <div style="display: flex; gap: 8px; margin-top: auto;">
+                        <a href="{model['url']}" target="_blank" style="flex: 1; text-align: center; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 8px 12px; border-radius: 6px; text-decoration: none; font-size: 12px; font-weight: bold; transition: all 0.2s;">
+                            🤗 View Model
+                        </a>
+                        <a href="{youtube_url}" target="_blank" style="flex: 1; text-align: center; background: linear-gradient(135deg, #ff0000 0%, #cc0000 100%); color: white; padding: 8px 12px; border-radius: 6px; text-decoration: none; font-size: 12px; font-weight: bold; transition: all 0.2s;">
+                            📺 Find on YouTube
+                        </a>
+                    </div>
+                </div>
+            """
+        
+        html_content += """
+            </div>
+        </div>
+        """
+    
+    html_content += f"""
+        <div style="text-align: center; margin-top: 30px; padding: 20px; background-color: #f8f9fa; border-radius: 10px;">
+            <p style="color: #6c757d; font-style: italic; margin-bottom: 10px;">
+                📊 Data fetched from Hugging Face API • Updated: {datetime.now().strftime("%Y-%m-%d %H:%M:%S")} UTC
+            </p>
+            <p style="color: #6c757d; font-size: 12px; margin: 0;">
+                Rankings based on likes received in the last 7 days • Found {len(models_data)} categories with active models
+            </p>
+        </div>
+    </div>
+    """
+    
+    return html_content
+
+def refresh_models():
+    """
+    Refresh and get the latest model data
+    """
+    models_data = get_hf_models_by_category()
+    formatted_display = format_model_display(models_data)
+    return formatted_display
+
+# Create Gradio interface
+def create_interface():
+    with gr.Blocks(
+        title="🤗 Top HF Models by Category",
+        theme=gr.themes.Soft(),
+        css="""
+        .gradio-container {
+            max-width: 1400px !important;
+        }
+        .gr-button {
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
+            border: none !important;
+            color: white !important;
+        }
+        """
+    ) as demo:
+        
+        gr.Markdown("""
+        # 🤗 Hugging Face Model Explorer
+        
+        Discover the most popular models across different categories on Hugging Face! 
+        This space shows the **top 3 models** in each category ranked by **likes received in the last 7 days**.
+        
+        Click the refresh button to get the latest rankings!
+        """)
+        
+        with gr.Row():
+            refresh_btn = gr.Button(
+                "🔄 Refresh Rankings", 
+                variant="primary", 
+                size="lg"
+            )
+        
+        with gr.Row():
+            gr.Markdown("""
+            **🎯 What you'll see:**
+            - ❤️ **Likes**: Community appreciation in the last 7 days
+            - 📥 **Downloads**: Total download count (all-time)  
+            - 🕒 **Updated**: Last modification date
+            - 🤗 **View Model**: Direct link to model page
+            - 📺 **Find on YouTube**: Search for tutorials and demos
+            """)
+        
+        output_html = gr.HTML(
+            value=refresh_models(),  # Load initial data
+            label="Top Models by Category"
+        )
+        
+        refresh_btn.click(
+            fn=refresh_models,
+            outputs=output_html
+        )
+        
+        gr.Markdown("""
+        ---
+        ### ℹ️ About This Space
+        
+        - **Data Source**: Hugging Face Models API (`/api/models`)
+        - **Ranking Metric**: Likes received in the last 7 days (`sort=likes7d`)
+        - **Categories**: All major model types (text, image, audio, multimodal, etc.)
+        - **Update Frequency**: Real-time (when you click refresh)
+        
+        **Note**: Only categories with available models are displayed. Some specialized categories might not appear if no models are currently trending.
+        
+        🚀 **Pro tip**: Use the YouTube button to find tutorials, demos, and implementation guides for each model!
+        """)
+    
+    return demo
+
+# Launch the application
+if __name__ == "__main__":
+    demo = create_interface()
+    demo.launch(
+        server_name="0.0.0.0",  # For Hugging Face Spaces
+        server_port=7860,       # Standard port for HF Spaces
+        share=False,
+        debug=False
+    )