app.py

import gradio as gr
import logging
import tempfile
import os

# Set up logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

def create_interface():
    """Create the Gradio interface"""
    
    def generate_video_interface(prompt, model_id, num_frames, fps, num_inference_steps, guidance_scale, seed):
        """Interface function for video generation"""
        if not prompt.strip():
            return None, "Please enter a video description"
        
        # For demo purposes, return a message instead of actual video generation
        # This will work on Hugging Face Spaces without NumPy issues
        return None, f"Demo mode: Would generate video for '{prompt}' using {model_id} with {num_frames} frames at {fps} FPS"
    
    # Custom CSS for better styling
    custom_css = """
    .gradio-container {
        max-width: 1200px !important;
        margin: 0 auto !important;
    }
    .generate-btn {
        background: linear-gradient(45deg, #667eea 0%, #764ba2 100%) !important;
        border: none !important;
        color: white !important;
        font-weight: bold !important;
    }
    .status-box {
        background-color: #f8f9fa !important;
        border: 1px solid #dee2e6 !important;
    }
    """
    
    # Available models for demo
    models = {
        "damo-vilab/text-to-video-ms-1.7b": {
            "name": "DAMO Text-to-Video MS-1.7B",
            "description": "Fast and efficient text-to-video model",
            "max_frames": 16,
            "fps": 8,
            "quality": "Good",
            "speed": "Fast"
        },
        "cerspense/zeroscope_v2_XL": {
            "name": "Zeroscope v2 XL",
            "description": "High-quality text-to-video model",
            "max_frames": 24,
            "fps": 6,
            "quality": "Excellent",
            "speed": "Medium"
        }
    }
    
    # Create interface
    with gr.Blocks(title="AI Video Creator Pro", theme=gr.themes.Soft(), css=custom_css) as interface:
        
        # Professional Header
        with gr.Group():
            gr.Markdown("""
            # 🎬 AI Video Creator Pro
            ### Transform Your Ideas Into Stunning Videos with AI-Powered Generation
            """)
        
        with gr.Row():
            with gr.Column(scale=2):
                # Main Input Section
                with gr.Group():
                    gr.Markdown("## 🎯 Video Generation")
                    
                    prompt = gr.Textbox(
                        label="📝 Video Description",
                        placeholder="Describe the video you want to create... (e.g., 'A majestic dragon soaring through a mystical forest with glowing mushrooms')",
                        lines=3,
                        max_lines=5,
                        container=True
                    )
                    
                    model_id = gr.Dropdown(
                        choices=list(models.keys()),
                        value=list(models.keys())[0],
                        label="🤖 AI Model",
                        info="Choose the AI model for video generation",
                        container=True
                    )
                    
                    with gr.Row():
                        num_frames = gr.Slider(
                            minimum=8,
                            maximum=32,
                            value=16,
                            step=1,
                            label="🎞️ Video Length (Frames)",
                            info="More frames = longer video"
                        )
                        
                        fps = gr.Slider(
                            minimum=4,
                            maximum=12,
                            value=8,
                            step=1,
                            label="⚡ FPS",
                            info="Frames per second"
                        )
                    
                    with gr.Row():
                        num_inference_steps = gr.Slider(
                            minimum=10,
                            maximum=50,
                            value=25,
                            step=1,
                            label="🎨 Quality Steps",
                            info="More steps = better quality but slower"
                        )
                        
                        guidance_scale = gr.Slider(
                            minimum=1.0,
                            maximum=20.0,
                            value=7.5,
                            step=0.5,
                            label="🎯 Guidance Scale",
                            info="Higher values = more prompt adherence"
                        )
                    
                    seed = gr.Number(
                        label="🎲 Seed (Optional)",
                        value=None,
                        info="Set for reproducible results",
                        container=True
                    )
                
                # Generate Button
                generate_btn = gr.Button("🚀 Generate Professional Video", variant="primary", size="lg")
                
                # Output Section
                with gr.Group():
                    gr.Markdown("## 📺 Generated Video")
                    status_text = gr.Textbox(label="📊 Status", interactive=False)
                    video_output = gr.Video(label="🎬 Your Video")
            
            with gr.Column(scale=1):
                # Model Information
                with gr.Group():
                    gr.Markdown("## 🤖 AI Model Details")
                    model_info = gr.JSON(label="Current Model Specifications")
                
                # Examples
                with gr.Group():
                    gr.Markdown("## 💡 Inspiration Examples")
                    gr.Markdown("""
                    **Try these example prompts:**
                    
                    • A beautiful sunset over the ocean with waves crashing on the shore
                    • A cat playing with a ball of yarn in a cozy living room
                    • A futuristic city with flying cars and neon lights
                    • A butterfly emerging from a cocoon in a garden
                    • A rocket launching into space with fire and smoke
                    • A majestic dragon soaring through a mystical forest with glowing mushrooms
                    """)
                
                # Features
                with gr.Group():
                    gr.Markdown("## ✨ Features")
                    gr.Markdown("""
                    🎬 **Multiple AI Models**
                    - State-of-the-art video generation
                    - Quality vs speed options
                    
                    🎨 **Advanced Controls**
                    - Quality settings
                    - Reproducible results
                    
                    ⚡ **Fast Processing**
                    - GPU acceleration
                    - Optimized pipelines
                    """)
        
        # Event handlers
        generate_btn.click(
            fn=generate_video_interface,
            inputs=[prompt, model_id, num_frames, fps, num_inference_steps, guidance_scale, seed],
            outputs=[video_output, status_text]
        )
        
        # Update model info when model changes
        def update_model_info(model_id):
            info = models.get(model_id, {"error": "Model not found"})
            if not isinstance(info, dict):
                info = {"error": "Invalid model info"}
            return info
        
        model_id.change(
            fn=update_model_info,
            inputs=model_id,
            outputs=model_info
        )
        
        # Load initial model info
        interface.load(lambda: models[list(models.keys())[0]], outputs=model_info)
    
    return interface

# Create and launch the interface
interface = create_interface()
interface.launch(
    server_name="0.0.0.0",
    server_port=7860,
    share=True,
    show_error=True
)