Update app.py

app.py

@@ -1,351 +1,29 @@
 import gradio as gr
-import os
-from huggingface_hub import InferenceClient
-import tempfile
-import shutil
-from pathlib import Path
 
-# Initialize the client
-client = InferenceClient(
-    provider="fal-ai",
-    api_key=os.environ.get("HF_TOKEN"),
-    bill_to="huggingface",
-)
-
-def text_to_video(prompt, duration=5, aspect_ratio="16:9", resolution="720p", profile: gr.OAuthProfile | None = None):
-    """Generate video from text prompt"""
-    try:
-        if profile is None:
-            return None, "❌ Click Sign in with Hugging Face button to use this app for free"
-        
-        if not prompt or prompt.strip() == "":
-            return None, "Please enter a text prompt"
-        
-        # Generate video from text
-        video = client.text_to_video(
-            prompt,
-            model="akhaliq/veo3.1-fast",
-        )
-        
-        # Save the video to a temporary file
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmp_file:
-            tmp_file.write(video)
-            video_path = tmp_file.name
-        
-        return video_path, f"✅ Video generated successfully from prompt: '{prompt[:50]}...'"
-    
-    except Exception as e:
-        return None, f"❌ Error generating video: {str(e)}"
-
-def image_to_video(image, prompt, duration=5, aspect_ratio="16:9", resolution="720p", profile: gr.OAuthProfile | None = None):
-    """Generate video from image and prompt"""
-    try:
-        if profile is None:
-            return None, "❌ Click Sign in with Hugging Face button to use this app for free"
-        
-        if image is None:
-            return None, "Please upload an image"
-        
-        if not prompt or prompt.strip() == "":
-            return None, "Please enter a prompt describing the motion"
-        
-        # Read the image file
-        if isinstance(image, str):
-            # If image is a file path
-            with open(image, "rb") as image_file:
-                input_image = image_file.read()
-        else:
-            # If image is already bytes or similar
-            import io
-            from PIL import Image as PILImage
-            
-            # Convert to bytes if necessary
-            if isinstance(image, PILImage.Image):
-                buffer = io.BytesIO()
-                image.save(buffer, format='PNG')
-                input_image = buffer.getvalue()
-            else:
-                # Assume it's a numpy array or similar
-                pil_image = PILImage.fromarray(image)
-                buffer = io.BytesIO()
-                pil_image.save(buffer, format='PNG')
-                input_image = buffer.getvalue()
-        
-        # Generate video from image
-        video = client.image_to_video(
-            input_image,
-            prompt=prompt,
-            model="akhaliq/veo3.1-fast-image-to-video",
-        )
-        
-        # Save the video to a temporary file
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as tmp_file:
-            tmp_file.write(video)
-            video_path = tmp_file.name
-        
-        return video_path, f"✅ Video generated successfully with motion: '{prompt[:50]}...'"
-    
-    except Exception as e:
-        return None, f"❌ Error generating video: {str(e)}"
-
-def clear_text_tab():
-    """Clear text-to-video tab"""
-    return "", None, ""
-
-def clear_image_tab():
-    """Clear image-to-video tab"""
-    return None, "", None, ""
-
-# Custom CSS for better styling
+# Custom CSS to hide everything except maintenance message
 custom_css = """
-.container {
-    max-width: 1200px;
-    margin: auto;
-}
-.header-link {
-    text-decoration: none;
-    color: #2196F3;
-    font-weight: bold;
-}
-.header-link:hover {
-    text-decoration: underline;
-}
-.status-box {
-    padding: 10px;
-    border-radius: 5px;
-    margin-top: 10px;
+.gradio-container > * {
+    display: none !important;
 }
-.auth-warning {
-    color: #ff6b00;
-    font-weight: bold;
+.maintenance-message {
+    display: block !important;
     text-align: center;
-    margin: 1em 0;
-    padding: 1em;
-    background-color: #fff3e0;
-    border-radius: 5px;
-}
-.mobile-link-container {
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-    padding: 1.5em;
-    border-radius: 10px;
-    text-align: center;
-    margin: 1em 0;
-    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
-}
-.mobile-link {
-    color: white !important;
-    font-size: 1.2em;
-    font-weight: bold;
-    text-decoration: none;
-    display: inline-block;
-    padding: 0.5em 1.5em;
-    background: rgba(255, 255, 255, 0.2);
-    border-radius: 25px;
-    transition: all 0.3s ease;
-}
-.mobile-link:hover {
-    background: rgba(255, 255, 255, 0.3);
-    transform: translateY(-2px);
-    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
-}
-.mobile-text {
-    color: white;
-    margin-bottom: 0.5em;
-    font-size: 1.1em;
+    padding: 50px 20px;
+    font-size: 1.5em;
 }
 """
 
 # Create the Gradio interface
-with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator") as demo:
+with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="Veo 3.1") as demo:
     gr.Markdown(
         """
-        # 🎬 AI Video Generator
-        ### Generate stunning videos from text or animate your images with AI
-        #### Powered by VEO 3.1 Fast Model | [Built with anycoder](https://huggingface.co/spaces/akhaliq/anycoder)
-        """
-    )
-    
-    # Add mobile link section
-    gr.HTML(
-        """
-        <div class="mobile-link-container">
-            <div class="mobile-text">📱 On mobile? Use the optimized version:</div>
-            <a href="https://akhaliq-veo3-1-fast.hf.space" target="_blank" class="mobile-link">
-                🚀 Open Mobile Version
-            </a>
-        </div>
-        """
-    )
-    
-    gr.HTML(
-        """
-        <div class="auth-warning">
-            ⚠️ You must Sign in with Hugging Face using the button below to use this app.
-        </div>
-        """
-    )
-    
-    # Add login button - required for OAuth
-    gr.LoginButton()
-    
-    with gr.Tabs() as tabs:
-        # Text-to-Video Tab
-        with gr.Tab("📝 Text to Video", id=0):
-            gr.Markdown("### Transform your text descriptions into dynamic videos")
-            
-            with gr.Row():
-                with gr.Column(scale=1):
-                    text_prompt = gr.Textbox(
-                        label="Text Prompt",
-                        placeholder="Describe the video you want to create... (e.g., 'A young man walking on the street during sunset')",
-                        lines=4,
-                        max_lines=6
-                    )
-                    
-                    with gr.Row():
-                        text_generate_btn = gr.Button("🎬 Generate Video", variant="primary", scale=2)
-                        text_clear_btn = gr.ClearButton(value="🗑️ Clear", scale=1)
-                    
-                    text_status = gr.Textbox(
-                        label="Status",
-                        interactive=False,
-                        visible=True,
-                        elem_classes=["status-box"]
-                    )
-                
-                with gr.Column(scale=1):
-                    text_video_output = gr.Video(
-                        label="Generated Video",
-                        autoplay=True,
-                        show_download_button=True,
-                        height=400
-                    )
-            
-            # Examples for text-to-video
-            gr.Examples(
-                examples=[
-                    ["A serene beach at sunset with gentle waves"],
-                    ["A bustling city street with neon lights at night"],
-                    ["A majestic eagle soaring through mountain peaks"],
-                    ["An astronaut floating in space near the International Space Station"],
-                    ["Cherry blossoms falling in slow motion in a Japanese garden"],
-                ],
-                inputs=text_prompt,
-                label="Example Prompts"
-            )
+        # 🚧 Under Maintenance
         
-        # Image-to-Video Tab
-        with gr.Tab("🖼️ Image to Video", id=1):
-            gr.Markdown("### Bring your static images to life with motion")
-            
-            with gr.Row():
-                with gr.Column(scale=1):
-                    image_input = gr.Image(
-                        label="Upload Image",
-                        type="pil",
-                        height=300
-                    )
-                    
-                    image_prompt = gr.Textbox(
-                        label="Motion Prompt",
-                        placeholder="Describe how the image should move... (e.g., 'The cat starts to dance')",
-                        lines=3,
-                        max_lines=5
-                    )
-                    
-                    with gr.Row():
-                        image_generate_btn = gr.Button("🎬 Animate Image", variant="primary", scale=2)
-                        image_clear_btn = gr.ClearButton(value="🗑️ Clear", scale=1)
-                    
-                    image_status = gr.Textbox(
-                        label="Status",
-                        interactive=False,
-                        visible=True,
-                        elem_classes=["status-box"]
-                    )
-                
-                with gr.Column(scale=1):
-                    image_video_output = gr.Video(
-                        label="Generated Video",
-                        autoplay=True,
-                        show_download_button=True,
-                        height=400
-                    )
-            
-            # Examples for image-to-video
-            gr.Examples(
-                examples=[
-                    [None, "The person starts walking forward"],
-                    [None, "The animal begins to run"],
-                    [None, "Camera slowly zooms in while the subject smiles"],
-                    [None, "The flowers sway gently in the breeze"],
-                    [None, "The clouds move across the sky in time-lapse"],
-                ],
-                inputs=[image_input, image_prompt],
-                label="Example Motion Prompts"
-            )
-    
-    # How to Use section
-    with gr.Accordion("📖 How to Use", open=False):
-        gr.Markdown(
-            """
-            ### Text to Video:
-            1. Enter a detailed description of the video you want to create
-            2. Optionally adjust advanced settings (duration, aspect ratio, resolution)
-            3. Click "Generate Video" and wait for the AI to create your video
-            4. Download or preview your generated video
-            
-            ### Image to Video:
-            1. Upload an image you want to animate
-            2. Describe the motion or action you want to add to the image
-            3. Optionally adjust advanced settings
-            4. Click "Animate Image" to bring your image to life
-            5. Download or preview your animated video
-            
-            ### Tips for Better Results:
-            - Be specific and descriptive in your prompts
-            - For image-to-video, describe natural motions that fit the image
-            - Use high-quality input images for better results
-            - Experiment with different prompts to get the desired effect
-            
-            ### Mobile Users:
-            - For the best mobile experience, use the optimized version at: https://akhaliq-veo3-1-fast.hf.space
-            """
-        )
-    
-    # Event handlers
-    text_generate_btn.click(
-        fn=text_to_video,
-        inputs=[text_prompt],
-        outputs=[text_video_output, text_status],
-        show_progress="full",
-        queue=False,
-        api_name=False,
-        show_api=False
-    )
-    
-    text_clear_btn.click(
-        fn=clear_text_tab,
-        inputs=[],
-        outputs=[text_prompt, text_video_output, text_status],
-        queue=False
-    )
-    
-    image_generate_btn.click(
-        fn=image_to_video,
-        inputs=[image_input, image_prompt],
-        outputs=[image_video_output, image_status],
-        show_progress="full",
-        queue=False,
-        api_name=False,
-        show_api=False
-    )
-    
-    image_clear_btn.click(
-        fn=clear_image_tab,
-        inputs=[],
-        outputs=[image_input, image_prompt, image_video_output, image_status],
-        queue=False
+        This application is currently under maintenance. Please check back later.
+        
+        We apologize for any inconvenience.
+        """,
+        elem_classes=["maintenance-message"]
     )
 
 # Launch the app