Update app.py

app.py

@@ -2,7 +2,6 @@ import gradio as gr
 import os
 from huggingface_hub import InferenceClient
 import tempfile
-import shutil
 from pathlib import Path
 
 # Initialize the client
@@ -12,305 +11,156 @@ client = InferenceClient(
     bill_to="huggingface",
 )
 
-def text_to_video(prompt, duration=5, aspect_ratio="16:9", resolution="720p", profile: gr.OAuthProfile | None = None):
+def text_to_video(prompt, aspect_ratio="16:9", 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
+
+        # Generate video from text with aspect ratio parameter
         video = client.text_to_video(
             prompt,
             model="akhaliq/veo3.1-fast",
+            aspect_ratio=aspect_ratio,
         )
-        
-        # Save the video to a temporary file
+
+        # Save the video
         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):
+
+def image_to_video(image, prompt, aspect_ratio="16:9", 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()
+
+        import io
+        from PIL import Image as PILImage
+
+        # Convert image to bytes
+        buffer = io.BytesIO()
+        if isinstance(image, PILImage.Image):
+            image.save(buffer, format='PNG')
         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
+            PILImage.fromarray(image).save(buffer, format='PNG')
+        input_image = buffer.getvalue()
+
+        # Generate video from image with aspect ratio parameter
         video = client.image_to_video(
             input_image,
             prompt=prompt,
             model="akhaliq/veo3.1-fast-image-to-video",
+            aspect_ratio=aspect_ratio,
         )
-        
-        # Save the video to a temporary file
+
+        # Save the video
         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
 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;
 }
-.auth-warning {
-    color: #ff6b00;
-    font-weight: bold;
-    text-align: center;
-    margin: 1em 0;
-    padding: 1em;
-    background-color: #fff3e0;
-    border-radius: 5px;
-}
 """
 
-# Create the Gradio interface
+# Interface
 with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator") 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)
-        """
-    )
-    
-    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.Markdown("# 🎬 AI Video Generator\n### Generate videos from text or animate images with AI")
+
     gr.LoginButton()
-    
+
     with gr.Tabs() as tabs:
-        # Text-to-Video Tab
+        # --- TEXT TO VIDEO TAB ---
         with gr.Tab("📝 Text to Video", id=0):
-            gr.Markdown("### Transform your text descriptions into dynamic videos")
-            
+            text_prompt = gr.Textbox(
+                label="Text Prompt",
+                placeholder="Describe the video you want to create...",
+                lines=4
+            )
+            text_aspect = gr.Radio(
+                choices=["16:9", "9:16"],
+                value="16:9",
+                label="Aspect Ratio"
+            )
+
             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"
+                text_generate_btn = gr.Button("🎬 Generate Video", variant="primary")
+                text_clear_btn = gr.ClearButton(value="🗑️ Clear")
+
+            text_status = gr.Textbox(label="Status", interactive=False)
+            text_video_output = gr.Video(label="Generated Video", autoplay=True, show_download_button=True)
+
+            text_generate_btn.click(
+                fn=text_to_video,
+                inputs=[text_prompt, text_aspect],
+                outputs=[text_video_output, text_status],
+                show_progress="full"
+            )
+
+            text_clear_btn.click(
+                fn=lambda: ("", None, ""),
+                outputs=[text_prompt, text_video_output, text_status]
             )
-        
-        # Image-to-Video Tab
+
+        # --- IMAGE TO VIDEO TAB ---
         with gr.Tab("🖼️ Image to Video", id=1):
-            gr.Markdown("### Bring your static images to life with motion")
-            
+            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...")
+            image_aspect = gr.Radio(
+                choices=["16:9", "9:16"],
+                value="16:9",
+                label="Aspect Ratio"
+            )
+
             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"
+                image_generate_btn = gr.Button("🎬 Animate Image", variant="primary")
+                image_clear_btn = gr.ClearButton(value="🗑️ Clear")
+
+            image_status = gr.Textbox(label="Status", interactive=False)
+            image_video_output = gr.Video(label="Generated Video", autoplay=True, show_download_button=True)
+
+            image_generate_btn.click(
+                fn=image_to_video,
+                inputs=[image_input, image_prompt, image_aspect],
+                outputs=[image_video_output, image_status],
+                show_progress="full"
             )
-    
-    # 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
-            """
-        )
-    
-    # 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
-    )
-
-# Launch the app
+
+            image_clear_btn.click(
+                fn=lambda: (None, "", None, ""),
+                outputs=[image_input, image_prompt, image_video_output, image_status]
+            )
+
+# Launch
 if __name__ == "__main__":
-    demo.launch(
-        show_api=False,
-        share=False,
-        show_error=True,
-        enable_monitoring=False,
-        quiet=True,
-        ssr_mode=True
-    )
+    demo.launch(share=False, show_api=False, show_error=True, quiet=True)