Update app.py

app.py

@@ -2,280 +2,193 @@ import gradio as gr
 import os
 from huggingface_hub import InferenceClient
 import tempfile
-import shutil
 from pathlib import Path
+from PIL import Image as PILImage
+import io
 
-# Initialize the client
+# Initialize the Hugging Face Inference client
 client = InferenceClient(
     provider="fal-ai",
-    api_key=os.environ.get("HF_TOKEN"),
+    api_key=os.environ.get("HF_TOKEN"),  # Your HF token must be set in the environment
     bill_to="huggingface",
 )
 
-def text_to_video(prompt, duration=5, aspect_ratio="16:9", resolution="720p", profile: gr.OAuthProfile | None = None):
+# --- Core Functions ---
+def text_to_video(prompt, duration=5, aspect_ratio="16:9", resolution="720p"):
     """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"
-        
+            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):
+
+def image_to_video(image, prompt, duration=5, aspect_ratio="16:9", resolution="720p"):
     """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"
-        
+            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()
+            return None, "⚠️ Please enter a motion description."
+
+        # Convert image to bytes
+        if isinstance(image, PILImage.Image):
+            buffer = io.BytesIO()
+            image.save(buffer, format="PNG")
+            input_image = buffer.getvalue()
         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()
-        
+            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 ---
 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
+# --- Gradio App ---
 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)
+        # 🎬 AI Video Generator  
+        ### Generate stunning videos from text or animate your images with AI  
+        #### Powered by VEO 3.1 Fast Model
         """
     )
-    
-    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):
+        with gr.Tab("📝 Text to Video"):
             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')",
+                        placeholder="Describe the video you want to create...",
                         lines=4,
                         max_lines=6
                     )
-                    
+
                     with gr.Accordion("Advanced Settings", open=False):
-                        text_duration = gr.Slider(
-                            minimum=1,
-                            maximum=10,
-                            value=5,
-                            step=1,
-                            label="Duration (seconds)",
-                            info="Video duration in seconds"
-                        )
+                        text_duration = gr.Slider(1, 10, value=5, step=1, label="Duration (seconds)")
                         text_aspect_ratio = gr.Dropdown(
-                            choices=["16:9", "9:16", "1:1", "4:3", "21:9"],
-                            value="16:9",
-                            label="Aspect Ratio",
-                            info="Video aspect ratio"
+                            ["16:9", "9:16", "1:1", "4:3", "21:9"], value="16:9", label="Aspect Ratio"
                         )
                         text_resolution = gr.Dropdown(
-                            choices=["480p", "720p", "1080p"],
-                            value="720p",
-                            label="Resolution",
-                            info="Video resolution"
+                            ["480p", "720p", "1080p"], value="720p", label="Resolution"
                         )
-                    
+
                     with gr.Row():
-                        text_generate_btn = gr.Button("🎬 Generate Video", variant="primary", scale=2)
-                        text_clear_btn = gr.ClearButton(value="🗑️ Clear", scale=1)
-                    
+                        text_generate_btn = gr.Button("🎬 Generate Video", variant="primary")
+                        text_clear_btn = gr.ClearButton(value="🗑️ Clear")
+
                     text_status = gr.Textbox(
-                        label="Status",
-                        interactive=False,
-                        visible=True,
-                        elem_classes=["status-box"]
+                        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
+                        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"],
+                    ["An astronaut floating in space near the ISS"],
+                    ["Cherry blossoms falling in a Japanese garden"],
                 ],
                 inputs=text_prompt,
-                label="Example Prompts"
+                label="Example Prompts",
             )
-        
+
         # Image-to-Video Tab
-        with gr.Tab("🖼️ Image to Video", id=1):
+        with gr.Tab("🖼️ Image to Video"):
             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_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')",
+                        placeholder="Describe how the image should move...",
                         lines=3,
                         max_lines=5
                     )
-                    
+
                     with gr.Accordion("Advanced Settings", open=False):
-                        image_duration = gr.Slider(
-                            minimum=1,
-                            maximum=10,
-                            value=5,
-                            step=1,
-                            label="Duration (seconds)",
-                            info="Video duration in seconds"
-                        )
+                        image_duration = gr.Slider(1, 10, value=5, step=1, label="Duration (seconds)")
                         image_aspect_ratio = gr.Dropdown(
-                            choices=["16:9", "9:16", "1:1", "4:3", "21:9"],
-                            value="16:9",
-                            label="Aspect Ratio",
-                            info="Video aspect ratio"
+                            ["16:9", "9:16", "1:1", "4:3", "21:9"], value="16:9", label="Aspect Ratio"
                         )
                         image_resolution = gr.Dropdown(
-                            choices=["480p", "720p", "1080p"],
-                            value="720p",
-                            label="Resolution",
-                            info="Video resolution"
+                            ["480p", "720p", "1080p"], value="720p", label="Resolution"
                         )
-                    
+
                     with gr.Row():
-                        image_generate_btn = gr.Button("🎬 Animate Image", variant="primary", scale=2)
-                        image_clear_btn = gr.ClearButton(value="🗑️ Clear", scale=1)
-                    
+                        image_generate_btn = gr.Button("🎬 Animate Image", variant="primary")
+                        image_clear_btn = gr.ClearButton(value="🗑️ Clear")
+
                     image_status = gr.Textbox(
-                        label="Status",
-                        interactive=False,
-                        visible=True,
-                        elem_classes=["status-box"]
+                        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
+                        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"],
@@ -285,75 +198,34 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator
                     [None, "The clouds move across the sky in time-lapse"],
                 ],
                 inputs=[image_input, image_prompt],
-                label="Example Motion Prompts"
+                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
-            """
-        )
-    
-    # Event handlers
+
+    # --- Event handlers ---
     text_generate_btn.click(
         fn=text_to_video,
         inputs=[text_prompt, text_duration, text_aspect_ratio, text_resolution],
         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, image_duration, image_aspect_ratio, image_resolution],
         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
 if __name__ == "__main__":
-    demo.launch(
-        show_api=False,
-        share=False,
-        show_error=True,
-        enable_monitoring=False,
-        quiet=True
-    )
+    demo.launch(show_api=False, share=False, quiet=True)