Update app.py

app.py

@@ -4,84 +4,44 @@ from huggingface_hub import InferenceClient
 import tempfile
 import shutil
 from pathlib import Path
-from typing import Optional, Union
-import time
 
-# -------------------------
-# Utilities
-# -------------------------
+# Initialize the client
+client = InferenceClient(
+    provider="fal-ai",
+    api_key=os.environ.get("HF_TOKEN"),
+    bill_to="huggingface",
+)
 
-def cleanup_temp_files():
-    try:
-        temp_dir = tempfile.gettempdir()
-        for file_path in Path(temp_dir).glob("*.mp4"):
-            try:
-                if file_path.stat().st_mtime < (time.time() - 300):
-                    file_path.unlink(missing_ok=True)
-            except Exception:
-                pass
-    except Exception as e:
-        print(f"Cleanup error: {e}")
-
-def _client_from_token(token: Optional[str]) -> InferenceClient:
-    if not token:
-        raise gr.Error("Please sign in first. This app requires your Hugging Face login.")
-    # IMPORTANT: do not set bill_to when using user OAuth tokens
-    return InferenceClient(
-        provider="fal-ai",
-        api_key=token,
-    )
-
-def _save_bytes_as_temp_mp4(data: bytes) -> str:
-    temp_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
-    try:
-        temp_file.write(data)
-        temp_file.flush()
-        return temp_file.name
-    finally:
-        temp_file.close()
-
-def text_to_video(prompt, token: gr.OAuthToken | None, duration=5, aspect_ratio="16:9", resolution="720p", *_):
+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 token is None or not getattr(token, "token", None):
-            return None, "❌ Sign in with Hugging Face to continue. This app uses your inference provider credits."
+        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"
         
-        cleanup_temp_files()
-        
-        # Create client with user's token
-        client = _client_from_token(token.token)
-        
         # Generate video from text
-        try:
-            video = client.text_to_video(
-                prompt,
-                model="akhaliq/veo3.1-fast",
-            )
-        except Exception as e:
-            import requests
-            if isinstance(e, requests.HTTPError) and getattr(e.response, "status_code", None) == 403:
-                return None, "❌ Access denied by provider (403). Make sure your HF account has credits/permission for provider 'fal-ai' and model 'akhaliq/veo3.1-fast'."
-            raise
+        video = client.text_to_video(
+            prompt,
+            model="akhaliq/veo3.1-fast",
+        )
         
         # Save the video to a temporary file
-        video_path = _save_bytes_as_temp_mp4(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 gr.Error as e:
-        return None, f"❌ {str(e)}"
     except Exception as e:
-        return None, f"❌ Generation failed. If this keeps happening, check your provider quota or try again later."
+        return None, f"❌ Error generating video: {str(e)}"
 
-def image_to_video(image, prompt, token: gr.OAuthToken | None, duration=5, aspect_ratio="16:9", resolution="720p", *_):
+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 token is None or not getattr(token, "token", None):
-            return None, "❌ Sign in with Hugging Face to continue. This app uses your inference provider credits."
+        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"
@@ -89,8 +49,6 @@ def image_to_video(image, prompt, token: gr.OAuthToken | None, duration=5, aspec
         if not prompt or prompt.strip() == "":
             return None, "Please enter a prompt describing the motion"
         
-        cleanup_temp_files()
-        
         # Read the image file
         if isinstance(image, str):
             # If image is a file path
@@ -113,31 +71,22 @@ def image_to_video(image, prompt, token: gr.OAuthToken | None, duration=5, aspec
                 pil_image.save(buffer, format='PNG')
                 input_image = buffer.getvalue()
         
-        # Create client with user's token
-        client = _client_from_token(token.token)
-        
         # Generate video from image
-        try:
-            video = client.image_to_video(
-                input_image,
-                prompt=prompt,
-                model="akhaliq/veo3.1-fast-image-to-video",
-            )
-        except Exception as e:
-            import requests
-            if isinstance(e, requests.HTTPError) and getattr(e.response, "status_code", None) == 403:
-                return None, "❌ Access denied by provider (403). Make sure your HF account has credits/permission for provider 'fal-ai' and model 'akhaliq/veo3.1-fast-image-to-video'."
-            raise
+        video = client.image_to_video(
+            input_image,
+            prompt=prompt,
+            model="akhaliq/veo3.1-fast-image-to-video",
+        )
         
         # Save the video to a temporary file
-        video_path = _save_bytes_as_temp_mp4(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 gr.Error as e:
-        return None, f"❌ {str(e)}"
     except Exception as e:
-        return None, f"❌ Generation failed. If this keeps happening, check your provider quota or try again later."
+        return None, f"❌ Error generating video: {str(e)}"
 
 def clear_text_tab():
     """Clear text-to-video tab"""
@@ -166,15 +115,14 @@ custom_css = """
     border-radius: 5px;
     margin-top: 10px;
 }
-.notice {
-    background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-    color: white;
-    padding: 14px 16px;
-    border-radius: 12px;
-    margin: 18px auto 6px;
-    max-width: 860px;
+.auth-warning {
+    color: #ff6b00;
+    font-weight: bold;
     text-align: center;
-    font-size: 0.98rem;
+    margin: 1em 0;
+    padding: 1em;
+    background-color: #fff3e0;
+    border-radius: 5px;
 }
 .mobile-link-container {
     background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
@@ -208,31 +156,12 @@ custom_css = """
 """
 
 # Create the Gradio interface
-with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator (Paid)") as demo:
+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 via Hugging Face Inference API (provider: fal-ai)
-        """
-    )
-    
-    gr.HTML(
-        """
-        <div style="text-align:center; max-width:900px; margin:0 auto;">
-            <h1 style="font-size:2.2em; margin-bottom:6px;">🎬 Sora-2</h1>
-            <p style="color:#777; margin:0 0 8px;">Generate videos via the Hugging Face Inference API (provider: fal-ai)</p>
-            <div class="notice">
-                <b>Heads up:</b> This is a paid app that uses <b>your</b> inference provider credits when you run generations.
-                Free users get <b>$0.10 in included credits</b>. <b>PRO users</b> get <b>$2 in included credits</b> 
-                and can continue using beyond that (with billing). 
-                <a href='http://huggingface.co/subscribe/pro?source=veo3' target='_blank' style='color:#fff; text-decoration:underline; font-weight:bold;'>Subscribe to PRO</a> 
-                for more credits. Please sign in with your Hugging Face account to continue.
-            </div>
-            <p style="font-size: 0.9em; color: #999; margin-top: 10px;">
-                Built with <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="color:#fff; text-decoration:underline;">anycoder</a>
-            </p>
-        </div>
+        #### Powered by VEO 3.1 Fast Model | [Built with anycoder](https://huggingface.co/spaces/akhaliq/anycoder)
         """
     )
     
@@ -250,14 +179,14 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator
     
     gr.HTML(
         """
-        <p style="text-align: center; font-size: 0.9em; color: #999; margin-top: 10px;">
-            Built with <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="color:#667eea; text-decoration:underline;">anycoder</a>
-        </p>
+        <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
-    login_btn = gr.LoginButton("Sign in with Hugging Face")
+    gr.LoginButton()
     
     with gr.Tabs() as tabs:
         # Text-to-Video Tab
@@ -387,7 +316,7 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator
     # Event handlers
     text_generate_btn.click(
         fn=text_to_video,
-        inputs=[text_prompt, login_btn],
+        inputs=[text_prompt],
         outputs=[text_video_output, text_status],
         show_progress="full",
         queue=False,
@@ -404,7 +333,7 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator
     
     image_generate_btn.click(
         fn=image_to_video,
-        inputs=[image_input, image_prompt, login_btn],
+        inputs=[image_input, image_prompt],
         outputs=[image_video_output, image_status],
         show_progress="full",
         queue=False,
@@ -421,14 +350,6 @@ with gr.Blocks(css=custom_css, theme=gr.themes.Soft(), title="AI Video Generator
 
 # Launch the app
 if __name__ == "__main__":
-    try:
-        cleanup_temp_files()
-        if os.path.exists("gradio_cached_examples"):
-            shutil.rmtree("gradio_cached_examples", ignore_errors=True)
-    except Exception as e:
-        print(f"Initial cleanup error: {e}")
-    
-    demo.queue(status_update_rate="auto", api_open=False, default_concurrency_limit=None)
     demo.launch(
         show_api=False,
         share=False,