Update app.py

app.py

@@ -6,21 +6,13 @@ from typing import Optional, Union
 from huggingface_hub import InferenceClient
 from pathlib import Path
 
-# Initialize Hugging Face Inference Client with fal-ai provider
-client = InferenceClient(
-    provider="fal-ai",
-    api_key=os.environ.get("HF_TOKEN"),
-    bill_to="huggingface",
-)
+# ---------- Utilities ----------
 
 def cleanup_temp_files():
-    """Clean up old temporary video files to prevent storage overflow."""
     try:
         temp_dir = tempfile.gettempdir()
-        # Clean up old .mp4 files in temp directory
         for file_path in Path(temp_dir).glob("*.mp4"):
             try:
-                # Remove files older than 5 minutes
                 import time
                 if file_path.stat().st_mtime < (time.time() - 300):
                     file_path.unlink(missing_ok=True)
@@ -29,64 +21,59 @@ def cleanup_temp_files():
     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.")
+    return InferenceClient(
+        provider="fal-ai",
+        api_key=token,          # OAuth token from gr.LoginButton
+        bill_to="huggingface",  # keep if you need consolidated billing; otherwise remove
+    )
+
+# ---------- Inference wrappers (NO env fallback) ----------
+
 def generate_video(
     prompt: str,
+    token: gr.OAuthToken | None,
     duration: int = 8,
     size: str = "1280x720",
-    api_key: Optional[str] = None
 ) -> Optional[str]:
-    """Generate video using Sora-2 through Hugging Face Inference API with fal-ai provider."""
+    if token is None or not getattr(token, "token", None):
+        raise gr.Error("Sign in with Hugging Face to continue. This app uses your inference credits.")
+    if not prompt or not prompt.strip():
+        return None
+
     cleanup_temp_files()
     try:
-        if api_key:
-            temp_client = InferenceClient(
-                provider="fal-ai",
-                api_key=api_key,
-                bill_to="huggingface",
-            )
-        else:
-            temp_client = client
-            if not os.environ.get("HF_TOKEN") and not api_key:
-                return None
-        
-        video_bytes = temp_client.text_to_video(
+        client = _client_from_token(token.token)
+        video_bytes = client.text_to_video(
             prompt,
-            model="akhaliq/sora-2",
+            model="akhaliq/sora-2",  # served by fal-ai
+            # You can pass provider-specific kwargs here if supported
         )
-        
         temp_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
         try:
             temp_file.write(video_bytes)
             temp_file.flush()
-            video_path = temp_file.name
+            return temp_file.name
         finally:
             temp_file.close()
-        
-        return video_path
     except Exception as e:
-        return None
+        # Optional: surface a friendlier message
+        raise gr.Error("Generation failed. If this keeps happening, check your provider quota or try again.")
 
 def generate_video_from_image(
-    image: Union[str, bytes],
+    image: Union[str, bytes, None],
     prompt: str,
-    api_key: Optional[str] = None
+    token: gr.OAuthToken | None,
 ) -> Optional[str]:
-    """Generate a video from a single input image + prompt using Sora-2 image-to-video."""
-    cleanup_temp_files()
-    if not prompt or prompt.strip() == "":
+    if token is None or not getattr(token, "token", None):
+        raise gr.Error("Sign in with Hugging Face to continue. This app uses your inference credits.")
+    if not image or not prompt or not prompt.strip():
         return None
-    try:
-        if api_key:
-            temp_client = InferenceClient(
-                provider="fal-ai",
-                api_key=api_key,
-                bill_to="huggingface",
-            )
-        else:
-            temp_client = client
-            if not os.environ.get("HF_TOKEN") and not api_key:
-                return None
 
+    cleanup_temp_files()
+    try:
         if isinstance(image, str):
             with open(image, "rb") as f:
                 input_image = f.read()
@@ -95,53 +82,23 @@ def generate_video_from_image(
         else:
             return None
 
-        video_bytes = temp_client.image_to_video(
+        client = _client_from_token(token.token)
+        video_bytes = client.image_to_video(
             input_image,
             prompt=prompt,
             model="akhaliq/sora-2-image-to-video",
         )
-
         temp_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
         try:
             temp_file.write(video_bytes)
             temp_file.flush()
-            video_path = temp_file.name
+            return temp_file.name
         finally:
             temp_file.close()
-
-        return video_path
     except Exception as e:
-        return None
+        raise gr.Error("Generation failed. If this keeps happening, check your provider quota or try again.")
 
-def generate_with_auth(
-    prompt: str, 
-    profile: gr.OAuthProfile | None
-) -> Optional[str]:
-    """Wrapper function that checks if user is logged in before generating video."""
-    if profile is None:
-        raise gr.Error("Click Sign in with Hugging Face button to use this app for free")
-    
-    if not prompt or prompt.strip() == "":
-        return None
-    
-    return generate_video(
-        prompt, 
-        duration=8, 
-        size="1280x720", 
-        api_key=None
-    )
-
-def generate_with_auth_image(
-    prompt: str,
-    image_path: Optional[str],
-    profile: gr.OAuthProfile | None
-) -> Optional[str]:
-    """Checks login status then calls image->video generator."""
-    if profile is None:
-        raise gr.Error("Click Sign in with Hugging Face button to use this app for free")
-    if not image_path:
-        return None
-    return generate_video_from_image(image=image_path, prompt=prompt, api_key=None)
+# ---------- UI ----------
 
 def create_ui():
     css = '''
@@ -149,71 +106,64 @@ def create_ui():
     .dark .logo-dark{display: block !important}
     .dark .logo-light{display: none}
     #sub_title{margin-top: -20px !important}
-    .mobile-notice {
+    .notice {
         background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
         color: white;
-        padding: 15px;
-        border-radius: 10px;
-        margin: 20px auto;
-        max-width: 600px;
+        padding: 14px 16px;
+        border-radius: 12px;
+        margin: 18px auto 6px;
+        max-width: 820px;
         text-align: center;
-    }
-    .mobile-notice a {
-        color: #fff;
-        text-decoration: underline;
-        font-weight: bold;
+        font-size: 0.98rem;
     }
     '''
-    
-    with gr.Blocks(title="Sora-2", theme=gr.themes.Soft(), css=css) as demo:
+
+    with gr.Blocks(title="Sora-2 (paid via your provider credits)", theme=gr.themes.Soft(), css=css) as demo:
         gr.HTML("""
-            <div style="text-align: center; max-width: 800px; margin: 0 auto;">
-                <h1 style="font-size: 2.5em; margin-bottom: 0.5em;">
-                    🎬 Sora-2
-                </h1>
-                <p style="font-size: 1.1em; color: #666; margin-bottom: 20px;">Generate stunning videos using OpenAI's Sora-2 model</p>
-                <div class="mobile-notice">
-                    📱 On mobile? Use the optimized version: <a href="https://akhaliq-sora-2.hf.space" target="_blank">akhaliq-sora-2.hf.space</a>
+            <div style="text-align:center; max-width:860px; 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 app is <b>paid</b> and uses <b>your</b> inference provider credits when you run generations.
+                    Please sign in with your Hugging Face account to continue.
                 </div>
-                <p style='color: orange;'>⚠️ You must Sign in with Hugging Face using the button to use this app.</p>
-                <p style="font-size: 0.9em; color: #999; margin-top: 15px;">
-                    Built with <a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" style="color: #667eea;">anycoder</a>
+                <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>
         """)
-        
-        # Add login button - required for OAuth
-        gr.LoginButton()
-        
-        # Text -> Video
+
+        # Required login. Token is passed into all callbacks.
+        login_btn = gr.LoginButton("Sign in with Hugging Face")
+
         with gr.Row():
             with gr.Column(scale=1):
                 prompt_input = gr.Textbox(
                     label="Enter your prompt",
-                    placeholder="Describe the video you want to create...",
+                    placeholder="Describe the video you want to create…",
                     lines=4,
                     elem_id="prompt-text-input"
                 )
-                generate_btn = gr.Button("🎥 Generate Video", variant="primary", size="lg")
+                generate_btn = gr.Button("🎥 Generate Video", variant="primary")
             with gr.Column(scale=1):
                 video_output = gr.Video(
-                    label="Generated Video", 
-                    height=400, 
-                    interactive=False, 
+                    label="Generated Video",
+                    height=400,
+                    interactive=False,
                     show_download_button=True,
                     elem_id="text-to-video"
                 )
-        
+
+        # Note: we pass BOTH prompt and login_btn (token) to the function
         generate_btn.click(
-            fn=generate_with_auth,
-            inputs=[prompt_input],
+            fn=generate_video,
+            inputs=[prompt_input, login_btn],
             outputs=[video_output],
         )
 
-        # Image -> Video UI
         gr.HTML("""
-            <div style="text-align: center; margin: 40px 0 10px;">
-                <h3 style="margin-bottom: 8px;">🖼️ ➜ 🎬 Image → Video (beta)</h3>
+            <div style="text-align:center; margin: 34px 0 10px;">
+                <h3 style="margin-bottom:6px;">🖼️ ➜ 🎬 Image → Video (beta)</h3>
                 <p style="color:#666; margin:0;">Turn a single image into a short video with a guiding prompt.</p>
             </div>
         """)
@@ -229,32 +179,25 @@ def create_ui():
                 generate_img_btn = gr.Button("🎥 Generate from Image", variant="primary")
             with gr.Column(scale=1):
                 video_output_img = gr.Video(
-                    label="Generated Video (from Image)", 
-                    height=400, 
-                    interactive=False, 
+                    label="Generated Video (from Image)",
+                    height=400,
+                    interactive=False,
                     show_download_button=True,
                     elem_id="image-to-video"
                 )
 
         generate_img_btn.click(
-            fn=generate_with_auth_image,
-            inputs=[img_prompt_input, image_input],
+            fn=generate_video_from_image,
+            inputs=[image_input, img_prompt_input, login_btn],
             outputs=[video_output_img],
         )
-        
-        # Example usage guidance
+
+        # Keep examples UI-only to avoid auto-charging on click
         gr.Examples(
-            examples=[
-                ["A majestic golden eagle soaring through a vibrant sunset sky"],
-            ],
-            inputs=prompt_input,
-            outputs=video_output,
-            fn=generate_video,
-            cache_examples=False,
-            api_name=False,
-            show_api=False,
+            examples=[["A majestic golden eagle soaring through a vibrant sunset sky"]],
+            inputs=prompt_input
         )
-    
+
     return demo
 
 if __name__ == "__main__":
@@ -264,17 +207,7 @@ if __name__ == "__main__":
             shutil.rmtree("gradio_cached_examples", ignore_errors=True)
     except Exception as e:
         print(f"Initial cleanup error: {e}")
-    
+
     app = create_ui()
-    # Configure queue with optimized settings for OAuth-enabled app
-    app.queue(
-        status_update_rate="auto",
-        api_open=False,  # Disable public API access for security
-        default_concurrency_limit=None  # Allow multiple concurrent requests
-    )
-    app.launch(
-        show_api=False,
-        enable_monitoring=False,
-        quiet=True,
-        ssr_mode=True
-    )
+    app.queue(status_update_rate="auto", api_open=False, default_concurrency_limit=None)
+    app.launch(show_api=False, enable_monitoring=False, quiet=True, ssr_mode=True)