Update app.py
Browse files
app.py
CHANGED
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@@ -23,7 +23,7 @@ def verify_pro_status(token: Optional[Union[gr.OAuthToken, str]]) -> bool:
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elif isinstance(token, str):
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token_str = token
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else:
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return False
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try:
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user_info = whoami(token=token_str)
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@@ -52,12 +52,12 @@ def cleanup_temp_files():
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def generate_video(
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prompt: str,
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duration: int = 8,
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size: str = "1280x720",
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api_key: Optional[str] = None
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) -> Tuple[Optional[str], str]:
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"""
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-
Generate video using Sora-2
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Returns tuple of (video_path, status_message).
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"""
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# Clean up old files before generating new ones
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@@ -74,15 +74,16 @@ def generate_video(
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else:
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temp_client = client
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if not os.environ.get("HF_TOKEN") and not api_key:
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return None, "β Please set HF_TOKEN environment variable
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# Call Sora-2 through Hugging Face Inference API
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video_bytes = temp_client.text_to_video(
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prompt,
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model="akhaliq/sora-2",
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)
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# Save to temporary file with proper cleanup
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temp_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
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try:
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temp_file.write(video_bytes)
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@@ -98,65 +99,12 @@ def generate_video(
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error_msg = f"β Error generating video: {str(e)}"
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return None, error_msg
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def generate_image_to_video(
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image_path: str,
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prompt: str,
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api_key: Optional[str] = None
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) -> Tuple[Optional[str], str]:
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"""
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Generate video using Sora-2 Image-to-Video through Hugging Face Inference API with fal-ai provider.
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Returns tuple of (video_path, status_message).
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"""
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cleanup_temp_files() # Clean up old files
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if not image_path:
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return None, "β Please upload an image."
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if not prompt or prompt.strip() == "":
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return None, "β Please enter a prompt for the video generation."
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try:
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if api_key:
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temp_client = InferenceClient(
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provider="fal-ai",
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api_key=api_key,
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bill_to="huggingface",
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)
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else:
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temp_client = client
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if not os.environ.get("HF_TOKEN") and not api_key:
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return None, "β Please set HF_TOKEN environment variable or provide an API key."
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-
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with open(image_path, "rb") as image_file:
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input_image_bytes = image_file.read()
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video_bytes = temp_client.image_to_video(
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input_image_bytes,
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prompt=prompt,
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model="akhaliq/sora-2-image-to-video", # Specific model for image-to-video
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)
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temp_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
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try:
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temp_file.write(video_bytes)
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temp_file.flush()
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video_path = temp_file.name
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finally:
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temp_file.close()
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status_message = f"β
Video generated successfully from image and prompt!"
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return video_path, status_message
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except Exception as e:
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error_msg = f"β Error generating video from image: {str(e)}"
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return None, error_msg
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-
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def generate_with_pro_auth(
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prompt: str,
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oauth_token: Optional[gr.OAuthToken] = None
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) -> Tuple[Optional[str], str]:
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"""
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Wrapper function that checks if user is PRO before generating
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"""
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# Check if user is PRO
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if not verify_pro_status(oauth_token):
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@@ -176,47 +124,14 @@ def generate_with_pro_auth(
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return video_path, status
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def generate_image_to_video_with_pro_auth(
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image_path: str,
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prompt: str,
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oauth_token: Optional[gr.OAuthToken] = None # Gradio will auto-inject this based on type hint
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) -> Tuple[Optional[str], str]:
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"""
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Wrapper function that checks if user is PRO before generating image-to-video.
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"""
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if not verify_pro_status(oauth_token):
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raise gr.Error("Access Denied. This app is exclusively for Hugging Face PRO users. Please subscribe to PRO to use this app.")
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if not image_path:
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return None, "β Please upload an image."
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if not prompt or prompt.strip() == "":
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return None, "β Please enter a prompt"
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video_path, status = generate_image_to_video(
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image_path,
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prompt,
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api_key=None # This will use the environment HF_TOKEN
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)
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return video_path, status
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-
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def simple_generate(prompt: str) -> Optional[str]:
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"""Simplified wrapper for
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if not prompt or prompt.strip() == "":
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return None
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video_path, _ = generate_video(prompt, duration=8, size="1280x720", api_key=None)
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return video_path
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def simple_generate_image_to_video(image_path: str, prompt: str) -> Optional[str]:
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"""Simplified wrapper for image-to-video examples that only returns video."""
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if not image_path or not prompt or prompt.strip() == "":
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return None
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video_path, _ = generate_image_to_video(image_path, prompt, api_key=None)
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return video_path
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def create_ui():
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"""Create the Gradio interface with PRO verification."""
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@@ -237,11 +152,11 @@ def create_ui():
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}
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'''
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with gr.Blocks(title="Sora-2 Text
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gr.HTML("""
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<div style="text-align: center; max-width: 800px; margin: 0 auto;">
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<h1 style="font-size: 2.5em; margin-bottom: 0.5em;">
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π¬ Sora-2 Text
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<span class="pro-badge">PRO</span>
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</h1>
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<p style="font-size: 1.1em; color: #666; margin-bottom: 20px;">Generate stunning videos using OpenAI's Sora-2 model</p>
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@@ -271,115 +186,62 @@ def create_ui():
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</div>
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""")
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with gr.
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with gr.
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placeholder="Describe the video you want to create...",
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lines=4
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)
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with gr.Accordion("Advanced Settings", open=False):
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gr.Markdown("*Coming soon: Duration and resolution controls*")
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generate_btn_text = gr.Button("π₯ Generate Video from Text", variant="primary", size="lg")
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with gr.Column(scale=1):
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video_output_text = gr.Video(
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label="Generated Video",
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height=400,
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interactive=False,
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show_download_button=True
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)
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status_output_text = gr.Textbox(
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label="Status",
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interactive=False,
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visible=True
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)
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# Examples section with queue disabled
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gr.Examples(
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examples=[
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"A serene beach at sunset with waves gently rolling onto the shore",
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"A butterfly emerging from its chrysalis in slow motion",
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"Northern lights dancing across a starry night sky",
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"A bustling city street transitioning from day to night in timelapse",
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"A close-up of coffee being poured into a cup with steam rising",
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"Cherry blossoms falling in slow motion in a Japanese garden"
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],
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inputs=prompt_input_text,
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outputs=video_output_text,
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fn=simple_generate, # Examples use simplified function
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cache_examples=False,
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api_name=False,
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show_api=False,
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)
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with gr.Row():
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with gr.Column(scale=1):
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image_input = gr.Image(
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label="Upload your input image",
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type="filepath",
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height=300,
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value="https://huggingface.co/spaces/akhaliq/sora-2/raw/main/cat.png" # Example image
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)
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prompt_input_image = gr.Textbox(
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label="Enter your text prompt for the video",
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placeholder="Describe the action or style you want for the video (e.g., 'The cat starts to dance')",
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lines=3
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)
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generate_btn_image = gr.Button("πΌοΈ Generate Video from Image", variant="primary", size="lg")
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with gr.Column(scale=1):
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video_output_image = gr.Video(
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label="Generated Video",
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height=400,
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interactive=False,
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show_download_button=True
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)
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status_output_image = gr.Textbox(
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label="Status",
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interactive=False,
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visible=True
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)
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gr.Examples(
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examples=[
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["https://huggingface.co/spaces/akhaliq/sora-2/raw/main/cat.png", "The cat starts to dance"],
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["https://huggingface.co/spaces/akhaliq/sora-2/raw/main/forest.png", "A magical forest where trees shimmer with light"],
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["https://huggingface.co/spaces/akhaliq/sora-2/raw/main/car.png", "A classic car driving through a futuristic city"]
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],
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inputs=[image_input, prompt_input_image],
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outputs=video_output_image,
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fn=simple_generate_image_to_video,
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cache_examples=False,
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api_name=False,
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show_api=False,
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)
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outputs=[video_output_image, status_output_image],
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queue=False,
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api_name=False,
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show_api=False,
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)
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# Footer
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gr.HTML("""
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<div style="text-align: center; margin-top: 40px; padding: 20px; border-top: 1px solid #e0e0e0;">
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@@ -388,9 +250,7 @@ def create_ui():
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""")
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def control_access(profile: Optional[gr.OAuthProfile] = None, oauth_token: Optional[gr.OAuthToken] = None):
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"""Control interface visibility based on PRO status.
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Gradio automatically injects gr.OAuthProfile and gr.OAuthToken based on type hints
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when OAuth is enabled for the Space."""
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if not profile:
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# User not logged in
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return gr.update(visible=False), gr.update(visible=False)
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@@ -403,12 +263,12 @@ def create_ui():
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message = """
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## β¨ Exclusive Access for PRO Users
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Thank you for your interest in the Sora-2 Text
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This advanced AI video generation tool is available exclusively for Hugging Face **PRO** members.
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### What you get with PRO:
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-
- β
Unlimited access to Sora-2 video generation
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- β
High-quality video outputs up to 1280x720
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- β
Fast generation times with priority queue
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- β
Access to other exclusive PRO Spaces
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return gr.update(visible=False), gr.update(visible=True, value=message)
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# Check access on load
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# No explicit inputs are needed here as gr.OAuthProfile and gr.OAuthToken are
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# provided automatically by Gradio to the function based on type hints.
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demo.load(
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control_access,
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inputs=None,
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outputs=[main_interface, pro_message]
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)
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elif isinstance(token, str):
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token_str = token
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else:
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return False
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try:
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user_info = whoami(token=token_str)
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def generate_video(
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prompt: str,
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duration: int = 8,
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size: str = "1280x720",
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api_key: Optional[str] = None
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) -> Tuple[Optional[str], str]:
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"""
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+
Generate video using Sora-2 through Hugging Face Inference API with fal-ai provider.
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Returns tuple of (video_path, status_message).
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"""
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# Clean up old files before generating new ones
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else:
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temp_client = client
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if not os.environ.get("HF_TOKEN") and not api_key:
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return None, "β Please set HF_TOKEN environment variable."
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# Call Sora-2 through Hugging Face Inference API
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video_bytes = temp_client.text_to_video(
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prompt,
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model="akhaliq/sora-2",
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)
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# Save to temporary file with proper cleanup
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# Use NamedTemporaryFile with delete=True but keep reference
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temp_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
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try:
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temp_file.write(video_bytes)
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error_msg = f"β Error generating video: {str(e)}"
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return None, error_msg
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def generate_with_pro_auth(
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prompt: str,
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oauth_token: Optional[gr.OAuthToken] = None
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) -> Tuple[Optional[str], str]:
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"""
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+
Wrapper function that checks if user is PRO before generating video.
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"""
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# Check if user is PRO
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if not verify_pro_status(oauth_token):
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return video_path, status
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def simple_generate(prompt: str) -> Optional[str]:
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"""Simplified wrapper for examples that only returns video."""
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if not prompt or prompt.strip() == "":
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return None
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video_path, _ = generate_video(prompt, duration=8, size="1280x720", api_key=None)
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return video_path
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def create_ui():
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"""Create the Gradio interface with PRO verification."""
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| 152 |
}
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'''
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+
with gr.Blocks(title="Sora-2 Text-to-Video Generator", theme=gr.themes.Soft(), css=css) as demo:
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gr.HTML("""
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<div style="text-align: center; max-width: 800px; margin: 0 auto;">
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<h1 style="font-size: 2.5em; margin-bottom: 0.5em;">
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+
π¬ Sora-2 Text-to-Video Generator
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<span class="pro-badge">PRO</span>
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</h1>
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<p style="font-size: 1.1em; color: #666; margin-bottom: 20px;">Generate stunning videos using OpenAI's Sora-2 model</p>
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</div>
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""")
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+
with gr.Row():
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+
with gr.Column(scale=1):
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+
prompt_input = gr.Textbox(
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+
label="Enter your prompt",
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+
placeholder="Describe the video you want to create...",
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+
lines=4
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| 195 |
)
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| 197 |
+
with gr.Accordion("Advanced Settings", open=False):
|
| 198 |
+
gr.Markdown("*Coming soon: Duration and resolution controls*")
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+
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| 200 |
+
generate_btn = gr.Button("π₯ Generate Video", variant="primary", size="lg")
|
| 201 |
+
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| 202 |
+
with gr.Column(scale=1):
|
| 203 |
+
video_output = gr.Video(
|
| 204 |
+
label="Generated Video",
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| 205 |
+
height=400,
|
| 206 |
+
interactive=False,
|
| 207 |
+
show_download_button=True
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| 208 |
)
|
| 209 |
+
status_output = gr.Textbox(
|
| 210 |
+
label="Status",
|
| 211 |
+
interactive=False,
|
| 212 |
+
visible=True
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|
| 213 |
)
|
| 214 |
|
| 215 |
+
# Hidden manual token input removed - not needed anymore
|
| 216 |
+
|
| 217 |
+
# Examples section with queue disabled
|
| 218 |
+
gr.Examples(
|
| 219 |
+
examples=[
|
| 220 |
+
"A serene beach at sunset with waves gently rolling onto the shore",
|
| 221 |
+
"A butterfly emerging from its chrysalis in slow motion",
|
| 222 |
+
"Northern lights dancing across a starry night sky",
|
| 223 |
+
"A bustling city street transitioning from day to night in timelapse",
|
| 224 |
+
"A close-up of coffee being poured into a cup with steam rising",
|
| 225 |
+
"Cherry blossoms falling in slow motion in a Japanese garden"
|
| 226 |
+
],
|
| 227 |
+
inputs=prompt_input,
|
| 228 |
+
outputs=video_output,
|
| 229 |
+
fn=simple_generate, # Examples use simplified function
|
| 230 |
+
cache_examples=False,
|
| 231 |
+
api_name=False,
|
| 232 |
+
show_api=False,
|
| 233 |
+
)
|
| 234 |
+
|
| 235 |
+
# Event handler for generation with queue disabled
|
| 236 |
+
generate_btn.click(
|
| 237 |
+
fn=generate_with_pro_auth,
|
| 238 |
+
inputs=[prompt_input],
|
| 239 |
+
outputs=[video_output, status_output],
|
| 240 |
+
queue=False,
|
| 241 |
+
api_name=False,
|
| 242 |
+
show_api=False,
|
| 243 |
+
)
|
| 244 |
+
|
| 245 |
# Footer
|
| 246 |
gr.HTML("""
|
| 247 |
<div style="text-align: center; margin-top: 40px; padding: 20px; border-top: 1px solid #e0e0e0;">
|
|
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|
| 250 |
""")
|
| 251 |
|
| 252 |
def control_access(profile: Optional[gr.OAuthProfile] = None, oauth_token: Optional[gr.OAuthToken] = None):
|
| 253 |
+
"""Control interface visibility based on PRO status."""
|
|
|
|
|
|
|
| 254 |
if not profile:
|
| 255 |
# User not logged in
|
| 256 |
return gr.update(visible=False), gr.update(visible=False)
|
|
|
|
| 263 |
message = """
|
| 264 |
## β¨ Exclusive Access for PRO Users
|
| 265 |
|
| 266 |
+
Thank you for your interest in the Sora-2 Text-to-Video Generator!
|
| 267 |
|
| 268 |
This advanced AI video generation tool is available exclusively for Hugging Face **PRO** members.
|
| 269 |
|
| 270 |
### What you get with PRO:
|
| 271 |
+
- β
Unlimited access to Sora-2 video generation
|
| 272 |
- β
High-quality video outputs up to 1280x720
|
| 273 |
- β
Fast generation times with priority queue
|
| 274 |
- β
Access to other exclusive PRO Spaces
|
|
|
|
| 300 |
return gr.update(visible=False), gr.update(visible=True, value=message)
|
| 301 |
|
| 302 |
# Check access on load
|
|
|
|
|
|
|
| 303 |
demo.load(
|
| 304 |
control_access,
|
| 305 |
+
inputs=None,
|
| 306 |
outputs=[main_interface, pro_message]
|
| 307 |
)
|
| 308 |
|