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Update app.py
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app.py
CHANGED
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import gradio as gr
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from models import generate_image, MODEL_ID
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from config import APPLE_TENCENT_THEME
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from typing import Optional
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def create_ui():
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"""Create the main application UI with Hugging Face OAuth authentication"""
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with gr.Blocks(title=f"Tencent HunyuanImage-3.0 Demo", theme=APPLE_TENCENT_THEME) as demo:
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with gr.Row():
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with gr.Column(scale=3):
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gr.HTML(
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f"<div style='text-align: center; max-width: 700px; margin: 0 auto;'>"
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f"<h1>Tencent {MODEL_ID.split('/')[-1]}</h1>"
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f"<p>Generate images using Tencent's state-of-the-art model hosted by FAL AI.</p>"
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f"Built with <a href='https://huggingface.co/spaces/akhaliq/anycoder' target='_blank'>anycoder</a>"
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f"</div>"
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)
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with gr.Column(scale=1):
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size="lg",
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variant="huggingface"
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)
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# User info display
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user_info = gr.Markdown("", visible=False)
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# Main interface container - hidden until authenticated
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with gr.Group(visible=False) as main_interface:
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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="Prompt",
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placeholder="e.g., A detailed watercolor painting of a small red fox sleeping on a pile of autumn leaves.",
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lines=4
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)
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with gr.Row():
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generate_btn = gr.Button("🎨 Generate Image", variant="primary", scale=2)
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clear_btn = gr.Button("🗑️ Clear", variant="secondary", scale=1)
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# Additional settings in an accordion
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with gr.Accordion("⚙️ Advanced Settings", open=False):
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gr.Markdown("""
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Advanced settings are not implemented in this demo.
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You can add parameters like:
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- Image size
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- Number of steps
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- Guidance scale
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- Seed
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""")
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with gr.Column(scale=1):
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output_image = gr.Image(
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label="Generated Image",
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height=512,
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width=512,
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interactive=False,
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show_download_button=True
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)
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# Generation status
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status_text = gr.Markdown("Ready to generate...", visible=True)
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# Example prompts
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gr.Examples(
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examples=[
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"A detailed watercolor painting of a small red fox sleeping on a pile of autumn leaves.",
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"A futuristic cityscape at sunset with flying cars and neon lights",
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"A serene Japanese garden with cherry blossoms and a koi pond",
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"A steampunk mechanical owl perched on an ancient tree",
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"An astronaut playing guitar on the moon with Earth in the background"
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],
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inputs=prompt_input,
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outputs=[output_image, status_text],
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fn=lambda prompt: generate_with_status(prompt, user_profile_state.value),
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cache_examples=False,
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show_api=False,
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)
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# Welcome message for non-authenticated users
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welcome_message = gr.HTML(
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"""
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<div style='text-align: center; max-width: 600px; margin: 50px auto; padding: 30px;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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border-radius: 20px; box-shadow: 0 10px 30px rgba(0,0,0,0.2);'>
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<h2 style='color: white; margin-bottom: 20px;'>🎨 Welcome to HunyuanImage-3.0</h2>
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<p style='color: rgba(255,255,255,0.9); font-size: 16px; line-height: 1.6;'>
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Sign in with your Hugging Face account to start generating amazing images
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with Tencent's state-of-the-art AI model.
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</p>
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<div style='margin-top: 30px; padding: 20px; background: rgba(255,255,255,0.1);
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border-radius: 10px;'>
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<p style='color: white; margin: 0;'>
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<strong>✨ Features:</strong><br>
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• High-quality image generation<br>
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• Easy-to-use interface<br>
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• Multiple example prompts<br>
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• Download generated images
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</p>
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</div>
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<p style='color: rgba(255,255,255,0.8); font-size: 14px; margin-top: 20px;'>
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Click the "Sign in with Hugging Face" button above to get started
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</p>
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</div>
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""",
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visible=True
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)
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# Authentication handling functions
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def update_ui_on_auth(profile: gr.OAuthProfile | None) -> tuple:
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"""Update UI based on authentication status"""
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if profile is None:
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# User is not authenticated
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return (
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gr.update(visible=False), # main_interface
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gr.update(visible=True), # welcome_message
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"", # user_info
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gr.update(visible=False), # user_info visibility
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None # user_profile_state
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)
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# User is authenticated
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user_text = f"### 👤 Welcome, {profile.name}!\n\n"
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if profile.username:
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user_text += f"**Username:** @{profile.username}\n"
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if hasattr(profile, 'email') and profile.email:
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user_text += f"**Email:** {profile.email}\n"
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)
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"""Generate image with status updates and user verification"""
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if profile is None:
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return None, "⚠️ Please sign in to generate images!"
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if not prompt:
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return None, "⚠️ Please enter a prompt!"
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try:
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# You can log user activity here if needed
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print(f"User {profile.username} is generating an image with prompt: {prompt[:50]}...")
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# Generate the image
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image = generate_image(prompt)
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return image, "✅ Image generated successfully!"
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except Exception as e:
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return None, f"❌ Error: {str(e)}"
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def clear_interface():
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"""Clear the interface"""
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return "", None, "Ready to generate..."
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# Load event to check authentication status
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demo.load(
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fn=update_ui_on_auth,
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inputs=None,
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outputs=[main_interface, welcome_message, user_info, user_info, user_profile_state],
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queue=False,
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show_api=False,
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)
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# Login button click event (also handles logout)
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login_button.click(
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fn=update_ui_on_auth,
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inputs=None,
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outputs=[main_interface, welcome_message, user_info, user_info, user_profile_state],
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queue=False,
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show_api=False,
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)
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# Generate button event
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generate_btn.click(
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fn=
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inputs=[prompt_input
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outputs=[output_image
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queue=False,
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)
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#
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"""
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<div style='text-align: center; margin-top: 40px; padding: 20px; border-top: 1px solid #e0e0e0;'>
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<p style='color: #666; font-size: 14px;'>
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This demo uses Hugging Face OAuth for secure authentication.
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Your session will remain active until you logout.
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<br>For the best results, provide detailed prompts with specific descriptions.
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</p>
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</div>
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"""
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)
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return demo
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# Additional helper function for logging/tracking (optional)
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def log_user_activity(profile: gr.OAuthProfile, action: str, details: str = ""):
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"""Log user activity for analytics or monitoring"""
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if profile:
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print(f"[{action}] User: {profile.username}, Name: {profile.name}, Details: {details}")
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if __name__ == "__main__":
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app = create_ui()
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# Launch the app
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# Note: OAuth features work best when deployed on Hugging Face Spaces
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# For local development, it will use the local HF account (via hf auth login)
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app.launch(
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show_api=False,
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enable_monitoring=False,
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quiet=True,
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server_name="0.0.0.0", # Change to "0.0.0.0" to allow external access
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server_port=7860, # Default Gradio port
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)
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# Note: When deploying to Hugging Face Spaces, you can configure OAuth permissions
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# in the README file as described here: https://huggingface.co/docs/hub/en/spaces-oauth
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import gradio as gr
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from models import generate_image, MODEL_ID
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from config import APPLE_TENCENT_THEME
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def create_ui():
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with gr.Blocks(title=f"Tencent HunyuanImage-3.0 Demo", theme=APPLE_TENCENT_THEME) as demo:
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gr.HTML(
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f"<div style='text-align: center; max-width: 700px; margin: 0 auto;'>"
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f"<h1>Tencent {MODEL_ID.split('/')[-1]}</h1>"
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f"<p>Generate images using Tencent's state-of-the-art model hosted by FAL AI.</p>"
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f"Built with <a href='https://huggingface.co/spaces/akhaliq/anycoder' target='_blank'>anycoder</a>"
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f"</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="Prompt",
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placeholder="e.g., A detailed watercolor painting of a small red fox sleeping on a pile of autumn leaves.",
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lines=4
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)
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generate_btn = gr.Button("🎨 Generate Image", variant="primary")
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with gr.Column(scale=1):
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output_image = gr.Image(
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label="Generated Image",
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height=512,
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width=512,
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interactive=False,
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show_download_button=True
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)
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# Set up the event listener with all queue-related features disabled
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generate_btn.click(
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fn=generate_image,
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inputs=[prompt_input],
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outputs=[output_image],
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queue=False, # Disable queue for this event
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api_name=False, # Disable API endpoint creation
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show_api=False, # Don't show this in API docs
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# Example usage guidance with queue features disabled
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gr.Examples(
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examples=[
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"A detailed watercolor painting of a small red fox sleeping on a pile of autumn leaves."
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],
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inputs=prompt_input,
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outputs=output_image,
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fn=generate_image,
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cache_examples=False, # Don't cache examples
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api_name=False, # No API endpoint for examples
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show_api=False, # Don't show in API docs
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)
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return demo
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if __name__ == "__main__":
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app = create_ui()
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# Launch without queue, API, and monitoring features
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app.launch(
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show_api=False, # Hide API documentation
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enable_monitoring=False, # Disable monitoring to prevent any background queuing
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quiet=True, # Reduce console output
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)
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