Spaces:
Running
on
Zero
Running
on
Zero
Replace gallery with single image output
Browse filesSimplify the UI by showing one generated image at a time instead of
accumulating images in a gallery. This removes unnecessary state
management and makes the interface cleaner.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <[email protected]>
app.py
CHANGED
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@@ -365,7 +365,7 @@ def prompt_enhance(prompt, enable_enhance):
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@spaces.GPU
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def generate(
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prompt, resolution="1024x1024 ( 1:1 )", seed=42, steps=9, shift=3.0, random_seed=True,
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):
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"""
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Generate an image using the Z-Image model based on the provided prompt and settings.
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@@ -381,13 +381,12 @@ def generate(
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steps (int): Number of inference steps for the diffusion process
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shift (float): Time shift parameter for the flow matching scheduler
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random_seed (bool): Whether to generate a new random seed, if True will ignore the seed input
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gallery_images (list): List of previously generated images to append to (only needed for the Gradio UI)
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enhance (bool): This was Whether to enhance the prompt (DISABLED! Do not use)
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progress (gr.Progress): Gradio progress tracker for displaying generation progress (only needed for the Gradio UI)
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Returns:
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tuple: (
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- seed_str: String representation of the seed used for generation
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- seed_int: Integer representation of the seed used for generation
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"""
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@@ -420,11 +419,7 @@ def generate(
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shift=shift,
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)
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-
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gallery_images = []
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gallery_images.append(image)
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return gallery_images, str(new_seed), int(new_seed)
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init_app()
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@@ -479,8 +474,8 @@ with gr.Blocks(title="Z-Image Demo") as demo:
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gr.Examples(examples=EXAMPLE_PROMPTS, inputs=prompt_input, label=None)
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with gr.Column(scale=1):
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-
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label="Generated
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)
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used_seed = gr.Textbox(label="Seed Used", interactive=False)
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@@ -502,8 +497,8 @@ with gr.Blocks(title="Z-Image Demo") as demo:
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generate_btn.click(
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generate,
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inputs=[prompt_input, resolution, seed, steps, shift, random_seed
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outputs=[
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api_visibility="public",
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)
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@spaces.GPU
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def generate(
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prompt, resolution="1024x1024 ( 1:1 )", seed=42, steps=9, shift=3.0, random_seed=True, enhance=False, progress=gr.Progress(track_tqdm=True)
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):
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"""
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Generate an image using the Z-Image model based on the provided prompt and settings.
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steps (int): Number of inference steps for the diffusion process
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shift (float): Time shift parameter for the flow matching scheduler
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random_seed (bool): Whether to generate a new random seed, if True will ignore the seed input
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enhance (bool): This was Whether to enhance the prompt (DISABLED! Do not use)
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progress (gr.Progress): Gradio progress tracker for displaying generation progress (only needed for the Gradio UI)
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Returns:
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tuple: (image, seed_str, seed_int)
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- image: The generated image
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- seed_str: String representation of the seed used for generation
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- seed_int: Integer representation of the seed used for generation
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"""
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shift=shift,
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)
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return image, str(new_seed), int(new_seed)
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init_app()
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gr.Examples(examples=EXAMPLE_PROMPTS, inputs=prompt_input, label=None)
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with gr.Column(scale=1):
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output_image = gr.Image(
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label="Generated Image", height=600, format="png", interactive=False
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)
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used_seed = gr.Textbox(label="Seed Used", interactive=False)
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generate_btn.click(
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generate,
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inputs=[prompt_input, resolution, seed, steps, shift, random_seed],
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outputs=[output_image, used_seed, seed],
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api_visibility="public",
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)
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