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import gradio as gr
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import spaces
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from model import Model
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from settings import MAX_SEED
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from utils import randomize_seed_fn
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def create_demo(model: Model) -> gr.Blocks:
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examples = [
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"A chair that looks like an avocado",
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"An airplane that looks like a banana",
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"A spaceship",
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"A birthday cupcake",
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"A chair that looks like a tree",
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"A green boot",
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"A penguin",
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"Ube ice cream cone",
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"A bowl of vegetables",
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]
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@spaces.GPU
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def process_example_fn(prompt: str) -> str:
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return model.run_text(prompt)
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@spaces.GPU
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def run(prompt: str, seed: int, guidance_scale: float, num_inference_steps: int) -> str:
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return model.run_text(prompt, seed, guidance_scale, num_inference_steps)
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with gr.Blocks() as demo:
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with gr.Group():
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with gr.Row(elem_id="prompt-container"):
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prompt = gr.Text(
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label="Prompt",
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show_label=False,
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max_lines=1,
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placeholder="Enter your prompt",
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submit_btn=True,
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)
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result = gr.Model3D(label="Result", show_label=False)
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with gr.Accordion("Advanced options", open=False):
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seed = gr.Slider(
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label="Seed",
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minimum=0,
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maximum=MAX_SEED,
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step=1,
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value=0,
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)
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randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
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guidance_scale = gr.Slider(
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label="Guidance scale",
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minimum=1,
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maximum=20,
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step=0.1,
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value=15.0,
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)
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num_inference_steps = gr.Slider(
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label="Number of inference steps",
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minimum=2,
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maximum=100,
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step=1,
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value=64,
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)
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gr.Examples(
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examples=examples,
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inputs=prompt,
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outputs=result,
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fn=process_example_fn,
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)
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prompt.submit(
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fn=randomize_seed_fn,
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inputs=[seed, randomize_seed],
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outputs=seed,
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api_name=False,
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concurrency_limit=None,
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).then(
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fn=run,
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inputs=[
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prompt,
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seed,
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guidance_scale,
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num_inference_steps,
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],
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outputs=result,
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api_name="text-to-3d",
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concurrency_id="gpu",
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concurrency_limit=1,
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)
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return demo
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