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