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#!/usr/bin/env python
import gradio as gr
from model import Model
from settings import CACHE_EXAMPLES, 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",
]
def process_example_fn(prompt: str) -> str:
return model.run_text(prompt)
with gr.Blocks() as demo:
with gr.Box():
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,
cache_examples=CACHE_EXAMPLES,
)
inputs = [
prompt,
seed,
guidance_scale,
num_inference_steps,
]
prompt.submit(
fn=randomize_seed_fn,
inputs=[seed, randomize_seed],
outputs=seed,
queue=False,
api_name=False,
).then(
fn=model.run_text,
inputs=inputs,
outputs=result,
api_name=False,
)
run_button.click(
fn=randomize_seed_fn,
inputs=[seed, randomize_seed],
outputs=seed,
queue=False,
api_name=False,
).then(
fn=model.run_text,
inputs=inputs,
outputs=result,
api_name="text-to-3d",
)
return demo
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