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import gradio as gr
from gradio_client import Client
client = Client("multimodalart/FLUX.1-merged")
def infer(prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, api_name):
result = client.predict(
prompt=prompt,
seed=seed,
randomize_seed=True,
width=width,
height=height,
guidance_scale=guidance_scale,
num_inference_steps=num_inference_steps,
api_name="/infer"
)
return result
css="""
#col-container {
margin: 0 auto;
max-width: 520px;
}
"""
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(f"""
FallnAI: DiffusionLab Beta
""")
with gr.Row():
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt",
container=False,
)
run_button = gr.Button("Create", scale=0)
result = gr.Image(label="Result", show_label=False)
with gr.Accordion("Advanced Settings", open=False):
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=999999,
step=1,
value=0,
)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
with gr.Row():
width = gr.Slider(
label="Width",
minimum=256,
maximum=2048,
step=32,
value=1024,
)
height = gr.Slider(
label="Height",
minimum=256,
maximum=2024,
step=32,
value=1024,
)
with gr.Row():
guidance_scale = gr.Slider(
label="Guidance scale",
minimum=0.1,
maximum=10.0,
step=0.1,
value=1.0,
)
num_inference_steps = gr.Slider(
label="Number of inference steps",
minimum=1,
maximum=12,
step=1,
value=2,
)
run_button.click(
fn = infer,
inputs = [prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps,api_name],
outputs = [result, seed]
)
demo.queue().launch() |