app.py

import os
import gradio as gr
from gradio_client import Client



def infer (prompt, style_prompt, inf_steps, guidance_scale, width, height, seed, lora_weight, progress=gr.Progress(track_tqdm=True)):    
    custom_model="lichorosario/dott_remastered_style_lora_sdxl"
    weight_name="dott_style.safetensors"

    client = Client("fffiloni/sd-xl-custom-model")
    result = client.predict(
    		custom_model=custom_model,
    		api_name="/load_model"
    )

    client = Client("fffiloni/sd-xl-custom-model")
    prompt = "dott style. "+prompt+". "+style_prompt
    result = client.predict(
		custom_model=custom_model,
		weight_name=weight_name,
		prompt=prompt,
		inf_steps=inf_steps,
		guidance_scale=guidance_scale,
		width=width,
		height=height,
		seed=seed,
		lora_weight=lora_weight,
		api_name="/infer"
    )

    new_result = result + (prompt, )

    return new_result




css="""
#col-container{
    margin: 0 auto;
    max-width: 720px;
    text-align: left;
}
div#warning-duplicate {
    background-color: #ebf5ff;
    padding: 0 16px 16px;
    margin: 20px 0;
}
div#warning-duplicate > .gr-prose > h2, div#warning-duplicate > .gr-prose > p {
    color: #0f4592!important;
}
div#warning-duplicate strong {
    color: #0f4592;
}
p.actions {
    display: flex;
    align-items: center;
    margin: 20px 0;
}
div#warning-duplicate .actions a {
    display: inline-block;
    margin-right: 10px;
}
button#load_model_btn{
    height: 46px;
}
#status_info{
    font-size: 0.9em;
}
.custom-color {
    color: #030303 !important;
}
"""

with gr.Blocks(css=css) as demo:
    with gr.Column(elem_id="col-container"):
        prompt_in = gr.Textbox(
          label="Your Prompt",
          info = "Dont' forget to include your trigger word if necessary"
        )   
        style_prompt_in = gr.Textbox(
          label="Your Style Prompt"
        )   
        used_prompt = gr.Textbox(
            label="Used prompt"
        )
        with gr.Accordion("Advanced Settings", open=False):
            with gr.Row():
                inf_steps = gr.Slider(
                    label="Inference steps",
                    minimum=12,
                    maximum=50,
                    step=1,
                    value=25
                )
                guidance_scale = gr.Slider(
                    label="Guidance scale",
                    minimum=0.0,
                    maximum=50.0,
                    step=0.1,
                    value=7.5
                )
            with gr.Row():
                width = gr.Slider(
                    label="Width",
                    minimum=256,
                    maximum=2048,
                    step=32,
                    value=1024,
                )
                height = gr.Slider(
                    label="Height",
                    minimum=256,
                    maximum=2048,
                    step=32,
                    value=1024,
                )
    
            with gr.Row():
                seed = gr.Slider(
                    label="Seed",
                    info = "-1 denotes a random seed",
                    minimum=-1,
                    maximum=423538377342,
                    step=1,
                    value=-1
                )
                last_used_seed = gr.Number(
                    label = "Last used seed",
                    info = "the seed used in the last generation",
                )
            lora_weight = gr.Slider(
                label="LoRa weigth",
                minimum=0.0,
                maximum=1.0,
                step=0.01,
                value=1.0
            )
    submit_btn = gr.Button("Submit")
    image_out = gr.Image(label="Image output")

    submit_btn.click(
        fn = infer,
        inputs = [prompt_in, style_prompt_in, inf_steps, guidance_scale, width, height, seed, lora_weight],
        outputs = [image_out, last_used_seed, used_prompt]
    )

demo.launch()