app.py

import gradio as gr
from model import models
from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery,
    change_model, warm_model, get_model_info_md, loaded_models,
    get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
    get_recom_prompt_type, set_recom_prompt_preset, get_tag_type)

max_images = 8
MAX_SEED = 2**32-1
load_models(models)

css = """
.model_info { text-align: center; }
.output { width=112px; height=112px; !important; }
.gallery { width=100%; min_height=768px; !important; }
"""

with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
    with gr.Column(): 
        with gr.Group():
            model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
            model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
        with gr.Group():
            clear_prompt = gr.Button(value="Clear Prompt 🗑️", size="sm", scale=1)
            prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True)
            neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")
            with gr.Accordion("Advanced options", open=False):
                with gr.Row():
                    width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
                    height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
                with gr.Row():
                    steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
                    cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
                seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
            with gr.Accordion("Recommended Prompt", open=False):
                recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
                with gr.Row():
                    positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
                    positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"])
                    negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[])
                    negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"])
        image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=1)
        with gr.Row():
            run_button = gr.Button("Generate Image", scale=6)
            random_button = gr.Button("Random Model 🎲", scale=3)
            stop_button = gr.Button('Stop', interactive=False, scale=1)
    with gr.Column(): 
        with gr.Group():
            with gr.Row():
                output = [gr.Image(label='', elem_classes="output", type="filepath", format="png",
                          show_download_button=True, show_share_button=False, show_label=False,
                          interactive=False, min_width=80, visible=True) for _ in range(max_images)]
        with gr.Group():
            results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False,
                                 container=True, format="png", object_fit="cover", columns=2, rows=2)
            image_files = gr.Files(label="Download", interactive=False)
            clear_results = gr.Button("Clear Gallery / Download 🗑️")
    with gr.Column(): 
        examples = gr.Examples(
            examples = [
                ["souryuu asuka langley, 1girl, neon genesis evangelion, plugsuit, pilot suit, red bodysuit, sitting, crossing legs, black eye patch, cat hat, throne, symmetrical, looking down, from bottom, looking at viewer, outdoors"],
                ["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
                ["kafuu chino, 1girl, solo"],
                ["1girl"],
                ["beautiful sunset"],
            ],
            inputs=[prompt],
        )
        gr.Markdown(
            f"""This demo was created in reference to the following demos.<br>
    [Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood), 
    [Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL), 
    [Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX).
                """
        )
        gr.DuplicateButton(value="Duplicate Space")
        gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")

    gr.on(triggers=[run_button.click, prompt.submit, random_button.click], fn=lambda: gr.update(interactive=True), inputs=None, outputs=stop_button, show_api=False)
    model_name.change(change_model, [model_name], [model_info], queue=False, show_api=False)\
    .success(warm_model, [model_name], None, queue=True, show_api=False)
    for i, o in enumerate(output):
        img_i = gr.Number(i, visible=False)
        image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=False)
        gen_event = gr.on(triggers=[run_button.click, prompt.submit],
         fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
         outputs=[o], queue=True, show_api=False)
        gen_event2 = gr.on(triggers=[random_button.click],
         fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_rand_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
         outputs=[o], queue=True, show_api=False)
        o.change(save_gallery, [o, results], [results, image_files], show_api=False)
        stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False)

    clear_prompt.click(lambda: None, None, [prompt], queue=False, show_api=False)
    clear_results.click(lambda: (None, None), None, [results, image_files], queue=False, show_api=False)
    recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
     [positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=False, show_api=False)

demo.queue(default_concurrency_limit=200, max_size=200)
demo.launch(max_threads=400)