app.py

import gradio as gr
import os 
import sys
from pathlib import Path
from all_models import models
from externalmod import gr_Interface_load
from prompt_extend import extend_prompt
from random import randint
import asyncio
from threading import RLock
lock = RLock()
HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None # If private or gated models aren't used, ENV setting is unnecessary.

inference_timeout = 300
MAX_SEED = 2**32-1
current_model = models[0]
new_models = ", ".join([m.split("/")[-1] for m in models[0:6]])
text_gen1 = extend_prompt
#text_gen1=gr_Interface_load("spaces/phenomenon1981/MagicPrompt-Stable-Diffusion") 
#text_gen1=gr_Interface_load("spaces/Yntec/prompt-extend") 
#text_gen1=gr_Interface_load("spaces/daspartho/prompt-extend") 
#text_gen1=gr_Interface_load("spaces/Omnibus/MagicPrompt-Stable-Diffusion_link")

models2 = [gr_Interface_load(f"models/{m}", live=False, preprocess=True, postprocess=False, hf_token=HF_TOKEN) for m in models]
   
def text_it1(inputs, text_gen1=text_gen1):
        go_t1 = text_gen1(inputs)
        return(go_t1)

def set_model(current_model):
    current_model = models[current_model]
    return gr.update(label=(f"{current_model}"))

def send_it1(inputs, model_choice, neg_input, height, width, steps, cfg, seed): #negative_prompt,
        #proc1 = models2[model_choice]
        #output1 = proc1(inputs)
        output1 = gen_fn(model_choice, inputs, neg_input, height, width, steps, cfg, seed)
        #negative_prompt=negative_prompt
        return (output1)

# https://huggingface.co/docs/api-inference/detailed_parameters
# https://huggingface.co/docs/huggingface_hub/package_reference/inference_client
async def infer(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1, timeout=inference_timeout):
    from pathlib import Path
    kwargs = {}
    if height is not None and height >= 256: kwargs["height"] = height
    if width is not None and width >= 256: kwargs["width"] = width
    if steps is not None and steps >= 1: kwargs["num_inference_steps"] = steps
    if cfg is not None and cfg > 0: cfg = kwargs["guidance_scale"] = cfg
    noise = ""
    if seed >= 0: kwargs["seed"] = seed
    else:
        rand = randint(1, 500)
        for i in range(rand):
            noise += " "
    task = asyncio.create_task(asyncio.to_thread(models2[model_index].fn,
                               prompt=f'{prompt} {noise}', negative_prompt=nprompt, **kwargs, token=HF_TOKEN))
    await asyncio.sleep(0)
    try:
        result = await asyncio.wait_for(task, timeout=timeout)
    except (Exception, asyncio.TimeoutError) as e:
        print(e)
        print(f"Task timed out: {models2[model_index]}")
        if not task.done(): task.cancel()
        result = None
    if task.done() and result is not None:
        with lock:
            png_path = "image.png"
            result.save(png_path)
            image = str(Path(png_path).resolve())
        return image
    return None

def gen_fn(model_index, prompt, nprompt="", height=None, width=None, steps=None, cfg=None, seed=-1):
    try:
        loop = asyncio.new_event_loop()
        result = loop.run_until_complete(infer(model_index, prompt, nprompt,
                                         height, width, steps, cfg, seed, inference_timeout))
    except (Exception, asyncio.CancelledError) as e:
        print(e)
        print(f"Task aborted: {models2[model_index]}")
        result = None
    finally:
        loop.close()
    return result

css="""

.gradio-container {!important; font-family: 'IBM Plex Sans', sans-serif !important;

 text-align: center; max-width: 1200px; margin: 0 auto; !important;}

h1 {font-size: 6em; color: #ffc99f; margin-top: 30px; margin-bottom: 30px;

 text-shadow: 3px 3px 0 rgba(0, 0, 0, 1) !important;}

h3 {color: #ffc99f; !important;}

h4 {display: inline-block; color: #ffffff !important; }

.wrapper img {font-size: 98% !important; white-space: nowrap !important;

 text-align: center !important; display: inline-block !important;color: #ffffff !important;}

.wrapper {color: #ffffff !important;}

.text-gray-500 {color: #ffc99f !important;}

.gr-box {background-image: linear-gradient(#182634, #1e2f40, #254150) !important; border-top-color: #000000 !important;

 border-right-color: #ffffff !important; border-bottom-color: #ffffff !important; border-left-color: #000000 !important;}

"""

with gr.Blocks(theme='John6666/YntecLight', fill_width=True, css=css) as myface:
    gr.HTML(f"""

     <div style="text-align: center; max-width: 1200px; margin: 0 auto;">

              <div>

                <style>

                    h1 {{

                    font-size: 6em;

                    color: #ffc99f;

                    margin-top: 30px;

                    margin-bottom: 30px;

                    text-shadow: 3px 3px 0 rgba(0, 0, 0, 1) !important;

                   }}

                   h3 {{

                    color: #ffc99f; !important;

                   }}

                   h4 {{

                    display: inline-block;

                    color: #ffffff !important;

                   }}

                   .wrapper img {{

                    font-size: 98% !important;

                    white-space: nowrap !important;

                    text-align: center !important;

                    display: inline-block !important;

                    color: #ffffff !important;

                   }}

                   .wrapper {{

                    color: #ffffff !important;

                   }}

                   .gradio-container {{

                   background-image: linear-gradient(#254150, #1e2f40, #182634) !important;

                   color: #ffaa66 !important;

                   font-family: 'IBM Plex Sans', sans-serif !important;

                   }}

                   .text-gray-500 {{

                   color: #ffc99f !important;

                   }}

                   .gr-box {{

    background-image: linear-gradient(#182634, #1e2f40, #254150) !important;

    border-top-color: #000000 !important;

    border-right-color: #ffffff !important;

    border-bottom-color: #ffffff !important;

    border-left-color: #000000 !important;

                   }}

                   .gr-input {{

                   color: #ffc99f; !important;

                   background-color: #254150 !important;

                   }}

                   :root {{

    --neutral-100: #000000 !important;

                   }}

                </style>

                <body>

                <div class="center"><h1>Toy World</h1>

                </div>

                </body>

              </div>

              <p style="margin-bottom: 1px; color: #ffaa66;">

              <h3>Blitz Diffusion - {int(len(models))} Stable Diffusion models, but why? For your enjoyment!</h3></p>

              <br><div class="wrapper">8.1 <img src="https://huggingface.co/Yntec/DucHaitenLofi/resolve/main/NEW.webp" alt="NEW!" style="width:32px;height:16px;">Toys to play with: {new_models} and 6 more!</div>

              <p style="margin-bottom: 1px; font-size: 98%">

              <br><h4>If a model is already loaded each new image takes less than <b>10</b> seconds to generate!</h4></p>

              <p style="margin-bottom: 1px; color: #ffffff;">

              <br><div class="wrapper">Generate 6 images from 1 prompt at the <u><a href="https://huggingface.co/spaces/Yntec/PrintingPress">PrintingPress</a></u>, and use 6 models simultaneusly at <u><a href="https://huggingface.co/spaces/Yntec/diffusion80xx">Diffusion80XX</a></u>!

        </p></p>

            </div>

            """, elem_classes="gr-box")
    with gr.Row():
        with gr.Column(scale=100):
            #Model selection dropdown
            model_name1 = gr.Dropdown(label="Select Model", choices=[m for m in models], type="index",
                                      value=current_model, interactive=True, elem_classes="gr-box")
    with gr.Row():
        with gr.Column(scale=100):
            with gr.Group():
                magic1 = gr.Textbox(label="Your Prompt", lines=4, elem_classes="gr-box") #Positive
                with gr.Accordion("Advanced", open=False, visible=True):
                    neg_input = gr.Textbox(label='Negative prompt', lines=1, elem_classes="gr-box")
                    with gr.Row():
                        width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0, elem_classes="gr-box")
                        height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0, elem_classes="gr-box")
                    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, elem_classes="gr-box")
                        cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0, elem_classes="gr-box")
                        seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1, elem_classes="gr-box")
            run=gr.Button("Generate Image", elem_classes="gr-button")
    with gr.Row():
        with gr.Column():
            output1 = gr.Image(label=(f"{current_model}"), format="png", elem_classes="gr-box")
    with gr.Row():
        with gr.Column(scale=50):
            input_text = gr.Textbox(label="Use this box to extend an idea automagically, by typing some words and clicking Extend Idea", lines=2, elem_classes="gr-box")
            see_prompts = gr.Button("Extend Idea -> overwrite the contents of the `Your Prompt´ box above", elem_classes="gr-button")
            use_short = gr.Button("Copy the contents of this box to the `Your Prompt´ box above", elem_classes="gr-button")
    def short_prompt(inputs):
        return (inputs)
    
    model_name1.change(set_model, inputs=model_name1, outputs=[output1])
    gr.on(
        triggers=[run.click, magic1.submit],
        fn=send_it1,
        inputs=[magic1, model_name1, neg_input, height, width, steps, cfg, seed],
        outputs=[output1],
    )
    use_short.click(short_prompt, inputs=[input_text], outputs=magic1)
    see_prompts.click(text_it1, inputs=[input_text], outputs=magic1)
    
#myface.queue()
myface.launch(inline=True, show_api=False)