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]
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="""
#container { max-width: 1200px; margin: 0 auto; !important; }
.output { width=112px; height=112px; !important; }
.gallery { width=100%; min_height=768px; !important; }
.guide { text-align: center; !important; }
"""

with gr.Blocks(theme='Hev832/Applio', fill_width=True) as myface:
    
    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)
    with gr.Row():
        with gr.Column(scale=100):
            with gr.Group():
                magic1 = gr.Textbox(label="Your Prompt", lines=4) #Positive
                with gr.Accordion("Advanced", open=False, visible=True):
                    neg_input = gr.Textbox(label='Negative prompt:', lines=1)
                    with gr.Row():
                        width = gr.Number(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
                        height = gr.Number(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
                    with gr.Row():
                        steps = gr.Number(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
                        cfg = gr.Number(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.Column(scale=100):
            #negative_prompt=gr.Textbox(label="Negative Prompt", lines=1)
            gr.HTML("""<style>           .gr-button {
            color: #ffffff !important;
            text-shadow: 1px 1px 0 rgba(0, 0, 0, 1) !important;
            background-image: linear-gradient(#76635a, #d2a489) !important;
            border-radius: 24px !important;
            border: solid 1px !important;
            border-top-color: #ffc99f !important;
            border-right-color: #000000 !important;
            border-bottom-color: #000000 !important;
            border-left-color: #ffc99f !important;
            padding: 6px 30px;
}
.gr-button:active {
            color: #ffc99f !important;
            font-size: 98% !important;
            text-shadow: 0px 0px 0 rgba(0, 0, 0, 1) !important;
            background-image: linear-gradient(#d2a489, #76635a) !important;
            border-top-color: #000000 !important;
            border-right-color: #ffffff !important;
            border-bottom-color: #ffffff !important;
            border-left-color: #000000 !important;
}
.gr-button:hover {
  filter: brightness(130%);
}
</style>""")
            run = gr.Button("Generate Image")
    with gr.Row():
        with gr.Column():
            output1 = gr.Image(label=(f"{current_model}"), show_download_button=True, elem_classes="output",
                               interactive=False, show_share_button=False, format=".png")
                
    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)
            see_prompts=gr.Button("Extend Idea -> overwrite the contents of the `Your Prompt´ box above")
            use_short=gr.Button("Copy the contents of this box to the `Your Prompt´ box above")
    def short_prompt(inputs):
        return (inputs)
    
    model_name1.change(set_model, inputs=model_name1, outputs=[output1])
    
    #run.click(send_it1, inputs=[magic1, model_name1, neg_input, height, width, steps, cfg, seed], 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(default_concurrency_limit=200, max_size=200)
myface.launch(show_api=False, share=True, max_threads=400)