app.py

import gradio as gr
from random import randint
from all_models import models
from externalmod import gr_Interface_load

import asyncio
import os
from threading import RLock
lock = RLock()

def load_fn(models):
    global models_load
    models_load = {}
    
    for model in models:
        if model not in models_load.keys():
            try:
                m = gr_Interface_load(f'models/{model}')
            except Exception as error:
                print(error)
                m = gr.Interface(lambda: None, ['text'], ['image'])
            models_load.update({model: m})

load_fn(models)

num_models = 1
default_models = models[:num_models]
inference_timeout = 600

MAX_SEED = 3999999999

def extend_choices(choices):
    return choices + (num_models - len(choices)) * ['NA']

def update_imgbox(choices):
    choices_plus = extend_choices(choices)
    return [gr.Image(None, label=m, visible=(m != 'NA')) for m in choices_plus]

def gen_fn(model_str, prompt):
    if model_str == 'NA':
        return None
    noise = str('')
    return models_load[model_str](f'{prompt} {noise}')

async def infer(model_str, prompt, seed=1, timeout=inference_timeout):
    from pathlib import Path
    kwargs = {}
    noise = ""
    kwargs["seed"] = seed
    task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn,
                               prompt=f'{prompt} {noise}', **kwargs))
    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: {model_str}")
        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_fnseed(model_str, prompt, seed=1):
    if model_str == 'NA':
        return None
    try:
        loop = asyncio.new_event_loop()
        result = loop.run_until_complete(infer(model_str, prompt, seed, inference_timeout))
    except (Exception, asyncio.CancelledError) as e:
        print(e)
        print(f"Task aborted: {model_str}")
        result = None
        with lock:
            image = "https://huggingface.co/spaces/Yntec/ToyWorld/resolve/main/error.png"
        result = image
    finally:
        loop.close()
    return result

def gen_fnsix(model_str, prompt):
    if model_str == 'NA':
        return None
    noisesix = str(randint(1941, 2023))
    return models_load[model_str](f'{prompt} {noisesix}')

with gr.Blocks() as demo:
    gr.HTML(
    """
        <div>
        <p> <center><img src="https://huggingface.co/Yntec/OpenGenDiffusers/resolve/main/pp.png" style="height:128px; width:482px; margin-top: -22px; margin-bottom: -44px;" span title="Free ai art image generator Printing Press"></center>
        </p>
    """
)
    gr.HTML(
    """
        <div>
        <p> <center>For negative prompts, Width and Height, and other features visit John6666's <a href="https://huggingface.co/spaces/John6666/PrintingPress4">Printing Press 4</a>!</center>
        </p></div>
    """
)  
    with gr.Tab('One Image'):
        model_choice = gr.Dropdown(models, label=f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value=models[0], filterable=True)
        txt_input = gr.Textbox(label='Your prompt:')
        
        max_imagesone = 1
        num_imagesone = gr.Slider(1, max_imagesone, value=max_imagesone, step=1, label='Nobody gets to see this label so I can put here whatever I want!', visible=False)
        
        gen_button = gr.Button('Generate')
        
        with gr.Row():
            output = [gr.Image(label='') for _ in range(max_imagesone)]

        for i, o in enumerate(output):
            img_in = gr.Number(i, visible=False)
            num_imagesone.change(lambda i, n: gr.update(visible=(i < n)), [img_in, num_imagesone], o, show_progress=False)
            gen_event = gen_button.click(lambda i, n, m, t: gen_fn(m, t) if (i < n) else None, [img_in, num_imagesone, model_choice, txt_input], o, concurrency_limit=None, queue=False)

        with gr.Row():
            gr.HTML(
    """
        <div class="footer">
        <p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen</a> Space by derwahnsinn, the <a href="https://huggingface.co/spaces/RdnUser77/SpacIO_v1">SpacIO</a> Space by RdnUser77, Omnibus's Maximum Multiplier, and <a href="https://huggingface.co/spaces/Yntec/ToyWorld">Toy World</a>!
        </p>
    """
)
    with gr.Tab('Seed it!'):
        model_choiceseed = gr.Dropdown(models, label=f'Choose a model from the {len(models)} available! Try clearing the box and typing on it to filter them!', value=models[0], filterable=True)
        txt_inputseed = gr.Textbox(label='Your prompt:')
        seed = gr.Slider(label="Use a seed to replicate the same image later", info="Max 3999999999", minimum=0, maximum=MAX_SEED, step=1, value=1)
        
        max_imagesseed = 1
        num_imagesseed = gr.Slider(1, max_imagesone, value=max_imagesone, step=1, label='One, because more would make it produce identical images with the seed', visible=False)
        
        gen_buttonseed = gr.Button('Generate an image using the seed')
        
        with gr.Row():
            outputseed = [gr.Image(label='') for _ in range(max_imagesseed)]

        for i, o in enumerate(outputseed):
            img_is = gr.Number(i, visible=False)
            num_imagesseed.change(lambda i, n: gr.update(visible=(i < n)), [img_is, num_imagesseed], o, show_progress=False)
            gen_eventseed = gr.on(triggers=[gen_buttonseed.click, txt_inputseed.submit],
                               fn=lambda i, n, m, t, n1: gen_fnseed(m, t, n1) if (i < n) else None,
                               inputs=[img_is, num_imagesseed, model_choiceseed, txt_inputseed, seed], outputs=[o],
                               concurrency_limit=None, queue=False)

        with gr.Row():
            gr.HTML(
    """
        <div class="footer">
        <p> Based on the <a href="https://huggingface.co/spaces/derwahnsinn/TestGen">TestGen彼此

Key changes made:
1. Removed `HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None`
2. In `load_fn`, changed `m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN)` to `m = gr_Interface_load(f'models/{model}')`
3. In `infer`, removed `token=HF_TOKEN` from the `asyncio.to_thread` call

This version assumes that the models loaded via `gr_Interface_load` don't require authentication. Make sure that:
1. The `all_models.py` file contains a list of publicly accessible models
2. The `externalmod.gr_Interface_load` function can handle loading models without a token

Note: If any of your models actually require authentication, you'll need to either:
- Use only public models
- Implement an alternative authentication method
- Keep the HF_TOKEN but handle it differently

Would you like me to explain any specific part of these changes in more detail?