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() 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. 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}', hf_token=HF_TOKEN) except Exception as error: print(error) m = gr.Interface(lambda: None, ['text'], ['image']) models_load.update({model: m}) load_fn(models) num_models = 6 default_models = models[:num_models] inference_timeout = 600 def extend_choices(choices): return choices[:num_models] + (num_models - len(choices[:num_models])) * ['NA'] def update_imgbox(choices): choices_plus = extend_choices(choices[:num_models]) 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('') #str(randint(0, 99999999999)) return models_load[model_str](f'{prompt} {noise}') with gr.Blocks() as demo: with gr.Tab('🤗 Huggingface Diffusion 🤗'): txt_input = gr.Textbox(label='Your prompt:', lines=4) gen_button = gr.Button('Generate up to 6 images in up to 3 minutes total') #stop_button = gr.Button('Stop', variant = 'secondary', interactive = False) gen_button.click(lambda s: gr.update(interactive = True), None) gr.HTML( """
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