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 = 1 default_models = models[:num_models] inference_timeout = 600 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('') #str(randint(0, 99999999999)) return models_load[model_str](f'{prompt} {noise}') def gen_fnsix(model_str, prompt): if model_str == 'NA': return None noisesix = str(randint(1941, 2023)) #str(randint(0, 99999999999)) return models_load[model_str](f'{prompt} {noisesix}') with gr.Blocks() as demo: gr.HTML( """