import gradio as gr from random import randint from all_models import models def load_fn(models): global models_load models_load = {} for model in models: if model not in models_load.keys(): try: m = gr.load(f'models/{model}') except Exception as error: m = gr.Interface(lambda txt: None, ['text'], ['image']) models_load.update({model: m}) load_fn(models) num_models = 6 default_models = models[:num_models] 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 = (o != 'NA')) for m in choices_plus] def gen_fn(model_str, prompt): if model_str == 'NA': return None noise = str(randint(0, 99999999999)) return models_load[model_str](f'{prompt} {noise}') with gr.Blocks() as demo: with gr.Tab('Multiple models'): with gr.Accordion('Model selection'): model_choice = gr.Dropdown(models, label = f'Choose up to {num_models} different models', value = default_models, multiselect = True, max_choices = num_models, interactive = True) txt_input = gr.Textbox(label = 'Prompt text') gen_button = gr.Button('Generate') with gr.Row(): output = [gr.Image(label = m) for m in default_models] current_models = [gr.Textbox(m, visible = False) for m in default_models] model_choice.change(update_imgbox, model_choice, output) model_choice.change(extend_choices, model_choice, current_models) for m, o in zip(current_models, output): gen_button.click(gen_fn, [m, txt_input], o) with gr.Tab('Single model'): model_choice2 = gr.Dropdown(models, label = 'Choose model', value = models[0], filterable = False) txt_input2 = gr.Textbox(label = 'Prompt text') gen_button2 = gr.Button('Generate') with gr.Row(): num_images = 6 output2 = [gr.Image(label = '') for _ in range(num_images)] for o in output2: gen_button2.click(gen_fn, [model_choice2, txt_input2], o) demo.queue(concurrency_count = 36) demo.launch()