Spaces:
Running
Running
| import gradio as gr | |
| from random import randint | |
| from all_models import models | |
| from datetime import datetime | |
| now2 = 0 | |
| kii=" needs async iterative function for all models selected to go to appropriate output boxes, because gradio update lost multiselect? OR not. where am i, how did i find myself here, what is this strange language"; | |
| def get_current_time(): | |
| now = datetime.now() | |
| now2 = now | |
| current_time = now2.strftime("%Y-%m-%d %H:%M:%S") | |
| ki = f'{kii} {current_time}' | |
| return ki | |
| 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 = len(models) | |
| 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=(m != 'NA')) for m in choices_plus] | |
| def gen_fn(model_str, prompt): | |
| if model_str == 'NA': | |
| return None | |
| noise = str(randint(0, 9999)) | |
| return models_load[model_str](f'{prompt} {noise}') | |
| def process_choices(selected_choices): | |
| results = [] | |
| for choice in selected_choices: | |
| results.append(f"Processed data for {choice}") # Example output for each model | |
| return results # Return a separate output for each choice | |
| def make_me(): | |
| with gr.Row(): | |
| txt_input = gr.Textbox(lines=2, value=kii) | |
| #txt_input = gr.Textbox(label='Your prompt:', lines=2, value=kii) | |
| gen_button = gr.Button('Generate images') | |
| stop_button = gr.Button('Stop', variant='secondary', interactive=False) | |
| gen_button.click(lambda s: gr.update(interactive=True), None, stop_button) | |
| gr.HTML(""" | |
| <div style="text-align: center; max-width: 100%; margin: 0 auto;"> | |
| <body> | |
| </body> | |
| </div> | |
| """) | |
| 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] | |
| for m, o in zip(current_models, output): | |
| gen_event = gen_button.click(gen_fn, [m, txt_input], o) | |
| stop_button.click(lambda s: gr.update(interactive=False), None, stop_button, cancels=[gen_event]) | |
| with gr.Accordion('Model selection'): | |
| # model_choice = gr.CheckboxGroup(models, label=f' {num_models} different models selected', value=default_models, multiselect=True, interactive=True, filterable=False) | |
| model_choice = gr.CheckboxGroup(models, label=f' {num_models} different models selected', value=default_models, interactive=True ) | |
| model_choice.change(update_imgbox, model_choice, output) | |
| model_choice.change(extend_choices, model_choice, current_models) | |
| 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 and Omnibus's Maximum Multiplier! | |
| </p> | |
| """) | |
| js_code = """ | |
| console.log('testing js_code'); | |
| """ | |
| with gr.Blocks(css=""" | |
| label.float.svelte-i3tvor { top:auto!important; bottom: 0; position: absolute; background: rgba(0,0,0,0.0); left: var(--block-label-margin); color: rgba(200,200,200,.7);} | |
| .genbut { max-width: 50px; max-height: 30px; width:150px; height:30px} | |
| .stopbut { max-width: 50px; max-height: 30px; width:150px; height:30px} | |
| .float.svelte-1mwvhlq { position: absolute; top: var(--block-label-margin); left: var(--block-label-margin); background: none; border: none;} | |
| """) as demo: | |
| gr.Markdown("<script>" + js_code + "</script>") | |
| make_me() | |
| demo.queue() | |
| demo.launch(max_threads=200 ) | |
| # output = [gr.Image(label=m, height=170) for m in default_models] | |
| #demo.queue(concurrency_count=200) | |
| #demo.launch() | |