Update app.py
Browse files
app.py
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import gradio as gr
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from model import models
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from multit2i import (
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change_model, warm_model, get_model_info_md, loaded_models,
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get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
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get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en
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#
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def set_hf_token(hf_token):
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"""Функция для установки HF_TOKEN и проверки его активации"""
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if hf_token:
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os.environ["HF_TOKEN"] = hf_token #
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return f"✅ HF_TOKEN установлен!", gr.update(value=hf_token, interactive=True)
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else:
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return "❌ Токен не введен!", gr.update(value="", interactive=True)
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#
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#
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token_status = gr.Markdown("🔴 HF_TOKEN не установлен")
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# Подключаем обработчик кнопки
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confirm_token.click(set_hf_token, inputs=[hf_token_input], outputs=[token_status, hf_token_input])
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# Вставляем эти элементы в твой UI
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with gr.Blocks(theme="NoCrypt/miku@>=1.2.2") as demo:
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with gr.Tab("Settings"):
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gr.Markdown("### Настройки токена Hugging Face")
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hf_token_input.render() # Поле ввода
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confirm_token.render() # Кнопка активации
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token_status.render() # Статус токена
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max_images = 8
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MAX_SEED = 2**32-1
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load_models(models)
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css = """
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.model_info { text-align: center; }
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.output { width=112px; height=112px; max_width=112px; max_height=112px; !important; }
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.gallery { min_width=512px; min_height=512px; max_height=1024px; !important; }
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"""
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with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
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with gr.Tab("Image Generator"):
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with gr.Row():
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with gr.Column(scale=10):
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@@ -61,13 +48,13 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
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with gr.Accordion("Advanced options", open=False):
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neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")
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with gr.Row():
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width = gr.Slider(label="Width",
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height = gr.Slider(label="Height",
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steps = gr.Slider(label="
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with gr.Row():
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cfg = gr.Slider(label="Guidance scale",
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seed = gr.Slider(label="Seed",
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seed_rand = gr.Button("Randomize Seed
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recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
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with gr.Row():
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positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
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run_button = gr.Button("Generate Image", variant="primary", scale=8)
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random_button = gr.Button("Random Model 🎲", variant="secondary", scale=3)
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stop_button = gr.Button('Stop', interactive=False, variant="stop", scale=1)
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with gr.Group():
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model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
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model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
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with gr.Column(scale=10):
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with gr.Group():
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with gr.Row():
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@@ -97,83 +84,31 @@ with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
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container=True, format="png", object_fit="cover", columns=2, rows=2)
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image_files = gr.Files(label="Download", interactive=False)
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clear_results = gr.Button("Clear Gallery / Download 🗑️", variant="secondary")
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with gr.Column():
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examples = gr.Examples(
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examples = [
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["souryuu asuka langley, 1girl, neon genesis evangelion, plugsuit, pilot suit, red bodysuit, sitting, crossing legs, black eye patch, cat hat, throne, symmetrical, looking down, from bottom, looking at viewer, outdoors"],
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["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
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["kafuu chino, 1girl, solo"],
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["1girl"],
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["beautiful sunset"],
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],
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inputs=[prompt],
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cache_examples=False,
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)
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with gr.Tab("PNG Info"):
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def extract_exif_data(image):
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if image is None: return ""
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try:
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metadata_keys = ['parameters', 'metadata', 'prompt', 'Comment']
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for key in metadata_keys:
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if key in image.info:
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return image.info[key]
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return str(image.info)
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except Exception as e:
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return f"Error extracting metadata: {str(e)}"
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with gr.Row():
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with gr.Column():
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image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
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with gr.Column():
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result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
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inputs=[image_metadata],
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outputs=[result_metadata],
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)
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gr.Markdown(
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f"""This demo was created in reference to the following demos.<br>
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[Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood),
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[Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL),
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[Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX).
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"""
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)
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gr.DuplicateButton(value="Duplicate Space")
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gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.")
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gr.on(triggers=[run_button.click, prompt.submit, random_button.click], fn=lambda: gr.update(interactive=True), inputs=None, outputs=stop_button, show_api=False)
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model_name.change(change_model, [model_name], [model_info], queue=True, show_api=True)\
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.success(warm_model, [model_name], None, queue=True, show_api=True)
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for i, o in enumerate(output):
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img_i = gr.Number(i, visible=False)
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image_num.change(lambda i, n: gr.update(visible
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gen_event = gr.on(
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clear_prompt.click(lambda: (None, None), None, [prompt, neg_prompt], queue=True, show_api=True)
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clear_results.click(lambda: (None, None), None, [results, image_files], queue=True, show_api=True)
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recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
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seed_rand.click(randomize_seed, None, [seed], queue=True
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trans_prompt.click(translate_to_en, [prompt], [prompt], queue=True
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.then(translate_to_en, [neg_prompt], [neg_prompt], queue=True
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demo.queue(default_concurrency_limit=240, max_size=240)
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demo.launch(max_threads=400, ssr_mode=True)
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# https://github.com/gradio-app/gradio/issues/6339
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demo.queue(concurrency_count=50)
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demo.launch()
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import gradio as gr
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import os
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from model import models
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from multit2i import (
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load_models, infer_fn, infer_rand_fn, save_gallery,
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change_model, warm_model, get_model_info_md, loaded_models,
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get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
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get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en
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)
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# Устанавливаем максимальные значения
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max_images = 8
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MAX_SEED = 2**32 - 1
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load_models(models)
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# CSS для оформления
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css = """
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.model_info { text-align: center; }
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.output { width=112px; height=112px; max_width=112px; max_height=112px; !important; }
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.gallery { min_width=512px; min_height=512px; max_height=1024px; !important; }
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"""
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# Функция установки HF_TOKEN
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def set_hf_token(hf_token):
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if hf_token:
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os.environ["HF_TOKEN"] = hf_token # Сохраняем токен в окружении
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return f"✅ HF_TOKEN установлен!", gr.update(value=hf_token, interactive=True)
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else:
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return "❌ Токен не введен!", gr.update(value="", interactive=True)
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# Основной интерфейс
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with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
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with gr.Tab("Settings"): # Вкладка для настройки HF_TOKEN
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gr.Markdown("### Настройки токена Hugging Face")
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hf_token_input = gr.Textbox(label="Введите HF Token", type="password", interactive=True)
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confirm_token = gr.Button("Активировать HF_TOKEN")
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token_status = gr.Markdown("🔴 HF_TOKEN не установлен")
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confirm_token.click(set_hf_token, inputs=[hf_token_input], outputs=[token_status, hf_token_input])
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with gr.Tab("Image Generator"):
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with gr.Row():
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with gr.Column(scale=10):
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with gr.Accordion("Advanced options", open=False):
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neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")
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with gr.Row():
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width = gr.Slider(label="Width", maximum=2048, step=32, value=0)
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height = gr.Slider(label="Height", maximum=2048, step=32, value=0)
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steps = gr.Slider(label="Inference steps", maximum=100, step=1, value=0)
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with gr.Row():
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cfg = gr.Slider(label="Guidance scale", maximum=30.0, step=0.1, value=0)
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seed = gr.Slider(label="Seed", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
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seed_rand = gr.Button("🎲 Randomize Seed", size="sm", variant="secondary")
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recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
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with gr.Row():
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positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
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run_button = gr.Button("Generate Image", variant="primary", scale=8)
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random_button = gr.Button("Random Model 🎲", variant="secondary", scale=3)
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stop_button = gr.Button('Stop', interactive=False, variant="stop", scale=1)
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with gr.Group():
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model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
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model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
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with gr.Column(scale=10):
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with gr.Group():
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with gr.Row():
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container=True, format="png", object_fit="cover", columns=2, rows=2)
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image_files = gr.Files(label="Download", interactive=False)
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clear_results = gr.Button("Clear Gallery / Download 🗑️", variant="secondary")
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model_name.change(change_model, [model_name], [model_info], queue=True)\
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.success(warm_model, [model_name], None, queue=True)
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for i, o in enumerate(output):
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img_i = gr.Number(i, visible=False)
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image_num.change(lambda i, n: gr.update(visible=(i < n)), [img_i, image_num], o)
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gen_event = gr.on(
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triggers=[run_button.click, prompt.submit],
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fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_fn(m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4) if (i < n) else None,
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inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
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positive_prefix, positive_suffix, negative_prefix, negative_suffix],
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outputs=[o], queue=True
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)
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o.change(save_gallery, [o, results], [results, image_files])
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stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event])
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clear_prompt.click(lambda: (None, None), None, [prompt, neg_prompt], queue=True)
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clear_results.click(lambda: (None, None), None, [results, image_files], queue=True)
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recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
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[positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=True)
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seed_rand.click(randomize_seed, None, [seed], queue=True)
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trans_prompt.click(translate_to_en, [prompt], [prompt], queue=True)\
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.then(translate_to_en, [neg_prompt], [neg_prompt], queue=True)
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# Запуск интерфейса
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demo.queue(default_concurrency_limit=240, max_size=240)
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demo.launch(max_threads=400, ssr_mode=True)
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