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from PIL import Image |
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import gradio as gr |
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from random import randint |
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import torch |
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import os |
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os.environ["CUDA_VISIBLE_DEVICES"] = "" |
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device = "cpu" |
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model_repo_id = "stabilityai/sdxl-turbo" |
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torch_dtype = torch.float32 |
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models = [ |
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'stabilityai/stable-diffusion-3.5-large-turbo', |
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'black-forest-labs/FLUX.1-dev', |
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'strangerzonehf/Flux-Isometric-3D-LoRA', |
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'ckpt/kivotos-xl-2.0', |
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'stabilityai/stable-diffusion-3.5-large', |
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'yodayo-ai/clandestine-xl-1.0', |
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'yodayo-ai/kivotos-xl-2.0', |
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'yodayo-ai/holodayo-xl-2.1', |
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'prithivMLmods/SD3.5-Large-Anime-LoRA', |
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'FluffyKaeloky/Midnight-Miqu-103B-v1.5', |
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'cagliostrolab/animagine-xl-3.1', |
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'votepurchase/ponyDiffusionV6XL', |
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'eienmojiki/Anything-XL', |
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'eienmojiki/Starry-XL-v5.2', |
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"digiplay/MilkyWonderland_v1", |
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'Sombressoul/Yi-34B-200K-AWQ', |
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'digiplay/majicMIX_realistic_v7', |
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'votepurchase/counterfeitV30_v30', |
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'Linaqruf/animagine-xl-2.0', |
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'KBlueLeaf/Kohaku-XL-Epsilon-rev3', |
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'KBlueLeaf/Kohaku-XL-Zeta', |
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'kayfahaarukku/UrangDiffusion-1.4', |
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'Eugeoter/artiwaifu-diffusion-2.0', |
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'Raelina/Rae-Diffusion-XL-V2', |
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'Raelina/Raemu-XL-V4', |
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'Jonjew/NSFWMaster', |
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] |
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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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def make_me(): |
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with gr.Row(): |
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with gr.Column(scale=10): |
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with gr.Group(): |
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prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True) |
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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", info="If 0, the default value is used.", maximum=1216, step=32, value=0) |
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height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0) |
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steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0) |
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with gr.Row(): |
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cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0) |
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seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", 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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positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"]) |
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negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[]) |
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negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"]) |
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with gr.Row(): |
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image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=2) |
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trans_prompt = gr.Button(value="Translate 📝", variant="secondary", size="sm", scale=2) |
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clear_prompt = gr.Button(value="Clear 🗑️", variant="secondary", size="sm", scale=1) |
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with gr.Row(): |
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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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output = [gr.Image(label='', elem_classes="output", type="filepath", format="png", |
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show_download_button=True, show_share_button=False, show_label=False, |
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interactive=False, min_width=80, visible=True, width=112, height=112) for _ in range(max_images)] |
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with gr.Group(): |
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results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False, |
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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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image_metadata.change( |
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fn=extract_exif_data, |
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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 = (i < n)), [img_i, image_num], o, show_api=True) |
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gen_event = gr.on(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, show_api=False) |
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gen_event2 = gr.on(triggers=[random_button.click], |
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fn=lambda i, n, m, t1, t2, n1, n2, n3, n4, n5, l1, l2, l3, l4: infer_rand_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, show_api=False) |
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o.change(save_gallery, [o, results], [results, image_files], show_api=False) |
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stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False) |
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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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[positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=True, show_api=True) |
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seed_rand.click(randomize_seed, None, [seed], queue=True, show_api=True) |
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trans_prompt.click(translate_to_en, [prompt], [prompt], queue=True, show_api=True)\ |
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.then(translate_to_en, [neg_prompt], [neg_prompt], queue=True, show_api=True) |
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with gr.Row(): |
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gr.HTML("") |
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custom_css = """ |
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:root { |
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--body-background-fill: #2d3d4f; |
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} |
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body { |
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background-color: var(--body-background-fill) !important; |
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color: #2d3d4f; |
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margin: 0; |
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padding: 0; |
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font-family: Arial, sans-serif; |
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height: 100vh; |
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overflow-y: auto; |
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} |
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.gradio-container { |
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background-color: #2d3d4f; |
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color: #c5c6c7; |
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padding: 20px; |
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border-radius: 8px; |
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2); |
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width: 100%; |
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max-width: 1200px; |
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margin: 20px auto; |
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display: block; |
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min-height: 100vh; |
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} |
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.app_title { |
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background-color: #2d3d4f; |
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color: #c5c6c7; |
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padding: 10px 20px; |
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border-bottom: 1px solid #3b4252; |
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text-align: center; |
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font-size: 24px; |
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font-weight: bold; |
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width: 100%; |
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box-sizing: border-box; |
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margin-bottom: 20px; |
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} |
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.custom_textbox { |
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background-color: #2d343f; |
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border: 1px solid #3b4252; |
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color: #7f8184; |
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padding: 10px; |
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border-radius: 4px; |
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margin-bottom: 10px; |
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width: 100%; |
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box-sizing: border-box; |
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} |
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.custom_gen_button { |
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background-color: #8b38ff; |
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border: 1px solid #ffffff; |
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color: blue; |
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padding: 15px 32px; |
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text-align: center; |
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text-decoration: none; |
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display: inline-block; |
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font-size: 16px; |
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margin: 4px 2px; |
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cursor: pointer; |
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2); |
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transition: transform 0.2s, box-shadow 0.2s; |
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border-radius: 4px; |
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} |
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.custom_gen_button:hover { |
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transform: translateY(-2px); |
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box-shadow: 0 6px 10px rgba(0, 0, 0, 0.3); |
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} |
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.custom_stop_button { |
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background-color: #6200ea; |
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border: 1px solid #ffffff; |
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color: blue; |
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padding: 15px 32px; |
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text-align: center; |
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text-decoration: none; |
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display: inline-block; |
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font-size: 16px; |
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margin: 4px 2px; |
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cursor: pointer; |
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2); |
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transition: transform 0.2s, box-shadow 0.2s; |
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border-radius: 4px; |
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} |
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.custom_stop_button:hover { |
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transform: translateY(-2px); |
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box-shadow: 0 6px 10px rgba(0, 0, 0, 0.3); |
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} |
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.custom_image { |
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border: 1px solid #3b4252; |
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background-color: #2d343f; |
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border-radius: 4px; |
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margin: 10px; |
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max-width: 100%; |
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box-sizing: border-box; |
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} |
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.custom_accordion { |
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background-color: #2d3d4f; |
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color: #7f8184; |
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border: 1px solid #3b4252; |
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border-radius: 4px; |
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margin-top: 20px; |
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width: 100%; |
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box-sizing: border-box; |
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transition: margin 0.2s ease; |
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} |
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.custom_accordion .gr-accordion-header { |
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background-color: #2d3d4f; |
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color: #7f8184; |
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padding: 10px 20px; |
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border-bottom: 1px solid #5b6270; |
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cursor: pointer; |
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font-size: 18px; |
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font-weight: bold; |
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height: 40px; |
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display: flex; |
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align-items: center; |
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} |
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.custom_accordion .gr-accordion-header:hover { |
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background-color: #2d3d4f; |
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} |
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.custom_accordion .gr-accordion-content { |
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padding: 10px 20px; |
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background-color: #2d3d4f; |
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border-top: 1px solid #5b6270; |
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max-height: 0; |
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overflow: hidden; |
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transition: max-height 0.2s ease; |
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} |
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.custom_accordion .gr-accordion-content.open { |
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max-height: 500px; |
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} |
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.custom_checkbox_group { |
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background-color: #2d343f; |
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border: 1px solid #3b4252; |
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color: #7f8184; |
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border-radius: 4px; |
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padding: 10px; |
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width: 100%; |
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box-sizing: border-box; |
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} |
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@media (max-width: 768px) { |
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.gradio-container { |
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width: 100%; |
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margin: 0; |
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padding: 10px; |
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} |
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.custom_textbox,.custom_image,.custom_checkbox_group { |
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width: 100%; |
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box-sizing: border-box; |
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} |
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} |
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""" |
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with gr.Blocks(css=custom_css) as demo: |
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make_me() |
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demo.queue(default_concurrency_limit=340, max_size=400) |
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demo.launch(max_threads=400, ssr_mode=False) |
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demo.queue(concurrency_count=50) |
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demo.launch() |