Update app.py

app.py

@@ -1,186 +1,179 @@
-import gradio as gr
-from model import models
-from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery,
-    change_model, warm_model, get_model_info_md, loaded_models, warm_models,
-    get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
-    get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en)
-from tagger.tagger import (predict_tags_wd, remove_specific_prompt, convert_danbooru_to_e621_prompt,
-    insert_recom_prompt, compose_prompt_to_copy)
-from tagger.fl2sd3longcap import predict_tags_fl2_sd3
-from tagger.v2 import V2_ALL_MODELS, v2_random_prompt
-from tagger.utils import (V2_ASPECT_RATIO_OPTIONS, V2_RATING_OPTIONS,
-    V2_LENGTH_OPTIONS, V2_IDENTITY_OPTIONS)
-
-max_images = 6
-MAX_SEED = 2**32-1
-load_models(models)
-warm_models(models[0:max_images])
-
-css = """
-.title { font-size: 3em; align-items: center; text-align: center; }
-.info { align-items: center; text-align: center; }
-.model_info { text-align: center; }
-.output { width=112px; height=112px; max_width=112px; max_height=112px; !important; }
-.gallery { min_width=512px; min_height=512px; max_height=1024px; !important; }
-"""
-
-with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
-    with gr.Tab("Image Generator"):
-        with gr.Row():
-            with gr.Column(scale=10): 
-                with gr.Group():
-                    with gr.Accordion("Prompt from Image File", open=False):
-                        tagger_image = gr.Image(label="Input image", type="pil", format="png", sources=["upload", "clipboard"], height=256)
-                        with gr.Accordion(label="Advanced options", open=False):
-                            with gr.Row(equal_height=True):
-                                tagger_general_threshold = gr.Slider(label="Threshold", minimum=0.0, maximum=1.0, value=0.3, step=0.01, interactive=True)
-                                tagger_character_threshold = gr.Slider(label="Character threshold", minimum=0.0, maximum=1.0, value=0.8, step=0.01, interactive=True)
-                                tagger_tag_type = gr.Radio(label="Convert tags to", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru")
-                            with gr.Row(equal_height=True):
-                                tagger_recom_prompt = gr.Radio(label="Insert reccomended prompt", choices=["None", "Animagine", "Pony"], value="None", interactive=True)  
-                                tagger_keep_tags = gr.Radio(label="Remove tags leaving only the following", choices=["body", "dress", "all"], value="all")
-                        tagger_algorithms = gr.CheckboxGroup(["Use WD Tagger", "Use Florence-2-SD3-Long-Captioner"], label="Algorithms", value=["Use WD Tagger"])
-                        tagger_generate_from_image = gr.Button(value="Generate Tags from Image", variant="secondary")
-                    with gr.Accordion("Prompt Transformer", open=False):
-                        with gr.Row(equal_height=True):
-                            v2_character = gr.Textbox(label="Character", placeholder="hatsune miku", scale=2)
-                            v2_series = gr.Textbox(label="Series", placeholder="vocaloid", scale=2)
-                        with gr.Row(equal_height=True):
-                            v2_rating = gr.Radio(label="Rating", choices=list(V2_RATING_OPTIONS), value="sfw")
-                            v2_aspect_ratio = gr.Radio(label="Aspect ratio", info="The aspect ratio of the image.", choices=list(V2_ASPECT_RATIO_OPTIONS), value="square", visible=False)
-                            v2_length = gr.Radio(label="Length", info="The total length of the tags.", choices=list(V2_LENGTH_OPTIONS), value="long")
-                        with gr.Row(equal_height=True):
-                            v2_identity = gr.Radio(label="Keep identity", info="How strictly to keep the identity of the character or subject. If you specify the detail of subject in the prompt, you should choose `strict`. Otherwise, choose `none` or `lax`. `none` is very creative but sometimes ignores the input prompt.", choices=list(V2_IDENTITY_OPTIONS), value="lax")                    
-                            v2_ban_tags = gr.Textbox(label="Ban tags", info="Tags to ban from the output.", placeholder="alternate costumen, ...", value="censored")
-                            v2_tag_type = gr.Radio(label="Tag Type", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru", visible=False)
-                        v2_model = gr.Dropdown(label="Model", choices=list(V2_ALL_MODELS.keys()), value=list(V2_ALL_MODELS.keys())[0])
-                        v2_copy = gr.Button(value="Copy to clipboard", variant="secondary", size="sm", interactive=False)
-                        random_prompt = gr.Button(value="Extend 🎲", variant="secondary")
-                    prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True)
-                    with gr.Accordion("Advanced options", open=False):
-                        neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")
-                        with gr.Row(equal_height=True):
-                            width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                            height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0)
-                            steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0)
-                        with gr.Row(equal_height=True):
-                            cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0)
-                            seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1)
-                            seed_rand = gr.Button("Randomize Seed 🎲", size="sm", variant="secondary")
-                        recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
-                        with gr.Row(equal_height=True):
-                            positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
-                            positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"])
-                            negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[])
-                            negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"])
-                    with gr.Row(equal_height=True):
-                        image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=2)
-                        trans_prompt = gr.Button(value="Translate 📝", variant="secondary", size="sm", scale=2)
-                        clear_prompt = gr.Button(value="Clear 🗑️", variant="secondary", size="sm", scale=1)
-                    
-                with gr.Row(equal_height=True):
-                    run_button = gr.Button("Generate Image", variant="primary", scale=6)
-                    random_button = gr.Button("Random Model 🎲", variant="secondary", scale=3)
-                    #stop_button = gr.Button('Stop', variant="stop", interactive=False, scale=1)
-                with gr.Group():
-                    model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
-                    model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
-            with gr.Column(scale=10): 
-                with gr.Group():
-                    with gr.Row():
-                        output = [gr.Image(label='', elem_classes="output", type="filepath", format="png",
-                                show_download_button=True, show_share_button=False, show_label=False,
-                                interactive=False, min_width=80, visible=True, width=112, height=112) for _ in range(max_images)]
-                with gr.Group():
-                    results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False,
-                                        container=True, format="png", object_fit="cover", columns=2, rows=2)
-                    image_files = gr.Files(label="Download", interactive=False)
-                    clear_results = gr.Button("Clear Gallery / Download 🗑️", variant="secondary")
-        with gr.Column(): 
-            examples = gr.Examples(
-                examples = [
-                    ["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"],
-                    ["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
-                    ["kafuu chino, 1girl, solo"],
-                    ["1girl"],
-                    ["beautiful sunset"],
-                ],
-                inputs=[prompt],
-                cache_examples=False,
-            )
-    with gr.Tab("PNG Info"):
-        def extract_exif_data(image):
-            if image is None: return ""
-            try:
-                metadata_keys = ['parameters', 'metadata', 'prompt', 'Comment']
-                for key in metadata_keys:
-                    if key in image.info:
-                        return image.info[key]
-                return str(image.info)
-            except Exception as e:
-                return f"Error extracting metadata: {str(e)}"
-        with gr.Row():
-            with gr.Column():
-                image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
-            with gr.Column():
-                result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
-                image_metadata.change(
-                    fn=extract_exif_data,
-                    inputs=[image_metadata],
-                    outputs=[result_metadata],
-                )
-    gr.Markdown(
-        f"""This demo was created in reference to the following demos.<br>
-[Nymbo/Flood](https://huggingface.co/spaces/Nymbo/Flood), 
-[Yntec/ToyWorldXL](https://huggingface.co/spaces/Yntec/ToyWorldXL), 
-[Yntec/Diffusion80XX](https://huggingface.co/spaces/Yntec/Diffusion80XX).
-        """, elem_classes="info")
-    gr.DuplicateButton(value="Duplicate Space")
-    gr.Markdown(f"Just a few edits to *model.py* are all it takes to complete your own collection.", elem_classes="info")
-
-    #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)
-    model_name.change(change_model, [model_name], [model_info], queue=False, show_api=False)\
-    .success(warm_model, [model_name], None, queue=False, show_api=False)
-    for i, o in enumerate(output):
-        img_i = gr.Number(i, visible=False)
-        image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=False)
-        gen_event = gr.on(triggers=[run_button.click, prompt.submit],
-         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,
-         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
-                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
-         outputs=[o], queue=False, show_api=False)  # Be sure to delete ", queue=False" when activating the stop button
-        gen_event2 = gr.on(triggers=[random_button.click],
-         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,
-         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
-                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
-         outputs=[o], queue=False, show_api=False)  # Be sure to delete ", queue=False" when activating the stop button
-        o.change(save_gallery, [o, results], [results, image_files], show_api=False)
-        #stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False)
-
-    clear_prompt.click(lambda: (None, None, None, None), None, [prompt, neg_prompt, v2_character, v2_series], queue=False, show_api=False)
-    clear_results.click(lambda: (None, None), None, [results, image_files], queue=False, show_api=False)
-    recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
-     [positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=False, show_api=False)
-    seed_rand.click(randomize_seed, None, [seed], queue=False, show_api=False)
-    trans_prompt.click(translate_to_en, [prompt], [prompt], queue=False, show_api=False)\
-    .then(translate_to_en, [neg_prompt], [neg_prompt], queue=False, show_api=False)
-
-    random_prompt.click(
-        v2_random_prompt, [prompt, v2_series, v2_character, v2_rating, v2_aspect_ratio, v2_length,
-          v2_identity, v2_ban_tags, v2_model], [prompt, v2_series, v2_character], show_api=False,
-    ).success(get_tag_type, [positive_prefix, positive_suffix, negative_prefix, negative_suffix], [v2_tag_type], queue=False, show_api=False
-    ).success(convert_danbooru_to_e621_prompt, [prompt, v2_tag_type], [prompt], queue=False, show_api=False)
-    tagger_generate_from_image.click(lambda: ("", "", ""), None, [v2_series, v2_character, prompt], queue=False, show_api=False,
-    ).success(
-        predict_tags_wd,
-        [tagger_image, prompt, tagger_algorithms, tagger_general_threshold, tagger_character_threshold],
-        [v2_series, v2_character, prompt, v2_copy],
-        show_api=False,
-    ).success(predict_tags_fl2_sd3, [tagger_image, prompt, tagger_algorithms], [prompt], show_api=False,
-    ).success(remove_specific_prompt, [prompt, tagger_keep_tags], [prompt], queue=False, show_api=False,
-    ).success(convert_danbooru_to_e621_prompt, [prompt, tagger_tag_type], [prompt], queue=False, show_api=False,
-    ).success(insert_recom_prompt, [prompt, neg_prompt, tagger_recom_prompt], [prompt, neg_prompt], queue=False, show_api=False,
-    ).success(compose_prompt_to_copy, [v2_character, v2_series, prompt], [prompt], queue=False, show_api=False)
-
-#demo.queue(default_concurrency_limit=200, max_size=200)
-demo.launch(max_threads=400, ssr_mode=False)
+import gradio as gr
+from model import models
+from multit2i import (load_models, infer_fn, infer_rand_fn, save_gallery,
+    change_model, warm_model, get_model_info_md, loaded_models, warm_models,
+    get_positive_prefix, get_positive_suffix, get_negative_prefix, get_negative_suffix,
+    get_recom_prompt_type, set_recom_prompt_preset, get_tag_type, randomize_seed, translate_to_en)
+from tagger.tagger import (predict_tags_wd, remove_specific_prompt, convert_danbooru_to_e621_prompt,
+    insert_recom_prompt, compose_prompt_to_copy)
+from tagger.fl2sd3longcap import predict_tags_fl2_sd3
+from tagger.v2 import V2_ALL_MODELS, v2_random_prompt
+from tagger.utils import (V2_ASPECT_RATIO_OPTIONS, V2_RATING_OPTIONS,
+    V2_LENGTH_OPTIONS, V2_IDENTITY_OPTIONS)
+
+max_images = 6
+MAX_SEED = 2**32-1
+load_models(models)
+warm_models(models[0:max_images])
+
+css = """
+.title { font-size: 3em; align-items: center; text-align: center; }
+.info { align-items: center; text-align: center; }
+.model_info { text-align: center; }
+.output { width=112px; height=112px; max_width=112px; max_height=112px; !important; }
+.gallery { min_width=512px; min_height=512px; max_height=1024px; !important; }
+"""
+
+with gr.Blocks(theme="NoCrypt/miku@>=1.2.2", fill_width=True, css=css) as demo:
+    with gr.Tab("Image Generator"):
+        with gr.Row():
+            with gr.Column(scale=10): 
+                with gr.Group():
+                    with gr.Accordion("Prompt from Image File", open=False):
+                        tagger_image = gr.Image(label="Input image", type="pil", format="png", sources=["upload", "clipboard"], height=256)
+                        with gr.Accordion(label="Advanced options", open=False):
+                            with gr.Row(equal_height=True):
+                                tagger_general_threshold = gr.Slider(label="Threshold", minimum=0.0, maximum=1.0, value=0.3, step=0.01, interactive=True)
+                                tagger_character_threshold = gr.Slider(label="Character threshold", minimum=0.0, maximum=1.0, value=0.8, step=0.01, interactive=True)
+                                tagger_tag_type = gr.Radio(label="Convert tags to", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru")
+                            with gr.Row(equal_height=True):
+                                tagger_recom_prompt = gr.Radio(label="Insert reccomended prompt", choices=["None", "Animagine", "Pony"], value="None", interactive=True)  
+                                tagger_keep_tags = gr.Radio(label="Remove tags leaving only the following", choices=["body", "dress", "all"], value="all")
+                        tagger_algorithms = gr.CheckboxGroup(["Use WD Tagger", "Use Florence-2-SD3-Long-Captioner"], label="Algorithms", value=["Use WD Tagger"])
+                        tagger_generate_from_image = gr.Button(value="Generate Tags from Image", variant="secondary")
+                    with gr.Accordion("Prompt Transformer", open=False):
+                        with gr.Row(equal_height=True):
+                            v2_character = gr.Textbox(label="Character", placeholder="hatsune miku", scale=2)
+                            v2_series = gr.Textbox(label="Series", placeholder="vocaloid", scale=2)
+                        with gr.Row(equal_height=True):
+                            v2_rating = gr.Radio(label="Rating", choices=list(V2_RATING_OPTIONS), value="sfw")
+                            v2_aspect_ratio = gr.Radio(label="Aspect ratio", info="The aspect ratio of the image.", choices=list(V2_ASPECT_RATIO_OPTIONS), value="square", visible=False)
+                            v2_length = gr.Radio(label="Length", info="The total length of the tags.", choices=list(V2_LENGTH_OPTIONS), value="long")
+                        with gr.Row(equal_height=True):
+                            v2_identity = gr.Radio(label="Keep identity", info="How strictly to keep the identity of the character or subject. If you specify the detail of subject in the prompt, you should choose `strict`. Otherwise, choose `none` or `lax`. `none` is very creative but sometimes ignores the input prompt.", choices=list(V2_IDENTITY_OPTIONS), value="lax")                    
+                            v2_ban_tags = gr.Textbox(label="Ban tags", info="Tags to ban from the output.", placeholder="alternate costumen, ...", value="censored")
+                            v2_tag_type = gr.Radio(label="Tag Type", info="danbooru for common, e621 for Pony.", choices=["danbooru", "e621"], value="danbooru", visible=False)
+                        v2_model = gr.Dropdown(label="Model", choices=list(V2_ALL_MODELS.keys()), value=list(V2_ALL_MODELS.keys())[0])
+                        v2_copy = gr.Button(value="Copy to clipboard", variant="secondary", size="sm", interactive=False)
+                        random_prompt = gr.Button(value="Extend 🎲", variant="secondary")
+                    prompt = gr.Text(label="Prompt", lines=2, max_lines=8, placeholder="1girl, solo, ...", show_copy_button=True)
+                    with gr.Accordion("Advanced options", open=False):
+                        neg_prompt = gr.Text(label="Negative Prompt", lines=1, max_lines=8, placeholder="")
+                        with gr.Row(equal_height=True):
+                            width = gr.Slider(label="Width",  maximum=1216, step=32, value=0)
+                            height = gr.Slider(label="Height",  maximum=1216, step=32, value=0)
+                            steps = gr.Slider(label="Number of inference steps", maximum=100, step=1, value=0)
+                        with gr.Row(equal_height=True):
+                            cfg = gr.Slider(label="Guidance scale", maximum=30.0, step=0.1, value=0)
+                            seed = gr.Slider(label="Seed",  minimum=-1, maximum=MAX_SEED, step=1, value=-1)
+                            seed_rand = gr.Button("Randomize Seed 🎲", size="sm", variant="secondary")
+                        recom_prompt_preset = gr.Radio(label="Set Presets", choices=get_recom_prompt_type(), value="Common")
+                        with gr.Row(equal_height=True):
+                            positive_prefix = gr.CheckboxGroup(label="Use Positive Prefix", choices=get_positive_prefix(), value=[])
+                            positive_suffix = gr.CheckboxGroup(label="Use Positive Suffix", choices=get_positive_suffix(), value=["Common"])
+                            negative_prefix = gr.CheckboxGroup(label="Use Negative Prefix", choices=get_negative_prefix(), value=[])
+                            negative_suffix = gr.CheckboxGroup(label="Use Negative Suffix", choices=get_negative_suffix(), value=["Common"])
+                    with gr.Row(equal_height=True):
+                        image_num = gr.Slider(label="Number of images", minimum=1, maximum=max_images, value=1, step=1, interactive=True, scale=2)
+                        trans_prompt = gr.Button(value="Translate 📝", variant="secondary", size="sm", scale=2)
+                        clear_prompt = gr.Button(value="Clear 🗑️", variant="secondary", size="sm", scale=1)
+                    
+                with gr.Row(equal_height=True):
+                    run_button = gr.Button("Generate Image", variant="primary", scale=6)
+                    random_button = gr.Button("Random Model 🎲", variant="secondary", scale=3)
+                    #stop_button = gr.Button('Stop', variant="stop", interactive=False, scale=1)
+                with gr.Group():
+                    model_name = gr.Dropdown(label="Select Model", choices=list(loaded_models.keys()), value=list(loaded_models.keys())[0], allow_custom_value=True)
+                    model_info = gr.Markdown(value=get_model_info_md(list(loaded_models.keys())[0]), elem_classes="model_info")
+            with gr.Column(scale=10): 
+                with gr.Group():
+                    with gr.Row():
+                        output = [gr.Image(label='', elem_classes="output", type="filepath", format="png",
+                                show_download_button=True, show_share_button=False, show_label=False,
+                                interactive=False, min_width=80, visible=True, width=112, height=112) for _ in range(max_images)]
+                with gr.Group():
+                    results = gr.Gallery(label="Gallery", elem_classes="gallery", interactive=False, show_download_button=True, show_share_button=False,
+                                        container=True, format="png", object_fit="cover", columns=2, rows=2)
+                    image_files = gr.Files(label="Download", interactive=False)
+                    clear_results = gr.Button("Clear Gallery / Download 🗑️", variant="secondary")
+        with gr.Column(): 
+            examples = gr.Examples(
+                examples = [
+                    ["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"],
+                    ["sailor moon, magical girl transformation, sparkles and ribbons, soft pastel colors, crescent moon motif, starry night sky background, shoujo manga style"],
+                    ["kafuu chino, 1girl, solo"],
+                    ["1girl"],
+                    ["beautiful sunset"],
+                ],
+                inputs=[prompt],
+                cache_examples=False,
+            )
+    with gr.Tab("PNG Info"):
+        def extract_exif_data(image):
+            if image is None: return ""
+            try:
+                metadata_keys = ['parameters', 'metadata', 'prompt', 'Comment']
+                for key in metadata_keys:
+                    if key in image.info:
+                        return image.info[key]
+                return str(image.info)
+            except Exception as e:
+                return f"Error extracting metadata: {str(e)}"
+        with gr.Row():
+            with gr.Column():
+                image_metadata = gr.Image(label="Image with metadata", type="pil", sources=["upload"])
+            with gr.Column():
+                result_metadata = gr.Textbox(label="Metadata", show_label=True, show_copy_button=True, interactive=False, container=True, max_lines=99)
+                image_metadata.change(
+                    fn=extract_exif_data,
+                    inputs=[image_metadata],
+                    outputs=[result_metadata],
+                )
+    gr.DuplicateButton(value="Duplicate Space")
+
+    #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)
+    model_name.change(change_model, [model_name], [model_info], queue=False, show_api=False)\
+    .success(warm_model, [model_name], None, queue=False, show_api=False)
+    for i, o in enumerate(output):
+        img_i = gr.Number(i, visible=False)
+        image_num.change(lambda i, n: gr.update(visible = (i < n)), [img_i, image_num], o, show_api=False)
+        gen_event = gr.on(triggers=[run_button.click, prompt.submit],
+         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,
+         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
+                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
+         outputs=[o], queue=False, show_api=False)  # Be sure to delete ", queue=False" when activating the stop button
+        gen_event2 = gr.on(triggers=[random_button.click],
+         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,
+         inputs=[img_i, image_num, model_name, prompt, neg_prompt, height, width, steps, cfg, seed,
+                  positive_prefix, positive_suffix, negative_prefix, negative_suffix],
+         outputs=[o], queue=False, show_api=False)  # Be sure to delete ", queue=False" when activating the stop button
+        o.change(save_gallery, [o, results], [results, image_files], show_api=False)
+        #stop_button.click(lambda: gr.update(interactive=False), None, stop_button, cancels=[gen_event, gen_event2], show_api=False)
+
+    clear_prompt.click(lambda: (None, None, None, None), None, [prompt, neg_prompt, v2_character, v2_series], queue=False, show_api=False)
+    clear_results.click(lambda: (None, None), None, [results, image_files], queue=False, show_api=False)
+    recom_prompt_preset.change(set_recom_prompt_preset, [recom_prompt_preset],
+     [positive_prefix, positive_suffix, negative_prefix, negative_suffix], queue=False, show_api=False)
+    seed_rand.click(randomize_seed, None, [seed], queue=False, show_api=False)
+    trans_prompt.click(translate_to_en, [prompt], [prompt], queue=False, show_api=False)\
+    .then(translate_to_en, [neg_prompt], [neg_prompt], queue=False, show_api=False)
+
+    random_prompt.click(
+        v2_random_prompt, [prompt, v2_series, v2_character, v2_rating, v2_aspect_ratio, v2_length,
+          v2_identity, v2_ban_tags, v2_model], [prompt, v2_series, v2_character], show_api=False,
+    ).success(get_tag_type, [positive_prefix, positive_suffix, negative_prefix, negative_suffix], [v2_tag_type], queue=False, show_api=False
+    ).success(convert_danbooru_to_e621_prompt, [prompt, v2_tag_type], [prompt], queue=False, show_api=False)
+    tagger_generate_from_image.click(lambda: ("", "", ""), None, [v2_series, v2_character, prompt], queue=False, show_api=False,
+    ).success(
+        predict_tags_wd,
+        [tagger_image, prompt, tagger_algorithms, tagger_general_threshold, tagger_character_threshold],
+        [v2_series, v2_character, prompt, v2_copy],
+        show_api=False,
+    ).success(predict_tags_fl2_sd3, [tagger_image, prompt, tagger_algorithms], [prompt], show_api=False,
+    ).success(remove_specific_prompt, [prompt, tagger_keep_tags], [prompt], queue=False, show_api=False,
+    ).success(convert_danbooru_to_e621_prompt, [prompt, tagger_tag_type], [prompt], queue=False, show_api=False,
+    ).success(insert_recom_prompt, [prompt, neg_prompt, tagger_recom_prompt], [prompt, neg_prompt], queue=False, show_api=False,
+    ).success(compose_prompt_to_copy, [v2_character, v2_series, prompt], [prompt], queue=False, show_api=False)
+
+#demo.queue(default_concurrency_limit=200, max_size=200)
+demo.launch(max_threads=400, ssr_mode=False)