import os import datetime import threading import time import json import toml import gradio as gr import shutil from huggingface_hub import HfApi, snapshot_download import pandas as pd from gradio.processing_utils import save_bytes_to_cache from gradio.utils import get_upload_folder from pnginfo import read_info_from_image, send_paras from images_history import img_history_ui from director_tools import director_ui, send_outputs from tagger import tagger_ui from utils import set_token, generate_novelai_image, image_from_bytes, get_remain_anlas, calculate_cost, vibe_encode, vibe_to_json, base642image client_config = toml.load("config.toml")['client'] today_count = 0 today = datetime.date.today().strftime('%Y-%m-%d') api = HfApi() def get_count(): global today_count, today now = datetime.date.today().strftime('%Y-%m-%d') if now != today: today = now today_count = 0 return today_count def change_schedule(sampler): if sampler == "ddim_v3": return gr.Dropdown(value="native", interactive=False) elif sampler == "k_dpmpp_2m": return gr.Dropdown(value="exponential", interactive=True) else: return gr.Dropdown(value="karras", interactive=True) def draw_position(x, y): string = ('⬜'*(5*(y - 1) + x -1) + '⬛').ljust(25, '⬜') out = '示例图


' + '
'.join([string[i:i+5] for i in range(0, 25, 5)]) + "

" return out def dynparas(*args): return list(args) def control_ui(): model = gr.Dropdown(choices=["nai-diffusion-3", "nai-diffusion-4-curated-preview", "nai-diffusion-furry-3", "nai-diffusion-4-full", "nai-diffusion-4-5-curated", "nai-diffusion-4-5-full"], value="nai-diffusion-4-5-full", label="模型") prompt = gr.TextArea(elem_id='txt2img_prompt', label="提示词", lines=3) quality_tags = gr.TextArea( elem_id='txt2img_qua_prompt', label="质量词", lines=1, value=client_config['default_quality'], ) neg_prompt = gr.TextArea( elem_id='txt2img_neg_prompt', label="负面词", lines=1, value=client_config['default_neg'], ) prompt.focus(fn=None, inputs=None, js="() => {run();}") quality_tags.focus(fn=None, inputs=None, js="() => {run();}") neg_prompt.focus(fn=None, inputs=None, js="() => {run();}") with gr.Column(): with gr.Accordion("参数设置", open=False): with gr.Row(): sampler = gr.Dropdown( choices=[ "k_euler", "k_euler_ancestral", "k_dpmpp_2s_ancestral", "k_dpmpp_2m_sde", "k_dpmpp_2m", "k_dpmpp_sde", "ddim_v3" ], value="k_euler", label="采样器", interactive=True ) scale = gr.Slider(label="CFG Scale", value=5.0, minimum=0, maximum=10, step=0.1) steps = gr.Slider(label="步数", value=28, minimum=1, maximum=50, step=1) with gr.Row(): seed = gr.Number(label="种子", value=-1, step=1, maximum=2**32-1, minimum=-1, scale=3) rand_seed = gr.Button('🎲️', scale=1) reuse_seed = gr.Button('♻️', scale=1) with gr.Row(): presets = gr.Dropdown(choices=['1024x1024', '832x1216', '1216x832', '768x1344', '1344x768'], value='1024x1024', label='预设比例', scale=1) width = gr.Slider(label="宽度", value=1024, minimum=64, maximum=2048, step=64, scale=3) height = gr.Slider(label="高度", value=1024, minimum=64, maximum=2048, step=64, scale=3) presets.change(lambda s:tuple(map(int, s.split('x'))), inputs=presets, outputs=[width, height]) with gr.Accordion('风格迁移', open=False) as vibe_tab: str_norm = gr.Checkbox(label='参考强度归一化', value=True) ref_images = gr.Gallery(label="上传单(多)张图片", format="png", value=None, interactive=True, type="pil", show_share_button=False) info_extracts = gr.State([]) ref_strs = gr.State([]) encode = gr.Button('生成vibe文件(仅nai4,每张图消耗2点)') vibe_files = gr.Files(label='nai4 vibe文件', value=None, file_types=['.naiv4vibe']) vibe_thumbs = gr.Gallery(label='vibes预览图', interactive=False, visible=False) encode.click(vibe_transfer, inputs=[model, ref_images, info_extracts, vibe_files], outputs=[ref_images, info_extracts, vibe_files], concurrency_limit=1) vibe_files.change(display_vibe_thumbs, inputs=vibe_files, outputs=vibe_thumbs) @gr.render(inputs=[ref_images, vibe_files, info_extracts, ref_strs], triggers=[ref_images.change, vibe_files.change]) def multiple_vibes(images, vibes, extracts, strengths): exts = [] strs = [] if images != None: for i, _ in enumerate(images): with gr.Row(): extract = gr.Slider(label=f"图片{i + 1} 参考信息提取", elem_id=f"ref_info_{i + 1}", value=extracts[i] if i < len(extracts) else 1, minimum=0, maximum=1, step=0.1, interactive=True) strength = gr.Slider(label=f"图片{i + 1} 参考强度", elem_id=f"ref_strength_{i + 1}", value=strengths[i] if i < len(extracts) else 0.6, minimum=0, maximum=1, step=0.1, interactive=True) exts.append(extract) strs.append(strength) if vibes != None: for i, _ in enumerate(vibes): with gr.Row(): strength = gr.Slider(label=f"Vibe{i + 1} 参考强度", elem_id=f"vibe_strength_{i + 1}", value=strengths[len(extracts) + i] if len(extracts) + i < len(strengths) else 0.6, minimum=0, maximum=1, step=0.1, interactive=True) strs.append(strength) for e in exts: e.change(fn=dynparas, inputs=exts, outputs=info_extracts) for s in strs: s.change(fn=dynparas, inputs=strs, outputs=ref_strs) def change_values(items, base, default, prefix=False): if prefix: postfix = base[len(prefix):] if len(prefix) < len(base) else [] if items is None: return postfix elif len(items) <= len(prefix): return base[:len(items)] + postfix else: return base[:len(prefix)] + [default] * (len(items) - len(prefix)) + postfix else: if items is None: return [] elif len(items) <= len(base): return base[:len(items)] else: return base + [default] * (len(items) - len(base)) ref_images.change(lambda i, e, s: (change_values(i, e, 1), change_values(i, s, 0.6, e)), inputs=[ref_images, info_extracts, ref_strs], outputs=[info_extracts, ref_strs]) vibe_files.change(change_values, inputs=[vibe_files, info_extracts, ref_strs], outputs=ref_strs) with gr.Accordion('附加输入', open=False, elem_id="i2i_tab") as i2i_tab: with gr.Tab('图生图', elem_id="i2i_block") as i2i: i2i_image = gr.Image(label="上传图片", value=None, sources=["upload", "clipboard", "webcam"], interactive=True, type="pil", show_share_button=False) i2i_str = gr.Slider(label='去噪强度', value=0.7, minimum=0, maximum=0.99, step=0.01) i2i_noise = gr.Slider(label='噪声', value=0, minimum=0, maximum=1, step=0.1) reuse_img_i2i = gr.Button(value='使用上一次生成的图片') with gr.Tab('局部重绘', elem_id="inp_block") as inp: overlay = gr.Checkbox(label='覆盖原图', value=True) inp_img = gr.ImageMask(label="上传图片", value=None, sources=["upload", "clipboard", "webcam"], interactive=True, type="pil", eraser=False, transforms=None, brush=gr.Brush(colors=['#FFFFFF'], color_mode='fixed'), layers=False, show_share_button=False, show_download_button=False) inp_str = gr.Slider(label="重绘强度", value=1, minimum=0.01, maximum=1, step=0.01) reuse_img_inp = gr.Button(value='使用上一次生成的图片') selection = gr.Radio(choices=['i2i', 'inp'], value='i2i', visible=False) with gr.Accordion("角色控制(仅nai4有效)", open=False, elem_id="v4chars_tab") as chars: with gr.Row(): num_chars = gr.Number(value=0, label="角色数量", minimum=0, maximum=6) auto_pos = gr.Checkbox(value=True, label="AI自动决定位置") char_prompts = gr.State(['']*6) char_ucs = gr.State(['']*6) char_coords_x = gr.State([3]*6) char_coords_y = gr.State([3]*6) rerender = gr.Checkbox(value=False, visible=False) @gr.render(inputs=[num_chars, auto_pos, char_prompts, char_ucs, char_coords_x, char_coords_y], triggers=[num_chars.change, auto_pos.change, rerender.change]) def characterPrompts(num, is_auto, char_p, char_np, cds_x, cds_y): prompts = [] neg_prompts = [] coords_x = [] coords_y = [] for i in range(num): with gr.Row(): with gr.Column(): p = gr.TextArea(lines=2, value=char_p[i], elem_id=f"txt2img_char{i + 1}_p", label=f"角色{i + 1}提示词") np = gr.TextArea(lines=2, value=char_np[i], elem_id=f"txt2img_char{i + 1}_n", label=f"角色{i + 1}负面提示词") p.focus(fn=None, inputs=None, js="() => {run();}") np.focus(fn=None, inputs=None, js="() => {run();}") with gr.Row(): pos_visual = gr.HTML(value=draw_position(cds_y[i], cds_x[i])) with gr.Column(): coord_y = gr.Number(value=cds_y[i], label="行", minimum=1, maximum=5, interactive=not is_auto) coord_x = gr.Number(value=cds_x[i], label="列", minimum=1, maximum=5, interactive=not is_auto) coord_x.change(draw_position, inputs=[coord_x, coord_y], outputs=pos_visual) coord_y.change(draw_position, inputs=[coord_x, coord_y], outputs=pos_visual) prompts.append(p) neg_prompts.append(np) coords_x.append(coord_x) coords_y.append(coord_y) for i in range(num): def change_one(orignal, new_one, index=i): orignal[index] = new_one return orignal prompts[i].input(fn=change_one, inputs=[char_prompts, prompts[i]], outputs=char_prompts) neg_prompts[i].input(fn=change_one, inputs=[char_ucs, neg_prompts[i]], outputs=char_ucs) coords_x[i].input(fn=change_one, inputs=[char_coords_x, coords_x[i]], outputs=char_coords_x) coords_y[i].input(fn=change_one, inputs=[char_coords_y, coords_y[i]], outputs=char_coords_y) num_chars.change(lambda: gr.Accordion(open=True), inputs=None, outputs=chars) auto_pos.change(lambda: gr.Accordion(open=True), inputs=None, outputs=chars) with gr.Accordion('角色参考(仅nai4.5有效)', open=False, elem_id="v4.5char_tab") as v45char_tab: chr_image = gr.Image(label="上传图片", value=None, sources=["upload", "clipboard", "webcam"], interactive=True, type="pil", show_share_button=False) fidelity = gr.Slider(label='参考度', value=1, minimum=0, maximum=1, step=0.05) style_aware = gr.Checkbox(label='参考风格', value=True) with gr.Accordion('高级选项', open=False): scheduler = gr.Dropdown( choices=[ "native", "karras", "exponential", "polyexponential" ], value="karras", label="Scheduler", interactive=True ) with gr.Row(): smea = gr.Checkbox(False, label="SMEA") dyn = gr.Checkbox(False, label="SMEA DYN") variety = gr.Checkbox(False, label="Variety+") legacy = gr.Checkbox(False, label="Legacy Prompt (nai4)") with gr.Row(): dyn_threshold = gr.Checkbox(False, label="Decrisp") cfg_rescale = gr.Slider(0, 1, 0, step=0.01, label="CFG rescale") save = gr.Checkbox(value=True, label='云端保存图片') gen_btn = gr.Button(value="生成", variant="primary") stop_btn = gr.Button(value="取消", variant="stop", visible=False) sampler.change(change_schedule, sampler, scheduler) rand_seed.click(fn=lambda: -1, inputs=None, outputs=seed) i2i.select(lambda: 'i2i', inputs=None, outputs=selection) inp.select(lambda: 'inp', inputs=None, outputs=selection) return gen_btn, stop_btn, \ [model, prompt, quality_tags, neg_prompt, seed, scale, width, height, steps, sampler, scheduler, smea, dyn, dyn_threshold, cfg_rescale, variety, \ ref_images, info_extracts, ref_strs, vibe_files, str_norm, i2i_image, i2i_str, i2i_noise, overlay, inp_img, inp_str, selection, \ num_chars, auto_pos, char_prompts, char_ucs, char_coords_x, char_coords_y, legacy, chr_image, fidelity, style_aware], \ [save, rand_seed, reuse_seed, reuse_img_i2i, reuse_img_inp, vibe_tab, i2i_tab, rerender] def generate(model, prompt, quality_tags, neg_prompt, seed, scale, width, height, steps, sampler, scheduler, smea, dyn, dyn_threshold, cfg_rescale, variety, ref_images, info_extracts, ref_strs, vibe_files, str_norm, i2i_image, i2i_str, i2i_noise, overlay, inp_img, inp_str, selection, num_chars, auto_pos, char_prompts, char_ucs, char_coords_x, char_coords_y, legacy, chr_image, fidelity, style_aware): global today_count set_token(os.environ.get('token')) img_data, payload = generate_novelai_image( model, f"{prompt}, {quality_tags}", neg_prompt, seed, scale, width, height, steps, sampler, scheduler, smea, dyn, dyn_threshold, cfg_rescale, variety, ref_images, info_extracts, ref_strs, vibe_files, str_norm, i2i_image, i2i_str, i2i_noise, overlay, inp_img, inp_str, selection, auto_pos, char_prompts[:num_chars], char_ucs[:num_chars], char_coords_x[:num_chars], char_coords_y[:num_chars], legacy, chr_image, fidelity, style_aware ) if not isinstance(img_data, bytes): return gr.Image(value=None), payload today_count = get_count() + 1 img = image_from_bytes(img_data) return img, payload def preview_ui(): with gr.Blocks(css='#preview_image { height: 100%;}'): image = gr.Image(format='png', elem_id='preview_image', interactive=False, type='filepath', show_share_button=False) send_dtool = gr.Button(value="发送到定向修图", visible=False) image.change(lambda i: gr.Button(visible=False) if i is None else gr.Button(visible=True), inputs=image, outputs=send_dtool) info = gr.JSON(value={}, label="生成信息") return image, info, send_dtool def rename_save_img(path, payload, save): if path is None: return None default = os.path.basename(path) filename = str(today_count).rjust(5, '0') + '-' + str(payload['parameters']['seed']) + '.png' renamed_path = path.replace(default, filename) if os.path.exists(renamed_path): return renamed_path os.replace(path, renamed_path) if save: save_path = client_config['save_path'] today = datetime.date.today().strftime('%Y-%m-%d') today_path = os.path.join(save_path, today) os.makedirs(today_path, exist_ok=True) file_path = os.path.join(today_path, filename) shutil.copy(renamed_path, file_path) api.upload_file(path_or_fileobj=file_path, path_in_repo=file_path, repo_id="P01yH3dr0n/naimages", repo_type="dataset", token=os.environ.get("hf_token")) return renamed_path def vibe_transfer(model, ref_images, info_extracts, vibe_files): if (not model.startswith('nai-diffusion-4')) or ref_images is None: return ref_images, info_extracts, vibe_files orig, vibes = vibe_encode(model, ref_images, info_extracts) files = [] for i in range(len(ref_images)): data, name = vibe_to_json(model, ref_images[i][0], info_extracts[i], orig[i], vibes[i]) tmp_path = save_bytes_to_cache(data.encode('utf-8'), name + '.naiv4vibe', get_upload_folder()) files.append(tmp_path) if vibe_files is None: vibe_files = [] return None, [], vibe_files + files def display_vibe_thumbs(vibe_files): thumbs = [] if vibe_files is None: return gr.Gallery(value=None, visible=False) for v in vibe_files: with open(v) as f: data = json.load(f)['thumbnail'].replace('data:image/jpeg;base64,', '') thumbs.append(base642image(data)) return gr.Gallery(value=thumbs, visible=True) def update_btn_cost(model, w, h, s, sm, dyn, ref_imgs, i2i_img, i2i_str, inp_img, inp_str, selection, chr_img): if selection == 'i2i' and i2i_img != None: cost = calculate_cost(w, h, s, False, False, i2i_str) elif selection == 'inp' and inp_img['background'] != None: cost = calculate_cost(w, h, s, False, False, inp_str if model.startswith('nai-diffusion-4') else 1) else: cost = calculate_cost(w, h, s, sm, dyn) if len(ref_imgs) and model.startswith('nai-diffusion-4'): cost += len(ref_imgs) * 2 if chr_img != None and model.startswith('nai-diffusion-4-5'): cost += 5 return gr.Button(value=f"生成(预计消耗{cost}点数)") def main_ui(): with gr.Blocks(): with gr.Row(variant="panel"): with gr.Column(): gen_btn, stop_btn, paras, others = control_ui() with gr.Column(): image, info, send_dtool = preview_ui() cost_list = [paras[0]] + paras[6:9] + paras[11:13] + [paras[17]] + paras[21:23] + paras[25:28] + [paras[35]] for component in cost_list: component.change(update_btn_cost, inputs=cost_list, outputs=gen_btn) gen = gen_btn.click(lambda: (gr.Button(visible=False), gr.Button(visible=True)), inputs=None, outputs=[gen_btn, stop_btn]).then( vibe_transfer, inputs=[paras[0], paras[16], paras[17], paras[19]], outputs=[paras[16], paras[17], paras[19]]).then( generate, inputs=paras, outputs=[image, info], concurrency_limit=1, concurrency_id="generate").then( rename_save_img, inputs=[image, info, others[0]], outputs=image, trigger_mode="once").then( lambda: (gr.Button(visible=True), gr.Button(visible=False)), inputs=None, outputs=[gen_btn, stop_btn]) others[2].click(lambda o, s: o if len(s) == 0 else s['parameters']['seed'], inputs=[paras[4], info], outputs=paras[4]) others[3].click(lambda i: i, inputs=image, outputs=paras[21]) others[4].click(lambda i: gr.ImageEditor(value=i), inputs=image, outputs=paras[25]) stop_btn.click(lambda: (gr.Button(visible=True), gr.Button(visible=False)), inputs=None, outputs=[gen_btn, stop_btn], cancels=[gen]) return image, paras, others, send_dtool def util_ui(): with gr.Blocks(): with gr.Row(equal_height=False): with gr.Column(variant='panel'): image = gr.Image(label="上传图片", image_mode="RGBA", sources=["upload"], interactive=True, type="pil") with gr.Column(variant='panel'): info = gr.HTML('') items = gr.JSON(value={}, visible=False) png2main = gr.Button('参数发送到文生图', visible=False) items.change(lambda i: gr.Button(visible=True) if len(i) else gr.Button(visible=False), inputs=items, outputs=png2main) return png2main, items, info, image def load_javascript(): head = '' for f in sorted(os.listdir('./tagcomplete/javascript')): head += f'\n' share = gr.routes.templates.TemplateResponse def template_response(*args, **kwargs): res = share(*args, **kwargs) res.body = res.body.replace(b'', f'{head}'.encode("utf8")) res.init_headers() return res gr.routes.templates.TemplateResponse = template_response def send_and_jump(component, fn, inputs, outputs, tab, trigger): component.click(fn, inputs=inputs, outputs=outputs) component.click(fn=None, js="(x) => { if (x !== null && x != 0) document.getElementById('" + tab + "-button').click();}", inputs=trigger) def send_jump_select(component, fn, inputs, outputs, tab, accordin, trigger, secondary=None): extra_js = '' if secondary is not None: extra_js = "document.getElementById('" + secondary + "-button').click();" component.click(fn, inputs=inputs, outputs=outputs).success( lambda x: gr.Accordion(open=True) if x else gr.Accordion(), inputs=trigger, outputs=accordin) component.click(fn=None, js="(x) => { if (x !== null && x != 0) document.getElementById('" + tab + "-button').click();" + extra_js + " return null; }", inputs=trigger) def sync_chants(c, path='tagcomplete/tags/demo-chants.json'): c.rename(columns={"名称": 'name', "别名": 'terms', "tags": 'content', "颜色": 'color'}).to_json(path, orient='records') api.upload_file(path_or_fileobj=path, path_in_repo=path, repo_id="P01yH3dr0n/naimages", repo_type="dataset", token=os.environ.get("hf_token")) def ui(): load_javascript() set_token(os.environ.get('token')) with gr.Blocks(title="NAI Client", analytics_enabled=False, theme=gr.themes.Soft(), js="() => {document.body.classList.toggle('dark', false);}", delete_cache=[604800, 604800]) as website: with gr.Row(): remain_anlas = gr.Textbox(label="剩余点数", value=get_remain_anlas, scale=3) refresh = gr.Button("🔄") refresh.click(get_remain_anlas, inputs=None, outputs=remain_anlas) with gr.Tabs(): with gr.TabItem("图片生成", elem_id="client_ui_main"): image, paras, others, send_dtool = main_ui() with gr.TabItem("定向修图", elem_id="client_ui_dtool"): from_t2i, send_i2i, send_inp, send_vib, in_image, out_image, d_index = director_ui() with gr.TabItem("图片信息读取"): png2main, png_items, info, read_image = util_ui() with gr.TabItem("Tagger反推"): tags, tagger2main = tagger_ui() with gr.TabItem("云端图片浏览") as tab: gallery, h_index, gal2main, gal_items, history2ref, history2i2i, history2inp, history2dtl = img_history_ui(tab) with gr.TabItem("设置"): switchLightDark = gr.Button(value="切换浅色/深色模式") switchLightDark.click(fn=None, js="() => {document.body.classList.toggle('dark');}") loadTagComplete = gr.Button(value="重新加载tag补全") loadTagComplete.click(fn=None, js="() => {document.getElementById('client_ui_main-button').click();run();}") clearTagCache = gr.Button(value="清除tag补全缓存") clearTagCache.click(fn=None, js="() => {clearAllRecords();}") chant_path = 'tagcomplete/tags/demo-chants.json' api.hf_hub_download(local_dir='./', filename=chant_path, repo_id="P01yH3dr0n/naimages", repo_type="dataset", token=os.environ.get("hf_token")) with gr.Blocks(): table = gr.Dataframe(label="现有预设串(预设串自动补全方法:,选择后替换;添加修改后需清除缓存;多个别名用英文逗号','隔开)", value=lambda: pd.read_json(chant_path), headers=["名称", "别名", "tags", "颜色"], datatype=["str", "str", "str", "number"], row_count=5, col_count=(4, "fixed"), wrap=True, interactive=True, show_row_numbers=True, show_search='search') table.change(sync_chants, inputs=table) send_and_jump(png2main, send_paras, [png_items] + paras[:16] + paras[28:35] + [others[7]], paras[:16] + paras[28:35] + [others[7]], "client_ui_main", read_image) send_and_jump(gal2main, send_paras, [gal_items] + paras[:16] + paras[28:35] + [others[7]], paras[:16] + paras[28:35] + [others[7]], "client_ui_main", gal_items) from_t2i.click(lambda x: x, inputs=image, outputs=in_image) send_jump_select(send_i2i, send_outputs, [out_image, d_index], paras[21], "client_ui_main", others[6], out_image, "i2i_block") send_jump_select(send_inp, send_outputs, [out_image, d_index], paras[25], "client_ui_main", others[6], out_image, "inp_block") send_jump_select(send_vib, (lambda l, i: l if i == -1 else [l[i]]), [out_image, d_index], paras[16], "client_ui_main", others[5], out_image) send_and_jump(send_dtool, (lambda x: x), image, in_image, "client_ui_dtool", image) send_jump_select(history2i2i, send_outputs, [gallery, h_index], paras[21], "client_ui_main", others[6], gal_items, "i2i_block") send_jump_select(history2inp, send_outputs, [gallery, h_index], paras[25], "client_ui_main", others[6], gal_items, "inp_block") send_jump_select(history2ref, (lambda l, i: None if i == -1 else [l[i]]), [gallery, h_index], paras[16], "client_ui_main", others[5], gal_items) send_and_jump(history2dtl, send_outputs, [gallery, h_index], in_image, "client_ui_dtool", gal_items) send_and_jump(tagger2main, (lambda x: x), tags, paras[1], "client_ui_main", tags) read_image.change(read_info_from_image, inputs=read_image, outputs=[info, png_items]) return website def download_dataset(): max_retries = None # 最大重试次数(设为None表示无限重试) base_delay = 10 # 基础等待时间(秒) attempt = 0 while True: try: snapshot_download(repo_id="P01yH3dr0n/naimages", repo_type="dataset", local_dir="./", etag_timeout=120, token=os.environ.get("hf_token")) print("✅ 数据集下载成功!") return except Exception as e: print(f"❌ 下载失败: {str(e)}") if max_retries and attempt >= max_retries: raise RuntimeError(f"经过 {max_retries} 次重试仍失败") # 指数退避计算 delay = base_delay * (2 ** attempt) print(f"⏱ {delay}秒后重试...") time.sleep(delay) attempt += 1 if __name__ == '__main__': download_thread = threading.Thread(target=download_dataset, daemon=True) download_thread.start() website = ui() website.queue(default_concurrency_limit=5) website.launch(auth=(os.environ.get('account'), os.environ.get('password')), allowed_paths=['tagcomplete'], debug=True, ssr_mode=False)