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import os |
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import gradio as gr |
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import modules.scripts as scripts |
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from modules import script_callbacks |
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from scripts.library import ( |
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model, |
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setting, |
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liblibai, |
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model_action_liblibai, |
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) |
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root_path = os.getcwd() |
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extension_path = scripts.basedir() |
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model.get_custom_model_folder() |
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liblibai.record_local_info() |
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setting.load() |
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def on_ui_tabs(): |
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def get_model_names_by_input(model_type, empty_info_only): |
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names = liblibai.get_model_names_by_input(model_type, empty_info_only) |
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return model_name_drop.update(choices=names) |
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def get_model_info_by_url(url): |
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response = model_action_liblibai.get_model_info_by_url(url) |
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model_info, model_name, model_type, subfolders, version_strs = response if response else ({}, "", "", [], []) |
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return [model_info, model_name, model_type, dl_subfolder_drop.update(choices=subfolders), dl_version_drop.update(choices=version_strs)] |
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with gr.Blocks(analytics_enabled=False) as liblibai_helper: |
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with gr.Row(): |
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with gr.Column(elem_id="left_block", scale=3): |
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max_size_preview = setting.data["model"]["max_size_preview"] |
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model_types = list(model.folders.keys()) |
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no_info_model_names = liblibai.get_model_names_by_input("ckpt", False) |
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dl_model_info = gr.State({}) |
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with gr.Box(elem_classes="helper_box"): |
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with gr.Column(): |
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gr.Markdown("### 扫描本地模型") |
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with gr.Row(): |
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with gr.Column(scale=4): |
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scan_model_types_ckbg = gr.CheckboxGroup(choices=model_types, label="模型种类", value=model_types) |
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with gr.Column(scale=3): |
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max_size_preview_ckb = gr.Checkbox(label="下载最大尺寸的预览图", value=max_size_preview, elem_id="ch_max_size_preview_ckb") |
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scan_model_liblibai_btn = gr.Button(value="开始扫描", variant="primary", elem_id="ch_scan_model_liblibai_btn") |
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scan_model_log_md = gr.Markdown(value="扫描会持续一段时间，请在控制台查看详细信息。", elem_id="ch_scan_model_log_md") |
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with gr.Box(elem_classes="helper_box"): |
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with gr.Column(): |
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gr.Markdown("### 使用URL从LiblibAI获取模型信息") |
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gr.Markdown("在LiblibAI扫描不到对应的本地模型时可以使用这个功能") |
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with gr.Row(): |
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model_type_drop = gr.Dropdown(choices=model_types, label="模型种类", value="ckpt", multiselect=False) |
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model_name_drop = gr.Dropdown(choices=no_info_model_names, label="模型名称", value="", multiselect=False) |
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empty_info_only_ckb = gr.Checkbox(label="只显示没有信息的模型", value=False, elem_id="ch_empty_info_only_ckb", elem_classes="ch_vpadding") |
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model_url_or_id_txtbox = gr.Textbox(label="LiblibAI URL", lines=1, value="") |
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get_liblibai_model_info_by_id_btn = gr.Button(value="获取模型信息", variant="primary") |
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get_model_by_id_log_md = gr.Markdown("") |
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with gr.Box(elem_classes="helper_box"): |
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with gr.Column(): |
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gr.Markdown("### 模型下载") |
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gr.Markdown("1. 通过LiblibAI URL获取模型信息") |
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dl_model_url_or_id_txtbox = gr.Textbox(label="LiblibAI URL", lines=1, value="") |
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dl_model_info_btn = gr.Button(value="下载模型信息", variant="primary") |
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gr.Markdown(value="2. 选择子文件夹和模型版本") |
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with gr.Row(): |
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dl_model_name_txtbox = gr.Textbox(label="模型名称", interactive=False, lines=1, value="") |
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dl_model_type_txtbox = gr.Textbox(label="模型类型", interactive=False, lines=1, value="") |
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dl_subfolder_drop = gr.Dropdown(choices=[], label="子文件夹", value="", interactive=True, multiselect=False) |
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dl_version_drop = gr.Dropdown(choices=[], label="模型版本", value="", interactive=True, multiselect=False) |
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gr.Markdown(value="3. 从LiblibAI下载模型") |
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dl_liblibai_model_by_id_btn = gr.Button(value="下载模型", variant="primary") |
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dl_log_md = gr.Markdown(value="下载状态显示在控制台中。") |
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with gr.Box(elem_classes="helper_box"): |
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with gr.Column(): |
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gr.Markdown("### 通过LiblibAI检查模型的新版本") |
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model_types_ckbg = gr.CheckboxGroup(choices=model_types, label="模型种类", value=["lora"]) |
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check_models_new_version_btn = gr.Button(value="检查模型版本", variant="primary") |
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check_models_new_version_log_md = gr.HTML("这将会花费一些时间，请在控制台中查看详细信息。") |
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scan_model_liblibai_btn.click(model_action_liblibai.scan_model, inputs=[scan_model_types_ckbg, max_size_preview_ckb], outputs=scan_model_log_md) |
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model_type_drop.change(get_model_names_by_input, inputs=[model_type_drop, empty_info_only_ckb], outputs=model_name_drop) |
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empty_info_only_ckb.change(get_model_names_by_input, inputs=[model_type_drop, empty_info_only_ckb], outputs=model_name_drop) |
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get_liblibai_model_info_by_id_btn.click(model_action_liblibai.get_model_info_by_input, inputs=[model_type_drop, model_name_drop, model_url_or_id_txtbox, max_size_preview_ckb], outputs=get_model_by_id_log_md) |
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dl_model_info_btn.click(get_model_info_by_url, inputs=dl_model_url_or_id_txtbox, outputs=[dl_model_info, dl_model_name_txtbox, dl_model_type_txtbox, dl_subfolder_drop, dl_version_drop]) |
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dl_liblibai_model_by_id_btn.click(model_action_liblibai.download_model_by_input, inputs=[dl_model_info, dl_model_type_txtbox, dl_subfolder_drop, dl_version_drop, max_size_preview_ckb], outputs=dl_log_md) |
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check_models_new_version_btn.click(model_action_liblibai.check_models_new_version_to_md, inputs=model_types_ckbg, outputs=check_models_new_version_log_md) |
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with gr.Column(elem_id="right_block", scale=4): |
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with gr.Box(elem_classes="helper_box"): |
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gr.HTML(""" |
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<iframe id="liblibai-iframe" |
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height="1100vh" |
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width="100%" scrolling="auto" |
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src="https://www.liblib.ai/" |
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> |
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</iframe> |
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""") |
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return (liblibai_helper , "L站助手", "liblibai_helper"), |
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script_callbacks.on_ui_tabs(on_ui_tabs) |
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