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# -*- coding: utf-8 -*-
import os
import gradio as gr
import modules.scripts as scripts
from modules import script_callbacks
from scripts.library import (
model,
setting,
liblibai,
model_action_liblibai,
)
root_path = os.getcwd()
extension_path = scripts.basedir()
model.get_custom_model_folder()
liblibai.record_local_info()
setting.load()
def on_ui_tabs():
# ====Event's function====
def get_model_names_by_input(model_type, empty_info_only):
names = liblibai.get_model_names_by_input(model_type, empty_info_only)
return model_name_drop.update(choices=names)
def get_model_info_by_url(url):
response = model_action_liblibai.get_model_info_by_url(url)
model_info, model_name, model_type, subfolders, version_strs = response if response else ({}, "", "", [], [])
return [model_info, model_name, model_type, dl_subfolder_drop.update(choices=subfolders), dl_version_drop.update(choices=version_strs)]
# ====UI====
with gr.Blocks(analytics_enabled=False) as liblibai_helper:
with gr.Row():
with gr.Column(elem_id="left_block", scale=3):
# init
max_size_preview = setting.data["model"]["max_size_preview"]
model_types = list(model.folders.keys())
no_info_model_names = liblibai.get_model_names_by_input("ckpt", False)
# session data
dl_model_info = gr.State({})
with gr.Box(elem_classes="helper_box"):
with gr.Column():
gr.Markdown("### 扫描本地模型")
with gr.Row():
with gr.Column(scale=4):
scan_model_types_ckbg = gr.CheckboxGroup(choices=model_types, label="模型种类", value=model_types)
with gr.Column(scale=3):
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")
scan_model_liblibai_btn = gr.Button(value="开始扫描", variant="primary", elem_id="ch_scan_model_liblibai_btn")
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")
with gr.Box(elem_classes="helper_box"):
with gr.Column():
gr.Markdown("### 使用URL从LiblibAI获取模型信息")
gr.Markdown("在LiblibAI扫描不到对应的本地模型时可以使用这个功能")
with gr.Row():
model_type_drop = gr.Dropdown(choices=model_types, label="模型种类", value="ckpt", multiselect=False)
model_name_drop = gr.Dropdown(choices=no_info_model_names, label="模型名称", value="", multiselect=False)
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")
model_url_or_id_txtbox = gr.Textbox(label="LiblibAI URL", lines=1, value="")
get_liblibai_model_info_by_id_btn = gr.Button(value="获取模型信息", variant="primary")
get_model_by_id_log_md = gr.Markdown("")
with gr.Box(elem_classes="helper_box"):
with gr.Column():
gr.Markdown("### 模型下载")
gr.Markdown("1. 通过LiblibAI URL获取模型信息")
dl_model_url_or_id_txtbox = gr.Textbox(label="LiblibAI URL", lines=1, value="")
dl_model_info_btn = gr.Button(value="下载模型信息", variant="primary")
gr.Markdown(value="2. 选择子文件夹和模型版本")
with gr.Row():
dl_model_name_txtbox = gr.Textbox(label="模型名称", interactive=False, lines=1, value="")
dl_model_type_txtbox = gr.Textbox(label="模型类型", interactive=False, lines=1, value="")
dl_subfolder_drop = gr.Dropdown(choices=[], label="子文件夹", value="", interactive=True, multiselect=False)
dl_version_drop = gr.Dropdown(choices=[], label="模型版本", value="", interactive=True, multiselect=False)
gr.Markdown(value="3. 从LiblibAI下载模型")
dl_liblibai_model_by_id_btn = gr.Button(value="下载模型", variant="primary")
dl_log_md = gr.Markdown(value="下载状态显示在控制台中。")
with gr.Box(elem_classes="helper_box"):
with gr.Column():
gr.Markdown("### 通过LiblibAI检查模型的新版本")
model_types_ckbg = gr.CheckboxGroup(choices=model_types, label="模型种类", value=["lora"])
check_models_new_version_btn = gr.Button(value="检查模型版本", variant="primary")
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。")
# ====events====
# Scan Models for Liblibai
scan_model_liblibai_btn.click(model_action_liblibai.scan_model, inputs=[scan_model_types_ckbg, max_size_preview_ckb], outputs=scan_model_log_md)
# Get Liblibai Model Info by Model Page URL
model_type_drop.change(get_model_names_by_input, inputs=[model_type_drop, empty_info_only_ckb], outputs=model_name_drop)
empty_info_only_ckb.change(get_model_names_by_input, inputs=[model_type_drop, empty_info_only_ckb], outputs=model_name_drop)
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)
# Download Model
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])
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)
# Check models' new version
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)
with gr.Column(elem_id="right_block", scale=4):
with gr.Box(elem_classes="helper_box"):
gr.HTML("""
<iframe id="liblibai-iframe"
height="1100vh"
width="100%" scrolling="auto"
src="https://www.liblib.ai/"
>
</iframe>
""")
return (liblibai_helper , "L站助手", "liblibai_helper"),
script_callbacks.on_ui_tabs(on_ui_tabs)
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