# -*- coding: utf-8 -*- """ GPT-SoVITS WebUI 精简版 保留功能：模型持久化、参考音频持久化、推理参数持久化、记住最后选中预设 核心优化：抽离持久化逻辑到 persistence_tools.py，主文件大幅精简，结构清晰 """ import psutil import os import sys import json import yaml import random import re import shutil from pathlib import Path import torch import gradio as gr # 设置进程优先级（仅Windows有效） def set_high_priority(): if os.name != "nt": return p = psutil.Process(os.getpid()) try: p.nice(psutil.HIGH_PRIORITY_CLASS) print("已将进程优先级设为 High") except psutil.AccessDenied: print("权限不足，无法修改优先级（请用管理员运行）") set_high_priority() # ===================== 导入自定义持久化工具类（核心精简关键） ===================== from persistence_tools import ( init_last_selected_models, read_last_selected_models, write_last_selected_models, read_last_selected_preset, write_last_selected_preset, clear_last_selected_preset, load_ref_presets, get_preset_by_name, save_ref_preset_core, delete_ref_preset_core, load_infer_settings, save_infer_settings_core, restore_default_infer_settings_core, REF_AUDIO_DIR ) # ===================== 原有核心依赖导入 ===================== now_dir = os.getcwd() sys.path.append(now_dir) sys.path.append("%s/GPT_SoVITS" % (now_dir)) # 屏蔽无关日志 import logging logging.getLogger("markdown_it").setLevel(logging.ERROR) logging.getLogger("urllib3").setLevel(logging.ERROR) logging.getLogger("httpcore").setLevel(logging.ERROR) logging.getLogger("httpx").setLevel(logging.ERROR) logging.getLogger("asyncio").setLevel(logging.ERROR) logging.getLogger("charset_normalizer").setLevel(logging.ERROR) logging.getLogger("torchaudio._extension").setLevel(logging.ERROR) # 配置参数初始化 infer_ttswebui = int(os.environ.get("infer_ttswebui", 9872)) is_share = eval(os.environ.get("is_share", "False")) if "_CUDA_VISIBLE_DEVICES" in os.environ: os.environ["CUDA_VISIBLE_DEVICES"] = os.environ["_CUDA_VISIBLE_DEVICES"] is_half = eval(os.environ.get("is_half", "True")) and torch.cuda.is_available() gpt_path = os.environ.get("gpt_path", None) sovits_path = os.environ.get("sovits_path", None) cnhubert_base_path = os.environ.get("cnhubert_base_path", None) bert_path = os.environ.get("bert_path", None) version = model_version = os.environ.get("version", "v2") # 标记是否直接打开推理页 is_direct_launch = (gpt_path is None) and (sovits_path is None) # 多语言配置 from tools.i18n.i18n import I18nAuto, scan_language_list language = os.environ.get("language", "Auto") language = sys.argv[-1] if sys.argv[-1] in scan_language_list() else language i18n = I18nAuto(language=language) # TTS 推理核心 from TTS_infer_pack.text_segmentation_method import get_method from TTS_infer_pack.TTS import NO_PROMPT_ERROR, TTS, TTS_Config # 样式与配置工具 from tools.assets import css, js, top_html from config import change_choices, get_weights_names, name2gpt_path, name2sovits_path from process_ckpt import get_sovits_version_from_path_fast # ===================== 全局变量初始化 ===================== # 设备配置 device = "cuda" if torch.cuda.is_available() else "cpu" # 语种字典 dict_language_v1 = { i18n("中文"): "all_zh", i18n("英文"): "en", i18n("日文"): "all_ja", i18n("中英混合"): "zh", i18n("日英混合"): "ja", i18n("多语种混合"): "auto", } dict_language_v2 = { i18n("中文"): "all_zh", i18n("英文"): "en", i18n("日文"): "all_ja", i18n("粤语"): "all_yue", i18n("韩文"): "all_ko", i18n("中英混合"): "zh", i18n("日英混合"): "ja", i18n("粤英混合"): "yue", i18n("韩英混合"): "ko", i18n("多语种混合"): "auto", i18n("多语种混合(粤语)"): "auto_yue", } dict_language = dict_language_v1 if version == "v1" else dict_language_v2 # 文本切分方法 cut_method = { i18n("不切"): "cut0", i18n("凑四句一切"): "cut1", i18n("凑50字一切"): "cut2", i18n("按中文句号。切"): "cut3", i18n("按英文句号.切"): "cut4", i18n("按标点符号切"): "cut5", } # V3/V4 标记 v3v4set = {"v3", "v4"} # 模型列表初始化 SoVITS_names, GPT_names = get_weights_names() from config import pretrained_sovits_name path_sovits_v3 = pretrained_sovits_name["v3"] path_sovits_v4 = pretrained_sovits_name["v4"] is_exist_s2gv3 = os.path.exists(path_sovits_v3) is_exist_s2gv4 = os.path.exists(path_sovits_v4) # TTS 配置与管道初始化 tts_config = TTS_Config("GPT_SoVITS/configs/tts_infer.yaml") tts_config.device = device tts_config.is_half = is_half tts_config.update_version(version) if gpt_path is not None and "！" not in gpt_path and "!" not in gpt_path: tts_config.t2s_weights_path = gpt_path if sovits_path is not None and "！" not in sovits_path and "!" not in sovits_path: tts_config.vits_weights_path = sovits_path if cnhubert_base_path is not None: tts_config.cnhuhbert_base_path = cnhubert_base_path if bert_path is not None: tts_config.bert_base_path = bert_path tts_pipeline = TTS(tts_config) gpt_path = tts_config.t2s_weights_path sovits_path = tts_config.vits_weights_path version = tts_config.version # 参考预设全局变量 ref_presets = load_ref_presets() preset_names = [p["name"] for p in ref_presets] if ref_presets else [] # ===================== 精简版辅助函数 ===================== def custom_sort_key(s): """自定义排序键（数字自然排序）""" parts = re.split("(\d+)", s) return [int(part) if part.isdigit() else part for part in parts] def init_ui_preset_config(): """初始化UI配置（优先加载最后选中的预设）""" global ref_presets, preset_names ref_presets = load_ref_presets() preset_names = [p["name"] for p in ref_presets] if ref_presets else [] is_interactive = bool(preset_names) # 优先读取最后选中的预设 last_selected = read_last_selected_preset() default_selected = last_selected if (last_selected and last_selected in preset_names) else (preset_names[0] if preset_names else None) default_preset = get_preset_by_name(default_selected) return ( gr.update(choices=preset_names, value=default_selected, interactive=is_interactive), default_preset["name"], default_preset["ref_audio_path"], default_preset["prompt_text"], default_preset["prompt_language"] ) def update_popup_text(preset_name, is_delete): """更新弹窗提示文本""" preset_name = preset_name.strip() if is_delete: return gr.update(value=i18n(f"确定要删除配置「{preset_name}」吗？删除后无法恢复！")) else: return gr.update(value=i18n(f"配置「{preset_name}」已存在，确定要覆盖吗？覆盖后无法恢复！")) def reset_confirm_result(): """重置确认结果为False""" return False def save_ref_preset_wrapper(preset_name, ref_audio_path, prompt_text, prompt_language, confirm_override=False): """保存预设包装器（适配Gradio输出）""" msg, success, new_preset_names = save_ref_preset_core(preset_name, ref_audio_path, prompt_text, prompt_language, confirm_override) style = gr.update(elem_classes=["config-error-border"]) if not success else gr.update(elem_classes=["config-default-border"]) dropdown_update = gr.update(choices=new_preset_names, value=preset_name if success and preset_name in new_preset_names else (new_preset_names[0] if new_preset_names else None), interactive=bool(new_preset_names)) return msg, style, dropdown_update def delete_ref_preset_wrapper(preset_name): """删除预设包装器（适配Gradio输出）""" msg, new_preset_names, new_selected = delete_ref_preset_core(preset_name) dropdown_update = gr.update(choices=new_preset_names, value=new_selected, interactive=bool(new_preset_names)) new_preset = get_preset_by_name(new_selected) return ( msg, dropdown_update, new_preset["name"], new_preset["ref_audio_path"], new_preset["prompt_text"], new_preset["prompt_language"] ) def on_preset_selected(preset_name): """预设切换回调（记录最后选中）""" if not preset_name or not ref_presets: return "", None, "", i18n("中文") preset = get_preset_by_name(preset_name) audio_path = preset["ref_audio_path"] # 记录最后选中的预设 write_last_selected_preset(preset_name) return preset["name"], audio_path, preset["prompt_text"], preset["prompt_language"] # ===================== 推理核心函数 ===================== def inference( text, text_lang, ref_audio_path, aux_ref_audio_paths, prompt_text, prompt_lang, top_k, top_p, temperature, text_split_method, batch_size, speed_factor, ref_text_free, split_bucket, fragment_interval, seed, keep_random, parallel_infer, repetition_penalty, sample_steps, super_sampling, ): """语音合成推理核心""" seed = -1 if keep_random else seed actual_seed = seed if seed not in [-1, "", None] else random.randint(0, 2**32 - 1) ref_audio_path = ref_audio_path if ref_audio_path else "" inputs = { "text": text, "text_lang": dict_language[text_lang], "ref_audio_path": ref_audio_path, "aux_ref_audio_paths": [item.name for item in aux_ref_audio_paths] if aux_ref_audio_paths is not None else [], "prompt_text": prompt_text if not ref_text_free else "", "prompt_lang": dict_language[prompt_lang], "top_k": top_k, "top_p": top_p, "temperature": temperature, "text_split_method": cut_method[text_split_method], "batch_size": int(batch_size), "speed_factor": float(speed_factor), "split_bucket": split_bucket, "return_fragment": False, "fragment_interval": fragment_interval, "seed": actual_seed, "parallel_infer": parallel_infer, "repetition_penalty": repetition_penalty, "sample_steps": int(sample_steps), "super_sampling": super_sampling, } try: for item in tts_pipeline.run(inputs): yield item, actual_seed except NO_PROMPT_ERROR: return i18n("V3不支持无参考文本模式，请填写参考文本！") # ===================== 模型切换函数（保留预设记忆） ===================== def change_sovits_weights(sovits_path, current_gpt_selected, prompt_language=None, text_language=None): """切换SoVITS模型（保留最后选中预设）""" if "！" in sovits_path or "!" in sovits_path: sovits_path = name2sovits_path[sovits_path] global version, model_version, dict_language, if_lora_v3, ref_presets, preset_names version, model_version, if_lora_v3 = get_sovits_version_from_path_fast(sovits_path) is_exist = is_exist_s2gv3 if model_version == "v3" else is_exist_s2gv4 path_sovits = path_sovits_v3 if model_version == "v3" else path_sovits_v4 # 底模缺失校验 if if_lora_v3 and not is_exist: info = path_sovits + "SoVITS %s" % model_version + i18n("底模缺失，无法加载相应 LoRA 权重") return i18n(info) # 更新语种字典与预设 dict_language = dict_language_v1 if version == "v1" else dict_language_v2 ref_presets = load_ref_presets() preset_names = [p["name"] for p in ref_presets] if ref_presets else [] # 恢复最后选中的预设 last_selected = read_last_selected_preset() default_selected = last_selected if (last_selected and last_selected in preset_names) else (preset_names[0] if preset_names else None) # 更新模型配置文件 if is_direct_launch: valid_gpt_path = current_gpt_selected if (current_gpt_selected in GPT_names and os.path.exists(current_gpt_selected)) else GPT_names[-1] write_last_selected_models(valid_gpt_path, sovits_path, version) # 初始化返回值 if prompt_language is None or text_language is None: return # 语种兼容性校验 prompt_text_update, prompt_language_update = {"__type__": "update"}, {"__type__": "update", "value": prompt_language} if prompt_language not in list(dict_language.keys()): prompt_text_update = {"__type__": "update", "value": ""} prompt_language_update = {"__type__": "update", "value": i18n("中文")} text_update, text_language_update = {"__type__": "update"}, {"__type__": "update", "value": text_language} if text_language not in list(dict_language.keys()): text_update = {"__type__": "update", "value": ""} text_language_update = {"__type__": "update", "value": i18n("中文")} # V3/V4 特殊配置 visible_sample_steps = model_version in v3v4set visible_inp_refs = not visible_sample_steps ref_text_free_interactive = model_version not in v3v4set # 加载中状态 yield ( {"__type__": "update", "choices": list(dict_language.keys())}, {"__type__": "update", "choices": list(dict_language.keys())}, prompt_text_update, prompt_language_update, text_update, text_language_update, {"__type__": "update", "interactive": visible_sample_steps, "value": 32}, {"__type__": "update", "visible": visible_inp_refs}, {"__type__": "update", "interactive": ref_text_free_interactive}, {"__type__": "update", "value": i18n("模型加载中，请等待"), "interactive": False}, gr.update(choices=preset_names, value=default_selected, interactive=bool(preset_names)), ) # 加载模型权重 tts_pipeline.init_vits_weights(sovits_path) # 加载完成状态 yield ( {"__type__": "update", "choices": list(dict_language.keys())}, {"__type__": "update", "choices": list(dict_language.keys())}, prompt_text_update, prompt_language_update, text_update, text_language_update, {"__type__": "update", "interactive": visible_sample_steps, "value": 32}, {"__type__": "update", "visible": visible_inp_refs}, {"__type__": "update", "interactive": ref_text_free_interactive}, {"__type__": "update", "value": i18n("合成语音"), "interactive": True}, gr.update(choices=preset_names, value=default_selected, interactive=bool(preset_names)), ) # 更新 weight.json with open("./weight.json", "r") as f: data = json.loads(f.read()) data["SoVITS"][version] = sovits_path with open("./weight.json", "w") as f: json.dump(data, f) def change_gpt_weights(gpt_path): """切换GPT模型""" if "！" in gpt_path or "!" in gpt_path: gpt_path = name2gpt_path[gpt_path] tts_pipeline.init_t2s_weights(gpt_path) if is_direct_launch: current_sovits_path = sovits_path if 'sovits_path' in globals() else SoVITS_names[0] current_version = version if 'version' in globals() else "v2" write_last_selected_models(gpt_path, current_sovits_path, current_version) # ===================== 推理参数持久化包装函数 ===================== def init_infer_settings(): """初始化推理参数""" settings = load_infer_settings() return ( settings["batch_size"], settings["sample_steps"], settings["fragment_interval"], settings["speed_factor"], settings["top_k"], settings["top_p"], settings["temperature"], settings["repetition_penalty"], settings["how_to_cut"], settings["super_sampling"], settings["parallel_infer"], settings["split_bucket"], settings["seed"], settings["keep_random"] ) def save_infer_settings_wrapper(batch_size, sample_steps, fragment_interval, speed_factor, top_k, top_p, temperature, repetition_penalty, how_to_cut, super_sampling, parallel_infer, split_bucket, seed, keep_random): """保存推理参数包装器""" settings = { "batch_size": batch_size, "sample_steps": sample_steps, "fragment_interval": fragment_interval, "speed_factor": speed_factor, "top_k": top_k, "top_p": top_p, "temperature": temperature, "repetition_penalty": repetition_penalty, "how_to_cut": how_to_cut, "super_sampling": super_sampling, "parallel_infer": parallel_infer, "split_bucket": split_bucket, "seed": -1 if keep_random else seed, "keep_random": keep_random } return save_infer_settings_core(settings) # ===================== Gradio UI 构建（精简版） ===================== custom_css = """ /* 保存失败红边框样式（强制覆盖默认样式） */ .config-error-border { border: 2px solid #ff3b30 !important; border-radius: 4px !important; padding: 6px !important; } /* 保存成功/默认边框样式（还原原有样式） */ .config-default-border { border: 1px solid #e5e7eb !important; border-radius: 4px !important; padding: 6px !important; } /* 模拟弹窗样式：紧凑居中+自动换行+窄宽度 */ .simulated-popup { position: fixed; top: 50%; left: 50%; transform: translate(-50%, -50%); background: white; border: 1px solid #e5e7eb; border-radius: 8px; box-shadow: 0 4px 15px rgba(0, 0, 0, 0.1); padding: 15px; z-index: 9999; min-width: 300px; max-width: 350px; text-align: center; } /* 弹窗文本自动换行 */ .simulated-popup .markdown-text { word-wrap: break-word; line-height: 1.5; color: #333; } /* 弹窗遮罩层 */ .popup-mask { position: fixed; top: 0; left: 0; width: 100%; height: 100%; background: rgba(0, 0, 0, 0.4); z-index: 9998; } /* 按钮区域：紧凑间距+适配宽度 */ .popup-buttons { margin-top: 15px; display: flex; justify-content: center; gap: 10px; } /* 按钮样式优化：适配弹窗宽度 */ .popup-buttons button { min-width: 80px; padding: 6px 12px; } .btn-group-spacing { display: flex !important; flex-direction: row !important; gap: 10px !important; padding:5px 10px 5px 10px; align-items: center !important; justify-content: flex-start !important; } .btn-group-spacing button{ border-radius:5px; } """ with gr.Blocks(title="GPT-SoVITS WebUI", analytics_enabled=False, js=js, css=css + custom_css) as app: # 状态变量 current_preset = gr.State("") confirm_flag = gr.State(False) infer_confirm_flag = gr.State(False) infer_restore_flag = gr.State(False) # 顶部HTML gr.HTML(top_html.format( i18n("本软件以MIT协议开源, 作者不对软件具备任何控制力, 使用软件者、传播软件导出的声音者自负全责.") + i18n("如不认可该条款, 则不能使用或引用软件包内任何代码和文件. 详见根目录LICENSE.") ), elem_classes="markdown") # 模型切换区域 with gr.Column(): gr.Markdown(value=i18n("模型切换")) with gr.Row(): GPT_dropdown = gr.Dropdown( label=i18n("GPT模型列表"), choices=sorted(GPT_names, key=custom_sort_key), value=gpt_path, interactive=True, ) SoVITS_dropdown = gr.Dropdown( label=i18n("SoVITS模型列表"), choices=sorted(SoVITS_names, key=custom_sort_key), value=sovits_path, interactive=True, ) refresh_button = gr.Button(i18n("刷新模型路径"), variant="primary") refresh_button.click(fn=change_choices, inputs=[], outputs=[SoVITS_dropdown, GPT_dropdown]) # 核心功能区域 with gr.Row(): with gr.Column(): gr.Markdown(value=i18n("*请上传并填写参考信息（支持多组预设配置切换/删除，主参考音频为必填项，自动持久化不丢失）")) # 预设选择与名称输入 with gr.Row(): preset_dropdown = gr.Dropdown( label=i18n("选择预设参考配置"), choices=preset_names, value=preset_names[0] if preset_names else None, interactive=bool(preset_names), ) preset_name_input = gr.Textbox( label=i18n("当前配置名称（保存时使用）"), value="", placeholder=i18n("填写配置名称，点击保存按钮即可持久化"), lines=1, scale=1 ) # 配置提示框 save_config_msg = gr.Textbox( label=i18n("配置操作提示"), value="", lines=1, interactive=False, elem_classes=["config-default-border"] ) # 保存/删除按钮 with gr.Row(): save_ref_config_btn = gr.Button(i18n("保存当前参考为选中配置"), variant="primary") delete_ref_config_btn = gr.Button(i18n("删除当前选中配置"), variant="primary") # 音频与文本输入 with gr.Row(): inp_ref = gr.Audio( label=i18n("主参考音频(3~10秒)【必填，自动持久化】"), type="filepath", value=None ) inp_refs = gr.File( label=i18n("辅参考音频(可选多个)"), file_count="multiple", visible=True if model_version != "v3" else False, ) prompt_text = gr.Textbox( label=i18n("主参考音频的文本【可选】"), value="", lines=2 ) with gr.Row(): prompt_language = gr.Dropdown( label=i18n("主参考音频的语种"), choices=list(dict_language.keys()), value=i18n("中文") ) ref_text_free = gr.Checkbox( label=i18n("开启无参考文本模式"), value=False, interactive=True if model_version != "v3" else False, show_label=True, ) # 模拟弹窗（删除/覆盖） delete_mask = gr.Column(visible=False, elem_classes=["popup-mask"]) with gr.Column(visible=False, elem_classes=["simulated-popup"]) as delete_popup: delete_text = gr.Markdown(value="") with gr.Row(elem_classes=["popup-buttons"]): delete_confirm_btn = gr.Button(i18n("确认删除"), variant="primary") delete_cancel_btn = gr.Button(i18n("取消"), variant="primary") override_mask = gr.Column(visible=False, elem_classes=["popup-mask"]) with gr.Column(visible=False, elem_classes=["simulated-popup"]) as override_popup: override_text = gr.Markdown(value="") with gr.Row(elem_classes=["popup-buttons"]): override_confirm_btn = gr.Button(i18n("确认覆盖"), variant="primary") override_cancel_btn = gr.Button(i18n("取消"), variant="primary") # 事件绑定：预设切换 preset_dropdown.change( fn=on_preset_selected, inputs=[preset_dropdown], outputs=[preset_name_input, inp_ref, prompt_text, prompt_language] ) # 事件绑定：保存预设 save_ref_config_btn.click( fn=lambda pname: (pname.strip(), any(p["name"].strip() == pname.strip() for p in ref_presets)), inputs=[preset_name_input], outputs=[current_preset, confirm_flag] ).then( fn=lambda exists, pname: ( gr.update(visible=exists), gr.update(visible=exists), update_popup_text(pname, False) ), inputs=[confirm_flag, preset_name_input], outputs=[override_mask, override_popup, override_text] ).then( fn=save_ref_preset_wrapper, inputs=[preset_name_input, inp_ref, prompt_text, prompt_language, confirm_flag], outputs=[save_config_msg, save_config_msg, preset_dropdown] ) # 事件绑定：覆盖确认 override_confirm_btn.click( fn=lambda: (True, gr.update(visible=False), gr.update(visible=False)), inputs=[], outputs=[confirm_flag, override_mask, override_popup] ).then( fn=save_ref_preset_wrapper, inputs=[preset_name_input, inp_ref, prompt_text, prompt_language, confirm_flag], outputs=[save_config_msg, save_config_msg, preset_dropdown] ).then( fn=reset_confirm_result, inputs=[], outputs=[confirm_flag] ) # 事件绑定：覆盖取消 override_cancel_btn.click( fn=lambda: (False, gr.update(visible=False), gr.update(visible=False), i18n("覆盖操作已取消")), inputs=[], outputs=[confirm_flag, override_mask, override_popup, save_config_msg] ) # 事件绑定：删除预设 delete_ref_config_btn.click( fn=lambda pname: (pname, gr.update(visible=True), gr.update(visible=True), update_popup_text(pname, True)), inputs=[preset_dropdown], outputs=[current_preset, delete_mask, delete_popup, delete_text] ) # 事件绑定：删除确认 delete_confirm_btn.click( fn=lambda: (True, gr.update(visible=False), gr.update(visible=False)), inputs=[], outputs=[confirm_flag, delete_mask, delete_popup] ).then( fn=delete_ref_preset_wrapper, inputs=[preset_dropdown], outputs=[save_config_msg, preset_dropdown, preset_name_input, inp_ref, prompt_text, prompt_language] ).then( fn=reset_confirm_result, inputs=[], outputs=[confirm_flag] ) # 事件绑定：删除取消 delete_cancel_btn.click( fn=lambda pname: (False, gr.update(visible=False), gr.update(visible=False), i18n("删除操作已取消")), inputs=[preset_dropdown], outputs=[confirm_flag, delete_mask, delete_popup, save_config_msg] ) with gr.Column(): gr.Markdown(value=i18n("*请填写需要合成的目标文本和语种模式")) # 操作教程提示 gr.HTML('''

GPT-SoVITS 新增功能说明

1.默认模型：进入推理页面时，自动加载最后一次使用的模型。
2.参考音频：自动保存到 GPT_SoVITS/ref_audios/，多组预设可切换，重启不丢失。
3.推理参数：可保存自定义参数，恢复默认值，无需每次重新调整。
''') # 目标文本输入 text = gr.Textbox(label=i18n("需要合成的文本"), value="", lines=20, max_lines=20) text_language = gr.Dropdown( label=i18n("需要合成的文本的语种"), choices=list(dict_language.keys()), value=i18n("中文") ) # 推理设置区域 with gr.Group(): gr.Markdown(value=i18n("推理设置")) with gr.Row(): with gr.Column(): with gr.Row(): batch_size = gr.Slider(minimum=1, maximum=200, step=1, label=i18n("batch_size"), value=20, interactive=True) sample_steps = gr.Radio(label=i18n("采样步数(仅V3/4生效)"), value=32, choices=[4, 8, 16, 32, 64, 128], visible=True) with gr.Row(): fragment_interval = gr.Slider(minimum=0.01, maximum=1, step=0.01, label=i18n("分段间隔(秒)"), value=0.2, interactive=True) speed_factor = gr.Slider(minimum=0.6, maximum=1.65, step=0.05, label="语速", value=1.0, interactive=True) with gr.Row(): top_k = gr.Slider(minimum=1, maximum=100, step=1, label=i18n("top_k"), value=5, interactive=True) top_p = gr.Slider(minimum=0, maximum=1, step=0.05, label=i18n("top_p"), value=1, interactive=True) with gr.Row(): temperature = gr.Slider(minimum=0, maximum=1, step=0.05, label=i18n("temperature"), value=1, interactive=True) repetition_penalty = gr.Slider(minimum=0, maximum=2, step=0.05, label=i18n("重复惩罚"), value=1.35, interactive=True) with gr.Column(): with gr.Row(): how_to_cut = gr.Dropdown( label=i18n("怎么切"), choices=list(cut_method.keys()), value=i18n("凑四句一切"), interactive=True, scale=1, ) super_sampling = gr.Checkbox(label=i18n("音频超采样(仅V3生效)"), value=False, interactive=True, show_label=True) with gr.Row(): parallel_infer = gr.Checkbox(label=i18n("并行推理"), value=True, interactive=True, show_label=True) split_bucket = gr.Checkbox(label=i18n("数据分桶"), value=True, interactive=True, show_label=True) with gr.Row(): seed = gr.Number(label=i18n("随机种子"), value=-1) keep_random = gr.Checkbox(label=i18n("保持随机"), value=True, interactive=True, show_label=True) output = gr.Audio(label=i18n("输出的语音")) # 推理操作按钮 with gr.Row(): # ========== 新增：两个按钮（保存推理设置、恢复默认设置） ========== with gr.Row(elem_classes=["btn-group-spacing"]): save_infer_settings_btn = gr.Button(i18n("保存推理设置"), variant="primary") restore_default_settings_btn = gr.Button(i18n("恢复默认设置"), variant="primary") with gr.Row(elem_classes=["btn-group-spacing"]): inference_button = gr.Button(i18n("合成语音"), variant="primary") stop_infer = gr.Button(i18n("终止合成"), variant="primary") # ===================== 推理保存确认弹窗（原有，保持不变） ===================== infer_save_mask = gr.Column(visible=False, elem_classes=["popup-mask"]) with gr.Column(visible=False, elem_classes=["simulated-popup"]) as infer_save_popup: infer_save_text = gr.Markdown(value=i18n("确定要保存当前推理设置吗？保存后将覆盖原有配置！")) with gr.Row(elem_classes=["popup-buttons"]): infer_save_confirm_btn = gr.Button(i18n("确认保存"), variant="primary") infer_save_cancel_btn = gr.Button(i18n("取消"), variant="primary") # ===================== 【新增】：推理恢复默认确认弹窗 ===================== infer_restore_mask = gr.Column(visible=False, elem_classes=["popup-mask"]) with gr.Column(visible=False, elem_classes=["simulated-popup"]) as infer_restore_popup: infer_restore_text = gr.Markdown(value=i18n("确定要恢复推理设置为默认值吗？所有自定义参数将被覆盖，且无法恢复！")) with gr.Row(elem_classes=["popup-buttons"]): infer_restore_confirm_btn = gr.Button(i18n("确认恢复"), variant="primary") infer_restore_cancel_btn = gr.Button(i18n("取消"), variant="primary") # 推理保存专用提示框（原有，保持不变） infer_save_msg = gr.Textbox( label=i18n("推理设置操作提示"), value="", lines=1, interactive=False, elem_classes=["config-default-border"] ) # 事件绑定：保存推理参数 save_infer_settings_btn.click( fn=lambda: (gr.update(visible=True), gr.update(visible=True)), inputs=[], outputs=[infer_save_mask, infer_save_popup] ) infer_save_confirm_btn.click( fn=lambda: (True, gr.update(visible=False), gr.update(visible=False)), inputs=[], outputs=[infer_confirm_flag, infer_save_mask, infer_save_popup] ).then( fn=save_infer_settings_wrapper, inputs=[batch_size, sample_steps, fragment_interval, speed_factor, top_k, top_p, temperature, repetition_penalty, how_to_cut, super_sampling, parallel_infer, split_bucket, seed, keep_random], outputs=[infer_save_msg] ).then( fn=lambda: False, inputs=[], outputs=[infer_confirm_flag] ) infer_save_cancel_btn.click( fn=lambda: (False, gr.update(visible=False), gr.update(visible=False), i18n("保存操作已取消")), inputs=[], outputs=[infer_confirm_flag, infer_save_mask, infer_save_popup, infer_save_msg] ) # 事件绑定：恢复默认推理参数 restore_default_settings_btn.click( fn=lambda: (gr.update(visible=True), gr.update(visible=True)), inputs=[], outputs=[infer_restore_mask, infer_restore_popup] ) infer_restore_confirm_btn.click( fn=lambda: (True, gr.update(visible=False), gr.update(visible=False)), inputs=[], outputs=[infer_restore_flag, infer_restore_mask, infer_restore_popup] ).then( fn=restore_default_infer_settings_core, inputs=[], outputs=[batch_size, sample_steps, fragment_interval, speed_factor, top_k, top_p, temperature, repetition_penalty, how_to_cut, super_sampling, parallel_infer, split_bucket, seed, keep_random] ).then( fn=lambda: i18n("推理设置已恢复为默认值！"), inputs=[], outputs=[infer_save_msg] ).then( fn=lambda: False, inputs=[], outputs=[infer_restore_flag] ) infer_restore_cancel_btn.click( fn=lambda: (False, gr.update(visible=False), gr.update(visible=False), i18n("恢复操作已取消")), inputs=[], outputs=[infer_restore_flag, infer_restore_mask, infer_restore_popup, infer_save_msg] ) # 事件绑定：合成语音 inference_button.click( inference, inputs=[text, text_language, inp_ref, inp_refs, prompt_text, prompt_language, top_k, top_p, temperature, how_to_cut, batch_size, speed_factor, ref_text_free, split_bucket, fragment_interval, seed, keep_random, parallel_infer, repetition_penalty, sample_steps, super_sampling], outputs=[output, seed] ) # 事件绑定：终止合成 stop_infer.click(tts_pipeline.stop, [], []) # 事件绑定：SoVITS模型切换 SoVITS_dropdown.change( change_sovits_weights, inputs=[SoVITS_dropdown, GPT_dropdown, prompt_language, text_language], outputs=[prompt_language, text_language, prompt_text, prompt_language, text, text_language, sample_steps, inp_refs, ref_text_free, inference_button, preset_dropdown] ) # 事件绑定：GPT模型切换 GPT_dropdown.change(change_gpt_weights, [GPT_dropdown], []) # 文本切分工具 with gr.Group(): gr.Markdown(value=i18n("文本切分工具（太长的文本建议先切分）")) with gr.Row(): text_inp = gr.Textbox(label=i18n("切分前文本"), value="", lines=4) _how_to_cut = gr.Radio(label=i18n("怎么切"), choices=list(cut_method.keys()), value=i18n("凑四句一切"), interactive=True) cut_text = gr.Button(i18n("切分"), variant="primary") text_opt = gr.Textbox(label=i18n("切分后文本"), value="", lines=4) def to_cut(text_inp, how_to_cut): if not text_inp.strip(): return "" method = get_method(cut_method[how_to_cut]) return method(text_inp) cut_text.click(to_cut, [text_inp, _how_to_cut], [text_opt]) # 页面加载初始化 app.load(fn=init_ui_preset_config, inputs=[], outputs=[preset_dropdown, preset_name_input, inp_ref, prompt_text, prompt_language]) app.load(fn=init_infer_settings, inputs=[], outputs=[batch_size, sample_steps, fragment_interval, speed_factor, top_k, top_p, temperature, repetition_penalty, how_to_cut, super_sampling, parallel_infer, split_bucket, seed, keep_random]) # ===================== 应用入口 ===================== if __name__ == "__main__": # 初始化 weight.json if not os.path.exists("./weight.json"): with open("./weight.json", "w", encoding="utf-8") as file: json.dump({"GPT": {}, "SoVITS": {}}, file) # 直接打开推理页的模型配置初始化 if is_direct_launch: default_gpt_path = gpt_path default_sovits_path = sovits_path default_version = version last_selected_data = read_last_selected_models() if last_selected_data is None: init_last_selected_models(default_gpt_path, default_sovits_path, default_version) else: # 加载保存的模型配置 saved_gpt = last_selected_data["gpt_model_path"] saved_sovits = last_selected_data["sovits_model_path"] saved_version = last_selected_data["version"] if saved_gpt in GPT_names and os.path.exists(saved_gpt): gpt_path = saved_gpt if saved_sovits in SoVITS_names and os.path.exists(saved_sovits): sovits_path = saved_sovits if saved_version in ["v1", "v2", "v3", "v4"]: version = saved_version # 主动加载模型权重 valid_gpt_path = gpt_path if (gpt_path in GPT_names and os.path.exists(gpt_path)) else GPT_names[-1] if "！" in valid_gpt_path or "!" in valid_gpt_path: valid_gpt_path = name2gpt_path[valid_gpt_path] tts_pipeline.init_t2s_weights(valid_gpt_path) valid_sovits_path = sovits_path if (sovits_path in SoVITS_names and os.path.exists(sovits_path)) else SoVITS_names[0] if "！" in valid_sovits_path or "!" in valid_sovits_path: valid_sovits_path = name2sovits_path[valid_sovits_path] tts_pipeline.init_vits_weights(valid_sovits_path) # 更新 weight.json with open("./weight.json", "r", encoding="utf-8") as f: weight_data = json.loads(f.read()) weight_data["GPT"][version] = valid_gpt_path weight_data["SoVITS"][version] = valid_sovits_path with open("./weight.json", "w", encoding="utf-8") as f: json.dump(weight_data, f, ensure_ascii=False, indent=4) # 启动Gradio应用 app.queue().launch( server_name="0.0.0.0", inbrowser=True, share=is_share, server_port=infer_ttswebui, )