Merge 7f6787121bca21f78a77a9c9de9206f9b48179d7 into ea2d2a81667239d37615697e8f0056e35bab2db6

.gitignore

@@ -193,3 +193,8 @@ cython_debug/
 
 # PyPI configuration file
 .pypirc
+/.vs
+/GPT_SoVITS/configs/tts_infer.yaml
+/GPT_SoVITS/configs/infer_settings.json
+/last_selected_preset.json
+/last_selected_models.json

GPT_SoVITS/configs/tts_infer.yaml

@@ -1,56 +0,0 @@
-custom:
-  bert_base_path: GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large
-  cnhuhbert_base_path: GPT_SoVITS/pretrained_models/chinese-hubert-base
-  device: cuda
-  is_half: true
-  t2s_weights_path: GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt
-  version: v2
-  vits_weights_path: GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth
-v1:
-  bert_base_path: GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large
-  cnhuhbert_base_path: GPT_SoVITS/pretrained_models/chinese-hubert-base
-  device: cpu
-  is_half: false
-  t2s_weights_path: GPT_SoVITS/pretrained_models/s1bert25hz-2kh-longer-epoch=68e-step=50232.ckpt
-  version: v1
-  vits_weights_path: GPT_SoVITS/pretrained_models/s2G488k.pth
-v2:
-  bert_base_path: GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large
-  cnhuhbert_base_path: GPT_SoVITS/pretrained_models/chinese-hubert-base
-  device: cpu
-  is_half: false
-  t2s_weights_path: GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s1bert25hz-5kh-longer-epoch=12-step=369668.ckpt
-  version: v2
-  vits_weights_path: GPT_SoVITS/pretrained_models/gsv-v2final-pretrained/s2G2333k.pth
-v2Pro:
-  bert_base_path: GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large
-  cnhuhbert_base_path: GPT_SoVITS/pretrained_models/chinese-hubert-base
-  device: cpu
-  is_half: false
-  t2s_weights_path: GPT_SoVITS/pretrained_models/s1v3.ckpt
-  version: v2Pro
-  vits_weights_path: GPT_SoVITS/pretrained_models/v2Pro/s2Gv2Pro.pth
-v2ProPlus:
-  bert_base_path: GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large
-  cnhuhbert_base_path: GPT_SoVITS/pretrained_models/chinese-hubert-base
-  device: cpu
-  is_half: false
-  t2s_weights_path: GPT_SoVITS/pretrained_models/s1v3.ckpt
-  version: v2ProPlus
-  vits_weights_path: GPT_SoVITS/pretrained_models/v2Pro/s2Gv2ProPlus.pth
-v3:
-  bert_base_path: GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large
-  cnhuhbert_base_path: GPT_SoVITS/pretrained_models/chinese-hubert-base
-  device: cpu
-  is_half: false
-  t2s_weights_path: GPT_SoVITS/pretrained_models/s1v3.ckpt
-  version: v3
-  vits_weights_path: GPT_SoVITS/pretrained_models/s2Gv3.pth
-v4:
-  bert_base_path: GPT_SoVITS/pretrained_models/chinese-roberta-wwm-ext-large
-  cnhuhbert_base_path: GPT_SoVITS/pretrained_models/chinese-hubert-base
-  device: cpu
-  is_half: false
-  t2s_weights_path: GPT_SoVITS/pretrained_models/s1v3.ckpt
-  version: v4
-  vits_weights_path: GPT_SoVITS/pretrained_models/gsv-v4-pretrained/s2Gv4.pth

GPT_SoVITS/persistence_tools.py

@@ -0,0 +1,425 @@
+# -*- coding: utf-8 -*-
+"""
+GPT-SoVITS 持久化工具类
+包含：模型配置、参考音频、推理参数 的持久化读写与管理
+抽离自主文件，减少主文件臃肿，方便后续维护
+"""
+import json
+import yaml
+import hashlib
+import os
+import shutil
+import random
+from pathlib import Path
+
+# ===================== 全局配置（统一管理所有持久化文件路径） =====================
+# 模型持久化配置文件
+LAST_SELECTED_MODELS_JSON = Path("./last_selected_models.json")
+# 参考预设最后选中配置文件
+LAST_SELECTED_PRESET_JSON = Path("./last_selected_preset.json")
+# 参考音频持久化目录
+REF_AUDIO_DIR = Path("GPT_SoVITS/ref_audios")
+# 参考预设配置文件
+REF_PRESETS_YAML = Path("GPT_SoVITS/configs/ref_audios_presets.yaml")
+# 推理参数配置文件
+INFER_SETTINGS_JSON = Path("GPT_SoVITS/configs/infer_settings.json")
+
+# 参考音频配置常量
+MAX_FILENAME_LENGTH = 40
+INVALID_FILE_CHARS = set(r'\/:*?"<>|')
+
+# 默认推理参数
+DEFAULT_INFER_SETTINGS = {
+    "batch_size": 20,
+    "sample_steps": 32,
+    "fragment_interval": 0.2,
+    "speed_factor": 1.0,
+    "top_k": 5,
+    "top_p": 1.0,
+    "temperature": 1.0,
+    "repetition_penalty": 1.35,
+    "how_to_cut": "凑四句一切",
+    "super_sampling": False,
+    "parallel_infer": True,
+    "split_bucket": True,
+    "seed": -1,
+    "keep_random": True
+}
+
+# ===================== 通用工具函数（抽离重复逻辑） =====================
+def sanitize_filename(name):
+    """清理文件名中的非法字符，替换为下划线"""
+    if not name:
+        return "unnamed_preset"
+    return ''.join(c if c not in INVALID_FILE_CHARS else '_' for c in name)
+
+def get_audio_md5(file_path, chunk_size=4096):
+    """计算音频文件的MD5值（取前8位），用于区分不同音频内容"""
+    if not os.path.exists(file_path):
+        return "invalid_file"
+    try:
+        md5 = hashlib.md5()
+        with open(file_path, 'rb') as f:
+            while chunk := f.read(chunk_size):
+                md5.update(chunk)
+        return md5.hexdigest()[:8]
+    except Exception as e:
+        print(f"计算音频MD5失败：{e}")
+        return f"err_{random.randint(10000000, 99999999)}"
+
+def ensure_dir_exists(dir_path):
+    """确保目录存在，不存在则创建"""
+    if dir_path and not dir_path.exists():
+        dir_path.mkdir(exist_ok=True, parents=True)
+
+# ===================== 1. 模型配置持久化（last_selected_models.json） =====================
+def init_last_selected_models(gpt_default, sovits_default, current_version):
+    """初始化模型配置文件，写入默认模型路径"""
+    ensure_dir_exists(LAST_SELECTED_MODELS_JSON.parent)
+    init_data = {
+        "gpt_model_path": gpt_default,
+        "sovits_model_path": sovits_default,
+        "version": current_version
+    }
+    with open(LAST_SELECTED_MODELS_JSON, "w", encoding="utf-8") as f:
+        json.dump(init_data, f, ensure_ascii=False, indent=4)
+    print(f"首次生成模型配置文件：{LAST_SELECTED_MODELS_JSON}")
+    return init_data
+
+def read_last_selected_models():
+    """读取模型配置文件中的路径"""
+    if not LAST_SELECTED_MODELS_JSON.exists():
+        return None
+    try:
+        with open(LAST_SELECTED_MODELS_JSON, "r", encoding="utf-8") as f:
+            data = json.load(f)
+        # 校验必要字段
+        required_fields = ["gpt_model_path", "sovits_model_path", "version"]
+        for field in required_fields:
+            if field not in data:
+                return None
+        return data
+    except Exception as e:
+        print(f"读取模型配置失败：{e}")
+        return None
+
+def write_last_selected_models(gpt_path_new, sovits_path_new, current_version):
+    """写入新的模型路径到配置文件"""
+    ensure_dir_exists(LAST_SELECTED_MODELS_JSON.parent)
+    try:
+        data = read_last_selected_models() or {}
+        data["gpt_model_path"] = gpt_path_new
+        data["sovits_model_path"] = sovits_path_new
+        data["version"] = current_version
+        with open(LAST_SELECTED_MODELS_JSON, "w", encoding="utf-8") as f:
+            json.dump(data, f, ensure_ascii=False, indent=4)
+    except Exception as e:
+        print(f"写入模型配置失败：{e}")
+
+# ===================== 2. 参考音频预设持久化（last_selected_preset.json + ref_audios_presets.yaml） =====================
+# 2.1 最后选中预设的读写清
+def read_last_selected_preset():
+    """读取最后一次选中的预设名称"""
+    if not LAST_SELECTED_PRESET_JSON.exists():
+        return None
+    try:
+        with open(LAST_SELECTED_PRESET_JSON, "r", encoding="utf-8") as f:
+            data = json.load(f)
+        return data.get("last_selected_preset")
+    except Exception as e:
+        print(f"读取最后选中预设失败：{e}")
+        return None
+
+def write_last_selected_preset(preset_name):
+    """写入最后一次选中的预设名称"""
+    ensure_dir_exists(LAST_SELECTED_PRESET_JSON.parent)
+    try:
+        data = {"last_selected_preset": preset_name.strip()}
+        with open(LAST_SELECTED_PRESET_JSON, "w", encoding="utf-8") as f:
+            json.dump(data, f, ensure_ascii=False, indent=4)
+        print(f"已记录最后选中的预设：{preset_name.strip()}")
+    except Exception as e:
+        print(f"写入最后选中预设失败：{e}")
+
+def clear_last_selected_preset():
+    """清空最后选中的预设记录"""
+    if not LAST_SELECTED_PRESET_JSON.exists():
+        return
+    try:
+        with open(LAST_SELECTED_PRESET_JSON, "w", encoding="utf-8") as f:
+            json.dump({"last_selected_preset": ""}, f, ensure_ascii=False, indent=4)
+    except Exception as e:
+        print(f"清空最后选中预设失败：{e}")
+
+# 2.2 参考预设配置的加载/保存/删除
+def load_ref_presets():
+    """加载多组参考预设配置"""
+    ensure_dir_exists(REF_PRESETS_YAML.parent)
+    
+    # 新增：配置文件不存在时，自动创建空文件
+    if not REF_PRESETS_YAML.exists():
+        with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f:
+            yaml.dump([], f, indent=4, allow_unicode=True)
+        print(f"暂未检测到参考预设配置文件，已自动创建空文件：{REF_PRESETS_YAML}")
+        return []
+    
+    try:
+        with open(REF_PRESETS_YAML, "r", encoding="utf-8") as f:
+            presets = yaml.load(f, Loader=yaml.FullLoader) or []
+        
+        # 兼容旧格式转换
+        if isinstance(presets, dict):
+            presets = [{"name": "旧配置转换", "ref_audio_path": presets.get("ref_audio_path"),
+                        "prompt_text": presets.get("prompt_text", ""), "prompt_language": presets.get("prompt_language", "中文")}]
+        
+        # 补充缺失字段 + 校验音频路径
+        default_template = {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"}
+        for preset in presets:
+            for key, value in default_template.items():
+                preset.setdefault(key, value)
+            # 校验音频路径有效性
+            audio_path = preset["ref_audio_path"]
+            if audio_path and not os.path.exists(str(audio_path)):
+                preset["ref_audio_path"] = None
+        
+        # 清理冗余音频
+        clean_unreferenced_audios(presets)
+        print(f"参考预设加载成功，共 {len(presets)} 组")
+        return presets
+    except Exception as e:
+        print(f"参考预设加载失败：{e}")
+        return []
+
+def get_preset_by_name(preset_name, presets=None):
+    """根据配置名称查询对应的配置详情"""
+    # 核心修复：先判断 preset_name 是否为 None，避免 AttributeError
+    if preset_name is None:
+        return {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"}
+    
+    if not presets:
+        presets = load_ref_presets()
+    
+    # 现在再调用 strip()，确保 preset_name 不是 None
+    preset_name_str = preset_name.strip()
+    for preset in presets:
+        if preset["name"].strip() == preset_name_str:
+            return preset
+    
+    # 无匹配预设时，返回空的合法预设字典
+    return {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"}
+
+def save_ref_preset_core(preset_name, ref_audio_path, prompt_text, prompt_language, confirm_override=False):
+    """保存/覆盖参考预设核心逻辑（返回：提示信息、是否成功、预设列表）"""
+    ensure_dir_exists(REF_AUDIO_DIR)
+    presets = load_ref_presets()
+    preset_name = preset_name.strip()
+    
+    # 前置校验
+    if not ref_audio_path or not os.path.exists(str(ref_audio_path)):
+        return "保存失败！请先上传有效的主参考音频文件。", False, [p["name"] for p in presets]
+    if not preset_name:
+        return "保存失败！配置名称不能为空。", False, [p["name"] for p in presets]
+    
+    # 音频持久化处理
+    persistent_audio_path = get_persistent_audio_path(ref_audio_path, preset_name)
+    if not persistent_audio_path:
+        return "保存失败！音频文件持久化存储失败。", False, [p["name"] for p in presets]
+    
+    # 同名检测
+    preset_index = -1
+    for idx, p in enumerate(presets):
+        if p["name"].strip() == preset_name:
+            preset_index = idx
+            break
+    
+    if preset_index >= 0 and not confirm_override:
+        return f"配置「{preset_name}」已存在，如需替换请确认覆盖！", False, [p["name"] for p in presets]
+    
+    # 构造新配置
+    new_preset = {
+        "name": preset_name,
+        "ref_audio_path": persistent_audio_path,
+        "prompt_text": prompt_text,
+        "prompt_language": prompt_language
+    }
+    
+    # 更新配置列表
+    is_new_preset = preset_index < 0
+    if preset_index >= 0:
+        presets[preset_index] = new_preset
+        tip = "同名配置已覆盖！"
+    else:
+        presets.append(new_preset)
+        tip = "新配置已新增！"
+    
+    # 写入配置文件
+    try:
+        with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f:
+            yaml.dump(presets, f, indent=4, allow_unicode=True)
+        
+        # 新增预设自动记录为最后选中
+        if is_new_preset:
+            write_last_selected_preset(preset_name)
+        
+        preset_names = [p["name"] for p in presets]
+        return f"配置保存成功！{tip}", True, preset_names
+    except Exception as e:
+        return f"保存失败：{str(e)}", False, [p["name"] for p in presets]
+
+def delete_ref_preset_core(preset_name):
+    """删除参考预设核心逻辑（返回：提示信息、预设列表、默认选中预设）"""
+    presets = load_ref_presets()
+    preset_name = preset_name.strip()
+    
+    if not presets:
+        return "暂无配置可删除！", [], None
+    
+    # 获取待删除音频路径
+    target_audio_path = None
+    for p in presets:
+        if p["name"].strip() == preset_name:
+            target_audio_path = p.get("ref_audio_path")
+            break
+    
+    # 过滤删除
+    presets = [p for p in presets if p["name"].strip() != preset_name]
+    
+    # 写入配置文件
+    try:
+        with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f:
+            yaml.dump(presets, f, indent=4, allow_unicode=True)
+        
+        # 删除对应音频
+        if target_audio_path and os.path.exists(target_audio_path):
+            os.unlink(target_audio_path)
+            print(f"同步删除配置对应音频：{target_audio_path}")
+        
+        # 清空最后选中记录（若删除的是最后选中的预设）
+        last_selected = read_last_selected_preset()
+        if last_selected and last_selected == preset_name:
+            clear_last_selected_preset()
+        
+        preset_names = [p["name"] for p in presets]
+        new_selected = preset_names[0] if preset_names else None
+        tip = "配置删除成功！已同步清理对应音频文件" if preset_names else "配置删除成功！已同步清理对应音频文件，当前无剩余配置"
+        return tip, preset_names, new_selected
+    except Exception as e:
+        return f"删除失败：{str(e)}", [p["name"] for p in presets], preset_name
+
+# 2.3 参考音频文件管理
+def get_persistent_audio_path(src_audio_path, preset_name):
+    """获取音频持久化路径，清理同配置名旧音频"""
+    if not src_audio_path or not os.path.exists(src_audio_path):
+        return None
+    
+    # 清理文件名
+    safe_preset_name = sanitize_filename(preset_name)
+    safe_preset_name = safe_preset_name[:MAX_FILENAME_LENGTH]
+    
+    # 提取后缀
+    src_suffix = Path(src_audio_path).suffix.lower()
+    if not src_suffix or src_suffix not in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]:
+        src_suffix = ".wav"
+    
+    # 计算MD5
+    audio_md5 = get_audio_md5(src_audio_path)
+    dst_filename = f"{safe_preset_name}_{audio_md5}{src_suffix}"
+    dst_path = REF_AUDIO_DIR / dst_filename
+    
+    # 清理同配置名旧音频
+    for old_audio in REF_AUDIO_DIR.glob(f"{safe_preset_name}_*"):
+        if old_audio.suffix.lower() in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]:
+            try:
+                old_audio.unlink()
+            except Exception as e:
+                print(f"清理旧音频失败：{e}")
+    
+    # 复制新音频
+    try:
+        shutil.copy2(src_audio_path, dst_path)
+        return str(dst_path)
+    except Exception as e:
+        print(f"音频持久化复制失败：{e}")
+        return None
+
+def clean_unreferenced_audios(presets):
+    """清理未被任何预设引用的冗余音频"""
+    if not REF_AUDIO_DIR.exists():
+        return
+    
+    # 收集已引用音频
+    referenced = set()
+    for preset in presets:
+        audio_path = preset.get("ref_audio_path")
+        if audio_path and os.path.exists(audio_path):
+            referenced.add(Path(audio_path).absolute())
+    
+    # 删除未引用音频
+    deleted_count = 0
+    for audio_file in REF_AUDIO_DIR.glob("*"):
+        if audio_file.is_file() and audio_file.suffix.lower() in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]:
+            if audio_file.absolute() not in referenced:
+                try:
+                    audio_file.unlink()
+                    deleted_count += 1
+                except Exception as e:
+                    print(f"清理冗余音频失败：{e}")
+    
+    if deleted_count > 0:
+        print(f"清理冗余未引用音频 {deleted_count} 个")
+
+# ===================== 3. 推理参数持久化（infer_settings.json） =====================
+def load_infer_settings():
+    """加载推理参数配置"""
+    ensure_dir_exists(INFER_SETTINGS_JSON.parent)
+    if not INFER_SETTINGS_JSON.exists():
+        return DEFAULT_INFER_SETTINGS
+    try:
+        with open(INFER_SETTINGS_JSON, "r", encoding="utf-8") as f:
+            saved = json.load(f)
+        return {**DEFAULT_INFER_SETTINGS, **saved}
+    except Exception as e:
+        print(f"加载推理参数失败，使用默认值：{e}")
+        return DEFAULT_INFER_SETTINGS
+
+def save_infer_settings_core(settings):
+    """保存推理参数核心逻辑（返回：提示信息）"""
+    ensure_dir_exists(INFER_SETTINGS_JSON.parent)
+    try:
+        with open(INFER_SETTINGS_JSON, "w", encoding="utf-8") as f:
+            json.dump(settings, f, indent=4, ensure_ascii=False)
+        
+        # 精简日志输出
+        print(f"✅ 推理配置保存成功：{INFER_SETTINGS_JSON.absolute()}")
+        return "推理设置保存成功！已覆盖原有配置文件。"
+    except Exception as e:
+        print(f"❌ 推理配置保存失败：{e}")
+        return f"推理设置保存失败：{str(e)}"
+
+def restore_default_infer_settings_core():
+    """恢复推理参数默认值核心逻辑（返回：默认参数列表）"""
+    ensure_dir_exists(INFER_SETTINGS_JSON.parent)
+    try:
+        with open(INFER_SETTINGS_JSON, "w", encoding="utf-8") as f:
+            json.dump(DEFAULT_INFER_SETTINGS, f, indent=4, ensure_ascii=False)
+        print(f"✅ 推理配置已恢复默认值：{INFER_SETTINGS_JSON.absolute()}")
+    except Exception as e:
+        print(f"❌ 推理配置恢复默认失败：{e}")
+    
+    # 返回默认参数（按顺序对应UI组件）
+    return [
+        DEFAULT_INFER_SETTINGS["batch_size"],
+        DEFAULT_INFER_SETTINGS["sample_steps"],
+        DEFAULT_INFER_SETTINGS["fragment_interval"],
+        DEFAULT_INFER_SETTINGS["speed_factor"],
+        DEFAULT_INFER_SETTINGS["top_k"],
+        DEFAULT_INFER_SETTINGS["top_p"],
+        DEFAULT_INFER_SETTINGS["temperature"],
+        DEFAULT_INFER_SETTINGS["repetition_penalty"],
+        DEFAULT_INFER_SETTINGS["how_to_cut"],
+        DEFAULT_INFER_SETTINGS["super_sampling"],
+        DEFAULT_INFER_SETTINGS["parallel_infer"],
+        DEFAULT_INFER_SETTINGS["split_bucket"],
+        DEFAULT_INFER_SETTINGS["seed"],
+        DEFAULT_INFER_SETTINGS["keep_random"]
+    ]

gowebui_batched_infer.bat

@@ -0,0 +1,33 @@
+@echo off
+:: 1. 切换命令行编码为UTF-8，解决中文显示乱码（必须放在最前面）
+chcp 65001 > nul
+
+:: 2. 获取当前bat文件所在目录并格式化
+set "SCRIPT_DIR=%~dp0"
+set "SCRIPT_DIR=%SCRIPT_DIR:~0,-1%"
+
+:: 3. 切换到脚本根目录
+cd /d "%SCRIPT_DIR%"
+
+:: 4. 创建专属TEMP目录（补充主页面的核心步骤）
+if not exist "TEMP" md "TEMP"
+set "TEMP=%SCRIPT_DIR%\TEMP"
+
+:: 5. 设置核心环境变量（补充推理脚本依赖的配置）
+set "version=v2Pro"
+:: 语言配置
+set "language=zh_CN"
+:: 启用半精度推理（GPU用户推荐，CPU用户改为False）
+set "is_half=True"
+:: 指定GPU卡号（多卡可修改，无GPU则删除此行）
+set "_CUDA_VISIBLE_DEVICES=0"
+
+:: 6. 将runtime目录加入环境变量，确保能调用内置python
+set "PATH=%SCRIPT_DIR%\runtime;%PATH%"
+
+:: 7. 直接启动并行推理脚本，传入中文语言参数
+echo 正在启动GPT-SoVITS并行推理页面...
+runtime\python.exe -I GPT_SoVITS/inference_webui_fast.py zh_CN
+
+:: 8. 执行完成后暂停，便于查看报错信息
+pause