mirror of
https://github.com/RVC-Boss/GPT-SoVITS.git
synced 2026-04-29 21:00:42 +08:00
425 lines
16 KiB
Python
425 lines
16 KiB
Python
# -*- coding: utf-8 -*-
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"""
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GPT-SoVITS 持久化工具类
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包含：模型配置、参考音频、推理参数 的持久化读写与管理
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抽离自主文件，减少主文件臃肿，方便后续维护
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"""
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import json
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import yaml
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import hashlib
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import os
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import shutil
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import random
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from pathlib import Path
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# ===================== 全局配置（统一管理所有持久化文件路径） =====================
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# 模型持久化配置文件
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LAST_SELECTED_MODELS_JSON = Path("./last_selected_models.json")
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# 参考预设最后选中配置文件
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LAST_SELECTED_PRESET_JSON = Path("./last_selected_preset.json")
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# 参考音频持久化目录
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REF_AUDIO_DIR = Path("GPT_SoVITS/ref_audios")
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# 参考预设配置文件
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REF_PRESETS_YAML = Path("GPT_SoVITS/configs/ref_audios_presets.yaml")
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# 推理参数配置文件
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INFER_SETTINGS_JSON = Path("GPT_SoVITS/configs/infer_settings.json")
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# 参考音频配置常量
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MAX_FILENAME_LENGTH = 40
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INVALID_FILE_CHARS = set(r'\/:*?"<>|')
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# 默认推理参数
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DEFAULT_INFER_SETTINGS = {
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"batch_size": 20,
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"sample_steps": 32,
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"fragment_interval": 0.2,
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"speed_factor": 1.0,
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"top_k": 5,
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"top_p": 1.0,
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"temperature": 1.0,
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"repetition_penalty": 1.35,
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"how_to_cut": "凑四句一切",
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"super_sampling": False,
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"parallel_infer": True,
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"split_bucket": True,
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"seed": -1,
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"keep_random": True
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}
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# ===================== 通用工具函数（抽离重复逻辑） =====================
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def sanitize_filename(name):
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"""清理文件名中的非法字符，替换为下划线"""
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if not name:
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return "unnamed_preset"
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return ''.join(c if c not in INVALID_FILE_CHARS else '_' for c in name)
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def get_audio_md5(file_path, chunk_size=4096):
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"""计算音频文件的MD5值（取前8位），用于区分不同音频内容"""
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if not os.path.exists(file_path):
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return "invalid_file"
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try:
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md5 = hashlib.md5()
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with open(file_path, 'rb') as f:
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while chunk := f.read(chunk_size):
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md5.update(chunk)
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return md5.hexdigest()[:8]
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except Exception as e:
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print(f"计算音频MD5失败：{e}")
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return f"err_{random.randint(10000000, 99999999)}"
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def ensure_dir_exists(dir_path):
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"""确保目录存在，不存在则创建"""
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if dir_path and not dir_path.exists():
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dir_path.mkdir(exist_ok=True, parents=True)
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# ===================== 1. 模型配置持久化（last_selected_models.json） =====================
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def init_last_selected_models(gpt_default, sovits_default, current_version):
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"""初始化模型配置文件，写入默认模型路径"""
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ensure_dir_exists(LAST_SELECTED_MODELS_JSON.parent)
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init_data = {
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"gpt_model_path": gpt_default,
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"sovits_model_path": sovits_default,
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"version": current_version
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}
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with open(LAST_SELECTED_MODELS_JSON, "w", encoding="utf-8") as f:
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json.dump(init_data, f, ensure_ascii=False, indent=4)
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print(f"首次生成模型配置文件：{LAST_SELECTED_MODELS_JSON}")
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return init_data
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def read_last_selected_models():
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"""读取模型配置文件中的路径"""
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if not LAST_SELECTED_MODELS_JSON.exists():
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return None
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try:
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with open(LAST_SELECTED_MODELS_JSON, "r", encoding="utf-8") as f:
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data = json.load(f)
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# 校验必要字段
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required_fields = ["gpt_model_path", "sovits_model_path", "version"]
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for field in required_fields:
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if field not in data:
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return None
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return data
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except Exception as e:
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print(f"读取模型配置失败：{e}")
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return None
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def write_last_selected_models(gpt_path_new, sovits_path_new, current_version):
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"""写入新的模型路径到配置文件"""
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ensure_dir_exists(LAST_SELECTED_MODELS_JSON.parent)
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try:
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data = read_last_selected_models() or {}
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data["gpt_model_path"] = gpt_path_new
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data["sovits_model_path"] = sovits_path_new
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data["version"] = current_version
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with open(LAST_SELECTED_MODELS_JSON, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=4)
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except Exception as e:
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print(f"写入模型配置失败：{e}")
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# ===================== 2. 参考音频预设持久化（last_selected_preset.json + ref_audios_presets.yaml） =====================
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# 2.1 最后选中预设的读写清
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def read_last_selected_preset():
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"""读取最后一次选中的预设名称"""
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if not LAST_SELECTED_PRESET_JSON.exists():
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return None
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try:
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with open(LAST_SELECTED_PRESET_JSON, "r", encoding="utf-8") as f:
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data = json.load(f)
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return data.get("last_selected_preset")
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except Exception as e:
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print(f"读取最后选中预设失败：{e}")
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return None
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def write_last_selected_preset(preset_name):
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"""写入最后一次选中的预设名称"""
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ensure_dir_exists(LAST_SELECTED_PRESET_JSON.parent)
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try:
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data = {"last_selected_preset": preset_name.strip()}
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with open(LAST_SELECTED_PRESET_JSON, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=4)
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print(f"已记录最后选中的预设：{preset_name.strip()}")
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except Exception as e:
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print(f"写入最后选中预设失败：{e}")
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def clear_last_selected_preset():
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"""清空最后选中的预设记录"""
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if not LAST_SELECTED_PRESET_JSON.exists():
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return
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try:
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with open(LAST_SELECTED_PRESET_JSON, "w", encoding="utf-8") as f:
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json.dump({"last_selected_preset": ""}, f, ensure_ascii=False, indent=4)
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except Exception as e:
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print(f"清空最后选中预设失败：{e}")
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# 2.2 参考预设配置的加载/保存/删除
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def load_ref_presets():
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"""加载多组参考预设配置"""
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ensure_dir_exists(REF_PRESETS_YAML.parent)
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# 新增：配置文件不存在时，自动创建空文件
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if not REF_PRESETS_YAML.exists():
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with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f:
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yaml.dump([], f, indent=4, allow_unicode=True)
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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}")
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return []
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try:
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with open(REF_PRESETS_YAML, "r", encoding="utf-8") as f:
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presets = yaml.load(f, Loader=yaml.FullLoader) or []
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# 兼容旧格式转换
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if isinstance(presets, dict):
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presets = [{"name": "旧配置转换", "ref_audio_path": presets.get("ref_audio_path"),
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"prompt_text": presets.get("prompt_text", ""), "prompt_language": presets.get("prompt_language", "中文")}]
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# 补充缺失字段 + 校验音频路径
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default_template = {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"}
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for preset in presets:
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for key, value in default_template.items():
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preset.setdefault(key, value)
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# 校验音频路径有效性
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audio_path = preset["ref_audio_path"]
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if audio_path and not os.path.exists(str(audio_path)):
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preset["ref_audio_path"] = None
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# 清理冗余音频
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clean_unreferenced_audios(presets)
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print(f"参考预设加载成功，共 {len(presets)} 组")
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return presets
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except Exception as e:
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print(f"参考预设加载失败：{e}")
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return []
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def get_preset_by_name(preset_name, presets=None):
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"""根据配置名称查询对应的配置详情"""
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# 核心修复：先判断 preset_name 是否为 None，避免 AttributeError
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if preset_name is None:
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return {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"}
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if not presets:
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presets = load_ref_presets()
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# 现在再调用 strip()，确保 preset_name 不是 None
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preset_name_str = preset_name.strip()
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for preset in presets:
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if preset["name"].strip() == preset_name_str:
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return preset
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# 无匹配预设时，返回空的合法预设字典
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return {"name": "", "ref_audio_path": None, "prompt_text": "", "prompt_language": "中文"}
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def save_ref_preset_core(preset_name, ref_audio_path, prompt_text, prompt_language, confirm_override=False):
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"""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）"""
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ensure_dir_exists(REF_AUDIO_DIR)
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presets = load_ref_presets()
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preset_name = preset_name.strip()
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# 前置校验
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if not ref_audio_path or not os.path.exists(str(ref_audio_path)):
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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]
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if not preset_name:
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return "保存失败！配置名称不能为空。", False, [p["name"] for p in presets]
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# 音频持久化处理
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persistent_audio_path = get_persistent_audio_path(ref_audio_path, preset_name)
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if not persistent_audio_path:
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return "保存失败！音频文件持久化存储失败。", False, [p["name"] for p in presets]
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# 同名检测
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preset_index = -1
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for idx, p in enumerate(presets):
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if p["name"].strip() == preset_name:
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preset_index = idx
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break
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if preset_index >= 0 and not confirm_override:
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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]
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# 构造新配置
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new_preset = {
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"name": preset_name,
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"ref_audio_path": persistent_audio_path,
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"prompt_text": prompt_text,
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"prompt_language": prompt_language
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}
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# 更新配置列表
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is_new_preset = preset_index < 0
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if preset_index >= 0:
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presets[preset_index] = new_preset
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tip = "同名配置已覆盖！"
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else:
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presets.append(new_preset)
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tip = "新配置已新增！"
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# 写入配置文件
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try:
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with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f:
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yaml.dump(presets, f, indent=4, allow_unicode=True)
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# 新增预设自动记录为最后选中
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if is_new_preset:
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write_last_selected_preset(preset_name)
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preset_names = [p["name"] for p in presets]
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return f"配置保存成功！{tip}", True, preset_names
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except Exception as e:
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return f"保存失败：{str(e)}", False, [p["name"] for p in presets]
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def delete_ref_preset_core(preset_name):
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"""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）"""
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presets = load_ref_presets()
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preset_name = preset_name.strip()
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if not presets:
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return "暂无配置可删除！", [], None
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# 获取待删除音频路径
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target_audio_path = None
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for p in presets:
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if p["name"].strip() == preset_name:
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target_audio_path = p.get("ref_audio_path")
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break
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# 过滤删除
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presets = [p for p in presets if p["name"].strip() != preset_name]
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# 写入配置文件
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try:
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with open(REF_PRESETS_YAML, "w", encoding="utf-8") as f:
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yaml.dump(presets, f, indent=4, allow_unicode=True)
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# 删除对应音频
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if target_audio_path and os.path.exists(target_audio_path):
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os.unlink(target_audio_path)
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print(f"同步删除配置对应音频：{target_audio_path}")
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# 清空最后选中记录（若删除的是最后选中的预设）
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last_selected = read_last_selected_preset()
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if last_selected and last_selected == preset_name:
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clear_last_selected_preset()
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preset_names = [p["name"] for p in presets]
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new_selected = preset_names[0] if preset_names else None
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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"
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return tip, preset_names, new_selected
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except Exception as e:
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return f"删除失败：{str(e)}", [p["name"] for p in presets], preset_name
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# 2.3 参考音频文件管理
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def get_persistent_audio_path(src_audio_path, preset_name):
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"""获取音频持久化路径，清理同配置名旧音频"""
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if not src_audio_path or not os.path.exists(src_audio_path):
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return None
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# 清理文件名
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safe_preset_name = sanitize_filename(preset_name)
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safe_preset_name = safe_preset_name[:MAX_FILENAME_LENGTH]
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# 提取后缀
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src_suffix = Path(src_audio_path).suffix.lower()
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if not src_suffix or src_suffix not in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]:
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src_suffix = ".wav"
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# 计算MD5
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audio_md5 = get_audio_md5(src_audio_path)
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dst_filename = f"{safe_preset_name}_{audio_md5}{src_suffix}"
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dst_path = REF_AUDIO_DIR / dst_filename
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# 清理同配置名旧音频
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for old_audio in REF_AUDIO_DIR.glob(f"{safe_preset_name}_*"):
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if old_audio.suffix.lower() in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]:
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try:
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old_audio.unlink()
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except Exception as e:
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print(f"清理旧音频失败：{e}")
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# 复制新音频
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try:
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shutil.copy2(src_audio_path, dst_path)
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return str(dst_path)
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except Exception as e:
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print(f"音频持久化复制失败：{e}")
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return None
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def clean_unreferenced_audios(presets):
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"""清理未被任何预设引用的冗余音频"""
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if not REF_AUDIO_DIR.exists():
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return
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# 收集已引用音频
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referenced = set()
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for preset in presets:
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audio_path = preset.get("ref_audio_path")
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if audio_path and os.path.exists(audio_path):
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referenced.add(Path(audio_path).absolute())
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# 删除未引用音频
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deleted_count = 0
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for audio_file in REF_AUDIO_DIR.glob("*"):
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if audio_file.is_file() and audio_file.suffix.lower() in [".wav", ".mp3", ".flac", ".ogg", ".m4a"]:
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if audio_file.absolute() not in referenced:
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try:
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audio_file.unlink()
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deleted_count += 1
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except Exception as e:
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print(f"清理冗余音频失败：{e}")
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if deleted_count > 0:
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print(f"清理冗余未引用音频 {deleted_count} 个")
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# ===================== 3. 推理参数持久化（infer_settings.json） =====================
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def load_infer_settings():
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"""加载推理参数配置"""
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ensure_dir_exists(INFER_SETTINGS_JSON.parent)
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if not INFER_SETTINGS_JSON.exists():
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return DEFAULT_INFER_SETTINGS
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try:
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with open(INFER_SETTINGS_JSON, "r", encoding="utf-8") as f:
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saved = json.load(f)
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return {**DEFAULT_INFER_SETTINGS, **saved}
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except Exception as e:
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print(f"加载推理参数失败，使用默认值：{e}")
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return DEFAULT_INFER_SETTINGS
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def save_infer_settings_core(settings):
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"""保存推理参数核心逻辑（返回：提示信息）"""
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ensure_dir_exists(INFER_SETTINGS_JSON.parent)
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try:
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with open(INFER_SETTINGS_JSON, "w", encoding="utf-8") as f:
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json.dump(settings, f, indent=4, ensure_ascii=False)
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# 精简日志输出
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print(f"✅ 推理配置保存成功：{INFER_SETTINGS_JSON.absolute()}")
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return "推理设置保存成功！已覆盖原有配置文件。"
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except Exception as e:
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print(f"❌ 推理配置保存失败：{e}")
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return f"推理设置保存失败：{str(e)}"
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def restore_default_infer_settings_core():
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"""恢复推理参数默认值核心逻辑（返回：默认参数列表）"""
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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"]
|
||
] |