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将GPT-SoVITS TTS移出built in，优化kfc提示词

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Windpicker-owo
2025-12-08 22:08:31 +08:00
parent f76cf36bae
commit a2be8685c2
13 changed files with 49 additions and 1738 deletions
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4
src/chat/replyer/default_generator.py
View File

@@ -131,7 +131,7 @@ def init_prompt():
{group_chat_reminder_block} {group_chat_reminder_block}
- 在称呼用户时，请使用更自然的昵称或简称。对于长英文名，可使用首字母缩写；对于中文名，可提炼合适的简称。禁止直接复述复杂的用户名或输出用户名中的任何符号，让称呼更像人类习惯，注意，简称不是必须的，合理的使用。 - 在称呼用户时，请使用更自然的昵称或简称。对于长英文名，可使用首字母缩写；对于中文名，可提炼合适的简称。禁止直接复述复杂的用户名或输出用户名中的任何符号，让称呼更像人类习惯，注意，简称不是必须的，合理的使用。
你的回复应该是一条简短、完整且口语化的回复。 你的回复应该是一条简短、且口语化的回复。
-------------------------------- --------------------------------
{time_block} {time_block}
@@ -218,7 +218,7 @@ If you need to use the search tool, please directly call the function "lpmm_sear
{safety_guidelines_block} {safety_guidelines_block}
{group_chat_reminder_block} {group_chat_reminder_block}
- 在称呼用户时，请使用更自然的昵称或简称。对于长英文名，可使用首字母缩写；对于中文名，可提炼合适的简称。禁止直接复述复杂的用户名或输出用户名中的任何符号，让称呼更像人类习惯，注意，简称不是必须的，合理的使用。 - 在称呼用户时，请使用更自然的昵称或简称。对于长英文名，可使用首字母缩写；对于中文名，可提炼合适的简称。禁止直接复述复杂的用户名或输出用户名中的任何符号，让称呼更像人类习惯，注意，简称不是必须的，合理的使用。
你的回复应该是一条简短、完整且口语化的回复。 你的回复应该是一条简短、且口语化的回复。
-------------------------------- --------------------------------
{time_block} {time_block}

11
src/plugins/built_in/kokoro_flow_chatter/prompt/builder.py
View File

@@ -208,6 +208,10 @@ class PromptBuilder:
if personality.identity: if personality.identity:
parts.append(personality.identity) parts.append(personality.identity)
background_story = getattr(personality, "background_story", "")
if background_story:
parts.append(f"## 背景故事（请理解并作为行动依据，但不要在对话中直接复述）\n{background_story}")
return "\n\n".join(parts) if parts else "你是一个温暖、真诚的人。" return "\n\n".join(parts) if parts else "你是一个温暖、真诚的人。"
def _build_safety_guidelines_block(self) -> str: def _build_safety_guidelines_block(self) -> str:
@@ -245,6 +249,7 @@ class PromptBuilder:
# 2. 添加学习到的表达习惯 # 2. 添加学习到的表达习惯
if learned_habits and learned_habits.strip(): if learned_habits and learned_habits.strip():
# 如果 learned_habits 已经有标题，直接追加；否则添加标题 # 如果 learned_habits 已经有标题，直接追加；否则添加标题
parts.append("你可以参考以下的语言习惯，当情景合适就使用，但不要生硬使用，以合理的方式结合到你的回复中：")
if learned_habits.startswith("### "): if learned_habits.startswith("### "):
# 移除原有标题，统一格式 # 移除原有标题，统一格式
lines = learned_habits.split("\n") lines = learned_habits.split("\n")
@@ -499,7 +504,7 @@ class PromptBuilder:
# 跳过没有实际文本内容的消息 # 跳过没有实际文本内容的消息
content = getattr(msg, "processed_plain_text", "") or getattr(msg, "display_message", "") content = getattr(msg, "processed_plain_text", "") or getattr(msg, "display_message", "")
if not content or not content.strip(): if not content or not content.strip() or content == "":
continue continue
filtered.append(msg) filtered.append(msg)
@@ -849,7 +854,7 @@ class PromptBuilder:
"thought": "你的想法", "thought": "你的想法",
"actions": [{"type": "kfc_reply", "content": "你的回复"}], "actions": [{"type": "kfc_reply", "content": "你的回复"}],
"expected_reaction": "期待的反应", "expected_reaction": "期待的反应",
"max_wait_seconds": 300 "max_wait_seconds": 0
}""" }"""
async def _get_planner_output_format(self) -> str: async def _get_planner_output_format(self) -> str:
@@ -866,7 +871,7 @@ class PromptBuilder:
"thought": "你的想法", "thought": "你的想法",
"actions": [{"type": "kfc_reply"}], "actions": [{"type": "kfc_reply"}],
"expected_reaction": "期待的反应", "expected_reaction": "期待的反应",
"max_wait_seconds": 300 "max_wait_seconds": 0
} }
注意：kfc_reply 动作不需要填写 content 字段，回复内容会单独生成。""" 注意：kfc_reply 动作不需要填写 content 字段，回复内容会单独生成。"""

82
src/plugins/built_in/kokoro_flow_chatter/prompt/prompts.py
View File

@@ -12,43 +12,42 @@ from src.chat.utils.prompt import Prompt
kfc_MAIN_PROMPT = Prompt( kfc_MAIN_PROMPT = Prompt(
name="kfc_main", name="kfc_main",
template="""# 你与 {user_name} 的私聊 template="""# 人设
## 人设
{persona_block} {persona_block}
## 安全互动准则 # 场景
{safety_guidelines_block} 你正在和 {user_name} 私下聊天。
## 你与 {user_name} 的关系 # 你与 {user_name} 的关系
{relation_block} {relation_block}
## 相关记忆 # 安全互动准则
{safety_guidelines_block}
# 相关信息
{memory_block} {memory_block}
## 工具信息 ## 工具信息
{tool_info} {tool_info}
## 你们之间最近的活动记录 # 你们之间最近的活动记录
以下是你和 {user_name} 最近的互动历史，按时间顺序记录了你们的对话和你的心理活动： 以下是你和 {user_name} 最近的互动历史，按时间顺序记录了你们的对话和你的心理活动：
{activity_stream} {activity_stream}
## 当前情况 # 聊天历史总览
{current_situation}
## 聊天历史总览
以下是你和 {user_name} 的聊天记录，帮助你更好地理解对话上下文： 以下是你和 {user_name} 的聊天记录，帮助你更好地理解对话上下文：
{chat_history_block} {chat_history_block}
## 你可以做的事情 # 当前情况
{current_situation}
# 你可以做的事情
{available_actions} {available_actions}
## 你的表达习惯 # 表达习惯
{expression_habits} {expression_habits}
## 你的回复格式 # 回复格式
{output_format} {output_format}
""", """,
) )
@@ -67,7 +66,7 @@ kfc_OUTPUT_FORMAT = Prompt(
{{"type": "动作名称", ...动作参数}} {{"type": "动作名称", ...动作参数}}
], ],
"expected_reaction": "你期待对方的反应是什么", "expected_reaction": "你期待对方的反应是什么",
"max_wait_seconds": 等待时间（秒），0 表示不等待 - `max_wait_seconds`：预估的等待时间（秒），请根据对话节奏来判断。通常你应该设置为0避免总是等待显得聒噪，但是当你觉得你需要等待对方回复时，可以设置一个合理的等待时间。
}} }}
``` ```
@@ -75,7 +74,7 @@ kfc_OUTPUT_FORMAT = Prompt(
- `thought`：你的内心独白，记录你此刻的想法和感受。要自然，不要技术性语言。 - `thought`：你的内心独白，记录你此刻的想法和感受。要自然，不要技术性语言。
- `actions`：你要执行的动作列表。每个动作是一个对象，必须包含 `type` 字段指定动作类型，其他字段根据动作类型不同而不同（参考上面每个动作的示例）。 - `actions`：你要执行的动作列表。每个动作是一个对象，必须包含 `type` 字段指定动作类型，其他字段根据动作类型不同而不同（参考上面每个动作的示例）。
- `expected_reaction`：你期待对方如何回应（用于判断是否需要等待） - `expected_reaction`：你期待对方如何回应（用于判断是否需要等待）
- `max_wait_seconds`：设定等待时间（秒），0 表示不等待，超时后你会考虑是否要主动说点什么。如果你认为聊天没有继续的必要，或不想打扰对方，可以设为 0。 - `max_wait_seconds`：预估的等待时间（秒），请根据对话节奏来判断。通常你应该设置为0避免总是等待显得聒噪，但是当你觉得你需要等待对方回复时，可以设置一个合理的等待时间。
### 注意事项 ### 注意事项
- 动作参数直接写在动作对象里，不需要 `action_data` 包装 - 动作参数直接写在动作对象里，不需要 `action_data` 包装
@@ -121,7 +120,7 @@ kfc_SITUATION_REPLY_LATE = Prompt(
你原本打算最多等 {max_wait_minutes:.1f} 分钟，但实际等了 {elapsed_minutes:.1f} 分钟才收到回复。 你原本打算最多等 {max_wait_minutes:.1f} 分钟，但实际等了 {elapsed_minutes:.1f} 分钟才收到回复。
虽然有点迟，但 {user_name} 终于回复了：「{latest_message}」 虽然有点迟，但 {user_name} 终于回复了：「{latest_message}」
请决定你接下来要怎么回应。（可以选择轻轻抱怨一下迟到，也可以装作没在意）""", 请决定你接下来要怎么回应。""",
) )
kfc_SITUATION_TIMEOUT = Prompt( kfc_SITUATION_TIMEOUT = Prompt(
@@ -179,7 +178,7 @@ kfc_SITUATION_PROACTIVE = Prompt(
# 用户消息条目 # 用户消息条目
kfc_ENTRY_USER_MESSAGE = Prompt( kfc_ENTRY_USER_MESSAGE = Prompt(
name="kfc_entry_user_message", name="kfc_entry_user_message",
template="""【{time}】{user_name} 说： template="""【{time}】{user_name} 发来消息：
"{content}" "{content}"
""", """,
) )
@@ -249,7 +248,7 @@ kfc_PLANNER_OUTPUT_FORMAT = Prompt(
{{"type": "动作名称", ...动作参数}} {{"type": "动作名称", ...动作参数}}
], ],
"expected_reaction": "你期待对方的反应是什么", "expected_reaction": "你期待对方的反应是什么",
"max_wait_seconds": "预估的等待时间（秒）" - `max_wait_seconds`：预估的等待时间（秒），请根据对话节奏来判断。通常你应该设置为0避免总是等待显得聒噪，但是当你觉得你需要等待对方回复时，可以设置一个合理的等待时间。
}} }}
``` ```
@@ -258,10 +257,7 @@ kfc_PLANNER_OUTPUT_FORMAT = Prompt(
- `actions`：你要执行的动作列表。每个动作是一个对象，必须包含 `type` 字段指定动作类型，其他字段根据动作类型不同而不同（参考上面每个动作的示例）。 - `actions`：你要执行的动作列表。每个动作是一个对象，必须包含 `type` 字段指定动作类型，其他字段根据动作类型不同而不同（参考上面每个动作的示例）。
- 对于 `kfc_reply` 动作，只需要指定 `{{"type": "kfc_reply"}}`，不需要填写 `content` 字段（回复内容会单独生成） - 对于 `kfc_reply` 动作，只需要指定 `{{"type": "kfc_reply"}}`，不需要填写 `content` 字段（回复内容会单独生成）
- `expected_reaction`：你期待对方如何回应（用于判断是否需要等待） - `expected_reaction`：你期待对方如何回应（用于判断是否需要等待）
- `max_wait_seconds`：预估的等待时间（秒），这很关键，请根据对话节奏来判断： - `max_wait_seconds`：预估的等待时间（秒），请根据对话节奏来判断。通常你应该设置为0避免总是等待，但是当你觉得你需要等待对方回复时，可以设置一个合理的等待时间。
- 如果你刚问了一个开放性问题（比如"你觉得呢？"、"后来怎么样了？"），或者对话明显还在兴头上，设置一个等待时间（比如 60-180 秒），给对方思考和打字的时间。
- 如果对话感觉自然结束了（比如晚安、拜拜），或者你给出了一个总结性的陈述，那就设置为 0，表示你觉得可以告一段落了。
- 不要总是设为 0，那会显得你很急着结束对话。
### 注意事项 ### 注意事项
- 动作参数直接写在动作对象里，不需要 `action_data` 包装 - 动作参数直接写在动作对象里，不需要 `action_data` 包装
@@ -275,41 +271,41 @@ kfc_PLANNER_OUTPUT_FORMAT = Prompt(
kfc_REPLYER_PROMPT = Prompt( kfc_REPLYER_PROMPT = Prompt(
name="kfc_replyer", name="kfc_replyer",
template="""# 你与 {user_name} 的私聊 template="""
## 人设 # 人设
{persona_block} {persona_block}
## 安全互动准则 # 安全互动准则
{safety_guidelines_block} {safety_guidelines_block}
## 你与 {user_name} 的关系 # 你与 {user_name} 的关系
{relation_block} {relation_block}
# 相关信息
## 相关记忆 ## 相关记忆
{memory_block} {memory_block}
## 工具信息 ## 工具信息
{tool_info} {tool_info}
## 你们之间发生的事（活动流） # 你们之间发生的事（活动流）
以下是你和 {user_name} 最近的互动历史，按时间顺序记录了你们的对话和你的心理活动： 以下是你和 {user_name} 最近的互动历史，按时间顺序记录了你们的对话和你的心理活动：
{activity_stream} {activity_stream}
## 当前情况 # 当前情况
{current_situation} {current_situation}
## 聊天历史总览 # 聊天历史总览
以下是你和 {user_name} 的聊天记录，帮助你更好地理解对话上下文： 以下是你和 {user_name} 的聊天记录，帮助你更好地理解对话上下文：
{chat_history_block} {chat_history_block}
## 你的表达习惯 # 表达习惯
{expression_habits} {expression_habits}
## 你的决策 ## 你的决策
你已经决定要回复 {user_name}。 你已经决定要回复 {user_name}的最新消息。
你需要生成一段紧密相关且与历史消息相关的回复。 你需要生成一段紧密相关且与历史消息相关的回复。
**你的想法**：{thought} **你的想法**：{thought}
@@ -321,7 +317,7 @@ kfc_REPLYER_PROMPT = Prompt(
- 请注意不要输出多余内容(包括前后缀，冒号和引号，at，[xx：xxx]系统格式化文字或 @等 )。只输出回复内容。 - 请注意不要输出多余内容(包括前后缀，冒号和引号，at，[xx：xxx]系统格式化文字或 @等 )。只输出回复内容。
- 在称呼用户时，请使用更自然的昵称或简称。对于长英文名，可使用首字母缩写；对于中文名，可提炼合适的简称。禁止直接复述复杂的用户名或输出用户名中的任何符号，让称呼更像人类习惯，注意，简称不是必须的，合理的使用。 - 在称呼用户时，请使用更自然的昵称或简称。对于长英文名，可使用首字母缩写；对于中文名，可提炼合适的简称。禁止直接复述复杂的用户名或输出用户名中的任何符号，让称呼更像人类习惯，注意，简称不是必须的，合理的使用。
你的回复应该是一条简短、完整且口语化的回复。 你的回复应该是一条简短、且口语化的回复。
现在，你说：""", 现在，你说：""",
) )
@@ -336,8 +332,7 @@ kfc_REPLYER_CONTEXT_IN_TIME = Prompt(
name="kfc_replyer_context_in_time", name="kfc_replyer_context_in_time",
template="""你等了 {elapsed_minutes:.1f} 分钟（原本打算最多等 {max_wait_minutes:.1f} 分钟），{user_name} 终于回复了： template="""你等了 {elapsed_minutes:.1f} 分钟（原本打算最多等 {max_wait_minutes:.1f} 分钟），{user_name} 终于回复了：
「{target_message}」 「{target_message}」
""",
你可以表现出一点"等到了回复"的欣喜或轻松。""",
) )
kfc_REPLYER_CONTEXT_LATE = Prompt( kfc_REPLYER_CONTEXT_LATE = Prompt(
@@ -345,7 +340,7 @@ kfc_REPLYER_CONTEXT_LATE = Prompt(
template="""你等了 {elapsed_minutes:.1f} 分钟（原本只打算等 {max_wait_minutes:.1f} 分钟），{user_name} 才回复： template="""你等了 {elapsed_minutes:.1f} 分钟（原本只打算等 {max_wait_minutes:.1f} 分钟），{user_name} 才回复：
「{target_message}」 「{target_message}」
虽然有点晚，但对方终于回复了。你可以选择轻轻抱怨一下，也可以装作没在意。""", 虽然有点晚，但对方终于回复了。""",
) )
kfc_REPLYER_CONTEXT_PROACTIVE = Prompt( kfc_REPLYER_CONTEXT_PROACTIVE = Prompt(
@@ -408,7 +403,7 @@ kfc_UNIFIED_OUTPUT_FORMAT = Prompt(
{{"type": "kfc_reply", "content": "你的回复内容"}} {{"type": "kfc_reply", "content": "你的回复内容"}}
], ],
"expected_reaction": "你期待对方的反应是什么", "expected_reaction": "你期待对方的反应是什么",
"max_wait_seconds": "预估的等待时间（秒）" - `max_wait_seconds`：预估的等待时间（秒），请根据对话节奏来判断。通常你应该设置为0避免总是等待显得聒噪，但是当你觉得你需要等待对方回复时，可以设置一个合理的等待时间。
}} }}
``` ```
@@ -416,10 +411,7 @@ kfc_UNIFIED_OUTPUT_FORMAT = Prompt(
- `thought`：你的内心独白，记录你此刻的想法和感受。要自然，不要技术性语言。 - `thought`：你的内心独白，记录你此刻的想法和感受。要自然，不要技术性语言。
- `actions`：你要执行的动作列表。对于 `kfc_reply` 动作，**必须**填写 `content` 字段，写上你要说的话。 - `actions`：你要执行的动作列表。对于 `kfc_reply` 动作，**必须**填写 `content` 字段，写上你要说的话。
- `expected_reaction`：你期待对方如何回应（用于判断是否需要等待） - `expected_reaction`：你期待对方如何回应（用于判断是否需要等待）
- `max_wait_seconds`：预估的等待时间（秒），这很关键，请根据对话节奏来判断： - `max_wait_seconds`：预估的等待时间（秒），请根据对话节奏来判断。通常你应该设置为0避免总是等待而显得聒噪，但是当你觉得你需要等待对方回复时，可以设置一个合理的等待时间。
- 如果你刚问了一个开放性问题（比如"你觉得呢？"、"后来怎么样了？"），或者对话明显还在兴头上，设置一个等待时间（比如 60-180 秒），给对方思考和打字的时间。
- 如果对话感觉自然结束了（比如晚安、拜拜），或者你给出了一个总结性的陈述，那就设置为 0，表示你觉得可以告一段落了。
- 不要总是设为 0，那会显得你很急着结束对话。
### 注意事项 ### 注意事项
- kfc_reply 的 content 字段是**必填**的，直接写你要发送的消息内容 - kfc_reply 的 content 字段是**必填**的，直接写你要发送的消息内容

2
src/plugins/built_in/social_toolkit_plugin/plugin.py
View File

@@ -195,7 +195,7 @@ class PokeAction(BaseAction):
for i in range(times): for i in range(times):
logger.info(f"正在向 {display_name} ({user_id}) 发送第 {i + 1}/{times} 次戳一戳...") logger.info(f"正在向 {display_name} ({user_id}) 发送第 {i + 1}/{times} 次戳一戳...")
await self.send_command( await self.send_command(
"SEND_POKE", args=poke_args "SEND_POKE", args=poke_args, storage_message=False
) )
# 添加一个延迟，避免因发送过快导致后续戳一戳失败 # 添加一个延迟，避免因发送过快导致后续戳一戳失败
await asyncio.sleep(1.5) await asyncio.sleep(1.5)

2
src/plugins/built_in/tts_plugin/plugin.py
View File

@@ -149,7 +149,7 @@ class TTSPlugin(BasePlugin):
"plugin": { "plugin": {
"name": ConfigField(type=str, default="tts_plugin", description="插件名称", required=True), "name": ConfigField(type=str, default="tts_plugin", description="插件名称", required=True),
"version": ConfigField(type=str, default="0.1.0", description="插件版本号"), "version": ConfigField(type=str, default="0.1.0", description="插件版本号"),
"enabled": ConfigField(type=bool, default=True, description="是否启用插件"), "enabled": ConfigField(type=bool, default=False, description="是否启用插件"),
"description": ConfigField(type=str, default="文字转语音插件", description="插件描述", required=True), "description": ConfigField(type=str, default="文字转语音插件", description="插件描述", required=True),
}, },
"components": {"enable_tts": ConfigField(type=bool, default=True, description="是否启用TTS Action")}, "components": {"enable_tts": ConfigField(type=bool, default=True, description="是否启用TTS Action")},

661
src/plugins/built_in/tts_voice_plugin/LICENSE
View File

@@ -1,661 +0,0 @@
GNU AFFERO GENERAL PUBLIC LICENSE
Version 3, 19 November 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
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How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
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To do so, attach the following notices to the program. It is safest
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state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
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You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If your software can interact with users remotely through a computer
network, you should also make sure that it provides a way for users to
get its source. For example, if your program is a web application, its
interface could display a "Source" link that leads users to an archive
of the code. There are many ways you could offer source, and different
solutions will be better for different programs; see section 13 for the
specific requirements.
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU AGPL, see
<https://www.gnu.org/licenses/>.

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src/plugins/built_in/tts_voice_plugin/README.md
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# GPT-SoVITS 语音合成插件（多风格版）
## 简介
本插件基于 GPT-SoVITS，实现文本转语音（TTS）功能，支持多种语音风格和多语言（中文/英文/日文）。适用于需要将文本内容以语音形式发送的场景，如语音回复、朗读长文本、增强表达效果等。
(此版本适用于麦麦09x版)
## 功能特性
- 支持多种语音风格（如默认、温柔等，可自定义扩展）
- 支持多语言自动检测与指定（zh/en/ja）
- 可配置参考音频、参考文本、模型权重等参数
- 兼容多种聊天平台（如 QQ、Telegram 等）
- 关键词激活，灵活触发
## 安装与配置
1. **拷贝插件文件夹**到你的插件目录下（如 `plugins/tts_voice_plugin/`）。
2. **配置 `config.toml`**，参考下方配置示例：
```toml
[plugin]
enabled = true
config_version = "1.0.0"
[tts]
timeout = 30
max_text_length = 500
server = "http://127.0.0.1:9880"
[tts_styles.default]
refer_wav = ""
prompt_text = ""
prompt_language = "zh"
gpt_weights = ""
sovits_weights = ""
[tts_styles.gentle]
refer_wav = ""
prompt_text = ""
prompt_language = "zh"
gpt_weights = ""
sovits_weights = ""
```
- `server`：TTS 服务后端地址（需部署 GPT-SoVITS 服务）
- `tts_styles`：可自定义多种风格，每种风格可配置不同参考音频、文本、模型权重等
## 使用方法
- 在聊天中输入关键词（如“语音”、“说话”、“朗读”、“voice”、“tts”等）即可触发语音合成功能
- 可通过参数指定风格、语言、参考音频等
- 支持自动检测文本语言
## 主要参数说明
| 参数名 | 说明 |
|------------------|----------------------------|
| text | 要转换为语音的文本内容 |
| text_language | 文本语言（zh/en/ja） |
| refer_wav_path | 参考音频路径（可选） |
| prompt_text | 参考音频文本（可选） |
| prompt_language | 参考音频语言（可选） |
| voice_style | 语音风格（如 default/gentle）|
## 扩展风格
如需添加新风格，在 `config.toml` 的 `[tts_styles]` 下增加分组即可。例如：
```toml
[tts_styles."活泼"]
refer_wav = "path/to/lively.wav"
prompt_text = "活泼的语气"
prompt_language = "zh"
gpt_weights = ""
sovits_weights = ""
```
## 依赖
- Python 3.7+
- aiohttp
- GPT-SoVITS 服务端
## 作者
- 插件作者：靓仔
- 插件版本：1.0.0
## License
AGPL-3.0

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src/plugins/built_in/tts_voice_plugin/__init__.py
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from src.plugin_system.base.plugin_metadata import PluginMetadata
__plugin_meta__ = PluginMetadata(
name="GPT-SoVITS 语音合成插件",
description="基于 GPT-SoVITS 的文本转语音插件，支持多种语言和多风格语音合成。",
usage=" ",
version="2.0.0",
author="靓仔",
license="AGPL-v3.0",
repository_url="https://github.com/xuqian13/tts_voice_plugin",
keywords=["tts", "语音合成", "文本转语音", "gpt-sovits", "语音", "朗读", "多风格", "语音播报"],
categories=["Utility", "Communication", "Accessibility"],
extra={
"is_built_in": False,
"plugin_type": "tools",
},
python_dependencies = ["aiohttp", "soundfile", "pedalboard"]
)

269
src/plugins/built_in/tts_voice_plugin/actions/tts_action.py
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"""
TTS 语音合成 Action
"""
from pathlib import Path
from typing import ClassVar
import toml
from src.chat.utils.self_voice_cache import register_self_voice
from src.common.logger import get_logger
from src.plugin_system.base.base_action import BaseAction, ChatMode
from ..services.manager import get_service
logger = get_logger("tts_voice_plugin.action")
class TTSVoiceAction(BaseAction):
"""
通过关键词或规划器自动触发 TTS 语音合成
"""
action_name = "tts_voice_action"
action_description = "将你生成好的文本转换为语音并发送。注意：这是纯语音合成，只能说话，不能唱歌！"
mode_enable = ChatMode.ALL
parallel_action = False
action_parameters: ClassVar[dict] = {
"tts_voice_text": {
"type": "string",
"description": "需要转换为语音并发送的完整、自然、适合口语的文本内容。注意：只能是说话内容，不能是歌词或唱歌！",
"required": True
},
"voice_style": {
"type": "string",
"description": "语音的风格。请根据对话的情感和上下文选择一个最合适的风格。如果未提供，将使用默认风格。",
"required": False
},
"text_language": {
"type": "string",
"description": (
"指定用于合成的语言模式，请务必根据文本内容选择最精确、范围最小的选项以获得最佳效果。"
"可用选项说明：\n"
"- 'zh': 中文与英文混合 (最优选)\n"
"- 'ja': 日文与英文混合 (最优选)\n"
"- 'yue': 粤语与英文混合 (最优选)\n"
"- 'ko': 韩文与英文混合 (最优选)\n"
"- 'en': 纯英文\n"
"- 'all_zh': 纯中文\n"
"- 'all_ja': 纯日文\n"
"- 'all_yue': 纯粤语\n"
"- 'all_ko': 纯韩文\n"
"- 'auto': 多语种混合自动识别 (备用选项，当前两种语言时优先使用上面的精确选项)\n"
"- 'auto_yue': 多语种混合自动识别（包含粤语）(备用选项)"
),
"required": False
}
}
action_require: ClassVar[list] = [
"【核心限制】此动作只能用于说话，绝对不能用于唱歌！TTS无法发出有音调的歌声，只会输出平淡的念白。如果用户要求唱歌，不要使用此动作！",
"在调用此动作时，你必须在 'tts_voice_text' 参数中提供要合成语音的完整回复内容。这是强制性的。",
"当用户明确请求使用语音进行回复时，例如'发个语音听听'、'用语音说'等。",
"当对话内容适合用语音表达，例如讲故事、念诗、撒嬌或进行角色扮演时。",
"在表达特殊情感（如安慰、鼓励、庆祝）的场景下，可以主动使用语音来增强感染力。",
"不要在日常的、简短的问答或闲聊中频繁使用语音，避免打扰用户。",
"提供的 'tts_voice_text' 内容必须是纯粹的对话，不能包含任何括号或方括号括起来的动作、表情、或场景描述（例如，不要出现 '(笑)' 或 '[歪头]'）",
"**重要**：此动作专为语音合成设计，因此 'tts_voice_text' 参数的内容必须是纯净、标准的口语文本。请务必抑制你通常的、富有表现力的文本风格，不要使用任何辅助聊天或增强视觉效果的特殊符号（例如 '♪', '～', '∽', '☆' 等），因为它们无法被正确合成为语音。",
"【**最终规则**】'tts_voice_text' 参数中，所有句子和停顿【必须】使用且只能使用以下四个标准标点符号：'，' (逗号)、'。' (句号)、'？' (问号)、'！' (叹号)。任何其他符号，特别是 '...'、'～' 以及任何表情符号或装饰性符号，都【严禁】出现，否则将导致语音合成严重失败。"
]
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# 关键配置项现在由 TTSService 管理
self.tts_service = get_service("tts")
# 动态更新 voice_style 参数描述（包含可用风格）
self._update_voice_style_parameter()
def _update_voice_style_parameter(self):
"""动态更新 voice_style 参数描述，包含实际可用的风格选项"""
try:
available_styles = self._get_available_styles_safe()
if available_styles:
styles_list = "、".join(available_styles)
updated_description = (
f"语音的风格。请根据对话的情感和上下文选择一个最合适的风格。"
f"当前可用风格：{styles_list}。如果未提供，将使用默认风格。"
)
# 更新实例的参数描述
self.action_parameters["voice_style"]["description"] = updated_description
logger.debug(f"{self.log_prefix} 已更新语音风格参数描述，包含 {len(available_styles)} 个可用风格")
else:
logger.warning(f"{self.log_prefix} 无法获取可用语音风格，使用默认参数描述")
except Exception as e:
logger.error(f"{self.log_prefix} 更新语音风格参数时出错: {e}")
def _get_available_styles_safe(self) -> list[str]:
"""安全地获取可用语音风格列表"""
try:
# 首先尝试从TTS服务获取
if hasattr(self.tts_service, "get_available_styles"):
styles = self.tts_service.get_available_styles()
if styles:
return styles
# 回退到直接读取配置文件
plugin_file = Path(__file__).resolve()
bot_root = plugin_file.parent.parent.parent.parent.parent.parent
config_file = bot_root / "config" / "plugins" / "tts_voice_plugin" / "config.toml"
if config_file.exists():
with open(config_file, encoding="utf-8") as f:
config = toml.load(f)
styles_config = config.get("tts_styles", [])
if isinstance(styles_config, list):
style_names = []
for style in styles_config:
if isinstance(style, dict):
name = style.get("style_name")
if isinstance(name, str) and name:
style_names.append(name)
return style_names if style_names else ["default"]
except Exception as e:
logger.debug(f"{self.log_prefix} 获取可用语音风格时出错: {e}")
return ["default"] # 安全回退
@classmethod
def get_action_info(cls) -> "ActionInfo":
"""重写获取Action信息的方法，动态更新参数描述"""
# 先调用父类方法获取基础信息
info = super().get_action_info()
# 尝试动态更新 voice_style 参数描述
try:
# 尝试获取可用风格（不创建完整实例）
available_styles = cls._get_available_styles_for_info()
if available_styles:
styles_list = "、".join(available_styles)
updated_description = (
f"语音的风格。请根据对话的情感和上下文选择一个最合适的风格。"
f"当前可用风格：{styles_list}。如果未提供，将使用默认风格。"
)
# 更新参数描述
info.action_parameters["voice_style"]["description"] = updated_description
except Exception as e:
logger.debug(f"[TTSVoiceAction] 在获取Action信息时更新参数描述失败: {e}")
return info
@classmethod
def _get_available_styles_for_info(cls) -> list[str]:
"""为 get_action_info 方法获取可用风格（类方法版本）"""
try:
# 构建配置文件路径
plugin_file = Path(__file__).resolve()
bot_root = plugin_file.parent.parent.parent.parent.parent.parent
config_file = bot_root / "config" / "plugins" / "tts_voice_plugin" / "config.toml"
if config_file.exists():
with open(config_file, encoding="utf-8") as f:
config = toml.load(f)
styles_config = config.get("tts_styles", [])
if isinstance(styles_config, list):
style_names = []
for style in styles_config:
if isinstance(style, dict):
name = style.get("style_name")
if isinstance(name, str) and name:
style_names.append(name)
return style_names if style_names else ["default"]
except Exception:
pass
return ["default"] # 安全回退
async def go_activate(self, llm_judge_model=None) -> bool:
"""
判断此 Action 是否应该被激活。
满足以下任一条件即可激活：
1. 55% 的随机概率
2. 匹配到预设的关键词
3. LLM 判断当前场景适合发送语音
"""
# 条件1: 随机激活
if await self._random_activation(0.25):
logger.info(f"{self.log_prefix} 随机激活成功 (25%)")
return True
# 条件2: 关键词激活
keywords = [
"发语音", "语音", "说句话", "用语音说", "听你", "听声音", "想你", "想听声音",
"讲个话", "说段话", "念一下", "读一下", "用嘴说", "说", "能发语音吗", "亲口"
]
if await self._keyword_match(keywords):
logger.info(f"{self.log_prefix} 关键词激活成功")
return True
# 条件3: LLM 判断激活
# 注意：这里我们复用 action_require 里的描述，让 LLM 的判断更精准
if await self._llm_judge_activation(
llm_judge_model=llm_judge_model
):
logger.info(f"{self.log_prefix} LLM 判断激活成功")
return True
logger.debug(f"{self.log_prefix} 所有激活条件均未满足，不激活")
return False
async def execute(self) -> tuple[bool, str]:
"""
执行 Action 的核心逻辑
"""
try:
if not self.tts_service:
logger.error(f"{self.log_prefix} TTSService 未注册或初始化失败，静默处理。")
return False, "TTSService 未注册或初始化失败"
initial_text = self.action_data.get("tts_voice_text", "").strip()
voice_style = self.action_data.get("voice_style", "default")
# 新增：从决策模型获取指定的语言模式
text_language = self.action_data.get("text_language") # 如果模型没给，就是 None
logger.info(f"{self.log_prefix} 接收到规划器初步文本: '{initial_text[:70]}...', 指定风格: {voice_style}, 指定语言: {text_language}")
# 1. 使用规划器提供的文本
text = initial_text
if not text:
logger.warning(f"{self.log_prefix} 规划器提供的文本为空，静默处理。")
return False, "规划器提供的文本为空"
# 2. 调用 TTSService 生成语音
logger.info(f"{self.log_prefix} 使用最终文本进行语音合成: '{text[:70]}...'")
audio_b64 = await self.tts_service.generate_voice(
text=text,
style_hint=voice_style,
language_hint=text_language # 新增：将决策模型指定的语言传递给服务
)
if audio_b64:
# 在发送语音前，将文本注册到缓存中
register_self_voice(audio_b64, text)
await self.send_custom(message_type="voice", content=audio_b64)
logger.info(f"{self.log_prefix} GPT-SoVITS语音发送成功")
await self.store_action_info(
action_prompt_display=f"将文本转换为语音并发送 (风格:{voice_style})",
action_done=True
)
return True, f"成功生成并发送语音，文本长度: {len(text)}字符"
else:
logger.error(f"{self.log_prefix} TTS服务未能返回音频数据，静默处理。")
await self.store_action_info(
action_prompt_display="语音合成失败: TTS服务未能返回音频数据",
action_done=False
)
return False, "语音合成失败"
except Exception as e:
logger.error(f"{self.log_prefix} 语音合成过程中发生未知错误: {e!s}")
await self.store_action_info(
action_prompt_display=f"语音合成失败: {e!s}",
action_done=False
)
return False, f"语音合成出错: {e!s}"

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src/plugins/built_in/tts_voice_plugin/commands/tts_command.py
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"""
TTS 语音合成命令
"""
from typing import ClassVar
from src.common.logger import get_logger
from src.plugin_system.base.command_args import CommandArgs
from src.plugin_system.base.plus_command import PlusCommand
from src.plugin_system.utils.permission_decorators import require_permission
from ..services.manager import get_service
logger = get_logger("tts_voice_plugin.command")
class TTSVoiceCommand(PlusCommand):
"""
通过命令手动触发 TTS 语音合成
"""
command_name: str = "tts"
command_description: str = "使用GPT-SoVITS将文本转换为语音并发送"
command_aliases: ClassVar[list[str]] = ["语音合成", "说"]
command_usage = "/tts <要说的文本> [风格]"
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
@require_permission("plugin.tts_voice_plugin.command.use")
async def execute(self, args: CommandArgs) -> tuple[bool, str, bool]:
"""
执行命令的核心逻辑
"""
all_args = args.get_args()
if not all_args:
await self.send_text("请提供要转换为语音的文本内容哦！")
return False, "缺少文本参数", True
try:
tts_service = get_service("tts")
if not tts_service:
raise RuntimeError("TTSService 未注册或初始化失败")
# 获取可用风格列表
available_styles = tts_service.tts_styles.keys()
text_to_speak = ""
style_hint = "default"
# 检查最后一个参数是否是有效的风格
if len(all_args) > 1 and all_args[-1] in available_styles:
style_hint = all_args[-1]
text_to_speak = " ".join(all_args[:-1])
else:
# 如果最后一个参数不是风格，则全部都是文本
text_to_speak = " ".join(all_args)
# 保持默认风格，让 service 层决定是否需要情感分析
style_hint = "default"
if not text_to_speak:
await self.send_text("请提供要转换为语音的文本内容哦！")
return False, "文本内容为空", True
audio_b64 = await tts_service.generate_voice(text_to_speak, style_hint)
if audio_b64:
await self.send_type(message_type="voice", content=audio_b64)
return True, "语音发送成功", True
else:
await self.send_text("❌ 语音合成失败，请检查服务状态或配置。")
return False, "语音合成失败", True
except Exception as e:
logger.error(f"执行 /tts 命令时出错: {e}")
await self.send_text("❌ 语音合成时发生了意想不到的错误，请查看日志。")
return False, "命令执行异常", True

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src/plugins/built_in/tts_voice_plugin/plugin.py
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"""
TTS Voice 插件 - 重构版
"""
from pathlib import Path
from typing import Any, ClassVar
import toml
from src.common.logger import get_logger
from src.plugin_system import BasePlugin, ComponentInfo, register_plugin
from src.plugin_system.base.component_types import PermissionNodeField
from .actions.tts_action import TTSVoiceAction
from .commands.tts_command import TTSVoiceCommand
from .services.manager import register_service
from .services.tts_service import TTSService
logger = get_logger("tts_voice_plugin")
@register_plugin
class TTSVoicePlugin(BasePlugin):
"""
GPT-SoVITS 语音合成插件 - 重构版
"""
plugin_name = "tts_voice_plugin"
plugin_description = "基于GPT-SoVITS的文本转语音插件（重构版）"
plugin_version = "3.1.2"
plugin_author = "Kilo Code & 靚仔"
# enable_plugin 应该由配置文件控制，不在此处硬编码
config_file_name = "config.toml"
dependencies: ClassVar[list[str]] = []
permission_nodes: ClassVar[list[PermissionNodeField]] = [
PermissionNodeField(node_name="command.use", description="是否可以使用 /tts 命令"),
]
config_schema: ClassVar[dict] = {}
config_section_descriptions: ClassVar[dict] = {
"plugin": "插件基本配置",
"components": "组件启用控制",
"tts": "TTS语音合成基础配置",
"tts_advanced": "TTS高级参数配置（语速、采样、批处理等）",
"tts_styles": "TTS风格参数配置（每个分组为一种风格）"
}
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.tts_service = None
def _create_default_config(self, config_file: Path):
"""
如果配置文件不存在，则创建一个默认的配置文件。
"""
if config_file.is_file():
return
logger.info(f"TTS 配置文件不存在，正在创建默认配置文件于: {config_file}")
default_config_content = """# 插件基础配置
[plugin]
enable = false
keywords = [
"发语音", "语音", "说句话", "用语音说", "听你", "听声音", "想听你", "想听声音",
"讲个话", "说段话", "念一下", "读一下", "用嘴说", "说", "能发语音吗","亲口"
]
# 组件启用控制
[components]
action_enabled = true
command_enabled = true
# TTS 语音合成基础配置
[tts]
server = "http://127.0.0.1:9880"
timeout = 180
max_text_length = 1000
# TTS 风格参数配置
# 每个 [[tts_styles]] 代表一个独立的语音风格配置
[[tts_styles]]
# 风格的唯一标识符，必须有一个名为 "default"
style_name = "default"
# 显示名称
name = "默认"
# 参考音频路径
refer_wav_path = "C:/path/to/your/reference.wav"
# 参考音频文本
prompt_text = "这是一个示例文本，请替换为您自己的参考音频文本。"
# 参考音频语言
prompt_language = "zh"
# GPT 模型路径
gpt_weights = "C:/path/to/your/gpt_weights.ckpt"
# SoVITS 模型路径
sovits_weights = "C:/path/to/your/sovits_weights.pth"
# 语速
speed_factor = 1.0
# TTS 高级参数配置
[tts_advanced]
media_type = "wav"
top_k = 9
top_p = 0.8
temperature = 0.8
batch_size = 6
batch_threshold = 0.75
text_split_method = "cut5"
repetition_penalty = 1.4
sample_steps = 150
super_sampling = true
# 空间音效配置
[spatial_effects]
# 是否启用空间音效处理
enabled = false
# 是否启用标准混响效果
reverb_enabled = false
# 混响的房间大小 (建议范围 0.0-1.0)
room_size = 0.2
# 混响的阻尼/高频衰减 (建议范围 0.0-1.0)
damping = 0.6
# 混响的湿声（效果声）比例 (建议范围 0.0-1.0)
wet_level = 0.3
# 混响的干声（原声）比例 (建议范围 0.0-1.0)
dry_level = 0.8
# 混响的立体声宽度 (建议范围 0.0-1.0)
width = 1.0
# 是否启用卷积混响（需要assets/small_room_ir.wav文件）
convolution_enabled = false
# 卷积混响的干湿比 (建议范围 0.0-1.0)
convolution_mix = 0.7
"""
try:
config_file.parent.mkdir(parents=True, exist_ok=True)
with open(config_file, "w", encoding="utf-8") as f:
f.write(default_config_content.strip())
logger.info("默认 TTS 配置文件创建成功。")
except Exception as e:
logger.error(f"创建默认 TTS 配置文件失败: {e}")
def _get_config_wrapper(self, key: str, default: Any = None) -> Any:
"""
配置获取的包装器，用于解决 get_config 无法直接获取动态表（如 tts_styles）和未在 schema 中定义的节的问题。
由于插件系统的 schema 为空时不会加载未定义的键，这里手动读取配置文件以获取所需配置。
"""
# 需要手动加载的顶级配置节
manual_load_keys = ["tts_styles", "spatial_effects", "tts_advanced", "tts"]
top_key = key.split(".")[0]
if top_key in manual_load_keys:
try:
plugin_file = Path(__file__).resolve()
bot_root = plugin_file.parent.parent.parent.parent.parent
config_file = bot_root / "config" / "plugins" / self.plugin_name / self.config_file_name
if not config_file.is_file():
logger.error(f"TTS config file not found at robustly constructed path: {config_file}")
return default
full_config = toml.loads(config_file.read_text(encoding="utf-8"))
# 支持点状路径访问
value = full_config
for k in key.split("."):
if isinstance(value, dict):
value = value.get(k)
else:
return default
return value if value is not None else default
except Exception as e:
logger.error(f"Failed to manually load '{key}' from config: {e}")
return default
return self.get_config(key, default)
async def on_plugin_loaded(self):
"""
插件加载完成后的回调，初始化并注册服务。
"""
logger.info("初始化 TTSVoicePlugin...")
plugin_file = Path(__file__).resolve()
bot_root = plugin_file.parent.parent.parent.parent.parent
config_file = bot_root / "config" / "plugins" / self.plugin_name / self.config_file_name
self._create_default_config(config_file)
# 实例化 TTSService，并传入 get_config 方法
self.tts_service = TTSService(self._get_config_wrapper)
# 注册服务
register_service("tts", self.tts_service)
logger.info("TTSService 已成功初始化并注册。")
def get_plugin_components(self) -> list[tuple[ComponentInfo, type]]:
"""
返回插件包含的组件列表。
"""
components = []
if self.get_config("components.action_enabled", True):
components.append((TTSVoiceAction.get_action_info(), TTSVoiceAction))
if self.get_config("components.command_enabled", True):
components.append((TTSVoiceCommand.get_plus_command_info(), TTSVoiceCommand))
return components

19
src/plugins/built_in/tts_voice_plugin/services/manager.py
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@@ -1,19 +0,0 @@
"""
服务管理器
用于注册和获取插件内部使用的服务实例。
"""
from typing import Any
_services: dict[str, Any] = {}
def register_service(name: str, instance: Any) -> None:
"""注册一个服务实例"""
_services[name] = instance
def get_service(name: str) -> Any:
"""获取一个已注册的服务实例"""
return _services.get(name)

344
src/plugins/built_in/tts_voice_plugin/services/tts_service.py
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@@ -1,344 +0,0 @@
"""
TTS 核心服务
"""
import asyncio
import base64
import io
import os
import re
from collections.abc import Callable
from typing import Any
import aiohttp
import soundfile as sf
from pedalboard import Convolution, Pedalboard, Reverb
from pedalboard.io import AudioFile
from src.common.logger import get_logger
logger = get_logger("tts_voice_plugin.service")
class TTSService:
"""封装了TTS合成的核心逻辑"""
def __init__(self, get_config_func: Callable[[str, Any], Any]):
self.get_config = get_config_func
self.tts_styles: dict[str, Any] = {}
self.timeout: int = 60
self.max_text_length: int = 500
self._load_config()
def _load_config(self) -> None:
"""加载插件配置"""
try:
self.timeout = self.get_config("tts.timeout", 60)
self.max_text_length = self.get_config("tts.max_text_length", 500)
self.tts_styles = self._load_tts_styles()
if self.tts_styles:
logger.info(f"TTS服务已成功加载风格: {list(self.tts_styles.keys())}")
else:
logger.warning("TTS风格配置为空，请检查配置文件")
except Exception as e:
logger.error(f"TTS服务配置加载失败: {e}")
def _load_tts_styles(self) -> dict[str, dict[str, Any]]:
"""加载 TTS 风格配置"""
styles = {}
global_server = self.get_config("tts.server", "http://127.0.0.1:9880")
tts_styles_config = self.get_config("tts_styles", [])
if not isinstance(tts_styles_config, list):
logger.error(f"tts_styles 配置不是一个列表, 而是 {type(tts_styles_config)}")
return styles
default_cfg = next((s for s in tts_styles_config if s.get("style_name") == "default"), None)
if not default_cfg:
logger.error("在 tts_styles 配置中未找到 'default' 风格，这是必需的。")
return styles
default_refer_wav = default_cfg.get("refer_wav_path", "")
default_prompt_text = default_cfg.get("prompt_text", "")
default_gpt_weights = default_cfg.get("gpt_weights", "")
default_sovits_weights = default_cfg.get("sovits_weights", "")
if not default_refer_wav:
logger.warning("TTS 'default' style is missing 'refer_wav_path'.")
for style_cfg in tts_styles_config:
if not isinstance(style_cfg, dict):
continue
style_name = style_cfg.get("style_name")
if not style_name:
continue
styles[style_name] = {
"url": global_server,
"name": style_cfg.get("name", style_name),
"refer_wav_path": style_cfg.get("refer_wav_path", default_refer_wav),
"prompt_text": style_cfg.get("prompt_text", default_prompt_text),
"prompt_language": style_cfg.get("prompt_language", "zh"),
"gpt_weights": style_cfg.get("gpt_weights", default_gpt_weights),
"sovits_weights": style_cfg.get("sovits_weights", default_sovits_weights),
"speed_factor": style_cfg.get("speed_factor"),
"text_language": style_cfg.get("text_language", "auto"), # 新增：读取文本语言模式
}
return styles
def _determine_final_language(self, text: str, mode: str) -> str:
"""根据配置的语言策略和文本内容，决定最终发送给API的语言代码"""
# 如果策略是具体的语言（如 all_zh, ja），直接使用
if mode not in ["auto", "auto_yue"]:
return mode
# 对于 auto 和 auto_yue 策略，进行内容检测
# 优先检测粤语
if mode == "auto_yue":
cantonese_keywords = ["嘅", "喺", "咗", "唔", "係", "啲", "咩", "乜", "喂"]
if any(keyword in text for keyword in cantonese_keywords):
logger.info("在 auto_yue 模式下检测到粤语关键词，最终语言: yue")
return "yue"
# 检测日语（简单启发式规则）
japanese_chars = len(re.findall(r"[\u3040-\u309f\u30a0-\u30ff]", text))
if japanese_chars > 5 and japanese_chars > len(re.findall(r"[\u4e00-\u9fff]", text)) * 0.5:
logger.info("检测到日语字符，最终语言: ja")
return "ja"
# 默认回退到中文
logger.info(f"在 {mode} 模式下未检测到特定语言，默认回退到: zh")
return "zh"
def _clean_text_for_tts(self, text: str) -> str:
# 1. 基本清理
text = re.sub(r"[\(（\[【].*?[\)）\]】]", "", text)
text = re.sub(r"([，。！？、；：,.!?;:~\-`])\1+", r"\1", text)
text = re.sub(r"~{2,}|～{2,}", "，", text)
text = re.sub(r"\.{3,}|…{1,}", "。", text)
# 2. 词语替换
replacements = {"www": "哈哈哈", "hhh": "哈哈", "233": "哈哈", "666": "厉害", "88": "拜拜"}
for old, new in replacements.items():
text = text.replace(old, new)
# 3. 移除不必要的字符 (恢复使用更安全的原版正则，避免误删)
text = re.sub(r"[^\u4e00-\u9fff\u3040-\u309f\u30a0-\u30ffa-zA-Z0-9\s，。！？、；：,.!?;:~～]", "", text)
# 4. 确保结尾有标点
if text and not text.endswith(tuple("，。！？、；：,.!?;:")):
text += "。"
# 5. 智能截断 (保留改进的截断逻辑)
if len(text) > self.max_text_length:
cut_text = text[:self.max_text_length]
punctuation = "。！？.…"
last_punc_pos = max(cut_text.rfind(p) for p in punctuation)
if last_punc_pos != -1:
text = cut_text[:last_punc_pos + 1]
else:
last_comma_pos = max(cut_text.rfind(p) for p in "，、；,;")
if last_comma_pos != -1:
text = cut_text[:last_comma_pos + 1]
else:
text = cut_text
return text.strip()
async def _call_tts_api(self, server_config: dict, text: str, text_language: str, **kwargs) -> bytes | None:
"""
最终修复版：先切换模型，然后仅通过路径发送合成请求。
"""
ref_wav_path = kwargs.get("refer_wav_path")
if not ref_wav_path:
logger.error(f"API 调用失败：缺少 refer_wav_path。当前风格配置: {server_config}")
return None
try:
base_url = server_config["url"].rstrip("/")
# --- 步骤一：像稳定版一样，先切换模型 ---
async def switch_model_weights(weights_path: str | None, weight_type: str):
if not weights_path:
return
api_endpoint = f"/set_{weight_type}_weights"
switch_url = f"{base_url}{api_endpoint}"
try:
async with aiohttp.ClientSession(timeout=aiohttp.ClientTimeout(total=self.timeout)) as session:
async with session.get(switch_url, params={"weights_path": weights_path}) as resp:
if resp.status != 200:
error_text = await resp.text()
logger.error(f"切换 {weight_type} 模型失败: {resp.status} - {error_text}")
else:
logger.info(f"成功切换 {weight_type} 模型为: {weights_path}")
except Exception as e:
logger.error(f"请求切换 {weight_type} 模型时发生网络异常: {e}")
await switch_model_weights(kwargs.get("gpt_weights"), "gpt")
await switch_model_weights(kwargs.get("sovits_weights"), "sovits")
# --- 步骤二：构建纯净的、不含Base64的请求数据 ---
data = {
"text": text,
"text_lang": text_language,
"ref_audio_path": ref_wav_path,
"prompt_text": kwargs.get("prompt_text", ""),
"prompt_lang": kwargs.get("prompt_language", "zh"),
# 在稳定版中，这两个参数是通过API切换的，而不是直接放在请求体里
# "gpt_model_path": kwargs.get("gpt_weights"),
# "sovits_model_path": kwargs.get("sovits_weights"),
}
# 合并高级配置
advanced_config = self.get_config("tts_advanced", {})
if isinstance(advanced_config, dict):
data.update({k: v for k, v in advanced_config.items() if v is not None})
# 优先使用风格特定的语速
if server_config.get("speed_factor") is not None:
data["speed_factor"] = server_config["speed_factor"]
# --- 步骤三：发送最终的合成请求 ---
tts_url = base_url if base_url.endswith("/tts") else f"{base_url}/tts"
logger.info(f"发送到 TTS API 的数据: {data}")
async with aiohttp.ClientSession() as session:
async with session.post(tts_url, json=data, timeout=aiohttp.ClientTimeout(total=self.timeout)) as response:
if response.status == 200:
return await response.read()
else:
error_info = await response.text()
logger.error(f"TTS API调用失败: {response.status} - {error_info}")
return None
except asyncio.TimeoutError:
logger.error("TTS服务请求超时")
return None
except Exception as e:
logger.error(f"TTS API调用异常: {e}")
return None
async def _apply_spatial_audio_effect(self, audio_data: bytes) -> bytes | None:
"""根据配置应用空间效果（混响和卷积）"""
try:
effects_config = self.get_config("spatial_effects", {})
if not effects_config.get("enabled", False):
return audio_data
# 获取插件目录和IR文件路径
# 基于 __file__ 构建稳健的、独立于当前工作目录的路径
plugin_file = os.path.abspath(__file__)
# services -> tts_voice_plugin -> plugins -> Bot
bot_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(plugin_file))))
ir_path = os.path.join(bot_root, "assets", "small_room_ir.wav")
effects = []
# 根据配置添加Reverb效果
if effects_config.get("reverb_enabled", False):
effects.append(Reverb(
room_size=effects_config.get("room_size", 0.15),
damping=effects_config.get("damping", 0.5),
wet_level=effects_config.get("wet_level", 0.33),
dry_level=effects_config.get("dry_level", 0.4),
width=effects_config.get("width", 1.0)
))
# 根据配置添加Convolution效果
if effects_config.get("convolution_enabled", False) and os.path.exists(ir_path):
effects.append(Convolution(
impulse_response_filename=ir_path,
mix=effects_config.get("convolution_mix", 0.5)
))
elif effects_config.get("convolution_enabled"):
logger.warning(f"卷积混响已启用，但IR文件不存在 ({ir_path})，跳过该效果。")
if not effects:
return audio_data
# 将原始音频数据加载到内存中的 AudioFile 对象
with io.BytesIO(audio_data) as audio_stream:
with AudioFile(audio_stream, "r") as f:
board = Pedalboard(effects)
effected = board(f.read(f.frames), f.samplerate)
# 将处理后的音频数据写回内存中的字节流
with io.BytesIO() as output_stream:
# 使用 soundfile 写入，因为它更稳定
sf.write(output_stream, effected.T, f.samplerate, format="WAV")
processed_audio_data = output_stream.getvalue()
logger.info("成功应用空间效果。")
return processed_audio_data
except Exception as e:
logger.error(f"应用空间效果时出错: {e}")
return audio_data # 如果出错，返回原始音频
async def generate_voice(self, text: str, style_hint: str = "default", language_hint: str | None = None) -> str | None:
self._load_config()
if not self.tts_styles:
logger.error("TTS风格配置为空，无法生成语音。")
return None
style = style_hint if style_hint in self.tts_styles else "default"
if style not in self.tts_styles:
if "default" in self.tts_styles:
style = "default"
logger.warning(f"指定风格 '{style_hint}' 不存在，自动回退到: 'default'")
elif self.tts_styles:
style = next(iter(self.tts_styles))
logger.warning(f"指定风格 '{style_hint}' 和 'default' 均不存在，自动回退到第一个可用风格: {style}")
else:
logger.error("没有任何可用的TTS风格配置")
return None
server_config = self.tts_styles[style]
clean_text = self._clean_text_for_tts(text)
if not clean_text:
return None
# 语言决策流程：
# 1. 优先使用决策模型直接指定的 language_hint (最高优先级)
if language_hint:
final_language = language_hint
logger.info(f"使用决策模型指定的语言: {final_language}")
else:
# 2. 如果模型未指定，则使用风格配置的 language_policy
language_policy = server_config.get("text_language", "auto")
final_language = self._determine_final_language(clean_text, language_policy)
logger.info(f"决策模型未指定语言，使用策略 '{language_policy}' -> 最终语言: {final_language}")
logger.info(f"开始TTS语音合成，文本：{clean_text[:50]}..., 风格：{style}, 最终语言: {final_language}")
audio_data = await self._call_tts_api(
server_config=server_config, text=clean_text, text_language=final_language,
refer_wav_path=server_config.get("refer_wav_path"),
prompt_text=server_config.get("prompt_text"),
prompt_language=server_config.get("prompt_language"),
gpt_weights=server_config.get("gpt_weights"),
sovits_weights=server_config.get("sovits_weights"),
)
if audio_data:
# 检查是否启用空间音频效果
spatial_config = self.get_config("spatial_effects", {})
if spatial_config.get("enabled", False):
logger.info("检测到已启用空间音频效果，开始处理...")
processed_audio = await self._apply_spatial_audio_effect(audio_data)
if processed_audio:
logger.info("空间音频效果应用成功！")
audio_data = processed_audio
else:
logger.warning("空间音频效果应用失败，将使用原始音频。")
return base64.b64encode(audio_data).decode("utf-8")
return None