mirror of https://github.com/Mai-with-u/MaiBot.git
85 lines
3.2 KiB
Python
85 lines
3.2 KiB
Python
from src.common.logger_manager import get_logger
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from src.chat.focus_chat.planners.actions.base_action import ActionActivationType
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from src.chat.focus_chat.planners.actions.plugin_action import PluginAction, register_action
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from typing import Tuple
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logger = get_logger("tts_action")
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@register_action
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class TTSAction(PluginAction):
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"""TTS语音转换动作处理类"""
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action_name = "tts_action"
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action_description = "将文本转换为语音进行播放，适用于需要语音输出的场景"
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action_parameters = {
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"text": "需要转换为语音的文本内容，必填，内容应当适合语音播报，语句流畅、清晰",
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}
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action_require = [
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"当需要发送语音信息时使用",
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"当用户明确要求使用语音功能时使用",
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"当表达内容更适合用语音而不是文字传达时使用",
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"当用户想听到语音回答而非阅读文本时使用",
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]
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enable_plugin = True # 启用插件
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associated_types = ["tts_text"]
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focus_activation_type = ActionActivationType.LLM_JUDGE
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normal_activation_type = ActionActivationType.KEYWORD
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# 关键词配置 - Normal模式下使用关键词触发
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activation_keywords = ["语音", "tts", "播报", "读出来", "语音播放", "听", "朗读"]
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keyword_case_sensitive = False
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# 并行执行设置 - TTS可以与回复并行执行，不覆盖回复内容
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parallel_action = False
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async def process(self) -> Tuple[bool, str]:
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"""处理TTS文本转语音动作"""
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logger.info(f"{self.log_prefix} 执行TTS动作: {self.reasoning}")
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# 获取要转换的文本
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text = self.action_data.get("text")
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if not text:
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logger.error(f"{self.log_prefix} 执行TTS动作时未提供文本内容")
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return False, "执行TTS动作失败：未提供文本内容"
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# 确保文本适合TTS使用
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processed_text = self._process_text_for_tts(text)
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try:
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# 发送TTS消息
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await self.send_message(type="tts_text", data=processed_text)
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logger.info(f"{self.log_prefix} TTS动作执行成功，文本长度: {len(processed_text)}")
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return True, "TTS动作执行成功"
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except Exception as e:
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logger.error(f"{self.log_prefix} 执行TTS动作时出错: {e}")
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return False, f"执行TTS动作时出错: {e}"
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def _process_text_for_tts(self, text: str) -> str:
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"""
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处理文本使其更适合TTS使用
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- 移除不必要的特殊字符和表情符号
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- 修正标点符号以提高语音质量
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- 优化文本结构使语音更流畅
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"""
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# 这里可以添加文本处理逻辑
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# 例如：移除多余的标点、表情符号，优化语句结构等
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# 简单示例实现
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processed_text = text
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# 移除多余的标点符号
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import re
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processed_text = re.sub(r"([!?,.;:。！？，、；：])\1+", r"\1", processed_text)
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# 确保句子结尾有合适的标点
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if not any(processed_text.endswith(end) for end in [".", "?", "!", "。", "！", "？"]):
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processed_text = processed_text + "。"
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return processed_text
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