mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-29 13:03:56 +08:00
update: 更改to_tts保存临时文件判断
This commit is contained in:
Sakura-RanChen
@@ -8,7 +8,7 @@ from datetime import datetime
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from core.utils import textUtils
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from abc import ABC, abstractmethod
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from config.logger import setup_logging
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from core.utils.util import audio_to_data
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from core.utils.util import audio_to_data, audio_bytes_to_data
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from core.utils.tts import MarkdownCleaner
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from core.utils.output_counter import add_device_output
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from core.handle.reportHandle import enqueue_tts_report
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@@ -20,7 +20,6 @@ from core.providers.tts.dto.dto import (
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InterfaceType,
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)
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import traceback
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TAG = __name__
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@@ -33,6 +32,7 @@ class TTSProviderBase(ABC):
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self.conn = None
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self.tts_timeout = 10
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self.delete_audio_file = delete_audio_file
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self.audio_file_type = "wav"
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self.output_file = config.get("output_dir", "tmp/")
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self.tts_text_queue = queue.Queue()
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self.tts_audio_queue = queue.Queue()
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@@ -76,35 +76,60 @@ class TTSProviderBase(ABC):
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)
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def to_tts(self, text):
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tmp_file = self.generate_filename()
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try:
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max_repeat_time = 5
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text = MarkdownCleaner.clean_markdown(text)
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while not os.path.exists(tmp_file) and max_repeat_time > 0:
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text = MarkdownCleaner.clean_markdown(text)
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max_repeat_time = 5
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if self.delete_audio_file:
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# 需要删除文件的直接转为音频数据
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while max_repeat_time > 0:
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try:
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asyncio.run(self.text_to_speak(text, tmp_file))
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audio_bytes = asyncio.run(self.text_to_speak(text, None))
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if audio_bytes:
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audio_datas, _ = audio_bytes_to_data(audio_bytes, file_type=self.audio_file_type, is_opus=True)
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return audio_datas
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else:
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max_repeat_time -= 1
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except Exception as e:
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logger.bind(tag=TAG).warning(
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f"语音生成失败{5 - max_repeat_time + 1}次: {text}，错误: {e}"
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)
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# 未执行成功，删除文件
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if os.path.exists(tmp_file):
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os.remove(tmp_file)
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max_repeat_time -= 1
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if max_repeat_time > 0:
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logger.bind(tag=TAG).info(
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f"语音生成成功: {text}:{tmp_file}，重试{5 - max_repeat_time}次"
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f"语音生成成功: {text}，重试{5 - max_repeat_time}次"
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)
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else:
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logger.bind(tag=TAG).error(
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f"语音生成失败: {text}，请检查网络或服务是否正常"
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)
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return tmp_file
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except Exception as e:
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logger.bind(tag=TAG).error(f"Failed to generate TTS file: {e}")
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return None
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else:
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tmp_file = self.generate_filename()
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try:
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while not os.path.exists(tmp_file) and max_repeat_time > 0:
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try:
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asyncio.run(self.text_to_speak(text, tmp_file))
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except Exception as e:
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logger.bind(tag=TAG).warning(
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f"语音生成失败{5 - max_repeat_time + 1}次: {text}，错误: {e}"
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)
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# 未执行成功，删除文件
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if os.path.exists(tmp_file):
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os.remove(tmp_file)
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max_repeat_time -= 1
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if max_repeat_time > 0:
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logger.bind(tag=TAG).info(
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f"语音生成成功: {text}:{tmp_file}，重试{5 - max_repeat_time}次"
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)
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else:
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logger.bind(tag=TAG).error(
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f"语音生成失败: {text}，请检查网络或服务是否正常"
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)
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return tmp_file
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except Exception as e:
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logger.bind(tag=TAG).error(f"Failed to generate TTS file: {e}")
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return None
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@abstractmethod
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async def text_to_speak(self, text, output_file):
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@@ -192,12 +217,19 @@ class TTSProviderBase(ABC):
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self.tts_text_buff.append(message.content_detail)
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segment_text = self._get_segment_text()
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if segment_text:
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tts_file = self.to_tts(segment_text)
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if tts_file:
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audio_datas = self._process_audio_file(tts_file)
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self.tts_audio_queue.put(
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(message.sentence_type, audio_datas, segment_text)
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)
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if self.delete_audio_file:
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audio_datas = self.to_tts(segment_text)
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if audio_datas:
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self.tts_audio_queue.put(
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(message.sentence_type, audio_datas, segment_text)
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)
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else:
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tts_file = self.to_tts(segment_text)
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if tts_file:
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audio_datas = self._process_audio_file(tts_file)
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self.tts_audio_queue.put(
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(message.sentence_type, audio_datas, segment_text)
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)
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elif ContentType.FILE == message.content_type:
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self._process_remaining_text()
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tts_file = message.content_file
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@@ -334,11 +366,18 @@ class TTSProviderBase(ABC):
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if remaining_text:
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segment_text = textUtils.get_string_no_punctuation_or_emoji(remaining_text)
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if segment_text:
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tts_file = self.to_tts(segment_text)
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audio_datas = self._process_audio_file(tts_file)
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self.tts_audio_queue.put(
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(SentenceType.MIDDLE, audio_datas, segment_text)
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)
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if self.delete_audio_file:
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audio_datas = self.to_tts(segment_text)
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if audio_datas:
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self.tts_audio_queue.put(
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(SentenceType.MIDDLE, audio_datas, segment_text)
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)
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else:
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tts_file = self.to_tts(segment_text)
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audio_datas = self._process_audio_file(tts_file)
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self.tts_audio_queue.put(
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(SentenceType.MIDDLE, audio_datas, segment_text)
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)
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self.processed_chars += len(full_text)
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return True
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return False
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