LLM和TTS采用适配器模式进行解耦，方便扩展更多服务平台调用

core/providers/tts/base.py

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+import asyncio
+import logging
+import os
+import json
+import uuid
+import base64
+# from datetime import datetime
+# import edge_tts
+import numpy as np
+import opuslib
+# import requests
+# from core.utils.util import read_config, get_project_dir
+from pydub import AudioSegment
+from abc import ABC, abstractmethod
+
+logger = logging.getLogger(__name__)
+
+class TTSProviderBase(ABC):
+    def __init__(self, config, delete_audio_file):
+        self.delete_audio_file = delete_audio_file
+        self.output_file = config.get("output_file")
+
+    @abstractmethod
+    def generate_filename(self):
+        pass
+
+    def to_tts(self, text):
+        tmp_file = self.generate_filename()
+        try:
+            max_repeat_time = 5
+            while not os.path.exists(tmp_file) and max_repeat_time > 0:
+                asyncio.run(self.text_to_speak(text, tmp_file))
+                if not os.path.exists(tmp_file):
+                    max_repeat_time = max_repeat_time - 1
+                    logger.error(f"语音生成失败: {text}:{tmp_file}，再试{max_repeat_time}次")
+
+            if max_repeat_time>0:
+                logger.info(f"语音生成成功: {text}:{tmp_file}，重试{5-max_repeat_time}次")
+
+            return tmp_file
+        except Exception as e:
+            logger.info(f"Failed to generate TTS file: {e}")
+            return None
+
+    @abstractmethod
+    async def text_to_speak(self, text, output_file):
+        pass
+
+    def wav_to_opus_data(self, wav_file_path):
+        # 使用pydub加载PCM文件
+        # 获取文件后缀名
+        file_type = os.path.splitext(wav_file_path)[1]
+        if file_type:
+            file_type = file_type.lstrip('.')
+        audio = AudioSegment.from_file(wav_file_path, format=file_type)
+
+        duration = len(audio) / 1000.0
+
+        # 转换为单声道和16kHz采样率（确保与编码器匹配）
+        audio = audio.set_channels(1).set_frame_rate(16000)
+
+        # 获取原始PCM数据（16位小端）
+        raw_data = audio.raw_data
+
+        # 初始化Opus编码器
+        encoder = opuslib.Encoder(16000, 1, opuslib.APPLICATION_AUDIO)
+
+        # 编码参数
+        frame_duration = 60  # 60ms per frame
+        frame_size = int(16000 * frame_duration / 1000)  # 960 samples/frame
+
+        opus_datas = []
+        # 按帧处理所有音频数据（包括最后一帧可能补零）
+        for i in range(0, len(raw_data), frame_size * 2):  # 16bit=2bytes/sample
+            # 获取当前帧的二进制数据
+            chunk = raw_data[i:i + frame_size * 2]
+
+            # 如果最后一帧不足，补零
+            if len(chunk) < frame_size * 2:
+                chunk += b'\x00' * (frame_size * 2 - len(chunk))
+
+            # 转换为numpy数组处理
+            np_frame = np.frombuffer(chunk, dtype=np.int16)
+
+            # 编码Opus数据
+            opus_data = encoder.encode(np_frame.tobytes(), frame_size)
+            opus_datas.append(opus_data)
+
+        return opus_datas, duration

core/providers/tts/doubao.py

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+import os
+import uuid
+import json
+import base64
+import requests
+from datetime import datetime
+from core.providers.tts.base import TTSProviderBase
+
+class TTSProvider(TTSProviderBase):
+    def __init__(self, config, delete_audio_file):
+        super().__init__(config, delete_audio_file)
+        self.appid = config.get("appid")
+        self.access_token = config.get("access_token")
+        self.cluster = config.get("cluster")
+        self.voice = config.get("voice")
+
+        self.host = "openspeech.bytedance.com"
+        self.api_url = f"https://{self.host}/api/v1/tts"
+        self.header = {"Authorization": f"Bearer;{self.access_token}"}
+
+    def generate_filename(self, extension=".wav"):
+        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
+
+    async def text_to_speak(self, text, output_file):
+        request_json = {
+            "app": {
+                "appid": self.appid,
+                "token": "access_token",
+                "cluster": self.cluster
+            },
+            "user": {
+                "uid": "1"
+            },
+            "audio": {
+                "voice_type": self.voice,
+                "encoding": "wav",
+                "speed_ratio": 1.0,
+                "volume_ratio": 1.0,
+                "pitch_ratio": 1.0,
+            },
+            "request": {
+                "reqid": str(uuid.uuid4()),
+                "text": text,
+                "text_type": "plain",
+                "operation": "query",
+                "with_frontend": 1,
+                "frontend_type": "unitTson"
+            }
+        }
+
+        resp = requests.post(self.api_url, json.dumps(request_json), headers=self.header)
+        if "data" in resp.json():
+            data = resp.json()["data"]
+            file_to_save = open(output_file, "wb")
+            file_to_save.write(base64.b64decode(data))

core/providers/tts/edge.py

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+import os
+import uuid
+import edge_tts
+from datetime import datetime
+from core.providers.tts.base import TTSProviderBase
+
+class TTSProvider(TTSProviderBase):
+    def __init__(self, config, delete_audio_file):
+        super().__init__(config, delete_audio_file)
+        self.voice = config.get("voice")
+
+    def generate_filename(self, extension=".mp3"):
+        return os.path.join(self.output_file, f"tts-{datetime.now().date()}@{uuid.uuid4().hex}{extension}")
+
+    async def text_to_speak(self, text, output_file):
+        communicate = edge_tts.Communicate(text, voice=self.voice)  # Use your preferred voice
+        await communicate.save(output_file)