add asr and tts with settings

src/blackbox/asrsensevoice.py

@@ -0,0 +1,103 @@
+from io import BytesIO
+from typing import Any, Coroutine
+
+from fastapi import Request, Response, status
+from fastapi.responses import JSONResponse
+
+from funasr import AutoModel
+from funasr.utils.postprocess_utils import rich_transcription_postprocess
+from .blackbox import Blackbox
+from injector import singleton, inject
+
+import tempfile
+
+import os
+from ..configuration import SenseVoiceConf
+
+from ..log.logging_time import logging_time
+import logging
+logger = logging.getLogger(__name__)
+
+@singleton
+class ASR(Blackbox):
+    mode: str
+    url: str
+    speed: int
+    device: str
+    language: str
+    speaker: str
+
+    @logging_time(logger=logger)
+    def model_init(self, sensevoice_config: SenseVoiceConf) -> None:
+
+        model_dir = "/home/gpu/Workspace/Models/SenseVoice/SenseVoiceSmall"
+
+        self.speed = sensevoice_config.speed
+        self.device = sensevoice_config.device
+        self.language = sensevoice_config.language
+        self.speaker = sensevoice_config.speaker
+        self.device = sensevoice_config.device
+        self.url = ''
+        self.mode = sensevoice_config.mode
+        self.asr = None
+        self.speaker_ids = None
+        os.environ['CUDA_VISIBLE_DEVICES'] = str(sensevoice_config.device)
+        if self.mode == 'local':
+            self.asr = AutoModel(
+            model=model_dir,
+            trust_remote_code=True,
+            remote_code= "/home/gpu/Workspace/SenseVoice/model.py",
+            vad_model="fsmn-vad",
+            vad_kwargs={"max_single_segment_time": 30000},
+            device="cuda:0",
+        )   
+            
+        else:
+            self.url = sensevoice_config.url
+        logging.info('#### Initializing SenseVoiceASR Service in cuda:' + str(sensevoice_config.device) + ' mode...')
+
+    @inject
+    def __init__(self, sensevoice_config: SenseVoiceConf) -> None:
+        self.model_init(sensevoice_config)
+ 
+    def __call__(self, *args, **kwargs):
+        return self.processing(*args, **kwargs)
+    
+    async def processing(self,  *args, **kwargs):
+        data = args[0]
+        # 创建一个临时文件
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_audio_file:
+            temp_audio_file.write(data)
+            temp_audio_path = temp_audio_file.name
+        res = self.asr.generate(
+            input=temp_audio_path,
+            cache={},
+            language="auto",  # "zh", "en", "yue", "ja", "ko", "nospeech"
+            use_itn=True,
+            batch_size_s=60,
+            merge_vad=True,  #
+            merge_length_s=15,
+        )        
+        # results = self.paraformer([BytesIO(data)])
+        results = rich_transcription_postprocess(res[0]["text"])
+        os.remove(temp_audio_path)
+        if len(results) == 0:
+            return None
+        return results
+
+    def valid(self, data: any) -> bool:
+        if isinstance(data, bytes):
+            return True
+        return False
+    
+    async def fast_api_handler(self, request: Request) -> Response:
+        data = (await request.form()).get("audio")
+        if data is None:
+            # self.logger.warn("asr bag request","type", "fast_api_handler", "api", "asr")
+            return JSONResponse(content={"error": "data is required"}, status_code=status.HTTP_400_BAD_REQUEST)
+        d = await data.read()
+        try:
+            txt = await self.processing(d)
+        except ValueError as e:
+            return JSONResponse(content={"error": str(e)}, status_code=status.HTTP_400_BAD_REQUEST)
+        return JSONResponse(content={"text": txt}, status_code=status.HTTP_200_OK)