mirror of
https://github.com/BoardWare-Genius/jarvis-models.git
synced 2025-12-13 16:53:24 +00:00
103 lines
3.5 KiB
Python
103 lines
3.5 KiB
Python
from io import BytesIO
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from typing import Any, Coroutine
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from fastapi import Request, Response, status
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from fastapi.responses import JSONResponse
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from funasr import AutoModel
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from funasr.utils.postprocess_utils import rich_transcription_postprocess
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from .blackbox import Blackbox
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from injector import singleton, inject
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import tempfile
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import os
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from ..configuration import SenseVoiceConf
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from ..log.logging_time import logging_time
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import logging
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logger = logging.getLogger(__name__)
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@singleton
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class ASR(Blackbox):
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mode: str
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url: str
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speed: int
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device: str
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language: str
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speaker: str
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@logging_time(logger=logger)
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def model_init(self, sensevoice_config: SenseVoiceConf) -> None:
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model_dir = "/home/gpu/Workspace/Models/SenseVoice/SenseVoiceSmall"
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self.speed = sensevoice_config.speed
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self.device = sensevoice_config.device
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self.language = sensevoice_config.language
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self.speaker = sensevoice_config.speaker
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self.device = sensevoice_config.device
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self.url = ''
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self.mode = sensevoice_config.mode
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self.asr = None
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self.speaker_ids = None
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os.environ['CUDA_VISIBLE_DEVICES'] = str(sensevoice_config.device)
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if self.mode == 'local':
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self.asr = AutoModel(
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model=model_dir,
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trust_remote_code=True,
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remote_code= "/home/gpu/Workspace/SenseVoice/model.py",
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vad_model="fsmn-vad",
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vad_kwargs={"max_single_segment_time": 30000},
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device="cuda:0",
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)
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else:
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self.url = sensevoice_config.url
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logging.info('#### Initializing SenseVoiceASR Service in cuda:' + str(sensevoice_config.device) + ' mode...')
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@inject
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def __init__(self, sensevoice_config: SenseVoiceConf) -> None:
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self.model_init(sensevoice_config)
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def __call__(self, *args, **kwargs):
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return self.processing(*args, **kwargs)
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async def processing(self, *args, **kwargs):
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data = args[0]
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# 创建一个临时文件
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with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as temp_audio_file:
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temp_audio_file.write(data)
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temp_audio_path = temp_audio_file.name
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res = self.asr.generate(
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input=temp_audio_path,
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cache={},
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language="auto", # "zh", "en", "yue", "ja", "ko", "nospeech"
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use_itn=True,
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batch_size_s=60,
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merge_vad=True, #
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merge_length_s=15,
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)
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# results = self.paraformer([BytesIO(data)])
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results = rich_transcription_postprocess(res[0]["text"])
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os.remove(temp_audio_path)
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if len(results) == 0:
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return None
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return results
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def valid(self, data: any) -> bool:
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if isinstance(data, bytes):
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return True
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return False
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async def fast_api_handler(self, request: Request) -> Response:
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data = (await request.form()).get("audio")
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if data is None:
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# self.logger.warn("asr bag request","type", "fast_api_handler", "api", "asr")
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return JSONResponse(content={"error": "data is required"}, status_code=status.HTTP_400_BAD_REQUEST)
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d = await data.read()
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try:
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txt = await self.processing(d)
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except ValueError as e:
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return JSONResponse(content={"error": str(e)}, status_code=status.HTTP_400_BAD_REQUEST)
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return JSONResponse(content={"text": txt}, status_code=status.HTTP_200_OK) |