mirror of
https://github.com/modelscope/FunASR
synced 2025-09-15 14:48:36 +08:00
132 lines
4.7 KiB
Python
132 lines
4.7 KiB
Python
import argparse
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import logging
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import os
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import uuid
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import aiofiles
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import uvicorn
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from fastapi import FastAPI, File, UploadFile
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from modelscope.utils.logger import get_logger
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from funasr import AutoModel
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logger = get_logger(log_level=logging.INFO)
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logger.setLevel(logging.INFO)
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parser = argparse.ArgumentParser()
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parser.add_argument("--host",
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type=str,
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default="0.0.0.0",
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required=False,
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help="host ip, localhost, 0.0.0.0")
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parser.add_argument("--port",
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type=int,
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default=8000,
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required=False,
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help="server port")
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parser.add_argument("--asr_model",
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type=str,
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default="paraformer-zh",
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help="asr model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo")
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parser.add_argument("--asr_model_revision",
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type=str,
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default="v2.0.4",
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help="")
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parser.add_argument("--vad_model",
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type=str,
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default="fsmn-vad",
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help="vad model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo")
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parser.add_argument("--vad_model_revision",
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type=str,
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default="v2.0.4",
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help="")
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parser.add_argument("--punc_model",
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type=str,
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default="ct-punc-c",
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help="model from https://github.com/alibaba-damo-academy/FunASR?tab=readme-ov-file#model-zoo")
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parser.add_argument("--punc_model_revision",
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type=str,
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default="v2.0.4",
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help="")
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parser.add_argument("--ngpu",
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type=int,
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default=1,
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help="0 for cpu, 1 for gpu")
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parser.add_argument("--device",
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type=str,
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default="cuda",
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help="cuda, cpu")
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parser.add_argument("--ncpu",
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type=int,
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default=4,
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help="cpu cores")
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parser.add_argument("--hotword_path",
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type=str,
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default='hotwords.txt',
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help="hot word txt path, only the hot word model works")
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parser.add_argument("--certfile",
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type=str,
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default=None,
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required=False,
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help="certfile for ssl")
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parser.add_argument("--keyfile",
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type=str,
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default=None,
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required=False,
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help="keyfile for ssl")
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parser.add_argument("--temp_dir",
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type=str,
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default="temp_dir/",
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required=False,
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help="temp dir")
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args = parser.parse_args()
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logger.info("----------- Configuration Arguments -----------")
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for arg, value in vars(args).items():
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logger.info("%s: %s" % (arg, value))
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logger.info("------------------------------------------------")
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os.makedirs(args.temp_dir, exist_ok=True)
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logger.info("model loading")
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# load funasr model
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model = AutoModel(model=args.asr_model,
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model_revision=args.asr_model_revision,
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vad_model=args.vad_model,
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vad_model_revision=args.vad_model_revision,
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punc_model=args.punc_model,
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punc_model_revision=args.punc_model_revision,
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ngpu=args.ngpu,
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ncpu=args.ncpu,
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device=args.device,
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disable_pbar=True,
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disable_log=True)
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logger.info("loaded models!")
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app = FastAPI(title="FunASR")
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param_dict = {}
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if args.hotword_path is not None and os.path.exists(args.hotword_path):
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with open(args.hotword_path, 'r', encoding='utf-8') as f:
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lines = f.readlines()
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lines = [line.strip() for line in lines]
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hotword = ' '.join(lines)
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logger.info(f'热词：{hotword}')
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param_dict['hotword'] = hotword
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@app.post("/recognition")
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async def api_recognition(audio: UploadFile = File(..., description="audio file")):
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suffix = audio.filename.split('.')[-1]
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audio_path = f'{args.temp_dir}/{str(uuid.uuid1())}.{suffix}'
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async with aiofiles.open(audio_path, 'wb') as out_file:
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content = await audio.read()
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await out_file.write(content)
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rec_result = model.generate(input=audio_path, batch_size_s=300, **param_dict)
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ret = {"result": rec_result[0]['text'], "code": 0}
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logger.info(f'识别结果：{ret}')
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return ret
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if __name__ == '__main__':
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uvicorn.run(app, host=args.host, port=args.port, ssl_keyfile=args.keyfile, ssl_certfile=args.certfile)
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