b4d8e1a19b
* add AudioQnA comps * readme * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * revert to main br * draft tests Signed-off-by: Spycsh <sihan.chen@intel.com> * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * fix * rm old yml * fix name * fix * remove * longer warmup time * Modify the corresponding format according to the backend new structure. Signed-off-by: Yue, Wenjiao <wenjiao.yue@intel.com> * Update .env * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci --------- Signed-off-by: Spycsh <sihan.chen@intel.com> Signed-off-by: Yue, Wenjiao <wenjiao.yue@intel.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: WenjiaoYue <wenjiao.yue@intel.com> Co-authored-by: chen, suyue <suyue.chen@intel.com>
70 lines
2.0 KiB
Python
70 lines
2.0 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# Copyright (C) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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#
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import argparse
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import os
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import uvicorn
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from asr import AudioSpeechRecognition
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from fastapi import FastAPI, File, UploadFile
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from fastapi.responses import Response
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from pydub import AudioSegment
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from starlette.middleware.cors import CORSMiddleware
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app = FastAPI()
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asr = None
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app.add_middleware(
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CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"]
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)
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@app.get("/v1/health")
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async def health() -> Response:
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"""Health check."""
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return Response(status_code=200)
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@app.post("/v1/audio/transcriptions")
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async def audio_to_text(file: UploadFile = File(...)):
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file_name = file.filename
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print(f"Received file: {file_name}")
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with open("tmp_audio_bytes", "wb") as fout:
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content = await file.read()
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fout.write(content)
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audio = AudioSegment.from_file("tmp_audio_bytes")
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audio = audio.set_frame_rate(16000)
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# bytes to wav
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file_name = file_name + ".wav"
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audio.export(f"{file_name}", format="wav")
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try:
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asr_result = asr.audio2text(file_name)
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except Exception as e:
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print(e)
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asr_result = e
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finally:
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os.remove(file_name)
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os.remove("tmp_audio_bytes")
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return {"asr_result": asr_result}
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--host", type=str, default="0.0.0.0")
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parser.add_argument("--port", type=int, default=8008)
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parser.add_argument("--model_name_or_path", type=str, default="openai/whisper-tiny")
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parser.add_argument("--bf16", default=False, action="store_true")
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parser.add_argument("--language", type=str, default="english")
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parser.add_argument("--device", type=str, default="cpu")
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args = parser.parse_args()
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asr = AudioSpeechRecognition(
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model_name_or_path=args.model_name_or_path, bf16=args.bf16, language=args.language, device=args.device
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)
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uvicorn.run(app, host=args.host, port=args.port)
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