47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
from fastapi import FastAPI, UploadFile, File, Form, HTTPException, Header
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from pydantic import BaseModel
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from faster_whisper import WhisperModel
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import os
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app = FastAPI()
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# 支持的模型
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SUPPORTED_MODELS = {
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"FunAudioLLM/SenseVoiceSmall": "small",
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"FunAudioLLM/SenseVoiceMedium": "medium",
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"FunAudioLLM/SenseVoiceLarge": "large"
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}
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# 模型缓存（常驻内存）
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MODEL_CACHE = {}
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def get_model(model_name: str):
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if model_name not in SUPPORTED_MODELS:
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raise HTTPException(status_code=400, detail="Unsupported model")
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if model_name not in MODEL_CACHE:
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MODEL_CACHE[model_name] = WhisperModel(SUPPORTED_MODELS[model_name], compute_type="int8")
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return MODEL_CACHE[model_name]
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@app.post("/audio/transcriptions")
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async def transcribe_audio(
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file: UploadFile = File(...),
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model: str = Form(...),
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authorization: str = Header(None)
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):
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if not authorization or not authorization.startswith("Bearer "):
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raise HTTPException(status_code=401, detail="Unauthorized")
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# 保存音频临时文件
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audio_path = "temp_audio." + file.filename.split(".")[-1]
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with open(audio_path, "wb") as f:
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f.write(await file.read())
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# 模型推理
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model_runner = get_model(model)
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segments, _ = model_runner.transcribe(audio_path)
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text = " ".join([seg.text for seg in segments])
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os.remove(audio_path)
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return {"text": text}
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