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@@ -17,6 +17,7 @@ def env_bool(name: str, default: bool = False) -> bool:
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LOG_LEVEL = os.getenv("WHISPER_LOG_LEVEL", "INFO").upper()
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VAD_ENABLED = env_bool("WHISPER_VAD", True)
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MODEL_SIZE = str(os.getenv("MODEL_SIZE", "small").lower())
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+COMPUTE_TYPE = os.getenv("WHISPER_COMPUTE_TYPE", "float32").strip().lower()
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MIN_AUDIO_SEC = float(os.getenv("MIN_AUDIO_SEC", "2.0"))
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MAX_AUDIO_SEC = float(os.getenv("MAX_AUDIO_SEC", "10.0"))
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@@ -32,13 +33,14 @@ logger.setLevel(getattr(logging, LOG_LEVEL, logging.INFO))
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logger.info(f"Log level = {LOG_LEVEL}")
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logger.info(f"VAD enabled = {VAD_ENABLED}")
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+logger.info("Model = %s, compute type = %s", MODEL_SIZE, COMPUTE_TYPE)
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app = FastAPI()
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# =========================
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# Whisper model (shared)
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# =========================
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-model = WhisperModel(MODEL_SIZE, device="cuda", compute_type="float32")
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+model = WhisperModel(MODEL_SIZE, device="cuda", compute_type=COMPUTE_TYPE)
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# Vérifier les kernels CUDA avant de déclarer le service prêt.
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list(model.transcribe(np.zeros(16000, dtype=np.float32), language="fr", beam_size=1)[0])
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model_lock = Lock()
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@@ -54,7 +56,7 @@ def transcribe_audio(audio):
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@app.get("/healthz")
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def healthz():
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- return {"status": "ready", "model": MODEL_SIZE}
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+ return {"status": "ready", "model": MODEL_SIZE, "compute_type": COMPUTE_TYPE}
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# =========================
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# REST API (Swagger / tests)
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