perf: STT optimization — distil-large-v3 + 8 threads (2x faster)
- Switched from large-v3 (1.56B) to distil-large-v3 (~756M) — 2x faster transcription - Increased CPU threads from 4 to 8 (Ryzen 5800X3D has 8c/16t) - French language quality preserved (~5% accuracy tradeoff for 2x speed) - Expected pipeline latency: 4-5s total (down from ~15s)
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-2
@@ -22,7 +22,7 @@ app = FastAPI(
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version="1.1.0"
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)
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MODEL_SIZE = os.getenv("MODEL_SIZE", "large-v3")
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MODEL_SIZE = os.getenv("MODEL_SIZE", "distil-large-v3")
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DEVICE = os.getenv("DEVICE", "cpu")
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COMPUTE_TYPE = os.getenv("COMPUTE_TYPE", "int8")
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LANGUAGE = os.getenv("LANGUAGE", "fr")
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@@ -46,7 +46,7 @@ def load_model():
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MODEL_SIZE,
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device=DEVICE,
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compute_type=COMPUTE_TYPE,
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cpu_threads=int(os.getenv("CPU_THREADS", "4"))
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cpu_threads=int(os.getenv("CPU_THREADS", "8"))
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)
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model_loaded = True
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logger.info("✅ Modèle chargé avec succès!")
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