56 lines
1.5 KiB
Python
56 lines
1.5 KiB
Python
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"""Whisper transcription service — CPU-only, async-ready."""
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import io
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import tempfile
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import time
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from pathlib import Path
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_model = None
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_model_name = None
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def _load_model(name: str = "base"):
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"""Lazy-load Whisper model (downloads on first use)."""
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global _model, _model_name
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import whisper
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if _model is None or _model_name != name:
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_model = whisper.load_model(name)
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_model_name = name
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return _model
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def transcribe_bytes(audio_bytes: bytes, model_name: str = "base") -> dict:
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"""Transcribe audio from bytes. Returns {"text": "...", "segments": [...], "language": "..."}"""
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t0 = time.time()
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model = _load_model(model_name)
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# Write to temp file (whisper needs a file path or numpy array)
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suffix = ".wav"
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with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
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tmp.write(audio_bytes)
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tmp_path = tmp.name
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try:
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result = model.transcribe(tmp_path, fp16=False) # fp16=False for CPU
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finally:
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Path(tmp_path).unlink(missing_ok=True)
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elapsed = round(time.time() - t0, 1)
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return {
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"text": result["text"].strip(),
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"segments": [
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{
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"start": round(seg["start"], 2),
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"end": round(seg["end"], 2),
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"text": seg["text"].strip(),
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}
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for seg in result.get("segments", [])
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],
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"language": result.get("language", "unknown"),
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"duration_seconds": elapsed,
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"model": model_name,
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}
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