spb/zyquo-mlx Public MIT
The local MLX foundry for your Mac — run, fine-tune, quantize, and ship models. Nothing leaves your machine.
Swift 93.4%
Python 3.8%
Makefile 2.2%
Shell 0.5%
1#2# zyquo_transcribe.py3# Zyquo MLX4#5# Author: Simon-Pierre Boucher6# Mail: contact@spboucher.ai7#8# Speech-to-text driver over mlx-whisper (docs/MLX-RESEARCH.md §3.2).9# JSON-lines protocol on stdout.10#11# Usage: zyquo_transcribe.py --model <dir-or-repo> --audio <file>1213import argparse14import json15import sys161718def emit(obj):19 sys.stdout.write(json.dumps(obj) + "\n")20 sys.stdout.flush()212223def main():24 parser = argparse.ArgumentParser()25 parser.add_argument("--model", required=True)26 parser.add_argument("--audio", required=True)27 args = parser.parse_args()2829 try:30 emit({"event": "start", "stage": "transcribing", "audio": args.audio})31 import mlx_whisper3233 result = mlx_whisper.transcribe(args.audio, path_or_hf_repo=args.model)34 emit({35 "event": "done",36 "text": result.get("text", "").strip(),37 "language": result.get("language"),38 "segments": len(result.get("segments", [])),39 })40 except Exception as exc: # noqa: BLE00141 emit({"event": "error", "message": str(exc), "type": type(exc).__name__})42 sys.exit(1)434445if __name__ == "__main__":46 main()47