From 02ca896808188a26a760ce0bad1135660244b4b4 Mon Sep 17 00:00:00 2001 From: Damien Date: Wed, 17 Jun 2026 11:51:23 +0200 Subject: [PATCH] Add Voxtral support with audio preprocessing --- pyproject.toml | 2 + src/audio_summary/pipeline/transcription.py | 44 ++- uv.lock | 386 +++++++++++++++++++- 3 files changed, 428 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 087060e..a180788 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -18,6 +18,8 @@ dependencies = [ "mlx-whisper>=0.4.0", "psutil>=6.0.0", "yt-dlp>=2025.3.27", + "librosa>=0.11.0", + "mistral-common>=1.11.3", ] [project.scripts] audio-summary = "audio_summary.cli:main" diff --git a/src/audio_summary/pipeline/transcription.py b/src/audio_summary/pipeline/transcription.py index aefe4c4..2a0487c 100644 --- a/src/audio_summary/pipeline/transcription.py +++ b/src/audio_summary/pipeline/transcription.py @@ -9,6 +9,10 @@ Two engines are supported, selected through ``config.STTModel.engine``: * ``whisper`` -> ``mlx-whisper`` fallback for memory-constrained Macs. """ +import os +import subprocess +import tempfile + from ..models import STTModel # Upper bound on generated tokens for a full-file transcription. The non-realtime @@ -16,6 +20,38 @@ from ..models import STTModel # recording, so we raise it well above the length of a long-form transcript. _VOXTRAL_MAX_TOKENS = 32768 +# Sample rate Voxtral expects; we resample to it during the WAV conversion below. +_VOXTRAL_SAMPLE_RATE = 16000 + + +def _to_wav_16k_mono(src: str) -> str: + """Transcode ``src`` to a temporary 16 kHz mono WAV via ffmpeg. + + Voxtral's processor loads audio through soundfile/libsndfile, which cannot + decode AAC/M4A (and several other compressed formats). ffmpeg (a project + prerequisite) handles those, so we normalize the input first. The caller is + responsible for deleting the returned path. + """ + fd, wav_path = tempfile.mkstemp(suffix=".wav") + os.close(fd) + subprocess.run( + [ + "ffmpeg", + "-y", + "-i", + src, + "-ac", + "1", + "-ar", + str(_VOXTRAL_SAMPLE_RATE), + wav_path, + ], + check=True, + stdout=subprocess.DEVNULL, + stderr=subprocess.DEVNULL, + ) + return wav_path + def _transcribe_voxtral(file_path: str, model_repo: str, language: str | None) -> str: """Transcribe using Mistral Voxtral through mlx-audio.""" @@ -28,7 +64,13 @@ def _transcribe_voxtral(file_path: str, model_repo: str, language: str | None) - kwargs: dict = {"max_tokens": _VOXTRAL_MAX_TOKENS} if language: kwargs["language"] = language - result = model.generate(file_path, **kwargs) + + # Hand Voxtral a soundfile-readable WAV regardless of the source container. + wav_path = _to_wav_16k_mono(file_path) + try: + result = model.generate(wav_path, **kwargs) + finally: + os.remove(wav_path) return result.text.strip() diff --git a/uv.lock 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