Files
speech/app/asr/config.py
du5t ce064d6894 Add VibeVoice-ASR backend
Third ASR backend option alongside faster-whisper and qwen3. Builds
microsoft/VibeVoice from source (pinned to a specific commit, since it's
custom modeling code not in transformers' Auto* registry) into its own venv,
inheriting the base image's torch/CUDA. Comes with built-in speaker
diarization (VibeVoiceASRProcessor.post_process_transcription returns
per-segment speaker ids directly, no separate pyannote pass needed).

Verified end-to-end against a real recording: 200 OK, correct Korean
transcription, speaker labels populated.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-23 16:54:34 +09:00

42 lines
1.4 KiB
Python

from __future__ import annotations
from pathlib import Path
from typing import Optional
from core.config import env_str
ASR_BASE_DIR = Path(env_str("ASR_BASE_DIR", "/srv/asr"))
MODEL_CACHE = Path(env_str("WHISPER_CACHE_DIR", str(ASR_BASE_DIR / "models-cache")))
UPLOAD_DIR = ASR_BASE_DIR / "uploads"
RESULT_DIR = ASR_BASE_DIR / "results"
CUSTOM_MODEL_DIR = ASR_BASE_DIR / "custom-models"
DEVICE = env_str("ASR_DEVICE", "cuda")
COMPUTE_TYPE = env_str("ASR_COMPUTE_TYPE", "float16")
DEFAULT_BACKEND = env_str("DEFAULT_BACKEND", "faster-whisper")
DEFAULT_MODEL = env_str("DEFAULT_MODEL", "large-v3")
DEFAULT_LANGUAGE = env_str("DEFAULT_LANGUAGE", "ko")
FASTER_WHISPER_URL = env_str("FASTER_WHISPER_URL", "http://127.0.0.1:8001")
QWEN3_URL = env_str("QWEN3_URL", "http://127.0.0.1:8004")
VIBEVOICE_URL = env_str("VIBEVOICE_URL", "http://127.0.0.1:8006")
PYANNOTE_HF_TOKEN = env_str("PYANNOTE_HF_TOKEN", "")
def ensure_runtime_dirs() -> None:
for p in [ASR_BASE_DIR, MODEL_CACHE, UPLOAD_DIR, RESULT_DIR, CUSTOM_MODEL_DIR]:
p.mkdir(parents=True, exist_ok=True)
def resolve_custom_model_path(custom_model_path: Optional[str]) -> Optional[str]:
if not custom_model_path:
return None
raw = custom_model_path.strip()
if not raw:
return None
candidate = Path(raw)
if candidate.is_absolute():
return str(candidate)
return str((CUSTOM_MODEL_DIR / candidate).resolve())