Files
product/services/asr.py
T
2026-03-29 23:01:39 +08:00

66 lines
2.1 KiB
Python

from __future__ import annotations
import logging
from typing import Optional
import numpy as np
logger = logging.getLogger(__name__)
class ASRService:
def __init__(self) -> None:
self._model = None
self._post = None
self._ready = False
self._attempted = False
self._init_error: Optional[str] = None
self._device: str = "uninitialized"
def _ensure_loaded(self) -> None:
if self._ready or self._attempted:
return
self._attempted = True
from funasr import AutoModel
from funasr.utils.postprocess_utils import rich_transcription_postprocess
errors: list[str] = []
for device in ("cuda:0", "cpu"):
try:
self._model = AutoModel(
model="FunAudioLLM/SenseVoiceSmall",
device=device,
hub="hf",
)
self._post = rich_transcription_postprocess
self._ready = True
self._init_error = None
self._device = device
if device != "cuda:0":
logger.warning("ASR running in degraded mode on %s", device)
return
except Exception as exc: # pragma: no cover
errors.append(f"{device}: {exc}")
self._init_error = " | ".join(errors)
self._device = "unavailable"
logger.warning("ASR unavailable: %s", self._init_error)
async def transcribe(self, audio_16k: np.ndarray) -> str:
self._ensure_loaded()
if self._ready and self._model is not None and self._post is not None:
res = self._model.generate(
input=audio_16k,
cache={},
language="zh",
use_itn=True,
)
return self._post(res[0]["text"])
# When ASR is unavailable, avoid emitting fake user text that would trigger a bogus LLM reply.
return ""
@property
def health(self) -> dict:
return {"ready": self._ready, "attempted": self._attempted, "device": self._device, "error": self._init_error}