37 lines
1 KiB
Python
37 lines
1 KiB
Python
|
import io
|
||
|
|
import threading
|
||
|
|
import wave
|
||
|
|
|
||
|
|
from django.conf import settings
|
||
|
|
|
||
|
|
# Lazy per-process singleton: each gunicorn worker loads its own copy on first
|
||
|
|
# use rather than all workers loading the ONNX model at startup (the host runs
|
||
|
|
# several other containers with limited spare RAM).
|
||
|
|
_voice = None
|
||
|
|
_lock = threading.Lock()
|
||
|
|
|
||
|
|
|
||
|
|
def _get_voice():
|
||
|
|
global _voice
|
||
|
|
if _voice is None:
|
||
|
|
with _lock:
|
||
|
|
if _voice is None:
|
||
|
|
from piper import PiperVoice
|
||
|
|
_voice = PiperVoice.load(str(settings.TTS_MODEL_PATH))
|
||
|
|
return _voice
|
||
|
|
|
||
|
|
|
||
|
|
def synthesize_wav(text):
|
||
|
|
"""Synthesize `text` to WAV bytes.
|
||
|
|
|
||
|
|
Never persists or logs `text` — callers must not log it either. The lock
|
||
|
|
also serializes inference, since one onnxruntime session isn't meant to
|
||
|
|
run concurrent calls within a process.
|
||
|
|
"""
|
||
|
|
voice = _get_voice()
|
||
|
|
buf = io.BytesIO()
|
||
|
|
with _lock:
|
||
|
|
with wave.open(buf, 'wb') as wav_file:
|
||
|
|
voice.synthesize_wav(text, wav_file)
|
||
|
|
return buf.getvalue()
|