"""Persistent offline Qwen-TTS worker; line-delimited stdin, no prompt logging."""
import json,sys
from pathlib import Path

def main():
 model_path=sys.argv[1]
 try:
  import torch,soundfile as sf
  from qwen_tts import Qwen3TTSModel
  model=Qwen3TTSModel.from_pretrained(model_path,device_map='cuda:0',dtype=torch.bfloat16,attn_implementation='sdpa',local_files_only=True)
 except Exception as exc:
  print(json.dumps(dict(ready=False,error='CUDA-Speicher reicht nicht aus.' if 'outofmemory' in type(exc).__name__.lower() or 'out of memory' in str(exc).lower() else 'TTS-Modell konnte nicht geladen werden.')),flush=True)
  return 1
 print(json.dumps(dict(ready=True)),flush=True)
 for line in sys.stdin:
  root=None
  try:
   request=json.loads(line);root=Path(request['output'])
   waves,rate=model.generate_custom_voice(text=request['text'],language=request['language'],speaker=request['speaker'],max_new_tokens=1024)
   wave=waves[0]
   if request['speed']!=1:
    import librosa
    wave=librosa.effects.time_stretch(wave,rate=request['speed'])
   sf.write(root/'result.wav',wave,rate,subtype='PCM_16')
   (root/'result.json').write_text(json.dumps(dict(ok=True,sample_rate=rate,duration=len(wave)/rate)))
  except Exception as exc:
   if root is not None:
    (root/'result.json').write_text(json.dumps(dict(ok=False,error='CUDA-Speicher reicht nicht aus.' if 'outofmemory' in type(exc).__name__.lower() or 'out of memory' in str(exc).lower() else 'TTS-Ausführung fehlgeschlagen: '+type(exc).__name__)))
 return 0
if __name__=='__main__':sys.exit(main())