31 lines
1.5 KiB
Python
31 lines
1.5 KiB
Python
"""Persistent offline Qwen-TTS worker; line-delimited stdin, no prompt logging."""
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import json,sys
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from pathlib import Path
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def main():
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model_path=sys.argv[1]
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try:
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import torch,soundfile as sf
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from qwen_tts import Qwen3TTSModel
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model=Qwen3TTSModel.from_pretrained(model_path,device_map='cuda:0',dtype=torch.bfloat16,attn_implementation='sdpa',local_files_only=True)
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except Exception as exc:
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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)
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return 1
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print(json.dumps(dict(ready=True)),flush=True)
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for line in sys.stdin:
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root=None
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try:
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request=json.loads(line);root=Path(request['output'])
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waves,rate=model.generate_custom_voice(text=request['text'],language=request['language'],speaker=request['speaker'],max_new_tokens=1024)
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wave=waves[0]
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if request['speed']!=1:
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import librosa
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wave=librosa.effects.time_stretch(wave,rate=request['speed'])
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sf.write(root/'result.wav',wave,rate,subtype='PCM_16')
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(root/'result.json').write_text(json.dumps(dict(ok=True,sample_rate=rate,duration=len(wave)/rate)))
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except Exception as exc:
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if root is not None:
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(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__)))
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return 0
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if __name__=='__main__':sys.exit(main())
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