"""Serial own TTS workers with shared model reservation, WAV results and cancellation."""
import json,os,signal,subprocess,threading,time,uuid,hashlib
from pathlib import Path
from tts_runtime import REPO,REVISION,SPEAKERS,LANGUAGES
from image_test import probe,cgroup_headroom
class TTSTests:
 def __init__(self,root,profiles,runtime):
  self.root=Path(root);self.profiles=profiles;self.runtime=runtime;self.lock=threading.RLock();self.job=None;self.process=None;self.cancel=threading.Event();self.acquire=lambda wait=False:lambda:None
 def status(self):
  with self.lock:return dict(job=dict(self.job) if self.job else None,runtime=self.runtime.status())
 def blockers(self,p):
  if p['model']['repo']!=REPO or p['model']['file']!='model.safetensors' or p['model'].get('revision')!=REVISION:return ['Dieses Modell ist nicht CUDA-CustomVoice. Unter TTS → Einrichten die passende Variante installieren und dem Profil zuordnen.']
  return [] if self.runtime.status()['installed'] else ['TTS-Laufzeit unter TTS → Einrichten installieren.']
 def assign(self,ident,revision):
  if not self.runtime.status()['installed']:raise ValueError('Zuerst TTS einrichten.')
  entry_id=self.runtime.ensure_library()
  p=next((p for p in self.profiles.status()['profiles'] if p['id']==ident),None)
  if not p or p['kind']!='audio':raise ValueError('TTS-Profil nicht gefunden.')
  return self.profiles.save(dict(id=ident,revision=revision,name=p['name'],kind='audio',model_id=entry_id,parameters=p['parameters']))
 def start(self,profile_id,text,speaker='Ryan',language='German',wait=False,speed=None):
  if not isinstance(text,str) or not 1<=len(text.strip())<=1000:raise ValueError('Text mit 1–1000 Zeichen erforderlich.')
  if speaker not in SPEAKERS or language not in LANGUAGES:raise ValueError('Ungültige Stimme oder Sprache.')
  if speed is not None and (type(speed) not in (int,float) or not .25<=speed<=4):raise ValueError('Geschwindigkeit muss zwischen 0,25 und 4 liegen.')
  release=self.acquire(wait)
  try:
   with self.lock:
    if self.job and self.job['state']=='running':raise ValueError('TTS-Auftrag läuft bereits.')
    p=next((p for p in self.profiles.status()['profiles'] if p['id']==profile_id and p['kind']=='audio'),None)
    if not p or not p['runnable']:raise ValueError('TTS-Profil noch nicht eingerichtet.')
    gpu=next((g for g in probe() if 'RTX 3060' in g['name'] and not g['processes'] and g['free_mib']>7000),None)
    if not gpu:raise ValueError('Die RTX 3060 muss frei sein und mindestens 7 GiB freien Speicher haben.')
    headroom=cgroup_headroom()
    if headroom is not None and headroom<8*1024**3:raise ValueError('Zu wenig freier Deck-RAM für TTS.')
    self.cancel.clear();ident=uuid.uuid4().hex;self.root.mkdir(parents=True,exist_ok=True,mode=0o700)
    self.job=dict(id=ident,state='running',phase='Sprachmodell wird geladen',profile_id=profile_id,started_at=time.time())
    threading.Thread(target=self._run,args=(ident,text,speaker,language,speed if speed is not None else p['parameters']['speed'],gpu,release),daemon=True).start();return dict(self.job)
  except Exception:release();raise
 def _run(self,ident,text,speaker,language,speed,gpu,release):
  directory=self.root/ident;process=None;state='failed';phase='TTS-Ausführung fehlgeschlagen'
  try:
   directory.mkdir(mode=0o700);python,model=self.runtime.paths()
   env={k:v for k,v in os.environ.items() if not k.startswith(('HF_','LLAMA_'))};env.update(CUDA_VISIBLE_DEVICES=gpu['uuid'],HF_HUB_OFFLINE='1',TRANSFORMERS_OFFLINE='1',OMP_NUM_THREADS='2',HOME=str(directory))
   with self.lock:
    if self.cancel.is_set():raise InterruptedError()
    process=subprocess.Popen([str(python),str(Path(__file__).with_name('tts_worker.py'))],stdin=subprocess.PIPE,stdout=subprocess.DEVNULL,stderr=subprocess.DEVNULL,start_new_session=True,env=env);self.process=process;self.job['phase']='Sprache wird auf der RTX 3060 erzeugt'
   process.stdin.write(json.dumps(dict(model=str(model),output=str(directory),text=text,speaker=speaker,language=language,speed=speed)).encode());process.stdin.close()
   end=time.monotonic()+600
   while process.poll() is None:
    if self.cancel.wait(1):raise InterruptedError()
    if time.monotonic()>end:raise ValueError('Zeitlimit der Sprachgenerierung erreicht.')
    current=next((g for g in probe() if g['uuid']==gpu['uuid']),None)
    if not current or current['processes']>1:raise ValueError('Die reservierte GPU wurde anderweitig belegt.')
   result=json.loads((directory/'result.json').read_text()) if (directory/'result.json').exists() else dict(ok=False,error='Worker beendet: möglicher Speichermangel oder Laufzeitfehler.')
   if self.cancel.is_set():raise InterruptedError()
   if not result['ok']:raise ValueError(result['error'])
   wav=directory/'result.wav'
   if not wav.exists() or wav.stat().st_size>32*1024**2:raise ValueError('Ungültige Audioausgabe.')
   state='complete';phase='Sprache fertig · Modell entladen'
  except InterruptedError:state='cancelled';phase='Sprachgenerierung abgebrochen'
  except Exception as exc:phase=str(exc) if isinstance(exc,ValueError) else 'Sprachgenerierung fehlgeschlagen. Laufzeit und Ressourcen prüfen.'
  finally:
   if process and process.poll() is None:
    try:
     os.killpg(process.pid,signal.SIGTERM)
     try:process.wait(timeout=5)
     except subprocess.TimeoutExpired:os.killpg(process.pid,signal.SIGKILL);process.wait()
    except ProcessLookupError:pass
   if state=='complete':(directory/'complete').touch()
   with self.lock:self.process=None;self.job.update(state=state,phase=phase,finished_at=time.time())
   release()
 def stop(self):
  self.cancel.set()
  with self.lock:process=self.process
  if process and process.poll() is None:
   try:os.killpg(process.pid,signal.SIGTERM)
   except ProcessLookupError:pass
  return dict(cancellation_requested=True)
 def audio(self,ident):
  if not isinstance(ident,str) or len(ident)!=32 or any(c not in '0123456789abcdef' for c in ident) or not (self.root/ident/'complete').exists():raise ValueError('Audio noch nicht verfügbar.')
  return (self.root/ident/'result.wav').read_bytes()