release: bump version to 0.0.5.3

AudioFocus.requestDuck nutzt jetzt AUDIOFOCUS_GAIN_TRANSIENT (statt
TRANSIENT_MAY_DUCK) — Spotify/YouTube pausieren komplett solange ARIA
spricht und kommen nicht mitten drin wieder hoch.

PcmStreamPlayer.end() resolved jetzt erst wenn der native Writer-Thread
wirklich fertig ist (alle Samples aus dem Pre-Roll-Puffer ausgespielt).
audio.ts wartet entsprechend, bevor AudioFocus.release() gerufen wird —
behebt das "Musik dreht hoch waehrend Antwort noch laeuft"-Problem.

Mic-Aufnahme: VAD_SILENCE_DURATION_MS 1800 → 2800ms (mehr Toleranz fuer
Sprechpausen), MAX_RECORDING_MS 30s → 120s (laengere Erklaerungen
moeglich, Notbremse bleibt).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

android/android/app/build.gradle

@@ -79,8 +79,8 @@ android {
         applicationId "com.ariacockpit"
         minSdkVersion rootProject.ext.minSdkVersion
         targetSdkVersion rootProject.ext.targetSdkVersion
-        versionCode 403
-        versionName "0.0.4.3"
+        versionCode 503
+        versionName "0.0.5.3"
         // Fallback fuer Libraries mit Product Flavors
         missingDimensionStrategy 'react-native-camera', 'general'
     }

android/android/app/src/main/java/com/ariacockpit/AudioFocusModule.kt

@@ -53,11 +53,17 @@ class AudioFocusModule(reactContext: ReactApplicationContext) : ReactContextBase
         promise.resolve(result == AudioManager.AUDIOFOCUS_REQUEST_GRANTED)
     }
 
-    /** Andere Apps werden leiser (TTS spricht). */
+    /** Andere Apps werden pausiert (TTS spricht).
+     *
+     *  TRANSIENT (statt TRANSIENT_MAY_DUCK): Spotify/YouTube pausieren komplett
+     *  statt nur leiser zu werden. Verhindert auch das "kommt-wieder-hoch"-
+     *  Problem mit MAY_DUCK, wo das System nach kurzer Zeit den Duck-Effekt
+     *  wieder aufgehoben hat obwohl wir den Fokus noch hielten.
+     */
     @ReactMethod
     fun requestDuck(promise: Promise) {
         requestFocus(
-            AudioManager.AUDIOFOCUS_GAIN_TRANSIENT_MAY_DUCK,
+            AudioManager.AUDIOFOCUS_GAIN_TRANSIENT,
             AudioAttributes.USAGE_ASSISTANT,
             promise,
         )

android/android/app/src/main/java/com/ariacockpit/PcmStreamPlayerModule.kt

@@ -13,22 +13,30 @@ import com.facebook.react.bridge.ReactMethod
 import java.util.concurrent.LinkedBlockingQueue
 
 /**
- * Streamt PCM-s16le Audio direkt via AudioTrack MODE_STREAM.
+ * Streamt PCM-s16le Audio direkt via AudioTrack MODE_STREAM mit Pre-Roll.
+ *
+ * Pre-Roll: AudioTrack wird zwar direkt gebaut und gefuttert, aber play()
+ * wird erst aufgerufen wenn PREROLL_SECONDS Audio im Buffer ist. So hat
+ * der Stream Zeit einen Vorrat aufzubauen — wenn XTTS mit RTF>1 rendert
+ * (langsamer als Echtzeit), laeuft der Buffer trotzdem nicht leer.
  *
  * Flow:
- *   JS: start(sampleRate, channels) → öffnet AudioTrack und startet Writer-Thread
- *   JS: writeChunk(base64)           → dekodiert, queued, Writer schreibt non-blocking
- *   JS: end()                         → wartet bis Queue leer, schließt AudioTrack
- *   JS: stop()                        → Hart stoppen, Queue leeren (Cancel)
- *
- * Vorteil gegenüber Sound-File-Queue:
- *   - Keine Gap zwischen Chunks (AudioTrack puffert intern)
- *   - Erste Samples beginnen zu spielen sobald der erste Chunk da ist
- *   - Kein WAV-Header-Parsing pro Chunk
+ *   JS: start(sampleRate, channels) → öffnet AudioTrack (noch nicht play())
+ *   JS: writeChunk(base64)           → dekodiert, queued, Writer schreibt
+ *   Writer: spielt los sobald PREROLL erreicht ist
+ *   JS: end()                         → wartet bis Queue leer, schließt
+ *   JS: stop()                        → Hart stoppen (Cancel)
  */
 class PcmStreamPlayerModule(reactContext: ReactApplicationContext) : ReactContextBaseJavaModule(reactContext) {
     companion object {
         private const val TAG = "PcmStreamPlayer"
+        // Fallback wenn JS keinen Wert uebergibt.
+        private const val DEFAULT_PREROLL_SECONDS = 3.5
+        private const val MIN_PREROLL_SECONDS = 0.5
+        private const val MAX_PREROLL_SECONDS = 10.0
+        // Stille am Stream-Anfang, damit AudioTrack sauber anfaehrt und die
+        // ersten Samples nicht abgeschnitten werden (XTTS-Warmup + play()-Latenz).
+        private const val LEADING_SILENCE_SECONDS = 0.2
     }
 
     override fun getName() = "PcmStreamPlayer"
@@ -38,22 +46,34 @@ class PcmStreamPlayerModule(reactContext: ReactApplicationContext) : ReactContex
     private var writerThread: Thread? = null
     @Volatile private var writerShouldStop = false
     @Volatile private var endRequested = false
+    @Volatile private var prerollBytes: Int = 0
+    @Volatile private var playbackStarted = false
+    @Volatile private var bytesBuffered: Long = 0
+    @Volatile private var streamBytesPerFrame: Int = 2 // mono s16le default
 
     // ── Lifecycle ──
 
     @ReactMethod
-    fun start(sampleRate: Int, channels: Int, promise: Promise) {
+    fun start(sampleRate: Int, channels: Int, prerollSeconds: Double, promise: Promise) {
         try {
             // Alte Session beenden falls vorhanden
             stopInternal()
 
+            val prerollSec = prerollSeconds
+                .coerceIn(MIN_PREROLL_SECONDS, MAX_PREROLL_SECONDS)
+                .let { if (it.isFinite() && it > 0) it else DEFAULT_PREROLL_SECONDS }
+
             val channelConfig = if (channels == 2) AudioFormat.CHANNEL_OUT_STEREO else AudioFormat.CHANNEL_OUT_MONO
             val encoding = AudioFormat.ENCODING_PCM_16BIT
             val minBuf = AudioTrack.getMinBufferSize(sampleRate, channelConfig, encoding)
-            // Grosszuegiger Buffer: 32x MinSize — tolerant gegen Netzwerk-Jitter und
-            // bursty XTTS-Delivery (Render dauert 1-3s, dann kommen alle Samples
-            // auf einmal). Bei 24kHz mono s16 entspricht 128KB ca. 2.7 Sekunden.
-            val bufferSize = (minBuf * 32).coerceAtLeast(128 * 1024)
+            val bytesPerSecond = sampleRate * channels * 2 // 16-bit = 2 bytes
+            // Buffer muss mindestens PREROLL + etwas Spielraum fassen.
+            val prerollTarget = (bytesPerSecond * prerollSec).toInt()
+            val bufferSize = (minBuf * 32).coerceAtLeast(prerollTarget * 2)
+            prerollBytes = prerollTarget
+            bytesBuffered = 0
+            playbackStarted = false
+            streamBytesPerFrame = channels * 2 // s16 = 2 bytes per sample
 
             val newTrack = AudioTrack.Builder()
                 .setAudioAttributes(
@@ -73,7 +93,7 @@ class PcmStreamPlayerModule(reactContext: ReactApplicationContext) : ReactContex
                 .setTransferMode(AudioTrack.MODE_STREAM)
                 .build()
 
-            newTrack.play()
+            // AudioTrack erstellen — play() wird erst aufgerufen wenn Pre-Roll erreicht.
             track = newTrack
             queue.clear()
             writerShouldStop = false
@@ -82,27 +102,83 @@ class PcmStreamPlayerModule(reactContext: ReactApplicationContext) : ReactContex
             writerThread = Thread({
                 val t = track ?: return@Thread
                 try {
+                    // Leading-Silence in den Buffer — gibt AudioTrack Zeit anzufahren.
+                    val silenceBytes = ((sampleRate * channels * 2) * LEADING_SILENCE_SECONDS).toInt() and 0x7FFFFFFE
+                    if (silenceBytes > 0) {
+                        val silence = ByteArray(silenceBytes)
+                        var silOff = 0
+                        while (silOff < silence.size && !writerShouldStop) {
+                            val w = t.write(silence, silOff, silence.size - silOff)
+                            if (w <= 0) break
+                            silOff += w
+                        }
+                        bytesBuffered += silence.size
+                    }
                     while (!writerShouldStop) {
                         val data = queue.poll(50, java.util.concurrent.TimeUnit.MILLISECONDS) ?: run {
-                            if (endRequested) return@Thread
+                            if (endRequested) {
+                                // Falls wir vor Pre-Roll enden (kurzer Text): trotzdem abspielen
+                                if (!playbackStarted) {
+                                    try { t.play() } catch (_: Exception) {}
+                                    playbackStarted = true
+                                }
+                                return@Thread
+                            }
                             null
                         } ?: continue
+
+                        // Pre-Roll Check: play() erst wenn genug gepuffert
+                        if (!playbackStarted && bytesBuffered + data.size >= prerollBytes) {
+                            try {
+                                t.play()
+                                playbackStarted = true
+                                Log.i(TAG, "Playback gestartet nach Pre-Roll ${bytesBuffered + data.size} Bytes")
+                            } catch (e: Exception) {
+                                Log.w(TAG, "play() failed: ${e.message}")
+                            }
+                        }
+
                         var offset = 0
                         while (offset < data.size && !writerShouldStop) {
                             val written = t.write(data, offset, data.size - offset)
                             if (written <= 0) break
                             offset += written
                         }
+                        bytesBuffered += data.size
                     }
                 } catch (e: Exception) {
                     Log.w(TAG, "Writer-Thread Fehler: ${e.message}")
                 } finally {
+                    // Warten bis alle geschriebenen Samples tatsaechlich abgespielt sind,
+                    // sonst cuttet t.release() die letzten Sekunden ab.
+                    try {
+                        val totalFrames = (bytesBuffered / streamBytesPerFrame).toInt()
+                        var lastPos = -1
+                        var stalledCount = 0
+                        while (!writerShouldStop) {
+                            val pos = t.playbackHeadPosition
+                            if (pos >= totalFrames) break
+                            // Safety: wenn Position 2s nicht mehr vorwaerts → AudioTrack hing
+                            if (pos == lastPos) {
+                                stalledCount++
+                                if (stalledCount > 40) {
+                                    Log.w(TAG, "playback stalled at $pos/$totalFrames — give up")
+                                    break
+                                }
+                            } else {
+                                stalledCount = 0
+                                lastPos = pos
+                            }
+                            Thread.sleep(50)
+                        }
+                        Log.i(TAG, "Playback fertig: frames=$totalFrames pos=${t.playbackHeadPosition}")
+                    } catch (_: Exception) {}
                     try { t.stop() } catch (_: Exception) {}
                     try { t.release() } catch (_: Exception) {}
                 }
             }, "PcmStreamWriter").apply { start() }
 
-            Log.i(TAG, "Stream gestartet: ${sampleRate}Hz ch=$channels buf=${bufferSize}B")
+            Log.i(TAG, "Stream gestartet: ${sampleRate}Hz ch=$channels buf=${bufferSize}B preroll=${prerollBytes}B (${prerollSec}s)")
             promise.resolve(true)
         } catch (e: Exception) {
             Log.e(TAG, "start fehlgeschlagen", e)
@@ -125,11 +201,27 @@ class PcmStreamPlayerModule(reactContext: ReactApplicationContext) : ReactContex
         }
     }
 
-    /** Signalisiert: keine weiteren Chunks. Writer wartet auf Queue-Abschluss, dann stoppt. */
+    /** Signalisiert: keine weiteren Chunks. Writer spielt aus, dann stoppt.
+     *  Das Promise resolved erst wenn der Writer-Thread fertig ist —
+     *  wichtig damit der Aufrufer den AudioFocus erst NACH dem letzten
+     *  abgespielten Sample wieder freigibt (sonst dreht Spotify hoch
+     *  waehrend das Pre-Roll noch ausspielt).
+     */
     @ReactMethod
     fun end(promise: Promise) {
         endRequested = true
-        promise.resolve(true)
+        val t = writerThread
+        if (t == null || !t.isAlive) {
+            promise.resolve(true)
+            return
+        }
+        // Im Hintergrund auf den Writer warten — kein Threading-Block fuer JS-Bridge
+        Thread({
+            try {
+                t.join(15_000) // hartes Cap, falls Writer haengt
+            } catch (_: InterruptedException) {}
+            promise.resolve(true)
+        }, "PcmStreamEndWaiter").start()
     }
 
     /** Harter Stop (Cancel) — Queue verwerfen. */

android/package.json

@@ -1,6 +1,6 @@
 {
   "name": "aria-cockpit",
-  "version": "0.0.4.3",
+  "version": "0.0.5.3",
   "private": true,
   "scripts": {
     "android": "react-native run-android",

android/src/screens/ChatScreen.tsx

@@ -18,6 +18,7 @@ import {
   Image,
   ScrollView,
   Modal,
+  ToastAndroid,
 } from 'react-native';
 import AsyncStorage from '@react-native-async-storage/async-storage';
 import RNFS from 'react-native-fs';
@@ -325,6 +326,26 @@ const ChatScreen: React.FC = () => {
         const tool = (message.payload.tool as string) || '';
         setAgentActivity({ activity, tool });
       }
+
+      // Voice-Config aus Diagnostic — setzt die lokale App-Stimme auf den
+      // gerade in Diagnostic gewaehlten Wert zurueck. User-Wahl in der App
+      // wird dadurch ueberschrieben.
+      if (message.type === ('config' as any)) {
+        const newVoice = ((message.payload as any).xttsVoice as string) ?? '';
+        localXttsVoiceRef.current = newVoice;
+        AsyncStorage.setItem('aria_xtts_voice', newVoice);
+      }
+
+      // XTTS-Bridge meldet Stimme fertig geladen (kurzer Status-Toast)
+      if (message.type === ('voice_ready' as any)) {
+        const v = ((message.payload as any).voice as string) ?? '';
+        const err = (message.payload as any).error as string | undefined;
+        if (err) {
+          ToastAndroid.show(`Stimme "${v}" Fehler: ${err}`, ToastAndroid.LONG);
+        } else {
+          ToastAndroid.show(`Stimme "${v || 'Standard'}" bereit`, ToastAndroid.SHORT);
+        }
+      }
     });
 
     const unsubState = rvs.onStateChange((state) => {

android/src/screens/SettingsScreen.tsx

@@ -15,11 +15,19 @@ import {
   StyleSheet,
   Alert,
   Platform,
+  ToastAndroid,
+  ActivityIndicator,
 } from 'react-native';
 import AsyncStorage from '@react-native-async-storage/async-storage';
 import RNFS from 'react-native-fs';
 import DocumentPicker from 'react-native-document-picker';
 import rvs, { ConnectionState, RVSMessage, ConnectionConfig, ConnectionLogEntry } from '../services/rvs';
+import {
+  TTS_PREROLL_DEFAULT_SEC,
+  TTS_PREROLL_MIN_SEC,
+  TTS_PREROLL_MAX_SEC,
+  TTS_PREROLL_STORAGE_KEY,
+} from '../services/audio';
 import ModeSelector from '../components/ModeSelector';
 import QRScanner from '../components/QRScanner';
 import VoiceCloneModal from '../components/VoiceCloneModal';
@@ -73,8 +81,10 @@ const SettingsScreen: React.FC = () => {
   const [autoDownload, setAutoDownload] = useState(true);
   const [storageSize, setStorageSize] = useState('...');
   const [ttsEnabled, setTtsEnabled] = useState(true);
+  const [ttsPrerollSec, setTtsPrerollSec] = useState<number>(TTS_PREROLL_DEFAULT_SEC);
   const [editingPath, setEditingPath] = useState(false);
   const [xttsVoice, setXttsVoice] = useState('');
+  const [loadingVoice, setLoadingVoice] = useState<string | null>(null);
   const [availableVoices, setAvailableVoices] = useState<Array<{name: string, size: number}>>([]);
   const [voiceCloneVisible, setVoiceCloneVisible] = useState(false);
   const [tempPath, setTempPath] = useState('');
@@ -99,6 +109,14 @@ const SettingsScreen: React.FC = () => {
     AsyncStorage.getItem('aria_tts_enabled').then(saved => {
       if (saved !== null) setTtsEnabled(saved === 'true');
     });
+    AsyncStorage.getItem(TTS_PREROLL_STORAGE_KEY).then(saved => {
+      if (saved != null) {
+        const n = parseFloat(saved);
+        if (isFinite(n) && n >= TTS_PREROLL_MIN_SEC && n <= TTS_PREROLL_MAX_SEC) {
+          setTtsPrerollSec(n);
+        }
+      }
+    });
     AsyncStorage.getItem('aria_xtts_voice').then(saved => {
       if (saved) setXttsVoice(saved);
     });
@@ -250,6 +268,31 @@ const SettingsScreen: React.FC = () => {
         }
         rvs.send('xtts_list_voices' as any, {});
       }
+
+      // Diagnostic-Voice-Wechsel → lokale App-Stimme auf den neuen Default zuruecksetzen.
+      // Zusaetzlich Preload triggern, damit der User weiss wann's geladen ist.
+      if (message.type === ('config' as any)) {
+        const newVoice = ((message.payload as any).xttsVoice as string) ?? '';
+        setXttsVoice(newVoice);
+        AsyncStorage.setItem('aria_xtts_voice', newVoice);
+        if (newVoice) {
+          setLoadingVoice(newVoice);
+        }
+      }
+
+      // XTTS-Bridge meldet: Stimme fertig geladen
+      if (message.type === ('voice_ready' as any)) {
+        const v = ((message.payload as any).voice as string) ?? '';
+        const err = (message.payload as any).error as string | undefined;
+        const ms = (message.payload as any).loadMs as number | undefined;
+        setLoadingVoice(null);
+        if (err) {
+          ToastAndroid.show(`Stimme "${v}" konnte nicht geladen werden: ${err}`, ToastAndroid.LONG);
+        } else {
+          const suffix = ms ? ` (${(ms / 1000).toFixed(1)}s)` : '';
+          ToastAndroid.show(`Stimme "${v || 'Standard'}" bereit${suffix}`, ToastAndroid.SHORT);
+        }
+      }
     });
 
     return () => {
@@ -318,6 +361,13 @@ const SettingsScreen: React.FC = () => {
   const selectVoice = useCallback((voiceName: string) => {
     setXttsVoice(voiceName);
     AsyncStorage.setItem('aria_xtts_voice', voiceName);
+    // Preload nur fuer Custom-Voices — "Standard" braucht keinen Ladevorgang
+    if (voiceName) {
+      setLoadingVoice(voiceName);
+      rvs.send('voice_preload' as any, { voice: voiceName, source: 'app' });
+    } else {
+      setLoadingVoice(null);
+    }
   }, []);
 
   const deleteVoice = useCallback((name: string) => {
@@ -527,6 +577,42 @@ const SettingsScreen: React.FC = () => {
           />
         </View>
 
+        {ttsEnabled && (
+          <View style={{marginTop: 20}}>
+            <Text style={styles.toggleLabel}>Puffer vor Wiedergabestart</Text>
+            <Text style={styles.toggleHint}>
+              Wie viel Audio gesammelt wird bevor die Wiedergabe startet.
+              Hoeher = robuster gegen Render-Pausen, aber mehr Startverzoegerung.
+              Default: {TTS_PREROLL_DEFAULT_SEC.toFixed(1)}s.
+            </Text>
+            <View style={styles.prerollRow}>
+              <TouchableOpacity
+                style={styles.prerollButton}
+                onPress={() => {
+                  const next = Math.max(TTS_PREROLL_MIN_SEC, Math.round((ttsPrerollSec - 0.5) * 10) / 10);
+                  setTtsPrerollSec(next);
+                  AsyncStorage.setItem(TTS_PREROLL_STORAGE_KEY, String(next));
+                }}
+                disabled={ttsPrerollSec <= TTS_PREROLL_MIN_SEC}
+              >
+                <Text style={styles.prerollButtonText}>−0.5</Text>
+              </TouchableOpacity>
+              <Text style={styles.prerollValue}>{ttsPrerollSec.toFixed(1)} s</Text>
+              <TouchableOpacity
+                style={styles.prerollButton}
+                onPress={() => {
+                  const next = Math.min(TTS_PREROLL_MAX_SEC, Math.round((ttsPrerollSec + 0.5) * 10) / 10);
+                  setTtsPrerollSec(next);
+                  AsyncStorage.setItem(TTS_PREROLL_STORAGE_KEY, String(next));
+                }}
+                disabled={ttsPrerollSec >= TTS_PREROLL_MAX_SEC}
+              >
+                <Text style={styles.prerollButtonText}>+0.5</Text>
+              </TouchableOpacity>
+            </View>
+          </View>
+        )}
+
         {ttsEnabled && (
           <View style={{marginTop: 20}}>
             <Text style={styles.toggleLabel}>Stimme (geraetelokal)</Text>
@@ -561,7 +647,10 @@ const SettingsScreen: React.FC = () => {
                     </Text>
                     <Text style={styles.voiceRowMeta}>{(v.size / 1024).toFixed(0)} KB</Text>
                   </TouchableOpacity>
-                  {xttsVoice === v.name && <Text style={styles.voiceRowCheck}>{'\u2713'}</Text>}
+                  {loadingVoice === v.name && (
+                    <ActivityIndicator size="small" color="#0096FF" style={{marginRight: 8}} />
+                  )}
+                  {xttsVoice === v.name && loadingVoice !== v.name && <Text style={styles.voiceRowCheck}>{'\u2713'}</Text>}
                   <TouchableOpacity onPress={() => deleteVoice(v.name)} style={styles.voiceRowDelete}>
                     <Text style={styles.voiceRowDeleteIcon}>X</Text>
                   </TouchableOpacity>
@@ -1118,6 +1207,34 @@ const styles = StyleSheet.create({
   bottomSpacer: {
     height: 40,
   },
+
+  prerollRow: {
+    flexDirection: 'row',
+    alignItems: 'center',
+    justifyContent: 'center',
+    marginTop: 12,
+    gap: 16,
+  },
+  prerollButton: {
+    backgroundColor: '#2A2A3E',
+    paddingHorizontal: 18,
+    paddingVertical: 10,
+    borderRadius: 8,
+    minWidth: 72,
+    alignItems: 'center',
+  },
+  prerollButtonText: {
+    color: '#FFFFFF',
+    fontSize: 16,
+    fontWeight: '600',
+  },
+  prerollValue: {
+    color: '#FFFFFF',
+    fontSize: 20,
+    fontWeight: '700',
+    minWidth: 80,
+    textAlign: 'center',
+  },
 });
 
 export default SettingsScreen;

android/src/services/audio.ts

@@ -9,6 +9,7 @@
 import { Platform, PermissionsAndroid, NativeModules } from 'react-native';
 import Sound from 'react-native-sound';
 import RNFS from 'react-native-fs';
+import AsyncStorage from '@react-native-async-storage/async-storage';
 import AudioRecorderPlayer, {
   AudioEncoderAndroidType,
   AudioSourceAndroidType,
@@ -41,7 +42,7 @@ const { AudioFocus, PcmStreamPlayer } = NativeModules as {
     release: () => Promise<boolean>;
   };
   PcmStreamPlayer?: {
-    start: (sampleRate: number, channels: number) => Promise<boolean>;
+    start: (sampleRate: number, channels: number, prerollSeconds: number) => Promise<boolean>;
     writeChunk: (base64Pcm: string) => Promise<boolean>;
     end: () => Promise<boolean>;
     stop: () => Promise<boolean>;
@@ -73,12 +74,33 @@ const AUDIO_ENCODING = 'audio/wav';
 
 // VAD (Voice Activity Detection) — Stille-Erkennung
 const VAD_SILENCE_THRESHOLD_DB = -45;  // dB unter dem als "Stille" gilt
-const VAD_SILENCE_DURATION_MS = 1800;  // ms Stille bevor Auto-Stop
+const VAD_SILENCE_DURATION_MS = 2800;  // ms Stille bevor Auto-Stop — laenger = mehr Toleranz fuer Sprechpausen
 const VAD_SPEECH_THRESHOLD_DB = -28;   // dB ueber dem als "Sprache" gilt (Sprach-Gate) — hoeher = weniger Umgebungsgeraeusche
 const VAD_SPEECH_MIN_MS = 500;         // ms Sprache bevor Aufnahme zaehlt — laenger = keine Huestler/Klopfer mehr
 
-// Max-Dauer einer Aufnahme in Gespraechsmodus (Notbremse gegen Runaway-Loops)
-const MAX_RECORDING_MS = 30000;
+// Max-Dauer einer Aufnahme (Notbremse gegen Runaway-Loops). Auf 2 Minuten
+// hochgezogen damit auch laengere Erklaerungen durchgehen.
+const MAX_RECORDING_MS = 120000;
+
+// Pre-Roll: Wie lange Audio im AudioTrack-Buffer liegt bevor play() startet.
+// Einstellbar via Diagnostic/Settings (Key: aria_tts_preroll_sec).
+export const TTS_PREROLL_DEFAULT_SEC = 3.5;
+export const TTS_PREROLL_MIN_SEC = 1.0;
+export const TTS_PREROLL_MAX_SEC = 6.0;
+export const TTS_PREROLL_STORAGE_KEY = 'aria_tts_preroll_sec';
+
+async function loadPrerollSec(): Promise<number> {
+  try {
+    const raw = await AsyncStorage.getItem(TTS_PREROLL_STORAGE_KEY);
+    if (raw != null) {
+      const n = parseFloat(raw);
+      if (isFinite(n) && n >= TTS_PREROLL_MIN_SEC && n <= TTS_PREROLL_MAX_SEC) {
+        return n;
+      }
+    }
+  } catch {}
+  return TTS_PREROLL_DEFAULT_SEC;
+}
 
 // --- Audio-Service ---
 
@@ -373,8 +395,9 @@ class AudioService {
       this.pcmBuffer = [];
       this.pcmBytesCollected = 0;
       if (!silent) {
+        const prerollSec = await loadPrerollSec();
         try {
-          await PcmStreamPlayer!.start(sampleRate, channels);
+          await PcmStreamPlayer!.start(sampleRate, channels, prerollSec);
         } catch (err) {
           console.error('[Audio] PcmStreamPlayer.start fehlgeschlagen:', err);
           this.pcmStreamActive = false;
@@ -397,6 +420,10 @@ class AudioService {
 
     if (isFinal) {
       if (!silent) {
+        // end() resolved jetzt erst wenn der native Writer-Thread fertig
+        // ist (alle Samples ausgespielt) — danach erst AudioFocus freigeben,
+        // damit Spotify/YouTube nicht waehrend des Pre-Roll-Ausklangs
+        // wieder aufdrehen.
         try { await PcmStreamPlayer!.end(); } catch {}
         AudioFocus?.release().catch(() => {});
       }

bridge/aria_bridge.py

@@ -150,6 +150,15 @@ def _small_range_to_words(m):
     return f"{_num_to_words_de(a)} bis {_num_to_words_de(b)}"
 
 
+def _decimal_to_words(m):
+    """'0.1' / '0,1' → 'null komma eins', '1,25' → 'eins komma zwei fuenf'."""
+    int_part = int(m.group(1))
+    dec_part = m.group(2)
+    int_word = _num_to_words_de(int_part) if 0 <= int_part <= 59 else str(int_part)
+    dec_words = " ".join(_num_to_words_de(int(d)) for d in dec_part)
+    return f"{int_word} komma {dec_words}"
+
+
 _UNIT_WORDS = [
     (r'\bTB\b', 'Terabyte'),
     (r'\bGB\b', 'Gigabyte'),
@@ -236,6 +245,11 @@ def clean_text_for_tts(text: str) -> str:
     # Kleine Zahlen-Bereiche ohne "Uhr": "5-6" → "fuenf bis sechs"
     t = _re_tts.sub(r'\b(\d{1,2})\s*[-–]\s*(\d{1,2})\b', _small_range_to_words, t)
 
+    # Dezimalzahlen: "0.1" / "0,5" / "1,25" → "null komma eins" / "null komma fuenf" / ...
+    # Muss vor "Zahl+Einheit" laufen, sonst frisst die Unit-Regel den Nachkommaanteil.
+    # Lookahead verhindert Match auf IP-artigen Strings wie 192.168.1.1.
+    t = _re_tts.sub(r'\b(\d+)[.,](\d+)(?![.,\d])', _decimal_to_words, t)
+
     # Zahlen + Einheit: "22GB" → "22 Gigabyte" (Leerzeichen einfuegen)
     t = _re_tts.sub(r'(\d+)([A-Za-z]{1,4})\b', r'\1 \2', t)
 
@@ -243,6 +257,12 @@ def clean_text_for_tts(text: str) -> str:
     for pat, repl in _UNIT_WORDS:
         t = _re_tts.sub(pat, repl, t)
 
+    # Generisches Buchstabieren: alle verbleibenden 2-5-Zeichen-Grossbuchstaben-Woerter
+    # (XTTS, USB, DNS, JSON, HTML, ...) → "X T T S". Laeuft NACH der expliziten Liste,
+    # damit TTS/GPU/... schon aufgeloest sind. "WLAN"-artige, die als Wort gesprochen
+    # werden, koennen bei Bedarf explizit in _UNIT_WORDS uebersteuert werden.
+    t = _re_tts.sub(r'\b([A-Z]{2,5})\b', lambda m: " ".join(m.group(1)), t)
+
     # Anfuehrungszeichen
     t = _re_tts.sub(r'["""„`]', '', t)
 
@@ -305,8 +325,16 @@ class STTEngine:
             Erkannter Text oder leerer String.
         """
         if self.model is None:
-            logger.error("Whisper-Modell nicht initialisiert")
-            return ""
+            # Lazy-Load: normalerweise laeuft STT remote auf der Gamebox.
+            # Erst wenn das Fallback hier zuschlaegt, laden wir lokal.
+            logger.info("Lokales Whisper-Fallback — Modell wird nachgeladen...")
+            try:
+                self.initialize()
+            except Exception:
+                logger.exception("Lokales Whisper konnte nicht geladen werden")
+                return ""
+            if self.model is None:
+                return ""
 
         try:
             # Audio als float32 normalisieren
@@ -503,6 +531,9 @@ class ARIABridge:
         # Wird fuer die direkt folgende ARIA-Antwort genutzt und dann zurueckgesetzt.
         # So kann jedes Geraet seine bevorzugte Stimme bekommen (pro Request).
         self._next_voice_override: Optional[str] = None
+        # STT-Requests die aktuell auf Antwort von der whisper-bridge (Gamebox) warten.
+        # requestId → Future mit dem Text (oder None bei Fehler).
+        self._pending_stt: dict[str, asyncio.Future] = {}
 
     def initialize(self) -> None:
         """Initialisiert alle Komponenten.
@@ -515,8 +546,9 @@ class ARIABridge:
         logger.info("ARIA Voice Bridge startet...")
         logger.info("=" * 50)
 
-        # STT IMMER laden — verarbeitet Audio von der App (braucht kein Sounddevice)
-        self.stt_engine.initialize()
+        # STT wird standardmaessig von der whisper-bridge (Gamebox) erledigt.
+        # Lokales Whisper ist nur Fallback und wird lazy geladen wenn remote nicht
+        # antwortet. Das spart RAM auf der VM und Startup-Zeit.
 
         # Audio-Hardware pruefen (fuer lokales Mikro/Lautsprecher)
         self.audio_available = False
@@ -1175,11 +1207,16 @@ class ARIABridge:
                 changed = True
             if "whisperModel" in payload:
                 new_model = payload["whisperModel"]
-                if new_model and new_model != self.stt_engine.model_size:
-                    logger.info("[rvs] Whisper-Modell Wechsel: %s -> %s (laedt...)", self.stt_engine.model_size, new_model)
-                    loop = asyncio.get_event_loop()
-                    if await loop.run_in_executor(None, self.stt_engine.reload, new_model):
-                        changed = True
+                allowed = {"tiny", "base", "small", "medium", "large-v3"}
+                if new_model in allowed and new_model != self.stt_engine.model_size:
+                    # Merken und mitschicken an whisper-bridge (Gamebox).
+                    # Lokales Modell wird NICHT geladen — nur das Fallback braucht's,
+                    # und das passiert erst on-demand wenn Remote nicht antwortet.
+                    logger.info("[rvs] Whisper-Modell → %s (nur Config; Modell laedt Gamebox)",
+                                new_model)
+                    self.stt_engine.model_size = new_model
+                    self.stt_engine.model = None
+                    changed = True
             # Persistent speichern in Shared Volume
             if changed:
                 try:
@@ -1339,22 +1376,117 @@ class ARIABridge:
                         mime_type, duration_ms, len(audio_b64) // 1365)
             asyncio.create_task(self._process_app_audio(audio_b64, mime_type))
 
+        elif msg_type == "stt_response":
+            # Antwort der whisper-bridge auf unseren stt_request
+            request_id = payload.get("requestId", "")
+            future = self._pending_stt.get(request_id)
+            if future is None or future.done():
+                return
+            error = payload.get("error", "")
+            if error:
+                logger.warning("[rvs] stt_response Fehler: %s", error)
+                future.set_result(None)
+            else:
+                text = payload.get("text", "")
+                stt_ms = payload.get("sttMs", 0)
+                model = payload.get("model", "?")
+                logger.info("[rvs] Remote-STT OK (%s, %dms): '%s'", model, stt_ms, (text or "")[:80])
+                future.set_result(text)
+            return
+
         else:
             logger.debug("[rvs] Unbekannter Typ: %s", msg_type)
 
+    # STT-Orchestrierung: zuerst Remote (Gamebox), Fallback lokal.
+    # Timeout grosszuegig gewaehlt, damit auch ein erstmaliger Modell-Load
+    # auf der Gamebox (bis ~30s bei large-v3) durchgeht.
+    _STT_REMOTE_TIMEOUT_S = 45.0
+
     async def _process_app_audio(self, audio_b64: str, mime_type: str) -> None:
-        """Decodiert App-Audio (Base64 AAC/MP4), konvertiert zu 16kHz PCM, STT, sendet an core."""
+        """App-Audio → STT → aria-core. Primaer via whisper-bridge (RVS), Fallback lokal."""
+        # Erst Remote versuchen
+        text = await self._stt_remote(audio_b64, mime_type)
+        if text is None:
+            # Remote hat nicht geantwortet → lokales Whisper
+            logger.warning("[rvs] Remote-STT nicht verfuegbar — Fallback auf lokales Whisper")
+            text = await self._stt_local(audio_b64, mime_type)
+        if text is None:
+            return
+
+        if text.strip():
+            logger.info("[rvs] STT Ergebnis: '%s'", text[:80])
+            # ERST an aria-core senden (wichtigster Schritt)
+            await self.send_to_core(text, source="app-voice")
+            # STT-Text an RVS senden (fuer Anzeige in App + Diagnostic)
+            # sender="stt" damit Bridge es ignoriert (kein Loop)
+            try:
+                await self._send_to_rvs({
+                    "type": "chat",
+                    "payload": {
+                        "text": text,
+                        "sender": "stt",
+                    },
+                    "timestamp": int(asyncio.get_event_loop().time() * 1000),
+                })
+            except Exception as e:
+                logger.warning("[rvs] STT-Text konnte nicht an RVS gesendet werden: %s", e)
+        else:
+            logger.info("[rvs] Keine Sprache erkannt — ignoriert")
+
+    async def _stt_remote(self, audio_b64: str, mime_type: str) -> Optional[str]:
+        """Schickt Audio an die whisper-bridge und wartet auf stt_response.
+
+        Rueckgabe:
+            str  — erkannter Text (kann leer sein)
+            None — Remote-STT nicht erreichbar oder Fehler/Timeout (→ Fallback)
+        """
+        if self.ws_rvs is None:
+            return None
+
+        request_id = str(uuid.uuid4())
+        loop = asyncio.get_event_loop()
+        future: asyncio.Future = loop.create_future()
+        self._pending_stt[request_id] = future
+
+        try:
+            model = getattr(self.stt_engine, "model_size", "small")
+            logger.info("[rvs] stt_request → whisper-bridge (id=%s, model=%s, %dKB)",
+                        request_id[:8], model, len(audio_b64) // 1365)
+            ok = await self._send_to_rvs({
+                "type": "stt_request",
+                "payload": {
+                    "requestId": request_id,
+                    "audio": audio_b64,
+                    "mimeType": mime_type,
+                    "model": model,
+                    "language": getattr(self.stt_engine, "language", "de"),
+                },
+                "timestamp": int(loop.time() * 1000),
+            })
+            if not ok:
+                logger.warning("[rvs] stt_request konnte nicht gesendet werden — skip Remote")
+                return None
+            return await asyncio.wait_for(future, timeout=self._STT_REMOTE_TIMEOUT_S)
+        except asyncio.TimeoutError:
+            logger.warning("[rvs] Remote-STT Timeout (%.0fs)", self._STT_REMOTE_TIMEOUT_S)
+            return None
+        except Exception as e:
+            logger.warning("[rvs] Remote-STT Fehler: %s", e)
+            return None
+        finally:
+            self._pending_stt.pop(request_id, None)
+
+    async def _stt_local(self, audio_b64: str, mime_type: str) -> Optional[str]:
+        """Lokales Whisper-Fallback: FFmpeg → float32 → stt_engine.transcribe."""
         loop = asyncio.get_event_loop()
         tmp_in = None
         tmp_out = None
         try:
-            # Base64 → temp-Datei
             ext = ".mp4" if "mp4" in mime_type else ".wav" if "wav" in mime_type else ".ogg"
             tmp_in = tempfile.NamedTemporaryFile(suffix=ext, delete=False)
             tmp_in.write(base64.b64decode(audio_b64))
             tmp_in.close()
 
-            # FFmpeg: beliebiges Format → 16kHz mono PCM (raw float32)
             tmp_out = tempfile.NamedTemporaryFile(suffix=".raw", delete=False)
             tmp_out.close()
 
@@ -1369,55 +1501,34 @@ class ARIABridge:
             )
             if result.returncode != 0:
                 logger.error("[rvs] FFmpeg Fehler: %s", result.stderr.decode()[:200])
-                return
+                return None
 
-            # PCM lesen → numpy float32
             audio_data = np.fromfile(tmp_out.name, dtype=np.float32)
             if len(audio_data) == 0:
                 logger.warning("[rvs] Leere Audio-Daten nach Konvertierung")
-                return
+                return None
 
             duration_s = len(audio_data) / 16000.0
-            logger.info("[rvs] Audio konvertiert: %.1fs, %d samples", duration_s, len(audio_data))
-
-            # STT
-            text = await loop.run_in_executor(None, self.stt_engine.transcribe, audio_data)
-
-            if text.strip():
-                logger.info("[rvs] STT Ergebnis: '%s'", text[:80])
-                # ERST an aria-core senden (wichtigster Schritt)
-                await self.send_to_core(text, source="app-voice")
-                # STT-Text an RVS senden (fuer Anzeige in App + Diagnostic)
-                # sender="stt" damit Bridge es ignoriert (kein Loop)
-                try:
-                    await self._send_to_rvs({
-                        "type": "chat",
-                        "payload": {
-                            "text": text,
-                            "sender": "stt",
-                        },
-                        "timestamp": int(asyncio.get_event_loop().time() * 1000),
-                    })
-                except Exception as e:
-                    logger.warning("[rvs] STT-Text konnte nicht an RVS gesendet werden: %s", e)
-            else:
-                logger.info("[rvs] Keine Sprache erkannt — ignoriert")
-
+            logger.info("[rvs] Lokal-STT: %.1fs Audio, model=%s", duration_s, self.stt_engine.model_size)
+            return await loop.run_in_executor(None, self.stt_engine.transcribe, audio_data)
         except Exception:
-            logger.exception("[rvs] Audio-Verarbeitung fehlgeschlagen")
+            logger.exception("[rvs] Lokales STT fehlgeschlagen")
+            return None
         finally:
-            # Temp-Dateien aufraeumen
-            for f in [tmp_in, tmp_out]:
+            for f in (tmp_in, tmp_out):
                 if f:
                     try:
                         os.unlink(f.name)
                     except OSError:
                         pass
 
-    async def _send_to_rvs(self, message: dict) -> None:
-        """Sendet eine Nachricht an die App (via RVS) mit Verbindungs-Check."""
+    async def _send_to_rvs(self, message: dict) -> bool:
+        """Sendet eine Nachricht an die App (via RVS) mit Verbindungs-Check.
+
+        Rueckgabe: True wenn erfolgreich gesendet, False wenn Verbindung tot.
+        """
         if self.ws_rvs is None:
-            return
+            return False
 
         # Ping-Check: Verbindung wirklich aktiv?
         try:
@@ -1431,12 +1542,14 @@ class ARIABridge:
                 pass
             self.ws_rvs = None
             # Reconnect wird vom connect_to_rvs Loop uebernommen
-            return
+            return False
 
         try:
             await self.ws_rvs.send(json.dumps(message))
+            return True
         except Exception:
             logger.warning("[rvs] Sendefehler — RVS nicht erreichbar")
+            return False
 
     # ── Log-Streaming an die App ─────────────────────────────
 

diagnostic/index.html

@@ -438,13 +438,14 @@
         </div>
 
         <!-- XTTS Stimme -->
-        <div style="display:flex;align-items:center;gap:12px;margin-bottom:12px;">
+        <div style="display:flex;align-items:center;gap:12px;margin-bottom:6px;">
           <label style="color:#8888AA;font-size:12px;">XTTS Stimme:</label>
           <select id="diag-xtts-voice" onchange="sendVoiceConfig()" style="background:#1E1E2E;color:#fff;border:1px solid #2A2A3E;border-radius:6px;padding:6px 10px;font-size:13px;">
             <option value="">Standard (XTTS Default)</option>
           </select>
           <button class="btn secondary" onclick="loadXTTSVoices()" style="padding:4px 10px;font-size:11px;">Laden</button>
         </div>
+        <div id="voice-status" style="font-size:11px;min-height:14px;margin-bottom:12px;color:#8888AA;"></div>
 
         <!-- Gecloned Stimmen — Liste mit Loeschen -->
         <div id="xtts-voice-list" style="margin-bottom:12px;"></div>
@@ -851,6 +852,25 @@
           return;
         }
 
+        if (msg.type === 'voice_ready') {
+          const v = msg.payload?.voice || '';
+          const err = msg.payload?.error;
+          const ms = msg.payload?.loadMs;
+          const statusEl = document.getElementById('voice-status');
+          if (statusEl) {
+            if (err) {
+              statusEl.textContent = `⚠️ Stimme "${v}" Fehler: ${err}`;
+              statusEl.style.color = '#FF3B30';
+            } else {
+              statusEl.textContent = `✅ Stimme "${v || 'Standard'}" bereit${ms ? ` (${(ms/1000).toFixed(1)}s)` : ''}`;
+              statusEl.style.color = '#34C759';
+            }
+            setTimeout(() => { if (statusEl) statusEl.textContent = ''; }, 5000);
+          }
+          addLog('info', 'xtts', err ? `Voice "${v}": ${err}` : `Voice "${v || 'Standard'}" bereit`);
+          return;
+        }
+
         if (msg.type === 'watchdog') {
           const colors = { warning: '#FFD60A', fixing: '#FF9500', fixed: '#34C759', error: '#FF3B30' };
           const color = colors[msg.status] || '#FFD60A';
@@ -1551,6 +1571,11 @@
       const xttsVoice = document.getElementById('diag-xtts-voice').value;
       const whisperModel = document.getElementById('diag-whisper-model').value;
       send({ action: 'send_voice_config', ttsEnabled, xttsVoice, whisperModel });
+      const statusEl = document.getElementById('voice-status');
+      if (statusEl && xttsVoice) {
+        statusEl.textContent = `⏳ Stimme "${xttsVoice}" wird geladen...`;
+        statusEl.style.color = '#FFD60A';
+      }
     }
 
     // ── Passwort-Feld Anzeigen/Verbergen ─────────────────────

diagnostic/server.js

@@ -626,6 +626,17 @@ function connectRVS(forcePlain) {
         // Mode-Broadcast von der Bridge → an Browser-Clients weiterreichen
         log("info", "rvs", `Mode-Broadcast: ${msg.payload?.mode} (${msg.payload?.name})`);
         broadcast({ type: "mode", payload: msg.payload });
+      } else if (msg.type === "voice_ready") {
+        // XTTS-Bridge meldet Stimme fertig geladen → an Browser durchreichen
+        const v = msg.payload?.voice || "";
+        const err = msg.payload?.error;
+        const ms = msg.payload?.loadMs;
+        if (err) {
+          log("warn", "rvs", `Voice-Ready Fehler fuer "${v}": ${err}`);
+        } else {
+          log("info", "rvs", `Voice "${v || "default"}" geladen${ms ? ` in ${(ms/1000).toFixed(1)}s` : ""}`);
+        }
+        broadcast({ type: "voice_ready", payload: msg.payload });
       } else {
         log("debug", "rvs", `Nachricht: ${JSON.stringify(msg).slice(0, 150)}`);
       }

rvs/server.js

@@ -19,6 +19,8 @@ const ALLOWED_TYPES = new Set([
   "agent_activity", "cancel_request",
   "audio_pcm",
   "xtts_delete_voice",
+  "voice_preload", "voice_ready",
+  "stt_request", "stt_response",
 ]);
 
 // Token-Raum: token -> { clients: Set<ws> }

xtts/Dockerfile

@@ -1,5 +0,0 @@
-FROM node:22-alpine
-WORKDIR /app
-COPY bridge.js package.json ./
-RUN npm install --production
-CMD ["node", "bridge.js"]

xtts/bridge.js

@@ -1,402 +0,0 @@
-/**
- * ARIA XTTS Bridge — Verbindet XTTS v2 Server mit dem RVS
- *
- * Empfaengt tts_request ueber RVS → rendert Audio via XTTS API → sendet zurueck
- * Empfaengt voice_upload → speichert Voice-Sample fuer Cloning
- * Empfaengt xtts_list_voices → listet verfuegbare Stimmen
- */
-
-const WebSocket = require("ws");
-const http = require("http");
-const https = require("https");
-const fs = require("fs");
-const path = require("path");
-
-const XTTS_API_URL = process.env.XTTS_API_URL || "http://xtts:8000";
-const RVS_HOST = process.env.RVS_HOST || "";
-const RVS_PORT = process.env.RVS_PORT || "443";
-const RVS_TLS = process.env.RVS_TLS || "true";
-const RVS_TLS_FALLBACK = process.env.RVS_TLS_FALLBACK || "true";
-const RVS_TOKEN = process.env.RVS_TOKEN || "";
-const VOICES_DIR = "/voices";
-
-function log(msg) {
-  console.log(`[${new Date().toISOString()}] ${msg}`);
-}
-
-// ── RVS Verbindung ──────────────────────────────────
-
-let rvsWs = null;
-let retryDelay = 2;
-
-function connectRVS(forcePlain) {
-  if (!RVS_HOST || !RVS_TOKEN) {
-    log("RVS nicht konfiguriert — beende");
-    process.exit(1);
-  }
-
-  const useTls = RVS_TLS === "true" && !forcePlain;
-  const proto = useTls ? "wss" : "ws";
-  const url = `${proto}://${RVS_HOST}:${RVS_PORT}?token=${RVS_TOKEN}`;
-
-  log(`Verbinde zu RVS: ${proto}://${RVS_HOST}:${RVS_PORT}`);
-
-  const ws = new WebSocket(url);
-
-  ws.on("open", () => {
-    log("RVS verbunden — warte auf TTS-Requests");
-    rvsWs = ws;
-    retryDelay = 2;
-
-    // Keepalive
-    setInterval(() => {
-      if (ws.readyState === WebSocket.OPEN) {
-        ws.ping();
-        ws.send(JSON.stringify({ type: "heartbeat", timestamp: Date.now() }));
-      }
-    }, 25000);
-  });
-
-  ws.on("message", async (raw) => {
-    try {
-      const msg = JSON.parse(raw.toString());
-
-      if (msg.type === "xtts_request") {
-        await handleTTSRequest(msg.payload);
-      } else if (msg.type === "voice_upload") {
-        await handleVoiceUpload(msg.payload);
-      } else if (msg.type === "xtts_list_voices") {
-        await handleListVoices();
-      } else if (msg.type === "xtts_delete_voice") {
-        await handleDeleteVoice(msg.payload);
-      }
-    } catch (err) {
-      log(`Fehler: ${err.message}`);
-    }
-  });
-
-  ws.on("close", () => {
-    log("RVS Verbindung geschlossen");
-    rvsWs = null;
-    setTimeout(() => connectRVS(), Math.min(retryDelay * 1000, 30000));
-    retryDelay = Math.min(retryDelay * 2, 30);
-  });
-
-  ws.on("error", (err) => {
-    log(`RVS Fehler: ${err.message}`);
-    if (useTls && RVS_TLS_FALLBACK === "true") {
-      log("TLS fehlgeschlagen — Fallback auf ws://");
-      ws.removeAllListeners();
-      try { ws.close(); } catch (_) {}
-      connectRVS(true);
-    }
-  });
-}
-
-// ── TTS Request Handler ─────────────────────────────
-
-// ── TTS-Queue ──────────────────────────────────────
-// XTTS verarbeitet Requests sequenziell, damit Streams sich nicht ueberlappen.
-// Ohne Queue wuerden parallele Requests parallel streamen → App bekommt
-// interleaved PCM-Chunks aus zwei Rendern → klingt wie Chaos.
-let ttsQueue = Promise.resolve();
-
-function handleTTSRequest(payload) {
-  ttsQueue = ttsQueue.then(() => _runTTSRequest(payload)).catch(err => {
-    log(`TTS-Queue Fehler: ${err.message}`);
-  });
-  return ttsQueue;
-}
-
-async function _runTTSRequest(payload) {
-  const { text, voice, requestId, language, messageId } = payload;
-  if (!text) return;
-
-  // Markdown-Cleanup (Bridge macht jetzt auch Cleanup, aber safety net)
-  let cleanText = text
-    .replace(/\*\*([^*]+)\*\*/g, "$1")
-    .replace(/\*([^*]+)\*/g, "$1")
-    .replace(/`([^`]+)`/g, "$1")
-    .replace(/```[\s\S]*?```/g, "")
-    .replace(/\[([^\]]+)\]\([^)]+\)/g, "$1")
-    .replace(/#{1,6}\s*/g, "")
-    .replace(/>\s*/g, "")
-    .replace(/[-*]\s+/g, "")
-    .replace(/\n{2,}/g, ". ")
-    .replace(/\n/g, ", ")
-    .replace(/\s{2,}/g, " ")
-    .replace(/["""„]/g, "")
-    .replace(/\(\)/g, "")
-    .trim();
-
-  log(`TTS-Request (streaming): "${cleanText.slice(0, 80)}..." (${cleanText.length} chars, voice: ${voice || "default"})`);
-
-  try {
-    const voiceSample = voice ? path.join(VOICES_DIR, `${voice}.wav`) : null;
-    const hasCustomVoice = voiceSample && fs.existsSync(voiceSample);
-
-    let chunkIndex = 0;
-    let pcmMeta = null;
-
-    // EIN Request fuer den GANZEN Text — kein Gap zwischen Saetzen.
-    // XTTS rendert und wir streamen PCM sobald es reinkommt.
-    await streamXTTSAsPCM(
-      cleanText,
-      language || "de",
-      hasCustomVoice ? voiceSample : null,
-      (pcmBase64, meta) => {
-        if (!pcmMeta) pcmMeta = meta;
-        sendToRVS({
-          type: "audio_pcm",
-          payload: {
-            requestId: requestId || "",
-            messageId: messageId || "",
-            base64: pcmBase64,
-            format: "pcm_s16le",
-            sampleRate: meta.sampleRate,
-            channels: meta.channels,
-            voice: voice || "default",
-            chunk: chunkIndex++,
-            final: false,
-          },
-          timestamp: Date.now(),
-        });
-      },
-    );
-
-    // Am Ende: final-Flag damit App weiss "fertig" und Cache geschrieben werden kann
-    if (pcmMeta) {
-      sendToRVS({
-        type: "audio_pcm",
-        payload: {
-          requestId: requestId || "",
-          messageId: messageId || "",
-          base64: "",
-          format: "pcm_s16le",
-          sampleRate: pcmMeta.sampleRate,
-          channels: pcmMeta.channels,
-          voice: voice || "default",
-          chunk: chunkIndex++,
-          final: true,
-        },
-        timestamp: Date.now(),
-      });
-    }
-
-    log(`TTS komplett: ${chunkIndex} PCM-Frames gestreamt (${cleanText.length} chars)`);
-  } catch (err) {
-    log(`TTS Fehler: ${err.message}`);
-    sendToRVS({
-      type: "xtts_response",
-      payload: { requestId, error: err.message },
-      timestamp: Date.now(),
-    });
-  }
-}
-
-/**
- * Ruft /tts_to_audio/ auf und streamt das resultierende WAV bereits waehrend
- * des Empfangs in PCM-Frames an den Callback. Der WAV-Header wird einmal
- * geparst, danach werden nur noch raw PCM-Samples weitergeleitet.
- *
- * Warum nicht echtes /tts_stream/? daswer123 hat den Endpoint, aber die
- * Audio-Quality ist dort niedriger und er produziert beim ersten Chunk
- * oft Artefakte. Pragmatischer Weg: /tts_to_audio/ + Response-Stream
- * chunkweise auslesen. Das ist zwar kein echtes Server-Streaming, aber
- * gibt uns deutlich kleinere Netzwerk-Haeppchen und die App kann via
- * AudioTrack MODE_STREAM sofort nahtlos abspielen.
- */
-function streamXTTSAsPCM(text, language, speakerWav, onPcmChunk) {
-  return new Promise((resolve, reject) => {
-    const body = JSON.stringify({
-      text,
-      language,
-      speaker_wav: speakerWav || "",
-    });
-
-    const url = new URL(`${XTTS_API_URL}/tts_to_audio/`);
-    const options = {
-      hostname: url.hostname,
-      port: url.port,
-      path: url.pathname,
-      method: "POST",
-      headers: {
-        "Content-Type": "application/json",
-        "Content-Length": Buffer.byteLength(body),
-      },
-      timeout: 60000,
-    };
-
-    const req = http.request(options, (res) => {
-      if (res.statusCode !== 200) {
-        let body = "";
-        res.on("data", (d) => { body += d.toString(); });
-        res.on("end", () => reject(new Error(`XTTS HTTP ${res.statusCode}: ${body.slice(0, 200)}`)));
-        return;
-      }
-
-      let headerParsed = false;
-      let sampleRate = 24000;
-      let channels = 1;
-      let leftover = Buffer.alloc(0); // ungerade Byte-Reste fuer das naechste Chunk
-      const HEADER_BYTES = 44;
-      let headerBuf = Buffer.alloc(0);
-      const PCM_CHUNK_BYTES = 8192; // ~170ms bei 24kHz s16 mono
-
-      res.on("data", (chunk) => {
-        let data = chunk;
-
-        // WAV-Header konsumieren (44 Bytes)
-        if (!headerParsed) {
-          headerBuf = Buffer.concat([headerBuf, data]);
-          if (headerBuf.length < HEADER_BYTES) return;
-          // Header lesen
-          const header = headerBuf.slice(0, HEADER_BYTES);
-          try {
-            channels = header.readUInt16LE(22);
-            sampleRate = header.readUInt32LE(24);
-          } catch (_) {}
-          headerParsed = true;
-          data = headerBuf.slice(HEADER_BYTES);
-        }
-
-        // leftover aus vorherigem Chunk + neuer data
-        let combined = Buffer.concat([leftover, data]);
-
-        // In PCM_CHUNK_BYTES-Happen zerlegen (Vielfache von 2 damit keine Sample-Splits)
-        while (combined.length >= PCM_CHUNK_BYTES) {
-          const slice = combined.slice(0, PCM_CHUNK_BYTES);
-          combined = combined.slice(PCM_CHUNK_BYTES);
-          onPcmChunk(slice.toString("base64"), { sampleRate, channels });
-        }
-        leftover = combined;
-      });
-
-      res.on("end", () => {
-        // Rest-Daten senden
-        if (leftover.length > 0) {
-          onPcmChunk(leftover.toString("base64"), { sampleRate, channels });
-        }
-        resolve();
-      });
-
-      res.on("error", reject);
-    });
-
-    req.on("error", reject);
-    req.on("timeout", () => { req.destroy(); reject(new Error("XTTS API Timeout (60s)")); });
-    req.write(body);
-    req.end();
-  });
-}
-
-// ── Voice Upload Handler ────────────────────────────
-
-async function handleVoiceUpload(payload) {
-  const { name, samples } = payload;
-  if (!name || !samples || !Array.isArray(samples) || samples.length === 0) {
-    log("Voice Upload: Ungueltige Daten");
-    return;
-  }
-
-  log(`Voice Upload: "${name}" (${samples.length} Samples)`);
-
-  try {
-    // Alle Samples zusammenfuegen
-    const buffers = samples.map(s => Buffer.from(s.base64, "base64"));
-    const combined = Buffer.concat(buffers);
-
-    // Als WAV speichern
-    fs.mkdirSync(VOICES_DIR, { recursive: true });
-    const filePath = path.join(VOICES_DIR, `${name.replace(/[^a-zA-Z0-9_-]/g, "_")}.wav`);
-    fs.writeFileSync(filePath, combined);
-
-    log(`Voice gespeichert: ${filePath} (${(combined.length / 1024).toFixed(0)}KB)`);
-
-    sendToRVS({
-      type: "xtts_voice_saved",
-      payload: { name, size: combined.length, path: filePath },
-      timestamp: Date.now(),
-    });
-  } catch (err) {
-    log(`Voice Upload Fehler: ${err.message}`);
-  }
-}
-
-// ── Voice Delete Handler ────────────────────────────
-
-async function handleDeleteVoice(payload) {
-  const { name } = payload || {};
-  if (!name || typeof name !== "string") {
-    log("Voice Delete: ungueltiger Name");
-    return;
-  }
-  const safe = name.replace(/[^a-zA-Z0-9_-]/g, "_");
-  const filePath = path.join(VOICES_DIR, `${safe}.wav`);
-  try {
-    if (fs.existsSync(filePath)) {
-      fs.unlinkSync(filePath);
-      log(`Voice geloescht: ${filePath}`);
-    } else {
-      log(`Voice Delete: Datei existiert nicht (${filePath})`);
-    }
-    // Aktualisierte Liste an alle Clients senden
-    await handleListVoices();
-  } catch (err) {
-    log(`Voice Delete Fehler: ${err.message}`);
-  }
-}
-
-// ── Voice List Handler ──────────────────────────────
-
-async function handleListVoices() {
-  try {
-    const files = fs.existsSync(VOICES_DIR)
-      ? fs.readdirSync(VOICES_DIR).filter(f => f.endsWith(".wav"))
-      : [];
-
-    const voices = files.map(f => ({
-      name: path.basename(f, ".wav"),
-      file: f,
-      size: fs.statSync(path.join(VOICES_DIR, f)).size,
-    }));
-
-    log(`Stimmen: ${voices.length} verfuegbar`);
-
-    sendToRVS({
-      type: "xtts_voices_list",
-      payload: { voices },
-      timestamp: Date.now(),
-    });
-  } catch (err) {
-    log(`Stimmen-Liste Fehler: ${err.message}`);
-  }
-}
-
-// ── RVS senden ──────────────────────────────────────
-
-function sendToRVS(msg) {
-  if (rvsWs && rvsWs.readyState === WebSocket.OPEN) {
-    rvsWs.send(JSON.stringify(msg));
-  }
-}
-
-// ── Start ───────────────────────────────────────────
-
-log("ARIA XTTS Bridge startet...");
-log(`XTTS API: ${XTTS_API_URL}`);
-log(`RVS: ${RVS_HOST}:${RVS_PORT}`);
-
-// Warten bis XTTS API erreichbar ist
-function waitForXTTS(callback, attempts) {
-  if (attempts <= 0) { log("XTTS API nicht erreichbar — starte trotzdem"); callback(); return; }
-  http.get(`${XTTS_API_URL}/docs`, (res) => {
-    log(`XTTS API erreichbar (HTTP ${res.statusCode})`);
-    callback();
-  }).on("error", () => {
-    log(`XTTS API noch nicht bereit — warte (${attempts} Versuche uebrig)...`);
-    setTimeout(() => waitForXTTS(callback, attempts - 1), 10000); // 10s statt 5s (Model laden dauert)
-  });
-}
-
-waitForXTTS(() => connectRVS(), 30); // Max 5min warten

xtts/docker-compose.yml

@@ -1,7 +1,7 @@
 # ════════════════════════════════════════════════
-#  ARIA XTTS v2 — GPU TTS Server
+#  ARIA Gamebox Stack — GPU F5-TTS + Whisper STT
 #  Laeuft auf dem Gaming-PC (RTX 3060)
-#  Verbindet sich zum RVS fuer TTS-Requests
+#  Verbindet sich zum RVS fuer TTS/STT-Requests
 # ════════════════════════════════════════════════
 #
 #  Voraussetzungen:
@@ -10,15 +10,18 @@
 #    - .env mit RVS-Verbindungsdaten
 #
 #  Start: docker compose up -d
-#  Test:  curl http://localhost:8000/docs
 # ════════════════════════════════════════════════
 
 services:
 
-  # ─── XTTS v2 API Server (GPU) ─────────────────
-  xtts:
-    image: daswer123/xtts-api-server:latest
-    container_name: aria-xtts
+  # ─── F5-TTS Bridge (GPU) ──────────────────────
+  # Ersetzt den frueheren XTTS-Stack. Empfaengt xtts_request via RVS,
+  # rendert via F5-TTS mit Voice-Cloning, streamt PCM an die App.
+  # Voice-Upload: speichert WAV und laesst whisper-bridge den Referenz-
+  # text transkribieren — der User muss nichts eintippen.
+  f5tts-bridge:
+    build: ./f5tts
+    container_name: aria-f5tts-bridge
     deploy:
       resources:
         reservations:
@@ -26,31 +29,53 @@ services:
             - driver: nvidia
               count: 1
               capabilities: [gpu]
-    ports:
-      - "8000:8020"
     volumes:
-      - xtts-models:/app/xtts_models             # Model-Cache (~2GB)
-      - ./voices:/voices                        # Custom Voice Samples
+      - ./voices:/voices                         # WAV + TXT Referenz
+      - f5tts-models:/root/.cache/huggingface    # Model-Cache persistieren
     environment:
-      - COQUI_TOS_AGREED=1
-    restart: unless-stopped
-
-  # ─── XTTS Bridge (verbindet zu RVS) ───────────
-  xtts-bridge:
-    build: .
-    container_name: aria-xtts-bridge
-    depends_on:
-      - xtts
-    volumes:
-      - ./voices:/voices                        # Shared mit XTTS-Server
-    environment:
-      - XTTS_API_URL=http://xtts:8020
       - RVS_HOST=${RVS_HOST}
       - RVS_PORT=${RVS_PORT:-443}
       - RVS_TLS=${RVS_TLS:-true}
       - RVS_TLS_FALLBACK=${RVS_TLS_FALLBACK:-true}
       - RVS_TOKEN=${RVS_TOKEN}
+      - F5TTS_MODEL=${F5TTS_MODEL:-F5TTS_v1_Base}
+      - F5TTS_DEVICE=${F5TTS_DEVICE:-cuda}
+      - VOICES_DIR=/voices
+    restart: unless-stopped
+
+  # ─── Whisper STT (GPU) ────────────────────────
+  # Faster-Whisper auf der Gamebox statt auf der VM (CPU) —
+  # deutlich schneller. Verbindet sich selbst per WebSocket an
+  # den RVS und nimmt dort stt_request Nachrichten der aria-bridge
+  # entgegen, antwortet mit stt_response. Zusaetzlich nutzt die
+  # f5tts-bridge Whisper intern fuer die Referenz-Transkription bei
+  # Voice-Uploads. Laedt das Modell beim Start vor; auf Config-
+  # Broadcasts (Diagnostic → whisperModel) wird zur Laufzeit hot-
+  # swapped.
+  whisper-bridge:
+    build: ./whisper
+    container_name: aria-whisper-bridge
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    environment:
+      - RVS_HOST=${RVS_HOST}
+      - RVS_PORT=${RVS_PORT:-443}
+      - RVS_TLS=${RVS_TLS:-true}
+      - RVS_TLS_FALLBACK=${RVS_TLS_FALLBACK:-true}
+      - RVS_TOKEN=${RVS_TOKEN}
+      - WHISPER_MODEL=${WHISPER_MODEL:-small}
+      - WHISPER_DEVICE=${WHISPER_DEVICE:-cuda}
+      - WHISPER_COMPUTE_TYPE=${WHISPER_COMPUTE_TYPE:-float16}
+      - WHISPER_LANGUAGE=${WHISPER_LANGUAGE:-de}
+    volumes:
+      - whisper-models:/root/.cache/huggingface
     restart: unless-stopped
 
 volumes:
-  xtts-models:
+  f5tts-models:
+  whisper-models:

xtts/f5tts/Dockerfile

@@ -0,0 +1,21 @@
+FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04
+
+ENV DEBIAN_FRONTEND=noninteractive
+ENV PYTHONUNBUFFERED=1
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3 python3-pip ffmpeg git \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+# PyTorch CUDA-Wheels zuerst (f5-tts zieht sonst CPU-only Torch rein)
+RUN pip3 install --no-cache-dir torch==2.3.1 torchaudio==2.3.1 \
+    --index-url https://download.pytorch.org/whl/cu121
+
+COPY requirements.txt .
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+COPY bridge.py .
+
+CMD ["python3", "bridge.py"]

xtts/f5tts/bridge.py

@@ -0,0 +1,580 @@
+#!/usr/bin/env python3
+"""
+ARIA F5-TTS Bridge — laeuft auf der Gamebox (RTX 3060).
+
+Empfaengt xtts_request via RVS → F5-TTS Voice Cloning auf GPU → streamt
+16-bit PCM Chunks als audio_pcm Nachrichten zurueck an die App.
+
+Voice-Layout im VOICES_DIR:
+  {name}.wav   — Referenz-Audio (6-10s, 24kHz mono empfohlen)
+  {name}.txt   — Referenz-Text (UTF-8, was im WAV gesprochen wird)
+
+Beim voice_upload senden wir intern einen stt_request an die whisper-bridge
+und legen die Transkription als .txt ab — der User muss keinen Text eingeben.
+
+Env:
+  RVS_HOST, RVS_PORT, RVS_TLS, RVS_TLS_FALLBACK, RVS_TOKEN
+  F5TTS_MODEL   Default: F5TTS_v1_Base
+  F5TTS_DEVICE  Default: cuda
+  VOICES_DIR    Default: /voices
+"""
+import asyncio
+import base64
+import json
+import logging
+import os
+import re
+import subprocess
+import sys
+import tempfile
+import time
+import uuid
+from pathlib import Path
+from typing import Optional
+
+import numpy as np
+import soundfile as sf
+import websockets
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger("f5tts-bridge")
+# HuggingFace + Torch download-Logs etwas daempfen
+logging.getLogger("httpx").setLevel(logging.WARNING)
+logging.getLogger("urllib3").setLevel(logging.WARNING)
+
+RVS_HOST = os.getenv("RVS_HOST", "").strip()
+RVS_PORT = int(os.getenv("RVS_PORT", "443"))
+RVS_TLS = os.getenv("RVS_TLS", "true").lower() == "true"
+RVS_TLS_FALLBACK = os.getenv("RVS_TLS_FALLBACK", "true").lower() == "true"
+RVS_TOKEN = os.getenv("RVS_TOKEN", "").strip()
+
+F5TTS_MODEL = os.getenv("F5TTS_MODEL", "F5TTS_v1_Base")
+F5TTS_DEVICE = os.getenv("F5TTS_DEVICE", "cuda")
+VOICES_DIR = Path(os.getenv("VOICES_DIR", "/voices"))
+
+PCM_CHUNK_BYTES = 8192   # ~170ms @ 24kHz mono s16
+TARGET_SR = 24000        # F5-TTS native
+
+# ── Lazy F5-TTS Loader ──────────────────────────────────────
+
+_F5TTS_cls = None
+
+
+def _get_f5tts_cls():
+    """Lazy import damit Startup-Logs nicht durch Torch-Warnungen zumuellen."""
+    global _F5TTS_cls
+    if _F5TTS_cls is None:
+        from f5_tts.api import F5TTS as _cls
+        _F5TTS_cls = _cls
+    return _F5TTS_cls
+
+
+class F5Runner:
+    """Haelt das F5-TTS-Modell. Synthese laeuft im Executor (blocking)."""
+
+    def __init__(self) -> None:
+        self.model = None
+        self._lock = asyncio.Lock()
+
+    def _load_blocking(self) -> None:
+        cls = _get_f5tts_cls()
+        logger.info("Lade F5-TTS '%s' (device=%s)...", F5TTS_MODEL, F5TTS_DEVICE)
+        t0 = time.time()
+        self.model = cls(model=F5TTS_MODEL, device=F5TTS_DEVICE)
+        logger.info("F5-TTS geladen in %.1fs", time.time() - t0)
+
+    async def ensure_loaded(self) -> None:
+        async with self._lock:
+            if self.model is not None:
+                return
+            loop = asyncio.get_event_loop()
+            await loop.run_in_executor(None, self._load_blocking)
+
+    def _infer_blocking(self, gen_text: str, ref_wav: str, ref_text: str) -> tuple[np.ndarray, int]:
+        wav, sr, _ = self.model.infer(
+            ref_file=ref_wav,
+            ref_text=ref_text,
+            gen_text=gen_text,
+            remove_silence=True,
+            seed=-1,
+        )
+        # F5-TTS gibt float32 1D-Array — auf 24kHz sample-rate standard
+        if not isinstance(wav, np.ndarray):
+            wav = np.asarray(wav, dtype=np.float32)
+        if wav.ndim > 1:
+            wav = wav.squeeze()
+        return wav.astype(np.float32), int(sr)
+
+    async def synthesize(self, gen_text: str, ref_wav: str, ref_text: str) -> tuple[np.ndarray, int]:
+        await self.ensure_loaded()
+        loop = asyncio.get_event_loop()
+        return await loop.run_in_executor(None, self._infer_blocking, gen_text, ref_wav, ref_text)
+
+
+# ── Helpers ─────────────────────────────────────────────────
+
+_SENTENCE_SPLIT = re.compile(r"(?<=[.!?])\s+|\n+")
+
+
+def split_sentences(text: str, max_len: int = 350) -> list[str]:
+    """Teilt langen Text an Satzgrenzen. Kurze Texte bleiben als-is."""
+    text = text.strip()
+    if not text:
+        return []
+    if len(text) <= max_len:
+        return [text]
+    parts = [p.strip() for p in _SENTENCE_SPLIT.split(text) if p.strip()]
+    # Zu kurze Fragmente mergen damit F5-TTS nicht an jedem Komma neu startet
+    merged: list[str] = []
+    buf = ""
+    for p in parts:
+        if len(buf) + len(p) + 1 <= max_len:
+            buf = f"{buf} {p}".strip()
+        else:
+            if buf:
+                merged.append(buf)
+            buf = p
+    if buf:
+        merged.append(buf)
+    return merged or [text]
+
+
+def float_to_pcm16(wav: np.ndarray) -> bytes:
+    """Float32 (-1..+1) → int16 little-endian bytes."""
+    wav = np.clip(wav, -1.0, 1.0)
+    pcm = (wav * 32767.0).astype(np.int16)
+    return pcm.tobytes()
+
+
+def sanitize_voice_name(name: str) -> str:
+    return re.sub(r"[^a-zA-Z0-9_-]", "_", name)
+
+
+def voice_paths(name: str) -> tuple[Path, Path]:
+    safe = sanitize_voice_name(name)
+    return VOICES_DIR / f"{safe}.wav", VOICES_DIR / f"{safe}.txt"
+
+
+def ensure_24k_mono_wav(src_wav: Path) -> Path:
+    """F5-TTS moechte 24kHz mono als Referenz — ffmpeg konvertiert inplace.
+
+    Wenn das File schon passt, wird nichts geaendert. Sonst wird es
+    reingeschrieben (Original wird ueberschrieben).
+    """
+    try:
+        info = sf.info(str(src_wav))
+        if info.samplerate == TARGET_SR and info.channels == 1:
+            return src_wav
+    except Exception:
+        pass
+    tmp_out = src_wav.with_suffix(".conv.wav")
+    cmd = ["ffmpeg", "-y", "-i", str(src_wav),
+           "-ar", str(TARGET_SR), "-ac", "1", "-f", "wav", str(tmp_out)]
+    r = subprocess.run(cmd, capture_output=True, timeout=30)
+    if r.returncode != 0:
+        logger.warning("ffmpeg-Konvertierung von %s fehlgeschlagen: %s",
+                       src_wav, r.stderr.decode(errors="replace")[:200])
+        try:
+            tmp_out.unlink()
+        except OSError:
+            pass
+        return src_wav
+    os.replace(tmp_out, src_wav)
+    return src_wav
+
+
+async def _send(ws, mtype: str, payload: dict) -> None:
+    try:
+        await ws.send(json.dumps({
+            "type": mtype,
+            "payload": payload,
+            "timestamp": int(time.time() * 1000),
+        }))
+    except Exception as e:
+        logger.warning("Send fehlgeschlagen (%s): %s", mtype, e)
+
+
+# ── Interne Transkription via whisper-bridge ────────────────
+
+_pending_stt: dict[str, asyncio.Future] = {}
+_STT_TIMEOUT_S = 60.0
+
+
+async def request_transcription(ws, wav_path: Path, language: str = "de") -> Optional[str]:
+    """Sendet einen stt_request an die whisper-bridge (ueber RVS) und wartet auf stt_response."""
+    try:
+        with open(wav_path, "rb") as f:
+            audio_b64 = base64.b64encode(f.read()).decode("ascii")
+    except Exception as e:
+        logger.error("Lesen %s fehlgeschlagen: %s", wav_path, e)
+        return None
+
+    request_id = str(uuid.uuid4())
+    loop = asyncio.get_event_loop()
+    fut: asyncio.Future = loop.create_future()
+    _pending_stt[request_id] = fut
+
+    try:
+        await _send(ws, "stt_request", {
+            "requestId": request_id,
+            "audio": audio_b64,
+            "mimeType": "audio/wav",
+            "model": "small",  # klein reicht fuer Voice-Referenz
+            "language": language,
+        })
+        return await asyncio.wait_for(fut, timeout=_STT_TIMEOUT_S)
+    except asyncio.TimeoutError:
+        logger.warning("Transkription Timeout fuer %s", wav_path.name)
+        return None
+    except Exception as e:
+        logger.warning("Transkription Fehler: %s", e)
+        return None
+    finally:
+        _pending_stt.pop(request_id, None)
+
+
+# ── TTS-Request Handler ─────────────────────────────────────
+
+# Queue damit sich parallele Requests nicht ueberlappen (GPU-Throughput)
+_tts_queue: asyncio.Queue[tuple] = asyncio.Queue()
+
+
+async def _tts_worker(ws, runner: F5Runner) -> None:
+    """Serialisiert Synthesen — GPU kann sonst OOM gehen."""
+    while True:
+        text, voice, request_id, message_id, language = await _tts_queue.get()
+        try:
+            await _do_tts(ws, runner, text, voice, request_id, message_id, language)
+        except Exception:
+            logger.exception("TTS-Worker Fehler")
+        finally:
+            _tts_queue.task_done()
+
+
+async def _do_tts(ws, runner: F5Runner, text: str, voice: str,
+                  request_id: str, message_id: str, language: str) -> None:
+    t0 = time.time()
+    ref_wav_path, ref_txt_path = voice_paths(voice) if voice else (None, None)
+    has_custom = bool(voice and ref_wav_path and ref_wav_path.exists() and ref_txt_path.exists())
+    if voice and not has_custom:
+        # Wenn nur WAV da ist aber kein txt → on-the-fly transkribieren
+        if ref_wav_path and ref_wav_path.exists() and (not ref_txt_path or not ref_txt_path.exists()):
+            logger.info("Voice '%s' hat kein txt — transkribiere on-the-fly", voice)
+            text_ref = await request_transcription(ws, ref_wav_path, language)
+            if text_ref:
+                try:
+                    ref_txt_path.write_text(text_ref.strip(), encoding="utf-8")
+                    has_custom = True
+                    logger.info("Referenz-Text nachgezogen: '%s'", text_ref[:60])
+                except Exception as e:
+                    logger.warning("Referenz-Text speichern fehlgeschlagen: %s", e)
+        if not has_custom:
+            logger.warning("Voice '%s' nicht komplett (%s, txt=%s) — nehme Default",
+                           voice, ref_wav_path, (ref_txt_path and ref_txt_path.exists()))
+
+    if has_custom:
+        ref_wav_str = str(ref_wav_path)
+        ref_text = ref_txt_path.read_text(encoding="utf-8").strip()
+    else:
+        # Fallback: kein Custom-Voice. F5-TTS braucht IMMER eine Referenz,
+        # wir nehmen default_ref.wav/txt falls vorhanden, sonst die erste
+        # gefundene Voice im Ordner.
+        default_wav = VOICES_DIR / "default_ref.wav"
+        default_txt = VOICES_DIR / "default_ref.txt"
+        if default_wav.exists() and default_txt.exists():
+            ref_wav_str = str(default_wav)
+            ref_text = default_txt.read_text(encoding="utf-8").strip()
+        else:
+            # Nimm irgendein vorhandenes voice-Paar
+            pair = next(
+                ((w, t) for w, t in (
+                    (v, v.with_suffix(".txt")) for v in VOICES_DIR.glob("*.wav")
+                ) if t.exists()),
+                None,
+            )
+            if not pair:
+                logger.error("Keine Referenz-Stimme im VOICES_DIR — TTS abgebrochen")
+                return
+            ref_wav_str, ref_text = str(pair[0]), pair[1].read_text(encoding="utf-8").strip()
+
+    sentences = split_sentences(text)
+    logger.info("F5-TTS: %d Satz(e), voice=%s (%s)", len(sentences), voice or "default", ref_wav_str)
+
+    chunk_index = 0
+    pcm_sr = TARGET_SR
+    for i, sent in enumerate(sentences):
+        try:
+            wav, sr = await runner.synthesize(sent, ref_wav_str, ref_text)
+            pcm_sr = sr
+            pcm_bytes = float_to_pcm16(wav)
+            # Erste PCM-Chunk des allerersten Satzes bekommt Fade-In (maskiert
+            # eventuelle Warmup-Glitches). Alle anderen Chunks bleiben wie sind.
+            if i == 0 and chunk_index == 0:
+                pcm_bytes = _fade_in_pcm16(pcm_bytes, sr, 120)
+
+            # Stueckeln
+            for off in range(0, len(pcm_bytes), PCM_CHUNK_BYTES):
+                slice_ = pcm_bytes[off:off + PCM_CHUNK_BYTES]
+                await _send(ws, "audio_pcm", {
+                    "requestId": request_id,
+                    "messageId": message_id,
+                    "base64": base64.b64encode(slice_).decode("ascii"),
+                    "format": "pcm_s16le",
+                    "sampleRate": sr,
+                    "channels": 1,
+                    "voice": voice or "default",
+                    "chunk": chunk_index,
+                    "final": False,
+                })
+                chunk_index += 1
+        except Exception as e:
+            logger.exception("F5-TTS Synthese-Fehler (Satz %d)", i)
+            await _send(ws, "xtts_response", {
+                "requestId": request_id,
+                "error": str(e)[:200],
+            })
+            return
+
+    # Final-Marker
+    await _send(ws, "audio_pcm", {
+        "requestId": request_id,
+        "messageId": message_id,
+        "base64": "",
+        "format": "pcm_s16le",
+        "sampleRate": pcm_sr,
+        "channels": 1,
+        "voice": voice or "default",
+        "chunk": chunk_index,
+        "final": True,
+    })
+
+    logger.info("TTS komplett: %d Chunks, %.2fs render (voice=%s, text=%d chars)",
+                chunk_index, time.time() - t0, voice or "default", len(text))
+
+
+def _fade_in_pcm16(pcm: bytes, sr: int, fade_ms: int) -> bytes:
+    """Linear Fade-In auf erste fade_ms — maskiert Warmup-Glitches."""
+    arr = np.frombuffer(pcm, dtype=np.int16).copy()
+    fade_samples = min(int((fade_ms / 1000.0) * sr), len(arr))
+    if fade_samples <= 0:
+        return pcm
+    ramp = np.linspace(0.0, 1.0, fade_samples, dtype=np.float32)
+    arr[:fade_samples] = (arr[:fade_samples].astype(np.float32) * ramp).astype(np.int16)
+    return arr.tobytes()
+
+
+# ── Voice Management Handlers ───────────────────────────────
+
+async def handle_voice_upload(ws, payload: dict) -> None:
+    name = (payload.get("name") or "").strip()
+    samples = payload.get("samples") or []
+    if not name or not samples:
+        logger.warning("voice_upload: ungueltig (name=%r, samples=%d)", name, len(samples))
+        return
+    logger.info("Voice-Upload: '%s' (%d Samples)", name, len(samples))
+
+    try:
+        VOICES_DIR.mkdir(parents=True, exist_ok=True)
+        safe = sanitize_voice_name(name)
+        wav_path = VOICES_DIR / f"{safe}.wav"
+        txt_path = VOICES_DIR / f"{safe}.txt"
+
+        # Samples zusammenfuegen
+        buffers = [base64.b64decode(s.get("base64", "")) for s in samples]
+        with open(wav_path, "wb") as f:
+            for b in buffers:
+                f.write(b)
+        size_kb = wav_path.stat().st_size / 1024
+        logger.info("Voice WAV gespeichert: %s (%.0fKB)", wav_path, size_kb)
+
+        # Auf 24kHz mono normalisieren (falls App in anderem Format liefert)
+        ensure_24k_mono_wav(wav_path)
+
+        # Transkription ueber whisper-bridge anfragen
+        logger.info("Transkribiere '%s' via whisper-bridge...", name)
+        text = await request_transcription(ws, wav_path, language="de")
+        if not text:
+            logger.warning("Transkription fehlgeschlagen — speichere Platzhalter-Text")
+            text = "Das ist ein Referenz Audio."
+        txt_path.write_text(text.strip(), encoding="utf-8")
+        logger.info("Voice '%s' komplett (txt: %s)", name, text[:80])
+
+        await _send(ws, "xtts_voice_saved", {
+            "name": name, "size": int(size_kb * 1024), "refText": text.strip(),
+        })
+        # Liste aktualisieren
+        await handle_list_voices(ws)
+    except Exception as e:
+        logger.exception("voice_upload Fehler")
+        await _send(ws, "xtts_voice_saved", {"name": name, "error": str(e)[:200]})
+
+
+async def handle_list_voices(ws) -> None:
+    try:
+        voices = []
+        if VOICES_DIR.exists():
+            for wav in sorted(VOICES_DIR.glob("*.wav")):
+                txt = wav.with_suffix(".txt")
+                voices.append({
+                    "name": wav.stem,
+                    "file": wav.name,
+                    "size": wav.stat().st_size,
+                    "hasRefText": txt.exists(),
+                })
+        logger.info("Stimmen-Liste: %d", len(voices))
+        await _send(ws, "xtts_voices_list", {"voices": voices})
+    except Exception:
+        logger.exception("handle_list_voices Fehler")
+
+
+async def handle_delete_voice(ws, payload: dict) -> None:
+    name = (payload.get("name") or "").strip()
+    if not name:
+        return
+    try:
+        wav, txt = voice_paths(name)
+        for p in (wav, txt):
+            if p.exists():
+                p.unlink()
+                logger.info("Voice geloescht: %s", p)
+        await handle_list_voices(ws)
+    except Exception:
+        logger.exception("handle_delete_voice Fehler")
+
+
+# Letzte diagnostisch-gesetzte Voice (verhindert Endlos-Preload bei jedem config)
+_last_diag_voice = ""
+
+
+async def handle_voice_preload(ws, payload: dict, runner: F5Runner) -> None:
+    voice = (payload.get("voice") or "").strip()
+    request_id = payload.get("requestId", "")
+    logger.info("Voice-Preload angefordert: '%s'", voice or "default")
+
+    try:
+        ref_wav, ref_txt = voice_paths(voice) if voice else (None, None)
+        if voice and (not ref_wav or not ref_wav.exists()):
+            await _send(ws, "voice_ready", {"voice": voice, "requestId": request_id, "error": "voice-file-not-found"})
+            return
+
+        # Ref-Text sicherstellen (falls nur WAV da ist)
+        if voice and ref_txt and not ref_txt.exists():
+            text = await request_transcription(ws, ref_wav, language="de")
+            if text:
+                ref_txt.write_text(text.strip(), encoding="utf-8")
+                logger.info("Referenz-Text beim Preload nachgezogen")
+
+        # Dummy-Render zum Warmup
+        t0 = time.time()
+        await _do_tts(ws, runner, "ja.", voice, f"preload-{request_id}", "", "de")
+        ms = int((time.time() - t0) * 1000)
+        await _send(ws, "voice_ready", {"voice": voice, "requestId": request_id, "loadMs": ms})
+    except Exception as e:
+        logger.exception("Voice-Preload Fehler")
+        await _send(ws, "voice_ready", {"voice": voice, "requestId": request_id, "error": str(e)[:200]})
+
+
+# ── Haupt-Loop ──────────────────────────────────────────────
+
+async def run_loop(runner: F5Runner) -> None:
+    # Preload im Hintergrund starten damit der Startup nicht blockiert
+    asyncio.create_task(runner.ensure_loaded())
+
+    use_tls = RVS_TLS
+    retry_s = 2
+    tls_fallback_tried = False
+    global _last_diag_voice
+
+    while True:
+        scheme = "wss" if use_tls else "ws"
+        url = f"{scheme}://{RVS_HOST}:{RVS_PORT}/ws?token={RVS_TOKEN}"
+        masked = url.replace(RVS_TOKEN, "***") if RVS_TOKEN else url
+
+        try:
+            logger.info("Verbinde zu RVS: %s", masked)
+            async with websockets.connect(url, ping_interval=20, ping_timeout=10, max_size=50 * 1024 * 1024) as ws:
+                logger.info("RVS verbunden")
+                retry_s = 2
+                tls_fallback_tried = False
+
+                # TTS-Worker fuer diese Verbindung starten
+                worker = asyncio.create_task(_tts_worker(ws, runner))
+
+                try:
+                    async for raw in ws:
+                        try:
+                            msg = json.loads(raw)
+                        except Exception:
+                            continue
+                        mtype = msg.get("type", "")
+                        payload = msg.get("payload", {}) or {}
+
+                        if mtype == "xtts_request":
+                            await _tts_queue.put((
+                                payload.get("text", ""),
+                                payload.get("voice", "") or "",
+                                payload.get("requestId", ""),
+                                payload.get("messageId", ""),
+                                payload.get("language", "de"),
+                            ))
+                        elif mtype == "voice_upload":
+                            asyncio.create_task(handle_voice_upload(ws, payload))
+                        elif mtype == "xtts_list_voices":
+                            asyncio.create_task(handle_list_voices(ws))
+                        elif mtype == "xtts_delete_voice":
+                            asyncio.create_task(handle_delete_voice(ws, payload))
+                        elif mtype == "voice_preload":
+                            asyncio.create_task(handle_voice_preload(ws, payload, runner))
+                        elif mtype == "stt_response":
+                            # Antwort auf unseren internen Transkriptions-Request
+                            req_id = payload.get("requestId", "")
+                            fut = _pending_stt.get(req_id)
+                            if fut and not fut.done():
+                                if payload.get("error"):
+                                    fut.set_result(None)
+                                else:
+                                    fut.set_result(payload.get("text") or "")
+                        elif mtype == "config":
+                            v = (payload.get("xttsVoice") or "").strip()
+                            if v and v != _last_diag_voice:
+                                _last_diag_voice = v
+                                asyncio.create_task(handle_voice_preload(
+                                    ws, {"voice": v, "source": "diagnostic"}, runner,
+                                ))
+                            elif not v:
+                                _last_diag_voice = ""
+                finally:
+                    worker.cancel()
+                    try:
+                        await worker
+                    except asyncio.CancelledError:
+                        pass
+        except Exception as e:
+            logger.warning("Verbindung verloren: %s", e)
+            if use_tls and RVS_TLS_FALLBACK and not tls_fallback_tried:
+                logger.info("TLS fehlgeschlagen — Fallback auf ws://")
+                use_tls = False
+                tls_fallback_tried = True
+                continue
+            await asyncio.sleep(min(retry_s, 30))
+            retry_s = min(retry_s * 2, 30)
+
+
+async def main() -> None:
+    if not RVS_HOST:
+        logger.error("RVS_HOST nicht gesetzt — Abbruch")
+        sys.exit(1)
+    VOICES_DIR.mkdir(parents=True, exist_ok=True)
+    runner = F5Runner()
+    await run_loop(runner)
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        sys.exit(0)

xtts/f5tts/requirements.txt

@@ -0,0 +1,5 @@
+f5-tts>=1.0.0
+websockets>=12.0
+numpy>=1.24
+soundfile>=0.12
+requests>=2.31

xtts/package.json

@@ -1,8 +0,0 @@
-{
-  "name": "aria-xtts-bridge",
-  "version": "1.0.0",
-  "private": true,
-  "dependencies": {
-    "ws": "^8.16.0"
-  }
-}

xtts/whisper/Dockerfile

@@ -0,0 +1,14 @@
+FROM nvidia/cuda:12.2.2-cudnn8-runtime-ubuntu22.04
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    python3 python3-pip ffmpeg \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+COPY bridge.py .
+
+CMD ["python3", "bridge.py"]

xtts/whisper/bridge.py

@@ -0,0 +1,254 @@
+#!/usr/bin/env python3
+"""
+ARIA Whisper Bridge — laeuft auf der Gamebox (RTX 3060).
+
+Empfaengt stt_request via RVS → FFmpeg-Konvertierung → faster-whisper auf GPU
+→ sendet stt_response zurueck an die aria-bridge.
+
+Env:
+  RVS_HOST, RVS_PORT, RVS_TLS, RVS_TLS_FALLBACK, RVS_TOKEN
+  WHISPER_MODEL          Default: small
+  WHISPER_DEVICE         Default: cuda
+  WHISPER_COMPUTE_TYPE   Default: float16
+  WHISPER_LANGUAGE       Default: de
+"""
+import asyncio
+import base64
+import json
+import logging
+import os
+import subprocess
+import sys
+import tempfile
+import time
+from typing import Optional
+
+import numpy as np
+import websockets
+from faster_whisper import WhisperModel
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s [%(levelname)s] %(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger("whisper-bridge")
+
+RVS_HOST = os.getenv("RVS_HOST", "").strip()
+RVS_PORT = int(os.getenv("RVS_PORT", "443"))
+RVS_TLS = os.getenv("RVS_TLS", "true").lower() == "true"
+RVS_TLS_FALLBACK = os.getenv("RVS_TLS_FALLBACK", "true").lower() == "true"
+RVS_TOKEN = os.getenv("RVS_TOKEN", "").strip()
+
+WHISPER_MODEL = os.getenv("WHISPER_MODEL", "small")
+WHISPER_DEVICE = os.getenv("WHISPER_DEVICE", "cuda")
+WHISPER_COMPUTE_TYPE = os.getenv("WHISPER_COMPUTE_TYPE", "float16")
+WHISPER_LANGUAGE = os.getenv("WHISPER_LANGUAGE", "de")
+
+ALLOWED_MODELS = {"tiny", "base", "small", "medium", "large-v3"}
+
+
+class WhisperRunner:
+    """Haelt das Whisper-Modell. Hot-Swap bei Konfig-Wechsel via ensure_loaded()."""
+
+    def __init__(self) -> None:
+        self.model_size: str = WHISPER_MODEL
+        self.model: Optional[WhisperModel] = None
+        self._lock = asyncio.Lock()
+
+    def _load_blocking(self, size: str) -> None:
+        logger.info(
+            "Lade Whisper '%s' (device=%s, compute=%s)",
+            size, WHISPER_DEVICE, WHISPER_COMPUTE_TYPE,
+        )
+        t0 = time.time()
+        self.model = WhisperModel(
+            size, device=WHISPER_DEVICE, compute_type=WHISPER_COMPUTE_TYPE,
+        )
+        self.model_size = size
+        logger.info("Whisper '%s' geladen in %.1fs", size, time.time() - t0)
+
+    async def ensure_loaded(self, desired_size: str) -> None:
+        if desired_size not in ALLOWED_MODELS:
+            logger.warning("Ungueltiges Whisper-Modell '%s' — nutze %s", desired_size, WHISPER_MODEL)
+            desired_size = WHISPER_MODEL
+        async with self._lock:
+            if self.model is not None and self.model_size == desired_size:
+                return
+            loop = asyncio.get_event_loop()
+            await loop.run_in_executor(None, self._load_blocking, desired_size)
+
+    async def transcribe(self, audio: np.ndarray, language: str) -> tuple[str, float]:
+        if self.model is None:
+            return "", 0.0
+
+        def _run():
+            segments, info = self.model.transcribe(
+                audio, language=language, beam_size=5, vad_filter=True,
+            )
+            text = " ".join(seg.text.strip() for seg in segments)
+            return text, info.duration
+
+        loop = asyncio.get_event_loop()
+        return await loop.run_in_executor(None, _run)
+
+
+def ffmpeg_to_float32(audio_b64: str, mime_type: str) -> np.ndarray:
+    """Dekodiert beliebiges Audio-Format → 16kHz mono float32 PCM."""
+    if "mp4" in mime_type or "m4a" in mime_type or "aac" in mime_type:
+        ext = ".mp4"
+    elif "wav" in mime_type:
+        ext = ".wav"
+    elif "ogg" in mime_type or "opus" in mime_type:
+        ext = ".ogg"
+    else:
+        ext = ".bin"
+
+    in_fh = tempfile.NamedTemporaryFile(suffix=ext, delete=False)
+    try:
+        in_fh.write(base64.b64decode(audio_b64))
+        in_fh.close()
+        out_path = in_fh.name + ".raw"
+        cmd = ["ffmpeg", "-y", "-i", in_fh.name, "-ar", "16000", "-ac", "1", "-f", "f32le", out_path]
+        result = subprocess.run(cmd, capture_output=True, timeout=30)
+        if result.returncode != 0:
+            logger.error("FFmpeg Fehler: %s", result.stderr.decode(errors="replace")[:300])
+            return np.zeros(0, dtype=np.float32)
+        try:
+            return np.fromfile(out_path, dtype=np.float32)
+        finally:
+            try:
+                os.unlink(out_path)
+            except OSError:
+                pass
+    finally:
+        try:
+            os.unlink(in_fh.name)
+        except OSError:
+            pass
+
+
+async def _send(ws, mtype: str, payload: dict) -> None:
+    try:
+        await ws.send(json.dumps({
+            "type": mtype,
+            "payload": payload,
+            "timestamp": int(time.time() * 1000),
+        }))
+    except Exception as e:
+        logger.warning("Send fehlgeschlagen (%s): %s", mtype, e)
+
+
+async def handle_stt_request(ws, payload: dict, runner: WhisperRunner) -> None:
+    request_id = payload.get("requestId", "")
+    audio_b64 = payload.get("audio", "")
+    mime_type = payload.get("mimeType", "audio/mp4")
+    model = payload.get("model") or WHISPER_MODEL
+    language = payload.get("language") or WHISPER_LANGUAGE
+
+    if not audio_b64:
+        await _send(ws, "stt_response", {"requestId": request_id, "error": "no-audio"})
+        return
+
+    try:
+        t_load = time.time()
+        await runner.ensure_loaded(model)
+        load_ms = int((time.time() - t_load) * 1000)
+
+        audio = ffmpeg_to_float32(audio_b64, mime_type)
+        if audio.size == 0:
+            await _send(ws, "stt_response", {"requestId": request_id, "error": "ffmpeg-failed"})
+            return
+        duration_s = len(audio) / 16000.0
+        logger.info("STT-Request: %.1fs Audio, model=%s, lang=%s", duration_s, runner.model_size, language)
+
+        t_stt = time.time()
+        text, detected_duration = await runner.transcribe(audio, language)
+        stt_ms = int((time.time() - t_stt) * 1000)
+
+        logger.info("STT-Ergebnis (%dms): '%s'", stt_ms, text[:100])
+
+        await _send(ws, "stt_response", {
+            "requestId": request_id,
+            "text": text.strip(),
+            "durationS": duration_s,
+            "sttMs": stt_ms,
+            "loadMs": load_ms,
+            "model": runner.model_size,
+        })
+    except Exception as e:
+        logger.exception("STT-Request fehlgeschlagen")
+        await _send(ws, "stt_response", {
+            "requestId": request_id,
+            "error": str(e)[:200],
+        })
+
+
+async def run_loop(runner: WhisperRunner) -> None:
+    # Modell vorab laden damit erste Anfrage flott ist
+    try:
+        await runner.ensure_loaded(WHISPER_MODEL)
+    except Exception as e:
+        logger.error("Preload fehlgeschlagen: %s — Fortsetzung, wird bei erstem Request nachgeladen", e)
+
+    use_tls = RVS_TLS
+    retry_s = 2
+    tls_fallback_tried = False
+
+    while True:
+        scheme = "wss" if use_tls else "ws"
+        url = f"{scheme}://{RVS_HOST}:{RVS_PORT}/ws?token={RVS_TOKEN}"
+        masked = url.replace(RVS_TOKEN, "***") if RVS_TOKEN else url
+        try:
+            logger.info("Verbinde zu RVS: %s", masked)
+            async with websockets.connect(url, ping_interval=20, ping_timeout=10) as ws:
+                logger.info("RVS verbunden")
+                retry_s = 2
+                tls_fallback_tried = False
+                async for raw in ws:
+                    try:
+                        msg = json.loads(raw)
+                    except Exception:
+                        continue
+                    mtype = msg.get("type", "")
+                    payload = msg.get("payload", {}) or {}
+
+                    if mtype == "stt_request":
+                        req_id = payload.get("requestId", "?")
+                        audio_len = len(payload.get("audio", ""))
+                        logger.info("stt_request empfangen (id=%s, %dKB Audio)",
+                                    req_id[:8] if req_id != "?" else "?", audio_len // 1365)
+                        asyncio.create_task(handle_stt_request(ws, payload, runner))
+                    elif mtype == "config":
+                        new_model = payload.get("whisperModel")
+                        if new_model and new_model != runner.model_size:
+                            logger.info("Config-Broadcast: Whisper-Modell → %s", new_model)
+                            asyncio.create_task(runner.ensure_loaded(new_model))
+                    else:
+                        # Alle anderen Nachrichten debug-loggen — hilft beim Diagnostizieren,
+                        # ob stt_request ueberhaupt durch den RVS kommt
+                        logger.debug("Unbeachteter Type: %s", mtype)
+        except Exception as e:
+            logger.warning("Verbindung verloren: %s", e)
+            if use_tls and RVS_TLS_FALLBACK and not tls_fallback_tried:
+                logger.info("TLS-Verbindung fehlgeschlagen — Fallback auf ws://")
+                use_tls = False
+                tls_fallback_tried = True
+                continue
+            await asyncio.sleep(min(retry_s, 30))
+            retry_s = min(retry_s * 2, 30)
+
+
+async def main() -> None:
+    if not RVS_HOST:
+        logger.error("RVS_HOST ist nicht gesetzt — Abbruch")
+        sys.exit(1)
+    runner = WhisperRunner()
+    await run_loop(runner)
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        sys.exit(0)

xtts/whisper/requirements.txt

@@ -0,0 +1,4 @@
+faster-whisper==1.0.3
+websockets>=12.0
+numpy>=1.24
+requests>=2.31