Use qwen3-asr throughout speech integrations

router/ai_profile_router.py

@@ -219,7 +219,7 @@ TTS_DEFAULT_FORMAT = "mp3"
 STT_WORKER_URL = os.environ.get("STT_WORKER_URL", "http://127.0.0.1:8084")
 STT_TIMEOUT = float(os.environ.get("STT_TIMEOUT", "120"))  # s, pro Transkription
 STT_CONNECT_TIMEOUT = float(os.environ.get("STT_CONNECT_TIMEOUT", "5"))
-STT_MODEL = "whisper-1"  # OpenClaw/OpenAI compatibility alias; Qwen3-ASR serves it
+STT_MODEL = "qwen3-asr"
 
 # Maximale Upload-Größe (Bytes) – verhindert unbegrenzten RAM-Verbrauch.
 # 50 MB ist für Audio-Dateien (WebM/Opus, WAV, MP3) mehr als ausreichend.
@@ -2848,12 +2848,6 @@ class Handler(BaseHTTPRequestHandler):
                 "owned_by": "qwen3-asr",
                 "type": "transcription",
             })
-            models.append({
-                "id": "qwen3-asr",
-                "object": "model",
-                "owned_by": "qwen3-asr",
-                "type": "transcription",
-            })
         if tts.get("ready"):
             models.append({
                 "id": TTS_MODEL,
@@ -2974,7 +2968,7 @@ class Handler(BaseHTTPRequestHandler):
 
         # Modell-Validierung
         model = fields.get("model", STT_MODEL)
-        if model not in (STT_MODEL, "whisper", "qwen3-asr"):
+        if model != STT_MODEL:
             self._send_error(400, f"unbekanntes Modell: {model!r} "
                                   f"(erwartet: {STT_MODEL})",
                              "invalid_request_error", "unknown_model")