feat(dashboard): default STT=medium, apply feedback+loading, log categories+filters

- Default STT model changed small -> medium (WhisperSTT default + service env;
  medium pre-cached). UI labels/hints updated.
- Model 적용 buttons: if the picked model == current, flash "변경사항 없음" for 3s
  then show the current model again; if it actually changes, STT shows a live
  loading panel that polls /api/models until the worker is ready and logs
  completion to the event log (set_stt_model/set_llm_model now return `changed`).
- Event/error log gains categories (READY, CONNECT, MODEL, TTS, VOICE, FILTER,
  SETTING, TURN, BRAIN, VISION, PIPELINE, …): Monitor.log takes an optional `cat`,
  call sites tagged, and each line shows a coloured category chip. A bot
  (re)connection now logs a CONNECT event.
- Log search extended: filter by 레벨(type), 종류(category, auto-populated), and
  시간(time range) in addition to free text.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

wsai/backends/whisper.py

@@ -18,7 +18,7 @@ stays usable directly.
 Env:
     WSAI_WHISPER_PYTHON    interpreter with faster-whisper installed
                            (default: /home/claude/jarvis-stt/whisper312/bin/python)
-    WSAI_WHISPER_MODEL     model size/name (default: small)
+    WSAI_WHISPER_MODEL     model size/name (default: medium)
     WSAI_WHISPER_DEVICE    cpu | cuda | auto  (default auto: GPU if present,
                            else CPU; the worker falls back to CPU if CUDA fails)
     WSAI_WHISPER_LANGUAGE  forced language, e.g. ko (default ko; "" = autodetect)
@@ -67,7 +67,7 @@ class WhisperSTT:
         audio_source: AsyncIterator[str] | None = None,
     ) -> None:
         self.python = python or os.environ.get("WSAI_WHISPER_PYTHON", _DEFAULT_PYTHON)
-        self.model = model or os.environ.get("WSAI_WHISPER_MODEL", "small")
+        self.model = model or os.environ.get("WSAI_WHISPER_MODEL", "medium")
         self.device = device or os.environ.get("WSAI_WHISPER_DEVICE", "auto")
         # "" means autodetect; a real code like "ko" forces the language.
         env_lang = os.environ.get("WSAI_WHISPER_LANGUAGE", "ko")