feat: VoiceCoach v2.1 - GPU local, Ollama LLM, settings panel, token server separation

- pipeline.py: switched LLM from OpenClaw/Claude to local Ollama, added settings loading, sentence aggregator, async SpeechBrain, tuned VAD
- main.py: simplified (no more token server thread, just pipeline)
- token_server.py: NEW - standalone token + settings API server
- docker-compose.yml: all services on GPU machine, added token-server service, CUDA speaches, Ollama LLM
- web-client/index.html: added settings panel with sliders
- web-client/app.js: settings management, localStorage persistence, push to server
- web-client/style.css: settings panel styles
- web-client/nginx.conf: proxy to token-server instead of pipecat-agent
- patch_livekit.py: updated with proper indentation-safe patching

pipecat-agent/whisper_stt.py

@@ -0,0 +1,35 @@
+"""
+Local STT service using faster-whisper.
+Replaces Deepgram with fully self-hosted speech-to-text.
+"""
+import io
+import logging
+import wave
+import numpy as np
+from faster_whisper import WhisperModel
+
+logger = logging.getLogger(__name__)
+
+
+class LocalWhisperSTT:
+    """Wraps faster-whisper for use in the Pipecat pipeline."""
+
+    def __init__(self, model_size: str = "medium", device: str = "cpu", compute_type: str = "int8"):
+        logger.info(f"Loading faster-whisper model: {model_size} on {device}")
+        self.model = WhisperModel(model_size, device=device, compute_type=compute_type)
+        logger.info("faster-whisper model loaded.")
+
+    def transcribe(self, audio_bytes: bytes, sample_rate: int = 16000) -> str:
+        """Transcribe raw PCM audio bytes to text."""
+        audio_array = np.frombuffer(audio_bytes, dtype=np.int16).astype(np.float32) / 32768.0
+
+        segments, info = self.model.transcribe(
+            audio_array,
+            beam_size=5,
+            language="en",
+            vad_filter=True,
+            vad_parameters=dict(min_silence_duration_ms=500),
+        )
+
+        text = " ".join(seg.text.strip() for seg in segments)
+        return text