feat: voice-agent MVP — LXC web frontend + Mac AI worker

LXC-Frontend (FastAPI + HTML/JS):
- Audio-Upload (MP3/WAV/M4A/MP4/OGG/FLAC, max. 500 MB)
- SQLite Job-Store, BackgroundTask-Pipeline
- Job-Liste mit Live-Status, Downloads (DOCX + JSON)
- Mac-Health-Indicator im UI

Mac-Worker (FastAPI):
- /api/transcribe (lightning-whisper-mlx | faster-whisper | mock)
- /api/summarize + /api/protocol via Ollama (llama3.1:8b)
- /api/export/docx via python-docx

Deploy:
- systemd-Service, Nginx Reverse-Proxy
- deploy/install.sh: idempotentes LXC-Setup

Doku: README.md, lxc-frontend/README.md, mac-worker/README.md

lxc-frontend/app/services/pipeline.py

@@ -0,0 +1,76 @@
+import json
+import logging
+from datetime import datetime, timezone
+from pathlib import Path
+
+from sqlmodel import Session
+
+from app.core.config import settings
+from app.core.db import engine
+from app.core.mac_client import MacClient
+from app.models.job import Job, JobStatus
+
+log = logging.getLogger("voice-agent.pipeline")
+
+
+def _update(job_id: int, **fields) -> None:
+    with Session(engine) as s:
+        job = s.get(Job, job_id)
+        if not job:
+            return
+        for k, v in fields.items():
+            setattr(job, k, v)
+        job.updated_at = datetime.now(timezone.utc)
+        s.add(job)
+        s.commit()
+
+
+async def run_pipeline(job_id: int) -> None:
+    """Run the full pipeline: transcribe → summarize → protocol → DOCX."""
+    client = MacClient()
+
+    with Session(engine) as s:
+        job = s.get(Job, job_id)
+        if not job:
+            log.error("Job %s not found", job_id)
+            return
+        audio_path = settings.upload_dir / job.filename
+        title = job.title or audio_path.stem
+
+    job_dir = settings.result_dir / str(job_id)
+    job_dir.mkdir(parents=True, exist_ok=True)
+
+    try:
+        _update(job_id, status=JobStatus.TRANSCRIBING, progress=10)
+        log.info("[job %s] transcribe", job_id)
+        tx = await client.transcribe(audio_path, language="de")
+        transcript_path = job_dir / "transcript.json"
+        transcript_path.write_text(json.dumps(tx, ensure_ascii=False, indent=2), encoding="utf-8")
+        _update(job_id, transcript_path=str(transcript_path), progress=45)
+
+        transcript_text = tx.get("text") or "\n".join(s.get("text", "") for s in tx.get("segments", []))
+
+        _update(job_id, status=JobStatus.SUMMARIZING, progress=55)
+        log.info("[job %s] summarize", job_id)
+        summary = await client.summarize(transcript_text, title=title)
+        summary_path = job_dir / "summary.json"
+        summary_path.write_text(json.dumps(summary, ensure_ascii=False, indent=2), encoding="utf-8")
+        _update(job_id, summary_path=str(summary_path), progress=70)
+
+        _update(job_id, status=JobStatus.PROTOCOLLING, progress=75)
+        log.info("[job %s] protocol", job_id)
+        protocol = await client.protocol(transcript_text, summary, title=title)
+        protocol_path = job_dir / "protocol.json"
+        protocol_path.write_text(json.dumps(protocol, ensure_ascii=False, indent=2), encoding="utf-8")
+        _update(job_id, protocol_path=str(protocol_path), progress=85)
+
+        _update(job_id, status=JobStatus.EXPORTING, progress=90)
+        log.info("[job %s] export docx", job_id)
+        docx_bytes = await client.export_docx(protocol)
+        docx_path = job_dir / "protocol.docx"
+        docx_path.write_bytes(docx_bytes)
+        _update(job_id, docx_path=str(docx_path), status=JobStatus.DONE, progress=100)
+        log.info("[job %s] done", job_id)
+    except Exception as e:  # noqa: BLE001
+        log.exception("[job %s] failed", job_id)
+        _update(job_id, status=JobStatus.FAILED, error=f"{type(e).__name__}: {e}")