Initial haunt-fm implementation

Full music recommendation pipeline: listening history capture via webhook,
Last.fm candidate discovery, iTunes preview download, CLAP audio embeddings
(512-dim), pgvector cosine similarity recommendations, playlist generation
with known/new track interleaving, and Music Assistant playback via HA.

Includes: FastAPI app, SQLAlchemy models, Alembic migrations, Docker Compose
with pgvector/pg17, status dashboard, and all API endpoints.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/haunt_fm/api/status_page.py

@@ -0,0 +1,23 @@
+from datetime import datetime, timezone
+from pathlib import Path
+
+from fastapi import APIRouter, Depends, Request
+from fastapi.responses import HTMLResponse
+from jinja2 import Environment, FileSystemLoader
+from sqlalchemy.ext.asyncio import AsyncSession
+
+from haunt_fm.api.status import status as get_status_data
+from haunt_fm.db import get_session
+
+router = APIRouter()
+
+_template_dir = Path(__file__).parent.parent / "templates"
+_jinja_env = Environment(loader=FileSystemLoader(str(_template_dir)), autoescape=True)
+
+
+@router.get("/", response_class=HTMLResponse)
+async def status_page(request: Request, session: AsyncSession = Depends(get_session)):
+    data = await get_status_data(session)
+    template = _jinja_env.get_template("status.html")
+    html = template.render(data=data, now=datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M UTC"))
+    return HTMLResponse(html)