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/config.py

@@ -0,0 +1,27 @@
+from pydantic_settings import BaseSettings
+
+
+class Settings(BaseSettings):
+    model_config = {"env_prefix": "HAUNTFM_"}
+
+    # Database
+    database_url: str = "postgresql+asyncpg://hauntfm:changeme@localhost:5432/hauntfm"
+
+    # Last.fm
+    lastfm_api_key: str = ""
+
+    # Home Assistant
+    ha_url: str = "http://192.168.86.51:8123"
+    ha_token: str = ""
+
+    # CLAP model
+    model_cache_dir: str = "/app/model-cache"
+    audio_cache_dir: str = "/app/audio-cache"
+
+    # Embedding worker
+    embedding_worker_enabled: bool = True
+    embedding_batch_size: int = 10
+    embedding_interval_seconds: int = 30
+
+
+settings = Settings()