Blend taste profile with text-embedded mood descriptions (e.g. "chill
ambient lo-fi") using pre-blended vector search against the existing
HNSW index. New optional `vibe` and `alpha` params on playlist generate
and recommendations endpoints. Backward compatible — no vibe = pure
taste profile (alpha=1.0).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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>
