Milestone #160 Opt 2 (era half). A third taste facet alongside artists
+ genre tags: signed weights over decade buckets ("1990s") derived from
albums.release_date, rebuilt daily and scored into the taste match.
- Migration 0045: taste_profile_eras table (mirrors taste_profile_tags)
+ taste_tuning.era_scale column (DEFAULT 0.5).
- Build side (internal/taste): Config.EraScale ([0,1] damper, mirrors
EnrichedTagScale), accumulate folds each play/like's decade at
base*EraScale, persist atomic-replaces the era rows.
- Scorer (internal/recommendation): TasteProfile gains an era term (own
tanh scale + additive 0.15 share so it never weakens the existing
artist/tag signal when a track is undated); candidate queries return
album release_date; decadeOf mirrors the builder helper.
- Tuning lab: era_scale threaded through recsettings + admin API + web
card (auto-renders the new row) + Go/web tests.
Mood facet deferred to #1534 (partial enrichment coverage + needs
candidate-side enriched-tag loading).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The taste recompute's tag facet now unions the cached track_tags
(MusicBrainz/Last.fm folksonomy tags) alongside raw ID3 genre, so a coarse
"Rock" gains "post-punk / shoegaze / melancholic".
- taste_profile.sql: ListPlayEngagementInputsForUser +
ListLikedTrackTasteInputsForUser now return track_id to key the
enriched-tag lookup.
- accumulate(): for each play, fold its track's enriched tags weighted by
engagement × tag.weight × EnrichedTagScale; for each liked track, by the
tag-like bonus × tag.weight × scale. A track with no cached tags
contributes genre only (graceful).
- New Config.EnrichedTagScale (default 0.5) — enriched tags augment the
ID3 signal without swamping it; 0 = genre-only. Flows through
recsettings.TasteConfig() (starts from DefaultConfig). Promoting it into
the admin tuning lab is a small follow-up.
Unit-tested the pure foldEnrichedTags helper (overlap accumulation +
scale=0 disable).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Build a persistent, decaying model of each user's taste, recomputed daily,
that later phases consume across every recommendation surface. Phase 1 only
BUILDS the object — no behaviour change to what's surfaced yet.
Core mechanic — graded engagement (replaces binary was_skipped for learning;
was_skipped stays for History): a play's completion ratio maps to a signal in
[-1,+1] via two linear ramps (instant-skip → -1, ~0.30 neutral, ≥0.90 → +1).
Time-decayed (half-life ~75d) so recent behaviour dominates and the profile
tracks drift.
Per operator constraints:
- No explicit dislike button — negatives come only from passive behaviour
(early skips). Nothing recorded to regret or opt out of.
- Negatives are track-scoped; artist/tag weight is the decayed SUM of their
tracks' engagement, so one skip nets out against many good plays (a
DB test asserts a liked artist stays positive despite an early-skipped
track). A floor clamp bounds how negative any single entity can get.
- migration 0035: taste_profile_artists / taste_profile_tags (signed weight,
indexed by (user, weight DESC)).
- internal/taste: engagement.go (pure curve + decay) + profile.go
(accumulate plays + like bonuses, floor damping, size caps, atomic-replace).
- scheduler: rebuildUserDaily recomputes the profile before the playlist
build (so phase 2 can read it), best-effort — a taste failure never blocks
playlist building. Wired into the daily job + startup catch-up only (not
manual/lazy rebuilds).
- tests: pure (engagement curve, decay, ranking, floor, genre split) +
DB-backed (positive/negative weights, aggregation-protects-artist, like
bonus, atomic replace). All green vs real Postgres.
Config knobs live in taste.DefaultConfig() for now; wiring them into the
server RecommendationConfig is a later follow-up.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
bvandeusen