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f367eeaa9d |
fix(recommendation): Songs-like gets its own profile so it stops wandering
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Operator, 2026-09-10: "when I play it I'm expecting to get a consistent
sound and style from the experience... I was getting a seeming wide variety
of music from each one when I was hoping to stay in a certain neighborhood."
Songs-like shared the `daily_mix` weight profile with For-You, and that
sharing WAS the bug. The two surfaces want opposite things: For-You answers
"what will they enjoy today" and is supposed to roam; Songs-like answers
"what sounds like THIS". Under one profile the broad answer wins.
The arithmetic, from the shared weights:
unrelated track, liked, not played recently → 1.0 + 2.0 + 1.0 = 4.0
PERFECT similarity match, not liked → 1.0 + 1.5 = 2.5
Liking something outranked sounding like the seed, because LikeBoost (2.0)
exceeded SimilarityWeight's whole range (1.5) and TasteWeight (1.5, and
seed-INDEPENDENT) matched it outright. Under the new profile the same pair
scores 5.00 vs 2.00.
Two levers, because either alone leaves the other's failure intact:
POOL. Songs-like now takes its own CandidateSourceLimits. The default gave
~29% of candidates a sim_score of literally zero — `taste_overlap` and
`random_fill` are both `0.0::float8` in recommendation.sql, seed-independent
by construction. Same total pool size; composition shifts to arms that
measure distance from the seed, LBSimilar doubled.
WEIGHTS. A third profile beside radio and daily_mix, DB-backed and live per
rule 25, with the property that similarity's range exceeds the combined
range of every seed-independent differentiator — so a closer match cannot
be beaten on likes, freshness and taste alone, while tracks within ~0.39
similarity of each other still get ordered by what the user likes.
Rule 131 changed the pool design mid-way and for the better. Zeroing the
two seed-independent arms was the first instinct and is exactly the
vanish-or-nothing shape that rule forbids: a seed with thin ListenBrainz
coverage would yield a short mix or none. They are the tier-3 FLOOR — cut
hard, never removed — and the weights keep them at the bottom of the
ranking rather than out of the pool. "A few tracks further from the seed
than we'd like" beats "no playlist".
Caught while wiring it: switching only pickTopN's final Score would have
been nearly INERT. scoreAndSortCandidates does the selection sort, and the
caller caps and truncates in that order — so the playlist would still have
been chosen by daily_mix and merely relabelled with songs_like numbers. It
now takes the profile as a parameter, and each surface passes its own.
Also corrects the daily_mix card's blurb, which claimed Songs-like as one
of its surfaces and no longer is.
Guards pin behaviour rather than the numbers, since numbers get retuned:
that similarity beats an unrelated liked track, that daily_mix still
DOESN'T (or the split buys nothing), that the tier-3 floor is non-zero,
and that the UI card shows its own values rather than falling back. Each
falsified against its named regression first.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01SQ31KQpYbStyK5y58UmPLH
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799dab029a |
feat(discover): rank suggestions by taste-tag overlap — #2377 (server)
The payoff slice. Until now a candidate's only claim on a slot was "some
artist you play is adjacent to it in a similarity graph" — a fact that says
nothing about whether the music sounds like anything you like. Now the
candidate's own folksonomy tags (cached by slice 5) are compared against
the user's taste-profile tags, so the deck ranks on taste and can say WHY.
The blend is MULTIPLICATIVE — score × (1 + weight × overlap) — and that
choice carries the whole safety argument:
- An untagged candidate has overlap 0, so its score is EXACTLY unchanged.
Tag coverage is permanently partial (#2376); it must cost a candidate
nothing, not sink it (rule #131).
- Nothing can leapfrog on tags alone. An additive term with a large
weight would let a near-zero-similarity artist outrank a strong match
for sharing one popular tag, which reads as noise.
- Weight 0 restores pure similarity order bit-for-bit, so the operator's
knob has a real off position.
overlap = Σ(shared) candWeight × normalizedTasteWeight ÷ Σ(all) candWeight.
Normalizing the taste side by the user's strongest tag makes the score
comparable across users (taste weights accumulate with listening, so a
heavy listener's raw numbers dwarf a new user's while meaning the same
thing). Dividing by the candidate's own mass makes it comparable across
candidates, so a densely-tagged artist can't win on tag count alone.
Applied to the whole over-fetched pool BEFORE selectSuggestions, so the
rotation and diversity rules operate on blended scores — boosting only the
twelve already chosen by similarity would leave the re-ranking undone.
A query failure is returned, NOT degraded past. Graceful degradation is
for expected absence (no taste profile, no cached tags) and both are
handled explicitly as empty inputs; swallowing a real error would hide a
broken DB behind a subtly worse ranking that nothing reports.
Migration 0051 adds a FOURTH tuning scope rather than columns on
taste_tuning, because snooze_days lives here too and a snooze must never
be read as taste signal (#2374) — filing it under 'taste' would put it one
careless join from the leak that design forbids. Expanding
recommendation_tuning_audit's CHECK is in the same migration per rule #36,
and a test asserts the audit row lands, which is what would catch its
absence.
snooze_days moves out of a Go constant onto the tuning card (rule #25),
closing the deferral from #2374.
Tag-overlap tests use deliberately SKEWED fixtures: an evenly-matching pool
cannot exercise a re-ranking, since every candidate gets the same
multiplier and the order is unchanged whether the blend works or not.
Admin UI + client attribution follow in this batch — rule #27.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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f0c08e7326 |
feat(taste): mood taste facet — #1534
Milestone #160 Opt 2b (mood half of the era+mood option). A fourth taste facet alongside artists + genre tags + eras: signed weights over canonical mood buckets (melancholic / energetic / chill / …) derived from a track's enriched folksonomy tags (#1490). - internal/mood: shared vocabulary — Of(tags) maps folksonomy tags to canonical mood buckets (synonyms collapse). Imported by both the taste builder and the scorer so a track's mood is derived identically. - Migration 0047: taste_profile_moods table + taste_tuning.mood_scale (DEFAULT 0.5). - Build side (internal/taste): Config.MoodScale ([0,1] damper, mirrors EraScale); accumulate folds each play/like's mood buckets at base*MoodScale; persist atomic-replaces the mood rows. - Scorer (internal/recommendation): TasteProfile gains a mood term (own tanh scale + additive 0.12 share, so it never weakens the existing signal when a track has no mood tags). Match now takes the candidate's mood buckets; loaded per candidate (ListTrackTagsForTracks → mood.Of) in the primary similarity loader only — the near-whole-library fallback pool passes nil (mood → 0) to avoid a full-library tag scan. - Tuning lab: mood_scale threaded through recsettings + admin API + web card ("Mood weight" row) + Go/web tests. Coverage is partial (grows with tag enrichment; richer once Last.fm is keyed), so mood is a supplement — neutral for tracks with no mood tags. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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65dd132b3d |
feat(taste): time-of-day / weekday context conditioning — #1531
Milestone #160 Opt 3 (temporal half). A new additive scoring term that boosts a candidate when its artist's play history concentrates in the CURRENT daypart × weekday-type cell, in the user's local timezone. - Migration 0046: recommendation_weight_profiles.context_time_weight (per-profile scoring weight, DEFAULT 1.0). - Query ListArtistContextPlayCountsForUser: per-artist completed-play counts split by the current cell (daypart night[22,5)/morning[5,12)/ afternoon[12,17)/evening[17,22) × weekday-vs-weekend) via started_at AT TIME ZONE users.timezone; 365-day window, skips excluded. - internal/recommendation/context.go: LoadContextAffinity computes each artist's shrunk cell-share minus the user's baseline share, clamped to [-1,1]; sparse artists shrink toward baseline (pseudo-count 5), unknown artists → 0 (cold-start neutral). - Score() gains context_affinity_score · ContextTimeWeight; both candidate loaders set it per candidate. - Tuning lab: ContextTimeWeight threaded through recsettings + admin API + web card ("Time-of-day weight" row) + Go/web tests. Shipped 1.0 both profiles (uniform start, re-bakeable). Device-class axis deferred to #1551 (needs a client_id → device-class mapping that doesn't exist yet). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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40384cc05e |
feat(taste): era/decade taste facet — #1530
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> |
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2b3be8311a |
feat(tuning): expose EnrichedTagScale in the tuning lab (#1520)
Promote the enriched-tag weight (#1490) from a taste.Config default into the DB-backed tuning lab so operators can dial how much folksonomy tags count vs raw ID3 genre (rule #25). - Migration 0044: taste_tuning.enriched_tag_scale (DEFAULT 0.5, backfills the existing row). - recsettings: TasteTuning gains the field; seeded/read/updated through reconcile + persistTaste; applyTastePatch validates it to [0,1] (generic non-half-life clamp) and diffTaste audits it; TasteConfig maps it into the profile build. - API: tasteTuningResp exposes enriched_tag_scale. - Web tuning card: a data-driven "Enriched tag weight" knob (0 = genre only). Tests: recsettings persist+range, web fixture field. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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0d0a8f46b1 |
feat(tuning): scoring weights → DB-backed admin tuning lab
The recommendation scoring knobs move out of YAML (radio profile) and out of the systemMixWeights hard-code (daily_mix profile) into DB-backed settings with live effect (#1250) — the defaults-discovery lab per decision #1247: the operator turns knobs to find good values, which then get baked back into shipped defaults; end users and other operators should never need the card. - Migration 0040: recommendation_weight_profiles (radio / daily_mix, 8 weight columns), taste_tuning singleton (engagement half-life + completion-curve points), recommendation_tuning_audit (one row per change with a {field, old, new} diff — the trend view's markers, #1251). - internal/recsettings: boot reconcile seeds shipped defaults without clobbering tuned rows (coverart SettingsService pattern), validates patches (bounds, curve ordering), writes audit rows, and pushes daily_mix weights + taste config into package playlists. No-op patches write no audit row. - playlists gains SetSystemMixWeights / SetTasteConfig swap points under a RWMutex — no signature threading through the producers; the scheduler's taste rebuild reads the pushed config. - Radio reads its weight profile from the service per request; the 8 weight fields leave config.RecommendationConfig (YAML keeps only RecentlyPlayedHours / RadioSize / RadioSizeMax). - Admin API: GET/PATCH/reset under /api/admin/recommendation-tuning, echoing current + shipped values. - Web: new admin Tuning tab — two weight profiles side by side, taste card, per-scope save (changed fields only) + reset, deviation dots against shipped defaults. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TsF3cNoKrqCYsU78cXC8U6 |