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
Milestone #160 Opt 3b. Adds device class as a third context axis on top
of the #1531 time-of-day/weekday affinity: on the radio path, a candidate
is boosted when its artist concentrates in the current (daypart × weekday
× device) cell. Client-sent (client_id is opaque; no UA stored), so it's
captured going forward and applies to radio only (daily mixes are
cron-built with no device → stay device-agnostic).
Server:
- Migration 0048: play_events.device_class text NULL (no CHECK; normalized
in Go — one whitelist entry per new client class, not a migration).
- events.go: eventRequest.device_class + normalizeDeviceClass (whitelist →
mobile/web/…, else "other", empty → NULL); threaded through both
RecordPlayStartedWithSource and RecordOfflinePlay into InsertPlayEvent.
- ListArtistContextPlayCountsForUser gains a current-device param; the cell
FILTER adds AND ($2='' OR device_class=$2) — '' reproduces the #1531
time-only behaviour exactly (used by mixes). SessionVector.DeviceClass
carries it; the radio handler derives the current device from the user's
latest play (GetLatestPlayDeviceClassForUser) — request-free proxy.
- No new tuning knob: device narrows the existing ContextAffinityScore
(reuses context_time_weight).
Clients:
- web: play_started sends device_class 'web'.
- android: play_started + offline replay send 'mobile' (EventsWire +
PlayOfflinePayload + MutationReplayer + PlayEventsReporter).
Test: LoadContextAffinity device-narrowing integration test (mobile vs web
artist separation; device-agnostic parity).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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>
Milestone #160 Opt 5. A collaborative candidate arm: tracks by artists
co-played across the instance with the seed's artist.
Minstrel is a single shared-library, multi-user server (no per-user
library ACL — verified: no owner/share/group model), so the "household"
is the whole instance's user set; the rule #47 scoping is satisfied by
the shared-library boundary. Single-user servers produce no edges.
- No migration: source='user_cooccurrence' was pre-whitelisted in the
0009 similarity CHECK from day one.
- internal/db/queries/coplay.sql: Delete + Insert artist co-play edges.
Score = Jaccard of the two artists' distinct-player sets (controls for
globally-popular artists); >= 2 co-players AND Jaccard >= floor kept
(the floor also self-limits hub artists). Completed plays, 365d window.
- internal/coplay: periodic worker (6h) that atomic-replaces the
user_cooccurrence edge set from play_events — pure local SQL, no
external calls. Wired in main.go alongside the similarity worker.
- LoadRadioCandidatesV2: new coplay_artists arm (source='user_cooccurrence',
seed-artist based, 0.5 damp like similar_artists) + $11 limit;
CandidateSourceLimits.UserCoplay (default 20, For-You 40).
- Integration tests: perfect-overlap Jaccard=1.0 edge + single-user
empty-set gate.
Device axis and AcousticBrainz (Opt 4) are separately tracked; this
closes the milestone-#160 sequential options.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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>
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>
2a re-ranks the existing pool by TasteMatch; this ensures taste-relevant tracks
ARE in the pool. Adds a 6th arm to LoadRadioCandidatesV2: in-library tracks by
the user's top positively-weighted taste-profile artists ($10 K, weight > 0,
deterministic weight-DESC,id order so it doesn't reintroduce same-day
nondeterminism). Pool-inclusion only (sim_score 0) — TasteMatch already scores
the fit. Empty for cold-start users (no profile).
- CandidateSourceLimits.TasteOverlap; default 20 (radio), 80 for For-You via
systemForYouSourceLimits.
- You-might-like deliberately sets TasteOverlap=0: it surfaces NOT-actively-
engaged artists, so flooding its pool with top-taste (mostly already-played)
artists would just feed the read-time dedup.
- Test: positive-weight artist's track enters via the arm; negative-weight one
is excluded (weight > 0). Existing pool tests unaffected (no profile seeded).
Deferred within 2b: profile-seeded For-You — marginal given the arm + TasteMatch
already inject taste broadly (top-played seed ≈ top-taste artist).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The profile built in phase 1 now changes what gets surfaced. Adds a TasteMatch
term to the weighted-shuffle score so candidates are re-ranked by their fit to
the user's learned taste (positive draws toward it; negative reflects passive
avoidance; 0 at cold start).
- recommendation/score.go: ScoringInputs.TasteMatchScore ([-1,+1]) +
ScoringWeights.TasteWeight + the term in Score.
- recommendation/taste.go: LoadTasteProfile reads the taste_profile_* tables;
TasteProfile.Match blends the candidate's artist weight (0.7) and avg genre-tag
weight (0.3), each tanh-squashed by a fixed scale so one outlier artist can't
compress the rest. Unknown artist/tags and empty profiles → 0 (neutral).
- candidates.go: both candidate loaders set TasteMatchScore per candidate, so
every Score caller (system playlists incl. You-might-like, radio) becomes
taste-aware automatically.
- weights: systemMixWeights.TasteWeight = 1.5 (daily mixes are the primary
taste surface); config.RecommendationConfig gains taste_weight (default 1.0,
lighter — radio is seed-directed) wired into the radio handler.
- tests: pure (Match curve incl. saturation/clamp/empty-neutral, Score term
add+subtract) + DB round-trip (seed taste rows → Match positive). All green
vs real Postgres; existing playlist/radio tests unaffected (empty profile →
zero taste effect).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Adds a 6th argument (currentVector SessionVector) to LoadCandidates,
bulk-fetches the user's active contextual_likes in one query, and sets
ContextualMatchScore on each candidate's ScoringInputs via max-similarity
over that candidate's like vectors. Adds helper + 6 integration tests
covering no-likes, single match, multi-like max, soft-delete filtering,
seed-like filtering, and seed-current short-circuit. Adds contextual_likes
to the TRUNCATE list in testPool to prevent cross-test leakage.
internal/api/radio.go is intentionally left broken (Task 6 fixes it).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
bvandeusenandClaude Opus 5