feat(taste): time-of-day / weekday context conditioning — #1531
test-go / test (push) Successful in 35s
test-web / test (push) Successful in 42s
test-go / integration (push) Successful in 4m46s

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>
This commit is contained in:
2026-07-14 09:31:43 -04:00
parent 40384cc05e
commit 65dd132b3d
18 changed files with 437 additions and 119 deletions
+4
View File
@@ -67,6 +67,10 @@ var weightFields = map[string]weightField{
get: func(w recommendation.ScoringWeights) float64 { return w.TasteWeight },
set: func(w *recommendation.ScoringWeights, v float64) { w.TasteWeight = v },
},
"context_time_weight": {
get: func(w recommendation.ScoringWeights) float64 { return w.ContextTimeWeight },
set: func(w *recommendation.ScoringWeights, v float64) { w.ContextTimeWeight = v },
},
}
// applyWeightPatch validates and applies a partial update, returning
+49 -42
View File
@@ -54,16 +54,19 @@ type TasteTuning struct {
// here from config.RecommendationConfig — YAML is bootstrap-only,
// rule: config in UI). Radio is seed-directed (the user picked a
// direction), so taste is a lighter nudge than in the daily mixes.
// ContextTimeWeight starts uniform (1.0) across both profiles pending
// trend data (#1531); split them once the metrics view justifies it.
func ShippedRadioWeights() recommendation.ScoringWeights {
return recommendation.ScoringWeights{
BaseWeight: 1.0,
LikeBoost: 2.0,
RecencyWeight: 1.0,
SkipPenalty: 1.0,
JitterMagnitude: 0.1,
ContextWeight: 2.0,
SimilarityWeight: 2.0,
TasteWeight: 1.0,
BaseWeight: 1.0,
LikeBoost: 2.0,
RecencyWeight: 1.0,
SkipPenalty: 1.0,
JitterMagnitude: 0.1,
ContextWeight: 2.0,
SimilarityWeight: 2.0,
TasteWeight: 1.0,
ContextTimeWeight: 1.0,
}
}
@@ -71,14 +74,15 @@ func ShippedRadioWeights() recommendation.ScoringWeights {
// Must stay in sync with the pre-push literal in playlists/system.go.
func ShippedDailyMixWeights() recommendation.ScoringWeights {
return recommendation.ScoringWeights{
BaseWeight: 1.0,
LikeBoost: 2.0,
RecencyWeight: 1.0,
SkipPenalty: 2.0,
JitterMagnitude: 0.1,
ContextWeight: 0.5,
SimilarityWeight: 1.5,
TasteWeight: 1.5,
BaseWeight: 1.0,
LikeBoost: 2.0,
RecencyWeight: 1.0,
SkipPenalty: 2.0,
JitterMagnitude: 0.1,
ContextWeight: 0.5,
SimilarityWeight: 1.5,
TasteWeight: 1.5,
ContextTimeWeight: 1.0,
}
}
@@ -348,41 +352,44 @@ func (s *Service) audit(
func upsertParams(profile string, w recommendation.ScoringWeights) dbq.UpsertWeightProfileDefaultsParams {
return dbq.UpsertWeightProfileDefaultsParams{
Profile: profile,
BaseWeight: w.BaseWeight,
LikeBoost: w.LikeBoost,
RecencyWeight: w.RecencyWeight,
SkipPenalty: w.SkipPenalty,
JitterMagnitude: w.JitterMagnitude,
ContextWeight: w.ContextWeight,
SimilarityWeight: w.SimilarityWeight,
TasteWeight: w.TasteWeight,
Profile: profile,
BaseWeight: w.BaseWeight,
LikeBoost: w.LikeBoost,
RecencyWeight: w.RecencyWeight,
SkipPenalty: w.SkipPenalty,
JitterMagnitude: w.JitterMagnitude,
ContextWeight: w.ContextWeight,
SimilarityWeight: w.SimilarityWeight,
TasteWeight: w.TasteWeight,
ContextTimeWeight: w.ContextTimeWeight,
}
}
func updateParams(profile string, w recommendation.ScoringWeights) dbq.UpdateWeightProfileParams {
return dbq.UpdateWeightProfileParams{
Profile: profile,
BaseWeight: w.BaseWeight,
LikeBoost: w.LikeBoost,
RecencyWeight: w.RecencyWeight,
SkipPenalty: w.SkipPenalty,
JitterMagnitude: w.JitterMagnitude,
ContextWeight: w.ContextWeight,
SimilarityWeight: w.SimilarityWeight,
TasteWeight: w.TasteWeight,
Profile: profile,
BaseWeight: w.BaseWeight,
LikeBoost: w.LikeBoost,
RecencyWeight: w.RecencyWeight,
SkipPenalty: w.SkipPenalty,
JitterMagnitude: w.JitterMagnitude,
ContextWeight: w.ContextWeight,
SimilarityWeight: w.SimilarityWeight,
TasteWeight: w.TasteWeight,
ContextTimeWeight: w.ContextTimeWeight,
}
}
func weightsFromRow(r dbq.RecommendationWeightProfile) recommendation.ScoringWeights {
return recommendation.ScoringWeights{
BaseWeight: r.BaseWeight,
LikeBoost: r.LikeBoost,
RecencyWeight: r.RecencyWeight,
SkipPenalty: r.SkipPenalty,
JitterMagnitude: r.JitterMagnitude,
ContextWeight: r.ContextWeight,
SimilarityWeight: r.SimilarityWeight,
TasteWeight: r.TasteWeight,
BaseWeight: r.BaseWeight,
LikeBoost: r.LikeBoost,
RecencyWeight: r.RecencyWeight,
SkipPenalty: r.SkipPenalty,
JitterMagnitude: r.JitterMagnitude,
ContextWeight: r.ContextWeight,
SimilarityWeight: r.SimilarityWeight,
TasteWeight: r.TasteWeight,
ContextTimeWeight: r.ContextTimeWeight,
}
}