f0c08e7326
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>
192 lines
6.9 KiB
Go
192 lines
6.9 KiB
Go
// patch.go — field-name mapping + validation for the tuning patches.
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// Wire field names are the snake_case column names; the admin API and
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// web card use them verbatim.
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package recsettings
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import (
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"errors"
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"fmt"
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"git.fabledsword.com/bvandeusen/minstrel/internal/recommendation"
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)
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var (
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ErrUnknownScope = errors.New("unknown tuning scope")
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ErrUnknownField = errors.New("unknown tuning field")
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ErrOutOfRange = errors.New("tuning value out of range")
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)
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// weightBound caps every scoring weight's magnitude. The scoring
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// terms are all in [-1, 1] before weighting, so ±10 is far past any
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// useful setting — the bound exists to catch typos (e.g. 100 for
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// 1.00), not to constrain exploration.
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const weightBound = 10.0
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// weightField describes one patchable ScoringWeights field.
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type weightField struct {
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get func(recommendation.ScoringWeights) float64
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set func(*recommendation.ScoringWeights, float64)
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// nonNegative marks fields where a negative value is meaningless
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// (a negative jitter magnitude or skip penalty inverts intent in a
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// way the score formula already expresses through its sign).
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nonNegative bool
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}
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var weightFields = map[string]weightField{
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"base_weight": {
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get: func(w recommendation.ScoringWeights) float64 { return w.BaseWeight },
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set: func(w *recommendation.ScoringWeights, v float64) { w.BaseWeight = v },
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},
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"like_boost": {
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get: func(w recommendation.ScoringWeights) float64 { return w.LikeBoost },
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set: func(w *recommendation.ScoringWeights, v float64) { w.LikeBoost = v },
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},
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"recency_weight": {
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get: func(w recommendation.ScoringWeights) float64 { return w.RecencyWeight },
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set: func(w *recommendation.ScoringWeights, v float64) { w.RecencyWeight = v },
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},
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"skip_penalty": {
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get: func(w recommendation.ScoringWeights) float64 { return w.SkipPenalty },
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set: func(w *recommendation.ScoringWeights, v float64) { w.SkipPenalty = v },
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nonNegative: true,
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},
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"jitter_magnitude": {
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get: func(w recommendation.ScoringWeights) float64 { return w.JitterMagnitude },
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set: func(w *recommendation.ScoringWeights, v float64) { w.JitterMagnitude = v },
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nonNegative: true,
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},
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"context_weight": {
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get: func(w recommendation.ScoringWeights) float64 { return w.ContextWeight },
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set: func(w *recommendation.ScoringWeights, v float64) { w.ContextWeight = v },
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},
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"similarity_weight": {
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get: func(w recommendation.ScoringWeights) float64 { return w.SimilarityWeight },
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set: func(w *recommendation.ScoringWeights, v float64) { w.SimilarityWeight = v },
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},
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"taste_weight": {
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get: func(w recommendation.ScoringWeights) float64 { return w.TasteWeight },
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set: func(w *recommendation.ScoringWeights, v float64) { w.TasteWeight = v },
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},
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"context_time_weight": {
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get: func(w recommendation.ScoringWeights) float64 { return w.ContextTimeWeight },
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set: func(w *recommendation.ScoringWeights, v float64) { w.ContextTimeWeight = v },
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},
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}
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// applyWeightPatch validates and applies a partial update, returning
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// the new weights and the list of actual changes (values equal to the
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// current setting are dropped, so a re-submitted form is a no-op).
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func applyWeightPatch(
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current recommendation.ScoringWeights, patch map[string]float64,
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) (recommendation.ScoringWeights, []fieldChange, error) {
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next := current
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var changes []fieldChange
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for field, v := range patch {
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f, ok := weightFields[field]
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if !ok {
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return current, nil, fmt.Errorf("%w: %q", ErrUnknownField, field)
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}
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if v < -weightBound || v > weightBound {
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return current, nil, fmt.Errorf("%w: %s = %v (|v| must be <= %v)",
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ErrOutOfRange, field, v, weightBound)
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}
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if f.nonNegative && v < 0 {
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return current, nil, fmt.Errorf("%w: %s = %v (must be >= 0)",
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ErrOutOfRange, field, v)
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}
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old := f.get(next)
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if old == v {
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continue
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}
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f.set(&next, v)
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changes = append(changes, fieldChange{Field: field, Old: old, New: v})
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}
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return next, changes, nil
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}
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// Taste tuning bounds. The half-life window is generous — from "taste
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// is last week" to "taste is a decade" — and the curve points must
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// stay ordered inside [0, 1] or the engagement ramps degenerate.
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const (
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tasteHalfLifeMin = 1.0
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tasteHalfLifeMax = 3650.0
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)
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// applyTastePatch validates and applies a partial taste update. The
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// curve-ordering invariant (hard_skip < neutral < full) is checked on
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// the PATCHED result, so a patch may move several points at once.
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func applyTastePatch(current TasteTuning, patch map[string]float64) (TasteTuning, []fieldChange, error) {
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next := current
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var changes []fieldChange
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for field, v := range patch {
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var target *float64
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switch field {
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case "half_life_days":
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if v < tasteHalfLifeMin || v > tasteHalfLifeMax {
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return current, nil, fmt.Errorf("%w: %s = %v (must be in [%v, %v])",
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ErrOutOfRange, field, v, tasteHalfLifeMin, tasteHalfLifeMax)
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}
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target = &next.HalfLifeDays
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case "engagement_hard_skip":
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target = &next.EngagementHardSkip
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case "engagement_neutral":
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target = &next.EngagementNeutral
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case "engagement_full":
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target = &next.EngagementFull
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case "enriched_tag_scale":
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target = &next.EnrichedTagScale
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case "era_scale":
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target = &next.EraScale
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case "mood_scale":
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target = &next.MoodScale
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default:
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return current, nil, fmt.Errorf("%w: %q", ErrUnknownField, field)
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}
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if field != "half_life_days" && (v < 0 || v > 1) {
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return current, nil, fmt.Errorf("%w: %s = %v (must be in [0, 1])",
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ErrOutOfRange, field, v)
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}
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if *target == v {
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continue
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}
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changes = append(changes, fieldChange{Field: field, Old: *target, New: v})
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*target = v
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}
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if !(next.EngagementHardSkip < next.EngagementNeutral &&
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next.EngagementNeutral < next.EngagementFull) {
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return current, nil, fmt.Errorf(
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"%w: engagement curve must satisfy hard_skip < neutral < full (got %v < %v < %v)",
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ErrOutOfRange, next.EngagementHardSkip, next.EngagementNeutral, next.EngagementFull)
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}
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return next, changes, nil
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}
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// diffWeights returns per-field changes from a to b (empty when equal).
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func diffWeights(a, b recommendation.ScoringWeights) []fieldChange {
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var out []fieldChange
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for field, f := range weightFields {
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if f.get(a) != f.get(b) {
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out = append(out, fieldChange{Field: field, Old: f.get(a), New: f.get(b)})
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}
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}
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return out
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}
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// diffTaste returns per-field changes from a to b (empty when equal).
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func diffTaste(a, b TasteTuning) []fieldChange {
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var out []fieldChange
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add := func(field string, oldV, newV float64) {
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if oldV != newV {
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out = append(out, fieldChange{Field: field, Old: oldV, New: newV})
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}
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}
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add("half_life_days", a.HalfLifeDays, b.HalfLifeDays)
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add("engagement_hard_skip", a.EngagementHardSkip, b.EngagementHardSkip)
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add("engagement_neutral", a.EngagementNeutral, b.EngagementNeutral)
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add("engagement_full", a.EngagementFull, b.EngagementFull)
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add("enriched_tag_scale", a.EnrichedTagScale, b.EnrichedTagScale)
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add("era_scale", a.EraScale, b.EraScale)
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add("mood_scale", a.MoodScale, b.MoodScale)
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return out
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}
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