bvandeusen
aff346c731
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>
92 lines
2.6 KiB
Go
92 lines
2.6 KiB
Go
package recommendation
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import (
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"context"
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"math"
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"github.com/jackc/pgx/v5/pgtype"
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"git.fabledsword.com/bvandeusen/minstrel/internal/db/dbq"
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)
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// Taste-match tuning. The taste profile (written by internal/taste) holds
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// signed, unbounded artist/tag weights; these scales squash them into a
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// bounded [-1, +1] match via tanh, so one outlier artist can't compress the
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// rest toward zero (as a per-user max-normalisation would). A weight at the
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// scale value maps to tanh(1) ≈ 0.76 — "clearly a preference."
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const (
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tasteArtistScale = 4.0
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tasteTagScale = 3.0
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tasteArtistShare = 0.7
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tasteTagShare = 0.3
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tasteProfileLimit = 2000 // read cap; profiles are size-capped on write
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)
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// TasteProfile is the read-side view of a user's learned taste: signed
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// weights over artists and genre tags. The zero value (and any unknown
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// artist/tag) contributes 0, so cold-start users get no taste effect.
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type TasteProfile struct {
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artists map[pgtype.UUID]float64
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tags map[string]float64
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}
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// LoadTasteProfile reads the user's taste profile from the taste_profile_*
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// tables (written daily by internal/taste). Returns an empty profile with no
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// error when the user has none.
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func LoadTasteProfile(ctx context.Context, q *dbq.Queries, userID pgtype.UUID) (TasteProfile, error) {
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arts, err := q.ListTasteProfileArtistsForUser(ctx, dbq.ListTasteProfileArtistsForUserParams{
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UserID: userID, Limit: tasteProfileLimit,
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})
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if err != nil {
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return TasteProfile{}, err
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}
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tags, err := q.ListTasteProfileTagsForUser(ctx, dbq.ListTasteProfileTagsForUserParams{
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UserID: userID, Limit: tasteProfileLimit,
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})
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if err != nil {
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return TasteProfile{}, err
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}
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p := TasteProfile{
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artists: make(map[pgtype.UUID]float64, len(arts)),
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tags: make(map[string]float64, len(tags)),
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}
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for _, a := range arts {
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p.artists[a.ArtistID] = a.Weight
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}
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for _, t := range tags {
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p.tags[t.Tag] = t.Weight
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}
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return p, nil
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}
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// Match scores a candidate track's fit to the profile in [-1, +1]: a blend of
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// the artist's taste weight and the average of its genre tags' weights, each
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// tanh-squashed. Absent artist/tags contribute 0.
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func (p TasteProfile) Match(artistID pgtype.UUID, genre *string) float64 {
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a := math.Tanh(p.artists[artistID] / tasteArtistScale)
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var tg float64
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if genre != nil {
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tags := splitGenres(*genre)
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if len(tags) > 0 {
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var sum float64
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for _, t := range tags {
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sum += p.tags[t]
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}
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tg = math.Tanh((sum / float64(len(tags))) / tasteTagScale)
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}
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}
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return clampUnit(tasteArtistShare*a + tasteTagShare*tg)
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}
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// clampUnit constrains x to [-1, 1].
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func clampUnit(x float64) float64 {
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if x < -1 {
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return -1
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}
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if x > 1 {
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return 1
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}
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return x
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}
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