bvandeusen
277898a49a
Add per-user artist-suggestion service ranking out-of-library MBIDs by signal x similarity. Single-CTE SQL collects user likes (5x weight) and recency-decayed plays, joins against artist_similarity_unmatched, and filters in-library candidates plus non-terminal lidarr_requests. The service resolves top-3 attribution seeds to artist names in a batched GetArtistsByIDs call so the UI can render "because you liked X" reasons. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
103 lines
2.9 KiB
Go
103 lines
2.9 KiB
Go
// suggestions.go is the M5c per-user artist-suggestion service. Reads
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// the user's likes + plays, projects them through artist_similarity_unmatched
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// via a single CTE, returns top-N candidates with top-3 attribution seeds
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// resolved to artist names.
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package recommendation
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import (
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"context"
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"fmt"
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"github.com/jackc/pgx/v5/pgtype"
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"github.com/jackc/pgx/v5/pgxpool"
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"git.fabledsword.com/bvandeusen/minstrel/internal/db/dbq"
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)
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// ArtistSuggestion is one ranked candidate with its top-3 attribution seeds.
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type ArtistSuggestion struct {
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MBID string
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Name string
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Score float64
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Attribution []SeedContribution
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}
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// SeedContribution is one of the top-3 contributing seeds for a candidate.
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type SeedContribution struct {
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ArtistID pgtype.UUID
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Name string
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Contribution float64
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IsLiked bool
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PlayCount int64
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}
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// SuggestArtists returns top-N artist suggestions for the user. limit is
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// capped at 50 (default 12 when out of range); halfLifeDays is the
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// recency-decay half-life for plays (default 30, operator-tunable).
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func SuggestArtists(ctx context.Context, pool *pgxpool.Pool, userID pgtype.UUID, halfLifeDays float64, limit int) ([]ArtistSuggestion, error) {
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if limit <= 0 || limit > 50 {
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limit = 12
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}
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if halfLifeDays <= 0 {
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halfLifeDays = 30
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}
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q := dbq.New(pool)
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rows, err := q.SuggestArtistsForUser(ctx, dbq.SuggestArtistsForUserParams{
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UserID: userID,
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Column2: halfLifeDays,
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Limit: int32(limit),
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})
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if err != nil {
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return nil, fmt.Errorf("suggest: query: %w", err)
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}
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if len(rows) == 0 {
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return []ArtistSuggestion{}, nil
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}
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// Collect the union of top-3 seed IDs across all rows for one batched
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// name lookup. pgtype.UUID is a comparable struct so it works as a map
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// key directly.
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seedSet := make(map[pgtype.UUID]struct{}, len(rows)*3)
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for _, r := range rows {
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for _, sid := range r.TopSeedIds {
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seedSet[sid] = struct{}{}
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}
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}
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seedIDs := make([]pgtype.UUID, 0, len(seedSet))
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for id := range seedSet {
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seedIDs = append(seedIDs, id)
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}
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artists, err := q.GetArtistsByIDs(ctx, seedIDs)
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if err != nil {
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return nil, fmt.Errorf("suggest: resolve seeds: %w", err)
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}
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nameByID := make(map[pgtype.UUID]string, len(artists))
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for _, a := range artists {
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nameByID[a.ID] = a.Name
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}
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out := make([]ArtistSuggestion, 0, len(rows))
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for _, r := range rows {
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attribution := make([]SeedContribution, 0, len(r.TopSeedIds))
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for i, sid := range r.TopSeedIds {
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if i >= len(r.TopContributions) || i >= len(r.TopIsLiked) || i >= len(r.TopPlayCounts) {
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break
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}
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attribution = append(attribution, SeedContribution{
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ArtistID: sid,
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Name: nameByID[sid],
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Contribution: r.TopContributions[i],
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IsLiked: r.TopIsLiked[i],
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PlayCount: r.TopPlayCounts[i],
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})
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}
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out = append(out, ArtistSuggestion{
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MBID: r.CandidateMbid,
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Name: r.CandidateName,
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Score: r.TotalScore,
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Attribution: attribution,
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})
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}
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return out, nil
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}
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