feat(taste): household co-play similarity — #1533

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>

internal/db/dbq/coplay.sql.go

@@ -0,0 +1,78 @@
+// Code generated by sqlc. DO NOT EDIT.
+// versions:
+//   sqlc v1.31.1
+// source: coplay.sql
+
+package dbq
+
+import (
+	"context"
+)
+
+const deleteArtistCoplayEdges = `-- name: DeleteArtistCoplayEdges :exec
+
+DELETE FROM artist_similarity WHERE source = 'user_cooccurrence'
+`
+
+// Household co-play similarity (#1533, milestone #160 Opt 5). Minstrel is a
+// single shared-library, multi-user server (no per-user library ACL), so the
+// "household" is the whole instance's user set. These queries recompute
+// artist–artist co-occurrence edges from play_events and store them in
+// artist_similarity under the pre-provisioned source = 'user_cooccurrence'
+// (whitelisted in the 0009 CHECK from day one). A periodic worker DELETEs then
+// re-INSERTs so edges that fall below threshold disappear. Single-user servers
+// produce no edges (the >= 2 co-player gate), so the arm is empty there.
+func (q *Queries) DeleteArtistCoplayEdges(ctx context.Context) error {
+	_, err := q.db.Exec(ctx, deleteArtistCoplayEdges)
+	return err
+}
+
+const insertArtistCoplayEdges = `-- name: InsertArtistCoplayEdges :exec
+WITH user_artists AS (
+    SELECT DISTINCT pe.user_id, t.artist_id
+    FROM play_events pe
+    JOIN tracks t ON t.id = pe.track_id
+    WHERE pe.was_skipped = false
+      AND pe.started_at > now() - interval '365 days'
+),
+artist_players AS (
+    SELECT artist_id, count(*)::float8 AS players
+    FROM user_artists
+    GROUP BY artist_id
+),
+pairs AS (
+    SELECT ua.artist_id AS a_id,
+           ub.artist_id AS b_id,
+           count(*)::float8 AS coplayers
+    FROM user_artists ua
+    JOIN user_artists ub
+      ON ua.user_id = ub.user_id AND ua.artist_id <> ub.artist_id
+    GROUP BY ua.artist_id, ub.artist_id
+    HAVING count(*) >= 2
+),
+scored AS (
+    SELECT p.a_id, p.b_id,
+           p.coplayers / (pa.players + pb.players - p.coplayers) AS score
+    FROM pairs p
+    JOIN artist_players pa ON pa.artist_id = p.a_id
+    JOIN artist_players pb ON pb.artist_id = p.b_id
+)
+INSERT INTO artist_similarity (artist_a_id, artist_b_id, score, source, fetched_at)
+SELECT a_id, b_id, score, 'user_cooccurrence', now()
+FROM scored
+WHERE score >= $1
+ON CONFLICT (artist_a_id, artist_b_id, source)
+DO UPDATE SET score = EXCLUDED.score, fetched_at = EXCLUDED.fetched_at
+`
+
+// Two artists are "co-played" when the same users play both. score is the
+// Jaccard of their distinct-player sets — coplayers / (playersA + playersB −
+// coplayers) in (0,1] — which controls for globally-popular artists (an artist
+// everyone plays would otherwise co-occur with everything). Only pairs with
+// >= 2 distinct co-players AND Jaccard >= $1 (a floor that both prunes weak
+// edges and self-limits hub artists, whose large denominators drag their
+// Jaccard down) are kept. Completed plays only, 365-day window.
+func (q *Queries) InsertArtistCoplayEdges(ctx context.Context, score float64) error {
+	_, err := q.db.Exec(ctx, insertArtistCoplayEdges, score)
+	return err
+}

internal/db/dbq/recommendation.sql.go

@@ -835,6 +835,22 @@ taste_overlap AS (
     ORDER BY tpa.weight DESC, t.id
     LIMIT $10
 ),
+coplay_artists AS (
+    -- Household co-play (#1533): tracks by artists co-played across the
+    -- instance with the seed's artist (source='user_cooccurrence', built by
+    -- the coplay worker). Mirrors similar_artists but from local co-occurrence
+    -- instead of ListenBrainz; empty on single-user servers. Same 0.5 damp as
+    -- similar_artists since it's artist-level.
+    SELECT t.id AS track_id, asim.score * 0.5 AS sim_score
+    FROM artist_similarity asim
+    JOIN tracks t ON t.artist_id = asim.artist_b_id
+    JOIN seed_artist sa ON asim.artist_a_id = sa.artist_id
+    WHERE asim.source = 'user_cooccurrence'
+      AND t.id NOT IN (SELECT id FROM excluded_ids)
+      AND t.id <> $2
+    ORDER BY asim.score DESC, random()
+    LIMIT $11
+),
 random_fill AS (
     SELECT t.id AS track_id, 0.0::float8 AS sim_score
     FROM tracks t
@@ -846,6 +862,7 @@ random_fill AS (
           UNION SELECT track_id FROM tag_overlap
           UNION SELECT track_id FROM likes_overlap
           UNION SELECT track_id FROM taste_overlap
+          UNION SELECT track_id FROM coplay_artists
       )
     ORDER BY random()
     LIMIT $9
@@ -864,6 +881,7 @@ FROM (
     UNION ALL SELECT track_id, sim_score FROM tag_overlap
     UNION ALL SELECT track_id, sim_score FROM likes_overlap
     UNION ALL SELECT track_id, sim_score FROM taste_overlap
+    UNION ALL SELECT track_id, sim_score FROM coplay_artists
     UNION ALL SELECT track_id, sim_score FROM random_fill
 ) u
 JOIN tracks t ON t.id = u.track_id
@@ -894,6 +912,7 @@ type LoadRadioCandidatesV2Params struct {
 	Limit_4 int32
 	Limit_5 int32
 	Limit_6 int32
+	Limit_7 int32
 }
 
 type LoadRadioCandidatesV2Row struct {
@@ -914,7 +933,9 @@ type LoadRadioCandidatesV2Row struct {
 //	$10 taste_overlap K (#796 phase 2b — tracks by the user's top
 //	positively-weighted taste-profile artists, so taste-relevant tracks
 //	enter the pool even when the similarity/random arms miss them; scored
-//	in Go via TasteMatch, so sim_score here is 0 pool-inclusion).
+//	in Go via TasteMatch, so sim_score here is 0 pool-inclusion),
+//	$11 coplay_artists K (#1533 — tracks by artists co-played across the
+//	instance with the seed's artist; source='user_cooccurrence').
 //
 // Returns same shape as LoadRadioCandidates plus similarity_score column.
 func (q *Queries) LoadRadioCandidatesV2(ctx context.Context, arg LoadRadioCandidatesV2Params) ([]LoadRadioCandidatesV2Row, error) {
@@ -929,6 +950,7 @@ func (q *Queries) LoadRadioCandidatesV2(ctx context.Context, arg LoadRadioCandid
 		arg.Limit_4,
 		arg.Limit_5,
 		arg.Limit_6,
+		arg.Limit_7,
 	)
 	if err != nil {
 		return nil, err