-- name: LoadRadioCandidates :many -- Returns all tracks except the seed and any played by the user within -- the last $3 hours, joined with the stats needed for scoring: -- is_liked — boolean from general_likes for this user -- last_played_at — max(play_events.started_at) for this user/track -- play_count — count of play_events for this user/track -- skip_count — play_events where was_skipped=true SELECT sqlc.embed(t), (l.user_id IS NOT NULL)::bool AS is_liked, pe.last_played_at::timestamptz AS last_played_at, pe.play_count, pe.skip_count FROM tracks t LEFT JOIN general_likes l ON l.user_id = $1 AND l.track_id = t.id LEFT JOIN LATERAL ( SELECT max(started_at) AS last_played_at, count(*) AS play_count, count(*) FILTER (WHERE was_skipped) AS skip_count FROM play_events WHERE user_id = $1 AND track_id = t.id ) pe ON true WHERE t.id <> $2 AND NOT EXISTS ( SELECT 1 FROM play_events WHERE user_id = $1 AND track_id = t.id AND started_at > now() - $3 * interval '1 hour' ) AND NOT EXISTS ( SELECT 1 FROM lidarr_quarantine q WHERE q.user_id = $1 AND q.track_id = t.id ); -- name: LoadRadioCandidatesV2 :many -- M4c: similarity-driven candidate pool. 5-way UNION: -- $1 user_id, $2 seed_track_id, $3 recently_played_hours, -- $4 exclude (uuid[]), $5 lb_similar K, $6 similar_artists K, -- $7 tag_overlap K, $8 likes_overlap K, $9 random_fill K. -- Returns same shape as LoadRadioCandidates plus similarity_score column. WITH seed_artist AS ( SELECT artist_id FROM tracks WHERE tracks.id = $2 ), seed_tags AS ( SELECT trim(g) AS tag FROM tracks t LEFT JOIN LATERAL regexp_split_to_table(coalesce(t.genre, ''), '[;,]') AS g(tag) ON true WHERE t.id = $2 AND trim(g) <> '' ), excluded_ids AS ( SELECT unnest($4::uuid[]) AS id UNION ALL SELECT pe.track_id AS id FROM play_events pe WHERE pe.user_id = $1 AND pe.started_at > now() - $3 * interval '1 hour' UNION ALL SELECT q.track_id AS id FROM lidarr_quarantine q WHERE q.user_id = $1 ), lb_similar AS ( SELECT ts.track_b_id AS track_id, ts.score AS sim_score FROM track_similarity ts WHERE ts.track_a_id = $2 AND ts.source = 'listenbrainz' AND ts.track_b_id NOT IN (SELECT id FROM excluded_ids) ORDER BY ts.score DESC LIMIT $5 ), similar_artists AS ( 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 = 'listenbrainz' AND t.id NOT IN (SELECT id FROM excluded_ids) ORDER BY asim.score DESC, random() LIMIT $6 ), tag_overlap AS ( SELECT t.id AS track_id, (count(DISTINCT trim(g))::float8 / GREATEST((SELECT count(*) FROM seed_tags), 1)) AS sim_score FROM tracks t LEFT JOIN LATERAL regexp_split_to_table(coalesce(t.genre, ''), '[;,]') AS g_split(g) ON true WHERE trim(g_split.g) IN (SELECT tag FROM seed_tags) AND t.id NOT IN (SELECT id FROM excluded_ids) AND t.id <> $2 GROUP BY t.id HAVING count(DISTINCT trim(g_split.g)) > 0 ORDER BY sim_score DESC LIMIT $7 ), likes_overlap AS ( SELECT gl.track_id, 0.6::float8 AS sim_score FROM general_likes gl WHERE gl.user_id = $1 AND gl.track_id NOT IN (SELECT id FROM excluded_ids) AND EXISTS ( SELECT 1 FROM tracks t LEFT JOIN LATERAL regexp_split_to_table(coalesce(t.genre, ''), '[;,]') AS g_overlap(g) ON true WHERE t.id = gl.track_id AND trim(g_overlap.g) IN (SELECT tag FROM seed_tags) ) ORDER BY random() LIMIT $8 ), random_fill AS ( SELECT t.id AS track_id, 0.0::float8 AS sim_score FROM tracks t WHERE t.id NOT IN (SELECT id FROM excluded_ids) AND t.id <> $2 AND t.id NOT IN ( SELECT track_id FROM lb_similar UNION SELECT track_id FROM similar_artists UNION SELECT track_id FROM tag_overlap UNION SELECT track_id FROM likes_overlap ) ORDER BY random() LIMIT $9 ) SELECT sqlc.embed(t), (l.user_id IS NOT NULL)::bool AS is_liked, pe.last_played_at::timestamptz AS last_played_at, pe.play_count, pe.skip_count, COALESCE(max(u.sim_score), 0.0) AS similarity_score FROM ( SELECT track_id, sim_score FROM lb_similar UNION ALL SELECT track_id, sim_score FROM similar_artists 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 random_fill ) u JOIN tracks t ON t.id = u.track_id LEFT JOIN general_likes l ON l.user_id = $1 AND l.track_id = t.id LEFT JOIN LATERAL ( SELECT max(started_at) AS last_played_at, count(*) AS play_count, count(*) FILTER (WHERE was_skipped) AS skip_count FROM play_events WHERE user_id = $1 AND track_id = t.id ) pe ON true GROUP BY t.id, t.title, t.album_id, t.artist_id, t.duration_ms, t.file_path, t.file_format, t.file_size, t.bitrate, t.track_number, t.disc_number, t.mbid, t.genre, t.added_at, t.updated_at, l.user_id, pe.last_played_at, pe.play_count, pe.skip_count; -- name: SuggestArtistsForUser :many -- M5c: per-user artist suggestions ranked by signal x similarity. The -- seeds CTE collects the user's likes (x5) plus recency-decayed plays -- (exp(-age_days / $2)). The contributions CTE joins those seeds against -- artist_similarity_unmatched and filters out candidates already in -- library or already in a non-terminal lidarr_request. The outer SELECT -- aggregates per candidate, returning the top-3 contributing seeds for -- attribution. $1=user_id, $2=half_life_days, $3=limit. WITH seeds AS ( SELECT a.id AS artist_id, 5.0 * (CASE WHEN gla.artist_id IS NOT NULL THEN 1 ELSE 0 END) + COALESCE(SUM(EXP(- EXTRACT(epoch FROM now() - pe.started_at) / ($2::float8 * 86400.0))), 0) AS signal, (gla.artist_id IS NOT NULL) AS is_liked, COUNT(pe.id)::bigint AS play_count FROM artists a LEFT JOIN general_likes_artists gla ON gla.artist_id = a.id AND gla.user_id = $1 LEFT JOIN tracks t ON t.artist_id = a.id LEFT JOIN play_events pe ON pe.track_id = t.id AND pe.user_id = $1 WHERE gla.artist_id IS NOT NULL OR pe.id IS NOT NULL GROUP BY a.id, gla.artist_id ), contributions AS ( SELECT u.candidate_mbid, u.candidate_name, seeds.artist_id AS seed_id, seeds.is_liked, seeds.play_count, seeds.signal * u.score AS contribution FROM artist_similarity_unmatched u JOIN seeds ON seeds.artist_id = u.seed_artist_id WHERE NOT EXISTS (SELECT 1 FROM artists WHERE mbid = u.candidate_mbid) AND NOT EXISTS ( SELECT 1 FROM lidarr_requests r WHERE r.user_id = $1 AND r.lidarr_artist_mbid = u.candidate_mbid AND r.status NOT IN ('rejected', 'failed') ) ) SELECT candidate_mbid, candidate_name, SUM(contribution)::float8 AS total_score, ((array_agg(seed_id ORDER BY contribution DESC))[1:3])::uuid[] AS top_seed_ids, ((array_agg(contribution ORDER BY contribution DESC))[1:3])::float8[] AS top_contributions, ((array_agg(is_liked ORDER BY contribution DESC))[1:3])::boolean[] AS top_is_liked, ((array_agg(play_count ORDER BY contribution DESC))[1:3])::bigint[] AS top_play_counts FROM contributions GROUP BY candidate_mbid, candidate_name ORDER BY total_score DESC LIMIT $3; -- name: ListMostPlayedTracksForUser :many -- M6a: top-N tracks by completed-play count for the user. was_skipped -- excludes skips so a user spamming next doesn't fabricate a top track. -- Quarantined tracks (per-user soft-hide from M5b) are filtered out. SELECT sqlc.embed(t), albums.title AS album_title, artists.name AS artist_name FROM tracks t JOIN albums ON albums.id = t.album_id JOIN artists ON artists.id = t.artist_id JOIN play_events pe ON pe.track_id = t.id WHERE pe.user_id = $1 AND pe.was_skipped = false AND NOT EXISTS ( SELECT 1 FROM lidarr_quarantine q WHERE q.user_id = $1 AND q.track_id = t.id ) GROUP BY t.id, t.title, t.album_id, t.artist_id, t.duration_ms, t.file_path, t.file_format, t.file_size, t.bitrate, t.track_number, t.disc_number, t.mbid, t.genre, t.added_at, t.updated_at, albums.title, artists.name ORDER BY count(*) DESC, t.id LIMIT $2; -- name: ListLastPlayedArtistsForUser :many -- M6a: artists ranked by max(play_events.started_at) for the user, with -- a derived cover_album_id via a representative-album lateral join (most -- recent album that has cover_art_path set). album_count joined for the -- ArtistRef wire shape. SELECT sqlc.embed(a), cov.id AS cover_album_id, cnt.album_count::bigint AS album_count, max_started.started_at::timestamptz AS last_played_at FROM artists a JOIN LATERAL ( SELECT max(pe.started_at) AS started_at FROM play_events pe JOIN tracks t ON t.id = pe.track_id WHERE pe.user_id = $1 AND t.artist_id = a.id ) max_started ON max_started.started_at IS NOT NULL LEFT JOIN LATERAL ( SELECT id FROM albums WHERE artist_id = a.id AND cover_art_path IS NOT NULL ORDER BY created_at DESC LIMIT 1 ) cov ON true LEFT JOIN LATERAL ( SELECT count(*) AS album_count FROM albums WHERE artist_id = a.id ) cnt ON true ORDER BY max_started.started_at DESC, a.id LIMIT $2; -- name: ListRediscoverAlbumsForUser :many -- M6a: albums liked >30 days ago AND not played in the last 14 days, -- ordered by longest-since-last-play first. The HAVING clause uses an -- epoch sentinel so albums with NO plays count as eligible (their -- "last play" is treated as 1970, which is always >14 days ago). WITH eligible AS ( SELECT al.id AS album_id, gla.liked_at, max(pe.started_at) AS last_played FROM general_likes_albums gla JOIN albums al ON al.id = gla.album_id LEFT JOIN tracks t ON t.album_id = al.id LEFT JOIN play_events pe ON pe.track_id = t.id AND pe.user_id = $1 WHERE gla.user_id = $1 AND gla.liked_at < now() - interval '30 days' GROUP BY al.id, gla.liked_at HAVING COALESCE(max(pe.started_at), '1970-01-01'::timestamptz) < now() - interval '14 days' ) SELECT sqlc.embed(albums), artists.name AS artist_name FROM eligible e JOIN albums ON albums.id = e.album_id JOIN artists ON artists.id = albums.artist_id ORDER BY (now() - COALESCE(e.last_played, e.liked_at)) DESC, albums.id LIMIT $2; -- name: ListRediscoverAlbumsFallbackForUser :many -- M6a: random sample of liked albums for the user. The Go service uses -- this to top up the rediscover row when ListRediscoverAlbumsForUser -- returns fewer than `limit` rows. SELECT sqlc.embed(albums), artists.name AS artist_name FROM general_likes_albums gla JOIN albums ON albums.id = gla.album_id JOIN artists ON artists.id = albums.artist_id WHERE gla.user_id = $1 ORDER BY random() LIMIT $2; -- name: ListRediscoverArtistsForUser :many -- M6a: artists liked >30 days ago AND none of their tracks played in the -- last 14 days, ordered by longest-since-last-play. cover_album_id is -- derived from a representative album (LEFT JOIN LATERAL). WITH eligible AS ( SELECT a.id AS artist_id, gla.liked_at, max(pe.started_at) AS last_played FROM general_likes_artists gla JOIN artists a ON a.id = gla.artist_id LEFT JOIN tracks t ON t.artist_id = a.id LEFT JOIN play_events pe ON pe.track_id = t.id AND pe.user_id = $1 WHERE gla.user_id = $1 AND gla.liked_at < now() - interval '30 days' GROUP BY a.id, gla.liked_at HAVING COALESCE(max(pe.started_at), '1970-01-01'::timestamptz) < now() - interval '14 days' ) SELECT sqlc.embed(artists), cov.id AS cover_album_id, cnt.album_count::bigint AS album_count FROM eligible e JOIN artists ON artists.id = e.artist_id LEFT JOIN LATERAL ( SELECT id FROM albums WHERE artist_id = artists.id AND cover_art_path IS NOT NULL ORDER BY created_at DESC LIMIT 1 ) cov ON true LEFT JOIN LATERAL ( SELECT count(*) AS album_count FROM albums WHERE artist_id = artists.id ) cnt ON true ORDER BY (now() - COALESCE(e.last_played, e.liked_at)) DESC, artists.id LIMIT $2; -- name: ListRediscoverArtistsFallbackForUser :many SELECT sqlc.embed(artists), cov.id AS cover_album_id, cnt.album_count::bigint AS album_count FROM general_likes_artists gla JOIN artists ON artists.id = gla.artist_id LEFT JOIN LATERAL ( SELECT id FROM albums WHERE artist_id = artists.id AND cover_art_path IS NOT NULL ORDER BY created_at DESC LIMIT 1 ) cov ON true LEFT JOIN LATERAL ( SELECT count(*) AS album_count FROM albums WHERE artist_id = artists.id ) cnt ON true WHERE gla.user_id = $1 ORDER BY random() LIMIT $2;