minstrel/internal/db/dbq/recommendation.sql.go

// Code generated by sqlc. DO NOT EDIT.
// versions:
//   sqlc v1.31.1
// source: recommendation.sql

package dbq

import (
	"context"

	"github.com/jackc/pgx/v5/pgtype"
)

const listArtistContextPlayCountsForUser = `-- name: ListArtistContextPlayCountsForUser :many
WITH tz AS (
    SELECT COALESCE(NULLIF(u.timezone, ''), 'UTC') AS zone
    FROM users u WHERE u.id = $1
),
now_cell AS (
    SELECT
        CASE
            WHEN EXTRACT(hour FROM now() AT TIME ZONE tz.zone) < 5  THEN 3
            WHEN EXTRACT(hour FROM now() AT TIME ZONE tz.zone) < 12 THEN 0
            WHEN EXTRACT(hour FROM now() AT TIME ZONE tz.zone) < 17 THEN 1
            WHEN EXTRACT(hour FROM now() AT TIME ZONE tz.zone) < 22 THEN 2
            ELSE 3
        END AS daypart,
        (EXTRACT(isodow FROM now() AT TIME ZONE tz.zone) >= 6) AS is_weekend
    FROM tz
),
plays AS (
    SELECT t.artist_id,
           CASE
               WHEN EXTRACT(hour FROM pe.started_at AT TIME ZONE tz.zone) < 5  THEN 3
               WHEN EXTRACT(hour FROM pe.started_at AT TIME ZONE tz.zone) < 12 THEN 0
               WHEN EXTRACT(hour FROM pe.started_at AT TIME ZONE tz.zone) < 17 THEN 1
               WHEN EXTRACT(hour FROM pe.started_at AT TIME ZONE tz.zone) < 22 THEN 2
               ELSE 3
           END AS daypart,
           (EXTRACT(isodow FROM pe.started_at AT TIME ZONE tz.zone) >= 6) AS is_weekend
    FROM play_events pe
    JOIN tracks t ON t.id = pe.track_id
    CROSS JOIN tz
    WHERE pe.user_id = $1
      AND pe.was_skipped = false
      AND pe.started_at > now() - interval '365 days'
)
SELECT p.artist_id,
       count(*) AS total_plays,
       count(*) FILTER (
           WHERE p.daypart = (SELECT daypart FROM now_cell)
             AND p.is_weekend = (SELECT is_weekend FROM now_cell)
       ) AS cell_plays
FROM plays p
GROUP BY p.artist_id
`

type ListArtistContextPlayCountsForUserRow struct {
	ArtistID   pgtype.UUID
	TotalPlays int64
	CellPlays  int64
}

// Per-artist completed-play counts split by whether each play falls in the
// CURRENT daypart × weekday-type cell, in the user's local timezone (#1531).
// Feeds the context-affinity scoring term: an artist whose plays concentrate
// in the current cell (vs the user's overall baseline, computed Go-side from
// these rows) gets boosted right now. Skips excluded; a 365-day window bounds
// cost. Daypart buckets: night [22,5) morning [5,12) afternoon [12,17)
// evening [17,22). Weekend = ISO days 6–7 (Sat/Sun).
func (q *Queries) ListArtistContextPlayCountsForUser(ctx context.Context, id pgtype.UUID) ([]ListArtistContextPlayCountsForUserRow, error) {
	rows, err := q.db.Query(ctx, listArtistContextPlayCountsForUser, id)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListArtistContextPlayCountsForUserRow
	for rows.Next() {
		var i ListArtistContextPlayCountsForUserRow
		if err := rows.Scan(&i.ArtistID, &i.TotalPlays, &i.CellPlays); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const listLastPlayedArtistsForUser = `-- name: ListLastPlayedArtistsForUser :many
WITH user_plays AS (
    SELECT t.artist_id, max(pe.started_at) AS last_started
    FROM play_events pe
    JOIN tracks t ON t.id = pe.track_id
    WHERE pe.user_id = $1
    GROUP BY t.artist_id
)
SELECT a.id, a.name, a.sort_name, a.mbid, a.created_at, a.updated_at, a.artist_thumb_path, a.artist_fanart_path, a.artist_art_source, a.artist_art_sources_version,
       cov.id AS cover_album_id,
       cnt.album_count::bigint AS album_count,
       up.last_started::timestamptz AS last_played_at
FROM user_plays up
JOIN artists a ON a.id = up.artist_id
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 up.last_started DESC, a.id
LIMIT $2
`

type ListLastPlayedArtistsForUserParams struct {
	UserID pgtype.UUID
	Limit  int32
}

type ListLastPlayedArtistsForUserRow struct {
	Artist       Artist
	CoverAlbumID pgtype.UUID
	AlbumCount   int64
	LastPlayedAt pgtype.Timestamptz
}

// 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.
//
// Earlier shape iterated `FROM artists a` and ran a LATERAL play_events
// subquery per artist — O(total_artists) plan even for users with a
// handful of plays. New shape aggregates the user's plays by artist
// via the play_events → tracks join up front (uses
// play_events_user_track_idx + tracks pkey lookups), then attaches
// the artist row and lateral cover/count subqueries only for the
// artists that actually appear. Distinct-artists set is small for a
// typical user, so cost is bounded by play history not library size.
func (q *Queries) ListLastPlayedArtistsForUser(ctx context.Context, arg ListLastPlayedArtistsForUserParams) ([]ListLastPlayedArtistsForUserRow, error) {
	rows, err := q.db.Query(ctx, listLastPlayedArtistsForUser, arg.UserID, arg.Limit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListLastPlayedArtistsForUserRow
	for rows.Next() {
		var i ListLastPlayedArtistsForUserRow
		if err := rows.Scan(
			&i.Artist.ID,
			&i.Artist.Name,
			&i.Artist.SortName,
			&i.Artist.Mbid,
			&i.Artist.CreatedAt,
			&i.Artist.UpdatedAt,
			&i.Artist.ArtistThumbPath,
			&i.Artist.ArtistFanartPath,
			&i.Artist.ArtistArtSource,
			&i.Artist.ArtistArtSourcesVersion,
			&i.CoverAlbumID,
			&i.AlbumCount,
			&i.LastPlayedAt,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const listMostPlayedTracksForArtist = `-- name: ListMostPlayedTracksForArtist :many
WITH plays AS (
    SELECT track_id, count(*) AS cnt
    FROM play_events
    WHERE user_id = $2 AND was_skipped = false
    GROUP BY track_id
)
SELECT t.id, t.title, t.album_id, t.artist_id, t.track_number, t.disc_number, t.duration_ms, t.file_path, t.file_size, t.file_format, t.bitrate, t.mbid, t.genre, t.added_at, t.updated_at, t.tag_source, t.tag_sources_version,
       albums.title AS album_title,
       artists.name AS artist_name
FROM plays p
JOIN tracks t   ON t.id = p.track_id
JOIN albums     ON albums.id  = t.album_id
JOIN artists    ON artists.id = t.artist_id
WHERE t.artist_id = $1
  AND NOT EXISTS (
      SELECT 1 FROM lidarr_quarantine q
      WHERE q.user_id = $2 AND q.track_id = t.id
  )
ORDER BY p.cnt DESC, t.id
LIMIT $3
`

type ListMostPlayedTracksForArtistParams struct {
	ArtistID    pgtype.UUID
	UserID      pgtype.UUID
	ResultLimit int32
}

type ListMostPlayedTracksForArtistRow struct {
	Track      Track
	AlbumTitle string
	ArtistName string
}

// Top tracks for one artist by this user's completed-play count (skips
// excluded, quarantine filtered). Same projection as
// ListMostPlayedTracksForUser plus an artist_id filter, so the handler
// reuses trackRefFrom(row.Track, row.AlbumTitle, row.ArtistName).
func (q *Queries) ListMostPlayedTracksForArtist(ctx context.Context, arg ListMostPlayedTracksForArtistParams) ([]ListMostPlayedTracksForArtistRow, error) {
	rows, err := q.db.Query(ctx, listMostPlayedTracksForArtist, arg.ArtistID, arg.UserID, arg.ResultLimit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListMostPlayedTracksForArtistRow
	for rows.Next() {
		var i ListMostPlayedTracksForArtistRow
		if err := rows.Scan(
			&i.Track.ID,
			&i.Track.Title,
			&i.Track.AlbumID,
			&i.Track.ArtistID,
			&i.Track.TrackNumber,
			&i.Track.DiscNumber,
			&i.Track.DurationMs,
			&i.Track.FilePath,
			&i.Track.FileSize,
			&i.Track.FileFormat,
			&i.Track.Bitrate,
			&i.Track.Mbid,
			&i.Track.Genre,
			&i.Track.AddedAt,
			&i.Track.UpdatedAt,
			&i.Track.TagSource,
			&i.Track.TagSourcesVersion,
			&i.AlbumTitle,
			&i.ArtistName,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const listMostPlayedTracksForUser = `-- name: ListMostPlayedTracksForUser :many
WITH plays AS (
    SELECT track_id, count(*) AS cnt
    FROM play_events
    WHERE user_id = $1 AND was_skipped = false
    GROUP BY track_id
)
SELECT t.id, t.title, t.album_id, t.artist_id, t.track_number, t.disc_number, t.duration_ms, t.file_path, t.file_size, t.file_format, t.bitrate, t.mbid, t.genre, t.added_at, t.updated_at, t.tag_source, t.tag_sources_version,
       albums.title AS album_title,
       artists.name AS artist_name
FROM plays p
JOIN tracks t   ON t.id = p.track_id
JOIN albums     ON albums.id  = t.album_id
JOIN artists    ON artists.id = t.artist_id
WHERE NOT EXISTS (
    SELECT 1 FROM lidarr_quarantine q
    WHERE q.user_id = $1 AND q.track_id = t.id
)
ORDER BY p.cnt DESC, t.id
LIMIT $2
`

type ListMostPlayedTracksForUserParams struct {
	UserID pgtype.UUID
	Limit  int32
}

type ListMostPlayedTracksForUserRow struct {
	Track      Track
	AlbumTitle string
	ArtistName string
}

// 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.
//
// Aggregate play_events first (uses play_events_user_track_idx) and
// join through tracks/albums/artists only for the survivors. Earlier
// shape did the join across every play_event row before grouping —
// O(plays) instead of O(distinct tracks).
func (q *Queries) ListMostPlayedTracksForUser(ctx context.Context, arg ListMostPlayedTracksForUserParams) ([]ListMostPlayedTracksForUserRow, error) {
	rows, err := q.db.Query(ctx, listMostPlayedTracksForUser, arg.UserID, arg.Limit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListMostPlayedTracksForUserRow
	for rows.Next() {
		var i ListMostPlayedTracksForUserRow
		if err := rows.Scan(
			&i.Track.ID,
			&i.Track.Title,
			&i.Track.AlbumID,
			&i.Track.ArtistID,
			&i.Track.TrackNumber,
			&i.Track.DiscNumber,
			&i.Track.DurationMs,
			&i.Track.FilePath,
			&i.Track.FileSize,
			&i.Track.FileFormat,
			&i.Track.Bitrate,
			&i.Track.Mbid,
			&i.Track.Genre,
			&i.Track.AddedAt,
			&i.Track.UpdatedAt,
			&i.Track.TagSource,
			&i.Track.TagSourcesVersion,
			&i.AlbumTitle,
			&i.ArtistName,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const listRediscoverAlbumsFallbackForUser = `-- name: ListRediscoverAlbumsFallbackForUser :many
SELECT albums.id, albums.title, albums.sort_title, albums.artist_id, albums.release_date, albums.mbid, albums.cover_art_path, albums.created_at, albums.updated_at, albums.cover_art_source, albums.cover_art_sources_version, 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 md5(albums.id::text || current_date::text)
LIMIT $2
`

type ListRediscoverAlbumsFallbackForUserParams struct {
	UserID pgtype.UUID
	Limit  int32
}

type ListRediscoverAlbumsFallbackForUserRow struct {
	Album      Album
	ArtistName string
}

// Daily-stable random sample of liked albums for the user. The Go
// service uses this to top up the rediscover row when the primary
// eligibility query returns fewer than the inner limit. Same daily
// hash ordering as the primary so the fallback rows stay stable
// through the day instead of reshuffling on every refresh. Hash
// omits user_id so sqlc can keep the user_id parameter UUID-typed
// (a $1::text cast would force the param to string); eligibility
// already differs per user, so output sets differ regardless.
func (q *Queries) ListRediscoverAlbumsFallbackForUser(ctx context.Context, arg ListRediscoverAlbumsFallbackForUserParams) ([]ListRediscoverAlbumsFallbackForUserRow, error) {
	rows, err := q.db.Query(ctx, listRediscoverAlbumsFallbackForUser, arg.UserID, arg.Limit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListRediscoverAlbumsFallbackForUserRow
	for rows.Next() {
		var i ListRediscoverAlbumsFallbackForUserRow
		if err := rows.Scan(
			&i.Album.ID,
			&i.Album.Title,
			&i.Album.SortTitle,
			&i.Album.ArtistID,
			&i.Album.ReleaseDate,
			&i.Album.Mbid,
			&i.Album.CoverArtPath,
			&i.Album.CreatedAt,
			&i.Album.UpdatedAt,
			&i.Album.CoverArtSource,
			&i.Album.CoverArtSourcesVersion,
			&i.ArtistName,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const listRediscoverAlbumsForUser = `-- name: ListRediscoverAlbumsForUser :many
WITH liked_signal AS (
    -- Path (a): explicit album-likes >30 days old.
    SELECT al.id AS album_id, gla.liked_at AS like_at
    FROM general_likes_albums gla
    JOIN albums al ON al.id = gla.album_id
    WHERE gla.user_id = $1
      AND gla.liked_at < now() - interval '30 days'
    UNION ALL
    -- Path (b): >=2 liked tracks per album, earliest like >30 days old.
    SELECT t.album_id, MIN(gl.liked_at) AS like_at
    FROM general_likes gl
    JOIN tracks t ON t.id = gl.track_id
    WHERE gl.user_id = $1
    GROUP BY t.album_id
    HAVING COUNT(*) >= 2
       AND MIN(gl.liked_at) < now() - interval '30 days'
),
eligible AS (
    SELECT ls.album_id,
           MIN(ls.like_at) AS like_at,
           max(pe.started_at) AS last_played
    FROM liked_signal ls
    LEFT JOIN tracks t       ON t.album_id = ls.album_id
    LEFT JOIN play_events pe ON pe.track_id = t.id AND pe.user_id = $1
    GROUP BY ls.album_id
    HAVING COALESCE(max(pe.started_at), '1970-01-01'::timestamptz)
           < now() - interval '14 days'
)
SELECT albums.id, albums.title, albums.sort_title, albums.artist_id, albums.release_date, albums.mbid, albums.cover_art_path, albums.created_at, albums.updated_at, albums.cover_art_source, albums.cover_art_sources_version, 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 md5(albums.id::text || current_date::text)
LIMIT $2
`

type ListRediscoverAlbumsForUserParams struct {
	UserID pgtype.UUID
	Limit  int32
}

type ListRediscoverAlbumsForUserRow struct {
	Album      Album
	ArtistName string
}

// Albums eligible for Rediscover via either signal:
//
//	(a) explicit album-like (general_likes_albums) liked >30 days ago, OR
//	(b) >=2 liked tracks from the album (general_likes), where the
//	    earliest such track-like is >30 days ago.
//
// AND not played in the last 14 days. The HAVING epoch sentinel keeps
// albums with NO play history eligible (treated as last-played in 1970).
// Ordering is daily-stable random (md5 of album+user+date hashes),
// so the row rotates at midnight local without re-running per request.
// Final cap + diversity + cross-section dedup land in the Go layer
// (internal/recommendation/home.go).
func (q *Queries) ListRediscoverAlbumsForUser(ctx context.Context, arg ListRediscoverAlbumsForUserParams) ([]ListRediscoverAlbumsForUserRow, error) {
	rows, err := q.db.Query(ctx, listRediscoverAlbumsForUser, arg.UserID, arg.Limit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListRediscoverAlbumsForUserRow
	for rows.Next() {
		var i ListRediscoverAlbumsForUserRow
		if err := rows.Scan(
			&i.Album.ID,
			&i.Album.Title,
			&i.Album.SortTitle,
			&i.Album.ArtistID,
			&i.Album.ReleaseDate,
			&i.Album.Mbid,
			&i.Album.CoverArtPath,
			&i.Album.CreatedAt,
			&i.Album.UpdatedAt,
			&i.Album.CoverArtSource,
			&i.Album.CoverArtSourcesVersion,
			&i.ArtistName,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const listRediscoverArtistsFallbackForUser = `-- name: ListRediscoverArtistsFallbackForUser :many
SELECT artists.id, artists.name, artists.sort_name, artists.mbid, artists.created_at, artists.updated_at, artists.artist_thumb_path, artists.artist_fanart_path, artists.artist_art_source, artists.artist_art_sources_version,
       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 md5(artists.id::text || current_date::text)
LIMIT $2
`

type ListRediscoverArtistsFallbackForUserParams struct {
	UserID pgtype.UUID
	Limit  int32
}

type ListRediscoverArtistsFallbackForUserRow struct {
	Artist       Artist
	CoverAlbumID pgtype.UUID
	AlbumCount   int64
}

// Daily-stable random sample of liked artists, paired with the Go
// top-up logic in HomeData when the primary eligibility query returns
// fewer than the inner limit. Daily hash ordering matches the primary
// (omitting user_id from the hash for the same sqlc-typing reason).
func (q *Queries) ListRediscoverArtistsFallbackForUser(ctx context.Context, arg ListRediscoverArtistsFallbackForUserParams) ([]ListRediscoverArtistsFallbackForUserRow, error) {
	rows, err := q.db.Query(ctx, listRediscoverArtistsFallbackForUser, arg.UserID, arg.Limit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListRediscoverArtistsFallbackForUserRow
	for rows.Next() {
		var i ListRediscoverArtistsFallbackForUserRow
		if err := rows.Scan(
			&i.Artist.ID,
			&i.Artist.Name,
			&i.Artist.SortName,
			&i.Artist.Mbid,
			&i.Artist.CreatedAt,
			&i.Artist.UpdatedAt,
			&i.Artist.ArtistThumbPath,
			&i.Artist.ArtistFanartPath,
			&i.Artist.ArtistArtSource,
			&i.Artist.ArtistArtSourcesVersion,
			&i.CoverAlbumID,
			&i.AlbumCount,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const listRediscoverArtistsForUser = `-- name: ListRediscoverArtistsForUser :many
WITH liked_signal AS (
    SELECT a.id AS artist_id, gla.liked_at AS like_at
    FROM general_likes_artists gla
    JOIN artists a ON a.id = gla.artist_id
    WHERE gla.user_id = $1
      AND gla.liked_at < now() - interval '30 days'
    UNION ALL
    SELECT t.artist_id, MIN(gl.liked_at) AS like_at
    FROM general_likes gl
    JOIN tracks t ON t.id = gl.track_id
    WHERE gl.user_id = $1
    GROUP BY t.artist_id
    HAVING COUNT(*) >= 3
       AND MIN(gl.liked_at) < now() - interval '30 days'
),
eligible AS (
    SELECT ls.artist_id,
           MIN(ls.like_at) AS like_at,
           max(pe.started_at) AS last_played
    FROM liked_signal ls
    LEFT JOIN tracks t       ON t.artist_id = ls.artist_id
    LEFT JOIN play_events pe ON pe.track_id = t.id AND pe.user_id = $1
    GROUP BY ls.artist_id
    HAVING COALESCE(max(pe.started_at), '1970-01-01'::timestamptz)
           < now() - interval '14 days'
)
SELECT artists.id, artists.name, artists.sort_name, artists.mbid, artists.created_at, artists.updated_at, artists.artist_thumb_path, artists.artist_fanart_path, artists.artist_art_source, artists.artist_art_sources_version,
       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 md5(artists.id::text || current_date::text)
LIMIT $2
`

type ListRediscoverArtistsForUserParams struct {
	UserID pgtype.UUID
	Limit  int32
}

type ListRediscoverArtistsForUserRow struct {
	Artist       Artist
	CoverAlbumID pgtype.UUID
	AlbumCount   int64
}

// Artists eligible for Rediscover via either signal:
//
//	(a) explicit artist-like (general_likes_artists) liked >30 days ago, OR
//	(b) >=3 liked tracks from the artist (general_likes), where the
//	    earliest such track-like is >30 days ago.
//
// AND none of their tracks played in the last 14 days. Higher track
// threshold than the album path (3 vs 2) because artists span many
// releases, so the bar is higher to avoid surfacing one-hit-wonder
// affinities. Ordering is daily-stable random (md5 of artist+user+date
// hashes). cover_album_id derived from a representative album (most
// recently created album with cover_art_path set).
func (q *Queries) ListRediscoverArtistsForUser(ctx context.Context, arg ListRediscoverArtistsForUserParams) ([]ListRediscoverArtistsForUserRow, error) {
	rows, err := q.db.Query(ctx, listRediscoverArtistsForUser, arg.UserID, arg.Limit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []ListRediscoverArtistsForUserRow
	for rows.Next() {
		var i ListRediscoverArtistsForUserRow
		if err := rows.Scan(
			&i.Artist.ID,
			&i.Artist.Name,
			&i.Artist.SortName,
			&i.Artist.Mbid,
			&i.Artist.CreatedAt,
			&i.Artist.UpdatedAt,
			&i.Artist.ArtistThumbPath,
			&i.Artist.ArtistFanartPath,
			&i.Artist.ArtistArtSource,
			&i.Artist.ArtistArtSourcesVersion,
			&i.CoverAlbumID,
			&i.AlbumCount,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const loadRadioCandidates = `-- name: LoadRadioCandidates :many
SELECT
    t.id, t.title, t.album_id, t.artist_id, t.track_number, t.disc_number, t.duration_ms, t.file_path, t.file_size, t.file_format, t.bitrate, t.mbid, t.genre, t.added_at, t.updated_at, t.tag_source, t.tag_sources_version,
    (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,
    al.release_date AS release_date
FROM tracks t
JOIN albums al ON al.id = t.album_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
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
  )
`

type LoadRadioCandidatesParams struct {
	UserID  pgtype.UUID
	ID      pgtype.UUID
	Column3 interface{}
}

type LoadRadioCandidatesRow struct {
	Track        Track
	IsLiked      bool
	LastPlayedAt pgtype.Timestamptz
	PlayCount    int64
	SkipCount    int64
	ReleaseDate  pgtype.Date
}

// 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
func (q *Queries) LoadRadioCandidates(ctx context.Context, arg LoadRadioCandidatesParams) ([]LoadRadioCandidatesRow, error) {
	rows, err := q.db.Query(ctx, loadRadioCandidates, arg.UserID, arg.ID, arg.Column3)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []LoadRadioCandidatesRow
	for rows.Next() {
		var i LoadRadioCandidatesRow
		if err := rows.Scan(
			&i.Track.ID,
			&i.Track.Title,
			&i.Track.AlbumID,
			&i.Track.ArtistID,
			&i.Track.TrackNumber,
			&i.Track.DiscNumber,
			&i.Track.DurationMs,
			&i.Track.FilePath,
			&i.Track.FileSize,
			&i.Track.FileFormat,
			&i.Track.Bitrate,
			&i.Track.Mbid,
			&i.Track.Genre,
			&i.Track.AddedAt,
			&i.Track.UpdatedAt,
			&i.Track.TagSource,
			&i.Track.TagSourcesVersion,
			&i.IsLiked,
			&i.LastPlayedAt,
			&i.PlayCount,
			&i.SkipCount,
			&i.ReleaseDate,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const loadRadioCandidatesV2 = `-- name: LoadRadioCandidatesV2 :many

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
),
taste_overlap AS (
    SELECT t.id AS track_id, 0.0::float8 AS sim_score
    FROM taste_profile_artists tpa
    JOIN tracks t ON t.artist_id = tpa.artist_id
    WHERE tpa.user_id = $1
      AND tpa.weight > 0
      AND t.id NOT IN (SELECT id FROM excluded_ids)
      AND t.id <> $2
    ORDER BY tpa.weight DESC, t.id
    LIMIT $10
),
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
          UNION SELECT track_id FROM taste_overlap
      )
    ORDER BY random()
    LIMIT $9
)
SELECT
    t.id, t.title, t.album_id, t.artist_id, t.track_number, t.disc_number, t.duration_ms, t.file_path, t.file_size, t.file_format, t.bitrate, t.mbid, t.genre, t.added_at, t.updated_at, t.tag_source, t.tag_sources_version,
    (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,
    al.release_date AS release_date,
    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 taste_overlap
    UNION ALL SELECT track_id, sim_score FROM random_fill
) u
JOIN tracks t ON t.id = u.track_id
JOIN albums al ON al.id = t.album_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,
         al.release_date
`

type LoadRadioCandidatesV2Params struct {
	UserID  pgtype.UUID
	ID      pgtype.UUID
	Column3 interface{}
	Column4 []pgtype.UUID
	Limit   int32
	Limit_2 int32
	Limit_3 int32
	Limit_4 int32
	Limit_5 int32
	Limit_6 int32
}

type LoadRadioCandidatesV2Row struct {
	Track           Track
	IsLiked         bool
	LastPlayedAt    pgtype.Timestamptz
	PlayCount       int64
	SkipCount       int64
	ReleaseDate     pgtype.Date
	SimilarityScore interface{}
}

// M4c: similarity-driven candidate pool. 6-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,
//	$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).
//
// Returns same shape as LoadRadioCandidates plus similarity_score column.
func (q *Queries) LoadRadioCandidatesV2(ctx context.Context, arg LoadRadioCandidatesV2Params) ([]LoadRadioCandidatesV2Row, error) {
	rows, err := q.db.Query(ctx, loadRadioCandidatesV2,
		arg.UserID,
		arg.ID,
		arg.Column3,
		arg.Column4,
		arg.Limit,
		arg.Limit_2,
		arg.Limit_3,
		arg.Limit_4,
		arg.Limit_5,
		arg.Limit_6,
	)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []LoadRadioCandidatesV2Row
	for rows.Next() {
		var i LoadRadioCandidatesV2Row
		if err := rows.Scan(
			&i.Track.ID,
			&i.Track.Title,
			&i.Track.AlbumID,
			&i.Track.ArtistID,
			&i.Track.TrackNumber,
			&i.Track.DiscNumber,
			&i.Track.DurationMs,
			&i.Track.FilePath,
			&i.Track.FileSize,
			&i.Track.FileFormat,
			&i.Track.Bitrate,
			&i.Track.Mbid,
			&i.Track.Genre,
			&i.Track.AddedAt,
			&i.Track.UpdatedAt,
			&i.Track.TagSource,
			&i.Track.TagSourcesVersion,
			&i.IsLiked,
			&i.LastPlayedAt,
			&i.PlayCount,
			&i.SkipCount,
			&i.ReleaseDate,
			&i.SimilarityScore,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}

const suggestArtistsForUser = `-- name: SuggestArtistsForUser :many
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
`

type SuggestArtistsForUserParams struct {
	UserID  pgtype.UUID
	Column2 float64
	Limit   int32
}

type SuggestArtistsForUserRow struct {
	CandidateMbid    string
	CandidateName    string
	TotalScore       float64
	TopSeedIds       []pgtype.UUID
	TopContributions []float64
	TopIsLiked       []bool
	TopPlayCounts    []int64
}

// 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.
func (q *Queries) SuggestArtistsForUser(ctx context.Context, arg SuggestArtistsForUserParams) ([]SuggestArtistsForUserRow, error) {
	rows, err := q.db.Query(ctx, suggestArtistsForUser, arg.UserID, arg.Column2, arg.Limit)
	if err != nil {
		return nil, err
	}
	defer rows.Close()
	var items []SuggestArtistsForUserRow
	for rows.Next() {
		var i SuggestArtistsForUserRow
		if err := rows.Scan(
			&i.CandidateMbid,
			&i.CandidateName,
			&i.TotalScore,
			&i.TopSeedIds,
			&i.TopContributions,
			&i.TopIsLiked,
			&i.TopPlayCounts,
		); err != nil {
			return nil, err
		}
		items = append(items, i)
	}
	if err := rows.Err(); err != nil {
		return nil, err
	}
	return items, nil
}