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feat(taste): time-of-day / weekday context conditioning — #1531
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Milestone #160 Opt 3 (temporal half). A new additive scoring term that
boosts a candidate when its artist's play history concentrates in the
CURRENT daypart × weekday-type cell, in the user's local timezone.

- Migration 0046: recommendation_weight_profiles.context_time_weight
  (per-profile scoring weight, DEFAULT 1.0).
- Query ListArtistContextPlayCountsForUser: per-artist completed-play
  counts split by the current cell (daypart night[22,5)/morning[5,12)/
  afternoon[12,17)/evening[17,22) × weekday-vs-weekend) via
  started_at AT TIME ZONE users.timezone; 365-day window, skips excluded.
- internal/recommendation/context.go: LoadContextAffinity computes each
  artist's shrunk cell-share minus the user's baseline share, clamped to
  [-1,1]; sparse artists shrink toward baseline (pseudo-count 5), unknown
  artists → 0 (cold-start neutral).
- Score() gains context_affinity_score · ContextTimeWeight; both
  candidate loaders set it per candidate.
- Tuning lab: ContextTimeWeight threaded through recsettings + admin API
  + web card ("Time-of-day weight" row) + Go/web tests. Shipped 1.0 both
  profiles (uniform start, re-bakeable).

Device-class axis deferred to #1551 (needs a client_id → device-class
mapping that doesn't exist yet).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Bryan Van Deusen
2026-07-14 09:31:43 -04:00
parent 40384cc05e
commit 65dd132b3d
18 changed files with 437 additions and 119 deletions
Download Patch File Download Diff File Expand all files Collapse all files
internal/db/dbq/models.go
+11 -10
View File
@@ -446,16 +446,17 @@ type RecommendationTuningAudit struct {
}
type RecommendationWeightProfile struct {
Profile string
BaseWeight float64
LikeBoost float64
RecencyWeight float64
SkipPenalty float64
JitterMagnitude float64
ContextWeight float64
SimilarityWeight float64
TasteWeight float64
UpdatedAt pgtype.Timestamptz
Profile string
BaseWeight float64
LikeBoost float64
RecencyWeight float64
SkipPenalty float64
JitterMagnitude float64
ContextWeight float64
SimilarityWeight float64
TasteWeight float64
UpdatedAt pgtype.Timestamptz
ContextTimeWeight float64
}
type RegistrationSetting struct {
internal/db/dbq/recommendation.sql.go
+77
View File
@@ -11,6 +11,83 @@ import (
"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
internal/db/dbq/recommendation_tuning.sql.go
+39 -31
View File
@@ -82,7 +82,7 @@ func (q *Queries) ListTuningAudit(ctx context.Context, limit int32) ([]Recommend
}
const listWeightProfiles = `-- name: ListWeightProfiles :many
SELECT profile, base_weight, like_boost, recency_weight, skip_penalty, jitter_magnitude, context_weight, similarity_weight, taste_weight, updated_at FROM recommendation_weight_profiles ORDER BY profile
SELECT profile, base_weight, like_boost, recency_weight, skip_penalty, jitter_magnitude, context_weight, similarity_weight, taste_weight, updated_at, context_time_weight FROM recommendation_weight_profiles ORDER BY profile
`
func (q *Queries) ListWeightProfiles(ctx context.Context) ([]RecommendationWeightProfile, error) {
@@ -105,6 +105,7 @@ func (q *Queries) ListWeightProfiles(ctx context.Context) ([]RecommendationWeigh
&i.SimilarityWeight,
&i.TasteWeight,
&i.UpdatedAt,
&i.ContextTimeWeight,
); err != nil {
return nil, err
}
@@ -163,29 +164,31 @@ func (q *Queries) UpdateTasteTuning(ctx context.Context, arg UpdateTasteTuningPa
const updateWeightProfile = `-- name: UpdateWeightProfile :one
UPDATE recommendation_weight_profiles
SET base_weight = $2,
like_boost = $3,
recency_weight = $4,
skip_penalty = $5,
jitter_magnitude = $6,
context_weight = $7,
similarity_weight = $8,
taste_weight = $9,
updated_at = now()
SET base_weight = $2,
like_boost = $3,
recency_weight = $4,
skip_penalty = $5,
jitter_magnitude = $6,
context_weight = $7,
similarity_weight = $8,
taste_weight = $9,
context_time_weight = $10,
updated_at = now()
WHERE profile = $1
RETURNING profile, base_weight, like_boost, recency_weight, skip_penalty, jitter_magnitude, context_weight, similarity_weight, taste_weight, updated_at
RETURNING profile, base_weight, like_boost, recency_weight, skip_penalty, jitter_magnitude, context_weight, similarity_weight, taste_weight, updated_at, context_time_weight
`
type UpdateWeightProfileParams struct {
Profile string
BaseWeight float64
LikeBoost float64
RecencyWeight float64
SkipPenalty float64
JitterMagnitude float64
ContextWeight float64
SimilarityWeight float64
TasteWeight float64
Profile string
BaseWeight float64
LikeBoost float64
RecencyWeight float64
SkipPenalty float64
JitterMagnitude float64
ContextWeight float64
SimilarityWeight float64
TasteWeight float64
ContextTimeWeight float64
}
func (q *Queries) UpdateWeightProfile(ctx context.Context, arg UpdateWeightProfileParams) (RecommendationWeightProfile, error) {
@@ -199,6 +202,7 @@ func (q *Queries) UpdateWeightProfile(ctx context.Context, arg UpdateWeightProfi
arg.ContextWeight,
arg.SimilarityWeight,
arg.TasteWeight,
arg.ContextTimeWeight,
)
var i RecommendationWeightProfile
err := row.Scan(
@@ -212,6 +216,7 @@ func (q *Queries) UpdateWeightProfile(ctx context.Context, arg UpdateWeightProfi
&i.SimilarityWeight,
&i.TasteWeight,
&i.UpdatedAt,
&i.ContextTimeWeight,
)
return i, err
}
@@ -249,21 +254,23 @@ const upsertWeightProfileDefaults = `-- name: UpsertWeightProfileDefaults :exec
INSERT INTO recommendation_weight_profiles (
profile, base_weight, like_boost, recency_weight, skip_penalty,
jitter_magnitude, context_weight, similarity_weight, taste_weight
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9)
jitter_magnitude, context_weight, similarity_weight, taste_weight,
context_time_weight
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10)
ON CONFLICT (profile) DO NOTHING
`
type UpsertWeightProfileDefaultsParams struct {
Profile string
BaseWeight float64
LikeBoost float64
RecencyWeight float64
SkipPenalty float64
JitterMagnitude float64
ContextWeight float64
SimilarityWeight float64
TasteWeight float64
Profile string
BaseWeight float64
LikeBoost float64
RecencyWeight float64
SkipPenalty float64
JitterMagnitude float64
ContextWeight float64
SimilarityWeight float64
TasteWeight float64
ContextTimeWeight float64
}
// Recommendation tuning lab queries (#1250). Seeding happens via the
@@ -281,6 +288,7 @@ func (q *Queries) UpsertWeightProfileDefaults(ctx context.Context, arg UpsertWei
arg.ContextWeight,
arg.SimilarityWeight,
arg.TasteWeight,
arg.ContextTimeWeight,
)
return err
}
internal/db/migrations/0046_context_time_weight.down.sql
+1
View File
@@ -0,0 +1 @@
ALTER TABLE recommendation_weight_profiles DROP COLUMN IF EXISTS context_time_weight;
internal/db/migrations/0046_context_time_weight.up.sql
+12
View File
@@ -0,0 +1,12 @@
-- 0046_context_time_weight.up.sql — time-of-day/weekday context conditioning
-- (#1531, milestone #160 Opt 3). Adds a per-profile scoring weight for the new
-- context-affinity term: how strongly a candidate is boosted when its artist's
-- play history concentrates in the current daypart × weekday-type cell (in the
-- user's local timezone). Mirrors the other ScoringWeights columns.
--
-- DEFAULT 1.0 backfills both existing profile rows to a modest on-value; the
-- Go ShippedRadioWeights/ShippedDailyMixWeights carry the same 1.0 so fresh
-- installs seed identically. Reconcile only seeds MISSING rows (ON CONFLICT DO
-- NOTHING), so existing rows rely on this DEFAULT until an operator resets.
ALTER TABLE recommendation_weight_profiles
ADD COLUMN context_time_weight double precision NOT NULL DEFAULT 1.0;
internal/db/queries/recommendation.sql
+50
View File
@@ -173,6 +173,56 @@ GROUP BY t.id, t.title, t.album_id, t.artist_id, t.duration_ms, t.file_path,
l.user_id, pe.last_played_at, pe.play_count, pe.skip_count,
al.release_date;
-- name: ListArtistContextPlayCountsForUser :many
-- 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).
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;
-- 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
internal/db/queries/recommendation_tuning.sql
+13 -11
View File
@@ -6,8 +6,9 @@
-- doesn't exist yet. Never overwrites operator-tuned values.
INSERT INTO recommendation_weight_profiles (
profile, base_weight, like_boost, recency_weight, skip_penalty,
jitter_magnitude, context_weight, similarity_weight, taste_weight
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9)
jitter_magnitude, context_weight, similarity_weight, taste_weight,
context_time_weight
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10)
ON CONFLICT (profile) DO NOTHING;
-- name: ListWeightProfiles :many
@@ -15,15 +16,16 @@ SELECT * FROM recommendation_weight_profiles ORDER BY profile;
-- name: UpdateWeightProfile :one
UPDATE recommendation_weight_profiles
SET base_weight = $2,
like_boost = $3,
recency_weight = $4,
skip_penalty = $5,
jitter_magnitude = $6,
context_weight = $7,
similarity_weight = $8,
taste_weight = $9,
updated_at = now()
SET base_weight = $2,
like_boost = $3,
recency_weight = $4,
skip_penalty = $5,
jitter_magnitude = $6,
context_weight = $7,
similarity_weight = $8,
taste_weight = $9,
context_time_weight = $10,
updated_at = now()
WHERE profile = $1
RETURNING *;