Commit Graph

4 Commits

Author SHA1 Message Date
bvandeusen 9ad4343c76 feat(tuning): weekly trend view — per-surface series + knob-turn markers
test-go / test (push) Successful in 33s
test-web / test (push) Failing after 38s
test-go / integration (push) Successful in 4m44s
The verify half of the tune→verify loop (#1251), on the same admin
Tuning page as the knobs:

- RecommendationWeeklyTrends: weekly per-source outcomes aggregated
  across all users (the knobs are global, so judging a turn needs
  global outcomes — rows carry rates only, no track/user identity),
  with a taste-hit count per bucket: plays whose track's artist has a
  positive weight in the player's current taste profile. That's the
  "cheap recompute" reading — retroactive over the whole window, at
  the cost of profile drift.
- GET /api/admin/recommendation-trends?weeks=N (default 12, cap 52):
  per-family weekly series (skip rate, sample-weighted completion,
  taste-hit rate) plus the tuning-audit markers inside the window.
- Web: sparkline table under the tuning cards — skip rate per week on
  a shared axis with dashed ticks at knob turns, latest-week columns,
  window taste-hit rate, low-volume rows dimmed as anecdote, and a
  plain-text list of the window's tuning changes.

Also fixes the revive unused-parameter lint on the tuning GET handler
that failed CI run 1903 on the previous commit.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TsF3cNoKrqCYsU78cXC8U6
2026-07-03 09:29:33 -04:00
bvandeusen fb4431207d feat(recommendation): For You exploration attribution — taste vs fresh picks
test-go / test (push) Successful in 31s
test-web / test (push) Successful in 37s
test-go / integration (push) Successful in 4m37s
Milestone #127 step 2 (#1249). For You deliberately blends two
populations — a head of top-scored taste picks and a tail sampled from
deeper ranking (the freshness injection) — but the metrics judged it as
one blob, so its skip rate couldn't distinguish "the taste engine is
missing" from "the freshness tax is too high". That number decides the
exploration share before we tune it.

- Migration 0038: nullable pick_kind ('taste'|'fresh') on both
  playlist_tracks (stamped at snapshot build) and play_events (frozen at
  play-ingestion — the snapshot rebuilds daily, so attribution cannot be
  reconstructed at read time).
- Builder: pickHeadAndTail marks head=taste / tail=fresh; the small-pool
  fallback is all taste (top-N-by-score IS the taste mechanism). Other
  variants persist NULL.
- Ingestion: for_you plays (live + offline replay) look the track up in
  the user's current snapshot; not found → unattributed, never guessed.
- Metrics: For You's row gains a breakdown (taste / fresh / earlier
  unattributed plays), parent row stays the sum; web card renders the
  sub-rows indented with the same baseline deltas + low-data dimming.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TsF3cNoKrqCYsU78cXC8U6
2026-07-02 20:39:41 -04:00
bvandeusen 60533073ad feat(metrics): bucketed surface families + manual-plays baseline (#1248, milestone 127)
test-go / test (push) Successful in 31s
test-web / test (push) Successful in 37s
test-go / integration (push) Successful in 4m30s
The recommendation metrics table was observable but not actionable: raw
source strings (album:<uuid> one-offs) drowned the stable surfaces, and
manual plays were excluded so skip rates had no control group.

- SQL: include NULL-source rows (the baseline) and carry completion_n
  so family merges can weight avg_completion correctly.
- Handler buckets raw sources into stable families (radio:<uuid> →
  Radio, album:/artist: → direct plays, etc.) grouped by surface
  intent: go-to / discovery / direct — each band judged against its
  job, since discovery mixes are expected to skip hotter. Families
  under 20 plays are flagged low-confidence, not hidden.
- Settings card renders the baseline row and per-surface deltas in
  percentage points vs baseline (worse-than-baseline deltas in danger
  color), intent hint copy per group, low-data rows dimmed.
- Pure-unit test for the bucketing/merge; DB test updated to the new
  contract (baseline included, radio:<uuid> collapse).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TsF3cNoKrqCYsU78cXC8U6
2026-07-02 18:00:40 -04:00
bvandeusen 1a7515e6ea feat(taste): phase 4 — recommendation observability (#796)
test-go / test (push) Successful in 33s
test-web / test (push) Successful in 41s
test-go / integration (push) Successful in 4m24s
Per-source play outcomes so the operator can see whether each recommendation
surface is landing and tune the now-operator-tunable taste weights.

Server:
- query RecommendationSourceMetricsForUser: groups the user's play_events by
  source (system-playlist surface), reporting plays / skips / avg completion
  over a window; NULL-source (library/radio) plays excluded.
- GET /api/me/recommendation-metrics?days=30 (default 30, capped 365) →
  {window_days, sources:[{source, plays, skips, skip_rate, avg_completion}]}.
- handler test: 401 unauth; per-source aggregation + NULL-source exclusion +
  skip_rate / avg_completion math.

Web:
- lib/api/metrics.ts: query + friendly source labels.
- settings page gains a "Recommendation metrics" card (table of surface / plays
  / skip rate / avg completion), with loading/error/empty states.
- settings tests mock the new query (manual subscribe-store, hoisting-safe).

Note: You-might-like plays aren't source-tagged (it's a Home row, not a system
playlist), so this covers For-You / Discover / the mixes. Tagging YML plays
would be a client follow-up.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-12 00:28:30 -04:00