5 Commits
Author SHA1 Message Date
mrleo1nid fff91c446b feat(recommendations): collect demographics and advance age cohorts
ci / ts / ts (packages + web) (push) Successful in 3m19s
ci / db / db (push) Successful in 53s
ci / module boundaries / boundaries (push) Successful in 7s
ci / api / api (push) Successful in 51s
ci / contract / contract (сгенерированный код совпадает с openapi.yaml) (push) Successful in 1m3s
ci / recommender / recommender (push) Failing after 16s
ci / mobile / mobile (Metro-бандл Android) (push) Successful in 1m15s
2026-10-22 14:19:52 +03:00
mrleo1nidandClaude Opus 5.5 fb07f962eb feat: taste onboarding for new listeners (M6)
ci / contract / contract (сгенерированный код совпадает с openapi.yaml) (push) Successful in 1m2s
ci / db / db (push) Failing after 1m29s
ci / ts / ts (packages + web) (push) Successful in 49s
ci / api / api (push) Successful in 1m25s
ci / mobile / mobile (Metro-бандл Android) (push) Successful in 48s
ci / recommender / recommender (push) Successful in 21s
- GET /onboarding offers the library's top artists (with album covers)
  and genres and says whether to show it (not done and < 10 plays);
  PUT /me/onboarding stores the choice or a skip (migration 00009).
- The recommender seeds the taste from it while the user has fewer than
  30 scored tracks: chosen artists' tracks +1, chosen genres +0.5.
- Web: onboarding replaces the wave on the home page until done or
  skipped; artist grid with covers, genre chips, at least 3 artists.
- e2e journey and the recommender DB test cover it.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-20 22:35:43 +03:00
mrleo1nidandClaude Opus 5.5 ff0aafdb1e feat(recommender): Thompson-sampling bandit over candidate sources (M6)
ci / recommender / recommender (push) Failing after 4s
ci / db / db (push) Failing after 2m21s
Nightly Beta(α, β) per user and source from wave impressions (reward:
complete or like, ×0.99 daily decay) stored in user_profiles_rec.bandit;
the wave adds 0.2·(θ − 0.5) per candidate source, sources without data
stay neutral. The user's exploration share now follows how well `fresh`
does against the other sources.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-20 22:31:24 +03:00
mrleo1nidandClaude Opus 5.5 3afed02f23 feat(recommender): nightly ALS with offline metrics and CF candidates in the wave (M6)
ci / recommender / recommender (push) Successful in 37s
- Implicit scores from play events and reactions per the signals table
  (90-day half-life, weaker skips outside the wave, dislikes override).
- numpy ALS for implicit feedback; time-split evaluation on the last
  7 days (NDCG@10, Recall@50) against a popularity baseline; a new model
  is activated only if NDCG@10 does not regress by more than 2%.
- Vectors are written to track_embeddings.cf and user_profiles_rec.taste_cf,
  versions to model_versions; NightlyTrainer runs at TRAIN_HOUR and on
  first start, `pipu-rec train` runs it manually.
- Wave: cf and item_cf candidate sources and a 0.10 cf term in the v1
  score; impressions are tagged heuristic-v1+cf.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-20 17:54:25 +03:00
mrleo1nidandClaude Opus 5.5 ef29b85320 feat(rec): audio analyzer and My Wave v1 engine (M4)
ci / api / api (push) Successful in 27s
ci / recommender / recommender (push) Successful in 1m0s
ci / docker / docker (образы собираются — их сервер собирает сам при обновлении) (push) Successful in 1m26s
- migration 00006: track features and embeddings (pgvector, HNSW),
  analysis queue filled by a trigger on new tracks, wave sessions and
  impressions, recommender profiles, model versions
- analyzer basic-1 (ADR-014): ffmpeg decode, three 30 s excerpts,
  256-d timbre/rhythm embedding, tempo by onset autocorrelation, key,
  loudness, energy, danceability, acousticness, intro length; worker
  with SKIP LOCKED claims, retries and re-analysis on version change
- wave engine v1: candidates (session/taste similarity, fresh,
  liked artists, rediscover, popular, exploration, seed), filters
  (dislikes, played in 3 h, already served), heuristic score, activity
  and mood fit from contexts.yaml with relaxing thresholds, MMR with
  one track per artist, exploration share, session vector updated by
  reactions and a change of course after three skips
- POST /internal/wave/batch with the catalog index cached in memory
  and the session kept in Redis

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-20 12:20:55 +03:00