fix(search): reindex on a fresh Meilisearch

Deleting a missing <uid>_next index is accepted with 202 and fails inside the
task with index_not_found. That error was not treated as not-found, so the first
reindex aborted and search stayed unavailable until indexes existed.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

.gitea/workflows/release.yml

@@ -48,6 +48,8 @@ jobs:
   android:
     name: android (APK в релиз)
     needs: release
+    # Обычно 10–15 минут; дольше — значит, сборка упёрлась в память, лучше упасть, чем держать раннер.
+    timeout-minutes: 60
     runs-on: ubuntu-latest
     # Постоянные кэши на хосте раннера: дистрибутив и зависимости Gradle, его build cache, Android SDK и NDK
     # переживают job (−4 мин на релиз). Работают, если в config.yaml раннера разрешены тома
@@ -60,7 +62,7 @@ jobs:
       image: docker.gitea.com/runner-images:ubuntu-latest
       # Жёсткие пределы контейнера: сборка не должна забирать всю VM раннера (а через неё — хост гипервизора).
       # Своп запрещён (memory-swap = memory): лучше OOM внутри контейнера, чем подвисший хост.
-      options: --cpus=3 --memory=6g --memory-swap=6g
+      options: --cpus=3 --memory=7g --memory-swap=7g
       volumes:
         - /opt/ci-cache/gradle:/root/.gradle
         - /opt/ci-cache/android:/root/.android
@@ -106,6 +108,8 @@ jobs:
           # CMake / ninja нативной части React Native по умолчанию берут все ядра — ограничиваем.
           CMAKE_BUILD_PARALLEL_LEVEL: "2"
           NINJAFLAGS: "-j2"
+          # JS-бандл (Metro) собирается внутри Gradle отдельным node — не даём ему разрастись.
+          NODE_OPTIONS: "--max-old-space-size=1536"
         # Только arm64-v8a: C++-часть React Native собирается под каждую ABI, и четыре ABI
         # вместе с NDK (~2.5 ГБ) не помещаются на диск раннера. arm64 — все устройства с 2017+.
         # Память: на раннере 8 ГБ, и без ограничений Gradle + демон Kotlin + Metro вызывают OOM killer.
@@ -120,7 +124,7 @@ jobs:
           cd android
           # nice / ionice: сборка уступает CPU и диск всему остальному на машине
           gradle=(nice -n 19 ionice -c 3 ./gradlew --max-workers=2 --build-cache -PreactNativeArchitectures=arm64-v8a
-            -Pkotlin.compiler.execution.strategy=in-process -Dorg.gradle.jvmargs="-Xmx2560m -XX:MaxMetaspaceSize=512m")
+            -Pkotlin.compiler.execution.strategy=in-process -Dorg.gradle.jvmargs="-Xmx2048m -XX:MaxMetaspaceSize=512m")
           # Без New Architecture (app.config.ts) CMake приложения не собирается — отдельный codegen не нужен.
           if grep -q '^newArchEnabled=true' gradle.properties; then
             "${gradle[@]}" generateCodegenArtifactsFromSchema

api/openapi.yaml

@@ -1256,6 +1256,38 @@ paths:
           description: Снято
         default:
           $ref: "#/components/responses/Problem"
+  /api/v1/onboarding:
+    get:
+      operationId: getOnboarding
+      tags: [wave]
+      summary: Онбординг вкуса — исполнители и жанры библиотеки для выбора
+      description: |
+        `required` — показать онбординг: пользователь его не проходил и не пропускал, а своей истории почти нет.
+      responses:
+        "200":
+          description: Варианты и состояние
+          content:
+            application/json:
+              schema:
+                $ref: "#/components/schemas/Onboarding"
+        default:
+          $ref: "#/components/responses/Problem"
+  /api/v1/me/onboarding:
+    put:
+      operationId: saveOnboarding
+      tags: [wave]
+      summary: Сохранить выбор онбординга (или пропуск — пустые списки)
+      requestBody:
+        required: true
+        content:
+          application/json:
+            schema:
+              $ref: "#/components/schemas/OnboardingChoice"
+      responses:
+        "204":
+          description: Сохранено
+        default:
+          $ref: "#/components/responses/Problem"
   /api/v1/wave/options:
     get:
       operationId: getWaveOptions
@@ -1442,6 +1474,59 @@ components:
           schema:
             $ref: "#/components/schemas/Problem"
   schemas:
+    Onboarding:
+      type: object
+      required: [required, artists, genres]
+      properties:
+        required:
+          type: boolean
+        artists:
+          type: array
+          items:
+            type: object
+            required: [id, name, track_count, cover_url, cover_colors]
+            properties:
+              id:
+                type: string
+                format: uuid
+              name:
+                type: string
+              track_count:
+                type: integer
+              cover_url:
+                type: string
+                nullable: true
+                description: Обложка самого большого альбома исполнителя
+              cover_colors:
+                type: array
+                items:
+                  type: string
+        genres:
+          type: array
+          items:
+            type: object
+            required: [name, track_count]
+            properties:
+              name:
+                type: string
+              track_count:
+                type: integer
+    OnboardingChoice:
+      type: object
+      required: [artist_ids, genres]
+      properties:
+        artist_ids:
+          type: array
+          maxItems: 50
+          items:
+            type: string
+            format: uuid
+        genres:
+          type: array
+          maxItems: 30
+          items:
+            type: string
+            maxLength: 100
     UserRef:
       type: object
       required: [id, username]

apps/web/src/pages/HomePage.tsx

@@ -1,5 +1,5 @@
 import { unwrap } from '@pipu/core';
-import { useQuery } from '@tanstack/react-query';
+import { useQuery, useQueryClient } from '@tanstack/react-query';
 import { useState } from 'react';
 import { useTranslation } from 'react-i18next';
 
@@ -24,6 +24,7 @@ import {
 import { cx, FormError, Icon } from '../shared/ui/ui';
 import { WaveButton } from '../widgets/wave/WaveButton';
 import s from './home.module.css';
+import { Onboarding } from './Onboarding';
 
 /** Иконки Material Symbols по именам из /wave/options. */
 const ICONS: Record<string, string> = {
@@ -44,8 +45,28 @@ const WAVE_COLORS: [string, string, string] = ['#2F80FF', '#7C5CFF', '#35D3FF'];
 
 type Tr = (key: string) => string;
 
-/** Главная (раскладка Center): кнопка «Моя волна» и под ней выбор занятия и настроения. */
+/** Главная: для нового пользователя без истории — сначала онбординг вкуса, затем волна. */
 export function HomePage() {
+  const session = useSession();
+  const queryClient = useQueryClient();
+  const onboarding = useQuery({
+    queryKey: ['onboarding'],
+    queryFn: async () => unwrap(await session.client.GET('/api/v1/onboarding')),
+    staleTime: Infinity,
+  });
+  if (onboarding.data?.required) {
+    return (
+      <Onboarding
+        options={onboarding.data}
+        onDone={() => queryClient.setQueryData(['onboarding'], { ...onboarding.data, required: false })}
+      />
+    );
+  }
+  return <WaveHome />;
+}
+
+/** Главная (раскладка Center): кнопка «Моя волна» и под ней выбор занятия и настроения. */
+function WaveHome() {
   const { t } = useTranslation();
   const tr = t as unknown as Tr;
   const session = useSession();

apps/web/src/pages/Onboarding.tsx

@@ -0,0 +1,113 @@
+import type { components } from '@pipu/api-client';
+import { unwrap } from '@pipu/core';
+import { useMutation } from '@tanstack/react-query';
+import { useState } from 'react';
+import { useTranslation } from 'react-i18next';
+
+import { useSession } from '../app/session';
+import { Cover } from '../entities/catalog';
+import { useErrorText } from '../shared/lib/errors';
+import { checkIcon } from '../shared/ui/icons';
+import { Button, cx, FormError, Icon } from '../shared/ui/ui';
+import s from './onboarding.module.css';
+
+type Options = components['schemas']['Onboarding'];
+
+/** Минимум исполнителей, чтобы волне было от чего оттолкнуться. */
+const MIN_ARTISTS = 3;
+
+/**
+ * Онбординг вкуса (docs/recommendations.md#7): исполнители и жанры библиотеки — начальный вкус «Моей волны»,
+ * пока своей истории почти нет. Пропуск тоже запоминается: второй раз не спросим.
+ */
+export function Onboarding({ options, onDone }: { options: Options; onDone: () => void }) {
+  const { t } = useTranslation();
+  const session = useSession();
+  const errorText = useErrorText();
+  const [artists, setArtists] = useState<Set<string>>(new Set());
+  const [genres, setGenres] = useState<Set<string>>(new Set());
+  const save = useMutation({
+    mutationFn: async (skip: boolean) =>
+      unwrap(
+        await session.client.PUT('/api/v1/me/onboarding', {
+          body: skip ? { artist_ids: [], genres: [] } : { artist_ids: [...artists], genres: [...genres] },
+        }),
+      ),
+    onSuccess: onDone,
+  });
+  // Функциональное обновление: быстрые нажатия подряд не теряют выбор.
+  const toggle = (update: (fn: (prev: Set<string>) => Set<string>) => void, key: string) =>
+    update((prev) => {
+      const next = new Set(prev);
+      if (next.has(key)) next.delete(key);
+      else next.add(key);
+      return next;
+    });
+  const enough = artists.size >= MIN_ARTISTS || (artists.size > 0 && genres.size > 0);
+
+  return (
+    <div className={s.page}>
+      <header className={s.head}>
+        <h1>{t('onboarding.title')}</h1>
+        <p>{t('onboarding.subtitle')}</p>
+      </header>
+
+      <section aria-label={t('onboarding.artists')}>
+        <h2 className={s.label}>{t('onboarding.artists')}</h2>
+        <div className={s.artists}>
+          {options.artists.map((a) => {
+            const on = artists.has(a.id);
+            return (
+              <button
+                key={a.id}
+                type="button"
+                className={cx(s.artist, on && s.on)}
+                aria-pressed={on}
+                onClick={() => toggle(setArtists, a.id)}
+              >
+                <span className={s.avatar}>
+                  <Cover album={{ id: a.id, cover_url: a.cover_url, cover_colors: a.cover_colors }} size={96} round />
+                  {on && (
+                    <span className={s.check}>
+                      <Icon src={checkIcon} size={22} />
+                    </span>
+                  )}
+                </span>
+                <span className={s.name}>{a.name}</span>
+              </button>
+            );
+          })}
+        </div>
+      </section>
+
+      {options.genres.length > 0 && (
+        <section aria-label={t('onboarding.genres')}>
+          <h2 className={s.label}>{t('onboarding.genres')}</h2>
+          <div className={s.genres}>
+            {options.genres.map((g) => (
+              <button
+                key={g.name}
+                type="button"
+                className={s.genre}
+                aria-pressed={genres.has(g.name)}
+                onClick={() => toggle(setGenres, g.name)}
+              >
+                {g.name}
+              </button>
+            ))}
+          </div>
+        </section>
+      )}
+
+      <FormError>{save.error ? errorText(save.error) : null}</FormError>
+      <div className={s.actions}>
+        <Button variant="ghost" busy={save.isPending && save.variables} onClick={() => save.mutate(true)}>
+          {t('onboarding.skip')}
+        </Button>
+        <Button variant="primary" busy={save.isPending && !save.variables} disabled={!enough} onClick={() => save.mutate(false)}>
+          {enough ? t('onboarding.done') : t('onboarding.pick_more', { count: MIN_ARTISTS - artists.size })}
+        </Button>
+      </div>
+    </div>
+  );
+}

apps/web/src/pages/onboarding.module.css

@@ -0,0 +1,124 @@
+.page {
+  display: flex;
+  flex-direction: column;
+  gap: 28px;
+  max-width: 1100px;
+  margin: 0 auto;
+  animation: pipuIn 0.2s ease-out;
+}
+
+.head h1 {
+  margin: 0 0 8px;
+  font-family: var(--font-display);
+  font-size: 32px;
+  font-weight: 600;
+  letter-spacing: -0.02em;
+}
+
+.head p {
+  margin: 0;
+  color: var(--text2);
+}
+
+.label {
+  margin: 0 0 14px;
+  font-size: 13px;
+  font-weight: 700;
+  letter-spacing: 0.08em;
+  text-transform: uppercase;
+  color: var(--text3);
+}
+
+.artists {
+  display: grid;
+  grid-template-columns: repeat(auto-fill, minmax(120px, 1fr));
+  gap: 18px 12px;
+}
+
+.artist {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  gap: 10px;
+  padding: 10px 6px;
+  border-radius: var(--radius-lg);
+  text-align: center;
+}
+
+.artist:hover {
+  background: var(--hover);
+}
+
+.avatar {
+  position: relative;
+  border-radius: 50%;
+  transition:
+    box-shadow 0.15s,
+    transform 0.15s;
+}
+
+.on .avatar {
+  box-shadow:
+    0 0 0 3px var(--bg),
+    0 0 0 5px var(--accent);
+  transform: scale(0.96);
+}
+
+.check {
+  position: absolute;
+  right: -2px;
+  bottom: -2px;
+  display: grid;
+  place-items: center;
+  width: 32px;
+  height: 32px;
+  border-radius: 50%;
+  background: var(--accent);
+  color: #fff;
+  box-shadow: var(--glow);
+}
+
+.name {
+  font-size: 14px;
+  font-weight: 600;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+  max-width: 100%;
+}
+
+.genres {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 8px;
+}
+
+.genre {
+  height: 38px;
+  padding: 0 16px;
+  border-radius: var(--radius-pill);
+  border: 1px solid var(--line);
+  background: var(--surface2);
+  font-weight: 600;
+  font-size: 14px;
+}
+
+.genre[aria-pressed='true'] {
+  background: var(--accent);
+  border-color: var(--accent);
+  color: #fff;
+  box-shadow: var(--glow);
+}
+
+.actions {
+  position: sticky;
+  bottom: 16px;
+  display: flex;
+  justify-content: flex-end;
+  gap: 10px;
+  padding: 12px;
+  border-radius: var(--radius-lg);
+  border: 1px solid var(--line2);
+  background: var(--glass);
+  backdrop-filter: blur(28px) saturate(1.3);
+}

docs/ci-cd.md

@@ -103,7 +103,7 @@ container:
     - /opt/ci-cache/**   # постоянные кэши Gradle и Android SDK для job android в release.yml
 ```
 
-Сборка APK ограничена сама (`release.yml`: контейнер `--cpus=3 --memory=6g` без свопа, CMake / ninja / Gradle
+Сборка APK ограничена сама (`release.yml`: контейнер `--cpus=3 --memory=7g` без свопа, Gradle `-Xmx2g`, Metro `--max-old-space-size=1536`, таймаут 60 мин, CMake / ninja / Gradle
 по 2 потока, `nice` / `ionice`). Если раннер — VM в гипервизоре (Proxmox), дополнительно ограничьте её там:
 фиксированная RAM без ballooning, сумма RAM всех VM меньше RAM хоста, `cpulimit` ≤ половины ядер хоста,
 лимит дискового I/O — иначе тяжёлая сборка может подвесить весь хост.

docs/library-and-storage.md

@@ -35,8 +35,7 @@
   `fsync`, сверка SHA-256, атомарный `rename`. Перезапись существующих файлов и удаление запрещены на уровне кода агента.
 - Права на NFS-сервере: экспорт должен разрешать запись для UID/GID агента (`PIPU_FILE_UID` / `PIPU_FILE_GID`,
   задаются в `.env` под владельца музыки на файловом сервере); новые файлы — `0644`, каталоги — `0755`.
-- `POST /admin/sources/{id}/test` для такого источника дополнительно проверяет запись: создаёт и удаляет
-  `.pipu-write-test` в корне.
+- `POST /admin/sources/{id}/test` для такого источника дополнительно проверяет право записи — без создания файлов.
 - У источника задаётся `write_template` — шаблон пути для новых файлов, с автоподбором по существующей структуре
   и проверкой обратимости через регэкспы источника (подробно — [uploads.md](uploads.md#7-раскладка-в-хранилище-как-принято-на-сервере)).
 
@@ -44,8 +43,11 @@
 - Агент: `POST /internal/files` `{source_id, local_path?, rel_path, staging_path, sha256}` → `{rel_path, size, renamed}`;
   `POST /internal/files/test` — проверка записи. NFS с `accepts_uploads` монтируется rw в `/library-rw/<id>` (каталог
   внутри контейнера агента), а в `/library/<id>` — bind этой точки с `remount,ro`. Local-источники пишутся через
-  `/library-host-rw` (тот же `LIBRARY_HOST`, на запись — только у агента). Итоговое имя создаётся жёсткой ссылкой
-  на временный файл (`link` не перезаписывает, в отличие от `rename`); занято — ` (2)`, ` (3)`…
+  `/library-host-rw` (тот же `LIBRARY_HOST`, на запись — только у агента). На музыкальный диск не пишется ничего,
+  кроме самих треков: файл создаётся сразу под итоговым именем (`O_EXCL` — существующий не перезаписывается;
+  занято — ` (2)`, ` (3)`…), `fsync`, сверка SHA-256; при ошибке агент удаляет свой недописанный файл и созданные
+  для него пустые каталоги. Проверка записи — `access(W_OK)` и флаг read-only файловой системы, без пробного файла.
+  Остальные сервисы видят музыку только на чтение (`read_only` в compose).
   Владелец новых файлов и каталогов — `PIPU_FILE_UID` / `PIPU_FILE_GID` (`-1` — не менять).
 - Шаблон: `meta.ParseTemplate` / `Render` (очистка имён, пределы длины), `meta.SuggestTemplate` (регэксп → шаблон через
   `regexp/syntax`: именованные группы → поля, `(?:(?P<disc>\d)-)?` → `{disc:1-}`, необязательная группа → `[ ]`,

docs/recommendations.md

@@ -152,6 +152,14 @@ score = 0.35·cos(e, session_vec) + 0.25·max_c cos(e, centroid_c) + 0.15·artis
 Обучение — ночью; новая модель активируется, только если офлайн-NDCG@10 не хуже активной более чем на 2%.
 Пока размеченных показов меньше ~20k, используется v1 (переключение автоматическое по порогу).
 
+Реализация (`pipu_rec/train/ranker.py`): при каждом показе волна пишет вектор признаков кандидата
+в `rec_impression_features` (29 признаков, `FEATURE_NAMES` в `wave/engine.py`; порядок версионируется
+`FEATURES_VERSION`). Ночью признаки соединяются с исходами `wave_impressions`, группа — сессия волны;
+валидация — сессии последних 7 дней. Модель включается, если её NDCG@10 не ниже порядка по оценке v1
+и не хуже активной более чем на 2%. Модель хранится строкой в `model_versions.artifact` (kind `ranker`),
+сервис загружает активную при старте и после ночного обучения; в выдаче её порядок заменяет оценку v1,
+MMR-разнообразие и квоты остаются. Пока модели нет, `model_ver` показа — версия v1.
+
 ### 6.4 Занятия и настроения
 
 Каждый контекст — профиль целевых значений аудиопризнаков (`services/recommender/config/contexts.yaml`,
@@ -191,6 +199,11 @@ score = 0.35·cos(e, session_vec) + 0.25·max_c cos(e, centroid_c) + 0.15·artis
 что одному пользователю лучше заходит `fresh`, а другому — `rediscover`. Параметры затухают
 (×0.99 в день), чтобы подстраиваться под смену вкуса.
 
+Реализация (`pipu_rec/train/bandit.py`): параметры пересчитываются ночью по `wave_impressions` за 90 дней
+(награда — `complete` / `like`) в `user_profiles_rec.bandit`; при сборке пачки источник получает бонус
+`0.2·(θ − 0.5)`, где θ ~ Beta(α, β) (источник без наблюдений — нейтральные 0.5). `exploration` следует за
+успехом `fresh` относительно остальных источников (0.05–0.4).
+
 ### 6.7 Реакция в реальном времени
 
 - Клиент держит в очереди 2 трека вперёд и запрашивает новую пачку, когда осталось ≤ 2.
@@ -204,6 +217,10 @@ score = 0.35·cos(e, session_vec) + 0.25·max_c cos(e, centroid_c) + 0.15·artis
 - **Новый пользователь**: опциональный онбординг (выбрать 3+ жанра или исполнителя) → начальные центроиды.
   Без онбординга — первые пачки из `popular` и максимально разнообразных кластеров библиотеки
   (по одному треку из разных кластеров), exploration 40% на первые 30 треков.
+- Реализация онбординга: `GET /onboarding` (40 исполнителей с наибольшим числом треков, 24 жанра; `required` —
+  не пройден и своей истории < 10 треков), `PUT /me/onboarding` → `user_profiles_rec.onboarding`; пустой выбор —
+  пропуск. Рекомендатель, пока своих оценок < 30, добавляет псевдооценки: треки выбранных исполнителей +1,
+  жанров +0.5 (до 300 треков). Веб показывает онбординг на главной вместо волны.
 - **Новый трек**: сразу доступен через `audio_sim` / `fresh` (как только проанализирован), без единого прослушивания.
 
 ## 8. Обучение на всех пользователях

docs/uploads.md

@@ -161,9 +161,9 @@
 2. Запросить у `storage-agent` запись: `POST /internal/files` `{source_id, rel_path, staging_path}`.
    Агент:
    - создаёт каталоги;
-   - копирует во временный файл `.<name>.pipu-tmp` в целевой папке, `fsync`;
-   - сверяет SHA-256 копии со staging;
-   - атомарно переименовывает в итоговое имя.
+   - создаёт файл сразу под итоговым именем (`O_EXCL`, существующий не перезаписывается), копирует, `fsync`;
+   - сверяет SHA-256 копии со staging; при ошибке удаляет свой файл и созданные пустые каталоги —
+     на музыкальный диск не попадает ничего, кроме треков.
 3. Запустить точечный скан файла (`scan_path`) → трек появляется в каталоге и поиске, ставится в аудиоанализ.
    В `media_files` сохраняется `upload_id` — история происхождения.
 4. Удалить файл из staging, освободить квоту, статус `imported`, запись в `audit_log`.

packages/api-client/src/generated/schema.ts

@@ -1066,6 +1066,43 @@ export interface paths {
         patch?: never;
         trace?: never;
     };
+    "/api/v1/onboarding": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        /**
+         * Онбординг вкуса — исполнители и жанры библиотеки для выбора
+         * @description `required` — показать онбординг: пользователь его не проходил и не пропускал, а своей истории почти нет.
+         */
+        get: operations["getOnboarding"];
+        put?: never;
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
+    "/api/v1/me/onboarding": {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        get?: never;
+        /** Сохранить выбор онбординга (или пропуск — пустые списки) */
+        put: operations["saveOnboarding"];
+        post?: never;
+        delete?: never;
+        options?: never;
+        head?: never;
+        patch?: never;
+        trace?: never;
+    };
     "/api/v1/wave/options": {
         parameters: {
             query?: never;
@@ -1181,6 +1218,26 @@ export interface paths {
 export type webhooks = Record<string, never>;
 export interface components {
     schemas: {
+        Onboarding: {
+            required: boolean;
+            artists: {
+                /** Format: uuid */
+                id: string;
+                name: string;
+                track_count: number;
+                /** @description Обложка самого большого альбома исполнителя */
+                cover_url: string | null;
+                cover_colors: string[];
+            }[];
+            genres: {
+                name: string;
+                track_count: number;
+            }[];
+        };
+        OnboardingChoice: {
+            artist_ids: string[];
+            genres: string[];
+        };
         UserRef: {
             /** Format: uuid */
             id: string;
@@ -3599,6 +3656,50 @@ export interface operations {
             default: components["responses"]["Problem"];
         };
     };
+    getOnboarding: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody?: never;
+        responses: {
+            /** @description Варианты и состояние */
+            200: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content: {
+                    "application/json": components["schemas"]["Onboarding"];
+                };
+            };
+            default: components["responses"]["Problem"];
+        };
+    };
+    saveOnboarding: {
+        parameters: {
+            query?: never;
+            header?: never;
+            path?: never;
+            cookie?: never;
+        };
+        requestBody: {
+            content: {
+                "application/json": components["schemas"]["OnboardingChoice"];
+            };
+        };
+        responses: {
+            /** @description Сохранено */
+            204: {
+                headers: {
+                    [name: string]: unknown;
+                };
+                content?: never;
+            };
+            default: components["responses"]["Problem"];
+        };
+    };
     getWaveOptions: {
         parameters: {
             query?: never;

packages/i18n/locales/en/common.json

@@ -278,5 +278,17 @@
     "cache": "Recent tracks cache",
     "cache_clear": "Clear ({{size}} MB)",
     "cache_pending": "Will be cleared on next launch"
+  },
+  "onboarding": {
+    "title": "What do you like to listen to?",
+    "subtitle": "Pick a few artists and genres to start My Wave. After that it learns from what you play.",
+    "artists": "Artists",
+    "genres": "Genres",
+    "skip": "Skip",
+    "done": "Done — to the wave",
+    "pick_more_one": "Pick {{count}} more artist",
+    "pick_more_few": "Pick {{count}} more artists",
+    "pick_more_many": "Pick {{count}} more artists",
+    "pick_more_other": "Pick {{count}} more artists"
   }
 }

packages/i18n/locales/ru/common.json

@@ -278,5 +278,17 @@
     "cache": "Кэш недавних треков",
     "cache_clear": "Очистить ({{size}} МБ)",
     "cache_pending": "Очистится при следующем запуске"
+  },
+  "onboarding": {
+    "title": "Что вы любите слушать?",
+    "subtitle": "Отметьте несколько исполнителей и жанров — с них начнётся «Моя волна». Дальше она будет учиться на ваших прослушиваниях.",
+    "artists": "Исполнители",
+    "genres": "Жанры",
+    "skip": "Пропустить",
+    "done": "Готово — к волне",
+    "pick_more_one": "Выберите ещё {{count}} исполнителя",
+    "pick_more_few": "Выберите ещё {{count}} исполнителя",
+    "pick_more_many": "Выберите ещё {{count}} исполнителей",
+    "pick_more_other": "Выберите ещё {{count}} исполнителя"
   }
 }

services/api/cmd/api/e2e_test.go

@@ -271,6 +271,19 @@ func TestUserJourney(t *testing.T) {
 	c.ok("GET", "/api/v1/me/likes", nil, &likes)
 	require.Equal(t, 1, likes.Total)
 
+	// 7½. Онбординг: варианты из библиотеки, выбор сохраняется, второй раз не предлагается.
+	var onb struct {
+		Required bool `json:"required"`
+		Artists  []struct {
+			ID string `json:"id"`
+		} `json:"artists"`
+	}
+	c.ok("GET", "/api/v1/onboarding", nil, &onb)
+	require.NotEmpty(t, onb.Artists)
+	c.ok("PUT", "/api/v1/me/onboarding", map[string]any{"artist_ids": []string{onb.Artists[0].ID}, "genres": []string{}}, nil)
+	c.ok("GET", "/api/v1/onboarding", nil, &onb)
+	require.False(t, onb.Required)
+
 	// 8. «Моя волна»: рекомендатель недоступен — запасная волна из библиотеки.
 	var wave struct {
 		SessionID string  `json:"session_id"`

services/api/go.mod

@@ -6,6 +6,7 @@ tool github.com/oapi-codegen/oapi-codegen/v2/cmd/oapi-codegen
 
 require (
 	github.com/caarlos0/env/v11 v11.3.1
+	github.com/cespare/xxhash/v2 v2.3.0
 	github.com/getkin/kin-openapi v0.127.0
 	github.com/go-chi/chi/v5 v5.2.2
 	github.com/golang-jwt/jwt/v5 v5.2.2
@@ -16,11 +17,12 @@ require (
 	github.com/redis/go-redis/v9 v9.10.0
 	github.com/stretchr/testify v1.10.0
 	golang.org/x/crypto v0.38.0
+	golang.org/x/sys v0.33.0
+	golang.org/x/text v0.25.0
 )
 
 require (
 	github.com/apapsch/go-jsonmerge/v2 v2.0.0 // indirect
-	github.com/cespare/xxhash/v2 v2.3.0 // indirect
 	github.com/davecgh/go-spew v1.1.1 // indirect
 	github.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f // indirect
 	github.com/dprotaso/go-yit v0.0.0-20220510233725-9ba8df137936 // indirect
@@ -43,8 +45,6 @@ require (
 	go.uber.org/multierr v1.11.0 // indirect
 	golang.org/x/mod v0.17.0 // indirect
 	golang.org/x/sync v0.14.0 // indirect
-	golang.org/x/sys v0.33.0 // indirect
-	golang.org/x/text v0.25.0 // indirect
 	golang.org/x/tools v0.21.1-0.20240508182429-e35e4ccd0d2d // indirect
 	gopkg.in/yaml.v2 v2.4.0 // indirect
 	gopkg.in/yaml.v3 v3.0.1 // indirect

services/api/internal/api/gen/api.gen.go

@@ -488,6 +488,30 @@ type Me struct {
 	Username              string             `json:"username"`
 }
 
+// Onboarding defines model for Onboarding.
+type Onboarding struct {
+	Artists []struct {
+		CoverColors []string `json:"cover_colors"`
+
+		// CoverUrl Обложка самого большого альбома исполнителя
+		CoverUrl   *string            `json:"cover_url"`
+		Id         openapi_types.UUID `json:"id"`
+		Name       string             `json:"name"`
+		TrackCount int                `json:"track_count"`
+	} `json:"artists"`
+	Genres []struct {
+		Name       string `json:"name"`
+		TrackCount int    `json:"track_count"`
+	} `json:"genres"`
+	Required bool `json:"required"`
+}
+
+// OnboardingChoice defines model for OnboardingChoice.
+type OnboardingChoice struct {
+	ArtistIds []openapi_types.UUID `json:"artist_ids"`
+	Genres    []string             `json:"genres"`
+}
+
 // PathPattern defines model for PathPattern.
 type PathPattern struct {
 	IsEnabled bool   `json:"is_enabled"`
@@ -1394,6 +1418,9 @@ type UpdateMeJSONRequestBody = UpdateMeRequest
 // SetBootstrapCredentialsJSONRequestBody defines body for SetBootstrapCredentials for application/json ContentType.
 type SetBootstrapCredentialsJSONRequestBody = BootstrapCredentialsRequest
 
+// SaveOnboardingJSONRequestBody defines body for SaveOnboarding for application/json ContentType.
+type SaveOnboardingJSONRequestBody = OnboardingChoice
+
 // ChangePasswordJSONRequestBody defines body for ChangePassword for application/json ContentType.
 type ChangePasswordJSONRequestBody = ChangePasswordRequest
 
@@ -1564,6 +1591,9 @@ type ServerInterface interface {
 	// Лайки, новые сверху
 	// (GET /api/v1/me/likes)
 	GetLikes(w http.ResponseWriter, r *http.Request, params GetLikesParams)
+	// Сохранить выбор онбординга (или пропуск — пустые списки)
+	// (PUT /api/v1/me/onboarding)
+	SaveOnboarding(w http.ResponseWriter, r *http.Request)
 	// Сменить пароль
 	// (POST /api/v1/me/password)
 	ChangePassword(w http.ResponseWriter, r *http.Request)
@@ -1585,6 +1615,9 @@ type ServerInterface interface {
 	// Завершить сессию на устройстве
 	// (DELETE /api/v1/me/sessions/{id})
 	RevokeMySession(w http.ResponseWriter, r *http.Request, id openapi_types.UUID)
+	// Онбординг вкуса — исполнители и жанры библиотеки для выбора
+	// (GET /api/v1/onboarding)
+	GetOnboarding(w http.ResponseWriter, r *http.Request)
 	// Страница поиска
 	// (GET /api/v1/search)
 	Search(w http.ResponseWriter, r *http.Request, params SearchParams)
@@ -1927,6 +1960,12 @@ func (_ Unimplemented) GetLikes(w http.ResponseWriter, r *http.Request, params G
 	w.WriteHeader(http.StatusNotImplemented)
 }
 
+// Сохранить выбор онбординга (или пропуск — пустые списки)
+// (PUT /api/v1/me/onboarding)
+func (_ Unimplemented) SaveOnboarding(w http.ResponseWriter, r *http.Request) {
+	w.WriteHeader(http.StatusNotImplemented)
+}
+
 // Сменить пароль
 // (POST /api/v1/me/password)
 func (_ Unimplemented) ChangePassword(w http.ResponseWriter, r *http.Request) {
@@ -1969,6 +2008,12 @@ func (_ Unimplemented) RevokeMySession(w http.ResponseWriter, r *http.Request, i
 	w.WriteHeader(http.StatusNotImplemented)
 }
 
+// Онбординг вкуса — исполнители и жанры библиотеки для выбора
+// (GET /api/v1/onboarding)
+func (_ Unimplemented) GetOnboarding(w http.ResponseWriter, r *http.Request) {
+	w.WriteHeader(http.StatusNotImplemented)
+}
+
 // Страница поиска
 // (GET /api/v1/search)
 func (_ Unimplemented) Search(w http.ResponseWriter, r *http.Request, params SearchParams) {
@@ -3519,6 +3564,26 @@ func (siw *ServerInterfaceWrapper) GetLikes(w http.ResponseWriter, r *http.Reque
 	handler.ServeHTTP(w, r)
 }
 
+// SaveOnboarding operation middleware
+func (siw *ServerInterfaceWrapper) SaveOnboarding(w http.ResponseWriter, r *http.Request) {
+
+	ctx := r.Context()
+
+	ctx = context.WithValue(ctx, BearerAuthScopes, []string{})
+
+	r = r.WithContext(ctx)
+
+	handler := http.Handler(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		siw.Handler.SaveOnboarding(w, r)
+	}))
+
+	for _, middleware := range siw.HandlerMiddlewares {
+		handler = middleware(handler)
+	}
+
+	handler.ServeHTTP(w, r)
+}
+
 // ChangePassword operation middleware
 func (siw *ServerInterfaceWrapper) ChangePassword(w http.ResponseWriter, r *http.Request) {
 
@@ -3692,6 +3757,26 @@ func (siw *ServerInterfaceWrapper) RevokeMySession(w http.ResponseWriter, r *htt
 	handler.ServeHTTP(w, r)
 }
 
+// GetOnboarding operation middleware
+func (siw *ServerInterfaceWrapper) GetOnboarding(w http.ResponseWriter, r *http.Request) {
+
+	ctx := r.Context()
+
+	ctx = context.WithValue(ctx, BearerAuthScopes, []string{})
+
+	r = r.WithContext(ctx)
+
+	handler := http.Handler(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		siw.Handler.GetOnboarding(w, r)
+	}))
+
+	for _, middleware := range siw.HandlerMiddlewares {
+		handler = middleware(handler)
+	}
+
+	handler.ServeHTTP(w, r)
+}
+
 // Search operation middleware
 func (siw *ServerInterfaceWrapper) Search(w http.ResponseWriter, r *http.Request) {
 
@@ -4497,6 +4582,9 @@ func HandlerWithOptions(si ServerInterface, options ChiServerOptions) http.Handl
 	r.Group(func(r chi.Router) {
 		r.Get(options.BaseURL+"/api/v1/me/likes", wrapper.GetLikes)
 	})
+	r.Group(func(r chi.Router) {
+		r.Put(options.BaseURL+"/api/v1/me/onboarding", wrapper.SaveOnboarding)
+	})
 	r.Group(func(r chi.Router) {
 		r.Post(options.BaseURL+"/api/v1/me/password", wrapper.ChangePassword)
 	})
@@ -4518,6 +4606,9 @@ func HandlerWithOptions(si ServerInterface, options ChiServerOptions) http.Handl
 	r.Group(func(r chi.Router) {
 		r.Delete(options.BaseURL+"/api/v1/me/sessions/{id}", wrapper.RevokeMySession)
 	})
+	r.Group(func(r chi.Router) {
+		r.Get(options.BaseURL+"/api/v1/onboarding", wrapper.GetOnboarding)
+	})
 	r.Group(func(r chi.Router) {
 		r.Get(options.BaseURL+"/api/v1/search", wrapper.Search)
 	})
@@ -5956,6 +6047,34 @@ func (response GetLikesdefaultApplicationProblemPlusJSONResponse) VisitGetLikesR
 	return json.NewEncoder(w).Encode(response.Body)
 }
 
+type SaveOnboardingRequestObject struct {
+	Body *SaveOnboardingJSONRequestBody
+}
+
+type SaveOnboardingResponseObject interface {
+	VisitSaveOnboardingResponse(w http.ResponseWriter) error
+}
+
+type SaveOnboarding204Response struct {
+}
+
+func (response SaveOnboarding204Response) VisitSaveOnboardingResponse(w http.ResponseWriter) error {
+	w.WriteHeader(204)
+	return nil
+}
+
+type SaveOnboardingdefaultApplicationProblemPlusJSONResponse struct {
+	Body       Problem
+	StatusCode int
+}
+
+func (response SaveOnboardingdefaultApplicationProblemPlusJSONResponse) VisitSaveOnboardingResponse(w http.ResponseWriter) error {
+	w.Header().Set("Content-Type", "application/problem+json")
+	w.WriteHeader(response.StatusCode)
+
+	return json.NewEncoder(w).Encode(response.Body)
+}
+
 type ChangePasswordRequestObject struct {
 	Body *ChangePasswordJSONRequestBody
 }
@@ -6155,6 +6274,34 @@ func (response RevokeMySessiondefaultApplicationProblemPlusJSONResponse) VisitRe
 	return json.NewEncoder(w).Encode(response.Body)
 }
 
+type GetOnboardingRequestObject struct {
+}
+
+type GetOnboardingResponseObject interface {
+	VisitGetOnboardingResponse(w http.ResponseWriter) error
+}
+
+type GetOnboarding200JSONResponse Onboarding
+
+func (response GetOnboarding200JSONResponse) VisitGetOnboardingResponse(w http.ResponseWriter) error {
+	w.Header().Set("Content-Type", "application/json")
+	w.WriteHeader(200)
+
+	return json.NewEncoder(w).Encode(response)
+}
+
+type GetOnboardingdefaultApplicationProblemPlusJSONResponse struct {
+	Body       Problem
+	StatusCode int
+}
+
+func (response GetOnboardingdefaultApplicationProblemPlusJSONResponse) VisitGetOnboardingResponse(w http.ResponseWriter) error {
+	w.Header().Set("Content-Type", "application/problem+json")
+	w.WriteHeader(response.StatusCode)
+
+	return json.NewEncoder(w).Encode(response.Body)
+}
+
 type SearchRequestObject struct {
 	Params SearchParams
 }
@@ -6812,6 +6959,9 @@ type StrictServerInterface interface {
 	// Лайки, новые сверху
 	// (GET /api/v1/me/likes)
 	GetLikes(ctx context.Context, request GetLikesRequestObject) (GetLikesResponseObject, error)
+	// Сохранить выбор онбординга (или пропуск — пустые списки)
+	// (PUT /api/v1/me/onboarding)
+	SaveOnboarding(ctx context.Context, request SaveOnboardingRequestObject) (SaveOnboardingResponseObject, error)
 	// Сменить пароль
 	// (POST /api/v1/me/password)
 	ChangePassword(ctx context.Context, request ChangePasswordRequestObject) (ChangePasswordResponseObject, error)
@@ -6833,6 +6983,9 @@ type StrictServerInterface interface {
 	// Завершить сессию на устройстве
 	// (DELETE /api/v1/me/sessions/{id})
 	RevokeMySession(ctx context.Context, request RevokeMySessionRequestObject) (RevokeMySessionResponseObject, error)
+	// Онбординг вкуса — исполнители и жанры библиотеки для выбора
+	// (GET /api/v1/onboarding)
+	GetOnboarding(ctx context.Context, request GetOnboardingRequestObject) (GetOnboardingResponseObject, error)
 	// Страница поиска
 	// (GET /api/v1/search)
 	Search(ctx context.Context, request SearchRequestObject) (SearchResponseObject, error)
@@ -8220,6 +8373,37 @@ func (sh *strictHandler) GetLikes(w http.ResponseWriter, r *http.Request, params
 	}
 }
 
+// SaveOnboarding operation middleware
+func (sh *strictHandler) SaveOnboarding(w http.ResponseWriter, r *http.Request) {
+	var request SaveOnboardingRequestObject
+
+	var body SaveOnboardingJSONRequestBody
+	if err := json.NewDecoder(r.Body).Decode(&body); err != nil {
+		sh.options.RequestErrorHandlerFunc(w, r, fmt.Errorf("can't decode JSON body: %w", err))
+		return
+	}
+	request.Body = &body
+
+	handler := func(ctx context.Context, w http.ResponseWriter, r *http.Request, request interface{}) (interface{}, error) {
+		return sh.ssi.SaveOnboarding(ctx, request.(SaveOnboardingRequestObject))
+	}
+	for _, middleware := range sh.middlewares {
+		handler = middleware(handler, "SaveOnboarding")
+	}
+
+	response, err := handler(r.Context(), w, r, request)
+
+	if err != nil {
+		sh.options.ResponseErrorHandlerFunc(w, r, err)
+	} else if validResponse, ok := response.(SaveOnboardingResponseObject); ok {
+		if err := validResponse.VisitSaveOnboardingResponse(w); err != nil {
+			sh.options.ResponseErrorHandlerFunc(w, r, err)
+		}
+	} else if response != nil {
+		sh.options.ResponseErrorHandlerFunc(w, r, fmt.Errorf("unexpected response type: %T", response))
+	}
+}
+
 // ChangePassword operation middleware
 func (sh *strictHandler) ChangePassword(w http.ResponseWriter, r *http.Request) {
 	var request ChangePasswordRequestObject
@@ -8415,6 +8599,30 @@ func (sh *strictHandler) RevokeMySession(w http.ResponseWriter, r *http.Request,
 	}
 }
 
+// GetOnboarding operation middleware
+func (sh *strictHandler) GetOnboarding(w http.ResponseWriter, r *http.Request) {
+	var request GetOnboardingRequestObject
+
+	handler := func(ctx context.Context, w http.ResponseWriter, r *http.Request, request interface{}) (interface{}, error) {
+		return sh.ssi.GetOnboarding(ctx, request.(GetOnboardingRequestObject))
+	}
+	for _, middleware := range sh.middlewares {
+		handler = middleware(handler, "GetOnboarding")
+	}
+
+	response, err := handler(r.Context(), w, r, request)
+
+	if err != nil {
+		sh.options.ResponseErrorHandlerFunc(w, r, err)
+	} else if validResponse, ok := response.(GetOnboardingResponseObject); ok {
+		if err := validResponse.VisitGetOnboardingResponse(w); err != nil {
+			sh.options.ResponseErrorHandlerFunc(w, r, err)
+		}
+	} else if response != nil {
+		sh.options.ResponseErrorHandlerFunc(w, r, fmt.Errorf("unexpected response type: %T", response))
+	}
+}
+
 // Search operation middleware
 func (sh *strictHandler) Search(w http.ResponseWriter, r *http.Request, params SearchParams) {
 	var request SearchRequestObject
@@ -8911,241 +9119,246 @@ func (sh *strictHandler) GetReadyz(w http.ResponseWriter, r *http.Request) {
 // Base64 encoded, gzipped, json marshaled Swagger object
 var swaggerSpec = []string{
 
-	"H4sIAAAAAAAC/+x9/2/cRpbnv0L07gHSbFuSHTuzI2NxcJxk4tt4orGcyx3Gvm6quyRxzSbbJFu2xjAg",
-	"WZM4OXmscW52d7A7SSY7t7gD8ktLVlttfQXyFxT/hflLDvVeFVlFFr+0xJaTxf1kq5tdrHr16tX7+nmP",
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+	"WsbdvgaJAgLhtz3heH4OPLGPLqozsyaoOkUqMW7UL+CxidMDh9GR4V8FpgqG7WAHeB4JL0PD26YOQvwL",
+	"19vSDXWK+t+MTYD75hqZdWF9hdnXH5hr5H3+2CQbcEnDVAid1hVTRxKO0KOWAjEUtaJxY37hNbQu/63D",
+	"WyzwWGJZUi5stpxYovcQLAamBxs+qQaE5hqBMfRYDpdrHUiqQS5Kl5DA/OM00sfnKy9PSPwlvAyVs+++",
+	"Zddr9BQDUIf0ONr67rA61UqzU952ujHpSvXVf34VSSJi3dvZVTdraX+lq7ydMDtfZy96cPEdNAsZPIVV",
+	"Uhs7pxKhkzuIXQGzGvnFY8AGuymiR7HNFlu6SQsyuFOgq6oImo15NGYdRoZJNKH6OXkwaaH4c85Cr45l",
+	"vq6XTyBdm3eBVPkQ6u5FJyBA05YSV5mCx/GitpVa2QTCUM8Wq8S0g9VfFykS7/JHJlkzB0OgOVoAnfAJ",
+	"71uOrv7igME/QTQgDuKeyi9QszrkeKFHzO564W7cwicmW3PWXS/YC16uvs8Dg5tJtJq7NgXas/C3X5l7",
+	"/cIm9xUUG8QhRE1GmHbiQ2TgYXb6RTT+X6Btn2DzD0HpE/oMK55EQCiRuSLlZtuYqrh901pGUef0UWOJ",
+	"mB7xroXBKpsiE4iY8ICCNPTsxnxjFgQlf9dHcXQQ3/mw+ZHcL1X+u0eUb6HHgPSBaAArfSR89tJHPCdD",
+	"+iSOh8k/THKrpU9BWMhT6PcbD+8+/H8BAAD//3i1BR+BNQEA",
 }
 
 // GetSwagger returns the content of the embedded swagger specification file

services/api/internal/search/meili.go

@@ -77,6 +77,7 @@ func (m *Meili) wait(ctx context.Context, t taskRef) error {
 			Status string `json:"status"`
 			Error  *struct {
 				Message string `json:"message"`
+				Code    string `json:"code"`
 			} `json:"error"`
 		}
 		if err := m.do(ctx, http.MethodGet, fmt.Sprintf("/tasks/%d", t.TaskUID), nil, &task); err != nil {
@@ -88,6 +89,10 @@ func (m *Meili) wait(ctx context.Context, t taskRef) error {
 		case "failed", "canceled":
 			msg := task.Status
 			if task.Error != nil {
+				// Удаление отсутствующего индекса принимается (202) и падает уже в задаче.
+				if task.Error.Code == "index_not_found" {
+					return fmt.Errorf("%w: task %d: %s", ErrMeiliNotFound, t.TaskUID, task.Error.Message)
+				}
 				msg = task.Error.Message
 			}
 			return fmt.Errorf("meilisearch: task %d: %s", t.TaskUID, msg)

services/api/internal/search/meili_test.go

@@ -0,0 +1,28 @@
+package search
+
+import (
+	"context"
+	"errors"
+	"net/http"
+	"net/http/httptest"
+	"testing"
+)
+
+// На чистом Meilisearch удаление несуществующего индекса падает в задаче, а не ответом 404.
+func TestCallMapsFailedIndexTaskToNotFound(t *testing.T) {
+	srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
+		w.Header().Set("Content-Type", "application/json")
+		if r.Method == http.MethodDelete {
+			w.WriteHeader(http.StatusAccepted)
+			_, _ = w.Write([]byte(`{"taskUid":0}`))
+			return
+		}
+		_, _ = w.Write([]byte(`{"status":"failed","error":{"code":"index_not_found","message":"Index ` + "`x`" + ` not found."}}`))
+	}))
+	defer srv.Close()
+
+	err := NewMeili(srv.URL, "").call(context.Background(), http.MethodDelete, "/indexes/x", nil)
+	if !errors.Is(err, ErrMeiliNotFound) {
+		t.Fatalf("err = %v, want ErrMeiliNotFound", err)
+	}
+}

services/api/internal/storageagent/access_other.go

@@ -0,0 +1,20 @@
+//go:build !unix
+
+package storageagent
+
+import (
+	"errors"
+	"os"
+)
+
+// canWrite — запасная проверка для не-Unix (только разработка): бит записи у каталога.
+func canWrite(dir string) error {
+	info, err := os.Stat(dir)
+	if err != nil {
+		return err
+	}
+	if info.Mode().Perm()&0o200 == 0 {
+		return errors.New("directory is not writable")
+	}
+	return nil
+}

services/api/internal/storageagent/access_unix.go

@@ -0,0 +1,18 @@
+//go:build unix
+
+package storageagent
+
+import (
+	"errors"
+
+	"golang.org/x/sys/unix"
+)
+
+// canWrite — можно ли создавать файлы в каталоге (без пробной записи); read-only монтирование — ошибка.
+func canWrite(dir string) error {
+	var st unix.Statfs_t
+	if err := unix.Statfs(dir, &st); err == nil && st.Flags&unix.ST_RDONLY != 0 {
+		return errors.New("filesystem is mounted read-only")
+	}
+	return unix.Access(dir, unix.W_OK|unix.X_OK)
+}

services/api/internal/storageagent/files.go

@@ -142,27 +142,19 @@ func (a *agent) writeFile(w http.ResponseWriter, r *http.Request) {
 	writeJSON(w, http.StatusOK, res)
 }
 
-// write копирует staging во временный файл рядом с целью, fsync, сверяет SHA-256 и создаёт итоговое имя
-// жёсткой ссылкой (не перезаписывает существующий файл, в отличие от rename), затем убирает временный.
+// write копирует staging сразу под итоговым именем (O_EXCL — существующий файл не перезаписывается, при
+// конфликте — « (2)»), fsync, сверяет SHA-256 копии. На музыкальный диск не попадает ничего, кроме самого трека:
+// ни временных файлов, ни служебных пометок. При любой ошибке недописанный файл и созданные для него пустые
+// каталоги удаляются — агент убирает только то, что создал сам.
 func (a *agent) write(root, rel, staging string, want []byte) (WriteResult, error) {
-	target := filepath.Join(root, filepath.FromSlash(rel))
-	dir := filepath.Dir(target)
-	if err := a.mkdirs(root, dir); err != nil {
-		return WriteResult{}, err
-	}
-	tmp := filepath.Join(dir, "."+filepath.Base(target)+".pipu-tmp")
-	size, err := a.copyTemp(staging, tmp)
-	if err != nil {
-		_ = os.Remove(tmp)
-		return WriteResult{}, err
-	}
-	defer func() { _ = os.Remove(tmp) }()
-	got, err := fileSHA256(tmp)
+	dir := filepath.Dir(filepath.Join(root, filepath.FromSlash(rel)))
+	created, err := a.mkdirs(root, dir)
 	if err != nil {
 		return WriteResult{}, err
 	}
-	if !bytes.Equal(got, want) {
-		return WriteResult{}, fmt.Errorf("checksum mismatch: copy %x, expected %x", got, want)
+	fail := func(err error) (WriteResult, error) {
+		removeEmpty(created)
+		return WriteResult{}, err
 	}
 
 	ext := path.Ext(rel)
@@ -172,24 +164,39 @@ func (a *agent) write(root, rel, staging string, want []byte) (WriteResult, erro
 		if n > 1 {
 			name = fmt.Sprintf("%s (%d)%s", base, n, ext)
 		}
-		err := os.Link(tmp, filepath.Join(root, filepath.FromSlash(name)))
+		target := filepath.Join(root, filepath.FromSlash(name))
+		dst, err := os.OpenFile(target, os.O_CREATE|os.O_EXCL|os.O_WRONLY, 0o644)
+		if os.IsExist(err) {
+			continue
+		}
+		if err != nil {
+			return fail(fmt.Errorf("create: %w", err))
+		}
+		size, err := copyInto(dst, staging)
 		if err == nil {
-			syncDir(dir)
-			return WriteResult{RelPath: name, Size: size, Renamed: n > 1}, nil
+			var got []byte
+			if got, err = fileSHA256(target); err == nil && !bytes.Equal(got, want) {
+				err = fmt.Errorf("checksum mismatch: copy %x, expected %x", got, want)
+			}
 		}
-		if !os.IsExist(err) {
-			return WriteResult{}, fmt.Errorf("link: %w", err)
+		if err != nil {
+			_ = os.Remove(target) // наш собственный недописанный / испорченный файл
+			return fail(err)
 		}
+		a.chown(target)
+		syncDir(dir)
+		return WriteResult{RelPath: name, Size: size, Renamed: n > 1}, nil
 	}
-	return WriteResult{}, errors.New("too many files with the same name")
+	return fail(errors.New("too many files with the same name"))
 }
 
-// mkdirs создаёт недостающие каталоги от root до dir (0755, владелец — FileUID/FileGID).
-func (a *agent) mkdirs(root, dir string) error {
+// mkdirs создаёт недостающие каталоги от root до dir (0755, владелец — FileUID/FileGID) и возвращает созданные.
+func (a *agent) mkdirs(root, dir string) ([]string, error) {
 	rel, err := filepath.Rel(root, dir)
 	if err != nil || strings.HasPrefix(rel, "..") {
-		return errBadPath
+		return nil, errBadPath
 	}
+	var created []string
 	cur := root
 	for _, seg := range strings.Split(rel, string(filepath.Separator)) {
 		if seg == "." || seg == "" {
@@ -200,24 +207,30 @@ func (a *agent) mkdirs(root, dir string) error {
 			if os.IsExist(err) {
 				continue
 			}
-			return fmt.Errorf("mkdir: %w", err)
+			removeEmpty(created)
+			return nil, fmt.Errorf("mkdir: %w", err)
 		}
+		created = append(created, cur)
 		a.chown(cur)
 	}
-	return nil
+	return created, nil
 }
 
-func (a *agent) copyTemp(staging, tmp string) (int64, error) {
+// removeEmpty удаляет созданные каталоги от глубоких к верхним; os.Remove не трогает непустые.
+func removeEmpty(dirs []string) {
+	for i := len(dirs) - 1; i >= 0; i-- {
+		_ = os.Remove(dirs[i])
+	}
+}
+
+// copyInto копирует staging в открытый файл и делает fsync; файл закрывается.
+func copyInto(dst *os.File, staging string) (int64, error) {
 	src, err := os.Open(staging)
 	if err != nil {
+		_ = dst.Close()
 		return 0, fmt.Errorf("staging: %w", err)
 	}
 	defer func() { _ = src.Close() }()
-	_ = os.Remove(tmp) // остаток прерванной попытки
-	dst, err := os.OpenFile(tmp, os.O_CREATE|os.O_EXCL|os.O_WRONLY, 0o644)
-	if err != nil {
-		return 0, fmt.Errorf("create temp: %w", err)
-	}
 	n, err := io.Copy(dst, src)
 	if err == nil {
 		err = dst.Sync()
@@ -228,7 +241,6 @@ func (a *agent) copyTemp(staging, tmp string) (int64, error) {
 	if err != nil {
 		return 0, fmt.Errorf("copy: %w", err)
 	}
-	a.chown(tmp)
 	return n, nil
 }
 
@@ -240,7 +252,8 @@ func (a *agent) chown(p string) {
 	}
 }
 
-// testWrite создаёт и удаляет .pipu-write-test в корне источника на запись.
+// testWrite проверяет право записи в корень источника, ничего не создавая на диске (access(W_OK);
+// на NFS ответ даёт сам сервер с учётом root_squash и прав экспорта).
 func (a *agent) testWrite(w http.ResponseWriter, r *http.Request) {
 	var req WriteTestRequest
 	if !a.decode(w, r, &req) {
@@ -251,16 +264,7 @@ func (a *agent) testWrite(w http.ResponseWriter, r *http.Request) {
 		writeJSON(w, http.StatusOK, WriteTestResult{Message: err.Error()})
 		return
 	}
-	p := filepath.Join(root, ".pipu-write-test")
-	f, err := os.OpenFile(p, os.O_CREATE|os.O_TRUNC|os.O_WRONLY, 0o644)
-	if err == nil {
-		_, err = f.WriteString("pipu")
-		if cerr := f.Close(); err == nil {
-			err = cerr
-		}
-	}
-	_ = os.Remove(p)
-	if err != nil {
+	if err := canWrite(root); err != nil {
 		writeJSON(w, http.StatusOK, WriteTestResult{Message: "cannot write: " + err.Error()})
 		return
 	}

services/api/internal/storageagent/files_test.go

@@ -9,6 +9,7 @@ import (
 	"net/http/httptest"
 	"os"
 	"path/filepath"
+	"strings"
 	"testing"
 
 	"github.com/stretchr/testify/assert"
@@ -74,6 +75,7 @@ func TestWriteFile(t *testing.T) {
 	assert.True(t, res.Renamed)
 	entries, _ := os.ReadDir(dir)
 	assert.Len(t, entries, 2)
+	assertOnlyMusic(t, filepath.Join(e.paths.LibraryRW, srcID))
 
 	// Local-источник пишется в LIBRARY_HOST.
 	local := "music"
@@ -103,8 +105,21 @@ func TestWriteFileRejects(t *testing.T) {
 	other := sha256.Sum256([]byte("other"))
 	rec := e.post("/internal/files", WriteRequest{SourceID: srcID, RelPath: "A/x.flac", StagingPath: "u1/f1", SHA256: hex.EncodeToString(other[:])})
 	assert.Equal(t, http.StatusInternalServerError, rec.Code)
-	entries, _ := os.ReadDir(filepath.Join(e.paths.LibraryRW, srcID, "A"))
-	assert.Empty(t, entries)
+	// Созданная под файл папка тоже убрана: на диске не остаётся следов неудачной записи.
+	assert.NoDirExists(t, filepath.Join(e.paths.LibraryRW, srcID, "A"))
+	assertOnlyMusic(t, filepath.Join(e.paths.LibraryRW, srcID))
+}
+
+// assertOnlyMusic — в дереве хранилища только аудиофайлы и каталоги: ни временных, ни служебных файлов.
+func assertOnlyMusic(t *testing.T, root string) {
+	t.Helper()
+	require.NoError(t, filepath.WalkDir(root, func(p string, d os.DirEntry, err error) error {
+		if err != nil || d.IsDir() {
+			return err
+		}
+		assert.True(t, audioExt[strings.ToLower(filepath.Ext(p))] && !strings.HasPrefix(d.Name(), "."), "unexpected file %s", p)
+		return nil
+	}))
 }
 
 func TestWritableMount(t *testing.T) {
@@ -120,7 +135,8 @@ func TestWritableMount(t *testing.T) {
 	var res WriteTestResult
 	require.NoError(t, json.Unmarshal(rec.Body.Bytes(), &res))
 	assert.True(t, res.OK, res.Message)
-	assert.NoFileExists(t, filepath.Join(rw, ".pipu-write-test"))
+	entries, _ := os.ReadDir(rw)
+	assert.Empty(t, entries, "write check creates nothing")
 
 	// Без accepts_uploads rw-точка снимается.
 	e.post("/internal/mounts", MountRequest{SourceID: srcID, NFSSpec: NFSSpec{Server: "nas", Export: "/music"}})

services/api/internal/wave/onboarding.go

@@ -0,0 +1,141 @@
+package wave
+
+import (
+	"context"
+	"encoding/json"
+	"fmt"
+
+	"github.com/google/uuid"
+
+	"pipu/api/internal/api/gen"
+)
+
+// Онбординг вкуса (docs/recommendations.md#7): новый пользователь отмечает исполнителей и жанры — рекомендатель
+// берёт их как начальный вкус, пока своей истории мало. Пропуск сохраняется пустым выбором.
+
+const (
+	onboardingArtists = 40
+	onboardingGenres  = 24
+	// История, после которой онбординг уже не предлагается: вкус и так виден по прослушиваниям.
+	onboardingMinHistory = 10
+)
+
+// GetOnboarding реализует gen.StrictServerInterface.
+func (h *Handler) GetOnboarding(ctx context.Context, _ gen.GetOnboardingRequestObject) (gen.GetOnboardingResponseObject, error) {
+	p, err := principal(ctx)
+	if err != nil {
+		return nil, err
+	}
+	out := gen.GetOnboarding200JSONResponse{}
+	var done bool
+	var plays int
+	if err := h.pool.QueryRow(ctx, `
+		SELECT EXISTS (SELECT 1 FROM user_profiles_rec WHERE user_id = $1 AND onboarding IS NOT NULL),
+			(SELECT count(*) FROM user_track_stats WHERE user_id = $1)`, p.UserID).Scan(&done, &plays); err != nil {
+		return nil, fmt.Errorf("wave: onboarding state: %w", err)
+	}
+
+	rows, err := h.pool.Query(ctx, `
+		SELECT a.id, a.name, count(*) AS n,
+			(SELECT al.id FROM albums al WHERE al.album_artist_id = a.id
+				ORDER BY (SELECT count(*) FROM tracks t WHERE t.album_id = al.id) DESC, al.id LIMIT 1)
+		FROM artists a JOIN track_artists ta ON ta.artist_id = a.id AND ta.role = 'main'
+		GROUP BY a.id ORDER BY n DESC, a.name LIMIT $1`, onboardingArtists)
+	if err != nil {
+		return nil, fmt.Errorf("wave: onboarding artists: %w", err)
+	}
+	type artist struct {
+		id, album *uuid.UUID
+		name      string
+		n         int
+	}
+	var artists []artist
+	for rows.Next() {
+		var a artist
+		var id uuid.UUID
+		if err := rows.Scan(&id, &a.name, &a.n, &a.album); err != nil {
+			rows.Close()
+			return nil, fmt.Errorf("wave: onboarding artists: %w", err)
+		}
+		a.id = &id
+		artists = append(artists, a)
+	}
+	rows.Close()
+	dto := h.dto()
+	for _, a := range artists {
+		item := struct {
+			CoverColors []string  `json:"cover_colors"`
+			CoverUrl    *string   `json:"cover_url"`
+			Id          uuid.UUID `json:"id"`
+			Name        string    `json:"name"`
+			TrackCount  int       `json:"track_count"`
+		}{Id: *a.id, Name: a.name, TrackCount: a.n, CoverColors: []string{}}
+		if a.album != nil {
+			if al, err := h.catalog.Album(ctx, *a.album); err == nil {
+				sum := dto.AlbumSummary(al)
+				item.CoverUrl, item.CoverColors = sum.CoverUrl, sum.CoverColors
+			}
+		}
+		out.Artists = append(out.Artists, item)
+	}
+
+	grows, err := h.pool.Query(ctx, `
+		SELECT g.name, count(DISTINCT tg.track_id) AS n FROM track_genres tg JOIN genres g ON g.id = tg.genre_id
+		GROUP BY g.name ORDER BY n DESC, g.name LIMIT $1`, onboardingGenres)
+	if err != nil {
+		return nil, fmt.Errorf("wave: onboarding genres: %w", err)
+	}
+	for grows.Next() {
+		var g struct {
+			Name       string `json:"name"`
+			TrackCount int    `json:"track_count"`
+		}
+		if err := grows.Scan(&g.Name, &g.TrackCount); err != nil {
+			grows.Close()
+			return nil, fmt.Errorf("wave: onboarding genres: %w", err)
+		}
+		out.Genres = append(out.Genres, g)
+	}
+	grows.Close()
+	if out.Artists == nil {
+		out.Artists = []struct {
+			CoverColors []string  `json:"cover_colors"`
+			CoverUrl    *string   `json:"cover_url"`
+			Id          uuid.UUID `json:"id"`
+			Name        string    `json:"name"`
+			TrackCount  int       `json:"track_count"`
+		}{}
+	}
+	if out.Genres == nil {
+		out.Genres = []struct {
+			Name       string `json:"name"`
+			TrackCount int    `json:"track_count"`
+		}{}
+	}
+	out.Required = !done && plays < onboardingMinHistory && len(out.Artists) > 0
+	return out, nil
+}
+
+// SaveOnboarding реализует gen.StrictServerInterface.
+func (h *Handler) SaveOnboarding(ctx context.Context, req gen.SaveOnboardingRequestObject) (gen.SaveOnboardingResponseObject, error) {
+	p, err := principal(ctx)
+	if err != nil {
+		return nil, err
+	}
+	ids := req.Body.ArtistIds
+	if ids == nil {
+		ids = []uuid.UUID{}
+	}
+	genres := req.Body.Genres
+	if genres == nil {
+		genres = []string{}
+	}
+	raw, _ := json.Marshal(map[string]any{"artist_ids": ids, "genres": genres})
+	if _, err := h.pool.Exec(ctx, `
+		INSERT INTO user_profiles_rec (user_id, onboarding, updated_at) VALUES ($1, $2, now())
+		ON CONFLICT (user_id) DO UPDATE SET onboarding = EXCLUDED.onboarding, updated_at = now()`,
+		p.UserID, raw); err != nil {
+		return nil, fmt.Errorf("wave: save onboarding: %w", err)
+	}
+	return gen.SaveOnboarding204Response{}, nil
+}

services/api/migrations/00009_onboarding.sql

@@ -0,0 +1,7 @@
+-- +goose Up
+-- Онбординг «Моей волны» (docs/recommendations.md#7): выбранные исполнители и жанры — начальный вкус,
+-- пока своей истории мало. NULL — онбординг ещё не пройден и не пропущен.
+ALTER TABLE user_profiles_rec ADD COLUMN onboarding jsonb;
+
+-- +goose Down
+ALTER TABLE user_profiles_rec DROP COLUMN onboarding;

services/api/migrations/00010_ranker.sql

@@ -0,0 +1,17 @@
+-- +goose Up
+-- Ранжировщик волны v2 (docs/recommendations.md#6.3): признаки кандидата в момент показа — для обучения
+-- LightGBM на исходах показов (wave_impressions.outcome); артефакт модели хранится в model_versions.
+CREATE TABLE rec_impression_features (
+  wave_session_id uuid NOT NULL REFERENCES wave_sessions(id) ON DELETE CASCADE,
+  track_id        uuid NOT NULL,
+  features        real[] NOT NULL,
+  served_at       timestamptz NOT NULL DEFAULT now(),
+  PRIMARY KEY (wave_session_id, track_id)
+);
+CREATE INDEX rec_impression_features_served_idx ON rec_impression_features (served_at);
+
+ALTER TABLE model_versions ADD COLUMN artifact text;
+
+-- +goose Down
+ALTER TABLE model_versions DROP COLUMN artifact;
+DROP TABLE rec_impression_features;

services/recommender/Dockerfile

@@ -15,8 +15,8 @@ COPY services/recommender/ ./
 RUN --mount=type=cache,target=/root/.cache/uv uv sync --frozen --no-dev
 
 FROM python:3.12-slim
-# ffmpeg декодирует аудио для анализатора.
-RUN apt-get update && apt-get install -y --no-install-recommends ffmpeg && rm -rf /var/lib/apt/lists/*     && useradd --system --uid 10001 pipu
+# ffmpeg декодирует аудио для анализатора; libgomp1 нужен LightGBM (ранжировщик волны).
+RUN apt-get update && apt-get install -y --no-install-recommends ffmpeg libgomp1 && rm -rf /var/lib/apt/lists/*     && useradd --system --uid 10001 pipu
 COPY --from=build /app /app
 ARG VERSION=0.0.0-dev
 ENV PATH=/app/.venv/bin:$PATH PIPU_VERSION=${VERSION} PYTHONUNBUFFERED=1

services/recommender/pipu_rec/cli.py

@@ -30,7 +30,7 @@ def _serve(settings: Settings) -> None:
     wave = WaveService(settings.database_url, settings.redis_url, load_contexts(settings.contexts_path))
     if settings.train_hour >= 0:
         # После активации новой модели каталог перечитывается сразу — горячая подмена векторов.
-        NightlyTrainer(settings.database_url, settings.train_hour, on_done=wave.index.refresh).start()
+        NightlyTrainer(settings.database_url, settings.train_hour, on_done=wave.reload).start()
     app = create_app(settings, {"postgres": check_postgres, "redis": check_redis}, wave)
     uvicorn.run(app, host=settings.http_host, port=settings.http_port, log_level=settings.log_level)
 

services/recommender/pipu_rec/train/bandit.py

@@ -0,0 +1,68 @@
+"""Бандит по источникам кандидатов (docs/recommendations.md#6.6): Beta(α, β) на пару (пользователь, источник).
+
+Награда — трек из источника доигран или лайкнут; скип и дизлайк — неудача. Наблюдения затухают ×0.99 в день,
+чтобы бандит подстраивался под смену вкуса. Доля «нового» (exploration) следует за успехом источника `fresh`.
+"""
+
+from __future__ import annotations
+
+import json
+from collections import defaultdict
+from typing import Any
+
+import psycopg
+
+DAILY_DECAY = 0.99
+REWARD = {"complete": 1.0, "like": 1.0, "skip": 0.0, "skip_early": 0.0, "dislike": 0.0}
+EXPLORATION_MIN, EXPLORATION_MAX = 0.05, 0.4
+
+Params = dict[str, list[float]]  # источник → [α, β]
+
+
+def compute(rows: list[tuple[str, str, str, float]], now: float) -> dict[str, Params]:
+    """rows: (user, source, outcome, served_at) → user → source → [α, β] с приором Beta(1, 1)."""
+    out: dict[str, Params] = defaultdict(dict)
+    for user, source, outcome, ts in rows:
+        r = REWARD.get(outcome)
+        if r is None:
+            continue
+        w = DAILY_DECAY ** max((now - ts) / 86400.0, 0.0)
+        ab = out[user].setdefault(source, [1.0, 1.0])
+        ab[0] += w * r
+        ab[1] += w * (1.0 - r)
+    return {u: {s: [round(a, 4), round(b, 4)] for s, (a, b) in p.items()} for u, p in out.items()}
+
+
+def exploration(params: Params, default: float = 0.15) -> float:
+    """Доля «нового»: успешнее `fresh` относительно остальных источников — больше исследования."""
+    fresh = params.get("fresh")
+    others = [a / (a + b) for s, (a, b) in params.items() if s != "fresh"]
+    if fresh is None or not others:
+        return default
+    rate = fresh[0] / (fresh[0] + fresh[1])
+    base = sum(others) / len(others)
+    value = default * (rate / base if base > 0 else 1.0)
+    return round(min(max(value, EXPLORATION_MIN), EXPLORATION_MAX), 3)
+
+
+def update_bandits(conn: psycopg.Connection[Any], now: float) -> int:
+    """Пересчитывает параметры по показам волны за 90 дней. Возвращает число пользователей."""
+    rows = conn.execute(
+        """
+        SELECT ws.user_id::text, wi.candidate_source, wi.outcome, extract(epoch FROM wi.served_at)::float8
+        FROM wave_impressions wi JOIN wave_sessions ws ON ws.id = wi.wave_session_id
+        WHERE wi.outcome IS NOT NULL AND wi.served_at > now() - interval '90 days'
+        """
+    ).fetchall()
+    params = compute([(u, s, o, float(ts)) for u, s, o, ts in rows], now)
+    with conn.transaction(), conn.cursor() as cur:
+        cur.executemany(
+            """
+            INSERT INTO user_profiles_rec (user_id, bandit, exploration, updated_at)
+            VALUES (%s, %s, %s, now())
+            ON CONFLICT (user_id) DO UPDATE SET bandit = EXCLUDED.bandit, exploration = EXCLUDED.exploration,
+                updated_at = now()
+            """,
+            [(u, json.dumps(p), exploration(p)) for u, p in params.items()],
+        )
+    return len(params)

services/recommender/pipu_rec/train/pipeline.py

@@ -15,7 +15,9 @@ import numpy as np
 import psycopg
 
 from pipu_rec.train.als import ALSModel, normalize, train_als
+from pipu_rec.train.bandit import update_bandits
 from pipu_rec.train.metrics import evaluate
+from pipu_rec.train.ranker import train_and_save
 from pipu_rec.train.signals import DISLIKE, LIKE, Interaction, event_weight, implicit_scores
 
 log = logging.getLogger(__name__)
@@ -157,9 +159,21 @@ def train_all(dsn: str, now: float | None = None) -> dict[str, Any]:
         if not conn.execute("SELECT pg_try_advisory_lock(%s)", (ADVISORY_LOCK,)).fetchone()[0]:  # type: ignore[index]
             return {"skipped": "another training is running"}
         try:
+            # Бандит считается всегда — ему хватает и пары сессий волны, в отличие от ALS.
+            bandit_users = update_bandits(conn, now)
+            # Ранжировщик v2 учится на показах волны и от числа событий ALS не зависит.
+            try:
+                ranker = train_and_save(conn, now)
+            except Exception as e:  # обучение ранжировщика не должно мешать ALS
+                log.exception("ranker training failed")
+                ranker = {"ranker": {"error": str(e)}}
             interactions = load_interactions(conn)
             if len(interactions) < MIN_INTERACTIONS:
-                return {"skipped": f"only {len(interactions)} interactions"}
+                return {
+                    "skipped": f"only {len(interactions)} interactions",
+                    "bandit_users": bandit_users,
+                    **ranker,
+                }
             started = time.monotonic()
             offline = offline_metrics(interactions, now)
             model = train_als(implicit_scores(interactions, now))
@@ -171,6 +185,7 @@ def train_all(dsn: str, now: float | None = None) -> dict[str, Any]:
                 "users": len(model.users),
                 "items": len(model.items),
                 "interactions": len(interactions),
+                "bandit_users": bandit_users,
                 "train_s": round(time.monotonic() - started, 1),
             }
             if not should_activate(offline, active_metrics(conn, "als")):
@@ -180,10 +195,10 @@ def train_all(dsn: str, now: float | None = None) -> dict[str, Any]:
                     (version, json.dumps(metrics)),
                 )
                 log.warning("als %s not activated: offline metrics regressed %s", version, offline)
-                return {"version": version, "activated": False, **metrics}
+                return {"version": version, "activated": False, **metrics, **ranker}
             save_als(conn, model, version, metrics)
             log.info("als %s activated: %s", version, metrics)
-            return {"version": version, "activated": True, **metrics}
+            return {"version": version, "activated": True, **metrics, **ranker}
         finally:
             conn.execute("SELECT pg_advisory_unlock(%s)", (ADVISORY_LOCK,))
 
@@ -214,7 +229,8 @@ class NightlyTrainer:
         try:
             result = train_all(self.dsn)
             log.info("training finished: %s", result)
-            if result.get("activated") and self.on_done:
+            ranker_on = bool((result.get("ranker") or {}).get("activated"))
+            if (result.get("activated") or ranker_on) and self.on_done:
                 self.on_done()
         except Exception:
             log.exception("training failed")

services/recommender/pipu_rec/train/ranker.py

@@ -0,0 +1,197 @@
+"""Ранжировщик волны v2 — LightGBM lambdarank на показах всех пользователей (docs/recommendations.md#6.3).
+
+Признаки кандидата пишутся в момент показа (rec_impression_features), метка — исход показа:
+3 — лайк, 2 — доиграл, 0 — скип; ранний скип и дизлайк — 0 с весом ×2. Группа — сессия волны.
+Новая модель включается, только если её NDCG@10 на отложенной неделе не хуже порядка по оценке v1 и не хуже
+активной модели более чем на 2%. Пока размеченных показов меньше MIN_ROWS, работает v1.
+"""
+
+from __future__ import annotations
+
+import datetime as dt
+import json
+import logging
+import math
+import threading
+from collections import defaultdict
+from typing import Any
+
+import lightgbm as lgb
+import numpy as np
+import psycopg
+from numpy.typing import NDArray
+
+from pipu_rec.wave.engine import FEATURE_NAMES, FEATURES_VERSION
+
+log = logging.getLogger(__name__)
+
+MIN_ROWS = 20_000
+HOLDOUT_DAYS = 7
+MAX_REGRESSION = 0.02
+LABEL = {"like": 3, "complete": 2, "skip": 0, "skip_early": 0, "dislike": 0}
+WEIGHT = {"skip_early": 2.0, "dislike": 2.0}
+V1_COLUMN = FEATURE_NAMES.index("v1_score")
+
+
+Row = tuple[str, list[float], str, float]  # сессия, признаки, исход, время показа
+
+
+def load_rows(conn: psycopg.Connection[Any]) -> list[Row]:
+    rows = conn.execute(
+        """
+        SELECT f.wave_session_id::text, f.features, wi.outcome, extract(epoch FROM f.served_at)::float8
+        FROM rec_impression_features f
+        JOIN wave_impressions wi ON wi.wave_session_id = f.wave_session_id AND wi.track_id = f.track_id
+        WHERE wi.outcome IS NOT NULL AND f.served_at > now() - interval '90 days'
+        ORDER BY f.wave_session_id, f.served_at
+        """
+    ).fetchall()
+    return [(s, list(x), o, float(ts)) for s, x, o, ts in rows if o in LABEL and len(x) == len(FEATURE_NAMES)]
+
+
+def _groups(rows: list[Row]) -> list[list[Row]]:
+    by: dict[str, list[Row]] = defaultdict(list)
+    for r in rows:
+        by[r[0]].append(r)
+    return [g for g in by.values() if len(g) > 1]
+
+
+def _ndcg(scores: NDArray[np.float64], labels: NDArray[np.float64], k: int = 10) -> float | None:
+    if labels.max() <= 0:
+        return None  # в группе нечего ранжировать — в среднем не участвует
+    order = np.argsort(-scores)[:k]
+    dcg = sum((2 ** labels[i] - 1) / math.log2(r + 2) for r, i in enumerate(order))
+    ideal = sorted(labels, reverse=True)[:k]
+    idcg = sum((2**v - 1) / math.log2(r + 2) for r, v in enumerate(ideal))
+    return float(dcg / idcg) if idcg > 0 else None
+
+
+def mean_ndcg(groups: list[list[Row]], score: Any) -> float:
+    vals = []
+    for g in groups:
+        x = np.array([r[1] for r in g], dtype=np.float64)
+        y = np.array([LABEL[r[2]] for r in g], dtype=np.float64)
+        v = _ndcg(np.asarray(score(x), dtype=np.float64), y)
+        if v is not None:
+            vals.append(v)
+    return round(float(np.mean(vals)), 4) if vals else 0.0
+
+
+def train(rows: list[Row], now: float, min_rows: int = MIN_ROWS) -> tuple[lgb.Booster | None, dict[str, Any]]:
+    """Обучает модель; None — данных мало (метрики объясняют почему)."""
+    metrics: dict[str, Any] = {"rows": len(rows), "features_version": FEATURES_VERSION}
+    if len(rows) < min_rows:
+        metrics["skipped"] = f"need {min_rows} labelled impressions"
+        return None, metrics
+    cutoff = now - HOLDOUT_DAYS * 86400
+    groups = _groups(rows)
+    train_g = [g for g in groups if max(r[3] for r in g) < cutoff]
+    valid_g = [g for g in groups if max(r[3] for r in g) >= cutoff]
+    if not train_g or not valid_g:
+        metrics["skipped"] = "no time split"
+        return None, metrics
+
+    def matrix(
+        gs: list[list[Row]],
+    ) -> tuple[NDArray[np.float64], NDArray[np.int64], NDArray[np.float64], list[int]]:
+        x = np.array([r[1] for g in gs for r in g], dtype=np.float64)
+        y = np.array([LABEL[r[2]] for g in gs for r in g], dtype=np.int64)
+        w = np.array([WEIGHT.get(r[2], 1.0) for g in gs for r in g], dtype=np.float64)
+        return x, y, w, [len(g) for g in gs]
+
+    x, y, w, group = matrix(train_g)
+    params = {
+        "objective": "lambdarank",
+        "learning_rate": 0.05,
+        "num_leaves": 31,
+        "min_data_in_leaf": 20,
+        "verbose": -1,
+    }
+    booster = lgb.train(params, lgb.Dataset(x, y, weight=w, group=group), num_boost_round=200)
+    metrics.update(
+        {
+            "train_groups": len(train_g),
+            "valid_groups": len(valid_g),
+            "ndcg@10": mean_ndcg(valid_g, booster.predict),
+            "ndcg@10_v1": mean_ndcg(valid_g, lambda m: m[:, V1_COLUMN]),
+        }
+    )
+    return booster, metrics
+
+
+def should_activate(metrics: dict[str, Any], current: dict[str, Any] | None) -> bool:
+    new = float(metrics.get("ndcg@10", 0.0))
+    if new < float(metrics.get("ndcg@10_v1", 0.0)):
+        return False
+    if current and current.get("ndcg@10"):
+        return new >= float(current["ndcg@10"]) * (1 - MAX_REGRESSION)
+    return True
+
+
+def train_and_save(conn: psycopg.Connection[Any], now: float) -> dict[str, Any]:
+    """Шаг ночного пайплайна: обучение, проверка, запись в model_versions."""
+    booster, metrics = train(load_rows(conn), now)
+    if booster is None:
+        return {"ranker": metrics}
+    version = "lgbm-" + dt.datetime.fromtimestamp(now, dt.UTC).strftime("%Y%m%d%H%M")
+    row = conn.execute(
+        "SELECT metrics FROM model_versions WHERE kind = 'ranker' AND is_active "
+        "ORDER BY created_at DESC LIMIT 1"
+    ).fetchone()
+    active = should_activate(metrics, row[0] if row else None)
+    with conn.transaction():
+        if active:
+            conn.execute("UPDATE model_versions SET is_active = false WHERE kind = 'ranker' AND is_active")
+        conn.execute(
+            "INSERT INTO model_versions (id, kind, metrics, is_active, artifact) "
+            "VALUES (%s, 'ranker', %s, %s, %s) "
+            "ON CONFLICT (id) DO NOTHING",
+            (version, json.dumps(metrics), active, booster.model_to_string()),
+        )
+    log.info("ranker %s %s: %s", version, "activated" if active else "kept inactive", metrics)
+    return {"ranker": {"version": version, "activated": active, **metrics}}
+
+
+class LoadedRanker:
+    """Активная модель в памяти сервиса (Ranker для engine.build_batch)."""
+
+    def __init__(self, version: str, model: str) -> None:
+        self.version = version
+        self.booster = lgb.Booster(model_str=model)
+
+    def predict(self, x: NDArray[np.float64]) -> NDArray[np.float64]:
+        return np.asarray(self.booster.predict(x), dtype=np.float64)
+
+
+class RankerHolder:
+    """Загружает активный ранжировщик из model_versions; reload — после ночного обучения."""
+
+    def __init__(self, dsn: str) -> None:
+        self.dsn = dsn
+        self._ranker: LoadedRanker | None = None
+        self._loaded = False
+        self._lock = threading.Lock()
+
+    def get(self) -> LoadedRanker | None:
+        if not self._loaded:
+            self.reload()
+        return self._ranker
+
+    def reload(self) -> None:
+        with self._lock:
+            self._loaded = True
+            try:
+                with psycopg.connect(self.dsn) as conn:
+                    row = conn.execute(
+                        "SELECT id, artifact, metrics FROM model_versions "
+                        "WHERE kind = 'ranker' AND is_active "
+                        "AND artifact IS NOT NULL ORDER BY created_at DESC LIMIT 1"
+                    ).fetchone()
+                if row is None or (row[2] or {}).get("features_version") != FEATURES_VERSION:
+                    self._ranker = None
+                    return
+                self._ranker = LoadedRanker(row[0], row[1])
+                log.info("ranker %s loaded", row[0])
+            except Exception:
+                log.exception("ranker load failed — wave uses v1")
+                self._ranker = None

services/recommender/pipu_rec/wave/engine.py

@@ -2,7 +2,10 @@
 
 from __future__ import annotations
 
+import math
+import time
 from dataclasses import dataclass, field
+from typing import Protocol
 
 import numpy as np
 from numpy.typing import NDArray
@@ -93,6 +96,9 @@ class Profile:
     rediscover: set[str]  # любимые, не игравшие > 60 дней
     exploration: float = 0.15
     taste_cf: list[float] | None = None  # фактор пользователя ALS
+    bandit: dict[str, list[float]] = field(
+        default_factory=dict
+    )  # источник → [α, β] (docs/recommendations.md#6.6)
     recent_likes: list[str] = field(default_factory=list)  # последние лайки, новые первыми (для item_cf)
 
 
@@ -111,8 +117,60 @@ class Pick:
     id: str
     source: str
     score: float
+    features: list[float] | None = None  # вектор признаков в момент показа (для обучения ранжировщика)
 
 
+# Источники кандидатов (one-hot в признаках ранжировщика; порядок фиксирован).
+SOURCES = ["seed", "fresh", "audio_sim", "cf", "item_cf", "artist", "rediscover", "popular", "explore"]
+
+# Признаки ранжировщика v2 (docs/recommendations.md#6.3). Порядок — часть формата модели:
+# менять только вместе с FEATURES_VERSION (старые модели тогда не загружаются).
+FEATURE_NAMES = [
+    "sim_session",
+    "sim_taste",
+    "cf",
+    "artist_affinity",
+    "popularity",
+    "v1_score",
+    "context_fit",
+    "is_new",
+    "liked_recent",
+    "bandit_mean",
+    *[f"src_{s}" for s in SOURCES],
+    "energy",
+    "bpm",
+    "danceability",
+    "valence",
+    "hour_sin",
+    "hour_cos",
+    "position",
+    "skips_in_row",
+    "has_activity",
+    "has_mood",
+]
+FEATURES_VERSION = 1
+
+
+class Ranker(Protocol):
+    """Обученный ранжировщик: оценки кандидатов по матрице признаков (строки — кандидаты)."""
+
+    version: str
+
+    def predict(self, x: NDArray[np.float64]) -> NDArray[np.float64]: ...
+
+
+@dataclass
+class Context:
+    """Контекст показа для признаков ранжировщика."""
+
+    hour: float = field(default_factory=lambda: time.localtime().tm_hour + time.localtime().tm_min / 60)
+    has_activity: bool = False
+    has_mood: bool = False
+
+
+# Вес бонуса бандита к оценке (θ − 0.5 ∈ [−0.5, 0.5]).
+BANDIT_WEIGHT = 0.2
+
 # Вклад реакции в сессионный вектор: s ← normalize(s + η·r·e).
 REACTION_WEIGHT = {"complete": 1.0, "like": 2.0, "skip_early": -1.0, "dislike": -2.0, "skip": -0.5}
 ETA = 0.3
@@ -176,10 +234,66 @@ def cf_scores(index: CatalogIndex, profile: Profile) -> NDArray[np.float64] | No
     return np.where(index.has_cf, index.cf @ u, 0.0).astype(np.float64)
 
 
-def model_version(index: CatalogIndex, profile: Profile) -> str:
+def model_version(index: CatalogIndex, profile: Profile, ranker: Ranker | None = None) -> str:
+    if ranker is not None:
+        return ranker.version
     return MODEL_VER + (CF_SUFFIX if cf_scores(index, profile) is not None else "")
 
 
+def candidate_features(
+    index: CatalogIndex,
+    profile: Profile,
+    session: Session,
+    cand: NDArray[np.intp],
+    sources: dict[int, str],
+    sim_session: NDArray[np.float64],
+    sim_taste: NDArray[np.float64],
+    cf_score: NDArray[np.float64] | None,
+    artist_aff: NDArray[np.float64],
+    v1: NDArray[np.float64],
+    context_fit: NDArray[np.float64],
+    ctx: Context,
+) -> NDArray[np.float64]:
+    """Матрица признаков (кандидаты × FEATURE_NAMES)."""
+    m = len(cand)
+    x = np.zeros((m, len(FEATURE_NAMES)), dtype=np.float64)
+
+    def feat(name: str) -> NDArray[np.float64]:
+        v = index.features.get(name)
+        if v is None:
+            return np.full(m, -1.0)
+        return np.nan_to_num(v[cand], nan=-1.0)
+
+    col = {n: k for k, n in enumerate(FEATURE_NAMES)}
+    x[:, col["sim_session"]] = sim_session[cand]
+    x[:, col["sim_taste"]] = sim_taste[cand]
+    x[:, col["cf"]] = cf_score[cand] if cf_score is not None else 0.0
+    x[:, col["artist_affinity"]] = artist_aff[cand]
+    x[:, col["popularity"]] = index.popularity[cand]
+    x[:, col["v1_score"]] = v1
+    x[:, col["context_fit"]] = context_fit
+    x[:, col["is_new"]] = [index.ids[i] not in profile.played for i in cand]
+    x[:, col["liked_recent"]] = [index.ids[i] in profile.liked_recent for i in cand]
+    for j, i in enumerate(cand):
+        src = sources[int(i)]
+        ab = profile.bandit.get(src)
+        x[j, col["bandit_mean"]] = ab[0] / (ab[0] + ab[1]) if ab else 0.5
+        if src in SOURCES:
+            x[j, col[f"src_{src}"]] = 1.0
+    x[:, col["energy"]] = feat("energy")
+    bpm = feat("bpm")
+    x[:, col["bpm"]] = np.where(bpm > 0, bpm / 200.0, -1.0)
+    x[:, col["danceability"]] = feat("danceability")
+    x[:, col["valence"]] = feat("valence")
+    x[:, col["hour_sin"]] = math.sin(2 * math.pi * ctx.hour / 24)
+    x[:, col["hour_cos"]] = math.cos(2 * math.pi * ctx.hour / 24)
+    x[:, col["position"]] = min(len(session.served) / 50.0, 1.0)
+    x[:, col["skips_in_row"]] = min(session.skips_in_row / 3.0, 1.0)
+    x[:, col["has_activity"]] = float(ctx.has_activity)
+    x[:, col["has_mood"]] = float(ctx.has_mood)
+    return x
+
+
 def _top(scores: NDArray[np.float64], mask: NDArray[np.bool_], k: int) -> NDArray[np.intp]:
     idx = np.nonzero(mask)[0]
     if len(idx) <= k:
@@ -197,6 +311,8 @@ def build_batch(
     exclude: set[str] | None = None,
     seed_ids: list[str] | None = None,
     rng: np.random.Generator | None = None,
+    ranker: Ranker | None = None,
+    ctx: Context | None = None,
 ) -> list[Pick]:
     """Кандидаты → фильтры → оценка → соответствие контексту → MMR с правилами разнообразия."""
     rng = rng or np.random.default_rng()
@@ -273,7 +389,7 @@ def build_batch(
     add(rng.permutation(np.nonzero(allowed)[0])[:40].tolist(), "explore")
 
     cand = np.array(sorted(sources))
-    # 3. Оценка v1.
+    # 3. Оценка v1 (она же — признак и запасной вариант для v2).
     score = (
         0.35 * sim_session[cand]
         + 0.25 * sim_taste[cand]
@@ -284,8 +400,17 @@ def build_batch(
     )
     liked_recent = np.array([index.ids[i] in profile.liked_recent for i in cand])
     score = score - 0.2 * liked_recent
+    # Бандит: семплирование Томпсона по источникам — удачные для пользователя источники получают бонус.
+    # Источник без наблюдений — нейтральные 0.5 (без шума, иначе холодный старт ранжировался бы случайно).
+    theta: dict[str, float] = {}
+    for src in set(sources.values()):
+        ab = profile.bandit.get(src)
+        theta[src] = float(rng.beta(ab[0], ab[1])) if ab else 0.5
+    score = score + BANDIT_WEIGHT * (np.array([theta[sources[int(i)]] for i in cand]) - 0.5)
+    v1 = score.copy()
 
     # 4. Соответствие контексту; если отсеялось слишком много — порог ослабляется.
+    f = np.ones(len(cand))
     if rules:
         f = fit({k: v[cand] for k, v in index.features.items()}, rules)
         # Нужен запас для разнообразия, но не больше 50 и не больше четверти пула.
@@ -294,11 +419,33 @@ def build_batch(
             keep = f >= threshold
             if keep.sum() >= enough or threshold == 0.0:
                 break
-        cand, score, f = cand[keep], score[keep], f[keep]
+        cand, score, f, v1 = cand[keep], score[keep], f[keep], v1[keep]
         score = score + 0.5 * f  # контекст важнее вкуса, когда выбран явно
     if len(cand) == 0:
         return []
 
+    # Признаки кандидатов: пишутся с показом (обучение v2) и подаются обученному ранжировщику.
+    ctx = ctx or Context()
+    f64 = np.float64
+    x = candidate_features(
+        index,
+        profile,
+        session,
+        cand,
+        sources,
+        np.asarray(sim_session, f64),
+        np.asarray(sim_taste, f64),
+        cf_score,
+        np.asarray(artist_aff, f64),
+        np.asarray(v1, f64),
+        np.asarray(f, f64),
+        ctx,
+    )
+    if ranker is not None:
+        # v2: порядок задаёт модель; в MMR нужна шкала 0..1 — берём ранг предсказания.
+        pred = ranker.predict(x)
+        score = np.argsort(np.argsort(pred)) / max(len(pred) - 1, 1)
+
     # 5. MMR + правила: 1 трек исполнителя на пачку, не больше 2 на последние 10; доля «нового».
     picks: list[Pick] = []
     chosen: list[int] = []
@@ -333,7 +480,14 @@ def build_batch(
         i = int(cand[best_j])
         chosen.append(i)
         order.remove(best_j)
-        picks.append(Pick(id=index.ids[i], source=sources[i], score=round(float(score[best_j]), 4)))
+        picks.append(
+            Pick(
+                id=index.ids[i],
+                source=sources[i],
+                score=round(float(score[best_j]), 4),
+                features=x[best_j].tolist(),
+            )
+        )
 
     # Исследование: «новых» (неслышанных) меньше доли exploration — заменяем ими слабейшие выборы.
     fresh_left = sorted(
@@ -348,5 +502,7 @@ def build_batch(
         weakest = min(others, key=lambda k: picks[k].score)
         if any(index.artist[index.pos[p.id]] == index.artist[i] for k, p in enumerate(picks) if k != weakest):
             continue
-        picks[weakest] = Pick(id=index.ids[i], source="fresh", score=round(float(score[j]), 4))
+        picks[weakest] = Pick(
+            id=index.ids[i], source="fresh", score=round(float(score[j]), 4), features=x[j].tolist()
+        )
     return picks

services/recommender/pipu_rec/wave/service.py

@@ -2,18 +2,22 @@
 
 from __future__ import annotations
 
+import logging
 from typing import Literal
 
 import numpy as np
 import psycopg
 from pydantic import BaseModel, Field
 
+from pipu_rec.train.ranker import RankerHolder
 from pipu_rec.wave.contexts import Contexts, Rule
-from pipu_rec.wave.engine import Pick, build_batch, model_version, taste_centroids, update_session
+from pipu_rec.wave.engine import Context, Pick, build_batch, model_version, taste_centroids, update_session
 from pipu_rec.wave.store import IndexHolder, SessionStore, load_profile, seed_tracks
 
 MAX_SERVED_MEMORY = 300
 
+log = logging.getLogger(__name__)
+
 Outcome = Literal["complete", "skip", "skip_early", "like", "dislike"]
 
 
@@ -55,6 +59,12 @@ class WaveService:
         self.index = IndexHolder(dsn)
         self.sessions = SessionStore(redis_url)
         self.contexts = contexts
+        self.ranker = RankerHolder(dsn)
+
+    def reload(self) -> None:
+        """После ночного обучения: перечитать каталог (векторы ALS) и активный ранжировщик."""
+        self.index.refresh()
+        self.ranker.reload()
 
     def rules(self, activity: str | None, mood: str | None) -> list[Rule]:
         """Занятие и настроение комбинируются — пересечение профилей; неизвестный ключ игнорируется."""
@@ -74,6 +84,7 @@ class WaveService:
         update_session(
             index, session, [(f.track_id, f.outcome) for f in req.feedback], taste_centroids(index, profile)
         )
+        ranker = self.ranker.get()
         picks: list[Pick] = build_batch(
             index,
             profile,
@@ -83,12 +94,31 @@ class WaveService:
             exclude=set(req.exclude_ids),
             seed_ids=seeds,
             rng=np.random.default_rng(),
+            ranker=ranker,
+            ctx=Context(has_activity=bool(req.activity), has_mood=bool(req.mood)),
         )
+        self.log_features(req.session_id, picks)
         session.served = (session.served + [p.id for p in picks])[-MAX_SERVED_MEMORY:]
         artists = [index.artist[index.pos[p.id]] for p in picks]
         session.recent_artists = (session.recent_artists + artists)[-10:]
         self.sessions.put(req.session_id, session)
         return BatchResponse(
             tracks=[BatchTrack(id=p.id, source=p.source, score=p.score) for p in picks],
-            model_ver=model_version(index, profile),
+            model_ver=model_version(index, profile, ranker),
         )
+
+    def log_features(self, session_id: str, picks: list[Pick]) -> None:
+        """Признаки показанных треков — обучающие данные ранжировщика v2. Сбой записи не ломает волну."""
+        rows = [(session_id, p.id, p.features) for p in picks if p.features is not None]
+        if not rows:
+            return
+        try:
+            with psycopg.connect(self.dsn, autocommit=True) as conn, conn.cursor() as cur:
+                cur.executemany(
+                    "INSERT INTO rec_impression_features (wave_session_id, track_id, features) "
+                    "VALUES (%s, %s, %s) "
+                    "ON CONFLICT DO NOTHING",
+                    rows,
+                )
+        except psycopg.Error as e:
+            log.warning("impression features not saved: %s", e)

services/recommender/pipu_rec/wave/store.py

@@ -156,10 +156,14 @@ def load_profile(conn: psycopg.Connection[Any], user_id: str) -> Profile:
         )
     }
     row = conn.execute(
-        "SELECT exploration, taste_cf::text FROM user_profiles_rec WHERE user_id = %s", (user_id,)
+        "SELECT exploration, taste_cf::text, bandit, onboarding FROM user_profiles_rec WHERE user_id = %s",
+        (user_id,),
     ).fetchone()
+    if row and row[3] and len(scores) < ONBOARDING_UNTIL:
+        apply_onboarding(conn, scores, row[3])
     exploration = float(row[0]) if row else 0.15
     taste_cf = parse_vector(row[1]) if row else None
+    bandit = {str(k): [float(x) for x in v] for k, v in (row[2] or {}).items()} if row else {}
     if len(played) < 30:
         exploration = max(exploration, 0.4)  # холодный старт: больше исследования на первых треках
     day = 86400
@@ -173,10 +177,41 @@ def load_profile(conn: psycopg.Connection[Any], user_id: str) -> Profile:
         rediscover={t for t, s in scores.items() if s > 1.5 and now - last.get(t, now) > 60 * day},
         exploration=exploration,
         taste_cf=taste_cf.tolist() if taste_cf is not None else None,
+        bandit=bandit,
         recent_likes=recent_likes,
     )
 
 
+# Пока своих оценок меньше, выбор онбординга задаёт начальный вкус (docs/recommendations.md#7).
+ONBOARDING_UNTIL = 30
+ONBOARDING_LIMIT = 300
+
+
+def apply_onboarding(conn: psycopg.Connection[Any], scores: dict[str, float], choice: dict[str, Any]) -> None:
+    """Псевдооценки: треки выбранных исполнителей +1, выбранных жанров +0.5 (до ONBOARDING_LIMIT треков).
+    Собственные оценки не перезаписываются; в «слышанное» эти треки не попадают."""
+    artists = [str(a) for a in choice.get("artist_ids") or []]
+    genres = [str(g).lower() for g in choice.get("genres") or []]
+    pseudo: dict[str, float] = {}
+    if artists:
+        for (tid,) in conn.execute(
+            "SELECT DISTINCT track_id::text FROM track_artists WHERE artist_id::text = ANY(%s) LIMIT %s",
+            (artists, ONBOARDING_LIMIT),
+        ):
+            pseudo[tid] = pseudo.get(tid, 0.0) + 1.0
+    if genres:
+        for (tid,) in conn.execute(
+            """
+            SELECT DISTINCT tg.track_id::text FROM track_genres tg JOIN genres g ON g.id = tg.genre_id
+            WHERE lower(g.name) = ANY(%s) LIMIT %s
+            """,
+            (genres, ONBOARDING_LIMIT),
+        ):
+            pseudo[tid] = pseudo.get(tid, 0.0) + 0.5
+    for tid, v in pseudo.items():
+        scores.setdefault(tid, v)
+
+
 def seed_tracks(conn: psycopg.Connection[Any], seed_type: str, seed_id: str) -> list[str]:
     """Треки, от которых запущена волна: трек, альбом или исполнитель."""
     queries = {

services/recommender/pyproject.toml

@@ -11,6 +11,7 @@ dependencies = [
     "redis>=6.2,<7",
     "numpy>=2.2,<3",
     "pyyaml>=6.0,<7",
+    "lightgbm>=4.5,<5",
 ]
 
 [project.scripts]

services/recommender/tests/test_db_integration.py

@@ -3,6 +3,7 @@
 Локально: TEST_DATABASE_URL=postgresql://… uv run pytest tests/test_db_integration.py
 """
 
+import json
 import os
 import time
 import uuid
@@ -139,3 +140,44 @@ def test_training_and_wave_queries(world: dict[str, Any]) -> None:
         assert active is not None and active[0] == 1
     picks = build_batch(index, profile, Session(), [], n=5, rng=np.random.default_rng(0))
     assert len(picks) == 5
+
+
+def test_onboarding_seeds_taste(world: dict[str, Any]) -> None:
+    user = uid()
+    with psycopg.connect(DSN, autocommit=True) as conn:
+        conn.execute(
+            "INSERT INTO users (id, username, password_hash) VALUES (%s, %s, 'x')", (user, f"new-{user[:6]}")
+        )
+        artist = conn.execute(
+            "SELECT artist_id::text FROM track_artists WHERE track_id = %s", (world["tracks"][0],)
+        ).fetchone()
+        assert artist is not None
+        conn.execute(
+            "INSERT INTO user_profiles_rec (user_id, onboarding) VALUES (%s, %s)",
+            (user, json.dumps({"artist_ids": [artist[0]], "genres": []})),
+        )
+        profile = load_profile(conn, user)
+    assert len(profile.scores) >= 10, "chosen artist's tracks become the initial taste"
+    assert not profile.played
+
+
+def test_impression_features_roundtrip(world: dict[str, Any]) -> None:
+    from pipu_rec.train.ranker import load_rows, train_and_save
+    from pipu_rec.wave.engine import FEATURE_NAMES
+
+    session, user, track = uid(), world["users"][0], world["tracks"][0]
+    with psycopg.connect(DSN, autocommit=True) as conn:
+        conn.execute("INSERT INTO wave_sessions (id, user_id) VALUES (%s, %s)", (session, user))
+        conn.execute(
+            "INSERT INTO wave_impressions (wave_session_id, position, track_id, candidate_source, outcome) "
+            "VALUES (%s, 0, %s, 'audio_sim', 'complete')",
+            (session, track),
+        )
+        conn.execute(
+            "INSERT INTO rec_impression_features (wave_session_id, track_id, features) VALUES (%s, %s, %s)",
+            (session, track, [0.5] * len(FEATURE_NAMES)),
+        )
+        rows = load_rows(conn)
+        assert any(r[0] == session and r[2] == "complete" for r in rows)
+        result = train_and_save(conn, time.time())
+        assert "skipped" in result["ranker"], "too few impressions — v1 stays"

services/recommender/tests/test_train.py

@@ -116,3 +116,96 @@ def test_cf_vectors_are_padded_to_column_size() -> None:
     v = np.ones((3, 5), dtype=np.float32)
     assert pad(v).shape == (3, CF_DIM)
     assert pad(np.ones((2, 80), dtype=np.float32)).shape == (2, CF_DIM)
+
+
+def test_bandit_params_and_exploration() -> None:
+    from pipu_rec.train.bandit import compute, exploration
+
+    now = 100 * DAY
+    rows = [("u", "fresh", "complete", now)] * 8 + [("u", "fresh", "skip", now)] * 2
+    rows += [("u", "audio_sim", "complete", now)] * 2 + [("u", "audio_sim", "skip_early", now)] * 8
+    rows += [("u", "cf", "complete", now - 69 * DAY)]  # затухание: ~0.5
+    p = compute(rows, now)["u"]
+    assert p["fresh"] == [9.0, 3.0]
+    assert p["audio_sim"] == [3.0, 9.0]
+    assert 1.4 < p["cf"][0] < 1.6
+    assert exploration(p) > 0.15  # «новое» заходит лучше остального — исследования больше
+    assert exploration({"fresh": [1.0, 9.0], "audio_sim": [9.0, 1.0]}) == 0.05
+
+
+def test_bandit_favours_successful_source() -> None:
+    n = 60
+    ids = [f"t{i}" for i in range(n)]
+    index = CatalogIndex.build(
+        ids=ids, artist=[f"a{i}" for i in range(n)], raw_emb=[None] * n, features={}, plays=[0] * n
+    )
+    good = Profile(
+        scores={},
+        disliked=set(),
+        disliked_artists=set(),
+        recent=set(),
+        played=set(),
+        liked_recent=set(),
+        rediscover=set(),
+        exploration=0.0,
+        bandit={"popular": [50.0, 1.0], "explore": [1.0, 50.0]},
+    )
+    picks = build_batch(index, good, Session(), [], n=5, rng=np.random.default_rng(1))
+    assert sum(p.source == "popular" for p in picks) >= 4
+
+
+def test_ranker_learns_what_v1_misses() -> None:
+    from pipu_rec.train.ranker import V1_COLUMN, should_activate, train
+    from pipu_rec.wave.engine import FEATURE_NAMES
+
+    rng = np.random.default_rng(0)
+    now = 200 * DAY
+    rows = []
+    col = FEATURE_NAMES.index("sim_session")
+    for g in range(400):
+        ts = now - (1 if g >= 320 else 30) * DAY  # последние сессии — отложенная неделя
+        for _ in range(8):
+            x = rng.random(len(FEATURE_NAMES)).tolist()
+            # Исход определяется sim_session, а оценка v1 в признаках — случайный шум.
+            outcome = "like" if x[col] > 0.85 else "complete" if x[col] > 0.5 else "skip_early"
+            x[V1_COLUMN] = float(rng.random())
+            rows.append((f"s{g}", x, outcome, ts))
+    booster, m = train(rows, now, min_rows=100)
+    assert booster is not None, m
+    assert m["ndcg@10"] > m["ndcg@10_v1"] + 0.1, m
+    assert should_activate(m, None)
+    assert not should_activate({"ndcg@10": 0.5, "ndcg@10_v1": 0.6}, None)
+    assert not should_activate({"ndcg@10": 0.7, "ndcg@10_v1": 0.6}, {"ndcg@10": 0.8})
+    _, few = train(rows[:50], now)
+    assert "skipped" in few
+
+
+def test_engine_uses_ranker_and_logs_features() -> None:
+    from pipu_rec.wave.engine import FEATURE_NAMES
+
+    n = 40
+    ids = [f"t{i}" for i in range(n)]
+    index = CatalogIndex.build(
+        ids=ids, artist=[f"a{i}" for i in range(n)], raw_emb=[None] * n, features={}, plays=[0] * n
+    )
+    profile = Profile(
+        scores={},
+        disliked=set(),
+        disliked_artists=set(),
+        recent=set(),
+        played=set(),
+        liked_recent=set(),
+        rediscover=set(),
+        exploration=0.0,
+    )
+
+    class LastFirst:
+        version = "fake-ranker"
+
+        def predict(self, x: np.ndarray) -> np.ndarray:
+            return -x[:, FEATURE_NAMES.index("popularity")] + np.arange(len(x)) * 1e-3
+
+    picks = build_batch(index, profile, Session(), [], n=5, rng=np.random.default_rng(0), ranker=LastFirst())
+    assert len(picks) == 5
+    assert all(p.features is not None and len(p.features) == len(FEATURE_NAMES) for p in picks)
+    assert model_version(index, profile, LastFirst()) == "fake-ranker"

services/recommender/uv.lock

@@ -176,6 +176,24 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/ff/3d/9668a400c8dd81d162eba38b33fa49fa6205f1a64493570a13fbb815c3ee/librt-0.16.0-cp312-cp312-win_arm64.whl", hash = "sha256:f7be7cf555bc30ec12622e9447299cc4a9b8ff307548b634794353db0c2065dc", size = 116572, upload-time = "2026-09-29T00:53:04.815Z" },
 ]
 
+[[package]]
+name = "lightgbm"
+version = "4.7.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "narwhals" },
+    { name = "numpy" },
+    { name = "scipy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/63/8e/4db5e29290d7e619c307fdb8dab0a0514090af2ce3ec483050e024ec6126/lightgbm-4.7.0.tar.gz", hash = "sha256:f8e20f682c9aabd000bcf4a7ed8aa6f473c1adfecccae34ec24e823d156f4af0", size = 1792896, upload-time = "2026-07-18T21:00:56.139Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/cd/05/7213965863cba1ed0150ad045bceed6276a1afaaaedbaeff4699ec4f0ccb/lightgbm-4.7.0-py3-none-macosx_10_15_x86_64.whl", hash = "sha256:dfc1cfe8e760387be1e7ba7a214688be21fdff96e4ed9749188f83e1877c2477", size = 1877851, upload-time = "2026-07-18T21:00:35.225Z" },
+    { url = "https://files.pythonhosted.org/packages/b2/86/f4fe714f2e0bf3941705a20d7f6849dc476276d71236e82ea6b0d6539b86/lightgbm-4.7.0-py3-none-macosx_12_0_arm64.whl", hash = "sha256:129535462686f274df179133643118c5c5c5667167fe6c3a28d955f0b3c8e868", size = 1498914, upload-time = "2026-07-18T21:00:36.549Z" },
+    { url = "https://files.pythonhosted.org/packages/c6/a3/b29580948b92e8c2f84dea70118ac702ff067dc52ec4ffb5d73c953536a5/lightgbm-4.7.0-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d4529acec5c6fefe4768302a529707d0ead90f6a6f42df694b856212e09695b8", size = 3349492, upload-time = "2026-07-18T21:00:37.943Z" },
+    { url = "https://files.pythonhosted.org/packages/15/eb/837ea3b40cc36e22eeebb9785c01e42b2c255d033eea1d2d9ee8e2540e55/lightgbm-4.7.0-py3-none-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d23e922acd891e77212e4d0fbcee9ba973c96dee479491341d05ba595357ebb7", size = 3476028, upload-time = "2026-07-18T21:00:39.331Z" },
+    { url = "https://files.pythonhosted.org/packages/d5/0b/c5c17d862b12ce292f24cd85d40f2f8f8981668fbdbd43fdc2625eccbc79/lightgbm-4.7.0-py3-none-win_amd64.whl", hash = "sha256:f42d1e5b32b6f170e606d7c689c6165671da98d7bf37f1addec2623efc8740c9", size = 1360833, upload-time = "2026-07-18T21:00:40.865Z" },
+]
+
 [[package]]
 name = "mypy"
 version = "1.20.2"
@@ -207,6 +225,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/79/7b/2c79738432f5c924bef5071f933bcc9efd0473bac3b4aa584a6f7c1c8df8/mypy_extensions-1.1.0-py3-none-any.whl", hash = "sha256:1be4cccdb0f2482337c4743e60421de3a356cd97508abadd57d47403e94f5505", size = 4963, upload-time = "2025-04-22T14:54:22.983Z" },
 ]
 
+[[package]]
+name = "narwhals"
+version = "2.27.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/bf/21/f64d6b2dbea7bf3f8c38cdc786dcc6ef012ca3d173ad208c782c9a7bedf6/narwhals-2.27.1.tar.gz", hash = "sha256:aed93076a3ea42d9c32c88e4eb5ea422a21937011cbe1f480f9572a523c82094", size = 735013, upload-time = "2026-10-10T06:52:18.113Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d1/89/5d4c86da1130d9059681e5b6cd7645df5c10279a6a079c5c37dcb2cc6f3f/narwhals-2.27.1-py3-none-any.whl", hash = "sha256:d057df13f5852b8e157596e82eb5e955fad267425df5e420e0ee9863da483b31", size = 483211, upload-time = "2026-10-10T06:52:16.32Z" },
+]
+
 [[package]]
 name = "numpy"
 version = "2.5.4"
@@ -262,6 +289,7 @@ version = "0.1.0"
 source = { editable = "." }
 dependencies = [
     { name = "fastapi" },
+    { name = "lightgbm" },
     { name = "numpy" },
     { name = "psycopg", extra = ["binary"] },
     { name = "pydantic-settings" },
@@ -282,6 +310,7 @@ dev = [
 [package.metadata]
 requires-dist = [
     { name = "fastapi", specifier = ">=0.115,<1" },
+    { name = "lightgbm", specifier = ">=4.5,<5" },
     { name = "numpy", specifier = ">=2.2,<3" },
     { name = "psycopg", extras = ["binary"], specifier = ">=3.2,<4" },
     { name = "pydantic-settings", specifier = ">=2.9,<3" },
@@ -490,6 +519,27 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/df/c9/0f2a4dea06a5e12c1191ee3d96b1e1233797d0d5e18f97a2b909a95a9836/ruff-0.17.1-py3-none-win_arm64.whl", hash = "sha256:42400b9a6ff8515ff27796f07f92e0195be011c86e81e381606f58ea5502fef4", size = 9853542, upload-time = "2026-10-15T15:23:16.05Z" },
 ]
 
+[[package]]
+name = "scipy"
+version = "1.18.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/7e/74/66de6258867beb2ef08f35f9f2ac017a52cacd5081714d239ff1a442d458/scipy-1.18.1.tar.gz", hash = "sha256:52c4b7422442aba924d03ad4019852b08a92e64ea187b933135687bfe2747307", size = 30781235, upload-time = "2026-08-21T23:28:50.599Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/18/f7/240c110c08693826b4513a52f5717d62ec7c7af72f2920821247c03b17b3/scipy-1.18.1-cp312-cp312-macosx_10_15_x86_64.whl", hash = "sha256:457fd7a2a8edeb044ab6ffbc0aa03ff6cd18491356e5e0c834d76ce621b916d1", size = 31111061, upload-time = "2026-08-21T23:23:44.522Z" },
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