Scaffold enligt new-project-playbook: README, plan, CI-workflow, build-task

lyssnarr — musik-discovery på Pi5. Jellyseerr-lik UI, sök (MusicBrainz +
YT Music), schemalagda Gemini-förslag från Lidarr-bibliotek + Youtubarr-
spellistor, add-to-Lidarr / spela inline / öppna i YT Music.
Plan i doc/plan.md — implementation börjar när planen är bekräftad.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01824ZrvG2mDYYrmwqypLNup

.gitea/workflows/build.yaml

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+name: build-and-push
+
+# Bygger lyssnarr-imagen på Pi5-runnern (arm64, nativt) och pushar till den
+# lokala registryn — samma mönster som Archivum. Multi-stage (frontend ->
+# backend -> runtime), build-context är repo-roten. Pull:a på Pi5 med
+# localhost:5000/lyssnarr:latest (dockge-stacken).
+#
+# OBS: bygget kör bredvid live-tjänsterna på Pi5 — nice/ionice + BUILD_CPUS=2
+# så boxen förblir responsiv (max 2 tunga byggen samtidigt, se infra-Doc).
+
+on:
+  push:
+    branches: [master]
+    paths:
+      - "backend/**"
+      - "frontend/**"
+      - "docker/**"
+      - "package.json"
+      - ".gitea/workflows/build.yaml"
+  workflow_dispatch: {}
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Build & push image
+        run: |
+          nice -n 19 ionice -c 3 docker build --progress=plain \
+            --build-arg BUILD_CPUS=2 \
+            -f docker/Dockerfile \
+            -t localhost:5000/lyssnarr:latest \
+            -t "localhost:5000/lyssnarr:${GITHUB_SHA::12}" \
+            .
+          docker push localhost:5000/lyssnarr:latest
+          docker push "localhost:5000/lyssnarr:${GITHUB_SHA::12}"

.gitignore

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+build/
+node_modules/
+dist/
+.env
+.env.*
+*.sqlite3
+data/
+coverage/
+.DS_Store
+*.log

.vscode/tasks.json

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+{
+  "version": "2.0.0",
+  "tasks": [
+    {
+      "label": "build",
+      "type": "shell",
+      "command": "npm run build",
+      "group": { "kind": "build", "isDefault": true },
+      "problemMatcher": []
+    }
+  ]
+}

README.md

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+# lyssnarr
+
+Self-hosted music discovery for the Pi5 — a Jellyseerr-style web UI that
+finds new music for you. Search for artists/albums/tracks, get scheduled
+AI-generated suggestions (Gemini) based on what you recently listened to
+and what you add to your YouTube Music playlists, and add anything to
+Lidarr with one click — or play it inline / open it in YouTube Music.
+
+See [`doc/plan.md`](doc/plan.md) for the agreed plan and the
+[Gitea wiki](https://gitea.brasse-pc.eu/brasse/lyssnarr/wiki) for
+architecture notes.
+
+## Prerequisites (dev box = Arch/Garuda)
+
+```bash
+sudo pacman -S nodejs npm     # node >= 20
+```
+
+## Build & run
+
+```bash
+git clone gitea-claude:brasse/lyssnarr.git
+cd lyssnarr
+npm install                   # installs backend + frontend workspaces
+npm run build                 # -> ./build/ (frontend dist + backend)
+npm run dev                   # dev servers (Vite + Fastify, hot reload)
+npm test
+```
+
+## Runtime configuration
+
+All secrets live in the Dockge stack `.env` on the Pi5 — never in the
+repo. Key variables (full list in `doc/plan.md`):
+
+| Var | What |
+|-----|------|
+| `GEMINI_API_KEY`      | Google AI Studio key for suggestion generation |
+| `LIDARR_URL` / `LIDARR_API_KEY` | Lidarr instance to add music to |
+| `SESSION_SECRET`      | cookie signing |
+| `APP_PASSWORD_HASH`   | bcrypt hash for the single-user login |
+
+## Deploy
+
+CI (`.gitea/workflows/build.yaml`) builds the arm64 image on the Pi5
+runner and pushes `localhost:5000/lyssnarr:latest`; the Dockge stack
+`/srv/dockge-staks/lyssnarr/` runs it behind NPM as
+`https://lyssnarr.brasse-pc.eu`.

doc/plan.md

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+# lyssnarr — plan
+
+## Goal
+
+Self-hosted music-discovery web app on the Pi5. A Jellyseerr-style UI
+where Björn can (a) search for new artists, albums and tracks, and
+(b) get **scheduled** AI-generated suggestions based on two taste
+signals: recent listening in the local library (Jellyfin) and tracks
+recently added to his YouTube Music playlists (via Youtubarr's data).
+Every result can be added to Lidarr with one click, opened in YouTube
+Music, or played inline in the app.
+
+## Stack
+
+- **Backend:** Node ≥ 20, Fastify, better-sqlite3 (suggestion history +
+  feedback), node-cron (scheduled generation)
+- **Frontend:** Vue 3 + Vite; dark, poster/card-based UI modelled on
+  Jellyseerr (top search bar, discover grid, action buttons per card);
+  built to static files served by the backend
+- **Container:** single arm64 image, multi-stage Dockerfile
+  (frontend build → backend deps → slim runtime), mirrors Archivum
+
+## Deploy target
+
+Pattern B (container on Pi5):
+Gitea Actions on the Pi5 runner → `localhost:5000/lyssnarr:latest` →
+Dockge stack `/srv/dockge-staks/lyssnarr/` → NPM vhost
+`https://lyssnarr.brasse-pc.eu` (public from day one → the app ships
+with login from day one: single user, bcrypt-hashed password from the
+stack `.env`, signed session cookie).
+
+## Integrations
+
+| What | How |
+|------|-----|
+| **Lidarr** | REST API (`http://lidarr:8686`): add/monitor artists & albums, check what's already in the library |
+| **MusicBrainz** | search + canonical MBIDs (Lidarr adds are MBID-based) |
+| **YouTube Music** | unofficial YT Music search from Node → browse/video IDs for "open in YT Music" deep links, thumbnails for the cards, inline playback via YouTube IFrame embed |
+| **Gemini API** | suggestion generation; `GEMINI_API_KEY` + model via env |
+| **Youtubarr** | read-only mount of its SQLite (`/srv/docker/youtubarr/data/db.sqlite3`) → "recently added to playlists" signal |
+| **Jellyfin** | play-history signal — blocked until a music library exists in Jellyfin (milestone 6) |
+
+## UI sketch (Jellyseerr-like)
+
+- Top: search bar with artist/album/track scope
+- Landing "Upptäck": latest suggestion batch as poster cards, each with
+  Gemini's one-line motivation
+- Card actions: **➕ Lidarr** · **▶ Spela** (inline YouTube embed) ·
+  **↗ YT Music** (deep link)
+- Badge on cards already in the Lidarr library
+- History page with earlier batches
+
+## Milestones
+
+1. **Skeleton end-to-end** — repo, CI, Dockerfile, dockge stack, NPM
+   vhost, login; an empty authenticated shell reachable on
+   `lyssnarr.brasse-pc.eu`
+2. **Lidarr integration** — library state + add/monitor actions
+3. **Search page** — MusicBrainz search enriched with YT Music
+   thumbnails/links, add/play/open actions
+4. **On-demand suggestions** — "generera nu": Gemini prompt built from
+   Lidarr library + Youtubarr playlist adds
+5. **Scheduler + history** — cron-generated batches, history page
+6. **Jellyfin signal** — recent music plays feed the prompt (requires
+   music library in Jellyfin)
+
+## Roadmap / expansions (proposed — Björn confirms/strikes)
+
+- 👍/👎 feedback per suggestion, fed into the next Gemini prompt
+- Auto-add top suggestions to Lidarr as monitored (configurable)
+- Track-level batches exported as M3U playlists into Jellyfin
+- Library profile page (genre/decade distribution)
+- Webhook/notification when a new batch lands
+- Liked Music as a direct signal (ytmusicapi sidecar or Node port)
+
+## Open questions
+
+- Gemini model: default `gemini-2.5-flash`, configurable via env — ok?
+- Auth: built-in single-user login vs Authentik forward-auth later
+- Artwork order: YT Music thumbnails first, Cover Art Archive fallback