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bnair123 93e7c13f3d feat: implement AI-curated playlist service and dashboard integration

- Added hierarchical AGENTS.md knowledge base
- Implemented PlaylistService with 6h themed and 24h devotion mix logic
- Integrated AI theme generation for 6h playlists via Gemini/OpenAI
- Added /playlists/refresh and metadata endpoints to API
- Updated background worker with scheduled playlist curation
- Created frontend PlaylistsSection, Tooltip components and integrated into Dashboard
- Added Alembic migration for playlist tracking columns
- Fixed Docker healthcheck with curl installation

2025-12-30 09:45:19 +04:00

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SERVICES KNOWLEDGE BASE

Target: backend/app/services/ Context: Central business logic, 7+ specialized services, LLM integration.

OVERVIEW

Core logic hub transforming raw music data into metrics, playlists, and AI narratives.

Data Ingress/Egress: SpotifyClient (OAuth/Player), GeniusClient (Lyrics), ReccoBeatsClient (Audio Features).
Analytics: StatsService (HHI, Gini, clustering, heatmaps, skip detection).
AI/Narrative: NarrativeService (LLM prompt engineering, multi-provider support), AIService (Simple Gemini analysis).
Orchestration: PlaylistService (AI-curated dynamic playlist generation).

WHERE TO LOOK

Service	File	Key Responsibilities
Analytics	`stats_service.py`	Metrics (Volume, Vibe, Time, Taste, LifeCycle).
Spotify	`spotify_client.py`	Auth, Player API, Playlist CRUD.
Narrative	`narrative_service.py`	LLM payload shaping, system prompts, JSON parsing.
Playlists	`playlist_service.py`	Periodic curation logic (6h/24h cycles).
Enrichment	`reccobeats_client.py`	External audio features (energy, valence).
Lyrics	`genius_client.py`	Song/Artist metadata & lyrics search.

CONVENTIONS

Async Everywhere: All external API clients (Spotify, ReccoBeats) use httpx.AsyncClient.
Stat Modularization: StatsService splits logic into compute_X_stats methods; returns serializable dicts.
Provider Agnostic AI: NarrativeService detects OPENAI_API_KEY vs GEMINI_API_KEY automatically.
Payload Shaping: AI services aggressively prune stats JSON before sending to LLM to save tokens.
Fallbacks: All AI/External calls have explicit fallback/empty return states.

ANTI-PATTERNS

Blocking I/O: GeniusClient is synchronous; avoid calling in hot async paths.
Service Circularity: PlaylistService depends on StatsService. Avoid reversing this.
N+1 DB Hits: Aggregations in StatsService should use joinedload or batch queries.
Missing Checksums: Audio features assume presence; always check for None before math.
Token Waste: Never pass raw DB models to NarrativeService; use shaped dicts.

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