StreamyStats

Analytics and AI recommendations for Jellyfin libraries

806 stars 37 forks last commit first released

Actively maintained

Last commit 10 Jun 2026.

StreamyStats is a statistics and analytics service for Jellyfin that collects playback and library data to provide dashboards and visualizations. It also optionally adds AI-powered chat and recommendations by embedding library items and using semantic search.

Key Features

  • Overview dashboard with key metrics, live sessions, and recommendations
  • User-specific watch history, viewing statistics, and filtering
  • Library and client statistics, including watch-time graphs
  • Multi-server and multi-user support
  • Imports existing data from Jellystat and Jellyfin Playback Reporting plugin
  • Optional AI chat with function calling tools for semantic library search, stats queries, and personalized recommendations
  • Optional embedding pipeline using OpenAI-compatible APIs for vector similarity recommendations

Use Cases

  • Monitor Jellyfin usage trends across users, clients, and libraries
  • Discover what content is most watched and how watch time changes over time
  • Provide personalized watch recommendations and semantic search for large media libraries

Limitations and Considerations

  • AI features require enabling and configuring an OpenAI-compatible provider and embeddings storage
  • Project is maintained as a hobby project, so stability and release cadence may vary

StreamyStats is a strong fit for Jellyfin administrators who want deeper usage insights than the built-in UI provides, with the option to layer on semantic search and recommendation features. It can run in Docker for a straightforward deployment and scales primarily with library size and collected playback history.

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