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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.