Streamystats: Advanced Analytics and AI for Your Jellyfin Library

Introduction

Streamystats is an innovative statistics service for Jellyfin, designed to provide comprehensive analytics and data visualization for your media library. Built with modern frameworks like Next.js, React, TypeScript, and Hono, it transforms your viewing data into insightful information. Key features include a detailed dashboard with overview statistics, live sessions, user-specific watch history, and library statistics.

What sets Streamystats apart are its advanced AI capabilities. It offers an interactive AI chat interface that allows you to query your library, get personalized watch recommendations, and perform semantic searches using embeddings. Recommendations are generated based on your watch history, with clear explanations for each suggestion. The project also supports multi-server and multi-user setups, making it a versatile tool for any Jellyfin enthusiast.

Installation

Getting Streamystats up and running is straightforward, with Docker being the recommended method.

• Install Docker and Docker Compose: Ensure you have these installed on your system.
• Copy docker-compose.yml: Obtain the docker-compose.yml file from the repository to your desired location. It's recommended to use the :latest tag for the most recent features.
• Configure Ports: Adjust any default ports if necessary. The default web port is 3000.
• Set SESSION_SECRET: Change the SESSION_SECRET in the docker-compose.yml file to a strong, random string. You can generate one using

  openssl rand -hex 64

  .
• Start Application: Run

  docker-compose up -d

  to start Streamystats in the background.
• Access Interface: Open your web browser and navigate to http://localhost:3000.
• Follow Setup Wizard: Complete the initial setup wizard to connect your Jellyfin server.

Note that the first load might take some time, depending on the size of your Jellyfin library. For stable deployments, pinning to specific version tags is recommended. Always take a database backup before updating to a newer image version, as Streamystats does not perform automatic database rollbacks.

Examples

Once Streamystats is configured, users are greeted with a rich, interactive dashboard. This central hub provides an overview of your media consumption, including live sessions, trending content, and personalized recommendations. You can dive deep into user-specific watch histories, track viewing patterns over time with advanced filtering on watch time graphs, and analyze overall library statistics.

The AI chat feature offers a unique way to interact with your media. Ask questions about your library, discover content based on specific criteria, or get tailored recommendations. For instance, you could ask, "What are some highly-rated sci-fi movies I haven't watched yet?" or "Show me recommendations similar to [Movie Title]". The system leverages vector similarity to provide intelligent suggestions, complete with explanations of why certain items were recommended based on your viewing habits.

Why use Streamystats

Streamystats is an essential addition for any Jellyfin user looking to gain deeper insights into their media consumption. It moves beyond basic playback tracking by offering advanced analytics and data visualization that reveal trends and patterns in your viewing habits. The integration of AI, including semantic search and personalized recommendations, elevates the user experience, making content discovery more intelligent and engaging.

Whether you want to understand your most-watched genres, track individual user activity, or simply find your next favorite show with AI-powered suggestions, Streamystats provides the tools to do so. Its multi-server and multi-user support ensures it scales with your needs, making it a powerful, comprehensive solution for enhancing your Jellyfin ecosystem.

Links

Explore the Streamystats repository on GitHub for more details, contributions, and updates:

• Streamystats GitHub Repository