Recommendarr is an AI-powered web application designed to provide personalized movie and TV show recommendations. It targets users of media servers like Sonarr, Radarr, Plex, and Jellyfin, offering a more tailored viewing experience by analyzing existing libraries and watch histories.

How It Works

Recommendarr leverages Large Language Models (LLMs) to generate recommendations. It integrates directly with media management tools (Sonarr, Radarr) and streaming platforms (Plex, Jellyfin, Tautulli, Trakt) to ingest user library and watch history data. This data is then processed by an LLM, which can be hosted locally (Ollama, LM Studio) or accessed via OpenAI or compatible APIs, to produce tailored suggestions.

Quick Start & Requirements

• Install: docker run -d --name recommendarr -p 3000:3000 -v recommendarr-data:/app/server/data tannermiddleton/recommendarr:latest
• Prerequisites: Docker, access to Sonarr, Radarr, Plex, Jellyfin, Tautulli, or Trakt.
• Setup: Visit http://localhost:3000 after running the container. Default login: admin/1234.
• Docs: Recommendarr Wiki

Highlighted Details

• AI-driven recommendations based on Sonarr, Radarr, Plex, Jellyfin, Tautulli, and Trakt data.
• Supports OpenAI, Ollama, LM Studio, and other OpenAI-compatible AI services.
• Features include dark/light mode, poster image generation, and customization options.
• Requires port forwarding or reverse proxy setup for external access.

Maintenance & Community

• Active development is indicated by recent updates.
• Community support is available via a Discord Community.

Licensing & Compatibility

• Licensed under the MIT License.
• Permissive license allows for commercial use and integration with closed-source applications.

Limitations & Caveats

External access requires manual port configuration or setting up a reverse proxy. Initial setup involves connecting to various media services and configuring an AI provider.