Recommendarr is a sophisticated web application that leverages artificial intelligence to provide personalized recommendations for TV shows and movies. By analyzing data from Sonarr, Radarr, and Plex libraries, Recommendarr delivers curated suggestions tailored to user preferences.

Features

• AI-Powered Recommendations: Generate tailored TV show and movie suggestions based on an existing media library, enhancing entertainment choices.
• Seamless Integration: Connects effortlessly to Sonarr and Radarr media servers, as well as optional Plex integration for detailed watch history analysis.
• Flexible AI Support: Compatible with various AI services including OpenAI, local models (Ollama/LM Studio), or any other OpenAI-compatible API, allowing for versatile application.
• Customizable Settings: Adjust recommendation parameters, including count and model settings, to suit individual needs.
• User-Friendly Interface: Features both Dark and Light modes, ensuring a comfortable viewing experience regardless of user preference.
• Rich Visuals: Displays media posters with fallback generation for missing images.

Getting Started

To utilize Recommendarr, a few requirements must be met:

• Access to a Sonarr instance for TV recommendations,
• Access to a Radarr instance for movie recommendations,
• Optional access to a Plex instance for watch history analysis,
• An OpenAI API key or a compatible local model server,
• Node.js (v14+) and npm for local development.

AI Services Compatibility

Recommendarr supports a myriad of AI services to facilitate recommendations, including:

• OpenAI API: Integration with models like GPT-3.5 and GPT-4 for sophisticated recommendations.
• Ollama and LM Studio: Support for running models locally.
• Self-hosted models: Compatible with any service that offers OpenAI-compatible chat completions.

Recommendation Process

1. Connect Services: Users begin by linking their Sonarr and Radarr instances.
2. Set Up AI Service: Configure the chosen AI service through the settings interface.
3. Generate Recommendations: Navigate to the recommendation sections, adjust settings as desired, and retrieve personalized suggestions featuring descriptions and visuals.

Privacy and Security

User data remains secure within the application. Credentials and API keys are stored in local storage, ensuring no private information is exposed externally. Additionally, there’s no tracking or analytics involved, providing a secure environment for users.

Recommendarr optimally enhances media consumption experiences by delivering tailored recommendations, making it a valuable tool for any media enthusiast.