giuseppe99barchetta/SuggestArr
Python tool that automates media content requests to Jellyseer/Overseer based on watch history, with optional LLM-driven personalized recommendations and natural language search.
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SuggestArr connects to media servers like Jellyfin, Plex, and Emby to retrieve recently watched content, then uses TMDb for similarity matching and optional LLM integration for hyper-personalized recommendations. The system can generate AI reasoning for suggestions and supports natural language queries to find matching titles. It automates sending content requests to Seer applications to keep media libraries stocked without manual intervention.
Frequently asked
- What is giuseppe99barchetta/SuggestArr?
- Python tool that automates media content requests to Jellyseer/Overseer based on watch history, with optional LLM-driven personalized recommendations and natural language search.
- Is SuggestArr open source?
- Yes — giuseppe99barchetta/SuggestArr is open source, released under the MIT license.
- What language is SuggestArr written in?
- giuseppe99barchetta/SuggestArr is primarily written in Python.
- How popular is SuggestArr?
- giuseppe99barchetta/SuggestArr has 1.2k stars on GitHub.
- Where can I find SuggestArr?
- giuseppe99barchetta/SuggestArr is on GitHub at https://github.com/giuseppe99barchetta/SuggestArr.