I just pushed v22 of my project : a local AI companion for Radarr, that goes beyond generic genre or TMDb lists.

This isn’t “yet another recommender”. It’s your personal taste explorer that actually gets the vibe you want in natural language and builds recommendations starting from your existing library.

Key highlights from a real recent run:

  • Command: --mood "dystopian films like Idiocracy, Gattaca or In Time"
  • Output: Metropolis (1927), V for Vendetta, Children of Men, Brazil (1985), Minority Report, Dark City, Equilibrium, Upgrade, The Road… → oppressive/surveillance/inequality/societal critique atmosphere, not just “dark sci-fi”.

How it works :

  • Starts by sampling random movies from your Radarr collection (or uses your mood/like/saga input).
  • Asks a local Ollama LLM (e.g. mistral-small:22b) for 25 thematic suggestions based on atmosphere/vibe.
  • Validates each via OMDb (IMDb rating, genres, plot, director, cast…).
  • Scores intelligently: IMDb rating + genre match + director/actor bonus + plot embedding similarity (cosine on Ollama embeddings).
  • Adds the top ones directly to Radarr (with confirmation: all / one-by-one / no).
  • Persistent blacklist to avoid repeats.

Different modes :

  • --mood "dark psychological thrillers with unreliable narrators" , any vibe you describe
  • --like "Parasite" --mood "mind-bending class warfare" (or just --like "Whiplash")
  • --saga (auto-detects incomplete sagas in your library and suggests missing entries) or --saga "Star Wars"
  • --director "Kubrick" / --actor "De Niro" / --cast "Pacino De Niro" (movies where they co-star)
  • --analyze → full library audit + gaps (e.g. “You’re missing Kurosawa classics and French New Wave”)
  • --watchlist → import from Letterboxd/IMDb
  • --auto → perfect for daily cron / Task Scheduler (wake up to 10 fresh additions)

Standout features:

  • 100% local + privacy-first (Ollama + free OMDb API only)
  • No cloud AI, no tracking
  • colored console output, logs, stats, HTML/CSV exports
  • Synopsis preview before adding
  • Configurable quality profile, min IMDb, availability filters
  • Works on Windows, Linux, Mac

GitHub (clean single-file Python script + great README):
https://github.com/nikodindon/radarr-movie-recommender

If you’re tired of generic Discover lists, Netflix-style randomness, or manual hunting give it a spin. The vibe/mood mode + auto saga completion really change how you expand your collection.

Let me know what you think, any weird mood examples you’d like to test, or features you’d want added!

  • hendrik@palaver.p3x.deEnglish
    11·
    2 days ago

    Lol. For someone who says they expect other people to learn something, you’re a bit short in supply. I mean this would be an opportunity for someone (me) to learn something. But a down-vote won’t do it. And lessons on what not to do (discuss 2.5h, expect it to think) don’t lead anywhere either. I’d need to know what to do in my situation. Or where to find such information?!

    Or was it because I said I value efficiency and for some reason you’re team bloat? I seriously don’t get it.