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Local AI Companion for Radarr: Uses Ollama to Understand Your Taste (Vibe, Atmosphere, Mood), Auto-Complete Sagas, Explore Filmographies, and Add Movies Seamlessly (lemmy.world)
submitted 3 days ago* (last edited 9 hours ago) by nikodindon@lemmy.world to c/selfhosted@lemmy.world
72 comments fedilink hide all child comments
 

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!

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[–] nikodindon@lemmy.world 1 points 9 hours ago

Thanks for the discussion ! I Added more details on the various modes. Apparently I sparked some controversy , I understand some people don't like AI. I find the tool pretty cool to use, feel free to test it and report anything you want ^^

[–] circuscritic@lemmy.ca 46 points 3 days ago* (last edited 3 days ago) (19 children)

Since no one is leaving critical comments that might explain all the downvotes, I'm going to assume they're reflexively anti-AI, which frankly, is a position that I'm sympathetic to.

But one of the benign useful things I already use AI for, is giving it criterias for shows and asking it to generate lists.

So I think your project is pretty neat and well within the scope of actually useful things that AI models, especially local ones, can provide the users.

[–] webkitten@piefed.social 18 points 2 days ago

Seriously; local AI use is what everyone should strive for not only for privacy but because it's better than using a large data centre and the power use for Ollama is negligible.

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[–] meldrik@lemmy.wtf 13 points 2 days ago (1 children)

This is a cool tool. Thanks for sharing. Don’t worry about the downvotes. The Fediverse has a few anti-AI zealots who love to brigade.

[–] nikodindon@lemmy.world 1 points 9 hours ago

Thank you ! :)

[–] timestatic@feddit.org 9 points 2 days ago (1 children)

Sorry OP that you're getting downvote bombed. This is actually really neat. People go nuts when they hear AI but this is fully local so I think this reaction is unjust. This has nothing to do with ram prices since that stems from data centers or corpos pushing AI on you. Thank you for sharing

[–] nikodindon@lemmy.world 2 points 9 hours ago

thanks for your comment :) I edited my original post to explain the project better

[–] pfr@piefed.social 7 points 2 days ago (1 children)

Anti-AI evangelism is at its peak rn.

[–] Andres4NY@social.ridetrans.it 2 points 2 days ago* (last edited 2 days ago) (2 children)

@pfr @nikodindon That assumes it won't get worse, which I hope it does. AI companies have forced me to take down web stuff that I had running for almost 2 decades, because their scrapers are so aggressive.

[–] halloween_spookster@lemmy.world 1 points 2 days ago

20 decades

Found the time traveler!

[–] meldrik@lemmy.wtf 1 points 2 days ago (1 children)

Like what and what have you tried to block it?

[–] Andres4NY@social.ridetrans.it 1 points 2 days ago (1 children)

@meldrik They're impossible to block based on IP ranges alone. It's why all the FOSS git forges and bug trackers have started using stuff like anubis. But yes, I initially tried to block them (this was before anubis existed).

It was a few things that I had to take down; a gitweb instance with some of my own repos, for example. And a personal photo gallery. The scrapers would do pathological things like running repeated search queries for random email addresses or strings.

[–] meldrik@lemmy.wtf 1 points 2 days ago

I’m hosting several things, including Lemmy and PeerTube. I haven’t really been aware of any scrapers, but do you know of any software that can help block it?

[–] fubarx@lemmy.world 7 points 2 days ago (1 children)

The more local inference, the better. Nice work!

[–] nikodindon@lemmy.world 1 points 9 hours ago

thanks for your kind comment :)

[–] eager_eagle@lemmy.world 20 points 3 days ago (1 children)

that's pretty cool, this is just the wrong crowd, don't worry about the downvotes

[–] nikodindon@lemmy.world 1 points 9 hours ago

thanks ! ^^

[–] Scrath@lemmy.dbzer0.com 9 points 3 days ago (3 children)

I remember building something vaguely related in a university course on AI before ChatGPT was released and the whole LLM thing hadn't taken off.

The user had the option to enter a couple movies (so long as they were present in the weird semantic database thing our professor told us to use) and we calculated a similarity matrix between them and all other movies in the database based on their tags and by putting the description through a natural language processing pipeline.

The result was the user getting a couple surprisingly accurate recommendations.

Considering we had to calculate this similarity score for every movie in the database it was obviously not very efficient but I wonder how it would scale up against current LLM models, both in terms of accuracy and energy efficiency.

One issue, if you want to call it that, is that our approach was deterministic. Enter the same movies, get the same results. I don't think an LLM is as predictable for that

[–] LiveLM@lemmy.zip 4 points 3 days ago

One issue, if you want to call it that, is that our approach was deterministic. Enter the same movies, get the same results. I don't think an LLM is as predictable for that

Maybe lowering the temperature will help with this?
Besides, a tinge of randomness could even be considered a fun feature.

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[–] Overspark@piefed.social 7 points 3 days ago (1 children)

A recommendation for Moonrise Kingdom based on Mickey 17? The genres might match, but those are totally different movies.

[–] Janx@piefed.social 5 points 3 days ago (1 children)

Also, A Bug's Life from Mickey 17!?

[–] borari@lemmy.dbzer0.com 2 points 2 days ago

That made me lol so hard. Like what’s the fucking point of this thing when it comes up with shit like that?

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