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!
Haha. I think there’s often a rough idea on what kind of programmer people are, judging by their opinion on these AI tools.
Have you tried arguing with your AI assistant for 2.5h straight about memory allocation, and why it can’t just take some example code from some documentation? And it keeps doing memory allocation wrong? Scold it over and over again to use linear algebra instead of trigonometric functions which won’t cut it? Have you tried connecting Claude Code to your oscilloscope and soldering iron to see what kind of mess its code produces?
I’m fairly sure there are reasons to use AI in software development. And there are also good reasons to do without AI, just use your brain and be done with it in one or two hours instead of wasting half a workday arguing and then still ending up doing it yourself 😅
I don’t think these programmers are idiots. There’s a lot of nuance to it. And it’s not easy at all to apply AI correctly so it ends up saving you time.
I mean, I haven’t argued with an AI for 2.5 hours straight, because I know how to use them. And I don’t expect them to think for me, because I know they’re not capable of it.
I was writing assembly language for embedded controllers where the memory is measured in bytes not megabytes, professionally, before half of you were born. I’ve developed preemptive multitasking OSes for 8 but microcontrollers, by hand, for money. These skills ceased to be particularly useful decades ago, but I didn’t sit down and sulk because optimising compilers and ludicrously cheap memory had ended my career, I moved with the times.
Practically everyone who calls themselves a “programmer” has never had the training wheels taken off since the invention of managed runtimes, you don’t now get to complain about what is or is not proper programming. The actual software engineers, who understood that the code was always just a side effect of their real job - understanding and solving problems - just have a new, and really cool, tool to learn how to use. The ones who aren’t up to it will spend 2.5hrs arguing with their AI, and then go back to coding for a hobby. And that’s fine - but if you refuse to learn AI as a tool, you no longer have a career in this industry. Any more than I would’ve if I had refused to accept that memory is basically free now and compilers can write assembly better than me.
I don’t have a definite answer to it. Could be the case I’m somehow intelligent enough to remember all the quirks of C and C++. Eat a book on my favorite microcontroller in 3 days and remember details about the peripherals and processor. But somehow I’m too stupid to figure out how AI works. I can’t rule it out. At least I’ve tried.
I still think microcontroller programming is way more fun than coding some big Node.JS application with a bazillion of dependencies.
And I sometimes wish people would write an instant messenger like we have 4MB of RAM available and not eat up 1GB with their Electron app, which then also gets flagged by the maintainers for using some components that have open vulnerabilities, twice a year.
I mean I don’t see any reason why I shouldn’t be allowed to complain about it.
But yeah, software development is always changing. And sometimes I wonder if things are for the better or the worse.
I’ve had a lot of bad experience with embedded stuff and trying to let AI do it for me. I mostly ended up wasting time. I always thought it must be because these LLMs are mainly trained on regular computer code, without these constraints and that’s why they always smuggle in silly mistakes. And while fixing one thing, they break a different thing. But could also be my stupidity.
I’ve had a way better time letting it do webfrontends, CSS, JavaScript… even architecture.
But I don’t think this (specifically) is one of the big issues with AI anyway. People are free to learn whatever they want. There’s a lot if niches in computer science. And diversity is a good thing.
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.