recommend me movies that i have NOT seen

04/04/25: oai 6 google deep research totally ignore the exclusion list and recommend tons of excluded titles. i feel like a way to solve this would be some kine of tool that allows them to query a suggestion against an exclusion list with embeddings as part of the reasoning or research process.

03/08/25: exclusion lists work reliable with reasoning models. this change in model capabilites make this repo obsolete.

asking llms for movie recs is great \ just you don't want to get recommended movies you've seen already \ so you list all the movies you've seen already \ models struggle to exclude them tho \ this project tries to solve this with a code-based check

how it works

1. user describes movie preferences
2. preferences are turned into a series of search queries
3. /r/MovieSuggestions is searched for relevant results
4. posts with 1st level comments are retrieved
5. llm extracts movie titles from comments
6. already seen movies are filtered out, using imdb csv export
7. remaining movies are checked against user preferences again to ensure quality

usage

• config.ts
• user.txt : describe your movie preferences, likes, dislikes, actors, directors, up to you
• seen.txt : newline sep list of movie titles that u have seen already
  • imdb.ipynb: if you want to gen from an imdb list like your check-ins or ratings
  • seen_extra.txt : sometimes reddit mentioned titles don't match either of imdb title or imdb original title, in that case you can blacklist them manually with the reddit mentioned title alias, case doesn't matter

bash OPENAI_API_KEY="" REDDIT_API_KEY=""

• reddit api key is an access token obtained via oauth, you have to setup a reddit script app and run through the oauth flow to get one

bash pnpm i

bash pnpm tsx main.ts

example

input

• avoid movies that are just at a single location, i prefer 'open world' kinda feel
• avoid movies that are too shaky, action with tons of cut scenes and fights and gun fire, it can have some, but should be a good balance with actual depth
• fucked up stuff is a plus, like black mirror, memento, existenz etc, david cronenberg
• avoid overly romance, sex is a plus but not overly relationship / love driven, heavy
• shouldn't feel too old, it's okay if it's older, but it shouldn't feel old, taxi driver is old but doesn't feel old, great movie
• shouldn't be a too femaleish theme like black swan
• shouldn't be a politics, police or law heavy movie, it can be in there but shouldn't be the main theme
• no musicals, no documentaries, no black and white, no silent movies
• i like cyberpunk, scifi, mystery, thriller btw, not limited to but i like those

output

1. [5/5] A Scanner Darkly src
2. [5/5] Synchronic src
3. [5/5] The Quiet Earth src
4. [5/5] Primer src
5. [5/5] Moon src
6. [5/5] Possessor src
7. [5/5] Brazil src
8. [5/5] Never Let Me Go src
9. [5/5] The Arrival src
10. [5/5] Coherence src
11. [4/5] The Lobster src
12. [4/5] Perfect Blue src
13. [4/5] Sputnik src
14. [4/5] Liquid Sky src
15. [4/5] Lifeforce src
16. [4/5] The Hidden src
17. [4/5] Antiviral src
18. [4/5] Infinity Pool src
19. [4/5] Time Crimes src
20. [4/5] After Yang src
21. [4/5] I Am Mother src
22. [4/5] What Happened to Monday src
23. [4/5] Prospect src
24. [4/5] Space Sweepers src
25. [4/5] Resolution src
26. [3/5] The Killing of a Sacred Deer src
27. [3/5] Under the Silver Lake src
28. [3/5] Sin City src
29. [3/5] They Cloned Tyrone src
30. [3/5] Spring src
31. [3/5] Spectral src
32. [3/5] Returner src
33. [2/5] Blood Quantum src
34. [2/5] Infinity Chamber src