Can any devs help me find a solution for this?

Building a game and when a user guesses word X, I want to see if it's sufficiently similar to word Y. could I deploy some kind of mini, local LLM inside my codebase for this? ideally don't want to wait / pay each time for an openai api call.

founder of eventcaster (@event / events.xyz), hosting /latenightcrew, member of 🍊 dao

if you have a Postgres instance you could leverage ILIKE for semantic search unless you need it to be lexically similar.

👨‍💻 /uno and /outside, @unofficial

if you're not needing fast results, i would just recommend running Ollama in a Docker container locally, add your computer to a VPC, and go from there. maybe @gm8xx8 has better recommendations.

if you're not needing fast results, i would just recommend running Ollama in a Docker container locally, add your computer to a VPC, and go from there. maybe @gm8xx8 has better recommendations.

https://github.com/ollama/ollama

yeah good idea. right now I have a dictionary of words and then use Levenshtein distance to determine it.

the issue is that it's highly subjective. for example, for some questions, answering "dog" should translate to "pet", but in cases where there are other animals as answers, it should not be accepted. So I would pass the question and other answers in when asking the LLM.

Or you could pg-trgm, lot faster if you can make indexes

Or you could pg-trgm, lot faster if you can make indexes

https://www.postgresql.org/docs/current/pgtrgm.html