alt Hacker NewsEventually someone will figure out how to use a graph database to allow an agent to efficiency build & cull context to achieve near determinant activities. Seems like one needs a sufficiently powerful schema and a harness that properly builds the graph of agent knowledge, like how ants naturally figure how where sugar is, when that stockpile depletes and shifts to other sources.
This looks neat, but if you want it to be used for AI purposes, you might want to show a schema more complicated than a twitter network.
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I'd wager the problem is on the side of "LLMs can't value/rank information good enough" rather than "The graph database wasn't flexible/good enough", but I'd be happy to be shown counter-examples.
I'm sure once that problem been solved, you can use the built-in map/object of whatever language, and it'll be good enough. Add save/load to disk via JSON and you have long-term persistence too. But since LLMs still aren't clever enough, I don't think the underlying implementation matters too much.
the airline graph is more complex, I can show the schema for that if you think it's useful?
Working on exactly that! We're local first, but do distributed sync with iroh. Written in rust and fully open source.
Imho having a graph database that is really easy to use and write new cli applications on top of works much better. You don't need strong schema validation so long as you can gracefully ignore what your schema doesn't expect by viewing queries as type/schema declarations.
https://github.com/magic-locker/faculties