Comment by rcarmo
3 hours ago
Nice to see more OKF-based approaches. My entry in this field is https://rcarmo.github.io/projects/memento/, which I’ve been running for a few months now.
3 hours ago
Nice to see more OKF-based approaches. My entry in this field is https://rcarmo.github.io/projects/memento/, which I’ve been running for a few months now.
Since you built something on OKF, how would you contrast it with knowledge graph implementations? How do you manage the ontology of what to keep knowledge about? Any cases where traversal would have helped?
Please excuse my noob-ish, naïve question, but to what extent is the business of getting the LLM to actually consult memory a model-dependent thing? Do you have to introduce the tool and guide models with different language for different model families?
Looking at your tool descriptions (as wit the ones on the original post) I wonder if this something perhaps only current frontier models will do, but the systems themselves seem like they'd be even more useful for open weights models with shorter working contexts.
I have seen the value of recording past sessions but I am more skeptical of the value in recording facts, which may soon become stale, about a constantly changing code base. Got benchmarks?
Well, do you see the value of writing notes for yourself occasionally, even though they might soon become stale in your constantly changing environment? Yes, right?
Same principle. It's a good idea to have a schedule to clean them up periodically - an idea you can also put into a note.