Thanks for the reply! So you've actually built your own custom vector DB on top of the memory layer? That's definitely something new.
I'm honestly not sold on memory layers as a whole, I find that adding more context only serves to make the LLM's dumber and I've been slowly leaning towards just having no memory and working on features in isolation.
You've done benchmarks already so that's another step in the right direction, do you find that these benchmarks are good indications of practicality? Have you seen a major difference in LLM performance utilizing this as a memory layer?
Good that it's open source, though always sus about what they actually do. I've seen a lot of supposed memory layers end up just being a RAG system with remember and recall over pg_vector or something. I'll admit I haven't really looked into the code to verify whether that's actually the case so open to being fact checked.
I'm honestly not sold on memory layers as a whole, I find that adding more context only serves to make the LLM's dumber and I've been slowly leaning towards just having no memory and working on features in isolation.
You've done benchmarks already so that's another step in the right direction, do you find that these benchmarks are good indications of practicality? Have you seen a major difference in LLM performance utilizing this as a memory layer?