Evolving agentic memory frameworks

Key Takeaways

Did you take any different approaches from AM on the LLM calls and the search and retrieval style? >> Yes. Uh in in from AM I mean uh they just uh had a simple prompt where at the time of uh inserting a memory they used to process it first and then insert. And what I mean by insertion is like it forms relationships between the top most similar memories that it could find in the database. Mhm. >> Um and at the retrieval it just used to take the query and then just take the query and do a semantic search on the top most and it takes the topmost K memories and also goes one level deeper because now we can see for all of those top K memories what are the connected other connected memories and you just take them also into account. >> Obviously they will be like less similar to the original query that you have. we added birectional uh connections between these two. So there was only a single connection uh between the memories I I as far as I remember. So I I changed that to like birectional connections because it doesn't make sense if one is going that to only one side because uh every connection that is represented in the graph uh it shouldn't be only that it defines this. I mean we can even have a uh backward connection saying uh it is defined by so that at the time of uh retrieval if this one comes up so this also has some thing to uh give like more context to the model so that at the time of retrieval we can use this and this Together.