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We built a persistent agent memory layer on Elasticsearch with 0.89 recall

We built a persistent agent memory layer on Elasticsearch with 0.89 recall

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Comments (25)

  • stingraycharles
    This is such a basic thing nowadays, and ElasticSearch is massive overkill for it. Something like SQLite or LanceDB or basically any vector database is much more appropriate.This seems to be coming from the “we must make ElasticSearch AI-compatible” department more than anything.
  • itissid
    I have a request: can this text be even more AI generated?
  • 0xbadcafebee
    Summary of the article (https://pastebin.com/aawJfrF6) since the original one is like reading an academic paper filtered through an LLM that hates human readers.It seems like a cool approach. Don't know if it's novel but it's much smarter than "shove markdown files into directories".
  • voidUpdate
    For someone who isn't super familiar, what is "R@10", and is 0.89 good? It's impossible to google for
  • koinedad
    I think this is cool and helpful but my biggest complaint is the writing style and word choice just scream LLM
  • anon
    undefined
  • reactordev
    I built one into my agent using sqlite…
  • tuo-lei
    so the 11% miss rate - do users actually notice when the agent drops a memory? like if someone already said they tried X and the agent suggests it again.
  • winterissnowing
    [flagged]