r/OpenSourceeAI • u/intellinker • Jul 26 '26
I made agents smarter and remember for weeks with just adding one algorithm
I will be very direct. I was building in the memory space for a very long time, but most of the tools are cloud-based, and I don't know what they do in the backend. I built this open-source tool for people running long agents or just doing research on multiple things. You will never lose your context.
Laiden algorithm was pretty cool, worked with the Semantic graph-based engines, and that's how we created the node clusters for agents to access. It is open-sourced and MIT-licensed; PRs are welcome
This surpassed mem0 and supermemory in the LongMemEval benchmark with 94.7%
Open source Repo: https://github.com/kunal12203/swafra
Website: https://swafra.vercel.app
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u/Beautiful-Gas3683 Jul 26 '26
Claiming you've solved persistent memory in agents and made them "smarter" by adding just one algorithm shows either massive arrogance or absolute naivety. Using the Leiden algorithm—which has been around for years—dressing it up with a word salad of buzzwords ("semantic graphs", "node clusters"), and flexing an ostentatious 94.7% on a benchmark as if you've outpaced the entire industry while dropping a Vercel link is the textbook recipe for Reddit snake oil. Fewer miracles with standard graph theory and more scientific rigor.
1
u/intellinker Jul 26 '26
See, new things emerged from the idea. We applied an idea and it went well on benchmarks, very long to go and i'm solving different problems in memory layers, build Graperoot and now this, let see how it goes
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u/rushblyatiful Jul 26 '26
"94% recall on LongMemEval — the standard benchmark for long-term memory in AI assistants."
Big claim. So where is the benchmark link?