I have not. My experience has been a few seconds for an 1024x1024 with medium density of text, FWIW. Feel free to try it on a few test images, model is pretty small and fast, but yeah no formal evals on CPU.
cool idea. but for ex over time if users update db schemas, agents run old queries and got errors, is there a mechanism in your lib for agents to examine and self-correct? also is there an auto memory compression the moment the context becomes too big?
good point! yes, there's a feedback mcp tool that agents are instructed to use when they want to save/update ktx "memories". This is a way to keep the wiki+semantic layer up to date beyond the initial ingestion. Plus every time there's a new ingestion the reconciliation mechanism will gather potentially drifting context in one place.
We don't have a manual compression yet, it's part of our other product that ktx used to be a part of before it became open-source. But we decided to move that feature to OSS too, so expect it to come out in the next releases !
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