This looks interesting, and will try it out to see what it can do, I like the idea of using temporal values as a significant weight, but one thing isn't really clear to me.

> Traditional Vector DBs require extensive setup, cloud dependencies, and vendor lock-in:

Is this really true ? What's wrong with running your own local Redis vector db? They have their open source version that's separate to their hosted offering..

> https://redis.io/docs/latest/operate/oss_and_stack/

Am I missing something ?

Parts of this weekend is alloted for a local inference build. It genuinely looks interesting. This is kinda what I hoped for local llm scene would become: everything becomes modular and you just swap pieces you want or think would work well together.

How would you compare and contrast this to Steve Yegge's Beads (https://github.com/steveyegge/beads/), or to ordinary file-based memory following vendors' guidelines (https://code.claude.com/docs/en/memory)?

It would awesome if this could be part of AgentFS which also runs on SQLite.

You would be able to easily offer agents that have all of a tenants data and agent state in a single file which can be synced onto s3.

https://github.com/tursodatabase/agentfs