TRADITIONAL RAG HAS A MASSIVE AMNESIA PROBLEM.
It rediscovers knowledge from scratch on every single query, and nothing ever accumulates.
🚨 OpenKB is a new open-source alternative that finally fixes this.
Based on a brilliant concept outlined by @Karpathy, OpenKB treats document retrieval as a compilation step.
When you drop in a new PDF or codebase, the LLM:
✦ Generates a summary
✦ Updates concept pages
✦ creates actual cross-references
The benefits for devs are huge:
→ Contradictions in your source material are flagged automatically
→ Synthesis reflects everything the system has consumed, not just random K-nearest chunks
→ You get a human-readable, inspectable build artifact
Powered by @PageIndexAI for vectorless retrieval on long docs, this is a massive step up for local AI workflows.
Best part?
It's 100% free and open-source.
repo link in 🧵↓