portable-ai-runner / docs /BLIND-TEST-RUNBOOK.md
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home tower -> USB -> friend's machine blind-test runbook
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BLIND TEST - home tower to friend's machine, no internet

The proof that matters: the whole system - app, engine, weights - lives in ONE zip and runs cold on a machine you have never touched.

AT HOME (online)

pip install huggingface_hub requests
huggingface-cli download Johnny5b/portable-ai-runner --repo-type dataset --local-dir CORTEX
cd CORTEX
python setup.py --model ornith        # 5.8 GB Ornith + 639 MB Qwen3-0.6B, sha256-verified
python scripts/make_zip.py            # -> CORTEX-DRIVE-<date>.zip (~6.6 GB, zip sha256 printed)

Put BOTH on the USB stick: the zip, and the Python 3.12 Windows/macOS installer (python.org/downloads) - then the friend machine needs no internet at all.

AT THE FRIEND'S HOUSE (offline)

  1. Copy the zip off the USB, unzip it to a folder (right-click -> Extract All).

  2. If the machine has no Python: run the Python installer FROM THE USB STICK.

  3. Double-click serve.py (or: python serve.py). No pip, no internet needed - serve.py runs on the bare standard library; the LAN mesh just switches off.

  4. Open Chrome -> http://localhost:8080

  5. Models tab -> Scan -> Load next to Ornith-1.5-9B (needs ~16 GB RAM; on 8 GB machines use Qwen3-0.6B). It reads the GGUF from the folder - NO internet is touched. Engine pill must read: llama.cpp WASM - drive (offline).

  6. Chat. Under every reply you will see:

    [TRACE:AWAKE] symbols=... files_read=... lookup_ms=...  |  [TRACE:GEN] tok=... tok_s=...
    

    Those lines are appended to memories/audit_ledger.jsonl on the drive.

WHAT TO CHECK (the actual proof)

  • engine pill says 'drive (offline)' - never CDN
  • capThreads says multi-thread enabled (COOP/COEP ok)
  • a trace line appears under every reply
  • python -c "import json;print(json.loads(open('memories/audit_ledger.jsonl').readlines()[-1]))" shows your measurement traces
  • turn off Wi-Fi before starting - nothing should care

EXPECTED (honest)

  • Ornith-9B browser load needs RAM: 16 GB comfortable, 8 GB risky (use Qwen3-0.6B).
  • tok_s in the traces is UNMEASURED before tonight - whatever your friend's machine produces IS the first browser-tier measurement. Record it.