apiVersion: lumbridge/v1
kind: Scene
metadata:
  name: qwen38-dflash
  version: 1
  description: "qwen38 with the brain on DFlash2 speculative decoding instead of EAGLE."
  author: karti
  tags: [brain, vision, voice, long-context, sglang, dflash, experimental]

# ⛔ BLOCKED 2026-08-21 — DO NOT ACTIVATE ON THE CURRENT IMAGE.
#
# Our pinned image (lmsysorg/sglang@sha256:3c0abdf4…) ADVERTISES DFLASH as a
# builtin speculative algorithm — `sglang serve --help` lists
#   "Builtins: EAGLE, EAGLE3, NEXTN, STANDALONE, NGRAM, DFLASH, DSPARK"
# and accepts every flag (--speculative-draft-model-path,
# --mamba-radix-cache-strategy). It boots, loads all 4 shards, then dies at the
# draft-worker step with:
#
#   File ".../speculative/dflash_worker_v2.py", line 195, in __init__
#   File ".../speculative/draft_worker_common.py", line 83, in build_draft_tp_worker
#   ValueError: Cannot find model module. 'DFlash2DraftModel' is not a
#   registered model in the Transformers library ... and 'AutoModel' is not
#   present in the model config's 'auto_map'
#
# i.e. the ALGORITHM is builtin but the DRAFT MODEL ARCHITECTURE is not
# registered. That is precisely why MiaAI-Lab's recipe builds a DERIVED image
# from its `patch/` directory for DFlash2 while DSpark runs on the stock image.
# The flag surface being present is NOT evidence the path works — it boots for
# ~3 minutes before failing, and with `--rm` the logs vanish with the container.
#
# TO UNBLOCK: build MiaAI-Lab/Qwen3.8-27B-SGLang-DGX-Spark's patched image
# (./start-dflash.sh builds it), then repin the digest in the registry entry.
#
# WORTH IT? MiaAI-Lab's measured table for this box class:
#   probe              EAGLE/MTP   DSpark   DFlash2
#   code                    34.5     51.5      50.9
#   long essay              24.1     18.3      25.4
#   short chat              21.0     23.2      66.6
# Our EAGLE baseline measured HERE on 2026-08-21: decode 22.8 tok/s mean
# (TTFT 223ms), tool-calling 15/15, with live squawk traffic on the box —
# consistent with the 21.0 short-chat column. DSpark is NOT worth the swap for
# us (23.2 vs 22.8 short chat; its win is coding, which is Claude's job here,
# not spark's). DFlash2's 66.6 short-chat number is the only prize worth the
# image build — and it is the number most in need of independent confirmation,
# since MiaAI-Lab itself footnotes it as "once token-counted correctly".
#
# The drafter is already downloaded: /srv/models/Qwen3.8-27B-DFlash2
# (z-lab/Qwen3.8-27B-DFlash2@50307d4, 3.6 GB).
#
# A/B TWIN OF `qwen38`. Identical model set and identical brain flags except the
# speculative algorithm (EAGLE -> DFLASH) and the drafter mount, so a benchmark
# delta is attributable to the algorithm alone.
#
# Same ordering rule as `qwen38`: brain FIRST. --mem-fraction-static is a
# fraction of TOTAL memory and is reserved as a static pool at boot.
#
# Same activation race too: do not `docker stop` then immediately activate —
# wait for `free -g` to show the memory back first.
#
# Compare with:
#   lumbridge-compute eval run performance --model brain-qwen38-dflash
#   python3 /tmp/toolbench.py http://127.0.0.1:8001/v1 brain-qwen38-dflash 3
# Baseline to beat (EAGLE, measured 2026-08-21, with live squawk traffic on the
# box): decode 22.8 tok/s mean, TTFT 223ms, tool-calling 15/15.
#
# Revert with `lumbridge-compute scene activate qwen38`.
models:
  - brain-qwen38-dflash
  - ears
  - voice-vox
  - voice

budget_gb: 100
activation:
  order: listed
  wait_healthy: true