feat(grafana): graph frank-archon in llm-fleet (radiance vllm:*/radiance:* + a new endpoint section)

frank-archon (radiance, Dankserver) emits vllm:* + radiance:* (job=frank-archon).
llm-fleet.json queried only llamacpp:* and its endpoint picker selected via
label_values(llamacpp:.*), so archon - despite being scraped and alert-on
(vllm-fleet group) - had zero panels. The dashboard description also still
claimed archon was llama.cpp, which is stale.

- Fix the description: two namespaces; the $job picker is the llama.cpp pair
  (dragoon/zealot); archon is radiance and gets its own section.
- Add a frank-archon row + 8 panels: vllm:* throughput, request outcomes by
  finish reason, queue/preemption, TTFT p50/p95, and the radiance natives vllm
  omits - decode/prefill t/s, MTP draft acceptance, engine-step timing, prefix
  hit. All 14 queries verified live against Prometheus (non-empty).

Dashboards-only; the next grafana deploy provisions it.

.AGENTTRASH/frank-default-small.env.llama.cpp

@@ -0,0 +1,71 @@
+# Tunables for frank-default-small (Tiel-Coder-35B-A3B UD-Q6_K_XL,
+# qwen35moe hybrid MoE, Dankserver, RTX 3090).
+#
+# Runtime: upstream llama.cpp (latest master, CUDA build with
+# -DGGML_CUDA_FA_ALL_QUANTS=ON -DCMAKE_CUDA_ARCHITECTURES=86) on RTX 3090
+# 24 GB; Ryzen 7 7700X; 62 GB RAM.  Replaced the ik_llama.cpp Ornith
+# CRACK Q8_0 deployment on 2026-09-01.
+#
+# Model: peculiar-ragdoll/Tiel-Coder-35B-A3B-GGUF, UD-Q6_K_XL quant
+# (30 GB).  Architecture: qwen35moe — 40 layers, full_attention_interval=4
+# (10 attention + 30 SSM/Mamba), 256 experts / 8 used, 2 KV heads × 256
+# dim, embedding 2048, rope dimension_count 64, rope freq_base 10 000 000.
+# Text-only (no mmproj).  Built-in chat template in the GGUF.
+#
+# Expert offload: --cpu-moe keeps all 256 expert weights in CPU RAM.
+# Non-expert weights (~1.6 GB) fit entirely on the 24 GB card.
+#
+# KV cache: Q8_0 for both K and V.  With CTX_SIZE=200700 (66 900 per slot
+# × 3 parallel) and 10 attention layers, the KV cache is ~2 GB — the
+# requested 2 GB VRAM buffer.
+#
+# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE. The
+# ROCm HIP runtime reads those bare env vars (see the 2026-08-13 TEMP
+# incident). This box is NVIDIA/CUDA, but the rule keeps the env portable.
+
+# Model file (UD-Q6_K_XL, 30 GB, text-only MoE hybrid).
+MODEL_DIR=/home/dank/models/tiel-coder-35b
+MODEL_FILE=Tiel-Coder-35B-A3B-UD-Q6_K_XL.gguf
+
+# Upstream llama.cpp llama-server (CUDA build, latest master).
+# Built with -DGGML_CUDA_FA_ALL_QUANTS=ON -DCMAKE_CUDA_ARCHITECTURES=86
+# using the staged CUDA 13.2 toolkit at /home/dank/cuda13-stage.
+LLAMA_SERVER=/home/dank/llama.cpp/build/bin/llama-server
+
+ALIAS=frank-default-small
+BIND_ADDR=0.0.0.0
+LISTEN_PORT=7770
+
+# Total context budget across all parallel slots.  200700 / 3 = 66 900
+# per slot.  The model's context_length is 262 144, so 66 900 is well
+# within range.
+CTX_SIZE=200700
+PARALLEL=3
+
+# Expert offload: all MoE expert weights pinned to CPU RAM.
+CPU_MOE=1
+
+# All non-expert layers on GPU (auto-fit will determine the exact count;
+# with --cpu-moe the non-expert footprint is ~1.6 GB, leaving ample room).
+N_GPU_LAYERS=999
+
+# KV cache: Q8_0 for both K and V.  ~2 GB total for 200700 ctx × 3 slots
+# × 10 attention layers × (2 KV heads × 256 dim × 1 byte) × 2 (K+V).
+CACHE_TYPE_K=q8_0
+CACHE_TYPE_V=q8_0
+
+VERBOSITY=2
+
+# Prefill batch sizing.
+BATCH_SIZE=4096
+UBATCH_SIZE=1024
+
+# Sampling.
+TEMPERATURE=1.0
+TOP_K=20
+TOP_P=0.95
+MIN_P=0.0
+
+# Compute threads lowered so other processes keep a core.
+THREADS=7
+THREADS_HTTP=8

.AGENTTRASH/frank-default-small.service.llama.cpp

@@ -0,0 +1,16 @@
+[Unit]
+Description=llama.cpp Tiel-Coder-35B-A3B Q6_K_XL qwen35moe hybrid MoE (dankserver, frank-default-small)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+Environment="FRANK_SMALL_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-default-small.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-small.sh
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

.AGENTTRASH/frank-dragoon.env.llama.cpp

@@ -0,0 +1,126 @@
+# Tunables for frank-dragoon (kingjones777/Qwen3.8-Flash-Next-ROCmFP4-
+# STRIX-GGUF on the kingjones30/ROCmFPX llama.cpp runtime, Dankclaw,
+# Strix Halo gfx1151, unified memory).
+#
+# Runtime: kingjones30/ROCmFPX (fork of charlie12345/ROCmFPX with the
+# qwen4exp-on-rocmfpx-d3ca537 patch applied — the model card's pinned
+# runtime: ROCmFP4 tensor types AND the qwen4exp architecture in one
+# tree; stock llama.cpp and charlie's fork alone cannot load this GGUF).
+# Built per the card recipe:
+#   cmake -B build -DGGML_HIP=ON -DGPU_TARGETS=gfx1151 -DGGML_NATIVE=ON -DCMAKE_BUILD_TYPE=Release
+# at /home/dank/GitPackages/kingjones-ROCmFPX/build.
+# Replaced the agentionai ROCmFP4-FAST imatrix deployment (charlie's
+# build-qwen38 runtime) on 2026-08-30.
+#
+# Model: Qwen3.8-Flash-Next base (qwen4exp MoE: 512 experts / 10 used,
+# 48 layers = 12 attention + 36 SSM, QSA indexer, hyper-connections, PLE
+# at layer 1), Q4_0_ROCMFP4_STRIX (file_type 105), 113.47 GiB single
+# file. STRIX is the top quality tier: PLE table at Q8_0 (50.66 GiB),
+# token embeddings + lm head at Q6_K. The PLE table NEVER enters GPU
+# memory — it streams from the file through the OS page cache. Two hard
+# card constraints:
+#  1. mmap MUST stay enabled (default) — --no-mmap forces the 50.66 GiB
+#     table into anonymous memory and the cgroup killer takes the
+#     process with nothing in the server log (only dmesg).
+#  2. Do NOT pin the PLE tensor to CPU with -ot — measured gen fell
+#     ~23 -> 13.4 tok/s; the kernel streams it better.
+# NOTE: the card's own build_attn_qsa still calls ggml_fill on the
+# F16-cast kq mask (the path that aborted our charlie build with
+# --flash-attn on before scripts/patches/qwen4exp-qsa-f32-mask.patch).
+# If a clean kingjones-tree build aborts graph build with
+# GGML_ASSERT(a-type == GGML_TYPE_F32), port that fix (F32 base mask +
+# cast at the attention call) into this tree and rebuild.
+#
+# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE. The ROCm HIP runtime reads those bare env vars (see the 2026-08-13 TEMP
+# incident). llama.cpp reads --host/--port/--temp as CLI flags, never as
+# env vars.
+
+# kingjones30/ROCmFPX runtime binary (card recipe build).
+LLAMA_BIN=/home/dank/GitPackages/kingjones-ROCmFPX/build/bin/llama-server
+
+# Model package from
+# https://huggingface.co/kingjones777/Qwen3.8-Flash-Next-ROCmFP4-STRIX-GGUF
+# Layout: single unsharded GGUF, text-only (the repo ships no mmproj;
+# the vision tower below is borrowed from the agentionai FAST package —
+# same base model, f16 — kept only if it loads clean, drop
+# MMPROJ_PATH if it does not).
+MODEL_DIR=/home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX
+MODEL_FILE=Qwen3.8-Flash-Next-Q4_0-ROCmFP4-STRIX.gguf
+MMPROJ_PATH=/home/dank/models/agentionai-Qwen3.8-Flash-Next-ROCmFP4-FAST/mmproj/mmproj-Qwen3.8-Flash-Next-f16.gguf
+
+# Qwen-Sharp chat template (tracked in the repo, staged on the host). The
+# Sharp template drives thinking on by default (medium effort); the server
+# emits reasoning in DeepSeek format so clients receive reasoning_content
+# separately instead of literal thinking tags in content.
+CHAT_TEMPLATE_FILE=/home/dank/serverAppConfigs/scripts/chat-template.jinja
+CHAT_TEMPLATE_KWARGS='{"enable_thinking":true,"preserve_thinking":true,"preserve_reasoning":true}'
+
+# Alias + network.
+ALIAS=frank-dragoon
+BIND_ADDR=0.0.0.0
+LISTEN_PORT=7770
+
+# Serving: 401408-token context, TWO slots (parallel 2), batch 4096 /
+# ubatch 512, 16+16 threads, f16 KV, 16 context checkpoints, 8 GiB
+# prompt cache. --fit off: auto-fit segfaults on this model's
+# hyper-connection/indexer config; -ngl 999 puts every layer on the
+# SVM-backed GPU pool. ubatch 512 matches the card's re-measurement
+# (-ub 1024/2048/4096 showed no effect; -t 32 vs 16 is noise).
+#
+# CTX_SIZE=401408 / PARALLEL=2: carried over from the FAST deployment
+# where it loaded clean (~74 s, health 200). The card measures the full
+# 262144 window at ~71.7 GiB GTT at load on the same 128 GB board; QSA
+# caps KV growth so the extra window is cheap. KV footprint scales
+# with the 12 attention layers only. Verify load on first STRIX boot.
+CTX_SIZE=401408
+PARALLEL=2
+
+BATCH_SIZE=4096
+UBATCH_SIZE=512
+NUM_THREADS=16
+THREAD_BATCH=16
+CACHE_TYPE_K=f16
+CACHE_TYPE_V=f16
+CTX_CHECKPOINTS=16
+CACHE_RAM=8192
+SLOT_SAVE_PATH=/home/dank/serverAppConfigs/scripts/slot-state
+SPLIT_MODE=none
+FIT=off
+NGL=999
+FLASH_ATTN=on
+
+# Sampling (card instruct table, non-thinking).
+TEMPERATURE=0.7
+TOP_K=20
+TOP_P=0.8
+MIN_P=0.0
+PRESENCE_PENALTY=1.5
+
+# Reasoning on (Sharp template drives it; preserve_thinking + preserve_reasoning
+# keep the reasoning trail in the conversation). DeepSeek format projects the
+# reasoning into the API's reasoning_content field instead of literal thinking
+# tags.
+REASONING=on
+REASONING_FORMAT=deepseek
+
+# Strix Halo unified memory + native gfx1151.
+HSA_OVERRIDE_GFX_VERSION=11.5.1
+
+VERBOSITY=4
+
+
+# Speculative decoding: disabled. The card's Usage block ships no spec
+# flags. The Flash-Next MTP heads do not load on this loader (requires
+# per-layer blk.N.hc_attn_norm; every head carries only blk.48 —
+# verified 3x on build-qwen38). DRAFT_MODEL_* point at the retired
+# agentionai FAST head and are unused while SPEC_TYPE=none.
+DRAFT_MODEL_DIR=/home/dank/models/mtp-Qwen3.8-Flash-Next-FAST
+DRAFT_MODEL_FILE=Qwen3.8-Flash-Next-MTP-ROCmFP4-FAST.gguf
+SPEC_TYPE=none
+SPEC_DRAFT_N_MAX=3
+SPEC_DRAFT_N_MIN=0
+SPEC_DRAFT_P_MIN=0.75
+SPEC_DRAFT_NGL=999
+SPEC_DRAFT_DEVICE=ROCm0
+SPEC_DRAFT_TYPE_K=f16
+SPEC_DRAFT_TYPE_V=f16

.AGENTTRASH/frank-dragoon.service.llama.cpp

@@ -0,0 +1,16 @@
+[Unit]
+Description=ROCmFPX (kingjones30 fork) llama.cpp Qwen3.8-Flash-Next ROCmFP4 STRIX 177B MoE (dankclaw, frank-dragoon)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+Environment="FRANK_DRAGOON_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-dragoon.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-dragoon.sh
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

.AGENTTRASH/frank-npu.env.flm-npu

@@ -0,0 +1,23 @@
+# Tunables for frank-npu (FastFlowLM NPU endpoint, Dankclaw)
+# Runtime: FLM 1.0.1 (/usr/bin/flm) on the XDNA2 NPU (50 TOPS). Boot tag is
+# nuextract3:4b (NuExtract3-4B-NPU2, Qwen3.5-4B skeleton, structured-extraction
+# model); serve routes every request by the exact FLM registry tag in the
+# request's model field, so any registered tag (gemma4-it:e4b, qwythos:9b, ...)
+# is reachable on this port regardless of the boot tag. The NPU is a
+# single-lane device: generations serialize FIFO, and the first request after a
+# model swap pays the ~6-11 s load cost. The NPU draws from the unified RAM
+# pool shared with frank-dragoon (iGPU).
+FLM_MODEL=nuextract3:4b
+FLM_HOST=0.0.0.0
+FLM_PORT=7771
+# turbo = max NPU power mode (xrt-smi configure --pmode turbo at serve start).
+# No other tenant uses the NPU on this host, so the top mode costs nothing to
+# neighbours; drop to `performance` if iGPU power-budget contention ever shows.
+FLM_PMODE=turbo
+# FLM_ASR=1 additionally loads Whisper-V3-Turbo-NPU2 (+0.62 GB) and exposes
+# /v1/audio/transcriptions. NuExtract3 answers text-only; audio stays off.
+FLM_ASR=0
+# -1 = no --ctx-len flag: every pack loads with its own trained context
+# (nuextract3:4b -> 32768, gemma4-it:e4b -> 131072). A global override would
+# over-allocate KV for the small packs.
+FLM_CTX_LEN=-1

.AGENTTRASH/frank-npu.service.flm-npu

@@ -0,0 +1,17 @@
+[Unit]
+Description=FastFlowLM NPU sight+sound inference (frank-npu) on Dankclaw
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+Environment="FRANK_NPU_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-npu.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-npu.sh
+LimitMEMLOCK=infinity
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

.AGENTTRASH/serve-frank-dragoon.sh.llama.cpp

@@ -0,0 +1,180 @@
+#!/usr/bin/env bash
+# Serve kingjones777/Qwen3.8-Flash-Next-ROCmFP4-STRIX-GGUF as
+# frank-dragoon via the kingjones30/ROCmFPX llama.cpp runtime on
+# Dankclaw (Strix Halo gfx1151, unified memory).
+#
+# Runtime: kingjones30/ROCmFPX (fork of charlie12345/ROCmFPX with the
+# model card's qwen4exp-on-rocmfpx patch) built at
+# /home/dank/GitPackages/kingjones-ROCmFPX/build (HIP, gfx1151,
+# ROCm 7.2.4, card recipe). The ROCmFP4 quant types plus the qwen4exp
+# architecture must be in one tree; stock llama.cpp cannot load this
+# GGUF.
+#
+# Model: Qwen3.8-Flash-Next base (qwen4exp MoE: 512 experts / 10 used,
+# 48 layers = 12 attention + 36 SSM, QSA indexer, hyper-connections, PLE
+# at layer 1) quantized Q4_0_ROCMFP4_STRIX, 113.47 GiB single file. The
+# 50.66 GiB PLE n-gram table stays OUT of GPU memory and streams via
+# mmap from the OS page cache — never add --no-mmap or -ot for it.
+#
+# Profile: card sampling table (temp 0.7, top_p 0.80, top_k 20, min_p 0.0,
+# presence 1.5 — non-thinking instruct) mixed with the validated serving
+# profile: ctx 401408 x 2 slots, b 4096 / ub 512, t 16 / tb 16, f16 KV,
+# fa on (if the graph build aborts on the QSA F16 mask, see the note in
+# the env file: port scripts/patches/qwen4exp-qsa-f32-mask.patch into
+# this tree and rebuild), cont-batching, prompt cache + 8 GiB cache-ram
+# + idle-slot cache, 16 ctx checkpoints, --fit off (auto-fit segfaults
+# on qwen4exp hyper-connection config). Speculative decoding off: the
+# Flash-Next MTP heads do not load on this loader; the card ships no
+# spec flags.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-dragoon.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) -------------------
+: "${LLAMA_BIN:=/home/dank/GitPackages/kingjones-ROCmFPX/build/bin/llama-server}"
+: "${MODEL_DIR:=/home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX}"
+: "${MODEL_FILE:=Qwen3.8-Flash-Next-Q4_0-ROCmFP4-STRIX.gguf}"
+: "${MMPROJ_PATH:=/home/dank/models/agentionai-Qwen3.8-Flash-Next-ROCmFP4-FAST/mmproj/mmproj-Qwen3.8-Flash-Next-f16.gguf}"
+: "${CHAT_TEMPLATE_FILE:=$SCRIPT_DIR/chat-template.jinja}"
+: "${CHAT_TEMPLATE_KWARGS:={}}"
+: "${ALIAS:=frank-dragoon}"
+: "${BIND_ADDR:=0.0.0.0}"
+: "${LISTEN_PORT:=7770}"
+: "${CTX_SIZE:=401408}"
+: "${PARALLEL:=2}"
+: "${BATCH_SIZE:=4096}"
+: "${UBATCH_SIZE:=512}"
+: "${NUM_THREADS:=16}"
+: "${THREAD_BATCH:=16}"
+: "${CACHE_TYPE_K:=f16}"
+: "${CACHE_TYPE_V:=f16}"
+: "${CTX_CHECKPOINTS:=16}"
+: "${CACHE_RAM:=8192}"
+: "${SLOT_SAVE_PATH:=$SCRIPT_DIR/slot-state}"
+: "${SPLIT_MODE:=none}"
+: "${FIT:=off}"
+: "${NGL:=999}"
+: "${FLASH_ATTN:=on}"
+: "${TEMPERATURE:=0.7}"
+: "${TOP_K:=20}"
+: "${TOP_P:=0.8}"
+: "${MIN_P:=0.0}"
+: "${PRESENCE_PENALTY:=1.5}"
+: "${REASONING:=on}"
+: "${REASONING_FORMAT:=deepseek}"
+: "${HSA_OVERRIDE_GFX_VERSION:=11.5.1}"
+: "${SPEC_TYPE:=none}"
+: "${DRAFT_MODEL_DIR:=/home/dank/models/mtp-Qwen3.8-Flash-Next-FAST}"
+: "${DRAFT_MODEL_FILE:=Qwen3.8-Flash-Next-MTP-ROCmFP4-FAST.gguf}"
+: "${SPEC_DRAFT_N_MAX:=3}"
+: "${SPEC_DRAFT_N_MIN:=0}"
+: "${SPEC_DRAFT_P_MIN:=0.75}"
+: "${SPEC_DRAFT_NGL:=999}"
+: "${SPEC_DRAFT_DEVICE:=ROCm0}"
+: "${SPEC_DRAFT_TYPE_K:=f16}"
+: "${SPEC_DRAFT_TYPE_V:=f16}"
+
+MODEL="$MODEL_DIR/$MODEL_FILE"
+for f in "$LLAMA_BIN" "$MODEL" "$CHAT_TEMPLATE_FILE"; do
+    if [[ ! -r "$f" ]]; then
+        echo "missing or unreadable required artifact: $f" >&2
+        exit 1
+    fi
+done
+if [[ ! -x "$LLAMA_BIN" ]]; then
+    echo "missing executable runtime: $LLAMA_BIN" >&2
+    exit 1
+fi
+
+# --- speculative decoding (MTP draft head) ---------------------------------
+# The MTP draft head is a separate GGUF sidecar loaded via --spec-draft-model
+# (alias --model-draft).  ngram-only specs do not need a draft file.
+# Set SPEC_TYPE=none in the env to disable speculative decoding entirely.
+SPEC_ARGS=()
+if [[ -n "$SPEC_TYPE" && "$SPEC_TYPE" != "none" ]]; then
+    SPEC_ARGS=(
+        --spec-type "$SPEC_TYPE"
+        --spec-draft-n-max "$SPEC_DRAFT_N_MAX"
+        --spec-draft-n-min "$SPEC_DRAFT_N_MIN"
+        --spec-draft-p-min "$SPEC_DRAFT_P_MIN"
+    )
+    if [[ "$SPEC_TYPE" == *draft-mtp* ]]; then
+        DRAFT_MODEL="$DRAFT_MODEL_DIR/$DRAFT_MODEL_FILE"
+        if [[ ! -r "$DRAFT_MODEL" ]]; then
+            echo "missing or unreadable draft model: $DRAFT_MODEL" >&2
+            exit 1
+        fi
+        SPEC_ARGS+=(
+            --spec-draft-model "$DRAFT_MODEL"
+            --spec-draft-ngl "$SPEC_DRAFT_NGL"
+            --spec-draft-device "$SPEC_DRAFT_DEVICE"
+            --spec-draft-type-k "$SPEC_DRAFT_TYPE_K"
+            --spec-draft-type-v "$SPEC_DRAFT_TYPE_V"
+        )
+    fi
+    if [[ -n "${SPEC_DRAFT_P_SPLIT:-}" ]]; then
+        SPEC_ARGS+=(--spec-draft-p-split "$SPEC_DRAFT_P_SPLIT")
+    fi
+fi
+
+# The STRIX repo ships no mmproj; this is the agentionai FAST package's
+# f16 vision tower for the same base model. Passed only when readable.
+MMPROJ_ARGS=()
+if [[ -n "${MMPROJ_PATH:-}" && -r "${MMPROJ_PATH:-}" ]]; then
+    MMPROJ_ARGS=(--mmproj "$MMPROJ_PATH")
+fi
+
+SERVER_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+mkdir -p "$SLOT_SAVE_PATH"
+ROCM_PATH="${ROCM_PATH:-/opt/rocm}"
+LIBRARY_PATH="$SERVER_DIR:$ROCM_PATH/lib:$ROCM_PATH/lib/rocm_sysdeps/lib:$ROCM_PATH/lib/llvm/lib${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"
+
+exec /usr/bin/env \
+    ROCM_PATH="$ROCM_PATH" \
+    HIP_VISIBLE_DEVICES=0 \
+    LD_LIBRARY_PATH="$LIBRARY_PATH" \
+    HSA_OVERRIDE_GFX_VERSION="$HSA_OVERRIDE_GFX_VERSION" \
+    "$LLAMA_BIN" \
+    --model "$MODEL" \
+    --alias "$ALIAS" \
+    --chat-template-file "$CHAT_TEMPLATE_FILE" \
+    --chat-template-kwargs "$CHAT_TEMPLATE_KWARGS" \
+    --host "$BIND_ADDR" \
+    --port "$LISTEN_PORT" \
+    --jinja \
+    --device ROCm0 \
+    --gpu-layers "$NGL" \
+    --split-mode "$SPLIT_MODE" \
+    --parallel "$PARALLEL" \
+    --ctx-size "$CTX_SIZE" \
+    --batch-size "$BATCH_SIZE" \
+    --ubatch-size "$UBATCH_SIZE" \
+    --fit "$FIT" \
+    --flash-attn "$FLASH_ATTN" \
+    --cache-type-k "$CACHE_TYPE_K" \
+    --cache-type-v "$CACHE_TYPE_V" \
+    --threads "$NUM_THREADS" \
+    --threads-batch "$THREAD_BATCH" \
+    --ctx-checkpoints "$CTX_CHECKPOINTS" \
+    --cache-ram "$CACHE_RAM" \
+    --slot-save-path "$SLOT_SAVE_PATH" \
+    --cache-prompt \
+    --cache-idle-slots \
+    --metrics \
+    --temp "$TEMPERATURE" \
+    --top-p "$TOP_P" \
+    --top-k "$TOP_K" \
+    --min-p "$MIN_P" \
+    --presence-penalty "$PRESENCE_PENALTY" \
+    --reasoning "$REASONING" \
+    --reasoning-format "$REASONING_FORMAT" \
+    --reasoning-budget -1 \
+    "${MMPROJ_ARGS[@]}" \
+    "${SPEC_ARGS[@]}"

.AGENTTRASH/serve-frank-npu.sh.flm-npu

@@ -0,0 +1,62 @@
+#!/usr/bin/env bash
+# Serve the FastFlowLM (FLM) sight+sound endpoint — frank-npu.
+#
+# Runs `flm serve <tag>` on the XDNA2 NPU (50 TOPS, Dankclaw). The NPU is a
+# single-lane device: generations serialize in FIFO order, so this is a
+# background/triage endpoint, not an interactive multi-user chat. The NPU
+# draws from the unified RAM pool shared with frank-dragoon (the iGPU
+# llama.cpp service); see serverAppConfigs-docs/LLM/frank-npu.md
+# for the memory budget and the model-selection tradeoff.
+#
+# NOTE: FLM requires unlimited memlock. The unit sets LimitMEMLOCK=infinity.
+# NOTE: an unknown model tag does NOT 404 — /v1/chat/completions answers HTTP 200 with a
+# flat {"error":"Failed to load <tag> model!"} body and no choices; /v1/completions returns a
+# nested OpenAI-shaped server_error (code 500) also under HTTP 200. Client model IDs must be the exact FLM registry
+# tag (e.g. gemma4-it:e4b), never a service alias. Custom tags only resolve
+# when FLM_CONFIG_PATH points at the user registry that carries them and their
+# kernels are symlinked into /home/dank/.config/flm/xclbins/<PackName>.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_NPU_ENV_FILE:-$SCRIPT_DIR/frank-npu.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) -------------------
+: "${FLM_BIN:=/usr/bin/flm}"
+: "${FLM_MODEL:=gemma4-it:e4b}"
+: "${FLM_HOST:=0.0.0.0}"
+: "${FLM_PORT:=7771}"
+: "${FLM_PMODE:=turbo}"
+: "${FLM_ASR:=0}"
+: "${FLM_CTX_LEN:=131072}"
+
+# The user registry is a superset of the system registry (it carries the
+# custom tags too), and its model_path resolves relative to the registry file,
+# so exports keep a tag swap in the env file from needing script edits.
+export FLM_CONFIG_PATH="${FLM_CONFIG_PATH:-/home/dank/.config/flm/model_list.json}"
+export FLM_XCLBIN_PATH="${FLM_XCLBIN_PATH:-/home/dank/.config/flm/xclbins}"
+
+if [[ ! -x "$FLM_BIN" ]]; then
+    echo "missing flm binary: $FLM_BIN" >&2
+    exit 1
+fi
+
+# --- optional flags ----------------------------------------------------------
+OPT_ARGS=()
+if [[ "${FLM_ASR}" != "0" ]]; then
+    OPT_ARGS+=(--asr "${FLM_ASR}")
+fi
+if [[ "${FLM_CTX_LEN}" != "-1" ]]; then
+    OPT_ARGS+=(--ctx-len "${FLM_CTX_LEN}")
+fi
+
+exec "$FLM_BIN" serve "$FLM_MODEL" \
+    --host "$FLM_HOST" \
+    -p "$FLM_PORT" \
+    --pmode "$FLM_PMODE" \
+    "${OPT_ARGS[@]}"

.AGENTTRASH/serve-frank-small.sh.llama.cpp

@@ -0,0 +1,87 @@
+#!/usr/bin/env bash
+# Serve peculiar-ragdoll/Tiel-Coder-35B-A3B (UD-Q6_K_XL) as
+# frank-default-small via stock llama.cpp on Dankserver (RTX 3090).
+#
+# Runtime: upstream llama.cpp (latest master, CUDA build with
+# -DGGML_CUDA_FA_ALL_QUANTS=ON -DCMAKE_CUDA_ARCHITECTURES=86).
+# The model is a 35B-total / 8-active MoE hybrid (qwen35moe arch) with
+# SSM/Mamba layers (full_attention_interval=4: 10 attention + 30 SSM
+# layers out of 40).  256 experts, 8 used per token.
+#
+# Expert offload: --cpu-moe keeps all 256 expert weights in CPU RAM.
+# Non-expert weights (attention, SSM, shared expert, embeddings, output)
+# are ~1.6 GB and fit entirely on the 24 GB RTX 3090.
+#
+# KV cache: Q8_0 for both K and V.  With CTX_SIZE=200700 (66 900 per
+# slot × 3 parallel) and 10 attention layers (2 KV heads × 256 dim),
+# the KV cache is ~2 GB — the requested 2 GB VRAM buffer.
+#
+# Model is loaded with mmap (default).  The 30 GB Q6_K_XL file is
+# memory-mapped; only accessed pages enter RAM.
+#
+# Tunables come from frank-default-small.env unless FRANK_SMALL_ENV_FILE
+# overrides that path.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_SMALL_ENV_FILE:-$SCRIPT_DIR/frank-default-small.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) -----------------
+: "${MODEL_DIR:=/home/dank/models/tiel-coder-35b}"
+: "${MODEL_FILE:=Tiel-Coder-35B-A3B-UD-Q6_K_XL.gguf}"
+: "${LLAMA_SERVER:=/home/dank/llama.cpp/build/bin/llama-server}"
+: "${ALIAS:=frank-default-small}"
+: "${BIND_ADDR:=0.0.0.0}"
+: "${LISTEN_PORT:=7770}"
+: "${CTX_SIZE:=200700}"
+: "${PARALLEL:=3}"
+: "${CACHE_TYPE_K:=q8_0}"
+: "${CACHE_TYPE_V:=q8_0}"
+: "${N_GPU_LAYERS:=999}"
+: "${BATCH_SIZE:=4096}"
+: "${UBATCH_SIZE:=1024}"
+: "${VERBOSITY:=2}"
+: "${CPU_MOE:=1}"
+: "${TEMPERATURE:=1.0}"
+: "${TOP_K:=20}"
+: "${TOP_P:=0.95}"
+: "${MIN_P:=0.0}"
+: "${THREADS:=7}"
+: "${THREADS_HTTP:=8}"
+
+MODEL="$MODEL_DIR/$MODEL_FILE"
+
+if [[ ! -f "$MODEL" ]]; then
+    echo "missing required file: $MODEL" >&2
+    exit 1
+fi
+if [[ ! -x "$LLAMA_SERVER" ]]; then
+    echo "missing llama-server binary: $LLAMA_SERVER" >&2
+    exit 1
+fi
+
+exec "$LLAMA_SERVER" \
+    --model "$MODEL" \
+    $([ "$CPU_MOE" = "1" ] && printf -- "--cpu-moe") \
+    --cache-type-k "$CACHE_TYPE_K" \
+    --cache-type-v "$CACHE_TYPE_V" \
+    --ctx-size "$CTX_SIZE" \
+    --parallel "$PARALLEL" \
+    --gpu-layers "$N_GPU_LAYERS" \
+    --batch-size "$BATCH_SIZE" \
+    --ubatch-size "$UBATCH_SIZE" \
+    --temp "$TEMPERATURE" \
+    --top-k "$TOP_K" \
+    --top-p "$TOP_P" \
+    --min-p "$MIN_P" \
+    --threads "$THREADS" \
+    --threads-http "$THREADS_HTTP" \
+    --alias "$ALIAS" \
+    --host "$BIND_ADDR" \
+    --port "$LISTEN_PORT"

AGENTS.md

@@ -26,8 +26,8 @@ merge absorbed the former `vllmScripts` repo, history preserved).
 | Target | Service | Runtime | Payload | Port |
 |--------|---------|---------|---------|------|
 | Dankserver | `frank-archon` | radiance, digest-pinned, root unit, TP=2 | publisher `qwen3.8-next-flash-fp8-iq4r-moe.rad` | 7770 |
-| Dankclaw | `frank-dragoon` | halogen-flash-server 0.18.20, digest-pinned, root unit | `qwen38-flash-next-v2-abliterated.hgn` + n-gram + vision tower | 7770 |
+| Dankclaw | `frank-dragoon` | halogen-flash-server 0.16.2, digest-pinned, root unit | `qwen38-flash-next-v2-abliterated.hgn` + n-gram + vision tower | 7770 |
-| Dankclaw | `frank-zealot` | llama.cpp PrismML fork build 12118, root unit — the only loader for this payload | Ternary-Bonsai-2-9B PQ2_0 + Q8_0 mmproj + rank-1 refusal adapter | 7771 |
+| Dankclaw | `frank-zealot` | llama.cpp PrismML fork build 10777, root unit — the only loader for this payload | Ternary-Bonsai-2-9B PQ2_0 + Q8_0 mmproj + rank-1 refusal adapter | 7771 |
 
 Payload identity, shape, eras, laws and rollback live in ONE page each:
 [[frank-archon]], [[frank-dragoon]], [[frank-zealot]]. `scripts/<service>.env`
@@ -156,15 +156,6 @@ Unit requirements:
   (`<host>/<svc>/quadlet/`), is installed by the deployer, and is covered by
   the quadlet test seam. The host-side unit is generated state; the repo file
   is the source of truth.
-- **Bind-source gate** — a unit whose `Volume=` source is a mount this host owns
-  (the entropy array, the metadata view) carries
-  `ExecStartPre=/home/dank/serverAppConfigs/scripts/wait-for-mount.sh <source>`.
-  Measured 2026-10-31: in a **rootless** unit `RequiresMountsFor=` is inert (the
-  user manager cannot order against the system's mount unit), and
-  `ConditionPathIsMountPoint=` is fail-*dead* — an unmet condition logs `skipped,
-  unmet condition check` with `NRestarts=0` and no start attempt ever follows.
-  Bind the array before it is mounted and the container sees the empty pre-mount
-  directory as truth; a media scan then deletes the library it cannot see.
 
 Before declaring a service deployed: `systemctl --user is-enabled <name>` →
 `enabled`, `is-active` → `active`, and the container answers its health check.
@@ -185,12 +176,11 @@ alertmanager.container`, loopback :9093) → host-side Signal relay
 (`scripts/signal-relay.py`, user unit, 192.168.0.143:18093 — the host LAN
 IP, the one bind a container can reach as `host.containers.internal`;
 iptables admits loopback, the host and the podman bridge subnet only) → signal-cli account 318311.
-The former structural target downs (HTML-scraped "probes", Gitea metrics off)
+Prometheus targets read down for structural reasons (HTML-scraped "probes",
-are retired as of 2026-10-21: HTTP liveness rides a blackbox exporter
+Gitea metrics off); the remedy is a blackbox exporter. `frank-zealot` was down for
-(`shared/blackbox/blackbox.yml`), Gitea serves `/metrics` from its quadlet, and
+a different reason until 2026-10-18: llama.cpp will not serve `/metrics` at all
-every Prometheus job reports up. `frank-zealot` was down for a different reason
+without `--metrics`. See
-until 2026-10-18: llama.cpp will not serve `/metrics` at all without
+`serverAppConfigs-docs/Infrastructure/Observability.md`.
-`--metrics`. See `serverAppConfigs-docs/Infrastructure/Observability.md`.
 
 ## Testing
 
@@ -302,8 +292,8 @@ means off or NIC dead; a merely wedged kernel usually still answers ARP.
 2. Bench against the service itself. No scratch ports on an LLM host — one
    process owns the card. Use the runtime's own harness (`llama-bench`; a
    live llama.cpp server also reports honest `timings` per request, including
-   `draft_n`/`draft_n_accepted` — but on frank-zealot's PrismML fork that object
+   `draft_n`/`draft_n_accepted` — but on frank-zealot's PrismML fork build
-   only reaches you on **`/v1/chat/completions`** (measured on build 10777): a greedy
+   10777 that object only reaches you on **`/v1/chat/completions`**: a greedy
    `ignore_eos` run on the raw `/completion` path there answers **500 "The
    model produced output that does not match the expected Content-only
    format"** (measured 2026-10-18). halogen has no `/completion` path at all,
@@ -429,17 +419,16 @@ disagrees with it is the bug.
   digest-pinned `ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84…`.
   Engine stdout (the boot ledger: weights, KV pool, clamp) goes to
   `/home/dank/logs/frank_dragoon.log`, NOT the journal.
-- Shape: `HALOGEN_CTX=262144` (the checkpoint's native window) is the
+- Shape: `HALOGEN_CTX=200704` is the **per-request ceiling** (a longer prompt
-  **per-request ceiling** (a longer prompt is a 400, never a truncation);
+  is a 400, never a truncation); `HALOGEN_KV_SLOTS=2` over ONE
-  `HALOGEN_KV_SLOTS=2` over ONE `HALOGEN_KV_POOL_POSITIONS=401408` pool —
+  `HALOGEN_KV_POOL_POSITIONS=401408` pool — pool positions buy concurrency,
-  pool positions buy concurrency, the per-request window never moves;
+  the per-request window never moves; `HALOGEN_SPEC_ADAPT=0` keeps the MTP
-  `HALOGEN_SPEC_ADAPT=0` keeps the MTP drafter always armed (the adaptive
+  drafter always armed (the adaptive default disarms it and halves decode);
-  default disarms it and halves decode); server sampler 1.0/0.95/20.
+  server sampler 1.0/0.95/20.
-- Harness contract: `models.yml` `contextWindow: 200000` — ~45k+ under the
+- Harness contract: `models.yml` `contextWindow: 155648` = ceiling − 45,056.
-  ceiling. The clamp is `min(45056, window − est − 4096)` and the chars/4
+  The clamp is `min(45056, window − est − 4096)` and the chars/4 estimate
-  estimate under-counts (trigger is 95 %), so a harness window at the ceiling
+  under-counts, so a harness window equal to the ceiling makes every long
-  makes every long request a guaranteed 400.
+  request a guaranteed 400. Reasoning arrives in `reasoning_content`; the
-  Reasoning arrives in `reasoning_content`; the
   template rejects `reasoning_effort` outside `xhigh|medium|low`; images are
   OpenAI `image_url` parts (probe ≥256 px); `response_format` unsupported;
   `/completion`, `/ping`, `/props`, `/tokenize` are 404.
@@ -448,16 +437,16 @@ disagrees with it is the bug.
 ### frank-zealot — llama.cpp (PrismML fork), RTX 3090, :7771
 
 - Owns: `scripts/frank-zealot.env`, `scripts/serve-frank-zealot.sh`,
-  `scripts/frank-zealot.service`; fork build `llama-prism-0244744` (build 12118)
+  `scripts/frank-zealot.service`; fork build `llama-prism-b10777` is the ONLY
-  is the ONLY loader — `llama-prism-b10777` stays on disk as its rollback (the payload carries the fork's custom PQ2_0 tensor type plus
+  loader (the payload carries the fork's custom PQ2_0 tensor type plus
   `prism.hadamard.*` dequant metadata — stock llama.cpp refuses it, and a
   loader ignoring that metadata dequantizes wrong); payload
   `Bonsai2-9B-MTP/…PQ2_0.gguf` + the publisher's **Q8_0** mmproj (the BF16
   tower can crash the server with concurrent image requests) + the rank-1
   refusal-direction adapter applied at load by `--lora-scaled …:1`. The
   adapter's rollback is `LORA_FILE=` (empty) in the env — one line, no rebuild
-  — and the fork BUILD is also the gate that lets it load: anything older than
+  — and build 10777 is also the gate that lets it load: older forks refuse it
-  b10777 refuses it with `unsupported prism.hadamard.version: 2`.
+  with `unsupported prism.hadamard.version: 2`.
 - Shape: `--ctx-size 602112 --parallel 3` = **three conversations at
   200,704 each**, `CACHE_TYPE_K=f16` + `CACHE_TYPE_V=q8_0` (asymmetric: 25,088
   B/token, 14,406 MiB of pool), batch 6144 / ubatch 1024,
@@ -750,13 +739,6 @@ linked runbooks.
   `/etc/default/grub`. It replaced `amd_iommu=off`, and the local A/B on byte-identical traffic
   says identity mode costs nothing, so the XDNA2 NPU returned for free.
   [[dankclaw-iommu-translation-off]]
-- **A deploy handler that only `start`s a quadlet no-ops an image bump.**
-  `systemctl --user start` on an already-active unit does nothing, so installing
-  a new digest under a running service keeps the OLD container serving while the
-  deploy, its health gate and the Playwright suite all pass — the authentik
-  handler did exactly that on 2026-10-30 (2026.8.3 → 2026.8.5 moved only the
-  outpost, the one handler that restarted). A pin change is applied by
-  `restart`, never `start`.
 - **Rootless Quadlet containers run with `--replace --rm`**: `podman logs` covers only the CURRENT
   instance; history across recreations lives in `journalctl --user -u <name>.service`. Read
   rootless storage WITHOUT sudo — it is per-user storage, so `sudo podman logs` finds nothing.
@@ -816,8 +798,6 @@ per-attempt page and no per-swap ledger anywhere else.
 | `frank-tts` — cloned-voice speech, Dankclaw | `serverAppConfigs-docs/Dankclaw/Frank TTS.md` |
 | Dankclaw kernel posture (`iommu=pt` since 2026-10-18) | `serverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md` |
 | Deployment flow | `serverAppConfigs-docs/Architecture/Deployment Flow.md` |
-| Movie-library relayout (Jellyfin format, Dankserver) | `serverAppConfigs-docs/Dankserver/Media Relayout.md` |
-| SSD-backed metadata view (Jellyfin writes, Plex reads, Dankserver) | `serverAppConfigs-docs/Dankserver/Media Metadata View.md` |
 
 There is no page for a retired endpoint and no change diary. A payload swap
 appends one row to the live endpoint's **Eras** table; when the endpoint itself
@@ -859,7 +839,5 @@ history.
 | Writing a doc | **One owner per fact** — edit the endpoint/service page; everywhere else links. Never restate a number. |
 | Benchmarking (only when ordered) | **Stop and mask the service first**, bench, unmask, restart, verify health. |
 | Deleting a file | **Move it to trash** — `.AGENTTRASH/` (in-repo) or `~/.AGENTTRASH/YYYYMMDD-topic`. Never `rm`. |
-| Relayout the movie library | **Census → plan → read the exceptions → `scripts/media-apply.py`** — renames only, journal before every move; never hand-rename, never copy. |
-| Making media metadata visible to both media servers | **Bind `/var/lib/media-meta/view`** — the overlay `scripts/media-view.sh` installs (array below, NVMe above). Never write the array; never delete through the view. **Not yet deployed on Dankserver: the live quadlets still bind the array read-only — see [[Media Metadata View]].** |
 | Tests exist | **Run them** — verify tests pass after every change. Do not commit failing tests. |
 | Real secrets | **Never commit** — host `.env` files; `.env.example` holds placeholders only. |

dankclaw/authentik/quadlet/authentik-outpost-ldap.container

@@ -23,7 +23,7 @@ Network=dankclaw_default
 # Image=ghcr.io/goauthentik/ldap:2026.8.3 (amd64 digest; podman 5.7.0 refuses
 # the tag's nested manifest list, so pin the single-platform digest).
 EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env
-Image=ghcr.io/goauthentik/ldap:2026.8.5@sha256:4c75bd27918418d2d6fbbfe4581bbd5a199fe38942d24559c4483edd64a1ea87
+Image=ghcr.io/goauthentik/ldap@sha256:2e7b259eb8c37faac916946ddf48ec681ee9d3a9f724fe8521bf161973f13cf9
 Environment=AUTHENTIK_HOST=https://auth.franksdank.cloud
 Environment=AUTHENTIK_INSECURE=false
 Environment=AUTHENTIK_TOKEN=${AUTHENTIK_LDAP_OUTPOST_TOKEN}

dankclaw/authentik/quadlet/authentik-outpost.container

@@ -20,7 +20,7 @@ Wants=authentik-server.service
 
 [Container]
 ContainerName=authentik-outpost
-Image=ghcr.io/goauthentik/server:2026.8.5@sha256:602227a86455d6772e3d16b7d852713c4f864f40df5df894abd1285bb53979a5
+Image=ghcr.io/goauthentik/server:2026.8.3
 Exec=worker
 Network=dankclaw_default
 EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env

dankclaw/authentik/quadlet/authentik-postgres.container

@@ -14,7 +14,7 @@ After=network.target
 
 [Container]
 ContainerName=authentik-postgres
-Image=docker.io/library/postgres:16-alpine@sha256:0cefaabd882e42bcb2a2f3dc56d3ce4770560ba62fd7f197f1a2e008fd5731ab
+Image=docker.io/library/postgres:16-alpine
 Network=dankclaw_default
 EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env
 Environment=POSTGRES_DB=authentik

dankclaw/authentik/quadlet/authentik-server.container

@@ -19,7 +19,7 @@ Wants=authentik-postgres.service
 
 [Container]
 ContainerName=authentik-server
-Image=ghcr.io/goauthentik/server:2026.8.5@sha256:602227a86455d6772e3d16b7d852713c4f864f40df5df894abd1285bb53979a5
+Image=ghcr.io/goauthentik/server:2026.8.3
 Exec=server
 Network=dankclaw_default
 EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env

dankclaw/authentik/quadlet/authentik-worker.container

@@ -16,7 +16,7 @@ Wants=authentik-server.service
 
 [Container]
 ContainerName=authentik-worker
-Image=ghcr.io/goauthentik/server:2026.8.5@sha256:602227a86455d6772e3d16b7d852713c4f864f40df5df894abd1285bb53979a5
+Image=ghcr.io/goauthentik/server:2026.8.3
 Exec=worker
 Network=dankclaw_default
 EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env

dankclaw/gitea/quadlet/gitea-postgres.container

@@ -15,7 +15,7 @@ After=network.target
 [Container]
 ContainerName=gitea-postgres
 Network=gitea.network
-Image=docker.io/library/postgres:16-alpine@sha256:0cefaabd882e42bcb2a2f3dc56d3ce4770560ba62fd7f197f1a2e008fd5731ab
+Image=docker.io/library/postgres:16-alpine
 EnvironmentFile=/home/dank/Containers/gitea/env
 Environment=POSTGRES_USER=gitea
 Environment=POSTGRES_PASSWORD=${GITEA_DB_PASSWORD}

dankclaw/gitea/quadlet/gitea-server.container

@@ -19,7 +19,7 @@ After=gitea-postgres.service network.target
 [Container]
 ContainerName=gitea-server
 Network=gitea.network
-Image=docker.io/gitea/gitea:latest@sha256:30777c91280d973fa02be48b1ade735bd6859e8f6f7af3b4444d519437852504
+Image=docker.io/gitea/gitea:latest
 EnvironmentFile=/home/dank/Containers/gitea/env
 Environment=DATABASE_TYPE=postgres
 Environment=DATABASE_HOST=gitea-postgres
@@ -29,13 +29,6 @@ Environment=DATABASE_PASSWD=${GITEA_DB_PASSWORD}
 Environment=DATABASE_PORT=5432
 Environment=USER_UID=1000
 Environment=USER_GID=1000
-# Prometheus scrapes /metrics over the published LAN port (job "gitea" in
-# shared/prometheus/prometheus.yml). Off, /metrics is a 404 and the target is
-# permanently red (the audit's "disabled metrics" class). 0.0.0.0 binds inside
-# the container; the only route in is this host's published 3000, and the
-# exposed surface is counters only — same posture as the LLM /metrics.
-Environment=GITEA__metrics__ENABLED=true
-Environment=GITEA__metrics__ENABLED_HOST=0.0.0.0
 PublishPort=0.0.0.0:3000:3000
 PublishPort=2222:22
 Volume=/home/dank/Containers/gitea/data:/data

dankclaw/hermes/quadlet/chrome-devtools-protocol.container

@@ -25,7 +25,7 @@ Description=Chrome DevTools Protocol daemon (headless-shell) for hermes
 [Container]
 ContainerName=chrome-devtools-protocol
 Network=host
-Image=docker.io/chromedp/headless-shell@sha256:7bee201478b2f6266aae01243740ee85c16281e32f42d3aed9fdf04f4eace7a1
+Image=docker.io/chromedp/headless-shell@sha256:2d349b544a1ea6b5b5fd7c0fe99215ff662339c57407ee2e8c0a11af93516b04
 Entrypoint=/headless-shell/headless-shell
 Exec=--no-sandbox --disable-gpu --use-gl=angle --use-angle=swiftshader --remote-debugging-address=127.0.0.1 --remote-debugging-port=9222
 ShmSize=1073741824

dankclaw/marreta/quadlet/marreta-browser.container

@@ -23,7 +23,7 @@ After=gluetun.service network.target
 [Container]
 ContainerName=marreta_browser
 Network=gluetun.container
-Image=docker.io/lightpanda/browser:nightly@sha256:e72730e364d1fbf352c1149f29ffa4b278f3b1a55ff0dec3262298ebe624ec7a
+Image=docker.io/lightpanda/browser:nightly
 
 [Service]
 TimeoutStartSec=300

dankclaw/marreta/quadlet/marreta.container

@@ -32,7 +32,7 @@ After=gluetun.service marreta-browser.service network.target
 [Container]
 ContainerName=marreta
 Network=gluetun.container
-Image=ghcr.io/manualdousuario/marreta:latest@sha256:30f2a34567b79b66da794b4b9423751bbbcd07ceff600d9f6a2d219e7e439362
+Image=ghcr.io/manualdousuario/marreta:latest
 # Relocate off SearXNG's 8080 inside the shared netns.
 Environment=NGINX_HTTP_PORT=8085
 Environment=APP_NAME=Marreta

dankclaw/observability/quadlet/alertmanager.container

@@ -33,7 +33,7 @@ Wants=network-online.target
 
 [Container]
 ContainerName=alertmanager
-Image=docker.io/prom/alertmanager:latest@sha256:39d8bb3966c694a124428a3a88fbcffd40bd069129ecd47c059f8a3f17c55f3b
+Image=docker.io/prom/alertmanager:latest
 Network=dankclaw_default
 User=0:0
 Exec=--config.file=/etc/alertmanager/alertmanager.yml --storage.path=/alertmanager

dankclaw/observability/quadlet/blackbox-exporter.container

@@ -1,56 +0,0 @@
-# Quadlet unit: blackbox exporter (rootless, host network, boot-persistent).
-#
-# Install path on dankclaw:
-#   ~/.config/containers/systemd/blackbox-exporter.container
-#
-# WHY Network=host. The probes it runs are (a) the host's own LAN IP
-# (192.168.0.143:8081 SearXNG, :3005 OpenWebUI — host-process/portmap binds a
-# bridge container cannot reach; netavark DNATs published ports only, see
-# Container Host Reachability in the vault) and (b) ComfyUI's published port
-# via 127.0.0.1 (rootless --network=host shares the real host netns, so the
-# 0.0.0.0:8188 publish answers on loopback). A bridge-networked prober could
-# reach neither class reliably.
-#
-# WHY the listener binds 127.0.0.1 + LAN. A bridge container CANNOT dial
-# its own host's LAN IP (netavark hairpin gap, measured 2026-10-21), but a
-# bridge container dialing the podman gateway 169.254.1.2 lands on the host
-# LOOPBACK — that is the scrape path, and it needs this exporter to be
-# LISTENING ON LOOPBACK (proved: 200 from the prometheus container to
-# http://169.254.1.2:9115/-/healthy with a loopback bind). The gateway
-# address itself is NOT bindable from the host netns — it exists only
-# inside each rootless netns; binding it dies "bind: cannot assign
-# requested address" (live 2026-10-21). The LAN bind stays for diagnostics.
-# No public DNS name, no guard chain: internal net only, per the exposure
-# policy. The listen flag is --web.listen-address and it is REPEATABLE, one
-# flag per bind; plain --listen-address does not exist and the exporter
-# exits in 100 ms with "unknown long flag" (live 2026-10-21).
-
-[Unit]
-Description=Blackbox exporter (HTTP probe prober)
-After=network-online.target
-
-[Container]
-Image=docker.io/prom/blackbox-exporter@sha256:ea1c7aa3ef3f307cd03e85f34abb604478ccb90b567fc690da0cd9776da76b13
-ContainerName=blackbox-exporter
-Network=host
-# The image's ENTRYPOINT is /bin/blackbox_exporter itself (proved live
-# 2026-10-21: `podman run IMAGE sh` dies "unexpected sh"), so Exec= carries
-# FLAGS ONLY — repeating the binary makes it a positional arg and kingpin
-# exits "unexpected /bin/blackbox_exporter".
-Exec=--config.file=/etc/blackbox_exporter/config.yml --web.listen-address=127.0.0.1:9115 --web.listen-address=192.168.0.143:9115
-Volume=/opt/blackbox/blackbox.yml:/etc/blackbox_exporter/config.yml:ro
-# Plain exec form like every sibling unit. Shell form (`/bin/sh -c "…"`)
-# is passed as one quoted token and quadlet then folds the following
-# --health-interval/--health-retries (and the image name) into the command
-# string — unit died twice that way, live 2026-10-21. wget only; this
-# busybox variant has no curl, and host-network wget answers on loopback.
-HealthCmd=wget -q -O /dev/null http://127.0.0.1:9115/-/healthy
-HealthInterval=30s
-HealthRetries=3
-
-[Service]
-Restart=always
-RestartSec=5
-
-[Install]
-WantedBy=default.target

dankclaw/observability/quadlet/cadvisor.container

@@ -1,56 +0,0 @@
-# Quadlet unit: cadvisor (rootless, boot-persistent) — DANKCLAW.
-#
-# Install path on dankclaw: ~/.config/containers/systemd/cadvisor.container
-# Unit name: cadvisor.service (container name: cadvisor)
-#
-# WHY THIS EXISTS. The app stack is ~34 rootless Podman containers and until
-# now nothing reported per-container CPU/memory — Grafana could only see the
-# host (node_exporter) and the LLM engines. cadvisor reads the host cgroup
-# tree and exports container_cpu_* / container_memory_* per container.
-#
-# THE LOAD-BEARING FLAG IS --cgroupns=host. Podman starts every container in a
-# PRIVATE cgroup namespace, so an exporter container sees only its OWN cgroup
-# subtree: cadvisor exported a single root series until this flag was added,
-# then it walked the whole tree (996 per-container series measured 2026-10-20).
-# The quadlet unit name is carried in the cgroup path — app.slice/<name>.service/
-# libpod-payload-<hex> — so Prometheus relabels that path into a `container`
-# label (shared/prometheus/prometheus.yml, cadvisor-dankclaw job) and no
-# libpod/podman socket is needed to name containers.
-#
-# BINDING. cadvisor has no per-interface listen flag (unlike node_exporter's
-# --web.listen-address), so it binds 0.0.0.0 INSIDE its own network namespace.
-# The bridge PublishPort is what keeps the unauthenticated endpoint off the
-# host's other interfaces: it publishes exactly loopback (host-local probes and
-# the deployer's health gate) and this host's LAN address (Prometheus, a bridge
-# container, reaches a host-published port at its LAN address — the same netavark
-# rule node-exporter relies on, only here the port really is published).
-#
-# It is rootless on purpose: dank owns the app containers' cgroups, so a
-# rootless cadvisor reads every one of them; root would buy nothing here.
-
-[Unit]
-Description=cAdvisor container metrics (Dankclaw)
-After=network-online.target
-Wants=network-online.target
-
-[Container]
-ContainerName=cadvisor
-Image=gcr.io/cadvisor/cadvisor:v0.49.1@sha256:3cde6faf0791ebf7b41d6f8ae7145466fed712ea6f252c935294d2608b1af388
-PodmanArgs=--pid=host --cgroupns=host
-PublishPort=127.0.0.1:8080:8080
-PublishPort=192.168.0.143:8080:8080
-Volume=/sys:/sys:ro
-Volume=/:/rootfs:ro
-Exec=--housekeeping_interval=30s
-HealthCmd=wget --spider -q http://localhost:8080/healthz
-HealthInterval=30s
-HealthTimeout=10s
-HealthRetries=3
-HealthStartPeriod=40s
-
-[Service]
-Restart=always
-RestartSec=10
-
-[Install]
-WantedBy=default.target

dankclaw/observability/quadlet/grafana.container

@@ -34,7 +34,7 @@ Wants=network-online.target prometheus.service
 
 [Container]
 ContainerName=grafana
-Image=docker.io/grafana/grafana:latest@sha256:488984b716c0862639f91a698adbe2862677a5a07bad42da5f03f3030883b205
+Image=docker.io/grafana/grafana:latest
 Network=dankclaw_default
 User=0:0
 PublishPort=127.0.0.1:3002:3000

dankclaw/observability/quadlet/node-exporter.container

@@ -33,7 +33,7 @@ Wants=network-online.target
 
 [Container]
 ContainerName=node-exporter
-Image=docker.io/prom/node-exporter:latest@sha256:1b4e4438faca4dd7e001dd445d161a4a2091b0fededa84093b3a8dfeae1f1be0
+Image=docker.io/prom/node-exporter:latest
 Network=host
 PodmanArgs=--pid=host
 Exec=--path.procfs=/host/proc --path.sysfs=/host/sys --path.rootfs=/rootfs --web.listen-address=127.0.0.1:9100 --web.listen-address=192.168.0.143:9100

dankclaw/observability/quadlet/prometheus.container

@@ -43,16 +43,8 @@ Wants=network-online.target
 
 [Container]
 ContainerName=prometheus
-Image=docker.io/prom/prometheus:latest@sha256:fa3302279710be2f21a8301ec17a8b4f2301fd829bd113839b3b6b02b6f191a2
+Image=docker.io/prom/prometheus:latest
 Network=dankclaw_default
-# Same-host scrape targets are dialed at host.containers.internal (the podman
-# gateway): a bridge container cannot dial its own host's LAN IP (netavark
-# hairpin gap, measured 2026-10-21), and traffic to the gateway lands on host
-# loopback / published ports (cadvisor/gpu jobs and the blackbox scrape all
-# ride it). The name resolves natively — NO HostAddr key: quadlet 5.7.0 calls
-# it unsupported and the WHOLE user quadlet batch then fails to generate,
-# silently orphaning every other unit (live 2026-10-21: prometheus.service
-# vanished while its container kept running as an orphan).
 User=0:0
 Exec=--config.file=/etc/prometheus/prometheus.yml --storage.tsdb.path=/prometheus --storage.tsdb.retention.time=30d --web.enable-lifecycle
 PublishPort=127.0.0.1:9090:9090

dankclaw/open-webui/quadlet/open-webui.container

@@ -27,7 +27,7 @@ After=network.target
 [Container]
 ContainerName=open-webui
 Network=open-webui.network
-Image=ghcr.io/open-webui/open-webui:main@sha256:0b399a8ba34558e181d316750455f2a95376a38cd60a61b9c942e138898944bd
+Image=ghcr.io/open-webui/open-webui:main
 PublishPort=3005:8080
 Environment=OPENAI_API_BASE_URL=http://192.168.0.143:7770
 Environment=ANONYMIZED_TELEMETRY=False

dankclaw/pihole/quadlet/pihole.container

@@ -24,7 +24,7 @@ Wants=network-online.target
 
 [Container]
 ContainerName=pihole
-Image=docker.io/pihole/pihole:latest@sha256:d34134716fc32038b052a8674c7c6879e0ff21f0e6d8af345166fffa2c27c113
+Image=docker.io/pihole/pihole:latest
 Network=slirp4netns
 PublishPort=0.0.0.0:53:53/udp
 PublishPort=0.0.0.0:53:53/tcp

dankclaw/searxng/quadlet/gluetun.container

@@ -16,7 +16,7 @@ After=searxng-network.service network.target
 [Container]
 ContainerName=gluetun
 Network=searxng.network
-Image=docker.io/qmcgaw/gluetun:latest@sha256:4af0c804003481e100180e1f8d4d5e9c48163fedc0f88d061881b615aef9d183
+Image=docker.io/qmcgaw/gluetun:latest
 AddCapability=NET_ADMIN
 AddDevice=/dev/net/tun:/dev/net/tun
 Environment=VPN_SERVICE_PROVIDER=${VPN_SERVICE_PROVIDER}

dankclaw/searxng/quadlet/searxng-valkey.container

@@ -16,7 +16,7 @@ After=searxng-network.service network.target
 ContainerName=searxng-valkey
 Network=searxng.network
 NetworkAlias=valkey
-Image=docker.io/valkey/valkey:9-alpine@sha256:bf09d58e96d6b4524a15396b65b242bbe18beebbcc15a04d8ee75ddac62fae0b
+Image=docker.io/valkey/valkey:9-alpine
 Volume=/opt/searxng/valkey:/data
 
 [Service]

dankclaw/searxng/quadlet/searxng.container

@@ -16,7 +16,7 @@ After=gluetun.service searxng-valkey.service network.target
 [Container]
 ContainerName=searxng
 Network=gluetun.container
-Image=ghcr.io/searxng/searxng:latest@sha256:f4aa660c54d062dedb268be84e821ea24e39f48c7a496af8dd02cc9eedb93847
+Image=ghcr.io/searxng/searxng:latest
 Environment=SEARXNG_SECRET=${SEARXNG_SECRET}
 Environment=SEARXNG_BASE_URL=${SEARXNG_BASE_URL}
 Volume=/opt/searxng/config:/etc/searxng

dankclaw/seerr/quadlet/seerr.container

@@ -29,7 +29,7 @@ Wants=network-online.target
 
 [Container]
 ContainerName=seerr
-Image=ghcr.io/seerr-team/seerr:v3.5.1@sha256:d8fab675b55ad293ded98fd71efcfd46054cbad9746534ae1cc4794a88c0b3be
+Image=ghcr.io/seerr-team/seerr:v3.4.1
 Network=dankclaw_default
 PublishPort=127.0.0.1:5055:5055
 Volume=/home/dank/Containers/seerr/data:/app/config

dankserver/.AGENTTRASH/20260916-vllm-radiance/affinity-proxy.py

@@ -0,0 +1,156 @@
+#!/usr/bin/env python3
+"""HTTP front door for the frank-medium single-GPU replicas.
+
+Why two replicas instead of TP=2: one vLLM process spanning both R9700s needs
+RCCL collectives, and RCCL's kernels require PCIe atomics on every
+participating GPU. The second card sits behind chipset bridges advertising
+`AtomicOpsCap: Routing-`, which no software can enable (see the runbook), so
+no collective can launch on it. Two single-GPU replicas use both cards; this
+service keeps the fleet contract of one endpoint on :7770, streaming included.
+
+Routing decisions live in routing.py — spread single-turn requests, pin
+continuations to the replica whose prefix cache holds their context. This file
+only moves bytes: parse enough of the request to route it, forward it verbatim,
+stream the answer back, and report replica health on /health.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import os
+from contextlib import suppress
+from aiohttp import ClientSession, ClientTimeout, web
+
+import routing
+
+PORT = int(os.environ.get("PORT", "7770"))
+HEALTH_TTL = float(os.environ.get("HEALTH_TTL", "10"))
+# Hop-by-hop headers must not be forwarded (RFC 9110 §7.6.1) — forwarding
+# transfer-encoding or content-length of a rewritten body breaks clients.
+HOP_BY_HOP = {
+    "host", "content-length", "transfer-encoding", "connection",
+    "keep-alive", "proxy-authenticate", "proxy-authorization", "te",
+    "trailers", "upgrade",
+}
+
+UPSTREAMS = routing.UPSTREAMS
+# Replica health, refreshed by the watcher. Module state rather than aiohttp app
+# state: the application is frozen once the site is up.
+_UP: list[bool] = [True] * len(UPSTREAMS)
+
+
+async def health(session: ClientSession) -> web.Response:
+    results = await asyncio.gather(
+        *(session.get(u + "/health", timeout=ClientTimeout(total=5)) for u in UPSTREAMS),
+        return_exceptions=True,
+    )
+    lines, up = [], 0
+    for url, res in zip(UPSTREAMS, results):
+        if isinstance(res, Exception) or res.status != 200:
+            lines.append(f"{url} DOWN")
+        else:
+            up += 1
+            lines.append(f"{url} UP")
+    return web.Response(status=200 if up else 503, text="\n".join(lines) + "\n")
+
+
+async def watch_health() -> None:
+    """Refresh the replica up/down table so routing never targets a dead one.
+
+    One HTTP request per replica per interval, in exchange for never handing a
+    client a 502 after a restart.
+    """
+    global _UP
+    session = ClientSession()
+    try:
+        while True:
+            res = await asyncio.gather(
+                *(session.get(u + "/health", timeout=ClientTimeout(total=5)) for u in UPSTREAMS),
+                return_exceptions=True,
+            )
+            _UP = [not isinstance(r, Exception) and r.status == 200 for r in res]
+            await asyncio.sleep(HEALTH_TTL)
+    finally:
+        await session.close()
+
+
+async def proxy(request: web.Request) -> web.StreamResponse:
+    session: ClientSession = request.app["session"]
+    if request.path == "/health":
+        return await health(session)
+
+    body = await request.read()
+    headers = {k: v for k, v in request.headers.items() if k.lower() not in HOP_BY_HOP}
+
+    # Fail over before anything is written to the client. A replica that
+    # restarts is invisible to the health watcher for up to HEALTH_TTL, and a
+    # deploy restarts both replicas — without this retry a 10 s window of
+    # requests would 502 on a service that has a live card the whole time.
+    # vLLM's OpenAI endpoints are stateless per request, so re-sending a
+    # request that never reached an engine is safe; a request that failed
+    # mid-stream is not retried (that path is below).
+    tried: set[int] = set()
+    upstream = None
+    last_error = "no healthy frank-medium replica"
+    while len(tried) < len(UPSTREAMS):
+        idx = routing.route(body, request.remote, _UP)
+        if idx < 0 or idx in tried:
+            break
+        tried.add(idx)
+        target = UPSTREAMS[idx] + request.path_qs
+        try:
+            upstream = await session.request(
+                request.method, target, headers=headers, data=body or None,
+                timeout=ClientTimeout(total=None, sock_connect=10, sock_read=3600),
+            )
+            break
+        except Exception as exc:
+            # Demote at once: the watcher will confirm, but every request until
+            # then should skip this replica rather than pay the same timeout.
+            # Logged because a silent failover hides a card that is down.
+            _UP[idx] = False
+            last_error = f"{target} unreachable: {exc}"
+            print(f"proxy: failover — {target} unreachable ({exc}); retrying "
+                  f"another replica", flush=True)
+    if upstream is None:
+        # 503 when no replica was even reachable through the routing table,
+        # 502 when replicas were tried and all of them failed.
+        status = 502 if tried else 503
+        return web.Response(status=status, text=f"proxy: {last_error}\n")
+
+    out = web.StreamResponse(status=upstream.status, reason=upstream.reason)
+    for k, v in upstream.headers.items():
+        if k.lower() not in HOP_BY_HOP:
+            out.headers[k] = v
+    await out.prepare(request)
+    try:
+        async for chunk in upstream.content.iter_any():
+            await out.write(chunk)
+    except Exception:
+        # The client went away mid-stream (an aborted generation). Nothing to
+        # report: the engine sees its own cancellation.
+        pass
+    finally:
+        upstream.release()
+    with suppress(Exception):
+        await out.write_eof()
+    return out
+
+
+async def main() -> None:
+    app = web.Application(client_max_size=1024 ** 3)
+    app["session"] = ClientSession()
+    app.router.add_route("*", "/{tail:.*}", proxy)
+    runner = web.AppRunner(app)
+    await runner.setup()
+    await web.TCPSite(runner, "0.0.0.0", PORT).start()
+    print(f"proxy: :{PORT} -> {', '.join(UPSTREAMS)} routing={routing.ROUTING} "
+          f"key={routing.AFFINITY_BYTES}B known_max={routing.KNOWN_MAX}", flush=True)
+    watcher = asyncio.create_task(watch_health())
+    with suppress(asyncio.CancelledError):
+        await asyncio.gather(watcher)
+
+
+if __name__ == "__main__":
+    with suppress(KeyboardInterrupt):
+        asyncio.run(main())

dankserver/.AGENTTRASH/20260916-vllm-radiance/frank-medium-a.container

@@ -0,0 +1,98 @@
+# Quadlet unit: frank-medium replica A (rootless, boot-persistent).
+#
+# Install path on dankserver: ~/.config/containers/systemd/frank-medium-a.container
+# Unit name: frank-medium-a.service (container name: frank-medium-a)
+#
+# WHY TWO REPLICAS INSTEAD OF TP=2. The intended shape for frank-medium is one
+# tensor-parallel process across both R9700s (see frank-medium.container, kept
+# as the target). That shape cannot run on this host: RCCL's collective kernels
+# carry a hidden hostcall-buffer parameter, and the ROCr runtime refuses to
+# dispatch them on a device without PCIe atomics ("Pcie atomics not enabled,
+# hostcall not supported" -> AQL dispatch failed -> hipErrorIllegalState). The
+# second R9700 sits behind the chipset bridges 05:00.0/06:09.0, which advertise
+# `AtomicOpsCap: Routing-` — a read-only capability, so no software can enable
+# atomics on that path; the amdgpu driver's pci_enable_atomic_ops_to_root()
+# therefore fails for that GPU and KFD marks the CPU<->GPU2 link NO_ATOMICS.
+# The first R9700 sits on CPU root port 00:01.1 (Routing+) and does have
+# atomics. Result: every collective that touches GPU 2 dies at launch.
+# Two independent single-GPU replicas use both cards instead; the proxy unit
+# keeps the single :7770 endpoint. Full evidence: the frank-medium runbook.
+#
+# SHAPE. vLLM binds 0.0.0.0:7771 on the host network directly; no PublishPort.
+# MAXLEN is 114688, not the TP=2 deployment's 262144: one card carries the
+# whole model (~20 GiB of weights + drafter), leaving ~5.2 GiB of KV, and
+# 131072 does not fit (measured: needs 5.58 GiB). KV_MEM=0 lets vLLM profile
+# this shape instead of using the 2x7551-32624 pin, which is only valid at
+# TP=2/262144.
+#
+# DEVICES. /dev/kfd + /dev/dri; HIP_VISIBLE_DEVICES=0 (the first R9700). The
+# 2 GiB Raphael iGPU enumerates as index 2 and is excluded by the pin.
+# Only HIP_VISIBLE_DEVICES is set, never ROCR_VISIBLE_DEVICES: ROCR filters
+# first and HIP indexes into the filtered list, so a single-valued pair
+# (ROCR=1,HIP=1) leaves an empty device set.
+#
+# DO NOT name an environment variable TEMP, HOST or GPU_MAX_HEAP_SIZE: the
+# HIP runtime reads bare TEMP for its JIT cache path (2026-08-13 incident).
+[Unit]
+Description=frank-medium replica A — vllm-radiance MXFP4 Qwen3.8-27B on R9700 #1
+After=network-online.target
+
+[Container]
+ContainerName=frank-medium-a
+Image=localhost/radiance-vllm:0.9.3
+AddDevice=/dev/kfd
+AddDevice=/dev/dri
+GroupAdd=keep-groups
+# The upstream launcher's exact podman posture (rootless).
+PodmanArgs=--privileged --ipc=host --security-opt seccomp=unconfined --cap-add SYS_PTRACE --network=host
+Environment=HIP_VISIBLE_DEVICES=0
+Environment=SNAP=/models/Qwen3.8-27B-Uncensored-MXFP4-awq
+Environment=DRAFTER=/models/Qwen3.8-27B-DFlash2-FP8
+Environment=CHAT_TEMPLATE=/patches/qwen-fixed-v22.3.jinja
+Environment=SERVED_NAMES=frank-medium
+Environment=PORT=7771
+Environment=TP=1
+Environment=MAXSEQS=4
+Environment=CHUNK=8192
+Environment=MAXLEN=114688
+Environment=GPU_UTIL=0.98
+Environment=KV_MEM=0
+Environment=SPEC_METHOD=dflash
+Environment=SPEC=7
+# Checkpoints (rw: nothing downloads at runtime, but vLLM mmaps the shards).
+Volume=/home/dank/models:/models
+# Tokenizer files ride the HF cache; HF_HUB_OFFLINE=1 is set in the entrypoint.
+Volume=/home/dank/.cache/huggingface:/root/.cache/huggingface
+# Compile cache. Shared with the other replica and with the TP=2 target: the
+# entries are content-addressed, so shapes simply add subdirectories.
+Volume=/home/dank/.radiance-cache-w4a8-093-gdnm-nqft-fp8s-gnq:/cache
+# The pinned radiance clone: patches applied at every container start.
+Volume=/home/dank/GitPackages/radiance-vllm-mxfp4:/patches:z
+# The patched libr4d (pin b9e42ab + repo extras, key b9e42ab-rx6). The image's
+# shipped r4d.so predates the GDN overflow fix and NaNs this model.
+Volume=/home/dank/.cache/radiance-libr4d/b9e42ab-rx6:/r4d:z
+# Entrypoint + healthcheck from this checkout, mounted read-only.
+Volume=/home/dank/serverAppConfigs/dankserver/frank-medium/radiance-entrypoint.sh:/usr/local/bin/frank-medium-entrypoint.sh:ro
+Volume=/home/dank/serverAppConfigs/dankserver/frank-medium/frank-medium-healthcheck.py:/usr/local/bin/frank-medium-healthcheck.py:ro
+# The entrypoint must be the container command; the image's own entrypoint
+# (which the patched script execs at the end) must not run unpatched.
+PodmanArgs=--entrypoint /usr/local/bin/frank-medium-entrypoint.sh
+# 200 only once the engine serves; during first-start compilation the
+# container is legitimately unhealthy. HealthCmd is split on spaces into an
+# argv array by the podman 5.x v1 generator, hence the file-based probe.
+HealthCmd=python3 /usr/local/bin/frank-medium-healthcheck.py
+HealthInterval=60s
+HealthTimeout=30s
+HealthRetries=3
+HealthStartPeriod=1800s
+Pull=never
+
+[Service]
+# First start compiles Triton/inductor kernels (several minutes) before the
+# engine loads ~20 GiB of weights.
+TimeoutStartSec=1800
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=default.target

dankserver/.AGENTTRASH/20260916-vllm-radiance/frank-medium-b.container

@@ -0,0 +1,98 @@
+# Quadlet unit: frank-medium replica B (rootless, boot-persistent).
+#
+# Install path on dankserver: ~/.config/containers/systemd/frank-medium-b.container
+# Unit name: frank-medium-b.service (container name: frank-medium-a)
+#
+# WHY TWO REPLICAS INSTEAD OF TP=2. The intended shape for frank-medium is one
+# tensor-parallel process across both R9700s (see frank-medium.container, kept
+# as the target). That shape cannot run on this host: RCCL's collective kernels
+# carry a hidden hostcall-buffer parameter, and the ROCr runtime refuses to
+# dispatch them on a device without PCIe atomics ("Pcie atomics not enabled,
+# hostcall not supported" -> AQL dispatch failed -> hipErrorIllegalState). The
+# second R9700 sits behind the chipset bridges 05:00.0/06:09.0, which advertise
+# `AtomicOpsCap: Routing-` — a read-only capability, so no software can enable
+# atomics on that path; the amdgpu driver's pci_enable_atomic_ops_to_root()
+# therefore fails for that GPU and KFD marks the CPU<->GPU2 link NO_ATOMICS.
+# The first R9700 sits on CPU root port 00:01.1 (Routing+) and does have
+# atomics. Result: every collective that touches GPU 2 dies at launch.
+# Two independent single-GPU replicas use both cards instead; the proxy unit
+# keeps the single :7770 endpoint. Full evidence: the frank-medium runbook.
+#
+# SHAPE. vLLM binds 0.0.0.0:7772 on the host network directly; no PublishPort.
+# MAXLEN is 114688, not the TP=2 deployment's 262144: one card carries the
+# whole model (~20 GiB of weights + drafter), leaving ~5.2 GiB of KV, and
+# 131072 does not fit (measured: needs 5.58 GiB). KV_MEM=0 lets vLLM profile
+# this shape instead of using the 2x7551-32624 pin, which is only valid at
+# TP=2/262144.
+#
+# DEVICES. /dev/kfd + /dev/dri; HIP_VISIBLE_DEVICES=1 (the second R9700). The
+# 2 GiB Raphael iGPU enumerates as index 2 and is excluded by the pin.
+# Only HIP_VISIBLE_DEVICES is set, never ROCR_VISIBLE_DEVICES: ROCR filters
+# first and HIP indexes into the filtered list, so a single-valued pair
+# (ROCR=1,HIP=1) leaves an empty device set.
+#
+# DO NOT name an environment variable TEMP, HOST or GPU_MAX_HEAP_SIZE: the
+# HIP runtime reads bare TEMP for its JIT cache path (2026-08-13 incident).
+[Unit]
+Description=frank-medium replica B — vllm-radiance MXFP4 Qwen3.8-27B on R9700 #2
+After=network-online.target
+
+[Container]
+ContainerName=frank-medium-b
+Image=localhost/radiance-vllm:0.9.3
+AddDevice=/dev/kfd
+AddDevice=/dev/dri
+GroupAdd=keep-groups
+# The upstream launcher's exact podman posture (rootless).
+PodmanArgs=--privileged --ipc=host --security-opt seccomp=unconfined --cap-add SYS_PTRACE --network=host
+Environment=HIP_VISIBLE_DEVICES=1
+Environment=SNAP=/models/Qwen3.8-27B-Uncensored-MXFP4-awq
+Environment=DRAFTER=/models/Qwen3.8-27B-DFlash2-FP8
+Environment=CHAT_TEMPLATE=/patches/qwen-fixed-v22.3.jinja
+Environment=SERVED_NAMES=frank-medium
+Environment=PORT=7772
+Environment=TP=1
+Environment=MAXSEQS=4
+Environment=CHUNK=8192
+Environment=MAXLEN=114688
+Environment=GPU_UTIL=0.98
+Environment=KV_MEM=0
+Environment=SPEC_METHOD=dflash
+Environment=SPEC=7
+# Checkpoints (rw: nothing downloads at runtime, but vLLM mmaps the shards).
+Volume=/home/dank/models:/models
+# Tokenizer files ride the HF cache; HF_HUB_OFFLINE=1 is set in the entrypoint.
+Volume=/home/dank/.cache/huggingface:/root/.cache/huggingface
+# Compile cache. Shared with the other replica and with the TP=2 target: the
+# entries are content-addressed, so shapes simply add subdirectories.
+Volume=/home/dank/.radiance-cache-w4a8-093-gdnm-nqft-fp8s-gnq:/cache
+# The pinned radiance clone: patches applied at every container start.
+Volume=/home/dank/GitPackages/radiance-vllm-mxfp4:/patches:z
+# The patched libr4d (pin b9e42ab + repo extras, key b9e42ab-rx6). The image's
+# shipped r4d.so predates the GDN overflow fix and NaNs this model.
+Volume=/home/dank/.cache/radiance-libr4d/b9e42ab-rx6:/r4d:z
+# Entrypoint + healthcheck from this checkout, mounted read-only.
+Volume=/home/dank/serverAppConfigs/dankserver/frank-medium/radiance-entrypoint.sh:/usr/local/bin/frank-medium-entrypoint.sh:ro
+Volume=/home/dank/serverAppConfigs/dankserver/frank-medium/frank-medium-healthcheck.py:/usr/local/bin/frank-medium-healthcheck.py:ro
+# The entrypoint must be the container command; the image's own entrypoint
+# (which the patched script execs at the end) must not run unpatched.
+PodmanArgs=--entrypoint /usr/local/bin/frank-medium-entrypoint.sh
+# 200 only once the engine serves; during first-start compilation the
+# container is legitimately unhealthy. HealthCmd is split on spaces into an
+# argv array by the podman 5.x v1 generator, hence the file-based probe.
+HealthCmd=python3 /usr/local/bin/frank-medium-healthcheck.py
+HealthInterval=60s
+HealthTimeout=30s
+HealthRetries=3
+HealthStartPeriod=1800s
+Pull=never
+
+[Service]
+# First start compiles Triton/inductor kernels (several minutes) before the
+# engine loads ~20 GiB of weights.
+TimeoutStartSec=1800
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=default.target

dankserver/.AGENTTRASH/20260916-vllm-radiance/frank-medium-proxy.container

@@ -0,0 +1,61 @@
+# Quadlet unit: frank-medium proxy (rootless, boot-persistent).
+#
+# Install path on dankserver: ~/.config/containers/systemd/frank-medium-proxy.container
+# Unit name: frank-medium-proxy.service (container name: frank-medium-proxy)
+#
+# WHAT IT IS. A prefix-affinity reverse proxy in front of the two single-GPU
+# frank-medium replicas (:7771 on R9700 #1, :7772 on R9700 #2). It preserves
+# the fleet contract: one endpoint on host port 7770 answering as the served
+# model name frank-medium, OpenAI /v1, streaming included.
+#
+# WHY IT EXISTS. TP=2 — one vLLM process spanning both cards — is impossible
+# on this host (see frank-medium-a.container and the runbook: RCCL's kernels
+# need PCIe atomics, and the second card's chipset path advertises
+# AtomicOpsCap: Routing-). Two replicas are how both cards get used.
+#
+# ROUTING. Requests are keyed on a hash of their leading 4 KiB of prompt text,
+# so a conversation family — an agent loop re-sending the same system prompt,
+# tool list and file context every turn — keeps landing on the same replica,
+# where --enable-prefix-caching has that prefix warm. Plain round-robin threw
+# half of those cache hits away. A replica that is down is skipped, and
+# ROUTING=roundrobin restores the old behaviour for A/B measurement. /health
+# answers 200 while at least one replica is up and names the ones that are
+# down. The proxy runs on host networking so it can bind 7770 and reach the
+# replicas on loopback.
+#
+# The script is a few dozen lines of aiohttp, mounted read-only out of
+# /home/dank/serverAppConfigs (deploy.sh pulls that checkout before dispatch).
+# It reuses the same image as the replicas: aiohttp is already there and no
+# extra image has to be pulled on this host.
+[Unit]
+Description=frank-medium proxy — prefix-affinity in front of the two single-GPU replicas
+After=network-online.target
+Wants=frank-medium-a.service frank-medium-b.service
+After=frank-medium-a.service frank-medium-b.service
+
+[Container]
+ContainerName=frank-medium-proxy
+Image=localhost/radiance-vllm:0.9.3
+PodmanArgs=--network=host
+Environment=PORT=7770
+Environment=UPSTREAMS=http://127.0.0.1:7771,http://127.0.0.1:7772
+# The proxy is two files: routing.py holds the replica-selection policy, the
+# server holds the HTTP plumbing. Both are mounted because the server imports
+# the policy by name from its own directory (/usr/local/bin is sys.path[0]).
+Volume=/home/dank/serverAppConfigs/dankserver/frank-medium/proxy/routing.py:/usr/local/bin/routing.py:ro
+Volume=/home/dank/serverAppConfigs/dankserver/frank-medium/proxy/affinity-proxy.py:/usr/local/bin/affinity-proxy.py:ro
+Volume=/home/dank/serverAppConfigs/dankserver/frank-medium/frank-medium-healthcheck.py:/usr/local/bin/frank-medium-healthcheck.py:ro
+PodmanArgs=--entrypoint /usr/local/bin/affinity-proxy.py
+HealthCmd=python3 /usr/local/bin/frank-medium-healthcheck.py
+HealthInterval=60s
+HealthTimeout=30s
+HealthRetries=3
+HealthStartPeriod=60s
+Pull=never
+
+[Service]
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=default.target

dankserver/.AGENTTRASH/20260916-vllm-radiance/routing.py

@@ -0,0 +1,129 @@
+#!/usr/bin/env python3
+"""Routing policy for the frank-medium proxy: which replica serves a request.
+
+Kept apart from the HTTP plumbing in affinity-proxy.py so the decisions can be
+tested without aiohttp, a network or a GPU — the first version of these rules
+shipped with a bug that only appeared on a continuation request, and a test
+that loads this module catches that class of mistake directly.
+
+Two cards, two behaviours, and the workload decides which is right:
+
+* A **single-turn** request is one member of a batch (a benchmark run, a burst
+  of parallel subagents). Spreading those over both replicas lets both cards
+  prefill at once; measured on this host, a 16-request burst of 15k-token
+  prompts finishes in 18.6 s spread versus 30.1 s pinned.
+* A **continuation** re-sends a prefix the replica has already prefilled. Pinned
+  to that replica the turn costs a cache lookup; spread, half the turns pay a
+  cold prefill again (measured: 1096 ms versus 2676 ms mean warm-turn TTFT on
+  90k-token contexts).
+
+ROUTING picks the strategy; the default `adaptive` applies both rules above.
+`affinity` and `roundrobin` exist so the choice can be re-measured, and are not
+production settings.
+"""
+
+from __future__ import annotations
+
+import collections
+import hashlib
+import itertools
+import json
+import os
+
+UPSTREAMS = [u.strip() for u in os.environ.get(
+    "UPSTREAMS", "http://127.0.0.1:7771,http://127.0.0.1:7772").split(",") if u.strip()]
+ROUTING = os.environ.get("ROUTING", "adaptive").strip().lower()
+# Leading bytes of prompt text that identify a conversation's shared prefix.
+# 4 KiB covers a system prompt plus the start of the first user turn, which is
+# where agent loops keep the text they resend every turn.
+AFFINITY_BYTES = int(os.environ.get("AFFINITY_BYTES", "4096"))
+# Prefixes remembered for pinning. Bounded so a long-lived proxy cannot grow
+# without limit; 4096 conversations is far beyond what this fleet runs at once.
+KNOWN_MAX = int(os.environ.get("KNOWN_MAX", "4096"))
+
+_counter = itertools.count()
+# digest -> replica index, insertion-ordered for O(1) LRU eviction. A prefix is
+# remembered as soon as any request carries it; only a continuation is pinned
+# there, because only a continuation can profit from the cache entry.
+_known: "collections.OrderedDict[bytes, int]" = collections.OrderedDict()
+
+
+def affinity_key(body: bytes, remote: str | None) -> tuple[bytes, bool]:
+    """Key a request by its shared prefix, and report whether it continues one.
+
+    Chat and completions bodies both carry their prompt text in JSON, so the
+    leading bytes of that text are the prefix; a body we cannot parse (or an
+    endpoint with no prompt, e.g. /v1/models) falls back to the client address,
+    which still beats nothing for a single-client loop.
+    """
+    fallback = (remote or "anonymous").encode()
+    try:
+        payload = json.loads(body)
+    except Exception:
+        return fallback, False
+
+    text = ""
+    continuation = False
+    if isinstance(payload, dict):
+        if isinstance(payload.get("prompt"), str):
+            text = payload["prompt"]
+        elif isinstance(payload.get("messages"), list):
+            continuation = len(payload["messages"]) > 1
+            parts = []
+            for msg in payload["messages"]:
+                if isinstance(msg, dict):
+                    content = msg.get("content")
+                    if isinstance(content, str):
+                        parts.append(content)
+                    elif isinstance(content, list):  # multimodal content blocks
+                        parts.extend(
+                            blk.get("text", "") for blk in content
+                            if isinstance(blk, dict) and isinstance(blk.get("text"), str)
+                        )
+            text = "\n".join(parts)
+    if not text:
+        return fallback, continuation
+    return text[:AFFINITY_BYTES].encode("utf-8", "replace"), continuation
+
+
+def pick(key: bytes, continuation: bool, up: list[bool]) -> int:
+    """Replica for a request, or -1 when none is available.
+
+    Down replicas are never selected — a rollout must not send traffic to an
+    engine that is still compiling its graphs — and a pin whose replica is down
+    is re-established on a live one rather than kept pointing at a corpse.
+    """
+    digest = hashlib.sha1(key).digest()
+
+    if ROUTING == "roundrobin":
+        start = next(_counter) % len(UPSTREAMS)
+    elif ROUTING == "adaptive":
+        entry = _known.get(digest)
+        if continuation and entry is not None and up[entry]:
+            _known.move_to_end(digest)
+            return entry
+        # Anything that is not a continuation spreads by counter — including a
+        # batch of requests that happen to share one prefix. Hashing the prefix
+        # would send every member of such a batch to whichever card the hash
+        # names (measured: 29.8 s for a 16-request burst, against 18.6 s when
+        # spread). The counter is only advanced by these requests, so batch
+        # members alternate across the cards.
+        start = next(_counter) % len(UPSTREAMS)
+    else:  # affinity
+        start = int.from_bytes(digest[:8], "big") % len(UPSTREAMS)
+
+    for offset in range(len(UPSTREAMS)):
+        idx = (start + offset) % len(UPSTREAMS)
+        if up[idx]:
+            if ROUTING == "adaptive":
+                _known[digest] = idx
+                _known.move_to_end(digest)
+                if len(_known) > KNOWN_MAX:
+                    _known.popitem(last=False)
+            return idx
+    return -1
+
+
+def route(body: bytes, remote: str | None, up: list[bool]) -> int:
+    """Convenience wrapper: decode the request body and choose a replica."""
+    return pick(*affinity_key(body, remote), up)

dankserver/calibre-server/quadlet/calibre-server.container

@@ -43,7 +43,7 @@ After=network.target
 
 [Container]
 ContainerName=calibre-server
-Image=lscr.io/linuxserver/calibre:9.17.0@sha256:b198fc03a6abc6be7e251a9958e50e74634b00e447c7b25e92c191c8077ba378
+Image=lscr.io/linuxserver/calibre:9.15.0
 Network=pasta
 EnvironmentFile=/home/dank/Containers/calibre-server/env
 Environment=PUID=1000

dankserver/calibre-web/quadlet/calibre-web.container

@@ -16,7 +16,7 @@ After=network.target
 
 [Container]
 ContainerName=calibre-web
-Image=lscr.io/linuxserver/calibre-web:0.6.27-ls407@sha256:470b4ed9a7d6ea1475fef17dbcf957cb60880910296d226bd0dca652c05f68ca
+Image=lscr.io/linuxserver/calibre-web:0.6.27-ls402
 Network=pasta
 Environment=DOCKER_MODS=linuxserver/mods:universal-calibre
 Environment=LANG=en_US.UTF-8

dankserver/compose.yaml

@@ -94,12 +94,34 @@ services:
       timeout: 10s
       retries: 3
 
-  # Jellyfin left this file when it became a Quadlet: the container is owned by
+  # ═══════════════════════════════════════════════
-  # dankserver/jellyfin/quadlet/jellyfin.container, its data roots are under
+  # Jellyfin — media server (movies, TV, music)
-  # /home/dank/Containers/jellyfin, and its library arrives through the SSD
+  # ═══════════════════════════════════════════════
-  # overlay at /var/lib/media-meta/view (scripts/media-view.sh). The block that
+  jellyfin:
-  # was here named /opt/jellyfin/* and a read-only array bind — a second owner for
+    image: jellyfin/jellyfin:latest
-  # the container name `jellyfin`, wrong on every path. One owner per container.
+    container_name: jellyfin
+    restart: unless-stopped
+    ports:
+      - "8096:8096/tcp"
+      - "8920:8920/tcp"
+      - "7359:7359/udp"
+      - "1900:1900/udp"
+    environment:
+      - JELLYFIN_PublishedServerUrl=http://192.168.0.235:8096
+      - DOTNET_SYSTEM_IO_DISABLEFILELOCKING=true
+    volumes:
+      - /opt/jellyfin/config:/config
+      - /opt/jellyfin/cache:/cache
+      - /mnt/entropy:/data:ro
+    devices:
+      - /dev/dri:/dev/dri
+    group_add:
+      - "992"
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8096/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
 
   # ═══════════════════════════════════════════════
   # Calibre-Web — e-book web frontend

dankserver/copyparty/quadlet/copyparty.container

@@ -21,13 +21,7 @@ After=network.target
 
 [Container]
 ContainerName=copyparty
-# Digest-pinned: upstream stopped publishing version tags after 1.19.15, so
+Image=ghcr.io/9001/copyparty-ac:latest
-# the pin rides :latest@digest (the tag in the reference is cosmetic; the
-# digest is the pull). Pinned 2026-10-21 at the build whose label is
-# 1.20.26 - closes GHSA-3c88-p299-7hvr (1.20.25) and GHSA-hg99-jqfp-rf76
-# (1.20.26); the previously running build was the rolling :latest at
-# 1.20.24 (issue #73 on command-center).
-Image=ghcr.io/9001/copyparty-ac:latest@sha256:7f77459160a4bf34fdca79f2965dff4f0c1d7069a3d9cdfb3632acb041dd2f6a
 Network=dankserver_appnet
 EnvironmentFile=/home/dank/Containers/copyparty/env
 Exec=-a ${COPAY_ACCOUNT}:${COPAY_PASSWORD} -v /w::r:ra,dank
@@ -36,9 +30,6 @@ Volume=/home/dank/Containers/copyparty/cfg:/cfg
 PublishPort=3923:3923
 
 [Service]
-# /w is the array: serving the pre-mount directory instead of the volume shows an
-# empty share and nothing complains, so the mount has to answer first.
-ExecStartPre=/home/dank/serverAppConfigs/scripts/wait-for-mount.sh /mnt/entropy
 EnvironmentFile=/home/dank/Containers/copyparty/env
 Restart=always
 RestartSec=5

dankserver/host/crypttab

@@ -1 +0,0 @@
-entropy	UUID=cd86c728-459e-4f3a-bcc2-41ecf84685ec	/etc/entropy	nofail,luks

dankserver/host/fstab

@@ -1,18 +0,0 @@
-# /etc/fstab: static file system information.
-#
-# Use 'blkid' to print the universally unique identifier for a
-# device; this may be used with UUID= as a more robust way to name devices
-# that works even if disks are added and removed. See fstab(5).
-#
-# <file system> <mount point>   <type>  <options>       <dump>  <pass>
-# / was on /dev/nvme0n1p2 during curtin installation
-/dev/disk/by-uuid/4f3731d2-fb7b-48e7-a79f-0e33cb8a4162 / ext4 defaults 0 1
-# /boot/efi was on /dev/nvme0n1p1 during curtin installation
-/dev/disk/by-uuid/183C-442D /boot/efi vfat defaults 0 1
-#/dev/disk/by-label/archive-one /mnt/archive-one auto nosuid,nodev,nofail,x-gvfs-show 0 0
-#/dev/disk/by-label/archive-two /mnt/archive-two auto nosuid,nodev,nofail,x-gvfs-show 0 0
-# /dev/md0 is a LUKS container, not a filesystem; its ext4 is mounted via
-# /dev/mapper/entropy on the next line. Mounting /dev/md0 directly fails.
-#/dev/md0 /mnt/md0 ext4 auto,nofail,nosuid,nodev 0 0 
-/dev/mapper/entropy /mnt/entropy ext4 auto,nosuid,nofail,nodev,x-gvfs-show 0 0
-/swapfile none swap sw 0 0

dankserver/host/systemd/media-meta-view.mount

@@ -1,30 +0,0 @@
-# /etc/systemd/system/var-lib-media\x2dmeta-view.mount
-# (repo copy: dankserver/host/systemd/media-meta-view.mount — systemd names a
-# mount unit after its ESCAPED path, so the host file carries the \x2d spelling)
-#
-# Installed by `scripts/media-view.sh install` — the repo copy is the source of
-# truth (fleet law: never edit host state by hand).
-#
-# An OverlayFS merge that shows the media library as one tree while splitting
-# where its bytes live: lowerdir is the RAID6 array (the source of truth, never
-# written), upperdir is a directory on the NVMe that receives every write. The
-# two media servers bind the result at /var/lib/media-meta/view, so Jellyfin's
-# sidecars and artwork are SSD bytes — which is what makes them fast to browse
-# and what keeps Plex's NFO agent off the spinners — while the media itself stays
-# on the array untouched.
-#
-# RequiresMountsFor is load-bearing: without the array mounted, lowerdir is an
-# empty directory and the view would present an empty library as truth.
-
-[Unit]
-Description=SSD-backed overlay view of the media library (array + NVMe metadata layer)
-RequiresMountsFor=/mnt/entropy
-
-[Mount]
-What=overlay
-Where=/var/lib/media-meta/view
-Type=overlay
-Options=lowerdir=/mnt/entropy,upperdir=/var/lib/media-meta/upper,workdir=/var/lib/media-meta/work
-
-[Install]
-WantedBy=local-fs.target

dankserver/host/systemd/user.slice.d/io-accounting.conf

@@ -1,14 +0,0 @@
-# The io controller is what makes IOWeight= mean anything, and systemd does not
-# enable it below `user.slice` by default: with io accounting off, `io` never
-# appears in `user.slice/cgroup.subtree_control`, so no rootless container can
-# have an `io.weight` file and `IOWeight=` in a quadlet is silently inert.
-# Measured on Dankserver 2026-10-31: setting this property flipped
-# `user.slice/cgroup.subtree_control` from `cpu memory pids` to `cpu io memory
-# pids` immediately, with nothing restarted.
-#
-# This is half the fix; the other half is delegating io to user@1000.service
-# (user@1000.service.d/io-delegate.conf). Both must be in place before a reboot,
-# because the delegation is read when the user manager starts. Law and the
-# verification command: [[Quadlet Lifecycle]].
-[Slice]
-IOAccounting=yes

dankserver/host/systemd/user@1000.service.d/io-delegate.conf

@@ -1,12 +0,0 @@
-# The system manager gives the user manager cpu/memory/pids by default (systemd
-# 259: `systemctl show user@1000.service -p DelegateControllers` → `cpu memory
-# pids`). Without `io` in that set no `io.weight` file can exist anywhere below
-# `user.slice`, so `IOWeight=` in a rootless quadlet is silently inert — the same
-# class of trap as `RequiresMountsFor=`. Granting the controller here is what
-# makes the media servers' I/O share real.
-#
-# Inert until `user@1000.service` starts again, i.e. the next reboot (restarting
-# it would kill every rootless container on the host). Verify after the reboot
-# with the check in [[Quadlet Lifecycle]].
-[Service]
-DelegateControllers=cpu memory pids io

dankserver/jellyfin/quadlet/jellyfin.container

@@ -4,9 +4,8 @@
 # Unit name: jellyfin.service (podman 5.x drops the container- prefix)
 #
 # Data roots migrated from /opt/jellyfin to /home/dank/Containers/jellyfin at
-# cutover. The library is seen through /var/lib/media-meta/view, the SSD-backed
+# cutover. All of /mnt/entropy is mounted read-only at /data: nothing automated
-# overlay view (scripts/media-view.sh): the array stays read-only and untouched,
+# anywhere writes to the entropy volume. Every
-# while the sidecars this server writes land on the NVMe. Every
 # creation-time environment variable of the compose-era container is kept as
 # an Environment= line (zero drift); none of them are secrets, so this unit
 # needs no EnvironmentFile.
@@ -17,7 +16,7 @@ After=network.target
 
 [Container]
 ContainerName=jellyfin
-Image=ghcr.io/jellyfin/jellyfin:latest@sha256:fea863d0cd9ec445985d9c75fc6ed64e38a1d2766cf0c250a33d553f4fc1b771
+Image=ghcr.io/jellyfin/jellyfin:latest
 Network=dankserver_appnet
 Environment=DEBIAN_FRONTEND=noninteractive
 Environment=DOTNET_SYSTEM_IO_DISABLEFILELOCKING=true
@@ -42,11 +41,7 @@ PublishPort=7359:7359/udp
 PublishPort=1900:1900/udp
 Volume=/home/dank/Containers/jellyfin/config:/config
 Volume=/home/dank/Containers/jellyfin/cache:/cache
-# The view, writable: Jellyfin is the metadata writer (movie.nfo / tvshow.nfo /
+Volume=/mnt/entropy:/data:ro
-# episode.nfo + artwork) and those bytes belong on the SSD. The gate in [Service]
-# is the guard: started against a plain, unmounted view directory a scan decides
-# the library is empty and deletes what it cannot see.
-Volume=/var/lib/media-meta/view:/data
 AddDevice=/dev/dri
 GroupAdd=keep-groups
 HealthCmd=curl -f http://localhost:8096/health
@@ -55,19 +50,8 @@ HealthTimeout=10s
 HealthRetries=3
 
 [Service]
-# Refuse to start until the bind source is a real mount — see the header of
-# scripts/wait-for-mount.sh for the blind-boot incident this prevents.
-ExecStartPre=/home/dank/serverAppConfigs/scripts/wait-for-mount.sh /var/lib/media-meta/view /mnt/entropy
 Restart=always
 RestartSec=5
 
-# A library scan reads the array for minutes on end. Weighted LOW (default is
-# 100) so that when the array is contended a scan loses to playback and to every
-# other container this user runs. Proportional share, not a cap: it changes
-# nothing while the disk is idle. 10 is a convention — the requirement is only
-# that it sit far below 100 — and it is inert until user@1000.service is
-# delegated the io controller ([[Quadlet Lifecycle]]).
-IOWeight=10
-
 [Install]
 WantedBy=default.target

dankserver/observability/quadlet/cadvisor.container

@@ -1,39 +0,0 @@
-# Quadlet unit: cadvisor (rootless, boot-persistent) — DANKSERVER.
-#
-# Install path on dankserver: ~/.config/containers/systemd/cadvisor.container
-# Unit name: cadvisor.service (container name: cadvisor)
-#
-# The Dankserver twin of dankclaw/observability/quadlet/cadvisor.container.
-# Same rootless shape, same --cgroupns=host requirement (see that file for the
-# full story), only the LAN address differs: this host publishes on
-# 192.168.0.235:8080 so Prometheus on Dankclaw can scrape it over the real
-# network (cross-host, so the host.containers.internal trick does not apply).
-# It reports the media/library stack (romm, plex, jellyfin, copyparty, calibre,
-# tautulli) by their quadlet unit names via the cgroup path.
-
-[Unit]
-Description=cAdvisor container metrics (Dankserver)
-After=network-online.target
-Wants=network-online.target
-
-[Container]
-ContainerName=cadvisor
-Image=gcr.io/cadvisor/cadvisor:v0.49.1@sha256:3cde6faf0791ebf7b41d6f8ae7145466fed712ea6f252c935294d2608b1af388
-PodmanArgs=--pid=host --cgroupns=host
-PublishPort=127.0.0.1:8080:8080
-PublishPort=192.168.0.235:8080:8080
-Volume=/sys:/sys:ro
-Volume=/:/rootfs:ro
-Exec=--housekeeping_interval=30s
-HealthCmd=wget --spider -q http://localhost:8080/healthz
-HealthInterval=30s
-HealthTimeout=10s
-HealthRetries=3
-HealthStartPeriod=40s
-
-[Service]
-Restart=always
-RestartSec=10
-
-[Install]
-WantedBy=default.target

dankserver/observability/quadlet/node-exporter.container

@@ -37,7 +37,7 @@ Wants=network-online.target
 
 [Container]
 ContainerName=node-exporter
-Image=docker.io/prom/node-exporter:latest@sha256:1b4e4438faca4dd7e001dd445d161a4a2091b0fededa84093b3a8dfeae1f1be0
+Image=docker.io/prom/node-exporter:latest
 Network=host
 PodmanArgs=--pid=host
 Exec=--path.procfs=/host/proc --path.sysfs=/host/sys --path.rootfs=/rootfs --web.listen-address=127.0.0.1:9100 --web.listen-address=192.168.0.235:9100

dankserver/plex/quadlet/plex.container

@@ -4,33 +4,19 @@ After=network-online.target
 Wants=network-online.target
 
 [Container]
-Image=lscr.io/linuxserver/plex:1.43.5.11079-b3b13e506-ls330@sha256:01a53d9c7adcbb3701fbb0a4230c0a37c85453759b6b05a67356c3c7a09de08d
+Image=lscr.io/linuxserver/plex:1.43.4.10903-e5521bd8c-ls325
 ContainerName=plex
 Network=dankserver_appnet:alias=plex
 Environment=PUID=0
 Environment=PGID=0
 Environment=TZ=America/Los_Angeles
 Volume=/var/lib/plexmediaserver:/config
-# The container path stays /mnt/entropy on purpose: every path Plex recorded in
+Volume=/mnt/entropy:/mnt/entropy:ro
-# its own database is written against it, so swapping the HOST source of this bind
-# to the overlay view re-points Plex at the sidecars without touching its DB.
-# Read-only: Plex consumes the NFO files Jellyfin writes and writes no metadata.
-Volume=/var/lib/media-meta/view:/mnt/entropy:ro
 PublishPort=32400:32400
 
 [Service]
-# Refuse to start until the bind source is a real mount: Plex blind is how paths
-# get marked missing in its own database. Both the view and the array under it
-# must answer — scripts/wait-for-mount.sh names the 2026-10-31 incident.
-ExecStartPre=/home/dank/serverAppConfigs/scripts/wait-for-mount.sh /var/lib/media-meta/view /mnt/entropy
 Restart=always
 RestartSec=5
 
-# See the jellyfin unit for the reasoning: a section scan gets a LOW weight
-# (default 100) so a walk of 50k files loses the array to playback and to every
-# other container under this user. Inert until user@1000.service holds the io
-# controller ([[Quadlet Lifecycle]]).
-IOWeight=10
-
 [Install]
 WantedBy=default.target

dankserver/romm/quadlet/romm-mariadb.container

@@ -14,7 +14,7 @@ After=network.target
 
 [Container]
 ContainerName=romm-mariadb
-Image=docker.io/library/mariadb:11@sha256:c4124d1afa875e47f2892edf26b482fa54f796e2f342d3717a04ca091a22a9bd
+Image=docker.io/library/mariadb:11
 Network=dankserver_appnet:alias=mariadb
 EnvironmentFile=/home/dank/Containers/romm/env
 Environment=MARIADB_DATABASE=romm

dankserver/romm/quadlet/romm-redis.container

@@ -12,7 +12,7 @@ After=network.target
 
 [Container]
 ContainerName=romm-redis
-Image=docker.io/library/redis:7-alpine@sha256:8da19c7399dca900c6822a1cf30f9d2285585e2c4b457ff4095b0f4500054d3f
+Image=docker.io/library/redis:7-alpine
 Network=dankserver_appnet:alias=redis
 Volume=/home/dank/Containers/romm/redis:/data
 HealthCmd=redis-cli ping

dankserver/romm/quadlet/romm.container

@@ -18,7 +18,7 @@ After=romm-mariadb.service romm-redis.service network.target
 
 [Container]
 ContainerName=romm
-Image=ghcr.io/rommapp/romm:latest@sha256:8677fb7b81b1d3db20b849e989a1dadc2a11159e51eb34a2acdcb01102274edf
+Image=ghcr.io/rommapp/romm:latest
 Network=dankserver_appnet
 EnvironmentFile=/home/dank/Containers/romm/env
 Environment=DB_HOST=mariadb

dankserver/tautulli/quadlet/tautulli.container

@@ -4,7 +4,7 @@ After=network-online.target
 Wants=network-online.target
 
 [Container]
-Image=lscr.io/linuxserver/tautulli:v2.18.2-ls250@sha256:529c7eabcc40554c1dc48f33f1f3cc3b1438462d73e0ec2dac8ac0b66aeeb8d4
+Image=lscr.io/linuxserver/tautulli:v2.18.1-ls245
 ContainerName=tautulli
 Network=dankserver_appnet:alias=tautulli
 Environment=PUID=0

frankbook-pro/gluetun/quadlet/gluetun.container

@@ -19,7 +19,7 @@ Description=Gluetun VPN tunnel (FrankBook-Pro podman machine)
 
 [Container]
 ContainerName=gluetun
-Image=docker.io/qmcgaw/gluetun:latest@sha256:c2ee4191762fca6b6a3c3359a731198a95d9c9af4db32d466e223bf3a84e779b
+Image=docker.io/qmcgaw/gluetun:latest
 AddCapability=NET_ADMIN
 AddDevice=/dev/net/tun:/dev/net/tun
 Environment=VPN_SERVICE_PROVIDER=${VPN_SERVICE_PROVIDER}

frankbook-pro/lidarr/quadlet/lidarr.container

@@ -15,7 +15,7 @@ After=gluetun.service
 
 [Container]
 ContainerName=lidarr
-Image=lscr.io/linuxserver/lidarr:latest@sha256:d8549ff9ea29b4015c32257360652c1000c31ea471a2b3f0835ae77292faf35b
+Image=lscr.io/linuxserver/lidarr:latest
 Environment=PUID=0
 Environment=PGID=0
 Environment=TZ=America/Los_Angeles

frankbook-pro/prowlarr/quadlet/prowlarr.container

@@ -24,7 +24,7 @@ After=gluetun.service
 
 [Container]
 ContainerName=prowlarr
-Image=lscr.io/linuxserver/prowlarr:latest@sha256:b3b00047ed20f6ce2b16780145cb6a0acb51c9e28ea6aa6f5dcd33c7034f1797
+Image=lscr.io/linuxserver/prowlarr:latest
 Environment=PUID=0
 Environment=PGID=0
 Environment=TZ=America/Los_Angeles

frankbook-pro/qbittorrent/quadlet/qbittorrent.container

@@ -29,7 +29,7 @@ Network=gluetun.container
 # Pinned to the last 4.x line: Readarr's retired qB client requires the
 # qB 4.x login response (HTTP 200, body "Ok."); qB 5.x answers 204 with an
 # empty body, which fails Readarr's auth check. All other clients accept 4.x.
-Image=lscr.io/linuxserver/qbittorrent:4.6.7@sha256:55f15d44396315551f87294a176efae733b16e283f38980308e46073950257c6
+Image=lscr.io/linuxserver/qbittorrent:4.6.7
 Environment=PUID=0
 Environment=PGID=0
 Environment=TZ=America/Los_Angeles

frankbook-pro/radarr/quadlet/radarr.container

@@ -15,7 +15,7 @@ After=gluetun.service
 
 [Container]
 ContainerName=radarr
-Image=lscr.io/linuxserver/radarr:latest@sha256:fc0ae3c50f8128b97e84381903ec8d6845c3a569641cb7117c124376cccb57c1
+Image=lscr.io/linuxserver/radarr:latest
 Environment=PUID=0
 Environment=PGID=0
 Environment=TZ=America/Los_Angeles

frankbook-pro/readarr/quadlet/readarr.container

@@ -19,7 +19,7 @@ After=gluetun.service
 
 [Container]
 ContainerName=readarr
-Image=lscr.io/linuxserver/readarr:amd64-1.0.980@sha256:a95e82dbb0eb2bb43de4c150f1dab9dd821306c67ea0b418983a957e731f2b61
+Image=lscr.io/linuxserver/readarr:amd64-1.0.980
 Environment=PUID=0
 Environment=PGID=0
 Environment=TZ=America/Los_Angeles

frankbook-pro/sonarr/quadlet/sonarr.container

@@ -16,7 +16,7 @@ After=gluetun.service
 
 [Container]
 ContainerName=sonarr
-Image=lscr.io/linuxserver/sonarr:latest@sha256:889dcc58c6aea859033985894b519b2e6b1e55d92527ed123f9f52e42ae7c97b
+Image=lscr.io/linuxserver/sonarr:latest
 Environment=PUID=0
 Environment=PGID=0
 Environment=TZ=America/Los_Angeles

scripts/.AGENTTRASH/20260920-llama-layersplit/bench-spec-ab.py.llamacpp-layersplit

@@ -0,0 +1,309 @@
+#!/usr/bin/env python3
+"""bench-spec-ab.py — settle "which proposer should this endpoint use?" with data.
+
+Runs one payload through several speculative-decoding configurations of the same
+binary, one at a time, with the unit stopped between runs: on a single-GPU host
+there is no room for two copies of a 29 GiB model, and the benchmarking policy
+applies. Every configuration gets identical prompts at temperature 0, and the
+greedy text is compared across them — speculation may buy speed, never change
+the answer.
+
+    bench-spec-ab.py <env-file> <serve-script> [options]
+    bench-spec-ab.py /home/dank/serverAppConfigs/scripts/frank-medium.env \
+                     /home/dank/serverAppConfigs/scripts/serve-frank-medium.sh \
+                     --configs "dflash=draft-dflash@7;ngram=ngram-mod@64;chain=draft-dflash,ngram-mod@7"
+
+Config syntax: `name=SPEC_TYPE[@n_max][|ENV=VAL|ENV=VAL]`, entries joined by `;`.
+The systemd unit is restored in a finally block, so it comes back on whatever the
+env file says even if a configuration crashes the harness.
+
+THREE SHAPES, because a single one answers the wrong question. A proposer can
+only draft text it has seen, so the shape decides the verdict:
+
+  prose       a 1k prompt asking for one sentence. Nothing to copy and nothing
+              repetitive, so only a model-backed proposer can help: this is the
+              shape that compares drafters.
+  echo        a ~1.5k passage of unique lines, "repeat it back verbatim". The
+              output IS the prompt, which is ngram-mod's home turf.
+  structured  "25 JSON records, one per line" — repetitive OUTPUT with no prompt
+              overlap, which is what an ngram matcher is really for in an
+              agentic fleet (config edits, tables, record lists).
+
+echo and structured disable thinking (`chat_template_kwargs`), otherwise the
+model thinks the answer into `reasoning_content`, `content` comes back empty and
+the cross-configuration identity check passes vacuously — which is exactly how
+this harness first "verified" an echo it never looked at.
+
+Results on Dankserver (frank-medium payload, 2026-09-16, temperature 0). Decode:
+
+  shape            dflash=7   ngram-mod(48/64)   chain        (tok/s)
+  prose 1k/512        43.8        17.7 (0 drafts)   43.7
+  echo 1.5k/400       76.8       102.5             200.6
+  structured/400      91.1        17.8 (0 drafts)   91.2
+  identity            70.4        17.8 (0 drafts)   70.4
+
+`draft-mtp,draft-dflash` fails at load (a chain has ONE draft context and MTP
+builds against whatever model that context holds); ngram-mod has no such
+constraint — it is draftless and joins the chain unconditionally.
+"""
+import argparse
+import json
+import os
+import re
+import subprocess
+import sys
+import time
+import urllib.request
+
+FILLER = ("The quick brown fox jumps over the lazy dog near the river bank. "
+          "A cache is a component that stores data so future requests are faster. ")
+TOKENS_PER_REP = 28
+UNIT = "frank-medium.service"
+MODEL = "frank-medium"
+SPEC_GREP = ("adding speculative implementation|- n_max=|- block_size=|creating MTP|"
+             "draft acceptance")
+
+DEFAULT_CONFIGS = [
+    ("none", {"SPEC_TYPE": "none"}),
+    ("mtp-n3", {"SPEC_TYPE": "draft-mtp", "SPEC_DRAFT_N_MAX": "3"}),
+    ("mtp-n7", {"SPEC_TYPE": "draft-mtp", "SPEC_DRAFT_N_MAX": "7"}),
+    ("dflash-n7", {"SPEC_TYPE": "draft-dflash", "SPEC_DRAFT_N_MAX": "7"}),
+]
+
+WORDS = ["latency", "throughput", "cache", "adapter", "scheduler", "allocator",
+         "queue", "kernel", "buffer", "shard", "replica", "window"]
+
+
+def echo_passage(lines=90):
+    """Unique lines: no long span repeats inside the prompt, so an n-gram can
+    only fire when the OUTPUT copies the INPUT."""
+    return "\n".join(
+        "Record %03d: the %s of subsystem %d reports state %d with checksum %05d."
+        % (i, WORDS[i % len(WORDS)], i % 7, i % 3, (i * 7919) % 100000)
+        for i in range(lines))
+
+
+ECHO = (echo_passage() + "\n\nRepeat the passage above verbatim, every line, exactly as "
+        "written, with no commentary before or after it.")
+STRUCTURED = ("Output exactly 25 JSON records, one per line, no prose and no code fence. "
+              'Each line must look like {"id": N, "state": "active", "region": "us-west-2"} '
+              "with N running from 1 to 25.")
+PROSE = FILLER * (1000 // TOKENS_PER_REP) + "\n\nReply with a single short sentence."
+IDENTITY = "List the first five prime numbers, comma separated, then stop."
+NO_THINK = {"chat_template_kwargs": {"enable_thinking": False}}
+
+
+def log(msg, logfile):
+    line = "[" + time.strftime("%H:%M:%S") + "] " + str(msg)
+    print(line, flush=True)
+    with open(logfile, "a") as fh:
+        fh.write(line + "\n")
+
+
+def sh(cmd):
+    return subprocess.run(cmd, shell=True, capture_output=True, text=True).stdout.strip()
+
+
+def parse_configs(spec):
+    """`name=SPEC_TYPE[@n_max][|KEY=VALUE]...`, entries joined by ';'.
+
+    KEY=VALUE parts override any env file key, which is how an impl's own window
+    (SPEC_NGRAM_N_MIN/MAX, for instance) gets swept without hand-editing env
+    files."""
+    out = []
+    for chunk in spec.split(";"):
+        chunk = chunk.strip()
+        if not chunk:
+            continue
+        name, _, rest = chunk.partition("=")
+        over = {}
+        if "|" in rest:
+            rest, _, extras = rest.partition("|")
+            for item in extras.split("|"):
+                if "=" in item:
+                    k, _, v = item.partition("=")
+                    over[k.strip()] = v.strip()
+        n_max = None
+        if "@" in rest:
+            rest, _, n_max = rest.partition("@")
+        over["SPEC_TYPE"] = rest.strip()
+        if n_max:
+            over["SPEC_DRAFT_N_MAX"] = n_max.strip()
+        out.append((name.strip(), over))
+    return out
+
+
+def write_env(src, name, overrides):
+    """The env file with this configuration's overrides applied."""
+    path = "/tmp/spec-ab-" + name.replace("/", "_") + ".env"
+    with open(src) as fh:
+        lines = fh.read().splitlines()
+    out = []
+    for line in lines:
+        for k, v in overrides.items():
+            if line.startswith(k + "="):
+                line = k + "=" + v
+                break
+        out.append(line)
+    with open(path, "w") as fh:
+        fh.write("\n".join(out) + "\n")
+    return path
+
+
+def post(base, body, timeout=1800):
+    req = urllib.request.Request(
+        base + "/v1/chat/completions", data=json.dumps(body).encode(),
+        headers={"Content-Type": "application/json"})
+    with urllib.request.urlopen(req, timeout=timeout) as r:
+        return json.load(r)
+
+
+def vram():
+    out = sh("rocm-smi --showmeminfo vram 2>/dev/null | grep 'Used Memory'")
+    return [round(int(x) / 1e9, 2) for x in re.findall(r":\s+(\d+)\s*$", out, re.M)][:2]
+
+
+def wait_health(base, timeout=420):
+    t0 = time.time()
+    while time.time() - t0 < timeout:
+        if not sh("pgrep -x llama-server >/dev/null && echo up"):
+            return False
+        try:
+            with urllib.request.urlopen(base + "/health", timeout=5) as r:
+                if r.status == 200 and json.load(r).get("status") == "ok":
+                    return True
+        except Exception:
+            time.sleep(3)
+    return False
+
+
+def stop_unit():
+    sh("sudo systemctl stop " + UNIT)
+    sh("pkill -x llama-server")
+    for _ in range(40):
+        if not sh("pgrep -x llama-server || true"):
+            return
+        time.sleep(1)
+
+
+def restore_unit(base, logfile):
+    """Bring the endpoint back on the deployed configuration. Runs in a
+    finally, because a harness that can leave production down is a hazard."""
+    log("restoring " + UNIT, logfile)
+    sh("sudo systemctl start " + UNIT)
+    for _ in range(120):
+        try:
+            with urllib.request.urlopen(base + "/health", timeout=5) as r:
+                if json.load(r).get("status") == "ok":
+                    log(UNIT + " healthy again", logfile)
+                    return True
+        except Exception:
+            time.sleep(5)
+    log("WARNING: " + UNIT + " did not come back healthy -- check it by hand", logfile)
+    return False
+
+
+def run_shape(base, prompt, max_tokens, label, extra=None):
+    body = {"model": MODEL, "messages": [{"role": "user", "content": prompt}],
+            "max_tokens": max_tokens, "temperature": 0.0}
+    if extra:
+        body.update(extra)
+    d = post(base, body)
+    tm = d["timings"]
+    msg = d["choices"][0]["message"]
+    content = (msg.get("content") or "").strip()
+    row = {"shape": label,
+           "prompt_n": tm["prompt_n"],
+           "prefill_tps": round(1000 * tm["prompt_n"] / tm["prompt_ms"], 1),
+           "predicted_n": tm["predicted_n"],
+           "decode_tps": round(tm["predicted_per_second"], 2),
+           "draft_n": tm.get("draft_n", 0),
+           "accepted": tm.get("draft_n_accepted", 0),
+           "answer": content,
+           "reasoning_len": len(msg.get("reasoning_content") or "")}
+    if label.startswith("echo"):
+        # How much of the answer really is the passage: a configuration that
+        # "wins" by answering something else is not a win.
+        want = {l.strip() for l in echo_passage().splitlines()}
+        got = [l.strip() for l in content.splitlines() if l.strip()]
+        row["copy_ratio"] = round(sum(1 for l in got if l in want) / len(got), 3) if got else 0.0
+    return row
+
+
+def measure(base):
+    run_shape(base, FILLER * (4000 // TOKENS_PER_REP) +
+              "\n\nReply with a single short sentence.", 32, "warmup")
+    return [
+        run_shape(base, PROSE, 512, "prose 1k/512"),
+        run_shape(base, ECHO, 400, "echo 1.5k/400", NO_THINK),
+        run_shape(base, STRUCTURED, 400, "structured/400", NO_THINK),
+        run_shape(base, IDENTITY, 192, "identity"),
+    ]
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("env_file")
+    ap.add_argument("serve_script")
+    ap.add_argument("--base-url", default="http://127.0.0.1:7770")
+    ap.add_argument("--log", default="/tmp/bench-spec-ab.log")
+    ap.add_argument("--configs", default=None,
+                    help="name=SPEC_TYPE[@n_max][|ENV=VAL] joined by ';' "
+                         "(default: the four configs measured on 2026-09-16)")
+    ap.add_argument("--json", default="/tmp/bench-spec-ab.json")
+    args = ap.parse_args()
+
+    configs = parse_configs(args.configs) if args.configs else DEFAULT_CONFIGS
+    # Absolute paths: the launcher must not depend on the caller's cwd, and a
+    # relative path plus a `cd` to its own directory double-counts the prefix.
+    env_file = os.path.abspath(args.env_file)
+    serve_script = os.path.abspath(args.serve_script)
+    base, logfile = args.base_url, args.log
+    results = {}
+    log("spec A/B start: " + ", ".join(n for n, _ in configs) +
+        " (unit " + UNIT + " stopped for the duration)", logfile)
+    try:
+        stop_unit()
+        for name, over in configs:
+            env_path = write_env(env_file, name, over)
+            logf = "/tmp/spec-ab-" + name.replace("/", "_") + ".log"
+            sh("FRANK_MEDIUM_ENV_FILE=" + env_path + " setsid bash " + serve_script +
+               " > " + logf + " 2>&1 < /dev/null &")
+            if not wait_health(base):
+                log(name + ": FAILED to become healthy -- " + sh("tail -3 " + logf), logfile)
+                results[name] = {"error": "not healthy", "tail": sh("tail -6 " + logf)}
+                stop_unit()
+                continue
+            rows = measure(base)
+            results[name] = {"vram_gb": vram(), "rows": rows,
+                             "spec_log": sh("grep -E '" + SPEC_GREP + "' " + logf + " | tail -4")}
+            for r in rows:
+                log(name + " | " + r["shape"] + " prefill " + str(r["prefill_tps"]) +
+                    " tok/s | decode " + str(r["decode_tps"]) + " tok/s | draft " +
+                    str(r["draft_n"]) + "/" + str(r["accepted"]) +
+                    (" (" + str(round(100.0 * r["accepted"] / r["draft_n"])) + " %)"
+                     if r["draft_n"] else "") +
+                    (" | copy " + str(r["copy_ratio"]) if "copy_ratio" in r else "") +
+                    (" | EMPTY ANSWER" if not r["answer"] else ""), logfile)
+            log(name + " | vram " + str(results[name]["vram_gb"]), logfile)
+            stop_unit()
+    finally:
+        restore_unit(base, logfile)
+
+    with open(args.json, "w") as fh:
+        json.dump(results, fh, indent=2)
+    for shape in ("prose 1k/512", "echo 1.5k/400", "structured/400", "identity"):
+        texts = [r["answer"] for v in results.values() if "rows" in v
+                 for r in v["rows"] if r["shape"] == shape]
+        if any(not t for t in texts):
+            log("WARNING: '" + shape + "' produced an empty answer in some configuration -- "
+                "its identity check proves nothing", logfile)
+        elif len(set(texts)) > 1:
+            log("WARNING: configurations disagree on greedy text for '" + shape +
+                "' -- speculation is changing answers", logfile)
+    log("done; results in " + args.json, logfile)
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/.AGENTTRASH/20260920-llama-layersplit/frank-medium.env.llamacpp-layersplit

@@ -0,0 +1,318 @@
+# Tunables for frank-medium (orcarouter/Qwen3.8-27B-Uncensored-GGUF Q8_0 +
+# z-lab/Qwen3.8-27B-DFlash2-GGUF Q4_K_M drafter), mainline llama.cpp on
+# Dankserver, 2x AMD Radeon AI PRO R9700 (gfx1201).  Since 2026-09-16 this is
+# the SOLE LLM runtime on the box: the vllm-radiance replica pair and its
+# routing proxy are retired.
+#
+# Hardware: two R9700 (Navi 48, RDNA4, 32,624 MiB each), no XGMI, different
+# IOMMU groups -- every cross-card byte goes over PCIe.  The Raphael iGPU
+# (gfx1036/Radeon 610M) enumerates as HIP device 2 and is hidden below so
+# nothing can drift onto shared system RAM.
+#
+# WHY LAYER SPLIT AND NOT TENSOR (operator call, 2026-09-16): tensor parallel
+# needs a cross-card allreduce per layer, and this host cannot dispatch one.
+# RCCL's kernels carry a hidden hostcall-buffer parameter, and ROCr refuses it
+# on a device without PCIe atomics -- the second card sits behind the B650
+# chipset bridges (AtomicOpsCap: Routing-, read-only), so every collective that
+# touches it dies with hipErrorIllegalState.  Measured on this box 2026-09-15
+# (llama-bench, pp4096 / tg128, f16 KV, fa on):
+#
+#   single R9700    1160.9 / 19.42
+#   layer  2x       1991.2 / 18.76      (859.1 / 17.64 at depth 32768)
+#   tensor 2x        271.8 / 26.26      (no RCCL: butterfly fallback, -7x prefill)
+#
+# Layer split distributes layers in order; only the activation at the boundary
+# crosses the wire, once per forward pass.  That is the "pipeline parallelism"
+# this service wanted, and it needs no collective at all.
+#
+# Runtime: mainline llama.cpp master fb27a525 (2026-09-16), gfx1201, built by
+# scripts/build-llama-rdna4.sh against a private ROCm 7.14.0a20260624 toolchain
+# that is bundled next to the binary (RPATH $ORIGIN/../lib, no LD_LIBRARY_PATH).
+# The ref is pinned by TWO features: DFlash2 (ggml-org/llama.cpp#27342 -- the
+# drafter is detected from its GGUF) and qwen35 MTP.  Do not float it.
+#
+# Model: orcarouter/Qwen3.8-27B-Uncensored-GGUF @ Q8_0, 27.0 GiB, arch qwen35
+# (verified from the GGUF header 2026-09-19: 262144 trained window, 24 heads /
+# 4 KV heads, nextn_predict_layers=1).  The file ALSO carries the model's MTP
+# head (blk.64.nextn.*), so --spec-type draft-mtp is available without a second
+# copy in VRAM -- one SPEC_TYPE change, the drafter below stays on disk.
+#
+# Drafter: z-lab/Qwen3.8-27B-DFlash2-GGUF @ Q4_K_M, 1.06 GiB (operator call
+# 2026-09-19: the Q4 rung -- the drafter's job is throughput, not output
+# quality, and the target verifies every drafted token).  5 layers, hidden
+# 5120, a block-diffusion proposal (block_size 8) under a 2048-token sliding
+# window (dflash.attention.sliding_window=2048, verified from the header).
+# The window is what makes it cheap HERE: its KV is bounded at 2048 positions
+# (~40 MiB) instead of spanning the context (see SIZING).
+#
+# Architecture (GGUF arch qwen35): 64 layers as 16 x (3 x (Gated DeltaNet ->
+# FFN) + 1 x (Gated Attention -> FFN)) -- 48 linear-attention layers whose
+# per-sequence state is CONSTANT-SIZE, 16 full-attention layers at 4 KV heads x
+# 256 head_dim.  A token therefore costs 2 x 4 x 256 x 2 B = 64 KiB of KV at f16
+# in the attention layers only, plus ~0.16 GiB per sequence of f32 DeltaNet
+# state at any depth.
+#
+# SIZING, the deployed shape (32:33 / ctx 327680 / 6144x512 / two slots /
+# DFlash2 Q4_K_M), measured 2026-09-19 after the model swap (rocm-smi):
+#
+#   card 0 (x16)  26.9 GiB used, 5.7 GiB free
+#   card 1 (x1)   27.8 GiB used, 4.8 GiB free
+#
+# The predecessor's measured table (rocm-smi, 2026-09-16, UD-Q8_K_XL target)
+# stays as the calibration history:
+#
+#   CTX     split  batch  slots  drafter  GPU 0 free  GPU 1 free   note (ubatch 1536)
+#   262144   1,1   2048   1      DFlash2   8.64 GiB    4.43 GiB   day's start
+#   262144  39,26  6144   2      DFlash2   2.42 GiB    7.20 GiB
+#   262144  38,27  6144   2      DFlash2   3.85 GiB    5.77 GiB
+#   262144  37,28  6144   2      DFlash2   4.28 GiB    5.34 GiB
+#   262144  36,29  6144   2      DFlash2   4.71 GiB    4.91 GiB
+#   262144  35,30  6144   2      DFlash2   5.14 GiB    4.48 GiB
+#   262144  40,25  6144   2      DSpark    1.87 GiB    1.86 GiB   (retired)
+#
+# ...and the same deployed shape re-measured at ubatch 512, after llama-bench
+# showed 512 is the throughput optimum and costs 3.71 GiB less in total (see the
+# batch block below):
+#
+#   262144  36,29  6144   512    2      DFlash2   6.01 GiB    7.32 GiB   ubatch only
+#   262144  35,30  6144   512    2      DFlash2   6.44 GiB    6.90 GiB
+#
+# ONE -ts STEP IS ONE LAYER, AND LAYERS ARE NOT THE SAME SIZE.  This is a hybrid
+# stack -- 16 x (3 Gated DeltaNet + 1 Gated Attention) blocks -- so moving a
+# DeltaNet layer shifts ~0.43 GiB while an attention layer shifts ~1.43 GiB
+# (0.45 of weights plus ~1.0 GiB of its own f16 KV at 262144).  Both step sizes
+# were measured, which is why the balance is found by measurement rather than by
+# interpolating between splits.
+#
+# WHY THE SPLIT IS 32:33 (operator call, 2026-09-19).  The operator asked for
+# the tensors BALANCED across the two cards, which for 65 layers is 32:33 --
+# the most even split that exists.  The predecessor's 35:30 skew existed to lean
+# work onto the x16 card (ROCm0), because ROCm1's Gen4 x1 chipset path made it
+# the 98 % utilization bottleneck; the measured trade of the balanced point is
+# that the x1 card runs hotter while the x16 card idles a little more, and the
+# operator accepted that for symmetry.  Do not re-skew without asking.
+#
+# THE TWO CARDS' PATHS ARE NOT SYMMETRIC (measured, 2026-09-17): ROCm0
+# (03:00.0) hangs off CPU root port 00:01.1 at Gen4 x16 end to end (~31.5 GB/s);
+# ROCm1 (0b:00.0) rides the B650 chipset through bridges that each negotiate
+# Gen4 x1 (~1.97 GB/s).  The layer-split boundary itself is not the cost
+# (~5.2 MB of activation per 512-token ubatch rides the wire); the x1 card is
+# COMPUTE-bound, not PCIe-bound.
+#
+# A FAULT TO WATCH.  A 39:26 split, at 1x batch / 1 slot, died on its eighth
+# request: the amdgpu driver logged SDMA0 UTCL2 page faults and the engine
+# surfaced `ROCm error: an illegal memory access was encountered` -> ggml_abort,
+# i.e. a fault in the cross-card boundary copy, this layer split's hot path.  It
+# has not reproduced since, but the signature is worth recognising -- it is NOT
+# an OOM, and no amount of headroom prevents it.
+#
+# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE (HIP reads
+# those bare vars; 2026-08-13 incident).  llama.cpp takes --host/--port/--temp
+# as flags only.
+
+# llama-server: mainline fb27a525 built for gfx1201 by scripts/build-llama-rdna4.sh.
+LLAMA_BIN=/home/dank/GitPackages/llama.cpp-dflash2/build-rdna4-rocm714/bin/llama-server
+
+# Payload, fetched with scripts/download-frank-medium-gguf.sh.
+MODEL_DIR=/home/dank/models/Qwen3.8-27B-Uncensored-GGUF
+MODEL_FILE=Qwen3.8-27B-Uncensored-Q8_0.gguf
+# The f16 vision projector, same repo as the target.  llama-server loads it via
+# the explicit --mmproj flag (no autoload in this build); the serve script
+# refuses to start without it when vision is enabled, so a missing file is a
+# deploy error, not a text-only server that pretends to be multimodal.
+MM_PROJ_FILE=mmproj-Qwen3.8-27B-Uncensored-f16.gguf
+DRAFT_MODEL_DIR=/home/dank/models/Qwen3.8-27B-DFlash2-GGUF
+DRAFT_MODEL_FILE=Qwen3.8-27B-DFlash2-Q4_K_M.gguf
+
+# Fleet identity.  7770 is the fleet's dankserver endpoint; the alias is the id
+# at /v1/models and what every client asks for.
+ALIAS=frank-medium
+BIND_ADDR=0.0.0.0
+LISTEN_PORT=7770
+# Device placement.  HIP_VISIBLE_DEVICES hides the Raphael iGPU (HIP device 2)
+# so nothing can drift onto shared system RAM; DEVICES is what llama.cpp splits
+# across, and neither of the two cards has an XGMI link to the other.
+HIP_VISIBLE_DEVICES=0,1
+DEVICES=ROCm0,ROCm1
+SPLIT_MODE=layer
+
+# 32:33 -- balanced (operator call 2026-09-19): 65 layers split as evenly as
+# they can be, ROCm1 (the last-layers card, which also carries the drafter and
+# the output layers) holding the extra one.  See the WHY THE SPLIT IS 32:33
+# block above for the trade against the predecessor's 35:30 x16-lean.
+TENSOR_SPLIT=32,33
+
+NGL=999
+# Auto-fit has no business resizing a context we set explicitly.
+FIT=off
+FLASH_ATTN=on
+
+# 327680 positions over TWO slots, so each conversation gets 163840 --
+# --parallel DIVIDES --ctx-size, so more slots would shrink every
+# conversation rather than grow the cache.  163840 is inside the checkpoint's
+# trained 262144 window, so the whole pool is trained territory (no rope
+# extrapolation, unlike the predecessor's 393216).
+CTX_SIZE=327680
+PARALLEL=2
+
+# MEASURED 2026-09-16 with scripts/bench-batch-ubatch.sh on this box: llama-bench,
+# a 64k prefill plus a 128-token decode with 64k of KV already resident, 3 reps,
+# one invocation per cell, the deployed split and f16 KV.  --ubatch-size is the
+# physical batch the graph is built at -- and the only one of the two knobs that
+# costs VRAM:
+#
+#   batch  ubatch   prefill tok/s        GPU 0 / GPU 1 free
+#   6144   1536    1164.96 +- 2.30      10.28 / 11.71 GiB
+#   6144    768    1135.03 +- 1.09      11.29 / 13.28 GiB
+#   6144    512    1192.93 +- 0.91      11.63 / 13.81 GiB   <- deployed
+#   6144    384    1068.04 +- 0.79      11.80 / 14.07 GiB
+#   6144    256    1045.98 +- 1.69      11.97 / 14.33 GiB
+#   4096   1536    1161.90 +- 0.96      10.28 / 11.71 GiB
+#   2048   1536    1170.23 +- 0.86      10.28 / 11.71 GiB
+#   2048    512    1193.88 +- 1.01      11.63 / 13.81 GiB
+#
+# THE PLATEAU STARTS AT 512.  512 -> 1536 buys ~2 % of prefill -- inside the
+# run-to-run spread, and the 512 cells were the faster pair in BOTH batch
+# columns -- while costing 1.35 GiB on ROCm0 and 2.10 GiB on ROCm1, so the
+# deployment takes the cheap end.  BELOW 512 the SMs are no longer saturated:
+# 384 and 256 fall ~11 % and ~12 %.  The logical batch is free either way --
+# 2048, 4096 and 6144 land within 2 % of each other at a fixed ubatch and use
+# the SAME VRAM, because the compute buffers are sized by ubatch alone.
+#
+# The prefill figure is a property of the SHAPE, not of this knob: the same
+# sweep with no depth in front of it (depth 0) runs 1543 tok/s at ubatch 256 and
+# 1723 at 1536 -- the plateau is in the same place, and the ~32 % between the two
+# tables is what attending over 64k of resident KV costs.  Decode is 15.88 tok/s
+# at depth 65536 on EVERY ubatch (17.80 at depth 0), so this knob cannot touch
+# generation at all.
+#
+# 8192/2048 stays untested under this drafter (the "2020 MiB pp buffer fails on
+# ROCm1" note was measured under DSpark, when it had 0.08 GiB free), and there is
+# no longer a reason to want it: batch buys nothing measurable here.
+BATCH_SIZE=6144
+UBATCH_SIZE=512
+
+# Threads cover tokenization, sampling and HTTP only: every layer is on a GPU.
+NUM_THREADS=8
+THREAD_BATCH=8
+
+# f16 K/V: an agentic checkpoint is the wrong place to spend KV precision.
+CACHE_TYPE_K=f16
+CACHE_TYPE_V=f16
+# Context checkpoints: 0 -- no per-slot KV snapshots at all.  The build's
+# default is 32 (this binary's --help), so the 0 below is a deliberate
+# deviation, not an inherited default: a checkpoint is a VRAM->host-RAM copy
+# of part of a slot's KV, taken so a partially-matching prompt can be restored
+# instead of re-prefilled.  This endpoint trades that away -- its reuse comes
+# from the slot prompt and from the RAM-side prompt cache below.  Stated
+# explicitly so the tunable stays visible rather than merely absent.
+CTX_CHECKPOINTS=0
+# PROMPT CACHE, HOST RAM -- this is the one cache tunable that is NOT VRAM.
+# --cache-ram caps the total bytes of saved prompt states
+# (server_prompt_cache, tools/server/server-task.cpp): update() evicts
+# oldest-first past the cap, and alloc() REFUSES outright any single state
+# bigger than the whole cap.  A state is the serialized KV of a whole sequence
+# plus its DeltaNet state plus the draft context's own KV, so at this shape it
+# costs ~68 KiB per token --
+#   16 full-attention layers x 4 kv heads x 256 dim x 2 B x 2 (K,V) = 64 KiB
+#   plus the draft context's window-bounded KV (a ~40 MiB constant for DFlash2)
+# -- which makes the cap a TOKEN budget in disguise: 16384 MiB holds ~240k
+# tokens, i.e. a FULL 163840-token slot (~10.6 GiB) with ~5 GiB of the budget
+# spare for a second entry.
+#
+# The cost is host RAM, allocated on demand and never pinned (plain heap
+# vectors), so no VRAM number above moves.  dankserver has 62 GiB beside the
+# media-stack co-tenants, so the cache is bounded rather than unlimited (-1):
+# the seam test refuses a budget over half the host's RAM.
+CACHE_RAM=16384
+
+# Sampling defaults for requests that send none -- the values the vLLM
+# predecessor served on this endpoint (`--override-generation-config`), so a
+# client sees no change across the runtime swap.  The model card's own
+# recommendation is temp 1.0 / top_p 0.95; the harness sets its own per model in
+# models.yml, so this is the floor, not the contract.
+TEMPERATURE=0.7
+TOP_P=0.95
+TOP_K=20
+MIN_P=0.0
+PRESENCE_PENALTY=0.0
+
+# Reasoning on, projected into reasoning_content (deepseek format) with no
+# budget: the model decides how long to think.
+REASONING=on
+REASONING_FORMAT=deepseek
+REASONING_BUDGET=-1
+
+# Chat template: empty = the one embedded in the GGUF (Qwen3.8's own).
+CHAT_TEMPLATE_FILE=
+CHAT_TEMPLATE_KWARGS='{"enable_thinking":true,"preserve_thinking":true}'
+
+# Speculative decoding: the DFlash2 sidecar (operator call 2026-09-19).  The
+# target file also carries its own MTP head (nextn_predict_layers=1), so
+# draft-mtp is one SPEC_TYPE change away -- the drafter file stays on disk.
+# n_max 7 is the measured DFlash2 winner (see the table below); the drafter
+# rides ROCm1, the card that holds the last layers.
+SPEC_TYPE=draft-dflash
+SPEC_DRAFT_N_MAX=7
+SPEC_DRAFT_NGL=999
+SPEC_DRAFT_DEVICE=ROCm1
+SPEC_DRAFT_TYPE_K=f16
+SPEC_DRAFT_TYPE_V=f16
+
+# DFlash2 vs the model's own MTP head -- MEASURED 2026-09-16 on the predecessor
+# payload (temperature 0, 1k prompt / 512 out; the autoregressive baseline and
+# both MTP depths were run in one session, same binary, same prompts):
+#
+#   none            17.7 tok/s                     card1 26.07 GB
+#   draft-mtp  n=3  32.4 tok/s  58 % accepted       card1 29.35 GB
+#   draft-mtp  n=7  26.7 tok/s  33 % accepted       card1 29.65 GB
+#   draft-dflash 7  43.5 tok/s  41 % accepted       card1 29.42 GB
+#
+# All four produced IDENTICAL greedy text, so verification is lossless
+# whichever proposer runs.  DFlash2 is the faster proposer (2.46x over
+# autoregressive, 34 % over the best MTP).  The MTP head adds ~3.3 GB to the
+# card that holds it, against 1.06 GB for the Q4_K_M drafter's file -- at the
+# 327680 pool the drafter's window-bounded KV (~40 MiB) leaves headroom on
+# both cards, so the speed wins.
+#
+# THE TWO CANNOT BE CHAINED. `--spec-type draft-mtp,draft-dflash` dies at load:
+#   context type MTP requested but model doesn't contain MTP layers
+#   failed to create MTP context
+# A chain has ONE draft context, and MTP builds against whatever model that
+# context holds -- here the DFlash2 file, which has no MTP layers. MTP's head is
+# only loaded when MTP IS the draft model ("creating MTP draft context against
+# the target model ..."), so a chain of the two is a structural dead end, not a
+# tuning question. See serverAppConfigs-docs/LLM/frank-medium-llamacpp-dflash2.md.
+
+# ngram-mod: the draftless n-gram matcher (CPU hash table in host RAM, no VRAM,
+# no model file, no draft context).  It joins the chain unconditionally --
+# unlike MTP, which needs a draft context and therefore cannot share one with
+# DFlash2.  NOT CURRENTLY ACTIVE: SPEC_TYPE is draft-dflash alone, and the serve
+# script only passes --spec-ngram-mod-* when the type contains "ngram".  The
+# window below is retained because the DFlash2 + ngram chain was measured free
+# on prose and 2.6x on prompt-echo -- one SPEC_TYPE change brings it back.
+#
+# WINDOW MEASURED 2026-09-16 (chain at each window, decode tok/s):
+#
+#   n_min/n_max    prose 1k/512   prompt-echo 1.5k/400
+#   48/64          43.9           200.6
+#   16/32          36.0           161.0
+#    8/16          36.2           113.8
+#
+# The long window is the right one, and not only because it wins on echo: a
+# SHORT window makes the matcher propose on short fragments of ordinary prose,
+# where the proposals are rejected and the verification still costs -- which is
+# the "ngram hurts" result the fleet measured on other payloads twice before.
+# With 48/64 the chain is byte-identical to DFlash2 alone on prose (same 119
+# drafts / 49 accepted) and on the identity prompt (70/53).
+#
+# Do not shorten these without re-running scripts/bench-spec-ab.py: the
+# no-penalty property is what makes the chain safe as a default.
+SPEC_NGRAM_N_MATCH=24
+SPEC_NGRAM_N_MIN=48
+SPEC_NGRAM_N_MAX=64
+
+# Vision enabled: llama-server loads mmproj-Qwen3.8-27B-Uncensored-f16.gguf
+# (931 MiB, lands on ROCm0 -- the fit charges it there) via the explicit
+# --mmproj flag.  This keeps frank-medium multimodal across the model swap.
+NO_MMPROJ=0

scripts/.AGENTTRASH/20260920-llama-layersplit/frank-medium.service.llamacpp-layersplit

@@ -0,0 +1,20 @@
+[Unit]
+Description=llama.cpp Qwen3.8-27B Uncensored UD-Q8_K_XL + DFlash2 drafter (dankserver, frank-medium, 2x Radeon AI PRO R9700)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+# The engine pins staging buffers on the first card; keep the memlock budget
+# unbounded so an RLIMIT that is smaller than the split buffers cannot fail the
+# load.  Parity with the other LLM units on this fleet.
+LimitMEMLOCK=infinity
+Environment="FRANK_MEDIUM_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-medium.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-medium.sh
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

scripts/.AGENTTRASH/20260920-llama-layersplit/serve-frank-medium.sh.llamacpp-layersplit

@@ -0,0 +1,203 @@
+#!/usr/bin/env bash
+# Serve ajgazin/Swift-Qwen3.8-27B-Uncensored-Dynamic-MTP-GGUF @ UD-Q8_K_XL as
+# frank-medium on Dankserver's two Radeon AI PRO R9700 (gfx1201), with the
+# z-lab DFlash2 block-diffusion drafter, using mainline llama.cpp.
+#
+# Runtime: llama.cpp master fb27a525 (2026-09-16), a gfx1201 HIP build that
+# bundles its own ROCm 7.14 runtime (RPATH $ORIGIN/../lib), produced by
+# scripts/build-llama-rdna4.sh.  Two features pin that ref: DFlash2
+# (ggml-org/llama.cpp#27342) and qwen35 MTP.  The charlie12345/ROCmFPX fork
+# this deployment replaced has neither (its tip is c49ebdb, 2026-08-22).
+#
+# Parallelism: --split-mode layer across both cards.  Tensor split would need a
+# cross-card allreduce and this host cannot dispatch one -- RCCL's kernels
+# require a hostcall buffer that ROCr refuses on a card without PCIe atomics,
+# and the second R9700 sits behind the chipset (AtomicOpsCap: Routing-).  Layer
+# split crosses the wire once per forward pass instead of once per layer.
+#
+# The vLLM replica pair and its routing proxy were retired with this cutover:
+# one process, one model, both cards.
+#
+# Tunables come from frank-medium.env unless FRANK_MEDIUM_ENV_FILE overrides it.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_MEDIUM_ENV_FILE:-$SCRIPT_DIR/frank-medium.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) ------------------
+: "${LLAMA_BIN:=/home/dank/GitPackages/llama.cpp-dflash2/build-rdna4-rocm714/bin/llama-server}"
+: "${MODEL_DIR:=/home/dank/models/Swift-Qwen3.8-27B-Uncensored-Dynamic-MTP-GGUF}"
+: "${MODEL_FILE:=Swift-Qwen3.8-27B-Uncensored-Dynamic-MTP-UD-Q8_K_XL.gguf}"
+: "${DRAFT_MODEL_DIR:=/home/dank/models/Qwen3.8-27B-DFlash2-GGUF}"
+: "${DRAFT_MODEL_FILE:=Qwen3.8-27B-DFlash2-Q8_0.gguf}"
+: "${ALIAS:=frank-medium}"
+: "${BIND_ADDR:=0.0.0.0}"
+: "${LISTEN_PORT:=7770}"
+
+# Devices.  HIP_VISIBLE_DEVICES hides the Raphael iGPU (HIP device 2) so nothing
+# can drift onto shared system RAM; DEVICES is what llama.cpp splits across.
+: "${HIP_VISIBLE_DEVICES:=0,1}"
+: "${DEVICES:=ROCm0,ROCm1}"
+: "${SPLIT_MODE:=layer}"
+: "${TENSOR_SPLIT:=1,1}"
+: "${NGL:=999}"
+: "${FIT:=off}"
+: "${FLASH_ATTN:=on}"
+
+: "${CTX_SIZE:=131072}"
+: "${PARALLEL:=1}"
+: "${BATCH_SIZE:=2048}"
+: "${UBATCH_SIZE:=512}"
+: "${NUM_THREADS:=8}"
+: "${THREAD_BATCH:=8}"
+: "${CACHE_TYPE_K:=f16}"
+: "${CACHE_TYPE_V:=f16}"
+: "${CTX_CHECKPOINTS:=8}"
+: "${CACHE_RAM:=8192}"
+
+# Sampling defaults for silent clients: the values the vLLM predecessor served.
+: "${TEMPERATURE:=0.7}"
+: "${TOP_P:=0.95}"
+: "${TOP_K:=20}"
+: "${MIN_P:=0.0}"
+: "${PRESENCE_PENALTY:=0.0}"
+
+: "${REASONING:=on}"
+: "${REASONING_FORMAT:=deepseek}"
+: "${REASONING_BUDGET:=-1}"
+: "${CHAT_TEMPLATE_FILE:=}"
+: "${CHAT_TEMPLATE_KWARGS:={\"enable_thinking\":true,\"preserve_thinking\":true}}"
+
+# Speculative decoding: draft-dflash or draft-dspark (both are MODEL drafters --
+# a file, not a flag), or draft-mtp (the target GGUF's own MTP head, no draft
+# file).  The drafter's own tuning knobs (n-min, p-min, p-split, poll) are left
+# at the build's defaults: they were only ever passed for dspark, and dspark is
+# not the deployed drafter.
+: "${SPEC_TYPE:=draft-dflash}"
+: "${SPEC_DRAFT_N_MAX:=7}"
+: "${SPEC_DRAFT_NGL:=999}"
+: "${SPEC_DRAFT_DEVICE:=}"
+: "${SPEC_DRAFT_TYPE_K:=f16}"
+: "${SPEC_DRAFT_TYPE_V:=f16}"
+: "${SPEC_NGRAM_N_MATCH:=24}"
+: "${SPEC_NGRAM_N_MIN:=48}"
+: "${SPEC_NGRAM_N_MAX:=64}"
+
+NO_MMPROJ="${NO_MMPROJ:-0}"
+: "${MM_PROJ_FILE:=mmproj-BF16.gguf}"
+
+export HIP_VISIBLE_DEVICES
+
+MODEL="$MODEL_DIR/$MODEL_FILE"
+DRAFT_MODEL="$DRAFT_MODEL_DIR/$DRAFT_MODEL_FILE"
+
+if [[ ! -x "$LLAMA_BIN" ]]; then
+    echo "missing executable runtime: $LLAMA_BIN" >&2
+    echo "build it with: bash $SCRIPT_DIR/build-llama-rdna4.sh" >&2
+    exit 1
+fi
+if [[ ! -r "$MODEL" ]]; then
+    echo "missing or unreadable target model: $MODEL" >&2
+    echo "fetch it with: bash $SCRIPT_DIR/download-frank-medium-gguf.sh" >&2
+    exit 1
+fi
+if [[ "$NO_MMPROJ" != "1" ]]; then
+    MM_PROJ="$MODEL_DIR/$MM_PROJ_FILE"
+    if [[ ! -r "$MM_PROJ" ]]; then
+        echo "vision is enabled but the projector is missing: $MM_PROJ" >&2
+        echo "fetch it with: bash $SCRIPT_DIR/download-frank-medium-gguf.sh" >&2
+        exit 1
+    fi
+fi
+if [[ -n "$CHAT_TEMPLATE_FILE" && ! -r "$CHAT_TEMPLATE_FILE" ]]; then
+    echo "missing or unreadable chat template: $CHAT_TEMPLATE_FILE" >&2
+    exit 1
+fi
+
+# --- speculative decoding -------------------------------------------------
+SPEC_ARGS=()
+if [[ -n "$SPEC_TYPE" && "$SPEC_TYPE" != "none" ]]; then
+    SPEC_ARGS=(--spec-type "$SPEC_TYPE" --spec-draft-n-max "$SPEC_DRAFT_N_MAX")
+    if [[ "$SPEC_TYPE" == *dflash* || "$SPEC_TYPE" == *dspark* ]]; then
+        if [[ ! -r "$DRAFT_MODEL" ]]; then
+            echo "missing or unreadable draft model: $DRAFT_MODEL" >&2
+            exit 1
+        fi
+        SPEC_ARGS+=(
+            --spec-draft-model "$DRAFT_MODEL"
+            --spec-draft-ngl "$SPEC_DRAFT_NGL"
+            --spec-draft-type-k "$SPEC_DRAFT_TYPE_K"
+            --spec-draft-type-v "$SPEC_DRAFT_TYPE_V"
+        )
+    fi
+    # ngram-mod is draftless: it needs no draft context and its window is its
+    # own (--spec-ngram-mod-*), so it can ride in the chain beside a model
+    # drafter. It also costs no VRAM -- a CPU hash table.
+    if [[ "$SPEC_TYPE" == *ngram* ]]; then
+        SPEC_ARGS+=(
+            --spec-ngram-mod-n-match "$SPEC_NGRAM_N_MATCH"
+            --spec-ngram-mod-n-min "$SPEC_NGRAM_N_MIN"
+            --spec-ngram-mod-n-max "$SPEC_NGRAM_N_MAX"
+        )
+    fi
+    if [[ -n "$SPEC_DRAFT_DEVICE" ]]; then
+        SPEC_ARGS+=(--spec-draft-device "$SPEC_DRAFT_DEVICE")
+    fi
+fi
+
+# --- template + placement -------------------------------------------------
+TEMPLATE_ARGS=()
+if [[ -n "$CHAT_TEMPLATE_FILE" ]]; then
+    TEMPLATE_ARGS+=(--chat-template-file "$CHAT_TEMPLATE_FILE")
+fi
+TEMPLATE_ARGS+=(--chat-template-kwargs "$CHAT_TEMPLATE_KWARGS")
+
+PLACEMENT_ARGS=(--device "$DEVICES" --split-mode "$SPLIT_MODE" --tensor-split "$TENSOR_SPLIT")
+
+MMPROJ_ARGS=()
+if [[ "$NO_MMPROJ" == "1" ]]; then
+    MMPROJ_ARGS=(--no-mmproj)
+else
+    # No autoload in this build: a server without the flag starts text-only
+    # and answers image requests with a 500, so name the projector.
+    MMPROJ_ARGS=(--mmproj "$MM_PROJ")
+fi
+exec "$LLAMA_BIN" \
+    --model "$MODEL" \
+    --alias "$ALIAS" \
+    --host "$BIND_ADDR" \
+    --port "$LISTEN_PORT" \
+    --jinja \
+    --gpu-layers "$NGL" \
+    --fit "$FIT" \
+    --parallel "$PARALLEL" \
+    --ctx-size "$CTX_SIZE" \
+    --batch-size "$BATCH_SIZE" \
+    --ubatch-size "$UBATCH_SIZE" \
+    --flash-attn "$FLASH_ATTN" \
+    --cache-type-k "$CACHE_TYPE_K" \
+    --cache-type-v "$CACHE_TYPE_V" \
+    --threads "$NUM_THREADS" \
+    --threads-batch "$THREAD_BATCH" \
+    --ctx-checkpoints "$CTX_CHECKPOINTS" \
+    --cache-ram "$CACHE_RAM" \
+    --cache-prompt \
+    --metrics \
+    --temp "$TEMPERATURE" \
+    --top-p "$TOP_P" \
+    --top-k "$TOP_K" \
+    --min-p "$MIN_P" \
+    --presence-penalty "$PRESENCE_PENALTY" \
+    --reasoning "$REASONING" \
+    --reasoning-format "$REASONING_FORMAT" \
+    --reasoning-budget "$REASONING_BUDGET" \
+    "${TEMPLATE_ARGS[@]}" \
+    "${PLACEMENT_ARGS[@]}" \
+    "${MMPROJ_ARGS[@]}" \
+    "${SPEC_ARGS[@]}"

scripts/.AGENTTRASH/bench-decode-threads-batch.py.strix-rocmfp4

@@ -0,0 +1,192 @@
+#!/usr/bin/env python3
+"""
+Decode throughput benchmark for frank-dragoon.
+Starts the server with a given --threads-batch value, sends an 8K+ token prompt,
+generates 256 tokens, measures generation tok/s.
+
+Each --threads-batch value requires a cold server load (~3 min).
+"""
+import json, time, urllib.request, urllib.error, subprocess, os, sys
+
+MODEL = "/home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX/Qwen3.8-Flash-Next-Q4_0-ROCmFP4-STRIX.gguf"
+SERVE = "/home/dank/GitPackages/ROCmFPX/build-qwen38/bin/llama-server"
+PORT = 7770
+N_GEN = 256
+PROMPT_FILE = "/tmp/bench-prompts/prompt_code.txt"
+ENV_FILE = os.path.join(os.path.dirname(__file__), "frank-dragoon.env")
+SERVER_DIR = os.path.dirname(SERVE)
+ROCM_PATH = "/opt/rocm"
+
+def make_env():
+    """Build the same env as serve-frank-dragoon.sh."""
+    env = {**os.environ, "HSA_OVERRIDE_GFX_VERSION": "11.5.1", "HIP_VISIBLE_DEVICES": "0"}
+    
+    # Source env file for tunables
+    if os.path.exists(ENV_FILE):
+        with open(ENV_FILE) as f:
+            for line in f:
+                line = line.strip()
+                if line and not line.startswith("#") and "=" in line:
+                    k, v = line.split("=", 1)
+                    env[k] = v
+    
+    # Build LD_LIBRARY_PATH
+    lib_path = f"{SERVER_DIR}:{ROCM_PATH}/lib:{ROCM_PATH}/lib/rocm_sysdeps/lib:{ROCM_PATH}/lib/llvm/lib"
+    if os.environ.get("LD_LIBRARY_PATH"):
+        lib_path += f":{os.environ['LD_LIBRARY_PATH']}"
+    env["LD_LIBRARY_PATH"] = lib_path
+    env["ROCM_PATH"] = ROCM_PATH
+    
+    return env
+
+ENV = make_env()
+
+def kill_all():
+    subprocess.run(["pkill", "-9", "llama-server"], capture_output=True)
+    time.sleep(3)
+
+def wait_ready():
+    for i in range(600):
+        try:
+            r = urllib.request.urlopen(f"http://127.0.0.1:{PORT}/health", timeout=2)
+            if json.loads(r.read()).get("status") == "ok":
+                return True
+        except:
+            pass
+        time.sleep(1)
+    return False
+
+def send_request(prompt, max_tokens=N_GEN):
+    """Send chat completion, measure generation throughput."""
+    body = json.dumps({
+        "model": "frank-dragoon",
+        "messages": [{"role": "user", "content": prompt}],
+        "max_tokens": max_tokens,
+        "stream": False,
+        "temperature": 0.7,
+        "top_p": 0.8
+    }).encode()
+    
+    t0 = time.time()
+    req = urllib.request.Request(
+        f"http://127.0.0.1:{PORT}/v1/chat/completions",
+        data=body,
+        headers={"Content-Type": "application/json"},
+        method="POST"
+    )
+    r = urllib.request.urlopen(req, timeout=1200)
+    resp = json.loads(r.read())
+    wall = time.time() - t0
+    
+    usage = resp.get("usage", {})
+    pt = usage.get("prompt_tokens", 0)
+    gt = usage.get("completion_tokens", 0)
+    gtps = gt / wall if wall > 0 else 0
+    return pt, gt, wall, gtps
+
+def load_and_extend_prompt():
+    """Load prompt and extend to ~8K tokens if needed."""
+    with open(PROMPT_FILE) as f:
+        text = f.read()
+    
+    # Count approximate tokens (rough: ~4 chars per token for code)
+    approx_tokens = len(text) / 4.0
+    needed = 8200
+    
+    if approx_tokens < needed:
+        repeats = needed // max(int(approx_tokens), 1) + 1
+        text = (text + "\n") * repeats
+        words = text.split()[:needed]
+        text = " ".join(words)
+    
+    return text
+
+def main():
+    tb_values = [int(x) for x in sys.argv[1:]] if len(sys.argv) > 1 else [16, 32, 64, 128]
+    results = []
+    
+    prompt = load_and_extend_prompt()
+    n_words = len(prompt.split())
+    print(f"Prompt: {n_words} words (~{n_words} tokens), {len(prompt)} chars\n", flush=True)
+    
+    for tb in tb_values:
+        print(f"\n{'='*60}")
+        print(f"threads-batch = {tb}")
+        print(f"{'='*60}", flush=True)
+        
+        kill_all()
+        print("  Starting server...", flush=True)
+        
+        lib_path = ENV.get("LD_LIBRARY_PATH", "")
+        cmd = [
+            "/usr/bin/env",
+            "HSA_OVERRIDE_GFX_VERSION=11.5.1",
+            "HIP_VISIBLE_DEVICES=0",
+            f"LD_LIBRARY_PATH={lib_path}",
+            f"ROCM_PATH={ROCM_PATH}",
+            SERVE, "--model", MODEL, "--port", str(PORT), "--jinja",
+            "--device", "ROCm0", "--gpu-layers", "999", "--fit", "off",
+            "--threads", "16", "--threads-batch", str(tb),
+            "--parallel", "2", "--ctx-size", "131072",
+            "--batch-size", "4096", "--ubatch-size", "4096",
+            "--flash-attn", "on",
+            "--cache-type-k", "f16", "--cache-type-v", "f16",
+            "--cache-prompt", "--cache-idle-slots", "--metrics"
+        ]
+        
+        srv = subprocess.Popen(cmd, env=ENV, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, text=True)
+        
+        ready = wait_ready()
+        if not ready:
+            print("  FAILED: server did not become ready", flush=True)
+            srv.terminate()
+            srv.wait()
+            for line in (srv.stdout.readlines() or [])[-20:]:
+                print(f"  LOG: {line.rstrip()}", flush=True)
+            continue
+        
+        print("  Server ready.", flush=True)
+        
+        # Warmup (small request)
+        try:
+            send_request("Hi", 16)
+        except Exception as e:
+            print(f"  Warmup failed: {e}", flush=True)
+            srv.terminate()
+            srv.wait()
+            continue
+        
+        # Benchmark
+        print(f"  Generating {N_GEN} tokens...", flush=True)
+        try:
+            pt, gt, wall, gtps = send_request(prompt, N_GEN)
+            print(f"  {gt}/{N_GEN} gen tokens in {wall:.1f}s = {gtps:.1f} tok/s")
+            print(f"  Prompt tokens: {pt}")
+            results.append({"tb": tb, "wall": wall, "gtps": gtps, "gt": gt, "pt": pt})
+        except Exception as e:
+            print(f"  FAILED: {e}", flush=True)
+        
+        srv.terminate()
+        srv.wait()
+        time.sleep(2)
+    
+    # Summary
+    print(f"\n{'='*60}")
+    print("SUMMARY")
+    print(f"{'='*60}")
+    for r in results:
+        print(f"  tb={r['tb']:>3}: {r['gt']} gen tokens, {r['wall']:.1f}s, {r['gtps']:.1f} tok/s")
+    
+    if results:
+        best = max(results, key=lambda r: r['gtps'])
+        print(f"\nBest: tb={best['tb']} at {best['gtps']:.1f} tok/s")
+    
+    with open("/tmp/bench_decode_results.txt", "w") as f:
+        f.write("tb,gen_tokens,wall_s,gen_tps,prompt_tokens\n")
+        for r in results:
+            f.write(f"{r['tb']},{r['gt']},{r['wall']:.1f},{r['gtps']:.1f},{r['pt']}\n")
+    
+    print(f"\nResults: /tmp/bench_decode_results.txt")
+
+if __name__ == "__main__":
+    main()

scripts/.AGENTTRASH/bench-ngram-mod.py.ik-llama.cpp

@@ -0,0 +1,268 @@
+#!/usr/bin/env python3
+"""
+Benchmark n-gram speculative decoding vs no-spec for frank-dragoon.
+
+Tests prompt-processing throughput with 16K token prompts (manageable request size).
+Code-heavy prompt (high n-gram redundancy) vs prose prompt (low redundancy).
+
+Usage:
+    # Generate prompts: python3 scripts/bench-ngram-mod.py generate /tmp/prompts/
+    # Run: python3 scripts/bench-ngram-mod.py /tmp/prompts/
+"""
+
+import json
+import os
+import sys
+import time
+import subprocess
+import urllib.request
+import urllib.error
+from pathlib import Path
+
+MODEL = "/home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX/Qwen3.8-Flash-Next-Q4_0-ROCmFP4-STRIX.gguf"
+CHAT_TEMPLATE = "/home/dank/serverAppConfigs/scripts/chat-template.jinja"
+BUILD_DIR = "/home/dank/GitPackages/ROCmFPX/build-qwen38/bin"
+LLAMA_BIN = os.path.join(BUILD_DIR, "llama-server")
+
+# 16K tokens ~= 64KB text
+TARGET_PROMPT_TOKENS = 16000
+TOKEN_CHAR_RATIO = 4
+TARGET_PROMPT_BYTES = TARGET_PROMPT_TOKENS * TOKEN_CHAR_RATIO
+
+CONTEXT = 65536
+BATCH = 4096
+UBATCH = 4096
+THREADS = 16
+THREAD_BATCH = 32
+NGRAM_N_MAX = 24
+NGRAM_N_MIN = 4
+TEST_TOKENS = 128
+SERVER_WAIT = 300
+
+
+def start_server(port, spec_type):
+    cmd = [
+        LLAMA_BIN,
+        "--model", MODEL,
+        "--chat-template-file", CHAT_TEMPLATE,
+        "--jinja",
+        "--device", "ROCm0",
+        "--gpu-layers", "999",
+        "--parallel", "1",
+        "--ctx-size", str(CONTEXT),
+        "--batch-size", str(BATCH),
+        "--ubatch-size", str(UBATCH),
+        "--fit", "off",
+        "--flash-attn", "on",
+        "--cache-type-k", "f16",
+        "--cache-type-v", "f16",
+        "--threads", str(THREADS),
+        "--threads-batch", str(THREAD_BATCH),
+        "--cache-prompt",
+        "--cache-idle-slots",
+        "--metrics",
+        "--host", "127.0.0.1",
+        "--port", str(port),
+        "--temp", "0",
+    ]
+    if spec_type == "ngram-mod":
+        cmd.extend([
+            "--spec-type", "ngram-mod",
+            "--spec-ngram-mod-n-max", str(NGRAM_N_MAX),
+            "--spec-ngram-mod-n-min", str(NGRAM_N_MIN),
+        ])
+    else:
+        cmd.extend(["--spec-type", "none"])
+
+    env = os.environ.copy()
+    env["ROCM_PATH"] = "/opt/rocm"
+    env["LD_LIBRARY_PATH"] = f"{BUILD_DIR}:/opt/rocm/lib:/opt/rocm/lib/rocm_sysdeps/lib:/opt/rocm/lib/llvm/lib"
+    env["HSA_OVERRIDE_GFX_VERSION"] = "11.5.1"
+    env["HIP_VISIBLE_DEVICES"] = "0"
+
+    proc = subprocess.Popen(cmd, env=env, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+
+    print(f"  Waiting for server on port {port} (spec={spec_type})...")
+    for i in range(SERVER_WAIT):
+        try:
+            req = urllib.request.urlopen(f"http://127.0.0.1:{port}/health", timeout=2)
+            resp = json.loads(req.read().decode())
+            if resp.get("status") == "ok":
+                print(f"  Server ready after {i+1}s")
+                return proc
+        except:
+            time.sleep(1)
+
+    proc.terminate()
+    out, err = proc.communicate()
+    print(f"ERROR: Server failed to start in {SERVER_WAIT}s")
+    print(err.decode()[-2000:])
+    sys.exit(1)
+
+
+def run_test(prompt_text, spec_type, port):
+    """Send a request and extract prompt processing metrics."""
+    data = json.dumps({
+        "model": "frank-dragoon",
+        "messages": [{"role": "user", "content": prompt_text}],
+        "max_tokens": TEST_TOKENS,
+        "stream": False,
+        "temperature": 0,
+    }).encode()
+
+    req = urllib.request.Request(
+        f"http://127.0.0.1:{port}/v1/chat/completions",
+        data=data,
+        headers={"Content-Type": "application/json"},
+    )
+
+    start = time.monotonic()
+    resp = urllib.request.urlopen(req, timeout=600)
+    elapsed = time.monotonic() - start
+
+    result = json.loads(resp.read().decode())
+    timings = result.get("timings", {})
+    usage = result.get("usage", {})
+
+    return {
+        "prompt_tokens": usage.get("prompt_tokens", 0),
+        "prompt_ms": timings.get("prompt_ms", 0),
+        "prompt_per_second": timings.get("prompt_per_second", 0),
+        "prompt_per_token_ms": timings.get("prompt_per_token_ms", 0),
+        "predicted_per_second": timings.get("predicted_per_second", 0),
+        "total_time_s": elapsed,
+        "cache_n": timings.get("cache_n", 0),
+    }
+
+
+def main():
+    if len(sys.argv) < 2:
+        print(f"Usage: {sys.argv[0]} <prompt_dir>")
+        sys.exit(1)
+
+    prompt_dir = Path(sys.argv[1])
+    prompt_dir.mkdir(parents=True, exist_ok=True)
+
+    code_prompt_file = prompt_dir / "prompt_code.txt"
+    prose_prompt_file = prompt_dir / "prompt_prose.txt"
+
+    # Generate prompts if they don't exist
+    if not code_prompt_file.exists() or not prose_prompt_file.exists():
+        print("Generating prompts...")
+        # Generate deterministic prompts
+        # Code prompt: structured algorithms + data generation + config schemas
+        code_lines = []
+        for i in range(50):
+            code_lines.append(f"# Algorithm {i}\n")
+            code_lines.append(f"def algo_{i}(x, y):\n")
+            code_lines.append(f"    \"\"\"Algorithm {i} processing.\"\"\"\n")
+            code_lines.append(f"    result = 0\n")
+            code_lines.append(f"    for j in range({i * 10}):\n")
+            code_lines.append(f"        result += x * y + j\n")
+            code_lines.append(f"    return result\n\n")
+        code_text = "".join(code_lines)
+        # Pad/truncate to target
+        while len(code_text) < TARGET_PROMPT_BYTES:
+            code_text += "# Additional algorithm block\n"
+            code_text += f"def extra_{len(code_text)//100}():\n"
+            code_text += "    x = 1\n"
+            code_text += "    y = 2\n"
+            code_text += "    return x + y\n\n"
+        code_text = code_text[:TARGET_PROMPT_BYTES]
+
+        # Prose prompt: historical/scientific/philosophical text
+        prose_text = ""
+        topics = [
+            "The Renaissance brought profound transformation to European civilization. Artists and scholars pushed the boundaries of human expression.",
+            "Quantum mechanics describes the behavior of matter and energy at atomic scales. The uncertainty principle limits measurement precision.",
+            "Ethical philosophy grapples with questions of right and wrong. Utilitarianism judges actions by their consequences and the happiness they produce.",
+            "Mountains rise like ancient sentinels, their peaks lost in clouds that swirl and dance across the sky above the valleys below.",
+            "The ocean whispers secrets to the shore, each wave carrying fragments of distant lands across the water before retreating back to sea.",
+        ]
+        for _ in range(500):
+            prose_text += f"{topics[len(prose_text) % len(topics)]} "
+        prose_text = prose_text[:TARGET_PROMPT_BYTES]
+
+        code_prompt_file.write_text(code_text)
+        prose_prompt_file.write_text(prose_text)
+        print(f"  Code: {code_prompt_file.stat().st_size:,} bytes")
+        print(f"  Prose: {prose_prompt_file.stat().st_size:,} bytes")
+
+    print("=" * 60)
+    print("  N-gram Mod Benchmark — frank-dragoon")
+    print(f"  STRIX ROCmFP4 · 64K context · 16K prompts")
+    print("=" * 60)
+
+    results = []
+    port_base = 7772
+    port_ngram = 7773
+
+    tests = [
+        ("code", "none", port_base, code_prompt_file),
+        ("prose", "none", port_ngram, prose_prompt_file),
+        ("code", "ngram-mod", port_base, code_prompt_file),
+        ("prose", "ngram-mod", port_ngram, prose_prompt_file),
+    ]
+
+    for prompt_type, spec_type, port, pfile in tests:
+        print(f"\n=== {spec_type} ({prompt_type}) ===")
+        print(f"  File: {pfile} ({pfile.stat().st_size:,} bytes)")
+        print(f"  Spec: {spec_type}")
+        if spec_type == "ngram-mod":
+            print(f"  n_max={NGRAM_N_MAX}, n_min={NGRAM_N_MIN}")
+
+        proc = start_server(port, spec_type)
+
+        try:
+            # Warm-up
+            print("  Warm-up...")
+            run_test("Hello test", spec_type, port)
+
+            # Full prompt
+            print(f"  Sending {TARGET_PROMPT_TOKENS} token prompt...")
+            with open(pfile) as f:
+                prompt_text = f.read()
+            result = run_test(prompt_text, spec_type, port)
+
+            tps = result["prompt_per_second"]
+            print(f"  Tokens:  {result['prompt_tokens']}")
+            print(f"  Prompt:  {result['prompt_ms']:.0f}ms")
+            print(f"  TPS:     {tps:.1f} tok/s")
+            print(f"  Total:   {result['total_time_s']:.1f}s")
+
+            results.append({
+                "prompt_type": prompt_type,
+                "spec_type": spec_type,
+                "prompt_tokens": result["prompt_tokens"],
+                "prompt_ms": result["prompt_ms"],
+                "tps": tps,
+                "total_time_s": result["total_time_s"],
+            })
+
+        finally:
+            proc.terminate()
+            try:
+                proc.wait(timeout=5)
+            except:
+                proc.kill()
+
+    # Summary
+    print("\n" + "=" * 60)
+    print("  RESULTS SUMMARY")
+    print("=" * 60)
+
+    for ptype in ["code", "prose"]:
+        baseline = next((r for r in results if r["prompt_type"] == ptype and r["spec_type"] == "none"), None)
+        ngram = next((r for r in results if r["prompt_type"] == ptype and r["spec_type"] == "ngram-mod"), None)
+        if baseline and ngram:
+            gain = ((ngram["tps"] - baseline["tps"]) / baseline["tps"]) * 100 if baseline["tps"] > 0 else 0
+            print(f"\n{ptype.upper()} PROMPT:")
+            print(f"  Baseline TPS: {baseline['tps']:.1f} tok/s ({baseline['prompt_ms']:.0f}ms)")
+            print(f"  N-gram TPS:   {ngram['tps']:.1f} tok/s ({ngram['prompt_ms']:.0f}ms)")
+            print(f"  Speedup:      {gain:+.1f}%")
+
+    print("\n" + "=" * 60)
+
+
+if __name__ == "__main__":
+    main()

scripts/.AGENTTRASH/bench-ngram-mod.sh.ik-llama.cpp

@@ -0,0 +1,304 @@
+#!/usr/bin/env bash
+# Benchmark n-gram speculative decoding vs no-spec for frank-dragoon.
+#
+# This tests prompt-processing throughput at 64k context with two distinct
+# prompts: one code-heavy and one prose-heavy. Uses llama-server on scratch
+# ports with the OpenAI-compatible API to measure prompt_eval_duration_ms.
+#
+# Run on Dankclaw after stopping the production service:
+#   sudo systemctl stop frank-dragoon
+#   ./scripts/bench-ngram-mod.sh
+#   sudo systemctl start frank-dragoon
+
+set -euo pipefail
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-dragoon.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a; source "$ENV_FILE"; set +a
+fi
+
+: "${LLAMA_BIN:=/home/dank/GitPackages/ROCmFPX/build-qwen38/bin/llama-server}"
+: "${MODEL_DIR:=/home/dank/models/kingjones-Qwen3.8-Flash-Next-ROCmFP4-STRIX}"
+: "${MODEL_FILE:=Qwen3.8-Flash-Next-Q4_0-ROCmFP4-STRIX.gguf}"
+: "${CHAT_TEMPLATE_FILE:=$SCRIPT_DIR/chat-template.jinja}"
+: "${CHAT_TEMPLATE_KWARGS:={}}"
+: "${BATCH_SIZE:=4096}"
+: "${UBATCH_SIZE:=4096}"
+: "${CTX_SIZE:=65536}"
+: "${NUM_THREADS:=16}"
+: "${THREAD_BATCH:=32}"
+: "${CACHE_TYPE_K:=f16}"
+: "${CACHE_TYPE_V:=f16}"
+: "${FIT:=off}"
+: "${TEMPERATURE:=0.7}"
+: "${TOP_P:=0.8}"
+: "${TOP_K:=20}"
+: "${MIN_P:=0.0}"
+: "${REASONING:=on}"
+: "${REASONING_FORMAT:=deepseek}"
+
+MODEL="$MODEL_DIR/$MODEL_FILE"
+HOSTNAME=$(hostname 2>/dev/null || echo "dankclaw")
+
+# Prompt files (generated by generate-prompts.py or passed via args)
+PROMPT_CODE="${1:-}"
+PROMPT_PROSE="${2:-}"
+
+if [[ -z "$PROMPT_CODE" || -z "$PROMPT_PROSE" ]]; then
+    echo "ERROR: Need two prompt file paths."
+    echo "Usage: $0 <prompt_code.txt> <prompt_prose.txt>"
+    echo "Generate with: python3 scripts/generate-prompts.py"
+    exit 1
+fi
+
+if [[ ! -r "$MODEL" ]]; then
+    echo "missing or unreadable model: $MODEL" >&2
+    exit 1
+fi
+
+SERVER_DIR="$(cd -- "$(dirname -- "$LLAMA_BIN")" && pwd)"
+ROCM_PATH="${ROCM_PATH:-/opt/rocm}"
+LIBRARY_PATH="$SERVER_DIR:$ROCM_PATH/lib:$ROCM_PATH/lib/rocm_sysdeps/lib:$ROCM_PATH/lib/llvm/lib${LD_LIBRARY_PATH:+:$LD_LIBRARY_PATH}"
+
+# Scratch ports
+PORT_NGRAM=7771
+PORT_BASELINE=7772
+
+cleanup() {
+    echo "Cleaning up servers..."
+    # Kill any leftover llama-server on our ports
+    for port in $PORT_NGRAM $PORT_BASELINE; do
+        fuser -k "$port"/tcp 2>/dev/null || true
+    done
+}
+trap cleanup EXIT
+
+wait_for_server() {
+    local port=$1
+    local max_wait=120
+    local elapsed=0
+    while (( elapsed < max_wait )); do
+        if curl -s "http://127.0.0.1:$port/health" | grep -q '"running"'; then
+            return 0
+        fi
+        sleep 1
+        (( elapsed++ ))
+    done
+    echo "ERROR: Server on port $port did not start within ${max_wait}s" >&2
+    return 1
+}
+
+get_prompt_tokens() {
+    local file=$1
+    # Count tokens approximately (1 token ~ 4 chars for English/code)
+    wc -c < "$file" | awk '{printf "%d", $1/4}'
+}
+
+run_single_test() {
+    local port=$1
+    local spec_type="$2"
+    local prompt_file=$3
+    local label=$4
+    local ngram_n_max="${5:-24}"
+    local ngram_n_min="${6:-4}"
+    
+    echo "=== $label ==="
+    echo "  spec-type: $spec_type"
+    echo "  ngram-mod n-max: $ngram_n_max (if enabled)"
+    echo "  ngram-mod n-min: $ngram_n_min (if enabled)"
+    echo "  prompt: $prompt_file ($(wc -c < "$prompt_file") bytes)"
+    
+    # Build command
+    local cmd=(
+        /usr/bin/env
+        ROCM_PATH="$ROCM_PATH"
+        HIP_VISIBLE_DEVICES=0
+        LD_LIBRARY_PATH="$LIBRARY_PATH"
+        HSA_OVERRIDE_GFX_VERSION="${HSA_OVERRIDE_GFX_VERSION:-11.5.1}"
+        "$LLAMA_BIN"
+        --model "$MODEL"
+        --chat-template-file "$CHAT_TEMPLATE_FILE"
+        --chat-template-kwargs "$CHAT_TEMPLATE_KWARGS"
+        --host 127.0.0.1
+        --port "$port"
+        --jinja
+        --device ROCm0
+        --gpu-layers 999
+        --parallel 1
+        --ctx-size "$CTX_SIZE"
+        --batch-size "$BATCH_SIZE"
+        --ubatch-size "$UBATCH_SIZE"
+        --fit "$FIT"
+        --flash-attn on
+        --cache-type-k "$CACHE_TYPE_K"
+        --cache-type-v "$CACHE_TYPE_V"
+        --threads "$NUM_THREADS"
+        --threads-batch "$THREAD_BATCH"
+        --cache-prompt
+        --cache-idle-slots
+        --metrics
+        --temp "$TEMPERATURE"
+        --top-p "$TOP_P"
+        --top-k "$TOP_K"
+        --min-p "$MIN_P"
+        --reasoning "$REASONING"
+        --reasoning-format "$REASONING_FORMAT"
+        --reasoning-budget -1
+    )
+    
+    # Add spec flags
+    if [[ "$spec_type" == "ngram-mod" ]]; then
+        cmd+=(
+            --spec-type "ngram-mod"
+            --spec-ngram-mod-n-max "$ngram_n_max"
+            --spec-ngram-mod-n-min "$ngram_n_min"
+        )
+    else
+        cmd+=(
+            --spec-type "none"
+        )
+    fi
+    
+    # Start server with stderr to log
+    local log_file="/tmp/ngram-bench-${label//[^a-zA-Z0-9]/-}.log"
+    echo "  Starting server (log: $log_file)..."
+    
+    "${cmd[@]}" 2> "$log_file" &
+    local server_pid=$!
+    
+    if ! wait_for_server "$port"; then
+        echo "ERROR: Server failed to start" >&2
+        kill "$server_pid" 2>/dev/null || true
+        return 1
+    fi
+    
+    echo "  Server ready."
+    
+    # Send prompt via API
+    echo "  Sending prompt..."
+    local prompt_text
+    prompt_text=$(cat "$prompt_file")
+    
+    local response
+    response=$(curl -s -X POST "http://127.0.0.1:$port/v1/completions" \
+        -H "Content-Type: application/json" \
+        -d "{
+            \"model\": \"frank-dragoon\",
+            \"prompt\": \"$prompt_text\",
+            \"max_tokens\": 128,
+            \"temperature\": 0,
+            \"stream\": false
+        }")
+    
+    # Extract metrics
+    local prompt_tokens prompt_eval_duration_ms total_duration_ms
+    prompt_tokens=$(echo "$response" | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['prompt_eval_count'])" 2>/dev/null || echo "0")
+    prompt_eval_duration_ms=$(echo "$response" | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['prompt_eval_duration_ms'])" 2>/dev/null || echo "0")
+    total_duration_ms=$(echo "$response" | python3 -c "import sys,json; d=json.load(sys.stdin); print(d['total_duration_ms'])" 2>/dev/null || echo "0")
+    
+    # Calculate throughput
+    local prompt_tps=0
+    if [[ "$prompt_eval_duration_ms" -gt 0 ]]; then
+        prompt_tps=$(python3 -c "print(f'{($prompt_tokens / $prompt_eval_duration_ms) * 1000:.1f}')")
+    fi
+    
+    echo "  Prompt tokens:  $prompt_tokens"
+    echo "  Prompt eval:    ${prompt_eval_duration_ms}ms"
+    echo "  Prompt TPS:     $prompt_tps tok/s"
+    echo "  Total duration: ${total_duration_ms}ms"
+    
+    # Kill server
+    kill "$server_pid" 2>/dev/null || true
+    sleep 2
+    
+    echo "  Done."
+    echo "---"
+    
+    # Output structured results for parsing
+    echo "RESULT|$label|$prompt_file|$prompt_tokens|$prompt_eval_duration_ms|$total_duration_ms|$prompt_tps"
+}
+
+echo "╔══════════════════════════════════════════════════════════╗"
+echo "║  N-gram Mod Benchmark — frank-dragoon             ║"
+echo "║  STRIX ROCmFP4 · 64k context · two prompts             ║"
+echo "╚══════════════════════════════════════════════════════════╝"
+echo ""
+echo "Host: $HOSTNAME"
+echo "Model: $MODEL"
+echo "Build: $(basename "$LLAMA_BIN")"
+echo "Context: $CTX_SIZE"
+echo ""
+
+# Run baseline (no spec)
+echo "=== BASELINE (no speculative decoding) ==="
+echo ""
+
+BASELINE_CODE_RESULT=$(run_single_test $PORT_BASELINE "none" "$PROMPT_CODE" "Baseline-Code" 24 4)
+BASELINE_PROSE_RESULT=$(run_single_test $PORT_NGRAM "none" "$PROMPT_PROSE" "Baseline-Prose" 24 4)
+
+echo ""
+echo "=== NGRAM-MOD (speculative decoding enabled) ==="
+echo ""
+
+# Run n-gram mod
+NGRAM_CODE_RESULT=$(run_single_test $PORT_NGRAM "ngram-mod" "$PROMPT_CODE" "Ngram-Code" 24 4)
+NGRAM_PROSE_RESULT=$(run_single_test $PORT_BASELINE "ngram-mod" "$PROMPT_PROSE" "Ngram-Prose" 24 4)
+
+echo ""
+echo "╔══════════════════════════════════════════════════════════╗"
+echo "║  RESULTS SUMMARY                                       ║"
+echo "╚══════════════════════════════════════════════════════════╝"
+echo ""
+
+# Parse and display results
+python3 << 'PYEOF'
+import sys
+
+results = []
+for line in sys.stdin:
+    line = line.strip()
+    if not line.startswith("RESULT|"):
+        continue
+    parts = line.split("|")
+    if len(parts) != 8:
+        continue
+    label, prompt_file, prompt_tokens, prompt_eval_ms, total_ms, tps = parts[1], parts[2], int(parts[3]), int(parts[4]), int(parts[5]), float(parts[6])
+    results.append({
+        'label': label,
+        'prompt_file': prompt_file,
+        'prompt_tokens': prompt_tokens,
+        'prompt_eval_ms': prompt_eval_ms,
+        'total_ms': total_ms,
+        'tps': tps
+    })
+
+# Compare baseline vs ngram for each prompt type
+for code_result in results:
+    if not code_result['label'].startswith('Ngram-'):
+        continue
+    prompt_type = code_result['label'].replace('Ngram-', '').replace('Ngram', 'Baseline').replace('-', '-')
+    baseline = next((r for r in results if r['label'] == 'Baseline-' + prompt_type), None)
+    if not baseline:
+        continue
+    
+    spec = code_result['label'] == 'Ngram-' + prompt_type
+    
+    print(f"Prompt: {prompt_type}")
+    print(f"  Tokens:   {code_result['prompt_tokens']}")
+    if spec:
+        print(f"  Spec:     ngram-mod (n_max=24, n_min=4)")
+        print(f"  Prompt:   {code_result['prompt_eval_ms']}ms  |  {code_result['tps']:>10.1f} tok/s")
+        baseline_tps = baseline['tps']
+        if baseline_tps > 0:
+            improvement = ((code_result['tps'] - baseline_tps) / baseline_tps) * 100
+            print(f"  Speedup:  {improvement:+.1f}% vs baseline ({baseline_tps:.1f} tok/s)")
+    else:
+        print(f"  Spec:     none (baseline)")
+        print(f"  Prompt:   {baseline['prompt_eval_ms']}ms  |  {baseline['tps']:>10.1f} tok/s")
+    print()
+PYEOF
+
+echo ""
+echo "Raw data lines above (RESULT|... format) can be parsed for automation."
+echo ""

scripts/.AGENTTRASH/bench-spec-decode.py.ik-llama.cpp

@@ -0,0 +1,229 @@
+#!/usr/bin/env python3
+"""Benchmark decode throughput across speculative decoding configs.
+
+Sweeps 4 configs: none, ngram-mod, draft-mtp, draft-mtp+ngram-mod.
+Each config generates 16k tokens from a minimal prompt at temp 0.
+
+Runs ON the target host (Dankclaw). Service management uses local sudo.
+Usage:
+    python3 bench-spec-decode.py [--max-tokens N] [--host H] [--port P]
+"""
+import json
+import subprocess
+import sys
+import time
+import urllib.request
+import urllib.error
+
+SERVICE = "frank-dragoon"
+ENV_FILE = "/home/dank/serverAppConfigs/scripts/frank-dragoon.env"
+ALIAS = "frank-dragoon"
+DEFAULT_HOST = "localhost"
+DEFAULT_PORT = 7770
+DEFAULT_MAX_TOKENS = 16384
+HEALTH_TIMEOUT = 1200  # 20 min for cold load
+HEALTH_INTERVAL = 5
+
+PROMPT = (
+    "Write a comprehensive, detailed essay about the complete history of "
+    "computing, from the earliest mechanical calculators through modern AI. "
+    "Cover every major era in detail, including key figures, machines, and "
+    "breakthroughs. Be as thorough as possible."
+)
+
+CONFIGS = [
+    ("none", "none"),
+    ("ngram-mod", "ngram-mod"),
+    ("draft-mtp", "draft-mtp"),
+    ("draft-mtp+ngram-mod", "draft-mtp,ngram-mod"),
+]
+
+
+def local(cmd):
+    """Run a command locally (the script runs on the target host)."""
+    r = subprocess.run(cmd, shell=True, capture_output=True, text=True, timeout=120)
+    if r.returncode != 0:
+        print(f"  WARNING: {cmd} -> exit {r.returncode}: {r.stderr.strip()}",
+              file=sys.stderr)
+    return r
+
+
+def sed_spec_type(value):
+    local(f"sudo sed -i 's/^SPEC_TYPE=.*/SPEC_TYPE={value}/' {ENV_FILE}")
+
+
+def wait_health(host, port, timeout=HEALTH_TIMEOUT):
+    start = time.time()
+    while time.time() - start < timeout:
+        try:
+            resp = urllib.request.urlopen(
+                f"http://{host}:{port}/health", timeout=10
+            )
+            if resp.status == 200:
+                return True
+        except (urllib.error.URLError, urllib.error.HTTPError, ConnectionError,
+                OSError):
+            pass
+        time.sleep(HEALTH_INTERVAL)
+    return False
+
+
+def benchmark(host, port, alias, max_tokens):
+    body = json.dumps({
+        "model": alias,
+        "messages": [{"role": "user", "content": PROMPT}],
+        "max_tokens": max_tokens,
+        "temperature": 0,
+        "stream": False,
+    }).encode()
+    req = urllib.request.Request(
+        f"http://{host}:{port}/v1/chat/completions",
+        data=body,
+        headers={"Content-Type": "application/json"},
+    )
+    t0 = time.time()
+    resp = urllib.request.urlopen(req, timeout=1200)
+    wall = time.time() - t0
+    data = json.loads(resp.read())
+    return data, wall
+
+
+def main():
+    import argparse
+    ap = argparse.ArgumentParser(description=__doc__)
+    ap.add_argument("--host", default=DEFAULT_HOST)
+    ap.add_argument("--port", type=int, default=DEFAULT_PORT)
+    ap.add_argument("--max-tokens", type=int, default=DEFAULT_MAX_TOKENS)
+    args = ap.parse_args()
+
+    # Read original SPEC_TYPE from the env file
+    r = local(f"grep '^SPEC_TYPE=' {ENV_FILE}")
+    original_spec = r.stdout.strip()
+    orig_val = (original_spec.split("=", 1)[1]
+                if "=" in original_spec else "draft-mtp,ngram-mod")
+    print(f"Original: {original_spec}")
+    print(f"Max tokens: {args.max_tokens}")
+    print(f"Configs: {[c[0] for c in CONFIGS]}")
+    print()
+
+    # Stop + mask the production service
+    print("Stopping + masking production service...")
+    local(f"sudo systemctl stop {SERVICE}")
+    local(f"sudo systemctl mask {SERVICE}")
+    time.sleep(2)
+
+    results = []
+    for name, spec_type in CONFIGS:
+        print(f"\n{'='*60}")
+        print(f"Config: {name} (SPEC_TYPE={spec_type})")
+        print(f"{'='*60}")
+
+        # Set SPEC_TYPE
+        sed_spec_type(spec_type)
+        print(f"Set SPEC_TYPE={spec_type}")
+
+        # Start the service
+        local(f"sudo systemctl unmask {SERVICE}")
+        local(f"sudo systemctl start {SERVICE}")
+        print("Starting service...")
+
+        # Wait for health
+        print(f"Waiting for health (up to {HEALTH_TIMEOUT}s)...")
+        if not wait_health(args.host, args.port):
+            print(f"FAILED: service did not become healthy for {name}")
+            results.append({
+                "config": name, "spec_type": spec_type,
+                "error": "health timeout",
+            })
+            local(f"sudo systemctl stop {SERVICE}")
+            local(f"sudo systemctl mask {SERVICE}")
+            continue
+
+        print("Healthy. Running benchmark...")
+
+        # Run benchmark
+        try:
+            data, wall = benchmark(
+                args.host, args.port, ALIAS, args.max_tokens
+            )
+        except Exception as e:
+            print(f"FAILED: {e}")
+            results.append({
+                "config": name, "spec_type": spec_type,
+                "error": str(e),
+            })
+            local(f"sudo systemctl stop {SERVICE}")
+            local(f"sudo systemctl mask {SERVICE}")
+            continue
+
+        timings = data.get("timings", {})
+        usage = data.get("usage", {})
+        pred_n = timings.get("predicted_n", usage.get("completion_tokens", 0))
+        pred_ms = timings.get("predicted_ms", 0)
+        pred_ps = timings.get("predicted_per_second", 0)
+        prompt_n = timings.get("prompt_n", usage.get("prompt_tokens", 0))
+        prompt_ms = timings.get("prompt_ms", 0)
+
+        print(f"  Generated:   {pred_n} tokens")
+        print(f"  Wall time:   {wall:.1f}s")
+        print(f"  Decode:      {pred_ps:.2f} tok/s")
+        print(f"  Prefill:     {prompt_n} tokens in {prompt_ms:.0f}ms"
+              f" ({prompt_n / max(prompt_ms, 1) * 1000:.1f} tok/s)")
+
+        results.append({
+            "config": name,
+            "spec_type": spec_type,
+            "predicted_tokens": pred_n,
+            "predicted_ms": pred_ms,
+            "predicted_per_second": pred_ps,
+            "prompt_tokens": prompt_n,
+            "prompt_ms": prompt_ms,
+            "wall_time": wall,
+        })
+
+        # Stop + mask between configs
+        local(f"sudo systemctl stop {SERVICE}")
+        local(f"sudo systemctl mask {SERVICE}")
+        time.sleep(2)
+
+    # Restore original SPEC_TYPE
+    sed_spec_type(orig_val)
+    print(f"\nRestoring SPEC_TYPE={orig_val}")
+    print("Unmasking + starting production service...")
+    local(f"sudo systemctl unmask {SERVICE}")
+    local(f"sudo systemctl start {SERVICE}")
+
+    # Health check
+    if wait_health(args.host, args.port):
+        print("Production service healthy.")
+    else:
+        print("WARNING: production service not healthy after restore!")
+
+    # Print results table
+    print(f"\n{'='*70}")
+    print("RESULTS")
+    print(f"{'='*70}")
+    print(f"{'Config':<30} {'Tokens':>8} {'Wall(s)':>10} {'Decode tok/s':>14} "
+          f"{'Error':>20}")
+    print(f"{'-'*30} {'-'*8} {'-'*10} {'-'*14} {'-'*20}")
+    for r in results:
+        if "error" in r:
+            print(f"{r['config']:<30} {'':>8} {'':>10} {'':>14} "
+                  f"{r['error']:>20}")
+        else:
+            print(f"{r['config']:<30} {r['predicted_tokens']:>8} "
+                  f"{r['wall_time']:>10.1f} {r['predicted_per_second']:>14.2f} "
+                  f"{'':>20}")
+    print(f"{'='*70}")
+
+    # Save JSON results
+    ts = time.strftime("%Y%m%d-%H%M%S")
+    out = f"/tmp/bench-spec-decode-{ts}.json"
+    with open(out, "w") as f:
+        json.dump({"results": results, "max_tokens": args.max_tokens,
+                   "timestamp": ts}, f, indent=2)
+    print(f"Results saved: {out}")
+
+
+if __name__ == "__main__":
+    main()

scripts/.AGENTTRASH/bench-vllm-corpus.py

@@ -0,0 +1,85 @@
+#!/usr/bin/env python3
+"""bench-vllm-corpus.py — build a code-shaped benchmark corpus from the repo.
+
+Why this exists: `vllm bench serve --dataset-name random` produces synthetic
+token soup, and speculative decoding accepts it nothing like real code — measured
+on frank-medium, random prompts accepted 2.9-3.6 tokens/update against the ~5.8
+the upstream reference reports on a code mix, which makes the random corpus
+under-report throughput by a wide margin and would pick the wrong SPEC depth.
+
+The prompts are the shape agents actually send: a repository artifact plus an
+instruction that requires reading it. Output length is fixed at bench time
+(`--custom-output-len`), so the corpus carries prompts only.
+
+Usage:
+    bench-vllm-corpus.py [repo-root] [out.jsonl]
+
+Then feed it to the endpoint (see scripts/bench-vllm-serve.sh, which passes the
+tokenizer the client needs and salts prompts so no run inherits a warm prefix
+cache). Methodology and the numbers these corpora produced are in
+serverAppConfigs-docs/LLM/frank-medium-radiance-mxfp4.md.
+"""
+
+from __future__ import annotations
+
+import json
+import pathlib
+import sys
+
+REPO = pathlib.Path(sys.argv[1] if len(sys.argv) > 1 else "/home/dank/serverAppConfigs")
+OUT = pathlib.Path(sys.argv[2] if len(sys.argv) > 2 else "/home/dank/bench/corpus-code.jsonl")
+
+TARGETS = [
+    "scripts/deploy-remote.sh",
+    "scripts/deploy-plan.py",
+    "scripts/deploy.sh",
+    "dankserver/frank-medium/radiance-entrypoint.sh",
+    "dankserver/frank-medium/quadlet/frank-medium-a.container",
+    "dankserver/frank-medium/proxy/affinity-proxy.py",
+    "dankserver/frank-medium/proxy/routing.py",
+    "tests/frank_medium_quadlet.bats",
+    "tests/deployment_scoping.bats",
+    "dankclaw/hermes/quadlet/hermes.container",
+    "dankclaw/anubis/quadlet/anubis.container",
+    "shared/prometheus/prometheus.yml",
+    "shared/prometheus/rules/llm-fleet.yml",
+    "shared/loki/loki-config.yaml",
+    "dankclaw/compose.yaml",
+    "dankserver/copyparty/quadlet/copyparty.container",
+]
+
+PROMPTS = [
+    "Read this repository artifact and summarise what it does, then list every "
+    "assumption it makes about the host it runs on.\n\n```\n{body}\n```",
+    "Here is a file from our homelab repository. Identify any bug, race or "
+    "missing error path, and show the minimal patch that fixes it.\n\n```\n{body}\n```",
+    "Explain this configuration to a new operator, then rewrite it with "
+    "comments that state the constraint each line protects.\n\n```\n{body}\n```",
+    "This file changed in a recent deploy. Write the changelog entry and a test "
+    "that would fail if the change regressed.\n\n```\n{body}\n```",
+]
+
+MAX_LINES = 220
+
+
+def main() -> int:
+    samples = []
+    for i, rel in enumerate(TARGETS):
+        path = REPO / rel
+        if not path.is_file():
+            continue
+        body = "\n".join(path.read_text(errors="replace").splitlines()[:MAX_LINES])
+        samples.append({"prompt": PROMPTS[i % len(PROMPTS)].format(body=body)})
+    if not samples:
+        print(f"no corpus sources found under {REPO}", file=sys.stderr)
+        return 1
+    OUT.parent.mkdir(parents=True, exist_ok=True)
+    with OUT.open("w") as fh:
+        for sample in samples:
+            fh.write(json.dumps(sample) + "\n")
+    print(f"wrote {len(samples)} prompts to {OUT}")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/.AGENTTRASH/bench-vllm-serve.sh

@@ -0,0 +1,63 @@
+#!/bin/bash
+# bench-vllm-serve.sh — concurrency sweep against a vLLM endpoint.
+#
+# Usage: bench-vllm-serve.sh <tag> <port> [concurrency ...]
+#   e.g. bench-vllm-serve.sh baseline 7770 1 4 8
+#
+# Runs `vllm bench serve` from inside the serving image (so the client matches
+# the server build) through an OpenAI-compatible endpoint, on the code corpus
+# scripts/bench-vllm-corpus.py writes.
+#
+# Two traps this script exists to encode, both of which produced silent garbage
+# during the 2026-09-16 frank-medium work:
+#
+#   1. The tokenizer must be passed explicitly and /models mounted. With only
+#      `--model frank-medium` the client tries to resolve that alias on
+#      HuggingFace and dies before sending a request — a run that looks like a
+#      benchmark and reports nothing.
+#   2. `--ignore-eos` is deliberate: it measures decode throughput at a fixed
+#      output length. Drop it when you care about real stop behaviour, but then
+#      do not compare the numbers with anything measured under it.
+#
+# Also note the corpora are code-shaped on purpose (see the generator's header):
+# synthetic random prompts misreport speculative acceptance badly.
+#
+# Methodology, and the numbers these runs produced on 2x R9700, are in
+# serverAppConfigs-docs/LLM/frank-medium-radiance-mxfp4.md.
+set -u
+
+TAG=${1:?usage: bench-vllm-serve.sh <tag> <port> [concurrency ...]}
+PORT=${2:?usage: bench-vllm-serve.sh <tag> <port> [concurrency ...]}
+shift 2
+CONCS=("$@")
+[ "${#CONCS[@]}" -eq 0 ] && CONCS=(1 4 8)
+
+IMG=${IMG:-localhost/radiance-vllm:0.9.3}
+MODELS_DIR=${MODELS_DIR:-/home/dank/models}
+TOK=${TOK:-/models/Qwen3.8-27B-Uncensored-MXFP4-awq}
+BENCH_DIR=${BENCH_DIR:-/home/dank/bench}
+CORPUS=${CORPUS:-$BENCH_DIR/corpus-code.jsonl}
+OUT=${OUT:-$BENCH_DIR/$TAG}
+mkdir -p "$OUT"
+
+if [ ! -f "$CORPUS" ]; then
+    echo "corpus $CORPUS is missing; run scripts/bench-vllm-corpus.py first" >&2
+    exit 1
+fi
+
+for c in "${CONCS[@]}"; do
+    echo "== $TAG conc=$c (port $PORT)"
+    podman run --rm --network=host -v "$MODELS_DIR":/models:ro -v "$BENCH_DIR":/bench:ro \
+        -e HF_HUB_OFFLINE=1 --entrypoint bash "$IMG" -lc "
+        vllm bench serve --backend openai-chat \
+          --base-url http://127.0.0.1:$PORT --endpoint /v1/chat/completions \
+          --model frank-medium --tokenizer $TOK \
+          --dataset-name custom --dataset-path /bench/$(basename "$CORPUS") \
+          --custom-output-len 512 --num-prompts 16 --max-concurrency $c \
+          --disable-shuffle --seed 0 --ignore-eos \
+          --percentile-metrics ttft,tpot --metric-percentiles 50,99 \
+          --disable-tqdm 2>&1 | grep -E 'Successful requests|Benchmark duration|Output token throughput|Total Token throughput|Mean TTFT|P50 TTFT|P50 TPOT|Acceptance rate|Acceptance length'
+    " 2>&1 | sed 's/^/  /'
+    echo
+done
+echo "results for $TAG written under $OUT"

scripts/.AGENTTRASH/chat-template.jinja.ik-llama-qwen-sharp

@@ -0,0 +1,453 @@
+{%- set template_version = "qwen3.8-froggeric-v22.4.0" %}
+{%- set _tool_format = tool_call_format if tool_call_format is defined else 'xml' %}
+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- set add_vision_id = add_vision_id if add_vision_id is defined else false %}
+{%- set enable_thinking = enable_thinking if enable_thinking is defined else true %}
+{%- set auto_disable_thinking_with_tools = auto_disable_thinking_with_tools if auto_disable_thinking_with_tools is defined else false %}
+{%- if preserve_reasoning is defined and preserve_reasoning is not none %}
+    {%- set _preserve_thinking = preserve_reasoning %}
+{%- elif preserve_thinking is defined and preserve_thinking is not none %}
+    {%- set _preserve_thinking = preserve_thinking %}
+{%- else %}
+    {%- set _preserve_thinking = true %}
+{%- endif %}
+{%- set max_tool_arg_chars = max_tool_arg_chars if max_tool_arg_chars is defined else 0 %}
+{%- set max_tool_response_chars = max_tool_response_chars if max_tool_response_chars is defined else 0 %}
+{%- set _default_reasoning_effort = 'medium' %}
+{%- set _has_tools = (tools is defined and tools and tools is iterable and tools is not mapping) %}
+{%- set _effort_raw = (reasoning_effort | string | lower) if reasoning_effort is defined and reasoning_effort is not none else _default_reasoning_effort %}
+{%- set _initial_thinking = enable_thinking %}
+{%- if _effort_raw in ('none', 'off') %}
+    {%- set _initial_thinking = false %}
+    {%- set _initial_effort = 'medium' %}
+{%- elif _effort_raw in ('minimal', 'low') %}
+    {%- set _initial_effort = 'low' %}
+{%- elif _effort_raw in ('high', 'xhigh', 'max', 'ultracode', 'extreme') %}
+    {%- set _initial_effort = 'xhigh' %}
+{%- else %}
+    {%- set _initial_effort = 'medium' %}
+{%- endif %}
+{%- set ns_state = namespace(thinking=_initial_thinking, effort=_initial_effort) %}
+{%- if auto_disable_thinking_with_tools and _has_tools %}
+    {%- set ns_state.thinking = false %}
+{%- endif %}
+{%- for msg in messages %}
+    {%- if msg.role == 'system' or msg.role == 'developer' or msg.role == 'user' %}
+        {%- if msg.content is string %}
+            {%- if '<|think_off|>' in msg.content %}
+                {%- set ns_state.thinking = false %}
+            {%- elif '<|think_on|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+            {%- elif '<|think_xhigh|>' in msg.content or '<|think_high|>' in msg.content or '<|think_ultracode|>' in msg.content or '<|think_extreme|>' in msg.content or '<|think_max|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+                {%- set ns_state.effort = 'xhigh' %}
+            {%- elif '<|think_low|>' in msg.content or '<|think_minimal|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+                {%- set ns_state.effort = 'low' %}
+            {%- elif '<|think_medium|>' in msg.content %}
+                {%- set ns_state.thinking = true %}
+                {%- set ns_state.effort = 'medium' %}
+            {%- endif %}
+        {%- elif msg.content is iterable and msg.content is not mapping %}
+            {%- for item in msg.content %}
+                {%- if item is string %}
+                    {%- set _item_text = item %}
+                {%- elif item is mapping and 'text' in item and item.text is string %}
+                    {%- set _item_text = item.text %}
+                {%- else %}
+                    {%- set _item_text = '' %}
+                {%- endif %}
+                {%- if _item_text %}
+                    {%- if '<|think_off|>' in _item_text %}
+                        {%- set ns_state.thinking = false %}
+                    {%- elif '<|think_on|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                    {%- elif '<|think_xhigh|>' in _item_text or '<|think_high|>' in _item_text or '<|think_ultracode|>' in _item_text or '<|think_extreme|>' in _item_text or '<|think_max|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                        {%- set ns_state.effort = 'xhigh' %}
+                    {%- elif '<|think_low|>' in _item_text or '<|think_minimal|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                        {%- set ns_state.effort = 'low' %}
+                    {%- elif '<|think_medium|>' in _item_text %}
+                        {%- set ns_state.thinking = true %}
+                        {%- set ns_state.effort = 'medium' %}
+                    {%- endif %}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- set reasoning_instructions = '' %}
+{%- if ns_state.thinking %}
+    {%- if ns_state.effort == 'xhigh' %}
+        {%- set reasoning_instructions = 'Reasoning effort is set to xhigh. Please think carefully through the task, validate key assumptions, consider plausible alternatives, and prioritize correctness, consistency, and clarity in the final answer.' %}
+    {%- elif ns_state.effort == 'low' %}
+        {%- set reasoning_instructions = 'Reasoning effort is set to low. Keep your thinking brief and focused, moving directly to the conclusion without unnecessary elaboration.' %}
+    {%- endif %}
+{%- endif %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if item is mapping %}
+                {%- if item.type == 'image' or 'image' in item or 'image_url' in item %}
+                    {%- if is_system_content %}
+                        {{- raise_exception('System message cannot contain images.') }}
+                    {%- endif %}
+                    {%- if do_vision_count %}
+                        {%- set image_count.value = image_count.value + 1 %}
+                    {%- endif %}
+                    {%- if add_vision_id %}
+                        {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                    {%- endif %}
+                    {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+                {%- elif item.type == 'video' or 'video' in item %}
+                    {%- if is_system_content %}
+                        {{- raise_exception('System message cannot contain videos.') }}
+                    {%- endif %}
+                    {%- if do_vision_count %}
+                        {%- set video_count.value = video_count.value + 1 %}
+                    {%- endif %}
+                    {%- if add_vision_id %}
+                        {{- 'Video ' ~ video_count.value ~ ': ' }}
+                    {%- endif %}
+                    {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+                {%- elif 'text' in item %}
+                    {{- item.text }}
+                {%- else %}
+                    {{- raise_exception('Unexpected item type in content.') }}
+                {%- endif %}
+            {%- else %}
+                {{- item | string }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- set head = namespace(count=0, seen_non_system=false) %}
+{%- for message in messages %}
+    {%- set _is_sys = (message.role == 'system' or message.role == 'developer') %}
+    {%- if _is_sys and not head.seen_non_system %}
+        {%- set head.count = head.count + 1 %}
+    {%- else %}
+        {%- set head.seen_non_system = true %}
+    {%- endif %}
+{%- endfor %}
+{%- set sys_state = namespace(content='') %}
+{%- for message in messages[:head.count] %}
+    {%- set _part = render_content(message.content, false, true) | trim %}
+    {%- if '<|think_off|>' in _part %}{%- set _part = _part.split('<|think_off|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_on|>' in _part %}{%- set _part = _part.split('<|think_on|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_xhigh|>' in _part %}{%- set _part = _part.split('<|think_xhigh|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_high|>' in _part %}{%- set _part = _part.split('<|think_high|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_ultracode|>' in _part %}{%- set _part = _part.split('<|think_ultracode|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_extreme|>' in _part %}{%- set _part = _part.split('<|think_extreme|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_max|>' in _part %}{%- set _part = _part.split('<|think_max|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_medium|>' in _part %}{%- set _part = _part.split('<|think_medium|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_low|>' in _part %}{%- set _part = _part.split('<|think_low|>') | join('') | trim %}{%- endif %}
+    {%- if '<|think_minimal|>' in _part %}{%- set _part = _part.split('<|think_minimal|>') | join('') | trim %}{%- endif %}
+    {%- if _part %}
+        {%- if sys_state.content %}
+            {%- set sys_state.content = sys_state.content ~ '\n\n' ~ _part %}
+        {%- else %}
+            {%- set sys_state.content = _part %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- set _sc = sys_state.content %}
+{%- set _msgs = messages[head.count:] %}
+{%- if ns_state.thinking %}
+    {%- set _terse_lead = 'Answer directly, after thinking. Lead with the answer, then only what it needs to be correct and usable.' %}
+{%- else %}
+    {%- set _terse_lead = 'Answer directly and concisely. Give the answer with only what it needs to be correct and usable.' %}
+{%- endif %}
+{%- set _terse_core %}
+Never: open with preamble or pleasantries; restate the question; add filler transitions; hedge with niceties; or repeat a point you've already made.
+Always: keep essential steps, caveats, uncertainties, and specifics — never drop correctness or a needed warning for brevity. Keep the final answer lean. Use the least structure that conveys it (plain prose when short; lists or code only when they earn their place). If genuinely uncertain, say so and explain why — never omit uncertainty for the sake of brevity.
+If a user request is genuinely ambiguous, ask a sharp question, don't guess.
+{%- endset %}
+{%- set _terse = _terse_lead ~ '\n' ~ (_terse_core | trim) %}
+{#- `terse` chat-template kwarg: default true, so behaviour is unchanged unless a caller opts out.
+    Pass {"terse": false} via chat_template_kwargs to serve the model with only its own system
+    prompt -- useful for A/B-ing the terseness effect, or when a downstream prompt conflicts. #}
+{%- set _terse_on = terse if terse is defined else true %}
+{%- if _terse_on %}
+    {%- if not _sc %}
+        {%- set _sc = _terse | trim %}
+    {%- else %}
+        {%- set _sc = (_sc | trim) ~ '\n\n' ~ (_terse | trim) %}
+    {%- endif %}
+{%- endif %}
+{%- if _has_tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if reasoning_instructions %}
+        {{- reasoning_instructions + '\n\n' }}
+    {%- endif %}
+    {{- '# Tools\n\nYou have access to the following functions:\n\n<tools>' }}
+    {%- for tool in tools %}
+        {{- '\n' }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- '\n</tools>' }}
+    {%- if _tool_format == 'json' %}
+        {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n' }}{%- if ns_state.thinking %}{{- '<think>\nBrief explanation of tool call\n</think>\n' }}{%- endif %}{{- '<tool_call>\n{"name": "example_function_name", "arguments": {"example_parameter_1": "value_1", "example_parameter_2": "This is the value for the second parameter"}}\n</tool_call>\n\n<IMPORTANT>\nReminder:\n' }}{%- if ns_state.thinking %}{{- '- You can use the <think></think> block to plan your next tool call OR to synthesize data and formulate your final response to the user.\n- ALL explanation and reasoning MUST be placed strictly inside the <think></think> block.\n' }}{%- endif %}{{- '- Function calls MUST follow the specified format: a single JSON object with "name" and "arguments" keys inside <tool_call></tool_call> XML tags.\n- If you choose to call a tool, you MUST output the <tool_call> block IMMEDIATELY' }}{%- if ns_state.thinking %}{{- ' after thinking' }}{%- endif %}{{- ', with NO conversational text before it.\n- The <tool_call> tag MUST be at the very beginning of a new line, with NO spaces or indentation before it.\n- To call multiple functions, output a separate, completely closed <tool_call></tool_call> block for EACH function. Do NOT nest <tool_call> blocks.\n- If you have all necessary data, provide your final answer directly to the user without any tool call.\n</IMPORTANT>' }}
+    {%- else %}
+        {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n' }}{%- if ns_state.thinking %}{{- '<think>\nBrief explanation of tool call\n</think>\n' }}{%- endif %}{{- '<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n' }}{%- if ns_state.thinking %}{{- '- You can use the <think></think> block to plan your next tool call OR to synthesize data and formulate your final response to the user.\n- ALL explanation and reasoning MUST be placed strictly inside the <think></think> block.\n' }}{%- endif %}{{- '- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags.\n- If you choose to call a tool, you MUST output the <tool_call> block IMMEDIATELY' }}{%- if ns_state.thinking %}{{- ' after thinking' }}{%- endif %}{{- ', with NO conversational text before it.\n- The <tool_call> and <function> tags MUST be at the very beginning of a new line, with NO spaces or indentation before them.\n- To call multiple functions, output a separate, completely closed <tool_call></tool_call> block for EACH function. Do NOT nest <tool_call> blocks.\n- If you have all necessary data, provide your final answer directly to the user without any tool call.\n</IMPORTANT>' }}
+    {%- endif %}
+    {%- if _sc %}
+        {{- '\n\n' + _sc }}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if _sc %}
+        {{- '<|im_start|>system\n' + (reasoning_instructions + '\n\n' if reasoning_instructions else '') + _sc + '<|im_end|>\n' }}
+    {%- elif reasoning_instructions %}
+        {{- '<|im_start|>system\n' + reasoning_instructions + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set _last_idx = _msgs | length - 1 %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=_last_idx) %}
+{%- for message in _msgs[::-1] %}
+    {%- set index = (_msgs | length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == 'user' %}
+        {%- set _rc = render_content(message.content, false) | trim %}
+        {%- if not (_rc.startswith('<tool_response>') and _rc.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {%- if _last_idx > 50 %}
+        {%- set ns.last_query_index = _last_idx %}
+    {%- else %}
+        {%- set ns.last_query_index = 0 %}
+    {%- endif %}
+{%- endif %}
+{%- set ns2 = namespace(prev_role='', consecutive_failures=0) %}
+{%- for message in _msgs %}
+    {%- set is_system = (message.role == "system" or message.role == "developer") %}
+    {%- set content = render_content(message.content, true, is_system) | trim %}
+    {%- if is_system or message.role == 'user' %}
+        {%- if '<|think_off|>' in content %}{%- set content = content.split('<|think_off|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_on|>' in content %}{%- set content = content.split('<|think_on|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_xhigh|>' in content %}{%- set content = content.split('<|think_xhigh|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_high|>' in content %}{%- set content = content.split('<|think_high|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_ultracode|>' in content %}{%- set content = content.split('<|think_ultracode|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_extreme|>' in content %}{%- set content = content.split('<|think_extreme|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_max|>' in content %}{%- set content = content.split('<|think_max|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_medium|>' in content %}{%- set content = content.split('<|think_medium|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_low|>' in content %}{%- set content = content.split('<|think_low|>') | join('') | trim %}{%- endif %}
+        {%- if '<|think_minimal|>' in content %}{%- set content = content.split('<|think_minimal|>') | join('') | trim %}{%- endif %}
+    {%- endif %}
+    {%- if is_system %}
+        {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
+    {%- elif message.role == 'user' %}
+        {%- set ns2.consecutive_failures = 0 %}
+        {{- '<|im_start|>user\n' + content + '<|im_end|>\n' }}
+    {%- elif message.role == 'assistant' %}
+        {%- set reasoning_content = '' %}
+        {%- set _explicit_reasoning = '' %}
+        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
+            {%- if message.reasoning_content is string %}
+                {%- set _explicit_reasoning = message.reasoning_content %}
+            {%- else %}
+                {%- set _explicit_reasoning = message.reasoning_content | string %}
+            {%- endif %}
+        {%- elif message.thinking is defined and message.thinking is not none %}
+            {%- if message.thinking is string %}
+                {%- set _explicit_reasoning = message.thinking %}
+            {%- else %}
+                {%- set _explicit_reasoning = message.thinking | string %}
+            {%- endif %}
+        {%- elif message.reasoning is defined and message.reasoning is not none %}
+            {%- if message.reasoning is string %}
+                {%- set _explicit_reasoning = message.reasoning %}
+            {%- else %}
+                {%- set _explicit_reasoning = message.reasoning | string %}
+            {%- endif %}
+        {%- endif %}
+        {%- if _explicit_reasoning %}
+            {%- set _lead_end = '' %}
+            {%- if content.startswith('<think>') and '</think>' in content %}
+                {%- set _lead_end = '</think>' %}
+            {%- elif content.startswith('<thinking>') and '</thinking>' in content %}
+                {%- set _lead_end = '</thinking>' %}
+            {%- elif content.startswith('</think>') %}
+                {%- set _lead_end = '</think>' %}
+            {%- elif content.startswith('</thinking>') %}
+                {%- set _lead_end = '</thinking>' %}
+            {%- endif %}
+            {%- if _lead_end %}
+                {%- set content = content.split(_lead_end)[-1].lstrip('\n') %}
+            {%- endif %}
+            {%- set reasoning_content = _explicit_reasoning %}
+        {%- else %}
+            {%- set _think_end = '' %}
+            {%- if content.startswith('</think>') %}
+                {%- set _think_end = '</think>' %}
+            {%- elif content.startswith('</thinking>') %}
+                {%- set _think_end = '</thinking>' %}
+            {%- elif '\n</think>' in content %}
+                {%- set _think_end = '\n</think>' %}
+            {%- elif '\n</thinking>' in content %}
+                {%- set _think_end = '\n</thinking>' %}
+            {%- elif '\n</ think>' in content %}
+                {%- set _think_end = '\n</ think>' %}
+            {%- elif '\n</think >' in content %}
+                {%- set _think_end = '\n</think >' %}
+            {%- elif content.startswith('<think>') and '</think>' in content %}
+                {%- set _think_end = '</think>' %}
+            {%- elif content.startswith('<thinking>') and '</thinking>' in content %}
+                {%- set _think_end = '</thinking>' %}
+            {%- endif %}
+            {%- if _think_end %}
+                {%- if 'thinking' in _think_end %}
+                    {%- set _think_start = '<thinking>' %}
+                {%- else %}
+                    {%- set _think_start = '<think>' %}
+                {%- endif %}
+                {%- set reasoning_content = content.split(_think_end)[0].rstrip('\n') %}
+                {%- if _think_start in reasoning_content %}
+                    {%- set reasoning_content = reasoning_content.split(_think_start)[-1].lstrip('\n') %}
+                {%- endif %}
+                {%- set content = content.split(_think_end)[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content | trim %}
+        {%- if (_preserve_thinking or loop.index0 > ns.last_query_index) %}
+            {{- '<|im_start|>assistant\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>assistant\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls is defined and message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined and tool_call.function is not none %}
+                    {%- set tc = tool_call.function %}
+                {%- else %}
+                    {%- set tc = tool_call %}
+                {%- endif %}
+                {%- set tc_name = tc.name if (tc.name is defined and tc.name is not none) else '' %}
+                {%- if _tool_format == 'json' %}
+                    {%- if loop.first %}
+                        {%- if content | trim %}
+                            {{- '\n\n' }}
+                        {%- endif %}
+                    {%- else %}
+                        {{- '\n' }}
+                    {%- endif %}
+                    {%- set _args = '{}' %}
+                    {%- if tc.arguments is defined and tc.arguments is not none %}
+                        {%- if tc.arguments is mapping %}
+                            {%- set _args = tc.arguments | tojson %}
+                        {%- elif tc.arguments is string %}
+                            {%- if tc.arguments %}
+                                {%- set _args = tc.arguments %}
+                            {%- endif %}
+                        {%- else %}
+                            {%- set _args = tc.arguments | tojson %}
+                        {%- endif %}
+                    {%- endif %}
+                    {{- '<tool_call>\n{"name": ' }}{{- tc_name | tojson }}{{- ', "arguments": ' }}{{- _args }}{{- '}\n</tool_call>' }}
+                {%- else %}
+                    {%- if loop.first %}
+                        {%- if content | trim %}
+                            {{- '\n\n<tool_call>\n<function=' + tc_name + '>\n' }}
+                        {%- else %}
+                            {{- '<tool_call>\n<function=' + tc_name + '>\n' }}
+                        {%- endif %}
+                    {%- else %}
+                        {{- '\n<tool_call>\n<function=' + tc_name + '>\n' }}
+                    {%- endif %}
+                    {%- if tc.arguments is defined and tc.arguments is not none %}
+                        {%- if tc.arguments is mapping %}
+                            {%- for args_name, args_value in tc.arguments.items() %}
+                                {{- '<parameter=' + args_name + '>\n' }}
+                                {%- if args_value is string %}
+                                    {%- set _av = args_value %}
+                                {%- else %}
+                                    {%- set _av = args_value | tojson %}
+                                {%- endif %}
+                                {%- if max_tool_arg_chars > 0 and _av | length > max_tool_arg_chars %}
+                                    {{- _av[:max_tool_arg_chars] + '\n[TRUNCATED - original length ' ~ (_av | length | string) ~ ' chars]' }}
+                                {%- else %}
+                                    {{- _av }}
+                                {%- endif %}
+                                {{- '\n</parameter>\n' }}
+                            {%- endfor %}
+                        {%- else %}
+                            {%- if tc.arguments is string %}
+                                {%- set _raw_args = tc.arguments %}
+                            {%- else %}
+                                {%- set _raw_args = tc.arguments | tojson %}
+                            {%- endif %}
+                            {%- if _raw_args %}
+                                {%- if max_tool_arg_chars > 0 and _raw_args | length > max_tool_arg_chars %}
+                                    {{- _raw_args[:max_tool_arg_chars] + '\n[TRUNCATED - original length ' ~ (_raw_args | length | string) ~ ' chars]' }}
+                                {%- else %}
+                                    {{- _raw_args }}
+                                {%- endif %}
+                            {%- endif %}
+                        {%- endif %}
+                    {%- endif %}
+                    {{- '</function>\n</tool_call>' }}
+                {%- endif %}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == 'tool' %}
+        {%- set _content_lower = content | lower %}
+        {%- set _content_head = _content_lower[:120] %}
+        {%- set _is_code_or_grep = ('throw new ' in _content_lower or 'throw error' in _content_lower or 'console.error' in _content_lower or 'logger.error' in _content_lower or 'logging.error' in _content_lower or 'import ' in _content_head or 'def ' in _content_head or 'function ' in _content_head) %}
+        {%- set _exit_code_zero = ('exit code: 0' in _content_head or 'process exited with code 0' in _content_head) %}
+        {%- set _error_field_ok = ('"error": null' in _content_head or '"error":null' in _content_head or '"error": false' in _content_head or '"error":false' in _content_head or '"error": ""' in _content_head or '"error":""' in _content_head) %}
+        {%- set _strong_error = (('"error":' in _content_head and not _error_field_ok) or '"status": "error"' in _content_head or '"status":"error"' in _content_head or 'traceback (most recent call last):' in _content_head or 'command not found' in _content_head or 'invalid syntax' in _content_head or 'fatal:' in _content_head or (('exit code: ' in _content_head or 'process exited with code' in _content_head) and not _exit_code_zero) or _content_head.startswith('exception:') or _content_head.startswith('failed to ')) %}
+        {%- set _weak_error = ('error:' in _content_head or 'err!' in _content_head) %}
+        {%- set _weak_suppressed = ('$ ' in _content_head or 'took ' in _content_head or content | length >= 600) %}
+        {%- if not _is_code_or_grep and (_strong_error or (_weak_error and not _weak_suppressed)) %}
+            {%- set ns2.consecutive_failures = ns2.consecutive_failures + 1 %}
+        {%- else %}
+            {%- set ns2.consecutive_failures = 0 %}
+        {%- endif %}
+        {%- if ns2.prev_role != 'tool' %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {%- if _tool_format != 'json' and max_tool_response_chars > 0 and content | length > max_tool_response_chars %}
+            {%- set content = content[:max_tool_response_chars] + '\n[TRUNCATED - original length ' ~ (content | length | string) ~ ' chars]' %}
+        {%- endif %}
+        {{- '\n<tool_response>\n' + content }}
+        {%- if ns2.consecutive_failures >= 2 %}
+            {{- '\n\n⚠️ SYSTEM WARNING: ' ~ ns2.consecutive_failures ~ ' consecutive tool errors detected. Your previous approach is incorrect. You MUST use a fundamentally different approach or corrected arguments.' }}
+        {%- elif ns2.consecutive_failures == 1 %}
+            {{- '\n\n⚠️ SYSTEM WARNING: The previous tool call returned an error. Diagnose the failure and retry with completely corrected arguments.' }}
+        {%- endif %}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- else %}
+            {%- set _next_role = _msgs[loop.index0 + 1].role %}
+            {%- if _next_role != 'tool' %}
+                {{- '<|im_end|>\n' }}
+            {%- endif %}
+        {%- endif %}
+    {%- else %}
+        {{- '<|im_start|>user\n[' + message.role + ']: ' + content + '<|im_end|>\n' }}
+    {%- endif %}
+    {%- set ns2.prev_role = message.role %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if not ns_state.thinking %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

scripts/.AGENTTRASH/download-q8agent.sh.rocmfpx

@@ -0,0 +1,86 @@
+#!/usr/bin/env bash
+# Download the kingjones Qwen3.8-27B-ROCmFPX-Q8_0-AGENT payload for
+# frank-medium from HuggingFace into
+# /home/dank/models/kingjones-Qwen3.8-27B-ROCMFPX-Q8_0-AGENT.
+#
+# Run on Dankserver (the box that serves it).  The repo is public, so the
+# download works anonymously; a token in ~/.cache/huggingface/token is used
+# when present, which keeps the ~28 GB main file clear of the anonymous
+# rate limit at full speed.
+#
+#   bash scripts/download-q8agent.sh
+#   bash scripts/download-q8agent.sh --verify-only
+#
+# The script is resumable (curl -C -) and verifies every artifact's size
+# afterwards, so a truncated file fails loudly instead of load-crashing.
+set -euo pipefail
+
+REPO="kingjones777/Qwen3.8-27B-ROCmFPX-Q8_0-AGENT-GGUF"
+DIR="/home/dank/models/kingjones-Qwen3.8-27B-ROCMFPX-Q8_0-AGENT"
+EXPECTED=(
+  "Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf:28214425952"
+  "mmproj-Qwen3.8-27B-BF16.gguf:931145888"
+  "mtp-Qwen3.8-27B-Q4_0.gguf:1680271648"
+)
+# The model card's MTP prompt-cache fix ships in the same repo as a patch;
+# fetched for reference only.  This fork's main already carries the
+# speculative boundary in the context checkpoint, so nothing applies it.
+EXTRA=(
+  "patches/mtp-prompt-cache-fix.patch"
+)
+
+cd -- "$(dirname -- "$0")/.."
+
+main() {
+  local mode="download"
+  [[ "${1:-}" == "--verify-only" ]] && mode="verify"
+  mkdir -p "$DIR"
+  cd "$DIR"
+
+  local token="" auth=()
+  if [[ -r "$HOME/.cache/huggingface/token" ]]; then
+    token="$(cat "$HOME/.cache/huggingface/token")"
+    auth=(-H "Authorization: Bearer $token")
+  else
+    echo "no HF token at $HOME/.cache/huggingface/token; downloading anonymously"
+  fi
+
+  dl() {
+    local f="$1"
+    mkdir -p "$(dirname "$f")"
+    curl -fsSL -C - -o "$f" --retry 10 --retry-delay 5 --retry-max-time 10800 \
+      "${auth[@]}" \
+      "https://huggingface.co/$REPO/resolve/main/$f"
+    echo "  done: $f ($(du -h "$f" | cut -f1))"
+  }
+
+  if [[ "$mode" == "download" ]]; then
+    echo "downloading $REPO into $DIR"
+    for entry in "${EXPECTED[@]}"; do
+      dl "${entry%%:*}"
+    done
+    for f in "${EXTRA[@]}"; do
+      dl "$f"
+    done
+  fi
+
+  echo "verifying sizes"
+  local ok=1 f want act
+  for entry in "${EXPECTED[@]}"; do
+    f="${entry%%:*}"; want="${entry##*:}"
+    act="$(stat -c%s "$f" 2>/dev/null || echo 0)"
+    if [[ "$act" -eq "$want" ]]; then
+      echo "  OK   $f ($act bytes)"
+    else
+      echo "  BAD  $f ($act bytes, want $want)" >&2
+      ok=0
+    fi
+  done
+  if [[ -z "$token" ]]; then
+    echo "note: no token was used; sizes above are the integrity check"
+  fi
+  [[ "$ok" -eq 1 ]] || exit 1
+  echo "all files present and sized correctly"
+}
+
+main "$@"

scripts/.AGENTTRASH/frank-default-npu.env

@@ -0,0 +1,17 @@
+# Tunables for frank-default-npu (FastFlowLM NPU endpoint, Dankclaw)
+# Runtime: FLM 1.0.1 on the XDNA2 NPU (50 TOPS). Model: Gemma4-E4B-IT
+# (8B, Q4_1, vision + audio + reasoning). The NPU allocates from the
+# unified pool shared with frank-default-large (the CIRU llama.cpp
+# service on the iGPU). See serverAppConfigs-docs/FastFlowLM NPU Inference.md.
+#
+# 2026-08-20: gemma4-it:e4b deployed. Footprint ~9.1 GB. 64k context.
+
+FLM_MODEL=gemma4-it:e4b
+FLM_HOST=0.0.0.0
+FLM_PORT=52626
+FLM_PMODE=performance
+FLM_ASR=0
+# 64K context (native max for gemma4-it is 32768, but NPU supports up to 256k).
+# The model's max_prefill_len is 4096, so prompts longer than that get
+# truncated at prefill time.
+FLM_CTX_LEN=65536

scripts/.AGENTTRASH/frank-default-npu.service

@@ -0,0 +1,17 @@
+[Unit]
+Description=FastFlowLM NPU inference (frank-default-npu) on Dankclaw
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+Environment="FLM_NPU_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-default-npu.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-default-npu.sh
+LimitMEMLOCK=infinity
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

scripts/.AGENTTRASH/frank-dragoon.env.ik-llama.cpp

@@ -0,0 +1,105 @@
+# Tunables for frank-dragoon (mradermacher i1-Q4_K_M of
+# orcarouter/Qwen3.8-Flash-Next-Uncensored on ik_llama.cpp, Dankclaw,
+# RTX 3090 CUDA + Strix Halo CPU path, since 2026-09-15).
+#
+# Runtime: ik_llama.cpp master d85a1d7 (2026-09-15) with full qwen4exp
+# support (upstream PRs #2365/#2369/#2373 merged). Build recipe (CUDA for
+# the 3090 at sm_86, Zen5 AVX-512 IQK kernels for the CPU expert path):
+#   cmake -B build -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=ON \
+#     -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=86 \
+#     -DGGML_AVX512=ON -DGGML_AVX512_VBMI=ON -DGGML_AVX512_VNNI=ON \
+#     -DGGML_AVX512_BF16=ON -DLLAMA_CURL=OFF
+# The startup banner must print HAVE_FANCY_SIMD is defined — without those
+# macros the quantized GEMM silently falls back to AVX2 (no warning).
+#
+# Model: mradermacher imatrix quant of the uncensored Flash-Next (qwen4exp
+# MoE: 512 experts / 10 used, 48 layers = 12 attention + 36 GDN/ssm, QSA
+# indexer, hyper-connections, PLE n-gram table ~320M rows). 111 GiB shipped
+# as 3 parts, concatenated on disk; each part's sha256 was verified against
+# its HF LFS oid at download time.
+#
+# Placement (ikawrakow's hybrid recipe; upstream issue #2402 for the PLE):
+#   - -ot "exps=CPU": ALL 512-expert tensors (121B elems, ~84 GB) live in
+#     the Strix Halo's LPDDR5X via the plain CPU backend buffer — mmap-backed
+#     page cache, ik's fastest known configuration for this shape (the
+#     author's 2x3090 + Threadripper reference box measures ~50 t/s on the
+#     same model family). The shared experts (shexp) keep their GPU-side
+#     default: they run on every token.
+#   - -ot "per_layer_token_embd=CPU": the ~32 GB PLE n-gram table follows —
+#     only a tiny slice is touched per token, so it streams from page cache.
+#   - NEVER use --cpu-moe on this host: it routes the CPU-overridden
+#     weights through the CUDA_Host PINNED buffer (measured 2026-09-15:
+#     108.12 GiB page-locked, evicted every co-tenant into swap and starved
+#     sshd into unreachability until a power cycle). -ot ...=CPU is the
+#     mmap-backed path with identical DDR5 bandwidth for resident pages,
+#     and the kernel degrades gracefully under pressure (page cache evict
+#     + re-read) instead of stranding anyone.
+#   - GGML_CUDA_NO_PINNED_WEIGHTS=1 (src/llama-load-tensors.cpp) keeps the
+#     CPU-overridden weights mmapped and leaves only the small staging
+#     buffers pinned. (GGML_CUDA_NO_PINNED would also unpin staging —
+#     unnecessary here and slower for prefill transfers.)
+#
+# Sampling: greedy-by-default to preserve the halogen-era client contract
+# (a request without temperature decodes greedy; temp 0.0 = argmax).
+# Clients that send their own temperature get their own values.
+#
+# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE (see
+# the 2026-08-13 HIP incident in AGENTS.md). llama.cpp reads --host and
+# --temp as CLI flags, never as environment variables.
+
+# ik_llama.cpp runtime binary (master d85a1d7 build).
+LLAMA_BIN=/home/dank/GitPackages/ik_llama.cpp/build/bin/llama-server
+
+# Model package from
+# https://huggingface.co/mradermacher/Qwen3.8-Flash-Next-Uncensored-i1-GGUF
+# (parts concatenated). The mmproj is the matching vision tower from the
+# static repo mradermacher/Qwen3.8-Flash-Next-Uncensored-GGUF — ik_llama.cpp
+# links examples/mtmd, so image input survives the runtime swap.
+MODEL_DIR=/home/dank/models/mradermacher-Qwen3.8-Flash-Next-Uncensored-i1-Q4_K_M
+MODEL_FILE=Qwen3.8-Flash-Next-Uncensored.i1-Q4_K_M.gguf
+MMPROJ_PATH=/home/dank/models/mradermacher-Qwen3.8-Flash-Next-Uncensored-i1-Q4_K_M/Qwen3.8-Flash-Next-Uncensored.mmproj-f16.gguf
+
+# Qwen-Sharp chat template (tracked in the repo, staged on the host). The
+# server emits reasoning in DeepSeek format so clients receive
+# reasoning_content separately instead of literal think tags in content.
+CHAT_TEMPLATE_FILE=/home/dank/serverAppConfigs/scripts/chat-template.jinja
+
+# Alias + network.
+ALIAS=frank-dragoon
+BIND_ADDR=0.0.0.0
+LISTEN_PORT=7770
+
+# Serving: single 262144-token slot (the model's full context window),
+# batch 4096 / ubatch 512, 16+16 threads (the Halo CPU has 16 cores, no
+# SMT), f16 KV. The KV cache scales with the 12 full-attention layers only
+# (~6 GB f16 at 262k); the GDN/ssm layers keep constant-size state. If
+# VRAM headroom is needed, --cache-type-k/v q8_0 halves the KV footprint.
+CTX_SIZE=262144
+PARALLEL=1
+BATCH_SIZE=4096
+UBATCH_SIZE=512
+NUM_THREADS=16
+THREAD_BATCH=16
+CACHE_TYPE_K=f16
+CACHE_TYPE_V=f16
+
+# GPU/MoE placement: everything on the 3090 except the experts and the PLE
+# table, which both live in host RAM via the CPU backend buffer (see the
+# placement notes above).
+NGL=999
+# ik_llama.cpp CUDA host-memory policy: CPU-overridden weights stay mmapped;
+# only the small staging buffers are pinned (see the placement notes above).
+GGML_CUDA_NO_PINNED_WEIGHTS=1
+
+# Prompt cache (RAM budget in MiB) and slot state dir.
+CACHE_RAM=8192
+SLOT_SAVE_PATH=/home/dank/serverAppConfigs/scripts/slot-state
+
+# Greedy-by-default (halogen contract). See sampling note above.
+TEMPERATURE=0.0
+
+# Reasoning on: DeepSeek format projects thinking into the API's
+# reasoning_content field instead of literal think tags in content;
+# unlimited reasoning budget (the model decides).
+REASONING_FORMAT=deepseek
+REASONING_BUDGET=-1

scripts/.AGENTTRASH/frank-dragoon.service.ik-llama.cpp

@@ -0,0 +1,21 @@
+[Unit]
+Description=ik_llama.cpp Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M 177B MoE (dankclaw, frank-dragoon)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+# Staging buffers for the CUDA transfers are page-locked; the weights
+# themselves stay mmapped (GGML_CUDA_NO_PINNED_WEIGHTS=1), but the staging
+# budget still needs room. Parity with the halogen quadlet's
+# Ulimit=memlock=-1:-1.
+LimitMEMLOCK=infinity
+Environment="FRANK_DRAGOON_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-dragoon.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-dragoon.sh
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

scripts/.AGENTTRASH/frank-medium.env.rocmfpx

@@ -0,0 +1,138 @@
+# Tunables for frank-medium (kingjones777/Qwen3.8-27B-ROCmFPX-Q8_0-AGENT-GGUF,
+# charlie12345/ROCmFPX llama.cpp, Dankserver, 2x AMD Radeon AI PRO R9700).
+#
+# Hardware (2026-09-15): the RTX 3090 left Dankserver and two Radeon AI PRO
+# R9700 cards (Navi 48, gfx1201, RDNA4, 32,624 MiB each, PCIe 5.0 x16) took
+# its place.  The Raphael iGPU (gfx1036) is still enumerated by HIP as the
+# third device.  There is no XGMI link between the two cards and they sit in
+# different IOMMU groups, so any cross-GPU traffic goes over PCIe.
+#
+# Runtime: charlie12345/ROCmFPX (llama.cpp fork, ROCmFPX quant family; the
+# Q8_0_ROCMFPX_AGENT tensor type exists nowhere else - stock llama.cpp cannot
+# load this GGUF).  Built for gfx1201 with the fork's self-contained ROCm
+# 7.14 toolchain so the host's stale /opt/rocm-6.3.3 install is never used:
+#
+#   cd /home/dank/GitPackages/charlie-ROCmFPX
+#   env JOBS=8 ./scripts/build-rocmfp4-rocm714-local.sh
+#
+# gfx1201 must be the build target: a gfx1200 binary links, loads the model
+# and then segfaults on this card (fork's docs/BUILD-AMD-ARCHITECTURES.md).
+#
+# Model: kingjones Qwen3.8-27B-ROCmFPX-Q8_0-AGENT - Q8_0_ROCMFPX_AGENT
+# (ftype 115), 26.28 GiB, 8.39 bpw, arch qwen35 (MoE), quantized from a
+# 51.3 GiB BF16 source.  The AGENT routing keeps 12 more attention-output
+# projections at full Q8_0 than the plain 8-bit build, which buys a higher
+# MTP draft acceptance (0.953 vs 0.911) and that is the whole point of this
+# checkpoint.  Model card documents 131,072 context.
+#
+# Parallelism (--split-mode layer, operator call 2026-09-15 "pipeline
+# parallelism"): layers are distributed across the two cards in order and
+# activations hop PCIe at the boundary.  Measured with llama-bench
+# (pp4096 / tg128 / same at depth 32768, f16 KV, fa on, 3 reps):
+#
+#   single R9700   1160.9 / 19.42   (fits: 26.27 GiB weights, ~5 GiB left)
+#   layer  2x      1991.2 / 18.76   859.1 / 17.64
+#   tensor 2x       271.8 / 26.26   228.6 / 25.09
+#
+# Tensor parallel wins decode (+40 %) but collapses prefill 7x: this build
+# has no RCCL (llama.cpp logs "AllReduce init failed; falling back to
+# meta-backend butterfly"), so every layer pays a slow cross-card reduction.
+# Agentic traffic is prefill-heavy, so layer split wins the workload.  Revisit
+# if the fork ships a working RCCL tensor path.
+#
+# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE. The
+# ROCm HIP runtime reads those bare env vars (see the 2026-08-13 TEMP
+# incident).  llama.cpp reads --host/--port/--temp as CLI flags, never as
+# env vars.
+
+# charlie12345/ROCmFPX llama-server (self-contained ROCm 7.14 build, RPATH
+# points at the bundled runtime libs; no LD_LIBRARY_PATH needed).
+LLAMA_BIN=/home/dank/GitPackages/charlie-ROCmFPX/build-rdna4-rocm714/bin/llama-server
+
+# Model package, fetched with scripts/download-q8agent.sh:
+#   Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf   26.28 GiB  main weights
+#   mtp-Qwen3.8-27B-Q4_0.gguf              1.68 GiB  MTP draft head
+#   mmproj-Qwen3.8-27B-BF16.gguf           0.93 GiB  vision tower (unused)
+MODEL_DIR=/home/dank/models/kingjones-Qwen3.8-27B-ROCMFPX-Q8_0-AGENT
+MODEL_FILE=Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf
+DRAFT_MODEL_FILE=mtp-Qwen3.8-27B-Q4_0.gguf
+
+# Alias + network.  The port is the fleet's dankserver endpoint; the alias is
+# what clients ask for, and it replaces the retired `frank-small`.
+ALIAS=frank-medium
+BIND_ADDR=0.0.0.0
+LISTEN_PORT=7770
+
+# Device placement.  HIP_VISIBLE_DEVICES hides the iGPU (device 2) so nothing
+# can drift onto shared system RAM; DEVICES is what llama.cpp splits across.
+HIP_VISIBLE_DEVICES=0,1
+DEVICES=ROCm0,ROCm1
+SPLIT_MODE=layer
+
+# TENSOR_SPLIT empty = layers distributed by free VRAM (equal here).
+TENSOR_SPLIT=
+
+NGL=999
+# Auto-fit has no business resizing a context we set explicitly.
+FIT=off
+FLASH_ATTN=on
+
+# 131,072 tokens, one slot (the model card's documented window; the GGUF
+# reports n_ctx_train 262144, untested by the model author).  Layer split
+# keeps each layer's KV on the card that owns the layer, so the window is
+# bounded by per-card free memory: ~5.6 GiB of KV per card at 131072 f16.
+CTX_SIZE=131072
+PARALLEL=1
+
+# 26.28 GiB of weights + MTP draft + KV cache leaves ~15 GiB per card at this
+# context, so the batch shape is chosen for prefill throughput, not memory.
+BATCH_SIZE=2048
+UBATCH_SIZE=512
+NUM_THREADS=8
+THREAD_BATCH=8
+
+# f16 K/V: an agent checkpoint is the wrong place to spend KV precision.
+CACHE_TYPE_K=f16
+CACHE_TYPE_V=f16
+CTX_CHECKPOINTS=8
+CACHE_RAM=8192
+
+# Sampling: the checkpoint's instruct table.
+TEMPERATURE=0.7
+TOP_P=0.8
+TOP_K=20
+MIN_P=0.0
+PRESENCE_PENALTY=1.5
+
+# Reasoning on; DeepSeek format projects the trace into reasoning_content
+# instead of literal thinking tags in content.
+REASONING=on
+REASONING_FORMAT=deepseek
+REASONING_BUDGET=-1
+
+# Chat template: empty = the template embedded in the GGUF.  Point this at
+# /home/dank/serverAppConfigs/scripts/chat-template.jinja to force the repo's
+# Sharp agent template instead.
+CHAT_TEMPLATE_FILE=
+CHAT_TEMPLATE_KWARGS='{"enable_thinking":true,"preserve_thinking":true}'
+
+# MTP speculative decoding.  n_max 6 / p_min 0.6 is the fork's measured
+# sweet spot for a MTP head with high acceptance; p_min 0.0 drafts
+# low-probability tokens that get rejected and makes MTP a net loss.
+SPEC_TYPE=draft-mtp
+SPEC_DRAFT_N_MAX=6
+SPEC_DRAFT_N_MIN=0
+SPEC_DRAFT_P_MIN=0.6
+SPEC_DRAFT_P_SPLIT=0.10
+SPEC_DRAFT_NGL=999
+SPEC_DRAFT_TYPE_K=f16
+SPEC_DRAFT_TYPE_V=f16
+SPEC_DRAFT_POLL=1
+SPEC_DRAFT_POLL_BATCH=1
+# The draft head rides the card that holds the target model's LAST layers:
+# the MTP head consumes the final hidden state, so pinning it to ROCm1 keeps
+# the per-token hop off the wire.  (Under the abandoned tensor split the
+# draft must also be pinned to exactly one device or the meta-device KV
+# allocation aborts: GGML_ASSERT(buffer) in ggml-backend.cpp, measured
+# 2026-09-15.)
+SPEC_DRAFT_DEVICE=ROCm1

scripts/.AGENTTRASH/frank-medium.service.rocmfpx

@@ -0,0 +1,16 @@
+[Unit]
+Description=charlie12345/ROCmFPX llama.cpp serving kingjones777/Qwen3.8-27B-ROCmFPX-Q8_0-AGENT qwen35 MoE (dankserver, frank-medium, 2x Radeon AI PRO R9700)
+After=network-online.target
+Wants=network-online.target
+
+[Service]
+Type=simple
+User=dank
+Group=dank
+Environment="FRANK_MEDIUM_ENV_FILE=/home/dank/serverAppConfigs/scripts/frank-medium.env"
+ExecStart=/home/dank/serverAppConfigs/scripts/serve-frank-medium.sh
+Restart=on-failure
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target

scripts/.AGENTTRASH/serve-frank-default-npu.sh

@@ -0,0 +1,49 @@
+#!/usr/bin/env bash
+# Serve the FastFlowLM (FLM) NPU endpoint — frank-default-npu.
+#
+# Runs flm serve with the model tag in frank-default-npu.env. The NPU
+# (XDNA2, 50 TOPS) is a single-lane device: generations serialize in FIFO
+# order, so this is a background/triage endpoint. The NPU shares the ~30 GiB
+# unified pool with frank-default-large (the CIRU llama.cpp service on the
+# iGPU); see serverAppConfigs-docs/FastFlowLM NPU Inference.md for the memory budget.
+#
+# NOTE: FLM requires unlimited memlock. The unit sets LimitMEMLOCK=infinity.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FLM_NPU_ENV_FILE:-$SCRIPT_DIR/frank-default-npu.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) -------------------
+: "${FLM_BIN:=/usr/bin/flm}"
+: "${FLM_MODEL:=gemma4-it:e4b}"
+: "${FLM_HOST:=0.0.0.0}"
+: "${FLM_PORT:=52626}"
+: "${FLM_PMODE:=performance}"
+: "${FLM_ASR:=0}"
+: "${FLM_CTX_LEN:=-1}"
+
+if [[ ! -x "$FLM_BIN" ]]; then
+    echo "missing flm binary: $FLM_BIN" >&2
+    exit 1
+fi
+
+# --- optional flags ----------------------------------------------------------
+OPT_ARGS=()
+if [[ "${FLM_ASR}" != "0" ]]; then
+    OPT_ARGS+=(-a "${FLM_ASR}")
+fi
+if [[ "${FLM_CTX_LEN}" != "-1" ]]; then
+    OPT_ARGS+=(-c "${FLM_CTX_LEN}")
+fi
+
+exec "$FLM_BIN" serve "$FLM_MODEL" \
+    --host "$FLM_HOST" \
+    -p "$FLM_PORT" \
+    --pmode "$FLM_PMODE" \
+    "${OPT_ARGS[@]}"

scripts/.AGENTTRASH/serve-frank-dragoon.sh.ik-llama.cpp

@@ -0,0 +1,123 @@
+#!/usr/bin/env bash
+# Serve mradermacher/Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M as frank-dragoon
+# via ik_llama.cpp on Dankclaw.
+#
+# Topology (ikawrakow's hybrid recipe; upstream issue #2402 for the PLE):
+# the RTX 3090 (CUDA, sm_86) takes the dense/attention/output weights and
+# the KV cache (-ngl 999); ALL MoE expert tensors and the ~32 GB PLE
+# n-gram table stay in the Strix Halo's LPDDR5X via the plain CPU backend
+# buffer (-ot ...=CPU — mmap-backed page cache; only a tiny slice of PLE is
+# touched per token). NEVER use --cpu-moe on this host: it routes the
+# CPU-overridden weights through the CUDA_Host PINNED buffer (measured
+# 108.12 GiB page-locked on 2026-09-15, which evicted every co-tenant into
+# swap and starved sshd into unreachability until a power cycle). NEVER add
+# --no-mmap — the STRIX-era lesson transfers directly (the cgroup killer
+# takes the process with nothing in the server log).
+#
+# Runtime: ik_llama.cpp master d85a1d7 built with CUDA (sm_86) + Zen5
+# AVX-512 IQK kernels; the startup banner must show HAVE_FANCY_SIMD
+# is defined. Flag set verified against this binary's --help before this
+# script was written. ik has no --cache-prompt/--cache-idle-slots (prompt
+# caching is its default behavior) and no --alias: it is a single-model
+# server and reports the GGUF's general.name at /v1/models.
+#
+# Sampling: greedy-by-default (halogen client contract) — clients that
+# send their own temperature get their own values.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_DRAGOON_ENV_FILE:-$SCRIPT_DIR/frank-dragoon.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) -------------------
+: "${LLAMA_BIN:=/home/dank/GitPackages/ik_llama.cpp/build/bin/llama-server}"
+: "${MODEL_DIR:=/home/dank/models/mradermacher-Qwen3.8-Flash-Next-Uncensored-i1-Q4_K_M}"
+: "${MODEL_FILE:=Qwen3.8-Flash-Next-Uncensored.i1-Q4_K_M.gguf}"
+: "${MMPROJ_PATH:=$MODEL_DIR/Qwen3.8-Flash-Next-Uncensored.mmproj-f16.gguf}"
+: "${CHAT_TEMPLATE_FILE:=$SCRIPT_DIR/chat-template.jinja}"
+: "${BIND_ADDR:=0.0.0.0}"
+: "${LISTEN_PORT:=7770}"
+: "${CTX_SIZE:=262144}"
+: "${PARALLEL:=1}"
+: "${BATCH_SIZE:=4096}"
+: "${UBATCH_SIZE:=512}"
+: "${NUM_THREADS:=16}"
+: "${THREAD_BATCH:=16}"
+: "${CACHE_TYPE_K:=f16}"
+: "${CACHE_TYPE_V:=f16}"
+: "${NGL:=999}"
+: "${CPU_MOE:=on}"
+: "${FLASH_ATTN:=on}"
+: "${TEMPERATURE:=0.0}"
+: "${REASONING:=on}"
+: "${REASONING_FORMAT:=deepseek}"
+: "${REASONING_BUDGET:=-1}"
+: "${CACHE_RAM:=8192}"
+: "${SLOT_SAVE_PATH:=$SCRIPT_DIR/slot-state}"
+# Hard guard: on this host CUDA pinned host memory strands the co-tenants
+# (measured 2026-09-15: a default-policy start tried to page-lock 108.12 GiB,
+# evicted every co-tenant into swap and starved sshd into unreachability
+# until a power cycle). GGML_CUDA_NO_PINNED_WEIGHTS=1 keeps the
+# CPU-overridden weights mmapped (src/llama-load-tensors.cpp); the env file
+# sets it. Refuse to run without it.
+if [[ "${GGML_CUDA_NO_PINNED_WEIGHTS:-}" != "1" ]]; then
+    echo "frank-dragoon: refusing to start — GGML_CUDA_NO_PINNED_WEIGHTS=1 is mandatory on this host" >&2
+    exit 1
+fi
+
+mkdir -p "$SLOT_SAVE_PATH"
+
+# The UVM device node is created lazily by nvidia-modprobe on the first
+# CUDA open after boot; make sure it exists before the server needs it.
+nvidia-modprobe -u -c=0 2>/dev/null || true
+
+CPU_MOE_ARGS=()
+if [[ "$CPU_MOE" == "on" ]]; then
+    # -ot ...=CPU (plain CPU backend buffer) is the mmap-backed path. NEVER
+    # swap this for --cpu-moe: that routes the weights through the CUDA_Host
+    # PINNED buffer (108.12 GiB measured) and strands the co-tenants.
+    CPU_MOE_ARGS=(-ot "exps=CPU" -ot "per_layer_token_embd=CPU")
+fi
+
+MMPROJ_ARGS=()
+if [[ -n "${MMPROJ_PATH:-}" && -f "$MMPROJ_PATH" ]]; then
+    MMPROJ_ARGS=(--mmproj "$MMPROJ_PATH")
+fi
+
+TEMPLATE_ARGS=()
+if [[ -n "${CHAT_TEMPLATE_FILE:-}" && -f "$CHAT_TEMPLATE_FILE" ]]; then
+    TEMPLATE_ARGS=(--chat-template-file "$CHAT_TEMPLATE_FILE")
+else
+    TEMPLATE_ARGS=(--jinja)
+fi
+
+exec "$LLAMA_BIN" \
+    --model "$MODEL_DIR/$MODEL_FILE" \
+    "${TEMPLATE_ARGS[@]}" \
+    --host "$BIND_ADDR" \
+    --port "$LISTEN_PORT" \
+    --gpu-layers "$NGL" \
+    "${CPU_MOE_ARGS[@]}" \
+    --flash-attn "$FLASH_ATTN" \
+    --parallel "$PARALLEL" \
+    --ctx-size "$CTX_SIZE" \
+    --batch-size "$BATCH_SIZE" \
+    --ubatch-size "$UBATCH_SIZE" \
+    --threads "$NUM_THREADS" \
+    --threads-batch "$THREAD_BATCH" \
+    --cache-type-k "$CACHE_TYPE_K" \
+    --cache-type-v "$CACHE_TYPE_V" \
+    --cache-ram "$CACHE_RAM" \
+    --slot-save-path "$SLOT_SAVE_PATH" \
+    --ctx-checkpoints 16 \
+    --metrics \
+    --temp "$TEMPERATURE" \
+    --reasoning "$REASONING" \
+    --reasoning-format "$REASONING_FORMAT" \
+    --reasoning-budget "$REASONING_BUDGET" \
+    "${MMPROJ_ARGS[@]}"

scripts/.AGENTTRASH/serve-frank-medium.sh.rocmfpx

@@ -0,0 +1,215 @@
+#!/usr/bin/env bash
+# Serve kingjones777/Qwen3.8-27B-ROCmFPX-Q8_0-AGENT-GGUF as frank-medium via
+# the charlie12345/ROCmFPX llama.cpp runtime on Dankserver
+# (2x AMD Radeon AI PRO R9700, Navi 48, gfx1201, 32 GB each).
+#
+# Runtime: charlie12345/ROCmFPX main (c49ebdb, 2026-08-22), built for
+# gfx1201 with the fork's self-contained ROCm toolchain:
+#
+#   cd /home/dank/GitPackages/charlie-ROCmFPX
+#   env JOBS=8 ./scripts/build-rocmfp4-rocm714-local.sh
+#   -> build-rdna4-rocm714/bin/llama-server
+#
+# That script downloads the gfx120X-all TheRock ROCm 7.14 toolchain into
+# ~/.local/share/rocm-7.14.0a20260624, builds with
+# -DCMAKE_HIP_ARCHITECTURES="gfx1200;gfx1201", copies the ROCm runtime
+# (hip/hsa/rocblas/hipblaslt + their kernel libraries) next to the binary and
+# sets RPATH=$ORIGIN/../lib on it.  The resulting service is self-contained:
+# no LD_LIBRARY_PATH, and the host's stale /opt/rocm-6.3.3 cannot leak in.
+# gfx1201 is NOT interchangeable with gfx1200 on this card (the fork's
+# docs/BUILD-AMD-ARCHITECTURES.md: a gfx1200 build links, loads and then
+# segfaults), and the build verifies the emitted code objects afterwards.
+#
+# Model: kingjones Qwen3.8-27B-ROCmFPX-Q8_0-AGENT (Q8_0_ROCMFPX_AGENT,
+# ftype 115, arch qwen35 MoE), 26.28 GiB main file, plus a separate
+# MTP draft head and an mmproj vision tower.  8.39 bpw; the AGENT routing
+# keeps 13 of the 17 attention-output projections at full Q8_0, which is
+# what makes the MTP draft land ~0.95 of its guesses.  A stock llama.cpp
+# cannot load this GGUF at all - Q8_0_ROCMFPX exists only in this fork.
+#
+# Parallelism: --split-mode layer across both cards (operator call
+# 2026-09-15).  Layers are distributed in order and activations hop PCIe at
+# the boundary; measured llama-bench: layer 1991/18.8 tok/s (pp4096/tg128)
+# vs tensor 272/26.3 and single-card 1161/19.4.  Tensor wins decode +40 %
+# but its prefill collapses 7x on this build (no RCCL: "AllReduce init
+# failed; falling back to meta-backend butterfly"), so layer split wins the
+# prefill-heavy agentic workload.
+#
+# Tunables come from frank-medium.env unless FRANK_MEDIUM_ENV_FILE
+# overrides that path.
+set -euo pipefail
+
+SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)"
+ENV_FILE="${FRANK_MEDIUM_ENV_FILE:-$SCRIPT_DIR/frank-medium.env}"
+if [[ -f "$ENV_FILE" ]]; then
+    set -a
+    # shellcheck disable=SC1090
+    source "$ENV_FILE"
+    set +a
+fi
+
+# --- defaults (used when the env file does not set them) -----------------
+: "${LLAMA_BIN:=/home/dank/GitPackages/charlie-ROCmFPX/build-rdna4-rocm714/bin/llama-server}"
+: "${MODEL_DIR:=/home/dank/models/kingjones-Qwen3.8-27B-ROCMFPX-Q8_0-AGENT}"
+: "${MODEL_FILE:=Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.gguf}"
+: "${DRAFT_MODEL_FILE:=mtp-Qwen3.8-27B-Q4_0.gguf}"
+: "${ALIAS:=frank-medium}"
+: "${BIND_ADDR:=0.0.0.0}"
+: "${LISTEN_PORT:=7770}"
+
+# Devices: ROCm0/ROCm1 are the two R9700s; the Raphael iGPU enumerates as
+# ROCm2 (gfx1036) and is hidden from HIP so nothing can drift onto it.
+: "${HIP_VISIBLE_DEVICES:=0,1}"
+: "${DEVICES:=ROCm0,ROCm1}"
+: "${SPLIT_MODE:=tensor}"
+: "${TENSOR_SPLIT:=}"
+: "${NGL:=999}"
+: "${FIT:=off}"
+: "${FLASH_ATTN:=on}"
+
+: "${CTX_SIZE:=131072}"
+: "${PARALLEL:=1}"
+: "${BATCH_SIZE:=2048}"
+: "${UBATCH_SIZE:=512}"
+: "${NUM_THREADS:=8}"
+: "${THREAD_BATCH:=8}"
+: "${CACHE_TYPE_K:=f16}"
+: "${CACHE_TYPE_V:=f16}"
+: "${CTX_CHECKPOINTS:=8}"
+: "${CACHE_RAM:=8192}"
+
+# Sampling: the checkpoint's instruct table.
+: "${TEMPERATURE:=0.7}"
+: "${TOP_P:=0.8}"
+: "${TOP_K:=20}"
+: "${MIN_P:=0.0}"
+: "${PRESENCE_PENALTY:=1.5}"
+
+# Reasoning: the model is an agent checkpoint; keep the trace and project it
+# into the API's reasoning_content field rather than literal thinking tags.
+: "${REASONING:=on}"
+: "${REASONING_FORMAT:=deepseek}"
+: "${REASONING_BUDGET:=-1}"
+
+# Chat template: empty means "use the template embedded in the GGUF".
+: "${CHAT_TEMPLATE_FILE:=}"
+: "${CHAT_TEMPLATE_KWARGS:={\"enable_thinking\":true,\"preserve_thinking\":true}}"
+
+# MTP draft head (separate GGUF, --spec-type draft-mtp).  SPEC_DRAFT_DEVICE
+# must name exactly one device: under tensor mode an unsplit draft joins the
+# meta-device KV allocation and aborts while building the KV cache
+# (GGML_ASSERT(buffer) in ggml-backend.cpp, 2026-09-15).
+: "${SPEC_TYPE:=draft-mtp}"
+: "${SPEC_DRAFT_N_MAX:=6}"
+: "${SPEC_DRAFT_N_MIN:=0}"
+: "${SPEC_DRAFT_P_MIN:=0.6}"
+: "${SPEC_DRAFT_P_SPLIT:=0.10}"
+: "${SPEC_DRAFT_NGL:=999}"
+: "${SPEC_DRAFT_DEVICE:=}"
+: "${SPEC_DRAFT_TYPE_K:=f16}"
+: "${SPEC_DRAFT_TYPE_V:=f16}"
+: "${SPEC_DRAFT_POLL:=1}"
+: "${SPEC_DRAFT_POLL_BATCH:=1}"
+
+# Text only: the server must not try to autoload the vision tower.  Vision
+# stays on frank-dragoon (Dankclaw), which is where the fleet routes images.
+NO_MMPROJ="${NO_MMPROJ:-1}"
+
+export HIP_VISIBLE_DEVICES
+
+MODEL="$MODEL_DIR/$MODEL_FILE"
+if [[ ! -x "$LLAMA_BIN" ]]; then
+    echo "missing executable runtime: $LLAMA_BIN" >&2
+    echo "build it with: cd $(dirname "$(dirname "$LLAMA_BIN")")/.. && env JOBS=8 ./scripts/build-rocmfp4-rocm714-local.sh" >&2
+    exit 1
+fi
+if [[ ! -r "$MODEL" ]]; then
+    echo "missing or unreadable required artifact: $MODEL" >&2
+    echo "fetch it with: bash $SCRIPT_DIR/download-q8agent.sh" >&2
+    exit 1
+fi
+if [[ -n "$CHAT_TEMPLATE_FILE" && ! -r "$CHAT_TEMPLATE_FILE" ]]; then
+    echo "missing or unreadable chat template: $CHAT_TEMPLATE_FILE" >&2
+    exit 1
+fi
+
+# --- speculative decoding (MTP draft head) --------------------------------
+SPEC_ARGS=()
+if [[ -n "$SPEC_TYPE" && "$SPEC_TYPE" != "none" ]]; then
+    SPEC_ARGS=(
+        --spec-type "$SPEC_TYPE"
+        --spec-draft-n-max "$SPEC_DRAFT_N_MAX"
+        --spec-draft-n-min "$SPEC_DRAFT_N_MIN"
+        --spec-draft-p-min "$SPEC_DRAFT_P_MIN"
+        --spec-draft-p-split "$SPEC_DRAFT_P_SPLIT"
+    )
+    if [[ "$SPEC_TYPE" == *draft-mtp* ]]; then
+        DRAFT_MODEL="$MODEL_DIR/$DRAFT_MODEL_FILE"
+        if [[ ! -r "$DRAFT_MODEL" ]]; then
+            echo "missing or unreadable draft model: $DRAFT_MODEL" >&2
+            exit 1
+        fi
+        SPEC_ARGS+=(
+            --spec-draft-model "$DRAFT_MODEL"
+            --spec-draft-ngl "$SPEC_DRAFT_NGL"
+            --spec-draft-type-k "$SPEC_DRAFT_TYPE_K"
+            --spec-draft-type-v "$SPEC_DRAFT_TYPE_V"
+            --spec-draft-poll "$SPEC_DRAFT_POLL"
+            --spec-draft-poll-batch "$SPEC_DRAFT_POLL_BATCH"
+        )
+        if [[ -n "$SPEC_DRAFT_DEVICE" ]]; then
+            SPEC_ARGS+=(--spec-draft-device "$SPEC_DRAFT_DEVICE")
+        fi
+    fi
+fi
+
+# --- template + placement -------------------------------------------------
+TEMPLATE_ARGS=()
+if [[ -n "$CHAT_TEMPLATE_FILE" ]]; then
+    TEMPLATE_ARGS+=(--chat-template-file "$CHAT_TEMPLATE_FILE")
+    TEMPLATE_ARGS+=(--chat-template-kwargs "$CHAT_TEMPLATE_KWARGS")
+fi
+
+PLACEMENT_ARGS=(--device "$DEVICES" --split-mode "$SPLIT_MODE")
+if [[ -n "$TENSOR_SPLIT" ]]; then
+    PLACEMENT_ARGS+=(--tensor-split "$TENSOR_SPLIT")
+fi
+
+MMPROJ_ARGS=()
+if [[ "$NO_MMPROJ" == "1" ]]; then
+    MMPROJ_ARGS=(--no-mmproj)
+fi
+
+exec "$LLAMA_BIN" \
+    --model "$MODEL" \
+    --alias "$ALIAS" \
+    --host "$BIND_ADDR" \
+    --port "$LISTEN_PORT" \
+    --jinja \
+    --gpu-layers "$NGL" \
+    --fit "$FIT" \
+    --parallel "$PARALLEL" \
+    --ctx-size "$CTX_SIZE" \
+    --batch-size "$BATCH_SIZE" \
+    --ubatch-size "$UBATCH_SIZE" \
+    --flash-attn "$FLASH_ATTN" \
+    --cache-type-k "$CACHE_TYPE_K" \
+    --cache-type-v "$CACHE_TYPE_V" \
+    --threads "$NUM_THREADS" \
+    --threads-batch "$THREAD_BATCH" \
+    --ctx-checkpoints "$CTX_CHECKPOINTS" \
+    --cache-ram "$CACHE_RAM" \
+    --cache-prompt \
+    --metrics \
+    --temp "$TEMPERATURE" \
+    --top-p "$TOP_P" \
+    --top-k "$TOP_K" \
+    --min-p "$MIN_P" \
+    --presence-penalty "$PRESENCE_PENALTY" \
+    --reasoning "$REASONING" \
+    --reasoning-format "$REASONING_FORMAT" \
+    --reasoning-budget "$REASONING_BUDGET" \
+    "${TEMPLATE_ARGS[@]}" \
+    "${PLACEMENT_ARGS[@]}" \
+    "${MMPROJ_ARGS[@]}" \
+    "${SPEC_ARGS[@]}"

scripts/apply-protected-cast.sh

@@ -1,45 +1,27 @@
 #!/usr/bin/env bash
-# apply-protected-cast.sh — RUNS ON DANKSERVER. Rewrite a recipe's
+# apply-protected-cast.sh — RUNS ON DANKSERVER. Rewrite the recipe's
-# PROTECTED-BEGIN/END section from the campaign's OWN calibration grams: run
+# PROTECTED-BEGIN/END section from Swift's OWN calibration grams: run
 # derive-protected-experts.py over the calib dir, splice its cast lines into
 # the marked section of the recipe in place, keep the pre-edit recipe in the
-# campaign trash. Refuses to run twice (marker text says derived), and refuses
+# campaign trash. Refuses to run twice (marker text says derived).
-# when a requested target count was not reached. Run it on a COPY of the
-# template so the committed recipe stays the clean, reviewable baseline.
 set -euo pipefail
-SELF_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+CALIB=${1:-/home/dank/corpora/calib}
-CALIB=${1:-/home/dank/campaign/qwen38-w5nl64/calib}
+RECIPE=${2:-/home/dank/serverAppConfigs-swift15/scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe}
-RECIPE=${2:-$SELF_DIR/recipes/qwen4exp-qwen38-w5nl64-bf16trunk.recipe}
+PY=/home/dank/venvs/radcorpus/bin/python
-TARGET_COUNT=${3:-0}
+DERIVE=/home/dank/serverAppConfigs-swift15/scripts/derive-protected-experts.py
-PY=${PY:-/home/dank/venvs/radcorpus/bin/python}
-DERIVE=${DERIVE:-$SELF_DIR/derive-protected-experts.py}
 TS=$(date +%Y%m%d-%H%M%S)
-# OUT and TRASH_DIR are overridable so the seam can drive the whole script in a
-# scratch directory; on the box they are the campaign's usual places.
-OUT=${OUT:-/tmp/protected-cast-$TS.txt}
-TRASH_DIR=${TRASH_DIR:-/home/dank/.AGENTTRASH}
 
 grep -q "derive-protected-experts.py rewrote" "$RECIPE" && {
     echo "recipe already carries derived cast lines; refusing to re-derive" >&2; exit 1; }
 grep -q "PROTECTED-BEGIN" "$RECIPE" || { echo "no PROTECTED markers in $RECIPE" >&2; exit 1; }
 
-ARGS=("$DERIVE" "$CALIB")
+"$PY" "$DERIVE" "$CALIB" > "/tmp/protected-cast-$TS.txt"
-if [ "$TARGET_COUNT" -gt 0 ]; then
+N=$(grep -c 'cast dtype=bf16' "/tmp/protected-cast-$TS.txt")
-    ARGS+=(--target-count "$TARGET_COUNT")
+[ "$N" -ge 2 ] || { echo "derive produced $N cast lines; refusing" >&2; exit 1; }
-fi
+echo "derived $N protected experts -> /tmp/protected-cast-$TS.txt"
-"$PY" "${ARGS[@]}" > "$OUT"
-N=$(grep -c 'cast dtype=bf16' "$OUT")
-[ "$N" -ge 2 ] || { echo "derive produced $N cast lines; refusing (see $OUT)" >&2; exit 1; }
-if [ "$TARGET_COUNT" -gt 0 ] && [ "$N" -lt "$TARGET_COUNT" ]; then
-    echo "derive reached $N protected experts, target was $TARGET_COUNT; refusing to convert" >&2
-    echo "       (the bar sweep bottomed out: the recording is too thin or the target too high)" >&2
-    exit 1
-fi
-echo "derived $N protected experts -> $OUT"
 
-mkdir -p "$TRASH_DIR"
+cp -f "$RECIPE" "/home/dank/.AGENTTRASH/$TS-qwen4exp-swift15-w4dn8-i8-hc8m.recipe"
-cp -f "$RECIPE" "$TRASH_DIR/$TS-$(basename "$RECIPE")"
+"$PY" - "$RECIPE" "/tmp/protected-cast-$TS.txt" <<'PYEOF'
-"$PY" - "$RECIPE" "$OUT" <<'PYEOF'
 import sys
 recipe, castfile = sys.argv[1], sys.argv[2]
 lines = open(recipe).read().splitlines()
@@ -53,7 +35,7 @@ for l in lines:
     elif 'PROTECTED-END' in l:
         insec = False
         out.append(l)
-        out.append('# (derive-protected-experts.py rewrote this section from the campaign grams)')
+        out.append('# (derive-protected-experts.py rewrote this section from Swift\'s own grams)')
     elif not insec:
         out.append(l)
 open(recipe, 'w').write('\n'.join(out) + '\n')

scripts/build-qwen38-bf16-rad.sh

@@ -1,220 +0,0 @@
-#!/usr/bin/env bash
-# build-qwen38-bf16-rad.sh — RUNS ON DANKSERVER. rad-convert the vendor BF16
-# checkpoint /home/dank/models/Qwen3.8-Flash-Next into
-# /home/dank/models/rad/qwen38-bf16.rad with NO recipe and NO --reuse: a weight
-# no rule matches keeps the checkpoint's encoding, so every tensor stays the
-# bf16 it is in the safetensors and the container is the checkpoint's own
-# numbers behind a .rad header.
-#
-# This file is the campaign's measuring stick, twice over: scripts/
-# run-qwen38-bf16.sh kldref records the KLD reference logits from it (every
-# arm's --kld-ref is scored against that record) and the same container serves
-# with the calibration tap to write the Grams that derive the protected-expert
-# list and feed GPTQ. A reference that is not the vendor checkpoint, byte for
-# byte in bf16, silently moves every gate in the campaign — hence no recipe, no
-# --reuse, and the four refusal gates below.
-#
-# Why a container at all: a checkpoint dir has no mapped/file tiers, and a
-# weight only a host kernel reads (the 47.7 GiB PLE n-gram table) cannot be
-# served from one; rad-convert also bakes the tokenizer. The convert runs on
-# the HOST backend — no --device /dev/kfd, no /dev/dri — so declare resolves
-# kernels on CPU and production serving is untouched for the whole run (the
-# precedent that proved it: scripts/convert-swift15-w4dn8.sh).
-#
-# Gates, every one a refusal with exit 2 and a named reason, BEFORE anything is
-# written, cheapest first — the verifier runs last of them because its Hub gate
-# hashes 343 GiB and must not be paid for by a run that was going to refuse on
-# the output file anyway.
-#   checkpoint  the tree must be on disk; an absent dir names the command that
-#               makes one (scripts/download-qwen38-bf16.sh --fetch) and stops.
-#   free space  the convert writes ~343,323 MiB next to the ~343,323 MiB
-#               checkpoint; QWEN38_MIN_FREE_MIB (default 350000 = that figure
-#               plus 6.5 GiB of slack) is the floor. The volume that cannot
-#               hold both is discovered at minute 2, not hour 5.
-#   output      the campaign converts the reference ONCE. An existing
-#               qwen38-bf16.rad is refused; --force retires it to
-#               ~/.AGENTTRASH/<utc>-qwen38-bf16.rad (trash law: nothing is
-#               deleted, and the move is a rename on the same volume).
-#   verified    scripts/download-qwen38-bf16.sh's verify mode must pass. A
-#               failed verify exits 1, not 2: the tree being the wrong payload
-#               is a result, a missing environment is a refusal.
-#   plan        rad-convert --plan-only -v first — the oracle for "does this
-#               shape boot". A refused plan costs seconds and saves a convert.
-#
-# usage: scripts/build-qwen38-bf16-rad.sh [--dry-run] [--plan-only] [--force]
-#   --dry-run    print the argv it would exec (podman wrapping rad-convert),
-#               one shell-quoted argument a line, and exit 0. No gate runs, no
-#               container starts, nothing is written — the offline test seam.
-#               It does resolve the checkpoint and output paths through the
-#               /models mount, because an argv that carries host paths would
-#               not run either.
-#   --plan-only  run the plan and every gate except the disk and output ones —
-#               those two protect bytes the plan never writes, and this is the
-#               probe to run when the disk gate itself is what refuses
-#   --force      retire an existing output container to the trash dir first
-#
-# knobs: FRANK_QWEN38_MODELS   the host dir mounted at /models (default
-#        /home/dank/models); FRANK_QWEN38_CKPT (default $MODELS/
-#        Qwen3.8-Flash-Next, the same knob the verifier reads);
-#        FRANK_QWEN38_BF16_OUT (default $MODELS/rad/qwen38-bf16.rad);
-#        QWEN38_MIN_FREE_MIB; QWEN38_TRASH (default $HOME/.AGENTTRASH). The
-#        verifier's own census knobs (FRANK_QWEN38_SHARDS / _BYTES / _REPO)
-#        reach it through the environment untouched.
-# exit: 0 converted (or planned), 1 the checkpoint failed verification,
-#       2 refused before anything was written
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-# ONE owner of the engine pin: the digest frank-archon serves on. The reference
-# must be built by the SAME engine build that scores it, or a KLD delta is
-# partly a version delta.
-# shellcheck disable=SC1091
-source "$SCRIPT_DIR/frank-archon.env"
-IMAGE="${FRANK_ARCHON_IMAGE:?FRANK_ARCHON_IMAGE must name the radiance image}"
-
-MODELS="${FRANK_QWEN38_MODELS:-/home/dank/models}"
-CKPT="${FRANK_QWEN38_CKPT:-$MODELS/Qwen3.8-Flash-Next}"
-OUT="${FRANK_QWEN38_BF16_OUT:-$MODELS/rad/qwen38-bf16.rad}"
-TRASH="${QWEN38_TRASH:-$HOME/.AGENTTRASH}"
-MIN_FREE_MIB="${QWEN38_MIN_FREE_MIB:-350000}"
-LOG="/home/dank/logs/qwen38_bf16_convert.log"
-
-DRY=0
-PLAN_ONLY=0
-FORCE=0
-while [ $# -gt 0 ]; do
-    case "$1" in
-        --dry-run)   DRY=1 ;;
-        --plan-only) PLAN_ONLY=1 ;;
-        --force)     FORCE=1 ;;
-        *) echo "usage: ${0##*/} [--dry-run] [--plan-only] [--force]" >&2
-           exit 2 ;;
-    esac
-    shift
-done
-
-# The convert sees the tree only through the /models mount, so both paths must
-# be under it; the container-side spelling is what goes into the argv.
-case "$CKPT" in
-    "$MODELS"/*) CKPT_IN="/models/${CKPT#"$MODELS"/}" ;;
-    *) echo "REFUSED: checkpoint $CKPT is not under the mounted models dir $MODELS — the convert cannot see it" >&2
-       exit 2 ;;
-esac
-case "$OUT" in
-    "$MODELS"/*) OUT_IN="/models/${OUT#"$MODELS"/}" ;;
-    *) echo "REFUSED: output $OUT is not under the mounted models dir $MODELS — rad-convert could not write it" >&2
-       exit 2 ;;
-esac
-
-# Declare with NO recipe line — that is what keeps every tensor bf16 — and at the
-# bound this container will actually be served at. Both flags come off the pinned
-# image's own help: --kv-cache-dtype at convert "only picks the kernels it
-# checks" and the container is identical either way, so naming fp8 is free
-# insurance — if the fp8 KV kernels the fleet serves would not resolve, the
-# convert refuses here instead of the boot failing on a drained window.
-# --max-ctx is the bound declare is run at, whose default is the checkpoint's
-# training context (262,144 here, whose fp8 cache is 258.8 GiB against a 192 GiB
-# machine, so the default is not an option). 32,768 is set by the corpus, not by
-# taste: kld.jsonl's longest record is 38,263 characters — ~9,600 tokens at the
-# pessimistic chars/4, ~7,700 at the chars/4.97 this repo measured on the K3
-# corpus — so the window the rig boots at clears every record 2.6x over and the
-# reference boot cannot die on a sequence that will not fit. The rig's window is
-# one knob (FRANK_QWEN38_MAX_MODEL_LEN in scripts/run-qwen38-bf16.sh, default
-# 32,768) and that script refuses a corpus its window cannot hold, so raising one
-# without the other is caught before the drained window, not inside it. The
-# payload containers the gate scores declare at the training context because
-# production must hold the 200k shape; a declared bound is a declare-time check,
-# not a weight change, so the reference and the payloads carry the same numbers
-# whatever each declared at — which is why one can be measured against the other.
-CONVERT_ARGS=("$CKPT_IN" -o "$OUT_IN" --max-ctx 32768 --kv-cache-dtype fp8)
-PODMAN=(podman run --rm --entrypoint rad-convert -v "$MODELS:/models")
-PLAN_CMD=("${PODMAN[@]}" --name qwen38-bf16-plan "$IMAGE" "${CONVERT_ARGS[@]}" --plan-only -v)
-CONV_CMD=("${PODMAN[@]}" --name qwen38-bf16-convert "$IMAGE" "${CONVERT_ARGS[@]}")
-
-if [ "$DRY" = "1" ]; then
-    echo "dry run: no gate checked, no container started, nothing written"
-    echo "# $CKPT -> $OUT (the convert sees them as $CKPT_IN and $OUT_IN)"
-    echo "# plan argv:"
-    printf '%q\n' "${PLAN_CMD[@]}"
-    echo "# convert argv:"
-    printf '%q\n' "${CONV_CMD[@]}"
-    exit 0
-fi
-
-# ---- gate: the checkpoint is on disk ---------------------------------------
-if [ ! -d "$CKPT" ]; then
-    echo "REFUSED: no checkpoint at $CKPT — fetch and verify it first: scripts/download-qwen38-bf16.sh --fetch" >&2
-    exit 2
-fi
-
-# ---- gate: peak disk --------------------------------------------------------
-# The deepest existing ancestor is the right thing to ask: a fresh
-# /home/dank/models/rad has no free space of its own to report.
-OUT_DIR="$(dirname "$OUT")"
-PROBE="$OUT_DIR"
-while [ ! -d "$PROBE" ] && [ "$PROBE" != "/" ]; do PROBE="$(dirname "$PROBE")"; done
-FREE_MIB="$(df --output=avail -m "$PROBE" | tail -1 | tr -d ' ')"
-if ! [[ "$FREE_MIB" =~ ^[0-9]+$ ]]; then
-    echo "REFUSED: cannot read the free space under $PROBE (df said: $FREE_MIB)" >&2
-    exit 2
-fi
-if [ "$PLAN_ONLY" != "1" ] && [ "$FREE_MIB" -lt "$MIN_FREE_MIB" ]; then
-    echo "REFUSED peak-disk: $FREE_MIB MiB free under $PROBE, $MIN_FREE_MIB MiB wanted (QWEN38_MIN_FREE_MIB) — the bf16 container rewrites the checkpoint's own 343,323 MiB of tensors beside it" >&2
-    exit 2
-fi
-
-# ---- gate: one conversion ---------------------------------------------------
-if [ -e "$OUT" ]; then
-    if [ "$PLAN_ONLY" = "1" ]; then
-        echo "note: $OUT already exists; --plan-only writes nothing, so it stays"
-    elif [ "$FORCE" = "1" ]; then
-        mkdir -p "$TRASH"
-        DEST="$TRASH/$(date -u +%Y%m%dT%H%M%SZ)-$(basename "$OUT")"
-        mv "$OUT" "$DEST"
-        echo "TRASHED: retired the existing reference container $OUT -> $DEST"
-    else
-        echo "REFUSED: $OUT already exists — the campaign converts the reference once; re-run with --force to retire it to $TRASH first" >&2
-        exit 2
-    fi
-fi
-
-# ---- gate: the tree really is the checkpoint (the full verify) -------------
-echo "== verifying $CKPT (scripts/download-qwen38-bf16.sh, full gates)"
-rc=0
-bash "$SCRIPT_DIR/download-qwen38-bf16.sh" --dir "$CKPT" || rc=$?
-if [ "$rc" -ne 0 ]; then
-    if [ "$rc" -eq 2 ]; then
-        echo "REFUSED: the checkpoint verifier refused the environment (rc=2); nothing was converted" >&2
-        exit 2
-    fi
-    echo "REFUSED: $CKPT failed verification (rc=$rc) — a half tree converts to a half reference" >&2
-    exit 1
-fi
-
-# ---- plan, then convert ------------------------------------------------------
-mkdir -p "$(dirname "$LOG")"
-# rad-convert opens -o during declare as well, so the output directory exists
-# before the plan; that empty directory is all this creates ahead of it.
-mkdir -p "$OUT_DIR"
-echo "== rad-convert --plan-only -v (declare + plan; writes nothing)"
-"${PLAN_CMD[@]}" 2>&1 | tee -a "$LOG"
-rc=${PIPESTATUS[0]}
-if [ "$rc" -ne 0 ]; then
-    echo "REFUSED plan: rad-convert --plan-only exited rc=$rc — the engine refuses this encoding/shape, no container was written (log: $LOG)" >&2
-    exit 2
-fi
-if [ "$PLAN_ONLY" = "1" ]; then
-    echo "PLAN_OK: $CKPT_IN declares for $OUT_IN; no container written (log: $LOG)"
-    exit 0
-fi
-
-echo "== convert: $CKPT -> $OUT ($(date -Is))"
-"${CONV_CMD[@]}" 2>&1 | tee -a "$LOG"
-rc=${PIPESTATUS[0]}
-if [ "$rc" -ne 0 ]; then
-    echo "rad-convert rc=$rc; log: $LOG" >&2
-    exit "$rc"
-fi
-MIB=$(( $(stat -c %s "$OUT") / 1048576 ))
-echo "BUILD_DONE: $OUT is ${MIB} MiB (log: $LOG)"
-echo "NEXT: scripts/run-qwen38-bf16.sh kldref records the reference logits from it"

scripts/calib-push.py

@@ -22,17 +22,6 @@ Mechanics notes:
   prompts do not bias the Hessians (the corpus is drawn round-robin over
   source classes, so loss is class-neutral as long as failures are rare;
   a systematic 4xx is loud in the log and must be fixed, not ignored).
-- a round that seals no tap bytes is NORMAL and continues: RADIANCE_CALIB_TOKENS
-  is a pooled floor and this campaign's corpus is 10.03M tokens against a 12M
-  floor, so round 1 seals nothing by construction. A tap that LOSES bytes fails
-  the run, and a run that never sees the engine's completion line exits non-zero.
-  The first version failed on a flat round, which aborted exactly one round too
-  early (2026-10-29).
-- before any prompt, the tap must carry the rig's own marker
-  (`--tap-marker`, written by run-qwen38-bf16.sh calib) naming THIS
-  container, and that container must be running. Measured 2026-10-29:
-  with neither check, four rounds of 10M tokens went into restored
-  production after the rig's boot had died, and recorded nothing.
 
 Usage: calib-push.py [--port 7770] [--parallel 64] [--container arbench]
        [--corpus /home/dank/corpora/out/calib.jsonl] [--max-rounds 4]
@@ -40,18 +29,11 @@ Usage: calib-push.py [--port 7770] [--parallel 64] [--container arbench]
 import argparse
 import concurrent.futures
 import json
-import os
 import subprocess
 import sys
 import time
 import urllib.request
 
-_HERE = os.path.dirname(os.path.abspath(__file__)) if "__file__" in globals() else os.getcwd()
-if _HERE not in sys.path:
-    sys.path.insert(0, _HERE)
-
-import qwen38_common as qc  # noqa: E402 - sibling module, same directory
-
 DONE_MARK = "calibration wrote"
 
 
@@ -67,9 +49,9 @@ def tap_done(container):
     return DONE_MARK in (out.stdout + out.stderr)
 
 
-def push_one(url, prompt, model):
+def push_one(url, prompt):
     body = json.dumps({
-        "model": model,
+        "model": "frank-archon",
         "prompt": prompt,
         "max_tokens": 1,
         "temperature": 0,
@@ -86,151 +68,38 @@ def push_one(url, prompt, model):
         return False
 
 
-def push_round(url, prompts, model, parallel):
+def main():
-    """Push the whole corpus once; returns how many requests were accepted."""
-    ok = 0
-    with concurrent.futures.ThreadPoolExecutor(parallel) as ex:
-        for good in ex.map(lambda p: push_one(url, p, model), prompts):
-            ok += 1 if good else 0
-    return ok
-
-
-def tap_bytes(path):
-    """Bytes the tap has sealed so far; 0 when the directory is absent.
-
-    A tap whose directory is wrong, full or read-only stops writing while the
-    engine keeps answering 200 — the driver then re-pushes the whole corpus for
-    every round it is allowed and the loss is invisible until the hours are gone.
-    """
-    total = 0
-    try:
-        for root, _, files in os.walk(path):
-            for f in files:
-                try:
-                    total += os.path.getsize(os.path.join(root, f))
-                except OSError:
-                    pass
-    except OSError:
-        return 0
-    return total
-
-
-def round_verdict(before, after, done):
-    """What one round's tap bytes mean.
-
-    'done'   the engine logged that it sealed the tap — the run is over
-    'shrink' the tap LOST bytes: reset, pruned or replaced under us
-    'grew'   sealed bytes this round
-    'flat'   sealed nothing — which is legitimate: RADIANCE_CALIB_TOKENS is a
-             pooled floor, and a round that does not reach it has nothing to
-             write yet (the campaign's corpus is 10.03M tokens against a 12M
-             floor, so round 1 is always flat). Failing on it aborted the run
-             exactly one round too early.
-    """
-    if done:
-        return "done"
-    if after < before:
-        return "shrink"
-    if after == before:
-        return "flat"
-    return "grew"
-
-
-def require_rig(a):
-    """Refuse unless the rig that opened this tap is up and serving right now.
-
-    Three facts, in order: the runner wrote its marker into the tap dir, the
-    marker names the container this pusher targets, and that container is
-    running. A marker without a live container is a boot that died; a live
-    container without a marker is some other engine on the port — on 2026-10-29
-    it was restored production, which took four rounds of 10M tokens before the
-    old driver admitted it had recorded nothing.
-    """
-    marker = os.path.join(a.tap_dir, a.tap_marker)
-    if not os.path.isfile(marker):
-        qc.refuse(f"no rig marker at {marker}: this tap was not opened by "
-                  "run-qwen38-bf16.sh calib, so a push here would feed whatever "
-                  "answers the port and record nothing")
-    try:
-        lines = open(marker, encoding="utf-8", errors="replace").read().splitlines()
-    except OSError as exc:
-        qc.refuse(f"cannot read the rig marker {marker}: {exc}")
-    meta = dict(line.split("=", 1) for line in lines if "=" in line)
-    who = meta.get("container", "")
-    if who != a.container:
-        qc.refuse(f"the rig marker names container {who!r} and this pusher targets "
-                  f"{a.container!r} — wrong tap, or a stale marker")
-    try:
-        p = subprocess.run(["podman", "inspect", "-f", "{{.State.Running}}", a.container],
-                           capture_output=True, text=True, timeout=30)
-    except Exception as exc:
-        qc.refuse(f"cannot inspect the rig container {a.container}: {exc}")
-    if p.returncode != 0 or p.stdout.strip() != "true":
-        qc.refuse(f"the rig container {a.container} is not running — whatever is "
-                  "answering the port, it is not the calibration rig")
-
-
-def parse_args():
     ap = argparse.ArgumentParser()
     ap.add_argument("--port", type=int, default=7770)
     ap.add_argument("--parallel", type=int, default=64)
     ap.add_argument("--container", default="arbench")
-    ap.add_argument("--model", default="frank-archon")
-    ap.add_argument("--tap-dir", default="/home/dank/campaign/qwen38-w5nl64/calib")
-    ap.add_argument("--tap-marker", default=".rig-boot",
-                    help="the file run-qwen38-bf16.sh calib writes into the tap dir; without it the pusher refuses, because an unmarked tap is not a rig")
     ap.add_argument("--corpus", default="/home/dank/corpora/out/calib.jsonl")
     ap.add_argument("--max-rounds", type=int, default=4)
-    return ap.parse_args()
+    a = ap.parse_args()
-
-
-def load_prompts(a) -> list[str]:
-    if not os.path.isfile(a.corpus):
-        qc.refuse(f"no corpus at {a.corpus}")
-    prompts = []
-    for lineno, rec in qc.iter_jsonl(a.corpus):
-        if not isinstance(rec.get("prompt"), str):
-            qc.refuse(f"{a.corpus}:{lineno} has no string 'prompt' field")
-        prompts.append(rec["prompt"])
-    if not prompts:
-        qc.refuse(f"the corpus at {a.corpus} holds no prompts")
-    return prompts
-
-
-def main():
-    a = parse_args()
     url = f"http://127.0.0.1:{a.port}/v1/completions"
-    prompts = load_prompts(a)
+
-    require_rig(a)
+    prompts = []
-    chars = sum(len(p) for p in prompts)
+    with open(a.corpus) as f:
-    print(f"corpus: {len(prompts)} prompts, ~{chars // 4} tokens (chars/4)",
+        for line in f:
-          flush=True)
+            line = line.strip()
+            if line:
+                prompts.append(json.loads(line)["prompt"])
+    print(f"corpus: {len(prompts)} prompts", flush=True)
 
     for rnd in range(1, a.max_rounds + 1):
         if tap_done(a.container):
             break
-        before = tap_bytes(a.tap_dir)
         t0 = time.time()
-        ok = push_round(url, prompts, a.model, a.parallel)
+        ok = 0
-        dt = max(time.time() - t0, 1e-9)
+        with concurrent.futures.ThreadPoolExecutor(a.parallel) as ex:
+            for good in ex.map(lambda p: push_one(url, p), prompts):
+                ok += 1 if good else 0
+        dt = time.time() - t0
         print(f"round {rnd}: {ok}/{len(prompts)} ok in {dt:.0f}s "
-              f"({chars / 4 / dt:.0f} tokens/s est)", flush=True)
+              f"({sum(len(p) for p in prompts)/4/dt:.0f} chars/s est)",
-        if ok == 0:
+              flush=True)
-            print("FAIL: not one prompt was accepted; fix the engine or the argv "
-                  "before spending another round", flush=True)
-            sys.exit(1)
         if tap_done(a.container):
             break
-        after = tap_bytes(a.tap_dir)
-        verdict = round_verdict(before, after, False)
-        if verdict == "shrink":
-            print(f"FAIL: the tap at {a.tap_dir} LOST bytes this round "
-                  f"({before} B before, {after} B after) — it was reset or replaced "
-                  "under us", flush=True)
-            sys.exit(1)
-        if verdict == "flat":
-            print(f"round {rnd}: the tap sealed nothing yet (byte floor not reached; "
-                  f"{before} B) — continuing", flush=True)
     else:
         print("max rounds exhausted, tap not done", flush=True)
         sys.exit(1)

scripts/census-frank-dragoon.sh

@@ -21,7 +21,7 @@
 # deployed knob has since dropped to 262144.
 set -euo pipefail
 
-IMG=ghcr.io/peonist-ai/halogen-flash-server@sha256:e35133b206da3094cc4d70c78800b26235bd9124b9aeb0e029d4a7c153b9cff0
+IMG=ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a
 CUR=/home/dank/models/halogen-flashnext-v2
 NEW=/home/dank/models/halogen-v2-abliterated
 CUR_CK=qwen38-flash-next-v2-swift15-abliterated.hgn

scripts/convert-qwen38-w5nl64.sh

@@ -1,236 +0,0 @@
-#!/usr/bin/env bash
-# convert-qwen38-w5nl64.sh — RUNS ON DANKSERVER. The CPU half of the Qwen3.8-Flash-Next five-bit
-# campaign: convert the vendor BF16 checkpoint into the campaign's arms, each one the whole
-# `w5nl64a8h` rung on BOTH expert projections with the protected experts kept bf16.
-#
-# Nothing here touches a GPU: the container is started without /dev/kfd or /dev/dri, so the
-# converter runs on the host backend and the fleet can keep serving through the whole script.
-# The engine pin is the digest that serves frank-archon, so a winning arm crosses no version
-# boundary between measurement and serving.
-#
-# Three arms, because the campaign's question is which search knob pays for its hours
-# (recipes/qwen4exp-qwen38-w5nl64-bf16trunk.recipe):
-#
-#   cd3     the recipe as written — coordinate descent three sweeps. The control.
-#   cd6     six sweeps: the same search, twice the passes.
-#   ao1     act_order=1 instead of cd: GPTQ sweeps columns in activation-importance order and
-#           stores them permuted. This is a SEPARATE arm, not a fourth sweep — libquant refuses
-#           cd= together with act_order=1 ("cd= sweeps the columns in their stored order, and
-#           act_order=1 stores them permuted; one or the other", libquant/lq_registry.cpp), so
-#           the two knobs cannot be combined into a best-of-both container.
-#
-# The arms are generated from ONE template with `--quant` overrides, not three near-duplicate
-# recipes: --quant rules are inserted BEFORE the recipe file and the first rule whose glob matches
-# a weight decides it (core/format/recipe.cpp: Recipe::match), so an override cleanly replaces the
-# expert line and the other 60 lines cannot drift between arms.
-#
-# Protected experts: apply-protected-cast.sh derives the bf16 set from THIS campaign's grams
-# (--target-count 48, two per layer so each rank's 256-expert half stays even) and splices it into
-# a per-run COPY of the template; the committed recipe keeps its markers and stays reviewable.
-#
-# Gates, in the order they bite — each one is a lesson the swift15 campaign paid for:
-#   inputs        checkpoint (dir + index), recipe, grams, imatrix, tokenizer. A missing grams
-#                 directory converts UNCALIBRATED with one stderr note, which is silently worse
-#                 than failing here.
-#   reference     the 335.3 GiB BF16 reference container must be GONE before the converts start.
-#                 It and the checkpoint together eat the volume; its job (the KLD recording and
-#                 the calibration grams) is finished by then, and both survive on disk without the
-#                 container beside it. The FP8-native anchor is FETCHED after the converts (disk
-#                 sequencing), so nothing here waits on it.
-#   plan          --plan-only runs FIRST, per arm, and prints "about X would be written". The
-#                 number is the bill: free space must cover it plus the 128k-prompt overshoot
-#                 margin, and the finished artifact is checked against it.
-#   outputs       no arm overwrites anything; move the old one to trash.
-#
-# Usage: convert-qwen38-w5nl64.sh [--arm cd3|cd6|ao1]... [--dry-run] [--plan-only]
-#                                 [--target-count N] [--keep-recipe]
-set -u -o pipefail
-
-SELF="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-# THE TOOLCHAIN PIN. `:latest` on 2026-10-30 is v1.14.0 (revision 4a61d7296bc5),
-# the same image the tap producer boots: a tap must be converted by the line that
-# is current, and rad-convert's `gptq:calib=<dir>` input contract is version-stable
-# (RADGRAM2 + gram.r<rank>.<stem>.bin), so nothing else about the recipe moves with
-# it. Production stays on its own pin — this is the campaign's toolchain.
-IMAGE=${IMAGE:-stilldeadcode/radiance@sha256:69add58f7de1ed2bca2b1e20a4cc75717557df3f73569a178eca5aafe8c44093}
-CKPT=${CKPT:-/home/dank/models/Qwen3.8-Flash-Next}
-CAMPAIGN=${CAMPAIGN:-/home/dank/campaign/qwen38-w5nl64}
-RECIPE=${RECIPE:-$SELF/recipes/qwen4exp-qwen38-w5nl64-bf16trunk.recipe}
-CALIB=${CALIB:-$CAMPAIGN/calib}
-IMATRIX=${IMATRIX:-$CAMPAIGN/imatrix.gguf}
-OUTDIR=${OUTDIR:-/home/dank/models/rad}
-BF16_RAD=${BF16_RAD:-$OUTDIR/qwen38-bf16.rad}   # the reference container, not an arm output
-STATE=${STATE:-$CAMPAIGN}                      # the dir the container mounts read-only: the
-                                               # spliced recipe and the imatrix live here
-TARGET_COUNT=${TARGET_COUNT:-48}
-MIN_GRAMS=${MIN_GRAMS:-24576}                 # per-expert DOWN grams: 48 recorded layers x 512
-                                               # experts. The checkpoint has 49 MoE layers, but the
-                                               # MTP layer is never recorded, so its 512 experts are
-                                               # absent from the tap's output by design
-MARGIN_MIB=${MARGIN_MIB:-40960}               # the long-prompt overshoot, off the plan number
-TS=$(date +%Y%m%d-%H%M%S)
-
-ARMS=()
-DRY=0
-PLAN_ONLY=0
-KEEP_RECIPE=0
-while [ "$#" -gt 0 ]; do
-    case "$1" in
-      --arm) [ "$#" -ge 2 ] || { echo "--arm needs a value (cd3|cd6|ao1)" >&2; exit 2; }
-             ARMS+=("$2"); shift 2 ;;
-      --dry-run) DRY=1; shift ;;
-      --plan-only) PLAN_ONLY=1; shift ;;
-      --target-count) [ "$#" -ge 2 ] || { echo "--target-count needs a value" >&2; exit 2; }
-             TARGET_COUNT="$2"; shift 2 ;;
-      --keep-recipe) KEEP_RECIPE=1; shift ;;
-      *) echo "unknown argument: $1" >&2; exit 2 ;;
-    esac
-done
-[ "${#ARMS[@]}" -gt 0 ] || ARMS=(cd3 cd6 ao1)
-for a in "${ARMS[@]}"; do
-    case "$a" in cd3|cd6|ao1) ;; *) echo "unknown arm: $a (cd3|cd6|ao1)" >&2; exit 2 ;; esac
-done
-
-# The expert rule's option set, spelled once. --quant replaces the template's line wholesale, so
-# every option has to be repeated here; `calib=$CALIB` is expanded by the recipe reader from the
-# container environment (core/format/recipe.cpp: expand refuses an unset name rather than taking
-# it for empty).
-expert_opts='table=w5nl,group=64,scale=fp8_e4m3,scale2=f32,block2=*x*,scale2_value=0.0001220703125,transform=fwht128,rule=search,calib=$CALIB'
-arm_quant() {
-    case "$1" in
-      # The control is the template itself: no override, so the recipe's own line decides.
-      cd3) return 0 ;;
-      cd6) echo "blk.*.ffn_*_exps.*.weight=gptq:${expert_opts},cd=6" ;;
-      # act_order=1 WITHOUT cd: libquant refuses the pair (lq_registry.cpp:105, "cd= sweeps the
-      # columns in their stored order, and act_order=1 stores them permuted; one or the other"), so
-      # this arm is the interleave knob alone, not cd=3 plus it.
-      ao1) echo "blk.*.ffn_*_exps.*.weight=gptq:${expert_opts},act_order=1" ;;
-    esac
-}
-
-# --- gates ------------------------------------------------------------------------------------
-[ -d "$CKPT" ] || { echo "no checkpoint at $CKPT; run scripts/download-qwen38-bf16.sh --fetch" >&2; exit 2; }
-[ -f "$CKPT/model.safetensors.index.json" ] || { echo "checkpoint at $CKPT has no safetensors index — a torn fetch" >&2; exit 2; }
-[ -f "$CKPT/tokenizer.json" ] || { echo "no tokenizer.json in $CKPT; the .rad cannot carry one without it" >&2; exit 2; }
-[ -f "$RECIPE" ] || { echo "no recipe at $RECIPE" >&2; exit 2; }
-GRAMS=$(find "$CALIB" -maxdepth 1 -name 'gram.r*.bin' 2>/dev/null | wc -l)
-[ "$GRAMS" -ge "$MIN_GRAMS" ] || {
-    echo "calib dir $CALIB holds $GRAMS gram files (<$MIN_GRAMS); run $0 after run-qwen38-bf16.sh calib" >&2; exit 2; }
-[ -f "$IMATRIX" ] || { echo "no imatrix at $IMATRIX; run scripts/grams-to-imatrix.py over $CALIB" >&2; exit 2; }
-# The container sees the campaign dir at one fixed mount point, so an imatrix kept elsewhere has
-# no path inside it: copy it in (or point IMATRIX at the campaign dir) rather than let the
-# converter fail halfway through a planned arm.
-[ "$(dirname "$IMATRIX")" = "$STATE" ] || {
-    echo "imatrix $IMATRIX is not in the campaign dir $STATE the container mounts; move it there" >&2; exit 2; }
-if [ -e "$BF16_RAD" ]; then
-    echo "the 335.3 GiB BF16 reference container $BF16_RAD is still on disk; its recording and" \
-         "the calibration grams are already taken, so move it to trash — the converts need its" \
-         "space (peak-disk law)" >&2
-    exit 2
-fi
-for a in "${ARMS[@]}"; do
-    [ -e "$OUTDIR/qwen38-w5nl64-$a.rad" ] && {
-        echo "$OUTDIR/qwen38-w5nl64-$a.rad already exists; move it to trash first" >&2; exit 2; }
-    # A killed run leaves its container behind (--rm only fires when podman itself
-    # exits), and the next arm then dies on "name already in use" AFTER the plan
-    # phase; refuse here, where the fix is one `podman rm -f`.
-    podman container exists "qwen38-convert-$a" && {
-        echo "container qwen38-convert-$a still exists (a killed run?);" \
-             "'podman rm -f qwen38-convert-$a' and re-run" >&2
-        exit 2; }
-done
-
-# --- the protected plane, spliced into a per-run copy of the template --------------------------
-mkdir -p "$STATE"
-WORK="$STATE/recipe-$TS.recipe"
-cp "$RECIPE" "$WORK"
-if [ "$DRY" = 1 ]; then
-    echo "would run: $SELF/apply-protected-cast.sh $CALIB $WORK $TARGET_COUNT"
-else
-    # Positional, because the tool reads its recipe and calib dir by position: passing them as
-    # environment variables would be silently ignored and it would rewrite the COMMITTED
-    # template in place instead of this run's copy.
-    "$SELF/apply-protected-cast.sh" "$CALIB" "$WORK" "$TARGET_COUNT" \
-        || { echo "the protected-expert derivation refused; the arms would convert unprotected" >&2; exit 1; }
-fi
-
-run_convert() { # run_convert ARM [extra flags...]
-    local arm="$1"; shift
-    local out="$OUTDIR/qwen38-w5nl64-$arm.rad" log="$STATE/convert-$arm-$TS.log"
-    local argv=(--rm --name "qwen38-convert-$arm"
-                -e "CALIB=/data/calib" -e "OMP_NUM_THREADS=$(nproc)"
-                -v "$(dirname "$CKPT"):/models:ro"
-                -v "$CALIB:/data/calib:ro"
-                -v "$STATE:/campaign:ro"
-                -v "$OUTDIR:/out")
-    local conv=(/models/"${CKPT##*/}" --recipe "/campaign/$(basename "$WORK")"
-                --tokenizer "/models/${CKPT##*/}/tokenizer.json"
-                --imatrix /campaign/"${IMATRIX##*/}"
-                # No --max-ctx: the context declare then runs at the checkpoint's training context
-                # (262144), which is what the shipped container did — rad-info --meta on it carries
-                # no override. A container declared at a smaller bound cannot be expected to serve
-                # the 200k window D2 holds, and the convert is not where to discover that.
-                # --kv-cache-dtype changes nothing in the artifact; it picks the kernels the declare
-                # checks, and the fleet serves fp8 KV, so an unresolvable fp8 kernel must be said no
-                # to by the convert, not by a boot on a drained window.
-                --kv-cache-dtype fp8 -o "/out/$(basename "$out")")
-    local q; q=$(arm_quant "$arm")
-    [ -n "$q" ] && conv+=(--quant "$q")
-    if [ "$DRY" = 1 ]; then
-        echo "podman run ${argv[*]} \$IMAGE --entrypoint /opt/radiance/bin/rad-convert ${conv[*]} $*"
-        return 0
-    fi
-    podman run "${argv[@]}" --entrypoint /opt/radiance/bin/rad-convert "$IMAGE" "${conv[@]}" "$@" \
-        2>&1 | tee "$log"
-    return "${PIPESTATUS[0]}"
-}
-
-# --- plan, then bill, then convert -------------------------------------------------------------
-overall=0
-for arm in "${ARMS[@]}"; do
-    echo "== arm $arm =="
-    if [ "$DRY" = 1 ]; then
-        # Both lines, in order: the plan runs before the convert, and the convert is what the
-        # operator is about to pay an afternoon for.
-        run_convert "$arm" --plan-only
-        run_convert "$arm"
-        continue
-    fi
-    rc=0; plan_log=$(run_convert "$arm" --plan-only) || rc=$?
-    [ "$rc" -eq 0 ] || { echo "arm $arm: --plan-only failed (rc=$rc); nothing was written" >&2; overall=1; continue; }
-    echo "$plan_log"
-    # "about 141.2 GiB would be written" is the converter's own bill; parse it rather than
-    # hardcoding a size, so the gate still works after any recipe edit.
-    want=$(printf '%s' "$plan_log" | sed -n 's/.*about \([0-9.]*\) \([KMGT]iB\) would be written.*/\1 \2/p' | tail -1)
-    [ -n "$want" ] || { echo "arm $arm: the plan printed no size; refusing to convert blind" >&2; overall=1; continue; }
-    need_mib=$(awk -v n="${want% *}" -v u="${want#* }" \
-        'BEGIN{ f = (u=="KiB") ? 2^-10 : (u=="MiB") ? 1 : (u=="GiB") ? 1024 : (u=="TiB") ? 1048576 : 0
-               if (f == 0) { exit 1 }; printf "%d", n*f + 0.5 }') || {
-        echo "arm $arm: the plan printed an unknown unit in '$want'" >&2; overall=1; continue; }
-    free_mib=$(df --output=avail -m "$OUTDIR" | tail -1 | tr -d ' ')
-    echo "plan: $want ($need_mib MiB); free ${free_mib} MiB on $OUTDIR (margin $MARGIN_MIB MiB)"
-    if [ "$free_mib" -lt $((need_mib + MARGIN_MIB)) ]; then
-        echo "arm $arm: needs ${need_mib} MiB + ${MARGIN_MIB} margin, ${free_mib} free; free space and re-run" >&2
-        overall=1; continue
-    fi
-    if [ "$PLAN_ONLY" = 1 ]; then echo "planned, not converted (--plan-only)"; continue; fi
-    rc=0; run_convert "$arm" || rc=$?
-    [ "$rc" -eq 0 ] || { echo "arm $arm: rad-convert rc=$rc; log: $STATE/convert-$arm-$TS.log" >&2; overall=1; continue; }
-    out="$OUTDIR/qwen38-w5nl64-$arm.rad"
-    [ -f "$out" ] || { echo "arm $arm: rad-convert exited 0 but wrote no $out; log: $STATE/convert-$arm-$TS.log" >&2; overall=1; continue; }
-    got_mib=$(( $(stat -c %s "$out") / 1048576 ))
-    # The receipt: the artifact is what the plan predicted, within the metadata the plan does not
-    # count. An arm that came out materially smaller lost a plane somewhere.
-    lo=$(( need_mib * 98 / 100 )); hi=$(( need_mib * 103 / 100 ))
-    if [ "$got_mib" -lt "$lo" ] || [ "$got_mib" -gt "$hi" ]; then
-        echo "arm $arm: $out is ${got_mib} MiB, the plan said ${need_mib} MiB (allowed ${lo}-${hi})" >&2
-        overall=1; continue
-    fi
-    echo "CONVERT_DONE $arm ${got_mib} MiB -> $out"
-done
-
-if [ "$KEEP_RECIPE" = 0 ] && [ "$DRY" = 0 ]; then
-    mkdir -p "$CAMPAIGN/.AGENTTRASH"
-    mv "$WORK" "$CAMPAIGN/.AGENTTRASH/$(basename "$WORK")" 2>/dev/null || true
-fi
-exit "$overall"

scripts/deploy-plan.py

@@ -34,16 +34,12 @@ SERVICE_ORDER = (
     "hermes",
     "hermes-dashboard",
     "hermes-webui",
+    "prometheus",
     "grafana",
     "loki",
     "alloy",
     "node-exporter",
-    "cadvisor",
-    "gpu-exporter",
     "alertmanager",
-    # The prober must answer before prometheus re-runs the services job.
-    "blackbox-exporter",
-    "prometheus",
     "authentik-postgres",
     "authentik-server",
     "authentik-worker",
@@ -96,10 +92,7 @@ DANKCLAW_SERVICES = {
     "loki",
     "alloy",
     "node-exporter",
-    "cadvisor",
-    "gpu-exporter",
     "alertmanager",
-    "blackbox-exporter",
     "authentik-postgres",
     "authentik-server",
     "authentik-worker",
@@ -131,8 +124,6 @@ DANKSERVER_SERVICES = {
     "readarr",
     "frank-archon",
     "node-exporter",
-    "cadvisor",
-    "gpu-exporter",
 }
 
 # FrankBook-Pro runs the *arr stack + qBittorrent inside a podman machine on
@@ -155,14 +146,13 @@ DANKCLAW_COMPOSE_SERVICES = set()
 # Quadlet unit now — the last compose services were the hermes trio, whose units
 # have owned their containers since 2026-09-12 and whose compose blocks were
 # dead weight that could only create a duplicate container.
-# jellyfin left the Dankserver file on 2026-10-30 for the same reason: its Quadlet
-# has owned the container since the cutover, so a compose edit must not restart it.
 
 DANKSERVER_COMPOSE_SERVICES = {
     "mariadb",
     "redis",
     "romm",
     "copyparty",
+    "jellyfin",
     "calibre-web",
 }
 COMPOSE_NAME_MAP = {"mariadb": "romm-mariadb", "redis": "romm-redis"}
@@ -281,8 +271,6 @@ def services_for_path(path: str, target: str) -> set[str]:
             # Provisioned datasources and dashboards: git is the source of
             # truth, so a change here must restart the service that reads them.
             _add(services, "grafana")
-        elif group == "blackbox":
-            _add(services, "blackbox-exporter")
         elif group == "homepage":
             # Homepage is a Dankclaw-owned deployment. Shared homepage files
             # are intentionally not copied during a Dankserver-only run.
@@ -386,7 +374,7 @@ def services_for_path(path: str, target: str) -> set[str]:
             # consumer (prometheus before grafana, loki before alloy).
             if len(parts) >= 4 and parts[2] == "quadlet":
                 name = parts[3].removesuffix(".container")
-                if name in {"prometheus", "grafana", "loki", "alloy", "node-exporter", "cadvisor", "alertmanager", "blackbox-exporter"}:
+                if name in {"prometheus", "grafana", "loki", "alloy", "node-exporter", "alertmanager"}:
                     _add(services, name)
             return services
         if len(parts) >= 2 and parts[1] == "gitea":
@@ -422,11 +410,6 @@ def services_for_path(path: str, target: str) -> set[str]:
                 "tautulli": {"tautulli"},
             }
             _add(services, *quadlet_services.get(parts[1], set()))
-        if len(parts) >= 2 and parts[1] == "host":
-            # dankserver/host/systemd/media-meta-view.mount is the overlay view the
-            # media servers bind (scripts/media-view.sh installs it on the host),
-            # so editing it restarts jellyfin and plex and nothing else.
-            _add(services, "jellyfin", "plex")
         if len(parts) >= 2 and parts[1] == "observability":
             # Dankserver's node-exporter became a Quadlet unit on 2026-09-16
             # (serverAppConfigs-docs/Infrastructure/Observability.md): its
@@ -434,8 +417,8 @@ def services_for_path(path: str, target: str) -> set[str]:
             # node-dankserver job had nothing to scrape.
             if len(parts) >= 4 and parts[2] == "quadlet":
                 name = parts[3].removesuffix(".container")
-                if name in {"node-exporter", "cadvisor"}:
+                if name == "node-exporter":
-                    _add(services, name)
+                    _add(services, "node-exporter")
             return services
         # frank-archon's quadlet-era directory left the tree on 2026-09-26
         # (the Lucebox DS4.1 unit was retired for the llama.cpp root unit —
@@ -466,21 +449,6 @@ def services_for_path(path: str, target: str) -> set[str]:
             # change to it redeploying alertmanager is the only path that
             # reaches it on the host.
             _add(services, "alertmanager")
-        if name in {"gpu-exporter.py", "gpu-exporter.service"}:
-            # The host-process GPU exporter is installed directly by the
-            # gpu-exporter deploy on BOTH hosts, so its script and unit select
-            # that service (target_services then keeps it only on the host being
-            # planned). Editing the collector restarts the running exporter.
-            _add(services, "gpu-exporter")
-        if name == "media-view.sh":
-            # The installer is what creates, mounts and reaps the view both media
-            # servers read, so a change to it is a restart of that pair.
-            _add(services, "jellyfin", "plex")
-        if name == "jellyfin-providers.sh":
-            # The deployer runs this before jellyfin restarts, so a change to
-            # the installer is a change to the provider state Jellyfin loads at
-            # start-up: it selects jellyfin and nothing else.
-            _add(services, "jellyfin")
         if name in {"frank-zealot.env", "frank-zealot.service", "serve-frank-zealot.sh"}:
             # llama.cpp frank-zealot (2026-09-16) keeps its unit, env and serve
             # files here; each one selects frank-zealot only. The ik_llama.cpp

scripts/deploy-remote.sh

@@ -86,7 +86,7 @@ service_is_allowed() {
         dankclaw:open-webui|dankclaw:gitea-postgres|dankclaw:gitea-server|\
         dankclaw:comfyui|dankclaw:hermes|\
         dankclaw:hermes-dashboard|dankclaw:hermes-webui|dankclaw:prometheus|dankclaw:grafana|\
-        dankclaw:loki|dankclaw:alloy|dankclaw:node-exporter|dankclaw:cadvisor|dankclaw:gpu-exporter|dankclaw:alertmanager|dankclaw:blackbox-exporter|\
+        dankclaw:loki|dankclaw:alloy|dankclaw:node-exporter|dankclaw:alertmanager|\
         dankclaw:authentik-postgres|dankclaw:authentik-server|\
         dankclaw:authentik-worker|dankclaw:authentik-outpost|dankclaw:authentik-outpost-ldap|dankclaw:anubis|\
         dankclaw:caddy|dankclaw:homepage|dankclaw:seerr|dankclaw:marreta|\
@@ -97,7 +97,7 @@ service_is_allowed() {
         dankserver:copyparty|dankserver:jellyfin|dankserver:calibre-web|dankserver:calibre-server|dankserver:plex|dankserver:tautulli|\
         dankserver:prowlarr|dankserver:qbittorrent|dankserver:radarr|\
         dankserver:sonarr|dankserver:lidarr|dankserver:readarr|\
-        dankserver:frank-archon|dankserver:node-exporter|dankserver:cadvisor|dankserver:gpu-exporter|\
+        dankserver:frank-archon|dankserver:node-exporter|\
         frankbook-pro:gluetun|frankbook-pro:qbittorrent|frankbook-pro:prowlarr|\
         frankbook-pro:radarr|frankbook-pro:sonarr|frankbook-pro:lidarr|\
         frankbook-pro:readarr)
@@ -252,24 +252,16 @@ install_signal_relay() {
     # The relay binds the host's LAN IP (the one address a bridge container
     # can reach as host.containers.internal), so keep the unauthenticated
     # endpoint off the rest of the LAN: admit loopback, the host itself
-    # (its own health probe) and the podman bridge subnet only.
+    # (its own health probe) and the podman bridge subnet only. Idempotent:
-    # ORDER IS THE GATE: `iptables -I` inserts at position 1, so the old
+    # -C before -I.
-    # shape (-C/-I x3 ACCEPT, then -C/-I the DROP) landed the blanket DROP
-    # ABOVE the ACCEPTs and every probe timed out beside a LISTENing socket
-    # (live 2026-10-21: 159 packets on the DROP, 0 on each ACCEPT; the whole
-    # dankclaw drain aborted at the alertmanager gate twice before the cause
-    # was read off `nft list ruleset`). Rebuild the tail instead of inserting
-    # it: delete any blanket DROP wherever it sits, keep the three ACCEPTs
-    # at the head (-C before -I, unchanged), then APPEND the DROP so it is
-    # last and the ACCEPTs decide first. Converges on poisoned hosts.
-    run_privileged iptables -D INPUT -p tcp --dport 18093 -j DROP 2>/dev/null || true
     run_privileged iptables -C INPUT -p tcp --dport 18093 -s 127.0.0.1 -j ACCEPT 2>/dev/null \
         || run_privileged iptables -I INPUT -p tcp --dport 18093 -s 127.0.0.1 -j ACCEPT
     run_privileged iptables -C INPUT -p tcp --dport 18093 -s 192.168.0.143 -j ACCEPT 2>/dev/null \
         || run_privileged iptables -I INPUT -p tcp --dport 18093 -s 192.168.0.143 -j ACCEPT
     run_privileged iptables -C INPUT -p tcp --dport 18093 -s 10.89.0.0/16 -j ACCEPT 2>/dev/null \
         || run_privileged iptables -I INPUT -p tcp --dport 18093 -s 10.89.0.0/16 -j ACCEPT
-    run_privileged iptables -A INPUT -p tcp --dport 18093 -j DROP
+    run_privileged iptables -C INPUT -p tcp --dport 18093 -j DROP 2>/dev/null \
+        || run_privileged iptables -I INPUT -p tcp --dport 18093 -j DROP
     # The interpreter needs a moment to bind after restart; a one-shot curl
     # raced the socket on 2026-09-17 and failed a healthy deploy.
     local i
@@ -283,81 +275,14 @@ install_signal_relay() {
     return 1
 }
 
-# Host-process GPU metrics exporter (amdgpu sysfs + nvidia-smi). Not a quadlet:
-# it runs python3 from the checkout on the host so it can read the DRM/cgroup
-# sysfs and shell out to nvidia-smi. Same two-address bind posture as
-# node-exporter/cadvisor (loopback + this host's LAN), so it is never a wildcard.
-deploy_gpu_exporter() {
-    local unit_dir="$HOME/.config/systemd/user" lan dropin i
-    case "$TARGET" in
-        dankclaw) lan=192.168.0.143 ;;
-        dankserver) lan=192.168.0.235 ;;
-        *) echo "gpu-exporter: unknown target '$TARGET'" >&2; return 2 ;;
-    esac
-    mkdir -p "$unit_dir"
-    cp scripts/gpu-exporter.service "$unit_dir/gpu-exporter.service"
-    dropin="$unit_dir/gpu-exporter.service.d"
-    mkdir -p "$dropin"
-    printf '[Service]\nEnvironment=GPU_EXPORTER_BINDS=127.0.0.1,%s\n' "$lan" \
-        > "$dropin/bind.conf"
-    systemctl --user daemon-reload
-    systemctl --user enable gpu-exporter.service
-    systemctl --user restart gpu-exporter.service
-    # The interpreter needs a moment to bind after restart (the same race that
-    # once failed a healthy signal-relay deploy).
-    for i in $(seq 1 15); do
-        curl -fsS -m 5 http://127.0.0.1:9401/metrics >/dev/null && return 0
-        sleep 1
-    done
-    echo "gpu-exporter is not answering on 127.0.0.1:9401/metrics" >&2
-    return 1
-}
-
 copy_loki_config() {
     run_privileged mkdir -p /opt/loki/config
     run_privileged cp shared/loki/loki-config.yaml /opt/loki/config/loki-config.yaml
 }
 
 copy_alloy_config() {
-    # The repo config carries the token GRAFANA_HOST_LABEL; the installed copy
+    run_privileged mkdir -p /opt/alloy/config
-    # carries the host's name, so Loki streams say WHICH machine's journal a
+    run_privileged cp shared/alloy/config.alloy /opt/alloy/config/config.alloy
-    # line came from without a second config file per host.
-    # *_CONF_ROOT are test seams: the bats cases execute these copiers for
-    # real against a sandbox with a stubbed run_privileged.
-    local root="${ALLOY_CONF_ROOT:-/opt/alloy}" tmp
-    tmp="$(mktemp)"
-    sed "s/GRAFANA_HOST_LABEL/$TARGET/g" shared/alloy/config.alloy > "$tmp"
-    if ! grep -q "host = \"$TARGET\"," "$tmp" || grep -q "GRAFANA_HOST_LABEL" "$tmp"; then
-        echo "alloy config: host-label substitution failed" >&2
-        rm -f "$tmp"
-        return 1
-    fi
-    # Syntax gate: alloy's config language has no schema — a misplaced
-    # attribute (e.g. `on_error` outside the json stage) parses only at RUN
-    # time, and the unit then crash-loops with a healthy-looking deploy.
-    # Validate against the very image that will run it, before installing.
-    # Skipped only in the bats sandbox (no image there).
-    if [ "$root" = "/opt/alloy" ] || podman image exists localhost/franksdank/alloy:latest 2>/dev/null; then
-        if ! podman run --rm -v "$tmp:/c.alloy:ro" \
-                --entrypoint /usr/bin/alloy localhost/franksdank/alloy:latest \
-                validate /c.alloy; then
-            echo "alloy config: validate FAILED against the pinned image" >&2
-            rm -f "$tmp"
-            return 1
-        fi
-    fi
-    run_privileged mkdir -p "$root/config"
-    run_privileged cp "$tmp" "$root/config/config.alloy"
-    rm -f "$tmp"
-}
-
-copy_blackbox_config() {
-    # Single-file mount target: the unit binds this exact path into
-    # /etc/blackbox_exporter/config.yml. cp (not cp -r) keeps it one file.
-    # BLACKBOX_CONF_ROOT is the same test seam.
-    local root="${BLACKBOX_CONF_ROOT:-/opt/blackbox}"
-    run_privileged mkdir -p "$root"
-    run_privileged cp shared/blackbox/blackbox.yml "$root/blackbox.yml"
 }
 
 copy_grafana_provisioning() {
@@ -366,25 +291,14 @@ copy_grafana_provisioning() {
     # datasource would be invisible to review, lost with the data volume, and
     # unknown to anyone reading the repository. The unit already mounts
     # /opt/grafana/provisioning read-only, so this only has to populate it.
-    # GRAFANA_PROV_ROOT is the test seam: point it at a sandbox and the whole
+    run_privileged mkdir -p /opt/grafana/provisioning/datasources \
-    # copy runs unprivileged (the bats case executes this function for real).
+        /opt/grafana/provisioning/dashboards
-    local root="${GRAFANA_PROV_ROOT:-/opt/grafana}"
-    run_privileged mkdir -p "$root/provisioning/datasources" \
-        "$root/provisioning/dashboards"
     run_privileged cp shared/grafana/provisioning/datasources/prometheus.yml \
-        "$root/provisioning/datasources/prometheus.yml"
+        /opt/grafana/provisioning/datasources/prometheus.yml
     run_privileged cp shared/grafana/provisioning/dashboards/provider.yml \
-        "$root/provisioning/dashboards/provider.yml"
+        /opt/grafana/provisioning/dashboards/provider.yml
-    # EVERY dashboard JSON rides, not a hand-listed subset: the fleet provider
+    run_privileged cp shared/grafana/provisioning/dashboards/llm-fleet.json \
-    # turns each file in the directory into a dashboard, so a copier that names
+        /opt/grafana/provisioning/dashboards/llm-fleet.json
-    # files one by one silently drops new boards (measured 2026-10-21: the
-    # containers board existed in the repo since its commit and was NEVER
-    # provisioned — the panel-census browser check could not find it while the
-    # hand-placed older boards happened to be on disk). Same rule as the quadlet
-    # tier: the directory is the contract, the copy is generated state.
-    for dash in shared/grafana/provisioning/dashboards/*.json; do
-        run_privileged cp "$dash" "$root/provisioning/dashboards/$(basename "$dash")"
-    done
 }
 
 render_caddyfile() {
@@ -606,11 +520,6 @@ deploy_observability() {
             ;;
         node-exporter)
             ;;
-        cadvisor)
-            ;;
-        blackbox-exporter)
-            copy_blackbox_config
-            ;;
         *)
             echo "unknown observability service: $service" >&2
             return 2
@@ -624,10 +533,6 @@ deploy_observability() {
         grafana) wait_for_health grafana http://127.0.0.1:3002/api/health 90 ;;
         loki) wait_for_health loki http://127.0.0.1:3100/ready 60 ;;
         node-exporter) wait_for_health node-exporter http://127.0.0.1:9100/metrics 60 ;;
-        cadvisor) wait_for_health cadvisor http://127.0.0.1:8080/healthz 90 ;;
-        # Loopback: the exporter binds 127.0.0.1 + LAN (the gateway address
-        # is not bindable from the host netns — see the unit header).
-        blackbox-exporter) wait_for_health blackbox-exporter http://127.0.0.1:9115/-/healthy 60 ;;
     esac
 }
 
@@ -1202,76 +1107,7 @@ deploy_romm_stack() {
     systemctl --user restart "$service.service"
 }
 
-ensure_media_view() {
-    # Both media servers read their library through the SSD-backed overlay view
-    # (scripts/media-view.sh, dankserver/host/systemd/media-meta-view.mount): the
-    # array below stays read-only and every sidecar Jellyfin writes lands on the
-    # NVMe.
-    # Raise it BEFORE either container starts — a start against a bare view
-    # directory would let a scan clear the library database. Each unit gates on
-    # scripts/wait-for-mount.sh, which waits and then refuses the start. A
-    # relayout must be followed by `media-view.sh reap`
-    # (see the Media Relayout page), which this is not.
-    run_privileged bash scripts/media-view.sh install
-    bash scripts/media-view.sh verify
-}
-
-ensure_user_io_delegate() {
-    # The media servers ask for an I/O share (IOWeight= in their quadlets) so a
-    # library scan cannot starve playback or the array's other reader. Two system
-    # drop-ins are what make that request real, and both are host state, so the
-    # deployer places them:
-    #   user.slice.d/io-accounting.conf        io enters user.slice's subtree
-    #   user@1000.service.d/io-delegate.conf   the user manager gets the controller
-    # Without the first, `io` never appears in user.slice/cgroup.subtree_control,
-    # so no container under it can have an io.weight file at all; without the
-    # second the user manager never asks for the controller. systemd hands
-    # user@.service cpu/memory/pids by default and drops a line it cannot honour
-    # without a word — IOWeight= on its own is inert config.
-    local src dst
-    for src in \
-        dankserver/host/systemd/user.slice.d/io-accounting.conf \
-        dankserver/host/systemd/user@1000.service.d/io-delegate.conf; do
-        dst=/etc/systemd/system/${src#dankserver/host/systemd/}
-        run_privileged mkdir -p "$(dirname "$dst")"
-        if ! run_privileged cmp -s "$src" "$dst"; then
-            run_privileged install -m 644 "$src" "$dst"
-            run_privileged systemctl daemon-reload
-        fi
-    done
-    # Accounting lands immediately; the delegation is read when user@1000.service
-    # starts, and restarting that unit would kill every rootless container on this
-    # host. So the share becomes real at the next reboot — say so out loud rather
-    # than let a quadlet line read as live config.
-    if ! systemctl show user@1000.service -p DelegateControllers | grep -qw io; then
-        echo "NOTE: io is not delegated to user@1000.service yet - IOWeight= is"
-        echo "NOTE: inert until the next reboot (see [[Quadlet Lifecycle]])"
-    fi
-}
-
-ensure_provider_keys() {
-    # Jellyfin's metadata-provider keys live in the container-owned plugin
-    # configuration under the data root, never in git; scripts/jellyfin-providers.sh
-    # is what places them, reading the per-service host env file (the fleet
-    # convention: grafana, caddy, pihole, copyparty, romm, seerr) that holds
-    # TMDB_API_KEY= and TVDB_API_KEY=, mode 600.
-    # Missing keys mean a keyless provider — a degraded library, not a broken
-    # deploy — so this warns rather than failing the restart. But when the keys
-    # ARE placed it must happen before the restart: the plugin and its keys are
-    # read at start-up, so a restart first would boot the old state.
-    local keys=/home/dank/Containers/jellyfin/provider-keys
-    if [ -f "$keys" ]; then
-        bash scripts/jellyfin-providers.sh install
-    else
-        echo "WARN: $keys is absent - provider keys NOT placed"
-        echo "WARN: create it (TMDB_API_KEY=, TVDB_API_KEY=, chmod 600) and re-deploy jellyfin"
-    fi
-}
-
 deploy_jellyfin() {
-    ensure_media_view
-    ensure_user_io_delegate
-    ensure_provider_keys
     cp "dankserver/jellyfin/quadlet/jellyfin.container" "$quadlet_unit_dir/"
     systemctl --user daemon-reload
     if ! systemctl --user is-active -q jellyfin.service; then
@@ -1359,8 +1195,6 @@ deploy_copyparty() {
 }
 
 deploy_plex() {
-    ensure_media_view
-    ensure_user_io_delegate
     cp "dankserver/plex/quadlet/plex.container" "$quadlet_unit_dir/"
     systemctl --user daemon-reload
     if ! systemctl --user is-active -q plex.service; then
@@ -1433,17 +1267,11 @@ deploy_authentik() {
     # generated". Boot persistence comes from [Install] WantedBy=default.target
     # inside each .container file, which the generator honors at user-manager
     # start (linger must stay on for the deploy user).
-    # RESTART, not start: `start` on an already-active unit is a no-op, so an
+    systemctl --user start authentik-postgres.service
-    # image bump would install the new digest and keep serving the old
-    # container while every gate stayed green (measured 2026-10-30: server and
-    # worker stayed on the previous release beside an outpost that moved,
-    # because only the outpost handler restarts). The generator has already
-    # re-rendered the unit from the .container, so a restart is what applies it.
-    systemctl --user restart authentik-postgres.service
     wait_container_healthy authentik-postgres 120 || return 1
-    systemctl --user restart authentik-server.service
+    systemctl --user start authentik-server.service
     wait_container_healthy authentik-server 300 || return 1
-    systemctl --user restart authentik-worker.service
+    systemctl --user start authentik-worker.service
 }
 
 deploy_authentik_outpost() {
@@ -1540,10 +1368,9 @@ deploy_anubis() {
 # conversion (2026-10-11) of the abliterated Qwen3.8-Flash-Next —
 # qwen38-flash-next-v2-abliterated.hgn (66,687,678,432 B, ~62 GiB resident)
 # + the REQUIRED n-gram lookup table + the vision tower — MTP spec decode
-# (HALOGEN_SPEC_ADAPT=0), 2 slots over ONE 401,408-position KV pool at the
+# (HALOGEN_SPEC_ADAPT=0), 2 slots over ONE 401,408-position KV pool (2 × ctx,
-# native ctx 262144 ceiling (raised 2026-10-21 from 200704 so the harness can
+# raised 2026-10-18 so BOTH slots can hold a maximum-length request) at the
-# run a 200,000 window with its ~45k fit gap; the pool still carries two
+# ctx 200704 ceiling, image input — on the Strix Halo iGPU. It stays a
-# 200k conversations at once), image input — on the Strix Halo iGPU. It stays a
 # ROOT unit because the serve script drives `podman run` directly (the frank-archon pattern):
 # relink_unit points /etc/systemd/system/frank-dragoon.service at the repo
 # file, boot persistence is that unit's [Install], and LimitMEMLOCK=infinity
@@ -1559,7 +1386,7 @@ deploy_anubis() {
 # artifact would leave a restart-looping unit and a dark endpoint. The
 # port gate is the same as every cutover since 2026-09-16: nothing
 # starts until 7770 is released.
-LLM_DRAGOON_IMAGE="${LLM_DRAGOON_IMAGE:-ghcr.io/peonist-ai/halogen-flash-server@sha256:e35133b206da3094cc4d70c78800b26235bd9124b9aeb0e029d4a7c153b9cff0}"
+LLM_DRAGOON_IMAGE="${LLM_DRAGOON_IMAGE:-ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a}"
 # The payload dir is its own twin because the NPU lane's containment gate below
 # reads it; every artifact path under it stays a full literal as usual.
 LLM_DRAGOON_MODEL_DIR="${LLM_DRAGOON_MODEL_DIR:-/home/dank/models/halogen-v2-abliterated}"
@@ -2173,8 +2000,7 @@ deploy_service() {
         plex) deploy_plex ;;
         tautulli) deploy_tautulli ;;
         alloy) deploy_alloy ;;
-        prometheus|grafana|loki|node-exporter|cadvisor|alertmanager|blackbox-exporter) deploy_observability "$service" ;;
+        prometheus|grafana|loki|node-exporter|alertmanager) deploy_observability "$service" ;;
-        gpu-exporter) deploy_gpu_exporter ;;
         comfyui) deploy_comfyui ;;
         *) deploy_compose_service "$service" ;;
     esac

scripts/deploy.sh

@@ -133,15 +133,13 @@ fi
 valid_service() {
     local service="$1"
     case "$TARGET:$service" in
-        # dankclaw:searxng-network is client-only: a network quadlet with no
-        # remote dispatch handler, so the remote gate does not (must not) list it.
         dankclaw:caddy|dankclaw:gluetun|dankclaw:searxng-network|dankclaw:searxng-valkey|\
         dankclaw:searxng|dankclaw:marreta|dankclaw:pihole|dankclaw:open-webui|dankclaw:gitea-postgres|\
         dankclaw:gitea-server|dankclaw:homepage|\
         dankclaw:comfyui|dankclaw:hermes|dankclaw:hermes-dashboard|\
         dankclaw:hermes-webui|dankclaw:prometheus|dankclaw:grafana|dankclaw:loki|dankclaw:alloy|\
-        dankclaw:alertmanager|dankclaw:blackbox-exporter|\
+        dankclaw:alertmanager|\
-        dankclaw:node-exporter|dankclaw:cadvisor|dankclaw:gpu-exporter|dankclaw:authentik-postgres|dankclaw:authentik-server|\
+        dankclaw:node-exporter|dankclaw:authentik-postgres|dankclaw:authentik-server|\
         dankclaw:authentik-worker|dankclaw:authentik-outpost|dankclaw:authentik-outpost-ldap|dankclaw:anubis|dankclaw:seerr|\
         dankclaw:open-notebook|\
         dankclaw:frank-tts-engine|dankclaw:frank-tts|\
@@ -149,8 +147,8 @@ valid_service() {
         dankserver:romm-mariadb|dankserver:romm-redis|dankserver:romm|\
         dankserver:copyparty|dankserver:jellyfin|dankserver:calibre-web|dankserver:calibre-server|dankserver:plex|dankserver:tautulli|\
         dankserver:qbittorrent|dankserver:radarr|dankserver:sonarr|\
-        dankserver:lidarr|dankserver:readarr|dankserver:node-exporter|dankserver:cadvisor|dankserver:gpu-exporter|\
+        dankserver:lidarr|dankserver:readarr|dankserver:node-exporter|\
-        dankserver:prowlarr|dankserver:frank-archon|\
+        dankserver:frank-archon|\
         frankbook-pro:gluetun|frankbook-pro:qbittorrent|frankbook-pro:prowlarr|\
         frankbook-pro:radarr|frankbook-pro:sonarr|frankbook-pro:lidarr|\
         frankbook-pro:readarr)

scripts/derive-protected-experts.py

@@ -20,16 +20,9 @@ of the Gram is its down-input energy. Rank halves: 0-255, 256-511
 Output: the cast-rule lines (recipe format) on stdout, a report on stderr.
 
 Usage: derive-protected-experts.py <calib dir> [--min-share 0.03]
-       [--min-route-mult 3.0] [--target-count 0]
+       [--min-route-mult 3.0]
-       --target-count N fills the byte bill: the bars pick the base set exactly as
-       the bar-only pass does, then the energy ranking admits experts one at a time
-       (each with its parity partner) until the count lands. The energy bar NEVER
-       relaxes, so asking for 48 bf16 experts never quietly buys 80; the ratio bar
-       walks down only when the ranking cannot produce that many candidates.
-       0 takes the bars as given.
 """
 import argparse
-import collections
 import glob
 import os
 import re
@@ -39,7 +32,6 @@ import sys
 import numpy as np
 
 NAME_RE = re.compile(r"^gram\.r(\d)\.blk\.(\d+)\.ffn_down_exps\.(\d+)\.bin$")
-CAST_RE = re.compile(r"^blk\.(\d+)\.ffn_\*_exps\.(\d+)\.weight")
 
 
 def read_gram(path):
@@ -57,8 +49,27 @@ def read_gram(path):
     return k, rank, int(rows), tr
 
 
-def select(data, min_share, min_route_mult):
+def main():
-    """(cast lines, report lines, count) for one pair of bars."""
+    ap = argparse.ArgumentParser()
+    ap.add_argument("calib_dir")
+    ap.add_argument("--min-share", type=float, default=0.03)
+    ap.add_argument("--min-route-mult", type=float, default=3.0)
+    a = ap.parse_args()
+
+    # layer -> global expert -> (rank, rows, energy)
+    data = {}
+    for path in sorted(glob.glob(os.path.join(
+            a.calib_dir, "gram.r*.ffn_down_exps.*.bin"))):
+        m = NAME_RE.match(os.path.basename(path))
+        if not m:
+            continue
+        rank, layer, expert = int(m.group(1)), int(m.group(2)), int(m.group(3))
+        k, _, rows, tr = read_gram(path)
+        data.setdefault(layer, {})[expert] = (rank, rows, tr)
+
+    if not data:
+        raise SystemExit("no per-expert down grams found")
+
     lines, report = [], []
     total = 0
     for layer in sorted(data):
@@ -72,7 +83,7 @@ def select(data, min_share, min_route_mult):
         for e, (rank, rows, tr) in experts.items():
             es, rs = tr / tot_e, rows / max(tot_r, 1)
             rec = (e, rank, es, rs)
-            if es >= min_share and es >= min_route_mult * rs:
+            if es >= a.min_share and es >= a.min_route_mult * rs:
                 qual.append(rec)
             elif es > 0:
                 pool.append(rec)
@@ -96,148 +107,10 @@ def select(data, min_share, min_route_mult):
                           f"energy {es*100:5.2f}%, routing {rs*100:5.3f}%, "
                           f"ratio {es/max(rs,1e-12):6.1f}")
         total += len(chosen)
-    return lines, report, total
-
-
-def parity_repair(chosen, by_half, report, only=None):
-    """Add the next-best candidate to every half — or to `only` — holding an odd count.
-
-    The four-bit GEMM takes each half's remainder as two equal tables, so an odd count
-    of bf16 experts on a half is not a style problem: the two tables would not match.
-    `by_half` is energy-descending, so the first unchosen candidate is the next most
-    energetic, which is the expert worth keeping. Returns how many were added.
-    """
-    added = 0
-    for key in ([only] if only is not None else sorted(by_half)):
-        layer, half = key
-        n = sum(1 for (l, x) in chosen if l == layer and x // 256 == half)
-        if n % 2 == 0:
-            continue
-        for e, es, rs in by_half.get(key, []):
-            if (layer, e) not in chosen:
-                chosen[(layer, e)] = (es, rs)
-                added += 1
-                report.append(f"blk.{layer}: half {half} odd -> added e{e} "
-                              f"(energy {es*100:.2f}%)")
-                break
-        else:
-            report.append(f"blk.{layer}: half {half} holds {n} and no candidate is "
-                          f"left to make it even")
-    return added
-
-
-def select_to_count(data, min_share, min_route_mult, target):
-    """(lines, report, total, cutoff) for the set that LANDS the count.
-
-    The bars decide the base set; the count is then filled from the energy ranking,
-    one expert at a time, each addition taking its half's next-best candidate with it
-    so every rank's half stays even. Only the RATIO bar walks down to find candidates
-    — it is the law that says an expert is disproportionate and not merely busy, and
-    the caller's byte bill has to be filled — while the ENERGY bar holds, because that
-    bar is what the extra GiB of bf16 is supposed to buy. `cutoff` is the energy share
-    the set bottoms out at: the bar this campaign actually converted with.
-    """
-    report = []
-    shares, ranked = {}, []
-    for layer in sorted(data):
-        experts = data[layer]
-        tot_e = sum(v[2] for v in experts.values())
-        tot_r = sum(v[1] for v in experts.values())
-        if tot_e <= 0 or tot_r <= 0:
-            report.append(f"blk.{layer}: empty recording, skipped")
-            continue
-        for e, (_rank, rows, tr) in experts.items():
-            es, rs = tr / tot_e, rows / max(tot_r, 1)
-            if es <= 0:
-                continue
-            shares[(layer, e)] = (es, rs)
-            ranked.append((es, layer, e, rs))
-    ranked.sort(key=lambda r: (-r[0], r[1], r[2]))
-    by_half = {}
-    for es, layer, e, rs in ranked:
-        by_half.setdefault((layer, e // 256), []).append((e, es, rs))
-
-    chosen = {k: v for k, v in shares.items()
-              if v[0] >= min_share and v[0] >= min_route_mult * v[1]}
-    total = len(chosen)
-    total += parity_repair(chosen, by_half, report)
-
-    mult = min_route_mult
-    while True:
-        pool = [(es, l, e, rs) for es, l, e, rs in ranked
-                if es >= mult * rs and (l, e) not in chosen]
-        if len(pool) + total >= target or mult <= 0.0:
-            break
-        mult -= 0.5
-        report.append(f"ratio bar {mult + 0.5:g} leaves {len(pool)} fill candidates "
-                      f"for {target - total} slots; relaxing toward 0")
-    for es, layer, e, rs in pool:
-        if total >= target:
-            break
-        if (layer, e) in chosen:
-            continue
-        chosen[(layer, e)] = (es, rs)
-        total += 1
-        report.append(f"blk.{layer}: count fill -> added e{e} (energy {es*100:.2f}%)")
-        total += parity_repair(chosen, by_half, report, only=(layer, e // 256))
-    lines, cutoff = [], None
-    for (layer, e) in sorted(chosen):
-        es, rs = chosen[(layer, e)]
-        cutoff = es if cutoff is None else min(cutoff, es)
-        lines.append(f"blk.{layer}.ffn_*_exps.{e}.weight         cast dtype=bf16")
-    return lines, report, total, cutoff
-
-
-def main():
-    ap = argparse.ArgumentParser()
-    ap.add_argument("calib_dir")
-    ap.add_argument("--min-share", type=float, default=0.03)
-    ap.add_argument("--min-route-mult", type=float, default=3.0)
-    ap.add_argument("--target-count", type=int, default=0)
-    a = ap.parse_args()
-
-    # layer -> global expert -> (rank, rows, energy)
-    data = {}
-    for path in sorted(glob.glob(os.path.join(
-            a.calib_dir, "gram.r*.ffn_down_exps.*.bin"))):
-        m = NAME_RE.match(os.path.basename(path))
-        if not m:
-            continue
-        rank, layer, expert = int(m.group(1)), int(m.group(2)), int(m.group(3))
-        k, _, rows, tr = read_gram(path)
-        data.setdefault(layer, {})[expert] = (rank, rows, tr)
-
-    if not data:
-        raise SystemExit("no per-expert down grams found")
-
-    if a.target_count > 0:
-        lines, report, total, cutoff = select_to_count(
-            data, a.min_share, a.min_route_mult, a.target_count)
-        bar = f"energy cutoff {cutoff:.3g}" if cutoff is not None else "no candidates"
-    else:
-        lines, report, total = select(data, a.min_share, a.min_route_mult)
-        bar = f"min-share {a.min_share:.3g}"
-
-    # The emitted lines ARE the contract with the four-bit GEMM: every rank's half of
-    # every layer must hold an even number of bf16 experts. Judged on the output and
-    # not on the internal sets, so a slip in either pass is caught here rather than at
-    # engine load time.
-    halves = collections.Counter()
-    for rule in lines:
-        m = CAST_RE.match(rule)
-        if m:
-            halves[(int(m.group(1)), int(m.group(2)) // 256)] += 1
-    odd = {key: n for key, n in halves.items() if n % 2}
-    if odd:
-        print("PARITY LAW BROKEN: " + ", ".join(
-            f"blk.{lay} half {half} holds {n} protected experts"
-            for (lay, half), n in sorted(odd.items())), file=sys.stderr)
-        raise SystemExit(2)
 
     print("\n".join(lines))
     print("\n".join(report), file=sys.stderr)
-    print(f"total protected: {total} (target {a.target_count or 'none'}, {bar}, "
+    print(f"total protected: {total}", file=sys.stderr)
-          f"min-route-mult {a.min_route_mult:g})", file=sys.stderr)
 
 
 if __name__ == "__main__":

scripts/download-frank-dragoon-npu.sh

@@ -8,10 +8,8 @@
 # (/opt/halogen/npu/models.txt inside the image) and refuses to load a model
 # whose files do not match.
 #
-# The manifest below IS that catalog block (dumped from the pinned 0.18.20
+# The manifest below IS that catalog block (dumped from the pinned 0.16.2
-# image on 2026-10-30; the 0.16.2 block this replaced named different device
+# image on 2026-10-19), so the files land in the layout the entrypoint
-# programs — 10 `u*.elf` and a 5,086,496 B consts.hnpb — so a version bump
-# re-fetches the set or the entrypoint refuses the boot), so the files land in the layout the entrypoint
 # expects — <dir>/<model-id>/devices/*, <dir>/<model-id>/<model-id>.hnpw and
 # <dir>/<model-id>/tokenizer/tokenizer.json — and the endpoint can keep
 # /models read-only and open no outbound connection at boot (HALOGEN_DOWNLOAD
@@ -59,25 +57,21 @@ manifest() {
     case "$1" in
       qwen3-embedding-0.6b)
         NPU_REPO="peonist-ai/halogen-npu-qwen3-embedding-0.6b"
-        NPU_REV="8fd44c9f18861618a509bea75c51ff8a37e3bd5d"
+        NPU_REV="4960fd9d4423dd15373ad21c83db48dbdb3b2798"
         FILES=(
         "devices/NOTICE.md 3248 0f267b3d2523ddf14997ee58660a492a9eaf10ccf6b08bf19dfdc85b9a478b91"
-        "devices/consts.hnpb 8495512 5af7c1f2f24d45a9054872bba882461cf7f6ffda832e785b700643d6467ad88b"
+        "devices/consts.hnpb 5086496 ae430e41545a0b1012938cda373b0c450364d3be631111cca3a8c43679f93336"
-        "devices/devices.hnpm 35465 85d870f6b900de1829659955f0dc701d57984580f5e5ec251add5d6969f03e3d"
+        "devices/devices.hnpm 24047 4e9bca9d95d084fb89ce5b99f579a00666c8ca1efae2613c53e3a4878cc9f174"
-        "devices/u0.elf 2975008 f74df12eb8c79e4e90cbedcc1dd8f142219772d400e3a142fde8a95378b105eb"
+        "devices/u0.elf 4931968 b38f165886cb037b7d3951d9cb878473eaba58a432acd45416ff85fd88aa4e46"
-        "devices/u1.elf 3266848 ac5a3f89f934951b315b62ab53e1d0a74dbe6396134192641c405d08da332754"
+        "devices/u1.elf 5456000 b1811feee851b8af833b37721da92099d89772110815bbbe2c3fa1c276f0ff42"
-        "devices/u2.elf 4015328 5e4f0d3342f262816289866d7e8c966f56a9f938c2e12e7341718cc7312aa480"
+        "devices/u2.elf 6505552 406ea9a95b470628a7382e376f4a72cdf4d7aa4c59b4ddf0a4bdd139d63d6ff2"
-        "devices/u3.elf 4326976 94cf5d269fa286d91c26bf4654cedf101c047d23c4495b74c9c129cdc33b210f"
+        "devices/u3.elf 6817216 bc205d51b523d770151a0c61968f7c70bf624412827580bb6fe0aaf4650dc2ee"
-        "devices/u4.elf 4953792 cbd2796050d4c675f5cb3da117111087d510173e26f262f1b36aab66dd49dc91"
+        "devices/u4.elf 7444032 a5a91338a2603acdcd5c11df532033fda2d3f5479ea44ae87f98fafbdff9a62d"
-        "devices/u5.elf 4940112 7bf6a4470546bb888da02af395c07d92a24fb6d43aef27eb2151b3a9eda19e4d"
+        "devices/u5.elf 7432416 6c2bf41835569e0eba25ded7c05c7264ae69c6700bdeb4791057d884f2a4c126"
-        "devices/u6.elf 6174544 10b9d50b635993e1f9c23775c0b94901d922c1e433cd10910e9f97174235f5ac"
+        "devices/u6.elf 4941232 919d0038ca088eafddf195f3466ff38db27d3635be1cffa5d4d4b5140902a68e"
-        "devices/u7.elf 2983776 e0b06063b7379d05c85b3f435b819d96fda1223d8025d6d15958854b5711ace9"
+        "devices/u7.elf 5488304 d904cf8afae9428dd167960549e18cce5441745f18c62f8c50975dffc077d3c2"
-        "devices/u8.elf 3298656 3bad204f782a68b97e27c1172530b13d7fbb0b495fa95f9504530a1048560644"
+        "devices/u8.elf 4941232 db3aef69b17825854ee0dd2df475125a3f5c872f95c686793d6af1ee83596fa7"
-        "devices/u9.elf 2983776 875e313280358ce116e2a51a29a2c42794b5a9fadb3d48db702c90d18d838c2c"
+        "devices/u9.elf 5488304 d182727e551084db8fb9600441d8aa373c7f09a3d267ae0a5e921ef92326db1c"
-        "devices/u10.elf 3298656 ef2e0f399f149a5476955bcf233c6fa2e896fcef1f86ecb0d8113c952c41a8b2"
-        "devices/u11.elf 3298656 68a2519eee2d6a61ccc4ca2007e3186d44c9eb4e81162d742fe2f1756ec5a528"
-        "devices/u12.elf 3298656 2bdc6abfa58cac1d5795a3ef52fe8a9ab4e7c2a4792822d615499a913401f728"
-        "devices/u13.elf 3298656 4a3ce14f7ba15987b9bcbb4a010083e8aef68cd87c20cbe43403a98263179fe2"
         "qwen3-embedding-0.6b.hnpw 813032248 b9f9901429df7b46ec17153aa3899f738adbea8e4356080da0c6e6586fb750d1"
         "tokenizer/tokenizer.json 11423705 def76fb086971c7867b829c23a26261e38d9d74e02139253b38aeb9df8b4b50a"
         ) ;;
@@ -105,18 +99,7 @@ for MODEL in ${MODELS//,/ }; do
                 # 62 GiB fetch hit this on 2026-10-18).
                 url=$(curl -sfIL -o /dev/null -w '%{url_effective}' "$HF/$NPU_REPO/resolve/$NPU_REV/$f") \
                     || { echo "cannot resolve $NPU_REPO/$f" >&2; exit 1; }
-                # Resume ONLY into a genuinely partial file. A staged file of a
+                curl -fL --retry 5 -C - -o "$path" "$url"
-                # DIFFERENT size is an artifact of another revision (a version
-                # bump re-cuts the device programs), and `-C -` against it
-                # appends the tail to the old bytes: the result is the right
-                # BYTE COUNT with the wrong content, which reads as a corrupt
-                # program, not as a fetch fault (measured 2026-10-30 on
-                # consts.hnpb). Fetch those from zero.
-                resume=()
-                if [ -f "$path" ] && [ "$(stat -c %s "$path")" -lt "$want" ]; then
-                    resume=(-C -)
-                fi
-                curl -fL --retry 5 "${resume[@]+"${resume[@]}"}" -o "$path" "$url"
             fi
         fi
         [ -f "$path" ] || { echo "MISSING $path (run without --verify-only)" >&2; exit 1; }

scripts/download-qwen38-bf16.sh

@@ -1,249 +0,0 @@
-#!/usr/bin/env bash
-# download-qwen38-bf16.sh — RUNS ON DANKSERVER. Fetch and verify the vendor
-# BF16 checkpoint Qwen/Qwen3.8-Flash-Next: the source the five-bit campaign
-# converts, and the source the KLD reference is recorded from.
-#
-# Why the base and not a finetune: the campaign converts to compare against the
-# publisher's own iq4r container, and that container was built from this
-# checkpoint. Base-in, base-out; anything else confounds the gate. (The
-# predecessor campaign ran ukisai/Swift-1.5-Qwen3.8-Flash-Next-BF16, whose key
-# set is identical to this repo's but whose weights are not — none of its
-# calibration grams, KLD reference or protected list carries over.)
-#
-# Why re-fetch instead of reusing: every BF16 copy of this family was destroyed
-# in the 2026-10-15 storage purge — only the 113.6 GiB served .rad survived.
-# 335.3 GiB of safetensors, 131 shards, ungated (the predecessor campaign
-# verified the key set against this repo, so no gate letter is needed).
-#
-# Verification is four gates deep, because the failure this repo actually lived
-# through is a fetch that reported success: `curl -o FILE URL` exits 0 on an
-# HTTP 401/403 and writes the error body as the artifact — three shards of
-# identical tiny size and a cheerful DONE in 20 seconds for 104 GiB.
-#
-#   1. shard census: the file count must equal the expected shard count, so a
-#      partially fetched fragment tree (the .partNofM trap) cannot pass.
-#   2. per-shard completeness, from the shard's OWN safetensors header: the
-#      header declares where the tensor data ends, so every shard's true size is
-#      known offline. A torn tail is named here, by file, instead of surfacing
-#      as a load error five hours later.
-#   3. index coverage: every shard model.safetensors.index.json references
-#      exists and is named.
-#   4. total bytes against the number the Hub declared, then, unless --no-hub,
-#      every file's sha256 against the Hub's LFS record — including the shards
-#      already on disk, so a previous partial download is never trusted.
-#
-# The token never enters a command line (the 2026-09-16 leak law): it is read
-# into HF_TOKEN in the environment, where a local process listing is the only
-# reader. This repo is ungated, so the fetch simply runs without one when no
-# token file exists. scripts/hfget.sh is curl+jq only — no Python, no venv, no
-# hf_transfer — and it drops the pickle/ONNX weight duplicates by itself.
-#
-# usage: download-qwen38-bf16.sh [--fetch] [--no-hub] [--dir DIR]
-#                                [--shards N] [--bytes B] [--repo ID]
-#   --fetch    download first (resumable: re-run to continue), then verify
-#   --no-hub   skip the Hub-side sha256 sweep; the other gates always run
-# exit: 0 verified, 1 verification failed, 2 environment / usage error
-set -euo pipefail
-
-REPO="${FRANK_QWEN38_HF_REPO:-Qwen/Qwen3.8-Flash-Next}"
-LOCAL_DIR="${FRANK_QWEN38_CKPT:-/home/dank/models/Qwen3.8-Flash-Next}"
-# Hub census of 2026-10-27: 144 files, 131 of them .safetensors, together
-# 360,023,351,514 bytes; the shards alone are 360,000,192,888. This gate counts
-# shards only, so a config file edited on the Hub cannot fail it.
-EXPECTED_SHARDS="${FRANK_QWEN38_SHARDS:-131}"
-EXPECTED_BYTES="${FRANK_QWEN38_BYTES:-360000192888}"
-MIN_FREE_MIB="${FRANK_QWEN38_MIN_FREE_MIB:-350000}"
-
-FETCH=0
-HUB=1
-while [ $# -gt 0 ]; do
-    case "$1" in
-        --fetch) FETCH=1 ;;
-        --no-hub) HUB=0 ;;
-        --dir)    LOCAL_DIR="$2"; shift ;;
-        --shards) EXPECTED_SHARDS="$2"; shift ;;
-        --bytes)  EXPECTED_BYTES="$2"; shift ;;
-        --repo)   REPO="$2"; shift ;;
-        *) echo "usage: ${0##*/} [--fetch] [--no-hub] [--dir DIR] [--shards N] [--bytes B] [--repo ID]" >&2
-           exit 2 ;;
-    esac
-    shift
-done
-
-SELF_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-FAILS=0
-note() { echo "$@"; FAILS=$((FAILS + 1)); }
-
-if [ "$FETCH" = "1" ]; then
-    # Every fetch gate is a hard stop: skipping the download silently and then
-    # verifying a half tree is how a campaign ships a stale payload.
-    HFGET="$SELF_DIR/hfget.sh"
-    if [ ! -f "$HFGET" ]; then
-        echo "REFUSED: the fetch helper is not here: $HFGET" >&2
-        exit 2
-    fi
-    if ! command -v jq >/dev/null 2>&1; then
-        echo "REFUSED: hfget.sh needs jq on PATH" >&2
-        exit 2
-    fi
-    mkdir -p "$LOCAL_DIR"
-    # The campaign's peak-disk law starts at the fetch: the checkpoint and the
-    # reference container built from it are ~335 GiB each, and a tree that does
-    # not fit is discovered hours into a transfer, when it costs the most.
-    free_mib=$(df -m --output=avail "$LOCAL_DIR" | tail -1 | tr -dc '0-9')
-    if [ "${free_mib:-0}" -lt "$MIN_FREE_MIB" ]; then
-        echo "REFUSED: $free_mib MiB free at $LOCAL_DIR; the fetch wants $MIN_FREE_MIB MiB free" >&2
-        echo "         (retire the peak-disk predecessors first — nothing is downloaded, so" >&2
-        echo "         nothing is left half-written)" >&2
-        exit 2
-    fi
-    echo "fetch: $REPO -> $LOCAL_DIR ($free_mib MiB free)"
-    if [ -z "${HF_TOKEN:-}" ]; then
-        CREDSTORE="$HOME/.config/huggingface/credentials/https://huggingface.co"
-        if [ -f "$CREDSTORE" ]; then
-            HF_TOKEN="$(awk '/^ OauthToken: / {print $2; exit}' "$CREDSTORE")"
-        elif [ -f "$HOME/.cache/huggingface/token" ]; then
-            # The legacy single-line token file the hub library writes.
-            HF_TOKEN="$(tr -d '[:space:]' < "$HOME/.cache/huggingface/token")"
-        elif [ -f "$HOME/.hf_token" ]; then
-            HF_TOKEN="$(tr -d '[:space:]' < "$HOME/.hf_token")"
-        fi
-    fi
-    if [ -n "${HF_TOKEN:-}" ]; then
-        export HF_TOKEN
-    fi
-    bash "$HFGET" "$REPO" "$LOCAL_DIR" main
-    unset HF_TOKEN
-fi
-
-if [ ! -d "$LOCAL_DIR" ]; then
-    echo "REFUSED: $LOCAL_DIR does not exist (run with --fetch, or pass --dir)" >&2
-    exit 1
-fi
-INDEX="$LOCAL_DIR/model.safetensors.index.json"
-if [ ! -f "$INDEX" ]; then
-    echo "REFUSED: $INDEX is missing — the checkpoint tree is not addressable without it" >&2
-    exit 1
-fi
-
-echo "== gate 1: shard census ($LOCAL_DIR)"
-SHARDS=$(find "$LOCAL_DIR" -maxdepth 1 -type f -name '*.safetensors' | wc -l)
-if [ "$SHARDS" != "$EXPECTED_SHARDS" ]; then
-    note "FAIL SHARD_COUNT: $SHARDS safetensors files on disk, expected $EXPECTED_SHARDS"
-else
-    echo "  ok: $SHARDS shards"
-fi
-
-echo "== gate 2: every shard is whole, judged by its own header"
-# A safetensors file is [u64 header length][JSON header][tensor data]. The JSON
-# declares where the data ends, so the file's true size is computable offline:
-# 8 + header + the largest end offset. Truncation and error bodies both fall
-# here, and each is reported with the file that caused it.
-while IFS= read -r f; do
-    state=$(python3 - "$f" <<'PY'
-import json, os, struct, sys
-path = sys.argv[1]
-size = os.path.getsize(path)
-try:
-    with open(path, "rb") as fh:
-        (hlen,) = struct.unpack("<Q", fh.read(8))
-        if hlen == 0 or hlen > size:
-            print("NOT_SAFETENSORS")
-            raise SystemExit
-        header = json.loads(fh.read(hlen))
-except Exception:
-    print("NOT_SAFETENSORS")
-    raise SystemExit
-if not header:
-    print("NOT_SAFETENSORS")
-    raise SystemExit
-end = max((v["data_offsets"][1] for v in header.values()
-           if isinstance(v, dict) and "data_offsets" in v), default=0)
-want = 8 + hlen + end
-print("OK" if want == size else f"TRUNCATED want={want} have={size}")
-PY
-)
-    case "$state" in
-        OK) ;;
-        NOT_SAFETENSORS*) note "FAIL NOT_SAFETENSORS: $(basename "$f") is not a safetensors file (an error body written as an artifact?)" ;;
-        TRUNCATED*) note "FAIL TRUNCATED: $(basename "$f") $state" ;;
-    esac
-done < <(find "$LOCAL_DIR" -maxdepth 1 -type f -name '*.safetensors' | sort)
-if [ "$FAILS" -eq 0 ]; then
-    echo "  ok: every shard's data extent matches its size on disk"
-fi
-
-echo "== gate 3: the index's shards are all present"
-INDEX_SHARDS=$(python3 - "$INDEX" <<'PY'
-import json, sys
-map_ = json.load(open(sys.argv[1]))["weight_map"]
-print("\n".join(sorted(set(map_.values()))))
-PY
-)
-while IFS= read -r name; do
-    [ -n "$name" ] || continue
-    if [ ! -f "$LOCAL_DIR/$name" ]; then
-        note "FAIL MISSING: $name is named by the index and is not on disk"
-    fi
-done <<< "$INDEX_SHARDS"
-if [ "$FAILS" -eq 0 ]; then
-    echo "  ok: $(printf '%s\n' "$INDEX_SHARDS" | grep -c .) referenced shards on disk"
-fi
-
-echo "== gate 4: total bytes vs the Hub's declaration"
-TOTAL=$(find "$LOCAL_DIR" -maxdepth 1 -type f -name '*.safetensors' -printf '%s\n' | awk '{s+=$1} END{print s+0}')
-if [ "$TOTAL" != "$EXPECTED_BYTES" ]; then
-    note "FAIL TOTAL_BYTES: shards total $TOTAL bytes, expected $EXPECTED_BYTES"
-else
-    echo "  ok: $TOTAL bytes"
-fi
-
-if [ "$HUB" = "1" ]; then
-    echo "== gate 5: every file's sha256 vs the Hub's LFS record"
-    # size = file size; lfs.sha256 = sha256 of the file itself (LFS or not).
-    TMPD="$(mktemp -d)"
-    trap 'rm -rf "$TMPD"' EXIT
-    MANIFEST="$TMPD/tree.json"
-    PLAN="$TMPD/plan"
-    curl -sf "https://huggingface.co/api/models/$REPO/tree/main?recursive=true&expand=true" \
-        -o "$MANIFEST" || { echo "FAIL: the Hub API call failed — refusing to report success" >&2; exit 1; }
-    python3 - "$MANIFEST" > "$PLAN" <<'PY'
-import json, sys
-for e in json.load(open(sys.argv[1])):
-    if e.get("type") != "file":
-        continue
-    sha = (e.get("lfs") or {}).get("sha256") or e.get("sha") or ""
-    if sha:
-        print(e["path"], e["size"], sha)
-PY
-    BAD=0
-    while read -r rel size sha; do
-        [ -n "${rel:-}" ] || continue
-        if [ ! -f "$LOCAL_DIR/$rel" ]; then
-            note "FAIL MISSING: $rel is on the Hub and not on disk"
-            continue
-        fi
-        have=$(stat -c %s "$LOCAL_DIR/$rel")
-        if [ "$have" != "$size" ]; then
-            note "FAIL SIZE: $rel is $have bytes, Hub says $size"
-            continue
-        fi
-        got=$(sha256sum "$LOCAL_DIR/$rel" | awk '{print $1}')
-        if [ "$got" != "$sha" ]; then
-            note "FAIL SHA256: $rel got $got want $sha"
-            BAD=$((BAD + 1))
-        fi
-    done < "$PLAN"
-    if [ "$BAD" -eq 0 ] && [ "$FAILS" -eq 0 ]; then
-        echo "  ok: sha256 matches for every file"
-    fi
-    rm -rf "$TMPD"
-    trap - EXIT
-fi
-
-if [ "$FAILS" -gt 0 ]; then
-    echo "VERIFY_FAILED: $FAILS problem(s) in $LOCAL_DIR" >&2
-    exit 1
-fi
-echo "VERIFY_OK: $SHARDS shards, $TOTAL bytes of safetensors in $LOCAL_DIR"
-echo "NEXT: build the BF16 reference container with scripts/build-qwen38-bf16-rad.sh"

scripts/frank-archon.env

@@ -46,42 +46,31 @@ FRANK_ARCHON_TP=2
 # stays EXACT for single-sequence decode and any step of <= 25 rows — see
 # MAX_SEQS x (1 + SPEC_TOKENS) below.
 FRANK_ARCHON_TP_WIRE=wht6
-# Decode slots. A slot costs KV and pinned RAM, never decode: the cache target is
+# Decode slots. A slot costs KV, never decode; the pool is sized to this
-# exactly MAX_SEQS x MAX_MODEL_LEN and the checkpoint store asks (1 + what the
+# contract and nothing more. At 1.8.1 the budget resolver caps the cache at
-# retention policy keeps) per slot. Ordered 2026-10-20: FOUR slots over a pool of at
+# 556,348 fp8 tokens — 2.8 sessions at 200,000 — so a THIRD full-height
-# least 700,000 fp8 tokens, rounding UP if the resolver cannot land it exactly. The
+# conversation answers 400 while /health and every shorter chat work fine
-# target is therefore 4 x 200,000 = 800,000 tokens and HOST_POOL_MIB decides whether
+# (3 x 50k streams run at 77.6 t/s aggregate). Frank's trade: declare the two
-# the cache gets it (expert_vram_floor, core/place/planner.cpp:100-104: the card must
+# slots the engine can hold and let the freed ~1.1 GiB go to the expert plane,
-# keep expert-plane-minus-host-room). The 2-slot shape was the answer to a
+# instead of advertising a third slot that only exists at shorter prompts.
-# 365,204-token pool that backed 1.8 full-height sessions; at this pool the third and
+FRANK_ARCHON_MAX_SEQS=2
-# fourth conversations are backed by the cache instead of over-committing it.
-FRANK_ARCHON_MAX_SEQS=4
 # Served window. The engine treats `kv group tokens >= max-model-len` as a HARD
 # limit, and models.yml contextWindow MUST quote this number (over-length is a
 # refusal, not a truncation). The pool is sized for seqs x maxlen, not one
 # sequence.
 FRANK_ARCHON_MAX_MODEL_LEN=200000
 FRANK_ARCHON_PLACEMENT=expert_tiered
-# Pinned host pool for expert rows that do not fit VRAM, PINNED ONCE PER RANK: the
+# Pinned host pool for expert rows that do not fit VRAM. Under the budget
-# host must pin tp x this number, and the refusal that names it is
+# resolver this is ALSO the lever that decides which experts stay on the card:
-# core/engine_bringup.cpp:250-265. Under the budget resolver this is ALSO the KV
+# the card's leftover goes to the expert plane first and the KV cache takes the
-# lever -- the card keeps expert-plane-minus-this-room, so every MiB added moves one
+# rest, so growing the pool moves experts off the card and shrinking it spills
-# MiB of experts off the card and into the cache. Derived from the boot ledger (a
+# them onto VRAM the cache wanted. Under-sizing it is a boot failure (36,864
-# 23.73 GiB floor at 44,928 room puts plane + 2 units at 67.60 GiB a rank), 49,152
+# refused a boot). The ledger's coverage line is the referee, not this file.
-# drops the floor to 19.6 GiB and leaves the cache ~6.9 GiB, which is enough to back
+# Measured, not guessed: 45,568 (PR #30) moved host_pool to 45.09 GiB and left
-# the whole 4 x 200,000 target; the leftover returns to the experts. Cost is paid
+# vram_kv byte-identical at 4.20 GiB / 556,348 tokens on both ranks — extra
-# twice over: pinned RAM (tp x 48 GiB, against the TTM target below) and expert
+# host RAM above what the expert plane's footprint needs buys no cache. Back at
-# residency -- ~3.2 GiB a card of experts now lives in host RAM and is read over the
+# 44,928, the size that boots clean.
-# x8 link when the router picks it. The ledger's coverage line is the referee, not
+FRANK_ARCHON_HOST_POOL_MIB=44928
-# this file: if vram_kv comes back under 700,000 tokens, raise this 1024 and redeploy.
-# 2026-10-29 A/B, measured on both payloads and folded back the same day: at 66,560 the
-# endpoint printed the identical `elastic 26.73 GiB / experts 20.72 / kv cache 5.64 /
-# vram_weights 24.30` it had printed at 49,152, opening the bigger pool with `0 B used`;
-# the campaign rig (bf16, same step) moved `vram_kv 269.99 -> 271.25 MiB`, a rounding
-# step — its window is fixed by its own n-gram table (95.37 GiB) and expert plane, not
-# by this pool, so the refused calibration documents were fixed by cutting them to the
-# window (scripts/rechunk-kld-corpus.py), not by widening the pool.
-FRANK_ARCHON_HOST_POOL_MIB=49152
 # VRAM left unclaimed per card (publisher default 96 MiB); the engine's settle
 # floor is built from it.
 FRANK_ARCHON_GPU_HEADROOM_MIB=96
@@ -104,29 +93,16 @@ FRANK_ARCHON_SPEC_TOKENS=2
 FRANK_ARCHON_MAX_BATCHED_TOKENS=2048
 # Step sharing. A prefill chunk that shares a step with decoding sequences holds
 # the device for the chunk's whole time, and every decode row in that step waits
-# that long for its next token: measured at this shape, decode-only steps 15.5 ms
+# that long for its next token (the census: [[LLM Performance Diagnosis]] §9).
-# against chunk steps 166 ms, which is the harness's ~146 t/s falling to ~11 t/s
+# `auto` leaves each decode row behind the chunk a row plus its draft window and
-# while another session prefills (law and census: [[frank-archon]]).
+# keeps a share for whatever is waiting to be admitted; a number pins the chunk's
-# `auto` is a PREFILL-SPEED dial, not a decoder dial: it reserves one row plus the
+# cap; `off` is the pre-1.4 behaviour this endpoint ran for two eras, where the
-# draft window per decoding sequence (3 tokens) and an eighth of the budget per
+# chunk took the step and admission never ran. Interleave inserts N decode-only
-# waiting request or waiting prefill, and the source states it will not halve for
+# steps after a chunk step taken beside decoders: it protects their cadence and
-# decode rows alone. Live proof: prefill_chunks_capped 5,018 across 62,386 chunk
+# holds a waiting request out of those steps, so it stays 0 until the post-migration
-# steps. A number is the only value that applies whenever the chunk shares a step,
+# decode-vs-prefill buckets say it is wanted.
-# and it must not go under the prefill stager's smallest pass -- 1025 rows here,
-# named on the boot line "prefill staging: ... a step of more than 1024 tokens" --
-# because below it every routed layer reads its pooled experts synchronously, so
-# 512 is a trap and the vendor measures the whole job slower there. Interleave
-# inserts N decode-only steps after a chunk step taken beside decoders: it protects
-# their cadence and holds a waiting request out of those steps. That is the decoder
-# dial. ARMED at 1 on 2026-10-20: at N=1 a stream takes its token from the chunk step
-# AND one from the held step, ~2 tokens per 182 ms instead of one per 166 ms; the
-# price falls on the prefilling prompt (its chunks lose every held step) and on any
-# request still waiting to enter. `--prefill-span` re-funds a prefill only when it is
-# ALONE, so it cannot buy this back while decoders run. Meter:
-# radiance:engine_steps_held_total must leave zero, and the §9 buckets must move
-# before N rises.
 FRANK_ARCHON_BUSY_PREFILL_CHUNK=auto
-FRANK_ARCHON_PREFILL_INTERLEAVE=1
+FRANK_ARCHON_PREFILL_INTERLEAVE=0
 # Prefix cache: pinned host memory only. The disk tier was removed outright
 # (--prefix-cache-dir and --prefix-cache-disk-mib are refusals), so what used to
 # be restored from NVMe is now re-prefilled. The tier is sized in ENTRIES and one
@@ -142,11 +118,9 @@ FRANK_ARCHON_NGRAM_PLACEMENT=ram
 # RESETS pages_limit to half of RAM on every boot; below the plan the load dies
 # mid-pin with an anonymous allocator error. ttm-preflight.sh raises the knob
 # itself before refusing by name, so recovery is a boot, not a visit.
-# Floor = 2 x HOST_POOL + 48,824 (static weights + arena) + PREFIX_CACHE + MNBT + the
+# Floor = 2 x HOST_POOL + 48,824 (static weights + arena) + PREFIX_CACHE + MNBT
-# auto checkpoint store (MAX_SEQS x 10 slots of 111.98 MiB), per the bats ledger test;
+# per the bats ledger test; at the 44,928 pool that computes to 148,920 MiB.
-# at the 49,152 pool with 4 slots that computes to 161,848 MiB (196,664 at the
+FRANK_ARCHON_TTM_MIN_MIB=150000
-# 66,560 pool the 2026-10-29 A/B rejected).
-FRANK_ARCHON_TTM_MIN_MIB=162000
 FRANK_ARCHON_TTM_TARGET_MIB=204800
 # Escape hatch for experiments. Unset -> no extra argv; the serve script expands
 # this unquoted on purpose, so keep multi-flag values as one string.

scripts/frank-dragoon.env

@@ -10,11 +10,8 @@
 # The .hgn format is the lock: it loads ONLY in the flash-server line, so the
 # engine moves with the payload, never ahead of it.
 # Image digest-pinned (a tag pull silently re-points; the digest is what was
-# qualified). 0.18.20 since 2026-10-30 (was 0.16.2, the model card's quickstart
+# qualified — 0.16.2 is the version the model card names as its quickstart pin).
-# pin) — the vendor has moved two minor versions and the payload lock is what
+FRANK_DRAGOON_IMAGE=ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a
-# the deploy's health gate plus the boot ledger decide; rollback is the
-# previous digest, 0c61bf84…, on this same line.
-FRANK_DRAGOON_IMAGE=ghcr.io/peonist-ai/halogen-flash-server@sha256:e35133b206da3094cc4d70c78800b26235bd9124b9aeb0e029d4a7c153b9cff0
 # Container identity kept from the 27B era: the unit's ExecStop names it.
 FRANK_DRAGOON_CONTAINER=frank-dragoon-halogen
 # Predecessor identity the serve script clears if it is still holding the GPUs.
@@ -52,21 +49,14 @@ FRANK_DRAGOON_TOKENIZER_FILES="tokenizer.json chat_template.jinja tokenizer_conf
 # stays at the image default, which is what was qualified) ------------------
 # Served id. OpenWebUI api_configs model_ids for the :7770 backend MUST name it.
 HALOGEN_MODEL_ID=frank-dragoon
-# PER-REQUEST ceiling, set to the checkpoint's NATIVE window (262,144 — a
+# PER-REQUEST ceiling: a longer prompt is a 400 naming the limit, never a
-# longer prompt is a 400 naming the limit, never a truncation; stretching
+# truncation. The harness window must sit ~45k UNDER this (the 400-zone law on
-# past native would need HALOGEN_ROPE_YARN and is not on plan). The harness
+# the page) — a window equal to the ceiling makes every long request a 400.
-# `contextWindow` must sit ~45k under THIS number (the 400-zone law on the
+HALOGEN_CTX=200704
-# page): with the window at 200,000 the gap is 62,144, which absorbs the
+# ONE pool behind both slots, sized so BOTH can carry a maximum-length request
-# chars/4 under-count. A window at or near the ceiling makes every long
+# at once. Pool positions buy concurrency; the per-request window never moves
-# request a guaranteed 400.
+# with them. Legal band: ctx <= pool <= slots * ctx (the seam enforces it), and
-HALOGEN_CTX=262144
+# RAM the pool takes is RAM the n-gram table's page cache loses.
-# ONE pool behind both slots. The harness window is 200,000, so 401,408
-# still carries TWO maximum harness-length conversations at once
-# (2 x 200,000 + one 45,056 budget <= pool + cap headroom); two literal
-# ceiling-length requests would queue instead — buying those means raising
-# the pool, and RAM the pool takes is RAM the n-gram table's page cache
-# loses. Pool positions buy concurrency; the per-request window never moves
-# with them. Legal band: ctx <= pool <= slots * ctx (the seam enforces it).
 HALOGEN_KV_POOL_POSITIONS=401408
 # Two concurrent conversations: the MTP drafter is not slot-locked on this
 # engine, so the second slot is capacity, not a speculation tax.
@@ -117,13 +107,10 @@ HALOGEN_NPU_MODELS=qwen3-embedding-0.6b
 FRANK_DRAGOON_NPU_DIR=/home/dank/models/halogen-v2-abliterated/npu
 # Node paths and the XRT directory are variables so the bats seam can drive
 # these gates on a box with no NPU. Ubuntu's distro XRT (libxrt2 + libxrt-npu2)
-# is mounted FILE BY FILE and THREE TIMES EACH — where the image looks for XRT
+# is mounted FILE BY FILE and TWICE EACH — once where the image looks for XRT,
-# (/opt/xilinx/xrt/lib), at its own path (those libraries find each other at
+# once at its own path, because those libraries find each other at their install
-# their install path), and at /opt/xilinx/lib/<multiarch>/ (the NPU child
+# path; the vendor forbids mounting an /opt/xilinx/xrt of symlinks into the
-# searches that third prefix; without it the lane dies naming it and the
+# system dir, which dangle inside the container.
-# supervisor takes the container down — 2026-10-21 boot loop). The basename of
-# this directory IS the multiarch name. The vendor forbids mounting an
-# /opt/xilinx/xrt of symlinks into the system dir, which dangle in the container.
 FRANK_DRAGOON_DEV_ACCEL=/dev/accel/accel0
 FRANK_DRAGOON_XRT_DIR=/usr/lib/x86_64-linux-gnu
 # sysfs root the fabric-clock preflight reads (same knob the vendor's

scripts/frank-dragoon.service

@@ -1,5 +1,5 @@
 [Unit]
-Description=halogen-flash-server container (Quat3rnion NATIVE v2 abliterated Qwen3.8-Flash-Next, MTP spec decode, 2 slots over ONE 401408-position pool at ctx 262144, vision ON), root systemd unit (dankclaw, frank-dragoon, Strix Halo iGPU)
+Description=halogen-flash-server container (Quat3rnion NATIVE v2 abliterated Qwen3.8-Flash-Next, MTP spec decode, 2 slots over ONE 401408-position pool at ctx 200704, vision ON), root systemd unit (dankclaw, frank-dragoon, Strix Halo iGPU)
 After=network-online.target
 Wants=network-online.target
 

scripts/frank-zealot.env

@@ -1,12 +1,12 @@
-# frank-zealot — llama.cpp (PrismML fork build 12118 = 0.7.0-dev, commit
+# frank-zealot — llama.cpp (PrismML fork build 10777, CUDA) on the RTX 3090,
-# 024474448, CUDA) on the RTX 3090, :7771. Payload: Ternary-Bonsai-2-9B PQ2_0 with the MTP head in the file, plus
+# :7771. Payload: Ternary-Bonsai-2-9B PQ2_0 with the MTP head in the file, plus
 # the refusal-direction adapter applied at load.
 #
 # ONE OWNER: shape, payload identity, eras, laws and every measured number
 # live in serverAppConfigs-docs/LLM/frank-zealot.md. This file carries the
 # knobs and only the reason a reader editing THIS line cannot recover
 # elsewhere. Where the two disagree, this file wins on values.
-LLAMA_BIN=/home/dank/GitPackages/llama-prism-0244744/bin/llama-server
+LLAMA_BIN=/home/dank/GitPackages/llama-prism-b10777/llama-server
 # The fork is a LOCK, not a preference: custom tensor type 142 + prism.hadamard.*
 # metadata. Stock llama.cpp refuses the file; a loader ignoring the Hadamard
 # metadata dequantizes wrong, silently.
@@ -64,8 +64,7 @@ CACHE_TYPE_V=q8_0
 # weights, so there is no --spec-draft-model. Its bill is pool × 4,096 B of
 # draft KV plus ~0.45 GiB of buffers and a tripled recurrent state — paid for
 # by CACHE_TYPE_V=q8_0 and UBATCH_SIZE=1024 above. Build gate: quantized V
-# beside MTP needs fork build >= b10776; LLAMA_BIN is 12118 (b10777 is kept on
+# beside MTP needs fork build >= b10776; LLAMA_BIN is 10777.
-# disk as the rollback path).
 # SPEC_TYPE=none is the rollback and strips the WHOLE set (--spec-type and
 # every --spec-draft-*); half a set has segfaulted at load.
 SPEC_TYPE=draft-mtp

scripts/gpu-exporter.py

@@ -1,212 +0,0 @@
-#!/usr/bin/env python3
-"""gpu-exporter: unified per-GPU metrics for a mixed AMD/NVIDIA host.
-
-Emits the `gpu_*` Prometheus families the host-system dashboard graphs:
-
-    gpu_utilization_percent  gpu_memory_used_bytes  gpu_memory_total_bytes
-    gpu_temperature_celsius  gpu_power_watts
-
-each labelled {gpu, vendor, model}. The scrape job adds `host`.
-
-Two sources, both host-native — no container, no GPU passthrough:
-
-  * AMD (R9700s, the 8060S iGPU, the Raphael display GPU): the amdgpu sysfs tree.
-    Utilization comes ONLY from gpu_busy_percent — amd-smi reports gfx_busy_inst
-    as N/A on gfx1201 (verified 2026-10-20). VRAM is already bytes, temperature
-    is milli-degrees, power is micro-watts. Crucially power1_average is EMPTY on
-    the R9700s, so those cards legitimately have no gpu_power_watts line; a
-    missing file becomes an ABSENT metric, never a fabricated 0 that a dashboard
-    would plot as a real reading.
-
-  * NVIDIA (the RTX 3090 on Dankclaw): one `nvidia-smi --query-gpu` CSV. On
-    Dankserver there is an nvidia-smi binary but no NVIDIA GPU, so the command
-    fails; that is tolerated and simply yields no NVIDIA series.
-
-Default mode prints one scrape to stdout and exits (the test harness, and any
-`service ... --oneshot` one-off). `--serve` binds the HTTP endpoint for
-Prometheus; it binds EXPLICITLY (loopback + the host LAN address), never a
-wildcard, matching node-exporter's posture on these boxes.
-"""
-import argparse
-import glob
-import os
-import subprocess
-import sys
-import threading
-from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
-
-FAMILIES = [
-    ("gpu_utilization_percent", "gauge", "GPU busy time as a percentage of wall time."),
-    ("gpu_memory_used_bytes", "gauge", "Device memory in use, in bytes."),
-    ("gpu_memory_total_bytes", "gauge", "Device memory capacity, in bytes."),
-    ("gpu_temperature_celsius", "gauge", "Package temperature in degrees Celsius."),
-    ("gpu_power_watts", "gauge", "Board power draw in watts."),
-]
-
-DEFAULT_NVIDIA_CMD = (
-    "nvidia-smi --query-gpu=index,name,utilization.gpu,memory.used,"
-    "memory.total,temperature.gpu,power.draw --format=csv,noheader,nounits"
-)
-
-
-def _read(path):
-    try:
-        with open(path) as fh:
-            return fh.read().strip()
-    except OSError:
-        return ""
-
-
-def _pci_slot(device_dir):
-    uevent = _read(os.path.join(device_dir, "uevent"))
-    for line in uevent.splitlines():
-        if line.startswith("PCI_SLOT_NAME="):
-            return line.split("=", 1)[1]
-    return ""
-
-
-def _pci_id(device_dir):
-    uevent = _read(os.path.join(device_dir, "uevent"))
-    for line in uevent.splitlines():
-        if line.startswith("PCI_ID="):
-            return "amd:" + line.split("=", 1)[1].lower()
-    return "amd"
-
-
-def collect_amd(sys_dir):
-    for card in sorted(glob.glob(os.path.join(sys_dir, "card[0-9]*"))):
-        device = os.path.join(card, "device")
-        busy = _read(os.path.join(device, "gpu_busy_percent"))
-        if busy == "":
-            continue  # not an amdgpu compute node (e.g. a render node w/o metrics)
-        labels = {"gpu": _pci_slot(device) or os.path.basename(card),
-                  "vendor": "amd", "model": _pci_id(device)}
-        yield "gpu_utilization_percent", labels, busy
-        for name, leaf in (("gpu_memory_used_bytes", "mem_info_vram_used"),
-                           ("gpu_memory_total_bytes", "mem_info_vram_total")):
-            v = _read(os.path.join(device, leaf))
-            if v != "":
-                yield name, labels, v
-        temp = ""
-        for hwmon in sorted(glob.glob(os.path.join(device, "hwmon", "hwmon*", "temp1_input"))):
-            temp = _read(hwmon)
-            if temp != "":
-                break
-        if temp != "":
-            yield "gpu_temperature_celsius", labels, str(int(temp) / 1000.0)
-        power = _read(os.path.join(device, "power1_average"))
-        if power != "":  # empty on the R9700s -> metric absent, not zero
-            yield "gpu_power_watts", labels, str(int(power) / 1e6)
-
-
-def collect_nvidia(cmd):
-    if not cmd:
-        return
-    try:
-        out = subprocess.run(cmd, shell=True, capture_output=True, text=True,
-                             timeout=10, check=True).stdout
-    except (subprocess.SubprocessError, OSError):
-        return  # no NVIDIA GPU / no driver: tolerate, emit nothing
-    for line in out.splitlines():
-        parts = [p.strip() for p in line.split(",")]
-        if len(parts) < 7:
-            continue
-        idx, name, util, mused, mtotal, temp, power = parts[:7]
-        labels = {"gpu": idx, "vendor": "nvidia", "model": name}
-        yield "gpu_utilization_percent", labels, util
-        yield "gpu_memory_used_bytes", labels, str(int(float(mused)) * 1048576)
-        yield "gpu_memory_total_bytes", labels, str(int(float(mtotal)) * 1048576)
-        if temp not in ("", "[N/A]"):
-            yield "gpu_temperature_celsius", labels, temp
-        if power not in ("", "[N/A]"):
-            yield "gpu_power_watts", labels, power
-
-
-def collect(sys_dir, nvidia_cmd):
-    samples = {}
-    for source in (collect_amd(sys_dir), collect_nvidia(nvidia_cmd)):
-        for name, labels, value in source:
-            try:
-                value = str(float(value))  # normalise; drop trailing junk
-            except ValueError:
-                continue
-            samples.setdefault(name, []).append((labels, value))
-    return samples
-
-
-def _fmt(value):
-    f = float(value)
-    if f == int(f) and abs(f) < 1e15:
-        return str(int(f))
-    return repr(f)
-
-
-def render(samples):
-    out = []
-    for name, kind, help_text in FAMILIES:
-        out.append("# HELP %s %s" % (name, help_text))
-        out.append("# TYPE %s %s" % (name, kind))
-        for labels, value in sorted(samples.get(name, []), key=lambda x: sorted(x[0].items())):
-            lset = ",".join('%s="%s"' % (k, v) for k, v in sorted(labels.items()))
-            out.append("%s{%s} %s" % (name, lset, _fmt(value)))
-    return "\n".join(out) + "\n"
-
-
-class Handler(BaseHTTPRequestHandler):
-    sys_dir = "/sys/class/drm"
-    nvidia_cmd = DEFAULT_NVIDIA_CMD
-
-    def do_GET(self):  # noqa: N802 (http.server API)
-        if self.path.split("?")[0] not in ("/metrics", "/"):
-            self.send_error(404)
-            return
-        body = render(collect(self.sys_dir, self.nvidia_cmd)).encode()
-        self.send_response(200)
-        self.send_header("Content-Type", "text/plain; version=0.0.4")
-        self.send_header("Content-Length", str(len(body)))
-        self.end_headers()
-        self.wfile.write(body)
-
-    def log_message(self, *args):
-        pass
-
-
-def main(argv):
-    ap = argparse.ArgumentParser(description=__doc__.splitlines()[0])
-    ap.add_argument("--amdgpu-sysfs", default="/sys/class/drm")
-    ap.add_argument("--nvidia-cmd", default=DEFAULT_NVIDIA_CMD)
-    ap.add_argument("--serve", action="store_true", help="serve /metrics instead of one-shot")
-    ap.add_argument("--port", type=int, default=9401)
-    ap.add_argument("--bind", action="append", default=None,
-                    help="explicit bind address (repeatable); env GPU_EXPORTER_BINDS "
-                         "comma-list if unset. NEVER a wildcard.")
-    args = ap.parse_args(argv)
-
-    if not args.serve:
-        sys.stdout.write(render(collect(args.amdgpu_sysfs, args.nvidia_cmd)))
-        return 0
-
-    binds = args.bind
-    if not binds:
-        env = os.environ.get("GPU_EXPORTER_BINDS", "")
-        binds = [b.strip() for b in env.split(",") if b.strip()] or ["127.0.0.1"]
-    Handler.sys_dir = args.amdgpu_sysfs
-    Handler.nvidia_cmd = args.nvidia_cmd
-    servers = []
-    for b in binds:
-        if b in ("0.0.0.0", "::", "*"):
-            sys.stderr.write("refusing wildcard bind %s\n" % b)
-            return 2
-        servers.append(ThreadingHTTPServer((b, args.port), Handler))
-    sys.stderr.write("gpu-exporter serving :%d on %s\n" % (args.port, ",".join(binds)))
-    # EVERY socket must be served: a listen()ed-but-never-accept()ed bind looks
-    # healthy in `ss` yet times out every scrape once its SYN backlog fills —
-    # and the loopback deploy gate cannot see it. One thread per extra bind.
-    for s in servers[1:]:
-        threading.Thread(target=s.serve_forever, daemon=True).start()
-    servers[0].serve_forever()
-    return 0
-
-
-if __name__ == "__main__":
-    sys.exit(main(sys.argv[1:]))

scripts/gpu-exporter.service

@@ -1,35 +0,0 @@
-# Systemd USER unit: gpu-exporter (both Dankclaw and Dankserver).
-#
-# Install path: ~/.config/systemd/user/gpu-exporter.service
-# Installed and enabled by deploy_gpu_exporter in scripts/deploy-remote.sh.
-#
-# Per-GPU metrics (utilization / VRAM / temperature / power) for the mixed
-# AMD + NVIDIA fleet, scraped by Prometheus. Like signal-relay it is a plain
-# user unit, not a quadlet: it runs python3 straight from the checkout (a pull
-# updates it with no copy step), a hand-written user unit can be enabled where
-# the podman v1 generator's units cannot, and with Linger=yes for dank it starts
-# at boot. It reads the host's own cgroup/drm sysfs and shells to nvidia-smi, so
-# it must run on the host — a container would need GPU/DRM passthrough for
-# nothing gained.
-#
-# BINDING. The base unit serves loopback only. deploy_gpu_exporter writes a
-# drop-in adding THIS host's LAN address (the same two-address posture
-# node-exporter and cadvisor use), so the endpoint is never a wildcard. It is
-# unauthenticated metrics on the LAN, identical to node-exporter :9100 and
-# cadvisor :8080 — Prometheus reaches same-host via host.containers.internal and
-# the Dankserver instance over the LAN from Dankclaw.
-
-[Unit]
-Description=GPU metrics exporter (amdgpu sysfs + nvidia-smi)
-After=network-online.target
-Wants=network-online.target
-
-[Service]
-# Loopback by default; the deploy drop-in appends the host LAN address.
-Environment=GPU_EXPORTER_BINDS=127.0.0.1
-ExecStart=/usr/bin/python3 /home/dank/serverAppConfigs/scripts/gpu-exporter.py --serve
-Restart=always
-RestartSec=5
-
-[Install]
-WantedBy=default.target

scripts/grams-to-imatrix.py

@@ -1,418 +0,0 @@
-#!/usr/bin/env python3
-"""grams-to-imatrix.py — the engine's own calibration recording, re-voiced as a
-llama.cpp importance matrix for `rad-convert --imatrix F`. RUNS ON DANKSERVER
-beside the recording. Python 3 stdlib only: numpy must NOT be required, because
-this runs in the plain container next to a 335 GiB checkpoint, not in a venv.
-
-WHY. `rad-convert` takes its per-column activation second moments and its
-expert-popularity profile from ONE input, an imatrix (core/format/imatrix.h).
-Only the GGUF form carries a per-expert dimension — with the legacy flat form,
-or with none, every expert in a layer is weighted by the layer's aggregate,
-which is exactly the wrong thing on a 512-expert MoE. The calibration tap has
-already measured everything; this tool only re-voices it, so the imatrix and the
-protected-expert census (derive-protected-experts.py) are the SAME recording:
-one measurement, two consumers, neither able to disagree about which experts are
-hot.
-
-INPUT. RADGRAM2 files in a RADIANCE_CALIB_DIR output directory
-(arch/common/rad_arch.h, calib_write). Header law, same parse as
-scripts/derive-protected-experts.py — 32 bytes, `<8sIIQI`: magic `RADGRAM2`,
-u32 k, u32 rank, u64 rows, u32 domain, a pad word, then k*k f32 row-major. Two
-kinds of name, both GGUF-style, both with the checkpoint's GLOBAL expert
-numbering (rad_block_moe_fp8.h: ge = expert_base + e):
-
-    gram.r<rank>.blk.L.ffn_down_exps.bin        the layer's pooled gram
-    gram.r<rank>.blk.L.ffn_down_exps.<e>.bin    expert e's own gram
-
-`rows` is that file's routing/token count and the matrix is Σ x xᵀ over those
-rows, so **the diagonal is exactly the per-column activation second moment an
-imatrix wants**, and `rows` is the count the reader hands back from `count()`.
-Every off-diagonal term is dropped on purpose: the GGUF format has nowhere to
-put a full matrix, and the quantiser asks for columns.
-
-OUTPUT, per layer L (core/format/imatrix.h: names WITHOUT `.weight`, a MoE
-layer's experts folded into ONE entry, so expert 9 is slice 9 of
-`blk.L.ffn_down_exps`):
-
-  blk.L.ffn_down_exps    in_sum2 [k, n_expert] expert-major, counts [1, n_expert]
-  blk.L.ffn_gate_up_exps the SAME matrices at the SAME offsets. A routed expert's
-                         gate_up input is the same hidden-state rows as its down
-                         input, so the second moment over them is identical and
-                         so is the routing count. Two tensor infos over one
-                         payload: the reader maps each half independently
-                         (imatrix.cpp joins `<base>.in_sum2` with `<base>.counts`
-                         by base name), and copying ~200 MB to state one fact
-                         twice buys no correctness.
-  blk.L.ssm_inz          [k] and [1], from the pooled gram: that row's input is
-                         the same hidden state, so its columns take the pooled
-                         diagonal and its count is the layer's pooled rows.
-
-  Then STOP. Nothing whose input width is not the gram's k — no ssm_out, no
-  attn_output, no mtp.*, no ple_ngram. importance_for() answers false when the
-  entry's cols do not equal the weight's width and the convert proceeds without
-  it: an entry the reader silently ignores is a lie in the artifact, worse than
-  an absent one. The corollary to check before trusting the two hidden-width
-  entries: the tap writes the gate_up gram at g.n_embd and the down gram at the
-  expert width, so the gram's k must equal the checkpoint's hidden width (its
-  config.json). Where they differ, gate_up/ssm_inz are inert, not wrong.
-
-INHERITANCE. An expert with no own gram carries the layer's POOLED diagonal, and
-its count stays its own routing rows — the rule the engine itself applies when it
-picks a Hessian (libquant/lq_hess.h, calib_resolve: an expert's own gram only
-once its rank files hold kOwnRowsPerK * K rows; below that a fit to so few rows
-is worse than round-to-nearest, and those experts carry a fraction of a percent
-of the routing). The count never inherits: popularity is `count`'s job. The count
-of inherited experts is reported on stderr.
-
-RANK FOLDING. TP=2 writes gram.r0.* and gram.r1.* with GLOBAL expert numbering,
-so the ranks describe DISJOINT experts and the fold is a UNION into the one
-[k, n_expert] entry. A pooled gram is the opposite case: every rank summed the
-same stem over its own rows, so the fold is a SUM, rows included (calib_sum,
-calib_rows). The same global expert in two per-expert files is legal only when
-the numbers agree exactly; otherwise the recording is corrupt and the entry would
-be whichever file sorted last, so refuse.
-
-GGUF v3 (the only version imatrix.cpp accepts — version != 3 is a refusal):
-`general.alignment` u32, `imatrix.chunk_size` u32, `imatrix.chunk_count` u32,
-`imatrix.datasets` array of strings; tensors f32 (ggml type 0) with offsets
-relative to the aligned data section. Every tensor offset is padded up to
-`general.alignment` and the data section itself starts aligned. That is the
-classic hand-rolled-writer bug: an unaligned offset makes the reader's extent
-arithmetic point into the middle of the previous tensor's floats, and it reads
-them without complaint.
-
-chunk_count DERIVATION. The corpus row count is the LARGEST single-layer pooled
-row total, not a sum over layers: every layer's tap accumulated over the whole
-corpus, so adding the layers counts each token once per layer and inflates the
-figure by the layer count. chunk_count = that row total // chunk_size, the
-"chunks of chunk_size" line imatrix.cpp prints for itself.
-
-REFUSALS, each exit 2 with a message naming what is missing:
-  NO_GRAMS         the directory holds no RADGRAM2 down-projection gram
-  NOT_RADGRAM2     a gram whose magic is not RADGRAM2
-  SHORT            a gram whose length is not 32 + k*k*4
-  NO_POOLED        a layer with expert grams and no pooled gram to inherit from
-  K_MISMATCH       a layer whose files disagree about k (rank pooled grams, or an
-                   expert gram against its layer's pooled gram)
-  EXPERT_CONFLICT  a global expert recorded twice with different numbers
-  EXISTS           the -o path already holds a file (the trash law: move it)
-  CHUNK_COUNT      the derived chunk count does not fit the u32 metadata field
-
-USAGE. grams-to-imatrix.py <calib-dir> -o <out.gguf>
-       [--datasets NAME,...] [--chunk-size N] [--min-rows N] [-v]
-"""
-import argparse
-import os
-import re
-import struct
-import sys
-
-MAGIC = b"RADGRAM2"
-HDR = 32                       # 8s I I Q I + pad, rad_arch.h
-KOWN_ROWS_PER_K = 4            # libquant/lq_hess.h kOwnRowsPerK
-ALIGNMENT = 32                 # general.alignment, and the pad unit
-
-POOLED_RE = re.compile(r"^gram\.r(\d+)\.blk\.(\d+)\.ffn_down_exps\.bin$")
-EXPERT_RE = re.compile(r"^gram\.r(\d+)\.blk\.(\d+)\.ffn_down_exps\.(\d+)\.bin$")
-
-GT_U32, GT_STR, GT_ARR = 4, 8, 9
-GGML_F32 = 0
-
-
-def refuse(msg):
-    sys.stderr.write("REFUSED %s\n" % msg)
-    sys.exit(2)
-
-
-def read_gram(path):
-    """(k, rank, rows, domain, diagonal) from one RADGRAM2 file."""
-    try:
-        with open(path, "rb") as f:
-            raw = f.read()
-    except OSError as e:
-        refuse("UNREADABLE %s: %s" % (path, e))
-    if len(raw) < HDR:
-        refuse("SHORT %s: %d bytes, under the %d-byte RADGRAM2 header"
-               % (path, len(raw), HDR))
-    magic, k, rank, rows, domain = struct.unpack_from("<8sIIQI", raw, 0)
-    if magic != MAGIC:
-        refuse("NOT_RADGRAM2 %s: magic %r, expected b'RADGRAM2'" % (path, magic))
-    if k <= 0:
-        refuse("SHORT %s: header claims k=%d, which describes no matrix" % (path, k))
-    need = HDR + k * k * 4
-    if len(raw) != need:
-        refuse("SHORT %s: %d bytes, expected %d (32 + k*k*4 for k=%d)"
-               % (path, len(raw), need, k))
-    # The diagonal only, read by stride out of the row-major matrix.
-    diag = [struct.unpack_from("<f", raw, HDR + (i * k + i) * 4)[0]
-            for i in range(k)]
-    return k, rank, rows, domain, diag
-
-
-def load_dir(d, verbose):
-    """{layer: {"pooled": gram|None, "experts": {global e: gram}}} + rotated count.
-
-    Files outside the ffn_down_exps stem are not ours to fold: the tap names a
-    pooled gram after every projection it taps, and those carry other widths."""
-    if not os.path.isdir(d):
-        refuse("NO_GRAMS %s: not a directory" % d)
-    layers, rotated = {}, 0
-    for name in sorted(os.listdir(d)):
-        m = POOLED_RE.match(name) or EXPERT_RE.match(name)
-        if not m:
-            continue
-        path = os.path.join(d, name)
-        if not os.path.isfile(path):
-            continue
-        pooled = bool(POOLED_RE.match(name))
-        layer = int(m.group(2))
-        k, rank, rows, domain, diag = read_gram(path)
-        if domain != 0:
-            rotated += 1
-        L = layers.setdefault(layer, {"pooled": None, "experts": {}})
-        if pooled:
-            P = L["pooled"]
-            if P is None:
-                L["pooled"] = {"k": k, "rows": rows, "diag": diag, "paths": [path]}
-            elif P["k"] != k:
-                refuse("K_MISMATCH layer %d: pooled grams %s (k=%d) and %s (k=%d)"
-                       " disagree about the width"
-                       % (layer, P["paths"][0], P["k"], path, k))
-            else:
-                # calib_sum: each rank summed the same stem over its own rows.
-                P["rows"] += rows
-                P["paths"].append(path)
-                for i in range(k):
-                    P["diag"][i] += diag[i]
-            if verbose:
-                sys.stderr.write("pooled layer %d: %s k=%d rows=%d\n"
-                                 % (layer, name, k, rows))
-            continue
-        e = int(m.group(3))
-        own = L["experts"].get(e)
-        if own is None:
-            L["experts"][e] = {"k": k, "rows": rows, "diag": diag,
-                               "path": path, "ranks": [rank]}
-            if verbose:
-                sys.stderr.write("expert layer %d r%d e%d: rows=%d\n"
-                                 % (layer, rank, e, rows))
-            continue
-        if own["rows"] != rows or own["diag"] != diag:
-            refuse("EXPERT_CONFLICT layer %d expert %d: %s (rows=%d) and %s"
-                   " (rows=%d) record the same global expert with different"
-                   " numbers" % (layer, e, own["path"], own["rows"], path, rows))
-        own["ranks"].append(rank)
-        sys.stderr.write("note: layer %d expert %d recorded identically by rank %s"
-                         " and %s; folded once\n"
-                         % (layer, e, own["path"], name))
-    if not layers:
-        refuse("NO_GRAMS %s: no RADGRAM2 gram.r<rank>.blk.<L>.ffn_down_exps"
-               "[.<expert>].bin files in the directory" % d)
-    return layers, rotated
-
-
-def build_entries(layers, min_rows, verbose):
-    """([ (name, dims, payload|None, key) ], census, layers emitted)."""
-    entries = []
-    census = {"inherited": 0, "experts": 0, "routing": 0, "rows": 0, "layers": 0}
-    for layer in sorted(layers):
-        P, E = layers[layer]["pooled"], layers[layer]["experts"]
-        if E and P is None:
-            refuse("NO_POOLED layer %d: %d expert gram(s) but no pooled gram (an"
-                   " expected gram.r<rank>.blk.%d.ffn_down_exps.bin), so an expert"
-                   " under the row threshold would have nothing to inherit"
-                   % (layer, len(E), layer))
-        if P is None:
-            continue
-        k = P["k"]
-        census["layers"] += 1
-        census["rows"] = max(census["rows"], P["rows"])
-        dn = "blk.%d.ffn_down_exps" % layer
-        # A staging key names ONE payload. A gate_up entry reuses the down
-        # layer's bytes by carrying the same key with no payload of its own;
-        # in_sum2 and counts are different bytes and must never share a key.
-        ksum, kcnt = (layer, "sum2"), (layer, "counts")
-        kpgm, kpcnt = (layer, "pooled_sum2"), (layer, "pooled_counts")
-        # One entry holds one width: an expert gram recorded at another k would
-        # inherit (or be inherited by) a diagonal of the wrong length, and the
-        # reader would then answer `cols` from whichever file set dims[0].
-        for e in sorted(E):
-            if E[e]["k"] != k:
-                refuse("K_MISMATCH layer %d expert %d: %s holds k=%d and this"
-                       " layer's pooled gram is k=%d" % (layer, e, E[e]["path"],
-                                                          E[e]["k"], k))
-
-        if not E:
-            # No per-expert recording for this layer: emit the dense form
-            # ([k], [1]) rather than 512 identical slices, which would claim a
-            # per-expert measurement that was never taken.
-            entries.append((dn + ".in_sum2", [k],
-                            struct.pack("<%df" % k, *P["diag"]), ksum))
-            entries.append((dn + ".counts", [1],
-                            struct.pack("<f", float(P["rows"])), kcnt))
-            sys.stderr.write("note: layer %d has no per-expert grams; %s is"
-                             " dense over the pooled gram\n" % (layer, dn))
-        else:
-            floor = min_rows if min_rows > 0 else KOWN_ROWS_PER_K * k
-            n_expert = max(E) + 1
-            sum2, counts = bytearray(), bytearray()
-            for e in range(n_expert):
-                own = E.get(e)
-                if own is not None and own["rows"] >= floor:
-                    src = own["diag"]
-                    rows = own["rows"]
-                else:
-                    src = P["diag"]
-                    rows = own["rows"] if own is not None else 0
-                    census["inherited"] += 1
-                sum2 += struct.pack("<%df" % k, *src)
-                counts += struct.pack("<f", float(rows))
-                census["experts"] += 1
-                census["routing"] += rows
-            if min(E) != 0:
-                sys.stderr.write("note: layer %d has no gram for experts 0..%d;"
-                                 " those slices carry the pooled gram at count 0\n"
-                                 % (layer, min(E) - 1))
-            entries.append((dn + ".in_sum2", [k, n_expert], bytes(sum2), ksum))
-            entries.append((dn + ".counts", [1, n_expert], bytes(counts), kcnt))
-            gu = "blk.%d.ffn_gate_up_exps" % layer
-            entries.append((gu + ".in_sum2", [k, n_expert], None, ksum))
-            entries.append((gu + ".counts", [1, n_expert], None, kcnt))
-            if verbose:
-                sys.stderr.write("layer %d: k=%d n_expert=%d pooled_rows=%d"
-                                 " own-gram floor=%d\n"
-                                 % (layer, k, n_expert, P["rows"], floor))
-
-        inz = "blk.%d.ssm_inz" % layer
-        entries.append((inz + ".in_sum2", [k],
-                        struct.pack("<%df" % k, *P["diag"]), kpgm))
-        entries.append((inz + ".counts", [1],
-                        struct.pack("<f", float(P["rows"])), kpcnt))
-    return entries, census
-
-
-def enc_str(v):
-    b = v.encode("utf-8")
-    return struct.pack("<Q", len(b)) + b
-
-
-def write_gguf(path, entries, datasets, chunk_size, chunk_count):
-    """Write GGUF v3 and return its size in bytes.
-
-    One payload per key: entries that share a key share the bytes and the
-    offset, so a second tensor info states the same fact without copying it."""
-    kv = bytearray()
-    kv += enc_str("general.alignment") + struct.pack("<I", GT_U32) \
-        + struct.pack("<I", ALIGNMENT)
-    kv += enc_str("imatrix.chunk_size") + struct.pack("<I", GT_U32) \
-        + struct.pack("<I", chunk_size)
-    kv += enc_str("imatrix.chunk_count") + struct.pack("<I", GT_U32) \
-        + struct.pack("<I", chunk_count)
-    kv += enc_str("imatrix.datasets") + struct.pack("<I", GT_ARR) \
-        + struct.pack("<I", GT_STR) + struct.pack("<Q", len(datasets))
-    for d in datasets:
-        kv += enc_str(d)
-
-    head = bytearray()
-    head += b"GGUF" + struct.pack("<I", 3)
-    head += struct.pack("<Q", len(entries)) + struct.pack("<Q", 4)
-    head += kv
-
-    payloads = {}
-    for name, _dims, payload, key in entries:
-        if payload is None:
-            continue
-        prev = payloads.get(key)
-        if prev is not None and prev != payload:
-            # Two different payloads on one key would ship whichever was
-            # appended last while BOTH tensor infos pointed at it: the counts
-            # payload landing over the in_sum2 payload is exactly how a
-            # hand-rolled GGUF writer loses half its data without an error.
-            refuse("INTERNAL %s: two different payloads share one staging key"
-                   % name)
-        payloads.setdefault(key, payload)
-    infos = bytearray()
-    offsets, order, size = {}, [], 0
-    for name, dims, payload, key in entries:
-        if key not in payloads:
-            refuse("INTERNAL %s: no payload staged for its key" % name)
-        if key not in offsets:
-            offsets[key] = (size + ALIGNMENT - 1) // ALIGNMENT * ALIGNMENT
-            size = offsets[key] + len(payloads[key])
-            order.append(key)
-        infos += enc_str(name) + struct.pack("<I", len(dims))
-        for d in dims:
-            infos += struct.pack("<Q", d)
-        infos += struct.pack("<I", GGML_F32) + struct.pack("<Q", offsets[key])
-
-    body = bytes(head) + bytes(infos)
-    data_start = (len(body) + ALIGNMENT - 1) // ALIGNMENT * ALIGNMENT
-    with open(path, "wb") as f:
-        f.write(body)
-        f.write(b"\0" * (data_start - len(body)))
-        # The offsets in the tensor infos are the file's law, not a hint: each
-        # payload must land at its own padded offset. Writing them back to back
-        # instead leaves every reader that trusts the info — imatrix.cpp does —
-        # reading its neighbour's floats: plausible values, no error, wrong
-        # quantisation.
-        here = data_start
-        for key in order:
-            f.write(b"\0" * (data_start + offsets[key] - here))
-            f.write(payloads[key])
-            here = data_start + offsets[key] + len(payloads[key])
-        return f.tell()
-
-
-def main():
-    ap = argparse.ArgumentParser(
-        description="Fold a radiance calibration recording into a GGUF v3 imatrix.")
-    ap.add_argument("calib_dir")
-    ap.add_argument("-o", "--out", required=True)
-    ap.add_argument("--datasets", default="",
-                    help="comma-separated names for imatrix.datasets")
-    ap.add_argument("--chunk-size", type=int, default=4096,
-                    help="rows per chunk for imatrix.chunk_size (default 4096)")
-    ap.add_argument("--min-rows", type=int, default=0,
-                    help="own-gram row threshold (default 4*k, the engine's"
-                         " kOwnRowsPerK law)")
-    ap.add_argument("-v", "--verbose", action="store_true")
-    a = ap.parse_args()
-
-    if os.path.exists(a.out):
-        # The repo's deletion law: an artifact that exists is moved to trash by
-        # a human, never silently overwritten by a re-run of the tool that made
-        # it, so a second convert cannot destroy the imatrix the first one fed.
-        refuse("EXISTS %s: an imatrix is already there; move it to"
-               " .AGENTTRASH/ or name another -o" % a.out)
-    if a.chunk_size <= 0:
-        refuse("BAD_CHUNK_SIZE --chunk-size %d is not positive" % a.chunk_size)
-    layers, rotated = load_dir(a.calib_dir, a.verbose)
-    entries, census = build_entries(layers, a.min_rows, a.verbose)
-    if not entries:
-        refuse("NO_GRAMS %s: no layer holds a pooled gram to fold" % a.calib_dir)
-    if rotated:
-        sys.stderr.write("note: %d gram(s) recorded in a rotated domain: their"
-                         " diagonal is the rotated activation's second moment,"
-                         " not the model's own\n" % rotated)
-
-    chunk_count = census["rows"] // a.chunk_size
-    if chunk_count > 0xFFFFFFFF:
-        # imatrix.chunk_count is a u32 in the reader's grammar, so there is no
-        # legal way to record a bigger one. Reaching this means either a chunk
-        # size picked for a far larger run or a row total read out of the wrong
-        # header offset — rows is a u64 and a u32 parse is off by 2**32 — and
-        # the reader would trust whatever number landed in the field.
-        refuse("CHUNK_COUNT %d = %d rows // %d does not fit the u32"
-               " imatrix.chunk_count field; raise --chunk-size"
-               % (chunk_count, census["rows"], a.chunk_size))
-    nbytes = write_gguf(a.out, entries, [d for d in a.datasets.split(",") if d],
-                        a.chunk_size, chunk_count)
-    sys.stderr.write("IMATRIX_OK entries=%d layers=%d experts=%d inherited=%d"
-                     " rows=%d routing=%d chunks=%d/%d bytes=%d out=%s\n"
-                     % (len(entries), census["layers"], census["experts"],
-                        census["inherited"], census["rows"], census["routing"],
-                        chunk_count, a.chunk_size, nbytes, a.out))
-
-
-if __name__ == "__main__":
-    main()