diff --git a/scripts/deploy-remote.sh b/scripts/deploy-remote.sh index 86ff4a5..f4382c8 100755 --- a/scripts/deploy-remote.sh +++ b/scripts/deploy-remote.sh @@ -1084,12 +1084,12 @@ wait_for_llm_large_ready() { # # It is a SEPARATE endpoint on port 7771; frank-large keeps 7770. The 3090 is # not shared: frank-large's halogen engine runs on the gfx1151 iGPU. -LLM_SMALL_MODEL="${LLM_SMALL_MODEL:-/home/dank/models/Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp/Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp.gguf}" +LLM_SMALL_MODEL="${LLM_SMALL_MODEL:-/home/dank/models/Gemma4-12B-QAT/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf}" deploy_llm_small() { if [[ ! -f "$LLM_SMALL_MODEL" ]]; then echo "ERROR: model absent at $LLM_SMALL_MODEL" >&2 - echo "frank-small: fetch ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF (the -mtp build plus the mmproj) first;" >&2 + echo "frank-small: fetch HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced (Q4_K_M, the mmproj and the MTP sidecar) first;" >&2 echo "frank-small: refusing to start a unit that cannot load." >&2 return 1 fi diff --git a/scripts/frank-small.env b/scripts/frank-small.env index 898f52f..699fbef 100644 --- a/scripts/frank-small.env +++ b/scripts/frank-small.env @@ -1,110 +1,90 @@ -# Tunables for frank-small (ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF, the IQ3_S -# build with the MTP head, plus the BF16 vision projector) on mainline -# llama.cpp, Dankclaw's RTX 3090, since 2026-09-16. +# Tunables for frank-small (HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS- +# Balanced, Q4_K_M, plus the BF16 vision projector and the separate MTP +# sidecar) on mainline llama.cpp, Dankclaw's RTX 3090, since 2026-09-17. # -# Runtime: llama.cpp master 37b53fd (2026-09-16), CUDA build for sm_86: +# Runtime: llama.cpp master 37b53fd, CUDA build for sm_86: # cmake -B build-cuda -DCMAKE_BUILD_TYPE=Release -DGGML_NATIVE=ON \ -# -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=86 +# -DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=86 -DGGML_CUDA_FA_ALL_QUANTS=ON # cmake --build build-cuda --target llama-server -j -# GGML_CUDA_FA_ALL_QUANTS is deliberately OFF in that build: it is only needed -# for QUANTIZED KV with flash attention, and this service runs f16 KV (below). +# GGML_CUDA_FA_ALL_QUANTS is ON: this service runs q8_0 KV with flash +# attention, and without the flag quantized-KV prefill collapses ~12x on +# CUDA (see the CUDA lesson in AGENTS.md). # -# Model: ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF, the `-mtp` build of IQ3_S. -# GSQ-RCO assigns a separate quantization type to every tensor from a -# gradient-based search under a total size budget, rather than applying one -# type throughout; IQ3_S at 3.50 bpw is the release's task-lossless operating -# point (AIME25 100.00 and LiveCodeBench v6 85.71 match BF16 exactly, -# GPQA-Diamond 0.51 behind, at 11.8 GB against 53.8). +# Model: HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced at Q4_K_M +# (6.87 GiB). Architecture (GGUF arch gemma4): 48 layers, MHA with 16 kv +# heads x 512 head_dim, rope freq_base 1e6, final logit softcapping 30, +# per-layer token embeddings (PLE) inside the file, and a sliding-window +# attention pattern (attention.sliding_window = 1024) -- most layers cache +# only a 1024-position window, which is why the KV pool is a fraction of +# the full-ctx x all-layers number. # -# WHY THAT FILE: the `-mtp` build is ~0.35 GB larger because it carries the -# model's Multi-Token Prediction head as GGUF block `blk.64.nextn.*` -# (qwen35.nextn_predict_layers = 1). llama.cpp loads it from the SAME file -- -# `--spec-type draft-mtp` sets load_mtp, and the draft context runs on the main -# model's weights (common/common.cpp passes shares_model when there is no -# --model-draft; speculative.cpp gives it LLAMA_CONTEXT_TYPE_MTP), so there is -# no second 12 GB copy in VRAM. MTP is therefore a property of the FILE, not of -# the flags: the plain IQ3_S build has no MTP tensors to load. +# MTP: the Multi-Token Prediction head ships as a SEPARATE file +# (mtp-gemma-4-12B-it.gguf, arch gemma4-assistant, 4 nextn layers, 0.24 +# GiB). Unlike the Qwen3.8 -mtp build (head inside the main file), this one +# is passed via --model-draft with --spec-type draft-mtp, so the draft +# context loads the assistant model. The same --spec-type value chains the +# draftless ngram-mod matcher, which attaches unconditionally; two +# context-backed drafters cannot share one process, so draft-mtp,ngram-mod +# is the only legal shape that carries both. # -# Architecture (GGUF arch qwen35): 64 layers laid out as 16 x (3 x (Gated -# DeltaNet -> FFN) + 1 x (Gated Attention -> FFN)) -- 48 linear-attention -# layers with CONSTANT-SIZE per-sequence state and 16 full-attention layers, -# 4 KV heads x 256 head_dim. Only the attention layers take KV, so a token -# costs 2 (K,V) x 4 heads x 256 x 2 B = 64 KiB at f16 (34 KiB at q8_0, 18 KiB -# at q4_0), and the DeltaNet layers add ~0.16 GiB per sequence in f32 at any -# depth. +# SIZING (RTX 3090, 24576 MiB): not modelled by hand -- CTX_SIZE is left +# unset and --fit sizes the KV pool (q8_0 K and V) against what the 6.87 +# GiB of weights, the 0.16 GiB projector, the MTP sidecar's draft context +# and the compute buffers leave on the card. The engine prints the chosen +# context at startup; read it from the log, do not hard-code it back here. # -# SIZING (RTX 3090, 24576 MiB) -- modelled, and the loader's own ledger -# ("KV self size", "compute buffer size") outranks it: -# weights 11.29 GiB (12,120,016,960 B) -# mmproj 0.87 GiB (931,146,528 B, 27 blocks) -# MTP draft KV 0.50 GiB (its context is n_ctx long -# over one nextn layer: 4 KiB/token) -# DeltaNet state 0.16 GiB (one sequence) -# CUDA context + prefill/decode bufs ~1.5 GiB -# KV at CTX_SIZE 8.00 GiB (131,072 x 64 KiB) -# -------- -# ~22.3 GiB of 24, ~2 GiB of slack -# The binding number is the KV: ~9.5 GiB is left after the fixed terms, which -# at 64 KiB/token is ~155k tokens across all slots. The deployed shape is one -# slot at 131,072, full f16 precision, no KV quantization risk, no rebuild. -# Alternatives inside the same budget: 2 x 65536 at f16; 4 x 65536 or -# 1 x 262144 at q8_0, both of which need a rebuild with -# -DGGML_CUDA_FA_ALL_QUANTS=ON (without it quantized-KV prefill collapses -# ~12x on CUDA -- see the CUDA lesson in AGENTS.md). -# --parallel N DIVIDES --ctx-size between slots; it does not multiply. One slot -# means a second concurrent request queues behind the first. +# Vision: --mmproj loads the BF16 projector (11 tensors, 52M params; it +# also carries an audio encoder, unused by the fleet). The fleet's image +# path lives here, which is why halogen no longer sets HALOGEN_VISION_TOWER. # -# Sampling: greedy by default, which is the fleet contract (a request that -# sends no temperature decodes greedy; a client that sends one gets its own). -# Qwen's own agentic evaluations used temperature 1.0 / top_p 0.95, and the -# harness applies exactly that per model in models.yml (extraBody), the same -# way it did for the earlier frank-large runtime. +# Sampling: greedy by default (the fleet contract); a client that sends a +# temperature gets its own, and the harness applies per-model overrides +# from models.yml. # -# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE (HIP reads -# those bare vars on the ROCm hosts -- see the 2026-08-13 incident in +# WARNING: do not name any variable TEMP, HOST, or GPU_MAX_HEAP_SIZE (HIP +# reads those bare vars on the ROCm hosts -- see the 2026-08-13 incident in # AGENTS.md). This box is CUDA, but the rule keeps env files portable. -# llama.cpp runtime binary: mainline master 37b53fd, CUDA sm_86. +# llama.cpp runtime binary: mainline master 37b53fd, CUDA sm_86, +# FA_ALL_QUANTS=ON. LLAMA_BIN=/home/dank/GitPackages/llama.cpp-mainline/build-cuda/bin/llama-server -# Model package. The -mtp file is required for speculative decoding. -MODEL_DIR=/home/dank/models/Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp -MODEL_FILE=Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp.gguf -MMPROJ_PATH=/home/dank/models/Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp/mmproj-Qwen3.8-27B-BF16.gguf +# Model package. The MTP sidecar file is required for speculative decoding. +MODEL_DIR=/home/dank/models/Gemma4-12B-QAT +MODEL_FILE=Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-Q4_K_M.gguf +MMPROJ_PATH=/home/dank/models/Gemma4-12B-QAT/mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf +DRAFT_FILE=mtp-gemma-4-12B-it.gguf -# Fleet identity and network. 7771 is this service's own endpoint on Dankclaw; -# 7770 stays frank-large's. The alias is the id at /v1/models and what clients -# ask for -- the harness entry in models.yml names it. +# Fleet identity and network. 7771 is this service's own endpoint on +# Dankclaw; 7770 stays frank-large's. The alias is the id at /v1/models and +# what clients ask for -- the harness entry in models.yml names it. ALIAS=frank-small BIND_ADDR=0.0.0.0 LISTEN_PORT=7771 -# One slot at 131,072 tokens with f16 KV (see the sizing note above). -CTX_SIZE=131072 +# Context: intentionally unset -- --fit decides it (see the sizing note). +# One slot; a second concurrent request queues behind the first. PARALLEL=1 -CACHE_TYPE_K=f16 -CACHE_TYPE_V=f16 +CACHE_TYPE_K=q8_0 +CACHE_TYPE_V=q8_0 -# Batch geometry: llama.cpp's own defaults (2048 logical / 512 physical). The -# prefill wall clock at this model size is set by the card, not by ubatch, and -# the small ubatch keeps the DeltaNet chunk buffers small. Raise UBATCH_SIZE -# only after reading the compute buffer size the loader reports. +# Batch geometry: llama.cpp's own defaults (2048 logical / 512 physical). BATCH_SIZE=2048 UBATCH_SIZE=512 # CPU threads: this service runs entirely on the GPU (NGL=999), so threads -# cover tokenization, sampling and the HTTP layer only. Deliberately modest -- -# this host's CPU is shared with halogen's engine, which is CPU-hungry. +# cover tokenization, sampling and the HTTP layer only. Deliberately modest +# -- this host's CPU is shared with halogen's engine, which is CPU-hungry. NUM_THREADS=8 THREAD_BATCH=8 -# Every layer on the 3090, with flash attention. +# Every layer on the 3090, with flash attention (required for q8 KV). NGL=999 FLASH_ATTN=on -# Speculative decoding from the model's own MTP head (see the model note). -# Draft depth stays llama.cpp's default of 3 tokens. -SPEC_TYPE=draft-mtp +# Speculative decoding: the MTP sidecar (draft context) chained with the +# draftless ngram-mod matcher. Draft depth stays llama.cpp's default of 3. +SPEC_TYPE=draft-mtp,ngram-mod # Greedy default (fleet contract); reasoning is extracted into # reasoning_content with an unlimited budget (the model decides). diff --git a/scripts/serve-frank-small.sh b/scripts/serve-frank-small.sh index 4a939f1..7dd1710 100755 --- a/scripts/serve-frank-small.sh +++ b/scripts/serve-frank-small.sh @@ -1,21 +1,27 @@ #!/usr/bin/env bash -# Serve ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp as frank-small on Dankclaw's -# RTX 3090 via mainline llama.cpp. +# Serve HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced (Q4_K_M) as +# frank-small on Dankclaw's RTX 3090 via mainline llama.cpp. # -# Topology: the whole model lives in VRAM (-ngl 999) -- 11.29 GiB of IQ3_S-mtp -# weights, 0.87 GiB of BF16 vision projector and ~8 GiB of f16 KV inside the -# card's 24 GiB. The host CPU only tokenizes and samples here; this box's CPU +# Topology: the whole model lives in VRAM (-ngl 999) -- 6.87 GiB of Q4_K_M +# weights plus the BF16 vision projector and q8_0 KV inside the card's +# 24 GiB. The host CPU only tokenizes and samples here; this box's CPU # belongs to the halogen engine that serves frank-large. # -# MTP: the `-mtp` build carries the NextN block (blk.64.nextn.*), and -# `--spec-type draft-mtp` makes llama.cpp load it and run the draft context on -# the SAME weights. There is no --model-draft here on purpose: a separate draft -# path would load a second 12 GB copy of a 12 GB model. Draft depth is -# llama.cpp's default (--spec-draft-n-max 3). +# MTP: this model's Multi-Token Prediction head ships as a SEPARATE file +# (mtp-gemma-4-12B-it.gguf, arch gemma4-assistant, 4 nextn layers). It is +# passed via --model-draft with --spec-type draft-mtp: the draft context +# loads the assistant model. The same --spec-type value chains the +# draftless ngram-mod matcher, which attaches unconditionally; two +# context-backed drafters cannot share one process, so this chain is the +# only shape that carries both. # -# Vision: --mmproj loads the BF16 projector, so image content parts work. The -# fleet's image path moved here from frank-large on 2026-09-16, which is why -# halogen no longer sets HALOGEN_VISION_TOWER. +# Context: CTX_SIZE is left unset and --fit sizes the KV pool (q8_0 K and +# V) against what the weights, projector, draft context and compute +# buffers leave on the card; the chosen value lands in the startup log. +# +# Vision: --mmproj loads the BF16 projector (it also carries an audio +# encoder; vision is the fleet contract). The fleet's image path lives +# here, which is why halogen no longer sets HALOGEN_VISION_TOWER. # # Sampling: greedy by default (the fleet contract). Clients that send their own # temperature get their own values, and the harness overrides per model from @@ -40,11 +46,12 @@ fi : "${LLAMA_BIN:=/home/dank/GitPackages/llama.cpp-mainline/build-cuda/bin/llama-server}" : "${MODEL_DIR:=/home/dank/models/Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp}" : "${MODEL_FILE:=Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp.gguf}" -: "${MMPROJ_PATH:=$MODEL_DIR/mmproj-Qwen3.8-27B-BF16.gguf}" +: "${MMPROJ_PATH:=$MODEL_DIR/mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16.gguf}" +: "${DRAFT_FILE:=}" : "${ALIAS:=frank-small}" : "${BIND_ADDR:=0.0.0.0}" : "${LISTEN_PORT:=7771}" -: "${CTX_SIZE:=131072}" +: "${CTX_SIZE:=}" : "${PARALLEL:=1}" : "${CACHE_TYPE_K:=f16}" : "${CACHE_TYPE_V:=f16}" @@ -65,6 +72,9 @@ fi for path in "$LLAMA_BIN" "$MODEL_DIR/$MODEL_FILE" "$MMPROJ_PATH"; do [[ -e "$path" ]] || { echo "frank-small: missing $path" >&2; exit 1; } done +if [[ -n "${DRAFT_FILE:-}" ]]; then + [[ -e "$MODEL_DIR/$DRAFT_FILE" ]] || { echo "frank-small: missing $MODEL_DIR/$DRAFT_FILE" >&2; exit 1; } +fi # 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. @@ -80,15 +90,30 @@ if [[ -n "${SPEC_TYPE:-}" && "$SPEC_TYPE" != "none" ]]; then SPEC_ARGS=(--spec-type "$SPEC_TYPE") fi +DRAFT_ARGS=() +if [[ -n "${DRAFT_FILE:-}" ]]; then + DRAFT_ARGS=(--model-draft "$MODEL_DIR/$DRAFT_FILE") +fi + +# CTX_SIZE set -> pinned context. Unset -> --fit sizes the KV pool against +# whatever the weights, projector, draft context and compute buffers leave +# on the card; the engine prints the chosen value at startup. +if [[ -n "${CTX_SIZE:-}" ]]; then + CTX_ARGS=(--ctx-size "$CTX_SIZE") +else + CTX_ARGS=(--fit on) +fi + exec "$LLAMA_BIN" \ --model "$MODEL_DIR/$MODEL_FILE" \ "${MMPROJ_ARGS[@]}" \ + "${DRAFT_ARGS[@]}" \ --alias "$ALIAS" \ --host "$BIND_ADDR" \ --port "$LISTEN_PORT" \ --gpu-layers "$NGL" \ --flash-attn "$FLASH_ATTN" \ - --ctx-size "$CTX_SIZE" \ + "${CTX_ARGS[@]}" \ --parallel "$PARALLEL" \ --batch-size "$BATCH_SIZE" \ --ubatch-size "$UBATCH_SIZE" \ diff --git a/tests/frank_small_unit.bats b/tests/frank_small_unit.bats index a982279..d952d8e 100755 --- a/tests/frank_small_unit.bats +++ b/tests/frank_small_unit.bats @@ -4,9 +4,9 @@ # went back to the halogen engine on the iGPU. This seam pins what the flags # alone do not say: boot persistence for a NATIVE runtime (no generated quadlet # is involved), the repo-relative paths the unit executes, the separate client -# port, the MTP contract (the head lives in the weights file, and no second copy -# of the model is loaded for it), the vision handoff from frank-large, and the -# KV budget that has to fit a 24 GiB card beside 12 GiB of weights. +# port, the MTP contract (the head is a separate sidecar file loaded as the +# draft model, chained behind ngram-mod), the vision handoff from frank-large, +# and the KV budget: q8_0 quantized KV whose context --fit sizes to the card. load helpers @@ -45,41 +45,42 @@ QUADLET_LARGE="$REPO_ROOT/dankclaw/frank-large/quadlet/frank-large.container" grep -q -- '--metrics' "$SERVE" } -@test "frank-small's MTP head comes from the weights file, not a second copy" { - grep -q '^SPEC_TYPE=draft-mtp$' "$ENV_FILE" +@test "frank-small drafts with the MTP sidecar chained behind ngram-mod" { + grep -q '^SPEC_TYPE=draft-mtp,ngram-mod$' "$ENV_FILE" grep -q -- '--spec-type "$SPEC_TYPE"' "$SERVE" - # The -mtp build is the one carrying blk.64.nextn.*; the plain IQ3_S has no - # MTP tensors at all, so MTP is a property of the file, not of the flags. - grep -q '^MODEL_FILE=.*-mtp\.gguf$' "$ENV_FILE" - # A separate draft model would load a second 12 GiB copy of a 12 GiB model. - # Only the effective configuration counts: the script's own comment explains - # why there is no draft path, and a textual grep would match that prose. - ! grep -vE '^[[:space:]]*#' "$SERVE" | grep -q -- '--model-draft' + # The Gemma4 MTP head is a separate assistant file (gemma4-assistant, 4 + # nextn layers); it loads as --model-draft and shares the target's last + # layers' KV. ngram-mod is draftless, so the chain is legal. + grep -q '^DRAFT_FILE=mtp-gemma-4-12B-it\.gguf$' "$ENV_FILE" + grep -q -- '--model-draft "$MODEL_DIR/$DRAFT_FILE"' "$SERVE" } @test "frank-small carries the fleet's image path, and only it" { - grep -q '^MMPROJ_PATH=.*mmproj-Qwen3\.8-27B-BF16\.gguf$' "$ENV_FILE" + grep -q '^MMPROJ_PATH=.*mmproj-Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced-BF16\.gguf$' "$ENV_FILE" grep -q -- '--mmproj "$MMPROJ_PATH"' "$SERVE" ! grep -q 'HALOGEN_VISION_TOWER' "$QUADLET_LARGE" } -@test "frank-small's KV fits the card beside the weights it loads" { - local ctx parallel parallel_slots cache_k cache_v - ctx="$(sed -nE 's/^CTX_SIZE=([0-9]+)$/\1/p' "$ENV_FILE")" +@test "frank-small quantizes KV to q8 and lets --fit size the context" { + local parallel cache_k cache_v ctx parallel="$(sed -nE 's/^PARALLEL=([0-9]+)$/\1/p' "$ENV_FILE")" cache_k="$(sed -nE 's/^CACHE_TYPE_K=(.+)$/\1/p' "$ENV_FILE")" cache_v="$(sed -nE 's/^CACHE_TYPE_V=(.+)$/\1/p' "$ENV_FILE")" - [ -n "$ctx" ] && [ -n "$parallel" ] && [ -n "$cache_k" ] && [ -n "$cache_v" ] + ctx="$(sed -nE 's/^CTX_SIZE=([0-9]+)$/\1/p' "$ENV_FILE")" + [ -n "$parallel" ] && [ -n "$cache_k" ] && [ -n "$cache_v" ] [ "$parallel" -ge 1 ] - # qwen35 spends KV on its 16 full-attention layers only: 2 (K,V) x 4 heads x - # 256 dim x 2 B = 64 KiB per token at f16. 11.29 GiB of weights + 0.87 of - # mmproj + ~2 GiB of context/compute/MTP leave under 10 GiB of the card's - # 24 GiB for KV, and --parallel divides --ctx-size between the slots. - [ $((ctx * 64)) -le $((10 * 1024 * 1024)) ] - # f16 is the deployed type on purpose: a quantized KV needs the - # GGML_CUDA_FA_ALL_QUANTS build option, without which prefill on CUDA - # collapses about 12x (see the CUDA lesson in AGENTS.md). - [ "$cache_k" = "f16" ] && [ "$cache_v" = "f16" ] + # q8_0 KV is what fits the 24 GiB card beside 7.4 GiB of Q4_K_M weights + + # mmproj + sidecar: Gemma4's 16 kv heads x 512 dim cost 16 KiB per token + # per layer at q8, and the model's sliding-window pattern keeps the pool + # far below full-ctx x all-layers. The engine itself sizes the context: + # CTX_SIZE is unset, so the serve script passes --fit on. + [ -z "$ctx" ] + [ "$cache_k" = "q8_0" ] && [ "$cache_v" = "q8_0" ] + grep -q -- '--fit on' "$SERVE" + # Quantized KV on CUDA needs the GGML_CUDA_FA_ALL_QUANTS build option, + # without which prefill collapses about 12x (see the CUDA lesson in + # AGENTS.md). The build-cuda tree must carry it. + grep -q '^FLASH_ATTN=on$' "$ENV_FILE" } @test "frank-small runs on its own port beside frank-large's" { @@ -98,7 +99,7 @@ QUADLET_LARGE="$REPO_ROOT/dankclaw/frank-large/quadlet/frank-large.container" grep -q 'relink_unit frank-small' "$REMOTE_DEPLOY" grep -q 'systemctl enable frank-small.service' "$REMOTE_DEPLOY" grep -q 'systemctl restart frank-small.service' "$REMOTE_DEPLOY" - grep -q 'Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp' "$REMOTE_DEPLOY" + grep -q 'Gemma4-12B-QAT' "$REMOTE_DEPLOY" grep -q 'refusing to start a unit that cannot load' "$REMOTE_DEPLOY" grep -q '127.0.0.1:7771/health' "$REMOTE_DEPLOY" }