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Author SHA1 Message Date
Frank 19fdffe8bd docs(agents): a start-only quadlet handler no-ops an image bump
The law today's authentik bump paid for: start on an active unit is a no-op, so
the new digest installs and the old container keeps serving behind three green
gates. Restart applies a pin.
2026-10-30 15:34:10 -07:00
Frank f7aec7f154 fix(authentik): restart the units so an image bump actually applies
The handler called `systemctl --user start` on all three units. Start is a
no-op for an already-active unit, so installing a new digest under an active
authentik left the old container serving: today's 2026.8.3 -> 2026.8.5 bump
moved only the OUTPOST (whose handler restarts) and left server + worker on
2026.8.3 while the deploy, the health gate and the e2e suite were all green.
The generator re-renders from the .container, so a restart is the step that
applies a pin.
2026-10-30 15:34:02 -07:00
Frank e1d4d59773 docs(dragoon,zealot): record both runtime pins as they now run
frank-dragoon: engine 0.18.20 (image e35133b2…), the 18-model NPU catalog, the
re-cut qwen3-embedding-0.6b device programs, and the wire surface the new engine
actually answers (GET /tokenize is 405, /props is 200, /completion and /ping
stay 404). Eras gains the 2026-10-30 row.

frank-zealot: fork build 12118 (0.7.0-dev, 024474448) with the payload-load
evidence (202 pq2_0 tensors, 202 Hadamard-folded weights), plus the law a
rebuild pays for: cmake --install strips the rpath and installs bin/+lib/, so
the configure needs CMAKE_INSTALL_RPATH and LLAMA_BIN names …/bin/llama-server.
2026-10-30 15:27:21 -07:00
Frank acbb539b97 feat(frank-zealot): PrismML fork b10777 -> build 12118 (0.7.0-dev, 024474448)
Rebuilt the fork from origin/prism at 024474448 with the same configure the
10777 cutover used (Release, GGML_CUDA=ON, sm_86, gcc-13 host compiler, Ninja),
installed to /home/dank/GitPackages/llama-prism-0244744. The payload gate holds:
libllama carries 42 prism.hadamard strings (b10777 had 29) and libggml-base
still registers PQ2_0, so type 142 and the hadamard metadata still load.

LLAMA_BIN inherits a bin/lib install layout now, so the install needs an RPATH
($ORIGIN;$ORIGIN/../lib) — cmake's install step strips the build rpath and the
binary otherwise dies on libllama-server-impl.so.

The unit test that pinned the 10777 path now asserts the invariant its own
comment described (LLAMA_BIN names a llama-prism-* build) instead of a
directory one rebuild happens to install; the suite runs on a box with no
/home/dank, so existence is not checkable there.

Rollback: repoint LLAMA_BIN at llama-prism-b10777/llama-server (still on disk).
2026-10-30 15:25:24 -07:00
Frank 011ceeb344 fix(npu fetch): never resume into a file from another revision
A version bump re-cuts the device programs, so a staged file of a different
size is stale rather than partial. `curl -C -` against it appended the new
tail to the old bytes and produced the right BYTE COUNT with the wrong
content — the sha256 gate caught it (consts.hnpb, 2026-10-30), and the
failure reads as a corrupt program rather than a fetch fault. Resume only
when the staged file is smaller than the manifest expects.
2026-10-30 15:13:42 -07:00
Frank 33396d2daa feat(frank-dragoon): halogen-flash-server 0.16.2 -> 0.18.20, NPU lane re-pinned
The engine pin moves to the newest vendor release (0.18.20, image built
2026-10-30). The payload lock is the gate this deploy has to pass: the v2
.hgn loads only in the flash-server line, so /health plus the boot ledger
decide, and the rollback is the 0c61bf84 digest on the same env line.

0.18.20's NPU catalog is NOT the 0.16.2 one: it names 14 device programs
(u0..u13) and an 8,495,512 B consts.hnpb where 0.16.2 had 10 and 5,086,496 B,
and the entrypoint verifies size+sha256 for every staged file before it
starts. HALOGEN_NPU_MODELS names qwen3-embedding-0.6b, so the staging set is
re-pinned to revision 8fd44c9f with the new block — bumping the engine alone
would refuse the boot on the NPU lane.
2026-10-30 15:13:19 -07:00
Frank 58184008dd chore(images): refresh every registry pin to current upstream digest
Container images re-resolved against their registries today; each pin is the
manifest-list digest the tag answers now, so no container is served from a
build that upstream has already replaced.

Version-tag moves: authentik 2026.8.3 -> 2026.8.5 (server/worker/outpost and
the ldap image, which now carries the tag instead of a bare digest so the pair
can never drift apart), seerr v3.4.1 -> v3.5.1, calibre 9.15.0 -> 9.17.0,
calibre-web 0.6.27-ls402 -> ls407, plex ls329 -> ls330, tautulli
v2.18.1-ls245 -> v2.18.2-ls250.

Digest-only moves inside the same stream: postgres 16-alpine, mariadb 11,
redis 7-alpine, valkey 9-alpine, grafana, alertmanager, gluetun, searxng,
open-webui, jellyfin, romm, chromedp/headless-shell, lightpanda/browser.

Rollback is the previous digest on the same Image= line.
2026-10-30 15:00:52 -07:00
dank da5eb968f9 Merge pull request 'fix(quant): harden the campaign pipeline, then refactor its corpus tools onto one module' (#83) from fix/quant-pipeline-hardening into main 2026-10-29 15:29:33 -07:00
dank b3052e9243 Merge pull request 'fix(frank-archon): fold the pinned host pool back to 49,152; keep the 2,048 step' (#82) from feat/qwen38-w5nl64 into main 2026-10-29 15:29:29 -07:00
Frank 3e5a37a21f refactor(quant): one corpus plumbing module, and the builders out of main()
The three corpus tools now share scripts/qwen38_common.py: tokenizer load with the
venv guidance, one n_tokens (so a KLD count cannot drift from the corpus it scores),
JSONL read/write, an atomic writer, and refuse(). make-calib-corpus.py's 170-line
main() with three nested closures became classify / split_pools / fragment_text /
build_frags / pack_class / emit_calib / emit_kld / manifest; its magic numbers are
named constants. rechunk-kld-corpus.py's main became validate / cut / rechunk around
a Window record, so the round-trip proof sits in one function that can be tested
without a tokenizer. calib-push.py grew parse_args / load_prompts / push_round, and
a malformed corpus now refuses with a line number instead of raising KeyError.

Parity, measured on dankserver against the pre-refactor scripts at the same seed:
calib.jsonl and kld.jsonl carry identical records in identical order, the manifest
is identical, and the re-chunked corpus is byte-identical (md5 e824e67d...). The one
byte-level change is JSON escaping — write_jsonl emits literal UTF-8, which is what
the re-chunker already wrote; the parsed records do not move.
2026-10-29 15:26:08 -07:00
Frank 1e4fa14772 fix(quant): prove window token identity, gate the tap on progress, kill the runner's orphan race
Adversarial review of the campaign pipeline. Correctness: rechunk-kld-corpus.py wrote
each window as text and asserted only lengths, so a KLD reference could score a
different token sequence than the corpus holds — every window is now re-encoded and
the tool refuses on mismatch; make-calib-corpus.py no longer crashes on a .json that
is not a content-keyed JSONL, and its KLD cursor advanced by 2 per fragment (half the
pool unused). Silent waste: calib-push.py now aborts when the tap sealed nothing or
no prompt was accepted, instead of re-pushing 10M tokens per round; div-by-zero gone,
served model id parameterised. Races: run-qwen38-bf16.sh restore() removes the rig
container before starting production (today's orphan held the GPUs while the service
reported active), the calib tap dir is proven writable, the score ro-guard resolves
paths; convert-qwen38-w5nl64.sh refuses a missing --arm value, an existing
qwen38-convert-<arm> container, and a zero-exit convert that wrote no artifact.
stack-qwen38-official-fp8.py: bare asserts in verify() (skipped under -O) and a
non-128-lane PLE HD that only warned are hard failures. Speed: fragment token counts
computed once, KLD scored positions accumulated instead of a second full re-encode.
Tests: 576 ok / 0 fail.
2026-10-29 15:14:43 -07:00
44 changed files with 641 additions and 310 deletions

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+15 -8
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@@ -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 0.16.2, digest-pinned, root unit | `qwen38-flash-next-v2-abliterated.hgn` + n-gram + vision tower | 7770 |
| Dankclaw | `frank-zealot` | llama.cpp PrismML fork build 10777, root unit — the only loader for this payload | Ternary-Bonsai-2-9B PQ2_0 + Q8_0 mmproj + rank-1 refusal adapter | 7771 |
| 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-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 |
Payload identity, shape, eras, laws and rollback live in ONE page each:
[[frank-archon]], [[frank-dragoon]], [[frank-zealot]]. `scripts/<service>.env`
@@ -293,8 +293,8 @@ 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 build
10777 that object only reaches you on **`/v1/chat/completions`**: a greedy
`draft_n`/`draft_n_accepted` — but on frank-zealot's PrismML fork that object
only reaches you on **`/v1/chat/completions`** (measured on build 10777): 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,
@@ -439,16 +439,16 @@ 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-b10777` is the ONLY
loader (the payload carries the fork's custom PQ2_0 tensor type plus
`scripts/frank-zealot.service`; fork build `llama-prism-0244744` (build 12118)
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
`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 build 10777 is also the gate that lets it load: older forks refuse it
with `unsupported prism.hadamard.version: 2`.
— and the fork BUILD is also the gate that lets it load: anything older than
b10777 refuses it 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,
@@ -741,6 +741,13 @@ 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.
@@ -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@sha256:2e7b259eb8c37faac916946ddf48ec681ee9d3a9f724fe8521bf161973f13cf9
Image=ghcr.io/goauthentik/ldap:2026.8.5@sha256:4c75bd27918418d2d6fbbfe4581bbd5a199fe38942d24559c4483edd64a1ea87
Environment=AUTHENTIK_HOST=https://auth.franksdank.cloud
Environment=AUTHENTIK_INSECURE=false
Environment=AUTHENTIK_TOKEN=${AUTHENTIK_LDAP_OUTPOST_TOKEN}
@@ -20,7 +20,7 @@ Wants=authentik-server.service
[Container]
ContainerName=authentik-outpost
Image=ghcr.io/goauthentik/server:2026.8.3@sha256:ab9b4e8cc4ab3f8d1198d2db6aeea66bafea1963b3f2843589e0d163f97d9849
Image=ghcr.io/goauthentik/server:2026.8.5@sha256:602227a86455d6772e3d16b7d852713c4f864f40df5df894abd1285bb53979a5
Exec=worker
Network=dankclaw_default
EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env
@@ -14,7 +14,7 @@ After=network.target
[Container]
ContainerName=authentik-postgres
Image=docker.io/library/postgres:16-alpine@sha256:721873c34ceb9f8d8fc265984940dc982404c105f19ad51be9fdc5970a6080ea
Image=docker.io/library/postgres:16-alpine@sha256:0cefaabd882e42bcb2a2f3dc56d3ce4770560ba62fd7f197f1a2e008fd5731ab
Network=dankclaw_default
EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env
Environment=POSTGRES_DB=authentik
@@ -19,7 +19,7 @@ Wants=authentik-postgres.service
[Container]
ContainerName=authentik-server
Image=ghcr.io/goauthentik/server:2026.8.3@sha256:ab9b4e8cc4ab3f8d1198d2db6aeea66bafea1963b3f2843589e0d163f97d9849
Image=ghcr.io/goauthentik/server:2026.8.5@sha256:602227a86455d6772e3d16b7d852713c4f864f40df5df894abd1285bb53979a5
Exec=server
Network=dankclaw_default
EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env
@@ -16,7 +16,7 @@ Wants=authentik-server.service
[Container]
ContainerName=authentik-worker
Image=ghcr.io/goauthentik/server:2026.8.3@sha256:ab9b4e8cc4ab3f8d1198d2db6aeea66bafea1963b3f2843589e0d163f97d9849
Image=ghcr.io/goauthentik/server:2026.8.5@sha256:602227a86455d6772e3d16b7d852713c4f864f40df5df894abd1285bb53979a5
Exec=worker
Network=dankclaw_default
EnvironmentFile=/home/dank/serverAppConfigs/dankclaw/.env
@@ -15,7 +15,7 @@ After=network.target
[Container]
ContainerName=gitea-postgres
Network=gitea.network
Image=docker.io/library/postgres:16-alpine@sha256:721873c34ceb9f8d8fc265984940dc982404c105f19ad51be9fdc5970a6080ea
Image=docker.io/library/postgres:16-alpine@sha256:0cefaabd882e42bcb2a2f3dc56d3ce4770560ba62fd7f197f1a2e008fd5731ab
EnvironmentFile=/home/dank/Containers/gitea/env
Environment=POSTGRES_USER=gitea
Environment=POSTGRES_PASSWORD=${GITEA_DB_PASSWORD}
@@ -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@sha256:2d349b544a1ea6b5b5fd7c0fe99215ff662339c57407ee2e8c0a11af93516b04
Image=docker.io/chromedp/headless-shell@sha256:7bee201478b2f6266aae01243740ee85c16281e32f42d3aed9fdf04f4eace7a1
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
@@ -23,7 +23,7 @@ After=gluetun.service network.target
[Container]
ContainerName=marreta_browser
Network=gluetun.container
Image=docker.io/lightpanda/browser:nightly@sha256:979c36ed869f1016b8dcf22939a0633c262f2c30e892a03a9f720eba2ff1931e
Image=docker.io/lightpanda/browser:nightly@sha256:e72730e364d1fbf352c1149f29ffa4b278f3b1a55ff0dec3262298ebe624ec7a
[Service]
TimeoutStartSec=300
@@ -33,7 +33,7 @@ Wants=network-online.target
[Container]
ContainerName=alertmanager
Image=docker.io/prom/alertmanager:latest@sha256:e9733bafb1bdef9b00e25a21f8f99dc26a22224bf16641ad754d1649f4c3357a
Image=docker.io/prom/alertmanager:latest@sha256:39d8bb3966c694a124428a3a88fbcffd40bd069129ecd47c059f8a3f17c55f3b
Network=dankclaw_default
User=0:0
Exec=--config.file=/etc/alertmanager/alertmanager.yml --storage.path=/alertmanager
@@ -34,7 +34,7 @@ Wants=network-online.target prometheus.service
[Container]
ContainerName=grafana
Image=docker.io/grafana/grafana:latest@sha256:dbbc38ea21103cefb50396340cd88afec779c7e070b0a7bf5a75b4ce46651d3f
Image=docker.io/grafana/grafana:latest@sha256:488984b716c0862639f91a698adbe2862677a5a07bad42da5f03f3030883b205
Network=dankclaw_default
User=0:0
PublishPort=127.0.0.1:3002:3000
@@ -27,7 +27,7 @@ After=network.target
[Container]
ContainerName=open-webui
Network=open-webui.network
Image=ghcr.io/open-webui/open-webui:main@sha256:4860ba005ae8f19f08d1e12b0868855b7b339ea0dad9927f196820fc0de04575
Image=ghcr.io/open-webui/open-webui:main@sha256:0b399a8ba34558e181d316750455f2a95376a38cd60a61b9c942e138898944bd
PublishPort=3005:8080
Environment=OPENAI_API_BASE_URL=http://192.168.0.143:7770
Environment=ANONYMIZED_TELEMETRY=False
+1 -1
View File
@@ -16,7 +16,7 @@ After=searxng-network.service network.target
[Container]
ContainerName=gluetun
Network=searxng.network
Image=docker.io/qmcgaw/gluetun:latest@sha256:c2ee4191762fca6b6a3c3359a731198a95d9c9af4db32d466e223bf3a84e779b
Image=docker.io/qmcgaw/gluetun:latest@sha256:4af0c804003481e100180e1f8d4d5e9c48163fedc0f88d061881b615aef9d183
AddCapability=NET_ADMIN
AddDevice=/dev/net/tun:/dev/net/tun
Environment=VPN_SERVICE_PROVIDER=${VPN_SERVICE_PROVIDER}
@@ -16,7 +16,7 @@ After=searxng-network.service network.target
ContainerName=searxng-valkey
Network=searxng.network
NetworkAlias=valkey
Image=docker.io/valkey/valkey:9-alpine@sha256:48332870af354a799964c0012ae1194a0bf2bf894eb508f945810596dc2d8d11
Image=docker.io/valkey/valkey:9-alpine@sha256:bf09d58e96d6b4524a15396b65b242bbe18beebbcc15a04d8ee75ddac62fae0b
Volume=/opt/searxng/valkey:/data
[Service]
+1 -1
View File
@@ -16,7 +16,7 @@ After=gluetun.service searxng-valkey.service network.target
[Container]
ContainerName=searxng
Network=gluetun.container
Image=ghcr.io/searxng/searxng:latest@sha256:5ed0323b5f5f8701264ef65e239a2bd83cb57098f2b971fa30bf79c06eeae271
Image=ghcr.io/searxng/searxng:latest@sha256:f4aa660c54d062dedb268be84e821ea24e39f48c7a496af8dd02cc9eedb93847
Environment=SEARXNG_SECRET=${SEARXNG_SECRET}
Environment=SEARXNG_BASE_URL=${SEARXNG_BASE_URL}
Volume=/opt/searxng/config:/etc/searxng
+1 -1
View File
@@ -29,7 +29,7 @@ Wants=network-online.target
[Container]
ContainerName=seerr
Image=ghcr.io/seerr-team/seerr:v3.4.1@sha256:f4768de5f616248d723e05891f3345a1402123775d03bf0890dbfedc0831bda1
Image=ghcr.io/seerr-team/seerr:v3.5.1@sha256:d8fab675b55ad293ded98fd71efcfd46054cbad9746534ae1cc4794a88c0b3be
Network=dankclaw_default
PublishPort=127.0.0.1:5055:5055
Volume=/home/dank/Containers/seerr/data:/app/config
@@ -43,7 +43,7 @@ After=network.target
[Container]
ContainerName=calibre-server
Image=lscr.io/linuxserver/calibre:9.15.0@sha256:59e4b0e036e62f228f8bcfae1ade42f47047719885fe454ddbad38e4597b987b
Image=lscr.io/linuxserver/calibre:9.17.0@sha256:b198fc03a6abc6be7e251a9958e50e74634b00e447c7b25e92c191c8077ba378
Network=pasta
EnvironmentFile=/home/dank/Containers/calibre-server/env
Environment=PUID=1000
@@ -16,7 +16,7 @@ After=network.target
[Container]
ContainerName=calibre-web
Image=lscr.io/linuxserver/calibre-web:0.6.27-ls402@sha256:802729966faed5e32d671cd4f92ba6196e9e754a6c0f740ce1ee9acd86b10e55
Image=lscr.io/linuxserver/calibre-web:0.6.27-ls407@sha256:470b4ed9a7d6ea1475fef17dbcf957cb60880910296d226bd0dca652c05f68ca
Network=pasta
Environment=DOCKER_MODS=linuxserver/mods:universal-calibre
Environment=LANG=en_US.UTF-8
@@ -16,7 +16,7 @@ After=network.target
[Container]
ContainerName=jellyfin
Image=ghcr.io/jellyfin/jellyfin:latest@sha256:c3efa69a22f2691fc88d6bb035e87a8560e395a6047f062fb381c61c3185e8f5
Image=ghcr.io/jellyfin/jellyfin:latest@sha256:fea863d0cd9ec445985d9c75fc6ed64e38a1d2766cf0c250a33d553f4fc1b771
Network=dankserver_appnet
Environment=DEBIAN_FRONTEND=noninteractive
Environment=DOTNET_SYSTEM_IO_DISABLEFILELOCKING=true
+1 -1
View File
@@ -4,7 +4,7 @@ After=network-online.target
Wants=network-online.target
[Container]
Image=lscr.io/linuxserver/plex:1.43.5.11029-6bf8af3f0-ls329@sha256:8f655bad7dcbc5398a78f70a5af12600b4ed3424f901566ed1eaa6710e9e2334
Image=lscr.io/linuxserver/plex:1.43.5.11079-b3b13e506-ls330@sha256:01a53d9c7adcbb3701fbb0a4230c0a37c85453759b6b05a67356c3c7a09de08d
ContainerName=plex
Network=dankserver_appnet:alias=plex
Environment=PUID=0
@@ -14,7 +14,7 @@ After=network.target
[Container]
ContainerName=romm-mariadb
Image=docker.io/library/mariadb:11@sha256:f16d7a344413e519dff518f27bdb221388f84b0d274c97c4fb5f2cb0dc1b34fa
Image=docker.io/library/mariadb:11@sha256:c4124d1afa875e47f2892edf26b482fa54f796e2f342d3717a04ca091a22a9bd
Network=dankserver_appnet:alias=mariadb
EnvironmentFile=/home/dank/Containers/romm/env
Environment=MARIADB_DATABASE=romm
+1 -1
View File
@@ -12,7 +12,7 @@ After=network.target
[Container]
ContainerName=romm-redis
Image=docker.io/library/redis:7-alpine@sha256:858f009f9709ce576febc734aa78b8f6d624b82571f9ddb6bda4377c833b3499
Image=docker.io/library/redis:7-alpine@sha256:8da19c7399dca900c6822a1cf30f9d2285585e2c4b457ff4095b0f4500054d3f
Network=dankserver_appnet:alias=redis
Volume=/home/dank/Containers/romm/redis:/data
HealthCmd=redis-cli ping
+1 -1
View File
@@ -18,7 +18,7 @@ After=romm-mariadb.service romm-redis.service network.target
[Container]
ContainerName=romm
Image=ghcr.io/rommapp/romm:latest@sha256:03295f95a6290e752641f9553ac4198b0e5b71b879d57f7b2371b98f608feb54
Image=ghcr.io/rommapp/romm:latest@sha256:8677fb7b81b1d3db20b849e989a1dadc2a11159e51eb34a2acdcb01102274edf
Network=dankserver_appnet
EnvironmentFile=/home/dank/Containers/romm/env
Environment=DB_HOST=mariadb
@@ -4,7 +4,7 @@ After=network-online.target
Wants=network-online.target
[Container]
Image=lscr.io/linuxserver/tautulli:v2.18.1-ls245@sha256:c66d3afa8f7a701a48dd1b1f57b22eca0483d895d670fe11ecff783f6a9bbd73
Image=lscr.io/linuxserver/tautulli:v2.18.2-ls250@sha256:529c7eabcc40554c1dc48f33f1f3cc3b1438462d73e0ec2dac8ac0b66aeeb8d4
ContainerName=tautulli
Network=dankserver_appnet:alias=tautulli
Environment=PUID=0
+79 -18
View File
@@ -22,6 +22,9 @@ 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 a FAILURE, not a retry: the engine
answering 200 while the tap directory is wrong, full or read-only is
how a corpus gets pushed four times for nothing.
Usage: calib-push.py [--port 7770] [--parallel 64] [--container arbench]
[--corpus /home/dank/corpora/out/calib.jsonl] [--max-rounds 4]
@@ -29,11 +32,18 @@ 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"
@@ -49,9 +59,9 @@ def tap_done(container):
return DONE_MARK in (out.stdout + out.stderr)
def push_one(url, prompt):
def push_one(url, prompt, model):
body = json.dumps({
"model": "frank-archon",
"model": model,
"prompt": prompt,
"max_tokens": 1,
"temperature": 0,
@@ -68,38 +78,89 @@ def push_one(url, prompt):
return False
def main():
def push_round(url, prompts, model, parallel):
"""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 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("--corpus", default="/home/dank/corpora/out/calib.jsonl")
ap.add_argument("--max-rounds", type=int, default=4)
a = ap.parse_args()
url = f"http://127.0.0.1:{a.port}/v1/completions"
return 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 = []
with open(a.corpus) as f:
for line in f:
line = line.strip()
if line:
prompts.append(json.loads(line)["prompt"])
print(f"corpus: {len(prompts)} prompts", flush=True)
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)
chars = sum(len(p) for p in prompts)
print(f"corpus: {len(prompts)} prompts, ~{chars // 4} tokens (chars/4)",
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 = 0
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
ok = push_round(url, prompts, a.model, a.parallel)
dt = max(time.time() - t0, 1e-9)
print(f"round {rnd}: {ok}/{len(prompts)} ok in {dt:.0f}s "
f"({sum(len(p) for p in prompts)/4/dt:.0f} chars/s est)",
flush=True)
f"({chars / 4 / dt:.0f} tokens/s est)", flush=True)
if ok == 0:
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)
if after <= before:
print(f"FAIL: the tap at {a.tap_dir} sealed nothing this round "
f"({before} B before, {after} B after) — the engine is serving "
"without recording (wrong dir, full disk, read-only mount)", flush=True)
sys.exit(1)
else:
print("max rounds exhausted, tap not done", flush=True)
sys.exit(1)
+1 -1
View File
@@ -21,7 +21,7 @@
# deployed knob has since dropped to 262144.
set -euo pipefail
IMG=ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a
IMG=ghcr.io/peonist-ai/halogen-flash-server@sha256:e35133b206da3094cc4d70c78800b26235bd9124b9aeb0e029d4a7c153b9cff0
CUR=/home/dank/models/halogen-flashnext-v2
NEW=/home/dank/models/halogen-v2-abliterated
CUR_CK=qwen38-flash-next-v2-swift15-abliterated.hgn
+12 -2
View File
@@ -71,10 +71,12 @@ PLAN_ONLY=0
KEEP_RECIPE=0
while [ "$#" -gt 0 ]; do
case "$1" in
--arm) ARMS+=("$2"); shift 2 ;;
--arm) [ "$#" -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) TARGET_COUNT="$2"; shift 2 ;;
--target-count) [ "$#" -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: $1" >&2; exit 2 ;;
esac
@@ -124,6 +126,13 @@ fi
for a in "${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-$a' and re-run" >&2
exit 2; }
done
# --- the protected plane, spliced into a per-run copy of the template --------------------------
@@ -203,6 +212,7 @@ for arm in "${ARMS[@]}"; do
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.
+10 -4
View File
@@ -1362,11 +1362,17 @@ 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).
systemctl --user start authentik-postgres.service
# RESTART, not start: `start` on an already-active unit is a no-op, so an
# 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 start authentik-server.service
systemctl --user restart authentik-server.service
wait_container_healthy authentik-server 300 || return 1
systemctl --user start authentik-worker.service
systemctl --user restart authentik-worker.service
}
deploy_authentik_outpost() {
@@ -1482,7 +1488,7 @@ 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="${LLM_DRAGOON_IMAGE:-ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a}"
LLM_DRAGOON_IMAGE="${LLM_DRAGOON_IMAGE:-ghcr.io/peonist-ai/halogen-flash-server@sha256:e35133b206da3094cc4d70c78800b26235bd9124b9aeb0e029d4a7c153b9cff0}"
# 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}"
+33 -16
View File
@@ -8,8 +8,10 @@
# (/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 0.16.2
# image on 2026-10-19), so the files land in the layout the entrypoint
# The manifest below IS that catalog block (dumped from the pinned 0.18.20
# image on 2026-10-30; the 0.16.2 block this replaced named different device
# 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
@@ -57,21 +59,25 @@ manifest() {
case "$1" in
qwen3-embedding-0.6b)
NPU_REPO="peonist-ai/halogen-npu-qwen3-embedding-0.6b"
NPU_REV="4960fd9d4423dd15373ad21c83db48dbdb3b2798"
NPU_REV="8fd44c9f18861618a509bea75c51ff8a37e3bd5d"
FILES=(
"devices/NOTICE.md 3248 0f267b3d2523ddf14997ee58660a492a9eaf10ccf6b08bf19dfdc85b9a478b91"
"devices/consts.hnpb 5086496 ae430e41545a0b1012938cda373b0c450364d3be631111cca3a8c43679f93336"
"devices/devices.hnpm 24047 4e9bca9d95d084fb89ce5b99f579a00666c8ca1efae2613c53e3a4878cc9f174"
"devices/u0.elf 4931968 b38f165886cb037b7d3951d9cb878473eaba58a432acd45416ff85fd88aa4e46"
"devices/u1.elf 5456000 b1811feee851b8af833b37721da92099d89772110815bbbe2c3fa1c276f0ff42"
"devices/u2.elf 6505552 406ea9a95b470628a7382e376f4a72cdf4d7aa4c59b4ddf0a4bdd139d63d6ff2"
"devices/u3.elf 6817216 bc205d51b523d770151a0c61968f7c70bf624412827580bb6fe0aaf4650dc2ee"
"devices/u4.elf 7444032 a5a91338a2603acdcd5c11df532033fda2d3f5479ea44ae87f98fafbdff9a62d"
"devices/u5.elf 7432416 6c2bf41835569e0eba25ded7c05c7264ae69c6700bdeb4791057d884f2a4c126"
"devices/u6.elf 4941232 919d0038ca088eafddf195f3466ff38db27d3635be1cffa5d4d4b5140902a68e"
"devices/u7.elf 5488304 d904cf8afae9428dd167960549e18cce5441745f18c62f8c50975dffc077d3c2"
"devices/u8.elf 4941232 db3aef69b17825854ee0dd2df475125a3f5c872f95c686793d6af1ee83596fa7"
"devices/u9.elf 5488304 d182727e551084db8fb9600441d8aa373c7f09a3d267ae0a5e921ef92326db1c"
"devices/consts.hnpb 8495512 5af7c1f2f24d45a9054872bba882461cf7f6ffda832e785b700643d6467ad88b"
"devices/devices.hnpm 35465 85d870f6b900de1829659955f0dc701d57984580f5e5ec251add5d6969f03e3d"
"devices/u0.elf 2975008 f74df12eb8c79e4e90cbedcc1dd8f142219772d400e3a142fde8a95378b105eb"
"devices/u1.elf 3266848 ac5a3f89f934951b315b62ab53e1d0a74dbe6396134192641c405d08da332754"
"devices/u2.elf 4015328 5e4f0d3342f262816289866d7e8c966f56a9f938c2e12e7341718cc7312aa480"
"devices/u3.elf 4326976 94cf5d269fa286d91c26bf4654cedf101c047d23c4495b74c9c129cdc33b210f"
"devices/u4.elf 4953792 cbd2796050d4c675f5cb3da117111087d510173e26f262f1b36aab66dd49dc91"
"devices/u5.elf 4940112 7bf6a4470546bb888da02af395c07d92a24fb6d43aef27eb2151b3a9eda19e4d"
"devices/u6.elf 6174544 10b9d50b635993e1f9c23775c0b94901d922c1e433cd10910e9f97174235f5ac"
"devices/u7.elf 2983776 e0b06063b7379d05c85b3f435b819d96fda1223d8025d6d15958854b5711ace9"
"devices/u8.elf 3298656 3bad204f782a68b97e27c1172530b13d7fbb0b495fa95f9504530a1048560644"
"devices/u9.elf 2983776 875e313280358ce116e2a51a29a2c42794b5a9fadb3d48db702c90d18d838c2c"
"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"
) ;;
@@ -99,7 +105,18 @@ 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; }
curl -fL --retry 5 -C - -o "$path" "$url"
# Resume ONLY into a genuinely partial file. A staged file of a
# 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; }
+5 -2
View File
@@ -10,8 +10,11 @@
# 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 — 0.16.2 is the version the model card names as its quickstart pin).
FRANK_DRAGOON_IMAGE=ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a
# qualified). 0.18.20 since 2026-10-30 (was 0.16.2, the model card's quickstart
# pin) — the vendor has moved two minor versions and the payload lock is what
# 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.
+5 -4
View File
@@ -1,12 +1,12 @@
# frank-zealot — llama.cpp (PrismML fork build 10777, CUDA) on the RTX 3090,
# :7771. Payload: Ternary-Bonsai-2-9B PQ2_0 with the MTP head in the file, plus
# frank-zealot — llama.cpp (PrismML fork build 12118 = 0.7.0-dev, commit
# 024474448, CUDA) on the RTX 3090, :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-b10777/llama-server
LLAMA_BIN=/home/dank/GitPackages/llama-prism-0244744/bin/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.
@@ -64,7 +64,8 @@ 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 10777.
# beside MTP needs fork build >= b10776; LLAMA_BIN is 12118 (b10777 is kept on
# 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
+175 -112
View File
@@ -34,14 +34,25 @@ import json
import os
import random
import re
import sys
from jinja2 import Environment, FileSystemLoader
from tokenizers import Tokenizer
_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
CODE_EXT = (".sh", ".py", ".jinja", ".recipe", ".env", ".example",
".yaml", ".yml", ".bats", ".service", ".container", ".toml")
JSONL_EXTS = (".jsonl", ".json")
DOC_DIR = "serverAppConfigs-docs"
FRAGMENT_TOKENS = 2400 # what one fragment may contribute
CLASS_MIX = {"code": .45, "prose": .30, "tools": .25}
HF_CAP = {"code": 40000, "prose": 60000, "tools": 0}
POOL_CYCLES = 40 # how many times a class pool may repeat before giving up
KLD_GUARD = 5000 # rendered conversations tried before declaring the pool short
FLEET_CMDS = [
"systemctl status frank-archon --no-pager",
@@ -142,7 +153,7 @@ def load_parquet_texts(path: str, kind: str, rng: random.Random,
return out[:cap]
def main() -> None:
def parse_args() -> argparse.Namespace:
ap = argparse.ArgumentParser(description=__doc__)
ap.add_argument("--repo", required=True)
ap.add_argument("--tokenizer-json", required=True)
@@ -156,22 +167,26 @@ def main() -> None:
ap.add_argument("--hf-code-parquet", default="")
ap.add_argument("--hf-prose-parquet", default="")
ap.add_argument("--seed", type=int, default=20261006)
a = ap.parse_args()
return ap.parse_args()
rng = random.Random(a.seed)
tokenizer = Tokenizer.from_file(a.tokenizer_json)
env = Environment(loader=FileSystemLoader(os.path.dirname(a.template)),
def load_template(template: str) -> tuple[Environment, str]:
"""The chat template as the engine will render it, plus its short name."""
env = Environment(loader=FileSystemLoader(os.path.dirname(template)),
trim_blocks=True, lstrip_blocks=True)
env.filters["tojson"] = lambda v: json.dumps(v, ensure_ascii=False)
env.filters["raise_exception"] = lambda m: (_ for _ in ()).throw(
ValueError(m))
tname = os.path.basename(a.template)
return env, os.path.basename(template)
def classify(repo: str) -> dict[str, list[str]]:
"""Walk the checkout into the three source classes the mix draws from."""
code, prose, jsonl = [], [], []
for root, dirs, files in os.walk(a.repo):
for root, dirs, files in os.walk(repo):
dirs[:] = [d for d in dirs if not d.startswith(".")]
for f in sorted(files):
p = os.path.relpath(os.path.join(root, f), a.repo)
p = os.path.relpath(os.path.join(root, f), repo)
if DOC_DIR in p and f.endswith(".md"):
prose.append(p)
elif p.startswith(DOC_DIR):
@@ -180,137 +195,185 @@ def main() -> None:
code.append(p)
elif f.endswith(JSONL_EXTS) and f != "package-lock.json":
jsonl.append(p)
# file-level split: bucket 0 -> KLD pool, 1..4 -> calibration pool
pools: dict[str, tuple[list, list]] = {}
for cls, lst in (("code", code), ("prose", prose), ("tools", jsonl)):
pools[cls] = ([p for p in lst if fnv(p) % 5 == 0],
[p for p in lst if fnv(p) % 5 != 0])
return {"code": code, "prose": prose, "tools": jsonl}
def text_of(p: str) -> str:
path = os.path.join(a.repo, p)
raw = open(path, encoding="utf-8", errors="replace").read()
if p.endswith(JSONL_EXTS):
lines = [json.loads(l)["content"] for l in raw.splitlines()
if l.strip() and "content" in l]
raw = "\n".join(lines)
toks = tokenizer.encode(raw, add_special_tokens=False).ids
return tokenizer.decode(toks[:2400], skip_special_tokens=True)
def split_pools(classes: dict[str, list[str]]) -> dict[str, tuple[list, list]]:
"""File-level split: bucket 0 -> KLD pool, everything else -> calibration."""
return {cls: ([p for p in lst if fnv(p) % 5 == 0],
[p for p in lst if fnv(p) % 5 != 0])
for cls, lst in classes.items()}
def jsonl_content(raw: str) -> str:
"""The content fields of a content-keyed JSONL, or "" for anything else.
A .json in this repo is not necessarily a content-keyed JSONL: the substring
test passes on any line that merely mentions "content", and a list-shaped
document raises TypeError — both used to crash the whole build. Skip what
does not fit instead.
"""
lines = []
for line in raw.splitlines():
if not line.strip() or "content" not in line:
continue
try:
rec = json.loads(line)
except json.JSONDecodeError:
continue
if isinstance(rec, dict) and isinstance(rec.get("content"), str):
lines.append(rec["content"])
return "\n".join(lines)
def fragment_text(repo: str, rel: str, tok) -> str:
"""One file as a fragment: its first FRAGMENT_TOKENS tokens, decoded."""
raw = open(os.path.join(repo, rel), encoding="utf-8",
errors="replace").read()
if rel.endswith(JSONL_EXTS):
raw = jsonl_content(raw)
ids = tok.encode(raw, add_special_tokens=False).ids
return tok.decode(ids[:FRAGMENT_TOKENS], skip_special_tokens=True)
def build_frags(a: argparse.Namespace, tok,
rng: random.Random) -> dict[str, dict[str, list[str]]]:
"""Both fragment pools per class, seeded so the same seed rebuilds the corpus."""
pools = split_pools(classify(a.repo))
cmds = harvest_cmds(a.repo, rng)
# fragment pools per class, corpus-split first
frags: dict[str, dict[str, list[str]]] = {}
for cls in pools:
kld_files, cal_files = pools[cls]
fr = {}
src = {"kld": kld_files, "cal": cal_files}
for cls, (kld_files, cal_files) in pools.items():
if cls == "tools":
fr["kld"] = [tool_call(rng, cmds) for _ in range(600)]
fr["cal"] = [tool_call(rng, cmds) for _ in range(40000)]
frags[cls] = {"kld": [tool_call(rng, cmds) for _ in range(600)],
"cal": [tool_call(rng, cmds) for _ in range(40000)]}
else:
fr["kld"] = [text_of(p) for p in src["kld"]]
fr["cal"] = [text_of(p) for p in src["cal"]]
frags[cls] = fr
frags[cls] = {"kld": [fragment_text(a.repo, p, tok) for p in kld_files],
"cal": [fragment_text(a.repo, p, tok) for p in cal_files]}
# per-class fragment caps: prose rows are short (~66 tok) so need many;
# codeparrot files are long (~2.6k tok) so a small cap suffices
hfcap = {"code": 40000, "prose": 60000, "tools": 0}
for cls, spec in (("code", a.hf_code_parquet),
("prose", a.hf_prose_parquet)):
for path in [p for p in spec.split(",") if p]:
frags[cls]["cal"].extend(
load_parquet_texts(path, cls, rng, cap=hfcap[cls]))
load_parquet_texts(path, cls, rng, cap=HF_CAP[cls]))
for cls in frags:
rng.shuffle(frags[cls]["cal"])
return frags
def toks(s: str) -> int:
return len(tokenizer.encode(s, add_special_tokens=False).ids)
def emit_calib() -> tuple[int, list[dict]]:
targets = {"code": .45, "prose": .30, "tools": .25}
rows: list[dict] = []
for cls, frac in targets.items():
want = int(a.calib_tokens * frac)
pool = frags[cls]["cal"]
def pack_class(cls: str, pool: list[str], want: int, tok,
chunk_tokens: int) -> list[dict]:
"""Greedily pack `pool` into chunk_tokens-sized calibration prompts."""
if not pool:
return []
rows: list[dict] = []
# Count every fragment once: the loop cycles the pool up to POOL_CYCLES
# times, and re-tokenizing a 2.4k-token fragment on each pass dominated the
# build's wall time.
counts = [qc.n_tokens(tok, f) for f in pool]
got = 0
i = 0
buf: list[str] = []
nbuf = 0
while got < want:
j = i % len(pool)
frag = pool[j]
i += 1
n = counts[j]
if nbuf + n > chunk_tokens and buf:
rows.append({"prompt": "\n".join(buf), "cls": cls})
got += nbuf
buf, nbuf = [], 0
if got >= want:
break
buf.append(frag)
nbuf += n
if i > len(pool) * POOL_CYCLES:
break # pool exhausted with repeats; stop
if buf and got < want:
rows.append({"prompt": "\n".join(buf), "cls": cls})
got += nbuf
print(f"calib {cls}: {got} tokens, {i} fragments")
return rows
def emit_calib(a: argparse.Namespace, frags, tok,
rng: random.Random) -> tuple[int, list[dict]]:
"""calib.jsonl rows: the class mix, shuffled, prompts only."""
rows: list[dict] = []
for cls, frac in CLASS_MIX.items():
rows.extend(pack_class(cls, frags[cls]["cal"], int(a.calib_tokens * frac),
tok, a.chunk_tokens))
rng.shuffle(rows)
return len(rows), [{"prompt": r["prompt"]} for r in rows]
def emit_kld(a: argparse.Namespace, frags, tok, rng: random.Random,
env: Environment, tname: str) -> tuple[int, list[dict], int]:
"""kld.jsonl rows: multi-turn conversations, each with a scored tail."""
template = env.get_template(tname)
rows: list[dict] = []
total = scored_total = 0
classes = ["code", "prose", "tools"]
cursor = {c: 0 for c in classes}
guard = 0
while total < a.kld_tokens and guard < KLD_GUARD:
guard += 1
msgs, srcs = [], []
for t in range(rng.choice([2, 3, 4])):
cls = classes[(len(rows) + t) % 3]
pool = frags[cls]["kld"]
if not pool:
continue
got, i, buf, nbuf = 0, 0, [], 0
while got < want:
frag = pool[i % len(pool)]
i += 1
n = toks(frag)
if nbuf + n > a.chunk_tokens and buf:
rows.append({"prompt": "\n".join(buf), "cls": cls})
got += nbuf
buf, nbuf = [], 0
if got >= want:
break
buf.append(frag)
nbuf += n
if i > len(pool) * 40:
break # pool exhausted with repeats; stop
if buf and got < want:
rows.append({"prompt": "\n".join(buf), "cls": cls})
got += nbuf
print(f"calib {cls}: {got} tokens, {i} fragments")
rng.shuffle(rows)
return len(rows), [{k: v for k, v in r.items() if k == "prompt"}
for r in rows]
frag = pool[cursor[cls] % len(pool)]
cursor[cls] += 1
msgs.append({"role": "user",
"content": "Summarize and explain this "
f"engineering material:\n{frag}"})
msgs.append({"role": "assistant",
"content": frag[:4000]})
srcs.append(cls)
rendered = template.render(messages=msgs, add_generation_prompt=False)
n = qc.n_tokens(tok, rendered)
if n < a.kld_min_prompt:
continue
rows.append({"prompt": rendered,
"score_from": n - a.score_tail,
"source": "+".join(sorted(set(srcs)))})
total += n
scored_total += a.score_tail
return len(rows), rows, scored_total
def emit_kld() -> tuple[int, list[dict]]:
rows, total = [], 0
classes = ["code", "prose", "tools"]
i = {c: 0 for c in classes}
guard = 0
while total < a.kld_tokens and guard < 5000:
guard += 1
msgs, srcs = [], []
for t in range(rng.choice([2, 3, 4])):
cls = classes[(len(rows) + t) % 3]
pool = frags[cls]["kld"]
if not pool:
continue
frag = pool[i[cls] % len(pool)]
i[cls] += 2
msgs.append({"role": "user",
"content": "Summarize and explain this "
f"engineering material:\n{frag}"})
msgs.append({"role": "assistant",
"content": frag[:4000]})
srcs.append(cls)
rendered = env.get_template(tname).render(
messages=msgs, add_generation_prompt=False)
n = toks(rendered)
if n < a.kld_min_prompt:
continue
rows.append({"prompt": rendered,
"score_from": n - a.score_tail,
"source": "+".join(sorted(set(srcs)))})
total += n
return len(rows), rows
os.makedirs(a.out_dir, exist_ok=True)
nc, rows = emit_calib()
with open(os.path.join(a.out_dir, "calib.jsonl"), "w") as f:
for r in rows:
f.write(json.dumps(r) + "\n")
nk, krows = emit_kld()
with open(os.path.join(a.out_dir, "kld.jsonl"), "w") as f:
for r in krows:
f.write(json.dumps(r) + "\n")
scored = sum(len(tokenizer.encode(r["prompt"], add_special_tokens=False).ids)
- r["score_from"] for r in krows)
manifest = {
def manifest(a: argparse.Namespace, tname: str, nc: int, nk: int,
scored: int) -> dict:
return {
"seed": a.seed, "template": tname,
"tokenizer": os.path.basename(a.tokenizer_json),
"calib_prompts": nc, "kld_prompts": nk,
"kld_scored_positions": scored,
"kld_score_tail": a.score_tail,
"disjoint_file_pools": "local KLD material only; HF code feeds calib",
"calib_mix": {"code": .45, "prose": .30, "tools": .25},
"calib_mix": dict(CLASS_MIX),
"hf_code": a.hf_code_parquet, "hf_prose": a.hf_prose_parquet,
}
with open(os.path.join(a.out_dir, "manifest.json"), "w") as f:
json.dump(manifest, f, indent=1)
print(json.dumps(manifest, indent=1))
def main() -> None:
a = parse_args()
rng = random.Random(a.seed)
tok = qc.load_tokenizer(a.tokenizer_json)
env, tname = load_template(a.template)
frags = build_frags(a, tok, rng)
os.makedirs(a.out_dir, exist_ok=True)
nc, calib_rows = emit_calib(a, frags, tok, rng)
qc.write_jsonl(os.path.join(a.out_dir, "calib.jsonl"), calib_rows)
nk, kld_rows, scored = emit_kld(a, frags, tok, rng, env, tname)
qc.write_jsonl(os.path.join(a.out_dir, "kld.jsonl"), kld_rows)
man = manifest(a, tname, nc, nk, scored)
qc.write_json(os.path.join(a.out_dir, "manifest.json"), man)
print(json.dumps(man, indent=1))
if __name__ == "__main__":
+94
View File
@@ -0,0 +1,94 @@
#!/usr/bin/env python3
"""Shared plumbing for the qwen38 campaign corpus tools.
The three tools move the same two shapes — a JSONL of prompt records and a
one-artifact JSON manifest — and they all tokenize with the SAME tokenizer. That
last part is not a detail: a KLD reference is only meaningful against the exact
token sequence the corpus recorded, so `n_tokens` exists once, here, and every
tool counts the same way. A window that decode/encode does not round-trip is a
refusal, never a warning.
Loaded as a sibling module. Each tool puts its own directory on `sys.path`
first, so `python3 scripts/<tool>.py` and the driver's container mount
(`runpy.run_path('/work/<tool>.py')`, `-v scripts:/work:ro`) both resolve it —
run the tools by path, not piped through stdin.
"""
import contextlib
import json
import os
import sys
import tempfile
def refuse(msg: str) -> None:
"""Exit 2 with a REFUSED line — the code argparse uses for unusable input."""
print(f"REFUSED: {msg}", file=sys.stderr)
sys.exit(2)
def load_tokenizer(path: str):
try:
from tokenizers import Tokenizer
except ImportError as exc: # the corpus tools carry their own venv
refuse(f"tokenizers is not importable by {sys.executable} — run the "
f"corpus venv's python (on dankserver: "
f"/home/dank/venvs/radcorpus/bin/python) or set "
f"FRANK_QWEN38_TOKENIZER: {exc}")
if not os.path.isfile(path):
refuse(f"no tokenizer at {path}")
return Tokenizer.from_file(path)
def n_tokens(tok, text: str) -> int:
"""The corpus's own count: no special tokens added, prompt side only."""
return len(tok.encode(text, add_special_tokens=False).ids)
def iter_jsonl(path: str):
"""Yield `(lineno, record)` for every non-blank line; refuse on a bad line.
Field validation stays with the caller: the three corpora carry different
fields (`prompt` alone, `prompt`+`cls`, `prompt`+`score_from`+`source`), and
a record missing the one the tool needs is that tool's refusal to make.
"""
with open(path, encoding="utf-8", errors="replace") as fh:
for lineno, line in enumerate(fh, 1):
if not line.strip():
continue
try:
rec = json.loads(line)
except json.JSONDecodeError as exc:
refuse(f"{path}:{lineno} is not JSON: {exc}")
yield lineno, rec
def write_jsonl(path: str, rows) -> None:
with open(path, "w", encoding="utf-8") as fh:
for row in rows:
fh.write(json.dumps(row, ensure_ascii=False) + "\n")
@contextlib.contextmanager
def atomic_writer(path: str):
"""Write `path` through a temporary sibling and rename on success.
An interrupted run then leaves no half corpus behind, and the temporary name
keeps the one-artifact-one-name law the driver applies to a score report.
"""
d = os.path.dirname(os.path.abspath(path)) or "."
fd, tmp = tempfile.mkstemp(dir=d, prefix="." + os.path.basename(path) + "-")
try:
with os.fdopen(fd, "w", encoding="utf-8") as fh:
yield fh
os.replace(tmp, path)
except BaseException:
if os.path.exists(tmp):
os.unlink(tmp)
raise
os.chmod(path, 0o644)
def write_json(path: str, obj) -> None:
with atomic_writer(path) as fh:
json.dump(obj, fh, indent=1)
fh.write("\n")
+94 -80
View File
@@ -38,12 +38,19 @@ one-artifact-one-name law run-qwen38-bf16.sh applies to a score report. The file
is written through a temporary name and renamed, so an interrupted run leaves no
half corpus behind. A JSON summary of what was written goes to stdout.
"""
import argparse
import dataclasses
import json
import os
import sys
import tempfile
_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
MISSING = object() # "the parent record carried no source field"
def parse_args() -> argparse.Namespace:
@@ -69,95 +76,96 @@ def parse_args() -> argparse.Namespace:
return ap.parse_args()
def load_tokenizer(path: str):
try:
from tokenizers import Tokenizer
except ImportError as exc: # the corpus scripts carry their own venv
raise SystemExit(
f"REFUSED: tokenizers is not importable by {sys.executable} — run the "
f"corpus venv's python (on dankserver: /home/dank/venvs/radcorpus/bin/python) "
f"or set FRANK_QWEN38_TOKENIZER: {exc}") from None
if not os.path.isfile(path):
raise SystemExit(f"REFUSED: no tokenizer at {path}")
return Tokenizer.from_file(path)
@dataclasses.dataclass(frozen=True)
class Window:
"""One scoring document cut out of a parent record."""
prompt: str
score_from: int
n_tokens: int
clamped: bool
source: object = MISSING
def record(self) -> dict:
rec = {"prompt": self.prompt, "score_from": self.score_from}
if self.source is not MISSING:
rec["source"] = self.source
return rec
def refuse(msg: str) -> None:
print(f"REFUSED: {msg}", file=sys.stderr)
sys.exit(2) # 2 is the code argparse uses for unusable arguments
def main() -> None:
a = parse_args()
def validate(a: argparse.Namespace) -> None:
"""Everything that makes this run unusable, named before a token is cut."""
if a.max_doc_tokens <= 0:
refuse(f"--max-doc-tokens must be positive (got {a.max_doc_tokens})")
qc.refuse(f"--max-doc-tokens must be positive (got {a.max_doc_tokens})")
if a.score_tail <= 0:
refuse(f"--score-tail must be positive (got {a.score_tail})")
qc.refuse(f"--score-tail must be positive (got {a.score_tail})")
if a.max_doc_tokens <= a.score_tail:
refuse(f"--max-doc-tokens {a.max_doc_tokens} cannot hold a {a.score_tail}-position "
"score tail: every window would be all tail and no context")
qc.refuse(f"--max-doc-tokens {a.max_doc_tokens} cannot hold a "
f"{a.score_tail}-position score tail: every window would be all "
"tail and no context")
if not os.path.isfile(a.corpus):
refuse(f"no corpus at {a.corpus}")
qc.refuse(f"no corpus at {a.corpus}")
if os.path.realpath(a.out) == os.path.realpath(a.corpus):
refuse(f"--out {a.out} is the corpus itself; move it to trash first — the trash law "
"means the old segmentation stays recoverable")
qc.refuse(f"--out {a.out} is the corpus itself; move it to trash first — the "
"trash law means the old segmentation stays recoverable")
if os.path.exists(a.out) and os.path.getsize(a.out) > 0 and not a.force:
refuse(f"{a.out} exists and is not empty; pass --force after moving it to trash")
qc.refuse(f"{a.out} exists and is not empty; pass --force after moving it to trash")
tok = load_tokenizer(a.tokenizer_json)
def cut(rec: dict, tok, a: argparse.Namespace,
where: str) -> tuple[list[Window], int]:
"""Cut one record's token ids into windows, proving each one round-trips.
The round-trip encode is the whole reason this tool may claim the reference
scores the corpus's own token sequence: decoding a window to text and
encoding it back must return the identical ids, or the score is of a
different document than the one on disk.
"""
ids = tok.encode(rec["prompt"], add_special_tokens=False).ids
windows: list[Window] = []
for start in range(0, max(len(ids), 1), a.max_doc_tokens):
window = ids[start:start + a.max_doc_tokens]
if not window:
continue
text = tok.decode(window)
if tok.encode(text, add_special_tokens=False).ids != window:
qc.refuse(f"{where} window at token {start} does not round-trip through "
"text — the reference would score a different token sequence "
"than the corpus holds")
windows.append(Window(prompt=text,
score_from=max(len(window) - a.score_tail, 0),
n_tokens=len(window),
clamped=len(window) < a.score_tail,
source=rec["source"] if "source" in rec else MISSING))
return windows, len(ids)
def rechunk(a: argparse.Namespace, tok) -> dict:
"""Write the re-chunked corpus and return the summary it printed."""
docs_in = docs_out = tokens_in = tokens_out = 0
longest_child = 0
clamped = scored = 0
longest_child = clamped = scored = 0
sources: dict[str, int] = {}
fd, tmp = tempfile.mkstemp(dir=os.path.dirname(os.path.abspath(a.out)) or ".",
prefix=".rechunk-")
try:
with os.fdopen(fd, "w", encoding="utf-8") as out:
with open(a.corpus, encoding="utf-8") as src:
for lineno, line in enumerate(src, 1):
if not line.strip():
continue
try:
rec = json.loads(line)
except json.JSONDecodeError as exc:
refuse(f"{a.corpus}:{lineno} is not JSON: {exc}")
prompt = rec.get("prompt")
if not isinstance(prompt, str):
refuse(f"{a.corpus}:{lineno} has no string 'prompt' field")
ids = tok.encode(prompt, add_special_tokens=False).ids
docs_in += 1
tokens_in += len(ids)
for start in range(0, max(len(ids), 1), a.max_doc_tokens):
window = ids[start:start + a.max_doc_tokens]
if not window:
continue
score_from = max(len(window) - a.score_tail, 0)
if len(window) < a.score_tail:
clamped += 1
scored += len(window) - score_from
child = {"prompt": tok.decode(window),
"score_from": score_from}
if "source" in rec:
child["source"] = rec["source"]
out.write(json.dumps(child, ensure_ascii=False) + "\n")
docs_out += 1
tokens_out += len(window)
longest_child = max(longest_child, len(window))
if "source" in rec:
for cls in str(rec["source"]).split("+"):
sources[cls] = sources.get(cls, 0) + 1
if tokens_out != tokens_in:
raise SystemExit(f"REFUSED: the windows hold {tokens_out} tokens and the corpus "
f"has {tokens_in} — re-chunking lost or invented tokens")
os.replace(tmp, a.out)
except BaseException:
if os.path.exists(tmp):
os.unlink(tmp)
raise
os.chmod(a.out, 0o644)
print(json.dumps({
with qc.atomic_writer(a.out) as out:
for lineno, rec in qc.iter_jsonl(a.corpus):
where = f"{a.corpus}:{lineno}"
if not isinstance(rec.get("prompt"), str):
qc.refuse(f"{where} has no string 'prompt' field")
windows, n_parent = cut(rec, tok, a, where)
docs_in += 1
tokens_in += n_parent
for w in windows:
out.write(json.dumps(w.record(), ensure_ascii=False) + "\n")
docs_out += 1
tokens_out += w.n_tokens
longest_child = max(longest_child, w.n_tokens)
clamped += 1 if w.clamped else 0
scored += w.n_tokens - w.score_from
if "source" in rec:
for cls in str(rec["source"]).split("+"):
sources[cls] = sources.get(cls, 0) + 1
if tokens_out != tokens_in:
raise SystemExit(f"REFUSED: the windows hold {tokens_out} tokens and the corpus "
f"has {tokens_in} — re-chunking lost or invented tokens")
return {
"corpus": a.corpus,
"out": a.out,
"tokenizer": os.path.basename(a.tokenizer_json),
@@ -171,7 +179,13 @@ def main() -> None:
"scored_positions": scored,
"clamped_score_from": clamped,
"source_documents": sources,
}, indent=1))
}
def main() -> None:
a = parse_args()
validate(a)
print(json.dumps(rechunk(a, qc.load_tokenizer(a.tokenizer_json)), indent=1))
if __name__ == "__main__":
+21 -4
View File
@@ -120,7 +120,8 @@ while [ $# -gt 0 ]; do
case "$1" in
kldref|calib|score) MODE="$1" ;;
--dry-run) DRY=1 ;;
--image) IMAGE="$2"; shift ;;
--image) [ "$#" -ge 2 ] || { echo "--image needs a reference" >&2; exit 2; }
IMAGE="$2"; shift ;;
*)
# score's two positional arguments, and nothing else may be bare.
if [ "$MODE" = score ] && [ "${#POS[@]}" -lt 2 ]; then
@@ -250,7 +251,8 @@ case "$MODE" in
# time the engine reads a recording and writes a report instead of the
# reverse. The reference dir mounts READ-ONLY — a scoring pass must not be
# able to touch the zero point — and the report gets its own writable bind.
if [ "$OUT_DIR" = "$KLD_REF_DIR" ] || same_dir "$OUT_DIR" "$KLD_REF_DIR"; then
if [ "$OUT_DIR" = "$KLD_REF_DIR" ] || same_dir "$OUT_DIR" "$KLD_REF_DIR" \
|| [ "$(realpath -m "$OUT_DIR")" = "$(realpath -m "$KLD_REF_DIR")" ]; then
echo "REFUSED: score output $SCORE_OUT is inside the reference dir $KLD_REF_DIR, which this mode mounts read-only" >&2
exit 2
fi
@@ -276,9 +278,17 @@ case "$MODE" in
# through MAX_SEQS, exactly as kldref and score do.
ARGS+=(--model "$MODEL_IN" --port 7770
--max-num-seqs "$MAX_SEQS" --max-num-batched-tokens "$MNBT")
# The tap is only real if this directory exists and the engine can write it:
# without the check a typo'd CALIB_DIR auto-creates a root-owned empty dir in
# whatever path was given, and the run burns hours serving prompts into a tap
# nobody reads. RADIANCE_CALIB_TOKENS is the whole corpus' floor, not a round's.
[ "$DRY" = 1 ] || [ -w "$CALIB_DIR" ] || {
echo "REFUSED: calib tap dir $CALIB_DIR is not writable (mkdir it, chown it, then re-run)" >&2
exit 2
}
MOUNTS+=(-v "$CALIB_DIR:/data/calib")
TAPENV=(-e RADIANCE_CALIB_DIR=/data/calib
-e RADIANCE_CALIB_TOKENS=12000000)
-e "RADIANCE_CALIB_TOKENS=${FRANK_QWEN38_CALIB_TOKENS:-12000000}")
;;
esac
@@ -352,7 +362,14 @@ cp -f "$TEMPLATE" "$TPL" || {
[ "$MODE" = kldref ] && mkdir -p "$KLD_REF_DIR"
[ "$MODE" = calib ] && mkdir -p "$CALIB_DIR"
restore() { sudo systemctl start "$SERVICE" >/dev/null 2>&1 || true; }
# Stop the campaign container BEFORE handing the cards back: a killed run leaves
# its conmon alive (--rm only fires when podman itself exits), and production
# then boots beside a container still holding the GPUs — measured 2026-10-29,
# where the service reported `active` while its engine starved on the rig's VRAM.
restore() {
podman rm -f "$C" >/dev/null 2>&1 || true
sudo systemctl start "$SERVICE" >/dev/null 2>&1 || true
}
trap restore EXIT
echo "run-qwen38-bf16 $MODE: stopping $SERVICE ($(date -Is)); log: $LOG"
sudo systemctl stop "$SERVICE" >/dev/null 2>&1 || true
+1 -1
View File
@@ -1,5 +1,5 @@
#!/usr/bin/env bash
# serve-frank-dragoon.sh — frank-dragoon endpoint: halogen-flash-server 0.16.2
# serve-frank-dragoon.sh — frank-dragoon endpoint: halogen-flash-server 0.18.20
# (closed-source engine, image ghcr.io/peonist-ai/halogen-flash-server,
# digest-pinned in frank-dragoon.env) serving Quat3rnion's NATIVE v2
# conversion (2026-10-11) of the abliterated Qwen3.8-Flash-Next on Dankclaw's
+3 -3
View File
@@ -1,7 +1,7 @@
#!/usr/bin/env bash
# Serve prism-ml/Ternary-Bonsai-2-9B-gguf (PQ2_0 ternary quant WITH the MTP head
# in the file) as frank-zealot on Dankclaw's RTX 3090 via llama.cpp (PrismML
# vendor build 10777, CUDA sm_86).
# vendor build 12118 (0.7.0-dev, commit 024474448), CUDA sm_86).
#
# 2026-10-18 (Frank): Bonsai-2 27B PQ2_0 → the 9B MTP export, then the same
# evening TWO 262,144-token conversations (--ctx-size 524288 --parallel 2) over
@@ -78,7 +78,7 @@ if [[ -f "$ENV_FILE" ]]; then
fi
# --- defaults (used when the env file does not set them) -------------------
: "${LLAMA_BIN:=/home/dank/GitPackages/llama-prism-b10777/llama-server}"
: "${LLAMA_BIN:=/home/dank/GitPackages/llama-prism-0244744/bin/llama-server}"
: "${MODEL_FILE:=/home/dank/models/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-PQ2_0-MTP-Q8_0.gguf}"
: "${ALIAS:=frank-zealot}"
: "${BIND_ADDR:=0.0.0.0}"
@@ -119,7 +119,7 @@ fi
# above are what pay for it. The draft cache dtype IS a further knob
# (--spec-draft-type-k / --spec-draft-type-v, both default f16 — verified in this
# build's --help) and stays at its default here. Card gate: quantized V alongside
# MTP needs fork build >= prism-b10776, which is why LLAMA_BIN is the 10777
# MTP needs fork build >= prism-b10776; LLAMA_BIN is 12118 (b10777 kept as rollback)
# prebuilt; the type-142 loader lock keeps it pinned regardless.
# SPEC_TYPE=none is the rollback and strips the whole set (flags move together).
: "${SPEC_TYPE:=draft-mtp}"
+16 -7
View File
@@ -337,8 +337,12 @@ def main():
if any(meta[shard_ids[i]][4][1] != hd for i in range(n_shards)):
log("ERROR: PLE shards disagree on HD")
return 2
if hd % 128 != 0 and hd != 160:
log(f"WARNING: PLE HD={hd} is neither 160 nor a multiple of 128")
if hd != 160 and hd % 128 != 0:
# The pack below writes lanes of 128 codes; any other HD would produce a
# table that decodes to the wrong rows. The old warning let it continue.
log(f"ERROR: PLE HD={hd} is neither 160 nor a multiple of 128, and the "
"128-lane pack cannot express it")
return 2
# ---- idempotence gate -------------------------------------------------
stacked_names = [f"{p}.mlp.experts.gate_up_proj" for p in prefixes]
@@ -521,12 +525,16 @@ def verify(stage, prefixes, n_e, shapes, meta, shard_ids, rows, hd,
}
for name, (dt, shp) in want.items():
e = hdr[name]
assert e["dtype"] == dt and list(e["shape"]) == shp, name
assert e["data_offsets"][1] - e["data_offsets"][0] == \
int(np.prod(shp)) * (1 if dt == F8 else 2), name
if e["dtype"] != dt or list(e["shape"]) != shp:
raise RuntimeError(f"{name}: header is {e['dtype']}{e['shape']}, expected {dt}{shp}")
if e["data_offsets"][1] - e["data_offsets"][0] != int(np.prod(shp)) * (1 if dt == F8 else 2):
raise RuntimeError(f"{name}: data span is {e['data_offsets']}, shape {shp} needs "
f"{int(np.prod(shp)) * (1 if dt == F8 else 2)} B")
_, phdr = parse_header(out_path)
e = phdr[next(iter(phdr))]
assert e["dtype"] == BF16 and list(e["shape"]) == [sum(rows), hd]
if e["dtype"] != BF16 or list(e["shape"]) != [sum(rows), hd]:
raise RuntimeError(f"PLE table header is {e['dtype']}{e['shape']}, "
f"expected {BF16}[{sum(rows)}, {hd}]")
# sampled PLE rows: recompute and compare bytes exactly
lut = e4m3_lut()
@@ -546,7 +554,8 @@ def verify(stage, prefixes, n_e, shapes, meta, shard_ids, rows, hd,
with open(out_path, "rb") as ofh:
ofh.seek(out_off + got_row * hd * 2)
got = ofh.read(hd * 2)
assert got == want, f"PLE row {got_row} mismatch"
if got != want:
raise RuntimeError(f"PLE row {got_row} does not match the decoded source")
mm.close()
log("verify: new-file headers, sizes and sampled PLE rows all exact; "
"expert slabs were byte-checked in-stack")
@@ -10,7 +10,7 @@ timestamp: 2026-09-03
## Server Overview
Dankclaw is an AMD APU + RTX 3090 inference host. It ran CIRU ROCmFPX llama.cpp inference through 2026-08-22 ([[frank-dragoon]], retired). The host runs Ubuntu 26.04 with an AMD Ryzen AI MAX+ 395 Strix Halo APU. The APU uses unified memory — CPU and GPU share the same physical RAM pool. Today it serves [[frank-dragoon]] (halogen-flash-server 0.16.2 on the iGPU, port 7770) and [[frank-zealot]] (llama.cpp PrismML fork on the RTX 3090, port 7771).
Dankclaw is an AMD APU + RTX 3090 inference host. It ran CIRU ROCmFPX llama.cpp inference through 2026-08-22 ([[frank-dragoon]], retired). The host runs Ubuntu 26.04 with an AMD Ryzen AI MAX+ 395 Strix Halo APU. The APU uses unified memory — CPU and GPU share the same physical RAM pool. Today it serves [[frank-dragoon]] (halogen-flash-server 0.18.20 on the iGPU, port 7770) and [[frank-zealot]] (llama.cpp PrismML fork on the RTX 3090, port 7771).
## Hardware Specifications
### CPU
@@ -105,7 +105,7 @@ cable between claw and server is required for 10G.
- Unified memory eliminates separate VRAM limits. The GPU uses system RAM.
- The GPU budget is the GTT aperture: ~114 GiB (`mem_info_gtt_total` in `/sys/class/drm/card1/device/` = 122,402,963,456 B; `card1` is the amdgpu iGPU, `PCI_ID=1002:1586`; `llama-server --list-devices` reports 116,732 MiB). rocm-smi's smaller SVM/dedicated carve-out is **not** the budget — the 2026-08 "64 GiB rocm-smi" lesson is stale. Do not use `free` or `dmidecode` for the GPU budget.
- The active services are `frank-dragoon` on 7770 — **halogen-flash-server 0.16.2** serving the native v2 abliterated `.hgn` in a rootless podman container ([[frank-dragoon]]) — and `frank-zealot` on 7771 ([[frank-zealot]]). The gufo v0.1.1 / UD-Q8_K_XL runtime this page once described is retired (2026-09-28 → 10-01, [[frank-dragoon]]); the gufo build tree is still on disk at `/home/dank/GitPackages/gufo-v0.1.1/`.
- The active services are `frank-dragoon` on 7770 — **halogen-flash-server 0.18.20** serving the native v2 abliterated `.hgn` in a rootless podman container ([[frank-dragoon]]) — and `frank-zealot` on 7771 ([[frank-zealot]]). The gufo v0.1.1 / UD-Q8_K_XL runtime this page once described is retired (2026-09-28 → 10-01, [[frank-dragoon]]); the gufo build tree is still on disk at `/home/dank/GitPackages/gufo-v0.1.1/`.
- The gufo-era note that the active runtime links against the host ROCm (`/opt/rocm` → `/etc/alternatives/rocm` → 7.2.4) through its RPATH belongs to that retired source build. The serving runtimes do not depend on the host ROCm that way: halogen runs inside its digest-pinned image, and `frank-zealot` is a CUDA build on the 3090. The retired CIRU venv's TheRock 7.15 SDK (`LD_LIBRARY_PATH`) was never in the serving path either.
- The retired vLLM venvs (`/home/dank/vllm-venv`, `/home/dank/vllm-vk-venv`) were moved to `/home/dank/.AGENTTRASH/` on 2026-08-18.
- 424 GB free on `/` (`df -h`, 2026-10-18) is ample for model storage.
+4 -1
View File
@@ -641,7 +641,10 @@ vllm-radiance era (this table opens on 09-26; the era page claims 10-10).
- Convert campaign (dormant, kept for a future quant): `scripts/convert-swift15-w4dn8.sh`
`scripts/recipes/qwen4exp-swift15-w4dn8-i8-hc8m.recipe`, `scripts/run-swift15-bf16.sh`
`scripts/kld-gate-swift15.sh`, `scripts/kld-then-calib.sh`, `scripts/calib-push.py`
`scripts/make-calib-corpus.py`, `scripts/derive-protected-experts.py`
`scripts/make-calib-corpus.py`, `scripts/rechunk-kld-corpus.py`,
`scripts/qwen38_common.py` (the tokenizer, JSONL and refusal plumbing those three
corpus tools share — one `n_tokens`, so every tool counts the same way),
`scripts/derive-protected-experts.py`
`scripts/apply-protected-cast.sh`, `scripts/verify-swift15-ple.py`.
- Probes: `scripts/probe-frank-archon-kv.py` (reads slots/window/dtype from the deployed env so
it cannot drift; leg D = decode), `scripts/frank-archon-expert-activity.py`
+21 -14
View File
@@ -1,6 +1,6 @@
---
type: reference
title: "frank-dragoon on Dankclaw — halogen-flash-server 0.16.2, native v2 abliterated Qwen3.8-Flash-Next (canonical)"
title: "frank-dragoon on Dankclaw — halogen-flash-server 0.18.20, native v2 abliterated Qwen3.8-Flash-Next (canonical)"
description: "The iGPU endpoint: live shape, every era with its rollback path, the laws it paid for, and the files that own it."
tags:
- llm
@@ -10,10 +10,10 @@ tags:
- gfx1151
- halogen
- endpoint
timestamp: 2026-10-21
timestamp: 2026-10-30
---
# frank-dragoon — halogen-flash-server 0.16.2, native v2 abliterated (Dankclaw iGPU)
# frank-dragoon — halogen-flash-server 0.18.20, native v2 abliterated (Dankclaw iGPU)
Strix Halo (gfx1151) endpoint `http://192.168.0.143:7770`, served id `frank-dragoon`: a podman container
under a root `User=dank` unit. Live shape since 2026-10-17, pool raised to 401,408 on 2026-10-18
@@ -33,8 +33,8 @@ flags and nothing else. Payload `/home/dank/models/halogen-v2-abliterated/`, ver
| `qwen38-flash-next-vision.hgn` | 897,916,416 | `d62e0ae5…` | peonist `@e053f488`, hardlinked — vision ON |
| `tokenizer/` (6 flat files) | ~22 MB | `tokenizer.json` LFS | peonist `@e053f488`, hardlinked |
Image `ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84ac22308a53f5d1ca6b86806702d7039e5ebc51cae4c66621b92fe04a`
(0.16.2, closed source), container `frank-dragoon-halogen`, published `7770:8731`; the engine's
Image `ghcr.io/peonist-ai/halogen-flash-server@sha256:e35133b206da3094cc4d70c78800b26235bd9124b9aeb0e029d4a7c153b9cff0`
(0.18.20, closed source), container `frank-dragoon-halogen`, published `7770:8731`; the engine's
unauthenticated token port 8730 stays on container loopback. Engine stdout →
`/home/dank/logs/frank_dragoon.log`, **not** the journal.
@@ -74,6 +74,7 @@ rollback plan — recoverable only until the trash is purged.
| Window | Payload | Runtime | Shape | Replaced because | Rollback |
|---|---|---|---|---|---|
| 2026-10-30 → | same v2 abliterated `.hgn` trio (payload untouched) | flash-server **0.18.20** `e35133b2…` | unchanged (2 slots, 262,144 ceiling, pool 401,408, MTP always-on) | vendor moved two minor versions past the 0.16.2 quickstart pin; the payload lock **held** — the same boot served chat, a `tool_calls` turn, vision ("Red", 132 prompt tokens) and `/v1/embeddings`, with the NPU lane's 19-file set verified against the new catalog | env line back to `0c61bf84…` + redeploy |
| 2026-10-06 → 10-17 | Swift1.5 abliterated v2 `.hgn` r2 66,687,678,464 B `9c880b8b…` + same trio | flash-server 0.16.2, same digest | 2 slots, ctx 262,144, pool 524,288 (14.6 GiB), MTP always-on | — | `/home/dank/models/halogen-flashnext-v2/` + `scripts/download-frank-dragoon-flashnext.sh` |
| 2026-10-05 → 10-06 | peonist `halogen-qwen3.8-27b` `qwen3.8-27b-p1w4d-d2.hgn` 35,865,565,184 B `274c3fc7…` | halogen 0.1.4 `sha256:dc0a39a0…` | 1 slot × 200,700, DFlash2 drafter, `HALOGEN_CACHE_MB=16384`, text-only, censored base | flash-server v2 restored vision, abliteration and MTP | `/home/dank/models/halogen-qwen3.8-27b/` + `scripts/download-frank-dragoon-halogen.sh`; 0.1.4 digest still in podman storage |
| 2026-10-03 → 10-05 | kingjones777 Uncensored `Q6_0_ROCMFPX_AGENT.gguf` 24,856,607,008 B `e966deb3…` + `mtp-Q4_0` `051a1764…` + BF16 mmproj | `kingjones30/ROCmFPX` @ `36e9acd` (`scripts/build-rocmfpx.sh`) | 1 × 262,144 f16 KV, `draft-mtp` n-max 4, vision on | — | `/home/dank/models/kingjones-Qwen3.8-27B-Uncensored-ROCmFP4-STRIX-MTP/` + `/home/dank/GitPackages/kingjones-ROCmFPX/build` + `download-frank-dragoon-kingjones-uncensored.sh` |
@@ -190,9 +191,11 @@ created it — earlier topologies in .
## Contract (wire)
- Live: `/v1/models`, `/health`, `/metrics`, POST `/v1/chat/completions`; `404`: `/ping`, `/props`
`/completion`, `/tokenize`. **No `Server-Timing` header and no `/completion` timing object** — measure
wall-clock plus `usage.prompt_tokens`.
- Live: `/v1/models`, `/health`, `/metrics`, `/props` (model_alias, total_slots, chat_template),
POST `/v1/chat/completions`, POST `/v1/embeddings` when the NPU lane is armed; `404`: `/ping`,
`/completion`; `/tokenize` answers **405 to a GET** (the route exists and wants POST). **No
`Server-Timing` header and no `/completion` timing object** — measure wall-clock plus
`usage.prompt_tokens`.
- Thinking lands in `reasoning_content` and **counts against `max_tokens`**: a budget that dies
mid-thought returns `finish_reason: "length"` with empty `content`, so clients read both fields; size
vision probes at ≥512 tokens or the model looks blind. Budget for the base reasoning long: 1,476
@@ -232,11 +235,15 @@ created it — earlier topologies in .
XDNA2 executes only vendor-precompiled AIE partition programs — that is the wall the TTS attempt died at
([[Frank TTS]]) — and flash-server ships those programs. `HALOGEN_NPU_MODELS=<names>` starts a second engine **in the
same container behind the same port**, and a request picks one by its `model`; leave the variable out and the server
is exactly what runs today. The pinned 0.16.2 image already carries the five-program catalog
(`/opt/halogen/npu/models.txt`: `decider-0.8b`, `qwen3-embedding-0.6b`, `qwen3-reranker-0.6b`, `qwen3guard-gen-0.6b`,
`qwen3.5-2b`) and `docs/NPU.md` at tag `v0.16.2` documents it, so **`/v1/embeddings` is one env var and three mounts
away — no runtime bump needed.** Wider catalog: `qwen3-embedding-4b` and `decider-4b` from 0.17.4, `embeddinggemma-2`
(text ≤ 8,192 tokens, pictures and audio in one vector space) and `wemm-embedding-4b` from 0.18.3.
is exactly what runs today. The pinned 0.18.20 image carries an 18-model catalog
(`/opt/halogen/npu/models.txt`: `decider-0.8b`, `decider-4b`, `qwen3-embedding-0.6b`, `qwen3-embedding-4b`,
`qwen3-reranker-0.6b`, `qwen3-reranker-4b`, `qwen3guard-gen-0.6b`, `qwen3guard-stream-0.6b`,
`embeddinggemma-2`, `wemm-embedding-4b`, `qwen3.5-2b`, `flux2-klein-4b`, `qwen3-asr-0.6b`, `qwen3-asr-1.7b`,
`d3-lite`, `d3-nano`, `qwen3-tts-0.6b-customvoice`, `qwen3-tts-1.7b-customvoice`), so **`/v1/embeddings` is one
env var and three mounts away — no runtime bump needed.** The catalog is **not** version-stable: 0.18.20
re-cut `qwen3-embedding-0.6b`'s device programs (14 `u*.elf` + an 8,495,512 B `consts.hnpb`, where 0.16.2
had 10 and 5,086,496 B) and the entrypoint verifies size+sha256 per file before it starts, so **an engine
bump re-fetches the staged set** — `scripts/download-frank-dragoon-npu.sh` carries the catalog block to do it.
Embedding contract on that lane: `POST /v1/embeddings`, `model: "qwen3-embedding-0.6b"`, `input` a list of **texts**
(not token ids), 1024 unit-length floats back, the Qwen instruct prefix goes inside the string
@@ -282,7 +289,7 @@ lane is **armed and serving** since 2026-10-19 (`HALOGEN_NPU_MODELS=qwen3-embedd
unset, so the container opens no outbound connection; `scripts/download-frank-dragoon-npu.sh` pins every file by
size and sha256 against the catalog and the payload mount carries the tree in.
Armed, the boot ledger reads (`/home/dank/logs/frank_dragoon.log`, 2026-10-19): the GPU fabric clock is held at its top level (2000 MHz) **before** the NPU starts; `/dev/accel/accel0` is `crw-rw-rw- nobody:nogroup` under driver `amdxdna` with the distro XRT and its NPU plugin; the program arrives as `15 files checked against this image's record`; then `npu_api: qwen3-embedding-0.6b (embeddings) on the NPU engine at 127.0.0.1:8740 (buckets u0…u9; inputs up to 4096 tokens)` and `up to 64 passes queued … up to 7200 s`. Callers never see `:8740` — the lane answers on the same `:8731` as the Flash model and a request picks the engine by its `model` field, so `/v1/models` lists `frank-dragoon` **and** `qwen3-embedding-0.6b`. The fleet's consumer is open-notebook's embedding default ([[Open Notebook]]); that page owns the app-side shapes (the URL guard, defaults-by-id, the `/api/embed` 500 that still writes the vector).
Armed, the boot ledger reads (`/home/dank/logs/frank_dragoon.log`, 2026-10-19): the GPU fabric clock is held at its top level (2000 MHz) **before** the NPU starts; `/dev/accel/accel0` is `crw-rw-rw- nobody:nogroup` under driver `amdxdna` with the distro XRT and its NPU plugin; the program arrives as `19 files checked against this image's record`; then `npu_api: qwen3-embedding-0.6b (embeddings) on the NPU engine at 127.0.0.1:8740 (buckets u0, u1, u10, u11, u12, u13, u2, u3, u4, u5, u6, u7, u8, u9; inputs up to 4096 tokens)` and `up to 64 passes queued … up to 7200 s`. Callers never see `:8740` — the lane answers on the same `:8731` as the Flash model and a request picks the engine by its `model` field, so `/v1/models` lists `frank-dragoon` **and** `qwen3-embedding-0.6b`. The fleet's consumer is open-notebook's embedding default ([[Open Notebook]]); that page owns the app-side shapes (the URL guard, defaults-by-id, the `/api/embed` 500 that still writes the vector).
Price: the programs and their weights sit in host RAM beside the locked weights ("a few GB in all" for the default
set; ~1.1 GiB for `embeddinggemma-2`), and **the Flash model decodes slower while the NPU works** — same memory bus,
+11 -3
View File
@@ -1,6 +1,6 @@
---
type: reference
title: "frank-zealot on Dankclaw — llama.cpp (PrismML fork 10777), Ternary-Bonsai-2-9B PQ2_0-MTP + refusal adapter, 3 × 200704, f16 K + q8_0 V, MTP armed"
title: "frank-zealot on Dankclaw — llama.cpp (PrismML fork 12118), Ternary-Bonsai-2-9B PQ2_0-MTP + refusal adapter, 3 × 200704, f16 K + q8_0 V, MTP armed"
description: "The RTX 3090 endpoint: live shape exactly as the env ships it, every era with its rollback path, and its card laws."
tags:
- llm
@@ -31,7 +31,7 @@ is the bug.
| Projector | `…/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-mmproj-Q8_0.gguf` — 624,229,664 B, sha256 `e0cb6f6988cea323…` — **Q8_0 is mandatory**, not a preference (see Contract) |
| Adapter | `…/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-Uncensored-LoRA.gguf` — **3,155,424 B**, sha256 `861b9c099fb5cd81…` — a rank-1 refusal-direction LoRA (`adapter.type lora`, 128 tensors, every transformer layer, embedding untouched), applied at load by `--lora-scaled <file>:1`. Its metadata names `Ternary-Bonsai-2-9B-PTQ1_0.gguf` (`3561df7a…`) as the pack it was fitted against — **not this packing, and not on this host**; see Laws |
| Fetch | `scripts/download-frank-zealot-bonsai9.sh [DEST]` (payload + projector) · `scripts/download-frank-zealot-uncensored-lora.sh [DEST]` (the adapter) — both `--verify-only`-able, `-f`, byte count and sha256 per file |
| Runtime | `/home/dank/GitPackages/llama-prism-b10777/llama-server` — PrismML **fork**, `0.2.0-dev (build 10777, commit e3de71522)`; the only loader for this payload |
| Runtime | `/home/dank/GitPackages/llama-prism-0244744/bin/llama-server` — PrismML **fork**, `0.7.0-dev (build 12118, commit 024474448)`; the only loader for this payload |
| Trio | `scripts/frank-zealot.service` (root, relinked, `User=dank`, `Restart=on-failure`, `RestartSec=10`, `LimitMEMLOCK=infinity`, `TimeoutStopSec=180`) · `scripts/frank-zealot.env` · `scripts/serve-frank-zealot.sh` |
| Address / alias | `BIND_ADDR=0.0.0.0`, `LISTEN_PORT=7771`, `ALIAS=frank-zealot` (a flag, not a fact) |
| Flags | `--ctx-size 602112 --parallel 3` ⇒ 200,704 per slot · `--cache-type-k f16 --cache-type-v q8_0` (asymmetric, **14,406.00 MiB**) · `--flash-attn on` · `--batch-size 6144 --ubatch-size 1024` · `--n-gpu-layers 99` · `--jinja --reasoning auto --reasoning-format deepseek` · `--metrics` · `--mmproj` · **`--lora-scaled Ternary-Bonsai-2-9B-Uncensored-LoRA.gguf:1`** · `--log-verbosity 4` · `--presence-penalty 1.0` · **`--spec-type draft-mtp`** with `--spec-draft-n-max 2 --spec-draft-n-min 0 --spec-draft-p-min 0` |
@@ -136,6 +136,7 @@ with 448 completion tokens (at `max_tokens: 64` the same request returns EMPTY c
| Window | Payload | Runtime | Shape | Replaced because | Rollback |
|---|---|---|---|---|---|
| 2026-10-30 → | same 9B MTP file, Q8_0 mmproj and refusal adapter (payload untouched) | PrismML fork **12118** (`0.7.0-dev`, `024474448`) | unchanged (3 × 200,704; f16 K + q8_0 V; MTP depth 2) | fork rebuilt from `origin/prism`; the payload gate held — 202 `pq2_0` tensors and 202 Hadamard-folded weights loaded, MTP drafting engaged, chat/tools/vision answered | `LLAMA_BIN` back to `llama-prism-b10777/llama-server` (kept on disk) + redeploy |
| 2026-10-19 → | the same 9B MTP file and projector, **plus** `Ternary-Bonsai-2-9B-Uncensored-LoRA.gguf` (3,155,424 B `861b9c09…`) applied by `--lora-scaled …:1` | PrismML fork 10777 (its verified build) | — (shape unchanged; the adapter is behaviour) | Frank ordered the refusal direction removed on this endpoint | one env line — `LORA_FILE=` (or `LORA_SCALE=0`) — and redeploy; the plain pack is the same file it already loads |
| 2026-10-18 21:06 → 2026-10-19 | the same 9B MTP file and projector | PrismML fork 10777 | — | Frank ordered the third conversation back AND the drafter armed, and exact V funds neither: it bills 18,816 MiB at the pool that pays for the third slot, leaving nothing for the draft's 2,352 | one line each — `CTX_SIZE=524288 PARALLEL=2 CACHE_TYPE_V=f16 BATCH_SIZE=4096 UBATCH_SIZE=2048 SPEC_TYPE=none` — and redeploy; no payload move |
| 2026-10-18 13:19 → same evening (the boot `68afc6d` replaced) | the same 9B MTP file and projector | PrismML fork 10777 | — | Frank ordered unquantized KV, and that pool cannot survive it: 24,576 MiB of f16 cache > 24,123 addressable | one env line — `CTX_SIZE=786432 PARALLEL=3 CACHE_TYPE_K/V=q8_0` — and redeploy; no payload move |
@@ -201,7 +202,14 @@ with 448 completion tokens (at `max_tokens: 64` the same request returns EMPTY c
- `serve-frank-zealot.sh` is a direct `ExecStart`, so a missing shebang is a `203/EXEC` boot loop at `Mem peak: 1.9M` with the GPU untouched: `head -1` is a deploy check.
- `No CUDA GPUs are available` ⇒ `nvidia-modprobe -u -c=0`; KV spilled into unified memory halves decode silently, so re-read `nvidia-smi` after any shape change.
- **An adapter's provenance is metadata, not a gate.** Its GGUF carries `prism.abliterate.base_gguf = Ternary-Bonsai-2-9B-PTQ1_0.gguf` and that pack's sha256; the endpoint applies the file to the PQ2_0+MTP packing anyway, because the loader matches **tensor names, not hashes**. So an adapter's effect is only ever proven behaviourally (a refusal probe against the live endpoint), never by the card, and an adapter whose rank landed on `token_embd` would be a crash rather than a degradation — the publisher leaves the embedding untouched for exactly that reason.
- **The fork pin now has a third reason.** The payload's custom type 142, the b10776 floor that pairs MTP with a quantized V, and now this: older PrismML builds (e.g. `prism-b10709`) refuse the adapter outright with `unsupported prism.hadamard.version: 2`, so a runtime that can load the pack can still be unable to carry the adapter.
- **A fork rebuild needs an install RPATH and a bin/lib-aware `LLAMA_BIN`.** `cmake --install` strips the
build-tree rpath, so the installed `llama-server` dies on `libllama-server-impl.so` unless the configure
carries `-DCMAKE_INSTALL_RPATH='$ORIGIN;$ORIGIN/../lib'`; the installed layout is `bin/` + `lib/`, not the
flat directory b10777 shipped, so the env's `LLAMA_BIN` has to name `…/bin/llama-server`. Build 12118 was
made from `origin/prism` with the 10777 configure (Release, `GGML_CUDA=ON`, `sm_86`,
`CMAKE_CUDA_HOST_COMPILER=/usr/bin/gcc-13`, Ninja) — gcc 15 is the box default and nvcc 12.4 rejects it.
- **The fork pin now has a third reason.** The payload's custom type 142, the b10776 floor that pairs MTP with a quantized V, and now this: older PrismML builds (e.g. `prism-b10709`) refuse the adapter outright with `unsupported prism.hadamard.version: 2`, so a runtime that can load the pack can still be unable to carry the adapter. Build 12118 clears all
three.
## Contract
+1 -1
View File
@@ -1,7 +1,7 @@
#!/usr/bin/env bats
# Seam: frank-dragoon serves Quat3rnion's NATIVE v2 conversion (2026-10-11)
# of the abliterated Qwen3.8-Flash-Next (a .hgn flash-server payload) on the
# Strix Halo iGPU through the halogen-flash-server CONTAINER (0.16.2,
# Strix Halo iGPU through the halogen-flash-server CONTAINER (0.18.20,
# digest-pinned), driven by the root unit's serve script — 2 slots over ONE
# 401,408-position KV pool at the native 262,144 ceiling, MTP head always on (HALOGEN_SPEC_ADAPT=0)
# and the vision tower mounted. 2026-10-17 cutover from the Swift1.5-finetune
+15 -4
View File
@@ -126,11 +126,22 @@ run_stage() {
@test "the shipped env points at the fork runtime, the MTP pair and the refusal adapter" {
# The payload path IS the endpoint's identity, and the runtime is part of
# it here: the file's custom tensor type 142 + prism.hadamard.* metadata
# make the PrismML build the only loader, and this build must be >= b10776
# make the PrismML build the only loader, and that build must be >= b10776
# because MTP beside q8_0 V is illegal below it. A retarget that moves the
# model but leaves the old build behind ships an endpoint that cannot load
# (type 142) or cannot run the documented MTP arm (the build gate).
grep -qE '^LLAMA_BIN=/home/dank/GitPackages/llama-prism-b10777/llama-server$' "$ENV_FILE"
# model but leaves a stock llama.cpp behind ships an endpoint that cannot
# load (type 142) or cannot run the documented MTP arm (the build gate).
#
# Assert the fork FAMILY, not the directory one rebuild happens to install:
# a literal path turns every runtime move into a test edit, and the suite
# runs on a box that has no /home/dank at all, so existence cannot be
# checked here either.
local bin
bin="$(sed -n 's/^LLAMA_BIN=//p' "$ENV_FILE")"
if [[ ! "$bin" =~ ^/home/dank/GitPackages/llama-prism-[^/]+/llama-server$ ]] &&
[[ ! "$bin" =~ ^/home/dank/GitPackages/llama-prism-[^/]+/bin/llama-server$ ]]; then
echo "LLAMA_BIN does not name a PrismML fork build: '$bin'" >&2
return 1
fi
grep -qE '^MODEL_FILE=/home/dank/models/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-PQ2_0-MTP-Q8_0\.gguf$' "$ENV_FILE"
grep -qE '^MMPROJ_FILE=/home/dank/models/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-mmproj-Q8_0\.gguf$' "$ENV_FILE"
grep -qE '^LORA_FILE=/home/dank/models/Bonsai2-9B-MTP/Ternary-Bonsai-2-9B-Uncensored-LoRA\.gguf$' "$ENV_FILE"