A starter model with no room failed init after ten minutes and left the
firewall and the judge uninstalled.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
server init (and the setup screens) write guard.default [baseline] —
secrets refused, cards masked, injection recorded, the judge refusing
S1-S4, S7, S9-S12 in prompts and answers, fail open after 5s — fetch the
judge into the mirror and run it on a node's CPU. --no-guard-model leaves
it out. The closing text names what init cannot do: TLS on the client
port and backup recipients.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The README's status stopped at v0.9 and listed gaps since closed; onboarding
still said there was no SSO and no roles.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
notify.webhooks sends signed JSON or Slack-compatible messages, queued,
retried, de-duplicated hourly; ctl notify test checks each webhook.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A new internal/clientip says who sent a request and how: the connection's
address, scheme and Host, or through a configured proxy what it forwarded.
The base URL in pages and setup scripts, isHTTPS for cookies, and the
per-address limits of auth and the sign-in forms use it. /setup scripts are
no-store.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The admin listener answered any local process: models added, nodes
upgraded, engine keys listed, the heap dumped. /api and /debug now demand
the token the server writes 0600 to its state directory on first start;
ctl, the console and node add send it (sudo, LLMGW_ADMIN_TOKEN or
--token-file). pprof is off unless debug_pprof. admin_listen off loopback
is refused unless admin_remote. Dashboard pages, /metrics and /health are
unchanged.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The supervisor drops to the run_as user (default llmgw-engine) when the
agent is root: its credential and groups, a 0700 home under the work
directory as the working directory, HOME and XDG_CACHE_HOME there. A node
without the user keeps engines as root and logs why. node add creates the
user in the video and render groups.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Without agent_tls the control plane served plaintext h2c on every
interface, and any machine reaching it could register as any node. The
server now refuses to start that way unless agent_insecure: true, and then
binds loopback when agent_listen names only a port.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Monitor draws CPU, memory, GPUs, requests, tokens, latency, network and disk
as Braille charts over 5m/1h/24h/7d, then per node, card and model
sparklines; node and model pages have their own. History is read from
monitoring.prometheus through POST /api/v1/metrics/range, or without it
from what the console saw. The control plane serves the cluster's machines
for Prometheus http_sd at /prometheus/targets on its metrics port, and node
add installs prometheus-node-exporter.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The console starts a serve or update job over the admin API and stays,
instead of closing to follow the download. Jobs lists them with their
progress and steps; the sidebar counts those running. ctl model serve and
update take --detach; ctl jobs lists jobs and follows one.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Ranking what was free first made every file come out on the CPU on a cluster
whose one card was in use. The plan now ranks by hardware alone, free now
only breaking a tie; a model served onto cards that are busy is added and
waits for them, the job ending as waiting rather than failed.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The control plane reads the model's shape from one GGUF header or its
config.json and lists, for every file, the best way it runs here: one card,
several of a node's (by layer for llama.cpp, tensor-parallel for vLLM),
several nodes' over one fabric (vLLM, pipeline-parallel between them), or a
CPU node; what each card holds and whether it is free now. ctl model plan
prints it; model serve takes its file and way unless told, gives a GGUF on
GPUs a GPU profile, and with --fallbacks adds the next best ways. The
console shows it per file and asks for the way and the fallback.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
model serve takes --projector, fetched beside the weights and loaded by
llama.cpp with --mmproj, and --format safetensors with --gpu-class and --tp,
which fetches the weights with their config and tokenizer and runs them on
vLLM. The console offers both, F switching between GGUF and original
weights. The mirror view is one row per version with its files on Enter.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Every document and a page for every command, built from their help, read
like info: topics, contents, find. ? opens the console's own page, which is
new and covers every screen.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model served from the registry records its origin: repository, commit and
each file's checksum; one served before is worked out from the mirror's
record of where it fetched the file. Every mirror.update_check (6h) the
control plane asks whether those files changed there. ctl model updates
lists it, ctl model update fetches beside the old files, checks, swaps and
replaces replicas one at a time, ctl model rollback goes back. The console
shows it on Models and offers the same.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The console gains live views of nodes, GPUs, models, replicas, usage and
agent logs, and a settings tree over every key of server.yaml (agent.yaml on
a node), generated from the configuration structs: values with their
defaults and doc comments, edited in dialogs, saved only once the service's
own loader accepts them, comments kept. The generator now tells blocks apart
by package, which brings the TLS, engine and supervisor settings back into
the reference.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The setup screens can reach a database machine by a join code instead of
ssh: they listen on 7444 and show a short code; llmgw join dials out,
checks the setup by fingerprint, admits itself with the code's secret, and
runs what the setup sends until it is done. A joined machine is one more
onboard.Remote, so checks and the Patroni install run over it unchanged.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
With nothing installed, sudo llmgw asks for one machine or three, takes how
to reach the other two (ssh agent, key or password, and a sudo password used
only for the install), checks every machine first, shows the plan and its
command line, and installs. On a control plane it opens a console with the
cluster's state and the next steps. Machines are reached with Go's ssh so a
password works; the store's etcd and access rules use this machine's routed
address rather than a client-facing name.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
init --patroni user@host ... installs PostgreSQL, Patroni and etcd on the
given machines over ssh, with this one as the third etcd vote, makes the role
and database, and moves the store in use into the cluster. Each step checks
first, so it changes nothing on a cluster that is up. For a store of several
hosts the control plane publishes each member's role, state and lag from
Patroni, a stopped member as missing, prints it in ctl status, and alerts on
it. Making an administrator on PostgreSQL sent a bool to an integer column;
it sends an integer now.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Requests by outcome, tokens and first-token time per tenant, at the level
router.tenant_label names (team by default), and every budget's share spent
this period. Rules alert on budgets at 80% and 100%, tenants hitting limits,
failing, spiking past their weekly average, or waiting on first tokens.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Charts, totals and budgets summed the request table on every view. Usage is
now also summed in the writing transaction into five-minute, hourly and daily
tables per key, person, project and model, with latency and first-token
histograms. Charts read the coarsest tier their slices allow; totals and
budgets compose rows, slices, hours and days, and stay exact. Request records
can be given a retention without moving any total.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
An organization's members, limits and use are a panel of the people page,
where they can also be changed, so the administrator's menu loses its
Organizations entry and /org redirects there. Managers keep /org.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A team's members, quota and spend were on three pages that linked to each
other. They are three tabs of one page now, each at its old address, and
choosing anything in the tree opens its limits, capacity and use beside it,
editable in place.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Each engine has a list of builds, best first, from what its project
publishes and how each was compiled: llama.cpp CUDA 13.3, CUDA 12.8
(driver 570 for the GPUs it ships as PTX), then Vulkan, never the CPU
build on an NVIDIA node; vLLM CUDA 13, then CUDA 12.9, and for GPUs
older than every build of the version asked for, the newest built for
them (V100: 0.19.1). The node takes the first its hardware meets and
that installs and computes on the GPU, moving on when one does not, and
reports the version it runs. GPU processes are read from nvidia-smi's
full report, so Vulkan engines count as on their GPU.
Refs #2.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Read from vLLM's release pipeline: every x86 build from 0.20.0 has
kernels for compute 7.5 and up, the CUDA 12.9 one included, and 0.19.1
is the last built for 7.0. PyPI's build is CUDA 13 from 0.20, not 0.26.
A V100 asked for a newer vLLM is refused, naming 0.19.1 for
engine_overrides; the CUDA 12.9 fallback is for older drivers on
Turing and newer. The cu129 wheel is found among the release's assets,
since its manylinux tag differs between versions.
Refs #2.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A node that cannot run the CUDA 13 build installs the same version's
CUDA 12.9 build from vLLM's GitHub release, with PyTorch's cu129 torch;
the install computes on the GPU before it counts. The build can be
chosen per node — auto, cu13, cu129, none — on the cluster page, with
ctl engine-build, or over the admin API; the control plane keeps the
choice and tells the node at once.
Refs #2.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
engine_overrides give nodes picked by GPU class, id or labels their own
engine versions; node add --disable-engine keeps one off a node; what
vLLM cannot do on a node is a warning rather than a refused node; the
CUDA requirement follows the version; a hand-named binary is no longer
replaced by an installed one.
Refs #2 (items 4 and 7).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
