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>
The mirror keeps where it fetched a file beside it, and reports that and the
checksum after it restarts. A model whose files the mirror cannot trace is
found on the registry: a repository holding a file of that name that has the
commit the mirror's directory is named after, with every file at the same
size, the most downloaded first. ctl model origin and the console set one by
hand, checked the same way. Commits compare shortened.
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>
Serve a model is a view of the registry's GGUF models, trending or searched;
Enter on one lists its files, and the one chosen is served with
llmgw ctl model serve. A form of one field is applied by Enter on it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Accounts, API keys and Organizations views read the store and change it by
running the users, keys and org commands in-process, so their checks and
messages are the ones shown. A Mirror view lists what the mirror holds and
which models use it, downloads into it and removes from it. Models gain
adding from a definition file.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Enter on a row of Models, Nodes or Replicas opens what can be done to it,
as forms and questions over the admin API. A Quotas view sets and clears
capacity quotas. Do gains serving a model, upgrading the cluster,
restarting every replica and a backup.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The summary's GPU, fabric and idle tables were written to standard output
regardless of the writer they were given, so on a cluster with a GPU the
console printed the GPU table across its full screen every three seconds.
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>
server add gives another machine this llmgw, a certificate, the
configuration and store address, lets it into the store through Patroni, and
starts it; --vip keeps a floating address on the leader with keepalived,
following a new /leader endpoint. Nodes learn every control plane from the
leader and notice a dead one by HTTP/2 ping instead of after the kernel's
fifteen minutes. The setup, console, node and init screens are drawn full
screen in one frame: title bar, sidebar, bordered panel, key bar, dialogs.
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>
deploy/ha documents PostgreSQL under Patroni with a three-member etcd, as
running on the reference cluster, and the address that follows the primary.
Backups read such an address as libpq host and port lists and prefer a
standby, rather than resolving the list as one name.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Requests and tokens by tenant, the shares failing and refused by a limit,
first-token p95, budgets spent this period and the day's heaviest users,
filtered by a tenant chooser. Installed beside the cluster dashboard.
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>
Percentiles are read from the histograms kept with the usage sums and shown
per group on the usage tab and in the people page's panels. Requests refused
by a limit are recorded as 429s against their owner, free of charge, so a team
hitting its limits shows as such. Usage can be grouped by model.
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>
A model with replicas on a card and on CPUs answered at either speed with no
way to tell which. The picker names where each model runs, each reply names
the hardware that served it, and every answer carries x-llmgw-hardware.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A card with something else on it when the agent started stayed out of
placement after that process let go of it, until the agent restarted. The
agent now sends what processes other than its own engines hold on each card,
and the control plane replaces the registration verdict with it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Every minute the agent reads nvidia-smi's full report, its NVLink error
counters and the kernel's XID lines. They are published per card,
shown on the node page and the GPU map, charted in Grafana, and five
alerts watch them.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The cluster page draws every card coloured by utilisation, memory or
temperature, and lists replicas whose every card is under 5% busy.
llmgw_gpu_assigned says which replica, model and owner hold each card.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
They were read once, at agent start, and published unchanged since.
Each sample now carries utilisation, memory and bandwidth in use, the SM
clock and uncorrected ECC errors. The node page charts each card, the
cluster page the fleet by class, Grafana has a GPU row, and three GPU
alerts are added.
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>
tp on a llama.cpp GPU profile is read as gpus_per_node rather than
refused, and a Hugging Face repository page as a vLLM source as the
repository id, so models written that way are placed after the upgrade
instead of dropped from the catalog. Engines adopted after an upgrade
are checked for computing on their GPUs too.
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>
The explorer fetches a safetensors set with its config and tokenizer;
the mirror gives out a version's manifest only once nothing is
downloading and every shard its index names is there, with each file's
sha256, which nodes check; mirror add takes several URLs; a repository
page is refused as a source.
Refs #2 (item 9).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A taken address on PostgreSQL fell through to a generic error, because
the store looked for SQLite's "UNIQUE". It checks code 23505 too. The
done page tells someone whose address had an account to sign in or ask
for a reset, without saying which case it was; other failures give a
logged reference.
Refs #2 (item 6).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>