Each agent measures its node's memory read rate when it starts: every CPU
sums a share of a buffer past any cache, a tenth of free memory at most,
the best of four passes, in a fraction of a second; reported in Host
(mem_bandwidth_gbs) and NodeView. A token on a CPU reads every weight it
uses once, so one reply's speed is about that rate over those bytes:
modelplan.CPUTokensPerSecond, 0.68 of the measured rate plus 5 ms a token,
calibrated on the PoC against llama.cpp's predicted_per_second (node01
24.9 GB/s, qwen2.5-1.5b: 14.5 measured, 14.7 estimated; node05 41.9 GB/s,
qwen2.5-14b: 3.3 and 3.2). A model of experts named …-A3B reads its active
part (ActiveShare).
The explorer shows it as CPU tok/s, at Q4_K_M on the fastest node that
holds the model; a repository's page gives it for each GGUF by its size.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Python pickles (.bin, .pt, .pth, .ckpt, .pkl) run whatever they hold when
loaded, as the engine's user, on the node; that is how the malicious models
found on Hugging Face work. The node refuses such a source, or a mirror set
holding one, before fetching anything. A model added with one, or given
one, is refused, while one already in the catalog still loads and is
refused by its node with the same words. vLLM and SGLang downloading a
model by its id get --load-format safetensors. The mirror page marks the
file. allow_pickle: true on a model lets it through on purpose, carried to
the node in EngineProfile.allow_pickle.
BACKLOG M lists the rest: checksums against Hugging Face on every path,
its own scan, trusted publishers, engines without the internet, an eval
before an untrusted model serves.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
A tool's answer is read by the caller's policies as the prompt it
becomes, so an instruction planted in a ticket is withheld and personal
data redacted; its arguments are read before they leave. ctl mcp add
--rate bounds each caller's calls a minute to a server (migration 0050),
and five failures in a row take a server out for a minute, its tools
off the list.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
ctl guard judge check, and POST /api/v1/guard/judges/check, time three
judgments of a 280-token prompt, then a burst at once, against the
policies' wait: ok, tight or slow, about how many requests a second can
be judged, and what to do. server init runs it once the judge is up and
says a machine too slow before the next steps; the wait is not changed
without asking. BACKLOG reordered by what goes wrong where installed.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Its tools say what llmgw ctl does: cluster_status, list_nodes,
list_models, list_replicas, explain_placement, node_logs; none changes
anything. The admin API serves it at POST /api/v1/mcp, and the gateway
answers a server registered as llmgw:admin in its own process, so no
token is kept and each control plane serves it. ctl mcp add takes
--bearer-file for a token sent as Authorization: Bearer.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
llmgw ctl mcp add|list|remove|test and /api/v1/mcp/servers keep the
servers; a token given with --secret-file is kept in the store, sealed,
and named by reference. keys limits --tools, and the console's limits
form, grant tools as patterns. Documented in install.md and clients.md.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The startup timeout runs from when a node's download last moved, so a
model of hundreds of gigabytes on a slow mirror is not failed while it
arrives. ctl model serve --env sets engine variables (NCCL_DEBUG=INFO)
on every node, and a layout given by hand keeps expert parallelism for a
model of experts. docs/large-models.md: how a model is split, what each
way needs of a card, and a checklist for bringing one up on a fabric.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A mixture-of-experts model on more than one card is served with vLLM's
--enable-expert-parallel; config.json's experts are read by any of their
names, and a model that also reads pictures is sized by its text_config.
Tensor parallelism past the KV heads is allowed when it is a multiple of
them (Qwen3-235B, four KV heads, runs on eight cards), which the plan
had refused. Several nodes are offered in any number, not only powers of
two. Each way says what it needs of a card, part by part, and of all its
cards; the serve form checks a context longer than planned still fits.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A judge a policy names and the catalog lacked was served with 3 GB, no
cores and llama.cpp's prompt cache; on a busy node its judgments missed
their budget and fail: closed refused the requests. It now gets init's
2 GB and cores, and every judge modelserve serves runs with
--cache-ram 0.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
People → Sign-in shows single sign-on, Active Directory and SCIM, and
the directory's last sync. E sets up Entra ID from the tenant and client
IDs; D sets up Active Directory, tried from the control plane first:
each server bound, people who may sign in, members of each mapped group.
The secrets go into the store as store:auth/..., sealed by the master
key, and the CA into the settings, so no control plane needs a file.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
An external model takes api_key_files, each a file and an optional weight,
in place of api_key_file. Each key is an endpoint of its own
(external:MODEL#1, #2), so the router's scoring, retries and breakers work
per key. A key answering 429 is passed over while its breaker is open. A
key answering 401 is passed over too, and external_key_refused is sent,
naming the endpoint and never the key; with a single key the 401 is still
the client's. A key whose file cannot be read is left out, and usage
records which key answered by its endpoint.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
flux and sf3d on one card handed it to each other, each starting ComfyUI
and loading its weights from nothing (BACKLOG H3, placement side). An
environment of two or more models now gets a hidden catalog entry,
comfyui-env-<name>: on its first member's profiles with the most memory
any member needs, on demand for the longest idle timeout, carrying every
member's weights, repositories and the environment's custom nodes. The
members get no replicas of their own; asking for one wants the entry.
The agent fetches each member's weights; the gate links all of them,
refusing two weights files of one name, links each member's Hugging Face
repository, and answers /v1/models for every member. The control plane
offers the replica under the members' names with each one's workflow and
checkpoint, which the router sends by the model asked for. A member's
sibling never evicts the replica serving it, and the members' load counts
as the entry's.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
One job at a time, a 3D job waiting for the card held up another model's
job that could have run (seen on the PoC, BACKLOG H7). The leader's worker
claims jobs while fewer than eight run, passing over the models that have
one running, and starts each in its own goroutine; one ending wakes it for
the next. Lease and leader-only rules are as they were.
BACKLOG: H5–H7 marked, H8 (presets) and H9 (what the PoC taught) written.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A customer's portal had no Images or 3D pages: nobody had written a
definition for either, on a cluster whose V100 runs both. The leading
control plane now adds flux-schnell and triposr, on demand, once a node
has a card that fits one, the cluster installs ComfyUI, and the catalog
makes nothing of that kind. presets.auto (a live setting, on by default)
turns it off; a preset somebody removes is recorded as declined and not
added back until added again by hand. Each addition is in the audit log.
GET /api/v1/presets says how each preset stands, the ComfyUI the cluster
installs, and why one is not added; POST /api/v1/presets/{name} adds one
(setting engines.comfyui where there is none); PUT /api/v1/presets/auto
switches it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Stable Fast 3D's texture_baker and uv_unwrapper are C++/CUDA packages no
index has; on the PoC they were built and installed into ComfyUI's
environment by hand. nodes[].build names such directories, and the gate
builds each as a wheel with ComfyUI's Python, for the compute capability
torch reports for the replica's own card, keeps it on the node by the
node's commit, the architecture and the directory, and installs it
beside the replica with the node's requirements. A copy in ComfyUI's
environment does not pin it. A node with no CUDA toolkit says so.
comfyui.huggingface_repo shows the replica's weights to a node that
loads them by repository name, in the engines' Hugging Face cache, so a
gated repository needs no token on the node.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A catalog entry meant for many sites cannot know their GPU class names:
the PoC has a Quadro RTX 6000, a customer an A100, another an L40S. A
profile may now say gpu: {min_compute_capability, min_memory_gb} in
place of gpu_class, and stands for every class in the cluster that meets
it, named <profile>@<class>, at its own priority; placement still sees
exact classes. ProfileByName and EngineProfile resolve such a name to
the profile on that class, so every caller that maps a replica back to
its profile works unchanged. A ComfyUI profile may carry its own
workflow, checkpoint and nodes, and with its own source an fp8 workflow
and weights go to cards with fp8 and fp16 ones to Turing.
A profile by need is left out of placement until the cluster's cards are
known: with no class it would have read as a CPU profile.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model's catalog entry now says what its workflow takes and makes:
comfyui.inputs, each a placeholder of its name with a type (text, int,
float, bool, choice, image, mask, audio, video, file), bounds, choices
and a default; and comfyui.output, which gains video, audio and files
beside pictures and meshes. POST /v1/workflows/runs with {model, inputs}
checks a request against them before a job is written — a required input
left out, an unknown one, a number out of bounds, a song sent as a
picture, another owner's file id are each refused with what was wrong —
and the job worker replays it to a replica, where the files go into
ComfyUI's input directory, the workflow is filled and run, and the first
file of the model's output kind is the job's result. /v1/models lists
each ComfyUI model's workflow, so a client can build its form.
A PNG result carries the licence in an iTXt chunk, as a GLB does in
asset.extras. A file whose server named no type is typed by its name
before its bytes, so a WAV is audio/wav, not audio/wave.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A ComfyUI model may name an environment: the models of one environment
agree on every custom node they both name and on every package range,
so one replica can carry all of them and ComfyUI moves between their
weights itself rather than the card being handed over with a cold start
each time. The catalog refuses an environment that cannot share a
Python, naming both models; Catalog.Environments gives each one's
models, the union of their nodes and their weight sources, for
placement to build on.
A licence gains an id (SPDX where there is one), whether its output may
be used commercially, the regions it excludes, a revenue cap and the
attribution it asks for, so a person's or a site's choice of licences
can be matched without reading prose.
BACKLOG gains section H: ComfyUI as a platform.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
/v1/openapi.json is the API clients use — OpenAI's endpoints, Anthropic's,
and what llmgw adds — in OpenAPI 3.1, generated from internal/clientapi's
route table by the generator the admin API's document comes from, now
told each document's title, server, token and error. A test reads the
router's mux.HandleFunc calls and refuses a route described and not
mounted, or mounted and not described. Asked for before there is a key,
so it needs none.
/docs/api shows it in Swagger UI 5.33.1 (Apache 2.0, served from the
gateway as the page's policy requires): Authorize takes a key, Try it out
sends to this gateway. Staff are offered the admin API's document too,
from /docs/api/admin.json, which nobody else is given.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
/3d beside /images, while some model makes meshes: a picture chosen, the
job asked for through the same path an API client's takes, its progress
shown (waiting for the card, n ahead; making it, the node and percent),
and the mesh in a viewer — model-viewer 4.4.0 (Apache 2.0, with three.js
and lit), served from the gateway since the page's policy loads scripts
from nowhere else — with a download and the model's licence. The mesh is
served to its owner from /3d/jobs/{id}/file; another project's person is
told there is no such job.
A job made from the portal acted for a key that does not exist: the
worker now rebuilds a session's principal from the account that made it,
while it is active and still in the project the job is charged to.
ctl 3d list|get|cancel, over /api/v1/client-jobs (/api/v1/jobs is the
control plane's own work, which ctl jobs shows).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
TripoSR's checkpoint loads with transformers 4, and ComfyUI runs 5: of a
package a node names, its range decides, and of everything else what
ComfyUI runs.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
G2: the gate keeps a websocket open to its ComfyUI under a client id of its
own, puts that id on every workflow it lets through — ComfyUI tells only
the client that queued a workflow how it goes — and keeps the last word on
each: the node running, its step of how many. It answers at
/progress/{prompt_id}. While a job's request waits, the router reads the
queue (queued, n ahead) and the gate (running, node, step, percent) and
writes it into the job, which a client reads back. Only into a job of the
same key: a tag naming another's job writes nothing.
G3, the rest of the plumbing: comfyui.nodes names custom nodes by https
repository and full commit, with the PyPI packages they need. The gate puts
each in the replica's own custom_nodes at that commit and installs the
packages beside the replica, constrained to the versions ComfyUI's
environment already has, which it never changes. The catalog refuses a
branch for a commit and anything but package specs for requirements. An
OBJ a node saves leaves the gateway as a GLB, colours kept, so every mesh
can carry its licence.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
G3, the part that needs no model: a ComfyUI model's comfyui.output (or
external.output) says pictures or meshes. A request for a 3D model — a
job at /v1/3d/generations — carries the picture as base64; at the replica
it is uploaded to ComfyUI's input directory (the gate lets /upload/image
through), the workflow is filled in with its name, the seed and the
resolution, and the mesh the workflow saves comes back with its type,
which is the file the job keeps. comfy.Client reads every list of files an
output names, not "images" only, and types a file by its extension where
ComfyUI sends octet-stream.
A model's license (name, url, notice) is said in /v1/models and in the
job, and written into a GLB's asset.extras, since the file travels without
the API; a mesh it cannot be written into is refused. per_mesh in
auth.pricing, usage.meshes in the rows, the sums and the export
(migration 0045). A picture asked of a mesh model, or a mesh of a picture
model, is refused saying which it makes.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The catalog had one source a model, so an embedding model served by vLLM
from its repository on a card and by llama.cpp from a GGUF on CPUs had its
entry swapped by hand halfway through the metallurgy import. A profile's
source is what its engine loads and placement looks for; the model's is
the default, and what updates and canaries move. ctl model add checks
every source, the GGUF check reads each llama.cpp profile's, and ctl
weights collects none a profile loads. An empty source leaves a profile's
fingerprint as it was, so running replicas do not read as stale.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The five-minute, hourly and daily sums gain images (migration 0042), and
the CSV and JSON exports a column for them: once request rows were past
their retention, an export said what pictures cost but not how many there
were. The pictures made before are added to the sums from their rows.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model whose profiles run engine comfyui is placed on a node's card like
any other, and makes pictures there. ComfyUI asks for no key, so the agent
starts it behind llmgw comfyui-gate: ComfyUI on the loopback, the gate on
the replica's port demanding the replica's key and letting through only
what the router asks — queueing, waiting, fetching, cancelling. The gate
answers the agent's /health and /v1/models, shows ComfyUI the fetched
weights by their own names, and gives each replica its own base directory.
ComfyUI runs as the gate's child, so its card memory is the replica's.
A node offers the engine when agent.yaml names its ComfyUI
(engines.comfyui.dir). The model's comfyui: block names the workflow and,
for a source that is a set of files, the checkpoint.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
auth.pricing takes per_image, charged on top of a prompt's tokens; a model
priced only per picture is not free, so a spent budget still stops it.
Each usage row keeps how many pictures were made (migration 0041), and
ctl request and the admin API's request view show them.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
An external model with api: comfyui is a ComfyUI server. A request for
pictures goes through the same key, allowlist, limit, admission and guard
checks as any other; at the replica it becomes a workflow — a built-in
(flux-schnell, flux-dev) or a JSON file in API format, with {{prompt}},
{{width}}, {{seed}} and the like filled in — queued, waited on, and its
pictures sent back as b64_json. A client that leaves takes its workflow
off the queue or interrupts it. ComfyUI is never scraped for metrics.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Qwen3-Embedding and models like it are trained with an instruction on the
query side only. The prefix goes before the question a knowledge-base
search embeds, at answer time and in the admin API's search; documents
reach /v1/embeddings from llmgw-kb as they are.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
What llmgw org, keys and users did against the store on a control plane
can now be done remotely and by automation: the tree read, added to,
renamed, moved and emptied; keys issued (the key in the answer, once),
listed and revoked, with the scopes' lifetime limits; people put in and
taken out of the tree, their keys in projects they no longer reach
revoked with it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
An adapter now has an owner (org, team, project, user or key): only callers
there see it, and to anyone else it is a model that does not exist, absent
from /v1/models too. A training job's owner defaults to the one collection
its pairs come from, must be able to read every collection they come from,
and pairs from a knowledge base are never made public. ctl train publish
keeps the GGUF or PEFT files on the mirror, which accepts uploads now, and
sets the owned adapter after the usual architecture check.
The knowledge bases' cache_salt follows the collections searched rather
than the organization, so two teams of one organization no longer share
cached passages.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A job names the catalog model the adapter is for, the safetensors weights to
train on, the node and the MiB of a card it needs, and question/answer pairs.
The control plane sends it when the node's agent is there and nothing else
trains on it; the agent trains with its installed vLLM's torch and a pinned
overlay of peft and accelerate (no second environment), as the engines'
user, on the card with that much free — beside an engine, if it leaves that
much — converts the adapter to GGUF with the installed llama.cpp's own
conversion code when the model is served by llama.cpp, and sends what it
made back in pieces, kept in the store to download. Progress, loss and peak
card memory are reported as it goes; a node that goes fails its job.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A chat model of the cluster reads each chunk and writes questions a person
might ask of it with the answers it holds, streamed as NDJSON a chunk at a
time, for people to correct before an adapter is trained on it. A chunk that
gave no pairs says so on its own line.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
On an organization, team, project or key, the narrowest winning: llmgw ctl
kb default, POST /api/v1/kb/defaults, and the console's Knowledge screen. A
request's own X-Llmgw-Knowledge overrides it and none turns it off. A default
never refuses a request: a collection the caller cannot read is left out, and
a failed search answers without passages. Removing a collection takes it out
of every default.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Collections made for an organization, team, project or person, their
dimension asked of the embedding model; granted and revoked by path, never
outside their organization; their documents listed and removed; and a search
an operator can try. In the OpenAPI document.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
judge ask showed Qwen3Guard's controversial verdict as "safe (Violent)"; it
now says controversial, which a policy's judge.controversial counts. The
stray-judge note called a judge no policy asks any more "served as a model
clients use"; a model with role: guard is now said to be a judge no policy
asks.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Llama Guard 3 1B could not tell ordinary coding requests from harmful ones:
on the PoC it scored "continue" 0.51, "continue the code above" 0.89 and
"how do I kill all child processes in bash" 0.92 unsafe, against 0.97 to
1.00 for harmful requests, at Q4_K_M and Q8_0 alike, with its own template.
A site had "continue" refused. Qwen3Guard-Gen 0.6B gave the ordinary ones
0.15 at the most and the harmful ones 1.00, in 0.8 GB on CPUs.
- format qwen3guard: its prompt written out as its template writes it, for
requests and answers, and its Safe / Unsafe / Controversial verdict read;
controversial counts as the policy's judge.controversial says, safe by
default.
- judge.models: judges asked in turn, the first that answers deciding; a
failure is recorded against the judge that failed. guard judge use sets
the order, replacing categories none of the judges names.
- known judges (Qwen3Guard 0.6B/4B/8B, Llama Guard 1B/8B): guard judge
enable serves any of them, --gpu the 4B on the roomiest GPU class as a
standard model; the leader fetches and serves one a policy names that the
catalog lacks.
- server init installs qwen3guard-0.6b with the baseline's categories.
- a judge reads a long text by its start and end, which fit its context,
rather than overflowing it and refusing the request under fail: closed.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Issue #3 asked for commands to stop and start the system, and 05aa21c gave
only one machine's services. Now:
- llmgw stop sets serving.stopped in the cluster's settings, live: the
reconciler wants every model at no replicas, freeing every GPU, and the
gateway answers every POST under /v1/ with 503 system_stopped. The control
planes, agents and mirror keep running, and no model's definition changes.
- llmgw start clears it; every model is placed again as it asks.
- llmgw restart has every agent restart over its stream (RestartAgent), then
the other control planes over ssh, standbys before a leader, then this
one; engines keep serving.
- llmgw status is the cluster's summary, saying when it is stopped.
One machine's services moved to llmgw service status|start|stop|restart.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
doctor sums findings up as two readinesses - the node's, which decides
whether it joins, and multi-node, its fabrics for replicas spanning nodes -
prints fabric findings in a section of their own, and gives both in --json.
node add says the multi-node one. NodeView.multi_node says whether a node's
declared fabrics are up, naming adapters that are down, and ctl nodes shows
it beside the fabric.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A model's replicas restarted one at a time, always. RestartPace says how
many restart at once: MaxSurge beside themselves (replacement first),
MaxUnavailable stopped first (no room needed, out while loading); the
reconciler begins that many per model per pass. The admin API takes
max_surge and max_unavailable on POST /api/v1/restart.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
NodeView carries engine_versions and compute_capabilities; ctl nodes shows
llamacpp b10991 and 6000-24g (7.5). A profile's engine_version restricts it
to nodes whose engine version starts with it, and explain-placement says
which version a node has, or which engines it has when it lacks the one
asked for.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
llama.cpp's start-up output is read as a shard becomes ready: the devices it
used, its backend, and the layers it offloaded. That goes up with READY in a
new ShardStatus.compute, is kept on the shard, and is shown by the admin
API, ctl replicas (ON) and the console (COMPUTE). A shard given GPUs whose
engine says it found no usable GPU or offloaded no layer is stopped and
failed, even where nvidia-smi cannot be asked.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
guard.enabled (unset is on) makes every policy check nothing while false,
live: llmgw ctl guard off/on set it in the cluster's settings, and ctl
status, ctl guard list and the guardrails page say when they are off.
A refusal by a judge names the hazard it saw - judge: S6,Specialized
Advice - and the verdict is kept with the request in a new usage column,
guard_rule, shown by ctl request, the request log and the guardrails page.
llmgw ctl guard judge ask has a judge read a text, past the cache, and shows
its raw answer and how it is read; the endpoint is kept out of the audit so
no text is recorded.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
llmgw ctl guard judge status lists each judge model the policies ask:
in the catalog, as a judge, replicas ready, its last failure to answer, and
what is wrong in words. enable serves the missing one through model serve -
Llama Guard 3 1B on CPUs, role guard, under the name the policies give it -
with --replace for a model of that name that is not a judge; the console has
it under Do. GET /api/v1/guard/judges, and the summary's judges, put the
problem on ctl status and the console's Overview.
A Llama Guard file served from the mirror page is added as a judge, under
the name the policies ask, rather than as a model clients use the policies
never find. ctl says plainly when the API answers with a page.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Everything in server.yaml that is not one machine's own is now a versioned
document in the store (cluster_settings), the same on every control plane.
The first start against a store imports the file's cluster keys, with the
baseline guard policy when there is none; after that those keys in a file
are ignored, with a warning.
Each control plane polls the document's version and its own server.yaml's
hash. A change is validated and applied: guard live (Gate.Replace), anything
else by a graceful restart that systemd brings back, standbys first and the
leader 30s later. A version that does not load on a machine is not applied;
at start the newest one that loads is used, so a bad edit cannot keep every
control plane down.
llmgw ctl config show/get/set/unset/edit/history/rollback, the admin API
under /api/v1/settings, and the console's Settings screen, which layers the
store's document over the machine's file, write it. Commands beside the
control plane that read cluster keys (init, node add, server add, backup,
upgrade) read the layered configuration; init --bundle writes offline to
the store once it holds the settings.
A standby that becomes the leader re-reads models, engine choices and
facility holds from the store.
Retires appendGuardIfMissing: the import does it.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A binary installed by hand made ctl upgrade say this machine already ran
the release and leave the old server running. And a node had 15 seconds
to answer an upgrade the control plane gives five minutes, so a node that
was upgrading stopped the run.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The console never mentioned them. A Guardrails view shows each policy with
its mode, fail behaviour and checks, whether its judge models have replicas
ready, where policies are attached (attach and detach from it), and what
they did in a window. The admin API gains GET /api/v1/guard/events, and GET
/api/v1/guard says what each policy does.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A control plane being stopped held every agent's stream for the thirty
seconds of a graceful shutdown, so the standby led within four seconds and
had no nodes for thirty. The agent server is now closed, not drained. A
control plane that loses its lease while it lives on lets its agents go,
rather than keeping nodes the new leader cannot reach.
ctl status and the console's Overview say which control plane leads, which
stand by, and whether the floating address is on the leader. The console
adds a control plane (Do → Add a control plane), asking for the machine and
the floating address. server add says when the mirror would refuse the new
control plane.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Conflicts with facility-aware placement (config, control, admin API routes,
store test tables) all keep both; the generated reference and OpenAPI
document regenerated.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
