/admin/mcp, for administrators only, since a server's credential reaches
whatever it guards: each server's state, who has been granted its tools,
its rate, the headers it is sent by name with the sealed ones marked, and
its address; adding one with a bearer token or another header kept in the
store; testing it with its credential and listing its tools; granting them
to a team, project, org, person or key, written into that level's limits
beside its other grants and its rate and budget; revoking; changing;
replacing the credential; turning off and on; removing; and how a person
points an agent at the gateway's /mcp with a key of their own. English and
Turkish. The secret's field is named so the audit line redacts it.
The admin API's server merge and test are package functions now,
adminapi.MCPServerFrom and adminapi.TestMCPServer, shared by both.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Measuring it in the startup scan held every agent half a second or more
before registering, which on a shared CI runner was past the failover
tests' wait. Now it runs once a process, in the background, the first time
it is asked for, and Heartbeat.mem_bandwidth_gbs carries it when known;
the control plane keeps the last figure and a heartbeat without one leaves
it. The agent's tests do not measure.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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>
Judged by the nodes as they are now, through modelplan.Options, the
planner that serving a model uses: GGUF at Q4_K_M from the parameter count,
safetensors at the size the registry's dtype breakdown gives (packed AWQ,
GPTQ and MXFP4 at four bits), FP8 only where a card has compute capability
8.9, MLX safetensors never. A picture model is judged against one card. A
cluster with cards asks the registry for safetensors too, a hundred at a
time; one without asks for GGUF only. The page says what it judged by: the
largest card, its capability, the most RAM on one node.
On a repository's page a file set no node holds is marked with what it
needs, against what the best node offers, and has no Fetch button.
Tried against the PoC's seven nodes and Hugging Face's trending hundred:
63 shown, the rest too big for one 24 GB Turing card or FP8.
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>
The same text again was answered from what the engine kept of the last
reading, in a tenth of the time: the check read 4.9 s, then 0.5 and 0.5.
Each judgment now begins with a line of its own.
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>
Found on a fresh HA install with a judge machine: the leader saw the
policy's judge missing while init was still fetching it, served one
itself, and its entry replaced init's, so a second judge ran off the
judge machine. The keeper now waits ten minutes after it starts, and a
serve job it starts gives way to a model added meanwhile (AddNew).
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
The judges' machine was selected by the judge's profile, but any other
model could still be placed beside it. A node labelled llmgw.role now
takes only profiles whose selector asks for that role.
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>
CI run 394, on a commit that changed only BACKLOG.md, failed with a data
race in TestAVisionModelIsServedWithItsProjectorBesideIt. The serve job's
goroutine wrote j.Request without the lock (since efffdb6, which sized
embedding slots), while Get's snapshot read the job under it. Every other
write to a running job holds the lock. It did not reproduce in 30 runs
here; the race detector's trace names this write and that read.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A v0.14.6 install on fewer than eight cores refused every request until
its judge was given cores by hand, and upgrading did not change that. The
judge keeper, on the leader, now finds a judge whose entry is exactly what
init before v0.14.7 wrote: one llama.cpp CPU profile, an 8192 context and
nothing else, 2 or 4 GB, none to two cores. It gives the judge 2 GB,
--cache-ram 0 and cores by init's rule through modelsvc.SetProfiles, then
restarts its ready replicas. The replica count is left as it is. A judge
whose entry differs is left alone, and the log says so once.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
On a 4-core single-machine install, `ctl model resources` was run on the
judge (to two cores) and on the starter (to none), then both restarted.
The judge's restart was refused: its replacement fit on no node even with
its old replica stopped, because the starter still held its two cores. A
restart now waits for other restarts under way (queued, retiring or
draining) when their going would make room, up to DrainGrace.
A drained replica was also kept until its model had enough live replicas,
and a replica being restarted that still answers did not count. So with
replicas restarted one after another, each drained one waited out the
five-minute grace, holding its room.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Measured again after the store fixes. Cutting the store primary's power no
longer hung requests, but leadership moved anyway: the lease had lapsed for
everyone while Patroni promoted the standby, and a standby asked first. The
new leader then spent about 25 s without its nodes, and so without its
judges.
A standby that saw the store out of reach now leaves the lease alone for one
renew round after the store returns. The default lease is 10 s, and a node
detects a control plane that died silently in 8 s (5 s idle, 3 s ping)
rather than 15.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
140 named 150 a store member, 150 named itself a control plane: Prometheus
asking both scraped 150 twice and counted its every series twice, and asked
of 140 alone while 150 led it lost every node. Each control plane now lists
all of them as control planes before the store's members, so two answers
agree and a target is scraped once. The shipped prometheus.yml says to
scrape and ask every control plane.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Apertus 70B with a 65536-token pool, and then 8B with 131072, on a 24 GB
card loaded their weights and failed to make their context on every start,
the 8B taking the card from the 70B each time only to fail. ctl model serve
now shrinks a pool the card cannot hold beside the weights (KV cache from
the GGUF's shape, 90% of the card, a gigabyte for the engine), saying so,
and refuses weights that do not fit at all; the portal's serve form refuses
such a pool and says the largest that fits.
The mirror page removed the 70B's weights while the catalog still had the
model, whose replicas went on loading the node's copy with nothing said.
Removing weights a catalog model loads is refused, naming the model.
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>
ctl model serve served one as a chat model: no --embedding, four slots, a
512-token batch, embeddings unset, and a chat smoke test it could not
pass. A GGUF that pools (<arch>.pooling_type), or --embeddings, gets
--embedding, 32 slots of 1024 tokens unless sized otherwise, a batch that
holds a whole passage, the embeddings capability, and one vector asked for
as its smoke test (canaries and updates too). An import of a hundred
thousand chunks had gone at the pace of four slots with the card a third
busy.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
On one card shared by flux and sf3d, a mesh asked for after a picture
waited out the picture model's five minutes of protection and two of idle.
on_demand.evict_after_idle and on_demand.min_lifetime set those for the
cluster, in force on the leader as they change; unset keeps 2m and 5m.
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>
flux-schnell and triposr come with llmgw as presets: their workflow,
custom nodes, packages and licence as they were found and tried on the
PoC, and a profile that says the card it needs rather than a class, so the
entry places on any site's cards. TripoSR's workflow is built in, with the
LLMGWPrepareForMesh node that keeps a picture's background out of the
mesh, which the copy in the document had left out.
`ctl model add PRESET` adds one, and has the nodes install ComfyUI when
the cluster's settings name none; `ctl model presets` lists them; the
console's add-model dialog offers them beside a definition file. A
ComfyUI build is now also checked to keep its order on a Turing card, so
a node's installed cu13 is not replaced by the cu126 build.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The VLM is to come first on the one card. Its class makes it take the card
from flux, triposr or sf3d when asked for, but idle eviction ignored class:
a 3D job two minutes into a lull would have taken the card from it. Idle
eviction offers only replicas of no higher class than the model wanting
room, and the wait such a model is told runs to the holder's idle timeout.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Removed and added again to give it a licence, qwen3-vl-8b came back loading
by itself: its name was still on the wanted list from before. A model that
leaves the catalog leaves the list too.
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>
After a control plane restart flux, adopted and asked for by nobody, had no
last use and so was never idle enough to evict: a 3D job waited out its
whole fifteen minutes with no estimate. It counts as used at adoption, as it
is already counted as wanted then; a replica in use is reported by the
router within seconds.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A 3D job waiting for the picture model to give up the one card had an empty
progress; its client could not tell waiting from stuck. The control plane
says which model holds the cards and when it lets go, plus the waiting
model's last start; the 503 carries it as headers, and a job keeps it as
progress {state: waiting_gpu, held_by, eta_seconds}.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
flux evicted to make room for triposr was placed again two seconds later:
still on the wanted list, and first in the catalog, it took back the card
it had just given up, and the 3D job went on waiting. Its last replica
evicted, it leaves the list until it is asked for again.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A 3D job asked for straight after a picture, on a cluster with one card,
failed at once with "cannot be placed": flux held the card, too freshly
started to evict. The cards coming back when an on-demand model goes idle
makes it a wait, so the request is told to retry and the job waits.
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 control plane that has just started or become leader has heard no
requests, and read the on-demand replicas its nodes report as wanted by
nobody: it drained every one of them at every failover. An adopted replica
of an on-demand model now gets a whole idle timeout from its adoption.
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>
