With slurm.users llmgw, each project is a Slurm account, its organization's
and team's above it, with the project's members and its team's and
organization's on it; slurm.conf holds a job to its user's accounts. The
controller's agent keeps them with sacctmgr, only what it made, and reports
the jobs that ended in the last day; the leader records each once, its
GPU-hours (core-hours without cards) priced at auth.gpu_hour_cost into its
project's usage as model slurm/PARTITION.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
auth.gpu_hour_cost (and core_hour_cost) is what an hour of a GPU (a core)
costs the operator. The leader keeps, by the hour, the GPU- and core-hours
each model's replicas hold (held_1h); llmgw ctl prices suggest spreads a
model's over the tokens it served, an output token counted as four input
ones and a cached prompt token as a tenth of one, and --apply writes the
prices into auth.pricing. Idle hours are in the cost, so a model held and
little used comes out dear; one held and billed nothing is shown with what
it held.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
slurm.containers (ctl slurm containers on) has every Slurm machine's agent
install enroot from NVIDIA's release and build pyxis against its own
Slurm, both pinned and checked against their digests, and on GPU machines
nvidia-container-cli from NVIDIA's repository. enroot keeps each user's
containers under /run/enroot and /var/lib/enroot, needing no login
session, with the shared path in every container. The leader has Slurm
load pyxis only once every machine reports it: plugstack.conf's
"required" fails every job on a machine without the plugin.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Tried on the PoC: lending cuda01, the one GPU node, its model had nowhere
else to go and waited out the drain's five-minute grace, while ctl slurm
status said only "1 replica(s) still to move off". It now says the time
that replica is stopped at. Also recorded: Slurm on a GPU node, tried on
cuda01 (gres, ConstrainDevices, accounting of gres/gpu).
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Setup asks for webhooks, but one left empty was never mentioned again: a
lost node or a judge down was told nobody. With no notify.webhooks in the
cluster's settings, ctl status and the console's Overview say so, and how
to set one. BACKLOG: the judge's refusal after a placement change, tried
again on idle VMs, did not happen; a cold judge's first answer is 2-3x
slower but inside its budget.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
slurm.shared mounts the site's NFS export, has an llmgw node export the path
over NFS to the Slurm machines alone (2049 in the firewall), or looks for a
file system the site mounts. slurm.users "llmgw" makes each active account a
Linux user on every Slurm machine: login from its e-mail, a UID from 200000
kept in slurm_users and never reused, its home on the shared path, its SSH
keys from the portal's Profile (or ctl slurm users keys) read by sshd from
/etc/llmgw/ssh-keys. server init --slurm chooses /shared from the first
machine and llmgw's users; --slurm-shared and --slurm-users change that.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Since 23.11 Slurm runs badly without accounting storage: the main
scheduler passes every job by as InvalidAccount. slurmdbd takes MySQL or
MariaDB only, so the controller's agent installs MariaDB beside it,
answering that machine alone, makes the database and its user (the
password made from the munge key, never on a command line), runs
slurmdbd and adds the cluster, all before slurmctld. A MariaDB that was
on the machine before keeps its settings. slurm.conf accounts the jobs
there, with what each used from its cgroup and the cards, and the
priority is multifactor again. Port 6819 joins Slurm's in the firewall.
ctl slurm status and the console say whether slurmdbd runs; the install
screen, server init --slurm and the guide say what is put where.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
internal/control/slurmsvc tells each node what it is, writes slurm.conf
and gres.conf from the nodes' reports and the inventory, and moves each node
of slurm.nodes between llmgw and Slurm: lent, drained of replicas first, then
resumed in Slurm; taken back, drained in Slurm and cordoned in llmgw until
its last job step ends. Kept every tick from the settings and the agents'
reports, so a new leader carries on. A broken Slurm never keeps a node from
llmgw. GET /api/v1/slurm; ctl slurm status, setup, lend, reclaim, off.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The mirror page's form began every GGUF model at 4096 tokens, the
console's at 4096 or the plan's figure. Both now start at what the model
was trained for, cut to the most whose KV cache fits beside the weights
where the form places it; the mirror page's slots are as many of that, up
to four, as the room left holds. Plan carries the trained context.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
A profile's replicas, set on any of a model's profiles, is how many of its
replicas run there; the scaling becomes the sum. The reconciler starts the
ones short of their profile before stopping the ones over, so a change of
split never runs fewer. ctl model replicas sets them, adding a profile on
CPUs to a GGUF model; the router already fills the higher-priority pool
first, which the CPU profile is put below.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Each agent measures one core's memory rate beside the whole machine's; the
estimate takes a replica's threads at about one core's rate each, up to the
machine's, calibrated by llama-bench on the PoC. The serve form shows it
beside a card's, warns when slow, and asks for the CPU on purpose when a
reply would take minutes; ctl model plan, the console and serve jobs say
it too.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Each router's per-counter request and token counts, this minute's and the
last, ride the standby's two-second exchange with the leader. The leader
answers each standby with everyone else's sum, its own included, and puts
the standbys' sum in force on its own router; each limiter adds the
others' counts to its sliding window.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A standby follows the leader's Ready replicas over the agent port, every
two seconds, and reports back the replicas its router used and the
on-demand models it was asked for. No engine keys travel: every control
plane derives them from the cluster secret. Budgets are raised to the
store's every 30 s. Unheard from the leader for a minute, a standby
passes /v1 on as before. Off by default.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
max_output on POST /api/v1/models/{name}/context, --max-output on ctl model
context, and a field in the console's Context length… form. Alone it changes
only the catalog's limit, which the router holds max_tokens to, and starts no
replica again; with a context it is set with it, never past it.
Strata's context is now changed like the others', through its setup's
--context, which writes the engine's start script at each start. Neither
needs a model removed and added again any more.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
The busy figure is nvidia-smi's utilization.gpu: the share of time any
kernel ran, which a kernel on one SM fills. On cuda01 decode read 92% busy
while the SMs had work 69% of the time and issued on 18% of their cycles.
Busy is now said to be that, and beside it: each card's draw against its
power limit (efficiency table, fleet and node charts, the console's GPU
work chart), and where the profiling counters can be read, SMs active, SM
occupancy, tensor cores and DRAM (llmgw_gpu_*_active_percent), from NVML's
GPM on Hopper and later or a dcgm-exporter on the node
(discovery.dcgm_exporter). The GPU map colours by work by default and keeps
busy as a mode. A MIG instance is never published with its card's profile.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
llmgw ctl model gpus MODEL N [--profile P] [--in-place],
POST /api/v1/models/{name}/gpus and the console's GPUs…: how many cards of
one node each replica uses. Tensor parallel for vLLM, SGLang and
TensorRT-LLM, held to the model's KV heads (modelplan.SplitsHeads, now one
rule for the planner and this); the layers split for llama.cpp, its old
--tensor-split dropped. Refused for a count no node has, for cards that
would not hold the weights and the context, and for engines on one card.
The replicas start again beside the old ones; with no room beside them the
command says so, and --in-place stops each first.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
ctl model context MODEL TOKENS [--slots N], POST /api/v1/models/{name}/context
and the console's Context length…: the catalog, the engine's arguments and
the KV memory change together, refused past the trained context or what the
cards hold, then the replicas restart one by one.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
From review.
- /profile asked before signing in keeps its query for ten minutes, and
the sign-in (password or OIDC) returns to it: VS Code's sign-in state
came back lost, and the confirmation came every time. Only /profile is
ever returned to.
- The extension keeps an https gateway at https when a link names it by
plain http (a proxy ending TLS unannounced), so the key is never sent in
the clear. The install command says --force, since dev builds share a
version and VS Code kept the old one.
- Every frame of every install recording is checked for a key, a
password or a private key, not only the page.
- The admin API document again matches the API: f94d902's
MCPServerRequest.clear was not in it.
- CHANGELOG for this round's fixes.
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>
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>
