A multimodal model is loaded with the `mmproj` found beside its weights --
which is how a repository publishes the pair -- and an attached image rides
in the request as an `image_url` data URI, so it reaches a model on another
machine without the file going there. Nothing is done for a model without a
projector: no captioning, no OCR, no second model.
Whether a session takes pictures is measured rather than assumed:
`/props`'s `modalities.vision` from the server that loaded the model, in
three states, because a model still coming off disk has genuinely not said.
Unknown is offered rather than refused -- a control withheld because nobody
could ask goes missing from sessions that would have taken it. The answer
reaches the phone twice per model as `Event::Images`, so the photo button is
withdrawn the moment a model with vision is left rather than at whatever
later point the session row is fetched again.
A message carrying an image a model cannot read is stopped rather than
stripped: `llama-server` refuses the whole request over one image part, and
a message sent without its picture would be answered as though the picture
had never been mentioned. The phone will not attach one, and the driver
refuses it again at the three moments the answer can first exist -- at the
door, when a message queued behind a loading model is read, and at the tool
boundary a steer enters by. An earlier turn's image folds into a line of
words for a model without vision, so switching a conversation onto one does
not end it.
A projector is filtered out of the models a provider *offers*, since a
session started on one is a server that cannot load it; it stays in the
machine's own model list, where a file on a disk is managed.
Verified against ggml-org/SmolVLM-256M-Instruct-GGUF, local and over ssh:
"In this picture there is a red circle." Switching that session to
Qwen3-0.6B reports `refused`, refuses the next picture with the reason, and
still answers an ordinary message.
A llama.cpp session had its own `llama-server`: two sessions on one model
held two copies of it in memory, a model change bought a load only that
session benefited from, and the process was a session's to end. A machine's
models are now served by one `llama-server` in **router mode** -- no `-m`,
a preset file naming models and their flags, a child server per model asked
for, and each request routed by its `model` field. So one server per model
with that model's own settings is what a machine runs, while this backend
has one process, one port and one record per machine to keep track of.
The record is the mechanism every other driver already uses, so a restart
adopts it; a session records the same pid in its own directory as
`Detail::Shared`, and `process::signal` refuses to signal one of those --
which is what keeps stopping, deleting or cleaning up after one session
from unloading a model every other session is using. Nothing stops a router
on its own. That is deliberate (a loaded model is minutes of disk) and it is
why the machines tab now has a card per provider that opens its own screen:
how each model is loaded, how many stay in memory, Unload, and Stop.
How a model is *loaded* therefore belongs to the model on its machine rather
than to a session -- context size, GPU layers, threads, slots, speculative
decoding -- written into the preset as llama-server's own argument names.
Saving them re-reads that file, which unloads the model; that is the change
taking effect, and the dialog says so before you save. What stays a
session's is everything that rides on a request, including which tools it
offers: the router hosts one set for the machine and the choice is a filter
applied here, so it costs no reload (2,181 tokens of prompt with all seven,
698 with none).
Verified end to end against the scratch backend and the emulator: two
sessions sharing one loaded model with one child process, a second session
joining it with a 26ms prefill, a backend restart adopting the router and
answering with the prompt cache intact, the same over ssh to this VM, a
model's settings reaching the running server, Unload, and Stop leaving every
session `exited` with no error line.
iris-ai