The catalogue held three models and the development inventory carried a second, CI-only list that both AI roles pulled in through their variant 0. That made the model a variant concern and split one fact across a group_var, an inventory file and two meta files.
AI_LOCAL_MODELS now holds the single entry the CI list held, qwen2.5 0.5b instruct at 531 MB in Q8_0, which lms get is already proven to fetch in this stack. AI_LOCAL_MODELS_CI and both variant overrides are gone, so variant 0 states only container_backup and the memory limits.
The dropped entries have no consumer: llama3, mistral and nomic appear solely in test fixtures that stub the lookups, and nothing requests an embedding model, the only embed matches being the filters that exclude one when picking the chat model. LITELLM_CHAT_MODEL takes the first non-embed alias, so it resolves and LITELLM_USABLE stays true.
Note this changes production, not only CI: a deployment no longer pulls a 7B model or an embedding model. It also shrinks the pre-pull that burned 18796s in job 104622514450 from gigabytes to 531 MB.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
svc-ai-lmstudio had no model-load step at all: tasks/00_core.yml set the
once-flag and the container network, nothing else. The gateway published
lmstudio/default anyway, so the route existed and nothing could answer it.
wp-compose-tor.log:48994 shows the route written into the config, :51770 shows
the warm step reaching qwen2.5:0.5b on Ollama instead, and the green ai-engine
spec ran against that. LM Studio was deployed, published and never prompted.
The pre-pull mirrors the one that works. tasks/01_manager_ops.yml resolves the
hosting node and container id, loops the declared models through
`lms get --yes --gguf`, overlaps them with async/poll and reaps before
playwright, exactly like svc-ai-ollama. That `lms` exists is measured, not
assumed: /app/daemon-run.sh:67 in the image starts ./.bundle/lms server start,
and `lms get --help` documents -y for scripting and --gguf for the format.
Synonymity needs both namespaces in one place. Ollama knows qwen2.5:0.5b, LM
Studio knows qwen2.5-0.5b-instruct, so AI_LOCAL_MODELS carries both per entry:
`alias` is what the gateway publishes and what Ollama pulls, `name` is what
`lms get` resolves. Both roles now reference that one list, and config.yaml.j2
publishes each backend under the alias, routing Ollama to ollama/<alias> and LM
Studio to openai/<name>. The lmstudio loop skips an alias Ollama already
publishes, so two backends never produce a duplicate model_name and Ollama
keeps precedence. lmstudio/default is gone; the model name is now the same
whichever backend answers it.
Ollama's preload_models changes shape from a list of strings to the {alias,
name} entries. Every consumer moves with it: the pull command, the template
loop, and both expressions in 16_ai.yml. An inventory that overrides
`applications.svc-ai-ollama.services.ollama.preload_models` with the old string
list will break at map(attribute='alias'); this is a deliberate shape change,
in the spirit of 7b15c61dfc.
The CI model list is not a property of an installation, so AI_LOCAL_MODELS_CI
lives in inventories/development/default.yml, whose own header scopes that file
to the cross-cutting environment knobs. test_variable_definitions only knew
group_vars, so it reported the constant as undefined; the shipped inventories
are a definition source too, because the deploy CLI bakes them into host_vars,
and the guard's own docstring already claimed "defined somewhere in the
repository".
A latent crash came out of this: `| list | first` raises on an empty sequence,
so a backend deployed without preload models blew up LITELLM_CHAT_MODEL. Ollama
with only embedding models could already hit it; the existing test dodged it by
rendering only _SERVED. `| default('')` now yields the empty string that
_SERVED already reports as false.
Tests: config.yaml.j2 is rendered rather than read, over ollama-only,
lmstudio-only, both and neither, asserting the published model_name set, that
both backends name the same alias, that a shared alias is published once and
routed to Ollama, and that the render is valid YAML. test_litellm_chat_model
gains the lmstudio branch, the no-preload case and the same-model assertion.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Open WebUI talked to Ollama directly. It now speaks the OpenAI-compatible surface of svc-ai-litellm with a per-consumer virtual key, so a second backend or an external provider becomes a gateway config change instead of a role change. A lint keeps future roles off the model servers.
The gateway advertised a hardcoded model list (ollama/llama3, ollama/nomic-embed-text) while the matrix variant preloads smollm2:135m, so it offered only models the backend did not have and hid the one it did. The list is derived from the ollama preload SPOT now.
The chat spec followed the rename: it gates on litellm instead of the removed ollama service flag, and picks the first non-embedding model from /api/models rather than pinning a variant-specific name, so it exercises the chain rather than a fixture.
Routing openwebui through the gateway pulls both model backends into the closure of every role that consumes it, which pushed nextcloud variant 2 over the memory budget. The budget stays at 32/64 GB; instead the matrix variants of svc-ai-ollama and svc-ai-lmstudio now declare the size their test model needs (1g/2g) while the base keeps the 6g/8g that llama3 and mistral require. The budget guard only saw half of that: it replaced the evaluated role with its variant but counted every dependency from meta/services.yml, a combination no matrix round deploys. It now evaluates every variant-carrying role at the same round index, falling back to variant 0, the way the deploy planner does.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Consumers of the model plane speak one OpenAI-compatible endpoint and
carry one virtual key; which backend answers is the gateway's business.
svc-ai-litellm renders its model_list from the round's actual topology,
so an alias only exists when its backend role is in group_names, and it
emits an explicit empty list when no backend is present at all because
LiteLLM rejects a bare model_list: key.
Keys reach the gateway through the per-consumer credential rather than
being minted there: 01_keys.yml probes /key/info and only POSTs
/key/generate on 404, so reruns stay idempotent. The consumer list is
built in 00_core.yml, not inside the included file, because 01_keys.yml
delegates to the hosting node and delegate_to is templated before when.
The gateway declares ollama and lmstudio as consumer flags so the
network renderer attaches it to its own backends; without them it cannot
reach them.
svc-ai-lmstudio runs the headless llmster daemon behind expose only, so
it is reachable from the gateway but never bound on the host, matching
svc-ai-ollama.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
kevinveenbirkenbachandClaude Opus 5