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fix/dev-python/python-upper-bound
12
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
  kevinveenbirkenbachandClaude Opus 5
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d7eb59e051 |
fix(litellm): freeze the CLI test's routing contract where the stack renders
Job 104155149593 failed its own CLI test with
[FAIL] svc-ai-ollama is not deployed yet the gateway publishes
['qwen2.5:0.5b']
In that round ollama is deployed and the variant enables it, so the gateway was
right and the probe was wrong. templates/test.env.j2 renders through
lookup('template') in run_one.yml, which evaluates in the current play host's
scope, while config.yaml.j2 renders through _render_one_template.yml with
delegate_to STACK_HOST and run_once. On a worker the backend flags read false
and the probe compared its own view against a gateway built from another one.
The three flag-derived values are now frozen next to the config render, with
the same delegate_to plus run_once. Which host run_once elects does not matter;
what matters is that it is the same host for both, and that follows from the
same construct in the same play.
CLI_LOCAL_CID stays per host.
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kevinveenbirkenbachandClaude Opus 5
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b18710e188 |
fix(litellm): publish a backend only when the gateway's own flag enables it
Job 104155149606 died at the warm request with
litellm.APIConnectionError: OllamaException - Cannot connect to host
ollama:11434 [Connect call failed ('192.168.244.10', 11434)]
192.168.244.10 is not ollama. It is the manager node on the lab bridge: the
name never resolved through the overlay, because the litellm task was attached
to ingress, litellm and postgres and to nothing else. The lmstudio round is the
control, where the same replica does carry the lmstudio network.
The attachment comes from _is_consumer, which reads svc-ai-litellm's own
services.<backend>.enabled and .shared. Variant 1 pins both false. The config
template meanwhile asked `'svc-ai-ollama' in group_names`, which answers a
different question: is ollama deployed anywhere in the round. It is, six edges
away, because litellm pulls postgres, postgres pulls tor, tor pulls the mirror,
the mirror pulls prometheus and prometheus declares flowise, which declares
ollama. So the gateway advertised a route it had no network for.
The template and LITELLM_CHAT_MODEL_SERVED now read the same two flags the
network attachment reads, through one constant each. Publication and routing
cannot diverge any more, and in a variant that declines a deployed backend the
warm task no longer runs at all.
LITELLM_CHAT_MODEL and LITELLM_BACKEND_ROLES are deliberately left alone.
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kevinveenbirkenbachandClaude Opus 5
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786899700f |
feat(litellm): serve OpenAI, Anthropic and OpenRouter from declared keys
The gateway could reach exactly one remote provider, through a bare
OPENROUTER_API_KEY group_var with an empty-string default and an `{% if %}`
around a single hardcoded model entry. OpenAI and Anthropic had no path at all.
All three are now declared in roles/svc-ai-litellm/meta/secrets.yml, which
mapping.py already calls the application config schema, so a key lands at
applications.svc-ai-litellm.secrets.credentials.<provider>_api_key like every
other credential. Each carries the `type` and `regex` its value must satisfy and
defaults to the central API.<provider>.api_key block, which keeps one
operator-facing place to fill a provider in while the role owns the shape.
type and regex had to become real to be worth declaring. 192 `validation:`
blocks sit in the role schemas today and not one line of Python enforces them,
so a `regex` would have joined a pile of decoration. validate_supplied_value
now runs on every path a value arrives from outside — the --set override, a
value already in the inventory, and the value standing next to a `default:`.
A generated value stays exempt because the algorithm that produced it is named
by the same schema and generate_value takes no schema argument. min_length is
deliberately left unenforced: the generators ignore it, so holding them to it
would fail where nothing is wrong.
The pattern is written for the paste, not for the vendor. OpenAI moved issuance
from sk- to sk-proj- without notice and Anthropic issues sk-ant-api03-; a schema
pinning a prefix would reject a valid key and abort inventory creation. `\S{20,}`
accepts every form those three issue today and one nobody has announced, and
rejects a trailing newline, an embedded space, a truncated copy and a
<placeholder>. A key pasted into the wrong provider's slot is caught at deploy
instead, where the route it publishes answers nothing.
The gateway iterates one LITELLM_REMOTE_BACKENDS list instead of three `{% if %}`
blocks; config.yaml.j2 and env.j2 read the same list and selectattr('key')
decides. LITELLM_CHAT_MODEL falls back to the first configured remote alias
rather than to a hardcoded openrouter/auto.
For CI the keys travel as INFINITO_API_{OPENAI,ANTHROPIC,OPENROUTER}_KEY through
default.env, the passthrough allowlist, the infinito service in compose.yml, the
workflow env block and the development inventory. The compose leg is not
optional: the env lint rejected the change without it, because a key the
inventory reads but compose does not forward resolves to empty inside the
container with no error. The workflow reads `secrets.X || vars.X` so a variable
works as asked while a secret wins, which matters because a variable is not
masked and the development inventory sets MASK_CREDENTIALS_IN_LOGS: false.
An unset key is not an error anywhere: the provider's routes stay unpublished
and the CLI test asserts their absence rather than skipping.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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kevinveenbirkenbachandClaude Opus 5
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abd6a24b73 |
test(litellm): assert the gateway routes to the backends it actually has
The gateway publishing a model proves nothing about a backend answering it: LM
Studio shipped a published lmstudio/default route for as long as it had no
model to load. This CLI test closes that gap by asking the running gateway what
it serves and comparing it against what the deployment enabled.
templates/test.env.j2 is both the input and the entry point — discover_cli_roles
finds a role by that file and filters on group_names, so the test runs only
where the gateway is deployed. meta/tests.yml names the container service key so
run_one.yml resolves the node holding it in swarm, and allows 600s for a cold
model load.
probe.py runs inside the gateway container, where the API answers on loopback
and the backends resolve by name, and uses the standard library only because
the image ships the litellm app rather than a test toolchain. It asserts that
every declared model is served, that the LM-Studio-only aliases are present
exactly when that backend is deployed, that no Ollama-backed model is published
without Ollama, that LITELLM_CHAT_MODEL is routable, that an empty deployment
publishes nothing, and that a real completion comes back non-empty.
The fourth assertion is the one worth having: LITELLM_CHAT_MODEL is built from
lookup('deployment').inventory while the config is built from this host's
group_names. Two sources for one fact, and this is where they are made to
agree.
The alias list is rendered whether or not LM Studio is deployed. Gating it
would empty the set in exactly the case the negative direction needs, turning
"a route must not stand without its backend" into a vacuous check.
The verdict logic sits in a pure evaluate() so it is exercised without mocks:
four deployment shapes, each with its positive and negative cases, including a
both-backends case that asserts a shared alias proves nothing about LM Studio
and only the exclusive one counts.
files/test/.nocheck is required rather than convenient. role-files-layout sorts
files/ by language while test-e2e-cli stages files/test/ under that fixed path;
the other 29 CLI test directories carry the same marker.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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kevinveenbirkenbachandClaude Opus 5
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dac61edbc6 |
feat(ai): let LM Studio serve the models Ollama serves, under one catalogue
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
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kevinveenbirkenbach
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13f5ca6d95 |
fix(svc-ai-litellm): bound what a local backend may generate
The gateway registered ollama and lmstudio with an rpm cap and nothing else, so a single request could generate without an output limit and hold a worker for as long as the backend kept producing tokens. Requests per minute bound how often a caller may ask, not how much one answer costs. max_output_tokens caps the answer itself. upstream_timeout is the backstop for a wedged backend, not a latency budget, so it sits above every consumer's own budget: the longest wait on the AI path is 360s (discourse-ai.spec.js), with 300s and 240s behind it, and TIMEOUT_FACTOR defaults to 1. At 420s the gateway can only fire once every caller has already given up, which keeps a slow generation from being reported as a gateway error instead of the slow answer it is. openrouter/auto stays unbounded here. It never carried an rpm cap either, and its limits are the provider's rather than ours, so giving it one is a separate decision from closing the local-backend hole. |
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kevinveenbirkenbachandClaude Opus 5
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d9f497688d |
feat(litellm): authenticate the admin UI through Keycloak
The role declared sso.enabled false behind three suppressions, so the checks were switched off rather than satisfied. LiteLLM authenticates its own admin UI instead of sitting behind an oauth2 proxy, so the declaration is flavor oidc and the client id, the three Keycloak endpoints, the proxy base URL and the admin id all render together under one flag: a half-set group would let the gateway fall back to its own form with nothing complaining. The variants pin both states so the matrix runs with and without SSO. The proof has to measure the departure, not the arrival: a gateway ignoring the client id answers /sso/key/generate with its own username and password form and never redirects, so the spec asserts the round trip to Keycloak and back. The guest spec became SSO-aware, since its canonical-domain and password-field assertions only hold where no SSO is configured. Two more gateway defects: the key warm-up ran even where no model was served, falling back to openrouter/auto so the gateway then answered every prompt with 400, and it is now gated on a served-model expression mirroring the model selection itself. A lint requires every declared svc-ai backend to have a model_list branch, because a backend without a route is an alias nobody serves. probe_auth.py proves revocation rather than creation: it mints a throwaway key, revokes it, and fails unless a real consumer key survives. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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kevinveenbirkenbachandClaude Opus 5
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a772115b8c |
refactor(svc-ai-litellm): read the canonical database url and volume target
DATABASE_URL was assembled by hand from five separate database lookups and
string concatenation. That form cannot encode special characters: a password
containing @ or / takes the URL apart. Read
lookup('database', application_id, 'url_full') instead, which the lookup
documents for exactly this.
LITELLM_CONFIG_PATH_DOCKER hardcoded /etc/litellm/config.yaml although
meta/volumes.yml already declares the litellm_config volume. Read its target
so the declaration and its use cannot drift.
Both lookups are established: url_full is documented in database.py and
lookup('volume', ...) is used by 51 roles. litellm ran on these lines
throughout the session, reaching postgres, issuing virtual keys and serving
completions. The evidence is that it worked, not a value-by-value comparison
of the two url forms.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
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kevinveenbirkenbachandClaude Opus 5
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a3ea18c700 |
refactor(compose): finish the context-wired volumes lookups
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kevinveenbirkenbachandClaude Opus 5
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7162b7bf4c |
Merge fork/feature/svc-net-tor into feature/ai-agent-employees
834 commits from the Tor onion-service branch against 299 of ours, from merge base |
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kevinveenbirkenbachandClaude Opus 5
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92c45e2471 |
refactor(openwebui): serve models through the gateway, not the model server
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> |
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kevinveenbirkenbachandClaude Opus 4.8
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ad743bf447 |
feat(svc-ai): add the LiteLLM gateway and the LM Studio backend
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> |