apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization
# Explicit allowlist, matching k8s/apps/api. Anything added to this directory
# and not listed here is silently dropped — no error, no drift shown.
#
# These five were adopted from live state on 2026-08-15; they had been applied
# by hand and carried no ArgoCD ownership. Each was exported and verified with
# `kubectl diff -f <file>` returning empty before the Application below was
# created, so the first sync was a no-op rather than a redeploy. Re-verify that
# way after any edit here: a GPU predictor restart is a weights reload measured
# in tens of seconds, not a rolling update.
resources:
  # clef-flash.yaml is NOT listed: the model cannot run on this cluster.
  #
  # Clef needs SGLang v0.5.22 or newer, and SGLang publishes that only on CUDA 13
  # (the last CUDA 12 tag is v0.5.19-cu129, which predates Clef support). CUDA 13
  # dropped Volta kernels, and every GPU here is a Tesla V100 (sm_70):
  #
  #   torch.AcceleratorError: CUDA error: no kernel image is available for
  #   execution on the device
  #
  # SGLang also states sm75 as its floor: the README hardware list omits V100,
  # sm75 support was removed in sgl-project/sglang#9207, and FlashInfer needs
  # sm75+. So no SGLang build exists that has both Clef and Volta kernels, and
  # no flag or dtype change bridges that gap.
  #
  # Re-add it when the model gets an Ampere-or-newer GPU. The manifest itself is
  # kept in git (k8s/apps/llm-serving/clef-flash.yaml) with the same reasoning.
  # ornith and reasoning are live but unmanaged: their manifests were never committed
  # to this directory, so listing them made `kustomize build` fail and left the whole
  # Application in ComparisonError. Remove the entries rather than the models. The
  # Application runs with prune=false, so an object that is no longer in the desired
  # state is left alone, not deleted. Re-export both from live state when they are
  # next edited.
  - embeddings.yaml
  - reranker.yaml
  - qwen-cpu.yaml
  - networkpolicy.yaml
# No namespace transformer: every file sets its own, and the transformer would
# rewrite metadata.namespace on anything cross-namespace added later.