# -- Default values for chart vllm-omni
# -- Declare variables to be passed into your templates.

# -- HuggingFace model ID to serve
model: "Tongyi-MAI/Z-Image-Turbo"

# -- Image configuration
image:
  # -- Image repository
  repository: "vllm/vllm-omni"
  # -- Image tag
  tag: "v0.16.0"
  # -- Override the container command entirely. If empty, the chart constructs
  # -- it automatically from model + omniArgs.
  command: []
  # -- Optional environment variables for the container
  env: []
  # -- Security context override
  securityContext: {}

# -- Container port
containerPort: 8000
# -- Service name (auto-generated from release name if empty)
serviceName:
# -- Service port
servicePort: 80
# -- Additional ports configuration
extraPorts: []

# -- Number of replicas
replicaCount: 1

# -- Deployment strategy configuration
deploymentStrategy: {}

# -- Resource configuration
resources:
  requests:
    # -- Number of CPUs
    cpu: 4
    # -- CPU memory
    memory: 24Gi
    # -- Number of GPUs
    nvidia.com/gpu: 1
  limits:
    # -- Number of CPUs
    cpu: 4
    # -- CPU memory
    memory: 24Gi
    # -- Number of GPUs
    nvidia.com/gpu: 1

# -- GPU model types for node affinity scheduling (optional)
# -- Leave empty to schedule on any GPU node. Set to restrict to specific GPU types.
# -- Example: ["NVIDIA-A100-SXM4-40GB"]
gpuModels: []

# -- vllm-omni specific CLI arguments
omniArgs:
  # -- Additional raw CLI flags appended to the serve command (list of strings)
  extraArgs: []
  # -- Enable VAE slicing for memory optimization
  vaeUseSlicing: false
  # -- Enable VAE tiling for memory optimization
  vaeUseTiling: false
  # -- Enable CPU offloading for diffusion models
  enableCpuOffload: false
  # -- Number of GPUs for diffusion inference (empty = auto)
  numGpus:
  # -- Path to deploy config file (empty = auto-detected from model)
  deployConfigPath:
  # -- Cache backend: none, tea_cache, or cache_dit
  cacheBackend: "none"
  # -- Default sampling params as a JSON string
  defaultSamplingParams:
  # -- Worker backend: multi_process or ray
  workerBackend: "multi_process"

# -- HuggingFace token for gated models (optional)
hfToken: ""

# -- Shared memory size for PyTorch multiprocessing
shmSize: "8Gi"

# -- Model cache configuration (HuggingFace downloads)
modelCache:
  # -- Use a PersistentVolumeClaim for model cache (recommended for production)
  enabled: true
  # -- Storage size for the PVC
  storageSize: "50Gi"
  # -- Storage class name (empty = cluster default)
  storageClassName: ""
  # -- Access modes
  accessModes:
    - ReadWriteOnce

# -- Autoscaling configuration
autoscaling:
  # -- Enable autoscaling
  enabled: false
  # -- Minimum replicas
  minReplicas: 1
  # -- Maximum replicas
  maxReplicas: 10
  # -- Target CPU utilization for autoscaling
  targetCPUUtilizationPercentage: 80
  # targetMemoryUtilizationPercentage: 80

# -- ConfigMap data (key-value pairs injected as environment variables)
configs: {}

# -- Secrets data (key-value pairs, base64-encoded automatically)
secrets: {}

# -- External ConfigMaps/Secrets references
externalConfigs: []

# -- Custom Kubernetes objects
customObjects: []

# -- PodDisruptionBudget max unavailable
maxUnavailablePodDisruptionBudget: ""

# -- Additional init containers
extraInit:
  initContainers: []

# -- Additional sidecar containers
extraContainers: []

# -- Startup probe configuration
# -- Protects slow-starting containers. Liveness and readiness probes
# -- do not start until the startup probe succeeds.
# -- failureThreshold * periodSeconds = max startup time (40 * 30 = 1200s = 20 min)
startupProbe:
  # -- HTTP check configuration
  httpGet:
    # -- Path to check
    path: /health
    # -- Port to check (uses named port to stay in sync with containerPort)
    port: "container-port"
  # -- Failures before killing the container
  failureThreshold: 40
  # -- How often to perform the probe
  periodSeconds: 30

# -- Readiness probe configuration
readinessProbe:
  # -- How often to perform the probe
  periodSeconds: 10
  # -- Failures before marking unready
  failureThreshold: 3
  # -- HTTP check configuration
  httpGet:
    # -- Path to check
    path: /health
    # -- Port to check (uses named port to stay in sync with containerPort)
    port: "container-port"

# -- Liveness probe configuration
livenessProbe:
  # -- Failures before restarting
  failureThreshold: 3
  # -- How often to perform the probe
  periodSeconds: 15
  # -- HTTP check configuration
  httpGet:
    # -- Path to check
    path: /health
    # -- Port to check (uses named port to stay in sync with containerPort)
    port: "container-port"

# -- Ingress configuration
ingress:
  # -- Enable Ingress
  enabled: false
  # -- Ingress class name (e.g., nginx, traefik)
  ingressClassName: ""
  # -- Hostname for the Ingress rule
  host: "vllm-omni.example.com"
  # -- Additional annotations
  annotations: {}
  # -- TLS configuration
  tls: []
  #  - secretName: vllm-omni-tls
  #    hosts:
  #      - vllm-omni.example.com

# -- Node selector for pod scheduling
nodeSelector: {}

# -- Tolerations for pod scheduling
tolerations: []

# -- Labels applied to all resources
labels:
  app: "vllm-omni"