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vllm-omni/examples/online_serving/chart-helm/values.yaml
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2026-03-09 16:02:23 +00:00

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# -- 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 stage configs file (empty = auto-detected from model)
stageConfigsPath:
# -- 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"