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otwld ollama helm chart banner

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Ollama, get up and running with large language models, locally.

This Community Chart is for deploying Ollama.

Requirements

  • Kubernetes: >= 1.16.0-0 for CPU only

  • Kubernetes: >= 1.26.0-0 for GPU stable support (NVIDIA and AMD)

Not all GPUs are currently supported with ollama (especially with AMD)

Deploying Ollama chart

To install the ollama chart in the ollama namespace:

helm repo add ollama-helm https://otwld.github.io/ollama-helm/
helm repo update
helm install ollama ollama-helm/ollama --namespace ollama

Upgrading Ollama chart

First please read the release notes of Ollama to make sure there are no backwards incompatible changes.

Make adjustments to your values as needed, then run helm upgrade:

# -- This pulls the latest version of the ollama chart from the repo.
helm repo update
helm upgrade ollama ollama-helm/ollama --namespace ollama --values values.yaml

Uninstalling Ollama chart

To uninstall/delete the ollama deployment in the ollama namespace:

helm delete ollama --namespace ollama

Substitute your values if they differ from the examples. See helm delete --help for a full reference on delete parameters and flags.

Interact with Ollama

Examples

  • It's highly recommended to run an updated version of Kubernetes for deploying ollama with GPU

Basic values.yaml example with GPU and two models pulled at startup

ollama:
  gpu:
    # -- Enable GPU integration
    enabled: true
    
    # -- GPU type: 'nvidia' or 'amd'
    type: 'nvidia'
    
    # -- Specify the number of GPU to 1
    number: 1
   
  # -- List of models to pull at container startup
  models:
    pull:
      - mistral
      - llama2

Basic values.yaml example with Ingress

ollama:
  models:
    pull:
      - llama2
  
ingress:
  enabled: true
  hosts:
  - host: ollama.domain.lan
    paths:
      - path: /
        pathType: Prefix
  • API is now reachable at ollama.domain.lan

Upgrading from 0.X.X to 1.X.X

The version 1.X.X introduces the ability to load models in memory at startup, the values have been changed.

Please change ollama.models to ollama.models.pull to avoid errors before upgrading:

ollama:
  models:
    - mistral
    - llama2

To:

ollama:
  models:
    pull:
      - mistral
      - llama2

Helm Values

Key Type Default Description
affinity object {} Affinity for pod assignment
autoscaling.enabled bool false Enable autoscaling
autoscaling.maxReplicas int 100 Number of maximum replicas
autoscaling.minReplicas int 1 Number of minimum replicas
autoscaling.targetCPUUtilizationPercentage int 80 CPU usage to target replica
extraArgs list [] Additional arguments on the output Deployment definition.
extraEnv list [] Additional environments variables on the output Deployment definition. For extra OLLAMA env, please refer to https://github.com/ollama/ollama/blob/main/envconfig/config.go
extraEnvFrom list [] Additionl environment variables from external sources (like ConfigMap)
fullnameOverride string "" String to fully override template
hostIPC bool false Use the host’s ipc namespace.
hostNetwork bool false Use the host's network namespace.
hostPID bool false Use the host’s pid namespace
image.pullPolicy string "IfNotPresent" Docker pull policy
image.repository string "ollama/ollama" Docker image registry
image.tag string "" Docker image tag, overrides the image tag whose default is the chart appVersion.
imagePullSecrets list [] Docker registry secret names as an array
ingress.annotations object {} Additional annotations for the Ingress resource.
ingress.className string "" IngressClass that will be used to implement the Ingress (Kubernetes 1.18+)
ingress.enabled bool false Enable ingress controller resource
ingress.hosts[0].host string "ollama.local"
ingress.hosts[0].paths[0].path string "/"
ingress.hosts[0].paths[0].pathType string "Prefix"
ingress.tls list [] The tls configuration for hostnames to be covered with this ingress record.
initContainers list [] Init containers to add to the pod
knative.containerConcurrency int 0 Knative service container concurrency
knative.enabled bool false Enable Knative integration
knative.idleTimeoutSeconds int 300 Knative service idle timeout seconds
knative.responseStartTimeoutSeconds int 300 Knative service response start timeout seconds
knative.timeoutSeconds int 300 Knative service timeout seconds
lifecycle object {} Lifecycle for pod assignment (override ollama.models startup pulling)
livenessProbe.enabled bool true Enable livenessProbe
livenessProbe.failureThreshold int 6 Failure threshold for livenessProbe
livenessProbe.initialDelaySeconds int 60 Initial delay seconds for livenessProbe
livenessProbe.path string "/" Request path for livenessProbe
livenessProbe.periodSeconds int 10 Period seconds for livenessProbe
livenessProbe.successThreshold int 1 Success threshold for livenessProbe
livenessProbe.timeoutSeconds int 5 Timeout seconds for livenessProbe
nameOverride string "" String to partially override template (will maintain the release name)
namespaceOverride string "" String to override the namespace
nodeSelector object {} Node labels for pod assignment.
ollama.gpu.enabled bool false Enable GPU integration
ollama.gpu.mig.devices object {} Specify the mig devices and the corresponding number
ollama.gpu.mig.enabled bool false Enable multiple mig devices If enabled you will have to specify the mig devices If enabled is set to false this section is ignored
ollama.gpu.number int 1 Specify the number of GPU If you use MIG section below then this parameter is ignored
ollama.gpu.nvidiaResource string "nvidia.com/gpu" only for nvidia cards; change to (example) 'nvidia.com/mig-1g.10gb' to use MIG slice
ollama.gpu.type string "nvidia" GPU type: 'nvidia' or 'amd' If 'ollama.gpu.enabled', default value is nvidia If set to 'amd', this will add 'rocm' suffix to image tag if 'image.tag' is not override This is due cause AMD and CPU/CUDA are different images
ollama.insecure bool false Add insecure flag for pulling at container startup
ollama.models.pull list [] List of models to pull at container startup The more you add, the longer the container will take to start if models are not present pull: - llama2 - mistral
ollama.models.run list [] List of models to load in memory at container startup run: - llama2 - mistral
ollama.mountPath string "" Override ollama-data volume mount path, default: "/root/.ollama"
persistentVolume.accessModes list ["ReadWriteOnce"] Ollama server data Persistent Volume access modes Must match those of existing PV or dynamic provisioner Ref: http://kubernetes.io/docs/user-guide/persistent-volumes/
persistentVolume.annotations object {} Ollama server data Persistent Volume annotations
persistentVolume.enabled bool false Enable persistence using PVC
persistentVolume.existingClaim string "" If you'd like to bring your own PVC for persisting Ollama state, pass the name of the created + ready PVC here. If set, this Chart will not create the default PVC. Requires server.persistentVolume.enabled: true
persistentVolume.size string "30Gi" Ollama server data Persistent Volume size
persistentVolume.storageClass string "" Ollama server data Persistent Volume Storage Class If defined, storageClassName: If set to "-", storageClassName: "", which disables dynamic provisioning If undefined (the default) or set to null, no storageClassName spec is set, choosing the default provisioner. (gp2 on AWS, standard on GKE, AWS & OpenStack)
persistentVolume.subPath string "" Subdirectory of Ollama server data Persistent Volume to mount Useful if the volume's root directory is not empty
persistentVolume.volumeMode string "" Ollama server data Persistent Volume Binding Mode If defined, volumeMode: If empty (the default) or set to null, no volumeBindingMode spec is set, choosing the default mode.
persistentVolume.volumeName string "" Pre-existing PV to attach this claim to Useful if a CSI auto-provisions a PV for you and you want to always reference the PV moving forward
podAnnotations object {} Map of annotations to add to the pods
podLabels object {} Map of labels to add to the pods
podSecurityContext object {} Pod Security Context
readinessProbe.enabled bool true Enable readinessProbe
readinessProbe.failureThreshold int 6 Failure threshold for readinessProbe
readinessProbe.initialDelaySeconds int 30 Initial delay seconds for readinessProbe
readinessProbe.path string "/" Request path for readinessProbe
readinessProbe.periodSeconds int 5 Period seconds for readinessProbe
readinessProbe.successThreshold int 1 Success threshold for readinessProbe
readinessProbe.timeoutSeconds int 3 Timeout seconds for readinessProbe
replicaCount int 1 Number of replicas
resources.limits object {} Pod limit
resources.requests object {} Pod requests
runtimeClassName string "" Specify runtime class
securityContext object {} Container Security Context
service.annotations object {} Annotations to add to the service
service.loadBalancerIP string nil Load Balancer IP address
service.nodePort int 31434 Service node port when service type is 'NodePort'
service.port int 11434 Service port
service.type string "ClusterIP" Service type
serviceAccount.annotations object {} Annotations to add to the service account
serviceAccount.automount bool true Automatically mount a ServiceAccount's API credentials?
serviceAccount.create bool true Specifies whether a service account should be created
serviceAccount.name string "" The name of the service account to use. If not set and create is true, a name is generated using the fullname template
tolerations list [] Tolerations for pod assignment
topologySpreadConstraints object {} Topology Spread Constraints for pod assignment
updateStrategy.type string "Recreate" Deployment strategy can be "Recreate" or "RollingUpdate". Default is Recreate
volumeMounts list [] Additional volumeMounts on the output Deployment definition.
volumes list [] Additional volumes on the output Deployment definition.

Core team

Jean Baptiste Detroyes
     Jean Baptiste Detroyes     
Jean Baptiste Detroyes
     Nathan Tréhout     

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