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docs: update helm chart instructions

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mudler 2023-04-30 23:24:28 +02:00
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@ -153,26 +153,47 @@ Currently LocalAI comes as container images and can be used with docker or a con
### Run LocalAI in Kubernetes
LocalAI can be installed inside Kubernetes with helm.
<details>
The local-ai Helm chart supports two options for the LocalAI server's models directory:
1. Basic deployment with no persistent volume. You must manually update the Deployment to configure your own models directory.
Install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == false`.
2. Advanced, two-phase deployment to provision the models directory using a DataVolume. Requires [Containerized Data Importer CDI](https://github.com/kubevirt/containerized-data-importer) to be pre-installed in your cluster.
First, install the chart with `.Values.deployment.volumes.enabled == false` and `.Values.dataVolume.enabled == true`:
1. Add the helm repo
```bash
helm install local-ai charts/local-ai -n local-ai --create-namespace
helm repo add go-skynet https://go-skynet.github.io/helm-charts/
```
Wait for CDI to create an importer Pod for the DataVolume and for the importer pod to finish provisioning the model archive inside the PV.
Once the PV is provisioned and the importer Pod removed, set `.Values.deployment.volumes.enabled == true` and `.Values.dataVolume.enabled == false` and upgrade the chart:
1. Create a values files with your settings:
```bash
helm upgrade local-ai -n local-ai charts/local-ai
cat <<EOF > values.yaml
deployment:
image: quay.io/go-skynet/local-ai:latest
env:
threads: 4
contextSize: 1024
modelsPath: "/models"
# Optionally create a PVC, mount the PV to the LocalAI Deployment,
# and download a model to prepopulate the models directory
modelsVolume:
enabled: true
url: "https://gpt4all.io/models/ggml-gpt4all-j.bin"
pvc:
size: 6Gi
accessModes:
- ReadWriteOnce
auth:
# Optional value for HTTP basic access authentication header
basic: "" # 'username:password' base64 encoded
service:
type: ClusterIP
annotations: {}
# If using an AWS load balancer, you'll need to override the default 60s load balancer idle timeout
# service.beta.kubernetes.io/aws-load-balancer-connection-idle-timeout: "1200"
EOF
```
This will update the local-ai Deployment to mount the PV that was provisioned by the DataVolume.
3. Install the helm chart:
```bash
helm repo update
helm install local-ai go-skynet/local-ai -f values.yaml
```
Check out also the [helm chart repository on GitHub](https://github.com/go-skynet/helm-charts).
</details>