chore: update README to include new Helm values (#369)

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Robert Gracey 2023-05-25 00:27:54 +10:00 committed by GitHub
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@ -608,47 +608,69 @@ It should work, however you need to make sure you give enough resources to the c
LocalAI can be installed inside Kubernetes with helm.
<details>
By default, the helm chart will install LocalAI instance using the ggml-gpt4all-j model without persistent storage.
1. Add the helm repo
```bash
helm repo add go-skynet https://go-skynet.github.io/helm-charts/
```
1. Create a values files with your settings:
```bash
cat <<EOF > values.yaml
2. Install the helm chart:
```bash
helm repo update
helm install local-ai go-skynet/local-ai -f values.yaml
```
> **Note:** For further configuration options, see the [helm chart repository on GitHub](https://github.com/go-skynet/helm-charts).
### Example values
Deploy a single LocalAI pod with 6GB of persistent storage serving up a `ggml-gpt4all-j` model with custom prompt.
```yaml
### values.yaml
deployment:
image: quay.io/go-skynet/local-ai:latest
# Adjust the number of threads and context size for model inference
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:
threads: 14
contextSize: 512
# Set the pod requests/limits
resources:
limits:
cpu: 4000m
memory: 7000Mi
requests:
cpu: 100m
memory: 6000Mi
# Add a custom prompt template for the ggml-gpt4all-j model
promptTemplates:
# The name of the model this template belongs to
ggml-gpt4all-j.bin.tmpl: |
This is my custom prompt template...
### Prompt:
{{.Input}}
### Response:
# Model configuration
models:
# Don't re-download models on pod creation
forceDownload: false
# List of models to download and serve
list:
- url: "https://gpt4all.io/models/ggml-gpt4all-j.bin"
# Optional basic HTTP authentication
basicAuth: base64EncodedCredentials
# Enable 6Gb of persistent storage models and prompt templates
persistence:
enabled: true
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
```
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>
## Supported OpenAI API endpoints