How to deploy with Helm#

This guide provides step-by-step instructions for deploying the Document Summarization Sample Application using Helm.

Prerequisites#

Before you begin, ensure that you have the following prerequisites:

Steps to deploy with Helm#

Following steps should be followed to deploy Document Summarization application using Helm. You can install from source code or pull the chart from Docker hub.

Steps 1 to 3 varies depending on if the user prefers to build or pull the Helm details.

Option 1: Install from Docker Hub#

Step 1: Pull the Specific Chart#

Use the following command to pull the Helm chart from Docker Hub:

helm pull oci://registry-1.docker.io/intel/document-summarization --version 1.0.0

🔍 Refer to the Docker Hub tags page for details on the latest version number to use for the sample application. Use the above specified version for release-1.2.0.

Refer to the release notes for details on the latest version number to use for the sample application.

Step 2: Extract the .tgz File#

After pulling the chart, extract the .tgz file:

tar -xvf document-summarization-<version-no>.tgz

This will create a directory named document-summarization containing the chart files. Navigate to the extracted directory.

cd document-summarization

Step 3: Configure the values.yaml File#

Edit the values.yaml file to set the necessary environment variables. Ensure you set the proxy settings as required.

Key

Description

Example Value

global.proxy.noProxy

NOPROXY

<your-no-proxy>

global.proxy.httpProxy

HTTP PROXY

<your-http-proxy>

global.proxy.httpsProxy

HTTPS PROXY

<your-https-proxy>

global.huggingface.token

Your Hugging Face API token

<your-huggingface-token

global.ui.nodePort

Sets the static port (in the 30000–32767 range)

global.otlp

OTLP Endpoint

<your-otlp-endpoint>

global.llm.llmModelId

Model to be used with ovms

Intel/neural-chat-7b-v3-3 or microsoft/Phi-3.5-mini-instruct

Option 2: Install from Source#

Step 1: Clone the Repository#

Clone the repository containing the Helm chart:

git clone https://github.com/open-edge-platform/edge-ai-libraries.git edge-ai-libraries -b release-1.2.0

Step 2: Change to the Chart Directory#

Navigate to the chart directory:

cd edge-ai-libraries/sample-applications/document-summarization/chart

Step 3: Configure the values.yaml File#

Edit the values.yaml file located in the chart directory to set the necessary environment variables. Refer to the table in Option 1, Step 3 for the list of keys and example values.

Step 4: Build Helm Dependencies#

Navigate to the chart directory and build the Helm dependencies using the following command:

helm dependency build

Common Steps after configuration#

Step 5: Deploy the Helm Chart#

Deploy the Document Summarization Helm chart:

helm install document-summarization . -n <your-namespace>

Note: When deploying OVMS, the OVMS service is observed to take more time than other model serving due to model conversion time.

Step 6: Verify the Deployment#

Check the status of the deployed resources to ensure everything is running correctly

kubectl get pods -n <your-namespace>
kubectl get services -n <your-namespace>

Step 7: Retrieving the Service Endpoint (NodePort and NodeIP)#

To access a docsum-nginx service running in your Kubernetes cluster using NodePort, you need to retrieve:

  • NodeIP – The internal IP of a worker node.

  • NodePort – The port exposed by the service.

Run the following command after replacing <ui-node-port> with your actual values:

  kubectl get nodes -o wide | awk '$2 == "Ready" {print $6 ":<ui-node-port>"; exit}'

Simply copy and paste the output into your browser.

Step 8: Update Helm Dependencies#

If any changes are made to the subcharts, update the Helm dependencies using the following command:

helm dependency update

Step 9: Uninstall Helm chart#

To uninstall helm charts deployed, use the following command:

helm uninstall document-summarization -n <your-namespace>

Verification#

  • Ensure that all pods are running and the services are accessible.

  • Access the application dashboard and verify that it is functioning as expected.

Troubleshooting#

  • If you encounter any issues during the deployment process, check the Kubernetes logs for errors:

    kubectl logs <pod-name>

  • If the PVC created during a Helm chart deployment is not removed or auto-deleted due to a deployment failure or being stuck, it must be deleted manually using the following commands:

    # List the PVCs present in the given namespace
kubectl get pvc -n <namespace>

# Delete the required PVC from the namespace
kubectl delete pvc <pvc-name> -n <namespace>