Install Prompts in an on-prem environment (optional)

Installing Prompts in an on-prem environment requires installing Adala, our data labeling agent microservice.

You only need to complete these steps if you want to use Prompts. For more information, see our Prompts overview.

Prerequisites

• Kubernetes cluster v1.24 or later
• Helm v3.8.0 or later
• Docker CLI (for logging into Docker Hub)

Resource requirements

Before installing, ensure your Kubernetes cluster can provide the following minimum resources for Adala:

Resource	Requirement
CPU	6 cores
Memory	12 GB

1. Authenticate to Docker Hub and validate access

You will need your Docker Hub username and password. If you do not have them, request access from the HumanSignal team.

Log in to DockerHub to access the private OCI repository:

docker login -u CUSTOMER_USERNAME

When prompted, enter your Docker Hub password.

Then verify your credentials and access:

helm pull oci://registry-1.docker.io/heartexlabs/adala

Expected output:

Pulled: registry-1.docker.io/heartexlabs/adala:X.X.X
Digest: sha256:***************************************************

2. Create a Kubernetes secret for image pulling

Create a Kubernetes secret to allow your cluster to pull private Adala images:

kubectl create secret docker-registry heartex-pull-key \
  --docker-server=https://index.docker.io/v2/ \
  --docker-username=CUSTOMER_USERNAME \
  --docker-password=CUSTOMER_PASSWORD

3. Prepare your custom values file

Create a file named custom.values.yaml with the following contents:

adala-app:
  deployment:
    image:
      tag: 20250428.151611-master-592e818
      pullSecrets:
        - heartex-pull-key
adala-worker:
  deployment:
    image:
      tag: 20250428.151611-master-592e818
      pullSecrets:
        - heartex-pull-key

4. Create a dedicated namespace for Adala

Create a dedicated namespace prompt for Adala:

kubectl create namespace prompt

5. Install the Adala Helm chart

Run the following command to install Adala using your custom values:

helm install lse oci://registry-1.docker.io/heartexlabs/adala --values custom.values.yaml

6. Validate that Adala is running

Check if all pods in the prompt namespace are in the Running or Completed state:

kubectl get pods -n prompt

You should see output where all pods have STATUS set to Running, for example:

NAME                                  READY   STATUS    RESTARTS       AGE
adala-adala-app-d4564ffd7-gtmhx       1/1     Running   0              100m
adala-adala-kafka-controller-0        1/1     Running   0              110m
adala-adala-kafka-controller-1        1/1     Running   0              111m
adala-adala-kafka-controller-2        1/1     Running   0              113m
adala-adala-redis-master-0            1/1     Running   0              125m
adala-adala-worker-5d87f97f76-mq952   1/1     Running   0              111m

If any pod is not running, you can investigate further:

kubectl describe pod <pod-name> -n prompt

or

kubectl logs <pod-name> -n prompt

7. Update the Label Studio values.yaml file

You will need to update the global section of your Label Studio Enterprise values.yaml file to include the following:

• Add the Adala endpoint, which will allow Label Studio to connect to Adala.
• Add the Prompts feature flag, to enable Prompts visibility within Label Studio.

global:
  extraEnvironmentVars:
    PROMPTER_ADALA_URL: http://adala-adala-app.prompt:8000
  featureFlags:
    fflag_feat_all_dia_835_prompter_workflow_long: true

Note the following for PROMPTER_ADALA_URL:

• prompt is the namespace where Adala is installed.
• adala-adala-app is the name of the Adala service automatically created by the Helm release.
• Port 8000 is the default port where Adala listens.

After updating the values file, redeploy Label Studio to apply the changes.