PrizmDoc® v14.6 Preview Release - Updated
PrizmDoc Worker Overview / Worker API Admin Guide / Deploy AI Hub to Kubernetes
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    Deploy AI Hub to Kubernetes
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    Resources Used in PrizmDoc Deployment

    In addition to the core workload resources needed for a functioning installation, various additional capabilities can be supported through the instantiation of one or more process manager instances and supporting workers.

    The AI Hub provides PrizmDoc with AI capabilities when paired with a Process Manager instance.

    AI Hub

    AI Hub can be created as a standard deployment. Supplying the string YES in the ACCEPT_EULA environment variable signifies that you accept the worker's license agreement.

    You will also need to provide URLs where workers can locate the Process Manager's internal API and PrizmDoc Server endpoints.

    Example

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: accusoft-ai-hub
    spec:
      replicas: 1
      selector:
        matchLabels:
          app: accusoft-ai-hub
      template:
        metadata:
          labels:
            app: accusoft-ai-hub
        spec:
          containers:
          - name: ai-hub
            image: accusoft/ai-hub:<TBD: Version Number>
            env:
            - name: LOG_LEVEL
              value: "info"
            - name: PROCESS_MANAGER_INTERNAL_URL
              value: "http://accusoft-process-manager-internal:80"
            - name: WORKFILE_SERVICE_URL
              value: "http://prizmdoc-server.prizmdoc.svc:18681"
            - name: ACCEPT_EULA
              value: "YES"
            resources:
              limits:
                cpu: 1000m
                memory: 1000Mi
              requests:
                cpu: 1000m
                memory: 1000Mi
            livenessProbe:
              httpGet:
                path: /health
                port: 4100
              initialDelaySeconds: 1
              periodSeconds: 30
              timeoutSeconds: 5
            ports:
            - name: internal
              containerPort: 4100