refactor(demo): remove rhoai function from common.sh (llm-d#588)

Signed-off-by: Raymond Zhao <zhaoeryi@gmail.com>

Author: yizhaodev

examples/deploy-demo/common.sh

@@ -716,157 +716,6 @@ do_deploy_batch_gateway_helm() {
     create_batch_destinationrule
 }
 
-# ── DSC-based Batch Gateway Deployment ──────────────────────────────────
-#
-# do_deploy_batch_gateway_dsc isvc_name [pass_through_headers]
-#
-# Deploys batch-gateway via the LLMBatchGateway CR (operator-managed).
-# Installs dependencies (Redis, PostgreSQL, MinIO/PVC), creates the CR,
-# waits for it to be ready, and sets up HTTPRoute + DestinationRule.
-#
-# Args:
-#   isvc_name             Model / InferenceService name (used in the model URL path)
-#   pass_through_headers  Comma-separated list of HTTP headers to forward (optional, empty = none)
-
-do_deploy_batch_gateway_dsc() {
-    local isvc_name="$1"
-    local pass_through_headers="${2:-}"
-
-    local operator_type="${OPERATOR_TYPE:-rhoai}"
-    local apps_namespace
-    case "${operator_type}" in
-        rhoai) apps_namespace="redhat-ods-applications" ;;
-        odh)   apps_namespace="opendatahub" ;;
-        *)     die "Unknown OPERATOR_TYPE: ${operator_type}" ;;
-    esac
-
-    step "Enabling aigateway + batchGateway in DataScienceCluster..."
-    kubectl patch datasciencecluster default-dsc --type=merge -p '{"spec":{"components":{"aigateway":{"managementState":"Managed","batchGateway":{"managementState":"Managed"}}}}}'
-
-    wait_for_deployment "ai-gateway-operator" "${apps_namespace}" 300s
-    wait_for_deployment "llm-d-batch-gateway-operator" "${apps_namespace}" 300s
-    wait_for_crd "llmbatchgateways.batch.llm-d.ai"
-
-    kubectl get namespace "${BATCH_NAMESPACE}" &>/dev/null || kubectl create namespace "${BATCH_NAMESPACE}"
-    kubectl label namespace "${BATCH_NAMESPACE}" llm-d.ai/gateway-route=true --overwrite
-
-    install_batch_exchange
-    install_batch_postgresql
-    if [ "${BATCH_STORAGE_TYPE}" = "s3" ]; then
-        install_batch_minio
-    else
-        create_batch_pvc
-    fi
-    create_batch_secret
-
-    local internal_gw_svc
-    internal_gw_svc=$(kubectl get svc -n "${BATCH_INTERNAL_GATEWAY_NAMESPACE}" \
-        -l "gateway.networking.k8s.io/gateway-name=${BATCH_INTERNAL_GATEWAY_NAME}" \
-        -o jsonpath='{.items[0].metadata.name}' 2>/dev/null || echo "")
-    [ -z "${internal_gw_svc}" ] && die "No service found for Internal Gateway '${BATCH_INTERNAL_GATEWAY_NAME}'."
-    local model_url="http://${internal_gw_svc}.${BATCH_INTERNAL_GATEWAY_NAMESPACE}.svc.cluster.local/${LLM_NAMESPACE}/${isvc_name}"
-    log "Model URL (via Internal Gateway): ${model_url}"
-
-    local processor_config_yaml=""
-    if [ "${ENABLE_FLOW_CONTROL}" = "true" ]; then
-        processor_config_yaml="    config:
-      inferenceObjective: ${BATCH_FLOW_CONTROL_OBJECTIVE}"
-        log "Flow control: processor will send x-gateway-inference-objective: ${BATCH_FLOW_CONTROL_OBJECTIVE}"
-    fi
-
-    local file_storage_yaml
-    if [ "${BATCH_STORAGE_TYPE}" = "s3" ]; then
-        local minio_endpoint="http://${BATCH_MINIO_RELEASE}.${BATCH_NAMESPACE}.svc.cluster.local:9000"
-        file_storage_yaml="    s3:
-      region: ${MINIO_REGION}
-      bucket: ${MINIO_BUCKET}
-      endpoint: ${minio_endpoint}
-      accessKeyId: ${MINIO_ROOT_USER}
-      prefix: ${MINIO_BUCKET}
-      usePathStyle: true
-      autoCreateBucket: true"
-    else
-        file_storage_yaml="    fs:
-      basePath: /tmp/batch-gateway
-      claimName: ${BATCH_FILES_PVC_NAME}"
-    fi
-
-    local apiserver_batch_api_yaml=""
-    if [ -n "${pass_through_headers}" ]; then
-        local header_items=""
-        IFS=',' read -ra _headers <<< "${pass_through_headers}"
-        for h in "${_headers[@]}"; do
-            header_items="${header_items}
-        - ${h}"
-        done
-        apiserver_batch_api_yaml="    config:
-      batchAPI:
-        passThroughHeaders:${header_items}"
-    fi
-
-    step "Creating LLMBatchGateway CR..."
-    kubectl apply -f - <<EOF
-apiVersion: batch.llm-d.ai/v1alpha1
-kind: LLMBatchGateway
-metadata:
-  name: ${BATCH_INSTANCE_NAME}
-  namespace: ${BATCH_NAMESPACE}
-spec:
-  secretRef:
-    name: ${BATCH_APP_SECRET_NAME}
-  dbBackend: ${BATCH_DB_TYPE}
-  fileStorage:
-${file_storage_yaml}
-  apiServer:
-    replicas: 1
-${apiserver_batch_api_yaml}
-  processor:
-    replicas: 1
-    resources:
-      requests:
-        cpu: 100m
-        memory: 256Mi
-      limits:
-        cpu: "1"
-        memory: 1Gi
-    globalInferenceGateway:
-      url: ${model_url}
-      requestTimeout: ${GW_REQUEST_TIMEOUT}
-      maxRetries: ${GW_MAX_RETRIES}
-      initialBackoff: ${GW_INITIAL_BACKOFF}
-      maxBackoff: ${GW_MAX_BACKOFF}
-${processor_config_yaml}
-  gc:
-    interval: 30m
-  tls:
-    enabled: true
-    certManager:
-      issuerName: ${TLS_ISSUER_NAME}
-      issuerKind: ClusterIssuer
-      dnsNames:
-      - ${BATCH_INSTANCE_NAME}-apiserver
-      - ${BATCH_INSTANCE_NAME}-apiserver.${BATCH_NAMESPACE}.svc.cluster.local
-      - localhost
-EOF
-
-    step "Waiting for LLMBatchGateway to be ready..."
-    kubectl wait llmbatchgateway/${BATCH_INSTANCE_NAME} -n "${BATCH_NAMESPACE}" \
-        --for=condition=Ready --timeout=300s
-    log "LLMBatchGateway is ready."
-
-    step "Waiting for AIGateway to be ready..."
-    kubectl wait aigateway/default-aigateway --for=condition=Ready --timeout=300s
-    log "AIGateway is ready."
-
-    # TODO: Change to die once https://github.com/opendatahub-io/ai-gateway-operator/issues/47 is fixed.
-    step "Waiting for DataScienceCluster to be ready..."
-    kubectl wait dsc/default-dsc --for=condition=Ready --timeout=60s \
-        || warn "DataScienceCluster is not Ready (known issue: github.com/opendatahub-io/ai-gateway-operator/issues/47)"
-
-    create_batch_httproute
-    create_batch_destinationrule
-}
-
 # ── Internal Gateway ──────────────────────────────────────────────────────────
 #
 # Creates a ClusterIP-only Gateway for the batch processor to access LLM