Kserve with Github URI

# network-policy.yaml
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: allow-all-egress
  namespace: kserve-test
spec:
  podSelector: {}
  policyTypes:
  - Egress
  egress:
  - {}  # 모든 외부 연결 허용

---
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: allow-all-ingress
  namespace: kserve-test
spec:
  podSelector: {}
  policyTypes:
  - Ingress
  ingress:
  - {}  # 모든 내부 연결 허용

# 1. KServe 네임스페이스 생성
apiVersion: v1
kind: Namespace
metadata:
  name: kserve-test

---
# 2. ServiceAccount 생성 (모델 다운로드를 위한 권한)
apiVersion: v1
kind: ServiceAccount
metadata:
  name: model-loader
  namespace: kserve-test

---
# 3. Role 생성
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: model-loader-role
  namespace: kserve-test
rules:
- apiGroups: [""]
  resources: ["pods", "services"]
  verbs: ["create", "get", "list", "watch"]
- apiGroups: ["serving.kserve.io"]
  resources: ["inferenceservices"]
  verbs: ["create", "get", "list", "watch"]

---
# 4. RoleBinding 생성
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: model-loader-binding
  namespace: kserve-test
subjects:
- kind: ServiceAccount
  name: model-loader
  namespace: kserve-test
roleRef:
  kind: Role
  name: model-loader-role
  apiGroup: rbac.authorization.k8s.io

---
# 5. InferenceService 배포
apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
  name: sklearn-from-uri
  namespace: kserve-test
spec:
  predictor:
    serviceAccountName: model-loader
    model:
      modelFormat:
        name: sklearn
      storageUri: "https://github.com/tduffy000/kfserving-uri-examples/blob/master/sklearn/frozen/model.joblib?raw=true"
# storageUri: "https://raw.githubusercontent.com/tduffy000/kfserving-uri-examples/master/sklearn/frozen/model.joblib"
---
# 6. 추론 요청을 위한 샘플 Input (input.json)
{
  "instances": [
    [6.8,  2.8,  4.8,  1.4],
    [6.0,  3.4,  4.5,  1.6]
  ]
}