apiVersion: batch/v1
kind: Job
metadata:
  name: test-iris-inference
  namespace: kserve
spec:
  template:
    spec:
      containers:
      - name: test
        image: python:3.9-slim
        command:
        - /bin/sh
        - -c
        - |
          cat << 'EOF' | python
          import urllib.request
          import json

          # KServe endpoint (v2 protocol)
          url = "http://iris-classifier-predictor.kserve.svc.cluster.local/v2/models/iris-classifier/infer"

          # Iris class names
          class_names = ["setosa", "versicolor", "virginica"]

          # Test samples with expected results
          test_cases = [
              {"data": [5.1, 3.5, 1.4, 0.2], "expected": "setosa"},
              {"data": [6.7, 3.0, 5.2, 2.3], "expected": "virginica"},
              {"data": [5.9, 3.0, 4.2, 1.5], "expected": "versicolor"},
          ]

          print("=" * 60)
          print("Testing Iris Classifier InferenceService")
          print("=" * 60)
          print(f"Endpoint: {url}")
          print()

          for i, test_case in enumerate(test_cases, 1):
              print(f"Test Case {i}:")
              print(f"  Input: {test_case['data']}")
              print(f"  Expected: {test_case['expected']}")

              # v2 protocol payload
              payload = {
                  "inputs": [
                      {
                          "name": "input-0",
                          "shape": [1, 4],
                          "datatype": "FP64",
                          "data": [test_case['data']]
                      }
                  ]
              }

              try:
                  req = urllib.request.Request(
                      url,
                      data=json.dumps(payload).encode('utf-8'),
                      headers={'Content-Type': 'application/json'}
                  )
                  with urllib.request.urlopen(req) as response:
                      result = json.loads(response.read().decode('utf-8'))
                      prediction = result['outputs'][0]['data'][0]
                      predicted_class = class_names[prediction]

                      status = "✓ PASS" if predicted_class == test_case['expected'] else "✗ FAIL"
                      print(f"  Predicted: {predicted_class} (class {prediction})")
                      print(f"  Status: {status}")

              except Exception as e:
                  print(f"  Error: {e}")

              print()

          print("=" * 60)
          print("Test completed")
          print("=" * 60)
          EOF
      restartPolicy: Never
  backoffLimit: 1
---
# Alternative: curl-based quick test
# apiVersion: batch/v1
# kind: Job
# metadata:
#   name: test-iris-inference-curl
#   namespace: kserve
# spec:
#   template:
#     spec:
#       containers:
#       - name: test
#         image: curlimages/curl:latest
#         command:
#         - /bin/sh
#         - -c
#         - |
#           echo "Testing Iris Classifier Inference Service..."
#           echo ""
#           echo "Endpoint: http://iris-classifier-predictor.kserve.svc.cluster.local/v2/models/iris-classifier/infer"
#           echo ""
#           echo "Sending test request with sample data: [5.1, 3.5, 1.4, 0.2]"
#           echo "Expected prediction: class 0 (setosa)"
#           echo ""
#
#           curl -v -X POST \
#             http://iris-classifier-predictor.kserve.svc.cluster.local/v2/models/iris-classifier/infer \
#             -H "Content-Type: application/json" \
#             -d '{
#               "inputs": [
#                 {
#                   "name": "input-0",
#                   "shape": [1, 4],
#                   "datatype": "FP64",
#                   "data": [[5.1, 3.5, 1.4, 0.2]]
#                 }
#               ]
#             }'
#
#           echo ""
#           echo ""
#           echo "Testing with multiple samples..."
#           echo ""
#
#           curl -X POST \
#             http://iris-classifier-predictor.kserve.svc.cluster.local/v2/models/iris-classifier/infer \
#             -H "Content-Type: application/json" \
#             -d '{
#               "inputs": [
#                 {
#                   "name": "input-0",
#                   "shape": [3, 4],
#                   "datatype": "FP64",
#                   "data": [
#                     [5.1, 3.5, 1.4, 0.2],
#                     [6.7, 3.0, 5.2, 2.3],
#                     [5.9, 3.0, 4.2, 1.5]
#                   ]
#                 }
#               ]
#             }'
#
#           echo ""
#       restartPolicy: Never
#   backoffLimit: 1