feat(kserve): install KServe

2025-11-10 21:31:35 +09:00
parent 27de65dd37
commit 2b0687330c
14 changed files with 1974 additions and 0 deletions
--- a/examples/kserve-mlflow-iris/04-test-inference-job.yaml
+++ b/examples/kserve-mlflow-iris/04-test-inference-job.yaml
@@ -0,0 +1,146 @@
+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