[pull] main from kubeflow:main

catalog/internal/catalog/modelcatalog/loader.go

@@ -329,9 +329,11 @@ func (l *ModelLoader) updateDatabase(ctx context.Context) error {
 					}
 				}
 
-				for _, handler := range l.handlers {
-					handler(ctx, record)
+			for _, handler := range l.handlers {
+				if err := handler(ctx, record); err != nil {
+					glog.Errorf("%s: event handler error: %v", *attr.Name, err)
 				}
+			}
 			}()
 		}
 	}()

catalog/internal/catalog/modelcatalog/performance_metrics.go

@@ -107,6 +107,11 @@ func (pr *performanceRecord) UnmarshalJSON(data []byte) error {
 	if id, ok := raw["id"].(string); ok {
 		pr.ID = id
 	}
+	if pr.ID == "" {
+		if configID, ok := raw["config_id"].(string); ok && configID != "" {
+			pr.ID = configID
+		}
+	}
 	if modelID, ok := raw["model_id"].(string); ok {
 		pr.ModelID = modelID
 	}
@@ -505,19 +510,28 @@ func createAccuracyMetricsArtifact(evalRecords []evaluationRecord, modelID int32
 	// Properties can be empty or contain general metadata
 	properties := []models.Properties{}
 
-	// Create custom properties - simple mapping of benchmark_name to score_value
-	customProperties := []models.Properties{}
-
+	// Create custom properties - simple mapping of benchmark_name to score_value.
+	// Deduplicate by benchmark name: if multiple evaluation records share the same
+	// benchmark, keep the last score encountered. This prevents DB constraint violations
+	// on the (artifact_id, name, is_custom_property) composite primary key.
+	benchmarkScores := make(map[string]float64, len(evalRecords))
 	for _, evalRecord := range evalRecords {
-		// Add the benchmark score as a named property (e.g., "aime24": 63.3333)
 		if score, ok := evalRecord.CustomProperties["score"].(float64); ok {
-			customProperties = append(customProperties, models.Properties{
-				Name:        evalRecord.Benchmark,
-				DoubleValue: &score,
-			})
+			if _, duplicate := benchmarkScores[evalRecord.Benchmark]; duplicate {
+				glog.Warningf("Duplicate benchmark %q for model %d, using latest score", evalRecord.Benchmark, modelID)
+			}
+			benchmarkScores[evalRecord.Benchmark] = score
 		}
 	}
 
+	customProperties := make([]models.Properties, 0, len(benchmarkScores)+1)
+	for benchmark, score := range benchmarkScores {
+		customProperties = append(customProperties, models.Properties{
+			Name:        benchmark,
+			DoubleValue: &score,
+		})
+	}
+
 	// Add overall_average custom property from metadata.json overall_accuracy field
 	if overallAccuracy != nil {
 		customProperties = append(customProperties, models.Properties{

catalog/internal/catalog/modelcatalog/performance_metrics_test.go

@@ -330,6 +330,88 @@ func TestOverallAccuracyToOverallAverage(t *testing.T) {
 	})
 }
 
+func TestCreateAccuracyMetricsArtifact_DuplicateBenchmarks(t *testing.T) {
+	t.Run("duplicate benchmarks are deduplicated using last score", func(t *testing.T) {
+		evalRecords := []evaluationRecord{
+			{Benchmark: "mmlu", CustomProperties: map[string]any{"score": 80.0}},
+			{Benchmark: "aime24", CustomProperties: map[string]any{"score": 63.3}},
+			{Benchmark: "mmlu", CustomProperties: map[string]any{"score": 85.0}},
+		}
+
+		artifact := createAccuracyMetricsArtifact(evalRecords, 1, 100, nil, nil, nil)
+
+		// Count occurrences of each benchmark name
+		benchmarkCounts := map[string]int{}
+		benchmarkScores := map[string]float64{}
+		for _, prop := range *artifact.CustomProperties {
+			benchmarkCounts[prop.Name]++
+			if prop.DoubleValue != nil {
+				benchmarkScores[prop.Name] = *prop.DoubleValue
+			}
+		}
+
+		// "mmlu" should appear exactly once (deduplicated)
+		if benchmarkCounts["mmlu"] != 1 {
+			t.Errorf("expected mmlu to appear once, got %d", benchmarkCounts["mmlu"])
+		}
+
+		// The last score (85.0) should win
+		if benchmarkScores["mmlu"] != 85.0 {
+			t.Errorf("expected mmlu score 85.0, got %v", benchmarkScores["mmlu"])
+		}
+
+		// "aime24" should still be present
+		if benchmarkCounts["aime24"] != 1 {
+			t.Errorf("expected aime24 to appear once, got %d", benchmarkCounts["aime24"])
+		}
+		if benchmarkScores["aime24"] != 63.3 {
+			t.Errorf("expected aime24 score 63.3, got %v", benchmarkScores["aime24"])
+		}
+	})
+
+	t.Run("no duplicates produces all benchmarks", func(t *testing.T) {
+		evalRecords := []evaluationRecord{
+			{Benchmark: "mmlu", CustomProperties: map[string]any{"score": 90.0}},
+			{Benchmark: "aime24", CustomProperties: map[string]any{"score": 63.3}},
+			{Benchmark: "gpqa", CustomProperties: map[string]any{"score": 72.5}},
+		}
+
+		artifact := createAccuracyMetricsArtifact(evalRecords, 1, 100, nil, nil, nil)
+
+		benchmarkNames := map[string]bool{}
+		for _, prop := range *artifact.CustomProperties {
+			benchmarkNames[prop.Name] = true
+		}
+
+		for _, expected := range []string{"mmlu", "aime24", "gpqa"} {
+			if !benchmarkNames[expected] {
+				t.Errorf("expected benchmark %q not found in custom properties", expected)
+			}
+		}
+	})
+
+	t.Run("all records with same benchmark produce single property", func(t *testing.T) {
+		evalRecords := []evaluationRecord{
+			{Benchmark: "mmlu", CustomProperties: map[string]any{"score": 80.0}},
+			{Benchmark: "mmlu", CustomProperties: map[string]any{"score": 82.0}},
+			{Benchmark: "mmlu", CustomProperties: map[string]any{"score": 85.0}},
+		}
+
+		artifact := createAccuracyMetricsArtifact(evalRecords, 1, 100, nil, nil, nil)
+
+		count := 0
+		for _, prop := range *artifact.CustomProperties {
+			if prop.Name == "mmlu" {
+				count++
+			}
+		}
+
+		if count != 1 {
+			t.Errorf("expected exactly 1 mmlu property, got %d", count)
+		}
+	})
+}
+
 func TestEvaluationRecordUnmarshalJSON(t *testing.T) {
 	tests := []struct {
 		name             string

clients/python/pyproject.toml

@@ -24,7 +24,7 @@ aiohttp-retry = "^2.8.3"
 # allows for reentrant event loops (used for sync client) - Python 3.14 compatible
 nest-asyncio2 = "^1.7.1"
 
-huggingface-hub = { version = ">=0.20.1,<1.13.0", optional = true }
+huggingface-hub = { version = ">=0.20.1,<1.14.0", optional = true }
 olot = { version = "^0.1.17", optional = true }
 boto3 = { version = "^1.37.34", optional = true }
 rh-model-signing = { version = "1.0.1", optional = true }

clients/ui/frontend/src/__tests__/cypress/cypress/pages/modelRegistryView/registerAndStoreFields.ts

@@ -48,7 +48,9 @@ class RegisterAndStoreFields {
   }
 
   selectNamespace(name: string) {
-    this.findNamespaceSelectCombobox().scrollIntoView().click({ force: true });
+    this.findNamespaceSelectCombobox().should('not.be.disabled');
+    this.findNamespaceSelectCombobox().scrollIntoView().click();
+    cy.findByRole('listbox').should('be.visible');
     cy.findByRole('option', { name }).click();
   }
 
@@ -66,11 +68,12 @@ class RegisterAndStoreFields {
   }
 
   shouldHaveNamespaceOptions(namespaces: string[]) {
-    this.findNamespaceSelectCombobox().scrollIntoView().click({ force: true });
+    this.findNamespaceSelectCombobox().should('not.be.disabled');
+    this.findNamespaceSelectCombobox().scrollIntoView().click();
     namespaces.forEach((namespace) => {
       cy.findByRole('option', { name: namespace }).should('exist');
     });
-    this.findNamespaceSelectCombobox().scrollIntoView().click({ force: true });
+    this.findNamespaceSelectCombobox().scrollIntoView().click();
     return this;
   }
 
@@ -301,9 +304,18 @@ class RegisterAndStoreFields {
     this.findSourceS3SecretAccessKeyInput().type(secretAccessKey);
   }
 
+  /** Sets model type (required on register page). Uses Predictive by default. */
+  selectModelType(
+    optionName: 'Predictive Model' | 'Generative AI model (Example, LLM)' = 'Predictive Model',
+  ) {
+    cy.get('#register-model-type-toggle').click();
+    cy.findByRole('option', { name: optionName }).click();
+  }
+
   // Convenience method to fill all required fields for submission
   fillAllRequiredFields() {
     this.fillModelName('test-model');
+    this.selectModelType();
     this.fillVersionName('v1.0.0');
     this.fillJobName('my-transfer-job');
     this.fillSourceEndpoint('https://s3.amazonaws.com');

clients/ui/frontend/src/__tests__/cypress/cypress/tests/mocked/modelRegistry/registerAndStoreFields.cy.ts

@@ -331,6 +331,7 @@ describe('Register and Store Fields - Credential Validation', () => {
   it('Should have submit button disabled when S3 access key ID is missing', () => {
     // Fill all fields except S3 access key ID
     registerAndStoreFields.fillModelName('test-model');
+    registerAndStoreFields.selectModelType();
     registerAndStoreFields.fillVersionName('v1.0.0');
     registerAndStoreFields.fillJobName('my-transfer-job');
     registerAndStoreFields.fillSourceEndpoint('https://s3.amazonaws.com');
@@ -349,6 +350,7 @@ describe('Register and Store Fields - Credential Validation', () => {
   it('Should have submit button disabled when S3 secret access key is missing', () => {
     // Fill all fields except S3 secret access key
     registerAndStoreFields.fillModelName('test-model');
+    registerAndStoreFields.selectModelType();
     registerAndStoreFields.fillVersionName('v1.0.0');
     registerAndStoreFields.fillJobName('my-transfer-job');
     registerAndStoreFields.fillSourceEndpoint('https://s3.amazonaws.com');
@@ -367,6 +369,7 @@ describe('Register and Store Fields - Credential Validation', () => {
   it('Should have submit button disabled when OCI username is missing', () => {
     // Fill all fields except OCI username
     registerAndStoreFields.fillModelName('test-model');
+    registerAndStoreFields.selectModelType();
     registerAndStoreFields.fillVersionName('v1.0.0');
     registerAndStoreFields.fillJobName('my-transfer-job');
     registerAndStoreFields.fillSourceEndpoint('https://s3.amazonaws.com');
@@ -385,6 +388,7 @@ describe('Register and Store Fields - Credential Validation', () => {
   it('Should have submit button disabled when OCI password is missing', () => {
     // Fill all fields except OCI password
     registerAndStoreFields.fillModelName('test-model');
+    registerAndStoreFields.selectModelType();
     registerAndStoreFields.fillVersionName('v1.0.0');
     registerAndStoreFields.fillJobName('my-transfer-job');
     registerAndStoreFields.fillSourceEndpoint('https://s3.amazonaws.com');