Added tests for the new Optic vector functions.

marklogic-client-api/src/test/java/com/marklogic/client/test/rows/VectorTest.java

@@ -0,0 +1,124 @@
+package com.marklogic.client.test.rows;
+
+import com.fasterxml.jackson.databind.node.ArrayNode;
+import com.marklogic.client.FailedRequestException;
+import com.marklogic.client.expression.PlanBuilder;
+import com.marklogic.client.row.RowRecord;
+import com.marklogic.client.test.junit5.RequiresML12;
+import com.marklogic.client.type.ServerExpression;
+import com.marklogic.client.type.XsDoubleSeqVal;
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.BeforeEach;
+import org.junit.jupiter.api.Disabled;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.extension.ExtendWith;
+
+import java.util.List;
+
+import static org.junit.jupiter.api.Assertions.*;
+
+@ExtendWith(RequiresML12.class)
+class VectorTest extends AbstractOpticUpdateTest {
+
+	XsDoubleSeqVal sampleVector;
+	XsDoubleSeqVal twoDimensionalVector;
+	ServerExpression invalidVector;
+
+	@BeforeEach
+	void beforeEach() {
+		sampleVector = op.xs.doubleSeq(1.2, 3.4, 5.6);
+		twoDimensionalVector = op.xs.doubleSeq(1.2, 3.4);
+		invalidVector = op.xs.string("InvalidVector");
+		rowManager.withUpdate(false);
+	}
+
+	@Test
+	void vectorFunctionsHappyPath() {
+		PlanBuilder.ModifyPlan plan =
+			op.fromView("vectors", "persons")
+				.bind(op.as("sampleVector", sampleVector))
+				.bind(op.as("cosineSimilarity", op.vec.cosineSimilarity(op.col("embedding"),op.col("sampleVector"))))
+				.bind(op.as("dotProduct", op.vec.dotProduct(op.col("embedding"),op.col("sampleVector"))))
+				.bind(op.as("euclideanDistance", op.vec.euclideanDistance(op.col("embedding"),op.col("sampleVector"))))
+				.bind(op.as("dimension", op.vec.dimension(op.col("sampleVector"))))
+				.bind(op.as("normalize", op.vec.normalize(op.col("sampleVector"))))
+				.bind(op.as("magnitude", op.vec.magnitude(op.col("sampleVector"))))
+				.bind(op.as("get", op.vec.get(op.col("sampleVector"), op.xs.integer(2))))
+				.bind(op.as("add", op.vec.add(op.col("embedding"),op.col("sampleVector"))))
+				.bind(op.as("subtract", op.vec.subtract(op.col("embedding"),op.col("sampleVector"))))
+				.bind(op.as("base64Encode", op.vec.base64Encode(op.col("sampleVector"))))
+				.bind(op.as("base64Decode", op.vec.base64Decode(op.col("base64Encode"))))
+				.bind(op.as("subVector", op.vec.subvector(op.col("sampleVector"), op.xs.integer(1), op.xs.integer(1))))
+				.select(
+					op.col("cosineSimilarity"), op.col("dotProduct"), op.col("euclideanDistance"),
+					op.col("name"), op.col("dimension"), op.col("normalize"),
+					op.col("magnitude"), op.col("get"), op.col("add"), op.col("subtract"),
+					op.col("base64Encode"), op.col("base64Decode"), op.col("subVector")
+				)
+				.limit(5);
+		List<RowRecord> rows = resultRows(plan);
+		assertEquals(2, rows.size());
+		rows.forEach(row -> {
+//			 Simple a sanity checks to verify that the functions ran. Very little concern about the actual return values.
+			double cosineSimilarity = row.getDouble("cosineSimilarity");
+			assertTrue((cosineSimilarity > 0) && (cosineSimilarity < 1),"Unexpected value: " + cosineSimilarity);
+			double dotProduct = row.getDouble("dotProduct");
+			Assertions.assertTrue(dotProduct > 0, "Unexpected value: " + dotProduct);
+			double euclideanDistance = row.getDouble("euclideanDistance");
+			Assertions.assertTrue(euclideanDistance > 0, "Unexpected value: " + euclideanDistance);
+			assertEquals(3, row.getInt("dimension"));
+			assertEquals(3, ((ArrayNode) row.get("normalize")).size());
+			double magnitude = row.getDouble("magnitude");
+			assertTrue( magnitude > 0, "Unexpected value: " + magnitude);
+			assertEquals(3, ((ArrayNode) row.get("add")).size());
+			assertEquals(3, ((ArrayNode) row.get("subtract")).size());
+			assertFalse(row.getString("base64Encode").isEmpty());
+			assertEquals(3, ((ArrayNode) row.get("base64Decode")).size());
+			assertEquals(5.6, row.getDouble("get"));
+			assertEquals(1, ((ArrayNode) row.get("subVector")).size());
+		});
+	}
+
+	@Test
+	void cosineSimilarity_DimensionMismatch() {
+		PlanBuilder.ModifyPlan plan =
+			op.fromView("vectors", "persons")
+				.bind(op.as("sampleVector", twoDimensionalVector))
+				.bind(op.as("cosineSimilarity", op.vec.cosineSimilarity(op.col("embedding"),op.col("sampleVector"))))
+				.select(op.col("name"), op.col("summary"), op.col("cosineSimilarity"));
+		Exception exception = assertThrows(FailedRequestException.class, () -> resultRows(plan));
+		String actualMessage = exception.getMessage();
+		assertTrue(actualMessage.contains("Server Message: VEC-DIMMISMATCH"), "Unexpected message: " + actualMessage);
+		assertTrue(actualMessage.contains("Mismatched dimension: Vector dimensions must be equal"), "Unexpected message: " + actualMessage);
+	}
+
+	@Test
+	void cosineSimilarity_InvalidVector() {
+		PlanBuilder.ModifyPlan plan =
+			op.fromView("vectors", "persons")
+				.bind(op.as("sampleVector", invalidVector))
+				.bind(op.as("cosineSimilarity", op.vec.cosineSimilarity(op.col("embedding"),op.col("sampleVector"))))
+				.select(op.col("name"), op.col("summary"), op.col("cosineSimilarity"));
+		Exception exception = assertThrows(FailedRequestException.class, () -> resultRows(plan));
+		String actualMessage = exception.getMessage();
+		assertTrue(actualMessage.contains("Server Message: XDMP-ARGTYPE"), "Unexpected message: " + actualMessage);
+		assertTrue(actualMessage.contains("arg2 is not of type vec:vector"), "Unexpected message: " + actualMessage);
+	}
+
+	@Test
+	@Disabled("See ticket MLE-15508")
+	void vectorScore() {
+		PlanBuilder.ModifyPlan plan =
+			op.fromView("vectors", "persons")
+				.bind(op.as("vectorScore", op.vec.vectorScore(op.xs.unsignedInt(1), op.xs.doubleVal(2))))
+				.select(op.col("vectorScore"))
+				.limit(5);
+		List<RowRecord> rows = resultRows(plan);
+		assertEquals(2, rows.size());
+		rows.forEach(row -> {
+			double vectorScore = row.getDouble("vectorScore");
+			assertTrue(vectorScore > 0, "Unexpected value: " + vectorScore);
+		});
+	}
+
+}

test-app/src/main/ml-data/optic/vectors/alice.json

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+{
+	"person": {
+		"name": "Alice",
+		"summary": "About Alice",
+		"embedding": [
+			1.1,
+			2.2,
+			3.3
+		]
+	}
+}

test-app/src/main/ml-data/optic/vectors/bob.json

@@ -0,0 +1,11 @@
+{
+	"person": {
+		"name": "Bob",
+		"summary": "Below Bob",
+		"embedding": [
+			9.9,
+			8.8,
+			7.7
+		]
+	}
+}

test-app/src/main/ml-schemas/tde/vector.xml

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+<template xmlns="http://marklogic.com/xdmp/tde">
+	<context>/person</context>
+	<directories><directory>/optic/vectors/</directory></directories>
+	<rows>
+		<row>
+			<schema-name>vectors</schema-name>
+			<view-name>persons</view-name>
+			<columns>
+				<column>
+					<name>name</name>
+					<scalar-type>string</scalar-type>
+					<val>name</val>
+				</column>
+
+				<column>
+					<name>summary</name>
+					<scalar-type>string</scalar-type>
+					<val>summary</val>
+				</column>
+
+				<column>
+					<name>embedding</name>
+					<scalar-type>vector</scalar-type>
+					<val>vec:vector(embedding)</val>
+					<dimension>3</dimension>
+					<invalid-values>reject</invalid-values>
+				</column>
+			</columns>
+		</row>
+	</rows>
+</template>