package io.qdrant.client;

import com.google.common.primitives.Floats;

import io.qdrant.client.grpc.Points.DenseVector;

import io.qdrant.client.grpc.Points.Document;

import io.qdrant.client.grpc.Points.Image;

import io.qdrant.client.grpc.Points.InferenceObject;

import io.qdrant.client.grpc.Points.MultiDenseVector;

import io.qdrant.client.grpc.Points.SparseVector;

import io.qdrant.client.grpc.Points.Vector;

import java.util.ArrayList;

import java.util.List;

import java.util.stream.Collectors;

/** Convenience methods for constructing {@link Vector} */

public final class VectorFactory {

private VectorFactory() {}

/**

* Creates a vector from a list of floats

*

* @param values A map of vector names to values

* @return A new instance of {@link Vector}

*/

public static Vector vector(List<Float> values) {

return Vector.newBuilder()

.setDense(DenseVector.newBuilder().addAllData(values).build())

.build();

}

/**

* Creates a vector from a list of floats

*

* @param values A list of values

* @return A new instance of {@link Vector}

*/

public static Vector vector(float... values) {

return Vector.newBuilder()

.setDense(DenseVector.newBuilder().addAllData(Floats.asList(values)).build())

.build();

}

/**

* Creates a sparse vector from a list of floats and integers as indices

*

* @param vector The list of floats representing the vector.

* @param indices The list of integers representing the indices.

* @return A new instance of {@link Vector}

*/

public static Vector vector(List<Float> vector, List<Integer> indices) {

return Vector.newBuilder()

.setSparse(SparseVector.newBuilder().addAllValues(vector).addAllIndices(indices).build())

.build();

}

/**

* Creates a vector from a document for cloud inference.

*

* @param document The document to vectorize.

* @return A new instance of {@link Vector}

*/

public static Vector vector(Document document) {

return Vector.newBuilder().setDocument(document).build();

}

/**

* Creates a vector from an image for cloud inference.

*

* @param image The image to vectorize.

* @return A new instance of {@link Vector}

*/

public static Vector vector(Image image) {

return Vector.newBuilder().setImage(image).build();

}

/**

* Creates a vector from an inference object.

*

* @param object The inference object to vectorize.

* @return A new instance of {@link Vector}

*/

public static Vector vector(InferenceObject object) {

return Vector.newBuilder().setObject(object).build();

}

/**

* Creates a multi vector from a nested list of floats

*

* @param vectors The nested list of floats representing the multi vector.

* @return A new instance of {@link Vector}

*/

public static Vector multiVector(List<List<Float>> vectors) {

List<DenseVector> denseVectors =

vectors.stream()

.map(v -> DenseVector.newBuilder().addAllData(v).build())

.collect(Collectors.toList());

return Vector.newBuilder()

.setMultiDense(MultiDenseVector.newBuilder().addAllVectors(denseVectors).build())

.build();

}

/**

* Creates a multi vector from a nested array of floats

*

* @param vectors The nested array of floats representing the multi vector.

* @return A new instance of {@link Vector}

*/

public static Vector multiVector(float[][] vectors) {

List<DenseVector> denseVectors = new ArrayList<>();

for (float[] vector : vectors) {

denseVectors.add(DenseVector.newBuilder().addAllData(Floats.asList(vector)).build());

}

return Vector.newBuilder()

.setMultiDense(MultiDenseVector.newBuilder().addAllVectors(denseVectors).build())

.build();

}

}