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2 changes: 2 additions & 0 deletions lucene/CHANGES.txt
Original file line number Diff line number Diff line change
Expand Up @@ -121,6 +121,8 @@ New Features
* GITHUB#14009: Add a new Query that can rescore other Query based on a generic DoubleValueSource
and trim the results down to top N (Anh Dung Bui)

* GITHUB#14729: Support for Re-Ranking Queries using Late Interaction Model Multi-Vectors. (Vigya Sharma, Jim Ferenczi)

Improvements
---------------------
* GITHUB#14458: Add an IndexDeletion policy that retains the last N commits. (Owais Kazi)
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,138 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package org.apache.lucene.document;

import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import java.nio.FloatBuffer;
import org.apache.lucene.util.BytesRef;

/**
* A field for storing multi-vector values for late interaction models.
*
* <p>The value is stored as a binary payload, and can be retrieved using {@link
* LateInteractionField#decode(BytesRef)}. Multi-vectors are expected to have the same dimension for
* each composing token vector. This is stored along with the token vectors in the first 4 bytes of
* the payload.
*
* <p>Note: This field does not ensure consistency in token vector dimensions for values across
* documents.
*/
public class LateInteractionField extends BinaryDocValuesField {

/**
* Creates a new {@link LateInteractionField} from the provided multi-vector matrix.
*
* @param name field name
* @param value multi-vector value
*/
public LateInteractionField(String name, float[][] value) {
super(name, encode(value));
}

/**
* Set multi-vector value for the field.
*
* <p>Value should not be null or empty. Composing token vectors for provided multi-vector value
* should have the same dimension.
*/
public void setValue(float[][] value) {
this.fieldsData = encode(value);
}

/** Returns the multi-vector value stored in this field */
public float[][] getValue() {
return decode((BytesRef) fieldsData);
}

/**
* Encodes provided multi-vector matrix into a {@link BytesRef} that can be stored in the {@link
* LateInteractionField}.
*
* <p>Composing token vectors for the multi-vector are expected to have the same dimension, which
* is stored along with the token vectors in the first 4 bytes of the payload. Use {@link
* LateInteractionField#decode(BytesRef)} to retrieve the multi-vector.
*
* @param value Multi-Vector to encode
* @return BytesRef representation for provided multi-vector
*/
public static BytesRef encode(float[][] value) {
if (value == null || value.length == 0) {
throw new IllegalArgumentException("Value should not be null or empty");
}
if (value[0] == null || value[0].length == 0) {
throw new IllegalArgumentException("Composing token vectors should not be null or empty");
}
final int tokenVectorDimension = value[0].length;
final ByteBuffer buffer =
ByteBuffer.allocate(Integer.BYTES + value.length * tokenVectorDimension * Float.BYTES)
.order(ByteOrder.LITTLE_ENDIAN);
// TODO: Should we store dimension in FieldType to ensure consistency across all documents?
buffer.putInt(tokenVectorDimension);
FloatBuffer floatBuffer = buffer.asFloatBuffer();
for (int i = 0; i < value.length; i++) {
if (value[i].length != tokenVectorDimension) {
throw new IllegalArgumentException(
"Composing token vectors should have the same dimension. "
+ "Mismatching dimensions detected between token[0] and token["
+ i
+ "], "
+ value[0].length
+ " != "
+ value[i].length);
}
floatBuffer.put(value[i]);
}
return new BytesRef(buffer.array());
}

/**
* Decodes provided {@link BytesRef} into a multi-vector matrix.
*
* <p>The token vectors are expected to have the same dimension, which is stored along with the
* token vectors in the first 4 bytes of the payload. Meant to be used as a counterpart to {@link
* LateInteractionField#encode(float[][])}
*
* @param payload to decode into multi-vector value
* @return decoded multi-vector value
*/
public static float[][] decode(BytesRef payload) {
final ByteBuffer buffer = ByteBuffer.wrap(payload.bytes, payload.offset, payload.length);
buffer.order(ByteOrder.LITTLE_ENDIAN);
final int tokenVectorDimension = buffer.getInt();
int numVectors = (payload.length - Integer.BYTES) / (tokenVectorDimension * Float.BYTES);
if (numVectors * tokenVectorDimension * Float.BYTES + Integer.BYTES != payload.length) {
throw new IllegalArgumentException(
"Provided payload does not appear to have been encoded via LateInteractionField.encode. "
+ "Payload length should be equal to 4 + numVectors * tokenVectorDimension, "
+ "got "
+ payload.length
+ " != 4 + "
+ numVectors
+ " * "
+ tokenVectorDimension);
}
var floatBuffer = buffer.asFloatBuffer();
float[][] value = new float[numVectors][];
for (int i = 0; i < numVectors; i++) {
value[i] = new float[tokenVectorDimension];
floatBuffer.get(value[i]);
}
return value;
}
}
Original file line number Diff line number Diff line change
@@ -0,0 +1,183 @@
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package org.apache.lucene.search;

import java.io.IOException;
import java.util.Arrays;
import java.util.Objects;
import org.apache.lucene.document.LateInteractionField;
import org.apache.lucene.index.BinaryDocValues;
import org.apache.lucene.index.LeafReaderContext;
import org.apache.lucene.index.VectorSimilarityFunction;

/**
* A {@link DoubleValuesSource} that scores documents using similarity between a multi-vector query,
* and indexed document multi-vectors.
*
* <p>This is useful re-ranking query results using late interaction models, where documents and
* queries are represented as multi-vectors of composing token vectors. Document vectors are indexed
* using {@link org.apache.lucene.document.LateInteractionField}.
*
* @lucene.experimental
*/
public class LateInteractionFloatValuesSource extends DoubleValuesSource {

private final String fieldName;
private final float[][] queryVector;
private final VectorSimilarityFunction vectorSimilarityFunction;
private final MultiVectorSimilarity scoreFunction;

public LateInteractionFloatValuesSource(String fieldName, float[][] queryVector) {
this(fieldName, queryVector, VectorSimilarityFunction.COSINE, ScoreFunction.SUM_MAX_SIM);
}

public LateInteractionFloatValuesSource(
String fieldName, float[][] queryVector, VectorSimilarityFunction vectorSimilarityFunction) {
this(fieldName, queryVector, vectorSimilarityFunction, ScoreFunction.SUM_MAX_SIM);
}

public LateInteractionFloatValuesSource(
String fieldName,
float[][] queryVector,
VectorSimilarityFunction vectorSimilarityFunction,
MultiVectorSimilarity scoreFunction) {
this.fieldName = Objects.requireNonNull(fieldName);
this.queryVector = validateQueryVector(queryVector);
this.vectorSimilarityFunction = Objects.requireNonNull(vectorSimilarityFunction);
this.scoreFunction = Objects.requireNonNull(scoreFunction);
}

private float[][] validateQueryVector(float[][] queryVector) {
if (queryVector == null || queryVector.length == 0) {
throw new IllegalArgumentException("queryVector must not be null or empty");
}
if (queryVector[0] == null || queryVector[0].length == 0) {
throw new IllegalArgumentException(
"composing token vectors in provided query vector should not be null or empty");
}
for (int i = 1; i < queryVector.length; i++) {
if (queryVector[i] == null || queryVector[i].length != queryVector[0].length) {
throw new IllegalArgumentException(
"all composing token vectors in provided query vector should have the same length");
}
}
return queryVector;
}

@Override
public DoubleValues getValues(LeafReaderContext ctx, DoubleValues scores) throws IOException {
BinaryDocValues values = ctx.reader().getBinaryDocValues(fieldName);
if (values == null) {
return DoubleValues.EMPTY;
}

return new DoubleValues() {
@Override
public double doubleValue() throws IOException {
return scoreFunction.compare(
queryVector,
LateInteractionField.decode(values.binaryValue()),
vectorSimilarityFunction);
}

@Override
public boolean advanceExact(int doc) throws IOException {
return values.advanceExact(doc);
}
};
}

@Override
public boolean needsScores() {
return false;
}

@Override
public DoubleValuesSource rewrite(IndexSearcher reader) throws IOException {
return this;
}

@Override
public int hashCode() {
return Objects.hash(
fieldName, Arrays.deepHashCode(queryVector), vectorSimilarityFunction, scoreFunction);
}

@Override
public boolean equals(Object obj) {
if (this == obj) return true;
if (obj == null || getClass() != obj.getClass()) return false;
LateInteractionFloatValuesSource other = (LateInteractionFloatValuesSource) obj;
return Objects.equals(fieldName, other.fieldName)
&& vectorSimilarityFunction == other.vectorSimilarityFunction
&& scoreFunction == other.scoreFunction
&& Arrays.deepEquals(queryVector, other.queryVector);
}

@Override
public String toString() {
return "LateInteractionFloatValuesSource(fieldName="
+ fieldName
+ " similarityFunction="
+ vectorSimilarityFunction
+ " scoreFunction="
+ scoreFunction.getClass()
+ " queryVector="
+ Arrays.deepToString(queryVector)
+ ")";
}

@Override
public boolean isCacheable(LeafReaderContext ctx) {
return true;
}

/** Defines the function to compute similarity score between query and document multi-vectors */
public enum ScoreFunction implements MultiVectorSimilarity {

/** Computes the sum of max similarity between query and document vectors */
SUM_MAX_SIM {
@Override
public float compare(
float[][] queryVector,
float[][] docVector,
VectorSimilarityFunction vectorSimilarityFunction) {
if (docVector.length == 0) {
return Float.MIN_VALUE;
}
float result = 0f;
for (float[] q : queryVector) {
float maxSim = Float.MIN_VALUE;
for (float[] d : docVector) {
if (q.length != d.length) {
throw new IllegalArgumentException(
"Provided multi-vectors are incompatible. "
+ "Their composing token vectors should have the same dimension, got "
+ q.length
+ " != "
+ d.length);
}
maxSim = Float.max(maxSim, vectorSimilarityFunction.compare(q, d));
}
result += maxSim;
}
return result;
}
};
}
}
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