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GH-3896 Similarity searches with the MariaDBVectorStore do not provide a score #3898

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GH-3896 Similarity searches with the MariaDBVectorStore do not provide a score #3898

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10 changes: 7 additions & 3 deletions ...db-store/src/main/java/org/springframework/ai/vectorstore/mariadb/MariaDBVectorStore.java
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Original file line number Diff line number Diff line change
Expand Up @@ -485,9 +485,13 @@ public Document mapRow(ResultSet rs, int rowNum) throws SQLException {
Map<String, Object> metadata = toMap(rs.getString(3));
float distance = rs.getFloat(4);

metadata.put("distance", distance);

return new Document(id, content, metadata);
// @formatter:off
return Document.builder()
.id(id)
.text(content)
.metadata(metadata)
.score(1.0 - distance)
.build(); // @formatter:on
}

private Map<String, Object> toMap(String source) {
Expand Down
38 changes: 18 additions & 20 deletions ...ariadb-store/src/test/java/org/springframework/ai/vectorstore/mariadb/MariaDBStoreIT.java
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Original file line number Diff line number Diff line change
Expand Up @@ -122,20 +122,20 @@ static Stream<Arguments> provideFilters() {
);
}

private static boolean isSortedByDistance(List<Document> docs) {
private static boolean isSortedByScore(List<Document> docs) {

List<Float> distances = docs.stream().map(doc -> (Float) doc.getMetadata().get("distance")).toList();
List<Double> scores = docs.stream().map(Document::getScore).toList();

if (CollectionUtils.isEmpty(distances) || distances.size() == 1) {
if (CollectionUtils.isEmpty(scores) || scores.size() == 1) {
return true;
}

Iterator<Float> iter = distances.iterator();
Float current;
Float previous = iter.next();
Iterator<Double> iter = scores.iterator();
Double current;
Double previous = iter.next();
while (iter.hasNext()) {
current = iter.next();
if (previous > current) {
if (previous < current) {
return false;
}
previous = current;
Expand Down Expand Up @@ -166,7 +166,8 @@ public void addAndSearch(String distanceType) {
assertThat(results).hasSize(1);
Document resultDoc = results.get(0);
assertThat(resultDoc.getId()).isEqualTo(this.documents.get(2).getId());
assertThat(resultDoc.getMetadata()).containsKeys("meta2", "distance");
assertThat(resultDoc.getMetadata()).containsKeys("meta2");
assertThat(resultDoc.getScore()).isBetween(0.0, 1.0);

// Remove all documents from the store
vectorStore.delete(this.documents.stream().map(doc -> doc.getId()).toList());
Expand Down Expand Up @@ -315,7 +316,8 @@ public void documentUpdate(String distanceType) {
Document resultDoc = results.get(0);
assertThat(resultDoc.getId()).isEqualTo(document.getId());
assertThat(resultDoc.getText()).isEqualTo("Spring AI rocks!!");
assertThat(resultDoc.getMetadata()).containsKeys("meta1", "distance");
assertThat(resultDoc.getMetadata()).containsKeys("meta1");
assertThat(resultDoc.getScore()).isBetween(0.0, 1.0);

Document sameIdDocument = new Document(document.getId(),
"The World is Big and Salvation Lurks Around the Corner",
Expand All @@ -329,7 +331,8 @@ public void documentUpdate(String distanceType) {
resultDoc = results.get(0);
assertThat(resultDoc.getId()).isEqualTo(document.getId());
assertThat(resultDoc.getText()).isEqualTo("The World is Big and Salvation Lurks Around the Corner");
assertThat(resultDoc.getMetadata()).containsKeys("meta2", "distance");
assertThat(resultDoc.getMetadata()).containsKeys("meta2");
assertThat(resultDoc.getScore()).isBetween(0.0, 1.0);

dropTable(context);
});
Expand All @@ -350,19 +353,14 @@ public void searchWithThreshold(String distanceType) {

assertThat(fullResult).hasSize(3);

assertThat(isSortedByDistance(fullResult)).isTrue();
assertThat(isSortedByScore(fullResult)).isTrue();

List<Float> distances = fullResult.stream()
.map(doc -> (Float) doc.getMetadata().get("distance"))
.toList();
List<Double> scores = fullResult.stream().map(Document::getScore).toList();

float threshold = (distances.get(0) + distances.get(1)) / 2;
double threshold = (scores.get(0) + scores.get(1)) / 2;

List<Document> results = vectorStore.similaritySearch(SearchRequest.builder()
.query("Time Shelter")
.topK(5)
.similarityThreshold(1 - threshold)
.build());
List<Document> results = vectorStore.similaritySearch(
SearchRequest.builder().query("Time Shelter").topK(5).similarityThreshold(threshold).build());

assertThat(results).hasSize(1);
Document resultDoc = results.get(0);
Expand Down
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