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Optimize MistralAiEmbeddingModel dimensions method #4810

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Optimize MistralAiEmbeddingModel dimensions method #4810

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20 changes: 14 additions & 6 deletions ...ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiEmbeddingModel.java
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@

package org.springframework.ai.mistralai;

import java.util.HashMap;
import java.util.List;
import java.util.Map;

Expand Down Expand Up @@ -56,16 +57,14 @@ public class MistralAiEmbeddingModel extends AbstractEmbeddingModel {

private static final Logger logger = LoggerFactory.getLogger(MistralAiEmbeddingModel.class);

private static final EmbeddingModelObservationConvention DEFAULT_OBSERVATION_CONVENTION = new DefaultEmbeddingModelObservationConvention();

/**
* Known embedding dimensions for Mistral AI models. Maps model names to their
* respective embedding vector dimensions. This allows the dimensions() method to
* return the correct value without making an API call.
*/
private static final Map<String, Integer> KNOWN_EMBEDDING_DIMENSIONS = Map.of(
MistralAiApi.EmbeddingModel.EMBED.getValue(), 1024, MistralAiApi.EmbeddingModel.CODESTRAL_EMBED.getValue(),
1536);

private static final EmbeddingModelObservationConvention DEFAULT_OBSERVATION_CONVENTION = new DefaultEmbeddingModelObservationConvention();
private final Map<String, Integer> knownEmbeddingDimensions = createKnownEmbeddingDimensions();
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@nicolaskrier nicolaskrier Nov 6, 2025

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I was a bit concerned about making a class constant mutable that is why I have decided to make it an attribute.


private final MistralAiEmbeddingOptions defaultOptions;

Expand All @@ -85,6 +84,14 @@ public class MistralAiEmbeddingModel extends AbstractEmbeddingModel {
*/
private EmbeddingModelObservationConvention observationConvention = DEFAULT_OBSERVATION_CONVENTION;

private static Map<String, Integer> createKnownEmbeddingDimensions() {
Map<String, Integer> knownEmbeddingDimensions = new HashMap<>();
knownEmbeddingDimensions.put(MistralAiApi.EmbeddingModel.EMBED.getValue(), 1024);
knownEmbeddingDimensions.put(MistralAiApi.EmbeddingModel.CODESTRAL_EMBED.getValue(), 1536);

return knownEmbeddingDimensions;
}

public MistralAiEmbeddingModel(MistralAiApi mistralAiApi, MetadataMode metadataMode,
MistralAiEmbeddingOptions options, RetryTemplate retryTemplate, ObservationRegistry observationRegistry) {
Assert.notNull(mistralAiApi, "mistralAiApi must not be null");
Expand Down Expand Up @@ -174,7 +181,8 @@ public float[] embed(Document document) {

@Override
public int dimensions() {
return KNOWN_EMBEDDING_DIMENSIONS.getOrDefault(this.defaultOptions.getModel(), super.dimensions());
return this.knownEmbeddingDimensions.computeIfAbsent(this.defaultOptions.getModel(),
model -> super.dimensions());
}

/**
Expand Down
27 changes: 16 additions & 11 deletions ...stral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiEmbeddingModelTests.java
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Original file line number Diff line number Diff line change
Expand Up @@ -16,6 +16,7 @@

package org.springframework.ai.mistralai;

import java.util.Arrays;
import java.util.List;

import org.junit.jupiter.api.Test;
Expand All @@ -28,6 +29,7 @@

import static org.assertj.core.api.Assertions.assertThat;
import static org.mockito.ArgumentMatchers.any;
import static org.mockito.Mockito.verify;
import static org.mockito.Mockito.when;

/**
Expand Down Expand Up @@ -77,7 +79,7 @@ void testDimensionsForCodestralEmbedModel() {
void testDimensionsFallbackForUnknownModel() {
MistralAiApi mockApi = createMockApiWithEmbeddingResponse(512);

// Use a model name that doesn't exist in KNOWN_EMBEDDING_DIMENSIONS
// Use a model name that doesn't exist in knownEmbeddingDimensions.
MistralAiEmbeddingOptions options = MistralAiEmbeddingOptions.builder().withModel("unknown-model").build();

MistralAiEmbeddingModel model = MistralAiEmbeddingModel.builder()
Expand All @@ -87,17 +89,23 @@ void testDimensionsFallbackForUnknownModel() {
.retryTemplate(RetryUtils.DEFAULT_RETRY_TEMPLATE)
.build();

// Should fall back to super.dimensions() which detects dimensions from the API
// response
// For the first call, it should fall back to super.dimensions() which detects
// dimensions from the API response.
assertThat(model.dimensions()).isEqualTo(512);

// For the second call, it should use the cache mechanism.
assertThat(model.dimensions()).isEqualTo(512);

// Verify that super.dimensions() has been called once.
verify(mockApi).embeddings(any());
}

@Test
void testAllEmbeddingModelsHaveDimensionMapping() {
// This test ensures that KNOWN_EMBEDDING_DIMENSIONS map stays in sync with the
// EmbeddingModel enum
// This test ensures that knownEmbeddingDimensions map stays in sync with the
// EmbeddingModel enum.
// If a new model is added to the enum but not to the dimensions map, this test
// will help catch it
// will help catch it.

for (MistralAiApi.EmbeddingModel embeddingModel : MistralAiApi.EmbeddingModel.values()) {
MistralAiApi mockApi = createMockApiWithEmbeddingResponse(1024);
Expand Down Expand Up @@ -138,16 +146,13 @@ private MistralAiApi createMockApiWithEmbeddingResponse(int dimensions) {

// Create a mock embedding response with the specified dimensions
float[] embedding = new float[dimensions];
for (int i = 0; i < dimensions; i++) {
embedding[i] = 0.1f;
}
Arrays.fill(embedding, 0.1f);

MistralAiApi.Embedding embeddingData = new MistralAiApi.Embedding(0, embedding, "embedding");

MistralAiApi.Usage usage = new MistralAiApi.Usage(10, 0, 10);

MistralAiApi.EmbeddingList embeddingList = new MistralAiApi.EmbeddingList("object", List.of(embeddingData),
"model", usage);
var embeddingList = new MistralAiApi.EmbeddingList<>("object", List.of(embeddingData), "model", usage);

when(mockApi.embeddings(any())).thenReturn(ResponseEntity.ok(embeddingList));

Expand Down