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test: Add comprehensive test coverage for AzureOpenAiChatOptions and PostgresMlEmbeddingOptions #4042

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merged 1 commit into from
Aug 6, 2025
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test: Add comprehensive test coverage for AzureOpenAiChatOptions and PostgresMlEmbeddingOptions #4042

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112 changes: 112 additions & 0 deletions ...i/src/test/java/org/springframework/ai/azure/openai/AzureChatCompletionsOptionsTests.java
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Original file line number Diff line number Diff line change
Expand Up @@ -166,4 +166,116 @@ public void createChatOptionsWithPresencePenaltyAndFrequencyPenalty(Double prese
}
}

@Test
public void createRequestWithMinimalOptions() {
OpenAIClientBuilder mockClient = Mockito.mock(OpenAIClientBuilder.class);

var minimalOptions = AzureOpenAiChatOptions.builder().deploymentName("MINIMAL_MODEL").build();

var client = AzureOpenAiChatModel.builder()
.openAIClientBuilder(mockClient)
.defaultOptions(minimalOptions)
.build();

var requestOptions = client.toAzureChatCompletionsOptions(new Prompt("Test message"));

assertThat(requestOptions.getModel()).isEqualTo("MINIMAL_MODEL");
assertThat(requestOptions.getTemperature()).isNull();
assertThat(requestOptions.getMaxTokens()).isNull();
assertThat(requestOptions.getTopP()).isNull();
}

@Test
public void createRequestWithEmptyStopList() {
OpenAIClientBuilder mockClient = Mockito.mock(OpenAIClientBuilder.class);

var options = AzureOpenAiChatOptions.builder().deploymentName("TEST_MODEL").stop(List.of()).build();

var client = AzureOpenAiChatModel.builder().openAIClientBuilder(mockClient).defaultOptions(options).build();

var requestOptions = client.toAzureChatCompletionsOptions(new Prompt("Test message"));

assertThat(requestOptions.getStop()).isEmpty();
}

@Test
public void createRequestWithEmptyLogitBias() {
OpenAIClientBuilder mockClient = Mockito.mock(OpenAIClientBuilder.class);

var options = AzureOpenAiChatOptions.builder().deploymentName("TEST_MODEL").logitBias(Map.of()).build();

var client = AzureOpenAiChatModel.builder().openAIClientBuilder(mockClient).defaultOptions(options).build();

var requestOptions = client.toAzureChatCompletionsOptions(new Prompt("Test message"));

assertThat(requestOptions.getLogitBias()).isEmpty();
}

@Test
public void createRequestWithLogprobsDisabled() {
OpenAIClientBuilder mockClient = Mockito.mock(OpenAIClientBuilder.class);

var options = AzureOpenAiChatOptions.builder()
.deploymentName("TEST_MODEL")
.logprobs(false)
.topLogprobs(0)
.build();

var client = AzureOpenAiChatModel.builder().openAIClientBuilder(mockClient).defaultOptions(options).build();

var requestOptions = client.toAzureChatCompletionsOptions(new Prompt("Test message"));

assertThat(requestOptions.isLogprobs()).isFalse();
assertThat(requestOptions.getTopLogprobs()).isEqualTo(0);
}

@Test
public void createRequestWithSingleStopSequence() {
OpenAIClientBuilder mockClient = Mockito.mock(OpenAIClientBuilder.class);

var options = AzureOpenAiChatOptions.builder().deploymentName("SINGLE_STOP_MODEL").stop(List.of("END")).build();

var client = AzureOpenAiChatModel.builder().openAIClientBuilder(mockClient).defaultOptions(options).build();

var requestOptions = client.toAzureChatCompletionsOptions(new Prompt("Test message"));

assertThat(requestOptions.getStop()).hasSize(1);
assertThat(requestOptions.getStop()).containsExactly("END");
}

@Test
public void builderPatternTest() {
var options = AzureOpenAiChatOptions.builder()
.deploymentName("BUILDER_TEST_MODEL")
.temperature(0.7)
.maxTokens(1500)
.build();

assertThat(options.getDeploymentName()).isEqualTo("BUILDER_TEST_MODEL");
assertThat(options.getTemperature()).isEqualTo(0.7);
assertThat(options.getMaxTokens()).isEqualTo(1500);
}

@ParameterizedTest
@MethodSource("provideResponseFormatTypes")
public void createRequestWithDifferentResponseFormats(Type responseFormatType, Class<?> expectedFormatClass) {
OpenAIClientBuilder mockClient = Mockito.mock(OpenAIClientBuilder.class);

var options = AzureOpenAiChatOptions.builder()
.deploymentName("FORMAT_TEST_MODEL")
.responseFormat(AzureOpenAiResponseFormat.builder().type(responseFormatType).build())
.build();

var client = AzureOpenAiChatModel.builder().openAIClientBuilder(mockClient).defaultOptions(options).build();

var requestOptions = client.toAzureChatCompletionsOptions(new Prompt("Test message"));

assertThat(requestOptions.getResponseFormat()).isInstanceOf(expectedFormatClass);
}

private static Stream<Arguments> provideResponseFormatTypes() {
return Stream.of(Arguments.of(Type.TEXT, ChatCompletionsTextResponseFormat.class),
Arguments.of(Type.JSON_OBJECT, ChatCompletionsJsonResponseFormat.class));
}

}
108 changes: 108 additions & 0 deletions ...esml/src/test/java/org/springframework/ai/postgresml/PostgresMlEmbeddingOptionsTests.java
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Expand Up @@ -95,4 +95,112 @@ public void mergeOptions() {
assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.ALL);
}

@Test
public void builderWithEmptyKwargs() {
PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder().kwargs(Map.of()).build();

assertThat(options.getKwargs()).isEmpty();
assertThat(options.getKwargs()).isNotNull();
}

@Test
public void builderWithMultipleKwargs() {
Map<String, Object> kwargs = Map.of("device", "gpu", "batch_size", 32, "max_length", 512, "normalize", true);

PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder().kwargs(kwargs).build();

assertThat(options.getKwargs()).hasSize(4);
assertThat(options.getKwargs().get("device")).isEqualTo("gpu");
assertThat(options.getKwargs().get("batch_size")).isEqualTo(32);
assertThat(options.getKwargs().get("max_length")).isEqualTo(512);
assertThat(options.getKwargs().get("normalize")).isEqualTo(true);
}

@Test
public void allVectorTypes() {
for (PostgresMlEmbeddingModel.VectorType vectorType : PostgresMlEmbeddingModel.VectorType.values()) {
PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder().vectorType(vectorType).build();

assertThat(options.getVectorType()).isEqualTo(vectorType);
}
}

@Test
public void allMetadataModes() {
for (org.springframework.ai.document.MetadataMode mode : org.springframework.ai.document.MetadataMode
.values()) {
PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder().metadataMode(mode).build();

assertThat(options.getMetadataMode()).isEqualTo(mode);
}
}

@Test
public void mergeOptionsWithNullInput() {
var jdbcTemplate = Mockito.mock(JdbcTemplate.class);
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(jdbcTemplate);

PostgresMlEmbeddingOptions options = embeddingModel.mergeOptions(null);

// Should return default options when input is null
assertThat(options.getTransformer()).isEqualTo(PostgresMlEmbeddingModel.DEFAULT_TRANSFORMER_MODEL);
assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_ARRAY);
assertThat(options.getKwargs()).isEqualTo(Map.of());
assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.EMBED);
}

@Test
public void mergeOptionsPreservesOriginal() {
var jdbcTemplate = Mockito.mock(JdbcTemplate.class);
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(jdbcTemplate);

PostgresMlEmbeddingOptions original = PostgresMlEmbeddingOptions.builder()
.transformer("original-model")
.kwargs(Map.of("original", "value"))
.build();

PostgresMlEmbeddingOptions merged = embeddingModel.mergeOptions(original);

// Verify original options are not modified
assertThat(original.getTransformer()).isEqualTo("original-model");
assertThat(original.getKwargs()).containsEntry("original", "value");

// Verify merged options have expected values
assertThat(merged.getTransformer()).isEqualTo("original-model");
}

@Test
public void mergeOptionsWithComplexKwargs() {
var jdbcTemplate = Mockito.mock(JdbcTemplate.class);
PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(jdbcTemplate);

Map<String, Object> complexKwargs = Map.of("device", "cuda:0", "model_kwargs",
Map.of("trust_remote_code", true), "encode_kwargs",
Map.of("normalize_embeddings", true, "batch_size", 64));

PostgresMlEmbeddingOptions options = embeddingModel
.mergeOptions(PostgresMlEmbeddingOptions.builder().kwargs(complexKwargs).build());

assertThat(options.getKwargs()).hasSize(3);
assertThat(options.getKwargs().get("device")).isEqualTo("cuda:0");
assertThat(options.getKwargs().get("model_kwargs")).isInstanceOf(Map.class);
assertThat(options.getKwargs().get("encode_kwargs")).isInstanceOf(Map.class);
}

@Test
public void builderChaining() {
PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder()
.transformer("model-1")
.transformer("model-2") // Should override previous value
.vectorType(PostgresMlEmbeddingModel.VectorType.PG_VECTOR)
.metadataMode(org.springframework.ai.document.MetadataMode.ALL)
.kwargs(Map.of("key1", "value1"))
.kwargs(Map.of("key2", "value2")) // Should override previous kwargs
.build();

assertThat(options.getTransformer()).isEqualTo("model-2");
assertThat(options.getKwargs()).containsEntry("key2", "value2");
assertThat(options.getKwargs()).doesNotContainKey("key1");
}

}