Rename the ModelClient class hiearchy into Model

- Rename ModelClient into Model. Update all code and doc references.
 - Rename ChatClient to ChatModel. Update all ChatClient suffixes and chatClient fields and variables in code and doc.
 - Rename EmbeddingClient into EmbeddingModel. Update the XxxEmbeddingClient class and variable suffixes and embeddingClient variables and fields in code and docs.
 - Rename ImageClient into ImageModel. ....
 - Rename SpeechClient into SpeechModel ....
 - Rename TranscriptionClient into TranscriptionModel ...
 - Update all javadocs and antora pages. Update the related diagrams.

models/spring-ai-anthropic/src/main/java/org/springframework/ai/anthropic/AnthropicChatModel.java

@@ -26,7 +26,7 @@ import java.util.stream.Collectors;
 
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import reactor.core.publisher.Flux;
 
 import org.springframework.ai.anthropic.api.AnthropicApi;
@@ -41,7 +41,7 @@ import org.springframework.ai.anthropic.api.AnthropicApi.Usage;
 import org.springframework.ai.anthropic.metadata.AnthropicChatResponseMetadata;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.messages.MessageType;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.prompt.ChatOptions;
@@ -56,16 +56,16 @@ import org.springframework.util.Assert;
 import org.springframework.util.CollectionUtils;
 
 /**
- * The {@link ChatCaller} implementation for the Anthropic service.
+ * The {@link ChatModel} implementation for the Anthropic service.
  *
  * @author Christian Tzolov
  * @since 1.0.0
  */
-public class AnthropicModelCaller extends
+public class AnthropicChatModel extends
 		AbstractFunctionCallSupport<AnthropicApi.RequestMessage, AnthropicApi.ChatCompletionRequest, ResponseEntity<AnthropicApi.ChatCompletion>>
-		implements ChatCaller, StreamingChatCaller {
+		implements ChatModel, StreamingChatModel {
 
-	private static final Logger logger = LoggerFactory.getLogger(AnthropicModelCaller.class);
+	private static final Logger logger = LoggerFactory.getLogger(AnthropicChatModel.class);
 
 	public static final String DEFAULT_MODEL_NAME = AnthropicApi.ChatModel.CLAUDE_3_OPUS.getValue();
 
@@ -89,10 +89,10 @@ public class AnthropicModelCaller extends
 	public final RetryTemplate retryTemplate;
 
 	/**
-	 * Construct a new {@link AnthropicModelCaller} instance.
+	 * Construct a new {@link AnthropicChatModel} instance.
 	 * @param anthropicApi the lower-level API for the Anthropic service.
 	 */
-	public AnthropicModelCaller(AnthropicApi anthropicApi) {
+	public AnthropicChatModel(AnthropicApi anthropicApi) {
 		this(anthropicApi,
 				AnthropicChatOptions.builder()
 					.withModel(DEFAULT_MODEL_NAME)
@@ -102,34 +102,34 @@ public class AnthropicModelCaller extends
 	}
 
 	/**
-	 * Construct a new {@link AnthropicModelCaller} instance.
+	 * Construct a new {@link AnthropicChatModel} instance.
 	 * @param anthropicApi the lower-level API for the Anthropic service.
 	 * @param defaultOptions the default options used for the chat completion requests.
 	 */
-	public AnthropicModelCaller(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions) {
+	public AnthropicChatModel(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions) {
 		this(anthropicApi, defaultOptions, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * Construct a new {@link AnthropicModelCaller} instance.
+	 * Construct a new {@link AnthropicChatModel} instance.
 	 * @param anthropicApi the lower-level API for the Anthropic service.
 	 * @param defaultOptions the default options used for the chat completion requests.
 	 * @param retryTemplate the retry template used to retry the Anthropic API calls.
 	 */
-	public AnthropicModelCaller(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions,
+	public AnthropicChatModel(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions,
 			RetryTemplate retryTemplate) {
 		this(anthropicApi, defaultOptions, retryTemplate, null);
 	}
 
 	/**
-	 * Construct a new {@link AnthropicModelCaller} instance.
+	 * Construct a new {@link AnthropicChatModel} instance.
 	 * @param anthropicApi the lower-level API for the Anthropic service.
 	 * @param defaultOptions the default options used for the chat completion requests.
 	 * @param retryTemplate the retry template used to retry the Anthropic API calls.
 	 * @param functionCallbackContext the function callback context used to store the
 	 * state of the function calls.
 	 */
-	public AnthropicModelCaller(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions,
+	public AnthropicChatModel(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions,
 			RetryTemplate retryTemplate, FunctionCallbackContext functionCallbackContext) {
 
 		super(functionCallbackContext);

models/spring-ai-anthropic/src/main/java/org/springframework/ai/anthropic/AnthropicChatOptions.java

@@ -51,11 +51,11 @@ public class AnthropicChatOptions implements ChatOptions, FunctionCallingOptions
 	private @JsonProperty("top_k") Integer topK;
 
 	/**
-	 * Tool Function Callbacks to register with the ModelCall. For Prompt
+	 * Tool Function Callbacks to register with the ChatModel. For Prompt
 	 * Options the functionCallbacks are automatically enabled for the duration of the
 	 * prompt execution. For Default Options the functionCallbacks are registered but
 	 * disabled by default. Use the enableFunctions to set the functions from the registry
-	 * to be used by the ModelCall chat completion requests.
+	 * to be used by the ChatModel chat completion requests.
 	 */
 	@NestedConfigurationProperty
 	@JsonIgnore

models/spring-ai-anthropic/src/test/java/org/springframework/ai/anthropic/AnthropicChatModelIT.java

@@ -29,10 +29,10 @@ import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.anthropic.api.AnthropicApi;
 import org.springframework.ai.anthropic.api.tool.MockWeatherService;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.messages.AssistantMessage;
 import org.springframework.ai.chat.messages.Media;
 import org.springframework.ai.chat.messages.Message;
@@ -56,15 +56,15 @@ import static org.assertj.core.api.Assertions.assertThat;
 
 @SpringBootTest(classes = AnthropicTestConfiguration.class, properties = "spring.ai.retry.on-http-codes=429")
 @EnabledIfEnvironmentVariable(named = "ANTHROPIC_API_KEY", matches = ".+")
-class AnthropicModelCallerIT {
+class AnthropicChatModelIT {
 
-	private static final Logger logger = LoggerFactory.getLogger(AnthropicModelCallerIT.class);
+	private static final Logger logger = LoggerFactory.getLogger(AnthropicChatModelIT.class);
 
 	@Autowired
-	protected ChatCaller modelCaller;
+	protected ChatModel chatModel;
 
 	@Autowired
-	protected StreamingChatCaller streamingChatClient;
+	protected StreamingChatModel streamingChatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -76,7 +76,7 @@ class AnthropicModelCallerIT {
 		SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate(systemResource);
 		Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", "Bob", "voice", "pirate"));
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		ChatResponse response = modelCaller.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getMetadata().getUsage().getGenerationTokens()).isGreaterThan(0);
 		assertThat(response.getMetadata().getUsage().getPromptTokens()).isGreaterThan(0);
@@ -102,7 +102,7 @@ class AnthropicModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.modelCaller.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = listOutputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -120,7 +120,7 @@ class AnthropicModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = mapOutputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -142,7 +142,7 @@ class AnthropicModelCallerIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = beanOutputConverter.convert(generation.getOutput().getContent());
 		logger.info("" + actorsFilms);
@@ -163,7 +163,7 @@ class AnthropicModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = streamingChatClient.stream(prompt)
+		String generationTextFromStream = streamingChatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -187,7 +187,7 @@ class AnthropicModelCallerIT {
 		var userMessage = new UserMessage("Explain what do you see on this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		var response = modelCaller.call(new Prompt(List.of(userMessage)));
+		var response = chatModel.call(new Prompt(List.of(userMessage)));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple", "basket");
@@ -209,7 +209,7 @@ class AnthropicModelCallerIT {
 				.build()))
 			.build();
 
-		ChatResponse response = modelCaller.call(new Prompt(messages, promptOptions));
+		ChatResponse response = chatModel.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 

models/spring-ai-anthropic/src/test/java/org/springframework/ai/anthropic/AnthropicTestConfiguration.java

@@ -38,9 +38,9 @@ public class AnthropicTestConfiguration {
 	}
 
 	@Bean
-	public AnthropicModelCaller openAiChatClient(AnthropicApi api) {
-		AnthropicModelCaller anthropicChatClient = new AnthropicModelCaller(api);
-		return anthropicChatClient;
+	public AnthropicChatModel openAiChatModel(AnthropicApi api) {
+		AnthropicChatModel anthropicChatModel = new AnthropicChatModel(api);
+		return anthropicChatModel;
 	}
 
 }

models/spring-ai-anthropic/src/test/java/org/springframework/ai/anthropic/ChatCompletionRequestTests.java

@@ -30,7 +30,7 @@ public class ChatCompletionRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new AnthropicModelCaller(new AnthropicApi("TEST"),
+		var client = new AnthropicChatModel(new AnthropicApi("TEST"),
 				AnthropicChatOptions.builder().withModel("DEFAULT_MODEL").withTemperature(66.6f).build());
 
 		var request = client.createRequest(new Prompt("Test message content"), false);

models/spring-ai-azure-openai/src/main/java/org/springframework/ai/azure/openai/AzureOpenAiChatModel.java

@@ -38,10 +38,10 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.azure.openai.metadata.AzureOpenAiChatResponseMetadata;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.messages.Message;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.metadata.PromptMetadata;
@@ -63,7 +63,7 @@ import java.util.Set;
 import java.util.concurrent.atomic.AtomicBoolean;
 
 /**
- * {@link ChatCaller} implementation for {@literal Microsoft Azure AI} backed by
+ * {@link ChatModel} implementation for {@literal Microsoft Azure AI} backed by
  * {@link OpenAIClient}.
  *
  * @author Mark Pollack
@@ -71,12 +71,12 @@ import java.util.concurrent.atomic.AtomicBoolean;
  * @author John Blum
  * @author Christian Tzolov
  * @author Grogdunn
- * @see ChatCaller
+ * @see ChatModel
  * @see com.azure.ai.openai.OpenAIClient
  */
-public class AzureOpenAiModelCaller
+public class AzureOpenAiChatModel
 		extends AbstractFunctionCallSupport<ChatRequestMessage, ChatCompletionsOptions, ChatCompletions>
-		implements ChatCaller, StreamingChatCaller {
+		implements ChatModel, StreamingChatModel {
 
 	private static final String DEFAULT_DEPLOYMENT_NAME = "gpt-35-turbo";
 
@@ -94,7 +94,7 @@ public class AzureOpenAiModelCaller
 	 */
 	private final OpenAIClient openAIClient;
 
-	public AzureOpenAiModelCaller(OpenAIClient microsoftOpenAiClient) {
+	public AzureOpenAiChatModel(OpenAIClient microsoftOpenAiClient) {
 		this(microsoftOpenAiClient,
 				AzureOpenAiChatOptions.builder()
 					.withDeploymentName(DEFAULT_DEPLOYMENT_NAME)
@@ -102,11 +102,11 @@ public class AzureOpenAiModelCaller
 					.build());
 	}
 
-	public AzureOpenAiModelCaller(OpenAIClient microsoftOpenAiClient, AzureOpenAiChatOptions options) {
+	public AzureOpenAiChatModel(OpenAIClient microsoftOpenAiClient, AzureOpenAiChatOptions options) {
 		this(microsoftOpenAiClient, options, null);
 	}
 
-	public AzureOpenAiModelCaller(OpenAIClient microsoftOpenAiClient, AzureOpenAiChatOptions options,
+	public AzureOpenAiChatModel(OpenAIClient microsoftOpenAiClient, AzureOpenAiChatOptions options,
 			FunctionCallbackContext functionCallbackContext) {
 		super(functionCallbackContext);
 		Assert.notNull(microsoftOpenAiClient, "com.azure.ai.openai.OpenAIClient must not be null");
@@ -117,10 +117,10 @@ public class AzureOpenAiModelCaller
 
 	/**
 	 * @deprecated since 0.8.0, use
-	 * {@link #AzureOpenAiModelCall(OpenAIClient, AzureOpenAiChatOptions)} instead.
+	 * {@link #AzureOpenAiChatModel(OpenAIClient, AzureOpenAiChatOptions)} instead.
 	 */
 	@Deprecated(forRemoval = true, since = "0.8.0")
-	public AzureOpenAiModelCaller withDefaultOptions(AzureOpenAiChatOptions defaultOptions) {
+	public AzureOpenAiChatModel withDefaultOptions(AzureOpenAiChatOptions defaultOptions) {
 		Assert.notNull(defaultOptions, "DefaultOptions must not be null");
 		this.defaultOptions = defaultOptions;
 		return this;

models/spring-ai-azure-openai/src/main/java/org/springframework/ai/azure/openai/AzureOpenAiChatOptions.java

@@ -127,11 +127,11 @@ public class AzureOpenAiChatOptions implements FunctionCallingOptions, ChatOptio
 	private String deploymentName;
 
 	/**
-	 * OpenAI Tool Function Callbacks to register with the ModelCall. For Prompt Options
+	 * OpenAI Tool Function Callbacks to register with the ChatModel. For Prompt Options
 	 * the functionCallbacks are automatically enabled for the duration of the prompt
 	 * execution. For Default Options the functionCallbacks are registered but disabled by
 	 * default. Use the enableFunctions to set the functions from the registry to be used
-	 * by the ModelCall chat completion requests.
+	 * by the ChatModel chat completion requests.
 	 */
 	@NestedConfigurationProperty
 	@JsonIgnore

models/spring-ai-azure-openai/src/main/java/org/springframework/ai/azure/openai/AzureOpenAiEmbeddingModel.java

@@ -28,7 +28,7 @@ import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.MetadataMode;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -37,9 +37,9 @@ import org.springframework.ai.embedding.EmbeddingResponseMetadata;
 import org.springframework.ai.model.ModelOptionsUtils;
 import org.springframework.util.Assert;
 
-public class AzureOpenAiEmbeddingClient extends AbstractEmbeddingClient {
+public class AzureOpenAiEmbeddingModel extends AbstractEmbeddingModel {
 
-	private static final Logger logger = LoggerFactory.getLogger(AzureOpenAiEmbeddingClient.class);
+	private static final Logger logger = LoggerFactory.getLogger(AzureOpenAiEmbeddingModel.class);
 
 	private final OpenAIClient azureOpenAiClient;
 
@@ -47,16 +47,16 @@ public class AzureOpenAiEmbeddingClient extends AbstractEmbeddingClient {
 
 	private final MetadataMode metadataMode;
 
-	public AzureOpenAiEmbeddingClient(OpenAIClient azureOpenAiClient) {
+	public AzureOpenAiEmbeddingModel(OpenAIClient azureOpenAiClient) {
 		this(azureOpenAiClient, MetadataMode.EMBED);
 	}
 
-	public AzureOpenAiEmbeddingClient(OpenAIClient azureOpenAiClient, MetadataMode metadataMode) {
+	public AzureOpenAiEmbeddingModel(OpenAIClient azureOpenAiClient, MetadataMode metadataMode) {
 		this(azureOpenAiClient, metadataMode,
 				AzureOpenAiEmbeddingOptions.builder().withDeploymentName("text-embedding-ada-002").build());
 	}
 
-	public AzureOpenAiEmbeddingClient(OpenAIClient azureOpenAiClient, MetadataMode metadataMode,
+	public AzureOpenAiEmbeddingModel(OpenAIClient azureOpenAiClient, MetadataMode metadataMode,
 			AzureOpenAiEmbeddingOptions options) {
 		Assert.notNull(azureOpenAiClient, "com.azure.ai.openai.OpenAIClient must not be null");
 		Assert.notNull(metadataMode, "Metadata mode must not be null");

models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/AzureChatCompletionsOptionsTests.java

@@ -53,7 +53,7 @@ public class AzureChatCompletionsOptionsTests {
 			.withUser("user")
 			.build();
 
-		var client = new AzureOpenAiModelCaller(mockClient, defaultOptions);
+		var client = new AzureOpenAiChatModel(mockClient, defaultOptions);
 
 		var requestOptions = client.toAzureChatCompletionsOptions(new Prompt("Test message content"));
 

models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/AzureEmbeddingsOptionsTests.java

@@ -36,7 +36,7 @@ public class AzureEmbeddingsOptionsTests {
 	public void createRequestWithChatOptions() {
 
 		OpenAIClient mockClient = Mockito.mock(OpenAIClient.class);
-		var client = new AzureOpenAiEmbeddingClient(mockClient, MetadataMode.EMBED,
+		var client = new AzureOpenAiEmbeddingModel(mockClient, MetadataMode.EMBED,
 				AzureOpenAiEmbeddingOptions.builder()
 					.withDeploymentName("DEFAULT_MODEL")
 					.withUser("USER_TEST")

models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/AzureOpenAiChatModelIT.java

@@ -46,13 +46,13 @@ import org.springframework.core.convert.support.DefaultConversionService;
 
 import static org.assertj.core.api.Assertions.assertThat;
 
-@SpringBootTest(classes = AzureOpenAiModelCallIerT.TestConfiguration.class)
+@SpringBootTest(classes = AzureOpenAiChatModelIT.TestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "AZURE_OPENAI_API_KEY", matches = ".+")
 @EnabledIfEnvironmentVariable(named = "AZURE_OPENAI_ENDPOINT", matches = ".+")
-class AzureOpenAiModelCallIerT {
+class AzureOpenAiChatModelIT {
 
 	@Autowired
-	private AzureOpenAiModelCaller chatClient;
+	private AzureOpenAiChatModel chatModel;
 
 	record ActorsFilms(String actor, List<String> movies) {
 	}
@@ -69,7 +69,7 @@ class AzureOpenAiModelCallIerT {
 		UserMessage userMessage = new UserMessage("Generate the names of 5 famous pirates.");
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		ChatResponse response = chatClient.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
 
@@ -86,7 +86,7 @@ class AzureOpenAiModelCallIerT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatClient.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -105,7 +105,7 @@ class AzureOpenAiModelCallIerT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatClient.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -124,7 +124,7 @@ class AzureOpenAiModelCallIerT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatClient.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilms actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isNotNull();
@@ -145,7 +145,7 @@ class AzureOpenAiModelCallIerT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatClient.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		System.out.println(actorsFilms);
@@ -166,7 +166,7 @@ class AzureOpenAiModelCallIerT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = chatClient.stream(prompt)
+		String generationTextFromStream = chatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -194,8 +194,8 @@ class AzureOpenAiModelCallIerT {
 		}
 
 		@Bean
-		public AzureOpenAiModelCaller azureOpenAiChatClient(OpenAIClient openAIClient) {
-			return new AzureOpenAiModelCaller(openAIClient,
+		public AzureOpenAiChatModel azureOpenAiChatModel(OpenAIClient openAIClient) {
+			return new AzureOpenAiChatModel(openAIClient,
 					AzureOpenAiChatOptions.builder().withDeploymentName("gpt-35-turbo").withMaxTokens(200).build());
 
 		}

models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/AzureOpenAiEmbeddingModelIT.java

@@ -34,25 +34,25 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AZURE_OPENAI_API_KEY", matches = ".+")
 @EnabledIfEnvironmentVariable(named = "AZURE_OPENAI_ENDPOINT", matches = ".+")
-class AzureOpenAiEmbeddingClientIT {
+class AzureOpenAiEmbeddingModelIT {
 
 	@Autowired
-	private AzureOpenAiEmbeddingClient embeddingClient;
+	private AzureOpenAiEmbeddingModel embeddingModel;
 
 	@Test
 	void singleEmbedding() {
-		assertThat(embeddingClient).isNotNull();
-		EmbeddingResponse embeddingResponse = embeddingClient.embedForResponse(List.of("Hello World"));
+		assertThat(embeddingModel).isNotNull();
+		EmbeddingResponse embeddingResponse = embeddingModel.embedForResponse(List.of("Hello World"));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).isNotEmpty();
-		System.out.println(embeddingClient.dimensions());
-		assertThat(embeddingClient.dimensions()).isEqualTo(1536);
+		System.out.println(embeddingModel.dimensions());
+		assertThat(embeddingModel.dimensions()).isEqualTo(1536);
 	}
 
 	@Test
 	void batchEmbedding() {
-		assertThat(embeddingClient).isNotNull();
-		EmbeddingResponse embeddingResponse = embeddingClient
+		assertThat(embeddingModel).isNotNull();
+		EmbeddingResponse embeddingResponse = embeddingModel
 			.embedForResponse(List.of("Hello World", "World is big and salvation is near"));
 		assertThat(embeddingResponse.getResults()).hasSize(2);
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).isNotEmpty();
@@ -60,7 +60,7 @@ class AzureOpenAiEmbeddingClientIT {
 		assertThat(embeddingResponse.getResults().get(1).getOutput()).isNotEmpty();
 		assertThat(embeddingResponse.getResults().get(1).getIndex()).isEqualTo(1);
 
-		assertThat(embeddingClient.dimensions()).isEqualTo(1536);
+		assertThat(embeddingModel.dimensions()).isEqualTo(1536);
 	}
 
 	@SpringBootConfiguration
@@ -74,8 +74,8 @@ class AzureOpenAiEmbeddingClientIT {
 		}
 
 		@Bean
-		public AzureOpenAiEmbeddingClient azureEmbeddingClient(OpenAIClient openAIClient) {
-			return new AzureOpenAiEmbeddingClient(openAIClient);
+		public AzureOpenAiEmbeddingModel azureEmbeddingModel(OpenAIClient openAIClient) {
+			return new AzureOpenAiEmbeddingModel(openAIClient);
 		}
 
 	}

models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/MockAzureOpenAiTestConfiguration.java

@@ -59,8 +59,8 @@ public class MockAzureOpenAiTestConfiguration {
 	}
 
 	@Bean
-	AzureOpenAiModelCaller azureOpenAiChatClient(OpenAIClient microsoftAzureOpenAiClient) {
-		return new AzureOpenAiModelCaller(microsoftAzureOpenAiClient);
+	AzureOpenAiChatModel azureOpenAiChatModel(OpenAIClient microsoftAzureOpenAiClient) {
+		return new AzureOpenAiChatModel(microsoftAzureOpenAiClient);
 	}
 
 }

models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/function/AzureOpenAiChatModelFunctionCallIT.java

@@ -29,7 +29,7 @@ import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-import org.springframework.ai.azure.openai.AzureOpenAiModelCaller;
+import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
 import org.springframework.ai.azure.openai.AzureOpenAiChatOptions;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
@@ -46,18 +46,18 @@ import reactor.core.publisher.Flux;
 
 import static org.assertj.core.api.Assertions.assertThat;
 
-@SpringBootTest(classes = AzureOpenAiModelCallFunctionCallIT.TestConfiguration.class)
+@SpringBootTest(classes = AzureOpenAiChatModelFunctionCallIT.TestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "AZURE_OPENAI_API_KEY", matches = ".+")
 @EnabledIfEnvironmentVariable(named = "AZURE_OPENAI_ENDPOINT", matches = ".+")
-class AzureOpenAiModelCallFunctionCallIT {
+class AzureOpenAiChatModelFunctionCallIT {
 
-	private static final Logger logger = LoggerFactory.getLogger(AzureOpenAiModelCallFunctionCallIT.class);
+	private static final Logger logger = LoggerFactory.getLogger(AzureOpenAiChatModelFunctionCallIT.class);
 
 	@Autowired
 	private String selectedModel;
 
 	@Autowired
-	private AzureOpenAiModelCaller chatClient;
+	private AzureOpenAiChatModel chatModel;
 
 	@Test
 	void functionCallTest() {
@@ -75,7 +75,7 @@ class AzureOpenAiModelCallFunctionCallIT {
 				.build()))
 			.build();
 
-		ChatResponse response = chatClient.call(new Prompt(messages, promptOptions));
+		ChatResponse response = chatModel.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
@@ -99,7 +99,7 @@ class AzureOpenAiModelCallFunctionCallIT {
 				.build()))
 			.build();
 
-		Flux<ChatResponse> response = chatClient.stream(new Prompt(messages, promptOptions));
+		Flux<ChatResponse> response = chatModel.stream(new Prompt(messages, promptOptions));
 
 		final var counter = new AtomicInteger();
 		String content = response.doOnEach(listSignal -> counter.getAndIncrement())
@@ -129,8 +129,8 @@ class AzureOpenAiModelCallFunctionCallIT {
 		}
 
 		@Bean
-		public AzureOpenAiModelCaller azureOpenAiChatClient(OpenAIClient openAIClient, String selectedModel) {
-			return new AzureOpenAiModelCaller(openAIClient,
+		public AzureOpenAiChatModel azureOpenAiChatModel(OpenAIClient openAIClient, String selectedModel) {
+			return new AzureOpenAiChatModel(openAIClient,
 					AzureOpenAiChatOptions.builder().withDeploymentName(selectedModel).withMaxTokens(500).build());
 		}
 

models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/metadata/AzureOpenAiChatModelMetadataTests.java

@@ -23,7 +23,7 @@ import com.azure.ai.openai.models.ContentFilterResultsForChoice;
 import com.azure.ai.openai.models.ContentFilterSeverity;
 import org.junit.jupiter.api.Test;
 
-import org.springframework.ai.azure.openai.AzureOpenAiModelCaller;
+import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
 import org.springframework.ai.azure.openai.MockAzureOpenAiTestConfiguration;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
@@ -55,7 +55,7 @@ import org.springframework.web.context.request.WebRequest;
 import static org.assertj.core.api.Assertions.assertThat;
 
 /**
- * Unit Tests for {@link AzureOpenAiModelCaller} asserting AI metadata.
+ * Unit Tests for {@link AzureOpenAiChatModel} asserting AI metadata.
  *
  * @author John Blum
  * @author Christian Tzolov
@@ -63,12 +63,12 @@ import static org.assertj.core.api.Assertions.assertThat;
  */
 @SpringBootTest
 @ActiveProfiles("spring-ai-azure-openai-mocks")
-@ContextConfiguration(classes = AzureOpenAiModelCallMetadataTests.TestConfiguration.class)
+@ContextConfiguration(classes = AzureOpenAiChatModelMetadataTests.TestConfiguration.class)
 @SuppressWarnings("unused")
-class AzureOpenAiModelCallMetadataTests {
+class AzureOpenAiChatModelMetadataTests {
 
 	@Autowired
-	private AzureOpenAiModelCaller aiClient;
+	private AzureOpenAiChatModel aiClient;
 
 	@Test
 	void azureOpenAiMetadataCapturedDuringGeneration() {

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicChatModel.java

@@ -17,7 +17,7 @@ package org.springframework.ai.bedrock.anthropic;
 
 import java.util.List;
 
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.prompt.ChatOptions;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
@@ -27,25 +27,25 @@ import org.springframework.ai.bedrock.MessageToPromptConverter;
 import org.springframework.ai.bedrock.anthropic.api.AnthropicChatBedrockApi;
 import org.springframework.ai.bedrock.anthropic.api.AnthropicChatBedrockApi.AnthropicChatRequest;
 import org.springframework.ai.bedrock.anthropic.api.AnthropicChatBedrockApi.AnthropicChatResponse;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.Generation;
 import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.ai.model.ModelOptionsUtils;
 
 /**
- * Java {@link ChatCaller} and {@link StreamingChatCaller} for the Bedrock Anthropic chat
+ * Java {@link ChatModel} and {@link StreamingChatModel} for the Bedrock Anthropic chat
  * generative.
  *
  * @author Christian Tzolov
  * @since 0.8.0
  */
-public class BedrockAnthropicModelCaller implements ChatCaller, StreamingChatCaller {
+public class BedrockAnthropicChatModel implements ChatModel, StreamingChatModel {
 
 	private final AnthropicChatBedrockApi anthropicChatApi;
 
 	private final AnthropicChatOptions defaultOptions;
 
-	public BedrockAnthropicModelCaller(AnthropicChatBedrockApi chatApi) {
+	public BedrockAnthropicChatModel(AnthropicChatBedrockApi chatApi) {
 		this(chatApi,
 				AnthropicChatOptions.builder()
 					.withTemperature(0.8f)
@@ -55,7 +55,7 @@ public class BedrockAnthropicModelCaller implements ChatCaller, StreamingChatCal
 					.build());
 	}
 
-	public BedrockAnthropicModelCaller(AnthropicChatBedrockApi chatApi, AnthropicChatOptions options) {
+	public BedrockAnthropicChatModel(AnthropicChatBedrockApi chatApi, AnthropicChatOptions options) {
 		this.anthropicChatApi = chatApi;
 		this.defaultOptions = options;
 	}

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3ChatModel.java

@@ -15,18 +15,25 @@
  */
 package org.springframework.ai.bedrock.anthropic3;
 
-import org.springframework.ai.bedrock.anthropic.AnthropicChatOptions;
+import java.util.ArrayList;
+import java.util.Base64;
+import java.util.List;
+import java.util.concurrent.atomic.AtomicReference;
+import java.util.stream.Collectors;
+
+import reactor.core.publisher.Flux;
+
 import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi;
 import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi.AnthropicChatRequest;
 import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi.AnthropicChatResponse;
 import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi.AnthropicChatStreamingResponse.StreamingType;
-import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi.MediaContent;
 import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi.ChatCompletionMessage;
 import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi.ChatCompletionMessage.Role;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.bedrock.anthropic3.api.Anthropic3ChatBedrockApi.MediaContent;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.messages.Message;
 import org.springframework.ai.chat.messages.MessageType;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
@@ -35,29 +42,21 @@ import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.ai.model.ModelOptionsUtils;
 import org.springframework.util.CollectionUtils;
 
-import reactor.core.publisher.Flux;
-
-import java.util.ArrayList;
-import java.util.Base64;
-import java.util.List;
-import java.util.concurrent.atomic.AtomicReference;
-import java.util.stream.Collectors;
-
 /**
- * Java {@link ChatCaller} and {@link StreamingChatCaller} for the Bedrock Anthropic chat
+ * Java {@link ChatModel} and {@link StreamingChatModel} for the Bedrock Anthropic chat
  * generative.
  *
  * @author Ben Middleton
  * @author Christian Tzolov
  * @since 1.0.0
  */
-public class BedrockAnthropic3ModelCaller implements ChatCaller, StreamingChatCaller {
+public class BedrockAnthropic3ChatModel implements ChatModel, StreamingChatModel {
 
 	private final Anthropic3ChatBedrockApi anthropicChatApi;
 
 	private final Anthropic3ChatOptions defaultOptions;
 
-	public BedrockAnthropic3ModelCaller(Anthropic3ChatBedrockApi chatApi) {
+	public BedrockAnthropic3ChatModel(Anthropic3ChatBedrockApi chatApi) {
 		this(chatApi,
 				Anthropic3ChatOptions.builder()
 					.withTemperature(0.8f)
@@ -67,7 +66,7 @@ public class BedrockAnthropic3ModelCaller implements ChatCaller, StreamingChatCa
 					.build());
 	}
 
-	public BedrockAnthropic3ModelCaller(Anthropic3ChatBedrockApi chatApi, Anthropic3ChatOptions options) {
+	public BedrockAnthropic3ChatModel(Anthropic3ChatBedrockApi chatApi, Anthropic3ChatOptions options) {
 		this.anthropicChatApi = chatApi;
 		this.defaultOptions = options;
 	}

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatModel.java

@@ -24,11 +24,11 @@ import org.springframework.ai.bedrock.MessageToPromptConverter;
 import org.springframework.ai.bedrock.cohere.api.CohereChatBedrockApi;
 import org.springframework.ai.bedrock.cohere.api.CohereChatBedrockApi.CohereChatRequest;
 import org.springframework.ai.bedrock.cohere.api.CohereChatBedrockApi.CohereChatResponse;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.prompt.ChatOptions;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.metadata.Usage;
 import org.springframework.ai.chat.prompt.Prompt;
@@ -39,17 +39,17 @@ import org.springframework.util.Assert;
  * @author Christian Tzolov
  * @since 0.8.0
  */
-public class BedrockCohereModelCaller implements ChatCaller, StreamingChatCaller {
+public class BedrockCohereChatModel implements ChatModel, StreamingChatModel {
 
 	private final CohereChatBedrockApi chatApi;
 
 	private final BedrockCohereChatOptions defaultOptions;
 
-	public BedrockCohereModelCaller(CohereChatBedrockApi chatApi) {
+	public BedrockCohereChatModel(CohereChatBedrockApi chatApi) {
 		this(chatApi, BedrockCohereChatOptions.builder().build());
 	}
 
-	public BedrockCohereModelCaller(CohereChatBedrockApi chatApi, BedrockCohereChatOptions options) {
+	public BedrockCohereChatModel(CohereChatBedrockApi chatApi, BedrockCohereChatOptions options) {
 		Assert.notNull(chatApi, "CohereChatBedrockApi must not be null");
 		Assert.notNull(options, "BedrockCohereChatOptions must not be null");
 

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/cohere/BedrockCohereEmbeddingModel.java

@@ -22,7 +22,7 @@ import org.springframework.ai.bedrock.cohere.api.CohereEmbeddingBedrockApi;
 import org.springframework.ai.bedrock.cohere.api.CohereEmbeddingBedrockApi.CohereEmbeddingRequest;
 import org.springframework.ai.bedrock.cohere.api.CohereEmbeddingBedrockApi.CohereEmbeddingResponse;
 import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -31,14 +31,14 @@ import org.springframework.ai.model.ModelOptionsUtils;
 import org.springframework.util.Assert;
 
 /**
- * {@link org.springframework.ai.embedding.EmbeddingClient} implementation that uses the
+ * {@link org.springframework.ai.embedding.EmbeddingModel} implementation that uses the
  * Bedrock Cohere Embedding API. Note: The invocation metrics are not exposed by AWS for
  * this API. If this change in the future we will add it as metadata.
  *
  * @author Christian Tzolov
  * @since 0.8.0
  */
-public class BedrockCohereEmbeddingClient extends AbstractEmbeddingClient {
+public class BedrockCohereEmbeddingModel extends AbstractEmbeddingModel {
 
 	private final CohereEmbeddingBedrockApi embeddingApi;
 
@@ -50,7 +50,7 @@ public class BedrockCohereEmbeddingClient extends AbstractEmbeddingClient {
 	// private CohereEmbeddingRequest.Truncate truncate =
 	// CohereEmbeddingRequest.Truncate.NONE;
 
-	public BedrockCohereEmbeddingClient(CohereEmbeddingBedrockApi cohereEmbeddingBedrockApi) {
+	public BedrockCohereEmbeddingModel(CohereEmbeddingBedrockApi cohereEmbeddingBedrockApi) {
 		this(cohereEmbeddingBedrockApi,
 				BedrockCohereEmbeddingOptions.builder()
 					.withInputType(CohereEmbeddingRequest.InputType.SEARCH_DOCUMENT)
@@ -58,7 +58,7 @@ public class BedrockCohereEmbeddingClient extends AbstractEmbeddingClient {
 					.build());
 	}
 
-	public BedrockCohereEmbeddingClient(CohereEmbeddingBedrockApi cohereEmbeddingBedrockApi,
+	public BedrockCohereEmbeddingModel(CohereEmbeddingBedrockApi cohereEmbeddingBedrockApi,
 			BedrockCohereEmbeddingOptions options) {
 		Assert.notNull(cohereEmbeddingBedrockApi, "CohereEmbeddingBedrockApi must not be null");
 		Assert.notNull(options, "BedrockCohereEmbeddingOptions must not be null");
@@ -71,7 +71,7 @@ public class BedrockCohereEmbeddingClient extends AbstractEmbeddingClient {
 	// * @param inputType the input type to use.
 	// * @return this client.
 	// */
-	// public BedrockCohereEmbeddingClient withInputType(CohereEmbeddingRequest.InputType
+	// public BedrockCohereEmbeddingModel withInputType(CohereEmbeddingRequest.InputType
 	// inputType) {
 	// this.inputType = inputType;
 	// return this;
@@ -85,7 +85,7 @@ public class BedrockCohereEmbeddingClient extends AbstractEmbeddingClient {
 	// * @param truncate the truncate option to use.
 	// * @return this client.
 	// */
-	// public BedrockCohereEmbeddingClient withTruncate(CohereEmbeddingRequest.Truncate
+	// public BedrockCohereEmbeddingModel withTruncate(CohereEmbeddingRequest.Truncate
 	// truncate) {
 	// this.truncate = truncate;
 	// return this;

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/jurassic2/BedrockAi21Jurassic2ChatModel.java

@@ -19,7 +19,7 @@ package org.springframework.ai.bedrock.jurassic2;
 import org.springframework.ai.bedrock.MessageToPromptConverter;
 import org.springframework.ai.bedrock.jurassic2.api.Ai21Jurassic2ChatBedrockApi;
 import org.springframework.ai.bedrock.jurassic2.api.Ai21Jurassic2ChatBedrockApi.Ai21Jurassic2ChatRequest;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
@@ -29,19 +29,18 @@ import org.springframework.ai.model.ModelOptionsUtils;
 import org.springframework.util.Assert;
 
 /**
- * Java {@link ChatCaller} for the Bedrock Jurassic2 chat generative model.
+ * Java {@link ChatModel} for the Bedrock Jurassic2 chat generative model.
  *
  * @author Ahmed Yousri
  * @since 1.0.0
  */
-public class BedrockAi21Jurassic2ModelCaller implements ChatCaller {
+public class BedrockAi21Jurassic2ChatModel implements ChatModel {
 
 	private final Ai21Jurassic2ChatBedrockApi chatApi;
 
 	private final BedrockAi21Jurassic2ChatOptions defaultOptions;
 
-	public BedrockAi21Jurassic2ModelCaller(Ai21Jurassic2ChatBedrockApi chatApi,
-			BedrockAi21Jurassic2ChatOptions options) {
+	public BedrockAi21Jurassic2ChatModel(Ai21Jurassic2ChatBedrockApi chatApi, BedrockAi21Jurassic2ChatOptions options) {
 		Assert.notNull(chatApi, "Ai21Jurassic2ChatBedrockApi must not be null");
 		Assert.notNull(options, "BedrockAi21Jurassic2ChatOptions must not be null");
 
@@ -49,7 +48,7 @@ public class BedrockAi21Jurassic2ModelCaller implements ChatCaller {
 		this.defaultOptions = options;
 	}
 
-	public BedrockAi21Jurassic2ModelCaller(Ai21Jurassic2ChatBedrockApi chatApi) {
+	public BedrockAi21Jurassic2ChatModel(Ai21Jurassic2ChatBedrockApi chatApi) {
 		this(chatApi,
 				BedrockAi21Jurassic2ChatOptions.builder()
 					.withTemperature(0.8f)
@@ -114,8 +113,8 @@ public class BedrockAi21Jurassic2ModelCaller implements ChatCaller {
 			return this;
 		}
 
-		public BedrockAi21Jurassic2ModelCaller build() {
-			return new BedrockAi21Jurassic2ModelCaller(chatApi,
+		public BedrockAi21Jurassic2ChatModel build() {
+			return new BedrockAi21Jurassic2ChatModel(chatApi,
 					options != null ? options : BedrockAi21Jurassic2ChatOptions.builder().build());
 		}
 

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/llama/BedrockLlamaChatModel.java

@@ -23,11 +23,11 @@ import org.springframework.ai.bedrock.MessageToPromptConverter;
 import org.springframework.ai.bedrock.llama.api.LlamaChatBedrockApi;
 import org.springframework.ai.bedrock.llama.api.LlamaChatBedrockApi.LlamaChatRequest;
 import org.springframework.ai.bedrock.llama.api.LlamaChatBedrockApi.LlamaChatResponse;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.prompt.ChatOptions;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.metadata.Usage;
 import org.springframework.ai.chat.prompt.Prompt;
@@ -35,25 +35,25 @@ import org.springframework.ai.model.ModelOptionsUtils;
 import org.springframework.util.Assert;
 
 /**
- * Java {@link ChatCaller} and {@link StreamingChatCaller} for the Bedrock Llama chat
+ * Java {@link ChatModel} and {@link StreamingChatModel} for the Bedrock Llama chat
  * generative.
  *
  * @author Christian Tzolov
  * @author Wei Jiang
  * @since 0.8.0
  */
-public class BedrockLlamaModelCaller implements ChatCaller, StreamingChatCaller {
+public class BedrockLlamaChatModel implements ChatModel, StreamingChatModel {
 
 	private final LlamaChatBedrockApi chatApi;
 
 	private final BedrockLlamaChatOptions defaultOptions;
 
-	public BedrockLlamaModelCaller(LlamaChatBedrockApi chatApi) {
+	public BedrockLlamaChatModel(LlamaChatBedrockApi chatApi) {
 		this(chatApi,
 				BedrockLlamaChatOptions.builder().withTemperature(0.8f).withTopP(0.9f).withMaxGenLen(100).build());
 	}
 
-	public BedrockLlamaModelCaller(LlamaChatBedrockApi chatApi, BedrockLlamaChatOptions options) {
+	public BedrockLlamaChatModel(LlamaChatBedrockApi chatApi, BedrockLlamaChatOptions options) {
 		Assert.notNull(chatApi, "LlamaChatBedrockApi must not be null");
 		Assert.notNull(options, "BedrockLlamaChatOptions must not be null");
 

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanChatModel.java

@@ -24,11 +24,11 @@ import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi;
 import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi.TitanChatRequest;
 import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi.TitanChatResponse;
 import org.springframework.ai.bedrock.titan.api.TitanChatBedrockApi.TitanChatResponseChunk;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.prompt.ChatOptions;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.metadata.Usage;
 import org.springframework.ai.chat.prompt.Prompt;
@@ -39,17 +39,17 @@ import org.springframework.util.Assert;
  * @author Christian Tzolov
  * @since 0.8.0
  */
-public class BedrockTitanModelCaller implements ChatCaller, StreamingChatCaller {
+public class BedrockTitanChatModel implements ChatModel, StreamingChatModel {
 
 	private final TitanChatBedrockApi chatApi;
 
 	private final BedrockTitanChatOptions defaultOptions;
 
-	public BedrockTitanModelCaller(TitanChatBedrockApi chatApi) {
+	public BedrockTitanChatModel(TitanChatBedrockApi chatApi) {
 		this(chatApi, BedrockTitanChatOptions.builder().withTemperature(0.8f).build());
 	}
 
-	public BedrockTitanModelCaller(TitanChatBedrockApi chatApi, BedrockTitanChatOptions defaultOptions) {
+	public BedrockTitanChatModel(TitanChatBedrockApi chatApi, BedrockTitanChatOptions defaultOptions) {
 		Assert.notNull(chatApi, "ChatApi must not be null");
 		Assert.notNull(defaultOptions, "DefaultOptions must not be null");
 		this.chatApi = chatApi;

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanEmbeddingModel.java

@@ -26,7 +26,7 @@ import org.springframework.ai.bedrock.titan.api.TitanEmbeddingBedrockApi;
 import org.springframework.ai.bedrock.titan.api.TitanEmbeddingBedrockApi.TitanEmbeddingRequest;
 import org.springframework.ai.bedrock.titan.api.TitanEmbeddingBedrockApi.TitanEmbeddingResponse;
 import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -34,7 +34,7 @@ import org.springframework.ai.embedding.EmbeddingResponse;
 import org.springframework.util.Assert;
 
 /**
- * {@link org.springframework.ai.embedding.EmbeddingClient} implementation that uses the
+ * {@link org.springframework.ai.embedding.EmbeddingModel} implementation that uses the
  * Bedrock Titan Embedding API. Titan Embedding supports text and image (encoded in
  * base64) inputs.
  *
@@ -44,7 +44,7 @@ import org.springframework.util.Assert;
  * @author Wei Jiang
  * @since 0.8.0
  */
-public class BedrockTitanEmbeddingClient extends AbstractEmbeddingClient {
+public class BedrockTitanEmbeddingModel extends AbstractEmbeddingModel {
 
 	private final Logger logger = LoggerFactory.getLogger(getClass());
 
@@ -61,7 +61,7 @@ public class BedrockTitanEmbeddingClient extends AbstractEmbeddingClient {
 	 */
 	private InputType inputType = InputType.TEXT;
 
-	public BedrockTitanEmbeddingClient(TitanEmbeddingBedrockApi titanEmbeddingBedrockApi) {
+	public BedrockTitanEmbeddingModel(TitanEmbeddingBedrockApi titanEmbeddingBedrockApi) {
 		this.embeddingApi = titanEmbeddingBedrockApi;
 	}
 
@@ -69,7 +69,7 @@ public class BedrockTitanEmbeddingClient extends AbstractEmbeddingClient {
 	 * Titan Embedding API input types. Could be either text or image (encoded in base64).
 	 * @param inputType the input type to use.
 	 */
-	public BedrockTitanEmbeddingClient withInputType(InputType inputType) {
+	public BedrockTitanEmbeddingModel withInputType(InputType inputType) {
 		this.inputType = inputType;
 		return this;
 	}

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanEmbeddingOptions.java

@@ -18,7 +18,7 @@ package org.springframework.ai.bedrock.titan;
 import com.fasterxml.jackson.annotation.JsonInclude;
 import com.fasterxml.jackson.annotation.JsonInclude.Include;
 
-import org.springframework.ai.bedrock.titan.BedrockTitanEmbeddingClient.InputType;
+import org.springframework.ai.bedrock.titan.BedrockTitanEmbeddingModel.InputType;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.util.Assert;
 

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicChatModelIT.java

@@ -55,12 +55,12 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AWS_ACCESS_KEY_ID", matches = ".*")
 @EnabledIfEnvironmentVariable(named = "AWS_SECRET_ACCESS_KEY", matches = ".*")
-class BedrockAnthropicModelCallerIT {
+class BedrockAnthropicChatModelIT {
 
-	private static final Logger logger = LoggerFactory.getLogger(BedrockAnthropicModelCallerIT.class);
+	private static final Logger logger = LoggerFactory.getLogger(BedrockAnthropicChatModelIT.class);
 
 	@Autowired
-	private BedrockAnthropicModelCaller client;
+	private BedrockAnthropicChatModel chatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -68,8 +68,8 @@ class BedrockAnthropicModelCallerIT {
 	@Test
 	void multipleStreamAttempts() {
 
-		Flux<ChatResponse> joke1Stream = client.stream(new Prompt(new UserMessage("Tell me a joke?")));
-		Flux<ChatResponse> joke2Stream = client.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
+		Flux<ChatResponse> joke1Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a joke?")));
+		Flux<ChatResponse> joke2Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
 
 		String joke1 = joke1Stream.collectList()
 			.block()
@@ -101,7 +101,7 @@ class BedrockAnthropicModelCallerIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -119,7 +119,7 @@ class BedrockAnthropicModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputParser.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -137,7 +137,7 @@ class BedrockAnthropicModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -161,7 +161,7 @@ class BedrockAnthropicModelCallerIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConvert.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -182,7 +182,7 @@ class BedrockAnthropicModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = client.stream(prompt)
+		String generationTextFromStream = chatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -209,8 +209,8 @@ class BedrockAnthropicModelCallerIT {
 		}
 
 		@Bean
-		public BedrockAnthropicModelCaller anthropicChatClient(AnthropicChatBedrockApi anthropicApi) {
-			return new BedrockAnthropicModelCaller(anthropicApi);
+		public BedrockAnthropicChatModel anthropicChatModel(AnthropicChatBedrockApi anthropicApi) {
+			return new BedrockAnthropicChatModel(anthropicApi);
 		}
 
 	}

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicCreateRequestTests.java

@@ -38,7 +38,7 @@ public class BedrockAnthropicCreateRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new BedrockAnthropicModelCaller(anthropicChatApi,
+		var client = new BedrockAnthropicChatModel(anthropicChatApi,
 				AnthropicChatOptions.builder()
 					.withTemperature(66.6f)
 					.withTopK(66)

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3ChatModelIT.java

@@ -59,12 +59,12 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AWS_ACCESS_KEY_ID", matches = ".*")
 @EnabledIfEnvironmentVariable(named = "AWS_SECRET_ACCESS_KEY", matches = ".*")
-class BedrockAnthropic3ModelCallerIT {
+class BedrockAnthropic3ChatModelIT {
 
-	private static final Logger logger = LoggerFactory.getLogger(BedrockAnthropic3ModelCallerIT.class);
+	private static final Logger logger = LoggerFactory.getLogger(BedrockAnthropic3ChatModelIT.class);
 
 	@Autowired
-	private BedrockAnthropic3ModelCaller client;
+	private BedrockAnthropic3ChatModel chatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -72,8 +72,8 @@ class BedrockAnthropic3ModelCallerIT {
 	@Test
 	void multipleStreamAttempts() {
 
-		Flux<ChatResponse> joke1Stream = client.stream(new Prompt(new UserMessage("Tell me a joke?")));
-		Flux<ChatResponse> joke2Stream = client.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
+		Flux<ChatResponse> joke1Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a joke?")));
+		Flux<ChatResponse> joke2Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
 
 		String joke1 = joke1Stream.collectList()
 			.block()
@@ -105,7 +105,7 @@ class BedrockAnthropic3ModelCallerIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -123,7 +123,7 @@ class BedrockAnthropic3ModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -142,7 +142,7 @@ class BedrockAnthropic3ModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -166,7 +166,7 @@ class BedrockAnthropic3ModelCallerIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -187,7 +187,7 @@ class BedrockAnthropic3ModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = client.stream(prompt)
+		String generationTextFromStream = chatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -211,7 +211,7 @@ class BedrockAnthropic3ModelCallerIT {
 		var userMessage = new UserMessage("Explain what do you see o this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		var response = client.call(new Prompt(List.of(userMessage)));
+		var response = chatModel.call(new Prompt(List.of(userMessage)));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple", "basket");
@@ -228,8 +228,8 @@ class BedrockAnthropic3ModelCallerIT {
 		}
 
 		@Bean
-		public BedrockAnthropic3ModelCaller anthropicChatClient(Anthropic3ChatBedrockApi anthropicApi) {
-			return new BedrockAnthropic3ModelCaller(anthropicApi);
+		public BedrockAnthropic3ChatModel anthropicChatModel(Anthropic3ChatBedrockApi anthropicApi) {
+			return new BedrockAnthropic3ChatModel(anthropicApi);
 		}
 
 	}

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3CreateRequestTests.java

@@ -37,7 +37,7 @@ public class BedrockAnthropic3CreateRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new BedrockAnthropic3ModelCaller(anthropicChatApi,
+		var client = new BedrockAnthropic3ChatModel(anthropicChatApi,
 				Anthropic3ChatOptions.builder()
 					.withTemperature(66.6f)
 					.withTopK(66)

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatCreateRequestTests.java

@@ -45,7 +45,7 @@ public class BedrockCohereChatCreateRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new BedrockCohereModelCaller(chatApi,
+		var client = new BedrockCohereChatModel(chatApi,
 				BedrockCohereChatOptions.builder()
 					.withTemperature(66.6f)
 					.withTopK(66)

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatModelIT.java

@@ -54,10 +54,10 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AWS_ACCESS_KEY_ID", matches = ".*")
 @EnabledIfEnvironmentVariable(named = "AWS_SECRET_ACCESS_KEY", matches = ".*")
-class BedrockCohereModelCallerIT {
+class BedrockCohereChatModelIT {
 
 	@Autowired
-	private BedrockCohereModelCaller client;
+	private BedrockCohereChatModel chatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -65,8 +65,8 @@ class BedrockCohereModelCallerIT {
 	@Test
 	void multipleStreamAttempts() {
 
-		Flux<ChatResponse> joke1Stream = client.stream(new Prompt(new UserMessage("Tell me a joke?")));
-		Flux<ChatResponse> joke2Stream = client.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
+		Flux<ChatResponse> joke1Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a joke?")));
+		Flux<ChatResponse> joke2Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
 
 		String joke1 = joke1Stream.collectList()
 			.block()
@@ -98,7 +98,7 @@ class BedrockCohereModelCallerIT {
 		SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate(systemResource);
 		Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", name, "voice", voice));
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
 
@@ -115,7 +115,7 @@ class BedrockCohereModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -134,7 +134,7 @@ class BedrockCohereModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -157,7 +157,7 @@ class BedrockCohereModelCallerIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -178,7 +178,7 @@ class BedrockCohereModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = client.stream(prompt)
+		String generationTextFromStream = chatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -205,8 +205,8 @@ class BedrockCohereModelCallerIT {
 		}
 
 		@Bean
-		public BedrockCohereModelCaller cohereChatClient(CohereChatBedrockApi cohereApi) {
-			return new BedrockCohereModelCaller(cohereApi);
+		public BedrockCohereChatModel cohereChatModel(CohereChatBedrockApi cohereApi) {
+			return new BedrockCohereChatModel(cohereApi);
 		}
 
 	}

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/cohere/BedrockCohereEmbeddingModelIT.java

@@ -39,24 +39,24 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AWS_ACCESS_KEY_ID", matches = ".*")
 @EnabledIfEnvironmentVariable(named = "AWS_SECRET_ACCESS_KEY", matches = ".*")
-class BedrockCohereEmbeddingClientIT {
+class BedrockCohereEmbeddingModelIT {
 
 	@Autowired
-	private BedrockCohereEmbeddingClient embeddingClient;
+	private BedrockCohereEmbeddingModel embeddingModel;
 
 	@Test
 	void singleEmbedding() {
-		assertThat(embeddingClient).isNotNull();
-		EmbeddingResponse embeddingResponse = embeddingClient.embedForResponse(List.of("Hello World"));
+		assertThat(embeddingModel).isNotNull();
+		EmbeddingResponse embeddingResponse = embeddingModel.embedForResponse(List.of("Hello World"));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).isNotEmpty();
-		assertThat(embeddingClient.dimensions()).isEqualTo(1024);
+		assertThat(embeddingModel.dimensions()).isEqualTo(1024);
 	}
 
 	@Test
 	void batchEmbedding() {
-		assertThat(embeddingClient).isNotNull();
-		EmbeddingResponse embeddingResponse = embeddingClient
+		assertThat(embeddingModel).isNotNull();
+		EmbeddingResponse embeddingResponse = embeddingModel
 			.embedForResponse(List.of("Hello World", "World is big and salvation is near"));
 		assertThat(embeddingResponse.getResults()).hasSize(2);
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).isNotEmpty();
@@ -64,13 +64,13 @@ class BedrockCohereEmbeddingClientIT {
 		assertThat(embeddingResponse.getResults().get(1).getOutput()).isNotEmpty();
 		assertThat(embeddingResponse.getResults().get(1).getIndex()).isEqualTo(1);
 
-		assertThat(embeddingClient.dimensions()).isEqualTo(1024);
+		assertThat(embeddingModel.dimensions()).isEqualTo(1024);
 	}
 
 	@Test
 	void embeddingWthOptions() {
-		assertThat(embeddingClient).isNotNull();
-		EmbeddingResponse embeddingResponse = embeddingClient
+		assertThat(embeddingModel).isNotNull();
+		EmbeddingResponse embeddingResponse = embeddingModel
 			.call(new EmbeddingRequest(List.of("Hello World", "World is big and salvation is near"),
 					BedrockCohereEmbeddingOptions.builder().withInputType(InputType.SEARCH_DOCUMENT).build()));
 		assertThat(embeddingResponse.getResults()).hasSize(2);
@@ -79,7 +79,7 @@ class BedrockCohereEmbeddingClientIT {
 		assertThat(embeddingResponse.getResults().get(1).getOutput()).isNotEmpty();
 		assertThat(embeddingResponse.getResults().get(1).getIndex()).isEqualTo(1);
 
-		assertThat(embeddingClient.dimensions()).isEqualTo(1024);
+		assertThat(embeddingModel.dimensions()).isEqualTo(1024);
 	}
 
 	@SpringBootConfiguration
@@ -93,8 +93,8 @@ class BedrockCohereEmbeddingClientIT {
 		}
 
 		@Bean
-		public BedrockCohereEmbeddingClient cohereAiEmbedding(CohereEmbeddingBedrockApi cohereEmbeddingApi) {
-			return new BedrockCohereEmbeddingClient(cohereEmbeddingApi);
+		public BedrockCohereEmbeddingModel cohereAiEmbedding(CohereEmbeddingBedrockApi cohereEmbeddingApi) {
+			return new BedrockCohereEmbeddingModel(cohereEmbeddingApi);
 		}
 
 	}

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/jurassic2/BedrockAi21Jurassic2ChatModelIT.java

@@ -49,10 +49,10 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AWS_ACCESS_KEY_ID", matches = ".*")
 @EnabledIfEnvironmentVariable(named = "AWS_SECRET_ACCESS_KEY", matches = ".*")
-class BedrockAi21Jurassic2ModelCallerIT {
+class BedrockAi21Jurassic2ChatModelIT {
 
 	@Autowired
-	private BedrockAi21Jurassic2ModelCaller client;
+	private BedrockAi21Jurassic2ChatModel chatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -66,7 +66,7 @@ class BedrockAi21Jurassic2ModelCallerIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -83,7 +83,7 @@ class BedrockAi21Jurassic2ModelCallerIT {
 		UserMessage userMessage = new UserMessage("Can you express happiness using an emoji like 😄 ?");
 		Prompt prompt = new Prompt(List.of(userMessage), options);
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).matches(content -> content.contains("😄"));
 	}
@@ -103,7 +103,7 @@ class BedrockAi21Jurassic2ModelCallerIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage), options);
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).doesNotContain("😄");
 	}
@@ -120,7 +120,7 @@ class BedrockAi21Jurassic2ModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -135,7 +135,7 @@ class BedrockAi21Jurassic2ModelCallerIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("AI");
 	}
@@ -152,9 +152,9 @@ class BedrockAi21Jurassic2ModelCallerIT {
 		}
 
 		@Bean
-		public BedrockAi21Jurassic2ModelCaller bedrockAi21Jurassic2ChatClient(
+		public BedrockAi21Jurassic2ChatModel bedrockAi21Jurassic2ChatModel(
 				Ai21Jurassic2ChatBedrockApi jurassic2ChatBedrockApi) {
-			return new BedrockAi21Jurassic2ModelCaller(jurassic2ChatBedrockApi,
+			return new BedrockAi21Jurassic2ChatModel(jurassic2ChatBedrockApi,
 					BedrockAi21Jurassic2ChatOptions.builder()
 						.withTemperature(0.5f)
 						.withMaxTokens(100)

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/llama/BedrockLlamaCreateRequestTests.java

@@ -45,7 +45,7 @@ public class BedrockLlamaCreateRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new BedrockLlamaModelCaller(api,
+		var client = new BedrockLlamaChatModel(api,
 				BedrockLlamaChatOptions.builder().withTemperature(66.6f).withMaxGenLen(666).withTopP(0.66f).build());
 
 		var request = client.createRequest(new Prompt("Test message content"));

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/llama/BedrockLlamaModelCallerIT.java

@@ -54,10 +54,10 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AWS_ACCESS_KEY_ID", matches = ".*")
 @EnabledIfEnvironmentVariable(named = "AWS_SECRET_ACCESS_KEY", matches = ".*")
-class BedrockLlamaModelCallerIT {
+class BedrockLlamaChatModelIT {
 
 	@Autowired
-	private BedrockLlamaModelCaller client;
+	private BedrockLlamaChatModel chatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -65,8 +65,8 @@ class BedrockLlamaModelCallerIT {
 	@Test
 	void multipleStreamAttempts() {
 
-		Flux<ChatResponse> joke2Stream = client.stream(new Prompt(new UserMessage("Tell me a Toy joke?")));
-		Flux<ChatResponse> joke1Stream = client.stream(new Prompt(new UserMessage("Tell me a joke?")));
+		Flux<ChatResponse> joke2Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a Toy joke?")));
+		Flux<ChatResponse> joke1Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a joke?")));
 
 		String joke1 = joke1Stream.collectList()
 			.block()
@@ -98,7 +98,7 @@ class BedrockLlamaModelCallerIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -116,7 +116,7 @@ class BedrockLlamaModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -134,7 +134,7 @@ class BedrockLlamaModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -158,7 +158,7 @@ class BedrockLlamaModelCallerIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -179,7 +179,7 @@ class BedrockLlamaModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = client.stream(prompt)
+		String generationTextFromStream = chatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -206,8 +206,8 @@ class BedrockLlamaModelCallerIT {
 		}
 
 		@Bean
-		public BedrockLlamaModelCaller llamaChatClient(LlamaChatBedrockApi llamaApi) {
-			return new BedrockLlamaModelCaller(llamaApi,
+		public BedrockLlamaChatModel llamaChatModel(LlamaChatBedrockApi llamaApi) {
+			return new BedrockLlamaChatModel(llamaApi,
 					BedrockLlamaChatOptions.builder().withTemperature(0.5f).withMaxGenLen(100).withTopP(0.9f).build());
 		}
 

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/titan/BedrockTitanChatCreateRequestTests.java

@@ -41,7 +41,7 @@ public class BedrockTitanChatCreateRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new BedrockTitanModelCaller(api,
+		var client = new BedrockTitanChatModel(api,
 				BedrockTitanChatOptions.builder()
 					.withTemperature(66.6f)
 					.withTopP(0.66f)

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/titan/BedrockTitanEmbeddingModelIT.java

@@ -26,7 +26,7 @@ import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 import software.amazon.awssdk.auth.credentials.EnvironmentVariableCredentialsProvider;
 import software.amazon.awssdk.regions.Region;
 
-import org.springframework.ai.bedrock.titan.BedrockTitanEmbeddingClient.InputType;
+import org.springframework.ai.bedrock.titan.BedrockTitanEmbeddingModel.InputType;
 import org.springframework.ai.bedrock.titan.api.TitanEmbeddingBedrockApi;
 import org.springframework.ai.bedrock.titan.api.TitanEmbeddingBedrockApi.TitanEmbeddingModel;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -44,19 +44,19 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @EnabledIfEnvironmentVariable(named = "AWS_ACCESS_KEY_ID", matches = ".*")
 @EnabledIfEnvironmentVariable(named = "AWS_SECRET_ACCESS_KEY", matches = ".*")
-class BedrockTitanEmbeddingClientIT {
+class BedrockTitanEmbeddingModelIT {
 
 	@Autowired
-	private BedrockTitanEmbeddingClient embeddingClient;
+	private BedrockTitanEmbeddingModel embeddingModel;
 
 	@Test
 	void singleEmbedding() {
-		assertThat(embeddingClient).isNotNull();
-		EmbeddingResponse embeddingResponse = embeddingClient.call(new EmbeddingRequest(List.of("Hello World"),
+		assertThat(embeddingModel).isNotNull();
+		EmbeddingResponse embeddingResponse = embeddingModel.call(new EmbeddingRequest(List.of("Hello World"),
 				BedrockTitanEmbeddingOptions.builder().withInputType(InputType.TEXT).build()));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).isNotEmpty();
-		assertThat(embeddingClient.dimensions()).isEqualTo(1024);
+		assertThat(embeddingModel.dimensions()).isEqualTo(1024);
 	}
 
 	@Test
@@ -65,12 +65,12 @@ class BedrockTitanEmbeddingClientIT {
 		byte[] image = new DefaultResourceLoader().getResource("classpath:/spring_framework.png")
 			.getContentAsByteArray();
 
-		EmbeddingResponse embeddingResponse = embeddingClient
+		EmbeddingResponse embeddingResponse = embeddingModel
 			.call(new EmbeddingRequest(List.of(Base64.getEncoder().encodeToString(image)),
 					BedrockTitanEmbeddingOptions.builder().withInputType(InputType.IMAGE).build()));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).isNotEmpty();
-		assertThat(embeddingClient.dimensions()).isEqualTo(1024);
+		assertThat(embeddingModel.dimensions()).isEqualTo(1024);
 	}
 
 	@SpringBootConfiguration
@@ -84,8 +84,8 @@ class BedrockTitanEmbeddingClientIT {
 		}
 
 		@Bean
-		public BedrockTitanEmbeddingClient titanEmbedding(TitanEmbeddingBedrockApi titanEmbeddingApi) {
-			return new BedrockTitanEmbeddingClient(titanEmbeddingApi);
+		public BedrockTitanEmbeddingModel titanEmbedding(TitanEmbeddingBedrockApi titanEmbeddingApi) {
+			return new BedrockTitanEmbeddingModel(titanEmbeddingApi);
 		}
 
 	}

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/titan/BedrockTitanModelCalerlIT.java

@@ -58,7 +58,7 @@ import static org.assertj.core.api.Assertions.assertThat;
 class BedrockTitanModelCalerlIT {
 
 	@Autowired
-	private BedrockTitanModelCaller client;
+	private BedrockTitanChatModel chatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -66,8 +66,8 @@ class BedrockTitanModelCalerlIT {
 	@Test
 	void multipleStreamAttempts() {
 
-		Flux<ChatResponse> joke1Stream = client.stream(new Prompt(new UserMessage("Tell me a joke?")));
-		Flux<ChatResponse> joke2Stream = client.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
+		Flux<ChatResponse> joke1Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a joke?")));
+		Flux<ChatResponse> joke2Stream = chatModel.stream(new Prompt(new UserMessage("Tell me a toy joke?")));
 
 		String joke1 = joke1Stream.collectList()
 			.block()
@@ -99,7 +99,7 @@ class BedrockTitanModelCalerlIT {
 		SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate(systemResource);
 		Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", name, "voice", voice));
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
 
@@ -117,7 +117,7 @@ class BedrockTitanModelCalerlIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -138,7 +138,7 @@ class BedrockTitanModelCalerlIT {
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -162,7 +162,7 @@ class BedrockTitanModelCalerlIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -184,7 +184,7 @@ class BedrockTitanModelCalerlIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = client.stream(prompt)
+		String generationTextFromStream = chatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -211,8 +211,8 @@ class BedrockTitanModelCalerlIT {
 		}
 
 		@Bean
-		public BedrockTitanModelCaller titanChatClient(TitanChatBedrockApi titanApi) {
-			return new BedrockTitanModelCaller(titanApi);
+		public BedrockTitanChatModel titanChatModel(TitanChatBedrockApi titanApi) {
+			return new BedrockTitanChatModel(titanApi);
 		}
 
 	}

models/spring-ai-huggingface/src/main/java/org/springframework/ai/huggingface/HuggingfaceChatModel.java

@@ -22,7 +22,7 @@ import java.util.Map;
 import com.fasterxml.jackson.core.type.TypeReference;
 import com.fasterxml.jackson.databind.ObjectMapper;
 
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
 import org.springframework.ai.huggingface.api.TextGenerationInferenceApi;
@@ -36,12 +36,12 @@ import org.springframework.ai.chat.prompt.ChatOptionsBuilder;
 import org.springframework.ai.chat.prompt.Prompt;
 
 /**
- * An implementation of {@link ChatCaller} that interfaces with HuggingFace Inference
+ * An implementation of {@link ChatModel} that interfaces with HuggingFace Inference
  * Endpoints for text generation.
  *
  * @author Mark Pollack
  */
-public class HuggingfaceModelCaller implements ChatCaller {
+public class HuggingfaceChatModel implements ChatModel {
 
 	/**
 	 * Token required for authenticating with the HuggingFace Inference API.
@@ -70,11 +70,11 @@ public class HuggingfaceModelCaller implements ChatCaller {
 	private int maxNewTokens = 1000;
 
 	/**
-	 * Constructs a new HuggingfaceModelCall with the specified API token and base path.
+	 * Constructs a new HuggingfaceChatModel with the specified API token and base path.
 	 * @param apiToken The API token for HuggingFace.
 	 * @param basePath The base path for API requests.
 	 */
-	public HuggingfaceModelCaller(final String apiToken, String basePath) {
+	public HuggingfaceChatModel(final String apiToken, String basePath) {
 		this.apiToken = apiToken;
 		this.apiClient.setBasePath(basePath);
 		this.apiClient.addDefaultHeader("Authorization", "Bearer " + this.apiToken);

models/spring-ai-huggingface/src/test/java/org/springframework/ai/huggingface/HuggingfaceTestConfiguration.java

@@ -23,7 +23,7 @@ import org.springframework.util.StringUtils;
 public class HuggingfaceTestConfiguration {
 
 	@Bean
-	public HuggingfaceModelCaller huggingfaceChatClient() {
+	public HuggingfaceChatModel huggingfaceChatModel() {
 		String apiKey = System.getenv("HUGGINGFACE_API_KEY");
 		if (!StringUtils.hasText(apiKey)) {
 			throw new IllegalArgumentException(
@@ -31,9 +31,9 @@ public class HuggingfaceTestConfiguration {
 		}
 		// Created aws-mistral-7b-instruct-v0-1-805 via
 		// https://ui.endpoints.huggingface.co/
-		HuggingfaceModelCaller huggingfaceChatClient = new HuggingfaceModelCaller(apiKey,
+		HuggingfaceChatModel huggingfaceChatModel = new HuggingfaceChatModel(apiKey,
 				"https://f6hg7b3cvlmntp5i.us-east-1.aws.endpoints.huggingface.cloud");
-		return huggingfaceChatClient;
+		return huggingfaceChatModel;
 	}
 
 }

models/spring-ai-huggingface/src/test/java/org/springframework/ai/huggingface/client/ClientIT.java

@@ -20,7 +20,7 @@ import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 
 import org.springframework.ai.chat.ChatResponse;
-import org.springframework.ai.huggingface.HuggingfaceModelCaller;
+import org.springframework.ai.huggingface.HuggingfaceChatModel;
 import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.boot.test.context.SpringBootTest;
@@ -33,7 +33,7 @@ import static org.assertj.core.api.Assertions.assertThat;
 public class ClientIT {
 
 	@Autowired
-	protected HuggingfaceModelCaller huggingfaceChatClient;
+	protected HuggingfaceChatModel huggingfaceChatModel;
 
 	@Test
 	void helloWorldCompletion() {
@@ -46,7 +46,7 @@ public class ClientIT {
 				[/INST]
 				 """;
 		Prompt prompt = new Prompt(mistral7bInstruct);
-		ChatResponse chatResponse = huggingfaceChatClient.call(prompt);
+		ChatResponse chatResponse = huggingfaceChatModel.call(prompt);
 		assertThat(chatResponse.getResult().getOutput().getContent()).isNotEmpty();
 		String expectedResponse = """
 				```json

models/spring-ai-minimax/src/main/java/org/springframework/ai/minimax/MiniMaxChatModel.java

@@ -15,14 +15,23 @@
  */
 package org.springframework.ai.minimax;
 
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+import java.util.Set;
+import java.util.concurrent.ConcurrentHashMap;
+
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
+import reactor.core.publisher.Flux;
 
-import org.springframework.ai.chat.ChatCaller;
-import org.springframework.ai.chat.ChatClient;
+import org.springframework.ai.chat.ChatModel;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.prompt.ChatOptions;
 import org.springframework.ai.chat.prompt.Prompt;
@@ -36,33 +45,22 @@ import org.springframework.http.ResponseEntity;
 import org.springframework.retry.support.RetryTemplate;
 import org.springframework.util.Assert;
 import org.springframework.util.CollectionUtils;
-import org.springframework.util.MimeType;
-import reactor.core.publisher.Flux;
-
-import java.util.Base64;
-import java.util.HashMap;
-import java.util.HashSet;
-import java.util.List;
-import java.util.Map;
-import java.util.Optional;
-import java.util.Set;
-import java.util.concurrent.ConcurrentHashMap;
 
 /**
- * {@link ChatClient} and {@link StreamingChatCaller} implementation for
- * {@literal MiniMax} backed by {@link MiniMaxApi}.
+ * {@link ChatModel} and {@link StreamingChatModel} implementation for {@literal MiniMax}
+ * backed by {@link MiniMaxApi}.
  *
  * @author Geng Rong
- * @see ChatClient
- * @see StreamingChatCaller
+ * @see ChatModel
+ * @see StreamingChatModel
  * @see MiniMaxApi
  * @since 1.0.0 M1
  */
-public class MiniMaxChatCaller extends
+public class MiniMaxChatModel extends
 		AbstractFunctionCallSupport<MiniMaxApi.ChatCompletionMessage, MiniMaxApi.ChatCompletionRequest, ResponseEntity<MiniMaxApi.ChatCompletion>>
-		implements ChatCaller, StreamingChatCaller {
+		implements ChatModel, StreamingChatModel {
 
-	private static final Logger logger = LoggerFactory.getLogger(MiniMaxChatCaller.class);
+	private static final Logger logger = LoggerFactory.getLogger(MiniMaxChatModel.class);
 
 	/**
 	 * The default options used for the chat completion requests.
@@ -80,35 +78,35 @@ public class MiniMaxChatCaller extends
 	private final MiniMaxApi miniMaxApi;
 
 	/**
-	 * Creates an instance of the MiniMaxChatClient.
+	 * Creates an instance of the MiniMaxChatModel.
 	 * @param miniMaxApi The MiniMaxApi instance to be used for interacting with the
 	 * MiniMax Chat API.
 	 * @throws IllegalArgumentException if MiniMaxApi is null
 	 */
-	public MiniMaxChatCaller(MiniMaxApi miniMaxApi) {
+	public MiniMaxChatModel(MiniMaxApi miniMaxApi) {
 		this(miniMaxApi,
 				MiniMaxChatOptions.builder().withModel(MiniMaxApi.DEFAULT_CHAT_MODEL).withTemperature(0.7f).build());
 	}
 
 	/**
-	 * Initializes an instance of the MiniMaxChatClient.
+	 * Initializes an instance of the MiniMaxChatModel.
 	 * @param miniMaxApi The MiniMaxApi instance to be used for interacting with the
 	 * MiniMax Chat API.
-	 * @param options The MiniMaxChatOptions to configure the chat client.
+	 * @param options The MiniMaxChatOptions to configure the chat model.
 	 */
-	public MiniMaxChatCaller(MiniMaxApi miniMaxApi, MiniMaxChatOptions options) {
+	public MiniMaxChatModel(MiniMaxApi miniMaxApi, MiniMaxChatOptions options) {
 		this(miniMaxApi, options, null, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * Initializes a new instance of the MiniMaxChatClient.
+	 * Initializes a new instance of the MiniMaxChatModel.
 	 * @param miniMaxApi The MiniMaxApi instance to be used for interacting with the
 	 * MiniMax Chat API.
-	 * @param options The MiniMaxChatOptions to configure the chat client.
+	 * @param options The MiniMaxChatOptions to configure the chat model.
 	 * @param functionCallbackContext The function callback context.
 	 * @param retryTemplate The retry template.
 	 */
-	public MiniMaxChatCaller(MiniMaxApi miniMaxApi, MiniMaxChatOptions options,
+	public MiniMaxChatModel(MiniMaxApi miniMaxApi, MiniMaxChatOptions options,
 			FunctionCallbackContext functionCallbackContext, RetryTemplate retryTemplate) {
 		super(functionCallbackContext);
 		Assert.notNull(miniMaxApi, "MiniMaxApi must not be null");

models/spring-ai-minimax/src/main/java/org/springframework/ai/minimax/MiniMaxChatOptions.java

@@ -114,10 +114,10 @@ public class MiniMaxChatOptions implements FunctionCallingOptions, ChatOptions {
 	private @JsonProperty("tool_choice") String toolChoice;
 
 	/**
-	 * MiniMax Tool Function Callbacks to register with the ChatClient.
+	 * MiniMax Tool Function Callbacks to register with the ChatModel.
 	 * For Prompt Options the functionCallbacks are automatically enabled for the duration of the prompt execution.
 	 * For Default Options the functionCallbacks are registered but disabled by default. Use the enableFunctions to set the functions
-	 * from the registry to be used by the ChatClient chat completion requests.
+	 * from the registry to be used by the ChatModel chat completion requests.
 	 */
 	@NestedConfigurationProperty
 	@JsonIgnore

models/spring-ai-minimax/src/main/java/org/springframework/ai/minimax/MiniMaxEmbeddingModel.java

@@ -19,7 +19,7 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.MetadataMode;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -40,9 +40,9 @@ import java.util.List;
  * @author Geng Rong
  * @since 1.0.0 M1
  */
-public class MiniMaxEmbeddingClient extends AbstractEmbeddingClient {
+public class MiniMaxEmbeddingModel extends AbstractEmbeddingModel {
 
-	private static final Logger logger = LoggerFactory.getLogger(MiniMaxEmbeddingClient.class);
+	private static final Logger logger = LoggerFactory.getLogger(MiniMaxEmbeddingModel.class);
 
 	private final MiniMaxEmbeddingOptions defaultOptions;
 
@@ -53,43 +53,43 @@ public class MiniMaxEmbeddingClient extends AbstractEmbeddingClient {
 	private final MetadataMode metadataMode;
 
 	/**
-	 * Constructor for the MiniMaxEmbeddingClient class.
+	 * Constructor for the MiniMaxEmbeddingModel class.
 	 * @param miniMaxApi The MiniMaxApi instance to use for making API requests.
 	 */
-	public MiniMaxEmbeddingClient(MiniMaxApi miniMaxApi) {
+	public MiniMaxEmbeddingModel(MiniMaxApi miniMaxApi) {
 		this(miniMaxApi, MetadataMode.EMBED);
 	}
 
 	/**
-	 * Initializes a new instance of the MiniMaxEmbeddingClient class.
+	 * Initializes a new instance of the MiniMaxEmbeddingModel class.
 	 * @param miniMaxApi The MiniMaxApi instance to use for making API requests.
 	 * @param metadataMode The mode for generating metadata.
 	 */
-	public MiniMaxEmbeddingClient(MiniMaxApi miniMaxApi, MetadataMode metadataMode) {
+	public MiniMaxEmbeddingModel(MiniMaxApi miniMaxApi, MetadataMode metadataMode) {
 		this(miniMaxApi, metadataMode,
 				MiniMaxEmbeddingOptions.builder().withModel(MiniMaxApi.DEFAULT_EMBEDDING_MODEL).build(),
 				RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * Initializes a new instance of the MiniMaxEmbeddingClient class.
+	 * Initializes a new instance of the MiniMaxEmbeddingModel class.
 	 * @param miniMaxApi The MiniMaxApi instance to use for making API requests.
 	 * @param metadataMode The mode for generating metadata.
 	 * @param miniMaxEmbeddingOptions The options for MiniMax embedding.
 	 */
-	public MiniMaxEmbeddingClient(MiniMaxApi miniMaxApi, MetadataMode metadataMode,
+	public MiniMaxEmbeddingModel(MiniMaxApi miniMaxApi, MetadataMode metadataMode,
 			MiniMaxEmbeddingOptions miniMaxEmbeddingOptions) {
 		this(miniMaxApi, metadataMode, miniMaxEmbeddingOptions, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * Initializes a new instance of the MiniMaxEmbeddingClient class.
+	 * Initializes a new instance of the MiniMaxEmbeddingModel class.
 	 * @param miniMaxApi - The MiniMaxApi instance to use for making API requests.
 	 * @param metadataMode - The mode for generating metadata.
 	 * @param options - The options for MiniMax embedding.
 	 * @param retryTemplate - The RetryTemplate for retrying failed API requests.
 	 */
-	public MiniMaxEmbeddingClient(MiniMaxApi miniMaxApi, MetadataMode metadataMode, MiniMaxEmbeddingOptions options,
+	public MiniMaxEmbeddingModel(MiniMaxApi miniMaxApi, MetadataMode metadataMode, MiniMaxEmbeddingOptions options,
 			RetryTemplate retryTemplate) {
 		Assert.notNull(miniMaxApi, "MiniMaxApi must not be null");
 		Assert.notNull(metadataMode, "metadataMode must not be null");

models/spring-ai-minimax/src/test/java/org/springframework/ai/minimax/ChatCompletionRequestTests.java

@@ -33,7 +33,7 @@ public class ChatCompletionRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new MiniMaxChatCaller(new MiniMaxApi("TEST"),
+		var client = new MiniMaxChatModel(new MiniMaxApi("TEST"),
 				MiniMaxChatOptions.builder().withModel("DEFAULT_MODEL").withTemperature(66.6f).build());
 
 		var request = client.createRequest(new Prompt("Test message content"), false);
@@ -59,7 +59,7 @@ public class ChatCompletionRequestTests {
 
 		final String TOOL_FUNCTION_NAME = "CurrentWeather";
 
-		var client = new MiniMaxChatCaller(new MiniMaxApi("TEST"),
+		var client = new MiniMaxChatModel(new MiniMaxApi("TEST"),
 				MiniMaxChatOptions.builder().withModel("DEFAULT_MODEL").build());
 
 		var request = client.createRequest(new Prompt("Test message content",
@@ -89,7 +89,7 @@ public class ChatCompletionRequestTests {
 
 		final String TOOL_FUNCTION_NAME = "CurrentWeather";
 
-		var client = new MiniMaxChatCaller(new MiniMaxApi("TEST"),
+		var client = new MiniMaxChatModel(new MiniMaxApi("TEST"),
 				MiniMaxChatOptions.builder()
 					.withModel("DEFAULT_MODEL")
 					.withFunctionCallbacks(List.of(FunctionCallbackWrapper.builder(new MockWeatherService())

models/spring-ai-minimax/src/test/java/org/springframework/ai/minimax/MiniMaxTestConfiguration.java

@@ -15,7 +15,7 @@
  */
 package org.springframework.ai.minimax;
 
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.minimax.api.MiniMaxApi;
 import org.springframework.boot.SpringBootConfiguration;
 import org.springframework.context.annotation.Bean;
@@ -42,13 +42,13 @@ public class MiniMaxTestConfiguration {
 	}
 
 	@Bean
-	public MiniMaxChatCaller miniMaxChatClient(MiniMaxApi api) {
-		return new MiniMaxChatCaller(api);
+	public MiniMaxChatModel miniMaxChatModel(MiniMaxApi api) {
+		return new MiniMaxChatModel(api);
 	}
 
 	@Bean
-	public EmbeddingClient miniMaxEmbeddingClient(MiniMaxApi api) {
-		return new MiniMaxEmbeddingClient(api);
+	public EmbeddingModel miniMaxEmbeddingModel(MiniMaxApi api) {
+		return new MiniMaxEmbeddingModel(api);
 	}
 
 }

models/spring-ai-minimax/src/test/java/org/springframework/ai/minimax/api/MiniMaxRetryTests.java

@@ -22,9 +22,9 @@ import org.mockito.Mock;
 import org.mockito.junit.jupiter.MockitoExtension;
 import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.ai.document.MetadataMode;
-import org.springframework.ai.minimax.MiniMaxChatCaller;
+import org.springframework.ai.minimax.MiniMaxChatModel;
 import org.springframework.ai.minimax.MiniMaxChatOptions;
-import org.springframework.ai.minimax.MiniMaxEmbeddingClient;
+import org.springframework.ai.minimax.MiniMaxEmbeddingModel;
 import org.springframework.ai.minimax.MiniMaxEmbeddingOptions;
 import org.springframework.ai.minimax.api.MiniMaxApi.ChatCompletion;
 import org.springframework.ai.minimax.api.MiniMaxApi.ChatCompletionChunk;
@@ -83,9 +83,9 @@ public class MiniMaxRetryTests {
 
 	private @Mock MiniMaxApi miniMaxApi;
 
-	private MiniMaxChatCaller chatClient;
+	private MiniMaxChatModel chatModel;
 
-	private MiniMaxEmbeddingClient embeddingClient;
+	private MiniMaxEmbeddingModel embeddingModel;
 
 	@BeforeEach
 	public void beforeEach() {
@@ -93,8 +93,8 @@ public class MiniMaxRetryTests {
 		retryListener = new TestRetryListener();
 		retryTemplate.registerListener(retryListener);
 
-		chatClient = new MiniMaxChatCaller(miniMaxApi, MiniMaxChatOptions.builder().build(), null, retryTemplate);
-		embeddingClient = new MiniMaxEmbeddingClient(miniMaxApi, MetadataMode.EMBED,
+		chatModel = new MiniMaxChatModel(miniMaxApi, MiniMaxChatOptions.builder().build(), null, retryTemplate);
+		embeddingModel = new MiniMaxEmbeddingModel(miniMaxApi, MetadataMode.EMBED,
 				MiniMaxEmbeddingOptions.builder().build(), retryTemplate);
 	}
 
@@ -111,7 +111,7 @@ public class MiniMaxRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedChatCompletion)));
 
-		var result = chatClient.call(new Prompt("text"));
+		var result = chatModel.call(new Prompt("text"));
 
 		assertThat(result).isNotNull();
 		assertThat(result.getResult().getOutput().getContent()).isSameAs("Response");
@@ -123,7 +123,7 @@ public class MiniMaxRetryTests {
     public void miniMaxChatNonTransientError() {
         when(miniMaxApi.chatCompletionEntity(isA(ChatCompletionRequest.class)))
                 .thenThrow(new RuntimeException("Non Transient Error"));
-        assertThrows(RuntimeException.class, () -> chatClient.call(new Prompt("text")));
+        assertThrows(RuntimeException.class, () -> chatModel.call(new Prompt("text")));
     }
 
 	@Test
@@ -139,7 +139,7 @@ public class MiniMaxRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(Flux.just(expectedChatCompletion));
 
-		var result = chatClient.stream(new Prompt("text"));
+		var result = chatModel.stream(new Prompt("text"));
 
 		assertThat(result).isNotNull();
 		assertThat(result.collectList().block().get(0).getResult().getOutput().getContent()).isSameAs("Response");
@@ -151,7 +151,7 @@ public class MiniMaxRetryTests {
     public void miniMaxChatStreamNonTransientError() {
         when(miniMaxApi.chatCompletionStream(isA(ChatCompletionRequest.class)))
                 .thenThrow(new RuntimeException("Non Transient Error"));
-        assertThrows(RuntimeException.class, () -> chatClient.stream(new Prompt("text")));
+        assertThrows(RuntimeException.class, () -> chatModel.stream(new Prompt("text")));
     }
 
 	@Test
@@ -164,7 +164,7 @@ public class MiniMaxRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedEmbeddings)));
 
-		var result = embeddingClient
+		var result = embeddingModel
 			.call(new org.springframework.ai.embedding.EmbeddingRequest(List.of("text1", "text2"), null));
 
 		assertThat(result).isNotNull();
@@ -177,7 +177,7 @@ public class MiniMaxRetryTests {
     public void miniMaxEmbeddingNonTransientError() {
         when(miniMaxApi.embeddings(isA(EmbeddingRequest.class)))
                 .thenThrow(new RuntimeException("Non Transient Error"));
-        assertThrows(RuntimeException.class, () -> embeddingClient
+        assertThrows(RuntimeException.class, () -> embeddingModel
                 .call(new org.springframework.ai.embedding.EmbeddingRequest(List.of("text1", "text2"), null)));
     }
 

models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiChatModel.java

@@ -17,10 +17,10 @@ package org.springframework.ai.mistralai;
 
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.prompt.ChatOptions;
 import org.springframework.ai.chat.prompt.Prompt;
@@ -55,9 +55,9 @@ import java.util.concurrent.ConcurrentHashMap;
  * @author Grogdunn
  * @since 0.8.1
  */
-public class MistralAiModelCaller extends
+public class MistralAiChatModel extends
 		AbstractFunctionCallSupport<MistralAiApi.ChatCompletionMessage, MistralAiApi.ChatCompletionRequest, ResponseEntity<MistralAiApi.ChatCompletion>>
-		implements ChatCaller, StreamingChatCaller {
+		implements ChatModel, StreamingChatModel {
 
 	private final Logger log = LoggerFactory.getLogger(getClass());
 
@@ -73,7 +73,7 @@ public class MistralAiModelCaller extends
 
 	private final RetryTemplate retryTemplate;
 
-	public MistralAiModelCaller(MistralAiApi mistralAiApi) {
+	public MistralAiChatModel(MistralAiApi mistralAiApi) {
 		this(mistralAiApi,
 				MistralAiChatOptions.builder()
 					.withTemperature(0.7f)
@@ -83,11 +83,11 @@ public class MistralAiModelCaller extends
 					.build());
 	}
 
-	public MistralAiModelCaller(MistralAiApi mistralAiApi, MistralAiChatOptions options) {
+	public MistralAiChatModel(MistralAiApi mistralAiApi, MistralAiChatOptions options) {
 		this(mistralAiApi, options, null, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
-	public MistralAiModelCaller(MistralAiApi mistralAiApi, MistralAiChatOptions options,
+	public MistralAiChatModel(MistralAiApi mistralAiApi, MistralAiChatOptions options,
 			FunctionCallbackContext functionCallbackContext, RetryTemplate retryTemplate) {
 		super(functionCallbackContext);
 		Assert.notNull(mistralAiApi, "MistralAiApi must not be null");

models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiChatOptions.java

@@ -101,11 +101,11 @@ public class MistralAiChatOptions implements FunctionCallingOptions, ChatOptions
 	private @JsonProperty("tool_choice") ToolChoice toolChoice;
 
 	/**
-	 * MistralAI Tool Function Callbacks to register with the ModelCall. For Prompt
+	 * MistralAI Tool Function Callbacks to register with the ChatModel. For Prompt
 	 * Options the functionCallbacks are automatically enabled for the duration of the
 	 * prompt execution. For Default Options the functionCallbacks are registered but
 	 * disabled by default. Use the enableFunctions to set the functions from the registry
-	 * to be used by the ModelCall chat completion requests.
+	 * to be used by the ChatModel chat completion requests.
 	 */
 	@NestedConfigurationProperty
 	@JsonIgnore

models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiEmbeddingModel.java

@@ -22,7 +22,7 @@ import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.MetadataMode;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -38,7 +38,7 @@ import org.springframework.util.Assert;
  * @author Ricken Bazolo
  * @since 0.8.1
  */
-public class MistralAiEmbeddingClient extends AbstractEmbeddingClient {
+public class MistralAiEmbeddingModel extends AbstractEmbeddingModel {
 
 	private final Logger log = LoggerFactory.getLogger(getClass());
 
@@ -50,21 +50,21 @@ public class MistralAiEmbeddingClient extends AbstractEmbeddingClient {
 
 	private final RetryTemplate retryTemplate;
 
-	public MistralAiEmbeddingClient(MistralAiApi mistralAiApi) {
+	public MistralAiEmbeddingModel(MistralAiApi mistralAiApi) {
 		this(mistralAiApi, MetadataMode.EMBED);
 	}
 
-	public MistralAiEmbeddingClient(MistralAiApi mistralAiApi, MetadataMode metadataMode) {
+	public MistralAiEmbeddingModel(MistralAiApi mistralAiApi, MetadataMode metadataMode) {
 		this(mistralAiApi, metadataMode,
 				MistralAiEmbeddingOptions.builder().withModel(MistralAiApi.EmbeddingModel.EMBED.getValue()).build(),
 				RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
-	public MistralAiEmbeddingClient(MistralAiApi mistralAiApi, MistralAiEmbeddingOptions options) {
+	public MistralAiEmbeddingModel(MistralAiApi mistralAiApi, MistralAiEmbeddingOptions options) {
 		this(mistralAiApi, MetadataMode.EMBED, options, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
-	public MistralAiEmbeddingClient(MistralAiApi mistralAiApi, MetadataMode metadataMode,
+	public MistralAiEmbeddingModel(MistralAiApi mistralAiApi, MetadataMode metadataMode,
 			MistralAiEmbeddingOptions options, RetryTemplate retryTemplate) {
 		Assert.notNull(mistralAiApi, "MistralAiApi must not be null");
 		Assert.notNull(metadataMode, "metadataMode must not be null");

models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiChatCompletionRequestTest.java

@@ -32,12 +32,12 @@ import static org.assertj.core.api.Assertions.assertThat;
 @EnabledIfEnvironmentVariable(named = "MISTRAL_AI_API_KEY", matches = ".+")
 public class MistralAiChatCompletionRequestTest {
 
-	MistralAiModelCaller chatClient = new MistralAiModelCaller(new MistralAiApi("test"));
+	MistralAiChatModel chatModel = new MistralAiChatModel(new MistralAiApi("test"));
 
 	@Test
 	void chatCompletionDefaultRequestTest() {
 
-		var request = chatClient.createRequest(new Prompt("test content"), false);
+		var request = chatModel.createRequest(new Prompt("test content"), false);
 
 		assertThat(request.messages()).hasSize(1);
 		assertThat(request.topP()).isEqualTo(1);
@@ -52,7 +52,7 @@ public class MistralAiChatCompletionRequestTest {
 
 		var options = MistralAiChatOptions.builder().withTemperature(0.5f).withTopP(0.8f).build();
 
-		var request = chatClient.createRequest(new Prompt("test content", options), true);
+		var request = chatModel.createRequest(new Prompt("test content", options), true);
 
 		assertThat(request.messages().size()).isEqualTo(1);
 		assertThat(request.topP()).isEqualTo(0.8f);

models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiChatModelIT.java

@@ -27,10 +27,10 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import reactor.core.publisher.Flux;
 
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.messages.AssistantMessage;
 import org.springframework.ai.chat.messages.Message;
 import org.springframework.ai.chat.messages.UserMessage;
@@ -56,15 +56,15 @@ import static org.assertj.core.api.Assertions.assertThat;
  */
 @SpringBootTest(classes = MistralAiTestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "MISTRAL_AI_API_KEY", matches = ".+")
-class MistralAiModelCallerIT {
+class MistralAiChatModelIT {
 
-	private static final Logger logger = LoggerFactory.getLogger(MistralAiModelCallerIT.class);
+	private static final Logger logger = LoggerFactory.getLogger(MistralAiChatModelIT.class);
 
 	@Autowired
-	protected ChatCaller modelCaller;
+	protected ChatModel chatModel;
 
 	@Autowired
-	protected StreamingChatCaller streamingChatClient;
+	protected StreamingChatModel streamingChatModel;
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -90,7 +90,7 @@ class MistralAiModelCallerIT {
 		// NOTE: Mistral expects the system message to be before the user message or will
 		// fail with 400 error.
 		Prompt prompt = new Prompt(List.of(systemMessage, userMessage));
-		ChatResponse response = modelCaller.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getResults().get(0).getOutput().getContent()).contains("Blackbeard");
 	}
@@ -108,7 +108,7 @@ class MistralAiModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.modelCaller.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -126,7 +126,7 @@ class MistralAiModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -148,7 +148,7 @@ class MistralAiModelCallerIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		logger.info("" + actorsFilms);
@@ -169,7 +169,7 @@ class MistralAiModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = streamingChatClient.stream(prompt)
+		String generationTextFromStream = streamingChatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -201,7 +201,7 @@ class MistralAiModelCallerIT {
 				.build()))
 			.build();
 
-		ChatResponse response = modelCaller.call(new Prompt(messages, promptOptions));
+		ChatResponse response = chatModel.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
@@ -224,7 +224,7 @@ class MistralAiModelCallerIT {
 				.build()))
 			.build();
 
-		Flux<ChatResponse> response = streamingChatClient.stream(new Prompt(messages, promptOptions));
+		Flux<ChatResponse> response = streamingChatModel.stream(new Prompt(messages, promptOptions));
 
 		String content = response.collectList()
 			.block()

models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiEmbeddingIT.java

@@ -31,25 +31,25 @@ import static org.assertj.core.api.Assertions.assertThat;
 class MistralAiEmbeddingIT {
 
 	@Autowired
-	private MistralAiEmbeddingClient mistralAiEmbeddingClient;
+	private MistralAiEmbeddingModel mistralAiEmbeddingModel;
 
 	@Test
 	void defaultEmbedding() {
-		assertThat(mistralAiEmbeddingClient).isNotNull();
-		var embeddingResponse = mistralAiEmbeddingClient.embedForResponse(List.of("Hello World"));
+		assertThat(mistralAiEmbeddingModel).isNotNull();
+		var embeddingResponse = mistralAiEmbeddingModel.embedForResponse(List.of("Hello World"));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0)).isNotNull();
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).hasSize(1024);
 		assertThat(embeddingResponse.getMetadata()).containsEntry("model", "mistral-embed");
 		assertThat(embeddingResponse.getMetadata()).containsEntry("total-tokens", 4);
 		assertThat(embeddingResponse.getMetadata()).containsEntry("prompt-tokens", 4);
-		assertThat(mistralAiEmbeddingClient.dimensions()).isEqualTo(1024);
+		assertThat(mistralAiEmbeddingModel.dimensions()).isEqualTo(1024);
 	}
 
 	@Test
 	void embeddingTest() {
-		assertThat(mistralAiEmbeddingClient).isNotNull();
-		var embeddingResponse = mistralAiEmbeddingClient.call(new EmbeddingRequest(
+		assertThat(mistralAiEmbeddingModel).isNotNull();
+		var embeddingResponse = mistralAiEmbeddingModel.call(new EmbeddingRequest(
 				List.of("Hello World", "World is big"),
 				MistralAiEmbeddingOptions.builder().withModel("mistral-embed").withEncodingFormat("float").build()));
 		assertThat(embeddingResponse.getResults()).hasSize(2);
@@ -58,7 +58,7 @@ class MistralAiEmbeddingIT {
 		assertThat(embeddingResponse.getMetadata()).containsEntry("model", "mistral-embed");
 		assertThat(embeddingResponse.getMetadata()).containsEntry("total-tokens", 9);
 		assertThat(embeddingResponse.getMetadata()).containsEntry("prompt-tokens", 9);
-		assertThat(mistralAiEmbeddingClient.dimensions()).isEqualTo(1024);
+		assertThat(mistralAiEmbeddingModel.dimensions()).isEqualTo(1024);
 	}
 
 }

models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiRetryTests.java

@@ -82,9 +82,9 @@ public class MistralAiRetryTests {
 
 	private @Mock MistralAiApi mistralAiApi;
 
-	private MistralAiModelCaller chatClient;
+	private MistralAiChatModel chatModel;
 
-	private MistralAiEmbeddingClient embeddingClient;
+	private MistralAiEmbeddingModel embeddingModel;
 
 	@BeforeEach
 	public void beforeEach() {
@@ -92,7 +92,7 @@ public class MistralAiRetryTests {
 		retryListener = new TestRetryListener();
 		retryTemplate.registerListener(retryListener);
 
-		chatClient = new MistralAiModelCaller(mistralAiApi,
+		chatModel = new MistralAiChatModel(mistralAiApi,
 				MistralAiChatOptions.builder()
 					.withTemperature(0.7f)
 					.withTopP(1f)
@@ -100,7 +100,7 @@ public class MistralAiRetryTests {
 					.withModel(MistralAiApi.ChatModel.TINY.getValue())
 					.build(),
 				null, retryTemplate);
-		embeddingClient = new MistralAiEmbeddingClient(mistralAiApi, MetadataMode.EMBED,
+		embeddingModel = new MistralAiEmbeddingModel(mistralAiApi, MetadataMode.EMBED,
 				MistralAiEmbeddingOptions.builder().withModel(MistralAiApi.EmbeddingModel.EMBED.getValue()).build(),
 				retryTemplate);
 	}
@@ -118,7 +118,7 @@ public class MistralAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedChatCompletion)));
 
-		var result = chatClient.call(new Prompt("text"));
+		var result = chatModel.call(new Prompt("text"));
 
 		assertThat(result).isNotNull();
 		assertThat(result.getResult().getOutput().getContent()).isSameAs("Response");
@@ -130,7 +130,7 @@ public class MistralAiRetryTests {
 	public void mistralAiChatNonTransientError() {
 		when(mistralAiApi.chatCompletionEntity(isA(ChatCompletionRequest.class)))
 				.thenThrow(new RuntimeException("Non Transient Error"));
-		assertThrows(RuntimeException.class, () -> chatClient.call(new Prompt("text")));
+		assertThrows(RuntimeException.class, () -> chatModel.call(new Prompt("text")));
 	}
 
 	@Test
@@ -146,7 +146,7 @@ public class MistralAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(Flux.just(expectedChatCompletion));
 
-		var result = chatClient.stream(new Prompt("text"));
+		var result = chatModel.stream(new Prompt("text"));
 
 		assertThat(result).isNotNull();
 		assertThat(result.collectList().block().get(0).getResult().getOutput().getContent()).isSameAs("Response");
@@ -158,7 +158,7 @@ public class MistralAiRetryTests {
 	public void mistralAiChatStreamNonTransientError() {
 		when(mistralAiApi.chatCompletionStream(isA(ChatCompletionRequest.class)))
 				.thenThrow(new RuntimeException("Non Transient Error"));
-		assertThrows(RuntimeException.class, () -> chatClient.stream(new Prompt("text")));
+		assertThrows(RuntimeException.class, () -> chatModel.stream(new Prompt("text")));
 	}
 
 	@Test
@@ -172,7 +172,7 @@ public class MistralAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedEmbeddings)));
 
-		var result = embeddingClient
+		var result = embeddingModel
 			.call(new org.springframework.ai.embedding.EmbeddingRequest(List.of("text1", "text2"), null));
 
 		assertThat(result).isNotNull();
@@ -185,7 +185,7 @@ public class MistralAiRetryTests {
 	public void mistralAiEmbeddingNonTransientError() {
 		when(mistralAiApi.embeddings(isA(EmbeddingRequest.class)))
 				.thenThrow(new RuntimeException("Non Transient Error"));
-		assertThrows(RuntimeException.class, () -> embeddingClient
+		assertThrows(RuntimeException.class, () -> embeddingModel
 				.call(new org.springframework.ai.embedding.EmbeddingRequest(List.of("text1", "text2"), null)));
 	}
 

models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiTestConfiguration.java

@@ -15,7 +15,7 @@
  */
 package org.springframework.ai.mistralai;
 
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.mistralai.api.MistralAiApi;
 import org.springframework.boot.SpringBootConfiguration;
 import org.springframework.context.annotation.Bean;
@@ -35,14 +35,14 @@ public class MistralAiTestConfiguration {
 	}
 
 	@Bean
-	public EmbeddingClient mistralAiEmbeddingClient(MistralAiApi api) {
-		return new MistralAiEmbeddingClient(api,
+	public EmbeddingModel mistralAiEmbeddingModel(MistralAiApi api) {
+		return new MistralAiEmbeddingModel(api,
 				MistralAiEmbeddingOptions.builder().withModel(MistralAiApi.EmbeddingModel.EMBED.getValue()).build());
 	}
 
 	@Bean
-	public MistralAiModelCaller mistralAiChatClient(MistralAiApi mistralAiApi) {
-		return new MistralAiModelCaller(mistralAiApi,
+	public MistralAiChatModel mistralAiChatModel(MistralAiApi mistralAiApi) {
+		return new MistralAiChatModel(mistralAiApi,
 				MistralAiChatOptions.builder().withModel(MistralAiApi.ChatModel.MIXTRAL.getValue()).build());
 	}
 

models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/OllamaChatModel.java

@@ -18,13 +18,13 @@ package org.springframework.ai.ollama;
 import java.util.Base64;
 import java.util.List;
 
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.ollama.metadata.OllamaChatResponseMetadata;
 import reactor.core.publisher.Flux;
 
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.messages.Message;
 import org.springframework.ai.chat.messages.MessageType;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
@@ -39,7 +39,7 @@ import org.springframework.util.CollectionUtils;
 import org.springframework.util.StringUtils;
 
 /**
- * {@link ChatCaller} implementation for {@literal Ollama}.
+ * {@link ChatModel} implementation for {@literal Ollama}.
  *
  * Ollama allows developers to run large language models and generate embeddings locally.
  * It supports open-source models available on [Ollama AI
@@ -52,7 +52,7 @@ import org.springframework.util.StringUtils;
  * @author Christian Tzolov
  * @since 0.8.0
  */
-public class OllamaModelCaller implements ChatCaller, StreamingChatCaller {
+public class OllamaChatModel implements ChatModel, StreamingChatModel {
 
 	/**
 	 * Low-level Ollama API library.
@@ -64,11 +64,11 @@ public class OllamaModelCaller implements ChatCaller, StreamingChatCaller {
 	 */
 	private OllamaOptions defaultOptions;
 
-	public OllamaModelCaller(OllamaApi chatApi) {
+	public OllamaChatModel(OllamaApi chatApi) {
 		this(chatApi, OllamaOptions.create().withModel(OllamaOptions.DEFAULT_MODEL));
 	}
 
-	public OllamaModelCaller(OllamaApi chatApi, OllamaOptions defaultOptions) {
+	public OllamaChatModel(OllamaApi chatApi, OllamaOptions defaultOptions) {
 		Assert.notNull(chatApi, "OllamaApi must not be null");
 		Assert.notNull(defaultOptions, "DefaultOptions must not be null");
 		this.chatApi = chatApi;
@@ -79,7 +79,7 @@ public class OllamaModelCaller implements ChatCaller, StreamingChatCaller {
 	 * @deprecated Use {@link OllamaOptions#setModel} instead.
 	 */
 	@Deprecated
-	public OllamaModelCaller withModel(String model) {
+	public OllamaChatModel withModel(String model) {
 		this.defaultOptions.setModel(model);
 		return this;
 	}
@@ -88,7 +88,7 @@ public class OllamaModelCaller implements ChatCaller, StreamingChatCaller {
 	 * @deprecated Use {@link OllamaOptions} constructor instead.
 	 */
 	@Deprecated
-	public OllamaModelCaller withDefaultOptions(OllamaOptions options) {
+	public OllamaChatModel withDefaultOptions(OllamaOptions options) {
 		this.defaultOptions = options;
 		return this;
 	}

models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/OllamaEmbeddingModel.java

@@ -23,9 +23,9 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingResponse;
 import org.springframework.ai.model.ModelOptionsUtils;
@@ -36,7 +36,7 @@ import org.springframework.util.Assert;
 import org.springframework.util.StringUtils;
 
 /**
- * {@link EmbeddingClient} implementation for {@literal Ollama}.
+ * {@link EmbeddingModel} implementation for {@literal Ollama}.
  *
  * Ollama allows developers to run large language models and generate embeddings locally.
  * It supports open-source models available on [Ollama AI
@@ -51,7 +51,7 @@ import org.springframework.util.StringUtils;
  * @author Christian Tzolov
  * @since 0.8.0
  */
-public class OllamaEmbeddingClient extends AbstractEmbeddingClient {
+public class OllamaEmbeddingModel extends AbstractEmbeddingModel {
 
 	private final Logger logger = LoggerFactory.getLogger(getClass());
 
@@ -62,11 +62,11 @@ public class OllamaEmbeddingClient extends AbstractEmbeddingClient {
 	 */
 	private OllamaOptions defaultOptions = OllamaOptions.create().withModel(OllamaOptions.DEFAULT_MODEL);
 
-	public OllamaEmbeddingClient(OllamaApi ollamaApi) {
+	public OllamaEmbeddingModel(OllamaApi ollamaApi) {
 		this.ollamaApi = ollamaApi;
 	}
 
-	public OllamaEmbeddingClient(OllamaApi ollamaApi, OllamaOptions defaultOptions) {
+	public OllamaEmbeddingModel(OllamaApi ollamaApi, OllamaOptions defaultOptions) {
 		this.ollamaApi = ollamaApi;
 		this.defaultOptions = defaultOptions;
 	}
@@ -75,7 +75,7 @@ public class OllamaEmbeddingClient extends AbstractEmbeddingClient {
 	 * @deprecated Use {@link OllamaOptions#setModel} instead.
 	 */
 	@Deprecated
-	public OllamaEmbeddingClient withModel(String model) {
+	public OllamaEmbeddingModel withModel(String model) {
 		this.defaultOptions.setModel(model);
 		return this;
 	}
@@ -84,7 +84,7 @@ public class OllamaEmbeddingClient extends AbstractEmbeddingClient {
 	 * @deprecated Use {@link OllamaOptions} constructor instead.
 	 */
 	@Deprecated
-	public OllamaEmbeddingClient withDefaultOptions(OllamaOptions options) {
+	public OllamaEmbeddingModel withDefaultOptions(OllamaOptions options) {
 		this.defaultOptions = options;
 		return this;
 	}

models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatModelIT.java

@@ -56,11 +56,11 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @Testcontainers
 @Disabled("For manual smoke testing only.")
-class OllamaModelCallerIT {
+class OllamaChatModelIT {
 
 	private static String MODEL = "mistral";
 
-	private static final Log logger = LogFactory.getLog(OllamaModelCallerIT.class);
+	private static final Log logger = LogFactory.getLog(OllamaChatModelIT.class);
 
 	@Container
 	static OllamaContainer ollamaContainer = new OllamaContainer("ollama/ollama:0.1.32");
@@ -77,7 +77,7 @@ class OllamaModelCallerIT {
 	}
 
 	@Autowired
-	private OllamaModelCaller client;
+	private OllamaChatModel chatModel;
 
 	@Test
 	void roleTest() {
@@ -95,13 +95,13 @@ class OllamaModelCallerIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage), portableOptions);
 
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 
 		// ollama specific options
 		var ollamaOptions = new OllamaOptions().withLowVRAM(true);
 
-		response = client.call(new Prompt(List.of(userMessage, systemMessage), ollamaOptions));
+		response = chatModel.call(new Prompt(List.of(userMessage, systemMessage), ollamaOptions));
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 
 	}
@@ -109,7 +109,7 @@ class OllamaModelCallerIT {
 	@Test
 	void usageTest() {
 		Prompt prompt = new Prompt("Tell me a joke");
-		ChatResponse response = client.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		Usage usage = response.getMetadata().getUsage();
 
 		assertThat(usage).isNotNull();
@@ -131,7 +131,7 @@ class OllamaModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -151,7 +151,7 @@ class OllamaModelCallerIT {
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -173,7 +173,7 @@ class OllamaModelCallerIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -194,7 +194,7 @@ class OllamaModelCallerIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = client.stream(prompt)
+		String generationTextFromStream = chatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -219,8 +219,8 @@ class OllamaModelCallerIT {
 		}
 
 		@Bean
-		public OllamaModelCaller ollamaChat(OllamaApi ollamaApi) {
-			return new OllamaModelCaller(ollamaApi, OllamaOptions.create().withModel(MODEL).withTemperature(0.9f));
+		public OllamaChatModel ollamaChat(OllamaApi ollamaApi) {
+			return new OllamaChatModel(ollamaApi, OllamaOptions.create().withModel(MODEL).withTemperature(0.9f));
 		}
 
 	}

models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatModelMultimodalIT.java

@@ -44,11 +44,11 @@ import static org.assertj.core.api.Assertions.assertThat;
 @SpringBootTest
 @Testcontainers
 @Disabled("For manual smoke testing only.")
-class OllamaModelCallerMultimodalIT {
+class OllamaChatModelMultimodalIT {
 
 	private static String MODEL = "llava";
 
-	private static final Log logger = LogFactory.getLog(OllamaModelCallerIT.class);
+	private static final Log logger = LogFactory.getLog(OllamaChatModelIT.class);
 
 	@Container
 	static OllamaContainer ollamaContainer = new OllamaContainer("ollama/ollama:0.1.32");
@@ -65,7 +65,7 @@ class OllamaModelCallerMultimodalIT {
 	}
 
 	@Autowired
-	private OllamaModelCaller client;
+	private OllamaChatModel chatModel;
 
 	@Test
 	void multiModalityTest() throws IOException {
@@ -75,7 +75,7 @@ class OllamaModelCallerMultimodalIT {
 		var userMessage = new UserMessage("Explain what do you see on this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		var response = client.call(new Prompt(List.of(userMessage)));
+		var response = chatModel.call(new Prompt(List.of(userMessage)));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple", "basket");
@@ -90,8 +90,8 @@ class OllamaModelCallerMultimodalIT {
 		}
 
 		@Bean
-		public OllamaModelCaller ollamaChat(OllamaApi ollamaApi) {
-			return new OllamaModelCaller(ollamaApi, OllamaOptions.create().withModel(MODEL).withTemperature(0.9f));
+		public OllamaChatModel ollamaChat(OllamaApi ollamaApi) {
+			return new OllamaChatModel(ollamaApi, OllamaOptions.create().withModel(MODEL).withTemperature(0.9f));
 		}
 
 	}

models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatRequestTests.java

@@ -30,13 +30,13 @@ import static org.assertj.core.api.Assertions.assertThat;
  */
 public class OllamaChatRequestTests {
 
-	OllamaModelCaller client = new OllamaModelCaller(new OllamaApi(),
+	OllamaChatModel chatModel = new OllamaChatModel(new OllamaApi(),
 			new OllamaOptions().withModel("MODEL_NAME").withTopK(99).withTemperature(66.6f).withNumGPU(1));
 
 	@Test
 	public void createRequestWithDefaultOptions() {
 
-		var request = client.ollamaChatRequest(new Prompt("Test message content"), false);
+		var request = chatModel.ollamaChatRequest(new Prompt("Test message content"), false);
 
 		assertThat(request.messages()).hasSize(1);
 		assertThat(request.stream()).isFalse();
@@ -54,7 +54,7 @@ public class OllamaChatRequestTests {
 		// Runtime options should override the default options.
 		OllamaOptions promptOptions = new OllamaOptions().withTemperature(0.8f).withTopP(0.5f).withNumGPU(2);
 
-		var request = client.ollamaChatRequest(new Prompt("Test message content", promptOptions), true);
+		var request = chatModel.ollamaChatRequest(new Prompt("Test message content", promptOptions), true);
 
 		assertThat(request.messages()).hasSize(1);
 		assertThat(request.stream()).isTrue();
@@ -79,7 +79,7 @@ public class OllamaChatRequestTests {
 			.withTopP(0.6f)
 			.build();
 
-		var request = client.ollamaChatRequest(new Prompt("Test message content", portablePromptOptions), true);
+		var request = chatModel.ollamaChatRequest(new Prompt("Test message content", portablePromptOptions), true);
 
 		assertThat(request.messages()).hasSize(1);
 		assertThat(request.stream()).isTrue();
@@ -97,7 +97,7 @@ public class OllamaChatRequestTests {
 		// Ollama runtime options.
 		OllamaOptions promptOptions = new OllamaOptions().withModel("PROMPT_MODEL");
 
-		var request = client.ollamaChatRequest(new Prompt("Test message content", promptOptions), true);
+		var request = chatModel.ollamaChatRequest(new Prompt("Test message content", promptOptions), true);
 
 		assertThat(request.model()).isEqualTo("PROMPT_MODEL");
 	}
@@ -105,17 +105,17 @@ public class OllamaChatRequestTests {
 	@Test
 	public void createRequestWithDefaultOptionsModelOverride() {
 
-		OllamaModelCaller client2 = new OllamaModelCaller(new OllamaApi(),
+		OllamaChatModel chatModel = new OllamaChatModel(new OllamaApi(),
 				new OllamaOptions().withModel("DEFAULT_OPTIONS_MODEL"));
 
-		var request = client2.ollamaChatRequest(new Prompt("Test message content"), true);
+		var request = chatModel.ollamaChatRequest(new Prompt("Test message content"), true);
 
 		assertThat(request.model()).isEqualTo("DEFAULT_OPTIONS_MODEL");
 
 		// Prompt options should override the default options.
 		OllamaOptions promptOptions = new OllamaOptions().withModel("PROMPT_MODEL");
 
-		request = client2.ollamaChatRequest(new Prompt("Test message content", promptOptions), true);
+		request = chatModel.ollamaChatRequest(new Prompt("Test message content", promptOptions), true);
 
 		assertThat(request.model()).isEqualTo("PROMPT_MODEL");
 	}

models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaEmbeddingModelIT.java

@@ -23,9 +23,9 @@ import org.apache.commons.logging.LogFactory;
 import org.junit.jupiter.api.BeforeAll;
 import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
-import org.testcontainers.containers.GenericContainer;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
+import org.testcontainers.ollama.OllamaContainer;
 
 import org.springframework.ai.embedding.EmbeddingResponse;
 import org.springframework.ai.ollama.api.OllamaApi;
@@ -34,14 +34,13 @@ import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.boot.SpringBootConfiguration;
 import org.springframework.boot.test.context.SpringBootTest;
 import org.springframework.context.annotation.Bean;
-import org.testcontainers.ollama.OllamaContainer;
 
 import static org.assertj.core.api.Assertions.assertThat;
 
 @SpringBootTest
 @Disabled("For manual smoke testing only.")
 @Testcontainers
-class OllamaEmbeddingClientIT {
+class OllamaEmbeddingModelIT {
 
 	private static final Log logger = LogFactory.getLog(OllamaApiIT.class);
 
@@ -60,15 +59,15 @@ class OllamaEmbeddingClientIT {
 	}
 
 	@Autowired
-	private OllamaEmbeddingClient embeddingClient;
+	private OllamaEmbeddingModel embeddingModel;
 
 	@Test
 	void singleEmbedding() {
-		assertThat(embeddingClient).isNotNull();
-		EmbeddingResponse embeddingResponse = embeddingClient.embedForResponse(List.of("Hello World"));
+		assertThat(embeddingModel).isNotNull();
+		EmbeddingResponse embeddingResponse = embeddingModel.embedForResponse(List.of("Hello World"));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).isNotEmpty();
-		assertThat(embeddingClient.dimensions()).isEqualTo(3200);
+		assertThat(embeddingModel.dimensions()).isEqualTo(3200);
 	}
 
 	@SpringBootConfiguration
@@ -80,8 +79,8 @@ class OllamaEmbeddingClientIT {
 		}
 
 		@Bean
-		public OllamaEmbeddingClient ollamaEmbedding(OllamaApi ollamaApi) {
-			return new OllamaEmbeddingClient(ollamaApi).withModel("orca-mini");
+		public OllamaEmbeddingModel ollamaEmbedding(OllamaApi ollamaApi) {
+			return new OllamaEmbeddingModel(ollamaApi).withModel("orca-mini");
 		}
 
 	}

models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaEmbeddingRequestTests.java

@@ -28,13 +28,13 @@ import static org.assertj.core.api.Assertions.assertThat;
  */
 public class OllamaEmbeddingRequestTests {
 
-	OllamaEmbeddingClient client = new OllamaEmbeddingClient(new OllamaApi()).withDefaultOptions(
+	OllamaEmbeddingModel chatModel = new OllamaEmbeddingModel(new OllamaApi()).withDefaultOptions(
 			new OllamaOptions().withModel("DEFAULT_MODEL").withMainGPU(11).withUseMMap(true).withNumGPU(1));
 
 	@Test
 	public void ollamaEmbeddingRequestDefaultOptions() {
 
-		var request = client.ollamaEmbeddingRequest("Hello", null);
+		var request = chatModel.ollamaEmbeddingRequest("Hello", null);
 
 		assertThat(request.model()).isEqualTo("DEFAULT_MODEL");
 		assertThat(request.options().get("num_gpu")).isEqualTo(1);
@@ -51,7 +51,7 @@ public class OllamaEmbeddingRequestTests {
 			.withUseMMap(true)
 			.withNumGPU(2);
 
-		var request = client.ollamaEmbeddingRequest("Hello", promptOptions);
+		var request = chatModel.ollamaEmbeddingRequest("Hello", promptOptions);
 
 		assertThat(request.model()).isEqualTo("PROMPT_MODEL");
 		assertThat(request.options().get("num_gpu")).isEqualTo(2);

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiAudioSpeechModel.java

@@ -24,10 +24,10 @@ import org.springframework.ai.openai.api.OpenAiAudioApi;
 import org.springframework.ai.openai.api.OpenAiAudioApi.SpeechRequest.AudioResponseFormat;
 import org.springframework.ai.openai.api.common.OpenAiApiException;
 import org.springframework.ai.openai.audio.speech.Speech;
-import org.springframework.ai.openai.audio.speech.SpeechClient;
+import org.springframework.ai.openai.audio.speech.SpeechModel;
 import org.springframework.ai.openai.audio.speech.SpeechPrompt;
 import org.springframework.ai.openai.audio.speech.SpeechResponse;
-import org.springframework.ai.openai.audio.speech.StreamingSpeechClient;
+import org.springframework.ai.openai.audio.speech.StreamingSpeechModel;
 import org.springframework.ai.openai.metadata.audio.OpenAiAudioSpeechResponseMetadata;
 import org.springframework.ai.openai.metadata.support.OpenAiResponseHeaderExtractor;
 import org.springframework.http.ResponseEntity;
@@ -44,7 +44,7 @@ import java.time.Duration;
  * @see OpenAiAudioApi
  * @since 1.0.0-M1
  */
-public class OpenAiAudioSpeechClient implements SpeechClient, StreamingSpeechClient {
+public class OpenAiAudioSpeechModel implements SpeechModel, StreamingSpeechModel {
 
 	private final Logger logger = LoggerFactory.getLogger(getClass());
 
@@ -61,12 +61,12 @@ public class OpenAiAudioSpeechClient implements SpeechClient, StreamingSpeechCli
 	private final OpenAiAudioApi audioApi;
 
 	/**
-	 * Initializes a new instance of the OpenAiAudioSpeechClient class with the provided
+	 * Initializes a new instance of the OpenAiAudioSpeechModel class with the provided
 	 * OpenAiAudioApi. It uses the model tts-1, response format mp3, voice alloy, and the
 	 * default speed of 1.0.
 	 * @param audioApi The OpenAiAudioApi to use for speech synthesis.
 	 */
-	public OpenAiAudioSpeechClient(OpenAiAudioApi audioApi) {
+	public OpenAiAudioSpeechModel(OpenAiAudioApi audioApi) {
 		this(audioApi,
 				OpenAiAudioSpeechOptions.builder()
 					.withModel(OpenAiAudioApi.TtsModel.TTS_1.getValue())
@@ -77,13 +77,13 @@ public class OpenAiAudioSpeechClient implements SpeechClient, StreamingSpeechCli
 	}
 
 	/**
-	 * Initializes a new instance of the OpenAiAudioSpeechClient class with the provided
+	 * Initializes a new instance of the OpenAiAudioSpeechModel class with the provided
 	 * OpenAiAudioApi and options.
 	 * @param audioApi The OpenAiAudioApi to use for speech synthesis.
 	 * @param options The OpenAiAudioSpeechOptions containing the speech synthesis
 	 * options.
 	 */
-	public OpenAiAudioSpeechClient(OpenAiAudioApi audioApi, OpenAiAudioSpeechOptions options) {
+	public OpenAiAudioSpeechModel(OpenAiAudioApi audioApi, OpenAiAudioSpeechOptions options) {
 		Assert.notNull(audioApi, "OpenAiAudioApi must not be null");
 		Assert.notNull(options, "OpenAiSpeechOptions must not be null");
 		this.audioApi = audioApi;

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiAudioTranscriptionModel.java

@@ -35,7 +35,7 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.chat.metadata.RateLimit;
-import org.springframework.ai.model.ModelClient;
+import org.springframework.ai.model.Model;
 import org.springframework.ai.openai.api.OpenAiAudioApi;
 import org.springframework.ai.openai.api.OpenAiAudioApi.StructuredResponse;
 import org.springframework.ai.openai.audio.transcription.AudioTranscription;
@@ -59,8 +59,7 @@ import org.springframework.util.Assert;
  * @see OpenAiAudioApi
  * @since 0.8.1
  */
-public class OpenAiAudioTranscriptionClient
-		implements ModelClient<AudioTranscriptionPrompt, AudioTranscriptionResponse> {
+public class OpenAiAudioTranscriptionModel implements Model<AudioTranscriptionPrompt, AudioTranscriptionResponse> {
 
 	private final Logger logger = LoggerFactory.getLogger(getClass());
 
@@ -71,11 +70,11 @@ public class OpenAiAudioTranscriptionClient
 	private final OpenAiAudioApi audioApi;
 
 	/**
-	 * OpenAiAudioTranscriptionClient is a client class used to interact with the OpenAI
+	 * OpenAiAudioTranscriptionModel is a client class used to interact with the OpenAI
 	 * Audio Transcription API.
 	 * @param audioApi The OpenAiAudioApi instance to be used for making API calls.
 	 */
-	public OpenAiAudioTranscriptionClient(OpenAiAudioApi audioApi) {
+	public OpenAiAudioTranscriptionModel(OpenAiAudioApi audioApi) {
 		this(audioApi,
 				OpenAiAudioTranscriptionOptions.builder()
 					.withModel(OpenAiAudioApi.WhisperModel.WHISPER_1.getValue())
@@ -86,25 +85,25 @@ public class OpenAiAudioTranscriptionClient
 	}
 
 	/**
-	 * OpenAiAudioTranscriptionClient is a client class used to interact with the OpenAI
+	 * OpenAiAudioTranscriptionModel is a client class used to interact with the OpenAI
 	 * Audio Transcription API.
 	 * @param audioApi The OpenAiAudioApi instance to be used for making API calls.
 	 * @param options The OpenAiAudioTranscriptionOptions instance for configuring the
 	 * audio transcription.
 	 */
-	public OpenAiAudioTranscriptionClient(OpenAiAudioApi audioApi, OpenAiAudioTranscriptionOptions options) {
+	public OpenAiAudioTranscriptionModel(OpenAiAudioApi audioApi, OpenAiAudioTranscriptionOptions options) {
 		this(audioApi, options, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * OpenAiAudioTranscriptionClient is a client class used to interact with the OpenAI
+	 * OpenAiAudioTranscriptionModel is a client class used to interact with the OpenAI
 	 * Audio Transcription API.
 	 * @param audioApi The OpenAiAudioApi instance to be used for making API calls.
 	 * @param options The OpenAiAudioTranscriptionOptions instance for configuring the
 	 * audio transcription.
 	 * @param retryTemplate The RetryTemplate instance for retrying failed API calls.
 	 */
-	public OpenAiAudioTranscriptionClient(OpenAiAudioApi audioApi, OpenAiAudioTranscriptionOptions options,
+	public OpenAiAudioTranscriptionModel(OpenAiAudioApi audioApi, OpenAiAudioTranscriptionOptions options,
 			RetryTemplate retryTemplate) {
 		Assert.notNull(audioApi, "OpenAiAudioApi must not be null");
 		Assert.notNull(options, "OpenAiTranscriptionOptions must not be null");

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiChatModel.java

@@ -17,10 +17,10 @@ package org.springframework.ai.openai;
 
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.metadata.ChatGenerationMetadata;
 import org.springframework.ai.chat.metadata.RateLimit;
 import org.springframework.ai.chat.prompt.ChatOptions;
@@ -58,7 +58,7 @@ import java.util.Set;
 import java.util.concurrent.ConcurrentHashMap;
 
 /**
- * {@link ChatCaller} and {@link StreamingChatCaller} implementation for {@literal OpenAI}
+ * {@link ChatModel} and {@link StreamingChatModel} implementation for {@literal OpenAI}
  * backed by {@link OpenAiApi}.
  *
  * @author Mark Pollack
@@ -68,15 +68,15 @@ import java.util.concurrent.ConcurrentHashMap;
  * @author Josh Long
  * @author Jemin Huh
  * @author Grogdunn
- * @see ChatCaller
- * @see StreamingChatCaller
+ * @see ChatModel
+ * @see StreamingChatModel
  * @see OpenAiApi
  */
-public class OpenAiModelCaller extends
+public class OpenAiChatModel extends
 		AbstractFunctionCallSupport<ChatCompletionMessage, OpenAiApi.ChatCompletionRequest, ResponseEntity<ChatCompletion>>
-		implements ChatCaller, StreamingChatCaller {
+		implements ChatModel, StreamingChatModel {
 
-	private static final Logger logger = LoggerFactory.getLogger(OpenAiModelCaller.class);
+	private static final Logger logger = LoggerFactory.getLogger(OpenAiChatModel.class);
 
 	/**
 	 * The default options used for the chat completion requests.
@@ -94,35 +94,35 @@ public class OpenAiModelCaller extends
 	private final OpenAiApi openAiApi;
 
 	/**
-	 * Creates an instance of the OpenAiModelCall.
+	 * Creates an instance of the OpenAiChatModel.
 	 * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI
 	 * Chat API.
 	 * @throws IllegalArgumentException if openAiApi is null
 	 */
-	public OpenAiModelCaller(OpenAiApi openAiApi) {
+	public OpenAiChatModel(OpenAiApi openAiApi) {
 		this(openAiApi,
 				OpenAiChatOptions.builder().withModel(OpenAiApi.DEFAULT_CHAT_MODEL).withTemperature(0.7f).build());
 	}
 
 	/**
-	 * Initializes an instance of the OpenAiModelCall.
+	 * Initializes an instance of the OpenAiChatModel.
 	 * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI
 	 * Chat API.
-	 * @param options The OpenAiChatOptions to configure the chat client.
+	 * @param options The OpenAiChatOptions to configure the chat model.
 	 */
-	public OpenAiModelCaller(OpenAiApi openAiApi, OpenAiChatOptions options) {
+	public OpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options) {
 		this(openAiApi, options, null, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * Initializes a new instance of the OpenAiModelCall.
+	 * Initializes a new instance of the OpenAiChatModel.
 	 * @param openAiApi The OpenAiApi instance to be used for interacting with the OpenAI
 	 * Chat API.
-	 * @param options The OpenAiChatOptions to configure the chat client.
+	 * @param options The OpenAiChatOptions to configure the chat model.
 	 * @param functionCallbackContext The function callback context.
 	 * @param retryTemplate The retry template.
 	 */
-	public OpenAiModelCaller(OpenAiApi openAiApi, OpenAiChatOptions options,
+	public OpenAiChatModel(OpenAiApi openAiApi, OpenAiChatOptions options,
 			FunctionCallbackContext functionCallbackContext, RetryTemplate retryTemplate) {
 		super(functionCallbackContext);
 		Assert.notNull(openAiApi, "OpenAiApi must not be null");

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiChatOptions.java

@@ -134,10 +134,10 @@ public class OpenAiChatOptions implements FunctionCallingOptions, ChatOptions {
 	private @JsonProperty("user") String user;
 
 	/**
-	 * OpenAI Tool Function Callbacks to register with the ModelCall.
+	 * OpenAI Tool Function Callbacks to register with the ChatModel.
 	 * For Prompt Options the functionCallbacks are automatically enabled for the duration of the prompt execution.
 	 * For Default Options the functionCallbacks are registered but disabled by default. Use the enableFunctions to set the functions
-	 * from the registry to be used by the ModelCall chat completion requests.
+	 * from the registry to be used by the ChatModel chat completion requests.
 	 */
 	@NestedConfigurationProperty
 	@JsonIgnore

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiEmbeddingModel.java

@@ -22,7 +22,7 @@ import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.MetadataMode;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -41,9 +41,9 @@ import org.springframework.util.Assert;
  *
  * @author Christian Tzolov
  */
-public class OpenAiEmbeddingClient extends AbstractEmbeddingClient {
+public class OpenAiEmbeddingModel extends AbstractEmbeddingModel {
 
-	private static final Logger logger = LoggerFactory.getLogger(OpenAiEmbeddingClient.class);
+	private static final Logger logger = LoggerFactory.getLogger(OpenAiEmbeddingModel.class);
 
 	private final OpenAiEmbeddingOptions defaultOptions;
 
@@ -54,43 +54,43 @@ public class OpenAiEmbeddingClient extends AbstractEmbeddingClient {
 	private final MetadataMode metadataMode;
 
 	/**
-	 * Constructor for the OpenAiEmbeddingClient class.
+	 * Constructor for the OpenAiEmbeddingModel class.
 	 * @param openAiApi The OpenAiApi instance to use for making API requests.
 	 */
-	public OpenAiEmbeddingClient(OpenAiApi openAiApi) {
+	public OpenAiEmbeddingModel(OpenAiApi openAiApi) {
 		this(openAiApi, MetadataMode.EMBED);
 	}
 
 	/**
-	 * Initializes a new instance of the OpenAiEmbeddingClient class.
+	 * Initializes a new instance of the OpenAiEmbeddingModel class.
 	 * @param openAiApi The OpenAiApi instance to use for making API requests.
 	 * @param metadataMode The mode for generating metadata.
 	 */
-	public OpenAiEmbeddingClient(OpenAiApi openAiApi, MetadataMode metadataMode) {
+	public OpenAiEmbeddingModel(OpenAiApi openAiApi, MetadataMode metadataMode) {
 		this(openAiApi, metadataMode,
 				OpenAiEmbeddingOptions.builder().withModel(OpenAiApi.DEFAULT_EMBEDDING_MODEL).build(),
 				RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * Initializes a new instance of the OpenAiEmbeddingClient class.
+	 * Initializes a new instance of the OpenAiEmbeddingModel class.
 	 * @param openAiApi The OpenAiApi instance to use for making API requests.
 	 * @param metadataMode The mode for generating metadata.
 	 * @param openAiEmbeddingOptions The options for OpenAi embedding.
 	 */
-	public OpenAiEmbeddingClient(OpenAiApi openAiApi, MetadataMode metadataMode,
+	public OpenAiEmbeddingModel(OpenAiApi openAiApi, MetadataMode metadataMode,
 			OpenAiEmbeddingOptions openAiEmbeddingOptions) {
 		this(openAiApi, metadataMode, openAiEmbeddingOptions, RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
 	/**
-	 * Initializes a new instance of the OpenAiEmbeddingClient class.
+	 * Initializes a new instance of the OpenAiEmbeddingModel class.
 	 * @param openAiApi - The OpenAiApi instance to use for making API requests.
 	 * @param metadataMode - The mode for generating metadata.
 	 * @param options - The options for OpenAI embedding.
 	 * @param retryTemplate - The RetryTemplate for retrying failed API requests.
 	 */
-	public OpenAiEmbeddingClient(OpenAiApi openAiApi, MetadataMode metadataMode, OpenAiEmbeddingOptions options,
+	public OpenAiEmbeddingModel(OpenAiApi openAiApi, MetadataMode metadataMode, OpenAiEmbeddingOptions options,
 			RetryTemplate retryTemplate) {
 		Assert.notNull(openAiApi, "OpenAiService must not be null");
 		Assert.notNull(metadataMode, "metadataMode must not be null");

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiImageModel.java

@@ -21,7 +21,7 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.image.Image;
-import org.springframework.ai.image.ImageClient;
+import org.springframework.ai.image.ImageModel;
 import org.springframework.ai.image.ImageGeneration;
 import org.springframework.ai.image.ImageOptions;
 import org.springframework.ai.image.ImagePrompt;
@@ -37,16 +37,16 @@ import org.springframework.retry.support.RetryTemplate;
 import org.springframework.util.Assert;
 
 /**
- * OpenAiImageClient is a class that implements the ImageClient interface. It provides a
+ * OpenAiImageModel is a class that implements the ImageModel interface. It provides a
  * client for calling the OpenAI image generation API.
  *
  * @author Mark Pollack
  * @author Christian Tzolov
  * @since 0.8.0
  */
-public class OpenAiImageClient implements ImageClient {
+public class OpenAiImageModel implements ImageModel {
 
-	private final static Logger logger = LoggerFactory.getLogger(OpenAiImageClient.class);
+	private final static Logger logger = LoggerFactory.getLogger(OpenAiImageModel.class);
 
 	private OpenAiImageOptions defaultOptions;
 
@@ -54,11 +54,11 @@ public class OpenAiImageClient implements ImageClient {
 
 	public final RetryTemplate retryTemplate;
 
-	public OpenAiImageClient(OpenAiImageApi openAiImageApi) {
+	public OpenAiImageModel(OpenAiImageApi openAiImageApi) {
 		this(openAiImageApi, OpenAiImageOptions.builder().build(), RetryUtils.DEFAULT_RETRY_TEMPLATE);
 	}
 
-	public OpenAiImageClient(OpenAiImageApi openAiImageApi, OpenAiImageOptions defaultOptions,
+	public OpenAiImageModel(OpenAiImageApi openAiImageApi, OpenAiImageOptions defaultOptions,
 			RetryTemplate retryTemplate) {
 		Assert.notNull(openAiImageApi, "OpenAiImageApi must not be null");
 		Assert.notNull(defaultOptions, "defaultOptions must not be null");

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/audio/speech/SpeechModel.java

@@ -16,10 +16,10 @@
 
 package org.springframework.ai.openai.audio.speech;
 
-import org.springframework.ai.model.ModelClient;
+import org.springframework.ai.model.Model;
 
 /**
- * The {@link SpeechClient} interface provides a way to interact with the OpenAI
+ * The {@link SpeechModel} interface provides a way to interact with the OpenAI
  * Text-to-Speech (TTS) API. It allows you to convert text input into lifelike spoken
  * audio.
  *
@@ -27,7 +27,7 @@ import org.springframework.ai.model.ModelClient;
  * @since 1.0.0-M1
  */
 @FunctionalInterface
-public interface SpeechClient extends ModelClient<SpeechPrompt, SpeechResponse> {
+public interface SpeechModel extends Model<SpeechPrompt, SpeechResponse> {
 
 	/**
 	 * Generates spoken audio from the provided text message.

models/spring-ai-openai/src/main/java/org/springframework/ai/openai/audio/speech/StreamingSpeechModel.java

@@ -16,11 +16,11 @@
 
 package org.springframework.ai.openai.audio.speech;
 
-import org.springframework.ai.model.StreamingModelClient;
+import org.springframework.ai.model.StreamingModel;
 import reactor.core.publisher.Flux;
 
 /**
- * The {@link StreamingSpeechClient} interface provides a way to interact with the OpenAI
+ * The {@link StreamingSpeechModel} interface provides a way to interact with the OpenAI
  * Text-to-Speech (TTS) API using a streaming approach, allowing you to receive the
  * generated audio in a real-time fashion.
  *
@@ -28,7 +28,7 @@ import reactor.core.publisher.Flux;
  * @since 1.0.0-M1
  */
 @FunctionalInterface
-public interface StreamingSpeechClient extends StreamingModelClient<SpeechPrompt, SpeechResponse> {
+public interface StreamingSpeechModel extends StreamingModel<SpeechPrompt, SpeechResponse> {
 
 	/**
 	 * Generates a stream of audio bytes from the provided text message.

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/ChatCompletionRequestTests.java

@@ -34,7 +34,7 @@ public class ChatCompletionRequestTests {
 	@Test
 	public void createRequestWithChatOptions() {
 
-		var client = new OpenAiModelCaller(new OpenAiApi("TEST"),
+		var client = new OpenAiChatModel(new OpenAiApi("TEST"),
 				OpenAiChatOptions.builder().withModel("DEFAULT_MODEL").withTemperature(66.6f).build());
 
 		var request = client.createRequest(new Prompt("Test message content"), false);
@@ -60,7 +60,7 @@ public class ChatCompletionRequestTests {
 
 		final String TOOL_FUNCTION_NAME = "CurrentWeather";
 
-		var client = new OpenAiModelCaller(new OpenAiApi("TEST"),
+		var client = new OpenAiChatModel(new OpenAiApi("TEST"),
 				OpenAiChatOptions.builder().withModel("DEFAULT_MODEL").build());
 
 		var request = client.createRequest(new Prompt("Test message content",
@@ -90,7 +90,7 @@ public class ChatCompletionRequestTests {
 
 		final String TOOL_FUNCTION_NAME = "CurrentWeather";
 
-		var client = new OpenAiModelCaller(new OpenAiApi("TEST"),
+		var client = new OpenAiChatModel(new OpenAiApi("TEST"),
 				OpenAiChatOptions.builder()
 					.withModel("DEFAULT_MODEL")
 					.withFunctionCallbacks(List.of(FunctionCallbackWrapper.builder(new MockWeatherService())

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/OpenAiTestConfiguration.java

@@ -15,7 +15,7 @@
  */
 package org.springframework.ai.openai;
 
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.openai.api.OpenAiAudioApi;
 import org.springframework.ai.openai.api.OpenAiImageApi;
@@ -51,33 +51,33 @@ public class OpenAiTestConfiguration {
 	}
 
 	@Bean
-	public OpenAiModelCaller openAiChatClient(OpenAiApi api) {
-		OpenAiModelCaller openAiChatClient = new OpenAiModelCaller(api);
-		return openAiChatClient;
+	public OpenAiChatModel openAiChatModel(OpenAiApi api) {
+		OpenAiChatModel openAiChatModel = new OpenAiChatModel(api);
+		return openAiChatModel;
 	}
 
 	@Bean
-	public OpenAiAudioTranscriptionClient openAiTranscriptionClient(OpenAiAudioApi api) {
-		OpenAiAudioTranscriptionClient openAiTranscriptionClient = new OpenAiAudioTranscriptionClient(api);
-		return openAiTranscriptionClient;
+	public OpenAiAudioTranscriptionModel openAiTranscriptionModel(OpenAiAudioApi api) {
+		OpenAiAudioTranscriptionModel openAiTranscriptionModel = new OpenAiAudioTranscriptionModel(api);
+		return openAiTranscriptionModel;
 	}
 
 	@Bean
-	public OpenAiAudioSpeechClient openAiAudioSpeechClient(OpenAiAudioApi api) {
-		OpenAiAudioSpeechClient openAiAudioSpeechClient = new OpenAiAudioSpeechClient(api);
-		return openAiAudioSpeechClient;
+	public OpenAiAudioSpeechModel openAiAudioSpeechModel(OpenAiAudioApi api) {
+		OpenAiAudioSpeechModel openAiAudioSpeechModel = new OpenAiAudioSpeechModel(api);
+		return openAiAudioSpeechModel;
 	}
 
 	@Bean
-	public OpenAiImageClient openAiImageClient(OpenAiImageApi imageApi) {
-		OpenAiImageClient openAiImageClient = new OpenAiImageClient(imageApi);
-		// openAiImageClient.setModel("foobar");
-		return openAiImageClient;
+	public OpenAiImageModel openAiImageModel(OpenAiImageApi imageApi) {
+		OpenAiImageModel openAiImageModel = new OpenAiImageModel(imageApi);
+		// openAiImageModel.setModel("foobar");
+		return openAiImageModel;
 	}
 
 	@Bean
-	public EmbeddingClient openAiEmbeddingClient(OpenAiApi api) {
-		return new OpenAiEmbeddingClient(api);
+	public EmbeddingModel openAiEmbeddingModel(OpenAiApi api) {
+		return new OpenAiEmbeddingModel(api);
 	}
 
 }

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/TranscriptionRequestTests.java

@@ -34,7 +34,7 @@ public class TranscriptionRequestTests {
 	@Test
 	public void defaultOptions() {
 
-		var client = new OpenAiAudioTranscriptionClient(new OpenAiAudioApi("TEST"),
+		var client = new OpenAiAudioTranscriptionModel(new OpenAiAudioApi("TEST"),
 				OpenAiAudioTranscriptionOptions.builder()
 					.withModel("DEFAULT_MODEL")
 					.withResponseFormat(TranscriptResponseFormat.TEXT)
@@ -58,7 +58,7 @@ public class TranscriptionRequestTests {
 	@Test
 	public void runtimeOptions() {
 
-		var client = new OpenAiAudioTranscriptionClient(new OpenAiAudioApi("TEST"),
+		var client = new OpenAiAudioTranscriptionModel(new OpenAiAudioApi("TEST"),
 				OpenAiAudioTranscriptionOptions.builder()
 					.withModel("DEFAULT_MODEL")
 					.withResponseFormat(TranscriptResponseFormat.TEXT)

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/acme/AcmeIT.java

@@ -26,9 +26,9 @@ import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.document.Document;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.OpenAiTestConfiguration;
-import org.springframework.ai.openai.OpenAiEmbeddingClient;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
 import org.springframework.ai.openai.testutils.AbstractIT;
 import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.ai.chat.prompt.SystemPromptTemplate;
@@ -58,16 +58,16 @@ public class AcmeIT extends AbstractIT {
 	private Resource systemBikePrompt;
 
 	@Autowired
-	private OpenAiEmbeddingClient embeddingClient;
+	private OpenAiEmbeddingModel embeddingModel;
 
 	@Autowired
-	private OpenAiModelCaller chatClient;
+	private OpenAiChatModel chatModel;
 
 	@Test
 	void beanTest() {
 		assertThat(bikesResource).isNotNull();
-		assertThat(embeddingClient).isNotNull();
-		assertThat(chatClient).isNotNull();
+		assertThat(embeddingModel).isNotNull();
+		assertThat(chatModel).isNotNull();
 	}
 
 	// @Test
@@ -81,7 +81,7 @@ public class AcmeIT extends AbstractIT {
 		// Step 2 - Create embeddings and save to vector store
 
 		logger.info("Creating Embeddings...");
-		VectorStore vectorStore = new SimpleVectorStore(embeddingClient);
+		VectorStore vectorStore = new SimpleVectorStore(embeddingModel);
 
 		vectorStore.accept(textSplitter.apply(jsonReader.get()));
 
@@ -108,7 +108,7 @@ public class AcmeIT extends AbstractIT {
 		logger.info("Asking AI generative to reply to question.");
 		Prompt prompt = new Prompt(List.of(systemMessage, userMessage));
 		logger.info("AI responded.");
-		ChatResponse response = chatClient.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 
 		evaluateQuestionAndAnswer(userQuery, response, true);
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/audio/speech/OpenAiSpeechModelIT.java

@@ -32,13 +32,13 @@ import static org.assertj.core.api.Assertions.assertThat;
 
 @SpringBootTest(classes = OpenAiTestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
-class OpenAiSpeechClientIT extends AbstractIT {
+class OpenAiSpeechModelIT extends AbstractIT {
 
 	private static final Float SPEED = 1.0f;
 
 	@Test
 	void shouldSuccessfullyStreamAudioBytesForEmptyMessage() {
-		Flux<byte[]> response = speechClient.stream("Today is a wonderful day to build something people love!");
+		Flux<byte[]> response = speechModel.stream("Today is a wonderful day to build something people love!");
 		assertThat(response).isNotNull();
 		assertThat(response.collectList().block()).isNotNull();
 		System.out.println(response.collectList().block());
@@ -46,7 +46,7 @@ class OpenAiSpeechClientIT extends AbstractIT {
 
 	@Test
 	void shouldProduceAudioBytesDirectlyFromMessage() {
-		byte[] audioBytes = speechClient.call("Today is a wonderful day to build something people love!");
+		byte[] audioBytes = speechModel.call("Today is a wonderful day to build something people love!");
 		assertThat(audioBytes).hasSizeGreaterThan(0);
 
 	}
@@ -61,7 +61,7 @@ class OpenAiSpeechClientIT extends AbstractIT {
 			.build();
 		SpeechPrompt speechPrompt = new SpeechPrompt("Today is a wonderful day to build something people love!",
 				speechOptions);
-		SpeechResponse response = speechClient.call(speechPrompt);
+		SpeechResponse response = speechModel.call(speechPrompt);
 		byte[] audioBytes = response.getResult().getOutput();
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getResults().get(0).getOutput()).isNotEmpty();
@@ -79,7 +79,7 @@ class OpenAiSpeechClientIT extends AbstractIT {
 			.build();
 		SpeechPrompt speechPrompt = new SpeechPrompt("Today is a wonderful day to build something people love!",
 				speechOptions);
-		SpeechResponse response = speechClient.call(speechPrompt);
+		SpeechResponse response = speechModel.call(speechPrompt);
 		OpenAiAudioSpeechResponseMetadata metadata = response.getMetadata();
 		assertThat(metadata).isNotNull();
 		assertThat(metadata.getRateLimit()).isNotNull();
@@ -100,7 +100,7 @@ class OpenAiSpeechClientIT extends AbstractIT {
 
 		SpeechPrompt speechPrompt = new SpeechPrompt("Today is a wonderful day to build something people love!",
 				speechOptions);
-		Flux<SpeechResponse> responseFlux = speechClient.stream(speechPrompt);
+		Flux<SpeechResponse> responseFlux = speechModel.stream(speechPrompt);
 		assertThat(responseFlux).isNotNull();
 		List<SpeechResponse> responses = responseFlux.collectList().block();
 		assertThat(responses).isNotNull();

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/audio/speech/OpenAiSpeechModelWithSpeechResponseMetadataTests.java

@@ -18,7 +18,7 @@ package org.springframework.ai.openai.audio.speech;
 
 import org.junit.jupiter.api.AfterEach;
 import org.junit.jupiter.api.Test;
-import org.springframework.ai.openai.OpenAiAudioSpeechClient;
+import org.springframework.ai.openai.OpenAiAudioSpeechModel;
 import org.springframework.ai.openai.OpenAiAudioSpeechOptions;
 import org.springframework.ai.openai.api.OpenAiAudioApi;
 import org.springframework.ai.openai.metadata.audio.OpenAiAudioSpeechResponseMetadata;
@@ -45,15 +45,15 @@ import static org.springframework.test.web.client.response.MockRestResponseCreat
 /**
  * @author Ahmed Yousri
  */
-@RestClientTest(OpenAiSpeechClientWithSpeechResponseMetadataTests.Config.class)
-public class OpenAiSpeechClientWithSpeechResponseMetadataTests {
+@RestClientTest(OpenAiSpeechModelWithSpeechResponseMetadataTests.Config.class)
+public class OpenAiSpeechModelWithSpeechResponseMetadataTests {
 
 	private static String TEST_API_KEY = "sk-1234567890";
 
 	private static final Float SPEED = 1.0f;
 
 	@Autowired
-	private OpenAiAudioSpeechClient openAiSpeechClient;
+	private OpenAiAudioSpeechModel openAiSpeechClient;
 
 	@Autowired
 	private MockRestServiceServer server;
@@ -121,8 +121,8 @@ public class OpenAiSpeechClientWithSpeechResponseMetadataTests {
 	static class Config {
 
 		@Bean
-		public OpenAiAudioSpeechClient openAiAudioSpeechClient(OpenAiAudioApi openAiAudioApi) {
-			return new OpenAiAudioSpeechClient(openAiAudioApi);
+		public OpenAiAudioSpeechModel openAiAudioSpeechClient(OpenAiAudioApi openAiAudioApi) {
+			return new OpenAiAudioSpeechModel(openAiAudioApi);
 		}
 
 		@Bean

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/audio/transcription/OpenAiTranscriptionModelIT.java

@@ -31,7 +31,7 @@ import static org.assertj.core.api.Assertions.assertThat;
 
 @SpringBootTest(classes = OpenAiTestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
-class OpenAiTranscriptionClientIT extends AbstractIT {
+class OpenAiTranscriptionModelIT extends AbstractIT {
 
 	@Value("classpath:/speech/jfk.flac")
 	private Resource audioFile;
@@ -43,7 +43,7 @@ class OpenAiTranscriptionClientIT extends AbstractIT {
 			.withTemperature(0f)
 			.build();
 		AudioTranscriptionPrompt transcriptionRequest = new AudioTranscriptionPrompt(audioFile, transcriptionOptions);
-		AudioTranscriptionResponse response = transcriptionClient.call(transcriptionRequest);
+		AudioTranscriptionResponse response = transcriptionModel.call(transcriptionRequest);
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getResults().get(0).getOutput().toLowerCase().contains("fellow")).isTrue();
 	}
@@ -59,7 +59,7 @@ class OpenAiTranscriptionClientIT extends AbstractIT {
 			.withResponseFormat(responseFormat)
 			.build();
 		AudioTranscriptionPrompt transcriptionRequest = new AudioTranscriptionPrompt(audioFile, transcriptionOptions);
-		AudioTranscriptionResponse response = transcriptionClient.call(transcriptionRequest);
+		AudioTranscriptionResponse response = transcriptionModel.call(transcriptionRequest);
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getResults().get(0).getOutput().toLowerCase().contains("fellow")).isTrue();
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/audio/transcription/OpenAiTranscriptionModelWithTranscriptionResponseMetadataTests.java

@@ -21,7 +21,7 @@ import org.junit.jupiter.api.AfterEach;
 import org.junit.jupiter.api.Test;
 
 import org.springframework.ai.chat.metadata.RateLimit;
-import org.springframework.ai.openai.OpenAiAudioTranscriptionClient;
+import org.springframework.ai.openai.OpenAiAudioTranscriptionModel;
 import org.springframework.ai.openai.api.OpenAiAudioApi;
 import org.springframework.ai.openai.metadata.audio.OpenAiAudioTranscriptionMetadata;
 import org.springframework.ai.openai.metadata.audio.OpenAiAudioTranscriptionResponseMetadata;
@@ -48,13 +48,13 @@ import static org.springframework.test.web.client.response.MockRestResponseCreat
 /**
  * @author Michael Lavelle
  */
-@RestClientTest(OpenAiTranscriptionClientWithTranscriptionResponseMetadataTests.Config.class)
-public class OpenAiTranscriptionClientWithTranscriptionResponseMetadataTests {
+@RestClientTest(OpenAiTranscriptionModelWithTranscriptionResponseMetadataTests.Config.class)
+public class OpenAiTranscriptionModelWithTranscriptionResponseMetadataTests {
 
 	private static String TEST_API_KEY = "sk-1234567890";
 
 	@Autowired
-	private OpenAiAudioTranscriptionClient openAiTranscriptionClient;
+	private OpenAiAudioTranscriptionModel openAiTranscriptionClient;
 
 	@Autowired
 	private MockRestServiceServer server;
@@ -156,8 +156,8 @@ public class OpenAiTranscriptionClientWithTranscriptionResponseMetadataTests {
 		}
 
 		@Bean
-		public OpenAiAudioTranscriptionClient openAiClient(OpenAiAudioApi openAiAudioApi) {
-			return new OpenAiAudioTranscriptionClient(openAiAudioApi);
+		public OpenAiAudioTranscriptionModel openAiClient(OpenAiAudioApi openAiAudioApi) {
+			return new OpenAiAudioTranscriptionModel(openAiAudioApi);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/audio/transcription/TranscriptionModelTests.java

@@ -18,7 +18,7 @@ package org.springframework.ai.openai.audio.transcription;
 import org.junit.jupiter.api.Test;
 import org.mockito.Mockito;
 
-import org.springframework.ai.openai.OpenAiAudioTranscriptionClient;
+import org.springframework.ai.openai.OpenAiAudioTranscriptionModel;
 import org.springframework.core.io.Resource;
 
 import static org.assertj.core.api.Assertions.assertThat;
@@ -33,18 +33,18 @@ import static org.mockito.Mockito.verifyNoMoreInteractions;
 import static org.mockito.Mockito.when;
 
 /**
- * Unit Tests for {@link TranscriptionClient}.
+ * Unit Tests for {@link TranscriptionModel}.
  *
  * @author Michael Lavelle
  */
-class TranscriptionClientTests {
+class TranscriptionModelTests {
 
 	@Test
 	void transcrbeRequestReturnsResponseCorrectly() {
 
 		Resource mockAudioFile = Mockito.mock(Resource.class);
 
-		OpenAiAudioTranscriptionClient mockClient = Mockito.mock(OpenAiAudioTranscriptionClient.class);
+		OpenAiAudioTranscriptionModel mockClient = Mockito.mock(OpenAiAudioTranscriptionModel.class);
 
 		String mockTranscription = "All your bases are belong to us";
 

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatClientIT.java

@@ -32,6 +32,7 @@ import org.slf4j.LoggerFactory;
 import reactor.core.publisher.Flux;
 
 import org.springframework.ai.chat.ChatClient;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.converter.BeanOutputConverter;
 import org.springframework.ai.openai.OpenAiChatOptions;
@@ -52,7 +53,7 @@ import static org.assertj.core.api.Assertions.assertThat;
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
 class OpenAiChatClientIT extends AbstractIT {
 
-	private static final Logger logger = LoggerFactory.getLogger(OpenAiModelCallerIT.class);
+	private static final Logger logger = LoggerFactory.getLogger(OpenAiChatClientIT.class);
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemTextResource;
@@ -61,7 +62,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void roleTest() {
 
 		// @formatter:off
-		ChatResponse response = ChatClient.builder(modelCaller).build().prompt()
+		ChatResponse response = ChatClient.builder(chatModel).build().prompt()
 				.system(s -> s.text(systemTextResource)
 						.param("name", "Bob")
 						.param("voice", "pirate"))
@@ -78,7 +79,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	@Test
 	void listOutputConverter() {
 		// @formatter:off
-		Collection<String> collection = ChatClient.builder(modelCaller).build().prompt()
+		Collection<String> collection = ChatClient.builder(chatModel).build().prompt()
 				.user(u -> u.text("List five {subject}")
 						.param("subject", "ice cream flavors"))
 				.call()
@@ -92,7 +93,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void listOutputConverter2() {
 
 		// @formatter:off
-		List<ActorsFilmsRecord> actorsFilms = ChatClient.builder(modelCaller).build().prompt()
+		List<ActorsFilmsRecord> actorsFilms = ChatClient.builder(chatModel).build().prompt()
 				.user("Generate the filmography of 5 movies for Tom Hanks and Bill Murray.")
 				.call()
 				.single(new ParameterizedTypeReference<List<ActorsFilmsRecord>>() {
@@ -108,7 +109,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void listOutputConverter3() {
 
 		// @formatter:off
-		Collection<ActorsFilmsRecord> actorsFilms = ChatClient.builder(modelCaller).build().prompt()
+		Collection<ActorsFilmsRecord> actorsFilms = ChatClient.builder(chatModel).build().prompt()
 				.user("Generate the filmography of 5 movies for Tom Hanks and Bill Murray.")
 				.call()
 				.list(ActorsFilmsRecord.class);
@@ -122,7 +123,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	@Test
 	void mapOutputConverter() {
 		// @formatter:off
-		Map<String, Object> result = ChatClient.builder(modelCaller).build().prompt()
+		Map<String, Object> result = ChatClient.builder(chatModel).build().prompt()
 				.user(u -> u.text("Provide me a List of {subject}")
 						.param("subject", "an array of numbers from 1 to 9 under they key name 'numbers'"))
 				.call()
@@ -137,7 +138,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void beanOutputConverter() {
 
 		// @formatter:off
-		ActorsFilms actorsFilms = ChatClient.builder(modelCaller).build().prompt()
+		ActorsFilms actorsFilms = ChatClient.builder(chatModel).build().prompt()
 				.user("Generate the filmography for a random actor.")
 				.call()
 				.single(ActorsFilms.class);
@@ -154,7 +155,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void beanOutputConverterRecords() {
 
 		// @formatter:off
-		ActorsFilmsRecord actorsFilms = ChatClient.builder(modelCaller).build().prompt()
+		ActorsFilmsRecord actorsFilms = ChatClient.builder(chatModel).build().prompt()
 				.user("Generate the filmography of 5 movies for Tom Hanks.")
 				.call()
 				.single(ActorsFilmsRecord.class);
@@ -171,7 +172,7 @@ class OpenAiChatClientIT extends AbstractIT {
 		BeanOutputConverter<ActorsFilmsRecord> outputConverter = new BeanOutputConverter<>(ActorsFilmsRecord.class);
 
 		// @formatter:off
-		Flux<String> chatResponse = ChatClient.builder(modelCaller)
+		Flux<String> chatResponse = ChatClient.builder(chatModel)
 				.build()
 				.prompt()
 				.user(u -> u
@@ -198,7 +199,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void functionCallTest() {
 
 		// @formatter:off
-		String response = ChatClient.builder(modelCaller).build().prompt()
+		String response = ChatClient.builder(chatModel).build().prompt()
 				.user(u -> u.text("What's the weather like in San Francisco, Tokyo, and Paris?"))
 				.function("getCurrentWeather", "Get the weather in location", new MockWeatherService())
 				.call()
@@ -216,7 +217,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void streamFunctionCallTest() {
 
 		// @formatter:off
-		Flux<String> response = ChatClient.builder(modelCaller).build().prompt()
+		Flux<String> response = ChatClient.builder(chatModel).build().prompt()
 				.user("What's the weather like in San Francisco, Tokyo, and Paris?")
 				.function("getCurrentWeather", "Get the weather in location", new MockWeatherService())
 				.stream()
@@ -236,7 +237,7 @@ class OpenAiChatClientIT extends AbstractIT {
 	void multiModalityEmbeddedImage(String modelName) throws IOException {
 
 		// @formatter:off
-		String response = ChatClient.builder(modelCaller).build().prompt()
+		String response = ChatClient.builder(chatModel).build().prompt()
 				// TODO consider adding model(...) method to ChatClient as a shortcut to
 				// OpenAiChatOptions.builder().withModel(modelName).build()
 				.options(OpenAiChatOptions.builder().withModel(modelName).build())
@@ -259,7 +260,7 @@ class OpenAiChatClientIT extends AbstractIT {
 		URL url = new URL("https://docs.spring.io/spring-ai/reference/1.0-SNAPSHOT/_images/multimodal.test.png");
 
 		// @formatter:off
-		String response = ChatClient.builder(modelCaller).build().prompt()
+		String response = ChatClient.builder(chatModel).build().prompt()
 				// TODO consider adding model(...) method to ChatClient as a shortcut to
 				// OpenAiChatOptions.builder().withModel(modelName).build()
 				.options(OpenAiChatOptions.builder().withModel(modelName).build())
@@ -280,7 +281,7 @@ class OpenAiChatClientIT extends AbstractIT {
 		URL url = new URL("https://docs.spring.io/spring-ai/reference/1.0-SNAPSHOT/_images/multimodal.test.png");
 
 		// @formatter:off
-		Flux<String> response = ChatClient.builder(modelCaller).build().prompt()
+		Flux<String> response = ChatClient.builder(chatModel).build().prompt()
 				.options(OpenAiChatOptions.builder().withModel(OpenAiApi.ChatModel.GPT_4_VISION_PREVIEW.getValue())
 						.build())
 				.user(u -> u.text("Explain what do you see on this picture?")

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatModel2IT.java

@@ -27,7 +27,7 @@ import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.prompt.Prompt;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.OpenAiChatOptions;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.openai.api.OpenAiApi.ChatCompletionRequest;
@@ -41,14 +41,14 @@ import static org.assertj.core.api.Assertions.assertThat;
 /**
  * @author Christian Tzolov
  */
-@SpringBootTest(classes = OpenAiModelCaller2IT.Config.class)
+@SpringBootTest(classes = OpenAiChatModel2IT.Config.class)
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
-public class OpenAiModelCaller2IT {
+public class OpenAiChatModel2IT {
 
 	private final Logger logger = LoggerFactory.getLogger(getClass());
 
 	@Autowired
-	private OpenAiModelCaller openAiChatClient;
+	private OpenAiChatModel openAiChatModel;
 
 	@Test
 	void responseFormatTest() throws JsonMappingException, JsonProcessingException {
@@ -67,7 +67,7 @@ public class OpenAiModelCaller2IT {
 					.withResponseFormat(new ChatCompletionRequest.ResponseFormat("json_object"))
 					.build());
 
-		ChatResponse response = this.openAiChatClient.call(prompt);
+		ChatResponse response = this.openAiChatModel.call(prompt);
 
 		assertThat(response).isNotNull();
 
@@ -99,8 +99,8 @@ public class OpenAiModelCaller2IT {
 		}
 
 		@Bean
-		public OpenAiModelCaller openAiClient(OpenAiApi openAiApi) {
-			return new OpenAiModelCaller(openAiApi);
+		public OpenAiChatModel openAiClient(OpenAiApi openAiApi) {
+			return new OpenAiChatModel(openAiApi);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatModelIT.java

@@ -31,7 +31,6 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import reactor.core.publisher.Flux;
 
-import org.springframework.ai.chat.ChatClient;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
 import org.springframework.ai.chat.messages.AssistantMessage;
@@ -61,9 +60,9 @@ import static org.assertj.core.api.Assertions.assertThat;
 
 @SpringBootTest(classes = OpenAiTestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
-class OpenAiModelCallerIT extends AbstractIT {
+class OpenAiChatModelIT extends AbstractIT {
 
-	private static final Logger logger = LoggerFactory.getLogger(OpenAiModelCallerIT.class);
+	private static final Logger logger = LoggerFactory.getLogger(OpenAiChatModelIT.class);
 
 	@Value("classpath:/prompts/system-message.st")
 	private Resource systemResource;
@@ -75,7 +74,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 		SystemPromptTemplate systemPromptTemplate = new SystemPromptTemplate(systemResource);
 		Message systemMessage = systemPromptTemplate.createMessage(Map.of("name", "Bob", "voice", "pirate"));
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		ChatResponse response = modelCaller.call(prompt);
+		ChatResponse response = chatModel.call(prompt);
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getResults().get(0).getOutput().getContent()).contains("Blackbeard");
 		// needs fine tuning... evaluateQuestionAndAnswer(request, response, false);
@@ -94,7 +93,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.modelCaller.call(prompt).getResult();
+		Generation generation = this.chatModel.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -113,7 +112,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "an array of numbers from 1 to 9 under they key name 'numbers'", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		Map<String, Object> result = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(result.get("numbers")).isEqualTo(Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9));
@@ -132,7 +131,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilms actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 	}
@@ -152,7 +151,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		logger.info("" + actorsFilms);
@@ -173,7 +172,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = streamingChatClient.stream(prompt)
+		String generationTextFromStream = streamingChatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()
@@ -205,7 +204,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 				.build()))
 			.build();
 
-		ChatResponse response = modelCaller.call(new Prompt(messages, promptOptions));
+		ChatResponse response = chatModel.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
@@ -230,7 +229,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 				.build()))
 			.build();
 
-		Flux<ChatResponse> response = streamingChatClient.stream(new Prompt(messages, promptOptions));
+		Flux<ChatResponse> response = streamingChatModel.stream(new Prompt(messages, promptOptions));
 
 		String content = response.collectList()
 			.block()
@@ -256,7 +255,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 		var userMessage = new UserMessage("Explain what do you see on this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		var response = modelCaller
+		var response = chatModel
 			.call(new Prompt(List.of(userMessage), OpenAiChatOptions.builder().withModel(modelName).build()));
 
 		logger.info(response.getResult().getOutput().getContent());
@@ -272,7 +271,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 			.of(new Media(MimeTypeUtils.IMAGE_PNG,
 					new URL("https://docs.spring.io/spring-ai/reference/1.0-SNAPSHOT/_images/multimodal.test.png"))));
 
-		ChatResponse response = modelCaller
+		ChatResponse response = chatModel
 			.call(new Prompt(List.of(userMessage), OpenAiChatOptions.builder().withModel(modelName).build()));
 
 		logger.info(response.getResult().getOutput().getContent());
@@ -287,7 +286,7 @@ class OpenAiModelCallerIT extends AbstractIT {
 			.of(new Media(MimeTypeUtils.IMAGE_PNG,
 					new URL("https://docs.spring.io/spring-ai/reference/1.0-SNAPSHOT/_images/multimodal.test.png"))));
 
-		Flux<ChatResponse> response = streamingChatClient.stream(new Prompt(List.of(userMessage),
+		Flux<ChatResponse> response = streamingChatModel.stream(new Prompt(List.of(userMessage),
 				OpenAiChatOptions.builder().withModel(OpenAiApi.ChatModel.GPT_4_VISION_PREVIEW.getValue()).build()));
 
 		String content = response.collectList()

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatModelTypeReferenceBeanOutputConverterIT.java

@@ -39,10 +39,10 @@ import static org.assertj.core.api.Assertions.assertThat;
 
 @SpringBootTest(classes = OpenAiTestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
-class OpenAiModelCallerTypeReferenceBeanOutputConverterIT extends AbstractIT {
+class OpenAiChatModelTypeReferenceBeanOutputConverterIT extends AbstractIT {
 
 	private static final Logger logger = LoggerFactory
-		.getLogger(OpenAiModelCallerTypeReferenceBeanOutputConverterIT.class);
+		.getLogger(OpenAiChatModelTypeReferenceBeanOutputConverterIT.class);
 
 	record ActorsFilmsRecord(String actor, List<String> movies) {
 	}
@@ -61,7 +61,7 @@ class OpenAiModelCallerTypeReferenceBeanOutputConverterIT extends AbstractIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = modelCaller.call(prompt).getResult();
+		Generation generation = chatModel.call(prompt).getResult();
 
 		List<ActorsFilmsRecord> actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		logger.info("" + actorsFilms);
@@ -87,7 +87,7 @@ class OpenAiModelCallerTypeReferenceBeanOutputConverterIT extends AbstractIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
 
-		String generationTextFromStream = streamingChatClient.stream(prompt)
+		String generationTextFromStream = streamingChatModel.stream(prompt)
 			.collectList()
 			.block()
 			.stream()

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatModelWithChatResponseMetadataTests.java

@@ -27,7 +27,7 @@ import org.springframework.ai.chat.metadata.PromptMetadata;
 import org.springframework.ai.chat.metadata.RateLimit;
 import org.springframework.ai.chat.metadata.Usage;
 import org.springframework.ai.openai.api.OpenAiApi;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.metadata.support.OpenAiApiResponseHeaders;
 import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.beans.factory.annotation.Autowired;
@@ -51,13 +51,13 @@ import static org.springframework.test.web.client.response.MockRestResponseCreat
  * @author Christian Tzolov
  * @since 0.7.0
  */
-@RestClientTest(OpenAiChatClientWithChatResponseMetadataTests.Config.class)
-public class OpenAiChatClientWithChatResponseMetadataTests {
+@RestClientTest(OpenAiChatModelWithChatResponseMetadataTests.Config.class)
+public class OpenAiChatModelWithChatResponseMetadataTests {
 
 	private static String TEST_API_KEY = "sk-1234567890";
 
 	@Autowired
-	private OpenAiModelCaller openAiChatClient;
+	private OpenAiChatModel openAiChatClient;
 
 	@Autowired
 	private MockRestServiceServer server;
@@ -171,8 +171,8 @@ public class OpenAiChatClientWithChatResponseMetadataTests {
 		}
 
 		@Bean
-		public OpenAiModelCaller openAiClient(OpenAiApi openAiApi) {
-			return new OpenAiModelCaller(openAiApi);
+		public OpenAiChatModel openAiClient(OpenAiApi openAiApi) {
+			return new OpenAiChatModel(openAiApi);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiRetryTests.java

@@ -29,13 +29,13 @@ import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.ai.document.MetadataMode;
 import org.springframework.ai.image.ImageMessage;
 import org.springframework.ai.image.ImagePrompt;
-import org.springframework.ai.openai.OpenAiAudioTranscriptionClient;
+import org.springframework.ai.openai.OpenAiAudioTranscriptionModel;
 import org.springframework.ai.openai.OpenAiAudioTranscriptionOptions;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.OpenAiChatOptions;
-import org.springframework.ai.openai.OpenAiEmbeddingClient;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
 import org.springframework.ai.openai.OpenAiEmbeddingOptions;
-import org.springframework.ai.openai.OpenAiImageClient;
+import org.springframework.ai.openai.OpenAiImageModel;
 import org.springframework.ai.openai.OpenAiImageOptions;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.openai.api.OpenAiApi.ChatCompletion;
@@ -107,13 +107,13 @@ public class OpenAiRetryTests {
 
 	private @Mock OpenAiImageApi openAiImageApi;
 
-	private OpenAiModelCaller chatClient;
+	private OpenAiChatModel chatModel;
 
-	private OpenAiEmbeddingClient embeddingClient;
+	private OpenAiEmbeddingModel embeddingModel;
 
-	private OpenAiAudioTranscriptionClient audioTranscriptionClient;
+	private OpenAiAudioTranscriptionModel audioTranscriptionModel;
 
-	private OpenAiImageClient imageClient;
+	private OpenAiImageModel imageModel;
 
 	@BeforeEach
 	public void beforeEach() {
@@ -121,16 +121,16 @@ public class OpenAiRetryTests {
 		retryListener = new TestRetryListener();
 		retryTemplate.registerListener(retryListener);
 
-		chatClient = new OpenAiModelCaller(openAiApi, OpenAiChatOptions.builder().build(), null, retryTemplate);
-		embeddingClient = new OpenAiEmbeddingClient(openAiApi, MetadataMode.EMBED,
+		chatModel = new OpenAiChatModel(openAiApi, OpenAiChatOptions.builder().build(), null, retryTemplate);
+		embeddingModel = new OpenAiEmbeddingModel(openAiApi, MetadataMode.EMBED,
 				OpenAiEmbeddingOptions.builder().build(), retryTemplate);
-		audioTranscriptionClient = new OpenAiAudioTranscriptionClient(openAiAudioApi,
+		audioTranscriptionModel = new OpenAiAudioTranscriptionModel(openAiAudioApi,
 				OpenAiAudioTranscriptionOptions.builder()
 					.withModel("model")
 					.withResponseFormat(TranscriptResponseFormat.JSON)
 					.build(),
 				retryTemplate);
-		imageClient = new OpenAiImageClient(openAiImageApi, OpenAiImageOptions.builder().build(), retryTemplate);
+		imageModel = new OpenAiImageModel(openAiImageApi, OpenAiImageOptions.builder().build(), retryTemplate);
 	}
 
 	@Test
@@ -146,7 +146,7 @@ public class OpenAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedChatCompletion)));
 
-		var result = chatClient.call(new Prompt("text"));
+		var result = chatModel.call(new Prompt("text"));
 
 		assertThat(result).isNotNull();
 		assertThat(result.getResult().getOutput().getContent()).isSameAs("Response");
@@ -158,7 +158,7 @@ public class OpenAiRetryTests {
 	public void openAiChatNonTransientError() {
 		when(openAiApi.chatCompletionEntity(isA(ChatCompletionRequest.class)))
 				.thenThrow(new RuntimeException("Non Transient Error"));
-		assertThrows(RuntimeException.class, () -> chatClient.call(new Prompt("text")));
+		assertThrows(RuntimeException.class, () -> chatModel.call(new Prompt("text")));
 	}
 
 	@Test
@@ -174,7 +174,7 @@ public class OpenAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(Flux.just(expectedChatCompletion));
 
-		var result = chatClient.stream(new Prompt("text"));
+		var result = chatModel.stream(new Prompt("text"));
 
 		assertThat(result).isNotNull();
 		assertThat(result.collectList().block().get(0).getResult().getOutput().getContent()).isSameAs("Response");
@@ -186,7 +186,7 @@ public class OpenAiRetryTests {
 	public void openAiChatStreamNonTransientError() {
 		when(openAiApi.chatCompletionStream(isA(ChatCompletionRequest.class)))
 				.thenThrow(new RuntimeException("Non Transient Error"));
-		assertThrows(RuntimeException.class, () -> chatClient.stream(new Prompt("text")));
+		assertThrows(RuntimeException.class, () -> chatModel.stream(new Prompt("text")));
 	}
 
 	@Test
@@ -199,7 +199,7 @@ public class OpenAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedEmbeddings)));
 
-		var result = embeddingClient
+		var result = embeddingModel
 			.call(new org.springframework.ai.embedding.EmbeddingRequest(List.of("text1", "text2"), null));
 
 		assertThat(result).isNotNull();
@@ -212,7 +212,7 @@ public class OpenAiRetryTests {
 	public void openAiEmbeddingNonTransientError() {
 		when(openAiApi.embeddings(isA(EmbeddingRequest.class)))
 				.thenThrow(new RuntimeException("Non Transient Error"));
-		assertThrows(RuntimeException.class, () -> embeddingClient
+		assertThrows(RuntimeException.class, () -> embeddingModel
 				.call(new org.springframework.ai.embedding.EmbeddingRequest(List.of("text1", "text2"), null)));
 	}
 
@@ -226,7 +226,7 @@ public class OpenAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedResponse)));
 
-		AudioTranscriptionResponse result = audioTranscriptionClient
+		AudioTranscriptionResponse result = audioTranscriptionModel
 			.call(new AudioTranscriptionPrompt(new ClassPathResource("speech/jfk.flac")));
 
 		assertThat(result).isNotNull();
@@ -239,7 +239,7 @@ public class OpenAiRetryTests {
 	public void openAiAudioTranscriptionNonTransientError() {
 		when(openAiAudioApi.createTranscription(isA(TranscriptionRequest.class), isA(Class.class)))
 				.thenThrow(new RuntimeException("Transient Error 1"));
-		assertThrows(RuntimeException.class, () -> audioTranscriptionClient
+		assertThrows(RuntimeException.class, () -> audioTranscriptionModel
 				.call(new AudioTranscriptionPrompt(new ClassPathResource("speech/jfk.flac"))));
 	}
 
@@ -253,7 +253,7 @@ public class OpenAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedResponse)));
 
-		var result = imageClient.call(new ImagePrompt(List.of(new ImageMessage("Image Message"))));
+		var result = imageModel.call(new ImagePrompt(List.of(new ImageMessage("Image Message"))));
 
 		assertThat(result).isNotNull();
 		assertThat(result.getResult().getOutput().getUrl()).isEqualTo("url678");
@@ -266,7 +266,7 @@ public class OpenAiRetryTests {
 		when(openAiImageApi.createImage(isA(OpenAiImageRequest.class)))
 				.thenThrow(new RuntimeException("Transient Error 1"));
 		assertThrows(RuntimeException.class,
-				() -> imageClient.call(new ImagePrompt(List.of(new ImageMessage("Image Message")))));
+				() -> imageModel.call(new ImagePrompt(List.of(new ImageMessage("Image Message")))));
 	}
 
 }

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/ChatMemoryLongTermSystemPromptIT.java

@@ -33,11 +33,11 @@ import org.springframework.ai.chat.memory.VectorStoreChatMemoryChatServiceListen
 import org.springframework.ai.chat.memory.VectorStoreChatMemoryRetriever;
 import org.springframework.ai.chat.memory.LastMaxTokenSizeContentTransformer;
 import org.springframework.ai.chat.memory.SystemPromptChatMemoryAugmentor;
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.evaluation.BaseMemoryTest;
 import org.springframework.ai.evaluation.RelevancyEvaluator;
-import org.springframework.ai.openai.OpenAiModelCaller;
-import org.springframework.ai.openai.OpenAiEmbeddingClient;
+import org.springframework.ai.openai.OpenAiChatModel;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
 import org.springframework.ai.tokenizer.TokenCountEstimator;
@@ -75,21 +75,21 @@ public class ChatMemoryLongTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public OpenAiModelCaller openAiClient(OpenAiApi openAiApi) {
-			return new OpenAiModelCaller(openAiApi);
+		public OpenAiChatModel openAiClient(OpenAiApi openAiApi) {
+			return new OpenAiChatModel(openAiApi);
 		}
 
 		@Bean
-		public EmbeddingClient embeddingClient(OpenAiApi openAiApi) {
-			return new OpenAiEmbeddingClient(openAiApi);
+		public EmbeddingModel embeddingModel(OpenAiApi openAiApi) {
+			return new OpenAiEmbeddingModel(openAiApi);
 		}
 
 		@Bean
-		public VectorStore qdrantVectorStore(EmbeddingClient embeddingClient) {
+		public VectorStore qdrantVectorStore(EmbeddingModel embeddingModel) {
 			QdrantClient qdrantClient = new QdrantClient(QdrantGrpcClient
 				.newBuilder(qdrantContainer.getHost(), qdrantContainer.getMappedPort(QDRANT_GRPC_PORT), false)
 				.build());
-			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingClient);
+			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingModel);
 		}
 
 		@Bean
@@ -98,10 +98,10 @@ public class ChatMemoryLongTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public ChatService memoryChatService(OpenAiModelCaller chatClient, VectorStore vectorStore,
+		public ChatService memoryChatService(OpenAiChatModel chatModel, VectorStore vectorStore,
 				TokenCountEstimator tokenCountEstimator) {
 
-			return PromptTransformingChatService.builder(chatClient)
+			return PromptTransformingChatService.builder(chatModel)
 				.withRetrievers(List.of(new VectorStoreChatMemoryRetriever(vectorStore, 10)))
 				.withContentPostProcessors(List.of(new LastMaxTokenSizeContentTransformer(tokenCountEstimator, 1000)))
 				.withAugmentors(List.of(new SystemPromptChatMemoryAugmentor()))
@@ -110,10 +110,10 @@ public class ChatMemoryLongTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public StreamingChatService memoryStreamingChatService(OpenAiModelCaller streamingChatClient,
+		public StreamingChatService memoryStreamingChatService(OpenAiChatModel streamingChatModel,
 				VectorStore vectorStore, TokenCountEstimator tokenCountEstimator) {
 
-			return StreamingPromptTransformingChatService.builder(streamingChatClient)
+			return StreamingPromptTransformingChatService.builder(streamingChatModel)
 				.withRetrievers(List.of(new VectorStoreChatMemoryRetriever(vectorStore, 10)))
 				.withDocumentPostProcessors(List.of(new LastMaxTokenSizeContentTransformer(tokenCountEstimator, 1000)))
 				.withAugmentors(List.of(new SystemPromptChatMemoryAugmentor()))
@@ -122,8 +122,8 @@ public class ChatMemoryLongTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public RelevancyEvaluator relevancyEvaluator(OpenAiModelCaller chatClient) {
-			return new RelevancyEvaluator(chatClient);
+		public RelevancyEvaluator relevancyEvaluator(OpenAiChatModel chatModel) {
+			return new RelevancyEvaluator(chatModel);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/ChatMemoryShortTermMessageListIT.java

@@ -31,7 +31,7 @@ import org.springframework.ai.chat.memory.LastMaxTokenSizeContentTransformer;
 import org.springframework.ai.chat.memory.MessageChatMemoryAugmentor;
 import org.springframework.ai.evaluation.BaseMemoryTest;
 import org.springframework.ai.evaluation.RelevancyEvaluator;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
 import org.springframework.ai.tokenizer.TokenCountEstimator;
@@ -59,8 +59,8 @@ public class ChatMemoryShortTermMessageListIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public OpenAiModelCaller openAiClient(OpenAiApi openAiApi) {
-			return new OpenAiModelCaller(openAiApi);
+		public OpenAiChatModel openAiClient(OpenAiApi openAiApi) {
+			return new OpenAiChatModel(openAiApi);
 		}
 
 		@Bean
@@ -74,10 +74,10 @@ public class ChatMemoryShortTermMessageListIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public ChatService memoryChatService(OpenAiModelCaller chatClient, ChatMemory chatHistory,
+		public ChatService memoryChatService(OpenAiChatModel chatModel, ChatMemory chatHistory,
 				TokenCountEstimator tokenCountEstimator) {
 
-			return PromptTransformingChatService.builder(chatClient)
+			return PromptTransformingChatService.builder(chatModel)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))
 				.withContentPostProcessors(List.of(new LastMaxTokenSizeContentTransformer(tokenCountEstimator, 1000)))
 				.withAugmentors(List.of(new MessageChatMemoryAugmentor()))
@@ -86,10 +86,10 @@ public class ChatMemoryShortTermMessageListIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public StreamingChatService memoryStreamingChatService(OpenAiModelCaller streamingChatClient,
+		public StreamingChatService memoryStreamingChatService(OpenAiChatModel streamingChatModel,
 				ChatMemory chatHistory, TokenCountEstimator tokenCountEstimator) {
 
-			return StreamingPromptTransformingChatService.builder(streamingChatClient)
+			return StreamingPromptTransformingChatService.builder(streamingChatModel)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))
 				.withDocumentPostProcessors(List.of(new LastMaxTokenSizeContentTransformer(tokenCountEstimator, 1000)))
 				.withAugmentors(List.of(new MessageChatMemoryAugmentor()))
@@ -98,8 +98,8 @@ public class ChatMemoryShortTermMessageListIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public RelevancyEvaluator relevancyEvaluator(OpenAiModelCaller chatClient) {
-			return new RelevancyEvaluator(chatClient);
+		public RelevancyEvaluator relevancyEvaluator(OpenAiChatModel chatModel) {
+			return new RelevancyEvaluator(chatModel);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/ChatMemoryShortTermSystemPromptIT.java

@@ -32,7 +32,7 @@ import org.springframework.ai.chat.memory.LastMaxTokenSizeContentTransformer;
 import org.springframework.ai.chat.memory.SystemPromptChatMemoryAugmentor;
 import org.springframework.ai.evaluation.BaseMemoryTest;
 import org.springframework.ai.evaluation.RelevancyEvaluator;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
 import org.springframework.ai.tokenizer.TokenCountEstimator;
@@ -60,8 +60,8 @@ public class ChatMemoryShortTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public OpenAiModelCaller openAiClient(OpenAiApi openAiApi) {
-			return new OpenAiModelCaller(openAiApi);
+		public OpenAiChatModel openAiClient(OpenAiApi openAiApi) {
+			return new OpenAiChatModel(openAiApi);
 		}
 
 		@Bean
@@ -75,10 +75,10 @@ public class ChatMemoryShortTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public ChatService memoryChatService(OpenAiModelCaller chatClient, ChatMemory chatHistory,
+		public ChatService memoryChatService(OpenAiChatModel chatModel, ChatMemory chatHistory,
 				TokenCountEstimator tokenCountEstimator) {
 
-			return PromptTransformingChatService.builder(chatClient)
+			return PromptTransformingChatService.builder(chatModel)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))
 				.withContentPostProcessors(List.of(new LastMaxTokenSizeContentTransformer(tokenCountEstimator, 1000)))
 				.withAugmentors(List.of(new SystemPromptChatMemoryAugmentor()))
@@ -87,10 +87,10 @@ public class ChatMemoryShortTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public StreamingChatService memoryStreamingChatService(OpenAiModelCaller streamingChatClient,
+		public StreamingChatService memoryStreamingChatService(OpenAiChatModel streamingChatModel,
 				ChatMemory chatHistory, TokenCountEstimator tokenCountEstimator) {
 
-			return StreamingPromptTransformingChatService.builder(streamingChatClient)
+			return StreamingPromptTransformingChatService.builder(streamingChatModel)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))
 				.withDocumentPostProcessors(List.of(new LastMaxTokenSizeContentTransformer(tokenCountEstimator, 1000)))
 				.withAugmentors(List.of(new SystemPromptChatMemoryAugmentor()))
@@ -99,8 +99,8 @@ public class ChatMemoryShortTermSystemPromptIT extends BaseMemoryTest {
 		}
 
 		@Bean
-		public RelevancyEvaluator relevancyEvaluator(OpenAiModelCaller chatClient) {
-			return new RelevancyEvaluator(chatClient);
+		public RelevancyEvaluator relevancyEvaluator(OpenAiChatModel chatModel) {
+			return new RelevancyEvaluator(chatModel);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/LongShortTermChatMemoryWithRagIT.java

@@ -30,7 +30,7 @@ import org.springframework.ai.chat.prompt.transformer.ChatServiceContext;
 import org.springframework.ai.chat.service.ChatService;
 import org.springframework.ai.chat.service.PromptTransformingChatService;
 import org.springframework.ai.openai.OpenAiChatOptions;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
 import org.testcontainers.qdrant.QdrantContainer;
@@ -50,10 +50,10 @@ import org.springframework.ai.chat.prompt.transformer.TransformerContentType;
 import org.springframework.ai.chat.prompt.transformer.VectorStoreRetriever;
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.DocumentTransformer;
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.evaluation.EvaluationResponse;
 import org.springframework.ai.evaluation.RelevancyEvaluator;
-import org.springframework.ai.openai.OpenAiEmbeddingClient;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.reader.JsonReader;
 import org.springframework.ai.tokenizer.JTokkitTokenCountEstimator;
@@ -163,21 +163,21 @@ public class LongShortTermChatMemoryWithRagIT {
 		}
 
 		@Bean
-		public OpenAiModelCaller openAiClient(OpenAiApi openAiApi) {
-			return new OpenAiModelCaller(openAiApi);
+		public OpenAiChatModel openAiClient(OpenAiApi openAiApi) {
+			return new OpenAiChatModel(openAiApi);
 		}
 
 		@Bean
-		public OpenAiEmbeddingClient embeddingClient(OpenAiApi openAiApi) {
-			return new OpenAiEmbeddingClient(openAiApi);
+		public OpenAiEmbeddingModel embeddingModel(OpenAiApi openAiApi) {
+			return new OpenAiEmbeddingModel(openAiApi);
 		}
 
 		@Bean
-		public VectorStore qdrantVectorStore(EmbeddingClient embeddingClient) {
+		public VectorStore qdrantVectorStore(EmbeddingModel embeddingModel) {
 			QdrantClient qdrantClient = new QdrantClient(QdrantGrpcClient
 				.newBuilder(qdrantContainer.getHost(), qdrantContainer.getMappedPort(QDRANT_GRPC_PORT), false)
 				.build());
-			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingClient);
+			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingModel);
 		}
 
 		@Bean
@@ -186,10 +186,10 @@ public class LongShortTermChatMemoryWithRagIT {
 		}
 
 		@Bean
-		public ChatService memoryChatService(OpenAiModelCaller chatClient, VectorStore vectorStore,
+		public ChatService memoryChatService(OpenAiChatModel chatModel, VectorStore vectorStore,
 				TokenCountEstimator tokenCountEstimator, ChatMemory chatHistory) {
 
-			return PromptTransformingChatService.builder(chatClient)
+			return PromptTransformingChatService.builder(chatModel)
 				.withRetrievers(List.of(new VectorStoreRetriever(vectorStore, SearchRequest.defaults()),
 						ChatMemoryRetriever.builder()
 							.withChatHistory(chatHistory)
@@ -223,12 +223,12 @@ public class LongShortTermChatMemoryWithRagIT {
 		}
 
 		// @Bean
-		// public StreamingChatService memoryStreamingChatAgent(OpenAiModelCall
-		// streamingChatClient,
+		// public StreamingChatService memoryStreamingChatAgent(OpenAiChatModel
+		// streamingChatModel,
 		// VectorStore vectorStore, TokenCountEstimator tokenCountEstimator, ChatHistory
 		// chatHistory) {
 
-		// return StreamingPromptTransformingChatService.builder(streamingChatClient)
+		// return StreamingPromptTransformingChatService.builder(streamingChatModel)
 		// .withRetrievers(List.of(new ChatHistoryRetriever(chatHistory), new
 		// DocumentChatHistoryRetriever(vectorStore, 10)))
 		// .withDocumentPostProcessors(List.of(new
@@ -240,13 +240,13 @@ public class LongShortTermChatMemoryWithRagIT {
 		// }
 
 		@Bean
-		public RelevancyEvaluator relevancyEvaluator(OpenAiModelCaller chatClient) {
+		public RelevancyEvaluator relevancyEvaluator(OpenAiChatModel chatModel) {
 			// Use GPT 4 as a better model for determining relevancy. gpt 3.5 makes basic
 			// mistakes
 			OpenAiChatOptions openAiChatOptions = OpenAiChatOptions.builder()
 				.withModel(GPT_4_TURBO_PREVIEW.getValue())
 				.build();
-			return new RelevancyEvaluator(chatClient, openAiChatOptions);
+			return new RelevancyEvaluator(chatModel, openAiChatOptions);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/OpenAiPromptTransformingChatServiceIT.java

@@ -23,7 +23,7 @@ import io.qdrant.client.QdrantClient;
 import io.qdrant.client.QdrantGrpcClient;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.service.ChatService;
 import org.springframework.ai.chat.prompt.transformer.TransformerContentType;
 import org.springframework.ai.document.Document;
@@ -38,11 +38,11 @@ import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.ai.chat.prompt.transformer.ChatServiceContext;
 import org.springframework.ai.chat.prompt.transformer.QuestionContextAugmentor;
 import org.springframework.ai.chat.prompt.transformer.VectorStoreRetriever;
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.evaluation.EvaluationResponse;
 import org.springframework.ai.evaluation.RelevancyEvaluator;
-import org.springframework.ai.openai.OpenAiModelCaller;
-import org.springframework.ai.openai.OpenAiEmbeddingClient;
+import org.springframework.ai.openai.OpenAiChatModel;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.reader.JsonReader;
 import org.springframework.ai.transformer.splitter.TokenTextSplitter;
@@ -71,7 +71,7 @@ public class OpenAiPromptTransformingChatServiceIT {
 	@Container
 	static QdrantContainer qdrantContainer = new QdrantContainer("qdrant/qdrant:v1.9.2");
 
-	private final ChatCaller modelCaller;
+	private final ChatModel chatModel;
 
 	private final VectorStore vectorStore;
 
@@ -81,9 +81,9 @@ public class OpenAiPromptTransformingChatServiceIT {
 	private ChatService chatService;
 
 	@Autowired
-	public OpenAiPromptTransformingChatServiceIT(ChatCaller modelCaller, ChatService chatService,
+	public OpenAiPromptTransformingChatServiceIT(ChatModel chatModel, ChatService chatService,
 			VectorStore vectorStore) {
-		this.modelCaller = modelCaller;
+		this.chatModel = chatModel;
 		this.chatService = chatService;
 		this.vectorStore = vectorStore;
 	}
@@ -102,7 +102,7 @@ public class OpenAiPromptTransformingChatServiceIT {
 		OpenAiChatOptions openAiChatOptions = OpenAiChatOptions.builder()
 			.withModel(GPT_4_TURBO_PREVIEW.getValue())
 			.build();
-		var relevancyEvaluator = new RelevancyEvaluator(this.modelCaller, openAiChatOptions);
+		var relevancyEvaluator = new RelevancyEvaluator(this.chatModel, openAiChatOptions);
 
 		EvaluationResponse evaluationResponse = relevancyEvaluator.evaluate(chatServiceResponse.toEvaluationRequest());
 		assertTrue(evaluationResponse.isPass(), "Response is not relevant to the question");
@@ -145,26 +145,26 @@ public class OpenAiPromptTransformingChatServiceIT {
 		}
 
 		@Bean
-		public ChatCaller openAiClient(OpenAiApi openAiApi) {
-			return new OpenAiModelCaller(openAiApi);
+		public ChatModel openAiClient(OpenAiApi openAiApi) {
+			return new OpenAiChatModel(openAiApi);
 		}
 
 		@Bean
-		public EmbeddingClient embeddingClient(OpenAiApi openAiApi) {
-			return new OpenAiEmbeddingClient(openAiApi);
+		public EmbeddingModel embeddingModel(OpenAiApi openAiApi) {
+			return new OpenAiEmbeddingModel(openAiApi);
 		}
 
 		@Bean
-		public VectorStore qdrantVectorStore(EmbeddingClient embeddingClient) {
+		public VectorStore qdrantVectorStore(EmbeddingModel embeddingModel) {
 			QdrantClient qdrantClient = new QdrantClient(QdrantGrpcClient
 				.newBuilder(qdrantContainer.getHost(), qdrantContainer.getMappedPort(QDRANT_GRPC_PORT), false)
 				.build());
-			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingClient);
+			return new QdrantVectorStore(qdrantClient, COLLECTION_NAME, embeddingModel);
 		}
 
 		@Bean
-		public ChatService chatService(ChatCaller modelCaller, VectorStore vectorStore) {
-			return PromptTransformingChatService.builder(modelCaller)
+		public ChatService chatService(ChatModel chatModel, VectorStore vectorStore) {
+			return PromptTransformingChatService.builder(chatModel)
 				.withRetrievers(List.of(new VectorStoreRetriever(vectorStore, SearchRequest.defaults())))
 				.withAugmentors(List.of(new QuestionContextAugmentor()))
 				.build();

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/embedding/EmbeddingIT.java

@@ -19,7 +19,7 @@ import org.junit.jupiter.api.Test;
 
 import org.springframework.ai.embedding.EmbeddingRequest;
 import org.springframework.ai.embedding.EmbeddingResponse;
-import org.springframework.ai.openai.OpenAiEmbeddingClient;
+import org.springframework.ai.openai.OpenAiEmbeddingModel;
 import org.springframework.ai.openai.OpenAiEmbeddingOptions;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.boot.test.context.SpringBootTest;
@@ -32,13 +32,13 @@ import static org.assertj.core.api.Assertions.assertThat;
 class EmbeddingIT {
 
 	@Autowired
-	private OpenAiEmbeddingClient embeddingClient;
+	private OpenAiEmbeddingModel embeddingModel;
 
 	@Test
 	void defaultEmbedding() {
-		assertThat(embeddingClient).isNotNull();
+		assertThat(embeddingModel).isNotNull();
 
-		EmbeddingResponse embeddingResponse = embeddingClient.embedForResponse(List.of("Hello World"));
+		EmbeddingResponse embeddingResponse = embeddingModel.embedForResponse(List.of("Hello World"));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0)).isNotNull();
 		assertThat(embeddingResponse.getResults().get(0).getOutput()).hasSize(1536);
@@ -46,13 +46,13 @@ class EmbeddingIT {
 		assertThat(embeddingResponse.getMetadata()).containsEntry("total-tokens", 2);
 		assertThat(embeddingResponse.getMetadata()).containsEntry("prompt-tokens", 2);
 
-		assertThat(embeddingClient.dimensions()).isEqualTo(1536);
+		assertThat(embeddingModel.dimensions()).isEqualTo(1536);
 	}
 
 	@Test
 	void embedding3Large() {
 
-		EmbeddingResponse embeddingResponse = embeddingClient.call(new EmbeddingRequest(List.of("Hello World"),
+		EmbeddingResponse embeddingResponse = embeddingModel.call(new EmbeddingRequest(List.of("Hello World"),
 				OpenAiEmbeddingOptions.builder().withModel("text-embedding-3-large").build()));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0)).isNotNull();
@@ -61,13 +61,13 @@ class EmbeddingIT {
 		assertThat(embeddingResponse.getMetadata()).containsEntry("total-tokens", 2);
 		assertThat(embeddingResponse.getMetadata()).containsEntry("prompt-tokens", 2);
 
-		// assertThat(embeddingClient.dimensions()).isEqualTo(3072);
+		// assertThat(embeddingModel.dimensions()).isEqualTo(3072);
 	}
 
 	@Test
 	void textEmbeddingAda002() {
 
-		EmbeddingResponse embeddingResponse = embeddingClient.call(new EmbeddingRequest(List.of("Hello World"),
+		EmbeddingResponse embeddingResponse = embeddingModel.call(new EmbeddingRequest(List.of("Hello World"),
 				OpenAiEmbeddingOptions.builder().withModel("text-embedding-3-small").build()));
 		assertThat(embeddingResponse.getResults()).hasSize(1);
 		assertThat(embeddingResponse.getResults().get(0)).isNotNull();
@@ -77,7 +77,7 @@ class EmbeddingIT {
 		assertThat(embeddingResponse.getMetadata()).containsEntry("total-tokens", 2);
 		assertThat(embeddingResponse.getMetadata()).containsEntry("prompt-tokens", 2);
 
-		// assertThat(embeddingClient.dimensions()).isEqualTo(3072);
+		// assertThat(embeddingModel.dimensions()).isEqualTo(3072);
 	}
 
 }

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/image/OpenAiImageModelIT.java

@@ -33,7 +33,7 @@ import static org.assertj.core.api.Assertions.assertThat;
 
 @SpringBootTest(classes = OpenAiTestConfiguration.class)
 @EnabledIfEnvironmentVariable(named = "OPENAI_API_KEY", matches = ".+")
-public class OpenAiImageClientIT extends AbstractIT {
+public class OpenAiImageModelIT extends AbstractIT {
 
 	@Test
 	void imageAsUrlTest() {
@@ -44,7 +44,7 @@ public class OpenAiImageClientIT extends AbstractIT {
 
 		ImagePrompt imagePrompt = new ImagePrompt(instructions, options);
 
-		ImageResponse imageResponse = imageClient.call(imagePrompt);
+		ImageResponse imageResponse = imageModel.call(imagePrompt);
 
 		assertThat(imageResponse.getResults()).hasSize(1);
 

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/image/OpenAiImageModelWithImageResponseMetadataTests.java

@@ -21,7 +21,7 @@ import org.springframework.ai.image.ImageGeneration;
 import org.springframework.ai.image.ImagePrompt;
 import org.springframework.ai.image.ImageResponse;
 import org.springframework.ai.image.ImageResponseMetadata;
-import org.springframework.ai.openai.OpenAiImageClient;
+import org.springframework.ai.openai.OpenAiImageModel;
 import org.springframework.ai.openai.api.OpenAiImageApi;
 import org.springframework.ai.openai.metadata.support.OpenAiApiResponseHeaders;
 import org.springframework.beans.factory.annotation.Autowired;
@@ -47,13 +47,13 @@ import static org.springframework.test.web.client.response.MockRestResponseCreat
  * @author Christian Tzolov
  * @since 0.7.0
  */
-@RestClientTest(OpenAiImageClientWithImageResponseMetadataTests.Config.class)
-public class OpenAiImageClientWithImageResponseMetadataTests {
+@RestClientTest(OpenAiImageModelWithImageResponseMetadataTests.Config.class)
+public class OpenAiImageModelWithImageResponseMetadataTests {
 
 	private static String TEST_API_KEY = "sk-1234567890";
 
 	@Autowired
-	private OpenAiImageClient openAiImageClient;
+	private OpenAiImageModel openAiImageModel;
 
 	@Autowired
 	private MockRestServiceServer server;
@@ -70,7 +70,7 @@ public class OpenAiImageClientWithImageResponseMetadataTests {
 
 		ImagePrompt prompt = new ImagePrompt("Create an image of a mini golden doodle dog.");
 
-		ImageResponse response = this.openAiImageClient.call(prompt);
+		ImageResponse response = this.openAiImageModel.call(prompt);
 
 		assertThat(response).isNotNull();
 		List<ImageGeneration> imageGenerations = response.getResults();
@@ -134,8 +134,8 @@ public class OpenAiImageClientWithImageResponseMetadataTests {
 		}
 
 		@Bean
-		public OpenAiImageClient openAiImageClient(OpenAiImageApi openAiImageApi) {
-			return new OpenAiImageClient(openAiImageApi);
+		public OpenAiImageModel openAiImageModel(OpenAiImageApi openAiImageApi) {
+			return new OpenAiImageModel(openAiImageApi);
 		}
 
 	}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/testutils/AbstractIT.java

@@ -21,16 +21,16 @@ import java.util.Map;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
-import org.springframework.ai.chat.ChatCaller;
+import org.springframework.ai.chat.ChatModel;
 import org.springframework.ai.chat.ChatResponse;
-import org.springframework.ai.chat.StreamingChatCaller;
+import org.springframework.ai.chat.StreamingChatModel;
 import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.ai.chat.prompt.PromptTemplate;
 import org.springframework.ai.chat.messages.Message;
 import org.springframework.ai.chat.messages.SystemMessage;
-import org.springframework.ai.image.ImageClient;
-import org.springframework.ai.openai.OpenAiAudioSpeechClient;
-import org.springframework.ai.openai.OpenAiAudioTranscriptionClient;
+import org.springframework.ai.image.ImageModel;
+import org.springframework.ai.openai.OpenAiAudioSpeechModel;
+import org.springframework.ai.openai.OpenAiAudioTranscriptionModel;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.beans.factory.annotation.Value;
 import org.springframework.core.io.Resource;
@@ -43,19 +43,19 @@ public abstract class AbstractIT {
 	private static final Logger logger = LoggerFactory.getLogger(AbstractIT.class);
 
 	@Autowired
-	protected ChatCaller modelCaller;
+	protected ChatModel chatModel;
 
 	@Autowired
-	protected StreamingChatCaller streamingChatClient;
+	protected StreamingChatModel streamingChatModel;
 
 	@Autowired
-	protected OpenAiAudioTranscriptionClient transcriptionClient;
+	protected OpenAiAudioTranscriptionModel transcriptionModel;
 
 	@Autowired
-	protected OpenAiAudioSpeechClient speechClient;
+	protected OpenAiAudioSpeechModel speechModel;
 
 	@Autowired
-	protected ImageClient imageClient;
+	protected ImageModel imageModel;
 
 	@Value("classpath:/prompts/eval/qa-evaluator-accurate-answer.st")
 	protected Resource qaEvaluatorAccurateAnswerResource;
@@ -85,12 +85,12 @@ public abstract class AbstractIT {
 		}
 		Message userMessage = userPromptTemplate.createMessage();
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		String yesOrNo = modelCaller.call(prompt).getResult().getOutput().getContent();
+		String yesOrNo = chatModel.call(prompt).getResult().getOutput().getContent();
 		logger.info("Is Answer related to question: " + yesOrNo);
 		if (yesOrNo.equalsIgnoreCase("no")) {
 			SystemMessage notRelatedSystemMessage = new SystemMessage(qaEvaluatorNotRelatedResource);
 			prompt = new Prompt(List.of(userMessage, notRelatedSystemMessage));
-			String reasonForFailure = modelCaller.call(prompt).getResult().getOutput().getContent();
+			String reasonForFailure = chatModel.call(prompt).getResult().getOutput().getContent();
 			fail(reasonForFailure);
 		}
 		else {

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/transformer/MetadataTransformerIT.java

@@ -24,7 +24,7 @@ import org.junit.jupiter.api.Test;
 
 import org.springframework.ai.document.DefaultContentFormatter;
 import org.springframework.ai.document.Document;
-import org.springframework.ai.openai.OpenAiModelCaller;
+import org.springframework.ai.openai.OpenAiChatModel;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.transformer.ContentFormatTransformer;
 import org.springframework.ai.transformer.KeywordMetadataEnricher;
@@ -163,18 +163,18 @@ public class MetadataTransformerIT {
 		}
 
 		@Bean
-		public OpenAiModelCaller openAiChatClient(OpenAiApi openAiApi) {
-			OpenAiModelCaller openAiChatClient = new OpenAiModelCaller(openAiApi);
-			return openAiChatClient;
+		public OpenAiChatModel openAiChatModel(OpenAiApi openAiApi) {
+			OpenAiChatModel openAiChatModel = new OpenAiChatModel(openAiApi);
+			return openAiChatModel;
 		}
 
 		@Bean
-		public KeywordMetadataEnricher keywordMetadata(OpenAiModelCaller aiClient) {
+		public KeywordMetadataEnricher keywordMetadata(OpenAiChatModel aiClient) {
 			return new KeywordMetadataEnricher(aiClient, 5);
 		}
 
 		@Bean
-		public SummaryMetadataEnricher summaryMetadata(OpenAiModelCaller aiClient) {
+		public SummaryMetadataEnricher summaryMetadata(OpenAiChatModel aiClient) {
 			return new SummaryMetadataEnricher(aiClient,
 					List.of(SummaryType.PREVIOUS, SummaryType.CURRENT, SummaryType.NEXT));
 		}

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/vectorstore/SimplePersistentVectorStoreIT.java

@@ -19,7 +19,7 @@ import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.io.CleanupMode;
 import org.junit.jupiter.api.io.TempDir;
 import org.springframework.ai.document.Document;
-import org.springframework.ai.embedding.EmbeddingClient;
+import org.springframework.ai.embedding.EmbeddingModel;
 import org.springframework.ai.reader.JsonReader;
 import org.springframework.ai.vectorstore.SimpleVectorStore;
 import org.springframework.ai.reader.JsonMetadataGenerator;
@@ -42,21 +42,21 @@ public class SimplePersistentVectorStoreIT {
 	private Resource bikesJsonResource;
 
 	@Autowired
-	private EmbeddingClient embeddingClient;
+	private EmbeddingModel embeddingModel;
 
 	@Test
 	void persist(@TempDir(cleanup = CleanupMode.ON_SUCCESS) Path workingDir) {
 		JsonReader jsonReader = new JsonReader(bikesJsonResource, new ProductMetadataGenerator(), "price", "name",
 				"shortDescription", "description", "tags");
 		List<Document> documents = jsonReader.get();
-		SimpleVectorStore vectorStore = new SimpleVectorStore(this.embeddingClient);
+		SimpleVectorStore vectorStore = new SimpleVectorStore(this.embeddingModel);
 		vectorStore.add(documents);
 
 		File tempFile = new File(workingDir.toFile(), "temp.txt");
 		vectorStore.save(tempFile);
 		assertThat(tempFile).isNotEmpty();
 		assertThat(tempFile).content().contains("Velo 99 XR1 AXS");
-		SimpleVectorStore vectorStore2 = new SimpleVectorStore(this.embeddingClient);
+		SimpleVectorStore vectorStore2 = new SimpleVectorStore(this.embeddingModel);
 
 		vectorStore2.load(tempFile);
 		List<Document> similaritySearch = vectorStore2.similaritySearch("Velo 99 XR1 AXS");

models/spring-ai-postgresml/src/main/java/org/springframework/ai/postgresml/PostgresMlEmbeddingModel.java

@@ -24,7 +24,7 @@ import java.util.Map;
 
 import org.springframework.ai.document.Document;
 import org.springframework.ai.document.MetadataMode;
-import org.springframework.ai.embedding.AbstractEmbeddingClient;
+import org.springframework.ai.embedding.AbstractEmbeddingModel;
 import org.springframework.ai.embedding.Embedding;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
@@ -39,12 +39,12 @@ import org.springframework.util.CollectionUtils;
 import org.springframework.util.StringUtils;
 
 /**
- * <a href="https://postgresml.org">PostgresML</a> EmbeddingClient
+ * <a href="https://postgresml.org">PostgresML</a> EmbeddingModel
  *
  * @author Toshiaki Maki
  * @author Christian Tzolov
  */
-public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implements InitializingBean {
+public class PostgresMlEmbeddingModel extends AbstractEmbeddingModel implements InitializingBean {
 
 	public static final String DEFAULT_TRANSFORMER_MODEL = "distilbert-base-uncased";
 
@@ -83,16 +83,16 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
 	 * a constructor
 	 * @param jdbcTemplate JdbcTemplate
 	 */
-	public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate) {
+	public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate) {
 		this(jdbcTemplate, PostgresMlEmbeddingOptions.builder().build());
 	}
 
 	/**
-	 * a PostgresMlEmbeddingClient constructor
+	 * a PostgresMlEmbeddingModel constructor
 	 * @param jdbcTemplate JdbcTemplate to use to interact with the database.
 	 * @param options PostgresMlEmbeddingOptions to configure the client.
 	 */
-	public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, PostgresMlEmbeddingOptions options) {
+	public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, PostgresMlEmbeddingOptions options) {
 		Assert.notNull(jdbcTemplate, "jdbc template must not be null.");
 		Assert.notNull(options, "options must not be null.");
 		Assert.notNull(options.getTransformer(), "transformer must not be null.");
@@ -110,7 +110,7 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
 	 * @param transformer huggingface sentence-transformer name
 	 */
 	@Deprecated(since = "0.8.0", forRemoval = true)
-	public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, String transformer) {
+	public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer) {
 		this(jdbcTemplate, transformer, VectorType.PG_ARRAY);
 	}
 
@@ -122,7 +122,7 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
 	 * @param vectorType vector type in PostgreSQL
 	 */
 	@Deprecated(since = "0.8.0", forRemoval = true)
-	public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType) {
+	public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType) {
 		this(jdbcTemplate, transformer, vectorType, Map.of(), MetadataMode.EMBED);
 	}
 
@@ -135,7 +135,7 @@ public class PostgresMlEmbeddingClient extends AbstractEmbeddingClient implement
 	 * @param kwargs optional arguments
 	 */
 	@Deprecated(since = "0.8.0", forRemoval = true)
-	public PostgresMlEmbeddingClient(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType,
+	public PostgresMlEmbeddingModel(JdbcTemplate jdbcTemplate, String transformer, VectorType vectorType,
 			Map<String, Object> kwargs, MetadataMode metadataMode) {
 		Assert.notNull(jdbcTemplate, "jdbc template must not be null.");
 		Assert.notNull(transformer, "transformer must not be null.");

models/spring-ai-postgresml/src/main/java/org/springframework/ai/postgresml/PostgresMlEmbeddingOptions.java

@@ -24,7 +24,7 @@ import com.fasterxml.jackson.annotation.JsonProperty;
 import org.springframework.ai.document.MetadataMode;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.model.ModelOptionsUtils;
-import org.springframework.ai.postgresml.PostgresMlEmbeddingClient.VectorType;
+import org.springframework.ai.postgresml.PostgresMlEmbeddingModel.VectorType;
 
 /**
  * @author Christian Tzolov
@@ -36,7 +36,7 @@ public class PostgresMlEmbeddingOptions implements EmbeddingOptions {
 	/**
 	 * The Huggingface transformer model to use for the embedding.
 	 */
-	private @JsonProperty("transformer") String transformer = PostgresMlEmbeddingClient.DEFAULT_TRANSFORMER_MODEL;
+	private @JsonProperty("transformer") String transformer = PostgresMlEmbeddingModel.DEFAULT_TRANSFORMER_MODEL;
 
 	/**
 	 * PostgresML vector type to use for the embedding.

models/spring-ai-postgresml/src/test/java/org/springframework/ai/postgresml/PostgresMlEmbeddingModelIT.java

@@ -30,7 +30,7 @@ import org.junit.jupiter.params.provider.ValueSource;
 import org.springframework.ai.embedding.EmbeddingOptions;
 import org.springframework.ai.embedding.EmbeddingRequest;
 import org.springframework.ai.embedding.EmbeddingResponse;
-import org.springframework.ai.postgresml.PostgresMlEmbeddingClient.VectorType;
+import org.springframework.ai.postgresml.PostgresMlEmbeddingModel.VectorType;
 
 import org.testcontainers.containers.PostgreSQLContainer;
 import org.testcontainers.containers.wait.strategy.LogMessageWaitStrategy;
@@ -56,7 +56,7 @@ import static org.assertj.core.api.Assertions.assertThat;
 @AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
 @Testcontainers
 @Disabled("Disabled from automatic execution, as it requires an excessive amount of memory (over 9GB)!")
-class PostgresMlEmbeddingClientIT {
+class PostgresMlEmbeddingModelIT {
 
 	@Container
 	@ServiceConnection
@@ -80,51 +80,51 @@ class PostgresMlEmbeddingClientIT {
 
 	@Test
 	void embed() {
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate);
-		embeddingClient.afterPropertiesSet();
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate);
+		embeddingModel.afterPropertiesSet();
 
-		List<Double> embed = embeddingClient.embed("Hello World!");
+		List<Double> embed = embeddingModel.embed("Hello World!");
 
 		assertThat(embed).hasSize(768);
 	}
 
 	@Test
 	void embedWithPgVector() {
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
 				PostgresMlEmbeddingOptions.builder()
 					.withTransformer("distilbert-base-uncased")
-					.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_VECTOR)
+					.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_VECTOR)
 					.build());
-		embeddingClient.afterPropertiesSet();
+		embeddingModel.afterPropertiesSet();
 
-		List<Double> embed = embeddingClient.embed(new Document("Hello World!"));
+		List<Double> embed = embeddingModel.embed(new Document("Hello World!"));
 
 		assertThat(embed).hasSize(768);
 	}
 
 	@Test
 	void embedWithDifferentModel() {
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
 				PostgresMlEmbeddingOptions.builder().withTransformer("intfloat/e5-small").build());
-		embeddingClient.afterPropertiesSet();
+		embeddingModel.afterPropertiesSet();
 
-		List<Double> embed = embeddingClient.embed(new Document("Hello World!"));
+		List<Double> embed = embeddingModel.embed(new Document("Hello World!"));
 
 		assertThat(embed).hasSize(384);
 	}
 
 	@Test
 	void embedWithKwargs() {
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
 				PostgresMlEmbeddingOptions.builder()
 					.withTransformer("distilbert-base-uncased")
-					.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_ARRAY)
+					.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_ARRAY)
 					.withKwargs(Map.of("device", "cpu"))
 					.withMetadataMode(MetadataMode.EMBED)
 					.build());
-		embeddingClient.afterPropertiesSet();
+		embeddingModel.afterPropertiesSet();
 
-		List<Double> embed = embeddingClient.embed(new Document("Hello World!"));
+		List<Double> embed = embeddingModel.embed(new Document("Hello World!"));
 
 		assertThat(embed).hasSize(768);
 	}
@@ -132,14 +132,14 @@ class PostgresMlEmbeddingClientIT {
 	@ParameterizedTest
 	@ValueSource(strings = { "PG_ARRAY", "PG_VECTOR" })
 	void embedForResponse(String vectorType) {
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
 				PostgresMlEmbeddingOptions.builder()
 					.withTransformer("distilbert-base-uncased")
 					.withVectorType(VectorType.valueOf(vectorType))
 					.build());
-		embeddingClient.afterPropertiesSet();
+		embeddingModel.afterPropertiesSet();
 
-		EmbeddingResponse embeddingResponse = embeddingClient
+		EmbeddingResponse embeddingResponse = embeddingModel
 			.embedForResponse(List.of("Hello World!", "Spring AI!", "LLM!"));
 
 		assertThat(embeddingResponse).isNotNull();
@@ -157,16 +157,16 @@ class PostgresMlEmbeddingClientIT {
 	@Test
 	void embedCallWithRequestOptionsOverride() {
 
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate,
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate,
 				PostgresMlEmbeddingOptions.builder()
 					.withTransformer("distilbert-base-uncased")
 					.withVectorType(VectorType.PG_VECTOR)
 					.build());
-		embeddingClient.afterPropertiesSet();
+		embeddingModel.afterPropertiesSet();
 
 		var request1 = new EmbeddingRequest(List.of("Hello World!", "Spring AI!", "LLM!"), EmbeddingOptions.EMPTY);
 
-		EmbeddingResponse embeddingResponse = embeddingClient.call(request1);
+		EmbeddingResponse embeddingResponse = embeddingModel.call(request1);
 
 		assertThat(embeddingResponse).isNotNull();
 		assertThat(embeddingResponse.getResults()).hasSize(3);
@@ -188,7 +188,7 @@ class PostgresMlEmbeddingClientIT {
 					.withKwargs(Map.of("device", "cpu"))
 					.build());
 
-		embeddingResponse = embeddingClient.call(request2);
+		embeddingResponse = embeddingModel.call(request2);
 
 		assertThat(embeddingResponse).isNotNull();
 		assertThat(embeddingResponse.getResults()).hasSize(3);
@@ -205,11 +205,11 @@ class PostgresMlEmbeddingClientIT {
 
 	@Test
 	void dimensions() {
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(this.jdbcTemplate);
-		embeddingClient.afterPropertiesSet();
-		Assertions.assertThat(embeddingClient.dimensions()).isEqualTo(768);
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(this.jdbcTemplate);
+		embeddingModel.afterPropertiesSet();
+		Assertions.assertThat(embeddingModel.dimensions()).isEqualTo(768);
 		// cached
-		Assertions.assertThat(embeddingClient.dimensions()).isEqualTo(768);
+		Assertions.assertThat(embeddingModel.dimensions()).isEqualTo(768);
 	}
 
 	@SpringBootApplication

models/spring-ai-postgresml/src/test/java/org/springframework/ai/postgresml/PostgresMlEmbeddingOptionsTests.java

@@ -34,8 +34,8 @@ public class PostgresMlEmbeddingOptionsTests {
 	public void defaultOptions() {
 		PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder().build();
 
-		assertThat(options.getTransformer()).isEqualTo(PostgresMlEmbeddingClient.DEFAULT_TRANSFORMER_MODEL);
-		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_ARRAY);
+		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);
 	}
@@ -44,13 +44,13 @@ public class PostgresMlEmbeddingOptionsTests {
 	public void newOptions() {
 		PostgresMlEmbeddingOptions options = PostgresMlEmbeddingOptions.builder()
 			.withTransformer("intfloat/e5-small")
-			.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_VECTOR)
+			.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_VECTOR)
 			.withMetadataMode(org.springframework.ai.document.MetadataMode.ALL)
 			.withKwargs(Map.of("device", "cpu"))
 			.build();
 
 		assertThat(options.getTransformer()).isEqualTo("intfloat/e5-small");
-		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_VECTOR);
+		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_VECTOR);
 		assertThat(options.getKwargs()).isEqualTo(Map.of("device", "cpu"));
 		assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.ALL);
 	}
@@ -59,37 +59,37 @@ public class PostgresMlEmbeddingOptionsTests {
 	public void mergeOptions() {
 
 		var jdbcTemplate = Mockito.mock(JdbcTemplate.class);
-		PostgresMlEmbeddingClient embeddingClient = new PostgresMlEmbeddingClient(jdbcTemplate);
+		PostgresMlEmbeddingModel embeddingModel = new PostgresMlEmbeddingModel(jdbcTemplate);
 
-		PostgresMlEmbeddingOptions options = embeddingClient.mergeOptions(EmbeddingOptions.EMPTY);
+		PostgresMlEmbeddingOptions options = embeddingModel.mergeOptions(EmbeddingOptions.EMPTY);
 
 		// Default options
-		assertThat(options.getTransformer()).isEqualTo(PostgresMlEmbeddingClient.DEFAULT_TRANSFORMER_MODEL);
-		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_ARRAY);
+		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);
 
 		// Partial override
-		options = embeddingClient.mergeOptions(PostgresMlEmbeddingOptions.builder()
+		options = embeddingModel.mergeOptions(PostgresMlEmbeddingOptions.builder()
 			.withTransformer("intfloat/e5-small")
 			.withKwargs(Map.of("device", "cpu"))
 			.build());
 
 		assertThat(options.getTransformer()).isEqualTo("intfloat/e5-small");
-		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_ARRAY); // Default
+		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_ARRAY); // Default
 		assertThat(options.getKwargs()).isEqualTo(Map.of("device", "cpu"));
 		assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.EMBED); // Default
 
 		// Complete override
-		options = embeddingClient.mergeOptions(PostgresMlEmbeddingOptions.builder()
+		options = embeddingModel.mergeOptions(PostgresMlEmbeddingOptions.builder()
 			.withTransformer("intfloat/e5-small")
-			.withVectorType(PostgresMlEmbeddingClient.VectorType.PG_VECTOR)
+			.withVectorType(PostgresMlEmbeddingModel.VectorType.PG_VECTOR)
 			.withMetadataMode(org.springframework.ai.document.MetadataMode.ALL)
 			.withKwargs(Map.of("device", "cpu"))
 			.build());
 
 		assertThat(options.getTransformer()).isEqualTo("intfloat/e5-small");
-		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingClient.VectorType.PG_VECTOR);
+		assertThat(options.getVectorType()).isEqualTo(PostgresMlEmbeddingModel.VectorType.PG_VECTOR);
 		assertThat(options.getKwargs()).isEqualTo(Map.of("device", "cpu"));
 		assertThat(options.getMetadataMode()).isEqualTo(org.springframework.ai.document.MetadataMode.ALL);
 	}

models/spring-ai-stability-ai/src/main/java/org/springframework/ai/stabilityai/StabilityAiImageModel.java

@@ -22,7 +22,7 @@ import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import org.springframework.ai.image.Image;
-import org.springframework.ai.image.ImageClient;
+import org.springframework.ai.image.ImageModel;
 import org.springframework.ai.image.ImageGeneration;
 import org.springframework.ai.image.ImageOptions;
 import org.springframework.ai.image.ImagePrompt;
@@ -34,10 +34,10 @@ import org.springframework.ai.stabilityai.api.StabilityAiImageOptions;
 import org.springframework.util.Assert;
 
 /**
- * StabilityAiImageClient is a class that implements the ImageClient interface. It
- * provides a client for calling the StabilityAI image generation API.
+ * StabilityAiImageModel is a class that implements the ImageModel interface. It provides
+ * a client for calling the StabilityAI image generation API.
  */
-public class StabilityAiImageClient implements ImageClient {
+public class StabilityAiImageModel implements ImageModel {
 
 	private final Logger logger = LoggerFactory.getLogger(getClass());
 
@@ -45,11 +45,11 @@ public class StabilityAiImageClient implements ImageClient {
 
 	private final StabilityAiApi stabilityAiApi;
 
-	public StabilityAiImageClient(StabilityAiApi stabilityAiApi) {
+	public StabilityAiImageModel(StabilityAiApi stabilityAiApi) {
 		this(stabilityAiApi, StabilityAiImageOptions.builder().build());
 	}
 
-	public StabilityAiImageClient(StabilityAiApi stabilityAiApi, StabilityAiImageOptions options) {
+	public StabilityAiImageModel(StabilityAiApi stabilityAiApi, StabilityAiImageOptions options) {
 		Assert.notNull(stabilityAiApi, "StabilityAiApi must not be null");
 		Assert.notNull(options, "StabilityAiImageOptions must not be null");
 		this.stabilityAiApi = stabilityAiApi;
@@ -61,20 +61,20 @@ public class StabilityAiImageClient implements ImageClient {
 	}
 
 	/**
-	 * Calls the StabilityAiImageClient with the given StabilityAiImagePrompt and returns
+	 * Calls the StabilityAiImageModel with the given StabilityAiImagePrompt and returns
 	 * the ImageResponse. This overloaded call method lets you pass the full set of Prompt
 	 * instructions that StabilityAI supports.
 	 * @param imagePrompt the StabilityAiImagePrompt containing the prompt and image model
 	 * options
-	 * @return the ImageResponse generated by the StabilityAiImageClient
+	 * @return the ImageResponse generated by the StabilityAiImageModel
 	 */
 	public ImageResponse call(ImagePrompt imagePrompt) {
 
 		ImageOptions runtimeOptions = imagePrompt.getOptions();
 
-		// Merge the runtime options passed via the prompt with the StabilityAiImageClient
+		// Merge the runtime options passed via the prompt with the StabilityAiImageModel
 		// options configured via Autoconfiguration.
-		// Runtime options overwrite StabilityAiImageClient options
+		// Runtime options overwrite StabilityAiImageModel options
 		StabilityAiImageOptions optionsToUse = ModelOptionsUtils.merge(runtimeOptions, this.options,
 				StabilityAiImageOptions.class);