chatclient

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

@@ -117,7 +117,7 @@ public class AnthropicChatConnector extends
 	 * @param retryTemplate the retry template used to retry the Anthropic API calls.
 	 */
 	public AnthropicChatConnector(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions,
-			RetryTemplate retryTemplate) {
+								  RetryTemplate retryTemplate) {
 		this(anthropicApi, defaultOptions, retryTemplate, null);
 	}
 
@@ -130,7 +130,7 @@ public class AnthropicChatConnector extends
 	 * state of the function calls.
 	 */
 	public AnthropicChatConnector(AnthropicApi anthropicApi, AnthropicChatOptions defaultOptions,
-			RetryTemplate retryTemplate, FunctionCallbackContext functionCallbackContext) {
+								  RetryTemplate retryTemplate, FunctionCallbackContext functionCallbackContext) {
 
 		super(functionCallbackContext);
 
@@ -144,7 +144,7 @@ public class AnthropicChatConnector extends
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		ChatCompletionRequest request = createRequest(prompt, false);
 

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

@@ -76,7 +76,7 @@ class AnthropicChatConnectorIT {
 		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 = chatConnector.execute(prompt);
+		ChatResponse response = chatConnector.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 AnthropicChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.chatConnector.execute(prompt).getResult();
+		Generation generation = this.chatConnector.call(prompt).getResult();
 
 		List<String> list = listOutputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -120,7 +120,7 @@ class AnthropicChatConnectorIT {
 		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 = chatConnector.execute(prompt).getResult();
+		Generation generation = chatConnector.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 AnthropicChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatConnector.execute(prompt).getResult();
+		Generation generation = chatConnector.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = beanOutputConverter.convert(generation.getOutput().getContent());
 		logger.info("" + actorsFilms);
@@ -187,14 +187,14 @@ class AnthropicChatConnectorIT {
 		var userMessage = new UserMessage("Explain what do you see on this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		var response = chatConnector.execute(new Prompt(List.of(userMessage)));
+		var response = chatConnector.call(new Prompt(List.of(userMessage)));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple", "basket");
 	}
 
 	@Test
-	void functionExecuteTest() {
+	void functionCallTest() {
 
 		UserMessage userMessage = new UserMessage(
 				"What's the weather like in San Francisco, Tokyo and Paris? Return the result in Celsius.");
@@ -209,7 +209,7 @@ class AnthropicChatConnectorIT {
 				.build()))
 			.build();
 
-		ChatResponse response = chatConnector.execute(new Prompt(messages, promptOptions));
+		ChatResponse response = chatConnector.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 

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

@@ -107,7 +107,7 @@ public class AzureOpenAiChatConnector
 	}
 
 	public AzureOpenAiChatConnector(OpenAIClient microsoftOpenAiClient, AzureOpenAiChatOptions options,
-			FunctionCallbackContext functionCallbackContext) {
+									FunctionCallbackContext functionCallbackContext) {
 		super(functionCallbackContext);
 		Assert.notNull(microsoftOpenAiClient, "com.azure.ai.openai.OpenAIClient must not be null");
 		Assert.notNull(options, "AzureOpenAiChatOptions must not be null");
@@ -131,7 +131,7 @@ public class AzureOpenAiChatConnector
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		ChatCompletionsOptions options = toAzureChatCompletionsOptions(prompt);
 		options.setStream(false);

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

@@ -69,7 +69,7 @@ class AzureOpenAiChatConnectorIT {
 		UserMessage userMessage = new UserMessage("Generate the names of 5 famous pirates.");
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		ChatResponse response = chatClient.execute(prompt);
+		ChatResponse response = chatClient.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
 
@@ -86,7 +86,7 @@ class AzureOpenAiChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatClient.execute(prompt).getResult();
+		Generation generation = chatClient.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -105,7 +105,7 @@ class AzureOpenAiChatConnectorIT {
 		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.execute(prompt).getResult();
+		Generation generation = chatClient.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 AzureOpenAiChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatClient.execute(prompt).getResult();
+		Generation generation = chatClient.call(prompt).getResult();
 
 		ActorsFilms actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isNotNull();
@@ -145,7 +145,7 @@ class AzureOpenAiChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatClient.execute(prompt).getResult();
+		Generation generation = chatClient.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		System.out.println(actorsFilms);

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

@@ -59,7 +59,7 @@ public class MockAzureOpenAiTestConfiguration {
 	}
 
 	@Bean
-	AzureOpenAiChatConnector azureOpenAiChatClient(OpenAIClient microsoftAzureOpenAiClient) {
+    AzureOpenAiChatConnector azureOpenAiChatClient(OpenAIClient microsoftAzureOpenAiClient) {
 		return new AzureOpenAiChatConnector(microsoftAzureOpenAiClient);
 	}
 

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

@@ -60,7 +60,7 @@ class AzureOpenAiChatConnectorFunctionCallIT {
 	private AzureOpenAiChatConnector chatClient;
 
 	@Test
-	void functionExecuteTest() {
+	void functionCallTest() {
 
 		UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, in Tokyo, and in Paris?");
 
@@ -75,7 +75,7 @@ class AzureOpenAiChatConnectorFunctionCallIT {
 				.build()))
 			.build();
 
-		ChatResponse response = chatClient.execute(new Prompt(messages, promptOptions));
+		ChatResponse response = chatClient.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
@@ -85,7 +85,7 @@ class AzureOpenAiChatConnectorFunctionCallIT {
 	}
 
 	@Test
-	void streamFunctionExecuteTest() {
+	void streamFunctionCallTest() {
 		UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?");
 
 		List<Message> messages = new ArrayList<>(List.of(userMessage));

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

@@ -75,7 +75,7 @@ class AzureOpenAiChatConnectorMetadataTests {
 
 		Prompt prompt = new Prompt("Can I fly like a bird?");
 
-		ChatResponse response = this.aiClient.execute(prompt);
+		ChatResponse response = this.aiClient.call(prompt);
 
 		assertThat(response).isNotNull();
 

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

@@ -61,7 +61,7 @@ public class BedrockAnthropicChatConnector implements ChatConnector, StreamingCh
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		AnthropicChatRequest request = createRequest(prompt);
 

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3ChatConnector.java

@@ -72,7 +72,7 @@ public class BedrockAnthropic3ChatConnector implements ChatConnector, StreamingC
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		AnthropicChatRequest request = createRequest(prompt);
 

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

@@ -58,7 +58,7 @@ public class BedrockCohereChatConnector implements ChatConnector, StreamingChatC
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 		CohereChatResponse response = this.chatApi.chatCompletion(this.createRequest(prompt, false));
 		List<Generation> generations = response.generations().stream().map(g -> {
 			return new Generation(g.text());

models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/jurassic2/BedrockAi21Jurassic2ChatConnector.java

@@ -41,7 +41,7 @@ public class BedrockAi21Jurassic2ChatConnector implements ChatConnector {
 	private final BedrockAi21Jurassic2ChatOptions defaultOptions;
 
 	public BedrockAi21Jurassic2ChatConnector(Ai21Jurassic2ChatBedrockApi chatApi,
-			BedrockAi21Jurassic2ChatOptions options) {
+											 BedrockAi21Jurassic2ChatOptions options) {
 		Assert.notNull(chatApi, "Ai21Jurassic2ChatBedrockApi must not be null");
 		Assert.notNull(options, "BedrockAi21Jurassic2ChatOptions must not be null");
 
@@ -59,7 +59,7 @@ public class BedrockAi21Jurassic2ChatConnector implements ChatConnector {
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 		var request = createRequest(prompt);
 		var response = this.chatApi.chatCompletion(request);
 

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

@@ -62,7 +62,7 @@ public class BedrockLlamaChatConnector implements ChatConnector, StreamingChatCl
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		var request = createRequest(prompt);
 

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

@@ -57,7 +57,7 @@ public class BedrockTitanChatConnector implements ChatConnector, StreamingChatCl
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 		TitanChatResponse response = this.chatApi.chatCompletion(this.createRequest(prompt));
 		List<Generation> generations = response.results().stream().map(result -> {
 			return new Generation(result.outputText());

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

@@ -101,7 +101,7 @@ class BedrockAnthropicChatConnectorIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -119,7 +119,7 @@ class BedrockAnthropicChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputParser.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -137,7 +137,7 @@ class BedrockAnthropicChatConnectorIT {
 		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.execute(prompt).getResult();
+		Generation generation = client.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 BedrockAnthropicChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConvert.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3ChatConnectorIT.java

@@ -105,7 +105,7 @@ class BedrockAnthropic3ChatConnectorIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -123,7 +123,7 @@ class BedrockAnthropic3ChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -142,7 +142,7 @@ class BedrockAnthropic3ChatConnectorIT {
 		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.execute(prompt).getResult();
+		Generation generation = client.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 BedrockAnthropic3ChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -211,7 +211,7 @@ class BedrockAnthropic3ChatConnectorIT {
 		var userMessage = new UserMessage("Explain what do you see o this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		var response = client.execute(new Prompt(List.of(userMessage)));
+		var response = client.call(new Prompt(List.of(userMessage)));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple", "basket");

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

@@ -98,7 +98,7 @@ class BedrockCohereChatConnectorIT {
 		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.execute(prompt);
+		ChatResponse response = client.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
 
@@ -115,7 +115,7 @@ class BedrockCohereChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -134,7 +134,7 @@ class BedrockCohereChatConnectorIT {
 		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.execute(prompt).getResult();
+		Generation generation = client.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 BedrockCohereChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");

models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/jurassic2/BedrockAi21Jurassic2ChatConnectorIT.java

@@ -66,7 +66,7 @@ class BedrockAi21Jurassic2ChatConnectorIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -83,7 +83,7 @@ class BedrockAi21Jurassic2ChatConnectorIT {
 		UserMessage userMessage = new UserMessage("Can you express happiness using an emoji like 😄 ?");
 		Prompt prompt = new Prompt(List.of(userMessage), options);
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).matches(content -> content.contains("😄"));
 	}
@@ -103,7 +103,7 @@ class BedrockAi21Jurassic2ChatConnectorIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage), options);
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).doesNotContain("😄");
 	}
@@ -120,7 +120,7 @@ class BedrockAi21Jurassic2ChatConnectorIT {
 		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.execute(prompt).getResult();
+		Generation generation = client.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 BedrockAi21Jurassic2ChatConnectorIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("AI");
 	}

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

@@ -98,7 +98,7 @@ class BedrockLlamaChatConnectorIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
@@ -116,7 +116,7 @@ class BedrockLlamaChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -134,7 +134,7 @@ class BedrockLlamaChatConnectorIT {
 		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.execute(prompt).getResult();
+		Generation generation = client.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 BedrockLlamaChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");

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

@@ -99,7 +99,7 @@ class BedrockTitanChatConnectorIT {
 		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.execute(prompt);
+		ChatResponse response = client.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
 
@@ -117,7 +117,7 @@ class BedrockTitanChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -138,7 +138,7 @@ class BedrockTitanChatConnectorIT {
 				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.execute(prompt).getResult();
+		Generation generation = client.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 BedrockTitanChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");

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

@@ -86,7 +86,7 @@ public class HuggingfaceChatConnector implements ChatConnector {
 	 * @return ChatResponse containing the generated text and other related details.
 	 */
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 		GenerateRequest generateRequest = new GenerateRequest();
 		generateRequest.setInputs(prompt.getContents());
 		GenerateParameters generateParameters = new GenerateParameters();

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

@@ -46,7 +46,7 @@ public class ClientIT {
 				[/INST]
 				 """;
 		Prompt prompt = new Prompt(mistral7bInstruct);
-		ChatResponse chatResponse = huggingfaceChatClient.execute(prompt);
+		ChatResponse chatResponse = huggingfaceChatClient.call(prompt);
 		assertThat(chatResponse.getResult().getOutput().getContent()).isNotEmpty();
 		String expectedResponse = """
 				```json

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

@@ -83,7 +83,7 @@ public class MistralAiChatConnector extends
 	}
 
 	public MistralAiChatConnector(MistralAiApi mistralAiApi, MistralAiChatOptions options,
-			FunctionCallbackContext functionCallbackContext, RetryTemplate retryTemplate) {
+								  FunctionCallbackContext functionCallbackContext, RetryTemplate retryTemplate) {
 		super(functionCallbackContext);
 		Assert.notNull(mistralAiApi, "MistralAiApi must not be null");
 		Assert.notNull(options, "Options must not be null");
@@ -94,7 +94,7 @@ public class MistralAiChatConnector extends
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 		var request = createRequest(prompt, false);
 
 		return retryTemplate.execute(ctx -> {

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

@@ -25,9 +25,9 @@ import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
+import org.springframework.ai.chat.connector.ChatConnector;
 import reactor.core.publisher.Flux;
 
-import org.springframework.ai.chat.connector.ChatConnector;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
 import org.springframework.ai.chat.StreamingChatClient;
@@ -90,7 +90,7 @@ class MistralAiChatConnectorIT {
 		// 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 = chatConnector.execute(prompt);
+		ChatResponse response = chatConnector.call(prompt);
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getResults().get(0).getOutput().getContent()).contains("Blackbeard");
 	}
@@ -108,7 +108,7 @@ class MistralAiChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.chatConnector.execute(prompt).getResult();
+		Generation generation = this.chatConnector.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -126,7 +126,7 @@ class MistralAiChatConnectorIT {
 		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 = chatConnector.execute(prompt).getResult();
+		Generation generation = chatConnector.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 MistralAiChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatConnector.execute(prompt).getResult();
+		Generation generation = chatConnector.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		logger.info("" + actorsFilms);
@@ -186,7 +186,7 @@ class MistralAiChatConnectorIT {
 	}
 
 	@Test
-	void functionExecuteTest() {
+	void functionCallTest() {
 
 		UserMessage userMessage = new UserMessage("What's the weather like in San Francisco?");
 
@@ -201,7 +201,7 @@ class MistralAiChatConnectorIT {
 				.build()))
 			.build();
 
-		ChatResponse response = chatConnector.execute(new Prompt(messages, promptOptions));
+		ChatResponse response = chatConnector.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
@@ -209,7 +209,7 @@ class MistralAiChatConnectorIT {
 	}
 
 	@Test
-	void streamFunctionExecuteTest() {
+	void streamFunctionCallTest() {
 
 		UserMessage userMessage = new UserMessage("What's the weather like in Tokyo, Japan?");
 

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

@@ -118,7 +118,7 @@ public class MistralAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedChatCompletion)));
 
-		var result = chatClient.execute(new Prompt("text"));
+		var result = chatClient.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.execute(new Prompt("text")));
+		assertThrows(RuntimeException.class, () -> chatClient.call(new Prompt("text")));
 	}
 
 	@Test

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

@@ -18,10 +18,10 @@ package org.springframework.ai.ollama;
 import java.util.Base64;
 import java.util.List;
 
+import org.springframework.ai.chat.connector.ChatConnector;
 import org.springframework.ai.ollama.metadata.OllamaChatResponseMetadata;
 import reactor.core.publisher.Flux;
 
-import org.springframework.ai.chat.connector.ChatConnector;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
 import org.springframework.ai.chat.StreamingChatClient;
@@ -94,7 +94,7 @@ public class OllamaChatConnector implements ChatConnector, StreamingChatClient {
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		OllamaApi.ChatResponse response = this.chatApi.chat(ollamaChatRequest(prompt, false));
 

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

@@ -95,13 +95,13 @@ class OllamaChatConnectorIT {
 
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage), portableOptions);
 
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 
 		// ollama specific options
 		var ollamaOptions = new OllamaOptions().withLowVRAM(true);
 
-		response = client.execute(new Prompt(List.of(userMessage, systemMessage), ollamaOptions));
+		response = client.call(new Prompt(List.of(userMessage, systemMessage), ollamaOptions));
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 
 	}
@@ -109,7 +109,7 @@ class OllamaChatConnectorIT {
 	@Test
 	void usageTest() {
 		Prompt prompt = new Prompt("Tell me a joke");
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 		Usage usage = response.getMetadata().getUsage();
 
 		assertThat(usage).isNotNull();
@@ -131,7 +131,7 @@ class OllamaChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -151,7 +151,7 @@ class OllamaChatConnectorIT {
 				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.execute(prompt).getResult();
+		Generation generation = client.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 OllamaChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");

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

@@ -75,7 +75,7 @@ class OllamaChatConnectorMultimodalIT {
 		var userMessage = new UserMessage("Explain what do you see on this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
-		var response = client.execute(new Prompt(List.of(userMessage)));
+		var response = client.call(new Prompt(List.of(userMessage)));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple", "basket");

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

@@ -123,7 +123,7 @@ public class OpenAiChatConnector extends
 	 * @param retryTemplate The retry template.
 	 */
 	public OpenAiChatConnector(OpenAiApi openAiApi, OpenAiChatOptions options,
-			FunctionCallbackContext functionCallbackContext, RetryTemplate retryTemplate) {
+							   FunctionCallbackContext functionCallbackContext, RetryTemplate retryTemplate) {
 		super(functionCallbackContext);
 		Assert.notNull(openAiApi, "OpenAiApi must not be null");
 		Assert.notNull(options, "Options must not be null");
@@ -134,7 +134,7 @@ public class OpenAiChatConnector extends
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		ChatCompletionRequest request = createRequest(prompt, false);
 

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

@@ -8,7 +8,7 @@ import org.springframework.context.annotation.Configuration;
 
 import java.util.Map;
 
-class ChatClientTest {
+class ChatConnectorTest {
 
 	@Configuration
 	static class ChatClientTestConfiguration {
@@ -28,7 +28,7 @@ class ChatClientTest {
 
 	private final ChatClient singularity;
 
-	ChatClientTest(@Autowired ChatClient singularity) {
+	ChatConnectorTest(@Autowired ChatClient singularity) {
 		this.singularity = singularity;
 	}
 

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

@@ -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.execute(prompt);
+		ChatResponse response = chatClient.call(prompt);
 
 		evaluateQuestionAndAnswer(userQuery, response, true);
 	}

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

@@ -74,7 +74,7 @@ public class OpenAiChatClientWithChatResponseMetadataTests {
 
 		Prompt prompt = new Prompt("Reach for the sky.");
 
-		ChatResponse response = this.openAiChatClient.execute(prompt);
+		ChatResponse response = this.openAiChatClient.call(prompt);
 
 		assertThat(response).isNotNull();
 

models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatConnector2IT.java

@@ -67,7 +67,7 @@ public class OpenAiChatConnector2IT {
 					.withResponseFormat(new ChatCompletionRequest.ResponseFormat("json_object"))
 					.build());
 
-		ChatResponse response = this.openAiChatClient.execute(prompt);
+		ChatResponse response = this.openAiChatClient.call(prompt);
 
 		assertThat(response).isNotNull();
 

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

@@ -74,7 +74,7 @@ class OpenAiChatConnectorIT 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 = chatConnector.execute(prompt);
+		ChatResponse response = chatConnector.call(prompt);
 		assertThat(response.getResults()).hasSize(1);
 		assertThat(response.getResults().get(0).getOutput().getContent()).contains("Blackbeard");
 		// needs fine tuning... evaluateQuestionAndAnswer(request, response, false);
@@ -93,7 +93,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.chatConnector.execute(prompt).getResult();
+		Generation generation = this.chatConnector.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -112,7 +112,7 @@ class OpenAiChatConnectorIT 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 = chatConnector.execute(prompt).getResult();
+		Generation generation = chatConnector.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));
@@ -131,7 +131,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatConnector.execute(prompt).getResult();
+		Generation generation = chatConnector.call(prompt).getResult();
 
 		ActorsFilms actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 	}
@@ -151,7 +151,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = chatConnector.execute(prompt).getResult();
+		Generation generation = chatConnector.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		logger.info("" + actorsFilms);
@@ -189,7 +189,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 	}
 
 	@Test
-	void functionExecuteTest() {
+	void functionCallTest() {
 
 		UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?");
 
@@ -204,7 +204,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 				.build()))
 			.build();
 
-		ChatResponse response = chatConnector.execute(new Prompt(messages, promptOptions));
+		ChatResponse response = chatConnector.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
@@ -214,7 +214,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 	}
 
 	@Test
-	void streamFunctionExecuteTest() {
+	void streamFunctionCallTest() {
 
 		UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?");
 
@@ -256,7 +256,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, imageData)));
 
 		var response = chatConnector
-			.execute(new Prompt(List.of(userMessage), OpenAiChatOptions.builder().withModel(modelName).build()));
+			.call(new Prompt(List.of(userMessage), OpenAiChatOptions.builder().withModel(modelName).build()));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple");
@@ -272,7 +272,7 @@ class OpenAiChatConnectorIT extends AbstractIT {
 					new URL("https://docs.spring.io/spring-ai/reference/1.0-SNAPSHOT/_images/multimodal.test.png"))));
 
 		ChatResponse response = chatConnector
-			.execute(new Prompt(List.of(userMessage), OpenAiChatOptions.builder().withModel(modelName).build()));
+			.call(new Prompt(List.of(userMessage), OpenAiChatOptions.builder().withModel(modelName).build()));
 
 		logger.info(response.getResult().getOutput().getContent());
 		assertThat(response.getResult().getOutput().getContent()).contains("bananas", "apple");

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

@@ -23,20 +23,14 @@ import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.extension.ExtendWith;
 import org.mockito.Mock;
 import org.mockito.junit.jupiter.MockitoExtension;
+import org.springframework.ai.openai.*;
 import reactor.core.publisher.Flux;
 
 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.OpenAiAudioTranscriptionOptions;
 import org.springframework.ai.openai.OpenAiChatConnector;
-import org.springframework.ai.openai.OpenAiChatOptions;
-import org.springframework.ai.openai.OpenAiEmbeddingClient;
-import org.springframework.ai.openai.OpenAiEmbeddingOptions;
-import org.springframework.ai.openai.OpenAiImageClient;
-import org.springframework.ai.openai.OpenAiImageOptions;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.openai.api.OpenAiApi.ChatCompletion;
 import org.springframework.ai.openai.api.OpenAiApi.ChatCompletionChunk;
@@ -146,7 +140,7 @@ public class OpenAiRetryTests {
 			.thenThrow(new TransientAiException("Transient Error 2"))
 			.thenReturn(ResponseEntity.of(Optional.of(expectedChatCompletion)));
 
-		var result = chatClient.execute(new Prompt("text"));
+		var result = chatClient.call(new Prompt("text"));
 
 		assertThat(result).isNotNull();
 		assertThat(result.getResult().getOutput().getContent()).isSameAs("Response");
@@ -158,7 +152,7 @@ public class OpenAiRetryTests {
 	public void openAiChatNonTransientError() {
 		when(openAiApi.chatCompletionEntity(isA(ChatCompletionRequest.class)))
 				.thenThrow(new RuntimeException("Non Transient Error"));
-		assertThrows(RuntimeException.class, () -> chatClient.execute(new Prompt("text")));
+		assertThrows(RuntimeException.class, () -> chatClient.call(new Prompt("text")));
 	}
 
 	@Test

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

@@ -99,7 +99,7 @@ public class ChatMemoryLongTermSystemPromptIT extends BaseMemoryTest {
 
 		@Bean
 		public ChatService memoryChatService(OpenAiChatConnector chatClient, VectorStore vectorStore,
-				TokenCountEstimator tokenCountEstimator) {
+                                             TokenCountEstimator tokenCountEstimator) {
 
 			return PromptTransformingChatService.builder(chatClient)
 				.withRetrievers(List.of(new VectorStoreChatMemoryRetriever(vectorStore, 10)))
@@ -111,7 +111,7 @@ public class ChatMemoryLongTermSystemPromptIT extends BaseMemoryTest {
 
 		@Bean
 		public StreamingChatService memoryStreamingChatService(OpenAiChatConnector streamingChatClient,
-				VectorStore vectorStore, TokenCountEstimator tokenCountEstimator) {
+                                                               VectorStore vectorStore, TokenCountEstimator tokenCountEstimator) {
 
 			return StreamingPromptTransformingChatService.builder(streamingChatClient)
 				.withRetrievers(List.of(new VectorStoreChatMemoryRetriever(vectorStore, 10)))

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

@@ -75,7 +75,7 @@ public class ChatMemoryShortTermMessageListIT extends BaseMemoryTest {
 
 		@Bean
 		public ChatService memoryChatService(OpenAiChatConnector chatClient, ChatMemory chatHistory,
-				TokenCountEstimator tokenCountEstimator) {
+                                             TokenCountEstimator tokenCountEstimator) {
 
 			return PromptTransformingChatService.builder(chatClient)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))
@@ -87,7 +87,7 @@ public class ChatMemoryShortTermMessageListIT extends BaseMemoryTest {
 
 		@Bean
 		public StreamingChatService memoryStreamingChatService(OpenAiChatConnector streamingChatClient,
-				ChatMemory chatHistory, TokenCountEstimator tokenCountEstimator) {
+                                                               ChatMemory chatHistory, TokenCountEstimator tokenCountEstimator) {
 
 			return StreamingPromptTransformingChatService.builder(streamingChatClient)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))

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

@@ -76,7 +76,7 @@ public class ChatMemoryShortTermSystemPromptIT extends BaseMemoryTest {
 
 		@Bean
 		public ChatService memoryChatService(OpenAiChatConnector chatClient, ChatMemory chatHistory,
-				TokenCountEstimator tokenCountEstimator) {
+                                             TokenCountEstimator tokenCountEstimator) {
 
 			return PromptTransformingChatService.builder(chatClient)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))
@@ -88,7 +88,7 @@ public class ChatMemoryShortTermSystemPromptIT extends BaseMemoryTest {
 
 		@Bean
 		public StreamingChatService memoryStreamingChatService(OpenAiChatConnector streamingChatClient,
-				ChatMemory chatHistory, TokenCountEstimator tokenCountEstimator) {
+                                                               ChatMemory chatHistory, TokenCountEstimator tokenCountEstimator) {
 
 			return StreamingPromptTransformingChatService.builder(streamingChatClient)
 				.withRetrievers(List.of(new ChatMemoryRetriever(chatHistory)))

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

@@ -29,6 +29,7 @@ import org.slf4j.LoggerFactory;
 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.OpenAiChatConnector;
 import org.springframework.ai.openai.OpenAiChatOptions;
 import org.testcontainers.junit.jupiter.Container;
 import org.testcontainers.junit.jupiter.Testcontainers;
@@ -52,7 +53,6 @@ import org.springframework.ai.document.DocumentTransformer;
 import org.springframework.ai.embedding.EmbeddingClient;
 import org.springframework.ai.evaluation.EvaluationResponse;
 import org.springframework.ai.evaluation.RelevancyEvaluator;
-import org.springframework.ai.openai.OpenAiChatConnector;
 import org.springframework.ai.openai.OpenAiEmbeddingClient;
 import org.springframework.ai.openai.api.OpenAiApi;
 import org.springframework.ai.reader.JsonReader;
@@ -187,7 +187,7 @@ public class LongShortTermChatMemoryWithRagIT {
 
 		@Bean
 		public ChatService memoryChatService(OpenAiChatConnector chatClient, VectorStore vectorStore,
-				TokenCountEstimator tokenCountEstimator, ChatMemory chatHistory) {
+                                             TokenCountEstimator tokenCountEstimator, ChatMemory chatHistory) {
 
 			return PromptTransformingChatService.builder(chatClient)
 				.withRetrievers(List.of(new VectorStoreRetriever(vectorStore, SearchRequest.defaults()),

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

@@ -82,7 +82,7 @@ public class OpenAiPromptTransformingChatServiceIT {
 
 	@Autowired
 	public OpenAiPromptTransformingChatServiceIT(ChatConnector chatConnector, ChatService chatService,
-			VectorStore vectorStore) {
+                                                 VectorStore vectorStore) {
 		this.chatConnector = chatConnector;
 		this.chatService = chatService;
 		this.vectorStore = vectorStore;

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

@@ -85,12 +85,12 @@ public abstract class AbstractIT {
 		}
 		Message userMessage = userPromptTemplate.createMessage();
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		String yesOrNo = chatConnector.execute(prompt).getResult().getOutput().getContent();
+		String yesOrNo = chatConnector.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 = chatConnector.execute(prompt).getResult().getOutput().getContent();
+			String reasonForFailure = chatConnector.call(prompt).getResult().getOutput().getContent();
 			fail(reasonForFailure);
 		}
 		else {

models/spring-ai-vertex-ai-gemini/src/main/java/org/springframework/ai/vertexai/gemini/VertexAiGeminiChatConnector.java

@@ -130,7 +130,7 @@ public class VertexAiGeminiChatConnector
 	}
 
 	public VertexAiGeminiChatConnector(VertexAI vertexAI, VertexAiGeminiChatOptions options,
-			FunctionCallbackContext functionCallbackContext) {
+									   FunctionCallbackContext functionCallbackContext) {
 
 		super(functionCallbackContext);
 
@@ -145,7 +145,7 @@ public class VertexAiGeminiChatConnector
 
 	// https://cloud.google.com/vertex-ai/docs/generative-ai/model-reference/gemini
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		var geminiRequest = createGeminiRequest(prompt);
 

models/spring-ai-vertex-ai-gemini/src/test/java/org/springframework/ai/vertexai/gemini/VertexAiGeminiChatConnectorIT.java

@@ -70,7 +70,7 @@ class VertexAiGeminiChatConnectorIT {
 		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.execute(prompt);
+		ChatResponse response = client.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 	}
 
@@ -87,7 +87,7 @@ class VertexAiGeminiChatConnectorIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputParser.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -106,7 +106,7 @@ class VertexAiGeminiChatConnectorIT {
 		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.execute(prompt).getResult();
+		Generation generation = client.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));
@@ -129,7 +129,7 @@ class VertexAiGeminiChatConnectorIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConvert.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");
@@ -191,7 +191,7 @@ class VertexAiGeminiChatConnectorIT {
 		var userMessage = new UserMessage("Explain what do you see o this picture?",
 				List.of(new Media(MimeTypeUtils.IMAGE_PNG, data)));
 
-		var response = client.execute(new Prompt(List.of(userMessage)));
+		var response = client.call(new Prompt(List.of(userMessage)));
 
 		// Response should contain something like:
 		// I see a bunch of bananas in a golden basket. The bananas are ripe and yellow.

models/spring-ai-vertex-ai-gemini/src/test/java/org/springframework/ai/vertexai/gemini/function/VertexAiGeminiChatConnectorFunctionCallingIT.java

@@ -68,7 +68,7 @@ public class VertexAiGeminiChatConnectorFunctionCallingIT {
 
 	@Test
 	// @Disabled("Google Vertex AI degraded support for parallel function calls")
-	public void functionExecuteExplicitOpenApiSchema() {
+	public void functionCallExplicitOpenApiSchema() {
 
 		UserMessage userMessage = new UserMessage(
 				"What's the weather like in San Francisco, in Paris and in Tokyo, Japan?"
@@ -106,7 +106,7 @@ public class VertexAiGeminiChatConnectorFunctionCallingIT {
 				.build()))
 			.build();
 
-		ChatResponse response = vertexGeminiClient.execute(new Prompt(messages, promptOptions));
+		ChatResponse response = vertexGeminiClient.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
@@ -118,7 +118,7 @@ public class VertexAiGeminiChatConnectorFunctionCallingIT {
 	}
 
 	@Test
-	public void functionExecuteTestInferredOpenApiSchema() {
+	public void functionCallTestInferredOpenApiSchema() {
 
 		UserMessage userMessage = new UserMessage("What's the weather like in Paris? Use Celsius units.");
 
@@ -141,14 +141,14 @@ public class VertexAiGeminiChatConnectorFunctionCallingIT {
 						.build()))
 			.build();
 
-		ChatResponse response = vertexGeminiClient.execute(new Prompt(messages, promptOptions));
+		ChatResponse response = vertexGeminiClient.call(new Prompt(messages, promptOptions));
 
 		logger.info("Response: {}", response);
 
 		assertThat(response.getResult().getOutput().getContent()).containsAnyOf("15.0", "15");
 
 		ChatResponse response2 = vertexGeminiClient
-			.execute(new Prompt("What is the payment status for transaction 696?", promptOptions));
+			.call(new Prompt("What is the payment status for transaction 696?", promptOptions));
 
 		logger.info("Response: {}", response2);
 
@@ -157,7 +157,7 @@ public class VertexAiGeminiChatConnectorFunctionCallingIT {
 	}
 
 	@Test
-	public void functionExecuteTestInferredOpenApiSchemaStream() {
+	public void functionCallTestInferredOpenApiSchemaStream() {
 
 		UserMessage userMessage = new UserMessage("What's the weather like in San Francisco in Celsius units?");
 		// UserMessage userMessage = new UserMessage(

models/spring-ai-vertex-ai-palm2/src/main/java/org/springframework/ai/vertexai/palm2/VertexAiPaLm2ChatConnector.java

@@ -55,7 +55,7 @@ public class VertexAiPaLm2ChatConnector implements ChatConnector {
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		GenerateMessageRequest request = createRequest(prompt);
 

models/spring-ai-vertex-ai-palm2/src/test/java/org/springframework/ai/vertexai/palm2/VertexAiPaLm2ChatGenerationClientIT.java

@@ -62,7 +62,7 @@ class VertexAiPaLm2ChatGenerationClientIT {
 		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.execute(prompt);
+		ChatResponse response = client.call(prompt);
 		assertThat(response.getResult().getOutput().getContent()).contains("Bartholomew");
 	}
 
@@ -79,7 +79,7 @@ class VertexAiPaLm2ChatGenerationClientIT {
 		PromptTemplate promptTemplate = new PromptTemplate(template,
 				Map.of("subject", "ice cream flavors.", "format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = this.client.execute(prompt).getResult();
+		Generation generation = this.client.call(prompt).getResult();
 
 		List<String> list = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(list).hasSize(5);
@@ -98,7 +98,7 @@ class VertexAiPaLm2ChatGenerationClientIT {
 		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.execute(prompt).getResult();
+		Generation generation = client.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));
@@ -120,7 +120,7 @@ class VertexAiPaLm2ChatGenerationClientIT {
 				""";
 		PromptTemplate promptTemplate = new PromptTemplate(template, Map.of("format", format));
 		Prompt prompt = new Prompt(promptTemplate.createMessage());
-		Generation generation = client.execute(prompt).getResult();
+		Generation generation = client.call(prompt).getResult();
 
 		ActorsFilmsRecord actorsFilms = outputConverter.convert(generation.getOutput().getContent());
 		assertThat(actorsFilms.actor()).isEqualTo("Tom Hanks");

models/spring-ai-watsonx-ai/src/main/java/org/springframework/ai/watsonx/WatsonxAiChatConnector.java

@@ -18,9 +18,9 @@ package org.springframework.ai.watsonx;
 import java.util.List;
 import java.util.Map;
 
+import org.springframework.ai.chat.connector.ChatConnector;
 import reactor.core.publisher.Flux;
 
-import org.springframework.ai.chat.connector.ChatConnector;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
 import org.springframework.ai.chat.StreamingChatClient;
@@ -76,7 +76,7 @@ public class WatsonxAiChatConnector implements ChatConnector, StreamingChatClien
 	}
 
 	@Override
-	public ChatResponse execute(Prompt prompt) {
+	public ChatResponse call(Prompt prompt) {
 
 		WatsonxAiRequest request = request(prompt);
 

models/spring-ai-watsonx-ai/src/test/java/org/springframework/ai/watsonx/WatsonxAiChatConnectorTest.java

@@ -155,7 +155,7 @@ public class WatsonxAiChatConnectorTest {
 	}
 
 	@Test
-	public void testExecuteMethod() {
+	public void testCallMethod() {
 		WatsonxAiApi mockChatApi = mock(WatsonxAiApi.class);
 		WatsonxAiChatConnector client = new WatsonxAiChatConnector(mockChatApi);
 
@@ -177,7 +177,7 @@ public class WatsonxAiChatConnectorTest {
 					Map.of("warnings", List.of(Map.of("message", "the message", "id", "disclaimer_warning")))));
 
 		ChatResponse expectedResponse = new ChatResponse(List.of(expectedGenerator));
-		ChatResponse response = client.execute(prompt);
+		ChatResponse response = client.call(prompt);
 
 		Assert.assertEquals(expectedResponse.getResults().size(), response.getResults().size());
 		Assert.assertEquals(expectedResponse.getResult().getOutput(), response.getResult().getOutput());

spring-ai-core/src/main/java/org/springframework/ai/chat/ChatClient.java

@@ -2,16 +2,28 @@ package org.springframework.ai.chat;
 
 import org.springframework.ai.chat.connector.ChatConnector;
 import org.springframework.ai.chat.messages.Media;
+import org.springframework.ai.chat.messages.Message;
+import org.springframework.ai.chat.prompt.ChatOptions;
+import org.springframework.ai.chat.prompt.Prompt;
 import org.springframework.core.ParameterizedTypeReference;
+import org.springframework.core.io.Resource;
+import org.springframework.util.MimeType;
+import reactor.core.publisher.Flux;
 
+import java.net.URL;
 import java.util.*;
+import java.util.function.Consumer;
 
 
 /**
+ * todo follow WebClient -> DefaultWebClient
+ * todo make sure ChatConnector also supports call(Prompt) and then mark as deprecated
+ *
  * @author Mark Pollack
- * @author Christian Tsolov
+ * @author Christian Tzolov
  * @author Josh Long
  */
+
 public class ChatClient {
 
 	private final ChatConnector connector;
@@ -23,7 +35,7 @@ public class ChatClient {
 	private final List<Media> media;
 
 	public ChatClient(ChatConnector connector, String defaultSystemPrompt, String defaultUserPrompt,
-			List<String> defaultFunctions, List<Media> defaultMedia) {
+					  List<String> defaultFunctions, List<Media> defaultMedia) {
 		this.connector = connector;
 		this.userPrompt = defaultUserPrompt;
 		this.systemPrompt = defaultSystemPrompt;
@@ -36,14 +48,41 @@ public class ChatClient {
 		return new ChatClientRequest(this.userPrompt, this.systemPrompt, this.functions, this.media);
 	}
 
-	public ChatClientRequest userPrompt(String userPrompt, Map<String, String> params) {
-		var ccr = new ChatClientRequest(userPrompt, this.systemPrompt, this.functions, this.media);
-		ccr.userPromptParams(params);
-		return ccr;
+	public ChatResponse call(Prompt prompt) {
+		return null;
 	}
 
-	public ChatClientRequest userPrompt(String userPrompt) {
-		return new ChatClientRequest(userPrompt, this.systemPrompt, this.functions, this.media);
+	public static class UserSpec {
+
+
+		public UserSpec media(List<Media> media) {
+			return this;
+		}
+
+		public UserSpec media(URL url, MimeType mimeType) {
+			return this;
+		}
+
+		public UserSpec media(Resource resource, MimeType type) {
+			return this;
+		}
+
+		public UserSpec media(Media... m) {
+			return this;
+		}
+
+		public UserSpec params(Map<String, Object> p) {
+			return this;
+		}
+
+		public UserSpec param(String k, String v) {
+			return this;
+		}
+	}
+
+
+	public ChatClientRequest user(Consumer<UserSpec> consumer) {
+		return null;
 	}
 
 	public static class ChatClientRequest {
@@ -60,15 +99,15 @@ public class ChatClient {
 
 		private final Map<String, String> systemPromptParams = new HashMap<>();
 
-		List<Media> media() {
+		List<Media> userMedia() {
 			return this.media;
 		}
 
-		String systemPrompt() {
+		String systemText() {
 			return this.systemPrompt;
 		}
 
-		String userPrompt() {
+		String userText() {
 			return this.userPrompt;
 		}
 
@@ -83,53 +122,119 @@ public class ChatClient {
 			this.media.addAll(media);
 		}
 
-		public ChatClientRequest userPromptParam(String key, String value) {
-			this.userPromptParams.put(key, value);
-			return this;
+		public ChatClientRequest messages(Message... messages) {
+			return null;
 		}
+//
+//		public ChatClientRequest userParam(String key, String value) {
+//			this.userPromptParams.put(key, value);
+//			return this;
+//		}
+//
+//		public ChatClientRequest systemParam(String key, String value) {
+//			this.systemPromptParams.put(key, value);
+//			return this;
+//		}
 
-		public ChatClientRequest systemPromptParam(String key, String value) {
-			this.systemPromptParams.put(key, value);
+		public <T extends ChatOptions> ChatClientRequest options(T options) {
 			return this;
 		}
+//
+//		public ChatClientRequest systemParams(Map<String, String> systemPromptParams) {
+//			this.systemPromptParams.putAll(systemPromptParams);
+//			return this;
+//		}
+//
+//		public ChatClientRequest userParams(Map<String, String> userPromptParams) {
+//			this.userPromptParams.putAll(userPromptParams);
+//			return this;
+//		}
+//
+//		public ChatClientRequest userText(Resource resource) {
+//			return userText(resource, Charset.defaultCharset());
+//		}
 
-		public ChatClientRequest systemPromptParams(Map<String, String> systemPromptParams) {
-			this.systemPromptParams.putAll(systemPromptParams);
-			return this;
-		}
-
-		public ChatClientRequest userPromptParams(Map<String, String> userPromptParams) {
-			this.userPromptParams.putAll(userPromptParams);
-			return this;
-		}
-
-		public ChatClientRequest userPrompt(String userPrompt) {
-			this.userPrompt = userPrompt;
-			return this;
-		}
-
-		public ChatClientRequest systemPrompt(String systemPrompt) {
-			this.systemPrompt = systemPrompt;
-			return this;
-		}
-
-		public ChatClientRequest media(Media... media) {
-			this.media.addAll(Arrays.asList(media));
-			return this;
-		}
+//		public ChatClientRequest userText(Resource resource, Charset charset) {
+//			try {
+//				this.userText(resource.getContentAsString(charset));
+//			} catch (IOException e) {
+//				throw new RuntimeException(e);
+//			}
+//			return this;
+//		}
+//
+//
+//		public ChatClientRequest userText(String userPrompt) {
+//			this.userPrompt = userPrompt;
+//			return this;
+//		}
+//
+//		public ChatClientRequest systemText(Resource systemPrompt) {
+//			return systemText(systemPrompt, Charset.defaultCharset());
+//		}
+//
+//		public ChatClientRequest systemText(Resource systemPrompt, Charset charset) {
+//			try {
+//				this.systemText(systemPrompt.getContentAsString(charset));
+//			} catch (IOException e) {
+//				throw new RuntimeException(e);
+//			}
+//			return this;
+//		}
+//
+//		public ChatClientRequest systemText(String systemPrompt) {
+//			this.systemPrompt = systemPrompt;
+//			return this;
+//		}
+//
+//		public ChatClientRequest userMedia(Media... media) {
+//			this.media.addAll(Arrays.asList(media));
+//			return this;
+//		}
 
 		public ChatClientRequest functions(String... functions) {
 			this.functions.addAll(Arrays.asList(functions));
 			return this;
 		}
 
-		public <T> T chat(Class<T> clzz) {
+
+		public static class ChatResponseSpec {
+
+			public <T> T single(ParameterizedTypeReference<T> t) {
+				return null;
+			}
+
+
+			public <T> T single(Class<T> clzz) {
+				return null;
+			}
+
+			public ChatResponse chatResponse() {
+				return null;
+			}
+
+			public <T> Flux<T> stream(Class<T> t) {
+				return null;
+			}
+
+			public <T> Flux<T> stream(ParameterizedTypeReference<T> t) {
+				return Flux.empty();
+			}
+
+			public <T> Collection<T> list(Class<T> clzz) {
+				return null;
+			}
+
+			public <T> Collection<T> list(ParameterizedTypeReference<Collection<T>> ptr) {
+				return List.of();
+			}
+
+		}
+
+		public ChatResponseSpec chat() {
 			return null;
 		}
 
-		public <T> T chat(ParameterizedTypeReference<T> clzz) {
-			return null;
-		}
 
 	}
 

spring-ai-core/src/main/java/org/springframework/ai/chat/DefaultChatClient.java

@@ -0,0 +1,57 @@
+package org.springframework.ai.chat;
+
+
+import org.springframework.ai.chat.connector.ChatConnector;
+import org.springframework.ai.chat.messages.Media;
+import org.springframework.ai.chat.prompt.Prompt;
+
+import java.util.List;
+import java.util.function.Consumer;
+
+public class DefaultChatClient implements ChatClient {
+
+    private final ChatConnector connector;
+
+    private final String userPrompt, systemPrompt;
+
+    private final List<String> functions;
+
+    private final List<Media> media;
+
+    public DefaultChatClient(ChatConnector connector, String defaultSystemPrompt, String defaultUserPrompt,
+                             List<String> defaultFunctions, List<Media> defaultMedia) {
+        this.connector = connector;
+        this.userPrompt = defaultUserPrompt;
+        this.systemPrompt = defaultSystemPrompt;
+        this.functions = defaultFunctions;
+        this.media = defaultMedia;
+
+    }
+
+    @Override
+    public ChatClientRequest build() {
+        return new ChatClientRequest(this.userPrompt, this.systemPrompt, this.functions, this.media);
+    }
+
+    @Override
+    public ChatResponse call(Prompt prompt) {
+        return null;
+    }
+
+    @Override
+    public ChatResponseSpec chat() {
+        return null;
+    }
+
+
+    public ChatClientRequest user(Consumer<UserSpec> consumer) {
+        return null;
+    }
+
+    public static ChatClientBuilder builder(ChatConnector connector) {
+        return new ChatClientBuilder(connector);
+    }
+
+}
+
+

spring-ai-core/src/main/java/org/springframework/ai/chat/connector/ChatConnector.java

@@ -30,6 +30,6 @@ public interface ChatConnector {
 	 * return (generation != null) ? generation.getOutput().getContent() : ""; }
 	 */
 
-	ChatResponse execute(Prompt prompt);
+	ChatResponse call(Prompt prompt);
 
 }

spring-ai-core/src/main/java/org/springframework/ai/chat/service/PromptTransformingChatService.java

@@ -46,8 +46,8 @@ public class PromptTransformingChatService implements ChatService {
 	private List<ChatServiceListener> chatServiceListeners;
 
 	public PromptTransformingChatService(ChatConnector chatConnector, List<PromptTransformer> retrievers,
-			List<PromptTransformer> documentPostProcessors, List<PromptTransformer> augmentors,
-			List<ChatServiceListener> chatServiceListeners) {
+                                         List<PromptTransformer> documentPostProcessors, List<PromptTransformer> augmentors,
+                                         List<ChatServiceListener> chatServiceListeners) {
 		Objects.requireNonNull(chatConnector, "chatConnector must not be null");
 		this.chatConnector = chatConnector;
 		this.retrievers = retrievers;
@@ -86,7 +86,7 @@ public class PromptTransformingChatService implements ChatService {
 		}
 
 		// Perform generation
-		ChatResponse chatResponse = this.chatConnector.execute(chatServiceContext.getPrompt());
+		ChatResponse chatResponse = this.chatConnector.call(chatServiceContext.getPrompt());
 
 		// Invoke Listeners onComplete
 		ChatServiceResponse chatServiceResponse = new ChatServiceResponse(chatServiceContext, chatResponse);

spring-ai-core/src/main/java/org/springframework/ai/evaluation/RelevancyEvaluator.java

@@ -52,7 +52,7 @@ public class RelevancyEvaluator implements Evaluator {
 		Message message = promptTemplate
 			.createMessage(Map.of("query", query, "response", response, "context", context));
 
-		ChatResponse chatResponse = this.chatConnector.execute(new Prompt(message, this.chatOptions));
+		ChatResponse chatResponse = this.chatConnector.call(new Prompt(message, this.chatOptions));
 
 		var evaluationResponse = chatResponse.getResult().getOutput().getContent();
 		boolean passing = false;

spring-ai-core/src/main/java/org/springframework/ai/transformer/KeywordMetadataEnricher.java

@@ -64,7 +64,7 @@ public class KeywordMetadataEnricher implements DocumentTransformer {
 
 			var template = new PromptTemplate(String.format(KEYWORDS_TEMPLATE, keywordCount));
 			Prompt prompt = template.create(Map.of(CONTEXT_STR_PLACEHOLDER, document.getContent()));
-			String keywords = this.chatConnector.execute(prompt).getResult().getOutput().getContent();
+			String keywords = this.chatConnector.call(prompt).getResult().getOutput().getContent();
 			document.getMetadata().putAll(Map.of(EXCERPT_KEYWORDS_METADATA_KEY, keywords));
 		}
 		return documents;

spring-ai-core/src/main/java/org/springframework/ai/transformer/SummaryMetadataEnricher.java

@@ -81,7 +81,7 @@ public class SummaryMetadataEnricher implements DocumentTransformer {
 	}
 
 	public SummaryMetadataEnricher(ChatConnector chatConnector, List<SummaryType> summaryTypes, String summaryTemplate,
-			MetadataMode metadataMode) {
+                                   MetadataMode metadataMode) {
 		Assert.notNull(chatConnector, "ChatConnector must not be null");
 		Assert.hasText(summaryTemplate, "Summary template must not be empty");
 
@@ -101,7 +101,7 @@ public class SummaryMetadataEnricher implements DocumentTransformer {
 
 			Prompt prompt = new PromptTemplate(this.summaryTemplate)
 				.create(Map.of(CONTEXT_STR_PLACEHOLDER, documentContext));
-			documentSummaries.add(this.chatConnector.execute(prompt).getResult().getOutput().getContent());
+			documentSummaries.add(this.chatConnector.call(prompt).getResult().getOutput().getContent());
 		}
 
 		for (int i = 0; i < documentSummaries.size(); i++) {

spring-ai-core/src/test/java/org/springframework/ai/chat/ChatConnectorTests.java

@@ -65,7 +65,7 @@ class ChatConnectorTests {
 		// ChatResponse response = spy(new
 		// ChatResponse(Collections.singletonList(generation)));
 
-		doCallRealMethod().when(mockClient).execute(anyString());
+		doCallRealMethod().when(mockClient).call(anyString());
 
 		doAnswer(invocationOnMock -> {
 
@@ -76,12 +76,12 @@ class ChatConnectorTests {
 
 			return response;
 
-		}).when(mockClient).execute(any(Prompt.class));
+		}).when(mockClient).call(any(Prompt.class));
 
-		assertThat(mockClient.execute(userMessage)).isEqualTo(responseMessage);
+		assertThat(mockClient.call(userMessage)).isEqualTo(responseMessage);
 
-		verify(mockClient, times(1)).execute(eq(userMessage));
-		verify(mockClient, times(1)).execute(isA(Prompt.class));
+		verify(mockClient, times(1)).call(eq(userMessage));
+		verify(mockClient, times(1)).call(isA(Prompt.class));
 		verify(response, times(1)).getResult();
 		verify(generation, times(1)).getOutput();
 		verify(mockAssistantMessage, times(1)).getContent();

spring-ai-core/src/test/java/org/springframework/ai/chat/memory/ChatMemoryTests.java

@@ -48,7 +48,7 @@ import static org.mockito.Mockito.when;
 public class ChatMemoryTests {
 
 	@Mock
-	ChatConnector chatConnector;
+    ChatConnector chatConnector;
 
 	@Mock
 	StreamingChatClient streamingChatClient;
@@ -90,7 +90,7 @@ public class ChatMemoryTests {
 
 	public void chatClientUserMessages(PromptTransformingChatService chatService, ChatMemory chatHistory) {
 
-		when(chatConnector.execute(promptCaptor.capture()))
+		when(chatConnector.call(promptCaptor.capture()))
 				.thenReturn(new ChatResponse(List.of(new Generation("assistant:1"))))
 				.thenReturn(new ChatResponse(List.of(new Generation("assistant:2"))))
 				.thenReturn(new ChatResponse(List.of(new Generation("assistant:3"))));

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/anthropic/AnthropicAutoConfiguration.java

@@ -58,8 +58,8 @@ public class AnthropicAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public AnthropicChatConnector anthropicChatClient(AnthropicApi anthropicApi, AnthropicChatProperties chatProperties,
-			RetryTemplate retryTemplate, FunctionCallbackContext functionCallbackContext,
-			List<FunctionCallback> toolFunctionCallbacks) {
+                                                      RetryTemplate retryTemplate, FunctionCallbackContext functionCallbackContext,
+                                                      List<FunctionCallback> toolFunctionCallbacks) {
 
 		if (!CollectionUtils.isEmpty(toolFunctionCallbacks)) {
 			chatProperties.getOptions().getFunctionCallbacks().addAll(toolFunctionCallbacks);

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/azure/openai/AzureOpenAiAutoConfiguration.java

@@ -59,8 +59,8 @@ public class AzureOpenAiAutoConfiguration {
 	@ConditionalOnProperty(prefix = AzureOpenAiChatProperties.CONFIG_PREFIX, name = "enabled", havingValue = "true",
 			matchIfMissing = true)
 	public AzureOpenAiChatConnector azureOpenAiChatClient(OpenAIClient openAIClient,
-			AzureOpenAiChatProperties chatProperties, List<FunctionCallback> toolFunctionCallbacks,
-			FunctionCallbackContext functionCallbackContext) {
+                                                          AzureOpenAiChatProperties chatProperties, List<FunctionCallback> toolFunctionCallbacks,
+                                                          FunctionCallbackContext functionCallbackContext) {
 
 		if (!CollectionUtils.isEmpty(toolFunctionCallbacks)) {
 			chatProperties.getOptions().getFunctionCallbacks().addAll(toolFunctionCallbacks);

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/bedrock/anthropic/BedrockAnthropicChatAutoConfiguration.java

@@ -60,7 +60,7 @@ public class BedrockAnthropicChatAutoConfiguration {
 	@Bean
 	@ConditionalOnBean(AnthropicChatBedrockApi.class)
 	public BedrockAnthropicChatConnector anthropicChatClient(AnthropicChatBedrockApi anthropicApi,
-			BedrockAnthropicChatProperties properties) {
+                                                             BedrockAnthropicChatProperties properties) {
 		return new BedrockAnthropicChatConnector(anthropicApi, properties.getOptions());
 	}
 

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/bedrock/anthropic3/BedrockAnthropic3ChatAutoConfiguration.java

@@ -60,7 +60,7 @@ public class BedrockAnthropic3ChatAutoConfiguration {
 	@Bean
 	@ConditionalOnBean(Anthropic3ChatBedrockApi.class)
 	public BedrockAnthropic3ChatConnector anthropic3ChatClient(Anthropic3ChatBedrockApi anthropicApi,
-			BedrockAnthropic3ChatProperties properties) {
+                                                               BedrockAnthropic3ChatProperties properties) {
 		return new BedrockAnthropic3ChatConnector(anthropicApi, properties.getOptions());
 	}
 

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/bedrock/cohere/BedrockCohereChatAutoConfiguration.java

@@ -58,7 +58,7 @@ public class BedrockCohereChatAutoConfiguration {
 	@Bean
 	@ConditionalOnBean(CohereChatBedrockApi.class)
 	public BedrockCohereChatConnector cohereChatClient(CohereChatBedrockApi cohereChatApi,
-			BedrockCohereChatProperties properties) {
+                                                       BedrockCohereChatProperties properties) {
 
 		return new BedrockCohereChatConnector(cohereChatApi, properties.getOptions());
 	}

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/bedrock/llama/BedrockLlamaChatAutoConfiguration.java

@@ -60,7 +60,7 @@ public class BedrockLlamaChatAutoConfiguration {
 	@Bean
 	@ConditionalOnBean(LlamaChatBedrockApi.class)
 	public BedrockLlamaChatConnector llamaChatClient(LlamaChatBedrockApi llamaApi,
-			BedrockLlamaChatProperties properties) {
+                                                     BedrockLlamaChatProperties properties) {
 
 		return new BedrockLlamaChatConnector(llamaApi, properties.getOptions());
 	}

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/bedrock/titan/BedrockTitanChatAutoConfiguration.java

@@ -58,7 +58,7 @@ public class BedrockTitanChatAutoConfiguration {
 	@Bean
 	@ConditionalOnBean(TitanChatBedrockApi.class)
 	public BedrockTitanChatConnector titanChatClient(TitanChatBedrockApi titanChatApi,
-			BedrockTitanChatProperties properties) {
+                                                     BedrockTitanChatProperties properties) {
 
 		return new BedrockTitanChatConnector(titanChatApi, properties.getOptions());
 	}

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/mistralai/MistralAiAutoConfiguration.java

@@ -70,9 +70,9 @@ public class MistralAiAutoConfiguration {
 	@ConditionalOnProperty(prefix = MistralAiChatProperties.CONFIG_PREFIX, name = "enabled", havingValue = "true",
 			matchIfMissing = true)
 	public MistralAiChatConnector mistralAiChatClient(MistralAiCommonProperties commonProperties,
-			MistralAiChatProperties chatProperties, RestClient.Builder restClientBuilder,
-			List<FunctionCallback> toolFunctionCallbacks, FunctionCallbackContext functionCallbackContext,
-			RetryTemplate retryTemplate, ResponseErrorHandler responseErrorHandler) {
+                                                      MistralAiChatProperties chatProperties, RestClient.Builder restClientBuilder,
+                                                      List<FunctionCallback> toolFunctionCallbacks, FunctionCallbackContext functionCallbackContext,
+                                                      RetryTemplate retryTemplate, ResponseErrorHandler responseErrorHandler) {
 
 		var mistralAiApi = mistralAiApi(chatProperties.getApiKey(), commonProperties.getApiKey(),
 				chatProperties.getBaseUrl(), commonProperties.getBaseUrl(), restClientBuilder, responseErrorHandler);

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/openai/OpenAiAutoConfiguration.java

@@ -55,9 +55,9 @@ public class OpenAiAutoConfiguration {
 	@ConditionalOnProperty(prefix = OpenAiChatProperties.CONFIG_PREFIX, name = "enabled", havingValue = "true",
 			matchIfMissing = true)
 	public OpenAiChatConnector openAiChatClient(OpenAiConnectionProperties commonProperties,
-			OpenAiChatProperties chatProperties, RestClient.Builder restClientBuilder,
-			List<FunctionCallback> toolFunctionCallbacks, FunctionCallbackContext functionCallbackContext,
-			RetryTemplate retryTemplate, ResponseErrorHandler responseErrorHandler) {
+                                                OpenAiChatProperties chatProperties, RestClient.Builder restClientBuilder,
+                                                List<FunctionCallback> toolFunctionCallbacks, FunctionCallbackContext functionCallbackContext,
+                                                RetryTemplate retryTemplate, ResponseErrorHandler responseErrorHandler) {
 
 		var openAiApi = openAiApi(chatProperties.getBaseUrl(), commonProperties.getBaseUrl(),
 				chatProperties.getApiKey(), commonProperties.getApiKey(), restClientBuilder, responseErrorHandler);

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vertexai/gemini/VertexAiGeminiAutoConfiguration.java

@@ -75,8 +75,8 @@ public class VertexAiGeminiAutoConfiguration {
 	@Bean
 	@ConditionalOnMissingBean
 	public VertexAiGeminiChatConnector vertexAiGeminiChat(VertexAI vertexAi,
-			VertexAiGeminiChatProperties chatProperties, List<FunctionCallback> toolFunctionCallbacks,
-			ApplicationContext context) {
+                                                          VertexAiGeminiChatProperties chatProperties, List<FunctionCallback> toolFunctionCallbacks,
+                                                          ApplicationContext context) {
 
 		FunctionCallbackContext functionCallbackContext = springAiFunctionManager(context);
 

spring-ai-spring-boot-autoconfigure/src/main/java/org/springframework/ai/autoconfigure/vertexai/palm2/VertexAiPalm2AutoConfiguration.java

@@ -48,7 +48,7 @@ public class VertexAiPalm2AutoConfiguration {
 	@ConditionalOnProperty(prefix = VertexAiPlam2ChatProperties.CONFIG_PREFIX, name = "enabled", havingValue = "true",
 			matchIfMissing = true)
 	public VertexAiPaLm2ChatConnector vertexAiChatClient(VertexAiPaLm2Api vertexAiApi,
-			VertexAiPlam2ChatProperties chatProperties) {
+                                                         VertexAiPlam2ChatProperties chatProperties) {
 		return new VertexAiPaLm2ChatConnector(vertexAiApi, chatProperties.getOptions());
 	}
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/anthropic/AnthropicAutoConfigurationIT.java

@@ -51,7 +51,7 @@ public class AnthropicAutoConfigurationIT {
 	void generate() {
 		contextRunner.run(context -> {
 			AnthropicChatConnector chatClient = context.getBean(AnthropicChatConnector.class);
-			String response = chatClient.execute("Hello");
+			String response = chatClient.call("Hello");
 			assertThat(response).isNotEmpty();
 			logger.info("Response: " + response);
 		});

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/anthropic/tool/FunctionCallWithFunctionBeanIT.java

@@ -66,14 +66,14 @@ class FunctionCallWithFunctionBeanIT {
 				var userMessage = new UserMessage(
 						"What's the weather like in San Francisco, in Paris, France and in Tokyo, Japan? Return the temperature in Celsius.");
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage),
+				ChatResponse response = chatClient.call(new Prompt(List.of(userMessage),
 						AnthropicChatOptions.builder().withFunction("weatherFunction").build()));
 
 				logger.info("Response: {}", response);
 
 				assertThat(response.getResult().getOutput().getContent()).contains("30", "10", "15");
 
-				response = chatClient.execute(new Prompt(List.of(userMessage),
+				response = chatClient.call(new Prompt(List.of(userMessage),
 						AnthropicChatOptions.builder().withFunction("weatherFunction3").build()));
 
 				logger.info("Response: {}", response);

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/anthropic/tool/FunctionCallWithPromptFunctionIT.java

@@ -66,7 +66,7 @@ public class FunctionCallWithPromptFunctionIT {
 						.build()))
 					.build();
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage), promptOptions));
+				ChatResponse response = chatClient.call(new Prompt(List.of(userMessage), promptOptions));
 
 				logger.info("Response: {}", response);
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/azure/AzureOpenAiAutoConfigurationIT.java

@@ -21,11 +21,11 @@ import java.util.stream.Collectors;
 
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.api.condition.EnabledIfEnvironmentVariable;
+import org.springframework.ai.azure.openai.AzureOpenAiChatConnector;
 import org.springframework.ai.chat.messages.AssistantMessage;
 import reactor.core.publisher.Flux;
 
 import org.springframework.ai.autoconfigure.azure.openai.AzureOpenAiAutoConfiguration;
-import org.springframework.ai.azure.openai.AzureOpenAiChatConnector;
 import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingClient;
 import org.springframework.ai.chat.ChatResponse;
 import org.springframework.ai.chat.Generation;
@@ -78,7 +78,7 @@ public class AzureOpenAiAutoConfigurationIT {
 	public void chatCompletion() {
 		contextRunner.run(context -> {
 			AzureOpenAiChatConnector chatClient = context.getBean(AzureOpenAiChatConnector.class);
-			ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = chatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/azure/tool/FunctionCallWithFunctionBeanIT.java

@@ -62,14 +62,14 @@ class FunctionCallWithFunctionBeanIT {
 				UserMessage userMessage = new UserMessage(
 						"What's the weather like in San Francisco, Paris and in Tokyo? Use Multi-turn function calling.");
 
-				ChatResponse response = chatConnector.execute(new Prompt(List.of(userMessage),
+				ChatResponse response = chatConnector.call(new Prompt(List.of(userMessage),
 						AzureOpenAiChatOptions.builder().withFunction("weatherFunction").build()));
 
 				logger.info("Response: {}", response);
 
 				assertThat(response.getResult().getOutput().getContent()).contains("30", "10", "15");
 
-				response = chatConnector.execute(new Prompt(List.of(userMessage),
+				response = chatConnector.call(new Prompt(List.of(userMessage),
 						AzureOpenAiChatOptions.builder().withFunction("weatherFunction3").build()));
 
 				logger.info("Response: {}", response);

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/azure/tool/FunctionCallWithFunctionWrapperIT.java

@@ -61,7 +61,7 @@ public class FunctionCallWithFunctionWrapperIT {
 				UserMessage userMessage = new UserMessage(
 						"What's the weather like in San Francisco, Paris and in Tokyo?");
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage),
+				ChatResponse response = chatClient.call(new Prompt(List.of(userMessage),
 						AzureOpenAiChatOptions.builder().withFunction("WeatherInfo").build()));
 
 				logger.info("Response: {}", response);

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/azure/tool/FunctionCallWithPromptFunctionIT.java

@@ -64,7 +64,7 @@ public class FunctionCallWithPromptFunctionIT {
 						.build()))
 					.build();
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage), promptOptions));
+				ChatResponse response = chatClient.call(new Prompt(List.of(userMessage), promptOptions));
 
 				logger.info("Response: {}", response);
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/bedrock/anthropic/BedrockAnthropicChatAutoConfigurationIT.java

@@ -70,7 +70,7 @@ public class BedrockAnthropicChatAutoConfigurationIT {
 	public void chatCompletion() {
 		contextRunner.run(context -> {
 			BedrockAnthropicChatConnector anthropicChatClient = context.getBean(BedrockAnthropicChatConnector.class);
-			ChatResponse response = anthropicChatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = anthropicChatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/bedrock/anthropic3/BedrockAnthropic3ChatAutoConfigurationIT.java

@@ -70,7 +70,7 @@ public class BedrockAnthropic3ChatAutoConfigurationIT {
 	public void chatCompletion() {
 		contextRunner.run(context -> {
 			BedrockAnthropic3ChatConnector anthropicChatClient = context.getBean(BedrockAnthropic3ChatConnector.class);
-			ChatResponse response = anthropicChatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = anthropicChatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/bedrock/cohere/BedrockCohereChatAutoConfigurationIT.java

@@ -73,7 +73,7 @@ public class BedrockCohereChatAutoConfigurationIT {
 	public void chatCompletion() {
 		contextRunner.run(context -> {
 			BedrockCohereChatConnector cohereChatClient = context.getBean(BedrockCohereChatConnector.class);
-			ChatResponse response = cohereChatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = cohereChatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/bedrock/jurassic2/BedrockAi21Jurassic2ChatAutoConfigurationIT.java

@@ -71,7 +71,7 @@ public class BedrockAi21Jurassic2ChatAutoConfigurationIT {
 		contextRunner.run(context -> {
 			BedrockAi21Jurassic2ChatConnector ai21Jurassic2ChatClient = context
 				.getBean(BedrockAi21Jurassic2ChatConnector.class);
-			ChatResponse response = ai21Jurassic2ChatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = ai21Jurassic2ChatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/bedrock/llama/BedrockLlamaChatAutoConfigurationIT.java

@@ -72,7 +72,7 @@ public class BedrockLlamaChatAutoConfigurationIT {
 	public void chatCompletion() {
 		contextRunner.run(context -> {
 			BedrockLlamaChatConnector llamaChatClient = context.getBean(BedrockLlamaChatConnector.class);
-			ChatResponse response = llamaChatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = llamaChatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/bedrock/titan/BedrockTitanChatAutoConfigurationIT.java

@@ -71,7 +71,7 @@ public class BedrockTitanChatAutoConfigurationIT {
 	public void chatCompletion() {
 		contextRunner.run(context -> {
 			BedrockTitanChatConnector chatClient = context.getBean(BedrockTitanChatConnector.class);
-			ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = chatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/mistralai/MistralAiAutoConfigurationIT.java

@@ -55,7 +55,7 @@ public class MistralAiAutoConfigurationIT {
 	void generate() {
 		contextRunner.run(context -> {
 			MistralAiChatConnector client = context.getBean(MistralAiChatConnector.class);
-			String response = client.execute("Hello");
+			String response = client.call("Hello");
 			assertThat(response).isNotEmpty();
 			logger.info("Response: " + response);
 		});

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/mistralai/tool/PaymentStatusBeanIT.java

@@ -63,7 +63,7 @@ class PaymentStatusBeanIT {
 				MistralAiChatConnector chatClient = context.getBean(MistralAiChatConnector.class);
 
 				ChatResponse response = chatClient
-					.execute(new Prompt(List.of(new UserMessage("What's the status of my transaction with id T1001?")),
+					.call(new Prompt(List.of(new UserMessage("What's the status of my transaction with id T1001?")),
 							MistralAiChatOptions.builder()
 								.withFunction("retrievePaymentStatus")
 								.withFunction("retrievePaymentDate")

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/mistralai/tool/PaymentStatusBeanOpenAiIT.java

@@ -70,7 +70,7 @@ class PaymentStatusBeanOpenAiIT {
 				OpenAiChatConnector chatClient = context.getBean(OpenAiChatConnector.class);
 
 				ChatResponse response = chatClient
-					.execute(new Prompt(List.of(new UserMessage("What's the status of my transaction with id T1001?")),
+					.call(new Prompt(List.of(new UserMessage("What's the status of my transaction with id T1001?")),
 							OpenAiChatOptions.builder()
 								.withFunction("retrievePaymentStatus")
 								.withFunction("retrievePaymentDate")

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/mistralai/tool/PaymentStatusPromptIT.java

@@ -86,7 +86,7 @@ public class PaymentStatusPromptIT {
 						.build()))
 					.build();
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage), promptOptions));
+				ChatResponse response = chatClient.call(new Prompt(List.of(userMessage), promptOptions));
 
 				logger.info("Response: {}", response);
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/mistralai/tool/WeatherServicePromptIT.java

@@ -79,7 +79,7 @@ public class WeatherServicePromptIT {
 						.build()))
 					.build();
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage), promptOptions));
+				ChatResponse response = chatClient.call(new Prompt(List.of(userMessage), promptOptions));
 
 				logger.info("Response: {}", response);
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/ollama/OllamaChatAutoConfigurationIT.java

@@ -105,7 +105,7 @@ public class OllamaChatAutoConfigurationIT {
 	public void chatCompletion() {
 		contextRunner.run(context -> {
 			OllamaChatConnector chatClient = context.getBean(OllamaChatConnector.class);
-			ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage, systemMessage)));
+			ChatResponse response = chatClient.call(new Prompt(List.of(userMessage, systemMessage)));
 			assertThat(response.getResult().getOutput().getContent()).contains("Blackbeard");
 		});
 	}

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/openai/OpenAiAutoConfigurationIT.java

@@ -56,7 +56,7 @@ public class OpenAiAutoConfigurationIT {
 	void generate() {
 		contextRunner.run(context -> {
 			OpenAiChatConnector client = context.getBean(OpenAiChatConnector.class);
-			String response = client.execute("Hello");
+			String response = client.call("Hello");
 			assertThat(response).isNotEmpty();
 			logger.info("Response: " + response);
 		});

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/openai/tool/FunctionCallbackInPromptIT.java

@@ -66,7 +66,7 @@ public class FunctionCallbackInPromptIT {
 					.build()))
 				.build();
 
-			ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage), promptOptions));
+			ChatResponse response = chatClient.call(new Prompt(List.of(userMessage), promptOptions));
 
 			logger.info("Response: {}", response);
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/openai/tool/FunctionCallbackWithPlainFunctionBeanIT.java

@@ -65,7 +65,7 @@ class FunctionCallbackWithPlainFunctionBeanIT {
 			// Test weatherFunction
 			UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?");
 
-			ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage),
+			ChatResponse response = chatClient.call(new Prompt(List.of(userMessage),
 					OpenAiChatOptions.builder().withFunction("weatherFunction").build()));
 
 			logger.info("Response: {}", response);
@@ -73,7 +73,7 @@ class FunctionCallbackWithPlainFunctionBeanIT {
 			assertThat(response.getResult().getOutput().getContent()).contains("30", "10", "15");
 
 			// Test weatherFunctionTwo
-			response = chatClient.execute(new Prompt(List.of(userMessage),
+			response = chatClient.call(new Prompt(List.of(userMessage),
 					OpenAiChatOptions.builder().withFunction("weatherFunctionTwo").build()));
 
 			logger.info("Response: {}", response);
@@ -96,7 +96,7 @@ class FunctionCallbackWithPlainFunctionBeanIT {
 				.withFunction("weatherFunction")
 				.build();
 
-			ChatResponse response = chatClient.execute(new Prompt(List.of(userMessage), functionOptions));
+			ChatResponse response = chatClient.call(new Prompt(List.of(userMessage), functionOptions));
 
 			logger.info("Response: {}", response);
 		});

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/openai/tool/FunctionCallbackWrapperIT.java

@@ -62,7 +62,7 @@ public class FunctionCallbackWrapperIT {
 
 			UserMessage userMessage = new UserMessage("What's the weather like in San Francisco, Tokyo, and Paris?");
 
-			ChatResponse response = chatClient.execute(
+			ChatResponse response = chatClient.call(
 					new Prompt(List.of(userMessage), OpenAiChatOptions.builder().withFunction("WeatherInfo").build()));
 
 			logger.info("Response: {}", response);

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vertexai/gemini/VertexAiGeminiAutoConfigurationIT.java

@@ -47,7 +47,7 @@ public class VertexAiGeminiAutoConfigurationIT {
 	void generate() {
 		contextRunner.run(context -> {
 			VertexAiGeminiChatConnector client = context.getBean(VertexAiGeminiChatConnector.class);
-			String response = client.execute("Hello");
+			String response = client.call("Hello");
 			assertThat(response).isNotEmpty();
 			logger.info("Response: " + response);
 		});

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vertexai/gemini/tool/FunctionCallWithFunctionBeanIT.java

@@ -72,7 +72,7 @@ class FunctionCallWithFunctionBeanIT {
 						// Please let me know how many function calls you've preformed.");
 						"What's the weather like in San Francisco, Paris and in Tokyo?");
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(systemMessage, userMessage),
+				ChatResponse response = chatClient.call(new Prompt(List.of(systemMessage, userMessage),
 						VertexAiGeminiChatOptions.builder().withFunction("weatherFunction").build()));
 				// ChatResponse response = chatConnector.call(new
 				// Prompt(List.of(userMessage),
@@ -84,7 +84,7 @@ class FunctionCallWithFunctionBeanIT {
 
 				Thread.sleep(10000);
 
-				response = chatClient.execute(new Prompt(List.of(systemMessage, userMessage),
+				response = chatClient.call(new Prompt(List.of(systemMessage, userMessage),
 						VertexAiGeminiChatOptions.builder().withFunction("weatherFunction3").build()));
 
 				logger.info("Response: {}", response);
@@ -92,7 +92,7 @@ class FunctionCallWithFunctionBeanIT {
 				assertThat(response.getResult().getOutput().getContent()).contains("30", "10", "15");
 
 				response = chatClient
-					.execute(new Prompt(List.of(systemMessage, userMessage), VertexAiGeminiChatOptions.builder().build()));
+					.call(new Prompt(List.of(systemMessage, userMessage), VertexAiGeminiChatOptions.builder().build()));
 
 				logger.info("Response: {}", response);
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vertexai/gemini/tool/FunctionCallWithFunctionWrapperIT.java

@@ -67,7 +67,7 @@ public class FunctionCallWithFunctionWrapperIT {
 						""");
 				var userMessage = new UserMessage("What's the weather like in San Francisco, Paris and in Tokyo?");
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(systemMessage, userMessage),
+				ChatResponse response = chatClient.call(new Prompt(List.of(systemMessage, userMessage),
 						VertexAiGeminiChatOptions.builder().withFunction("WeatherInfo").build()));
 
 				logger.info("Response: {}", response);

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vertexai/gemini/tool/FunctionCallWithPromptFunctionIT.java

@@ -72,7 +72,7 @@ public class FunctionCallWithPromptFunctionIT {
 						.build()))
 					.build();
 
-				ChatResponse response = chatClient.execute(new Prompt(List.of(systemMessage, userMessage), promptOptions));
+				ChatResponse response = chatClient.call(new Prompt(List.of(systemMessage, userMessage), promptOptions));
 
 				logger.info("Response: {}", response);
 
@@ -80,7 +80,7 @@ public class FunctionCallWithPromptFunctionIT {
 
 				// Verify that no function call is made.
 				response = chatClient
-					.execute(new Prompt(List.of(systemMessage, userMessage), VertexAiGeminiChatOptions.builder().build()));
+					.call(new Prompt(List.of(systemMessage, userMessage), VertexAiGeminiChatOptions.builder().build()));
 
 				logger.info("Response: {}", response);
 

spring-ai-spring-boot-autoconfigure/src/test/java/org/springframework/ai/autoconfigure/vertexai/palm2/VertexAiPaLm2AutoConfigurationIT.java

@@ -50,7 +50,7 @@ public class VertexAiPaLm2AutoConfigurationIT {
 		contextRunner.run(context -> {
 			VertexAiPaLm2ChatConnector client = context.getBean(VertexAiPaLm2ChatConnector.class);
 
-			String response = client.execute("Hello");
+			String response = client.call("Hello");
 
 			assertThat(response).isNotEmpty();
 			logger.info("Response: " + response);

spring-ai-test/src/main/java/org/springframework/ai/evaluation/BasicEvaluationTest.java

@@ -68,12 +68,12 @@ public class BasicEvaluationTest {
 		}
 		Message userMessage = userPromptTemplate.createMessage();
 		Prompt prompt = new Prompt(List.of(userMessage, systemMessage));
-		String yesOrNo = openAiChatConnector.execute(prompt).getResult().getOutput().getContent();
+		String yesOrNo = openAiChatConnector.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 = openAiChatConnector.execute(prompt).getResult().getOutput().getContent();
+			String reasonForFailure = openAiChatConnector.call(prompt).getResult().getOutput().getContent();
 			fail(reasonForFailure);
 		}
 		else {

vector-stores/spring-ai-hanadb-store/src/test/java/org/springframework/ai/vectorstore/CricketWorldCupHanaController.java

@@ -88,7 +88,7 @@ public class CricketWorldCupHanaController {
 
 		var userMessage = new UserMessage(message);
 		Prompt prompt = new Prompt(List.of(similarDocsMessage, userMessage));
-		String generation = chatConnector.execute(prompt).getResult().getOutput().getContent();
+		String generation = chatConnector.call(prompt).getResult().getOutput().getContent();
 		logger.info("Generation: {}", generation);
 		return Map.of("generation", generation);
 	}