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chatclient

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This commit is contained in:
Josh Long
2024-05-17 19:40:29 +02:00
parent a2147e8572
commit 981ea68b00
97 changed files with 409 additions and 253 deletions
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6
models/spring-ai-anthropic/src/main/java/org/springframework/ai/anthropic/AnthropicChatConnector.java
View File

@@ -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);

14
models/spring-ai-anthropic/src/test/java/org/springframework/ai/anthropic/AnthropicChatConnectorIT.java
View File

@@ -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);

4
models/spring-ai-azure-openai/src/main/java/org/springframework/ai/azure/openai/AzureOpenAiChatConnector.java
View File

@@ -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);

10
models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/AzureOpenAiChatConnectorIT.java
View File

@@ -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);

2
models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/MockAzureOpenAiTestConfiguration.java
View File

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

6
models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/function/AzureOpenAiChatConnectorFunctionCallIT.java
View File

@@ -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));

2
models/spring-ai-azure-openai/src/test/java/org/springframework/ai/azure/openai/metadata/AzureOpenAiChatConnectorMetadataTests.java
View File

@@ -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();

2
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicChatConnector.java
View File

@@ -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);

2
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3ChatConnector.java
View File

@@ -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);

2
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatConnector.java
View File

@@ -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());

4
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/jurassic2/BedrockAi21Jurassic2ChatConnector.java
View File

@@ -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);

2
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/llama/BedrockLlamaChatConnector.java
View File

@@ -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);

2
models/spring-ai-bedrock/src/main/java/org/springframework/ai/bedrock/titan/BedrockTitanChatConnector.java
View File

@@ -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());

8
models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/anthropic/BedrockAnthropicChatConnectorIT.java
View File

@@ -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");

10
models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/anthropic3/BedrockAnthropic3ChatConnectorIT.java
View File

@@ -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");

8
models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/cohere/BedrockCohereChatConnectorIT.java
View File

@@ -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");

10
models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/jurassic2/BedrockAi21Jurassic2ChatConnectorIT.java
View File

@@ -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");
}

8
models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/llama/BedrockLlamaChatConnectorIT.java
View File

@@ -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");

8
models/spring-ai-bedrock/src/test/java/org/springframework/ai/bedrock/titan/BedrockTitanChatConnectorIT.java
View File

@@ -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");

2
models/spring-ai-huggingface/src/main/java/org/springframework/ai/huggingface/HuggingfaceChatConnector.java
View File

@@ -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();

2
models/spring-ai-huggingface/src/test/java/org/springframework/ai/huggingface/client/ClientIT.java
View File

@@ -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

4
models/spring-ai-mistral-ai/src/main/java/org/springframework/ai/mistralai/MistralAiChatConnector.java
View File

@@ -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 -> {

16
models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiChatConnectorIT.java
View File

@@ -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?");

4
models/spring-ai-mistral-ai/src/test/java/org/springframework/ai/mistralai/MistralAiRetryTests.java
View File

@@ -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

4
models/spring-ai-ollama/src/main/java/org/springframework/ai/ollama/OllamaChatConnector.java
View File

@@ -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));

12
models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatConnectorIT.java
View File

@@ -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");

2
models/spring-ai-ollama/src/test/java/org/springframework/ai/ollama/OllamaChatConnectorMultimodalIT.java
View File

@@ -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");

4
models/spring-ai-openai/src/main/java/org/springframework/ai/openai/OpenAiChatConnector.java
View File

@@ -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);

4
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/ChatClientTest.java → models/spring-ai-openai/src/test/java/org/springframework/ai/openai/ChatConnectorTest.java
View File

@@ -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;
}

2
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/acme/AcmeIT.java
View File

@@ -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);
}

2
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatClientWithChatResponseMetadataTests.java
View File

@@ -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();

2
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatConnector2IT.java
View File

@@ -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();

20
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiChatConnectorIT.java
View File

@@ -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");

12
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/OpenAiRetryTests.java
View File

@@ -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

4
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/ChatMemoryLongTermSystemPromptIT.java
View File

@@ -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)))

4
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/ChatMemoryShortTermMessageListIT.java
View File

@@ -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)))

4
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/ChatMemoryShortTermSystemPromptIT.java
View File

@@ -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)))

4
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/LongShortTermChatMemoryWithRagIT.java
View File

@@ -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()),

2
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/chat/service/OpenAiPromptTransformingChatServiceIT.java
View File

@@ -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;

4
models/spring-ai-openai/src/test/java/org/springframework/ai/openai/testutils/AbstractIT.java
View File

@@ -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 {

4
models/spring-ai-vertex-ai-gemini/src/main/java/org/springframework/ai/vertexai/gemini/VertexAiGeminiChatConnector.java
View File

@@ -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);

10
models/spring-ai-vertex-ai-gemini/src/test/java/org/springframework/ai/vertexai/gemini/VertexAiGeminiChatConnectorIT.java
View File

@@ -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.

12
models/spring-ai-vertex-ai-gemini/src/test/java/org/springframework/ai/vertexai/gemini/function/VertexAiGeminiChatConnectorFunctionCallingIT.java
View File

@@ -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(

2
models/spring-ai-vertex-ai-palm2/src/main/java/org/springframework/ai/vertexai/palm2/VertexAiPaLm2ChatConnector.java
View File

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

8
models/spring-ai-vertex-ai-palm2/src/test/java/org/springframework/ai/vertexai/palm2/VertexAiPaLm2ChatGenerationClientIT.java
View File

@@ -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");

4
models/spring-ai-watsonx-ai/src/main/java/org/springframework/ai/watsonx/WatsonxAiChatConnector.java
View File

@@ -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);

4
models/spring-ai-watsonx-ai/src/test/java/org/springframework/ai/watsonx/WatsonxAiChatConnectorTest.java
View File

@@ -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());