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Merge pull request #17942 from sIvanovKonstantyn/master2
BAEL-8840 - A Guide to Spring AI Advisors
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‎spring-ai/pom.xml

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<properties>
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<spring-boot.version>3.3.2</spring-boot.version>
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<spring-ai.version>1.0.0-M1</spring-ai.version>
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<spring-ai.version>1.0.0-M3</spring-ai.version>
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<junit-jupiter.version>5.9.0</junit-jupiter.version>
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</properties>
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</project>

‎spring-ai/src/main/java/com/baeldung/springai/advisors/CustomLoggingAdvisor.java

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package com.baeldung.springai.advisors;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import org.springframework.ai.chat.client.advisor.api.AdvisedRequest;
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import org.springframework.ai.chat.client.advisor.api.AdvisedResponse;
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import org.springframework.ai.chat.client.advisor.api.CallAroundAdvisor;
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import org.springframework.ai.chat.client.advisor.api.CallAroundAdvisorChain;
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public class CustomLoggingAdvisor implements CallAroundAdvisor {
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private final static Logger logger = LoggerFactory.getLogger(CustomLoggingAdvisor.class);
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@Override
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public AdvisedResponse aroundCall(AdvisedRequest advisedRequest, CallAroundAdvisorChain chain) {
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advisedRequest = this.before(advisedRequest);
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AdvisedResponse advisedResponse = chain.nextAroundCall(advisedRequest);
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this.observeAfter(advisedResponse);
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return advisedResponse;
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}
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private void observeAfter(AdvisedResponse advisedResponse) {
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logger.info(advisedResponse.response()
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.getResult()
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.getOutput()
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.getContent());
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}
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private AdvisedRequest before(AdvisedRequest advisedRequest) {
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logger.info(advisedRequest.userText());
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return advisedRequest;
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}
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@Override
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public String getName() {
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return "CustomLoggingAdvisor";
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}
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@Override
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public int getOrder() {
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return Integer.MAX_VALUE;
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}
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}

‎spring-ai/src/main/java/com/baeldung/springai/web/ExceptionTranslator.java

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package com.baeldung.springai.web;
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import org.springframework.ai.openai.api.common.OpenAiApiException;
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import org.springframework.ai.openai.api.common.OpenAiApiClientErrorException;
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import org.springframework.http.HttpStatus;
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import org.springframework.http.ProblemDetail;
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import org.springframework.web.bind.annotation.ExceptionHandler;
@@ -14,8 +14,8 @@ public class ExceptionTranslator extends ResponseEntityExceptionHandler {
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public static final String OPEN_AI_CLIENT_RAISED_EXCEPTION = "Open AI client raised exception";
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@ExceptionHandler(OpenAiApiException.class)
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ProblemDetail handleOpenAiHttpException(OpenAiApiException ex) {
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@ExceptionHandler(OpenAiApiClientErrorException.class)
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ProblemDetail handleOpenAiHttpException(OpenAiApiClientErrorException ex) {
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HttpStatus status = Optional
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.ofNullable(HttpStatus.resolve(400))
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.orElse(HttpStatus.BAD_REQUEST);

‎spring-ai/src/test/java/com/baeldung/springai/advisors/SimpleVectorStoreConfiguration.java

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package com.baeldung.springai.advisors;
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import org.springframework.ai.document.Document;
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import org.springframework.ai.embedding.EmbeddingModel;
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import org.springframework.ai.vectorstore.SearchRequest;
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import org.springframework.ai.vectorstore.SimpleVectorStore;
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import org.springframework.ai.vectorstore.VectorStore;
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import org.springframework.beans.factory.annotation.Qualifier;
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import org.springframework.context.annotation.Bean;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.data.util.Pair;
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import java.util.Comparator;
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import java.util.List;
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@Configuration
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public class SimpleVectorStoreConfiguration {
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@Bean
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public VectorStore vectorStore(@Qualifier("openAiEmbeddingModel")EmbeddingModel embeddingModel) {
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return new SimpleVectorStore(embeddingModel) {
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@Override
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public List<Document> doSimilaritySearch(SearchRequest request) {
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float[] userQueryEmbedding = embeddingModel.embed(request.query);
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return this.store.values()
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.stream()
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.map(entry -> Pair.of(entry.getId(),
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EmbeddingMath.cosineSimilarity(userQueryEmbedding, entry.getEmbedding())))
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.filter(s -> s.getSecond() >= request.getSimilarityThreshold())
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.sorted(Comparator.comparing(Pair::getSecond))
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.limit(request.getTopK())
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.map(s -> this.store.get(s.getFirst()))
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.toList();
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}
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};
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}
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}

‎spring-ai/src/test/java/com/baeldung/springai/advisors/SpringAILiveTest.java

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package com.baeldung.springai.advisors;
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import org.junit.jupiter.api.BeforeEach;
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import org.junit.jupiter.api.Test;
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import org.junit.jupiter.api.extension.ExtendWith;
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import org.springframework.ai.autoconfigure.mistralai.MistralAiAutoConfiguration;
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import org.springframework.ai.autoconfigure.vectorstore.mongo.MongoDBAtlasVectorStoreAutoConfiguration;
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import org.springframework.ai.autoconfigure.vectorstore.redis.RedisVectorStoreAutoConfiguration;
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import org.springframework.ai.chat.client.ChatClient;
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import org.springframework.ai.chat.client.advisor.*;
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import org.springframework.ai.chat.memory.ChatMemory;
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import org.springframework.ai.chat.memory.InMemoryChatMemory;
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import org.springframework.ai.chat.model.ChatModel;
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import org.springframework.ai.document.Document;
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import org.springframework.ai.transformer.splitter.TokenTextSplitter;
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import org.springframework.ai.vectorstore.VectorStore;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.beans.factory.annotation.Qualifier;
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import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
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import org.springframework.boot.autoconfigure.mongo.MongoAutoConfiguration;
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import org.springframework.boot.test.context.SpringBootTest;
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import org.springframework.test.context.junit.jupiter.SpringExtension;
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import java.util.List;
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import static org.assertj.core.api.Assertions.assertThat;
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/*
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* To set the test environment:
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* populate OPENAI_API_KEY env. variable with active Open AI API key
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* */
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@SpringBootTest(classes = {ChatModel.class, SimpleVectorStoreConfiguration.class})
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@EnableAutoConfiguration(exclude = {RedisVectorStoreAutoConfiguration.class,
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MistralAiAutoConfiguration.class, MongoDBAtlasVectorStoreAutoConfiguration.class, MongoAutoConfiguration.class})
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@ExtendWith(SpringExtension.class)
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public class SpringAILiveTest {
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@Autowired
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@Qualifier("openAiChatModel")
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ChatModel chatModel;
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@Autowired
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VectorStore vectorStore;
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ChatClient chatClient;
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@BeforeEach
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void setup() {
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chatClient = ChatClient.builder(chatModel).build();
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}
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@Test
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void givenMessageChatMemoryAdvisor_whenAskingChatToIncrementTheResponseWithNewName_thenNamesFromTheChatHistoryExistInResponse() {
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ChatMemory chatMemory = new InMemoryChatMemory();
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MessageChatMemoryAdvisor chatMemoryAdvisor = new MessageChatMemoryAdvisor(chatMemory);
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String responseContent = chatClient.prompt()
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.user("Add this name to a list and return all the values: Bob")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Bob");
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responseContent = chatClient.prompt()
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.user("Add this name to a list and return all the values: John")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Bob")
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.contains("John");
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responseContent = chatClient.prompt()
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.user("Add this name to a list and return all the values: Anna")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Bob")
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.contains("John")
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.contains("Anna");
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}
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@Test
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void givenPromptChatMemoryAdvisor_whenAskingChatToIncrementTheResponseWithNewName_thenNamesFromTheChatHistoryExistInResponse() {
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ChatMemory chatMemory = new InMemoryChatMemory();
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PromptChatMemoryAdvisor chatMemoryAdvisor = new PromptChatMemoryAdvisor(chatMemory);
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String responseContent = chatClient.prompt()
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.user("Add this name to a list and return all the values: Bob")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Bob");
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responseContent = chatClient.prompt()
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.user("Add this name to a list and return all the values: John")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Bob")
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.contains("John");
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responseContent = chatClient.prompt()
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.user("Add this name to a list and return all the values: Anna")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Bob")
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.contains("John")
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.contains("Anna");
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}
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@Test
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void givenVectorStoreChatMemoryAdvisor_whenAskingChatToIncrementTheResponseWithNewName_thenNamesFromTheChatHistoryExistInResponse() {
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VectorStoreChatMemoryAdvisor chatMemoryAdvisor = new VectorStoreChatMemoryAdvisor(vectorStore);
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String responseContent = chatClient.prompt()
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.user("Find cats from our chat history, add Lion there and return a list")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Lion");
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responseContent = chatClient.prompt()
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.user("Find cats from our chat history, add Puma there and return a list")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Lion")
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.contains("Puma");
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responseContent = chatClient.prompt()
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.user("Find cats from our chat history, add Leopard there and return a list")
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.advisors(chatMemoryAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("Lion")
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.contains("Puma")
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.contains("Leopard");
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}
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@Test
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void givenQuestionAnswerAdvisor_whenAskingQuestion_thenAnswerShouldBeProvidedBasedOnVectorStoreInformation() {
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Document document = new Document("The sky is green");
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List<Document> documents = new TokenTextSplitter().apply(List.of(document));
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vectorStore.add(documents);
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QuestionAnswerAdvisor questionAnswerAdvisor = new QuestionAnswerAdvisor(vectorStore);
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String responseContent = chatClient.prompt()
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.user("What is the sky color?")
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.advisors(questionAnswerAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.containsIgnoringCase("green");
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}
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@Test
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void givenSafeGuardAdvisor_whenSendPromptWithSensitiveWord_thenExpectedMessageShouldBeReturned() {
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List<String> forbiddenWords = List.of("Word2");
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SafeGuardAdvisor safeGuardAdvisor = new SafeGuardAdvisor(forbiddenWords);
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String responseContent = chatClient.prompt()
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.user("Please split the 'Word2' into characters")
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.advisors(safeGuardAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("I'm unable to respond to that due to sensitive content");
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}
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@Test
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void givenCustomLoggingAdvisor_whenSendPrompt_thenPromptTextAndResponseShouldBeLogged() {
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CustomLoggingAdvisor customLoggingAdvisor = new CustomLoggingAdvisor();
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String responseContent = chatClient.prompt()
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.user("Count from 1 to 10")
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.advisors(customLoggingAdvisor)
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.call()
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.content();
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assertThat(responseContent)
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.contains("1")
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.contains("10");
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}
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}

‎spring-ai/src/test/java/com/baeldung/springai/rag/mongodb/RAGMongoDBApplicationManualTest.java

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package com.baeldung.springai.rag.mongodb;
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import com.baeldung.springai.rag.mongodb.config.VectorStoreConfig;
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import org.junit.jupiter.api.Test;
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import org.junit.jupiter.api.extension.ExtendWith;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import org.springframework.ai.autoconfigure.mistralai.MistralAiAutoConfiguration;
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import org.springframework.ai.autoconfigure.vectorstore.redis.RedisVectorStoreAutoConfiguration;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
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import org.springframework.boot.test.autoconfigure.web.servlet.AutoConfigureMockMvc;
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import org.springframework.boot.test.context.SpringBootTest;
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import org.springframework.test.context.junit.jupiter.SpringExtension;
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* */
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@AutoConfigureMockMvc
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@ExtendWith(SpringExtension.class)
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@SpringBootTest
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@EnableAutoConfiguration(exclude = {RedisVectorStoreAutoConfiguration.class, MistralAiAutoConfiguration.class})
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@SpringBootTest(classes = VectorStoreConfig.class)
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class RAGMongoDBApplicationManualTest {
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private static Logger logger = LoggerFactory.getLogger(RAGMongoDBApplicationManualTest.class);
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