codebase/building-an-ai-chatbot-using-deepseek-models-with-spring-ai [BAEL-9195] (#18325)

* add chatbot built on top of deepseek reasoning model

* refactor DeepSeekModelOutputConverter

* refactor usage of custom output converter

* fix: NPE

* incorporate feedback and add UT for custom converter

Author: hardikSinghBehl

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/Application.java

@@ -0,0 +1,25 @@
+package com.baeldung.springai.deepseek;
+
+import org.springframework.ai.autoconfigure.anthropic.AnthropicAutoConfiguration;
+import org.springframework.ai.autoconfigure.vectorstore.chroma.ChromaVectorStoreAutoConfiguration;
+import org.springframework.boot.SpringApplication;
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+import org.springframework.context.annotation.PropertySource;
+
+/**
+ * Excluding the below auto-configurations to avoid start up
+ * failure. Their corresponding starters are present on the classpath but are
+ * only needed by other articles in the shared codebase.
+ */
+@SpringBootApplication(exclude = {
+    AnthropicAutoConfiguration.class,
+    ChromaVectorStoreAutoConfiguration.class
+})
+@PropertySource("classpath:application-deepseek.properties")
+class Application {
+
+    public static void main(String[] args) {
+        SpringApplication.run(Application.class, args);
+    }
+
+}

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/ChatRequest.java

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+package com.baeldung.springai.deepseek;
+
+import org.springframework.lang.Nullable;
+
+import java.util.UUID;
+
+record ChatRequest(@Nullable UUID chatId, String question) {
+}

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/ChatResponse.java

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+package com.baeldung.springai.deepseek;
+
+import java.util.UUID;
+
+record ChatResponse(UUID chatId, String chainOfThought, String answer) {
+}

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/ChatbotConfiguration.java

@@ -0,0 +1,36 @@
+package com.baeldung.springai.deepseek;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
+import org.springframework.ai.chat.memory.ChatMemory;
+import org.springframework.ai.chat.memory.InMemoryChatMemory;
+import org.springframework.ai.chat.model.ChatModel;
+import org.springframework.beans.factory.annotation.Qualifier;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+
+@Configuration
+class ChatbotConfiguration {
+
+    @Bean
+    ChatMemory chatMemory() {
+        return new InMemoryChatMemory();
+    }
+
+    /**
+     * When using alternate providers, use the following qualifiers instead:
+     * - @Qualifier("bedrockProxyChatModel") for Amazon Bedrock Converse API
+     * - @Qualifier("ollamaChatModel") for Ollama
+     */
+    @Bean
+    ChatClient chatClient(
+        @Qualifier("openAiChatModel") ChatModel chatModel,
+        ChatMemory chatMemory
+    ) {
+        return ChatClient
+            .builder(chatModel)
+            .defaultAdvisors(new MessageChatMemoryAdvisor(chatMemory))
+            .build();
+    }
+
+}

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/ChatbotController.java

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+package com.baeldung.springai.deepseek;
+
+import org.springframework.http.ResponseEntity;
+import org.springframework.web.bind.annotation.PostMapping;
+import org.springframework.web.bind.annotation.RequestBody;
+import org.springframework.web.bind.annotation.RestController;
+
+@RestController
+class ChatbotController {
+
+    private final ChatbotService chatbotService;
+
+    ChatbotController(ChatbotService chatbotService) {
+        this.chatbotService = chatbotService;
+    }
+
+    @PostMapping("/chat")
+    ResponseEntity<ChatResponse> chat(@RequestBody ChatRequest chatRequest) {
+        ChatResponse chatResponse = chatbotService.chat(chatRequest);
+        return ResponseEntity.ok(chatResponse);
+    }
+
+}

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/ChatbotService.java

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+package com.baeldung.springai.deepseek;
+
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.stereotype.Service;
+
+import java.util.Optional;
+import java.util.UUID;
+
+@Service
+class ChatbotService {
+
+    private final ChatClient chatClient;
+
+    ChatbotService(ChatClient chatClient) {
+        this.chatClient = chatClient;
+    }
+
+    ChatResponse chat(ChatRequest chatRequest) {
+        UUID chatId = Optional
+            .ofNullable(chatRequest.chatId())
+            .orElse(UUID.randomUUID());
+        DeepSeekModelResponse response = chatClient
+            .prompt()
+            .user(chatRequest.question())
+            .advisors(advisorSpec ->
+                advisorSpec
+                    .param("chat_memory_conversation_id", chatId))
+            .call()
+            .entity(new DeepSeekModelOutputConverter());
+        return new ChatResponse(chatId, response.chainOfThought(), response.answer());
+    }
+
+}

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/DeepSeekModelOutputConverter.java

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+package com.baeldung.springai.deepseek;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.converter.StructuredOutputConverter;
+import org.springframework.lang.NonNull;
+import org.springframework.util.StringUtils;
+
+class DeepSeekModelOutputConverter implements StructuredOutputConverter<DeepSeekModelResponse> {
+
+    private static final Logger logger = LoggerFactory.getLogger(DeepSeekModelOutputConverter.class);
+    private static final String OPENING_THINK_TAG = "<think>";
+    private static final String CLOSING_THINK_TAG = "</think>";
+
+    @Override
+    public DeepSeekModelResponse convert(@NonNull String text) {
+        if (!StringUtils.hasText(text)) {
+            throw new IllegalArgumentException("Text cannot be blank");
+        }
+        int openingThinkTagIndex = text.indexOf(OPENING_THINK_TAG);
+        int closingThinkTagIndex = text.indexOf(CLOSING_THINK_TAG);
+
+        if (openingThinkTagIndex != -1 && closingThinkTagIndex != -1 && closingThinkTagIndex > openingThinkTagIndex) {
+            String chainOfThought = text.substring(openingThinkTagIndex + OPENING_THINK_TAG.length(), closingThinkTagIndex);
+            String answer = text.substring(closingThinkTagIndex + CLOSING_THINK_TAG.length());
+            return new DeepSeekModelResponse(chainOfThought, answer);
+        } else {
+            logger.debug("No <think> tags found in the response. Treating entire text as answer.");
+            return new DeepSeekModelResponse(null, text);
+        }
+    }
+
+    /**
+     * This method is used to define instructions for formatting the AI model's response,
+     * which are appended to the user prompt.
+     * See {@link org.springframework.ai.converter.BeanOutputConverter#getFormat()} for reference.
+     *
+     * However, in the current implementation, we extract only the AI response and its chain of thought,
+     * so no formatting instructions are needed.
+     */
+    @Override
+    public String getFormat() {
+        return null;
+    }
+
+}

spring-ai-2/src/main/java/com/baeldung/springai/deepseek/DeepSeekModelResponse.java

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+package com.baeldung.springai.deepseek;
+
+record DeepSeekModelResponse(String chainOfThought, String answer) {
+}

spring-ai-2/src/main/resources/application-deepseek.properties

@@ -0,0 +1,13 @@
+spring.ai.openai.api-key=${DEEPSEEK_API_KEY}
+spring.ai.openai.base-url=https://api.deepseek.com
+spring.ai.openai.chat.options.model=deepseek-reasoner
+spring.ai.openai.embedding.enabled=false
+
+spring.ai.ollama.chat.options.model=deepseek-r1
+spring.ai.ollama.embedding.enabled=false
+spring.ai.ollama.init.pull-model-strategy=when_missing
+
+spring.ai.bedrock.aws.access-key=${AWS_ACCESS_KEY}
+spring.ai.bedrock.aws.secret-key=${AWS_SECRET_KEY}
+spring.ai.bedrock.aws.region=${AWS_REGION}
+spring.ai.bedrock.converse.chat.options.model=arn:aws:sagemaker:REGION:ACCOUNT_ID:endpoint/ENDPOINT_NAME

spring-ai-2/src/test/java/com/baeldung/springai/deepseek/ChatbotServiceLiveTest.java

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+package com.baeldung.springai.deepseek;
+
+import org.junit.jupiter.api.Test;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.boot.test.context.SpringBootTest;
+
+import static org.assertj.core.api.Assertions.assertThat;
+
+@SpringBootTest
+class ChatbotServiceLiveTest {
+
+    @Autowired
+    private ChatbotService chatbotService;
+
+    @Test
+    void whenChatbotCalledInSequence_thenConversationContextIsMaintained() {
+        ChatRequest chatRequest = new ChatRequest(null, "What was the name of Superman's adoptive mother?");
+        ChatResponse chatResponse = chatbotService.chat(chatRequest);
+
+        assertThat(chatResponse)
+            .isNotNull()
+            .hasNoNullFieldsOrProperties();
+        assertThat(chatResponse.answer())
+            .contains("Martha");
+
+        ChatRequest followUpChatRequest = new ChatRequest(chatResponse.chatId(), "Which bald billionaire hates him?");
+        ChatResponse followUpChatResponse = chatbotService.chat(followUpChatRequest);
+
+        assertThat(followUpChatResponse)
+            .isNotNull()
+            .hasNoNullFieldsOrProperties();
+        assertThat(followUpChatResponse.answer())
+            .contains("Lex Luthor");
+    }
+
+}