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Zhongwei Li
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# LangChain4j Spring Boot Integration - Examples
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Comprehensive implementation examples for Spring Boot integration with LangChain4j.
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## Basic Setup Example
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### Complete Spring Boot Application
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```java
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@SpringBootApplication
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public class Langchain4jApplication {
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public static void main(String[] args) {
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SpringApplication.run(Langchain4jApplication.class, args);
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}
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}
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@Configuration
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public class AiConfiguration {
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@Bean
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@Profile("openai")
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public ChatModel openAiChatModel(@Value("${langchain4j.open-ai.chat-model.api-key}") String apiKey) {
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return OpenAiChatModel.builder()
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.apiKey(apiKey)
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.modelName("gpt-4o-mini")
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.temperature(0.7)
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.maxTokens(1000)
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.logRequests(true)
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.logResponses(true)
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.build();
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}
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@Bean
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public EmbeddingModel openAiEmbeddingModel(@Value("${langchain4j.open-ai.embedding-model.api-key}") String apiKey) {
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return OpenAiEmbeddingModel.builder()
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.apiKey(apiKey)
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.modelName("text-embedding-3-small")
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.dimensions(1536)
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.build();
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}
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}
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@AiService
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interface CustomerSupportAssistant {
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@SystemMessage("You are a helpful customer support agent for TechCorp. " +
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"Be polite, professional, and try to resolve customer issues efficiently. " +
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"If you cannot resolve an issue, escalate to a human agent.")
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String handleInquiry(String customerMessage);
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@UserMessage("Analyze this customer feedback and extract sentiment: {{feedback}}")
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@SystemMessage("Return only: POSITIVE, NEGATIVE, or NEUTRAL")
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String analyzeSentiment(String feedback);
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@UserMessage("Extract key entities from this text: {{text}}")
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@SystemMessage("Return a JSON object with entities as keys and their types as values")
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String extractEntities(String text);
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}
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@RestController
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@RequestMapping("/api/support")
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@RequiredArgsConstructor
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public class CustomerSupportController {
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private final CustomerSupportAssistant assistant;
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@PostMapping("/inquiry")
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public ResponseEntity<SupportResponse> handleInquiry(@RequestBody @Valid SupportRequest request) {
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String response = assistant.handleInquiry(request.getMessage());
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return ResponseEntity.ok(new SupportResponse(response, Instant.now()));
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}
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@PostMapping("/sentiment")
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public ResponseEntity<SentimentResponse> analyzeSentiment(@RequestBody @Valid SentimentRequest request) {
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String sentiment = assistant.analyzeSentiment(request.getFeedback());
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return ResponseEntity.ok(new SentimentResponse(sentiment, Instant.now()));
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}
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@PostMapping("/entities")
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public ResponseEntity<EntitiesResponse> extractEntities(@RequestBody @Valid EntitiesRequest request) {
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String entities = assistant.extractEntities(request.getText());
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return ResponseEntity.ok(new EntitiesResponse(entities, Instant.now()));
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}
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}
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// DTO Classes
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record SupportRequest(String message) {}
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record SupportResponse(String response, Instant timestamp) {}
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record SentimentRequest(String feedback) {}
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record SentimentResponse(String sentiment, Instant timestamp) {}
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record EntitiesRequest(String text) {}
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record EntitiesResponse(String entities, Instant timestamp) {}
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```
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## 2. Custom AI Service Bean Configuration
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**Scenario**: Configure AI services as Spring beans.
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```java
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@Configuration
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public class AiConfig {
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@Bean
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public ChatModel chatModel() {
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return OpenAiChatModel.builder()
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.apiKey(System.getenv("OPENAI_API_KEY"))
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.modelName("gpt-4o-mini")
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.temperature(0.7)
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.build();
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}
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@Bean
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public EmbeddingModel embeddingModel() {
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return OpenAiEmbeddingModel.builder()
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.apiKey(System.getenv("OPENAI_API_KEY"))
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.modelName("text-embedding-3-small")
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.build();
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}
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@Bean
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public DocumentAssistant documentAssistant(ChatModel chatModel) {
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return AiServices.builder(DocumentAssistant.class)
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.chatModel(chatModel)
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.chatMemory(MessageWindowChatMemory.withMaxMessages(10))
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.build();
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}
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}
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interface DocumentAssistant {
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String chat(String message);
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}
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```
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## 3. REST API with AI Service
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**Scenario**: Expose AI functionality via REST endpoints.
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```java
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@RestController
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@RequestMapping("/api/chat")
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public class ChatController {
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private final ChatAssistant assistant;
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@Autowired
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public ChatController(ChatAssistant assistant) {
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this.assistant = assistant;
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}
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@PostMapping
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public ResponseEntity<ChatResponse> chat(@RequestBody ChatRequest request) {
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try {
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String response = assistant.chat(request.getMessage());
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return ResponseEntity.ok(new ChatResponse(response));
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} catch (Exception e) {
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return ResponseEntity.internalServerError()
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.body(new ChatResponse("Error: " + e.getMessage()));
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}
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}
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@PostMapping("/stream")
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public ResponseEntity<StreamingResponseBody> streamChat(@RequestBody ChatRequest request) {
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return ResponseEntity.ok(outputStream -> {
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var streamAssistant = streamingAssistant;
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var stream = streamAssistant.streamChat(request.getMessage());
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stream.onNext(token -> {
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try {
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outputStream.write(token.getBytes());
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outputStream.flush();
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} catch (IOException e) {
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// Handle write error
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}
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}).start();
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});
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}
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}
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@Data
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class ChatRequest {
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private String message;
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}
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@Data
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class ChatResponse {
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private String response;
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}
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```
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## 4. Service with RAG Integration
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**Scenario**: Service layer with document search and retrieval.
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```java
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@Service
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public class KnowledgeBaseService {
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private final DocumentAssistant assistant;
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private final EmbeddingStore<TextSegment> embeddingStore;
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private final EmbeddingModel embeddingModel;
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@Autowired
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public KnowledgeBaseService(
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DocumentAssistant assistant,
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EmbeddingStore<TextSegment> embeddingStore,
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EmbeddingModel embeddingModel) {
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this.assistant = assistant;
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this.embeddingStore = embeddingStore;
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this.embeddingModel = embeddingModel;
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}
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public void ingestDocument(String content, Map<String, Object> metadata) {
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var document = Document.from(content);
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document.metadata().putAll(metadata);
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var ingestor = EmbeddingStoreIngestor.builder()
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.embeddingModel(embeddingModel)
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.embeddingStore(embeddingStore)
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.documentSplitter(DocumentSplitters.recursive(500, 50))
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.build();
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ingestor.ingest(document);
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}
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public String answerQuestion(String question) {
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return assistant.answerAbout(question);
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}
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}
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interface DocumentAssistant {
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String answerAbout(String question);
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}
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```
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## 5. Scheduled Task for Document Updates
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**Scenario**: Periodically update knowledge base.
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```java
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@Service
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public class DocumentUpdateService {
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private final EmbeddingStore<TextSegment> embeddingStore;
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private final EmbeddingModel embeddingModel;
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@Autowired
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public DocumentUpdateService(
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EmbeddingStore<TextSegment> embeddingStore,
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EmbeddingModel embeddingModel) {
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this.embeddingStore = embeddingStore;
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this.embeddingModel = embeddingModel;
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}
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@Scheduled(fixedRate = 86400000) // Daily
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public void updateDocuments() {
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var documents = fetchLatestDocuments();
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var ingestor = EmbeddingStoreIngestor.builder()
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.embeddingModel(embeddingModel)
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.embeddingStore(embeddingStore)
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.build();
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documents.forEach(ingestor::ingest);
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logger.info("Documents updated successfully");
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}
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private List<Document> fetchLatestDocuments() {
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// Fetch from database or external API
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return Collections.emptyList();
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}
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}
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```
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## 6. Controller with Tool Integration
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**Scenario**: AI service with business logic tools.
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```java
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@Service
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public class BusinessLogicService {
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@Tool("Get user by ID")
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public User getUser(@P("user ID") String userId) {
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// Implementation
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return new User(userId);
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}
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@Tool("Calculate discount")
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public double calculateDiscount(@P("purchase amount") double amount) {
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if (amount > 1000) return 0.15;
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if (amount > 500) return 0.10;
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return 0.05;
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}
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}
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@Service
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public class ToolAssistant {
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private final ChatModel chatModel;
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private final BusinessLogicService businessLogic;
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@Autowired
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public ToolAssistant(ChatModel chatModel, BusinessLogicService businessLogic) {
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this.chatModel = chatModel;
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this.businessLogic = businessLogic;
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}
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public String processRequest(String request) {
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return AiServices.builder(Assistant.class)
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.chatModel(chatModel)
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.tools(businessLogic)
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.build()
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.chat(request);
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}
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}
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interface Assistant {
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String chat(String message);
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}
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```
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## 7. Error Handling with Spring Exception Handler
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**Scenario**: Centralized error handling for AI services.
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```java
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@ControllerAdvice
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public class AiExceptionHandler {
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@ExceptionHandler(IllegalArgumentException.class)
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public ResponseEntity<ErrorResponse> handleBadRequest(IllegalArgumentException e) {
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return ResponseEntity.badRequest()
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.body(new ErrorResponse("Invalid input: " + e.getMessage()));
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}
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@ExceptionHandler(Exception.class)
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public ResponseEntity<ErrorResponse> handleError(Exception e) {
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logger.error("Error in AI service", e);
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return ResponseEntity.internalServerError()
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.body(new ErrorResponse("An error occurred: " + e.getMessage()));
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}
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}
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@Data
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class ErrorResponse {
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private String message;
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}
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```
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## 8. Configuration Properties
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**Scenario**: Externalize AI configuration.
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```java
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@Configuration
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@ConfigurationProperties(prefix = "app.ai")
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@Data
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public class AiProperties {
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private String openaiApiKey;
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private String openaiModel = "gpt-4o-mini";
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private double temperature = 0.7;
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private int maxTokens = 2000;
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private String embeddingModel = "text-embedding-3-small";
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private int memorySize = 10;
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private String vectorStoreType = "in-memory";
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}
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// application.yml
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app:
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ai:
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openai-api-key: ${OPENAI_API_KEY}
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openai-model: gpt-4o-mini
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temperature: 0.7
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max-tokens: 2000
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embedding-model: text-embedding-3-small
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memory-size: 10
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vector-store-type: pinecone
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```
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## 9. Integration Testing
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**Scenario**: Test AI services with Spring Boot Test.
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```java
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@SpringBootTest
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class ChatServiceTest {
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@MockBean
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private ChatModel chatModel;
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@Autowired
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private ChatService chatService;
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@Test
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void testChat() {
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when(chatModel.chat("Hello"))
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.thenReturn("Hi there!");
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String response = chatService.chat("Hello");
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assertEquals("Hi there!", response);
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}
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}
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```
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## 10. Async Processing with CompletableFuture
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**Scenario**: Non-blocking AI service calls.
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```java
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@Service
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@EnableAsync
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public class AsyncChatService {
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private final ChatModel chatModel;
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@Autowired
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public AsyncChatService(ChatModel chatModel) {
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this.chatModel = chatModel;
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}
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@Async
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public CompletableFuture<String> chatAsync(String message) {
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try {
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String response = chatModel.chat(message);
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return CompletableFuture.completedFuture(response);
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} catch (Exception e) {
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return CompletableFuture.failedFuture(e);
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}
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}
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}
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// Usage in controller
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@RestController
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public class AsyncController {
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@Autowired
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private AsyncChatService asyncChatService;
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@PostMapping("/chat/async")
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public CompletableFuture<ResponseEntity<String>> chatAsync(@RequestBody ChatRequest request) {
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return asyncChatService.chatAsync(request.getMessage())
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.thenApply(ResponseEntity::ok)
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.exceptionally(e -> ResponseEntity.internalServerError().build());
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}
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}
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```
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## Configuration Examples
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### Maven Dependency
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```xml
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-spring-boot-starter</artifactId>
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<version>0.27.0</version>
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</dependency>
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```
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### Gradle
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```gradle
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implementation 'dev.langchain4j:langchain4j-spring-boot-starter:0.27.0'
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```
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Reference in New Issue
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