spring.application.name=mongodb
spring.data.mongodb.database=rag
spring.ai.vectorstore.mongodb.collection-name=vector_store
spring.ai.vectorstore.mongodb.initialize-schema=true
spring.threads.virtual.enabled=true
management.endpoints.web.exposure.include=*
management.endpoint.health.show-details=always

id: 1, name: Prancer, description: "demonic, neurotic, man-hating..."

@Bean
ApplicationRunner mongoDbInitializer(MongoTemplate template, VectorStore vectorStore,
    @Value("${spring.ai.vectorstore.mongodb.collection-name}") String collectionName,
    ObjectMapper objectMapper) {
  return args -> {
    if (template.collectionExists(collectionName) && template.estimatedCount(collectionName) > 0) return;
    var documentData = DOGS_JSON_FILE.getContentAsString(Charset.defaultCharset());
    var jsonNode = objectMapper.readTree(documentData);
    jsonNode.spliterator().forEachRemaining(jsonNode1 -> {
      var id = jsonNode1.get("id").intValue();
      var name = jsonNode1.get("name").textValue();
      var description = jsonNode1.get("description").textValue();
      var document = new Document(String.format("id: %d, name: %s, description: %s", id, name, description));
      vectorStore.add(List.of(document));
    });
  };
}

@Controller
@ResponseBody
class AdoptionController {
  private final ChatClient ai;
  private final InMemoryChatMemoryRepository memoryRepository;

  AdoptionController(ChatClient.Builder ai, VectorStore vectorStore) {
    var system = """
      You are an AI-powered assistant to help people adopt a dog from Pooch Palace. 
      Information about dogs will be provided. If none, respond politely indicating no dogs available.
    """;
    this.memoryRepository = new InMemoryChatMemoryRepository();
    this.ai = ai.defaultSystem(system)
               .defaultAdvisors(new QuestionAnswerAdvisor(vectorStore))
               .build();
  }
  // Các endpoint sẽ được định nghĩa tiếp theo
}

@GetMapping("/{user}/dogs/assistant")
String inquire(@PathVariable String user, @RequestParam String question) {
  var memory = MessageWindowChatMemory.builder()
                  .chatMemoryRepository(memoryRepository)
                  .maxMessages(10)
                  .build();
  var memoryAdvisor = MessageChatMemoryAdvisor.builder(memory).build();
  return this.ai.prompt()
               .user(question)
               .advisors(a -> a.advisors(memoryAdvisor).param(ChatMemory.CONVERSATION_ID, user))
               .call()
               .content();
}

./mvnw -DskipTests -Pnative native:compile

./mvnw -DskipTests -Pnative spring-boot:build-image