[서은영] LLM 날씨 조회 제출합니다. #24

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3UN0 wants to merge 1 commit into next-step:main from 3UN0:3UN0

README.md

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-    # spring-sunshine-precourse
+    # Spring Sunshine - 날씨 조회 서비스
+    스프링 프레임워크를 사용한 AI 기반 날씨 조회 및 복장 추천 웹 서비스입니다.
+    ## 주요 기능
+    ### 1. 다양한 위치 지원
+    - **도시**: Seoul, Tokyo, NewYork, Paris, London
+    - **권역**: 수도권(Sudogwon), 영남권(Yeongnam)
+    - **구/군**: 강남구(Gangnam), 종로구(Jongno), 마포구(Mapo)
+    ### 2. AI 기반 날씨 요약
+    - Google Gemini AI를 사용한 자연어 날씨 요약
+    - 캐시 기능으로 비용 절약 및 성능 향상
+    - 토큰 사용량 및 비용 추정치 로깅
+    ### 3. 스마트 복장 추천
+    - 기온, 체감온도, 날씨 상태 기반 복장 추천
+    - 바람, 습도 등 세부 기상 조건 고려
+    ### 4. 사용량 추적
+    - 입력/출력 토큰 수 모니터링
+    - API 호출 비용 추정
+    - 캐시 사용 여부 추적
+    ## API 엔드포인트
+    ### 새로운 AI 기반 API
+    #### 1. 단일 위치 AI 요약 조회
+    ```
+    GET /api/v1/weather/summary/{location}?useCache=true
+    ```
+    **예시:**
+    ```bash
+    curl "http://localhost:8080/api/v1/weather/summary/Seoul?useCache=true"
+    curl "http://localhost:8080/api/v1/weather/summary/Gangnam"
+    curl "http://localhost:8080/api/v1/weather/summary/Sudogwon"
+    ```
+    **응답 예시:**
+    ```json
+    {
+      "city": "Seoul",
+      "temperature": 15.2,
+      "apparentTemperature": 13.8,
+      "skyCondition": "부분 흐림",
+      "humidity": 65.0,
+      "windSpeed": 3.2,
+      "aiSummary": "현재 서울의 기온은 15.2°C이며, 체감온도는 13.8°C입니다. 하늘은 부분적으로 흐리고 바람은 약합니다.",
+      "clothingRecommendation": "얇은 가디건, 긴팔 티셔츠, 면바지, 청바지",
+      "fromCache": false,
+      "usageInfo": {
+        "inputTokens": 45,
+        "outputTokens": 32,
+        "totalTokens": 77,
+        "modelName": "gemini-2.5-flash-lite",
+        "cacheUsed": false,
+        "estimatedCost": 0.000013
+      }
+    }
+    ```
+    #### 2. 다중 위치 AI 요약 조회
+    ```
+    GET /api/v1/weather/summary?locations=Seoul,Gangnam,Sudogwon&useCache=true
+    ```
+    #### 3. 캐시 설정 변경
+    ```
+    POST /api/v1/weather/cache?enabled=true
+    ```
+    ### 기존 호환 API
+    #### 기본 날씨 정보 조회
+    ```
+    GET /api/v1/weather/{city}
+    GET /api/v1/weather?cities=Seoul,Tokyo
+    ```
+    ## 지원 위치 목록
+    | 타입 | 위치명 | 설명 |
+    |------|--------|------|
+    | 도시 | Seoul | 서울 |
+    | 도시 | Tokyo | 도쿄 |
+    | 도시 | NewYork | 뉴욕 |
+    | 도시 | Paris | 파리 |
+    | 도시 | London | 런던 |
+    | 구/군 | Gangnam | 강남구 |
+    | 구/군 | Jongno | 종로구 |
+    | 구/군 | Mapo | 마포구 |
+    | 권역 | Sudogwon | 수도권 |
+    | 권역 | Yeongnam | 영남권 |
+    ## 복장 추천 기준
+    | 체감온도 | 추천 복장 |
+    |----------|----------|
+    | 28°C 이상 | 민소매, 반팔, 반바지, 원피스 |
+    | 23-27°C | 반팔, 얇은 셔츠, 반바지, 면바지 |
+    | 20-22°C | 얇은 가디건, 긴팔 티셔츠, 면바지, 청바지 |
+    | 17-19°C | 얇은 니트, 맨투맨, 가디건, 청바지 |
+    | 12-16°C | 자켓, 가디건, 청바지, 면바지 |
+    | 9-11°C | 트렌치코트, 야상, 니트, 청바지, 스타킹 |
+    | 5-8°C | 울코트, 히트텍, 니트, 청바지 |
+    | 5°C 미만 | 패딩, 두꺼운 코트, 목도리, 장갑, 기모제품 |
+    **추가 조건:**
+    - 흐림/비: 우산 필수
+    - 강풍(7m/s 이상): 바람막이 추천
+    - 고습도(80% 이상): 통풍이 잘 되는 소재 권장
+    ## 실행 방법
+    ```bash
+    ./gradlew bootRun
+    ```
+    ## 환경 설정
+    `application.properties`에서 다음 설정을 확인하세요:
+    ```properties
+    spring.ai.google.genai.api-key=YOUR_GEMINI_API_KEY
+    spring.ai.google.genai.chat.options.model=gemini-2.5-flash-lite
+    ```

build.gradle.kts

            
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    plugins {

        id("org.springframework.boot") version "3.3.1"

        id("io.spring.dependency-management") version "1.1.5"

        id("org.springframework.boot") version "3.5.8"

        id("io.spring.dependency-management") version "1.1.7"

        kotlin("plugin.jpa") version "1.9.24"

        kotlin("jvm") version "1.9.24"

        kotlin("plugin.spring") version "1.9.24"

    @@ -33,6 +33,8 @@ dependencies {
  
        testImplementation("org.springframework.boot:spring-boot-starter-test")

        testImplementation("org.jetbrains.kotlin:kotlin-test-junit5")

        testRuntimeOnly("org.junit.platform:junit-platform-launcher")

        implementation(platform("org.springframework.ai:spring-ai-bom:1.1.2"))

        implementation("org.springframework.ai:spring-ai-starter-model-google-genai")

    }

    kotlin {

    @@ -44,3 +46,7 @@ kotlin {
  
    tasks.withType<Test> {

        useJUnitPlatform()

    }

    springBoot {

        mainClass.set("sunshine.Application")

    }

src/main/java/study/Function.java

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+    package study;
+    import java.time.LocalDate;
+    import org.springframework.context.annotation.Bean;
+    import org.springframework.context.annotation.Configuration;
+    import org.springframework.context.annotation.Description;
+    @Configuration
+    class Function {
+        @Bean
+        @Description("Calculate a date after adding days from today")
+        public java.util.function.Function<AddDaysRequest, DateResponse> addDaysFromToday() {
+            return request -> {
+                LocalDate result = LocalDate.now().plusDays(request.days());
+                return new DateResponse(result.toString());
+            };
+        }
+        public record AddDaysRequest(int days) {
+        }
+        public record DateResponse(String date) {
+        }
+    }

src/main/java/study/JokeController.java

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+    package study;
+    import java.util.Map;
+    import org.springframework.ai.chat.client.ChatClient;
+    import org.springframework.ai.chat.messages.UserMessage;
+    import org.springframework.ai.chat.model.ChatResponse;
+    import org.springframework.ai.chat.prompt.Prompt;
+    import org.springframework.ai.chat.prompt.PromptTemplate;
+    import org.springframework.ai.chat.prompt.SystemPromptTemplate;
+    import org.springframework.web.bind.annotation.GetMapping;
+    import org.springframework.web.bind.annotation.RequestParam;
+    import org.springframework.web.bind.annotation.RestController;
+    @RestController
+    public class JokeController {
+        private final ChatClient client;
+        public JokeController(ChatClient.Builder builder) {
+            this.client = builder.build();
+        }
+        @GetMapping("/joke")
+        public String joke(
+                @RequestParam(defaultValue = "Tell me a joke") String message,
+                @RequestParam(defaultValue = "Programming") String topic) {
+            var template = new PromptTemplate("Tell me a joke about {topic}");
+            var prompt = template.render(Map.of("topic", topic));
+            return client.prompt(prompt)
+                    .call()
+                    .content();
+        }
+        @GetMapping("/joke2")
+        public ChatResponse joke2(
+                @RequestParam(defaultValue = "Bob") String name,
+                @RequestParam(defaultValue = "pirate") String voice) {
+            var template = new PromptTemplate("Tell me a joke about {topic}");
+            var userMessage = new UserMessage("""
+                    Tell me about three famous pirates from the Golden Age of Piracy and what they did.
+                    Write at least one sentence for each pirate.
+                    """
+            );
+            var systemPromptTemplate = new SystemPromptTemplate("""
+                    You are a helpful AI assistant.
+                    You are an AI assistant that helps people find information.
+                    Your name is {name}.
+                    You should reply to the user's request using your name and in the style of a {voice}.
+                    """
+            );
+            var systemMessage =
+                    systemPromptTemplate.createMessage(Map.of("name", name, "voice", voice));
+            var prompt = new Prompt(userMessage, systemMessage);
+            client.prompt(prompt).call().chatResponse();
+            return client.prompt(prompt)
+                    .call()
+                    .chatResponse();
+        }
+    //
+    //    @GetMapping("/actors")
+    //    public ActorFilms actors(
+    //            @RequestParam(defaultValue = "Bob") String actor
+    //    ) {
+    //
+    //        var beanOutputConverter = new BeanOutputConverter<>(ActorFilms.class);
+    //        var format = beanOutputConverter.getFormat();
+    //        var userMessage = """
+    //            Generate the filmography of 5 movies for {actor}.
+    //            {format}
+    //            """;
+    //        var promptTemplate = new PromptTemplate(Map.of("actor", actor, "format", format));
+    //        var prompt = promptTemplate.create();
+    //        beanOutputConverter.convert(chatClient.prompt(prompt).call().chatResponse().getResult().getOutput().getText());
+    //
+    //
+    //        return
+    //
+    //    }
+    //
+    //    public Vase
+    }

src/main/java/study/StudyApplication.java

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+    package study;
+    import org.springframework.boot.SpringApplication;
+    import org.springframework.boot.autoconfigure.SpringBootApplication;
+    @SpringBootApplication(scanBasePackages = "study")
+    class StudyApplication {
+      public static void main(String[] args) {
+        SpringApplication.run(StudyApplication.class, args);
+      }
+    }

src/main/java/sunshine/Application.java

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@@ Expand Up / @@ -3,7 +3,7 @@ @@
     import org.springframework.boot.SpringApplication;
     import org.springframework.boot.autoconfigure.SpringBootApplication;
-    @SpringBootApplication
+    @SpringBootApplication(scanBasePackages = "sunshine")
     public class Application {
         public static void main(String[] args) {
             SpringApplication.run(Application.class, args);
@@ Expand Down @@

src/main/java/sunshine/RestTemplateConfig.java

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+    package sunshine;
+    import org.springframework.context.annotation.Bean;
+    import org.springframework.context.annotation.Configuration;
+    import org.springframework.web.client.RestTemplate;
+    /**
+     * RestTemplate 설정
+     */
+    @Configuration
+    public class RestTemplateConfig {
+        @Bean
+        public RestTemplate restTemplate() {
+            return new RestTemplate();
+        }
+    }

src/main/java/sunshine/config/AiConfig.java

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+    package sunshine.config;
+    import org.springframework.ai.chat.client.ChatClient;
+    import org.springframework.ai.google.genai.GoogleGenAiChatModel;
+    import org.springframework.context.annotation.Bean;
+    import org.springframework.context.annotation.Configuration;
+    @Configuration
+    public class AiConfig {
+        @Bean
+        public ChatClient chatClient(GoogleGenAiChatModel chatModel) {
+            return ChatClient.builder(chatModel).build();
+        }
+    }

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