openai연동 및 ai 서비스 생성

src/main/java/com/caliverse/admin/domain/api/AIController.java

@@ -0,0 +1,27 @@
+package com.caliverse.admin.domain.api;
+
+import com.caliverse.admin.domain.request.AIRequest;
+import com.caliverse.admin.domain.response.AIResponse;
+import com.caliverse.admin.domain.service.AIService;
+import io.swagger.v3.oas.annotations.tags.Tag;
+import lombok.RequiredArgsConstructor;
+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.RequestMapping;
+import org.springframework.web.bind.annotation.RestController;
+
+@Tag(name = "AI 관련", description = "AI api 입니다.")
+@RestController
+@RequiredArgsConstructor
+@RequestMapping("/api/v1/ai")
+
+public class AIController {
+
+    private final AIService aiService;
+
+    @PostMapping("/analyze")
+    public ResponseEntity<AIResponse> aiAnalyze(@RequestBody AIRequest dataRequest){
+        return ResponseEntity.ok().body(aiService.aiMessageAnalyze(dataRequest));
+    }
+}

src/main/java/com/caliverse/admin/domain/entity/AI/AIRequestType.java

@@ -0,0 +1,6 @@
+package com.caliverse.admin.domain.entity.AI;
+
+public enum AIRequestType {
+    BUSINESS_LOG,
+    MAIL
+}

src/main/java/com/caliverse/admin/domain/entity/AI/AIRole.java

@@ -0,0 +1,7 @@
+package com.caliverse.admin.domain.entity.AI;
+
+public enum AIRole {
+    user,
+    system,
+    assistant
+}

src/main/java/com/caliverse/admin/domain/request/AIRequest.java

@@ -0,0 +1,19 @@
+package com.caliverse.admin.domain.request;
+
+import com.caliverse.admin.domain.entity.AI.AIRequestType;
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.util.Map;
+
+@Data
+@Builder
+@AllArgsConstructor
+@NoArgsConstructor
+public class AIRequest {
+    private String message;
+    private AIRequestType type;
+    private Map<String, Object> conditions;
+}

src/main/java/com/caliverse/admin/domain/request/OpenAIRequest.java

@@ -0,0 +1,20 @@
+package com.caliverse.admin.domain.request;
+
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.util.List;
+import java.util.Map;
+
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+@Builder
+public class OpenAIRequest {
+    private String model;
+    private List<Map<String, String>> messages;
+    @Builder.Default
+    private double temperature = 0.7;
+}

src/main/java/com/caliverse/admin/domain/response/AIResponse.java

@@ -0,0 +1,40 @@
+package com.caliverse.admin.domain.response;
+
+import com.caliverse.admin.history.domain.DynamodbDataInitializeHistory;
+import com.fasterxml.jackson.annotation.JsonInclude;
+import com.fasterxml.jackson.annotation.JsonProperty;
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.util.List;
+
+@Data
+@Builder
+@AllArgsConstructor
+@NoArgsConstructor
+public class AIResponse {
+    private int status;
+
+    private String result;
+
+    @JsonProperty("data")
+    private ResultData resultData;
+
+    @Data
+    @Builder
+    @JsonInclude(JsonInclude.Include.NON_NULL)
+    public static class ResultData {
+
+        private String message;
+        private String result;
+
+        private int total;
+        @JsonProperty("total_all")
+        private int totalAll;
+        @JsonProperty("page_no")
+        private int pageNo;
+    }
+
+}

src/main/java/com/caliverse/admin/domain/response/OpenAIResponse.java

@@ -0,0 +1,33 @@
+package com.caliverse.admin.domain.response;
+
+import lombok.AllArgsConstructor;
+import lombok.Builder;
+import lombok.Data;
+import lombok.NoArgsConstructor;
+
+import java.util.List;
+
+@Data
+@NoArgsConstructor
+@AllArgsConstructor
+@Builder
+public class OpenAIResponse {
+    private List<Choice> choices;
+
+    @Data
+    @NoArgsConstructor
+    @AllArgsConstructor
+    @Builder
+    public static class Choice {
+        private Message message;
+    }
+
+    @Data
+    @NoArgsConstructor
+    @AllArgsConstructor
+    @Builder
+    public static class Message {
+        private String role;
+        private String content;
+    }
+}

src/main/java/com/caliverse/admin/domain/service/AIService.java

@@ -0,0 +1,110 @@
+package com.caliverse.admin.domain.service;
+
+import com.caliverse.admin.domain.dao.admin.MailMapper;
+import com.caliverse.admin.domain.entity.AI.AIRequestType;
+import com.caliverse.admin.domain.entity.AI.AIRole;
+import com.caliverse.admin.domain.entity.Mail;
+import com.caliverse.admin.domain.request.AIRequest;
+import com.caliverse.admin.domain.request.LogGenericRequest;
+import com.caliverse.admin.domain.request.OpenAIRequest;
+import com.caliverse.admin.domain.response.AIResponse;
+import com.caliverse.admin.domain.response.OpenAIResponse;
+import com.caliverse.admin.global.common.code.CommonCode;
+import com.caliverse.admin.global.common.constants.CommonConstants;
+import com.caliverse.admin.global.common.utils.CommonUtils;
+import com.caliverse.admin.logs.Indicatordomain.GenericMongoLog;
+import com.caliverse.admin.logs.logservice.businesslogservice.BusinessLogGenericService;
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Service;
+
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Map;
+
+@Slf4j
+@Service
+@RequiredArgsConstructor
+public class AIService {
+    @Autowired
+    private ObjectMapper mapper;
+
+    private final OpenAIService openAIService;
+    private final BusinessLogGenericService businessLogGenericService;
+    private final MailMapper mailMapper;
+
+    public AIResponse aiMessageAnalyze(AIRequest dataRequest){
+        List<Map<String,String>> messages = initMessage();
+
+        List<?> data = getDataList(dataRequest.getType(), dataRequest.getConditions());
+
+        messages = splitDataToMessages(messages, data, dataRequest.getMessage());
+
+        OpenAIRequest openAIRequest = new OpenAIRequest();
+        openAIRequest.setMessages(messages);
+
+        OpenAIResponse result = openAIService.askOpenAI(openAIRequest);
+        log.info(result.getChoices().get(0).getMessage().getContent());
+        return AIResponse.builder()
+                .resultData(AIResponse.ResultData.builder()
+                        .result(result.getChoices().get(0).getMessage().getContent())
+                        .build())
+                .status(CommonCode.SUCCESS.getHttpStatus())
+                .result(CommonCode.SUCCESS.getResult())
+                .build();
+    }
+
+    private List<Map<String, String>> splitDataToMessages(List<Map<String,String>> messages, List<?> dataList, String userMessage) {
+        String dataJson;
+        try {
+            dataJson = mapper.writerWithDefaultPrettyPrinter().writeValueAsString(dataList);
+        } catch (JsonProcessingException e) {
+            throw new RuntimeException("JSON 변환 실패", e);
+        }
+        messages.add(CommonUtils.getAIMessage(AIRole.user, messageMerge(userMessage, dataJson)));
+
+        return messages;
+    }
+
+    private String messageMerge(String message, String data){
+        return String.format("사용자 질문: %s\n\n아래는 시스템이 제공하는 데이터입니다.\n%s", message, data);
+    }
+
+    private List<Map<String,String>> initMessage(){
+        List<Map<String,String>> messages = new ArrayList<>();
+        messages.add(CommonUtils.getAIMessage(AIRole.system,
+                """
+                            너는 프론트엔드 게시용 데이터를 생성하는 게임 데이터 분석 AI야. \
+                            사용자는 게임 로그 데이터와 함께 다양한 질문을 보낼 수 있어. \
+                            너는 항상 HTML 또는 React 코드 형식으로 응답해야 해. \
+                            응답에는 반드시 다음 항목을 포함해줘: \
+                            1) 분석된 내용 설명 \
+                            2) 분석된 요약 결과 (표 또는 문단) \
+                            3) 시각화 차트 (예: bar chart, pie chart 등) \
+                            응답은 반드시 한국어로 작성해. \
+                            절대로 파이썬, Java, Node.js 코드 같은 것은 포함하지 마. \
+                            사용자의 웹에 그대로 게시될 수 있는 코드만 생성해. \
+                            React를 쓸 경우, React 18 기준 코드로 TailwindCSS 기반의 스타일을 사용해줘.
+                        """));
+
+        return messages;
+    }
+
+    private List<?> getDataList(AIRequestType type, Map<String, Object> conditions){
+        switch (type){
+            case BUSINESS_LOG -> {
+                LogGenericRequest logReq = mapper.convertValue(conditions, LogGenericRequest.class);
+                List<GenericMongoLog> logs = businessLogGenericService.loadBusinessLogData(logReq, GenericMongoLog.class, true);
+                return logs;
+            }
+            case MAIL -> {
+                List<Mail> mailList = mailMapper.getMailList(conditions);
+                return mailList;
+            }
+            default -> throw new RuntimeException("Not Type");
+        }
+    }
+}

src/main/java/com/caliverse/admin/domain/service/OpenAIService.java

@@ -0,0 +1,358 @@
+package com.caliverse.admin.domain.service;
+
+import com.caliverse.admin.domain.request.OpenAIRequest;
+import com.caliverse.admin.domain.response.OpenAIResponse;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.core.io.FileSystemResource;
+import org.springframework.stereotype.Service;
+import org.springframework.util.LinkedMultiValueMap;
+import org.springframework.util.MultiValueMap;
+import org.springframework.web.client.RestTemplate;
+import org.springframework.http.*;
+
+import java.io.File;
+import java.util.Collections;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+
+@RequiredArgsConstructor
+@Service
+@Slf4j
+public class OpenAIService {
+    private final RestTemplate restTemplate;
+
+    @Value("${open-ai.url}")
+    private String api_url;
+
+    @Value("${open-ai.key}")
+    private String api_key;
+
+    @Value("${open-ai.chatModel}")
+    private String api_chat_model;
+
+    @Value("${open-ai.assistantsModel}")
+    private String api_assistants_model;
+
+    public OpenAIResponse askOpenAI(OpenAIRequest request) {
+        request.setModel(api_chat_model);
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setContentType(MediaType.APPLICATION_JSON);
+        headers.setBearerAuth(api_key);
+
+        HttpEntity<OpenAIRequest> entity = new HttpEntity<>(request, headers);
+
+        ResponseEntity<OpenAIResponse> response = restTemplate.exchange(
+                api_url + "chat/completions",
+                HttpMethod.POST,
+                entity,
+                OpenAIResponse.class
+        );
+
+        return response.getBody();
+    }
+
+    // 파일 업로드 메서드
+    public String uploadFile(String filePath) {
+        String url = "https://api.openai.com/v1/files";
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+        headers.setContentType(MediaType.MULTIPART_FORM_DATA);
+
+        MultiValueMap<String, Object> body = new LinkedMultiValueMap<>();
+        body.add("file", new FileSystemResource(new File(filePath)));
+        body.add("purpose", "assistants");
+
+        HttpEntity<MultiValueMap<String, Object>> requestEntity = new HttpEntity<>(body, headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.POST,
+                requestEntity,
+                Map.class
+        );
+
+        log.info("File uploaded successfully: {}", response.getBody());
+        return (String) response.getBody().get("id");
+    }
+
+    // Assistant 생성 메서드
+    public String createAssistant(String name, String instructions) {
+        String url = "https://api.openai.com/v1/assistants";
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+        headers.setContentType(MediaType.APPLICATION_JSON);
+
+        Map<String, Object> body = new HashMap<>();
+        body.put("model", api_assistants_model);
+        body.put("name", name);
+        body.put("instructions", instructions);
+        body.put("tools", List.of(Map.of("type", "retrieval")));
+
+        HttpEntity<Map<String, Object>> requestEntity = new HttpEntity<>(body, headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.POST,
+                requestEntity,
+                Map.class
+        );
+
+        log.info("Assistant created successfully: {}", response.getBody());
+        return (String) response.getBody().get("id");
+    }
+
+    // Thread 생성 메서드
+    public String createThread() {
+        String url = "https://api.openai.com/v1/threads";
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+        headers.setContentType(MediaType.APPLICATION_JSON);
+
+        Map<String, Object> body = new HashMap<>();
+
+        HttpEntity<Map<String, Object>> requestEntity = new HttpEntity<>(body, headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.POST,
+                requestEntity,
+                Map.class
+        );
+
+        log.info("Thread created successfully: {}", response.getBody());
+        return (String) response.getBody().get("id");
+    }
+
+    // Thread에 메시지 추가 메서드
+    public String addMessageToThread(String threadId, String content, String fileId) {
+        String url = "https://api.openai.com/v1/threads/" + threadId + "/messages";
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+        headers.setContentType(MediaType.APPLICATION_JSON);
+
+        Map<String, Object> body = new HashMap<>();
+        body.put("role", "user");
+        body.put("content", content);
+
+        if (fileId != null && !fileId.isEmpty()) {
+            body.put("file_ids", Collections.singletonList(fileId));
+        }
+
+        HttpEntity<Map<String, Object>> requestEntity = new HttpEntity<>(body, headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.POST,
+                requestEntity,
+                Map.class
+        );
+
+        log.info("Message added to thread successfully: {}", response.getBody());
+        return (String) response.getBody().get("id");
+    }
+
+    // Run 실행 메서드
+    public String startRun(String threadId, String assistantId) {
+        String url = "https://api.openai.com/v1/threads/" + threadId + "/runs";
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+        headers.setContentType(MediaType.APPLICATION_JSON);
+
+        Map<String, Object> body = new HashMap<>();
+        body.put("assistant_id", assistantId);
+
+        HttpEntity<Map<String, Object>> requestEntity = new HttpEntity<>(body, headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.POST,
+                requestEntity,
+                Map.class
+        );
+
+        log.info("Run started successfully: {}", response.getBody());
+        return (String) response.getBody().get("id");
+    }
+
+    // Run 상태 확인 메서드
+    public Map<String, Object> checkRunStatus(String threadId, String runId) {
+        String url = "https://api.openai.com/v1/threads/" + threadId + "/runs/" + runId;
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+
+        HttpEntity<Void> requestEntity = new HttpEntity<>(headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.GET,
+                requestEntity,
+                Map.class
+        );
+
+        log.debug("Run status: {}", response.getBody());
+        return response.getBody();
+    }
+
+    // Thread의 메시지 목록 조회 메서드
+    public List<Map<String, Object>> listMessages(String threadId) {
+        String url = "https://api.openai.com/v1/threads/" + threadId + "/messages";
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+
+        HttpEntity<Void> requestEntity = new HttpEntity<>(headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.GET,
+                requestEntity,
+                Map.class
+        );
+
+        log.debug("Thread messages: {}", response.getBody());
+        return (List<Map<String, Object>>) response.getBody().get("data");
+    }
+
+    // 마지막 Assistant 메시지 추출 메서드
+    public String extractLastAssistantMessage(String threadId) {
+        List<Map<String, Object>> messages = listMessages(threadId);
+
+        for (Map<String, Object> message : messages) {
+            if ("assistant".equals(message.get("role"))) {
+                List<Map<String, Object>> content = (List<Map<String, Object>>) message.get("content");
+                if (content != null && !content.isEmpty()) {
+                    for (Map<String, Object> contentItem : content) {
+                        if ("text".equals(contentItem.get("type"))) {
+                            Map<String, Object> text = (Map<String, Object>) contentItem.get("text");
+                            return (String) text.get("value");
+                        }
+                    }
+                }
+                break;  // 가장 최신 assistant 메시지만 처리
+            }
+        }
+
+        return "No assistant response found";
+    }
+
+    // 파일 삭제 메서드
+    public boolean deleteFile(String fileId) {
+        String url = "https://api.openai.com/v1/files/" + fileId;
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+
+        HttpEntity<Void> requestEntity = new HttpEntity<>(headers);
+
+        try {
+            ResponseEntity<Map> response = restTemplate.exchange(
+                    url,
+                    HttpMethod.DELETE,
+                    requestEntity,
+                    Map.class
+            );
+
+            log.info("File deleted successfully: {}", response.getBody());
+            return true;
+        } catch (Exception e) {
+            log.error("Error deleting file: {}", e.getMessage());
+            return false;
+        }
+    }
+
+    // Assistant 가져오기 또는 생성 메서드
+    public String getOrCreateAssistant() {
+        String url = "https://api.openai.com/v1/assistants";
+
+        HttpHeaders headers = new HttpHeaders();
+        headers.setBearerAuth(api_key);
+
+        HttpEntity<Void> requestEntity = new HttpEntity<>(headers);
+
+        ResponseEntity<Map> response = restTemplate.exchange(
+                url,
+                HttpMethod.GET,
+                requestEntity,
+                Map.class
+        );
+
+        List<Map<String, Object>> assistants = (List<Map<String, Object>>) response.getBody().get("data");
+
+        // 데이터 분석 어시스턴트 찾기
+        for (Map<String, Object> assistant : assistants) {
+            if ("Data Analyzer".equals(assistant.get("name"))) {
+                return (String) assistant.get("id");
+            }
+        }
+
+        // 없으면 새로 생성
+        return createAssistant("Data Analyzer",
+                "You are a data analysis assistant. Analyze the provided JSON data and generate visualizations. " +
+                        "Your responses should be in HTML format with appropriate visualizations using charts. " +
+                        "Focus on identifying patterns, trends, and insights from the data. " +
+                        "Use Korean language for all responses.");
+    }
+
+    // 전체 비동기 프로세스 실행 및 결과 대기 메서드
+    public String processDataAnalysisAndWait(String filePath, String question) {
+        try {
+            // 1. 파일 업로드
+            String fileId = uploadFile(filePath);
+
+            // 2. Assistant 얻기 또는 생성
+            String assistantId = getOrCreateAssistant();
+
+            // 3. Thread 생성
+            String threadId = createThread();
+
+            // 4. 메시지 추가
+            addMessageToThread(threadId, question, fileId);
+
+            // 5. Run 실행
+            String runId = startRun(threadId, assistantId);
+
+            // 6. 완료 대기 (최대 60초, 3초마다 체크)
+            String status = "queued";
+            int maxAttempts = 20;
+            int attempts = 0;
+
+            while (!status.equals("completed") && attempts < maxAttempts) {
+                Thread.sleep(3000);
+                Map<String, Object> runStatus = checkRunStatus(threadId, runId);
+                status = (String) runStatus.get("status");
+
+                if (status.equals("failed") || status.equals("cancelled")) {
+                    throw new RuntimeException("Run failed with status: " + status);
+                }
+
+                attempts++;
+            }
+
+            if (!status.equals("completed")) {
+                throw new RuntimeException("Run timed out after 60 seconds");
+            }
+
+            // 7. 응답 메시지 추출
+            String result = extractLastAssistantMessage(threadId);
+
+            // 8. 파일 정리 (선택적)
+            deleteFile(fileId);
+
+            return result;
+
+        } catch (Exception e) {
+            log.error("Error in data analysis process: {}", e.getMessage());
+            throw new RuntimeException("Data analysis failed: " + e.getMessage(), e);
+        }
+    }
+}

src/main/resources/config/application.yml

@@ -1,4 +1,8 @@
 spring:
+  servlet:
+    multipart:
+      max-file-size: 5MB
+      max-request-size: 10MB
   ## deploy
 #  profiles:
 #    active: stage
@@ -25,4 +29,15 @@ spring:
 password:
   expiration-days: 180
 
+open-ai:
+  key: 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
+  url: https://api.openai.com/v1/
+  chatModel: gpt-4o
+  assistantsModel: gpt-4-1106-preview
+
+claude:
+  key: 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
+  model: claude-3-7-sonnet-20250219
+  url: https://api.anthropic.com/v1/messages
+