[UPDATE] Experiments API에 MLflow 연동 로직 및 상세 조회 처리 추가, 엔티티 필드 업데이트 및 응답 처리 개선 (ExperimentsController, ExperimentsEntity)

src/main/java/kr/re/etri/autoflow/controllers/ExperimentsController.java

@@ -128,17 +128,15 @@ public class ExperimentsController {
     @PostMapping
     public Mono<ResponseEntity<ExperimentsEntity>> createExperiment(@RequestBody ExperimentsEntity experiment) {
 
-        // 1️⃣ DB 저장
         ExperimentsEntity saved = experimentsService.save(experiment);
 
-        // 2️⃣ Kubeflow payload
         Map<String, Object> kubeflowPayload = new HashMap<>();
         kubeflowPayload.put("display_name", saved.getDisplayName());
         kubeflowPayload.put("description", saved.getDescription());
         kubeflowPayload.put("namespace", "default");
 
         return webClientBuilder.build()
-                // Kubeflow 등록
+                // 1️⃣ Kubeflow 등록
                 .post()
                 .uri(kubeflowBaseUrl + "/apis/v2beta1/experiments")
                 .contentType(MediaType.APPLICATION_JSON)
@@ -168,15 +166,13 @@ public class ExperimentsController {
                         saved.setKubeflowStorageState((String) kubeflowResp.get("storage_state"));
                     }
 
-                    // DB 업데이트
                     experimentsService.save(saved);
                     log.info("Kubeflow experiment 등록 완료: {}", kubeflowResp);
 
-                    // 3️⃣ MLflow 등록
+                    // 2️⃣ MLflow 등록
                     Map<String, Object> mlflowPayload = new HashMap<>();
                     mlflowPayload.put("name", saved.getDisplayName());
-                    mlflowPayload.put("artifact_location", "/default/artifacts"); // 필요 시 변경
-                    // mlflowPayload.put("tags", ...); // 태그 필요 시 설정
+                    mlflowPayload.put("artifact_location", "/default/artifacts");
 
                     return webClientBuilder.build()
                             .post()
@@ -186,16 +182,60 @@ public class ExperimentsController {
                             .bodyValue(mlflowPayload)
                             .retrieve()
                             .bodyToMono(Map.class)
-                            .flatMap(mlflowResp -> {
-                                log.info("MLflow experiment 등록 완료: {}", mlflowResp);
+                            .flatMap(createResp -> {
+                                log.info("MLflow experiment 등록 완료: {}", createResp);
+                                String mlflowExpId = (String) createResp.get("experiment_id");
+
+                                // 3️⃣ MLflow 조회
+                                return webClientBuilder
+                                        .build()
+                                        .get()
+                                        .uri(mlflowBaseUrl + "/ajax-api/2.0/mlflow/experiments/get?experiment_id=" + mlflowExpId)
+                                        .headers(headers -> headers.setBasicAuth(mlflowUser, mlflowPassword))
+                                        .retrieve()
+                                        .bodyToMono(Map.class)
+                                        .flatMap(getResp -> {
+                                            log.info("MLflow experiment 상세 조회 완료: {}", getResp);
+                                            // 필요한 필드를 entity에 반영
+                                            if (getResp.containsKey("experiment")) {
+                                                Map<String, Object> exp = (Map<String, Object>) getResp.get("experiment");
+
+                                                // MLflow 응답 필드 반영
+                                                if (exp.containsKey("experiment_id")) {
+                                                    saved.setMlFlowId((String) exp.get("experiment_id"));
+                                                }
+
+                                                if (exp.containsKey("artifact_location")) {
+                                                    saved.setMlflow_artifactLocation((String) exp.get("artifact_location"));
+                                                }
+                                                if (exp.containsKey("lifecycle_stage")) {
+                                                    saved.setMlflowLifecycleStage((String) exp.get("lifecycle_stage"));
+                                                }
+                                                if (exp.containsKey("created_at")) {
+                                                    // created_at은 timestamp(ms)로 올 수도 있으므로 Instant 변환
+                                                    Object createdAtObj = exp.get("created_at");
+                                                    Instant createdAtInstant = null;
+                                                    if (createdAtObj instanceof Number) {
+                                                        createdAtInstant = Instant.ofEpochMilli(((Number) createdAtObj).longValue());
+                                                    } else if (createdAtObj instanceof String) {
+                                                        createdAtInstant = Instant.parse((String) createdAtObj);
+                                                    }
+                                                    if (createdAtInstant != null) {
+                                                        saved.setMlflowCreatedAt(
+                                                                createdAtInstant.atZone(ZoneId.of("Asia/Seoul")).toLocalDateTime()
+                                                        );
+                                                    }
+                                                }
+                                            }
+                                            experimentsService.save(saved);
                                             return Mono.just(ResponseEntity.ok(saved));
                                         });
+                            });
                 })
                 .doOnError(e -> log.error("Experiment 등록 실패", e));
     }
 
 
-
     @Operation(summary = "Experiment 수정")
     @PutMapping("/{id}")
     public ResponseEntity<ExperimentsEntity> updateExperiment(

src/main/resources/application.properties

@@ -57,3 +57,10 @@ minio.bucket=mlpipeline
 
 # Kubeflow
 kubeflow.url=http://192.168.10.135:32473/
+
+# MLflow
+mlflow.url=http://192.168.10.135:30128/
+mlflow.user=user
+mlflow.password=LImQa2Me37nu
+
+