자동완성 기능 추가

.gitignore

@@ -6,10 +6,12 @@ __pycache__/
 
 # Environment variables
 .env
+.env*
 
 # Claude AI related files
 .claudeignore
-# .claude/ 폴더는 커밋 대상 (에이전트 설정 포함)
+CLAUDE.md
+.claude/
 
 # VSCode settings
 .vscode/
@@ -36,3 +38,11 @@ static/
 # Log files
 *.log
 logs/
+
+# macOS
+.DS_Store
+.AppleDouble
+.LSOverride
+._*
+.Spotlight-V100
+.Trashes

.python-version

@@ -1 +1 @@
-3.13
+3.14

README.md

@@ -55,7 +55,6 @@ app/
 | ------ | -------------------------- | ----------------------------- |
 | POST   | `/song/generate`           | Suno AI를 이용한 노래 생성 요청 |
 | GET    | `/song/status/{task_id}`   | 노래 생성 상태 조회 (폴링)    |
-| GET    | `/song/download/{task_id}` | 생성된 노래 MP3 다운로드      |
 
 ## 환경 설정
 

app/core/common.py

@@ -5,7 +5,7 @@ from contextlib import asynccontextmanager
 from fastapi import FastAPI
 
 from app.utils.logger import get_logger
-
+from app.utils.nvMapPwScraper import NvMapPwScraper
 logger = get_logger("core")
 
 
@@ -24,6 +24,7 @@ async def lifespan(app: FastAPI):
 
             await create_db_tables()
             logger.info("Database tables created (DEBUG mode)")
+        await NvMapPwScraper.initiate_scraper()
     except asyncio.TimeoutError:
         logger.error("Database initialization timed out")
         # 타임아웃 시 앱 시작 중단하려면 raise, 계속하려면 pass

app/home/api/home_admin.py

@@ -1,6 +1,6 @@
 from sqladmin import ModelView
 
-from app.home.models import Image, Project
+from app.home.models import Image, Project, UserProject
 
 
 class ProjectAdmin(ModelView, model=Project):
@@ -100,3 +100,44 @@ class ImageAdmin(ModelView, model=Image):
         "img_url": "이미지 URL",
         "created_at": "생성일시",
     }
+
+
+class UserProjectAdmin(ModelView, model=UserProject):
+    name = "사용자-프로젝트"
+    name_plural = "사용자-프로젝트 목록"
+    icon = "fa-solid fa-link"
+    category = "프로젝트 관리"
+    page_size = 20
+
+    column_list = [
+        "id",
+        "user_id",
+        "project_id",
+    ]
+
+    column_details_list = [
+        "id",
+        "user_id",
+        "project_id",
+        "user",
+        "project",
+    ]
+
+    column_searchable_list = [
+        UserProject.user_id,
+        UserProject.project_id,
+    ]
+
+    column_sortable_list = [
+        UserProject.id,
+        UserProject.user_id,
+        UserProject.project_id,
+    ]
+
+    column_labels = {
+        "id": "ID",
+        "user_id": "사용자 ID",
+        "project_id": "프로젝트 ID",
+        "user": "사용자",
+        "project": "프로젝트",
+    }

app/home/api/routers/v1/home.py

@@ -13,6 +13,7 @@ from sqlalchemy.ext.asyncio import AsyncSession
 from app.database.session import get_session, AsyncSessionLocal
 from app.home.models import Image
 from app.home.schemas.home_schema import (
+    AutoCompleteRequest,
     CrawlingRequest,
     CrawlingResponse,
     ErrorResponse,
@@ -27,7 +28,8 @@ from app.utils.chatgpt_prompt import ChatgptService
 from app.utils.common import generate_task_id
 from app.utils.logger import get_logger
 from app.utils.nvMapScraper import NvMapScraper, GraphQLException
-from app.utils.prompts.prompts import  marketing_prompt
+from app.utils.nvMapPwScraper  import NvMapPwScraper
+from app.utils.prompts.prompts import marketing_prompt
 from config import MEDIA_ROOT
 
 # 로거 설정
@@ -105,28 +107,67 @@ def _extract_region_from_address(road_address: str | None) -> str:
     tags=["Crawling"],
 )
 async def crawling(request_body: CrawlingRequest):
-    """네이버 지도 장소 크롤링"""
+    return await _crawling_logic(request_body.url)
+
+@router.post(
+    "/autocomplete",
+    summary="네이버 자동완성 크롤링",
+    description="""
+네이버 검색 API 정보를 활용하여 Place ID를 추출한 뒤 자동으로 크롤링합니다.
+
+## 요청 필드
+- **url**: 네이버 지도 장소 URL (필수)
+
+## 반환 정보
+- **image_list**: 장소 이미지 URL 목록
+- **image_count**: 이미지 개수
+- **processed_info**: 가공된 장소 정보 (customer_name, region, detail_region_info)
+    """,
+    response_model=CrawlingResponse,
+    response_description="크롤링 결과",
+    responses={
+        200: {"description": "크롤링 성공", "model": CrawlingResponse},
+        400: {
+            "description": "잘못된 URL",
+            "model": ErrorResponse,
+        },
+        502: {
+            "description": "크롤링 실패",
+            "model": ErrorResponse,
+        },
+    },
+    tags=["Crawling"],
+)
+async def autocomplete_crawling(request_body: AutoCompleteRequest):
+    url = _autocomplete_logic(request_body.dict())
+    return await _crawling_logic(url)
+
+async def _crawling_logic(url:str):
     request_start = time.perf_counter()
     logger.info("[crawling] ========== START ==========")
-    logger.info(f"[crawling] URL: {request_body.url[:80]}...")
+    logger.info(f"[crawling] URL: {url[:80]}...")
 
     # ========== Step 1: 네이버 지도 크롤링 ==========
     step1_start = time.perf_counter()
     logger.info("[crawling] Step 1: 네이버 지도 크롤링 시작...")
 
     try:
-        scraper = NvMapScraper(request_body.url)
+        scraper = NvMapScraper(url)
         await scraper.scrap()
     except GraphQLException as e:
         step1_elapsed = (time.perf_counter() - step1_start) * 1000
-        logger.error(f"[crawling] Step 1 FAILED - GraphQL 크롤링 실패: {e} ({step1_elapsed:.1f}ms)")
+        logger.error(
+            f"[crawling] Step 1 FAILED - GraphQL 크롤링 실패: {e} ({step1_elapsed:.1f}ms)"
+        )
         raise HTTPException(
             status_code=status.HTTP_502_BAD_GATEWAY,
             detail=f"네이버 지도 크롤링에 실패했습니다: {e}",
         )
     except Exception as e:
         step1_elapsed = (time.perf_counter() - step1_start) * 1000
-        logger.error(f"[crawling] Step 1 FAILED - 크롤링 중 예기치 않은 오류: {e} ({step1_elapsed:.1f}ms)")
+        logger.error(
+            f"[crawling] Step 1 FAILED - 크롤링 중 예기치 않은 오류: {e} ({step1_elapsed:.1f}ms)"
+        )
         logger.exception("[crawling] Step 1 상세 오류:")
         raise HTTPException(
             status_code=status.HTTP_502_BAD_GATEWAY,
@@ -135,7 +176,9 @@ async def crawling(request_body: CrawlingRequest):
 
     step1_elapsed = (time.perf_counter() - step1_start) * 1000
     image_count = len(scraper.image_link_list) if scraper.image_link_list else 0
-    logger.info(f"[crawling] Step 1 완료 - 이미지 {image_count}개 ({step1_elapsed:.1f}ms)")
+    logger.info(
+        f"[crawling] Step 1 완료 - 이미지 {image_count}개 ({step1_elapsed:.1f}ms)"
+    )
 
     # ========== Step 2: 정보 가공 ==========
     step2_start = time.perf_counter()
@@ -156,7 +199,9 @@ async def crawling(request_body: CrawlingRequest):
         )
 
         step2_elapsed = (time.perf_counter() - step2_start) * 1000
-        logger.info(f"[crawling] Step 2 완료 - {customer_name}, {region} ({step2_elapsed:.1f}ms)")
+        logger.info(
+            f"[crawling] Step 2 완료 - {customer_name}, {region} ({step2_elapsed:.1f}ms)"
+        )
 
         # ========== Step 3: ChatGPT 마케팅 분석 ==========
         step3_start = time.perf_counter()
@@ -167,14 +212,16 @@ async def crawling(request_body: CrawlingRequest):
             step3_1_start = time.perf_counter()
             chatgpt_service = ChatgptService()
             step3_1_elapsed = (time.perf_counter() - step3_1_start) * 1000
-            logger.debug(f"[crawling]   Step 3-1: 서비스 초기화 완료 ({step3_1_elapsed:.1f}ms)")
+            logger.debug(
+                f"[crawling]   Step 3-1: 서비스 초기화 완료 ({step3_1_elapsed:.1f}ms)"
+            )
 
             # Step 3-2: 프롬프트 생성
             # step3_2_start = time.perf_counter()
             input_marketing_data = {
-                "customer_name" : customer_name,
-                "region" : region,
-                "detail_region_info" : road_address or ""
+                "customer_name": customer_name,
+                "region": region,
+                "detail_region_info": road_address or "",
             }
             # prompt = chatgpt_service.build_market_analysis_prompt()
             # prompt1 = marketing_prompt.build_prompt(input_marketing_data)
@@ -182,47 +229,81 @@ async def crawling(request_body: CrawlingRequest):
 
             # Step 3-3: GPT API 호출
             step3_3_start = time.perf_counter()
-            structured_report = await chatgpt_service.generate_structured_output(marketing_prompt, input_marketing_data)
+            structured_report = await chatgpt_service.generate_structured_output(
+                marketing_prompt, input_marketing_data
+            )
             step3_3_elapsed = (time.perf_counter() - step3_3_start) * 1000
-            logger.info(f"[crawling]   Step 3-3: GPT API 호출 완료 - ({step3_3_elapsed:.1f}ms)")
-            logger.debug(f"[crawling]   Step 3-3: GPT API 호출 완료 - ({step3_3_elapsed:.1f}ms)")
-
+            logger.info(
+                f"[crawling]   Step 3-3: GPT API 호출 완료 - ({step3_3_elapsed:.1f}ms)"
+            )
+            logger.debug(
+                f"[crawling]   Step 3-3: GPT API 호출 완료 - ({step3_3_elapsed:.1f}ms)"
+            )
 
             # Step 3-4: 응답 파싱 (크롤링에서 가져온 facility_info 전달)
             step3_4_start = time.perf_counter()
-            logger.debug(f"[crawling]   Step 3-4: 응답 파싱 시작 - facility_info: {scraper.facility_info}")
+            logger.debug(
+                f"[crawling]   Step 3-4: 응답 파싱 시작 - facility_info: {scraper.facility_info}"
+            )
 
             # 요약 Deprecated / 20250115 / Selling points를 첫 prompt에서 추출 중
             # parsed = await chatgpt_service.parse_marketing_analysis(
             #     structured_report, facility_info=scraper.facility_info
             # )
-            
+
             # marketing_analysis = MarketingAnalysis(**parsed)
 
+            logger.debug(
+                f"[crawling] structured_report 구조 확인:\n"
+                f"{'='*60}\n"
+                f"[report] type: {type(structured_report.get('report'))}\n"
+                f"{'-'*60}\n"
+                f"{structured_report.get('report')}\n"
+                f"{'='*60}\n"
+                f"[tags] type: {type(structured_report.get('tags'))}\n"
+                f"{'-'*60}\n"
+                f"{structured_report.get('tags')}\n"
+                f"{'='*60}\n"
+                f"[selling_points] type: {type(structured_report.get('selling_points'))}\n"
+                f"{'-'*60}\n"
+                f"{structured_report.get('selling_points')}\n"
+                f"{'='*60}"
+            )
+
             marketing_analysis = MarketingAnalysis(
                 report=structured_report["report"],
                 tags=structured_report["tags"],
-                facilities = list([sp['keywords'] for sp in structured_report["selling_points"]])# [json.dumps(structured_report["selling_points"])] # 나중에 Selling Points로 변수와 데이터구조 변경할 것
+                facilities=list(
+                    [sp["keywords"] for sp in structured_report["selling_points"]]
+                ),  # [json.dumps(structured_report["selling_points"])] # 나중에 Selling Points로 변수와 데이터구조 변경할 것
             )
-                # Selling Points 구조
-                    # print(sp['category'])
-                    # print(sp['keywords'])
-                    # print(sp['description'])
+            # Selling Points 구조
+            # print(sp['category'])
+            # print(sp['keywords'])
+            # print(sp['description'])
             step3_4_elapsed = (time.perf_counter() - step3_4_start) * 1000
-            logger.debug(f"[crawling]   Step 3-4: 응답 파싱 완료 ({step3_4_elapsed:.1f}ms)")
+            logger.debug(
+                f"[crawling]   Step 3-4: 응답 파싱 완료 ({step3_4_elapsed:.1f}ms)"
+            )
 
             step3_elapsed = (time.perf_counter() - step3_start) * 1000
-            logger.info(f"[crawling] Step 3 완료 - 마케팅 분석 성공 ({step3_elapsed:.1f}ms)")
+            logger.info(
+                f"[crawling] Step 3 완료 - 마케팅 분석 성공 ({step3_elapsed:.1f}ms)"
+            )
 
         except Exception as e:
             step3_elapsed = (time.perf_counter() - step3_start) * 1000
-            logger.error(f"[crawling] Step 3 FAILED - GPT 마케팅 분석 중 오류: {e} ({step3_elapsed:.1f}ms)")
+            logger.error(
+                f"[crawling] Step 3 FAILED - GPT 마케팅 분석 중 오류: {e} ({step3_elapsed:.1f}ms)"
+            )
             logger.exception("[crawling] Step 3 상세 오류:")
             # GPT 실패 시에도 크롤링 결과는 반환
             marketing_analysis = None
     else:
         step2_elapsed = (time.perf_counter() - step2_start) * 1000
-        logger.warning(f"[crawling] Step 2 - base_info 없음, 마케팅 분석 스킵 ({step2_elapsed:.1f}ms)")
+        logger.warning(
+            f"[crawling] Step 2 - base_info 없음, 마케팅 분석 스킵 ({step2_elapsed:.1f}ms)"
+        )
 
     # ========== 완료 ==========
     total_elapsed = (time.perf_counter() - request_start) * 1000
@@ -231,19 +312,36 @@ async def crawling(request_body: CrawlingRequest):
     logger.info(f"[crawling]   - Step 1 (크롤링): {step1_elapsed:.1f}ms")
     if scraper.base_info:
         logger.info(f"[crawling]   - Step 2 (정보가공): {step2_elapsed:.1f}ms")
-        if 'step3_elapsed' in locals():
+        if "step3_elapsed" in locals():
             logger.info(f"[crawling]   - Step 3 (GPT 분석): {step3_elapsed:.1f}ms")
-            if 'step3_3_elapsed' in locals():
+            if "step3_3_elapsed" in locals():
                 logger.info(f"[crawling]       - GPT API 호출: {step3_3_elapsed:.1f}ms")
 
     return {
         "image_list": scraper.image_link_list,
         "image_count": len(scraper.image_link_list) if scraper.image_link_list else 0,
         "processed_info": processed_info,
-        "marketing_analysis": marketing_analysis
+        "marketing_analysis": marketing_analysis,
     }
 
 
+async def _autocomplete_logic(autocomplete_item:dict):
+    step1_start = time.perf_counter()
+    try:
+        async with NvMapPwScraper() as pw_scraper:
+            new_url = await pw_scraper.get_place_id_url(autocomplete_item)
+    except Exception as e:
+        step1_elapsed = (time.perf_counter() - step1_start) * 1000
+        logger.error(
+            f"[crawling] Autocomplete FAILED - 자동완성 예기치 않은 오류: {e} ({step1_elapsed:.1f}ms)"
+        )
+        logger.exception("[crawling] Autocomplete 상세 오류:")
+        raise HTTPException(
+            status_code=status.HTTP_502_BAD_GATEWAY,
+            detail="자동완성 place id 추출 실패",
+        )
+    return new_url
+
 def _extract_image_name(url: str, index: int) -> str:
     """URL에서 이미지 이름 추출 또는 기본 이름 생성"""
     try:
@@ -598,6 +696,15 @@ curl -X POST "http://localhost:8000/image/upload/blob" \\
         400: {"description": "이미지가 제공되지 않음", "model": ErrorResponse},
     },
     tags=["Image-Blob"],
+    openapi_extra={
+        "requestBody": {
+            "content": {
+                "multipart/form-data": {
+                    "encoding": {"files": {"contentType": "application/octet-stream"}}
+                }
+            }
+        }
+    },
 )
 async def upload_images_blob(
     images_json: Optional[str] = Form(
@@ -606,7 +713,8 @@ async def upload_images_blob(
         examples=[IMAGES_JSON_EXAMPLE],
     ),
     files: Optional[list[UploadFile]] = File(
-        default=None, description="이미지 바이너리 파일 목록"
+        default=None,
+        description="이미지 바이너리 파일 목록",
     ),
 ) -> ImageUploadResponse:
     """이미지 업로드 (URL + Azure Blob Storage)
@@ -674,9 +782,11 @@ async def upload_images_blob(
         )
 
     stage1_time = time.perf_counter()
-    logger.info(f"[upload_images_blob] Stage 1 done - urls: {len(url_images)}, "
-                f"files: {len(valid_files_data)}, "
-                f"elapsed: {(stage1_time - request_start)*1000:.1f}ms")
+    logger.info(
+        f"[upload_images_blob] Stage 1 done - urls: {len(url_images)}, "
+        f"files: {len(valid_files_data)}, "
+        f"elapsed: {(stage1_time - request_start) * 1000:.1f}ms"
+    )
 
     # ========== Stage 2: Azure Blob 업로드 (세션 없음) ==========
     # 업로드 결과를 저장할 리스트 (나중에 DB에 저장)
@@ -695,8 +805,10 @@ async def upload_images_blob(
             )
             filename = f"{name_without_ext}_{img_order:03d}{ext}"
 
-            logger.debug(f"[upload_images_blob] Uploading file {idx+1}/{total_files}: "
-                         f"{filename} ({len(file_content)} bytes)")
+            logger.debug(
+                f"[upload_images_blob] Uploading file {idx + 1}/{total_files}: "
+                f"{filename} ({len(file_content)} bytes)"
+            )
 
             # Azure Blob Storage에 직접 업로드
             upload_success = await uploader.upload_image_bytes(file_content, filename)
@@ -705,15 +817,21 @@ async def upload_images_blob(
                 blob_url = uploader.public_url
                 blob_upload_results.append((original_name, blob_url))
                 img_order += 1
-                logger.debug(f"[upload_images_blob] File {idx+1}/{total_files} SUCCESS")
+                logger.debug(
+                    f"[upload_images_blob] File {idx + 1}/{total_files} SUCCESS"
+                )
             else:
                 skipped_files.append(filename)
-                logger.warning(f"[upload_images_blob] File {idx+1}/{total_files} FAILED")
+                logger.warning(
+                    f"[upload_images_blob] File {idx + 1}/{total_files} FAILED"
+                )
 
     stage2_time = time.perf_counter()
-    logger.info(f"[upload_images_blob] Stage 2 done - blob uploads: "
-                f"{len(blob_upload_results)}, skipped: {len(skipped_files)}, "
-                f"elapsed: {(stage2_time - stage1_time)*1000:.1f}ms")
+    logger.info(
+        f"[upload_images_blob] Stage 2 done - blob uploads: "
+        f"{len(blob_upload_results)}, skipped: {len(skipped_files)}, "
+        f"elapsed: {(stage2_time - stage1_time) * 1000:.1f}ms"
+    )
 
     # ========== Stage 3: DB 저장 (새 세션으로 빠르게 처리) ==========
     logger.info("[upload_images_blob] Stage 3 starting - DB save...")
@@ -724,9 +842,7 @@ async def upload_images_blob(
         async with AsyncSessionLocal() as session:
             # URL 이미지 저장
             for url_item in url_images:
-                img_name = (
-                    url_item.name or _extract_image_name(url_item.url, img_order)
-                )
+                img_name = url_item.name or _extract_image_name(url_item.url, img_order)
 
                 image = Image(
                     task_id=task_id,
@@ -772,9 +888,11 @@ async def upload_images_blob(
 
             await session.commit()
             stage3_time = time.perf_counter()
-            logger.info(f"[upload_images_blob] Stage 3 done - "
-                        f"saved: {len(result_images)}, "
-                        f"elapsed: {(stage3_time - stage2_time)*1000:.1f}ms")
+            logger.info(
+                f"[upload_images_blob] Stage 3 done - "
+                f"saved: {len(result_images)}, "
+                f"elapsed: {(stage3_time - stage2_time) * 1000:.1f}ms"
+            )
 
     except SQLAlchemyError as e:
         logger.error(f"[upload_images_blob] DB Error - task_id: {task_id}, error: {e}")
@@ -784,8 +902,10 @@ async def upload_images_blob(
             detail="이미지 저장 중 데이터베이스 오류가 발생했습니다.",
         )
     except Exception as e:
-        logger.error(f"[upload_images_blob] Stage 3 EXCEPTION - "
-                     f"task_id: {task_id}, error: {type(e).__name__}: {e}")
+        logger.error(
+            f"[upload_images_blob] Stage 3 EXCEPTION - "
+            f"task_id: {task_id}, error: {type(e).__name__}: {e}"
+        )
         logger.exception("[upload_images_blob] Stage 3 상세 오류:")
         raise HTTPException(
             status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
@@ -796,8 +916,10 @@ async def upload_images_blob(
     image_urls = [img.img_url for img in result_images]
 
     total_time = time.perf_counter() - request_start
-    logger.info(f"[upload_images_blob] SUCCESS - task_id: {task_id}, "
-                f"total: {saved_count}, total_time: {total_time*1000:.1f}ms")
+    logger.info(
+        f"[upload_images_blob] SUCCESS - task_id: {task_id}, "
+        f"total: {saved_count}, total_time: {total_time * 1000:.1f}ms"
+    )
 
     return ImageUploadResponse(
         task_id=task_id,

app/home/schemas/home_schema.py

@@ -122,6 +122,22 @@ class CrawlingRequest(BaseModel):
 
     url: str = Field(..., description="네이버 지도 장소 URL")
 
+class AutoCompleteRequest(BaseModel):
+    """자동완성 요청 스키마"""
+
+    model_config = ConfigDict(
+        json_schema_extra={
+            "example": {
+                'title': '<b>스테이</b>,<b>머뭄</b>',
+                'address': '전북특별자치도 군산시 신흥동 63-18',
+                'roadAddress': '전북특별자치도 군산시 절골길 18',
+            }
+        }
+    )
+
+    title: str = Field(..., description="네이버 검색 place API Title")
+    address: str = Field(..., description="네이버 검색 place API 지번주소")
+    roadAddress: Optional[str] = Field(None, description="네이버 검색 place API 도로명주소")
 
 class ProcessedInfo(BaseModel):
     """가공된 장소 정보 스키마"""

app/song/api/routers/v1/song.py

@@ -6,7 +6,6 @@ Song API Router
 엔드포인트 목록:
     - POST /song/generate/{task_id}: 노래 생성 요청 (task_id로 Project/Lyric 연결)
     - GET /song/status/{song_id}: Suno API 노래 생성 상태 조회
-    - GET /song/download/{task_id}: 노래 다운로드 상태 조회 (DB polling)
 
 사용 예시:
     from app.song.api.routers.v1.song import router
@@ -14,27 +13,20 @@ Song API Router
 """
 
 from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException
-from sqlalchemy import func, select
+from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.database.session import get_session
-from app.dependencies.pagination import (
-    PaginationParams,
-    get_pagination_params,
-)
 from app.home.models import Project
 from app.lyric.models import Lyric
-from app.song.models import Song
+from app.song.models import Song, SongTimestamp
 from app.song.schemas.song_schema import (
-    DownloadSongResponse,
     GenerateSongRequest,
     GenerateSongResponse,
     PollingSongResponse,
-    SongListItem,
 )
 from app.song.worker.song_task import download_and_upload_song_by_suno_task_id
 from app.utils.logger import get_logger
-from app.utils.pagination import PaginatedResponse
 from app.utils.suno import SunoService
 
 logger = get_logger("song")
@@ -127,7 +119,9 @@ async def generate_song(
             project = project_result.scalar_one_or_none()
 
             if not project:
-                logger.warning(f"[generate_song] Project NOT FOUND - task_id: {task_id}")
+                logger.warning(
+                    f"[generate_song] Project NOT FOUND - task_id: {task_id}"
+                )
                 raise HTTPException(
                     status_code=404,
                     detail=f"task_id '{task_id}'에 해당하는 Project를 찾을 수 없습니다.",
@@ -142,6 +136,13 @@ async def generate_song(
                 .limit(1)
             )
             lyric = lyric_result.scalar_one_or_none()
+            logger.debug(
+                f"[generate_song] Lyric query result - "
+                f"id: {lyric.id if lyric else None}, "
+                f"project_id: {lyric.project_id if lyric else None}, "
+                f"task_id: {lyric.task_id if lyric else None}, "
+                f"lyric_result: {lyric.lyric_result if lyric else None}"
+            )
 
             if not lyric:
                 logger.warning(f"[generate_song] Lyric NOT FOUND - task_id: {task_id}")
@@ -155,13 +156,25 @@ async def generate_song(
             logger.info(
                 f"[generate_song] Queries completed - task_id: {task_id}, "
                 f"project_id: {project_id}, lyric_id: {lyric_id}, "
-                f"elapsed: {(query_time - request_start)*1000:.1f}ms"
+                f"elapsed: {(query_time - request_start) * 1000:.1f}ms"
             )
 
             # Song 테이블에 초기 데이터 저장
             song_prompt = (
                 f"[Lyrics]\n{request_body.lyrics}\n\n[Genre]\n{request_body.genre}"
             )
+            logger.debug(
+                f"[generate_song] Lyrics comparison - task_id: {task_id}\n"
+                f"{'=' * 60}\n"
+                f"[lyric.lyric_result]\n"
+                f"{'-' * 60}\n"
+                f"{lyric.lyric_result}\n"
+                f"{'=' * 60}\n"
+                f"[song_prompt]\n"
+                f"{'-' * 60}\n"
+                f"{song_prompt}\n"
+                f"{'=' * 60}"
+            )
 
             song = Song(
                 project_id=project_id,
@@ -180,7 +193,7 @@ async def generate_song(
             logger.info(
                 f"[generate_song] Stage 1 DONE - Song saved - "
                 f"task_id: {task_id}, song_id: {song_id}, "
-                f"elapsed: {(stage1_time - request_start)*1000:.1f}ms"
+                f"elapsed: {(stage1_time - request_start) * 1000:.1f}ms"
             )
         # 세션이 여기서 자동으로 닫힘
 
@@ -217,7 +230,7 @@ async def generate_song(
         logger.info(
             f"[generate_song] Stage 2 DONE - task_id: {task_id}, "
             f"suno_task_id: {suno_task_id}, "
-            f"elapsed: {(stage2_time - stage2_start)*1000:.1f}ms"
+            f"elapsed: {(stage2_time - stage2_start) * 1000:.1f}ms"
         )
 
     except Exception as e:
@@ -263,12 +276,12 @@ async def generate_song(
         total_time = stage3_time - request_start
         logger.info(
             f"[generate_song] Stage 3 DONE - task_id: {task_id}, "
-            f"elapsed: {(stage3_time - stage3_start)*1000:.1f}ms"
+            f"elapsed: {(stage3_time - stage3_start) * 1000:.1f}ms"
         )
         logger.info(
             f"[generate_song] SUCCESS - task_id: {task_id}, "
             f"suno_task_id: {suno_task_id}, "
-            f"total_time: {total_time*1000:.1f}ms"
+            f"total_time: {total_time * 1000:.1f}ms"
         )
 
         return GenerateSongResponse(
@@ -324,7 +337,6 @@ GET /song/status/abc123...
 ## 참고
 - 이 엔드포인트는 Suno API의 상태를 반환합니다
 - SUCCESS 응답 시 백그라운드에서 MP3 다운로드 → Azure Blob Storage 업로드가 시작됩니다
-- 최종 완료 상태는 `/song/download/{task_id}` 엔드포인트에서 확인하세요
 - Song 테이블 상태: processing → uploading → completed
     """,
     response_model=PollingSongResponse,
@@ -343,13 +355,22 @@ async def get_song_status(
     Azure Blob Storage에 업로드한 뒤 Song 테이블의 status를 completed로,
     song_result_url을 Blob URL로 업데이트합니다.
     """
-    logger.info(f"[get_song_status] START - song_id: {song_id}")
+    suno_task_id = song_id  # 임시방편 / 외부 suno 노출 방지
+    logger.info(f"[get_song_status] START - song_id: {suno_task_id}")
     try:
         suno_service = SunoService()
-        result = await suno_service.get_task_status(song_id)
-        logger.debug(f"[get_song_status] Suno API raw response - song_id: {song_id}, result: {result}")
+        result = await suno_service.get_task_status(suno_task_id)
+        logger.debug(
+            f"[get_song_status] Suno API raw response - song_id: {suno_task_id}, result: {result}"
+        )
         parsed_response = suno_service.parse_status_response(result)
-        logger.info(f"[get_song_status] Suno API response - song_id: {song_id}, status: {parsed_response.status}")
+        logger.info(
+            f"[get_song_status] Suno API response - song_id: {suno_task_id}, status: {parsed_response.status}"
+        )
+
+        if parsed_response.status == "TEXT_SUCCESS" and result:
+            parsed_response.status = "processing"
+            return parsed_response
 
         # SUCCESS 상태인 경우 백그라운드에서 MP3 다운로드 및 Blob 업로드 진행
         if parsed_response.status == "SUCCESS" and result:
@@ -363,7 +384,9 @@ async def get_song_status(
                 first_clip = clips_data[0]
                 audio_url = first_clip.get("audioUrl")
                 clip_duration = first_clip.get("duration")
-                logger.debug(f"[get_song_status] Using first clip - id: {first_clip.get('id')}, audio_url: {audio_url}, duration: {clip_duration}")
+                logger.debug(
+                    f"[get_song_status] Using first clip - id: {first_clip.get('id')}, audio_url: {audio_url}, duration: {clip_duration}"
+                )
 
                 if audio_url:
                     # song_id로 Song 조회
@@ -386,9 +409,11 @@ async def get_song_status(
 
                         # 상태를 uploading으로 변경 (중복 호출 방지)
                         song.status = "uploading"
-                        song.suno_audio_id = first_clip.get('id')
+                        song.suno_audio_id = first_clip.get("id")
                         await session.commit()
-                        logger.info(f"[get_song_status] Song status changed to uploading - song_id: {song_id}")
+                        logger.info(
+                            f"[get_song_status] Song status changed to uploading - song_id: {suno_task_id}"
+                        )
 
                         # 백그라운드 태스크로 MP3 다운로드 및 Blob 업로드 실행
                         background_tasks.add_task(
@@ -398,16 +423,96 @@ async def get_song_status(
                             store_name=store_name,
                             duration=clip_duration,
                         )
-                        logger.info(f"[get_song_status] Background task scheduled - song_id: {song_id}, store_name: {store_name}")
+                        logger.info(
+                            f"[get_song_status] Background task scheduled - song_id: {suno_task_id}, store_name: {store_name}"
+                        )
+
+                        suno_audio_id = first_clip.get("id")
+                        word_data = await suno_service.get_lyric_timestamp(
+                            suno_task_id, suno_audio_id
+                        )
+                        logger.debug(
+                            f"[get_song_status] word_data from get_lyric_timestamp - "
+                            f"suno_task_id: {suno_task_id}, suno_audio_id: {suno_audio_id}, "
+                            f"word_data: {word_data}"
+                        )
+                        lyric_result = await session.execute(
+                            select(Lyric)
+                            .where(Lyric.task_id == song.task_id)
+                            .order_by(Lyric.created_at.desc())
+                            .limit(1)
+                        )
+                        lyric = lyric_result.scalar_one_or_none()
+                        gt_lyric = lyric.lyric_result
+                        lyric_line_list = gt_lyric.split("\n")
+                        sentences = [
+                            lyric_line.strip(",. ")
+                            for lyric_line in lyric_line_list
+                            if lyric_line and lyric_line != "---"
+                        ]
+                        logger.debug(
+                            f"[get_song_status] sentences from lyric - "
+                            f"sentences: {sentences}"
+                        )
+
+                        timestamped_lyrics = suno_service.align_lyrics(
+                            word_data, sentences
+                        )
+                        logger.debug(
+                            f"[get_song_status] sentences from lyric - "
+                            f"sentences: {sentences}"
+                        )
+
+                        # TODO : DB upload timestamped_lyrics
+                        for order_idx, timestamped_lyric in enumerate(
+                            timestamped_lyrics
+                        ):
+                            song_timestamp = SongTimestamp(
+                                suno_audio_id=suno_audio_id,
+                                order_idx=order_idx,
+                                lyric_line=timestamped_lyric["text"],
+                                start_time=timestamped_lyric["start_sec"],
+                                end_time=timestamped_lyric["end_sec"],
+                            )
+                            session.add(song_timestamp)
+
+                        await session.commit()
+                        parsed_response.status = "processing"
 
                     elif song and song.status == "uploading":
-                        logger.info(f"[get_song_status] SKIPPED - Song is already uploading, song_id: {song_id}")
-                        parsed_response.status == "uploading"
+                        logger.info(
+                            f"[get_song_status] SKIPPED - Song is already uploading, song_id: {suno_task_id}"
+                        )
+                        parsed_response.status = "uploading"
                     elif song and song.status == "completed":
-                        logger.info(f"[get_song_status] SKIPPED - Song already completed, song_id: {song_id}")
-                        parsed_response.status == "SUCCESS"
+                        logger.info(
+                            f"[get_song_status] SKIPPED - Song already completed, song_id: {suno_task_id}"
+                        )
+                        parsed_response.song_result_url = song.song_result_url
+                else:
+                    # audio_url이 없는 경우 에러 반환
+                    logger.error(
+                        f"[get_song_status] ERROR - audio_url not found in clips_data, song_id: {suno_task_id}"
+                    )
+                    return PollingSongResponse(
+                        success=False,
+                        status="error",
+                        message="Suno API 응답에서 audio_url을 찾을 수 없습니다.",
+                        error_message="audio_url not found in Suno API response",
+                    )
+            else:
+                # clips_data가 없는 경우 에러 반환
+                logger.error(
+                    f"[get_song_status] ERROR - clips_data not found, song_id: {suno_task_id}"
+                )
+                return PollingSongResponse(
+                    success=False,
+                    status="error",
+                    message="Suno API 응답에서 클립 데이터를 찾을 수 없습니다.",
+                    error_message="clips_data not found in Suno API response",
+                )
 
-        logger.info(f"[get_song_status] song_id: {song_id}")
+        logger.info(f"[get_song_status] END - song_id: {suno_task_id}")
         return parsed_response
 
     except Exception as e:
@@ -420,261 +525,3 @@ async def get_song_status(
             message="상태 조회에 실패했습니다.",
             error_message=f"{type(e).__name__}: {e}\n{traceback.format_exc()}",
         )
-
-
-@router.get(
-    "/download/{task_id}",
-    summary="노래 다운로드 상태 조회 (DB Polling)",
-    description="""
-task_id를 기반으로 Song 테이블의 상태를 조회하고,
-completed인 경우 Project 정보와 노래 URL을 반환합니다.
-
-## 경로 파라미터
-- **task_id**: 프로젝트 task_id (필수)
-
-## 반환 정보
-- **success**: 조회 성공 여부
-- **status**: DB 처리 상태 (processing, uploading, completed, failed, not_found, error)
-- **message**: 응답 메시지
-- **store_name**: 업체명 (completed 시)
-- **region**: 지역명 (completed 시)
-- **detail_region_info**: 상세 지역 정보 (completed 시)
-- **task_id**: 작업 고유 식별자
-- **language**: 언어 (completed 시)
-- **song_result_url**: 노래 결과 URL (completed 시, Azure Blob Storage URL)
-- **created_at**: 생성 일시 (completed 시)
-- **error_message**: 에러 메시지 (실패 시)
-
-## 사용 예시
-```
-GET /song/download/019123ab-cdef-7890-abcd-ef1234567890
-```
-
-## 상태 값 (DB 상태)
-- **processing**: Suno API에서 노래 생성 중
-- **uploading**: MP3 다운로드 및 Azure Blob 업로드 중
-- **completed**: 모든 작업 완료, Blob URL 사용 가능
-- **failed**: 노래 생성 또는 업로드 실패
-- **not_found**: task_id에 해당하는 Song 없음
-- **error**: 조회 중 오류 발생
-
-## 참고
-- 이 엔드포인트는 DB의 Song 테이블 상태를 반환합니다
-- completed 상태인 경우 Project 정보와 함께 song_result_url (Azure Blob URL)을 반환합니다
-- song_result_url 형식: {AZURE_BLOB_BASE_URL}/{task_id}/song/{store_name}.mp3
-    """,
-    response_model=DownloadSongResponse,
-    responses={
-        200: {"description": "조회 성공 (모든 상태에서 200 반환)"},
-    },
-)
-async def download_song(
-    task_id: str,
-    session: AsyncSession = Depends(get_session),
-) -> DownloadSongResponse:
-    """task_id로 Song 상태를 polling하고 completed 시 Project 정보와 노래 URL을 반환합니다."""
-    logger.info(f"[download_song] START - task_id: {task_id}")
-    try:
-        # task_id로 Song 조회 (여러 개 있을 경우 가장 최근 것 선택)
-        song_result = await session.execute(
-            select(Song)
-            .where(Song.task_id == task_id)
-            .order_by(Song.created_at.desc())
-            .limit(1)
-        )
-        song = song_result.scalar_one_or_none()
-
-        if not song:
-            logger.warning(f"[download_song] Song NOT FOUND - task_id: {task_id}")
-            return DownloadSongResponse(
-                success=False,
-                status="not_found",
-                message=f"task_id '{task_id}'에 해당하는 Song을 찾을 수 없습니다.",
-                error_message="Song not found",
-            )
-
-        logger.info(f"[download_song] Song found - task_id: {task_id}, status: {song.status}")
-
-        # processing 상태인 경우
-        if song.status == "processing":
-            logger.info(f"[download_song] PROCESSING - task_id: {task_id}")
-            return DownloadSongResponse(
-                success=True,
-                status="processing",
-                message="노래 생성이 진행 중입니다.",
-                task_id=task_id,
-            )
-
-        # uploading 상태인 경우
-        if song.status == "uploading":
-            logger.info(f"[download_song] UPLOADING - task_id: {task_id}")
-            return DownloadSongResponse(
-                success=True,
-                status="uploading",
-                message="노래 파일을 업로드 중입니다.",
-                task_id=task_id,
-            )
-
-        # failed 상태인 경우
-        if song.status == "failed":
-            logger.warning(f"[download_song] FAILED - task_id: {task_id}")
-            return DownloadSongResponse(
-                success=False,
-                status="failed",
-                message="노래 생성에 실패했습니다.",
-                task_id=task_id,
-                error_message="Song generation failed",
-            )
-
-        # completed 상태인 경우 - Project 정보 조회
-        project_result = await session.execute(
-            select(Project).where(Project.id == song.project_id)
-        )
-        project = project_result.scalar_one_or_none()
-
-        logger.info(f"[download_song] COMPLETED - task_id: {task_id}, song_result_url: {song.song_result_url}")
-        return DownloadSongResponse(
-            success=True,
-            status="completed",
-            message="노래 다운로드가 완료되었습니다.",
-            store_name=project.store_name if project else None,
-            region=project.region if project else None,
-            detail_region_info=project.detail_region_info if project else None,
-            task_id=task_id,
-            language=project.language if project else None,
-            song_result_url=song.song_result_url,
-            created_at=song.created_at,
-        )
-
-    except Exception as e:
-        logger.error(f"[download_song] EXCEPTION - task_id: {task_id}, error: {e}")
-        return DownloadSongResponse(
-            success=False,
-            status="error",
-            message="노래 다운로드 조회에 실패했습니다.",
-            error_message=str(e),
-        )
-
-
-@router.get(
-    "s/",
-    summary="생성된 노래 목록 조회",
-    description="""
-완료된 노래 목록을 페이지네이션하여 조회합니다.
-
-## 쿼리 파라미터
-- **page**: 페이지 번호 (1부터 시작, 기본값: 1)
-- **page_size**: 페이지당 데이터 수 (기본값: 10, 최대: 100)
-
-## 반환 정보
-- **items**: 노래 목록 (store_name, region, task_id, language, song_result_url, created_at)
-- **total**: 전체 데이터 수
-- **page**: 현재 페이지
-- **page_size**: 페이지당 데이터 수
-- **total_pages**: 전체 페이지 수
-- **has_next**: 다음 페이지 존재 여부
-- **has_prev**: 이전 페이지 존재 여부
-
-## 사용 예시
-```
-GET /songs/?page=1&page_size=10
-```
-
-## 참고
-- status가 'completed'인 노래만 반환됩니다.
-- created_at 기준 내림차순 정렬됩니다.
-    """,
-    response_model=PaginatedResponse[SongListItem],
-    responses={
-        200: {"description": "노래 목록 조회 성공"},
-    },
-)
-async def get_songs(
-    session: AsyncSession = Depends(get_session),
-    pagination: PaginationParams = Depends(get_pagination_params),
-) -> PaginatedResponse[SongListItem]:
-    """완료된 노래 목록을 페이지네이션하여 반환합니다."""
-    logger.info(f"[get_songs] START - page: {pagination.page}, page_size: {pagination.page_size}")
-    try:
-        offset = (pagination.page - 1) * pagination.page_size
-
-        # 서브쿼리: task_id별 최신 Song의 id 조회 (completed 상태, created_at 기준)
-        from sqlalchemy import and_
-
-        # task_id별 최신 created_at 조회
-        latest_subquery = (
-            select(
-                Song.task_id,
-                func.max(Song.created_at).label("max_created_at")
-            )
-            .where(Song.status == "completed")
-            .group_by(Song.task_id)
-            .subquery()
-        )
-
-        # 전체 개수 조회 (task_id별 최신 1개만)
-        count_query = select(func.count()).select_from(latest_subquery)
-        total_result = await session.execute(count_query)
-        total = total_result.scalar() or 0
-
-        # 데이터 조회 (completed 상태, task_id별 created_at 기준 최신 1개만, 최신순)
-        query = (
-            select(Song)
-            .join(
-                latest_subquery,
-                and_(
-                    Song.task_id == latest_subquery.c.task_id,
-                    Song.created_at == latest_subquery.c.max_created_at
-                )
-            )
-            .where(Song.status == "completed")
-            .order_by(Song.created_at.desc())
-            .offset(offset)
-            .limit(pagination.page_size)
-        )
-        result = await session.execute(query)
-        songs = result.scalars().all()
-
-        # Project 정보 일괄 조회 (N+1 문제 해결)
-        project_ids = [s.project_id for s in songs if s.project_id]
-        projects_map: dict = {}
-        if project_ids:
-            projects_result = await session.execute(
-                select(Project).where(Project.id.in_(project_ids))
-            )
-            projects_map = {p.id: p for p in projects_result.scalars().all()}
-
-        # SongListItem으로 변환
-        items = []
-        for song in songs:
-            project = projects_map.get(song.project_id)
-
-            item = SongListItem(
-                store_name=project.store_name if project else None,
-                region=project.region if project else None,
-                task_id=song.task_id,
-                language=song.language,
-                song_result_url=song.song_result_url,
-                created_at=song.created_at,
-            )
-            items.append(item)
-
-        response = PaginatedResponse.create(
-            items=items,
-            total=total,
-            page=pagination.page,
-            page_size=pagination.page_size,
-        )
-
-        logger.info(
-            f"[get_songs] SUCCESS - total: {total}, page: {pagination.page}, "
-            f"page_size: {pagination.page_size}, items_count: {len(items)}"
-        )
-        return response
-
-    except Exception as e:
-        logger.error(f"[get_songs] EXCEPTION - error: {e}")
-        raise HTTPException(
-            status_code=500,
-            detail=f"노래 목록 조회에 실패했습니다: {str(e)}",
-        )

app/song/api/song_admin.py

@@ -1,6 +1,6 @@
 from sqladmin import ModelView
 
-from app.song.models import Song
+from app.song.models import Song, SongTimestamp
 
 
 class SongAdmin(ModelView, model=Song):
@@ -67,3 +67,59 @@ class SongAdmin(ModelView, model=Song):
         "song_result_url": "결과 URL",
         "created_at": "생성일시",
     }
+
+
+class SongTimestampAdmin(ModelView, model=SongTimestamp):
+    name = "노래 타임스탬프"
+    name_plural = "노래 타임스탬프 목록"
+    icon = "fa-solid fa-clock"
+    category = "노래 관리"
+    page_size = 20
+
+    column_list = [
+        "id",
+        "suno_audio_id",
+        "order_idx",
+        "lyric_line",
+        "start_time",
+        "end_time",
+        "created_at",
+    ]
+
+    column_details_list = [
+        "id",
+        "suno_audio_id",
+        "order_idx",
+        "lyric_line",
+        "start_time",
+        "end_time",
+        "created_at",
+    ]
+
+    form_excluded_columns = ["created_at"]
+
+    column_searchable_list = [
+        SongTimestamp.suno_audio_id,
+        SongTimestamp.lyric_line,
+    ]
+
+    column_default_sort = (SongTimestamp.created_at, True)
+
+    column_sortable_list = [
+        SongTimestamp.id,
+        SongTimestamp.suno_audio_id,
+        SongTimestamp.order_idx,
+        SongTimestamp.start_time,
+        SongTimestamp.end_time,
+        SongTimestamp.created_at,
+    ]
+
+    column_labels = {
+        "id": "ID",
+        "suno_audio_id": "Suno 오디오 ID",
+        "order_idx": "순서",
+        "lyric_line": "가사",
+        "start_time": "시작 시간",
+        "end_time": "종료 시간",
+        "created_at": "생성일시",
+    }

app/song/schemas/song_schema.py

@@ -79,9 +79,30 @@ class GenerateSongResponse(BaseModel):
         }
     """
 
+    model_config = {
+        "json_schema_extra": {
+            "examples": [
+                {
+                    "success": True,
+                    "task_id": "019123ab-cdef-7890-abcd-ef1234567890",
+                    "song_id": "abc123...",
+                    "message": "노래 생성 요청이 접수되었습니다. song_id로 상태를 조회하세요.",
+                    "error_message": None,
+                },
+                {
+                    "success": False,
+                    "task_id": "019123ab-cdef-7890-abcd-ef1234567890",
+                    "song_id": None,
+                    "message": "노래 생성 요청에 실패했습니다.",
+                    "error_message": "Suno API connection error",
+                },
+            ]
+        }
+    }
+
     success: bool = Field(..., description="요청 성공 여부")
     task_id: Optional[str] = Field(None, description="내부 작업 ID (Project/Lyric task_id)")
-    song_id: Optional[str] = Field(None, description="Suno API 작업 ID")
+    song_id: Optional[str] = Field(None, description="Suno API 작업 ID (상태 조회에 사용)")
     message: str = Field(..., description="응답 메시지")
     error_message: Optional[str] = Field(None, description="에러 메시지 (실패 시)")
 
@@ -124,6 +145,7 @@ class PollingSongResponse(BaseModel):
         상태 값 (Suno API 응답):
         - PENDING: Suno API 대기 중
         - processing: Suno API에서 노래 생성 중
+        - uploading: MP3 다운로드 및 Azure Blob 업로드 중
         - SUCCESS: Suno API 노래 생성 완료 (백그라운드 Blob 업로드 시작)
         - TEXT_SUCCESS: Suno API 노래 생성 완료
         - failed: Suno API 노래 생성 실패
@@ -133,13 +155,15 @@ class PollingSongResponse(BaseModel):
         - 백그라운드에서 MP3 파일 다운로드 및 Azure Blob 업로드 시작
         - Song 테이블의 status가 uploading으로 변경
         - 업로드 완료 시 status가 completed로 변경, song_result_url에 Blob URL 저장
+        - completed 상태인 경우 song_result_url 반환
 
     Example Response (Pending):
         {
             "success": true,
             "status": "PENDING",
             "message": "노래 생성 대기 중입니다.",
-            "error_message": null
+            "error_message": null,
+            "song_result_url": null
         }
 
     Example Response (Processing):
@@ -147,15 +171,26 @@ class PollingSongResponse(BaseModel):
             "success": true,
             "status": "processing",
             "message": "노래를 생성하고 있습니다.",
-            "error_message": null
+            "error_message": null,
+            "song_result_url": null
         }
 
-    Example Response (Success):
+    Example Response (Uploading):
+        {
+            "success": true,
+            "status": "uploading",
+            "message": "노래 생성이 완료되었습니다.",
+            "error_message": null,
+            "song_result_url": null
+        }
+
+    Example Response (Success - Completed):
         {
             "success": true,
             "status": "SUCCESS",
             "message": "노래 생성이 완료되었습니다.",
-            "error_message": null
+            "error_message": null,
+            "song_result_url": "https://blob.azure.com/.../song.mp3"
         }
 
     Example Response (Failure):
@@ -163,131 +198,42 @@ class PollingSongResponse(BaseModel):
             "success": false,
             "status": "error",
             "message": "상태 조회에 실패했습니다.",
-            "error_message": "ConnectionError: ..."
+            "error_message": "ConnectionError: ...",
+            "song_result_url": null
         }
     """
 
+    model_config = {
+        "json_schema_extra": {
+            "examples": [
+                {
+                    "success": True,
+                    "status": "processing",
+                    "message": "노래를 생성하고 있습니다.",
+                    "error_message": None,
+                    "song_result_url": None,
+                },
+                {
+                    "success": True,
+                    "status": "SUCCESS",
+                    "message": "노래 생성이 완료되었습니다.",
+                    "error_message": None,
+                    "song_result_url": "https://blob.azure.com/.../song.mp3",
+                },
+            ]
+        }
+    }
+
     success: bool = Field(..., description="조회 성공 여부")
     status: Optional[str] = Field(
-        None, description="Suno API 작업 상태 (PENDING, processing, SUCCESS, TEXT_SUCCESS, failed, error)"
+        None,
+        description="작업 상태 (PENDING, processing, uploading, SUCCESS, TEXT_SUCCESS, failed, error)",
     )
     message: str = Field(..., description="상태 메시지")
     error_message: Optional[str] = Field(None, description="에러 메시지 (실패 시)")
-
-
-class SongListItem(BaseModel):
-    """노래 목록 아이템 스키마
-
-    Usage:
-        GET /songs 응답의 개별 노래 정보
-
-    Example:
-        {
-            "store_name": "스테이 머뭄",
-            "region": "군산",
-            "task_id": "019123ab-cdef-7890-abcd-ef1234567890",
-            "language": "Korean",
-            "song_result_url": "http://localhost:8000/media/2025-01-15/스테이머뭄.mp3",
-            "created_at": "2025-01-15T12:00:00"
-        }
-    """
-
-    store_name: Optional[str] = Field(None, description="업체명")
-    region: Optional[str] = Field(None, description="지역명")
-    task_id: str = Field(..., description="작업 고유 식별자")
-    language: Optional[str] = Field(None, description="언어")
-    song_result_url: Optional[str] = Field(None, description="노래 결과 URL")
-    created_at: Optional[datetime] = Field(None, description="생성 일시")
-
-
-class DownloadSongResponse(BaseModel):
-    """노래 다운로드 응답 스키마 (DB Polling)
-
-    Usage:
-        GET /song/download/{task_id}
-        DB의 Song 테이블 상태를 조회하고 완료 시 Project 정보와 노래 URL을 반환합니다.
-
-    Note:
-        상태 값 (DB 상태):
-        - processing: Suno API에서 노래 생성 중 (song_result_url은 null)
-        - uploading: MP3 다운로드 및 Azure Blob 업로드 중 (song_result_url은 null)
-        - completed: 모든 작업 완료 (song_result_url에 Azure Blob URL 포함)
-        - failed: 노래 생성 또는 업로드 실패
-        - not_found: task_id에 해당하는 Song 없음
-        - error: 조회 중 오류 발생
-
-    Example Response (Processing):
-        {
-            "success": true,
-            "status": "processing",
-            "message": "노래 생성이 진행 중입니다.",
-            "store_name": null,
-            "region": null,
-            "detail_region_info": null,
-            "task_id": "019123ab-cdef-7890-abcd-ef1234567890",
-            "language": null,
-            "song_result_url": null,
-            "created_at": null,
-            "error_message": null
-        }
-
-    Example Response (Uploading):
-        {
-            "success": true,
-            "status": "uploading",
-            "message": "노래 파일을 업로드 중입니다.",
-            "store_name": null,
-            "region": null,
-            "detail_region_info": null,
-            "task_id": "019123ab-cdef-7890-abcd-ef1234567890",
-            "language": null,
-            "song_result_url": null,
-            "created_at": null,
-            "error_message": null
-        }
-
-    Example Response (Completed):
-        {
-            "success": true,
-            "status": "completed",
-            "message": "노래 다운로드가 완료되었습니다.",
-            "store_name": "스테이 머뭄",
-            "region": "군산",
-            "detail_region_info": "군산 신흥동 말랭이 마을",
-            "task_id": "019123ab-cdef-7890-abcd-ef1234567890",
-            "language": "Korean",
-            "song_result_url": "https://blob.azure.com/.../song.mp3",
-            "created_at": "2025-01-15T12:00:00",
-            "error_message": null
-        }
-
-    Example Response (Not Found):
-        {
-            "success": false,
-            "status": "not_found",
-            "message": "task_id 'xxx'에 해당하는 Song을 찾을 수 없습니다.",
-            "store_name": null,
-            "region": null,
-            "detail_region_info": null,
-            "task_id": null,
-            "language": null,
-            "song_result_url": null,
-            "created_at": null,
-            "error_message": "Song not found"
-        }
-    """
-
-    success: bool = Field(..., description="조회 성공 여부")
-    status: str = Field(..., description="DB 처리 상태 (processing, uploading, completed, failed, not_found, error)")
-    message: str = Field(..., description="응답 메시지")
-    store_name: Optional[str] = Field(None, description="업체명")
-    region: Optional[str] = Field(None, description="지역명")
-    detail_region_info: Optional[str] = Field(None, description="상세 지역 정보")
-    task_id: Optional[str] = Field(None, description="작업 고유 식별자")
-    language: Optional[str] = Field(None, description="언어")
-    song_result_url: Optional[str] = Field(None, description="노래 결과 URL")
-    created_at: Optional[datetime] = Field(None, description="생성 일시")
-    error_message: Optional[str] = Field(None, description="에러 메시지 (실패 시)")
+    song_result_url: Optional[str] = Field(
+        None, description="노래 결과 URL (Song 테이블 status가 completed일 때 반환)"
+    )
 
 
 # =============================================================================

app/user/api/routers/v1/auth.py

@@ -78,7 +78,9 @@ async def kakao_callback(
     if forwarded_for:
         ip_address = forwarded_for.split(",")[0].strip()
 
-    logger.debug(f"[ROUTER] 클라이언트 정보 - ip: {ip_address}, user_agent: {user_agent}")
+    logger.debug(
+        f"[ROUTER] 클라이언트 정보 - ip: {ip_address}, user_agent: {user_agent}"
+    )
 
     result = await auth_service.kakao_login(
         code=code,
@@ -89,11 +91,13 @@ async def kakao_callback(
 
     # 프론트엔드로 토큰과 함께 리다이렉트
     redirect_url = (
-        f"https://{prj_settings.PROJECT_DOMAIN}"
+        f"{prj_settings.PROJECT_DOMAIN}"
         f"?access_token={result.access_token}"
         f"&refresh_token={result.refresh_token}"
     )
-    logger.info(f"[ROUTER] 카카오 콜백 완료, 프론트엔드로 리다이렉트 - redirect_url: {redirect_url[:50]}...")
+    logger.info(
+        f"[ROUTER] 카카오 콜백 완료, 프론트엔드로 리다이렉트 - redirect_url: {redirect_url[:50]}..."
+    )
     return RedirectResponse(url=redirect_url, status_code=302)
 
 
@@ -139,7 +143,9 @@ async def kakao_verify(
     if forwarded_for:
         ip_address = forwarded_for.split(",")[0].strip()
 
-    logger.debug(f"[ROUTER] 클라이언트 정보 - ip: {ip_address}, user_agent: {user_agent}")
+    logger.debug(
+        f"[ROUTER] 클라이언트 정보 - ip: {ip_address}, user_agent: {user_agent}"
+    )
 
     result = await auth_service.kakao_login(
         code=body.code,
@@ -148,7 +154,9 @@ async def kakao_verify(
         ip_address=ip_address,
     )
 
-    logger.info(f"[ROUTER] 카카오 인가 코드 검증 완료 - user_id: {result.user.id}, is_new_user: {result.user.is_new_user}")
+    logger.info(
+        f"[ROUTER] 카카오 인가 코드 검증 완료 - user_id: {result.user.id}, is_new_user: {result.user.is_new_user}"
+    )
     return result
 
 

app/user/api/user_admin.py

@@ -0,0 +1,215 @@
+from sqladmin import ModelView
+
+from app.user.models import RefreshToken, SocialAccount, User
+
+
+class UserAdmin(ModelView, model=User):
+    name = "사용자"
+    name_plural = "사용자 목록"
+    icon = "fa-solid fa-user"
+    category = "사용자 관리"
+    page_size = 20
+
+    column_list = [
+        "id",
+        "kakao_id",
+        "email",
+        "nickname",
+        "role",
+        "is_active",
+        "is_deleted",
+        "created_at",
+    ]
+
+    column_details_list = [
+        "id",
+        "kakao_id",
+        "email",
+        "nickname",
+        "profile_image_url",
+        "thumbnail_image_url",
+        "phone",
+        "name",
+        "birth_date",
+        "gender",
+        "is_active",
+        "is_admin",
+        "role",
+        "is_deleted",
+        "deleted_at",
+        "last_login_at",
+        "created_at",
+        "updated_at",
+    ]
+
+    form_excluded_columns = [
+        "created_at",
+        "updated_at",
+        "user_projects",
+        "refresh_tokens",
+        "social_accounts",
+    ]
+
+    column_searchable_list = [
+        User.kakao_id,
+        User.email,
+        User.nickname,
+        User.phone,
+        User.name,
+    ]
+
+    column_default_sort = (User.created_at, True)
+
+    column_sortable_list = [
+        User.id,
+        User.kakao_id,
+        User.email,
+        User.nickname,
+        User.role,
+        User.is_active,
+        User.is_deleted,
+        User.created_at,
+    ]
+
+    column_labels = {
+        "id": "ID",
+        "kakao_id": "카카오 ID",
+        "email": "이메일",
+        "nickname": "닉네임",
+        "profile_image_url": "프로필 이미지",
+        "thumbnail_image_url": "썸네일 이미지",
+        "phone": "전화번호",
+        "name": "실명",
+        "birth_date": "생년월일",
+        "gender": "성별",
+        "is_active": "활성화",
+        "is_admin": "관리자",
+        "role": "권한",
+        "is_deleted": "삭제됨",
+        "deleted_at": "삭제일시",
+        "last_login_at": "마지막 로그인",
+        "created_at": "생성일시",
+        "updated_at": "수정일시",
+    }
+
+
+class RefreshTokenAdmin(ModelView, model=RefreshToken):
+    name = "리프레시 토큰"
+    name_plural = "리프레시 토큰 목록"
+    icon = "fa-solid fa-key"
+    category = "사용자 관리"
+    page_size = 20
+
+    column_list = [
+        "id",
+        "user_id",
+        "is_revoked",
+        "expires_at",
+        "created_at",
+    ]
+
+    column_details_list = [
+        "id",
+        "user_id",
+        "token_hash",
+        "expires_at",
+        "is_revoked",
+        "created_at",
+        "revoked_at",
+        "user_agent",
+        "ip_address",
+    ]
+
+    form_excluded_columns = ["created_at", "user"]
+
+    column_searchable_list = [
+        RefreshToken.user_id,
+        RefreshToken.token_hash,
+        RefreshToken.ip_address,
+    ]
+
+    column_default_sort = (RefreshToken.created_at, True)
+
+    column_sortable_list = [
+        RefreshToken.id,
+        RefreshToken.user_id,
+        RefreshToken.is_revoked,
+        RefreshToken.expires_at,
+        RefreshToken.created_at,
+    ]
+
+    column_labels = {
+        "id": "ID",
+        "user_id": "사용자 ID",
+        "token_hash": "토큰 해시",
+        "expires_at": "만료일시",
+        "is_revoked": "폐기됨",
+        "created_at": "생성일시",
+        "revoked_at": "폐기일시",
+        "user_agent": "User Agent",
+        "ip_address": "IP 주소",
+    }
+
+
+class SocialAccountAdmin(ModelView, model=SocialAccount):
+    name = "소셜 계정"
+    name_plural = "소셜 계정 목록"
+    icon = "fa-solid fa-share-nodes"
+    category = "사용자 관리"
+    page_size = 20
+
+    column_list = [
+        "id",
+        "user_id",
+        "platform",
+        "platform_username",
+        "is_active",
+        "connected_at",
+    ]
+
+    column_details_list = [
+        "id",
+        "user_id",
+        "platform",
+        "platform_user_id",
+        "platform_username",
+        "platform_data",
+        "scope",
+        "token_expires_at",
+        "is_active",
+        "connected_at",
+        "updated_at",
+    ]
+
+    form_excluded_columns = ["connected_at", "updated_at", "user"]
+
+    column_searchable_list = [
+        SocialAccount.user_id,
+        SocialAccount.platform,
+        SocialAccount.platform_user_id,
+        SocialAccount.platform_username,
+    ]
+
+    column_default_sort = (SocialAccount.connected_at, True)
+
+    column_sortable_list = [
+        SocialAccount.id,
+        SocialAccount.user_id,
+        SocialAccount.platform,
+        SocialAccount.is_active,
+        SocialAccount.connected_at,
+    ]
+
+    column_labels = {
+        "id": "ID",
+        "user_id": "사용자 ID",
+        "platform": "플랫폼",
+        "platform_user_id": "플랫폼 사용자 ID",
+        "platform_username": "플랫폼 사용자명",
+        "platform_data": "플랫폼 데이터",
+        "scope": "권한 범위",
+        "token_expires_at": "토큰 만료일시",
+        "is_active": "활성화",
+        "connected_at": "연동일시",
+        "updated_at": "수정일시",
+    }

app/user/services/auth.py

@@ -114,7 +114,7 @@ class AuthService:
         user.last_login_at = datetime.now(timezone.utc)
         await session.commit()
 
-        redirect_url = f"https://{prj_settings.PROJECT_DOMAIN}"
+        redirect_url = f"{prj_settings.PROJECT_DOMAIN}"
         logger.info(f"[AUTH] 카카오 로그인 완료 - user_id: {user.id}, redirect_url: {redirect_url}")
         logger.debug(f"[AUTH] 응답 토큰 정보 - access_token: {access_token[:30]}..., refresh_token: {refresh_token[:30]}...")
 

app/utils/logger.py

@@ -254,14 +254,12 @@ def setup_uvicorn_logging() -> dict:
         # dictConfig 버전 (필수, 항상 1)
         # --------------------------------------------------------
         "version": 1,
-
         # --------------------------------------------------------
         # 기존 로거 비활성화 여부
         # False: 기존 로거 유지 (권장)
         # True: 기존 로거 모두 비활성화
         # --------------------------------------------------------
         "disable_existing_loggers": False,
-
         # --------------------------------------------------------
         # 포맷터 정의
         # 로그 메시지의 출력 형식을 지정합니다.
@@ -276,12 +274,11 @@ def setup_uvicorn_logging() -> dict:
             # HTTP 요청 로그용 포맷터
             # 사용 가능한 변수: client_addr, request_line, status_code
             "access": {
-                "format": "[{asctime}] {levelname:8} [{name}] {client_addr} - \"{request_line}\" {status_code}",
+                "format": '[{asctime}] {levelname:8} [{name}] {client_addr} - "{request_line}" {status_code}',
                 "datefmt": LoggerConfig.DATE_FORMAT,
                 "style": "{",
             },
         },
-
         # --------------------------------------------------------
         # 핸들러 정의
         # 로그를 어디에 출력할지 지정합니다.
@@ -300,7 +297,6 @@ def setup_uvicorn_logging() -> dict:
                 "stream": "ext://sys.stdout",
             },
         },
-
         # --------------------------------------------------------
         # 로거 정의
         # Uvicorn 내부에서 사용하는 로거들을 설정합니다.
@@ -309,19 +305,19 @@ def setup_uvicorn_logging() -> dict:
             # Uvicorn 메인 로거
             "uvicorn": {
                 "handlers": ["default"],
-                "level": "INFO",
+                "level": "DEBUG",
                 "propagate": False,  # 상위 로거로 전파 방지
             },
             # 에러/시작/종료 로그
             "uvicorn.error": {
                 "handlers": ["default"],
-                "level": "INFO",
+                "level": "DEBUG",
                 "propagate": False,
             },
             # HTTP 요청 로그 (GET /path HTTP/1.1 200 등)
             "uvicorn.access": {
                 "handlers": ["access"],
-                "level": "INFO",
+                "level": "DEBUG",
                 "propagate": False,
             },
         },

app/utils/nvMapPwScraper.py

@@ -2,7 +2,7 @@ import asyncio
 from playwright.async_api import async_playwright
 from urllib import parse
 
-class nvMapPwScraper():
+class NvMapPwScraper():
     # cls vars
     is_ready = False
     _playwright = None
@@ -107,7 +107,7 @@ patchedGetter.toString();''')
         if "/place/" in self.page.url:
             return self.page.url
 
-        if (count == self._max_retry / 2):
-            raise Exception("Failed to identify place id. loading timeout")
-        else:
-            raise Exception("Failed to identify place id. item is ambiguous")
+        # if (count == self._max_retry / 2):
+        #     raise Exception("Failed to identify place id. loading timeout")
+        # else:
+        #     raise Exception("Failed to identify place id. item is ambiguous")

app/utils/prompts-back/lyric_prompt.json

@@ -0,0 +1,34 @@
+{
+    "model": "gpt-5-mini",
+    "prompt_variables": [
+        "customer_name",
+        "region",
+        "detail_region_info",
+        "marketing_intelligence_summary",
+        "language",
+        "promotional_expression_example",
+        "timing_rules"
+    ],
+    "output_format": {
+        "format": {
+            "type": "json_schema",
+            "name": "lyric",
+            "schema": {
+                "type": "object",
+                "properties": {
+                    "lyric": {
+                        "type": "string"
+                    },
+                    "suno_prompt":{
+                        "type" : "string"
+                    }
+                },
+                "required": [
+                    "lyric", "suno_prompt"
+                ],
+                "additionalProperties": false
+            },
+            "strict": true
+        }
+    }
+}

app/utils/prompts-back/lyric_prompt.txt

@@ -0,0 +1,76 @@
+
+[ROLE]
+You are a content marketing expert, brand strategist, and creative songwriter
+specializing in Korean pension / accommodation businesses.
+You create lyrics strictly based on Brand & Marketing Intelligence analysis
+and optimized for viral short-form video content.
+
+[INPUT]
+Business Name: {customer_name}
+Region: {region}
+Region Details: {detail_region_info}
+Brand & Marketing Intelligence Report: {marketing_intelligence_summary}
+Output Language: {language}
+
+[INTERNAL ANALYSIS – DO NOT OUTPUT]
+Internally analyze the following to guide all creative decisions:
+- Core brand identity and positioning
+- Emotional hooks derived from selling points
+- Target audience lifestyle, desires, and travel motivation
+- Regional atmosphere and symbolic imagery
+- How the stay converts into “shareable moments”
+- Which selling points must surface implicitly in lyrics
+
+[LYRICS & MUSIC CREATION TASK]
+Based on the Brand & Marketing Intelligence Report for [{customer_name} ({region})], generate:
+- Original promotional lyrics
+- Music attributes for AI music generation (Suno-compatible prompt)
+The output must be designed for VIRAL DIGITAL CONTENT
+(short-form video, reels, ads).
+
+[LYRICS REQUIREMENTS]
+Mandatory Inclusions:
+- Business name
+- Region name
+- Promotion subject
+- Promotional expressions including:
+{promotional_expression_example}
+
+Content Rules:
+- Lyrics must be emotionally driven, not descriptive listings
+- Selling points must be IMPLIED, not explained
+- Must sound natural when sung
+- Must feel like a lifestyle moment, not an advertisement
+
+Tone & Style:
+- Warm, emotional, and aspirational
+- Trendy, viral-friendly phrasing
+- Calm but memorable hooks
+- Suitable for travel / stay-related content
+
+[SONG & MUSIC ATTRIBUTES – FOR SUNO PROMPT]
+After the lyrics, generate a concise music prompt including:
+Song mood (emotional keywords)
+BPM range
+Recommended genres (max 2)
+Key musical motifs or instruments
+Overall vibe (1 short sentence)
+
+[CRITICAL LANGUAGE REQUIREMENT – ABSOLUTE RULE]
+ALL OUTPUT MUST BE 100% WRITTEN IN {language}.
+no mixed languages
+All names, places, and expressions must be in {language} 
+Any violation invalidates the entire output
+
+[OUTPUT RULES – STRICT]
+{timing_rules}
+
+No explanations
+No headings
+No bullet points
+No analysis
+No extra text
+
+[FAILURE FORMAT]
+If generation is impossible:
+ERROR: Brief reason in English

app/utils/prompts-back/marketing_prompt.json

@@ -0,0 +1,91 @@
+{
+    "model": "gpt-5-mini",
+    "prompt_variables": [
+        "customer_name",
+        "region",
+        "detail_region_info"
+    ],
+    "output_format": {
+        "format": {
+            "type": "json_schema",
+            "name": "report",
+            "schema": {
+                "type": "object",
+                "properties": {
+                    "report": {
+                        "type": "object",
+                        "properties": {
+                            "summary": {
+                                "type": "string"
+                            },
+                            "details": {
+                                "type": "array",
+                                "items": {
+                                    "type": "object",
+                                    "properties": {
+                                        "detail_title": {
+                                            "type": "string"
+                                        },
+                                        "detail_description": {
+                                            "type": "string"
+                                        }
+                                    },
+                                    "required": [
+                                        "detail_title",
+                                        "detail_description"
+                                    ],
+                                    "additionalProperties": false
+                                }
+                            }
+                        },
+                        "required": [
+                            "summary",
+                            "details"
+                        ],
+                        "additionalProperties": false
+                    },
+                    "selling_points": {
+                        "type": "array",
+                        "items": {
+                            "type": "object",
+                            "properties": {
+                                "category": {
+                                    "type": "string"
+                                },
+                                "keywords": {
+                                    "type": "string"
+                                },
+                                "description": {
+                                    "type": "string"
+                                }
+                            },
+                            "required": [
+                                "category",
+                                "keywords",
+                                "description"
+                            ],
+                            "additionalProperties": false
+                        }
+                    },
+                    "tags": {
+                        "type": "array",
+                        "items": {
+                            "type": "string"
+                        }
+                    },
+                    "contents_advise": {
+                        "type": "string"
+                    }
+                },
+                "required": [
+                    "report",
+                    "selling_points",
+                    "tags",
+                    "contents_advise"
+                ],
+                "additionalProperties": false
+            },
+            "strict": true
+        }
+    }
+}

app/utils/prompts-back/marketing_prompt.txt

@@ -0,0 +1,64 @@
+
+[Role & Objective]
+Act as a content marketing expert with strong domain knowledge in the Korean pension / stay-accommodation industry.
+Your goal is to produce a Marketing Intelligence Report that will be shown to accommodation owners BEFORE any content is generated.
+The report must clearly explain what makes the property sellable, marketable, and scalable through content.
+
+[INPUT]
+- Business Name: {customer_name}
+- Region: {region}
+- Region Details: {detail_region_info}
+
+[Core Analysis Requirements]
+Analyze the property based on:
+Location, concept, and nearby environment
+Target customer behavior and reservation decision factors
+Include:
+- Target customer segments & personas
+- Unique Selling Propositions (USPs)
+- Competitive landscape (direct & indirect competitors)
+- Market positioning
+
+[Key Selling Point Structuring – UI Optimized]
+From the analysis above, extract the main Key Selling Points using the structure below.
+Rules:
+Focus only on factors that directly influence booking decisions
+Each selling point must be concise and visually scannable
+Language must be reusable for ads, short-form videos, and listing headlines
+Avoid full sentences in descriptions; use short selling phrases
+Do not provide in report
+
+Output format:
+[Category]
+(Tag keyword – 5~8 words, noun-based, UI oval-style)
+One-line selling phrase (not a full sentence)
+Limit:
+5 to 8 Key Selling Points only
+Do not provide in report
+
+[Content & Automation Readiness Check]
+Ensure that:
+Each tag keyword can directly map to a content theme
+Each selling phrase can be used as:
+- Video hook
+- Image headline
+- Ad copy snippet
+
+
+[Tag Generation Rules]
+- Tags must include **only core keywords that can be directly used for viral video song lyrics**
+- Each tag should be selected with **search discovery + emotional resonance + reservation conversion** in mind
+- The number of tags must be **exactly 5**
+- Tags must be **nouns or short keyword phrases**; full sentences are strictly prohibited
+- The following categories must be **balanced and all represented**:
+  1) **Location / Local context** (region name, neighborhood, travel context)
+  2) **Accommodation positioning** (emotional stay, private stay, boutique stay, etc.)
+  3) **Emotion / Experience** (healing, rest, one-day escape, memory, etc.)
+  4) **SNS / Viral signals** (Instagram vibes, picture-perfect day, aesthetic travel, etc.)
+  5) **Travel & booking intent** (travel, getaway, stay, relaxation, etc.)
+
+- If a brand name exists, **at least one tag must include the brand name or a brand-specific expression**
+- Avoid overly generic keywords (e.g., “hotel”, “travel” alone); **prioritize distinctive, differentiating phrases**
+- The final output must strictly follow the JSON format below, with no additional text
+
+  "tags": ["Tag1", "Tag2", "Tag3", "Tag4", "Tag5"]

app/utils/prompts-back/marketing_prompt_20260116.txt

@@ -0,0 +1,62 @@
+
+[Role & Objective]
+Act as a content marketing expert with strong domain knowledge in the Korean pension / stay-accommodation industry.
+Your goal is to produce a Marketing Intelligence Report that will be shown to accommodation owners BEFORE any content is generated.
+The report must clearly explain what makes the property sellable, marketable, and scalable through content.
+
+[INPUT]
+- Business Name: {customer_name}
+- Region: {region}
+- Region Details: {detail_region_info}
+
+[Core Analysis Requirements]
+Analyze the property based on:
+Location, concept, photos, online presence, and nearby environment
+Target customer behavior and reservation decision factors
+Include:
+- Target customer segments & personas
+- Unique Selling Propositions (USPs)
+- Competitive landscape (direct & indirect competitors)
+- Market positioning
+
+[Key Selling Point Structuring – UI Optimized]
+From the analysis above, extract the main Key Selling Points using the structure below.
+Rules:
+Focus only on factors that directly influence booking decisions
+Each selling point must be concise and visually scannable
+Language must be reusable for ads, short-form videos, and listing headlines
+Avoid full sentences in descriptions; use short selling phrases
+
+Output format:
+[Category]
+(Tag keyword – 5~8 words, noun-based, UI oval-style)
+One-line selling phrase (not a full sentence)
+Limit:
+5 to 8 Key Selling Points only
+
+[Content & Automation Readiness Check]
+Ensure that:
+Each tag keyword can directly map to a content theme
+Each selling phrase can be used as:
+- Video hook
+- Image headline
+- Ad copy snippet
+
+
+[Tag Generation Rules]
+- Tags must include **only core keywords that can be directly used for viral video song lyrics**
+- Each tag should be selected with **search discovery + emotional resonance + reservation conversion** in mind
+- The number of tags must be **exactly 5**
+- Tags must be **nouns or short keyword phrases**; full sentences are strictly prohibited
+- The following categories must be **balanced and all represented**:
+  1) **Location / Local context** (region name, neighborhood, travel context)
+  2) **Accommodation positioning** (emotional stay, private stay, boutique stay, etc.)
+  3) **Emotion / Experience** (healing, rest, one-day escape, memory, etc.)
+  4) **SNS / Viral signals** (Instagram vibes, picture-perfect day, aesthetic travel, etc.)
+  5) **Travel & booking intent** (travel, getaway, stay, relaxation, etc.)
+
+- If a brand name exists, **at least one tag must include the brand name or a brand-specific expression**
+- Avoid overly generic keywords (e.g., “hotel”, “travel” alone); **prioritize distinctive, differentiating phrases**
+- The final output must strictly follow the JSON format below, with no additional text
+
+  "tags": ["Tag1", "Tag2", "Tag3", "Tag4", "Tag5"]

app/utils/prompts-back/marketing_prompt_20260119.json

@@ -0,0 +1,58 @@
+{
+    "model": "gpt-5.2",
+    "prompt_variables": [
+        "customer_name",
+        "region",
+        "detail_region_info"
+    ],
+    "output_format": {
+        "format": {
+            "type": "json_schema",
+            "name": "report",
+            "schema": {
+                "type": "object",
+                "properties": {
+                    "report": {
+                        "type": "string"
+                    },
+                    "selling_points": {
+                        "type": "array",
+                        "items": {
+                            "type": "object",
+                            "properties": {
+                                "category": {
+                                    "type": "string"
+                                },
+                                "keywords": {
+                                    "type": "string"
+                                },
+                                "description": {
+                                    "type": "string"
+                                }
+                            },
+                            "required": [
+                                "category",
+                                "keywords",
+                                "description"
+                            ],
+                            "additionalProperties": false
+                        }
+                    },
+                    "tags": {
+                        "type": "array",
+                        "items": {
+                            "type": "string"
+                        }
+                    }
+                },
+                "required": [
+                    "report",
+                    "selling_points",
+                    "tags"
+                ],
+                "additionalProperties": false
+            },
+            "strict": true
+        }
+    }
+}

app/utils/prompts-back/prompts.py

@@ -0,0 +1,76 @@
+import os, json
+from abc import ABCMeta
+from config import prompt_settings
+from app.utils.logger import get_logger
+
+logger = get_logger("prompt")
+
+class Prompt():
+    prompt_name : str # ex) marketing_prompt
+    prompt_template_path : str #프롬프트 경로
+    prompt_template : str # fstring 포맷
+    prompt_input : list
+    prompt_output : dict
+    prompt_model : str
+              
+    def __init__(self, prompt_name, prompt_template_path):
+        self.prompt_name = prompt_name
+        self.prompt_template_path = prompt_template_path
+        self.prompt_template, prompt_dict = self.read_prompt()
+        self.prompt_input = prompt_dict['prompt_variables']
+        self.prompt_output = prompt_dict['output_format']
+        self.prompt_model = prompt_dict.get('model', "gpt-5-mini") 
+
+    def _reload_prompt(self):
+        self.prompt_template, prompt_dict = self.read_prompt()
+        self.prompt_input = prompt_dict['prompt_variables']
+        self.prompt_output = prompt_dict['output_format']
+        self.prompt_model = prompt_dict.get('model', "gpt-5-mini") 
+
+    def read_prompt(self) -> tuple[str, dict]:
+        template_text_path = self.prompt_template_path + ".txt"
+        prompt_dict_path = self.prompt_template_path + ".json"
+        with open(template_text_path, "r") as fp:
+            prompt_template = fp.read()
+        with open(prompt_dict_path, "r") as fp:
+            prompt_dict = json.load(fp)
+
+        return prompt_template, prompt_dict
+
+    def build_prompt(self, input_data:dict) -> str:
+        self.check_input(input_data)
+        build_template = self.prompt_template
+        logger.debug(f"build_template: {build_template}")
+        logger.debug(f"input_data: {input_data}")
+        build_template = build_template.format(**input_data)
+        return build_template
+          
+    def check_input(self, input_data:dict) -> bool:
+        missing_variables = input_data.keys() - set(self.prompt_input)
+        if missing_variables:
+            raise Exception(f"missing_variable for prompt {self.prompt_name} : {missing_variables}")
+
+        flooding_variables = set(self.prompt_input) - input_data.keys()
+        if flooding_variables:
+            raise Exception(f"flooding_variables for prompt {self.prompt_name} : {flooding_variables}")
+        return True
+    
+marketing_prompt = Prompt(
+    prompt_name=prompt_settings.MARKETING_PROMPT_NAME,
+    prompt_template_path=os.path.join(prompt_settings.PROMPT_FOLDER_ROOT, prompt_settings.MARKETING_PROMPT_NAME)
+)
+
+summarize_prompt = Prompt(
+    prompt_name=prompt_settings.SUMMARIZE_PROMPT_NAME,
+    prompt_template_path=os.path.join(prompt_settings.PROMPT_FOLDER_ROOT, prompt_settings.SUMMARIZE_PROMPT_NAME)
+)
+
+lyric_prompt = Prompt(
+    prompt_name=prompt_settings.LYLIC_PROMPT_NAME,
+    prompt_template_path=os.path.join(prompt_settings.PROMPT_FOLDER_ROOT, prompt_settings.LYLIC_PROMPT_NAME)
+)
+
+def reload_all_prompt():
+    marketing_prompt._reload_prompt()
+    summarize_prompt._reload_prompt()
+    lyric_prompt._reload_prompt()

app/utils/prompts-back/summarize_prompt.json

@@ -0,0 +1,33 @@
+{
+    "prompt_variables": [
+        "report",
+        "selling_points"
+    ],
+    "output_format": {
+        "format": {
+            "type": "json_schema",
+            "name": "tags",
+            "schema": {
+                "type": "object",
+                "properties": {
+                    "category": {
+                        "type": "string"
+                    },
+                    "tag_keywords": {
+                        "type": "string"
+                    },
+                    "description": {
+                        "type": "string"
+                    }
+                },
+                "required": [
+                    "category",
+                    "tag_keywords",
+                    "description"
+                ],
+                "additionalProperties": false
+            },
+            "strict": true
+        }
+    }
+} 

app/utils/prompts-back/summarize_prompt.txt

@@ -0,0 +1,53 @@
+
+입력 : 
+분석 보고서
+{report}
+
+셀링 포인트
+{selling_points}
+
+위 분석 결과를 바탕으로, 주요 셀링 포인트를 다음 구조로 재정리하라.
+
+조건:
+각 셀링 포인트는 반드시 ‘카테고리 → 태그 키워드 → 한 줄 설명’ 구조를 가질 것
+태그 키워드는 UI 상에서 타원(oval) 형태의 시각적 태그로 사용될 것을 가정하여
+- 3 ~ 6단어 이내
+- 명사 또는 명사형 키워드로 작성
+- 설명은 문장이 아닌, 짧은 ‘셀링 문구’ 형태로 작성할 것
+- 광고·숏폼·상세페이지 어디에도 바로 재사용 가능해야 함
+- 전체 셀링 포인트 개수는 5~7개로 제한
+
+출력 형식:
+[카테고리명]
+(태그 키워드)
+- 한 줄 설명 문구
+
+예시: 
+[공간 정체성]
+(100년 적산가옥 · 시간의 결)
+- 하루를 ‘숙박’이 아닌 ‘체류’로 바꾸는 공간
+
+[입지 & 희소성]
+(말랭이마을 · 로컬 히든플레이스)
+- 관광지가 아닌, 군산을 아는 사람의 선택
+
+[프라이버시]
+(독채 숙소 · 프라이빗 스테이)
+- 누구의 방해도 없는 완전한 휴식 구조
+
+[비주얼 경쟁력]
+(감성 인테리어 · 자연광 스폿)
+- 찍는 순간 콘텐츠가 되는 공간 설계
+
+[타깃 최적화]
+(커플 · 소규모 여행)
+- 둘에게 가장 이상적인 공간 밀도
+
+[체류 경험]
+(아무것도 안 해도 되는 하루)
+- 일정 없이도 만족되는 하루 루틴
+
+[브랜드 포지션]
+(호텔도 펜션도 아닌 아지트)
+- 다시 돌아오고 싶은 개인적 장소
+    

app/utils/suno.py

@@ -179,7 +179,7 @@ class SunoService:
                 raise ValueError("Suno API returned empty response for task status")
 
             return data
-        
+
     async def get_lyric_timestamp(self, task_id: str, audio_id: str) -> dict[str, Any]:
         """
         음악 타임스탬프 정보 추출
@@ -189,27 +189,24 @@ class SunoService:
             audio_id: 사용할 audio id
 
         Returns:
-            data.alignedWords: 수노 가사 input - startS endS 시간 데이터 매핑 
+            data.alignedWords: 수노 가사 input - startS endS 시간 데이터 매핑
         """
 
-        payload = {
-            "task_id" : task_id,
-            "audio_id" : audio_id
-        }
+        payload = {"task_id": task_id, "audio_id": audio_id}
         async with httpx.AsyncClient() as client:
             response = await client.post(
                 f"{self.BASE_URL}/generate/get-timestamped-lyrics",
                 headers=self.headers,
                 json=payload,
-                timeout=30.0,
+                timeout=120.0,
             )
             response.raise_for_status()
             data = response.json()
 
-            if not data or not data['data']:
+            if not data or not data["data"]:
                 raise ValueError("Suno API returned empty response for task status")
 
-            return data['data']['alignedWords']
+            return data["data"]["alignedWords"]
 
     def parse_status_response(self, result: dict | None) -> PollingSongResponse:
         """Suno API 상태 응답을 파싱하여 PollingSongResponse로 변환합니다.
@@ -284,83 +281,85 @@ class SunoService:
             message=status_messages.get(status, f"상태: {status}"),
             error_message=None,
         )
-    
+
     def align_lyrics(self, word_data: list[dict], sentences: list[str]) -> list[dict]:
         """
         word의 시작/끝 포지션만 저장하고, 시간은 word에서 참조
         """
-        
+
         # Step 1: 전체 텍스트 + word별 포지션 범위 저장
         full_text = ""
         word_ranges = []  # [(start_pos, end_pos, entry), ...]
-        
+
         for entry in word_data:
-            word = entry['word']
+            word = entry["word"]
             start_pos = len(full_text)
             full_text += word
             end_pos = len(full_text) - 1
-            
+
             word_ranges.append((start_pos, end_pos, entry))
-    
+
         # Step 2: 메타데이터 제거 + 포지션 재매핑
         meta_ranges = []
         i = 0
         while i < len(full_text):
-            if full_text[i] == '[':
+            if full_text[i] == "[":
                 start = i
-                while i < len(full_text) and full_text[i] != ']':
+                while i < len(full_text) and full_text[i] != "]":
                     i += 1
                 meta_ranges.append((start, i + 1))
             i += 1
-    
+
         clean_text = ""
         new_to_old = {}  # 클린 포지션 -> 원본 포지션
-        
+
         for old_pos, char in enumerate(full_text):
             in_meta = any(s <= old_pos < e for s, e in meta_ranges)
             if not in_meta:
                 new_to_old[len(clean_text)] = old_pos
                 clean_text += char
-    
+
         # Step 3: 포지션으로 word 찾기
         def get_word_at(old_pos: int):
             for start, end, entry in word_ranges:
                 if start <= old_pos <= end:
                     return entry
             return None
-        
+
         # Step 4: 문장 매칭
         def normalize(text):
-            return ''.join(c for c in text if c not in ' \n\t-')
-        
+            return "".join(c for c in text if c not in " \n\t-")
+
         norm_clean = normalize(clean_text)
-        norm_to_clean = [i for i, c in enumerate(clean_text) if c not in ' \n\t-']
-        
+        norm_to_clean = [i for i, c in enumerate(clean_text) if c not in " \n\t-"]
+
         results = []
         search_pos = 0
-    
+
         for sentence in sentences:
             norm_sentence = normalize(sentence)
             found_pos = norm_clean.find(norm_sentence, search_pos)
-    
+
             if found_pos != -1:
                 clean_start = norm_to_clean[found_pos]
                 clean_end = norm_to_clean[found_pos + len(norm_sentence) - 1]
-                
+
                 old_start = new_to_old[clean_start]
                 old_end = new_to_old[clean_end]
-                
+
                 word_start = get_word_at(old_start)
                 word_end = get_word_at(old_end)
-                
-                results.append({
-                    'text': sentence,
-                    'start_sec': word_start['startS'],
-                    'end_sec': word_end['endS'],
-                })
-                
+
+                results.append(
+                    {
+                        "text": sentence,
+                        "start_sec": word_start["startS"],
+                        "end_sec": word_end["endS"],
+                    }
+                )
+
                 search_pos = found_pos + len(norm_sentence)
             else:
-                results.append({'text': sentence, 'start_sec': None, 'end_sec': None})
-        
-        return results
+                results.append({"text": sentence, "start_sec": None, "end_sec": None})
+
+        return results

app/video/api/routers/v1/video.py

@@ -14,6 +14,7 @@ Video API Router
     app.include_router(router, prefix="/api/v1")
 """
 
+import json
 from typing import Literal
 
 from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, Query
@@ -21,13 +22,13 @@ from sqlalchemy import func, select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.database.session import get_session
-from app.dependencies.pagination import (
-    PaginationParams,
-    get_pagination_params,
-)
+from app.dependencies.pagination import PaginationParams, get_pagination_params
 from app.home.models import Image, Project
 from app.lyric.models import Lyric
 from app.song.models import Song, SongTimestamp
+from app.utils.creatomate import CreatomateService
+from app.utils.logger import get_logger
+from app.utils.pagination import PaginatedResponse
 from app.video.models import Video
 from app.video.schemas.video_schema import (
     DownloadVideoResponse,
@@ -37,9 +38,6 @@ from app.video.schemas.video_schema import (
     VideoRenderData,
 )
 from app.video.worker.video_task import download_and_upload_video_to_blob
-from app.utils.creatomate import CreatomateService
-from app.utils.pagination import PaginatedResponse
-from app.utils.logger import get_logger
 
 logger = get_logger("video")
 
@@ -114,10 +112,13 @@ async def generate_video(
     따라서 쿼리는 순차적으로 실행합니다.
     """
     import time
+
     from app.database.session import AsyncSessionLocal
 
     request_start = time.perf_counter()
-    logger.info(f"[generate_video] START - task_id: {task_id}, orientation: {orientation}")
+    logger.info(
+        f"[generate_video] START - task_id: {task_id}, orientation: {orientation}"
+    )
 
     # ==========================================================================
     # 1단계: DB 조회 및 초기 데이터 저장 (세션을 명시적으로 열고 닫음)
@@ -170,13 +171,17 @@ async def generate_video(
             )
 
             query_time = time.perf_counter()
-            logger.debug(f"[generate_video] Queries completed - task_id: {task_id}, "
-                  f"elapsed: {(query_time - request_start)*1000:.1f}ms")
+            logger.debug(
+                f"[generate_video] Queries completed - task_id: {task_id}, "
+                f"elapsed: {(query_time - request_start) * 1000:.1f}ms"
+            )
 
             # ===== 결과 처리: Project =====
             project = project_result.scalar_one_or_none()
             if not project:
-                logger.warning(f"[generate_video] Project NOT FOUND - task_id: {task_id}")
+                logger.warning(
+                    f"[generate_video] Project NOT FOUND - task_id: {task_id}"
+                )
                 raise HTTPException(
                     status_code=404,
                     detail=f"task_id '{task_id}'에 해당하는 Project를 찾을 수 없습니다.",
@@ -248,8 +253,10 @@ async def generate_video(
             await session.commit()
             video_id = video.id
             stage1_time = time.perf_counter()
-            logger.info(f"[generate_video] Video saved - task_id: {task_id}, id: {video_id}, "
-                  f"stage1_elapsed: {(stage1_time - request_start)*1000:.1f}ms")
+            logger.info(
+                f"[generate_video] Video saved - task_id: {task_id}, id: {video_id}, "
+                f"stage1_elapsed: {(stage1_time - request_start) * 1000:.1f}ms"
+            )
         # 세션이 여기서 자동으로 닫힘 (async with 블록 종료)
 
     except HTTPException:
@@ -269,15 +276,21 @@ async def generate_video(
     # ==========================================================================
     stage2_start = time.perf_counter()
     try:
-        logger.info(f"[generate_video] Stage 2 START - Creatomate API - task_id: {task_id}")
+        logger.info(
+            f"[generate_video] Stage 2 START - Creatomate API - task_id: {task_id}"
+        )
         creatomate_service = CreatomateService(
             orientation=orientation,
             target_duration=song_duration,
         )
-        logger.debug(f"[generate_video] Using template_id: {creatomate_service.template_id}, duration: {creatomate_service.target_duration} (song duration: {song_duration})")
+        logger.debug(
+            f"[generate_video] Using template_id: {creatomate_service.template_id}, duration: {creatomate_service.target_duration} (song duration: {song_duration})"
+        )
 
         # 6-1. 템플릿 조회 (비동기)
-        template = await creatomate_service.get_one_template_data_async(creatomate_service.template_id)
+        template = await creatomate_service.get_one_template_data_async(
+            creatomate_service.template_id
+        )
         logger.debug(f"[generate_video] Template fetched - task_id: {task_id}")
 
         # 6-2. elements에서 리소스 매핑 생성
@@ -302,26 +315,49 @@ async def generate_video(
             template,
             creatomate_service.target_duration,
         )
-        logger.debug(f"[generate_video] Duration extended to {creatomate_service.target_duration}s - task_id: {task_id}")
+        logger.debug(
+            f"[generate_video] Duration extended to {creatomate_service.target_duration}s - task_id: {task_id}"
+        )
 
         # 이런거 추가해야하는데 AI가 자꾸 번호 달면 제가 번호를 다 밀어야 하나요?
 
         song_timestamp_result = await session.execute(
-            select(SongTimestamp)
-            .where(SongTimestamp.suno_audio_id == song.suno_audio_id)
+            select(SongTimestamp).where(
+                SongTimestamp.suno_audio_id == song.suno_audio_id
+            )
         )
         song_timestamp_list = song_timestamp_result.scalars().all()
 
+        logger.debug(
+            f"[generate_video] song_timestamp_list count: {len(song_timestamp_list)}"
+        )
+        for i, ts in enumerate(song_timestamp_list):
+            logger.debug(
+                f"[generate_video] timestamp[{i}]: lyric_line={ts.lyric_line}, start_time={ts.start_time}, end_time={ts.end_time}"
+            )
+
         text_template = creatomate_service.get_text_template()
         for idx, aligned in enumerate(song_timestamp_list):
-            caption = creatomate_service.lining_lyric(text_template, idx, aligned.lyric_line, aligned.start_time, aligned.end_time )
-            final_template['source']['elements'].append(caption)
+            caption = creatomate_service.lining_lyric(
+                text_template,
+                idx,
+                aligned.lyric_line,
+                aligned.start_time,
+                aligned.end_time,
+            )
+            final_template["source"]["elements"].append(caption)
+
+        logger.debug(
+            f"[generate_video] final_template: {json.dumps(final_template, indent=2, ensure_ascii=False)}"
+        )
 
         # 6-5. 커스텀 렌더링 요청 (비동기)
         render_response = await creatomate_service.make_creatomate_custom_call_async(
             final_template["source"],
         )
-        logger.debug(f"[generate_video] Creatomate API response - task_id: {task_id}, response: {render_response}")
+        logger.debug(
+            f"[generate_video] Creatomate API response - task_id: {task_id}, response: {render_response}"
+        )
 
         # 렌더 ID 추출
         if isinstance(render_response, list) and len(render_response) > 0:
@@ -335,13 +371,16 @@ async def generate_video(
         logger.info(
             f"[generate_video] Stage 2 DONE - task_id: {task_id}, "
             f"render_id: {creatomate_render_id}, "
-            f"stage2_elapsed: {(stage2_time - stage2_start)*1000:.1f}ms"
+            f"stage2_elapsed: {(stage2_time - stage2_start) * 1000:.1f}ms"
         )
 
     except Exception as e:
-        logger.error(f"[generate_video] Creatomate API EXCEPTION - task_id: {task_id}, error: {e}")
+        logger.error(
+            f"[generate_video] Creatomate API EXCEPTION - task_id: {task_id}, error: {e}"
+        )
         # 외부 API 실패 시 Video 상태를 failed로 업데이트
         from app.database.session import AsyncSessionLocal
+
         async with AsyncSessionLocal() as update_session:
             video_result = await update_session.execute(
                 select(Video).where(Video.id == video_id)
@@ -365,6 +404,7 @@ async def generate_video(
     logger.info(f"[generate_video] Stage 3 START - DB update - task_id: {task_id}")
     try:
         from app.database.session import AsyncSessionLocal
+
         async with AsyncSessionLocal() as update_session:
             video_result = await update_session.execute(
                 select(Video).where(Video.id == video_id)
@@ -378,12 +418,12 @@ async def generate_video(
         total_time = stage3_time - request_start
         logger.debug(
             f"[generate_video] Stage 3 DONE - task_id: {task_id}, "
-            f"stage3_elapsed: {(stage3_time - stage3_start)*1000:.1f}ms"
+            f"stage3_elapsed: {(stage3_time - stage3_start) * 1000:.1f}ms"
         )
         logger.info(
             f"[generate_video] SUCCESS - task_id: {task_id}, "
             f"render_id: {creatomate_render_id}, "
-            f"total_time: {total_time*1000:.1f}ms"
+            f"total_time: {total_time * 1000:.1f}ms"
         )
 
         return GenerateVideoResponse(
@@ -395,7 +435,9 @@ async def generate_video(
         )
 
     except Exception as e:
-        logger.error(f"[generate_video] Update EXCEPTION - task_id: {task_id}, error: {e}")
+        logger.error(
+            f"[generate_video] Update EXCEPTION - task_id: {task_id}, error: {e}"
+        )
         return GenerateVideoResponse(
             success=False,
             task_id=task_id,
@@ -454,11 +496,15 @@ async def get_video_status(
     succeeded 상태인 경우 백그라운드에서 MP4 파일을 다운로드하고
     Video 테이블의 status를 completed로, result_movie_url을 업데이트합니다.
     """
-    logger.info(f"[get_video_status] START - creatomate_render_id: {creatomate_render_id}")
+    logger.info(
+        f"[get_video_status] START - creatomate_render_id: {creatomate_render_id}"
+    )
     try:
         creatomate_service = CreatomateService()
         result = await creatomate_service.get_render_status_async(creatomate_render_id)
-        logger.debug(f"[get_video_status] Creatomate API response - creatomate_render_id: {creatomate_render_id}, status: {result.get('status')}")
+        logger.debug(
+            f"[get_video_status] Creatomate API response - creatomate_render_id: {creatomate_render_id}, status: {result.get('status')}"
+        )
 
         status = result.get("status", "unknown")
         video_url = result.get("url")
@@ -496,7 +542,9 @@ async def get_video_status(
                 store_name = project.store_name if project else "video"
 
                 # 백그라운드 태스크로 MP4 다운로드 → Blob 업로드 → DB 업데이트 → 임시 파일 삭제
-                logger.info(f"[get_video_status] Background task args - task_id: {video.task_id}, video_url: {video_url}, store_name: {store_name}")
+                logger.info(
+                    f"[get_video_status] Background task args - task_id: {video.task_id}, video_url: {video_url}, store_name: {store_name}"
+                )
                 background_tasks.add_task(
                     download_and_upload_video_to_blob,
                     task_id=video.task_id,
@@ -504,7 +552,9 @@ async def get_video_status(
                     store_name=store_name,
                 )
             elif video and video.status == "completed":
-                logger.debug(f"[get_video_status] SKIPPED - Video already completed, creatomate_render_id: {creatomate_render_id}")
+                logger.debug(
+                    f"[get_video_status] SKIPPED - Video already completed, creatomate_render_id: {creatomate_render_id}"
+                )
 
         render_data = VideoRenderData(
             id=result.get("id"),
@@ -513,7 +563,9 @@ async def get_video_status(
             snapshot_url=result.get("snapshot_url"),
         )
 
-        logger.info(f"[get_video_status] SUCCESS - creatomate_render_id: {creatomate_render_id}")
+        logger.info(
+            f"[get_video_status] SUCCESS - creatomate_render_id: {creatomate_render_id}"
+        )
         return PollingVideoResponse(
             success=True,
             status=status,
@@ -526,7 +578,9 @@ async def get_video_status(
     except Exception as e:
         import traceback
 
-        logger.error(f"[get_video_status] EXCEPTION - creatomate_render_id: {creatomate_render_id}, error: {e}")
+        logger.error(
+            f"[get_video_status] EXCEPTION - creatomate_render_id: {creatomate_render_id}, error: {e}"
+        )
         return PollingVideoResponse(
             success=False,
             status="error",
@@ -598,7 +652,9 @@ async def download_video(
                 error_message="Video not found",
             )
 
-        logger.debug(f"[download_video] Video found - task_id: {task_id}, status: {video.status}")
+        logger.debug(
+            f"[download_video] Video found - task_id: {task_id}, status: {video.status}"
+        )
 
         # processing 상태인 경우
         if video.status == "processing":
@@ -627,7 +683,9 @@ async def download_video(
         )
         project = project_result.scalar_one_or_none()
 
-        logger.info(f"[download_video] COMPLETED - task_id: {task_id}, result_movie_url: {video.result_movie_url}")
+        logger.info(
+            f"[download_video] COMPLETED - task_id: {task_id}, result_movie_url: {video.result_movie_url}"
+        )
         return DownloadVideoResponse(
             success=True,
             status="completed",
@@ -689,7 +747,9 @@ async def get_videos(
     pagination: PaginationParams = Depends(get_pagination_params),
 ) -> PaginatedResponse[VideoListItem]:
     """완료된 영상 목록을 페이지네이션하여 반환합니다."""
-    logger.info(f"[get_videos] START - page: {pagination.page}, page_size: {pagination.page_size}")
+    logger.info(
+        f"[get_videos] START - page: {pagination.page}, page_size: {pagination.page_size}"
+    )
     try:
         offset = (pagination.page - 1) * pagination.page_size
 

app/video/api/video_admin.py

@@ -26,6 +26,7 @@ class VideoAdmin(ModelView, model=Video):
         "lyric_id",
         "song_id",
         "task_id",
+        "creatomate_render_id",
         "status",
         "result_movie_url",
         "created_at",
@@ -56,6 +57,7 @@ class VideoAdmin(ModelView, model=Video):
         "lyric_id": "가사 ID",
         "song_id": "노래 ID",
         "task_id": "작업 ID",
+        "creatomate_render_id": "Creatomate 렌더 ID",
         "status": "상태",
         "result_movie_url": "영상 URL",
         "created_at": "생성일시",

docs/analysis/async_architecture_design_report.md

@@ -111,7 +111,6 @@ async def get_item(
 **적용 엔드포인트:**
 - `GET /videos/` - 목록 조회
 - `GET /video/download/{task_id}` - 상태 조회
-- `GET /songs/` - 목록 조회
 
 #### 패턴 2: 명시적 세션 관리 (외부 API 호출 포함)
 

docs/plan/insert_project.md

@@ -0,0 +1,140 @@
+# Database INSERT 코드 위치 정리
+
+이 문서는 O2O Castad Backend 프로젝트에서 실제 동작하는 모든 DB INSERT 코드의 위치를 정리합니다.
+
+---
+
+## 1. User 모듈 (`app/user`)
+
+### 1.1 User 모델 INSERT
+- **파일**: `app/user/services/auth.py`
+- **라인**: 278
+- **메서드**: `_get_or_create_user()`
+- **API 엔드포인트**:
+  - `GET /auth/kakao/callback` - 카카오 로그인 콜백
+  - `POST /auth/kakao/verify` - 카카오 인가 코드 검증
+- **설명**: 카카오 로그인 시 신규 사용자 생성
+- **저장 필드**: `kakao_id`, `email`, `nickname`, `profile_image_url`, `thumbnail_image_url`
+
+### 1.2 RefreshToken 모델 INSERT
+- **파일**: `app/user/services/auth.py`
+- **라인**: 315
+- **메서드**: `_save_refresh_token()`
+- **API 엔드포인트**:
+  - `GET /auth/kakao/callback` - 카카오 로그인 콜백
+  - `POST /auth/kakao/verify` - 카카오 인가 코드 검증
+- **설명**: 로그인 시 리프레시 토큰 저장
+- **저장 필드**: `user_id`, `token_hash`, `expires_at`, `user_agent`, `ip_address`
+
+---
+
+## 2. Lyric 모듈 (`app/lyric`)
+
+### 2.1 Project 모델 INSERT
+- **파일**: `app/lyric/api/routers/v1/lyric.py`
+- **라인**: 297
+- **API 엔드포인트**: `POST /lyric/generate` - 가사 생성
+- **설명**: 가사 생성 요청 시 프로젝트 레코드 생성
+- **저장 필드**: `store_name`, `region`, `task_id`, `detail_region_info`, `language`
+
+### 2.2 Lyric 모델 INSERT
+- **파일**: `app/lyric/api/routers/v1/lyric.py`
+- **라인**: 317
+- **API 엔드포인트**: `POST /lyric/generate` - 가사 생성
+- **설명**: 가사 생성 요청 시 가사 레코드 생성 (초기 status: `processing`)
+- **저장 필드**: `project_id`, `task_id`, `status`, `lyric_prompt`, `lyric_result`, `language`
+
+---
+
+## 3. Song 모듈 (`app/song`)
+
+### 3.1 Song 모델 INSERT
+- **파일**: `app/song/api/routers/v1/song.py`
+- **라인**: 178
+- **API 엔드포인트**: `POST /song/generate/{task_id}` - 노래 생성
+- **설명**: 노래 생성 요청 시 노래 레코드 생성 (초기 status: `processing`)
+- **저장 필드**: `project_id`, `lyric_id`, `task_id`, `suno_task_id`, `status`, `song_prompt`, `language`
+
+### 3.2 SongTimestamp 모델 INSERT
+- **파일**: `app/song/api/routers/v1/song.py`
+- **라인**: 459
+- **API 엔드포인트**: `GET /song/status/{song_id}` - 노래 생성 상태 조회
+- **설명**: Suno API에서 노래 생성 완료(SUCCESS) 시 가사 타임스탬프 저장 (반복문으로 다건 INSERT)
+- **저장 필드**: `suno_audio_id`, `order_idx`, `lyric_line`, `start_time`, `end_time`
+
+---
+
+## 4. Video 모듈 (`app/video`)
+
+### 4.1 Video 모델 INSERT
+- **파일**: `app/video/api/routers/v1/video.py`
+- **라인**: 247
+- **API 엔드포인트**: `GET /video/generate/{task_id}` - 영상 생성
+- **설명**: 영상 생성 요청 시 영상 레코드 생성 (초기 status: `processing`)
+- **저장 필드**: `project_id`, `lyric_id`, `song_id`, `task_id`, `creatomate_render_id`, `status`
+
+---
+
+## 5. Home 모듈 (`app/home`) - 이미지 업로드
+
+### 5.1 Image 모델 INSERT (URL 이미지 - 서버 저장)
+- **파일**: `app/home/api/routers/v1/home.py`
+- **라인**: 486
+- **API 엔드포인트**: `POST /image/upload` (tags: Image-Server)
+- **설명**: 외부 URL 이미지를 Image 테이블에 저장
+- **저장 필드**: `task_id`, `img_name`, `img_url`, `img_order`
+
+### 5.2 Image 모델 INSERT (바이너리 파일 - 서버 저장)
+- **파일**: `app/home/api/routers/v1/home.py`
+- **라인**: 535
+- **API 엔드포인트**: `POST /image/upload` (tags: Image-Server)
+- **설명**: 업로드된 바이너리 파일을 media 폴더에 저장 후 Image 테이블에 저장
+- **저장 필드**: `task_id`, `img_name`, `img_url`, `img_order`
+
+### 5.3 Image 모델 INSERT (URL 이미지 - Blob)
+- **파일**: `app/home/api/routers/v1/home.py`
+- **라인**: 782
+- **API 엔드포인트**: `POST /image/upload/blob` (tags: Image-Blob)
+- **설명**: 외부 URL 이미지를 Image 테이블에 저장 (Azure Blob 엔드포인트)
+- **저장 필드**: `task_id`, `img_name`, `img_url`, `img_order`
+
+### 5.4 Image 모델 INSERT (Blob 업로드 결과)
+- **파일**: `app/home/api/routers/v1/home.py`
+- **라인**: 804
+- **API 엔드포인트**: `POST /image/upload/blob` (tags: Image-Blob)
+- **설명**: 바이너리 파일을 Azure Blob Storage에 업로드 후 Image 테이블에 저장
+- **저장 필드**: `task_id`, `img_name`, `img_url`, `img_order`
+
+---
+
+## 6. Base Services (미사용)
+
+아래 파일들은 공통 `_add()` 메서드를 정의하고 있으나, 현재 실제 API에서 직접 호출되지 않습니다.
+
+| 파일 | 라인 | 비고 |
+|------|------|------|
+| `app/lyric/services/base.py` | 15 | `_update()`에서만 내부 호출 |
+| `app/home/services/base.py` | 15 | `_update()`에서만 내부 호출 |
+| `app/song/services/base.py` | 15 | `_update()`에서만 내부 호출 |
+
+---
+
+## 요약 테이블
+
+| 모듈 | 모델 | 파일:라인 | API 엔드포인트 |
+|------|------|-----------|----------------|
+| User | User | `auth.py:278` | `GET /auth/kakao/callback`, `POST /auth/kakao/verify` |
+| User | RefreshToken | `auth.py:315` | `GET /auth/kakao/callback`, `POST /auth/kakao/verify` |
+| Lyric | Project | `lyric.py:297` | `POST /lyric/generate` |
+| Lyric | Lyric | `lyric.py:317` | `POST /lyric/generate` |
+| Song | Song | `song.py:178` | `POST /song/generate/{task_id}` |
+| Song | SongTimestamp | `song.py:459` | `GET /song/status/{song_id}` |
+| Video | Video | `video.py:247` | `GET /video/generate/{task_id}` |
+| Home | Image | `home.py:486` | `POST /image/upload` |
+| Home | Image | `home.py:535` | `POST /image/upload` |
+| Home | Image | `home.py:782` | `POST /image/upload/blob` |
+| Home | Image | `home.py:804` | `POST /image/upload/blob` |
+
+---
+
+*생성일: 2026-01-23*

main.py

@@ -69,7 +69,6 @@ tags_metadata = [
 
 1. `POST /api/v1/song/generate/{task_id}` - 노래 생성 요청
 2. `GET /api/v1/song/status/{song_id}` - Suno API 상태 확인
-3. `GET /api/v1/song/download/{task_id}` - 노래 다운로드 URL 조회
 """,
     },
     {
@@ -124,10 +123,7 @@ def custom_openapi():
         for method, operation in path_item.items():
             if method in ["get", "post", "put", "patch", "delete"]:
                 # /auth/me, /auth/logout 등 인증이 필요한 엔드포인트
-                if any(
-                    auth_path in path
-                    for auth_path in ["/auth/me", "/auth/logout"]
-                ):
+                if any(auth_path in path for auth_path in ["/auth/me", "/auth/logout"]):
                     operation["security"] = [{"BearerAuth": []}]
 
     app.openapi_schema = openapi_schema

main_tester.ipynb

@@ -1,723 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "e7af5103-62db-4a32-b431-6395c85d7ac9",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from app.home.api.routers.v1.home import crawling\n",
-    "from app.utils.prompts import prompts"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "6cf7ae9b-3ffe-4046-9cab-f33bc071b288",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from config import crawler_settings"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "4c4ec4c5-9efb-470f-99cf-a18a5b80352f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from app.home.schemas.home_schema import (\n",
-    "    CrawlingRequest,\n",
-    "    CrawlingResponse,\n",
-    "    ErrorResponse,\n",
-    "    ImageUploadResponse,\n",
-    "    ImageUploadResultItem,\n",
-    "    ImageUrlItem,\n",
-    "    MarketingAnalysis,\n",
-    "    ProcessedInfo,\n",
-    ")\n",
-    "import json"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "be5d0e16-8cc6-44d4-ae93-8252caa09940",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "val1 = CrawlingRequest(**{\"url\" : 'https://map.naver.com/p/entry/place/1903455560?placePath=/home?from=map&fromPanelNum=1&additionalHeight=76&timestamp=202601131552&locale=ko&svcName=map_pcv5&businessCategory=pension&c=15.00,0,0,0,dh'})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "c13742d7-70f4-4a6d-90c2-8b84f245a08c",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from app.utils.prompts.prompts import reload_all_prompt\n",
-    "reload_all_prompt()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "d4db2ec1-b2af-4993-8832-47f380c17015",
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[crawling] ========== START ==========\n",
-      "[crawling] URL: https://map.naver.com/p/entry/place/1903455560?placePath=/home?from=map&fromPane...\n",
-      "[crawling] Step 1: 네이버 지도 크롤링 시작...\n",
-      "[NvMapScraper] Requesting place_id: 1903455560\n",
-      "[NvMapScraper] SUCCESS - place_id: 1903455560\n",
-      "[crawling] Step 1 완료 - 이미지 44개 (659.9ms)\n",
-      "[crawling] Step 2: 정보 가공 시작...\n",
-      "[crawling] Step 2 완료 - 오블로모프, 군산시 (0.7ms)\n",
-      "[crawling] Step 3: ChatGPT 마케팅 분석 시작...\n",
-      "[crawling]   Step 3-1: 서비스 초기화 완료 (59.1ms)\n",
-      "build_template \n",
-      "[Role & Objective]\n",
-      "Act as a content marketing expert with strong domain knowledge in the Korean pension / stay-accommodation industry.\n",
-      "Your goal is to produce a Marketing Intelligence Report that will be shown to accommodation owners BEFORE any content is generated.\n",
-      "The report must clearly explain what makes the property sellable, marketable, and scalable through content.\n",
-      "\n",
-      "[INPUT]\n",
-      "- Business Name: {customer_name}\n",
-      "- Region: {region}\n",
-      "- Region Details: {detail_region_info}\n",
-      "\n",
-      "[Core Analysis Requirements]\n",
-      "Analyze the property based on:\n",
-      "Location, concept, photos, online presence, and nearby environment\n",
-      "Target customer behavior and reservation decision factors\n",
-      "Include:\n",
-      "- Target customer segments & personas\n",
-      "- Unique Selling Propositions (USPs)\n",
-      "- Competitive landscape (direct & indirect competitors)\n",
-      "- Market positioning\n",
-      "\n",
-      "[Key Selling Point Structuring – UI Optimized]\n",
-      "From the analysis above, extract the main Key Selling Points using the structure below.\n",
-      "Rules:\n",
-      "Focus only on factors that directly influence booking decisions\n",
-      "Each selling point must be concise and visually scannable\n",
-      "Language must be reusable for ads, short-form videos, and listing headlines\n",
-      "Avoid full sentences in descriptions; use short selling phrases\n",
-      "\n",
-      "Output format:\n",
-      "[Category]\n",
-      "(Tag keyword – 5~8 words, noun-based, UI oval-style)\n",
-      "One-line selling phrase (not a full sentence)\n",
-      "Limit:\n",
-      "5 to 8 Key Selling Points only\n",
-      "\n",
-      "[Content & Automation Readiness Check]\n",
-      "Ensure that:\n",
-      "Each tag keyword can directly map to a content theme\n",
-      "Each selling phrase can be used as:\n",
-      "- Video hook\n",
-      "- Image headline\n",
-      "- Ad copy snippet\n",
-      "\n",
-      "\n",
-      "[Tag Generation Rules]\n",
-      "- Tags must include **only core keywords that can be directly used for viral video song lyrics**\n",
-      "- Each tag should be selected with **search discovery + emotional resonance + reservation conversion** in mind\n",
-      "- The number of tags must be **exactly 5**\n",
-      "- Tags must be **nouns or short keyword phrases**; full sentences are strictly prohibited\n",
-      "- The following categories must be **balanced and all represented**:\n",
-      "  1) **Location / Local context** (region name, neighborhood, travel context)\n",
-      "  2) **Accommodation positioning** (emotional stay, private stay, boutique stay, etc.)\n",
-      "  3) **Emotion / Experience** (healing, rest, one-day escape, memory, etc.)\n",
-      "  4) **SNS / Viral signals** (Instagram vibes, picture-perfect day, aesthetic travel, etc.)\n",
-      "  5) **Travel & booking intent** (travel, getaway, stay, relaxation, etc.)\n",
-      "\n",
-      "- If a brand name exists, **at least one tag must include the brand name or a brand-specific expression**\n",
-      "- Avoid overly generic keywords (e.g., “hotel”, “travel” alone); **prioritize distinctive, differentiating phrases**\n",
-      "- The final output must strictly follow the JSON format below, with no additional text\n",
-      "\n",
-      "  \"tags\": [\"Tag1\", \"Tag2\", \"Tag3\", \"Tag4\", \"Tag5\"]\n",
-      "\n",
-      "input_data {'customer_name': '오블로모프', 'region': '군산시', 'detail_region_info': '전북 군산시 절골길 16'}\n",
-      "[ChatgptService] Generated Prompt (length: 2766)\n",
-      "[crawling]   Step 3-3: GPT API 호출 완료 - (59060.2ms)\n",
-      "[crawling]   Step 3-4: 응답 파싱 시작 - facility_info: 무선 인터넷, 예약, 주차\n",
-      "[crawling]   Step 3-4: 응답 파싱 완료 (0.1ms)\n",
-      "[crawling] Step 3 완료 - 마케팅 분석 성공 (59119.8ms)\n",
-      "[crawling] ========== COMPLETE ==========\n",
-      "[crawling] 총 소요시간: 59782.3ms\n",
-      "[crawling]   - Step 1 (크롤링): 659.9ms\n",
-      "[crawling]   - Step 2 (정보가공): 0.7ms\n",
-      "[crawling]   - Step 3 (GPT 분석): 59119.8ms\n",
-      "[crawling]       - GPT API 호출: 59060.2ms\n"
-     ]
-    }
-   ],
-   "source": [
-    "var2 = await crawling(val1)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "79f093f0-d7d2-4ed1-ba43-da06e4ee2073",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'image_list': ['https://ldb-phinf.pstatic.net/20230515_163/1684090233619kRU3v_JPEG/20230513_154207.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20250811_213/17548982879808X4MH_PNG/1.png',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_34/1712622373542UY8aC_JPEG/20231007_051403.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_37/1684090234513tT89X_JPEG/20230513_152018.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20241231_272/1735620966755B9XgT_PNG/DSC09054.png',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_100/1712622410472zgP15_JPEG/20230523_153219.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_151/1712623034401FzQbd_JPEG/Screenshot_20240409_093158_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_169/1712622316504ReKji_JPEG/20230728_125946.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230521_279/1684648422643NI2oj_JPEG/20230521_144343.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_52/1712622993632WR1sT_JPEG/Screenshot_20240409_093237_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20250811_151/1754898220223TNtvB_PNG/2.png',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_70/1712622381167p9QOI_JPEG/20230608_175722.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_144/1684090233161cR5mr_JPEG/20230513_180151.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_158/1712621983956CCqdo_JPEG/20240407_121826.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20250811_187/1754893113769iGO5X_JPEG/%B0%C5%BD%C7_01.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_31/17126219901822nnR4_JPEG/20240407_121615.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_94/1712621993863AWMKi_JPEG/20240407_121520.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_165/1684090236297fVhJM_JPEG/20230513_165348.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_102/1684090230350e1v0E_JPEG/20230513_162718.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_26/1684090232743arN2y_JPEG/20230513_174246.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20250811_273/1754893072358V3WcL_JPEG/%B5%F0%C5%D7%C0%CF%C4%C6_02.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_160/1712621974438LLNbD_JPEG/20240407_121848.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_218/1712623006036U39zE_JPEG/Screenshot_20240409_093114_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_210/16840902342654EkeL_JPEG/20230513_152107.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_216/1712623058832HBulg_JPEG/Screenshot_20240409_093309_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_184/1684090223226nO2Az_JPEG/20230514_143325.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_209/1684090697642BHNVR_JPEG/20230514_143528.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_16/1712623029052VNeaz_JPEG/Screenshot_20240409_093141_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_141/1684090233092KwtWy_JPEG/20230513_180105.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_177/1712623066424dcwJ2_JPEG/Screenshot_20240409_093511_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_181/16840902259407iA5Q_JPEG/20230514_144814.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_153/1684090224581Ih4ft_JPEG/20230514_143552.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_205/1684090231467WmulO_JPEG/20230513_180254.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20230515_120/1684090231233PkqCf_JPEG/20230513_152550.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_188/1712623039909sflvy_JPEG/Screenshot_20240409_093209_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_165/1712623049073j0TzM_JPEG/Screenshot_20240409_093254_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_3/17126230950579050V_JPEG/Screenshot_20240409_093412_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_270/1712623091524YX4E6_JPEG/Screenshot_20240409_093355_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_22/1712623083348btwTB_JPEG/Screenshot_20240409_093331_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_242/1712623087423Q7tHk_JPEG/Screenshot_20240409_093339_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_173/1712623098958aFhiB_JPEG/Screenshot_20240409_093422_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_113/1712623103270DOGKI_JPEG/Screenshot_20240409_093435_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_295/17126230704056BTRg_JPEG/Screenshot_20240409_093448_Airbnb.jpg',\n",
-       "  'https://ldb-phinf.pstatic.net/20240409_178/1712623075172JEt43_JPEG/Screenshot_20240409_093457_Airbnb.jpg'],\n",
-       " 'image_count': 44,\n",
-       " 'processed_info': ProcessedInfo(customer_name='오블로모프', region='군산시', detail_region_info='전북 군산시 절골길 16'),\n",
-       " 'marketing_analysis': MarketingAnalysis(report='요약\\n오블로모프(군산 절골길)는 ‘느림의 미학’을 콘셉트로 한 소규모 부티크 스테이로 포지셔닝할 때 강점이 큽니다. 군산의 근대문화·항구·로컬 카페·해산물 레퍼런스가 결합되면 ‘주말 힐링 + 인생샷’ 수요를 끌어올 수 있습니다. 사진·영상 중심의 콘텐츠, 지역 연계 체험, 예약 편의성(주차·즉시예약·정책 명확화)을 우선 강화하면 전환율 개선과 확장성(패키지, 시즌 프로모션)이 용이합니다.\\n위치 분석\\n- 주소: 전북 군산시 절골길 16 — 주거 밀집·골목형 동선으로 ‘조용한 휴식’ 기대 요소\\n- 인근: 근대문화·항구권 관광지·로컬 카페·해산물 식당 밀집(도보·단거리 이동권 장점)\\n- 교통: 자차 접근성·주차 여부가 예약 결정 핵심(대중교통 이용객 대비 자가용 고객 타깃화 필요)\\n콘셉트·포토·온라인 대비\\n- 콘셉트 잠재력: ‘오블로모프=느림·휴식’ 내러티브 활용 가능(브랜드 스토리텔링 유리)\\n- 포토 포인트 제안: 테라스 일출·실내 빈티지 소품·침구 근접 샷·로컬 푸드 플래팅\\n- 온라인: 네이버 예약, 인스타그램, 블로그(지역 키워드) 우선 등재 필요. 리뷰·FAQ·즉시예약 정보 노출 필수\\n주변 환경 영향요인\\n- 식음·체험: 해산물 전문점·카페투어·공방/산책 루트 연계로 1박 체류 가치 강화\\n- 시즌성: 주중 장기 체류보다는 주말·연휴 수요 집중, 계절별 촬영 포인트로 프로모션\\n타깃 고객 행동·예약 결정 요인\\n- 시각 요소 우선: 사진 퀄리티가 예약 전환을 좌우\\n- 프라이버시·편리성: 전용 테라스·주차·와이파이·편의시설(개인화된 체크인)이 중요\\n- 정책: 유연한 취소·즉시예약·가격 패키징(주말/주중/연박)로 예약장벽 완화\\n타깃 세그먼트(페르소나)\\n1) SNS 커플(25–35) — 인생샷·감성카페·주말 데이트 용도\\n2) 휴식형 성인(30–50) — ‘힐링’·프라이버시·느긋한 체류 선호\\n3) 콘텐츠 크리에이터·프리랜서(20–40) — 사진·영상 소재·원데이 촬영 스팟 수요\\n4) 가족·소규모 그룹(30–45) — 주차·편의시설·근거리 식사 옵션 필요\\nUSP(핵심 가치 제안)\\n- 절골길의 조용한 골목 위치로 프라이빗한 휴식 보장\\n- ‘오블로모프’ 감성의 느림·회복 스토리로 차별화\\n- 사진·영상 친화적 인테리어와 야외 테라스(콘텐츠 제작 가치 높음)\\n- 지역 미식·카페 루트와 연계한 플레이스 기반 체류 설계 가능\\n경쟁구도\\n- 직접 경쟁: 군산 내 소규모 펜션·게스트하우스·부티크 스테이\\n- 간접 경쟁: 지역 호텔·에어비앤비·당일치기 여행 코스\\n- 차별화 포인트: 브랜드 스토리(느림)·콘텐츠 친화성·로컬 연계 프로그램\\n시장 포지셔닝 제안\\n- 포지셔닝: ‘군산 절골의 느림 감성 부티크 스테이’ — mid-premium 티어\\n- 가격·프로모션: 주말 프리미엄, 주중 패키지·장기 할인 고려\\n콘텐츠·자동화 준비 체크리스트\\n- 필요 자산: ①외관 황금시간(골목샷) ②테라스/일몰 ③침실·욕실 클로즈업 ④로컬 푸드 컷 ⑤리뷰·게스트 스토리\\n- 콘텐츠 기획: 로컬 루트(카페·식당)·‘하루 힐링’ 숏폼(15–30s)·인테리어 B-roll(10s 반복 가능한 클립)\\n- 예약 전환 포인트 템플릿: 사진 헤로·편의 아이콘(주차·와이파이)·간단 정책·CTA\\n- 태그 매핑: 지역·브랜드·힐링·SNS·여행 의도(ads/shorts/리스트 헤드라인 직접 활용)\\n권장 다음 단계\\n1) 사진 촬영 10컷(상기 항목) 2) 인스타 12포스트 + 숏폼 6개 제작 3) 예약 페이지(네이버·에어비앤비) 표준화 및 FAQ 업데이트\\n', tags=['군산절골', '오블로모프스테이', '힐링스테이', '인생샷스폿', '주말여행'], facilities=['군산 절골길 근대문화 항구 카페거리 해산물', '오블로모프 느림의미학 프라이빗 부티크 스테이', '힐링 휴식 일상탈출 온전한쉼 감성여행', '감성포토 인생샷 테라스 일몰 빈티지인테리어', '주차편의 빠른예약 유연취소 와이파이 원데이스테이', '로컬식당 해산물 카페투어 산책코스 공방체험'])}"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "var2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "f3bf1d76-bd2a-43d5-8d39-f0ab2459701a",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Location\n",
-      "군산 절골 골목 스팟\n",
-      "골목 깊숙한 전원 감성, 조용한 휴식\n",
-      "Concept\n",
-      "프라이빗 전원스테이\n",
-      "소규모 전용 공간, 맞춤형 프라이버시\n",
-      "Visuals\n",
-      "인생샷 포토존\n",
-      "포토제닉 실내·외 컷, 밤 조명 무드\n",
-      "Experience\n",
-      "힐링 리셋 스테이\n",
-      "일상 탈출·짧은 리셋, 주말 최적\n",
-      "Digital\n",
-      "SNS 바이럴 감성\n",
-      "쇼트폼 영상·릴스용 비주얼 중심\n",
-      "Booking\n",
-      "주말 스테이케이션 패키지\n",
-      "주말 1박 패키지, 조식·체험 옵션\n"
-     ]
-    }
-   ],
-   "source": [
-    "for i in var2[\"selling_points\"]:\n",
-    "    print(i['category'])\n",
-    "    print(i['keywords'])\n",
-    "    print(i['description'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "c89cf2eb-4f16-4dc5-90c6-df89191b4e39",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[{'category': 'Location',\n",
-       "  'keywords': '군산 절골 골목 스팟',\n",
-       "  'description': '골목 깊숙한 전원 감성, 조용한 휴식'},\n",
-       " {'category': 'Concept',\n",
-       "  'keywords': '프라이빗 전원스테이',\n",
-       "  'description': '소규모 전용 공간, 맞춤형 프라이버시'},\n",
-       " {'category': 'Visuals',\n",
-       "  'keywords': '인생샷 포토존',\n",
-       "  'description': '포토제닉 실내·외 컷, 밤 조명 무드'},\n",
-       " {'category': 'Experience',\n",
-       "  'keywords': '힐링 리셋 스테이',\n",
-       "  'description': '일상 탈출·짧은 리셋, 주말 최적'},\n",
-       " {'category': 'Digital',\n",
-       "  'keywords': 'SNS 바이럴 감성',\n",
-       "  'description': '쇼트폼 영상·릴스용 비주얼 중심'},\n",
-       " {'category': 'Booking',\n",
-       "  'keywords': '주말 스테이케이션 패키지',\n",
-       "  'description': '주말 1박 패키지, 조식·체험 옵션'}]"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "var2[\"selling_points\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "231963d6-e209-41b3-8e78-2ad5d06943fe",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['오블로모프 군산 절골', '전원감성스테이', '힐링리셋', '인생샷 명소', '주말스테이케이션']"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "var2[\"tags\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "f8260222-d5a2-4018-b465-a4943c82bd3f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "lyric_prompt = \"\"\"\n",
-    "[ROLE]\n",
-    "You are a content marketing expert, brand strategist, and creative songwriter\n",
-    "specializing in Korean pension / accommodation businesses.\n",
-    "You create lyrics strictly based on Brand & Marketing Intelligence analysis\n",
-    "and optimized for viral short-form video content.\n",
-    "\n",
-    "[INPUT]\n",
-    "Business Name: {customer_name}\n",
-    "Region: {region}\n",
-    "Region Details: {detail_region_info}\n",
-    "Brand & Marketing Intelligence Report: {marketing_intelligence_summary}\n",
-    "Output Language: {language}\n",
-    "\n",
-    "[INTERNAL ANALYSIS – DO NOT OUTPUT]\n",
-    "Internally analyze the following to guide all creative decisions:\n",
-    "- Core brand identity and positioning\n",
-    "- Emotional hooks derived from selling points\n",
-    "- Target audience lifestyle, desires, and travel motivation\n",
-    "- Regional atmosphere and symbolic imagery\n",
-    "- How the stay converts into “shareable moments”\n",
-    "- Which selling points must surface implicitly in lyrics\n",
-    "\n",
-    "[LYRICS & MUSIC CREATION TASK]\n",
-    "Based on the Brand & Marketing Intelligence Report for [{customer_name} ({region})], generate:\n",
-    "- Original promotional lyrics\n",
-    "- Music attributes for AI music generation (Suno-compatible prompt)\n",
-    "The output must be designed for VIRAL DIGITAL CONTENT\n",
-    "(short-form video, reels, ads).\n",
-    "\n",
-    "[LYRICS REQUIREMENTS]\n",
-    "Mandatory Inclusions:\n",
-    "- Business name\n",
-    "- Region name\n",
-    "- Promotion subject\n",
-    "- Promotional expressions including:\n",
-    "{promotional_expressions[language]}\n",
-    "\n",
-    "Content Rules:\n",
-    "- Lyrics must be emotionally driven, not descriptive listings\n",
-    "- Selling points must be IMPLIED, not explained\n",
-    "- Must sound natural when sung\n",
-    "- Must feel like a lifestyle moment, not an advertisement\n",
-    "\n",
-    "Tone & Style:\n",
-    "- Warm, emotional, and aspirational\n",
-    "- Trendy, viral-friendly phrasing\n",
-    "- Calm but memorable hooks\n",
-    "- Suitable for travel / stay-related content\n",
-    "\n",
-    "[SONG & MUSIC ATTRIBUTES – FOR SUNO PROMPT]\n",
-    "After the lyrics, generate a concise music prompt including:\n",
-    "Song mood (emotional keywords)\n",
-    "BPM range\n",
-    "Recommended genres (max 2)\n",
-    "Key musical motifs or instruments\n",
-    "Overall vibe (1 short sentence)\n",
-    "\n",
-    "[CRITICAL LANGUAGE REQUIREMENT – ABSOLUTE RULE]\n",
-    "ALL OUTPUT MUST BE 100% WRITTEN IN {language}.\n",
-    "no mixed languages\n",
-    "All names, places, and expressions must be in {language} \n",
-    "Any violation invalidates the entire output\n",
-    "\n",
-    "[OUTPUT RULES – STRICT]\n",
-    "{timing_rules}\n",
-    "8–12 lines\n",
-    "Full verse flow, immersive mood\n",
-    "\n",
-    "No explanations\n",
-    "No headings\n",
-    "No bullet points\n",
-    "No analysis\n",
-    "No extra text\n",
-    "\n",
-    "[FAILURE FORMAT]\n",
-    "If generation is impossible:\n",
-    "ERROR: Brief reason in English\n",
-    "\"\"\"\n",
-    "lyric_prompt_dict = {\n",
-    "    \"prompt_variables\" :\n",
-    "    [\n",
-    "        \"customer_name\",\n",
-    "        \"region\",\n",
-    "        \"detail_region_info\",\n",
-    "        \"marketing_intelligence_summary\",\n",
-    "        \"language\",\n",
-    "        \"promotional_expression_example\",\n",
-    "        \"timing_rules\",\n",
-    "        \n",
-    "    ],\n",
-    "    \"output_format\" : {\n",
-    "        \"format\": {\n",
-    "            \"type\": \"json_schema\",\n",
-    "            \"name\": \"lyric\",\n",
-    "            \"schema\": {\n",
-    "                \"type\":\"object\",\n",
-    "                \"properties\" : {\n",
-    "                    \"lyric\" : { \n",
-    "                        \"type\" : \"string\"\n",
-    "                    }\n",
-    "                },\n",
-    "                \"required\": [\"lyric\"],\n",
-    "                \"additionalProperties\": False,\n",
-    "            },\n",
-    "            \"strict\": True\n",
-    "        }\n",
-    "    }\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "79edd82b-6f4c-43c7-9205-0b970afe06d7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "with open(\"./app/utils/prompts/marketing_prompt.txt\", \"w\") as fp:\n",
-    "    fp.write(marketing_prompt)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "id": "65a5a2a6-06a5-4ee1-a796-406c86aefc20",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "with open(\"prompts/summarize_prompt.json\", \"r\") as fp:\n",
-    "    p = json.load(fp)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "454d920f-e9ed-4fb2-806c-75b8f7033db9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'prompt_variables': ['report', 'selling_points'],\n",
-       " 'prompt': '\\n입력 : \\n분석 보고서\\n{report}\\n\\n셀링 포인트\\n{selling_points}\\n\\n위 분석 결과를 바탕으로, 주요 셀링 포인트를 다음 구조로 재정리하라.\\n\\n조건:\\n각 셀링 포인트는 반드시 ‘카테고리 → 태그 키워드 → 한 줄 설명’ 구조를 가질 것\\n태그 키워드는 UI 상에서 타원(oval) 형태의 시각적 태그로 사용될 것을 가정하여\\n- 3 ~ 6단어 이내\\n- 명사 또는 명사형 키워드로 작성\\n- 설명은 문장이 아닌, 짧은 ‘셀링 문구’ 형태로 작성할 것\\n- 광고·숏폼·상세페이지 어디에도 바로 재사용 가능해야 함\\n- 전체 셀링 포인트 개수는 5~7개로 제한\\n\\n출력 형식:\\n[카테고리명]\\n(태그 키워드)\\n- 한 줄 설명 문구\\n\\n예시: \\n[공간 정체성]\\n(100년 적산가옥 · 시간의 결)\\n- 하루를 ‘숙박’이 아닌 ‘체류’로 바꾸는 공간\\n\\n[입지 & 희소성]\\n(말랭이마을 · 로컬 히든플레이스)\\n- 관광지가 아닌, 군산을 아는 사람의 선택\\n\\n[프라이버시]\\n(독채 숙소 · 프라이빗 스테이)\\n- 누구의 방해도 없는 완전한 휴식 구조\\n\\n[비주얼 경쟁력]\\n(감성 인테리어 · 자연광 스폿)\\n- 찍는 순간 콘텐츠가 되는 공간 설계\\n\\n[타깃 최적화]\\n(커플 · 소규모 여행)\\n- 둘에게 가장 이상적인 공간 밀도\\n\\n[체류 경험]\\n(아무것도 안 해도 되는 하루)\\n- 일정 없이도 만족되는 하루 루틴\\n\\n[브랜드 포지션]\\n(호텔도 펜션도 아닌 아지트)\\n- 다시 돌아오고 싶은 개인적 장소\\n    ',\n",
-       " 'output_format': {'format': {'type': 'json_schema',\n",
-       "   'name': 'tags',\n",
-       "   'schema': {'type': 'object',\n",
-       "    'properties': {'category': {'type': 'string'},\n",
-       "     'tag_keywords': {'type': 'string'},\n",
-       "     'description': {'type': 'string'}},\n",
-       "    'required': ['category', 'tag_keywords', 'description'],\n",
-       "    'additionalProperties': False},\n",
-       "   'strict': True}}}"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "p"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "c46abcda-d6a8-485e-92f1-526fb28c6b53",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "marketing_prompt_dict = {\n",
-    "    \"model\" : \"gpt-5-mini\",\n",
-    "    \"prompt_variables\" :\n",
-    "    [\n",
-    "        \"customer_name\",\n",
-    "        \"region\",\n",
-    "        \"detail_region_info\"\n",
-    "    ],\n",
-    "    \"output_format\" : {\n",
-    "        \"format\": {\n",
-    "            \"type\": \"json_schema\",\n",
-    "            \"name\": \"report\",\n",
-    "            \"schema\": {\n",
-    "                \"type\" : \"object\",\n",
-    "                \"properties\" : {\n",
-    "                    \"report\" : {\n",
-    "                        \"type\": \"string\"\n",
-    "                    },\n",
-    "                    \"selling_points\" : {\n",
-    "                        \"type\": \"array\",\n",
-    "                        \"items\": {\n",
-    "                            \"type\": \"object\",\n",
-    "                            \"properties\" : {\n",
-    "                                \"category\" : {\"type\" : \"string\"},\n",
-    "                                \"keywords\" : {\"type\" : \"string\"},\n",
-    "                                \"description\" : {\"type\" : \"string\"}\n",
-    "                            },\n",
-    "                            \"required\": [\"category\", \"keywords\", \"description\"],\n",
-    "                            \"additionalProperties\": False,\n",
-    "                        },\n",
-    "                    },\n",
-    "                    \"tags\" : {\n",
-    "                        \"type\": \"array\",\n",
-    "                        \"items\": {\n",
-    "                            \"type\": \"string\"\n",
-    "                        },\n",
-    "                    },\n",
-    "                },\n",
-    "                \"required\": [\"report\", \"selling_points\", \"tags\"],\n",
-    "                \"additionalProperties\": False,\n",
-    "            },\n",
-    "            \"strict\": True\n",
-    "        }\n",
-    "    }\n",
-    "}\n",
-    "with open(\"./app/utils/prompts/marketing_prompt.json\", \"w\") as fp:\n",
-    "    json.dump(marketing_prompt_dict, fp, ensure_ascii=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "c3867dab-0c4e-46be-ad12-a9c02b5edb68",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "lyric_prompt = \"\"\"\n",
-    "[ROLE]\n",
-    "You are a content marketing expert, brand strategist, and creative songwriter\n",
-    "specializing in Korean pension / accommodation businesses.\n",
-    "You create lyrics strictly based on Brand & Marketing Intelligence analysis\n",
-    "and optimized for viral short-form video content.\n",
-    "\n",
-    "[INPUT]\n",
-    "Business Name: {customer_name}\n",
-    "Region: {region}\n",
-    "Region Details: {detail_region_info}\n",
-    "Brand & Marketing Intelligence Report: {marketing_intelligence_summary}\n",
-    "Output Language: {language}\n",
-    "\n",
-    "[INTERNAL ANALYSIS – DO NOT OUTPUT]\n",
-    "Internally analyze the following to guide all creative decisions:\n",
-    "- Core brand identity and positioning\n",
-    "- Emotional hooks derived from selling points\n",
-    "- Target audience lifestyle, desires, and travel motivation\n",
-    "- Regional atmosphere and symbolic imagery\n",
-    "- How the stay converts into “shareable moments”\n",
-    "- Which selling points must surface implicitly in lyrics\n",
-    "\n",
-    "[LYRICS & MUSIC CREATION TASK]\n",
-    "Based on the Brand & Marketing Intelligence Report for [{customer_name} ({region})], generate:\n",
-    "- Original promotional lyrics\n",
-    "- Music attributes for AI music generation (Suno-compatible prompt)\n",
-    "The output must be designed for VIRAL DIGITAL CONTENT\n",
-    "(short-form video, reels, ads).\n",
-    "\n",
-    "[LYRICS REQUIREMENTS]\n",
-    "Mandatory Inclusions:\n",
-    "- Business name\n",
-    "- Region name\n",
-    "- Promotion subject\n",
-    "- Promotional expressions including:\n",
-    "{promotional_expressions[language]}\n",
-    "\n",
-    "Content Rules:\n",
-    "- Lyrics must be emotionally driven, not descriptive listings\n",
-    "- Selling points must be IMPLIED, not explained\n",
-    "- Must sound natural when sung\n",
-    "- Must feel like a lifestyle moment, not an advertisement\n",
-    "\n",
-    "Tone & Style:\n",
-    "- Warm, emotional, and aspirational\n",
-    "- Trendy, viral-friendly phrasing\n",
-    "- Calm but memorable hooks\n",
-    "- Suitable for travel / stay-related content\n",
-    "\n",
-    "[SONG & MUSIC ATTRIBUTES – FOR SUNO PROMPT]\n",
-    "After the lyrics, generate a concise music prompt including:\n",
-    "Song mood (emotional keywords)\n",
-    "BPM range\n",
-    "Recommended genres (max 2)\n",
-    "Key musical motifs or instruments\n",
-    "Overall vibe (1 short sentence)\n",
-    "\n",
-    "[CRITICAL LANGUAGE REQUIREMENT – ABSOLUTE RULE]\n",
-    "ALL OUTPUT MUST BE 100% WRITTEN IN {language}.\n",
-    "no mixed languages\n",
-    "All names, places, and expressions must be in {language} \n",
-    "Any violation invalidates the entire output\n",
-    "\n",
-    "[OUTPUT RULES – STRICT]\n",
-    "{timing_rules}\n",
-    "8–12 lines\n",
-    "Full verse flow, immersive mood\n",
-    "\n",
-    "No explanations\n",
-    "No headings\n",
-    "No bullet points\n",
-    "No analysis\n",
-    "No extra text\n",
-    "\n",
-    "[FAILURE FORMAT]\n",
-    "If generation is impossible:\n",
-    "ERROR: Brief reason in English\n",
-    "\"\"\"\n",
-    "with open(\"./app/utils/prompts/lyric_prompt.txt\", \"w\") as fp:\n",
-    "    fp.write(lyric_prompt)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "5736ca4b-c379-4cae-84a9-534cad9576c7",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "lyric_prompt_dict = {\n",
-    "    \"model\" : \"gpt-5-mini\",\n",
-    "    \"prompt_variables\" :\n",
-    "    [\n",
-    "        \"customer_name\",\n",
-    "        \"region\",\n",
-    "        \"detail_region_info\",\n",
-    "        \"marketing_intelligence_summary\",\n",
-    "        \"language\",\n",
-    "        \"promotional_expression_example\",\n",
-    "        \"timing_rules\",\n",
-    "        \n",
-    "    ],\n",
-    "    \"output_format\" : {\n",
-    "        \"format\": {\n",
-    "            \"type\": \"json_schema\",\n",
-    "            \"name\": \"lyric\",\n",
-    "            \"schema\": {\n",
-    "                \"type\":\"object\",\n",
-    "                \"properties\" : {\n",
-    "                    \"lyric\" : { \n",
-    "                        \"type\" : \"string\"\n",
-    "                    }\n",
-    "                },\n",
-    "                \"required\": [\"lyric\"],\n",
-    "                \"additionalProperties\": False,\n",
-    "            },\n",
-    "            \"strict\": True\n",
-    "        }\n",
-    "    }\n",
-    "}\n",
-    "with open(\"./app/utils/prompts/lyric_prompt.json\", \"w\") as fp:\n",
-    "    json.dump(lyric_prompt_dict, fp, ensure_ascii=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "430c8914-4e6a-4b53-8903-f454e7ccb8e2",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.13.8"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

pyproject.toml

@@ -3,7 +3,7 @@ name = "o2o-castad-backend"
 version = "0.1.0"
 description = "Add your description here"
 readme = "README.md"
-requires-python = ">=3.13"
+requires-python = ">=3.14"
 dependencies = [
     "aiofiles>=25.1.0",
     "aiohttp>=3.13.2",
@@ -15,9 +15,10 @@ dependencies = [
     "openai>=2.13.0",
     "pydantic-settings>=2.12.0",
     "python-jose[cryptography]>=3.5.0",
+    "python-multipart>=0.0.21",
     "redis>=7.1.0",
     "ruff>=0.14.9",
-    "scalar-fastapi>=1.5.0",
+    "scalar-fastapi>=1.6.1",
     "sqladmin[full]>=0.22.0",
     "sqlalchemy[asyncio]>=2.0.45",
     "uuid7>=0.1.0",

uv.lock

@@ -1,6 +1,6 @@
 version = 1
 revision = 3
-requires-python = ">=3.13"
+requires-python = ">=3.14"
 
 [[package]]
 name = "aiofiles"
@@ -22,7 +22,7 @@ wheels = [
 
 [[package]]
 name = "aiohttp"
-version = "3.13.2"
+version = "3.13.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
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     { name = "propcache" },
     { name = "yarl" },
 ]
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