.gitignore

@@ -28,8 +28,6 @@ build/
 *.mp4
 media/
 
-
-*.ipynb_checkpoint*
 # Static files
 static/
 

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

@@ -27,7 +27,6 @@ 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 config import MEDIA_ROOT
 
 # 로거 설정
@@ -165,49 +164,33 @@ async def crawling(request_body: CrawlingRequest):
         try:
             # Step 3-1: ChatGPT 서비스 초기화
             step3_1_start = time.perf_counter()
-            chatgpt_service = ChatgptService()
+            chatgpt_service = ChatgptService(
+                customer_name=customer_name,
+                region=region,
+                detail_region_info=road_address or "",
+            )
             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)")
 
             # Step 3-2: 프롬프트 생성
-            # step3_2_start = time.perf_counter()
+            step3_2_start = time.perf_counter()
-            input_marketing_data = {
+            prompt = chatgpt_service.build_market_analysis_prompt()
-                "customer_name" : customer_name,
+            step3_2_elapsed = (time.perf_counter() - step3_2_start) * 1000
-                "region" : region,
+            logger.debug(f"[crawling]   Step 3-2: 프롬프트 생성 완료 - {len(prompt)}자 ({step3_2_elapsed:.1f}ms)")
-                "detail_region_info" : road_address or ""
-            }
-            # prompt = chatgpt_service.build_market_analysis_prompt()
-            # prompt1 = marketing_prompt.build_prompt(input_marketing_data)
-            # step3_2_elapsed = (time.perf_counter() - step3_2_start) * 1000
 
             # 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)
+            raw_response = await chatgpt_service.generate(prompt)
             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.info(f"[crawling]   Step 3-3: GPT API 호출 완료 - 응답 {len(raw_response)}자 ({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}")
-
+            parsed = await chatgpt_service.parse_marketing_analysis(
-            # 요약 Deprecated / 20250115 / Selling points를 첫 prompt에서 추출 중
+                raw_response
-            # parsed = await chatgpt_service.parse_marketing_analysis(
-            #     structured_report, facility_info=scraper.facility_info
-            # )
-            
-            # marketing_analysis = MarketingAnalysis(**parsed)
-
-            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
             )
-                # Selling Points 구조
+            marketing_analysis = MarketingAnalysis(**parsed)
-                    # 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)")
 
@@ -240,7 +223,7 @@ async def crawling(request_body: CrawlingRequest):
         "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,
     }
 
 

app/lyric/api/routers/v1/lyric.py

@@ -44,12 +44,10 @@ from app.utils.chatgpt_prompt import ChatgptService
 from app.utils.logger import get_logger
 from app.utils.pagination import PaginatedResponse, get_paginated
 
-from app.utils.prompts.prompts import lyric_prompt
-import traceback as tb
 # 로거 설정
 logger = get_logger("lyric")
 
-router = APIRouter(prefix="/lyric", tags=["lyric"])
+router = APIRouter(prefix="/lyric", tags=["Lyric"])
 
 
 # =============================================================================
@@ -230,7 +228,6 @@ async def generate_lyric(
     request_start = time.perf_counter()
     task_id = request_body.task_id
 
-
     logger.info(f"[generate_lyric] ========== START ==========")
     logger.info(
         f"[generate_lyric] task_id: {task_id}, "
@@ -243,45 +240,16 @@ async def generate_lyric(
         step1_start = time.perf_counter()
         logger.debug(f"[generate_lyric] Step 1: 서비스 초기화 및 프롬프트 생성...")
 
-        # service = ChatgptService(
+        service = ChatgptService(
-        #     customer_name=request_body.customer_name,
+            customer_name=request_body.customer_name,
-        #     region=request_body.region,
+            region=request_body.region,
-        #     detail_region_info=request_body.detail_region_info or "",
+            detail_region_info=request_body.detail_region_info or "",
-        #     language=request_body.language,
+            language=request_body.language,
-        # )
+        )
-
+        prompt = service.build_lyrics_prompt()
-        # prompt = service.build_lyrics_prompt()
-        # 원래는 실제 사용할 프롬프트가 들어가야 하나, 로직이 변경되어 이 시점에서 이곳에서 프롬프트를 생성할 이유가 없어서 삭제됨. 
-        # 기존 코드와의 호환을 위해 동일한 로직으로 프롬프트 생성
-
-        promotional_expressions = {
-            "Korean" : "인스타 감성, 사진같은 하루, 힐링, 여행, 감성 숙소",
-            "English" : "Instagram vibes, picture-perfect day, healing, travel, getaway",
-            "Chinese" : "网红打卡, 治愈系, 旅行, 度假, 拍照圣地",
-            "Japanese" : "インスタ映え, 写真のような一日, 癒し, 旅行, 絶景",
-            "Thai" : "ที่พักสวย, ฮีลใจ, เที่ยว, ถ่ายรูป, วิวสวย",
-            "Vietnamese" : "check-in đẹp, healing, du lịch, nghỉ dưỡng, view đẹp"
-            }# HARD CODED, 어디에 정리하지? 아직 정리되지 않음
-        
-        timing_rules = {
-            "60s" : """
-                8–12 lines
-                Full verse flow, immersive mood
-                """
-        }
-        lyric_input_data = {
-            "customer_name" : request_body.customer_name,
-            "region" : request_body.region,
-            "detail_region_info" : request_body.detail_region_info or "",
-            "marketing_intelligence_summary" : None, # task_idx 변경 후 marketing intelligence summary DB에 저장하고 사용할 필요가 있음
-            "language" : request_body.language,
-            "promotional_expression_example" : promotional_expressions[request_body.language],
-            "timing_rules" : timing_rules["60s"], # 아직은 선택지 하나
-        }
-        estimated_prompt = lyric_prompt.build_prompt(lyric_input_data) 
 
         step1_elapsed = (time.perf_counter() - step1_start) * 1000
-        #logger.debug(f"[generate_lyric] Step 1 완료 - 프롬프트 {len(prompt)}자 ({step1_elapsed:.1f}ms)")
+        logger.debug(f"[generate_lyric] Step 1 완료 - 프롬프트 {len(prompt)}자 ({step1_elapsed:.1f}ms)")
 
         # ========== Step 2: Project 테이블에 데이터 저장 ==========
         step2_start = time.perf_counter()
@@ -305,12 +273,11 @@ async def generate_lyric(
         step3_start = time.perf_counter()
         logger.debug(f"[generate_lyric] Step 3: Lyric 저장 (processing)...")
 
-        estimated_prompt = lyric_prompt.build_prompt(lyric_input_data) 
         lyric = Lyric(
             project_id=project.id,
             task_id=task_id,
             status="processing",
-            lyric_prompt=estimated_prompt,
+            lyric_prompt=prompt,
             lyric_result=None,
             language=request_body.language,
         )
@@ -328,8 +295,8 @@ async def generate_lyric(
         background_tasks.add_task(
             generate_lyric_background,
             task_id=task_id,
-            prompt=lyric_prompt,
+            prompt=prompt,
-            lyric_input_data=lyric_input_data,
+            language=request_body.language,
         )
 
         step4_elapsed = (time.perf_counter() - step4_start) * 1000
@@ -363,7 +330,7 @@ async def generate_lyric(
             task_id=task_id,
             lyric=None,
             language=request_body.language,
-            error_message=''.join(tb.format_exception(None, e, e.__traceback__)),
+            error_message=str(e),
         )
 
 

app/lyric/services/lyrics.py

@@ -0,0 +1,836 @@
+import random
+from typing import List
+
+from fastapi import Request, status
+from fastapi.exceptions import HTTPException
+from sqlalchemy import Connection, text
+from sqlalchemy.exc import SQLAlchemyError
+
+from app.lyric.schemas.lyrics_schema import (
+    AttributeData,
+    PromptTemplateData,
+    SongFormData,
+    SongSampleData,
+    StoreData,
+)
+from app.utils.chatgpt_prompt import chatgpt_api
+from app.utils.logger import get_logger
+
+# 로거 설정
+logger = get_logger("lyric")
+
+
+async def get_store_info(conn: Connection) -> List[StoreData]:
+    try:
+        query = """SELECT * FROM store_default_info;"""
+        result = await conn.execute(text(query))
+
+        all_store_info = [
+            StoreData(
+                id=row[0],
+                store_info=row[1],
+                store_name=row[2],
+                store_category=row[3],
+                store_region=row[4],
+                store_address=row[5],
+                store_phone_number=row[6],
+                created_at=row[7],
+            )
+            for row in result
+        ]
+
+        result.close()
+        return all_store_info
+    except SQLAlchemyError as e:
+        logger.error(f"Database error in get_store_info: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="요청하신 서비스가 잠시 내부적으로 문제가 발생하였습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected error in get_store_info: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="알수없는 이유로 서비스 오류가 발생하였습니다",
+        )
+
+
+async def get_attribute(conn: Connection) -> List[AttributeData]:
+    try:
+        query = """SELECT * FROM attribute;"""
+        result = await conn.execute(text(query))
+
+        all_attribute = [
+            AttributeData(
+                id=row[0],
+                attr_category=row[1],
+                attr_value=row[2],
+                created_at=row[3],
+            )
+            for row in result
+        ]
+
+        result.close()
+        return all_attribute
+    except SQLAlchemyError as e:
+        logger.error(f"Database error in get_attribute: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="요청하신 서비스가 잠시 내부적으로 문제가 발생하였습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected error in get_attribute: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="알수없는 이유로 서비스 오류가 발생하였습니다",
+        )
+
+
+async def get_attribute(conn: Connection) -> List[AttributeData]:
+    try:
+        query = """SELECT * FROM attribute;"""
+        result = await conn.execute(text(query))
+
+        all_attribute = [
+            AttributeData(
+                id=row[0],
+                attr_category=row[1],
+                attr_value=row[2],
+                created_at=row[3],
+            )
+            for row in result
+        ]
+
+        result.close()
+        return all_attribute
+    except SQLAlchemyError as e:
+        logger.error(f"Database error in get_attribute: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="요청하신 서비스가 잠시 내부적으로 문제가 발생하였습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected error in get_attribute: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="알수없는 이유로 서비스 오류가 발생하였습니다",
+        )
+
+
+async def get_sample_song(conn: Connection) -> List[SongSampleData]:
+    try:
+        query = """SELECT * FROM song_sample;"""
+        result = await conn.execute(text(query))
+
+        all_sample_song = [
+            SongSampleData(
+                id=row[0],
+                ai=row[1],
+                ai_model=row[2],
+                genre=row[3],
+                sample_song=row[4],
+            )
+            for row in result
+        ]
+
+        result.close()
+        return all_sample_song
+    except SQLAlchemyError as e:
+        logger.error(f"Database error in get_sample_song: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="요청하신 서비스가 잠시 내부적으로 문제가 발생하였습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected error in get_sample_song: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="알수없는 이유로 서비스 오류가 발생하였습니다",
+        )
+
+
+async def get_prompt_template(conn: Connection) -> List[PromptTemplateData]:
+    try:
+        query = """SELECT * FROM prompt_template;"""
+        result = await conn.execute(text(query))
+
+        all_prompt_template = [
+            PromptTemplateData(
+                id=row[0],
+                description=row[1],
+                prompt=row[2],
+            )
+            for row in result
+        ]
+
+        result.close()
+        return all_prompt_template
+    except SQLAlchemyError as e:
+        logger.error(f"Database error in get_prompt_template: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="요청하신 서비스가 잠시 내부적으로 문제가 발생하였습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected error in get_prompt_template: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="알수없는 이유로 서비스 오류가 발생하였습니다",
+        )
+
+
+async def get_song_result(conn: Connection) -> List[PromptTemplateData]:
+    try:
+        query = """SELECT * FROM prompt_template;"""
+        result = await conn.execute(text(query))
+
+        all_prompt_template = [
+            PromptTemplateData(
+                id=row[0],
+                description=row[1],
+                prompt=row[2],
+            )
+            for row in result
+        ]
+
+        result.close()
+        return all_prompt_template
+    except SQLAlchemyError as e:
+        logger.error(f"Database error in get_song_result: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="요청하신 서비스가 잠시 내부적으로 문제가 발생하였습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected error in get_song_result: {e}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="알수없는 이유로 서비스 오류가 발생하였습니다",
+        )
+
+
+async def make_song_result(request: Request, conn: Connection):
+    try:
+        # 1. Form 데이터 파싱
+        form_data = await SongFormData.from_form(request)
+
+        logger.info(f"{'=' * 60}")
+        logger.info(f"Store ID: {form_data.store_id}")
+        logger.info(f"Lyrics IDs: {form_data.lyrics_ids}")
+        logger.info(f"Prompt IDs: {form_data.prompts}")
+        logger.info(f"{'=' * 60}")
+
+        # 2. Store 정보 조회
+        store_query = """
+            SELECT * FROM store_default_info WHERE id=:id;
+        """
+        store_result = await conn.execute(text(store_query), {"id": form_data.store_id})
+
+        all_store_info = [
+            StoreData(
+                id=row[0],
+                store_info=row[1],
+                store_name=row[2],
+                store_category=row[3],
+                store_region=row[4],
+                store_address=row[5],
+                store_phone_number=row[6],
+                created_at=row[7],
+            )
+            for row in store_result
+        ]
+
+        if not all_store_info:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Store not found: {form_data.store_id}",
+            )
+
+        store_info = all_store_info[0]
+        logger.info(f"Store: {store_info.store_name}")
+
+        # 3. 속성 조회 -- 단계별 선택 프로세서시 구현 필요 없음
+
+        # 4. Sample Song 조회 및 결합
+        combined_sample_song = None
+
+        if form_data.lyrics_ids:
+            logger.info(f"[샘플 가사 조회] - {len(form_data.lyrics_ids)}개")
+
+            lyrics_query = """
+                SELECT sample_song FROM song_sample
+                WHERE id IN :ids
+                ORDER BY created_at;
+            """
+            lyrics_result = await conn.execute(
+                text(lyrics_query), {"ids": tuple(form_data.lyrics_ids)}
+            )
+
+            sample_songs = [
+                row.sample_song for row in lyrics_result.fetchall() if row.sample_song
+            ]
+
+            if sample_songs:
+                combined_sample_song = "\n\n".join(
+                    [f"[샘플 {i + 1}]\n{song}" for i, song in enumerate(sample_songs)]
+                )
+                logger.info(f"{len(sample_songs)}개의 샘플 가사 조회 완료")
+            else:
+                logger.info("샘플 가사가 비어있습니다")
+        else:
+            logger.info("선택된 lyrics가 없습니다")
+
+        # 5. 템플릿 가져오기
+        if not form_data.prompts:
+            raise HTTPException(
+                status_code=status.HTTP_400_BAD_REQUEST,
+                detail="프롬프트 ID가 필요합니다",
+            )
+
+        logger.info("템플릿 가져오기")
+
+        prompts_query = """
+            SELECT * FROM prompt_template WHERE id=:id;
+        """
+
+        # ✅ 수정: store_query → prompts_query
+        prompts_result = await conn.execute(
+            text(prompts_query), {"id": form_data.prompts}
+        )
+
+        prompts_info = [
+            PromptTemplateData(
+                id=row[0],
+                description=row[1],
+                prompt=row[2],
+            )
+            for row in prompts_result
+        ]
+
+        if not prompts_info:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Prompt not found: {form_data.prompts}",
+            )
+
+        prompt = prompts_info[0]
+        logger.debug(f"Prompt Template: {prompt.prompt}")
+
+        # ✅ 6. 프롬프트 조합
+        updated_prompt = prompt.prompt.replace("###", form_data.attributes_str).format(
+            name=store_info.store_name or "",
+            address=store_info.store_address or "",
+            category=store_info.store_category or "",
+            description=store_info.store_info or "",
+        )
+
+        updated_prompt += f"""
+
+            다음은 참고해야 하는 샘플 가사 정보입니다.
+
+            샘플 가사를 참고하여 작곡을 해주세요.
+
+            {combined_sample_song}
+            """
+
+        logger.debug(f"[업데이트된 프롬프트]\n{updated_prompt}")
+
+        # 7. 모델에게 요청
+        generated_lyrics = await chatgpt_api.generate(prompt=updated_prompt)
+
+        # 글자 수 계산
+        total_chars_with_space = len(generated_lyrics)
+        total_chars_without_space = len(
+            generated_lyrics.replace(" ", "")
+            .replace("\n", "")
+            .replace("\r", "")
+            .replace("\t", "")
+        )
+
+        # final_lyrics 생성
+        final_lyrics = f"""속성 {form_data.attributes_str}
+        전체 글자 수 (공백 포함): {total_chars_with_space}자
+        전체 글자 수 (공백 제외): {total_chars_without_space}자\r\n\r\n{generated_lyrics}"""
+
+        logger.debug("=" * 40)
+        logger.debug(f"[translate:form_data.attributes_str:] {form_data.attributes_str}")
+        logger.debug(f"[translate:total_chars_with_space:] {total_chars_with_space}")
+        logger.debug(f"[translate:total_chars_without_space:] {total_chars_without_space}")
+        logger.debug(f"[translate:final_lyrics:]\n{final_lyrics}")
+        logger.debug("=" * 40)
+
+        # 8. DB 저장
+        insert_query = """
+            INSERT INTO song_results_all (
+                store_info, store_name, store_category, store_address, store_phone_number,
+                description, prompt, attr_category, attr_value,
+                ai, ai_model, genre,
+                sample_song, result_song, created_at
+            ) VALUES (
+                :store_info, :store_name, :store_category, :store_address, :store_phone_number,
+                :description, :prompt, :attr_category, :attr_value,
+                :ai, :ai_model, :genre,
+                :sample_song, :result_song, NOW()
+            );
+        """
+
+        # ✅ attr_category, attr_value 추가
+        insert_params = {
+            "store_info": store_info.store_info or "",
+            "store_name": store_info.store_name,
+            "store_category": store_info.store_category or "",
+            "store_address": store_info.store_address or "",
+            "store_phone_number": store_info.store_phone_number or "",
+            "description": store_info.store_info or "",
+            "prompt": form_data.prompts,
+            "attr_category": ", ".join(form_data.attributes.keys())
+            if form_data.attributes
+            else "",
+            "attr_value": ", ".join(form_data.attributes.values())
+            if form_data.attributes
+            else "",
+            "ai": "ChatGPT",
+            "ai_model": form_data.llm_model,
+            "genre": "후크송",
+            "sample_song": combined_sample_song or "없음",
+            "result_song": final_lyrics,
+        }
+
+        await conn.execute(text(insert_query), insert_params)
+        await conn.commit()
+
+        logger.info("결과 저장 완료")
+
+        logger.info("전체 결과 조회 중...")
+
+        # 9. 생성 결과 가져오기 (created_at 역순)
+        select_query = """
+            SELECT * FROM song_results_all
+            ORDER BY created_at DESC;
+        """
+
+        all_results = await conn.execute(text(select_query))
+
+        results_list = [
+            {
+                "id": row.id,
+                "store_info": row.store_info,
+                "store_name": row.store_name,
+                "store_category": row.store_category,
+                "store_address": row.store_address,
+                "store_phone_number": row.store_phone_number,
+                "description": row.description,
+                "prompt": row.prompt,
+                "attr_category": row.attr_category,
+                "attr_value": row.attr_value,
+                "ai": row.ai,
+                "ai_model": row.ai_model,
+                "genre": row.genre,
+                "sample_song": row.sample_song,
+                "result_song": row.result_song,
+                "created_at": row.created_at.isoformat() if row.created_at else None,
+            }
+            for row in all_results.fetchall()
+        ]
+
+        logger.info(f"전체 {len(results_list)}개의 결과 조회 완료")
+
+        return results_list
+
+    except HTTPException:
+        raise
+    except SQLAlchemyError as e:
+        logger.error(f"Database Error: {e}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="데이터베이스 연결에 문제가 발생했습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected Error: {e}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="서비스 처리 중 오류가 발생했습니다.",
+        )
+
+
+async def get_song_result(conn: Connection):  # 반환 타입 수정
+    try:
+        select_query = """
+            SELECT * FROM song_results_all 
+            ORDER BY created_at DESC;
+        """
+
+        all_results = await conn.execute(text(select_query))
+
+        results_list = [
+            {
+                "id": row.id,
+                "store_info": row.store_info,
+                "store_name": row.store_name,
+                "store_category": row.store_category,
+                "store_address": row.store_address,
+                "store_phone_number": row.store_phone_number,
+                "description": row.description,
+                "prompt": row.prompt,
+                "attr_category": row.attr_category,
+                "attr_value": row.attr_value,
+                "ai": row.ai,
+                "ai_model": row.ai_model,
+                "season": row.season,
+                "num_of_people": row.num_of_people,
+                "people_category": row.people_category,
+                "genre": row.genre,
+                "sample_song": row.sample_song,
+                "result_song": row.result_song,
+                "created_at": row.created_at.isoformat() if row.created_at else None,
+            }
+            for row in all_results.fetchall()
+        ]
+
+        logger.info(f"전체 {len(results_list)}개의 결과 조회 완료")
+
+        return results_list
+    except HTTPException:  # HTTPException은 그대로 raise
+        raise
+    except SQLAlchemyError as e:
+        logger.error(f"Database Error: {e}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="데이터베이스 연결에 문제가 발생했습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected Error: {e}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="서비스 처리 중 오류가 발생했습니다.",
+        )
+
+
+async def make_automation(request: Request, conn: Connection):
+    try:
+        # 1. Form 데이터 파싱
+        form_data = await SongFormData.from_form(request)
+
+        logger.info(f"{'=' * 60}")
+        logger.info(f"Store ID: {form_data.store_id}")
+        logger.info(f"{'=' * 60}")
+
+        # 2. Store 정보 조회
+        store_query = """
+            SELECT * FROM store_default_info WHERE id=:id;
+        """
+        store_result = await conn.execute(text(store_query), {"id": form_data.store_id})
+
+        all_store_info = [
+            StoreData(
+                id=row[0],
+                store_info=row[1],
+                store_name=row[2],
+                store_category=row[3],
+                store_region=row[4],
+                store_address=row[5],
+                store_phone_number=row[6],
+                created_at=row[7],
+            )
+            for row in store_result
+        ]
+
+        if not all_store_info:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail=f"Store not found: {form_data.store_id}",
+            )
+
+        store_info = all_store_info[0]
+        logger.info(f"Store: {store_info.store_name}")
+
+        # 3. 속성 조회 -- 단계별 선택 프로세서시 구현 필요 없음
+        attribute_query = """
+            SELECT * FROM attribute;
+        """
+
+        attribute_results = await conn.execute(text(attribute_query))
+
+        # 결과 가져오기
+        attribute_rows = attribute_results.fetchall()
+
+        formatted_attributes = ""
+        selected_categories = []
+        selected_values = []
+
+        if attribute_rows:
+            attribute_list = [
+                AttributeData(
+                    id=row[0],
+                    attr_category=row[1],
+                    attr_value=row[2],
+                    created_at=row[3],
+                )
+                for row in attribute_rows
+            ]
+
+            # ✅ 각 category에서 하나의 value만 랜덤 선택
+            formatted_pairs = []
+            for attr in attribute_list:
+                # 쉼표로 분리 및 공백 제거
+                values = [v.strip() for v in attr.attr_value.split(",") if v.strip()]
+
+                if values:
+                    # 랜덤하게 하나만 선택
+                    selected_value = random.choice(values)
+                    formatted_pairs.append(f"{attr.attr_category} : {selected_value}")
+
+                    # ✅ 선택된 category와 value 저장
+                    selected_categories.append(attr.attr_category)
+                    selected_values.append(selected_value)
+
+            # 최종 문자열 생성
+            formatted_attributes = "\n".join(formatted_pairs)
+
+            logger.debug(f"[포맷팅된 문자열 속성 정보]\n{formatted_attributes}")
+        else:
+            logger.info("속성 데이터가 없습니다")
+            formatted_attributes = ""
+
+        # 4. 템플릿 가져오기
+        logger.info("템플릿 가져오기 (ID=1)")
+
+        prompts_query = """
+            SELECT * FROM prompt_template WHERE id=1;
+        """
+
+        prompts_result = await conn.execute(text(prompts_query))
+
+        row = prompts_result.fetchone()
+
+        if not row:
+            raise HTTPException(
+                status_code=status.HTTP_404_NOT_FOUND,
+                detail="Prompt ID 1 not found",
+            )
+
+        prompt = PromptTemplateData(
+            id=row[0],
+            description=row[1],
+            prompt=row[2],
+        )
+
+        logger.debug(f"Prompt Template: {prompt.prompt}")
+
+        # 5. 템플릿 조합
+
+        updated_prompt = prompt.prompt.replace("###", formatted_attributes).format(
+            name=store_info.store_name or "",
+            address=store_info.store_address or "",
+            category=store_info.store_category or "",
+            description=store_info.store_info or "",
+        )
+
+        logger.debug("=" * 80)
+        logger.debug("업데이트된 프롬프트")
+        logger.debug("=" * 80)
+        logger.debug(updated_prompt)
+        logger.debug("=" * 80)
+
+        # 4. Sample Song 조회 및 결합
+        combined_sample_song = None
+
+        if form_data.lyrics_ids:
+            logger.info(f"[샘플 가사 조회] - {len(form_data.lyrics_ids)}개")
+
+            lyrics_query = """
+                SELECT sample_song FROM song_sample
+                WHERE id IN :ids
+                ORDER BY created_at;
+            """
+            lyrics_result = await conn.execute(
+                text(lyrics_query), {"ids": tuple(form_data.lyrics_ids)}
+            )
+
+            sample_songs = [
+                row.sample_song for row in lyrics_result.fetchall() if row.sample_song
+            ]
+
+            if sample_songs:
+                combined_sample_song = "\n\n".join(
+                    [f"[샘플 {i + 1}]\n{song}" for i, song in enumerate(sample_songs)]
+                )
+                logger.info(f"{len(sample_songs)}개의 샘플 가사 조회 완료")
+            else:
+                logger.info("샘플 가사가 비어있습니다")
+        else:
+            logger.info("선택된 lyrics가 없습니다")
+
+        # 1. song_sample 테이블의 모든 ID 조회
+        logger.info("[샘플 가사 랜덤 선택]")
+
+        all_ids_query = """
+            SELECT id FROM song_sample;
+        """
+        ids_result = await conn.execute(text(all_ids_query))
+        all_ids = [row.id for row in ids_result.fetchall()]
+
+        logger.info(f"전체 샘플 가사 개수: {len(all_ids)}개")
+
+        # 2. 랜덤하게 3개 선택 (또는 전체 개수가 3개 미만이면 전체)
+        combined_sample_song = None
+
+        if all_ids:
+            # 3개 또는 전체 개수 중 작은 값 선택
+            sample_count = min(3, len(all_ids))
+            selected_ids = random.sample(all_ids, sample_count)
+
+            logger.info(f"랜덤 선택된 ID: {selected_ids}")
+
+            # 3. 선택된 ID로 샘플 가사 조회
+            lyrics_query = """
+                SELECT sample_song FROM song_sample
+                WHERE id IN :ids
+                ORDER BY created_at;
+            """
+            lyrics_result = await conn.execute(
+                text(lyrics_query), {"ids": tuple(selected_ids)}
+            )
+
+            sample_songs = [
+                row.sample_song for row in lyrics_result.fetchall() if row.sample_song
+            ]
+
+            # 4. combined_sample_song 생성
+            if sample_songs:
+                combined_sample_song = "\n\n".join(
+                    [f"[샘플 {i + 1}]\n{song}" for i, song in enumerate(sample_songs)]
+                )
+                logger.info(f"{len(sample_songs)}개의 샘플 가사 조회 완료")
+            else:
+                logger.info("샘플 가사가 비어있습니다")
+        else:
+            logger.info("song_sample 테이블에 데이터가 없습니다")
+
+        # 5. 프롬프트에 샘플 가사 추가
+        if combined_sample_song:
+            updated_prompt += f"""
+
+                다음은 참고해야 하는 샘플 가사 정보입니다.
+
+                샘플 가사를 참고하여 작곡을 해주세요.
+
+                {combined_sample_song}
+            """
+            logger.info("샘플 가사 정보가 프롬프트에 추가되었습니다")
+        else:
+            logger.info("샘플 가사가 없어 기본 프롬프트만 사용합니다")
+
+        logger.info(f"[최종 프롬프트 길이: {len(updated_prompt)} 자]")
+
+        # 7. 모델에게 요청
+        generated_lyrics = await chatgpt_api.generate(prompt=updated_prompt)
+
+        # 글자 수 계산
+        total_chars_with_space = len(generated_lyrics)
+        total_chars_without_space = len(
+            generated_lyrics.replace(" ", "")
+            .replace("\n", "")
+            .replace("\r", "")
+            .replace("\t", "")
+        )
+
+        # final_lyrics 생성
+        final_lyrics = f"""속성 {formatted_attributes}
+        전체 글자 수 (공백 포함): {total_chars_with_space}자
+        전체 글자 수 (공백 제외): {total_chars_without_space}자\r\n\r\n{generated_lyrics}"""
+
+        # 8. DB 저장
+        insert_query = """
+            INSERT INTO song_results_all (
+                store_info, store_name, store_category, store_address, store_phone_number,
+                description, prompt, attr_category, attr_value,
+                ai, ai_model, genre,
+                sample_song, result_song, created_at
+            ) VALUES (
+                :store_info, :store_name, :store_category, :store_address, :store_phone_number,
+                :description, :prompt, :attr_category, :attr_value,
+                :ai, :ai_model, :genre,
+                :sample_song, :result_song, NOW()
+            );
+        """
+        logger.debug("[insert_params 선택된 속성 확인]")
+        logger.debug(f"Categories: {selected_categories}")
+        logger.debug(f"Values: {selected_values}")
+
+        # attr_category, attr_value
+        insert_params = {
+            "store_info": store_info.store_info or "",
+            "store_name": store_info.store_name,
+            "store_category": store_info.store_category or "",
+            "store_address": store_info.store_address or "",
+            "store_phone_number": store_info.store_phone_number or "",
+            "description": store_info.store_info or "",
+            "prompt": prompt.id,
+            # 랜덤 선택된 category와 value 사용
+            "attr_category": ", ".join(selected_categories)
+            if selected_categories
+            else "",
+            "attr_value": ", ".join(selected_values) if selected_values else "",
+            "ai": "ChatGPT",
+            "ai_model": "gpt-5-mini",
+            "genre": "후크송",
+            "sample_song": combined_sample_song or "없음",
+            "result_song": final_lyrics,
+        }
+
+        await conn.execute(text(insert_query), insert_params)
+        await conn.commit()
+
+        logger.info("결과 저장 완료")
+
+        logger.info("전체 결과 조회 중...")
+
+        # 9. 생성 결과 가져오기 (created_at 역순)
+        select_query = """
+            SELECT * FROM song_results_all
+            ORDER BY created_at DESC;
+        """
+
+        all_results = await conn.execute(text(select_query))
+
+        results_list = [
+            {
+                "id": row.id,
+                "store_info": row.store_info,
+                "store_name": row.store_name,
+                "store_category": row.store_category,
+                "store_address": row.store_address,
+                "store_phone_number": row.store_phone_number,
+                "description": row.description,
+                "prompt": row.prompt,
+                "attr_category": row.attr_category,
+                "attr_value": row.attr_value,
+                "ai": row.ai,
+                "ai_model": row.ai_model,
+                "genre": row.genre,
+                "sample_song": row.sample_song,
+                "result_song": row.result_song,
+                "created_at": row.created_at.isoformat() if row.created_at else None,
+            }
+            for row in all_results.fetchall()
+        ]
+
+        logger.info(f"전체 {len(results_list)}개의 결과 조회 완료")
+
+        return results_list
+
+    except HTTPException:
+        raise
+    except SQLAlchemyError as e:
+        logger.error(f"Database Error: {e}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="데이터베이스 연결에 문제가 발생했습니다.",
+        )
+    except Exception as e:
+        logger.error(f"Unexpected Error: {e}", exc_info=True)
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail="서비스 처리 중 오류가 발생했습니다.",
+        )

app/lyric/worker/lyric_task.py

@@ -12,7 +12,6 @@ from sqlalchemy.exc import SQLAlchemyError
 from app.database.session import BackgroundSessionLocal
 from app.lyric.models import Lyric
 from app.utils.chatgpt_prompt import ChatgptService
-from app.utils.prompts.prompts import Prompt
 from app.utils.logger import get_logger
 
 # 로거 설정
@@ -65,8 +64,8 @@ async def _update_lyric_status(
 
 async def generate_lyric_background(
     task_id: str,
-    prompt: Prompt,
+    prompt: str,
-    lyric_input_data: dict, # 프롬프트 메타데이터에서 정의된 Input
+    language: str,
 ) -> None:
     """백그라운드에서 ChatGPT를 통해 가사를 생성하고 Lyric 테이블을 업데이트합니다.
 
@@ -81,22 +80,20 @@ async def generate_lyric_background(
     logger.info(f"[generate_lyric_background] START - task_id: {task_id}")
     logger.debug(f"[generate_lyric_background] ========== START ==========")
     logger.debug(f"[generate_lyric_background] task_id: {task_id}")
-    logger.debug(f"[generate_lyric_background] language: {lyric_input_data['language']}")
+    logger.debug(f"[generate_lyric_background] language: {language}")
-    #logger.debug(f"[generate_lyric_background] prompt length: {len(prompt)}자")
+    logger.debug(f"[generate_lyric_background] prompt length: {len(prompt)}자")
 
     try:
         # ========== Step 1: ChatGPT 서비스 초기화 ==========
         step1_start = time.perf_counter()
         logger.debug(f"[generate_lyric_background] Step 1: ChatGPT 서비스 초기화...")
 
-        # service = ChatgptService(
+        service = ChatgptService(
-        #     customer_name="",  # 프롬프트가 이미 생성되었으므로 빈 값
+            customer_name="",  # 프롬프트가 이미 생성되었으므로 빈 값
-        #     region="",
+            region="",
-        #     detail_region_info="",
+            detail_region_info="",
-        #     language=language,
+            language=language,
-        # )
+        )
-
-        chatgpt = ChatgptService()
 
         step1_elapsed = (time.perf_counter() - step1_start) * 1000
         logger.debug(f"[generate_lyric_background] Step 1 완료 ({step1_elapsed:.1f}ms)")
@@ -106,9 +103,8 @@ async def generate_lyric_background(
         logger.info(f"[generate_lyric_background] Step 2: ChatGPT API 호출 시작 - task_id: {task_id}")
         logger.debug(f"[generate_lyric_background] Step 2: ChatGPT API 호출 시작...")
 
-        #result = await service.generate(prompt=prompt)
+        result = await service.generate(prompt=prompt)
-        result_response = await chatgpt.generate_structured_output(prompt, lyric_input_data)
+
-        result = result_response['lyric']
         step2_elapsed = (time.perf_counter() - step2_start) * 1000
         logger.info(f"[generate_lyric_background] Step 2 완료 - 응답 {len(result)}자 ({step2_elapsed:.1f}ms)")
 

app/utils/chatgpt_prompt.py

@@ -5,11 +5,222 @@ from openai import AsyncOpenAI
 
 from app.utils.logger import get_logger
 from config import apikey_settings
-from app.utils.prompts.prompts import Prompt
 
 # 로거 설정
 logger = get_logger("chatgpt")
 
+# fmt: off
+LYRICS_PROMPT_TEMPLATE_ORI = """
+1.Act as a content marketing expert with domain knowledges in [pension/staying services] in Korea, Goal: plan viral content creation that lead online reservations and promotion
+2.Conduct an in-depth analysis of [업체명:{customer_name}] in [지역명:{region}] by examining their official website or informations, photos on never map and online presence. Create a comprehensive "[지역 상세: {detail_region_info}]_Brand & Marketing Intelligence Report in Korean, that includes:
+
+**Core Analysis:**
+- Target customer segments & personas
+- Unique Selling Propositions (USPs) and competitive differentiators
+- Comprehensive competitor landscape analysis (direct & indirect competitors)
+- Market positioning assessment
+
+**Content Strategy Framework:**
+- Seasonal content calendar with trend integration
+- Visual storytelling direction (shot-by-shot creative guidance)
+- Brand tone & voice guidelines
+- Content themes aligned with target audience behaviors
+
+**SEO & AEO Optimization:**
+- Recommended primary and long-tail keywords
+- SEO-optimized taglines and meta descriptions
+- Answer Engine Optimization (AEO) content suggestions
+- Local search optimization strategies
+
+**Actionable Recommendations:**
+- Content distribution strategy across platforms
+- KPI measurement framework
+- Budget allocation recommendations by content type
+
+콘텐츠 기획(Lyrics, Prompt for SUNO)
+1. Based on the Brand & Marketing Intelligence Report for [업체명 + 지역명 / {customer_name} ({region})], create original lyrics and define music attributes (song mood, BPM, genres, and key musical motifs, Prompt for Suno.com) specifically tailored for viral content.
+2. The lyrics should include, the name of [ Promotion Subject], [location], [main target],[Famous place, accessible in 10min],  promotional words including but not limited  to [인스타 감성], [사진같은 하루]
+
+Deliver outputs optimized for three formats:1 minute. Ensure that each version aligns with the brand's core identity and is suitable for use in digital marketing and social media campaigns, in Korean
+""".strip()
+# fmt: on
+
+LYRICS_PROMPT_TEMPLATE = """
+[ROLE]
+Content marketing expert and creative songwriter specializing in pension/accommodation services
+
+[INPUT]
+- Business Name: {customer_name}
+- Region: {region}
+- Region Details: {detail_region_info}
+- Output Language: {language}
+
+[INTERNAL ANALYSIS - DO NOT OUTPUT]
+Analyze the following internally to inform lyrics creation:
+- Target customer segments and personas
+- Unique Selling Propositions (USPs)
+- Regional characteristics and nearby attractions (within 10 min access)
+- Seasonal appeal points
+- Emotional triggers for the target audience
+
+[LYRICS REQUIREMENTS]
+1. Must Include Elements:
+   - Business name (TRANSLATED or TRANSLITERATED to {language})
+   - Region name (TRANSLATED or TRANSLITERATED to {language})
+   - Main target audience appeal
+   - Nearby famous places or regional characteristics
+
+2. Keywords Selection:
+   <<CRITICAL: Use ONLY the keywords for {language}. DO NOT transliterate or use keywords from other languages.>>
+   
+   Select keywords based on {language}:
+   - IF Korean: 인스타 감성, 사진같은 하루, 힐링, 여행, 감성 숙소
+   - IF English: Instagram vibes, picture-perfect day, healing, travel, getaway
+   - IF Chinese: 网红打卡, 治愈系, 旅行, 度假, 拍照圣地
+   - IF Japanese: インスタ映え, 写真のような一日, 癒し, 旅行, 絶景
+   - IF Thai: ที่พักสวย, ฮีลใจ, เที่ยว, ถ่ายรูป, วิวสวย
+   - IF Vietnamese: check-in đẹp, healing, du lịch, nghỉ dưỡng, view đẹp
+   
+   <<FORBIDDEN: Never transliterate keywords from other languages (e.g., "왕홍다카", "인스타바에", "티팍수아이" are WRONG)>>
+
+
+3. Structure:
+   - Length: For 1-minute video (approximately 8-12 lines)
+   - Flow: Verse structure suitable for music
+   - Rhythm: Natural speech rhythm in the specified language
+
+4. Tone:
+   - Emotional and heartfelt
+   - Trendy and viral-friendly
+   - Relatable to target audience
+
+[CRITICAL LANGUAGE REQUIREMENT - ABSOLUTE RULE]
+ALL OUTPUT MUST BE 100% WRITTEN IN {language} - NO EXCEPTIONS
+- ALL lyrics content: {language} ONLY
+- ALL proper nouns (business names, region names, place names): MUST be translated or transliterated to {language}
+- Korean input like "군산" must become "Gunsan" in English, "群山" in Chinese, "グンサン" in Japanese, etc.
+- Korean input like "스테이 머뭄" must become "Stay Meoum" in English, "住留" in Chinese, "ステイモーム" in Japanese, etc.
+- ZERO Korean characters (한글) allowed when output language is NOT Korean
+- ZERO mixing of languages - the entire output must be monolingual in {language}
+- This is a NON-NEGOTIABLE requirement
+- Any output containing characters from other languages is considered a COMPLETE FAILURE
+- Violation of this rule invalidates the entire response
+
+[OUTPUT RULES - STRICTLY ENFORCED]
+- Output lyrics ONLY
+- Lyrics MUST be written ENTIRELY in {language} - NO EXCEPTIONS
+- ALL names and places MUST be in {language} script/alphabet
+- NO Korean (한글), Chinese (漢字), Japanese (仮名), Thai (ไทย), or Vietnamese (Tiếng Việt) characters unless that is the selected output language
+- NO titles, descriptions, analysis, or explanations
+- NO greetings or closing remarks
+- NO additional commentary before or after lyrics
+- NO line numbers or labels
+- Follow the exact format below
+
+[OUTPUT FORMAT - SUCCESS]
+
+[Lyrics ENTIRELY in {language} here - no other language characters allowed]
+
+
+[OUTPUT FORMAT - FAILURE]
+If you cannot generate lyrics due to insufficient information, invalid input, or any other reason:
+
+ERROR: [Brief reason for failure in English]
+
+""".strip()
+# fmt: on
+
+MARKETING_ANALYSIS_PROMPT_TEMPLATE = """
+[ROLE]
+Content marketing expert specializing in pension/accommodation services in Korea
+
+[INPUT]
+- Business Name: {customer_name}
+- Region: {region}
+- Region Details: {detail_region_info}
+
+[ANALYSIS REQUIREMENTS]
+Provide comprehensive marketing analysis including:
+1. Target Customer Segments
+   - Primary and secondary target personas
+   - Age groups, travel preferences, booking patterns
+2. Unique Selling Propositions (USPs)
+   - Key differentiators based on location and region details
+   - Competitive advantages
+3. Regional Characteristics
+   - Nearby attractions and famous places (within 10 min access)
+   - Local food, activities, and experiences
+   - Transportation accessibility
+4. Seasonal Appeal Points
+   - Best seasons to visit
+   - Seasonal activities and events
+   - Peak/off-peak marketing opportunities
+5. Marketing Keywords
+   - Recommended hashtags and search keywords
+   - Trending terms relevant to the property
+
+[ADDITIONAL REQUIREMENTS]
+1. Recommended Tags
+   - Generate 5 recommended hashtags/tags based on the business characteristics
+   - Tags should be trendy, searchable, and relevant to accommodation marketing
+   - Return as JSON with key "tags"
+   - **MUST be written in Korean (한국어)**
+
+2. Facilities
+   - Based on the business name and region details, identify 5 likely facilities/amenities
+   - Consider typical facilities for accommodations in the given region
+   - Examples: 바베큐장, 수영장, 주차장, 와이파이, 주방, 테라스, 정원, etc.
+   - Return as JSON with key "facilities"
+   - **MUST be written in Korean (한국어)**
+
+[CRITICAL LANGUAGE REQUIREMENT - ABSOLUTE RULE]
+ALL OUTPUT MUST BE WRITTEN IN KOREAN (한국어) 
+- Analysis sections: Korean only
+- Tags: Korean only
+- Facilities: Korean only
+- This is a NON-NEGOTIABLE requirement
+- Any output in English or other languages is considered a FAILURE
+- Violation of this rule invalidates the entire response
+
+[OUTPUT RULES - STRICTLY ENFORCED]
+- Output analysis ONLY
+- ALL content MUST be written in Korean (한국어) - NO EXCEPTIONS
+- NO greetings or closing remarks
+- NO additional commentary before or after analysis
+- Follow the exact format below
+
+[OUTPUT FORMAT - SUCCESS]
+---
+## 타겟 고객 분석
+[한국어로 작성된 타겟 고객 분석]
+
+## 핵심 차별점 (USP)
+[한국어로 작성된 USP 분석]
+
+## 지역 특성
+[한국어로 작성된 지역 특성 분석]
+
+## 시즌별 매력 포인트
+[한국어로 작성된 시즌별 분석]
+
+## 마케팅 키워드
+[한국어로 작성된 마케팅 키워드]
+
+## JSON Data
+```json
+{{
+    "tags": ["태그1", "태그2", "태그3", "태그4", "태그5"],
+    "facilities": ["부대시설1", "부대시설2", "부대시설3", "부대시설4", "부대시설5"]
+}}
+```
+---
+
+[OUTPUT FORMAT - FAILURE]
+If you cannot generate analysis due to insufficient information, invalid input, or any other reason:
+---
+ERROR: [Brief reason for failure in English]
+---
+""".strip()
 # fmt: on
 
 
@@ -19,29 +230,173 @@ class ChatgptService:
     GPT 5.0 모델을 사용하여 마케팅 가사 및 분석을 생성합니다.
     """
 
-    def __init__(self):
+    def __init__(
-        self.client = AsyncOpenAI(api_key=apikey_settings.CHATGPT_API_KEY)
-        
-    async def _call_structured_output_with_response_gpt_api(self, prompt: str, output_format : dict, model:str) -> dict:
-        content = [{"type": "input_text", "text": prompt}]
-        response = await self.client.responses.create(
-            model=model, 
-            input=[{"role": "user", "content": content}],
-            text = output_format
-        )
-        structured_output = json.loads(response.output_text)
-        return structured_output or {}
-
-    async def generate_structured_output(
         self,
-        prompt : Prompt,
+        customer_name: str,
-        input_data : dict,
+        region: str,
-    ) -> str:
+        detail_region_info: str = "",
-        prompt_text = prompt.build_prompt(input_data)
+        language: str = "Korean",
+    ):
+        # 최신 모델: gpt-5-mini
+        self.model = "gpt-5-mini"
+        self.client = AsyncOpenAI(api_key=apikey_settings.CHATGPT_API_KEY)
+        self.customer_name = customer_name
+        self.region = region
+        self.detail_region_info = detail_region_info
+        self.language = language
 
-        print(f"[ChatgptService] Generated Prompt (length: {len(prompt_text)})")
+    def build_lyrics_prompt(self) -> str:
-        logger.info(f"[ChatgptService] Starting GPT request with structured output with model: {prompt.prompt_model}")
+        """LYRICS_PROMPT_TEMPLATE에 고객 정보를 대입하여 완성된 프롬프트 반환"""
+        return LYRICS_PROMPT_TEMPLATE.format(
+            customer_name=self.customer_name,
+            region=self.region,
+            detail_region_info=self.detail_region_info,
+            language=self.language,
+        )
+
+    def build_market_analysis_prompt(self) -> str:
+        """MARKETING_ANALYSIS_PROMPT_TEMPLATE에 고객 정보를 대입하여 완성된 프롬프트 반환"""
+        return MARKETING_ANALYSIS_PROMPT_TEMPLATE.format(
+            customer_name=self.customer_name,
+            region=self.region,
+            detail_region_info=self.detail_region_info,
+        )
+
+    async def _call_gpt_api(self, prompt: str) -> str:
+        """GPT API를 직접 호출합니다 (내부 메서드).
+
+        Args:
+            prompt: GPT에 전달할 프롬프트
+
+        Returns:
+            GPT 응답 문자열
+
+        Raises:
+            APIError, APIConnectionError, RateLimitError: OpenAI API 오류
+        """
+        completion = await self.client.chat.completions.create(
+            model=self.model, messages=[{"role": "user", "content": prompt}]
+        )
+        message = completion.choices[0].message.content
+        return message or ""
+
+    async def generate(
+        self,
+        prompt: str | None = None,
+    ) -> str:
+        """GPT에게 프롬프트를 전달하여 결과를 반환합니다.
+
+        Args:
+            prompt: GPT에 전달할 프롬프트 (None이면 기본 가사 프롬프트 사용)
+
+        Returns:
+            GPT 응답 문자열
+
+        Raises:
+            APIError, APIConnectionError, RateLimitError: OpenAI API 오류
+        """
+        if prompt is None:
+            prompt = self.build_lyrics_prompt()
+
+        logger.debug(f"[ChatgptService] Generated Prompt (length: {len(prompt)})")
+        logger.info(f"[ChatgptService] Starting GPT request with model: {self.model}")
 
         # GPT API 호출
-        response = await self._call_structured_output_with_response_gpt_api(prompt_text, prompt.prompt_output, prompt.prompt_model) 
+        response = await self._call_gpt_api(prompt)
+
+        logger.info(f"[ChatgptService] SUCCESS - Response length: {len(response)}")
         return response
+
+    async def summarize_marketing(self, text: str) -> str:
+        """마케팅 텍스트를 항목으로 구분하여 500자로 요약 정리.
+
+        Args:
+            text: 요약할 마케팅 텍스트
+
+        Returns:
+            요약된 텍스트
+
+        Raises:
+            APIError, APIConnectionError, RateLimitError: OpenAI API 오류
+        """
+        prompt = f"""[ROLE]
+마케팅 콘텐츠 요약 전문가
+
+[INPUT]
+{text}
+
+[TASK]
+위 텍스트를 분석하여 핵심 내용을 항목별로 구분하여 500자 이내로 요약해주세요.
+
+[OUTPUT REQUIREMENTS]
+- 5개 항목으로 구분: 타겟 고객, 핵심 차별점, 지역 특성, 시즌별 포인트
+- 각 항목은 줄바꿈으로 구분
+- 총 800자 이내로 요약
+- 내용의 누락이 있어서는 안된다
+- 문장이 자연스러워야 한다
+- 핵심 정보만 간결하게 포함
+- 한국어로 작성
+- 특수문자 사용 금지 (괄호, 슬래시, 하이픈, 물결표 등 제외)
+- 쉼표와 마침표만 사용하여 자연스러운 문장으로 작성
+
+[OUTPUT FORMAT - 반드시 아래 형식 준수]
+
+타겟 고객
+[대상 고객층을 자연스러운 문장으로 설명]
+
+핵심 차별점
+[숙소의 차별화 포인트를 자연스러운 문장으로 설명]
+
+지역 특성
+[주변 관광지와 지역 특색을 자연스러운 문장으로 설명]
+
+시즌별 포인트
+[계절별 매력 포인트를 자연스러운 문장으로 설명]
+"""
+# 추천 키워드
+# [마케팅에 활용할 키워드를 쉼표로 구분하여 나열]
+
+
+
+        result = await self.generate(prompt=prompt)
+
+        # --- 구분자 제거
+        if result.startswith("---"):
+            result = result[3:].strip()
+        if result.endswith("---"):
+            result = result[:-3].strip()
+
+        return result
+
+    async def parse_marketing_analysis(self, raw_response: str) -> dict:
+        """ChatGPT 마케팅 분석 응답을 파싱하고 요약하여 딕셔너리로 반환
+
+        Returns:
+            dict: {"report": str, "tags": list[str], "facilities": list[str]}
+        """
+        tags: list[str] = []
+        facilities: list[str] = []
+        report = raw_response
+
+        # JSON 블록 추출 시도
+        json_match = re.search(r"```json\s*(\{.*?\})\s*```", raw_response, re.DOTALL)
+        if json_match:
+            try:
+                json_data = json.loads(json_match.group(1))
+                tags = json_data.get("tags", [])
+                facilities = json_data.get("facilities", [])
+                # JSON 블록을 제외한 리포트 부분 추출
+                report = raw_response[: json_match.start()].strip()
+                # --- 구분자 제거
+                if report.startswith("---"):
+                    report = report[3:].strip()
+                if report.endswith("---"):
+                    report = report[:-3].strip()
+            except json.JSONDecodeError:
+                pass
+
+        # 리포트 내용을 500자로 요약
+        if report:
+            report = await self.summarize_marketing(report)
+
+        return {"report": report, "tags": tags, "facilities": facilities}

app/utils/prompts/lyric_prompt.json

@@ -1,34 +0,0 @@
-{
-    "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/lyric_prompt.txt

@@ -1,76 +0,0 @@
-
-[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/marketing_prompt.json

@@ -1,58 +0,0 @@
-{
-    "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/marketing_prompt.txt

@@ -1,64 +0,0 @@
-
-[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/marketing_prompt_20260116.txt

@@ -1,62 +0,0 @@
-
-[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/prompts.py

@@ -1,73 +0,0 @@
-import os, json
-from abc import ABCMeta
-from config import prompt_settings
-
-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
-        print("build_template", build_template)
-        print("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/summarize_prompt.json

@@ -1,33 +0,0 @@
-{
-    "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/summarize_prompt.txt

@@ -1,53 +0,0 @@
-
-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
-    

config.py

@@ -145,13 +145,6 @@ class CreatomateSettings(BaseSettings):
 
     model_config = _base_config
 
-class PromptSettings(BaseSettings):
-    PROMPT_FOLDER_ROOT : str = Field(default="./app/utils/prompts")
-    MARKETING_PROMPT_NAME : str = Field(default="marketing_prompt")
-    SUMMARIZE_PROMPT_NAME : str = Field(default="summarize_prompt")
-    LYLIC_PROMPT_NAME : str = Field(default="lyric_prompt")
-
-    model_config = _base_config
 
 class KakaoSettings(BaseSettings):
     """카카오 OAuth 설정"""
@@ -382,7 +375,6 @@ cors_settings = CORSSettings()
 crawler_settings = CrawlerSettings()
 azure_blob_settings = AzureBlobSettings()
 creatomate_settings = CreatomateSettings()
-prompt_settings = PromptSettings()
 log_settings = LogSettings()
 kakao_settings = KakaoSettings()
 jwt_settings = JWTSettings()

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
-}

poc/blob/blob_storage.py

@@ -1,77 +0,0 @@
-import aiohttp
-from pathlib import Path
-
-class BlobUploader():
-    root_url = "https://ado2mediastoragepublic.blob.core.windows.net/ado2-media-public-access/ado2-media-original/"
-    image_content_types = {
-        ".jpg": "image/jpeg",
-        ".jpeg": "image/jpeg",
-        ".png": "image/png",
-        ".gif": "image/gif",
-        ".webp": "image/webp",
-        ".bmp": "image/bmp"
-    }
-    # SAS TOKEN 입력으로 저장
-    def __init__(self, sas_token):
-        self.sas_token = sas_token
-
-    # 음악 파일 업로드 (user_idx/task_idx/music_file_name 경로에 저장), 해당 업로드 링크 출력 / 실패 시 None
-    async def upload_music_to_azure_blob(self, file_data : bytes, user_idx : str, task_idx : str, music_file_name : str) -> str:
-        url = f"{self.root_url}/{user_idx}/{task_idx}/{music_file_name}"
-        access_url = f"{url}?{self.sas_token}"
-        headers = {
-            "Content-Type": "audio/mpeg",
-            "x-ms-blob-type": "BlockBlob"
-        }
-        
-        async with aiohttp.ClientSession() as session:
-            async with session.put(access_url, data=file_data, headers=headers) as resp:
-                if resp.status in [200, 201]:
-                    return url
-                else:
-                    text = await resp.text()
-                    print(f"Failed Status Code: {resp.status}")
-                    print(f"Response: {text}")
-                    return None
-
-
-    # 영상 파일 업로드 (user_idx/task_idx/video_file_name 경로에 저장), 해당 업로드 링크 출력 / 실패 시 None
-    async def upload_video_to_azure_blob(self, file_data : bytes, user_idx : str, task_idx : str, video_file_name : str) -> str:
-        url = f"{self.root_url}/{user_idx}/{task_idx}/{video_file_name}"
-        access_url = f"{url}?{self.sas_token}"
-        headers = {
-            "Content-Type": "video/mp4",
-            "x-ms-blob-type": "BlockBlob"
-        }
-        
-        async with aiohttp.ClientSession() as session:
-            async with session.put(access_url, data=file_data, headers=headers) as resp:
-                if resp.status in [200, 201]:
-                    return url
-                else:
-                    text = await resp.text()
-                    print(f"Failed Status Code: {resp.status}")
-                    print(f"Response: {text}")
-                    return None
-
-
-    # 이미지 파일 업로드 (user_idx/task_idx/image_file_name 경로에 저장), 해당 업로드 링크 출력 / 실패 시 None
-    async def upload_image_to_azure_blob(self, file_data : bytes, user_idx : str, task_idx : str, image_file_name : str) -> str:
-        url = f"{self.root_url}/{user_idx}/{task_idx}/{image_file_name}"
-        access_url = f"{url}?{self.sas_token}"
-        extension = Path(image_file_name).suffix.lower()
-        content_type = self.image_content_types.get(extension, "image/jpeg")
-        headers = {
-            "Content-Type": content_type,
-            "x-ms-blob-type": "BlockBlob"
-        }
-        
-        async with aiohttp.ClientSession() as session:
-            async with session.put(access_url, data=file_data, headers=headers) as resp:
-                if resp.status in [200, 201]:
-                    return url
-                else:
-                    text = await resp.text()
-                    print(f"Failed Status Code: {resp.status}")
-                    print(f"Response: {text}")
-                    return None

poc/crawling/main.py

@@ -1,29 +0,0 @@
-import asyncio
-from nvMapScraper import nvMapScraper
-from nvMapPwScraper import nvMapPwScraper
-
-async def main_function():
-    await nvMapPwScraper.initiate_scraper()
-    selected = {'title': '<b>스테이</b>,<b>머뭄</b>',
-                    'link': 'https://www.instagram.com/staymeomoom',
-                    'category': '숙박>펜션',
-                    'description': '',
-                    'telephone': '',
-                    'address': '전북특별자치도 군산시 신흥동 63-18',
-                    'roadAddress': '전북특별자치도 군산시 절골길 18',
-                    'mapx': '1267061254',
-                    'mapy': '359864175',
-                    'lng': 126.7061254,
-                    'lat': 35.9864175}
-    
-    async with nvMapPwScraper() as pw_scraper:
-        new_url = await pw_scraper.get_place_id_url(selected)
-
-    print(new_url)
-    nv_scraper = nvMapScraper(new_url) # 이후 동일한 플로우
-    await nv_scraper.scrap()
-    print(nv_scraper.rawdata)
-    return
-
-print("running main_funtion..")
-asyncio.run(main_function())

poc/crawling/nvMapPwScraper.py

@@ -1,113 +0,0 @@
-import asyncio
-from playwright.async_api import async_playwright
-from urllib import parse
-
-class nvMapPwScraper():
-    # cls vars
-    is_ready = False
-    _playwright = None
-    _browser = None
-    _context = None
-    _win_width = 1280
-    _win_height = 720
-    _max_retry = 30 # place id timeout threshold seconds
-    
-    # instance var
-    page = None
-
-    @classmethod
-    def default_context_builder(cls):
-        context_builder_dict = {}
-        context_builder_dict['viewport'] = {
-                'width' : cls._win_width,
-                'height' : cls._win_height
-        }
-        context_builder_dict['screen'] = {
-                'width' : cls._win_width,
-                'height' : cls._win_height
-        }
-        context_builder_dict['user_agent'] = "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36"
-        context_builder_dict['locale'] = 'ko-KR'
-        context_builder_dict['timezone_id']='Asia/Seoul'
-
-        return context_builder_dict
-       
-    @classmethod
-    async def initiate_scraper(cls):
-        if not cls._playwright:
-            cls._playwright = await async_playwright().start()
-        if not cls._browser:
-            cls._browser = await cls._playwright.chromium.launch(headless=True)
-        if not cls._context:
-            cls._context = await cls._browser.new_context(**cls.default_context_builder())
-        cls.is_ready = True
-    
-    def __init__(self):
-        if not self.is_ready:
-            raise Exception("nvMapScraper is not initiated")
-
-    async def __aenter__(self):
-        await self.create_page()
-        return self
-
-    async def __aexit__(self, exc_type, exc, tb):
-        await self.page.close()
-        
-    async def create_page(self):
-        self.page = await self._context.new_page()
-        await self.page.add_init_script(
-'''const defaultGetter = Object.getOwnPropertyDescriptor(
-    Navigator.prototype,
-    "webdriver"
-).get;
-defaultGetter.apply(navigator);
-defaultGetter.toString();
-Object.defineProperty(Navigator.prototype, "webdriver", {
-    set: undefined,
-    enumerable: true,
-    configurable: true,
-    get: new Proxy(defaultGetter, {
-    apply: (target, thisArg, args) => {
-        Reflect.apply(target, thisArg, args);
-        return false;
-    },
-    }),
-});
-const patchedGetter = Object.getOwnPropertyDescriptor(
-    Navigator.prototype,
-    "webdriver"
-).get;
-patchedGetter.apply(navigator);
-patchedGetter.toString();''')
-
-        await self.page.set_extra_http_headers({
-            'sec-ch-ua': '\"Not?A_Brand\";v=\"99\", \"Chromium\";v=\"130\"'
-        })
-        await self.page.goto("http://google.com")
-        
-    async def goto_url(self, url, wait_until="domcontentloaded", timeout=20000):
-        page = self.page
-        await page.goto(url, wait_until=wait_until, timeout=timeout)
-
-    async def get_place_id_url(self, selected):
-        
-        title = selected['title'].replace("<b>", "").replace("</b>", "")
-        address = selected.get('roadAddress', selected['address']).replace("<b>", "").replace("</b>", "")
-        encoded_query = parse.quote(f"{address} {title}")
-        url = f"https://map.naver.com/p/search/{encoded_query}"
-
-        await self.goto_url(url, wait_until="networkidle",timeout = self._max_retry/2*1000)
-
-        if "/place/" in self.page.url:
-            return self.page.url
-
-        url = self.page.url.replace("?","?isCorrectAnswer=true&")
-        await self.goto_url(url, wait_until="networkidle",timeout = self._max_retry/2*1000)
-        
-        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")

poc/crawling/nvMapScraper.py

@@ -1,14 +1,13 @@
-import re
-import aiohttp
-import json
 import asyncio
-import bs4
+import json
+import re
+
+import aiohttp
 
-PLACE_PATTERN = r"/place/(\d+)"
 GRAPHQL_URL = "https://pcmap-api.place.naver.com/graphql"
-NAVER_COOKIES="NAC=mQ7mBownbQf4A; NNB=TQPII6AKDBFGQ; PLACE_LANGUAGE=ko; NACT=1; nid_inf=1431570813; NID_AUT=k2T7FraXOdIMRCHzEZIFtHQup+I7b87M5fd7+p65AXZTdGB/gelRmW8s/Q4oDxm8; tooltipDisplayed=true; SRT30=1762660151; NID_SES=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; _naver_usersession_=Kkgzim/64JicPJzgkIIvqQ==; page_uid=jesTPsqVWUZssE4qJeossssssD0-011300; SRT5=1762662010; BUC=z5Fu3sAYtFwpbRDrrDFYdn4AgK5hNkOqX-DdaLU7VJM="
+NAVER_COOKIES = "NAC=mQ7mBownbQf4A; NNB=TQPII6AKDBFGQ; PLACE_LANGUAGE=ko; NACT=1; nid_inf=1431570813; NID_AUT=k2T7FraXOdIMRCHzEZIFtHQup+I7b87M5fd7+p65AXZTdGB/gelRmW8s/Q4oDxm8; tooltipDisplayed=true; SRT30=1762660151; NID_SES=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; _naver_usersession_=Kkgzim/64JicPJzgkIIvqQ==; page_uid=jesTPsqVWUZssE4qJeossssssD0-011300; SRT5=1762662010; BUC=z5Fu3sAYtFwpbRDrrDFYdn4AgK5hNkOqX-DdaLU7VJM="
 
-OVERVIEW_QUERY = '''
+OVERVIEW_QUERY = """
 query getAccommodation($id: String!, $deviceType: String) {
     business: placeDetail(input: {id: $id, isNx: true, deviceType: $deviceType}) {
         base {
@@ -26,59 +25,52 @@ query getAccommodation($id: String!, $deviceType: String) {
         images { images { origin url } }
         cpImages(source: [ugcImage]) { images { origin url } }
     }
-}'''
+}"""
-
 REQUEST_HEADERS = {
     "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36",
     "Referer": "https://map.naver.com/",
     "Origin": "https://map.naver.com",
     "Content-Type": "application/json",
-    "Cookie": NAVER_COOKIES
+    "Cookie": NAVER_COOKIES,
 }
 
+
 class GraphQLException(Exception):
     pass
 
-class nvMapScraper():
-    url : str = None
-    scrap_type : str = None
-    rawdata : dict = None
-    image_link_list : list[str] = None
-    base_info : dict = None
 
+class nvMapScraper:
+    url: str = None
+    scrap_type: str = None
+    rawdata: dict = None
+    image_link_list: list[str] = None
+    base_info: dict = None
 
     def __init__(self, url):
         self.url = url
 
-    async def parse_url(self):
+    def parse_url(self):
-        if 'place' not in self.url:
+        place_pattern = r"/place/(\d+)"
-            if 'naver.me' in self.url:
-                async with aiohttp.ClientSession() as session:
-                    async with session.get(self.url) as response:
-                        self.url = str(response.url)
-            else:
-                raise GraphQLException("this shorten url not have place id")
         try:
-            place_id = re.search(PLACE_PATTERN, self.url)[1]
+            place_id = re.search(place_pattern, self.url)[1]
-        except Exception as E:
+        except:
-            raise GraphQLException("Cannot find place id")
+            raise GraphQLException()
 
         return place_id
 
     async def scrap(self):
         try:
-            place_id = await self.parse_url()
+            place_id = self.parse_url()
             data = await self.call_get_accomodation(place_id)
             self.rawdata = data
-            fac_data = await self.get_facility_string(place_id)
+            self.image_link_list = [
-            self.rawdata['facilities'] = fac_data
+                nv_image["origin"]
-            self.image_link_list = [nv_image['origin'] for nv_image in data['data']['business']['images']['images']]
+                for nv_image in data["data"]["business"]["images"]["images"]
-            self.base_info = data['data']['business']['base']
+            ]
-            self.facility_info = fac_data
+            self.base_info = data["data"]["business"]["base"]
             self.scrap_type = "GraphQL"
 
-        except GraphQLException as G:
+        except GraphQLException:
-            print (G)
             print("fallback")
             self.scrap_type = "Playwright"
             pass  # 나중에 pw 이용한 crawling으로 fallback 추가
@@ -87,33 +79,27 @@ class nvMapScraper():
 
     async def call_get_accomodation(self, place_id):
         payload = {
-            "operationName" : "getAccommodation",
+            "operationName": "getAccommodation",
-            "variables": { "id": place_id, "deviceType": "pc" },
+            "variables": {"id": place_id, "deviceType": "pc"},
             "query": OVERVIEW_QUERY,
         }
         json_payload = json.dumps(payload)
 
         async with aiohttp.ClientSession() as session:
-            async with session.post(GRAPHQL_URL, data=json_payload, headers=REQUEST_HEADERS) as response:
+            async with session.post(
-                response.encoding = 'utf-8'
+                GRAPHQL_URL, data=json_payload, headers=REQUEST_HEADERS
+            ) as response:
+                response.encoding = "utf-8"
                 if response.status == 200:  # 요청 성공
                     return await response.json()  # await 주의
                 else:  # 요청 실패
-                    print('실패 상태 코드:', response.status)
+                    print("실패 상태 코드:", response.status)
-                    print(response.text)
                     raise Exception()
 
-    async def get_facility_string(self, place_id):
-        url = f"https://pcmap.place.naver.com/accommodation/{place_id}/home"
-        async with aiohttp.ClientSession() as session:
-            async with session.get(url, headers=REQUEST_HEADERS) as response:
-                soup = bs4.BeautifulSoup(await response.read(), 'html.parser')
-                c_elem = soup.find('span', 'place_blind', string='편의')
-                facilities = c_elem.parent.parent.find('div').string
-        return facilities
 
-# url = "https://naver.me/IgJGCCic"
+url = "https://map.naver.com/p/search/%EC%8A%A4%ED%85%8C%EC%9D%B4%EB%A8%B8%EB%AD%84/place/1133638931?c=14.70,0,0,0,dh&placePath=/photo?businessCategory=pension&fromPanelNum=2&locale=ko&searchText=%EC%8A%A4%ED%85%8C%EC%9D%B4%EB%A8%B8%EB%AD%84&svcName=map_pcv5&timestamp=202512191123&fromPanelNum=2&locale=ko&searchText=%EC%8A%A4%ED%85%8C%EC%9D%B4%EB%A8%B8%EB%AD%84&svcName=map_pcv5&timestamp=202512191007&from=map&entry=bmp&filterType=%EC%97%85%EC%B2%B4&businessCategory=pension"
-# scraper = nvMapScraper(url)
+scraper = nvMapScraper(url)
-# asyncio.run(scraper.scrap())
+asyncio.run(scraper.scrap())
-# print(scraper.image_link_list)
+print(scraper.image_link_list)
-# print(len(scraper.image_link_list))
+print(len(scraper.image_link_list))
+print(scraper.base_info)

poc/timestamp_lyric/lyric_timestamp_mapper.py

@@ -1,42 +0,0 @@
-from openai import OpenAI
-from difflib import SequenceMatcher
-from dataclasses import dataclass
-from typing import List, Tuple
-import aiohttp, json
-
-
-@dataclass
-class TimestampedLyric:
-    text: str
-    start: float
-    end: float
-
-SUNO_BASE_URL="https://api.sunoapi.org"
-SUNO_TIMESTAMP_ROUTE = "/api/v1/generate/get-timestamped-lyrics"
-SUNO_DETAIL_ROUTE = "/api/v1/generate/record-info"
-
-class LyricTimestampMapper:
-    suno_api_key : str
-    def __init__(self, suno_api_key):
-        self.suno_api_key = suno_api_key
-    
-    async def get_suno_audio_id_from_task_id(self, suno_task_id): # expire if db save audio id
-        url = f"{SUNO_BASE_URL}{SUNO_DETAIL_ROUTE}"
-        headers = {"Authorization": f"Bearer {self.suno_api_key}"}
-        async with aiohttp.ClientSession() as session:
-            async with session.get(url, headers=headers, params={"taskId" : suno_task_id}) as response:
-                detail = await response.json()
-                result = detail['data']['response']['sunoData'][0]['id']
-        return result
-            
-    async def get_suno_timestamp(self, suno_task_id, suno_audio_id): # expire if db save audio id
-        url = f"{SUNO_BASE_URL}{SUNO_TIMESTAMP_ROUTE}"
-        headers = {"Authorization": f"Bearer {self.suno_api_key}"}
-        payload = {
-            "task_id" : suno_task_id,
-            "audio_id" : suno_audio_id
-        }
-        async with aiohttp.ClientSession() as session:
-            async with session.post(url, headers=headers, data=json.dumps(payload)) as response:
-                result = await response.json()
-        return result

poc/timestamp_lyric/test_mapper.py

@@ -1,19 +0,0 @@
-from lyric_timestamp_mapper import LyricTimestampMapper
-
-API_KEY = "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"
-AUDIO_PATH = "test_audio.mp3"
-
-GROUND_TRUTH_LYRICS = [
-    "첫 번째 가사 라인입니다",
-    "두 번째 가사 라인입니다",
-    "세 번째 가사 라인입니다",
-]
-
-mapper = LyricTimestampMapper(api_key=API_KEY)
-result = mapper.map_ground_truth(AUDIO_PATH, GROUND_TRUTH_LYRICS)
-
-for lyric in result:
-    if lyric.start >= 0:
-        print(f"[{lyric.start:.2f} - {lyric.end:.2f}] {lyric.text}")
-    else:
-        print(f"[매칭 실패] {lyric.text}")