feat: FastAPI 뼈대 구성(임시)

apps/pre-processing-service/app/api/endpoints/blog.py

@@ -1,6 +1,3 @@
-# app/api/endpoints/keywords.py
-from fastapi import APIRouter
-from app.decorators.logging import log_api_call
 from ...errors.CustomException import *
 from fastapi import APIRouter
 
@@ -14,8 +11,14 @@ async def root():
 
 @router.post("/rag/create", response_model=ResponseBlogCreate)
 async def rag_create(request: RequestBlogCreate):
+    """
+    RAG 기반 블로그 콘텐츠 생성
+    """
     return {"message": "blog API"}
 
 @router.post("/publish", response_model=RequestBlogPublish)
 async def publish(request: ResponseBlogPublish):
+    """
+    생성된 블로그 콘텐츠 배포
+    """
     return {"message": "blog API"}

apps/pre-processing-service/app/api/endpoints/keywords.py

@@ -1,12 +1,9 @@
 # app/api/endpoints/keywords.py
 from ...service.keyword_service import keyword_search
 
-from fastapi import APIRouter
-from app.decorators.logging import log_api_call
-from ...errors.CustomException import *
 from fastapi import APIRouter
 from ...errors.CustomException import  *
-from ...model.schemas import RequestNaverSearch, ResponseNaverSearch, RequestSadaguValidate, ResponsetSadaguValidate
+from ...model.schemas import RequestNaverSearch, ResponseNaverSearch
 
 # 이 파일만의 독립적인 라우터를 생성합니다.
 router = APIRouter()
@@ -32,7 +29,3 @@ async def search(request: RequestNaverSearch):
     """
     response_data= await keyword_search(request)
     return response_data
-
-@router.post("/ssadagu/validate",response_model=ResponseNaverSearch)
-async def ssadagu_validate(request: RequestNaverSearch):
-    return ResponseNaverSearch()

apps/pre-processing-service/app/api/endpoints/product.py

@@ -2,13 +2,43 @@
 from app.decorators.logging import log_api_call
 from ...errors.CustomException import InvalidItemDataException, ItemNotFoundException
 from ...service.crawl_service import crawl_product_detail
+from ...service.search_service import search_products
+from ...service.match_service import match_products
+from ...service.similarity_service import select_product_by_similarity
 from ...model.schemas import *
 
 router = APIRouter()
 
+@router.get("/")
+async def root():
+    return {"message": "product API"}
+
+@router.post("/search", response_model=ResponseSadaguSearch)
+async def search(request: RequestSadaguSearch):
+    """
+    상품 검색 엔드포인트
+    """
+    return search_products(request)
+
+@router.post("/match", response_model=ResponseSadaguMatch)
+async def match(request: RequestSadaguMatch):
+    """
+    상품 매칭 엔드포인트
+    """
+    return match_products(request)
+
+@router.post("/similarity", response_model=ResponseSadaguSimilarity)
+async def similarity(request: RequestSadaguSimilarity):
+    """
+    유사도 분석 엔드포인트
+    """
+    return select_product_by_similarity(request)
+
 @router.post("/crawl", response_model=ResponseSadaguCrawl)
-@log_api_call
 async def crawl(request: Request, body: RequestSadaguCrawl):
+    """
+    상품 상세 정보 크롤링 엔드포인트
+    """
     try:
         result = await crawl_product_detail(body)
         return result
@@ -17,5 +47,4 @@ async def crawl(request: Request, body: RequestSadaguCrawl):
     except ItemNotFoundException as e:
         raise HTTPException(status_code=e.status_code, detail=e.detail)
     except Exception as e:
-        # 나머지 예외는 500으로 처리
         raise HTTPException(status_code=500, detail=str(e))

apps/pre-processing-service/app/api/router.py

@@ -1,6 +1,6 @@
 # app/api/router.py
 from fastapi import APIRouter
-from .endpoints import keywords, blog,test,product
+from .endpoints import keywords, blog, product, test
 from ..core.config import settings
 
 api_router = APIRouter()
@@ -14,7 +14,7 @@
 #상품 API URL
 api_router.include_router(product.router, prefix="/product", tags=["product"])
 
-#모듈 테스터를 위한 endpoint
+#모듈 테스터를 위한 endpoint -> 추후 삭제 예정
 api_router.include_router(test.router, prefix="/test", tags=["Test"])
 
 @api_router.get("/")

apps/pre-processing-service/app/model/schemas.py

@@ -24,18 +24,44 @@ class RequestNaverSearch(RequestBase):
     end_date : Optional[str] = None
 
 class ResponseNaverSearch(ResponseBase):
-    category: str
+    category: Optional[str] = None
     keyword: str
     total_keyword: dict[int, str]
 
+# #키워드 사다구몰 검증
+# class RequestSadaguValidate(RequestBase):
+#     tag: str
+#     category: str
+#
+# class ResponsetSadaguValidate(ResponseBase):
+#     keyword: str
 
-#키워드 사다구몰 검증
-class RequestSadaguValidate(RequestBase):
-    tag: str
-    category: str
+# 2단계: 검색
+class RequestSadaguSearch(RequestBase):
+    keyword: str
+
+class ResponseSadaguSearch(ResponseBase):
+    keyword: str
+    search_results: list[dict]
+
+# 3단계: 매칭
+class RequestSadaguMatch(RequestBase):
+    keyword: str
+    search_results: list[dict]
+
+class ResponseSadaguMatch(ResponseBase):
+    keyword: str
+    matched_products: list[dict]
+
+# 4단계: 유사도
+class RequestSadaguSimilarity(RequestBase):
+    keyword: str
+    matched_products: list[dict]
 
-class ResponseSadaguValidate(ResponseBase):
+class ResponseSadaguSimilarity(ResponseBase):
     keyword: str
+    selected_product: dict | None = None
+    reason: str | None = None
 
 #사다구몰 크롤링
 class RequestSadaguCrawl(RequestBase):

apps/pre-processing-service/app/service/match_service.py

@@ -0,0 +1,21 @@
+import urllib
+
+from ..model.schemas import RequestSadaguMatch
+
+def match_products(request: RequestSadaguMatch) -> dict:
+    """
+    키워드 매칭 로직 (MeCab 등 사용)
+    """
+    keyword = request.keyword
+    products = request.search_results
+
+    # 키워드 매칭 로직 적용 해야함
+    matched = [p for p in products if keyword in p["title"]]
+
+    return {
+        "job_id": request.job_id,
+        "schedule_id": request.schedule_id,
+        "keyword": keyword,
+        "matched_products": matched,
+        "status": "success"
+    }

apps/pre-processing-service/app/service/search_service.py

@@ -0,0 +1,23 @@
+from ..model.schemas import RequestSadaguSearch
+import urllib.parse
+
+def search_products(request: RequestSadaguSearch) -> dict:
+    """
+    키워드 기반으로 상품을 검색하는 비즈니스 로직
+    """
+    keyword = request.keyword
+    encoded_keyword = urllib.parse.quote(keyword)
+
+    # Selenium/requests 로직 추가 해야함
+    search_results = [
+        {"url": f"https://ssadagu.kr/view.php?id=123"},
+        {"url": f"https://ssadagu.kr/view.php?id=456"}
+    ]
+
+    return {
+        "job_id": request.job_id,
+        "schedule_id": request.schedule_id,
+        "keyword": keyword,
+        "search_results": search_results,
+        "status": "success"
+    }

apps/pre-processing-service/app/service/similarity_service.py

@@ -0,0 +1,20 @@
+from ..model.schemas import RequestSadaguSimilarity
+
+def select_product_by_similarity(request: RequestSadaguSimilarity) -> dict:
+    """
+    BERT 기반 유사도 분석 후 상품 선택
+    """
+    keyword = request.keyword
+    candidates = request.matched_products
+
+    # 유사도 분석 로직 적용 해야함
+    selected = candidates[0] if candidates else None
+
+    return {
+        "job_id": request.job_id,
+        "schedule_id": request.schedule_id,
+        "keyword": keyword,
+        "selected_product": selected,
+        "reason": "샘플 로직: 첫 번째 매칭 선택",
+        "status": "success"
+    }