From a329f5a3667b35610b51db438c5c3cd460dbd55a Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 26 May 2025 20:49:48 +0900 Subject: [PATCH 01/39] =?UTF-8?q?=E2=9C=A8feat:=20Elasticsearch=20?= =?UTF-8?q?=EB=B0=8F=20Kibana=20=EC=84=9C=EB=B9=84=EC=8A=A4=20=EC=B6=94?= =?UTF-8?q?=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docker-compose.dev.yml | 28 ++++++++++++++++++++++++++++ docker-compose.test.yml | 27 +++++++++++++++++++++++++++ docker-compose.yml | 27 +++++++++++++++++++++++++++ 3 files changed, 82 insertions(+) diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml index a01aa3f..177931f 100644 --- a/docker-compose.dev.yml +++ b/docker-compose.dev.yml @@ -22,6 +22,7 @@ services: - ./app:/app depends_on: - db + - elasticsearch # <-- Elasticsearch 먼저 기동되도록 추가 networks: - default @@ -39,6 +40,33 @@ services: networks: - default + elasticsearch: + image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + container_name: elasticsearch + environment: + - discovery.type=single-node + - xpack.security.enabled=false + - ES_JAVA_OPTS=-Xms512m -Xmx512m # 메모리 조정 + ports: + - '9200:9200' + volumes: + - esdata:/usr/share/elasticsearch/data + networks: + - default + + kibana: + image: docker.elastic.co/kibana/kibana:7.17.0 + container_name: kibana + ports: + - '5601:5601' + environment: + - ELASTICSEARCH_HOSTS=http://elasticsearch:9200 + networks: + - default + +volumes: + esdata: + networks: default: driver: bridge diff --git a/docker-compose.test.yml b/docker-compose.test.yml index b80837c..7c1210e 100644 --- a/docker-compose.test.yml +++ b/docker-compose.test.yml @@ -22,6 +22,7 @@ services: - ./app:/app depends_on: - db + - elasticsearch # <-- Elasticsearch 먼저 기동되도록 추가 networks: - default @@ -39,6 +40,32 @@ services: networks: - default + elasticsearch: + image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + container_name: elasticsearch + environment: + - discovery.type=single-node + - xpack.security.enabled=false + - ES_JAVA_OPTS=-Xms512m -Xmx512m # 메모리 조정 + ports: + - '9200:9200' + volumes: + - esdata:/usr/share/elasticsearch/data + networks: + - default + + kibana: + image: docker.elastic.co/kibana/kibana:7.17.0 + container_name: kibana + ports: + - '5601:5601' + environment: + - ELASTICSEARCH_HOSTS=http://elasticsearch:9200 + networks: + - default + +volumes: + esdata: networks: default: diff --git a/docker-compose.yml b/docker-compose.yml index 508c22b..6e41ffb 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -22,6 +22,7 @@ services: - ./app:/app depends_on: - db + - elasticsearch # <-- Elasticsearch 먼저 기동되도록 추가 networks: - default @@ -39,6 +40,32 @@ services: networks: - default + elasticsearch: + image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + container_name: elasticsearch + environment: + - discovery.type=single-node + - xpack.security.enabled=false + - ES_JAVA_OPTS=-Xms512m -Xmx512m # 메모리 조정 + ports: + - '9200:9200' + volumes: + - esdata:/usr/share/elasticsearch/data + networks: + - default + + kibana: + image: docker.elastic.co/kibana/kibana:7.17.0 + container_name: kibana + ports: + - '5601:5601' + environment: + - ELASTICSEARCH_HOSTS=http://elasticsearch:9200 + networks: + - default + +volumes: + esdata: networks: default: From e85c32408d8be17873e5b0b88b2a909317268074 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 26 May 2025 21:04:53 +0900 Subject: [PATCH 02/39] =?UTF-8?q?=F0=9F=94=84refactor:=20README.md=20?= =?UTF-8?q?=ED=8C=8C=EC=9D=BC=20=EA=B5=AC=EC=A1=B0=20=EB=B0=8F=20=EB=82=B4?= =?UTF-8?q?=EC=9A=A9=20=EC=97=85=EB=8D=B0=EC=9D=B4=ED=8A=B8?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 78 +++++++++++++++++++++++++++++++++++++++++-------------- 1 file changed, 58 insertions(+), 20 deletions(-) diff --git a/README.md b/README.md index e40aebd..ceca13a 100644 --- a/README.md +++ b/README.md @@ -21,17 +21,48 @@ FastAPI와 MySQL을 사용한 카카오톡 챗봇 개발을 위한 템플릿 프 ``` ├── app/ -│ ├── scripts/ -│ │ └── core/ -│ │ └── endpoints.py +│ ├── core/ +│ │ └── __init__.py +│ ├── models/ +│ │ ├── __init__.py +│ │ ├── base.py +│ │ ├── category.py +│ │ ├── employee_category.py +│ │ ├── employeee_hire_type.py +│ │ ├── employee.py +│ │ ├── feature.py +│ │ ├── hire_type.py +│ │ ├── news.py +│ │ ├── user_category.py +│ │ └── users.py +│ ├── routers/ +│ │ ├── employee.py +│ │ ├── feature.py +│ │ ├── news.py +│ │ └── user.py │ ├── utils/ -│ │ ├── response_builder.py -│ │ └── text_utils.py -│ └── main.py +│ │ ├── __init__.py +│ │ ├── db_manager.py +│ │ ├── init_default_data.py +│ │ ├── insert_employee_data.py +│ │ ├── news_client.py +│ │ ├── news_provider_mapping.py +│ │ └── verifier.py +│ ├── dev.Dockerfile +│ ├── Dockerfile +│ ├── main.py +│ └── test.Dockerfile ├── tests/ │ └── unit/ │ ├── routers/ -│ │ └── test_kakao_router.py +│ ├── test_add_employee_data.py +│ ├── test_add_user_favorit.py +│ ├── test_employee_recommendation.py +│ ├── test_get_categories_by_feature.py +│ ├── test_get_my_category_list.py +│ ├── test_get_news_recommendations.py +│ ├── test_news_client.py +│ │── test_user_delete_favorite.py │ └── utils/ │ ├── response_builder/ │ │ └── test_response_builder.py @@ -63,18 +94,21 @@ FastAPI와 MySQL을 사용한 카카오톡 챗봇 개발을 위한 템플릿 프 ### 설치 및 실행 1. 저장소 클론 + ```bash git clone cd kakaotalk-chatbot-template ``` 2. 환경 변수 설정 + ```bash cp .env.example .env # .env 파일을 열어 필요한 설정 수정 ``` 3. Docker 컨테이너 실행 + ```bash docker-compose up --build ``` @@ -91,11 +125,13 @@ docker-compose up --build ### 의존성 관리 새로운 패키지 추가: + ```bash poetry add ``` 개발 의존성 추가: + ```bash poetry add --group dev ``` @@ -103,6 +139,7 @@ poetry add --group dev ### 테스트 테스트 실행: + ```bash # Docker 컨테이너 내부에서 실행 docker-compose exec app poetry run pytest @@ -114,6 +151,7 @@ docker-compose exec app poetry run pytest --cov=app --cov-report=term-missing ### 코드 품질 린팅 및 포맷팅: + ```bash # Ruff를 사용한 린팅 poetry run ruff check . @@ -134,19 +172,19 @@ poetry run black . ## 환경 변수 -| 변수명 | 설명 | 기본값 | -|--------|------|---------| -| APP_NAME | 애플리케이션 이름 | kakaotalk-chatbot | -| ENVIRONMENT | 실행 환경 | development | -| DEBUG | 디버그 모드 | True | -| HOST | 서버 호스트 | 0.0.0.0 | -| PORT | 서버 포트 | 8000 | -| DB_HOST | 데이터베이스 호스트 | db | -| DB_PORT | 데이터베이스 포트 | 3306 | -| DB_NAME | 데이터베이스 이름 | chatbot | -| DB_USER | 데이터베이스 사용자 | user | -| DB_PASSWORD | 데이터베이스 비밀번호 | password | -| SECRET_KEY | 보안 키 | your-secret-key-here | +| 변수명 | 설명 | 기본값 | +| ----------- | --------------------- | -------------------- | +| APP_NAME | 애플리케이션 이름 | kakaotalk-chatbot | +| ENVIRONMENT | 실행 환경 | development | +| DEBUG | 디버그 모드 | True | +| HOST | 서버 호스트 | 0.0.0.0 | +| PORT | 서버 포트 | 8000 | +| DB_HOST | 데이터베이스 호스트 | db | +| DB_PORT | 데이터베이스 포트 | 3306 | +| DB_NAME | 데이터베이스 이름 | chatbot | +| DB_USER | 데이터베이스 사용자 | user | +| DB_PASSWORD | 데이터베이스 비밀번호 | password | +| SECRET_KEY | 보안 키 | your-secret-key-here | ## 기여하기 From dc413d1efe053a6bba2d552c5269da1d05367e41 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 26 May 2025 21:10:49 +0900 Subject: [PATCH 03/39] =?UTF-8?q?=E2=9C=A8feat:=20Elasticsearch=20?= =?UTF-8?q?=EC=B9=B4=ED=85=8C=EA=B3=A0=EB=A6=AC=20=EC=9D=B8=EB=8D=B1?= =?UTF-8?q?=EC=8A=A4=20=EC=83=9D=EC=84=B1=20=EB=B0=8F=20employee=20DB=20?= =?UTF-8?q?=EA=B2=80=EC=83=89=20API=20=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 61 ++++++++++++++++++++++++++++++++++++- app/utils/init_es_index.py | 62 ++++++++++++++++++++++++++++++++++++++ 2 files changed, 122 insertions(+), 1 deletion(-) create mode 100644 app/utils/init_es_index.py diff --git a/app/routers/employee.py b/app/routers/employee.py index d139512..220929f 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -7,13 +7,15 @@ from fastapi import APIRouter, Depends, HTTPException, Query from sqlalchemy.orm import Session - +from elasticsearch import Elasticsearch from app.models import Employee, EmployeeCategory, UserCategory, Users from app.utils.db_manager import db_manager router = APIRouter() db_dependency = Depends(db_manager.get_db) # 전역 변수로 설정 +router = APIRouter() +es = Elasticsearch("http://localhost:9200") @router.get("/recommend") def get_recruit_recommendations( @@ -80,3 +82,60 @@ def get_recruit_recommendations( "results": jobs, "message": message } + +@router.get("/employee/search") +def search_employees( + user_id: str = Query(...), + q: str = Query(...), + limit: int = Query(10, ge=1, le=100), + db: Session = Depends(db_manager.get_db) +): + user = db.query(Users).filter(Users.user_id == user_id).first() + if not user: + raise HTTPException(status_code=404, detail="User not found") + + es_result = es.search( + index="categories", + body={ + "size": 1, + "query": { + "match": { + "category_name": { + "query": q, + "fuzziness": "AUTO" + } + } + } + } + ) + + hits = es_result.get("hits", {}).get("hits", []) + if not hits: + raise HTTPException(status_code=404, detail="No matching category found") + + matched_category = hits[0]["_source"]["category_name"] + category_id = hits[0]["_source"]["category_id"] + + jobs = ( + db.query(Employee) + .filter(Employee.category_id == category_id) + .order_by(Employee.start_date.desc()) + .limit(limit) + .all() + ) + + results = [ + { + "title": job.title, + "organization": job.organization, + "start_date": job.start_date, + "end_date": job.end_date, + "url": job.url + } + for job in jobs + ] + + return { + "matched_category": matched_category, + "results": results + } \ No newline at end of file diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py new file mode 100644 index 0000000..7e3b9d5 --- /dev/null +++ b/app/utils/init_es_index.py @@ -0,0 +1,62 @@ +from elasticsearch import Elasticsearch + +es = Elasticsearch("http://localhost:9200") + +CATEGORIES = [ + {"category_id": 1, "category_name": "IT/과학", "feature": "news"}, + {"category_id": 2, "category_name": "마케팅", "feature": "news"}, + {"category_id": 3, "category_name": "디자인", "feature": "news"}, + {"category_id": 4, "category_name": "경영/기획", "feature": "news"}, + {"category_id": 5, "category_name": "영업/제휴", "feature": "news"}, + {"category_id": 6, "category_name": "정치", "feature": "news"}, + {"category_id": 7, "category_name": "경제", "feature": "news"}, + {"category_id": 8, "category_name": "사회", "feature": "news"}, + {"category_id": 9, "category_name": "생활/문화", "feature": "news"}, + {"category_id": 10, "category_name": "세계", "feature": "news"}, + + {"category_id": 11, "category_name": "사업관리", "feature": "employee"}, + {"category_id": 12, "category_name": "경영·회계·사무", "feature": "employee"}, + {"category_id": 13, "category_name": "금융·보험", "feature": "employee"}, + {"category_id": 14, "category_name": "교육·자연·사회과학", "feature": "employee"}, + {"category_id": 15, "category_name": "법률·경찰·소방·교도·국방", "feature": "employee"}, + {"category_id": 16, "category_name": "보건·의료", "feature": "employee"}, + {"category_id": 17, "category_name": "사회복지·종교", "feature": "employee"}, + {"category_id": 18, "category_name": "문화·예술·디자인·방송", "feature": "employee"}, + {"category_id": 19, "category_name": "운전·운송", "feature": "employee"}, + {"category_id": 20, "category_name": "영업판매", "feature": "employee"}, + {"category_id": 21, "category_name": "경비·청소", "feature": "employee"}, + {"category_id": 22, "category_name": "이용·숙박·여행·오락·스포츠", "feature": "employee"}, + {"category_id": 23, "category_name": "음식서비스", "feature": "employee"}, + {"category_id": 24, "category_name": "건설", "feature": "employee"}, + {"category_id": 25, "category_name": "기계", "feature": "employee"}, + {"category_id": 26, "category_name": "재료", "feature": "employee"}, + {"category_id": 27, "category_name": "화학", "feature": "employee"}, + {"category_id": 28, "category_name": "섬유·의복", "feature": "employee"}, + {"category_id": 29, "category_name": "전기·전자", "feature": "employee"}, + {"category_id": 30, "category_name": "정보통신", "feature": "employee"}, + {"category_id": 31, "category_name": "식품가공", "feature": "employee"}, + {"category_id": 32, "category_name": "인쇄·목재·가구·공예", "feature": "employee"}, + {"category_id": 33, "category_name": "환경·에너지·안전", "feature": "employee"}, + {"category_id": 34, "category_name": "농림어업", "feature": "employee"}, + {"category_id": 35, "category_name": "연구", "feature": "employee"}, +] + +def create_category_index(): + if es.indices.exists(index="categories"): + es.indices.delete(index="categories") + + es.indices.create(index="categories", body={ + "mappings": { + "properties": { + "category_id": {"type": "integer"}, + "category_name": {"type": "text"}, + "feature": {"type": "keyword"} + } + } + }) + + for cat in CATEGORIES: + es.index(index="categories", document=cat) + +if __name__ == "__main__": + create_category_index() \ No newline at end of file From 1c21c687c2ee196fabe138876105b6c928ffa194 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 26 May 2025 21:12:49 +0900 Subject: [PATCH 04/39] =?UTF-8?q?=E2=9C=A8feat:=20DB=5Fsearch=20=EC=97=94?= =?UTF-8?q?=EB=93=9C=ED=8F=AC=EC=9D=B8=ED=8A=B8=20=EC=B6=94=EA=B0=80=20?= =?UTF-8?q?=EB=B0=8F=20=EA=B2=80=EC=83=89=20=EA=B8=B0=EB=8A=A5=20=EC=84=A4?= =?UTF-8?q?=EB=AA=85=20=EC=97=85=EB=8D=B0=EC=9D=B4=ED=8A=B8?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 26 ++++++++++++++++++++++---- 1 file changed, 22 insertions(+), 4 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 220929f..5100c0b 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -83,13 +83,31 @@ def get_recruit_recommendations( "message": message } -@router.get("/employee/search") +@router.get("/DB_search") def search_employees( - user_id: str = Query(...), - q: str = Query(...), - limit: int = Query(10, ge=1, le=100), + user_id: str = Query(..., description="사용자 ID"), + q: str = Query(..., description="검색할 카테고리 키워드 (예: '정보통신', '디자인')"), + limit: int = Query(10, ge=1, le=100, description="검색 결과 최대 개수 (기본값: 10, 최대: 100)"), db: Session = Depends(db_manager.get_db) ): + """ + 사용자가 입력한 키워드를 기반으로 가장 유사한 카테고리를 찾고, 해당 카테고리에 속한 채용 공고를 반환합니다. + + Args: + user_id (str): 검색을 수행할 사용자 ID. + q (str): 검색 키워드 (카테고리명). + limit (int): 반환할 채용 공고 수 (기본값: 10, 최대 100). + db (Session): 데이터베이스 세션 객체. + + Returns: + dict: 매칭된 카테고리명과 해당 카테고리에 속한 채용 공고 목록. + - matched_category (str): 검색 키워드와 가장 유사한 카테고리명. + - results (List[dict]): 채용공고 목록 (제목, 기관, 시작일, 종료일, 상세 URL 포함). + + Raises: + HTTPException 404: 사용자가 존재하지 않는 경우. + HTTPException 404: 키워드와 일치하는 카테고리를 찾을 수 없는 경우. + """ user = db.query(Users).filter(Users.user_id == user_id).first() if not user: raise HTTPException(status_code=404, detail="User not found") From 365c6dbb45606e8918c822456665a1079a480816 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 00:48:29 +0900 Subject: [PATCH 05/39] =?UTF-8?q?=E2=9C=A8feat:=20Elasticsearch=EB=A5=BC?= =?UTF-8?q?=20=EC=9D=B4=EC=9A=A9=ED=95=9C=20=EC=B9=B4=ED=85=8C=EA=B3=A0?= =?UTF-8?q?=EB=A6=AC=20=EA=B2=80=EC=83=89=20=EA=B8=B0=EB=8A=A5=20=EC=B6=94?= =?UTF-8?q?=EA=B0=80=20=EB=B0=8F=20=EA=B2=80=EC=83=89=20=EA=B2=B0=EA=B3=BC?= =?UTF-8?q?=20=EC=B2=98=EB=A6=AC=20=EA=B0=9C=EC=84=A0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 16 ++++++++++++---- 1 file changed, 12 insertions(+), 4 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 5100c0b..d7db22f 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -108,40 +108,47 @@ def search_employees( HTTPException 404: 사용자가 존재하지 않는 경우. HTTPException 404: 키워드와 일치하는 카테고리를 찾을 수 없는 경우. """ + + # ✅ 1. 사용자 존재 여부 확인 user = db.query(Users).filter(Users.user_id == user_id).first() if not user: raise HTTPException(status_code=404, detail="User not found") + # ✅ 2. Elasticsearch를 이용해 유사한 카테고리 검색 (fuzzy match) es_result = es.search( - index="categories", + index="categories", # 검색할 인덱스명 body={ - "size": 1, + "size": 1, # 가장 유사한 하나의 결과만 추출 "query": { "match": { "category_name": { "query": q, - "fuzziness": "AUTO" + "fuzziness": "AUTO" # 철자 오류 등 유사어 허용 } } } } ) + # ✅ 3. 검색 결과가 없으면 예외 처리 hits = es_result.get("hits", {}).get("hits", []) if not hits: raise HTTPException(status_code=404, detail="No matching category found") + # ✅ 4. 검색 결과에서 카테고리명과 ID 추출 matched_category = hits[0]["_source"]["category_name"] category_id = hits[0]["_source"]["category_id"] + # ✅ 5. 해당 카테고리에 속한 채용 공고를 최신순으로 조회 jobs = ( db.query(Employee) .filter(Employee.category_id == category_id) - .order_by(Employee.start_date.desc()) + .order_by(Employee.start_date.desc()) # 시작일 기준 최신순 정렬 .limit(limit) .all() ) + # ✅ 6. 결과를 JSON 형태로 정리 results = [ { "title": job.title, @@ -153,6 +160,7 @@ def search_employees( for job in jobs ] + # ✅ 7. 최종 응답 반환 return { "matched_category": matched_category, "results": results From 56df63b4074b6358b9dc8c8ea032d6de2a746b75 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 01:21:29 +0900 Subject: [PATCH 06/39] =?UTF-8?q?=E2=9C=A8feat:=20certifi=20=EB=B0=8F=20el?= =?UTF-8?q?asticsearch=20=ED=8C=A8=ED=82=A4=EC=A7=80=20=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- poetry.lock | 53 +++++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 1 + 2 files changed, 53 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 4cf1e77..3f7ef6c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -79,6 +79,18 @@ d = ["aiohttp (>=3.10)"] jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] uvloop = ["uvloop (>=0.15.2)"] +[[package]] +name = "certifi" +version = "2025.4.26" +description = "Python package for providing Mozilla's CA Bundle." +optional = false +python-versions = ">=3.6" +groups = ["main"] +files = [ + {file = "certifi-2025.4.26-py3-none-any.whl", hash = "sha256:30350364dfe371162649852c63336a15c70c6510c2ad5015b21c2345311805f3"}, + {file = "certifi-2025.4.26.tar.gz", hash = "sha256:0a816057ea3cdefcef70270d2c515e4506bbc954f417fa5ade2021213bb8f0c6"}, +] + [[package]] name = "click" version = "8.1.8" @@ -204,6 +216,28 @@ idna = ["idna (>=3.7)"] trio = ["trio (>=0.23)"] wmi = ["wmi (>=1.5.1)"] +[[package]] +name = "elasticsearch" +version = "7.17.12" +description = "Python client for Elasticsearch" +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,<4,>=2.7" +groups = ["main"] +files = [ + {file = "elasticsearch-7.17.12-py2.py3-none-any.whl", hash = "sha256:468fd5eef703c0d9238e29bcaf3a6fe4d6b092f917959fbf41f48f8fea3df2f8"}, + {file = "elasticsearch-7.17.12.tar.gz", hash = "sha256:a1f5733ae8cf1dbf0a78593389f2503c87dd97429976099832bf0626cdfaac8b"}, +] + +[package.dependencies] +certifi = "*" +urllib3 = ">=1.21.1,<2" + +[package.extras] +async = ["aiohttp (>=3,<4)"] +develop = ["black", "coverage", "jinja2", "mock", "pytest", "pytest-cov", "pyyaml", "requests (>=2.0.0,<3.0.0)", "sphinx (<1.7)", "sphinx-rtd-theme"] +docs = ["sphinx (<1.7)", "sphinx-rtd-theme"] +requests = ["requests (>=2.4.0,<3.0.0)"] + [[package]] name = "email-validator" version = "2.2.0" @@ -1022,6 +1056,23 @@ files = [ {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"}, ] +[[package]] +name = "urllib3" +version = "1.26.20" +description = "HTTP library with thread-safe connection pooling, file post, and more." +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" +groups = ["main"] +files = [ + {file = "urllib3-1.26.20-py2.py3-none-any.whl", hash = "sha256:0ed14ccfbf1c30a9072c7ca157e4319b70d65f623e91e7b32fadb2853431016e"}, + {file = "urllib3-1.26.20.tar.gz", hash = "sha256:40c2dc0c681e47eb8f90e7e27bf6ff7df2e677421fd46756da1161c39ca70d32"}, +] + +[package.extras] +brotli = ["brotli (==1.0.9) ; os_name != \"nt\" and python_version < \"3\" and platform_python_implementation == \"CPython\"", "brotli (>=1.0.9) ; python_version >= \"3\" and platform_python_implementation == \"CPython\"", "brotlicffi (>=0.8.0) ; (os_name != \"nt\" or python_version >= \"3\") and platform_python_implementation != \"CPython\"", "brotlipy (>=0.6.0) ; os_name == \"nt\" and python_version < \"3\""] +secure = ["certifi", "cryptography (>=1.3.4)", "idna (>=2.0.0)", "ipaddress ; python_version == \"2.7\"", "pyOpenSSL (>=0.14)", "urllib3-secure-extra"] +socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] + [[package]] name = "uvicorn" version = "0.27.1" @@ -1267,4 +1318,4 @@ files = [ [metadata] lock-version = "2.1" python-versions = "^3.11" -content-hash = "0a6195972baaad0f217546eaefa0830ba82f96eb2c10268506219f21398e2657" +content-hash = "4dbc61215b7b8c5acc80e3e40db13db4756d372597f013b41b23250b1edcc665" diff --git a/pyproject.toml b/pyproject.toml index ebdf8bd..2803639 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,6 +17,7 @@ pytest = "^8.3.5" pytest-cov = "^6.0.0" psycopg = "^3.2.6" ruff = "^0.11.4" +elasticsearch = "^7.17.0" [tool.poetry.group.dev.dependencies] ruff = "^0.11.2" From bd393fb284a8840dcbb0982f0923807a8763e40e Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 16:25:18 +0900 Subject: [PATCH 07/39] =?UTF-8?q?=E2=9C=A8feat:=20Elasticsearch=20?= =?UTF-8?q?=EC=97=B0=EA=B2=B0=EC=9D=84=20=ED=99=98=EA=B2=BD=20=EB=B3=80?= =?UTF-8?q?=EC=88=98=EB=A1=9C=20=EC=84=A4=EC=A0=95=ED=95=98=EA=B3=A0=20?= =?UTF-8?q?=EC=B9=B4=ED=85=8C=EA=B3=A0=EB=A6=AC=20=EC=83=89=EC=9D=B8=20?= =?UTF-8?q?=EC=83=9D=EC=84=B1=20=EC=8B=9C=20=EB=B6=84=EC=84=9D=EA=B8=B0=20?= =?UTF-8?q?=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 49 ++++++++++++++++++++++---------------- app/utils/init_es_index.py | 34 ++++++++++++++++++++++---- 2 files changed, 57 insertions(+), 26 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index d7db22f..c45331c 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -8,6 +8,7 @@ from fastapi import APIRouter, Depends, HTTPException, Query from sqlalchemy.orm import Session from elasticsearch import Elasticsearch +import os from app.models import Employee, EmployeeCategory, UserCategory, Users from app.utils.db_manager import db_manager @@ -15,7 +16,7 @@ db_dependency = Depends(db_manager.get_db) # 전역 변수로 설정 router = APIRouter() -es = Elasticsearch("http://localhost:9200") +es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) @router.get("/recommend") def get_recruit_recommendations( @@ -114,23 +115,28 @@ def search_employees( if not user: raise HTTPException(status_code=404, detail="User not found") - # ✅ 2. Elasticsearch를 이용해 유사한 카테고리 검색 (fuzzy match) - es_result = es.search( - index="categories", # 검색할 인덱스명 - body={ - "size": 1, # 가장 유사한 하나의 결과만 추출 - "query": { - "match": { - "category_name": { - "query": q, - "fuzziness": "AUTO" # 철자 오류 등 유사어 허용 + # ✅ 2. Elasticsearch 유사 카테고리 검색 + try: + es_result = es.search( + index="categories", + body={ + "size": 1, + "query": { + "match": { + "category_name": { + "query": q, + "fuzziness": "AUTO" + } } } } - } - ) + ) + except ConnectionError: + raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) - # ✅ 3. 검색 결과가 없으면 예외 처리 + # ✅ 3. 검색 결과 확인 hits = es_result.get("hits", {}).get("hits", []) if not hits: raise HTTPException(status_code=404, detail="No matching category found") @@ -142,8 +148,9 @@ def search_employees( # ✅ 5. 해당 카테고리에 속한 채용 공고를 최신순으로 조회 jobs = ( db.query(Employee) - .filter(Employee.category_id == category_id) - .order_by(Employee.start_date.desc()) # 시작일 기준 최신순 정렬 + .join(EmployeeCategory, Employee.recruit_id == EmployeeCategory.recruit_id) + .filter(EmployeeCategory.category_id == category_id) + .order_by(Employee.start_date.desc()) .limit(limit) .all() ) @@ -151,11 +158,11 @@ def search_employees( # ✅ 6. 결과를 JSON 형태로 정리 results = [ { - "title": job.title, - "organization": job.organization, - "start_date": job.start_date, - "end_date": job.end_date, - "url": job.url + "title": job.title, + "organization": job.institution, + "start_date": job.start_date.isoformat(), # date → 문자열 (ISO 포맷) + "end_date": job.end_date.isoformat(), + "url": job.detail_url } for job in jobs ] diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index 7e3b9d5..967e852 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -13,7 +13,6 @@ {"category_id": 8, "category_name": "사회", "feature": "news"}, {"category_id": 9, "category_name": "생활/문화", "feature": "news"}, {"category_id": 10, "category_name": "세계", "feature": "news"}, - {"category_id": 11, "category_name": "사업관리", "feature": "employee"}, {"category_id": 12, "category_name": "경영·회계·사무", "feature": "employee"}, {"category_id": 13, "category_name": "금융·보험", "feature": "employee"}, @@ -45,18 +44,43 @@ def create_category_index(): if es.indices.exists(index="categories"): es.indices.delete(index="categories") - es.indices.create(index="categories", body={ + index_body = { + "settings": { + "analysis": { + "tokenizer": { + "edge_ngram_tokenizer": { + "type": "edge_ngram", + "min_gram": 2, + "max_gram": 10, + "token_chars": ["letter", "digit"] + } + }, + "analyzer": { + "autocomplete": { + "type": "custom", + "tokenizer": "edge_ngram_tokenizer", + "filter": ["lowercase"] + } + } + } + }, "mappings": { "properties": { "category_id": {"type": "integer"}, - "category_name": {"type": "text"}, + "category_name": { + "type": "text", + "analyzer": "autocomplete", # 색인 시 edge_ngram 기반 분석 + "search_analyzer": "standard" # 검색 시 표준 분석기 사용 + }, "feature": {"type": "keyword"} } } - }) + } + + es.indices.create(index="categories", body=index_body) for cat in CATEGORIES: es.index(index="categories", document=cat) if __name__ == "__main__": - create_category_index() \ No newline at end of file + create_category_index() From 709eebaf73f62d4ee4d9893be186612de3bc8a28 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 16:34:02 +0900 Subject: [PATCH 08/39] =?UTF-8?q?=E2=9C=A8feat:=20DB=5Fsearch=20=EC=97=94?= =?UTF-8?q?=EB=93=9C=ED=8F=AC=EC=9D=B8=ED=8A=B8=EC=9D=98=20=EA=B2=80?= =?UTF-8?q?=EC=83=89=20=ED=8C=8C=EB=9D=BC=EB=AF=B8=ED=84=B0=20=EC=9D=B4?= =?UTF-8?q?=EB=A6=84=20=EC=88=98=EC=A0=95=20=EB=B0=8F=20=EA=B2=80=EC=83=89?= =?UTF-8?q?=20=EA=B2=B0=EA=B3=BC=20=EC=B2=98=EB=A6=AC=20=EA=B0=9C=EC=84=A0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 16 +++++++++++----- 1 file changed, 11 insertions(+), 5 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index c45331c..a1d29f5 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -87,7 +87,7 @@ def get_recruit_recommendations( @router.get("/DB_search") def search_employees( user_id: str = Query(..., description="사용자 ID"), - q: str = Query(..., description="검색할 카테고리 키워드 (예: '정보통신', '디자인')"), + keyword: str = Query(..., description="검색할 카테고리 키워드 (예: '정보통신', '디자인')"), limit: int = Query(10, ge=1, le=100, description="검색 결과 최대 개수 (기본값: 10, 최대: 100)"), db: Session = Depends(db_manager.get_db) ): @@ -122,9 +122,9 @@ def search_employees( body={ "size": 1, "query": { - "match": { + "match_phrase_prefix": { "category_name": { - "query": q, + "query": keyword, "fuzziness": "AUTO" } } @@ -138,8 +138,14 @@ def search_employees( # ✅ 3. 검색 결과 확인 hits = es_result.get("hits", {}).get("hits", []) - if not hits: - raise HTTPException(status_code=404, detail="No matching category found") + if hits: + matched_source = hits[0]["_source"] + matched_category = matched_source["category_name"] + category_id = matched_source["category_id"] + else: + # 기본 카테고리 설정 (예: category_id=0, 기타) + matched_category = "기타" + category_id = 0 # ✅ 4. 검색 결과에서 카테고리명과 ID 추출 matched_category = hits[0]["_source"]["category_name"] From c8953cc1fd96d6859253f9f23d1f7c297a994f2a Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 17:05:37 +0900 Subject: [PATCH 09/39] =?UTF-8?q?=E2=9C=A8feat:=20=EA=B2=80=EC=83=89=20?= =?UTF-8?q?=EA=B2=B0=EA=B3=BC=20=EC=B2=98=EB=A6=AC=20=EB=A1=9C=EC=A7=81=20?= =?UTF-8?q?=EA=B0=9C=EC=84=A0=20=EB=B0=8F=20=EA=B8=B0=EB=B3=B8=20=EC=B9=B4?= =?UTF-8?q?=ED=85=8C=EA=B3=A0=EB=A6=AC=20=EC=84=A4=EC=A0=95=20=EC=B6=94?= =?UTF-8?q?=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 22 ++++++++-------------- 1 file changed, 8 insertions(+), 14 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index a1d29f5..e1613b4 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -124,8 +124,7 @@ def search_employees( "query": { "match_phrase_prefix": { "category_name": { - "query": keyword, - "fuzziness": "AUTO" + "query": keyword } } } @@ -138,20 +137,15 @@ def search_employees( # ✅ 3. 검색 결과 확인 hits = es_result.get("hits", {}).get("hits", []) - if hits: + if not hits: + matched_category = "기타" + category_id = 0 + else: matched_source = hits[0]["_source"] matched_category = matched_source["category_name"] category_id = matched_source["category_id"] - else: - # 기본 카테고리 설정 (예: category_id=0, 기타) - matched_category = "기타" - category_id = 0 - - # ✅ 4. 검색 결과에서 카테고리명과 ID 추출 - matched_category = hits[0]["_source"]["category_name"] - category_id = hits[0]["_source"]["category_id"] - # ✅ 5. 해당 카테고리에 속한 채용 공고를 최신순으로 조회 + # ✅ 4. 해당 카테고리에 속한 채용 공고를 최신순으로 조회 jobs = ( db.query(Employee) .join(EmployeeCategory, Employee.recruit_id == EmployeeCategory.recruit_id) @@ -161,7 +155,7 @@ def search_employees( .all() ) - # ✅ 6. 결과를 JSON 형태로 정리 + # ✅ 5. 결과를 JSON 형태로 정리 results = [ { "title": job.title, @@ -173,7 +167,7 @@ def search_employees( for job in jobs ] - # ✅ 7. 최종 응답 반환 + # ✅ 6. 최종 응답 반환 return { "matched_category": matched_category, "results": results From 295394d843a19b709275c6a0d632276225426813 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 17:08:02 +0900 Subject: [PATCH 10/39] =?UTF-8?q?=E2=9C=A8feat:=20=EA=B2=80=EC=83=89=20?= =?UTF-8?q?=EA=B2=B0=EA=B3=BC=EA=B0=80=20=EC=97=86=EC=9D=84=20=EA=B2=BD?= =?UTF-8?q?=EC=9A=B0=20=EA=B8=B0=EB=B3=B8=20=EC=B9=B4=ED=85=8C=EA=B3=A0?= =?UTF-8?q?=EB=A6=AC=20=EC=84=A4=EC=A0=95=20=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index e1613b4..a4e6b3b 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -137,13 +137,14 @@ def search_employees( # ✅ 3. 검색 결과 확인 hits = es_result.get("hits", {}).get("hits", []) - if not hits: - matched_category = "기타" - category_id = 0 - else: + if hits: matched_source = hits[0]["_source"] matched_category = matched_source["category_name"] category_id = matched_source["category_id"] + else: + # 기본 카테고리 설정 (예: category_id=0, 기타) + matched_category = "기타" + category_id = 0 # ✅ 4. 해당 카테고리에 속한 채용 공고를 최신순으로 조회 jobs = ( From f7e1ee5795203379b36aff9502929b09025a81e0 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 17:11:28 +0900 Subject: [PATCH 11/39] =?UTF-8?q?=E2=9C=A8feat:=20=EA=B2=80=EC=83=89=20?= =?UTF-8?q?=EA=B8=B0=EB=8A=A5=EC=97=90=20'employee'=20=EC=B9=B4=ED=85=8C?= =?UTF-8?q?=EA=B3=A0=EB=A6=AC=20=ED=95=84=ED=84=B0=20=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 15 ++++++++++++--- 1 file changed, 12 insertions(+), 3 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index a4e6b3b..5ef0c05 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -122,9 +122,18 @@ def search_employees( body={ "size": 1, "query": { - "match_phrase_prefix": { - "category_name": { - "query": keyword + "bool": { + "must": { + "match_phrase_prefix": { + "category_name": { + "query": keyword + } + } + }, + "filter": { + "term": { + "feature": "employee" # ✅ 'employee' 기능 카테고리만 필터링 + } } } } From 174844e4b9d20b1eb1d90b1d1147959f8291ae60 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 19:57:47 +0900 Subject: [PATCH 12/39] =?UTF-8?q?=E2=9C=A8fix:=20=EA=B2=80=EC=83=89=20?= =?UTF-8?q?=EA=B2=B0=EA=B3=BC=EC=97=90=EC=84=9C=20'organization'=20?= =?UTF-8?q?=ED=95=84=EB=93=9C=EB=A5=BC=20'institution'=EC=9C=BC=EB=A1=9C?= =?UTF-8?q?=20=EC=88=98=EC=A0=95=20test=ED=8C=8C=EC=9D=BC=20=EC=B6=94?= =?UTF-8?q?=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 2 +- tests/unit/routers/test_employee_DB_search.py | 289 ++++++++++++++++++ 2 files changed, 290 insertions(+), 1 deletion(-) create mode 100644 tests/unit/routers/test_employee_DB_search.py diff --git a/app/routers/employee.py b/app/routers/employee.py index 5ef0c05..1263d53 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -169,7 +169,7 @@ def search_employees( results = [ { "title": job.title, - "organization": job.institution, + "institution": job.institution, "start_date": job.start_date.isoformat(), # date → 문자열 (ISO 포맷) "end_date": job.end_date.isoformat(), "url": job.detail_url diff --git a/tests/unit/routers/test_employee_DB_search.py b/tests/unit/routers/test_employee_DB_search.py new file mode 100644 index 0000000..81e4f6c --- /dev/null +++ b/tests/unit/routers/test_employee_DB_search.py @@ -0,0 +1,289 @@ +""" +사용자 맞춤 카테고리 기반 채용 공고 검색 API 테스트 모듈. + +이 모듈은 /DB_search 엔드포인트의 기능을 테스트합니다. + +주요 테스트 항목: + - 정상적인 키워드 검색 및 채용 공고 반환 + - 존재하지 않는 사용자 처리 + - Elasticsearch에서 카테고리 미검색 시 기본 카테고리 처리 + - 해당 카테고리에 채용 공고가 없을 경우 처리 + - limit 파라미터 동작 확인 (최대 개수 제한 등) +""" + +import datetime +import pytest +from fastapi.testclient import TestClient +from sqlalchemy import create_engine +from sqlalchemy.orm import sessionmaker +from sqlalchemy.sql import text +from unittest.mock import patch + +from app.main import app +from app.models import ( + Base, + Category, + Employee, + EmployeeCategory, + Feature, + Users, +) +from app.utils import db_manager + +# 테스트용 SQLite DB 설정 +TEST_DATABASE_URL = "sqlite:///./test.db" +engine = create_engine(TEST_DATABASE_URL, connect_args={"check_same_thread": False}) +TestingSessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) + +# DB 초기화 및 테이블 생성 +@pytest.fixture(scope="function") +def setup_database(): + """ + 테스트용 데이터베이스를 초기화하고, 모든 테이블을 생성합니다. + + 이 fixture는 테스트 함수 실행 전 매번 호출되어 데이터베이스를 깨끗한 상태로 초기화합니다. + 외래 키 제약 조건을 활성화하고, 기존 테이블은 모두 삭제 후 다시 생성합니다. + + Returns: + None + """ + with engine.connect() as conn: + conn.execute(text("PRAGMA foreign_keys = ON;")) # 외래 키 활성화 + Base.metadata.drop_all(bind=conn) # 기존 테이블 삭제 + Base.metadata.create_all(bind=conn) # 테이블 생성 + +# 테스트 DB 세션 생성 및 테스트 데이터 삽입 +@pytest.fixture(scope="function") +def test_db(setup_database): + """ + 테스트용 DB 세션을 생성하고 초기 데이터를 삽입합니다. + + setup_database fixture를 사용하여 DB를 초기화한 후, 테스트에 필요한 + 사용자, 기능, 카테고리, 채용 공고 등의 기본 데이터를 삽입합니다. + + 테스트 종료 시 세션을 롤백하고 종료하며, 모든 테이블을 삭제합니다. + + Yields: + Session: 테스트용 SQLAlchemy DB 세션 + """ + db = TestingSessionLocal() + # 기존 데이터 삭제 + db.query(EmployeeCategory).delete() + db.query(Employee).delete() + db.query(Category).delete() + db.query(Feature).delete() + db.query(Users).delete() + db.commit() + + # 테스트 데이터 삽입 + user = Users(user_id="user123", user_name="홍길동") + feature = Feature(feature_type="employee") + db.add_all([user, feature]) + db.commit() + db.refresh(user) + db.refresh(feature) + + category = Category(feature_id=feature.id, category_name="정보통신") + db.add(category) + db.commit() + db.refresh(category) + + job = Employee( + recruit_id=1, + title="정보통신 개발자", + institution="TechCorp", + start_date=datetime.date(2025, 5, 1), + end_date=datetime.date(2025, 5, 31), + recrut_se="R2010", + detail_url="https://example.com/job1", + recrut_pblnt_sn=123456, + ) + db.add(job) + db.commit() + db.refresh(job) + + emp_cat = EmployeeCategory(recruit_id=job.recruit_id, category_id=category.id) + db.add(emp_cat) + db.commit() + + yield db + + db.rollback() + db.close() + Base.metadata.drop_all(bind=engine) + +def override_get_db(): + """ + FastAPI 의존성 오버라이드용 함수. + + 테스트용 DB 세션을 생성하여 반환하며, + 사용 후 세션을 안전하게 종료합니다. + + Yields: + Session: 테스트용 SQLAlchemy DB 세션 + """ + db = TestingSessionLocal() + try: + yield db + finally: + db.close() + +app.dependency_overrides[db_manager.get_db] = override_get_db + +@pytest.fixture(scope="function") +def client(): + """ + FastAPI 테스트 클라이언트를 생성하여 반환합니다. + + Returns: + TestClient: FastAPI 테스트 클라이언트 인스턴스 + """ + return TestClient(app) + +# 🔹 정상 검색 테스트 +@patch("app.routers.your_router.es.search") # es.search 함수 패치 (실제 ES 호출 방지) +def test_search_employees_success(mock_es_search, client, test_db): + """ + Elasticsearch에서 정상적으로 카테고리 검색 결과를 받아 + 관련 채용 공고가 올바르게 반환되는지 검증하는 테스트입니다. + """ + # Elasticsearch가 "정보통신" 카테고리 검색 결과 반환 모킹 + mock_es_search.return_value = { + "hits": { + "hits": [ + { + "_source": { + "category_name": "정보통신", + "category_id": 1, + "feature": "employee" + } + } + ] + } + } + + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 5}) + assert response.status_code == 200 + + data = response.json() + assert data["matched_category"] == "정보통신" + assert isinstance(data["results"], list) + assert len(data["results"]) == 1 + assert data["results"][0]["title"] == "정보통신 개발자" + assert data["results"][0]["institution"] == "TechCorp" + +# 🔹 사용자 미존재 테스트 +def test_search_employees_user_not_found(client): + """ + 존재하지 않는 사용자 ID로 검색 요청 시 + 404 에러 및 'User not found' 메시지가 반환되는지 확인합니다. + """ + response = client.get("/DB_search", params={"user_id": "unknown", "keyword": "정보통신"}) + assert response.status_code == 404 + assert response.json() == {"detail": "User not found"} + +# 🔹 Elasticsearch에서 카테고리 미검색 시 기본값 처리 테스트 +@patch("app.routers.your_router.es.search") +def test_search_employees_no_category_found(mock_es_search, client, test_db): + """ + Elasticsearch에서 키워드에 해당하는 카테고리가 검색되지 않을 때 + 기본값 '기타' 카테고리로 처리되고 빈 결과가 반환되는지 검증합니다. + """ + mock_es_search.return_value = {"hits": {"hits": []}} # 검색 결과 없음 + + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "없는카테고리"}) + assert response.status_code == 200 + data = response.json() + assert data["matched_category"] == "기타" + assert isinstance(data["results"], list) + assert len(data["results"]) == 0 # 기본 category_id=0 이므로 관련 공고 없음 + +# 🔹 해당 카테고리에 채용 공고가 없을 경우 +@patch("app.routers.your_router.es.search") +def test_search_employees_no_jobs_in_category(mock_es_search, client, test_db): + """ + 검색된 카테고리는 존재하나 해당 카테고리에 등록된 채용 공고가 없을 때 + 빈 결과 리스트가 반환되는지 확인하는 테스트입니다. + """ + # 검색된 카테고리 ID를 존재하나, 해당 카테고리에 공고 없음 + mock_es_search.return_value = { + "hits": { + "hits": [ + { + "_source": { + "category_name": "정보통신", + "category_id": 9999, # 존재하지 않는 카테고리ID + "feature": "employee" + } + } + ] + } + } + + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + assert response.status_code == 200 + data = response.json() + assert data["matched_category"] == "정보통신" + assert isinstance(data["results"], list) + assert len(data["results"]) == 0 + +# 🔹 limit 파라미터 테스트 (최대 100, 기본 10 등) +@patch("app.routers.your_router.es.search") +def test_search_employees_limit_param(mock_es_search, client, test_db): + """ + 검색 시 limit 파라미터의 기본값, 지정값, 최대값 초과 시 + 각각 올바르게 처리되는지 검증합니다. + - 기본 limit 사용 + - limit 지정 사용 + - 최대값(100) 초과 시 422 에러 발생 확인 + """ + mock_es_search.return_value = { + "hits": { + "hits": [ + { + "_source": { + "category_name": "정보통신", + "category_id": 1, + "feature": "employee" + } + } + ] + } + } + + # 기본 limit=10 + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + assert response.status_code == 200 + + # limit=1 지정 + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 1}) + assert response.status_code == 200 + data = response.json() + assert len(data["results"]) <= 1 + + # limit가 최대 100 초과 시도 (FastAPI에서 자동 검증되어 422 에러가 발생할 것) + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 101}) + assert response.status_code == 422 # 유효성 검증 실패 + + +# 🔹 Elasticsearch 연결 실패 예외 테스트 +@patch("app.routers.your_router.es.search", side_effect=ConnectionError) +def test_search_employees_es_connection_error(mock_es_search, client, test_db): + """ + Elasticsearch 연결 실패 시 + 500 에러와 'Elasticsearch 연결 실패' 메시지가 반환되는지 확인합니다. + """ + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + assert response.status_code == 500 + assert response.json() == {"detail": "Elasticsearch 연결 실패"} + +# 🔹 Elasticsearch 기타 예외 테스트 +@patch("app.routers.your_router.es.search", side_effect=Exception("ES 오류")) +def test_search_employees_es_other_error(mock_es_search, client, test_db): + """ + Elasticsearch 검색 중 알 수 없는 예외 발생 시 + 500 에러와 예외 메시지가 포함된 응답이 반환되는지 검증합니다. + """ + response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + assert response.status_code == 500 + assert "ES 오류" in response.json()["detail"] From b61219b2c5d43d2f3ca09c74f523d523e531d3d1 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 22:05:49 +0900 Subject: [PATCH 13/39] =?UTF-8?q?=E2=9C=A8refactor:=20=EC=A4=91=EB=B3=B5?= =?UTF-8?q?=EB=90=9C=20APIRouter=20=EC=9D=B8=EC=8A=A4=ED=84=B4=EC=8A=A4=20?= =?UTF-8?q?=EC=A0=9C=EA=B1=B0=20=EB=B0=8F=20DB=5Fsearch=20=EC=97=94?= =?UTF-8?q?=EB=93=9C=ED=8F=AC=EC=9D=B8=ED=8A=B8=20=EA=B2=BD=EB=A1=9C=20?= =?UTF-8?q?=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 2 - app/utils/init_default_data.py | 3 + tests/unit/routers/test_employee_DB_search.py | 108 ++++++++++++------ 3 files changed, 75 insertions(+), 38 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 1263d53..007a7cb 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -14,8 +14,6 @@ router = APIRouter() db_dependency = Depends(db_manager.get_db) # 전역 변수로 설정 - -router = APIRouter() es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) @router.get("/recommend") diff --git a/app/utils/init_default_data.py b/app/utils/init_default_data.py index cbbe546..64ff8bb 100644 --- a/app/utils/init_default_data.py +++ b/app/utils/init_default_data.py @@ -70,6 +70,9 @@ def add_default_categories(db): Category(category_name="환경·에너지·안전", feature=feature_employee), Category(category_name="농림어업", feature=feature_employee), Category(category_name="연구", feature=feature_employee), + + + Category(category_id = 0, category_name="연구", feature=feature_employee), ] for category in categories: diff --git a/tests/unit/routers/test_employee_DB_search.py b/tests/unit/routers/test_employee_DB_search.py index 81e4f6c..5fcd7b1 100644 --- a/tests/unit/routers/test_employee_DB_search.py +++ b/tests/unit/routers/test_employee_DB_search.py @@ -27,8 +27,10 @@ EmployeeCategory, Feature, Users, + HireType, + EmployeeHireType, ) -from app.utils import db_manager +from app.utils.db_manager import db_manager # 테스트용 SQLite DB 설정 TEST_DATABASE_URL = "sqlite:///./test.db" @@ -67,9 +69,8 @@ def test_db(setup_database): Session: 테스트용 SQLAlchemy DB 세션 """ db = TestingSessionLocal() + # 기존 데이터 삭제 - db.query(EmployeeCategory).delete() - db.query(Employee).delete() db.query(Category).delete() db.query(Feature).delete() db.query(Users).delete() @@ -80,37 +81,72 @@ def test_db(setup_database): feature = Feature(feature_type="employee") db.add_all([user, feature]) db.commit() + db.refresh(user) db.refresh(feature) - category = Category(feature_id=feature.id, category_name="정보통신") + category = Category(feature_id=1, category_name="정보통신") db.add(category) db.commit() db.refresh(category) - job = Employee( + hire_type = HireType(hire_type_id=1, hire_type_name="정규직", hire_type_code="R1010") + db.add(hire_type) + db.commit() + db.refresh(hire_type) + + # 채용 공고 추가 + job1 = Employee( recruit_id=1, - title="정보통신 개발자", - institution="TechCorp", - start_date=datetime.date(2025, 5, 1), - end_date=datetime.date(2025, 5, 31), - recrut_se="R2010", - detail_url="https://example.com/job1", - recrut_pblnt_sn=123456, + title="정보통신 연구원", + institution="OpenAI", + start_date=datetime.date(2025, 4, 1), + end_date=datetime.date(2025, 4, 30), + recrut_se="R2030", # 신입 + 경력 + detail_url="https://example.com/openai", + recrut_pblnt_sn=280271, + ) + job2 = Employee( + recruit_id=2, + title="정보통신 엔지니어", + institution="Naver", + start_date=datetime.date(2025, 4, 5), + end_date=datetime.date(2025, 5, 5), + recrut_se="R2010", # 신입 + detail_url="https://example.com/naver", + recrut_pblnt_sn=280272, ) - db.add(job) + db.add_all([job1, job2]) db.commit() - db.refresh(job) - emp_cat = EmployeeCategory(recruit_id=job.recruit_id, category_id=category.id) - db.add(emp_cat) + employee_category1 = EmployeeCategory( + recruit_id=1, + category_id=1, # AI 카테고리 + ) + employee_category2 = EmployeeCategory( + recruit_id=2, + category_id=1, # AI 카테고리 + ) + db.add_all([employee_category1, employee_category2]) db.commit() - yield db + employee_hire_type1 = EmployeeHireType( + recruit_id=1, + hire_type_id=1, # 정규직 + ) + employee_hire_type2 = EmployeeHireType( + recruit_id=2, + hire_type_id=1, # 정규직 + ) + db.add_all([employee_hire_type1, employee_hire_type2]) + db.commit() - db.rollback() - db.close() - Base.metadata.drop_all(bind=engine) + yield db # 세션 제공 + + db.commit() + db.rollback() # 테스트 종료 후 변경 사항 되돌리기 + db.close() # 세션 종료 + Base.metadata.drop_all(bind=engine) # 테스트 끝나면 DB 초기화 def override_get_db(): """ @@ -141,7 +177,7 @@ def client(): return TestClient(app) # 🔹 정상 검색 테스트 -@patch("app.routers.your_router.es.search") # es.search 함수 패치 (실제 ES 호출 방지) +@patch("app.routers.employee.es.search") # es.search 함수 패치 (실제 ES 호출 방지) def test_search_employees_success(mock_es_search, client, test_db): """ Elasticsearch에서 정상적으로 카테고리 검색 결과를 받아 @@ -162,13 +198,13 @@ def test_search_employees_success(mock_es_search, client, test_db): } } - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 5}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 5}) assert response.status_code == 200 data = response.json() assert data["matched_category"] == "정보통신" assert isinstance(data["results"], list) - assert len(data["results"]) == 1 + assert len(data["results"]) == 2 assert data["results"][0]["title"] == "정보통신 개발자" assert data["results"][0]["institution"] == "TechCorp" @@ -178,12 +214,12 @@ def test_search_employees_user_not_found(client): 존재하지 않는 사용자 ID로 검색 요청 시 404 에러 및 'User not found' 메시지가 반환되는지 확인합니다. """ - response = client.get("/DB_search", params={"user_id": "unknown", "keyword": "정보통신"}) + response = client.get("/employee/DB_search", params={"user_id": "unknown", "keyword": "정보통신"}) assert response.status_code == 404 assert response.json() == {"detail": "User not found"} # 🔹 Elasticsearch에서 카테고리 미검색 시 기본값 처리 테스트 -@patch("app.routers.your_router.es.search") +@patch("app.routers.employee.es.search") def test_search_employees_no_category_found(mock_es_search, client, test_db): """ Elasticsearch에서 키워드에 해당하는 카테고리가 검색되지 않을 때 @@ -191,7 +227,7 @@ def test_search_employees_no_category_found(mock_es_search, client, test_db): """ mock_es_search.return_value = {"hits": {"hits": []}} # 검색 결과 없음 - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "없는카테고리"}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "없는카테고리"}) assert response.status_code == 200 data = response.json() assert data["matched_category"] == "기타" @@ -199,7 +235,7 @@ def test_search_employees_no_category_found(mock_es_search, client, test_db): assert len(data["results"]) == 0 # 기본 category_id=0 이므로 관련 공고 없음 # 🔹 해당 카테고리에 채용 공고가 없을 경우 -@patch("app.routers.your_router.es.search") +@patch("app.routers.employee.es.search") def test_search_employees_no_jobs_in_category(mock_es_search, client, test_db): """ 검색된 카테고리는 존재하나 해당 카테고리에 등록된 채용 공고가 없을 때 @@ -220,7 +256,7 @@ def test_search_employees_no_jobs_in_category(mock_es_search, client, test_db): } } - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) assert response.status_code == 200 data = response.json() assert data["matched_category"] == "정보통신" @@ -228,7 +264,7 @@ def test_search_employees_no_jobs_in_category(mock_es_search, client, test_db): assert len(data["results"]) == 0 # 🔹 limit 파라미터 테스트 (최대 100, 기본 10 등) -@patch("app.routers.your_router.es.search") +@patch("app.routers.employee.es.search") def test_search_employees_limit_param(mock_es_search, client, test_db): """ 검색 시 limit 파라미터의 기본값, 지정값, 최대값 초과 시 @@ -252,38 +288,38 @@ def test_search_employees_limit_param(mock_es_search, client, test_db): } # 기본 limit=10 - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) assert response.status_code == 200 # limit=1 지정 - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 1}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 1}) assert response.status_code == 200 data = response.json() assert len(data["results"]) <= 1 # limit가 최대 100 초과 시도 (FastAPI에서 자동 검증되어 422 에러가 발생할 것) - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 101}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "정보통신", "limit": 101}) assert response.status_code == 422 # 유효성 검증 실패 # 🔹 Elasticsearch 연결 실패 예외 테스트 -@patch("app.routers.your_router.es.search", side_effect=ConnectionError) +@patch("app.routers.employee.es.search", side_effect=ConnectionError) def test_search_employees_es_connection_error(mock_es_search, client, test_db): """ Elasticsearch 연결 실패 시 500 에러와 'Elasticsearch 연결 실패' 메시지가 반환되는지 확인합니다. """ - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) assert response.status_code == 500 assert response.json() == {"detail": "Elasticsearch 연결 실패"} # 🔹 Elasticsearch 기타 예외 테스트 -@patch("app.routers.your_router.es.search", side_effect=Exception("ES 오류")) +@patch("app.routers.employee.es.search", side_effect=Exception("ES 오류")) def test_search_employees_es_other_error(mock_es_search, client, test_db): """ Elasticsearch 검색 중 알 수 없는 예외 발생 시 500 에러와 예외 메시지가 포함된 응답이 반환되는지 검증합니다. """ - response = client.get("/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) + response = client.get("/employee/DB_search", params={"user_id": "user123", "keyword": "정보통신"}) assert response.status_code == 500 assert "ES 오류" in response.json()["detail"] From 57e927d470ca3b6b7e0a98421c49a049205c49c1 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Tue, 27 May 2025 22:06:05 +0900 Subject: [PATCH 14/39] =?UTF-8?q?=E2=9C=A8fix:=20=EC=B1=84=EC=9A=A9=20?= =?UTF-8?q?=EA=B3=B5=EA=B3=A0=20=EB=8D=B0=EC=9D=B4=ED=84=B0=20=EC=88=98?= =?UTF-8?q?=EC=A0=95=20=EB=B0=8F=20=EA=B2=80=EC=83=89=20=EA=B2=B0=EA=B3=BC?= =?UTF-8?q?=20=EC=88=98=20=EC=A1=B0=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- tests/unit/routers/test_employee_DB_search.py | 31 +++++++------------ 1 file changed, 11 insertions(+), 20 deletions(-) diff --git a/tests/unit/routers/test_employee_DB_search.py b/tests/unit/routers/test_employee_DB_search.py index 5fcd7b1..dba495f 100644 --- a/tests/unit/routers/test_employee_DB_search.py +++ b/tests/unit/routers/test_employee_DB_search.py @@ -96,28 +96,19 @@ def test_db(setup_database): db.refresh(hire_type) # 채용 공고 추가 - job1 = Employee( + job = Employee( recruit_id=1, - title="정보통신 연구원", - institution="OpenAI", - start_date=datetime.date(2025, 4, 1), - end_date=datetime.date(2025, 4, 30), - recrut_se="R2030", # 신입 + 경력 - detail_url="https://example.com/openai", - recrut_pblnt_sn=280271, + title="정보통신 개발자", + institution="TechCorp", + start_date=datetime.date(2025, 5, 1), + end_date=datetime.date(2025, 5, 31), + recrut_se="R2010", + detail_url="https://example.com/job1", + recrut_pblnt_sn=123456, ) - job2 = Employee( - recruit_id=2, - title="정보통신 엔지니어", - institution="Naver", - start_date=datetime.date(2025, 4, 5), - end_date=datetime.date(2025, 5, 5), - recrut_se="R2010", # 신입 - detail_url="https://example.com/naver", - recrut_pblnt_sn=280272, - ) - db.add_all([job1, job2]) + db.add(job) db.commit() + db.refresh(job) employee_category1 = EmployeeCategory( recruit_id=1, @@ -204,7 +195,7 @@ def test_search_employees_success(mock_es_search, client, test_db): data = response.json() assert data["matched_category"] == "정보통신" assert isinstance(data["results"], list) - assert len(data["results"]) == 2 + assert len(data["results"]) == 1 assert data["results"][0]["title"] == "정보통신 개발자" assert data["results"][0]["institution"] == "TechCorp" From 6afc5a5a7fc2ef30b874f880b4f56dfeedf17099 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Wed, 28 May 2025 19:30:03 +0900 Subject: [PATCH 15/39] =?UTF-8?q?=E2=9C=A8refactor:=20=ED=85=8C=EC=8A=A4?= =?UTF-8?q?=ED=8A=B8=20=EB=8D=B0=EC=9D=B4=ED=84=B0=20=EC=83=9D=EC=84=B1=20?= =?UTF-8?q?=EB=A1=9C=EC=A7=81=20=EA=B0=84=EC=86=8C=ED=99=94=20=EB=B0=8F=20?= =?UTF-8?q?=EC=82=AC=EC=9A=A9=EC=9E=90=20=EB=AF=B8=EC=A1=B4=EC=9E=AC=20?= =?UTF-8?q?=ED=85=8C=EC=8A=A4=ED=8A=B8=20=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- tests/unit/routers/test_employee_DB_search.py | 18 +++++------------- 1 file changed, 5 insertions(+), 13 deletions(-) diff --git a/tests/unit/routers/test_employee_DB_search.py b/tests/unit/routers/test_employee_DB_search.py index dba495f..55d727b 100644 --- a/tests/unit/routers/test_employee_DB_search.py +++ b/tests/unit/routers/test_employee_DB_search.py @@ -110,26 +110,18 @@ def test_db(setup_database): db.commit() db.refresh(job) - employee_category1 = EmployeeCategory( + employee_category = EmployeeCategory( recruit_id=1, category_id=1, # AI 카테고리 ) - employee_category2 = EmployeeCategory( - recruit_id=2, - category_id=1, # AI 카테고리 - ) - db.add_all([employee_category1, employee_category2]) + db.add(employee_category) db.commit() - employee_hire_type1 = EmployeeHireType( + employee_hire_type = EmployeeHireType( recruit_id=1, hire_type_id=1, # 정규직 ) - employee_hire_type2 = EmployeeHireType( - recruit_id=2, - hire_type_id=1, # 정규직 - ) - db.add_all([employee_hire_type1, employee_hire_type2]) + db.add(employee_hire_type) db.commit() yield db # 세션 제공 @@ -200,7 +192,7 @@ def test_search_employees_success(mock_es_search, client, test_db): assert data["results"][0]["institution"] == "TechCorp" # 🔹 사용자 미존재 테스트 -def test_search_employees_user_not_found(client): +def test_search_employees_user_not_found(client, setup_database): """ 존재하지 않는 사용자 ID로 검색 요청 시 404 에러 및 'User not found' 메시지가 반환되는지 확인합니다. From 167dc792a86b0162afd43c3107984da22570e9c5 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Wed, 28 May 2025 19:30:17 +0900 Subject: [PATCH 16/39] =?UTF-8?q?=E2=9C=A8feat:=20Elasticsearch=20?= =?UTF-8?q?=EC=B9=B4=ED=85=8C=EA=B3=A0=EB=A6=AC=20=EA=B2=80=EC=83=89=20?= =?UTF-8?q?=EA=B8=B0=EB=8A=A5=20=EA=B0=9C=EC=84=A0=20=EB=B0=8F=20=EC=9D=B8?= =?UTF-8?q?=EB=8D=B1=EC=8A=A4=20=EC=83=9D=EC=84=B1=20=EB=A1=9C=EC=A7=81=20?= =?UTF-8?q?=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 25 +++++++---- app/utils/init_es_index.py | 87 ++++++++++++++++++++++++-------------- 2 files changed, 71 insertions(+), 41 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 007a7cb..ea1042c 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -7,6 +7,7 @@ from fastapi import APIRouter, Depends, HTTPException, Query from sqlalchemy.orm import Session +from sentence_transformers import SentenceTransformer from elasticsearch import Elasticsearch import os from app.models import Employee, EmployeeCategory, UserCategory, Users @@ -15,6 +16,7 @@ router = APIRouter() db_dependency = Depends(db_manager.get_db) # 전역 변수로 설정 es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) +model = SentenceTransformer("all-MiniLM-L6-v2") @router.get("/recommend") def get_recruit_recommendations( @@ -115,22 +117,27 @@ def search_employees( # ✅ 2. Elasticsearch 유사 카테고리 검색 try: + embedding = model.encode(keyword).tolist() # 검색어 임베딩 벡터 생성 + es_result = es.search( - index="categories", + index="categories", # 벡터 임베딩이 저장된 Elasticsearch 인덱스 body={ "size": 1, "query": { - "bool": { - "must": { - "match_phrase_prefix": { - "category_name": { - "query": keyword + "script_score": { + "query": { + "bool": { + "filter": { + "term": { + "feature": "employee" # 'employee' 기능 카테고리만 필터링 + } } } }, - "filter": { - "term": { - "feature": "employee" # ✅ 'employee' 기능 카테고리만 필터링 + "script": { + "source": "cosineSimilarity(params.query_vector, 'category_vector') + 1.0", + "params": { + "query_vector": embedding } } } diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index 967e852..b761c00 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -1,7 +1,16 @@ +from sentence_transformers import SentenceTransformer from elasticsearch import Elasticsearch +# 모델 로드 (384차원 벡터 출력) +model = SentenceTransformer("all-MiniLM-L6-v2") + +# Elasticsearch 연결 es = Elasticsearch("http://localhost:9200") +# 인덱스명 +INDEX_NAME = "category_index" + +# 카테고리 목록 CATEGORIES = [ {"category_id": 1, "category_name": "IT/과학", "feature": "news"}, {"category_id": 2, "category_name": "마케팅", "feature": "news"}, @@ -41,46 +50,60 @@ ] def create_category_index(): - if es.indices.exists(index="categories"): - es.indices.delete(index="categories") + # 인덱스 존재 시 삭제 + if es.indices.exists(index=INDEX_NAME): + es.indices.delete(index=INDEX_NAME) - index_body = { - "settings": { - "analysis": { - "tokenizer": { - "edge_ngram_tokenizer": { - "type": "edge_ngram", - "min_gram": 2, - "max_gram": 10, - "token_chars": ["letter", "digit"] + # 인덱스 생성 + es.indices.create( + index=INDEX_NAME, + body={ + "settings": { + "analysis": { + "tokenizer": { + "edge_ngram_tokenizer": { + "type": "edge_ngram", + "min_gram": 1, + "max_gram": 20, + "token_chars": ["letter", "digit"] + } + }, + "analyzer": { + "edge_ngram_analyzer": { + "tokenizer": "edge_ngram_tokenizer", + "filter": ["lowercase"] + } } - }, - "analyzer": { - "autocomplete": { - "type": "custom", - "tokenizer": "edge_ngram_tokenizer", - "filter": ["lowercase"] + } + }, + "mappings": { + "properties": { + "category_id": {"type": "integer"}, + "feature": {"type": "keyword"}, + "category_name": { + "type": "text", + "analyzer": "edge_ngram_analyzer", + "search_analyzer": "standard" + }, + "category_vector": { + "type": "dense_vector", + "dims": 384, + "index": True, + "similarity": "cosine" } } } - }, - "mappings": { - "properties": { - "category_id": {"type": "integer"}, - "category_name": { - "type": "text", - "analyzer": "autocomplete", # 색인 시 edge_ngram 기반 분석 - "search_analyzer": "standard" # 검색 시 표준 분석기 사용 - }, - "feature": {"type": "keyword"} - } } - } - - es.indices.create(index="categories", body=index_body) + ) + # 색인 for cat in CATEGORIES: - es.index(index="categories", document=cat) + embedding = model.encode(cat["category_name"]).tolist() + doc = { + **cat, + "category_vector": embedding + } + es.index(index=INDEX_NAME, document=doc) if __name__ == "__main__": create_category_index() From 109c50cd6a994603ca6a117a7c45b55a93220bae Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Wed, 28 May 2025 20:02:46 +0900 Subject: [PATCH 17/39] Add sentence-transformers dependency to pyproject.toml --- poetry.lock | 1322 +++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 1 + 2 files changed, 1322 insertions(+), 1 deletion(-) diff --git a/poetry.lock b/poetry.lock index 3f7ef6c..a97c557 100644 --- a/poetry.lock +++ b/poetry.lock @@ -91,6 +91,108 @@ files = [ {file = "certifi-2025.4.26.tar.gz", hash = "sha256:0a816057ea3cdefcef70270d2c515e4506bbc954f417fa5ade2021213bb8f0c6"}, ] +[[package]] +name = "charset-normalizer" +version = "3.4.2" +description = "The Real First Universal Charset Detector. 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"triton-3.3.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fad99beafc860501d7fcc1fb7045d9496cbe2c882b1674640304949165a916e7"}, + {file = "triton-3.3.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:3161a2bf073d6b22c4e2f33f951f3e5e3001462b2570e6df9cd57565bdec2984"}, + {file = "triton-3.3.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b68c778f6c4218403a6bd01be7484f6dc9e20fe2083d22dd8aef33e3b87a10a3"}, + {file = "triton-3.3.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:47bc87ad66fa4ef17968299acacecaab71ce40a238890acc6ad197c3abe2b8f1"}, + {file = "triton-3.3.0-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ce4700fc14032af1e049005ae94ba908e71cd6c2df682239aed08e49bc71b742"}, + {file = "triton-3.3.0-cp39-cp39-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1f41403bfa0cbb3e24fd958ca7fee04e9681e55e539296db9aca30c42acae693"}, +] + +[package.dependencies] +setuptools = ">=40.8.0" + +[package.extras] +build = ["cmake (>=3.20)", "lit"] +tests = ["autopep8", "isort", "llnl-hatchet", "numpy", "pytest", "pytest-forked", "pytest-xdist", "scipy (>=1.7.1)"] +tutorials = ["matplotlib", "pandas", "tabulate"] + [[package]] name = "typing-extensions" version = "4.12.2" @@ -1318,4 +2638,4 @@ files = [ [metadata] lock-version = "2.1" python-versions = "^3.11" -content-hash = "4dbc61215b7b8c5acc80e3e40db13db4756d372597f013b41b23250b1edcc665" +content-hash = "5c8f7d17d1aede8dd1b9efaf4ac224fa99e31e9a0ba72a5ed5be1f97884311dc" diff --git a/pyproject.toml b/pyproject.toml index 2803639..b1eac41 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -18,6 +18,7 @@ pytest-cov = "^6.0.0" psycopg = "^3.2.6" ruff = "^0.11.4" elasticsearch = "^7.17.0" +sentence-transformers = "^2.2.2" [tool.poetry.group.dev.dependencies] ruff = "^0.11.2" From b411a501ecfec8352dec75c33e305a9f9e1c5315 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Wed, 28 May 2025 20:47:33 +0900 Subject: [PATCH 18/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EA=B2=80?= =?UTF-8?q?=EC=83=89=20=EC=BF=BC=EB=A6=AC=EC=9D=98=20=EC=9E=84=EB=B2=A0?= =?UTF-8?q?=EB=94=A9=20=ED=95=84=EB=93=9C=20=EC=9D=B4=EB=A6=84=20=EC=88=98?= =?UTF-8?q?=EC=A0=95=20=EB=B0=8F=20pyproject.toml=EC=97=90=EC=84=9C=20sent?= =?UTF-8?q?ence-transformers=20=EC=9D=98=EC=A1=B4=EC=84=B1=20=EC=88=98?= =?UTF-8?q?=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 9 ++++----- poetry.lock | 2 +- pyproject.toml | 2 +- 3 files changed, 6 insertions(+), 7 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index ea1042c..da80427 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -117,10 +117,9 @@ def search_employees( # ✅ 2. Elasticsearch 유사 카테고리 검색 try: - embedding = model.encode(keyword).tolist() # 검색어 임베딩 벡터 생성 - + embedding = model.encode(keyword).tolist() es_result = es.search( - index="categories", # 벡터 임베딩이 저장된 Elasticsearch 인덱스 + index="categories", body={ "size": 1, "query": { @@ -129,13 +128,13 @@ def search_employees( "bool": { "filter": { "term": { - "feature": "employee" # 'employee' 기능 카테고리만 필터링 + "feature": "employee" } } } }, "script": { - "source": "cosineSimilarity(params.query_vector, 'category_vector') + 1.0", + "source": "cosineSimilarity(params.query_vector, 'embedding') + 1.0", "params": { "query_vector": embedding } diff --git a/poetry.lock b/poetry.lock index a97c557..e7ead98 100644 --- a/poetry.lock +++ b/poetry.lock @@ -2638,4 +2638,4 @@ files = [ [metadata] lock-version = "2.1" python-versions = "^3.11" -content-hash = "5c8f7d17d1aede8dd1b9efaf4ac224fa99e31e9a0ba72a5ed5be1f97884311dc" +content-hash = "c1313a09f8f8f3d2bfecf7af0e2c31e8a7bf6e3f079c362c6be720240b6cf93d" diff --git a/pyproject.toml b/pyproject.toml index b1eac41..3ac1b37 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -18,7 +18,7 @@ pytest-cov = "^6.0.0" psycopg = "^3.2.6" ruff = "^0.11.4" elasticsearch = "^7.17.0" -sentence-transformers = "^2.2.2" +sentence-transformers = { version = "^2.2.2", extras = ["cpu"] } [tool.poetry.group.dev.dependencies] ruff = "^0.11.2" From a203e27b3e4cafba19c067d198774465336ebfb6 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Wed, 28 May 2025 21:57:53 +0900 Subject: [PATCH 19/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EB=B0=8F?= =?UTF-8?q?=20Kibana=20=EC=9D=B4=EB=AF=B8=EC=A7=80=20=EB=B2=84=EC=A0=84=20?= =?UTF-8?q?=EC=97=85=EB=8D=B0=EC=9D=B4=ED=8A=B8=20=EB=B0=8F=20=EA=B2=80?= =?UTF-8?q?=EC=83=89=20=EC=BF=BC=EB=A6=AC=EC=9D=98=20=EC=9E=84=EB=B2=A0?= =?UTF-8?q?=EB=94=A9=20=ED=95=84=EB=93=9C=20=EC=9D=B4=EB=A6=84=20=EC=88=98?= =?UTF-8?q?=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 2 +- docker-compose.dev.yml | 4 ++-- docker-compose.test.yml | 4 ++-- docker-compose.yml | 4 ++-- pyproject.toml | 2 +- 5 files changed, 8 insertions(+), 8 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index da80427..d684bf0 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -134,7 +134,7 @@ def search_employees( } }, "script": { - "source": "cosineSimilarity(params.query_vector, 'embedding') + 1.0", + "source": "cosineSimilarity(params.query_vector, 'category_vector') + 1.0", "params": { "query_vector": embedding } diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml index 177931f..c985aac 100644 --- a/docker-compose.dev.yml +++ b/docker-compose.dev.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:7.17.0 + image: docker.elastic.co/kibana/kibana:8.12.0 container_name: kibana ports: - '5601:5601' diff --git a/docker-compose.test.yml b/docker-compose.test.yml index 7c1210e..859e7ae 100644 --- a/docker-compose.test.yml +++ b/docker-compose.test.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:7.17.0 + image: docker.elastic.co/kibana/kibana:8.12.0 container_name: kibana ports: - '5601:5601' diff --git a/docker-compose.yml b/docker-compose.yml index 6e41ffb..10d953f 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:7.17.0 + image: docker.elastic.co/kibana/kibana:8.12.0 container_name: kibana ports: - '5601:5601' diff --git a/pyproject.toml b/pyproject.toml index 3ac1b37..fc2ca9f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,7 +17,7 @@ pytest = "^8.3.5" pytest-cov = "^6.0.0" psycopg = "^3.2.6" ruff = "^0.11.4" -elasticsearch = "^7.17.0" +elasticsearch = "^8.12.1" sentence-transformers = { version = "^2.2.2", extras = ["cpu"] } [tool.poetry.group.dev.dependencies] From 3e2fe68fd18830383846a38ac1448d57462a965a Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 02:18:49 +0900 Subject: [PATCH 20/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EA=B2=80?= =?UTF-8?q?=EC=83=89=20=EC=BF=BC=EB=A6=AC=EC=97=90=EC=84=9C=20=EB=B2=A1?= =?UTF-8?q?=ED=84=B0=20=EC=B0=A8=EC=9B=90=20=EB=B0=8F=20=EC=97=90=EB=9F=AC?= =?UTF-8?q?=20=EB=A1=9C=EA=B7=B8=20=EC=B6=9C=EB=A0=A5=20=EC=B6=94=EA=B0=80?= =?UTF-8?q?,=20=EC=9D=B8=EB=8D=B1=EC=8A=A4=20=EC=9D=B4=EB=A6=84=20?= =?UTF-8?q?=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 3 ++ app/utils/init_es_index.py | 2 +- poetry.lock | 70 ++++++++++++++++++++++++++++++++------ 3 files changed, 64 insertions(+), 11 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index d684bf0..2f99ec0 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -118,6 +118,7 @@ def search_employees( # ✅ 2. Elasticsearch 유사 카테고리 검색 try: embedding = model.encode(keyword).tolist() + print("쿼리 벡터 차원:", len(embedding)) # 384가 나와야 정상 es_result = es.search( index="categories", body={ @@ -146,6 +147,8 @@ def search_employees( except ConnectionError: raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") except Exception as e: + print("Elasticsearch 검색 중 에러 발생:", str(e)) # 로그 확인용 + print("상세 에러:", getattr(e, "info", None)) # 또는 e.body raise HTTPException(status_code=500, detail=str(e)) # ✅ 3. 검색 결과 확인 diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index b761c00..5842741 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -8,7 +8,7 @@ es = Elasticsearch("http://localhost:9200") # 인덱스명 -INDEX_NAME = "category_index" +INDEX_NAME = "categories" # 카테고리 목록 CATEGORIES = [ diff --git a/poetry.lock b/poetry.lock index e7ead98..13bd41a 100644 --- a/poetry.lock +++ b/poetry.lock @@ -318,27 +318,50 @@ idna = ["idna (>=3.7)"] trio = ["trio (>=0.23)"] wmi = ["wmi (>=1.5.1)"] +[[package]] +name = "elastic-transport" +version = "8.17.1" +description = "Transport classes and utilities shared among Python Elastic client libraries" +optional = false +python-versions = ">=3.8" +groups = ["main"] +files = [ + {file = "elastic_transport-8.17.1-py3-none-any.whl", hash = "sha256:192718f498f1d10c5e9aa8b9cf32aed405e469a7f0e9d6a8923431dbb2c59fb8"}, + {file = "elastic_transport-8.17.1.tar.gz", hash = "sha256:5edef32ac864dca8e2f0a613ef63491ee8d6b8cfb52881fa7313ba9290cac6d2"}, +] + +[package.dependencies] +certifi = "*" +urllib3 = ">=1.26.2,<3" + +[package.extras] +develop = ["aiohttp", "furo", "httpx", "opentelemetry-api", "opentelemetry-sdk", "orjson", "pytest", "pytest-asyncio", "pytest-cov", "pytest-httpserver", "pytest-mock", "requests", "respx", "sphinx (>2)", "sphinx-autodoc-typehints", "trustme"] + [[package]] name = "elasticsearch" -version = "7.17.12" +version = "8.18.1" description = "Python client for Elasticsearch" optional = false -python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,<4,>=2.7" +python-versions = ">=3.8" groups = ["main"] files = [ - {file = "elasticsearch-7.17.12-py2.py3-none-any.whl", hash = "sha256:468fd5eef703c0d9238e29bcaf3a6fe4d6b092f917959fbf41f48f8fea3df2f8"}, - {file = "elasticsearch-7.17.12.tar.gz", hash = "sha256:a1f5733ae8cf1dbf0a78593389f2503c87dd97429976099832bf0626cdfaac8b"}, + {file = "elasticsearch-8.18.1-py3-none-any.whl", hash = "sha256:1a8c8b5ec3ce5be88f96d2f898375671648e96272978bce0dee3137d9326aabb"}, + {file = "elasticsearch-8.18.1.tar.gz", hash = "sha256:998035f17a8c1fba7ae26b183dca797dcf95db86da6a7ecba56d31afc40f07c7"}, ] [package.dependencies] -certifi = "*" -urllib3 = ">=1.21.1,<2" +elastic-transport = ">=8.15.1,<9" +python-dateutil = "*" +typing-extensions = "*" [package.extras] async = ["aiohttp (>=3,<4)"] -develop = ["black", "coverage", "jinja2", "mock", "pytest", "pytest-cov", "pyyaml", "requests (>=2.0.0,<3.0.0)", "sphinx (<1.7)", "sphinx-rtd-theme"] -docs = ["sphinx (<1.7)", "sphinx-rtd-theme"] -requests = ["requests (>=2.4.0,<3.0.0)"] +dev = ["aiohttp", "black", "build", "coverage", "isort", "jinja2", "mapbox-vector-tile", "mypy", "nltk", "nox", "numpy", "orjson", "pandas", "pyarrow", "pyright", "pytest", "pytest-asyncio", "pytest-cov", "pytest-mock", "python-dateutil", "pyyaml (>=5.4)", "requests (>=2,<3)", "sentence-transformers", "simsimd", "tqdm", "twine", "types-python-dateutil", "types-tqdm", "unasync"] +docs = ["sphinx", "sphinx-autodoc-typehints", "sphinx-rtd-theme (>=2.0)"] +orjson = ["orjson (>=3)"] +pyarrow = ["pyarrow (>=1)"] +requests = ["requests (>=2.4.0,!=2.32.2,<3.0.0)"] +vectorstore-mmr = ["numpy (>=1)", "simsimd (>=3)"] [[package]] name = "email-validator" @@ -1545,6 +1568,21 @@ pytest = ">=4.6" [package.extras] testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"] +[[package]] +name = "python-dateutil" +version = "2.9.0.post0" +description = "Extensions to the standard Python datetime module" +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +groups = ["main"] +files = [ + {file = "python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3"}, + {file = "python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"}, +] + +[package.dependencies] +six = ">=1.5" + [[package]] name = "python-dotenv" version = "1.0.1" @@ -1981,6 +2019,18 @@ enabler = ["pytest-enabler (>=2.2)"] test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21) ; python_version >= \"3.9\" and sys_platform != \"cygwin\"", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf ; sys_platform != \"cygwin\"", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"] type = ["importlib_metadata (>=7.0.2) ; python_version < \"3.10\"", "jaraco.develop (>=7.21) ; sys_platform != \"cygwin\"", "mypy (==1.14.*)", "pytest-mypy"] +[[package]] +name = "six" +version = "1.17.0" +description = "Python 2 and 3 compatibility utilities" +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7" +groups = ["main"] +files = [ + {file = "six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274"}, + {file = "six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"}, +] + [[package]] name = "sniffio" version = "1.3.1" @@ -2638,4 +2688,4 @@ files = [ [metadata] lock-version = "2.1" python-versions = "^3.11" -content-hash = "c1313a09f8f8f3d2bfecf7af0e2c31e8a7bf6e3f079c362c6be720240b6cf93d" +content-hash = "634d5d189d834bab877cf5c42e199dd6bc1064fb7b36ae3a8e3e2c687f5a2284" From b6f850ca4d2bde25e885a0ad5ff96dbec000653f Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 03:17:03 +0900 Subject: [PATCH 21/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EA=B2=80?= =?UTF-8?q?=EC=83=89=20=EC=BF=BC=EB=A6=AC=EC=97=90=EC=84=9C=20=ED=95=84?= =?UTF-8?q?=ED=84=B0=20=EC=A1=B0=EA=B1=B4=EC=9D=84=20=EC=88=98=EC=A0=95?= =?UTF-8?q?=ED=95=98=EC=97=AC=20=EC=B9=B4=ED=85=8C=EA=B3=A0=EB=A6=AC=20?= =?UTF-8?q?=EB=B2=A1=ED=84=B0=20=EC=A1=B4=EC=9E=AC=20=EC=97=AC=EB=B6=80=20?= =?UTF-8?q?=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 9 ++++----- 1 file changed, 4 insertions(+), 5 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 2f99ec0..4517797 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -127,11 +127,10 @@ def search_employees( "script_score": { "query": { "bool": { - "filter": { - "term": { - "feature": "employee" - } - } + "filter": [ + {"exists": {"field": "category_vector"}}, + {"term": {"feature": "employee"}} + ] } }, "script": { From 41e4bedd95582f16e51446e5432a4a49c72d4144 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 13:42:23 +0900 Subject: [PATCH 22/39] =?UTF-8?q?=E2=9C=A8fix:=20=ED=99=98=EA=B2=BD?= =?UTF-8?q?=EB=B3=80=EC=88=98=20=EB=A1=9C=EB=94=A9=20=EB=B0=8F=20Hugging?= =?UTF-8?q?=20Face=20=EB=A1=9C=EA=B7=B8=EC=9D=B8=20=EC=B6=94=EA=B0=80,=20E?= =?UTF-8?q?lasticsearch=20=EC=9D=B8=EB=8D=B1=EC=8A=A4=20=EC=A1=B4=EC=9E=AC?= =?UTF-8?q?=20=EC=97=AC=EB=B6=80=20=EC=B2=B4=ED=81=AC=20=EA=B8=B0=EB=8A=A5?= =?UTF-8?q?=20=EA=B5=AC=ED=98=84?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 16 ++++- app/utils/init_es_index.py | 140 ++++++++++++++++++++++++++----------- 2 files changed, 114 insertions(+), 42 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 4517797..b93461c 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -8,16 +8,30 @@ from fastapi import APIRouter, Depends, HTTPException, Query from sqlalchemy.orm import Session from sentence_transformers import SentenceTransformer +from huggingface_hub import login from elasticsearch import Elasticsearch import os +from dotenv import load_dotenv from app.models import Employee, EmployeeCategory, UserCategory, Users from app.utils.db_manager import db_manager router = APIRouter() db_dependency = Depends(db_manager.get_db) # 전역 변수로 설정 -es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) + +# 환경변수 로딩 +load_dotenv() +hf_token = os.getenv("HUGGINGFACE_TOKEN") + +# Hugging Face 로그인 (모델 로딩 전) +if hf_token: + login(token=hf_token) + +# 모델 로드 (384차원 벡터 출력) model = SentenceTransformer("all-MiniLM-L6-v2") +# Elasticsearch 연결 +es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) + @router.get("/recommend") def get_recruit_recommendations( user_id: str = Query(..., description="추천을 받을 사용자 ID"), diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index 5842741..5731786 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -1,5 +1,17 @@ +import os +from dotenv import load_dotenv from sentence_transformers import SentenceTransformer +from huggingface_hub import login from elasticsearch import Elasticsearch +import requests # 추가 + +# 환경변수 로딩 +load_dotenv() +hf_token = os.getenv("HUGGINGFACE_TOKEN") + +# Hugging Face 로그인 (모델 로딩 전) +if hf_token: + login(token=hf_token) # 모델 로드 (384차원 벡터 출력) model = SentenceTransformer("all-MiniLM-L6-v2") @@ -10,7 +22,8 @@ # 인덱스명 INDEX_NAME = "categories" -# 카테고리 목록 +# 카테고리 목록 (생략) + CATEGORIES = [ {"category_id": 1, "category_name": "IT/과학", "feature": "news"}, {"category_id": 2, "category_name": "마케팅", "feature": "news"}, @@ -49,61 +62,106 @@ {"category_id": 35, "category_name": "연구", "feature": "employee"}, ] +def check_index_exists(index_name: str) -> bool: + """ + Elasticsearch에서 특정 인덱스가 존재하는지 여부를 확인한다. + + Args: + index_name (str): 확인할 Elasticsearch 인덱스명. + + Returns: + bool: 인덱스가 존재하면 True, 존재하지 않으면 False. + """ + url = f"http://localhost:9200/{index_name}" + try: + response = requests.head(url) + if response.status_code == 200: + return True + elif response.status_code == 404: + return False + else: + print(f"[⚠️] 인덱스 체크 예상치 못한 상태 코드: {response.status_code}, {response.text}") + return False + except Exception as e: + print(f"[❌] 인덱스 체크 실패: {e}") + return False + def create_category_index(): - # 인덱스 존재 시 삭제 - if es.indices.exists(index=INDEX_NAME): - es.indices.delete(index=INDEX_NAME) + """ + Elasticsearch에 'categories' 인덱스를 생성하고, + 카테고리 데이터를 384차원 임베딩 벡터와 함께 색인한다. + + 기존 인덱스가 존재할 경우 삭제 후 새로 생성한다. + + - edge_ngram tokenizer와 analyzer를 설정하여 + 카테고리명에 대해 부분검색이 가능하도록 한다. + - 'category_vector' 필드에는 SentenceTransformer로 생성한 벡터를 저장한다. + """ + # 기존 인덱스 삭제 (REST 호출로 존재 여부 체크) + if check_index_exists(INDEX_NAME): + try: + es.indices.delete(index=INDEX_NAME) + print(f"[ℹ️] 기존 인덱스 '{INDEX_NAME}' 삭제 완료") + except Exception as e: + print(f"[❌] 인덱스 삭제 실패: {e}") + return # 인덱스 생성 - es.indices.create( - index=INDEX_NAME, - body={ - "settings": { - "analysis": { - "tokenizer": { - "edge_ngram_tokenizer": { - "type": "edge_ngram", - "min_gram": 1, - "max_gram": 20, - "token_chars": ["letter", "digit"] - } - }, - "analyzer": { - "edge_ngram_analyzer": { - "tokenizer": "edge_ngram_tokenizer", - "filter": ["lowercase"] + try: + es.indices.create( + index=INDEX_NAME, + body={ + "settings": { + "analysis": { + "tokenizer": { + "edge_ngram_tokenizer": { + "type": "edge_ngram", + "min_gram": 1, + "max_gram": 20, + "token_chars": ["letter", "digit"] + } + }, + "analyzer": { + "edge_ngram_analyzer": { + "tokenizer": "edge_ngram_tokenizer", + "filter": ["lowercase"] + } } } - } - }, - "mappings": { - "properties": { - "category_id": {"type": "integer"}, - "feature": {"type": "keyword"}, - "category_name": { - "type": "text", - "analyzer": "edge_ngram_analyzer", - "search_analyzer": "standard" - }, - "category_vector": { - "type": "dense_vector", - "dims": 384, - "index": True, - "similarity": "cosine" + }, + "mappings": { + "properties": { + "category_id": {"type": "integer"}, + "feature": {"type": "keyword"}, + "category_name": { + "type": "text", + "analyzer": "edge_ngram_analyzer", + "search_analyzer": "standard" + }, + "category_vector": { + "type": "dense_vector", + "dims": 384 + } } } } - } - ) + ) + print(f"[✅] 인덱스 '{INDEX_NAME}' 생성 완료") + except Exception as e: + print("[❌] 인덱스 생성 실패:", e) + return - # 색인 + # 데이터 색인 for cat in CATEGORIES: embedding = model.encode(cat["category_name"]).tolist() doc = { **cat, "category_vector": embedding } - es.index(index=INDEX_NAME, document=doc) + try: + es.index(index=INDEX_NAME, document=doc) + except Exception as e: + print(f"[❌] 문서 색인 실패 (category_id={cat['category_id']}): {e}") if __name__ == "__main__": create_category_index() From b18f39ddf8a99406e353d000dabd4e5c7429a3ed Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 15:03:05 +0900 Subject: [PATCH 23/39] =?UTF-8?q?=E2=9C=A8fix:=20=EC=9C=A0=EC=82=AC?= =?UTF-8?q?=EB=8F=84=20=EA=B2=B0=EA=B3=BC=20=ED=95=84=ED=84=B0=EB=A7=81=20?= =?UTF-8?q?=EA=B8=B0=EB=8A=A5=20=EC=B6=94=EA=B0=80=20=EB=B0=8F=20=EA=B2=80?= =?UTF-8?q?=EC=83=89=20=EA=B2=B0=EA=B3=BC=20=EC=A0=95=EB=A0=AC=20=EA=B0=9C?= =?UTF-8?q?=EC=84=A0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 45 ++++++++++++++++++++++++++++++++++++----- 1 file changed, 40 insertions(+), 5 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index b93461c..ec9b5be 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -98,6 +98,24 @@ def get_recruit_recommendations( "message": message } +def filter_top_categories(similarity_results, min_score=0.6, top_n=5): + """ + 유사도 결과 필터링 + - min_score 이상 + - top_n 중 평균 이상 + """ + top_results = similarity_results[:top_n] + if not top_results: + return [] + + avg_score = sum([item["score"] for item in top_results]) / len(top_results) + + filtered = [ + item for item in top_results + if item["score"] >= min_score and item["score"] >= avg_score + ] + return filtered + @router.get("/DB_search") def search_employees( user_id: str = Query(..., description="사용자 ID"), @@ -136,7 +154,7 @@ def search_employees( es_result = es.search( index="categories", body={ - "size": 1, + "size": 10, "query": { "script_score": { "query": { @@ -167,11 +185,28 @@ def search_employees( # ✅ 3. 검색 결과 확인 hits = es_result.get("hits", {}).get("hits", []) if hits: - matched_source = hits[0]["_source"] - matched_category = matched_source["category_name"] - category_id = matched_source["category_id"] + hits_sorted = sorted( + hits, key=lambda x: x["_score"], reverse=True + ) + similarity_results = [ + { + "score": hit["_score"] - 1.0, + "category_id": hit["_source"]["category_id"], + "category_name": hit["_source"]["category_name"], + } + for hit in hits_sorted + ] + + filtered_results = filter_top_categories(similarity_results, min_score=0.6, top_n=5) + + if not filtered_results: + matched_category = "기타" + category_id = 0 + else: + best_match = filtered_results[0] + matched_category = best_match["category_name"] + category_id = best_match["category_id"] else: - # 기본 카테고리 설정 (예: category_id=0, 기타) matched_category = "기타" category_id = 0 From 80f8e13c73f5ae9c80be26e5f3e04899cc0bc554 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 15:38:58 +0900 Subject: [PATCH 24/39] =?UTF-8?q?=E2=9C=A8fix:=20Hugging=20Face=20?= =?UTF-8?q?=EB=AA=A8=EB=8D=B8=20=EB=A1=9C=EB=93=9C=20=EB=B0=8F=20=EC=9E=84?= =?UTF-8?q?=EB=B2=A0=EB=94=A9=20=EC=B0=A8=EC=9B=90=20=EC=9E=90=EB=8F=99=20?= =?UTF-8?q?=EC=B6=94=EC=A0=95=20=EA=B8=B0=EB=8A=A5=20=EC=B6=94=EA=B0=80,?= =?UTF-8?q?=20Elasticsearch=20=EC=9D=B8=EB=8D=B1=EC=8A=A4=20=EC=83=9D?= =?UTF-8?q?=EC=84=B1=20=EC=8B=9C=20=EC=B0=A8=EC=9B=90=20=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 10 +++++----- app/utils/init_es_index.py | 34 +++++++++++++++++----------------- 2 files changed, 22 insertions(+), 22 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index ec9b5be..b1fe7aa 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -26,8 +26,8 @@ if hf_token: login(token=hf_token) -# 모델 로드 (384차원 벡터 출력) -model = SentenceTransformer("all-MiniLM-L6-v2") +# 모델 로드 +model = SentenceTransformer("jhgan/ko-sroberta-multitask") # Elasticsearch 연결 es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) @@ -149,8 +149,8 @@ def search_employees( # ✅ 2. Elasticsearch 유사 카테고리 검색 try: - embedding = model.encode(keyword).tolist() - print("쿼리 벡터 차원:", len(embedding)) # 384가 나와야 정상 + embedding = model.encode(keyword, normalize_embeddings=True).tolist() + print("쿼리 벡터 차원:", len(embedding)) # 쿼리 벡터 차원 es_result = es.search( index="categories", body={ @@ -197,7 +197,7 @@ def search_employees( for hit in hits_sorted ] - filtered_results = filter_top_categories(similarity_results, min_score=0.6, top_n=5) + filtered_results = filter_top_categories(similarity_results, min_score=0.7, top_n=5) if not filtered_results: matched_category = "기타" diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index 5731786..9589a4a 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -3,18 +3,20 @@ from sentence_transformers import SentenceTransformer from huggingface_hub import login from elasticsearch import Elasticsearch -import requests # 추가 +import requests # 환경변수 로딩 load_dotenv() hf_token = os.getenv("HUGGINGFACE_TOKEN") -# Hugging Face 로그인 (모델 로딩 전) +# Hugging Face 로그인 if hf_token: login(token=hf_token) -# 모델 로드 (384차원 벡터 출력) -model = SentenceTransformer("all-MiniLM-L6-v2") +# ✅ 한국어 모델 로드 (임베딩 차원 자동 추정) +model = SentenceTransformer("jhgan/ko-sroberta-multitask") +embedding_dim = model.get_sentence_embedding_dimension() +print(f"[ℹ️] 임베딩 차원: {embedding_dim}") # Elasticsearch 연결 es = Elasticsearch("http://localhost:9200") @@ -22,8 +24,7 @@ # 인덱스명 INDEX_NAME = "categories" -# 카테고리 목록 (생략) - +# 카테고리 목록 CATEGORIES = [ {"category_id": 1, "category_name": "IT/과학", "feature": "news"}, {"category_id": 2, "category_name": "마케팅", "feature": "news"}, @@ -89,7 +90,7 @@ def check_index_exists(index_name: str) -> bool: def create_category_index(): """ Elasticsearch에 'categories' 인덱스를 생성하고, - 카테고리 데이터를 384차원 임베딩 벡터와 함께 색인한다. + 카테고리 데이터를 768차원 임베딩 벡터와 함께 색인한다. 기존 인덱스가 존재할 경우 삭제 후 새로 생성한다. @@ -140,7 +141,7 @@ def create_category_index(): }, "category_vector": { "type": "dense_vector", - "dims": 384 + "dims": embedding_dim # ✅ 자동 추정된 차원 사용 } } } @@ -148,20 +149,19 @@ def create_category_index(): ) print(f"[✅] 인덱스 '{INDEX_NAME}' 생성 완료") except Exception as e: - print("[❌] 인덱스 생성 실패:", e) + print(f"[❌] 인덱스 생성 실패: {e}") return - # 데이터 색인 for cat in CATEGORIES: - embedding = model.encode(cat["category_name"]).tolist() - doc = { - **cat, - "category_vector": embedding - } try: - es.index(index=INDEX_NAME, document=doc) + embedding = model.encode(cat["category_name"], normalize_embeddings=True).tolist() + doc = { + **cat, + "category_vector": embedding + } + es.index(index=INDEX_NAME, id=cat["category_id"], document=doc) # ✅ ID 지정 except Exception as e: print(f"[❌] 문서 색인 실패 (category_id={cat['category_id']}): {e}") if __name__ == "__main__": - create_category_index() + create_category_index() \ No newline at end of file From 3ae0e348d6f097a7a98ea3df8090d3b37c86fe53 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 16:18:53 +0900 Subject: [PATCH 25/39] =?UTF-8?q?=E2=9C=A8fix:=20=EC=BD=94=EB=93=9C=20?= =?UTF-8?q?=EC=A0=95=EB=A6=AC=20=EB=B0=8F=20=EC=9E=84=ED=8F=AC=ED=8A=B8=20?= =?UTF-8?q?=EC=88=9C=EC=84=9C=20=EC=88=98=EC=A0=95,=20=ED=85=8C=EC=8A=A4?= =?UTF-8?q?=ED=8A=B8=20=EB=AA=A8=EB=93=88=EC=97=90=EC=84=9C=20=EB=B6=88?= =?UTF-8?q?=ED=95=84=EC=9A=94=ED=95=9C=20=EC=9E=84=ED=8F=AC=ED=8A=B8=20?= =?UTF-8?q?=EC=A0=9C=EA=B1=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 20 ++++++++++--------- app/utils/init_es_index.py | 9 +++++---- tests/unit/routers/test_employee_DB_search.py | 7 ++++--- 3 files changed, 20 insertions(+), 16 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index b1fe7aa..3677626 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -5,13 +5,15 @@ """ -from fastapi import APIRouter, Depends, HTTPException, Query -from sqlalchemy.orm import Session -from sentence_transformers import SentenceTransformer -from huggingface_hub import login -from elasticsearch import Elasticsearch import os + from dotenv import load_dotenv +from elasticsearch import Elasticsearch +from fastapi import APIRouter, Depends, HTTPException, Query +from huggingface_hub import login +from sentence_transformers import SentenceTransformer +from sqlalchemy.orm import Session + from app.models import Employee, EmployeeCategory, UserCategory, Users from app.utils.db_manager import db_manager @@ -223,11 +225,11 @@ def search_employees( # ✅ 5. 결과를 JSON 형태로 정리 results = [ { - "title": job.title, - "institution": job.institution, + "title": job.title, + "institution": job.institution, "start_date": job.start_date.isoformat(), # date → 문자열 (ISO 포맷) "end_date": job.end_date.isoformat(), - "url": job.detail_url + "url": job.detail_url } for job in jobs ] @@ -236,4 +238,4 @@ def search_employees( return { "matched_category": matched_category, "results": results - } \ No newline at end of file + } diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index 9589a4a..a68d6bc 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -1,9 +1,10 @@ import os + +import requests from dotenv import load_dotenv -from sentence_transformers import SentenceTransformer -from huggingface_hub import login from elasticsearch import Elasticsearch -import requests +from huggingface_hub import login +from sentence_transformers import SentenceTransformer # 환경변수 로딩 load_dotenv() @@ -164,4 +165,4 @@ def create_category_index(): print(f"[❌] 문서 색인 실패 (category_id={cat['category_id']}): {e}") if __name__ == "__main__": - create_category_index() \ No newline at end of file + create_category_index() diff --git a/tests/unit/routers/test_employee_DB_search.py b/tests/unit/routers/test_employee_DB_search.py index 55d727b..daaabf7 100644 --- a/tests/unit/routers/test_employee_DB_search.py +++ b/tests/unit/routers/test_employee_DB_search.py @@ -12,12 +12,13 @@ """ import datetime +from unittest.mock import patch + import pytest from fastapi.testclient import TestClient from sqlalchemy import create_engine from sqlalchemy.orm import sessionmaker from sqlalchemy.sql import text -from unittest.mock import patch from app.main import app from app.models import ( @@ -25,10 +26,10 @@ Category, Employee, EmployeeCategory, + EmployeeHireType, Feature, - Users, HireType, - EmployeeHireType, + Users, ) from app.utils.db_manager import db_manager From 3c412ab0ff0182376f1f7fc7ff0ff8470c3f5f3f Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 16:22:35 +0900 Subject: [PATCH 26/39] =?UTF-8?q?=E2=9C=A8fix:=20=ED=99=98=EA=B2=BD?= =?UTF-8?q?=EB=B3=80=EC=88=98=20=EB=A1=9C=EB=94=A9=20=EB=B0=8F=20Hugging?= =?UTF-8?q?=20Face=20=EB=A1=9C=EA=B7=B8=EC=9D=B8=20=EB=A1=9C=EC=A7=81=20?= =?UTF-8?q?=EA=B0=9C=EC=84=A0,=20Elasticsearch=20=EC=97=B0=EA=B2=B0=20?= =?UTF-8?q?=EC=8B=9C=20=EC=9D=98=EC=A1=B4=EC=84=B1=20=EC=A0=95=EC=9D=98=20?= =?UTF-8?q?=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 3677626..e3d7ce4 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -24,6 +24,7 @@ load_dotenv() hf_token = os.getenv("HUGGINGFACE_TOKEN") + # Hugging Face 로그인 (모델 로딩 전) if hf_token: login(token=hf_token) @@ -34,6 +35,9 @@ # Elasticsearch 연결 es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) +# 모듈 레벨에서 의존성 정의 +get_db = Depends(db_manager.get_db) + @router.get("/recommend") def get_recruit_recommendations( user_id: str = Query(..., description="추천을 받을 사용자 ID"), @@ -123,7 +127,7 @@ def search_employees( user_id: str = Query(..., description="사용자 ID"), keyword: str = Query(..., description="검색할 카테고리 키워드 (예: '정보통신', '디자인')"), limit: int = Query(10, ge=1, le=100, description="검색 결과 최대 개수 (기본값: 10, 최대: 100)"), - db: Session = Depends(db_manager.get_db) + db: Session = get_db, ): """ 사용자가 입력한 키워드를 기반으로 가장 유사한 카테고리를 찾고, 해당 카테고리에 속한 채용 공고를 반환합니다. @@ -177,12 +181,13 @@ def search_employees( } } ) - except ConnectionError: - raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") + except ConnectionError as conn_err: + raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") from conn_err + except Exception as e: print("Elasticsearch 검색 중 에러 발생:", str(e)) # 로그 확인용 print("상세 에러:", getattr(e, "info", None)) # 또는 e.body - raise HTTPException(status_code=500, detail=str(e)) + raise HTTPException(status_code=500, detail=str(e)) from e # ✅ 3. 검색 결과 확인 hits = es_result.get("hits", {}).get("hits", []) From 47025261413116301ac3fd995bbdd663c6700c7d Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 16:31:50 +0900 Subject: [PATCH 27/39] =?UTF-8?q?=E2=9C=A8fix:=20=EC=B4=88=EA=B8=B0?= =?UTF-8?q?=ED=99=94=20=EC=8A=A4=ED=81=AC=EB=A6=BD=ED=8A=B8=20=EC=A3=BC?= =?UTF-8?q?=EC=84=9D=20=EC=B6=94=EA=B0=80=20=EB=B0=8F=20=EC=82=AC=EC=9A=A9?= =?UTF-8?q?=20=EB=B0=A9=EB=B2=95=20=EC=84=A4=EB=AA=85=20=EA=B0=9C=EC=84=A0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/utils/init_es_index.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index a68d6bc..fae1035 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -1,3 +1,19 @@ +""" +카테고리 정보를 Elasticsearch에 벡터 기반으로 색인하는 초기화 스크립트. + +이 스크립트는 다음과 같은 기능을 수행합니다: +1. Hugging Face에 로그인하여 한국어 SentenceTransformer 모델(jhgan/ko-sroberta-multitask)을 불러옵니다. +2. 카테고리명을 해당 모델로 임베딩(벡터화)하여 Elasticsearch의 'categories' 인덱스에 저장합니다. +3. 기존 인덱스가 존재할 경우 삭제 후 edge_ngram 분석기를 적용한 새 인덱스를 생성합니다. +4. 카테고리명으로 부분 검색이 가능하며, 유사 카테고리 검색을 위한 dense_vector 필드를 포함합니다. + +사용 전제 조건: +- .env 파일에 HUGGINGFACE_TOKEN이 포함되어 있어야 함 +- Elasticsearch 서버가 localhost:9200에서 실행 중이어야 함 + +실행 방법: +$ python init_es_index.py +""" import os import requests From 8b40accee9ea5f7b1369e9691597c3edf513166e Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Thu, 29 May 2025 16:35:33 +0900 Subject: [PATCH 28/39] =?UTF-8?q?=E2=9C=A8fix:=20=EC=9D=B8=EB=8D=B1?= =?UTF-8?q?=EC=8A=A4=20=EC=B4=88=EA=B8=B0=ED=99=94=20=ED=95=A8=EC=88=98=20?= =?UTF-8?q?=EC=B6=94=EA=B0=80=20=EB=B0=8F=20docker-compose=20=EC=8B=A4?= =?UTF-8?q?=ED=96=89=20=EC=8B=9C=20=EC=9E=90=EB=8F=99=20=EC=B4=88=EA=B8=B0?= =?UTF-8?q?=ED=99=94=20=EC=84=A4=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/main.py | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/app/main.py b/app/main.py index e668873..aa2b267 100644 --- a/app/main.py +++ b/app/main.py @@ -17,6 +17,12 @@ from app.routers.news import router as news_router from app.routers.user import router as user_router +# ✅ 인덱스 초기화 함수 불러오기 +from app.utils.init_es_index import create_category_index + +# ✅ 인덱스 초기화 (docker-compose up 시 실행) +create_category_index() + app = FastAPI( title="KakaoTalk Chatbot API", description="KakaoTalk Chatbot Template API", From d342fa670a3ab8af4dd27e28f996a88466bfc05e Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 2 Jun 2025 16:02:23 +0900 Subject: [PATCH 29/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EB=B0=8F?= =?UTF-8?q?=20Kibana=20=EB=B2=84=EC=A0=84=20=EB=8B=A4=EC=9A=B4=EA=B7=B8?= =?UTF-8?q?=EB=A0=88=EC=9D=B4=EB=93=9C,=20=EC=B4=88=EA=B8=B0=ED=99=94=20?= =?UTF-8?q?=EC=8A=A4=ED=81=AC=EB=A6=BD=ED=8A=B8=20=EB=B0=8F=20API=20?= =?UTF-8?q?=EC=BD=94=EB=93=9C=20=EC=A0=95=EB=A6=AC,=20=EB=B2=A1=ED=84=B0?= =?UTF-8?q?=EC=9E=84=EB=B2=A0=EB=94=A9=20=EB=B0=A9=EC=8B=9D=20=EC=A0=9C?= =?UTF-8?q?=EA=B1=B0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/main.py | 6 -- app/routers/employee.py | 112 ++++++------------------- app/utils/init_es_index.py | 164 ++++++++----------------------------- docker-compose.dev.yml | 4 +- docker-compose.test.yml | 4 +- docker-compose.yml | 4 +- pyproject.toml | 3 +- 7 files changed, 64 insertions(+), 233 deletions(-) diff --git a/app/main.py b/app/main.py index aa2b267..e668873 100644 --- a/app/main.py +++ b/app/main.py @@ -17,12 +17,6 @@ from app.routers.news import router as news_router from app.routers.user import router as user_router -# ✅ 인덱스 초기화 함수 불러오기 -from app.utils.init_es_index import create_category_index - -# ✅ 인덱스 초기화 (docker-compose up 시 실행) -create_category_index() - app = FastAPI( title="KakaoTalk Chatbot API", description="KakaoTalk Chatbot Template API", diff --git a/app/routers/employee.py b/app/routers/employee.py index e3d7ce4..007a7cb 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -5,39 +5,17 @@ """ -import os - -from dotenv import load_dotenv -from elasticsearch import Elasticsearch from fastapi import APIRouter, Depends, HTTPException, Query -from huggingface_hub import login -from sentence_transformers import SentenceTransformer from sqlalchemy.orm import Session - +from elasticsearch import Elasticsearch +import os from app.models import Employee, EmployeeCategory, UserCategory, Users from app.utils.db_manager import db_manager router = APIRouter() db_dependency = Depends(db_manager.get_db) # 전역 변수로 설정 - -# 환경변수 로딩 -load_dotenv() -hf_token = os.getenv("HUGGINGFACE_TOKEN") - - -# Hugging Face 로그인 (모델 로딩 전) -if hf_token: - login(token=hf_token) - -# 모델 로드 -model = SentenceTransformer("jhgan/ko-sroberta-multitask") - -# Elasticsearch 연결 es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) -# 모듈 레벨에서 의존성 정의 -get_db = Depends(db_manager.get_db) - @router.get("/recommend") def get_recruit_recommendations( user_id: str = Query(..., description="추천을 받을 사용자 ID"), @@ -104,30 +82,12 @@ def get_recruit_recommendations( "message": message } -def filter_top_categories(similarity_results, min_score=0.6, top_n=5): - """ - 유사도 결과 필터링 - - min_score 이상 - - top_n 중 평균 이상 - """ - top_results = similarity_results[:top_n] - if not top_results: - return [] - - avg_score = sum([item["score"] for item in top_results]) / len(top_results) - - filtered = [ - item for item in top_results - if item["score"] >= min_score and item["score"] >= avg_score - ] - return filtered - @router.get("/DB_search") def search_employees( user_id: str = Query(..., description="사용자 ID"), keyword: str = Query(..., description="검색할 카테고리 키워드 (예: '정보통신', '디자인')"), limit: int = Query(10, ge=1, le=100, description="검색 결과 최대 개수 (기본값: 10, 최대: 100)"), - db: Session = get_db, + db: Session = Depends(db_manager.get_db) ): """ 사용자가 입력한 키워드를 기반으로 가장 유사한 카테고리를 찾고, 해당 카테고리에 속한 채용 공고를 반환합니다. @@ -155,65 +115,41 @@ def search_employees( # ✅ 2. Elasticsearch 유사 카테고리 검색 try: - embedding = model.encode(keyword, normalize_embeddings=True).tolist() - print("쿼리 벡터 차원:", len(embedding)) # 쿼리 벡터 차원 es_result = es.search( index="categories", body={ - "size": 10, + "size": 1, "query": { - "script_score": { - "query": { - "bool": { - "filter": [ - {"exists": {"field": "category_vector"}}, - {"term": {"feature": "employee"}} - ] + "bool": { + "must": { + "match_phrase_prefix": { + "category_name": { + "query": keyword + } } }, - "script": { - "source": "cosineSimilarity(params.query_vector, 'category_vector') + 1.0", - "params": { - "query_vector": embedding + "filter": { + "term": { + "feature": "employee" # ✅ 'employee' 기능 카테고리만 필터링 } } } } } ) - except ConnectionError as conn_err: - raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") from conn_err - + except ConnectionError: + raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") except Exception as e: - print("Elasticsearch 검색 중 에러 발생:", str(e)) # 로그 확인용 - print("상세 에러:", getattr(e, "info", None)) # 또는 e.body - raise HTTPException(status_code=500, detail=str(e)) from e + raise HTTPException(status_code=500, detail=str(e)) # ✅ 3. 검색 결과 확인 hits = es_result.get("hits", {}).get("hits", []) if hits: - hits_sorted = sorted( - hits, key=lambda x: x["_score"], reverse=True - ) - similarity_results = [ - { - "score": hit["_score"] - 1.0, - "category_id": hit["_source"]["category_id"], - "category_name": hit["_source"]["category_name"], - } - for hit in hits_sorted - ] - - filtered_results = filter_top_categories(similarity_results, min_score=0.7, top_n=5) - - if not filtered_results: - matched_category = "기타" - category_id = 0 - else: - best_match = filtered_results[0] - matched_category = best_match["category_name"] - category_id = best_match["category_id"] + matched_source = hits[0]["_source"] + matched_category = matched_source["category_name"] + category_id = matched_source["category_id"] else: + # 기본 카테고리 설정 (예: category_id=0, 기타) matched_category = "기타" category_id = 0 @@ -230,11 +166,11 @@ def search_employees( # ✅ 5. 결과를 JSON 형태로 정리 results = [ { - "title": job.title, - "institution": job.institution, + "title": job.title, + "institution": job.institution, "start_date": job.start_date.isoformat(), # date → 문자열 (ISO 포맷) "end_date": job.end_date.isoformat(), - "url": job.detail_url + "url": job.detail_url } for job in jobs ] @@ -243,4 +179,4 @@ def search_employees( return { "matched_category": matched_category, "results": results - } + } \ No newline at end of file diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index fae1035..967e852 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -1,47 +1,7 @@ -""" -카테고리 정보를 Elasticsearch에 벡터 기반으로 색인하는 초기화 스크립트. - -이 스크립트는 다음과 같은 기능을 수행합니다: -1. Hugging Face에 로그인하여 한국어 SentenceTransformer 모델(jhgan/ko-sroberta-multitask)을 불러옵니다. -2. 카테고리명을 해당 모델로 임베딩(벡터화)하여 Elasticsearch의 'categories' 인덱스에 저장합니다. -3. 기존 인덱스가 존재할 경우 삭제 후 edge_ngram 분석기를 적용한 새 인덱스를 생성합니다. -4. 카테고리명으로 부분 검색이 가능하며, 유사 카테고리 검색을 위한 dense_vector 필드를 포함합니다. - -사용 전제 조건: -- .env 파일에 HUGGINGFACE_TOKEN이 포함되어 있어야 함 -- Elasticsearch 서버가 localhost:9200에서 실행 중이어야 함 - -실행 방법: -$ python init_es_index.py -""" -import os - -import requests -from dotenv import load_dotenv from elasticsearch import Elasticsearch -from huggingface_hub import login -from sentence_transformers import SentenceTransformer - -# 환경변수 로딩 -load_dotenv() -hf_token = os.getenv("HUGGINGFACE_TOKEN") -# Hugging Face 로그인 -if hf_token: - login(token=hf_token) - -# ✅ 한국어 모델 로드 (임베딩 차원 자동 추정) -model = SentenceTransformer("jhgan/ko-sroberta-multitask") -embedding_dim = model.get_sentence_embedding_dimension() -print(f"[ℹ️] 임베딩 차원: {embedding_dim}") - -# Elasticsearch 연결 es = Elasticsearch("http://localhost:9200") -# 인덱스명 -INDEX_NAME = "categories" - -# 카테고리 목록 CATEGORIES = [ {"category_id": 1, "category_name": "IT/과학", "feature": "news"}, {"category_id": 2, "category_name": "마케팅", "feature": "news"}, @@ -80,105 +40,47 @@ {"category_id": 35, "category_name": "연구", "feature": "employee"}, ] -def check_index_exists(index_name: str) -> bool: - """ - Elasticsearch에서 특정 인덱스가 존재하는지 여부를 확인한다. - - Args: - index_name (str): 확인할 Elasticsearch 인덱스명. - - Returns: - bool: 인덱스가 존재하면 True, 존재하지 않으면 False. - """ - url = f"http://localhost:9200/{index_name}" - try: - response = requests.head(url) - if response.status_code == 200: - return True - elif response.status_code == 404: - return False - else: - print(f"[⚠️] 인덱스 체크 예상치 못한 상태 코드: {response.status_code}, {response.text}") - return False - except Exception as e: - print(f"[❌] 인덱스 체크 실패: {e}") - return False - def create_category_index(): - """ - Elasticsearch에 'categories' 인덱스를 생성하고, - 카테고리 데이터를 768차원 임베딩 벡터와 함께 색인한다. - - 기존 인덱스가 존재할 경우 삭제 후 새로 생성한다. - - - edge_ngram tokenizer와 analyzer를 설정하여 - 카테고리명에 대해 부분검색이 가능하도록 한다. - - 'category_vector' 필드에는 SentenceTransformer로 생성한 벡터를 저장한다. - """ - # 기존 인덱스 삭제 (REST 호출로 존재 여부 체크) - if check_index_exists(INDEX_NAME): - try: - es.indices.delete(index=INDEX_NAME) - print(f"[ℹ️] 기존 인덱스 '{INDEX_NAME}' 삭제 완료") - except Exception as e: - print(f"[❌] 인덱스 삭제 실패: {e}") - return - - # 인덱스 생성 - try: - es.indices.create( - index=INDEX_NAME, - body={ - "settings": { - "analysis": { - "tokenizer": { - "edge_ngram_tokenizer": { - "type": "edge_ngram", - "min_gram": 1, - "max_gram": 20, - "token_chars": ["letter", "digit"] - } - }, - "analyzer": { - "edge_ngram_analyzer": { - "tokenizer": "edge_ngram_tokenizer", - "filter": ["lowercase"] - } - } + if es.indices.exists(index="categories"): + es.indices.delete(index="categories") + + index_body = { + "settings": { + "analysis": { + "tokenizer": { + "edge_ngram_tokenizer": { + "type": "edge_ngram", + "min_gram": 2, + "max_gram": 10, + "token_chars": ["letter", "digit"] } }, - "mappings": { - "properties": { - "category_id": {"type": "integer"}, - "feature": {"type": "keyword"}, - "category_name": { - "type": "text", - "analyzer": "edge_ngram_analyzer", - "search_analyzer": "standard" - }, - "category_vector": { - "type": "dense_vector", - "dims": embedding_dim # ✅ 자동 추정된 차원 사용 - } + "analyzer": { + "autocomplete": { + "type": "custom", + "tokenizer": "edge_ngram_tokenizer", + "filter": ["lowercase"] } } } - ) - print(f"[✅] 인덱스 '{INDEX_NAME}' 생성 완료") - except Exception as e: - print(f"[❌] 인덱스 생성 실패: {e}") - return + }, + "mappings": { + "properties": { + "category_id": {"type": "integer"}, + "category_name": { + "type": "text", + "analyzer": "autocomplete", # 색인 시 edge_ngram 기반 분석 + "search_analyzer": "standard" # 검색 시 표준 분석기 사용 + }, + "feature": {"type": "keyword"} + } + } + } + + es.indices.create(index="categories", body=index_body) for cat in CATEGORIES: - try: - embedding = model.encode(cat["category_name"], normalize_embeddings=True).tolist() - doc = { - **cat, - "category_vector": embedding - } - es.index(index=INDEX_NAME, id=cat["category_id"], document=doc) # ✅ ID 지정 - except Exception as e: - print(f"[❌] 문서 색인 실패 (category_id={cat['category_id']}): {e}") + es.index(index="categories", document=cat) if __name__ == "__main__": create_category_index() diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml index c985aac..177931f 100644 --- a/docker-compose.dev.yml +++ b/docker-compose.dev.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 + image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:8.12.0 + image: docker.elastic.co/kibana/kibana:7.17.0 container_name: kibana ports: - '5601:5601' diff --git a/docker-compose.test.yml b/docker-compose.test.yml index 859e7ae..7c1210e 100644 --- a/docker-compose.test.yml +++ b/docker-compose.test.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 + image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:8.12.0 + image: docker.elastic.co/kibana/kibana:7.17.0 container_name: kibana ports: - '5601:5601' diff --git a/docker-compose.yml b/docker-compose.yml index 10d953f..6e41ffb 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 + image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:8.12.0 + image: docker.elastic.co/kibana/kibana:7.17.0 container_name: kibana ports: - '5601:5601' diff --git a/pyproject.toml b/pyproject.toml index fc2ca9f..2803639 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,8 +17,7 @@ pytest = "^8.3.5" pytest-cov = "^6.0.0" psycopg = "^3.2.6" ruff = "^0.11.4" -elasticsearch = "^8.12.1" -sentence-transformers = { version = "^2.2.2", extras = ["cpu"] } +elasticsearch = "^7.17.0" [tool.poetry.group.dev.dependencies] ruff = "^0.11.2" From 0ca45b69bbd52fae3dc0e14e0b299d9c8989556b Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 2 Jun 2025 16:29:32 +0900 Subject: [PATCH 30/39] Implement feature X to enhance user experience and optimize performance --- poetry.lock | 1390 +-------------------------------------------------- 1 file changed, 10 insertions(+), 1380 deletions(-) diff --git a/poetry.lock b/poetry.lock index 13bd41a..3f7ef6c 100644 --- a/poetry.lock +++ b/poetry.lock @@ -91,108 +91,6 @@ files = [ {file = "certifi-2025.4.26.tar.gz", hash = "sha256:0a816057ea3cdefcef70270d2c515e4506bbc954f417fa5ade2021213bb8f0c6"}, ] -[[package]] -name = "charset-normalizer" -version = "3.4.2" -description = "The Real First Universal Charset Detector. 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"sha256:1f41403bfa0cbb3e24fd958ca7fee04e9681e55e539296db9aca30c42acae693"}, -] - -[package.dependencies] -setuptools = ">=40.8.0" - -[package.extras] -build = ["cmake (>=3.20)", "lit"] -tests = ["autopep8", "isort", "llnl-hatchet", "numpy", "pytest", "pytest-forked", "pytest-xdist", "scipy (>=1.7.1)"] -tutorials = ["matplotlib", "pandas", "tabulate"] - [[package]] name = "typing-extensions" version = "4.12.2" @@ -2688,4 +1318,4 @@ files = [ [metadata] lock-version = "2.1" python-versions = "^3.11" -content-hash = "634d5d189d834bab877cf5c42e199dd6bc1064fb7b36ae3a8e3e2c687f5a2284" +content-hash = "4dbc61215b7b8c5acc80e3e40db13db4756d372597f013b41b23250b1edcc665" From 822f3af808dba2ec8211d708482e0f2bbea69021 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 2 Jun 2025 16:36:44 +0900 Subject: [PATCH 31/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EB=B0=8F?= =?UTF-8?q?=20Kibana=20=EB=B2=84=EC=A0=84=20=EC=97=85=EB=8D=B0=EC=9D=B4?= =?UTF-8?q?=ED=8A=B8=20(7.17.0=20=E2=86=92=208.12.0)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docker-compose.dev.yml | 4 ++-- docker-compose.test.yml | 4 ++-- docker-compose.yml | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml index 177931f..c985aac 100644 --- a/docker-compose.dev.yml +++ b/docker-compose.dev.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:7.17.0 + image: docker.elastic.co/kibana/kibana:8.12.0 container_name: kibana ports: - '5601:5601' diff --git a/docker-compose.test.yml b/docker-compose.test.yml index 7c1210e..859e7ae 100644 --- a/docker-compose.test.yml +++ b/docker-compose.test.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:7.17.0 + image: docker.elastic.co/kibana/kibana:8.12.0 container_name: kibana ports: - '5601:5601' diff --git a/docker-compose.yml b/docker-compose.yml index 6e41ffb..10d953f 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -41,7 +41,7 @@ services: - default elasticsearch: - image: docker.elastic.co/elasticsearch/elasticsearch:7.17.0 + image: docker.elastic.co/elasticsearch/elasticsearch:8.12.0 container_name: elasticsearch environment: - discovery.type=single-node @@ -55,7 +55,7 @@ services: - default kibana: - image: docker.elastic.co/kibana/kibana:7.17.0 + image: docker.elastic.co/kibana/kibana:8.12.0 container_name: kibana ports: - '5601:5601' From c7745e41ec64fabe3e54ca4e23304d1a82a7d155 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 2 Jun 2025 16:53:30 +0900 Subject: [PATCH 32/39] =?UTF-8?q?=E2=9C=A8fix:=20=EA=B2=80=EC=83=89=20API?= =?UTF-8?q?=EC=9D=98=20=EB=A7=A4=EA=B0=9C=EB=B3=80=EC=88=98=20=EB=B0=8F=20?= =?UTF-8?q?=EC=98=88=EC=99=B8=20=EC=B2=98=EB=A6=AC=20=EA=B0=9C=EC=84=A0,?= =?UTF-8?q?=20Elasticsearch=20=EC=BF=BC=EB=A6=AC=20=EB=A1=9C=EC=A7=81=20?= =?UTF-8?q?=EC=B5=9C=EC=A0=81=ED=99=94=20+=20BM25=EA=B8=B0=EB=B2=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 72 +++++++++++++++++++++++++++----------- app/utils/init_es_index.py | 22 ++++++++++++ 2 files changed, 74 insertions(+), 20 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 007a7cb..c05a6e1 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -94,7 +94,7 @@ def search_employees( Args: user_id (str): 검색을 수행할 사용자 ID. - q (str): 검색 키워드 (카테고리명). + keyword (str): 검색 키워드 (카테고리명). limit (int): 반환할 채용 공고 수 (기본값: 10, 최대 100). db (Session): 데이터베이스 세션 객체. @@ -105,7 +105,7 @@ def search_employees( Raises: HTTPException 404: 사용자가 존재하지 않는 경우. - HTTPException 404: 키워드와 일치하는 카테고리를 찾을 수 없는 경우. + HTTPException 500: Elasticsearch 연결 실패 또는 기타 오류 발생 시. """ # ✅ 1. 사용자 존재 여부 확인 @@ -113,12 +113,12 @@ def search_employees( if not user: raise HTTPException(status_code=404, detail="User not found") - # ✅ 2. Elasticsearch 유사 카테고리 검색 try: - es_result = es.search( + # ✅ 2-1. match_phrase_prefix로 후보군 검색 (자동완성 역할) + prefix_result = es.search( index="categories", body={ - "size": 1, + "size": 10, "query": { "bool": { "must": { @@ -130,30 +130,62 @@ def search_employees( }, "filter": { "term": { - "feature": "employee" # ✅ 'employee' 기능 카테고리만 필터링 + "feature": "employee" } } } } } ) + prefix_hits = prefix_result.get("hits", {}).get("hits", []) + if not prefix_hits: + # 후보군 없으면 바로 기타 처리 + matched_category = "기타" + category_id = 0 + else: + candidate_names = [hit["_source"]["category_name"] for hit in prefix_hits] + candidate_ids = {hit["_source"]["category_name"]: hit["_source"]["category_id"] for hit in prefix_hits} + + # ✅ 2-2. BM25 기반 match 쿼리로 후보군 중 가장 유사한 카테고리 검색 + bm25_result = es.search( + index="categories", + body={ + "size": 1, + "query": { + "bool": { + "must": { + "match": { + "category_name": { + "query": keyword, + "operator": "and" + } + } + }, + "filter": { + "terms": { + "category_name.keyword": candidate_names # 후보군 필터링 + } + } + } + } + } + ) + bm25_hits = bm25_result.get("hits", {}).get("hits", []) + if bm25_hits: + matched_source = bm25_hits[0]["_source"] + matched_category = matched_source["category_name"] + category_id = matched_source["category_id"] + else: + # BM25가 후보군 중 적합한 것을 못 찾으면 prefix 후보 중 1순위 반환 + matched_category = prefix_hits[0]["_source"]["category_name"] + category_id = prefix_hits[0]["_source"]["category_id"] + except ConnectionError: raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") except Exception as e: raise HTTPException(status_code=500, detail=str(e)) - # ✅ 3. 검색 결과 확인 - hits = es_result.get("hits", {}).get("hits", []) - if hits: - matched_source = hits[0]["_source"] - matched_category = matched_source["category_name"] - category_id = matched_source["category_id"] - else: - # 기본 카테고리 설정 (예: category_id=0, 기타) - matched_category = "기타" - category_id = 0 - - # ✅ 4. 해당 카테고리에 속한 채용 공고를 최신순으로 조회 + # ✅ 3. 해당 카테고리에 속한 채용 공고 최신순 조회 jobs = ( db.query(Employee) .join(EmployeeCategory, Employee.recruit_id == EmployeeCategory.recruit_id) @@ -163,7 +195,7 @@ def search_employees( .all() ) - # ✅ 5. 결과를 JSON 형태로 정리 + # ✅ 4. 결과를 JSON 형태로 정리 results = [ { "title": job.title, @@ -175,7 +207,7 @@ def search_employees( for job in jobs ] - # ✅ 6. 최종 응답 반환 + # ✅ 5. 최종 응답 반환 return { "matched_category": matched_category, "results": results diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index 967e852..9b88b10 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -1,3 +1,10 @@ +""" +Elasticsearch에 카테고리 정보를 색인하는 모듈입니다. +이 모듈은 사전에 정의된 카테고리 리스트(CATEGORIES)를 기반으로 +Elasticsearch 'categories' 인덱스를 생성하고, 자동완성 기능을 지원하기 위해 +edge_ngram 분석기를 적용한 매핑을 설정합니다. +주요 기능은 인덱스 삭제 후 재생성 및 초기 데이터 삽입입니다. +""" from elasticsearch import Elasticsearch es = Elasticsearch("http://localhost:9200") @@ -41,6 +48,17 @@ ] def create_category_index(): + """ + Elasticsearch에 'categories' 인덱스를 생성하고, + 사전에 정의된 CATEGORIES 리스트의 데이터를 색인한다. + + 기존에 'categories' 인덱스가 존재하면 삭제 후 새로 생성한다. + + 인덱스 매핑은 다음과 같다: + - category_id: 정수형 + - category_name: 텍스트, edge_ngram 기반 자동완성(analyzer: autocomplete) 적용 + - feature: 키워드형, 카테고리 구분용 (예: 'news', 'employee') + """ if es.indices.exists(index="categories"): es.indices.delete(index="categories") @@ -83,4 +101,8 @@ def create_category_index(): es.index(index="categories", document=cat) if __name__ == "__main__": + """ + 메인 실행 시 create_category_index() 함수를 호출하여 + Elasticsearch에 'categories' 인덱스를 생성하고 초기 데이터를 색인한다. + """ create_category_index() From f0eeb689136c1dba3a2df3860c700fd749c2a8ea Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 2 Jun 2025 17:03:06 +0900 Subject: [PATCH 33/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EC=9E=84?= =?UTF-8?q?=ED=8F=AC=ED=8A=B8=20=EC=88=9C=EC=84=9C=20=EC=88=98=EC=A0=95=20?= =?UTF-8?q?=EB=B0=8F=20=EC=BD=94=EB=93=9C=20=EC=A0=95=EB=A6=AC?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index c05a6e1..393142d 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -5,10 +5,12 @@ """ +import os + +from elasticsearch import Elasticsearch from fastapi import APIRouter, Depends, HTTPException, Query from sqlalchemy.orm import Session -from elasticsearch import Elasticsearch -import os + from app.models import Employee, EmployeeCategory, UserCategory, Users from app.utils.db_manager import db_manager @@ -144,7 +146,6 @@ def search_employees( category_id = 0 else: candidate_names = [hit["_source"]["category_name"] for hit in prefix_hits] - candidate_ids = {hit["_source"]["category_name"]: hit["_source"]["category_id"] for hit in prefix_hits} # ✅ 2-2. BM25 기반 match 쿼리로 후보군 중 가장 유사한 카테고리 검색 bm25_result = es.search( @@ -198,11 +199,11 @@ def search_employees( # ✅ 4. 결과를 JSON 형태로 정리 results = [ { - "title": job.title, - "institution": job.institution, + "title": job.title, + "institution": job.institution, "start_date": job.start_date.isoformat(), # date → 문자열 (ISO 포맷) "end_date": job.end_date.isoformat(), - "url": job.detail_url + "url": job.detail_url } for job in jobs ] @@ -211,4 +212,4 @@ def search_employees( return { "matched_category": matched_category, "results": results - } \ No newline at end of file + } From 6f6accd3cc5e903da2cbd84b3b839e1014999655 Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Mon, 2 Jun 2025 17:08:09 +0900 Subject: [PATCH 34/39] =?UTF-8?q?=E2=9C=A8fix:=20=EB=B6=88=ED=95=84?= =?UTF-8?q?=EC=9A=94=20=EC=A3=BC=EC=84=9D=20=EB=B0=8F=20=EA=B3=B5=EB=B0=B1?= =?UTF-8?q?=20=EC=A0=9C=EA=B1=B0=20=EB=93=B1?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 8 ++++---- app/utils/init_es_index.py | 4 +--- 2 files changed, 5 insertions(+), 7 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 393142d..4fd9192 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -89,7 +89,7 @@ def search_employees( user_id: str = Query(..., description="사용자 ID"), keyword: str = Query(..., description="검색할 카테고리 키워드 (예: '정보통신', '디자인')"), limit: int = Query(10, ge=1, le=100, description="검색 결과 최대 개수 (기본값: 10, 최대: 100)"), - db: Session = Depends(db_manager.get_db) + db: Session = db_dependency ): """ 사용자가 입력한 키워드를 기반으로 가장 유사한 카테고리를 찾고, 해당 카테고리에 속한 채용 공고를 반환합니다. @@ -181,10 +181,10 @@ def search_employees( matched_category = prefix_hits[0]["_source"]["category_name"] category_id = prefix_hits[0]["_source"]["category_id"] - except ConnectionError: - raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") + except ConnectionError as e: + raise HTTPException(status_code=500, detail="Elasticsearch 연결 실패") from e except Exception as e: - raise HTTPException(status_code=500, detail=str(e)) + raise HTTPException(status_code=500, detail=str(e)) from e # ✅ 3. 해당 카테고리에 속한 채용 공고 최신순 조회 jobs = ( diff --git a/app/utils/init_es_index.py b/app/utils/init_es_index.py index 9b88b10..aa76b8b 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_es_index.py @@ -49,11 +49,9 @@ def create_category_index(): """ - Elasticsearch에 'categories' 인덱스를 생성하고, + Elasticsearch에 'categories' 인덱스를 생성하고, 사전에 정의된 CATEGORIES 리스트의 데이터를 색인한다. - 기존에 'categories' 인덱스가 존재하면 삭제 후 새로 생성한다. - 인덱스 매핑은 다음과 같다: - category_id: 정수형 - category_name: 텍스트, edge_ngram 기반 자동완성(analyzer: autocomplete) 적용 From 916a5e42b823ec6d161f088b2697b33c7605b72c Mon Sep 17 00:00:00 2001 From: Jeongminseo <112807942+minseo0810@users.noreply.github.com> Date: Wed, 4 Jun 2025 18:00:31 +0900 Subject: [PATCH 35/39] =?UTF-8?q?=E2=9C=A8feat:=20Elasticsearch=20?= =?UTF-8?q?=EC=B9=B4=ED=85=8C=EA=B3=A0=EB=A6=AC=20=EC=9D=B8=EB=8D=B1?= =?UTF-8?q?=EC=8A=A4=20=EC=83=9D=EC=84=B1=20=EB=B0=8F=20=EC=B4=88=EA=B8=B0?= =?UTF-8?q?=20=EB=8D=B0=EC=9D=B4=ED=84=B0=20=EC=83=89=EC=9D=B8=20=EA=B8=B0?= =?UTF-8?q?=EB=8A=A5=20=EC=B6=94=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 2 ++ app/main.py | 11 +++++++++++ ...s_index.py => init_elasticsearch_index.py} | 19 +++++++++++++++++-- 3 files changed, 30 insertions(+), 2 deletions(-) rename app/utils/{init_es_index.py => init_elasticsearch_index.py} (88%) diff --git a/README.md b/README.md index ceca13a..37700d8 100644 --- a/README.md +++ b/README.md @@ -44,6 +44,7 @@ FastAPI와 MySQL을 사용한 카카오톡 챗봇 개발을 위한 템플릿 프 │ │ ├── __init__.py │ │ ├── db_manager.py │ │ ├── init_default_data.py +│ │ ├── init_elasticsearch_index.py │ │ ├── insert_employee_data.py │ │ ├── news_client.py │ │ ├── news_provider_mapping.py @@ -57,6 +58,7 @@ FastAPI와 MySQL을 사용한 카카오톡 챗봇 개발을 위한 템플릿 프 │ ├── routers/ │ ├── test_add_employee_data.py │ ├── test_add_user_favorit.py +│ ├── test_employee_DB_search.py │ ├── test_employee_recommendation.py │ ├── test_get_categories_by_feature.py │ ├── test_get_my_category_list.py diff --git a/app/main.py b/app/main.py index e668873..4c93d30 100644 --- a/app/main.py +++ b/app/main.py @@ -9,6 +9,8 @@ - 기본 루트 엔드포인트 제공 """ +from contextlib import asynccontextmanager + from fastapi import FastAPI from fastapi.middleware.cors import CORSMiddleware @@ -16,6 +18,15 @@ from app.routers.feature import router as feature_router from app.routers.news import router as news_router from app.routers.user import router as user_router +from app.utils.init_elasticsearch_index import create_category_index + + +@asynccontextmanager +async def lifespan(app: FastAPI): + # 서버 시작 시 실행할 코드 + create_category_index() + yield + # 서버 종료 시 실행할 코드 (필요 시 여기에 정리 작업 가능) app = FastAPI( title="KakaoTalk Chatbot API", diff --git a/app/utils/init_es_index.py b/app/utils/init_elasticsearch_index.py similarity index 88% rename from app/utils/init_es_index.py rename to app/utils/init_elasticsearch_index.py index aa76b8b..1c334a8 100644 --- a/app/utils/init_es_index.py +++ b/app/utils/init_elasticsearch_index.py @@ -57,8 +57,11 @@ def create_category_index(): - category_name: 텍스트, edge_ngram 기반 자동완성(analyzer: autocomplete) 적용 - feature: 키워드형, 카테고리 구분용 (예: 'news', 'employee') """ + index_name = "categories" + if es.indices.exists(index="categories"): es.indices.delete(index="categories") + print(f"🗑️ 기존 Elasticsearch 인덱스 '{index_name}' 삭제 완료") index_body = { "settings": { @@ -93,10 +96,22 @@ def create_category_index(): } } - es.indices.create(index="categories", body=index_body) + try: + es.indices.create(index=index_name, body=index_body) + print(f"✅ Elasticsearch 인덱스 '{index_name}' 생성 완료") + except Exception as e: + print(f"❌ 인덱스 생성 실패: {e}") + return + success_count = 0 for cat in CATEGORIES: - es.index(index="categories", document=cat) + try: + es.index(index=index_name, document=cat) + success_count += 1 + except Exception as e: + print(f"⚠️ 색인 실패 (카테고리: {cat['category_name']}): {e}") + + print(f"📦 총 {success_count}개의 카테고리가 '{index_name}' 인덱스에 색인됨") if __name__ == "__main__": """ From 99e02a5019731e929434942b43fad6da31f81edb Mon Sep 17 00:00:00 2001 From: cux-maks Date: Sat, 7 Jun 2025 17:56:03 +0900 Subject: [PATCH 36/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=EB=8D=B0?= =?UTF-8?q?=EC=9D=B4=ED=84=B0=20=EB=B3=BC=EB=A5=A8=20=EA=B2=BD=EB=A1=9C=20?= =?UTF-8?q?=EC=88=98=EC=A0=95?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- docker-compose.dev.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docker-compose.dev.yml b/docker-compose.dev.yml index c985aac..9eed70d 100644 --- a/docker-compose.dev.yml +++ b/docker-compose.dev.yml @@ -50,7 +50,7 @@ services: ports: - '9200:9200' volumes: - - esdata:/usr/share/elasticsearch/data + - ./volumes/esdata:/usr/share/elasticsearch/data networks: - default From 60ee2b80f98db55db39705e536fbe0d9c5ddfca0 Mon Sep 17 00:00:00 2001 From: cux-maks Date: Sat, 7 Jun 2025 17:56:13 +0900 Subject: [PATCH 37/39] =?UTF-8?q?=E2=9C=A8fix:=20Elasticsearch=20=ED=98=B8?= =?UTF-8?q?=EC=8A=A4=ED=8A=B8=20=EC=A3=BC=EC=86=8C=EB=A5=BC=20=ED=99=98?= =?UTF-8?q?=EA=B2=BD=EB=B3=80=EC=88=98=EC=97=90=EC=84=9C=20=EA=B3=A0?= =?UTF-8?q?=EC=A0=95=EA=B0=92=EC=9C=BC=EB=A1=9C=20=EB=B3=80=EA=B2=BD?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 2 +- app/utils/init_elasticsearch_index.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index 4fd9192..c19e8d9 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -16,7 +16,7 @@ router = APIRouter() db_dependency = Depends(db_manager.get_db) # 전역 변수로 설정 -es = Elasticsearch(os.getenv("ES_HOST", "http://elasticsearch:9200")) +es = Elasticsearch("http://elasticsearch:9200") @router.get("/recommend") def get_recruit_recommendations( diff --git a/app/utils/init_elasticsearch_index.py b/app/utils/init_elasticsearch_index.py index 1c334a8..f291537 100644 --- a/app/utils/init_elasticsearch_index.py +++ b/app/utils/init_elasticsearch_index.py @@ -7,7 +7,7 @@ """ from elasticsearch import Elasticsearch -es = Elasticsearch("http://localhost:9200") +es = Elasticsearch("http://elasticsearch:9200") CATEGORIES = [ {"category_id": 1, "category_name": "IT/과학", "feature": "news"}, From 6fed410301a6f748c5edb2e199dcb15be704946c Mon Sep 17 00:00:00 2001 From: cux-maks Date: Sat, 7 Jun 2025 17:56:18 +0900 Subject: [PATCH 38/39] =?UTF-8?q?=E2=9C=A8fix:=20FastAPI=20=EC=84=A4?= =?UTF-8?q?=EC=A0=95=EC=97=90=20lifespan=20=EC=9D=B8=EC=9E=90=20=EC=B6=94?= =?UTF-8?q?=EA=B0=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/main.py | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/app/main.py b/app/main.py index 4c93d30..efb3ca0 100644 --- a/app/main.py +++ b/app/main.py @@ -31,7 +31,8 @@ async def lifespan(app: FastAPI): app = FastAPI( title="KakaoTalk Chatbot API", description="KakaoTalk Chatbot Template API", - version="0.1.0" + version="0.1.0", + lifespan=lifespan ) # CORS 미들웨어 설정 From cf8cd1d8b077e38c7e79d84653a0e700ef722589 Mon Sep 17 00:00:00 2001 From: cux-maks Date: Sat, 7 Jun 2025 17:58:06 +0900 Subject: [PATCH 39/39] =?UTF-8?q?=E2=9C=A8fix:=20=EB=B6=88=ED=95=84?= =?UTF-8?q?=EC=9A=94=ED=95=9C=20import=20=EB=AC=B8=20=EC=A0=9C=EA=B1=B0=20?= =?UTF-8?q?=EB=B0=8F=20=EC=BD=94=EB=93=9C=20=EC=A0=95=EB=A6=AC?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/routers/employee.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/app/routers/employee.py b/app/routers/employee.py index c19e8d9..03a2c8a 100644 --- a/app/routers/employee.py +++ b/app/routers/employee.py @@ -4,9 +4,6 @@ 사용자의 구독 정보를 바탕으로 관련된 채용 공고를 필터링하여 반환합니다. """ - -import os - from elasticsearch import Elasticsearch from fastapi import APIRouter, Depends, HTTPException, Query from sqlalchemy.orm import Session