From 6a5c411800c79ffda2cdfbcc2bfa17e71ab7deca Mon Sep 17 00:00:00 2001 From: hiondal Date: Sun, 15 Jun 2025 13:52:26 +0000 Subject: [PATCH] release --- .gitignore | 120 + restaurant/README.md | 415 ++ restaurant/app/main.py | 741 +++ restaurant/app/requirements.txt | 6 + restaurant/build-base.sh | 214 + restaurant/build.sh | 251 + restaurant/create-imagepullsecret.sh | 237 + restaurant/deployment/container/Dockerfile | 46 + .../deployment/container/Dockerfile-base | 37 + restaurant/deployment/manifest/configmap.yaml | 34 + .../deployment/manifest/deployment.yaml | 81 + restaurant/deployment/manifest/ingress.yaml | 38 + restaurant/deployment/manifest/secret.yaml | 10 + restaurant/deployment/manifest/service.yaml | 16 + restaurant/setup.sh | 212 + review/README.md | 480 ++ review/app/main.py | 1626 +++++++ review/app/requirements.txt | 9 + review/build-base.sh | 217 + review/build.sh | 257 + review/create-imagepullsecret.sh | 103 + review/deployment/container/Dockerfile | 72 + review/deployment/container/Dockerfile-base | 103 + review/deployment/manifests/configmap.yaml | 78 + review/deployment/manifests/deployment.yaml | 130 + review/deployment/manifests/ingress.yaml | 39 + review/deployment/manifests/secret.yaml | 21 + review/deployment/manifests/service.yaml | 17 + review/setup.sh | 280 ++ vector/README.md | 614 +++ vector/app/config/settings.py | 80 + vector/app/main.py | 917 ++++ vector/app/requirements.txt | 67 + vector/app/services/claude_service.py | 336 ++ vector/app/services/restaurant_service.py | 235 + vector/app/services/review_service.py | 467 ++ vector/app/services/vector_service.py | 728 +++ vector/app/utils/category_utils.py | 161 + vector/app/utils/data_utils.py | 194 + vector/build-base.sh | 282 ++ vector/build.sh | 337 ++ vector/create-imagepullsecret.sh | 236 + vector/deployment/container/Dockerfile | 100 + vector/deployment/container/Dockerfile-base | 138 + vector/deployment/manifest/configmap.yaml | 63 + vector/deployment/manifest/deployment.yaml | 164 + vector/deployment/manifest/ingress.yaml | 39 + vector/deployment/manifest/pvc.yaml | 18 + vector/deployment/manifest/secret.yaml | 11 + vector/deployment/manifest/service.yaml | 17 + vector/poetry.lock | 4274 +++++++++++++++++ vector/pyproject.toml | 41 + vector/setup.sh | 376 ++ 53 files changed, 15785 insertions(+) create mode 100644 .gitignore create mode 100644 restaurant/README.md create mode 100644 restaurant/app/main.py create mode 100644 restaurant/app/requirements.txt create mode 100755 restaurant/build-base.sh create mode 100755 restaurant/build.sh create mode 100755 restaurant/create-imagepullsecret.sh create mode 100644 restaurant/deployment/container/Dockerfile create mode 100644 restaurant/deployment/container/Dockerfile-base create mode 100644 restaurant/deployment/manifest/configmap.yaml create mode 100644 restaurant/deployment/manifest/deployment.yaml create mode 100644 restaurant/deployment/manifest/ingress.yaml create mode 100644 restaurant/deployment/manifest/secret.yaml create mode 100644 restaurant/deployment/manifest/service.yaml create mode 100755 restaurant/setup.sh create mode 100644 review/README.md create mode 100644 review/app/main.py create mode 100644 review/app/requirements.txt create mode 100755 review/build-base.sh create mode 100755 review/build.sh create mode 100755 review/create-imagepullsecret.sh create mode 100644 review/deployment/container/Dockerfile create mode 100644 review/deployment/container/Dockerfile-base create mode 100644 review/deployment/manifests/configmap.yaml create mode 100644 review/deployment/manifests/deployment.yaml create mode 100644 review/deployment/manifests/ingress.yaml create mode 100644 review/deployment/manifests/secret.yaml create mode 100644 review/deployment/manifests/service.yaml create mode 100755 review/setup.sh create mode 100644 vector/README.md create mode 100644 vector/app/config/settings.py create mode 100644 vector/app/main.py create mode 100644 vector/app/requirements.txt create mode 100644 vector/app/services/claude_service.py create mode 100644 vector/app/services/restaurant_service.py create mode 100644 vector/app/services/review_service.py create mode 100644 vector/app/services/vector_service.py create mode 100644 vector/app/utils/category_utils.py create mode 100644 vector/app/utils/data_utils.py create mode 100755 vector/build-base.sh create mode 100755 vector/build.sh create mode 100755 vector/create-imagepullsecret.sh create mode 100644 vector/deployment/container/Dockerfile create mode 100644 vector/deployment/container/Dockerfile-base create mode 100644 vector/deployment/manifest/configmap.yaml create mode 100644 vector/deployment/manifest/deployment.yaml create mode 100644 vector/deployment/manifest/ingress.yaml create mode 100644 vector/deployment/manifest/pvc.yaml create mode 100644 vector/deployment/manifest/secret.yaml create mode 100644 vector/deployment/manifest/service.yaml create mode 100644 vector/poetry.lock create mode 100644 vector/pyproject.toml create mode 100755 vector/setup.sh diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..4dbc92f --- /dev/null +++ b/.gitignore @@ -0,0 +1,120 @@ +# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +pip-wheel-metadata/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ + +# Virtual environments +venv/ +env/ +ENV/ +env.bak/ +venv.bak/ + +# IDE +.vscode/ +.idea/ +*.swp +*.swo +*~ + +# OS +.DS_Store +.DS_Store? +._* +.Spotlight-V100 +.Trashes +ehthumbs.db +Thumbs.db + +# Environment variables +.env +.env.local +.env.development.local +.env.test.local +.env.production.local + +# Logs +*.log +logs/ + +# Vector DB and ML Models +vector_db/ +*.pkl +*.model +*.bin +models/ +embeddings/ +checkpoints/ + +# Data files +data/ +*.csv +*.json +*.xlsx +*.parquet + +# Temporary files +tmp/ +temp/ +*.tmp +*.temp + +# Docker +.dockerignore + +# Node.js (if applicable) +node_modules/ +npm-debug.log* +yarn-debug.log* +yarn-error.log* + +# Database +*.db +*.sqlite +*.sqlite3 + +# Backup files +*.bak +*.backup \ No newline at end of file diff --git a/restaurant/README.md b/restaurant/README.md new file mode 100644 index 0000000..4a3e869 --- /dev/null +++ b/restaurant/README.md @@ -0,0 +1,415 @@ +# 카카오 API 기반 음식점 수집 서비스 + +카카오 로컬 API를 활용하여 음식점 정보를 수집하고 관리하는 RESTful API 서비스입니다. + +## 📋 프로젝트 개요 + +### 주요 기능 +- 🔍 **카카오 로컬 API 연동**: 키워드 및 지역 기반 음식점 검색 +- 📊 **다중 페이지 수집**: 최대 45페이지까지 데이터 수집 지원 +- 💾 **자동 JSON 저장**: 수집된 데이터를 JSON 파일로 자동 저장 +- 🚀 **RESTful API 제공**: FastAPI 기반의 완전한 API 서비스 +- 📚 **Swagger UI 지원**: 자동 생성되는 API 문서 +- ☸️ **Kubernetes 배포**: 완전한 컨테이너 오케스트레이션 지원 +- 🔧 **환경변수 설정**: ConfigMap과 Secret을 통한 유연한 설정 관리 + +### 기술 스택 +- **Backend**: Python 3.11, FastAPI, aiohttp +- **API**: Kakao Local API +- **Container**: Docker, Multi-stage build +- **Orchestration**: Kubernetes (AKS) +- **Registry**: Azure Container Registry (ACR) +- **Documentation**: Swagger UI, ReDoc + +## 🏗️ 프로젝트 구조 + +``` +review-api/restaurant/ +├── app/ # 애플리케이션 소스 +│ ├── main.py # 메인 애플리케이션 +│ └── requirements.txt # Python 의존성 +├── deployment/ # 배포 관련 파일 +│ ├── container/ # 컨테이너 이미지 빌드 +│ │ ├── Dockerfile # 서비스 이미지 빌드 +│ │ └── Dockerfile-base # 베이스 이미지 빌드 +│ └── manifests/ # Kubernetes 매니페스트 +│ ├── configmap.yaml # 환경 설정 +│ ├── secret.yaml # 민감 정보 (API 키) +│ ├── deployment.yaml # 애플리케이션 배포 +│ ├── service.yaml # 서비스 노출 +│ └── ingress.yaml # 외부 접근 +├── build-base.sh # 베이스 이미지 빌드 스크립트 +├── build.sh # 서비스 이미지 빌드 스크립트 +├── create-imagepullsecret.sh # ACR 인증 설정 스크립트 +├── setup.sh # 로컬 환경 설정 스크립트 +└── README.md # 프로젝트 문서 +``` + +## 📋 사전 작업 + +### 카카오 API 설정 +카카오 developers 포탈에서 애플리케이션 등록이 필요합니다. + +1. **포탈 접속**: https://developers.kakao.com/console/app +2. **애플리케이션 등록**: + - 앱 이름: `RestaurantCollector` + - 회사명: `{회사명}` + - 카테고리: `식음료` +3. **카카오맵 활성화**: 등록한 애플리케이션에서 좌측 '카카오맵' 메뉴 클릭하여 활성화 + +## 🚀 빠른 시작 + +### 1. 로컬 개발 환경 설정 + +```bash +# 저장소 클론 (review-api/restaurant 디렉토리로 이동) +cd review-api/restaurant + +# 환경 설정 스크립트 실행 +chmod +x setup.sh +./setup.sh + +# 가상환경 활성화 +source venv/bin/activate + +# 애플리케이션 실행 +python app/main.py +``` + +### 2. 로컬 웹 브라우저 접속 + +```bash +# 애플리케이션이 정상 실행된 후 아래 URL로 접속 +``` + +- **메인 페이지**: http://localhost:18000 +- **Swagger UI**: http://localhost:18000/docs +- **ReDoc**: http://localhost:18000/redoc +- **헬스체크**: http://localhost:18000/health + +### 3. API 테스트 + +```bash +# 기본 음식점 수집 +curl -X POST "http://localhost:18000/collect" \ + -H "Content-Type: application/json" \ + -d '{ + "query": "치킨", + "region": "서울", + "size": 15, + "pages": 3, + "save_to_file": true + }' + +# 수집된 파일 목록 조회 +curl "http://localhost:18000/list-files" + +# 파일 다운로드 (예시) +curl "http://localhost:18000/download/restaurant.json" -o downloaded_restaurants.json +``` + +## 🐳 Docker 컨테이너 실행 + +### 베이스 이미지 빌드 + +```bash +# ACR에 베이스 이미지 빌드 및 푸시 +./build-base.sh latest acrdigitalgarage03 rg-digitalgarage-03 +``` + +### 서비스 이미지 빌드 + +```bash +# ACR에 서비스 이미지 빌드 및 푸시 +./build.sh latest acrdigitalgarage03 rg-digitalgarage-03 +``` + +### 로컬 Docker 실행 + +```bash +# 컨테이너 실행 +docker run -p 18000:8000 \ + -e KAKAO_API_KEY=5cdc24407edbf8544f3954cfaa4650c6 \ + -e PORT=8000 \ + restaurant-api:latest + +# 백그라운드 실행 +docker run -d -p 18000:8000 \ + --name restaurant-api \ + -e KAKAO_API_KEY=5cdc24407edbf8544f3954cfaa4650c6 \ + -e PORT=8000 \ + restaurant-api:latest +``` + +## ☸️ Kubernetes 배포 + +### 1. ACR Image Pull Secret 생성 + +```bash +# Image Pull Secret 생성 +./create-imagepullsecret.sh acrdigitalgarage03 rg-digitalgarage-03 +``` + +### 2. Kubernetes 리소스 배포 + +```bash +# ConfigMap 및 Secret 적용 +kubectl apply -f deployment/manifests/configmap.yaml +kubectl apply -f deployment/manifests/secret.yaml + +# 애플리케이션 배포 +kubectl apply -f deployment/manifests/deployment.yaml +kubectl apply -f deployment/manifests/service.yaml +kubectl apply -f deployment/manifests/ingress.yaml +``` + +### 3. 배포 상태 확인 + +```bash +# Pod 상태 확인 +kubectl get pods -l app=restaurant-api + +# 서비스 상태 확인 +kubectl get svc restaurant-api-service + +# Ingress 상태 확인 +kubectl get ingress restaurant-api-ingress + +# 로그 확인 +kubectl logs -l app=restaurant-api -f +``` + +### 4. 🌐 외부 브라우저에서 접속하기 + +#### Ingress 주소 확인 방법 + +```bash +# 1. Ingress 설정된 호스트 확인 +kubectl get ingress restaurant-api-ingress -o jsonpath='{.spec.rules[0].host}' + +# 2. Ingress External IP 확인 (LoadBalancer 타입인 경우) +kubectl get ingress restaurant-api-ingress + +# 3. Ingress Controller의 External IP 확인 +kubectl get svc -n ingress-nginx ingress-nginx-controller + +# 4. 현재 설정된 ingress 주소 확인 +INGRESS_HOST=$(kubectl get ingress restaurant-api-ingress -o jsonpath='{.spec.rules[0].host}') +echo "🌐 Restaurant API URL: http://${INGRESS_HOST}" +``` + +#### 브라우저 접속 주소 + +현재 설정된 주소로 접속하세요: + +```bash +# 현재 설정된 기본 주소 (환경에 따라 다를 수 있음) +INGRESS_URL="http://restaurant-api.20.249.191.180.nip.io" +echo "브라우저에서 접속: ${INGRESS_URL}" +``` + +**주요 접속 페이지:** +- **🏠 메인 페이지**: http://restaurant-api.20.249.191.180.nip.io +- **📖 Swagger UI**: http://restaurant-api.20.249.191.180.nip.io/docs +- **📄 ReDoc**: http://restaurant-api.20.249.191.180.nip.io/redoc +- **❤️ 헬스체크**: http://restaurant-api.20.249.191.180.nip.io/health + +#### 접속 테스트 + +```bash +# API 접속 테스트 +curl "http://restaurant-api.20.249.191.180.nip.io/health" + +# 설정 정보 확인 +curl "http://restaurant-api.20.249.191.180.nip.io/config" + +# Swagger UI 접속 확인 +curl -I "http://restaurant-api.20.249.191.180.nip.io/docs" +``` + +## ⚙️ 환경 설정 + +### 환경 변수 + +| 변수명 | 기본값 | 설명 | +|--------|--------|------| +| `KAKAO_API_KEY` | `5cdc24407edbf8544f3954cfaa4650c6` | 카카오 API 키 | +| `APP_TITLE` | `카카오 API 기반 음식점 수집 서비스` | 애플리케이션 제목 | +| `HOST` | `0.0.0.0` | 서버 호스트 | +| `PORT` | `8000` | 서버 포트 (컨테이너 내부) | +| `DEFAULT_QUERY` | `음식점` | 기본 검색 키워드 | +| `DEFAULT_REGION` | `서울` | 기본 검색 지역 | +| `DEFAULT_SIZE` | `15` | 페이지당 결과 수 | +| `MAX_PAGES` | `45` | 최대 페이지 수 | +| `DATA_DIR` | `/app/data` | 데이터 저장 디렉토리 | +| `REQUEST_DELAY` | `0.1` | API 요청 간 지연시간(초) | + +## 📊 API 엔드포인트 + +### 주요 엔드포인트 + +| Method | Endpoint | 설명 | +|--------|----------|------| +| `GET` | `/` | 메인 페이지 | +| `GET` | `/docs` | Swagger UI 문서 | +| `GET` | `/health` | 헬스체크 | +| `POST` | `/collect` | 음식점 정보 수집 | +| `POST` | `/collect-background` | 백그라운드 수집 | +| `GET` | `/list-files` | 저장된 파일 목록 | +| `GET` | `/download/{filename}` | 파일 다운로드 | +| `GET` | `/config` | 환경 설정 확인 | + +### 수집 API 예시 + +```json +POST /collect +{ + "query": "피자", + "region": "강남구", + "size": 15, + "pages": 5, + "save_to_file": true +} +``` + +**응답:** +```json +{ + "success": true, + "message": "음식점 정보 수집이 완료되었습니다. (총 67개)", + "metadata": { + "collection_date": "2024-06-12T10:30:00", + "query": "피자", + "region": "강남구", + "total_count": 67, + "pages_collected": 5, + "execution_time": 12.5 + }, + "restaurants": [...], + "file_saved": true, + "file_path": "/app/data/restaurants_피자_강남구_20240612_103000.json" +} +``` + +## 🔧 개발 및 확장 + +### 로컬 개발 + +```bash +# 개발 모드로 실행 (자동 재시작) +uvicorn app.main:app --host 0.0.0.0 --port 18000 --reload + +# 의존성 추가 +pip install 새패키지명 +pip freeze > app/requirements.txt + +# 코드 포맷팅 +black app/main.py +flake8 app/main.py +``` + +### Ingress 호스트 변경 + +현재 환경에 맞게 Ingress 호스트를 변경하려면: + +```bash +# 1. 현재 External IP 확인 +kubectl get svc -n ingress-nginx ingress-nginx-controller + +# 2. deployment/manifests/ingress.yaml 파일에서 host 수정 +# 예: restaurant-api.{YOUR_EXTERNAL_IP}.nip.io + +# 3. 변경사항 적용 +kubectl apply -f deployment/manifests/ingress.yaml + +# 4. 새로운 주소 확인 +kubectl get ingress restaurant-api-ingress +``` + +## 🐛 문제 해결 + +### 일반적인 문제 + +**1. API 키 인증 실패** +```bash +# API 키 확인 +curl -H "Authorization: KakaoAK YOUR_API_KEY" \ + "https://dapi.kakao.com/v2/local/search/keyword.json?query=테스트&size=1" + +# 환경변수 확인 +echo $KAKAO_API_KEY +``` + +**2. Kubernetes 배포 실패** +```bash +# Pod 로그 확인 +kubectl logs -l app=restaurant-api + +# ConfigMap 확인 +kubectl get configmap restaurant-api-config -o yaml + +# Secret 확인 +kubectl get secret restaurant-api-secret -o yaml +``` + +**3. Ingress 접속 실패** +```bash +# Ingress Controller 상태 확인 +kubectl get pods -n ingress-nginx + +# Ingress 규칙 확인 +kubectl describe ingress restaurant-api-ingress + +# Service 연결 확인 +kubectl get endpoints restaurant-api-service +``` + +**4. 포트 관련 문제** +- 로컬 개발: 18000번 포트 사용 +- Docker 컨테이너: 8000번 포트로 실행 (외부 18000번으로 매핑) +- Kubernetes: 8000번 포트로 실행 (Service에서 80번으로 노출, Ingress를 통해 외부 접근) + +## 🎯 성능 최적화 + +### 권장 설정 + +```yaml +# deployment.yaml에서 리소스 최적화 +resources: + requests: + memory: "512Mi" + cpu: "250m" + limits: + memory: "1Gi" + cpu: "500m" +``` + +### 모니터링 + +```bash +# 리소스 사용량 확인 +kubectl top pods -l app=restaurant-api + +# 메트릭 수집 (Prometheus 설정 시) +kubectl get --raw /metrics +``` + +## 📈 향후 확장 계획 + +- [ ] **전국 확대**: 지역별 음식점 수집 기능 확장 +- [ ] **데이터베이스 연동**: PostgreSQL, MongoDB 지원 +- [ ] **비동기 작업 큐**: Celery, Redis 활용 +- [ ] **데이터 분석**: 음식점 트렌드 분석 기능 +- [ ] **알림 시스템**: 새로운 음식점 알림 기능 +- [ ] **사용자 인증**: JWT 기반 인증 시스템 +- [ ] **API 레이트 리미팅**: 요청 제한 기능 +- [ ] **GraphQL 지원**: 유연한 쿼리 인터페이스 +- [ ] **실시간 모니터링**: Grafana, Prometheus 연동 + +--- + +## 📞 지원 및 문의 + +- **이슈 리포트**: GitHub Issues +- **기술 문의**: 개발팀 Slack +- **API 문서**: Swagger UI에서 상세 확인 \ No newline at end of file diff --git a/restaurant/app/main.py b/restaurant/app/main.py new file mode 100644 index 0000000..81c8861 --- /dev/null +++ b/restaurant/app/main.py @@ -0,0 +1,741 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +카카오 API 기반 음식점 수집 서비스 +review-api/restaurant/app/main.py +""" + +import os +import json +import asyncio +import aiohttp +import logging +import sys +from datetime import datetime +from typing import Optional, List, Dict, Any +from fastapi import FastAPI, HTTPException, BackgroundTasks, Query +from fastapi.responses import HTMLResponse, FileResponse +from pydantic import BaseModel, Field +import uvicorn + +# ============================================================================= +# .env 파일 로딩 (다른 import보다 먼저) +# ============================================================================= +from dotenv import load_dotenv + +# .env 파일에서 환경변수 로드 +load_dotenv() + +# ============================================================================= +# 로깅 설정 +# ============================================================================= +logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', + handlers=[logging.StreamHandler(sys.stdout)] +) +logger = logging.getLogger(__name__) + +# ============================================================================= +# 환경 변수 설정 +# ============================================================================= +class Config: + """환경 변수 기반 설정 클래스""" + + # 애플리케이션 메타데이터 + APP_TITLE = os.getenv("APP_TITLE", "카카오 API 기반 음식점 수집 서비스") + APP_VERSION = os.getenv("APP_VERSION", "1.0.0") + APP_DESCRIPTION = os.getenv("APP_DESCRIPTION", "카카오 로컬 API를 활용한 음식점 정보 수집 시스템") + + # 서버 설정 + HOST = os.getenv("HOST", "0.0.0.0") + PORT = int(os.getenv("PORT", "8000")) + LOG_LEVEL = os.getenv("LOG_LEVEL", "info") + + # 카카오 API 설정 + KAKAO_API_KEY = os.getenv("KAKAO_API_KEY", "5cdc24407edbf8544f3954cfaa4650c6") + KAKAO_API_URL = "https://dapi.kakao.com/v2/local/search/keyword.json" + + # 검색 설정 + DEFAULT_QUERY = os.getenv("DEFAULT_QUERY", "음식점") + DEFAULT_REGION = os.getenv("DEFAULT_REGION", "서울") + DEFAULT_SIZE = int(os.getenv("DEFAULT_SIZE", "15")) + MAX_SIZE = int(os.getenv("MAX_SIZE", "15")) # 카카오 API 최대값 + MAX_PAGES = int(os.getenv("MAX_PAGES", "45")) # 카카오 API 최대 페이지 (45페이지 * 15 = 675개) + + # 파일 설정 + OUTPUT_FILE = os.getenv("OUTPUT_FILE", "restaurant.json") + DATA_DIR = os.getenv("DATA_DIR", "./data") + + # 요청 제한 설정 + REQUEST_DELAY = float(os.getenv("REQUEST_DELAY", "0.1")) # API 요청 간 지연시간(초) + REQUEST_TIMEOUT = int(os.getenv("REQUEST_TIMEOUT", "30")) + + # 헬스체크 설정 + HEALTH_CHECK_TIMEOUT = int(os.getenv("HEALTH_CHECK_TIMEOUT", "10")) + +config = Config() + +# 데이터 디렉토리 생성 +os.makedirs(config.DATA_DIR, exist_ok=True) + +# FastAPI 앱 초기화 +app = FastAPI( + title=config.APP_TITLE, + description=f""" + {config.APP_DESCRIPTION} + + **주요 기능:** + - 카카오 로컬 API를 활용한 음식점 정보 수집 + - 지역별, 키워드별 검색 지원 + - JSON 파일 자동 저장 기능 + - RESTful API 제공 + - Swagger UI 문서 제공 + + **API 키:** {config.KAKAO_API_KEY[:10]}... + **버전:** {config.APP_VERSION} + """, + version=config.APP_VERSION, + contact={ + "name": "관리자", + "email": "admin@example.com" + } +) + +# ============================================================================= +# Pydantic 모델 정의 +# ============================================================================= + +class RestaurantSearchRequest(BaseModel): + """음식점 검색 요청 모델""" + query: str = Field( + default=config.DEFAULT_QUERY, + description="검색 키워드 (예: 치킨, 피자, 한식)", + example="치킨" + ) + region: str = Field( + default=config.DEFAULT_REGION, + description="검색 지역 (예: 서울, 부산, 대구)", + example="서울" + ) + size: int = Field( + default=config.DEFAULT_SIZE, + description=f"페이지당 결과 수 (1-{config.MAX_SIZE})", + example=15, + ge=1, + le=config.MAX_SIZE + ) + pages: int = Field( + default=5, + description=f"검색할 페이지 수 (1-{config.MAX_PAGES})", + example=5, + ge=1, + le=config.MAX_PAGES + ) + save_to_file: bool = Field( + default=True, + description="결과를 JSON 파일로 저장할지 여부", + example=True + ) + +class RestaurantInfo(BaseModel): + """음식점 정보 모델""" + id: str = Field(description="카카오 장소 ID") + place_name: str = Field(description="장소명") + category_name: str = Field(description="카테고리명") + category_group_code: str = Field(description="카테고리 그룹 코드") + category_group_name: str = Field(description="카테고리 그룹명") + phone: str = Field(description="전화번호") + address_name: str = Field(description="전체 지번 주소") + road_address_name: str = Field(description="전체 도로명 주소") + place_url: str = Field(description="장소 상세페이지 URL") + distance: str = Field(description="중심좌표까지의 거리 (meter)") + x: str = Field(description="X 좌표값, 경위도인 경우 longitude") + y: str = Field(description="Y 좌표값, 경위도인 경우 latitude") + +class CollectionMetadata(BaseModel): + """수집 메타데이터""" + collection_date: str = Field(description="수집 날짜시간") + query: str = Field(description="검색 키워드") + region: str = Field(description="검색 지역") + total_count: int = Field(description="총 수집된 음식점 수") + pages_collected: int = Field(description="수집된 페이지 수") + api_key_used: str = Field(description="사용된 API 키 (마스킹)") + execution_time: float = Field(description="실행 시간(초)") + +class RestaurantSearchResponse(BaseModel): + """음식점 검색 응답 모델""" + success: bool = Field(description="검색 성공 여부") + message: str = Field(description="응답 메시지") + metadata: CollectionMetadata + restaurants: List[RestaurantInfo] + file_saved: bool = Field(description="파일 저장 여부") + file_path: Optional[str] = Field(description="저장된 파일 경로") + +class ErrorResponse(BaseModel): + """에러 응답 모델""" + success: bool = False + error: str + message: str + timestamp: str + +# ============================================================================= +# 카카오 API 클라이언트 +# ============================================================================= + +class KakaoRestaurantCollector: + """카카오 API를 활용한 음식점 수집기""" + + def __init__(self): + self.api_key = config.KAKAO_API_KEY + self.api_url = config.KAKAO_API_URL + self.session = None + logger.info("KakaoRestaurantCollector 초기화 완료") + + async def __aenter__(self): + """비동기 컨텍스트 매니저 진입""" + self.session = aiohttp.ClientSession( + timeout=aiohttp.ClientTimeout(total=config.REQUEST_TIMEOUT), + headers={ + 'Authorization': f'KakaoAK {self.api_key}', + 'Content-Type': 'application/json' + } + ) + return self + + async def __aexit__(self, exc_type, exc_val, exc_tb): + """비동기 컨텍스트 매니저 종료""" + if self.session: + await self.session.close() + + async def search_restaurants(self, query: str, region: str, size: int = 15, pages: int = 5) -> Dict[str, Any]: + """음식점 검색 실행 (개선된 버전)""" + logger.info(f"음식점 검색 시작: query='{query}', region='{region}', size={size}, pages={pages}") + + start_time = datetime.now() + all_restaurants = [] + collected_pages = 0 + empty_page_count = 0 # 연속 빈 페이지 카운터 추가 + + try: + for page in range(1, pages + 1): + logger.info(f"페이지 {page}/{pages} 검색 중...") + + # API 요청 파라미터 - 더 구체적인 검색 + params = { + 'query': f"{query} {region}", + 'category_group_code': 'FD6', # 음식점 카테고리 + 'page': page, + 'size': size, + 'sort': 'accuracy' + } + + try: + async with self.session.get(self.api_url, params=params) as response: + if response.status == 200: + data = await response.json() + documents = data.get('documents', []) + + if not documents: + empty_page_count += 1 + logger.warning(f"페이지 {page}에서 결과 없음 (연속 빈 페이지: {empty_page_count})") + + # 연속 3페이지가 비어있으면 종료 (개선) + if empty_page_count >= 3: + logger.info(f"연속 {empty_page_count}페이지 빈 결과로 검색 종료") + break + + # 빈 페이지여도 계속 진행 + await asyncio.sleep(config.REQUEST_DELAY) + continue + + # 결과가 있으면 빈 페이지 카운터 리셋 + empty_page_count = 0 + + # 음식점 정보 추출 및 저장 + page_restaurants = [] + for doc in documents: + restaurant = self._extract_restaurant_info(doc) + if restaurant: + page_restaurants.append(restaurant) + + all_restaurants.extend(page_restaurants) + collected_pages += 1 + + logger.info(f"페이지 {page} 완료: {len(page_restaurants)}개 음식점 수집 (총: {len(all_restaurants)}개)") + + # API 요청 제한을 위한 지연 + if page < pages: + await asyncio.sleep(config.REQUEST_DELAY) + + elif response.status == 400: + error_data = await response.json() + logger.warning(f"API 요청 오류 (페이지 {page}): {error_data}") + + # 400 오류여도 계속 진행 (다른 페이지는 성공할 수 있음) + empty_page_count += 1 + if empty_page_count >= 5: + break + continue + + elif response.status == 401: + logger.error("API 키 인증 실패") + raise HTTPException(status_code=401, detail="카카오 API 키 인증 실패") + + elif response.status == 429: + logger.warning("API 요청 한도 초과 - 2초 대기 후 재시도") + await asyncio.sleep(2) + continue + + else: + logger.error(f"API 요청 실패: HTTP {response.status}") + empty_page_count += 1 + if empty_page_count >= 5: + break + continue + + except asyncio.TimeoutError: + logger.error(f"페이지 {page} 요청 타임아웃") + empty_page_count += 1 + if empty_page_count >= 5: + break + continue + except Exception as e: + logger.error(f"페이지 {page} 요청 중 오류: {e}") + empty_page_count += 1 + if empty_page_count >= 5: + break + continue + + execution_time = (datetime.now() - start_time).total_seconds() + + # 중복 제거 + + logger.info(f"중복 제거 시작: {len(all_restaurants)}개") + + # 중복 제거 통계 + stats = { + 'total': len(all_restaurants), + 'by_place_url': 0, + 'by_place_id': 0, + 'by_coordinates': 0, + 'duplicates': 0 + } + + unique_restaurants = {} + + for restaurant in all_restaurants: + place_url = restaurant.get('place_url', '').strip() + place_id = restaurant.get('id', '').strip() + place_name = restaurant.get('place_name', '').strip() + x = restaurant.get('x', '').strip() + y = restaurant.get('y', '').strip() + + # 고유 키 생성 (다중 전략) + unique_key = None + + if place_url: + unique_key = f"url:{place_url}" + stats['by_place_url'] += 1 + elif place_id: + unique_key = f"id:{place_id}" + stats['by_place_id'] += 1 + elif place_name and x and y: + unique_key = f"coord:{place_name}:{x}:{y}" + stats['by_coordinates'] += 1 + else: + # 마지막 수단: 이름만으로 + unique_key = f"name:{place_name}" + + if unique_key: + if unique_key not in unique_restaurants: + unique_restaurants[unique_key] = restaurant + else: + stats['duplicates'] += 1 + + final_restaurants = list(unique_restaurants.values()) + + logger.info(f"중복 제거 완료:") + logger.info(f" 총 입력: {stats['total']}개") + logger.info(f" URL 기준: {stats['by_place_url']}개") + logger.info(f" ID 기준: {stats['by_place_id']}개") + logger.info(f" 좌표 기준: {stats['by_coordinates']}개") + logger.info(f" 중복 제거: {stats['duplicates']}개") + logger.info(f" 최종 결과: {len(final_restaurants)}개") + logger.info(f" 중복률: {(stats['duplicates']/stats['total']*100):.1f}%") + + logger.info(f"검색 완료: 총 {len(final_restaurants)}개 음식점 수집 (중복 제거 후), 수집된 페이지: {collected_pages}") + + return { + 'restaurants': final_restaurants, + 'metadata': { + 'collection_date': start_time.isoformat(), + 'query': query, + 'region': region, + 'total_count': len(final_restaurants), + 'pages_collected': collected_pages, + 'pages_requested': pages, + 'api_key_used': f"{self.api_key[:10]}...", + 'execution_time': execution_time + } + } + + except Exception as e: + logger.error(f"음식점 검색 중 오류: {e}") + raise + + def _extract_restaurant_info(self, document: Dict) -> Dict[str, Any]: + """카카오 API 응답에서 음식점 정보 추출""" + try: + return { + 'id': document.get('id', ''), + 'place_name': document.get('place_name', ''), + 'category_name': document.get('category_name', ''), + 'category_group_code': document.get('category_group_code', ''), + 'category_group_name': document.get('category_group_name', ''), + 'phone': document.get('phone', ''), + 'address_name': document.get('address_name', ''), + 'road_address_name': document.get('road_address_name', ''), + 'place_url': document.get('place_url', ''), + 'distance': document.get('distance', ''), + 'x': document.get('x', ''), + 'y': document.get('y', '') + } + except Exception as e: + logger.warning(f"음식점 정보 추출 실패: {e}") + return None + +# ============================================================================= +# 파일 관리 유틸리티 +# ============================================================================= + +def save_restaurants_to_file(data: Dict[str, Any], filename: str = None) -> str: + """음식점 데이터를 JSON 파일로 저장""" + if filename is None: + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + filename = f"restaurants_{timestamp}.json" + + file_path = os.path.join(config.DATA_DIR, filename) + + try: + with open(file_path, 'w', encoding='utf-8') as f: + json.dump(data, f, ensure_ascii=False, indent=2) + + logger.info(f"음식점 데이터 저장 완료: {file_path}") + return file_path + + except Exception as e: + logger.error(f"파일 저장 실패: {e}") + raise + +# ============================================================================= +# API 엔드포인트 +# ============================================================================= + +@app.get("/", response_class=HTMLResponse, include_in_schema=False) +async def root(): + """메인 페이지""" + return f""" + + + {config.APP_TITLE} + + + +
+

🍽️ {config.APP_TITLE}

+

카카오 로컬 API를 활용한 음식점 정보 수집 시스템

+

버전: {config.APP_VERSION}

+
+ +
+

📋 서비스 정보

+ +
+ +
+

⚙️ 환경 설정

+ +
+ +

📚 API 문서

+ Swagger UI 문서 + ReDoc 문서 + 헬스 체크 + +

🛠️ 사용 방법

+

POST /collect - 음식점 정보 수집

+ 
+{{
+  "query": "치킨",
+  "region": "서울",
+  "size": 15,
+  "pages": 5,
+  "save_to_file": true
+}}
+
+ +

GET /download/{filename} - 저장된 파일 다운로드

+ + + """ + +@app.post( + "/collect", + response_model=RestaurantSearchResponse, + summary="음식점 정보 수집", + description=""" + 카카오 로컬 API를 사용하여 지정된 조건의 음식점 정보를 수집합니다. + + **주요 기능:** + - 키워드 및 지역 기반 음식점 검색 + - 페이지네이션 지원 (최대 45페이지) + - JSON 파일 자동 저장 + - 중복 음식점 제거 + + **응답 시간:** 페이지 수에 따라 5초-60초 소요 + """, + responses={ + 200: {"description": "수집 성공", "model": RestaurantSearchResponse}, + 400: {"description": "잘못된 요청", "model": ErrorResponse}, + 401: {"description": "API 키 인증 실패", "model": ErrorResponse}, + 500: {"description": "서버 오류", "model": ErrorResponse} + } +) +async def collect_restaurants(request: RestaurantSearchRequest): + """음식점 정보 수집 API""" + logger.info(f"음식점 수집 요청: {request}") + + try: + async with KakaoRestaurantCollector() as collector: + # 음식점 검색 실행 + result = await collector.search_restaurants( + query=request.query, + region=request.region, + size=request.size, + pages=request.pages + ) + + # 파일 저장 + file_saved = False + file_path = None + + if request.save_to_file: + try: + # 파일명 생성 (쿼리와 지역 포함) + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + safe_query = "".join(c for c in request.query if c.isalnum() or c in (' ', '_')).strip() + safe_region = "".join(c for c in request.region if c.isalnum() or c in (' ', '_')).strip() + filename = f"restaurants_{safe_query}_{safe_region}_{timestamp}.json" + + file_path = save_restaurants_to_file(result, filename) + file_saved = True + + # 기본 파일명으로도 저장 (최신 결과) + default_path = save_restaurants_to_file(result, config.OUTPUT_FILE) + logger.info(f"기본 파일로도 저장: {default_path}") + + except Exception as save_error: + logger.error(f"파일 저장 실패: {save_error}") + file_saved = False + + # 응답 데이터 구성 + response_data = RestaurantSearchResponse( + success=True, + message=f"음식점 정보 수집이 완료되었습니다. (총 {len(result['restaurants'])}개)", + metadata=CollectionMetadata(**result['metadata']), + restaurants=[RestaurantInfo(**r) for r in result['restaurants']], + file_saved=file_saved, + file_path=file_path + ) + + logger.info(f"수집 완료: {len(result['restaurants'])}개 음식점") + return response_data + + except HTTPException: + raise + except Exception as e: + logger.error(f"음식점 수집 실패: {str(e)}") + raise HTTPException( + status_code=500, + detail={ + "success": False, + "error": "COLLECTION_FAILED", + "message": f"음식점 수집 중 오류가 발생했습니다: {str(e)}", + "timestamp": datetime.now().isoformat() + } + ) + +@app.get("/list-files", summary="저장된 파일 목록", description="저장된 음식점 데이터 파일 목록을 반환합니다.") +async def list_files(): + """저장된 파일 목록 조회""" + try: + files = [] + if os.path.exists(config.DATA_DIR): + for filename in os.listdir(config.DATA_DIR): + if filename.endswith('.json'): + file_path = os.path.join(config.DATA_DIR, filename) + file_stat = os.stat(file_path) + + files.append({ + 'filename': filename, + 'size': file_stat.st_size, + 'created': datetime.fromtimestamp(file_stat.st_ctime).isoformat(), + 'modified': datetime.fromtimestamp(file_stat.st_mtime).isoformat(), + 'download_url': f"/download/{filename}" + }) + + files.sort(key=lambda x: x['modified'], reverse=True) + + return { + 'success': True, + 'total_files': len(files), + 'files': files, + 'data_directory': config.DATA_DIR + } + + except Exception as e: + logger.error(f"파일 목록 조회 실패: {e}") + raise HTTPException(status_code=500, detail=f"파일 목록 조회 실패: {str(e)}") + +@app.get("/download/{filename}", summary="파일 다운로드", description="저장된 음식점 데이터 파일을 다운로드합니다.") +async def download_file(filename: str): + """파일 다운로드""" + file_path = os.path.join(config.DATA_DIR, filename) + + if not os.path.exists(file_path): + raise HTTPException(status_code=404, detail="파일을 찾을 수 없습니다.") + + if not filename.endswith('.json'): + raise HTTPException(status_code=400, detail="JSON 파일만 다운로드 가능합니다.") + + return FileResponse( + path=file_path, + filename=filename, + media_type='application/json' + ) + +@app.get("/health", summary="헬스 체크", description="API 서버 상태를 확인합니다.") +async def health_check(): + """헬스 체크""" + return { + "status": "healthy", + "timestamp": datetime.now().isoformat(), + "version": config.APP_VERSION, + "api_key_configured": bool(config.KAKAO_API_KEY), + "data_directory_exists": os.path.exists(config.DATA_DIR), + "message": f"{config.APP_TITLE}이 정상 작동 중입니다." + } + +@app.get("/config", summary="환경 설정 확인", description="현재 적용된 환경 변수 설정을 확인합니다.") +async def get_config(): + """환경 설정 확인""" + return { + "app_info": { + "title": config.APP_TITLE, + "version": config.APP_VERSION, + "description": config.APP_DESCRIPTION + }, + "server_config": { + "host": config.HOST, + "port": config.PORT, + "log_level": config.LOG_LEVEL + }, + "api_config": { + "kakao_api_url": config.KAKAO_API_URL, + "api_key_configured": bool(config.KAKAO_API_KEY), + "api_key_preview": f"{config.KAKAO_API_KEY[:10]}..." if config.KAKAO_API_KEY else None + }, + "search_defaults": { + "default_query": config.DEFAULT_QUERY, + "default_region": config.DEFAULT_REGION, + "default_size": config.DEFAULT_SIZE, + "max_size": config.MAX_SIZE, + "max_pages": config.MAX_PAGES + }, + "file_config": { + "output_file": config.OUTPUT_FILE, + "data_dir": config.DATA_DIR, + "data_dir_exists": os.path.exists(config.DATA_DIR) + }, + "request_config": { + "request_delay": config.REQUEST_DELAY, + "request_timeout": config.REQUEST_TIMEOUT, + "health_check_timeout": config.HEALTH_CHECK_TIMEOUT + }, + "timestamp": datetime.now().isoformat() + } + +# 백그라운드 작업을 위한 예제 (향후 확장용) +@app.post("/collect-background", summary="백그라운드 수집", description="음식점 정보를 백그라운드에서 수집합니다.") +async def collect_restaurants_background(background_tasks: BackgroundTasks, request: RestaurantSearchRequest): + """백그라운드 음식점 수집""" + + async def background_collect(): + try: + logger.info("백그라운드 수집 시작") + async with KakaoRestaurantCollector() as collector: + result = await collector.search_restaurants( + query=request.query, + region=request.region, + size=request.size, + pages=request.pages + ) + + if request.save_to_file: + timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") + filename = f"restaurants_bg_{timestamp}.json" + save_restaurants_to_file(result, filename) + + logger.info(f"백그라운드 수집 완료: {len(result['restaurants'])}개") + + except Exception as e: + logger.error(f"백그라운드 수집 실패: {e}") + + background_tasks.add_task(background_collect) + + return { + "success": True, + "message": "백그라운드 수집이 시작되었습니다.", + "timestamp": datetime.now().isoformat() + } + +if __name__ == "__main__": + print("🍽️ " + "="*60) + print(f" {config.APP_TITLE} 서버 시작") + print("="*64) + print(f"📊 설정 정보:") + print(f" - API 키: {config.KAKAO_API_KEY[:10]}...") + print(f" - 기본 검색어: {config.DEFAULT_QUERY}") + print(f" - 기본 지역: {config.DEFAULT_REGION}") + print(f" - 데이터 저장 경로: {config.DATA_DIR}") + print() + print(f"📚 문서:") + print(f" - Swagger UI: http://{config.HOST}:{config.PORT}/docs") + print(f" - ReDoc: http://{config.HOST}:{config.PORT}/redoc") + print(f" - 메인 페이지: http://{config.HOST}:{config.PORT}/") + print() + + uvicorn.run( + app, + host=config.HOST, + port=config.PORT, + log_level=config.LOG_LEVEL + ) + diff --git a/restaurant/app/requirements.txt b/restaurant/app/requirements.txt new file mode 100644 index 0000000..0b63a4e --- /dev/null +++ b/restaurant/app/requirements.txt @@ -0,0 +1,6 @@ +fastapi==0.104.1 +uvicorn[standard]==0.24.0 +aiohttp==3.9.1 +pydantic==2.5.0 +python-multipart==0.0.6 +python-dotenv==1.0.0 diff --git a/restaurant/build-base.sh b/restaurant/build-base.sh new file mode 100755 index 0000000..d5643e2 --- /dev/null +++ b/restaurant/build-base.sh @@ -0,0 +1,214 @@ +#!/bin/bash +# build-base.sh - Base Image 빌드 스크립트 + +set -e + +# 변수 설정 +BASE_IMAGE_NAME="restaurant-api-base" +BASE_IMAGE_TAG="${1:-latest}" +ACR_NAME="${2:-acrdigitalgarage03}" +RESOURCE_GROUP="${3:-rg-digitalgarage-03}" + +# ACR URL 자동 구성 +if [ -n "${ACR_NAME}" ]; then + REGISTRY="${ACR_NAME}.azurecr.io" + FULL_BASE_IMAGE_NAME="${REGISTRY}/${BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}" +else + FULL_BASE_IMAGE_NAME="${BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}" +fi + +# 고정된 Dockerfile 경로 +BASE_DOCKERFILE_PATH="deployment/container/Dockerfile-base" +BUILD_CONTEXT="." + +echo "=====================================================" +echo " 카카오 API 음식점 수집 서비스 Base Image 빌드" +echo "=====================================================" +echo "Base 이미지명: ${FULL_BASE_IMAGE_NAME}" +if [ -n "${ACR_NAME}" ]; then + echo "ACR 이름: ${ACR_NAME}" + echo "리소스 그룹: ${RESOURCE_GROUP}" +fi +echo "빌드 시작: $(date)" +echo "" + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [BASE_IMAGE_TAG] [ACR_NAME] [RESOURCE_GROUP]" + echo "" + echo "파라미터:" + echo " BASE_IMAGE_TAG: Base 이미지 태그 (기본값: latest)" + echo " ACR_NAME : Azure Container Registry 이름" + echo " RESOURCE_GROUP: Azure 리소스 그룹" + echo "" + echo "예시:" + echo " $0 v1.0.0 # 로컬 빌드만" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 # ACR 빌드 + 푸시" +} + +# ACR 로그인 함수 +acr_login() { + local acr_name="$1" + local resource_group="$2" + + echo "🔐 Azure Container Registry 로그인 중..." + + if ! command -v az &> /dev/null; then + echo "❌ Azure CLI (az)가 설치되지 않았습니다." + exit 1 + fi + + if ! command -v jq &> /dev/null; then + echo "❌ jq가 설치되지 않았습니다." + exit 1 + fi + + if ! az account show &> /dev/null; then + echo "❌ Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 + fi + + local credential_json + credential_json=$(az acr credential show --name "${acr_name}" --resource-group "${resource_group}" 2>/dev/null) + + if [ $? -ne 0 ]; then + echo "❌ ACR credential 조회 실패" + exit 1 + fi + + local username + local password + + username=$(echo "${credential_json}" | jq -r '.username') + password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + + if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + echo "❌ ACR credential 파싱 실패" + exit 1 + fi + + echo "🔐 Docker 로그인 실행 중..." + echo "${password}" | docker login "${REGISTRY}" -u "${username}" --password-stdin + + if [ $? -eq 0 ]; then + echo "✅ ACR 로그인 성공!" + return 0 + else + echo "❌ ACR 로그인 실패" + exit 1 + fi +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -n "${ACR_NAME}" ] && [ -z "${RESOURCE_GROUP}" ]; then + echo "❌ ACR_NAME이 제공된 경우 RESOURCE_GROUP도 필요합니다." + echo "" + show_usage + exit 1 +fi + +# 필수 파일 확인 +echo "📁 필수 파일 확인 중..." + +if [ ! -f "${BASE_DOCKERFILE_PATH}" ]; then + echo "❌ ${BASE_DOCKERFILE_PATH} 파일을 찾을 수 없습니다." + exit 1 +fi + +echo "✅ Base Dockerfile 확인 완료" +echo "📄 Base Dockerfile: ${BASE_DOCKERFILE_PATH}" + +# ACR 로그인 수행 +if [ -n "${ACR_NAME}" ] && [ -n "${RESOURCE_GROUP}" ]; then + echo "" + acr_login "${ACR_NAME}" "${RESOURCE_GROUP}" + echo "" +fi + +# Docker 빌드 +echo "🔨 Base Image 빌드 시작..." +echo "명령어: docker build -t \"${FULL_BASE_IMAGE_NAME}\" -f \"${BASE_DOCKERFILE_PATH}\" \"${BUILD_CONTEXT}\"" + +docker build -t "${FULL_BASE_IMAGE_NAME}" -f "${BASE_DOCKERFILE_PATH}" "${BUILD_CONTEXT}" + +if [ $? -eq 0 ]; then + echo "✅ Base Image 빌드 완료!" + echo "이미지명: ${FULL_BASE_IMAGE_NAME}" + + # 이미지 정보 표시 + echo "" + echo "📊 Base Image 정보:" + docker images "${FULL_BASE_IMAGE_NAME}" --format "table {{.Repository}}\t{{.Tag}}\t{{.Size}}\t{{.CreatedAt}}" + + # latest 태그 추가 생성 + if [ "${BASE_IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo "" + echo "🏷️ latest 태그 생성 중..." + docker tag "${FULL_BASE_IMAGE_NAME}" "${REGISTRY}/${BASE_IMAGE_NAME}:latest" + echo "✅ latest 태그 생성 완료: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + fi + + # ACR 푸시 + if [ -n "${ACR_NAME}" ]; then + echo "" + echo "🚀 ACR에 Base Image 푸시 중..." + + echo "📤 푸시 중: ${FULL_BASE_IMAGE_NAME}" + docker push "${FULL_BASE_IMAGE_NAME}" + + if [ $? -eq 0 ]; then + echo "✅ Base Image 푸시 성공" + + if [ "${BASE_IMAGE_TAG}" != "latest" ]; then + echo "📤 푸시 중: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + docker push "${REGISTRY}/${BASE_IMAGE_NAME}:latest" + + if [ $? -eq 0 ]; then + echo "✅ latest 태그 푸시 성공" + fi + fi + else + echo "❌ Base Image 푸시 실패" + exit 1 + fi + fi + + echo "" + echo "🎉 Base Image 빌드 완료!" + echo "" + echo "📋 완료된 작업:" + echo " ✅ Base Image 빌드: ${FULL_BASE_IMAGE_NAME}" + if [ "${BASE_IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo " ✅ latest 태그: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + fi + if [ -n "${ACR_NAME}" ]; then + echo " ✅ ACR 푸시 완료" + fi + + echo "" + echo "🧪 테스트 명령어:" + echo " docker run --rm ${FULL_BASE_IMAGE_NAME} python --version" + + echo "" + echo "📝 다음 단계:" + echo " 이제 Service Image를 빌드하세요:" + if [ -n "${ACR_NAME}" ]; then + echo " ./build.sh v1.0.0 ${ACR_NAME} ${RESOURCE_GROUP}" + else + echo " ./build.sh v1.0.0" + fi + +else + echo "❌ Base Image 빌드 실패!" + exit 1 +fi + +echo "" +echo "🏁 Base Image 빌드 프로세스 완료 - $(date)" diff --git a/restaurant/build.sh b/restaurant/build.sh new file mode 100755 index 0000000..1caf3b2 --- /dev/null +++ b/restaurant/build.sh @@ -0,0 +1,251 @@ +#!/bin/bash +# build.sh - Service Image 빌드 스크립트 (Base Image 활용) + +set -e + +# 변수 설정 +IMAGE_NAME="restaurant-api" +IMAGE_TAG="${1:-latest}" +ACR_NAME="${2:-acrdigitalgarage03}" +RESOURCE_GROUP="${3:-rg-digitalgarage-03}" +BASE_IMAGE_TAG="${4:-latest}" + +# ACR URL 자동 구성 +if [ -n "${ACR_NAME}" ]; then + REGISTRY="${ACR_NAME}.azurecr.io" + FULL_IMAGE_NAME="${REGISTRY}/${IMAGE_NAME}:${IMAGE_TAG}" + BASE_IMAGE="${REGISTRY}/restaurant-api-base:${BASE_IMAGE_TAG}" +else + FULL_IMAGE_NAME="${IMAGE_NAME}:${IMAGE_TAG}" + BASE_IMAGE="restaurant-api-base:${BASE_IMAGE_TAG}" +fi + +# 고정된 Dockerfile 경로 +DOCKERFILE_PATH="deployment/container/Dockerfile" +BUILD_CONTEXT="." + +echo "=====================================================" +echo " 카카오 API 음식점 수집 서비스 Service Image 빌드" +echo "=====================================================" +echo "Service 이미지명: ${FULL_IMAGE_NAME}" +echo "Base 이미지: ${BASE_IMAGE}" +if [ -n "${ACR_NAME}" ]; then + echo "ACR 이름: ${ACR_NAME}" + echo "리소스 그룹: ${RESOURCE_GROUP}" +fi +echo "빌드 시작: $(date)" +echo "" + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [IMAGE_TAG] [ACR_NAME] [RESOURCE_GROUP] [BASE_IMAGE_TAG]" + echo "" + echo "파라미터:" + echo " IMAGE_TAG : Service 이미지 태그 (기본값: latest)" + echo " ACR_NAME : Azure Container Registry 이름" + echo " RESOURCE_GROUP: Azure 리소스 그룹" + echo " BASE_IMAGE_TAG: Base 이미지 태그 (기본값: latest)" + echo "" + echo "예시:" + echo " $0 v1.0.0 # 로컬 빌드만" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 # ACR 빌드 + 푸시" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 v2.0.0 # 특정 Base Image 사용" + echo "" + echo "전제조건:" + echo " Base Image가 먼저 빌드되어 있어야 합니다:" + echo " ./build-base.sh ${BASE_IMAGE_TAG} [ACR_NAME] [RESOURCE_GROUP]" +} + +# ACR 로그인 함수 +acr_login() { + local acr_name="$1" + local resource_group="$2" + + echo "🔐 Azure Container Registry 로그인 중..." + + if ! command -v az &> /dev/null; then + echo "❌ Azure CLI (az)가 설치되지 않았습니다." + exit 1 + fi + + if ! command -v jq &> /dev/null; then + echo "❌ jq가 설치되지 않았습니다." + exit 1 + fi + + if ! az account show &> /dev/null; then + echo "❌ Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 + fi + + local credential_json + credential_json=$(az acr credential show --name "${acr_name}" --resource-group "${resource_group}" 2>/dev/null) + + if [ $? -ne 0 ]; then + echo "❌ ACR credential 조회 실패" + exit 1 + fi + + local username + local password + + username=$(echo "${credential_json}" | jq -r '.username') + password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + + if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + echo "❌ ACR credential 파싱 실패" + exit 1 + fi + + echo "🔐 Docker 로그인 실행 중..." + echo "${password}" | docker login "${REGISTRY}" -u "${username}" --password-stdin + + if [ $? -eq 0 ]; then + echo "✅ ACR 로그인 성공!" + return 0 + else + echo "❌ ACR 로그인 실패" + exit 1 + fi +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -n "${ACR_NAME}" ] && [ -z "${RESOURCE_GROUP}" ]; then + echo "❌ ACR_NAME이 제공된 경우 RESOURCE_GROUP도 필요합니다." + echo "" + show_usage + exit 1 +fi + +# 필수 파일 확인 +echo "📁 필수 파일 확인 중..." + +if [ ! -f "app/main.py" ]; then + echo "❌ app/main.py 파일을 찾을 수 없습니다." + exit 1 +fi + +if [ ! -f "app/requirements.txt" ]; then + echo "❌ app/requirements.txt 파일을 찾을 수 없습니다." + exit 1 +fi + +if [ ! -f "${DOCKERFILE_PATH}" ]; then + echo "❌ ${DOCKERFILE_PATH} 파일을 찾을 수 없습니다." + exit 1 +fi + +echo "✅ 모든 필수 파일이 확인되었습니다." +echo "📄 Dockerfile: ${DOCKERFILE_PATH}" +echo "🏗️ 빌드 컨텍스트: ${BUILD_CONTEXT}" + +# Base Image 존재 확인 +echo "" +echo "🔍 Base Image 확인 중..." +if docker image inspect "${BASE_IMAGE}" >/dev/null 2>&1; then + echo "✅ Base Image 확인됨: ${BASE_IMAGE}" +else + echo "❌ Base Image를 찾을 수 없습니다: ${BASE_IMAGE}" + echo "" + echo "Base Image를 먼저 빌드하세요:" + if [ -n "${ACR_NAME}" ]; then + echo " ./build-base.sh ${BASE_IMAGE_TAG} ${ACR_NAME} ${RESOURCE_GROUP}" + else + echo " ./build-base.sh ${BASE_IMAGE_TAG}" + fi + exit 1 +fi + +# ACR 로그인 수행 +if [ -n "${ACR_NAME}" ] && [ -n "${RESOURCE_GROUP}" ]; then + echo "" + acr_login "${ACR_NAME}" "${RESOURCE_GROUP}" + echo "" +fi + +# Docker 빌드 +echo "🔨 Service Image 빌드 시작... (빠른 빌드 예상)" +echo "명령어: docker build --build-arg BASE_IMAGE=\"${BASE_IMAGE}\" -t \"${FULL_IMAGE_NAME}\" -f \"${DOCKERFILE_PATH}\" \"${BUILD_CONTEXT}\"" + +docker build --build-arg BASE_IMAGE="${BASE_IMAGE}" -t "${FULL_IMAGE_NAME}" -f "${DOCKERFILE_PATH}" "${BUILD_CONTEXT}" + +if [ $? -eq 0 ]; then + echo "✅ Service Image 빌드 완료!" + echo "이미지명: ${FULL_IMAGE_NAME}" + + # 이미지 정보 표시 + echo "" + echo "📊 Service Image 정보:" + docker images "${FULL_IMAGE_NAME}" --format "table {{.Repository}}\t{{.Tag}}\t{{.Size}}\t{{.CreatedAt}}" + + # latest 태그 추가 생성 + if [ "${IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo "" + echo "🏷️ latest 태그 생성 중..." + docker tag "${FULL_IMAGE_NAME}" "${REGISTRY}/${IMAGE_NAME}:latest" + echo "✅ latest 태그 생성 완료: ${REGISTRY}/${IMAGE_NAME}:latest" + fi + + # ACR 푸시 + if [ -n "${ACR_NAME}" ]; then + echo "" + echo "🚀 ACR에 Service Image 푸시 중..." + + echo "📤 푸시 중: ${FULL_IMAGE_NAME}" + docker push "${FULL_IMAGE_NAME}" + + if [ $? -eq 0 ]; then + echo "✅ Service Image 푸시 성공" + + if [ "${IMAGE_TAG}" != "latest" ]; then + echo "📤 푸시 중: ${REGISTRY}/${IMAGE_NAME}:latest" + docker push "${REGISTRY}/${IMAGE_NAME}:latest" + + if [ $? -eq 0 ]; then + echo "✅ latest 태그 푸시 성공" + fi + fi + else + echo "❌ Service Image 푸시 실패" + exit 1 + fi + fi + + echo "" + echo "🎉 Service Image 빌드 완료!" + echo "" + echo "📋 완료된 작업:" + echo " ✅ Service Image 빌드: ${FULL_IMAGE_NAME}" + echo " ✅ 사용된 Base Image: ${BASE_IMAGE}" + if [ "${IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo " ✅ latest 태그: ${REGISTRY}/${IMAGE_NAME}:latest" + fi + if [ -n "${ACR_NAME}" ]; then + echo " ✅ ACR 푸시 완료" + fi + + echo "" + echo "🧪 테스트 명령어:" + echo " docker run -p 8000:8000 ${FULL_IMAGE_NAME}" + echo " curl http://localhost:8000/health" + + if [ -n "${ACR_NAME}" ]; then + echo "" + echo "🔍 ACR 이미지 확인:" + echo " az acr repository show-tags --name ${ACR_NAME} --repository ${IMAGE_NAME}" + fi + +else + echo "❌ Service Image 빌드 실패!" + exit 1 +fi + +echo "" +echo "🏁 Service Image 빌드 프로세스 완료 - $(date)" diff --git a/restaurant/create-imagepullsecret.sh b/restaurant/create-imagepullsecret.sh new file mode 100755 index 0000000..56ef6cd --- /dev/null +++ b/restaurant/create-imagepullsecret.sh @@ -0,0 +1,237 @@ +#!/bin/bash +# create-imagepullsecret.sh - ACR Image Pull Secret 생성 스크립트 + +set -e + +# 변수 설정 +ACR_NAME="${1:-acrdigitalgarage03}" +RESOURCE_GROUP="${2:-rg-digitalgarage-03}" +SECRET_NAME="${3:-acr-secret}" + +echo "=====================================================" +echo " ACR Image Pull Secret 생성 (Restaurant API)" +echo "=====================================================" + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [ACR_NAME] [RESOURCE_GROUP] [SECRET_NAME]" + echo "" + echo "파라미터:" + echo " ACR_NAME : Azure Container Registry 이름 (필수)" + echo " RESOURCE_GROUP: Azure 리소스 그룹 (필수)" + echo " SECRET_NAME : Secret 이름 (기본값: acr-secret)" + echo "" + echo "예시:" + echo " $0 acrdigitalgarage01 rg-digitalgarage-03" + echo " $0 acrdigitalgarage01 rg-digitalgarage-03 acr-prod-secret" + echo "" +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -z "${ACR_NAME}" ] || [ -z "${RESOURCE_GROUP}" ]; then + echo "❌ ACR_NAME과 RESOURCE_GROUP는 필수 파라미터입니다." + echo "" + show_usage + exit 1 +fi + +# 필수 도구 확인 +echo "🔧 필수 도구 확인 중..." + +if ! command -v az &> /dev/null; then + echo "❌ Azure CLI (az)가 설치되지 않았습니다." + echo "설치 방법: https://docs.microsoft.com/en-us/cli/azure/install-azure-cli" + exit 1 +fi + +if ! command -v kubectl &> /dev/null; then + echo "❌ kubectl이 설치되지 않았습니다." + echo "설치 방법: https://kubernetes.io/docs/tasks/tools/" + exit 1 +fi + +if ! command -v jq &> /dev/null; then + echo "❌ jq가 설치되지 않았습니다." + echo "설치 방법: sudo apt-get install jq" + exit 1 +fi + +echo "✅ 필수 도구 확인 완료" + +# Azure 로그인 확인 +echo "" +echo "🔐 Azure 로그인 상태 확인 중..." + +if ! az account show &> /dev/null; then + echo "❌ Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 +fi + +CURRENT_SUBSCRIPTION=$(az account show --query name -o tsv) +echo "✅ Azure 로그인 확인됨" +echo " 현재 구독: ${CURRENT_SUBSCRIPTION}" + +# Kubernetes 클러스터 연결 확인 +echo "" +echo "☸️ Kubernetes 클러스터 연결 확인 중..." + +if ! kubectl cluster-info &> /dev/null; then + echo "❌ Kubernetes 클러스터에 연결되지 않았습니다." + echo "클러스터 연결 방법:" + echo " az aks get-credentials --resource-group ${RESOURCE_GROUP} --name " + exit 1 +fi + +CURRENT_CONTEXT=$(kubectl config current-context) +echo "✅ Kubernetes 클러스터 연결 확인됨" +echo " 현재 컨텍스트: ${CURRENT_CONTEXT}" + +# ACR 정보 설정 +REGISTRY_URL="${ACR_NAME}.azurecr.io" + +echo "" +echo "📋 설정 정보:" +echo " ACR 이름: ${ACR_NAME}" +echo " 레지스트리 URL: ${REGISTRY_URL}" +echo " 리소스 그룹: ${RESOURCE_GROUP}" +echo " Secret 이름: ${SECRET_NAME}" + +# ACR 존재 확인 +echo "" +echo "🏪 ACR 존재 확인 중..." + +if ! az acr show --name "${ACR_NAME}" --resource-group "${RESOURCE_GROUP}" &> /dev/null; then + echo "❌ ACR을 찾을 수 없습니다." + echo "확인 사항:" + echo " - ACR 이름: ${ACR_NAME}" + echo " - 리소스 그룹: ${RESOURCE_GROUP}" + echo " - ACR이 해당 리소스 그룹에 존재하는지 확인" + exit 1 +fi + +echo "✅ ACR 존재 확인됨: ${ACR_NAME}" + +# ACR credential 조회 +echo "" +echo "🔑 ACR credential 조회 중..." + +credential_json=$(az acr credential show --name "${ACR_NAME}" --resource-group "${RESOURCE_GROUP}" 2>/dev/null) + +if [ $? -ne 0 ]; then + echo "❌ ACR credential 조회 실패" + echo "확인 사항:" + echo " - ACR 이름: ${ACR_NAME}" + echo " - 리소스 그룹: ${RESOURCE_GROUP}" + echo " - ACR에 대한 권한이 있는지 확인" + exit 1 +fi + +# JSON에서 username과 password 추출 +username=$(echo "${credential_json}" | jq -r '.username') +password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + +if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + echo "❌ ACR credential 파싱 실패" + echo "credential JSON:" + echo "${credential_json}" + exit 1 +fi + +echo "✅ ACR credential 조회 성공" +echo " 사용자명: ${username}" +echo " 비밀번호: ${password:0:10}..." + +# 기존 Secret 확인 및 삭제 +echo "" +echo "🔍 기존 Secret 확인 중..." + +if kubectl get secret "${SECRET_NAME}" &> /dev/null; then + echo "🗑️ 기존 Secret 삭제 중..." + kubectl delete secret "${SECRET_NAME}" + echo "✅ 기존 Secret 삭제 완료" +else + echo "✅ 기존 Secret 없음" +fi + +# Image Pull Secret 생성 +echo "" +echo "🔐 Image Pull Secret 생성 중..." + +kubectl create secret docker-registry "${SECRET_NAME}" \ + --docker-server="${REGISTRY_URL}" \ + --docker-username="${username}" \ + --docker-password="${password}" + +if [ $? -eq 0 ]; then + echo "✅ Image Pull Secret 생성 성공!" +else + echo "❌ Image Pull Secret 생성 실패" + exit 1 +fi + +# Secret 정보 확인 +echo "" +echo "📊 생성된 Secret 정보:" +kubectl describe secret "${SECRET_NAME}" + +echo "" +echo "🧪 Secret 테스트 중..." + +# Secret이 올바르게 생성되었는지 확인 +SECRET_TYPE=$(kubectl get secret "${SECRET_NAME}" -o jsonpath='{.type}') +if [ "${SECRET_TYPE}" = "kubernetes.io/dockerconfigjson" ]; then + echo "✅ Secret 타입 확인됨: ${SECRET_TYPE}" +else + echo "❌ Secret 타입 불일치: ${SECRET_TYPE}" +fi + +# Registry URL 확인 +SECRET_REGISTRY=$(kubectl get secret "${SECRET_NAME}" -o jsonpath='{.data.\.dockerconfigjson}' | base64 -d | jq -r ".auths | keys[0]") +if [ "${SECRET_REGISTRY}" = "${REGISTRY_URL}" ]; then + echo "✅ Registry URL 확인됨: ${SECRET_REGISTRY}" +else + echo "❌ Registry URL 불일치: ${SECRET_REGISTRY}" +fi + +echo "" +echo "🎉 ACR Image Pull Secret 생성 완료!" +echo "" +echo "📋 사용 방법:" +echo "" +echo "1. Deployment에서 imagePullSecrets 사용:" +echo " spec:" +echo " template:" +echo " spec:" +echo " imagePullSecrets:" +echo " - name: ${SECRET_NAME}" +echo "" +echo "2. ServiceAccount에 Secret 연결:" +echo " kubectl patch serviceaccount default -p '{\"imagePullSecrets\": [{\"name\": \"${SECRET_NAME}\"}]}'" +echo "" +echo "3. Secret 확인:" +echo " kubectl get secret ${SECRET_NAME}" +echo " kubectl describe secret ${SECRET_NAME}" +echo "" +echo "4. Secret 삭제 (필요시):" +echo " kubectl delete secret ${SECRET_NAME}" +echo "" +echo "🔧 다음 단계:" +echo "1. Deployment 매니페스트에 imagePullSecrets 추가" +echo "2. kubectl apply -f deployment/manifests/deployment.yaml" +echo "3. Pod 상태 확인: kubectl get pods" +echo "" +echo "💡 문제 해결:" +echo "- ErrImagePull 오류 시: Secret 이름과 레지스트리 URL 확인" +echo "- 권한 오류 시: ACR에 대한 적절한 권한 확인" +echo "- 네트워크 오류 시: 클러스터에서 ACR로의 네트워크 연결 확인" + +echo "" +echo "✅ Image Pull Secret 설정이 완료되었습니다!" + diff --git a/restaurant/deployment/container/Dockerfile b/restaurant/deployment/container/Dockerfile new file mode 100644 index 0000000..5eb4255 --- /dev/null +++ b/restaurant/deployment/container/Dockerfile @@ -0,0 +1,46 @@ +# deployment/container/Dockerfile +# Restaurant Collection Service Image +ARG BASE_IMAGE=restaurant-api-base:latest +FROM ${BASE_IMAGE} + +# 메타데이터 +LABEL maintainer="admin@example.com" +LABEL version="1.0.0" +LABEL description="카카오 API 기반 음식점 수집 서비스" + +# root로 전환 (패키지 설치용) +USER root + +# 환경 변수 설정 +ENV HOME=/home/appuser \ + PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 + +# Python 의존성 파일 복사 및 설치 +COPY app/requirements.txt /app/ +RUN pip install --no-cache-dir -r /app/requirements.txt + +# 애플리케이션 소스 복사 +COPY app/main.py /app/ + +# 데이터 디렉토리 생성 및 권한 설정 +RUN mkdir -p /app/data \ + && chown -R appuser:appuser /app \ + && chmod -R 755 /app + +# 비root 사용자로 전환 +USER appuser + +# 작업 디렉토리 설정 +WORKDIR /app + +# 포트 노출 +EXPOSE 18000 + +# 헬스체크 +HEALTHCHECK --interval=30s --timeout=15s --start-period=30s --retries=3 \ + CMD curl -f http://localhost:18000/health || exit 1 + +# 애플리케이션 실행 +CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "18000", "--log-level", "info"] + diff --git a/restaurant/deployment/container/Dockerfile-base b/restaurant/deployment/container/Dockerfile-base new file mode 100644 index 0000000..d7c0ee4 --- /dev/null +++ b/restaurant/deployment/container/Dockerfile-base @@ -0,0 +1,37 @@ +# deployment/container/Dockerfile-base +FROM python:3.11-slim + +# 메타데이터 +LABEL maintainer="admin@example.com" +LABEL description="카카오 API 기반 음식점 수집 서비스 - Base Image" +LABEL version="base-1.0.0" + +# 환경 변수 설정 +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + DEBIAN_FRONTEND=noninteractive + +# 필수 패키지 설치 +RUN apt-get update && apt-get install -y \ + curl \ + wget \ + ca-certificates \ + && rm -rf /var/lib/apt/lists/* + +# 비root 사용자 생성 +RUN groupadd -r appuser && useradd -r -g appuser -d /home/appuser -s /bin/bash appuser \ + && mkdir -p /home/appuser \ + && chown -R appuser:appuser /home/appuser + +# 작업 디렉토리 생성 +WORKDIR /app +RUN chown appuser:appuser /app + +# pip 업그레이드 +RUN pip install --no-cache-dir --upgrade pip + +# 포트 노출 +EXPOSE 8000 + +# 기본 명령어 (오버라이드 가능) +CMD ["python", "--version"] diff --git a/restaurant/deployment/manifest/configmap.yaml b/restaurant/deployment/manifest/configmap.yaml new file mode 100644 index 0000000..a8d8015 --- /dev/null +++ b/restaurant/deployment/manifest/configmap.yaml @@ -0,0 +1,34 @@ +# deployment/manifests/configmap.yaml +apiVersion: v1 +kind: ConfigMap +metadata: + name: restaurant-api-config +data: + # 애플리케이션 설정 + APP_TITLE: "카카오 API 기반 음식점 수집 서비스" + APP_VERSION: "1.0.0" + APP_DESCRIPTION: "카카오 로컬 API를 활용한 음식점 정보 수집 시스템" + + # 서버 설정 + HOST: "0.0.0.0" + PORT: "18000" + LOG_LEVEL: "info" + + # 카카오 API 설정 + KAKAO_API_URL: "https://dapi.kakao.com/v2/local/search/keyword.json" + + # 검색 기본값 + DEFAULT_QUERY: "음식점" + DEFAULT_REGION: "서울" + DEFAULT_SIZE: "15" + MAX_SIZE: "15" + MAX_PAGES: "45" + + # 파일 설정 + OUTPUT_FILE: "restaurant.json" + DATA_DIR: "/app/data" + + # 요청 제한 설정 + REQUEST_DELAY: "0.1" + REQUEST_TIMEOUT: "30" + HEALTH_CHECK_TIMEOUT: "10" diff --git a/restaurant/deployment/manifest/deployment.yaml b/restaurant/deployment/manifest/deployment.yaml new file mode 100644 index 0000000..21d119e --- /dev/null +++ b/restaurant/deployment/manifest/deployment.yaml @@ -0,0 +1,81 @@ +# deployment/manifests/deployment.yaml +apiVersion: apps/v1 +kind: Deployment +metadata: + name: restaurant-api + labels: + app: restaurant-api + version: v1 +spec: + replicas: 1 + selector: + matchLabels: + app: restaurant-api + template: + metadata: + labels: + app: restaurant-api + version: v1 + spec: + imagePullSecrets: + - name: acr-secret + containers: + - name: api + image: acrdigitalgarage03.azurecr.io/restaurant-api:latest + imagePullPolicy: Always + ports: + - containerPort: 18000 + name: http + + # ConfigMap 환경 변수 + envFrom: + - configMapRef: + name: restaurant-api-config + + # Secret 환경 변수 + env: + - name: KAKAO_API_KEY + valueFrom: + secretKeyRef: + name: restaurant-api-secret + key: KAKAO_API_KEY + + # 리소스 제한 + resources: + requests: + memory: "512Mi" + cpu: "250m" + limits: + memory: "1Gi" + cpu: "500m" + + # 헬스 체크 + livenessProbe: + httpGet: + path: /health + port: 18000 + initialDelaySeconds: 30 + periodSeconds: 30 + timeoutSeconds: 10 + failureThreshold: 3 + + readinessProbe: + httpGet: + path: /health + port: 18000 + initialDelaySeconds: 10 + periodSeconds: 10 + timeoutSeconds: 5 + failureThreshold: 3 + + # 볼륨 마운트 (데이터 저장용) + volumeMounts: + - name: data-volume + mountPath: /app/data + + # 볼륨 정의 + volumes: + - name: data-volume + emptyDir: {} + + restartPolicy: Always diff --git a/restaurant/deployment/manifest/ingress.yaml b/restaurant/deployment/manifest/ingress.yaml new file mode 100644 index 0000000..11765ed --- /dev/null +++ b/restaurant/deployment/manifest/ingress.yaml @@ -0,0 +1,38 @@ +# deployment/manifests/ingress.yaml +apiVersion: networking.k8s.io/v1 +kind: Ingress +metadata: + name: restaurant-api-ingress + annotations: + nginx.ingress.kubernetes.io/rewrite-target: / + nginx.ingress.kubernetes.io/ssl-redirect: "false" + nginx.ingress.kubernetes.io/proxy-body-size: "10m" + # 타임아웃 설정 (API 수집 시간 고려) + nginx.ingress.kubernetes.io/proxy-read-timeout: "300" + nginx.ingress.kubernetes.io/proxy-send-timeout: "300" + nginx.ingress.kubernetes.io/client-body-timeout: "300" + nginx.ingress.kubernetes.io/proxy-connect-timeout: "60" + # CORS 설정 + nginx.ingress.kubernetes.io/enable-cors: "true" + nginx.ingress.kubernetes.io/cors-allow-origin: "*" + nginx.ingress.kubernetes.io/cors-allow-methods: "GET, POST, OPTIONS" + nginx.ingress.kubernetes.io/cors-allow-headers: "DNT,User-Agent,X-Requested-With,If-Modified-Since,Cache-Control,Content-Type,Range,Authorization" +spec: + ingressClassName: nginx + rules: + # 환경에 맞게 호스트명 수정 필요 + - host: restaurant-api.20.249.191.180.nip.io + http: + paths: + - path: / + pathType: Prefix + backend: + service: + name: restaurant-api-service + port: + number: 80 + # TLS 설정 (HTTPS 필요시 주석 해제) + # tls: + # - hosts: + # - restaurant-api.example.com + # secretName: restaurant-api-tls diff --git a/restaurant/deployment/manifest/secret.yaml b/restaurant/deployment/manifest/secret.yaml new file mode 100644 index 0000000..b8faf24 --- /dev/null +++ b/restaurant/deployment/manifest/secret.yaml @@ -0,0 +1,10 @@ +# deployment/manifests/secret.yaml +apiVersion: v1 +kind: Secret +metadata: + name: restaurant-api-secret +type: Opaque +data: + # 카카오 API 키 (Base64 인코딩 필요) + # echo -n "5cdc24407edbf8544f3954cfaa4650c6" | base64 + KAKAO_API_KEY: NWNkYzI0NDA3ZWRiZjg1NDRmMzk1NGNmYWE0NjUwYzY= diff --git a/restaurant/deployment/manifest/service.yaml b/restaurant/deployment/manifest/service.yaml new file mode 100644 index 0000000..017694d --- /dev/null +++ b/restaurant/deployment/manifest/service.yaml @@ -0,0 +1,16 @@ +# deployment/manifests/service.yaml +apiVersion: v1 +kind: Service +metadata: + name: restaurant-api-service + labels: + app: restaurant-api +spec: + type: ClusterIP + ports: + - port: 80 + targetPort: 18000 + protocol: TCP + name: http + selector: + app: restaurant-api diff --git a/restaurant/setup.sh b/restaurant/setup.sh new file mode 100755 index 0000000..6f4250e --- /dev/null +++ b/restaurant/setup.sh @@ -0,0 +1,212 @@ +#!/bin/bash +# setup.sh - Restaurant API 환경 설정 스크립트 + +set -e + +echo "🍽️ Restaurant API 환경 설정 시작..." + +# 시스템 정보 확인 +echo "📊 시스템 정보:" +echo " - OS: $(lsb_release -d | cut -f2)" +echo " - Python: $(python3 --version 2>/dev/null || echo 'Python3 미설치')" +echo " - pip: $(pip3 --version 2>/dev/null || echo 'pip3 미설치')" + +# 필수 패키지 설치 +echo "" +echo "📦 필수 패키지 설치 중..." +sudo apt update +sudo apt install -y python3-pip python3-venv curl wget jq + +# Python 버전 확인 +PYTHON_VERSION=$(python3 -c "import sys; print('.'.join(map(str, sys.version_info[:2])))") +echo "📍 Python 버전: ${PYTHON_VERSION}" + +if [ "$(echo "${PYTHON_VERSION} < 3.8" | bc)" -eq 1 ]; then + echo "⚠️ Python 3.8 이상이 권장됩니다." +fi + +# Python 가상환경 설정 +echo "" +echo "🐍 Python 가상환경 설정 중..." +if [ ! -d "venv" ]; then + python3 -m venv venv + echo "✅ 가상환경 생성 완료" +else + echo "✅ 기존 가상환경 발견" +fi + +# 가상환경 활성화 및 라이브러리 설치 +echo "📚 Python 라이브러리 설치 중..." +source venv/bin/activate + +# pip 업그레이드 +pip install --upgrade pip + +# 필요한 라이브러리 설치 +if [ -f "app/requirements.txt" ]; then + pip install -r app/requirements.txt + echo "✅ requirements.txt에서 라이브러리 설치 완료" +else + echo "⚠️ app/requirements.txt 파일을 찾을 수 없습니다." + echo "🔧 기본 라이브러리들을 직접 설치합니다..." + pip install fastapi uvicorn aiohttp pydantic python-multipart python-dotenv +fi + +# 데이터 디렉토리 생성 +echo "" +echo "📁 데이터 디렉토리 설정 중..." +mkdir -p data +chmod 755 data +echo "✅ 데이터 디렉토리 생성: $(pwd)/data" + +# 환경변수 파일 생성 (예시) +echo "" +echo "⚙️ 환경변수 파일 생성 중..." +cat > .env << EOF +# 카카오 API 설정 +KAKAO_API_KEY=5cdc24407edbf8544f3954cfaa4650c6 + +# 서버 설정 +HOST=0.0.0.0 +PORT=18000 +LOG_LEVEL=info + +# 기본 검색 설정 +DEFAULT_QUERY=음식점 +DEFAULT_REGION=서울 +DEFAULT_SIZE=15 +MAX_PAGES=10 + +# 파일 설정 +OUTPUT_FILE=restaurant.json +DATA_DIR=./data + +# 요청 설정 +REQUEST_DELAY=0.1 +REQUEST_TIMEOUT=30 +EOF + echo "✅ .env 파일 생성 완료" + +# 네트워크 연결 테스트 +echo "" +echo "🌐 네트워크 연결 테스트 중..." + +# 카카오 API 연결 테스트 +if curl -s --connect-timeout 5 "https://dapi.kakao.com" > /dev/null; then + echo "✅ 카카오 API 서버 연결 가능" +else + echo "❌ 카카오 API 서버 연결 실패" + echo " 인터넷 연결 상태를 확인해주세요." +fi + +# API 키 유효성 간단 테스트 +echo "" +echo "🔑 API 키 유효성 테스트 중..." +API_KEY="5cdc24407edbf8544f3954cfaa4650c6" +TEST_RESPONSE=$(curl -s -w "%{http_code}" -o /dev/null \ + -H "Authorization: KakaoAK ${API_KEY}" \ + --data-urlencode "query=카카오프렌즈&size=1" \ + "https://dapi.kakao.com/v2/local/search/keyword.json") + +if [ "${TEST_RESPONSE}" = "200" ]; then + echo "✅ API 키 유효성 확인 완료" +elif [ "${TEST_RESPONSE}" = "401" ]; then + echo "❌ API 키 인증 실패" + echo " .env 파일의 KAKAO_API_KEY를 확인해주세요." +elif [ "${TEST_RESPONSE}" = "000" ]; then + echo "⚠️ 네트워크 연결 문제로 API 키 테스트 불가" +else + echo "⚠️ API 키 테스트 실패 (HTTP ${TEST_RESPONSE})" +fi + +# .env 파일 로딩 테스트 +echo "" +echo "🔧 .env 파일 로딩 테스트 중..." +python3 -c " +from dotenv import load_dotenv +import os +load_dotenv() +port = os.getenv('PORT', '8000') +data_dir = os.getenv('DATA_DIR', './data') +print(f'✅ .env 파일 로딩 성공') +print(f' - PORT: {port}') +print(f' - DATA_DIR: {data_dir}') +" 2>/dev/null && echo "✅ python-dotenv 동작 확인" || echo "❌ python-dotenv 설치 필요: pip install python-dotenv" + +# Docker 설치 확인 (선택사항) +echo "" +echo "🐳 Docker 설치 확인 중..." +if command -v docker &> /dev/null; then + DOCKER_VERSION=$(docker --version) + echo "✅ Docker 설치됨: ${DOCKER_VERSION}" + + # Docker 권한 확인 + if docker ps &> /dev/null; then + echo "✅ Docker 권한 확인됨" + else + echo "⚠️ Docker 권한 없음. 다음 명령어로 권한을 추가하세요:" + echo " sudo usermod -aG docker $USER" + echo " newgrp docker" + fi +else + echo "⚠️ Docker가 설치되지 않음 (컨테이너 배포 시 필요)" + echo " 설치 방법: https://docs.docker.com/engine/install/ubuntu/" +fi + +# 방화벽 설정 확인 +echo "" +echo "🔥 방화벽 설정 확인 중..." +if command -v ufw &> /dev/null; then + UFW_STATUS=$(sudo ufw status | head -n1 | awk '{print $2}') + if [ "${UFW_STATUS}" = "active" ]; then + echo "🔥 UFW 방화벽 활성화됨" + if sudo ufw status | grep -q "18000"; then + echo "✅ 포트 18000 방화벽 규칙 확인됨" + else + echo "⚠️ 포트 18000 방화벽 규칙 없음" + echo " 다음 명령어로 포트를 열어주세요:" + echo " sudo ufw allow 18000" + fi + else + echo "✅ UFW 방화벽 비활성화됨" + fi +else + echo "✅ UFW 방화벽 미설치" +fi + +echo "" +echo "🎉 환경 설정 완료!" +echo "" +echo "📋 다음 단계:" +echo "1. 가상환경 활성화:" +echo " source venv/bin/activate" +echo "" +echo "2. 애플리케이션 실행:" +echo " python app/main.py" +echo " 또는" +echo " uvicorn app.main:app --host 0.0.0.0 --port 18000 --reload" +echo "" +echo "3. 웹 브라우저에서 접속:" +echo " http://localhost:18000 (메인 페이지)" +echo " http://localhost:18000/docs (Swagger UI)" +echo " http://localhost:18000/health (헬스체크)" +echo "" +echo "4. API 테스트:" +echo " curl -X POST \"http://localhost:18000/collect\" \\" +echo " -H \"Content-Type: application/json\" \\" +echo " -d '{\"query\":\"치킨\",\"region\":\"서울\",\"pages\":2}'" +echo "" +echo "💡 문제 발생 시:" +echo " - 로그 확인: tail -f 로그파일" +echo " - 환경변수 확인: cat .env" +echo " - .env 로딩 확인: python -c \"from dotenv import load_dotenv; load_dotenv(); import os; print(os.getenv('PORT'))\"" +echo " - 네트워크 확인: curl https://dapi.kakao.com" +echo "" +echo "🔧 설정 파일 위치:" +echo " - 환경변수: $(pwd)/.env" +echo " - 데이터 저장: $(pwd)/data/" +echo " - 애플리케이션: $(pwd)/app/" + +deactivate 2>/dev/null || true +echo "" +echo "✅ 환경 설정이 완료되었습니다!" \ No newline at end of file diff --git a/review/README.md b/review/README.md new file mode 100644 index 0000000..efaca99 --- /dev/null +++ b/review/README.md @@ -0,0 +1,480 @@ +# 카카오맵 리뷰 분석 서비스 (교육용) + +AI 기반 리뷰 분석을 통해 소상공인의 고객 피드백 관리를 지원하는 RESTful API 서비스입니다. + +## ⚠️ 중요 법적 경고사항 + +**이 서비스는 교육 목적으로만 제작되었습니다.** + +### 법적 위험 +- 카카오 이용약관 위반 → 계정 정지, 법적 조치 +- 개인정보보호법(PIPA) 위반 → 과태료 최대 3억원 +- 저작권 및 데이터베이스권 침해 → 손해배상 +- 업무방해죄 → 5년 이하 징역 또는 1천500만원 이하 벌금 + +### 합법적 대안 +- **카카오 공식 API 활용** ([developers.kakao.com](https://developers.kakao.com)) +- 점주 대상 자체 가게 관리 서비스 개발 +- 사용자 동의 기반 데이터 수집 앱 +- 카카오와 정식 파트너십 체결 + +**실제 서비스 사용을 금지합니다!** + +--- + +## 📋 프로젝트 개요 + +### 주요 기능 +- 🔍 **카카오맵 리뷰 분석**: HTML 파싱 및 Selenium 기반 동적 수집 +- 🤖 **AI 기반 피드백**: Claude API 연동을 통한 맞춤형 개선 방안 제시 +- 📊 **감정 분석**: 긍정/부정/중립 감정 분류 및 통계 +- 💾 **Vector DB 연동**: 유사 케이스 검색 및 템플릿 활용 +- 🚀 **RESTful API 제공**: FastAPI 기반의 완전한 API 서비스 +- 📚 **Swagger UI 지원**: 자동 생성되는 API 문서 +- ☸️ **Kubernetes 배포**: 완전한 컨테이너 오케스트레이션 지원 +- 🔧 **환경변수 설정**: ConfigMap과 Secret을 통한 유연한 설정 관리 + +### 기술 스택 +- **Backend**: Python 3.11, FastAPI, aiohttp +- **Web Scraping**: Selenium, BeautifulSoup4, Chrome WebDriver +- **AI/ML**: Claude AI API, Vector DB (Chroma) +- **Database**: PostgreSQL (향후), Vector DB +- **Container**: Docker, Multi-stage build +- **Orchestration**: Kubernetes (AKS) +- **Registry**: Azure Container Registry (ACR) +- **Documentation**: Swagger UI, ReDoc + +## 🏗️ 프로젝트 구조 + +``` +review-api/review/ +├── app/ # 애플리케이션 소스 +│ ├── main.py # 메인 애플리케이션 +│ └── requirements.txt # Python 의존성 +├── deployment/ # 배포 관련 파일 +│ ├── container/ # 컨테이너 이미지 빌드 +│ │ ├── Dockerfile # 서비스 이미지 빌드 +│ │ └── Dockerfile-base # 베이스 이미지 빌드 +│ └── manifests/ # Kubernetes 매니페스트 +│ ├── configmap.yaml # 환경 설정 +│ ├── secret.yaml # 민감 정보 (API 키) +│ ├── deployment.yaml # 애플리케이션 배포 +│ ├── service.yaml # 서비스 노출 +│ └── ingress.yaml # 외부 접근 +├── build-base.sh # 베이스 이미지 빌드 스크립트 +├── build.sh # 서비스 이미지 빌드 스크립트 +├── create-imagepullsecret.sh # ACR 인증 설정 스크립트 +├── setup.sh # 로컬 환경 설정 스크립트 +└── README.md # 프로젝트 문서 +``` + +## 🚀 빠른 시작 + +### 1. 로컬 개발 환경 설정 + +```bash +# 저장소 클론 (review-api/review 디렉토리로 이동) +cd review-api/review + +# 환경 설정 스크립트 실행 +chmod +x setup.sh +./setup.sh + +# 가상환경 활성화 +source venv/bin/activate + +# 애플리케이션 실행 +python app/main.py +``` + +### 2. 로컬 웹 브라우저 접속 + +```bash +# 애플리케이션이 정상 실행된 후 아래 URL로 접속 +``` + +- **메인 페이지**: http://localhost:19000 +- **Swagger UI**: http://localhost:19000/docs +- **ReDoc**: http://localhost:19000/redoc +- **헬스체크**: http://localhost:19000/health +- **진단 정보**: http://localhost:19000/diagnostic +- **법적 경고**: http://localhost:19000/legal-warning + +### 3. API 테스트 (교육용) + +```bash +# 기본 리뷰 분석 (교육용 - 실제 사용 금지) +curl -X POST "http://localhost:19000/analyze" \ + -H "Content-Type: application/json" \ + -d '{ + "store_id": "501745730", + "days_limit": 7, + "max_time": 300 + }' + +# 환경 설정 확인 +curl "http://localhost:19000/config" + +# 법적 경고사항 확인 +curl "http://localhost:19000/legal-warning" +``` + +## 🐳 Docker 컨테이너 실행 + +### 베이스 이미지 빌드 + +```bash +# ACR에 베이스 이미지 빌드 및 푸시 +./build-base.sh latest acrdigitalgarage03 rg-digitalgarage-03 +``` + +### 서비스 이미지 빌드 + +```bash +# ACR에 서비스 이미지 빌드 및 푸시 +./build.sh latest acrdigitalgarage03 rg-digitalgarage-03 +``` + +### 로컬 Docker 실행 + +```bash +# 컨테이너 실행 +docker run -p 19000:19000 \ + -e APP_TITLE="카카오맵 리뷰 분석 API" \ + -e PORT=19000 \ + kakao-review-api:latest + +# 백그라운드 실행 +docker run -d -p 19000:19000 \ + --name kakao-review-api \ + -e PORT=19000 \ + kakao-review-api:latest +``` + +## ☸️ Kubernetes 배포 + +### 1. ACR Image Pull Secret 생성 + +```bash +# Image Pull Secret 생성 +./create-imagepullsecret.sh acrdigitalgarage03 rg-digitalgarage-03 +``` + +### 2. Kubernetes 리소스 배포 + +```bash +# ConfigMap 및 Secret 적용 +kubectl apply -f deployment/manifests/configmap.yaml +kubectl apply -f deployment/manifests/secret.yaml + +# 애플리케이션 배포 +kubectl apply -f deployment/manifests/deployment.yaml +kubectl apply -f deployment/manifests/service.yaml +kubectl apply -f deployment/manifests/ingress.yaml +``` + +### 3. 배포 상태 확인 + +```bash +# Pod 상태 확인 +kubectl get pods -l app=kakao-review-api + +# 서비스 상태 확인 +kubectl get svc kakao-review-api-service + +# Ingress 상태 확인 +kubectl get ingress kakao-review-api-ingress + +# 로그 확인 +kubectl logs -l app=kakao-review-api -f +``` + +### 4. 🌐 외부 브라우저에서 접속하기 + +#### Ingress 주소 확인 방법 + +```bash +# 1. Ingress 설정된 호스트 확인 +kubectl get ingress kakao-review-api-ingress -o jsonpath='{.spec.rules[0].host}' + +# 2. Ingress External IP 확인 (LoadBalancer 타입인 경우) +kubectl get ingress kakao-review-api-ingress + +# 3. Ingress Controller의 External IP 확인 +kubectl get svc -n ingress-nginx ingress-nginx-controller + +# 4. 현재 설정된 ingress 주소 확인 +INGRESS_HOST=$(kubectl get ingress kakao-review-api-ingress -o jsonpath='{.spec.rules[0].host}') +echo "🌐 Review API URL: http://${INGRESS_HOST}" +``` + +#### 브라우저 접속 주소 + +현재 설정된 주소로 접속하세요: + +```bash +# 현재 설정된 기본 주소 (환경에 따라 다를 수 있음) +INGRESS_URL="http://kakao-review-api.20.249.191.180.nip.io" +echo "브라우저에서 접속: ${INGRESS_URL}" +``` + +**주요 접속 페이지:** +- **🏠 메인 페이지**: http://kakao-review-api.20.249.191.180.nip.io +- **📖 Swagger UI**: http://kakao-review-api.20.249.191.180.nip.io/docs +- **📄 ReDoc**: http://kakao-review-api.20.249.191.180.nip.io/redoc +- **❤️ 헬스체크**: http://kakao-review-api.20.249.191.180.nip.io/health +- **🔧 진단 정보**: http://kakao-review-api.20.249.191.180.nip.io/diagnostic +- **⚠️ 법적 경고**: http://kakao-review-api.20.249.191.180.nip.io/legal-warning + +#### 접속 테스트 + +```bash +# API 접속 테스트 +curl "http://kakao-review-api.20.249.191.180.nip.io/health" + +# 설정 정보 확인 +curl "http://kakao-review-api.20.249.191.180.nip.io/config" + +# Swagger UI 접속 확인 +curl -I "http://kakao-review-api.20.249.191.180.nip.io/docs" + +# 법적 경고 확인 +curl "http://kakao-review-api.20.249.191.180.nip.io/legal-warning" +``` + +## ⚙️ 환경 설정 + +### 환경 변수 + +| 변수명 | 기본값 | 설명 | +|--------|--------|------| +| `APP_TITLE` | `카카오맵 리뷰 분석 API` | 애플리케이션 제목 | +| `APP_VERSION` | `1.0.1` | 애플리케이션 버전 | +| `HOST` | `0.0.0.0` | 서버 호스트 | +| `PORT` | `19000` | 서버 포트 | +| `DEFAULT_MAX_TIME` | `300` | 기본 최대 스크롤 시간(초) | +| `DEFAULT_DAYS_LIMIT` | `60` | 기본 날짜 제한(일) | +| `MAX_DAYS_LIMIT` | `365` | 최대 날짜 제한(일) | +| `CHROME_OPTIONS` | `--headless...` | Chrome 브라우저 옵션 | +| `LEGAL_WARNING_ENABLED` | `true` | 법적 경고 표시 여부 | +| `CONTACT_EMAIL` | `admin@example.com` | 연락처 이메일 | + +### Chrome 및 Selenium 설정 + +현재 서비스는 Chrome WebDriver를 사용합니다: + +```bash +# Chrome 설치 확인 +google-chrome --version + +# ChromeDriver 설치 확인 +chromedriver --version + +# Selenium 테스트 +python -c "from selenium import webdriver; print('Selenium 설치됨')" +``` + +## 📊 API 엔드포인트 + +### 주요 엔드포인트 + +| Method | Endpoint | 설명 | +|--------|----------|------| +| `GET` | `/` | 메인 페이지 | +| `GET` | `/docs` | Swagger UI 문서 | +| `GET` | `/health` | 헬스체크 | +| `GET` | `/diagnostic` | 시스템 진단 정보 | +| `POST` | `/analyze` | 리뷰 분석 수행 (교육용) | +| `GET` | `/config` | 환경 설정 확인 | +| `GET` | `/legal-warning` | 법적 경고사항 | + +### 리뷰 분석 API 예시 (교육용) + +```json +POST /analyze +{ + "store_id": "501745730", + "days_limit": 7, + "max_time": 300 +} +``` + +**응답:** +```json +{ + "success": true, + "message": "분석이 성공적으로 완료되었습니다.", + "store_info": { + "id": "501745730", + "name": "맛있는 식당", + "category": "한식", + "rating": "4.2", + "review_count": "1,234" + }, + "reviews": [...], + "analysis_date": "2024-06-12T10:30:00", + "total_reviews": 25, + "execution_time": 45.2 +} +``` + +## 🔧 개발 및 확장 + +### 로컬 개발 + +```bash +# 개발 모드로 실행 (자동 재시작) +uvicorn app.main:app --host 0.0.0.0 --port 19000 --reload + +# 의존성 추가 +pip install 새패키지명 +pip freeze > app/requirements.txt + +# 코드 포맷팅 +black app/main.py +flake8 app/main.py +``` + +### Ingress 호스트 변경 + +현재 환경에 맞게 Ingress 호스트를 변경하려면: + +```bash +# 1. 현재 External IP 확인 +kubectl get svc -n ingress-nginx ingress-nginx-controller + +# 2. deployment/manifests/ingress.yaml 파일에서 host 수정 +# 예: kakao-review-api.{YOUR_EXTERNAL_IP}.nip.io + +# 3. 변경사항 적용 +kubectl apply -f deployment/manifests/ingress.yaml + +# 4. 새로운 주소 확인 +kubectl get ingress kakao-review-api-ingress +``` + +## 🐛 문제 해결 + +### 일반적인 문제 + +**1. Chrome WebDriver 관련 문제** +```bash +# Chrome 설치 상태 확인 +docker run --rm kakao-review-api:latest google-chrome --version + +# ChromeDriver 버전 확인 +docker run --rm kakao-review-api:latest chromedriver --version + +# 헤드리스 모드 테스트 +curl -X POST "http://localhost:19000/analyze" \ + -H "Content-Type: application/json" \ + -d '{"store_id": "test", "days_limit": 1, "max_time": 30}' +``` + +**2. Kubernetes 배포 실패** +```bash +# Pod 로그 확인 (Chrome 에러 확인) +kubectl logs -l app=kakao-review-api + +# ConfigMap 확인 +kubectl get configmap kakao-review-api-config -o yaml + +# 리소스 사용량 확인 (Chrome이 메모리를 많이 사용함) +kubectl top pods -l app=kakao-review-api +``` + +**3. Ingress 접속 실패** +```bash +# Ingress Controller 상태 확인 +kubectl get pods -n ingress-nginx + +# Ingress 규칙 확인 +kubectl describe ingress kakao-review-api-ingress + +# Service 연결 확인 +kubectl get endpoints kakao-review-api-service + +# 타임아웃 설정 확인 (Chrome 분석은 시간이 오래 걸림) +kubectl get ingress kakao-review-api-ingress -o yaml | grep timeout +``` + +**4. 포트 관련 문제** +- 로컬 개발: 19000번 포트 사용 +- Docker 컨테이너: 19000번 포트로 실행 +- Kubernetes: 19000번 포트로 실행 (Service에서 80번으로 노출, Ingress를 통해 외부 접근) + +**5. 법적 문제 회피** +```bash +# 법적 경고 항상 확인 +curl "http://kakao-review-api.20.249.191.180.nip.io/legal-warning" + +# 교육용임을 명시하는 환경변수 설정 +export LEGAL_WARNING_ENABLED=true +export EDUCATIONAL_USE_ONLY=true +``` + +## 🎯 성능 최적화 + +### Chrome 최적화 설정 + +```yaml +# deployment.yaml에서 Chrome 최적화를 위한 리소스 설정 +resources: + requests: + memory: "1Gi" # Chrome은 메모리를 많이 사용 + cpu: "500m" + limits: + memory: "2Gi" # Chrome 분석을 위한 충분한 메모리 + cpu: "1000m" +``` + +### 타임아웃 설정 + +```yaml +# ingress.yaml에서 긴 분석 시간을 고려한 타임아웃 +nginx.ingress.kubernetes.io/proxy-read-timeout: "1800" # 30분 +nginx.ingress.kubernetes.io/proxy-send-timeout: "1800" # 30분 +``` + +## 📈 향후 확장 계획 + +- [ ] **Claude AI 연동**: 리뷰 분석 및 개선 방안 자동 생성 +- [ ] **Vector DB 구축**: 유사 케이스 검색 및 템플릿 관리 +- [ ] **PostgreSQL 연동**: 분석 결과 영구 저장 +- [ ] **다중 플랫폼 지원**: 네이버, 구글 등 추가 플랫폼 (합법적 방법으로) +- [ ] **실시간 분석**: WebSocket 기반 실시간 피드백 +- [ ] **사용자 인증**: JWT 기반 인증 시스템 +- [ ] **대시보드**: 분석 결과 시각화 +- [ ] **알림 시스템**: 새로운 리뷰 알림 기능 +- [ ] **감정 분석 고도화**: 더 정확한 감정 분류 +- [ ] **비즈니스 통찰**: AI 기반 개선 방안 제시 + +## ⚖️ 법적 준수 사항 + +### 필수 확인 사항 + +1. **교육용 목적으로만 사용** +2. **실제 서비스 환경에서 사용 금지** +3. **카카오 이용약관 준수** +4. **개인정보보호법 준수** +5. **저작권 침해 금지** + +### 권장 대안 + +1. **카카오 공식 API 사용** +2. **자체 플랫폼 개발** +3. **사용자 동의 기반 수집** +4. **정식 파트너십 체결** + +--- + +## 📞 지원 및 문의 + +- **이슈 리포트**: GitHub Issues +- **기술 문의**: 개발팀 Slack +- **법적 문의**: 법무팀 +- **API 문서**: Swagger UI에서 상세 확인 + +--- + +**⚠️ 재고지: 이 서비스는 교육용으로만 제작되었으며, 실제 운영 환경에서의 사용을 엄격히 금지합니다.** diff --git a/review/app/main.py b/review/app/main.py new file mode 100644 index 0000000..29969c4 --- /dev/null +++ b/review/app/main.py @@ -0,0 +1,1626 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +카카오맵 리뷰 분석 API (로깅 강화 버전) +ConfigMap과 Secret을 활용한 Kubernetes 배포용 + +app/main.py +""" + +import os +from fastapi import FastAPI, HTTPException, BackgroundTasks +from fastapi.responses import HTMLResponse +from pydantic import BaseModel, Field +from typing import Optional, List, Dict, Any +import asyncio +import threading +import json +from datetime import datetime, timedelta +import logging +import sys +import subprocess +import platform + +# 기존 분석기 import +from bs4 import BeautifulSoup +import re +import time + +# ============================================================================= +# .env 파일 로딩 (다른 import보다 먼저) +# ============================================================================= +from dotenv import load_dotenv + +# .env 파일에서 환경변수 로드 +load_dotenv() + +# ============================================================================= +# 로깅 설정 (가장 먼저) +# ============================================================================= +logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', + handlers=[ + logging.StreamHandler(sys.stdout) + ] +) +logger = logging.getLogger(__name__) + +# ============================================================================= +# 시스템 정보 로깅 +# ============================================================================= +logger.info("="*60) +logger.info("카카오맵 리뷰 분석 API 시작") +logger.info("="*60) +logger.info(f"Python 버전: {sys.version}") +logger.info(f"플랫폼: {platform.platform()}") +logger.info(f"아키텍처: {platform.architecture()}") +logger.info(f"현재 작업 디렉토리: {os.getcwd()}") + +# Python 경로 확인 +logger.info("Python 경로 정보:") +for i, path in enumerate(sys.path): + logger.info(f" [{i}] {path}") + +# ============================================================================= +# 패키지 설치 상태 확인 +# ============================================================================= +def check_package_installation(): + """설치된 패키지 확인""" + logger.info("패키지 설치 상태 확인 중...") + + required_packages = [ + 'selenium', 'webdriver-manager', 'beautifulsoup4', + 'fastapi', 'uvicorn', 'pydantic' + ] + + for package in required_packages: + try: + result = subprocess.run([sys.executable, '-m', 'pip', 'show', package], + capture_output=True, text=True) + if result.returncode == 0: + version_line = [line for line in result.stdout.split('\n') if line.startswith('Version:')] + version = version_line[0].split(':')[1].strip() if version_line else 'Unknown' + logger.info(f"✅ {package}: {version}") + else: + logger.error(f"❌ {package}: 설치되지 않음") + except Exception as e: + logger.error(f"❌ {package} 확인 실패: {e}") + +check_package_installation() + +# ============================================================================= +# Selenium 관련 import (세분화된 로깅) +# ============================================================================= +logger.info("Selenium 관련 모듈 import 시작...") + +SELENIUM_AVAILABLE = False +SELENIUM_IMPORT_ERRORS = [] + +# 각 모듈을 개별적으로 import하여 어디서 실패하는지 확인 +selenium_modules = [ + ('selenium', 'selenium'), + ('selenium.webdriver', 'webdriver'), + ('selenium.webdriver.chrome.options', 'Options'), + ('selenium.webdriver.common.by', 'By'), + ('selenium.webdriver.support.ui', 'WebDriverWait'), + ('selenium.webdriver.support', 'expected_conditions as EC'), + ('webdriver_manager.chrome', 'ChromeDriverManager'), + ('selenium.webdriver.chrome.service', 'Service') +] + +imported_modules = {} + +for module_path, import_name in selenium_modules: + try: + logger.info(f" 📦 {module_path}.{import_name} import 시도...") + if import_name == 'selenium': + import selenium + imported_modules['selenium'] = selenium + logger.info(f" ✅ selenium 버전: {selenium.__version__}") + elif import_name == 'webdriver': + from selenium import webdriver + imported_modules['webdriver'] = webdriver + logger.info(f" ✅ webdriver import 성공") + elif import_name == 'Options': + from selenium.webdriver.chrome.options import Options + imported_modules['Options'] = Options + logger.info(f" ✅ Options import 성공") + elif import_name == 'By': + from selenium.webdriver.common.by import By + imported_modules['By'] = By + logger.info(f" ✅ By import 성공") + elif import_name == 'WebDriverWait': + from selenium.webdriver.support.ui import WebDriverWait + imported_modules['WebDriverWait'] = WebDriverWait + logger.info(f" ✅ WebDriverWait import 성공") + elif import_name == 'expected_conditions as EC': + from selenium.webdriver.support import expected_conditions as EC + imported_modules['EC'] = EC + logger.info(f" ✅ expected_conditions import 성공") + elif import_name == 'ChromeDriverManager': + from webdriver_manager.chrome import ChromeDriverManager + imported_modules['ChromeDriverManager'] = ChromeDriverManager + logger.info(f" ✅ ChromeDriverManager import 성공") + elif import_name == 'Service': + from selenium.webdriver.chrome.service import Service + imported_modules['Service'] = Service + logger.info(f" ✅ Service import 성공") + + except ImportError as e: + error_msg = f"{module_path}.{import_name} import 실패: {e}" + logger.error(f" ❌ {error_msg}") + SELENIUM_IMPORT_ERRORS.append(error_msg) + except Exception as e: + error_msg = f"{module_path}.{import_name} import 중 예외 발생: {e}" + logger.error(f" ❌ {error_msg}") + SELENIUM_IMPORT_ERRORS.append(error_msg) + +# 모든 모듈이 성공적으로 import되었는지 확인 +required_modules = ['webdriver', 'Options', 'By', 'WebDriverWait', 'EC', 'ChromeDriverManager', 'Service'] +missing_modules = [mod for mod in required_modules if mod not in imported_modules] + +if missing_modules: + logger.error(f"❌ 누락된 모듈들: {missing_modules}") + SELENIUM_AVAILABLE = False +else: + logger.info("✅ 모든 Selenium 모듈 import 성공!") + SELENIUM_AVAILABLE = True + + # 전역 변수로 설정 + webdriver = imported_modules['webdriver'] + Options = imported_modules['Options'] + By = imported_modules['By'] + WebDriverWait = imported_modules['WebDriverWait'] + EC = imported_modules['EC'] + ChromeDriverManager = imported_modules['ChromeDriverManager'] + Service = imported_modules['Service'] + +logger.info(f"Selenium 사용 가능 여부: {SELENIUM_AVAILABLE}") +if SELENIUM_IMPORT_ERRORS: + logger.error("Import 오류 목록:") + for error in SELENIUM_IMPORT_ERRORS: + logger.error(f" - {error}") + +# ============================================================================= +# Chrome 설치 상태 확인 +# ============================================================================= +def check_chrome_installation(): + """Chrome 브라우저 설치 상태 확인""" + logger.info("Chrome 브라우저 설치 상태 확인 중...") + + chrome_paths = [ + '/usr/bin/google-chrome', + '/usr/bin/google-chrome-stable', + '/usr/bin/chromium-browser', + '/Applications/Google Chrome.app/Contents/MacOS/Google Chrome', + 'C:\\Program Files\\Google\\Chrome\\Application\\chrome.exe', + 'C:\\Program Files (x86)\\Google\\Chrome\\Application\\chrome.exe' + ] + + chrome_found = False + for path in chrome_paths: + if os.path.exists(path): + logger.info(f" ✅ Chrome 발견: {path}") + chrome_found = True + + # 버전 확인 시도 + try: + result = subprocess.run([path, '--version'], capture_output=True, text=True, timeout=5) + if result.returncode == 0: + logger.info(f" 📋 Chrome 버전: {result.stdout.strip()}") + except Exception as e: + logger.warning(f" ⚠️ Chrome 버전 확인 실패: {e}") + break + + if not chrome_found: + logger.error(" ❌ Chrome 브라우저가 설치되지 않음") + + # 시스템 명령어로 확인 시도 + try: + result = subprocess.run(['which', 'google-chrome'], capture_output=True, text=True) + if result.returncode == 0: + logger.info(f" ✅ PATH에서 Chrome 발견: {result.stdout.strip()}") + chrome_found = True + except: + pass + + try: + result = subprocess.run(['google-chrome', '--version'], capture_output=True, text=True, timeout=5) + if result.returncode == 0: + logger.info(f" ✅ 명령어로 Chrome 실행 가능: {result.stdout.strip()}") + chrome_found = True + except Exception as e: + logger.error(f" ❌ Chrome 명령어 실행 실패: {e}") + + return chrome_found + +chrome_available = check_chrome_installation() + +# ============================================================================= +# 환경 변수 설정 +# ============================================================================= +class Config: + """환경 변수 기반 설정 클래스""" + + # 애플리케이션 메타데이터 + APP_TITLE = os.getenv("APP_TITLE", "카카오맵 리뷰 분석 API") + APP_VERSION = os.getenv("APP_VERSION", "1.0.0") + APP_DESCRIPTION = os.getenv("APP_DESCRIPTION", "교육 목적 전용 - 실제 서비스 사용 금지") + + # 서버 설정 + HOST = os.getenv("HOST", "0.0.0.0") + PORT = int(os.getenv("PORT", "8000")) + WORKERS = int(os.getenv("WORKERS", "1")) + LOG_LEVEL = os.getenv("LOG_LEVEL", "info") + + # API 기본값 + DEFAULT_MAX_TIME = int(os.getenv("DEFAULT_MAX_TIME", "300")) + DEFAULT_DAYS_LIMIT = int(os.getenv("DEFAULT_DAYS_LIMIT", "7")) + MAX_DAYS_LIMIT = int(os.getenv("MAX_DAYS_LIMIT", "365")) + MIN_MAX_TIME = int(os.getenv("MIN_MAX_TIME", "60")) + MAX_MAX_TIME = int(os.getenv("MAX_MAX_TIME", "1800")) + + # Chrome 옵션 (ConfigMap에서 멀티라인 문자열로 받음) + CHROME_OPTIONS_RAW = os.getenv("CHROME_OPTIONS", """ + --headless + --no-sandbox + --disable-dev-shm-usage + --disable-gpu + --window-size=1920,1080 + --disable-extensions + --disable-plugins + --disable-usb-keyboard-detect + --no-first-run + --no-default-browser-check + --disable-logging + --log-level=3 + """) + + @property + def CHROME_OPTIONS_LIST(self): + """Chrome 옵션을 리스트로 파싱""" + return [opt.strip() for opt in self.CHROME_OPTIONS_RAW.strip().split('\n') if opt.strip()] + + # 스크롤링 설정 + SCROLL_CHECK_INTERVAL = int(os.getenv("SCROLL_CHECK_INTERVAL", "3")) + SCROLL_NO_CHANGE_LIMIT = int(os.getenv("SCROLL_NO_CHANGE_LIMIT", "8")) + SCROLL_WAIT_TIME_SHORT = float(os.getenv("SCROLL_WAIT_TIME_SHORT", "1.5")) + SCROLL_WAIT_TIME_LONG = float(os.getenv("SCROLL_WAIT_TIME_LONG", "2.0")) + + # 법적 경고 + LEGAL_WARNING_ENABLED = os.getenv("LEGAL_WARNING_ENABLED", "true").lower() == "true" + CONTACT_EMAIL = os.getenv("CONTACT_EMAIL", "admin@example.com") + + # 건강 체크 + HEALTH_CHECK_TIMEOUT = int(os.getenv("HEALTH_CHECK_TIMEOUT", "5")) + + # Secret 값들 (현재는 사용하지 않지만 향후 확장용) + EXTERNAL_API_KEY = os.getenv("EXTERNAL_API_KEY", "") + DB_USERNAME = os.getenv("DB_USERNAME", "") + DB_PASSWORD = os.getenv("DB_PASSWORD", "") + JWT_SECRET = os.getenv("JWT_SECRET", "") + +# 설정 인스턴스 +config = Config() + +logger.info("환경 설정 로드 완료:") +logger.info(f" - Chrome 옵션 개수: {len(config.CHROME_OPTIONS_LIST)}") +logger.info(f" - 기본 최대 시간: {config.DEFAULT_MAX_TIME}초") +logger.info(f" - 로그 레벨: {config.LOG_LEVEL}") + +# FastAPI 앱 초기화 (환경변수 사용) +app = FastAPI( + title=config.APP_TITLE, + description=f""" + **⚠️ 중요 법적 경고사항 ⚠️** + + {config.APP_DESCRIPTION} + + **진단 정보:** + - Selenium 사용 가능: {SELENIUM_AVAILABLE} + - Chrome 설치됨: {chrome_available} + - Import 오류 개수: {len(SELENIUM_IMPORT_ERRORS)} + + **법적 위험:** + - 카카오 이용약관 위반 → 계정 정지, 법적 조치 + - 개인정보보호법(PIPA) 위반 → 과태료 최대 3억원 + - 저작권 및 데이터베이스권 침해 → 손해배상 + - 업무방해죄 → 5년 이하 징역 또는 1천500만원 이하 벌금 + + **합법적 대안:** + - 카카오 공식 API 활용 (developers.kakao.com) + - 점주 대상 자체 가게 관리 서비스 개발 + - 사용자 동의 기반 데이터 수집 앱 + - 카카오와 정식 파트너십 체결 + + **이 API를 실제 서비스에 사용하지 마세요!** + + **환경:** 로컬 개발 + **버전:** {config.APP_VERSION} + **연락처:** {config.CONTACT_EMAIL} + """, + version=config.APP_VERSION, + contact={ + "name": "관리자", + "email": config.CONTACT_EMAIL + }, + license_info={ + "name": "Educational Use Only", + "url": "https://developers.kakao.com" + } +) + +# Pydantic 모델 정의 (기존과 동일) +class ReviewAnalysisRequest(BaseModel): + """리뷰 분석 요청 모델""" + store_id: str = Field( + ..., + description="카카오맵 가게 ID (예: 501745730)", + example="501745730", + min_length=1, + max_length=20 + ) + days_limit: Optional[int] = Field( + None, + description=f"며칠 이후의 리뷰만 수집할지 (None이면 모든 날짜, 최대 {config.MAX_DAYS_LIMIT}일)", + example=config.DEFAULT_DAYS_LIMIT, + ge=1, + le=config.MAX_DAYS_LIMIT + ) + max_time: int = Field( + config.DEFAULT_MAX_TIME, + description=f"최대 스크롤 시간(초, {config.MIN_MAX_TIME}-{config.MAX_MAX_TIME}초)", + example=config.DEFAULT_MAX_TIME, + ge=config.MIN_MAX_TIME, + le=config.MAX_MAX_TIME + ) + +class ReviewerStats(BaseModel): + """리뷰어 통계 정보""" + reviews: Optional[int] = None + average_rating: Optional[float] = None + followers: Optional[int] = None + +class ReviewData(BaseModel): + """개별 리뷰 데이터""" + reviewer_name: str + reviewer_level: str + reviewer_stats: ReviewerStats + rating: int + date: str + content: str + badges: List[str] + likes: int + photo_count: int + has_photos: bool + +class StoreInfo(BaseModel): + """가게 정보 (수정됨: id 필드 추가)""" + id: str = Field(description="가게 ID") + name: str + category: str + rating: str + review_count: str + status: str + address: str + +class DateFilter(BaseModel): + """날짜 필터 정보""" + cutoff_date: Optional[str] = None + filtered: bool + +class ReviewAnalysisResponse(BaseModel): + """리뷰 분석 응답 모델""" + success: bool = Field(description="분석 성공 여부") + message: str = Field(description="응답 메시지") + store_info: Optional[StoreInfo] = None + reviews: List[ReviewData] = [] + analysis_date: str = Field(description="분석 수행 날짜시간") + total_reviews: int = Field(description="수집된 총 리뷰 수") + analysis_method: str = "selenium" + date_filter: DateFilter + execution_time: float = Field(description="실행 시간(초)") + +class ErrorResponse(BaseModel): + """에러 응답 모델""" + success: bool = False + error: str + message: str + timestamp: str + +# 분석기 클래스 (로깅 강화) +class KakaoReviewAnalyzerAPI: + """로깅 강화된 카카오맵 리뷰 분석기""" + + def __init__(self): + self.store_info = {} + self.reviews = [] + self.cutoff_date = None + self.config = config + logger.info("KakaoReviewAnalyzerAPI 인스턴스 생성 완료") + + def analyze_by_store_id(self, store_id: str, days_limit: Optional[int] = None, max_scroll_time: int = None): + """Selenium을 사용한 동적 리뷰 분석 (ChromeDriver 경로 수정)""" + + logger.info("="*60) + logger.info("analyze_by_store_id 함수 시작") + logger.info("="*60) + + if max_scroll_time is None: + max_scroll_time = self.config.DEFAULT_MAX_TIME + + logger.info(f"입력 파라미터:") + logger.info(f" - store_id: {store_id}") + logger.info(f" - days_limit: {days_limit}") + logger.info(f" - max_scroll_time: {max_scroll_time}") + + # 날짜 제한 설정 + if days_limit is not None: + self.cutoff_date = datetime.now() - timedelta(days=days_limit) + logger.info(f"수집 기준일 설정: {self.cutoff_date.strftime('%Y.%m.%d')} 이후 리뷰만 수집") + else: + self.cutoff_date = None + logger.info("날짜 제한 없음: 모든 날짜의 리뷰 수집") + + target_url = f"https://place.map.kakao.com/{store_id}#comment" + logger.info(f"대상 URL 생성: {target_url}") + + driver = None + temp_profile = None + step_counter = 0 + + try: + # Step 1: Chrome 옵션 설정 + step_counter += 1 + logger.info(f"[단계 {step_counter}] Chrome 옵션 설정 중...") + + if not SELENIUM_AVAILABLE: + raise Exception(f"Selenium을 사용할 수 없음. Import 오류: {SELENIUM_IMPORT_ERRORS}") + + options = Options() + logger.info(f" Chrome Options 객체 생성 완료") + + for i, option in enumerate(self.config.CHROME_OPTIONS_LIST): + logger.info(f" 옵션 [{i+1}] 추가: {option}") + options.add_argument(option) + + # User Agent 추가 + user_agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36' + logger.info(f" User Agent 설정: {user_agent}") + options.add_argument(f'--user-agent={user_agent}') + + # 추가 최적화 옵션들 + experimental_options = ['enable-logging'] + logger.info(f" 실험적 옵션 제외: {experimental_options}") + options.add_experimental_option('excludeSwitches', experimental_options) + options.add_experimental_option('useAutomationExtension', False) + + logger.info(f" Chrome 옵션 설정 완료 (총 {len(self.config.CHROME_OPTIONS_LIST)+1}개)") + + # Step 2: WebDriver 초기화 (ChromeDriverManager 사용 중단) + step_counter += 1 + logger.info(f"[단계 {step_counter}] Chrome WebDriver 초기화 중...") + + # 🔧 시스템에 설치된 ChromeDriver 사용 + chromedriver_paths = [ + "/usr/local/bin/chromedriver", # Dockerfile에서 설치한 경로 + "/usr/bin/chromedriver", + "/opt/chromedriver/chromedriver", + "./chromedriver" + ] + + driver_path = None + for path in chromedriver_paths: + if os.path.exists(path) and os.access(path, os.X_OK): + logger.info(f" ChromeDriver 발견: {path}") + # 버전 확인 + try: + import subprocess + result = subprocess.run([path, "--version"], capture_output=True, text=True, timeout=5) + if result.returncode == 0: + logger.info(f" ChromeDriver 버전: {result.stdout.strip()}") + driver_path = path + break + except Exception as version_error: + logger.warning(f" {path} 버전 확인 실패: {version_error}") + continue + + if not driver_path: + # 마지막 수단: ChromeDriverManager 사용하되 올바른 실행 파일 찾기 + logger.info(" 시스템 ChromeDriver 없음 - ChromeDriverManager 사용...") + try: + # 🔧 ChromeDriverManager 개선 + os.environ['WDM_LOCAL'] = '/tmp/.wdm' + downloaded_path = ChromeDriverManager(cache_valid_range=7).install() + logger.info(f" 다운로드된 경로: {downloaded_path}") + + # 다운로드된 디렉토리에서 실제 실행 파일 찾기 + download_dir = os.path.dirname(downloaded_path) + possible_paths = [ + os.path.join(download_dir, "chromedriver"), + os.path.join(download_dir, "chromedriver-linux64", "chromedriver"), + downloaded_path + ] + + for candidate_path in possible_paths: + if os.path.exists(candidate_path) and os.access(candidate_path, os.X_OK): + # 파일이 실제 실행 파일인지 확인 (텍스트 파일이 아닌지) + try: + with open(candidate_path, 'rb') as f: + header = f.read(4) + # ELF 헤더 확인 (리눅스 실행 파일) + if header.startswith(b'\x7fELF'): + logger.info(f" 실행 가능한 ChromeDriver 발견: {candidate_path}") + driver_path = candidate_path + break + except Exception as file_check_error: + logger.warning(f" 파일 확인 실패: {candidate_path} - {file_check_error}") + continue + + if not driver_path: + raise Exception(f"다운로드된 디렉토리에서 실행 가능한 chromedriver를 찾을 수 없음: {download_dir}") + + except Exception as cdm_error: + logger.error(f" ChromeDriverManager 실패: {cdm_error}") + raise Exception(f"ChromeDriver를 찾을 수 없음. 시스템에 chromedriver를 설치하거나 Docker 이미지를 다시 빌드하세요.") + + # Service 객체 생성 + logger.info(f" ChromeDriver 경로 사용: {driver_path}") + service = Service(driver_path) + + # 🔧 Chrome 실행 환경 설정 + logger.info(" Chrome 실행 환경 설정...") + + # 임시 프로필 디렉토리 생성 + import tempfile + temp_profile = tempfile.mkdtemp(prefix='chrome_profile_') + logger.info(f" 임시 Chrome 프로필 생성: {temp_profile}") + + # Chrome 옵션에 프로필 경로 및 추가 안정성 옵션 추가 + options.add_argument(f'--user-data-dir={temp_profile}') + options.add_argument('--disable-web-security') + options.add_argument('--allow-running-insecure-content') + options.add_argument('--disable-blink-features=AutomationControlled') + options.add_experimental_option("excludeSwitches", ["enable-automation"]) + options.add_experimental_option('useAutomationExtension', False) + + logger.info(" 추가 안정성 옵션 적용 완료") + + # WebDriver 생성 + logger.info(" Chrome WebDriver 인스턴스 생성 중...") + try: + driver = webdriver.Chrome(service=service, options=options) + logger.info(" Chrome WebDriver 객체 생성 완료") + + # 🔧 즉시 연결 상태 확인 + logger.info(" Chrome 연결 상태 확인...") + driver.set_page_load_timeout(30) + driver.set_script_timeout(30) + driver.implicitly_wait(10) + + # 기본 페이지로 이동하여 연결 테스트 + logger.info(" 연결 테스트용 빈 페이지 로드...") + driver.get("data:text/html,Test

Connection Test

") + + # 페이지 제목 확인으로 연결 검증 + test_title = driver.title + logger.info(f" 연결 테스트 성공 - 페이지 제목: {test_title}") + + if not test_title: + raise Exception("Chrome 연결은 되었으나 페이지 로드 실패") + + logger.info(" Chrome WebDriver 연결 확인 완료") + + # Chrome 정보 확인 + try: + capabilities = driver.capabilities + chrome_version = capabilities.get('browserVersion', 'Unknown') + driver_version = capabilities.get('chrome', {}).get('chromedriverVersion', 'Unknown') + logger.info(f" Chrome 버전: {chrome_version}") + logger.info(f" ChromeDriver 버전: {driver_version}") + + # 창 크기 확인 + window_size = driver.get_window_size() + logger.info(f" 현재 창 크기: {window_size}") + except Exception as info_error: + logger.warning(f" Chrome 정보 확인 실패: {info_error}") + + except Exception as driver_error: + logger.error(f" Chrome WebDriver 생성/연결 실패: {driver_error}") + + # 리소스 정리 + if driver: + try: + driver.quit() + except: + pass + + if temp_profile and os.path.exists(temp_profile): + try: + import shutil + shutil.rmtree(temp_profile) + logger.info(" 임시 프로필 디렉토리 정리 완료") + except Exception as cleanup_error: + logger.warning(f" 임시 프로필 정리 실패: {cleanup_error}") + + error_details = { + "error_type": "WEBDRIVER_CONNECTION_FAILED", + "chrome_options_count": len(self.config.CHROME_OPTIONS_LIST), + "driver_path": driver_path, + "temp_profile": temp_profile, + "system_info": { + "checked_paths": chromedriver_paths, + "chrome_exists": os.path.exists("/usr/bin/google-chrome"), + "wdm_cache": os.path.exists("/tmp/.wdm") + } + } + raise Exception(f"Chrome WebDriver 연결 실패: {driver_error}\n상세 정보: {error_details}") + + # Step 3: 페이지 로드 + step_counter += 1 + logger.info(f"[단계 {step_counter}] 페이지 로드 시작...") + logger.info(f" 요청 URL: {target_url}") + + start_time = time.time() + try: + driver.get(target_url) + load_time = time.time() - start_time + logger.info(f" 페이지 로드 완료 (소요시간: {load_time:.2f}초)") + + # 페이지 정보 확인 + current_url = driver.current_url + page_title = driver.title + logger.info(f" 현재 URL: {current_url}") + logger.info(f" 페이지 제목: {page_title}") + + if "404" in page_title or "오류" in page_title: + raise Exception(f"유효하지 않은 페이지: {page_title}") + + # Body 로드 대기 + logger.info(" 페이지 body 로드 대기 중...") + WebDriverWait(driver, 15).until( + EC.presence_of_element_located((By.TAG_NAME, "body")) + ) + logger.info(" 페이지 body 로드 완료") + + except Exception as page_error: + logger.error(f" 페이지 로드 실패: {page_error}") + current_url = driver.current_url if driver else "N/A" + raise Exception(f"페이지 로드 실패 - 요청 URL: {target_url}, 현재 URL: {current_url}, 오류: {page_error}") + + # Step 4: 후기 탭 클릭 (이하 동일) + step_counter += 1 + logger.info(f"[단계 {step_counter}] 후기 탭 클릭 시도...") + + review_tab_selectors = [ + "//a[@href='#comment']", + "//a[contains(text(), '후기')]", + "//button[contains(text(), '후기')]", + "//*[@id='comment']", + "//a[contains(@class, 'comment')]" + ] + + review_tab_found = False + for i, selector in enumerate(review_tab_selectors): + try: + logger.info(f" 선택자 [{i+1}] 시도: {selector}") + review_tab = WebDriverWait(driver, 3).until( + EC.element_to_be_clickable((By.XPATH, selector)) + ) + logger.info(f" 후기 탭 발견: {selector}") + driver.execute_script("arguments[0].click();", review_tab) + time.sleep(3) + logger.info(f" 후기 탭 클릭 성공") + review_tab_found = True + break + except Exception as e: + logger.info(f" 선택자 [{i+1}] 실패: {e}") + continue + + if not review_tab_found: + logger.warning(" 후기 탭을 찾을 수 없음 - 기본 페이지에서 진행") + + # Step 5: 리뷰 목록 로드 확인 + step_counter += 1 + logger.info(f"[단계 {step_counter}] 리뷰 목록 로드 확인...") + + review_list_selectors = [ + ".list_review", + "[class*='review']", + "[class*='comment']", + ".review_list", + ".comment_list" + ] + + review_list_found = False + for i, selector in enumerate(review_list_selectors): + try: + logger.info(f" 리뷰 목록 선택자 [{i+1}] 시도: {selector}") + elements = driver.find_elements(By.CSS_SELECTOR, selector) + if elements: + logger.info(f" 리뷰 목록 발견: {selector} (요소 {len(elements)}개)") + review_list_found = True + break + except Exception as e: + logger.info(f" 리뷰 목록 선택자 [{i+1}] 실패: {e}") + + if not review_list_found: + logger.warning(" 리뷰 목록을 찾을 수 없음 - HTML에서 직접 추출 시도") + + # Step 6: 스크롤링 + step_counter += 1 + logger.info(f"[단계 {step_counter}] 스크롤링 시작...") + logger.info(f" 최대 스크롤 시간: {max_scroll_time}초") + + try: + self._smart_infinite_scroll(driver, max_scroll_time) + logger.info(" 스크롤링 완료") + except Exception as scroll_error: + logger.error(f" 스크롤링 중 오류: {scroll_error}") + logger.info(" 스크롤링 실패 - 현재까지 로드된 내용으로 분석 진행") + + # Step 7: HTML 분석 + step_counter += 1 + logger.info(f"[단계 {step_counter}] HTML 내용 분석...") + + html_content = driver.page_source + html_length = len(html_content) + logger.info(f" HTML 내용 추출 완료: {html_length:,}자") + + if html_length < 1000: + raise Exception(f"HTML 내용이 너무 짧음: {html_length}자") + + # HTML 분석 수행 + logger.info(" HTML 파싱 및 데이터 추출 시작...") + store_info, reviews = self.analyze_html_content(html_content, store_id) + + # 결과 검증 + if not store_info: + logger.warning(" 가게 정보 추출 실패 - 기본값 설정") + store_info = { + 'id': store_id, + 'name': f'Store_{store_id}', + 'category': '', + 'rating': '', + 'review_count': '', + 'status': '', + 'address': '' + } + else: + logger.info(f" 가게 정보 추출 성공: {store_info.get('name', 'N/A')}") + + if not reviews: + logger.warning(" 리뷰 데이터 추출 실패") + reviews = [] + else: + logger.info(f" 리뷰 데이터 추출 성공: {len(reviews)}개") + + logger.info("="*60) + logger.info("analyze_by_store_id 함수 완료") + logger.info(f"최종 결과: 가게 정보={store_info.get('name', 'N/A')}, 리뷰={len(reviews)}개") + logger.info("="*60) + + return store_info, reviews + + except Exception as e: + logger.error("="*60) + logger.error(f"[단계 {step_counter}] 오류 발생!") + logger.error(f"오류 내용: {str(e)}") + logger.error("="*60) + + # 상세 디버그 정보 수집 + debug_info = { + "failed_step": step_counter, + "store_id": store_id, + "target_url": target_url, + "max_scroll_time": max_scroll_time, + "days_limit": days_limit, + "selenium_available": SELENIUM_AVAILABLE, + "chrome_available": chrome_available, + "chrome_options_count": len(self.config.CHROME_OPTIONS_LIST), + "import_errors": SELENIUM_IMPORT_ERRORS, + "driver_status": "initialized" if driver else "not_initialized", + "temp_profile": temp_profile + } + + if driver: + try: + debug_info.update({ + "current_url": driver.current_url, + "page_title": driver.title, + "window_size": driver.get_window_size() + }) + except: + debug_info["driver_info"] = "driver_not_accessible" + + logger.error("디버그 정보:") + for key, value in debug_info.items(): + logger.error(f" {key}: {value}") + + raise Exception(f"리뷰 분석 실패 (단계 {step_counter}): {str(e)}") + + finally: + # 🔧 리소스 정리 강화 + logger.info("리소스 정리 중...") + + # WebDriver 정리 + if driver: + try: + logger.info(" Chrome WebDriver 종료 중...") + driver.quit() + logger.info(" Chrome WebDriver 종료 완료") + except Exception as cleanup_error: + logger.warning(f" WebDriver 정리 중 오류: {cleanup_error}") + else: + logger.info(" WebDriver가 초기화되지 않았음 - 정리 작업 불필요") + + # 임시 프로필 디렉토리 정리 + if temp_profile and os.path.exists(temp_profile): + try: + import shutil + shutil.rmtree(temp_profile) + logger.info(f" 임시 프로필 디렉토리 정리 완료: {temp_profile}") + except Exception as cleanup_error: + logger.warning(f" 임시 프로필 정리 실패: {cleanup_error}") + + logger.info("리소스 정리 완료") + + def _smart_infinite_scroll(self, driver, max_time): + """환경변수 기반 스마트 무한 스크롤링 (로깅 강화)""" + logger.info("스크롤링 세부 설정:") + logger.info(f" - 체크 간격: {self.config.SCROLL_CHECK_INTERVAL}회마다") + logger.info(f" - 변화 없음 제한: {self.config.SCROLL_NO_CHANGE_LIMIT}회") + logger.info(f" - 대기 시간 (짧음): {self.config.SCROLL_WAIT_TIME_SHORT}초") + logger.info(f" - 대기 시간 (김): {self.config.SCROLL_WAIT_TIME_LONG}초") + + start_time = time.time() + scroll_count = 0 + no_change_count = 0 + last_review_count = 0 + + while True: + scroll_count += 1 + elapsed_time = time.time() - start_time + + # 시간 제한 확인 + if elapsed_time > max_time: + logger.info(f"스크롤링 종료: 시간 제한 도달 ({max_time}초)") + break + + try: + # 현재 리뷰 개수 확인 + review_elements = driver.find_elements(By.CSS_SELECTOR, "ul.list_review li") + current_review_count = len(review_elements) + + # 10회마다 진행 상황 로깅 + if scroll_count % 10 == 0: + logger.info(f"스크롤링 진행: {scroll_count}회 | 리뷰 {current_review_count}개 | {elapsed_time:.1f}초 경과") + + # 날짜 기준 확인 + if self.cutoff_date and scroll_count % self.config.SCROLL_CHECK_INTERVAL == 0: + logger.info(f"날짜 기준 확인 중... (스크롤 {scroll_count}회)") + date_cutoff_reached, oldest_date = self._check_date_cutoff_realtime(driver) + if date_cutoff_reached: + logger.info(f"스크롤링 종료: 날짜 기준 도달 ({oldest_date})") + break + + # 리뷰 개수 변화 확인 + if current_review_count == last_review_count: + no_change_count += 1 + if no_change_count >= self.config.SCROLL_NO_CHANGE_LIMIT: + logger.info(f"스크롤링 종료: 더 이상 새로운 리뷰 없음 (총 {current_review_count}개)") + break + else: + no_change_count = 0 + last_review_count = current_review_count + + # 스크롤 실행 + driver.execute_script("window.scrollTo(0, document.body.scrollHeight);") + + # 대기 시간 조정 + wait_time = (self.config.SCROLL_WAIT_TIME_SHORT if current_review_count < 30 + else self.config.SCROLL_WAIT_TIME_LONG) + time.sleep(wait_time) + + except Exception as e: + logger.error(f"스크롤 {scroll_count}회 실행 실패: {e}") + break + + # 최종 결과 + final_count = len(driver.find_elements(By.CSS_SELECTOR, "ul.list_review li")) + logger.info(f"스크롤링 최종 결과:") + logger.info(f" - 총 스크롤 횟수: {scroll_count}회") + logger.info(f" - 최종 리뷰 개수: {final_count}개") + logger.info(f" - 총 소요 시간: {elapsed_time:.1f}초") + + def _check_date_cutoff_realtime(self, driver): + """실시간 날짜 기준 확인 (로깅 강화)""" + if not self.cutoff_date: + return False, None + + try: + date_elements = driver.find_elements(By.CSS_SELECTOR, "ul.list_review li .txt_date") + recent_dates = date_elements[-10:] if len(date_elements) > 10 else date_elements + + logger.debug(f"날짜 확인: 최근 {len(recent_dates)}개 날짜 요소 검사") + + for i, date_elem in enumerate(recent_dates): + try: + date_text = date_elem.text.strip() + if date_text.endswith('.'): + date_text = date_text[:-1] + + if not date_text: + continue + + review_date = datetime.strptime(date_text, '%Y.%m.%d') + logger.debug(f" 날짜 [{i+1}]: {date_text} vs 기준일 {self.cutoff_date.strftime('%Y.%m.%d')}") + + if review_date < self.cutoff_date: + logger.info(f"날짜 기준 충족: {date_text} < {self.cutoff_date.strftime('%Y.%m.%d')}") + return True, date_text + + except (ValueError, Exception) as e: + logger.debug(f" 날짜 파싱 실패 [{i+1}]: {date_text} - {e}") + continue + + except Exception as e: + logger.warning(f"날짜 확인 중 오류: {e}") + + return False, None + + def analyze_html_content(self, html_content, store_id): + """HTML 내용 분석 (수정됨: store_id 파라미터 추가)""" + logger.info("HTML 내용 분석 시작...") + + try: + soup = BeautifulSoup(html_content, 'html.parser') + logger.info("BeautifulSoup 파싱 완료") + + # 가게 정보 추출 + logger.info("가게 정보 추출 중...") + self.store_info = self._extract_store_info(soup, store_id) + logger.info(f"가게 정보 추출 완료: {self.store_info}") + + # 리뷰 추출 + logger.info("리뷰 목록 추출 중...") + self.reviews = self._extract_reviews(soup) + logger.info(f"리뷰 추출 완료: {len(self.reviews)}개") + + return self.store_info, self.reviews + + except Exception as e: + logger.error(f"HTML 분석 중 오류: {e}") + raise + + def _extract_store_info(self, soup, store_id): + """가게 정보 추출 (수정됨: id 필드 추가)""" + store_info = { + 'id': store_id, # 추가: 가게 ID 설정 + 'name': '', + 'category': '', + 'rating': '', + 'review_count': '', + 'status': '', + 'address': '' + } + + # 가게명 (수정: '장소명' 제거) + store_name = soup.select_one('h3.tit_place') + if store_name: + name_text = store_name.get_text(strip=True) + # '장소명' 텍스트 제거 + name_text = name_text.replace('장소명', '').strip() + store_info['name'] = name_text + logger.info(f" 가게ID: {store_info['id']}") + logger.info(f" 가게명: {store_info['name']}") + else: + logger.warning(" 가게명을 찾을 수 없음") + + # 카테고리 (수정: '장소 카테고리' 제거) + category = soup.select_one('span.info_cate') + if category: + category_text = category.get_text(strip=True) + # '장소 카테고리' 텍스트 제거 + category_text = category_text.replace('장소 카테고리', '').strip() + store_info['category'] = category_text + logger.info(f" 카테고리: {store_info['category']}") + else: + logger.warning(" 카테고리를 찾을 수 없음") + + # 별점 + rating = soup.select_one('span.num_star') + if rating: + store_info['rating'] = rating.get_text(strip=True) + logger.info(f" 별점: {store_info['rating']}") + else: + logger.warning(" 별점을 찾을 수 없음") + + # 후기 수 + review_count = soup.select_one('span.info_num') + if review_count: + count_text = review_count.get_text(strip=True) + numbers = re.findall(r'\d+', count_text) + if numbers: + store_info['review_count'] = numbers[0] + logger.info(f" 후기 수: {store_info['review_count']}") + else: + logger.warning(" 후기 수를 찾을 수 없음") + + # 영업 상태 + status = soup.select_one('span.info_state') + if status: + store_info['status'] = status.get_text(strip=True) + logger.info(f" 영업 상태: {store_info['status']}") + else: + logger.warning(" 영업 상태를 찾을 수 없음") + + # 주소 + address_meta = soup.find('meta', property='og:description') + if address_meta: + store_info['address'] = address_meta.get('content', '') + logger.info(f" 주소: {store_info['address']}") + else: + logger.warning(" 주소를 찾을 수 없음") + + return store_info + + def _extract_reviews(self, soup): + """리뷰 목록 추출 (로깅 강화)""" + reviews = [] + + review_list = soup.select_one('ul.list_review') + if not review_list: + logger.warning("리뷰 목록 컨테이너를 찾을 수 없음") + return reviews + + review_items = review_list.find_all('li', recursive=False) + logger.info(f"발견된 리뷰 아이템: {len(review_items)}개") + + skipped_count = 0 + processed_count = 0 + + for i, item in enumerate(review_items): + try: + if (i + 1) % 10 == 0: + logger.info(f"리뷰 처리 진행: {i+1}/{len(review_items)}") + + review_data = self._extract_single_review(item) + if review_data and review_data.get('reviewer_name'): + if self._is_review_within_date_range(review_data): + reviews.append(review_data) + processed_count += 1 + else: + skipped_count += 1 + if skipped_count > 5: + logger.info(f"연속 오래된 리뷰로 추출 중단 (총 {len(reviews)}개)") + break + + except Exception as e: + logger.warning(f"리뷰 #{i+1} 추출 실패: {e}") + + logger.info(f"리뷰 추출 완료: 처리됨={processed_count}개, 제외됨={skipped_count}개, 총={len(reviews)}개") + return reviews + + def _extract_single_review(self, item): + """개별 리뷰 데이터 추출 (수정됨: reviewer_name에서 '리뷰어 이름, ' 제거)""" + review_data = { + 'reviewer_name': '', + 'reviewer_level': '', + 'reviewer_stats': {}, + 'rating': 0, + 'date': '', + 'content': '', + 'badges': [], + 'likes': 0, + 'photo_count': 0, + 'has_photos': False + } + + # 리뷰어 이름 (수정: '리뷰어 이름, ' 제거) + name_elem = item.select_one('span.name_user') + if name_elem: + name_text = name_elem.get_text(strip=True) + # '리뷰어 이름, ' 텍스트 제거 (더 확실한 방법) + if '리뷰어 이름,' in name_text: + review_data['reviewer_name'] = name_text.replace('리뷰어 이름,', '').strip() + else: + review_data['reviewer_name'] = name_text + + # 리뷰어 레벨 + level_elem = item.select_one('span.txt_badge') + if level_elem: + review_data['reviewer_level'] = level_elem.get_text(strip=True) + + # 리뷰어 통계 + detail_list = item.select_one('ul.list_detail') + if detail_list: + stats_json = {} + for li in detail_list.find_all('li'): + stat = li.get_text(strip=True) + if '후기' in stat: + numbers = re.findall(r'\d+', stat) + if numbers: + stats_json['reviews'] = int(numbers[0]) + elif '별점평균' in stat: + numbers = re.findall(r'\d+\.?\d*', stat) + if numbers: + stats_json['average_rating'] = float(numbers[0]) + elif '팔로워' in stat: + numbers = re.findall(r'\d+', stat) + if numbers: + stats_json['followers'] = int(numbers[0]) + review_data['reviewer_stats'] = stats_json + + # 별점 + star_wrapper = item.select_one('span.wrap_grade') + if star_wrapper: + stars = star_wrapper.select('span.figure_star.on') + review_data['rating'] = len(stars) + + # 날짜 + date_elem = item.select_one('span.txt_date') + if date_elem: + date_text = date_elem.get_text(strip=True) + if date_text.endswith('.'): + date_text = date_text[:-1] + review_data['date'] = date_text + + # 리뷰 내용 + content_elem = item.select_one('p.desc_review') + if content_elem: + review_data['content'] = content_elem.get_text(strip=True) + + # 태그/배지 + badges = item.select('span.badge_point') + for badge in badges: + badge_text = badge.get_text(strip=True) + if badge_text and badge_text not in review_data['badges']: + review_data['badges'].append(badge_text) + + # 좋아요 수 + like_btn = item.select_one('button .txt_btn') + if like_btn: + like_text = like_btn.get_text(strip=True) + try: + review_data['likes'] = int(like_text) + except ValueError: + review_data['likes'] = 0 + + # 사진 개수 + photos = item.select('.review_thumb img, .thumb_img img') + review_data['photo_count'] = len(photos) + review_data['has_photos'] = len(photos) > 0 + + return review_data + + def _is_review_within_date_range(self, review_data): + """리뷰가 날짜 범위 내에 있는지 확인""" + if not self.cutoff_date: + return True + + date_str = review_data.get('date', '') + if not date_str: + return True + + try: + if date_str.endswith('.'): + date_str = date_str[:-1] + review_date = datetime.strptime(date_str, '%Y.%m.%d') + return review_date >= self.cutoff_date + except ValueError: + return True + +# API 엔드포인트 +@app.get("/", response_class=HTMLResponse, include_in_schema=False) +async def root(): + """메인 페이지 (진단 정보 포함)""" + + # 진단 정보 생성 + diagnosis_info = f""" +
+

🔧 시스템 진단 정보

+
    +
  • Selenium 사용 가능: {'✅ 예' if SELENIUM_AVAILABLE else '❌ 아니오'}
    • +
  • Chrome 설치됨: {'✅ 예' if chrome_available else '❌ 아니오'}
    • +
  • Import 오류 개수: {len(SELENIUM_IMPORT_ERRORS)}
    • +
  • Python 버전: {sys.version.split()[0]}
    • +
  • 플랫폼: {platform.platform()}
    • +
+ + {f''' +

❌ Import 오류 목록:

+
    + {''.join([f"
  • {error}
    • " for error in SELENIUM_IMPORT_ERRORS])} +
+ ''' if SELENIUM_IMPORT_ERRORS else ''} +
+ """ + + warning_section = "" + if config.LEGAL_WARNING_ENABLED: + warning_section = f""" +
+

⚠️ 중요 법적 경고사항

+

{config.APP_DESCRIPTION}

+
    +
  • 실제 웹사이트 크롤링은 불법입니다
    • +
  • 카카오 이용약관 위반 위험
    • +
  • 개인정보보호법 위반 위험
    • +
  • 업무방해죄 처벌 가능
    • +
+

합법적 대안을 사용하세요:

+
    +
  • 카카오 공식 API (developers.kakao.com)
    • +
  • 정식 파트너십 체결
    • +
  • 사용자 동의 기반 데이터 수집
    • +
+
+ """ + + return f""" + + + {config.APP_TITLE} + + + +
+

🔍 {config.APP_TITLE}

+

버전: {config.APP_VERSION}

+

환경: 로컬 개발

+

연락처: {config.CONTACT_EMAIL}

+
+ + {diagnosis_info} + + {warning_section} + +
+

🔧 환경 설정 정보

+
    +
  • 기본 최대 시간: {config.DEFAULT_MAX_TIME}초
    • +
  • 기본 날짜 제한: {config.DEFAULT_DAYS_LIMIT}일
    • +
  • 스크롤 체크 간격: {config.SCROLL_CHECK_INTERVAL}회
    • +
  • Chrome 옵션: {len(config.CHROME_OPTIONS_LIST)}개 설정
    • +
  • 로그 레벨: {config.LOG_LEVEL}
    • +
+
+ +

📚 API 문서

+ Swagger UI 문서 + ReDoc 문서 + 헬스 체크 + 진단 정보 + +

🛠️ 사용 방법

+

POST /analyze - 리뷰 분석 수행

+ 
+{{
+  "store_id": "501745730",
+  "days_limit": {config.DEFAULT_DAYS_LIMIT},
+  "max_time": {config.DEFAULT_MAX_TIME}
+}}
+
+ + + """ + +@app.post( + "/analyze", + response_model=ReviewAnalysisResponse, + summary="카카오맵 리뷰 분석 (로깅 강화)", + description=f""" + **⚠️ {config.APP_DESCRIPTION}** + + **진단 정보:** + - Selenium 사용 가능: {SELENIUM_AVAILABLE} + - Chrome 설치됨: {chrome_available} + - Import 오류 개수: {len(SELENIUM_IMPORT_ERRORS)} + + 지정한 카카오맵 가게의 리뷰를 분석합니다. + + **주요 기능:** + - 실시간 리뷰 수집 및 분석 + - 날짜 범위 필터링 (최대 {config.MAX_DAYS_LIMIT}일) + - 감정 분석 및 통계 + - JSON 형태 응답 + - 상세한 로깅 및 디버그 정보 + + **응답 시간:** 설정에 따라 {config.MIN_MAX_TIME//60}-{config.MAX_MAX_TIME//60}분 소요 + + **환경:** 로컬 개발 버전 + """, + responses={ + 200: {"description": "분석 성공", "model": ReviewAnalysisResponse}, + 400: {"description": "잘못된 요청", "model": ErrorResponse}, + 500: {"description": "서버 오류", "model": ErrorResponse} + } +) +async def analyze_reviews(request: ReviewAnalysisRequest): + """리뷰 분석 API (수정됨: environment 섹션 제거)""" + + logger.info("="*60) + logger.info("analyze_reviews API 호출") + logger.info("="*60) + logger.info(f"요청 파라미터: {request}") + + # Selenium 사용 가능성 확인 + if not SELENIUM_AVAILABLE: + error_detail = { + "success": False, + "error": "SELENIUM_NOT_AVAILABLE", + "message": "Selenium이 설치되지 않았습니다. pip install selenium webdriver-manager", + "timestamp": datetime.now().isoformat(), + "debug_info": { + "import_errors": SELENIUM_IMPORT_ERRORS, + "python_version": sys.version, + "platform": platform.platform(), + "chrome_available": chrome_available + } + } + logger.error("Selenium 사용 불가능!") + logger.error(f"Import 오류: {SELENIUM_IMPORT_ERRORS}") + + raise HTTPException(status_code=500, detail=error_detail) + + # Chrome 사용 가능성 확인 + if not chrome_available: + error_detail = { + "success": False, + "error": "CHROME_NOT_AVAILABLE", + "message": "Chrome 브라우저가 설치되지 않았습니다.", + "timestamp": datetime.now().isoformat() + } + logger.error("Chrome 브라우저 사용 불가능!") + raise HTTPException(status_code=500, detail=error_detail) + + start_time = time.time() + + try: + logger.info(f"리뷰 분석 시작: store_id={request.store_id}, days_limit={request.days_limit}, max_time={request.max_time}") + + # 분석기 실행 + def run_analysis(): + analyzer = KakaoReviewAnalyzerAPI() + return analyzer.analyze_by_store_id( + store_id=request.store_id, + days_limit=request.days_limit, + max_scroll_time=request.max_time + ) + + # 스레드에서 실행 + loop = asyncio.get_event_loop() + store_info, reviews = await loop.run_in_executor(None, run_analysis) + + execution_time = time.time() - start_time + + # 응답 데이터 구성 (environment 섹션 제거됨) + response_data = ReviewAnalysisResponse( + success=True, + message="분석이 성공적으로 완료되었습니다.", + store_info=StoreInfo(**store_info) if store_info else None, + reviews=[ + ReviewData( + reviewer_name=review['reviewer_name'], + reviewer_level=review['reviewer_level'], + reviewer_stats=ReviewerStats(**review['reviewer_stats']), + rating=review['rating'], + date=review['date'], + content=review['content'], + badges=review['badges'], + likes=review['likes'], + photo_count=review['photo_count'], + has_photos=review['has_photos'] + ) for review in reviews + ], + analysis_date=datetime.now().isoformat(), + total_reviews=len(reviews), + date_filter=DateFilter( + cutoff_date=(datetime.now() - timedelta(days=request.days_limit)).isoformat() if request.days_limit else None, + filtered=request.days_limit is not None + ), + execution_time=execution_time + ) + + logger.info(f"분석 완료: {len(reviews)}개 리뷰, {execution_time:.1f}초 소요") + logger.info("="*60) + return response_data + + except Exception as e: + execution_time = time.time() - start_time + logger.error(f"분석 실패: {str(e)}") + logger.error("="*60) + + raise HTTPException( + status_code=500, + detail={ + "success": False, + "error": "ANALYSIS_FAILED", + "message": f"리뷰 분석 중 오류가 발생했습니다: {str(e)}", + "timestamp": datetime.now().isoformat(), + "execution_time": execution_time, + "debug_info": { + "selenium_available": SELENIUM_AVAILABLE, + "chrome_available": chrome_available, + "import_errors": SELENIUM_IMPORT_ERRORS, + "request_params": { + "store_id": request.store_id, + "days_limit": request.days_limit, + "max_time": request.max_time + } + } + } + ) + +@app.get("/diagnostic", summary="상세 진단 정보", description="시스템 상태를 상세히 진단합니다.") +async def diagnostic(): + """상세 진단 정보 제공""" + + # 패키지 버전 확인 + package_info = {} + required_packages = ['selenium', 'webdriver-manager', 'beautifulsoup4', 'fastapi', 'uvicorn', 'pydantic'] + + for package in required_packages: + try: + result = subprocess.run([sys.executable, '-m', 'pip', 'show', package], + capture_output=True, text=True) + if result.returncode == 0: + version_line = [line for line in result.stdout.split('\n') if line.startswith('Version:')] + version = version_line[0].split(':')[1].strip() if version_line else 'Unknown' + package_info[package] = {"installed": True, "version": version} + else: + package_info[package] = {"installed": False, "version": None} + except Exception as e: + package_info[package] = {"installed": False, "error": str(e)} + + return { + "system_info": { + "python_version": sys.version, + "platform": platform.platform(), + "architecture": platform.architecture(), + "current_directory": os.getcwd(), + "python_path": sys.path[:5] # 처음 5개만 + }, + "selenium_info": { + "available": SELENIUM_AVAILABLE, + "import_errors": SELENIUM_IMPORT_ERRORS, + "imported_modules": list(imported_modules.keys()) if SELENIUM_AVAILABLE else [] + }, + "chrome_info": { + "available": chrome_available, + "common_paths_checked": [ + '/usr/bin/google-chrome', + '/usr/bin/google-chrome-stable', + '/usr/bin/chromium-browser', + '/Applications/Google Chrome.app/Contents/MacOS/Google Chrome' + ] + }, + "package_info": package_info, + "timestamp": datetime.now().isoformat() + } + +@app.get( + "/health", + summary="헬스 체크", + description="API 서버 상태를 확인합니다." +) +async def health_check(): + """헬스 체크 엔드포인트 (진단 정보 포함)""" + return { + "status": "healthy", + "timestamp": datetime.now().isoformat(), + "selenium_available": SELENIUM_AVAILABLE, + "chrome_available": chrome_available, + "version": config.APP_VERSION, + "message": f"{config.APP_TITLE}이 정상 작동 중입니다." if SELENIUM_AVAILABLE else "Selenium 모듈 문제로 제한된 기능만 사용 가능합니다." + } + +@app.get("/config", summary="환경 설정 확인", description="현재 적용된 환경 변수 설정을 확인합니다.") +async def get_config(): + """환경 설정 확인 엔드포인트""" + return { + "app_info": { + "title": config.APP_TITLE, + "version": config.APP_VERSION, + "description": config.APP_DESCRIPTION + }, + "server_config": { + "host": config.HOST, + "port": config.PORT, + "workers": config.WORKERS, + "log_level": config.LOG_LEVEL + }, + "api_defaults": { + "default_max_time": config.DEFAULT_MAX_TIME, + "default_days_limit": config.DEFAULT_DAYS_LIMIT, + "max_days_limit": config.MAX_DAYS_LIMIT, + "min_max_time": config.MIN_MAX_TIME, + "max_max_time": config.MAX_MAX_TIME + }, + "scroll_settings": { + "check_interval": config.SCROLL_CHECK_INTERVAL, + "no_change_limit": config.SCROLL_NO_CHANGE_LIMIT, + "wait_time_short": config.SCROLL_WAIT_TIME_SHORT, + "wait_time_long": config.SCROLL_WAIT_TIME_LONG + }, + "chrome_options": { + "count": len(config.CHROME_OPTIONS_LIST), + "options": config.CHROME_OPTIONS_LIST + }, + "features": { + "legal_warning_enabled": config.LEGAL_WARNING_ENABLED, + "contact_email": config.CONTACT_EMAIL, + "health_check_timeout": config.HEALTH_CHECK_TIMEOUT + }, + "diagnosis": { + "selenium_available": SELENIUM_AVAILABLE, + "chrome_available": chrome_available, + "import_error_count": len(SELENIUM_IMPORT_ERRORS) + }, + "timestamp": datetime.now().isoformat() + } + +@app.get("/legal-warning", summary="법적 경고사항", description="API 사용 시 주의해야 할 법적 사항을 안내합니다.") +async def legal_warning(): + """법적 경고사항 (환경변수 활용)""" + return { + "warning": f"⚠️ {config.APP_DESCRIPTION}", + "legal_risks": [ + "카카오 이용약관 위반 → 계정 정지, 법적 조치", + "개인정보보호법(PIPA) 위반 → 과태료 최대 3억원", + "저작권 및 데이터베이스권 침해 → 손해배상", + "업무방해죄 → 5년 이하 징역 또는 1천500만원 이하 벌금" + ], + "legal_alternatives": [ + "카카오 공식 API 활용 (developers.kakao.com)", + "점주 대상 자체 가게 관리 서비스 개발", + "사용자 동의 기반 데이터 수집 앱", + "카카오와 정식 파트너십 체결" + ], + "message": "이 API를 실제 서비스에 사용하지 마세요!", + "contact": config.CONTACT_EMAIL, + "version": config.APP_VERSION, + "timestamp": datetime.now().isoformat() + } + +if __name__ == "__main__": + import uvicorn + + print("🚨 " + "="*60) + print(" ⚠️ 중요 법적 경고사항 ⚠️") + print("="*64) + print(f"❌ {config.APP_DESCRIPTION}") + print("❌ 실제 웹사이트 크롤링은 불법입니다.") + print("✅ 카카오 공식 API를 사용하세요: developers.kakao.com") + print("="*64) + print() + + print(f"🚀 {config.APP_TITLE} 서버 시작") + print(f"📊 진단 정보:") + print(f" - Selenium 사용 가능: {SELENIUM_AVAILABLE}") + print(f" - Chrome 설치됨: {chrome_available}") + print(f" - Import 오류: {len(SELENIUM_IMPORT_ERRORS)}개") + print() + print(f"📚 Swagger 문서: http://{config.HOST}:{config.PORT}/docs") + print(f"📖 ReDoc 문서: http://{config.HOST}:{config.PORT}/redoc") + print(f"🏠 메인 페이지: http://{config.HOST}:{config.PORT}/") + print(f"🔧 진단 정보: http://{config.HOST}:{config.PORT}/diagnostic") + print() + + uvicorn.run( + app, + host=config.HOST, + port=config.PORT, + log_level=config.LOG_LEVEL + ) + diff --git a/review/app/requirements.txt b/review/app/requirements.txt new file mode 100644 index 0000000..9549d8a --- /dev/null +++ b/review/app/requirements.txt @@ -0,0 +1,9 @@ +fastapi==0.104.1 +uvicorn[standard]==0.24.0 +beautifulsoup4==4.12.2 +selenium==4.15.2 +webdriver-manager==4.0.1 +pydantic==2.5.0 +lxml==4.9.3 +python-multipart==0.0.6 +python-dotenv==1.0.0 \ No newline at end of file diff --git a/review/build-base.sh b/review/build-base.sh new file mode 100755 index 0000000..1981048 --- /dev/null +++ b/review/build-base.sh @@ -0,0 +1,217 @@ +#!/bin/bash +# build-base.sh - Base Image 빌드 스크립트 + +set -e + +# 변수 설정 +BASE_IMAGE_NAME="kakao-review-api-base" +BASE_IMAGE_TAG="${1:-latest}" +ACR_NAME="${2:-acrdigitalgarage03}" # ACR 이름 (예: acrdigitalgarage01) +RESOURCE_GROUP="${3:-rg-digitalgarage-03}" # 리소스 그룹 + +# ACR URL 자동 구성 +if [ -n "${ACR_NAME}" ]; then + REGISTRY="${ACR_NAME}.azurecr.io" + FULL_BASE_IMAGE_NAME="${REGISTRY}/${BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}" +else + FULL_BASE_IMAGE_NAME="${BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}" +fi + +# 고정된 Dockerfile 경로 +BASE_DOCKERFILE_PATH="deployment/container/Dockerfile-base" +BUILD_CONTEXT="." + +echo "=====================================================" +echo " 카카오맵 리뷰 분석 API Base Image 빌드" +echo "=====================================================" +echo "Base 이미지명: ${FULL_BASE_IMAGE_NAME}" +if [ -n "${ACR_NAME}" ]; then + echo "ACR 이름: ${ACR_NAME}" + echo "리소스 그룹: ${RESOURCE_GROUP}" +fi +echo "빌드 시작: $(date)" +echo "" + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [BASE_IMAGE_TAG] [ACR_NAME] [RESOURCE_GROUP]" + echo "" + echo "파라미터:" + echo " BASE_IMAGE_TAG: Base 이미지 태그 (기본값: latest)" + echo " ACR_NAME : Azure Container Registry 이름" + echo " RESOURCE_GROUP: Azure 리소스 그룹" + echo "" + echo "예시:" + echo " $0 v1.0.0 # 로컬 빌드만" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 # ACR 빌드 + 푸시" + echo "" + echo "주의: Base Image는 자주 빌드할 필요가 없습니다." + echo " Chrome 업데이트나 기본 패키지 변경 시에만 재빌드하세요." +} + +# ACR 로그인 함수 +acr_login() { + local acr_name="$1" + local resource_group="$2" + + echo "🔐 Azure Container Registry 로그인 중..." + + if ! command -v az &> /dev/null; then + echo "❌ Azure CLI (az)가 설치되지 않았습니다." + exit 1 + fi + + if ! command -v jq &> /dev/null; then + echo "❌ jq가 설치되지 않았습니다." + exit 1 + fi + + if ! az account show &> /dev/null; then + echo "❌ Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 + fi + + local credential_json + credential_json=$(az acr credential show --name "${acr_name}" --resource-group "${resource_group}" 2>/dev/null) + + if [ $? -ne 0 ]; then + echo "❌ ACR credential 조회 실패" + exit 1 + fi + + local username + local password + + username=$(echo "${credential_json}" | jq -r '.username') + password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + + if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + echo "❌ ACR credential 파싱 실패" + exit 1 + fi + + echo "🔐 Docker 로그인 실행 중..." + echo "${password}" | docker login "${REGISTRY}" -u "${username}" --password-stdin + + if [ $? -eq 0 ]; then + echo "✅ ACR 로그인 성공!" + return 0 + else + echo "❌ ACR 로그인 실패" + exit 1 + fi +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -n "${ACR_NAME}" ] && [ -z "${RESOURCE_GROUP}" ]; then + echo "❌ ACR_NAME이 제공된 경우 RESOURCE_GROUP도 필요합니다." + echo "" + show_usage + exit 1 +fi + +# 필수 파일 확인 +echo "📁 필수 파일 확인 중..." + +if [ ! -f "${BASE_DOCKERFILE_PATH}" ]; then + echo "❌ ${BASE_DOCKERFILE_PATH} 파일을 찾을 수 없습니다." + exit 1 +fi + +echo "✅ Base Dockerfile 확인 완료" +echo "📄 Base Dockerfile: ${BASE_DOCKERFILE_PATH}" + +# ACR 로그인 수행 +if [ -n "${ACR_NAME}" ] && [ -n "${RESOURCE_GROUP}" ]; then + echo "" + acr_login "${ACR_NAME}" "${RESOURCE_GROUP}" + echo "" +fi + +# Docker 빌드 +echo "🔨 Base Image 빌드 시작... (시간이 다소 소요됩니다)" +echo "명령어: docker build -t \"${FULL_BASE_IMAGE_NAME}\" -f \"${BASE_DOCKERFILE_PATH}\" \"${BUILD_CONTEXT}\"" + +docker build -t "${FULL_BASE_IMAGE_NAME}" -f "${BASE_DOCKERFILE_PATH}" "${BUILD_CONTEXT}" + +if [ $? -eq 0 ]; then + echo "✅ Base Image 빌드 완료!" + echo "이미지명: ${FULL_BASE_IMAGE_NAME}" + + # 이미지 정보 표시 + echo "" + echo "📊 Base Image 정보:" + docker images "${FULL_BASE_IMAGE_NAME}" --format "table {{.Repository}}\t{{.Tag}}\t{{.Size}}\t{{.CreatedAt}}" + + # latest 태그 추가 생성 + if [ "${BASE_IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo "" + echo "🏷️ latest 태그 생성 중..." + docker tag "${FULL_BASE_IMAGE_NAME}" "${REGISTRY}/${BASE_IMAGE_NAME}:latest" + echo "✅ latest 태그 생성 완료: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + fi + + # ACR 푸시 + if [ -n "${ACR_NAME}" ]; then + echo "" + echo "🚀 ACR에 Base Image 푸시 중..." + + echo "📤 푸시 중: ${FULL_BASE_IMAGE_NAME}" + docker push "${FULL_BASE_IMAGE_NAME}" + + if [ $? -eq 0 ]; then + echo "✅ Base Image 푸시 성공" + + if [ "${BASE_IMAGE_TAG}" != "latest" ]; then + echo "📤 푸시 중: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + docker push "${REGISTRY}/${BASE_IMAGE_NAME}:latest" + + if [ $? -eq 0 ]; then + echo "✅ latest 태그 푸시 성공" + fi + fi + else + echo "❌ Base Image 푸시 실패" + exit 1 + fi + fi + + echo "" + echo "🎉 Base Image 빌드 완료!" + echo "" + echo "📋 완료된 작업:" + echo " ✅ Base Image 빌드: ${FULL_BASE_IMAGE_NAME}" + if [ "${BASE_IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo " ✅ latest 태그: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + fi + if [ -n "${ACR_NAME}" ]; then + echo " ✅ ACR 푸시 완료" + fi + + echo "" + echo "🧪 테스트 명령어:" + echo " docker run --rm ${FULL_BASE_IMAGE_NAME} google-chrome --version" + + echo "" + echo "📝 다음 단계:" + echo " 이제 Service Image를 빌드하세요:" + if [ -n "${ACR_NAME}" ]; then + echo " ./scripts/build.sh v1.0.0 ${ACR_NAME} ${RESOURCE_GROUP}" + else + echo " ./scripts/build.sh v1.0.0" + fi + +else + echo "❌ Base Image 빌드 실패!" + exit 1 +fi + +echo "" +echo "🏁 Base Image 빌드 프로세스 완료 - $(date)" diff --git a/review/build.sh b/review/build.sh new file mode 100755 index 0000000..8dd35f6 --- /dev/null +++ b/review/build.sh @@ -0,0 +1,257 @@ +#!/bin/bash +# build.sh - Service Image 빌드 스크립트 (Base Image 활용) + +set -e + +# 변수 설정 +IMAGE_NAME="kakao-review-api" +IMAGE_TAG="${1:-latest}" +ACR_NAME="${2:-acrdigitalgarage03}" # ACR 이름 (예: acrdigitalgarage01) +RESOURCE_GROUP="${3:-rg-digitalgarage-03}" # 리소스 그룹 +BASE_IMAGE_TAG="${4:-latest}" # Base Image 태그 + +# ACR URL 자동 구성 +if [ -n "${ACR_NAME}" ]; then + REGISTRY="${ACR_NAME}.azurecr.io" + FULL_IMAGE_NAME="${REGISTRY}/${IMAGE_NAME}:${IMAGE_TAG}" + BASE_IMAGE="${REGISTRY}/kakao-review-api-base:${BASE_IMAGE_TAG}" +else + FULL_IMAGE_NAME="${IMAGE_NAME}:${IMAGE_TAG}" + BASE_IMAGE="kakao-review-api-base:${BASE_IMAGE_TAG}" +fi + +# 고정된 Dockerfile 경로 +DOCKERFILE_PATH="deployment/container/Dockerfile" +BUILD_CONTEXT="." + +echo "=====================================================" +echo " 카카오맵 리뷰 분석 API Service Image 빌드" +echo "=====================================================" +echo "Service 이미지명: ${FULL_IMAGE_NAME}" +echo "Base 이미지: ${BASE_IMAGE}" +if [ -n "${ACR_NAME}" ]; then + echo "ACR 이름: ${ACR_NAME}" + echo "리소스 그룹: ${RESOURCE_GROUP}" +fi +echo "빌드 시작: $(date)" +echo "" + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [IMAGE_TAG] [ACR_NAME] [RESOURCE_GROUP] [BASE_IMAGE_TAG]" + echo "" + echo "파라미터:" + echo " IMAGE_TAG : Service 이미지 태그 (기본값: latest)" + echo " ACR_NAME : Azure Container Registry 이름" + echo " RESOURCE_GROUP: Azure 리소스 그룹" + echo " BASE_IMAGE_TAG: Base 이미지 태그 (기본값: latest)" + echo "" + echo "예시:" + echo " $0 v1.0.0 # 로컬 빌드만" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 # ACR 빌드 + 푸시" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 v2.0.0 # 특정 Base Image 사용" + echo "" + echo "전제조건:" + echo " Base Image가 먼저 빌드되어 있어야 합니다:" + echo " ./scripts/build-base.sh ${BASE_IMAGE_TAG} [ACR_NAME] [RESOURCE_GROUP]" +} + +# ACR 로그인 함수 +acr_login() { + local acr_name="$1" + local resource_group="$2" + + echo "🔐 Azure Container Registry 로그인 중..." + + if ! command -v az &> /dev/null; then + echo "❌ Azure CLI (az)가 설치되지 않았습니다." + exit 1 + fi + + if ! command -v jq &> /dev/null; then + echo "❌ jq가 설치되지 않았습니다." + exit 1 + fi + + if ! az account show &> /dev/null; then + echo "❌ Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 + fi + + local credential_json + credential_json=$(az acr credential show --name "${acr_name}" --resource-group "${resource_group}" 2>/dev/null) + + if [ $? -ne 0 ]; then + echo "❌ ACR credential 조회 실패" + exit 1 + fi + + local username + local password + + username=$(echo "${credential_json}" | jq -r '.username') + password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + + if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + echo "❌ ACR credential 파싱 실패" + exit 1 + fi + + echo "🔐 Docker 로그인 실행 중..." + echo "${password}" | docker login "${REGISTRY}" -u "${username}" --password-stdin + + if [ $? -eq 0 ]; then + echo "✅ ACR 로그인 성공!" + return 0 + else + echo "❌ ACR 로그인 실패" + exit 1 + fi +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -n "${ACR_NAME}" ] && [ -z "${RESOURCE_GROUP}" ]; then + echo "❌ ACR_NAME이 제공된 경우 RESOURCE_GROUP도 필요합니다." + echo "" + show_usage + exit 1 +fi + +# 법적 경고 +echo "⚠️ 중요 법적 경고사항 ⚠️" +echo "이 이미지는 교육 목적으로만 사용하세요!" +echo "실제 서비스 사용 시 법적 책임을 질 수 있습니다." +echo "" + +# 필수 파일 확인 +echo "📁 필수 파일 확인 중..." + +if [ ! -f "app/main.py" ]; then + echo "❌ app/main.py 파일을 찾을 수 없습니다." + exit 1 +fi + +if [ ! -f "app/requirements.txt" ]; then + echo "❌ app/requirements.txt 파일을 찾을 수 없습니다." + exit 1 +fi + +if [ ! -f "${DOCKERFILE_PATH}" ]; then + echo "❌ ${DOCKERFILE_PATH} 파일을 찾을 수 없습니다." + exit 1 +fi + +echo "✅ 모든 필수 파일이 확인되었습니다." +echo "📄 Dockerfile: ${DOCKERFILE_PATH}" +echo "🏗️ 빌드 컨텍스트: ${BUILD_CONTEXT}" + +# Base Image 존재 확인 +echo "" +echo "🔍 Base Image 확인 중..." +if docker image inspect "${BASE_IMAGE}" >/dev/null 2>&1; then + echo "✅ Base Image 확인됨: ${BASE_IMAGE}" +else + echo "❌ Base Image를 찾을 수 없습니다: ${BASE_IMAGE}" + echo "" + echo "Base Image를 먼저 빌드하세요:" + if [ -n "${ACR_NAME}" ]; then + echo " ./scripts/build-base.sh ${BASE_IMAGE_TAG} ${ACR_NAME} ${RESOURCE_GROUP}" + else + echo " ./scripts/build-base.sh ${BASE_IMAGE_TAG}" + fi + exit 1 +fi + +# ACR 로그인 수행 +if [ -n "${ACR_NAME}" ] && [ -n "${RESOURCE_GROUP}" ]; then + echo "" + acr_login "${ACR_NAME}" "${RESOURCE_GROUP}" + echo "" +fi + +# Docker 빌드 +echo "🔨 Service Image 빌드 시작... (빠른 빌드 예상)" +echo "명령어: docker build --build-arg BASE_IMAGE=\"${BASE_IMAGE}\" -t \"${FULL_IMAGE_NAME}\" -f \"${DOCKERFILE_PATH}\" \"${BUILD_CONTEXT}\"" + +docker build --build-arg BASE_IMAGE="${BASE_IMAGE}" -t "${FULL_IMAGE_NAME}" -f "${DOCKERFILE_PATH}" "${BUILD_CONTEXT}" + +if [ $? -eq 0 ]; then + echo "✅ Service Image 빌드 완료!" + echo "이미지명: ${FULL_IMAGE_NAME}" + + # 이미지 정보 표시 + echo "" + echo "📊 Service Image 정보:" + docker images "${FULL_IMAGE_NAME}" --format "table {{.Repository}}\t{{.Tag}}\t{{.Size}}\t{{.CreatedAt}}" + + # latest 태그 추가 생성 + if [ "${IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo "" + echo "🏷️ latest 태그 생성 중..." + docker tag "${FULL_IMAGE_NAME}" "${REGISTRY}/${IMAGE_NAME}:latest" + echo "✅ latest 태그 생성 완료: ${REGISTRY}/${IMAGE_NAME}:latest" + fi + + # ACR 푸시 + if [ -n "${ACR_NAME}" ]; then + echo "" + echo "🚀 ACR에 Service Image 푸시 중..." + + echo "📤 푸시 중: ${FULL_IMAGE_NAME}" + docker push "${FULL_IMAGE_NAME}" + + if [ $? -eq 0 ]; then + echo "✅ Service Image 푸시 성공" + + if [ "${IMAGE_TAG}" != "latest" ]; then + echo "📤 푸시 중: ${REGISTRY}/${IMAGE_NAME}:latest" + docker push "${REGISTRY}/${IMAGE_NAME}:latest" + + if [ $? -eq 0 ]; then + echo "✅ latest 태그 푸시 성공" + fi + fi + else + echo "❌ Service Image 푸시 실패" + exit 1 + fi + fi + + echo "" + echo "🎉 Service Image 빌드 완료!" + echo "" + echo "📋 완료된 작업:" + echo " ✅ Service Image 빌드: ${FULL_IMAGE_NAME}" + echo " ✅ 사용된 Base Image: ${BASE_IMAGE}" + if [ "${IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo " ✅ latest 태그: ${REGISTRY}/${IMAGE_NAME}:latest" + fi + if [ -n "${ACR_NAME}" ]; then + echo " ✅ ACR 푸시 완료" + fi + + echo "" + echo "🧪 테스트 명령어:" + echo " docker run -p 8000:8000 ${FULL_IMAGE_NAME}" + echo " curl http://localhost:8000/health" + + if [ -n "${ACR_NAME}" ]; then + echo "" + echo "🔍 ACR 이미지 확인:" + echo " az acr repository show-tags --name ${ACR_NAME} --repository ${IMAGE_NAME}" + fi + +else + echo "❌ Service Image 빌드 실패!" + exit 1 +fi + +echo "" +echo "🏁 Service Image 빌드 프로세스 완료 - $(date)" \ No newline at end of file diff --git a/review/create-imagepullsecret.sh b/review/create-imagepullsecret.sh new file mode 100755 index 0000000..d9287c1 --- /dev/null +++ b/review/create-imagepullsecret.sh @@ -0,0 +1,103 @@ +#!/bin/bash +# create-image-pull-secret.sh - ACR Image Pull Secret 생성 스크립트 + +set -e + +# 변수 설정 +ACR_NAME="${1:-acrdigitalgarage03}" +RESOURCE_GROUP="${2:-rg-digitalgarage-03}" +SECRET_NAME="${3:-acr-secret}" + +echo "=====================================================" +echo " ACR Image Pull Secret 생성" +echo "=====================================================" + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [ACR_NAME] [RESOURCE_GROUP] [SECRET_NAME]" + echo "" + echo "파라미터:" + echo " ACR_NAME : Azure Container Registry 이름 (필수)" + echo " RESOURCE_GROUP: Azure 리소스 그룹 (필수)" + echo " SECRET_NAME : Secret 이름 (기본값: acr-secret)" + echo "" + echo "예시:" + echo " $0 acrdigitalgarage01 rg-digitalgarage-03" + echo " $0 acrdigitalgarage01 rg-digitalgarage-03 acr-prod-secret" + echo "" +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -z "${ACR_NAME}" ] || [ -z "${RESOURCE_GROUP}" ]; then + echo "❌ ACR_NAME과 RESOURCE_GROUP는 필수 파라미터입니다." + echo "" + show_usage + exit 1 +fi + +# ACR 정보 설정 +REGISTRY_URL="${ACR_NAME}.azurecr.io" + +echo "" +echo "📋 ACR 정보:" +echo " ACR 이름: ${ACR_NAME}" +echo " 레지스트리 URL: ${REGISTRY_URL}" +echo " 리소스 그룹: ${RESOURCE_GROUP}" +echo " Secret 이름: ${SECRET_NAME}" + +# ACR credential 조회 +echo "" +echo "🔑 ACR credential 조회 중..." + +credential_json=$(az acr credential show --name "${ACR_NAME}" --resource-group "${RESOURCE_GROUP}" 2>/dev/null) + +if [ $? -ne 0 ]; then + echo "❌ ACR credential 조회 실패" + echo "확인 사항:" + echo " - ACR 이름: ${ACR_NAME}" + echo " - 리소스 그룹: ${RESOURCE_GROUP}" + echo " - Azure 권한" + exit 1 +fi + +# JSON에서 username과 password 추출 +username=$(echo "${credential_json}" | jq -r '.username') +password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + +if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + echo "❌ ACR credential 파싱 실패" + exit 1 +fi + +echo "✅ ACR credential 조회 성공" +echo " 사용자명: ${username}" +echo " 비밀번호: ${password:0:10}..." + +# 기존 Secret 삭제 (있는 경우) +if kubectl get secret "${SECRET_NAME}" &> /dev/null; then + echo "" + echo "🗑️ 기존 Secret 삭제 중..." + kubectl delete secret "${SECRET_NAME}" +fi + +# Image Pull Secret 생성 +echo "" +echo "🔐 Image Pull Secret 생성 중..." + +kubectl create secret docker-registry "${SECRET_NAME}" \ + --docker-server="${REGISTRY_URL}" \ + --docker-username="${username}" \ + --docker-password="${password}" + +if [ $? -eq 0 ]; then + echo "✅ Image Pull Secret 생성 성공!" +else + echo "❌ Image Pull Secret 생성 실패" + exit 1 +fi diff --git a/review/deployment/container/Dockerfile b/review/deployment/container/Dockerfile new file mode 100644 index 0000000..9012187 --- /dev/null +++ b/review/deployment/container/Dockerfile @@ -0,0 +1,72 @@ +# deployment/container/Dockerfile +# Service Image - Base Image 위에 애플리케이션만 추가 (AKS 최적화) +ARG BASE_IMAGE=kakao-review-api-base:latest +FROM ${BASE_IMAGE} + +# 메타데이터 +LABEL maintainer="admin@example.com" +LABEL version="1.0.1" +LABEL description="카카오맵 리뷰 분석 API - Service Image (AKS 최적화)" + +# root로 전환 (패키지 설치용) +USER root + +# 🔧 Chrome 실행을 위한 환경 변수 설정 (VM 환경과 동일) +ENV HOME=/home/appuser \ + WDM_LOCAL=1 \ + WDM_LOG_LEVEL=0 \ + CHROME_BIN=/usr/bin/google-chrome \ + CHROMEDRIVER_BIN=/usr/local/bin/chromedriver \ + DISPLAY=:99 \ + DBUS_SESSION_BUS_ADDRESS=/dev/null + +# Python 의존성 파일 복사 및 설치 +COPY app/requirements.txt /app/ +RUN pip install --no-cache-dir -r /app/requirements.txt + +# 애플리케이션 소스 복사 +COPY app/main.py /app/ + +# 🔧 Chrome 실행을 위한 디렉토리 및 권한 설정 (VM 환경과 동일) +RUN mkdir -p /home/appuser/.cache/selenium \ + && mkdir -p /home/appuser/.wdm \ + && mkdir -p /home/appuser/.local/share \ + && mkdir -p /tmp/chrome-user-data \ + && mkdir -p /tmp/.wdm \ + && chown -R appuser:appuser /home/appuser \ + && chown -R appuser:appuser /tmp/chrome-user-data \ + && chown -R appuser:appuser /tmp/.wdm \ + && chmod -R 755 /home/appuser \ + && chmod -R 777 /tmp/chrome-user-data \ + && chmod -R 777 /tmp/.wdm + +# /app 디렉토리 권한 설정 +RUN chown -R appuser:appuser /app + +# 🔧 ChromeDriver 접근 권한 확인 및 테스트 +RUN echo "=== ChromeDriver 정보 ===" \ + && ls -la /usr/local/bin/chromedriver \ + && chromedriver --version \ + && echo "=== Chrome 정보 ===" \ + && google-chrome --version \ + && echo "=== 권한 테스트 ===" \ + && su - appuser -c "chromedriver --version" || echo "appuser ChromeDriver 접근 확인" + +# 🔧 간단한 Selenium import 테스트만 수행 +RUN python3 -c "from selenium import webdriver; from selenium.webdriver.chrome.options import Options; from selenium.webdriver.chrome.service import Service; print('✅ Selenium 모듈 import 성공')" + +# 🔧 컨테이너 내 사용자를 appuser로 변경 (하지만 Chrome은 root 권한 필요) +USER appuser + +# 작업 디렉토리 설정 +WORKDIR /app + +# 포트 노출 (review 서비스용) +EXPOSE 19000 + +# 🔧 헬스체크 (개선된 타임아웃) +HEALTHCHECK --interval=30s --timeout=15s --start-period=60s --retries=3 \ + CMD curl -f http://localhost:19000/health || exit 1 + +# 🔧 애플리케이션 실행 (로그 레벨 설정) +CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "19000", "--log-level", "info"] diff --git a/review/deployment/container/Dockerfile-base b/review/deployment/container/Dockerfile-base new file mode 100644 index 0000000..48595e6 --- /dev/null +++ b/review/deployment/container/Dockerfile-base @@ -0,0 +1,103 @@ +# deployment/container/Dockerfile-base +FROM python:3.11-slim + +# 메타데이터 +LABEL maintainer="admin@example.com" +LABEL description="카카오맵 리뷰 분석 API - Base Image with Chrome (AKS 최적화)" +LABEL version="base-1.0.2" + +# 환경 변수 설정 +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + DEBIAN_FRONTEND=noninteractive \ + CHROME_BIN=/usr/bin/google-chrome \ + CHROMEDRIVER_BIN=/usr/local/bin/chromedriver + +# 🔧 필수 패키지 설치 (VM setup.sh와 동일한 패키지들) +RUN apt-get update && apt-get install -y \ + python3-pip \ + python3-venv \ + unzip \ + wget \ + curl \ + ca-certificates \ + fonts-liberation \ + libasound2 \ + libatk-bridge2.0-0 \ + libdrm2 \ + libxcomposite1 \ + libxdamage1 \ + libxrandr2 \ + libgbm1 \ + libxss1 \ + libnss3 \ + libxext6 \ + libxfixes3 \ + libxi6 \ + libxrender1 \ + libcairo-gobject2 \ + libgtk-3-0 \ + libgdk-pixbuf2.0-0 \ + libgtk-3-dev \ + libgconf-2-4 \ + && rm -rf /var/lib/apt/lists/* + +# 🔧 Google Chrome 설치 (VM setup.sh와 동일한 방식) +RUN wget -q -O - https://dl.google.com/linux/linux_signing_key.pub | apt-key add - \ + && echo "deb [arch=amd64] http://dl.google.com/linux/chrome/deb/ stable main" > /etc/apt/sources.list.d/google-chrome.list \ + && apt-get update \ + && apt-get install -y google-chrome-stable \ + && rm -rf /var/lib/apt/lists/* + +# Chrome 설치 확인 +RUN google-chrome --version + +# 🔧 ChromeDriver 설치 (VM setup.sh와 동일한 방식) +RUN CHROME_VERSION=$(google-chrome --version | grep -oP '\d+\.\d+\.\d+\.\d+' | cut -d'.' -f1) \ + && echo "Chrome 주 버전: $CHROME_VERSION" \ + && CHROMEDRIVER_VERSION=$(curl -s "https://googlechromelabs.github.io/chrome-for-testing/LATEST_RELEASE_$CHROME_VERSION") \ + && echo "ChromeDriver 버전: $CHROMEDRIVER_VERSION" \ + && wget -q "https://storage.googleapis.com/chrome-for-testing-public/$CHROMEDRIVER_VERSION/linux64/chromedriver-linux64.zip" -O /tmp/chromedriver.zip \ + && unzip -q /tmp/chromedriver.zip -d /tmp/ \ + && mv /tmp/chromedriver-linux64/chromedriver /usr/local/bin/chromedriver \ + && chmod +x /usr/local/bin/chromedriver \ + && rm -rf /tmp/chromedriver* \ + && chromedriver --version + +# Chrome 및 ChromeDriver 최종 확인 +RUN echo "=== Chrome 정보 ===" \ + && google-chrome --version \ + && echo "=== ChromeDriver 정보 ===" \ + && chromedriver --version \ + && echo "=== 설치 경로 확인 ===" \ + && ls -la /usr/bin/google-chrome* \ + && ls -la /usr/local/bin/chromedriver + +# 🔧 Chrome 실행을 위한 디렉토리 생성 +RUN mkdir -p /tmp/chrome-user-data \ + && mkdir -p /home/appuser/.cache/selenium \ + && mkdir -p /home/appuser/.wdm \ + && mkdir -p /home/appuser/.local/share \ + && chmod 777 /tmp/chrome-user-data + +# 🔧 비root 사용자 생성 (하지만 Chrome은 root로 실행) +RUN groupadd -r appuser && useradd -r -g appuser -d /home/appuser -s /bin/bash appuser \ + && mkdir -p /home/appuser \ + && chown -R appuser:appuser /home/appuser + +# 작업 디렉토리 생성 +WORKDIR /app +RUN chown appuser:appuser /app + +# pip 업그레이드 +RUN pip install --no-cache-dir --upgrade pip + +# Chrome 실행 테스트 (빌드 시 검증) +RUN google-chrome --headless --no-sandbox --disable-dev-shm-usage --virtual-time-budget=1000 --run-all-compositor-stages-before-draw data:text/html,\\\Test\\\ || echo "Chrome 테스트 완료" + +# 포트 노출 +EXPOSE 8000 + +# 기본 명령어 (오버라이드 가능) +CMD ["python", "--version"] + diff --git a/review/deployment/manifests/configmap.yaml b/review/deployment/manifests/configmap.yaml new file mode 100644 index 0000000..0e64b6b --- /dev/null +++ b/review/deployment/manifests/configmap.yaml @@ -0,0 +1,78 @@ +# deployment/manifests/configmap.yaml +apiVersion: v1 +kind: ConfigMap +metadata: + name: kakao-review-api-config +data: + # 애플리케이션 설정 + APP_TITLE: "카카오맵 리뷰 분석 API" + APP_VERSION: "1.0.1" + APP_DESCRIPTION: "교육 목적 전용 - 실제 서비스 사용 금지" + + # 서버 설정 + HOST: "0.0.0.0" + PORT: "8000" + WORKERS: "1" + LOG_LEVEL: "info" + + # API 기본값 설정 (AKS 환경에 최적화) + DEFAULT_MAX_TIME: "300" + DEFAULT_DAYS_LIMIT: "60" + MAX_DAYS_LIMIT: "365" + MIN_MAX_TIME: "60" + MAX_MAX_TIME: "600" + + # 🔧 Chrome 브라우저 설정 (AKS 환경 최적화) + CHROME_OPTIONS: | + --headless=new + --no-sandbox + --disable-dev-shm-usage + --disable-gpu + --disable-software-rasterizer + --window-size=1920,1080 + --disable-extensions + --disable-plugins + --disable-usb-keyboard-detect + --no-first-run + --no-default-browser-check + --disable-logging + --log-level=3 + --disable-background-timer-throttling + --disable-backgrounding-occluded-windows + --disable-renderer-backgrounding + --disable-features=TranslateUI,VizDisplayCompositor + --disable-ipc-flooding-protection + --memory-pressure-off + --max_old_space_size=4096 + --no-zygote + --disable-setuid-sandbox + --disable-background-networking + --disable-default-apps + --disable-sync + --metrics-recording-only + --safebrowsing-disable-auto-update + --disable-prompt-on-repost + --disable-hang-monitor + --disable-client-side-phishing-detection + --disable-component-update + --disable-domain-reliability + --user-data-dir=/tmp/chrome-user-data + --data-path=/tmp/chrome-user-data + --disk-cache-dir=/tmp/chrome-cache + --aggressive-cache-discard + --disable-web-security + --allow-running-insecure-content + --disable-blink-features=AutomationControlled + + # 스크롤링 설정 (AKS 환경에 맞게 조정) + SCROLL_CHECK_INTERVAL: "5" + SCROLL_NO_CHANGE_LIMIT: "6" + SCROLL_WAIT_TIME_SHORT: "2.0" + SCROLL_WAIT_TIME_LONG: "3.0" + + # 법적 경고 메시지 + LEGAL_WARNING_ENABLED: "true" + CONTACT_EMAIL: "admin@example.com" + + # 건강 체크 설정 + HEALTH_CHECK_TIMEOUT: "10" diff --git a/review/deployment/manifests/deployment.yaml b/review/deployment/manifests/deployment.yaml new file mode 100644 index 0000000..226eb1a --- /dev/null +++ b/review/deployment/manifests/deployment.yaml @@ -0,0 +1,130 @@ +# deployment/manifests/deployment.yaml +apiVersion: apps/v1 +kind: Deployment +metadata: + name: kakao-review-api + labels: + app: kakao-review-api + version: v1 +spec: + replicas: 1 + selector: + matchLabels: + app: kakao-review-api + template: + metadata: + labels: + app: kakao-review-api + version: v1 + spec: + imagePullSecrets: + - name: acr-secret + containers: + - name: api + image: acrdigitalgarage03.azurecr.io/kakao-review-api:latest + imagePullPolicy: Always + ports: + - containerPort: 19000 + name: http + + # 🔧 ConfigMap 환경 변수 + envFrom: + - configMapRef: + name: kakao-review-api-config + + # 🔧 Secret 환경 변수 + env: + - name: EXTERNAL_API_KEY + valueFrom: + secretKeyRef: + name: kakao-review-api-secret + key: EXTERNAL_API_KEY + - name: DB_USERNAME + valueFrom: + secretKeyRef: + name: kakao-review-api-secret + key: DB_USERNAME + - name: DB_PASSWORD + valueFrom: + secretKeyRef: + name: kakao-review-api-secret + key: DB_PASSWORD + - name: JWT_SECRET + valueFrom: + secretKeyRef: + name: kakao-review-api-secret + key: JWT_SECRET + # 🔧 Chrome/ChromeDriver 환경 변수 (VM과 동일) + - name: WDM_LOCAL + value: "/tmp/.wdm" + - name: WDM_LOG_LEVEL + value: "0" + - name: CHROME_BIN + value: "/usr/bin/google-chrome" + - name: CHROMEDRIVER_BIN + value: "/usr/local/bin/chromedriver" + - name: DISPLAY + value: ":99" + - name: DBUS_SESSION_BUS_ADDRESS + value: "/dev/null" + + # 🔧 리소스 제한 (Chrome 실행에 충분한 리소스) + resources: + requests: + memory: "2Gi" + cpu: "1000m" + limits: + memory: "4Gi" + cpu: "2000m" + + # 🔧 헬스 체크 (타임아웃 증가) + livenessProbe: + httpGet: + path: /health + port: 19000 + initialDelaySeconds: 60 + periodSeconds: 30 + timeoutSeconds: 15 + failureThreshold: 5 + + readinessProbe: + httpGet: + path: /health + port: 19000 + initialDelaySeconds: 30 + periodSeconds: 10 + timeoutSeconds: 10 + failureThreshold: 5 + + # 🔧 간소화된 보안 컨텍스트 (AKS 호환) + securityContext: + runAsNonRoot: false + runAsUser: 0 + allowPrivilegeEscalation: true + readOnlyRootFilesystem: false + capabilities: + add: + - SYS_ADMIN + drop: [] + + # 🔧 볼륨 마운트 (Chrome 실행 최적화) + volumeMounts: + - name: tmp-volume + mountPath: /tmp + - name: dev-shm + mountPath: /dev/shm + + # 🔧 볼륨 정의 (간소화) + volumes: + - name: tmp-volume + emptyDir: {} + - name: dev-shm + emptyDir: + medium: Memory + sizeLimit: 2Gi + + restartPolicy: Always + + # 🔧 Pod 레벨 보안 설정 제거 (AKS 호환을 위해) + # securityContext: 제거 + diff --git a/review/deployment/manifests/ingress.yaml b/review/deployment/manifests/ingress.yaml new file mode 100644 index 0000000..e11b843 --- /dev/null +++ b/review/deployment/manifests/ingress.yaml @@ -0,0 +1,39 @@ +# deployment/manifests/ingress.yaml +apiVersion: networking.k8s.io/v1 +kind: Ingress +metadata: + name: kakao-review-api-ingress + annotations: + nginx.ingress.kubernetes.io/rewrite-target: / + nginx.ingress.kubernetes.io/ssl-redirect: "false" + nginx.ingress.kubernetes.io/proxy-body-size: "10m" + # 🔧 타임아웃 설정 (Chrome 분석 시간 고려) + nginx.ingress.kubernetes.io/proxy-read-timeout: "1800" + nginx.ingress.kubernetes.io/proxy-send-timeout: "1800" + nginx.ingress.kubernetes.io/client-body-timeout: "1800" + nginx.ingress.kubernetes.io/proxy-connect-timeout: "60" + # 🔧 CORS 설정 (필요시) + nginx.ingress.kubernetes.io/enable-cors: "true" + nginx.ingress.kubernetes.io/cors-allow-origin: "*" + nginx.ingress.kubernetes.io/cors-allow-methods: "GET, POST, OPTIONS" + nginx.ingress.kubernetes.io/cors-allow-headers: "DNT,User-Agent,X-Requested-With,If-Modified-Since,Cache-Control,Content-Type,Range,Authorization" +spec: + ingressClassName: nginx + rules: + # 🔧 환경에 맞게 호스트명 수정 필요 + - host: kakao-review-api.20.249.191.180.nip.io + http: + paths: + - path: / + pathType: Prefix + backend: + service: + name: kakao-review-api-service + port: + number: 80 + # 🔧 TLS 설정 (HTTPS 필요시 주석 해제) + # tls: + # - hosts: + # - kakao-review-api.example.com + # secretName: kakao-review-api-tls + diff --git a/review/deployment/manifests/secret.yaml b/review/deployment/manifests/secret.yaml new file mode 100644 index 0000000..db8b8cb --- /dev/null +++ b/review/deployment/manifests/secret.yaml @@ -0,0 +1,21 @@ +# deployment/manifests/secret.yaml +apiVersion: v1 +kind: Secret +metadata: + name: kakao-review-api-secret +type: Opaque +data: + # 🔧 현재 사용하지 않지만 향후 확장을 위한 플레이스홀더 + # 실제 값 설정 시: echo -n "your-value" | base64 + + # API 키 (향후 카카오 공식 API 연동용) + EXTERNAL_API_KEY: "" + + # 데이터베이스 연결 정보 (향후 DB 연동용) + DB_USERNAME: "" + DB_PASSWORD: "" + DB_HOST: "" + + # JWT 시크릿 (향후 인증 기능용) + JWT_SECRET: "" + diff --git a/review/deployment/manifests/service.yaml b/review/deployment/manifests/service.yaml new file mode 100644 index 0000000..874417d --- /dev/null +++ b/review/deployment/manifests/service.yaml @@ -0,0 +1,17 @@ +# deployment/manifests/service.yaml +apiVersion: v1 +kind: Service +metadata: + name: kakao-review-api-service + labels: + app: kakao-review-api +spec: + type: ClusterIP + ports: + - port: 80 + targetPort: 19000 + protocol: TCP + name: http + selector: + app: kakao-review-api + diff --git a/review/setup.sh b/review/setup.sh new file mode 100755 index 0000000..aa2154d --- /dev/null +++ b/review/setup.sh @@ -0,0 +1,280 @@ +#!/bin/bash +# setup.sh - Review Analysis API 환경 설정 스크립트 + +set -e + +echo "🔍 Review Analysis API 환경 설정 시작..." + +# 시스템 정보 확인 +echo "📊 시스템 정보:" +echo " - OS: $(lsb_release -d | cut -f2)" +echo " - Python: $(python3 --version 2>/dev/null || echo 'Python3 미설치')" +echo " - pip: $(pip3 --version 2>/dev/null || echo 'pip3 미설치')" + +# 필수 패키지 설치 +echo "" +echo "📦 필수 패키지 설치 중..." +sudo apt update +sudo apt install -y python3-pip python3-venv unzip wget curl jq + +# Chrome 브라우저 설치 (리뷰 분석용) +echo "" +echo "🌐 Chrome 브라우저 설치 확인 중..." +if ! command -v google-chrome &> /dev/null; then + echo "Chrome 브라우저 설치 중..." + wget -q -O - https://dl.google.com/linux/linux_signing_key.pub | sudo apt-key add - + echo "deb [arch=amd64] http://dl.google.com/linux/chrome/deb/ stable main" | sudo tee /etc/apt/sources.list.d/google-chrome.list + sudo apt update + sudo apt install -y google-chrome-stable + echo "✅ Chrome 브라우저 설치 완료" +else + CHROME_VERSION=$(google-chrome --version) + echo "✅ Chrome 브라우저 이미 설치됨: ${CHROME_VERSION}" +fi + +# ChromeDriver 설치 +echo "" +echo "🚗 ChromeDriver 설치 중..." +if [ -f "/usr/local/bin/chromedriver" ]; then + echo "기존 ChromeDriver 제거 중..." + sudo rm -f /usr/local/bin/chromedriver +fi + +CHROME_VERSION=$(google-chrome --version | grep -oP '\d+\.\d+\.\d+\.\d+' | cut -d'.' -f1) +echo "Chrome 주 버전: ${CHROME_VERSION}" + +CHROMEDRIVER_VERSION=$(curl -s "https://googlechromelabs.github.io/chrome-for-testing/LATEST_RELEASE_${CHROME_VERSION}") +echo "ChromeDriver 버전: ${CHROMEDRIVER_VERSION}" + +TEMP_DIR=$(mktemp -d) +cd "$TEMP_DIR" + +wget -q "https://storage.googleapis.com/chrome-for-testing-public/${CHROMEDRIVER_VERSION}/linux64/chromedriver-linux64.zip" +unzip -q chromedriver-linux64.zip +sudo mv chromedriver-linux64/chromedriver /usr/local/bin/ +sudo chmod +x /usr/local/bin/chromedriver + +cd - > /dev/null +rm -rf "$TEMP_DIR" + +echo "✅ ChromeDriver 설치 완료: $(chromedriver --version)" + +# Python 버전 확인 +PYTHON_VERSION=$(python3 -c "import sys; print('.'.join(map(str, sys.version_info[:2])))") +echo "" +echo "📍 Python 버전: ${PYTHON_VERSION}" + +if [ "$(echo "${PYTHON_VERSION} < 3.8" | bc)" -eq 1 ]; then + echo "⚠️ Python 3.8 이상이 권장됩니다." +fi + +# Python 가상환경 설정 +echo "" +echo "🐍 Python 가상환경 설정 중..." +if [ ! -d "venv" ]; then + python3 -m venv venv + echo "✅ 가상환경 생성 완료" +else + echo "✅ 기존 가상환경 발견" +fi + +# 가상환경 활성화 및 라이브러리 설치 +echo "📚 Python 라이브러리 설치 중..." +source venv/bin/activate + +# pip 업그레이드 +pip install --upgrade pip + +# 필요한 라이브러리 설치 +if [ -f "app/requirements.txt" ]; then + pip install -r app/requirements.txt + echo "✅ requirements.txt에서 라이브러리 설치 완료" +else + echo "⚠️ app/requirements.txt 파일을 찾을 수 없습니다." + echo "🔧 기본 라이브러리들을 직접 설치합니다..." + pip install fastapi uvicorn beautifulsoup4 selenium webdriver-manager pydantic python-multipart lxml +fi + +# 데이터 디렉토리 생성 +echo "" +echo "📁 데이터 디렉토리 설정 중..." +mkdir -p data +chmod 755 data +echo "✅ 데이터 디렉토리 생성: $(pwd)/data" + +# 환경변수 파일 생성 (예시) +echo "" +echo "⚙️ 환경변수 파일 생성 중..." +cat > .env << EOF +# 애플리케이션 설정 +APP_TITLE=카카오맵 리뷰 분석 API +APP_VERSION=1.0.1 +APP_DESCRIPTION=교육 목적 전용 - 실제 서비스 사용 금지 + +# 서버 설정 +HOST=0.0.0.0 +PORT=19000 +LOG_LEVEL=info + +# API 기본값 설정 +DEFAULT_MAX_TIME=300 +DEFAULT_DAYS_LIMIT=60 +MAX_DAYS_LIMIT=365 +MIN_MAX_TIME=60 +MAX_MAX_TIME=600 + +# Chrome 브라우저 설정 +CHROME_OPTIONS=--headless=new --no-sandbox --disable-dev-shm-usage --disable-gpu --window-size=1920,1080 +SCROLL_CHECK_INTERVAL=5 +SCROLL_NO_CHANGE_LIMIT=6 +SCROLL_WAIT_TIME_SHORT=2.0 +SCROLL_WAIT_TIME_LONG=3.0 + +# 법적 경고 메시지 +LEGAL_WARNING_ENABLED=true +CONTACT_EMAIL=admin@example.com + +# 건강 체크 설정 +HEALTH_CHECK_TIMEOUT=10 + +# AI API 설정 (향후 Claude API 연동용) +# CLAUDE_API_KEY=your_claude_api_key_here + +# 데이터베이스 설정 (향후 PostgreSQL 연동용) +# DB_HOST=localhost +# DB_PORT=5432 +# DB_NAME=review_analysis +# DB_USERNAME=your_db_username +# DB_PASSWORD=your_db_password +EOF + echo "✅ .env 파일 생성 완료" + +# 네트워크 연결 테스트 +echo "" +echo "🌐 네트워크 연결 테스트 중..." + +# 카카오맵 연결 테스트 +if curl -s --connect-timeout 5 "https://place.map.kakao.com" > /dev/null; then + echo "✅ 카카오맵 서버 연결 가능" +else + echo "❌ 카카오맵 서버 연결 실패" + echo " 인터넷 연결 상태를 확인해주세요." +fi + +# Selenium 및 Chrome 테스트 +echo "" +echo "🧪 Selenium 및 Chrome 테스트 중..." +source venv/bin/activate +python3 -c " +try: + from selenium import webdriver + from selenium.webdriver.chrome.options import Options + from selenium.webdriver.chrome.service import Service + print('✅ Selenium 모듈 import 성공') + + options = Options() + options.add_argument('--headless') + options.add_argument('--no-sandbox') + options.add_argument('--disable-dev-shm-usage') + + try: + service = Service('/usr/local/bin/chromedriver') + driver = webdriver.Chrome(service=service, options=options) + driver.get('data:text/html,

Test

') + title = driver.title + driver.quit() + print('✅ Chrome WebDriver 테스트 성공') + except Exception as e: + print(f'❌ Chrome WebDriver 테스트 실패: {e}') + +except ImportError as e: + print(f'❌ Selenium import 실패: {e}') +except Exception as e: + print(f'❌ 테스트 중 오류: {e}') +" + +# Docker 설치 확인 (선택사항) +echo "" +echo "🐳 Docker 설치 확인 중..." +if command -v docker &> /dev/null; then + DOCKER_VERSION=$(docker --version) + echo "✅ Docker 설치됨: ${DOCKER_VERSION}" + + # Docker 권한 확인 + if docker ps &> /dev/null; then + echo "✅ Docker 권한 확인됨" + else + echo "⚠️ Docker 권한 없음. 다음 명령어로 권한을 추가하세요:" + echo " sudo usermod -aG docker $USER" + echo " newgrp docker" + fi +else + echo "⚠️ Docker가 설치되지 않음 (컨테이너 배포 시 필요)" + echo " 설치 방법: https://docs.docker.com/engine/install/ubuntu/" +fi + +# 방화벽 설정 확인 +echo "" +echo "🔥 방화벽 설정 확인 중..." +if command -v ufw &> /dev/null; then + UFW_STATUS=$(sudo ufw status | head -n1 | awk '{print $2}') + if [ "${UFW_STATUS}" = "active" ]; then + echo "🔥 UFW 방화벽 활성화됨" + if sudo ufw status | grep -q "19000"; then + echo "✅ 포트 19000 방화벽 규칙 확인됨" + else + echo "⚠️ 포트 19000 방화벽 규칙 없음" + echo " 다음 명령어로 포트를 열어주세요:" + echo " sudo ufw allow 19000" + fi + else + echo "✅ UFW 방화벽 비활성화됨" + fi +else + echo "✅ UFW 방화벽 미설치" +fi + +echo "" +echo "🎉 환경 설정 완료!" +echo "" +echo "📋 다음 단계:" +echo "1. 가상환경 활성화:" +echo " source venv/bin/activate" +echo "" +echo "2. 환경변수 설정:" +echo " export DATA_DIR=\"./data\"" +echo "" +echo "3. 애플리케이션 실행:" +echo " python app/main.py" +echo " 또는" +echo " uvicorn app.main:app --host 0.0.0.0 --port 19000 --reload" +echo "" +echo "4. 웹 브라우저에서 접속:" +echo " http://localhost:19000 (메인 페이지)" +echo " http://localhost:19000/docs (Swagger UI)" +echo " http://localhost:19000/health (헬스체크)" +echo "" +echo "5. API 테스트:" +echo " curl -X POST \"http://localhost:19000/analyze\" \\" +echo " -H \"Content-Type: application/json\" \\" +echo " -d '{\"store_id\":\"501745730\",\"days_limit\":7,\"max_time\":300}'" +echo "" +echo "⚠️ 중요 법적 경고사항:" +echo " 이 서비스는 교육 목적으로만 사용하세요!" +echo " 실제 웹사이트 크롤링은 법적 위험이 있습니다." +echo " 카카오 공식 API를 사용하는 것을 권장합니다: developers.kakao.com" +echo "" +echo "💡 문제 발생 시:" +echo " - 로그 확인: tail -f 로그파일" +echo " - 환경변수 확인: cat .env" +echo " - Chrome 확인: google-chrome --version" +echo " - ChromeDriver 확인: chromedriver --version" +echo "" +echo "🔧 설정 파일 위치:" +echo " - 환경변수: $(pwd)/.env" +echo " - 데이터 저장: $(pwd)/data/" +echo " - 애플리케이션: $(pwd)/app/" + +deactivate 2>/dev/null || true +echo "" +echo "✅ Review Analysis API 환경 설정이 완료되었습니다!" \ No newline at end of file diff --git a/vector/README.md b/vector/README.md new file mode 100644 index 0000000..f8d1eba --- /dev/null +++ b/vector/README.md @@ -0,0 +1,614 @@ +# 음식점 Vector DB 구축 서비스 + +카카오 로컬 API를 활용하여 음식점 정보를 수집하고 Vector DB로 구축한 후, Claude AI와 연동하여 점주의 비즈니스 개선 요청을 처리하는 서비스입니다. + +## 📋 프로젝트 개요 + +### 주요 기능 +- 🔍 **카카오 로컬 API 연동**: 키워드 및 지역 기반 음식점 검색 +- 🤖 **Vector DB 구축**: Sentence Transformer를 이용한 임베딩 및 Chroma DB 저장 +- 🔄 **중복 처리 개선**: 기존 데이터 존재 여부 확인 및 업데이트/신규 추가 분리 +- 🧠 **Claude AI 연동**: 점주 액션 요청에 대한 맞춤형 조언 생성 +- 🎯 **유사도 검색**: Vector DB를 활용한 유사 음식점 검색 +- 📊 **처리 통계**: 신규 추가, 업데이트, 중복 등 상세 통계 제공 +- 🚀 **RESTful API 제공**: FastAPI 기반의 완전한 API 서비스 +- 📚 **Swagger UI 지원**: 자동 생성되는 API 문서 +- ☸️ **Kubernetes 배포**: 완전한 컨테이너 오케스트레이션 지원 +- 🔧 **환경변수 설정**: ConfigMap과 Secret을 통한 유연한 설정 관리 + +### 기술 스택 +- **Backend**: Python 3.11, FastAPI, aiohttp +- **Vector DB**: Chroma DB +- **ML**: Sentence Transformers, torch +- **AI**: Anthropic Claude API +- **External API**: Kakao Local API +- **Container**: Docker, Multi-stage build +- **Orchestration**: Kubernetes (AKS) +- **Registry**: Azure Container Registry (ACR) +- **Documentation**: Swagger UI, ReDoc + +## 🏗️ 프로젝트 구조 + +``` +review-api/vector/ +├── app/ # 애플리케이션 소스 +│ ├── main.py # 메인 애플리케이션 +│ ├── requirements.txt # Python 의존성 +│ ├── config/ # 설정 관리 +│ │ └── settings.py # 환경 설정 +│ ├── models/ # 데이터 모델 +│ ├── services/ # 비즈니스 로직 +│ │ ├── vector_service.py # Vector DB 서비스 +│ │ ├── claude_service.py # Claude AI 서비스 +│ │ └── kakao_service.py # 카카오 API 서비스 +│ └── utils/ # 유틸리티 함수 +│ └── data_utils.py # 데이터 처리 유틸 +├── deployment/ # 배포 관련 파일 +│ ├── container/ # 컨테이너 이미지 빌드 +│ │ ├── Dockerfile # 서비스 이미지 빌드 +│ │ └── Dockerfile-base # 베이스 이미지 빌드 +│ └── manifests/ # Kubernetes 매니페스트 +│ ├── configmap.yaml # 환경 설정 +│ ├── secret.yaml # 민감 정보 (API 키) +│ ├── deployment.yaml # 애플리케이션 배포 +│ ├── service.yaml # 서비스 노출 +│ ├── ingress.yaml # 외부 접근 +│ └── pvc.yaml # 영구 저장소 (Vector DB) +├── build-base.sh # 베이스 이미지 빌드 스크립트 +├── build.sh # 서비스 이미지 빌드 스크립트 +├── create-imagepullsecret.sh # ACR 인증 설정 스크립트 +├── setup.sh # 로컬 환경 설정 스크립트 +└── README.md # 프로젝트 문서 +``` + +## 📋 사전 작업 + +### 카카오 API 설정 +카카오 developers 포탈에서 애플리케이션 등록이 필요합니다. + +1. **포탈 접속**: https://developers.kakao.com/console/app +2. **애플리케이션 등록**: + - 앱 이름: `VectorDBBuilder` + - 회사명: `{회사명}` + - 카테고리: `식음료` +3. **카카오맵 활성화**: 등록한 애플리케이션에서 좌측 '카카오맵' 메뉴 클릭하여 활성화 + +### Claude API 설정 +Anthropic Claude API 키가 필요합니다. + +1. **포탈 접속**: https://console.anthropic.com/ +2. **API 키 발급**: Console에서 API Keys 메뉴에서 발급 +3. **모델 확인**: `claude-sonnet-4-20250514` 사용 + +## 🚀 빠른 시작 + +### 1. 로컬 개발 환경 설정 + +```bash +# 저장소 클론 (review-api/vector 디렉토리로 이동) +cd review-api/vector + +# 환경 설정 스크립트 실행 (시간이 오래 걸림) +chmod +x setup.sh +./setup.sh + +# 가상환경 활성화 +source venv/bin/activate + +# Claude API 키 설정 (.env 파일 생성/수정) +cat > .env << EOF +CLAUDE_API_KEY=your-actual-claude-api-key +KAKAO_API_KEY=your-kakao-api-key +EOF + +# 애플리케이션 실행 +python app/main.py +``` + +### 2. 로컬 웹 브라우저 접속 + +```bash +# 애플리케이션이 정상 실행된 후 아래 URL로 접속 +``` + +- **메인 페이지**: http://localhost:8000 +- **Swagger UI**: http://localhost:8000/docs +- **ReDoc**: http://localhost:8000/redoc +- **헬스체크**: http://localhost:8000/health +- **Vector DB 상태**: http://localhost:8000/vector-status +- **환경 설정**: http://localhost:8000/config + +### 3. API 테스트 + +```bash +# 1. Vector DB 구축 (지역과 가게명으로 동종업체 분석) +curl -X POST "http://localhost:8000/build-vector-db" \ + -H "Content-Type: application/json" \ + -d '{ + "region": "서울특별시 강남구 역삼동", + "store_name": "맛있는 치킨집", + "force_rebuild": false + }' + +# 2. 점주 액션 요청 (Claude AI 기반 조언) +curl -X POST "http://localhost:8000/action-request" \ + -H "Content-Type: application/json" \ + -d '{ + "store_id": "12345", + "context": "매출이 감소하고 있어서 메뉴 개선이 필요합니다." + }' + +# 3. Vector DB 상태 확인 +curl "http://localhost:8000/vector-status" + +# 4. 환경 설정 확인 +curl "http://localhost:8000/config" + +# 5. 유사 음식점 검색 +curl -X POST "http://localhost:8000/search-similar" \ + -H "Content-Type: application/json" \ + -d '{ + "query": "분위기 좋은 카페", + "business_type": "카페", + "limit": 5 + }' +``` + +## 🐳 Docker 컨테이너 실행 + +### 베이스 이미지 빌드 + +```bash +# ACR에 베이스 이미지 빌드 및 푸시 +./build-base.sh latest acrdigitalgarage03 rg-digitalgarage-03 + +# 로컬 베이스 이미지 빌드 +./build-base.sh latest +``` + +### 서비스 이미지 빌드 + +```bash +# ACR에 서비스 이미지 빌드 및 푸시 +./build.sh latest acrdigitalgarage03 rg-digitalgarage-03 + +# 로컬 서비스 이미지 빌드 +./build.sh latest +``` + +### 로컬 Docker 실행 + +```bash +# 컨테이너 실행 (환경변수 설정 필요) +docker run -p 8000:8000 \ + -e KAKAO_API_KEY="your-kakao-api-key" \ + -e CLAUDE_API_KEY="your-claude-api-key" \ + -e PORT=8000 \ + -v $(pwd)/vector_db:/app/vectordb \ + vector-api:latest + +# 백그라운드 실행 (영구 볼륨 사용) +docker volume create vector_db_vol +docker run -d -p 8000:8000 \ + --name vector-api \ + -e KAKAO_API_KEY="your-kakao-api-key" \ + -e CLAUDE_API_KEY="your-claude-api-key" \ + -e PORT=8000 \ + -v vector_db_vol:/app/vectordb \ + vector-api:latest + +# 컨테이너 로그 확인 +docker logs vector-api -f + +# Vector DB 데이터 확인 +docker exec -it vector-api ls -la /app/vectordb/ +``` + +## ☸️ Kubernetes 배포 + +### 1. ACR Image Pull Secret 생성 + +```bash +# Image Pull Secret 생성 +./create-imagepullsecret.sh acrdigitalgarage03 rg-digitalgarage-03 +``` + +### 2. Kubernetes 리소스 배포 + +```bash +# 영구 볼륨 생성 (Vector DB 저장용) +kubectl apply -f deployment/manifests/pvc.yaml + +# ConfigMap 및 Secret 적용 +kubectl apply -f deployment/manifests/configmap.yaml +kubectl apply -f deployment/manifests/secret.yaml + +# 애플리케이션 배포 +kubectl apply -f deployment/manifests/deployment.yaml +kubectl apply -f deployment/manifests/service.yaml +kubectl apply -f deployment/manifests/ingress.yaml +``` + +### 3. 배포 상태 확인 + +```bash +# Pod 상태 확인 +kubectl get pods -l app=vector-api + +# 서비스 상태 확인 +kubectl get svc vector-api-service + +# Ingress 상태 확인 +kubectl get ingress vector-api-ingress + +# PVC 상태 확인 (Vector DB 저장소) +kubectl get pvc vector-db-pvc + +# 로그 확인 +kubectl logs -l app=vector-api -f + +# Vector DB 디렉토리 확인 +kubectl exec -it deployment/vector-api -- ls -la /app/vectordb/ +``` + +### 4. 🌐 외부 브라우저에서 접속하기 + +#### Ingress 주소 확인 방법 + +```bash +# 1. Ingress 설정된 호스트 확인 +kubectl get ingress vector-api-ingress -o jsonpath='{.spec.rules[0].host}' + +# 2. Ingress External IP 확인 (LoadBalancer 타입인 경우) +kubectl get ingress vector-api-ingress + +# 3. Ingress Controller의 External IP 확인 +kubectl get svc -n ingress-nginx ingress-nginx-controller + +# 4. 현재 설정된 ingress 주소 확인 +INGRESS_HOST=$(kubectl get ingress vector-api-ingress -o jsonpath='{.spec.rules[0].host}') +echo "🌐 Vector API URL: http://${INGRESS_HOST}" +``` + +#### 브라우저 접속 주소 + +현재 설정된 주소로 접속하세요: + +```bash +# 현재 설정된 기본 주소 (환경에 따라 다를 수 있음) +INGRESS_URL="http://vector-api.20.249.191.180.nip.io" +echo "브라우저에서 접속: ${INGRESS_URL}" +``` + +**주요 접속 페이지:** +- **🏠 메인 페이지**: http://vector-api.20.249.191.180.nip.io +- **📖 Swagger UI**: http://vector-api.20.249.191.180.nip.io/docs +- **📄 ReDoc**: http://vector-api.20.249.191.180.nip.io/redoc +- **❤️ 헬스체크**: http://vector-api.20.249.191.180.nip.io/health +- **🗂️ Vector DB 상태**: http://vector-api.20.249.191.180.nip.io/vector-status +- **⚙️ 환경 설정**: http://vector-api.20.249.191.180.nip.io/config + +#### 접속 테스트 + +```bash +# API 접속 테스트 +curl "http://vector-api.20.249.191.180.nip.io/health" + +# Vector DB 상태 확인 +curl "http://vector-api.20.249.191.180.nip.io/vector-status" + +# 설정 정보 확인 +curl "http://vector-api.20.249.191.180.nip.io/config" + +# Swagger UI 접속 확인 +curl -I "http://vector-api.20.249.191.180.nip.io/docs" +``` + +## ⚙️ 환경 설정 + +### 필수 환경변수 + +| 변수명 | 설명 | 기본값 | 예시 | +|--------|------|--------|------| +| `KAKAO_API_KEY` | 카카오 API 키 | - | `your-kakao-api-key` | +| `CLAUDE_API_KEY` | Claude API 키 | - | `sk-ant-api03-...` | +| `CLAUDE_MODEL` | Claude 모델명 | `claude-sonnet-4-20250514` | `claude-sonnet-4-20250514` | + +### 선택적 환경변수 + +| 변수명 | 설명 | 기본값 | 예시 | +|--------|------|--------|------| +| `HOST` | 서버 호스트 | `0.0.0.0` | `localhost` | +| `PORT` | 서버 포트 | `8000` | `8000` | +| `LOG_LEVEL` | 로그 레벨 | `info` | `debug` | +| `VECTOR_DB_PATH` | Vector DB 경로 | `/app/vectordb` | `/data/vectordb` | +| `VECTOR_DB_COLLECTION` | 컬렉션명 | `restaurant_reviews` | `stores` | +| `EMBEDDING_MODEL` | 임베딩 모델 | `sentence-transformers/all-MiniLM-L6-v2` | - | +| `MAX_RESTAURANTS_PER_CATEGORY` | 카테고리별 최대 음식점 수 | `50` | `100` | +| `MAX_REVIEWS_PER_RESTAURANT` | 음식점별 최대 리뷰 수 | `100` | `200` | + +## 📊 API 엔드포인트 + +### 주요 엔드포인트 + +| Method | Endpoint | 설명 | +|--------|----------|------| +| `GET` | `/` | 메인 페이지 | +| `GET` | `/docs` | Swagger UI 문서 | +| `GET` | `/health` | 헬스체크 | +| `GET` | `/vector-status` | Vector DB 상태 확인 | +| `GET` | `/config` | 환경 설정 확인 | +| `POST` | `/build-vector-db` | Vector DB 구축 | +| `POST` | `/action-request` | AI 액션 요청 | +| `POST` | `/search-similar` | 유사 음식점 검색 | +| `GET` | `/collections` | 컬렉션 목록 조회 | + +### Vector DB 구축 API 예시 + +```json +POST /build-vector-db +{ + "region": "서울특별시 강남구 역삼동", + "store_name": "맛있는 치킨집", + "force_rebuild": false +} +``` + +**응답:** +```json +{ + "success": true, + "message": "Vector DB 구축이 완료되었습니다.", + "statistics": { + "total_processed": 150, + "newly_added": 120, + "updated": 25, + "duplicates": 5, + "total_vectors": 1450 + }, + "execution_time": 245.8, + "store_info": { + "name": "맛있는 치킨집", + "region": "서울특별시 강남구 역삼동", + "business_type": "치킨", + "similar_stores_found": 15 + } +} +``` + +### AI 액션 요청 API 예시 + +```json +POST /action-request +{ + "store_id": "12345", + "context": "매출이 감소하고 있어서 메뉴 개선이 필요합니다." +} +``` + +**응답:** +```json +{ + "success": true, + "recommendations": [ + { + "category": "메뉴 개선", + "priority": "high", + "action": "시즌 한정 메뉴 도입", + "description": "고객 선호도가 높은 트렌디한 메뉴를 계절별로 출시하여 재방문율을 높입니다.", + "timeframe": "1-2주", + "expected_impact": "매출 15-20% 증가 예상" + } + ], + "similar_cases": 3, + "analysis_date": "2024-06-12T10:30:00" +} +``` + +## 🔧 개발 및 확장 + +### 로컬 개발 + +```bash +# 개발 모드로 실행 (자동 재시작) +uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload + +# 의존성 추가 +pip install 새패키지명 +pip freeze > app/requirements.txt + +# Vector DB 디렉토리 확인 +ls -la ./vector_db/ + +# 코드 포맷팅 +black app/ +flake8 app/ +``` + +### Ingress 호스트 변경 + +현재 환경에 맞게 Ingress 호스트를 변경하려면: + +```bash +# 1. 현재 External IP 확인 +kubectl get svc -n ingress-nginx ingress-nginx-controller + +# 2. deployment/manifests/ingress.yaml 파일에서 host 수정 +# 예: vector-api.{YOUR_EXTERNAL_IP}.nip.io + +# 3. 변경사항 적용 +kubectl apply -f deployment/manifests/ingress.yaml + +# 4. 새로운 주소 확인 +kubectl get ingress vector-api-ingress +``` + +## 🐛 문제 해결 + +### 일반적인 문제 + +**1. Claude API 키 관련 문제** +```bash +# API 키 유효성 확인 +curl -X POST "https://api.anthropic.com/v1/messages" \ + -H "x-api-key: your-claude-api-key" \ + -H "Content-Type: application/json" \ + -d '{ + "model": "claude-sonnet-4-20250514", + "max_tokens": 10, + "messages": [{"role": "user", "content": "Hi"}] + }' + +# 환경변수 확인 +echo $CLAUDE_API_KEY +``` + +**2. Vector DB 관련 문제** +```bash +# Vector DB 디렉토리 권한 확인 +ls -la /app/vectordb/ + +# Vector DB 초기화 +curl -X POST "http://localhost:8000/reset-vector-db" + +# Collection 상태 확인 +curl "http://localhost:8000/vector-status" +``` + +**3. Kubernetes 배포 실패** +```bash +# Pod 로그 확인 (Vector DB 초기화 에러) +kubectl logs -l app=vector-api + +# PVC 상태 확인 +kubectl get pvc vector-db-pvc +kubectl describe pvc vector-db-pvc + +# ConfigMap 확인 +kubectl get configmap vector-api-config -o yaml + +# Secret 확인 +kubectl get secret vector-api-secret -o yaml +``` + +**4. 메모리 부족 문제** +```bash +# Vector DB 및 ML 모델이 메모리를 많이 사용 +kubectl top pods -l app=vector-api + +# 리소스 제한 확인 +kubectl describe pod -l app=vector-api +``` + +**5. 포트 관련 문제** +- 로컬 개발: 8000번 포트 +- Docker 컨테이너: 8000번 포트 +- Kubernetes: Service 80번 → Ingress 외부 접근 + +## 🎯 성능 최적화 + +### Vector DB 최적화 설정 + +```yaml +# deployment.yaml에서 Vector DB 최적화를 위한 리소스 설정 +resources: + requests: + memory: "2Gi" # Vector DB와 ML 모델이 메모리를 많이 사용 + cpu: "1000m" # 임베딩 계산을 위한 CPU + limits: + memory: "4Gi" # Vector 계산 및 Claude API 호출을 위한 충분한 메모리 + cpu: "2000m" # 병렬 처리를 위한 CPU +``` + +### 영구 저장소 설정 + +```yaml +# pvc.yaml에서 Vector DB 저장소 설정 +spec: + accessModes: + - ReadWriteOnce + resources: + requests: + storage: 10Gi # Vector 데이터 저장을 위한 충분한 공간 +``` + +### 타임아웃 설정 + +```yaml +# ingress.yaml에서 Vector DB 구축 시간을 고려한 타임아웃 +nginx.ingress.kubernetes.io/proxy-read-timeout: "1800" # 30분 +nginx.ingress.kubernetes.io/proxy-send-timeout: "1800" # 30분 +``` + +## 📈 Vector DB 워크플로우 + +### 1. Vector DB 구축 과정 + +```mermaid +graph TD + A[점주 요청] --> B[지역 및 업종 분석] + B --> C[카카오 API 음식점 수집] + C --> D[리뷰 데이터 수집] + D --> E[텍스트 전처리] + E --> F[Sentence Transformer 임베딩] + F --> G[Chroma DB 저장] + G --> H[중복 제거 및 메타데이터 구성] + H --> I[Vector DB 완성] +``` + +### 2. AI 액션 추천 과정 + +```mermaid +graph TD + A[점주 액션 요청] --> B[컨텍스트 분석] + B --> C[Vector 유사도 검색] + C --> D[관련 케이스 추출] + D --> E[Claude AI 프롬프트 구성] + E --> F[Claude API 호출] + F --> G[맞춤형 액션 플랜 생성] + G --> H[우선순위 및 실행 방안 제시] +``` + +## 📈 향후 확장 계획 + +- [ ] **다중 Vector DB 지원**: FAISS, Pinecone 추가 지원 +- [ ] **실시간 업데이트**: 새로운 리뷰 자동 임베딩 및 추가 +- [ ] **감정 분석 고도화**: 더 정교한 감정 및 의도 분류 +- [ ] **업종별 특화**: 업종별 맞춤형 Vector 모델 개발 +- [ ] **A/B 테스트**: 추천 효과 측정 및 개선 +- [ ] **대시보드**: Vector DB 현황 및 성능 모니터링 +- [ ] **배치 처리**: 대규모 데이터 처리 최적화 +- [ ] **API 버전 관리**: 하위 호환성 보장 +- [ ] **멀티모달 지원**: 이미지, 텍스트 통합 임베딩 +- [ ] **비즈니스 인텔리전스**: 시장 트렌드 분석 기능 + +## 🧠 AI/ML 구성 요소 + +### Sentence Transformers +- **모델**: `all-MiniLM-L6-v2` (다국어 지원, 384차원) +- **용도**: 한국어 텍스트 임베딩 +- **특징**: 빠른 속도, 합리적인 정확도 + +### Chroma Vector DB +- **저장 방식**: 영구 저장 (PVC) +- **인덱싱**: HNSW 알고리즘 +- **메타데이터**: 필터링 및 검색 최적화 + +### Claude AI +- **모델**: `claude-sonnet-4-20250514` +- **용도**: 비즈니스 액션 추천 +- **특징**: 높은 품질의 한국어 분석 + +--- + +## 📞 지원 및 문의 + +- **이슈 리포트**: GitHub Issues +- **기술 문의**: 개발팀 Slack +- **API 문의**: Anthropic Support +- **API 문서**: Swagger UI에서 상세 확인 + +--- + +**💡 팁: Vector DB 구축에는 시간이 오래 걸릴 수 있으니 충분한 타임아웃을 설정하고 진행 상황을 모니터링하세요.** + diff --git a/vector/app/config/settings.py b/vector/app/config/settings.py new file mode 100644 index 0000000..e5a59bb --- /dev/null +++ b/vector/app/config/settings.py @@ -0,0 +1,80 @@ +# app/config/settings.py +import os +from typing import Optional + +class Settings: + """환경 변수 기반 설정 클래스""" + + # 애플리케이션 메타데이터 + APP_TITLE = os.getenv("APP_TITLE", "음식점 Vector DB 구축 서비스") + APP_VERSION = os.getenv("APP_VERSION", "1.0.0") + APP_DESCRIPTION = os.getenv("APP_DESCRIPTION", "소상공인을 위한 AI 기반 경쟁업체 분석 및 액션 추천 시스템") + + # 서버 설정 + HOST = os.getenv("HOST", "0.0.0.0") + PORT = int(os.getenv("PORT", "8000")) + LOG_LEVEL = os.getenv("LOG_LEVEL", "info") + + # Restaurant API 설정 + RESTAURANT_API_HOST = os.getenv("RESTAURANT_API_HOST", "4.217.217.207") + RESTAURANT_API_PORT = os.getenv("RESTAURANT_API_PORT", "18000") + + @property + def RESTAURANT_API_URL(self) -> str: + return f"http://{self.RESTAURANT_API_HOST}:{self.RESTAURANT_API_PORT}" + + # Review API 설정 + REVIEW_API_HOST = os.getenv("REVIEW_API_HOST", "4.217.217.207") + REVIEW_API_PORT = os.getenv("REVIEW_API_PORT", "19000") + + @property + def REVIEW_API_URL(self) -> str: + return f"http://{self.REVIEW_API_HOST}:{self.REVIEW_API_PORT}" + + # Claude API 설정 + CLAUDE_API_KEY = os.getenv("CLAUDE_API_KEY", "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") + CLAUDE_MODEL = os.getenv("CLAUDE_MODEL", "claude-sonnet-4-20250514") + + # Vector DB 설정 + VECTOR_DB_PATH = os.getenv("VECTOR_DB_PATH", "/app/vectordb") + VECTOR_DB_COLLECTION = os.getenv("VECTOR_DB_COLLECTION", "restaurant_reviews") + EMBEDDING_MODEL = os.getenv("EMBEDDING_MODEL", "sentence-transformers/all-MiniLM-L6-v2") + + # 데이터 수집 설정 + MAX_RESTAURANTS_PER_CATEGORY = int(os.getenv("MAX_RESTAURANTS_PER_CATEGORY", "50")) + MAX_REVIEWS_PER_RESTAURANT = int(os.getenv("MAX_REVIEWS_PER_RESTAURANT", "100")) + REQUEST_DELAY = float(os.getenv("REQUEST_DELAY", "0.1")) + REQUEST_TIMEOUT = int(os.getenv("REQUEST_TIMEOUT", "600")) + + # 환경 감지 + @property + def IS_K8S_ENV(self) -> bool: + """Kubernetes 환경인지 확인""" + return ( + os.getenv("KUBERNETES_SERVICE_HOST") is not None or + self.RESTAURANT_API_HOST in ["restaurant-api-service", "kakao-review-api-service"] or + self.REVIEW_API_HOST in ["restaurant-api-service", "kakao-review-api-service"] + ) + + def get_restaurant_api_url(self) -> str: + """환경에 따른 Restaurant API URL 반환""" + if self.IS_K8S_ENV: + host = "restaurant-api-service" + port = "80" + else: + host = self.RESTAURANT_API_HOST + port = self.RESTAURANT_API_PORT + return f"http://{host}:{port}" + + def get_review_api_url(self) -> str: + """환경에 따른 Review API URL 반환""" + if self.IS_K8S_ENV: + host = "kakao-review-api-service" + port = "80" + else: + host = self.REVIEW_API_HOST + port = self.REVIEW_API_PORT + return f"http://{host}:{port}" + +# 설정 인스턴스 +settings = Settings() diff --git a/vector/app/main.py b/vector/app/main.py new file mode 100644 index 0000000..50e3aa9 --- /dev/null +++ b/vector/app/main.py @@ -0,0 +1,917 @@ +# vector/app/main.py +import os +import sys +import logging +from contextlib import asynccontextmanager +from datetime import datetime +from typing import Optional + +# 현재 디렉토리를 Python 경로에 추가 +sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + +# ============================================================================= +# .env 파일 로딩 (다른 import보다 먼저) +# ============================================================================= +from dotenv import load_dotenv + +# .env 파일에서 환경변수 로드 +load_dotenv() + +import asyncio +import fastapi +from fastapi import FastAPI, HTTPException, BackgroundTasks, Depends +from fastapi.responses import HTMLResponse, JSONResponse +from fastapi.middleware.cors import CORSMiddleware +from pydantic import BaseModel, Field + +# 프로젝트 모듈 import +from app.config.settings import settings +from app.models.restaurant_models import RestaurantSearchRequest, ErrorResponse +from app.models.vector_models import ( + VectorBuildRequest, VectorBuildResponse, + ActionRecommendationRequest, ActionRecommendationResponse, + VectorDBStatusResponse, VectorDBStatus +) +from app.services.restaurant_service import RestaurantService +from app.services.review_service import ReviewService +from app.services.vector_service import VectorService +from app.services.claude_service import ClaudeService +from app.utils.category_utils import extract_food_category + +# 로깅 설정 +logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(name)s - %(levelname)s - %(message)s', + handlers=[logging.StreamHandler(sys.stdout)] +) +logger = logging.getLogger(__name__) + +# 🔧 전역 변수 대신 애플리케이션 상태로 관리 +app_state = { + "vector_service": None, + "restaurant_service": None, + "review_service": None, + "claude_service": None, + "initialization_errors": {}, + "startup_completed": False +} + +# 추가 모델 정의 (find-reviews API용) +class FindReviewsRequest(BaseModel): + """리뷰 검색 요청 모델""" + region: str = Field( + ..., + description="지역 (시군구 + 읍면동)", + example="서울특별시 강남구 역삼동" + ) + store_name: str = Field( + ..., + description="가게명", + example="맛있는 한식당" + ) + +class RestaurantInfo(BaseModel): + """음식점 정보 모델""" + id: str = Field(description="카카오 장소 ID") + place_name: str = Field(description="장소명") + category_name: str = Field(description="카테고리명") + address_name: str = Field(description="전체 주소") + phone: str = Field(description="전화번호") + place_url: str = Field(description="장소 상세페이지 URL") + x: str = Field(description="X 좌표값 (경도)") + y: str = Field(description="Y 좌표값 (위도)") + +class FindReviewsResponse(BaseModel): + """리뷰 검색 응답 모델""" + success: bool = Field(description="검색 성공 여부") + message: str = Field(description="응답 메시지") + target_store: RestaurantInfo = Field(description="대상 가게 정보") + total_stores: int = Field(description="수집된 총 가게 수") + total_reviews: int = Field(description="수집된 총 리뷰 수") + food_category: str = Field(description="추출된 음식 카테고리") + region: str = Field(description="검색 지역") + +@asynccontextmanager +async def lifespan(app: FastAPI): + """🔧 애플리케이션 생명주기 관리 - 안전한 서비스 초기화""" + # 🚀 Startup 이벤트 + logger.info("🚀 Vector API 서비스 시작 중...") + startup_start_time = datetime.now() + + # 각 서비스 안전하게 초기화 + services_to_init = [ + ("restaurant_service", RestaurantService, "Restaurant API 서비스"), + ("review_service", ReviewService, "Review API 서비스"), + ("claude_service", ClaudeService, "Claude AI 서비스"), + ("vector_service", VectorService, "Vector DB 서비스") # 마지막에 초기화 + ] + + initialized_count = 0 + + for service_key, service_class, service_name in services_to_init: + try: + logger.info(f"🔧 {service_name} 초기화 중...") + app_state[service_key] = service_class() + logger.info(f"✅ {service_name} 초기화 완료") + initialized_count += 1 + + except Exception as e: + logger.error(f"❌ {service_name} 초기화 실패: {e}") + app_state["initialization_errors"][service_key] = str(e) + # 🔧 중요: 서비스 초기화 실패해도 앱은 시작 (헬스체크에서 확인) + continue + + startup_time = (datetime.now() - startup_start_time).total_seconds() + app_state["startup_completed"] = True + + logger.info(f"✅ Vector API 서비스 시작 완료!") + logger.info(f"📊 초기화 결과: {initialized_count}/{len(services_to_init)}개 서비스 성공") + logger.info(f"⏱️ 시작 소요시간: {startup_time:.2f}초") + + if app_state["initialization_errors"]: + logger.warning(f"⚠️ 초기화 실패 서비스: {list(app_state['initialization_errors'].keys())}") + + yield + + # 🛑 Shutdown 이벤트 + logger.info("🛑 Vector API 서비스 종료 중...") + + # 리소스 정리 + for service_key in ["vector_service", "restaurant_service", "review_service", "claude_service"]: + if app_state[service_key] is not None: + try: + # 서비스별 정리 작업이 있다면 여기서 수행 + logger.info(f"🔧 {service_key} 정리 중...") + except Exception as e: + logger.warning(f"⚠️ {service_key} 정리 실패: {e}") + finally: + app_state[service_key] = None + + app_state["startup_completed"] = False + logger.info("✅ Vector API 서비스 종료 완료") + +# 🔧 FastAPI 앱 초기화 (lifespan 이벤트 포함) +app = FastAPI( + title=settings.APP_TITLE, + description=f""" + {settings.APP_DESCRIPTION} + + **주요 기능:** + - 지역과 가게명으로 대상 가게 찾기 + - 동종 업체 리뷰 수집 및 분석 + - Vector DB 구축 및 관리 + - Claude AI 기반 액션 추천 + - 영속적 Vector DB 저장 + + **API 연동:** + - Restaurant API: {settings.get_restaurant_api_url() if hasattr(settings, 'get_restaurant_api_url') else 'N/A'} + - Review API: {settings.get_review_api_url() if hasattr(settings, 'get_review_api_url') else 'N/A'} + - Claude AI API: {settings.CLAUDE_MODEL} + + **Vector DB:** + - 경로: {settings.VECTOR_DB_PATH} + - 컬렉션: {settings.VECTOR_DB_COLLECTION} + - 임베딩 모델: {settings.EMBEDDING_MODEL} + + **버전:** {settings.APP_VERSION} + """, + version=settings.APP_VERSION, + contact={ + "name": "개발팀", + "email": "admin@example.com" + }, + lifespan=lifespan # 🔧 lifespan 이벤트 등록 +) + +# CORS 설정 +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +# 🔧 Dependency Injection - 서비스 제공자들 +def get_vector_service() -> VectorService: + """VectorService 의존성 주입""" + if app_state["vector_service"] is None: + error_msg = app_state["initialization_errors"].get("vector_service") + if error_msg: + raise HTTPException( + status_code=503, + detail=f"Vector service not available: {error_msg}" + ) + + # 런타임에 재시도 + try: + logger.info("🔧 VectorService 런타임 초기화 시도...") + app_state["vector_service"] = VectorService() + logger.info("✅ VectorService 런타임 초기화 성공") + except Exception as e: + logger.error(f"❌ VectorService 런타임 초기화 실패: {e}") + raise HTTPException( + status_code=503, + detail=f"Vector service initialization failed: {str(e)}" + ) + + return app_state["vector_service"] + +def get_restaurant_service() -> RestaurantService: + """RestaurantService 의존성 주입""" + if app_state["restaurant_service"] is None: + error_msg = app_state["initialization_errors"].get("restaurant_service") + if error_msg: + raise HTTPException( + status_code=503, + detail=f"Restaurant service not available: {error_msg}" + ) + + try: + app_state["restaurant_service"] = RestaurantService() + except Exception as e: + raise HTTPException(status_code=503, detail=str(e)) + + return app_state["restaurant_service"] + +def get_review_service() -> ReviewService: + """ReviewService 의존성 주입""" + if app_state["review_service"] is None: + error_msg = app_state["initialization_errors"].get("review_service") + if error_msg: + raise HTTPException( + status_code=503, + detail=f"Review service not available: {error_msg}" + ) + + try: + app_state["review_service"] = ReviewService() + except Exception as e: + raise HTTPException(status_code=503, detail=str(e)) + + return app_state["review_service"] + +def get_claude_service() -> ClaudeService: + """ClaudeService 의존성 주입""" + if app_state["claude_service"] is None: + error_msg = app_state["initialization_errors"].get("claude_service") + if error_msg: + raise HTTPException( + status_code=503, + detail=f"Claude service not available: {error_msg}" + ) + + try: + app_state["claude_service"] = ClaudeService() + except Exception as e: + raise HTTPException(status_code=503, detail=str(e)) + + return app_state["claude_service"] + +@app.get("/", response_class=HTMLResponse, include_in_schema=False) +async def root(): + """메인 페이지""" + # 🔧 안전한 DB 상태 조회 + try: + vector_service = app_state.get("vector_service") + if vector_service: + db_status = vector_service.get_db_status() + else: + db_status = { + 'collection_name': settings.VECTOR_DB_COLLECTION, + 'total_documents': 0, + 'total_stores': 0, + 'db_path': settings.VECTOR_DB_PATH, + 'status': 'not_initialized' + } + except Exception as e: + logger.warning(f"DB 상태 조회 실패: {e}") + db_status = {'status': 'error', 'error': str(e)} + + return f""" + + + {settings.APP_TITLE} + + + +

🍽️ {settings.APP_TITLE}

+

{settings.APP_DESCRIPTION}

+ +
+

📊 Vector DB 상태

+
    +
  • 컬렉션: {db_status.get('collection_name', 'N/A')}
    • +
  • 총 문서 수: {db_status.get('total_documents', 0)}
    • +
  • 가게 수: {db_status.get('total_stores', 0)}
    • +
  • DB 경로: {db_status.get('db_path', 'N/A')}
    • +
  • 상태: {db_status.get('status', 'Unknown')}
    • +
+ {f''' +
+

⚠️ 초기화 실패 서비스

+
    + {"".join([f"
  • {k}: {v}
    • " for k, v in app_state["initialization_errors"].items()])} +
+
+ ''' if app_state["initialization_errors"] else ''} +
+ +
+

🔧 시스템 구성

+
    +
  • Claude Model: {settings.CLAUDE_MODEL}
    • +
  • Embedding Model: {settings.EMBEDDING_MODEL}
    • +
  • Vector DB Path: {settings.VECTOR_DB_PATH}
    • +
  • 환경: {'Kubernetes' if hasattr(settings, 'IS_K8S_ENV') and settings.IS_K8S_ENV else 'Local'}
    • +
+
+ +

📚 API 문서

+ Swagger UI 문서 + ReDoc 문서 + 헬스 체크 + Vector DB 상태 + +

🛠️ 사용 방법

+

POST /find-reviews - 리뷰 검색 및 Vector DB 저장 (본인 가게 우선)

+ 
+{{
+  "region": "서울특별시 강남구 역삼동",
+  "store_name": "맛있는 한식당"
+}}
+
+ +

POST /build-vector - Vector DB 구축

+ 
+{{
+  "region": "서울특별시 강남구 역삼동",
+  "store_name": "맛있는 한식당",
+  "force_rebuild": false
+}}
+
+ +

POST /action-recommendation - 액션 추천 요청

+ 
+{{
+  "store_id": "12345",
+  "context": "매출이 감소하고 있어서 개선이 필요합니다"
+}}
+
+ + + """ + +@app.post("/find-reviews", response_model=FindReviewsResponse) +async def find_reviews( + request: FindReviewsRequest, + vector_service: VectorService = Depends(get_vector_service), + restaurant_service: RestaurantService = Depends(get_restaurant_service), + review_service: ReviewService = Depends(get_review_service) +): + """ + 지역과 가게명으로 리뷰를 찾아 Vector DB에 저장합니다. + 🔥 본인 가게 리뷰는 반드시 포함됩니다. (수정된 버전) + """ + start_time = datetime.now() + logger.info(f"🔍 리뷰 검색 요청: {request.region} - {request.store_name}") + + try: + # 1단계: 본인 가게 검색 + logger.info("1단계: 본인 가게 검색 중... (최우선)") + target_restaurant = await restaurant_service.find_store_by_name_and_region( + request.region, request.store_name + ) + + if not target_restaurant: + logger.error(f"❌ 본인 가게를 찾을 수 없음: {request.store_name}") + raise HTTPException( + status_code=404, + detail=f"'{request.store_name}' 가게를 찾을 수 없습니다. 가게명과 지역을 정확히 입력해주세요." + ) + + logger.info(f"✅ 본인 가게 발견: {target_restaurant.place_name} (ID: {target_restaurant.id})") + + # 2단계: 동종 업체 검색 + logger.info("2단계: 동종 업체 검색 중...") + similar_restaurants = [] + food_category = "기타" # 기본값 + + try: + food_category = extract_food_category(target_restaurant.category_name) + logger.info(f"추출된 음식 카테고리: {food_category}") + + similar_restaurants = await restaurant_service.find_similar_stores( + request.region, food_category, settings.MAX_RESTAURANTS_PER_CATEGORY + ) + + logger.info(f"✅ 동종 업체 {len(similar_restaurants)}개 발견") + + except Exception as e: + logger.warning(f"⚠️ 동종 업체 검색 실패 (본인 가게는 계속 진행): {e}") + + # 3단계: 전체 가게 목록 구성 (본인 가게 우선 + 중복 제거) + logger.info("3단계: 전체 가게 목록 구성 중...") + + # 본인 가게를 첫 번째로 배치 + all_restaurants = [target_restaurant] + + # 동종 업체 추가 (개선된 중복 제거) + for restaurant in similar_restaurants: + if not _is_duplicate_restaurant(target_restaurant, restaurant): + all_restaurants.append(restaurant) + + logger.info(f"✅ 전체 가게 목록 구성 완료: {len(all_restaurants)}개 (본인 가게 포함)") + + # 4단계: 전체 리뷰 수집 (본인 가게 우선 처리) + logger.info("4단계: 리뷰 수집 중... (본인 가게 우선)") + + # 본인 가게 우선 처리를 위한 특별 로직 + review_results = [] + + # 4-1: 본인 가게 리뷰 수집 (실패 시 전체 중단) + try: + logger.info("본인 가게 리뷰 우선 수집 중... (필수)") + target_store_info, target_reviews = await review_service.collect_store_reviews( + target_restaurant.id, + max_reviews=settings.MAX_REVIEWS_PER_RESTAURANT * 2 # 본인 가게는 더 많이 + ) + + if not target_store_info or not target_reviews: + logger.error(f"❌ 본인 가게 리뷰 수집 실패: {target_restaurant.place_name}") + raise HTTPException( + status_code=422, + detail=f"본인 가게 '{target_restaurant.place_name}'의 리뷰를 수집할 수 없습니다." + ) + + # 본인 가게 결과를 첫 번째로 설정 + review_results.append((target_restaurant.id, target_store_info, target_reviews)) + logger.info(f"✅ 본인 가게 리뷰 수집 성공: {len(target_reviews)}개") + + except HTTPException: + raise + except Exception as e: + logger.error(f"❌ 본인 가게 리뷰 수집 중 오류: {e}") + raise HTTPException( + status_code=500, + detail=f"본인 가게 리뷰 수집 중 오류가 발생했습니다: {str(e)}" + ) + + # 4-2: 동종 업체 리뷰 수집 (실패해도 본인 가게는 유지) + if len(all_restaurants) > 1: # 본인 가게 외에 다른 가게가 있는 경우 + try: + logger.info(f"동종 업체 리뷰 수집 중... ({len(all_restaurants) - 1}개)") + + # 본인 가게 제외한 동종 업체만 수집 + similar_restaurants_only = all_restaurants[1:] + similar_results = await review_service.collect_multiple_stores_reviews(similar_restaurants_only) + + # 동종 업체 결과 추가 + review_results.extend(similar_results) + + similar_reviews_count = sum(len(reviews) for _, _, reviews in similar_results) + logger.info(f"✅ 동종 업체 리뷰 수집 완료: {len(similar_results)}개 가게, {similar_reviews_count}개 리뷰") + + except Exception as e: + logger.warning(f"⚠️ 동종 업체 리뷰 수집 실패 (본인 가게는 유지): {e}") + else: + logger.info("동종 업체가 없어 본인 가게 리뷰만 사용") + + # 5단계: Vector DB 구축 + logger.info("5단계: Vector DB 구축 중...") + try: + # 대상 가게 정보를 딕셔너리로 변환 + target_store_info_dict = { + 'id': target_restaurant.id, + 'place_name': target_restaurant.place_name, + 'category_name': target_restaurant.category_name, + 'address_name': target_restaurant.address_name, + 'phone': target_restaurant.phone, + 'place_url': target_restaurant.place_url, + 'x': target_restaurant.x, + 'y': target_restaurant.y + } + + # Vector DB에 저장 + vector_result = await vector_service.build_vector_store( + target_store_info_dict, review_results, food_category, request.region + ) + + if not vector_result.get('success', False): + raise Exception(f"Vector DB 저장 실패: {vector_result.get('error', 'Unknown error')}") + + logger.info("✅ Vector DB 구축 완료") + + except Exception as e: + logger.error(f"❌ Vector DB 구축 실패: {e}") + raise HTTPException( + status_code=500, + detail=f"Vector DB 구축 중 오류가 발생했습니다: {str(e)}" + ) + + # 최종 검증: 본인 가게가 첫 번째에 있는지 확인 + if not review_results or review_results[0][0] != target_restaurant.id: + logger.error("❌ 본인 가게가 첫 번째에 없음") + raise HTTPException( + status_code=500, + detail="본인 가게 리뷰 처리 순서 오류가 발생했습니다." + ) + + # 성공 응답 + total_reviews = sum(len(reviews) for _, _, reviews in review_results) + execution_time = (datetime.now() - start_time).total_seconds() + + return FindReviewsResponse( + success=True, + message=f"✅ 본인 가게 리뷰 포함 보장 완료! (총 {len(review_results)}개 가게, {total_reviews}개 리뷰)", + target_store=RestaurantInfo( + id=target_restaurant.id, + place_name=target_restaurant.place_name, + category_name=target_restaurant.category_name, + address_name=target_restaurant.address_name, + phone=target_restaurant.phone, + place_url=target_restaurant.place_url, + x=target_restaurant.x, + y=target_restaurant.y + ), + total_stores=len(review_results), + total_reviews=total_reviews, + food_category=food_category, + region=request.region + ) + + except HTTPException: + raise + except Exception as e: + execution_time = (datetime.now() - start_time).total_seconds() + logger.error(f"❌ 전체 프로세스 실패: {e}") + raise HTTPException( + status_code=500, + detail=f"서비스 처리 중 예상치 못한 오류가 발생했습니다: {str(e)}" + ) + +def _is_duplicate_restaurant(restaurant1: RestaurantInfo, restaurant2: RestaurantInfo) -> bool: + """ + 두 음식점이 중복인지 확인 (개선된 로직) + + Args: + restaurant1: 첫 번째 음식점 + restaurant2: 두 번째 음식점 + + Returns: + 중복 여부 + """ + # 1. ID 기준 확인 + if restaurant1.id == restaurant2.id: + return True + + # 2. place_url에서 추출한 store_id 기준 확인 + store_id1 = _extract_store_id_from_place_url(restaurant1.place_url) + store_id2 = _extract_store_id_from_place_url(restaurant2.place_url) + + if store_id1 and store_id2 and store_id1 == store_id2: + return True + + # 3. restaurant.id와 place_url store_id 교차 확인 + if restaurant1.id == store_id2 or restaurant2.id == store_id1: + return True + + # 4. 이름 + 주소 기준 확인 (최후 방법) + if (restaurant1.place_name == restaurant2.place_name and + restaurant1.address_name == restaurant2.address_name): + return True + + return False + +def _extract_store_id_from_place_url(place_url: str) -> Optional[str]: + """ + 카카오맵 URL에서 store_id를 추출합니다. + + Args: + place_url: 카카오맵 장소 URL + + Returns: + 추출된 store_id 또는 None + """ + try: + if not place_url: + return None + + import re + # URL 패턴: https://place.map.kakao.com/123456789 + pattern = r'/(\d+)(?:\?|$|#)' + match = re.search(pattern, place_url) + + if match: + return match.group(1) + else: + return None + + except Exception: + return None + +@app.post( + "/action-recommendation", + response_model=ActionRecommendationResponse, + summary="액션 추천 요청", + description="점주가 Claude AI에게 액션 추천을 요청합니다." +) +async def action_recommendation( + request: ActionRecommendationRequest, + claude_service: ClaudeService = Depends(get_claude_service), + vector_service: VectorService = Depends(get_vector_service) +): + """🧠 Claude AI 액션 추천 API""" + try: + logger.info(f"액션 추천 요청: store_id={request.store_id}") + + start_time = datetime.now() + + # 1단계: Vector DB에서 컨텍스트 조회 + try: + db_status = vector_service.get_db_status() + + if db_status.get('total_documents', 0) == 0: + raise HTTPException( + status_code=404, + detail={ + "success": False, + "error": "NO_VECTOR_DATA", + "message": "Vector DB에 데이터가 없습니다. 먼저 /build-vector API를 호출하여 데이터를 구축해주세요.", + "timestamp": datetime.now().isoformat() + } + ) + + # Vector DB에서 유사한 케이스 검색 + context_data = vector_service.search_similar_cases(request.store_id, request.context) + + except HTTPException: + raise + except Exception as e: + logger.error(f"Vector DB 조회 실패: {e}") + # Vector DB 조회 실패해도 일반적인 추천은 제공 + context_data = None + + # 2단계: Claude AI 호출 (프롬프트 구성부터 파싱까지 모두 포함) + try: + # 컨텍스트 구성 + full_context = f"가게 ID: {request.store_id}\n점주 요청: {request.context}" + additional_context = context_data if context_data else None + + # Claude AI 액션 추천 생성 (완전한 처리) + claude_response, parsed_response = await claude_service.generate_action_recommendations( + context=full_context, + additional_context=additional_context + ) + + if not claude_response: + raise Exception("Claude AI로부터 응답을 받지 못했습니다") + + logger.info(f"Claude 응답 길이: {len(claude_response)} 문자") + json_parse_success = parsed_response is not None + + except Exception as e: + logger.error(f"Claude AI 호출 실패: {e}") + raise HTTPException( + status_code=500, + detail=f"AI 추천 생성 중 오류: {str(e)}" + ) + + # 3단계: 응답 구성 + claude_execution_time = (datetime.now() - start_time).total_seconds() + + # 가게 정보 추출 (Vector DB에서) + store_name = request.store_id # 기본값 + food_category = "기타" # 기본값 + + try: + store_context = vector_service.get_store_context(request.store_id) + if store_context: + store_name = store_context.get('store_name', request.store_id) + food_category = store_context.get('food_category', '기타') + except Exception as e: + logger.warning(f"가게 정보 추출 실패: {e}") + + response = ActionRecommendationResponse( + success=True, + message=f"액션 추천이 완료되었습니다. (실행시간: {claude_execution_time:.1f}초, JSON 파싱: {'성공' if json_parse_success else '실패'})", + claude_input=full_context + (f"\n--- 동종 업체 분석 데이터 ---\n{additional_context}" if additional_context else ""), + claude_response=claude_response, + parsed_response=parsed_response, + store_name=store_name, + food_category=food_category, + similar_stores_count=len(context_data.split("---")) if context_data else 0, + execution_time=claude_execution_time, + json_parse_success=json_parse_success + ) + + logger.info(f"✅ 액션 추천 완료: Claude 응답 {len(claude_response) if claude_response else 0} 문자, JSON 파싱 {'성공' if json_parse_success else '실패'}, {claude_execution_time:.1f}초 소요") + return response + + except HTTPException: + raise + except Exception as e: + logger.error(f"❌ 액션 추천 요청 실패: {str(e)}") + + raise HTTPException( + status_code=500, + detail={ + "success": False, + "error": "RECOMMENDATION_FAILED", + "message": f"액션 추천 중 오류가 발생했습니다: {str(e)}", + "timestamp": datetime.now().isoformat() + } + ) + +@app.get( + "/vector-status", + response_model=VectorDBStatusResponse, + summary="Vector DB 상태 조회", + description="Vector DB의 현재 상태를 조회합니다." +) +async def get_vector_db_status(vector_service: VectorService = Depends(get_vector_service)): + """Vector DB 상태 조회 API""" + try: + status_info = vector_service.get_db_status() + + status = VectorDBStatus( + collection_name=status_info['collection_name'], + total_documents=status_info['total_documents'], + total_stores=status_info['total_stores'], + db_path=status_info['db_path'], + last_updated=datetime.now().isoformat() + ) + + return VectorDBStatusResponse( + success=True, + status=status, + message="Vector DB 상태 조회가 완료되었습니다." + ) + + except Exception as e: + logger.error(f"Vector DB 상태 조회 실패: {e}") + + raise HTTPException( + status_code=500, + detail={ + "success": False, + "error": "STATUS_CHECK_FAILED", + "message": f"Vector DB 상태 조회 중 오류가 발생했습니다: {str(e)}", + "timestamp": datetime.now().isoformat() + } + ) + +@app.get("/health", summary="헬스 체크", description="API 서버 및 외부 서비스 상태를 확인합니다.") +async def health_check(): + """🏥 헬스체크 API""" + health_result = { + "status": "healthy", + "timestamp": datetime.now().isoformat(), + "services": {}, + "app_info": { + "name": settings.APP_TITLE, + "version": settings.APP_VERSION, + "startup_completed": app_state["startup_completed"] + } + } + + # 서비스별 헬스체크 + services_to_check = [ + ("restaurant_service", "restaurant_api"), + ("review_service", "review_api"), + ("claude_service", "claude_ai"), + ("vector_service", "vector_db") + ] + + healthy_count = 0 + total_checks = len(services_to_check) + + for service_key, health_key in services_to_check: + try: + service = app_state.get(service_key) + if service is None: + health_result["services"][health_key] = "not_initialized" + continue + + # 서비스별 헬스체크 메서드 호출 + if hasattr(service, 'health_check'): + status = await service.health_check() + else: + status = True # 헬스체크 메서드가 없으면 초기화됐다고 가정 + + # Vector DB의 경우 상세 정보 추가 + if health_key == "vector_db" and status: + try: + db_status = service.get_db_status() + health_result["vector_db_info"] = { + "total_documents": db_status.get('total_documents', 0), + "total_stores": db_status.get('total_stores', 0), + "db_path": db_status.get('db_path', '') + } + except: + pass + + health_result["services"][health_key] = "healthy" if status else "unhealthy" + if status: + healthy_count += 1 + + except Exception as e: + logger.warning(f"헬스체크 실패 - {service_key}: {e}") + health_result["services"][health_key] = f"error: {str(e)}" + + # 전체 상태 결정 + if healthy_count == total_checks: + health_result["status"] = "healthy" + elif healthy_count > 0: + health_result["status"] = "degraded" + else: + health_result["status"] = "unhealthy" + + # 요약 정보 + health_result["summary"] = { + "healthy_services": healthy_count, + "total_services": total_checks, + "health_percentage": round((healthy_count / total_checks) * 100, 1) + } + + # 초기화 에러가 있으면 포함 + if app_state["initialization_errors"]: + health_result["initialization_errors"] = app_state["initialization_errors"] + + # 환경 정보 + health_result["environment"] = { + "python_version": sys.version.split()[0], + "fastapi_version": fastapi.__version__, + "is_k8s": hasattr(settings, 'IS_K8S_ENV') and settings.IS_K8S_ENV, + "claude_model": settings.CLAUDE_MODEL + } + + # HTTP 상태 코드 결정 + if health_result["status"] == "healthy": + return health_result + elif health_result["status"] == "degraded": + return JSONResponse(status_code=200, content=health_result) # 부분 장애는 200 + else: + return JSONResponse(status_code=503, content=health_result) # 전체 장애는 503 + +# 🔧 전역 예외 처리 +@app.exception_handler(Exception) +async def global_exception_handler(request, exc): + """전역 예외 처리""" + logger.error(f"Unhandled exception: {exc}") + return JSONResponse( + status_code=500, + content={ + "error": "Internal server error", + "detail": str(exc) if settings.LOG_LEVEL.lower() == "debug" else "An unexpected error occurred", + "timestamp": datetime.now().isoformat(), + "path": str(request.url) + } + ) + +if __name__ == "__main__": + import uvicorn + + print("🍽️ " + "="*60) + print(f" {settings.APP_TITLE} 서버 시작") + print("="*64) + print(f"📊 구성 정보:") + print(f" - Python 버전: {sys.version.split()[0]}") + print(f" - FastAPI 버전: {fastapi.__version__}") + print(f" - Vector DB Path: {settings.VECTOR_DB_PATH}") + print(f" - Claude Model: {settings.CLAUDE_MODEL}") + print(f" - 환경: {'Kubernetes' if hasattr(settings, 'IS_K8S_ENV') and settings.IS_K8S_ENV else 'Local'}") + print() + print(f"📚 문서:") + print(f" - Swagger UI: http://{settings.HOST}:{settings.PORT}/docs") + print(f" - ReDoc: http://{settings.HOST}:{settings.PORT}/redoc") + print(f" - 메인 페이지: http://{settings.HOST}:{settings.PORT}/") + print() + + try: + uvicorn.run( + "app.main:app", # 🔧 문자열로 지정 (리로드 지원) + host=settings.HOST, + port=settings.PORT, + log_level=settings.LOG_LEVEL.lower(), + reload=False, # 프로덕션에서는 False + access_log=True, + loop="uvloop" if sys.platform != "win32" else "asyncio" + ) + except KeyboardInterrupt: + print("\n🛑 서버가 사용자에 의해 중단되었습니다.") + except Exception as e: + print(f"\n❌ 서버 시작 실패: {e}") + import traceback + traceback.print_exc() + sys.exit(1) + diff --git a/vector/app/requirements.txt b/vector/app/requirements.txt new file mode 100644 index 0000000..97bd268 --- /dev/null +++ b/vector/app/requirements.txt @@ -0,0 +1,67 @@ +# app/requirements.txt - 안정화된 Vector DB 서비스용 + +# ========================================== +# 기본 웹 프레임워크 (안정 버전) +# ========================================== +fastapi==0.104.1 +uvicorn[standard]==0.24.0 +pydantic==2.5.0 +python-dotenv==1.0.0 +python-multipart==0.0.6 + +# ========================================== +# HTTP 클라이언트 +# ========================================== +aiohttp==3.9.1 +requests==2.31.0 + +# ========================================== +# 데이터 처리 (안정 버전) +# ========================================== +numpy==1.24.3 +pandas==2.1.4 + +# ========================================== +# AI/ML 라이브러리 (호환성 검증된 버전) +# ========================================== +# PyTorch CPU 버전 (안정화) +torch==2.1.0+cpu --index-url https://download.pytorch.org/whl/cpu +torchvision==0.16.0+cpu --index-url https://download.pytorch.org/whl/cpu +torchaudio==2.1.0+cpu --index-url https://download.pytorch.org/whl/cpu + +# Transformer 라이브러리들 +tokenizers==0.15.2 +transformers==4.35.2 +huggingface-hub==0.19.4 + +# Sentence Transformers (안정 버전) +sentence-transformers==2.2.2 + +# ========================================== +# Vector DB - ChromaDB (안정 버전) +# ========================================== +# ChromaDB 0.4.24 사용 (호환성 검증됨) +chromadb==0.4.24 + +# ChromaDB 의존성 (호환 버전 고정) +hnswlib==0.7.0 +duckdb==0.9.2 + +# ========================================== +# Claude API (최신 안정 버전) +# ========================================== +anthropic>=0.40.0,<1.0.0 + +# ========================================== +# 기타 필수 라이브러리 +# ========================================== +typing-extensions==4.8.0 +sqlalchemy==2.0.23 + +# ========================================== +# 개발/디버깅 도구 (선택사항) +# ========================================== +# pytest==7.4.3 +# black==23.11.0 +# isort==5.12.0 + diff --git a/vector/app/services/claude_service.py b/vector/app/services/claude_service.py new file mode 100644 index 0000000..38ec659 --- /dev/null +++ b/vector/app/services/claude_service.py @@ -0,0 +1,336 @@ +# app/services/claude_service.py +import json +import logging +from typing import Optional, Dict, Any, Tuple +import anthropic +from ..config.settings import settings + +logger = logging.getLogger(__name__) + +class ClaudeService: + """Claude API 연동 서비스""" + + def __init__(self): + try: + # API 키 유효성 검사 + if not settings.CLAUDE_API_KEY or settings.CLAUDE_API_KEY.strip() == "": + raise ValueError("CLAUDE_API_KEY가 설정되지 않았습니다") + + # Claude 클라이언트 초기화 + self.client = anthropic.Anthropic(api_key=settings.CLAUDE_API_KEY) + self.model = settings.CLAUDE_MODEL + self.initialization_error = None + + logger.info(f"✅ ClaudeService 초기화 완료 (모델: {self.model})") + + except Exception as e: + self.initialization_error = str(e) + self.client = None + logger.error(f"❌ ClaudeService 초기화 실패: {e}") + + def is_ready(self) -> bool: + """서비스 준비 상태 확인""" + return self.client is not None and self.initialization_error is None + + def get_initialization_error(self) -> Optional[str]: + """초기화 에러 메시지 반환""" + return self.initialization_error + + async def test_api_connection(self) -> Tuple[bool, Optional[str]]: + """Claude API 연결을 테스트합니다.""" + if not self.is_ready(): + return False, self.initialization_error + + try: + logger.info("🔍 Claude API 연결 테스트 시작...") + + response = self.client.messages.create( + model=self.model, + max_tokens=50, + messages=[ + { + "role": "user", + "content": "안녕하세요. 연결 테스트입니다. '연결 성공'이라고 답변해주세요." + } + ] + ) + + if response.content and len(response.content) > 0: + logger.info("✅ Claude API 연결 테스트 성공") + return True, None + else: + error_msg = "Claude API 응답이 비어있음" + logger.warning(f"⚠️ {error_msg}") + return False, error_msg + + except Exception as e: + error_msg = f"Claude API 연결 테스트 실패: {str(e)}" + logger.error(f"❌ {error_msg}") + return False, error_msg + + async def generate_action_recommendations(self, context: str, additional_context: Optional[str] = None) -> Tuple[Optional[str], Optional[Dict[str, Any]]]: + """점주를 위한 액션 추천을 생성합니다.""" + if not self.is_ready(): + logger.error("ClaudeService가 준비되지 않음") + return None, None + + try: + logger.info("🤖 Claude API를 통한 액션 추천 생성 시작") + + prompt = self._build_action_prompt(context, additional_context) + + response = self.client.messages.create( + model=self.model, + max_tokens=4000, + temperature=0.7, + messages=[ + { + "role": "user", + "content": prompt + } + ] + ) + + if response.content and len(response.content) > 0: + raw_response = response.content[0].text + logger.info(f"✅ 액션 추천 생성 완료: {len(raw_response)} 문자") + + parsed_response = self._parse_json_response(raw_response) + return raw_response, parsed_response + else: + logger.warning("⚠️ Claude API 응답이 비어있음") + return None, None + + except Exception as e: + logger.error(f"❌ 액션 추천 생성 중 오류: {e}") + return None, None + + def _parse_json_response(self, raw_response: str) -> Optional[Dict[str, Any]]: + """Claude의 원본 응답에서 JSON을 추출하고 파싱합니다.""" + try: + import re + + # JSON 블록 찾기 + json_match = re.search(r'```json\s*\n(.*?)\n```', raw_response, re.DOTALL) + if json_match: + json_str = json_match.group(1).strip() + else: + brace_start = raw_response.find('{') + brace_end = raw_response.rfind('}') + + if brace_start != -1 and brace_end != -1 and brace_end > brace_start: + json_str = raw_response[brace_start:brace_end + 1] + else: + logger.warning("⚠️ JSON 패턴을 찾을 수 없음") + return None + + parsed_json = json.loads(json_str) + logger.info("✅ JSON 파싱 성공") + return parsed_json + + except json.JSONDecodeError as e: + logger.warning(f"⚠️ JSON 파싱 실패: {e}") + return None + except Exception as e: + logger.warning(f"⚠️ JSON 추출 실패: {e}") + return None + + def _build_action_prompt(self, context: str, additional_context: Optional[str] = None) -> str: + """액션 추천을 위한 프롬프트를 구성합니다.""" + + base_prompt = f"""당신은 소상공인을 위한 경영 컨설턴트입니다. 아래 정보를 바탕으로 실질적이고 구체적인 액션 추천을 해주세요. + +**분석 데이터:** +{context} + +**추천 요구사항:** +1. 단기 계획 (1-3개월): 즉시 실행 가능한 개선사항 +2. 중기 계획 (3-6개월): 점진적 개선 방안 +3. 장기 계획 (6개월-1년): 전략적 발전 방향 + +**응답 형식:** +반드시 아래 JSON 형식으로만 응답해주세요: + +```json +{{ + "summary": {{ + "current_situation": "현재 상황 요약", + "key_insights": ["핵심 인사이트 1", "핵심 인사이트 2", "핵심 인사이트 3"], + "priority_areas": ["우선 개선 영역 1", "우선 개선 영역 2"] + }}, + "action_plans": {{ + "short_term": [ + {{ + "title": "액션 제목", + "description": "구체적인 실행 방법", + "expected_impact": "예상 효과", + "timeline": "실행 기간", + "cost": "예상 비용" + }} + ], + "mid_term": [ + {{ + "title": "액션 제목", + "description": "구체적인 실행 방법", + "expected_impact": "예상 효과", + "timeline": "실행 기간", + "cost": "예상 비용" + }} + ], + "long_term": [ + {{ + "title": "액션 제목", + "description": "구체적인 실행 방법", + "expected_impact": "예상 효과", + "timeline": "실행 기간", + "cost": "예상 비용" + }} + ] + }}, + "implementation_tips": [ + "실행 팁 1", + "실행 팁 2", + "실행 팁 3" + ] +}} +``` + +**응답은 반드시 유효한 JSON 형식으로만 작성하고, JSON 앞뒤에 다른 텍스트는 포함하지 마세요.**""" + + if additional_context: + base_prompt += f"\n\n**점주 추가 요청사항:**\n{additional_context}\n" + + return base_prompt + + # ============================================================================= + # 호환성을 위한 메서드들 (기존 코드가 사용할 수 있도록) + # ============================================================================= + + async def get_recommendation(self, prompt: str) -> Optional[str]: + """Claude API를 호출하여 추천을 받습니다. (호환성용)""" + if not self.is_ready(): + logger.error("ClaudeService가 준비되지 않음") + return None + + try: + logger.info("🤖 Claude API 호출 시작") + + response = self.client.messages.create( + model=self.model, + max_tokens=4000, + temperature=0.7, + messages=[ + { + "role": "user", + "content": prompt + } + ] + ) + + if response.content and len(response.content) > 0: + raw_response = response.content[0].text + logger.info(f"✅ Claude API 응답 성공: {len(raw_response)} 문자") + return raw_response + else: + logger.warning("⚠️ Claude API 응답이 비어있음") + return None + + except Exception as e: + logger.error(f"❌ Claude API 호출 실패: {e}") + return None + + def parse_recommendation_response(self, raw_response: str) -> Optional[Dict[str, Any]]: + """Claude 응답에서 JSON을 추출하고 파싱합니다. (호환성용)""" + return self._parse_json_response(raw_response) + + def build_recommendation_prompt(self, store_id: str, context: str, vector_context: Optional[str] = None) -> str: + """액션 추천용 프롬프트를 구성합니다. (호환성용)""" + + prompt_parts = [ + "당신은 소상공인을 위한 경영 컨설턴트입니다.", + f"가게 ID: {store_id}", + f"점주 요청: {context}" + ] + + if vector_context: + prompt_parts.extend([ + "\n--- 동종 업체 분석 데이터 ---", + vector_context, + "--- 분석 데이터 끝 ---\n" + ]) + + prompt_parts.extend([ + "\n위 정보를 바탕으로 실질적이고 구체적인 액션 추천을 해주세요.", + "응답은 반드시 아래 JSON 형식으로만 작성해주세요:", + "", + "```json", + "{", + ' "summary": {', + ' "current_situation": "현재 상황 요약",', + ' "key_insights": ["핵심 인사이트 1", "핵심 인사이트 2"],', + ' "priority_areas": ["우선 개선 영역 1", "우선 개선 영역 2"]', + ' },', + ' "action_plans": {', + ' "short_term": [', + ' {', + ' "title": "즉시 실행 가능한 액션",', + ' "description": "구체적인 실행 방법",', + ' "expected_impact": "예상 효과",', + ' "timeline": "1-2주",', + ' "cost": "예상 비용"', + ' }', + ' ],', + ' "mid_term": [', + ' {', + ' "title": "중기 개선 방안",', + ' "description": "구체적인 실행 방법",', + ' "expected_impact": "예상 효과",', + ' "timeline": "1-3개월",', + ' "cost": "예상 비용"', + ' }', + ' ]', + ' },', + ' "implementation_tips": ["실행 팁 1", "실행 팁 2"]', + "}", + "```" + ]) + + return "\n".join(prompt_parts) + + def create_prompt_for_api_response(self, context: str, additional_context: Optional[str] = None) -> str: + """API 응답용 프롬프트를 생성합니다. (호환성용)""" + return self._build_action_prompt(context, additional_context) + + # ============================================================================= + # 헬스체크 및 상태 확인 메서드들 + # ============================================================================= + + def get_health_status(self) -> Dict[str, Any]: + """ClaudeService 상태 확인""" + try: + status = { + "service": "claude_api", + "status": "healthy" if self.is_ready() else "unhealthy", + "model": self.model, + "api_key_configured": bool(settings.CLAUDE_API_KEY and settings.CLAUDE_API_KEY.strip()), + "timestamp": self._get_timestamp() + } + + if self.initialization_error: + status["initialization_error"] = self.initialization_error + status["status"] = "error" + + return status + + except Exception as e: + return { + "service": "claude_api", + "status": "error", + "error": str(e), + "timestamp": self._get_timestamp() + } + + def _get_timestamp(self) -> str: + """현재 시간 문자열 반환""" + from datetime import datetime + return datetime.now().isoformat() \ No newline at end of file diff --git a/vector/app/services/restaurant_service.py b/vector/app/services/restaurant_service.py new file mode 100644 index 0000000..5a7100e --- /dev/null +++ b/vector/app/services/restaurant_service.py @@ -0,0 +1,235 @@ +# app/services/restaurant_service.py (수정된 버전) +import aiohttp +import asyncio +import logging +from typing import List, Optional, Dict, Any +from ..config.settings import settings +from ..models.restaurant_models import RestaurantInfo +from ..utils.category_utils import extract_food_category + +logger = logging.getLogger(__name__) + +class RestaurantService: + """음식점 API 연동 서비스""" + + def __init__(self): + self.base_url = settings.get_restaurant_api_url() + self.timeout = aiohttp.ClientTimeout(total=settings.REQUEST_TIMEOUT) + + async def find_store_by_name_and_region(self, region: str, store_name: str) -> Optional[RestaurantInfo]: + """ + 지역과 가게명으로 가게를 찾습니다. + + Args: + region: 지역 (시군구 + 읍면동) + store_name: 가게명 + + Returns: + 찾은 가게 정보 (첫 번째 결과) + """ + try: + logger.info(f"가게 검색 시작: region={region}, store_name={store_name}") + + async with aiohttp.ClientSession(timeout=self.timeout) as session: + # Restaurant API 호출 + url = f"{self.base_url}/collect" + payload = { + "query": store_name, + "region": region, + "size": 15, + "pages": 3, + "save_to_file": False + } + + logger.info(f"Restaurant API 호출: {url}") + async with session.post(url, json=payload) as response: + if response.status == 200: + data = await response.json() + restaurants = data.get('restaurants', []) + + if restaurants: + # 첫 번째 결과 반환 + restaurant_data = restaurants[0] + restaurant = RestaurantInfo(**restaurant_data) + + logger.info(f"가게 찾기 성공: {restaurant.place_name}") + return restaurant + else: + logger.warning(f"가게를 찾을 수 없음: {store_name}") + return None + else: + logger.error(f"Restaurant API 호출 실패: HTTP {response.status}") + error_text = await response.text() + logger.error(f"Error response: {error_text}") + return None + + except asyncio.TimeoutError: + logger.error("Restaurant API 호출 타임아웃") + return None + except Exception as e: + logger.error(f"가게 검색 중 오류: {str(e)}") + return None + + def _clean_food_category(self, food_category: str) -> str: + """ + 음식 카테고리를 정리하여 검색 키워드로 변환합니다. + + Args: + food_category: 원본 음식 카테고리 (예: "육류,고기") + + Returns: + 정리된 검색 키워드 (예: "육류 고기") + """ + if not food_category: + return "음식점" + + # 콤마와 슬래시를 공백으로 변경 + cleaned = food_category.replace(',', ' ').replace('/', ' ') + + # 불필요한 단어 제거 + stop_words = ['음식점', '요리', '전문점', '맛집'] + keywords = [] + + for keyword in cleaned.split(): + keyword = keyword.strip() + if keyword and keyword not in stop_words: + keywords.append(keyword) + + # 키워드가 없으면 기본 검색어 사용 + if not keywords: + return "음식점" + + # 🔧 지역 정보는 포함하지 않고 음식 카테고리만 반환 + return ' '.join(keywords) + + async def find_similar_stores(self, region: str, food_category: str, max_count: int = 50) -> List[RestaurantInfo]: + """ + 동종 업체를 찾습니다. + + Args: + region: 지역 + food_category: 음식 카테고리 + max_count: 최대 검색 개수 + + Returns: + 동종 업체 목록 + """ + try: + logger.info(f"동종 업체 검색 시작: region={region}, food_category={food_category}") + + # 🔧 검색 쿼리 생성 (음식 카테고리만 포함) + search_query = self._clean_food_category(food_category) + logger.info(f"음식점 수집 요청: query='{search_query}' region='{region}' size=15 pages=1 save_to_file=False") + + similar_stores = [] + + async with aiohttp.ClientSession(timeout=self.timeout) as session: + # 페이지별로 검색 (최대 5페이지) + max_pages = min(5, (max_count // 15) + 1) + + for page in range(1, max_pages + 1): + if len(similar_stores) >= max_count: + break + + url = f"{self.base_url}/collect" + # 🔧 수정된 payload - query에는 음식 카테고리만, region은 분리 + payload = { + "query": search_query, # 🔧 음식 카테고리만 포함 + "region": region, # 🔧 지역 정보는 별도 파라미터 + "size": 15, + "pages": 1, # 페이지별로 하나씩 호출 + "save_to_file": False + } + + logger.info(f"동종 업체 검색 페이지 {page}: query='{search_query}' region='{region}'") + + try: + async with session.post(url, json=payload) as response: + if response.status == 200: + data = await response.json() + restaurants = data.get('restaurants', []) + + for restaurant_data in restaurants: + if len(similar_stores) >= max_count: + break + + try: + restaurant = RestaurantInfo(**restaurant_data) + + # 카테고리 필터링 + restaurant_category = extract_food_category(restaurant.category_name) + if self._is_similar_food_category(food_category, restaurant_category): + similar_stores.append(restaurant) + logger.debug(f"유사 카테고리 매치: {restaurant.place_name} ({restaurant_category})") + + except Exception as e: + logger.warning(f"음식점 데이터 파싱 실패: {e}") + continue + + logger.info(f"페이지 {page} 완료: {len(restaurants)}개 음식점 수집") + + else: + logger.warning(f"동종 업체 검색 실패 (페이지 {page}): HTTP {response.status}") + continue + + except Exception as e: + logger.warning(f"페이지 {page} 검색 중 오류: {e}") + continue + + # API 요청 제한을 위한 지연 + await asyncio.sleep(settings.REQUEST_DELAY) + + logger.info(f"동종 업체 검색 완료: 총 {len(similar_stores)}개") + return similar_stores + + except Exception as e: + logger.error(f"동종 업체 검색 중 오류: {str(e)}") + return [] + + def _is_similar_food_category(self, target_category: str, restaurant_category: str) -> bool: + """ + 음식 카테고리가 유사한지 확인합니다. + + Args: + target_category: 대상 카테고리 + restaurant_category: 음식점 카테고리 + + Returns: + 유사성 여부 + """ + if not target_category or not restaurant_category: + return False + + # 정규화 + target_lower = target_category.lower().strip() + restaurant_lower = restaurant_category.lower().strip() + + # 완전 일치 + if target_lower == restaurant_lower: + return True + + # 키워드 기반 매칭 + target_keywords = set(target_lower.replace(',', ' ').replace('/', ' ').split()) + restaurant_keywords = set(restaurant_lower.replace(',', ' ').replace('/', ' ').split()) + + # 교집합이 있으면 유사한 것으로 판단 + common_keywords = target_keywords.intersection(restaurant_keywords) + + return len(common_keywords) > 0 + + async def health_check(self) -> bool: + """ + Restaurant API 상태를 확인합니다. + + Returns: + API 상태 (True: 정상, False: 비정상) + """ + try: + async with aiohttp.ClientSession(timeout=self.timeout) as session: + url = f"{self.base_url}/health" + async with session.get(url) as response: + return response.status == 200 + except Exception as e: + logger.error(f"Restaurant API 헬스체크 실패: {e}") + return False + diff --git a/vector/app/services/review_service.py b/vector/app/services/review_service.py new file mode 100644 index 0000000..c3b7f48 --- /dev/null +++ b/vector/app/services/review_service.py @@ -0,0 +1,467 @@ +# vector/app/services/review_service.py +import aiohttp +import asyncio +import logging +from typing import List, Dict, Any, Tuple, Optional +from ..config.settings import settings +from ..models.review_models import ReviewAnalysisResponse, StoreInfo, ReviewData +from ..models.restaurant_models import RestaurantInfo + +logger = logging.getLogger(__name__) + +class ReviewService: + """리뷰 API 연동 서비스 (본인 가게 우선 처리 강화)""" + + def __init__(self): + self.base_url = settings.get_review_api_url() + self.timeout = aiohttp.ClientTimeout(total=settings.REQUEST_TIMEOUT) + + async def collect_store_reviews(self, store_id: str, max_reviews: int = 100) -> Tuple[Optional[Dict[str, Any]], List[Dict[str, Any]]]: + """ + 단일 가게의 리뷰를 수집합니다. (본인 가게용 강화 처리) + + Args: + store_id: 카카오맵 가게 ID + max_reviews: 최대 수집할 리뷰 수 + + Returns: + (가게 정보, 리뷰 목록) 튜플 + """ + try: + logger.info(f"🏪 가게 리뷰 수집 시작: store_id={store_id} (최대 {max_reviews}개)") + + # 본인 가게는 더 관대한 타임아웃 설정 + timeout = aiohttp.ClientTimeout(total=900) # 15분 + + async with aiohttp.ClientSession(timeout=timeout) as session: + url = f"{self.base_url}/analyze" + payload = { + "store_id": store_id, + "days_limit": None, # 모든 날짜의 리뷰 수집 + "max_time": min(600, max_reviews * 3) # 리뷰 수에 따라 시간 조정, 최대 10분 + } + + logger.info(f"Review API 호출: {url} (타임아웃: {payload['max_time']}초)") + + async with session.post(url, json=payload) as response: + if response.status == 200: + data = await response.json() + + if data.get('success', False): + store_info = data.get('store_info') + reviews = data.get('reviews', []) + + logger.info(f"📊 원본 리뷰 수집: {len(reviews)}개") + + # 리뷰 품질 필터링 + filtered_reviews = self._filter_quality_reviews(reviews) + logger.info(f"📊 품질 필터링 후: {len(filtered_reviews)}개") + + # 리뷰 개수 제한 + if len(filtered_reviews) > max_reviews: + filtered_reviews = filtered_reviews[:max_reviews] + logger.info(f"📊 최종 리뷰 수: {len(filtered_reviews)}개 (제한 적용)") + + # 가게 정보와 리뷰 변환 + converted_store_info = self._convert_store_info(store_info) + converted_reviews = self._convert_reviews(filtered_reviews) + + if converted_store_info and converted_reviews: + logger.info(f"✅ 리뷰 수집 성공: {len(converted_reviews)}개") + return converted_store_info, converted_reviews + else: + logger.warning("⚠️ 변환된 데이터가 비어있음") + return None, [] + else: + error_msg = data.get('message', 'Unknown error') + logger.error(f"❌ 리뷰 분석 실패: {error_msg}") + return None, [] + else: + logger.error(f"❌ Review API 호출 실패: HTTP {response.status}") + error_text = await response.text() + logger.error(f"Error response: {error_text}") + return None, [] + + except asyncio.TimeoutError: + logger.error("❌ Review API 호출 타임아웃") + return None, [] + except Exception as e: + logger.error(f"❌ 리뷰 수집 중 오류: {str(e)}") + return None, [] + + def _filter_quality_reviews(self, reviews: List[Dict[str, Any]]) -> List[Dict[str, Any]]: + """리뷰 품질 필터링""" + try: + filtered = [] + + for review in reviews: + content = review.get('content', '').strip() + rating = review.get('rating', 0) + + # 품질 기준 + if (len(content) >= 10 and # 최소 10자 이상 + rating > 0 and # 별점이 있어야 함 + not self._is_spam_review(content)): # 스팸 제외 + filtered.append(review) + + logger.debug(f"품질 필터링: {len(reviews)} → {len(filtered)}") + return filtered + + except Exception as e: + logger.warning(f"⚠️ 리뷰 필터링 실패: {e}") + return reviews # 실패 시 원본 반환 + + def _is_spam_review(self, content: str) -> bool: + """스팸 리뷰 판별""" + try: + spam_keywords = [ + "추천추천", "최고최고", "맛있어요맛있어요", + "좋아요좋아요", "ㅎㅎㅎㅎ", "ㅋㅋㅋㅋ", + "굿굿굿", "Nice", "Good" + ] + + content_lower = content.lower() + + # 스팸 키워드 확인 + for keyword in spam_keywords: + if keyword.lower() in content_lower: + return True + + # 너무 짧거나 반복 문자 확인 + if len(set(content.replace(' ', ''))) < 3: # 고유 문자 3개 미만 + return True + + return False + + except Exception as e: + logger.warning(f"⚠️ 스팸 판별 실패: {e}") + return False + + def _convert_store_info(self, store_info): + """가게 정보 변환 (강화된 버전)""" + if not store_info: + logger.warning("⚠️ 가게 정보가 비어있음") + return None + + try: + converted = { + 'id': str(store_info.get('id', '')), + 'name': str(store_info.get('name', '')), + 'category': str(store_info.get('category', '')), + 'rating': str(store_info.get('rating', '')), + 'review_count': str(store_info.get('review_count', '')), + 'status': str(store_info.get('status', '')), + 'address': str(store_info.get('address', '')) + } + + # 필수 필드 확인 (ID와 이름은 반드시 있어야 함) + if not converted['id'] or not converted['name']: + logger.warning(f"⚠️ 필수 가게 정보 누락: ID={converted['id']}, Name={converted['name']}") + return None + + logger.debug(f"가게 정보 변환 성공: {converted['name']}") + return converted + + except Exception as e: + logger.error(f"❌ 가게 정보 변환 실패: {e}") + return None + + def _convert_reviews(self, reviews): + """리뷰 목록 변환 (강화된 버전)""" + if not reviews: + logger.warning("⚠️ 리뷰 목록이 비어있음") + return [] + + converted_reviews = [] + + for i, review in enumerate(reviews): + try: + # 안전한 형변환 + rating = 0 + try: + rating = int(review.get('rating', 0)) + except (ValueError, TypeError): + rating = 0 + + likes = 0 + try: + likes = int(review.get('likes', 0)) + except (ValueError, TypeError): + likes = 0 + + photo_count = 0 + try: + photo_count = int(review.get('photo_count', 0)) + except (ValueError, TypeError): + photo_count = 0 + + converted_review = { + 'reviewer_name': str(review.get('reviewer_name', 'Anonymous')), + 'rating': rating, + 'date': str(review.get('date', '')), + 'content': str(review.get('content', '')).strip(), + 'badges': list(review.get('badges', [])), + 'likes': likes, + 'photo_count': photo_count, + 'has_photos': bool(photo_count > 0) + } + + # 기본 검증 + if converted_review['content'] and converted_review['rating'] > 0: + converted_reviews.append(converted_review) + else: + logger.debug(f"⚠️ 리뷰 {i+1} 품질 미달로 제외") + + except Exception as e: + logger.warning(f"⚠️ 리뷰 {i+1} 변환 실패: {e}") + continue + + logger.info(f"리뷰 변환 완료: {len(reviews)} → {len(converted_reviews)}") + return converted_reviews + + async def collect_multiple_stores_reviews(self, restaurants: List[RestaurantInfo]) -> List[Tuple[str, Dict[str, Any], List[Dict[str, Any]]]]: + """ + 여러 가게의 리뷰를 수집합니다. + + Args: + restaurants: 음식점 목록 + + Returns: + (store_id, 가게 정보, 리뷰 목록) 튜플의 리스트 + """ + try: + logger.info(f"다중 가게 리뷰 수집 시작: {len(restaurants)}개 가게") + + results = [] + + # 동시성 제한을 위해 세마포어 사용 + semaphore = asyncio.Semaphore(3) # 최대 3개 동시 요청 + + async def collect_single_store(restaurant: RestaurantInfo): + async with semaphore: + try: + # 카카오맵 place_url에서 store_id 추출 시도 + store_id = self._extract_store_id_from_url(restaurant.place_url) + + if not store_id: + # URL에서 추출 실패 시 restaurant.id 사용 + store_id = restaurant.id + + if not store_id: + logger.warning(f"Store ID를 찾을 수 없음: {restaurant.place_name}") + return None + + logger.info(f"가게 {restaurant.place_name} 리뷰 수집 중...") + + # 리뷰 수집 (최대 50개로 제한) + store_info, reviews = await self.collect_store_reviews( + store_id, + max_reviews=settings.MAX_REVIEWS_PER_RESTAURANT + ) + + if store_info and reviews: + return (store_id, store_info, reviews) + else: + logger.warning(f"가게 {restaurant.place_name}의 리뷰 수집 실패") + return None + + except Exception as e: + logger.error(f"가게 {restaurant.place_name} 리뷰 수집 중 오류: {e}") + return None + + finally: + # API 요청 제한을 위한 지연 + await asyncio.sleep(settings.REQUEST_DELAY) + + # 병렬 처리 + tasks = [collect_single_store(restaurant) for restaurant in restaurants] + results_raw = await asyncio.gather(*tasks, return_exceptions=True) + + # 성공한 결과만 필터링 + for result in results_raw: + if result and not isinstance(result, Exception): + results.append(result) + + logger.info(f"다중 가게 리뷰 수집 완료: {len(results)}개 성공") + return results + + except Exception as e: + logger.error(f"다중 가게 리뷰 수집 중 오류: {str(e)}") + return [] + + def _extract_store_id_from_url(self, place_url: str) -> Optional[str]: + """ + 카카오맵 URL에서 store_id를 추출합니다. + + Args: + place_url: 카카오맵 장소 URL + + Returns: + 추출된 store_id 또는 None + """ + try: + if not place_url: + return None + + # URL 패턴: https://place.map.kakao.com/123456789 + import re + pattern = r'/(\d+)(?:\?|$|#)' + match = re.search(pattern, place_url) + + if match: + store_id = match.group(1) + logger.debug(f"URL에서 store_id 추출: {store_id}") + return store_id + else: + logger.debug(f"URL에서 store_id 추출 실패: {place_url}") + return None + + except Exception as e: + logger.warning(f"store_id 추출 중 오류: {e}") + return None + + def _build_store_info_from_restaurant(self, restaurant: RestaurantInfo) -> Dict[str, Any]: + """ + RestaurantInfo를 store_info 형식으로 변환합니다. + + Args: + restaurant: RestaurantInfo 객체 + + Returns: + store_info 딕셔너리 + """ + try: + return { + 'id': restaurant.id, + 'name': restaurant.place_name, + 'category': restaurant.category_name, + 'rating': '', # API에서 제공되지 않음 + 'review_count': '', # API에서 제공되지 않음 + 'status': '', # API에서 제공되지 않음 + 'address': restaurant.address_name + } + except Exception as e: + logger.error(f"RestaurantInfo 변환 실패: {e}") + return { + 'id': '', + 'name': '', + 'category': '', + 'rating': '', + 'review_count': '', + 'status': '', + 'address': '' + } + + def _convert_single_review_data(self, review_data: dict) -> dict: + """ + 단일 리뷰 데이터 변환 + + Args: + review_data: API 응답의 단일 리뷰 데이터 + + Returns: + 변환된 리뷰 데이터 + """ + try: + return { + 'reviewer_name': review_data.get('reviewer_name', ''), + 'reviewer_level': review_data.get('reviewer_level', ''), + 'reviewer_stats': review_data.get('reviewer_stats', {}), + 'rating': int(review_data.get('rating', 0)), + 'date': review_data.get('date', ''), + 'content': review_data.get('content', ''), + 'badges': review_data.get('badges', []), + 'likes': int(review_data.get('likes', 0)), + 'photo_count': int(review_data.get('photo_count', 0)), + 'has_photos': bool(review_data.get('has_photos', False)) + } + except Exception as e: + logger.warning(f"단일 리뷰 데이터 변환 실패: {e}") + return { + 'reviewer_name': 'Unknown', + 'reviewer_level': '', + 'reviewer_stats': {}, + 'rating': 0, + 'date': '', + 'content': '', + 'badges': [], + 'likes': 0, + 'photo_count': 0, + 'has_photos': False + } + + async def health_check(self) -> bool: + """ + Review API 상태를 확인합니다. + + Returns: + API 상태 (True: 정상, False: 비정상) + """ + try: + async with aiohttp.ClientSession(timeout=self.timeout) as session: + url = f"{self.base_url}/health" + async with session.get(url) as response: + is_healthy = response.status == 200 + if is_healthy: + logger.debug("Review API 헬스체크 성공") + else: + logger.warning(f"Review API 헬스체크 실패: HTTP {response.status}") + return is_healthy + except Exception as e: + logger.error(f"Review API 헬스체크 실패: {e}") + return False + + def get_api_info(self) -> Dict[str, Any]: + """ + Review API 정보를 반환합니다. + + Returns: + API 정보 딕셔너리 + """ + return { + "service_name": "Review API Service", + "base_url": self.base_url, + "timeout": self.timeout.total, + "max_reviews_per_restaurant": settings.MAX_REVIEWS_PER_RESTAURANT, + "request_delay": settings.REQUEST_DELAY + } + + async def test_connection(self) -> Dict[str, Any]: + """ + Review API 연결을 테스트합니다. + + Returns: + 테스트 결과 + """ + test_result = { + "service": "Review API", + "base_url": self.base_url, + "status": "unknown", + "response_time": None, + "error": None + } + + try: + import time + start_time = time.time() + + is_healthy = await self.health_check() + + response_time = time.time() - start_time + test_result["response_time"] = round(response_time, 3) + + if is_healthy: + test_result["status"] = "healthy" + logger.info(f"Review API 연결 테스트 성공: {response_time:.3f}초") + else: + test_result["status"] = "unhealthy" + test_result["error"] = "Health check failed" + logger.warning("Review API 연결 테스트 실패: 헬스체크 실패") + + except Exception as e: + test_result["status"] = "error" + test_result["error"] = str(e) + logger.error(f"Review API 연결 테스트 오류: {e}") + + return test_result + diff --git a/vector/app/services/vector_service.py b/vector/app/services/vector_service.py new file mode 100644 index 0000000..eb9ba99 --- /dev/null +++ b/vector/app/services/vector_service.py @@ -0,0 +1,728 @@ +# app/services/vector_service.py (개선된 버전) +import os +import json +import logging +import time +import shutil +import signal +from datetime import datetime +from typing import List, Dict, Any, Optional, Tuple +import chromadb +from chromadb.config import Settings as ChromaSettings +from sentence_transformers import SentenceTransformer +from ..config.settings import settings +from ..utils.data_utils import ( + create_store_hash, combine_store_and_reviews, generate_review_summary, + extract_text_for_embedding, create_metadata, is_duplicate_store +) + +logger = logging.getLogger(__name__) + +class VectorService: + """Vector DB 서비스 (개선된 초기화 로직)""" + + def __init__(self): + self.db_path = settings.VECTOR_DB_PATH + self.collection_name = settings.VECTOR_DB_COLLECTION + self.embedding_model_name = settings.EMBEDDING_MODEL + + # 상태 변수 + self.client = None + self.collection = None + self.embedding_model = None + self.initialization_error = None + + # 안전한 초기화 시도 + self._safe_initialize() + + def _safe_initialize(self): + """안전한 초기화 - 개선된 로직""" + try: + logger.info("🔧 VectorService 초기화 시작...") + + # 1단계: 디렉토리 권한 확인 + self._ensure_directory_permissions() + + # 2단계: ChromaDB 초기화 (호환성 확인 포함) + self._initialize_chromadb_with_compatibility_check() + + # 3단계: 임베딩 모델 로드 + self._initialize_embedding_model() + + logger.info("✅ VectorService 초기화 완료") + + except Exception as e: + self.initialization_error = str(e) + logger.error(f"❌ VectorService 초기화 실패: {e}") + logger.info("🔄 서비스는 런타임에 재시도 가능합니다") + + def _ensure_directory_permissions(self): + """Vector DB 디렉토리 권한을 확인하고 생성합니다""" + try: + logger.info(f"📁 Vector DB 디렉토리 설정: {self.db_path}") + + # 절대 경로로 변환 + abs_path = os.path.abspath(self.db_path) + + # 디렉토리 생성 + os.makedirs(abs_path, mode=0o755, exist_ok=True) + + # 권한 확인 + if not os.access(abs_path, os.W_OK): + logger.warning(f"⚠️ 쓰기 권한 없음: {abs_path}") + + # 권한 변경 시도 + try: + os.chmod(abs_path, 0o755) + logger.info("✅ 디렉토리 권한 변경 성공") + except Exception as chmod_error: + logger.warning(f"⚠️ 권한 변경 실패: {chmod_error}") + # 임시 디렉토리로 대체 + import tempfile + temp_dir = tempfile.mkdtemp(prefix="vectordb_") + logger.info(f"🔄 임시 디렉토리 사용: {temp_dir}") + self.db_path = temp_dir + abs_path = temp_dir + + # 테스트 파일 생성/삭제로 권한 확인 + test_file = os.path.join(abs_path, "test_permissions.tmp") + try: + with open(test_file, 'w') as f: + f.write("test") + os.remove(test_file) + logger.info("✅ 디렉토리 권한 확인 완료") + except Exception as test_error: + raise Exception(f"디렉토리 권한 테스트 실패: {test_error}") + + except Exception as e: + logger.error(f"❌ 디렉토리 설정 실패: {e}") + raise + + def _initialize_chromadb_with_compatibility_check(self): + """ChromaDB 초기화 (호환성 확인 포함)""" + max_retries = 3 + retry_delay = 2 + + for attempt in range(max_retries): + try: + logger.info(f"🔄 ChromaDB 초기화 시도 {attempt + 1}/{max_retries}") + + # 1단계: 기존 DB 호환성 확인 + existing_db_valid = self._check_existing_db_compatibility() + + # 2단계: ChromaDB 클라이언트 생성 + self._create_chromadb_client() + + # 3단계: 컬렉션 초기화 + self._initialize_collection(existing_db_valid) + + logger.info("✅ ChromaDB 초기화 완료") + return # 성공 시 루프 종료 + + except Exception as e: + logger.error(f"❌ ChromaDB 초기화 실패 (시도 {attempt + 1}): {e}") + + if attempt < max_retries - 1: + logger.info(f"🔄 {retry_delay}초 후 재시도...") + time.sleep(retry_delay) + retry_delay *= 2 # 지수 백오프 + else: + raise Exception(f"ChromaDB 초기화 최종 실패: {e}") + + def _check_existing_db_compatibility(self): + """기존 DB 호환성 확인""" + try: + if not os.path.exists(self.db_path): + logger.info("📁 새 DB 디렉토리 - 스키마 확인 불필요") + return False + + db_files = [f for f in os.listdir(self.db_path) if not f.startswith('.')] + if not db_files: + logger.info("📁 빈 DB 디렉토리 - 스키마 확인 불필요") + return False + + logger.info(f"📁 기존 DB 파일 발견: {db_files}") + + # 실제 호환성 테스트 + logger.info("🔍 기존 DB 호환성 테스트 중...") + + try: + # 테스트용 클라이언트 생성 + test_client = chromadb.PersistentClient(path=self.db_path) + test_client.heartbeat() + + # 컬렉션 접근 시도 + try: + test_collection = test_client.get_collection(name=self.collection_name) + count = test_collection.count() + logger.info(f"✅ 기존 DB 호환성 확인 완료: {count}개 벡터 존재") + return True + except Exception as collection_error: + logger.info(f"📝 기존 컬렉션 없음 (정상): {collection_error}") + return True # DB는 정상, 컬렉션만 새로 생성하면 됨 + + except Exception as compatibility_error: + # 실제 호환성 문제 발견 + logger.warning(f"⚠️ 실제 호환성 문제 발견: {compatibility_error}") + self._backup_incompatible_db() + return False + + except Exception as e: + logger.warning(f"⚠️ 호환성 확인 중 오류: {e}") + return False + + def _backup_incompatible_db(self): + """호환성 문제가 있는 DB 백업""" + try: + backup_path = f"{self.db_path}_backup_{datetime.now().strftime('%Y%m%d_%H%M%S')}" + logger.warning(f"🔄 호환성 문제로 기존 DB 백업: {backup_path}") + + shutil.move(self.db_path, backup_path) + logger.info(f"✅ 기존 DB 백업 완료: {backup_path}") + + # 새 디렉토리 생성 + os.makedirs(self.db_path, exist_ok=True) + + # 오래된 백업 정리 (7일 이상) + self._cleanup_old_backups() + + except Exception as backup_error: + logger.warning(f"⚠️ 백업 실패, 강제 삭제 진행: {backup_error}") + shutil.rmtree(self.db_path, ignore_errors=True) + os.makedirs(self.db_path, exist_ok=True) + + def _cleanup_old_backups(self): + """오래된 백업 파일 정리 (7일 이상)""" + try: + base_path = os.path.dirname(self.db_path) + backup_pattern = f"{os.path.basename(self.db_path)}_backup_" + cutoff_time = time.time() - (7 * 24 * 3600) # 7일 전 + + for item in os.listdir(base_path): + if item.startswith(backup_pattern): + backup_path = os.path.join(base_path, item) + if os.path.isdir(backup_path) and os.path.getctime(backup_path) < cutoff_time: + shutil.rmtree(backup_path, ignore_errors=True) + logger.info(f"🗑️ 오래된 백업 삭제: {backup_path}") + + except Exception as e: + logger.warning(f"⚠️ 백업 정리 중 오류: {e}") + + def _create_chromadb_client(self): + """ChromaDB 클라이언트 생성""" + try: + # 최신 버전 호환 설정 + chroma_settings = ChromaSettings( + anonymized_telemetry=False, + allow_reset=True, + is_persistent=True + ) + + self.client = chromadb.PersistentClient( + path=self.db_path, + settings=chroma_settings + ) + logger.info("✅ ChromaDB 클라이언트 생성 성공") + + except Exception as modern_error: + logger.warning(f"⚠️ 최신 설정 실패, 간단한 설정으로 재시도: {modern_error}") + + # 간단한 설정으로 재시도 + self.client = chromadb.PersistentClient(path=self.db_path) + logger.info("✅ ChromaDB 간단 설정 클라이언트 생성 성공") + + # 연결 테스트 + try: + self.client.heartbeat() + logger.info("✅ ChromaDB 연결 테스트 성공") + except Exception as heartbeat_error: + logger.warning(f"⚠️ Heartbeat 실패 (무시): {heartbeat_error}") + + def _initialize_collection(self, existing_db_valid: bool): + """컬렉션 초기화""" + try: + if existing_db_valid: + # 기존 컬렉션 로드 시도 + try: + self.collection = self.client.get_collection(name=self.collection_name) + count = self.collection.count() + logger.info(f"✅ 기존 컬렉션 로드 성공: {self.collection_name} ({count}개 벡터)") + return + except Exception as get_error: + logger.info(f"📝 기존 컬렉션 없음, 새로 생성: {get_error}") + + # 새 컬렉션 생성 + self.collection = self.client.create_collection( + name=self.collection_name, + metadata={ + "description": "Restaurant reviews vector store", + "created_at": datetime.now().isoformat(), + "version": "1.0" + } + ) + logger.info(f"✅ 새 컬렉션 생성 성공: {self.collection_name}") + + except Exception as create_error: + logger.error(f"❌ 컬렉션 초기화 실패: {create_error}") + + # 대체 컬렉션명으로 재시도 + fallback_name = f"{self.collection_name}_{int(time.time())}" + logger.info(f"🔄 대체 컬렉션명으로 재시도: {fallback_name}") + + self.collection = self.client.create_collection( + name=fallback_name, + metadata={"description": "Restaurant reviews (fallback)"} + ) + self.collection_name = fallback_name + logger.info(f"✅ 대체 컬렉션 생성 성공: {fallback_name}") + + def _initialize_embedding_model(self): + """임베딩 모델 초기화""" + try: + logger.info(f"🤖 임베딩 모델 로드 시작: {self.embedding_model_name}") + + # 캐시 디렉토리 설정 + cache_dir = os.path.join(os.path.expanduser("~"), ".cache", "sentence_transformers") + os.makedirs(cache_dir, exist_ok=True) + + # 권한 확인 + if not os.access(cache_dir, os.W_OK): + import tempfile + cache_dir = tempfile.mkdtemp(prefix="st_cache_") + logger.info(f"🔄 임시 캐시 디렉토리 사용: {cache_dir}") + + # 모델 로드 (타임아웃 설정) + def timeout_handler(signum, frame): + raise TimeoutError("임베딩 모델 로드 타임아웃") + + signal.signal(signal.SIGALRM, timeout_handler) + signal.alarm(300) # 5분 타임아웃 + + try: + self.embedding_model = SentenceTransformer( + self.embedding_model_name, + cache_folder=cache_dir, + device='cpu' # CPU 사용 명시 + ) + signal.alarm(0) # 타임아웃 해제 + + # 모델 테스트 + test_embedding = self.embedding_model.encode(["테스트 문장"]) + logger.info(f"✅ 임베딩 모델 로드 성공: {test_embedding.shape}") + + except TimeoutError: + signal.alarm(0) + raise Exception("임베딩 모델 로드 타임아웃 (5분)") + + except Exception as e: + logger.error(f"❌ 임베딩 모델 로드 실패: {e}") + raise + + def is_ready(self) -> bool: + """서비스 준비 상태 확인""" + return ( + self.client is not None and + self.collection is not None and + self.embedding_model is not None and + self.initialization_error is None + ) + + def get_initialization_error(self) -> Optional[str]: + """초기화 에러 메시지 반환""" + return self.initialization_error + + def retry_initialization(self) -> bool: + """초기화 재시도""" + try: + logger.info("🔄 VectorService 초기화 재시도...") + + # 상태 초기화 + self.client = None + self.collection = None + self.embedding_model = None + self.initialization_error = None + + # 재초기화 + self._safe_initialize() + + return self.is_ready() + + except Exception as e: + self.initialization_error = str(e) + logger.error(f"❌ 초기화 재시도 실패: {e}") + return False + + def reset_vector_db(self) -> Dict[str, Any]: + """Vector DB 완전 리셋""" + try: + logger.info("🔄 Vector DB 완전 리셋 시작...") + + # 기존 클라이언트 정리 + self.client = None + self.collection = None + + # DB 디렉토리 완전 삭제 + if os.path.exists(self.db_path): + shutil.rmtree(self.db_path, ignore_errors=True) + logger.info(f"✅ 기존 DB 디렉토리 삭제: {self.db_path}") + + # 새 디렉토리 생성 + os.makedirs(self.db_path, exist_ok=True) + logger.info(f"✅ 새 DB 디렉토리 생성: {self.db_path}") + + # 재초기화 + success = self.retry_initialization() + + if success: + return { + "success": True, + "message": "Vector DB가 성공적으로 리셋되었습니다", + "collection_name": self.collection_name, + "db_path": self.db_path + } + else: + return { + "success": False, + "error": self.initialization_error or "재초기화 실패" + } + + except Exception as e: + logger.error(f"❌ Vector DB 리셋 실패: {e}") + return { + "success": False, + "error": str(e) + } + + def get_health_status(self) -> Dict[str, Any]: + """서비스 상태 확인""" + try: + status = { + "service": "vector_db", + "status": "healthy" if self.is_ready() else "unhealthy", + "db_path": self.db_path, + "collection_name": self.collection_name, + "embedding_model": self.embedding_model_name, + "timestamp": datetime.now().isoformat() + } + + if self.initialization_error: + status["initialization_error"] = self.initialization_error + status["status"] = "error" + + # 상세 상태 + status["components"] = { + "client": "connected" if self.client else "disconnected", + "collection": "ready" if self.collection else "not_ready", + "embedding": "loaded" if self.embedding_model else "not_loaded" + } + + # 컬렉션 정보 + if self.collection: + try: + status["collection_count"] = self.collection.count() + except Exception as e: + status["collection_error"] = str(e) + + return status + + except Exception as e: + return { + "service": "vector_db", + "status": "error", + "error": str(e), + "timestamp": datetime.now().isoformat() + } + + def get_store_context(self, store_id: str) -> Optional[str]: + """스토어 ID로 컨텍스트 조회""" + try: + if not self.is_ready(): + logger.warning("VectorService가 준비되지 않음") + return None + + # 스토어 ID로 검색 + results = self.collection.get( + where={"store_id": store_id} + ) + + if not results or not results.get('documents'): + logger.warning(f"스토어 ID '{store_id}'에 대한 데이터 없음") + return None + + # 컨텍스트 생성 + documents = results['documents'] + metadatas = results.get('metadatas', []) + + context_parts = [] + for i, doc in enumerate(documents): + metadata = metadatas[i] if i < len(metadatas) else {} + + # 메타데이터 정보 추가 + if metadata: + context_parts.append(f"[{metadata.get('store_name', 'Unknown')}]") + + context_parts.append(doc) + context_parts.append("---") + + return "\n".join(context_parts) + + except Exception as e: + logger.error(f"스토어 컨텍스트 조회 실패: {e}") + return None + + async def build_vector_store(self, store_info: Dict[str, Any], similar_stores_data: List[Tuple[str, Dict[str, Any], List[Dict[str, Any]]]], food_category: str, region: str) -> Dict[str, Any]: + """Vector Store 구축 (완전 수정된 버전)""" + try: + if not self.is_ready(): + # 재시도 한 번 더 + if not self.retry_initialization(): + raise Exception("Vector DB가 초기화되지 않았습니다") + + logger.info(f"Vector Store 구축 시작: {len(similar_stores_data)}개 스토어") + + # 통계 초기화 + stats = { + "total_processed": 0, + "newly_added": 0, + "updated": 0, + "duplicates": 0, + "errors": 0 + } + + # 배치 처리용 리스트 + all_documents = [] + all_embeddings = [] + all_metadatas = [] + all_ids = [] + + # 각 스토어 처리 + for store_id, store_data, reviews in similar_stores_data: + try: + # 데이터 검증 + if not store_data or not reviews: + logger.warning(f"스토어 '{store_id}' 데이터 부족: store_data={bool(store_data)}, reviews={len(reviews) if reviews else 0}") + stats["errors"] += 1 + continue + + # 올바른 create_store_hash 호출 + store_hash = create_store_hash( + store_id=store_id, + store_name=store_data.get('place_name', ''), + region=region + ) + + # ChromaDB에서 직접 중복 확인 (is_duplicate_store 함수 사용하지 않음) + try: + # 같은 store_id로 이미 저장된 데이터가 있는지 확인 + existing_data = self.collection.get( + where={"store_id": store_id}, + limit=1 + ) + + if existing_data and len(existing_data.get('ids', [])) > 0: + logger.debug(f"중복 스토어 건너뛰기: {store_id}") + stats["duplicates"] += 1 + continue + + except Exception as dup_check_error: + # 중복 확인 실패는 로그만 남기고 계속 진행 + logger.warning(f"중복 확인 실패 (계속 진행): {dup_check_error}") + + # 올바른 extract_text_for_embedding 호출 + embedding_text = extract_text_for_embedding( + store_info=store_data, + reviews=reviews + ) + + # 임베딩 생성 + try: + embedding = self.embedding_model.encode(embedding_text) + embedding = embedding.tolist() # numpy array를 list로 변환 + except Exception as embed_error: + logger.error(f"임베딩 생성 실패 (store_id: {store_id}): {embed_error}") + stats["errors"] += 1 + continue + + # 올바른 create_metadata 호출 + metadata = create_metadata( + store_info=store_data, + food_category=food_category, + region=region + ) + + # 배치에 추가 + all_documents.append(embedding_text) + all_embeddings.append(embedding) + all_metadatas.append(metadata) + all_ids.append(f"{store_id}_{store_hash}") + + stats["total_processed"] += 1 + stats["newly_added"] += 1 + + if stats["total_processed"] % 10 == 0: + logger.info(f"처리 진행률: {stats['total_processed']}/{len(similar_stores_data)}") + + except Exception as store_error: + logger.error(f"음식점 처리 중 오류 (store_id: {store_id}): {store_error}") + stats["errors"] += 1 + continue + + # 배치로 벡터 저장 + if all_documents: + logger.info(f"벡터 배치 저장 시작: {len(all_documents)}개") + + try: + self.collection.add( + documents=all_documents, + embeddings=all_embeddings, + metadatas=all_metadatas, + ids=all_ids + ) + logger.info("✅ 벡터 배치 저장 성공") + + except Exception as save_error: + logger.error(f"❌ 벡터 저장 실패: {save_error}") + return { + "success": False, + "error": f"벡터 저장 실패: {str(save_error)}", + "statistics": stats + } + else: + logger.warning("⚠️ 저장할 벡터 데이터가 없음") + + # 최종 통계 + try: + total_vectors = self.collection.count() + logger.info(f"✅ Vector Store 구축 완료: 총 {total_vectors}개 벡터") + except Exception as count_error: + logger.warning(f"벡터 개수 확인 실패: {count_error}") + total_vectors = len(all_documents) + + return { + "success": True, + "message": "Vector Store 구축 완료", + "statistics": stats, + "total_vectors": total_vectors, + "store_info": store_info + } + + except Exception as e: + logger.error(f"Vector Store 구축 전체 실패: {e}") + return { + "success": False, + "error": str(e), + "statistics": stats if 'stats' in locals() else { + "total_processed": 0, + "newly_added": 0, + "updated": 0, + "duplicates": 0, + "errors": 1 + } + } + + def get_db_status(self) -> Dict[str, Any]: + """Vector DB 상태 정보를 반환합니다.""" + try: + if not self.is_ready(): + return { + 'collection_name': self.collection_name, + 'total_documents': 0, + 'total_stores': 0, + 'db_path': self.db_path, + 'status': 'not_ready', + 'initialization_error': self.initialization_error + } + + # 문서 개수 확인 + try: + total_documents = self.collection.count() + except Exception as e: + logger.warning(f"문서 개수 확인 실패: {e}") + total_documents = 0 + + # 고유 가게 수 확인 (store_id 기준) + try: + # 모든 메타데이터에서 고유 store_id 추출 + all_metadata = self.collection.get() + store_ids = set() + + if all_metadata.get('metadatas'): + for metadata in all_metadata['metadatas']: + store_id = metadata.get('store_id') + if store_id: + store_ids.add(store_id) + + total_stores = len(store_ids) + + except Exception as e: + logger.warning(f"가게 수 확인 실패: {e}") + total_stores = 0 + + return { + 'collection_name': self.collection_name, + 'total_documents': total_documents, + 'total_stores': total_stores, + 'db_path': self.db_path, + 'status': 'ready' + } + + except Exception as e: + logger.error(f"DB 상태 확인 실패: {e}") + return { + 'collection_name': self.collection_name, + 'total_documents': 0, + 'total_stores': 0, + 'db_path': self.db_path, + 'status': 'error', + 'error': str(e) + } + + def search_similar_cases(self, store_id: str, context: str) -> Optional[str]: + """유사한 케이스를 검색합니다.""" + try: + if not self.is_ready(): + logger.warning("VectorService가 준비되지 않음") + return None + + # 컨텍스트 기반 유사 검색 + try: + # 검색 쿼리를 임베딩으로 변환 + query_embedding = self.embedding_model.encode(context) + query_embedding = query_embedding.tolist() + + # 유사한 문서 검색 (상위 5개) + results = self.collection.query( + query_embeddings=[query_embedding], + n_results=5, + include=['documents', 'metadatas'] + ) + + if not results or not results.get('documents') or not results['documents'][0]: + logger.info("유사 케이스를 찾을 수 없음") + return None + + # 컨텍스트 조합 + context_parts = [] + documents = results['documents'][0] + metadatas = results.get('metadatas', [[]])[0] + + for i, doc in enumerate(documents): + metadata = metadatas[i] if i < len(metadatas) else {} + + # 가게 정보 추가 + store_name = metadata.get('store_name', 'Unknown') + food_category = metadata.get('food_category', 'Unknown') + + context_parts.append(f"[{food_category} - {store_name}]") + context_parts.append(doc[:500] + "..." if len(doc) > 500 else doc) + context_parts.append("---") + + return "\n".join(context_parts) + + except Exception as search_error: + logger.warning(f"벡터 검색 실패: {search_error}") + return None + + except Exception as e: + logger.error(f"유사 케이스 검색 실패: {e}") + return None diff --git a/vector/app/utils/category_utils.py b/vector/app/utils/category_utils.py new file mode 100644 index 0000000..9abcaa0 --- /dev/null +++ b/vector/app/utils/category_utils.py @@ -0,0 +1,161 @@ +# app/utils/category_utils.py (수정된 버전) +import re +from typing import Optional + +def extract_food_category(category_name: str) -> str: + """ + 카테고리명에서 음식 종류를 추출합니다. + '음식점 > 한식 > 육류,고기'에서 '한식'을 추출 + + Args: + category_name: 전체 카테고리명 + + Returns: + 추출된 음식 종류 + """ + if not category_name: + return "" + + # '>' 기준으로 분할하고 마지막 바로 전 요소 반환 + parts = category_name.split('>') + if len(parts) >= 2: + food_category = parts[-2].strip() # 마지막 바로 전 값 사용 + return food_category + elif len(parts) == 1: + return parts[0].strip() # 하나밖에 없으면 그것을 반환 + + return category_name.strip() + +def normalize_category(category: str) -> str: + """ + 카테고리를 정규화합니다. + + Args: + category: 원본 카테고리 + + Returns: + 정규화된 카테고리 + """ + if not category: + return "" + + # 공백 제거 및 소문자 변환 + normalized = category.strip().lower() + + # 특수문자 제거 (콤마, 슬래시 등은 유지) + normalized = re.sub(r'[^\w가-힣,/\s]', '', normalized) + + return normalized + +def is_similar_category(category1: str, category2: str) -> bool: + """ + 두 카테고리가 유사한지 판단합니다. + + Args: + category1: 첫 번째 카테고리 + category2: 두 번째 카테고리 + + Returns: + 유사 여부 + """ + if not category1 or not category2: + return False + + # 정규화 + norm1 = normalize_category(category1) + norm2 = normalize_category(category2) + + # 완전 일치 + if norm1 == norm2: + return True + + # 키워드 기반 유사성 검사 + keywords1 = set(norm1.replace(',', ' ').replace('/', ' ').split()) + keywords2 = set(norm2.replace(',', ' ').replace('/', ' ').split()) + + # 교집합이 하나 이상 있으면 유사한 것으로 판단 + common_keywords = keywords1.intersection(keywords2) + return len(common_keywords) > 0 + +def extract_main_category(category_name: str) -> str: + """ + 메인 카테고리를 추출합니다. (음식점 > 한식 에서 '한식' 추출) + + Args: + category_name: 전체 카테고리명 + + Returns: + 메인 카테고리 + """ + if not category_name: + return "" + + parts = category_name.split('>') + if len(parts) >= 2: + return parts[1].strip() + elif len(parts) == 1: + return parts[0].strip() + + return "" + +def build_search_query(region: str, food_category: str) -> str: + """ + 검색 쿼리를 구성합니다. (수정된 버전 - 지역 정보 제외) + + Args: + region: 지역 (사용하지 않음) + food_category: 음식 카테고리 + + Returns: + 검색 쿼리 문자열 (음식 카테고리만 포함) + """ + # 콤마와 슬래시를 공백으로 변경하여 검색 키워드 생성 + search_keywords = food_category.replace(',', ' ').replace('/', ' ') + + # 불필요한 단어 제거 + stop_words = ['음식점', '요리', '전문점', '맛집'] + keywords = [] + + for keyword in search_keywords.split(): + keyword = keyword.strip() + if keyword and keyword not in stop_words: + keywords.append(keyword) + + # 키워드가 없으면 기본 검색어 사용 + if not keywords: + keywords = ['음식점'] + + # 🔧 지역 정보는 포함하지 않고 음식 키워드만 반환 + query = ' '.join(keywords) + return query.strip() + +def clean_food_category_for_search(food_category: str) -> str: + """ + 음식 카테고리를 검색용 키워드로 정리합니다. + + Args: + food_category: 원본 음식 카테고리 + + Returns: + 정리된 검색 키워드 + """ + if not food_category: + return "음식점" + + # 콤마와 슬래시를 공백으로 변경 + cleaned = food_category.replace(',', ' ').replace('/', ' ') + + # 불필요한 단어 제거 + stop_words = ['음식점', '요리', '전문점', '맛집'] + keywords = [] + + for keyword in cleaned.split(): + keyword = keyword.strip() + if keyword and keyword not in stop_words: + keywords.append(keyword) + + # 키워드가 없으면 기본 검색어 사용 + if not keywords: + return "음식점" + + return ' '.join(keywords) diff --git a/vector/app/utils/data_utils.py b/vector/app/utils/data_utils.py new file mode 100644 index 0000000..687f446 --- /dev/null +++ b/vector/app/utils/data_utils.py @@ -0,0 +1,194 @@ +# app/utils/data_utils.py +import json +import hashlib +from datetime import datetime +from typing import Dict, List, Any, Optional + +def create_store_hash(store_id: str, store_name: str, region: str) -> str: + """ + 가게의 고유 해시를 생성합니다. + + Args: + store_id: 가게 ID + store_name: 가게명 + region: 지역 + + Returns: + 생성된 해시값 + """ + combined = f"{store_id}_{store_name}_{region}" + return hashlib.md5(combined.encode('utf-8')).hexdigest() + +def combine_store_and_reviews(store_info: Dict[str, Any], reviews: List[Dict[str, Any]]) -> str: + """ + 가게 정보와 리뷰를 결합하여 JSON 문자열을 생성합니다. + + Args: + store_info: 가게 정보 + reviews: 리뷰 목록 + + Returns: + 결합된 JSON 문자열 + """ + combined_data = { + "store_info": store_info, + "reviews": reviews, + "review_summary": generate_review_summary(reviews), + "combined_at": datetime.now().isoformat() + } + + return json.dumps(combined_data, ensure_ascii=False, separators=(',', ':')) + +def generate_review_summary(reviews: List[Dict[str, Any]]) -> Dict[str, Any]: + """ + 리뷰 목록에서 요약 정보를 생성합니다. + + Args: + reviews: 리뷰 목록 + + Returns: + 리뷰 요약 정보 + """ + if not reviews: + return { + "total_reviews": 0, + "average_rating": 0.0, + "rating_distribution": {}, + "common_keywords": [], + "sentiment_summary": { + "positive": 0, + "neutral": 0, + "negative": 0 + } + } + + # 기본 통계 + total_reviews = len(reviews) + ratings = [review.get('rating', 0) for review in reviews if review.get('rating', 0) > 0] + average_rating = sum(ratings) / len(ratings) if ratings else 0.0 + + # 별점 분포 + rating_distribution = {} + for rating in ratings: + rating_distribution[str(rating)] = rating_distribution.get(str(rating), 0) + 1 + + # 키워드 추출 (badges 기반) + keyword_counts = {} + for review in reviews: + badges = review.get('badges', []) + for badge in badges: + keyword_counts[badge] = keyword_counts.get(badge, 0) + 1 + + # 상위 키워드 추출 + common_keywords = sorted(keyword_counts.items(), key=lambda x: x[1], reverse=True)[:10] + common_keywords = [keyword for keyword, count in common_keywords] + + # 감정 분석 (간단한 별점 기반) + sentiment_summary = { + "positive": len([r for r in ratings if r >= 4]), + "neutral": len([r for r in ratings if r == 3]), + "negative": len([r for r in ratings if r <= 2]) + } + + return { + "total_reviews": total_reviews, + "average_rating": round(average_rating, 2), + "rating_distribution": rating_distribution, + "common_keywords": common_keywords, + "sentiment_summary": sentiment_summary, + "has_recent_reviews": any( + review.get('date', '') >= datetime.now().strftime('%Y.%m.%d') + for review in reviews[-10:] # 최근 10개 리뷰 확인 + ) + } + +def extract_text_for_embedding(store_info: Dict[str, Any], reviews: List[Dict[str, Any]]) -> str: + """ + 임베딩을 위한 텍스트를 추출합니다. + + Args: + store_info: 가게 정보 + reviews: 리뷰 목록 + + Returns: + 임베딩용 텍스트 + """ + # 가게 기본 정보 + store_text = f"가게명: {store_info.get('place_name', '')}\n" + store_text += f"카테고리: {store_info.get('category_name', '')}\n" + store_text += f"주소: {store_info.get('address_name', '')}\n" + + # 리뷰 내용 요약 + review_contents = [] + review_keywords = [] + + for review in reviews[:20]: # 최근 20개 리뷰만 사용 + content = review.get('content', '').strip() + if content: + review_contents.append(content) + + badges = review.get('badges', []) + review_keywords.extend(badges) + + # 리뷰 텍스트 조합 + if review_contents: + store_text += f"리뷰 내용: {' '.join(review_contents[:10])}\n" # 최대 10개 리뷰 + + # 키워드 조합 + if review_keywords: + unique_keywords = list(set(review_keywords)) + store_text += f"키워드: {', '.join(unique_keywords[:15])}\n" # 최대 15개 키워드 + + return store_text.strip() + +def create_metadata(store_info: Dict[str, Any], food_category: str, region: str) -> Dict[str, Any]: + """ + Vector DB용 메타데이터를 생성합니다. + + Args: + store_info: 가게 정보 + food_category: 음식 카테고리 + region: 지역 + + Returns: + 메타데이터 딕셔너리 + """ + return { + "store_id": store_info.get('id', ''), + "store_name": store_info.get('place_name', ''), + "food_category": food_category, + "region": region, + "category_name": store_info.get('category_name', ''), + "address": store_info.get('address_name', ''), + "phone": store_info.get('phone', ''), + "place_url": store_info.get('place_url', ''), + "x": store_info.get('x', ''), # 좌표를 개별 키로 분리 + "y": store_info.get('y', ''), # 좌표를 개별 키로 분리 + "last_updated": datetime.now().isoformat() + } + +def is_duplicate_store(metadata1: Dict[str, Any], metadata2: Dict[str, Any]) -> bool: + """ + 두 가게가 중복인지 확인합니다. + + Args: + metadata1: 첫 번째 가게 메타데이터 + metadata2: 두 번째 가게 메타데이터 + + Returns: + 중복 여부 + """ + # Store ID 기준 확인 + if metadata1.get('store_id') and metadata2.get('store_id'): + return metadata1['store_id'] == metadata2['store_id'] + + # 가게명 + 주소 기준 확인 + name1 = metadata1.get('store_name', '').strip() + name2 = metadata2.get('store_name', '').strip() + addr1 = metadata1.get('address', '').strip() + addr2 = metadata2.get('address', '').strip() + + if name1 and name2 and addr1 and addr2: + return name1 == name2 and addr1 == addr2 + + return False diff --git a/vector/build-base.sh b/vector/build-base.sh new file mode 100755 index 0000000..9a83655 --- /dev/null +++ b/vector/build-base.sh @@ -0,0 +1,282 @@ +#!/bin/bash +# build-base.sh - Poetry 기반 Vector DB API Base Image 빌드 스크립트 + +set -e + +# 변수 설정 +BASE_IMAGE_NAME="vector-api-base" +BASE_IMAGE_TAG="${1:-latest}" +ACR_NAME="${2:-acrdigitalgarage03}" +RESOURCE_GROUP="${3:-rg-digitalgarage-03}" + +# ACR URL 자동 구성 +if [ -n "${ACR_NAME}" ]; then + REGISTRY="${ACR_NAME}.azurecr.io" + FULL_BASE_IMAGE_NAME="${REGISTRY}/${BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}" +else + FULL_BASE_IMAGE_NAME="${BASE_IMAGE_NAME}:${BASE_IMAGE_TAG}" +fi + +# 고정된 파일 경로 +BASE_DOCKERFILE_PATH="deployment/container/Dockerfile-base" +BUILD_CONTEXT="." + +# 색상 설정 +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +BLUE='\033[0;34m' +CYAN='\033[0;36m' +NC='\033[0m' + +log_info() { echo -e "${CYAN}ℹ️ $1${NC}"; } +log_success() { echo -e "${GREEN}✅ $1${NC}"; } +log_warning() { echo -e "${YELLOW}⚠️ $1${NC}"; } +log_error() { echo -e "${RED}❌ $1${NC}"; } + +echo "========================================================" +echo "🚀 Poetry 기반 Vector DB API Base Image 빌드" +echo "========================================================" +echo "Base 이미지명: ${FULL_BASE_IMAGE_NAME}" +if [ -n "${ACR_NAME}" ]; then + echo "ACR 이름: ${ACR_NAME}" + echo "리소스 그룹: ${RESOURCE_GROUP}" +fi +echo "빌드 시작: $(date)" +echo "" +echo "📦 포함될 구성요소:" +echo " ✅ Python 3.11 + Poetry" +echo " ✅ 모든 AI/ML 의존성 (NumPy, PyTorch, Transformers)" +echo " ✅ Vector DB (ChromaDB, Chroma)" +echo " ✅ 웹 프레임워크 (FastAPI, Uvicorn)" +echo " ✅ Claude API (Anthropic)" +echo "" + +# 시작 시간 기록 +BUILD_START=$(date +%s) + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [BASE_IMAGE_TAG] [ACR_NAME] [RESOURCE_GROUP]" + echo "" + echo "파라미터:" + echo " BASE_IMAGE_TAG: Base 이미지 태그 (기본값: latest)" + echo " ACR_NAME : Azure Container Registry 이름" + echo " RESOURCE_GROUP: Azure 리소스 그룹" + echo "" + echo "예시:" + echo " $0 v2.0.0 # 로컬 빌드만" + echo " $0 v2.0.0 acrdigitalgarage01 rg-digitalgarage-03 # ACR 빌드 + 푸시" + echo "" + echo "💡 참고:" + echo " - Base Image는 한 번만 빌드하면 재사용 가능" + echo " - 모든 Python 의존성이 포함되어 Service Image 빌드 시간 단축" + echo " - Poetry 환경으로 패키지 관리" +} + +# ACR 로그인 함수 +acr_login() { + local acr_name="$1" + local resource_group="$2" + + log_info "Azure Container Registry 로그인 중..." + + if ! command -v az &> /dev/null; then + log_error "Azure CLI (az)가 설치되지 않았습니다." + exit 1 + fi + + if ! command -v jq &> /dev/null; then + log_error "jq가 설치되지 않았습니다." + exit 1 + fi + + if ! az account show &> /dev/null; then + log_error "Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 + fi + + local credential_json + credential_json=$(az acr credential show --name "${acr_name}" --resource-group "${resource_group}" 2>/dev/null) + + if [ $? -ne 0 ]; then + log_error "ACR credential 조회 실패" + exit 1 + fi + + local username + local password + + username=$(echo "${credential_json}" | jq -r '.username') + password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + + if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + log_error "ACR credential 파싱 실패" + exit 1 + fi + + echo "${password}" | docker login "${REGISTRY}" -u "${username}" --password-stdin + + if [ $? -eq 0 ]; then + log_success "ACR 로그인 성공!" + return 0 + else + log_error "ACR 로그인 실패" + exit 1 + fi +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -n "${ACR_NAME}" ] && [ -z "${RESOURCE_GROUP}" ]; then + log_error "ACR_NAME이 제공된 경우 RESOURCE_GROUP도 필요합니다." + echo "" + show_usage + exit 1 +fi + +# 필수 파일 확인 +log_info "필수 파일 확인 중..." + +if [ ! -f "${BASE_DOCKERFILE_PATH}" ]; then + log_error "${BASE_DOCKERFILE_PATH} 파일을 찾을 수 없습니다." + exit 1 +fi + +if [ ! -f "setup.sh" ]; then + log_error "setup.sh 파일을 찾을 수 없습니다." + log_error "Poetry 설치 스크립트(setup_poetry_vector.sh)를 setup.sh로 저장해주세요." + exit 1 +fi + +log_success "모든 필수 파일 확인 완료" +echo "📄 Base Dockerfile: ${BASE_DOCKERFILE_PATH}" +echo "📄 Poetry 설치 스크립트: setup.sh" + +# setup.sh 실행 가능 확인 +if [ ! -x "setup.sh" ]; then + log_warning "setup.sh 파일에 실행 권한이 없습니다. 실행 권한 추가 중..." + chmod +x setup.sh + log_success "실행 권한 추가 완료" +fi + +# 시스템 정보 확인 +log_info "시스템 정보 확인..." +echo " - OS: $(lsb_release -d 2>/dev/null | cut -f2 || echo 'Unknown')" +echo " - CPU Cores: $(nproc)" +echo " - Available Memory: $(free -h | awk '/^Mem:/ {print $7}' 2>/dev/null || echo 'Unknown')" +echo " - Docker Version: $(docker --version)" +echo " - Build Context: ${BUILD_CONTEXT}" + +# ACR 로그인 수행 +if [ -n "${ACR_NAME}" ] && [ -n "${RESOURCE_GROUP}" ]; then + echo "" + acr_login "${ACR_NAME}" "${RESOURCE_GROUP}" + echo "" +fi + +# Docker 빌드 +log_info "Poetry 기반 Base Image 빌드 시작..." +echo " - 예상 빌드 시간: 15-25분 (Poetry 의존성 해결 포함)" +echo " - 모든 Python 패키지가 Poetry로 설치됨" +echo " - 멀티스테이지 빌드로 크기 최적화" +echo "" +echo "🔨 빌드 명령어:" +echo "docker build -t \"${FULL_BASE_IMAGE_NAME}\" -f \"${BASE_DOCKERFILE_PATH}\" \"${BUILD_CONTEXT}\"" +echo "" + +docker build -t "${FULL_BASE_IMAGE_NAME}" -f "${BASE_DOCKERFILE_PATH}" "${BUILD_CONTEXT}" + +if [ $? -eq 0 ]; then + # 빌드 종료 시간 계산 + BUILD_END=$(date +%s) + BUILD_TIME=$((BUILD_END - BUILD_START)) + BUILD_MINUTES=$((BUILD_TIME / 60)) + BUILD_SECONDS=$((BUILD_TIME % 60)) + + log_success "Poetry 기반 Base Image 빌드 완료!" + echo "" + echo "⏱️ 총 빌드 시간: ${BUILD_MINUTES}분 ${BUILD_SECONDS}초" + + # 이미지 정보 표시 + echo "" + log_info "Base Image 정보:" + docker images "${FULL_BASE_IMAGE_NAME}" --format "table {{.Repository}}\t{{.Tag}}\t{{.Size}}\t{{.CreatedAt}}" + + # latest 태그 추가 생성 + if [ "${BASE_IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo "" + log_info "latest 태그 생성 중..." + docker tag "${FULL_BASE_IMAGE_NAME}" "${REGISTRY}/${BASE_IMAGE_NAME}:latest" + log_success "latest 태그 생성 완료: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + fi + + # ACR 푸시 + if [ -n "${ACR_NAME}" ]; then + echo "" + log_info "ACR에 Base Image 푸시 중..." + + echo "📤 푸시 중: ${FULL_BASE_IMAGE_NAME}" + docker push "${FULL_BASE_IMAGE_NAME}" + + if [ $? -eq 0 ]; then + log_success "Base Image 푸시 성공" + + if [ "${BASE_IMAGE_TAG}" != "latest" ]; then + echo "📤 푸시 중: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + docker push "${REGISTRY}/${BASE_IMAGE_NAME}:latest" + + if [ $? -eq 0 ]; then + log_success "latest 태그 푸시 성공" + fi + fi + else + log_error "Base Image 푸시 실패" + exit 1 + fi + fi + + echo "" + log_success "🎉 Poetry 기반 Base Image 빌드 완료!" + echo "" + echo "📋 완료된 작업:" + echo " ✅ Base Image 빌드: ${FULL_BASE_IMAGE_NAME}" + if [ "${BASE_IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo " ✅ latest 태그: ${REGISTRY}/${BASE_IMAGE_NAME}:latest" + fi + if [ -n "${ACR_NAME}" ]; then + echo " ✅ ACR 푸시 완료" + fi + echo " ✅ Poetry 환경 구성 완료" + echo " ✅ 모든 AI/ML 의존성 설치 완료" + + echo "" + echo "📝 다음 단계:" + echo " 이제 Service Image를 빌드하세요:" + if [ -n "${ACR_NAME}" ]; then + echo " ./build.sh v1.0.0 ${ACR_NAME} ${RESOURCE_GROUP}" + else + echo " ./build.sh v1.0.0" + fi + + echo "" + echo "💡 최적화 포인트:" + echo " ✅ Base Image: 한 번만 빌드 (주기적 업데이트)" + echo " ✅ Service Image: 매번 빠른 빌드 (앱 코드만)" + echo " ✅ Poetry 환경: 의존성 충돌 자동 해결" + echo " ✅ 개발 생산성: 빌드 대기시간 95% 단축" + +else + log_error "Base Image 빌드 실패!" + exit 1 +fi + +echo "" +echo "🏁 Base Image 빌드 프로세스 완료 - $(date)" + diff --git a/vector/build.sh b/vector/build.sh new file mode 100755 index 0000000..da51485 --- /dev/null +++ b/vector/build.sh @@ -0,0 +1,337 @@ +#!/bin/bash +# build.sh - Poetry 기반 Vector DB API Service Image 빌드 스크립트 + +set -e + +# 변수 설정 +IMAGE_NAME="vector-api" +IMAGE_TAG="${1:-latest}" +ACR_NAME="${2:-acrdigitalgarage03}" +RESOURCE_GROUP="${3:-rg-digitalgarage-03}" +BASE_IMAGE_TAG="${4:-latest}" + +# ACR URL 자동 구성 +if [ -n "${ACR_NAME}" ]; then + REGISTRY="${ACR_NAME}.azurecr.io" + FULL_IMAGE_NAME="${REGISTRY}/${IMAGE_NAME}:${IMAGE_TAG}" + BASE_IMAGE="${REGISTRY}/vector-api-base:${BASE_IMAGE_TAG}" +else + FULL_IMAGE_NAME="${IMAGE_NAME}:${IMAGE_TAG}" + BASE_IMAGE="vector-api-base:${BASE_IMAGE_TAG}" +fi + +# 고정된 파일 경로 +DOCKERFILE_PATH="deployment/container/Dockerfile" +BUILD_CONTEXT="." + +# 색상 설정 +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +BLUE='\033[0;34m' +CYAN='\033[0;36m' +NC='\033[0m' + +log_info() { echo -e "${CYAN}ℹ️ $1${NC}"; } +log_success() { echo -e "${GREEN}✅ $1${NC}"; } +log_warning() { echo -e "${YELLOW}⚠️ $1${NC}"; } +log_error() { echo -e "${RED}❌ $1${NC}"; } + +echo "========================================================" +echo "🚀 Poetry 기반 Vector DB API Service Image 빌드" +echo "========================================================" +echo "Service 이미지명: ${FULL_IMAGE_NAME}" +echo "Base 이미지: ${BASE_IMAGE}" +if [ -n "${ACR_NAME}" ]; then + echo "ACR 이름: ${ACR_NAME}" + echo "리소스 그룹: ${RESOURCE_GROUP}" +fi +echo "빌드 시작: $(date)" +echo "" + +# 시작 시간 기록 +BUILD_START=$(date +%s) + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [IMAGE_TAG] [ACR_NAME] [RESOURCE_GROUP] [BASE_IMAGE_TAG]" + echo "" + echo "파라미터:" + echo " IMAGE_TAG : Service 이미지 태그 (기본값: latest)" + echo " ACR_NAME : Azure Container Registry 이름" + echo " RESOURCE_GROUP: Azure 리소스 그룹" + echo " BASE_IMAGE_TAG: Base 이미지 태그 (기본값: latest)" + echo "" + echo "예시:" + echo " $0 v1.0.0 # 로컬 빌드만" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 # ACR 빌드 + 푸시" + echo " $0 v1.0.0 acrdigitalgarage01 rg-digitalgarage-03 v2.0.0 # 특정 Base Image 사용" + echo "" + echo "전제조건:" + echo " Poetry 기반 Base Image가 먼저 빌드되어 있어야 합니다:" + echo " ./build-base.sh ${BASE_IMAGE_TAG} [ACR_NAME] [RESOURCE_GROUP]" + echo "" + echo "💡 장점:" + echo " - 빠른 빌드: 앱 코드만 복사 (30초~2분)" + echo " - Poetry 환경: 의존성 관리 최적화" + echo " - 캐시 활용: Base Image 재사용으로 효율성 극대화" +} + +# ACR 로그인 함수 +acr_login() { + local acr_name="$1" + local resource_group="$2" + + log_info "Azure Container Registry 로그인 중..." + + if ! command -v az &> /dev/null; then + log_error "Azure CLI (az)가 설치되지 않았습니다." + exit 1 + fi + + if ! command -v jq &> /dev/null; then + log_error "jq가 설치되지 않았습니다." + exit 1 + fi + + if ! az account show &> /dev/null; then + log_error "Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 + fi + + local credential_json + credential_json=$(az acr credential show --name "${acr_name}" --resource-group "${resource_group}" 2>/dev/null) + + if [ $? -ne 0 ]; then + log_error "ACR credential 조회 실패" + exit 1 + fi + + local username + local password + + username=$(echo "${credential_json}" | jq -r '.username') + password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + + if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + log_error "ACR credential 파싱 실패" + exit 1 + fi + + echo "${password}" | docker login "${REGISTRY}" -u "${username}" --password-stdin + + if [ $? -eq 0 ]; then + log_success "ACR 로그인 성공!" + return 0 + else + log_error "ACR 로그인 실패" + exit 1 + fi +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -n "${ACR_NAME}" ] && [ -z "${RESOURCE_GROUP}" ]; then + log_error "ACR_NAME이 제공된 경우 RESOURCE_GROUP도 필요합니다." + echo "" + show_usage + exit 1 +fi + +# 필수 파일 확인 +log_info "필수 파일 확인 중..." + +if [ ! -f "app/main.py" ]; then + log_error "app/main.py 파일을 찾을 수 없습니다." + exit 1 +fi + +if [ ! -f "${DOCKERFILE_PATH}" ]; then + log_error "${DOCKERFILE_PATH} 파일을 찾을 수 없습니다." + exit 1 +fi + +log_success "모든 필수 파일이 확인되었습니다." +echo "📄 Service Dockerfile: ${DOCKERFILE_PATH}" +echo "📄 메인 애플리케이션: app/main.py" +echo "🏗️ 빌드 컨텍스트: ${BUILD_CONTEXT}" + +# Base Image 존재 확인 +echo "" +log_info "Poetry 기반 Base Image 확인 중..." +if docker image inspect "${BASE_IMAGE}" >/dev/null 2>&1; then + log_success "Base Image 확인됨: ${BASE_IMAGE}" + + # Base Image에서 Poetry 환경 확인 + log_info "Base Image Poetry 환경 검증 중..." + if docker run --rm "${BASE_IMAGE}" poetry --version >/dev/null 2>&1; then + POETRY_VERSION=$(docker run --rm "${BASE_IMAGE}" poetry --version 2>/dev/null) + log_success "Poetry 환경 확인됨: ${POETRY_VERSION}" + else + log_warning "Base Image에서 Poetry를 찾을 수 없습니다" + fi + + # Base Image 크기 확인 + BASE_SIZE=$(docker images "${BASE_IMAGE}" --format "{{.Size}}") + echo "📊 Base Image 크기: ${BASE_SIZE}" + +else + log_error "Base Image를 찾을 수 없습니다: ${BASE_IMAGE}" + echo "" + echo "📋 해결 방법:" + echo " Base Image를 먼저 빌드하세요:" + if [ -n "${ACR_NAME}" ]; then + echo " ./build-base.sh ${BASE_IMAGE_TAG} ${ACR_NAME} ${RESOURCE_GROUP}" + else + echo " ./build-base.sh ${BASE_IMAGE_TAG}" + fi + echo "" + echo " 또는 ACR에서 Base Image를 풀하세요:" + if [ -n "${ACR_NAME}" ]; then + echo " docker pull ${BASE_IMAGE}" + fi + exit 1 +fi + +# ACR 로그인 수행 +if [ -n "${ACR_NAME}" ] && [ -n "${RESOURCE_GROUP}" ]; then + echo "" + acr_login "${ACR_NAME}" "${RESOURCE_GROUP}" + echo "" +fi + +# Docker 빌드 +log_info "Poetry 기반 Service Image 빌드 시작..." +echo " - 예상 빌드 시간: 30초~2분 (앱 코드만 복사)" +echo " - Base Image 재사용으로 빠른 빌드" +echo " - Poetry 환경 상속" +echo "" +echo "🔨 빌드 명령어:" +echo "docker build --build-arg BASE_IMAGE=\"${BASE_IMAGE}\" -t \"${FULL_IMAGE_NAME}\" -f \"${DOCKERFILE_PATH}\" \"${BUILD_CONTEXT}\"" +echo "" + +docker build --build-arg BASE_IMAGE="${BASE_IMAGE}" -t "${FULL_IMAGE_NAME}" -f "${DOCKERFILE_PATH}" "${BUILD_CONTEXT}" + +if [ $? -eq 0 ]; then + # 빌드 종료 시간 계산 + BUILD_END=$(date +%s) + BUILD_TIME=$((BUILD_END - BUILD_START)) + BUILD_MINUTES=$((BUILD_TIME / 60)) + BUILD_SECONDS=$((BUILD_TIME % 60)) + + log_success "Service Image 빌드 완료!" + echo "" + echo "⏱️ 총 빌드 시간: ${BUILD_MINUTES}분 ${BUILD_SECONDS}초" + + # 이미지 정보 표시 + echo "" + log_info "Service Image 정보:" + docker images "${FULL_IMAGE_NAME}" --format "table {{.Repository}}\t{{.Tag}}\t{{.Size}}\t{{.CreatedAt}}" + + # 🧪 빌드된 이미지 검증 + log_info "Service Image 검증 중..." + echo "🔍 Poetry 환경 및 앱 코드 확인:" + + docker run --rm "${FULL_IMAGE_NAME}" sh -c " + echo '✅ Poetry 버전:' && poetry --version && + echo '✅ Python 버전:' && poetry run python --version && + echo '✅ 설치된 패키지 수:' && poetry show | wc -l && + echo '✅ 앱 코드 확인:' && ls -la /app/app/ 2>/dev/null | head -5 + " 2>/dev/null || log_warning "일부 검증에 실패했습니다." + + # latest 태그 추가 생성 + if [ "${IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo "" + log_info "latest 태그 생성 중..." + docker tag "${FULL_IMAGE_NAME}" "${REGISTRY}/${IMAGE_NAME}:latest" + log_success "latest 태그 생성 완료: ${REGISTRY}/${IMAGE_NAME}:latest" + fi + + # ACR 푸시 + if [ -n "${ACR_NAME}" ]; then + echo "" + log_info "ACR에 Service Image 푸시 중..." + + echo "📤 푸시 중: ${FULL_IMAGE_NAME}" + docker push "${FULL_IMAGE_NAME}" + + if [ $? -eq 0 ]; then + log_success "Service Image 푸시 성공" + + if [ "${IMAGE_TAG}" != "latest" ]; then + echo "📤 푸시 중: ${REGISTRY}/${IMAGE_NAME}:latest" + docker push "${REGISTRY}/${IMAGE_NAME}:latest" + + if [ $? -eq 0 ]; then + log_success "latest 태그 푸시 성공" + fi + fi + else + log_error "Service Image 푸시 실패" + exit 1 + fi + fi + + echo "" + log_success "🎉 Poetry 기반 Service Image 빌드 완료!" + echo "" + echo "📋 완료된 작업:" + echo " ✅ Service Image 빌드: ${FULL_IMAGE_NAME}" + echo " ✅ Base Image 활용: ${BASE_IMAGE}" + if [ "${IMAGE_TAG}" != "latest" ] && [ -n "${REGISTRY}" ]; then + echo " ✅ latest 태그: ${REGISTRY}/${IMAGE_NAME}:latest" + fi + if [ -n "${ACR_NAME}" ]; then + echo " ✅ ACR 푸시 완료" + fi + echo " ✅ Poetry 환경 상속" + + echo "" + echo "🧪 테스트 명령어:" + echo " # 로컬 실행 테스트" + echo " docker run --rm -p 8000:8000 ${FULL_IMAGE_NAME}" + echo "" + echo " # Poetry 환경 확인" + echo " docker run --rm ${FULL_IMAGE_NAME} poetry show" + echo "" + echo " # 앱 헬스체크" + echo " docker run --rm ${FULL_IMAGE_NAME} poetry run python -c \"import app.main; print('✅ 앱 로드 성공')\"" + + echo "" + echo "📝 다음 단계:" + echo " 1. 로컬 테스트:" + echo " docker run --rm -p 8000:8000 ${FULL_IMAGE_NAME}" + echo "" + echo " 2. Kubernetes 배포:" + echo " kubectl apply -f deployment/manifests/" + echo "" + echo " 3. 스케일링:" + echo " kubectl scale deployment vector-api --replicas=3" + + echo "" + echo "💡 성능 최적화:" + echo " ✅ 빠른 빌드: Base Image 재사용으로 빌드 시간 95% 단축" + echo " ✅ 효율적 캐시: Poetry 환경은 Base Image에서 관리" + echo " ✅ 작은 이미지: 앱 코드만 포함하여 배포 이미지 최소화" + echo " ✅ 개발 친화적: Poetry로 일관된 의존성 관리" + +else + log_error "Service Image 빌드 실패!" + echo "" + echo "🔍 문제 해결:" + echo " 1. Base Image 확인: docker images | grep vector-api-base" + echo " 2. Dockerfile 확인: cat ${DOCKERFILE_PATH}" + echo " 3. 앱 코드 확인: ls -la app/" + echo " 4. 빌드 로그 확인: 위의 에러 메시지 참조" + exit 1 +fi + +echo "" +echo "🏁 Service Image 빌드 프로세스 완료 - $(date)" + diff --git a/vector/create-imagepullsecret.sh b/vector/create-imagepullsecret.sh new file mode 100755 index 0000000..441417d --- /dev/null +++ b/vector/create-imagepullsecret.sh @@ -0,0 +1,236 @@ +#!/bin/bash +# create-imagepullsecret.sh - ACR Image Pull Secret 생성 스크립트 + +set -e + +# 변수 설정 +ACR_NAME="${1:-acrdigitalgarage03}" +RESOURCE_GROUP="${2:-rg-digitalgarage-03}" +SECRET_NAME="${3:-acr-secret}" + +echo "=====================================================" +echo " ACR Image Pull Secret 생성 (Vector API)" +echo "=====================================================" + +# 사용법 표시 함수 +show_usage() { + echo "사용법:" + echo " $0 [ACR_NAME] [RESOURCE_GROUP] [SECRET_NAME]" + echo "" + echo "파라미터:" + echo " ACR_NAME : Azure Container Registry 이름 (필수)" + echo " RESOURCE_GROUP: Azure 리소스 그룹 (필수)" + echo " SECRET_NAME : Secret 이름 (기본값: acr-secret)" + echo "" + echo "예시:" + echo " $0 acrdigitalgarage01 rg-digitalgarage-03" + echo " $0 acrdigitalgarage01 rg-digitalgarage-03 acr-prod-secret" + echo "" +} + +# 파라미터 검증 +if [ "$1" == "--help" ] || [ "$1" == "-h" ]; then + show_usage + exit 0 +fi + +if [ -z "${ACR_NAME}" ] || [ -z "${RESOURCE_GROUP}" ]; then + echo "❌ ACR_NAME과 RESOURCE_GROUP는 필수 파라미터입니다." + echo "" + show_usage + exit 1 +fi + +# 필수 도구 확인 +echo "🔧 필수 도구 확인 중..." + +if ! command -v az &> /dev/null; then + echo "❌ Azure CLI (az)가 설치되지 않았습니다." + echo "설치 방법: https://docs.microsoft.com/en-us/cli/azure/install-azure-cli" + exit 1 +fi + +if ! command -v kubectl &> /dev/null; then + echo "❌ kubectl이 설치되지 않았습니다." + echo "설치 방법: https://kubernetes.io/docs/tasks/tools/" + exit 1 +fi + +if ! command -v jq &> /dev/null; then + echo "❌ jq가 설치되지 않았습니다." + echo "설치 방법: sudo apt-get install jq" + exit 1 +fi + +echo "✅ 필수 도구 확인 완료" + +# Azure 로그인 확인 +echo "" +echo "🔐 Azure 로그인 상태 확인 중..." + +if ! az account show &> /dev/null; then + echo "❌ Azure에 로그인되지 않았습니다." + echo "로그인 명령: az login" + exit 1 +fi + +CURRENT_SUBSCRIPTION=$(az account show --query name -o tsv) +echo "✅ Azure 로그인 확인됨" +echo " 현재 구독: ${CURRENT_SUBSCRIPTION}" + +# Kubernetes 클러스터 연결 확인 +echo "" +echo "☸️ Kubernetes 클러스터 연결 확인 중..." + +if ! kubectl cluster-info &> /dev/null; then + echo "❌ Kubernetes 클러스터에 연결되지 않았습니다." + echo "클러스터 연결 방법:" + echo " az aks get-credentials --resource-group ${RESOURCE_GROUP} --name " + exit 1 +fi + +CURRENT_CONTEXT=$(kubectl config current-context) +echo "✅ Kubernetes 클러스터 연결 확인됨" +echo " 현재 컨텍스트: ${CURRENT_CONTEXT}" + +# ACR 정보 설정 +REGISTRY_URL="${ACR_NAME}.azurecr.io" + +echo "" +echo "📋 설정 정보:" +echo " ACR 이름: ${ACR_NAME}" +echo " 레지스트리 URL: ${REGISTRY_URL}" +echo " 리소스 그룹: ${RESOURCE_GROUP}" +echo " Secret 이름: ${SECRET_NAME}" + +# ACR 존재 확인 +echo "" +echo "🏪 ACR 존재 확인 중..." + +if ! az acr show --name "${ACR_NAME}" --resource-group "${RESOURCE_GROUP}" &> /dev/null; then + echo "❌ ACR을 찾을 수 없습니다." + echo "확인 사항:" + echo " - ACR 이름: ${ACR_NAME}" + echo " - 리소스 그룹: ${RESOURCE_GROUP}" + echo " - ACR이 해당 리소스 그룹에 존재하는지 확인" + exit 1 +fi + +echo "✅ ACR 존재 확인됨: ${ACR_NAME}" + +# ACR credential 조회 +echo "" +echo "🔑 ACR credential 조회 중..." + +credential_json=$(az acr credential show --name "${ACR_NAME}" --resource-group "${RESOURCE_GROUP}" 2>/dev/null) + +if [ $? -ne 0 ]; then + echo "❌ ACR credential 조회 실패" + echo "확인 사항:" + echo " - ACR 이름: ${ACR_NAME}" + echo " - 리소스 그룹: ${RESOURCE_GROUP}" + echo " - ACR에 대한 권한이 있는지 확인" + exit 1 +fi + +# JSON에서 username과 password 추출 +username=$(echo "${credential_json}" | jq -r '.username') +password=$(echo "${credential_json}" | jq -r '.passwords[0].value') + +if [ -z "${username}" ] || [ -z "${password}" ] || [ "${username}" == "null" ] || [ "${password}" == "null" ]; then + echo "❌ ACR credential 파싱 실패" + echo "credential JSON:" + echo "${credential_json}" + exit 1 +fi + +echo "✅ ACR credential 조회 성공" +echo " 사용자명: ${username}" +echo " 비밀번호: ${password:0:10}..." + +# 기존 Secret 확인 및 삭제 +echo "" +echo "🔍 기존 Secret 확인 중..." + +if kubectl get secret "${SECRET_NAME}" &> /dev/null; then + echo "🗑️ 기존 Secret 삭제 중..." + kubectl delete secret "${SECRET_NAME}" + echo "✅ 기존 Secret 삭제 완료" +else + echo "✅ 기존 Secret 없음" +fi + +# Image Pull Secret 생성 +echo "" +echo "🔐 Image Pull Secret 생성 중..." + +kubectl create secret docker-registry "${SECRET_NAME}" \ + --docker-server="${REGISTRY_URL}" \ + --docker-username="${username}" \ + --docker-password="${password}" + +if [ $? -eq 0 ]; then + echo "✅ Image Pull Secret 생성 성공!" +else + echo "❌ Image Pull Secret 생성 실패" + exit 1 +fi + +# Secret 정보 확인 +echo "" +echo "📊 생성된 Secret 정보:" +kubectl describe secret "${SECRET_NAME}" + +echo "" +echo "🧪 Secret 테스트 중..." + +# Secret이 올바르게 생성되었는지 확인 +SECRET_TYPE=$(kubectl get secret "${SECRET_NAME}" -o jsonpath='{.type}') +if [ "${SECRET_TYPE}" = "kubernetes.io/dockerconfigjson" ]; then + echo "✅ Secret 타입 확인됨: ${SECRET_TYPE}" +else + echo "❌ Secret 타입 불일치: ${SECRET_TYPE}" +fi + +# Registry URL 확인 +SECRET_REGISTRY=$(kubectl get secret "${SECRET_NAME}" -o jsonpath='{.data.\.dockerconfigjson}' | base64 -d | jq -r ".auths | keys[0]") +if [ "${SECRET_REGISTRY}" = "${REGISTRY_URL}" ]; then + echo "✅ Registry URL 확인됨: ${SECRET_REGISTRY}" +else + echo "❌ Registry URL 불일치: ${SECRET_REGISTRY}" +fi + +echo "" +echo "🎉 ACR Image Pull Secret 생성 완료!" +echo "" +echo "📋 사용 방법:" +echo "" +echo "1. Deployment에서 imagePullSecrets 사용:" +echo " spec:" +echo " template:" +echo " spec:" +echo " imagePullSecrets:" +echo " - name: ${SECRET_NAME}" +echo "" +echo "2. ServiceAccount에 Secret 연결:" +echo " kubectl patch serviceaccount default -p '{\"imagePullSecrets\": [{\"name\": \"${SECRET_NAME}\"}]}'" +echo "" +echo "3. Secret 확인:" +echo " kubectl get secret ${SECRET_NAME}" +echo " kubectl describe secret ${SECRET_NAME}" +echo "" +echo "4. Secret 삭제 (필요시):" +echo " kubectl delete secret ${SECRET_NAME}" +echo "" +echo "🔧 다음 단계:" +echo "1. Deployment 매니페스트에 imagePullSecrets 추가" +echo "2. kubectl apply -f deployment/manifests/deployment.yaml" +echo "3. Pod 상태 확인: kubectl get pods" +echo "" +echo "💡 문제 해결:" +echo "- ErrImagePull 오류 시: Secret 이름과 레지스트리 URL 확인" +echo "- 권한 오류 시: ACR에 대한 적절한 권한 확인" +echo "- 네트워크 오류 시: 클러스터에서 ACR로의 네트워크 연결 확인" + +echo "" +echo "✅ Image Pull Secret 설정이 완료되었습니다!" \ No newline at end of file diff --git a/vector/deployment/container/Dockerfile b/vector/deployment/container/Dockerfile new file mode 100644 index 0000000..18613d5 --- /dev/null +++ b/vector/deployment/container/Dockerfile @@ -0,0 +1,100 @@ +# deployment/container/Dockerfile +# Poetry 기반 Vector DB API Service Image - PVC 마운트 충돌 해결 + +# Base Image에서 상속 (Poetry 환경 포함) +ARG BASE_IMAGE=vector-api-base:latest +FROM ${BASE_IMAGE} + +# 메타데이터 +LABEL maintainer="admin@example.com" +LABEL version="1.0.2" +LABEL description="Vector DB API Service with Poetry - PVC Mount Fixed" + +# 환경 변수 설정 - Poetry 가상환경 경로 유지 +ENV HOME=/home/appuser \ + PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + POETRY_VENV_IN_PROJECT=false \ + POETRY_VIRTUALENVS_CREATE=true \ + POETRY_VIRTUALENVS_PATH=/opt/pypoetry/venvs \ + POETRY_CACHE_DIR=/opt/pypoetry/cache \ + POETRY_NO_INTERACTION=1 \ + PATH="/home/appuser/.local/bin:/opt/pypoetry/venvs/vector-api/bin:/usr/local/bin:/usr/bin:/bin" + +# root로 전환 (파일 복사 및 권한 설정용) +USER root + +# 🔧 Poetry 설정 파일들 복사 (의존성 정보) +COPY pyproject.toml poetry.lock* /app/ + +# 🚀 애플리케이션 소스 코드 복사 +COPY app/ /app/app/ + +# 📦 Poetry 의존성 설치 (가상환경이 /opt에 생성됨) +RUN cd /app && \ + # Poetry 설정 확인 및 재설정 + poetry config virtualenvs.in-project false && \ + poetry config virtualenvs.create true && \ + poetry config virtualenvs.path /opt/pypoetry/venvs && \ + poetry config cache-dir /opt/pypoetry/cache && \ + echo "🔧 Poetry 설정 확인:" && \ + poetry config --list && \ + echo "📦 의존성 설치 시작..." && \ + poetry install --no-dev --no-interaction && \ + echo "✅ 의존성 설치 완료" && \ + # 설치된 패키지 확인 + poetry show | head -10 && \ + # 가상환경 위치 확인 + poetry env info && \ + # 캐시 정리 + rm -rf $POETRY_CACHE_DIR/cache && \ + rm -rf /tmp/* + +# 📁 데이터 디렉토리 생성 및 권한 설정 +RUN mkdir -p /app/data /app/logs /app/vectordb \ + && chmod -R 755 /app/data /app/logs /app/vectordb + +# 👤 사용자 및 권한 설정 +RUN if id "appuser" &>/dev/null; then \ + chown -R appuser:appuser /app; \ + chown -R appuser:appuser /opt/pypoetry; \ + else \ + echo "appuser가 없어서 root로 실행됩니다"; \ + fi + +# 🔧 실행 스크립트 생성 (Poetry 가상환경 자동 활성화) +RUN cat > /app/start.sh << 'EOF' +#!/bin/bash +echo "🚀 Vector API 시작 중..." +echo "📍 현재 디렉토리: $(pwd)" +echo "🐍 Python 위치: $(which python)" +echo "📦 Poetry 위치: $(which poetry)" +echo "🔧 Poetry 가상환경 정보:" +poetry env info +echo "📋 설치된 패키지 (일부):" +poetry show | head -5 +echo "🔍 dotenv 모듈 테스트:" +poetry run python -c "from dotenv import load_dotenv; print('✅ dotenv 모듈 정상 로드')" +echo "🚀 애플리케이션 실행..." +exec poetry run python app/main.py +EOF + +RUN chmod +x /app/start.sh && \ + chown appuser:appuser /app/start.sh + +# 🏥 헬스체크 (의존성 확인 포함) +HEALTHCHECK --interval=30s --timeout=15s --start-period=60s --retries=3 \ + CMD poetry run python -c "from dotenv import load_dotenv; import app.main; print('✅ 앱 헬스체크 성공')" || exit 1 + +# 🚀 포트 노출 +EXPOSE 8000 + +# 📁 작업 디렉토리 설정 +WORKDIR /app + +# 👤 실행 사용자 설정 +USER appuser + +# 🎯 애플리케이션 실행 - 스크립트 사용 +CMD ["/app/start.sh"] + diff --git a/vector/deployment/container/Dockerfile-base b/vector/deployment/container/Dockerfile-base new file mode 100644 index 0000000..deab09a --- /dev/null +++ b/vector/deployment/container/Dockerfile-base @@ -0,0 +1,138 @@ +# deployment/container/Dockerfile-base +# Poetry 기반 Vector DB API Base Image - 홈 디렉토리 사용 (안전한 방식) + +FROM python:3.11-slim + +# 메타데이터 +LABEL description="Vector DB API Base Image with Poetry - Home Directory" +LABEL version="poetry-home-v1.0" +LABEL maintainer="admin@example.com" + +# 환경 변수 설정 - Poetry 가상환경을 홈 디렉토리로 이동 +ENV PYTHONDONTWRITEBYTECODE=1 \ + PYTHONUNBUFFERED=1 \ + DEBIAN_FRONTEND=noninteractive \ + PIP_NO_CACHE_DIR=1 \ + PIP_DISABLE_PIP_VERSION_CHECK=1 \ + POETRY_NO_INTERACTION=1 \ + POETRY_VENV_IN_PROJECT=false \ + POETRY_VIRTUALENVS_CREATE=true \ + POETRY_VIRTUALENVS_PATH=/home/appuser/.cache/pypoetry/venvs \ + POETRY_CACHE_DIR=/home/appuser/.cache/pypoetry/cache \ + HF_HUB_CACHE=/app/.cache/huggingface \ + TRANSFORMERS_CACHE=/app/.cache/transformers \ + SENTENCE_TRANSFORMERS_HOME=/app/.cache/sentence_transformers + +# 🔧 시스템 패키지 설치 +RUN apt-get update && apt-get install -y --no-install-recommends \ + build-essential \ + gcc \ + g++ \ + python3-dev \ + curl \ + wget \ + ca-certificates \ + git \ + sudo \ + lsb-release \ + bc \ + python3.11 \ + python3.11-venv \ + python3.11-dev \ + python3.11-distutils \ + && rm -rf /var/lib/apt/lists/* \ + && apt-get clean + +# 📦 pip 업그레이드 +RUN python3.11 -m pip install --no-cache-dir --upgrade pip setuptools wheel + +# 👤 비root 사용자 생성 (Poetry 설치 전에) +RUN groupadd -r appuser && \ + useradd -r -g appuser -d /home/appuser -s /bin/bash appuser && \ + mkdir -p /home/appuser && \ + chown -R appuser:appuser /home/appuser + +# 🔧 Poetry 가상환경 디렉토리 생성 (홈 디렉토리 사용) +RUN mkdir -p /home/appuser/.cache/pypoetry/venvs \ + /home/appuser/.cache/pypoetry/cache && \ + chown -R appuser:appuser /home/appuser/.cache && \ + chmod -R 755 /home/appuser/.cache + +# 🐍 Poetry를 appuser로 설치 +USER appuser +ENV PATH="/home/appuser/.local/bin:$PATH" + +# appuser 홈 디렉토리에 Poetry 설치 +RUN curl -sSL https://install.python-poetry.org | python3.11 - + +# Poetry 실행 권한 및 심볼릭 링크 (root 권한 필요) +USER root +RUN chmod +x /home/appuser/.local/bin/poetry && \ + ln -sf /home/appuser/.local/bin/poetry /usr/local/bin/poetry && \ + chown appuser:appuser /home/appuser/.local/bin/poetry + +# appuser로 다시 전환 +USER appuser + +# 🔧 Poetry 설정 - 가상환경을 홈 디렉토리로 이동 +RUN poetry config virtualenvs.in-project false && \ + poetry config virtualenvs.create true && \ + poetry config virtualenvs.path /home/appuser/.cache/pypoetry/venvs && \ + poetry config cache-dir /home/appuser/.cache/pypoetry/cache + +# Poetry 버전 확인 및 설정 검증 +RUN poetry --version && \ + poetry config --list && \ + ls -la /home/appuser/.local/bin/poetry && \ + which poetry + +# 🏗️ 작업 디렉토리 설정 및 권한 조정 +WORKDIR /app + +# root로 전환하여 디렉토리 소유권 설정 +USER root +RUN chown -R appuser:appuser /app + +# 📋 Poetry 설치 스크립트 복사 및 권한 설정 +COPY setup.sh /app/setup.sh +RUN chmod +x /app/setup.sh && \ + chown appuser:appuser /app/setup.sh + +# appuser로 전환하여 Poetry 환경 설정 +USER appuser + +# 🚀 Poetry 환경 설정 및 의존성 설치 +RUN cd /app && \ + export DEBIAN_FRONTEND=noninteractive && \ + ./setup.sh --skip-poetry-install --skip-python311-check --force-reinstall + +# 🗂️ 필요한 디렉토리 생성 및 권한 설정 +USER root +RUN mkdir -p /app/.cache/huggingface \ + /app/.cache/transformers \ + /app/.cache/sentence_transformers \ + /app/vectordb \ + /app/data \ + /app/logs && \ + chmod -R 755 /app/.cache /app/vectordb /app/data /app/logs && \ + chown -R appuser:appuser /app && \ + # Poetry 가상환경 디렉토리 권한 재확인 + chown -R appuser:appuser /home/appuser/.cache && \ + chmod -R 755 /home/appuser/.cache + +# 🧹 캐시 정리 +RUN rm -rf /tmp/* /var/tmp/* + +# 🚀 포트 노출 +EXPOSE 8000 + +# 🏥 간단한 헬스체크 (appuser 권한으로 실행) +HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \ + CMD su -c "poetry --version && poetry config virtualenvs.path" appuser || exit 1 + +# 👤 최종 사용자 설정 +USER appuser + +# 🎯 기본 명령어 +CMD ["poetry", "--version"] + diff --git a/vector/deployment/manifest/configmap.yaml b/vector/deployment/manifest/configmap.yaml new file mode 100644 index 0000000..1eea584 --- /dev/null +++ b/vector/deployment/manifest/configmap.yaml @@ -0,0 +1,63 @@ +apiVersion: v1 +kind: ConfigMap +metadata: + name: vector-api-config +data: + # 🔧 기존 애플리케이션 설정 (유지) + APP_TITLE: "음식점 Vector DB 구축 서비스" + APP_VERSION: "1.0.0" + APP_DESCRIPTION: "소상공인을 위한 AI 기반 경쟁업체 분석 및 액션 추천 시스템" + + # 🔧 기존 서버 설정 (유지) + HOST: "0.0.0.0" + PORT: "8000" + LOG_LEVEL: "debug" # 디버깅을 위해 debug로 변경 + + # 🔧 기존 Restaurant API 설정 (K8s 환경, 유지) + RESTAURANT_API_HOST: "restaurant-api-service" + RESTAURANT_API_PORT: "80" + + # 🔧 기존 Review API 설정 (K8s 환경, 유지) + REVIEW_API_HOST: "kakao-review-api-service" + REVIEW_API_PORT: "80" + + # 🔧 기존 Claude API 설정 (유지) + CLAUDE_MODEL: "claude-sonnet-4-20250514" + + # 🔧 기존 Vector DB 설정 (유지) + VECTOR_DB_PATH: "/app/vectordb" + VECTOR_DB_COLLECTION: "restaurant_reviews" + EMBEDDING_MODEL: "sentence-transformers/all-MiniLM-L6-v2" + + # 🔧 기존 데이터 수집 설정 (유지) + MAX_RESTAURANTS_PER_CATEGORY: "50" + MAX_REVIEWS_PER_RESTAURANT: "100" + REQUEST_DELAY: "0.1" + REQUEST_TIMEOUT: "600" + + # 🆕 ChromaDB 최신 버전 호환 설정 추가 + CHROMA_DB_IMPL: "duckdb+parquet" # SQLite 대신 DuckDB 사용 + ALLOW_RESET: "True" + ANONYMIZED_TELEMETRY: "False" + + # 🆕 Python 최적화 설정 + PYTHONUNBUFFERED: "1" + PYTHONDONTWRITEBYTECODE: "1" + + # 🆕 캐시 디렉토리 설정 + HF_HUB_CACHE: "/app/.cache/huggingface" + TRANSFORMERS_CACHE: "/app/.cache/transformers" + + # 🆕 FastAPI 설정 + FASTAPI_ENV: "production" + + # 🆕 Uvicorn 설정 + UVICORN_HOST: "0.0.0.0" + UVICORN_PORT: "8000" + UVICORN_LOG_LEVEL: "debug" + UVICORN_ACCESS_LOG: "true" + + # 🆕 타임아웃 설정 + STARTUP_TIMEOUT: "300" # 5분 + SHUTDOWN_TIMEOUT: "30" # 30초 + diff --git a/vector/deployment/manifest/deployment.yaml b/vector/deployment/manifest/deployment.yaml new file mode 100644 index 0000000..7306d73 --- /dev/null +++ b/vector/deployment/manifest/deployment.yaml @@ -0,0 +1,164 @@ +# deployment/manifests/deployment.yaml.fixed +apiVersion: apps/v1 +kind: Deployment +metadata: + name: vector-api + labels: + app: vector-api +spec: + replicas: 1 + selector: + matchLabels: + app: vector-api + template: + metadata: + labels: + app: vector-api + spec: + # 🔧 볼륨 권한 설정을 위한 initContainer + initContainers: + - name: volume-permissions + image: busybox:1.35 + command: + - /bin/sh + - -c + - | + echo "=== 볼륨 권한 설정 시작 ===" + mkdir -p /app/vectordb + chown -R 1000:1000 /app/vectordb + chmod -R 755 /app/vectordb + echo "=== 볼륨 권한 설정 완료 ===" + volumeMounts: + - name: vector-db-storage + mountPath: /app/vectordb + securityContext: + runAsUser: 0 + + containers: + - name: vector-api + image: acrdigitalgarage03.azurecr.io/vector-api:latest + imagePullPolicy: Always + ports: + - containerPort: 8000 + + # 🔧 보안 컨텍스트 + securityContext: + runAsNonRoot: true + runAsUser: 1000 + runAsGroup: 1000 + allowPrivilegeEscalation: false + readOnlyRootFilesystem: false + + # 🔧 리소스 설정 + resources: + requests: + memory: "4Gi" + cpu: "1000m" + limits: + memory: "8Gi" + cpu: "2000m" + + # 🏥 헬스체크 설정 + livenessProbe: + httpGet: + path: /health + port: 8000 + initialDelaySeconds: 120 + periodSeconds: 30 + timeoutSeconds: 15 + failureThreshold: 3 + + readinessProbe: + httpGet: + path: /health + port: 8000 + initialDelaySeconds: 60 + periodSeconds: 10 + timeoutSeconds: 10 + failureThreshold: 3 + + # 📂 볼륨 마운트 + volumeMounts: + - name: vector-db-storage + mountPath: /app/vectordb + + # ConfigMap 환경 변수 + envFrom: + - configMapRef: + name: vector-api-config + + # 🌍 환경변수 설정 (인증 필드 제거) + env: + - name: PYTHONUNBUFFERED + value: "1" + - name: PYTHONDONTWRITEBYTECODE + value: "1" + # 🔧 ChromaDB 기본 설정 (인증 필드 제거) + - name: ANONYMIZED_TELEMETRY + value: "False" + - name: CHROMA_DB_IMPL + value: "duckdb+parquet" + - name: ALLOW_RESET + value: "True" + # 🔧 로그 레벨 + - name: LOG_LEVEL + value: "info" + # 🔧 Claude API (ConfigMap에서 가져오기) + - name: CLAUDE_API_KEY + valueFrom: + secretKeyRef: + name: vector-api-secret + key: CLAUDE_API_KEY + - name: CLAUDE_MODEL + valueFrom: + configMapKeyRef: + name: vector-api-config + key: CLAUDE_MODEL + # 🔧 기타 설정 (ConfigMap에서 가져오기) + - name: APP_TITLE + valueFrom: + configMapKeyRef: + name: vector-api-config + key: APP_TITLE + - name: APP_VERSION + valueFrom: + configMapKeyRef: + name: vector-api-config + key: APP_VERSION + + # 📦 볼륨 설정 + volumes: + - name: vector-db-storage + persistentVolumeClaim: + claimName: vector-db-pvc + + # 🔐 이미지 Pull Secret + imagePullSecrets: + - name: acr-secret + + # 🎯 노드 선택 및 배치 설정 + nodeSelector: + agentpool: aipool + + tolerations: + - key: "dedicated" + operator: "Equal" + value: "aipool" + effect: "NoSchedule" + + affinity: + podAntiAffinity: + preferredDuringSchedulingIgnoredDuringExecution: + - weight: 100 + podAffinityTerm: + labelSelector: + matchExpressions: + - key: app + operator: In + values: + - vector-api + topologyKey: kubernetes.io/hostname + + restartPolicy: Always + dnsPolicy: ClusterFirst + diff --git a/vector/deployment/manifest/ingress.yaml b/vector/deployment/manifest/ingress.yaml new file mode 100644 index 0000000..dd30ec8 --- /dev/null +++ b/vector/deployment/manifest/ingress.yaml @@ -0,0 +1,39 @@ +# deployment/manifests/ingress.yaml +apiVersion: networking.k8s.io/v1 +kind: Ingress +metadata: + name: vector-api-ingress + annotations: + nginx.ingress.kubernetes.io/rewrite-target: / + nginx.ingress.kubernetes.io/ssl-redirect: "false" + nginx.ingress.kubernetes.io/proxy-body-size: "10m" + # Vector DB 구축 시간을 고려한 긴 타임아웃 설정 + nginx.ingress.kubernetes.io/proxy-read-timeout: "1800" + nginx.ingress.kubernetes.io/proxy-send-timeout: "1800" + nginx.ingress.kubernetes.io/client-body-timeout: "1800" + nginx.ingress.kubernetes.io/proxy-connect-timeout: "60" + # CORS 설정 + nginx.ingress.kubernetes.io/enable-cors: "true" + nginx.ingress.kubernetes.io/cors-allow-origin: "*" + nginx.ingress.kubernetes.io/cors-allow-methods: "GET, POST, OPTIONS" + nginx.ingress.kubernetes.io/cors-allow-headers: "DNT,User-Agent,X-Requested-With,If-Modified-Since,Cache-Control,Content-Type,Range,Authorization" +spec: + ingressClassName: nginx + rules: + # 환경에 맞게 호스트명 수정 필요 + - host: vector-api.20.249.191.180.nip.io + http: + paths: + - path: / + pathType: Prefix + backend: + service: + name: vector-api-service + port: + number: 80 + # TLS 설정 (HTTPS 필요시 주석 해제) + # tls: + # - hosts: + # - vector-api.example.com + # secretName: vector-api-tls + \ No newline at end of file diff --git a/vector/deployment/manifest/pvc.yaml b/vector/deployment/manifest/pvc.yaml new file mode 100644 index 0000000..430d88f --- /dev/null +++ b/vector/deployment/manifest/pvc.yaml @@ -0,0 +1,18 @@ +# deployment/manifests/pvc.yaml +apiVersion: v1 +kind: PersistentVolumeClaim +metadata: + name: vector-db-pvc + labels: + app: vector-api + component: storage +spec: + accessModes: + - ReadWriteOnce + resources: + requests: + storage: 10Gi + storageClassName: managed + # 선택적: 특정 PV에 바인딩하려는 경우 + # volumeName: vector-db-pv + \ No newline at end of file diff --git a/vector/deployment/manifest/secret.yaml b/vector/deployment/manifest/secret.yaml new file mode 100644 index 0000000..13ab1ed --- /dev/null +++ b/vector/deployment/manifest/secret.yaml @@ -0,0 +1,11 @@ +# deployment/manifests/secret.yaml +apiVersion: v1 +kind: Secret +metadata: + name: vector-api-secret +type: Opaque +data: + # Claude API 키 (Base64 인코딩 필요) + # echo -n "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" | base64 + CLAUDE_API_KEY: c2stYW50LWFwaTAzLUVGM1ZocXJJUkVmY3hOa1V3ZkdENDluZ0k1SGZhcTUwd3c4WGZMd0psckR6akczdzNPSHRYTzFBZEltczJuRng2cmc4bk84cWhnMnFwUU01WFJnLTQ1SDdIQUFB + \ No newline at 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"vector-api" +version = "1.0.0" +description = "Vector DB API with AI/ML capabilities" +authors = ["Developer "] +packages = [{include = "app"}] + +[tool.poetry.dependencies] +python = "^3.11" +fastapi = "0.115.9" +uvicorn = {extras = ["standard"], version = "^0.34.3"} +pydantic = "^2.11.7" +python-dotenv = "^1.1.0" +python-multipart = "^0.0.20" +aiohttp = "^3.12.13" +requests = "^2.32.4" +numpy = "^2.3.0" +pandas = "^2.3.0" +tokenizers = "^0.21.1" +transformers = "^4.52.4" +huggingface-hub = "^0.33.0" +sentence-transformers = "^4.1.0" +chromadb = "^1.0.12" +hnswlib = "^0.8.0" +duckdb = "^1.3.0" +anthropic = "^0.54.0" +typing-extensions = "^4.14.0" +sqlalchemy = "^2.0.41" +torch = {version = "^2.7.1+cpu", source = "pytorch-cpu"} +torchvision = {version = "^0.22.1+cpu", source = "pytorch-cpu"} +torchaudio = {version = "^2.7.1+cpu", source = "pytorch-cpu"} +starlette = ">=0.40.0,<0.46.0" + +[[tool.poetry.source]] +name = "pytorch-cpu" +url = "https://download.pytorch.org/whl/cpu" +priority = "supplemental" + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" diff --git a/vector/setup.sh b/vector/setup.sh new file mode 100755 index 0000000..502da6d --- /dev/null +++ b/vector/setup.sh @@ -0,0 +1,376 @@ +#!/bin/bash +# setup.sh - Poetry 기반 Vector DB API 의존성 설치 스크립트 (홈 디렉토리 사용) + +set -e + +# 색상 설정 +RED='\033[0;31m' +GREEN='\033[0;32m' +YELLOW='\033[1;33m' +BLUE='\033[0;34m' +CYAN='\033[0;36m' +NC='\033[0m' + +# 옵션 기본값 +SKIP_POETRY_INSTALL=false +SKIP_PYTHON311_CHECK=false +FORCE_REINSTALL=false +RUN_AFTER_INSTALL=false + +# 함수 정의 +log_info() { echo -e "${CYAN}ℹ️ $1${NC}"; } +log_success() { echo -e "${GREEN}✅ $1${NC}"; } +log_warning() { echo -e "${YELLOW}⚠️ $1${NC}"; } +log_error() { echo -e "${RED}❌ $1${NC}"; } +log_step() { echo -e "\n${BLUE}🔧 $1${NC}"; } + +# 사용법 표시 +show_usage() { + echo "사용법: $0 [옵션]" + echo "" + echo "옵션:" + echo " --skip-poetry-install Poetry 설치 건너뛰기" + echo " --skip-python311-check Python 3.11 확인 건너뛰기" + echo " --force-reinstall 기존 환경 제거 후 재설치" + echo " --run-after-install 설치 후 앱 자동 실행" + echo " --help 이 도움말 표시" +} + +# 파라미터 파싱 +while [[ $# -gt 0 ]]; do + case $1 in + --skip-poetry-install) + SKIP_POETRY_INSTALL=true + shift + ;; + --skip-python311-check) + SKIP_PYTHON311_CHECK=true + shift + ;; + --force-reinstall) + FORCE_REINSTALL=true + shift + ;; + --run-after-install) + RUN_AFTER_INSTALL=true + shift + ;; + --help) + show_usage + exit 0 + ;; + *) + log_error "알 수 없는 옵션: $1" + show_usage + exit 1 + ;; + esac +done + +echo "========================================================" +echo "🚀 Poetry 기반 Vector DB API 의존성 설치 (홈 디렉토리)" +echo "========================================================" +echo "설치 시작: $(date)" +echo "" + +INSTALL_START=$(date +%s) + +# ============================================================================= +# 1단계: Poetry 설치 확인 +# ============================================================================= +log_step "1단계: Poetry 설치 확인" + +if [ "$SKIP_POETRY_INSTALL" = true ]; then + log_info "Poetry 설치 확인을 건너뜁니다." +elif command -v poetry &> /dev/null; then + POETRY_VERSION=$(poetry --version) + log_success "Poetry 이미 설치됨: $POETRY_VERSION" +else + if [ -f /.dockerenv ]; then + log_error "Docker 환경에서 Poetry를 찾을 수 없습니다." + log_error "--skip-poetry-install 옵션을 제거하세요." + exit 1 + fi + + log_info "Poetry 설치 중..." + sudo apt update + sudo apt install -y python3-poetry + + # PATH 확인 + export PATH="$HOME/.local/bin:$PATH" + + if command -v poetry &> /dev/null; then + log_success "Poetry 설치 완료: $(poetry --version)" + else + log_error "Poetry 설치 실패" + exit 1 + fi +fi + +# ============================================================================= +# 2단계: Python 3.11 확인 +# ============================================================================= +log_step "2단계: Python 3.11 환경 확인" + +if [ "$SKIP_PYTHON311_CHECK" = false ]; then + if command -v python3.11 &> /dev/null; then + PYTHON311_VERSION=$(python3.11 --version) + log_success "Python 3.11 발견: $PYTHON311_VERSION" + else + log_warning "Python 3.11이 설치되어 있지 않습니다." + log_info "Python 3.11 설치 중..." + sudo apt update + sudo apt install -y python3.11 python3.11-venv python3.11-dev + + if command -v python3.11 &> /dev/null; then + log_success "Python 3.11 설치 완료: $(python3.11 --version)" + else + log_error "Python 3.11 설치 실패" + exit 1 + fi + fi +fi + +# ============================================================================= +# 3단계: Poetry 프로젝트 초기화 +# ============================================================================= +log_step "3단계: Poetry 프로젝트 초기화" + +# 기존 환경 제거 (강제 재설치 옵션) +if [ "$FORCE_REINSTALL" = true ]; then + log_info "기존 Poetry 환경 제거 중..." + poetry env remove --all 2>/dev/null || true + rm -f poetry.lock pyproject.toml 2>/dev/null || true +fi + +# pyproject.toml이 없는 경우 초기화 +if [ ! -f "pyproject.toml" ]; then + log_info "Poetry 프로젝트 초기화 중..." + + # 비대화형 초기화 + cat > pyproject.toml << 'EOF' +[tool.poetry] +name = "vector-api" +version = "1.0.0" +description = "Vector DB API with AI/ML capabilities" +authors = ["Developer "] +packages = [{include = "app"}] + +[tool.poetry.dependencies] +python = "^3.11" + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" +EOF + + log_success "pyproject.toml 생성 완료" +else + log_success "기존 pyproject.toml 사용" +fi + +# ============================================================================= +# 4단계: Poetry 가상환경 설정 (홈 디렉토리 사용) +# ============================================================================= +log_step "4단계: Poetry 가상환경 설정 (홈 디렉토리 사용)" + +log_info "Poetry 가상환경을 홈 디렉토리로 설정 중..." + +# 홈 디렉토리에 Poetry 관련 디렉토리 생성 +mkdir -p ~/.cache/pypoetry/venvs ~/.cache/pypoetry/cache + +# Poetry 설정 - 가상환경을 홈 디렉토리로 이동 +poetry config virtualenvs.in-project false +poetry config virtualenvs.create true +poetry config virtualenvs.path ~/.cache/pypoetry/venvs +poetry config cache-dir ~/.cache/pypoetry/cache + +# 설정 확인 +log_info "Poetry 설정 확인:" +poetry config --list | grep -E "(virtualenvs|cache)" + +# 권한 확인 +log_info "디렉토리 권한 확인:" +ls -la ~/.cache/pypoetry/ 2>/dev/null || log_info "디렉토리가 아직 생성되지 않음" + +log_success "Poetry 가상환경 설정 완료" + +# ============================================================================= +# 5단계: Python 3.11 환경 설정 +# ============================================================================= +log_step "5단계: Python 3.11 환경 설정" + +log_info "Poetry가 Python 3.11을 사용하도록 설정 중..." +poetry env use python3.11 + +# 환경 정보 확인 +POETRY_ENV_INFO=$(poetry config virtualenvs.path) +log_success "Poetry 가상환경 기본 경로: $POETRY_ENV_INFO" + +# ============================================================================= +# 6단계: 소스 우선순위 사전 설정 (중요!) +# ============================================================================= +log_step "6단계: 소스 우선순위 사전 설정" + +log_info "PyPI를 기본 소스로 확인 중..." +# PyPI는 기본적으로 존재하므로 확인만 함 +if poetry source show | grep -q "pypi"; then + log_success "PyPI 소스 확인됨" +else + log_warning "PyPI 소스가 없습니다 (비정상)" +fi + +log_success "소스 우선순위 사전 설정 완료" + +# ============================================================================= +# 7단계: 기본 웹 프레임워크 설치 +# ============================================================================= +log_step "7단계: 기본 웹 프레임워크 설치" + +log_info "FastAPI 및 관련 패키지 설치 중..." +poetry add "fastapi==0.115.9" +poetry add uvicorn[standard] pydantic python-dotenv python-multipart + +log_success "웹 프레임워크 설치 완료" + +# ============================================================================= +# 8단계: HTTP 클라이언트 설치 +# ============================================================================= +log_step "8단계: HTTP 클라이언트 설치" + +log_info "HTTP 클라이언트 설치 중..." +poetry add aiohttp requests + +log_success "HTTP 클라이언트 설치 완료" + +# ============================================================================= +# 9단계: 데이터 처리 라이브러리 설치 +# ============================================================================= +log_step "9단계: 데이터 처리 라이브러리 설치" + +log_info "NumPy, Pandas 설치 중..." +poetry add numpy pandas + +log_success "데이터 처리 라이브러리 설치 완료" + +# ============================================================================= +# 10단계: AI/ML 기초 라이브러리 설치 +# ============================================================================= +log_step "10단계: AI/ML 기초 라이브러리 설치" + +log_info "Tokenizers, Transformers 설치 중..." +poetry add tokenizers transformers huggingface-hub + +log_success "AI/ML 기초 라이브러리 설치 완료" + +# ============================================================================= +# 11단계: Sentence Transformers 설치 +# ============================================================================= +log_step "11단계: Sentence Transformers 설치" + +log_info "Sentence Transformers 설치 중..." +poetry add sentence-transformers + +log_success "Sentence Transformers 설치 완료" + +# ============================================================================= +# 12단계: Vector DB 라이브러리 설치 +# ============================================================================= +log_step "12단계: Vector DB 라이브러리 설치" + +log_info "ChromaDB, HNSW, DuckDB 설치 중..." +poetry add chromadb hnswlib duckdb + +log_success "Vector DB 라이브러리 설치 완료" + +# ============================================================================= +# 13단계: Claude API 라이브러리 설치 +# ============================================================================= +log_step "13단계: Claude API 라이브러리 설치" + +log_info "Anthropic Claude API 라이브러리 설치 중..." +poetry add anthropic + +log_success "Claude API 라이브러리 설치 완료" + +# ============================================================================= +# 14단계: 기타 필수 라이브러리 설치 +# ============================================================================= +log_step "14단계: 기타 필수 라이브러리 설치" + +log_info "기타 필수 라이브러리 설치 중..." +poetry add typing-extensions sqlalchemy + +log_success "기타 필수 라이브러리 설치 완료" + +# ============================================================================= +# 15단계: PyTorch CPU 버전 설치 +# ============================================================================= +log_step "15단계: PyTorch CPU 버전 설치" + +log_info "PyTorch CPU 버전 소스 추가 중..." +poetry source add pytorch-cpu https://download.pytorch.org/whl/cpu --priority=supplemental + +log_info "PyTorch CPU 버전 설치 중..." +poetry add torch --source pytorch-cpu +poetry add torchvision --source pytorch-cpu +poetry add torchaudio --source pytorch-cpu + +log_success "PyTorch CPU 버전 설치 완료" + +# ============================================================================= +# 16단계: Starlette 버전 호환성 확인 +# ============================================================================= +log_step "16단계: Starlette 버전 호환성 확인" + +log_info "Starlette 호환 버전 설치 중..." +poetry add "starlette>=0.40.0,<0.46.0" + +log_success "Starlette 호환성 확인 완료" + +# 종료 시간 계산 +INSTALL_END=$(date +%s) +INSTALL_TIME=$((INSTALL_END - INSTALL_START)) +MINUTES=$((INSTALL_TIME / 60)) +SECONDS=$((INSTALL_TIME % 60)) + +echo "" +echo "🎉 Poetry 기반 Vector DB API 설치 완료!" +echo "========================================================" +echo "⏱️ 총 설치 시간: ${MINUTES}분 ${SECONDS}초" +echo "📦 설치된 패키지 수: $(poetry show | wc -l)" +echo "🐍 Python 환경: $(poetry run python --version)" +echo "📁 환경 경로: $(poetry env info --path)" +echo "" + +echo "🚀 다음 단계:" +echo " 1. 가상환경 활성화:" +echo " poetry shell" +echo "" +echo " 2. 애플리케이션 실행:" +echo " poetry run python app/main.py" +echo "" +echo " 3. 개발 서버 실행:" +echo " poetry run uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload" +echo "" + +echo "💡 유용한 명령어:" +echo " - poetry show # 설치된 패키지 확인" +echo " - poetry show --tree # 의존성 트리 확인" +echo " - poetry add [패키지명] # 새 패키지 추가" +echo " - poetry update # 패키지 업데이트" +echo " - poetry env info # 환경 정보 확인" +echo "" + +# 자동 실행 옵션 +if [ "$RUN_AFTER_INSTALL" = true ]; then + if [ -f "app/main.py" ]; then + log_info "앱 자동 실행 중..." + poetry run python app/main.py + else + log_warning "app/main.py 파일이 없어 자동 실행을 건너뜁니다." + fi +fi + +log_success "설치 스크립트 완료! 🎊" +