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- Spring AI 1.0.0 (Vertex AI Gemini + Embedding + Chroma) 의존성 추가 - ChatMessage 엔티티, ChatMessageRepository 구현 - ChatService/ChatServiceImpl (RAG: 벡터 검색 → 컨텍스트 → Gemini 호출) - MockChatService (로컬 테스트용 더미 응답) - ChatController (Swagger 문서화 포함) - application.yml: Vertex AI Gemini/Embedding 설정 - application-local.yml: Chroma 자동설정 exclude, 더미 AI 설정 - ChatServiceImpl/ChatController에 @Profile(!local) 적용
- Spring AI BOM 1.0.0 → 1.1.0 업그레이드 - spring-ai-starter-model-vertex-ai-gemini/embedding 제거 - spring-ai-starter-model-google-genai 추가 (무료 API 키 방식) - application.yml: Vertex AI 설정 → Google GenAI API 키 설정 - application-local.yml: 더미 Vertex AI 값 → 더미 GenAI API 키
twodo0
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Mar 11, 2026
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ChatMessage를 Role로 구분한 건 대화 문맥을 관리하기에 아주 좋은 것 같습니다. 그런데 현재 ASSISTANT 역할일 떄도 memberId가 필수여서 DB에 무조건 넣어야 하는 구조입니다. 이 부분 개선되면 좋을 것 같습니다!
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#️⃣연관된 이슈
📝작업 내용
Spring AI 의존성 추가
Spring AI BOM 1.1.0
비용 절감을 위해 Vertex AI (유료, GCP 서비스 계정) → Google AI Studio (무료, API 키) 방식으로 전환
스크린샷 (선택)
💬리뷰 요구사항(선택)
Chroma DB 연동 및 실제 RAG 테스트는 Data Pipeline 담당자 구현 후 진행해야 합니다.
현재 로컬에서는 MockChatService가 더미 응답 제공하고 있습니다.