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  2. Claude를 사용하는 RAG 챗봇

Claude를 사용하는 RAG 챗봇

Bedrock에서 PDF 문서용 RAG 기능을 포함한 Claude를 사용해 서버리스, React 기반 챗봇을 생성하세요.

  • 생성형 AI
  • 서버리스

프롬프트

# AWS Claude RAG Chatbot Architecture Design Request
## Project Overview
I need a comprehensive design for a web-based chatbot application with the following key components:
- Claude 3 Sonnet on Amazon Bedrock as the LLM
- RAG capabilities for PDF documents stored in S3
- React frontend with real-time chat functionality
## Detailed Requirements
### 1. Core Functionality
- **User Interface**: Web-based chat interface built with React
- **AI Backend**: Claude 3 Sonnet model via Amazon Bedrock API
- **RAG System**: 
  - PDF document search and retrieval from S3
  - Document upload functionality for expanding knowledge base
  - Vector search across 1000+ documents
- **Persistence**:
  - Chat history storage and retrieval
  - User authentication and session management
### 2. Performance Requirements
- Support for 100 concurrent users
- Response times under 2 seconds for typical queries
- Ability to process and index documents up to 100MB each
### 3. Cost Optimization Targets
- Monthly operational cost under $200 for moderate usage
- Strategic use of spot instances where appropriate
- Caching implementation to minimize Bedrock API calls
- Pay-per-use services prioritized
### 4. Technical Architecture Preferences
- Serverless backend architecture (AWS Lambda)
- Vector database for embeddings (OpenSearch or equivalent)
- PDF processing pipeline for text extraction and embedding
- WebSocket implementation for real-time chat experience
- API Gateway for REST endpoint management
### 5. Security & Compliance Requirements
- End-to-end encryption for documents (at rest and in transit)
- IAM roles configured with least privilege principle
- Rate limiting implementation to prevent system abuse
- Comprehensive audit logging for all system interactions
## Deliverables Requested
1. Complete AWS solution architecture diagram
2. Infrastructure as Code (Terraform preferred)
3. Detailed deployment guide with step-by-step instructions
4. Cost estimation breakdown by AWS service
5. Security implementation details
6. Readme with full documentation

Please provide a solution that adheres to AWS Well-Architected Framework principles, with particular attention to reliability, performance efficiency, and cost optimization.
Provide your complete solution architecture without any preamble, starting with the high-level architecture diagram description.

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베타

  1. AWS 환경 및 비용 관리 설정
  2. AWS CLI 설치
    • 운영 체제에 맞는 AWS CLI을(를) 다운로드하여 설치합니다.
  3. 프롬프트 복사
    • ‘프롬프트 복사’를 클릭하여 프롬프트를 클립보드에 복사합니다.
  4. 프롬프트 테스트
    • 프롬프트를 AI 도구(예: Q Developer CLI)에 붙여넣고 실행하여 결과를 생성합니다.
  5. 검토, 배포 및 모니터링
    • 생성된 리소스와 예상 비용을 검토합니다.
    • 우선 개발 환경에 배포합니다.
    • 프로덕션으로 전환하기 전에 성과와 지출을 모니터링하세요.

이러한 프롬프트를 사용하면 고지 사항에 동의하는 것으로 간주됩니다.

Claude를 사용하는 RAG 챗봇 | AWS Startups