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Chatbot RAG con Claude

Crea un chatbot serverless basato su React utilizzando Claude su Bedrock con funzionalità RAG per documenti PDF.

  • IA generativa
  • Serverless

Prompt

# 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.

Come si usa?

BETA

  1. Configura il tuo ambiente AWS e il controllo dei costi
  2. Installazione di AWS CLI
    • Scarica e installa AWS CLI per il tuo sistema operativo.
  3. Copia il prompt
    • Fai clic su "Copia prompt" per copiare la richiesta negli appunti.
  4. Prova il prompt
    • Incolla il prompt nel tuo strumento di intelligenza artificiale (ad esempio, Q Developer CLI) ed eseguilo per generare i risultati.
  5. Rivedi, implementa e monitora
    • Rivedi le risorse generate e i costi stimati.
    • Implementa prima in un ambiente di sviluppo.
    • Monitora le prestazioni e la spesa prima di passare alla produzione.

Utilizzando queste istruzioni, l'utente accetta avvertenza.