by aws-samples · Agent Tool · ★ 221
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Serverless RAG Demo v2 Scalable RAG and Multi-Agent workflows powered by Amazon Bedrock, OpenSearch Serverless NextGen, and Bedrock AgentCore. Features Document Chat — Upload documents, ask questions with hybrid search (BM25 + KNN), per-user document isolation Multi-Agent — Strands Graph orchestrator with specialist nodes: code generation, presentations, web search, weather, retrieval Architecture ┌──────────────────────────────────────────────────────────────────┐ │ CloudFront │ │ Default behavior → S3 (React UI static build) │ │ + runtime-config.json (Cognito, API URLs) │ └──────────────────────────┬───────────────────────────────────────┘ │ ┌────────────┴────────────┐ │ Cognito Auth │ └────────────┬────────────┘ │ ┌─────────────────┼─────────────────┐ │ │ │ ▼ ▼ ▼ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │ API GW │ │ API GW │ │ S3 Upload │ │ (WSS) │ │ (REST) │ │ (Presigned) │ └──────┬──────┘ └──────┬──────┘ └────────┬────────┘ │ │ │ ▼ ▼ ▼ ┌─────────────┐ ┌─────────────┐ ┌─────────────────┐ │ AgentCore │ │ A
| Stars | 221 |
| Forks | 70 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT-0 |
| Quality Score | 41.7/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-03 |
| Created | 2023-08-23 |
| Platforms | claude-code, node |
| Est. Tokens | ~7542k |
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serverless-rag-demo is Amazon Bedrock Foundation models with Amazon Opensearch Serverless as a Vector DB. It is categorized as a Agent Tool with 221 GitHub stars.
serverless-rag-demo is primarily written in TypeScript. It covers topics such as anthropic, claude, haiku.
You can find installation instructions and usage details in the serverless-rag-demo GitHub repository at github.com/aws-samples/serverless-rag-demo. The project has 221 stars and 70 forks, indicating an active community.
serverless-rag-demo is released under the MIT-0 license, making it free to use and modify according to the license terms.
The top alternatives to serverless-rag-demo on Agent Skills Hub include value-for-fable, tools, mcp-framework. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.