Amazon Bedrock AgentCore 演示文稿生成智能体教程
AWS 机器学习博客发布教程,介绍如何用 Amazon Bedrock AgentCore 构建一套自动生成 PowerPoint 的智能体系统:在 AgentCore 运行时上部署单个主管智能体,借助 Strands Agents 框架在文档生成与内容摘要两类工具之间进行路由。系统通过 Amazon Bedrock Knowledge Bases、OpenSearch Serverless 与 Titan Text Embeddings v2 搭建 RAG 检索管线,由 Anthropic Claude Sonnet 4.6 生成内容、Stability AI Stable Image Inpaint 生成幻灯片配图,并以 .NET 8 最小 API 对外提供 HTTP 接口。AWS 称在其内部测试中该流程可在 90 秒内完成,并提供了公开代码仓库;该耗时仅为 AWS 自述,未附第三方验证。
它把检索、生成、配图与权限治理串成一条可部署的流水线,对企业内部文档自动化有参考价值。
A financial services team spends significant time each week manually creating client PowerPoint presentations from quarterly reports, compliance documents, and market analyses. Each presentation requires reading hundreds of pages, extracting key data points, structuring slides, and generating supporting visuals. This post walks you through building an AI agent system using Amazon Bedrock AgentCore that automates this workflow, completing in under 90 seconds in our internal testing. This approach reduces presentation creation time while grounding content in source documents. The solution deploys a supervisor agent on AgentCore runtime, a capability of Amazon Bedrock AgentCore, using the Strands Agents framework to orchestrate document generation and summarization tools. Anthropic Claude Sonnet 4.6 (available on Amazon Bedrock) handles content creation, Amazon Titan Text Embeddings v2 powers vector search, and Stability AI Stable Image Inpaint (available on Amazon Bedrock) generates slide images. This post includes a public repository with the code assets.
Solution overview
The solution deploys a single supervisor agent on Amazon Bedrock AgentCore runtime that selects between document generation and summarization tools based on user requests. A Retrieval Augmented Generation (RAG) pipeline uses Amazon OpenSearch Serverless for vector storage and semantic search across multimodal content.
#Amazon Bedrock AgentCore#Strands Agents#Anthropic Claude Sonnet 4.6#Amazon Titan Text Embeddings v2#Stability AI Stable Image Inpaint#Amazon Bedrock Knowledge Bases#Amazon OpenSearch Serverless#AWS Lambda#Amazon Bedrock Guardrails#Claude Haiku 4.5