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官方來源· AWS Artificial Intelligence· AI· 發布於 2026年10月1日
AWS 示範以 Amazon S3 Vectors 為 NVIDIA NeMo Agent Toolkit 建立持久記憶
AWS 的技術指南介紹如何在部署於 Amazon EKS 的 NVIDIA NeMo Agent Toolkit 中，使用 Amazon S3 Vectors 作為持久記憶層，並以多代理投資研究工作流程示範自訂記憶提供者的實作。
完整報導
AWS 於 2026 年 10 月 1 日發布技術指南，說明如何將 Amazon S3 Vectors 用作 NVIDIA NeMo Agent Toolkit（NAT）的持久記憶層。指南涵蓋在 Amazon Elastic Kubernetes Service（Amazon EKS）部署 NAT，並示範如何把 S3 Vectors 實作為自訂記憶提供者。
文章以多代理投資研究作為示範情境，聚焦於 NAT 記憶子系統如何運作，以及如何接入這個記憶提供者。這讓讀者能從一個具體工作流程了解指南所示的整合方式；公告並未將該情境描述為投資建議。
這篇內容延續 AWS 近期發布的實作指南方向。舉例而言，AWS 在 2026 年 9 月 30 日也發布了以 Amazon Bedrock Knowledge Bases 建立自然語言理賠助理的指南；本次文章則將焦點放在代理工作流程的持久記憶，以及 S3 Vectors 與 NAT 的整合。
為什麼值得注意
對正在評估代理架構的開發者而言，指南把記憶層、代理工具套件與部署環境放在同一個實作案例中，提供一條具體的整合參考，而非僅介紹單一服務。
來源證據
先看主要證據，再查看佐證來源與來源脈絡。
主要證據
1Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors
Venkata Sistla
“Learn how to use Amazon S3 Vectors as the persistent memory layer within the NVIDIA NeMo Agent Toolkit (NAT), deployed on Amazon Elastic Kubernetes Service (Amazon EKS). This post shows how NAT's memory subsystem works and how to implement Amazon S3 Vectors as a custom memory provider, using a multi-agent investment research use case.”
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