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官方來源· AWS Artificial Intelligence· AI· 發布於 2026年9月30日
AWS 示範以 AgentCore Runtime Instances 串接三個代理完成音樂製作流程
AWS 發布技術指南，展示三個 AI 代理如何在同一個 GPU 執行個體與共享檔案系統上，依序完成音樂生成、音訊處理與合規檢查。
完整報導
AWS 於 2026 年 9 月 30 日發布技術指南，示範如何以 Amazon Bedrock AgentCore Runtime Instances 建立多代理音樂製作流程。範例把三個各司其職的代理放在同一個 GPU 執行個體上，透過共享工作階段與檔案系統傳遞音訊及工作成果。
流程分為作曲、交付處理與合規檢查。作曲代理先將製作需求整理成音樂簡報，再使用 ACE-Step 生成音訊；交付代理讀取音檔、測量音訊特性並套用處理；合規代理則獨立複核交付目標，並比對錄音室既有曲庫的相似度。若檢查發現相似內容，流程可要求作曲代理重新生成，再進行檢查。
這篇指南展示的是 Runtime Instances 如何支援代理之間的檔案共享與接力，而不只是多個模型各自回應。AWS 將 Runtime Instances 定位為 Amazon Bedrock AgentCore 的長時間工作負載選項，提供受管理的 EC2 基礎設施、GPU、持久化儲存，以及最長 14 天的工作階段。AWS 先前於 2026 年 8 月 6 日介紹這項運算選項；本次文章則以音樂製作流程示範其實際組合方式。
為什麼值得注意
這個範例具體展示一種多代理工作流程：一個代理產生音訊，其他代理在共享環境中接續處理與檢查。對需要跨步驟傳遞大型檔案或延續長時間工作的開發者而言，這說明了 Runtime Instances 相較短時工作階段的用途。
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 a multi-agent music production pipeline on Amazon Bedrock AgentCore Runtime Instances
Evandro Franco
“Amazon Bedrock AgentCore Runtime Instances gives multi-agent workflows AWS managed EC2 infrastructure with GPUs, persistent volumes, and multi-day sessions. In this post, we deploy a three-agent music production pipeline where the agents colocate on one GPU instance, share a filesystem, and hand work to each other to produce a finished track.”
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