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公式動画&関連する動画 [How to Build and Test Multi-Agent Systems in Oracle AI Data Platform]
Build governed multi-agent systems in Oracle AI Data Platform to coordinate specialized AI agents, automate business processes, and validate agent behavior. See how Visual Builder, guardrails, conversation memory, traces, and testing support secure AI development, at the additional resources linked below.
In this tutorial, see how to build, test, and deploy a multi-agent system using Visual Builder in Oracle AI Data Platform. The tutorial shows how a supervisor agent can coordinate specialized executor agents to automate an expense compliance workflow, including evaluating expense reports against company policies and answering spending and budget questions with an Oracle Analytics Cloud connection.
See how to connect agents and other components on the visual canvas, configure guardrails to block potentially unsafe content and prompt injection attempts, and manage how conversation history is shared across agents. The tutorial also covers private state isolation, which maintains separate conversation histories between executor agents and the supervisor agent, as well as limiting conversation history to the last 20 messages.
Testing in the Playground helps validate the complete multi-agent workflow or individual agents independently. Traces provide visibility into how the supervisor agent delegates tasks to executor agents and assembles responses, while guardrail testing verifies protections for incoming messages and generated responses. The tutorial concludes by showing how deployment makes the agent available for production use on the selected AI compute and provides endpoint URLs for communicating with the deployed agent. Together, these capabilities support governed, collaborative multi-agent applications through a visual, low-code development experience.
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