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Databricks 介绍 Omnigent 策略：在动作执行前管控智能体成本与风险
Databricks 发文介绍其 Omnigent 策略：通过在动作发生前进行检查，控制智能体的开销与行为。据其描述，策略可设置花费上限、限制工具使用，并在整个会话中累积跟踪风险，达到阈值时要求下一次动作需经批准。文末附有官方博客与 GitHub 实验仓库链接。
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How do you stop an agent from overspending or taking one risky action too many? Omnigent policies can control both cost and behavior by checking actions before they happen. They can set spending limits, restrict tool usage, and track accumulated risk across a session so the next action can require approval once a threshold is reached. 🔗 Learn more in the blog: https://www.databricks.com/blog/contextual-policies-omnigent-using-session-state-better-govern-ai-agents 🔗 GitHub repo for this series: https://github.com/viktoriasemaan/agentic-ai-explained-labs
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