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其次,大模型没有天然的执行能力,需要辅以智能体工程来将意图转化为实际操作。工具调用是当前最主流的方式,大模型根据任务需求,生成结构化的函数调用指令,由智能体框架解析后执行相应操作,比如调用天气API、数据库查询、发送邮件等;另一种方式是模拟人类操作,通过视觉识别和模拟操作来"看屏幕、点按钮、填表单"来完成任务,近期大火的豆包手机就是这样完成智能体操作;对于更复杂的任务,智能体还可以配置代码解释器(Code Interpreter / Sandbox),让模型编程运行,这可以极大的扩展智能体的行动边界。

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For well-distributed points, nearest neighbor search is often near O(log⁡n)O(\log n)O(logn) in practice. In the worst case (all points clustered tightly or along a line), it can degrade to O(n)O(n)O(n), but this is uncommon with typical spatial data.

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