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 # Preface
 # Preface
 
 
 Since the end of 2022, Large Language Models (LLMs) represented by ChatGPT have swept across the world like a technological tsunami, completely transforming how we interact with artificial intelligence. The powerful natural language understanding and generation capabilities of LLMs have shown us a glimpse of the path toward Artificial General Intelligence (AGI). However, as the initial amazement settled, developers began exploring the next frontier: how to make AI not just a "question-answering" tool, but an "actor" capable of autonomous planning, tool invocation, and solving complex problems?
 Since the end of 2022, Large Language Models (LLMs) represented by ChatGPT have swept across the world like a technological tsunami, completely transforming how we interact with artificial intelligence. The powerful natural language understanding and generation capabilities of LLMs have shown us a glimpse of the path toward Artificial General Intelligence (AGI). However, as the initial amazement settled, developers began exploring the next frontier: how to make AI not just a "question-answering" tool, but an "actor" capable of autonomous planning, tool invocation, and solving complex problems?

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 # 前言
 # 前言
 自 2022 年底以来,以 ChatGPT 为代表的大语言模型(Large Language Model, LLM)如同一场技术海啸,彻底改变了我们与人工智能交互的方式。LLM 强大的自然语言理解和生成能力,让我们看到了通往通用人工智能(AGI)的曙光。然而,当最初的惊艳沉淀下来,开发者们开始探索下一个前沿:如何让 AI 不仅仅是一个“有问必答”的工具,而是成为一个能自主规划、调用工具、解决复杂问题的“行动者”?
 自 2022 年底以来,以 ChatGPT 为代表的大语言模型(Large Language Model, LLM)如同一场技术海啸,彻底改变了我们与人工智能交互的方式。LLM 强大的自然语言理解和生成能力,让我们看到了通往通用人工智能(AGI)的曙光。然而,当最初的惊艳沉淀下来,开发者们开始探索下一个前沿:如何让 AI 不仅仅是一个“有问必答”的工具,而是成为一个能自主规划、调用工具、解决复杂问题的“行动者”?