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Agent 面试题","","AI Agent 面试题：智能体架构、工具调用、任务规划、记忆机制与多智能体协作。",18,false,{"permalink":98,"postCount":73,"visiblePostCount":73},"\u002Fcategories\u002Fai-agent",[100,124,145,166,187],{"metadata":101,"spec":104,"status":113,"categories":118},{"name":102,"creationTimestamp":103},"post-agent-framework-211695a1","2026-09-13T10:01:18.600522Z",{"title":105,"slug":106,"cover":93,"excerpt":107,"publishTime":109,"categories":110,"tags":111,"priority":27,"pinned":96,"deleted":96,"visible":112,"allowComment":108},"主流的 AI Agent 框架有哪些？","agent-framework",{"raw":93,"autoGenerate":108},true,"2026-09-13T10:01:18.665516Z",[87],[],"PUBLIC",{"permalink":114,"excerpt":115,"lastModifyTime":116,"phase":117},"\u002Farchives\u002Fagent-framework","一、LangChain \u002F LangGraph LangChain：LLM 应用编排，支持工具、记忆、RAG。 LangGraph：基于图的 Agent 编排，适合复杂多步任务。 生态最丰富，社区活跃。 二、AutoGen 微软出品，多 Agent 对话框架。 支持多个 Agent 协作，角色灵活。","2026-09-16T09:33:09.815089Z","PUBLISHED",[119],{"metadata":120,"spec":122,"status":123,"postCount":73},{"name":87,"creationTimestamp":88,"labels":121},{"haloweb.section":90},{"displayName":92,"slug":87,"cover":93,"description":94,"priority":95,"hideFromList":96,"preventParentPostCascadeQuery":96},{"permalink":98,"postCount":73,"visiblePostCount":73},{"metadata":125,"spec":128,"status":135,"categories":139},{"name":126,"creationTimestamp":127},"post-agent-memory-1d1c7ff2","2026-09-13T10:01:18.406204Z",{"title":129,"slug":130,"cover":93,"excerpt":131,"publishTime":132,"categories":133,"tags":134,"priority":27,"pinned":96,"deleted":96,"visible":112,"allowComment":108},"AI Agent 的记忆机制？","agent-memory",{"raw":93,"autoGenerate":108},"2026-09-13T10:01:18.453521Z",[87],[],{"permalink":136,"excerpt":137,"lastModifyTime":138,"phase":117},"\u002Farchives\u002Fagent-memory","一、短期记忆 当前对话上下文。 受 LLM 上下文窗口限制。 太长会丢失早期信息，浪费 token。 二、长期记忆 向量数据库存储历史交互、知识。 检索相关记忆注入上下文。 支持跨会话记忆。 三、记忆类型 情景记忆：具体的交互经历。 语义记忆：事实和知识。 程序记忆：技能和流程。 四、记忆管理 写入","2026-09-16T09:17:13.287981Z",[140],{"metadata":141,"spec":143,"status":144,"postCount":73},{"name":87,"creationTimestamp":88,"labels":142},{"haloweb.section":90},{"displayName":92,"slug":87,"cover":93,"description":94,"priority":95,"hideFromList":96,"preventParentPostCascadeQuery":96},{"permalink":98,"postCount":73,"visiblePostCount":73},{"metadata":146,"spec":149,"status":156,"categories":160},{"name":147,"creationTimestamp":148},"post-agent-tools-15bf488c","2026-09-13T10:01:18.248931Z",{"title":150,"slug":151,"cover":93,"excerpt":152,"publishTime":153,"categories":154,"tags":155,"priority":27,"pinned":96,"deleted":96,"visible":112,"allowComment":108},"AI Agent 如何调用工具？","agent-tools",{"raw":93,"autoGenerate":108},"2026-09-13T10:01:18.294818Z",[87],[],{"permalink":157,"excerpt":158,"lastModifyTime":159,"phase":117},"\u002Farchives\u002Fagent-tools","一、Function Calling LLM 支持的函数调用能力。开发者定义工具 schema（名称、参数、描述），LLM 决定是否调用及参数，返回结构化 JSON。 二、流程 定义工具：名称、描述、参数 JSON Schema。 用户提问，LLM 判断需要调用工具。 LLM 返回工具名和参数。 应","2026-09-16T09:17:12.839579Z",[161],{"metadata":162,"spec":164,"status":165,"postCount":73},{"name":87,"creationTimestamp":88,"labels":163},{"haloweb.section":90},{"displayName":92,"slug":87,"cover":93,"description":94,"priority":95,"hideFromList":96,"preventParentPostCascadeQuery":96},{"permalink":98,"postCount":73,"visiblePostCount":73},{"metadata":167,"spec":170,"status":177,"categories":181},{"name":168,"creationTimestamp":169},"post-agent-react-f2f15e6c","2026-09-13T10:01:18.038102Z",{"title":171,"slug":172,"cover":93,"excerpt":173,"publishTime":174,"categories":175,"tags":176,"priority":27,"pinned":96,"deleted":96,"visible":112,"allowComment":108},"ReAct 模式是什么？","agent-react",{"raw":93,"autoGenerate":108},"2026-09-13T10:01:18.084028Z",[87],[],{"permalink":178,"excerpt":179,"lastModifyTime":180,"phase":117},"\u002Farchives\u002Fagent-react","一、定义 ReAct = Reasoning + Acting，是 Agent 的经典工作模式。交替进行推理和行动。 二、流程 Thought（思考）：分析当前状态，决定下一步。 Action（行动）：调用工具或执行操作。 Observation（观察）：获取执行结果。 循环 1-3，直到任务完成。","2026-09-16T09:17:12.241046Z",[182],{"metadata":183,"spec":185,"status":186,"postCount":73},{"name":87,"creationTimestamp":88,"labels":184},{"haloweb.section":90},{"displayName":92,"slug":87,"cover":93,"description":94,"priority":95,"hideFromList":96,"preventParentPostCascadeQuery":96},{"permalink":98,"postCount":73,"visiblePostCount":73},{"metadata":188,"spec":191,"status":198,"categories":202},{"name":189,"creationTimestamp":190},"post-agent-what-d43685b5","2026-09-13T10:01:17.835540Z",{"title":192,"slug":193,"cover":93,"excerpt":194,"publishTime":195,"categories":196,"tags":197,"priority":27,"pinned":96,"deleted":96,"visible":112,"allowComment":108},"什么是 AI Agent？","agent-what",{"raw":93,"autoGenerate":108},"2026-09-13T10:01:17.878824Z",[87],[],{"permalink":199,"excerpt":200,"lastModifyTime":201,"phase":117},"\u002Farchives\u002Fagent-what","一、定义 AI Agent 是能感知环境、自主决策并执行动作的智能体。它能基于目标，自主规划、调用工具、执行任务，而不仅仅是回答问题。 二、核心能力 感知：理解用户输入和环境状态。 规划：把目标拆解为步骤。 记忆：短期（对话上下文）和长期（向量库）记忆。 工具调用：调用搜索、代码执行、API 等工具","2026-09-16T09:17:11.805159Z",[203],{"metadata":204,"spec":206,"status":207,"postCount":73},{"name":87,"creationTimestamp":88,"labels":205},{"haloweb.section":90},{"displayName":92,"slug":87,"cover":93,"description":94,"priority":95,"hideFromList":96,"preventParentPostCascadeQuery":96},{"permalink":98,"postCount":73,"visiblePostCount":73},{"metadata":209,"spec":210,"status":214,"categories":215,"content":221},{"name":102,"creationTimestamp":103},{"title":105,"slug":106,"cover":93,"excerpt":211,"publishTime":109,"categories":212,"tags":213,"priority":27,"pinned":96,"deleted":96,"visible":112,"allowComment":108},{"raw":93,"autoGenerate":108},[87],[],{"permalink":114,"excerpt":115,"lastModifyTime":116,"phase":117},[216],{"metadata":217,"spec":219,"status":220,"postCount":73},{"name":87,"creationTimestamp":88,"labels":218},{"haloweb.section":90},{"displayName":92,"slug":87,"cover":93,"description":94,"priority":95,"hideFromList":96,"preventParentPostCascadeQuery":96},{"permalink":98,"postCount":73,"visiblePostCount":73},{"content":222,"raw":222},"\u003Ch2 style=\"\" id=\"%E4%B8%80%E3%80%81langchain-%2F-langgraph\">一、LangChain \u002F LangGraph\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">LangChain：LLM 应用编排，支持工具、记忆、RAG。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">LangGraph：基于图的 Agent 编排，适合复杂多步任务。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">生态最丰富，社区活跃。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2 style=\"\" id=\"%E4%BA%8C%E3%80%81autogen\">二、AutoGen\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">微软出品，多 Agent 对话框架。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">支持多个 Agent 协作，角色灵活。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">适合复杂任务拆解。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2 style=\"\" id=\"%E4%B8%89%E3%80%81crewai\">三、CrewAI\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">面向多 Agent 协作，定义角色和任务。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">简洁易用。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2 style=\"\" id=\"%E5%9B%9B%E3%80%81llamaindex\">四、LlamaIndex\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">数据框架，擅长 RAG。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">也支持 Agent。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2 style=\"\" id=\"%E4%BA%94%E3%80%81semantic-kernel\">五、Semantic Kernel\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">微软出品，.NET\u002FPython。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">企业级，与 Azure 集成好。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2 style=\"\" id=\"%E5%85%AD%E3%80%81openai-agents-sdk\">六、OpenAI Agents SDK\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">OpenAI 官方，轻量。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">原生支持 Function Calling、HandOff（Agent 间交接）。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2 style=\"\" id=\"%E4%B8%83%E3%80%81%E9%80%89%E6%8B%A9\">七、选择\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">快速原型 → LangChain。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">复杂编排 → LangGraph \u002F AutoGen。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">RAG 为主 → LlamaIndex。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">企业 .NET → Semantic Kernel。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Ch2 style=\"\" id=\"%E5%85%AB%E3%80%81%E8%B6%8B%E5%8A%BF\">八、趋势\u003C\u002Fh2>\u003Cul>\u003Cli>\u003Cp style=\"\">多 Agent 协作。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">标准化 Agent 协议（MCP）。\u003C\u002Fp>\u003C\u002Fli>\u003Cli>\u003Cp style=\"\">端到端 Agent 开发平台。\u003C\u002Fp>\u003C\u002Fli>\u003C\u002Ful>\u003Cp style=\"\">\u003C\u002Fp>"]