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应用：本地模型接入与能力调用》","![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw01.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=gdnTrdMxAsA1ElDdPAOFaqXpVVk%3D)\r\n\r\n\u003Cspan style=\"font-size:12px;color:#555;\">8 月 7 日，2026 夏季 InfiniTensor 训练营 AI 编程与智能体应用方向第七课《AI Agent 应用：本地模型接入与能力调用》开讲。\r\n前置课程《AI Agent 基础：从“会回答”到“能执行任务”的 AI 系统》讲了 AI Agent 的核心概念与工程落地框架，解析 Agent 与普通问答、固定工作流的本质区别。涵盖目标设定、状态管理、工具调用、反馈循环及安全边界等关键模块。\u003C\u002Fspan>\r\n\r\n本节课带你理解 Agent 的工程化本质，拆解 LangChain 支架体系，并通过实战演示打通本地模型与真实系统的安全连接。\r\n\r\n## 核心理念：模型 ≠ 能力\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw02.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=3Tp1cYmAUYDRL%2F8lVSXrow7VBRk%3D)\r\n\r\n在动手之前，必须厘清一个关键认知：**生成正确答案 ≠ 读取事实 ≠ 执行动作**。\r\n\r\n*   **模型的局限**：擅长语言理解、推理规划、生成工具调用意图（大脑）。\r\n*   **工具的补位**：负责查询真实数据、执行受控动作、调用 API（眼睛和手）。\r\n*   **核心差异**：Agent 不是单次问答，而是一个 **“感知-决策-执行-反馈”** 的闭环。模型生成意图，程序负责执行与控制。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw03.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=%2FVewfPWfW3SAV6ddm6m%2FeAMLYk4%3D)\r\n\r\n## LangChain：Agent 运行支架\r\n### 版本演进注意\r\n**1. 避坑指南**：旧版 LLMChain、固定 Chain 类型等已非主线。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw04.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=psMNJ5SNJjc9PPWHibd%2B8EBCtzA%3D)\r\n\r\n**2.当前推荐**：当前 LangChain 新版本推荐使用 create_agent 快速构建 Agent，其底层基于 LangGraph 的图结构执行模型，提供状态管理、持久化和复杂工作流编排能力。\r\n\r\n### 八大核心组件拆解\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw05.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=UqdLhQ9Pq23PTAnACGhLpXnCpBE%3D)\r\n\r\n\r\n| 组件 | 核心作用 | 关键点 |\r\n| :--- | :--- | :--- |\r\n| **Model** | 推理与决策核心 | 本地模型两层结构：Ollama (推理运行时) + ChatOllama (LangChain 接口) |\r\n| **Messages \u002F Prompt** | 模型看到什么 | 四类消息：System\u002FHuman\u002FAI\u002FTool；Prompt 是规则而非能力 |\r\n| **Tools** | 真实能力的封装 | 面向模型的 API 设计；参数明确、返回值结构化、权限边界清晰 |\r\n| **Agent** | 多步执行循环 | 模型判断 → 生成调用 → 程序执行 → 结果回传 → 继续或停止 |\r\n| **Memory\u002FRuntime** | 状态与身份管理 | State(工作台)、Context(环境参数)、Store(长期档案)；线程 ID 隔离 |\r\n| **Structured Output** | 业务契约 | 将自然语言转为可校验的 JSON\u002F数据结构，供下游系统消费 |\r\n| **Streaming** | 实时反馈 | 改善体验、展示进度、辅助调试；用于实时展示模型输出、工具调用事件和 Agent 执行状态 |\r\n| **Middleware** | 工程控制面 | 权限过滤、重试降级、敏感信息遮盖、Human-in-the-loop |\r\n\r\n### 权限控制双层防线\r\n**1. 软约束**：Prompt 告知角色与规则（辅助模型正确选择）。\r\n\r\n**2.硬边界**：程序级权限校验。用户身份来自可信 Runtime，工具可见性动态注入，执行前二次验证。**绝不信任用户输入或模型输出作为凭证**。\r\n\r\n### Context Engineering (上下文工程)\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw06.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=FQB%2FU%2F6Ch4n2u0viq9RxJZrJFrU%3D)\r\n\r\n- 比 Prompt Engineering 范围更大。\r\n- 中间件作为“漏斗”：筛选、压缩、过滤权限、格式化。\r\n- **目标**：给模型“刚刚好”的上下文，既足够完成任务，又不越权、不引入噪声。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw07.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=9X%2BNwVXgxkiTBthC9Soye0jQGXQ%3D)\r\n\r\n## 实战演示\r\n### 1: 模型 vs Agent 的区别\r\n- 对比测试：通用知识问答 vs 本机 Redis 状态确认。\r\n- **结论**：无工具时，模型无法获取实时事实。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw08.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=PW7FAyz9xTbGfXxQuVMjHiufGls%3D)\r\n\r\n### 2: 工具的独立性与安全性\r\n- 直接调用工具接口，验证结构化返回与文件锁记录。\r\n- **结论**：工具行为不依赖模型，`create_restart` 仅生成审批单而非直接重启。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw09.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=SMSlKwmujf410jvhEnVyKDRmYBQ%3D)\r\n\r\n### 3: Agent 循环与消息轨迹\r\n- 观察 Message Type 流转：User → AI (Tool Call) → Tool Result → AI (Final Answer)。\r\n- **结论**：基于可信工具信息整理结果，申请成功 ≠ 执行完成。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw10.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=W3nBub29gWKppvFJ6hxKVq%2FS9Ng%3D)\r\n\r\n### 4：权限注入验证\r\n- 对比 `viewer` 与 `operator` 角色。\r\n- **结论**：Prompt 无法提权；程序层强制拦截 viewer 的写操作请求。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw11.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=8KHIN8qwz112cmijK%2BDPjiui8Wk%3D)\r\n\r\n### 5: Memory 与线程隔离\r\n- 对比 InMemorySaver 与 SqliteSaver，验证不同 Checkpointer 对 Agent 状态持久化能力的区别。\r\n- **结论**：在配置 Checkpointer 后，同一 Thread ID 可以定位并恢复对应 Agent 状态。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw12.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=tiOsddgLAZ0ff1g4KuSMGK3kCsI%3D)\r\n\r\n### 6: 结构化输出\r\n- 验证 JSON Schema 约束下的稳定输出。\r\n- 观察流式反馈过程中的状态更新（非打字机效果，而是执行进度展示）。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw13.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=UfTtqd016j2otRfkjHvOjwzAJcQ%3D)\r\n\r\n### 7：Streaming\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw14.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=%2FT%2Bk%2BlXXOlvPYYtm9l1O%2BOpbfTY%3D)\r\n\r\n### 8: 中间件保存\r\n- 第一层：根据角色动态控制 Agent 可见工具集合，用于减少错误调用。\r\n- 第二层：工具内部再次校验 Runtime 中的可信角色。\r\n- **结论**：纵深防御，确保即使绕过 Agent 也无法越权。\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw15.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=HNFuDBvgbYst8dGUFudAr5noeT4%3D)\r\n\r\n\r\n\r\n\r\n## 加入训练营\r\n📺**完整课程内容，请观看直播或查看课程回放：**\r\n**InfiniTensor 官网**： https:\u002F\u002Fwww.infinitensor.com\r\n\r\n**B站直播**： InfiniTensor 官方直播间\r\n\r\n**视频号直播**： InfiniTensor 视频号预约\r\n\r\n**答疑交流**： 训练营官方社群⬇️\r\n\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002Fqun_1072.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=BXH4UNzWFOrSPQr6JCB10ba6f1k%3D)\r\n\r\n## 关注与交流\r\n![](https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002Fportal_news\u002Fnews_ewm02.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=n%2FSVGJ8eOraf6k1nlkjH0x9NZjY%3D)",{"publishTime":7,"createTime":109,"canonicalPath":114,"id":115,"title":116},"\u002Fstudy-material\u002Fstudy-95","study-95","2026 夏季 InfiniTensor 训练营推理引擎 5：《大模型服务系统》",14,"\u002Fstudy-material\u002Fstudy-96","study-96","markdown",{"publishTime":7,"createTime":109,"canonicalPath":122,"id":123,"title":124},"\u002Fstudy-material\u002Fstudy-97","study-97","2026 夏季 InfiniTensor 训练营前沿模型 4、AI 编程与智能体应用 8：《大模型自主智能体》",{"htmlContent":126,"headings":127},"\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw01.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=gdnTrdMxAsA1ElDdPAOFaqXpVVk%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>\u003Cspan style=\"font-size:12px;color:#555;\">8 月 7 日，2026 夏季 InfiniTensor 训练营 AI 编程与智能体应用方向第七课《AI Agent 应用：本地模型接入与能力调用》开讲。\u003Cbr>前置课程《AI Agent 基础：从“会回答”到“能执行任务”的 AI 系统》讲了 AI Agent 的核心概念与工程落地框架，解析 Agent 与普通问答、固定工作流的本质区别。涵盖目标设定、状态管理、工具调用、反馈循环及安全边界等关键模块。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>本节课带你理解 Agent 的工程化本质，拆解 LangChain 支架体系，并通过实战演示打通本地模型与真实系统的安全连接。\u003C\u002Fp>\n\u003Ch2 id=\"核心理念-模型-能力\">\u003Ca class=\"anchor\" href=\"#核心理念-模型-能力\" aria-label=\"跳转到标题：核心理念：模型 ≠ 能力\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>核心理念：模型 ≠ 能力\u003C\u002Fh2>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw02.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=3Tp1cYmAUYDRL%2F8lVSXrow7VBRk%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>在动手之前，必须厘清一个关键认知：\u003Cstrong>生成正确答案 ≠ 读取事实 ≠ 执行动作\u003C\u002Fstrong>。\u003C\u002Fp>\n\u003Cul>\n\u003Cli>\u003Cstrong>模型的局限\u003C\u002Fstrong>：擅长语言理解、推理规划、生成工具调用意图（大脑）。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>工具的补位\u003C\u002Fstrong>：负责查询真实数据、执行受控动作、调用 API（眼睛和手）。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>核心差异\u003C\u002Fstrong>：Agent 不是单次问答，而是一个 \u003Cstrong>“感知-决策-执行-反馈”\u003C\u002Fstrong> 的闭环。模型生成意图，程序负责执行与控制。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw03.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=%2FVewfPWfW3SAV6ddm6m%2FeAMLYk4%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch2 id=\"langchain-agent-运行支架\">\u003Ca class=\"anchor\" href=\"#langchain-agent-运行支架\" aria-label=\"跳转到标题：LangChain：Agent 运行支架\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>LangChain：Agent 运行支架\u003C\u002Fh2>\u003Ch3 id=\"版本演进注意\">\u003Ca class=\"anchor\" href=\"#版本演进注意\" aria-label=\"跳转到标题：版本演进注意\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>版本演进注意\u003C\u002Fh3>\u003Cp>\u003Cstrong>1. 避坑指南\u003C\u002Fstrong>：旧版 LLMChain、固定 Chain 类型等已非主线。\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw04.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=psMNJ5SNJjc9PPWHibd%2B8EBCtzA%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cp>\u003Cstrong>2.当前推荐\u003C\u002Fstrong>：当前 LangChain 新版本推荐使用 create_agent 快速构建 Agent，其底层基于 LangGraph 的图结构执行模型，提供状态管理、持久化和复杂工作流编排能力。\u003C\u002Fp>\n\u003Ch3 id=\"八大核心组件拆解\">\u003Ca class=\"anchor\" href=\"#八大核心组件拆解\" aria-label=\"跳转到标题：八大核心组件拆解\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>八大核心组件拆解\u003C\u002Fh3>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw05.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=UqdLhQ9Pq23PTAnACGhLpXnCpBE%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth align=\"left\">组件\u003C\u002Fth>\n\u003Cth align=\"left\">核心作用\u003C\u002Fth>\n\u003Cth align=\"left\">关键点\u003C\u002Fth>\n\u003C\u002Ftr>\n\u003C\u002Fthead>\n\u003Ctbody>\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Model\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">推理与决策核心\u003C\u002Ftd>\n\u003Ctd align=\"left\">本地模型两层结构：Ollama (推理运行时) + ChatOllama (LangChain 接口)\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Messages \u002F Prompt\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">模型看到什么\u003C\u002Ftd>\n\u003Ctd align=\"left\">四类消息：System\u002FHuman\u002FAI\u002FTool；Prompt 是规则而非能力\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Tools\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">真实能力的封装\u003C\u002Ftd>\n\u003Ctd align=\"left\">面向模型的 API 设计；参数明确、返回值结构化、权限边界清晰\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Agent\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">多步执行循环\u003C\u002Ftd>\n\u003Ctd align=\"left\">模型判断 → 生成调用 → 程序执行 → 结果回传 → 继续或停止\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Memory\u002FRuntime\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">状态与身份管理\u003C\u002Ftd>\n\u003Ctd align=\"left\">State(工作台)、Context(环境参数)、Store(长期档案)；线程 ID 隔离\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Structured Output\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">业务契约\u003C\u002Ftd>\n\u003Ctd align=\"left\">将自然语言转为可校验的 JSON\u002F数据结构，供下游系统消费\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Streaming\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">实时反馈\u003C\u002Ftd>\n\u003Ctd align=\"left\">改善体验、展示进度、辅助调试；用于实时展示模型输出、工具调用事件和 Agent 执行状态\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr>\n\u003Ctd align=\"left\">\u003Cstrong>Middleware\u003C\u002Fstrong>\u003C\u002Ftd>\n\u003Ctd align=\"left\">工程控制面\u003C\u002Ftd>\n\u003Ctd align=\"left\">权限过滤、重试降级、敏感信息遮盖、Human-in-the-loop\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003C\u002Ftbody>\u003C\u002Ftable>\n\u003Ch3 id=\"权限控制双层防线\">\u003Ca class=\"anchor\" href=\"#权限控制双层防线\" aria-label=\"跳转到标题：权限控制双层防线\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>权限控制双层防线\u003C\u002Fh3>\u003Cp>\u003Cstrong>1. 软约束\u003C\u002Fstrong>：Prompt 告知角色与规则（辅助模型正确选择）。\u003C\u002Fp>\n\u003Cp>\u003Cstrong>2.硬边界\u003C\u002Fstrong>：程序级权限校验。用户身份来自可信 Runtime，工具可见性动态注入，执行前二次验证。\u003Cstrong>绝不信任用户输入或模型输出作为凭证\u003C\u002Fstrong>。\u003C\u002Fp>\n\u003Ch3 id=\"context-engineering-上下文工程\">\u003Ca class=\"anchor\" href=\"#context-engineering-上下文工程\" aria-label=\"跳转到标题：Context Engineering (上下文工程)\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>Context Engineering (上下文工程)\u003C\u002Fh3>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw06.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=FQB%2FU%2F6Ch4n2u0viq9RxJZrJFrU%3D\" alt=\"\">\u003C\u002Fp>\n\u003Cul>\n\u003Cli>比 Prompt Engineering 范围更大。\u003C\u002Fli>\n\u003Cli>中间件作为“漏斗”：筛选、压缩、过滤权限、格式化。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>目标\u003C\u002Fstrong>：给模型“刚刚好”的上下文，既足够完成任务，又不越权、不引入噪声。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw07.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=9X%2BNwVXgxkiTBthC9Soye0jQGXQ%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch2 id=\"实战演示\">\u003Ca class=\"anchor\" href=\"#实战演示\" aria-label=\"跳转到标题：实战演示\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>实战演示\u003C\u002Fh2>\u003Ch3 id=\"1-模型-vs-agent-的区别\">\u003Ca class=\"anchor\" href=\"#1-模型-vs-agent-的区别\" aria-label=\"跳转到标题：1: 模型 vs Agent 的区别\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>1: 模型 vs Agent 的区别\u003C\u002Fh3>\u003Cul>\n\u003Cli>对比测试：通用知识问答 vs 本机 Redis 状态确认。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>结论\u003C\u002Fstrong>：无工具时，模型无法获取实时事实。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw08.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=PW7FAyz9xTbGfXxQuVMjHiufGls%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch3 id=\"2-工具的独立性与安全性\">\u003Ca class=\"anchor\" href=\"#2-工具的独立性与安全性\" aria-label=\"跳转到标题：2: 工具的独立性与安全性\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>2: 工具的独立性与安全性\u003C\u002Fh3>\u003Cul>\n\u003Cli>直接调用工具接口，验证结构化返回与文件锁记录。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>结论\u003C\u002Fstrong>：工具行为不依赖模型，\u003Ccode>create_restart\u003C\u002Fcode> 仅生成审批单而非直接重启。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw09.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=SMSlKwmujf410jvhEnVyKDRmYBQ%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch3 id=\"3-agent-循环与消息轨迹\">\u003Ca class=\"anchor\" href=\"#3-agent-循环与消息轨迹\" aria-label=\"跳转到标题：3: Agent 循环与消息轨迹\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>3: Agent 循环与消息轨迹\u003C\u002Fh3>\u003Cul>\n\u003Cli>观察 Message Type 流转：User → AI (Tool Call) → Tool Result → AI (Final Answer)。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>结论\u003C\u002Fstrong>：基于可信工具信息整理结果，申请成功 ≠ 执行完成。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw10.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=W3nBub29gWKppvFJ6hxKVq%2FS9Ng%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch3 id=\"4-权限注入验证\">\u003Ca class=\"anchor\" href=\"#4-权限注入验证\" aria-label=\"跳转到标题：4：权限注入验证\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>4：权限注入验证\u003C\u002Fh3>\u003Cul>\n\u003Cli>对比 \u003Ccode>viewer\u003C\u002Fcode> 与 \u003Ccode>operator\u003C\u002Fcode> 角色。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>结论\u003C\u002Fstrong>：Prompt 无法提权；程序层强制拦截 viewer 的写操作请求。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw11.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=8KHIN8qwz112cmijK%2BDPjiui8Wk%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch3 id=\"5-memory-与线程隔离\">\u003Ca class=\"anchor\" href=\"#5-memory-与线程隔离\" aria-label=\"跳转到标题：5: Memory 与线程隔离\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>5: Memory 与线程隔离\u003C\u002Fh3>\u003Cul>\n\u003Cli>对比 InMemorySaver 与 SqliteSaver，验证不同 Checkpointer 对 Agent 状态持久化能力的区别。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>结论\u003C\u002Fstrong>：在配置 Checkpointer 后，同一 Thread ID 可以定位并恢复对应 Agent 状态。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw12.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=tiOsddgLAZ0ff1g4KuSMGK3kCsI%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch3 id=\"6-结构化输出\">\u003Ca class=\"anchor\" href=\"#6-结构化输出\" aria-label=\"跳转到标题：6: 结构化输出\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>6: 结构化输出\u003C\u002Fh3>\u003Cul>\n\u003Cli>验证 JSON Schema 约束下的稳定输出。\u003C\u002Fli>\n\u003Cli>观察流式反馈过程中的状态更新（非打字机效果，而是执行进度展示）。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw13.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=UfTtqd016j2otRfkjHvOjwzAJcQ%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch3 id=\"7-streaming\">\u003Ca class=\"anchor\" href=\"#7-streaming\" aria-label=\"跳转到标题：7：Streaming\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>7：Streaming\u003C\u002Fh3>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw14.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=%2FT%2Bk%2BlXXOlvPYYtm9l1O%2BOpbfTY%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch3 id=\"8-中间件保存\">\u003Ca class=\"anchor\" href=\"#8-中间件保存\" aria-label=\"跳转到标题：8: 中间件保存\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>8: 中间件保存\u003C\u002Fh3>\u003Cul>\n\u003Cli>第一层：根据角色动态控制 Agent 可见工具集合，用于减少错误调用。\u003C\u002Fli>\n\u003Cli>第二层：工具内部再次校验 Runtime 中的可信角色。\u003C\u002Fli>\n\u003Cli>\u003Cstrong>结论\u003C\u002Fstrong>：纵深防御，确保即使绕过 Agent 也无法越权。\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002FKB_96_zw15.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=HNFuDBvgbYst8dGUFudAr5noeT4%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch2 id=\"加入训练营\">\u003Ca class=\"anchor\" href=\"#加入训练营\" aria-label=\"跳转到标题：加入训练营\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>加入训练营\u003C\u002Fh2>\u003Cp>📺\u003Cstrong>完整课程内容，请观看直播或查看课程回放：\u003C\u002Fstrong>\u003Cbr>\u003Cstrong>InfiniTensor 官网\u003C\u002Fstrong>： \u003Ca href=\"https:\u002F\u002Fwww.infinitensor.com\">https:\u002F\u002Fwww.infinitensor.com\u003C\u002Fa>\u003C\u002Fp>\n\u003Cp>\u003Cstrong>B站直播\u003C\u002Fstrong>： InfiniTensor 官方直播间\u003C\u002Fp>\n\u003Cp>\u003Cstrong>视频号直播\u003C\u002Fstrong>： InfiniTensor 视频号预约\u003C\u002Fp>\n\u003Cp>\u003Cstrong>答疑交流\u003C\u002Fstrong>： 训练营官方社群⬇️\u003C\u002Fp>\n\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002FKnowledge_Base\u002Fqun_1072.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=BXH4UNzWFOrSPQr6JCB10ba6f1k%3D\" alt=\"\">\u003C\u002Fp>\n\u003Ch2 id=\"关注与交流\">\u003Ca class=\"anchor\" href=\"#关注与交流\" aria-label=\"跳转到标题：关注与交流\">\u003Cspan class=\"octicon octicon-link\">\u003C\u002Fspan>\u003C\u002Fa>关注与交流\u003C\u002Fh2>\u003Cp>\u003Cimg src=\"https:\u002F\u002Foss.infinitensor.com\u002Fprod\u002Fimages\u002Fportal_news\u002Fnews_ewm02.jpg?Expires=1792752562&OSSAccessKeyId=LTAI5t9R6uzvTa69CT92cFvV&Signature=n%2FSVGJ8eOraf6k1nlkjH0x9NZjY%3D\" alt=\"\">\u003C\u002Fp>\n",[128,131,134,136,138,140,143,145,148,151,154,157,160,163,166,169,171],{"id":129,"text":130,"level":110},"核心理念-模型-能力","核心理念：模型 ≠ 能力",{"id":132,"text":133,"level":110},"langchain-agent-运行支架","LangChain：Agent 运行支架",{"id":135,"text":135,"level":9},"版本演进注意",{"id":137,"text":137,"level":9},"八大核心组件拆解",{"id":139,"text":139,"level":9},"权限控制双层防线",{"id":141,"text":142,"level":9},"context-engineering-上下文工程","Context Engineering (上下文工程)",{"id":144,"text":144,"level":110},"实战演示",{"id":146,"text":147,"level":9},"1-模型-vs-agent-的区别","1: 模型 vs Agent 的区别",{"id":149,"text":150,"level":9},"2-工具的独立性与安全性","2: 工具的独立性与安全性",{"id":152,"text":153,"level":9},"3-agent-循环与消息轨迹","3: Agent 循环与消息轨迹",{"id":155,"text":156,"level":9},"4-权限注入验证","4：权限注入验证",{"id":158,"text":159,"level":9},"5-memory-与线程隔离","5: Memory 与线程隔离",{"id":161,"text":162,"level":9},"6-结构化输出","6: 结构化输出",{"id":164,"text":165,"level":9},"7-streaming","7：Streaming",{"id":167,"text":168,"level":9},"8-中间件保存","8: 中间件保存",{"id":170,"text":170,"level":110},"加入训练营",{"id":172,"text":172,"level":110},"关注与交流"]