Hugging Face Agents Course（智能体课程）

The course is divided into 4 units. These will take you from the basics of agents to a final assignment with a benchmark.

课时

• The Hugging Face Agents Course
• units
  • en
    • bonus-unit1
      • Conclusion [[conclusion]]
      • Let's Fine-Tune Your Model for Function-Calling
      • Introduction
      • What is Function Calling?
    • bonus-unit2
      • AI Agent Observability & Evaluation
      • Bonus Unit 2: Observability and Evaluation of Agents
      • Quiz: Evaluating AI Agents
      • AI Agent Observability and Evaluation
    • bonus-unit3
      • Build Your Own Pokémon Battle Agent
      • Conclusion
      • From LLMs to AI Agents
      • Introduction
      • Launching Your Pokémon Battle Agent
      • The State of the Art in Using LLMs in Games
    • communication
      • Live 1: How the Course Works and First Q&A
    • unit0
      • (Optional) Discord 101 [[discord-101]]
      • Welcome to the 🤗 AI Agents Course [[introduction]]
      • Onboarding: Your First Steps ⛵
    • unit1
      • Actions: Enabling the Agent to Engage with Its Environment
      • Understanding AI Agents through the Thought-Action-Observation Cycle
      • Conclusion [[conclusion]]
      • Dummy Agent Library
      • Unit 1 Quiz
      • Introduction to Agents
      • Messages and Special Tokens
      • Observe: Integrating Feedback to Reflect and Adapt
      • quiz1
      • Quick Self-Check (ungraded) [[quiz2]]
      • Thought: Internal Reasoning and the ReAct Approach
      • What are Tools?
      • Let's Create Our First Agent Using smolagents
      • What is an Agent?
      • What are LLMs?
    • unit2
      • Introduction to Agentic Frameworks
      • langgraph
        • Building Blocks of LangGraph
        • Conclusion
        • Document Analysis Graph
        • Building Your First LangGraph
        • Introduction to LangGraph
        • Test Your Understanding of LangGraph
        • What is LangGraph? [[what-is-langgraph]]
      • llama-index
        • Using Agents in LlamaIndex
        • What are components in LlamaIndex?
        • Conclusion
        • Introduction to LlamaIndex
        • Introduction to the LlamaHub
        • Small Quiz (ungraded) [[quiz1]]
        • Quick Self-Check (ungraded) [[quiz2]]
        • Table of Contents
        • Using Tools in LlamaIndex
        • Creating agentic workflows in LlamaIndex
      • smolagents
        • Building Agents That Use Code
        • Conclusion
        • Exam Time!
        • Introduction to smolagents
        • Multi-Agent Systems
        • Small Quiz (ungraded) [[quiz1]]
        • Small Quiz (ungraded) [[quiz2]]
        • Building Agentic RAG Systems
        • Writing actions as code snippets or JSON blobs
        • Tools
        • Vision Agents with smolagents
        • Why use smolagents
    • unit3
      • agentic-rag
        • Creating Your Gala Agent
        • Agentic Retrieval Augmented Generation (RAG)
        • Conclusion
        • Introduction to Use Case for Agentic RAG
        • Creating a RAG Tool for Guest Stories
        • Building and Integrating Tools for Your Agent
    • unit4
      • And now? What topics I should learn?
      • Conclusion
      • Claim Your Certificate 🎓
      • Hands-On
      • Welcome to the final Unit [[introduction]]
      • What is GAIA?
  • zh-CN
    • bonus_unit2
      • AI 智能体(AI Agent)的可观测性与评估
      • 附加单元 2：AI 智能体(AI Agent)的可观测性与评估
      • 测验：评估 AI 智能体
      • AI 智能体可观测性与评估
    • bonus-unit1
      • 结论 (Conclusion) [[conclusion]]
      • 让我们为函数调用微调模型 (Let's Fine-Tune your model for function-calling)
      • 简介 (Introduction)
      • 什么是函数调用？(What is Function Calling?)
    • bonus-unit3
      • 构建你自己的宝可梦对战智能体
      • 结论
      • 从 LLM 到 AI 智能体
      • 介绍
      • 启动你的宝可梦战斗智能体
      • 游戏中使用 LLM 的最新技术
    • communication
      • 直播第一课：课程体系解读与首次答疑会
      • 后续单元发布时间表及常见问题解答
    • unit0
      • （选读） Discord 101 [[discord-101]]
      • 欢迎加入 🤗 AI Agents 课程 [[introduction]]
      • 启航准备：开启学习之旅 ⛵
    • unit1
      • 动作：使智能体能够与环境交互
      • 通过思考-行动-观察循环理解 AI 智能体 (Understanding AI Agents through the Thought-Action-Observation Cycle)
      • 总结 [[conclusion]]
      • 简单智能体库 (Dummy Agent Library)
      • 第一单元测验 (Unit 1 Quiz)
      • 智能体简介 (Introduction to Agents)
      • 消息和特殊 Tokens (Messages and Special Tokens)
      • Observe: 整合反馈以反思和调整
      • 小测验（不计分）[[quiz1]]
      • 快速自测（不计分）[[quiz2]]
      • 目录
      • 思维机制：内部推理与 ReAct 方法
      • 什么是工具？
      • 使用 smolagents 创建我们的第一个智能体
      • 什么是智能体？
      • 什么是大语言模型（LLMs）？
    • unit2
      • 智能体框架介绍
      • langgraph
        • LangGraph 的核心构建模块
        • 结语
        • 文档分析图
        • 构建你的第一个 LangGraph
        • 欢迎来到 LangGraph 的世界
        • 测试你对 LangGraph 的理解
        • 什么是 LangGraph？
      • llama-index
        • 在 LlamaIndex 中使用智能体
        • LlamaIndex 中的组件是什么？
        • 结语
        • LlamaIndex 简介
        • LlamaHub 简介
        • 小测验（不计分） [[quiz1]]
        • 快速自测（不计分）[[quiz2]]
        • 目录
        • 在 LlamaIndex 中使用工具
        • 在 LlamaIndex 中创建智能工作流
      • smolagents
        • 构建使用代码的智能体
        • 结论
        • 测验时间！
        • smolagents 简介
        • 多智能体系统
        • 小测验 (不计分) [[quiz1]]
        • 小测验（不计分）[[quiz2]]
        • 构建智能驱动的 RAG 系统
        • 将操作编写为代码片段或 JSON 结构
        • 工具
        • 使用 smolagents 构建视觉智能体
        • 为什么选择 smolagents
    • unit3
      • agentic-rag
        • 创建你的 Gala 智能体
        • 智能体增强检索生成（Agentic RAG）
        • 总结
        • 代理增强检索生成（Agentic RAG）用例介绍
        • 创建宾客信息检索生成（RAG）工具
        • 构建并集成智能体工具
    • unit4
      • 那现在呢？我应该学习哪些主题？
      • 结论
      • 领取你的证书 🎓
      • 动手实践
      • 欢迎来到最后一个单元 [[介绍]]
      • 什么是GAIA？

开始学习 → Conclusion [[conclusion]]