agent_learning

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A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.｜从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch

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Bilingual (EN/ZH) 23-chapter AI Agent textbook covering tools, memory, planning, RAG, context engineering, agentic RL, multi-agent systems, evaluation, security, and deployment, plus a small runnable reference agent with MCP server and offline tests.

Use Cases

Learning AI agent development from scratchBuilding ReAct-style agent loopsImplementing RAG pipelinesDesigning agent memory systemsRunning multi-agent collaboration experimentsServing agents via MCP server and FastAPIAgentic RL training with GRPOEvaluating and securing agents in productionCapstone: coding, data, and multimodal agentsTeaching agent engineering with runnable reference code

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Language: HTML
Frameworks: LangChain · LangGraph · DSPy · FastAPI · mdBook · MCP · Docker

agent_learning

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