Learning Resources AI AgentsLearning Resources

Swarm Tools

🐝 Multi-agent swarm coordination for OpenCode with learning capabilities, agent issue tracking, and management

Langchain1 0 Langgraph1 0 Learning

这是一个 LangChain 1.0 和 LangGraph 1.0 的学习仓库，学习如何进行agent开发，涵盖从基础概念到实战项目的完整学习路径。

BenchMARL

BenchMARL is a library for benchmarking Multi-Agent Reinforcement Learning (MARL). BenchMARL allows to quickly compare different MARL algorithms, tasks, and models while being systematically grounded in its two core tenets: reproducibility and standardization.

Open AgentRL

RLAnything (ICML 2026) & AutoTool (ICML 2026), DemyAgent: Open-Source RL for LLMs and Agentic Scenarios

VectorizedMultiAgentSimulator

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

Deerflow Book

本书围绕 DeerFlow 2.0，从理论到源码，系统讲解如何进行二次开发。(精校)

Learn Workbuddy

从 0 复刻 WorkBuddy-style 桌面 AI 助手 Harness：24 章 Python 教程，覆盖 Agent Loop、工具调用、记忆系统、Sidecar、沙盒审计、DeepSeek/OpenAI 评测轨迹

Agentic AI Systems

Practical system design, tools, and hands-on resources for building Gen-AI agents & agentic AI systems.

LLM Tool Survey

This is the repository for the Tool Learning survey.

LoongFlow

LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks.

MineStudio

MineStudio: A Streamlined Package for Minecraft AI Agent Development

Swytchcode Examples

Swytchcode demo projects with different agents

Sotopia

Sotopia: an Open-ended Social Learning Environment (ICLR 2024 spotlight)

AI Playground

📽️ Code from tutorials presented on the "Code AI with Rok" YouTube channel

Hello Agent System

👋 Hello Agent System — learn enterprise AI agent system design by building every production layer from scratch. 17 bilingual lessons (EN/中文) with tested exercises: tools, architectures, reliability, security, evals, distributed execution, cost, RAG, release ops. 企业级 Agent 系统设计训练营

RL Matrix

Deep Reinforcement Learning in C#

Cs329z Chinese

斯坦福 Stanford CS329Z Engineering AI Agents 中文教程：面向 Python 开发者的 AI 智能体课程，19 讲与 4 项实践，涵盖 LLM、RAG、工具调用、记忆、多智能体、评测与安全。完整 Markdown、在线与离线 HTML。Chinese course notes.

Rl Rvo Nav

[RA-Letter 2022] Reinforcement Learned Distributed Multi-Robot Navigation with Reciprocal Velocity Obstacle Shaped Rewards

Learn Agent

学习Agent开发的笔记，尝试让Agent从可用到可靠

LLM Rl Environments Lil Course

🌱 A little course on Reinforcement Learning Environments for evaluating and training Language Models

Learn Hermes Agent

A 27-chapter hands-on tutorial for building an autonomous AI agent from zero in Python. Agent loop, tool system, memory, skills, MCP, multi-platform gateway, and self-evolution — inspired by Hermes Agent.

LangGraphProjects

This is the official companion repository for the book The Complete LangGraph Blueprint: Build 50+ AI Agents for Business Success. The repository provides source code, practical examples, and resources to help you build dynamic AI agents using LangGraph, a cutting-edge graph-based framework for artificial intelligence workflows.

Easy Data X AI

《Easy Data x AI》是一门面向所有 AI 爱好者的数据与 AI 基础入门课程。通过双轨学习路径，从数据驱动视角学习构建 AI Agent。

Agentic AI Roadmap

A comprehensive AI learning roadmap covering Python fundamentals, mathematics, machine learning, deep learning, LLMs, and agentic systems — focused on hands-on projects, practical tools, and real-world deployment.