Langflow is a powerful tool for building and deploying AI-powered agents and workflows.
The agent engineering platform.
TradingAgents: Multi-Agents LLM Financial Trading Framework
Build resilient agents.
AI coworker with memory and collaboration
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
Portable AI agent runtime for the JVM. One @Agent class runs on Spring AI, LangChain4j, Anthropic, or 9 more behind one SPI. Token streaming, tool calls, human approvals, and governance over WebSocket, SSE, gRPC, or WebTransport/HTTP3. Speaks MCP, A2A, and AG-UI.
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Build production-ready AI agents in both Python and Typescript.
Must-read Papers on LLM Agents.
Modular AI HAL (Hardware Abstraction Layer) for Robots
Build, run and scale AI agents like API and microservices
Awesome List for Agentic RL
DATAGEN: AI-driven multi-agent research assistant automating hypothesis generation, data analysis, and report writing.
A compilation of the best multi-agent papers
MultiAgentPPT 是一个集成了 A2A(Agent2Agent)+ MCP(Model Context Protocol)+ ADK(Agent Development Kit) 架构的智能化演示文稿生成系统,支持通过多智能体协作和流式并发机制
For your multi-agent needs
For deep RL and the future of AI.
Large Language Model based Multi-Agents: A Survey of Progress and Challenges (In IJCAI 2024)
🤖 MateClaw — Your second brain with Multi-Agent Orchestration, MCP Protocol, Skills & Memory, Dream, and Multi-Channel Support. Built on Spring AI Alibaba.
A suite of test scenarios for multi-agent reinforcement learning.
Giselle: AI App Builder. Open Source.
轻量级多智能体协作系统 —— AI Agent 开发入门实战项目
Graph Engineering, simplified — with GraphCode. #graphcode
Autonomous multi-agent crypto intelligence & trading ecosystem for Robinhood Chain L2 (EVM #4663) operated via Discord Command Center, Terminal TUI, REST API, & Telegram
Guía de estudio: sistema multiagente con Google ADK, A2A y MCP