🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

🔍 An LLM-based Multi-agent Framework of Web Search Engine (like Perplexity.ai Pro and SearchGPT)

PraisonAI is a production-ready Multi AI Agents framework, designed to create AI Agents to automate and solve problems ranging from simple tasks to complex challenges. It provides a low-code solution to streamline the building and management of multi-agent LLM systems, emphasising simplicity, customisation, and effective human-agent collaboration.

Harness LLMs with Multi-Agent Programming

A model-driven approach to building AI agents in just a few lines of code.

Koog is the official Kotlin framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments. Koog is based on our AI products expertise and provides proven solutions for complex LLM and AI problems

Open-source Multi-agent Poster Generation from Papers

🏝️ OASIS: Open Agent Social Interaction Simulations with One Million Agents.

A fast and lightweight framework for creating decentralized agents with ease.

An agentic company research tool powered by LangGraph and Tavily that conducts deep diligence on companies using a multi-agent framework. It leverages Google's Gemini 2.0 Flash and OpenAI's GPT-4.1 on the backend for inference.

🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents

Python implementation of a bunch of multi-robot path-planning algorithms.

KaibanJS is a JavaScript-native framework for building and managing multi-agent systems with a Kanban-inspired approach.

Experts.js is the easiest way to create and deploy OpenAI's Assistants and link them together as Tools to create advanced Multi AI Agent Systems with expanded memory and attention to detail.

Agentic-RAG explores advanced Retrieval-Augmented Generation systems enhanced with AI LLM agents.

Resources of our paper "FilmAgent: A Multi-Agent Framework for End-to-End Film Automation in Virtual 3D Spaces". New versions in the making!

[Survey] A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX