Multi-agent orchestration system using Claude Code with Git worktree isolation and specialized AI agents for collaborative development

DoctorAgent-RL: A Multi-Agent Collaborative Reinforcement Learning System for Multi-Turn Clinical Dialogue

Official Repo for The Paper "Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems"

This project aims to integrate Crew AI's multi-agent collaboration framework into the ComfyUI environment. By combining the strengths of Crew AI's role-based, collaborative AI agent system with ComfyUI's intuitive interface, we will create a robust platform for managing and executing complex AI tasks seamlessly

A lightweight Python package for managing multi-agent orchestration. Easily define agents with custom instructions, tools, containers, and models, and orchestrate their interactions seamlessly. Perfect for building modular, collaborative AI systems.

Autonomous Intelligence is a framework for building collaborative, intelligent multi agent AI systems. The framework provides a robust infrastructure for creating and managing multiple AI agents, and enables developers and organizations to build, deploy, and optimize AI agents that work well in dynamic, complex environments.

[CVPR 2026] Refer-Agent: A Collaborative Multi-Agent System with Reasoning and Reflection for Referring Video Object Segmentation

卡车-无人机协同配送系统，通过多智能体强化学习(MAPPO)算法优化物流配送效率。系统模拟真实的城市配送场景，其中卡车作为移动补给站，无人机执行最后一公里配送任务。optimized using Multi-Agent Reinforcement Learning (MAPPO) algorithms to enhance logistics delivery efficiency. The system simulates real-world urban delivery scenarios where trucks serve as mobile supply stations, and drones carry out the last-mile delivery tasks

NumCraft - Multi-Agent Collaborative System for Intelligent G-Code Generation

It is an advanced medical CT image analysis system that uses a multi-agent collaborative framework and the latest AI technology to automatically analyze CT images, retrieve medical knowledge, and generate professional diagnostic reports.

Collaborative SLAM for Multi-Agent system in unknown environment

A curated list of awesome applications, tools, and resources for the Swarms framework by swarms.ai. Swarms is a powerful, production-grade framework for orchestrating multi-agent AI systems, enabling developers to build everything from simple autonomous agents to complex, collaborative swarms that can solve real-world problems.

A multi-agent system demonstrating the principles of Mind Evolution through collaborative problem-solving using different LLM providers.

Mandali (मंडली) — Autonomous multi-agent adversarial collaborative system using GitHub Copilot SDK

This repository contains the code samples and practical implementations from the "CODE Presents" webinar "Building Intelligent Multi-Agent Systems with Microsoft's Semantic Kernel." The session demonstrates how to orchestrate collaborative AI agents in .NET, featuring persistent vector memory and MCP tool integration.

Collaborative Multi-Agent AI System with LangGraph

This repository contains the lesson content and code examples for Week 6 of the Ready Tensor Agentic AI Developer Certification Program, focused on building collaborative multi-agent systems.

Collaborative Environment for Development of Reactive Multi-Agent Systems (PT-BR only for now)

Welcome to the Definitive Beginner's Guide to AI Agents and Multi-Agent Systems! This guide is your gateway to understanding the fundamentals of AI agents, their collaborative capabilities, and how they are transforming industries through sophisticated, enterprise-scale solutions.

This repository demonstrates a simple OpenAI Swarm-based system for multi-agent orchestration with Retrieval-Augmented Generation (RAG). It handles tasks like summarization, sentiment analysis, keyword extraction, and document search using FAISS and OpenAI models, showcasing the power of collaborative agents.

MedAgentAudit: Diagnosing and Quantifying Collaborative Failure Modes in Medical Multi-Agent Systems

A collection of demonstrations showcasing different patterns for implementing multi-agent workflows using LangGraph. Each example highlights specific orchestration approaches to help developers understand and build collaborative AI systems.

Multi agent system for demonstrating graph based collaborative multi-agent systems

An intelligent, multi-agent system to autonomously plan, write, edit, fact-check, and publish a complete book using the CrewAI framework and Groq's LLaMA-3-70B model. This AI pipeline mimics the collaborative process of human authors, editors, and publishers to streamline creative book development.

Autosearch is a sophisticated multi-agent system designed to automate and enhance academic research and content generation processes. The project leverages advanced AI capabilities in autogen to create a collaborative environment where specialized agents work together to research, analyze, and produce high-quality academic content.

A Multi-Agent System for Collaborative Dining Decisions

Multi-agent AI narrative simulation. Built with Python, it features a collaborative system of Director, Persona, and Chronicler agents. A custom caching protocol avoids duplicate API calls. Implements thread-safe concurrency, graceful degradation, and comprehensive logging.

A schema-based LLM framework for building multi-agent collaborative systems.

CrewAI-Powered-AI-Agents is a dynamic framework designed to build, manage, and orchestrate multi-agent AI systems using CrewAI. This repository provides a robust foundation for collaborative agents that work together to solve complex tasks autonomously.

This project demonstrates a multi-agent system built using AutoGen and Groq's LLaMA 3 model, designed to automate the analysis of Apple (AAPL) stock's daily closing prices over the past month. The system utilizes a collaborative architecture involving multiple AI agents—each assigned a specific role in the data analysis pipeline.