Knowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.
Neuro AI System of Agent Networks
Approving is an open-source, self-hostable platform for turning coding agents into visual, reviewable, and recoverable delivery workflows. Agents run in real Docker sandboxes, exchange structured artifacts, and pause for human Approve at critical nodes.
Codes accompanying the paper "Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning" (NeurIPS 2021 Spotlight https://arxiv.org/abs/2106.03400)
layer that lets you connect any agent, any tool, any api together.
OpenAI-compatible multi-account Codex and vibe coding proxy
Communication using GNN in MARL
HyDRA: Hybrid Dynamic RAG Agents, An advanced, agentic AI framework that transforms Retrieval-Augmented Generation from a static pipeline into a dynamic, learning reasoning system.
Multi-Agent Reinforcement Learning Environment for the card game SkyJo, compatible with PettingZoo and RLLIB
ShoppingClaw(虾购)是采用Langgraph架构设计的Mutil-agent电商智能消费决策系统。集成京东开放平台API为用户提供个性化商品推荐、精准导购等服务。
Landscape of AI agents, software using agents and companies that develop agent related products.
A Platform where user can speak confidently without hesitation. Its an Group Discussion where opponents are the AI , its for the introverts and the people who don't have the confidence to speak with real people.
Open-source multi-agent simulation engine to predict society-level response to launches, crises, campaigns, and narratives.
Basic Multiagents that collects, processes, and analyzes data to extract meaningful insights .Basic project only
A comprehensive enterprise orchestration framework for building AI-powered development teams using Claude Code.
Agentic Customer Support Orchestrator
基于 FastAPI + Vue 3 + LangGraph 的多 Agent 研究助手。项目以最小可理解的工程结构实现了规划、研究、写作三个 Agent 的协作流程，并提供前后端分离的聊天界面、SSE 流式响应、多会话管理和 LangGraph checkpoint 持久化能力。
A fast, eldritch-themed TUI that drives a multi-LLM coding workflow: Claude Code implements, Codex adversarially reviews: every loop grounded in ./check.sh.
一个支持"模型自动处理 + 人工干预确认"的多模型协作系统，通过规划模型、人工反馈环节、执行模型、输出模型的协同，将用户输入的问题/需求转化为结构化处理流程，经人工确认后执行，最终生成符合预期的结果。
Add a description, image, and links to the mutli-agent topic page so that developers can more easily learn about it.
To associate your repository with the mutli-agent topic, visit your repo's landing page and select "manage topics."