# Multi-Agent

Open Multi-Agent Canvas is an open-source multi-agent chat interface built using Next.js, LangGraph, and CopilotKit. It allows users to manage multiple agents within a dynamic conversation, primarily for travel planning and research. Leveraging advanced technologies, it provides users with an efficient and flexible multi-agent interaction experience. Its open-source nature allows developers to customize and extend it to meet diverse needs, offering high flexibility and scalability.

Gemini Pro Chatbot is a mobile chat application developed based on the Google Gemini Pro AI model. Built with React Native and Expo, it supports real-time streaming responses, code highlighting, and persistent message storage. The application allows users to optimize their chat experience by customizing system prompts and creating AI agents with different personalities. Its main advantages include powerful language understanding, flexible customization options, and cross-platform support, making it suitable for users who want to efficiently utilize AI for conversations and content creation.

PARTNR is a large-scale benchmarking initiative released by Meta FAIR, which includes 100,000 natural language tasks aimed at studying multi-agent reasoning and planning. PARTNR utilizes large language models (LLMs) to generate tasks while minimizing errors through simulation loops. It also supports evaluations of AI agents in collaboration with real human partners, facilitated through human-in-the-loop infrastructure. PARTNR reveals significant limitations of existing LLM-based planners in task coordination, tracking, and recovery from errors, with humans solving 93% of tasks compared to just 30% for LLMs.

AgileCoder is an innovative multi-agent software development framework inspired by the agile methodologies widely used in professional software engineering. Its core principle lies in a task-oriented approach rather than assigning fixed roles to agents. AgileCoder simulates real-world software development by creating a task backlog and dividing the development process into sprints, with each sprint dynamically updating the backlog. AgileCoder supports multiple models, including OpenAI, Azure OpenAI, Anthropic, and self-hosted Ollama models.

MetaGPT is a multi-agent framework that utilizes natural language programming technology to simulate a fully-functional software company team, facilitating rapid development and automated workflows. It represents the latest advancements in AI for software development, significantly enhancing development efficiency and reducing costs. Key benefits of MetaGPT include high levels of automation, multi-agent collaboration, and the capability to tackle complex software development tasks. The product background indicates that MetaGPT aims to provide users with a platform that can quickly respond to development demands using AI technology. Currently, the product seems to be in testing phase, and users can experience the product by joining the waiting list.

JaxMARL is a multi-agent reinforcement learning library that combines ease of use with GPU accelerated performance. It supports common multi-agent reinforcement learning environments and popular benchmark algorithms. The goal is to provide a comprehensive library for evaluating multi-agent reinforcement learning methods and comparing them with related benchmarks. It also introduces SMAX, a simplified version of the popular StarCraft Multi-Agent Challenge environment, which does not require running the StarCraft II game engine.