AgentMesh provides a modular infrastructure for developers to create networks of AI agents, each focusing on a specific task or domain. Agents can be dynamically discovered and registered at runtime, exchange messages asynchronously, and follow configurable routing rules. The framework handles retries, fallbacks, and error recovery, allowing multi-agent pipelines for data processing, decision support, or conversational use cases. It integrates easily with existing LLMs and custom models via a simple plugin interface.

AutoGen UI is a frontend toolkit designed to render and manage multi-agent conversational flows. It offers ready-made components such as chat windows, agent selectors, message timelines, and debugging panels. Developers can configure multiple AI agents, stream responses in real time, log each step of the conversation, and apply custom styling. It integrates easily with backend orchestration libraries to provide a complete end-to-end interface for building and monitoring AI agent interactions.