AI automated workflow

muAgent is an innovative Agent framework driven by a knowledge graph engine that supports multi-Agent orchestration and collaboration technology. It uses LLM+EKG (Eventic Knowledge Graph industry knowledge bearing) technology, combined with FunctionCall, CodeInterpreter, etc., to realize the automation of complex SOP processes through canvas drag and light text writing. muAgent is compatible with various Agent frameworks on the market and has core functions such as complex reasoning, online collaboration, manual interaction, and ready-to-use knowledge. This framework has been verified in multiple complex DevOps scenarios of Ant Group.

multi-agent-concierge is a multi-agent concierge system that uses multiple specialized agents to complete complex tasks and a "concierge" agent to guide users to the correct agent. Such systems are designed to handle multiple tasks with interdependencies, using hundreds of tools. The system demonstrates how to create implicit "chains" between agents through natural language instructions and manage these chains through "continuation" agents, while using global state to track users and their current status.

IoAI (Internet of Agents) is an intelligent agent interconnection framework that aims to achieve automated collaboration between different intelligent agents through a highly modular design. It allows developers to quickly integrate third-party intelligent agents and perform task allocation and execution through a unified interface. The core advantage of IoA is its flexibility and scalability, supporting a variety of application scenarios, including but not limited to collaborative paper writing, benchmark testing, and open instruction data sets.

AutoGPT is a powerful tool that allows users to create and run intelligent agents that can automate various tasks and make life easier. The goal of AutoGPT is to provide tools that allow users to focus on what matters. It pushes the frontiers of AI innovation by building and using AI agents.

llama-agents is an asynchronous-first framework for building, iterating, and productionizing multi-agent systems, including multi-agent communication, distributed tool execution, artificial-in-the-loop, and more. Each agent is treated as a service, constantly processing incoming tasks. Agents pull and publish messages from the message queue. At the top of the system is the control plane, which keeps track of ongoing tasks, services in the network, and decides which service should handle the next step of the task.

Agent-E is a system based on the AutoGen agent framework designed to automate operations on the user's computer, currently focusing on in-browser automation. It interacts with web browsers through natural language to perform operations such as filling out forms, searching and sorting e-commerce products, locating website content, managing playback settings, performing web searches, and managing project management platform tasks. Agent-E is growing and can handle a variety of tasks, but the best tasks are discovered by users themselves.

Agent Mode is a feature of Warp AI that allows users to complete multi-step workflows in the terminal using natural language. It recognizes and interprets natural language instructions, provides context-specific guidance, and guides users through multi-step tasks. Agent Mode utilizes OpenAI's API but does not store or retain user input or output data.

LaVague aims to redefine the internet browsing experience by converting natural language instructions into seamless browser interactions. It leverages natural language processing and Selenium integration to enable users or other AI to easily express web workflows and execute them on the browser.