AWorld: General Multi-Agent Assistance

AWorld is a framework designed to facilitate the building, evaluation, and execution of general multi-agent assistance systems. It aims to bridge the gap between theoretical MAS capabilities and practical real-world applications.

Core Concepts:

• agent: Autonomous AI components for decision-making and collaboration.
• swarm: Defines the topology of a multi-agent system.
• environment: Supports communication between agents and tools.
• task: Runnable work including dataset, agents, environment, and evaluation metrics.
• client: Submits tasks for execution.

Installation:
Requires Python>=3.11.

Key Features:

• Multi-tool support for browsers, Android simulation, shell, code execution, and file systems.
• AI-powered agents with delegation capabilities.
• Standardized protocol compatible with Model Contest Protocol (MCP) and gymnasium standards.

Dual Purpose:

• Agent Evaluation: Standardized benchmarking of agent capabilities.
• Model Training: Continuous improvement through collaborative competition.

AWorld uses a client-server architecture to decouple agents and environments, providing a unified interaction protocol. It supports both agent evaluation and model training, making it a versatile tool for developing and testing multi-agent systems.