Introducing Elemental: A Multi-Agent Framework for AI Agent Collaboration and Task Automation

Elemental is a multi-agent framework designed for task automation by facilitating collaboration between AI agents through conversation. It offers various features such as multi-agent task execution, customizable language models, multi-modal messages, customizable templates with variables, a dynamic orchestrator for planning and execution, and more. The framework supports different agent configurations like simple assistants, isolated agents, multi-agent teams, and workflows. Elemental also allows for the integration of MCP tools, external systems interaction, reasoning abilities, and observability of agent events. Agents can be created using Python with specified characteristics and tools depending on the task requirements. The project is maintained by AttoAgents, offering a versatile and dynamic solution for AI agent collaboration and task automation. For setup and operational instructions, refer to the documentation and examples provided on GitHub.