OWL
ActiveDescription
OWL (Optimized Workforce Learning) is a multi-agent collaboration framework for real-world task automation, decomposing and executing complex tasks through agent interaction.
OWL (Optimized Workforce Learning) is a multi-agent collaboration framework for real-world task automation, decomposing and executing complex tasks through agent interaction.
A multi-agent framework enabling AI agents to collaborate effectively, helping developers build powerful multi-agent systems.
ChatDev 2.0 enables full-lifecycle software development through LLM-powered multi-agent collaboration, simulating role-based teamwork in a virtual software company.
An LLM-based multi-agent framework that lets developers easily build multi-agent applications with core abstractions for agent roles, tools, knowledge management, and collaboration patterns.
A multi-agent collaboration framework where AI agents form crews to accomplish complex tasks together. Role definition, task assignment, tool sharing, and process orchestration.