CrewAI

CrewAI is a fast, lean Python framework for orchestrating role-playing, autonomous AI agents, uniquely designed to foster collaborative intelligence without relying on other agent frameworks. It empowers developers to create sophisticated multi-agent systems tailored to specific scenarios, offering both high-level simplicity and precise low-level control. This framework is ideal for developers and organizations building complex AI applications requiring secure, scalable, and manageable agent-driven automation, with options for CrewAI Crews (autonomous agents) and CrewAI Flows (event-driven workflows). Users appreciate its independence from other frameworks, leading to a faster and simpler experience. It provides flexible control over agent behavior, task dependencies, and output structures, and supports various LLMs, including local models via Ollama. It offers two powerful, complementary approaches that work seamlessly together to build sophisticated AI applications, Crews and Flows. Crews are teams of AI agents with true autonomy and agency. They work together through role-based collaboration to accomplish complex tasks, providing multi-agent automation, autonomous execution for tasks, and dynamic role assignment for flexible teamwork. Flows, the enterprise and production architecture, are event-driven workflows that deliver precise control over complex automations, enabling granular control for real-world scenarios. It supports secure, consistent state management between tasks, clean integration of AI with production Python code, and conditional branching for complex business logic. The framework also includes CrewAI AMP Suite, a comprehensive bundle for organizations requiring secure, scalable, and easy-to-manage agent-driven automation. Additionally, CrewAI supports various LLMs through different connection options. By default, agents use the OpenAI API. Alternatively, they can be configured to use local models via the Ollama tool, offering flexibility in model choice. It includes official CrewAI Skills, structured instructions that teach coding agents how to scaffold Flows, configure Crews, design agents and tasks, and follow CrewAI patterns.

Framework for orchestrating autonomous AI agents.