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CrewAI
Editor's PickA multi-agent orchestration framework for coordinating role-based AI agent teams
Agent details
- Kind
- framework
- Framework
- CrewAI
- Autonomy
- autonomous
Tools
- web_search
- file_read
- code_interpreter
- custom_tool
"Role-based agents that actually specialize. CrewAI makes multi-agent coordination feel intentional."
What is CrewAI?
CrewAI is an open-source Python framework for building multi-agent systems where each agent has a defined role, goal, toolset, and backstory. A crew orchestrator coordinates agents across tasks, either sequentially or in a hierarchical manager/worker pattern, making it a practical automation framework for workflows that benefit from agent specialization.
How does it work?
You define agents (researcher, writer, analyst) and tasks (find sources, draft report, fact-check). The Crew class wires them together and handles the execution loop: assigning tasks to agents, passing outputs between them, managing tool calls, and collecting the final result. CrewAI is LLM-agnostic; agents can use Claude, GPT-4, or any LangChain-compatible model.
For developers who need fine-grained control over agent state and branching logic, LangGraph provides a graph-based execution model that handles conditional flows CrewAI’s sequential and hierarchical modes cannot express. For fully autonomous task execution without orchestration code, AutoGPT takes a different approach where the agent determines its own next steps.
When should you use it?
Use CrewAI when you have a multi-step workflow with distinct agent roles (research, writing, review, execution) and want a framework that handles coordination with minimal boilerplate. It suits report generation, content pipelines, data analysis workflows, and any process that maps naturally to a team of specialists.
Frequently asked questions
What is the difference between a CrewAI Agent and a CrewAI Task?
An Agent is a persistent entity with a role, goal, and backstory that shapes how it approaches problems. A Task is a specific unit of work assigned to an agent, with a description and expected output. Agents exist across tasks; tasks execute sequentially or in parallel depending on the crew's process mode (sequential or hierarchical).
Does CrewAI support any LLM, or only OpenAI?
CrewAI supports any LangChain-compatible LLM, including OpenAI, Anthropic Claude, Mistral, Ollama local models, and others. Set the `llm` parameter on each Agent to the LLM instance you want. Claude works well for reasoning-heavy agents.
How does CrewAI handle errors when one agent in a crew fails?
CrewAI supports a `max_iter` parameter on each agent and a `max_rpm` rate limit. When an agent fails a task, it retries up to `max_iter` times. If it still fails, the error propagates to the crew orchestrator, which can be configured to raise an exception or log the failure and continue with the next task.