🧠 CrewAI Flashcards
CrewAI multi-agent framework helps you coordinate multiple AI agents with clear roles, goals, and tools. In addition, it supports popular LLM providers and simple Python APIs, so teams can build research assistants, planners, and copilots faster. The flashcards below summarize the core ideas and commands.
🤖 What is CrewAI?
A Python framework for multi-agent collaboration using structured roles, goals, tools, and workflows.
🧑💼 What is an Agent?
A specialized entity with a role, goal, tools, and an underlying LLM. It performs tasks autonomously.
🧩 What is a Crew?
A group of agents that work together on a shared objective while the framework coordinates interactions.
🔧 What tools can Agents use?
APIs, web search, custom functions, or memory-augmented chains. Therefore, agents can complete richer tasks.
🧠 Which LLMs are supported?
OpenAI, Anthropic, Hugging Face, Ollama, Cohere, and more via LangChain or direct APIs.
📦 What are common use cases?
Autonomous research, collaborative report generation, planning assistants, and customer support bots.
⚙️ How do I install it?
Use pip:
pip install crewai. Ensure Python 3.10+ is installed beforehand.📋 What is a Task?
An atomic unit of work assigned to an agent. Define the prompt, expected output, and tools.
🔁 What is the agent loop?
The agent receives messages, plans, uses tools if needed, and returns results to the crew. Consequently, progress becomes traceable.
🌐 Is it open-source?
Yes, community-driven under the MIT license. You can contribute via GitHub.
For official docs and examples, visit the
CrewAI documentation
and the CrewAI GitHub repository.
In addition, explore our Uplatz Blog for AI agent tutorials and patterns.
Therefore, the CrewAI multi-agent framework is a solid choice for teams building collaborative assistants and workflows.