CAMEL is research first. It came from asking what happens when agents talk to each other at scale, and it is built for running those experiments rather than shipping a product on Friday.
Reach for it when
- You are researching multi agent behaviour
- You want to generate synthetic conversation data
- You are interested in agent societies, not one assistant
Look elsewhere when
- You are shipping a product this month
- You want a small, opinionated API
What the lessons will cover
- 01Install and setup
- 02Role playing agents
- 03Societies
- 04Tools
- 05Memory
- 06Data generation
- 07Benchmarks
- 08An experiment end to end
Others in multi agent
CrewAIAgents with a role, a goal and a backstory.
AutoGenAgents that solve problems by talking to each other.
MetaGPTAgents assigned software company roles.Common questions
Is CAMEL-AI free to use?
CAMEL-AI is open source and free to run yourself. You still pay whichever model provider you point it at, and this tutorial is free with no signup.
Do I need to know Python to use CAMEL-AI?
Basic Python is enough. Functions, dictionaries and imports cover most of what CAMEL-AI asks of you.
When should I not use CAMEL-AI?
You are shipping a product this month. You want a small, opinionated API.
Lessons for CAMEL-AI are being written. Meanwhile the LangGraph tutorial covers the same ground: state, tools, loops, memory and human approval. Most of it carries straight over.
Start the LangGraph tutorial →