#3636th of 77 in Agent frameworks and SDKs
camel
Python framework for multi-agent systems, role-playing and synthetic data generation
- Stars
- 18k
- License
- Apache-2.0
- Last commit
- Oct 2026
- Last release
- Mar 2026
- Language
- Python
16,302 on 26 Mar 202617,962 on 22 Oct 2026
From GitHub's daily star counts.
Checked on GitHub.
Overview
CAMEL is a Python library, installed with pip install camel-ai, for building LLM agents and multi-agent societies. It provides ChatAgent, role-playing and workforce modules, toolkits, memory, retrievers, interpreters and benchmarks, plus data generation pipelines such as CoT, Self-Instruct and Source2Synth. It is run by a research community studying agent scaling behavior.
Who it is for: Python developers and researchers building multi-agent systems or datasets
Strengths
- Covers agents, societies, memory, retrievers, interpreters and benchmarks in one package
- Built-in synthetic data generation: CoT, Self-Instruct, Source2Synth, self-improving CoT
- Cookbooks and Hugging Face datasets published (AI Society, Code, Math, Physics)
- Installs from PyPI with optional extras such as web_tools
Weaknesses
- Research-oriented; production deployment guidance is not in the README
- Quick start example uses OpenAI and needs an API key
- Claim of simulating up to 1M agents is given without numbers or benchmarks
- No Docker image or compose file
What it needs
- no GPU
- Needs Python, LLM provider API key (e.g. OpenAI)
- Models: OpenAI, multiple LLM backends via ModelFactory
Quick answers
Is camel open source?
Yes. Its code is on GitHub under the Apache-2.0 license.
Does camel need a GPU?
No, it runs without one.
Also in Agent frameworks and SDKs
See all 77| Rank | Project | Score |
|---|---|---|
| 1 | ppt-masterAgent skill that turns documents into natively editable PowerPoint decks | 95 out of 100 |
| 2 | openai-agents-pythonPython SDK for multi-agent workflows with handoffs, guardrails and tracing | 90 out of 100 |
| 3 | mastraTypeScript framework for building AI agents, workflows and MCP servers | 90 out of 100 |
| #4 | langchainPython framework for building LLM agents and apps from interoperable components | 89 out of 100 |
| #5 | browser-usePython library that lets an LLM agent control a web browser | 89 out of 100 |