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The first and the best multi-agent framework. Finding the Scaling Law of Agents.

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Type
Open Source

About GitHub

CAMEL is an open-source multi-agent framework designed to study the scaling laws of agents. Developed by the CAMEL-AI community, it supports large-scale simulations with up to 1 million agents, enabling research into emergent behaviors, dynamic communication, and stateful memory. The framework follows a 'Code-as-Prompt' design principle, ensuring that code is interpretable by both humans and agents. It provides tools for data generation, task automation, and world simulation, backed by a community of over 100 researchers. CAMEL is free to use and aims to advance frontier research in multi-agent systems.

Key Features

Large-scale agent systems simulating up to 1 million agents
Dynamic communication enabling real-time interactions among agents
Stateful memory for multi-step interactions and complex tasks
Code-as-Prompt design principle ensuring code readability for both humans and agents
Support for multiple agent types, tasks, prompts, models, and simulated environments
Community-driven with over 100 researchers and open-source contributions

Pros & Cons

Pros
  • Open-source and free to use
  • Scalable architecture supporting up to 1 million agents
  • Stateful memory enables handling of sophisticated, multi-step tasks
  • Dynamic communication fosters seamless agent collaboration
  • Active community driving frontier research in multi-agent systems

Best For

Data generation for training and evaluationTask automation through multi-agent collaborationWorld simulation for studying emergent agent behaviorsResearch on scaling laws and agent capabilities