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ScriptsMar 31, 2026·2 min de lecture

CAMEL — Multi-Agent Framework at Scale

CAMEL is a multi-agent framework for studying scaling laws of AI agents. 16.6K+ GitHub stars. Up to 1M agents, RAG, memory systems, data generation. Apache 2.0.

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Introduction

CAMEL is an open-source multi-agent framework dedicated to finding the scaling laws of AI agents. With 16,600+ GitHub stars and Apache 2.0 license, CAMEL enables large-scale agent simulation (up to 1 million agents), dynamic inter-agent communication, stateful memory systems, RAG support, integrated tool and data generation, and diverse agent types and environments. Built for researchers and developers studying cooperative AI, task automation, and world simulation at scale.

Best for: Researchers and developers building multi-agent systems, cooperative AI, or large-scale simulations Works with: Claude Code, OpenAI Codex, Cursor, Gemini CLI, Windsurf Scale: Up to 1M agents in simulation

Key Features

  • 1M agent scale: Simulate up to one million interacting agents
  • Dynamic communication: Inter-agent messaging and coordination
  • Stateful memory: Persistent memory systems for agents
  • RAG support: Retrieval-augmented generation built in
  • Data generation: Automated data creation from agent interactions
  • Multiple benchmarks: Evaluate agent capabilities systematically
  • Tool integration: Agents can use external tools and APIs

FAQ

Q: What is CAMEL? A: CAMEL is a multi-agent framework with 16.6K+ stars for studying AI agent scaling laws. Supports up to 1M agents, RAG, memory systems, and data generation. Apache 2.0.

Q: How do I install CAMEL? A: pip install camel-ai. Create agents with ChatAgent and orchestrate multi-agent conversations.

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Source et remerciements

Created by CAMEL-AI. Licensed under Apache 2.0. camel-ai/camel — 16,600+ GitHub stars

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