# CAMEL-AI > Open-source multi-agent framework for building AI systems focused on data generation, world simulation, and task automation. CAMEL-AI is the world's first open-source multi-agent framework designed for exploring the scaling laws of AI agents. It provides a comprehensive platform for building multi-agent systems focused on data generation, world simulation, and task automation. The framework enables researchers and developers to create sophisticated AI agent interactions through role-playing, workforce management, and RAG pipelines. - **Role Playing Framework** - A unique cooperative agent framework that overcomes challenges like role flipping, assistant repeats, flake replies, and infinite loops through carefully designed prompt engineering and inception prompting techniques. - **Workforce System** - Enables multiple agents to work together to solve complex tasks with customizable configurations, allowing users to quickly set up multi-agent task solving systems. - **Data Generation Modules** - Includes Chain-of-Thought (CoT) data generation, Self-Instruct instruction generation, Source2Synth multi-hop Q&A generation, and self-improving CoT pipelines for creating high-quality synthetic training data. - **OASIS Simulation** - A scalable social media simulator that integrates LLMs with rule-based agents to realistically mimic behavior of up to one million users on platforms like Twitter and Reddit for studying social phenomena. - **Extensive Model Support** - Integrates with major AI providers including OpenAI, Anthropic, Google Gemini, Mistral AI, Cohere, Deepseek, Groq, Ollama, and many more for flexible model selection. - **RAG Pipeline Integration** - Retrieval-Augmented Generation capabilities that enhance task automation by integrating information retrieval with generative AI models for accurate, contextually relevant outputs. - **Graph RAG Support** - Advanced knowledge graph agent capabilities for enhanced reasoning and information retrieval across complex data structures. - **MCP Hub** - Dedicated Model Context Protocol hub for managing and integrating tools with LLMs and AI agents. To get started, install CAMEL via pip and explore the comprehensive documentation and cookbooks. The framework supports various agent types including Chat Agent, Critic Agent, Knowledge Graph Agent, Search Agent, and more. Join the active Discord community with 100+ researchers exploring frontier research in multi-agent systems. ## Features - Role Playing Framework - Workforce Multi-Agent System - Chain-of-Thought Data Generation - Self-Instruct Instruction Generation - Source2Synth Multi-Hop Q&A Generation - Self-Improving CoT Data Generation - OASIS Social Simulation - RAG Pipeline Integration - Graph RAG Support - Knowledge Graph Agent - MCP Hub Integration - Multiple LLM Provider Support - Chat Agent - Critic Agent - Embodied Agent - Search Agent - Task Agent ## Integrations OpenAI, Anthropic, Google Gemini, Mistral AI, Cohere, Deepseek, Groq, Ollama, LiteLLM, Nvidia, SambaNova, Together AI, Qwen, Yi, Zhipu AI, vLLM, Qdrant, Milvus, Composio, Firecrawl, HuggingFace ## Platforms API, DEVELOPER_SDK ## Pricing Open Source ## Links - Website: https://www.camel-ai.org - Documentation: https://docs.camel-ai.org/ - Repository: https://github.com/camel-ai/camel - EveryDev.ai: https://www.everydev.ai/tools/camel-ai