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camel-ai/camel

⭐ 17711 Python repository created 2023-03-17

CAMEL is an advanced open-source multi-agent framework designed to explore and understand the scaling laws of agents through large-scale simulations and research. It supports the creation and management of multi-agent systems with up to one million agents, enabling researchers to study emergent behaviors, capabilities, and potential risks in complex environments. The framework emphasizes evolvability, scalability, statefulness, and clear code-as-prompt principles to facilitate continuous agent evolution, efficient resource management, and multi-step interactions with environments. CAMEL is community-driven, with over 100 researchers contributing to its development and use. It supports dynamic communication among agents, allowing real-time collaboration to solve intricate tasks. Agents maintain stateful memory to leverage historical context for improved decision-making. The framework also supports multiple benchmarks for rigorous evaluation and reproducibility, and it accommodates various agent types, roles, tasks, models, and environments to support diverse research applications. Researchers can use CAMEL for data generation, task automation, and world simulation. It offers tools for generating structured datasets, automating complex workflows, and simulating realistic multi-agent environments. The framework integrates with external tools and APIs, such as search toolkits, to enhance agent capabilities. Installation is straightforward via PyPI, and the framework provides examples and documentation to help users get started quickly. Overall, CAMEL is a powerful platform for advancing multi-agent system research, enabling large-scale experiments, and fostering a collaborative community focused on understanding agent behaviors and scaling laws.

https://github.com/camel-ai/camel

agentagent-behaviorsagent-collaborationai-societiesartificial-intelligencebenchmarkscommunicative-aicooperative-aidata-generationdeep-learningdynamic-communicationemergent-behaviorsevolvabilitylarge-language-modelslarge-scale-simulationmulti-agent-frameworkmulti-agent-systemsnatural-language-processingreinforcement-learningresearch-communityscalabilityscaling-lawsstateful-memorysupervised-learningsynthetic-datatask-automationworld-simulation

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