CAMEL-AI
by CAMEL-AI.org
CAMEL-AI is an open-source framework and research community for studying and building communicative multi-agent systems. Its Python library provides agent abstractions, role-playing workflows, tools, memory, models, and task-oriented agent societies.
Why Abandoned
The official website, GitHub organization, framework repository, and documentation remain publicly available and show ongoing project activity. No verified acquisition or shutdown has been announced.
🩺 Health Signals
- HTTP Status
- 200
- Response
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- SSL
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- Confidence
- 96%
- Domain expires
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- Last content change
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- API status
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📅 Timeline
CAMEL research paper submitted
The foundational paper, “CAMEL: Communicative Agents for Mind Exploration of Large Scale Language Model Society,” was submitted to arXiv, introducing role-playing between communicative agents.
CAMEL paper published at NeurIPS 2023
The CAMEL paper was accepted for the NeurIPS 2023 conference track, establishing the project as an academic framework for studying autonomous cooperative agents.
AI Society and Code datasets released
CAMEL-AI announced the public release of its AI Society and Code datasets on Hugging Face for research into instruction-following and multi-agent interactions.
OASIS simulation framework announced
CAMEL-AI introduced OASIS, an open-source social-media simulation framework designed to model large populations of LLM-based agents.
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Flowise
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❓ Frequently Asked Questions
What is CAMEL-AI?
CAMEL-AI is an open-source framework and research community focused on communicative multi-agent systems. It supports experiments and applications in which language-model agents assume roles, use tools and memory, and cooperate on tasks.
Is CAMEL-AI open source and free to use?
Yes. The CAMEL Python framework is published on GitHub under the Apache License 2.0. Users may still incur charges when connecting it to paid model APIs or external services.
What programming language does CAMEL-AI use?
CAMEL-AI's primary framework is a Python library. Its documentation provides Python installation instructions and examples for configuring agents, models, tools, memories, and multi-agent workflows.
What can developers build with CAMEL-AI?
Developers can build role-playing agent teams, task-planning workflows, tool-using assistants, data-generation pipelines, and agent-based simulations. The project also supports research into cooperation and emergent behavior among language-model agents.
What are the best CAMEL-AI alternatives?
Relevant alternatives include Auto-GPT for autonomous-agent experiments, Dify and Flowise for visual LLM application workflows, and Botpress for building conversational agents. They differ in research focus, deployment model, and low-code support.