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

🏝️ OASIS: Open Agent Social Interaction Simulations with One Million Agents. https://oasis.camel-ai.org
https://github.com/camel-ai/oasis

agent-based-framework agent-based-simulation ai-societies deep-learning large-language-models large-scale llm-agents multi-agent-systems natural-language-processing

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🏝️ OASIS: Open Agent Social Interaction Simulations with One Million Agents. https://oasis.camel-ai.org

Host: GitHub
URL: https://github.com/camel-ai/oasis
Owner: camel-ai
License: apache-2.0
Created: 2024-11-13T05:20:49.000Z (6 months ago)
Default Branch: main
Last Pushed: 2025-05-09T07:05:00.000Z (16 days ago)
Last Synced: 2025-05-09T08:22:57.941Z (16 days ago)
Topics: agent-based-framework, agent-based-simulation, ai-societies, deep-learning, large-language-models, large-scale, llm-agents, multi-agent-systems, natural-language-processing
Language: Python
Homepage: https://docs.oasis.camel-ai.org/
Size: 121 MB
Stars: 1,415
Watchers: 15
Forks: 144
Open Issues: 32
Metadata Files:
- Readme: README.md
- License: LICENSE

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README

        


  

    

  





 OASIS: Open Agent Social Interaction Simulations with One Million Agents



[![Documentation][docs-image]][docs-url]

[![Discord][discord-image]][discord-url]

[![X][x-image]][x-url]

[![Reddit][reddit-image]][reddit-url]

[![Wechat][wechat-image]][wechat-url]

[![Wechat][oasis-image]][oasis-url]

[![Hugging Face][huggingface-image]][huggingface-url]

[![Star][star-image]][star-url]

[![Package License][package-license-image]][package-license-url]



[Community](https://github.com/camel-ai/camel#community) |

[Paper](https://arxiv.org/abs/2411.11581) |

[Examples](https://github.com/camel-ai/oasis/tree/main/scripts) |

[Dataset](https://huggingface.co/datasets/oasis-agent/oasis-dataset) |

[Citation](https://github.com/camel-ai/oasis#-citation) |

[Contributing](https://github.com/camel-ai/oasis#-contributing-to-oasis) |

[CAMEL-AI](https://www.camel-ai.org/)










  

🏝️ OASIS is a scalable, open-source social media simulator that incorporates large language model agents to realistically mimic the behavior of up to one million users on platforms like Twitter and Reddit. It's designed to facilitate the study of complex social phenomena such as information spread, group polarization, and herd behavior, offering a versatile tool for exploring diverse social dynamics and user interactions in digital environments.








🌟 Star OASIS on GitHub and be instantly notified of new releases.








    

  






## ✨ Key Features

### 📈 Scalability

OASIS supports simulations of up to ***one million agents***, enabling studies of social media dynamics at a scale comparable to real-world platforms.

### 📲 Dynamic Environments

Adapts to real-time changes in social networks and content, mirroring the fluid dynamics of platforms like **Twitter** and **Reddit** for authentic simulation experiences.

### 👍🏼 Diverse Action Spaces

Agents can perform **23 actions**, such as following, commenting, and reposting, allowing for rich, multi-faceted interactions.

### 🔥 Integrated Recommendation Systems

Features **interest-based** and **hot-score-based recommendation algorithms**, simulating how users discover content and interact within social media platforms.




## 📺 Demo Video

### Introducing OASIS: Open Agent Social Interaction Simulations with One Million Agents

https://github.com/user-attachments/assets/3bd2553c-d25d-4d8c-a739-1af51354b15a




For more showcaes:

- Can 1,000,000 AI agents simulate social media?

  [→Watch demo](https://www.youtube.com/watch?v=lprGHqkApus&t=2s)




## 🎯 Usecase



    

    

   

    

   

    



## ⚙️ Quick Start

1. **Install the OASIS package:**

Installing OASIS is a breeze thanks to its availability on PyPI. Simply open your terminal and run:

```bash

pip install camel-oasis

```

2. **Set up your OpenAI API key:**

```bash

# For Bash shell (Linux, macOS, Git Bash on Windows):

export OPENAI_API_KEY=

# For Windows Command Prompt:

set OPENAI_API_KEY=

```

3. **Prepare the agent profile file:**

Create the profile you want to assign to the agent. As an example, you can download [user_data_36.json](https://github.com/camel-ai/oasis/blob/main/data/reddit/user_data_36.json) and place it in your local `./data/reddit` folder.

4. **Run the following Python code:**

```python

import asyncio

import os

from camel.models import ModelFactory

from camel.types import ModelPlatformType, ModelType

import oasis

from oasis import ActionType, EnvAction, SingleAction

async def main():

  # Define the model for the agents

  openai_model = ModelFactory.create(

      model_platform=ModelPlatformType.OPENAI,

      model_type=ModelType.GPT_4O_MINI,

  )

  # Define the available actions for the agents

  available_actions = [

      ActionType.LIKE_POST,

      ActionType.CREATE_POST,

      ActionType.CREATE_COMMENT,

      ActionType.FOLLOW

  ]

  # Make the environment

  env = oasis.make(

      platform=oasis.DefaultPlatformType.REDDIT,

      database_path="reddit_simulation.db",

      agent_profile_path="./data/reddit/user_data_36.json",

      agent_models=openai_model,

      available_actions=available_actions,

  )

  # Run the environment

  await env.reset()

  action = SingleAction(

    agent_id=0,

    action=ActionType.CREATE_POST,

    args={"content": "Welcome to the OASIS World!"}

  )

  env_actions = EnvAction(

    activate_agents=list(range(10)),  # activate the first 10 agents

    intervention=[action]

  )

  # Apply interventions to the environment, refresh the recommendation system, and LLM agent perform actions

  await env.step(env_actions)

  # Close the environment

  await env.close()

if __name__ == "__main__":

  asyncio.run(main())

```




> \[!TIP\]

> For more detailed instructions and additional configuration options, check out the [documentation](https://docs.oasis.camel-ai.org/).

### More Tutorials

To discover how to create profiles for large-scale users, as well as how to visualize and analyze social simulation data once your experiment concludes, please refer to [More Tutorials](examples/experiment/user_generation_visualization.md) for detailed guidance.



  



## 📢 News

### Upcoming Features & Contributions

> We welcome community contributions! Join us in building these exciting features.

- [Support Multi Modal Platform](https://github.com/camel-ai/oasis/issues/47)

- [Connect to the Real World](https://github.com/camel-ai/oasis/issues/79)

### Latest Updates

📢 Refactor into the OASIS environment, publish camel-oasis on PyPI, and release the documentation. - 📆 April 24, 2025

- Support OPENAI Embedding model for Twhin-Bert Recommendation System. - 📆 March 25, 2025

- Updated social media links and QR codes in the README! Join OASIS & CAMEL on WeChat, X, Reddit, and Discord. - 📆 March 24, 2025

- Add multi-threading support to speed up LLM inference by 13x - 📆 March 4, 2025

- Slightly refactoring the database to add Quote Action and modify Repost Action - 📆 January 13, 2025

- Added the demo video and oasis's star history in the README - 📆 January 5, 2025

- Introduced an Electronic Mall on the Reddit platform - 📆 December 5, 2024

- OASIS initially released on arXiv - 📆 November 19, 2024

- OASIS GitHub repository initially launched - 📆 November 19, 2024

## 🥂 Contributing to OASIS🏝️

> We greatly appreciate your interest in contributing to our open-source initiative. To ensure a smooth collaboration and the success of contributions, we adhere to a set of contributing guidelines similar to those established by CAMEL. For a comprehensive understanding of the steps involved in contributing to our project, please refer to the CAMEL [contributing guidelines](https://github.com/camel-ai/camel/blob/master/CONTRIBUTING.md). 🤝🚀

>

> An essential part of contributing involves not only submitting new features with accompanying tests (and, ideally, examples) but also ensuring that these contributions pass our automated pytest suite. This approach helps us maintain the project's quality and reliability by verifying compatibility and functionality.

## 📬 Community & Contact

If you're keen on exploring new research opportunities or discoveries with our platform and wish to dive deeper or suggest new features, we're here to talk. Feel free to get in touch for more details at [email protected].




- Join us ([*Discord*](https://discord.camel-ai.org/) or [*WeChat*](https://ghli.org/camel/wechat.png)) in pushing the boundaries of finding the scaling laws of agents.

- Join WechatGroup for further discussions!



  



## 🌟 Star History

[![Star History Chart](https://api.star-history.com/svg?repos=camel-ai/oasis&type=Date)](https://star-history.com/#camel-ai/oasis&Date)

## 🔗 Citation

```

@misc{yang2024oasisopenagentsocial,

      title={OASIS: Open Agent Social Interaction Simulations with One Million Agents},

      author={Ziyi Yang and Zaibin Zhang and Zirui Zheng and Yuxian Jiang and Ziyue Gan and Zhiyu Wang and Zijian Ling and Jinsong Chen and Martz Ma and Bowen Dong and Prateek Gupta and Shuyue Hu and Zhenfei Yin and Guohao Li and Xu Jia and Lijun Wang and Bernard Ghanem and Huchuan Lu and Chaochao Lu and Wanli Ouyang and Yu Qiao and Philip Torr and Jing Shao},

      year={2024},

      eprint={2411.11581},

      archivePrefix={arXiv},

      primaryClass={cs.CL},

      url={https://arxiv.org/abs/2411.11581},

}

```

## 🙌 Acknowledgment

We would like to thank Douglas for designing the logo of our project.

## 🖺 License

The source code is licensed under Apache 2.0.

[discord-image]: https://img.shields.io/discord/1082486657678311454?logo=discord&labelColor=%20%235462eb&logoColor=%20%23f5f5f5&color=%20%235462eb

[discord-url]: https://discord.camel-ai.org/

[docs-image]: https://img.shields.io/badge/Documentation-EB3ECC

[docs-url]: https://docs.oasis.camel-ai.org/

[huggingface-image]: https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-CAMEL--AI-ffc107?color=ffc107&logoColor=white

[huggingface-url]: https://huggingface.co/camel-ai

[oasis-image]: https://img.shields.io/badge/WeChat-OASISProject-brightgreen?logo=wechat&logoColor=white

[oasis-url]: ./assets/wechatgroup.png

[package-license-image]: https://img.shields.io/badge/License-Apache_2.0-blue.svg

[package-license-url]: https://github.com/camel-ai/oasis/blob/main/licenses/LICENSE

[reddit-image]: https://img.shields.io/reddit/subreddit-subscribers/CamelAI?style=plastic&logo=reddit&label=r%2FCAMEL&labelColor=white

[reddit-url]: https://www.reddit.com/r/CamelAI/

[star-image]: https://img.shields.io/github/stars/camel-ai/oasis?label=stars&logo=github&color=brightgreen

[star-url]: https://github.com/camel-ai/oasis/stargazers

[wechat-image]: https://img.shields.io/badge/WeChat-CamelAIOrg-brightgreen?logo=wechat&logoColor=white

[wechat-url]: ./assets/wechat.JPGwechat.jpg

[x-image]: https://img.shields.io/twitter/follow/CamelAIOrg?style=social

[x-url]: https://x.com/CamelAIOrg