---
title: "oasis"
type: "tool"
slug: "camel-ai-oasis"
canonical_url: "https://www.graphcanon.com/tools/camel-ai-oasis"
github_url: "https://github.com/camel-ai/oasis"
homepage_url: "https://docs.oasis.camel-ai.org/"
stars: 4898
forks: 597
primary_language: "Python"
license: "Apache-2.0"
categories: ["ai-agents"]
tags: ["deep-learning", "ai-societies", "large-language-models", "natural-language-processing", "agent-based-simulation", "multi-agent-systems", "agent-based-framework"]
updated_at: "2026-07-07T18:40:28.642448+00:00"
---

# oasis

> OASIS: Open Agent Social Interaction Simulations with One Million Agents

A scalable, open-source social media simulator using large language model agents to study complex social phenomena such as information spread and group polarization.

## Facts

- Repository: https://github.com/camel-ai/oasis
- Homepage: https://docs.oasis.camel-ai.org/
- Stars: 4,898 · Forks: 597 · Open issues: 56 · Watchers: 31
- Primary language: Python
- License: Apache-2.0
- Last pushed: 2026-06-23T08:42:53+00:00

## Categories

- [AI Agents](/categories/ai-agents.md)

## Tags

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

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## README (excerpt)

```text
<div align="center">
  <a href="https://www.camel-ai.org/">
    <img src="assets/banner.png" alt=banner>
  </a>
</div>

</br>

<div align="center">

<h1> OASIS: Open Agent Social Interaction Simulations with One Million Agents
</h1>

[![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]

<h4 align="center">

[Community](https://github.com/camel-ai/camel#community) |
[Paper](https://arxiv.org/abs/2411.11581) |
[Examples](https://github.com/camel-ai/oasis/tree/main/examples) |
[Dataset](https://huggingface.co/datasets/echo-yiyiyi/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/)

</h4>

</div>

<br>

<p align="left">
  <img src='assets/intro.png'>

🏝️ 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.

</p>

<br>

<div align="center">
🌟 Star OASIS on GitHub and be instantly notified of new releases.
</div>

<br>

<div align="center">
    <img src="assets/star.gif" alt="Star" width="196" height="52">
  </a>
</div>

<br>

## ✨ 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.

<br>

## 📺 Demo Video

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

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

<br>

For more showcaes:

- Can 1,000,000 AI agents simulate social media?
  [→Watch demo](https://www.youtube.com/watch?v=lprGHqkApus&t=2s)

<br>

## 🎯 Usecase

<div align="left">
    <img src="assets/research_simulation.png" alt=usecase1>
    <img src="assets/interaction.png" alt=usecase2>
   <a href="http://www.matrix.eigent.ai">
    <img src="assets/content_creation.png" alt=usecase3>
   </a>
    <img src="assets/prediction.png" alt=usecase4>
</div>

## ⚙️ 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=<insert your OpenAI API key>

# For Windows Command Prompt:
set OPENAI_API_KEY=<insert your 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 ModelFact
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/camel-ai-oasis`](/api/graphcanon/tools/camel-ai-oasis)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_