# camel-ai/oasis

🏝️ OASIS: Open Agent Social Interaction Simulations with One Million Agents.

Repository: https://github.com/camel-ai/oasis
Canonical: https://ross.abutalabs.com/products/oasis
Homepage: https://docs.oasis.camel-ai.org/
Language: Python
License: Apache-2.0
License Family: permissive
Topics: agent-based-framework, agent-based-simulation, large-language-models, large-scale, llm-agents, deep-learning, natural-language-processing, ai-societies, multi-agent-systems
Last push: 2026-08-26T11:19:22+00:00

## Health v2 (maintenance only)
Score: 75/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 99, release rhythm 59, longevity 47
- inputs: {"age_days": 658, "days_push": 7, "days_rel": 272, "gap_med": 11, "n_releases_24m": 6}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5061, forks 623 (observed 2026-08-28T04:09:09.176017+00:00)

## What it is
OASIS is an open-source social media simulator that uses large language model and rule-based agents to mimic the behavior of up to one million users on platforms like Twitter and Reddit. It supports 23 agent actions, dynamic environments, and integrated recommendation systems for studying social phenomena at scale.

## Use cases
- simulate a million agents on a social network
- study information spread and group polarization
- model herd behavior on twitter or reddit
- test human-agent interactions in a dynamic social environment
- predict how content spreads through social networks
- generate realistic synthetic social media interactions
- run LLM agent-based social science experiments

## When to choose
- you need large-scale social media simulation with LLM agents
- you want to study emergent social phenomena like polarization or echo chambers
- you need built-in recommendation systems and diverse agent action spaces
- you want a pip-installable Python framework with OpenAI or other LLM backends

## When to avoid
- you need a general-purpose multi-agent framework not focused on social media
- you lack access to LLM APIs and want fully free simulation
- you need real-time production social platform features rather than research simulation
- your project requires small-scale, low-latency agent interactions

## Facets
- artifact type: library
- maturity: active
- function: agent-framework, simulation, llm-inference, machine-learning
- domain: artificial-intelligence, large-language-models, social-media, simulation
- platform: python, windows
- tags: social-media-simulation, multi-agent-systems, llm-agents, agent-based-modeling, million-agents, twitter, reddit, recommendation-systems, ai-agents, natural-language-processing, linux, macos

## Member repositories
- camel-ai/oasis (main) score 75

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:09.176017+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:17:18.799812+00:00, confidence not recorded.
  - readme: https://github.com/camel-ai/oasis (fetched 2026-08-28T04:09:09.176017+00:00, sha 526dc416b02e)
  - homepage: https://docs.oasis.camel-ai.org/ (fetched 2026-08-29T08:57:47.086893+00:00, sha 1eadf60ee178)
  - site_page: https://docs.oasis.camel-ai.org/quickstart (fetched 2026-08-29T08:57:47.088909+00:00, sha 00062d77e6f3)
- Data as of 2026-08-30T08:39:29.467469+00:00.