🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation [![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][owl-image]][owl-url] [![Hugging Face][huggingface-image]][huggingface-url] [![Star][star-image]][star-url] [![Package License][package-license-image]][package-license-url] 中文阅读 | Community | Installation | Examples | Paper | Citation | Contributing | CAMEL-AI | 🏆 OWL achieves 69.09 average score on GAIA...
| Stars | 20,123 |
| Forks | 2,297 |
| Language | Python |
| Category | AI 工具 |
| Quality Score | 61.1785544458609/100 |
| Open Issues | 118 |
| Last Updated | 2026-08-27 |
| Created | 2025-03-03 |
| Platforms | browser, python |
| Est. Tokens | ~20k |
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owl is 🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation. It is categorized as a AI 工具 with 20.1k GitHub stars.
owl is primarily written in Python. It covers topics such as agent, artificial-intelligence, multi-agent-systems.
You can find installation instructions and usage details in the owl GitHub repository at github.com/camel-ai/owl. The project has 20.1k stars and 2297 forks, indicating an active community.