by camel-ai · Agent Tool · ★ 19.3k
π¦ 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] δΈζι θ―» | Community | Installation | Examples | Paper | Citation | Contributing | CAMEL-AI | π OWL achieves 69.09 average score on GAIA benchmark and ranks <span style="color: #d81b60; font-weight: bold; font-size: 1
| Stars | 19,293 |
| Forks | 2,250 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 47.49/100 |
| Open Issues | 103 |
| Last Updated | 2026-03-20 |
| Created | 2025-03-03 |
| Platforms | browser, python |
| Est. Tokens | ~2407k |
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owl is π¦ OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation. It is categorized as a Agent Tool with 19.3k 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 19.3k stars and 2250 forks, indicating an active community.