OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
đŸ¦‰ OWL is a state-of-the-art framework designed to enhance multi-agent collaboration, enabling efficient task automation across various domains. Built on the CAMEL-AI Framework, OWL leverages dynamic agent interactions to revolutionize how AI agents work together to solve real-world tasks.
Key Features:
- High Performance: Achieved a score of 69.09 on the GAIA benchmark, ranking #1 among open-source frameworks.
- Multiple Installation Options: Supports installation via
uv,venv,conda, and Docker, catering to different user preferences. - Comprehensive Toolkits: Includes a variety of toolkits for web automation, document processing, code execution, and more.
- User-Friendly Web Interface: An enhanced web interface allows for easy interaction with OWL agents, including task history and model selection.
- Community Engagement: Encourages users to design unique challenges for AI agents, fostering innovation and collaboration.
Benefits:
- Natural Interactions: Facilitates more intuitive and robust task automation through dynamic agent collaboration.
- Versatile Applications: Suitable for diverse domains, from web searches to document analysis and multimodal processing.
- Active Community: Join a vibrant community of contributors and users to share insights and improvements.
Highlights:
- Supports various AI models, including OpenAI, Qwen, and DeepSeek.
- Provides extensive documentation and examples for quick start and advanced usage.
- Continuous updates and improvements based on user feedback and technological advancements.