Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
Online Search
Supports multiple search engines for real-time information retrieval.
Multimodal Processing
Handles internet or local videos, images, and audio data effectively.
Browser Automation
Utilizes the Playwright framework for simulating complex browser interactions.
Document Parsing
Extracts content from various document formats including Word, PDF, and PowerPoint.
OWL is a comprehensive framework designed to optimize multi-agent collaboration for real-world task automation. Built on the CAMEL-AI Framework, it enables AI agents to interact dynamically, leading to more natural and effective automation solutions. With its innovative approach, OWL not only enhances efficiency but also pushes the boundaries of what is achievable in AI-assisted task execution.
Supports Python versions 3.10, 3.11, or 3.12. Provides built-in toolkits for diverse tasks including data analysis, web interaction, and multimedia processing.
Automating customer service interactions using AI agents.
Streamlining data analysis tasks across different formats.
Enhancing research capabilities by integrating online search functionalities.
OWL is a framework that enhances the collaboration of AI agents for automating real-world tasks.
You can install OWL using multiple methods including cloning the GitHub repository and installing dependencies.
OWL supports Python for executing tasks and developing automation scripts.
