🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation

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中文阅读 | Community | Installation | Examples | Paper | Citation | Contributing | CAMEL-AI

🏆 OWL achieves 58.18 average score on GAIA benchmark and ranks 🏅️ #1 among open-source frameworks! 🏆

🦉 OWL is a cutting-edge framework for multi-agent collaboration that pushes the boundaries of task automation, built on top of the CAMEL-AI Framework.

Our vision is to revolutionize how AI agents collaborate to solve real-world tasks. By leveraging dynamic agent interactions, OWL enables more natural, efficient, and robust task automation across diverse domains.

📋 Table of Contents

• 📋 Table of Contents
• 🔥 News
• 🎬 Demo Video
• ✨️ Core Features
• 🛠️ Installation
  • Clone the Github repository
  • Set up Environment
  • Install Dependencies
  • Setup Environment Variables
• 🚀 Quick Start
• 🧪 Experiments
• ⏱️ Future Plans
• 📄 License
• 🖊️ Cite
• 🔥 Community
• ❓ FAQ
• ⭐ Star History

🔥 News

• [2025.03.07]: We open-source the codebase of 🦉 OWL project.

🎬 Demo Video

371254613005d51d73c82424e56a1d22.mp4

d106cfbff2c7b75978ee9d5631ebeb75.mp4

✨️ Core Features

• Real-time Information Retrieval: Leverage Wikipedia, Google Search, and other online sources for up-to-date information.
• Multimodal Processing: Support for handling internet or local videos, images, and audio data.
• Browser Automation: Utilize the Playwright framework for simulating browser interactions, including scrolling, clicking, input handling, downloading, navigation, and more.
• Document Parsing: Extract content from Word, Excel, PDF, and PowerPoint files, converting them into text or Markdown format.
• Code Execution: Write and execute Python code using interpreter.

🛠️ Installation

Clone the Github repository

git clone https://github.com/camel-ai/owl.git
cd owl

Set up Environment

Using Conda (recommended):

conda create -n owl python=3.11
conda activate owl

Using venv (alternative):

python -m venv owl_env
# On Windows
owl_env\Scripts\activate
# On Unix or MacOS
source owl_env/bin/activate

Install Dependencies

python -m pip install -r requirements.txt
playwright install

Setup Environment Variables

In the owl/.env_template file, you will find all the necessary API keys along with the websites where you can register for each service. To use these API services, follow these steps:

1. Copy and Rename: Duplicate the .env_example file and rename the copy to .env.
2. Fill in Your Keys: Open the .env file and insert your API keys in the corresponding fields.
3. For using more other models: please refer to our CAMEL models docs:https://docs.camel-ai.org/key_modules/models.html#supported-model-platforms-in-camel

Note: For optimal performance, we strongly recommend using OpenAI models. Our experiments show that other models may result in significantly lower performance on complex tasks and benchmarks.

🚀 Quick Start

Run the following minimal example:

python owl/run.py

You can run OWL agent with your own task by modifying the run.py script:

# Define your own task
question = "Task description here."

society = construct_society(question)
answer, chat_history, token_count = run_society(society)

logger.success(f"Answer: {answer}")

Example tasks you can try:

• "Find the latest stock price for Apple Inc."
• "Analyze the sentiment of recent tweets about climate change"
• "Help me debug this Python code: [your code here]"
• "Summarize the main points from this research paper: [paper URL]"

🧪 Experiments

We provided a script to reproduce the results on GAIA. You can check the run_gaia_roleplaying.py file and run the following command:

python run_gaia_roleplaying.py

⏱️ Future Plans

• Write a technical blog post detailing our exploration and insights in multi-agent collaboration in real-world tasks.
• Enhance the toolkit ecosystem with more specialized tools for domain-specific tasks.
• Develop more sophisticated agent interaction patterns and communication protocols

📄 License

The source code is licensed under Apache 2.0.

🖊️ Cite

If you find this repo useful, please cite:

@misc{owl2025,
  title        = {OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation},
  author       = {{CAMEL-AI.org}},
  howpublished = {\url{https://github.com/camel-ai/owl}},
  note         = {Accessed: 2025-03-07},
  year         = {2025}
}

🔥 Community

Join us for further discussions!

❓ FAQ

Q: Why is my Chrome browser showing a blank screen even though there's output in the console?

A: This is expected behavior. When OWL determines that a task can be completed using non-browser tools (like search, code analysis, etc.), the browser window may remain blank. The browser is only activated when web interaction is necessary. We plan to implement lazy loading in future updates to improve this user experience.

⭐ Star History