Install Python

Before installing OWL, ensure you have Python installed (version 3.10, 3.11, or 3.12 is supported):

Note for GAIA Benchmark Users: When running the GAIA benchmark evaluation, please use the gaia58.18 branch which includes a customized version of the CAMEL framework in the owl/camel directory. This version contains enhanced toolkits with improved stability specifically optimized for the GAIA benchmark compared to the standard CAMEL installation.

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# If not installed, download and install from https://www.python.org/downloads/

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## **Installation Options**

OWL supports multiple installation methods to fit your workflow preferences.

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# Install uv if you don't have it already
pip install uv

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# Create a virtual environment and install dependencies
uv venv .venv --python=3.10

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# Install CAMEL with all dependencies
uv pip install -e .

Install from requirements.txt

pip install -r requirements.txt --use-pep517

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# Option 1: Install as a package (recommended)
pip install -e .

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# Option 2: Install from requirements.txt
pip install -r requirements.txt --use-pep517

Option 4: Using Docker

Using Pre-built Image (Recommended)

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# This option downloads a ready-to-use image from Docker Hub

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# For users who need to customize the Docker image or cannot access Docker Hub:

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# Make the script executable and build the Docker image
chmod +x build_docker.sh
./build_docker.sh

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### Model Requirements

- **Tool Calling**: OWL requires models with robust tool calling capabilities to interact with various toolkits. Models must be able to understand tool descriptions, generate appropriate tool calls, and process tool outputs.

- **Multimodal Understanding**: For tasks involving web interaction, image analysis, or video processing, models with multimodal capabilities are required to interpret visual content and context.

#### Supported Models

For information on configuring AI models, please refer to our [CAMEL models documentation](https://docs.camel-ai.org/key_modules/models.html#supported-model-platforms-in-camel).

> **Note**: For optimal performance, we strongly recommend using OpenAI models (GPT-4 or later versions). Our experiments show that other models may result in significantly lower performance on complex tasks and benchmarks, especially those requiring advanced multi-modal understanding and tool use.

OWL supports various LLM backends, though capabilities may vary depending on the model's tool calling and multimodal abilities. You can use the following scripts to run with different models:

```bash

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### **Install Playwright MCP Service**

```bash
npm install -g @executeautomation/playwright-mcp-server
npx playwright install-deps

Try our comprehensive MCP examples:

• examples/run_mcp.py - Basic MCP functionality demonstration (local call, requires dependencies)
• examples/run_mcp_sse.py - Example using the SSE protocol (Use remote services, no dependencies)

📄 License

The source code is licensed under Apache 2.0.