Search and Rescue (SAR) Agent Framework - CSC 581

Introduction

This framework is for CSC 581 students to develop intelligent agents supporting the AI4S&R project. Students can create specialized agents for various SAR roles such as those listed in this spreadsheet:

https://docs.google.com/spreadsheets/d/1QZK5HAdDC-_XNui6S0JZTbJH5_PbYJTp8_gyhXmz8Ek/edit?usp=sharing https://docs.google.com/spreadsheets/d/11rBV9CbKNeQbWbaks8TF6GO7WcSUDS_-hAoH75UEkgQ/edit?usp=sharing

Each student or team will choose a specific role within the SAR ecosystem and implement an agent that provides decision support and automation for that role.

How to Submit

Please submit a link to your clone of the repository to Canvas.

Prerequisites

• Python 3.8 or higher
• pyenv (recommended for Python version management)
• pip (for dependency management)

Setup and Installation

1. Clone the repository:

git clone <repository-url>
cd sar-project

2. Set up Python environment:

# Using pyenv (recommended)
pyenv install 3.9.6  # or your preferred version
pyenv local 3.9.6

# Create and activate virtual environment
python -m venv .venv
source .venv/bin/activate  # On Unix/macOS
# or
.venv\Scripts\activate     # On Windows

3. Install dependencies:

pip install -r requirements.txt
pip install -e .

4. Configure environment variables:

OpenAI:

• Obtain required API keys:
  1. OpenAI API key: Sign up at https://platform.openai.com/signup
• Update your .env file with the following:

  OPENAI_API_KEY=your_openai_api_key_here
  

Google Gemini:

• Obtain required API keys:
  1. pip install google-generativeai
  2. import google.generativeai as genai
  3. Google Gemini API Key: Obtain at https://aistudio.google.com/apikey
• Configure with the following:

  genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
  

Make sure to keep your .env file private and never commit it to version control.

Project Structure

sar-project/
├── src/
│   └── sar_project/         # Main package directory
│       └── agents/          # Agent implementations
│       └── config/          # Configuration and settings
│       └── knowledge/       # Knowledge base implementations
├── tests/                   # Test directory
├── pyproject.toml           # Project metadata and build configuration
├── requirements.txt         # Project dependencies
└── .env                     # Environment configuration

Development

This project follows modern Python development practices:

1. Source code is organized in the src/sar_project layout
2. Use pip install -e . for development installation
3. Run tests with pytest tests/
4. Follow the existing code style and structure
5. Make sure to update requirements.txt when adding dependencies

FAQ

Assignment Questions

Q: How do I choose a role for my agent?

A: Review the list of SAR roles above and consider which aspects interest you most. Your agent should provide clear value to SAR operations through automation, decision support, or information processing.

Q: What capabilities should my agent have?

A: Your agent should handle tasks relevant to its role such as: data processing, decision making, communication with other agents, and providing actionable information to human operators.

Q: Can I add new dependencies?

A: Yes, you can add new Python packages to requirements.txt as needed for your implementation.

Technical Questions

Q: Why am I getting API key errors?

A: Ensure you've properly set up your .env file and obtained valid API keys from the services listed above.

Q: How do I test my agent?

A: Use the provided test framework in the tests/ directory. Write tests that verify your agent's core functionality.

Q: Can I use external libraries for my agent?

A: Yes, you can use external libraries as long as they are compatible.