Installation

To install this Python package, follow these steps:

1. Clone the repository to your local machine.
2. Navigate to the project directory.
3. Create a virtual environment using the command python -m venv env.
4. Activate the virtual environment:
   • On Windows: .\env\Scripts\activate
   • On macOS and Linux: source env/bin/activate
5. Install the required dependencies by running pip install -r requirements.txt.

.env Variables

To use a .env file and ensure that sensitive information is not committed to version control, follow these steps:

1. Create a file named .env in the project directory.
2. Add the necessary environment variables to the .env file, each on a new line in the format VARIABLE_NAME=VALUE.
3. Make sure to include the .env file in your .gitignore to prevent it from being tracked by Git.

That's it! You're now ready to use the Python package and manage your environment variables securely.

Working with this in Azure AI Foundry

Updates from March 2025

• Evaluations Lab is shown in course this will evolve with Automation of Evaluations
• Added DeepSeek R1 using LangChain + Exa AI this is housed in /14-azure-ai-inference
• In-progress (Agents in Azure Foundry via SDK)

Updates planned for Summer 2025

• Distillation
• Response API Updates
• Automated Red Team Agent (Evaluation of Application using PyRiT)

This assumes you have deployed the Azure AI Foundry + Workspace (Project) in a supported region East US 2 (US) see reference. https://learn.microsoft.com/en-us/azure/ai-studio/how-to/develop/simulator-interaction-data

Once you've used environment variables for the items in the script the modification is located on lines 77-85 The amount of turns, results, and jailbreak can change use the guidance on the evaluation that you'd like to test with this service.