How to Install dtx

Before you begin, choose how you want to run dtx depending on your environment and requirements.

Option 1: Install dtx locally with full dependencies (torch etc.)

This is recommended if you plan to run local models (e.g., Hugging Face, Ollama) on your machine.

pip install dtx[torch]

Includes:

• Core CLI
• torch, transformers for local LLM and classifier execution
• Supports all datasets and local execution

Option 2: Install dtx if torch is already installed

If your environment already has torch installed (for example, in a GPU-accelerated ML environment), you can skip extras:

pip install dtx

dtx will use your existing torch installation.

Tip: Verify torch is installed:

python -c "import torch; print(torch.__version__)"

Option 3: Use uv for fast installation in a clean environment

If you're creating a new environment and want fast dependency resolution with uv:

Install uv

curl -LsSf https://astral.sh/uv/install.sh | sh

Install dtx with full dependencies

uv pip install dtx[torch]

Option 4: Use Docker wrapper (ddtx)

If you prefer Dockerized execution (no local torch install required), you can use ddtx.

1. Install dtx (for the ddtx wrapper CLI):

pip install dtx

2. Use ddtx to run inside Docker:

ddtx redteam scope "Describe your agent" output.yml

Features:

• No need to install torch locally
• Fully containerized execution
• Automatically mounts .env and working directories
• Use Docker-managed templates and tools

Summary of Options

How to Get Started (Development)

Follow these steps to set up dtx for local development.

1. Clone the Repository

git clone https://github.com/YOUR-ORG/dtx.git
cd dtx

2. Install Dependencies

Run the following command:

make install

This will:

• Ensure the poetry-plugin-export is installed
• Install all dependencies including dev and torch groups
• Set up the dtx package in editable mode

3. Activate the Virtual Environment

Run this in your shell to activate the Poetry-managed virtual environment:

eval $(poetry env activate)

Alternatively, you can run:

make venv

This will print the exact eval command you need to run manually. For example:

Note: make cannot modify your current shell environment, so you must run the eval command directly.

4. Run the CLI

Once the environment is active, you can use the CLI:

dtx --help

5. Export Requirements (Optional)

To export the current environment to a requirements.txt file (useful for pip-based tools or deployment):

make export

This will generate a requirements.txt file including development and optional dependencies like torch.