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> Guide to creating and managing custom Docker environments for specialized video curation pipeline requirements

# Add Custom Environment

Package additional dependencies for a NeMo Curator pipeline in a container image.

The repository Dockerfile creates a Python environment with dependencies selected by its build arguments. Build it from the source revision you plan to use, then add system or Python packages your pipeline needs. Follow the [image build procedure](/reference/infra/container-environments#build-an-image) and check the Dockerfile for its defaults.

## Before You Start

Before you create the image, complete these tasks:

* Review the [pipeline concepts and diagrams](/about/concepts/video).
* Build a base image from the NeMo Curator Dockerfile or choose another suitable image.
* [Create custom code](/curate-video/tutorials/pipeline-customization/add-cust-code) if your environment supports a new module.

---

## How to Add Dependencies with a Dockerfile

Create a Dockerfile that adds system or Python packages to the base image.

### Define Build Steps

Use these steps to create and build the image:

1. Create an `environments` directory anywhere on your system to organize your custom pipeline stage environments.
2. Create a new folder for your environment, for example: `my-env/`.
3. Create a `Dockerfile` that installs your environment's dependencies on top of `nemo-curator:local`.

   ```dockerfile
   FROM nemo-curator:local

   # System deps
   RUN apt-get update && apt-get install -y --no-install-recommends \
       wget git && rm -rf /var/lib/apt/lists/*

   # Python deps (prefer aligning with pyproject optional extras)
   # Example: install video stacks used by NeMo Curator
   RUN pip install --no-cache-dir \
       av==13.1.0 opencv-python einops easydict

   # Optional: CV-CUDA (choose wheel that matches your CUDA/Python)
   # RUN pip install cvcuda_cu12

   # Optional: vLLM (see platform markers in pyproject)
   # RUN pip install vllm==0.9.2

   # Copy your code if needed
   COPY . /workspace
   WORKDIR /workspace
   ```

### Build the Image

Build and tag the image from the directory containing the Dockerfile:

```bash
docker build -t my-ray-curator:latest .
```

## Next Steps

Use the image in a [custom code pipeline](/curate-video/tutorials/pipeline-customization/add-cust-code).