Custom Docker Images
Custom Docker Images
Vellum Workflows are designed to run in a sandboxed environment. By default, the Vellum Python SDK uses a default Docker Image to run Workflows generated by the UI and pushed by the user from the CLI. However, sometimes you may want to use pre-existing logic from the rest of your repository, or some bespoke binaries that don’t translate well to the currently supported Vellum SDK languages. In these cases, you can use a custom Docker Image to run your Workflow.
Configuring a Custom Docker Image
To configure a custom Docker Image for a Vellum Workflow, you should first create a Dockerfile in the root of your Workflow module.
There are few important things to note about this Dockerfile:
- You must inherit from the
vellumai/python-workflow-runtime
image in order to run the Workflow on our infrastructure. - You have the flexibility to add any other dependencies you need to the image.
- The
vellum_start_server
command is required to start the Vellum Server.
Building and Pushing Your Custom Image
Once you have your Dockerfile, follow these steps to build and push your image to Vellum:
Configuring Your Workflow to Use the Custom Image
Once you’ve pushed the image, you can configure your Vellum Workflow to use the custom Docker Image by adding the following to your pyproject.toml
file:
This will tell Vellum to use the custom Docker Image when running the defined Workflow.
Using Custom Docker Images in the Workflow UI
After pushing your custom Docker image, you can select it in the Workflow Sandbox Settings. To do this:
- Open your Workflow in the Workflow Sandbox
- Click on the Settings button to open the Workflow Sandbox Settings modal
- In the “Container Image” section, you can select your custom Docker image from the dropdown
You can select from available system images or your own custom images. The dropdown allows you to choose the specific image tag as well.