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Start with the Runloop Quickstart to use the examples below.

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Overview

Mounts allow you to attach external resources to your Devbox at creation time. This provides a flexible way to inject code, files, data, and AI agents into your Devbox environment without manually uploading or cloning after the Devbox starts. All mount types use the unified mounts parameter when creating a Devbox, with a type discriminator to specify the mount type.

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Mount Types

Runloop supports four types of mounts:
Mount TypeDescriptionUse Case
Code MountClone a GitHub repositoryWorking with existing codebases
Object MountMount a storage objectLarge datasets, model weights, archives
File MountInject file content inlineConfig files, scripts, small text files
Agent MountMount a pre-configured AI agentRunning AI agents on your Devbox

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Using the Unified Mounts Parameter

All mounts are specified using the mounts array parameter. Each mount object requires a type field to identify the mount type: 
devbox = await runloop.devbox.create(
  mounts=[
    {
      "type": "code_mount",
      "repo_name": "my-repo",
      "repo_owner": "my-org",
    },
    {
      "type": "object_mount",
      "object_id": "obj_abc123",
      "object_path": "/home/user/data.csv"
    },
    {
      "type": "file_mount",
      "target": "/home/user/config.json",
      "content": '{"key": "value"}'
    },
    {
      "type": "agent_mount",
      "agent_name": "my-agent",
      "agent_path": "/home/user/agent"
    }
  ]
)

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Choosing the Right Mount Type

  • Code Mount: Best for cloning Git repositories. Supports private repos with authentication tokens.
  • Object Mount: Best for large files, binary data, datasets, or archives. Objects are stored in Runloop’s storage and can be reused across Devboxes.
  • File Mount: Best for small text files like configuration, scripts, or environment files. Content is provided inline.
  • Agent Mount: Best for mounting pre-configured AI agents that can be run on your Devbox.

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Next Steps