> ## Documentation Index
> Fetch the complete documentation index at: https://docs.kiteml.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart: augment a LeRobot dataset with one call

> Go from an API key to a downloaded, augmented LeRobot dataset in a few minutes using the Kite Platform API and a single curl request.

This guide takes you from zero to a finished dataset augmentation. You provide four things: a source dataset, a prompt, an episode count, and a destination. Kite generates the episodes on its GPUs and delivers a standard LeRobot dataset you can train on directly.

## Prerequisites

Before you begin, you need:

* A Kite account with API access enabled
* An **API key** — create one from **Developers → API keys** in the [dashboard](https://kiteml.com/app). Keys start with `kite_` and are shown only once.
* `curl` (or any HTTP client)

<Steps>
  <Step title="Set your API key">
    Export the key so the examples below can use it.

    ```bash theme={"system"}
    export KITE_API_KEY=kite_aBcDeFgH...
    ```
  </Step>

  <Step title="Verify it works">
    Confirm your key is valid against the API base URL, `https://api.kiteml.com/v1`.

    ```bash theme={"system"}
    curl https://api.kiteml.com/v1/keys/me \
      -H "Authorization: Bearer $KITE_API_KEY"
    ```
  </Step>

  <Step title="Start an augmentation">
    One call starts a run. Point it at a source dataset, describe the change, choose how many episodes, and where the results go.

    ```bash theme={"system"}
    curl -X POST https://api.kiteml.com/v1/augmentations \
      -H "Authorization: Bearer $KITE_API_KEY" \
      -H "Content-Type: application/json" \
      -d '{
        "source": { "repo_id": "lerobot/pusht" },
        "instructions": "change the table surface to white marble, vary the lighting",
        "config": { "episode_count": 20 },
        "output": { "type": "download" }
      }'
    ```

    You get back the augmentation resource — including its `id` — immediately, with `status: "queued"`.
  </Step>

  <Step title="Track it to completion">
    Poll the run until `status` is `succeeded`. It moves through `queued → processing → succeeded` with a live `progress` value.

    ```bash theme={"system"}
    curl https://api.kiteml.com/v1/augmentations/aug_01J8X4... \
      -H "Authorization: Bearer $KITE_API_KEY"
    ```
  </Step>

  <Step title="Get your dataset">
    A completed `download` run exposes its files under `output.files`. Fetch each one, preserving its `path`, to reconstruct a standard LeRobot Parquet dataset on disk — ready to train on with no conversion.
  </Step>
</Steps>

<Check>
  That's the full loop. For the details — idempotency, Hugging Face delivery, and the complete endpoint list — continue to [Augmentations](/platform-api/augmentation).
</Check>

<Tip>
  Need help? Reach out at [support@kiteml.com](mailto:support@kiteml.com).
</Tip>