API Authentication¶

The following document explains how to authenticate with Run:ai APIs.

Run:ai APIs are accessed using bearer tokens. A token can be obtained in several ways:

• When logging into the Run:ai user interface, you enter an email and password (or authenticated via single sign-on) which are used to obtain a token.
• When using the Run:ai command-line, you use a Kubernetes profile and are authenticated by pre-running runai login (or oc login with OpenShift). The command attaches a token to the profile and allows you access to Run:ai functionality.
• When using Run:ai APIs, you need to create an Application through the Run:ai user interface. The Application is created with specific roles and contains a secret. Using the secret you can obtain a token and use it within subsequent API calls.

Create a Client Application¶

• Open the Run:ai Run:ai User Interface.
• Go to Settings & Tools, Application and create a new Application.
• Copy the <APPLICATION> and <SECRET KEY> to be used below

Access rules for the Application¶

For you API requests to be accepted, you will need to set access rules for the application. To assign roles to an application, see Create or Delete rules.

Use the Roles table to assign the correct roles to the application.

Request an API Token¶

Use the above parameters to get a temporary token to access Run:ai as follows.

Example command to get an API token¶

Replace <COMPANY-URL> below with:

• For SaaS installations use <company>.run.ai

• For self-hosted use the Run:ai user interface URL.

    curl  -X POST \
      'https://<runai_url>/api/v1/token' \
      --header 'Accept: */*' \
      --header 'Content-Type: application/json' \
      --data-raw '{
      "grantType":"app_token",
      "AppId":"<APPLICATION NAME>",
      "AppSecret" : "<SECRET KEY>"
    }'

    import requests
    import json
    reqUrl = "https://cp-590d-run-13764-kc-upgrade.runailabs.com/api/v1/token"
    headersList = {
     "Accept": "*/*",
     "Content-Type": "application/json"
    }
    payload = json.dumps({
      "grantType":"app_token",
      "AppId":"<APPLICATION NAME>",
      "AppSecret" : "<SECRET KEY>"
    })
    response = requests.request("POST", reqUrl, data=payload,  headers=headersList)
    print(response.text)

Response¶

The API response will look as follows:

{
  "accessToken": "<TOKEN>", 
}

To call Run:ai REST APIs, the application must pass the retrieved accessToken as a Bearer token in the Authorization header of your HTTP request.