Install Vertex AI client libraries

Google Distributed Cloud (GDC) air-gapped offers various Vertex AI services, including Optical Character Recognition (OCR), Vertex AI Translation, and Speech-to-Text. Each service provides its own API, which you can install using client libraries.

Client libraries simplify accessing Vertex AI APIs from supported languages on Distributed Cloud. Although you can use Vertex AI APIs directly by making raw server requests, client libraries provide simplifications that reduce the required code.

Client libraries are the recommended method for accessing Vertex AI APIs programmatically, for example, on a JupyterLab notebook.

Install a Vertex AI client library in one of the following ways:

  • Extract the library file directly from the tar file.
  • Use a JupyterLab notebook to import the library.

This page describes the various types of client libraries that Distributed Cloud offers for Vertex AI APIs and explains how to install them from the tar file. To import a client library from a notebook, see Manage notebooks.

Vertex AI client libraries

Vertex AI offers different versions of client libraries for CentOS and Ubuntu operating systems.

The naming conventions of Vertex AI client libraries in the tar file are based on the operating system, the service name, and the version. The filenames adhere to the following format:

OS-google-cloud-SERVICE-VERSION.tar.gz

Replace the following:

  • OS: the name of the operating system where you want to install the client library. Allowed values are centos and ubuntu.

  • SERVICE: the name of the Vertex AI service from which you want to download the client library. The following are the allowed values:

    • aiplatform: the Vertex AI Platform client library.
    • speech: the Speech-to-Text client library.
    • translate: the Vertex AI Translation client library.
    • vision: the OCR client library.

  • VERSION: the version number of the client library, such as 3.8.0.

The following table contains the Vertex AI client libraries that Distributed Cloud supports:

Vertex AI service Operating system Filename
OCR Centos centos-google-cloud-vision-3.0.0.tar.gz
Ubuntu ubuntu-google-cloud-vision-3.0.0.tar.gz
Speech-to-Text Centos centos-google-cloud-speech-2.15.0.tar.gz
Ubuntu ubuntu-google-cloud-speech-2.15.0.tar.gz
Vertex AI Translation Centos centos-google-cloud-translate-3.8.0.tar.gz
Ubuntu ubuntu-google-cloud-translate-3.8.0.tar.gz
Vertex AI Platform Centos centos-google-cloud-aiplatform-1.34.0.tar.gz
Ubuntu ubuntu-google-cloud-aiplatform-1.34.0.tar.gz

Before you begin

Before downloading the tar file and extracting client libraries, follow these steps:

  1. Set up a project for Vertex AI.

  2. Authenticate with gdcloud CLI:

    gdcloud auth login

    For more information about how to authenticate with your configured identity provider, see the gdcloud CLI authentication.

  3. Assign the Cloud AI Viewer (cloud-ai-viewer) role to a service account. The service account requires this role to access the Vertex AI services.

  4. Verify that you have installed Python version 3.7.

Install a client library

After completing the prerequisites, follow these steps to download the tar file, and use the tar file to install a client library:

  1. Download the client library you want to install:

    wget https://GDC_URL/.well-known/static/client-libraries/CLIENT_LIBRARY

    Replace the following:

    • GDC_URL: the URL of your organization in GDC.
    • CLIENT_LIBRARY: the filename of the client library you want to download.

  2. Extract the library file:

    tar -zxf CLIENT_LIBRARY

  3. Install the client library in Distributed Cloud:

    pip install -r FOLDER_NAME/requirements.txt --no-index --find-links FOLDER_NAME

    Replace FOLDER_NAME with the path to the local directory where you downloaded the library file.

  4. Import the client library using a Python script. The following example shows a code snippet of a Python script that imports the Vertex AI Translation client library to illustrate what importing libraries looks like:

    from google.cloud import translate
translate_client = translate.Client(
 client_options={"API_ENDPOINT": "https://foo-translation.googleapis.com"})
result
= translate_client.translate(text, target_language="ru")

[...]

    This code sample is not complete. To make a Vertex AI Translation request, learn about translation features or translate text.

  5. Save the Python script with a name, such as translation-service.py.

  6. Run the Python script:

    python SCRIPT_NAME

    Replace SCRIPT_NAME with the name you gave to your Python script, such as translation-service.py.