[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間:2025-09-04 (世界標準時間)。"],[],[],null,["# Install Vertex AI client libraries\n\nThis page describes the various types of client libraries that\nGoogle Distributed Cloud (GDC) air-gapped appliance offers for Vertex AI APIs and\nexplains how to install them from the tar file.\n\nGDC air-gapped appliance offers various Vertex AI\nservices, including Optical Character Recognition (OCR), Vertex AI Translation, and\nSpeech-to-Text. Each service provides its own API, which you can install using\nclient libraries.\n\nClient libraries simplify accessing Vertex AI APIs from supported\nlanguages on GDC air-gapped appliance. Although you can use\nVertex AI APIs directly by making raw server requests, client\nlibraries provide simplifications that reduce the required code.\n\nClient libraries are the recommended method for accessing\nVertex AI APIs programmatically. Install a\nVertex AI client library by extracting the library file directly\nfrom the tar file.\n\nVertex AI client libraries\n--------------------------\n\nVertex AI offers different versions of client libraries for\nCentOS and Ubuntu operating systems.\n\nThe naming conventions of Vertex AI client libraries in the tar\nfile are based on the operating system, the service name, and the version. The\nfilenames adhere to the following format: \n\n \u003cvar translate=\"no\"\u003eOS\u003c/var\u003e-google-cloud-\u003cvar translate=\"no\"\u003eSERVICE\u003c/var\u003e-\u003cvar translate=\"no\"\u003eVERSION\u003c/var\u003e.tar.gz\n\nReplace the following:\n\n- \u003cvar translate=\"no\"\u003eOS\u003c/var\u003e: the name of the operating system where you want to install the client library. Allowed values are `centos` and `ubuntu`.\n- \u003cvar translate=\"no\"\u003eSERVICE\u003c/var\u003e: the name of the Vertex AI\n service from which you want to download the client library. The following are\n the allowed values:\n\n - `aiplatform`: the Vertex AI Platform client library.\n - `speech`: the Speech-to-Text client library.\n - `translate`: the Vertex AI Translation client library.\n - `vision`: the OCR client library.\n- \u003cvar translate=\"no\"\u003eVERSION\u003c/var\u003e: the version number of the client library,\n such as `3.8.0`.\n\nThe following table contains the Vertex AI client libraries that\nGDC air-gapped appliance supports:\n\nBefore you begin\n----------------\n\nBefore downloading the tar file and extracting client libraries, follow these\nsteps:\n\n1. [Set up a project for Vertex AI](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-set-up-project).\n\n2. Authenticate with gdcloud CLI:\n\n gdcloud auth login\n\n For more information about how to authenticate with your configured identity\n provider, see [the gdcloud CLI authentication](/distributed-cloud/hosted/docs/latest/appliance/resources/gdcloud-auth).\n3. Assign the Cloud AI Viewer (`cloud-ai-viewer`) role to [a service account](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-set-up-project#set-up-service).\n The service account requires this role to access the Vertex AI\n services.\n\n4. Verify that you have installed Python version 3.7.\n\nInstall a client library\n------------------------\n\nAfter completing the [prerequisites](#before-you-begin), follow these steps to\ndownload the tar file, and use the tar file to install a client library:\n\n1. Download the client library you want to install:\n\n wget https://\u003cvar translate=\"no\"\u003eGDC_URL\u003c/var\u003e/.well-known/static/client-libraries/\u003cvar translate=\"no\"\u003eCLIENT_LIBRARY\u003c/var\u003e\n\n Replace the following:\n - \u003cvar translate=\"no\"\u003eGDC_URL\u003c/var\u003e: the URL of your organization in GDC.\n - \u003cvar translate=\"no\"\u003eCLIENT_LIBRARY\u003c/var\u003e: the filename of the [client library](#clientlib) you want to download.\n2. Extract the library file:\n\n tar -zxf \u003cvar translate=\"no\"\u003eCLIENT_LIBRARY\u003c/var\u003e\n\n3. Install the client library in GDC air-gapped appliance:\n\n pip install -r \u003cvar translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003eFOLDER_NAME\u003c/span\u003e\u003c/var\u003e/requirements.txt --no-index --find-links \u003cvar translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003eFOLDER_NAME\u003c/span\u003e\u003c/var\u003e\n\n Replace \u003cvar translate=\"no\"\u003eFOLDER_NAME\u003c/var\u003e with the path to the local\n directory where you downloaded the library file.\n4. Import the client library using a Python script. The following example shows\n a code snippet of a Python script that imports the Vertex AI Translation\n client library to illustrate what importing libraries looks like:\n\n from google.cloud import https://cloud.google.com/python/docs/reference/translate/latest/google.cloud.translate_v2.client.Client.html\n translate_client = https://cloud.google.com/python/docs/reference/translate/latest/google.cloud.translate_v2.client.Client.html.https://cloud.google.com/python/docs/reference/translate/latest/google.cloud.translate_v2.client.Client.html(\n client_options={\"\u003cvar translate=\"no\"\u003eAPI_ENDPOINT\u003c/var\u003e\": \"https://foo-translation.googleapis.com\"})\n result\n = translate_client.https://cloud.google.com/python/docs/reference/translate/latest/google.cloud.translate_v2.client.Client.html(text, target_language=\"ru\")\n\n [...]\n\n This code sample is not complete. To make a Vertex AI Translation\n request, [learn about translation features](/distributed-cloud/hosted/docs/latest/appliance/application/ao-user/vertex-ai-translation).\n5. Save the Python script with a name, such as `translation-service.py`.\n\n6. Run the Python script:\n\n python \u003cvar translate=\"no\"\u003e\u003cspan class=\"devsite-syntax-n\"\u003eSCRIPT_NAME\u003c/span\u003e\u003c/var\u003e\n\n Replace \u003cvar translate=\"no\"\u003eSCRIPT_NAME\u003c/var\u003e with the name you gave to your\n Python script, such as `translation-service.py`."]]