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Questa pagina descrive i vari tipi di librerie client che
l'appliance air-gapped Google Distributed Cloud (GDC) offre per le API Vertex AI e
spiega come installarle dal file tar.
L'appliance GDC air-gapped offre vari servizi Vertex AI, tra cui il riconoscimento ottico dei caratteri (OCR), Vertex AI Translation e Speech-to-Text. Ogni servizio fornisce la propria API, che puoi installare utilizzando
le librerie client.
Le librerie client semplificano l'accesso alle API Vertex AI dai linguaggi supportati
sull'appliance GDC air-gapped. Sebbene tu possa utilizzare
le API Vertex AI direttamente effettuando richieste server non elaborate, le librerie
client forniscono semplificazioni che riducono il codice richiesto.
Le librerie client sono il metodo consigliato per accedere
alle API Vertex AI a livello di programmazione. Installa una
libreria client Vertex AI estraendo il file della libreria direttamente
dal file tar.
Librerie client Vertex AI
Vertex AI offre diverse versioni delle librerie client per i sistemi operativi CentOS e Ubuntu.
Le convenzioni di denominazione delle librerie client Vertex AI nel file tar
si basano sul sistema operativo, sul nome del servizio e sulla versione. I nomi dei file rispettano il seguente formato:
OS-google-cloud-SERVICE-VERSION.tar.gz
Sostituisci quanto segue:
OS: il nome del sistema operativo in cui vuoi installare la libreria client. I valori consentiti sono centos e ubuntu.
SERVICE: il nome del servizio Vertex AI
da cui vuoi scaricare la libreria client. Di seguito sono riportati
i valori consentiti:
aiplatform: la libreria client di Vertex AI Platform.
speech: la libreria client Speech-to-Text.
translate: la libreria client Vertex AI Translation.
vision: la libreria client OCR.
VERSION: il numero di versione della libreria client, ad esempio 3.8.0.
La tabella seguente contiene le librerie client di Vertex AI supportate
dall'appliance GDC air-gapped:
Assegna il ruolo Visualizzatore Cloud AI (cloud-ai-viewer) a un service account.
Il account di servizio richiede questo ruolo per accedere ai servizi Vertex AI.
Verifica di aver installato Python versione 3.7.
Installare una libreria client
Dopo aver completato i prerequisiti, segui questi passaggi per
scaricare il file tar e utilizzarlo per installare una libreria client:
Sostituisci FOLDER_NAME con il percorso della directory locale in cui hai scaricato il file della libreria.
Importa la libreria client utilizzando uno script Python. L'esempio seguente mostra
uno snippet di codice di uno script Python che importa la libreria client Vertex AI Translation
per illustrare l'aspetto dell'importazione delle librerie:
[[["Facile da capire","easyToUnderstand","thumb-up"],["Il problema è stato risolto","solvedMyProblem","thumb-up"],["Altra","otherUp","thumb-up"]],[["Difficile da capire","hardToUnderstand","thumb-down"],["Informazioni o codice di esempio errati","incorrectInformationOrSampleCode","thumb-down"],["Mancano le informazioni o gli esempi di cui ho bisogno","missingTheInformationSamplesINeed","thumb-down"],["Problema di traduzione","translationIssue","thumb-down"],["Altra","otherDown","thumb-down"]],["Ultimo aggiornamento 2025-09-04 UTC."],[],[],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`."]]
