Tetap teratur dengan koleksi
Simpan dan kategorikan konten berdasarkan preferensi Anda.
Halaman ini menjelaskan cara mengautentikasi panggilan ke layanan Vertex AI di Google Distributed Cloud (GDC) yang terisolasi. Anda harus menyiapkan autentikasi token untuk mengamankan permintaan ke Vertex AI API dalam aplikasi yang terisolasi dari internet. Proses ini memvalidasi permintaan API Anda dengan memberikan identitas Anda dan mengizinkan interaksi Anda.
Halaman ini ditujukan bagi developer aplikasi dalam grup operator aplikasi yang bertanggung jawab untuk menyiapkan aplikasi dan lingkungan pengembangan mereka guna mengaktifkan fitur AI. Untuk mengetahui informasi selengkapnya, lihat dokumentasi Audiens untuk GDC yang terisolasi dari internet.
Pastikan untuk mengupdate penyimpanan tepercaya lokal sebelum Anda menyiapkan autentikasi di lingkungan pengembangan.
Melakukan autentikasi ke layanan Vertex AI
Interaksi dengan layanan Vertex AI dilakukan melalui token autentikasi. Token adalah objek digital yang memverifikasi identitas dan otorisasi Anda setelah Anda memberikan kredensial yang valid. Token ini membawa informasi spesifik tentang akun Anda dan izin yang dimilikinya untuk mengakses dan beroperasi dengan layanan dan resource.
Dapatkan akses ke layanan Vertex AI atau model AI Generatif yang ingin Anda gunakan dengan memberi akun pengguna Anda peran yang sesuai yang tercantum dalam Menyiapkan izin IAM.
Login ke Distributed Cloud dengan akun pengguna yang harus Anda gunakan untuk berinteraksi dengan API:
Ganti ENDPOINT dengan endpoint API yang Anda gunakan untuk organisasi Anda. Untuk mengetahui informasi selengkapnya, lihat status dan endpoint layanan.
Bergantung pada penggunaan token autentikasi yang dimaksud, Anda mungkin perlu menyertakan port setelah endpoint layanan di jalur audiens sebagai berikut:
Jika Anda menggunakan library klien untuk permintaan, Anda harus menyertakan port :443 setelah endpoint layanan di jalur audiens. Oleh karena itu, jalur --audiences dalam perintah harus berupa https://ENDPOINT:443.
Jika Anda menggunakan gRPC, curl, atau panggilan REST terprogram untuk permintaan Anda, jangan sertakan port. Oleh karena itu, jalur --audiences dalam perintah harus berupa https://ENDPOINT.
Output menampilkan token autentikasi. Tambahkan token ke header permintaan command line yang Anda buat, seperti dalam contoh berikut:
-H"Authorization: Bearer TOKEN"
Ganti TOKEN dengan nilai untuk token autentikasi yang ditampilkan output.
Melakukan autentikasi dengan akun layanan Anda
Panduan berikut akan memandu Anda mendapatkan token autentikasi untuk akun layanan Anda:
Siapkan akun layanan yang ingin Anda gunakan untuk mengakses layanan Vertex AI atau model AI Generatif.
Berikan peran yang sesuai yang tercantum di Siapkan izin IAM kepada akun layanan agar akun tersebut dapat mengakses layanan atau model yang ingin Anda gunakan.
Ganti PATH_TO_SERVICE_KEY dengan jalur ke file JSON yang berisi pasangan kunci akun layanan Anda.
Instal library klien google-auth:
pipinstallgoogle-auth
Tambahkan kode berikut ke skrip Python:
importosimportgoogle.authfromgoogle.auth.transportimportrequestsimportrequestsasreqsos.environ["GOOGLE_APPLICATION_CREDENTIALS"]="PATH_TO_SERVICE_KEY"os.environ["GRPC_DEFAULT_SSL_ROOTS_FILE_PATH"]="CERT_NAME"# If you use a client library for your request,# you must include port :443 after the service endpoint# in the audience path.audience="https://ENDPOINT"creds,project_id=google.auth.default()print(project_id)creds=creds.with_gdch_audience(audience)deftest_get_token():sesh=reqs.Session()req=requests.Request(session=sesh)creds.refresh(req)print(creds.token)if__name__=="__main__":test_get_token()
Ganti kode berikut:
PATH_TO_SERVICE_KEY: jalur ke file JSON yang berisi pasangan kunci akun layanan Anda.
CERT_NAME: nama file sertifikat Certificate Authority (CA), seperti org-1-trust-bundle-ca.cert. Anda hanya memerlukan nilai ini jika berada di lingkungan pengembangan. Jika tidak, hilangkan.
ENDPOINT: endpoint API yang Anda gunakan untuk organisasi Anda. Untuk mengetahui informasi selengkapnya, lihat status dan endpoint layanan. Bergantung pada penggunaan yang dimaksudkan untuk token autentikasi, Anda mungkin perlu menyertakan port setelah endpoint layanan di jalur audiens sebagai berikut:
Jika Anda menggunakan library klien untuk permintaan, Anda harus menyertakan port :443 setelah endpoint layanan di jalur audiens. Oleh karena itu, jalur audience dalam skrip harus "https://ENDPOINT:443".
Jika Anda menggunakan gRPC, curl, atau panggilan REST terprogram untuk permintaan Anda, jangan sertakan port. Oleh karena itu, jalur audience dalam skrip harus "https://ENDPOINT".
Simpan skrip Python.
Jalankan skrip Python untuk mengambil token:
pythonSCRIPT_NAME
Ganti SCRIPT_NAME dengan nama yang Anda berikan ke skrip Python, seperti token.py.
Output menampilkan token autentikasi. Tambahkan token ke header permintaan command line yang Anda buat, seperti dalam contoh berikut:
-H"Authorization: Bearer TOKEN"
Ganti TOKEN dengan nilai untuk token autentikasi yang ditampilkan output.
[[["Mudah dipahami","easyToUnderstand","thumb-up"],["Memecahkan masalah saya","solvedMyProblem","thumb-up"],["Lainnya","otherUp","thumb-up"]],[["Sulit dipahami","hardToUnderstand","thumb-down"],["Informasi atau kode contoh salah","incorrectInformationOrSampleCode","thumb-down"],["Informasi/contoh yang saya butuhkan tidak ada","missingTheInformationSamplesINeed","thumb-down"],["Masalah terjemahan","translationIssue","thumb-down"],["Lainnya","otherDown","thumb-down"]],["Terakhir diperbarui pada 2025-09-04 UTC."],[[["\u003cp\u003eThis guide details the process of obtaining authentication tokens for accessing Vertex AI APIs on Google Distributed Cloud (GDC) air-gapped.\u003c/p\u003e\n"],["\u003cp\u003eAuthentication can be performed using either a user account or a service account, each with its own distinct set of steps.\u003c/p\u003e\n"],["\u003cp\u003eTo obtain a user account token, you must log in to Distributed Cloud and run a command that includes the relevant service endpoint.\u003c/p\u003e\n"],["\u003cp\u003eTo obtain a service account token, you'll use a python script that sets the relevant environmental variables and uses the \u003ccode\u003egoogle-auth\u003c/code\u003e client library, referencing the service key and relevant endpoint.\u003c/p\u003e\n"],["\u003cp\u003eThe obtained authentication token is then added to the header of your API requests as an authorization bearer token.\u003c/p\u003e\n"]]],[],null,["# Authenticate Vertex AI API requests\n\nThis page describes how to authenticate calls to Vertex AI services on Google Distributed Cloud (GDC) air-gapped. You must set up token authentication to secure your requests to the Vertex AI API within your air-gapped applications. This process validates your API requests by providing your identity and authorizing your interactions.\n\n\u003cbr /\u003e\n\nThis page is for application developers within application operator groups responsible for setting up their application and development environments to enable AI features. For more information, see [Audiences for GDC air-gapped documentation](/distributed-cloud/hosted/docs/latest/gdch/resources/audiences).\n\nBefore you begin\n----------------\n\nYou must have your project set up for Vertex AI. For more information, see [Set up a project for Vertex AI](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-set-up-project).\n\n- Make sure to update your local trust store before you set up authentication in your development environment.\n\nAuthenticating to Vertex AI services\n------------------------------------\n\nInteractions with Vertex AI services are done through authentication tokens. Tokens are digital objects that verify your identity and authorization after you provide valid credentials. The token carries specific information about your account and the permissions it has to access and operate with services and resources.\n\nThere are two ways you can set up authentication:\n\n- [Authenticate with your user account](#authenticate-with-user-account)\n- [Authenticate with your service account](#authenticate-with-service-account)\n\n### Authenticate with your user account\n\nThe following guides you through getting an authentication token for your user account:\n\n1. Note [the endpoint of the API](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-api-status) you want to use.\n\n2. Gain access to the Vertex AI service or Generative AI model you want to use by granting your user account the corresponding role listed in [Prepare IAM permissions](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-ao-permissions).\n\n3. Sign in to Distributed Cloud with the user account you have to interact with the API:\n\n gdcloud auth login\n\n4. Get the authentication token:\n\n gdcloud auth print-identity-token --audiences=https://\u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e\n\n Replace \u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e with the API endpoint that you use for your organization. For more information, [view service status and endpoints](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-api-status).\n\n Depending on the intended use of the authentication token, you might need to include the port after the service endpoint in the audiences path as follows:\n - If you use a [client library](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-install-libraries) for your request, you must include port `:443` after the service endpoint in the audiences path. Therefore, the `--audiences` path in the command must be `https://`\u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e`:443`.\n - If you use gRPC, `curl`, or programmatic REST calls for your request, don't include the port. Therefore, the `--audiences` path in the command must be `https://`\u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e.\n\n The output displays the authentication token. Add the token to the header of the command-line requests you make, as in the following example: \n\n -H \"Authorization: Bearer \u003cvar translate=\"no\"\u003eTOKEN\u003c/var\u003e\"\n\n Replace \u003cvar translate=\"no\"\u003eTOKEN\u003c/var\u003e with the value for the authentication token that the output displays.\n\n### Authenticate with your service account\n\nThe following guides you through getting an authentication token for your service account:\n\n1. Note [the endpoint of the API](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-api-status) you want to use.\n\n2. [Set up the service account](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-set-up-project#set-up-service) you want to use to access the Vertex AI service or Generative AI model.\n\n3. Grant the service account the corresponding role listed in [Prepare IAM permissions](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-ao-permissions) to let it gain access to the service or model you want to use.\n\n4. [Get the service key pairs of your service account](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/iam/service-identities#list_credentials_for_service_accounts).\n\n5. Set the following environment variable:\n\n export GOOGLE_APPLICATION_CREDENTIALS=\u003cvar translate=\"no\"\u003ePATH_TO_SERVICE_KEY\u003c/var\u003e\n\n Replace \u003cvar translate=\"no\"\u003ePATH_TO_SERVICE_KEY\u003c/var\u003e with the path to the JSON\n file that contains the key pairs of your service account.\n6. Install the `google-auth` client library:\n\n pip install google-auth\n\n7. Add the following code to a Python script:\n\n import os\n import google.auth\n from google.auth.transport import requests\n import requests as reqs\n\n os.environ[\"GOOGLE_APPLICATION_CREDENTIALS\"] = \"\u003cvar translate=\"no\"\u003ePATH_TO_SERVICE_KEY\u003c/var\u003e\"\n os.environ[\"GRPC_DEFAULT_SSL_ROOTS_FILE_PATH\"] = \"\u003cvar translate=\"no\"\u003eCERT_NAME\u003c/var\u003e\"\n\n # If you use a client library for your request,\n # you must include port :443 after the service endpoint\n # in the audience path.\n audience = \"https://\u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e\"\n\n creds, project_id = google.auth.default()\n print(project_id)\n creds = creds.with_gdch_audience(audience)\n\n def test_get_token():\n sesh = reqs.Session()\n req = requests.Request(session=sesh)\n creds.refresh(req)\n print(creds.token)\n\n if __name__==\"__main__\":\n test_get_token()\n\n Replace the following:\n - \u003cvar translate=\"no\"\u003ePATH_TO_SERVICE_KEY\u003c/var\u003e: the path to the JSON file that contains the key pairs of your service account.\n - \u003cvar translate=\"no\"\u003eCERT_NAME\u003c/var\u003e: the name of the Certificate Authority (CA) certificate file, such as `org-1-trust-bundle-ca.cert`. You only need this value if you are in a development environment. Otherwise, omit it.\n - \u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e: the API endpoint that you use for your organization. For more information, [view service status and endpoints](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-api-status). Depending on the intended use of the authentication token, you might need to include the port after the service endpoint in the audience path as follows:\n\n - If you use a [client library](/distributed-cloud/hosted/docs/latest/gdch/application/ao-user/vertex-ai-install-libraries) for your request, you must include port `:443` after the service endpoint in the audience path. Therefore, the `audience` path in the script must be `\"https://`\u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e`:443\"`.\n - If you use gRPC, `curl`, or programmatic REST calls for your request, don't include the port. Therefore, the `audience` path in the script must be `\"https://`\u003cvar translate=\"no\"\u003eENDPOINT\u003c/var\u003e`\"`.\n8. Save the Python script.\n\n9. Run the Python script to fetch the token:\n\n python \u003cvar translate=\"no\"\u003eSCRIPT_NAME\u003c/var\u003e\n\n Replace \u003cvar translate=\"no\"\u003eSCRIPT_NAME\u003c/var\u003e with the name you gave to your Python script, such as `token.py`.\n\n The output displays the authentication token. Add the token to the header of the command-line requests you make, as in the following example: \n\n -H \"Authorization: Bearer \u003cvar translate=\"no\"\u003eTOKEN\u003c/var\u003e\"\n\n Replace \u003cvar translate=\"no\"\u003eTOKEN\u003c/var\u003e with the value for the authentication token that the output displays."]]
