Authenticate

To use the OpenAI Python libraries, install the OpenAI SDK:

 pip  
install  
openai

To authenticate with the Chat Completions API, you can either modify your client setup or change your environment configuration to use Google authentication and a Vertex AI endpoint. Choose whichever method that's easier, and follow the steps for setting up depending on whether you want to call Gemini models or self-deployed Model Garden models.

Certain models in Model Garden and supported Hugging Face models need to be deployed to a Vertex AI endpoint first before they can serve requests. When calling these self-deployed models from the Chat Completions API, you need to specify the endpoint ID. To list your existing Vertex AI endpoints, use the gcloud ai endpoints list command .

Client setup

To programmatically get Google credentials in Python, you can use the google-auth Python SDK:

 pip  
install  
google-auth  
requests

Python

Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries . For more information, see the Vertex AI Python API reference documentation .

To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .

  import 
  
 openai 
 from 
  
 google.auth 
  
 import 
 default 
 import 
  
 google.auth.transport.requests 
 # TODO(developer): Update and un-comment below lines 
 # project_id = "PROJECT_ID" 
 # location = "us-central1" 
 # Programmatically get an access token 
 credentials 
 , 
 _ 
 = 
 default 
 ( 
 scopes 
 = 
 [ 
 "https://www.googleapis.com/auth/cloud-platform" 
 ]) 
 credentials 
 . 
 refresh 
 ( 
 google 
 . 
 auth 
 . 
 transport 
 . 
 requests 
 . 
 Request 
 ()) 
 # Note: the credential lives for 1 hour by default (https://cloud.google.com/docs/authentication/token-types#at-lifetime); after expiration, it must be refreshed. 
 ############################## 
 # Choose one of the following: 
 ############################## 
 # If you are calling a Gemini model, set the ENDPOINT_ID variable to use openapi. 
 ENDPOINT_ID 
 = 
 "openapi" 
 # If you are calling a self-deployed model from Model Garden, set the 
 # ENDPOINT_ID variable and set the client's base URL to use your endpoint. 
 # ENDPOINT_ID = "YOUR_ENDPOINT_ID" 
 # OpenAI Client 
 client 
 = 
 openai 
 . 
 OpenAI 
 ( 
 base_url 
 = 
 f 
 "https:// 
 { 
 location 
 } 
 -aiplatform.googleapis.com/v1/projects/ 
 { 
 project_id 
 } 
 /locations/ 
 { 
 location 
 } 
 /endpoints/ 
 { 
 ENDPOINT_ID 
 } 
 " 
 , 
 api_key 
 = 
 credentials 
 . 
 token 
 , 
 )

By default, service account access tokens last for 1 hour. You can extend the life of service account access tokens or periodically refresh your token and update the openai.api_key variable.

Environment variables

Install the Google Cloud CLI. The OpenAI library can read the OPENAI_API_KEY and OPENAI_BASE_URL environment variables to change the authentication and endpoint in their default client. Set the following variables:

 $  
 export 
  
 PROJECT_ID 
 = 
 PROJECT_ID 
$  
 export 
  
 LOCATION 
 = 
 LOCATION 
$  
 export 
  
 OPENAI_API_KEY 
 = 
 " 
 $( 
gcloud  
auth  
application-default  
print-access-token ) 
 "

To call a Gemini model, set the MODEL_ID variable and use the openapi endpoint:

 $  
 export 
  
 MODEL_ID 
 = 
 MODEL_ID 
$  
 export 
  
 OPENAI_BASE_URL 
 = 
 "https:// 
 ${ 
 LOCATION 
 } 
 -aiplatform.googleapis.com/v1beta1/projects/ 
 ${ 
 PROJECT_ID 
 } 
 /locations/ 
 ${ 
 LOCATION 
 } 
 /endpoints/openapi"

To call a self-deployed model from Model Garden, set the ENDPOINT variable and use that in your URL instead:

 $  
 export 
  
 ENDPOINT 
 = 
 ENDPOINT_ID 
$  
 export 
  
 OPENAI_BASE_URL 
 = 
 "https:// 
 ${ 
 LOCATION 
 } 
 -aiplatform.googleapis.com/v1beta1/projects/ 
 ${ 
 PROJECT_ID 
 } 
 /locations/ 
 ${ 
 LOCATION 
 } 
 /endpoints/ 
 ${ 
 ENDPOINT 
 } 
 "

Next, initialize the client:

  client 
 = 
 openai 
 . 
 OpenAI 
 ()

The Gemini Chat Completions API uses OAuth to authenticate with a short-lived access token . By default, service account access tokens last for 1 hour. You can extend the life of service account access tokens or periodically refresh your token and update the openai.api_key variable.

Refresh your credentials

The following example shows how to refresh your credentials automatically as needed:

Python

  from 
  
 typing 
  
 import 
 Any 
 import 
  
 google.auth 
 import 
  
 google.auth.transport.requests 
 import 
  
 openai 
 class 
  
 OpenAICredentialsRefresher 
 : 
 def 
  
 __init__ 
 ( 
 self 
 , 
 ** 
 kwargs 
 : 
 Any 
 ) 
 - 
> None 
 : 
 # Set a placeholder key here 
 self 
 . 
 client 
 = 
 openai 
 . 
 OpenAI 
 ( 
 ** 
 kwargs 
 , 
 api_key 
 = 
 "PLACEHOLDER" 
 ) 
 self 
 . 
 creds 
 , 
 self 
 . 
 project 
 = 
 google 
 . 
 auth 
 . 
 default 
 ( 
 scopes 
 = 
 [ 
 "https://www.googleapis.com/auth/cloud-platform" 
 ] 
 ) 
 def 
  
 __getattr__ 
 ( 
 self 
 , 
 name 
 : 
 str 
 ) 
 - 
> Any 
 : 
 if 
 not 
 self 
 . 
 creds 
 . 
 valid 
 : 
 self 
 . 
 creds 
 . 
 refresh 
 ( 
 google 
 . 
 auth 
 . 
 transport 
 . 
 requests 
 . 
 Request 
 ()) 
 if 
 not 
 self 
 . 
 creds 
 . 
 valid 
 : 
 raise 
 RuntimeError 
 ( 
 "Unable to refresh auth" 
 ) 
 self 
 . 
 client 
 . 
 api_key 
 = 
 self 
 . 
 creds 
 . 
 token 
 return 
 getattr 
 ( 
 self 
 . 
 client 
 , 
 name 
 ) 
 # TODO(developer): Update and un-comment below lines 
 # project_id = "PROJECT_ID" 
 # location = "us-central1" 
 client 
 = 
 OpenAICredentialsRefresher 
 ( 
 base_url 
 = 
 f 
 "https:// 
 { 
 location 
 } 
 -aiplatform.googleapis.com/v1/projects/ 
 { 
 project_id 
 } 
 /locations/ 
 { 
 location 
 } 
 /endpoints/openapi" 
 , 
 ) 
 response 
 = 
 client 
 . 
 chat 
 . 
 completions 
 . 
 create 
 ( 
 model 
 = 
 "google/gemini-2.0-flash-001" 
 , 
 messages 
 = 
 [{ 
 "role" 
 : 
 "user" 
 , 
 "content" 
 : 
 "Why is the sky blue?" 
 }], 
 ) 
 print 
 ( 
 response 
 )

What's next

See examples of calling the Chat Completions API with the OpenAI-compatible syntax.
See examples of calling the Inference API with the OpenAI-compatible syntax.
See examples of calling the Function Calling API with OpenAI-compatible syntax.
Learn more about the Gemini API .
Learn more about migrating from Azure OpenAI to the Gemini API .