async def sample_get_endpoint():
# Create a client
client = aiplatform_v1beta1.EndpointServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.GetEndpointRequest(name="name_value", )
# Make the request
response = await client.get_endpoint(request=request)
# Handle the response
print(response)
async def sample_list_endpoints():
# Create a client
client = aiplatform_v1beta1.EndpointServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.ListEndpointsRequest(parent="parent_value", )
# Make the request
page_result = client.list_endpoints(request=request)
# Handle the response
async for response in page_result:
print(response)
async def sample_update_endpoint():
# Create a client
client = aiplatform_v1beta1.EndpointServiceAsyncClient()
# Initialize request argument(s)
endpoint = aiplatform_v1beta1.Endpoint()
endpoint.display_name = "display_name_value"
request = aiplatform_v1beta1.UpdateEndpointRequest(endpoint=endpoint, )
# Make the request
response = await client.update_endpoint(request=request)
# Handle the response
print(response)
async def sample_delete_endpoint():
# Create a client
client = aiplatform_v1beta1.EndpointServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.DeleteEndpointRequest(name="name_value", )
# Make the request
operation = client.delete_endpoint(request=request)
print("Waiting for operation to complete...")
response = await operation.result()
# Handle the response
print(response)
async def sample_undeploy_model():
# Create a client
client = aiplatform_v1beta1.EndpointServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.UndeployModelRequest(
endpoint="endpoint_value",
deployed_model_id="deployed_model_id_value",
)
# Make the request
operation = client.undeploy_model(request=request)
print("Waiting for operation to complete...")
response = await operation.result()
# Handle the response
print(response)
async def sample_deploy_model():
# Create a client
client = aiplatform_v1beta1.EndpointServiceAsyncClient()
# Initialize request argument(s)
deployed_model = aiplatform_v1beta1.DeployedModel()
deployed_model.dedicated_resources.min_replica_count = 1803
deployed_model.model = "model_value"
request = aiplatform_v1beta1.DeployModelRequest(
endpoint="endpoint_value",
deployed_model=deployed_model,
)
# Make the request
operation = client.deploy_model(request=request)
print("Waiting for operation to complete...")
response = await operation.result()
# Handle the response
print(response)