azure.ai.ml.entities._endpoint.online_endpoint.OnlineEndpoint ManagedOnlineEndpoint 构造函数Python 复制 ManagedOnlineEndpoint(*, name: str | None = None, tags: Dict[str, Any] | None = None, properties: Dict[str, Any] | None = None, auth_mode: str = 'key', description: str | None...
GET https://management.azure.com/subscriptions/{subscriptionId}/providers/Microsoft.Network/locations/{region}/availablePrivateEndpointTypes?api-version=2021-03-01 输出应包括 Microsoft.ApiManagement.service 终结点类型:JSON 复制 [...] "name": "Microsoft.ApiManagement.service", "id": "/subscriptions...
通过运行以下命令设置终结点名称(将 YOUR_ENDPOINT_NAME 替换为唯一名称): Azure CLI 复制 export ENDPOINT_NAME="<YOUR_ENDPOINT_NAME>" 配置终结点: create-endpoint.yaml YAML 复制 $schema: https://azuremlschemas.azureedge.net/latest/managedOnlineEndpoint.schema.json name: my-endpoint auth_m...
model_name = "azureml://registries/azureml/models/deepset-roberta-base-squad2/versions/16" demo_deployment = ManagedOnlineDeployment( name="demo", endpoint_name=online_endpoint_name, model=model_name, instance_type="Standard_DS3_v2", instance_count=2, liveness_probe=ProbeSettings( failure_thre...
("OpenAI API key is required") try: from openai.lib.azure import AzureOpenAI except ImportError as exc: raise ImportError("Please install the openai package: pip install openai") from exc return AzureOpenAI(api_key=self.api_key, azure_endpoint=self.azure_endpoint, api_version=self.api_...
接下来让我们部署模型。点击资源管理中的模型部署 → 管理部署。 页面会跳转到Azure AI Studio中,点击[create new deployment](这里我选择 gpt-35-turbo),输入[Deployment name],点击[Create]。 创建完成后,您可以点击[Chat],在窗口进行交流了。 调用API 的 Endpoint 点击View Code查看代码,可直接API调用。
{your SP Client ID}"APP_SECRET="{your SP secret}"KUSTO_CLUSTER="{your adx cluster endpoint in format https://xxx.region.kusto.chinacloudapi.cn:443/}"#Init ADX ClientKCSB =KustoConnectionStringBuilder.with_aad_application_key_authentication(KUSTO_CLUSTER, APP_CLIENT_ID, APP_SECRET, AAD_...
Developers can use the standard MLflow tracking API to track runs and deploy models directly into Azure Machine Learning service. We also announced that managed MLflow is generally available on Azure Databricks and will use Azure Machine Learning to track the full ML lifecycle. The combination of ...
{ private String clientId=""; private String clientSecret=""; private String grantType = "client_credentials"; private String tokenEndpoint = "https://login.partner.microsoftonline.cn/{teantId}/oauth2/v2.0/token"; private String resourceId = "https://microsoftgraph.chinacloudapi.cn/.default...
("OpenAI API key is required") try: from openai.lib.azure import AzureOpenAI except ImportError as exc: raise ImportError("Please install the openai package: pip install openai") from exc return AzureOpenAI(api_key=self.api_key, azure_endpoint=self.azure_endpoint, api_version=self.api_...