python - 如何使用 Python 在 Unified AI Platform 上编辑端点设置？

Question

我已经成功地在统一云 AI 平台上创建了一个端点，并在其上部署了两个Model-Model A分别Model B具有 20% 和 80% 的流量。现在，在 Cloud Console（用户界面）上，我可以选择编辑设置 并将流量拆分分别更改为 30% 和 70%，然后Model部署 s。但是我无法弄清楚如何使用 Python Client API 来做到这一点。

此处提供的文档不足以理解我们如何做到这一点。任何帮助将不胜感激。

Answer 1

AI Platform Unified 的文档还没有关于如何使用 python 编辑流量的示例。这是代码：

注意：不要忘记在运行代码之前更新end_point（端点 ID）、（project项目 ID）的值。model_id_1model_id_2

from google.cloud import aiplatform
from google.cloud import aiplatform_v1


def update_endpoint_traffic(
    end_point: str, 
    project: str, 
    location: str = "us-central1",
    api_endpoint: str = "us-central1-aiplatform.googleapis.com",
    timeout: int = 7200,
):
    # The AI Platform services require regional API endpoints.
    client_options = {"api_endpoint": api_endpoint}
    # Initialize client that will be used to create and send requests.
    # This client only needs to be created once, and can be reused for multiple requests.
    client = aiplatform.gapic.EndpointServiceClient(client_options=client_options)
    client_model = aiplatform_v1.services.model_service.ModelServiceClient(client_options=client_options)

    deployed_model_id_list = []
    model_id_1 = 'xxxxxxxx' # place your model id here
    model_id_2 = 'xxxxxxxx' # place your model id here
    model_list = [f'projects/{project}/locations/{location}/models/{model_id_1}',f'projects/{project}/locations/{location}/models/{model_id_2}']

    for model in model_list:
        model_request = aiplatform_v1.types.GetModelRequest(name=model)
        model_info = client_model.get_model(request=model_request)
        deployed_models_info = model_info.deployed_models
        deployed_model_id=model_info.deployed_models[0].deployed_model_id
        deployed_model_id_list.append(deployed_model_id)

    traffic_split = {deployed_model_id_list[0]: 60, deployed_model_id_list[1]:40} #update values of 60 and 40 to desired traffic split ex.(30 70)

    name=f'projects/{project}/locations/{location}/endpoints/{end_point}'

    endpoint = aiplatform_v1.types.Endpoint(name=name,traffic_split=traffic_split)
    update_endpoint = aiplatform_v1.types.UpdateEndpointRequest(endpoint=endpoint)
    client.update_endpoint(request=update_endpoint)

update_endpoint_traffic(end_point='your-endpoint-id',project='your-project-id')