设置环境

在 Vertex AI 中使用 LangChain 之前，您需要确保已设置环境。您需要有启用了结算功能的 Google Cloud 项目，具有所需的权限，设置 Cloud Storage 存储桶，并安装 Vertex AI SDK for Python。请参阅以下主题，确保您已准备好开始在 Vertex AI 中使用 LangChain。

设置您的 Google Cloud 项目

Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the Vertex AI and Cloud Storage APIs.

Enable the APIs

In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

Go to project selector

Verify that billing is enabled for your Google Cloud project.

Enable the Vertex AI and Cloud Storage APIs.

Enable the APIs

获取所需的角色

如需获得使用推理引擎所需的权限，请让您的管理员为您授予项目的以下 IAM 角色：

• Vertex AI User (roles/aiplatform.user)
• Storage Admin (roles/storage.admin)

如需详细了解如何授予角色，请参阅管理对项目、文件夹和组织的访问权限。

您也可以通过自定义角色或其他预定义角色来获取所需的权限。

设置您的服务代理权限

您在推理引擎上部署的应用会以 AI Platform Reasoning Engine Service Agent 服务账号的身份运行。此账号具有 Vertex AI Reasoning Engine Service Agent 角色，该角色可授予推理引擎应用所需的基本权限。您可以在 IAM 文档中查看基本权限的完整列表。

如果您需要其他权限，可以通过执行以下步骤向此 Service Agent 授予其他角色：

1. 前往 IAM 页面，然后勾选“包括 Google 提供的角色授权”复选框。

   进入 IAM

2. 找到与 [e-mail] 匹配的主账号。

3. 依次点击“编辑”按钮和“保存”按钮，向主账号添加所需的角色。

手动生成 Reasoning Engine Service Agent

虽然 Reasoning Engine Service Agent 会在推理引擎部署期间自动预配，但在某些情况下，您可能需要事先手动生成 Reasoning Engine Service Agent。如果您需要向 Reasoning Engine Service Agent 授予特定角色，以确保部署过程具有必要的权限并避免可能发生的部署失败，则这一点尤为重要。

以下是手动生成 Reasoning Engine Service Agent 的步骤：

1. 使用 Google Cloud CLI 生成 Reasoning Engine Service Agent。

   gcloud beta services identity create --service=aiplatform.googleapis.com --project=PROJECT-ID-OR-PROJECT-NUMBER

   注意：Google Cloud CLI 命令的响应可能仅显示 Vertex AI Service Agent。但是，系统还会创建 Reasoning Engine Service Agent。

2. 前往 IAM 页面，然后点击授予访问权限。

   进入 IAM

3. 在添加主账号部分的新的主账号字段中，输入 [e-mail]。

4. 在分配角色部分，找到并选择您需要的角色。

5. 点击保存按钮。

创建 Cloud Storage 存储桶

推理引擎会在部署过程中将应用的制品暂存在 Cloud Storage 存储桶中。确保已通过身份验证以使用 Vertex AI 的主账号（您自己或服务账号）对此存储桶具有 Storage Admin 访问权限。这是因为 Vertex AI SDK for Python 会打包您的代码并将其写入此存储桶。

Google Cloud 控制台

1. In the Google Cloud console, go to the Cloud Storage Buckets page.

   Go to Buckets

2. Click Create.
3. On the Create a bucket page, enter your bucket information. To go to the next step, click Continue.
   1. In the Get started section, do the following:
      • Enter a globally unique name that meets the bucket naming requirements.
      • To add a bucket label, expand the Labels section (), click Add label, and specify a key and a value for your label.
   2. In the Choose where to store your data section, do the following:
      1. Select a Location type.
      2. Choose a location where your bucket's data is permanently stored from the Location type drop-down menu.
         • If you select the dual-region location type, you can also choose to enable turbo replication by using the relevant checkbox.
      3. To set up cross-bucket replication, select Add cross-bucket replication via Storage Transfer Service and follow these steps:

         Set up cross-bucket replication

         1. In the Bucket menu, select a bucket.

         2. In the Replication settings section, click Configure to configure settings for the replication job.

            The Configure cross-bucket replication pane appears.

            • To filter objects to replicate by object name prefix, enter a prefix that you want to include or exclude objects from, then click Add a prefix.
            • To set a storage class for the replicated objects, select a storage class from the Storage class menu. If you skip this step, the replicated objects will use the destination bucket's storage class by default.
            • Click Done.
   3. In the Choose how to store your data section, do the following:
      1. Select a default storage class for the bucket or Autoclass for automatic storage class management of your bucket's data.
      2. To enable hierarchical namespace, in the Optimize storage for data-intensive workloads section, select Enable hierarchical namespace on this bucket.
         Note: You cannot enable hierarchical namespace in existing buckets.
   4. In the Choose how to control access to objects section, select whether or not your bucket enforces public access prevention, and select an access control method for your bucket's objects.
      Note: You cannot change the Prevent public access setting if this setting is enforced at an organization policy.
   5. In the Choose how to protect object data section, do the following:
      • Select any of the options under Data protection that you want to set for your bucket.
        • To enable soft delete, click the Soft delete policy (For data recovery) checkbox, and specify the number of days you want to retain objects after deletion.
        • To set Object Versioning, click the Object versioning (For version control) checkbox, and specify the maximum number of versions per object and the number of days after which the noncurrent versions expire.
        • To enable the retention policy on objects and buckets, click the Retention (For compliance) checkbox, and then do the following:
          • To enable Object Retention Lock, click the Enable object retention checkbox.
          • To enable Bucket Lock, click the Set bucket retention policy checkbox, and choose a unit of time and a length of time for your retention period.
      • To choose how your object data will be encrypted, expand the Data encryption section (), and select a Data encryption method.
4. Click Create.

命令行

Create a Cloud Storage bucket and configure it as follows:
• 将 STORAGE_CLASS 替换为您偏好的存储类别。
• 将 LOCATION 替换为您偏好的位置（ASIA、EU 或 US）
• 将 BUCKET_NAME 替换为 符合存储桶名称要求的存储桶名称。

gcloud storage buckets create gs://BUCKET_NAME --default-storage-class STORAGE_CLASS --location LOCATION

安装并初始化 Python 版 Vertex AI SDK

运行以下命令以安装 Vertex AI SDK for Python 推理引擎软件包：

pip install google-cloud-aiplatform[reasoningengine,langchain]

运行以下代码，以导入并初始化适用于 Reasoning Engine 的 SDK：

import vertexai
from vertexai.preview import reasoning_engines

vertexai.init(
    project="PROJECT_ID",
    location="LOCATION",
    staging_bucket="gs://BUCKET_NAME",
)

• PROJECT_ID：您的项目 ID。
• LOCATION：您的区域。 目前只支持 us-central1。
• BUCKET_NAME：您的 Google Cloud 存储桶。

后续步骤

• 开发应用。