Vercel AI SDK - Anthropic Vertex Provider
nalaso/anthropic-vertex-ai is a community provider that uses Anthropic models through Vertex AI to provide language model support for the Vercel AI SDK.
Docs - anthropic-vertex-ai Documentation
Setup
The AnthropicVertex provider is available in the anthropic-vertex-ai module. You can install it with:
npm install anthropic-vertex-ai
# or
pnpm add anthropic-vertex-ai
# or
yarn add anthropic-vertex-ai
# or
bun add anthropic-vertex-ai
Provider Instance
You can import the default provider instance anthropicVertex from anthropic-vertex-ai:
import { anthropicVertex } from 'anthropic-vertex-ai';
If you need a customized setup, you can import createAnthropicVertex from anthropic-vertex-ai and create a provider instance with your settings:
import { createAnthropicVertex } from 'anthropic-vertex-ai';
const anthropicVertex = createAnthropicVertex({
region: 'us-central1',
projectId: 'your-project-id',
// other options
});
You can use the following optional settings to customize the AnthropicVertex provider instance:
-
region string
Your Google Vertex region. Defaults to the GOOGLE_VERTEX_REGION environment variable.
-
projectId string
Your Google Vertex project ID. Defaults to the GOOGLE_VERTEX_PROJECT_ID environment variable.
-
googleAuth GoogleAuth
Optional. The Authentication options provided by google-auth-library.
-
baseURL string
Use a different URL prefix for API calls, e.g., to use proxy servers.
The default prefix is https://{region}-aiplatform.googleapis.com/v1.
-
headers Record<string,string>
Custom headers to include in the requests.
-
fetch (input: RequestInfo, init?: RequestInit) => Promise<Response>
Custom fetch implementation. You can use it as a middleware to intercept requests,
or to provide a custom fetch implementation for e.g., testing.
Language Models
You can create models that call the Anthropic API through Vertex AI using the provider instance.
The first argument is the model ID, e.g., claude-3-sonnet@20240229:
const model = anthropicVertex('claude-3-sonnet@20240229');
Example: Generate Text
You can use AnthropicVertex language models to generate text with the generateText function:
import { anthropicVertex } from 'anthropic-vertex-ai';
import { generateText } from 'ai';
const { text } = await generateText({
model: anthropicVertex('claude-3-sonnet@20240229'),
prompt: 'Write a vegetarian lasagna recipe for 4 people.',
});
AnthropicVertex language models can also be used in the streamText, generateObject, and streamObject functions
(see AI SDK Core for more information).
Model Capabilities
| Model | Image Input | Object Generation | Tool Usage | Tool Streaming |
|---|
claude-3-5-sonnet@20240620 | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |
claude-3-opus@20240229 | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |
claude-3-sonnet@20240229 | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |
claude-3-haiku@20240307 | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |
Environment Variables
To use the AnthropicVertex provider, you need to set up the following environment variables:
GOOGLE_VERTEX_REGION: Your Google Vertex region (e.g., 'us-central1')GOOGLE_VERTEX_PROJECT_ID: Your Google Cloud project ID
Make sure to set these variables in your environment or in a .env file in your project root.
Authentication
The AnthropicVertex provider uses Google Cloud authentication. Make sure you have set up your Google Cloud credentials properly. You can either use a service account key file or default application credentials.
For more information on setting up authentication, refer to the Google Cloud Authentication guide.
