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Overview

The Vertex AI Anthropic provider connects core-ai to Claude models hosted on Google Vertex AI through the official @anthropic-ai/vertex-sdk client. It shares its request, streaming, tool-calling, structured-output, and reasoning behavior with @core-ai/anthropic — everything documented on the Anthropic Provider page applies equally here.

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Installation

npm install @core-ai/anthropic-vertex

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createAnthropicVertex()

Create a Vertex AI Anthropic provider instance. 
import { createAnthropicVertex } from '@core-ai/anthropic-vertex';

const anthropicVertex = createAnthropicVertex({
    projectId: process.env.GOOGLE_VERTEX_PROJECT,
    region: 'europe-west1',
});

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Options

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projectId
string
Your Google Cloud project id. Required unless client is provided.
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region
string
The Vertex AI region hosting the Claude model, for example europe-west1 or eu. Required unless client is provided. A provider instance targets a single region — create separate providers if you need models hosted in different regions.
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credentials
object
A parsed Google service account JSON key. When omitted, the provider falls back to Application Default Credentials (ADC).
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client
AnthropicChatClient
Provide your own configured client (for example a custom AnthropicVertex instance).
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defaultMaxTokens
number
default:"4096"
Default maximum tokens for completions. Can be overridden per request.

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Returns

AnthropicVertexProvider with method chatModel().

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Authentication

By default, the provider uses Application Default Credentials: 
const anthropicVertex = createAnthropicVertex({
    projectId: process.env.GOOGLE_VERTEX_PROJECT,
    region: 'europe-west1',
});
To authenticate with an explicit service account instead, parse the service account JSON and pass the resulting object as credentials: 
const anthropicVertex = createAnthropicVertex({
    projectId: process.env.GOOGLE_VERTEX_PROJECT,
    region: 'europe-west1',
    credentials: JSON.parse(
        process.env.GOOGLE_APPLICATION_CREDENTIALS_JSON ?? ''
    ),
});
You can also inject a preconfigured client: 
import { AnthropicVertex } from '@anthropic-ai/vertex-sdk';
import { createAnthropicVertex } from '@core-ai/anthropic-vertex';

const anthropicVertex = createAnthropicVertex({
    client: new AnthropicVertex({ projectId: 'my-project', region: 'eu' }),
});

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Model IDs and regions

Pass the Vertex model id (as listed in the Vertex AI Model Garden) to chatModel(). Model availability and naming vary by region — some Claude models are published to Vertex AI’s eu multi-region while others are published to region-specific endpoints such as europe-west1. Since a provider instance targets a single region, create separate providers for models hosted in different regions: 
const anthropicVertexEu = createAnthropicVertex({
    projectId: process.env.GOOGLE_VERTEX_PROJECT,
    region: 'eu',
});
const anthropicVertexEuWest1 = createAnthropicVertex({
    projectId: process.env.GOOGLE_VERTEX_PROJECT,
    region: 'europe-west1',
});

const model = anthropicVertexEuWest1.chatModel('claude-sonnet-4-6');
Pass the unversioned Vertex model id (e.g. claude-sonnet-4-6) rather than a version-pinned id (e.g. claude-sonnet-4-6@20250929). Reasoning- effort and sampling-restriction capability detection (getAnthropicModelCapabilities and friends in @core-ai/anthropic) only recognizes the unversioned form today, so a version-pinned id silently falls back to standard capabilities instead of the model’s actual ones.

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Capabilities

FeatureSupport
Chat CompletionYes
StreamingYes
Function CallingYes
VisionYes
ReasoningYes
Prompt CachingYes
EmbeddingsNo
Image GenerationNo
Model capability helpers such as getAnthropicModelCapabilities(modelId) are available from @core-ai/anthropic and apply to Vertex-hosted Claude models.

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Examples

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Basic chat

import { generate } from '@core-ai/core-ai';
import { createAnthropicVertex } from '@core-ai/anthropic-vertex';

const anthropicVertex = createAnthropicVertex({
    projectId: process.env.GOOGLE_VERTEX_PROJECT,
    region: 'europe-west1',
});

const result = await generate({
    model: anthropicVertex.chatModel('claude-sonnet-4-6'),
    messages: [{ role: 'user', content: 'Explain the theory of relativity' }],
    maxTokens: 1024,
});

console.log(result.content);

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Streaming

import { stream } from '@core-ai/core-ai';

const chatStream = await stream({
    model: anthropicVertex.chatModel('claude-sonnet-4-6'),
    messages: [{ role: 'user', content: 'Write a detailed analysis of...' }],
    maxTokens: 1024,
});

for await (const event of chatStream) {
    if (event.type === 'text-delta') {
        process.stdout.write(event.text);
    }
}

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Provider-specific options and reasoning

Provider options are namespaced under anthropic in providerOptions, matching @core-ai/anthropic: 
const result = await generate({
    model: anthropicVertex.chatModel('claude-sonnet-4-6'),
    messages: [{ role: 'user', content: 'Hello' }],
    maxTokens: 1024,
    providerOptions: {
        anthropic: {
            stopSequences: ['\n\n'],
        },
    },
});
See the Anthropic Provider docs for the full list of available fields, reasoning restrictions, and prompt-caching behavior — they apply unchanged to Vertex-hosted Claude models.

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Error handling

import { ProviderError } from '@core-ai/core-ai';

try {
    const result = await generate({
        model: anthropicVertex.chatModel('claude-sonnet-4-6'),
        messages: [{ role: 'user', content: 'Hello!' }],
        maxTokens: 1024,
    });
} catch (error) {
    if (error instanceof ProviderError) {
        console.error('Vertex Anthropic API error:', error.message);
        console.error('Status:', error.statusCode);
    }
}
Errors are attributed to provider id anthropic-vertex, distinguishing them from direct @core-ai/anthropic errors (anthropic).

Anthropic Provider

Claude models via the direct Anthropic API

Google GenAI Provider

Gemini models with multimodal support

Chat Completion Guide

Learn how to use chat completion