> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-opensw-1783454697-4d4e2b4.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Google Vertex AI integration

> Integrate with the Google Vertex AI LLM using LangChain JavaScript.

<Warning>
  **You are currently on a page documenting the use of Google Vertex models as text completion models. Many popular models available on Google Vertex are [chat completion models](/oss/javascript/langchain/models).**

  You may be looking for [this page instead](/oss/javascript/integrations/chat/google_vertex_ai/).
</Warning>

[Google Vertex](https://cloud.google.com/vertex-ai) is a service that exposes all foundation models available in Google Cloud, like `gemini-2.5-pro`, `gemini-2.5-flash`, etc.

This will help you get started with VertexAI completion models (LLMs) using LangChain. For detailed documentation on `VertexAI` features and configuration options, please refer to the [API reference](https://reference.langchain.com/javascript/langchain-google-vertexai/index/VertexAI).

## Overview

### Integration details

| Class                                                                                             | Package                                                                                  | Local | Serializable | PY support |                                                  Downloads                                                 |                                                 Version                                                 |
| :------------------------------------------------------------------------------------------------ | :--------------------------------------------------------------------------------------- | :---: | :----------: | :--------: | :--------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------: |
| [`VertexAI`](https://reference.langchain.com/javascript/langchain-google-vertexai/index/VertexAI) | [`@langchain/google-vertexai`](https://www.npmjs.com/package/@langchain/google-vertexai) |   ❌   |       ✅      |      ✅     | ![NPM - Downloads](https://img.shields.io/npm/dm/@langchain/google-vertexai?style=flat-square\&label=%20&) | ![NPM - Version](https://img.shields.io/npm/v/@langchain/google-vertexai?style=flat-square\&label=%20&) |

## Setup

LangChain.js supports two different authentication methods based on whether
you're running in a Node.js environment or a web environment.

To access VertexAI models you'll need to create a Google Cloud Platform (GCP) account, get an API key, and install the `@langchain/google-vertexai` integration package. On Node.js, that package uses [`@langchain/google-gauth`](https://github.com/langchain-ai/langchainjs/tree/main/libs/providers/langchain-google-gauth) for authentication (you do not need to install it separately).

### Credentials

#### Node.js

You should make sure the Vertex AI API is
enabled for the relevant project and that you've authenticated to
Google Cloud using one of these methods:

* You are logged into an account (using `gcloud auth application-default login`)
  permitted to that project.
* You are running on a machine using a service account that is permitted
  to the project.
* You have downloaded the credentials for a service account that is permitted
  to the project and set the `GOOGLE_APPLICATION_CREDENTIALS` environment
  variable to the path of this file.
  **or**
* You set the `GOOGLE_API_KEY` environment variable to the API key for the project.

#### Web

To call Vertex AI models in web environments (like Edge functions), you'll need to install
the `@langchain/google-vertexai-web` package.

Then, set your service account credentials in `GOOGLE_WEB_CREDENTIALS` (or the deprecated `GOOGLE_VERTEX_AI_WEB_CREDENTIALS`):

```bash theme={null}
export GOOGLE_WEB_CREDENTIALS='{"type":"service_account","project_id":"YOUR_PROJECT-12345",...}'
```

You can also pass your credentials directly in code like this:

```typescript theme={null}
import { VertexAI } from "@langchain/google-vertexai";
// Or uncomment this line if you're using the web version:
// import { VertexAI } from "@langchain/google-vertexai-web";

const model = new VertexAI({
  authOptions: {
    credentials: {"type":"service_account","project_id":"YOUR_PROJECT-12345",...},
  },
});
```

If you want to get automated tracing of your model calls you can also set your [LangSmith](/langsmith/observability) API key by uncommenting below:

```bash theme={null}
# export LANGSMITH_TRACING="true"
# export LANGSMITH_API_KEY="your-api-key"
```

### Installation

The LangChain VertexAI integration lives in the `@langchain/google-vertexai` package:

<CodeGroup>
  ```bash npm theme={null}
  npm install @langchain/google-vertexai @langchain/core
  ```

  ```bash yarn theme={null}
  yarn add @langchain/google-vertexai @langchain/core
  ```

  ```bash pnpm theme={null}
  pnpm add @langchain/google-vertexai @langchain/core
  ```
</CodeGroup>

or for web environments:

<CodeGroup>
  ```bash npm theme={null}
  npm install @langchain/google-vertexai-web @langchain/core
  ```

  ```bash yarn theme={null}
  yarn add @langchain/google-vertexai-web @langchain/core
  ```

  ```bash pnpm theme={null}
  pnpm add @langchain/google-vertexai-web @langchain/core
  ```
</CodeGroup>

## Instantiation

Now we can instantiate our model object and generate chat completions:

```typescript theme={null}
import { VertexAI } from "@langchain/google-vertexai-web"

const llm = new VertexAI({
  model: "gemini-pro",
  temperature: 0,
  maxRetries: 2,
  // other params...
})
```

## Invocation

```typescript theme={null}
const inputText = "VertexAI is an AI company that "

const completion = await llm.invoke(inputText)
completion
```

```txt theme={null}
offers a wide range of cloud computing services and artificial intelligence solutions to businesses and developers worldwide.
```

***

## API reference

For detailed documentation of all `VertexAI` features and configurations head to the [API reference](https://reference.langchain.com/javascript/langchain-google-vertexai/index/VertexAI).

***

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