> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
> Use this file to discover all available pages before exploring further.

# ChatVertexAI integration

> Integrate with the ChatVertexAI chat model using LangChain Python.

<Danger>
  **Deprecated**

  This integration is deprecated and will be removed in a future release. Please use [`ChatGoogleGenerativeAI`](/oss/python/integrations/chat/google_generative_ai) instead. See the full [release notes and migration guide](https://github.com/langchain-ai/langchain-google/discussions/1422).
</Danger>

Vertex AI exposes all foundational models available in Google Cloud, like `gemini-2.5-pro`, `gemini-2.5-flash`, etc. For a full and updated list of available models visit [VertexAI documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/models).

<Info>
  **Google Cloud VertexAI vs Gemini API**

  The Google Cloud VertexAI integration is separate from the [Google Gemini API](/oss/python/integrations/chat/google_generative_ai/). This page showcases an enterprise version of Gemini through Google Cloud Platform (GCP).
</Info>

<Tip>
  **API Reference**

  For detailed documentation of all features and configuration options, head to the [`ChatVertexAI`](https://reference.langchain.com/python/langchain-community/chat_models/vertexai/ChatVertexAI) API reference.
</Tip>

## Overview

### Integration details

| Class                                                                                                          | Package                                                                                          | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/google_vertex_ai) |                                                  Downloads                                                 |                                                 Version                                                 |
| :------------------------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------- | :----------: | :----------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------: |
| [`ChatVertexAI`](https://reference.langchain.com/python/langchain-community/chat_models/vertexai/ChatVertexAI) | [`langchain-google-vertexai`](https://reference.langchain.com/python/langchain-google-vertexai/) |     beta     |                                        ✅                                       | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-google-vertexai?style=flat-square\&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-google-vertexai?style=flat-square\&label=%20) |

### Model features

| [Tool calling](/oss/python/langchain/tools) | [Structured output](/oss/python/langchain/structured-output) | [Image input](/oss/python/langchain/messages#multimodal) | Audio input | Video input | [Token-level streaming](/oss/python/langchain/streaming/) | Native async | [Token usage](/oss/python/langchain/models#token-usage) | [Logprobs](/oss/python/langchain/models#log-probabilities) |
| :-----------------------------------------: | :----------------------------------------------------------: | :------------------------------------------------------: | :---------: | :---------: | :-------------------------------------------------------: | :----------: | :-----------------------------------------------------: | :--------------------------------------------------------: |
|                      ✅                      |                               ✅                              |                             ✅                            |      ✅      |      ✅      |                             ✅                             |       ✅      |                            ✅                            |                              ✅                             |

## Setup

To access VertexAI models you'll need to create a Google Cloud Platform account, set up credentials, and install the `langchain-google-vertexai` integration package.

### Credentials

To use the integration you must either:

* Have credentials configured for your environment (gcloud, workload identity, etc...)
* Store the path to a service account JSON file as the `GOOGLE_APPLICATION_CREDENTIALS` environment variable

This codebase uses the `google.auth` library which first looks for the application credentials variable mentioned above, and then looks for system-level auth.

For more information, see the `google.auth` [API reference](https://googleapis.dev/python/google-auth/latest/reference/google.auth.html#module-google.auth).

To enable automated tracing of your model calls, set your [LangSmith](/langsmith/observability) API key:

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")
os.environ["LANGSMITH_TRACING"] = "true"
```

### Installation

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

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
pip install -qU langchain-google-vertexai
```

## Instantiation

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

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_google_vertexai import ChatVertexAI

llm = ChatVertexAI(
    model="gemini-2.5-flash",
    temperature=0,
    max_tokens=None,
    max_retries=6,
    stop=None,
    # other params...
)
```

## Invocation

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
messages = [
    (
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ),
    ("human", "I love programming."),
]
ai_msg = llm.invoke(messages)
ai_msg
```

```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
AIMessage(content="J'adore programmer. \n", response_metadata={'is_blocked': False, 'safety_ratings': [{'category': 'HARM_CATEGORY_HATE_SPEECH', 'probability_label': 'NEGLIGIBLE', 'blocked': False}, {'category': 'HARM_CATEGORY_DANGEROUS_CONTENT', 'probability_label': 'NEGLIGIBLE', 'blocked': False}, {'category': 'HARM_CATEGORY_HARASSMENT', 'probability_label': 'NEGLIGIBLE', 'blocked': False}, {'category': 'HARM_CATEGORY_SEXUALLY_EXPLICIT', 'probability_label': 'NEGLIGIBLE', 'blocked': False}], 'usage_metadata': {'prompt_token_count': 20, 'candidates_token_count': 7, 'total_token_count': 27}}, id='run-7032733c-d05c-4f0c-a17a-6c575fdd1ae0-0', usage_metadata={'input_tokens': 20, 'output_tokens': 7, 'total_tokens': 27})
```

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
print(ai_msg.content)
```

```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
J'adore programmer.
```

## Built-in tools

Gemini supports a range of tools that are executed server-side.

### Google search

<Info>
  **Requires `langchain-google-vertexai>=2.0.11`**
</Info>

Gemini can execute a Google search and use the results to [ground its responses](https://ai.google.dev/gemini-api/docs/grounding):

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_google_vertexai import ChatVertexAI

llm = ChatVertexAI(model="gemini-2.5-flash").bind_tools([{"google_search": {}}])

response = llm.invoke("What is today's news?")
```

### Code execution

<Info>
  **Requires `langchain-google-vertexai>=2.0.25`**
</Info>

Gemini can [generate and execute Python code](https://ai.google.dev/gemini-api/docs/code-execution):

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_google_vertexai import ChatVertexAI

llm = ChatVertexAI(model="gemini-2.5-flash").bind_tools([{"code_execution": {}}])

response = llm.invoke("What is 3^3?")
```

***

## API reference

For detailed documentation of all features and configuration options, head to the [`ChatVertexAI`](https://reference.langchain.com/python/langchain-community/chat_models/vertexai/ChatVertexAI) API reference.

***

<div className="source-links">
  <Callout icon="terminal-2">
    [Connect these docs](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers.
  </Callout>

  <Callout icon="edit">
    [Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/oss/python/integrations/chat/google_vertex_ai.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose).
  </Callout>
</div>