ChatVertexAI 集成

使用 LangChain Python 集成 ChatVertexAI 聊天模型。

Deprecated

This integration is deprecated and will be removed in a future release. Please use ChatGoogleGenerativeAI instead. See the full release notes and migration guide.

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.

Google Cloud VertexAI vs Gemini API

The Google Cloud VertexAI integration is separate from the Google Gemini API. This page showcases an enterprise version of Gemini through Google Cloud Platform (GCP).

API 参考

有关所有 features and configuration options, 请前往 ChatVertexAI API reference.

概述

集成详情

类	包	可序列化	JS 支持	下载量	版本
ChatVertexAI	langchain-google-vertexai	beta	✅

模型功能

Tool calling	Structured output	Image input	音频输入	视频输入	Token-level streaming	原生异步	Token usage	Logprobs
✅	✅	✅	✅	✅	✅	✅	✅	✅

设置

要访问 VertexAI 模型，您需要创建一个 Google Cloud Platform account, set up credentials, and install the langchain-google-vertexai 集成包。

凭证

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.

更多信息，请参阅 the google.auth API reference.

要启用模型调用的自动追踪，请设置您的 LangSmith API key:

os.environ["LANGSMITH_API_KEY"] = getpass.getpass("请输入您的 LangSmith API 密钥: ")
os.environ["LANGSMITH_TRACING"] = "true"

安装

LangChain 的 VertexAI 集成位于 langchain-google-vertexai 包中：

pip install -qU langchain-google-vertexai

实例化

现在我们可以实例化模型对象并生成聊天补全：

from langchain_google_vertexai import ChatVertexAI

llm = ChatVertexAI(
    model="gemini-2.5-flash",
    temperature=0,
    max_tokens=None,
    max_retries=6,
    stop=None,
    # 其他参数...
)

调用

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

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})

print(ai_msg.content)

J'adore programmer.

Built-in tools

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

Google search

Requires langchain-google-vertexai>=2.0.11

Gemini can execute a Google search and use the results to ground its responses:

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

Requires langchain-google-vertexai>=2.0.25

Gemini can generate and execute Python code:

from langchain_google_vertexai import ChatVertexAI

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

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

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API 参考

有关所有 features and configuration options, 请前往 ChatVertexAI API reference.

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