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

# GoogleGenerativeAI 集成

> 在 LangChain 中开始使用传统 Gemini LLM。

> [!WARNING]
>
> **您当前所在的页面是关于使用 Google 模型作为文本补全模型的文档。许多流行的 Google 模型是 [chat completion models](https://langchain-docs-zh.mintlify.site/langchain/oss/langchain/models.md)。**
>
> 您可能需要查找 [此页面](https://langchain-docs-zh.mintlify.site/langchain/oss/python/integrations/chat/google_generative_ai.md)。

关于使用 [Google Generative AI](https://developers.generativeai.google/) 模型与 LangChain 集成的指南。注意：这与 Gemini 企业智能体平台 [集成](https://langchain-docs-zh.mintlify.site/langchain/oss/python/integrations/llms/google_vertex_ai.md) 无关。

## 设置

要使用 Google Generative AI，必须安装 `langchain-google-genai` Python 包并生成 API 键。[阅读更多细节](https://developers.generativeai.google/)。

```python theme={null}
pip install -qU  langchain-google-genai
```

```python theme={null}
from langchain_google_genai import GoogleGenerativeAI
```

```python theme={null}
from getpass import getpass

api_key = getpass()
```

```python theme={null}
llm = GoogleGenerativeAI(model="gemini-3.6-flash", google_api_key=api_key)
print(
    llm.invoke(
        "What are some of the pros and cons of Python as a programming language?"
    )
)
```

```text theme={null}
**Pros:**

* **Simplicity and Readability:** Python is known for its simple and easy-to-read syntax, which makes it accessible to beginners and reduces the chance of errors. It uses indentation to define blocks of code, making the code structure clear and visually appealing.

* **Versatility:** Python is a general-purpose language, meaning it can be used for a wide range of tasks, including web development, data science, machine learning, and desktop applications. This versatility makes it a popular choice for various projects and industries.

* **Large Community:** Python has a vast and active community of developers, which contributes to its growth and popularity. This community provides extensive documentation, tutorials, and open-source libraries, making it easy for Python developers to find support and resources.

* **Extensive Libraries:** Python offers a rich collection of libraries and frameworks for various tasks, such as data analysis (NumPy, Pandas), web development (Django, Flask), machine learning (Scikit-learn, TensorFlow), and many more. These libraries provide prebuilt functions and modules, allowing developers to quickly and efficiently solve common problems.

* **Cross-Platform Support:** Python is cross-platform, meaning it can run on various operating systems, including Windows, macOS, and Linux. This allows developers to write code that can be easily shared and used across different platforms.

**Cons:**

* **Speed and Performance:** Python is generally slower than compiled languages like C++ or Java due to its interpreted nature. This can be a disadvantage for performance-intensive tasks, such as real-time systems or heavy numerical computations.

* **Memory Usage:** Python programs tend to consume more memory compared to compiled languages. This is because Python uses a dynamic memory allocation system, which can lead to memory fragmentation and higher memory usage.

* **Lack of Static Typing:** Python is a dynamically typed language, which means that data types are not explicitly defined for variables. This can make it challenging to detect type errors during development, which can lead to unexpected behavior or errors at runtime.

* **GIL (Global Interpreter Lock):** Python uses a global interpreter lock (GIL) to ensure that only one thread can execute Python bytecode at a time. This can limit the scalability and parallelism of Python programs, especially in multi-threaded or multiprocessing scenarios.

* **Package Management:** While Python has a vast ecosystem of libraries and packages, managing dependencies and package versions can be challenging. The Python Package Index (PyPI) is the official repository for Python packages, but it can be difficult to ensure compatibility and avoid conflicts between different versions of packages.
```

## 在链中使用

```python theme={null}
from langchain_core.prompts import PromptTemplate
```

```python theme={null}
template = """Question: {question}

Answer: Let's think step by step."""
prompt = PromptTemplate.from_template(template)

chain = prompt | llm

question = "How much is 2+2?"
print(chain.invoke({"question": question}))
```

```text theme={null}
4
```

## 流式调用

```python theme={null}
import sys

stream = llm.stream_events("Tell me a short poem about snow", version="v3")
for token in stream.text:
    sys.stdout.write(token)
    sys.stdout.flush()
```

```text theme={null}
In winter's embrace, a silent ballet,
Snowflakes descend, a celestial display.
Whispering secrets, they softly fall,
A blanket of white, covering all.

With gentle grace, they paint the land,
Transforming the world into a winter wonderland.
Trees stand adorned in icy splendor,
A glistening spectacle, a sight to render.

Snowflakes twirl, like dancers on a stage,
Creating a symphony, a winter montage.
Their silent whispers, a sweet serenade,
As they dance and twirl, a snowy cascade.

In the hush of dawn, a frosty morn,
Snow sparkles bright, like diamonds reborn.
Each flake unique, in its own design,
A masterpiece crafted by the divine.

So let us revel in this wintry bliss,
As snowflakes fall, with a gentle kiss.
For in their embrace, we find a peace profound,
A frozen world, with magic all around.
```

### 安全设置

Gemini模型具有默认的安全设置，可被覆盖。如果模型频繁发出"安全警告"，可尝试调整 `safety_settings` 属性。例如，要关闭对危险内容的过滤，可通过以下方式构建大语言模型（LLM）：

```python theme={null}
from langchain_google_genai import GoogleGenerativeAI, HarmBlockThreshold, HarmCategory

llm = GoogleGenerativeAI(
    model="gemini-3.6-flash",
    google_api_key=api_key,
    safety_settings={
        HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT: HarmBlockThreshold.BLOCK_NONE,
    },
)
```

要查看安全设置分类及阈值的完整列表，请参考Google的[safety settings guide](https://ai.google.dev/gemini-api/docs/safety-settings)。

***

> 官方原文：[src/oss/python/integrations/llms/google\_generative\_ai.mdx](https://github.com/langchain-ai/docs/blob/main/src/oss/python/integrations/llms/google_generative_ai.mdx) · 非官方翻译，译文由 AI 生成，以英文原文为准。


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