> ## Documentation Index
> Fetch the complete documentation index at: https://nvd-54.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# PGVector 集成

> 使用 LangChain Python 与 PGVector 集成。

This page covers how to use the Postgres [PGVector](https://github.com/pgvector/pgvector) ecosystem within LangChain
It is broken into two parts: installation and setup, and then references to specific PGVector wrappers.

## 安装

* Install the Python 包 with `pip install pgvector`

## 设置

1. The first step is to create a database with the `pgvector` extension installed.

   Follow the steps at [PGVector Installation Steps](https://github.com/pgvector/pgvector#installation) to install the database and the extension. The docker image is the easiest way to get started.

## Wrappers

### 向量存储

存在一个围绕 Postgres 向量数据库的封装器，允许您将其用作向量存储，
无论是用于语义搜索还是示例选择。

要导入此向量存储：

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_community.vectorstores.pgvector import PGVector
```

### 使用方法

有关 PGVector Wrapper, see [this notebook](/oss/python/integrations/vectorstores/pgvector)

***

<div className="source-links">
  <Callout icon="terminal-2">
    [将这些文档连接](/use-these-docs) 到 Claude、VSCode 等工具，通过 MCP 获取实时答案。
  </Callout>

  <Callout icon="edit">
    [在 GitHub 上编辑此页面](https://github.com/langchain-ai/docs/edit/main/src/oss/python/integrations/providers/pgvector.mdx)或[提交 issue](https://github.com/langchain-ai/docs/issues/new/choose).
  </Callout>
</div>