langchain/docs/ecosystem/pgvector.md
Harrison Chase 705431aecc
big docs refactor (#1978)
Co-authored-by: Ankush Gola <ankush.gola@gmail.com>
2023-03-26 19:49:46 -07:00

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# PGVector
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.
## Installation
- Install the Python package with `pip install pgvector`
## Setup
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
### VectorStore
There exists a wrapper around Postgres vector databases, allowing you to use it as a vectorstore,
whether for semantic search or example selection.
To import this vectorstore:
```python
from langchain.vectorstores.pgvector import PGVector
```
### Usage
For a more detailed walkthrough of the PGVector Wrapper, see [this notebook](../modules/indexes/vectorstores/examples/pgvector.ipynb)