forked from Archives/langchain
705431aecc
Co-authored-by: Ankush Gola <ankush.gola@gmail.com>
30 lines
1023 B
Markdown
30 lines
1023 B
Markdown
# 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)
|