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This page covers how to use the Postgres PGVector ecosystem within LangChain It is broken into two parts: installation and setup, and then references to specific PGVector wrappers.


  • Install the Python package with pip install pgvector


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

    Follow the steps at PGVector Installation Steps to install the database and the extension. The docker image is the easiest way to get started.



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:

from langchain_community.vectorstores.pgvector import PGVector
API Reference:PGVector


For a more detailed walkthrough of the PGVector Wrapper, see this notebook

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