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.Documentation Index
Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-mdrxyo-1777658790-7be347c.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.
Installation
- Install the Python package with
pip install pgvector
Setup
-
The first step is to create a database with the
pgvectorextension 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.
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:Usage
For a more detailed walkthrough of the PGVector Wrapper, see this notebookConnect these docs to Claude, VSCode, and more via MCP for real-time answers.

