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Leonid Ganeline e2d7677526

docs: compound ecosystem and integrations (#4870 )

# Docs: compound ecosystem and integrations

**Problem statement:** We have a big overlap between the
References/Integrations and Ecosystem/LongChain Ecosystem pages. It
confuses users. It creates a situation when new integration is added
only on one of these pages, which creates even more confusion.
- removed References/Integrations page (but move all its information
into the individual integration pages - in the next PR).
- renamed Ecosystem/LongChain Ecosystem into Integrations/Integrations.
I like the Ecosystem term. It is more generic and semantically richer
than the Integration term. But it mentally overloads users. The
`integration` term is more concrete.
UPDATE: after discussion, the Ecosystem is the term.
Ecosystem/Integrations is the page (in place of Ecosystem/LongChain
Ecosystem).

As a result, a user gets a single place to start with the individual
integration.

2023-05-18 09:29:57 -07:00

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PGVector

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.

Installation

Install the Python package with pip install pgvector

Setup

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.

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:

from langchain.vectorstores.pgvector import PGVector

Usage

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

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