An implementation of LangChain vectorstore abstraction using postgres as the backend and utilizing the pgvector extension. Status · Setup · Instantiation · Query vector store

Postgres vector store integration. Install langchain_postgres and run the docker container. pip install -qU langchain-postgres docker run --name pgvector- ...

12 июл. 2023 г. · This blog post is a guide to building LLM applications with the LangChain framework in Python. We will use PostgreSQL and pgvector as a vector database for ...

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 ...

An improved version of this class is available in langchain_postgres as PGVector. Please use that class instead. To use, you should have the pgvector python ...

VectorStore implementation using Postgres and pgvector. To use, you should have the pgvector python package installed.

Build context-aware reasoning applications. Contribute to langchain-ai/langchain development by creating an account on GitHub.

Create a way to dynamically look up deprecated imports. Used to consolidate logic for raising deprecation warnings and handling optional imports.

PGVector wrapper from raw documents and pre-generated embeddings. Return VectorStore initialized from documents and embeddings.

LangChain.js supports using the pgvector Postgres extension. This guide provides a quick overview for getting started with PGVector vector stores.