LangChain4J Vector Stores Configuration

Configure vector stores for Retrieval-Augmented Generation applications with LangChain4J.

Overview

LangChain4J provides a unified abstraction for vector stores (PostgreSQL/pgvector, Pinecone, MongoDB Atlas, Milvus, Neo4j) with builder-based configuration, metadata filtering, and hybrid search support.

When to Use

• Configuring vector stores for semantic search and RAG applications
• Setting up embedding storage with metadata filtering and hybrid search
• Optimizing vector database performance for production AI workloads

Instructions

Set Up Basic Vector Store

Configure an embedding store for vector operations: