langchain4j-vector-stores-configuration SKILL.md skillA
langchain4j-vector-stores-configuration from giuseppe-trisciuoglio/developer-kit is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add giuseppe-trisciuoglio/developer-kit/langchain4j-vector-stores-configuration@git:20260324.a02e282Pins git:20260324.a02e282 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- giuseppe-trisciuoglio/developer-kit
- Path
plugins/developer-kit-java/skills/langchain4j-vector-stores-configuration/SKILL.md- Versions recorded
- 5
- Latest version
- git:20260324.a02e282, committed Mar 24, 2026
- First version recorded
- Feb 7, 2026
- Size
- 10,719 bytes
- Repository stars
- 367
- License
- MIT
Provides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# 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:
```java
@Bean
public EmbeddingStore<TextSegment> embeddingStore() {
return PgVectorEmbeddingStore.builder()
.host("localhost")
.port(5432)
.database("vectordb")
.user("username")
.password("password")
.table("embeddings")
.dimension(1536) // OpenAI embedding dimension
.createTable(true)
.useIndex(true)
.build();
}
```
### Validation Workflow
Follow this workflow to ensure correct vector store setup:
…Read the whole file at its exact version.
How to install
mdr add giuseppe-trisciuoglio/developer-kit/langchain4j-vector-stores-configuration@sha256:e7e767c9687cd5d9The line at the top of this page pins the label git:20260324.a02e282, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_itqzgxgryvy735e2)
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Versions
The registry has recorded 5 versions of this file, between Feb 7, 2026 and Mar 24, 2026, about one every 11 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260324.a02e282 latest | 2026-03-24 | a02e282 | 10,719 B | A | view · diff |
| git:20260223.c6d4db1 | 2026-02-23 | c6d4db1 | 10,721 B | A | view · diff |
| v1.1.0 | 2026-02-08 | 147afce | 10,849 B | A | view · diff |
| v1.1.0 | 2026-02-07 | 1a732c7 | 9,583 B | A | view · diff |
| v1.1.0 | 2026-02-07 | 654d94d | 9,558 B | A | view |
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Source
giuseppe-trisciuoglio/developer-kit · 367 stars · license MIT · pushed 2026-09-10 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_itqzgxgryvy735e2 GET https://markdownregistry.com/api/v1/resolve?ref=giuseppe-trisciuoglio/developer-kit/langchain4j-vector-stores-configuration GET https://markdownregistry.com/api/v1/blob/e7e767c9687cd5d9cb4877be44fc1a903fe9118613f96d132cc1f1a6c5203a4c
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