langchain-patterns

name	langchain_patterns
router_kit	AIKit
description	Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use when creating question-answering systems over document collections or AI assistants with external knowledge bases.
allowed-tools	Read, Write, Bash
category	ai-development
tags	["agents","algorithms","artificial intelligence","automation","chatbots","cognitive services","deep learning","document-ingestion","embedding","embeddings","frameworks","generative ai","inference","java","langchain patterns","langchain4j","large language models","llm","machine learning","model fine-tuning","natural language processing","neural networks","nlp","openai","prompt engineering","rag","retrieval augmented generation","retrieval-augmented-generation","tools","vector databases","vector-search","workflow automation"]
version	1.1.0
metadata	{"skillport":{"category":"auto-healed","tags":["prompt","ai","llm","rag","agent","embedding","model","agent orchestration","expert","guide","context engineering","expert","guide","langchain patterns","expert","guide","langchain_patterns"]}}

LangChain4j RAG Implementation Patterns

When to Use This Skill

Use this skill when:

• Building knowledge-based AI applications requiring external document access
• Implementing question-answering systems over large document collections
• Creating AI assistants with access to company knowledge bases
• Building semantic search capabilities for document repositories
• Implementing chat systems that reference specific information sources
• Creating AI applications requiring source attribution
• Building domain-specific AI systems with curated knowledge
• Implementing hybrid search combining vector similarity with traditional search
• Creating AI applications requiring real-time document updates
• Building multi-modal RAG systems with text, images, and other content types

Overview

Implement complete Retrieval-Augmented Generation (RAG) systems with LangChain4j. RAG enhances language models by providing relevant context from external knowledge sources, improving accuracy and reducing hallucinations.

Instructions

Initialize RAG Project

Create a new Spring Boot project with required dependencies:

pom.xml:

<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-spring-boot-starter</artifactId>
    <version>1.8.0</version>
</dependency>
<dependency>
    <groupId>dev.langchain4j</groupId>
    <artifactId>langchain4j-open-ai</artifactId>
    <version>1.8.0</version>
</>