Package dyntabs.ai.rag

Class RagEngine

java.lang.Object

dyntabs.ai.rag.RagEngine

public final class RagEngine
extends Object

RAG engine that loads documents, splits them, embeds them, and provides a ContentRetriever for use with AI assistants. Uses LangChain4J easy-rag module which includes Tika for PDF/DOCX and a local embedding model.

Method Summary

Modifier and Type	Method	Description
static dev.langchain4j.rag.content.retriever.ContentRetriever	createRetriever(EasyRAG ragAnnotation)	Creates a ContentRetriever based on the EasyRAG annotation.
static dev.langchain4j.rag.content.retriever.ContentRetriever	createRetriever(String[] sources, int maxResults, double minScore)	Creates a ContentRetriever programmatically.
static dev.langchain4j.rag.content.retriever.ContentRetriever	createRetriever(List<DocumentSource> documentSources, int maxResults, double minScore)	Creates a ContentRetriever from in-memory document sources.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

createRetriever

public static dev.langchain4j.rag.content.retriever.ContentRetriever createRetriever(EasyRAG ragAnnotation)

Creates a ContentRetriever based on the EasyRAG annotation.

createRetriever

public static dev.langchain4j.rag.content.retriever.ContentRetriever createRetriever(String[] sources,
 int maxResults,
 double minScore)

Creates a ContentRetriever programmatically.

createRetriever

public static dev.langchain4j.rag.content.retriever.ContentRetriever createRetriever(List<DocumentSource> documentSources,
 int maxResults,
 double minScore)

Creates a ContentRetriever from in-memory document sources.

Use this when documents come from a DMS, database, REST API, or any source that provides content as byte[].

Parameters:

documentSources - the documents as byte arrays

maxResults - maximum relevant segments to retrieve

minScore - minimum relevance score (0.0 to 1.0)

Returns:

a configured ContentRetriever