RAGFreeOpen Source

LANGCHAIN4J

Build LLM-powered Java applications with LangChain's JVM-native port

Apache-2.0

ABOUT

Java and JVM developers who want to build LLM-powered applications face a language gap — most AI frameworks are Python-first with minimal Java support. LangChain4j bridges this gap by providing a Java-native library with a unified API across LLM providers (OpenAI, Anthropic, Google, Ollama), embedding stores (Pinecone, Chroma, Weaviate), and RAG pipelines. It integrates natively with Spring Boot and Quarkus so enterprise Java teams can add AI features to existing applications without introducing a separate Python service.

INSTALL

<dependency>
  <groupId>dev.langchain4j</groupId>
  <artifactId>langchain4j</artifactId>
  <version>1.0.0</version>
</dependency>

INTEGRATION GUIDE

1. Add RAG-powered chat to Spring Boot applications using enterprise document stores and vector databases 2. Build AI agents with tool calling and function invocation from Java services without Python dependencies 3. Implement semantic search over internal documentation with embeddings stored in a JVM-compatible vector store 4. Create multi-step LLM workflows that chain prompts, data extraction, and decision logic in pure Java

LANGCHAIN4J

ABOUT

INTEGRATION GUIDE

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