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LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot.

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LangChain4j is an open-source Java library that gives JVM developers a unified API for connecting applications to more than 20 LLM providers, including Anthropic's Claude, and more than 30 embedding stores such as Pinecone, Milvus, and pgvector. Built from scratch around Java conventions like type safety, annotations, and dependency injection, it is not a port of the Python LangChain project. The library covers low-level capabilities including prompt templating, chat memory management, and function calling, as well as higher-level patterns such as autonomous agents and full retrieval-augmented generation pipelines spanning data ingestion through retrieval. MCP support is included for tool calling. Anthropic's Claude is accessible through the unified LLM provider interface, meaning Java teams can swap Claude in or out without rewriting application code. First-class integrations exist for Quarkus, Spring Boot, Helidon, and Micronaut, making the library a practical fit for enterprise Java developers who want to add LLM capabilities to existing service architectures.

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Last scanned: 6/11/2026
Get started
Method: Clone
Terminal
git clone https://github.com/langchain4j/langchain4j
1. Clone the repository.
2. Follow the README for installation and usage instructions.
Casos de uso

Resumen de Tools

# LangChain4j: idiomatic, open-source Java library for building LLM-powered applications on the JVM

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## Introduction

Welcome!

The goal of LangChain4j is to simplify integrating LLMs into Java applications.

Here's how:
1. **Unified APIs:**
   LLM providers (like OpenAI or Google Vertex AI) and embedding (vector) stores (such as Pinecone or Milvus)
   use proprietary APIs. LangChain4j offers a unified API to avoid the need for learning and implementing specific APIs for each of them.
   To experiment with different LLMs or embedding stores, you can easily switch between them without the need to rewrite your code.
   LangChain4j currently supports [20+ popular LLM providers](https://docs.langchain4j.dev/integrations/language-models/)
   and [30+ embedding stores](https://docs.langchain4j.dev/integrations/embedding-stores/).
2. **Comprehensive Toolbox:**
   Since early 2023, the community has been building numerous LLM-powered applications,
   identifying common abstractions, patterns, and techniques. LangChain4j has refined these into practical code.
   Our toolbox includes tools ranging from low-level prompt templating, chat memory management, and function calling
   to high-level patterns like Agents and RAG.
   For each abstraction, we provide an interface along with multiple ready-to-use implementations based on common techniques.
   Whether you're building a chatbot or developing a RAG with a complete pipeline from data ingestion to retrieval,
   LangChain4j offers a wide variety of options.
3. **Numerous Examples:**
   These [examples](https://github.com/langchain4j/langchain4j-examples) showcase how to begin creating various LLM-powered applications,
   providing inspiration and enabling you to start building quickly.

LangChain4j began development in early 2023 amid the ChatGPT hype.
We noticed a lack of Java counterparts to the numerous Python and JavaScript LLM libraries and frameworks,
and we had to fix that!

**Despite the name, LangChain4j is not a Java port of LangChain (Python) — it is built for Java, not ported to it.**
It is an idiomatic Java library designed from the ground up around Java conventions:
type safety, POJOs, annotations, interfaces, dependency injection, fluent APIs, and first-class integrations with Quarkus, Spring Boot, Helidon, and Micronaut.
Its API, internals, and release cycle are independent of the Python LangChain project.

We actively monitor community developments, aiming to quickly incorporate new techniques and integrations,
ensuring you stay up-to-date.
The library is under active development. While some features are still being worked on,
the core functionality is in place, allowing you to start building LLM-powered apps now!


## Documentation
Documentation can be found [here](https://docs.langchain4j.dev).

The documentation chatbot (experimental) can be found [here](https://chat.langchain4j.dev/).


## Getting Started
Getting started guide can be found [here](https://docs.langchain4j.dev/get-started).


## Code Examples
Please see examples of how LangChain4j can be used in [langchain4j-examples](https://github.com/langchain4j/langchain4j-examples) repo:
- [Examples in plain Java](https://github.com/langchain4j/langchain4j-examples/tree/main/other-examples/src/main/java)
- [Examples with Quarkus](https://github.com/quarkiverse/quarkus-langchain4j/tree/main/samples) (uses [quarkus-langchain4j](https://github.com/quarkiverse/quarkus-langchain4j) dependency)
- [Example with Spring Boot](https://github.com/langchain4j/langchain4j-examples/tree/main/spring-boot-example/src/main/java/dev/langchain4j/example)
- [Examples with Helidon](https://github.com/helidon-io/helidon-examples/tree/helidon-4.x/examples/integrations/langchain4j) (uses [io.helidon.integrations.langchain4j](https://mvnrepository.com/artifact/io.helidon.integrations.langchain4j) dependency)
- [Examples with Micronaut](https://github.com/micronaut-projects/micronaut-langchain4j/tree/0.3.x/doc-examples/example-openai-java) (uses [micronaut-langchain4j](https://micronaut-projects.github.io/micronaut-langchain4j/latest/guide/) dependency)

## Useful Materials
Useful materials can be found [here](https://docs.langchain4j.dev/useful-materials).


## Get Help
Please use [Discord](https://discord.gg/JzTFvyjG6R) or [GitHub discussions](https://github.com/langchain4j/langchain4j/discussions)
to get help.


## Request Features
Please let us know what features you need by [opening an issue](https://github.com/langchain4j/langchain4j/issues/new/choose).


## Contribute
Contribution guidelines can be found [here](https://github.com/langchain4j/langchain4j/blob/main/CONTRIBUTING.md).
anthropicchatgptchromaembeddingsgeminigpthuggingfacejavalangchainllamallmllmsmilvusollamaonnxopenaiopenai-apipgvectorpineconevector-database

Lo que la gente pregunta sobre langchain4j

¿Qué es langchain4j/langchain4j?

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langchain4j/langchain4j es tools para el ecosistema de Claude AI. LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It offers a unified API over popular LLM providers and vector stores, and makes implementing tool calling (including MCP support), agents and RAG easy. It integrates seamlessly with enterprise Java frameworks like Quarkus and Spring Boot. Tiene 12.3k estrellas en GitHub y se actualizó por última vez today.

¿Cómo se instala langchain4j?

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Puedes instalar langchain4j clonando el repositorio (https://github.com/langchain4j/langchain4j) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

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Nuestro agente de seguridad ha analizado langchain4j/langchain4j y le ha asignado un Trust Score de 100/100 (tier: Verified). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

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langchain4j/langchain4j es mantenido por langchain4j. La última actividad registrada en GitHub es de today, con 774 issues abiertos.

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