LangChain4j: Supercharge Your Java Application with the Power of LLMs

 

Today, many developers are adding smart features like chatting, answering questions, or summarizing text to their applications. Tools to do this are easy to find in Python, but for Java developers, the choices have been limited—until now.

 

LangChain4j is a library that helps Java developers add powerful language features to their applications more easily.

 

1. What Is LangChain4j?

LangChain4j is a Java library that makes it easier to connect your applications with language services, such as those from OpenAI or Google. These services can understand and generate human-like text.

 

LangChain4j started in early 2023 when tools like ChatGPT became popular. The creators noticed there weren’t many tools like this for Java developers. So they built LangChain4j by taking ideas from other tools like LangChain (Python), Haystack, and LlamaIndex, and added their own improvements.

 

2. What Makes LangChain4j Helpful?

2.1. One Simple Way to Connect to Many Services

Many companies offer language tools or storage for text (like OpenAI, Google, Pinecone, Milvus). But each one uses its own way of connecting, which can be hard to learn and manage.

 

LangChain4j solves this by giving you one simple way to work with all of them. You don’t have to learn a new system every time. You can also switch between services without changing your code much.

 

At the time of writing this post, LangChain4j works with:

 

·      Over 19 language service providers

·      Over 20 text storage services (called vector or embedding stores)

 

Following is the list of providers supported by LangChain4j:

 

·      Amazon Bedrock (Converse API)

·      Amazon Bedrock (Invoke API)

·      Anthropic

·      Azure OpenAI

·      ChatGLM

·      DashScope

·      GitHub Models

·      Google AI Gemini

·      Google Vertex AI Gemini

·      Google Vertex AI PaLM 2

·      Hugging Face

·      Jlama

·      LocalAI

·      Mistral AI

·      Ollama

·      OpenAI

·      Qianfan

·      Cloudflare Workers AI

·      Zhipu AI

 

You can get the latest list here (https://docs.langchain4j.dev/integrations/language-models/)

 

Following is the list of vectors embedding stores supported:

·      In-memory

·      AlloyDB for Postgres

·      Astra DB

·      Azure AI Search

·      Azure CosmosDB Mongo vCore

·      Azure CosmosDB NoSQL

·      Cassandra

·      Chroma

·      ClickHouse

·      Cloud SQL for Postgres

·      Coherence

·      Couchbase

·      DuckDB

·      Elasticsearch

·      Infinispan

·      Milvus

·      MongoDB Atlas

·      Neo4j

·      OpenSearch

·      Oracle

·      PGVector

·      Pinecone

·      Qdrant

·      Redis

·      Tablestore

·      Vearch

·      Vespa

·      Weaviate

 

Refer this link (https://docs.langchain4j.dev/integrations/embedding-stores/) to get latest stores supported by Langchain4j.

 

2.2. A Full Set of Ready-to-Use Tools

Since early 2023, developers have tried many ways to use these smart language features. They’ve found patterns that work well, like how to create good prompts, manage chat history, or find the best information to answer questions.

 

LangChain4j includes all these patterns in one place:

 

·      Basic tools: like creating prompts or managing chat memory

·      Advanced tools: like building question-answer systems or helpful agents

·      Interfaces and examples: so you can use these tools in different ways

 

Whether you're creating a chatbot or a system that searches and answers from your own data, LangChain4j gives you everything you need.

 

2.3 Easy-to-Follow Examples

LangChain4j comes with many examples that show you how to get started. These examples are simple and practical, helping you learn by doing. You can see how to build different kinds of smart features and start creating your own right away.

 

Refer this link (https://github.com/langchain4j/langchain4j-examples) to see all the examples to quickly start with.

 

2.4 Works with Popular Java Frameworks

LangChain4j is easy to use with frameworks you may already know, such as:

 

·      Spring Boot

·      Quarkus

·      Helidon

 

In summary, LangChain4j helps Java developers to build applications that understand and use language in smart ways. It brings together the tools, patterns, and examples you need to get started without switching to another programming language.

 You can download the working examples of this tutorial from this link.

 

References

https://github.com/langchain4j/langchain4j-examples

 

https://docs.langchain4j.dev/integrations/language-models/

 

https://docs.langchain4j.dev/integrations/embedding-stores/

 

Previous                                                    Next                                                    Home