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Here you will find tutorials covering all of LangChain4j's functionality, to guide you through the framework in steps of increasing complexity.

We will typically use OpenAI models for demonstration purposes, but we support a lot of other model providers too. The entire list of supported models can be found here.

Need inspiration?

Watch the talk by Lize Raes at Devoxx Belgium

Talk by Vaadin team about Building a RAG AI system in Spring Boot & LangChain4j

Fireside Chat: LangChain4j & Quarkus by Quarkusio

The Magic of AI Services with LangChain4j by Tales from the jar side

Or consider some of the use cases

  • You want to:
    • Implement a custom AI-powered chatbot that has access to your data and behaves the way you want it.

    • Implement a customer support chatbot that can:

      • politely answer customer questions
      • take /change/cancel orders
    • Implement an educational assistant that can:

      • Teach various subjects
      • Explain unclear parts
      • Assess user's understanding/knowledge
      • You want to process a lot of unstructured data (files, web pages, etc) and extract structured information from them. For example:
        • extract insights from customer reviews and support chat history
        • extract interesting information from the websites of your competitors
        • extract insights from CVs of job applicants
    • Generate information, for example:

      • Emails tailored for each of your customers
    • Generate content for your app/website:

      • Blog posts
      • Stories
    • Transform information, for example:

      • Summarize
      • Proofread and rewrite
      • Translate