Building RAG Chatbot in Java with Langchain4j and Qdrant DB

This project serves as a boilerplate and an illustration of an RAG chatbot built in Java using the LangChain4j library. The chatbot utilizes Qdrant Db as its vectorstore. Within this project, you will find implementations of both a Basic RAG chatbot and an Advanced RAG chatbot.

Technology and Dependencies

1. Java
2. Spring Boot (Maven)
3. Langchain4j
4. Qdrant DB
5. OpenAI

Prerequisites

Before you start working with this project, make sure you have the following prerequisites installed:

• Operating System:

  • Compatible with Windows, macOS, or Linux.

• Hardware:

  • A machine with at least 4GB RAM and a dual-core processor.

• Java Development Kit (JDK):

  • Install Java 17 or a compatible version.

• Integrated Development Environment (IDE):

  • (Optional) Choose a Java IDE of your preference:
    • Eclipse
    • IntelliJ IDEA

• Vector Store

  • Setup Qdrant Cloud free cluster

• Build Tool:

  • Apache Maven for building and managing dependencies.

• API Testing Tool:

  • Postman for testing APIs.

Project Setup in IntelliJ IDEA

• First download the project using the git clone command. git clone https://github.com/ritobrotos/java-langchain-rag-chatbot.git
• Launch IntelliJ IDEA on your machine.
• Open the project in IntelliJ. Importing project in IntelliJ doc.
• Since its a Maven project IntelliJ IDEA will detect the pom.xml file and automatically download the dependencies.
• In the ChatConstants file we have declared the variables QDRANT_GRPC_HOST, QDRANT_API_KEY and OPENAI_API_KEY which read their values from the environment.t.
• Set all the 3 values in the IntelliJ environment. Environment variable setup doc.

Running the Chatbot Application

• Locate the main class of your Spring Boot application, which is RagChatbotApplication.
• Right-click on the main class file and select Run RagChatbotApplication to initiate the Spring Boot application.
• Check the console output for any errors. Upon successful startup, you should observe messages indicating that the application has started on port 8080.
• Open a web browser and navigate to http://localhost:8080/chat. You should receive the message Welcome to Chat Bot, confirming the successful launch of your application.

References

• Hands-on Guide to Building LLM Apps in Java with Langchain4j and Qdrant DB