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This repository contains a documentation bot powered by an LLM using @langchain4j to swiftly find answers to your Spring Boot questions. It provides easy browsing of Spring documentation and leverages the RAG technique to retrieve relevant details on demand.

miliariadnane/spring-boot-doc-rag-bot

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Spring Boot Documentation Bot

🌐 Description

This repository contains a documentation bot powered by a large language model (LLM) using LangChain4j to quickly find answers to your Spring Boot questions. It allows easy browsing of Spring documentation and leverages retrieve and gather (RAG) to extract relevant details on demand. The bot is built with Spring Boot and uses LangChain4j to ingest Spring documentation URLs into the model for enhanced question answering about Spring frameworks and the overall Spring ecosystem.

📚 Table of Contents

📋 Prerequisites

🔧 Installing

  1. Clone the repository on your local machine.

    git clone https://github.com/miliariadnane/spring-boot-doc-rag-bot
    cd spring-boot-doc-rag-bot
  2. Open the application.yml file and replace OPEN_API_KEY with your own Open API key. For demo purposes, you can use the key "demo".

  3. Build the project.

    mvn clean install
  4. Run your Spring Boot application.

    mvn spring-boot:run
    

🛠️ Built With

  • Spring Boot - The web framework used
  • Maven - Dependency Management
  • LangChain4j - Used for integration of AI/LLM models into Java applications

📝 License

This project is licensed under the MIT License - see the LICENSE.md file for details

🌟 Support

If you find this project useful or interesting, please consider giving it a star ⭐ on GitHub. Your support is greatly appreciated! Also, if you have a moment, don't forget to make a duaa 🤲 for me and my parents. Thank you for your support!

📸 Application Screenshot

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This repository contains a documentation bot powered by an LLM using @langchain4j to swiftly find answers to your Spring Boot questions. It provides easy browsing of Spring documentation and leverages the RAG technique to retrieve relevant details on demand.

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