A comprehensive Retrieval-Augmented Generation (RAG) system built in Java that combines document retrieval with AI models for enhanced information processing and generation.
This project implements a state-of-the-art RAG (Retrieval-Augmented Generation) system using Java, leveraging semantic search and large language models to provide accurate, context-aware responses. By combining retrieval capabilities with generative AI, this system can process large document collections and generate informed answers based on relevant retrieved documents.
- 🔍 Advanced Document Retrieval - Semantic search using vector embeddings
- 🤖 LLM Integration - Integration with large language models for generation
- 📚 Document Processing - Efficient handling and indexing of large document collections
- 💾 Vector Storage - Optimized vector database for fast similarity search
- 🎯 Context-Aware Generation - Generate responses grounded in retrieved documents
- ���� Pipeline Architecture - Modular design for easy customization
- ⚡ Performance Optimized - Efficient retrieval and inference
- 🏗️ Enterprise-Ready - Built with Java for robustness and scalability
- Java 17 or higher
- Maven 3.6+
- Git
# Clone the repository
git clone https://github.com/Manikant2018/rag-project.git
cd rag-project
# Build the project
mvn clean install
# Run the application
mvn spring-boot:run