Java RAG System

Developed a robust Retrieval-Augmented Generation (RAG) pipeline entirely in Java, designed for efficient semantic search and context-aware answer generation.

Components: Includes document ingestion, embeddings generation via SentenceTransformer (Python API), and vector storage using Milvus.

Generation: Integrates Ollama for powerful text generation capabilities.

Functionality: Enables users to perform semantic searches and receive highly relevant, contextually accurate answers from a knowledge base.

Tech Stack: Java, Milvus, Ollama, Python.