🔥Build a Complete AI RAG Application with Java in 10 Hours | Spring AI | RAG | Full Project | HIndi

In this 10-hour end-to-end project, we will create a real-world AI application where users can register/login, upload multiple documents, and chat with their documents using Retrieval-Augmented Generation (RAG). You will learn how to integrate Spring AI with Large Language Models, generate embeddings, store vectors in PostgreSQL using PGVector, retrieve relevant document chunks, and build intelligent AI responses. 🔗 Complete DocMind Series:    • DocMind – Complete AI Based Project   💻 Source Code: https://github.com/LearnCodeWithDurge... 🎓 Spring Boot, Microservices, DevOps & AWS Live Batch: https://courses.learncodewithdurgesh.... 00:00 Video Introduction 01:21 Project Demonstration 11:36 Technologies and Tools that we use in this project 18:10 Setting up pgvector using docker compose 36:20 Understanding the workspace local sandbox 39:04 Configuring db with spring boot project 54:00 Project Achitecture, how backend work with ai 58:17 Configuring and openai 01:02:26 Understanding about gpt models, pricing and tokenization 01:08:06 Documenting project apis using spring doc openai 01:21:07 Working on storing entities information 01:29:45 Handling Exceptions in project 01:47:23 Understanding RAG for project 02:01:53 Implementing RAG in 2 Phases(Document Reader, Chunking, Storing using Vector store) 03:19:52 Implementing Retrieval and Generation (Similarity Search) 04:42:27 Completing Remaining APIS (ChatController) 04:50:28 Implementing CORS Configurations 04:54:32 Creating Frontend using AI (Antigravity IDE) version 1 --------------------------------------------------------------------------------------------------- 05:45:04 Starting Phase for this project - to add new features 05:58:21 Implementing JWT authentication in our application Creating Authentication and Authorisation 06:40:33 Implementing Authentication Filter to validate the request for jwt token 06:49:57 Configuring Spring Security 07:06:50 Implementing User Isolation Architecture (user login and maintain their private workspace) 08:15:06 Implementing ChatMemory in project 08:30:47 Implementing Permanent chat memory by writing custom jpachatmemory 09:30:00 Creating Version 2 of project using AI(Antigravity) If you like the project please subscribe and like ‪@LearnCodeWithDurgesh‬ ‪@aiwithdurgesh1‬ ‪@TheScriptStyle‬ 🔥 Technologies Covered: Java, Spring Boot, React.js, Spring AI, RAG, PostgreSQL, PGVector, Vector Database, Embeddings, REST APIs, Authentication and Document Processing. ✅ Features we build: User Login & Authentication Multiple Document Upload Document Processing & Chunking Vector Embeddings PGVector Storage Semantic Search RAG Pipeline AI Chat with Documents Spring Boot Backend React Frontend Complete Full Stack Integration This project is perfect for Java developers who want to learn Generative AI, Spring AI, RAG, Vector Databases, and how to build production-style AI applications using Java. #Java #SpringAI #SpringBoot #RAG #GenerativeAI #ReactJS #PGVector #ArtificialIntelligence