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🤖 Welcome to KishoreLytics! In this video, we’ll learn and build one of the most powerful concepts in modern AI — **RAG (Retrieval-Augmented Generation)**. We’ll break down the *architecture of RAG**, understand how it enhances LLMs like ChatGPT, and finally **build a real RAG Chatbot* where users can upload their own PDFs and ask questions — all step by step! --- ✅ What You’ll Learn: What is RAG and why it’s a breakthrough in AI RAG architecture explained (Retriever + Generator) How RAG connects your data to a language model How to create embeddings and store vector data Building a chatbot that answers questions from uploaded PDFs Using LangChain and vector databases in real time Full workflow: Upload → Process → Query → Respond --- 🎯 Who Should Watch: Beginners learning AI and Large Language Models Developers & Data Scientists building chatbots Students exploring NLP, Generative AI, and LangChain Anyone who wants to build a real-world AI project from scratch --- 💡 After watching this video, you’ll understand *how RAG systems work**, and you’ll build your own **AI chatbot* that can interact with your custom documents. 📺 Subscribe to @KishoreLytics for complete tutorials on RAG, LangChain, Python, SQL, and real AI projects — all 100% free! 💬 Drop your RAG project doubts in the comments — I reply to everyone. --- 🔗 Useful Links: 📘 Notes & Code Repository: https://github.com/Kishorelytics/Sql-... 🌐 Portfolio: https://kishorelytics.netlify.app 💼 LinkedIn: / kishore-kannan-n- 🎓 Try Free Practice Projects: https://lms-kishorelytics.vercel.app --- 🔖 Hashtags: #RAGTutorial #RAGArchitecture #RAGChatbot #RetrievalAugmentedGeneration #LangChain #AIChatbot #BuildWithKishoreLytics #LearnAI #GenerativeAI #ChatGPTProjects #PythonAI #MachineLearning #VectorDatabase #AI2025 #LLMTutorial #DataScience #OpenAI #KishoreLytics