Generative AI Day 12 | PDF Question Answering Agent

Colab file - https://colab.research.google.com/dri... Welcome to Day 12 of Generative AI & Agentic AI Full Course 🚀 In this video, we build a PDF Q&A AI Agent that can read documents and answer questions intelligently using RAG (Retrieval Augmented Generation) and Vector Databases. This is a real-world GenAI project used in: 👉 Chatbots 👉 Document analysis 👉 Knowledge assistants 🔹 What You Will Build: 👉 Upload PDF and extract text 👉 Convert text into embeddings 👉 Store data in vector database 👉 Ask questions from PDF 👉 Get accurate, context-based answers 🔹 Topics Covered: ✅ Project overview (PDF Q&A system) ✅ RAG pipeline implementation ✅ Embeddings + similarity search ✅ Vector database integration ✅ Query processing ✅ Real-world demo 🎯 This video is perfect for: ✔ Developers building AI apps ✔ Data Science & AI students ✔ GenAI learners ✔ Anyone interested in AI automation 👍 Like | 🔔 Subscribe | 💬 Ask your doubts in comments pdf qa ai pdf chatbot rag project ask questions from pdf langchain pdf chatbot vector database project ai document chatbot generative ai project agentic ai project llm rag application embedding search ai automation gen ai course machine learning project deep learning