How to Build Your First Production RAG Pipeline (in 15 Minutes)
Explore the AI Skill Paths 👉 https://jb.gg/academy/aws-courses 📩 Get my FREE weekly AI & data insights 👉 https://thu-vu.ck.page/49c5ee08f6 Setting up cloud infrastructure for generative AI can be complex. In this video, I simplified Amazon Bedrock deployment by walking you through the essential interface configurations to build and test a simple RAG pipeline for asking questions about your own documents. We focus on the practical steps required to get your environment ready: select an Amazon S3 data source, configure the embeddings model, finalize the vector store setup, and test your document QA pipeline. 🔑 TIMESTAMPS ▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀▀ 0:00 - Intro 0:41 - Why learn cloud skills? 1:53 - Brief intro to RAG 3:49 - What is Amazon Bedrock 4:42 - Create an account on AWS console 5:21 - Create a user 6:22 - Create knowledge base 8:19 - Create S3 bucket with source documents 9:21 - Configure data sources 9:52 - Choose document parsing strategy 10:10 - Choose an embedding model 11:12 - Choose vector store 12:30 - Test the pipeline with real questions 13:24 - Learn to build with code #aws #rag #ai #ThuVu
