Amazon Bedrock – RAG Explained with a Hands on Demo
Автор: ImTechnos
Загружено: 2025-10-14
Просмотров: 657
What if your AI could instantly pull the right information from your company’s own data?
In this video, we’ll explore Retrieval-Augmented Generation (RAG) — what it is, why it matters, and how to set it up step-by-step inside Amazon Bedrock using a real AWS project dataset.
⏱️ Chapters
00:00 – Intro: What you’ll learn today
00:15 – What is RAG? (Retrieval-Augmented Generation)
01:05 – Why RAG is important for accurate, real-world answers
01:30 – When to use RAG in enterprise projects
01:52 – How RAG works step-by-step
02:15 – RAG hands-on overview
02:55 – Creating an IAM user for Bedrock
04:30 – Exploring the project dataset
05:30 – Uploading dataset to Amazon S3
06:10 – Creating a Knowledge Base in Amazon Bedrock
07:07 – Understanding data source options
09:07 – Choosing parsing strategies (Default, Data Automation, FM Parser)
10:30 – Chunking strategy explained (Default, Fixed, Semantic, etc.)
13:30 – Configuring embeddings and vector store
15:40 – Testing RAG setup in Bedrock console
17:10 – Cleanup and resource deletion steps
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💬 Drop your questions in the comments — I’d love to help you out!
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