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Ask a normal AI model “what’s the alarm code at my cafe?” and it has no idea, because your handbook, notes, and PDFs were never part of its training data. It either refuses or makes something up. RAG fixes that, and it’s a lot simpler than most people make it sound. In this video I build a complete RAG system from scratch in plain Python and under 50 lines of code. No LangChain, no pre-built vector database, no closed-source models, and everything runs locally on your own computer, so it’s free and completely private.
? Tools I Use
Get 10% off with code techwithtim
Openclaw setup: https://www.hostinger.com/techwithtim
VPS setup: https://www.hostinger.com/techwithtim10
Wispr Flow (Best AI Dictation): https://ref.wisprflow.ai/TechWithTim-oct26
? Video Resources ?
Get all of the code in this video: https://www.aiagentbuilders.co/yt-resources/rag-from-scratch
⏳ Timestamps ⏳
00:00 | Overview
00:26 | The Problem
01:18 | What is RAG
02:03 | How it Works
03:01 | TripleTen
04:48 | Step 0 - Models
13:14 | Step 1 - Chunking
16:25 | Step 2 - Embedding
18:31 | Step 3 - Searching
21:47 | Step 4 - Calling the LLM
25:13 | Next Steps
Hashtags
#RAG #Python #Ollama
UAE Media License Number: 3635141