
RAG Pipeline: 7 Iterations Explained!
Cyril Imhof
Unlock the ultimate secret to supercharge your AI Agents and Generative AI! 🚀 Discover how a simple Python coding script for Retrieval Augmented Generation (RAG) can revolutionize your AI outputs, making them incredibly accurate, relevant, and engaging. This isn't just coding; it's an opportunity to build smarter AI! Imagine your AI producing content that's always fact-checked, grounded in your unique knowledge, and free from hallucinations. Our RAG script integrates seamlessly with custom data sources like PostgreSQL and pgml, delivering superior analysis and saving you time and cost on fine-tuning. Fetch precise information, manage databases effortlessly, and watch your AI thrive with context! This video breaks down a powerful Python script step-by-step. We'll cover: - Initial Setup & Database Connection - Defining RAG Collection & Pipeline - Ingesting Data into Your Knowledge Base - Performing Semantic Search - Integrating LLM for Context-Aware Generation - The Main Execution Workflow Get ready to transform your AI projects! Don't miss out on this treasure! ✨ Subscribe now to @PyLouis for more AI coding insights. Want the full coding prompt? Comment 'Vibe Prompt' below! #RAG #Python #GenerativeAI #AIagent #PostgreSQL #pgml #louispython #瑞格布恩运动鞋 #瑞格布恩 #瑞格布恩斯莱德西装外套 #瑞格布恩西装外套 @PyLouis

Cyril Imhof

Mehul Mathur

Nidhi Chouhan

Nidhi Chouhan

Daksh Rathore

Vikash Kumar

Data Science Gems

DATASKILLED