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NPrompt_Engineering
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
NRAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Popularity
Repository stars7,91930,197Highest
7-day net stars——
Fork1,0353,698Highest
30-day trendInsufficient historyInsufficient history
Maintenance
Last push2026-10-312026-11-02
Maintenance notesNot verifiedNot verified
Repository created2024-10-102024-07-13
License & use
LicenseLicense not declaredLicense not declared
PricingPricing not verifiedPricing not verified
Basics
Browse by purposeTutorialsRetrieval-augmented generation · Tutorials
TypeGuides & collectionsGuides & collections
SubcategoryAdvanced guidesAdvanced guides
PlatformNot verifiedNot verified
Cost detailsCheck current official software, hosting, model and infrastructure pricing.Check current official software, hosting, model and infrastructure pricing.
Pricing source——
First collected2026-11-032026-11-03
MetricRepository stars, not unique users or individual-skill installsRepository stars, not unique users or individual-skill installs
LanguageJupyter NotebookJupyter Notebook
About this project22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Measured at2026-11-02 19:00 UTC2026-11-02 18:59 UTC
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