rag-zero-to-hero-guide and RAG-Overview

rag-zero-to-hero-guide
51
Established
RAG-Overview
36
Emerging
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 2/25
Adoption 7/25
Maturity 15/25
Community 12/25
Stars: 1,271
Forks: 321
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 28
Forks: 4
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About rag-zero-to-hero-guide

KalyanKS-NLP/rag-zero-to-hero-guide

Comprehensive guide to learn RAG from basics to advanced.

This guide helps developers understand and implement Retrieval Augmented Generation (RAG) systems. It provides detailed explanations, practical examples, and tools for building RAG applications from scratch or with frameworks. You'll learn how to feed various data sources into a large language model and get accurate, contextually relevant outputs.

AI development LLM engineering NLP applications data retrieval machine learning systems

About RAG-Overview

ALucek/RAG-Overview

An intuitive approach towards understanding how Retrieval Augmented Generation (RAG) systems work, for the curious yet daunted reader

This resource helps anyone curious about how Retrieval Augmented Generation (RAG) systems function, especially if you've felt intimidated by the technical details. It explains how providing relevant, current, or specialized information alongside a question can dramatically improve the accuracy of large language model responses. The target audience is non-technical professionals who want to grasp the core concepts of RAG without diving into code.

AI-explainability LLM-understanding business-intelligence knowledge-management AI-strategy

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