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

Comprehensive guide to learn RAG from basics to advanced.

Repository: https://github.com/KalyanKS-NLP/rag-zero-to-hero-guide
Canonical: https://ross.abutalabs.com/products/rag-zero-to-hero-guide
Homepage: https://x.com/kalyan_kpl
Language: Jupyter Notebook
License: Apache-2.0
License Family: permissive
Topics: ai-engineer, generative-ai, large-language-models, llm-engineer, llm-rag, llms, retrieval-augmented-generation
Last push: 2025-03-29T03:29:24+00:00

## Health v2 (maintenance only)
Score: 26/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 13, release rhythm 35, longevity 38
- inputs: {"age_days": 536, "days_push": 522, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1410, forks 344 (observed 2026-08-28T04:04:38.897642+00:00)

## What it is
A comprehensive open-source guide and course for learning Retrieval-Augmented Generation (RAG) from basics to advanced topics. It includes markdown lessons and Jupyter notebook implementations covering RAG from scratch, with LangChain, over websites and YouTube videos, agentic RAG with CrewAI, and RAG evaluation metrics.

## Use cases
- learn RAG from scratch
- understand how retrieval-augmented generation works
- implement RAG with LangChain
- evaluate RAG pipeline performance
- build agentic RAG systems
- find a roadmap for becoming an LLM/RAG engineer

## When to choose
- you want a structured, free curriculum for learning RAG end to end
- you prefer hands-on Jupyter notebook examples with popular frameworks like LangChain and CrewAI
- you need to learn RAG evaluation metrics and best practices

## When to avoid
- you need a production-ready RAG framework or library rather than educational material
- you want a maintained software tool with releases and API stability
- you are looking for non-Python or non-LLM retrieval tutorials

## Facets
- artifact type: learning-resource
- maturity: active
- function: rag, llm-inference, agent-framework
- domain: large-language-models, tutorials, artificial-intelligence
- platform: python
- tags: jupyter-notebooks, rag-evaluation, langchain, crewai, agentic-rag, course, retrieval-augmented-generation

## Member repositories
- KalyanKS-NLP/rag-zero-to-hero-guide (main) score 26

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:38.897642+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:38:26.950863+00:00, confidence not recorded.
  - readme: https://github.com/KalyanKS-NLP/rag-zero-to-hero-guide (fetched 2026-08-28T04:04:38.897642+00:00, sha d3c93c87d120)
- Data as of 2026-08-30T08:39:29.467469+00:00.