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Comprehensive guide to learn RAG from basics to advanced.
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<h1 align ="center"> 👩🏼💻 RAG Zero to Hero Guide </h1>
This repository serves as a comprehensive guide to learn RAG from basics to advanced.
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## Quick links
||||
|---|---|---|
| [🧱 RAG Basics Course](#rag-basics-course) | [🚀 RAG Toolkit](#rag-toolkit) | [🩸 RAG Survey Papers](#rag-survey-papers) |
| [✅ RAG Evaluation Course](#rag-evaluation-course) | | |
## RAG Basics Course
| Topic | Description | Link |
|---------|-------------|------|
| What is RAG? | Explain RAG in with a simple example. | [Link](RAG%20Basics/What_is_RAG.md)|
| Why RAG? | Explain the drawbacks of LLMs and how RAG addresses them.| [Link](RAG%20Basics/Why_RAG.md)|
| How does RAG work? | Explain the different steps in RAG - Indexing, Retrieval, Augmentation and Generation.| [Link](RAG%20Basics/How_does_RAG_work.md)|
| RAG Benefits and Challenges | Discusses the benefits and challenges of RAG. | [Link](RAG%20Basics/RAG_Benefits_and_Challenges.md)|
| RAG Must Know Terms| Definitions of RAG must know terms. | [Link](RAG%20Basics/RAG_must_know_terms.md)|
| RAG Roadmap | Detailed roadmap to learn RAG from basics to advanced. | [Link](RAG%20Basics/RAG_Roadmap.md)|
| RAG Developer's Stack | Covers the various libraries used to build RAG systems | [Link](RAG%20Basics/RAG_Developer_Stack.md)|
| RAG from Scratch | RAG implementation from scratch without any frameworks. | [Link](RAG%20Basics/notebooks/RAG_from_Scratch.ipynb)
| RAG with LangChain | RAG implementation using LangChain framework. | [Link](RAG%20Basics/notebooks/RAG_with_LangChain.ipynb)
| Website RAG | RAG over a website implemented using LangChain framework. | [Link](RAG%20Basics/notebooks/Web_Page_RAG.ipynb)
| YouTube Video RAG | RAG over a YouTube video transcript implemented using LangChain framework. | [Link](RAG%20Basics/notebooks/YouTube_Video_RAG.ipynb)
| Agentic RAG | Agentic RAG system implemented using CrewAI framework. | [Link](RAG%20Basics/notebooks/AgenticRAG_with_CrewAI.ipynb)
## RAG Evaluation Course
| Topic | Description | Link |
|---------|-------------|------|
| RAG Evaluation Metrics Intro | Brief overview of RAG evaluation metrics | [Link](RAG%20Evaluation/rag_eval_intro.md) |
| RAG Retriever Evaluation Metrics | Detailed explanation of RAG retriever evaluation metrics | [Link](RAG%20Evaluation/rag_retriever_metrics.md) |
| RAG Generator Evaluation Metrics | Detailed explanation of RAG generator evaluation metrics | [Link](RAG%20Evaluation/rag_generator_metrics.md) |
| RAG Evaluation with RAGAS | Implementation of RAG evaluation metrics with RAGAS library | [Link](RAG%20Evaluation/notebooks/RAG_Evaluation_using_RAGAS.ipynb) |
| RAG Evaluation with DeepEval | Implementation of RAG evaluation metrics with DeepEval library | [Link](RAG%20Evaluation/notebooks/RAG_Evaluation_using_DeepEval.ipynb) |
| Detect Hallucination in RAG | Detection of hallucination in RAG using LLMs and LettuceDetect library | [Link](RAG%20Evaluation/notebooks/Hallucination_RAG.ipynb) |
## RAG Toolkit
<p align = "center"> <b> 🔴Frameworks🔴 </b> </p>
| Library | Description | Link |
|---------|-------------|------|
| LangChain | LangChain is a framework for developing applications powered by large language models (LLMs). | [Link](https://github.com/langchain-ai/langchain) |
| Llama Index | LlamaIndex is a data framework for your LLM applications | [Link](https://github.com/run-llama/llama_index) |
| Haystack | Haystack is an end-to-end LLM framework that allows you to buiExcerpt of 12,350 characters
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