# Advanced RAG Implementation Guide  

This repository contains a structured guide to implementing Retrieval-Augmented Generation (RAG). Each notebook in this repository is designed to teach a specific aspect of RAG, starting from the fundamentals to building an end-to-end pipeline.

## Acknowledgment
This guide is inspired by and based on the work of [ThatAIGuy](https://github.com/bansalkanav/Generative-AI-Scratch-2-Advance-By-ThatAIGuy). Full credit goes to the original author for their invaluable resources and insights.

## Topics
- **`1_fundamentals_of_rag.ipynb`**  
   Introduces the basics of Retrieval-Augmented Generation.

- **`2_langchain_retrieval_pipeline.ipynb`**  
   Covers how to set up a retrieval pipeline using LangChain for streamlined workflows.  

- **`3_overview_of_document_loaders.ipynb`**  
   Provides an overview of document loaders and their role in processing data for retrieval tasks.  

- **`4_document_loaders.ipynb`**  
   A deeper dive into using various document loaders with practical examples.  

- **`5_text_splitter_transformation.ipynb`**  
   Explains text splitting and transformations to optimize data for embedding and retrieval.  

- **`6_text_embedding_models.ipynb`**  
   Focuses on text embedding models and their configurations for generating meaningful vector representations.  

- **`7_vector_stores_and_retrievers.ipynb`**  
   Discusses vector stores and retrievers, showcasing how to store and retrieve information efficiently.  

- **`8_retrievers.ipynb`**  
   Detailed exploration of retriever types and their integration with vector stores.  

- **`9_End_to_End_RAG_Chain.ipynb`**  
   Combines all concepts into an end-to-end Retrieval-Augmented Generation pipeline.  

## How to Use  
1. Clone this repository.  
2. Install the required dependencies:  
   ```bash
   pip install -r requirements.txt
   ```  
3. Navigate through the notebooks in order, starting with `1_fundamentals_of_rag.ipynb`.  

## Prerequisites  
- Python 3.10 or higher
- Google API Key  
- Jupyter Notebook or Jupyter Lab  
- All dependencies listed in `requirements.txt`  

## Contributing  
Contributions are welcome! Feel free to fork this repository and submit a pull request.