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This project implements a Retrieval-Augmented Generation (RAG) model using LangChain for document retrieval and natural language generation. The model is designed to process a PDF document, split it into manageable chunks, and generate meaningful answers to queries based on the retrieved context.

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Dhruvrana8/RAG-For-The-Godfather

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LangChain Document Retrieval and Question Answering

This project demonstrates how to use LangChain to load a PDF document, split it into smaller chunks, create embeddings, and build a retrieval-based question-answering system using a Hugging Face model.

Requirements

Before running the code, make sure you have the following dependencies installed:

  • Python 3.7+
  • pip (Python package installer)

Install Required Libraries

To install the required libraries, you can use the following command:

pip install -r requirements.txt

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This project implements a Retrieval-Augmented Generation (RAG) model using LangChain for document retrieval and natural language generation. The model is designed to process a PDF document, split it into manageable chunks, and generate meaningful answers to queries based on the retrieved context.

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