Basic-RAG-using-Langchain

This project implements a basic Retrieval-Augmented Generation (RAG) system using Langchain, a framework for building applications that integrate language models with knowledge bases and other data sources.

Features

• Utilizes the Langchain framework to build a RAG system.
• Integrates with OpenAI's API for language model interactions.
• Includes document retrieval using FAISS for efficient search.
• Supports PDF document parsing with PyPDF.
• Built with Streamlit for easy deployment of web applications.

Requirements

Before running the project, ensure you have the following dependencies installed:

langchain
streamlit
pypdf
langchain-community
langchain-core
faiss-cpu
tiktoken
openai

You can install the dependencies using:

pip install -r requirements.txt

Usage

1. Clone the repository:

   cd Basic-RAG-using-Langchain

2. Install the required packages:

   pip install -r requirements.txt

3. Run the Streamlit app:

   streamlit run main.py

4. The app will be available on your local server. You can interact with the system to input questions and receive responses from the RAG model.

File Structure

• main.py: The main application script that integrates Langchain and OpenAI APIs to build the RAG system.
• Dockerfile: Contains instructions for containerizing the project for deployment.
• requirements.txt: Lists all the required packages to run the application.

License

This project is licensed under the MIT License.

Acknowledgments

• Langchain for providing the framework for building RAG systems.
• OpenAI for the language model.