RAG-Bot

RAG-Bot is a Retrieval-Augmented Generation (RAG) chatbot designed to provide informative responses based on user queries. It leverages advanced natural language processing techniques to retrieve relevant information from documents and generate coherent answers.

Features

• Document Retrieval: Efficiently retrieves relevant documents based on user input.
• Natural Language Processing: Utilizes state-of-the-art models for understanding and generating responses.
• User-Friendly Interface: Simple interaction model for users to ask questions and receive answers.
• Customizable: Easily extendable to include additional features or integrate with other data sources.

Installation

To set up RAG-Bot locally, follow these steps:

Prerequisites

• Python 3.8 or higher
• pip (Python package installer)

Steps to Install

1. Clone the Repository:

   git clone https://github.com/m-tabish/rag-bot.git
   cd rag-bot
   

2. Create a Virtual Environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use  `venv\Scripts\activate`
   pip install --quiet --upgrade langchain langchain-community langchain-chroma PyPDF2 langchain_google_genai streamlit langchain_huggingface python-dotenv
   

3. Install Required Packages:

   pip install -r requirements.txt
   

4. Set Up Environment Variables: Create a .env file in the project root directory and add your API keys and other configuration settings as required by the application.

Usage

To run the RAG-Bot, execute the following command in your terminal:

streamlit run main.py