Rag-QuerySystem

This project implements a Retrieval-Augmented Generation (RAG) query system using LangChain and various tools to provide intelligent answers from user-provided URLs. It features a backend built with FastAPI and a frontend powered by React and Material-UI.

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Getting Started

Follow the steps below to clone the repository, install dependencies, and start both the backend and frontend servers.

Prerequisites

• Python 3.8 or higher
• Node.js 16 or higher
• npm (comes with Node.js)
• Git

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Clone the Repository

# Clone the repository to your local machine
git clone https://github.com/buttaRahul/Rag-QuerySystem.git

# Navigate to the project directory
cd Rag-QuerySystem

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Backend Setup

Install Dependencies

# Navigate to the backend directory
cd backend

# Create a virtual environment
python -m venv venv

# Activate the virtual environment
# On Windows:
venv\Scripts\activate
# On macOS/Linux:
source venv/bin/activate

# Install Python dependencies
pip install -r requirements.txt

Start the Backend Server

Once dependencies are installed, start the backend server:

# Run the FastAPI backend server
uvicorn main:app --reload

# The server will run at http://127.0.0.1:8000

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Frontend Setup

Install Dependencies

Navigate to the frontend directory and install the required JavaScript dependencies:

# Navigate to the frontend directory
cd ../frontend

# Install npm packages
npm install

Start the Frontend Server

# Start the React frontend server
npm run dev

# The frontend server will run at http://localhost:3000

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Accessing the Application

Once both the backend and frontend servers are running:

• Open your browser and navigate to http://localhost:3000 to interact with the application.
• The backend API can be accessed at http://127.0.0.1:8000.

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Project Structure

• backend/: Contains the FastAPI backend code.
• frontend/: Contains the React frontend code.
• requirements.txt: Lists Python dependencies for the backend.
• package.json: Lists JavaScript dependencies for the frontend.

Project Demonstration

click the image to watch video demonstration