EduRAG: Smart Education using RAG (Streamlit Edition)

EduRAG is an AI-powered educational tool designed to provide fact-grounded answers to student queries directly from NCERT textbooks. This project leverages a Retrieval-Augmented Generation (RAG) pipeline to ensure that the information provided is accurate, relevant, and free from the noise of unverified internet sources.

This version features a simple and interactive frontend built with Streamlit.

How to Run This Project

Follow these steps to get your EduRAG application running locally.

Prerequisites:

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

Step 1: Set Up Your Project Folder

Create a new folder for your project (e.g., EduRAG_Streamlit). Inside this folder, create the following files:

• streamlit_app.py
• ingest.py
• requirements.txt
• README.md (this file)

Create a folder named data. This is where you will place your NCERT textbook PDFs.

Example folder structure:

EduRAG_Streamlit/ ├── data/ │ └── (Your NCERT PDFs go here) ├── streamlit_app.py ├── ingest.py ├── requirements.txt └── README.md

Step 2: Create a Virtual Environment

Open your terminal, navigate into your project folder, and run the following commands to create and activate a Python virtual environment:

On macOS/Linux

python -m venv venv source venv/bin/activate

On Windows (PowerShell)

python -m venv venv venv\Scripts\Activate.ps1

Step 3: Install Dependencies

With your virtual environment active, install all required libraries from requirements.txt:

pip install -r requirements.txt

Step 4: Add Your API Key

In the main project folder, create a file named .env and add your API key(s). Example:

GEMINI_API_KEY="YOUR_API_KEY_HERE"

Step 5: Process Your Textbooks

Put your NCERT PDFs into the data folder. Run the ingestion script to process them and build a local vector index:

python ingest.py

This may take a few minutes depending on the number and size of PDFs.

Step 6: Run the Streamlit App

Start the application:

streamlit run streamlit_app.py

Your browser should open with the EduRAG interface. Start asking questions!

Notes

• The chroma_db/ directory contains a local vector DB used during development and is excluded from the repository via .gitignore.
• Keep secrets (API keys) out of the repository — store them in .env which is ignored.

Contributing

Contributions and improvements are welcome. Open issues or pull requests on the project repository.