StudyGen-AI Project LIVE DEMO LINK : https://studygen-ai-60e1.onrender.com 👈👈😊

📚 StudyGen AI – AI PDF Study Assistant

About the Project

StudyGen AI is a web application developed as a college AIML project to make studying from PDF documents easier and more interactive.

Instead of reading long notes or textbooks manually, users can upload a PDF and interact with it using Artificial Intelligence. The application extracts the text from the uploaded document and uses a Retrieval-Augmented Generation (RAG) approach with the Google Gemini API to answer questions, generate summaries, create quizzes, and prepare flashcards.

The main goal of this project is to help students save time while improving their learning experience through AI.

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Features

• 📄 Upload PDF documents
• 💬 Ask questions about the uploaded PDF
• 📝 Generate AI-powered summaries
• ❓ Create multiple-choice quiz questions
• 🧠 Generate flashcards for quick revision
• 📥 Download generated study notes in Markdown format
• 🎨 Simple and responsive user interface

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Technologies Used

Frontend

• HTML5
• CSS3
• JavaScript

Backend

• Python
• Flask

Artificial Intelligence

• Google Gemini API
• Retrieval-Augmented Generation (RAG)

PDF Processing

• PyMuPDF

Vector Database

• ChromaDB

Other Libraries

• LangChain
• python-dotenv

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Project Structure

StudyGen_AI/
│
├── .env
├── requirements.txt
├── app.py
├── rag_engine.py
├── test_rag.py
│
├── templates/
│   └── index.html
│
└── static/
    ├── css/
    │   └── style.css
    │
    └── js/
        └── main.js

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Requirements

Before running the project, make sure you have the following installed:

• Python (3.10 or above)
• Visual Studio Code
• Git (optional)
• Google Gemini API Key

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Recommended VS Code Extensions

• Python (Microsoft)
• Pylance
• DotENV
• Markdown All in One

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Setup Instructions

Step 1: Open the Project

Open the StudyGen_AI folder in Visual Studio Code.

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Step 2: Create a Virtual Environment

Open the terminal and run:

python -m venv .venv

Activate the environment:

Windows

.venv\Scripts\activate

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Step 3: Install Required Packages

pip install -r requirements.txt

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Step 4: Configure Environment Variables

Create or edit the .env file in the project folder.

FLASK_SECRET_KEY=your_secret_key
GEMINI_API_KEY=your_gemini_api_key

To get your Gemini API Key:

1. Visit Google AI Studio.
2. Sign in with your Google account.
3. Create a new API Key.
4. Copy and paste it into the .env file.

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Step 5: Verify the Setup

Run:

python test_rag.py

If everything is configured correctly, the API connection will be verified.

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Step 6: Start the Application

Run:

python app.py

Open your browser and visit:

http://127.0.0.1:5000

Now upload a PDF and start using the application.

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How It Works

1. Upload a PDF document.
2. The application extracts the text.
3. The content is stored in a ChromaDB vector database.
4. Relevant information is retrieved using RAG.
5. Google Gemini generates answers based on the retrieved content.
6. Users can generate summaries, quizzes, and flashcards from the same PDF.

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Future Improvements

• User Login System
• Multiple PDF Support
• Voice-based Question Answering
• Multi-language Support
• Cloud Storage Integration
• Progress Tracking Dashboard

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Project Objective

The objective of this project is to demonstrate how Generative AI can improve learning by transforming static PDF documents into an interactive study assistant. It helps students quickly understand concepts, revise important topics, and test their knowledge using AI-generated content.

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Environment Variables

For security reasons, this repository does not include the .env file. Sensitive information such as API keys and secret keys should never be committed to GitHub.

Create a file named .env in the project root directory and add the following:

FLASK_SECRET_KEY=your_secret_key
GEMINI_API_KEY=your_gemini_api_key

Getting a Google Gemini API Key

1. Visit Google AI Studio.
2. Sign in with your Google account.
3. Click Create API Key.
4. Copy the generated API key.
5. Paste it into your .env file.

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Files Ignored by Git

This project uses a .gitignore file to exclude files and folders that should not be uploaded to GitHub.

The following are ignored:

• .env – Stores API keys and other sensitive environment variables.
• venv/ – Python virtual environment.
• .venv/ – Alternative virtual environment folder.
• __pycache__/ – Python cache files generated automatically.
• *.pyc – Compiled Python files.
• chroma_store/ – Local ChromaDB vector database generated at runtime.
• uploads/ – User-uploaded PDF files generated during application usage.

These files and folders are created automatically during development or contain sensitive information, so they are intentionally excluded from version control.

Note: After cloning this repository, create your own .env file and install the required dependencies before running the project.

Developed By

Deepak B
B.Tech CSE (Artificial Intelligence & Machine Learning)

College Mini Project – StudyGen AI