dms_project

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README

CryptoRand: Interactive Web Application for Exploring Cryptographic Pseudo-Random Number Generators

Author: Anugrah Singh (1AY23CS031)

CryptoRand is an interactive web application designed to demonstrate and educate users on the application of discrete mathematics principles in cryptographic pseudo-random number generators (PRNGs). The project allows users to generate sequences from PRNGs like the Linear Congruential Generator (LCG) and Blum Blum Shub (BBS), visualize their outputs, and learn underlying mathematical concepts through an AI-powered tutor (Gemma 3).

For a detailed explanation of the project, please see PROJECT_REPORT.md.

Tech Stack

Frontend: Vite with React
Styling: Tailwind CSS
Visualizations: Chart.js
Backend: Flask (Python)
AI Integration: Gemma 3 (locally hosted via LM Studio)
Mathematical Computations: NumPy/SciPy
Version Control: Git

Detailed Setup Instructions

1. Clone the Repository

git clone https://github.com/Anugrah-Singh/dms_project.git
cd dms_project

2. Set up LM Studio and Gemma 3

Download and Install LM Studio: Go to https://lmstudio.ai/ and download the version appropriate for your operating system. Install it.
Download Gemma 3:
- Open LM Studio.
- In the search bar (magnifying glass icon on the left), search for "Gemma 3".
- Download a Gemma 3 model (e.g., one of the smaller, faster GGUF versions if you are unsure).
Start the Local Server:
- Go to the "Local Server" tab (server icon, usually <-> on the left).
- Select the downloaded Gemma 3 model from the dropdown at the top.
- Click "Start Server". By default, it usually runs on http://localhost:1234/v1. Note this address.
- Ensure the server is running whenever you use the CryptoRand application.

3. Backend Setup (Flask/Python)

Navigate to the backend directory:
```
cd backend
```
Create and activate a Python virtual environment:
- If you don't have virtualenv installed, install it:
```
pip install virtualenv
```
- Create the virtual environment:
```
python -m venv venv
```
- Activate the virtual environment:
```
.\venv\Scripts\Activate.ps1
```
  (For bash/zsh on Linux/macOS, it would be source venv/bin/activate)
Install dependencies:
```
pip install -r requirements.txt
```
(Optional) Configure LM Studio API Endpoint:
- If your LM Studio server is running on a different port or you need to specify it, you might need to configure this in backend/app.py or via an environment variable if the application is set up to read it. (Check app.py for how the LM Studio URL is determined).
Run the Flask application:
```
flask run
```
The backend will typically run on http://127.0.0.1:5000.

4. Frontend Setup (Vite/React)

Install Node.js and npm:
- If you don't have Node.js and npm installed, download and install them from https://nodejs.org/. It's recommended to install an LTS version.
Navigate to the frontend directory:
```
cd ..\frontend 
```
(Assuming you are in the backend directory from the previous step. If you are in the project root, just cd frontend)
Install dependencies:
```
npm install
```
Run the Vite development server:
```
npm run dev
```
The frontend will typically be accessible at http://localhost:5173 (or another port if 5173 is busy, Vite will tell you). Open this URL in your web browser.

Running the Project

Backend

Navigate to the backend directory:
```
cd backend
```
Install dependencies:
```
pip install -r requirements.txt
```
Run the Flask application:
```
flask run
```
The backend will typically run on http://127.0.0.1:5000.

Frontend

Navigate to the frontend directory:
```
cd frontend
```
Install dependencies:
```
npm install
```
Run the Vite development server:
```
npm run dev
```
The frontend will typically be accessible at http://localhost:5173.

Project Report

For a comprehensive understanding of the project, including its goals, technical details, discrete mathematics concepts applied, and educational value, please refer to the PROJECT_REPORT.md.