Game Recommender (Hardware-based)

Full-stack app: HTML/CSS/JS frontend + Python (Flask) backend with a simple ML-like recommender that suggests games based on your CPU, GPU, and RAM.

Quick Start

1. Create and activate a virtual environment (optional but recommended):
   • Windows PowerShell:

py -3 -m venv .venv
.\.venv\Scripts\Activate.ps1

2. Install dependencies:

pip install -r requirements.txt

3. Run the server:

python app.py

4. Open the app in your browser:

• Go to http://127.0.0.1:5000/

Usage

Enter your CPU, GPU, and RAM. You can provide either:

• Numeric performance scores for CPU/GPU (e.g., PassMark-like scores) and RAM in GB, or
• Common model names (e.g., "i5-8400", "GTX 1060", "Ryzen 5 3600", "RTX 3060"). The app maps several common models to approximate scores. If unmapped, it extracts numbers when possible.

Tech Stack

• Backend: Flask, pandas, numpy, scikit-learn (for future similarity metrics)
• Frontend: HTML, CSS, Vanilla JS

Project Structure

.
├─ app.py                 # Flask app entrypoint
├─ recommender.py         # Hardware parsing + recommendation logic
├─ data\games.csv         # Sample game dataset with min/rec specs
├─ frontend\              # Static frontend served by Flask
│  ├─ index.html
│  ├─ styles.css
│  └─ script.js
├─ requirements.txt
└─ README.md

Notes

• The dataset is illustrative. Extend data/games.csv with more titles/specs to improve results.
• The recommendation ranks games where your hardware meets minimum requirements, and scores higher when your specs are closer to or above recommended specs.