A game recommendation system that suggests video games based on titles you've previously played. Built with Python and Prolog for logic-based recommendations.

• Personalized game recommendations based on your gaming history
• Prolog-powered recommendation logic
• Multiple recommendation strategies (genre, platform, rating similarity)
• Real game data from IGDB (Internet Game Database)
• Fast queries with SWI-Prolog backend

Before installation, ensure you have:

1. Python 3.12 or higher

   • Check: python3.12 --version
   • Download: https://www.python.org/downloads/

2. SWI-Prolog (MUST be installed BEFORE creating Python virtual environment)

   • macOS: brew install swi-prolog
   • Ubuntu/Debian: sudo apt-get install swi-prolog
   • Windows: https://www.swi-prolog.org/download/stable
   • Verify: swipl --version

3. IGDB API Account (free)

   • Required for fetching game data
   • Setup instructions below

git clone https://github.com/osyounis/new_game_plus.git
cd new_game_plus

python3 -m venv venv

# Activate on macOS/Linux
source venv/bin/activate

# Activate on Windows
venv\Scripts\activate

pip install --upgrade pip
pip install -r requirements.txt

1. Go to https://api-docs.igdb.com/#account-creation

2. Sign up for a Twitch account (if needed)

3. Visit https://dev.twitch.tv/console/apps

4. Click "Register Your Application"

5. Fill in:

   • Name: "New Game Plus Recommender"
   • OAuth Redirect URLs: http://localhost
   • Category: Application Integration

6. Click "Manage" → Copy your Client ID

7. Click "New Secret" → Copy your Client Secret

8. Create .env file in project root:

cp .env.example .env

9. Edit .env and add your credentials:

IGDB_CLIENT_ID=paste_your_client_id_here
IGDB_CLIENT_SECRET=paste_your_client_secret_here

# Fetch 50 games from IGDB
python src/igdb_client.py

# Convert to Prolog facts
python src/generate_facts.py

python src/main.py

You'll be prompted to enter a game title.

python src/main.py --game "Dark Souls"

python src/main.py --game "The Witcher 3" --limit 10

============================================================
Recommendations based on: Dark Souls
============================================================

Similar Games (Genre + Rating):
  1. Bloodborne
  2. Elden Ring
  3. Dark Souls II
  4. Demon's Souls
  5. Sekiro: Shadows Die Twice

Same Genre:
  1. Bloodborne
  2. The Witcher 3: Wild Hunt
  3. Dragon's Dogma
  ...

new_game_plus/
├── src/                    # Python source code
│   ├── main.py            # Main CLI application
│   ├── igdb_client.py     # IGDB API client
│   ├── generate_facts.py  # JSON → Prolog converter
│   └── prolog_bridge.py   # Python-Prolog interface (pyswip)
├── prolog/                 # Prolog knowledge base
│   ├── knowledge_base.pl  # Game facts (auto-generated)
│   └── rules.pl           # Recommendation rules
├── data/                   # Game data
│   └── games.json         # IGDB game data (50 games)
├── .env                    # API credentials (NOT in git)
├── .env.example           # Template for .env
├── requirements.txt       # Python dependencies
└── README.md              # This file

The recommendation system uses a hybrid Python-Prolog architecture:

1. Data Collection (igdb_client.py)

   • Fetches game data from IGDB API
   • Stores raw JSON in data/games.json

2. Fact Generation (generate_facts.py)

   • Converts JSON to Prolog facts
   • Creates prolog/knowledge_base.pl
   • Format: game(Title, Genre, Platform, Rating)

3. Recommendation Rules (prolog/rules.pl)

   • Defines logic for matching games
   • Strategies: genre, platform, rating similarity

4. Query Engine (prolog_bridge.py)

   • Bridges Python and Prolog via pyswip
   • Sends queries to Prolog
   • Returns results to Python

5. User Interface (main.py)

   • CLI for user interaction
   • Displays formatted recommendations

Data Flow:

IGDB API → igdb_client.py → data/games.json
                                    ↓
                             generate_facts.py
                                    ↓
                      prolog/knowledge_base.pl ← rules.pl
                                    ↓
           User → main.py → prolog_bridge.py → Prolog
                                    ↓
                            Recommendations

Test each component individually:

# Test IGDB API connection
python src/igdb_client.py

# Test Prolog fact generation
python src/generate_facts.py

# Test Prolog bridge directly
python src/prolog_bridge.py

# Test full system
python src/main.py --game "The Witcher 3: Wild Hunt"

GNU General Public License v3.0 - See LICENSE file for details

• IGDB API for game data
• SWI-Prolog for the logic programming engine
• pyswip for Python-Prolog integration