NotchNet Backend

NotchNet is an AI-powered Minecraft knowledge companion that uses RAG (Retrieval Augmented Generation) to answer questions about Minecraft and its mods.

🔗 Frontend Mod: notchnet-mod

Features

• 🏠 Local RAG Pipeline — Runs entirely on your machine using Ollama.
• 🌐 Dynamic Wiki Fetching — Fetch and index any MediaWiki-based wiki (e.g., RLCraft, Feed The Beast).
• 🎮 Auto Mod Detection — Automatically finds and learns about installed mods when the game launches.
• ☁️ Cloud Mode — Offload AI inference to a remote server for low-end machines.
• 🧠 Mod Awareness — Context-aware answers based on loaded wikis.

Quick Start

Prerequisites

• Python 3.10+
• Ollama installed and running
• 8GB VRAM + 16GB RAM for smooth local model inference

Run It

Windows:

start_local.bat

Mac/Linux:

chmod +x start_local.sh
./start_local.sh

The script will:

1. Create a virtual environment and install dependencies.
2. Ask if you want Local or Cloud/Remote AI.
3. Local: Pulls the default Ollama model (llama3:8b).
4. Cloud: Configures connection to your remote Ollama instance.
5. Start the API server at http://localhost:8000.

Ask a Question

curl -X POST http://localhost:8000/ask \\
     -H "Content-Type: application/json" \\
     -d '{"question": "How do I make a shield?"}'

Admin Endpoints

Add a Mod Wiki

curl -X POST http://localhost:8000/admin/add-wiki \\
     -H "Content-Type: application/json" \\
     -d '{
         "url": "https://rlcraft.fandom.com",
         "name": "RLCraft"
     }'

Project Structure

NotchNet/
├── config/           # RAG pipeline and config
├── mod_discovery/    # Auto-detect installed mods
├── server.py         # FastAPI/Flask server
├── start_local.sh    # Mac/Linux startup script
├── start_local.bat   # Windows startup script
├── wiki/             # Wiki loaders and cleaners
└── requirements.txt

License

MIT