RealmForge
Description
RealmForge: AI-powered procedural content generation for games using AFLOW workflows and Three.js visualization
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
RealmForge
Procedural content generation for games using LLMs. Generates scenes, characters, NPCs, and quests through a FastAPI server, with optional Three.js visualization.
Architecture
| Directory | Purpose |
|---|---|
src/api/ |
FastAPI server with routers for world, NPC, narrative, difficulty, visualization |
src/models/ |
Pydantic models for world, NPC, narrative, difficulty, player, visualization |
src/services/ |
Business logic: NPC generation, narrative, difficulty scaling, optimization |
src/config/ |
Settings (env-based configuration) |
What It Generates
| Content type | Description |
|---|---|
| Scenes | 3D environments (forests, towns, caves, dungeons) |
| Characters | Attribute sets and appearance descriptions |
| NPCs | Personalities, behaviors, backstories |
| Quests | Objectives, narrative text, rewards |
Generation is done via LLM calls orchestrated through an AFLOW-style workflow pipeline.
Requirements
- Python 3.11+
- API keys for your LLM provider (configured in
.env)
Setup
git clone https://github.com/jmanhype/RealmForge.git
cd RealmForge
pip install -e .
cp .env.example .env # add API keys
python -m src.api.main
Server runs at `localhost:8001`. API docs at `localhost:8001/docs`. Visualization at `localhost:8001/visualizer`.
Status
Prototype. The generation endpoints work but output quality depends entirely on the LLM and prompts used. The Three.js visualizer renders basic scenes. The roadmap lists game engine integrations (Unity, Unreal) and avatar format support (VRM) -- none of that exists yet. No tests are included.
Note: the repository contains `__pycache__` directories and `.pyc` files that should have been gitignored.
License
MIT
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