llmgine
The LLM-native game engine. An ECS game engine where intelligence is a coreprimitive: attach a Mind (LLM cognition), Eyes (perception/vision), andVoice (neural TTS) to any entity the same way you attach physics or asprite. An NPC, a boss, a monster, a quest giver, a faction, the weather — ifit's in the world, it can think, see, and speak.
Working title. TypeScript · 3D (three.js) + headless + 2D canvas · MIT.
deterministic 60 Hz ECS sim ←— validated intents —— async LLM minds
│ ▲
└—————— perception snapshots + pixel vision ———————┘
The hard problem: games are deterministic real-time loops; LLMs are slow,async, and non-deterministic. llmgine resolves it structurally:
- The sim never blocks on a thought. Minds observe snapshots, think ontheir own cadence (plus event wakeups: damaged, spoken to), and returnintents.
- Intents pass the same validated action pipeline as player input — a Mindcan only do what its body allows. No hallucinated teleports, no 9999 damage.
- Every LLM-augmented module has a deterministic fallback (behaviorpolicies, weighted loot tables, quest state machines). If the API is down,the game still runs.
- Genesis turns the LLM into a content generator: prefabs, loot, quests asvalidated JSON. The model proposes; the engine disposes.
Quickstart
npm install llmgine
import {
World, GameLoop, SpatialGrid, ActionRegistry, actionSystem,
Transform, Velocity, Named, Health, Speech, Behavior,
STANDARD_VERBS, behaviorSystem, movementSystem,
Mind, MindMemory, CognitionDriver, OpenAICompatibleProvider,
} from "llmgine";
const world = new World(42); // seeded — deterministic
const grid = new SpatialGrid();
const actions = new ActionRegistry();
for (const v of STANDARD_VERBS) actions.register(v);
// any entity + Mind = intelligent entity
const guard = world.create();
world.add(guard, Transform, { x: 0, y: 0 });
world.add(guard, Velocity);
world.add(guard, Named, { name: "Gate Guard" });
world.add(guard, Health);
world.add(guard, Speech);
world.add(guard, Behavior, { mode: "idle" });
world.add(guard, Mind, {
persona: "A vigilant town guard. Suspicious of strangers.",
goals: ["guard the gate"],
thinkEvery: 8, // seconds between thoughts
fallbackMode: "wander", // deterministic policy if the LLM is unavailable
});
world.add(guard, MindMemory);
const driver = new CognitionDriver({
provider: new OpenAICompatibleProvider(), // reads ZAI_API_KEY / LLM_API_KEY + LLM_BASE_URL
actions, grid,
});
world.addSystem(actionSystem(actions));
world.addSystem(behaviorSystem());
world.addSystem(movementSystem(grid));
world.addSystem(driver.system());
new GameLoop(world).start(); // browser; or loop.advance(n) headless
Get a free model (GLM)
The default provider targets z.ai's OpenAI-compatible API,where glm-4.5-flash is free — free minds for every NPC in your game:
- Create a key at z.ai and set
ZAI_API_KEY. - That's it. Tiers:
fast(flash — NPC chatter),smart(deep reasoning),vision(pixel Eyes). Map tiers to any models you like.
Any OpenAI-compatible endpoint works instead: OpenAI, Ollama, LM Studio, vLLM —new OpenAICompatibleProvider({ baseUrl, apiKey, models }).
Disclosure: if you want more than the free tier, this is a referral link forthe GLM Coding Plan — we may receive credit, which funds the project'sdevelopment: https://z.ai/subscribe?ic=BWTG6TRYYQ
The demo — The Neural Colosseum
A 3D torchlit arena: you (a gladiator) vs The Arena Master, a boss whosemind is a live GLM model. It perceives the pit, taunts you in character(rendered in the "thought ribbon" and speech bubbles, voiced by localKokoro neural TTS), commands its goblins,fights, and drops loot through deterministic tables. Remove the API key and thesame fight runs on pure instinct.
git clone https://github.com/lordbasilaiassistant-sudo/llmgine
cd llmgine && npm install
npm run demo # http://localhost:4173 — auto-detects ZAI_API_KEY locally
For AI agents: the MCP server
The engine ships as an MCP tool so agentscan build and test games headlessly:
{ "mcpServers": { "llmgine": { "command": "npx", "args": ["llmgine-mcp"], "env": { "ZAI_API_KEY": "…" } } } }
Tools: create_world, define_prefab, define_loot_table, spawn, act,run (advance N ticks → event log), query_world, generate_prefab(Genesis). An agent can design a boss, simulate 10 seconds of combat, and readthe death/loot events back — no browser, no human in the loop.
What's in the box
| Layer | Contents |
|---|---|
core |
ECS, fixed-timestep loop, seeded RNG, event journal, spatial grid, prefabs (validated JSON), action/intent pipeline, save/load |
| gameplay | combat (PvE/PvP, factions, aggro), loot/drop tables, quests + rewards, inventory, dialogue/speech, spawning — each fully functional with zero LLM |
ai |
provider-agnostic inference (tiers: fast/smart/vision), Mind/Eyes/Voice components, cognition scheduler, memory, budgets + caching, Genesis content generation |
render3d |
three.js renderer: model factories with live-sim-driven animation, chase cam, capture() for pixel vision |
render |
headless renderer (tests/servers/MCP) + canvas 2D (prototyping/minigames) |
mcp |
the engine as an agent tool |
Full design: ARCHITECTURE.md.
Honest status (v0.1)
Works (tested): everything in the table above — 50 unit tests + a live GLMsuite (npm run test:live) where a real model drives a Mind through the intentpipeline and Genesis generates a valid, spawnable prefab. The demo has beenplayed to completion by a scripted agent in a real browser: pack culled,boss duel won, quest completed, rewards granted, live GLM taunts mid-fight —and the same run with no API key completes on deterministic fallbacks.
Also in the box now (all tested): touch joystick + gamepad input, proceduralSFX + looping ambient music (zero asset files), verb-gated projectiles/rangedcombat, NavGrid A* pathfinding (behavior routes around obstacles), save slots(F5/F9 quicksave in the demo), glTF model helpers, and a provider-level repairfor GLM flash's malformed tool calls (captured live, unit-tested).
Also works (tested): npx llmgine create <name> scaffolds a playablestarter game; npx llmgine export windows|android|ios|pwa|store generates theElectron/.exe config, Capacitor mobile config, installable PWA, and a storelisting kit (assets checklist, pricing worksheet, AI disclosure) — generatoroutput is covered by CLI subprocess tests. The heavy toolchains run in yourgame project (#1tracks producing reference artifacts).
Remaining gaps (tracked as issues):
- Human feel-tests: audio ear-test (#2), phone/pad in hand (#3), a real .glbexercised in an example (#6).
- Multiplayer (the event journal + intent log are the designed foundation).
- Voxel/heightmap terrain; STT input.
- Vision ("pixels" Eyes) is wired end-to-end but not yet exercised by the demo.
License
MIT. Contributions welcome — see CONTRIBUTING.md.