llmgine

The LLM-native game engine. An ECS game engine where intelligence is a core primitive: attach a Mind (LLM cognition), Eyes (perception/vision), and Voice (neural TTS) to any entity the same way you attach physics or a sprite. An NPC, a boss, a monster, a quest giver, a faction, the weather — if it'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 on their own cadence (plus event wakeups: damaged, spoken to), and return intents.

• Intents pass the same validated action pipeline as player input — a Mind can only do what its body allows. No hallucinated teleports, no 9999 damage.

• Every LLM-augmented module has a deterministic fallback (behavior policies, 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 as validated 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

Related MCP server: antics-mcp

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:

1. Create a key at z.ai and set ZAI_API_KEY.

2. 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 for the GLM Coding Plan — we may receive credit, which funds the project's development: https://z.ai/subscribe?ic=BWTG6TRYYQ

The demo — The Neural Colosseum

A 3D torchlit arena: you (a gladiator) vs The Arena Master, a boss whose mind is a live GLM model. It perceives the pit, taunts you in character (rendered in the "thought ribbon" and speech bubbles, voiced by local Kokoro neural TTS), commands its goblins, fights, and drops loot through deterministic tables. Remove the API key and the same 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 agents can 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 read the death/loot events back — no browser, no human in the loop.

What's in the box

Full design: ARCHITECTURE.md.

Honest status (v0.1)

Works (tested): everything in the table above — 50 unit tests + a live GLM suite (npm run test:live) where a real model drives a Mind through the intent pipeline and Genesis generates a valid, spawnable prefab. The demo has been played 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, procedural SFX + looping ambient music (zero asset files), verb-gated projectiles/ranged combat, NavGrid A* pathfinding (behavior routes around obstacles), save slots (F5/F9 quicksave in the demo), glTF model helpers, and a provider-level repair for GLM flash's malformed tool calls (captured live, unit-tested).

Also works (tested): npx llmgine create <name> scaffolds a playable starter game; npx llmgine export windows|android|ios|pwa|store generates the Electron/.exe config, Capacitor mobile config, installable PWA, and a store listing kit (assets checklist, pricing worksheet, AI disclosure) — generator output is covered by CLI subprocess tests. The heavy toolchains run in your game project (#1 tracks producing reference artifacts).

Remaining gaps (tracked as issues):

• Human feel-tests: audio ear-test (#2), phone/pad in hand (#3), a real .glb exercised 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.