GROND_ENGINE

A stateful UI to generate Python 3D Raycasting payloads for LLM Code Interpreters. It operates as a Read-Eval-Print Loop (REPL) to test Large Language Models (LLMs) on spatial reasoning, deterministic physics, and long-horizon pathfinding.

Welcome to the GROND-REPL Controller

This tool allows you to explore a 3D environment rendered entirely in ASCII by tricking an AI's Python Sandbox into running a retro raycasting engine. Since the AI doesn't have an interactive screen, you play by "correspondence" (sending it a list of moves, and it sending you back a snapshot).

How to Play:

  1. Design (Optional): Use the MATRIX ARCHITECT to paint a custom map topology.
  2. Queue Your Moves: Use the TACTICAL INPUT buttons or MACRO AUTO-GEN to plan your path.
  3. Generate: Click > EXECUTE FORGE in the Payload Forge panel.
  4. Execute: Copy the generated Markdown payload and paste it directly into an LLM with a Code Interpreter.
  5. Behold: The LLM will execute the code and reply with your rendered ASCII frame and Telemetry HUD.

⚠️ THE GOLDEN RULE: Do NOT Clear the Queue!

LLM code environments frequently spin up and shut down, meaning they forget where you were standing between prompts. To fix this, our payload speed-runs your entire historical run from the spawn point every single time. ONLY click "✕ RESPAWN" if you want to wipe the queue and start back at the very beginning of the level!

TACTICAL INPUT

HOTKEYS: W A S D F P

MACRO AUTO-GEN

ACTION QUEUE

[ 0 QUEUED ]
[ BUFFER EMPTY ]

MATRIX ARCHITECT

LIVE TACTICAL PREVIEW

>

PAYLOAD FORGE

> SELECT_CAMOUFLAGE_DOMAIN
> ENTROPY SEED INJECTOR