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:
Design (Optional): Use the MATRIX ARCHITECT to paint a custom map topology.
Queue Your Moves: Use the TACTICAL INPUT buttons or MACRO AUTO-GEN to plan your path.
Generate: Click > EXECUTE FORGE in the Payload Forge panel.
Execute: Copy the generated Markdown payload and paste it directly into an LLM with a Code Interpreter.
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 ]
⏱️ ITL PROBE (Side-Channel)
Measure Time-to-First-Token and Execution Latency to detect server memory load.