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title: ghostloop demo
emoji: 🤖
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 5.12.0
python_version: "3.12"
app_file: app.py
pinned: true
license: mit
short_description: Drive any robot through a fail-closed safety pipeline.
tags:
- robotics
- embodied-ai
- agent
- mcp
- safety
- mujoco
- ros2
---
# ghostloop · live demo
The agent loop, embodied. Tool-using runtime + fail-closed safety
pipeline + sim-first execution + post-hoc analysis layer for
embodied AI / robotics. Sister project to
[GhostLM](https://github.com/joemunene-by/GhostLM).
This Space lets you pick a robot profile (Franka arm / Spot quadruped /
Tello drone / Stretch mobile arm / humanoid / TurtleBot) and dispatch
Intents through the safety pipeline that ships in the library.
- **GitHub:** https://github.com/joemunene-by/ghostloop
- **PyPI:** `pip install ghostloop`
- **arXiv:** _[link to be added once preprint is up]_
## What you can try here
1. Switch profiles to see how the same Runtime + safety pipeline shape
covers totally different morphologies.
2. Send `move_to {"x": 5, "y": 0, "z": 0}` on the Franka profile to
watch the GeofenceGate reject it with a structured reason.
3. Send `takeoff {"altitude": 1}` on the Tello profile to see the HITL
gate escalate.
4. Read the trace event JSON for any call — that's the same shape the
library emits for replay, diff, query, energy ledger, and judge
scoring.
## Beyond the demo
The full library does much more than this Space exposes:
- 6 backends (Mock / MuJoCo / PyBullet / Gymnasium / ROS 2 / Randomized).
- 12 policy gates including STL temporal properties.
- Counterfactual trace replay, causal failure attribution, LLM-as-judge.
- VLA-on-MuJoCo benchmark harness vs OpenVLA / π0 / RT-2 / Octo numbers.
- Safe-RL training loop with Lagrangian multiplier + HER.
- Production fleet dashboard with auth + rate limit + alarms + Prometheus.
- MCP server for Claude Desktop / Cursor / Continue / Cline / Zed / Gemini CLI.
`pip install ghostloop` and clone the repo for the full kit.
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