README.md

---
title: Neuro Flyt Training
emoji: 🚁
colorFrom: blue
colorTo: indigo
sdk: docker
pinned: false
---

# Project Neuro-Flyt 3D

**Goal:** Build a verifiable 3D Drone Control verification demo using Liquid Neural Networks.

## Installation

1.  **Clone the repository** (if you haven't already).
2.  **Install dependencies:**
    ```bash
    pip install -r requirements.txt
    ```
    *Note: You may need to install `opensimplex` and `ncps` manually if they are not in `requirements.txt` yet.*
    ```bash
    pip install opensimplex ncps
    ```

## Usage

### Run the Demo
To launch the 3D visualization with the "Antigravity" hurricane effect:
```bash
./run_demo.sh
```

### Verify Physics
To verify that the wind field is generating non-zero forces:
```bash
python test_physics.py
```

## Project Structure
-   `env/drone_3d.py`: Custom PyFlyt environment with 3D Perlin noise wind field.
-   `models/liquid_ppo.py`: PPO agent with LTC (Liquid Time-Constant) feature extractor.
-   `demo_3d.py`: Main visualization script.