# RIA Hub Technical Demo

This repository demonstrates a full ML pipeline via Gitea Actions:

- **Recordings**  
  A collection of raw `.npy` radio recordings stored via Git LFS.

- **Workflows**  
  A CI pipeline that automatically:
  1. Builds a labeled dataset from raw recordings  
  2. Trains a model on that dataset  
  3. Optimizes the model and packages an inference application  

- **Scripts**  
  - `scripts/build_dataset.sh`  
    Reads through `recordings/`, applies preprocessing, and outputs training `.npz` or `.csv` files into `data/`.  
  - `scripts/train_model.sh`  
    Consumes `data/`, trains a PyTorch model, and writes checkpoints to `checkpoints/`.  
  - `scripts/build_app.sh`  
    Takes the best checkpoint and builds a small inference CLI or server in `dist/`.


 