# 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/`.