Major framework modernization and quality-of-life improvements:
- Centralized Configuration: Replaced scattered, hardcoded hyperparameters and paths across all training/inference scripts with a single, documented `config.yaml` and `config_loader.py`.
- OS-Aware Audio Pipeline: Introduced `utils/audio_utils.py` to handle cross-platform audio loading. Automatically routes Windows to a robust `ffmpeg` subprocess to bypass unstable Python audio bindings, while keeping `torchaudio` for Linux.
- Dependency Management: Migrated from `requirements.txt` to `uv` with a fully configured `pyproject.toml`. Explicitly targets Python 3.12 and pulls PyTorch `cu128` wheels by default.
- Dataset Fixes: Restored the missing `dataset_e2e.py` required for proper STFT/GAN decoder training and updated all dataloaders to utilize the new AudioPipeline.
- Documentation & Housekeeping: Overhauled `README.md` with updated workflows, Windows instructions, and `uv` setup. Added a comprehensive `.gitignore` for virtual environments, model weights, and cache files.
Nighthawk