This page gives a quick path through the repository for contributors and power users.
| Path | Purpose |
|---|---|
README.md |
GitHub landing page |
docs/.vitepress/config.js |
Navigation and site structure for the /docs/ site |
web/ |
Static landing page assets for the published site root |
docs/ |
VitePress source for the versioned documentation site |
examples/ |
Notebooks and runnable examples |
foreblocks/ |
Main forecasting library |
foretools/ |
Companion tooling |
| Path | Purpose |
|---|---|
foreblocks/__init__.py |
Top-level public exports |
foreblocks/config.py |
Public configuration dataclasses (ModelConfig, TrainingConfig) |
foreblocks/models/ |
Model-level composition APIs (ForecastingModel, GraphForecastingModel) |
foreblocks/layers/ |
Reusable layer families, including graph convolutions and graph construction |
foreblocks/core/ |
Core forecasting internals and heads |
foreblocks/training/ |
Trainer and training support |
foreblocks/evaluation/ |
Evaluation and metrics |
foreblocks/data/ |
Dataset and dataloader helpers |
foreblocks/ts_handler/ |
Preprocessing and sequence construction |
foreblocks/tf/ |
Transformer stack and advanced attention |
foreblocks/darts/ |
Neural architecture search |
foreblocks/mltracker/ |
Experiment tracking |
foreblocks/hybrid_mamba/ |
Hybrid Mamba SSM blocks (HybridMambaBlock, HybridMamba2Block, SSD) |
foreblocks/mamba/ |
Original Mamba backbone with MoE, positional encoding, and eval tools |
foreblocks/kan/ |
Kolmogorov-Arnold Network backbone |
| Path | Purpose |
|---|---|
foretools/tsgen/ |
Synthetic time-series generation |
foretools/bohb/ |
BOHB, TPE configuration, pruning, and optimization plots |
foretools/foreminer/ |
Exploratory analysis and diagnostics |
foretools/fengineer/ |
Feature engineering utilities |
foretools/emd_like/ |
Decomposition tools |
foretools/tsaug/ |
AutoDA-Timeseries: automated data augmentation with adaptive policy |
| Task | Entry point |
|---|---|
| Training a baseline model | README.md, Getting Started |
| Understanding architecture composition | foreblocks/models/ |
| Working with graph forecasting | foreblocks/models/graph_forecasting.py, foreblocks/layers/graph/ |
| Configuring runs | foreblocks/config.py |
| Building dataloaders | foreblocks/data/dataset.py |
| Adding preprocessing logic | foreblocks/ts_handler/preprocessing.py |
| Exploring transformer internals | foreblocks/tf/transformer.py |
| Working on architecture search | foreblocks/darts/ |
| Using SSM / Mamba-style blocks | foreblocks/hybrid_mamba/layers.py |
| Generating synthetic data | foretools/tsgen/ |
| Running hyperparameter search | foretools/bohb/ |
| Augmenting training data adaptively | foretools/tsaug/ |