WALDO is a command-line tool for building auditable AI training datasets and models. It connects a Git-governed corpus index, content-addressed Parquet objects, and model artifacts with verifiable bills of materials (BOMs).
WALDO is under active development. It is being opened early so users and contributors can help shape the project through frequent, incremental releases. Expect interfaces and formats outside the documented compatibility contract to evolve.
- Inspect, verify, audit, ingest, update, and export indexed corpora.
- Read and publish canonical Parquet objects through local or S3 lookaside storage.
- Create corpus, training-run, model, and release provenance records.
- Forecast and train models through MLX, PyTorch, or single- and multi-host TorchTitan when the required runtime is installed.
- Export native WALDO, Hugging Face, MLX, GGUF, and Ollama packages.
WALDO does not prove that a license assertion is legally correct, that model output is safe, or that a generated disclosure alone establishes regulatory compliance. It records attributable facts and verifies artifact identity.
WALDO requires Go 1.25 or newer.
git clone https://github.com/openwaldo/waldo.git
cd waldo
go build -o ./waldo ./cmd/waldo
sudo install -m 0755 ./waldo /usr/local/bin/waldo
waldo --help
With no configured index, read-only index commands use a managed checkout at
~/.waldo/index:
waldo status
waldo index list
waldo index summary
waldo index verify --offline
Contributing data requires a separate writable index checkout:
git clone https://github.com/openwaldo/waldo-index.git
waldo config set index /path/to/waldo-index
waldo config set lookaside file:///tmp/waldo-lookaside
waldo index ingest --help
Use waldo <command> --help as the authoritative command reference.
Start with the documentation index. In particular:
Early feedback, testing, documentation improvements, and focused code contributions are welcome. See Contributing.
./testing/unit.sh
./testing/vet.sh
The full end-to-end suite is described in docs/TESTING.md.
WALDO is licensed under the Apache License 2.0. See NOTICE for attribution notices.