carbon-ops 0.1.0

Carbon Ops Guardrails — audit-ready carbon accounting for AI workloads

Carbon Ops Guardrails

Audit-ready carbon accounting pipeline for AI workloads. This repository captures the system design described in the portfolio site and provides scaffolding for future implementation.

What you can expect

• Signed telemetry ledger – every emission estimate will be ed25519 signed and anchored via Merkle proofs.
• Energy-to-carbon estimation – ingestion jobs will convert runtime metrics into kWh and CO₂e using grid intensity APIs.
• Evidence exports – repeatable audit packages with inclusion proofs and configuration snapshots.

Repository layout

carbon-ops/
├── README.md
├── pyproject.toml
├── src/
│   └── carbon_ops/
│       ├── __init__.py
│       ├── config.py
│       ├── ledger.py
│       └── pipeline.py
└── tests/
    └── test_placeholder.py

Quick start

1. Create and activate a Python 3.11 virtual environment.
2. Install the package in editable mode: pip install -e ".[dev]".
3. Run the placeholder tests: pytest.

Next steps

• Implement telemetry ingestion adapters for Vertex AI job logs.
• Flesh out the ledger module with ed25519 signing and Merkle tree anchoring.
• Integrate grid intensity providers (e.g., WattTime) and unit tests around estimation logic.

Licensing

Choose an open-source license before publishing (MIT, Apache-2.0, or BUSL-1.1 are all viable depending on release strategy).