Open-FDD: Arrow-native rule-based HVAC fault detection on a columnar execution engine.
Project description
Open-FDD
Open-source supervisory fault detection that runs locally on the edge — BACnet polling, BRICK equipment and point modeling, and AI-assisted commissioning, rule assignment, and diagnostics. Author Arrow-native Python rules in Rule Lab; trend plots and live operations from the Operator Bridge.
Get started
Docker (Operator Bridge) — published on GitHub Container Registry. Pull the three edge images (default tag latest):
| Image | Role |
|---|---|
ghcr.io/bbartling/openfdd-bridge |
API, dashboard, historian |
ghcr.io/bbartling/openfdd-commission |
BACnet discover, read, poll |
ghcr.io/bbartling/openfdd-mcp-rag |
Doc-search sidecar |
docker pull ghcr.io/bbartling/openfdd-bridge:latest
docker pull ghcr.io/bbartling/openfdd-commission:latest
docker pull ghcr.io/bbartling/openfdd-mcp-rag:latest
Edge bootstrap (compose, workspace/, auth): Run with Docker images.
Python (open-fdd) — PyPI package for Arrow-native rule linting and offline Rule Lab work:
pip install open-fdd
Full operator stack (BACnet polling, UI, assignments): use the Docker images above. Local clone, tests, and contributor layout: AGENTS.md and developer docs.
License
MIT — see LICENSE.
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