stroblmeandClaude Fable 5.1
3397739c14
A python node's ports and settings arrive as keyword arguments, so a declared name its `process` does not take was a TypeError on every call — and a node that loads fine and fails every time it runs is the quiet kind of broken: the hosted demo did it 720 times an hour for two days and the health badge read ok throughout. `_build_node` now reads a written body with `ast` and refuses the mismatch at load, so the node is an error on the canvas and an issue on publish. Skipped for `**kwargs`, a decorated or absent `process`, and the template a new node opens with. The SDK's generated shim always takes `**settings`, so synced flows are untouched. `/observability/summary` names a node that has failed in the last fifteen minutes and reads degraded while it does, which is what would have made the badge amber. `nodes.failing` carries the count. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01SkgNtaR6JspnHBFFP6crZj
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Fluksio
Fluksio is a node-based automation engine. You describe what should happen as a graph of small pieces of logic, and it keeps that graph running: reacting to what arrives, or executing once from parameters to a result.
It runs two kinds of graph:
- A live flow produces values forever. A sensor publishes, a rule fires, a relay closes, a dashboard on the wall shows what happened. It never ends.
- A run produces a value once. Parameters go in, stages execute, and it finishes, leaving metrics, artifacts and a record to compare against.
Both use the same nodes, the same type checking, the same editor and the same API.
What you get
- A flow engine that owns your graph, checks the types on every edge, and keeps running when a node fails.
- A canvas that lays flows out for you and an editor for the Python inside each node, with the running values drawn on the wires while you work.
- Dashboards built next to the logic that feeds them, including ones you can hang on a wall tablet that has no keyboard.
- Runs: parameters, metrics, artifacts, sweeps and a queryable history, with no second server and no project bootstrap per execution.
- Distributed workers: a node marked
device: gpuruns on the machine that has one, which dials out to the engine rather than needing to be reachable. - An HTTP API covering everything the browser does, plus an MCP endpoint for agents.
Start here
Getting started has two paths: one installs a Python package, the other stands up a server. Everything after that is shared.
To look before installing, the hosted demo at fluksio.com runs a real instance: a small-house panel, a media screen, and a lab where a training pipeline runs and its runs are compared, four screens on one panel.
Where things are
| If you want to… | Read |
|---|---|
| Understand what a flow, a node and a message are | Concepts |
| Drive Fluksio from the browser | The interface |
| Drive it from Python, a shell or CI | Code and the CLI |
| Look up a node type or a payload type | Reference |
Fluksio is self-hosted by default. An instance runs offline, keeps its data on its own disk, and never contacts anything unless you connect it to a portal yourself.