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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
54 lines
2.4 KiB
Markdown
54 lines
2.4 KiB
Markdown
# Fluksio
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Fluksio is a node-based automation engine. You describe what should happen as a
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graph of small pieces of logic, and it keeps that graph running: reacting to
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what arrives, or executing once from parameters to a result.
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It runs two kinds of graph:
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- A **live flow** produces values forever. A sensor publishes, a rule fires, a
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relay closes, a dashboard on the wall shows what happened. It never ends.
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- A **run** produces a value once. Parameters go in, stages execute, and it
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finishes, leaving metrics, artifacts and a record to compare against.
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Both use the same nodes, the same type checking, the same editor and the same
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API.
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## What you get
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- A **flow engine** that owns your graph, checks the types on every edge, and
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keeps running when a node fails.
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- A **canvas** that lays flows out for you and an editor for the Python inside
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each node, with the running values drawn on the wires while you work.
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- **Dashboards** built next to the logic that feeds them, including ones you
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can hang on a wall tablet that has no keyboard.
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- **Runs**: parameters, metrics, artifacts, sweeps and a queryable history, with
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no second server and no project bootstrap per execution.
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- **Distributed workers**: a node marked `device: gpu` runs on the machine that
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has one, which dials out to the engine rather than needing to be reachable.
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- An **HTTP API** covering everything the browser does, plus an MCP endpoint for
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agents.
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## Start here
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[Getting started](getting-started/index.md) has two paths: one installs a Python
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package, the other stands up a server. Everything after that is shared.
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To look before installing, the hosted demo at
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[fluksio.com](https://fluksio.com) runs a real instance: a small-house panel, a
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media screen, and a lab where a training pipeline runs and its runs are
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compared, four screens on one panel.
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## Where things are
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| If you want to… | Read |
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| Understand what a flow, a node and a message are | [Concepts](concepts/flows.md) |
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| Drive Fluksio from the browser | [The interface](interface/index.md) |
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| Drive it from Python, a shell or CI | [Code and the CLI](code/cli.md) |
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| Look up a node type or a payload type | [Reference](reference/node-types.md) |
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Fluksio is self-hosted by default. An instance runs offline, keeps its data
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on its own disk, and never contacts anything unless you
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[connect it to a portal](interface/portal.md) yourself.
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