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The site read as a design journal: rationale paragraphs, hedges
("deliberately", "on purpose", "genuinely"), meta-commentary about the docs
themselves, and one em-dash every ten lines carrying an aside.
Roughly twenty rationale blocks are gone or reduced to what a reader needs
in order to use the thing. Em-dashes go from 507 to 135, and what is left is
structural rather than prose: list and definition separators, table cells,
and four inside code blocks that quote what the CLI actually prints.
Also: api.example.com becomes api.fluksio.com (the emails stay, since
bootstrap.py really defaults to admin@example.com and RFC 2606 reserves it);
the mqtt table gains the two settings it had drifted behind on and inject's
wording matches the engine; llms.txt lists the two connector pages that were
in the nav but not in it; and the two device/device_policy notes now agree.
Builds clean under `zensical build --strict`.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015YrQnKV3bnQd4K342y8tKj
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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 with a small-house panel and a training pipeline on it.
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.