app/docs/code/cli.md

The fluksio command

pip install fluksio

Installs the engine and the fluksio command. Python 3.12 or newer, Linux or macOS.

The MQTT and InfluxDB connectors, outbound mail and error reporting are pip install 'fluksio[server]' — a deployment talking to devices wants them, and a laptop waiting on them to install does not. Everything else, the engine and every python node included, is in the plain install; a node type whose library is missing says which extra to add when one is actually built.

There is a second, smaller distribution — fluksio-worker — for a machine that should only run nodes for an engine elsewhere. It has none of the engine in it. See Remote workers.

The command is two things at once: serve, enroll and worker are an installation, while login, sync, run, runs, artifacts, sweep and status talk to one that may be anywhere.

Where an installation lives

.fluksio beside your code, found the way .git is: from the working directory, or any directory above it. Two repositories on one machine are therefore two engines, with their own flows, runs and token. fluksio serve makes one where there is none, and it ignores itself from within — a .gitignore of *, so a database and a credential cannot be committed by accident.

--global uses ~/.fluksio instead, shared by every directory. --data-dir (or FLUKSIO_HOME) names any directory outright and wins over both.

fluksio serve

Runs the engine.

fluksio serve

On the first start it creates an admin account and prints its password once. Nothing else has to be running: no database server, no message broker, no Docker.

At a terminal this opens a dashboard with the engine running under it; see below. --plain prints the log stream instead, which is also what happens with no terminal — in a container, under systemd, or in CI.

The default port moves out of the way when something already has it — 8001, 8002, and so on — and says which one it took; the URL written to client.json is the one it is actually on. A port you asked for is never moved off: --port 9000 on a taken 9000 fails, because something else is there and you named it.

What it will not do is start a second engine for the same installation. If the port is held by an engine already serving this directory, it says so and stops — one SQLite database wants one engine. Another installation's Fluksio on that port is named, and the move happens as usual.

Option	Default	What it does
--data-dir PATH	./.fluksio (or $FLUKSIO_HOME)	where this installation keeps everything
--host HOST	127.0.0.1	what to bind
--port PORT	8000, or the next free one	what to listen on
--plain	off at a terminal	the log stream rather than the dashboard
--log-level LEVEL	info	uvicorn's log level
--admin-email ADDR	admin@example.com	the account created on first run
--admin-password PW	generated	set it instead of having one generated
--enroll CODE	—	pair with a portal as part of coming up
--portal URL	—	the portal --enroll redeems at
--max-runs N	4	batch runs driven at once (FLOW_MAX_RUNS)
--max-cascades N	4	cascades in flight at once (FLOW_MAX_CASCADES)
--max-workers N	4	python worker processes (FLOW_MAX_WORKERS)
--gpus N	0	GPUs on this machine a node may be given (FLOW_GPUS)

Cards are declared rather than detected — asking a vendor's tooling would make one dependency two — so a machine with a GPU reports none until --gpus says otherwise, and a node asking for one is clamped to zero and runs alongside every other. --gpus 1 is what serialises them.

--enroll with --portal is the one-command setup: it pairs before the engine starts, so the connection is dialled as part of coming up rather than needing a restart. It is skipped if the installation is already enrolled.

!!! warning "One process"

`fluksio serve` holds the flow engine. A second one is a *second engine* —
duplicated subscriptions, duplicated cron ticks, two webhooks answering the
same path. Run one, and distribute work with
[workers](workers.md) instead.

!!! note "$HOME on a cluster"

A login node's home directory is often NFS, where SQLite's write-ahead log
does not work — the database would be locked or corrupt. `fluksio serve`
warns when it notices; point `--data-dir` at local disk.

What it prints

Created the admin account admin@example.com
  password: k3Qm-8vTpLdX
  Shown once. Change it from the dashboard.
Fluksio 0.1.0 — data in /home/you/.fluksio
  API      http://127.0.0.1:8000/api/v1
  No portal. Pair this installation with:
    fluksio enroll <code>

An enrolled installation says which portal it is on instead, and notes that the dashboard is served from there rather than here.

The dashboard

At a terminal, serve draws the health overview, the recent runs, and the engine's own log in a pane below — the output above is in there, not replaced by it.

Key	What it does
q	close the dashboard. The engine keeps running, and the pid is printed
s	stop the engine, or start it again
r	restart it
c	cancel the run the cursor is on
e	pair with a portal, without leaving the screen

The engine is a child process rather than a thread, which is what makes those possible — and what makes q a way out of the screen rather than a way to stop the engine. Running fluksio serve again reattaches to it.

An engine started elsewhere is adopted rather than duplicated, and can be stopped from here only when it is this installation's own: both the pidfile beside the data and a token this directory's key signed have to agree. Another installation's engine is named and left alone.

fluksio enroll

Pairs an existing installation with a portal.

fluksio enroll ABCD-1234

Option	What it does
--portal URL	a portal of your own, instead of https://hub.fluksio.com
--as EMAIL	the local account a portal session arrives as
--data-dir PATH	which installation, if not the one this directory is in

Get the code from the portal under Installations → Add installation. It is single-use and expires in fifteen minutes. --as matters when the installation has several superusers — without it, enrolment refuses rather than guessing.

Afterwards, fluksio serve dials the portal as it comes up, and keeps dialling: a portal that restarts, a wifi that changes, a laptop that suspends and wakes somewhere else all end the same connection, and the link is put back up without anybody noticing. A connection that stood up and then dropped is retried at once; one that never stood up waits a little longer each time, up to half a minute. See Accounts and the portal.

fluksio worker

Runs nodes for an engine elsewhere. Everything after worker belongs to the agent's own parser — it is the same program fluksio-worker installs, so the two are interchangeable:

fluksio worker --url wss://api.example.com/api/v1/workers/attach \
               --token "$FLUKSIO_WORKER_TOKEN" --labels gpu

See Remote workers.

Talking to an engine

The commands below are the client half: they run wherever you work, and address an engine over its API rather than being one — except under --local, which boots one inside the command instead.

fluksio login

fluksio login --url https://api.example.com

For an engine somewhere else. One you started yourself needs no login: fluksio serve writes the token as it comes up and says where it put it.

The token goes in this project's .fluksio/client.json, or with --global in ~/.fluksio/client.json. Every command below reads it from there — nearest first, walking up from the working directory — or from FLUKSIO_URL and FLUKSIO_TOKEN, or from its own --url and --token. A token an older version wrote to ~/.config/fluksio/client.json is still read.

fluksio sync

fluksio sync [PATH_OR_MODULE ...]        # default: the current directory

Imports what you name, collects the flows the decorators declared, and uploads each one with a generated import shim per node. A directory that is a package is walked; a dotted name is imported as it stands; nothing is loaded from a file path, because the shim has to import the same way.

A plain directory is walked all the way down, so one folder per study — fluksio sync dev over dev/s1_baseline/study.py — needs no naming. Hidden directories, __pycache__, node_modules and virtualenvs are left alone.

Each file is imported under the name its path spells beneath the directory being synced, so dev/s1/study.py and dev/s2/study.py are s1.study and s2.study and a study.py per study collides with nothing. No __init__.py is needed — the directories in between are namespace packages — which leaves a bare from study import ... in a test beside it working. A file at the top of what is synced keeps its plain name.

Flag	What it does
--dry-run	print the flow documents and shims, upload nothing
--no-publish	leave the upload as a draft
--force	overwrite a flow, or a node body, that was edited on the canvas

Every sync retires the engine's workers, including one that had nothing to upload — a worker holds your package in memory, so an edit to it is invisible until the process goes.

It also records, per node, which of your modules that node's function imports its way to, and what they hash to. That is what the stage cache keys on, so editing a helper a node calls into is reported as that node changing — train: updated (flow, fit) — and re-runs it, while editing something the node never reaches is left alone.

A sync that changed nothing says unchanged, which is the answer worth having. — published and — draft are said only when there was something to publish or a draft was genuinely left behind. An engine too old to store what a node's code reaches says so in a line naming both versions; until it is upgraded its cache is keyed on the whole repository, as it was before. See Getting started: data science.

fluksio run

fluksio run train --lr 0.05 --seed 7 [--wait]

Syncs the working directory and everything under it, then submits a run — so the command after an edit is this one and nothing else, from the repository root as readily as from the study's own folder. A study that will not import is a warning rather than a stopped run; the upload is already a no-op for a flow nothing changed in, so what the walk costs is importing the others. --sync dev/s1_baseline (repeatable) narrows it to what you name when that is not free, and --no-sync skips it entirely.

Flags that are not its own are the flow's inputs, typed by what the flow declares them as — so a name the flow has not got is refused by name, and --param lr=0.002 is told that one value is --lr 0.002 and several is a sweep. --wait blocks until the run finishes and exits non-zero if it failed. --follow waits as well, and prints the numbers the run reports as they arrive:

  train.loss[14] = 3.40295e-06

Ctrl-C while either is waiting cancels the run on the engine rather than only stopping the watching, and exits 130. --timeout SECONDS gives up waiting after that long and leaves the run going; it is nothing to do with a node's own timeout.

--seed N is the experiment's seed, and it does three things. It is recorded on the run, so what a result came from is answerable later. It goes into the digest that identifies a run's inputs, so two runs of one configuration with different seeds are different runs rather than a cache hit. And if the flow declares an input named seed, that is what fills it — so the number the run is labelled with is the number your code actually drew from, instead of merely looking like it. A flow that declares no such input still records it, and nothing reads it. Sweep over seeds with --param seed=1,2,3.

Any input takes what a previous run produced, named rather than typed out — a checkpoint, but equally a config object nobody wants to paste into a shell:

fluksio run evaluate --dataset @run:1758042000123-9f2ab41c.dataset
fluksio run evaluate --dataset sha256:6dd1f0…
fluksio run train --meta @run:1758042000123-9f2ab41c.dataset_meta

@run:<id>.<output> is whatever that run's output was, whole and with its own type; a bare digest is the content itself, resolved into a reference. Both spellings are reserved on every input, str included, so an input that has to carry one of them literally cannot. Passing the value as JSON still works and is what a script that already holds one does — the same thing flow.submit(dataset=run.result["dataset"]) does from Python.

Run a flow with no parameters at a terminal and it asks for them, one line per declared input, with the declared value in brackets:

lr (float) [0.05]: 0.01
epochs (int) [10]:
dataset (artifact): @run:1758042000123-9f2ab41c.dataset

Enter keeps what is in brackets, so pressing it through the lot runs the defaults. Nothing changes for a scripted run: passing any parameter, or piping the command, skips the questions, and --defaults skips them explicitly.

--no-sync runs what is already on the engine. Worth it in a tight loop where you know nothing changed, since syncing retires the workers and the next call pays its imports again. A directory that declares no flows syncs nothing and says nothing — a flow drawn on the canvas is run the same way.

--no-cache executes every node, including one an earlier run already answered. See Stage caching.

--local boots the engine inside this process instead of talking to a served one, so there is no fluksio serve terminal to keep open. It is the same installation either way — the same .fluksio, the same database, artifacts and run history — so a run made this way and a run made through a served engine cache against each other. It always waits, because the engine it starts lives exactly as long as the command. Starting one costs a few seconds of worker pool and module reconcile, against the ~15 ms of submitting to an engine that is already up: --local is for "I just want to run it", not for a loop you are iterating in.

fluksio status

fluksio status [--watch]

The home screen's top half in a terminal: whether the engine is healthy and what is wrong if not, whether it is paired with a portal and reaching it, then every flow with its state, its node count and whether it has unpublished changes, and the last few runs and failures under them.

A resources line names each machine the engine can run a node on and how much of it is in use, plus how many nodes are queued for one. It is absent on an engine that accounts for nothing.

The portal reads one of three ways. no portal means this installation was never enrolled. portal hub.fluksio.com means the link is up. portal unreachable names the error, and is the one worth acting on — the dashboard is served from the other end, so nobody can reach it while that is showing.

--watch keeps it on screen and refreshes every five seconds until Ctrl-C — the cadence the dashboard polls at, since nothing here moves faster. It needs a terminal; without one, run it without --watch and the output pipes cleanly.

--local reads the flows and history out of this directory with no engine served, the same way runs --local does. It cannot be watched: an in-process engine is the command itself, so nothing changes under it.

fluksio runs

fluksio runs [--flow train] [--limit 20]

The runs an engine has recorded, newest first: id, status, flow, duration, how long ago it was submitted, the commit of the repository it came from, and the inputs it was given. Statuses are coloured when a terminal is reading the output — ok green, error red, cached cyan.

Only the inputs that differ from what the flow declares are shown, and they are clamped to what is left of the terminal's width — a run that took the defaults lists none at all, and a flow taking a few kB of JSON does not push everything else off the line. Client.runs() and fluksio export runs are where the whole value is read. --local reads the same history from an in-process engine, without one having to be served.

fluksio flavors

fluksio flavors

The named sizes a node can ask for — @node(resources="gpu-small") — with the cores, memory and cards each stands for. Editing them is the Workers screen or POST /api/v1/flavors; this is the read.

fluksio sweep

fluksio sweep train --param lr=0.1,0.01 --param epochs=10,50 --wait

Every combination of the parameter lists, submitted as one group — four runs above, sharing a group_id and executing in parallel. Values are typed by the flow's inputs, the same as run's are, and --seed, --no-sync, --no-cache and --local mean what they do there. --wait blocks until all of them are finished and exits non-zero if any failed.

fluksio export

fluksio export metrics --flow train --list
fluksio export metrics --flow train --name train.train_loss --stride 10 -o curves.csv
fluksio export runs    --flow train --status ok > arms.csv

The two tables an analysis reads. export metrics is the long one — a row per run, metric and step — which is what a plotting library takes without reshaping; --name keeps the metrics it lists and --stride keeps every Nth point of each curve. export runs is the wide one: a row per run with its inputs as columns, its final numbers, its status, its duration and the commit and digest of the code it ran.

Every input the selected runs recorded becomes a column, so the schema does not move with the selection and a filter written against one export keeps working on the next; --params lr,seed narrows it to the axis a comparison is read along. --metrics narrows the final numbers the same way.

An input left out of a submit is recorded at the value the flow declares for it, so every row says what it was actually run with rather than leaving the cell blank.

A node usually returns a record rather than a scalar, so both sides take dotted paths into one: --metrics final_metrics.train_loss,test_metrics.known.perfect selects three fields rather than two blobs, and --params model.ansatz does the same for an input. The defaults reach the same depth — every number a result carries becomes a column wherever it sits, and a record's inputs are taken leaf by leaf rather than as one blob.

Metric names are flow-qualified — a node of train writing train_loss records train.train_loss — so --list prints the names the selected runs carry when the spelling is not obvious.

Both take --flow, --run ID (repeat it), --group, --status, --since, --until and --local, and both put the run id on every row: it is the join back to the run page and to what the run made.

--format is csv (the default), jsonl or parquet; output goes to stdout unless -o FILE names somewhere. Parquet keeps the types and needs pyarrow — pip install 'fluksio[parquet]' — and a file to write, since it is not a stream. In a notebook, Client.export_metrics() and Client.export_runs() answer the same rows as a list of dicts, which pandas.DataFrame takes directly.

fluksio artifacts

fluksio artifacts 1758042000123-9f2ab41c
fluksio artifacts 1758042000123-9f2ab41c weights -o model.npz

The files a run produced — what fluksio.save_artifact(...) wrote, and any artifact a node returned. Named alone it lists them: the message each left on, its size, its media type and the filename the node gave it. Name one and it is written here, under that filename unless -o says otherwise.

The message name is the one to pass, since it is what addresses the bytes; --local reads them from this directory without an engine served.

What lives in the data directory

.fluksio/               (or ~/.fluksio, with `--global`)
├── client.json         the token `serve` wrote, mode 600
├── .gitignore          `*` — a database and a credential, ignored from within
├── fluksio.db          SQLite: users, runs, metrics, observability, agents
├── flows/              a git repository — one directory per flow
│   ├── house/
│   │   ├── flow.json           the published structure
│   │   ├── nodes/*.py          the published node code
│   │   ├── flow.draft.json     unpublished edits, if any
│   │   └── nodes.draft/*.py
│   ├── _lib/           shared node sources
│   ├── _dashboards/    dashboards, drafts and all
│   └── requirements.txt        what the Modules screen installs
├── artifacts/          content-addressed bytes, two levels deep
├── user-venv/          the interpreter your node code runs on
├── secrets.enc         encrypted credentials, deliberately outside flows/
├── alerts.json         alert channels and rules
├── panels.json         wall-panel pairings
├── oauth-key.pem       signs agent tokens
├── cloud.json          the portal enrolment, if there is one
├── secret_key          signs sessions and derives the secrets key
└── env                 optional settings file

Two things follow from this layout and are worth internalising:

flows/ is a real git repository. git log is the history of every change anyone made to any flow. A run records the commit it ran at, so git show on that hash is literally the code that produced the number.

Backing up the data directory backs up the installation. Everything else is rebuildable. Copy it while the engine is stopped, or use SQLite's online backup for the database if it is not.

Settings

Settings come from the environment, or from an env file in the data directory. The ones you are most likely to touch:

Variable	Default	What it does
DATA_DIR	./.fluksio via the CLI; ~/.fluksio with --global	everything below it derives from this
DATABASE_URL	SQLite in the data dir	any SQLAlchemy URL
NODE_VENV	auto	which interpreter node code runs on: auto adopts the venv Fluksio was installed into, managed builds one of its own, or name an interpreter
REDIS_HOST	unset	flow state in Redis instead of memory; survives a restart
FRONTEND_HOST	—	the address used in mails, OAuth metadata and panel links
ENVIRONMENT	local	production closes the interactive API schema
MCP_ENABLED	false	opens the agent endpoint
SECRET_KEY	generated once	signs sessions, derives the secrets key

The full list is in Configuration.