stroblmeandClaude Opus 5
d471614e6a
The rate the media dtypes could carry was one frame every second or two: each
was a file on the data volume, an event on the socket, and a request back for
the bytes. This closes both halves of that, and they are one feature.
`save_artifact(..., volatile=True)` writes to a `VolatileStore` — the same
content-addressed store, in `/dev/shm`, bounded by size with the oldest falling
out (`ARTIFACT_VOLATILE_BYTES`, 48 MB under the container's raised `shm_size`).
Nothing sweeps it: a frame nobody kept is not worth walking the store to find.
`ArtifactStore.path` falls through to it, which is what lets a volatile frame be
an ordinary reference everywhere else — the dtype check, a panel's digest scope,
`load_artifact` in a node, and the widget's own fetch all work on one unchanged.
`adopt` copies one into the store when a run records it, so "returned media is
kept, emitted media is not" stays true.
The bytes then go down the flows websocket as a length-prefixed binary frame,
sent just ahead of the `message_value` naming them, so a tile has the frame when
it hears the value moved. Nothing is pushed unasked: a client names the messages
it is drawing (`{"type":"media","names":[…]}`), a panel's list is intersected
with the scope it already had, and only the newest frame per name in a batch is
sent — a client that fell behind is not handed frames it would draw over. The
tunnel relays text only, so a screen reached through a portal falls back to
fetching, which is why the rate table now has two rows.
Around the edges: the remote worker's fetch cache is bounded at last
(`FLUKSIO_ARTIFACT_CACHE_BYTES`), since content addressing means nothing in it
ever expires and a media stream fills it with chunks nothing asks for twice; a
port carrying an image draws the frame in the node panel rather than only
saying `image/png · frame.png · 1.79kB`; and an edge chip says that much instead
of a line of hash. The media screenshot stops waiting for `networkidle` — a
camera is a socket that never goes quiet, which is the point of it.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YC4u66vjzW54fnHu5Juhh9
Fluksio
Fluksio is a node-based automation software that brings trust and reliability to your flow. It just works and looks good. Get started by running
pip install fluksio
fluksio serve
and you're ready to go.
For data science
You can turn your existing data science project into a flow by decorating your functions with @node ...
# myresearch/train.py
import fluksio
from fluksio import Port, node
@node(
requires=["dataset", Port("lr", "float")],
provides=[Port("loss", "float", stream=True), Port("weights", "artifact")],
device="gpu", device_policy="prefer",
)
def fit(dataset, lr, epochs=25):
for epoch in range(epochs):
loss = step(...)
yield {"loss": loss} # published as it happens, kept as a series
return {"weights": fluksio.save_artifact("weights.pt")}
... and passing them to a Flow:
# myresearch/pipeline.py
from fluksio import Flow, Port
from myresearch.data import prepare
from myresearch.evaluate import evaluate
from myresearch.train import fit
train = Flow("train", nodes=[prepare, fit, evaluate],
inputs=[Port("lr", "float", initial=0.01)], outputs=["score"])
Fluksio will automatically infer the order of nodes based on the inputs and outputs you defined. When everything is set, you can launch your first run as follows:
fluksio run train --lr 0.05 --wait
Checkout our documentation for more infos.
Some other features
- Flows: typed messages between nodes, wired by name, edited on a canvas or declared in code. Every change is a commit in a git repository you own.
- Runs: an experiment and a CI-style job are the same entity. Parameters, seed, result, per-node timings, artifacts and the commit it ran at.
- Dashboards: charts and controls bound to the same messages the flows carry, with no separate metrics pipeline.
- Remote workers:
pip install fluksio-workeron the GPU box; it dials out over one websocket, so nothing there has to be reachable.
Fluksio can also be used for facility automation. Visit us on fluksio.com or go straight to our documentation.
License
Copyright (C) 2026 Melvin Strobl - GNU Affero General Public License v3.0 or later. Running a modified version over a network obliges you to offer its users the corresponding source (AGPL §13).