The workflow this serves: make a venv, install what you work with, then `pip
install fluksio` into the same one. Building a second environment beside it
was exactly wrong — the packages the nodes need are already here, and the
Modules screen was asking for them a second time.
`NODE_VENV=auto` (the default) adopts that venv. It declines in the three
cases where adopting would be wrong: `managed` says otherwise, a managed venv
already exists and may hold packages somebody installed on purpose, or the
engine is not running from a venv at all. The images set `managed`, since the
venv in them holds the app and nothing of anybody else's.
An adopted venv is never written to. `uv pip sync` makes a venv hold exactly
the manifest, so pointed at somebody's own environment it uninstalls their
work and the engine with it — `sync()` refuses outright and `reconcile()`
returns before it can be called at startup, which is where that would have
happened first. The Modules screen lists what is installed and drops its
editor; `pip` is how that environment changes.
`fluksio serve` now names the interpreter node code runs on, which is the
thing a data scientist most needs to know at that moment. `fluksio-worker`
already defaulted `--python` to its own interpreter, so a GPU box works the
same way — that was only ever undocumented.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012ue1tkFWB1bcGy3aWhCKpU
A cluster or GPU host installs `pip install fluksio-worker` and gets the
agent and the runner, not psycopg, numpy and the MCP SDK. The engine
depends on it as a workspace member, so the file it launches node code
with is the same file a remote worker runs — which is what keeps a node
unable to tell the difference. Copying the two files by hand still works.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
A wheel whose top-level module is `app` collides with anything else in a
user's venv, so the package that is about to be published takes the name
it is published under. Only the Python package moves; the repo, the
Docker WORKDIR and the compose project keep theirs.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
The API image ran four uvicorn workers, and each one built a full flow
controller — four sets of MQTT subscriptions, cron ticks and webhooks.
Runs one worker now; scaling out is the worker split, not more processes.
Adds a loop-lag watchdog and a deep /utils/health/ that fails when the
event loop is wedged or Redis is unreachable, the two failure modes a
process-alive check never sees. Autoheal restarts on that signal, behind
a compose profile because it mounts the Docker socket.
The private user-seeding routes now need an explicit opt-in rather than
just ENVIRONMENT=local, so a deployment that kept the default never
exposes them.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_011LF61rxW1FG5YCD2J9YqjY
The submodule collapse was only half applied: .gitmodules was deleted but
backend/ and frontend/ were still recorded as gitlinks, so none of their
files were tracked. Replace the gitlinks with the real trees.
Also untrack .env (it carried placeholder secrets) in favour of a tracked
.env.example, drop the committed __pycache__, and narrow the blanket *.png
ignore that would have swallowed design assets.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
stroblmeandClaude Fable 5