Commit Graph
89 Commits
Author SHA1 Message Date
stroblmeandClaude Opus 5 6bc71ddaf3 Record flags in history and draw them as steps
A bool was excluded from the history as "not a measurement", so a true/false
port had no curve in the node panel and none on an edge — only the word. It is
recorded as 0/1 now and drawn as steps, since a bezier through two states
slopes through readings that never happened. The axis is pinned to 0..1, so a
flag that was never on sits at the floor rather than mid-box.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-27 15:54:06 +02:00
stroblmeandClaude Opus 5 37a7df9d24 Let a sweep run more than four at a time, and name the run a failure was in
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Concurrent runs sat at 4 whatever FLOW_MAX_CASCADES said: that setting bounds
cascades, and the run drivers read a hardcoded MAX_PARALLEL nobody could reach.
FLOW_MAX_RUNS is the knob they read now, --max-runs/--max-cascades/--max-workers
are the same three as flags on serve, and the engine says which numbers it
started with — which is the only way to tell that a settings file was read.

Events keep the run they happened in. The payload always carried it and the
persist path dropped it, so reading one run's failures meant filtering the
engine-wide list; a batch run's id reaches those events now too, since a run
has no journaled item to name itself by.

Also: a provisioner's 0 means "no deadline" rather than "cancel on the next
reconcile", and a command that reaches no engine says how to start one.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015sbYeYaVgYQqm1sbx7wPdL
2026-08-27 14:17:51 +02:00
stroblmeandClaude Opus 5 c3675688c8 Wait for a deadline instead of polling for one
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The timer thread promoted due work on a fixed one-second tick, so every
delayed item was 0-1000ms late whatever the load — measured on the house
at 705ms mean on a rollershutter stop, which is 2-4% of a 26-second
travel and accumulates in the position the motor node believes it is at.
It now sleeps to the soonest deadline and is woken when a nearer one is
scheduled, which measures 0.9ms end to end through Redis.

A promoted timer also went to the back of the queue. It goes into a due
lane of its own that `claim` reads first, so work that has waited out a
deadline is not held up by work that is merely queued.

Beside it, in the same code: seeding a message now bumps its version, so
a re-put flow's synchronous nodes no longer wait forever on a value that
is sitting in state; the consumer group drops the consumers of engines
that are gone (138 had accumulated on this installation); and the cast
that closes the long-standing `xclaim` mypy error.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-27 11:51:58 +02:00
stroblmeandClaude Opus 5 40f8ad378d Ask a cluster for a machine when nothing here will do
Slurm is not a machine that attaches and stays; it is a queue somebody else
owns. So nothing here submits a node to it. It submits a job whose payload is an
ordinary worker dialling back in, and everything downstream — the protocol, the
artifacts, cancellation, the books — already worked and did not have to learn
what Slurm is.

The alternative, which Covalent takes, is to stage a serialized call and a
runner onto the login node, poll squeue and copy the result back: a second way
of running a node beside the one that exists. The cost of not doing that is one
assumption, that a compute node can open a connection outward. Where that is
false, _payload is the single method a staged variant would replace.

Clusters are configured in provisioners.json beside the alerts, since this is
infrastructure an operator writes rather than anything a flow says. The script
is generated with the system ssh and no new dependency, and prerun owns the
environment — deliberately no pip install, because what is on a cluster is
somebody's decision.

One outstanding request per profile, cancelled if it never attaches and on the
way out. Nothing autoscales.

The run gate needed the same hook: a run held before it starts never reaches the
placer's own wait, so it would have queued forever on a machine nothing had
asked for.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A6HeySA27EkGANZN95QySW
2026-08-27 09:09:44 +02:00
stroblmeandClaude Opus 5 a82f88cf0a Name the sizes a node can ask for
Raw cpus and gpus are a property of the machines an installation has, so a node
written against a cluster quietly stops meaning anything when the cluster is
replaced. A node says "gpu-small" instead, and what that is stored here —
editable, and read again every time the node is built, so changing the flavor
changes what the next run gets.

Memory joins the schema properly (`ram`, in MB, accepting "2G"), along with
`duration_s` for how long a node is expected to take. That one is recorded and
shown and nothing else yet: a statement for whoever is planning around the node,
not a limit — the limit is still `timeout`.

A flavor and a number for the same thing is refused, compared by value so an
editor writing the whole object back with its defaults still round-trips. A name
nothing stores is refused at the save, which covers the canvas and `fluksio
sync` at once, and deleting one a node still asks for says which node.

Four sizes are seeded on an installation that has none, and never re-seeded:
re-adding one somebody deliberately removed is an argument nobody wins.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A6HeySA27EkGANZN95QySW
2026-08-27 08:59:10 +02:00
stroblmeandClaude Opus 5 6ff56533f5 Schedule a node across every machine, not just this one
The engine answered "where does this node run" twice, in two ways that could
not see each other: a device sent it to a worker carrying that label, and
resources were counted against the engine's own cores. Declaring both meant the
second answer won and nothing was counted at all — which the data-science
getting-started page and the worked example both do.

One question now, in flow/placement.py: of every machine attached, which could
grant what this node asked for, and which of those has it free. The books move
onto each machine — one accountant per worker, built from the inventory it
reported — and the waiting moves above them, where one condition variable can
be woken by a release anywhere or by a worker attaching. Locks go one way:
placer, then a machine's books, never back.

So a node asking for a card now finds the box that has one, rather than being
clamped down to none and run here. When nothing can grant the ask at all it is
still cut down and run — a flow written on a cluster has to work on a laptop —
but the ceiling is one real machine now, since taking the largest of each
dimension separately can describe a machine nobody has.

Two things fixed on the way. A device on a connector node held every batch run
of its flow forever, waiting for a worker that could never run an entry point.
And `prefer` falling back to the engine skipped the books, so the fallback held
nothing.

The bench flow's node has taken a `params` argument that with_settings has not
forwarded for some time, so the benchmark could not run at all: 62 ms median
submit-to-result with this, against the 61 ms on record.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A6HeySA27EkGANZN95QySW
2026-08-27 08:49:36 +02:00
stroblmeandClaude Opus 5 1a9753fa9d Let a worker say what machine it is
A worker reported its labels and nothing about the machine behind them, so the
engine could route a node to a GPU box but not tell whether that box had a GPU
free. Inventory — cores, GPUs, memory — now arrives with the hello frame, and
the run frame carries back what the engine allocated for that call.

Which is protocol 2 on both ends. GPUs are never probed: asking a vendor tool
would make the one dependency two, so a GPU is what the batch job says it was
given or what --gpus says. A worker that reports nothing still attaches and is
scheduled by its label alone.

Two things a job scheduler needs: --max-idle stops a worker started for one job
rather than letting it hold its allocation to the walltime, and a refusal is now
fatal instead of a reconnect loop that reads as a hang in a job's log.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A6HeySA27EkGANZN95QySW
2026-08-27 08:29:35 +02:00
stroblmeandClaude Opus 5 0ffcabfdb9 Media dtypes: image, audio and video as narrowed artifact references
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A port may now declare `image`, `audio` or `video`. Each is the artifact
reference the engine already had, narrowed by the `media_type` on it, so a
speech recogniser declares what it eats rather than taking any bytes at all and
finding out. Bytes still never travel as a message and nothing on the wire
stops being JSON: a camera publishes one reference per frame, a microphone one
per chunk, and a reference may carry a `meta` dict nothing here interprets.

Streaming media is therefore an ordinary streaming port — with one change to
what that means. An emission used to journal an item with no payload, so
downstream read whatever was current when the item was claimed; a consumer
slower than its producer saw only the newest chunk and the ones between were
lost. That is right for a training curve and wrong for a second of speech, so
an emission now journals a `kind="emission"` item carrying its values, and the
executor hands them to the nodes reading that message instead of writing them
to state again. The value in state stays the latest, which is what everything
else reads, and the wave is filtered by what actually changed rather than
walking everything reachable. No queue serialization change — the existing
`outputs` field carries it.

Continuous media makes the store's missing GC a real problem, so this closes
it: `sweep_artifacts` runs hourly, keeps every digest a `run_artifact` row
records or a live message holds, spares anything written in the last hour, and
stands aside entirely while a run is in flight, since a node may store a
checkpoint long before it returns the reference to it. That also collects the
orphans a deleted flow has always left behind. `ARTIFACT_GC_INTERVAL_S=0` turns
it off.

Around the edges: `GET /artifacts/{digest}` serves the media type the caller
passes and answers ranged requests, so a browser plays a clip rather than
downloading it; `PUT` spools to disk instead of holding the whole body in
memory, as does `save_artifact` given a path; a Media widget draws whatever its
message points at, and a wall panel may fetch the bytes its own tiles are
showing and nothing else; and a connector gets `save_artifact`, for a device
whose readings are bytes.

What this cannot do is live video: a frame every second or two is a glance, and
the honest answer above that is the camera's own stream, which the widget takes
as a URL and the browser plays from source.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 23:44:55 +02:00
stroblmeandClaude Opus 5 8be7e424ba Cover the sink reaching a node the controller built
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The pieces were tested one at a time, so removing the one line in
`_build_node` that wraps a worker-backed function with its sink broke nothing
visible — while losing every generator node's last yield and returning None
in its place.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 23:01:15 +02:00
stroblmeandClaude Opus 5 4f3eaf950c Report a published node that has no code of its own
The store answers the new-node template when nothing was ever written for a
node, so such a node ran — returning {} on every call, reporting active and
ok, and saying nothing anywhere. Unreachable through `fluksio sync`, which
writes every body before it publishes; the editor end was open.

A run of a flow holding one is now refused, and the flow carries a
missing_source issue so it is visible before anybody runs it. A draft is
exempt: a node being written legitimately has no published body yet.

The generated client is regenerated for the new issue code, which also
catches up the drift left by earlier backend work (resources, code_digest,
idempotency_key).

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 22:55:11 +02:00
stroblmeandClaude Opus 5 69fc0ceeb5 Format the generator test's sink helper
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 22:53:41 +02:00
stroblmeandClaude Opus 5 001ec7b282 Key the stage cache by the node's input names, not the flow's
A cache key held qualified input names, so the same node reading the same
values through two flows keyed differently and only a node with no inputs
could ever hit across one. The fingerprint beside the key already says what
the node is, and it has been flow-agnostic since it moved ahead of
assign_flow — the names were the last thing tying an entry to one flow.

Inputs now reduce by the node's own name for them; a name belonging to
another flow keeps its prefix, since reading it is part of what the
execution is. Every stored entry misses once and is re-run.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 22:41:35 +02:00
stroblmeandClaude Opus 5 647644ebbd Check a generator's yield at the yield that produced it
The worker held each yield one behind, because the last one is the node's
result when the generator returns nothing of its own. Only the engine knows
what ports a node declared, so the check happened when the *next* yield
arrived — a pass late, which for a training loop is however long one epoch
takes.

The worker now sends every yield as it happens and returns whatever its
generator returned; EmitSink holds the last one back and decides at the end
of the call what it was. Old "emit" frames are still handled, so a remote
agent that has not been restarted keeps working.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 22:39:22 +02:00
stroblmeandClaude Opus 5 608d30d884 Let a node say how much of the machine it takes
Five concurrent training nodes, each sizing its thread pool to every core,
left the engine's own event loop unscheduled: the API stopped answering
within 10 s and every client died. The same shape on a GPU deadlocked a run
for 21 minutes at 0% utilisation with nothing failing and nothing to read --
it just sat in `running`.

@node(resources={"cpus": 2}) is the declaration. The engine holds that much
for the length of the execution, so more of them than the machine has room
for wait their turn rather than oversubscribing it, and a `gpus` node holds
its card exclusively. FLOW_CPUS defaults to every core but two, and those two
are what keeps the engine answering.

Because a thread cap is read when the process imports the library, a warm
worker cannot be told a different one -- so an environment gets a pool of its
own and nodes deriving the same one share it, rather than paying a cold start
per call on exactly the nodes whose imports are slowest. XLA_FLAGS is never
derived: it is a composed, version-dependent string, so it travels in
resources.env where it is visible.

A node that declares nothing is not accounted for and behaves as it always
did -- it just gets FLOW_CPUS/FLOW_MAX_WORKERS as a thread cap, which is the
half of this that fixes the reported incident without anybody declaring
anything. An operator who set OMP_NUM_THREADS themselves still wins.

Resources are claimed strictly before a worker slot, so the two blocking
waits cannot deadlock. A node queued for them publishes node_queued and shows
on GET /workers/resources, because waiting and hanging looked identical.

Accounted, not enforced: no cgroups, no rlimits. Scheduling across machines,
flavours and enforcement are the next steps.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 21:36:59 +02:00
stroblmeandClaude Opus 5 4a38c6ed31 Name the code a run ran, and let an interrupted sync finish
Three faults with one root: the stored body of a code-defined node is an
import shim, and nothing that mattered was ever read from the code itself.

- The run stamp could not identify what ran. The shim imports whatever is on
  disk when the worker starts, and an uncommitted tree stamps <commit>-dirty
  for every run it ever produces. Run.code_digest hashes the repository's .py
  files, memoized on their stat state, and it is read again when the run is
  actually claimed -- so a sweep queued for hours records the code each of its
  runs executed, not the code that was there when it was submitted.
- The stage cache adopted code that was too new. The fingerprint hashed the
  shim, which is invariant under any edit to the imported function or anything
  it calls into, so a re-run was served from cache and answered without the
  outputs the edit added. It now carries the repo digest and the node's
  declared ports. Every fingerprint changes once, which invalidates the
  existing cache; a canvas flow has no repository and keys as before.
- An interrupted sync looked like a hand-edited canvas. The engine answers a
  new-node template for a node with no stored body, and the template carries
  no marker, so the drift check read "somebody edited this" and demanded
  --force -- for the one state that re-running the sync is the fix for.
  NodeSource.missing states the fact, and sync skips those and reuses the
  bodies it read instead of asking for each one twice.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-26 21:27:10 +02:00
stroblmeandClaude Opus 5 180da3d640 Stop paying five Redis round trips and a global lock per message
The engine was I/O-bound on its own state backend. `RedisState.lock()` is one
key — `pipeline:_lock` — for the whole process, taken five times a message at
two round trips each, and every cascade and every node read queued behind it.
Inside it, reading a node's inputs was three round trips per input (an EXISTS
for `in`, then EXISTS and GET for the value), writing was two updates that a
single transaction already gives, and the version counters went one INCR at a
time.

Replaced with the atomic command that was always available: `get_present` is
one MGET and tells a missing key from one holding null, so the lock it used to
be read under bought nothing; value and timestamp land in one `update`, which
is a MULTI/EXEC; `increment_multi` pipelines the counters. `values()` — what
every websocket snapshot calls — is two reads whatever the message count
instead of two per message.

Beside that: every webhook did its blocking XADD on the asyncio event loop
(MQTT already used `to_thread`); the per-execution `NodeOutcome` was built and
validated even with no run watching; `_minute` built a tz-aware datetime per
event on the loop thread to key a dict, and now keys on an int; `move_due`
promoted delayed items one round trip each, every second; `FLOW_MAX_CASCADES`
makes the in-flight ceiling a setting rather than a constant.

`orjson` replaces stdlib json where a message pays for it — state, the
journal, the engine side of the worker pipe. `fluksio-worker` stays
dependency-free, and the run-cache digest stays on stdlib so no stored key is
invalidated. A non-finite number now stores as `null` rather than the bare
`NaN` that was never JSON.

Measured with `scripts/bench_engine.py` against a real Redis, 200 messages:
a five-node chain went from 43.9 to 103.1 msg/s with p50 latency 2110ms →
782ms and p95 3913ms → 1439ms; one source into twenty consumers went from 5.4
to 33.7 msg/s. In memory, twenty consumers went from 187 to 448 msg/s.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BpfSinyCBfjuieikyfMPbf
2026-08-26 10:12:25 +02:00
stroblmeandClaude Opus 5 a9136c7811 A rate limit now thins the work, not only the messages
The limit was applied in `apply_outputs`, which the executor reaches after the
item is off the queue — so a subscriber told to publish every 15s still cost a
queue entry, a `cascade_started`, a run record and a walk of everything
reachable from it per inbound message. Seven relay nodes behind one inverter
ran 192 times a minute to publish six.

Two halves, matching the two shapes it takes:

`trigger()` now keeps a value whose every port is inside its window and
journals nothing at all. The window split came out of `_throttled` as a
read-only `_window_split`, so the question is asked the same way in both
places and the exact split is still made once, at claim time.

A cascade carries the names it actually published, and the wave runs only the
nodes something in that set feeds. A node whose triggering inputs were all
held back is completed without running, which frees its own consumers to be
judged the same way — the case where a node re-published 619 messages a minute
off inputs that changed six times. Redeliveries and emissions carry no such
set and still walk everything, since one has a half-finished wave to finish
and the other is the value already being in state.

Skipping a node can make one ready that the scheduling pass has already walked
past, so `submit_ready` runs to a fixpoint. That also closes the same latent
hole on the replay path, where a done-marker skip could strand a join with no
future outstanding to come back for it.

Measured with the new `scripts/bench_engine.py`, 500 messages through the
house's shape: a limited source went from 500 cascades / 3500 node runs /
5009 events to 1 / 7 / 19, publishing the same 8 values; an unlimited source
into limited relays took the node reading them from 500 runs to 1.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BpfSinyCBfjuieikyfMPbf
2026-08-26 09:55:56 +02:00
stroblmeandClaude Opus 5 5726c80948 Say how much work is waiting, not just how much is running
`RedisWorkQueue.stats` read XPENDING, which counts entries delivered to a
consumer and not yet acknowledged — work in progress. Entries sitting in the
stream undelivered were counted nowhere, so an engine hours behind reported
itself idle: on the house, `pending: 4` while the group's lag was 1554.

The group's own `lag` is the missing number. `backlog` now carries it on both
queues (`len(_items)` in memory), leads the health tile, and a sustained one
publishes `engine_degraded` from the timer thread — named with the flow most
of the waiting work belongs to, sampled from the undelivered tail, since that
is the actionable half. It is a summary problem rather than a /utils/health
503: a backlog should not restart the container.

Also drops the keyspace `scan_iter` `stats()` did per poll to count parked
items — it walked every state and idempotency key twice per ten seconds — for
a set the park/unpark path maintains.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BpfSinyCBfjuieikyfMPbf
2026-08-26 09:43:23 +02:00
stroblmeandClaude Opus 5 3af5342a2b Advisory issues read as advice rather than failure
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`ADVISORY_ISSUES` moves next to `ValidationIssue` in pipeline.py, and the
model derives an `advisory` flag from its own code, so the distinction the
engine already made ships to the client instead of being re-guessed there.

The dock keeps its summary in `--destructive` only when a real fault is
among the issues and paints an advisory row `--muted-foreground`; the
canvas leaves advisories off a node's dot and border entirely, since node
status has three colours and no warning tier.

biome checks the generated `openapi.json`, which nothing formats since the
SDK script dropped its format pass — ignore it like the other generated
files.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_013Gf7WaExcJ9bs3kfJXB3nK
2026-08-25 21:46:40 +02:00
stroblmeandClaude Opus 5 a3a234756c A batch flow's input is a run parameter, not a missing value
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Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UytviPMJbXzD8P84nLvXcq
2026-08-25 18:51:54 +02:00
stroblmeandClaude Opus 5 df22475f54 Claim only what the cascade pool can run
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UytviPMJbXzD8P84nLvXcq
2026-08-25 18:33:28 +02:00
stroblmeandClaude Opus 5 3c15964364 A cached node keeps its curve, and any input can name a run's output
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A cache hit still replays no emissions — those values were the story of an
execution that is not happening — but the run they were recorded in is now
written on the row (`run_node.cached_from`), and the metrics endpoints read the
series back from there. So a reused run answers `run.metrics("train.loss")`
with the same points the run that trained did, rather than looking like a run
that produced no numbers at all. Pointed at rather than copied: a sweep of 500
reusing one frozen node would otherwise duplicate its curve 500 times.

That needed the cross-flow restore fixed first. The cache key has no flow in
it while the stored outputs are named for the flow that produced them, so
`quick.prepare` getting a hit from `train` wrote `train.dataset` into `quick`'s
state and the next node was called without its argument. One rule now covers
both halves: `requalify` reads a name owned by one flow as the same name in
another, applied to the restored outputs, to the node id behind the pointer,
and to the series names on the way out. Reuse across flows is kept.

Also: `@run:<id>.<output>` and a bare `sha256:` digest resolve on every input,
not only artifacts. Chaining a run's json config into the next one from a shell
meant pasting the whole object inline, and the CLI could not even send the
spelling — `_coerce` died in `json.loads` before the engine saw it. Both
spellings are reserved on every input now, `str` included, and `_from_run`
returns whatever the run's result holds rather than only a reference.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Dp9L6gakMVro1K2C5zdtBE
2026-08-25 15:12:28 +02:00
stroblme 7ff29ca939 Make a dashboard its widgets: drop the pages and sections nobody drew 2026-08-25 12:30:22 +02:00
stroblme 77754936c6 Pin a chart to the last few runs of a flow 2026-08-25 11:52:34 +02:00
stroblme d2951a325e Add a runs screen: a table, a run in full, and curves side by side 2026-08-25 11:44:13 +02:00
stroblmeandClaude Opus 5 4941c2787c Add fluksio status, and ask for a run's parameters at a terminal
Two halves of the same gap: the CLI could start work but not show you any.

`fluksio status` draws the home screen's top half in a terminal — health and
what is wrong with it, every flow with its state and node count, and the
recent runs and failures under them. `--watch` keeps it there. Rich does the
drawing; it was already installed under fastapi's own CLI, and is named now
because a command depends on it.

`fluksio run` with no parameters at a terminal asks for them, one line per
declared input with its declared value in brackets — so Enter through the lot
is what running the defaults looks like, and an artifact input takes the
`@run:` spelling the engine now resolves. A scripted run is untouched: passing
any parameter, or piping the command, skips the questions, as does --defaults.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019V5bsYGNxcgPs4xXmTPx69
2026-08-25 07:42:09 +02:00
stroblmeandClaude Opus 5 93374a310e Refuse what a node cannot publish, and stop timing out work that is fine
Four things the python SDK turned up, each fixed where every client sees it.

A key no port declares is now an error rather than a silent drop, on the
return, the yield and the emit alike — the contract the docs already stated.
The SDK reads literal yields at sync time, so a typo fails before anything
runs, and an emission of one fails the call rather than being logged where
nobody looks.

NaN and infinity are refused at the port. JSON cannot spell either, so one
that travelled came back as a 500, a socket frame that stopped the canvas, or
a metric batch the database dropped whole.

An artifact input takes `@run:<id>.<output>` or a bare digest, resolved on the
engine — so the CLI, the run dialog and a python caller mean the same thing,
and a sweep can pass one at all.

Node timeouts are off by default. The clock measured silence, which a training
node is full of, and remote workers had already stopped enforcing it — their
heartbeat reset it. Now a heartbeat proves the agent rather than the node,
ninety seconds of nothing fails the call either way, and the engine touches
work it is still running so a long node is not redelivered at sixty seconds.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_019V5bsYGNxcgPs4xXmTPx69
2026-08-25 07:30:14 +02:00
stroblmeandClaude Opus 5 400d7d9c5c Stage caching for batch runs, and an engine that lives in the command
Docs / docs (push) Successful in 19s
Playwright Tests / test-playwright (1, 2) (push) Failing after 1m5s
Playwright Tests / test-playwright (2, 2) (push) Failing after 20s
pre-commit / pre-commit (push) Failing after 2m33s
Test Backend / test-backend (push) Successful in 2m7s
Compose Smoke Test / test-compose (push) Failing after 20s
Playwright Tests / merge-reports (push) Failing after 1m3s
Publish / publish (push) Failing after 12s
A code node in a batch run is now fingerprinted by its source, its raw
settings and the values it reads — an artifact input counting as its digest,
which is what the content addressing was always for. A run that finds the key
restores what the earlier one returned and skips the node, recorded as
`cached`. The run history is the cache: `run_node.outputs` beside the
`cache_key` the schema already had, no second store. On for code nodes, never
for the built-in and connector types that have side effects; off per node with
`@node(cache=False)` and per run with `--no-cache`.

Emissions are not replayed on a hit, so a cached training node returns its
result without redrawing its curve. Recorded in NOTEPAD.md with the two other
deliberate limits.

`fluksio run --local` boots the real app in the command's own process and
drives it through its ASGI interface behind the ordinary client, so a run no
longer needs a `serve` terminal beside it — same data directory, same history,
and the cache carries between the two. It always waits, because the engine it
starts lives exactly as long as the command.

Also: `fluksio sweep --param lr=0.1,0.01` for the product of the lists,
`run --follow` for a run's numbers as they arrive, Ctrl-C cancelling a waited
run rather than abandoning it, coloured statuses on a terminal, and `name`
made optional on the metrics endpoint so a follower can ask for every series.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-24 20:31:31 +02:00
stroblmeandClaude Fable 5 fea57064f9 Run node code on the venv Fluksio was installed into
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
2026-08-24 10:35:13 +02:00
stroblme 0b5ce4fcbb Rework the dashboard into two looks over one behaviour
A dashboard is a wall panel somebody hangs in their own hallway, so it
now wears what they choose: a look, and a palette of their own colours.

Two complete component sets live under `Dashboard/ui/` — `glass`
(translucent panes over a slowly moving ground) and `material` (Material
3 tonal cards) — behind one prop contract. Every control's state,
keyboard and `aria-` live in `ui/core` and are shared, so the two sets
are the same dashboard drawn twice rather than two products: a set only
decides what a control looks like while doing it.

Four settings join the channel, each drivable by a flow like any other:
`look`, `palette`, `background` and `touch`. A palette is an ordered list
of hex colours — background, surface, primary, accent, text, then more
chart colours — pasted from a coolors.co link or typed, written onto the
canvas as the token variables everything already reads. Trailing roles
are derived, so three colours are a whole dashboard, and derived text is
held to AA rather than trusted (`theme.check.ts` measures it). A palette
also decides light or dark, since its first colour is the ground.

Widgets are measured against their own tile with container queries rather
than against the viewport, animate through `motion`, and can be drawn
without their title. The three reworks:

- a bar draws a row per reading, up to eight, each in the dashboard's own
  data colours and each able to carry its own scale — replacing readings
  nested in one fill, which could only ever share one colour and stop at
  three. Documents written the old way are read as rows.
- a chart's range picker moved to a column down its right-hand edge, which
  gives the plot back a whole row of a short tile.
- the colour wheel became a disc: hue is the angle and saturation the
  distance from the middle, so a colour is one gesture rather than three,
  with brightness on a slider beside it.

`index.css` and `lib/motion.ts` are untouched — the dashboard overrides
token *values* on its canvas, never the blocks the two repos share.
2026-08-23 21:52:14 +02:00
stroblmeandClaude Opus 5 95be9bc092 Pin that a per-flow publish deploys the source it just published
The worst thing moving publish off the whole-pipeline rebuild could do
is quietly keep running the old code, and nothing was watching for it.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01StpRc2C6au1WJ1EUU7fsfu
2026-08-23 19:09:02 +02:00
stroblmeandClaude Opus 5 56396732a4 Stop and start a flow without rebuilding anything
A stopped flow's nodes are built like any other flow's — being stopped
means having no subscriptions, schedules or webhooks, not being absent —
so a toggle only ever needed the lifecycle call and the gate that goes
with it. It was doing a whole-pipeline rebuild instead, which on a
populated installation is every node in every flow reconnecting.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01StpRc2C6au1WJ1EUU7fsfu
2026-08-23 18:35:28 +02:00
stroblmeandClaude Opus 5 a4a9f2adff Give the controller a per-flow rebuild, not yet called by anything
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01StpRc2C6au1WJ1EUU7fsfu
2026-08-23 17:51:18 +02:00
stroblmeandClaude Opus 5 3bb23fbd3e Let the supervisor stop one flow's tasks and clear its quarantine
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01StpRc2C6au1WJ1EUU7fsfu
2026-08-23 17:43:15 +02:00
stroblmeandClaude Opus 5 294b72d989 Let a pipeline swap one flow's nodes instead of being rebuilt
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01StpRc2C6au1WJ1EUU7fsfu
2026-08-23 17:41:14 +02:00
stroblmeandClaude Opus 5 084194f77b Warm a worker before the node's clock starts, and refuse to delete a live flow
A node's timeout now covers its body only: the pool loads the source into the
worker it picked, off the node's budget, so imports that outlast the timeout no
longer make a node impossible to run. Draft checks compile without caching, so
saving does not evict what a busy node is serving calls from. Requests carry an
id the worker echoes and the pool checks, a reply is encoded once, and the
remote-exception cache is bounded.

DELETE /flows/{name} answers 409 while the flow has a running or queued run,
which is what was letting run_node rows outlive their run.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01StpRc2C6au1WJ1EUU7fsfu
2026-08-23 17:11:55 +02:00
stroblmeandClaude Opus 5 c81d6cb21a Bound the pipeline teardown so a stuck node cannot wedge the controller
A node's stop() and a supervised task's cancellation are both waited on
inside the rebuild lock, and neither had a deadline: an MQTT client whose
broker never acknowledges the disconnect leaves aiomqtt's __aexit__
waiting forever, so reload() never returned and every start, stop or
publish behind it hung until the container was restarted.

Each node now gets five seconds to close and is abandoned after that, and
cancel_all reports what is still running rather than waiting on it — it
also no longer swallows a cancellation aimed at the caller, which used to
make the lock holder unkillable. A rebuild asked for by a request gives up
on the lock after fifteen seconds with RebuildBusy, answered as a 503.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01StpRc2C6au1WJ1EUU7fsfu
2026-08-23 16:36:48 +02:00
stroblmeandClaude Opus 5 148d50f2bd Grow a node with its ports, stop it flickering, draw what it reaches out to
- A node's height follows the ports on its busiest side. It is a function of
  the document, so `layoutGraph` reserves exactly what is drawn and nothing
  measured is fed back into the layout.
- The three status controls now sit in slots that are there whether the
  control is or not. A node running many times a second mounted and unmounted
  the stop button on every execution, resizing the card each time.
- A port bound to another flow's message is drawn as a label, naming the node
  at the far end and its type. Only the opposite direction was answered
  before. The scan behind both is now cached on the store's commit counter
  rather than reading every flow per request.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016ZeGnqVsf5VHQqvz4HdUhN
2026-08-23 06:35:28 +02:00
stroblme 4d36da27e1 Merge branch 'main' of git.stroblme.de:Fluksio/app 2026-08-22 14:18:23 +02:00
stroblmeandClaude Opus 5 ba707c8051 nodes: what porting the house needed from the vocabulary
Four small things, each with a device behind it.

An MQTT filter now routes what it subscribed to. `+` and `#` reached the
broker and were then looked up in an exact-match dict, so every message a
wildcard subscription received was dropped in silence.

`json_key` lifts a value out of the object a device wraps it in — Victron
publishes `{"value": 47}` on every path, which was otherwise a Python node
per port.

The trigger node learned `passthrough` and `wait_port`, because how long to
wait can be a value rather than a constant: a rollershutter takes 26 seconds
up and 28 down. A wait of zero sends nothing afterwards and still cancels
what the last message scheduled, which is how a stop is commanded once
instead of forever.

The HTTP sender takes fixed `query` parameters, so an API key is a secret
reference rather than a message on the canvas, and `send_inputs` off for a
request whose inputs are only a trigger.

Also: `delay` accepts fractional seconds, and `TZ` reaches the container, so
a cron expression means local time. Left unset it is UTC, as before.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-22 14:16:08 +02:00
stroblmeandClaude Opus 5 d958d7cde6 Add the dashboard settings channel, wired for theme and lock
A dashboard could only ever receive as a set of tiles. This adds the dashboard
itself as a receiver: `settings` maps a name to a value plus an optional
binding. Unbound, the setting is simply its value — a wall panel that is always
dark costs no flow. Bound, a flow drives it live and the value is the fallback.

Two settings are wired: `theme` (system/light/dark) and `locked` (read-only).
There is no schedule field on purpose — a node publishing to the bound message
on a cron is what a schedule is here, which is the point of a channel.

- `messages_for()` now walks a dashboard's bound settings as well as its
  widgets' bindings. Without this a paired screen is refused its own theme
  message, on the one surface the setting exists for; it bounds the socket too.
- `locked` is gated in `usePublish`, so every control inherits it, and each
  control also draws itself disabled — a dead button reads as broken otherwise.
  The panel surface says Read-only in the corner.
- The theme is a class on the dashboard's own surface, never the root: inside
  the app shell it must not flip the chrome. `.light` gains the tokens `.dark`
  already had (mirrored in the index repo) so both directions work on a subtree.
- Settings bindings are type-checked from the document alone, the rule widget
  bindings follow, and mirrored on the server.
- A bound setting is drawn on the flow canvas as a dashboard-level endpoint.
- The demo's house flow now publishes `home.panel_theme`, which the demo
  dashboard's theme binds to: the panel goes dark after sunset, at no tile cost.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_018tULRZJUkZsw7rMJ3h4xvu
2026-08-22 13:17:56 +02:00
stroblme 8224d12c8c Add a colour-wheel widget to the dashboard
A custom hue ring — a conic gradient, not a canvas — with saturation and
brightness sliders beside or under it depending on the tile's shape, sized
for a wall panel and reachable from a keyboard. It publishes [h, s, v] by
default, which is what the reference installation's DMX encoders read, and
`format` switches that to [r, g, b] or "#rrggbb".

`usePublish` moves to its own module so a widget in a file of its own can
reach it without importing `widgets.tsx` back.
2026-08-22 12:50:59 +02:00
stroblmeandClaude Opus 5 961a8f881d Keep the engine's state in SQLite, not Postgres
One process owns this database — the image has run a single uvicorn
worker for that reason since the four-engines bug — so a file beside the
flows is the honest shape for it, and it is what lets `fluksio serve`
need no infrastructure at all. Live values, node execution and the work
queue never came here anyway; what does is a rollup a minute at a time,
a row per cascade and the run history, and WAL keeps the readers going
while that one writer works.

DATA_DIR is now the one setting that moves everything an installation
keeps; the rest derive from it and the images still spell theirs out.
The schema is prepared in-process at startup, so the prestart service is
gone, and the ten Postgres-only revisions collapse into one portable
baseline.

Three things only worked because psycopg was casting for us: a token's
subject arriving as a string where the column is a UUID, `greatest`, and
`date_bin`. The timestamps needed a column type of their own — SQLite
stores no offset, and a naive datetime read back either raises against an
aware `now` or serialises as local time.

Postgres stays in the stack only for Umami, behind the analytics profile.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-21 22:19:45 +02:00
stroblmeandClaude Opus 5 2c369ac75f Split the worker into a distribution of its own
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>
2026-08-21 21:54:10 +02:00
stroblmeandClaude Opus 5 60d7ec81c0 Rename the import package app to fluksio
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>
2026-08-21 21:48:05 +02:00
stroblmeandClaude Opus 5 c912388ed6 Make lint report instead of rewriting, and stop verify guessing the domain
`make lint-frontend` was `biome check --write --unsafe ./` — a lint target that
reformatted the whole tree rather than checking it, which is why every parallel
change in this repo has had to work around it. `lint` checks now and a new
`format` writes. The pre-commit hook and CI needed no edit at all: both call
`bun run lint`, so they became checks the moment its meaning changed.

`app/Makefile` assigned DOMAIN from .env, and a plain assignment beats an
inherited environment variable and is not exported — so `cd app && make
dev-local` served localhost while the same checkout's tests targeted the
configured domain. `export DOMAIN ?=` gives the lattice that was intended:
command line, then environment, then .env.

Alongside: the backend's htmlcov bind mount created that directory as root, so
`make test-backend` died on the coverage step after every test had passed,
which reads like a test failure and is not one. The alerts screen's copy of
ALERTING_EVENTS is now checked by a test rather than trusted. And the shard
comment claimed two spec files where there are nine.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Uq8mtNb97A7praJLyeEYgs
2026-08-21 14:34:14 +02:00
stroblmeandClaude Opus 5 b0efb4b0f1 Let a node's failure outlive the run that followed it
A node's error cleared the moment it ran again, so a failure that genuinely
fired an alert could leave no trace on the canvas by the time anyone looked.
The engine records it now — on the node's status, so it survives a reload and
every client agrees — and reading the traceback is what clears it. The seam is
the event bus, which is where every failing path already meets: a queued live
run, an explicit run, a preview, and a single triggered node all publish
`node_error`, while the controller's own observer would have seen only one of
them.

That was half the confusion. The other half: clicking a failed neuron on Home
often landed on a flow where everything looked fine. Nodes merge into one
neuron by instance key — every InfluxDB node pointing at the same bucket is one
neuron — and the click went to whichever flow contributed a member first, not
the one that failed. It now goes to the failing member and selects it, and the
canvas marks a failing node rather than leaving it to the dot alone.

The inject node emitted one payload to every port it declared, whatever their
types, so an inject on a bool port carrying the text "true" raised at publish
time. Each port gets its own field now, typed and parsed by that port's dtype,
and remembers what it last sent. A port that is renamed carries its value with
it; one that is removed takes its value with it. An inject written before this
keeps emitting exactly what it did.

The derived-cron chip also appeared on the delay node, where `interval` is a
rate limit and a schedule derived from it means nothing.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Uq8mtNb97A7praJLyeEYgs
2026-08-21 14:33:41 +02:00
stroblmeandClaude Opus 5 c3ea884d72 Hold a new dashboard back until someone publishes it
A dashboard went live the moment it was created — an empty document straight to
the panels — while a new flow starts as a draft. It now works the way flows do:
published means `dashboard.json` exists, so every dashboard on every running
installation is already published and nothing needs migrating. Only the ones
created from here on start as drafts.

Mirroring FlowStore turned up a latent 500: discarding the draft of a dashboard
that had never been published unlinked its only file, and the read that followed
raised out of a 200 handler. It answers 400 now, the way a flow does.

Publishing all of them was 2N requests, because a publish has to name the
version it expects and the summaries did not carry one. They do now — and so do
the flow summaries, which had the same defect nobody had written down.

A panel had no way to hear about any of this. A publish, or a change to which
dashboards a panel carries, now puts one event on the bus and the screen
refetches what changed: no reload, so a wall display never blanks or asks for
its credential again. The subtle half is that a socket's message allowlist was
computed once at handshake — a reassigned panel would have fetched its new
document and then shown tiles that never updated.

The panels dialog logged non-superusers out. Every write in it needs a
superuser, not only the checkboxes the report mentioned, so the dialog is
read-only for everyone else. The logout itself was `main.tsx` treating 403 as a
dead session, against the contract deps.py spells out: only a 401 ends a
session, and a 403 now says so rather than silently signing someone out.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Uq8mtNb97A7praJLyeEYgs
2026-08-21 14:32:57 +02:00
stroblmeandClaude Opus 5 a8065ad91c Give the work queue its own Redis root, and pin what the suite runs as
The queue shared the `pipeline:` prefix with flow state, so `RedisState.clear()`
could DEL the queue stream and `keys()` enumerated queue entries — only callers
filtering `__`-prefixed names kept it safe. It moves to `queue:` without a
migration: whatever is in flight at the upgrade is dropped once, documented in
DEPLOY.md rather than papered over.

Alongside it: `pool_pre_ping`, so a connection idle across a Postgres restart
costs a round trip instead of a failed request; the test suite pins
ENVIRONMENT=local and DOMAIN=localhost itself rather than inheriting a
deployment's .env; and `depth` leaves the queue stats, where it reported the
capped journal length as if it were a backlog.

ALERTS_FILE and PANELS_FILE now point at /data. They defaulted to a path on no
volume, so alert routing and every wall-panel pairing were living in the
container's writable layer and vanishing on each rebuild. Carrying the existing
files across is a manual step; DEPLOY.md has it.

development.md was still the upstream template — compose.override.yml,
localhost.tiangolo.com, `docker compose watch` as the dev flow — and said
nothing about the Playwright suite. Rewritten against what the Makefiles
actually do. deployment.md was template text too, duplicating the root
DEPLOY.md, and is gone.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Uq8mtNb97A7praJLyeEYgs
2026-08-21 10:10:57 +02:00
stroblme 906203da1e Let a connector write, and publish strings bare
Two things stopped the engine commanding this house. ConnectorNode hardwired
its node function to a no-op, so an input message reaching a connector was
discarded and Art-Net's packet builder was unreachable; write() now carries
the input ports, which is additive so the contract version holds. And the MQTT
publisher JSON-encoded every payload, so "ON" went on the wire quoted and the
devices on a shared broker, which speak bare values, ignored it.

seed_house_control.py is the rig: a flow that drives the washing machine plug,
a dimmer and a colour fixture over MQTT, carries the same two as DMX on an
Art-Net node with transmit still off, and a dashboard to drive it by hand.
2026-08-20 21:57:27 +02:00