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  stroblmeandClaude Opus 5
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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>
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stroblmeandClaude Opus 5
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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> |
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stroblmeandClaude Opus 5
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266acd1661 |
Document the cascade guarantee and the cascade ceiling
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A node runs when something it reads was published, not merely when something upstream of it ran — worth saying now that it is true, since it is what a reader relies on when a rate-limited port goes quiet. Plus `FLOW_MAX_CASCADES` in the engine's configuration table. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01BpfSinyCBfjuieikyfMPbf |
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stroblmeandClaude Opus 5
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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 |
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stroblme
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4350916bd8 |
Scroll the runs table, pick a range, and choose what a comparison plots against
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stroblmeandClaude Opus 5
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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
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stroblme
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03e12b7647 |
Document the runs screen, the run context and the generated dashboard
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stroblmeandClaude Opus 5
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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 |
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stroblmeandClaude Opus 5
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400d7d9c5c |
Stage caching for batch runs, and an engine that lives in the command
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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> |
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stroblmeandClaude Opus 5
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11e032386b |
Publish the documentation site: docs.fluksio.com
A zensical site under docs/, served by a new `docs` compose service behind Traefik, built with --strict in CI. Same pattern the sibling n3xd workspace uses. Getting started splits the way the landing page does — one path is `pip install fluksio` and a training script, the other is a Docker stack and an afternoon in the browser — because the two audiences will not spend the same amount of time. Everything after that is shared: the concepts, the web interface (app and portal), the CLI and the API, and a reference for node types, payload types and configuration. The three flow guides move here from the docs submodule rather than being copied, so there is one version of them. Styling mirrors DESIGN-GUIDELINES.md: the app's token palette remapped onto Material's variables in both schemes, Inter, the 16px panel radius, and the one terracotta accent spent on the facility lane of the audience split. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01M7Xv3cJEW5c8AXxn2hoojV |