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91ef2bbe9a |
Key a node on the code it reaches, not on the repository around it
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`sync` follows each node function's imports through the project's own modules — stopping at the standard library, at anything installed, and at Fluksio itself, whose checkout would otherwise be most of every digest — and records the file list with what it hashed to. The engine hashes those files again when the run is claimed, so the fingerprint is live rather than a snapshot, and falls back to what sync recorded when it cannot see them: a remote worker's runs used to share one empty digest, and therefore one key. Three things follow. Editing a helper a node calls into re-runs that node, as before. Editing something the node never reaches no longer re-runs anything — a notebook two directories away was invalidating every arm. And `Run.code_digest` is now the hash of its nodes' digests, so it is neither looser nor tighter than "the code behind these numbers", which is what makes it worth joining an exported table on. `sync` says so too: it compares the per-node digest against the stored one, so a helper edit prints `train: updated (flow, fit)` instead of `unchanged`. The digest is read when the document is built rather than when the flow is declared, so a second `sync()` in one process sees an edit between them. Also: `fluksio runs` shows only the inputs that differ from what the flow declares, fitted to the terminal, so a flow taking a few kB of json no longer wraps every line. Every existing cache entry misses once — the fingerprint changed shape. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01A9Hdrmf2cwNABCnE5x9UJa |
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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 |
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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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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>
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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 |
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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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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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a38e2745eb |
Add a Python SDK: flows declared in your own repository
A data scientist keeps their code where it is and decorates it: `@node` declares a function's ports beside the function, `Flow(name, nodes=[...])` says which of them make a flow, and `use(fn, wire=..., **settings)` rebinds one for a single flow. `fluksio sync` uploads the document plus a generated import shim per node, so the store still holds a complete, runnable, git-versioned definition while the code it imports stays theirs. `fluksio login|run|runs` and `flow.submit().wait()` are the client half, over the run endpoints that already existed. Runs record the user repository's commit beside the store's, so "what code produced this number" is answerable on the side that now holds the code. - `fluksio/sdk/`: ports, decorators, the flow builder and its checks, the shim generator, an HTTP client and sync. Standard library only at import, so `from fluksio import node` in a training script pulls in no engine. - `FlowDef.origin` marks a flow code-defined; `Run.origin_commit` carries the repository's commit; `POST /modules/refresh` retires the workers without an install, which every sync calls — a worker holds the imported package in memory, so an edit to it is invisible until the process goes. - The canvas shows a generated body read-only and names the repository to edit instead; a body edited there stops the next sync rather than being discarded. - The worker's reporter carries inert `Port`, `node`, `use` and `Flow`, since the shim imports a module whose first line declares them. - `examples/myresearch` is the worked example, `make sync-example` uploads it. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_012ue1tkFWB1bcGy3aWhCKpU |