The engine runs where the automations are and the GPU is somewhere else,
usually behind a different network — so the worker connects out and the engine
answers over the socket it was given. Nothing has to expose Redis, and the
same connection works through the tunnel the hosted access will use.
What travels is the protocol the local pool already speaks, so a node cannot
tell which kind of worker it is on. A node declares device: gpu and
device_policy, the label is resolved per call (a worker attaching later needs
no rebuild), and a run whose labels nothing carries waits in the queue saying
what it waits for rather than failing — submit from the couch, the GPU box
picks it up when it is switched on.
Two things had to move with it. Compiling now happens on the machine that will
run the node: a node importing torch is correct on the GPU box and a missing
module on the engine, so checking it here failed nodes that were fine. And the
artifact endpoint accepts a worker's own credential, because storing a
checkpoint is exactly what that credential is for — and only that.
Verified against the real split: the training ran on this host (its checkpoint
names the machine and a numpy the engine does not have), streamed 40 metric
points back mid-run, and the evaluate node read the checkpoint on the engine.
Cancel kills the remote training; pulling the worker fails the run in six
seconds instead of waiting out its ten-minute timeout.
The worker script is handed to the interpreter by path, so app/flow was
sys.path[0] for every node: `import queue` got the engine's. It now drops
its own directory before anything else imports, and runs with the
deployment's credentials scrubbed out of its environment.
Also: reload builds off the event loop, the pool wakes what is blocked on
it when it stops, a refused metrics flush is kept for the next one rather
than dropped, and the cascade events are paired through failures.
mqtt, http, influx and delay carried the prototype's annotations and were
excluded wholesale. Annotating them leaves nothing to exclude: what the two
untyped dependencies need is an implicit-reexport allowance for
influxdb_client and the import-site ignore croniter already gets elsewhere.
InfluxDbNode.inject now takes the durable flag its supertype passes, and the
cron loop reads its stop event once instead of dereferencing a field that
stop_cron() may have cleared.
nodes.py had grown to 2k lines holding every integration behind a single
blanket mypy exemption. It is now a package split by the outside world
each node talks to, so the exemption shrinks to the four integration
modules; base and mlp are type-checked, which turned up a dozen missing
annotations.
The senders opened a fresh connection — and, in the MQTT case, a fresh
thread pool and event loop — for every single message. HTTP senders now
share one pooled client, and a publisher holds one broker connection for
its lifetime, fed from a bounded queue that drops the oldest value when
the broker cannot keep up.
An HTTP sender also no longer trips over a JSON reply that is not an
object: outputs are keyed by port, so a bare scalar is a valid reply with
nothing to publish.
The engine now speaks MCP at /mcp, with a built-in OAuth 2.1 authorization
server in front of it: an agent registers itself, sends a human to the browser
to approve it, and exchanges the resulting code for a token. PKCE is required,
codes are single-use and stored only as hashes, the browser is redirected to
the URI that was registered rather than the one asked for, and refresh tokens
rotate so that replaying a spent one revokes the whole line.
Twenty tools cover reading, building, publishing and running flows, and each
one calls the same REST endpoint the dashboard calls, in-process, carrying the
caller's own token. That keeps one description of what a flow is and what may
be done to it — validation, the draft/publish split, the version check — and
means an agent can do nothing a person could not do in the browser.
Agent tokens are RS256 with a keypair of their own rather than the secret that
signs browser sessions, so deleting the key withdraws every agent without
logging anyone out, and deps.decode_token grew the branch that trusting a
second issuer will need when the hosted login arrives.
Flows can now be taken off the engine and put back. Stopped state lives in a
runtime.json beside the flow, not in the flow document: the canvas autosaves
that document, so a stopped flow would otherwise start itself again on the
next edit. A stopped flow gets no subscriptions, schedules or webhooks, its
nodes are skipped by the scheduler, and running it answers 409. Pausing holds
a flow's nodes while its values keep arriving, so the canvas still shows what
is coming in.
Node code is user code and print is how it says things, so stdout is teed
through a contextvar sink active only during a node execution — one event per
execution, capped, so a chatty node cannot outrun the stream. A node that
fails sends its traceback the same way, trimmed to the author's own frames.
The dock gains a logs panel and a pause control; the dashboard replaces its
placeholder with what is running, stopped or failing; the edge inspector can
send the last message again.
Single-stepping is deferred and noted: the scheduler keeps no progress between
calls, so a step button would re-run the same node rather than advance.
The engine fell back to MemoryState because there was no Redis to talk
to, so every value was lost on restart. Adds a redis service with
append-only persistence, reachable only from the backend, and points
REDIS_HOST at it.
state.py and pipeline.py leave the strict-mypy exclusion. redis-py types
its calls as sync/async unions; the casts narrow that at the points of
use rather than switching to redis.asyncio, which would make a
deliberately synchronous backend asynchronous. nodes.py stays excluded.
The .env.example CORS entry belongs with the CI work that follows.
Makes the flow engine reachable from the API, which is what M3 needs before
any of it can reach the browser.
- app/flow is a package now; the prototype's watch-dir scripts and the
matplotlib/networkx visualiser are gone with their dependencies.
- Messages carry a serializable dtype instead of a live Python type, and a
port name, so the graph can speak qualified names while node functions keep
local arguments. Redis state is JSON, not pickle.
- Message names are namespaced per flow ("heating.temp"); a bare name resolves
to its own flow, a dotted one crosses flows.
- Several nodes may provide the same message: producers are a list, so fan-in
is a real edge instead of a silently dropped one.
- Flows are stored as flow.json plus node sources in a git repository, one
commit per save, with identical saves skipped so autosave stays quiet.
- Node failures are isolated and reported per node; validate() returns cycles
and unconnected inputs instead of raising deep in a run.
- Credentials live in an encrypted store and are referenced as {"$secret": …}.
- Engine events reach websocket clients through a bus, so values, node status
and execution show up live.
- exclude app/flow from ruff and mypy: it is not importable as a package and
nothing in the API reaches it, so 405 of the 412 findings were about code
scheduled for restructuring (see NOTEPAD.md)
- fix the 7 real findings outside it: col(...) around created_at for the
.desc() ordering, and a type: ignore that is no longer needed
- compose.local.yml resets the host ports compose.dev.yml publishes; the
integrated stack is served entirely through Traefik, and a port already
taken on the host used to fail the whole stack
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.
stroblme
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