Every output is a target and every input besides prompt a reading. A
targets setting gives descriptions, values, ranges and per-target
guards, model takes a trained pack's artifact digest, min_confidence
defaults to the model's threshold. A command is applied whole or not at
all, and targets the model was not trained on read degraded. The home
path (area/kind ports, groups, brightness, temperature answers) is gone.
wren's model answers "turn off all lights" with one call, and at 0.98 a
living room light switched on. The node now applies such a command to every
wired target of the kind. Number words become digits ("in five minutes"
lost its delay), aliases put the house's words and known mishearings in the
model's, and sensors.temperature is answered from <area>_temperature or
outdoor. tts writes out units and clock times before speaking.
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.
stroblme
Melvin Strobl