Stage caching for batch runs, and an engine that lives in the command

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>

backend/fluksio/main.py

@@ -157,6 +157,7 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
         controller=controller,
         queue=_work_queue("run"),
         state_factory=_run_state,
+        artifacts=artifacts,
     )
     app.state.run_service = run_service
     watchdog = LoopWatchdog(event_bus)