Node settings arrive as keyword arguments, not a params dict

A python node's settings are constants of its own function, so they are passed
the way its ports are: by name. The controller binds them to the compiled
function, the `params` field is gone from the worker and remote protocols, and
a setting sharing a port's name is reported as a node error rather than
shadowing it. The panel's scaffold follows suit and keeps the header in step
with both ports and settings.

The demo's `pace` moves from a flow input to a setting of the training node,
which is what it always was.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NUb8YpL2s3gmN9WTACTt4q

scripts/seed_demo_training.py

@@ -78,7 +78,7 @@ TRUE_SLOPE = 3.0
 TRUE_INTERCEPT = 2.0
 
 
-def process(seed, noise, samples, params):
+def process(seed, noise, samples):
     rng = random.Random(int(seed))
     rows = [
         [x, TRUE_SLOPE * x + TRUE_INTERCEPT + rng.gauss(0.0, float(noise))]
@@ -120,7 +120,7 @@ except ImportError:  # The engine's own venv has no numpy; a GPU box will.
     np = None
 
 
-def process(dataset, learning_rate, epochs, pace, params):
+def process(dataset, learning_rate, epochs, pace):
     with open(fluksio.load_artifact(dataset)) as handle:
         data = json.load(handle)
 
@@ -181,7 +181,7 @@ import json
 import fluksio
 
 
-def process(weights, dataset, params):
+def process(weights, dataset):
     with open(fluksio.load_artifact(weights)) as handle:
         fit = json.load(handle)
     with open(fluksio.load_artifact(dataset)) as handle:
@@ -235,11 +235,14 @@ NODES = [
         # Generous, and an *idle* timeout: a node that keeps publishing keeps
         # its deadline reset, so this is how long it may go quiet.
         "timeout": 300,
+        # A setting: a constant of this node's own code, reaching `process` as
+        # an argument like the ports beside it. Only so a human can watch the
+        # curve arrive — set it to 0 in the node panel for a sweep.
+        "params": {"pace": 0.15},
         "requires": [
             {"name": "dataset", "dtype": "artifact"},
             {"name": "learning_rate", "dtype": "float"},
             {"name": "epochs", "dtype": "int"},
-            {"name": "pace", "dtype": "float"},
         ],
         "provides": [
             # The curve. `stream` says this port publishes repeatedly while the
@@ -273,8 +276,6 @@ INPUTS = [
     {"spec": {"name": "samples", "dtype": "int"}, "initial": 200},
     {"spec": {"name": "learning_rate", "dtype": "float"}, "initial": 0.2},
     {"spec": {"name": "epochs", "dtype": "int"}, "initial": 40},
-    # Only so a human can watch the curve arrive; set it to 0 for a sweep.
-    {"spec": {"name": "pace", "dtype": "float"}, "initial": 0.15},
 ]
 
 #: What a run reports as its result. Everything else the flow computed stays
@@ -448,7 +449,8 @@ def main() -> int:
     print(
         f"\nOpen /view/{PANEL}, then start a run:\n"
         f'  POST {API}/api/v1/runs/flows/{FLOW} {{"params": {{}}}}\n'
-        "The curve fills in as it trains. For a sweep, set pace to 0."
+        "The curve fills in as it trains. For a sweep, set the training\n"
+        "node's 'pace' setting to 0."
     )
     return 0