wren node: untrained targets left out of the prompt, a read beside a held-back set goes on whole

backend/fluksio/flow/nodes/wren.py

@@ -445,11 +445,14 @@ class WrenNode(Node):
         threshold = 1.0
         if self.pack is not None:
             wren = _wren()
+            # A target the model never learnt is left out: shown, it is a line
+            # unlike any in training, which shifts the answers on the others.
             targets = [
                 wren.Target(
                     **t, value=_unset(t) if current.get(p) is None else current[p]
                 )
                 for p, t in self.targets.items()
+                if p not in self.untrained
             ]
             # One BLAS thread answers in about half the time for a model
             # this small. Scoped to the call, so numpy elsewhere in the
@@ -470,6 +473,9 @@ class WrenNode(Node):
             and (call.value is not None or current.get(call.target) is not None)
             for call in calls
         )
+        # A reading answered beside a set that is not written would drop the
+        # set unsaid, so the whole command goes on instead.
+        held = not self.cfg.apply and any(call.value is not None for call in calls)
         specs = {spec.port: spec for spec in [*self.input_ports, *self.output_ports]}
         writes: dict[str, Any] = {}
         actions: list[dict[str, Any]] = []
@@ -477,7 +483,7 @@ class WrenNode(Node):
         answers: list[str] = []
         for call in calls:
             spec, unit = specs[call.target], self.targets[call.target]["unit"]
-            applied = sure if call.value is None else sure and self.cfg.apply
+            applied = sure and (not held if call.value is None else self.cfg.apply)
             if call.value is None:
                 value = current.get(call.target)
                 if applied:

backend/tests/flow/test_wren.py

@@ -295,6 +295,8 @@ def test_a_target_the_model_was_not_trained_on_is_never_applied(fake_wren):
 
     fake_wren.answer = [fake_wren.Call("canopy", "DOWN")]
     out = node.execute({"house.command": "close the awning"})
+    # The model is not shown the targets it never learnt.
+    assert [t.name for t in fake_wren.targets[0]] == ["living_room_heating"]
     assert out is not None
     assert [a["applied"] for a in out["house.actions"]] == [False]
     assert out["house.unhandled"] == "close the awning"
@@ -325,6 +327,24 @@ def test_a_read_is_answered_from_the_target_value(fake_wren):
     assert out["house.unhandled"] == command
 
 
+def test_a_read_beside_a_set_not_written_goes_on_whole(fake_wren):
+    node = _node(
+        fake_wren, ("kitchen_light", DType.BOOL), inputs=[OUTDOOR], saying=True
+    )
+    fake_wren.answer = [
+        fake_wren.Call("outdoor_temperature"),
+        fake_wren.Call("kitchen_light", True),
+    ]
+    command = "how warm is it outside and turn on the kitchen light"
+
+    out = node.execute({"house.command": command, "house.outdoor": 6.2})
+
+    assert out is not None
+    assert [a["applied"] for a in out["house.actions"]] == [False, False]
+    assert out["house.unhandled"] == command
+    assert "house.reply" not in out or out["house.reply"] == CANT
+
+
 def test_a_delayed_call_is_held_by_the_work_queue(fake_wren, monkeypatch):
     node = _node(fake_wren, ("kitchen_light", DType.BOOL), saying=True, apply=True)
     deferred: list[tuple[dict[str, Any], float]] = []