feat(value-sources): optional normalization for magnitude sources

Add an opt-out `normalize` flag to the four magnitude value sources
(ha_entity, http, system_metrics, game_event). get_value() stays in
[0,1] for every source (the normalized scalar-bus invariant), so all
existing consumers — brightness sinks, gradient_map, template `name`
bindings, and color-strip bindable floats — are unaffected.

- normalize=False is a clamp-passthrough: skip the min/max rescale and
  clamp the raw reading into [0,1] (for sources already reporting a
  0..1 fraction). The un-normalized magnitude stays available via
  get_raw_value() / template raw[name] / automations.
- Add get_raw_value() + a raw channel to GameEventValueStream (it had
  none). game_event's flag is model/stream-level only (no CRUD schema).
- Finite-safe clamp01() util; harden the composite-layer brightness
  multiply (latent negative-wrap / >=1 skip) with it.
- Preview WebSocket: tolerate non-numeric raw, generalize raw-range.
- Frontend: settings-toggle slider per HA/system_metrics/http editor
  with min/max grey-out; toggle hidden for fixed-mapping percent
  metrics. en/ru/zh locale keys.
- Additive optional field (default True) — JSON round-trip, no migration.

Tests: store create/update round-trip, clamp-passthrough, live
normalize flip, game_event raw channel + build_stream forwarding,
and finite-safe clamp01.

server/tests/storage/test_value_source_store.py

@@ -7,7 +7,10 @@ from ledgrab.storage.value_source import (
     AnimatedValueSource,
     AudioValueSource,
     DaylightValueSource,
+    HAEntityValueSource,
+    HTTPValueSource,
     StaticValueSource,
+    SystemMetricsValueSource,
     ValueSource,
 )
 from ledgrab.storage.value_source_store import ValueSourceStore
@@ -238,6 +241,50 @@ class TestValueSourceStoreCRUD:
         assert updated.speed == 30.0
 
 
+# ---------------------------------------------------------------------------
+# normalize flag — full store create/update path (factory builder + applier)
+# ---------------------------------------------------------------------------
+
+
+class TestValueSourceNormalizeStoreRoundTrip:
+    """The ``normalize`` flag must survive the real write path —
+    create_source -> CREATE_BUILDERS and update_source -> UPDATE_APPLIERS —
+    not just dataclass from_dict/to_dict. A dropped builder/applier line would
+    silently revert/ignore the flag while every dataclass-level test stayed
+    green, so these exercise the factory layer end-to-end (game_event is
+    intentionally excluded — it has no store/CRUD path).
+    """
+
+    _CASES = [
+        ("ha_entity", {"ha_source_id": "ha1", "entity_id": "sensor.temp"}, HAEntityValueSource),
+        ("http", {"http_endpoint_id": "ep1"}, HTTPValueSource),
+        ("system_metrics", {"metric": "cpu_load"}, SystemMetricsValueSource),
+    ]
+
+    @pytest.mark.parametrize("source_type,kwargs,cls", _CASES)
+    def test_create_normalize_false_persists(self, store, source_type, kwargs, cls):
+        s = store.create_source(
+            name=f"{source_type}_n", source_type=source_type, normalize=False, **kwargs
+        )
+        assert isinstance(s, cls)
+        assert s.normalize is False
+        # Re-read exercises the SQLite blob persistence round-trip as well.
+        assert store.get_source(s.id).normalize is False
+
+    @pytest.mark.parametrize("source_type,kwargs,cls", _CASES)
+    def test_create_normalize_defaults_true(self, store, source_type, kwargs, cls):
+        s = store.create_source(name=f"{source_type}_d", source_type=source_type, **kwargs)
+        assert s.normalize is True
+
+    @pytest.mark.parametrize("source_type,kwargs,cls", _CASES)
+    def test_update_normalize_flip(self, store, source_type, kwargs, cls):
+        s = store.create_source(
+            name=f"{source_type}_u", source_type=source_type, normalize=False, **kwargs
+        )
+        assert store.update_source(s.id, normalize=True).normalize is True
+        assert store.update_source(s.id, normalize=False).normalize is False
+
+
 # ---------------------------------------------------------------------------
 # Name uniqueness
 # ---------------------------------------------------------------------------