Fix issues with workflow params ui

- set initial value for layer params
- prevent combo box from imposing minimum width
- handle images that don't match canvas size

ai_diffusion/custom_workflow.py

@@ -438,14 +438,17 @@ def collect_parameters(self, layers: "LayerManager", bounds: Bounds):
         params = copy(self.params)
         for md in self.metadata:
             param = params.get(md.name)
-            assert param is not None, f"Parameter {md.name} not found"
 
             if md.kind is ParamKind.image_layer:
+                if param is None and len(layers.images) > 0:
+                    param = layers.images[0].id
                 layer = layers.find(QUuid(param))
                 if layer is None:
                     raise ValueError(f"Input layer for parameter {md.name} not found")
                 params[md.name] = layer.get_pixels(bounds)
             elif md.kind is ParamKind.mask_layer:
+                if param is None and len(layers.masks) > 0:
+                    param = layers.masks[0].id
                 layer = layers.find(QUuid(param))
                 if layer is None:
                     raise ValueError(f"Input layer for parameter {md.name} not found")
@@ -455,6 +458,9 @@ def collect_parameters(self, layers: "LayerManager", bounds: Bounds):
                 if style is None:
                     raise ValueError(f"Style {param} not found")
                 params[md.name] = style
+            elif param is None:
+                raise ValueError(f"Parameter {md.name} not found")
+
         return params
 
     def _handle_job_finished(self, job: Job):

ai_diffusion/model.py

@@ -487,23 +487,27 @@ def show_preview(self, job_id: str, index: int, name_prefix="Preview"):
         job = self.jobs.find(job_id)
         assert job is not None, "Cannot show preview, invalid job id"
         name = f"[{name_prefix}] {trim_text(job.params.name, 77)}"
+        image = job.results[index]
+        bounds = job.params.bounds
+        if image.extent != bounds.extent:
+            image = Image.crop(image, Bounds(0, 0, *bounds.extent))
         if self._layer and self._layer.was_removed:
             self._layer = None  # layer was removed by user
         if self._layer is not None:
             self._layer.name = name
-            self._layer.write_pixels(job.results[index], job.params.bounds)
+            self._layer.write_pixels(image, bounds)
             self._layer.move_to_top()
         else:
-            self._layer = self.layers.create(
-                name, job.results[index], job.params.bounds, make_active=False
-            )
+            self._layer = self.layers.create(name, image, bounds, make_active=False)
             self._layer.is_locked = True
 
     def hide_preview(self):
         if self._layer is not None:
             self._layer.hide()
 
     def apply_result(self, image: Image, params: JobParams, behavior: ApplyBehavior, prefix=""):
+        if image.extent != params.bounds.extent:
+            image = Image.crop(image, Bounds(0, 0, *params.bounds.extent))
         if len(params.regions) == 0:
             if behavior is ApplyBehavior.replace:
                 self.layers.update_layer_image(self.layers.active, image, params.bounds)

ai_diffusion/ui/custom_workflow.py

@@ -30,8 +30,11 @@ class LayerSelect(QComboBox):
 
     def __init__(self, filter: str | None = None, parent: QWidget | None = None):
         super().__init__(parent)
-        self.setContentsMargins(0, 0, 0, 0)
         self.filter = filter
+
+        self.setContentsMargins(0, 0, 0, 0)
+        self.setMinimumContentsLength(20)
+        self.setSizeAdjustPolicy(QComboBox.SizeAdjustPolicy.AdjustToMinimumContentsLength)
         self.currentIndexChanged.connect(lambda _: self.value_changed.emit())
 
         self._update()
@@ -257,6 +260,9 @@ class ChoiceParamWidget(QComboBox):
 
     def __init__(self, param: CustomParam, parent: QWidget | None = None):
         super().__init__(parent)
+        self.setMinimumContentsLength(20)
+        self.setSizeAdjustPolicy(QComboBox.SizeAdjustPolicy.AdjustToMinimumContentsLength)
+
         if param.choices:
             self.addItems(param.choices)
         self.currentIndexChanged.connect(lambda _: self.value_changed.emit())

tests/test_workflow.py

@@ -180,7 +180,6 @@ def test_prepare_lora():
     files = FileLibrary(FileCollection(), FileCollection())
     fractal = files.loras.add(File.remote("x/FRACTAL.safetensors"))
     files.loras.set_meta(fractal, "lora_strength", 0.55)
-    files.loras.set_meta(fractal, "lora_triggers", "FRACTAL HEART")
 
     mop = files.loras.add(File.remote("MOTHER_OF_PEARL.safetensors"))
     files.loras.set_meta(mop, "lora_triggers", "crab")
@@ -200,7 +199,7 @@ def test_prepare_lora():
         files=files,
         perf=default_perf,
     )
-    assert job.conditioning and job.conditioning.positive == "test  baloon FRACTAL HEART space crab"
+    assert job.conditioning and job.conditioning.positive == "test  baloon  space crab"
     assert (
         job.models
         and LoraInput("PINK_UNICORNS.safetensors", 0.77) in job.models.loras