chore: update comfyui to dccca1

hordelib/consts.py

@@ -6,7 +6,7 @@
 
 from hordelib.config_path import get_hordelib_path
 
-COMFYUI_VERSION = "c5a369a33ddb622827552716d9b0119035a2e666"
+COMFYUI_VERSION = "dccca1daa5af1954d55918f365e83a3331019549"
 """The exact version of ComfyUI version to load."""
 
 REMOTE_PROXY = ""

hordelib/horde.py

@@ -511,6 +511,7 @@ def _final_pipeline_adjustments(self, payload, pipeline_data):
                         ),
                     )
                     continue
+
                 logger.debug(f"Found valid lora{verstext} {lora_name}")
                 if SharedModelManager.manager.compvis is None:
                     raise RuntimeError("Cannot use LORAs without a compvis loaded!")
@@ -783,7 +784,20 @@ def _inference(
 
         # Call the inference pipeline
         # logger.debug(payload)
-        images = self.generator.run_image_pipeline(pipeline_data, payload)
+        try:
+            images = self.generator.run_image_pipeline(pipeline_data, payload)
+        finally:
+            # This ensures that the lora failure list is flushed after each inference (even if it fails)
+            loras_failed = SharedModelManager.manager.get_lora_failures()
+
+        for lora in loras_failed:
+            faults.append(
+                GenMetadataEntry(
+                    type=METADATA_TYPE.lora,
+                    value=METADATA_VALUE.parse_failed,
+                    ref=lora,
+                ),
+            )
 
         results = self._process_results(images)
         ret_results = [

hordelib/model_manager/hyper.py

@@ -104,6 +104,26 @@ def models(self) -> dict:
     of the model object and whether it was loaded with Loras.
     """
 
+    _lora_failures: list[str] = []
+
+    def add_lora_failure(self, lora_name: str) -> None:
+        """Adds a Lora failure to the list of failures.
+
+        Args:
+            lora_name (str): The Lora name to add.
+        """
+        self._lora_failures.append(lora_name)
+
+    def get_lora_failures(self) -> list[str]:
+        """Returns the list of Lora failures.
+
+        Returns:
+            list[str]: The list of Lora failures.
+        """
+        returned_failures = self._lora_failures.copy()
+        self._lora_failures = []
+        return returned_failures
+
     def get_available_models(
         self,
         mm_include: Iterable[str | MODEL_CATEGORY_NAMES | type[BaseModelManager]] | None = None,

hordelib/nodes/node_lora_loader.py

@@ -4,6 +4,8 @@
 import folder_paths
 from loguru import logger
 
+from hordelib.shared_model_manager import SharedModelManager
+
 
 class HordeLoraLoader:
     def __init__(self):
@@ -62,12 +64,18 @@ def load_lora(self, model, clip, lora_name, strength_model, strength_clip):
                 self.loaded_lora = None
                 del temp
 
-        if lora is None:
-            lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
-            self.loaded_lora = (lora_path, lora)
-
-        model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora, strength_model, strength_clip)
-        return (model_lora, clip_lora)
+        try:
+            with logger.catch(reraise=True):
+                if lora is None:
+                    lora = comfy.utils.load_torch_file(lora_path, safe_load=True)
+                    self.loaded_lora = (lora_path, lora)
+
+                model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora, strength_model, strength_clip)
+                return (model_lora, clip_lora)
+        except Exception as e:
+            logger.error(f"Failed to load lora {lora_name}: {e}")
+            SharedModelManager.manager.add_lora_failure(lora_name)
+            return (model, clip)
 
 
 NODE_CLASS_MAPPINGS = {"HordeLoraLoader": HordeLoraLoader}

tests/test_internal_comfyui_failures.py

@@ -48,6 +48,14 @@ def test_lora_failure(
 
         with pytest.raises(RuntimeError, match="Pipeline failed to run"):
             hordelib_instance.basic_inference_single_image(data)
+
+        shared_model_manager.manager.add_lora_failure(lora_GlowingRunesAI)
+
+        with pytest.raises(RuntimeError, match="Pipeline failed to run"):
+            hordelib_instance.basic_inference_single_image(data)
+
+        assert len(shared_model_manager.manager._lora_failures) == 0
+
     finally:
         del os.environ["FAILURE_TEST"]
         assert os.getenv("FAILURE_TEST", False) is False