feat: add LoraDemoNode and LoraRandomizerNode with documentation

- Import and register two new nodes: LoraDemoNode and LoraRandomizerNode
- Update import exception handling for better readability with multi-line formatting
- Add comprehensive documentation file `docs/custom-node-ui-output.md` for UI output usage in custom nodes
- Ensure proper node registration in NODE_CLASS_MAPPINGS for ComfyUI integration
- Maintain backward compatibility with existing node structure and import fallbacks

py/nodes/lora_demo.py

@@ -0,0 +1,95 @@
+"""
+Lora Demo Node - Demonstrates LORAS custom widget type usage.
+
+This node accepts LORAS widget input and outputs a summary string.
+"""
+
+import logging
+import random
+
+logger = logging.getLogger(__name__)
+
+
+class LoraDemoNode:
+    """Demo node that uses LORAS custom widget type."""
+
+    NAME = "Lora Demo (LoraManager)"
+    CATEGORY = "Lora Manager/demo"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "loras": ("LORAS", {}),
+            }
+        }
+
+    RETURN_TYPES = ("STRING",)
+    RETURN_NAMES = ("summary",)
+
+    FUNCTION = "process"
+    OUTPUT_NODE = False
+
+    async def process(self, loras):
+        """
+        Process LoRAs input and return summary + UI data for widget.
+
+        Args:
+            loras: List of LoRA dictionaries with structure:
+                [{'name': str, 'strength': float, 'clipStrength': float, 'active': bool, ...}]
+
+        Returns:
+            Dictionary with 'result' (for workflow) and 'ui' (for frontend display)
+        """
+        from ..services.service_registry import ServiceRegistry
+
+        # Get lora scanner to access available loras
+        scanner = await ServiceRegistry.get_lora_scanner()
+
+        # Get available loras from cache
+        available_loras = []
+        try:
+            cache_data = await scanner.get_cached_data(force_refresh=False)
+            if cache_data and hasattr(cache_data, "raw_data"):
+                available_loras = cache_data.raw_data
+        except Exception as e:
+            logger.warning(f"[LoraDemoNode] Failed to get lora cache: {e}")
+
+        # Randomly select 3-5 loras
+        num_to_select = random.randint(3, 5)
+        if len(available_loras) < num_to_select:
+            num_to_select = len(available_loras)
+
+        selected_loras = (
+            random.sample(available_loras, num_to_select) if num_to_select > 0 else []
+        )
+
+        # Generate random loras data for widget
+        widget_loras = []
+        for lora in selected_loras:
+            strength = round(random.uniform(0.1, 1.0), 2)
+            widget_loras.append(
+                {
+                    "name": lora.get("file_name", "Unknown"),
+                    "strength": strength,
+                    "clipStrength": strength,
+                    "active": True,
+                    "expanded": False,
+                }
+            )
+
+        # Create summary string
+        active_names = [l["name"] for l in widget_loras]
+        summary = f"Randomized {len(active_names)} LoRAs: {', '.join(active_names)}"
+
+        logger.info(f"[LoraDemoNode] {summary}")
+
+        # Return format: result for workflow + ui for frontend
+        return {"result": (summary,), "ui": {"loras": widget_loras}}
+
+
+# Node class mappings for ComfyUI
+NODE_CLASS_MAPPINGS = {"LoraDemoNode": LoraDemoNode}
+
+# Display name mappings
+NODE_DISPLAY_NAME_MAPPINGS = {"LoraDemoNode": "LoRA Demo"}