Add lora loader node

nodes/lora_gateway.py

@@ -1,15 +0,0 @@
-class LoRAGateway:
-    """
-    LoRA Gateway Node
-    Acts as the entry point for LoRA management services
-    """
-    @classmethod
-    def INPUT_TYPES(cls):
-        return {
-            "required": {},
-            "optional": {}
-        }
-
-    RETURN_TYPES = ()
-    FUNCTION = "register_services"
-    CATEGORY = "LoRA Management"

nodes/lora_loader.py

@@ -0,0 +1,75 @@
+import re
+from nodes import LoraLoader
+from comfy.comfy_types import IO
+from ..services.lora_scanner import LoraScanner
+from ..config import config
+import asyncio
+import os
+
+class LoraManagerLoader:
+    NAME = "Lora Loader"
+    CATEGORY = "loaders"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "model": ("MODEL",),
+                "clip": ("CLIP",),
+                "text": (IO.STRING, {
+                    "multiline": True, 
+                    "dynamicPrompts": True, 
+                    "tooltip": "Format: <lora:lora_name:strength> separated by spaces or punctuation"
+                }),
+            },
+        }
+
+    RETURN_TYPES = ("MODEL", "CLIP", IO.STRING, IO.STRING)
+    RETURN_NAMES = ("MODEL", "CLIP", "loaded_loras", "trigger_words")
+    FUNCTION = "load_loras"
+
+    async def get_lora_info(self, lora_name):
+        """Get the lora path and trigger words from cache"""
+        scanner = await LoraScanner.get_instance()
+        cache = await scanner.get_cached_data()
+        
+        for item in cache.raw_data:
+            if item.get('file_name') == lora_name:
+                file_path = item.get('file_path')
+                if file_path:
+                    for root in config.loras_roots:
+                        root = root.replace(os.sep, '/')
+                        if file_path.startswith(root):
+                            relative_path = os.path.relpath(file_path, root).replace(os.sep, '/')
+                            # Get trigger words from civitai metadata
+                            civitai = item.get('civitai', {})
+                            trigger_words = civitai.get('trainedWords', []) if civitai else []
+                            return relative_path, trigger_words
+        return lora_name, []  # Fallback if not found
+
+    def load_loras(self, model, clip, text):
+        """Loads multiple LoRAs based on the text input format."""
+        lora_pattern = r'<lora:([^:]+):([\d\.]+)>'
+        lora_matches = re.finditer(lora_pattern, text)
+        
+        loaded_loras = []
+        all_trigger_words = []
+        
+        for match in lora_matches:
+            lora_name = match.group(1)
+            strength = float(match.group(2))
+            
+            # Get lora path and trigger words
+            lora_path, trigger_words = asyncio.run(self.get_lora_info(lora_name))
+            
+            # Apply the LoRA using the resolved path
+            model, clip = LoraLoader().load_lora(model, clip, lora_path, strength, strength)
+            loaded_loras.append(f"{lora_name}: {strength}")
+            
+            # Add trigger words to collection
+            all_trigger_words.extend(trigger_words)
+        
+        loaded_loras_text = "\n".join(loaded_loras) if loaded_loras else "No LoRAs loaded"
+        trigger_words_text = ", ".join(all_trigger_words) if all_trigger_words else ""
+
+        return (model, clip, loaded_loras_text, trigger_words_text)