feat: Introduce generation parameter merging from request, Civitai, and embedded image metadata, and enhance ComfyUI metadata parsing.

py/recipes/merger.py

@@ -0,0 +1,50 @@
+from typing import Any, Dict, Optional
+import logging
+
+logger = logging.getLogger(__name__)
+
+class GenParamsMerger:
+    """Utility to merge generation parameters from multiple sources with priority."""
+
+    BLACKLISTED_KEYS = {"id", "url", "userId", "username", "createdAt", "updatedAt", "hash"}
+
+    @staticmethod
+    def merge(
+        request_params: Optional[Dict[str, Any]] = None,
+        civitai_meta: Optional[Dict[str, Any]] = None,
+        embedded_metadata: Optional[Dict[str, Any]] = None
+    ) -> Dict[str, Any]:
+        """
+        Merge generation parameters from three sources.
+        
+        Priority: request_params > civitai_meta > embedded_metadata
+        
+        Args:
+            request_params: Params provided directly in the import request
+            civitai_meta: Params from Civitai Image API 'meta' field
+            embedded_metadata: Params extracted from image EXIF/embedded metadata
+            
+        Returns:
+            Merged parameters dictionary
+        """
+        result = {}
+
+        # 1. Start with embedded metadata (lowest priority)
+        if embedded_metadata:
+            # If it's a full recipe metadata, we use its gen_params
+            if "gen_params" in embedded_metadata and isinstance(embedded_metadata["gen_params"], dict):
+                result.update(embedded_metadata["gen_params"])
+            else:
+                # Otherwise assume the dict itself contains gen_params
+                result.update(embedded_metadata)
+
+        # 2. Layer Civitai meta (medium priority)
+        if civitai_meta:
+            result.update(civitai_meta)
+
+        # 3. Layer request params (highest priority)
+        if request_params:
+            result.update(request_params)
+
+        # Filter out blacklisted keys
+        return {k: v for k, v in result.items() if k not in GenParamsMerger.BLACKLISTED_KEYS}

py/recipes/parsers/comfy.py

@@ -36,9 +36,6 @@ class ComfyMetadataParser(RecipeMetadataParser):
             # Find all LoraLoader nodes
             lora_nodes = {k: v for k, v in data.items() if isinstance(v, dict) and v.get('class_type') == 'LoraLoader'}
             
-            if not lora_nodes:
-                return {"error": "No LoRA information found in this ComfyUI workflow", "loras": []}
-            
             # Process each LoraLoader node
             for node_id, node in lora_nodes.items():
                 if 'inputs' not in node or 'lora_name' not in node['inputs']: