feat: Implement metadata collection and processing framework with debug node for verification

py/metadata_collector/node_extractors.py

@@ -0,0 +1,163 @@
+class NodeMetadataExtractor:
+    """Base class for node-specific metadata extraction"""
+    
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        """Extract metadata from node inputs/outputs"""
+        pass
+        
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        """Update metadata with node outputs after execution"""
+        pass
+        
+class GenericNodeExtractor(NodeMetadataExtractor):
+    """Default extractor for nodes without specific handling"""
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        pass
+        
+class CheckpointLoaderExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "ckpt_name" not in inputs:
+            return
+            
+        model_name = inputs.get("ckpt_name")
+        if model_name:
+            metadata["models"][node_id] = {
+                "name": model_name,
+                "type": "checkpoint",
+                "node_id": node_id
+            }
+        
+class CLIPTextEncodeExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "text" not in inputs:
+            return
+            
+        text = inputs.get("text", "")
+        metadata["prompts"][node_id] = {
+            "text": text,
+            "node_id": node_id
+        }
+        
+class SamplerExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+            
+        sampling_params = {}
+        for key in ["seed", "steps", "cfg", "sampler_name", "scheduler", "denoise"]:
+            if key in inputs:
+                sampling_params[key] = inputs[key]
+                
+        metadata["sampling"][node_id] = {
+            "parameters": sampling_params,
+            "node_id": node_id
+        }
+        
+        # Extract latent image dimensions if available
+        if "latent_image" in inputs and inputs["latent_image"] is not None:
+            latent = inputs["latent_image"]
+            if isinstance(latent, dict) and "samples" in latent:
+                # Extract dimensions from latent tensor
+                samples = latent["samples"]
+                if hasattr(samples, "shape") and len(samples.shape) >= 3:
+                    # Correct shape interpretation: [batch_size, channels, height/8, width/8]
+                    # Multiply by 8 to get actual pixel dimensions
+                    height = int(samples.shape[2] * 8)
+                    width = int(samples.shape[3] * 8)
+                    
+                    if "size" not in metadata:
+                        metadata["size"] = {}
+                        
+                    metadata["size"][node_id] = {
+                        "width": width,
+                        "height": height,
+                        "node_id": node_id
+                    }
+
+class LoraLoaderExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "lora_name" not in inputs:
+            return
+            
+        lora_name = inputs.get("lora_name")
+        strength_model = inputs.get("strength_model", 1.0)
+        strength_clip = inputs.get("strength_clip", 1.0)
+        
+        metadata["loras"][node_id] = {
+            "name": lora_name,
+            "strength_model": strength_model,
+            "strength_clip": strength_clip,
+            "node_id": node_id
+        }
+
+class ImageSizeExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+        
+        width = inputs.get("width", 512)
+        height = inputs.get("height", 512)
+        
+        if "size" not in metadata:
+            metadata["size"] = {}
+            
+        metadata["size"][node_id] = {
+            "width": width,
+            "height": height,
+            "node_id": node_id
+        }
+
+class LoraLoaderManagerExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+            
+        # Handle LoraManager nodes which might store loras differently
+        if "loras" in inputs:
+            loras = inputs.get("loras", [])
+            if isinstance(loras, list):
+                active_loras = []
+                # Filter for active loras (may be a list of dicts with 'active' flag)
+                for lora in loras:
+                    if isinstance(lora, dict) and lora.get("active", True) and not lora.get("_isDummy", False):
+                        active_loras.append({
+                            "name": lora.get("name", ""),
+                            "strength": lora.get("strength", 1.0)
+                        })
+                
+                if active_loras:
+                    metadata["loras"][node_id] = {
+                        "lora_list": active_loras,
+                        "node_id": node_id
+                    }
+        
+        # If there's a direct text field with lora definitions
+        if "text" in inputs:
+            text = inputs.get("text", "")
+            if text and "<lora:" in text:
+                metadata["loras"][node_id] = {
+                    "raw_text": text,
+                    "node_id": node_id
+                }
+        
+# Registry of node-specific extractors
+NODE_EXTRACTORS = {
+    "CheckpointLoaderSimple": CheckpointLoaderExtractor,
+    "CLIPTextEncode": CLIPTextEncodeExtractor,
+    "KSampler": SamplerExtractor,
+    "LoraLoader": LoraLoaderExtractor,
+    "EmptyLatentImage": ImageSizeExtractor,
+    "Lora Loader (LoraManager)": LoraLoaderManagerExtractor,
+    "SamplerCustomAdvanced": SamplerExtractor,  # Add SamplerCustomAdvanced
+    "UNETLoader": CheckpointLoaderExtractor,    # Add UNETLoader
+    # Add other nodes as needed
+}