feat: Add conditioning matching to prompts and update metadata handling in node extractors. See #235

py/metadata_collector/metadata_processor.py

@@ -209,6 +209,44 @@ class MetadataProcessor:
                 
         return None
     
+    @staticmethod
+    def match_conditioning_to_prompts(metadata, sampler_id):
+        """
+        Match conditioning objects from a sampler to prompts in metadata
+        
+        Parameters:
+        - metadata: The workflow metadata
+        - sampler_id: ID of the sampler node to match
+        
+        Returns:
+        - Dictionary with 'prompt' and 'negative_prompt' if found
+        """
+        result = {
+            "prompt": "",
+            "negative_prompt": ""
+        }
+        
+        # Check if we have stored conditioning objects for this sampler
+        if sampler_id in metadata.get(PROMPTS, {}) and (
+            "pos_conditioning" in metadata[PROMPTS][sampler_id] or 
+            "neg_conditioning" in metadata[PROMPTS][sampler_id]):
+            
+            pos_conditioning = metadata[PROMPTS][sampler_id].get("pos_conditioning")
+            neg_conditioning = metadata[PROMPTS][sampler_id].get("neg_conditioning")
+            
+            # Try to match conditioning objects with those stored by CLIPTextEncodeExtractor
+            for prompt_node_id, prompt_data in metadata[PROMPTS].items():
+                if "conditioning" not in prompt_data:
+                    continue
+                    
+                if pos_conditioning is not None and id(prompt_data["conditioning"]) == id(pos_conditioning):
+                    result["prompt"] = prompt_data.get("text", "")
+                
+                if neg_conditioning is not None and id(prompt_data["conditioning"]) == id(neg_conditioning):
+                    result["negative_prompt"] = prompt_data.get("text", "")
+            
+        return result
+    
     @staticmethod
     def extract_generation_params(metadata, id=None):
         """
@@ -261,8 +299,14 @@ class MetadataProcessor:
             params["sampler"] = sampling_params.get("sampler_name")
             params["scheduler"] = sampling_params.get("scheduler")
             
-            # Trace connections from the primary sampler
+            # First try to match conditioning objects to prompts (new method)
-            if prompt and primary_sampler_id:
+            if primary_sampler_id:
+                prompt_results = MetadataProcessor.match_conditioning_to_prompts(metadata, primary_sampler_id)
+                params["prompt"] = prompt_results["prompt"]
+                params["negative_prompt"] = prompt_results["negative_prompt"]
+            
+            # If prompts were not found by object matching, fall back to tracing connections
+            if not params["prompt"] and prompt and primary_sampler_id:
                 # Check if this is a SamplerCustomAdvanced node
                 is_custom_advanced = False
                 if prompt.original_prompt and primary_sampler_id in prompt.original_prompt:

py/metadata_collector/node_extractors.py

@@ -47,6 +47,13 @@ class CLIPTextEncodeExtractor(NodeMetadataExtractor):
             "text": text,
             "node_id": node_id
         }
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        if outputs and isinstance(outputs, list) and len(outputs) > 0:
+            if isinstance(outputs[0], tuple) and len(outputs[0]) > 0:
+                conditioning = outputs[0][0]
+                metadata[PROMPTS][node_id]["conditioning"] = conditioning
         
 class SamplerExtractor(NodeMetadataExtractor):
     @staticmethod
@@ -64,6 +71,18 @@ class SamplerExtractor(NodeMetadataExtractor):
             "node_id": node_id,
             IS_SAMPLER: True  # Add sampler flag
         }
+
+        # Store the conditioning objects directly in metadata for later matching
+        pos_conditioning = inputs.get("positive", None)
+        neg_conditioning = inputs.get("negative", None)
+
+        # Save conditioning objects in metadata for later matching
+        if pos_conditioning is not None or neg_conditioning is not None:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            
+            metadata[PROMPTS][node_id]["pos_conditioning"] = pos_conditioning
+            metadata[PROMPTS][node_id]["neg_conditioning"] = neg_conditioning
         
         # Extract latent image dimensions if available
         if "latent_image" in inputs and inputs["latent_image"] is not None:
@@ -103,6 +122,18 @@ class KSamplerAdvancedExtractor(NodeMetadataExtractor):
             IS_SAMPLER: True  # Add sampler flag
         }
         
+        # Store the conditioning objects directly in metadata for later matching
+        pos_conditioning = inputs.get("positive", None)
+        neg_conditioning = inputs.get("negative", None)
+
+        # Save conditioning objects in metadata for later matching
+        if pos_conditioning is not None or neg_conditioning is not None:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            
+            metadata[PROMPTS][node_id]["pos_conditioning"] = pos_conditioning
+            metadata[PROMPTS][node_id]["neg_conditioning"] = neg_conditioning
+        
         # Extract latent image dimensions if available
         if "latent_image" in inputs and inputs["latent_image"] is not None:
             latent = inputs["latent_image"]
@@ -376,6 +407,13 @@ class CLIPTextEncodeFluxExtractor(NodeMetadataExtractor):
                 
             metadata[SAMPLING][node_id]["parameters"]["guidance"] = guidance_value
 
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        if outputs and isinstance(outputs, list) and len(outputs) > 0:
+            if isinstance(outputs[0], tuple) and len(outputs[0]) > 0:
+                conditioning = outputs[0][0]
+                metadata[PROMPTS][node_id]["conditioning"] = conditioning
+
 class CFGGuiderExtractor(NodeMetadataExtractor):
     @staticmethod
     def extract(node_id, inputs, outputs, metadata):
@@ -404,6 +442,7 @@ NODE_EXTRACTORS = {
     "BasicScheduler": BasicSchedulerExtractor,  # Add BasicScheduler
     # Loaders
     "CheckpointLoaderSimple": CheckpointLoaderExtractor,
+    "comfyLoader": CheckpointLoaderExtractor,  # eeasy comfyLoader
     "UNETLoader": UNETLoaderExtractor,          # Updated to use dedicated extractor
     "UnetLoaderGGUF": UNETLoaderExtractor,  # Updated to use dedicated extractor
     "LoraLoader": LoraLoaderExtractor,