Add IP-Adapter, Style & Reference Latent injectors

chain_injectors/flux1_ipadapter_injector.py

@@ -0,0 +1,46 @@
+def inject(assembler, chain_definition, chain_items):
+    if not chain_items:
+        return
+
+    ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+    if ksampler_name not in assembler.node_map:
+        print(f"Warning: KSampler node '{ksampler_name}' not found for Flux1 IPAdapter chain. Skipping.")
+        return
+        
+    ksampler_id = assembler.node_map[ksampler_name]
+
+    if 'model' not in assembler.workflow[ksampler_id]['inputs']:
+        print(f"Warning: KSampler node '{ksampler_name}' is missing 'model' input. Skipping Flux1 IPAdapter chain.")
+        return
+        
+    current_model_connection = assembler.workflow[ksampler_id]['inputs']['model']
+    
+    for item_data in chain_items:
+        image_loader_id = assembler._get_unique_id()
+        image_loader_node = assembler._get_node_template("LoadImage")
+        image_loader_node['inputs']['image'] = item_data['image']
+        assembler.workflow[image_loader_id] = image_loader_node
+
+        ipadapter_loader_id = assembler._get_unique_id()
+        ipadapter_loader_node = assembler._get_node_template("IPAdapterFluxLoader")
+        ipadapter_loader_node['inputs']['ipadapter'] = "ip-adapter.bin"
+        ipadapter_loader_node['inputs']['clip_vision'] = "google/siglip-so400m-patch14-384"
+        ipadapter_loader_node['inputs']['provider'] = "cuda"
+        assembler.workflow[ipadapter_loader_id] = ipadapter_loader_node
+        
+        apply_ipa_id = assembler._get_unique_id()
+        apply_ipa_node = assembler._get_node_template("ApplyIPAdapterFlux")
+        
+        apply_ipa_node['inputs']['weight'] = item_data['weight']
+        apply_ipa_node['inputs']['start_percent'] = item_data.get('start_percent', 0.0)
+        apply_ipa_node['inputs']['end_percent'] = item_data.get('end_percent', 0.6)
+        
+        apply_ipa_node['inputs']['model'] = current_model_connection
+        apply_ipa_node['inputs']['ipadapter_flux'] = [ipadapter_loader_id, 0]
+        apply_ipa_node['inputs']['image'] = [image_loader_id, 0]
+        
+        assembler.workflow[apply_ipa_id] = apply_ipa_node
+        current_model_connection = [apply_ipa_id, 0]
+
+    assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
+    print(f"Flux1 IPAdapter injector applied. KSampler model input re-routed through {len(chain_items)} IPAdapter(s).")

chain_injectors/ipadapter_injector.py

@@ -0,0 +1,106 @@
+def inject(assembler, chain_definition, chain_items):
+    if not chain_items:
+        return
+
+    final_settings = {}
+    if chain_items and isinstance(chain_items[-1], dict) and chain_items[-1].get('is_final_settings'):
+        final_settings = chain_items.pop()
+
+    if not chain_items:
+        return
+
+    end_node_name = chain_definition.get('end')
+    if not end_node_name or end_node_name not in assembler.node_map:
+        print(f"Warning: Target node '{end_node_name}' for IPAdapter chain not found. Skipping chain injection.")
+        return
+        
+    end_node_id = assembler.node_map[end_node_name]
+    
+    if 'model' not in assembler.workflow[end_node_id]['inputs']:
+        print(f"Warning: Target node '{end_node_name}' is missing 'model' input. Skipping IPAdapter chain.")
+        return
+    
+    current_model_connection = assembler.workflow[end_node_id]['inputs']['model']
+    
+    model_type = final_settings.get('model_type', 'sdxl')
+    megapixels = 1.05 if model_type == 'sdxl' else 0.39
+
+    pos_embed_outputs = []
+    neg_embed_outputs = []
+
+    for i, item_data in enumerate(chain_items):
+        loader_type = 'FaceID' if 'FACEID' in item_data.get('preset', '') else 'Unified'
+        
+        loader_template_name = "IPAdapterUnifiedLoader"
+        if loader_type == 'FaceID':
+            loader_template_name = "IPAdapterUnifiedLoaderFaceID"
+
+        image_loader_id = assembler._get_unique_id()
+        image_loader_node = assembler._get_node_template("LoadImage")
+        image_loader_node['inputs']['image'] = item_data['image']
+        assembler.workflow[image_loader_id] = image_loader_node
+        
+        image_scaler_id = assembler._get_unique_id()
+        image_scaler_node = assembler._get_node_template("ImageScaleToTotalPixels")
+        image_scaler_node['inputs']['image'] = [image_loader_id, 0]
+        image_scaler_node['inputs']['megapixels'] = megapixels
+        image_scaler_node['inputs']['upscale_method'] = "lanczos"
+        assembler.workflow[image_scaler_id] = image_scaler_node
+
+        ipadapter_loader_id = assembler._get_unique_id()
+        ipadapter_loader_node = assembler._get_node_template(loader_template_name)
+        ipadapter_loader_node['inputs']['model'] = current_model_connection
+        ipadapter_loader_node['inputs']['preset'] = item_data['preset']
+        if loader_type == 'FaceID':
+             ipadapter_loader_node['inputs']['lora_strength'] = item_data.get('lora_strength', 0.6)
+        assembler.workflow[ipadapter_loader_id] = ipadapter_loader_node
+        
+        encoder_id = assembler._get_unique_id()
+        encoder_node = assembler._get_node_template("IPAdapterEncoder")
+        encoder_node['inputs']['weight'] = item_data['weight']
+        encoder_node['inputs']['ipadapter'] = [ipadapter_loader_id, 1]
+        encoder_node['inputs']['image'] = [image_scaler_id, 0]
+        assembler.workflow[encoder_id] = encoder_node
+        
+        pos_embed_outputs.append([encoder_id, 0])
+        neg_embed_outputs.append([encoder_id, 1])
+
+    pos_combiner_id = assembler._get_unique_id()
+    pos_combiner_node = assembler._get_node_template("IPAdapterCombineEmbeds")
+    pos_combiner_node['inputs']['method'] = final_settings.get('final_combine_method', 'concat')
+    for i, conn in enumerate(pos_embed_outputs):
+        pos_combiner_node['inputs'][f'embed{i+1}'] = conn
+    assembler.workflow[pos_combiner_id] = pos_combiner_node
+
+    neg_combiner_id = assembler._get_unique_id()
+    neg_combiner_node = assembler._get_node_template("IPAdapterCombineEmbeds")
+    neg_combiner_node['inputs']['method'] = final_settings.get('final_combine_method', 'concat')
+    for i, conn in enumerate(neg_embed_outputs):
+        neg_combiner_node['inputs'][f'embed{i+1}'] = conn
+    assembler.workflow[neg_combiner_id] = neg_combiner_node
+    
+    final_loader_type = 'FaceID' if 'FACEID' in final_settings.get('final_preset', '') else 'Unified'
+    final_loader_template_name = "IPAdapterUnifiedLoader"
+    if final_loader_type == 'FaceID':
+        final_loader_template_name = "IPAdapterUnifiedLoaderFaceID"
+
+    final_loader_id = assembler._get_unique_id()
+    final_loader_node = assembler._get_node_template(final_loader_template_name)
+    final_loader_node['inputs']['model'] = current_model_connection
+    final_loader_node['inputs']['preset'] = final_settings.get('final_preset', 'STANDARD (medium strength)')
+    if final_loader_type == 'FaceID':
+        final_loader_node['inputs']['lora_strength'] = final_settings.get('final_lora_strength', 0.6)
+    assembler.workflow[final_loader_id] = final_loader_node
+
+    apply_embeds_id = assembler._get_unique_id()
+    apply_embeds_node = assembler._get_node_template("IPAdapterEmbeds")
+    apply_embeds_node['inputs']['weight'] = final_settings.get('final_weight', 1.0)
+    apply_embeds_node['inputs']['embeds_scaling'] = final_settings.get('final_embeds_scaling', 'V only')
+    apply_embeds_node['inputs']['model'] = [final_loader_id, 0]
+    apply_embeds_node['inputs']['ipadapter'] = [final_loader_id, 1]
+    apply_embeds_node['inputs']['pos_embed'] = [pos_combiner_id, 0]
+    apply_embeds_node['inputs']['neg_embed'] = [neg_combiner_id, 0]
+    assembler.workflow[apply_embeds_id] = apply_embeds_node
+
+    assembler.workflow[end_node_id]['inputs']['model'] = [apply_embeds_id, 0]
+    print(f"IPAdapter injector applied. Redirected '{end_node_name}' model input through {len(chain_items)} reference images.")

chain_injectors/newbie_lora_injector.py

@@ -0,0 +1,63 @@
+from copy import deepcopy
+
+def inject(assembler, chain_definition, chain_items):
+    if not chain_items:
+        return
+
+    output_map = chain_definition.get('output_map', {})
+    current_connections = {}
+    for key, type_name in output_map.items():
+        if ':' in str(key):
+            node_name, idx_str = key.split(':')
+            if node_name not in assembler.node_map:
+                print(f"Warning: [NewBie LoRA Injector] Node '{node_name}' in chain's output_map not found. Skipping.")
+                continue
+            node_id = assembler.node_map[node_name]
+            start_output_idx = int(idx_str)
+            current_connections[type_name] = [node_id, start_output_idx]
+        else:
+            print(f"Warning: [NewBie LoRA Injector] output_map key '{key}' is not in 'node:index' format. Skipping this connection.")
+
+    template_name = chain_definition.get('template')
+    if not template_name:
+        print(f"Warning: [NewBie LoRA Injector] No 'template' defined for chain. Skipping.")
+        return
+
+    for item_data in chain_items:
+        template = assembler._get_node_template(template_name)
+        node_data = deepcopy(template)
+        
+        node_data['inputs']['lora_name'] = item_data.get('lora_name')
+        node_data['inputs']['strength'] = item_data.get('strength_model', 1.0)
+        node_data['inputs']['enabled'] = True
+        
+        if 'model' in current_connections:
+            node_data['inputs']['model'] = current_connections['model']
+        if 'clip' in current_connections:
+            node_data['inputs']['clip'] = current_connections['clip']
+
+        new_node_id = assembler._get_unique_id()
+        assembler.workflow[new_node_id] = node_data
+        
+        current_connections['model'] = [new_node_id, 0]
+        current_connections['clip'] = [new_node_id, 1]
+
+    end_input_map = chain_definition.get('end_input_map', {})
+    for type_name, targets in end_input_map.items():
+        if type_name in current_connections:
+            if not isinstance(targets, list):
+                targets = [targets]
+            
+            for target_str in targets:
+                try:
+                    end_node_name, end_input_name = target_str.split(':')
+                    if end_node_name in assembler.node_map:
+                        end_node_id = assembler.node_map[end_node_name]
+                        assembler.workflow[end_node_id]['inputs'][end_input_name] = current_connections[type_name]
+                    else:
+                        print(f"Warning: [NewBie LoRA Injector] End node '{end_node_name}' for dynamic chain not found. Skipping connection.")
+                except ValueError:
+                    print(f"Warning: [NewBie LoRA Injector] Invalid target format '{target_str}' in end_input_map. Skipping.")
+
+    if chain_items:
+        print(f"NewBie LoRA injector applied. Re-routed model and clip through {len(chain_items)} LoRA(s).")

chain_injectors/reference_latent_injector.py

@@ -2,15 +2,78 @@ def inject(assembler, chain_definition, chain_items):
     if not chain_items:
         return
 
-    ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
-    flux_guidance_name = chain_definition.get('flux_guidance_node')
+    guider_node_name = chain_definition.get('guider_node')
+    guider_target_inputs = chain_definition.get('guider_target_inputs', [])
+    start_connections_map = chain_definition.get('start_connections', {})
     vae_node_name = chain_definition.get('vae_node', 'vae_loader')
 
+    if guider_node_name and guider_node_name in assembler.node_map and guider_target_inputs:
+        guider_id = assembler.node_map[guider_node_name]
+        if vae_node_name not in assembler.node_map:
+            print(f"Warning: VAE node '{vae_node_name}' not found for Guider chain. Skipping.")
+            return
+        vae_node_id = assembler.node_map[vae_node_name]
+        
+        print(f"ReferenceLatent injector targeting DualCFGGuider node '{guider_node_name}'.")
+
+        current_connections = {}
+        for target_input in guider_target_inputs:
+            conn_str = start_connections_map.get(target_input)
+            if not conn_str:
+                print(f"Warning: No start connection defined for '{target_input}' in Guider chain. Skipping this input.")
+                continue
+            try:
+                node_name, idx_str = conn_str.split(':')
+                node_id = assembler.node_map[node_name]
+                current_connections[target_input] = [node_id, int(idx_str)]
+            except (ValueError, KeyError):
+                print(f"Warning: Invalid start connection '{conn_str}' for '{target_input}'. Skipping.")
+
+        encoded_latents = []
+        for i, img_filename in enumerate(chain_items):
+            load_id = assembler._get_unique_id()
+            load_node = assembler._get_node_template("LoadImage")
+            load_node['inputs']['image'] = img_filename
+            assembler.workflow[load_id] = load_node
+            
+            scale_id = assembler._get_unique_id()
+            scale_node = assembler._get_node_template("ImageScaleToTotalPixels")
+            scale_node['inputs']['megapixels'] = 1.0
+            scale_node['inputs']['upscale_method'] = "lanczos"
+            scale_node['inputs']['image'] = [load_id, 0]
+            assembler.workflow[scale_id] = scale_node
+            
+            vae_encode_id = assembler._get_unique_id()
+            vae_encode_node = assembler._get_node_template("VAEEncode")
+            vae_encode_node['inputs']['pixels'] = [scale_id, 0]
+            vae_encode_node['inputs']['vae'] = [vae_node_id, 0]
+            assembler.workflow[vae_encode_id] = vae_encode_node
+            encoded_latents.append([vae_encode_id, 0])
+        
+        for target_input_name, start_connection in current_connections.items():
+            current_chain_head = start_connection
+            for i, latent_conn in enumerate(encoded_latents):
+                ref_latent_id = assembler._get_unique_id()
+                ref_latent_node = assembler._get_node_template("ReferenceLatent")
+                ref_latent_node['inputs']['conditioning'] = current_chain_head
+                ref_latent_node['inputs']['latent'] = latent_conn
+                ref_latent_node['_meta']['title'] = f"{target_input_name} RefLatent {i+1}"
+                assembler.workflow[ref_latent_id] = ref_latent_node
+                current_chain_head = [ref_latent_id, 0]
+            
+            assembler.workflow[guider_id]['inputs'][target_input_name] = current_chain_head
+            print(f"  - Input '{target_input_name}' of node '{guider_node_name}' re-routed through {len(chain_items)} reference images.")
+
+        return
+
+    flux_guidance_name = chain_definition.get('flux_guidance_node')
+    ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+
     if ksampler_name not in assembler.node_map:
-        print(f"Warning: [ReferenceLatent] KSampler node '{ksampler_name}' not found. Skipping.")
+        print(f"Warning: KSampler node '{ksampler_name}' not found for ReferenceLatent chain. Skipping.")
         return
     if vae_node_name not in assembler.node_map:
-        print(f"Warning: [ReferenceLatent] VAE loader node '{vae_node_name}' not found. Skipping.")
+        print(f"Warning: VAE loader node '{vae_node_name}' not found for ReferenceLatent chain. Skipping.")
         return
 
     ksampler_id = assembler.node_map[ksampler_name]
@@ -23,44 +86,72 @@ def inject(assembler, chain_definition, chain_items):
         if 'conditioning' in assembler.workflow[flux_guidance_id]['inputs']:
             pos_target_node_id = flux_guidance_id
             pos_target_input_name = 'conditioning'
-            print(f"ReferenceLatent injector targeting FluxGuidance node '{flux_guidance_name}'.")
+            print(f"ReferenceLatent injector targeting FluxGuidance node '{flux_guidance_name}' for positive chain.")
     
     if not pos_target_node_id:
         if 'positive' in assembler.workflow[ksampler_id]['inputs']:
             pos_target_node_id = ksampler_id
             pos_target_input_name = 'positive'
-            print(f"ReferenceLatent injector targeting KSampler node '{ksampler_name}'.")
+            print(f"ReferenceLatent injector targeting KSampler node '{ksampler_name}' for positive chain.")
         else:
-            print(f"Warning: [ReferenceLatent] Could not find a valid positive injection point. Skipping.")
+            print(f"Warning: Could not find a valid positive injection point for ReferenceLatent chain. Skipping.")
             return
 
     current_pos_conditioning = assembler.workflow[pos_target_node_id]['inputs'][pos_target_input_name]
 
-    for i, img_filename in enumerate(chain_items):
-        if not img_filename or not isinstance(img_filename, str):
-            continue
+    neg_target_node_id = ksampler_id
+    neg_target_input_name = 'negative'
+    if 'negative' not in assembler.workflow[neg_target_node_id]['inputs']:
+        print(f"Warning: KSampler node '{ksampler_name}' has no 'negative' input. Skipping negative ReferenceLatent chain.")
+        neg_target_node_id = None
+    
+    current_neg_conditioning = None
+    if neg_target_node_id:
+        current_neg_conditioning = assembler.workflow[neg_target_node_id]['inputs'][neg_target_input_name]
 
+    for i, img_filename in enumerate(chain_items):
         load_id = assembler._get_unique_id()
         load_node = assembler._get_node_template("LoadImage")
         load_node['inputs']['image'] = img_filename
+        load_node['_meta']['title'] = f"Load Reference Image {i+1}"
         assembler.workflow[load_id] = load_node
         
+        scale_id = assembler._get_unique_id()
+        scale_node = assembler._get_node_template("ImageScaleToTotalPixels")
+        scale_node['inputs']['megapixels'] = 1.0
+        scale_node['inputs']['upscale_method'] = "lanczos"
+        scale_node['inputs']['image'] = [load_id, 0]
+        scale_node['_meta']['title'] = f"Scale Reference {i+1}"
+        assembler.workflow[scale_id] = scale_node
+        
         vae_encode_id = assembler._get_unique_id()
         vae_encode_node = assembler._get_node_template("VAEEncode")
-        vae_encode_node['inputs']['pixels'] = [load_id, 0]
+        vae_encode_node['inputs']['pixels'] = [scale_id, 0]
         vae_encode_node['inputs']['vae'] = [vae_node_id, 0]
+        vae_encode_node['_meta']['title'] = f"VAE Encode Reference {i+1}"
         assembler.workflow[vae_encode_id] = vae_encode_node
         
         latent_conn = [vae_encode_id, 0]
 
-        ref_latent_id = assembler._get_unique_id()
-        ref_latent_node = assembler._get_node_template("ReferenceLatent")
-        ref_latent_node['inputs']['conditioning'] = current_pos_conditioning
-        ref_latent_node['inputs']['latent'] = latent_conn
-        assembler.workflow[ref_latent_id] = ref_latent_node
-        
-        current_pos_conditioning = [ref_latent_id, 0]
+        pos_ref_latent_id = assembler._get_unique_id()
+        pos_ref_latent_node = assembler._get_node_template("ReferenceLatent")
+        pos_ref_latent_node['inputs']['conditioning'] = current_pos_conditioning
+        pos_ref_latent_node['inputs']['latent'] = latent_conn
+        pos_ref_latent_node['_meta']['title'] = f"Positive ReferenceLatent {i+1}"
+        assembler.workflow[pos_ref_latent_id] = pos_ref_latent_node
+        current_pos_conditioning = [pos_ref_latent_id, 0]
+
+        if neg_target_node_id:
+            neg_ref_latent_id = assembler._get_unique_id()
+            neg_ref_latent_node = assembler._get_node_template("ReferenceLatent")
+            neg_ref_latent_node['inputs']['conditioning'] = current_neg_conditioning
+            neg_ref_latent_node['inputs']['latent'] = latent_conn
+            neg_ref_latent_node['_meta']['title'] = f"Negative ReferenceLatent {i+1}"
+            assembler.workflow[neg_ref_latent_id] = neg_ref_latent_node
+            current_neg_conditioning = [neg_ref_latent_id, 0]
 
     assembler.workflow[pos_target_node_id]['inputs'][pos_target_input_name] = current_pos_conditioning
+    if neg_target_node_id:
+        assembler.workflow[neg_target_node_id]['inputs'][neg_target_input_name] = current_neg_conditioning
     
-    print(f"ReferenceLatent injector applied. Re-routed inputs through {len(chain_items)} reference image(s).")
+    print(f"ReferenceLatent injector applied. Re-routed inputs through {len(chain_items)} reference images.")

chain_injectors/sd3_ipadapter_injector.py

@@ -0,0 +1,66 @@
+def inject(assembler, chain_definition, chain_items):
+    if not chain_items:
+        return
+
+    ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+    if ksampler_name not in assembler.node_map:
+        print(f"Warning: KSampler node '{ksampler_name}' not found for SD3 IPAdapter chain. Skipping.")
+        return
+        
+    ksampler_id = assembler.node_map[ksampler_name]
+
+    if 'model' not in assembler.workflow[ksampler_id]['inputs']:
+        print(f"Warning: KSampler node '{ksampler_name}' is missing 'model' input. Skipping SD3 IPAdapter chain.")
+        return
+        
+    current_model_connection = assembler.workflow[ksampler_id]['inputs']['model']
+    
+    clip_vision_loader_id = assembler._get_unique_id()
+    clip_vision_loader_node = assembler._get_node_template("CLIPVisionLoader")
+    clip_vision_loader_node['inputs']['clip_name'] = "sigclip_vision_patch14_384.safetensors"
+    assembler.workflow[clip_vision_loader_id] = clip_vision_loader_node
+
+    ipadapter_loader_id = assembler._get_unique_id()
+    ipadapter_loader_node = assembler._get_node_template("IPAdapterSD3Loader")
+    ipadapter_loader_node['inputs']['ipadapter'] = "ip-adapter_sd35l_instantx.bin"
+    ipadapter_loader_node['inputs']['provider'] = "cuda"
+    assembler.workflow[ipadapter_loader_id] = ipadapter_loader_node
+
+    for item_data in chain_items:
+        image_loader_id = assembler._get_unique_id()
+        image_loader_node = assembler._get_node_template("LoadImage")
+        image_loader_node['inputs']['image'] = item_data['image']
+        assembler.workflow[image_loader_id] = image_loader_node
+
+        image_scaler_id = assembler._get_unique_id()
+        image_scaler_node = assembler._get_node_template("ImageScaleToTotalPixels")
+        image_scaler_node['inputs']['image'] = [image_loader_id, 0]
+        image_scaler_node['inputs']['upscale_method'] = 'nearest-exact'
+        image_scaler_node['inputs']['megapixels'] = 1.0
+        assembler.workflow[image_scaler_id] = image_scaler_node
+
+        clip_vision_encode_id = assembler._get_unique_id()
+        clip_vision_encode_node = assembler._get_node_template("CLIPVisionEncode")
+        clip_vision_encode_node['inputs']['crop'] = "center"
+        clip_vision_encode_node['inputs']['clip_vision'] = [clip_vision_loader_id, 0]
+        clip_vision_encode_node['inputs']['image'] = [image_scaler_id, 0]
+        assembler.workflow[clip_vision_encode_id] = clip_vision_encode_node
+        
+        apply_ipa_id = assembler._get_unique_id()
+        apply_ipa_node = assembler._get_node_template("ApplyIPAdapterSD3")
+        
+        apply_ipa_node['inputs']['weight'] = item_data.get('weight', 1.0)
+        apply_ipa_node['inputs']['start_percent'] = item_data.get('start_percent', 0.0)
+        apply_ipa_node['inputs']['end_percent'] = item_data.get('end_percent', 1.0)
+        
+        apply_ipa_node['inputs']['model'] = current_model_connection
+        apply_ipa_node['inputs']['ipadapter'] = [ipadapter_loader_id, 0]
+        apply_ipa_node['inputs']['image_embed'] = [clip_vision_encode_id, 0]
+        
+        assembler.workflow[apply_ipa_id] = apply_ipa_node
+        
+        current_model_connection = [apply_ipa_id, 0]
+
+    assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
+    
+    print(f"SD3 IPAdapter injector applied. KSampler model input re-routed through {len(chain_items)} IPAdapter(s).")

chain_injectors/style_injector.py

@@ -0,0 +1,71 @@
+def inject(assembler, chain_definition, chain_items):
+    if not chain_items:
+        return
+
+    flux_guidance_name = chain_definition.get('flux_guidance_node')
+    ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+
+    target_node_id = None
+    target_input_name = None
+    
+    if flux_guidance_name and flux_guidance_name in assembler.node_map:
+        flux_guidance_id = assembler.node_map[flux_guidance_name]
+        if 'conditioning' in assembler.workflow[flux_guidance_id]['inputs']:
+            target_node_id = flux_guidance_id
+            target_input_name = 'conditioning'
+
+    if not target_node_id:
+        if ksampler_name in assembler.node_map:
+            ksampler_id = assembler.node_map[ksampler_name]
+            if 'positive' in assembler.workflow[ksampler_id]['inputs']:
+                target_node_id = ksampler_id
+                target_input_name = 'positive'
+        else:
+            return
+            
+    if not target_node_id:
+        return
+
+    current_conditioning = assembler.workflow[target_node_id]['inputs'][target_input_name]
+
+    style_model_loader_id = assembler._get_unique_id()
+    style_model_loader_node = assembler._get_node_template("StyleModelLoader")
+    style_model_loader_node['inputs']['style_model_name'] = "flux1-redux-dev.safetensors"
+    assembler.workflow[style_model_loader_id] = style_model_loader_node
+
+    clip_vision_loader_id = assembler._get_unique_id()
+    clip_vision_loader_node = assembler._get_node_template("CLIPVisionLoader")
+    clip_vision_loader_node['inputs']['clip_name'] = "sigclip_vision_patch14_384.safetensors"
+    assembler.workflow[clip_vision_loader_id] = clip_vision_loader_node
+
+    for item_data in chain_items:
+        image = item_data.get('image')
+        strength = item_data.get('strength', 1.0)
+        if not image or strength is None:
+            continue
+
+        load_image_id = assembler._get_unique_id()
+        clip_vision_encode_id = assembler._get_unique_id()
+        style_apply_id = assembler._get_unique_id()
+
+        load_image_node = assembler._get_node_template("LoadImage")
+        clip_vision_encode_node = assembler._get_node_template("CLIPVisionEncode")
+        style_apply_node = assembler._get_node_template("StyleModelApply")
+        
+        load_image_node['inputs']['image'] = image
+        clip_vision_encode_node['inputs']['crop'] = "center"
+        clip_vision_encode_node['inputs']['clip_vision'] = [clip_vision_loader_id, 0]
+        clip_vision_encode_node['inputs']['image'] = [load_image_id, 0]
+
+        style_apply_node['inputs']['strength'] = strength
+        style_apply_node['inputs']['strength_type'] = "multiply"
+        style_apply_node['inputs']['conditioning'] = current_conditioning
+        style_apply_node['inputs']['style_model'] = [style_model_loader_id, 0]
+        style_apply_node['inputs']['clip_vision_output'] = [clip_vision_encode_id, 0]
+        
+        assembler.workflow[load_image_id] = load_image_node
+        assembler.workflow[clip_vision_encode_id] = clip_vision_encode_node
+        assembler.workflow[style_apply_id] = style_apply_node
+        current_conditioning = [style_apply_id, 0]
+
+    assembler.workflow[target_node_id]['inputs'][target_input_name] = current_conditioning

yaml/ipadapter.yaml

@@ -0,0 +1,25 @@
+IPAdapter_presets:
+  SD1.5:
+    - "LIGHT - SD1.5 only (low strength)"
+    - "STANDARD (medium strength)"
+    - "VIT-G (medium strength)"
+    - "PLUS (high strength)"
+    - "PLUS FACE (portraits)"
+    - "FULL FACE - SD1.5 only (portraits stronger)"
+  SDXL:
+    - "STANDARD (medium strength)"
+    - "VIT-G (medium strength)"
+    - "PLUS (high strength)"
+    - "PLUS FACE (portraits)"
+
+IPAdapter_FaceID_presets:
+  SD1.5:
+    - "FACEID"
+    - "FACEID PLUS - SD1.5 only"
+    - "FACEID PLUS V2"
+    - "FACEID PORTRAIT (style transfer)"
+  SDXL:
+    - "FACEID"
+    - "FACEID PLUS V2"
+    - "FACEID PORTRAIT (style transfer)"
+    - "FACEID PORTRAIT UNNORM - SDXL only (strong)"

yaml/ipadapter_models.yaml

@@ -0,0 +1,55 @@
+- preset_name: "LIGHT - SD1.5 only (low strength)"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter_sd15_light_v11.bin"
+
+- preset_name: "STANDARD (medium strength)"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter_sdxl_vit-h.safetensors"
+  ipadapter: "ip-adapter_sd15.safetensors"
+
+- preset_name: "VIT-G (medium strength)"
+  clip_vision: "CLIP-ViT-bigG-14-laion2B-39B-b160k.safetensors"
+  ipadapter: "ip-adapter_sdxl.safetensors"
+  ipadapter: "ip-adapter_sd15_vit-G.safetensors"
+
+- preset_name: "PLUS (high strength)"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-plus_sdxl_vit-h.safetensors"
+  ipadapter: "ip-adapter-plus_sd15.safetensors"
+
+- preset_name: "PLUS FACE (portraits)"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-plus-face_sdxl_vit-h.safetensors"
+  ipadapter: "ip-adapter-plus-face_sd15.safetensors"
+
+- preset_name: "FULL FACE - SD1.5 only (portraits stronger)"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-full-face_sd15.safetensors"
+
+- preset_name: "FACEID"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-faceid_sdxl.bin"
+  loras: "ip-adapter-faceid_sdxl_lora.safetensors"
+  ipadapter: "ip-adapter-faceid_sd15.bin"
+  loras: "ip-adapter-faceid_sd15_lora.safetensors"
+
+- preset_name: "FACEID PLUS - SD1.5 only"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-faceid-plus_sd15.bin"
+  loras: "ip-adapter-faceid-plus_sd15_lora.safetensors"
+
+- preset_name: "FACEID PLUS V2"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-faceid-plusv2_sdxl.bin"
+  loras: "ip-adapter-faceid-plusv2_sdxl_lora.safetensors"
+  ipadapter: "ip-adapter-faceid-plusv2_sd15.bin"
+  loras: "ip-adapter-faceid-plusv2_sd15_lora.safetensors"
+
+- preset_name: "FACEID PORTRAIT (style transfer)"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-faceid-portrait_sdxl.bin"
+  ipadapter: "ip-adapter-faceid-portrait-v11_sd15.bin"
+
+- preset_name: "FACEID PORTRAIT UNNORM - SDXL only (strong)"
+  clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+  ipadapter: "ip-adapter-faceid-portrait_sdxl_unnorm.bin"

yaml/ipadapter_sd3_models.yaml

@@ -0,0 +1,2 @@
+ipadapter: "ip-adapter_sd35l_instantx.bin"
+clip_vision: "sigclip_vision_patch14_384.safetensors"