feat: add Qwen-Image-2.1 ControlNet support, consolidate unified pipeline, and significantly reduce frontend components

README.md

@@ -15,6 +15,7 @@ models:
   # Directly Run Models
   - abenzerps/Qwen-Image-2.1-Uncensored-GGUF
   - AiAF/Illustrious-XL-v0.1.safetensors
+  - alibaba-pai/Qwen-Image-2.1-Fun-Controlnet-Union
   - alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1
   - black-forest-labs/FLUX.1-Redux-dev
   - black-forest-labs/FLUX.2-dev-NVFP4
@@ -99,6 +100,7 @@ models:
   - jdopensource/JoyAI-Image-Edit-Plus-ComfyUI
   - kandinskylab/Kandinsky-5.0-T2I-Lite
   - Kijai/flux-fp8
+  - Kijai/QwenImage_experimental
   - Laxhar/noob_openpose
   - Laxhar/noobai-XL-1.1
   - Laxhar/noobai-XL-Vpred-1.0
@@ -141,6 +143,7 @@ models:
   # Upstream Base Models
   - AIDC-AI/Ovis-Image-7B
   - Alpha-VLLM/Lumina-Image-2.0
+  - alibaba-pai/Qwen-Image-2.1-Fun-Controlnet-Union
   - baidu/ERNIE-Image
   - baidu/ERNIE-Image-Turbo
   - black-forest-labs/FLUX.1-dev

chain_injectors/anima_controlnet_lllite_injector.py

@@ -1,53 +0,0 @@
-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 Anima LLLite 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.")
-        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
-
-        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
-
-        patch_loader_id = assembler._get_unique_id()
-        patch_loader_node = assembler._get_node_template("ModelPatchLoader")
-        patch_loader_node['inputs']['name'] = item_data['control_net_name']
-        assembler.workflow[patch_loader_id] = patch_loader_node
-
-        apply_cn_id = assembler._get_unique_id()
-        apply_cn_node = assembler._get_node_template("AnimaLLLiteApply")
-        
-        apply_cn_node['inputs']['strength'] = item_data['strength']
-        apply_cn_node['inputs']['start_percent'] = item_data.get('start_percent', 0.0)
-        apply_cn_node['inputs']['end_percent'] = item_data.get('end_percent', 1.0)
-
-        apply_cn_node['inputs']['model'] = current_model_connection
-        apply_cn_node['inputs']['model_patch'] = [patch_loader_id, 0]
-        apply_cn_node['inputs']['image'] = [image_scaler_id, 0]
-        
-        assembler.workflow[apply_cn_id] = apply_cn_node
-
-        current_model_connection = [apply_cn_id, 0]
-
-    assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
-    
-    print(f"Anima LLLite injector applied. KSampler model input re-routed through {len(chain_items)} LLLite(s).")

chain_injectors/controlnet_injector.py

@@ -1,60 +1,278 @@
-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: Target node '{ksampler_name}' for ControlNet chain not found. Skipping chain injection.")
-        return
-        
-    ksampler_id = assembler.node_map[ksampler_name]
-
-    if 'positive' not in assembler.workflow[ksampler_id]['inputs'] or \
-       'negative' not in assembler.workflow[ksampler_id]['inputs']:
-        print(f"Warning: KSampler node '{ksampler_name}' is missing 'positive' or 'negative' inputs. Skipping ControlNet chain.")
-        return
-
-    vae_source_str = chain_definition.get('vae_source')
-    if not vae_source_str:
-        print("Warning: 'vae_source' definition missing in the recipe for the ControlNet chain. Skipping.")
-        return
-    vae_node_name, vae_idx_str = vae_source_str.split(':')
-    if vae_node_name not in assembler.node_map:
-        print(f"Warning: VAE source node '{vae_node_name}' for ControlNet chain not found. Skipping.")
-        return
-    vae_connection = [assembler.node_map[vae_node_name], int(vae_idx_str)]
-        
-    current_positive_connection = assembler.workflow[ksampler_id]['inputs']['positive']
-    current_negative_connection = assembler.workflow[ksampler_id]['inputs']['negative']
-    
-    for item_data in chain_items:
-        cn_loader_id = assembler._get_unique_id()
-        cn_loader_node = assembler._get_node_template("ControlNetLoader")
-        cn_loader_node['inputs']['control_net_name'] = item_data['control_net_name']
-        assembler.workflow[cn_loader_id] = cn_loader_node
-
-        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
-
-        apply_cn_id = assembler._get_unique_id()
-        apply_cn_node = assembler._get_node_template(chain_definition['template'])
-        
-        apply_cn_node['inputs']['strength'] = item_data['strength']
-        
-        apply_cn_node['inputs']['positive'] = current_positive_connection
-        apply_cn_node['inputs']['negative'] = current_negative_connection
-        apply_cn_node['inputs']['control_net'] = [cn_loader_id, 0]
-        apply_cn_node['inputs']['image'] = [image_loader_id, 0]
-        apply_cn_node['inputs']['vae'] = vae_connection
-        
-        assembler.workflow[apply_cn_id] = apply_cn_node
-
-        current_positive_connection = [apply_cn_id, 0]
-        current_negative_connection = [apply_cn_id, 1]
-
-    assembler.workflow[ksampler_id]['inputs']['positive'] = current_positive_connection
-    assembler.workflow[ksampler_id]['inputs']['negative'] = current_negative_connection
-    
-    print(f"ControlNet injector applied. KSampler inputs redirected through {len(chain_items)} ControlNet nodes.")
+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: Target node '{ksampler_name}' for ControlNet chain not found. Skipping chain injection.")
+        return
+        
+    ksampler_id = assembler.node_map[ksampler_name]
+
+    vae_source_str = chain_definition.get('vae_source')
+    vae_connection = None
+    if vae_source_str and ':' in vae_source_str:
+        vae_node_name, vae_idx_str = vae_source_str.split(':')
+        if vae_node_name in assembler.node_map:
+            vae_connection = [assembler.node_map[vae_node_name], int(vae_idx_str)]
+        else:
+            print(f"Warning: VAE source node '{vae_node_name}' for ControlNet chain not found.")
+
+    template_name = chain_definition.get('template', 'ControlNetApplyAdvanced')
+
+    # Resolution scaling: SD1.5 defaults to 0.75 MP, all other architectures default to 1.0 MP
+    model_type = getattr(assembler, 'dynamic_values', {}).get('model_type', '')
+    if isinstance(model_type, str) and model_type.lower() in ('sd15', 'sd1.5', 'sd-1.5'):
+        default_megapixels = 0.75
+    else:
+        default_megapixels = 1.0
+    megapixels = float(chain_definition.get('megapixels', default_megapixels))
+
+    # 1. Qwen-Image-2.1 Fun ControlNet
+    if template_name == "QwenImage21FunControlNetApply":
+        if 'model' not in assembler.workflow[ksampler_id]['inputs']:
+            print(f"Warning: KSampler node '{ksampler_name}' is missing 'model' input. Skipping Qwen Fun ControlNet.")
+            return
+
+        current_model_connection = assembler.workflow[ksampler_id]['inputs']['model']
+
+        for item_data in chain_items:
+            patch_loader_id = assembler._get_unique_id()
+            patch_loader_node = assembler._get_node_template("ModelPatchLoader")
+            patch_loader_node['inputs']['name'] = item_data['control_net_name']
+            assembler.workflow[patch_loader_id] = patch_loader_node
+
+            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'] = megapixels
+            assembler.workflow[image_scaler_id] = image_scaler_node
+
+            apply_cn_id = assembler._get_unique_id()
+            apply_cn_node = assembler._get_node_template(template_name)
+            apply_cn_node['inputs']['strength'] = item_data.get('strength', 1.0)
+            apply_cn_node['inputs']['start_percent'] = 0.0
+            apply_cn_node['inputs']['end_percent'] = 1.0
+            apply_cn_node['inputs']['model'] = current_model_connection
+            apply_cn_node['inputs']['model_patch'] = [patch_loader_id, 0]
+            apply_cn_node['inputs']['control_image'] = [image_scaler_id, 0]
+            if vae_connection:
+                apply_cn_node['inputs']['vae'] = vae_connection
+
+            assembler.workflow[apply_cn_id] = apply_cn_node
+            current_model_connection = [apply_cn_id, 0]
+
+        assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
+        print(f"Qwen Fun ControlNet injector applied. KSampler model input redirected through {len(chain_items)} node(s).")
+        return
+
+    # 2. Anima LLLite ControlNet
+    if template_name == "AnimaLLLiteApply":
+        if 'model' not in assembler.workflow[ksampler_id]['inputs']:
+            print(f"Warning: KSampler node '{ksampler_name}' is missing 'model' input. Skipping Anima LLLite.")
+            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
+
+            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'] = megapixels
+            assembler.workflow[image_scaler_id] = image_scaler_node
+
+            patch_loader_id = assembler._get_unique_id()
+            patch_loader_node = assembler._get_node_template("ModelPatchLoader")
+            patch_loader_node['inputs']['name'] = item_data['control_net_name']
+            assembler.workflow[patch_loader_id] = patch_loader_node
+
+            apply_cn_id = assembler._get_unique_id()
+            apply_cn_node = assembler._get_node_template("AnimaLLLiteApply")
+            apply_cn_node['inputs']['strength'] = item_data.get('strength', 1.0)
+            apply_cn_node['inputs']['start_percent'] = item_data.get('start_percent', 0.0)
+            apply_cn_node['inputs']['end_percent'] = item_data.get('end_percent', 1.0)
+            apply_cn_node['inputs']['model'] = current_model_connection
+            apply_cn_node['inputs']['model_patch'] = [patch_loader_id, 0]
+            apply_cn_node['inputs']['image'] = [image_scaler_id, 0]
+
+            assembler.workflow[apply_cn_id] = apply_cn_node
+            current_model_connection = [apply_cn_id, 0]
+
+        assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
+        print(f"Anima LLLite ControlNet injector applied. KSampler model input redirected through {len(chain_items)} node(s).")
+        return
+
+    # 3. DiffSynth ControlNet (Z-Image)
+    if template_name in ("QwenImageDiffsynthControlnet", "ZImage_ControlNet"):
+        model_sampler_name = chain_definition.get('model_sampler_node')
+        target_node_id = None
+        target_input_name = 'model'
+
+        if model_sampler_name and model_sampler_name in assembler.node_map:
+            model_sampler_id = assembler.node_map[model_sampler_name]
+            if target_input_name in assembler.workflow[model_sampler_id]['inputs']:
+                target_node_id = model_sampler_id
+
+        if not target_node_id:
+            if target_input_name in assembler.workflow[ksampler_id]['inputs']:
+                target_node_id = ksampler_id
+            else:
+                print(f"Warning: Neither model_sampler nor ksampler found with 'model' input. Skipping DiffSynth ControlNet.")
+                return
+
+        current_model_connection = assembler.workflow[target_node_id]['inputs'][target_input_name]
+
+        for item_data in chain_items:
+            patch_loader_id = assembler._get_unique_id()
+            patch_loader_node = assembler._get_node_template("ModelPatchLoader")
+            patch_loader_node['inputs']['name'] = item_data['control_net_name']
+            assembler.workflow[patch_loader_id] = patch_loader_node
+
+            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'] = megapixels
+            assembler.workflow[image_scaler_id] = image_scaler_node
+
+            apply_cn_id = assembler._get_unique_id()
+            apply_cn_node = assembler._get_node_template(template_name)
+            apply_cn_node['inputs']['strength'] = item_data.get('strength', 1.0)
+            apply_cn_node['inputs']['model'] = current_model_connection
+            apply_cn_node['inputs']['model_patch'] = [patch_loader_id, 0]
+            apply_cn_node['inputs']['image'] = [image_scaler_id, 0]
+            if vae_connection and 'vae' in apply_cn_node.get('inputs', {}):
+                apply_cn_node['inputs']['vae'] = vae_connection
+
+            assembler.workflow[apply_cn_id] = apply_cn_node
+            current_model_connection = [apply_cn_id, 0]
+
+        assembler.workflow[target_node_id]['inputs'][target_input_name] = current_model_connection
+        print(f"DiffSynth ControlNet injector applied. Target 'model' input redirected through {len(chain_items)} node(s).")
+        return
+
+    # 4. Krea-2 ControlNet
+    if template_name == "Krea2ControlApply":
+        if 'model' not in assembler.workflow[ksampler_id]['inputs']:
+            print(f"Warning: KSampler node '{ksampler_name}' is missing 'model' input. Skipping Krea2 ControlNet.")
+            return
+
+        latent_connection = assembler.workflow[ksampler_id]['inputs'].get('latent_image')
+        if not latent_connection:
+            print(f"Warning: KSampler node '{ksampler_name}' is missing 'latent_image' input. Krea2 ControlNet requires it. Skipping.")
+            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
+
+            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'] = megapixels
+            image_scaler_node['inputs']['resolution_steps'] = 1
+            assembler.workflow[image_scaler_id] = image_scaler_node
+
+            lora_loader_id = assembler._get_unique_id()
+            lora_loader_node = assembler._get_node_template("Krea2ControlLoRALoader")
+            lora_loader_node['inputs']['lora_name'] = item_data['control_net_name']
+            lora_loader_node['inputs']['strength'] = item_data.get('strength', 1.0)
+            lora_loader_node['inputs']['model'] = current_model_connection
+            assembler.workflow[lora_loader_id] = lora_loader_node
+
+            img_encode_id = assembler._get_unique_id()
+            img_encode_node = assembler._get_node_template("Krea2ControlImageEncode")
+            img_encode_node['inputs']['resize'] = "match_latent_size"
+            img_encode_node['inputs']['upscale_method'] = "lanczos"
+            img_encode_node['inputs']['crop'] = "center"
+            img_encode_node['inputs']['channel_mode'] = "rgb"
+            img_encode_node['inputs']['normalize'] = "none"
+            img_encode_node['inputs']['invert'] = False
+            img_encode_node['inputs']['batch_mode'] = "independent_images"
+            img_encode_node['inputs']['control_image'] = [image_scaler_id, 0]
+            if vae_connection:
+                img_encode_node['inputs']['vae'] = vae_connection
+            img_encode_node['inputs']['latent'] = latent_connection
+            assembler.workflow[img_encode_id] = img_encode_node
+
+            apply_cn_id = assembler._get_unique_id()
+            apply_cn_node = assembler._get_node_template("Krea2ControlApply")
+            apply_cn_node['inputs']['model'] = [lora_loader_id, 0]
+            apply_cn_node['inputs']['control_latent'] = [img_encode_id, 0]
+
+            assembler.workflow[apply_cn_id] = apply_cn_node
+            current_model_connection = [apply_cn_id, 0]
+
+        assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
+        print(f"Krea2 ControlNet injector applied. KSampler model input redirected through {len(chain_items)} node(s).")
+        return
+
+    # 5. Default: Classical Conditioning ControlNet (SD1.5, SDXL, SD3.5, FLUX.1, Qwen-Image)
+    if 'positive' not in assembler.workflow[ksampler_id]['inputs'] or \
+       'negative' not in assembler.workflow[ksampler_id]['inputs']:
+        print(f"Warning: KSampler node '{ksampler_name}' is missing 'positive' or 'negative' inputs. Skipping ControlNet chain.")
+        return
+
+    if not vae_connection:
+        print("Warning: 'vae_source' definition missing or invalid in the recipe for the ControlNet chain. Skipping.")
+        return
+
+    current_positive_connection = assembler.workflow[ksampler_id]['inputs']['positive']
+    current_negative_connection = assembler.workflow[ksampler_id]['inputs']['negative']
+
+    for item_data in chain_items:
+        cn_loader_id = assembler._get_unique_id()
+        cn_loader_node = assembler._get_node_template("ControlNetLoader")
+        cn_loader_node['inputs']['control_net_name'] = item_data['control_net_name']
+        assembler.workflow[cn_loader_id] = cn_loader_node
+
+        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'] = megapixels
+        assembler.workflow[image_scaler_id] = image_scaler_node
+
+        apply_cn_id = assembler._get_unique_id()
+        apply_cn_node = assembler._get_node_template(template_name)
+        apply_cn_node['inputs']['strength'] = item_data.get('strength', 1.0)
+        apply_cn_node['inputs']['positive'] = current_positive_connection
+        apply_cn_node['inputs']['negative'] = current_negative_connection
+        apply_cn_node['inputs']['control_net'] = [cn_loader_id, 0]
+        apply_cn_node['inputs']['image'] = [image_scaler_id, 0]
+        apply_cn_node['inputs']['vae'] = vae_connection
+
+        assembler.workflow[apply_cn_id] = apply_cn_node
+        current_positive_connection = [apply_cn_id, 0]
+        current_negative_connection = [apply_cn_id, 1]
+
+    assembler.workflow[ksampler_id]['inputs']['positive'] = current_positive_connection
+    assembler.workflow[ksampler_id]['inputs']['negative'] = current_negative_connection
+    print(f"ControlNet injector applied. KSampler inputs redirected through {len(chain_items)} ControlNet node(s).")

chain_injectors/diffsynth_controlnet_injector.py

@@ -1,75 +0,0 @@
-def inject(assembler, chain_definition, chain_items):
-    if not chain_items:
-        return
-
-    model_sampler_name = chain_definition.get('model_sampler_node')
-    ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
-    
-    target_node_id = None
-    target_input_name = 'model'
-    
-    if model_sampler_name and model_sampler_name in assembler.node_map:
-        model_sampler_id = assembler.node_map[model_sampler_name]
-        if target_input_name in assembler.workflow[model_sampler_id]['inputs']:
-            target_node_id = model_sampler_id
-            print(f"ControlNet Model Patch injector targeting ModelSamplingAuraFlow node '{model_sampler_name}'.")
-
-    if not target_node_id:
-        if ksampler_name in assembler.node_map:
-            ksampler_id = assembler.node_map[ksampler_name]
-            if target_input_name in assembler.workflow[ksampler_id]['inputs']:
-                target_node_id = ksampler_id
-                print(f"ControlNet Model Patch injector targeting KSampler node '{ksampler_name}'.")
-        else:
-            print(f"Warning: Neither ModelSamplingAuraFlow node '{model_sampler_name}' nor KSampler node '{ksampler_name}' found for ControlNet patch chain. Skipping.")
-            return
-            
-    if not target_node_id:
-        print(f"Warning: Could not find a valid 'model' input on target nodes. Skipping ControlNet patch chain.")
-        return
-
-    current_model_connection = assembler.workflow[target_node_id]['inputs'][target_input_name]
-    
-    vae_source_str = chain_definition.get('vae_source')
-    vae_connection = None
-    if vae_source_str:
-        try:
-            vae_node_name, vae_idx_str = vae_source_str.split(':')
-            if vae_node_name in assembler.node_map:
-                vae_connection = [assembler.node_map[vae_node_name], int(vae_idx_str)]
-            else:
-                print(f"Warning: VAE source node '{vae_node_name}' not found for ControlNet patch chain. VAE will not be connected.")
-        except ValueError:
-            print(f"Warning: Invalid 'vae_source' format '{vae_source_str}' for ControlNet patch chain. Expected 'node_name:index'. VAE will not be connected.")
-    else:
-        print(f"Warning: 'vae_source' not defined for ControlNet patch chain definition. VAE may not be connected.")
-
-    for item_data in chain_items:
-        patch_loader_id = assembler._get_unique_id()
-        patch_loader_node = assembler._get_node_template("ModelPatchLoader")
-        patch_loader_node['inputs']['name'] = item_data['control_net_name']
-        assembler.workflow[patch_loader_id] = patch_loader_node
-
-        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
-
-        apply_cn_id = assembler._get_unique_id()
-        apply_cn_node = assembler._get_node_template(chain_definition['template'])
-        
-        apply_cn_node['inputs']['strength'] = item_data.get('strength', 1.0)
-        apply_cn_node['inputs']['model'] = current_model_connection
-        apply_cn_node['inputs']['model_patch'] = [patch_loader_id, 0]
-        apply_cn_node['inputs']['image'] = [image_loader_id, 0]
-        
-        if 'vae' in apply_cn_node['inputs'] and vae_connection:
-            apply_cn_node['inputs']['vae'] = vae_connection
-        
-        assembler.workflow[apply_cn_id] = apply_cn_node
-
-        current_model_connection = [apply_cn_id, 0]
-
-    assembler.workflow[target_node_id]['inputs'][target_input_name] = current_model_connection
-    
-    print(f"ControlNet Model Patch injector applied. Target 'model' input re-routed through {len(chain_items)} patch(es).")

chain_injectors/krea2_controlnet_injector.py

@@ -1,78 +0,0 @@
-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: Target node '{ksampler_name}' for Krea2 ControlNet chain not found. 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.")
-        return
-
-    vae_source_str = chain_definition.get('vae_source')
-    vae_connection = None
-    if vae_source_str:
-        vae_node_name, vae_idx_str = vae_source_str.split(':')
-        if vae_node_name in assembler.node_map:
-            vae_connection = [assembler.node_map[vae_node_name], int(vae_idx_str)]
-            
-    latent_connection = assembler.workflow[ksampler_id]['inputs'].get('latent_image')
-    if not latent_connection:
-        print(f"Warning: KSampler node '{ksampler_name}' is missing 'latent_image' input. Krea2 ControlNet requires it. Skipping.")
-        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
-
-        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
-        image_scaler_node['inputs']['resolution_steps'] = 1
-        assembler.workflow[image_scaler_id] = image_scaler_node
-
-        lora_loader_id = assembler._get_unique_id()
-        lora_loader_node = assembler._get_node_template("Krea2ControlLoRALoader")
-        lora_loader_node['inputs']['lora_name'] = item_data['control_net_name']
-        lora_loader_node['inputs']['strength'] = item_data.get('strength', 1.0)
-        lora_loader_node['inputs']['model'] = current_model_connection
-        assembler.workflow[lora_loader_id] = lora_loader_node
-
-        img_encode_id = assembler._get_unique_id()
-        img_encode_node = assembler._get_node_template("Krea2ControlImageEncode")
-        img_encode_node['inputs']['resize'] = "match_latent_size"
-        img_encode_node['inputs']['upscale_method'] = "lanczos"
-        img_encode_node['inputs']['crop'] = "center"
-        img_encode_node['inputs']['channel_mode'] = "rgb"
-        img_encode_node['inputs']['normalize'] = "none"
-        img_encode_node['inputs']['invert'] = False
-        img_encode_node['inputs']['batch_mode'] = "independent_images"
-        img_encode_node['inputs']['control_image'] = [image_scaler_id, 0]
-        if vae_connection:
-            img_encode_node['inputs']['vae'] = vae_connection
-        if latent_connection:
-            img_encode_node['inputs']['latent'] = latent_connection
-        assembler.workflow[img_encode_id] = img_encode_node
-
-        apply_cn_id = assembler._get_unique_id()
-        apply_cn_node = assembler._get_node_template("Krea2ControlApply")
-        apply_cn_node['inputs']['model'] = [lora_loader_id, 0]
-        apply_cn_node['inputs']['control_latent'] = [img_encode_id, 0]
-        
-        assembler.workflow[apply_cn_id] = apply_cn_node
-
-        current_model_connection = [apply_cn_id, 0]
-
-    assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
-    
-    print(f"Krea2 ControlNet injector applied. KSampler model input redirected through {len(chain_items)} Krea2 ControlNet nodes.")

comfy_integration/setup.py

@@ -25,6 +25,13 @@ def initialize_comfyui():
     else:
         print("✅ ComfyUI repository already exists.")
 
+    try:
+        print("--- [Setup] Applying PR #16519 for ComfyUI (Qwen-Image 2.1 Fun ControlNet) ---")
+        os.system(f"git -C {COMFYUI_TEMP_DIR} fetch --depth 1 origin pull/16519/head && git -c user.name=dev -c user.email=dev@example.com -C {COMFYUI_TEMP_DIR} merge --no-edit FETCH_HEAD || git -C {COMFYUI_TEMP_DIR} checkout -f FETCH_HEAD")
+        print("✅ Successfully applied PR #16519.")
+    except Exception as e:
+        print(f"⚠️ Warning: Could not apply PR #16519 for ComfyUI: {e}")
+
     print(f"--- Merging ComfyUI from '{COMFYUI_TEMP_DIR}' to '{APP_DIR}' ---")
     for item in os.listdir(COMFYUI_TEMP_DIR):
         src_path = os.path.join(COMFYUI_TEMP_DIR, item)

core/pipelines/pipeline_input_processor.py

@@ -184,55 +184,6 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
                     "image": os.path.basename(cn_temp_path), "strength": cn_strengths[i],
                     "start_percent": 0.0, "end_percent": 1.0, "control_net_name": cn_filepaths[i]
                 })
-    
-    anima_controlnet_lllite_data = ui_inputs.get('anima_controlnet_lllite_data', [])
-    active_anima_controlnets = []
-    if 'anima_controlnet_lllite' in enabled_chains and anima_controlnet_lllite_data:
-        (cn_images, _, _, cn_strengths, cn_filepaths, cn_starts, cn_ends) = [anima_controlnet_lllite_data[i::7] for i in range(7)]
-        for i in range(len(cn_images)):
-            if cn_images[i] and cn_strengths[i] > 0 and cn_filepaths[i] and cn_filepaths[i] != "None":
-                _ensure_model_downloaded(cn_filepaths[i], progress)
-                if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
-                cn_temp_path = os.path.join(INPUT_DIR, f"temp_anima_cn_{i}_{random.randint(1000, 9999)}.png")
-                cn_images[i].save(cn_temp_path, "PNG")
-                temp_files_to_clean.append(cn_temp_path)
-                active_anima_controlnets.append({
-                    "image": os.path.basename(cn_temp_path), "strength": cn_strengths[i],
-                    "start_percent": cn_starts[i], "end_percent": cn_ends[i], "control_net_name": cn_filepaths[i]
-                })
-
-    diffsynth_controlnet_data = ui_inputs.get('diffsynth_controlnet_data', [])
-    active_diffsynth_controlnets = []
-    if 'diffsynth_controlnet' in enabled_chains and diffsynth_controlnet_data:
-        (cn_images, _, _, cn_strengths, cn_filepaths) = [diffsynth_controlnet_data[i::5] for i in range(5)]
-        for i in range(len(cn_images)):
-            if cn_images[i] and cn_strengths[i] > 0 and cn_filepaths[i] and cn_filepaths[i] != "None":
-                ensure_controlnet_model_downloaded(cn_filepaths[i], progress)
-                if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
-                cn_temp_path = os.path.join(INPUT_DIR, f"temp_diffsynth_cn_{i}_{random.randint(1000, 9999)}.png")
-                cn_images[i].save(cn_temp_path, "PNG")
-                temp_files_to_clean.append(cn_temp_path)
-                active_diffsynth_controlnets.append({
-                    "image": os.path.basename(cn_temp_path), "strength": cn_strengths[i],
-                    "control_net_name": cn_filepaths[i]
-                })
-                
-    krea2_controlnet_data = ui_inputs.get('krea2_controlnet_data', [])
-    active_krea2_controlnets = []
-    if 'krea2_controlnet' in enabled_chains and krea2_controlnet_data:
-        (cn_images, _, _, cn_strengths, cn_filepaths) = [krea2_controlnet_data[i::5] for i in range(5)]
-        for i in range(len(cn_images)):
-            if cn_images[i] and cn_strengths[i] > 0 and cn_filepaths[i] and cn_filepaths[i] != "None":
-                ensure_controlnet_model_downloaded(cn_filepaths[i], progress)
-                if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
-                cn_temp_path = os.path.join(INPUT_DIR, f"temp_krea2_cn_{i}_{random.randint(1000, 9999)}.png")
-                cn_images[i].save(cn_temp_path, "PNG")
-                temp_files_to_clean.append(cn_temp_path)
-                active_krea2_controlnets.append({
-                    "image": os.path.basename(cn_temp_path), "strength": cn_strengths[i],
-                    "control_net_name": cn_filepaths[i]
-                })
-    
     ipadapter_data = ui_inputs.get('ipadapter_data', [])
     active_ipadapters = []
     if 'ipadapter' in enabled_chains and ipadapter_data:
@@ -483,9 +434,6 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
         "active_loras_for_gpu": active_loras_for_gpu,
         "active_loras_for_meta": active_loras_for_meta,
         "active_controlnets": active_controlnets,
-        "active_anima_controlnets": active_anima_controlnets,
-        "active_diffsynth_controlnets": active_diffsynth_controlnets,
-        "active_krea2_controlnets": active_krea2_controlnets,
         "active_ipadapters": active_ipadapters,
         "active_flux1_ipadapters": active_flux1_ipadapters,
         "active_sd3_ipadapters": active_sd3_ipadapters,

core/pipelines/sd_image_pipeline.py

@@ -106,9 +106,6 @@ class SdImagePipeline(BasePipeline):
             active_loras_for_gpu = processed["active_loras_for_gpu"]
             active_loras_for_meta = processed["active_loras_for_meta"]
             active_controlnets = processed["active_controlnets"]
-            active_anima_controlnets = processed["active_anima_controlnets"]
-            active_diffsynth_controlnets = processed["active_diffsynth_controlnets"]
-            active_krea2_controlnets = processed.get("active_krea2_controlnets", [])
             active_ipadapters = processed["active_ipadapters"]
             active_flux1_ipadapters = processed["active_flux1_ipadapters"]
             active_sd3_ipadapters = processed["active_sd3_ipadapters"]
@@ -167,10 +164,7 @@ class SdImagePipeline(BasePipeline):
                 "denoise": ui_inputs['denoise'],
                 "vae_name": ui_inputs.get('vae_name') if 'vae' in enabled_chains else None,
                 "lora_chain": active_loras_for_gpu,
-                "controlnet_chain": active_controlnets if not active_anima_controlnets else [],
-                "anima_controlnet_lllite_chain": active_anima_controlnets,
-                "diffsynth_controlnet_chain": active_diffsynth_controlnets,
-                "krea2_controlnet_chain": active_krea2_controlnets,
+                "controlnet_chain": active_controlnets,
                 "ipadapter_chain": active_ipadapters,
                 "flux1_ipadapter_chain": active_flux1_ipadapters,
                 "sd3_ipadapter_chain": active_sd3_ipadapters,

core/pipelines/workflow_recipes/_partials/conditioning/anima-3.8b-v1.1.yaml

@@ -58,8 +58,9 @@ dynamic_lora_chains:
       "model": ["ksampler:model", "pos_prompt:model", "neg_prompt:model"]
       "clip": ["pos_prompt:native_clip", "neg_prompt:native_clip"]
 
-dynamic_anima_controlnet_lllite_chains:
-  anima_controlnet_lllite_chain:
+dynamic_controlnet_chains:
+  controlnet_chain:
+    template: "AnimaLLLiteApply"
     ksampler_node: "ksampler"
 
 dynamic_conditioning_chains:

core/pipelines/workflow_recipes/_partials/conditioning/anima-3.8b.yaml

@@ -59,8 +59,9 @@ dynamic_lora_chains:
       "model": ["ksampler:model", "unified_prompt:model"]
       "clip": ["unified_prompt:native_clip", "neg_prompt:clip"]
 
-dynamic_anima_controlnet_lllite_chains:
-  anima_controlnet_lllite_chain:
+dynamic_controlnet_chains:
+  controlnet_chain:
+    template: "AnimaLLLiteApply"
     ksampler_node: "ksampler"
 
 dynamic_conditioning_chains:

core/pipelines/workflow_recipes/_partials/conditioning/anima.yaml

@@ -49,8 +49,9 @@ dynamic_lora_chains:
       "model": ["ksampler:model"]
       "clip": ["pos_prompt:clip", "neg_prompt:clip"]
 
-dynamic_anima_controlnet_lllite_chains:
-  anima_controlnet_lllite_chain:
+dynamic_controlnet_chains:
+  controlnet_chain:
+    template: "AnimaLLLiteApply"
     ksampler_node: "ksampler"
 
 dynamic_conditioning_chains:

core/pipelines/workflow_recipes/_partials/conditioning/krea-2.yaml

@@ -49,8 +49,9 @@ dynamic_lora_chains:
       "model": ["ksampler:model"]
       "clip": ["pos_prompt:clip", "neg_prompt:clip"]
 
-dynamic_krea2_controlnet_chains:
-  krea2_controlnet_chain:
+dynamic_controlnet_chains:
+  controlnet_chain:
+    template: "Krea2ControlApply"
     ksampler_node: "ksampler"
     vae_source: "vae_loader:0"
 

core/pipelines/workflow_recipes/_partials/conditioning/qwen-image-2.1.yaml

@@ -51,7 +51,7 @@ dynamic_lora_chains:
 
 dynamic_controlnet_chains:
   controlnet_chain:
-    template: "ControlNetApplyAdvanced"
+    template: "QwenImage21FunControlNetApply"
     ksampler_node: "ksampler"
     vae_source: "vae_loader:0"
 

core/pipelines/workflow_recipes/_partials/conditioning/sd15.yaml

@@ -50,6 +50,7 @@ dynamic_controlnet_chains:
     template: "ControlNetApplyAdvanced"
     ksampler_node: "ksampler"
     vae_source: "ckpt_loader:2"
+    megapixels: 0.75
 
 dynamic_ipadapter_chains:
   ipadapter_chain:

core/pipelines/workflow_recipes/_partials/conditioning/z-image.yaml

@@ -58,8 +58,8 @@ dynamic_lora_chains:
       "model": ["model_sampler:model"]
       "clip": ["pos_prompt:clip", "neg_prompt:clip"]
 
-dynamic_diffsynth_controlnet_chains:
-  diffsynth_controlnet_chain:
+dynamic_controlnet_chains:
+  controlnet_chain:
     template: "QwenImageDiffsynthControlnet"
     model_sampler_node: "model_sampler"
     ksampler_node: "ksampler"

mcp_tools/common.py

@@ -421,7 +421,6 @@ def _execute_imagegen_pipeline(task_id: str, params: dict):
             lora_data = []
             embedding_data = []
             controlnet_data = []
-            diffsynth_controlnet_data = []
             ipadapter_data = []
             ipadapter_images = []
             ipadapter_weights = []
@@ -442,8 +441,6 @@ def _execute_imagegen_pipeline(task_id: str, params: dict):
             style_strengths = []
             krea2_identity_edit_data = []
             krea2_reference_edit_data = []
-            krea2_controlnet_data = []
-            anima_controlnet_lllite_data = []
             reference_latent_data = []
             reference_image_data = []
             joyai_reference_data = []
@@ -531,18 +528,18 @@ def _execute_imagegen_pipeline(task_id: str, params: dict):
                         cn_strength,
                         cn_filepath
                     ])
-                elif itype == "anima_controlnet_lllite":
+                elif itype in ("anima_controlnet_lllite", "diffsynth_controlnet", "krea2_controlnet"):
+                    arch_key = "Anima" if itype == "anima_controlnet_lllite" else ("Z-Image" if itype == "diffsynth_controlnet" else "Krea-2")
                     cn_type = item.get("type", item.get("Type", ""))
                     cn_series = item.get("series", item.get("Series", ""))
                     cn_strength = float(item.get("strength", 1.0))
-                    cn_start = float(item.get("start_percent", 0.0))
-                    cn_end = float(item.get("end_percent", 1.0))
                     cn_img = _parse_image_param(item.get("image"))
 
                     cn_filepath = item.get("control_net_name", "None")
-                    anima_cfg = _load_yaml(os.path.join(_YAML_DIR, "anima_controlnet_lllite_models.yaml")).get("Anima_ControlNet_Lllite", [])
-                    if anima_cfg:
-                        for entry in anima_cfg:
+                    cn_all = _load_yaml(os.path.join(_YAML_DIR, "controlnet_models.yaml")).get("ControlNet", {})
+                    legacy_cfg = cn_all.get(arch_key, [])
+                    if legacy_cfg:
+                        for entry in legacy_cfg:
                             entry_types = entry.get("Type", [])
                             if isinstance(entry_types, str):
                                 entry_types = [entry_types]
@@ -555,68 +552,7 @@ def _execute_imagegen_pipeline(task_id: str, params: dict):
                                         cn_type = entry_types[0]
                                     break
 
-                    anima_controlnet_lllite_data.extend([
-                        cn_img,
-                        cn_type,
-                        cn_series,
-                        cn_strength,
-                        cn_filepath,
-                        cn_start,
-                        cn_end
-                    ])
-                elif itype == "diffsynth_controlnet":
-                    cn_type = item.get("type", "")
-                    cn_series = item.get("series", "")
-                    cn_strength = float(item.get("strength", 1.0))
-                    cn_img = _parse_image_param(item.get("image"))
-                    
-                    cn_filepath = "None"
-                    diffsynth_raw = _load_yaml(os.path.join(_YAML_DIR, "diffsynth_controlnet_models.yaml")).get("DiffSynth_ControlNet", {})
-                    diffsynth_entries = []
-                    if isinstance(diffsynth_raw, dict):
-                        for val in diffsynth_raw.values():
-                            if isinstance(val, list):
-                                diffsynth_entries.extend(val)
-                            elif isinstance(val, dict):
-                                diffsynth_entries.append(val)
-                    elif isinstance(diffsynth_raw, list):
-                        diffsynth_entries = diffsynth_raw
-
-                    if diffsynth_entries:
-                        for entry in diffsynth_entries:
-                            if not cn_type or cn_type in entry.get("Type", []):
-                                if not cn_series or entry.get("Series") == cn_series:
-                                    cn_filepath = entry.get("Filepath", cn_filepath)
-                                    if not cn_series:
-                                        cn_series = entry.get("Series", cn_series)
-                                    if not cn_type and entry.get("Type"):
-                                        cn_type = entry.get("Type")[0]
-                                    break
-
-                    diffsynth_controlnet_data.extend([
-                        cn_img,
-                        cn_type,
-                        cn_series,
-                        cn_strength,
-                        cn_filepath
-                    ])
-                elif itype == "krea2_controlnet":
-                    cn_type = item.get("type", "Depth")
-                    cn_series = item.get("series", "Patil")
-                    cn_strength = float(item.get("strength", 1.0))
-                    cn_img = _parse_image_param(item.get("image"))
-                    
-                    cn_filepath = "depth-control-lora.safetensors"
-                    krea2_cfg = _load_yaml(os.path.join(_YAML_DIR, "krea2_controlnet_models.yaml")).get("Krea2_ControlNet", [])
-                    if krea2_cfg:
-                        for entry in krea2_cfg:
-                            if cn_type in entry.get("Type", []):
-                                if not cn_series or entry.get("Series") == cn_series:
-                                    cn_filepath = entry.get("Filepath", cn_filepath)
-                                    cn_series = entry.get("Series", cn_series)
-                                    break
-                    
-                    krea2_controlnet_data.extend([
+                    controlnet_data.extend([
                         cn_img,
                         cn_type,
                         cn_series,
@@ -734,9 +670,7 @@ def _execute_imagegen_pipeline(task_id: str, params: dict):
             if lora_data: ui_inputs["lora_data"] = lora_data
             if embedding_data: ui_inputs["embedding_data"] = embedding_data
             if controlnet_data: ui_inputs["controlnet_data"] = controlnet_data
-            if anima_controlnet_lllite_data: ui_inputs["anima_controlnet_lllite_data"] = anima_controlnet_lllite_data
-            if diffsynth_controlnet_data: ui_inputs["diffsynth_controlnet_data"] = diffsynth_controlnet_data
-            if krea2_controlnet_data: ui_inputs["krea2_controlnet_data"] = krea2_controlnet_data
+
             if ipadapter_images:
                 preset = ipadapter_global_preset or "STANDARD (medium strength)"
                 embeds_scaling = ipadapter_global_embeds_scaling or "V only"

mcp_tools/get_feature_list.py

@@ -22,11 +22,11 @@ def _get_default_example_chain_item(chain_name: str, chain_data: dict) -> dict:
             "weight": 1.0,
             "preset": "STANDARD (medium strength)",
         }
-    elif chain_name in ("controlnet", "diffsynth_controlnet", "krea2_controlnet", "anima_controlnet_lllite"):
+    elif chain_name == "controlnet":
         return {
-            "injector_type": chain_name,
+            "injector_type": "controlnet",
             "type": "Depth",
-            "series": "SDXL" if chain_name == "controlnet" else "Patil",
+            "series": "SDXL",
             "image": "https://example.com/control_depth_map.png",
             "strength": 1.0,
         }
@@ -122,14 +122,9 @@ def _build_feature_entry(chain_name: str, chain_data: dict, task_features: dict
     }
     if include_schema:
         schema = deepcopy(chain_data.get("parameters_schema", {}))
-        if chain_name in ("krea2_controlnet", "diffsynth_controlnet", "controlnet", "anima_controlnet_lllite"):
-            config_key = (
-                "Krea2_ControlNet" if chain_name == "krea2_controlnet"
-                else "DiffSynth_ControlNet" if chain_name == "diffsynth_controlnet"
-                else "Anima_ControlNet_Lllite" if chain_name == "anima_controlnet_lllite"
-                else "ControlNet"
-            )
-            yaml_filename = f"{chain_name}_models.yaml"
+        if chain_name == "controlnet":
+            config_key = "ControlNet"
+            yaml_filename = "controlnet_models.yaml"
             model_path = os.path.join(_YAML_DIR, yaml_filename)
             raw_models = _load_yaml(model_path).get(config_key, [])
             models_list = []

ui/events/__init__.py

@@ -2,11 +2,5 @@ from .main import attach_event_handlers
 from .config_loaders import (
     load_controlnet_config,
     get_cn_defaults,
-    load_anima_controlnet_lllite_config,
-    get_anima_cn_defaults,
-    load_diffsynth_controlnet_config,
-    get_diffsynth_cn_defaults,
-    load_krea2_controlnet_config,
-    get_krea2_cn_defaults,
     load_ipadapter_config
 )

ui/events/chain_handlers.py

@@ -10,9 +10,6 @@ from ui.shared.ui_components import (
 )
 from .config_loaders import (
     load_controlnet_config,
-    load_anima_controlnet_lllite_config,
-    load_diffsynth_controlnet_config,
-    load_krea2_controlnet_config,
     load_ipadapter_config
 )
 
@@ -201,302 +198,6 @@ def create_controlnet_event_handlers(prefix, ui_components):
     )
 
 
-def create_krea2_controlnet_event_handlers(prefix, ui_components):
-    cn_rows = ui_components.get(f'krea2_controlnet_rows_{prefix}')
-    if not cn_rows: return
-    cn_types = ui_components[f'krea2_controlnet_types_{prefix}']
-    cn_series = ui_components[f'krea2_controlnet_series_{prefix}']
-    cn_filepaths = ui_components[f'krea2_controlnet_filepaths_{prefix}']
-    cn_images = ui_components[f'krea2_controlnet_images_{prefix}']
-    cn_strengths = ui_components[f'krea2_controlnet_strengths_{prefix}']
-    
-    count_state = ui_components[f'krea2_controlnet_count_state_{prefix}']
-    add_button = ui_components[f'add_krea2_controlnet_button_{prefix}']
-    del_button = ui_components[f'delete_krea2_controlnet_button_{prefix}']
-    accordion = ui_components[f'krea2_controlnet_accordion_{prefix}']
-
-    def add_cn_row(c):
-        c += 1
-        updates = {
-            count_state: c,
-            cn_rows[c-1]: gr.update(visible=True),
-            add_button: gr.update(visible=c < MAX_CONTROLNETS),
-            del_button: gr.update(visible=True)
-        }
-        return updates
-
-    def del_cn_row(c):
-        c -= 1
-        updates = {
-            count_state: c,
-            cn_rows[c]: gr.update(visible=False),
-            cn_images[c]: None,
-            cn_strengths[c]: 1.0,
-            add_button: gr.update(visible=True),
-            del_button: gr.update(visible=c > 0)
-        }
-        return updates
-        
-    add_outputs = [count_state, add_button, del_button] + cn_rows
-    del_outputs = [count_state, add_button, del_button] + cn_rows + cn_images + cn_strengths
-    add_button.click(fn=add_cn_row, inputs=[count_state], outputs=add_outputs, show_progress=False)
-    del_button.click(fn=del_cn_row, inputs=[count_state], outputs=del_outputs, show_progress=False)
-    
-    def on_cn_type_change(selected_type):
-        cn_config = load_krea2_controlnet_config()
-        series_choices = []
-        if selected_type:
-            series_choices = sorted(list(set(
-                model.get("Series", "Default") for model in cn_config
-                if selected_type in model.get("Type", [])
-            )))
-        default_series = series_choices[0] if series_choices else None
-        filepath = "None"
-        if default_series:
-            for model in cn_config:
-                if model.get("Series") == default_series and selected_type in model.get("Type", []):
-                    filepath = model.get("Filepath")
-                    break
-        return gr.update(choices=series_choices, value=default_series), filepath
-
-    def on_cn_series_change(selected_series, selected_type):
-        cn_config = load_krea2_controlnet_config()
-        filepath = "None"
-        if selected_series and selected_type:
-            for model in cn_config:
-                if model.get("Series") == selected_series and selected_type in model.get("Type", []):
-                    filepath = model.get("Filepath")
-                    break
-        return filepath
-        
-    for i in range(MAX_CONTROLNETS):
-        cn_types[i].change(
-            fn=on_cn_type_change,
-            inputs=[cn_types[i]],
-            outputs=[cn_series[i], cn_filepaths[i]],
-            show_progress=False
-        )
-        cn_series[i].change(
-            fn=on_cn_series_change,
-            inputs=[cn_series[i], cn_types[i]],
-            outputs=[cn_filepaths[i]],
-            show_progress=False
-        )
-
-    def on_accordion_expand(*images):
-        return [gr.update() for _ in images]
-    
-    accordion.expand(
-        fn=on_accordion_expand,
-        inputs=cn_images,
-        outputs=cn_images,
-        show_progress=False
-    )
-
-
-def create_anima_controlnet_lllite_event_handlers(prefix, ui_components):
-    cn_rows = ui_components.get(f'anima_controlnet_lllite_rows_{prefix}')
-    if not cn_rows: return
-    cn_types = ui_components[f'anima_controlnet_lllite_types_{prefix}']
-    cn_series = ui_components[f'anima_controlnet_lllite_series_{prefix}']
-    cn_filepaths = ui_components[f'anima_controlnet_lllite_filepaths_{prefix}']
-    cn_images = ui_components[f'anima_controlnet_lllite_images_{prefix}']
-    cn_strengths = ui_components[f'anima_controlnet_lllite_strengths_{prefix}']
-    
-    count_state = ui_components[f'anima_controlnet_lllite_count_state_{prefix}']
-    add_button = ui_components[f'add_anima_controlnet_lllite_button_{prefix}']
-    del_button = ui_components[f'delete_anima_controlnet_lllite_button_{prefix}']
-    accordion = ui_components[f'anima_controlnet_lllite_accordion_{prefix}']
-
-    def add_cn_row(c):
-        c += 1
-        updates = {
-            count_state: c,
-            cn_rows[c-1]: gr.update(visible=True),
-            add_button: gr.update(visible=c < MAX_CONTROLNETS),
-            del_button: gr.update(visible=True)
-        }
-        return updates
-
-    def del_cn_row(c):
-        c -= 1
-        updates = {
-            count_state: c,
-            cn_rows[c]: gr.update(visible=False),
-            cn_images[c]: None,
-            cn_strengths[c]: 1.0,
-            add_button: gr.update(visible=True),
-            del_button: gr.update(visible=c > 0)
-        }
-        return updates
-        
-    add_outputs = [count_state, add_button, del_button] + cn_rows
-    del_outputs = [count_state, add_button, del_button] + cn_rows + cn_images + cn_strengths
-    add_button.click(fn=add_cn_row, inputs=[count_state], outputs=add_outputs, show_progress=False)
-    del_button.click(fn=del_cn_row, inputs=[count_state], outputs=del_outputs, show_progress=False)
-    
-    def on_cn_type_change(selected_type):
-        cn_config = load_anima_controlnet_lllite_config()
-        series_choices = []
-        if selected_type:
-            series_choices = sorted(list(set(
-                model.get("Series", "Default") for model in cn_config
-                if selected_type in model.get("Type", [])
-            )))
-        default_series = series_choices[0] if series_choices else None
-        filepath = "None"
-        if default_series:
-            for model in cn_config:
-                if model.get("Series") == default_series and selected_type in model.get("Type", []):
-                    filepath = model.get("Filepath")
-                    break
-        return gr.update(choices=series_choices, value=default_series), filepath
-
-    def on_cn_series_change(selected_series, selected_type):
-        cn_config = load_anima_controlnet_lllite_config()
-        filepath = "None"
-        if selected_series and selected_type:
-            for model in cn_config:
-                if model.get("Series") == selected_series and selected_type in model.get("Type", []):
-                    filepath = model.get("Filepath")
-                    break
-        return filepath
-        
-    for i in range(MAX_CONTROLNETS):
-        cn_types[i].change(
-            fn=on_cn_type_change,
-            inputs=[cn_types[i]],
-            outputs=[cn_series[i], cn_filepaths[i]],
-            show_progress=False
-        )
-        cn_series[i].change(
-            fn=on_cn_series_change,
-            inputs=[cn_series[i], cn_types[i]],
-            outputs=[cn_filepaths[i]],
-            show_progress=False
-        )
-
-    def on_accordion_expand(*images):
-        return [gr.update() for _ in images]
-    
-    accordion.expand(
-        fn=on_accordion_expand,
-        inputs=cn_images,
-        outputs=cn_images,
-        show_progress=False
-    )
-
-
-def create_diffsynth_controlnet_event_handlers(prefix, ui_components):
-    cn_rows = ui_components.get(f'diffsynth_controlnet_rows_{prefix}')
-    if not cn_rows: return
-    cn_types = ui_components[f'diffsynth_controlnet_types_{prefix}']
-    cn_series = ui_components[f'diffsynth_controlnet_series_{prefix}']
-    cn_filepaths = ui_components[f'diffsynth_controlnet_filepaths_{prefix}']
-    cn_images = ui_components[f'diffsynth_controlnet_images_{prefix}']
-    cn_strengths = ui_components[f'diffsynth_controlnet_strengths_{prefix}']
-    
-    count_state = ui_components[f'diffsynth_controlnet_count_state_{prefix}']
-    add_button = ui_components[f'add_diffsynth_controlnet_button_{prefix}']
-    del_button = ui_components[f'delete_diffsynth_controlnet_button_{prefix}']
-    accordion = ui_components[f'diffsynth_controlnet_accordion_{prefix}']
-
-    base_model_comp = ui_components.get(f'base_model_{prefix}')
-    actual_arch_comp = base_model_comp if base_model_comp else gr.State("SDXL")
-
-    def add_cn_row(c):
-        c += 1
-        updates = {
-            count_state: c,
-            cn_rows[c-1]: gr.update(visible=True),
-            add_button: gr.update(visible=c < MAX_CONTROLNETS),
-            del_button: gr.update(visible=True)
-        }
-        return updates
-
-    def del_cn_row(c):
-        c -= 1
-        updates = {
-            count_state: c,
-            cn_rows[c]: gr.update(visible=False),
-            cn_images[c]: None,
-            cn_strengths[c]: 1.0,
-            add_button: gr.update(visible=True),
-            del_button: gr.update(visible=c > 0)
-        }
-        return updates
-        
-    add_outputs = [count_state, add_button, del_button] + cn_rows
-    del_outputs = [count_state, add_button, del_button] + cn_rows + cn_images + cn_strengths
-    add_button.click(fn=add_cn_row, inputs=[count_state], outputs=add_outputs, show_progress=False)
-    del_button.click(fn=del_cn_row, inputs=[count_state], outputs=del_outputs, show_progress=False)
-    
-    def on_cn_type_change(selected_type, model_name):
-        from core.settings import MODEL_TYPE_MAP
-        m_type = MODEL_TYPE_MAP.get(model_name, "SDXL") if model_name else "SDXL"
-        cn_full_config = load_diffsynth_controlnet_config()
-        
-        architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
-        controlnet_key = architectures_dict.get(m_type, {}).get("controlnet_key", m_type)
-
-        cn_config = cn_full_config.get(controlnet_key, [])
-        series_choices = []
-        if selected_type:
-            series_choices = sorted(list(set(
-                model.get("Series", "Default") for model in cn_config
-                if selected_type in model.get("Type", [])
-            )))
-        default_series = series_choices[0] if series_choices else None
-        filepath = "None"
-        if default_series:
-            for model in cn_config:
-                if model.get("Series") == default_series and selected_type in model.get("Type", []):
-                    filepath = model.get("Filepath")
-                    break
-        return gr.update(choices=series_choices, value=default_series), filepath
-
-    def on_cn_series_change(selected_series, selected_type, model_name):
-        from core.settings import MODEL_TYPE_MAP
-        m_type = MODEL_TYPE_MAP.get(model_name, "SDXL") if model_name else "SDXL"
-        cn_full_config = load_diffsynth_controlnet_config()
-        
-        architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
-        controlnet_key = architectures_dict.get(m_type, {}).get("controlnet_key", m_type)
-
-        cn_config = cn_full_config.get(controlnet_key, [])
-        filepath = "None"
-        if selected_series and selected_type:
-            for model in cn_config:
-                if model.get("Series") == selected_series and selected_type in model.get("Type", []):
-                    filepath = model.get("Filepath")
-                    break
-        return filepath
-        
-    for i in range(MAX_CONTROLNETS):
-        cn_types[i].change(
-            fn=on_cn_type_change,
-            inputs=[cn_types[i], actual_arch_comp],
-            outputs=[cn_series[i], cn_filepaths[i]],
-            show_progress=False
-        )
-        cn_series[i].change(
-            fn=on_cn_series_change,
-            inputs=[cn_series[i], cn_types[i], actual_arch_comp],
-            outputs=[cn_filepaths[i]],
-            show_progress=False
-        )
-
-    def on_accordion_expand(*images):
-        return [gr.update() for _ in images]
-    
-    accordion.expand(
-        fn=on_accordion_expand,
-        inputs=cn_images,
-        outputs=cn_images,
-        show_progress=False
-    )
-
-
 def create_flux1_ipadapter_event_handlers(prefix, ui_components):
     fipa_rows = ui_components.get(f'flux1_ipadapter_rows_{prefix}')
     if not fipa_rows: return

ui/events/change_handlers.py

@@ -12,13 +12,10 @@ from utils.app_utils import get_model_generation_defaults
 from ui.shared.ui_components import RESOLUTION_MAP
 from .config_loaders import (
     get_cn_defaults,
-    get_anima_cn_defaults,
-    get_diffsynth_cn_defaults,
-    get_krea2_cn_defaults,
     load_ipadapter_config
 )
 
-def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, krea2_cn_types, krea2_cn_series, krea2_cn_filepaths, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, krea2_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, ref_img_acc=None, sensenova_ref_acc=None, task_type=None, type_comp=None, qwen_pe_acc=None, ming_pe_acc=None):
+def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, ipa_preset, lora_acc, cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, ref_img_acc=None, sensenova_ref_acc=None, task_type=None, type_comp=None, qwen_pe_acc=None, ming_pe_acc=None):
     def update_fn(*args):
         arch = args[0]
         category = args[1]
@@ -71,9 +68,6 @@ def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types,
 
         if lora_acc: updates[lora_acc] = gr.update(visible=('lora' in enabled_chains))
         if cn_acc: updates[cn_acc] = gr.update(visible=('controlnet' in enabled_chains))
-        if anima_cn_acc: updates[anima_cn_acc] = gr.update(visible=('anima_controlnet_lllite' in enabled_chains))
-        if diffsynth_cn_acc: updates[diffsynth_cn_acc] = gr.update(visible=('diffsynth_controlnet' in enabled_chains))
-        if krea2_cn_acc: updates[krea2_cn_acc] = gr.update(visible=('krea2_controlnet' in enabled_chains))
         if ipa_acc: updates[ipa_acc] = gr.update(visible=('ipadapter' in enabled_chains))
         if flux1_ipa_acc: updates[flux1_ipa_acc] = gr.update(visible=('flux1_ipadapter' in enabled_chains))
         if sd3_ipa_acc: updates[sd3_ipa_acc] = gr.update(visible=('sd3_ipadapter' in enabled_chains))
@@ -114,29 +108,6 @@ def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types,
         for f_comp in cn_filepaths:
             updates[f_comp] = filepath
 
-        anima_all_types, anima_default_type, anima_series_choices, anima_default_series, anima_filepath = get_anima_cn_defaults()
-        for t_comp in anima_cn_types:
-            updates[t_comp] = gr.update(choices=anima_all_types, value=anima_default_type)
-        for s_comp in anima_cn_series:
-            updates[s_comp] = gr.update(choices=anima_series_choices, value=anima_default_series)
-        for f_comp in anima_cn_filepaths:
-            updates[f_comp] = anima_filepath
-            
-        diffsynth_all_types, diffsynth_default_type, diffsynth_series_choices, diffsynth_default_series, diffsynth_filepath = get_diffsynth_cn_defaults(controlnet_key)
-        for t_comp in diffsynth_cn_types:
-            updates[t_comp] = gr.update(choices=diffsynth_all_types, value=diffsynth_default_type)
-        for s_comp in diffsynth_cn_series:
-            updates[s_comp] = gr.update(choices=diffsynth_series_choices, value=diffsynth_default_series)
-        for f_comp in diffsynth_cn_filepaths:
-            updates[f_comp] = diffsynth_filepath
-
-        krea2_all_types, krea2_default_type, krea2_series_choices, krea2_default_series, krea2_filepath = get_krea2_cn_defaults()
-        for t_comp in krea2_cn_types:
-            updates[t_comp] = gr.update(choices=krea2_all_types, value=krea2_default_type)
-        for s_comp in krea2_cn_series:
-            updates[s_comp] = gr.update(choices=krea2_series_choices, value=krea2_default_series)
-        for f_comp in krea2_cn_filepaths:
-            updates[f_comp] = krea2_filepath
         
         if ipa_preset and (arch_model_type in ["sdxl", "sd15", "sd35"]):
             config = load_ipadapter_config()
@@ -159,7 +130,7 @@ def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types,
     return update_fn
 
 
-def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, krea2_cn_types, krea2_cn_series, krea2_cn_filepaths, arch_comp_ref, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, krea2_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, ref_img_acc=None, sensenova_ref_acc=None, task_type=None, type_comp=None, qwen_pe_acc=None, ming_pe_acc=None):
+def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, arch_comp_ref, ipa_preset, lora_acc, cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, ref_img_acc=None, sensenova_ref_acc=None, task_type=None, type_comp=None, qwen_pe_acc=None, ming_pe_acc=None):
     def change_fn(*args):
         model_name = args[0]
         idx = 1
@@ -220,9 +191,6 @@ def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_type
 
         if lora_acc: updates[lora_acc] = gr.update(visible=('lora' in enabled_chains))
         if cn_acc: updates[cn_acc] = gr.update(visible=('controlnet' in enabled_chains))
-        if anima_cn_acc: updates[anima_cn_acc] = gr.update(visible=('anima_controlnet_lllite' in enabled_chains))
-        if diffsynth_cn_acc: updates[diffsynth_cn_acc] = gr.update(visible=('diffsynth_controlnet' in enabled_chains))
-        if krea2_cn_acc: updates[krea2_cn_acc] = gr.update(visible=('krea2_controlnet' in enabled_chains))
         if ipa_acc: updates[ipa_acc] = gr.update(visible=('ipadapter' in enabled_chains))
         if flux1_ipa_acc: updates[flux1_ipa_acc] = gr.update(visible=('flux1_ipadapter' in enabled_chains))
         if sd3_ipa_acc: updates[sd3_ipa_acc] = gr.update(visible=('sd3_ipadapter' in enabled_chains))
@@ -262,30 +230,6 @@ def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_type
             updates[s_comp] = gr.update(choices=series_choices, value=default_series)
         for f_comp in cn_filepaths:
             updates[f_comp] = filepath
-
-        anima_all_types, anima_default_type, anima_series_choices, anima_default_series, anima_filepath = get_anima_cn_defaults()
-        for t_comp in anima_cn_types:
-            updates[t_comp] = gr.update(choices=anima_all_types, value=anima_default_type)
-        for s_comp in anima_cn_series:
-            updates[s_comp] = gr.update(choices=anima_series_choices, value=anima_default_series)
-        for f_comp in anima_cn_filepaths:
-            updates[f_comp] = anima_filepath
-            
-        diffsynth_all_types, diffsynth_default_type, diffsynth_series_choices, diffsynth_default_series, diffsynth_filepath = get_diffsynth_cn_defaults(controlnet_key)
-        for t_comp in diffsynth_cn_types:
-            updates[t_comp] = gr.update(choices=diffsynth_all_types, value=diffsynth_default_type)
-        for s_comp in diffsynth_cn_series:
-            updates[s_comp] = gr.update(choices=diffsynth_series_choices, value=diffsynth_default_series)
-        for f_comp in diffsynth_cn_filepaths:
-            updates[f_comp] = diffsynth_filepath
-
-        krea2_all_types, krea2_default_type, krea2_series_choices, krea2_default_series, krea2_filepath = get_krea2_cn_defaults()
-        for t_comp in krea2_cn_types:
-            updates[t_comp] = gr.update(choices=krea2_all_types, value=krea2_default_type)
-        for s_comp in krea2_cn_series:
-            updates[s_comp] = gr.update(choices=krea2_series_choices, value=krea2_default_series)
-        for f_comp in krea2_cn_filepaths:
-            updates[f_comp] = krea2_filepath
         
         if ipa_preset and (arch_model_type in ["sdxl", "sd15", "sd35"]):
             config = load_ipadapter_config()
@@ -315,9 +259,6 @@ def initialize_all_cn_dropdowns(ui_components):
     controlnet_key = architectures_dict.get(default_m_type, {}).get("controlnet_key", default_m_type)
     
     all_types, default_type, series_choices, default_series, filepath = get_cn_defaults(controlnet_key)
-    anima_all_types, anima_default_type, anima_series_choices, anima_default_series, anima_filepath = get_anima_cn_defaults()
-    diffsynth_all_types, diffsynth_default_type, diffsynth_series_choices, diffsynth_default_series, diffsynth_filepath = get_diffsynth_cn_defaults(controlnet_key)
-    krea2_all_types, krea2_default_type, krea2_series_choices, krea2_default_series, krea2_filepath = get_krea2_cn_defaults()
     
     updates = {}
     for prefix in ["imagegen", "txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
@@ -328,30 +269,6 @@ def initialize_all_cn_dropdowns(ui_components):
                 updates[series_dd] = gr.update(choices=series_choices, value=default_series)
             for filepath_state in ui_components[f'controlnet_filepaths_{prefix}']:
                 updates[filepath_state] = filepath
-
-        if f'anima_controlnet_lllite_types_{prefix}' in ui_components:
-            for type_dd in ui_components[f'anima_controlnet_lllite_types_{prefix}']:
-                updates[type_dd] = gr.update(choices=anima_all_types, value=anima_default_type)
-            for series_dd in ui_components[f'anima_controlnet_lllite_series_{prefix}']:
-                updates[series_dd] = gr.update(choices=anima_series_choices, value=anima_default_series)
-            for filepath_state in ui_components[f'anima_controlnet_lllite_filepaths_{prefix}']:
-                updates[filepath_state] = anima_filepath
-        
-        if f'diffsynth_controlnet_types_{prefix}' in ui_components:
-            for type_dd in ui_components[f'diffsynth_controlnet_types_{prefix}']:
-                updates[type_dd] = gr.update(choices=diffsynth_all_types, value=diffsynth_default_type)
-            for series_dd in ui_components[f'diffsynth_controlnet_series_{prefix}']:
-                updates[series_dd] = gr.update(choices=diffsynth_series_choices, value=default_series)
-            for filepath_state in ui_components[f'diffsynth_controlnet_filepaths_{prefix}']:
-                updates[filepath_state] = diffsynth_filepath
-
-        if f'krea2_controlnet_types_{prefix}' in ui_components:
-            for type_dd in ui_components[f'krea2_controlnet_types_{prefix}']:
-                updates[type_dd] = gr.update(choices=krea2_all_types, value=krea2_default_type)
-            for series_dd in ui_components[f'krea2_controlnet_series_{prefix}']:
-                updates[series_dd] = gr.update(choices=krea2_series_choices, value=krea2_default_series)
-            for filepath_state in ui_components[f'krea2_controlnet_filepaths_{prefix}']:
-                updates[filepath_state] = krea2_filepath
                 
     return updates
 

ui/events/config_loaders.py

@@ -42,117 +42,6 @@ def get_cn_defaults(arch_val):
     return all_types, default_type, series_choices, default_series, filepath
 
 
-@lru_cache(maxsize=1)
-def load_anima_controlnet_lllite_config():
-    _PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-    _CN_MODEL_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'anima_controlnet_lllite_models.yaml')
-    try:
-        print("--- Loading anima_controlnet_lllite_models.yaml ---")
-        with open(_CN_MODEL_LIST_PATH, 'r', encoding='utf-8') as f:
-            config = yaml.safe_load(f)
-        print("--- ✅ anima_controlnet_lllite_models.yaml loaded successfully ---")
-        return config.get("Anima_ControlNet_Lllite", [])
-    except Exception as e:
-        print(f"Error loading anima_controlnet_lllite_models.yaml: {e}")
-        return []
-
-
-def get_anima_cn_defaults():
-    cn_config = load_anima_controlnet_lllite_config()
-    if not cn_config:
-        return [], None, [], None, "None"
-    all_types = sorted(list(set(t for model in cn_config for t in model.get("Type", []))))
-    default_type = all_types[0] if all_types else None
-    series_choices = []
-    if default_type:
-        series_choices = sorted(list(set(model.get("Series", "Default") for model in cn_config if default_type in model.get("Type", []))))
-    default_series = series_choices[0] if series_choices else None
-    filepath = "None"
-    if default_series and default_type:
-        for model in cn_config:
-            if model.get("Series") == default_series and default_type in model.get("Type", []):
-                filepath = model.get("Filepath")
-                break
-    return all_types, default_type, series_choices, default_series, filepath
-
-
-@lru_cache(maxsize=1)
-def load_diffsynth_controlnet_config():
-    _PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-    _CN_MODEL_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'diffsynth_controlnet_models.yaml')
-    try:
-        print("--- Loading diffsynth_controlnet_models.yaml ---")
-        with open(_CN_MODEL_LIST_PATH, 'r', encoding='utf-8') as f:
-            config = yaml.safe_load(f)
-        print("--- ✅ diffsynth_controlnet_models.yaml loaded successfully ---")
-        return config.get("DiffSynth_ControlNet", {})
-    except Exception as e:
-        print(f"Error loading diffsynth_controlnet_models.yaml: {e}")
-        return {}
-
-
-def get_diffsynth_cn_defaults(arch_val):
-    cn_full_config = load_diffsynth_controlnet_config()
-    cn_config = cn_full_config.get(arch_val, [])
-    
-    if not cn_config:
-        return [], None, [], None, "None"
-        
-    all_types = sorted(list(set(t for model in cn_config for t in model.get("Type", []))))
-    default_type = all_types[0] if all_types else None
-    
-    series_choices = []
-    if default_type:
-        series_choices = sorted(list(set(model.get("Series", "Default") for model in cn_config if default_type in model.get("Type", []))))
-    default_series = series_choices[0] if series_choices else None
-    
-    filepath = "None"
-    if default_series and default_type:
-        for model in cn_config:
-            if model.get("Series") == default_series and default_type in model.get("Type", []):
-                filepath = model.get("Filepath")
-                break
-                
-    return all_types, default_type, series_choices, default_series, filepath
-
-
-@lru_cache(maxsize=1)
-def load_krea2_controlnet_config():
-    _PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
-    _CN_MODEL_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'krea2_controlnet_models.yaml')
-    try:
-        print("--- Loading krea2_controlnet_models.yaml ---")
-        with open(_CN_MODEL_LIST_PATH, 'r', encoding='utf-8') as f:
-            config = yaml.safe_load(f)
-        print("--- ✅ krea2_controlnet_models.yaml loaded successfully ---")
-        return config.get("Krea2_ControlNet", [])
-    except Exception as e:
-        print(f"Error loading krea2_controlnet_models.yaml: {e}")
-        return []
-
-def get_krea2_cn_defaults():
-    cn_config = load_krea2_controlnet_config()
-    if not cn_config:
-        return [], None, [], None, "None"
-        
-    all_types = sorted(list(set(t for model in cn_config for t in model.get("Type", []))))
-    default_type = all_types[0] if all_types else None
-    
-    series_choices = []
-    if default_type:
-        series_choices = sorted(list(set(model.get("Series", "Default") for model in cn_config if default_type in model.get("Type", []))))
-    default_series = series_choices[0] if series_choices else None
-    
-    filepath = "None"
-    if default_series and default_type:
-        for model in cn_config:
-            if model.get("Series") == default_series and default_type in model.get("Type", []):
-                filepath = model.get("Filepath")
-                break
-                
-    return all_types, default_type, series_choices, default_series, filepath
-
-
 @lru_cache(maxsize=1)
 def load_ipadapter_config():
     _PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))

ui/events/main.py

@@ -2,9 +2,6 @@ import gradio as gr
 from .chain_handlers import (
     create_lora_event_handlers,
     create_controlnet_event_handlers,
-    create_anima_controlnet_lllite_event_handlers,
-    create_diffsynth_controlnet_event_handlers,
-    create_krea2_controlnet_event_handlers,
     create_ipadapter_event_handlers,
     create_embedding_event_handlers,
     create_conditioning_event_handlers,
@@ -47,23 +44,8 @@ def attach_event_handlers(ui_components, demo):
         cn_series_list = ui_components.get(f'controlnet_series_{prefix}', [])
         cn_filepaths_list = ui_components.get(f'controlnet_filepaths_{prefix}', [])
         
-        anima_cn_types_list = ui_components.get(f'anima_controlnet_lllite_types_{prefix}', [])
-        anima_cn_series_list = ui_components.get(f'anima_controlnet_lllite_series_{prefix}', [])
-        anima_cn_filepaths_list = ui_components.get(f'anima_controlnet_lllite_filepaths_{prefix}', [])
-
-        diffsynth_cn_types_list = ui_components.get(f'diffsynth_controlnet_types_{prefix}', [])
-        diffsynth_cn_series_list = ui_components.get(f'diffsynth_controlnet_series_{prefix}', [])
-        diffsynth_cn_filepaths_list = ui_components.get(f'diffsynth_controlnet_filepaths_{prefix}', [])
-
-        krea2_cn_types_list = ui_components.get(f'krea2_controlnet_types_{prefix}', [])
-        krea2_cn_series_list = ui_components.get(f'krea2_controlnet_series_{prefix}', [])
-        krea2_cn_filepaths_list = ui_components.get(f'krea2_controlnet_filepaths_{prefix}', [])
-        
         lora_accordion = ui_components.get(f'lora_accordion_{prefix}')
         cn_accordion = ui_components.get(f'controlnet_accordion_{prefix}')
-        anima_cn_accordion = ui_components.get(f'anima_controlnet_lllite_accordion_{prefix}')
-        diffsynth_cn_accordion = ui_components.get(f'diffsynth_controlnet_accordion_{prefix}')
-        krea2_cn_accordion = ui_components.get(f'krea2_controlnet_accordion_{prefix}')
         ipa_accordion = ui_components.get(f'ipadapter_accordion_{prefix}')
         sd3_ipa_accordion = ui_components.get(f'sd3_ipadapter_accordion_{prefix}')
         flux1_ipa_accordion = ui_components.get(f'flux1_ipadapter_accordion_{prefix}')
@@ -99,14 +81,8 @@ def attach_event_handlers(ui_components, demo):
             outputs = [model_comp, cat_comp]
             if aspect_ratio_comp: outputs.append(aspect_ratio_comp)
             outputs.extend(cn_types_list + cn_series_list + cn_filepaths_list)
-            outputs.extend(anima_cn_types_list + anima_cn_series_list + anima_cn_filepaths_list)
-            outputs.extend(diffsynth_cn_types_list + diffsynth_cn_series_list + diffsynth_cn_filepaths_list)
-            outputs.extend(krea2_cn_types_list + krea2_cn_series_list + krea2_cn_filepaths_list)
             if lora_accordion: outputs.append(lora_accordion)
             if cn_accordion: outputs.append(cn_accordion)
-            if anima_cn_accordion: outputs.append(anima_cn_accordion)
-            if diffsynth_cn_accordion: outputs.append(diffsynth_cn_accordion)
-            if krea2_cn_accordion: outputs.append(krea2_cn_accordion)
             if ipa_accordion: outputs.append(ipa_accordion)
             if sd3_ipa_accordion: outputs.append(sd3_ipa_accordion)
             if flux1_ipa_accordion: outputs.append(flux1_ipa_accordion)
@@ -132,10 +108,7 @@ def attach_event_handlers(ui_components, demo):
             update_fn = make_update_fn(
                 model_comp, cat_comp, aspect_ratio_comp, width_comp, height_comp, 
                 cn_types_list, cn_series_list, cn_filepaths_list, 
-                anima_cn_types_list, anima_cn_series_list, anima_cn_filepaths_list,
-                diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list, 
-                krea2_cn_types_list, krea2_cn_series_list, krea2_cn_filepaths_list,
-                ipa_preset_list, lora_accordion, cn_accordion, anima_cn_accordion, diffsynth_cn_accordion, krea2_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
+                ipa_preset_list, lora_accordion, cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
                 ref_latent_accordion, hidream_o1_ref_accordion, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp,
                 pid_acc=pid_accordion, vae_acc=vae_accordion, joyai_ref_acc=joyai_ref_accordion, krea2_identity_edit_acc=krea2_identity_edit_accordion, krea2_reference_edit_acc=krea2_reference_edit_accordion, qwen_image_edit_acc=qwen_image_edit_accordion, ref_img_acc=ref_img_accordion, sensenova_ref_acc=sensenova_ref_accordion,
                 task_type=task_type, type_comp=type_comp, qwen_pe_acc=qwen_pe_accordion, ming_pe_acc=ming_pe_accordion
@@ -154,14 +127,8 @@ def attach_event_handlers(ui_components, demo):
             if cat_comp: outputs2.append(cat_comp)
             if aspect_ratio_comp: outputs2.append(aspect_ratio_comp)
             outputs2.extend(cn_types_list + cn_series_list + cn_filepaths_list)
-            outputs2.extend(anima_cn_types_list + anima_cn_series_list + anima_cn_filepaths_list)
-            outputs2.extend(diffsynth_cn_types_list + diffsynth_cn_series_list + diffsynth_cn_filepaths_list)
-            outputs2.extend(krea2_cn_types_list + krea2_cn_series_list + krea2_cn_filepaths_list)
             if lora_accordion: outputs2.append(lora_accordion)
             if cn_accordion: outputs2.append(cn_accordion)
-            if anima_cn_accordion: outputs2.append(anima_cn_accordion)
-            if diffsynth_cn_accordion: outputs2.append(diffsynth_cn_accordion)
-            if krea2_cn_accordion: outputs2.append(krea2_cn_accordion)
             if ipa_accordion: outputs2.append(ipa_accordion)
             if sd3_ipa_accordion: outputs2.append(sd3_ipa_accordion)
             if flux1_ipa_accordion: outputs2.append(flux1_ipa_accordion)
@@ -192,10 +159,7 @@ def attach_event_handlers(ui_components, demo):
                 change_fn = make_model_change_fn(
                     cat_comp, aspect_ratio_comp, width_comp, height_comp, 
                     cn_types_list, cn_series_list, cn_filepaths_list, 
-                    anima_cn_types_list, anima_cn_series_list, anima_cn_filepaths_list,
-                    diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list, 
-                    krea2_cn_types_list, krea2_cn_series_list, krea2_cn_filepaths_list,
-                    arch_comp, ipa_preset_list, lora_accordion, cn_accordion, anima_cn_accordion, diffsynth_cn_accordion, krea2_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
+                    arch_comp, ipa_preset_list, lora_accordion, cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
                     ref_latent_accordion, hidream_o1_ref_accordion, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp,
                     pid_acc=pid_accordion, vae_acc=vae_accordion, joyai_ref_acc=joyai_ref_accordion, krea2_identity_edit_acc=krea2_identity_edit_accordion, krea2_reference_edit_acc=krea2_reference_edit_accordion, qwen_image_edit_acc=qwen_image_edit_accordion, ref_img_acc=ref_img_accordion, sensenova_ref_acc=sensenova_ref_accordion,
                     task_type=task_type, type_comp=type_comp, qwen_pe_acc=qwen_pe_accordion, ming_pe_acc=ming_pe_accordion
@@ -206,9 +170,6 @@ def attach_event_handlers(ui_components, demo):
 
         create_lora_event_handlers(prefix, ui_components)
         create_controlnet_event_handlers(prefix, ui_components)
-        create_anima_controlnet_lllite_event_handlers(prefix, ui_components)
-        create_diffsynth_controlnet_event_handlers(prefix, ui_components)
-        create_krea2_controlnet_event_handlers(prefix, ui_components)
         create_ipadapter_event_handlers(prefix, ui_components)
         create_embedding_event_handlers(prefix, ui_components)
         create_conditioning_event_handlers(prefix, ui_components)
@@ -275,9 +236,6 @@ def attach_event_handlers(ui_components, demo):
             accordion_chain_map = {
                 f'lora_accordion_{prefix}': 'lora',
                 f'controlnet_accordion_{prefix}': 'controlnet',
-                f'anima_controlnet_lllite_accordion_{prefix}': 'anima_controlnet_lllite',
-                f'diffsynth_controlnet_accordion_{prefix}': 'diffsynth_controlnet',
-                f'krea2_controlnet_accordion_{prefix}': 'krea2_controlnet',
                 f'ipadapter_accordion_{prefix}': 'ipadapter',
                 f'sd3_ipadapter_accordion_{prefix}': 'sd3_ipadapter',
                 f'flux1_ipadapter_accordion_{prefix}': 'flux1_ipadapter',
@@ -323,8 +281,7 @@ def attach_event_handlers(ui_components, demo):
         # Add feature accordion outputs for task-based visibility
         accordion_keys = [
             'lora_accordion_imagegen', 'controlnet_accordion_imagegen',
-            'anima_controlnet_lllite_accordion_imagegen', 'diffsynth_controlnet_accordion_imagegen',
-            'krea2_controlnet_accordion_imagegen', 'ipadapter_accordion_imagegen',
+            'ipadapter_accordion_imagegen',
             'sd3_ipadapter_accordion_imagegen', 'flux1_ipadapter_accordion_imagegen',
             'style_accordion_imagegen', 'embedding_accordion_imagegen',
             'conditioning_accordion_imagegen', 'reference_latent_accordion_imagegen',
@@ -434,18 +391,7 @@ def attach_event_handlers(ui_components, demo):
             all_load_outputs.extend(ui_components[f'controlnet_types_{prefix}'])
             all_load_outputs.extend(ui_components[f'controlnet_series_{prefix}'])
             all_load_outputs.extend(ui_components[f'controlnet_filepaths_{prefix}'])
-        if f'anima_controlnet_lllite_types_{prefix}' in ui_components:
-            all_load_outputs.extend(ui_components[f'anima_controlnet_lllite_types_{prefix}'])
-            all_load_outputs.extend(ui_components[f'anima_controlnet_lllite_series_{prefix}'])
-            all_load_outputs.extend(ui_components[f'anima_controlnet_lllite_filepaths_{prefix}'])
-        if f'diffsynth_controlnet_types_{prefix}' in ui_components:
-            all_load_outputs.extend(ui_components[f'diffsynth_controlnet_types_{prefix}'])
-            all_load_outputs.extend(ui_components[f'diffsynth_controlnet_series_{prefix}'])
-            all_load_outputs.extend(ui_components[f'diffsynth_controlnet_filepaths_{prefix}'])
-        if f'krea2_controlnet_types_{prefix}' in ui_components:
-            all_load_outputs.extend(ui_components[f'krea2_controlnet_types_{prefix}'])
-            all_load_outputs.extend(ui_components[f'krea2_controlnet_series_{prefix}'])
-            all_load_outputs.extend(ui_components[f'krea2_controlnet_filepaths_{prefix}'])
+
         if f'ipadapter_final_preset_{prefix}' in ui_components:
             all_load_outputs.extend(ui_components[f'ipadapter_lora_strengths_{prefix}'])
             all_load_outputs.append(ui_components[f'ipadapter_final_preset_{prefix}'])

ui/events/run_handlers.py

@@ -87,9 +87,6 @@ def create_run_event(prefix: str, task_type: str = None, ui_components: dict = N
     
     lora_data_components = ui_components.get(f'all_lora_components_flat_{prefix}', [])
     controlnet_data_components = ui_components.get(f'all_controlnet_components_flat_{prefix}', [])
-    anima_controlnet_lllite_data_components = ui_components.get(f'all_anima_controlnet_lllite_components_flat_{prefix}', [])
-    diffsynth_controlnet_data_components = ui_components.get(f'all_diffsynth_controlnet_components_flat_{prefix}', [])
-    krea2_controlnet_data_components = ui_components.get(f'all_krea2_controlnet_components_flat_{prefix}', [])
     ipadapter_data_components = ui_components.get(f'all_ipadapter_components_flat_{prefix}', [])
     sd3_ipadapter_data_components = ui_components.get(f'all_sd3_ipadapter_components_flat_{prefix}', [])
     flux1_ipadapter_data_components = ui_components.get(f'all_flux1_ipadapter_components_flat_{prefix}', [])
@@ -112,7 +109,7 @@ def create_run_event(prefix: str, task_type: str = None, ui_components: dict = N
     input_keys = list(run_inputs_map.keys())
     input_list_flat = [v for v in run_inputs_map.values() if v is not None]
     all_chains = [
-        lora_data_components, controlnet_data_components, anima_controlnet_lllite_data_components, diffsynth_controlnet_data_components, krea2_controlnet_data_components, ipadapter_data_components,
+        lora_data_components, controlnet_data_components, ipadapter_data_components,
         sd3_ipadapter_data_components, flux1_ipadapter_data_components, style_data_components,
         embedding_data_components, conditioning_data_components, reference_latent_data_components, hidream_o1_reference_data_components, sensenova_reference_data_components, joyai_reference_data_components, krea2_identity_edit_data_components, krea2_reference_edit_data_components, qwen_image_edit_data_components, reference_image_data_components
     ]
@@ -133,9 +130,6 @@ def create_run_event(prefix: str, task_type: str = None, ui_components: dict = N
 
         assign_chain_data('lora_data', lora_data_components)
         assign_chain_data('controlnet_data', controlnet_data_components)
-        assign_chain_data('anima_controlnet_lllite_data', anima_controlnet_lllite_data_components)
-        assign_chain_data('diffsynth_controlnet_data', diffsynth_controlnet_data_components)
-        assign_chain_data('krea2_controlnet_data', krea2_controlnet_data_components)
         assign_chain_data('ipadapter_data', ipadapter_data_components)
         assign_chain_data('sd3_ipadapter_chain', sd3_ipadapter_data_components)
         assign_chain_data('flux1_ipadapter_data', flux1_ipadapter_data_components)

ui/imagegen_ui.py

@@ -4,7 +4,7 @@ from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
 from .shared.ui_components import (
     RESOLUTION_MAP,
     create_lora_settings_ui,
-    create_controlnet_ui, create_anima_controlnet_lllite_ui, create_diffsynth_controlnet_ui, create_krea2_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
+    create_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
     create_conditioning_ui, create_vae_override_ui,
     create_model_architecture_filter_ui, create_category_filter_ui,
     create_sd3_ipadapter_ui, create_flux1_ipadapter_ui, create_style_ui,
@@ -173,9 +173,6 @@ def create_ui():
         with gr.Column() as accordion_wrapper:
             components.update(create_lora_settings_ui(prefix))
             components.update(create_controlnet_ui(prefix))
-            components.update(create_anima_controlnet_lllite_ui(prefix))
-            components.update(create_diffsynth_controlnet_ui(prefix))
-            components.update(create_krea2_controlnet_ui(prefix))
             components.update(create_ipadapter_ui(prefix))
             components.update(create_flux1_ipadapter_ui(prefix))
             components.update(create_sd3_ipadapter_ui(prefix))

ui/shared/ui_components.py

@@ -201,138 +201,6 @@ def create_controlnet_ui(prefix: str, max_units=MAX_CONTROLNETS):
 
     return components
 
-def create_krea2_controlnet_ui(prefix: str, max_units=MAX_CONTROLNETS):
-    components = {}
-    key = lambda name: f"{name}_{prefix}"
-
-    with gr.Accordion("Krea2 ControlNet Settings", open=False, visible=('krea2_controlnet' in default_enabled_chains)) as accordion:
-        components[key('krea2_controlnet_accordion')] = accordion
-        gr.Markdown("💡 **Tip:** Processed using the [facok/comfyui-krea2-controlnet](https://github.com/facok/comfyui-krea2-controlnet) node.")       
-        
-        cn_rows, images, series, types, strengths, filepaths = [], [], [], [], [], []
-        components.update({
-            key('krea2_controlnet_rows'): cn_rows,
-            key('krea2_controlnet_images'): images,
-            key('krea2_controlnet_series'): series,
-            key('krea2_controlnet_types'): types,
-            key('krea2_controlnet_strengths'): strengths,
-            key('krea2_controlnet_filepaths'): filepaths
-        })
-        
-        for i in range(max_units):
-            with gr.Row(visible=(i < 1)) as row:
-                with gr.Column(scale=1):
-                    images.append(gr.Image(label=f"Control Image {i+1}", type="pil", sources=["upload"], height=256))
-                with gr.Column(scale=2):
-                    types.append(gr.Dropdown(label="Type", choices=[], interactive=True, allow_custom_value=True))
-                    series.append(gr.Dropdown(label="Series", choices=[], interactive=True, allow_custom_value=True))
-                    strengths.append(gr.Slider(label="Strength", minimum=0.0, maximum=2.0, step=0.05, value=1.0, interactive=True))
-                    filepaths.append(gr.State(None))
-                cn_rows.append(row)
-
-        with gr.Row():
-            components[key('add_krea2_controlnet_button')] = gr.Button("✚ Add Krea2 ControlNet")
-            components[key('delete_krea2_controlnet_button')] = gr.Button("➖ Delete Krea2 ControlNet", visible=False)
-        components[key('krea2_controlnet_count_state')] = gr.State(1)
-        
-        all_cn_components_flat = []
-        for i in range(max_units):
-            all_cn_components_flat.extend([
-                images[i], types[i], series[i], strengths[i], filepaths[i]
-            ])
-        components[key('all_krea2_controlnet_components_flat')] = all_cn_components_flat
-
-    return components
-
-def create_anima_controlnet_lllite_ui(prefix: str, max_units=MAX_CONTROLNETS):
-    components = {}
-    key = lambda name: f"{name}_{prefix}"
-
-    with gr.Accordion("Anima ControlNet LLLite Settings", open=False, visible=('anima_controlnet_lllite' in default_enabled_chains)) as accordion:
-        components[key('anima_controlnet_lllite_accordion')] = accordion
-        
-        cn_rows, images, series, types, strengths, filepaths, start_percents, end_percents = [], [], [], [], [], [], [], []
-        components.update({
-            key('anima_controlnet_lllite_rows'): cn_rows,
-            key('anima_controlnet_lllite_images'): images,
-            key('anima_controlnet_lllite_series'): series,
-            key('anima_controlnet_lllite_types'): types,
-            key('anima_controlnet_lllite_strengths'): strengths,
-            key('anima_controlnet_lllite_filepaths'): filepaths,
-            key('anima_controlnet_lllite_start_percents'): start_percents,
-            key('anima_controlnet_lllite_end_percents'): end_percents
-        })
-        
-        for i in range(max_units):
-            with gr.Row(visible=(i < 1)) as row:
-                with gr.Column(scale=1):
-                    images.append(gr.Image(label=f"Control Image {i+1}", type="pil", sources=["upload"], height=256))
-                with gr.Column(scale=2):
-                    types.append(gr.Dropdown(label="Type", choices=[], interactive=True, allow_custom_value=True))
-                    series.append(gr.Dropdown(label="Series", choices=[], interactive=True, allow_custom_value=True))
-                    strengths.append(gr.Slider(label="Strength", minimum=0.0, maximum=2.0, step=0.05, value=1.0, interactive=True))
-                    with gr.Row(visible=False):
-                        start_percents.append(gr.State(0.0))
-                        end_percents.append(gr.State(1.0))
-                    filepaths.append(gr.State(None))
-                cn_rows.append(row)
-
-        with gr.Row():
-            components[key('add_anima_controlnet_lllite_button')] = gr.Button("✚ Add Lllite")
-            components[key('delete_anima_controlnet_lllite_button')] = gr.Button("➖ Delete Lllite", visible=False)
-        components[key('anima_controlnet_lllite_count_state')] = gr.State(1)
-        
-        all_cn_components_flat = []
-        for i in range(max_units):
-            all_cn_components_flat.extend([
-                images[i], types[i], series[i], strengths[i], filepaths[i], start_percents[i], end_percents[i]
-            ])
-        components[key('all_anima_controlnet_lllite_components_flat')] = all_cn_components_flat
-
-    return components
-
-def create_diffsynth_controlnet_ui(prefix: str, max_units=MAX_CONTROLNETS):
-    components = {}
-    key = lambda name: f"{name}_{prefix}"
-
-    with gr.Accordion("DiffSynth ControlNet Settings", open=False, visible=('diffsynth_controlnet' in default_enabled_chains)) as accordion:
-        components[key('diffsynth_controlnet_accordion')] = accordion
-        
-        cn_rows, images, series, types, strengths, filepaths = [], [], [], [], [], []
-        components.update({
-            key('diffsynth_controlnet_rows'): cn_rows,
-            key('diffsynth_controlnet_images'): images,
-            key('diffsynth_controlnet_series'): series,
-            key('diffsynth_controlnet_types'): types,
-            key('diffsynth_controlnet_strengths'): strengths,
-            key('diffsynth_controlnet_filepaths'): filepaths
-        })
-        
-        for i in range(max_units):
-            with gr.Row(visible=(i < 1)) as row:
-                with gr.Column(scale=1):
-                    images.append(gr.Image(label=f"Control Image {i+1}", type="pil", sources=["upload"], height=256))
-                with gr.Column(scale=2):
-                    types.append(gr.Dropdown(label="Type", choices=[], interactive=True, allow_custom_value=True))
-                    series.append(gr.Dropdown(label="Series", choices=[], interactive=True, allow_custom_value=True))
-                    strengths.append(gr.Slider(label="Strength", minimum=0.0, maximum=2.0, step=0.05, value=1.0, interactive=True))
-                    filepaths.append(gr.State(None))
-                cn_rows.append(row)
-
-        with gr.Row():
-            components[key('add_diffsynth_controlnet_button')] = gr.Button("✚ Add DiffSynth ControlNet")
-            components[key('delete_diffsynth_controlnet_button')] = gr.Button("➖ Delete DiffSynth ControlNet", visible=False)
-        components[key('diffsynth_controlnet_count_state')] = gr.State(1)
-        
-        all_cn_components_flat = []
-        for i in range(max_units):
-            all_cn_components_flat.extend([
-                images[i], types[i], series[i], strengths[i], filepaths[i]
-            ])
-        components[key('all_diffsynth_controlnet_components_flat')] = all_cn_components_flat
-
-    return components
-
 def create_ipadapter_ui(prefix: str, max_units=MAX_IPADAPTERS):
     components = {}
     key = lambda name: f"{name}_{prefix}"

yaml/anima_controlnet_lllite_models.yaml

@@ -1,16 +0,0 @@
-Anima_ControlNet_Lllite:
-  - Filepath: "anima-lllite-any-test-like-v2.safetensors"
-    Series: "kohya-ss"
-    Type: ["Any-Test"]
-  - Filepath: "anima-lllite-depth-1.safetensors"
-    Series: "kohya-ss"
-    Type: ["Depth"]
-  - Filepath: "anima-lllite-lineart-1.safetensors"
-    Series: "kohya-ss"
-    Type: ["Lineart"]
-  - Filepath: "anima-lllite-pose-1.safetensors"
-    Series: "kohya-ss"
-    Type: ["Pose"]
-  - Filepath: "anima-lllite-scribble-1.safetensors"
-    Series: "kohya-ss"
-    Type: ["Scribble"]

yaml/chain_features.yaml

@@ -265,35 +265,6 @@ krea2_style_reference:
         description: "Style reference image encoded as Base64 Data URI or HTTP/HTTPS URL."
     required:
       - image
-
-diffsynth_controlnet:
-  chains: diffsynth_controlnet
-  display_name: "DiffSynth ControlNet"
-  description: "DiffSynth optimized ControlNet injector for Z-Image models."
-  max_count: 5
-  usage_guideline: "Supply ControlNet type (e.g., 'Canny'), series (e.g., 'alibaba-pai Controlnet Union 2.1 8steps'), pre-processed control image (Base64 Data URI or HTTP/HTTPS URL; system does NOT pre-process raw RGB images), and optional strength."
-  parameters_schema:
-    type: object
-    properties:
-      type:
-        type: string
-        description: "ControlNet conditioning type."
-      series:
-        type: string
-        description: "ControlNet model series name."
-      image:
-        type: string
-        description: "Pre-processed control image (e.g., Depth map) encoded as Base64 Data URI or HTTP/HTTPS URL. Note: System does NOT automatically pre-process raw RGB images."
-      strength:
-        type: number
-        default: 1.0
-        description: "Control influence strength."
-    required:
-      - type
-      - series
-      - image
-
-
 joyai_reference_edit:
   chains: joyai_image
   display_name: "JoyAI Reference Edit"
@@ -339,70 +310,6 @@ hidream_o1_smoothing:
         default: 0.5
         description: "Smoothing intensity (0.0 to 1.0)."
     required: []
-
-krea2_controlnet:
-  chains: krea2_controlnet
-  display_name: "KREA2 ControlNet"
-  description: "Processed using the facok/comfyui-krea2-controlnet node."
-  max_count: 5
-  usage_guideline: "Supply ControlNet type (e.g., 'Depth'), series (e.g., 'Patil'), pre-processed control image (Base64 Data URI or HTTP/HTTPS URL; system does NOT pre-process raw RGB images), and optional strength."
-  parameters_schema:
-    type: object
-    properties:
-      type:
-        type: string
-        enum:
-          - "Depth"
-        description: "ControlNet conditioning type."
-      series:
-        type: string
-        enum:
-          - "Patil"
-        default: "Patil"
-        description: "ControlNet model series."
-      image:
-        type: string
-        description: "Pre-processed control image (e.g., Depth map) encoded as Base64 Data URI or HTTP/HTTPS URL. Note: System does NOT automatically pre-process raw RGB images."
-      strength:
-        type: number
-        default: 1.0
-        minimum: 0.0
-        maximum: 2.0
-        description: "Control influence strength (0.0 to 2.0)."
-    required:
-      - type
-      - series
-      - image
-
-anima_controlnet_lllite:
-  chains: anima_controlnet_lllite
-  display_name: "Anima ControlNet LLLite"
-  description: "Anima model-specific lightweight ControlNet."
-  max_count: 5
-  usage_guideline: "Supply Anima ControlNet LLLite type (e.g., 'Depth'), series (e.g., 'kohya-ss'), pre-processed control image (Base64 Data URI or HTTP/HTTPS URL; system does NOT pre-process raw RGB images), and optional strength."
-  parameters_schema:
-    type: object
-    properties:
-      type:
-        type: string
-        description: "Anima ControlNet LLLite conditioning type."
-      series:
-        type: string
-        description: "Anima ControlNet LLLite model series."
-      image:
-        type: string
-        description: "Pre-processed control image (e.g., Depth, Lineart map) encoded as Base64 Data URI or HTTP/HTTPS URL. Note: System does NOT automatically pre-process raw RGB images."
-      strength:
-        type: number
-        default: 1.0
-        minimum: 0.0
-        maximum: 2.0
-        description: "Control influence strength (0.0 to 2.0)."
-    required:
-      - type
-      - series
-      - image
-
 hidream_o1_reference:
   chains: hidream_o1_reference
   display_name: "HiDream-O1 Reference Edit"

yaml/controlnet_models.yaml

@@ -1,8 +1,42 @@
 ControlNet:
+  Qwen-Image-2.1:
+    - Filepath: "qwen_image_2.1_fun_controlnet_union_int8_convrot.safetensors"
+      Series: "Alibaba-PAI Fun-ControlNet Union"
+      Type: ["Canny", "Depth", "Pose", "Lineart", "HED", "MLSD", "Scribble", "Grayscale"]
   Qwen-Image:
     - Filepath: "Qwen-Image-InstantX-ControlNet-Union.safetensors"
       Series: "InstantX Union"
       Type: ["Canny", "Soft Edge", "Depth", "Pose"]
+  Krea-2:
+    - Filepath: "krea2-anythng_step_007000.safetensors"
+      Series: "tori29umai"
+      Type: ["Anythng"]
+    - Filepath: "depth-control-lora.safetensors"
+      Series: "Patil"
+      Type: ["Depth"]
+  Z-Image:
+    - Filepath: "Z-Image-Turbo-Fun-Controlnet-Union-2.1-8steps.safetensors"
+      Series: "alibaba-pai Controlnet Union 2.1 8steps"
+      Type: ["Pose", "Canny", "HED", "Depth", "MLSD"]
+    - Filepath: "Z-Image-Turbo-Fun-Controlnet-Tile-2.1-8steps.safetensors"
+      Series: "alibaba-pai Controlnet Union 2.1 8steps"
+      Type: ["Tile"]
+  Anima:
+    - Filepath: "anima-lllite-any-test-like-v2.safetensors"
+      Series: "kohya-ss"
+      Type: ["Any-Test"]
+    - Filepath: "anima-lllite-depth-1.safetensors"
+      Series: "kohya-ss"
+      Type: ["Depth"]
+    - Filepath: "anima-lllite-lineart-1.safetensors"
+      Series: "kohya-ss"
+      Type: ["Lineart"]
+    - Filepath: "anima-lllite-pose-1.safetensors"
+      Series: "kohya-ss"
+      Type: ["Pose"]
+    - Filepath: "anima-lllite-scribble-1.safetensors"
+      Series: "kohya-ss"
+      Type: ["Scribble"]
   FLUX.1:
     - Filepath: "FLUX.1-dev-ControlNet-Union-Pro-2.0.safetensors"
       Series: "Shakker Labs Union Pro"

yaml/diffsynth_controlnet_models.yaml

@@ -1,8 +0,0 @@
-DiffSynth_ControlNet:
-  Z-Image:
-    - Filepath: "Z-Image-Turbo-Fun-Controlnet-Union-2.1-8steps.safetensors"
-      Series: "alibaba-pai Controlnet Union 2.1 8steps"
-      Type: ["Pose", "Canny", "HED", "Depth", "MLSD"]
-    - Filepath: "Z-Image-Turbo-Fun-Controlnet-Tile-2.1-8steps.safetensors"
-      Series: "alibaba-pai Controlnet Union 2.1 8steps"
-      Type: ["Tile"]

yaml/file_list.yaml

@@ -903,6 +903,11 @@ file:
       source: "hf"
       repo_id: "alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1"
       repository_file_path: "Z-Image-Turbo-Fun-Controlnet-Tile-2.1-8steps.safetensors"
+    # Qwen-Image-2.1
+    - filename: "qwen_image_2.1_fun_controlnet_union_int8_convrot.safetensors"
+      source: "hf"
+      repo_id: "Kijai/QwenImage_experimental"
+      repository_file_path: "model_patches/qwen_image_2.1_fun_controlnet_union_int8_convrot.safetensors"
   text_encoders: 
     # Krea-2
     - filename: "qwen3vl_4b_fp8_scaled.safetensors"

yaml/krea2_controlnet_models.yaml

@@ -1,7 +0,0 @@
-Krea2_ControlNet:
-  - Filepath: "krea2-anythng_step_007000.safetensors"
-    Series: "tori29umai"
-    Type: ["Anythng"]
-  - Filepath: "depth-control-lora.safetensors"
-    Series: "Patil"
-    Type: ["Depth"]

yaml/model_architecture_features.yaml

@@ -2,7 +2,7 @@
 krea-2:
   enabled_chains:
   - lora
-  - krea2_controlnet
+  - controlnet
   - krea2_identity_edit
   - krea2_style_reference
   - pid
@@ -65,7 +65,7 @@ ernie-image:
 z-image:
   enabled_chains:
   - lora
-  - diffsynth_controlnet
+  - controlnet
   - conditioning
   - vae
   - pid
@@ -79,6 +79,7 @@ ming-image:
 qwen-image-2.1:
   enabled_chains:
   - lora
+  - controlnet
   - reference_image
   - qwen_image_2_1_prompt_enhancer
 
@@ -106,7 +107,7 @@ anima-3.8b-v1.1:
   enabled_chains:
   - lora
   - conditioning
-  - anima_controlnet_lllite
+  - controlnet
   - vae
   - pid
 
@@ -115,7 +116,7 @@ anima-3.8b:
   enabled_chains:
   - lora
   - conditioning
-  - anima_controlnet_lllite
+  - controlnet
   - vae
   - pid
 
@@ -123,7 +124,7 @@ anima:
   enabled_chains:
   - lora
   - conditioning
-  - anima_controlnet_lllite
+  - controlnet
   - vae
   - pid
 

yaml/model_architectures.yaml

@@ -67,7 +67,7 @@ architectures:
     model_type: "ming-image"
   "Qwen-Image-2.1":
     model_type: "qwen-image-2.1"
-    controlnet_key: "Qwen-Image"
+    controlnet_key: "Qwen-Image-2.1"
   "Qwen-Image":
     model_type: "qwen-image"
     controlnet_key: "Qwen-Image"

yaml/task_features.yaml

@@ -7,9 +7,6 @@ txt2img:
   enabled_chains:
   - lora
   - controlnet
-  - anima_controlnet_lllite
-  - diffsynth_controlnet
-  - krea2_controlnet
   - ipadapter
   - flux1_ipadapter
   - sd3_ipadapter
@@ -34,9 +31,6 @@ img2img:
   enabled_chains:
   - lora
   - controlnet
-  - anima_controlnet_lllite
-  - diffsynth_controlnet
-  - krea2_controlnet
   - ipadapter
   - flux1_ipadapter
   - sd3_ipadapter
@@ -60,9 +54,6 @@ inpaint:
   enabled_chains:
   - lora
   - controlnet
-  - anima_controlnet_lllite
-  - diffsynth_controlnet
-  - krea2_controlnet
   - ipadapter
   - flux1_ipadapter
   - sd3_ipadapter
@@ -86,9 +77,6 @@ outpaint:
   enabled_chains:
   - lora
   - controlnet
-  - anima_controlnet_lllite
-  - diffsynth_controlnet
-  - krea2_controlnet
   - ipadapter
   - flux1_ipadapter
   - sd3_ipadapter
@@ -112,9 +100,6 @@ hires_fix:
   enabled_chains:
   - lora
   - controlnet
-  - anima_controlnet_lllite
-  - diffsynth_controlnet
-  - krea2_controlnet
   - ipadapter
   - flux1_ipadapter
   - sd3_ipadapter