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core/pipelines/pipeline_input_processor.py

@@ -5,7 +5,7 @@ import gradio as gr
 from PIL import Image, ImageChops
 from typing import Dict, Any, List
 
-from core.settings import INPUT_DIR
+from core.settings import INPUT_DIR, MULTIPLIERS_MAP
 from utils.app_utils import (
     sanitize_filename,
     get_lora_path,
@@ -21,6 +21,33 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
     task_type = ui_inputs['task_type']
     temp_files_to_clean = []
     
+    multiplier = MULTIPLIERS_MAP.get(workflow_model_type, 8)
+    img_w, img_h = 0, 0
+    if task_type == 'txt2img':
+        img_w = int(ui_inputs.get('width', 0))
+        img_h = int(ui_inputs.get('height', 0))
+    elif task_type == 'img2img':
+        input_image_pil = ui_inputs.get('img2img_image')
+        if input_image_pil:
+            img_w, img_h = input_image_pil.width, input_image_pil.height
+    elif task_type == 'inpaint':
+        inpaint_dict = ui_inputs.get('inpaint_image_dict')
+        if inpaint_dict and inpaint_dict.get('background'):
+            img_w, img_h = inpaint_dict['background'].width, inpaint_dict['background'].height
+    elif task_type == 'outpaint':
+        input_image_pil = ui_inputs.get('outpaint_image')
+        if input_image_pil:
+            img_w, img_h = input_image_pil.width, input_image_pil.height
+    elif task_type == 'hires_fix':
+        input_image_pil = ui_inputs.get('hires_image')
+        if input_image_pil:
+            img_w, img_h = input_image_pil.width, input_image_pil.height
+
+    if img_w > 0 and img_h > 0:
+        if (img_w % multiplier != 0) or (img_h % multiplier != 0):
+            warning_msg = f"Width and height must be multiples of {multiplier} for this model."
+            raise gr.Error(warning_msg)
+    
     lora_data = ui_inputs.get('lora_data', [])
     active_loras_for_gpu, active_loras_for_meta = [], []
     if lora_data:
@@ -270,7 +297,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
                 active_styles.append({
                     "image": os.path.basename(temp_path), "strength": st_strengths[i]
                 })
-    
+            
     reference_latent_data = ui_inputs.get('reference_latent_data', [])
     active_reference_latents = []
     if reference_latent_data:
@@ -292,7 +319,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
                 img.save(temp_path, "PNG")
                 temp_files_to_clean.append(temp_path)
                 active_hidream_o1_reference.append(os.path.basename(temp_path))
-    
+            
     vae_source = ui_inputs.get('vae_source')
     vae_id = ui_inputs.get('vae_id')
     vae_name_override = None

core/settings.py

@@ -192,6 +192,7 @@ try:
     MAX_IPADAPTERS = _constants.get('MAX_IPADAPTERS', 5)
     LORA_SOURCE_CHOICES = _constants.get('LORA_SOURCE_CHOICES', ["Civitai", "File"])
     RESOLUTION_MAP = _constants.get('RESOLUTION_MAP', {})
+    MULTIPLIERS_MAP = _constants.get('MULTIPLIERS_MAP', {})
     ARCHITECTURES_CONFIG = load_architectures_config()
     FEATURES_CONFIG = load_features_config()
     MODEL_DEFAULTS_CONFIG = load_model_defaults()
@@ -200,6 +201,7 @@ except Exception as e:
     MAX_LORAS, MAX_EMBEDDINGS, MAX_CONDITIONINGS, MAX_CONTROLNETS, MAX_IPADAPTERS = 5, 5, 10, 5, 5
     LORA_SOURCE_CHOICES = ["Civitai", "File"]
     RESOLUTION_MAP = {}
+    MULTIPLIERS_MAP = {}
     ARCHITECTURES_CONFIG = {}
     FEATURES_CONFIG = {}
     MODEL_DEFAULTS_CONFIG = {}

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.45.20
-comfyui-workflow-templates==0.10.7
+comfyui-workflow-templates==0.11.1
 comfyui-embedded-docs==0.5.6
 torch
 torchsde
@@ -22,7 +22,7 @@ alembic
 SQLAlchemy>=2.0.0
 filelock
 av>=16.0.0
-comfy-kitchen==0.2.15
+comfy-kitchen==0.2.16
 comfy-aimdo==0.4.10
 requests
 simpleeval>=1.0.0

utils/app_utils.py

@@ -185,8 +185,8 @@ def get_lora_path(source: str, id_or_url: str, civitai_key: str, progress) -> tu
             file_info = get_civitai_file_info(version_id)
             if file_info:
                 model_type = file_info.get('model_type')
-                if not model_type or model_type.lower() not in ['lora', 'lycoris', 'dora']:
-                    return None, f"Invalid Civitai model type '{model_type}' for LoRA. Allowed types: LoRA, LyCORIS, DoRA."
+                if model_type and model_type.lower() == 'checkpoint':
+                    return None, f"Invalid Civitai model type '{model_type}' for LoRA. Checkpoint models are not allowed."
             
             filename = sanitize_filename(f"civitai_{version_id}.safetensors")
             local_path = os.path.join(LORA_DIR, filename)
@@ -244,8 +244,8 @@ def get_embedding_path(source: str, id_or_url: str, civitai_key: str, progress)
             file_info = get_civitai_file_info(version_id)
             if file_info:
                 model_type = file_info.get('model_type')
-                if not model_type or model_type.lower() not in ['embedding', 'textualinversion']:
-                    return None, f"Invalid Civitai model type '{model_type}' for Embedding. Allowed types: Embedding."
+                if model_type and model_type.lower() == 'checkpoint':
+                    return None, f"Invalid Civitai model type '{model_type}' for Embedding. Checkpoint models are not allowed."
             
             file_ext = ".safetensors"
             if file_info and file_info.get('name') and file_info['name'].lower().endswith(('.pt', '.bin')):
@@ -306,8 +306,8 @@ def get_vae_path(source: str, id_or_url: str, civitai_key: str, progress) -> tup
             file_info = get_civitai_file_info(version_id)
             if file_info:
                 model_type = file_info.get('model_type')
-                if not model_type or model_type.lower() != 'vae':
-                    return None, f"Invalid Civitai model type '{model_type}' for VAE. Allowed types: VAE."
+                if model_type and model_type.lower() == 'checkpoint':
+                    return None, f"Invalid Civitai model type '{model_type}' for VAE. Checkpoint models are not allowed."
             
             file_ext = ".safetensors"
             if file_info and file_info.get('name') and file_info['name'].lower().endswith(('.pt', '.bin')):

yaml/constants.yaml

@@ -222,4 +222,33 @@ RESOLUTION_MAP:
     "4:3 (Classic Landscape)": [683, 512]
     "3:4 (Classic Portrait)": [512, 683]
     "3:2 (Landscape)": [768, 512]
-    "2:3 (Portrait)": [512, 768]
+    "2:3 (Portrait)": [512, 768]
+
+MULTIPLIERS_MAP:
+  krea-2: 1
+  boogu-image: 1
+  pixeldit: 1
+  ideogram-4: 1
+  lens: 1
+  flux2-kv: 1
+  flux2: 1
+  ernie-image: 1
+  z-image: 1
+  qwen-image: 1
+  longcat-image: 1
+  cosmos-predict2: 1
+  anima: 1
+  newbie-image: 1
+  kandinsky-5: 32
+  ovis-image: 1
+  hunyuanimage: 1
+  chroma1-radiance: 64
+  chroma1: 1
+  omnigen2: 1
+  lumina: 1
+  hidream-o1: 32
+  hidream-i1:
+  flux1: 1
+  sd35: 1
+  sdxl: 1
+  sd15: 1