diff --git a/README.md b/README.md
index 3c1828f0092979ae7b032bd9246b357c90733459..74b50d76216e89529f039ca313f7d929232fba4a 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,5 @@
---
-title: ImageGen - SDXL
+title: ImageGen
emoji: 🖼
colorFrom: purple
colorTo: red
@@ -7,4 +7,5 @@ sdk: gradio
sdk_version: "5.50.0"
app_file: app.py
short_description: Multi-task image generator with dynamic, chainable workflows
+pinned: true
---
diff --git a/app.py b/app.py
index b3c40ed672c9adab9408d5f7ce573e79ef9e7d8e..bd7ce944da56842e1e0f9df10ecae6c0188f16ed 100644
--- a/app.py
+++ b/app.py
@@ -1,7 +1,6 @@
import spaces
import os
import sys
-import requests
import site
APP_DIR = os.path.dirname(os.path.abspath(__file__))
@@ -45,9 +44,11 @@ def dummy_gpu_for_startup():
print("--- [GPU Startup] Startup check passed. ---")
return "Startup check passed."
+
def main():
from utils.app_utils import print_welcome_message
from scripts import build_sage_attention
+ from comfy_integration import setup as setup_comfyui
print_welcome_message()
@@ -58,7 +59,9 @@ def main():
except Exception as e:
print(f"--- [Setup] ❌ SageAttention installation failed: {e}. Continuing with default attention. ---")
-
+ print("--- [Setup] Starting ComfyUI initialization ---")
+ setup_comfyui.initialize_comfyui()
+
print("--- [Setup] Reloading site-packages to detect newly installed packages... ---")
try:
site.main()
@@ -66,48 +69,16 @@ def main():
except Exception as e:
print(f"--- [Setup] ⚠️ Warning: Could not fully reload site-packages: {e} ---")
- from comfy_integration import setup as setup_comfyui
- from utils.app_utils import (
- build_preprocessor_model_map,
- build_preprocessor_parameter_map,
- load_ipadapter_presets
- )
- from core import shared_state
- from core.settings import ALL_MODEL_MAP, ALL_FILE_DOWNLOAD_MAP
-
- def check_all_model_urls_on_startup():
- print("--- [Setup] Checking all model URL validity (one-time check) ---")
- for display_name, model_info in ALL_MODEL_MAP.items():
- repo_id, filename, _, _ = model_info
- if not repo_id: continue
-
- download_info = ALL_FILE_DOWNLOAD_MAP.get(filename, {})
- repo_file_path = download_info.get('repository_file_path', filename)
- url = f"https://huggingface.co/{repo_id}/resolve/main/{repo_file_path}"
-
- try:
- response = requests.head(url, timeout=5, allow_redirects=True)
- if response.status_code >= 400:
- print(f"❌ Invalid URL for '{display_name}': {url} (Status: {response.status_code})")
- shared_state.INVALID_MODEL_URLS[display_name] = True
- except requests.RequestException as e:
- print(f"❌ URL check failed for '{display_name}': {e}")
- shared_state.INVALID_MODEL_URLS[display_name] = True
- print("--- [Setup] ✅ Finished checking model URLs. ---")
+ print("--- Initiating GPU Startup Check & SageAttention Patch ---")
+ try:
+ dummy_gpu_for_startup()
+ except Exception as e:
+ print(f"--- [GPU Startup] ⚠️ Warning: Startup check failed: {e} ---")
- print("--- Starting Application Setup ---")
-
- setup_comfyui.initialize_comfyui()
+ from utils.app_utils import load_ipadapter_presets
- check_all_model_urls_on_startup()
+ print("--- Starting Application Setup ---")
- print("--- Building ControlNet preprocessor maps ---")
- from core.generation_logic import build_reverse_map
- build_reverse_map()
- build_preprocessor_model_map()
- build_preprocessor_parameter_map()
- print("--- ✅ ControlNet preprocessor setup complete. ---")
-
print("--- Loading IPAdapter presets ---")
load_ipadapter_presets()
print("--- ✅ IPAdapter setup complete. ---")
diff --git a/chain_injectors/diffsynth_controlnet_injector.py b/chain_injectors/diffsynth_controlnet_injector.py
new file mode 100644
index 0000000000000000000000000000000000000000..7c5a5a2ba15dfd7b54c281649ae36e0b3d2072ad
--- /dev/null
+++ b/chain_injectors/diffsynth_controlnet_injector.py
@@ -0,0 +1,75 @@
+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).")
\ No newline at end of file
diff --git a/chain_injectors/flux1_ipadapter_injector.py b/chain_injectors/flux1_ipadapter_injector.py
new file mode 100644
index 0000000000000000000000000000000000000000..66fa6cc32fb927a4572e32a4b66fe9d0d9feeb8d
--- /dev/null
+++ b/chain_injectors/flux1_ipadapter_injector.py
@@ -0,0 +1,46 @@
+def inject(assembler, chain_definition, chain_items):
+ if not chain_items:
+ return
+
+ ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+ if ksampler_name not in assembler.node_map:
+ print(f"Warning: KSampler node '{ksampler_name}' not found for Flux1 IPAdapter chain. Skipping.")
+ return
+
+ ksampler_id = assembler.node_map[ksampler_name]
+
+ if 'model' not in assembler.workflow[ksampler_id]['inputs']:
+ print(f"Warning: KSampler node '{ksampler_name}' is missing 'model' input. Skipping Flux1 IPAdapter chain.")
+ return
+
+ current_model_connection = assembler.workflow[ksampler_id]['inputs']['model']
+
+ for item_data in chain_items:
+ image_loader_id = assembler._get_unique_id()
+ image_loader_node = assembler._get_node_template("LoadImage")
+ image_loader_node['inputs']['image'] = item_data['image']
+ assembler.workflow[image_loader_id] = image_loader_node
+
+ ipadapter_loader_id = assembler._get_unique_id()
+ ipadapter_loader_node = assembler._get_node_template("IPAdapterFluxLoader")
+ ipadapter_loader_node['inputs']['ipadapter'] = "ip-adapter.bin"
+ ipadapter_loader_node['inputs']['clip_vision'] = "google/siglip-so400m-patch14-384"
+ ipadapter_loader_node['inputs']['provider'] = "cuda"
+ assembler.workflow[ipadapter_loader_id] = ipadapter_loader_node
+
+ apply_ipa_id = assembler._get_unique_id()
+ apply_ipa_node = assembler._get_node_template("ApplyIPAdapterFlux")
+
+ apply_ipa_node['inputs']['weight'] = item_data['weight']
+ apply_ipa_node['inputs']['start_percent'] = item_data.get('start_percent', 0.0)
+ apply_ipa_node['inputs']['end_percent'] = item_data.get('end_percent', 0.6)
+
+ apply_ipa_node['inputs']['model'] = current_model_connection
+ apply_ipa_node['inputs']['ipadapter_flux'] = [ipadapter_loader_id, 0]
+ apply_ipa_node['inputs']['image'] = [image_loader_id, 0]
+
+ assembler.workflow[apply_ipa_id] = apply_ipa_node
+ current_model_connection = [apply_ipa_id, 0]
+
+ assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
+ print(f"Flux1 IPAdapter injector applied. KSampler model input re-routed through {len(chain_items)} IPAdapter(s).")
\ No newline at end of file
diff --git a/chain_injectors/newbie_lora_injector.py b/chain_injectors/newbie_lora_injector.py
new file mode 100644
index 0000000000000000000000000000000000000000..6c13e8724a9b4c4fd4d6c8f32c1b0752c4029c9f
--- /dev/null
+++ b/chain_injectors/newbie_lora_injector.py
@@ -0,0 +1,63 @@
+from copy import deepcopy
+
+def inject(assembler, chain_definition, chain_items):
+ if not chain_items:
+ return
+
+ output_map = chain_definition.get('output_map', {})
+ current_connections = {}
+ for key, type_name in output_map.items():
+ if ':' in str(key):
+ node_name, idx_str = key.split(':')
+ if node_name not in assembler.node_map:
+ print(f"Warning: [NewBie LoRA Injector] Node '{node_name}' in chain's output_map not found. Skipping.")
+ continue
+ node_id = assembler.node_map[node_name]
+ start_output_idx = int(idx_str)
+ current_connections[type_name] = [node_id, start_output_idx]
+ else:
+ print(f"Warning: [NewBie LoRA Injector] output_map key '{key}' is not in 'node:index' format. Skipping this connection.")
+
+ template_name = chain_definition.get('template')
+ if not template_name:
+ print(f"Warning: [NewBie LoRA Injector] No 'template' defined for chain. Skipping.")
+ return
+
+ for item_data in chain_items:
+ template = assembler._get_node_template(template_name)
+ node_data = deepcopy(template)
+
+ node_data['inputs']['lora_name'] = item_data.get('lora_name')
+ node_data['inputs']['strength'] = item_data.get('strength_model', 1.0)
+ node_data['inputs']['enabled'] = True
+
+ if 'model' in current_connections:
+ node_data['inputs']['model'] = current_connections['model']
+ if 'clip' in current_connections:
+ node_data['inputs']['clip'] = current_connections['clip']
+
+ new_node_id = assembler._get_unique_id()
+ assembler.workflow[new_node_id] = node_data
+
+ current_connections['model'] = [new_node_id, 0]
+ current_connections['clip'] = [new_node_id, 1]
+
+ end_input_map = chain_definition.get('end_input_map', {})
+ for type_name, targets in end_input_map.items():
+ if type_name in current_connections:
+ if not isinstance(targets, list):
+ targets = [targets]
+
+ for target_str in targets:
+ try:
+ end_node_name, end_input_name = target_str.split(':')
+ if end_node_name in assembler.node_map:
+ end_node_id = assembler.node_map[end_node_name]
+ assembler.workflow[end_node_id]['inputs'][end_input_name] = current_connections[type_name]
+ else:
+ print(f"Warning: [NewBie LoRA Injector] End node '{end_node_name}' for dynamic chain not found. Skipping connection.")
+ except ValueError:
+ print(f"Warning: [NewBie LoRA Injector] Invalid target format '{target_str}' in end_input_map. Skipping.")
+
+ if chain_items:
+ print(f"NewBie LoRA injector applied. Re-routed model and clip through {len(chain_items)} LoRA(s).")
\ No newline at end of file
diff --git a/chain_injectors/reference_latent_injector.py b/chain_injectors/reference_latent_injector.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b5becbfef4f60842ecf3af1b977a6e93b7c55a4
--- /dev/null
+++ b/chain_injectors/reference_latent_injector.py
@@ -0,0 +1,157 @@
+def inject(assembler, chain_definition, chain_items):
+ if not chain_items:
+ return
+
+ guider_node_name = chain_definition.get('guider_node')
+ guider_target_inputs = chain_definition.get('guider_target_inputs', [])
+ start_connections_map = chain_definition.get('start_connections', {})
+ vae_node_name = chain_definition.get('vae_node', 'vae_loader')
+
+ if guider_node_name and guider_node_name in assembler.node_map and guider_target_inputs:
+ guider_id = assembler.node_map[guider_node_name]
+ if vae_node_name not in assembler.node_map:
+ print(f"Warning: VAE node '{vae_node_name}' not found for Guider chain. Skipping.")
+ return
+ vae_node_id = assembler.node_map[vae_node_name]
+
+ print(f"ReferenceLatent injector targeting DualCFGGuider node '{guider_node_name}'.")
+
+ current_connections = {}
+ for target_input in guider_target_inputs:
+ conn_str = start_connections_map.get(target_input)
+ if not conn_str:
+ print(f"Warning: No start connection defined for '{target_input}' in Guider chain. Skipping this input.")
+ continue
+ try:
+ node_name, idx_str = conn_str.split(':')
+ node_id = assembler.node_map[node_name]
+ current_connections[target_input] = [node_id, int(idx_str)]
+ except (ValueError, KeyError):
+ print(f"Warning: Invalid start connection '{conn_str}' for '{target_input}'. Skipping.")
+
+ encoded_latents = []
+ for i, img_filename in enumerate(chain_items):
+ load_id = assembler._get_unique_id()
+ load_node = assembler._get_node_template("LoadImage")
+ load_node['inputs']['image'] = img_filename
+ assembler.workflow[load_id] = load_node
+
+ scale_id = assembler._get_unique_id()
+ scale_node = assembler._get_node_template("ImageScaleToTotalPixels")
+ scale_node['inputs']['megapixels'] = 1.0
+ scale_node['inputs']['upscale_method'] = "lanczos"
+ scale_node['inputs']['image'] = [load_id, 0]
+ assembler.workflow[scale_id] = scale_node
+
+ vae_encode_id = assembler._get_unique_id()
+ vae_encode_node = assembler._get_node_template("VAEEncode")
+ vae_encode_node['inputs']['pixels'] = [scale_id, 0]
+ vae_encode_node['inputs']['vae'] = [vae_node_id, 0]
+ assembler.workflow[vae_encode_id] = vae_encode_node
+ encoded_latents.append([vae_encode_id, 0])
+
+ for target_input_name, start_connection in current_connections.items():
+ current_chain_head = start_connection
+ for i, latent_conn in enumerate(encoded_latents):
+ ref_latent_id = assembler._get_unique_id()
+ ref_latent_node = assembler._get_node_template("ReferenceLatent")
+ ref_latent_node['inputs']['conditioning'] = current_chain_head
+ ref_latent_node['inputs']['latent'] = latent_conn
+ ref_latent_node['_meta']['title'] = f"{target_input_name} RefLatent {i+1}"
+ assembler.workflow[ref_latent_id] = ref_latent_node
+ current_chain_head = [ref_latent_id, 0]
+
+ assembler.workflow[guider_id]['inputs'][target_input_name] = current_chain_head
+ print(f" - Input '{target_input_name}' of node '{guider_node_name}' re-routed through {len(chain_items)} reference images.")
+
+ return
+
+ flux_guidance_name = chain_definition.get('flux_guidance_node')
+ ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+
+ if ksampler_name not in assembler.node_map:
+ print(f"Warning: KSampler node '{ksampler_name}' not found for ReferenceLatent chain. Skipping.")
+ return
+ if vae_node_name not in assembler.node_map:
+ print(f"Warning: VAE loader node '{vae_node_name}' not found for ReferenceLatent chain. Skipping.")
+ return
+
+ ksampler_id = assembler.node_map[ksampler_name]
+ vae_node_id = assembler.node_map[vae_node_name]
+
+ pos_target_node_id = None
+ pos_target_input_name = None
+ if flux_guidance_name and flux_guidance_name in assembler.node_map:
+ flux_guidance_id = assembler.node_map[flux_guidance_name]
+ if 'conditioning' in assembler.workflow[flux_guidance_id]['inputs']:
+ pos_target_node_id = flux_guidance_id
+ pos_target_input_name = 'conditioning'
+ print(f"ReferenceLatent injector targeting FluxGuidance node '{flux_guidance_name}' for positive chain.")
+
+ if not pos_target_node_id:
+ if 'positive' in assembler.workflow[ksampler_id]['inputs']:
+ pos_target_node_id = ksampler_id
+ pos_target_input_name = 'positive'
+ print(f"ReferenceLatent injector targeting KSampler node '{ksampler_name}' for positive chain.")
+ else:
+ print(f"Warning: Could not find a valid positive injection point for ReferenceLatent chain. Skipping.")
+ return
+
+ current_pos_conditioning = assembler.workflow[pos_target_node_id]['inputs'][pos_target_input_name]
+
+ neg_target_node_id = ksampler_id
+ neg_target_input_name = 'negative'
+ if 'negative' not in assembler.workflow[neg_target_node_id]['inputs']:
+ print(f"Warning: KSampler node '{ksampler_name}' has no 'negative' input. Skipping negative ReferenceLatent chain.")
+ neg_target_node_id = None
+
+ current_neg_conditioning = None
+ if neg_target_node_id:
+ current_neg_conditioning = assembler.workflow[neg_target_node_id]['inputs'][neg_target_input_name]
+
+ for i, img_filename in enumerate(chain_items):
+ load_id = assembler._get_unique_id()
+ load_node = assembler._get_node_template("LoadImage")
+ load_node['inputs']['image'] = img_filename
+ load_node['_meta']['title'] = f"Load Reference Image {i+1}"
+ assembler.workflow[load_id] = load_node
+
+ scale_id = assembler._get_unique_id()
+ scale_node = assembler._get_node_template("ImageScaleToTotalPixels")
+ scale_node['inputs']['megapixels'] = 1.0
+ scale_node['inputs']['upscale_method'] = "lanczos"
+ scale_node['inputs']['image'] = [load_id, 0]
+ scale_node['_meta']['title'] = f"Scale Reference {i+1}"
+ assembler.workflow[scale_id] = scale_node
+
+ vae_encode_id = assembler._get_unique_id()
+ vae_encode_node = assembler._get_node_template("VAEEncode")
+ vae_encode_node['inputs']['pixels'] = [scale_id, 0]
+ vae_encode_node['inputs']['vae'] = [vae_node_id, 0]
+ vae_encode_node['_meta']['title'] = f"VAE Encode Reference {i+1}"
+ assembler.workflow[vae_encode_id] = vae_encode_node
+
+ latent_conn = [vae_encode_id, 0]
+
+ pos_ref_latent_id = assembler._get_unique_id()
+ pos_ref_latent_node = assembler._get_node_template("ReferenceLatent")
+ pos_ref_latent_node['inputs']['conditioning'] = current_pos_conditioning
+ pos_ref_latent_node['inputs']['latent'] = latent_conn
+ pos_ref_latent_node['_meta']['title'] = f"Positive ReferenceLatent {i+1}"
+ assembler.workflow[pos_ref_latent_id] = pos_ref_latent_node
+ current_pos_conditioning = [pos_ref_latent_id, 0]
+
+ if neg_target_node_id:
+ neg_ref_latent_id = assembler._get_unique_id()
+ neg_ref_latent_node = assembler._get_node_template("ReferenceLatent")
+ neg_ref_latent_node['inputs']['conditioning'] = current_neg_conditioning
+ neg_ref_latent_node['inputs']['latent'] = latent_conn
+ neg_ref_latent_node['_meta']['title'] = f"Negative ReferenceLatent {i+1}"
+ assembler.workflow[neg_ref_latent_id] = neg_ref_latent_node
+ current_neg_conditioning = [neg_ref_latent_id, 0]
+
+ assembler.workflow[pos_target_node_id]['inputs'][pos_target_input_name] = current_pos_conditioning
+ if neg_target_node_id:
+ assembler.workflow[neg_target_node_id]['inputs'][neg_target_input_name] = current_neg_conditioning
+
+ print(f"ReferenceLatent injector applied. Re-routed inputs through {len(chain_items)} reference images.")
\ No newline at end of file
diff --git a/chain_injectors/sd3_ipadapter_injector.py b/chain_injectors/sd3_ipadapter_injector.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b7a9846647adb7ce1c2c2402ffb56951fa7be7d
--- /dev/null
+++ b/chain_injectors/sd3_ipadapter_injector.py
@@ -0,0 +1,66 @@
+def inject(assembler, chain_definition, chain_items):
+ if not chain_items:
+ return
+
+ ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+ if ksampler_name not in assembler.node_map:
+ print(f"Warning: KSampler node '{ksampler_name}' not found for SD3 IPAdapter chain. Skipping.")
+ return
+
+ ksampler_id = assembler.node_map[ksampler_name]
+
+ if 'model' not in assembler.workflow[ksampler_id]['inputs']:
+ print(f"Warning: KSampler node '{ksampler_name}' is missing 'model' input. Skipping SD3 IPAdapter chain.")
+ return
+
+ current_model_connection = assembler.workflow[ksampler_id]['inputs']['model']
+
+ clip_vision_loader_id = assembler._get_unique_id()
+ clip_vision_loader_node = assembler._get_node_template("CLIPVisionLoader")
+ clip_vision_loader_node['inputs']['clip_name'] = "sigclip_vision_patch14_384.safetensors"
+ assembler.workflow[clip_vision_loader_id] = clip_vision_loader_node
+
+ ipadapter_loader_id = assembler._get_unique_id()
+ ipadapter_loader_node = assembler._get_node_template("IPAdapterSD3Loader")
+ ipadapter_loader_node['inputs']['ipadapter'] = "ip-adapter_sd35l_instantx.bin"
+ ipadapter_loader_node['inputs']['provider'] = "cuda"
+ assembler.workflow[ipadapter_loader_id] = ipadapter_loader_node
+
+ for item_data in chain_items:
+ image_loader_id = assembler._get_unique_id()
+ image_loader_node = assembler._get_node_template("LoadImage")
+ image_loader_node['inputs']['image'] = item_data['image']
+ assembler.workflow[image_loader_id] = image_loader_node
+
+ image_scaler_id = assembler._get_unique_id()
+ image_scaler_node = assembler._get_node_template("ImageScaleToTotalPixels")
+ image_scaler_node['inputs']['image'] = [image_loader_id, 0]
+ image_scaler_node['inputs']['upscale_method'] = 'nearest-exact'
+ image_scaler_node['inputs']['megapixels'] = 1.0
+ assembler.workflow[image_scaler_id] = image_scaler_node
+
+ clip_vision_encode_id = assembler._get_unique_id()
+ clip_vision_encode_node = assembler._get_node_template("CLIPVisionEncode")
+ clip_vision_encode_node['inputs']['crop'] = "center"
+ clip_vision_encode_node['inputs']['clip_vision'] = [clip_vision_loader_id, 0]
+ clip_vision_encode_node['inputs']['image'] = [image_scaler_id, 0]
+ assembler.workflow[clip_vision_encode_id] = clip_vision_encode_node
+
+ apply_ipa_id = assembler._get_unique_id()
+ apply_ipa_node = assembler._get_node_template("ApplyIPAdapterSD3")
+
+ apply_ipa_node['inputs']['weight'] = item_data.get('weight', 1.0)
+ apply_ipa_node['inputs']['start_percent'] = item_data.get('start_percent', 0.0)
+ apply_ipa_node['inputs']['end_percent'] = item_data.get('end_percent', 1.0)
+
+ apply_ipa_node['inputs']['model'] = current_model_connection
+ apply_ipa_node['inputs']['ipadapter'] = [ipadapter_loader_id, 0]
+ apply_ipa_node['inputs']['image_embed'] = [clip_vision_encode_id, 0]
+
+ assembler.workflow[apply_ipa_id] = apply_ipa_node
+
+ current_model_connection = [apply_ipa_id, 0]
+
+ assembler.workflow[ksampler_id]['inputs']['model'] = current_model_connection
+
+ print(f"SD3 IPAdapter injector applied. KSampler model input re-routed through {len(chain_items)} IPAdapter(s).")
\ No newline at end of file
diff --git a/chain_injectors/style_injector.py b/chain_injectors/style_injector.py
new file mode 100644
index 0000000000000000000000000000000000000000..48d903404d4752a8f821a4c00956135d890cdac8
--- /dev/null
+++ b/chain_injectors/style_injector.py
@@ -0,0 +1,71 @@
+def inject(assembler, chain_definition, chain_items):
+ if not chain_items:
+ return
+
+ flux_guidance_name = chain_definition.get('flux_guidance_node')
+ ksampler_name = chain_definition.get('ksampler_node', 'ksampler')
+
+ target_node_id = None
+ target_input_name = None
+
+ if flux_guidance_name and flux_guidance_name in assembler.node_map:
+ flux_guidance_id = assembler.node_map[flux_guidance_name]
+ if 'conditioning' in assembler.workflow[flux_guidance_id]['inputs']:
+ target_node_id = flux_guidance_id
+ target_input_name = 'conditioning'
+
+ if not target_node_id:
+ if ksampler_name in assembler.node_map:
+ ksampler_id = assembler.node_map[ksampler_name]
+ if 'positive' in assembler.workflow[ksampler_id]['inputs']:
+ target_node_id = ksampler_id
+ target_input_name = 'positive'
+ else:
+ return
+
+ if not target_node_id:
+ return
+
+ current_conditioning = assembler.workflow[target_node_id]['inputs'][target_input_name]
+
+ style_model_loader_id = assembler._get_unique_id()
+ style_model_loader_node = assembler._get_node_template("StyleModelLoader")
+ style_model_loader_node['inputs']['style_model_name'] = "flux1-redux-dev.safetensors"
+ assembler.workflow[style_model_loader_id] = style_model_loader_node
+
+ clip_vision_loader_id = assembler._get_unique_id()
+ clip_vision_loader_node = assembler._get_node_template("CLIPVisionLoader")
+ clip_vision_loader_node['inputs']['clip_name'] = "sigclip_vision_patch14_384.safetensors"
+ assembler.workflow[clip_vision_loader_id] = clip_vision_loader_node
+
+ for item_data in chain_items:
+ image = item_data.get('image')
+ strength = item_data.get('strength', 1.0)
+ if not image or strength is None:
+ continue
+
+ load_image_id = assembler._get_unique_id()
+ clip_vision_encode_id = assembler._get_unique_id()
+ style_apply_id = assembler._get_unique_id()
+
+ load_image_node = assembler._get_node_template("LoadImage")
+ clip_vision_encode_node = assembler._get_node_template("CLIPVisionEncode")
+ style_apply_node = assembler._get_node_template("StyleModelApply")
+
+ load_image_node['inputs']['image'] = image
+ clip_vision_encode_node['inputs']['crop'] = "center"
+ clip_vision_encode_node['inputs']['clip_vision'] = [clip_vision_loader_id, 0]
+ clip_vision_encode_node['inputs']['image'] = [load_image_id, 0]
+
+ style_apply_node['inputs']['strength'] = strength
+ style_apply_node['inputs']['strength_type'] = "multiply"
+ style_apply_node['inputs']['conditioning'] = current_conditioning
+ style_apply_node['inputs']['style_model'] = [style_model_loader_id, 0]
+ style_apply_node['inputs']['clip_vision_output'] = [clip_vision_encode_id, 0]
+
+ assembler.workflow[load_image_id] = load_image_node
+ assembler.workflow[clip_vision_encode_id] = clip_vision_encode_node
+ assembler.workflow[style_apply_id] = style_apply_node
+ current_conditioning = [style_apply_id, 0]
+
+ assembler.workflow[target_node_id]['inputs'][target_input_name] = current_conditioning
\ No newline at end of file
diff --git a/comfy_integration/nodes.py b/comfy_integration/nodes.py
index 76ba407e74bfffa63585c1e3505b39ec408d6711..7c37329e6422ca315c6afe7848bdafe5072c068f 100644
--- a/comfy_integration/nodes.py
+++ b/comfy_integration/nodes.py
@@ -23,6 +23,11 @@ CLIPTextEncodeSDXL = NODE_CLASS_MAPPINGS['CLIPTextEncodeSDXL']
LoraLoader = NODE_CLASS_MAPPINGS['LoraLoader']
CLIPSetLastLayer = NODE_CLASS_MAPPINGS['CLIPSetLastLayer']
+if 'EmptyHunyuanImageLatent' in NODE_CLASS_MAPPINGS:
+ EmptyHunyuanImageLatent = NODE_CLASS_MAPPINGS['EmptyHunyuanImageLatent']
+else:
+ print("⚠️ Warning: 'EmptyHunyuanImageLatent' not found in NODE_CLASS_MAPPINGS. HunyuanImage txt2img may fail if this node is required.")
+
try:
KSamplerNode = NODE_CLASS_MAPPINGS['KSampler']
SAMPLER_CHOICES = KSamplerNode.INPUT_TYPES()["required"]["sampler_name"][0]
diff --git a/comfy_integration/setup.py b/comfy_integration/setup.py
index b14b873cc0e7be9aa1fa809d328ffa19db425eb7..17f34ccc583fee8cfadeff1ee6aae708a1af9ba3 100644
--- a/comfy_integration/setup.py
+++ b/comfy_integration/setup.py
@@ -41,13 +41,8 @@ def initialize_comfyui():
print("--- Cloning third-party extensions for ComfyUI ---")
- controlnet_aux_path = os.path.join(APP_DIR, "custom_nodes", "comfyui_controlnet_aux")
- if not os.path.exists(controlnet_aux_path):
- os.system(f"git clone https://github.com/Fannovel16/comfyui_controlnet_aux.git {controlnet_aux_path}")
- print("✅ comfyui_controlnet_aux extension cloned.")
- else:
- print("✅ comfyui_controlnet_aux extension already exists.")
+ # 1. ComfyUI_IPAdapter_plus
ipadapter_plus_path = os.path.join(APP_DIR, "custom_nodes", "ComfyUI_IPAdapter_plus")
if not os.path.exists(ipadapter_plus_path):
os.system(f"git clone https://github.com/cubiq/ComfyUI_IPAdapter_plus.git {ipadapter_plus_path}")
@@ -55,6 +50,30 @@ def initialize_comfyui():
else:
print("✅ ComfyUI_IPAdapter_plus extension already exists.")
+ # 2. ComfyUI-InstantX-IPAdapter-SD3
+ ipadapter_plus_path = os.path.join(APP_DIR, "custom_nodes", "ComfyUI-InstantX-IPAdapter-SD3")
+ if not os.path.exists(ipadapter_plus_path):
+ os.system(f"git clone https://github.com/Slickytail/ComfyUI-InstantX-IPAdapter-SD3.git {ipadapter_plus_path}")
+ print("✅ ComfyUI-InstantX-IPAdapter-SD3 extension cloned.")
+ else:
+ print("✅ ComfyUI-InstantX-IPAdapter-SD3 extension already exists.")
+
+ # 3. ComfyUI-IPAdapter-Flux
+ ipadapter_flux_path = os.path.join(APP_DIR, "custom_nodes", "ComfyUI-IPAdapter-Flux")
+ if not os.path.exists(ipadapter_flux_path):
+ os.system(f"git clone https://github.com/Shakker-Labs/ComfyUI-IPAdapter-Flux.git {ipadapter_flux_path}")
+ print("✅ ComfyUI-IPAdapter-Flux extension cloned.")
+ else:
+ print("✅ ComfyUI-IPAdapter-Flux extension already exists.")
+
+ # 4. ComfyUI-Newbie-Nodes
+ newbie_nodes_path = os.path.join(APP_DIR, "custom_nodes", "ComfyUI-Newbie-Nodes")
+ if not os.path.exists(newbie_nodes_path):
+ os.system(f"git clone https://github.com/NewBieAI-Lab/ComfyUI-Newbie-Nodes.git {newbie_nodes_path}")
+ print("✅ ComfyUI-Newbie-Nodes extension cloned.")
+ else:
+ print("✅ ComfyUI-Newbie-Nodes extension already exists.")
+
print(f"✅ Current working directory is: {os.getcwd()}")
import comfy.model_management
@@ -62,12 +81,10 @@ def initialize_comfyui():
print("✅ ComfyUI initialized with default attention mechanism.")
- os.makedirs(os.path.join(APP_DIR, CHECKPOINT_DIR), exist_ok=True)
- os.makedirs(os.path.join(APP_DIR, LORA_DIR), exist_ok=True)
- os.makedirs(os.path.join(APP_DIR, EMBEDDING_DIR), exist_ok=True)
- os.makedirs(os.path.join(APP_DIR, CONTROLNET_DIR), exist_ok=True)
- os.makedirs(os.path.join(APP_DIR, DIFFUSION_MODELS_DIR), exist_ok=True)
- os.makedirs(os.path.join(APP_DIR, VAE_DIR), exist_ok=True)
- os.makedirs(os.path.join(APP_DIR, TEXT_ENCODERS_DIR), exist_ok=True)
+ for dir_path in CATEGORY_TO_DIR_MAP.values():
+ os.makedirs(os.path.join(APP_DIR, dir_path), exist_ok=True)
+
os.makedirs(os.path.join(APP_DIR, INPUT_DIR), exist_ok=True)
+ os.makedirs(os.path.join(APP_DIR, OUTPUT_DIR), exist_ok=True)
+
print("✅ All required model directories are present.")
\ No newline at end of file
diff --git a/core/generation_logic.py b/core/generation_logic.py
index 4e6433741c40a2e2342dc8dfe632fbf5ac60951d..a09b0076b3d2261c7f32420c87d157f967876041 100644
--- a/core/generation_logic.py
+++ b/core/generation_logic.py
@@ -1,25 +1,10 @@
from typing import Any, Dict
import gradio as gr
-from core.pipelines.controlnet_preprocessor import ControlNetPreprocessorPipeline
from core.pipelines.sd_image_pipeline import SdImagePipeline
-controlnet_preprocessor_pipeline = ControlNetPreprocessorPipeline()
sd_image_pipeline = SdImagePipeline()
-def build_reverse_map():
- from nodes import NODE_DISPLAY_NAME_MAPPINGS
- import core.pipelines.controlnet_preprocessor as cn_module
-
- if cn_module.REVERSE_DISPLAY_NAME_MAP is None:
- cn_module.REVERSE_DISPLAY_NAME_MAP = {v: k for k, v in NODE_DISPLAY_NAME_MAPPINGS.items()}
- if "Semantic Segmentor (legacy, alias for UniFormer)" not in cn_module.REVERSE_DISPLAY_NAME_MAP:
- cn_module.REVERSE_DISPLAY_NAME_MAP["Semantic Segmentor (legacy, alias for UniFormer)"] = "SemSegPreprocessor"
-
-
-def run_cn_preprocessor_entry(*args, **kwargs):
- return controlnet_preprocessor_pipeline.run(*args, **kwargs)
-
def generate_image_wrapper(ui_inputs: dict, progress=gr.Progress(track_tqdm=True)):
return sd_image_pipeline.run(ui_inputs=ui_inputs, progress=progress)
\ No newline at end of file
diff --git a/core/model_manager.py b/core/model_manager.py
index aae96b686035c23fe48e9dd513ff730a33d37b79..a4b0d217883a31d017df8f3b00ec9dbb7b271531 100644
--- a/core/model_manager.py
+++ b/core/model_manager.py
@@ -1,9 +1,8 @@
import gc
from typing import List
import gradio as gr
-
-from core.settings import ALL_MODEL_MAP
from utils.app_utils import _ensure_model_downloaded
+from core.settings import ALL_MODEL_MAP
class ModelManager:
_instance = None
@@ -23,11 +22,11 @@ class ModelManager:
print(f"--- [ModelManager] Ensuring models are downloaded: {required_models} ---")
for i, display_name in enumerate(required_models):
if progress and hasattr(progress, '__call__'):
- progress(i / len(required_models), desc=f"Checking file: {display_name}")
+ progress(i / max(len(required_models), 1), desc=f"Checking file: {display_name}")
try:
_ensure_model_downloaded(display_name, progress)
except Exception as e:
raise gr.Error(f"Failed to download model '{display_name}'. Reason: {e}")
print(f"--- [ModelManager] ✅ All required models are present on disk. ---")
-
+
model_manager = ModelManager()
\ No newline at end of file
diff --git a/core/pipelines/controlnet_preprocessor.py b/core/pipelines/controlnet_preprocessor.py
deleted file mode 100644
index bdfec36241e60425488b16bbc1e0bb14d39906ec..0000000000000000000000000000000000000000
--- a/core/pipelines/controlnet_preprocessor.py
+++ /dev/null
@@ -1,143 +0,0 @@
-from typing import Dict, Any, List
-import imageio
-import tempfile
-import numpy as np
-import torch
-import gradio as gr
-from PIL import Image
-import spaces
-
-from .base_pipeline import BasePipeline
-from comfy_integration.nodes import NODE_CLASS_MAPPINGS
-from nodes import NODE_DISPLAY_NAME_MAPPINGS
-from utils.app_utils import get_value_at_index
-
-REVERSE_DISPLAY_NAME_MAP = None
-CPU_ONLY_PREPROCESSORS = {
- "Binary Lines", "Canny Edge", "Color Pallete", "Fake Scribble Lines (aka scribble_hed)",
- "Image Intensity", "Image Luminance", "Inpaint Preprocessor", "PyraCanny", "Scribble Lines",
- "Scribble XDoG Lines", "Standard Lineart", "Content Shuffle", "Tile"
-}
-
-def run_node_by_function_name(node_instance: Any, **kwargs) -> Any:
- node_class = type(node_instance)
- function_name = getattr(node_class, 'FUNCTION', None)
- if not function_name:
- raise AttributeError(f"Node class '{node_class.__name__}' is missing the required 'FUNCTION' attribute.")
- execution_method = getattr(node_instance, function_name, None)
- if not callable(execution_method):
- raise AttributeError(f"Method '{function_name}' not found or not callable on node '{node_class.__name__}'.")
- return execution_method(**kwargs)
-
-class ControlNetPreprocessorPipeline(BasePipeline):
- def get_required_models(self, **kwargs) -> List[str]:
- return []
-
- def _gpu_logic(
- self, pil_images: List[Image.Image], preprocessor_name: str, model_name: str,
- params: Dict[str, Any], progress=gr.Progress(track_tqdm=True)
- ) -> List[Image.Image]:
- global REVERSE_DISPLAY_NAME_MAP
- if REVERSE_DISPLAY_NAME_MAP is None:
- raise RuntimeError("REVERSE_DISPLAY_NAME_MAP has not been initialized. `build_reverse_map` must be called on startup.")
-
- class_name = REVERSE_DISPLAY_NAME_MAP.get(preprocessor_name)
- if not class_name or class_name not in NODE_CLASS_MAPPINGS:
- raise ValueError(f"Preprocessor '{preprocessor_name}' not found.")
-
- preprocessor_instance = NODE_CLASS_MAPPINGS[class_name]()
- call_args = {**params, 'ckpt_name': model_name}
-
- processed_pil_images = []
- total_frames = len(pil_images)
-
- for i, frame_pil in enumerate(pil_images):
- progress(i / total_frames, desc=f"Processing frame {i+1}/{total_frames} with {preprocessor_name}...")
-
- frame_tensor = torch.from_numpy(np.array(frame_pil).astype(np.float32) / 255.0).unsqueeze(0)
-
- resolution_arg = {'resolution': max(frame_tensor.shape[2], frame_tensor.shape[3])}
-
- result_tuple = run_node_by_function_name(
- preprocessor_instance,
- image=frame_tensor,
- **resolution_arg,
- **call_args
- )
-
- processed_tensor = get_value_at_index(result_tuple, 0)
- processed_np = (processed_tensor.squeeze(0).cpu().numpy().clip(0, 1) * 255.0).astype(np.uint8)
- processed_pil_images.append(Image.fromarray(processed_np))
-
- return processed_pil_images
-
- def run(self, input_type, image_input, video_input, preprocessor_name, model_name, zero_gpu_duration, *args, progress=gr.Progress(track_tqdm=True)):
- from utils import app_utils
- pil_images, is_video, fps = [], False, 30
-
- progress(0, desc="Reading input file...")
- if input_type == "Image":
- if image_input is None: raise gr.Error("Please provide an input image.")
- pil_images = [image_input]
- elif input_type == "Video":
- if video_input is None: raise gr.Error("Please provide an input video.")
- try:
- video_reader = imageio.get_reader(video_input)
- meta = video_reader.get_meta_data()
- fps = meta.get('fps', 30)
- pil_images = [Image.fromarray(frame) for frame in video_reader]
- is_video = True
- video_reader.close()
- except Exception as e: raise gr.Error(f"Failed to read video file: {e}")
- else:
- raise gr.Error("Invalid input type selected.")
-
- if not pil_images: raise gr.Error("Could not extract any frames from the input.")
-
- if app_utils.PREPROCESSOR_PARAMETER_MAP is None:
- raise RuntimeError("Preprocessor parameter map is not built. Check startup logs.")
-
- params_config = app_utils.PREPROCESSOR_PARAMETER_MAP.get(preprocessor_name, [])
- sliders_params = [p for p in params_config if p['type'] in ["INT", "FLOAT"]]
- dropdown_params = [p for p in params_config if isinstance(p['type'], list)]
- checkbox_params = [p for p in params_config if p['type'] == "BOOLEAN"]
- ordered_params_config = sliders_params + dropdown_params + checkbox_params
- param_names = [p['name'] for p in ordered_params_config]
- provided_params = {param_names[i]: args[i] for i in range(len(param_names))}
-
- if preprocessor_name not in CPU_ONLY_PREPROCESSORS:
- print(f"--- '{preprocessor_name}' requires GPU, requesting ZeroGPU. ---")
- try:
- processed_pil_images = self._execute_gpu_logic(
- self._gpu_logic,
- duration=zero_gpu_duration,
- default_duration=60,
- task_name=f"Preprocessor '{preprocessor_name}'",
- pil_images=pil_images,
- preprocessor_name=preprocessor_name,
- model_name=model_name,
- params=provided_params,
- progress=progress
- )
- except Exception as e:
- import traceback; traceback.print_exc()
- raise gr.Error(f"Failed to run preprocessor '{preprocessor_name}' on GPU: {e}")
- else:
- print(f"--- Running '{preprocessor_name}' on CPU, no ZeroGPU requested. ---")
- try:
- processed_pil_images = self._gpu_logic(pil_images, preprocessor_name, model_name, provided_params, progress=progress)
- except Exception as e:
- import traceback; traceback.print_exc()
- raise gr.Error(f"Failed to run preprocessor '{preprocessor_name}' on CPU: {e}")
-
- if not processed_pil_images: raise gr.Error("Processing returned no frames.")
-
- progress(0.9, desc="Finalizing output...")
- if is_video:
- frames_np = [np.array(img) for img in processed_pil_images]
- frames_tensor = torch.from_numpy(np.stack(frames_np)).to(torch.float32) / 255.0
- video_path = self._encode_video_from_frames(frames_tensor, fps, progress)
- return [video_path]
- else:
- progress(1.0, desc="Done!")
- return processed_pil_images
\ No newline at end of file
diff --git a/core/pipelines/sd_image_pipeline.py b/core/pipelines/sd_image_pipeline.py
index d3ccc27f9c7352d85cc3dec3f6e57a7f7ff60a4b..edec50749f3672e9990e6d6bd3604ff3db49212d 100644
--- a/core/pipelines/sd_image_pipeline.py
+++ b/core/pipelines/sd_image_pipeline.py
@@ -16,7 +16,15 @@ from core.workflow_assembler import WorkflowAssembler
class SdImagePipeline(BasePipeline):
def get_required_models(self, model_display_name: str, **kwargs) -> List[str]:
- return [model_display_name]
+ model_info = ALL_MODEL_MAP.get(model_display_name)
+ if not model_info:
+ return [model_display_name]
+
+ path_or_components = model_info[1]
+ if isinstance(path_or_components, dict):
+ return [v for v in path_or_components.values() if v and v != "pixel_space"]
+ else:
+ return [model_display_name]
def _topological_sort(self, workflow: Dict[str, Any]) -> List[str]:
graph = defaultdict(list)
@@ -118,7 +126,7 @@ class SdImagePipeline(BasePipeline):
progress(0.4, desc="Executing workflow...")
initial_objects = {}
-
+
decoded_images_tensor = self._execute_workflow(workflow, initial_objects=initial_objects)
output_images = []
@@ -134,6 +142,7 @@ class SdImagePipeline(BasePipeline):
params_string = f"{ui_inputs['positive_prompt']}\nNegative prompt: {ui_inputs['negative_prompt']}\n"
params_string += f"Steps: {ui_inputs['num_inference_steps']}, Sampler: {ui_inputs['sampler']}, Scheduler: {ui_inputs['scheduler']}, CFG scale: {ui_inputs['guidance_scale']}, Seed: {current_seed}, Size: {width_for_meta}x{height_for_meta}, Base Model: {model_display_name}"
if ui_inputs['task_type'] != 'txt2img': params_string += f", Denoise: {ui_inputs['denoise']}"
+ if ui_inputs.get('clip_skip') and ui_inputs['clip_skip'] != 1: params_string += f", Clip skip: {abs(ui_inputs['clip_skip'])}"
if loras_string: params_string += f", {loras_string}"
pil_image.info = {'parameters': params_string.strip()}
@@ -145,26 +154,34 @@ class SdImagePipeline(BasePipeline):
progress(0, desc="Preparing models...")
task_type = ui_inputs['task_type']
+ model_display_name = ui_inputs['model_display_name']
+ model_type = MODEL_TYPE_MAP.get(model_display_name, 'sdxl')
+
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ workflow_model_type = architectures_dict.get(model_type, {}).get("model_type", "sdxl")
ui_inputs['positive_prompt'] = sanitize_prompt(ui_inputs.get('positive_prompt', ''))
ui_inputs['negative_prompt'] = sanitize_prompt(ui_inputs.get('negative_prompt', ''))
- required_models = self.get_required_models(model_display_name=ui_inputs['model_display_name'])
-
+ if 'clip_skip' in ui_inputs and ui_inputs['clip_skip'] is not None:
+ ui_inputs['clip_skip'] = -int(ui_inputs['clip_skip'])
+ else:
+ ui_inputs['clip_skip'] = -1
+
+ required_models = self.get_required_models(model_display_name=model_display_name)
self.model_manager.ensure_models_downloaded(required_models, progress=progress)
lora_data = ui_inputs.get('lora_data', [])
active_loras_for_gpu, active_loras_for_meta = [], []
if lora_data:
sources, ids, scales, files = lora_data[0::4], lora_data[1::4], lora_data[2::4], lora_data[3::4]
-
for i, (source, lora_id, scale, _) in enumerate(zip(sources, ids, scales, files)):
if scale > 0 and lora_id and lora_id.strip():
lora_filename = None
if source == "File":
lora_filename = sanitize_filename(lora_id)
elif source == "Civitai":
- local_path, status = get_lora_path(source, lora_id, ui_inputs['civitai_api_key'], progress)
+ local_path, status = get_lora_path(source, lora_id, os.environ.get("CIVITAI_API_KEY", ""), progress)
if local_path: lora_filename = os.path.basename(local_path)
else: raise gr.Error(f"Failed to prepare LoRA {lora_id}: {status}")
@@ -177,7 +194,6 @@ class SdImagePipeline(BasePipeline):
elif task_type == 'hires_fix': ui_inputs['denoise'] = ui_inputs.get('hires_denoise', 0.55)
temp_files_to_clean = []
-
if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
if task_type == 'img2img':
@@ -196,7 +212,6 @@ class SdImagePipeline(BasePipeline):
raise gr.Error("Inpainting requires an input image and a drawn mask.")
background_img = inpaint_dict['background'].convert("RGBA")
-
composite_mask_pil = Image.new('L', background_img.size, 0)
for layer in inpaint_dict['layers']:
if layer:
@@ -210,7 +225,7 @@ class SdImagePipeline(BasePipeline):
temp_file_path = os.path.join(INPUT_DIR, f"temp_inpaint_composite_{random.randint(1000, 9999)}.png")
composite_image_with_mask.save(temp_file_path, "PNG")
- ui_inputs['inpaint_image'] = os.path.basename(temp_file_path)
+ ui_inputs['input_image'] = os.path.basename(temp_file_path)
temp_files_to_clean.append(temp_file_path)
ui_inputs.pop('inpaint_mask', None)
@@ -221,6 +236,9 @@ class SdImagePipeline(BasePipeline):
input_image_pil.save(temp_file_path, "PNG")
ui_inputs['input_image'] = os.path.basename(temp_file_path)
temp_files_to_clean.append(temp_file_path)
+
+ ui_inputs['megapixels'] = 0.25
+ ui_inputs['grow_mask_by'] = ui_inputs.get('feathering', 10)
elif task_type == 'hires_fix':
input_image_pil = ui_inputs.get('hires_image')
@@ -240,7 +258,7 @@ class SdImagePipeline(BasePipeline):
if source == "File":
emb_filename = sanitize_filename(emb_id)
elif source == "Civitai":
- local_path, status = get_embedding_path(source, emb_id, ui_inputs['civitai_api_key'], progress)
+ local_path, status = get_embedding_path(source, emb_id, os.environ.get("CIVITAI_API_KEY", ""), progress)
if local_path: emb_filename = os.path.basename(local_path)
else: raise gr.Error(f"Failed to prepare Embedding {emb_id}: {status}")
@@ -256,19 +274,36 @@ class SdImagePipeline(BasePipeline):
controlnet_data = ui_inputs.get('controlnet_data', [])
active_controlnets = []
- (cn_images, _, _, cn_strengths, cn_filepaths) = [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_cn_{i}_{random.randint(1000, 9999)}.png")
- cn_images[i].save(cn_temp_path, "PNG")
- temp_files_to_clean.append(cn_temp_path)
- active_controlnets.append({
- "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]
- })
+ if controlnet_data:
+ (cn_images, _, _, cn_strengths, cn_filepaths) = [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_cn_{i}_{random.randint(1000, 9999)}.png")
+ cn_images[i].save(cn_temp_path, "PNG")
+ temp_files_to_clean.append(cn_temp_path)
+ active_controlnets.append({
+ "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]
+ })
+
+ diffsynth_controlnet_data = ui_inputs.get('diffsynth_controlnet_data', [])
+ active_diffsynth_controlnets = []
+ if 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]
+ })
ipadapter_data = ui_inputs.get('ipadapter_data', [])
active_ipadapters = []
@@ -276,13 +311,10 @@ class SdImagePipeline(BasePipeline):
num_ipa_units = (len(ipadapter_data) - 5) // 3
final_preset, final_weight, final_lora_strength, final_embeds_scaling, final_combine_method = ipadapter_data[-5:]
ipa_images, ipa_weights, ipa_lora_strengths = [ipadapter_data[i*num_ipa_units:(i+1)*num_ipa_units] for i in range(3)]
-
all_presets_to_download = set()
-
for i in range(num_ipa_units):
if ipa_images[i] and ipa_weights[i] > 0 and final_preset:
all_presets_to_download.add(final_preset)
-
if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
ipa_temp_path = os.path.join(INPUT_DIR, f"temp_ipa_{i}_{random.randint(1000, 9999)}.png")
ipa_images[i].save(ipa_temp_path, "PNG")
@@ -291,34 +323,111 @@ class SdImagePipeline(BasePipeline):
"image": os.path.basename(ipa_temp_path), "preset": final_preset,
"weight": ipa_weights[i], "lora_strength": ipa_lora_strengths[i]
})
-
if active_ipadapters and final_preset:
all_presets_to_download.add(final_preset)
-
for preset in all_presets_to_download:
ensure_ipadapter_models_downloaded(preset, progress)
-
+
+ model_type_key = 'sd15' if workflow_model_type == 'sd15' else 'sdxl'
if active_ipadapters:
active_ipadapters.append({
- 'is_final_settings': True, 'model_type': 'sdxl', 'final_preset': final_preset,
+ 'is_final_settings': True, 'model_type': model_type_key, 'final_preset': final_preset,
'final_weight': final_weight, 'final_lora_strength': final_lora_strength,
'final_embeds_scaling': final_embeds_scaling, 'final_combine_method': final_combine_method
})
+
+ flux1_ipadapter_data = ui_inputs.get('flux1_ipadapter_data', [])
+ active_flux1_ipadapters = []
+ if flux1_ipadapter_data:
+ num_units = len(flux1_ipadapter_data) // 4
+ f_images = flux1_ipadapter_data[0*num_units : 1*num_units]
+ f_weights = flux1_ipadapter_data[1*num_units : 2*num_units]
+ f_starts = flux1_ipadapter_data[2*num_units : 3*num_units]
+ f_ends = flux1_ipadapter_data[3*num_units : 4*num_units]
+ for i in range(len(f_images)):
+ if f_images[i] and f_weights[i] > 0:
+ from utils.app_utils import _ensure_model_downloaded
+ for filename in ["ip-adapter.bin"]:
+ _ensure_model_downloaded(filename, progress)
+
+ from huggingface_hub import snapshot_download
+ progress(0.5, desc="Caching HF SigLIP model...")
+ snapshot_download(
+ repo_id="google/siglip-so400m-patch14-384",
+ allow_patterns=["*.json", "*.safetensors", "*.txt"],
+ ignore_patterns=["*.msgpack", "*.h5", "*.bin"]
+ )
+
+ temp_path = os.path.join(INPUT_DIR, f"temp_fipa_{i}_{random.randint(1000, 9999)}.png")
+ f_images[i].save(temp_path, "PNG")
+ temp_files_to_clean.append(temp_path)
+ active_flux1_ipadapters.append({
+ "image": os.path.basename(temp_path),
+ "weight": f_weights[i], "start_percent": f_starts[i], "end_percent": f_ends[i]
+ })
+
+ sd3_ipadapter_data = ui_inputs.get('sd3_ipadapter_chain', [])
+ active_sd3_ipadapters = []
+ if sd3_ipadapter_data:
+ num_units = len(sd3_ipadapter_data) // 4
+ s_images = sd3_ipadapter_data[0*num_units : 1*num_units]
+ s_weights = sd3_ipadapter_data[1*num_units : 2*num_units]
+ s_starts = sd3_ipadapter_data[2*num_units : 3*num_units]
+ s_ends = sd3_ipadapter_data[3*num_units : 4*num_units]
+ sd3_ipa_downloaded = False
+ for i in range(len(s_images)):
+ if s_images[i] and s_weights[i] > 0:
+ if not sd3_ipa_downloaded:
+ from utils.app_utils import ensure_sd3_ipadapter_models_downloaded
+ ensure_sd3_ipadapter_models_downloaded(progress)
+ sd3_ipa_downloaded = True
+ temp_path = os.path.join(INPUT_DIR, f"temp_s3ipa_{i}_{random.randint(1000, 9999)}.png")
+ s_images[i].save(temp_path, "PNG")
+ temp_files_to_clean.append(temp_path)
+ active_sd3_ipadapters.append({
+ "image": os.path.basename(temp_path),
+ "weight": s_weights[i], "start_percent": s_starts[i], "end_percent": s_ends[i]
+ })
+
+ style_data = ui_inputs.get('style_data', [])
+ active_styles = []
+ if style_data:
+ num_units = len(style_data) // 2
+ st_images = style_data[0*num_units : 1*num_units]
+ st_strengths = style_data[1*num_units : 2*num_units]
+ for i in range(len(st_images)):
+ if st_images[i] and st_strengths[i] > 0:
+ from utils.app_utils import _ensure_model_downloaded
+ _ensure_model_downloaded("sigclip_vision_patch14_384.safetensors", progress)
+ temp_path = os.path.join(INPUT_DIR, f"temp_style_{i}_{random.randint(1000, 9999)}.png")
+ st_images[i].save(temp_path, "PNG")
+ temp_files_to_clean.append(temp_path)
+ 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:
+ for img in reference_latent_data:
+ if img:
+ if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
+ temp_path = os.path.join(INPUT_DIR, f"temp_ref_{random.randint(1000, 9999)}.png")
+ img.save(temp_path, "PNG")
+ temp_files_to_clean.append(temp_path)
+ active_reference_latents.append(os.path.basename(temp_path))
from utils.app_utils import get_vae_path
vae_source = ui_inputs.get('vae_source')
vae_id = ui_inputs.get('vae_id')
- vae_file = ui_inputs.get('vae_file')
vae_name_override = None
-
if vae_source and vae_source != "None":
if vae_source == "File":
vae_name_override = sanitize_filename(vae_id)
elif vae_source == "Civitai" and vae_id and vae_id.strip():
- local_path, status = get_vae_path(vae_source, vae_id, ui_inputs.get('civitai_api_key'), progress)
+ local_path, status = get_vae_path(vae_source, vae_id, os.environ.get("CIVITAI_API_KEY", ""), progress)
if local_path: vae_name_override = os.path.basename(local_path)
else: raise gr.Error(f"Failed to prepare VAE {vae_id}: {status}")
-
if vae_name_override:
ui_inputs['vae_name'] = vae_name_override
@@ -326,22 +435,12 @@ class SdImagePipeline(BasePipeline):
active_conditioning = []
if conditioning_data:
num_units = len(conditioning_data) // 6
- prompts = conditioning_data[0*num_units : 1*num_units]
- widths = conditioning_data[1*num_units : 2*num_units]
- heights = conditioning_data[2*num_units : 3*num_units]
- xs = conditioning_data[3*num_units : 4*num_units]
- ys = conditioning_data[4*num_units : 5*num_units]
- strengths = conditioning_data[5*num_units : 6*num_units]
-
+ prompts, widths, heights, xs, ys, strengths = [conditioning_data[i*num_units : (i+1)*num_units] for i in range(6)]
for i in range(num_units):
if prompts[i] and prompts[i].strip():
active_conditioning.append({
- "prompt": prompts[i],
- "width": int(widths[i]),
- "height": int(heights[i]),
- "x": int(xs[i]),
- "y": int(ys[i]),
- "strength": float(strengths[i])
+ "prompt": prompts[i], "width": int(widths[i]), "height": int(heights[i]),
+ "x": int(xs[i]), "y": int(ys[i]), "strength": float(strengths[i])
})
loras_string = f"LoRAs: [{', '.join(active_loras_for_meta)}]" if active_loras_for_meta else ""
@@ -350,31 +449,62 @@ class SdImagePipeline(BasePipeline):
if ui_inputs.get('seed') == -1:
ui_inputs['seed'] = random.randint(0, 2**32 - 1)
-
- dynamic_values = {'task_type': ui_inputs['task_type'], 'model_type': "sdxl"}
+
+ model_info = ALL_MODEL_MAP[model_display_name]
+ path_or_components = model_info[1]
+ latent_type = model_info[3] if len(model_info) > 3 and model_info[3] else 'latent'
+ latent_generator_template = "EmptyLatentImage"
+ if latent_type == 'sd3_latent':
+ latent_generator_template = "EmptySD3LatentImage"
+ elif latent_type == 'chroma_radiance_latent':
+ latent_generator_template = "EmptyChromaRadianceLatentImage"
+ elif latent_type == 'hunyuan_latent':
+ latent_generator_template = "EmptyHunyuanImageLatent"
+
+ dynamic_values = {
+ 'task_type': ui_inputs['task_type'],
+ 'model_type': workflow_model_type,
+ 'latent_type': latent_type,
+ 'latent_generator_template': latent_generator_template
+ }
recipe_path = os.path.join(os.path.dirname(__file__), "workflow_recipes", "sd_unified_recipe.yaml")
assembler = WorkflowAssembler(recipe_path, dynamic_values=dynamic_values)
workflow_inputs = {
+ **ui_inputs,
"positive_prompt": ui_inputs['positive_prompt'], "negative_prompt": ui_inputs['negative_prompt'],
"seed": ui_inputs['seed'], "steps": ui_inputs['num_inference_steps'], "cfg": ui_inputs['guidance_scale'],
"sampler_name": ui_inputs['sampler'], "scheduler": ui_inputs['scheduler'],
"batch_size": ui_inputs['batch_size'],
- "denoise": ui_inputs['denoise'],
- "input_image": ui_inputs.get('input_image'),
- "inpaint_image": ui_inputs.get('inpaint_image'),
- "inpaint_mask": ui_inputs.get('inpaint_mask'),
- "left": ui_inputs.get('outpaint_left'), "top": ui_inputs.get('outpaint_top'),
- "right": ui_inputs.get('outpaint_right'), "bottom": ui_inputs.get('outpaint_bottom'),
- "hires_upscaler": ui_inputs.get('hires_upscaler'), "hires_scale_by": ui_inputs.get('hires_scale_by'),
- "model_name": ALL_MODEL_MAP[ui_inputs['model_display_name']][1],
+ "clip_skip": ui_inputs['clip_skip'],
+ "denoise": ui_inputs['denoise'],
"vae_name": ui_inputs.get('vae_name'),
+ "guidance": ui_inputs.get('guidance', 3.5),
"lora_chain": active_loras_for_gpu,
"controlnet_chain": active_controlnets,
+ "diffsynth_controlnet_chain": active_diffsynth_controlnets,
"ipadapter_chain": active_ipadapters,
+ "flux1_ipadapter_chain": active_flux1_ipadapters,
+ "sd3_ipadapter_chain": active_sd3_ipadapters,
+ "style_chain": active_styles,
"conditioning_chain": active_conditioning,
+ "reference_latent_chain": active_reference_latents,
}
+
+ if isinstance(path_or_components, dict):
+ workflow_inputs.update({
+ 'unet_name': path_or_components.get('unet'),
+ 'vae_name': ui_inputs.get('vae_name') or path_or_components.get('vae'),
+ 'clip_name': path_or_components.get('clip'),
+ 'clip1_name': path_or_components.get('clip1'),
+ 'clip2_name': path_or_components.get('clip2'),
+ 'clip3_name': path_or_components.get('clip3'),
+ 'clip4_name': path_or_components.get('clip4'),
+ 'lora_name': path_or_components.get('lora'),
+ })
+ else:
+ workflow_inputs['model_name'] = path_or_components
if task_type == 'txt2img':
workflow_inputs['width'] = ui_inputs['width']
@@ -382,24 +512,19 @@ class SdImagePipeline(BasePipeline):
workflow = assembler.assemble(workflow_inputs)
- if workflow_inputs.get("vae_name"):
+ if ui_inputs.get("vae_name") and workflow_model_type not in ['flux1', 'hidream', 'lumina', 'omnigen2', 'chroma1-radiance', 'chroma1', 'hunyuanimage', 'ovis-image', 'longcat-image']:
print("--- [Workflow Patch] VAE override provided. Adding VAELoader and rewiring connections. ---")
vae_loader_id = assembler._get_unique_id()
vae_loader_node = assembler._get_node_template("VAELoader")
- vae_loader_node['inputs']['vae_name'] = workflow_inputs["vae_name"]
+ vae_loader_node['inputs']['vae_name'] = ui_inputs["vae_name"]
workflow[vae_loader_id] = vae_loader_node
vae_decode_id = assembler.node_map.get("vae_decode")
if vae_decode_id and vae_decode_id in workflow:
workflow[vae_decode_id]['inputs']['vae'] = [vae_loader_id, 0]
- print(f" - Rewired 'vae_decode' (ID: {vae_decode_id}) to use new VAELoader.")
-
vae_encode_id = assembler.node_map.get("vae_encode")
if vae_encode_id and vae_encode_id in workflow:
workflow[vae_encode_id]['inputs']['vae'] = [vae_loader_id, 0]
- print(f" - Rewired 'vae_encode' (ID: {vae_encode_id}) to use new VAELoader.")
- else:
- print("--- [Workflow Info] No VAE override. Using VAE from checkpoint. ---")
progress(1.0, desc="All models ready. Requesting GPU for generation...")
diff --git a/core/pipelines/workflow_recipes/_partials/_base_sampler.yaml b/core/pipelines/workflow_recipes/_partials/_base_sampler.yaml
deleted file mode 100644
index 63915d18a9406e57ab8db30538c81e1c47c6254e..0000000000000000000000000000000000000000
--- a/core/pipelines/workflow_recipes/_partials/_base_sampler.yaml
+++ /dev/null
@@ -1,23 +0,0 @@
-nodes:
- ksampler:
- class_type: KSampler
-
- vae_decode:
- class_type: VAEDecode
- save_image:
- class_type: SaveImage
- params: {}
-
-connections:
- - from: "ksampler:0"
- to: "vae_decode:samples"
- - from: "vae_decode:0"
- to: "save_image:images"
-
-ui_map:
- seed: "ksampler:seed"
- steps: "ksampler:steps"
- cfg: "ksampler:cfg"
- sampler_name: "ksampler:sampler_name"
- scheduler: "ksampler:scheduler"
- denoise: "ksampler:denoise"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/_base_sampler_sd.yaml b/core/pipelines/workflow_recipes/_partials/_base_sampler_sd.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..64780e0f91c03c4e26d2c48381ef2aef6453dd2a
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/_base_sampler_sd.yaml
@@ -0,0 +1,36 @@
+nodes:
+ pos_prompt:
+ class_type: CLIPTextEncode
+ title: "CLIP Text Encode (Positive)"
+ neg_prompt:
+ class_type: CLIPTextEncode
+ title: "CLIP Text Encode (Negative)"
+ ksampler:
+ class_type: KSampler
+ title: "KSampler"
+ params:
+ denoise: 1.0
+ vae_decode:
+ class_type: VAEDecode
+ title: "VAE Decode"
+ save_image:
+ class_type: SaveImage
+ title: "Save Image"
+ params: {}
+
+connections:
+ - from: "ksampler:0"
+ to: "vae_decode:samples"
+ - from: "vae_decode:0"
+ to: "save_image:images"
+
+ui_map:
+ positive_prompt: "pos_prompt:text"
+ negative_prompt: "neg_prompt:text"
+ seed: "ksampler:seed"
+ steps: "ksampler:steps"
+ cfg: "ksampler:cfg"
+ sampler_name: "ksampler:sampler_name"
+ scheduler: "ksampler:scheduler"
+ denoise: "ksampler:denoise"
+ filename_prefix: "save_image:filename_prefix"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/anima.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/anima.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f6a08f0afd20f53fe3c55680606b1ee1a0ef81e5
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/anima.yaml
@@ -0,0 +1,54 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "stable_diffusion"
+ device: "default"
+
+connections:
+ - from: "unet_loader:0"
+ to: "ksampler:model"
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["ksampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip_name: "clip_loader:clip_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/chroma1-radiance.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/chroma1-radiance.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..0b9a569f276b6ac2a909f9b06ee90e0f97eadf9a
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/chroma1-radiance.yaml
@@ -0,0 +1,59 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ params:
+ vae_name: "pixel_space"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "chroma"
+ device: "default"
+ t5_tokenizer:
+ class_type: T5TokenizerOptions
+ title: "T5TokenizerOptions"
+ params:
+ min_padding: 0
+ min_length: 3
+ model_sampler:
+ class_type: ModelSamplingAuraFlow
+ params:
+ shift: 3.0
+
+connections:
+ - from: "unet_loader:0"
+ to: "model_sampler:model"
+ - from: "model_sampler:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "t5_tokenizer:clip"
+ - from: "t5_tokenizer:0"
+ to: "pos_prompt:clip"
+ - from: "t5_tokenizer:0"
+ to: "neg_prompt:clip"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "t5_tokenizer:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ clip_name: "clip_loader:clip_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/chroma1.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/chroma1.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..36430aab40403c6f865c0a8269ee71d96b995efe
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/chroma1.yaml
@@ -0,0 +1,61 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "chroma"
+ device: "default"
+ t5_tokenizer:
+ class_type: T5TokenizerOptions
+ title: "T5TokenizerOptions"
+ params:
+ min_padding: 1
+ min_length: 0
+ fresca:
+ class_type: FreSca
+ title: "FreSca"
+ params:
+ scale_low: 1.0
+ scale_high: 2.5
+ freq_cutoff: 30
+
+connections:
+ - from: "unet_loader:0"
+ to: "fresca:model"
+ - from: "fresca:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "t5_tokenizer:clip"
+ - from: "t5_tokenizer:0"
+ to: "pos_prompt:clip"
+ - from: "t5_tokenizer:0"
+ to: "neg_prompt:clip"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "t5_tokenizer:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip_name: "clip_loader:clip_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/ernie-image.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/ernie-image.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..697ea92e2353f2ece2ebbbd5ca83230c54e87881
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/ernie-image.yaml
@@ -0,0 +1,54 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "flux2"
+ device: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+
+connections:
+ - from: "unet_loader:0"
+ to: "ksampler:model"
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["ksampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ clip_name: "clip_loader:clip_name"
+ vae_name: "vae_loader:vae_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/flux1.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/flux1.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7fd114dd312caa0479598def74f6f57a0bedf564
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/flux1.yaml
@@ -0,0 +1,64 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load FLUX UNET"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load FLUX VAE"
+ clip_loader:
+ class_type: DualCLIPLoader
+ title: "Load FLUX Dual CLIP"
+ params:
+ type: "flux"
+ device: "default"
+ flux_guidance:
+ class_type: FluxGuidance
+ title: "FluxGuidance"
+
+connections:
+ - from: "unet_loader:0"
+ to: "ksampler:model"
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+ - from: "pos_prompt:0"
+ to: "flux_guidance:conditioning"
+ - from: "flux_guidance:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+dynamic_controlnet_chains:
+ controlnet_chain:
+ template: "ControlNetApplyAdvanced"
+ ksampler_node: "ksampler"
+ vae_source: "vae_loader:0"
+
+dynamic_flux1_ipadapter_chains:
+ flux1_ipadapter_chain:
+ ksampler_node: "ksampler"
+
+dynamic_style_chains:
+ style_chain:
+ flux_guidance_node: "flux_guidance"
+ ksampler_node: "ksampler"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ flux_guidance_node: "flux_guidance"
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip1_name: "clip_loader:clip_name1"
+ clip2_name: "clip_loader:clip_name2"
+ guidance: "flux_guidance:guidance"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/flux2-kv.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/flux2-kv.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..c9cd6286f058a37e801c701e5d463228d66feadc
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/flux2-kv.yaml
@@ -0,0 +1,104 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "flux2"
+ device: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+
+ flux_kv_cache:
+ class_type: FluxKVCache
+ title: "Flux KV Cache"
+
+ pos_prompt:
+ class_type: CLIPTextEncode
+ title: "CLIP Text Encode (Positive)"
+ neg_prompt:
+ class_type: CLIPTextEncode
+ title: "CLIP Text Encode (Negative)"
+
+ ksampler:
+ class_type: KSampler
+ title: "KSampler"
+ params:
+ denoise: 1.0
+
+ vae_decode:
+ class_type: VAEDecode
+ title: "VAE Decode"
+
+ save_image:
+ class_type: SaveImage
+ title: "Save Image"
+
+connections:
+ - from: "unet_loader:0"
+ to: "flux_kv_cache:model"
+ - from: "flux_kv_cache:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "latent_source:0"
+ to: "ksampler:latent_image"
+
+ - from: "ksampler:0"
+ to: "vae_decode:samples"
+ - from: "vae_decode:0"
+ to: "save_image:images"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["flux_kv_cache:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_reference_latent_chains:
+ reference_latent_chain:
+ ksampler_node: "ksampler"
+ vae_node: "vae_loader"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ clip_name: "clip_loader:clip_name"
+ vae_name: "vae_loader:vae_name"
+
+ positive_prompt: "pos_prompt:text"
+ negative_prompt: "neg_prompt:text"
+
+ seed: "ksampler:seed"
+ steps: "ksampler:steps"
+ cfg: "ksampler:cfg"
+ sampler_name: "ksampler:sampler_name"
+ scheduler: "ksampler:scheduler"
+ denoise: "ksampler:denoise"
+
+ filename_prefix: "save_image:filename_prefix"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/flux2.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/flux2.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..49a5c55bfceaf5b792939342d12da365185111e5
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/flux2.yaml
@@ -0,0 +1,96 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "flux2"
+ device: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+
+ pos_prompt:
+ class_type: CLIPTextEncode
+ title: "CLIP Text Encode (Positive)"
+ neg_prompt:
+ class_type: CLIPTextEncode
+ title: "CLIP Text Encode (Negative)"
+
+ ksampler:
+ class_type: KSampler
+ title: "KSampler"
+ params:
+ denoise: 1.0
+
+ vae_decode:
+ class_type: VAEDecode
+ title: "VAE Decode"
+
+ save_image:
+ class_type: SaveImage
+ title: "Save Image"
+
+connections:
+ - from: "unet_loader:0"
+ to: "ksampler:model"
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "latent_source:0"
+ to: "ksampler:latent_image"
+
+ - from: "ksampler:0"
+ to: "vae_decode:samples"
+ - from: "vae_decode:0"
+ to: "save_image:images"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["ksampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_reference_latent_chains:
+ reference_latent_chain:
+ ksampler_node: "ksampler"
+ vae_node: "vae_loader"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ clip_name: "clip_loader:clip_name"
+ vae_name: "vae_loader:vae_name"
+
+ positive_prompt: "pos_prompt:text"
+ negative_prompt: "neg_prompt:text"
+
+ seed: "ksampler:seed"
+ steps: "ksampler:steps"
+ cfg: "ksampler:cfg"
+ sampler_name: "ksampler:sampler_name"
+ scheduler: "ksampler:scheduler"
+ denoise: "ksampler:denoise"
+
+ filename_prefix: "save_image:filename_prefix"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/hidream.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/hidream.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..1163c69deabaf68762e0aee9e1c27b12014e3f89
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/hidream.yaml
@@ -0,0 +1,53 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load HiDream UNET"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load HiDream VAE"
+ clip_loader:
+ class_type: QuadrupleCLIPLoader
+ title: "Load HiDream Quadruple CLIP"
+
+ model_sampler:
+ class_type: ModelSamplingSD3
+ title: "ModelSamplingSD3"
+ params:
+ shift: 6.0
+
+connections:
+ - from: "unet_loader:0"
+ to: "model_sampler:model"
+
+ - from: "model_sampler:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip1_name: "clip_loader:clip_name1"
+ clip2_name: "clip_loader:clip_name2"
+ clip3_name: "clip_loader:clip_name3"
+ clip4_name: "clip_loader:clip_name4"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/hunyuanimage.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/hunyuanimage.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..7fa9a42af9a6be0ff527e532026bd33309fc9373
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/hunyuanimage.yaml
@@ -0,0 +1,42 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Hunyuan UNET"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load Hunyuan VAE"
+ clip_loader:
+ class_type: DualCLIPLoader
+ title: "Load Hunyuan Dual CLIP"
+ params:
+ type: "hunyuan_image"
+ device: "default"
+
+connections:
+ - from: "unet_loader:0"
+ to: "ksampler:model"
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip1_name: "clip_loader:clip_name1"
+ clip2_name: "clip_loader:clip_name2"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/longcat-image.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/longcat-image.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..35097965ea3e30ae70c2d36019a8aa02e7709f9a
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/longcat-image.yaml
@@ -0,0 +1,83 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "longcat_image"
+ device: "default"
+
+ cfg_norm:
+ class_type: CFGNorm
+ title: "CFGNorm"
+ params:
+ strength: 1.0
+
+ flux_guidance_pos:
+ class_type: FluxGuidance
+ title: "FluxGuidance (Positive)"
+ params:
+ guidance: 4.0
+
+ flux_guidance_neg:
+ class_type: FluxGuidance
+ title: "FluxGuidance (Negative)"
+ params:
+ guidance: 4.0
+
+connections:
+ - from: "unet_loader:0"
+ to: "cfg_norm:model"
+ - from: "cfg_norm:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+
+ - from: "pos_prompt:0"
+ to: "flux_guidance_pos:conditioning"
+ - from: "neg_prompt:0"
+ to: "flux_guidance_neg:conditioning"
+
+ - from: "flux_guidance_pos:0"
+ to: "ksampler:positive"
+ - from: "flux_guidance_neg:0"
+ to: "ksampler:negative"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["cfg_norm:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ flux_guidance_node: "flux_guidance_pos"
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip_name: "clip_loader:clip_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/lumina.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/lumina.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3870541c779c66e8233b5f1c0a13a81f3f3c1523
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/lumina.yaml
@@ -0,0 +1,51 @@
+nodes:
+ ckpt_loader:
+ class_type: CheckpointLoaderSimple
+ title: "Load Checkpoint"
+ model_sampler:
+ class_type: ModelSamplingAuraFlow
+ title: "ModelSamplingAuraFlow"
+ params:
+ shift: 4.0
+
+connections:
+ - from: "ckpt_loader:0"
+ to: "model_sampler:model"
+ - from: "model_sampler:0"
+ to: "ksampler:model"
+
+ - from: "ckpt_loader:1"
+ to: "pos_prompt:clip"
+ - from: "ckpt_loader:1"
+ to: "neg_prompt:clip"
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "ckpt_loader:2"
+ to: "vae_decode:vae"
+ - from: "ckpt_loader:2"
+ to: "vae_encode:vae"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ start: "ckpt_loader"
+ output_map:
+ "0": "model"
+ "1": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["model_sampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "ckpt_loader:1"
+
+ui_map:
+ model_name: "ckpt_loader:ckpt_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/newbie-image.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/newbie-image.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ab287fbd9977623f60c5d44977c8865ee61745c9
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/newbie-image.yaml
@@ -0,0 +1,65 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ clip_loader:
+ class_type: DualCLIPLoader
+ title: "Load Dual CLIP"
+ params:
+ type: "newbie"
+ device: "default"
+ model_sampler:
+ class_type: ModelSamplingAuraFlow
+ title: "ModelSamplingAuraFlow"
+ params:
+ shift: 6
+
+connections:
+ - from: "unet_loader:0"
+ to: "model_sampler:model"
+ - from: "model_sampler:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_newbie_lora_chains:
+ lora_chain:
+ template: "NewBieLoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["model_sampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip1_name: "clip_loader:clip_name1"
+ clip2_name: "clip_loader:clip_name2"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/omnigen2.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/omnigen2.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..81d9307dd57d41c4cf74c46e05df4d105a5689ba
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/omnigen2.yaml
@@ -0,0 +1,59 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "omnigen2"
+ device: "default"
+
+connections:
+ - from: "unet_loader:0"
+ to: "ksampler:model"
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["ksampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+dynamic_reference_latent_chains:
+ reference_latent_chain:
+ ksampler_node: "ksampler"
+ vae_node: "vae_loader"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip_name: "clip_loader:clip_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/ovis-image.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/ovis-image.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ff757883324afc4fb2ec401bda3ae7f1bc0276d7
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/ovis-image.yaml
@@ -0,0 +1,50 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "ovis"
+ device: "default"
+ model_sampler:
+ class_type: ModelSamplingAuraFlow
+ params:
+ shift: 3.0
+
+connections:
+ - from: "unet_loader:0"
+ to: "model_sampler:model"
+ - from: "model_sampler:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip_name: "clip_loader:clip_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/qwen-image.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/qwen-image.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..9a8aa866a4a045fdf07841a4e229cc64cb254a04
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/qwen-image.yaml
@@ -0,0 +1,80 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Qwen UNET"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load Qwen VAE"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load Qwen CLIP"
+ params:
+ type: "qwen_image"
+ device: "default"
+
+ lora_loader:
+ class_type: LoraLoaderModelOnly
+ title: "Load Qwen Lightning LoRA"
+ params:
+ strength_model: 1.0
+ model_sampler:
+ class_type: ModelSamplingAuraFlow
+ title: "ModelSamplingAuraFlow"
+ params:
+ shift: 3.1
+
+connections:
+ - from: "unet_loader:0"
+ to: "lora_loader:model"
+ - from: "lora_loader:0"
+ to: "model_sampler:model"
+
+ - from: "model_sampler:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "lora_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["model_sampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_controlnet_chains:
+ controlnet_chain:
+ template: "ControlNetApplyAdvanced"
+ ksampler_node: "ksampler"
+ vae_source: "vae_loader:0"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip_name: "clip_loader:clip_name"
+ lora_name: "lora_loader:lora_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/sd15.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/sd15.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..65600018f31ef42aef4ff2d1453a91d6f659d204
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/sd15.yaml
@@ -0,0 +1,63 @@
+nodes:
+ ckpt_loader:
+ class_type: CheckpointLoaderSimple
+ title: "Load Checkpoint"
+ clip_set_last_layer:
+ class_type: CLIPSetLastLayer
+ title: "CLIP Set Last Layer"
+
+connections:
+ - from: "ckpt_loader:0"
+ to: "ksampler:model"
+ - from: "ckpt_loader:1"
+ to: "clip_set_last_layer:clip"
+ - from: "clip_set_last_layer:0"
+ to: "pos_prompt:clip"
+ - from: "clip_set_last_layer:0"
+ to: "neg_prompt:clip"
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+ - from: "ckpt_loader:2"
+ to: "vae_decode:vae"
+ - from: "ckpt_loader:2"
+ to: "vae_encode:vae"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ start: "clip_set_last_layer"
+ output_map:
+ "ckpt_loader:0": "model"
+ "0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["ksampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_controlnet_chains:
+ controlnet_chain:
+ template: "ControlNetApplyAdvanced"
+ ksampler_node: "ksampler"
+ vae_source: "ckpt_loader:2"
+
+dynamic_ipadapter_chains:
+ ipadapter_chain:
+ end: "ksampler"
+ final_preset: "{{ ipadapter_final_preset }}"
+ final_weight: "{{ ipadapter_final_weight }}"
+ final_embeds_scaling: "{{ ipadapter_embeds_scaling }}"
+ final_loader_type: "{{ ipadapter_final_loader_type }}"
+ final_lora_strength: "{{ ipadapter_final_lora_strength }}"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "clip_set_last_layer:0"
+
+ui_map:
+ model_name: "ckpt_loader:ckpt_name"
+ clip_skip: "clip_set_last_layer:stop_at_clip_layer"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/sd35.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/sd35.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..18874dc7e50ec6747d1d3361eda61dcfc90ff716
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/sd35.yaml
@@ -0,0 +1,52 @@
+nodes:
+ ckpt_loader:
+ class_type: CheckpointLoaderSimple
+ title: "Load Checkpoint"
+
+connections:
+ - from: "ckpt_loader:0"
+ to: "ksampler:model"
+ - from: "ckpt_loader:1"
+ to: "pos_prompt:clip"
+ - from: "ckpt_loader:1"
+ to: "neg_prompt:clip"
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+ - from: "ckpt_loader:2"
+ to: "vae_decode:vae"
+ - from: "ckpt_loader:2"
+ to: "vae_encode:vae"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ start: "ckpt_loader"
+ output_map:
+ "0": "model"
+ "1": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["ksampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_controlnet_chains:
+ controlnet_chain:
+ template: "ControlNetApplyAdvanced"
+ ksampler_node: "ksampler"
+ vae_source: "ckpt_loader:2"
+
+dynamic_sd3_ipadapter_chains:
+ sd3_ipadapter_chain:
+ ksampler_node: "ksampler"
+
+dynamic_conditioning_chains:
+ conditioning_chain:
+ ksampler_node: "ksampler"
+ clip_source: "ckpt_loader:1"
+
+ui_map:
+ model_name: "ckpt_loader:ckpt_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/sdxl.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/sdxl.yaml
index cd6c3310a8d7fba93e1c99363b859e176eadc85c..54b34e554ef7b2c1f43e8cb3c82f353a7f7388ae 100644
--- a/core/pipelines/workflow_recipes/_partials/conditioning/sdxl.yaml
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/sdxl.yaml
@@ -1,15 +1,7 @@
nodes:
ckpt_loader:
class_type: CheckpointLoaderSimple
- title: "Load SDXL Checkpoint"
-
- pos_prompt:
- class_type: CLIPTextEncode
- title: "Positive Prompt Encoder"
-
- neg_prompt:
- class_type: CLIPTextEncode
- title: "Negative Prompt Encoder"
+ title: "Load Checkpoint"
connections:
- from: "ckpt_loader:0"
@@ -18,26 +10,22 @@ connections:
to: "pos_prompt:clip"
- from: "ckpt_loader:1"
to: "neg_prompt:clip"
-
- - from: "ckpt_loader:2"
- to: "vae_decode:vae"
-
- from: "pos_prompt:0"
to: "ksampler:positive"
- from: "neg_prompt:0"
to: "ksampler:negative"
-
-ui_map:
- model_name: "ckpt_loader:ckpt_name"
- positive_prompt: "pos_prompt:text"
- negative_prompt: "neg_prompt:text"
-
+ - from: "ckpt_loader:2"
+ to: "vae_decode:vae"
+ - from: "ckpt_loader:2"
+ to: "vae_encode:vae"
+
dynamic_lora_chains:
lora_chain:
template: "LoraLoader"
+ start: "ckpt_loader"
output_map:
- "ckpt_loader:0": "model"
- "ckpt_loader:1": "clip"
+ "0": "model"
+ "1": "clip"
input_map:
"model": "model"
"clip": "clip"
@@ -57,8 +45,13 @@ dynamic_ipadapter_chains:
final_preset: "{{ ipadapter_final_preset }}"
final_weight: "{{ ipadapter_final_weight }}"
final_embeds_scaling: "{{ ipadapter_embeds_scaling }}"
+ final_loader_type: "{{ ipadapter_final_loader_type }}"
+ final_lora_strength: "{{ ipadapter_final_lora_strength }}"
dynamic_conditioning_chains:
conditioning_chain:
ksampler_node: "ksampler"
- clip_source: "ckpt_loader:1"
\ No newline at end of file
+ clip_source: "ckpt_loader:1"
+
+ui_map:
+ model_name: "ckpt_loader:ckpt_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/conditioning/z-image.yaml b/core/pipelines/workflow_recipes/_partials/conditioning/z-image.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ad004372e475f5e6b33699b18c8f68ed1d8e28d7
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/conditioning/z-image.yaml
@@ -0,0 +1,65 @@
+nodes:
+ unet_loader:
+ class_type: UNETLoader
+ title: "Load Diffusion Model"
+ params:
+ weight_dtype: "default"
+ vae_loader:
+ class_type: VAELoader
+ title: "Load VAE"
+ clip_loader:
+ class_type: CLIPLoader
+ title: "Load CLIP"
+ params:
+ type: "lumina2"
+ device: "default"
+ model_sampler:
+ class_type: ModelSamplingAuraFlow
+ params:
+ shift: 3.0
+
+connections:
+ - from: "unet_loader:0"
+ to: "model_sampler:model"
+ - from: "model_sampler:0"
+ to: "ksampler:model"
+
+ - from: "clip_loader:0"
+ to: "pos_prompt:clip"
+ - from: "clip_loader:0"
+ to: "neg_prompt:clip"
+
+ - from: "pos_prompt:0"
+ to: "ksampler:positive"
+ - from: "neg_prompt:0"
+ to: "ksampler:negative"
+
+ - from: "vae_loader:0"
+ to: "vae_decode:vae"
+ - from: "vae_loader:0"
+ to: "vae_encode:vae"
+
+dynamic_lora_chains:
+ lora_chain:
+ template: "LoraLoader"
+ output_map:
+ "unet_loader:0": "model"
+ "clip_loader:0": "clip"
+ input_map:
+ "model": "model"
+ "clip": "clip"
+ end_input_map:
+ "model": ["model_sampler:model"]
+ "clip": ["pos_prompt:clip", "neg_prompt:clip"]
+
+dynamic_diffsynth_controlnet_chains:
+ diffsynth_controlnet_chain:
+ template: "QwenImageDiffsynthControlnet"
+ model_sampler_node: "model_sampler"
+ ksampler_node: "ksampler"
+ vae_source: "vae_loader:0"
+
+ui_map:
+ unet_name: "unet_loader:unet_name"
+ vae_name: "vae_loader:vae_name"
+ clip_name: "clip_loader:clip_name"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/hires_fix.yaml b/core/pipelines/workflow_recipes/_partials/input/hires_fix.yaml
index 6a0d7d4a911ac56c46257f40e05f100dcc8ffcc4..e9d3dc9ebe7edbad54a4b017a903adcbc4ec8dab 100644
--- a/core/pipelines/workflow_recipes/_partials/input/hires_fix.yaml
+++ b/core/pipelines/workflow_recipes/_partials/input/hires_fix.yaml
@@ -1,15 +1,16 @@
nodes:
input_image_loader:
class_type: LoadImage
-
+ title: "Load Input Image"
vae_encode:
class_type: VAEEncode
-
+ title: "VAE Encode (Hires Pre-step)"
latent_upscaler:
class_type: LatentUpscaleBy
-
+ title: "Upscale Latent By"
latent_source:
class_type: RepeatLatentBatch
+ title: "Repeat Latent Batch for Hires"
connections:
- from: "input_image_loader:0"
diff --git a/core/pipelines/workflow_recipes/_partials/input/img2img.yaml b/core/pipelines/workflow_recipes/_partials/input/img2img.yaml
index 801d852c3450309dc078bc191b81e7fb5de4b88d..b753f53f77ed6971b995e7a5e3695b2b0ae12755 100644
--- a/core/pipelines/workflow_recipes/_partials/input/img2img.yaml
+++ b/core/pipelines/workflow_recipes/_partials/input/img2img.yaml
@@ -1,12 +1,13 @@
nodes:
input_image_loader:
class_type: LoadImage
-
+ title: "Load Input Image"
vae_encode:
class_type: VAEEncode
-
+ title: "VAE Encode (Img2Img)"
latent_source:
class_type: RepeatLatentBatch
+ title: "Repeat Latent Batch"
connections:
- from: "input_image_loader:0"
diff --git a/core/pipelines/workflow_recipes/_partials/input/inpaint.yaml b/core/pipelines/workflow_recipes/_partials/input/inpaint.yaml
index 24ef9e3a56b908cfabc5a71a28c7962cbaae43cd..93c9d37d8eef6029e077b54d2ecf264e17b69385 100644
--- a/core/pipelines/workflow_recipes/_partials/input/inpaint.yaml
+++ b/core/pipelines/workflow_recipes/_partials/input/inpaint.yaml
@@ -2,24 +2,22 @@ nodes:
inpaint_loader:
class_type: LoadImage
title: "Load Inpaint Image+Mask"
-
vae_encode:
class_type: VAEEncodeForInpaint
- params:
- grow_mask_by: 6
-
+ title: "VAE Encode (for Inpainting)"
latent_source:
class_type: RepeatLatentBatch
-
+ title: "Repeat Latent Batch"
+
connections:
- from: "inpaint_loader:0"
to: "vae_encode:pixels"
- from: "inpaint_loader:1"
to: "vae_encode:mask"
-
- from: "vae_encode:0"
to: "latent_source:samples"
ui_map:
- inpaint_image: "inpaint_loader:image"
- batch_size: "latent_source:amount"
\ No newline at end of file
+ input_image: "inpaint_loader:image"
+ batch_size: "latent_source:amount"
+ grow_mask_by: "vae_encode:grow_mask_by"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/outpaint.yaml b/core/pipelines/workflow_recipes/_partials/input/outpaint.yaml
index cc51384adcadcc00a2b4af6309679cc4f76ea9a6..dc0631ed514d2eba5536ece529266a47b725a5d0 100644
--- a/core/pipelines/workflow_recipes/_partials/input/outpaint.yaml
+++ b/core/pipelines/workflow_recipes/_partials/input/outpaint.yaml
@@ -1,38 +1,41 @@
nodes:
input_image_loader:
class_type: LoadImage
-
+ title: "Load Image for Outpaint"
+ scale_image:
+ class_type: ImageScaleToTotalPixels
+ title: "Scale Image to Total Pixels"
+ params:
+ upscale_method: "nearest-exact"
pad_image:
class_type: ImagePadForOutpaint
- params:
- feathering: 10
-
+ title: "Pad Image for Outpainting"
vae_encode:
class_type: VAEEncodeForInpaint
- params:
- grow_mask_by: 6
-
+ title: "VAE Encode (for Inpainting)"
latent_source:
class_type: RepeatLatentBatch
+ title: "Repeat Latent Batch"
connections:
- from: "input_image_loader:0"
+ to: "scale_image:image"
+ - from: "scale_image:0"
to: "pad_image:image"
-
- from: "pad_image:0"
to: "vae_encode:pixels"
- from: "pad_image:1"
to: "vae_encode:mask"
-
- from: "vae_encode:0"
to: "latent_source:samples"
ui_map:
input_image: "input_image_loader:image"
-
+ megapixels: "scale_image:megapixels"
left: "pad_image:left"
top: "pad_image:top"
right: "pad_image:right"
bottom: "pad_image:bottom"
-
+ feathering: "pad_image:feathering"
+ grow_mask_by: "vae_encode:grow_mask_by"
batch_size: "latent_source:amount"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/txt2img.yaml b/core/pipelines/workflow_recipes/_partials/input/txt2img.yaml
index 4db96f6e9cdcc95d4d331144203009d019e004e1..df5957ccbc518741945d22232a154fb298e215f0 100644
--- a/core/pipelines/workflow_recipes/_partials/input/txt2img.yaml
+++ b/core/pipelines/workflow_recipes/_partials/input/txt2img.yaml
@@ -1,8 +1,2 @@
-nodes:
- latent_source:
- class_type: EmptyLatentImage
-
-ui_map:
- width: "latent_source:width"
- height: "latent_source:height"
- batch_size: "latent_source:batch_size"
\ No newline at end of file
+imports:
+ - "txt2img_{{ latent_type }}.yaml"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/txt2img_chroma_radiance_latent.yaml b/core/pipelines/workflow_recipes/_partials/input/txt2img_chroma_radiance_latent.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..afd3897cfe93f950edd9c7753813e5545b29acf5
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/input/txt2img_chroma_radiance_latent.yaml
@@ -0,0 +1,11 @@
+nodes:
+ latent_source:
+ class_type: "EmptyChromaRadianceLatentImage"
+ title: "EmptyChromaRadianceLatentImage"
+
+connections: []
+
+ui_map:
+ width: "latent_source:width"
+ height: "latent_source:height"
+ batch_size: "latent_source:batch_size"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/txt2img_flux2_latent.yaml b/core/pipelines/workflow_recipes/_partials/input/txt2img_flux2_latent.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..95f1e8d5949cdf754ab158db1c04142cf0941c86
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/input/txt2img_flux2_latent.yaml
@@ -0,0 +1,11 @@
+nodes:
+ latent_source:
+ class_type: "EmptyFlux2LatentImage"
+ title: "Empty Flux 2 Latent"
+
+connections: []
+
+ui_map:
+ width: "latent_source:width"
+ height: "latent_source:height"
+ batch_size: "latent_source:batch_size"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/txt2img_hunyuan_latent.yaml b/core/pipelines/workflow_recipes/_partials/input/txt2img_hunyuan_latent.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..8e51ba57d67a8defaab28af552ed537d85e69eb7
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/input/txt2img_hunyuan_latent.yaml
@@ -0,0 +1,11 @@
+nodes:
+ latent_source:
+ class_type: "EmptyHunyuanImageLatent"
+ title: "EmptyHunyuanImageLatent"
+
+connections: []
+
+ui_map:
+ width: "latent_source:width"
+ height: "latent_source:height"
+ batch_size: "latent_source:batch_size"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/txt2img_latent.yaml b/core/pipelines/workflow_recipes/_partials/input/txt2img_latent.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..660a34331c2dd17882ba3398ea4a4dedd822c6a7
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/input/txt2img_latent.yaml
@@ -0,0 +1,11 @@
+nodes:
+ latent_source:
+ class_type: "{{ latent_generator_template }}"
+ title: "Empty Latent Image"
+
+connections: []
+
+ui_map:
+ width: "latent_source:width"
+ height: "latent_source:height"
+ batch_size: "latent_source:batch_size"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/_partials/input/txt2img_sd3_latent.yaml b/core/pipelines/workflow_recipes/_partials/input/txt2img_sd3_latent.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..fc9d1f5e58b90ff14cb460de95b6ac653f641239
--- /dev/null
+++ b/core/pipelines/workflow_recipes/_partials/input/txt2img_sd3_latent.yaml
@@ -0,0 +1,11 @@
+nodes:
+ latent_source:
+ class_type: "EmptySD3LatentImage"
+ title: "EmptySD3LatentImage"
+
+connections: []
+
+ui_map:
+ width: "latent_source:width"
+ height: "latent_source:height"
+ batch_size: "latent_source:batch_size"
\ No newline at end of file
diff --git a/core/pipelines/workflow_recipes/sd_unified_recipe.yaml b/core/pipelines/workflow_recipes/sd_unified_recipe.yaml
index fc3c28c83338122addd665f3a96065815bab800d..49c2ea500e0e24d7faea454da913bd646e033a67 100644
--- a/core/pipelines/workflow_recipes/sd_unified_recipe.yaml
+++ b/core/pipelines/workflow_recipes/sd_unified_recipe.yaml
@@ -1,10 +1,8 @@
imports:
- - "_partials/_base_sampler.yaml"
+ - "_partials/_base_sampler_sd.yaml"
- "_partials/input/{{ task_type }}.yaml"
- - "_partials/conditioning/sdxl.yaml"
+ - "_partials/conditioning/{{ model_type }}.yaml"
connections:
- from: "latent_source:0"
- to: "ksampler:latent_image"
- - from: "ckpt_loader:2"
- to: "vae_encode:vae"
\ No newline at end of file
+ to: "ksampler:latent_image"
\ No newline at end of file
diff --git a/core/settings.py b/core/settings.py
index e0b9ee169b63f788059ea5ea173f4fdb0e9c4a55..55cbd0ca3f161ace06b32aec1a69773870fbe8b6 100644
--- a/core/settings.py
+++ b/core/settings.py
@@ -6,18 +6,40 @@ CHECKPOINT_DIR = "models/checkpoints"
LORA_DIR = "models/loras"
EMBEDDING_DIR = "models/embeddings"
CONTROLNET_DIR = "models/controlnet"
+MODEL_PATCHES_DIR = "models/model_patches"
DIFFUSION_MODELS_DIR = "models/diffusion_models"
VAE_DIR = "models/vae"
TEXT_ENCODERS_DIR = "models/text_encoders"
+STYLE_MODELS_DIR = "models/style_models"
+CLIP_VISION_DIR = "models/clip_vision"
+IPADAPTER_DIR = "models/ipadapter"
+IPADAPTER_FLUX_DIR = "models/ipadapter-flux"
INPUT_DIR = "input"
OUTPUT_DIR = "output"
+CATEGORY_TO_DIR_MAP = {
+ "diffusion_models": DIFFUSION_MODELS_DIR,
+ "text_encoders": TEXT_ENCODERS_DIR,
+ "vae": VAE_DIR,
+ "checkpoints": CHECKPOINT_DIR,
+ "loras": LORA_DIR,
+ "controlnet": CONTROLNET_DIR,
+ "model_patches": MODEL_PATCHES_DIR,
+ "embeddings": EMBEDDING_DIR,
+ "style_models": STYLE_MODELS_DIR,
+ "clip_vision": CLIP_VISION_DIR,
+ "ipadapter": IPADAPTER_DIR,
+ "ipadapter-flux": IPADAPTER_FLUX_DIR
+}
+
_PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
_MODEL_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_list.yaml')
_FILE_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'file_list.yaml')
_IPADAPTER_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'ipadapter.yaml')
_CONSTANTS_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'constants.yaml')
-
+_MODEL_ARCHITECTURES_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_architectures.yaml')
+_IMAGE_GEN_FEATURES_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'image_gen_features.yaml')
+_MODEL_DEFAULTS_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_defaults.yaml')
def load_constants_from_yaml(filepath=_CONSTANTS_PATH):
if not os.path.exists(filepath):
@@ -26,6 +48,27 @@ def load_constants_from_yaml(filepath=_CONSTANTS_PATH):
with open(filepath, 'r', encoding='utf-8') as f:
return yaml.safe_load(f)
+def load_architectures_config(filepath=_MODEL_ARCHITECTURES_PATH):
+ if not os.path.exists(filepath):
+ print(f"Warning: Architectures file not found at {filepath}.")
+ return {}
+ with open(filepath, 'r', encoding='utf-8') as f:
+ return yaml.safe_load(f)
+
+def load_features_config(filepath=_IMAGE_GEN_FEATURES_PATH):
+ if not os.path.exists(filepath):
+ print(f"Warning: Features file not found at {filepath}.")
+ return {}
+ with open(filepath, 'r', encoding='utf-8') as f:
+ return yaml.safe_load(f)
+
+def load_model_defaults(filepath=_MODEL_DEFAULTS_PATH):
+ if not os.path.exists(filepath):
+ print(f"Warning: Model defaults file not found at {filepath}.")
+ return {}
+ with open(filepath, 'r', encoding='utf-8') as f:
+ return yaml.safe_load(f)
+
def load_file_download_map(filepath=_FILE_LIST_PATH):
if not os.path.exists(filepath):
raise FileNotFoundError(f"The file list (for downloads) was not found at: {filepath}")
@@ -58,27 +101,40 @@ def load_models_from_yaml(model_list_filepath=_MODEL_LIST_PATH, download_map=Non
}
category_map_names = {
"Checkpoint": "MODEL_MAP_CHECKPOINT",
+ "Checkpoints": "MODEL_MAP_CHECKPOINT"
}
- for category, models in model_data.items():
+ for category, architectures in model_data.items():
if category in category_map_names:
map_name = category_map_names[category]
- if not isinstance(models, list): continue
- for model in models:
- display_name = model['display_name']
- filename = model['path']
+ if not isinstance(architectures, dict): continue
+
+ for arch, arch_data in architectures.items():
+ if not isinstance(arch_data, dict): continue
+
+ latent_type = arch_data.get('latent_type', 'latent')
+ models = arch_data.get('models', [])
+ if not isinstance(models, list): continue
- download_info = download_map.get(filename, {})
- repo_id = download_info.get('repo_id', '')
-
- model_tuple = (
- repo_id,
- filename,
- "SDXL",
- None
- )
- model_maps[map_name][display_name] = model_tuple
- model_maps["ALL_MODEL_MAP"][display_name] = model_tuple
+ for model in models:
+ display_name = model['display_name']
+ path_or_components = model.get('path') or model.get('components')
+ mod_category = model.get('category', None)
+
+ repo_id = ''
+ if isinstance(path_or_components, str):
+ download_info = download_map.get(path_or_components, {})
+ repo_id = download_info.get('repo_id', '')
+
+ model_tuple = (
+ repo_id,
+ path_or_components,
+ arch,
+ latent_type,
+ mod_category
+ )
+ model_maps[map_name][display_name] = model_tuple
+ model_maps["ALL_MODEL_MAP"][display_name] = model_tuple
return model_maps
@@ -88,13 +144,43 @@ try:
MODEL_MAP_CHECKPOINT = loaded_maps["MODEL_MAP_CHECKPOINT"]
ALL_MODEL_MAP = loaded_maps["ALL_MODEL_MAP"]
+ category_to_model_type = {
+ "diffusion_models": "UNET",
+ "text_encoders": "TEXT_ENCODER",
+ "vae": "VAE",
+ "checkpoints": "SDXL",
+ "loras": "LORA",
+ "controlnet": "CONTROLNET",
+ "model_patches": "MODEL_PATCH",
+ "style_models": "STYLE",
+ "clip_vision": "CLIP_VISION",
+ "ipadapter": "IPADAPTER",
+ "ipadapter-flux": "IPADAPTER_FLUX"
+ }
+ for filename, file_info in ALL_FILE_DOWNLOAD_MAP.items():
+ if filename not in ALL_MODEL_MAP:
+ category = file_info.get('category')
+ model_type = category_to_model_type.get(category, 'UNKNOWN')
+ repo_id = file_info.get('repo_id', '')
+ ALL_MODEL_MAP[filename] = (repo_id, filename, model_type, None, None)
+
MODEL_TYPE_MAP = {k: v[2] for k, v in ALL_MODEL_MAP.items()}
+ ARCH_CATEGORIES_MAP = {}
+ for display_name, info in MODEL_MAP_CHECKPOINT.items():
+ arch = info[2]
+ cat = info[4] if len(info) > 4 else None
+ if arch not in ARCH_CATEGORIES_MAP:
+ ARCH_CATEGORIES_MAP[arch] = []
+ if cat and cat not in ARCH_CATEGORIES_MAP[arch]:
+ ARCH_CATEGORIES_MAP[arch].append(cat)
+
except Exception as e:
print(f"FATAL: Could not load model configuration from YAML. Error: {e}")
ALL_FILE_DOWNLOAD_MAP = {}
MODEL_MAP_CHECKPOINT, ALL_MODEL_MAP = {}, {}
MODEL_TYPE_MAP = {}
+ ARCH_CATEGORIES_MAP = {}
try:
@@ -104,13 +190,16 @@ try:
MAX_CONDITIONINGS = _constants.get('MAX_CONDITIONINGS', 10)
MAX_CONTROLNETS = _constants.get('MAX_CONTROLNETS', 5)
MAX_IPADAPTERS = _constants.get('MAX_IPADAPTERS', 5)
- LORA_SOURCE_CHOICES = _constants.get('LORA_SOURCE_CHOICES', ["Civitai", "Custom URL", "File"])
+ LORA_SOURCE_CHOICES = _constants.get('LORA_SOURCE_CHOICES', ["Civitai", "File"])
RESOLUTION_MAP = _constants.get('RESOLUTION_MAP', {})
+ ARCHITECTURES_CONFIG = load_architectures_config()
+ FEATURES_CONFIG = load_features_config()
+ MODEL_DEFAULTS_CONFIG = load_model_defaults()
except Exception as e:
print(f"FATAL: Could not load constants from YAML. Error: {e}")
MAX_LORAS, MAX_EMBEDDINGS, MAX_CONDITIONINGS, MAX_CONTROLNETS, MAX_IPADAPTERS = 5, 5, 10, 5, 5
- LORA_SOURCE_CHOICES = ["Civitai", "Custom URL", "File"]
+ LORA_SOURCE_CHOICES = ["Civitai", "File"]
RESOLUTION_MAP = {}
-
-
-DEFAULT_NEGATIVE_PROMPT = "monochrome, (low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn,"
\ No newline at end of file
+ ARCHITECTURES_CONFIG = {}
+ FEATURES_CONFIG = {}
+ MODEL_DEFAULTS_CONFIG = {}
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
index dd463cd02b9f69107d470a508751eab6950ecdf3..42592f722427291189a26b314e3b9f89c4719b5f 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -58,4 +58,5 @@ svglib
trimesh[easy]
yacs
yapf
-onnxruntime-gpu
\ No newline at end of file
+onnxruntime-gpu
+diffusers
\ No newline at end of file
diff --git a/ui/events.py b/ui/events.py
index d2267bfd16cfbb5b5b7381e66ffca4cef945f512..931923fb976e7beb4947ecd1efdae24962b0e5dd 100644
--- a/ui/events.py
+++ b/ui/events.py
@@ -8,8 +8,7 @@ from utils.app_utils import *
from core.generation_logic import *
from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
-from core.pipelines.controlnet_preprocessor import CPU_ONLY_PREPROCESSORS
-from utils.app_utils import PREPROCESSOR_MODEL_MAP, PREPROCESSOR_PARAMETER_MAP, save_uploaded_file_with_hash
+from utils.app_utils import save_uploaded_file_with_hash
from ui.shared.ui_components import RESOLUTION_MAP, MAX_CONTROLNETS, MAX_IPADAPTERS, MAX_EMBEDDINGS, MAX_CONDITIONINGS, MAX_LORAS
@@ -22,10 +21,74 @@ def load_controlnet_config():
with open(_CN_MODEL_LIST_PATH, 'r', encoding='utf-8') as f:
config = yaml.safe_load(f)
print("--- ✅ controlnet_models.yaml loaded successfully ---")
- return config.get("ControlNet", {}).get("SDXL", [])
+ return config.get("ControlNet", {})
except Exception as e:
print(f"Error loading controlnet_models.yaml: {e}")
- return []
+ return {}
+
+
+def get_cn_defaults(arch_val):
+ cn_full_config = load_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_diffsynth_controlnet_config():
+ _PROJECT_ROOT = 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_ipadapter_config():
@@ -42,118 +105,96 @@ def load_ipadapter_config():
return {}
-def attach_event_handlers(ui_components, demo):
- def update_cn_input_visibility(choice):
- return {
- ui_components["cn_image_input"]: gr.update(visible=choice == "Image"),
- ui_components["cn_video_input"]: gr.update(visible=choice == "Video")
- }
- ui_components["cn_input_type"].change(
- fn=update_cn_input_visibility,
- inputs=[ui_components["cn_input_type"]],
- outputs=[ui_components["cn_image_input"], ui_components["cn_video_input"]]
- )
+def apply_data_to_ui(data, prefix, ui_components):
+ final_sampler = data.get('sampler') if data.get('sampler') in SAMPLER_CHOICES else SAMPLER_CHOICES[0]
+ default_scheduler = 'normal' if 'normal' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0]
+ final_scheduler = data.get('scheduler') if data.get('scheduler') in SCHEDULER_CHOICES else default_scheduler
+
+ updates = {}
+ base_model_name = data.get('base_model')
- def update_preprocessor_models_dropdown(preprocessor_name):
- models = PREPROCESSOR_MODEL_MAP.get(preprocessor_name)
- if models:
- model_filenames = [m[1] for m in models]
- return gr.update(choices=model_filenames, value=model_filenames[0], visible=True)
- else:
- return gr.update(choices=[], value=None, visible=False)
-
- def update_preprocessor_settings_ui(preprocessor_name):
- from ui.layout import MAX_DYNAMIC_CONTROLS
- params = PREPROCESSOR_PARAMETER_MAP.get(preprocessor_name, [])
-
- slider_updates, dropdown_updates, checkbox_updates = [], [], []
-
- s_idx, d_idx, c_idx = 0, 0, 0
-
- for param in params:
- if s_idx + d_idx + c_idx >= MAX_DYNAMIC_CONTROLS: break
-
- name = param["name"]
- ptype = param["type"]
- config = param["config"]
- label = name.replace('_', ' ').title()
-
- if ptype == "INT" or ptype == "FLOAT":
- if s_idx < MAX_DYNAMIC_CONTROLS:
- slider_updates.append(gr.update(
- label=label,
- minimum=config.get('min', 0),
- maximum=config.get('max', 255),
- step=config.get('step', 0.1 if ptype == "FLOAT" else 1),
- value=config.get('default', 0),
- visible=True
- ))
- s_idx += 1
- elif isinstance(ptype, list):
- if d_idx < MAX_DYNAMIC_CONTROLS:
- dropdown_updates.append(gr.update(
- label=label,
- choices=ptype,
- value=config.get('default', ptype[0] if ptype else None),
- visible=True
- ))
- d_idx += 1
- elif ptype == "BOOLEAN":
- if c_idx < MAX_DYNAMIC_CONTROLS:
- checkbox_updates.append(gr.update(
- label=label,
- value=config.get('default', False),
- visible=True
- ))
- c_idx += 1
-
- for _ in range(s_idx, MAX_DYNAMIC_CONTROLS): slider_updates.append(gr.update(visible=False))
- for _ in range(d_idx, MAX_DYNAMIC_CONTROLS): dropdown_updates.append(gr.update(visible=False))
- for _ in range(c_idx, MAX_DYNAMIC_CONTROLS): checkbox_updates.append(gr.update(visible=False))
-
- return slider_updates + dropdown_updates + checkbox_updates
-
- def update_run_button_for_cpu(preprocessor_name):
- if preprocessor_name in CPU_ONLY_PREPROCESSORS:
- return gr.update(value="Run Preprocessor CPU Only", variant="primary"), gr.update(visible=False)
+ model_map = MODEL_MAP_CHECKPOINT
+
+ if f'base_model_{prefix}' in ui_components:
+ model_dropdown_component = ui_components[f'base_model_{prefix}']
+ if base_model_name and base_model_name in model_map:
+ updates[model_dropdown_component] = base_model_name
+ if f'model_arch_{prefix}' in ui_components:
+ m_type = MODEL_TYPE_MAP.get(base_model_name, "SDXL")
+ updates[ui_components[f'model_arch_{prefix}']] = m_type
+ if f'model_cat_{prefix}' in ui_components:
+ m_info = model_map.get(base_model_name)
+ m_cat = m_info[4] if m_info and len(m_info) > 4 else None
+ updates[ui_components[f'model_cat_{prefix}']] = m_cat if m_cat else "ALL"
else:
- return gr.update(value="Run Preprocessor", variant="primary"), gr.update(visible=True)
-
- ui_components["preprocessor_cn"].change(
- fn=update_preprocessor_models_dropdown,
- inputs=[ui_components["preprocessor_cn"]],
- outputs=[ui_components["preprocessor_model_cn"]]
- ).then(
- fn=update_preprocessor_settings_ui,
- inputs=[ui_components["preprocessor_cn"]],
- outputs=ui_components["cn_sliders"] + ui_components["cn_dropdowns"] + ui_components["cn_checkboxes"]
- ).then(
- fn=update_run_button_for_cpu,
- inputs=[ui_components["preprocessor_cn"]],
- outputs=[ui_components["run_cn"], ui_components["zero_gpu_cn"]]
- )
-
- all_dynamic_inputs = (
- ui_components["cn_sliders"] +
- ui_components["cn_dropdowns"] +
- ui_components["cn_checkboxes"]
- )
-
- ui_components["run_cn"].click(
- fn=run_cn_preprocessor_entry,
- inputs=[
- ui_components["cn_input_type"],
- ui_components["cn_image_input"],
- ui_components["cn_video_input"],
- ui_components["preprocessor_cn"],
- ui_components["preprocessor_model_cn"],
- ui_components["zero_gpu_cn"],
- ] + all_dynamic_inputs,
- outputs=[ui_components["output_gallery_cn"]]
- )
+ updates[model_dropdown_component] = gr.update()
+
+ common_params = {
+ f'prompt_{prefix}': data.get('prompt', ''),
+ f'neg_prompt_{prefix}': data.get('negative_prompt', ''),
+ f'seed_{prefix}': data.get('seed', -1),
+ f'cfg_{prefix}': data.get('cfg_scale', 7.5),
+ f'steps_{prefix}': data.get('steps', 28),
+ f'sampler_{prefix}': final_sampler,
+ f'scheduler_{prefix}': final_scheduler,
+ }
+
+ for comp_name, value in common_params.items():
+ if comp_name in ui_components:
+ updates[ui_components[comp_name]] = value
+
+ if prefix == 'txt2img':
+ if f'width_{prefix}' in ui_components:
+ updates[ui_components[f'width_{prefix}']] = data.get('width', 1024)
+ if f'height_{prefix}' in ui_components:
+ updates[ui_components[f'height_{prefix}']] = data.get('height', 1024)
+
+ tab_indices = {"txt2img": 0, "img2img": 1, "inpaint": 2, "outpaint": 3, "hires_fix": 4}
+ tab_index = tab_indices.get(prefix, 0)
+
+ updates[ui_components['tabs']] = gr.Tabs(selected=tab_index)
+
+ return updates
+
+
+def send_info_to_tab(image, prefix, ui_components):
+ if not image or not image.info.get('parameters', ''):
+ all_comps = [comp for comp_or_list in ui_components.values() for comp in (comp_or_list if isinstance(comp_or_list, list) else [comp_or_list])]
+ return {comp: gr.update() for comp in all_comps}
+
+ data = parse_parameters(image.info['parameters'])
+
+ image_input_map = {
+ "img2img": 'input_image_img2img',
+ "inpaint": 'input_image_dict_inpaint',
+ "outpaint": 'input_image_outpaint',
+ "hires_fix": 'input_image_hires_fix'
+ }
+
+ updates = apply_data_to_ui(data, prefix, ui_components)
+
+ if prefix in image_input_map and image_input_map[prefix] in ui_components:
+ component_key = image_input_map[prefix]
+ updates[ui_components[component_key]] = gr.update(value=image)
+
+ return updates
+
+
+def send_info_by_hash(image, ui_components):
+ if not image or not image.info.get('parameters', ''):
+ all_comps = [comp for comp_or_list in ui_components.values() for comp in (comp_or_list if isinstance(comp_or_list, list) else [comp_or_list])]
+ return {comp: gr.update() for comp in all_comps}
+
+ data = parse_parameters(image.info['parameters'])
+
+ return apply_data_to_ui(data, "txt2img", ui_components)
+
+
+def attach_event_handlers(ui_components, demo):
def create_lora_event_handlers(prefix):
- lora_rows = ui_components[f'lora_rows_{prefix}']
+ lora_rows = ui_components.get(f'lora_rows_{prefix}')
+ if not lora_rows: return
lora_ids = ui_components[f'lora_ids_{prefix}']
lora_scales = ui_components[f'lora_scales_{prefix}']
lora_uploads = ui_components[f'lora_uploads_{prefix}']
@@ -193,7 +234,8 @@ def attach_event_handlers(ui_components, demo):
del_button.click(del_lora_row, [count_state], del_outputs, show_progress=False)
def create_controlnet_event_handlers(prefix):
- cn_rows = ui_components[f'controlnet_rows_{prefix}']
+ cn_rows = ui_components.get(f'controlnet_rows_{prefix}')
+ if not cn_rows: return
cn_types = ui_components[f'controlnet_types_{prefix}']
cn_series = ui_components[f'controlnet_series_{prefix}']
cn_filepaths = ui_components[f'controlnet_filepaths_{prefix}']
@@ -205,6 +247,114 @@ def attach_event_handlers(ui_components, demo):
del_button = ui_components[f'delete_controlnet_button_{prefix}']
accordion = ui_components[f'controlnet_accordion_{prefix}']
+ arch_comp = ui_components.get(f'model_arch_{prefix}')
+ actual_arch_comp = arch_comp if arch_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, arch_val):
+ cn_full_config = load_controlnet_config()
+
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ controlnet_key = architectures_dict.get(arch_val, {}).get("controlnet_key", arch_val)
+
+ 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, arch_val):
+ cn_full_config = load_controlnet_config()
+
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ controlnet_key = architectures_dict.get(arch_val, {}).get("controlnet_key", arch_val)
+
+ 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_diffsynth_controlnet_event_handlers(prefix):
+ 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}']
+
+ arch_comp = ui_components.get(f'model_arch_{prefix}')
+ actual_arch_comp = arch_comp if arch_comp else gr.State("Z-Image")
+
def add_cn_row(c):
c += 1
updates = {
@@ -232,8 +382,13 @@ def attach_event_handlers(ui_components, demo):
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_controlnet_config()
+ def on_cn_type_change(selected_type, arch_val):
+ cn_full_config = load_diffsynth_controlnet_config()
+
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ controlnet_key = architectures_dict.get(arch_val, {}).get("controlnet_key", arch_val)
+
+ cn_config = cn_full_config.get(controlnet_key, [])
series_choices = []
if selected_type:
series_choices = sorted(list(set(
@@ -249,8 +404,13 @@ def attach_event_handlers(ui_components, demo):
break
return gr.update(choices=series_choices, value=default_series), filepath
- def on_cn_series_change(selected_series, selected_type):
- cn_config = load_controlnet_config()
+ def on_cn_series_change(selected_series, selected_type, arch_val):
+ cn_full_config = load_diffsynth_controlnet_config()
+
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ controlnet_key = architectures_dict.get(arch_val, {}).get("controlnet_key", arch_val)
+
+ cn_config = cn_full_config.get(controlnet_key, [])
filepath = "None"
if selected_series and selected_type:
for model in cn_config:
@@ -262,13 +422,13 @@ def attach_event_handlers(ui_components, demo):
for i in range(MAX_CONTROLNETS):
cn_types[i].change(
fn=on_cn_type_change,
- inputs=[cn_types[i]],
+ 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]],
+ inputs=[cn_series[i], cn_types[i], actual_arch_comp],
outputs=[cn_filepaths[i]],
show_progress=False
)
@@ -283,8 +443,69 @@ def attach_event_handlers(ui_components, demo):
show_progress=False
)
+ def create_flux1_ipadapter_event_handlers(prefix):
+ fipa_rows = ui_components.get(f'flux1_ipadapter_rows_{prefix}')
+ if not fipa_rows: return
+ count_state = ui_components[f'flux1_ipadapter_count_state_{prefix}']
+ add_button = ui_components[f'add_flux1_ipadapter_button_{prefix}']
+ del_button = ui_components[f'delete_flux1_ipadapter_button_{prefix}']
+
+ def add_fipa_row(c):
+ c += 1
+ return {
+ count_state: c,
+ fipa_rows[c - 1]: gr.update(visible=True),
+ add_button: gr.update(visible=c < MAX_IPADAPTERS),
+ del_button: gr.update(visible=True),
+ }
+
+ def del_fipa_row(c):
+ c -= 1
+ return {
+ count_state: c,
+ fipa_rows[c]: gr.update(visible=False),
+ add_button: gr.update(visible=True),
+ del_button: gr.update(visible=c > 0),
+ }
+
+ add_outputs = [count_state, add_button, del_button] + fipa_rows
+ del_outputs = [count_state, add_button, del_button] + fipa_rows
+ add_button.click(fn=add_fipa_row, inputs=[count_state], outputs=add_outputs, show_progress=False)
+ del_button.click(fn=del_fipa_row, inputs=[count_state], outputs=del_outputs, show_progress=False)
+
+ def create_style_event_handlers(prefix):
+ style_rows = ui_components.get(f'style_rows_{prefix}')
+ if not style_rows: return
+ count_state = ui_components[f'style_count_state_{prefix}']
+ add_button = ui_components[f'add_style_button_{prefix}']
+ del_button = ui_components[f'delete_style_button_{prefix}']
+
+ def add_style_row(c):
+ c += 1
+ return {
+ count_state: c,
+ style_rows[c - 1]: gr.update(visible=True),
+ add_button: gr.update(visible=c < 5),
+ del_button: gr.update(visible=True),
+ }
+
+ def del_style_row(c):
+ c -= 1
+ return {
+ count_state: c,
+ style_rows[c]: gr.update(visible=False),
+ add_button: gr.update(visible=True),
+ del_button: gr.update(visible=c > 0),
+ }
+
+ add_outputs = [count_state, add_button, del_button] + style_rows
+ del_outputs = [count_state, add_button, del_button] + style_rows
+ add_button.click(fn=add_style_row, inputs=[count_state], outputs=add_outputs, show_progress=False)
+ del_button.click(fn=del_style_row, inputs=[count_state], outputs=del_outputs, show_progress=False)
+
def create_ipadapter_event_handlers(prefix):
- ipa_rows = ui_components[f'ipadapter_rows_{prefix}']
+ ipa_rows = ui_components.get(f'ipadapter_rows_{prefix}')
+ if not ipa_rows: return
ipa_lora_strengths = ui_components[f'ipadapter_lora_strengths_{prefix}']
ipa_final_preset = ui_components[f'ipadapter_final_preset_{prefix}']
ipa_final_lora_strength = ui_components[f'ipadapter_final_lora_strength_{prefix}']
@@ -319,11 +540,10 @@ def attach_event_handlers(ui_components, demo):
def on_preset_change(preset_value):
config = load_ipadapter_config()
faceid_presets = []
- if isinstance(config, list):
- faceid_presets = [
- p.get('preset_name', '') for p in config
- if 'FACE' in p.get('preset_name', '') or 'FACEID' in p.get('preset_name', '')
- ]
+ if config:
+ faceid_presets.extend(config.get("IPAdapter_FaceID_presets", {}).get("SDXL", []))
+ faceid_presets.extend(config.get("IPAdapter_FaceID_presets", {}).get("SD1.5", []))
+
is_visible = preset_value in faceid_presets
updates = [gr.update(visible=is_visible)] * (MAX_IPADAPTERS + 1)
return updates
@@ -333,9 +553,42 @@ def attach_event_handlers(ui_components, demo):
accordion.expand(fn=lambda *imgs: [gr.update() for _ in imgs], inputs=ui_components[f'ipadapter_images_{prefix}'], outputs=ui_components[f'ipadapter_images_{prefix}'], show_progress=False)
+ def create_reference_latent_event_handlers(prefix):
+ ref_rows = ui_components.get(f'reference_latent_rows_{prefix}')
+ if not ref_rows: return
+ count_state = ui_components[f'reference_latent_count_state_{prefix}']
+ add_button = ui_components[f'add_reference_latent_button_{prefix}']
+ del_button = ui_components[f'delete_reference_latent_button_{prefix}']
+ images = ui_components[f'reference_latent_images_{prefix}']
+
+ def add_ref_row(c):
+ c += 1
+ return {
+ count_state: c,
+ ref_rows[c - 1]: gr.update(visible=True),
+ add_button: gr.update(visible=c < 10),
+ del_button: gr.update(visible=True),
+ }
+
+ def del_ref_row(c):
+ c -= 1
+ return {
+ count_state: c,
+ ref_rows[c]: gr.update(visible=False),
+ images[c]: None,
+ add_button: gr.update(visible=True),
+ del_button: gr.update(visible=c > 0),
+ }
+
+ add_outputs = [count_state, add_button, del_button] + ref_rows
+ del_outputs = [count_state, add_button, del_button] + ref_rows + images
+ add_button.click(fn=add_ref_row, inputs=[count_state], outputs=add_outputs, show_progress=False)
+ del_button.click(fn=del_ref_row, inputs=[count_state], outputs=del_outputs, show_progress=False)
+
def create_embedding_event_handlers(prefix):
- rows = ui_components[f'embedding_rows_{prefix}']
+ rows = ui_components.get(f'embedding_rows_{prefix}')
+ if not rows: return
ids = ui_components[f'embeddings_ids_{prefix}']
files = ui_components[f'embeddings_files_{prefix}']
count_state = ui_components[f'embedding_count_state_{prefix}']
@@ -368,7 +621,8 @@ def attach_event_handlers(ui_components, demo):
del_button.click(fn=del_row, inputs=[count_state], outputs=del_outputs, show_progress=False)
def create_conditioning_event_handlers(prefix):
- rows = ui_components[f'conditioning_rows_{prefix}']
+ rows = ui_components.get(f'conditioning_rows_{prefix}')
+ if not rows: return
prompts = ui_components[f'conditioning_prompts_{prefix}']
count_state = ui_components[f'conditioning_count_state_{prefix}']
add_button = ui_components[f'add_conditioning_button_{prefix}']
@@ -423,38 +677,48 @@ def attach_event_handlers(ui_components, demo):
def create_run_event(prefix: str, task_type: str):
run_inputs_map = {
'model_display_name': ui_components[f'base_model_{prefix}'],
- 'positive_prompt': ui_components[f'prompt_{prefix}'],
- 'negative_prompt': ui_components[f'neg_prompt_{prefix}'],
- 'seed': ui_components[f'seed_{prefix}'],
- 'batch_size': ui_components[f'batch_size_{prefix}'],
- 'guidance_scale': ui_components[f'cfg_{prefix}'],
- 'num_inference_steps': ui_components[f'steps_{prefix}'],
- 'sampler': ui_components[f'sampler_{prefix}'],
- 'scheduler': ui_components[f'scheduler_{prefix}'],
- 'zero_gpu_duration': ui_components[f'zero_gpu_{prefix}'],
- 'civitai_api_key': ui_components.get(f'civitai_api_key_{prefix}'),
- 'clip_skip': ui_components[f'clip_skip_{prefix}'],
+ 'positive_prompt': ui_components.get(f'prompt_{prefix}') or ui_components.get(f'{prefix}_positive_prompt'),
+ 'negative_prompt': ui_components.get(f'neg_prompt_{prefix}') or ui_components.get(f'{prefix}_negative_prompt'),
+ 'seed': ui_components.get(f'seed_{prefix}') or ui_components.get(f'{prefix}_seed'),
+ 'batch_size': ui_components.get(f'batch_size_{prefix}') or ui_components.get(f'{prefix}_batch_size'),
+ 'guidance_scale': ui_components.get(f'cfg_{prefix}') or ui_components.get(f'{prefix}_cfg'),
+ 'num_inference_steps': ui_components.get(f'steps_{prefix}') or ui_components.get(f'{prefix}_steps'),
+ 'sampler': ui_components.get(f'sampler_{prefix}') or ui_components.get(f'{prefix}_sampler_name'),
+ 'scheduler': ui_components.get(f'scheduler_{prefix}') or ui_components.get(f'{prefix}_scheduler'),
+ 'zero_gpu_duration': ui_components.get(f'zero_gpu_{prefix}'),
+
+ 'clip_skip': ui_components.get(f'clip_skip_{prefix}'),
+ 'guidance': ui_components.get(f'guidance_{prefix}'),
'task_type': gr.State(task_type)
}
if task_type not in ['img2img', 'inpaint']:
- run_inputs_map.update({'width': ui_components[f'width_{prefix}'], 'height': ui_components[f'height_{prefix}']})
+ run_inputs_map.update({
+ 'width': ui_components.get(f'width_{prefix}') or ui_components.get(f'{prefix}_width'),
+ 'height': ui_components.get(f'height_{prefix}') or ui_components.get(f'{prefix}_height')
+ })
task_specific_map = {
'img2img': {'img2img_image': f'input_image_{prefix}', 'img2img_denoise': f'denoise_{prefix}'},
- 'inpaint': {'inpaint_image_dict': f'input_image_dict_{prefix}'},
- 'outpaint': {'outpaint_image': f'input_image_{prefix}', 'outpaint_left': f'outpaint_left_{prefix}', 'outpaint_top': f'outpaint_top_{prefix}', 'outpaint_right': f'outpaint_right_{prefix}', 'outpaint_bottom': f'outpaint_bottom_{prefix}'},
+ 'inpaint': {'inpaint_image_dict': f'input_image_dict_{prefix}', 'grow_mask_by': f'grow_mask_by_{prefix}'},
+ 'outpaint': {'outpaint_image': f'input_image_{prefix}', 'left': f'left_{prefix}', 'top': f'top_{prefix}', 'right': f'right_{prefix}', 'bottom': f'bottom_{prefix}', 'feathering': f'feathering_{prefix}'},
'hires_fix': {'hires_image': f'input_image_{prefix}', 'hires_upscaler': f'hires_upscaler_{prefix}', 'hires_scale_by': f'hires_scale_by_{prefix}', 'hires_denoise': f'denoise_{prefix}'}
}
if task_type in task_specific_map:
for key, comp_name in task_specific_map[task_type].items():
- run_inputs_map[key] = ui_components[comp_name]
+ if comp_name in ui_components:
+ run_inputs_map[key] = ui_components[comp_name]
lora_data_components = ui_components.get(f'all_lora_components_flat_{prefix}', [])
controlnet_data_components = ui_components.get(f'all_controlnet_components_flat_{prefix}', [])
+ diffsynth_controlnet_data_components = ui_components.get(f'all_diffsynth_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}', [])
+ style_data_components = ui_components.get(f'all_style_components_flat_{prefix}', [])
embedding_data_components = ui_components.get(f'all_embedding_components_flat_{prefix}', [])
conditioning_data_components = ui_components.get(f'all_conditioning_components_flat_{prefix}', [])
+ reference_latent_data_components = ui_components.get(f'all_reference_latent_components_flat_{prefix}', [])
run_inputs_map['vae_source'] = ui_components.get(f'vae_source_{prefix}')
run_inputs_map['vae_id'] = ui_components.get(f'vae_id_{prefix}')
@@ -462,133 +726,441 @@ def attach_event_handlers(ui_components, demo):
input_keys = list(run_inputs_map.keys())
input_list_flat = [v for v in run_inputs_map.values() if v is not None]
- input_list_flat += lora_data_components + controlnet_data_components + ipadapter_data_components + embedding_data_components + conditioning_data_components
+ all_chains = [
+ lora_data_components, controlnet_data_components, diffsynth_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
+ ]
+ for chain in all_chains:
+ if chain:
+ input_list_flat.extend(chain)
def create_ui_inputs_dict(*args):
valid_keys = [k for k in input_keys if run_inputs_map[k] is not None]
ui_dict = dict(zip(valid_keys, args[:len(valid_keys)]))
arg_idx = len(valid_keys)
-
- ui_dict['lora_data'] = list(args[arg_idx : arg_idx + len(lora_data_components)])
- arg_idx += len(lora_data_components)
- ui_dict['controlnet_data'] = list(args[arg_idx : arg_idx + len(controlnet_data_components)])
- arg_idx += len(controlnet_data_components)
- ui_dict['ipadapter_data'] = list(args[arg_idx : arg_idx + len(ipadapter_data_components)])
- arg_idx += len(ipadapter_data_components)
- ui_dict['embedding_data'] = list(args[arg_idx : arg_idx + len(embedding_data_components)])
- arg_idx += len(embedding_data_components)
- ui_dict['conditioning_data'] = list(args[arg_idx : arg_idx + len(conditioning_data_components)])
+
+ def assign_chain_data(chain_key, components_list):
+ nonlocal arg_idx
+ if components_list:
+ ui_dict[chain_key] = list(args[arg_idx : arg_idx + len(components_list)])
+ arg_idx += len(components_list)
+
+ assign_chain_data('lora_data', lora_data_components)
+ assign_chain_data('controlnet_data', controlnet_data_components)
+ assign_chain_data('diffsynth_controlnet_data', diffsynth_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)
+ assign_chain_data('style_data', style_data_components)
+ assign_chain_data('embedding_data', embedding_data_components)
+ assign_chain_data('conditioning_data', conditioning_data_components)
+ assign_chain_data('reference_latent_data', reference_latent_data_components)
return ui_dict
- ui_components[f'run_{prefix}'].click(
- fn=lambda *args, progress=gr.Progress(track_tqdm=True): generate_image_wrapper(create_ui_inputs_dict(*args), progress),
- inputs=input_list_flat,
- outputs=[ui_components[f'result_{prefix}']]
- )
+ run_btn = ui_components.get(f'run_{prefix}') or ui_components.get(f'{prefix}_run_button')
+ res_gal = ui_components.get(f'result_{prefix}') or ui_components.get(f'{prefix}_output_gallery')
+ if run_btn and res_gal:
+ run_btn.click(
+ fn=lambda *args, progress=gr.Progress(track_tqdm=True): generate_image_wrapper(create_ui_inputs_dict(*args), progress),
+ inputs=input_list_flat,
+ outputs=[res_gal]
+ )
+
+ def make_update_fn(m_comp, cat_comp, cs_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, ipa_preset, lora_acc, cn_acc, diffsynth_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp):
+ def update_fn(*args):
+ arch = args[0]
+ category = args[1]
+ current_ar = args[2] if len(args) > 2 else None
+ from core.settings import MODEL_TYPE_MAP, MODEL_MAP_CHECKPOINT, FEATURES_CONFIG, ARCHITECTURES_CONFIG, MODEL_DEFAULTS_CONFIG, ARCH_CATEGORIES_MAP
+ from utils.app_utils import get_model_generation_defaults
+
+ if arch == "ALL":
+ valid_cats = list(set(cat for cats in ARCH_CATEGORIES_MAP.values() for cat in cats))
+ else:
+ valid_cats = ARCH_CATEGORIES_MAP.get(arch, [])
+
+ cat_choices = ["ALL"] + sorted(valid_cats)
+ new_category = category if category in cat_choices else "ALL"
+
+ choices = []
+ for name, info in MODEL_MAP_CHECKPOINT.items():
+ m_arch = info[2]
+ m_cat = info[4] if len(info) > 4 else None
+ arch_match = (arch == "ALL" or m_arch == arch)
+ cat_match = (new_category == "ALL" or m_cat == new_category)
+ if arch_match and cat_match:
+ choices.append(name)
+
+ val = choices[0] if choices else None
+
+ updates = {
+ m_comp: gr.update(choices=choices, value=val),
+ cat_comp: gr.update(choices=cat_choices, value=new_category)
+ }
+
+ m_type = MODEL_TYPE_MAP.get(val, "SDXL") if val else "SDXL"
+
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ arch_model_type = architectures_dict.get(m_type, {}).get("model_type", m_type.lower().replace(" ", "").replace(".", ""))
+
+ arch_features = FEATURES_CONFIG.get(arch_model_type, FEATURES_CONFIG.get('default', {}))
+ enabled_chains = arch_features.get('enabled_chains', [])
+
+ 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 diffsynth_cn_acc: updates[diffsynth_cn_acc] = gr.update(visible=('controlnet_model_patch' 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))
+ if style_acc: updates[style_acc] = gr.update(visible=('style' in enabled_chains))
+ if embed_acc: updates[embed_acc] = gr.update(visible=('embedding' in enabled_chains))
+ if cond_acc: updates[cond_acc] = gr.update(visible=('conditioning' in enabled_chains))
+ if ref_latent_acc: updates[ref_latent_acc] = gr.update(visible=('reference_latent' in enabled_chains))
+
+ if cs_comp:
+ updates[cs_comp] = gr.update(visible=(arch_model_type == "sd15"))
+ if guidance_comp:
+ updates[guidance_comp] = gr.update(visible=(arch_model_type == "flux1"))
+
+ if ar_comp:
+ res_key = arch_model_type
+ if res_key not in RESOLUTION_MAP:
+ res_key = 'sdxl'
+ res_map = RESOLUTION_MAP.get(res_key, {})
+ target_ar = current_ar if current_ar in res_map else (list(res_map.keys())[0] if res_map else "1:1 (Square)")
+ updates[ar_comp] = gr.update(choices=list(res_map.keys()), value=target_ar)
+ if width_comp and height_comp and target_ar in res_map:
+ updates[width_comp] = gr.update(value=res_map[target_ar][0])
+ updates[height_comp] = gr.update(value=res_map[target_ar][1])
+
+ controlnet_key = architectures_dict.get(m_type, {}).get("controlnet_key", m_type)
+
+ all_types, default_type, series_choices, default_series, filepath = get_cn_defaults(controlnet_key)
+ for t_comp in cn_types:
+ updates[t_comp] = gr.update(choices=all_types, value=default_type)
+ for s_comp in cn_series:
+ updates[s_comp] = gr.update(choices=series_choices, value=default_series)
+ for f_comp in cn_filepaths:
+ updates[f_comp] = 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
+
+ if ipa_preset and (arch_model_type in ["sdxl", "sd15", "sd35"]):
+ config = load_ipadapter_config()
+ ipa_arch_key = "SDXL" if arch_model_type in ["sdxl", "sd35"] else "SD1.5"
+ std_presets = config.get("IPAdapter_presets", {}).get(ipa_arch_key, [])
+ face_presets = config.get("IPAdapter_FaceID_presets", {}).get(ipa_arch_key, [])
+ all_ipa_presets = std_presets + face_presets
+ default_ipa = all_ipa_presets[0] if all_ipa_presets else None
+ updates[ipa_preset] = gr.update(choices=all_ipa_presets, value=default_ipa)
+
+ defaults = get_model_generation_defaults(val, arch_model_type, MODEL_DEFAULTS_CONFIG)
+ if steps_comp: updates[steps_comp] = gr.update(value=defaults.get('steps'))
+ if cfg_comp: updates[cfg_comp] = gr.update(value=defaults.get('cfg'))
+ if sampler_comp: updates[sampler_comp] = gr.update(value=defaults.get('sampler_name'))
+ if scheduler_comp: updates[scheduler_comp] = gr.update(value=defaults.get('scheduler'))
+ if prompt_comp: updates[prompt_comp] = gr.update(value=defaults.get('positive_prompt'))
+ if neg_prompt_comp: updates[neg_prompt_comp] = gr.update(value=defaults.get('negative_prompt'))
+
+ return updates
+ return update_fn
+
+ def make_model_change_fn(cat_comp_ref, cs_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, arch_comp_ref, ipa_preset, lora_acc, cn_acc, diffsynth_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp):
+ def change_fn(*args):
+ model_name = args[0]
+ idx = 1
+ current_arch = args[idx] if arch_comp_ref and idx < len(args) else None
+ if arch_comp_ref: idx += 1
+ current_cat = args[idx] if cat_comp_ref and idx < len(args) else None
+ if cat_comp_ref: idx += 1
+ current_ar = args[idx] if idx < len(args) else None
+ from core.settings import MODEL_TYPE_MAP, FEATURES_CONFIG, ARCHITECTURES_CONFIG, MODEL_DEFAULTS_CONFIG, ARCH_CATEGORIES_MAP, MODEL_MAP_CHECKPOINT
+ from utils.app_utils import get_model_generation_defaults
+ m_type = MODEL_TYPE_MAP.get(model_name, "SDXL")
+
+ m_info = MODEL_MAP_CHECKPOINT.get(model_name)
+ m_cat = m_info[4] if m_info and len(m_info) > 4 else None
+ if not m_cat: m_cat = "ALL"
+
+ updates = {}
+ target_arch = m_type
+ if arch_comp_ref:
+ if current_arch == "ALL":
+ updates[arch_comp_ref] = gr.update()
+ target_arch = "ALL"
+ else:
+ updates[arch_comp_ref] = m_type
+
+ if cat_comp_ref:
+ if target_arch == "ALL":
+ valid_cats = list(set(cat for cats in ARCH_CATEGORIES_MAP.values() for cat in cats))
+ else:
+ valid_cats = ARCH_CATEGORIES_MAP.get(target_arch, [])
+ cat_choices = ["ALL"] + sorted(valid_cats)
+
+ if current_cat == "ALL":
+ updates[cat_comp_ref] = gr.update(choices=cat_choices)
+ else:
+ updates[cat_comp_ref] = gr.update(choices=cat_choices, value=m_cat)
+
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ arch_model_type = architectures_dict.get(m_type, {}).get("model_type", m_type.lower().replace(" ", "").replace(".", ""))
+
+ arch_features = FEATURES_CONFIG.get(arch_model_type, FEATURES_CONFIG.get('default', {}))
+ enabled_chains = arch_features.get('enabled_chains', [])
+
+ 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 diffsynth_cn_acc: updates[diffsynth_cn_acc] = gr.update(visible=('controlnet_model_patch' 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))
+ if style_acc: updates[style_acc] = gr.update(visible=('style' in enabled_chains))
+ if embed_acc: updates[embed_acc] = gr.update(visible=('embedding' in enabled_chains))
+ if cond_acc: updates[cond_acc] = gr.update(visible=('conditioning' in enabled_chains))
+ if ref_latent_acc: updates[ref_latent_acc] = gr.update(visible=('reference_latent' in enabled_chains))
+
+ if cs_comp:
+ updates[cs_comp] = gr.update(visible=(arch_model_type == "sd15"))
+ if guidance_comp:
+ updates[guidance_comp] = gr.update(visible=(arch_model_type == "flux1"))
+
+ if ar_comp:
+ res_key = arch_model_type
+ if res_key not in RESOLUTION_MAP:
+ res_key = 'sdxl'
+ res_map = RESOLUTION_MAP.get(res_key, {})
+ target_ar = current_ar if current_ar in res_map else (list(res_map.keys())[0] if res_map else "1:1 (Square)")
+ updates[ar_comp] = gr.update(choices=list(res_map.keys()), value=target_ar)
+ if width_comp and height_comp and target_ar in res_map:
+ updates[width_comp] = gr.update(value=res_map[target_ar][0])
+ updates[height_comp] = gr.update(value=res_map[target_ar][1])
+
+ controlnet_key = architectures_dict.get(m_type, {}).get("controlnet_key", m_type)
+
+ all_types, default_type, series_choices, default_series, filepath = get_cn_defaults(controlnet_key)
+ for t_comp in cn_types:
+ updates[t_comp] = gr.update(choices=all_types, value=default_type)
+ for s_comp in cn_series:
+ updates[s_comp] = gr.update(choices=series_choices, value=default_series)
+ for f_comp in cn_filepaths:
+ updates[f_comp] = 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
+
+ if ipa_preset and (arch_model_type in ["sdxl", "sd15", "sd35"]):
+ config = load_ipadapter_config()
+ ipa_arch_key = "SDXL" if arch_model_type in ["sdxl", "sd35"] else "SD1.5"
+ std_presets = config.get("IPAdapter_presets", {}).get(ipa_arch_key, [])
+ face_presets = config.get("IPAdapter_FaceID_presets", {}).get(ipa_arch_key, [])
+ all_ipa_presets = std_presets + face_presets
+ default_ipa = all_ipa_presets[0] if all_ipa_presets else None
+ updates[ipa_preset] = gr.update(choices=all_ipa_presets, value=default_ipa)
+
+ defaults = get_model_generation_defaults(model_name, arch_model_type, MODEL_DEFAULTS_CONFIG)
+ if steps_comp: updates[steps_comp] = gr.update(value=defaults.get('steps'))
+ if cfg_comp: updates[cfg_comp] = gr.update(value=defaults.get('cfg'))
+ if sampler_comp: updates[sampler_comp] = gr.update(value=defaults.get('sampler_name'))
+ if scheduler_comp: updates[scheduler_comp] = gr.update(value=defaults.get('scheduler'))
+ if prompt_comp: updates[prompt_comp] = gr.update(value=defaults.get('positive_prompt'))
+ if neg_prompt_comp: updates[neg_prompt_comp] = gr.update(value=defaults.get('negative_prompt'))
+
+ return updates
+ return change_fn
for prefix, task_type in [
("txt2img", "txt2img"), ("img2img", "img2img"), ("inpaint", "inpaint"),
("outpaint", "outpaint"), ("hires_fix", "hires_fix"),
]:
- if f'add_lora_button_{prefix}' in ui_components:
- create_lora_event_handlers(prefix)
- lora_uploads = ui_components[f'lora_uploads_{prefix}']
- lora_ids = ui_components[f'lora_ids_{prefix}']
- lora_sources = ui_components[f'lora_sources_{prefix}']
- for i in range(MAX_LORAS):
- lora_uploads[i].upload(
- fn=on_lora_upload,
- inputs=[lora_uploads[i]],
- outputs=[lora_ids[i], lora_sources[i]],
- show_progress=False
- )
- if f'add_controlnet_button_{prefix}' in ui_components: create_controlnet_event_handlers(prefix)
- if f'add_ipadapter_button_{prefix}' in ui_components: create_ipadapter_event_handlers(prefix)
- if f'add_embedding_button_{prefix}' in ui_components:
- create_embedding_event_handlers(prefix)
- if f'embeddings_uploads_{prefix}' in ui_components:
- emb_uploads = ui_components[f'embeddings_uploads_{prefix}']
- emb_ids = ui_components[f'embeddings_ids_{prefix}']
- emb_sources = ui_components[f'embeddings_sources_{prefix}']
- emb_files = ui_components[f'embeddings_files_{prefix}']
- for i in range(MAX_EMBEDDINGS):
- emb_uploads[i].upload(
- fn=on_embedding_upload,
- inputs=[emb_uploads[i]],
- outputs=[emb_ids[i], emb_sources[i], emb_files[i]],
- show_progress=False
- )
- if f'add_conditioning_button_{prefix}' in ui_components: create_conditioning_event_handlers(prefix)
- if f'vae_source_{prefix}' in ui_components:
- upload_button = ui_components.get(f'vae_upload_button_{prefix}')
- if upload_button:
- upload_button.upload(
- fn=on_vae_upload,
- inputs=[upload_button],
- outputs=[
- ui_components[f'vae_id_{prefix}'],
- ui_components[f'vae_source_{prefix}'],
- ui_components[f'vae_file_{prefix}']
- ]
+
+ arch_comp = ui_components.get(f'model_arch_{prefix}')
+ cat_comp = ui_components.get(f'model_cat_{prefix}')
+ model_comp = ui_components.get(f'base_model_{prefix}')
+ clip_skip_comp = ui_components.get(f'clip_skip_{prefix}') or ui_components.get(f'{prefix}_clip_skip')
+ guidance_comp = ui_components.get(f'guidance_{prefix}') or ui_components.get(f'{prefix}_guidance')
+ aspect_ratio_comp = ui_components.get(f'aspect_ratio_{prefix}') or ui_components.get(f'{prefix}_aspect_ratio_dropdown')
+ width_comp = ui_components.get(f'width_{prefix}') or ui_components.get(f'{prefix}_width')
+ height_comp = ui_components.get(f'height_{prefix}') or ui_components.get(f'{prefix}_height')
+
+ cn_types_list = ui_components.get(f'controlnet_types_{prefix}', [])
+ cn_series_list = ui_components.get(f'controlnet_series_{prefix}', [])
+ cn_filepaths_list = ui_components.get(f'controlnet_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}', [])
+
+ lora_accordion = ui_components.get(f'lora_accordion_{prefix}')
+ cn_accordion = ui_components.get(f'controlnet_accordion_{prefix}')
+ diffsynth_cn_accordion = ui_components.get(f'diffsynth_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}')
+ style_accordion = ui_components.get(f'style_accordion_{prefix}')
+ embedding_accordion = ui_components.get(f'embedding_accordion_{prefix}')
+ conditioning_accordion = ui_components.get(f'conditioning_accordion_{prefix}')
+ ref_latent_accordion = ui_components.get(f'reference_latent_accordion_{prefix}')
+
+ ipa_preset_list = ui_components.get(f'ipadapter_final_preset_{prefix}')
+
+ prompt_comp = ui_components.get(f'prompt_{prefix}') or ui_components.get(f'{prefix}_positive_prompt')
+ neg_prompt_comp = ui_components.get(f'neg_prompt_{prefix}') or ui_components.get(f'{prefix}_negative_prompt')
+ steps_comp = ui_components.get(f'steps_{prefix}') or ui_components.get(f'{prefix}_steps')
+ cfg_comp = ui_components.get(f'cfg_{prefix}') or ui_components.get(f'{prefix}_cfg')
+ sampler_comp = ui_components.get(f'sampler_{prefix}') or ui_components.get(f'{prefix}_sampler_name')
+ scheduler_comp = ui_components.get(f'scheduler_{prefix}') or ui_components.get(f'{prefix}_scheduler')
+
+ extra_comps = [prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, width_comp, height_comp]
+ valid_extra_comps = [c for c in extra_comps if c is not None]
+
+ if arch_comp and cat_comp and model_comp:
+ outputs = [model_comp, cat_comp]
+ if clip_skip_comp: outputs.append(clip_skip_comp)
+ if guidance_comp: outputs.append(guidance_comp)
+ if aspect_ratio_comp: outputs.append(aspect_ratio_comp)
+ outputs.extend(cn_types_list + cn_series_list + cn_filepaths_list)
+ outputs.extend(diffsynth_cn_types_list + diffsynth_cn_series_list + diffsynth_cn_filepaths_list)
+ if lora_accordion: outputs.append(lora_accordion)
+ if cn_accordion: outputs.append(cn_accordion)
+ if diffsynth_cn_accordion: outputs.append(diffsynth_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)
+ if style_accordion: outputs.append(style_accordion)
+ if embedding_accordion: outputs.append(embedding_accordion)
+ if conditioning_accordion: outputs.append(conditioning_accordion)
+ if ref_latent_accordion: outputs.append(ref_latent_accordion)
+ if ipa_preset_list: outputs.append(ipa_preset_list)
+
+ outputs.extend(valid_extra_comps)
+
+ update_fn = make_update_fn(
+ model_comp, cat_comp, clip_skip_comp, aspect_ratio_comp, width_comp, height_comp,
+ cn_types_list, cn_series_list, cn_filepaths_list,
+ diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list,
+ ipa_preset_list, lora_accordion, cn_accordion, diffsynth_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
+ ref_latent_accordion, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp
+ )
+ inputs = [arch_comp, cat_comp]
+ if aspect_ratio_comp:
+ inputs.append(aspect_ratio_comp)
+ arch_comp.change(fn=update_fn, inputs=inputs, outputs=outputs)
+ cat_comp.change(fn=update_fn, inputs=inputs, outputs=outputs)
+
+ if model_comp:
+ outputs2 = []
+ if arch_comp: outputs2.append(arch_comp)
+ if cat_comp: outputs2.append(cat_comp)
+ if clip_skip_comp: outputs2.append(clip_skip_comp)
+ if guidance_comp: outputs2.append(guidance_comp)
+ if aspect_ratio_comp: outputs2.append(aspect_ratio_comp)
+ outputs2.extend(cn_types_list + cn_series_list + cn_filepaths_list)
+ outputs2.extend(diffsynth_cn_types_list + diffsynth_cn_series_list + diffsynth_cn_filepaths_list)
+ if lora_accordion: outputs2.append(lora_accordion)
+ if cn_accordion: outputs2.append(cn_accordion)
+ if diffsynth_cn_accordion: outputs2.append(diffsynth_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)
+ if style_accordion: outputs2.append(style_accordion)
+ if embedding_accordion: outputs2.append(embedding_accordion)
+ if conditioning_accordion: outputs2.append(conditioning_accordion)
+ if ref_latent_accordion: outputs2.append(ref_latent_accordion)
+ if ipa_preset_list: outputs2.append(ipa_preset_list)
+
+ outputs2.extend(valid_extra_comps)
+
+ if outputs2:
+ inputs2 = [model_comp]
+ if arch_comp: inputs2.append(arch_comp)
+ if cat_comp: inputs2.append(cat_comp)
+ if aspect_ratio_comp: inputs2.append(aspect_ratio_comp)
+ change_fn = make_model_change_fn(
+ cat_comp, clip_skip_comp, aspect_ratio_comp, width_comp, height_comp,
+ cn_types_list, cn_series_list, cn_filepaths_list,
+ diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list,
+ arch_comp, ipa_preset_list, lora_accordion, cn_accordion, diffsynth_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
+ ref_latent_accordion, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp
)
+ model_comp.change(fn=change_fn, inputs=inputs2, outputs=outputs2)
+ create_lora_event_handlers(prefix)
+ create_controlnet_event_handlers(prefix)
+ create_diffsynth_controlnet_event_handlers(prefix)
+ create_ipadapter_event_handlers(prefix)
+ create_embedding_event_handlers(prefix)
+ create_conditioning_event_handlers(prefix)
+ create_flux1_ipadapter_event_handlers(prefix)
+ create_style_event_handlers(prefix)
+ create_reference_latent_event_handlers(prefix)
create_run_event(prefix, task_type)
- def on_aspect_ratio_change(ratio_key, model_display_name):
- model_type = MODEL_TYPE_MAP.get(model_display_name, 'sdxl').lower()
- res_map = RESOLUTION_MAP.get(model_type, RESOLUTION_MAP.get("sdxl", {}))
- w, h = res_map.get(ratio_key, (1024, 1024))
- return w, h
- for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
- if f'aspect_ratio_{prefix}' in ui_components:
- aspect_ratio_dropdown = ui_components[f'aspect_ratio_{prefix}']
- width_component = ui_components[f'width_{prefix}']
- height_component = ui_components[f'height_{prefix}']
- model_dropdown = ui_components[f'base_model_{prefix}']
- aspect_ratio_dropdown.change(fn=on_aspect_ratio_change, inputs=[aspect_ratio_dropdown, model_dropdown], outputs=[width_component, height_component], show_progress=False)
-
if 'view_mode_inpaint' in ui_components:
def toggle_inpaint_fullscreen_view(view_mode):
is_fullscreen = (view_mode == "Fullscreen View")
other_elements_visible = not is_fullscreen
editor_height = 800 if is_fullscreen else 272
- return {
- ui_components['model_and_run_row_inpaint']: gr.update(visible=other_elements_visible),
+
+ updates = {
ui_components['prompts_column_inpaint']: gr.update(visible=other_elements_visible),
ui_components['params_and_gallery_row_inpaint']: gr.update(visible=other_elements_visible),
ui_components['accordion_wrapper_inpaint']: gr.update(visible=other_elements_visible),
ui_components['input_image_dict_inpaint']: gr.update(height=editor_height),
}
+
+ model_and_run_rows = ui_components.get('model_and_run_row_inpaint', [])
+ for row in model_and_run_rows:
+ updates[row] = gr.update(visible=other_elements_visible)
+
+ return updates
- output_components = [
- ui_components['model_and_run_row_inpaint'], ui_components['prompts_column_inpaint'],
- ui_components['params_and_gallery_row_inpaint'], ui_components['accordion_wrapper_inpaint'],
+ output_components = []
+ model_and_run_rows = ui_components.get('model_and_run_row_inpaint', [])
+ if isinstance(model_and_run_rows, list):
+ output_components.extend(model_and_run_rows)
+ else:
+ output_components.append(model_and_run_rows)
+
+ output_components.extend([
+ ui_components['prompts_column_inpaint'],
+ ui_components['params_and_gallery_row_inpaint'],
+ ui_components['accordion_wrapper_inpaint'],
ui_components['input_image_dict_inpaint']
- ]
- ui_components['view_mode_inpaint'].change(fn=toggle_inpaint_fullscreen_view, inputs=[ui_components['view_mode_inpaint']], outputs=output_components, show_progress=False)
+ ])
+
+ ui_components['view_mode_inpaint'].change(
+ fn=toggle_inpaint_fullscreen_view,
+ inputs=[ui_components['view_mode_inpaint']],
+ outputs=output_components,
+ show_progress=False
+ )
def initialize_all_cn_dropdowns():
- cn_config = load_controlnet_config()
- if not cn_config: return {}
-
- 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
+ from core.settings import MODEL_TYPE_MAP, MODEL_MAP_CHECKPOINT, ARCHITECTURES_CONFIG
+ default_model_name = list(MODEL_MAP_CHECKPOINT.keys())[0] if MODEL_MAP_CHECKPOINT else None
+ default_m_type = MODEL_TYPE_MAP.get(default_model_name, "SDXL") if default_model_name else "SDXL"
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ controlnet_key = architectures_dict.get(default_m_type, {}).get("controlnet_key", default_m_type)
- 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
+ all_types, default_type, series_choices, default_series, filepath = get_cn_defaults(controlnet_key)
+ diffsynth_all_types, diffsynth_default_type, diffsynth_series_choices, diffsynth_default_series, diffsynth_filepath = get_diffsynth_cn_defaults(controlnet_key)
- 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
-
updates = {}
for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
if f'controlnet_types_{prefix}' in ui_components:
@@ -598,22 +1170,30 @@ def attach_event_handlers(ui_components, demo):
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'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=diffsynth_default_series)
+ for filepath_state in ui_components[f'diffsynth_controlnet_filepaths_{prefix}']:
+ updates[filepath_state] = diffsynth_filepath
+
return updates
def initialize_all_ipa_dropdowns():
config = load_ipadapter_config()
- if not config or not isinstance(config, list): return {}
-
- unified_presets = []
- faceid_presets = []
- for preset_info in config:
- name = preset_info.get("preset_name")
- if not name:
- continue
- if "FACEID" in name or "FACE" in name:
- faceid_presets.append(name)
- else:
- unified_presets.append(name)
+ if not config: return {}
+
+ from core.settings import MODEL_TYPE_MAP, MODEL_MAP_CHECKPOINT, ARCHITECTURES_CONFIG
+ default_model_name = list(MODEL_MAP_CHECKPOINT.keys())[0] if MODEL_MAP_CHECKPOINT else None
+ default_m_type = MODEL_TYPE_MAP.get(default_model_name, "SDXL") if default_model_name else "SDXL"
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ arch_model_type = architectures_dict.get(default_m_type, {}).get("model_type", default_m_type.lower().replace(" ", "").replace(".", ""))
+ ipa_arch_key = "SDXL" if arch_model_type in ["sdxl", "sd35"] else "SD1.5"
+
+ unified_presets = config.get("IPAdapter_presets", {}).get(ipa_arch_key, [])
+ faceid_presets = config.get("IPAdapter_FaceID_presets", {}).get(ipa_arch_key, [])
all_presets = unified_presets + faceid_presets
default_preset = all_presets[0] if all_presets else None
@@ -636,19 +1216,6 @@ def attach_event_handlers(ui_components, demo):
all_updates = {**cn_updates, **ipa_updates}
- default_preprocessor = "Canny Edge"
- model_update = update_preprocessor_models_dropdown(default_preprocessor)
- all_updates[ui_components["preprocessor_model_cn"]] = model_update
-
- settings_outputs = update_preprocessor_settings_ui(default_preprocessor)
- dynamic_outputs = ui_components["cn_sliders"] + ui_components["cn_dropdowns"] + ui_components["cn_checkboxes"]
- for i, comp in enumerate(dynamic_outputs):
- all_updates[comp] = settings_outputs[i]
-
- run_button_update, zero_gpu_update = update_run_button_for_cpu(default_preprocessor)
- all_updates[ui_components["run_cn"]] = run_button_update
- all_updates[ui_components["zero_gpu_cn"]] = zero_gpu_update
-
return all_updates
all_load_outputs = []
@@ -657,22 +1224,35 @@ 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'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'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}'])
all_load_outputs.append(ui_components[f'ipadapter_final_lora_strength_{prefix}'])
- all_load_outputs.extend([
- ui_components["preprocessor_model_cn"],
- *ui_components["cn_sliders"],
- *ui_components["cn_dropdowns"],
- *ui_components["cn_checkboxes"],
- ui_components["run_cn"],
- ui_components["zero_gpu_cn"]
- ])
-
if all_load_outputs:
demo.load(
fn=run_on_load,
outputs=all_load_outputs
- )
\ No newline at end of file
+ )
+
+ def on_aspect_ratio_change(ratio_key, model_display_name):
+ from core.settings import MODEL_TYPE_MAP, ARCHITECTURES_CONFIG
+ m_type = MODEL_TYPE_MAP.get(model_display_name, 'SDXL')
+ architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+ arch_model_type = architectures_dict.get(m_type, {}).get("model_type", m_type.lower().replace(" ", "").replace(".", ""))
+
+ res_map = RESOLUTION_MAP.get(arch_model_type, RESOLUTION_MAP.get("sdxl", {}))
+ w, h = res_map.get(ratio_key, (1024, 1024))
+ return w, h
+
+ for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
+ aspect_ratio_dropdown = ui_components.get(f'aspect_ratio_{prefix}') or ui_components.get(f'{prefix}_aspect_ratio_dropdown')
+ width_component = ui_components.get(f'width_{prefix}') or ui_components.get(f'{prefix}_width')
+ height_component = ui_components.get(f'height_{prefix}') or ui_components.get(f'{prefix}_height')
+ model_dropdown = ui_components.get(f'base_model_{prefix}')
+ if aspect_ratio_dropdown and width_component and height_component and model_dropdown:
+ aspect_ratio_dropdown.change(fn=on_aspect_ratio_change, inputs=[aspect_ratio_dropdown, model_dropdown], outputs=[width_component, height_component], show_progress=False)
\ No newline at end of file
diff --git a/ui/layout.py b/ui/layout.py
index 17c3df460f17ede414ade4ee65c3e4d5256abbd0..68b4563573827917a21192623f66f6f3e8574774 100644
--- a/ui/layout.py
+++ b/ui/layout.py
@@ -6,83 +6,40 @@ from .shared import txt2img_ui, img2img_ui, inpaint_ui, outpaint_ui, hires_fix_u
MAX_DYNAMIC_CONTROLS = 10
-def get_preprocessor_choices():
- from nodes import NODE_DISPLAY_NAME_MAPPINGS
-
- preprocessor_names = [
- display_name for class_name, display_name in NODE_DISPLAY_NAME_MAPPINGS.items()
- if "Preprocessor" in class_name or "Segmentor" in class_name or
- "Estimator" in class_name or "Detector" in class_name
- ]
- return sorted(list(set(preprocessor_names)))
-
-
def build_ui(event_handler_function):
ui_components = {}
with gr.Blocks() as demo:
- gr.Markdown("# ImageGen - SDXL")
+ gr.Markdown("# ImageGen")
gr.Markdown(
- "This demo is a streamlined version of the [Comfy web UI](https://github.com/RioShiina47/comfy-webui)'s ImgGen functionality. "
+ "This demo is a streamlined version of the [Comfy web UI](https://github.com/RioShiina47/comfy-webui)'s ImageGen functionality. "
"Other versions are also available: "
"[FLUX.2](https://huggingface.co/spaces/RioShiina/ImageGen-FLUX.2), "
"[Z-Image](https://huggingface.co/spaces/RioShiina/ImageGen-Z-Image), "
"[Qwen-Image](https://huggingface.co/spaces/RioShiina/ImageGen-Qwen-Image), "
- "[Anima](https://huggingface.co/spaces/RioShiina/ImageGen-Anima), "
+ "[Anime](https://huggingface.co/spaces/RioShiina/ImageGen-Anime), "
"[Illustrious](https://huggingface.co/spaces/RioShiina/ImageGen-Illustrious), "
"[NoobAI](https://huggingface.co/spaces/RioShiina/ImageGen-NoobAI), "
"[Pony](https://huggingface.co/spaces/RioShiina/ImageGen-Pony)"
)
with gr.Tabs(elem_id="tabs_container") as tabs:
- with gr.TabItem("SDXL", id=0):
- with gr.Tabs(elem_id="image_gen_tabs") as image_gen_tabs:
- with gr.TabItem("Txt2Img", id=0):
- ui_components.update(txt2img_ui.create_ui())
-
- with gr.TabItem("Img2Img", id=1):
- ui_components.update(img2img_ui.create_ui())
+ with gr.TabItem("Txt2Img", id=0):
+ ui_components.update(txt2img_ui.create_ui())
+
+ with gr.TabItem("Img2Img", id=1):
+ ui_components.update(img2img_ui.create_ui())
- with gr.TabItem("Inpaint", id=2):
- ui_components.update(inpaint_ui.create_ui())
+ with gr.TabItem("Inpaint", id=2):
+ ui_components.update(inpaint_ui.create_ui())
- with gr.TabItem("Outpaint", id=3):
- ui_components.update(outpaint_ui.create_ui())
+ with gr.TabItem("Outpaint", id=3):
+ ui_components.update(outpaint_ui.create_ui())
- with gr.TabItem("Hires. Fix", id=4):
- ui_components.update(hires_fix_ui.create_ui())
-
- ui_components['image_gen_tabs'] = image_gen_tabs
+ with gr.TabItem("Hires. Fix", id=4):
+ ui_components.update(hires_fix_ui.create_ui())
- with gr.TabItem("Controlnet Preprocessors", id=1):
- gr.Markdown("## ControlNet Auxiliary Preprocessors")
- gr.Markdown("Powered by [Fannovel16/comfyui_controlnet_aux](https://github.com/Fannovel16/comfyui_controlnet_aux).")
- gr.Markdown("Upload an image or video to process it with a ControlNet preprocessor.")
- with gr.Row():
- with gr.Column(scale=1):
- cn_input_type = gr.Radio(["Image", "Video"], label="Input Type", value="Image")
- cn_image_input = gr.Image(type="pil", label="Input Image", visible=True, height=384)
- cn_video_input = gr.Video(label="Input Video", visible=False)
- preprocessor_cn = gr.Dropdown(label="Preprocessor", choices=get_preprocessor_choices(), value="Canny Edge")
- preprocessor_model_cn = gr.Dropdown(label="Preprocessor Model", choices=[], value=None, visible=False)
- with gr.Column() as preprocessor_settings_ui:
- cn_sliders, cn_dropdowns, cn_checkboxes = [], [], []
- for i in range(MAX_DYNAMIC_CONTROLS):
- cn_sliders.append(gr.Slider(visible=False, label=f"dyn_slider_{i}"))
- cn_dropdowns.append(gr.Dropdown(visible=False, label=f"dyn_dropdown_{i}"))
- cn_checkboxes.append(gr.Checkbox(visible=False, label=f"dyn_checkbox_{i}"))
- run_cn = gr.Button("Run Preprocessor", variant="primary")
- with gr.Column(scale=1):
- output_gallery_cn = gr.Gallery(label="Output", show_label=False, object_fit="contain", height=512)
- zero_gpu_cn = gr.Number(label="ZeroGPU Duration (s)", value=None, placeholder="Default: 60s, Max: 120s", info="Optional")
- ui_components.update({
- "cn_input_type": cn_input_type, "cn_image_input": cn_image_input, "cn_video_input": cn_video_input,
- "preprocessor_cn": preprocessor_cn, "preprocessor_model_cn": preprocessor_model_cn, "run_cn": run_cn,
- "zero_gpu_cn": zero_gpu_cn, "output_gallery_cn": output_gallery_cn,
- "preprocessor_settings_ui": preprocessor_settings_ui, "cn_sliders": cn_sliders,
- "cn_dropdowns": cn_dropdowns, "cn_checkboxes": cn_checkboxes
- })
-
ui_components["tabs"] = tabs
+ ui_components["image_gen_tabs"] = tabs
gr.Markdown("")
diff --git a/ui/shared/hires_fix_ui.py b/ui/shared/hires_fix_ui.py
index 93f2727431c38ececd602280ff2e502cefd6951f..5727d002946e99b00a7dc9bb366274f0f4345858 100644
--- a/ui/shared/hires_fix_ui.py
+++ b/ui/shared/hires_fix_ui.py
@@ -4,7 +4,10 @@ from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
from .ui_components import (
create_lora_settings_ui,
create_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
- create_conditioning_ui, create_vae_override_ui, create_api_key_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,
+ create_reference_latent_ui
)
def create_ui():
@@ -12,7 +15,10 @@ def create_ui():
components = {}
with gr.Column():
+ components.update(create_model_architecture_filter_ui(prefix))
+
with gr.Row():
+ components.update(create_category_filter_ui(prefix))
components[f'base_model_{prefix}'] = gr.Dropdown(
label="Base Model",
choices=list(MODEL_MAP_CHECKPOINT.keys()),
@@ -26,8 +32,8 @@ def create_ui():
with gr.Column(scale=1):
components[f'input_image_{prefix}'] = gr.Image(type="pil", label="Input Image", height=255)
with gr.Column(scale=2):
- components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3, placeholder="Describe the final image...")
- components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3, value="monochrome, (low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn,")
+ components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3)
+ components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3)
with gr.Row():
with gr.Column(scale=1):
@@ -54,21 +60,26 @@ def create_ui():
components[f'seed_{prefix}'] = gr.Number(label="Seed (-1 for random)", value=-1, precision=0)
components[f'batch_size_{prefix}'] = gr.Slider(label="Batch Size", minimum=1, maximum=16, step=1, value=1)
with gr.Row():
+ components[f'clip_skip_{prefix}'] = gr.Slider(label="Clip Skip", minimum=1, maximum=2, step=1, value=1, visible=False, interactive=True)
+ components[f'guidance_{prefix}'] = gr.Slider(label="Guidance (FLUX)", minimum=1.0, maximum=10.0, step=0.1, value=3.5, visible=False, interactive=True)
components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=None, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU.")
- components[f'clip_skip_{prefix}'] = gr.State(value=1)
components[f'width_{prefix}'] = gr.State(value=512)
components[f'height_{prefix}'] = gr.State(value=512)
with gr.Column(scale=1):
components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=1, object_fit="contain", height=610)
- components.update(create_api_key_ui(prefix))
+
components.update(create_lora_settings_ui(prefix))
components.update(create_controlnet_ui(prefix))
components.update(create_ipadapter_ui(prefix))
+ components.update(create_flux1_ipadapter_ui(prefix))
+ components.update(create_sd3_ipadapter_ui(prefix))
+ components.update(create_style_ui(prefix))
components.update(create_embedding_ui(prefix))
components.update(create_conditioning_ui(prefix))
+ components.update(create_reference_latent_ui(prefix))
components.update(create_vae_override_ui(prefix))
return components
\ No newline at end of file
diff --git a/ui/shared/img2img_ui.py b/ui/shared/img2img_ui.py
index ef76e20bc0672ef46acbd41bf925469ebc5e8d83..801049021fe12d21a8f03d5ddcbc35acabbab97b 100644
--- a/ui/shared/img2img_ui.py
+++ b/ui/shared/img2img_ui.py
@@ -3,8 +3,11 @@ from core.settings import MODEL_MAP_CHECKPOINT
from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
from .ui_components import (
create_lora_settings_ui,
- create_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
- create_conditioning_ui, create_vae_override_ui, create_api_key_ui
+ create_controlnet_ui, create_diffsynth_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,
+ create_reference_latent_ui
)
def create_ui():
@@ -12,7 +15,10 @@ def create_ui():
components = {}
with gr.Column():
+ components.update(create_model_architecture_filter_ui(prefix))
+
with gr.Row():
+ components.update(create_category_filter_ui(prefix))
components[f'base_model_{prefix}'] = gr.Dropdown(label="Base Model", choices=list(MODEL_MAP_CHECKPOINT.keys()), value=list(MODEL_MAP_CHECKPOINT.keys())[0], scale=3)
with gr.Column(scale=1):
components[f'run_{prefix}'] = gr.Button("Run", variant="primary")
@@ -22,8 +28,8 @@ def create_ui():
components[f'input_image_{prefix}'] = gr.Image(type="pil", label="Input Image", height=255)
with gr.Column(scale=2):
- components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3, placeholder="Enter your prompt")
- components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3, value="monochrome, (low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn,")
+ components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3)
+ components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3)
with gr.Row():
with gr.Column(scale=1):
@@ -39,19 +45,24 @@ def create_ui():
components[f'seed_{prefix}'] = gr.Number(label="Seed (-1 for random)", value=-1, precision=0)
components[f'batch_size_{prefix}'] = gr.Slider(label="Batch Size", minimum=1, maximum=16, step=1, value=1)
with gr.Row():
+ components[f'clip_skip_{prefix}'] = gr.Slider(label="Clip Skip", minimum=1, maximum=2, step=1, value=1, visible=False, interactive=True)
+ components[f'guidance_{prefix}'] = gr.Slider(label="Guidance (FLUX)", minimum=1.0, maximum=10.0, step=0.1, value=3.5, visible=False, interactive=True)
components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=None, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU. Longer jobs may need more time.")
- components[f'clip_skip_{prefix}'] = gr.State(value=1)
-
with gr.Column(scale=1):
components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=1, object_fit="contain", height=505)
- components.update(create_api_key_ui(prefix))
+
components.update(create_lora_settings_ui(prefix))
components.update(create_controlnet_ui(prefix))
+ components.update(create_diffsynth_controlnet_ui(prefix))
components.update(create_ipadapter_ui(prefix))
+ components.update(create_flux1_ipadapter_ui(prefix))
+ components.update(create_sd3_ipadapter_ui(prefix))
components.update(create_embedding_ui(prefix))
+ components.update(create_style_ui(prefix))
components.update(create_conditioning_ui(prefix))
+ components.update(create_reference_latent_ui(prefix))
components.update(create_vae_override_ui(prefix))
return components
\ No newline at end of file
diff --git a/ui/shared/inpaint_ui.py b/ui/shared/inpaint_ui.py
index d188e3be53a66bd20ea53efe24414fd35fec62c2..3a221d7ad92f1dca70372eafb461750f0f661096 100644
--- a/ui/shared/inpaint_ui.py
+++ b/ui/shared/inpaint_ui.py
@@ -2,8 +2,11 @@ import gradio as gr
from core.settings import MODEL_MAP_CHECKPOINT
from .ui_components import (
create_base_parameter_ui, create_lora_settings_ui,
- create_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
- create_conditioning_ui, create_vae_override_ui, create_api_key_ui
+ create_controlnet_ui, create_diffsynth_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,
+ create_reference_latent_ui
)
def create_ui():
@@ -11,7 +14,11 @@ def create_ui():
components = {}
with gr.Column():
+ with gr.Row() as arch_row:
+ components.update(create_model_architecture_filter_ui(prefix))
+
with gr.Row() as model_and_run_row:
+ components.update(create_category_filter_ui(prefix))
components[f'base_model_{prefix}'] = gr.Dropdown(
label="Base Model",
choices=list(MODEL_MAP_CHECKPOINT.keys()),
@@ -21,7 +28,7 @@ def create_ui():
with gr.Column(scale=1):
components[f'run_{prefix}'] = gr.Button("Run Inpaint", variant="primary")
- components[f'model_and_run_row_{prefix}'] = model_and_run_row
+ components[f'model_and_run_row_{prefix}'] = [arch_row, model_and_run_row]
with gr.Row() as main_content_row:
with gr.Column(scale=1) as editor_column:
@@ -39,14 +46,20 @@ def create_ui():
components[f'editor_column_{prefix}'] = editor_column
with gr.Column(scale=2) as prompts_column:
- components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=6, placeholder="Describe what to fill in the mask...")
- components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=6, value="monochrome, (low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn,")
+ components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=6)
+ components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=6)
components[f'prompts_column_{prefix}'] = prompts_column
with gr.Row() as params_and_gallery_row:
with gr.Column(scale=1):
- param_defaults = {'w': 1024, 'h': 1024, 'cs_vis': False, 'cs_val': 1}
from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
+ with gr.Row():
+ components[f'denoise_{prefix}'] = gr.Slider(
+ label="Denoise", minimum=0.0, maximum=1.0, step=0.05, value=1.0
+ )
+ components[f'grow_mask_by_{prefix}'] = gr.Slider(
+ label="Grow Mask By", minimum=0, maximum=64, step=1, value=6
+ )
with gr.Row():
components[f'sampler_{prefix}'] = gr.Dropdown(label="Sampler", choices=SAMPLER_CHOICES, value=SAMPLER_CHOICES[0])
components[f'scheduler_{prefix}'] = gr.Dropdown(label="Scheduler", choices=SCHEDULER_CHOICES, value='normal' if 'normal' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0])
@@ -57,24 +70,30 @@ def create_ui():
components[f'seed_{prefix}'] = gr.Number(label="Seed (-1 for random)", value=-1, precision=0)
components[f'batch_size_{prefix}'] = gr.Slider(label="Batch Size", minimum=1, maximum=16, step=1, value=1)
with gr.Row():
+ components[f'clip_skip_{prefix}'] = gr.Slider(label="Clip Skip", minimum=1, maximum=2, step=1, value=1, visible=False, interactive=True)
+ components[f'guidance_{prefix}'] = gr.Slider(label="Guidance (FLUX)", minimum=1.0, maximum=10.0, step=0.1, value=3.5, visible=False, interactive=True)
components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=None, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU.")
- components[f'clip_skip_{prefix}'] = gr.State(value=1)
components[f'width_{prefix}'] = gr.State(value=512)
components[f'height_{prefix}'] = gr.State(value=512)
with gr.Column(scale=1):
- components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=1, object_fit="contain", height=414)
+ components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=1, object_fit="contain", height=510)
components[f'params_and_gallery_row_{prefix}'] = params_and_gallery_row
with gr.Column() as accordion_wrapper:
- components.update(create_api_key_ui(prefix))
+
components.update(create_lora_settings_ui(prefix))
components.update(create_controlnet_ui(prefix))
+ components.update(create_diffsynth_controlnet_ui(prefix))
components.update(create_ipadapter_ui(prefix))
+ components.update(create_flux1_ipadapter_ui(prefix))
+ components.update(create_sd3_ipadapter_ui(prefix))
+ components.update(create_style_ui(prefix))
components.update(create_embedding_ui(prefix))
components.update(create_conditioning_ui(prefix))
+ components.update(create_reference_latent_ui(prefix))
components.update(create_vae_override_ui(prefix))
components[f'accordion_wrapper_{prefix}'] = accordion_wrapper
diff --git a/ui/shared/outpaint_ui.py b/ui/shared/outpaint_ui.py
index 0cf10b302c8ee505a7fd972fceca10b48773c6dd..b6bf9e969718a9916893b53bd378b4aa45e7c473 100644
--- a/ui/shared/outpaint_ui.py
+++ b/ui/shared/outpaint_ui.py
@@ -3,8 +3,11 @@ from core.settings import MODEL_MAP_CHECKPOINT
from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
from .ui_components import (
create_lora_settings_ui,
- create_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
- create_conditioning_ui, create_vae_override_ui, create_api_key_ui
+ create_controlnet_ui, create_diffsynth_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,
+ create_reference_latent_ui
)
def create_ui():
@@ -12,7 +15,10 @@ def create_ui():
components = {}
with gr.Column():
+ components.update(create_model_architecture_filter_ui(prefix))
+
with gr.Row():
+ components.update(create_category_filter_ui(prefix))
components[f'base_model_{prefix}'] = gr.Dropdown(
label="Base Model",
choices=list(MODEL_MAP_CHECKPOINT.keys()),
@@ -26,17 +32,19 @@ def create_ui():
with gr.Column(scale=1):
components[f'input_image_{prefix}'] = gr.Image(type="pil", label="Input Image", height=255)
with gr.Column(scale=2):
- components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3, placeholder="Describe the content for the expanded areas...")
- components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3, value="monochrome, (low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn,")
+ components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3)
+ components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3)
with gr.Row():
with gr.Column(scale=1):
with gr.Row():
- components[f'outpaint_left_{prefix}'] = gr.Slider(label="Pad Left", minimum=0, maximum=512, step=64, value=0)
- components[f'outpaint_right_{prefix}'] = gr.Slider(label="Pad Right", minimum=0, maximum=512, step=64, value=256)
+ components[f'left_{prefix}'] = gr.Slider(label="Pad Left", minimum=0, maximum=512, step=64, value=64)
+ components[f'right_{prefix}'] = gr.Slider(label="Pad Right", minimum=0, maximum=512, step=64, value=64)
with gr.Row():
- components[f'outpaint_top_{prefix}'] = gr.Slider(label="Pad Top", minimum=0, maximum=512, step=64, value=0)
- components[f'outpaint_bottom_{prefix}'] = gr.Slider(label="Pad Bottom", minimum=0, maximum=512, step=64, value=0)
+ components[f'top_{prefix}'] = gr.Slider(label="Pad Top", minimum=0, maximum=512, step=64, value=64)
+ components[f'bottom_{prefix}'] = gr.Slider(label="Pad Bottom", minimum=0, maximum=512, step=64, value=64)
+
+ components[f'feathering_{prefix}'] = gr.Slider(label="Feathering / Grow Mask", minimum=0, maximum=100, step=1, value=10)
with gr.Row():
components[f'sampler_{prefix}'] = gr.Dropdown(label="Sampler", choices=SAMPLER_CHOICES, value=SAMPLER_CHOICES[0])
@@ -48,21 +56,27 @@ def create_ui():
components[f'seed_{prefix}'] = gr.Number(label="Seed (-1 for random)", value=-1, precision=0)
components[f'batch_size_{prefix}'] = gr.Slider(label="Batch Size", minimum=1, maximum=16, step=1, value=1)
with gr.Row():
+ components[f'clip_skip_{prefix}'] = gr.Slider(label="Clip Skip", minimum=1, maximum=2, step=1, value=1, visible=False, interactive=True)
+ components[f'guidance_{prefix}'] = gr.Slider(label="Guidance (FLUX)", minimum=1.0, maximum=10.0, step=0.1, value=3.5, visible=False, interactive=True)
components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=None, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU.")
- components[f'clip_skip_{prefix}'] = gr.State(value=1)
components[f'width_{prefix}'] = gr.State(value=512)
components[f'height_{prefix}'] = gr.State(value=512)
with gr.Column(scale=1):
- components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=1, object_fit="contain", height=595)
+ components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=1, object_fit="contain", height=685)
- components.update(create_api_key_ui(prefix))
+
components.update(create_lora_settings_ui(prefix))
components.update(create_controlnet_ui(prefix))
+ components.update(create_diffsynth_controlnet_ui(prefix))
components.update(create_ipadapter_ui(prefix))
+ components.update(create_flux1_ipadapter_ui(prefix))
+ components.update(create_sd3_ipadapter_ui(prefix))
+ components.update(create_style_ui(prefix))
components.update(create_embedding_ui(prefix))
components.update(create_conditioning_ui(prefix))
+ components.update(create_reference_latent_ui(prefix))
components.update(create_vae_override_ui(prefix))
return components
\ No newline at end of file
diff --git a/ui/shared/txt2img_ui.py b/ui/shared/txt2img_ui.py
index 0a1cdc41571afc9d513f63121193dba91592c8f8..ef84f796e8d4c92fa456afe991a08a21d4faa9e2 100644
--- a/ui/shared/txt2img_ui.py
+++ b/ui/shared/txt2img_ui.py
@@ -2,8 +2,11 @@ import gradio as gr
from core.settings import MODEL_MAP_CHECKPOINT
from .ui_components import (
create_base_parameter_ui, create_lora_settings_ui,
- create_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
- create_conditioning_ui, create_vae_override_ui, create_api_key_ui
+ create_controlnet_ui, create_diffsynth_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,
+ create_reference_latent_ui
)
def create_ui():
@@ -12,13 +15,21 @@ def create_ui():
components = {}
with gr.Column():
+ components.update(create_model_architecture_filter_ui(prefix))
+
with gr.Row():
- components[f'base_model_{prefix}'] = gr.Dropdown(label="Base Model", choices=list(MODEL_MAP_CHECKPOINT.keys()), value=list(MODEL_MAP_CHECKPOINT.keys())[0], scale=3)
+ components.update(create_category_filter_ui(prefix))
+ components[f'base_model_{prefix}'] = gr.Dropdown(
+ label="Base Model",
+ choices=list(MODEL_MAP_CHECKPOINT.keys()),
+ value=list(MODEL_MAP_CHECKPOINT.keys())[0],
+ scale=3
+ )
with gr.Column(scale=1):
components[f'run_{prefix}'] = gr.Button("Run", variant="primary")
- components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3, placeholder="Enter your prompt")
- components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3, value="monochrome, (low quality, worst quality:1.2), 3d, watermark, signature, ugly, poorly drawn,")
+ components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3)
+ components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3)
with gr.Row():
with gr.Column(scale=1):
@@ -27,12 +38,17 @@ def create_ui():
with gr.Column(scale=1):
components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=2, object_fit="contain", height=627)
- components.update(create_api_key_ui(prefix))
+
components.update(create_lora_settings_ui(prefix))
components.update(create_controlnet_ui(prefix))
+ components.update(create_diffsynth_controlnet_ui(prefix))
components.update(create_ipadapter_ui(prefix))
+ components.update(create_flux1_ipadapter_ui(prefix))
+ components.update(create_sd3_ipadapter_ui(prefix))
components.update(create_embedding_ui(prefix))
+ components.update(create_style_ui(prefix))
components.update(create_conditioning_ui(prefix))
+ components.update(create_reference_latent_ui(prefix))
components.update(create_vae_override_ui(prefix))
return components
\ No newline at end of file
diff --git a/ui/shared/ui_components.py b/ui/shared/ui_components.py
index d71d085873eafdffa075d3571e6ec91cb442e91d..5b64b3896a8dbacf36d4ab5b12bb96fd3f10b2c7 100644
--- a/ui/shared/ui_components.py
+++ b/ui/shared/ui_components.py
@@ -2,29 +2,71 @@ import gradio as gr
from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
from core.settings import (
MAX_LORAS, LORA_SOURCE_CHOICES, MAX_EMBEDDINGS, MAX_CONDITIONINGS,
- MAX_CONTROLNETS, MAX_IPADAPTERS, RESOLUTION_MAP
+ MAX_CONTROLNETS, MAX_IPADAPTERS, RESOLUTION_MAP, ARCHITECTURES_CONFIG,
+ MODEL_MAP_CHECKPOINT, MODEL_TYPE_MAP, FEATURES_CONFIG, ARCH_CATEGORIES_MAP
)
import yaml
import os
from functools import lru_cache
+default_model_name = list(MODEL_MAP_CHECKPOINT.keys())[0] if MODEL_MAP_CHECKPOINT else None
+default_m_type = MODEL_TYPE_MAP.get(default_model_name, "SDXL") if default_model_name else "SDXL"
+default_architectures_dict = ARCHITECTURES_CONFIG.get('architectures', {})
+default_arch_model_type = default_architectures_dict.get(default_m_type, {}).get("model_type", default_m_type.lower().replace(" ", "").replace(".", ""))
+default_arch_features = FEATURES_CONFIG.get(default_arch_model_type, FEATURES_CONFIG.get('default', {}))
+default_enabled_chains = default_arch_features.get('enabled_chains', [])
+
+
@lru_cache(maxsize=1)
-def get_ipadapter_presets_from_yaml():
+def get_ipadapter_config_from_yaml():
try:
_PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
_IPADAPTER_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'ipadapter.yaml')
with open(_IPADAPTER_LIST_PATH, 'r', encoding='utf-8') as f:
config = yaml.safe_load(f)
- if isinstance(config, list):
- presets = [item.get('preset_name') for item in config if item.get('preset_name')]
- if "Composition" not in presets:
- pass
- return presets
- return []
+ return config
except Exception as e:
print(f"Warning: Could not load ipadapter.yaml for UI components: {e}")
- return ["STANDARD (medium strength)"]
+ return {}
+
+def get_ipadapter_presets(arch="SDXL"):
+ config = get_ipadapter_config_from_yaml()
+ presets = []
+ if config:
+ std_presets = config.get("IPAdapter_presets", {}).get(arch, [])
+ face_presets = config.get("IPAdapter_FaceID_presets", {}).get(arch, [])
+ if std_presets:
+ presets.extend(std_presets)
+ if face_presets:
+ presets.extend(face_presets)
+ return presets if presets else ["STANDARD (medium strength)"]
+
+def create_model_architecture_filter_ui(prefix):
+ components = {}
+ ordered_architectures = ARCHITECTURES_CONFIG.get("architecture_order", [])
+ choices = ["ALL"] + ordered_architectures
+
+ components[f'model_arch_{prefix}'] = gr.Radio(
+ label="Model Architecture",
+ choices=choices,
+ value="ALL",
+ interactive=True
+ )
+ return components
+def create_category_filter_ui(prefix):
+ valid_cats = list(set(cat for cats in ARCH_CATEGORIES_MAP.values() for cat in cats))
+ cat_choices = ["ALL"] + sorted(valid_cats)
+
+ components = {}
+ components[f'model_cat_{prefix}'] = gr.Dropdown(
+ label="Filter Models",
+ choices=cat_choices,
+ value="ALL",
+ interactive=True,
+ scale=1
+ )
+ return components
def create_base_parameter_ui(prefix, defaults=None):
if defaults is None:
@@ -35,7 +77,7 @@ def create_base_parameter_ui(prefix, defaults=None):
with gr.Row():
components[f'aspect_ratio_{prefix}'] = gr.Dropdown(
label="Aspect Ratio",
- choices=list(RESOLUTION_MAP['sdxl'].keys()),
+ choices=list(RESOLUTION_MAP.get('sdxl', {}).keys()),
value="1:1 (Square)",
interactive=True
)
@@ -52,33 +94,19 @@ def create_base_parameter_ui(prefix, defaults=None):
components[f'seed_{prefix}'] = gr.Number(label="Seed (-1 for random)", value=-1, precision=0)
components[f'batch_size_{prefix}'] = gr.Slider(label="Batch Size", minimum=1, maximum=16, step=1, value=1)
with gr.Row():
- components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=None, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU. Longer jobs may need more time.")
-
- components[f'clip_skip_{prefix}'] = gr.State(value=1)
+ components[f'clip_skip_{prefix}'] = gr.Slider(label="Clip Skip", minimum=1, maximum=2, step=1, value=1, visible=False, interactive=True)
+ components[f'guidance_{prefix}'] = gr.Slider(label="Guidance (FLUX)", minimum=1.0, maximum=10.0, step=0.1, value=3.5, visible=False, interactive=True)
+ components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=None, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU.")
return components
-def create_api_key_ui(prefix: str):
- components = {}
- with gr.Accordion("API Key Settings", open=False) as api_key_accordion:
- components[f'api_key_accordion_{prefix}'] = api_key_accordion
- gr.Markdown("💡 **Tip:** Enter API key (optional). An API key is required for resources that need a login to download. The key will be used for all Civitai downloads on this tab. You can also manually upload the corresponding files to avoid API Key leakage caused by potential vulnerabilities.")
- with gr.Row():
- components[f'civitai_api_key_{prefix}'] = gr.Textbox(
- label="Civitai API Key",
- type="password",
- placeholder="Enter your Civitai API key here (optional)"
- )
- return components
-
-
def create_lora_settings_ui(prefix: str):
components = {}
lora_rows, lora_sources, lora_ids, lora_scales, lora_uploads = [], [], [], [], []
- with gr.Accordion("LoRA Settings", open=False) as lora_accordion:
+ with gr.Accordion("LoRA Settings", open=False, visible=('lora' in default_enabled_chains)) as lora_accordion:
components[f'lora_accordion_{prefix}'] = lora_accordion
gr.Markdown("💡 **Tip:** When downloading from Civitai, please use the **Version ID**, not the Model ID. You can find the Version ID in the URL (e.g., `civitai.com/models/123?modelVersionId=456`) or under the model's download button.")
components[f'lora_count_state_{prefix}'] = gr.State(1)
@@ -117,7 +145,7 @@ def create_controlnet_ui(prefix: str, max_units=MAX_CONTROLNETS):
components = {}
key = lambda name: f"{name}_{prefix}"
- with gr.Accordion("ControlNet Settings", open=False) as accordion:
+ with gr.Accordion("ControlNet Settings", open=False, visible=('controlnet' in default_enabled_chains)) as accordion:
components[key('controlnet_accordion')] = accordion
cn_rows, images, series, types, strengths, filepaths = [], [], [], [], [], []
@@ -135,8 +163,8 @@ def create_controlnet_ui(prefix: str, max_units=MAX_CONTROLNETS):
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))
- series.append(gr.Dropdown(label="Series", choices=[], interactive=True))
+ 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)
@@ -155,14 +183,56 @@ def create_controlnet_ui(prefix: str, max_units=MAX_CONTROLNETS):
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=('controlnet_model_patch' 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}"
- sdxl_presets = get_ipadapter_presets_from_yaml()
+ sdxl_presets = get_ipadapter_presets("SDXL")
default_preset = sdxl_presets[0] if sdxl_presets else None
- with gr.Accordion("IPAdapter Settings", open=False) as accordion:
+ with gr.Accordion("IPAdapter Settings", open=False, visible=('ipadapter' in default_enabled_chains)) as accordion:
components[key('ipadapter_accordion')] = accordion
gr.Markdown("Powered by [cubiq/ComfyUI_IPAdapter_plus](https://github.com/cubiq/ComfyUI_IPAdapter_plus).")
@@ -171,7 +241,8 @@ def create_ipadapter_ui(prefix: str, max_units=MAX_IPADAPTERS):
label="Preset (for all images)",
choices=sdxl_presets,
value=default_preset,
- interactive=True
+ interactive=True,
+ allow_custom_value=True
)
components[key('ipadapter_embeds_scaling')] = gr.Dropdown(
label="Embeds Scaling",
@@ -203,7 +274,7 @@ def create_ipadapter_ui(prefix: str, max_units=MAX_IPADAPTERS):
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"IPAdapter Image {i+1}", type="pil", sources="upload", height=256))
+ images.append(gr.Image(label=f"IPAdapter Image {i+1}", type="pil", sources=["upload"], height=256))
with gr.Column(scale=2):
weights.append(gr.Slider(label="Weight", minimum=0.0, maximum=2.0, step=0.05, value=1.0, interactive=True))
lora_strengths.append(gr.Slider(label="LoRA Strength", minimum=0.0, maximum=2.0, step=0.05, value=0.6, interactive=True, visible=False))
@@ -226,11 +297,117 @@ def create_ipadapter_ui(prefix: str, max_units=MAX_IPADAPTERS):
return components
+def create_flux1_ipadapter_ui(prefix: str, max_units=MAX_IPADAPTERS):
+ components = {}
+ key = lambda name: f"{name}_{prefix}"
+
+ with gr.Accordion("IPAdapter Settings (FLUX.1)", open=False, visible=('flux1_ipadapter' in default_enabled_chains)) as accordion:
+ components[key('flux1_ipadapter_accordion')] = accordion
+
+ ipa_rows, images, weights, start_percents, end_percents = [], [], [], [], []
+ components.update({
+ key('flux1_ipadapter_rows'): ipa_rows,
+ key('flux1_ipadapter_images'): images,
+ key('flux1_ipadapter_weights'): weights,
+ key('flux1_ipadapter_start_percents'): start_percents,
+ key('flux1_ipadapter_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"IPAdapter Image {i+1}", type="pil", sources=["upload"], height=256))
+ with gr.Column(scale=2):
+ weights.append(gr.Slider(label="Weight", minimum=0.0, maximum=2.0, step=0.05, value=0.6, interactive=True))
+ with gr.Row():
+ start_percents.append(gr.Slider(label="Start At", minimum=0.0, maximum=1.0, step=0.01, value=0.0, interactive=True))
+ end_percents.append(gr.Slider(label="End At", minimum=0.0, maximum=1.0, step=0.01, value=0.6, interactive=True))
+ ipa_rows.append(row)
+
+ with gr.Row():
+ components[key('add_flux1_ipadapter_button')] = gr.Button("✚ Add IPAdapter (FLUX)")
+ components[key('delete_flux1_ipadapter_button')] = gr.Button("➖ Delete IPAdapter (FLUX)", visible=False)
+ components[key('flux1_ipadapter_count_state')] = gr.State(1)
+
+ all_flux1_ipa_components_flat = images + weights + start_percents + end_percents
+ components[key('all_flux1_ipadapter_components_flat')] = all_flux1_ipa_components_flat
+
+ return components
+
+def create_sd3_ipadapter_ui(prefix: str, max_units=MAX_IPADAPTERS):
+ components = {}
+ key = lambda name: f"{name}_{prefix}"
+
+ with gr.Accordion("IPAdapter Settings (SD3)", open=False, visible=('sd3_ipadapter' in default_enabled_chains)) as accordion:
+ components[key('sd3_ipadapter_accordion')] = accordion
+
+ ipa_rows, images, weights, start_percents, end_percents = [], [], [], [], []
+ components.update({
+ key('sd3_ipadapter_rows'): ipa_rows,
+ key('sd3_ipadapter_images'): images,
+ key('sd3_ipadapter_weights'): weights,
+ key('sd3_ipadapter_start_percents'): start_percents,
+ key('sd3_ipadapter_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"IPAdapter Image {i+1}", type="pil", sources=["upload"], height=256))
+ with gr.Column(scale=2):
+ weights.append(gr.Slider(label="Weight", minimum=0.0, maximum=2.0, step=0.05, value=0.5, interactive=True))
+ with gr.Row():
+ start_percents.append(gr.Slider(label="Start At", minimum=0.0, maximum=1.0, step=0.01, value=0.0, interactive=True))
+ end_percents.append(gr.Slider(label="End At", minimum=0.0, maximum=1.0, step=0.01, value=1.0, interactive=True))
+ ipa_rows.append(row)
+
+ with gr.Row():
+ components[key('add_sd3_ipadapter_button')] = gr.Button("✚ Add IPAdapter (SD3)")
+ components[key('delete_sd3_ipadapter_button')] = gr.Button("➖ Delete IPAdapter (SD3)", visible=False)
+ components[key('sd3_ipadapter_count_state')] = gr.State(1)
+
+ all_sd3_ipa_components_flat = images + weights + start_percents + end_percents
+ components[key('all_sd3_ipadapter_components_flat')] = all_sd3_ipa_components_flat
+
+ return components
+
+def create_style_ui(prefix: str):
+ components = {}
+ key = lambda name: f"{name}_{prefix}"
+
+ with gr.Accordion("Style Settings (FLUX.1)", open=False, visible=('style' in default_enabled_chains)) as accordion:
+ components[key('style_accordion')] = accordion
+
+ style_rows, images, strengths = [], [], []
+ components.update({
+ key('style_rows'): style_rows,
+ key('style_images'): images,
+ key('style_strengths'): strengths
+ })
+
+ for i in range(5):
+ with gr.Row(visible=(i < 1)) as row:
+ with gr.Column(scale=1):
+ images.append(gr.Image(label=f"Style Image {i+1}", type="pil", sources=["upload"], height=256))
+ with gr.Column(scale=2):
+ strengths.append(gr.Slider(label="Strength", minimum=0.0, maximum=2.0, step=0.05, value=1.0, interactive=True))
+ style_rows.append(row)
+
+ with gr.Row():
+ components[key('add_style_button')] = gr.Button("✚ Add Style (FLUX)")
+ components[key('delete_style_button')] = gr.Button("➖ Delete Style (FLUX)", visible=False)
+ components[key('style_count_state')] = gr.State(1)
+
+ all_style_components_flat = images + strengths
+ components[key('all_style_components_flat')] = all_style_components_flat
+
+ return components
+
def create_embedding_ui(prefix: str):
components = {}
key = lambda name: f"{name}_{prefix}"
- with gr.Accordion("Embedding Settings", open=False, visible=True) as accordion:
+ with gr.Accordion("Embedding Settings", open=False, visible=('embedding' in default_enabled_chains)) as accordion:
components[key('embedding_accordion')] = accordion
gr.Markdown("💡 **Tip:** Embeddings are automatically added to your prompt using `embedding:filename` syntax. When downloading from Civitai, please use the **Version ID**, not the Model ID. You can find the Version ID in the URL (e.g., `civitai.com/models/123?modelVersionId=456`) or under the model's download button. For instance, using the Version ID `456` from the example above would automatically append `embedding:civitai_456` to your positive prompt.")
@@ -268,7 +445,7 @@ def create_conditioning_ui(prefix: str):
components = {}
key = lambda name: f"{name}_{prefix}"
- with gr.Accordion("Conditioning Settings", open=False) as accordion:
+ with gr.Accordion("Conditioning Settings", open=False, visible=('conditioning' in default_enabled_chains)) as accordion:
components[key('conditioning_accordion')] = accordion
gr.Markdown("💡 **Tip:** Define rectangular areas and assign specific prompts to them. Coordinates (X, Y) start from the top-left corner.")
@@ -335,4 +512,33 @@ def create_vae_override_ui(prefix: str):
components[key('vae_upload_button')] = upload_btn
components[key('vae_file')] = gr.State(None)
+ return components
+
+def create_reference_latent_ui(prefix: str, max_units=10):
+ components = {}
+ key = lambda name: f"{name}_{prefix}"
+
+ with gr.Accordion("Reference Edit Settings", open=False, visible=('reference_latent' in default_enabled_chains)) as ref_accordion:
+ components[key('reference_latent_accordion')] = ref_accordion
+ gr.Markdown("💡 **Tip:** For multimodal models (like FLUX.2 or OmniGen), this feature enables powerful editing and combining capabilities. In txt2img mode, adding a single reference image performs an **Image Edit**, while adding multiple images performs an **Image Combine**.")
+
+ ref_image_groups = []
+ ref_image_inputs = []
+ with gr.Row():
+ for i in range(max_units):
+ with gr.Column(visible=(i < 1), min_width=160) as img_col:
+ img_comp = gr.Image(type="pil", label=f"Ref. {i+1}", sources=["upload"], height=150)
+ ref_image_groups.append(img_col)
+ ref_image_inputs.append(img_comp)
+
+ components[key('reference_latent_rows')] = ref_image_groups
+ components[key('reference_latent_images')] = ref_image_inputs
+
+ with gr.Row():
+ components[key('add_reference_latent_button')] = gr.Button("✚ Add Reference Image")
+ components[key('delete_reference_latent_button')] = gr.Button("➖ Delete Reference Image", visible=False)
+ components[key('reference_latent_count_state')] = gr.State(1)
+
+ components[key('all_reference_latent_components_flat')] = ref_image_inputs
+
return components
\ No newline at end of file
diff --git a/utils/app_utils.py b/utils/app_utils.py
index d2b352959f445623e17eae4fecedf2bec43f5f6f..ecd977295c2ab931479253391e8d3472c0cec79d 100644
--- a/utils/app_utils.py
+++ b/utils/app_utils.py
@@ -11,17 +11,38 @@ from huggingface_hub import hf_hub_download, constants as hf_constants
import torch
import numpy as np
from PIL import Image, ImageChops
-
+import yaml
from core.settings import *
DISK_LIMIT_GB = 120
MODELS_ROOT_DIR = "ComfyUI/models"
-PREPROCESSOR_MODEL_MAP = None
-PREPROCESSOR_PARAMETER_MAP = None
IPADAPTER_PRESETS = None
+class UniqueKeyLoader(yaml.SafeLoader):
+ """
+ A custom YAML loader that handles duplicate keys by grouping their values into a list.
+ """
+ def construct_mapping(self, node, deep=False):
+ mapping = []
+ for key_node, value_node in node.value:
+ key = self.construct_object(key_node, deep=deep)
+ value = self.construct_object(value_node, deep=deep)
+ mapping.append((key, value))
+
+ result = {}
+ for k, v in mapping:
+ if k in result:
+ if isinstance(result[k], list):
+ result[k].append(v)
+ else:
+ result[k] = [result[k], v]
+ else:
+ result[k] = v
+ return result
+
+UniqueKeyLoader.add_constructor(yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG, UniqueKeyLoader.construct_mapping)
def save_uploaded_file_with_hash(file_obj: gr.File, target_dir: str) -> str:
if not file_obj:
@@ -49,7 +70,6 @@ def save_uploaded_file_with_hash(file_obj: gr.File, target_dir: str) -> str:
return hashed_filename
-
def bytes_to_gb(byte_size: int) -> float:
if byte_size is None or byte_size == 0:
return 0.0
@@ -117,7 +137,6 @@ def enforce_disk_limit():
except Exception as e:
print(f"--- [Storage Manager] An unexpected error occurred: {e} ---")
-
def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
try:
return obj[index]
@@ -152,7 +171,6 @@ def sanitize_filename(filename: str) -> str:
sanitized = re.sub(r'[^\w\.\-]', '_', sanitized)
return sanitized.lstrip('/\\')
-
def get_civitai_file_info(version_id: str) -> dict | None:
api_url = f"https://civitai.com/api/v1/model-versions/{version_id}"
try:
@@ -169,7 +187,6 @@ def get_civitai_file_info(version_id: str) -> dict | None:
except Exception:
return None
-
def download_file(url: str, save_path: str, api_key: str = None, progress=None, desc: str = "") -> str:
enforce_disk_limit()
@@ -198,7 +215,6 @@ def download_file(url: str, save_path: str, api_key: str = None, progress=None,
os.remove(save_path)
return f"Download failed for {os.path.basename(save_path)}: {e}"
-
def get_lora_path(source: str, id_or_url: str, civitai_key: str, progress) -> tuple[str | None, str]:
if not id_or_url or not id_or_url.strip():
return None, "No ID/URL provided."
@@ -306,19 +322,19 @@ def _ensure_model_downloaded(display_name: str, progress=gr.Progress()):
if display_name not in ALL_MODEL_MAP:
raise ValueError(f"Model '{display_name}' not found in configuration.")
- _, repo_filename, model_type, _ = ALL_MODEL_MAP[display_name]
+ _, repo_filename, _, _ = ALL_MODEL_MAP[display_name]
+ base_filename = os.path.basename(repo_filename)
+
+ download_info = ALL_FILE_DOWNLOAD_MAP.get(base_filename)
+ if not download_info:
+ raise gr.Error(f"Model '{base_filename}' not found in file_list.yaml. Cannot download.")
+
+ category = download_info.get("category")
+ dest_dir = CATEGORY_TO_DIR_MAP.get(category)
- type_to_dir_map = {
- "SDXL": CHECKPOINT_DIR, "SD1.5": CHECKPOINT_DIR, "UNET": DIFFUSION_MODELS_DIR,
- "VAE": VAE_DIR, "TEXT_ENCODER": TEXT_ENCODERS_DIR, "LORA": LORA_DIR,
- "IPADAPTER": os.path.join(os.path.dirname(LORA_DIR), "ipadapter"),
- "CLIP_VISION": os.path.join(os.path.dirname(LORA_DIR), "clip_vision")
- }
- dest_dir = type_to_dir_map.get(model_type)
if not dest_dir:
- raise ValueError(f"Unknown model type '{model_type}' for '{display_name}'.")
+ raise ValueError(f"Unknown YAML category '{category}' for '{base_filename}'.")
- base_filename = os.path.basename(repo_filename)
dest_path = os.path.join(dest_dir, base_filename)
if os.path.lexists(dest_path):
@@ -328,10 +344,6 @@ def _ensure_model_downloaded(display_name: str, progress=gr.Progress()):
else:
return base_filename
- download_info = ALL_FILE_DOWNLOAD_MAP.get(base_filename)
- if not download_info:
- raise gr.Error(f"Model '{base_filename}' not found in file_list.yaml. Cannot download.")
-
source = download_info.get("source")
try:
progress(0, desc=f"Downloading: {base_filename}")
@@ -342,7 +354,7 @@ def _ensure_model_downloaded(display_name: str, progress=gr.Progress()):
if not repo_id:
raise ValueError(f"repo_id is missing for HF model '{base_filename}'")
- cached_path = hf_hub_download(repo_id=repo_id, filename=hf_filename)
+ cached_path = hf_hub_download(repo_id=repo_id, filename=hf_filename, token=os.environ.get("HF_TOKEN"))
os.makedirs(dest_dir, exist_ok=True)
os.symlink(cached_path, dest_path)
print(f"✅ Symlinked '{cached_path}' to '{dest_path}'")
@@ -357,7 +369,7 @@ def _ensure_model_downloaded(display_name: str, progress=gr.Progress()):
raise ConnectionError(f"Could not get download URL for Civitai model version ID {model_version_id}")
status = download_file(
- file_info['downloadUrl'], dest_path, progress=progress, desc=f"Downloading: {base_filename}"
+ file_info['downloadUrl'], dest_path, api_key=os.environ.get("CIVITAI_API_KEY", ""), progress=progress, desc=f"Downloading: {base_filename}"
)
if "Failed" in status:
raise ConnectionError(status)
@@ -379,14 +391,21 @@ def ensure_controlnet_model_downloaded(filename: str, progress):
if not filename or filename == "None":
return
- dest_path = os.path.join(CONTROLNET_DIR, filename)
- if os.path.exists(dest_path):
- return
-
download_info = ALL_FILE_DOWNLOAD_MAP.get(filename)
if not download_info:
raise gr.Error(f"ControlNet model '{filename}' not found in configuration (file_list.yaml). Cannot download.")
+ category = download_info.get("category", "controlnet")
+ dest_dir = CATEGORY_TO_DIR_MAP.get(category, CONTROLNET_DIR)
+ dest_path = os.path.join(dest_dir, filename)
+
+ if os.path.lexists(dest_path):
+ if not os.path.exists(dest_path):
+ print(f"⚠️ Found and removed broken symlink: {dest_path}")
+ os.remove(dest_path)
+ else:
+ return
+
source = download_info.get("source")
try:
@@ -397,8 +416,8 @@ def ensure_controlnet_model_downloaded(filename: str, progress):
raise ValueError("repo_id is missing for Hugging Face download.")
progress(0, desc=f"Downloading CN: {filename}")
- cached_path = hf_hub_download(repo_id=repo_id, filename=repo_filename)
- os.makedirs(CONTROLNET_DIR, exist_ok=True)
+ cached_path = hf_hub_download(repo_id=repo_id, filename=repo_filename, token=os.environ.get("HF_TOKEN"))
+ os.makedirs(dest_dir, exist_ok=True)
os.symlink(cached_path, dest_path)
print(f"✅ Symlinked ControlNet '{cached_path}' to '{dest_path}'")
progress(1.0, desc=f"Downloaded CN: {filename}")
@@ -415,6 +434,7 @@ def ensure_controlnet_model_downloaded(filename: str, progress):
status = download_file(
file_info['downloadUrl'],
dest_path,
+ api_key=os.environ.get("CIVITAI_API_KEY", ""),
progress=progress,
desc=f"Downloading CN: {filename}"
)
@@ -437,16 +457,16 @@ def load_ipadapter_presets():
return
_PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
- _IPADAPTER_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'ipadapter.yaml')
+ _IPADAPTER_MODELS_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'ipadapter_models.yaml')
try:
- with open(_IPADAPTER_LIST_PATH, 'r', encoding='utf-8') as f:
- presets_list = yaml.safe_load(f)
+ with open(_IPADAPTER_MODELS_PATH, 'r', encoding='utf-8') as f:
+ presets_list = yaml.load(f, Loader=UniqueKeyLoader)
IPADAPTER_PRESETS = {item['preset_name']: item for item in presets_list}
print("✅ IPAdapter presets loaded successfully.")
except Exception as e:
- print(f"❌ FATAL: Could not load or parse ipadapter.yaml. IPAdapter will not work. Error: {e}")
+ print(f"❌ FATAL: Could not load or parse ipadapter_models.yaml. IPAdapter will not work. Error: {e}")
IPADAPTER_PRESETS = {}
def ensure_ipadapter_models_downloaded(preset_name: str, progress):
@@ -461,13 +481,21 @@ def ensure_ipadapter_models_downloaded(preset_name: str, progress):
print(f"⚠️ Warning: IPAdapter preset '{preset_name}' not found in configuration. Skipping download.")
return
- model_files_to_check = {
- preset_info.get('vision_model'): 'CLIP_VISION',
- preset_info.get('ipadapter_model'): 'IPADAPTER',
- preset_info.get('lora_model'): 'LORA'
- }
+ model_files_to_check = []
+
+ def add_files(value, type_name):
+ if not value: return
+ if isinstance(value, list):
+ for v in value:
+ model_files_to_check.append((v, type_name))
+ else:
+ model_files_to_check.append((value, type_name))
- for filename, model_type in model_files_to_check.items():
+ add_files(preset_info.get('clip_vision'), 'CLIP_VISION')
+ add_files(preset_info.get('ipadapter'), 'IPADAPTER')
+ add_files(preset_info.get('loras'), 'LORA')
+
+ for filename, model_type in model_files_to_check:
if not filename:
continue
@@ -482,67 +510,20 @@ def ensure_ipadapter_models_downloaded(preset_name: str, progress):
print(f"❌ Error ensuring download for IPAdapter asset '{filename}': {e}")
-def build_preprocessor_model_map():
- global PREPROCESSOR_MODEL_MAP
- if PREPROCESSOR_MODEL_MAP is not None: return PREPROCESSOR_MODEL_MAP
- print("--- Building ControlNet Preprocessor model map ---")
- manual_map = {
- "dwpose": [("yzd-v/DWPose", "yolox_l.onnx"), ("yzd-v/DWPose", "dw-ll_ucoco_384.onnx"), ("hr16/UnJIT-DWPose", "dw-ll_ucoco.onnx"), ("hr16/DWPose-TorchScript-BatchSize5", "dw-ll_ucoco_384_bs5.torchscript.pt"), ("hr16/DWPose-TorchScript-BatchSize5", "rtmpose-m_ap10k_256_bs5.torchscript.pt"), ("hr16/yolo-nas-fp16", "yolo_nas_l_fp16.onnx"), ("hr16/yolo-nas-fp16", "yolo_nas_m_fp16.onnx"), ("hr16/yolo-nas-fp16", "yolo_nas_s_fp16.onnx")],
- "densepose": [("LayerNorm/DensePose-TorchScript-with-hint-image", "densepose_r50_fpn_dl.torchscript"), ("LayerNorm/DensePose-TorchScript-with-hint-image", "densepose_r101_fpn_dl.torchscript")]
- }
- temp_map = {}
- from nodes import NODE_DISPLAY_NAME_MAPPINGS
- wrappers_dir = Path("./custom_nodes/comfyui_controlnet_aux/node_wrappers/")
- if not wrappers_dir.exists():
- print("⚠️ ControlNet AUX wrappers directory not found. Cannot build model map.")
- PREPROCESSOR_MODEL_MAP = {}; return PREPROCESSOR_MODEL_MAP
- for wrapper_file in wrappers_dir.glob("*.py"):
- if wrapper_file.name == "__init__.py": continue
- with open(wrapper_file, 'r', encoding='utf-8') as f:
- content = f.read()
- display_name_matches = re.findall(r'NODE_DISPLAY_NAME_MAPPINGS\s*=\s*{(?:.|\n)*?["\'](.*?)["\']\s*:\s*["\'](.*?)["\']', content)
- for _, display_name in display_name_matches:
- if display_name not in temp_map: temp_map[display_name] = []
- manual_key = wrapper_file.stem
- if manual_key in manual_map: temp_map[display_name].extend(manual_map[manual_key])
- matches = re.findall(r"from_pretrained\s*\(\s*(?:filename=)?\s*f?[\"']([^\"']+)[\"']", content)
- for model_filename in matches:
- repo_id = "lllyasviel/Annotators"
- if "depth_anything" in model_filename and "v2" in model_filename: repo_id = "LiheYoung/Depth-Anything-V2"
- elif "depth_anything" in model_filename: repo_id = "LiheYoung/Depth-Anything"
- elif "diffusion_edge" in model_filename: repo_id = "hr16/Diffusion-Edge"
- temp_map[display_name].append((repo_id, model_filename))
- final_map = {name: sorted(list(set(models))) for name, models in temp_map.items() if models}
- PREPROCESSOR_MODEL_MAP = final_map
- print("✅ ControlNet Preprocessor model map built."); return PREPROCESSOR_MODEL_MAP
-
-def build_preprocessor_parameter_map():
- global PREPROCESSOR_PARAMETER_MAP
- if PREPROCESSOR_PARAMETER_MAP is not None: return
- print("--- Building ControlNet Preprocessor parameter map ---")
- param_map = {}
- from nodes import NODE_CLASS_MAPPINGS, NODE_DISPLAY_NAME_MAPPINGS
- for class_name, node_class in NODE_CLASS_MAPPINGS.items():
- if not hasattr(node_class, "INPUT_TYPES"): continue
- if hasattr(node_class, '__module__') and 'comfyui_controlnet_aux.node_wrappers' not in node_class.__module__: continue
- display_name = NODE_DISPLAY_NAME_MAPPINGS.get(class_name)
- if not display_name: continue
- try:
- input_types = node_class.INPUT_TYPES()
- all_inputs = {**input_types.get('required', {}), **input_types.get('optional', {})}
- params = []
- for name, details in all_inputs.items():
- if name in ['image', 'resolution', 'pose_kps']: continue
- if not isinstance(details, (list, tuple)) or not details: continue
- param_type = details[0]
- param_config = details[1] if len(details) > 1 and isinstance(details[1], dict) else {}
- param_info = {"name": name, "type": param_type, "config": param_config}
- params.append(param_info)
- if params: param_map[display_name] = params
- except Exception as e:
- print(f"⚠️ Could not parse parameters for {display_name}: {e}")
- PREPROCESSOR_PARAMETER_MAP = param_map
- print("✅ ControlNet Preprocessor parameter map built.")
+def ensure_sd3_ipadapter_models_downloaded(progress):
+ _PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+ yaml_path = os.path.join(_PROJECT_ROOT, 'yaml', 'ipadapter_sd3_models.yaml')
+ try:
+ with open(yaml_path, 'r', encoding='utf-8') as f:
+ sd3_models = yaml.safe_load(f)
+ if sd3_models:
+ if 'ipadapter' in sd3_models:
+ _ensure_model_downloaded(sd3_models['ipadapter'], progress)
+ if 'clip_vision' in sd3_models:
+ _ensure_model_downloaded(sd3_models['clip_vision'], progress)
+ except Exception as e:
+ print(f"Warning: Failed to load or download sd3 ipadapter models: {e}")
+
def print_welcome_message():
author_name = "RioShiina"
@@ -561,4 +542,24 @@ def print_welcome_message():
f"{border}\n"
)
- print(message)
\ No newline at end of file
+ print(message)
+
+def get_model_generation_defaults(model_display_name: str, model_type: str, defaults_config: dict):
+ final_defaults = {
+ 'steps': 25, 'cfg': 7.0, 'sampler_name': 'euler', 'scheduler': 'simple',
+ 'positive_prompt': '', 'negative_prompt': ''
+ }
+
+ if 'Default' in defaults_config:
+ final_defaults.update(defaults_config['Default'])
+
+ model_type_key = next((key for key in defaults_config if key.lower().replace(" ", "-").replace(".", "") == model_type.lower()), None)
+ if model_type_key:
+ model_type_config = defaults_config[model_type_key]
+ if '_defaults' in model_type_config:
+ final_defaults.update(model_type_config['_defaults'])
+
+ if model_display_name in model_type_config:
+ final_defaults.update(model_type_config[model_display_name])
+
+ return final_defaults
\ No newline at end of file
diff --git a/yaml/constants.yaml b/yaml/constants.yaml
index 8a5eaefd0feb43a9af23efb01608e1512ca1830f..91e988ac66bece15f1265a47e2e11eddff9320b9 100644
--- a/yaml/constants.yaml
+++ b/yaml/constants.yaml
@@ -3,9 +3,114 @@ MAX_CONTROLNETS: 5
MAX_IPADAPTERS: 5
MAX_EMBEDDINGS: 5
MAX_CONDITIONINGS: 10
+MAX_REFERENCE_LATENTS: 10
LORA_SOURCE_CHOICES: ["Civitai", "File"]
RESOLUTION_MAP:
+ ernie-image:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ flux2:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ flux2-kv:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ qwen-image:
+ "1:1 (Square)": [1328, 1328]
+ "16:9 (Landscape)": [1664, 928]
+ "9:16 (Portrait)": [928, 1664]
+ "4:3 (Classic)": [1472, 1104]
+ "3:4 (Classic Portrait)": [1104, 1472]
+ "3:2 (Photography)": [1536, 1024]
+ "2:3 (Photography Portrait)": [1024, 1536]
+ longcat-image:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ anima:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ newbie-image:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ omnigen2:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ lumina:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ ovis-image:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ flux1:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ hidream:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ sd35:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
sdxl:
"1:1 (Square)": [1024, 1024]
"16:9 (Landscape)": [1344, 768]
@@ -13,4 +118,36 @@ RESOLUTION_MAP:
"4:3 (Classic)": [1152, 896]
"3:4 (Classic Portrait)": [896, 1152]
"3:2 (Photography)": [1216, 832]
- "2:3 (Photography Portrait)": [832, 1216]
\ No newline at end of file
+ "2:3 (Photography Portrait)": [832, 1216]
+ sd15:
+ "1:1 (Square)": [512, 512]
+ "16:9 (Landscape)": [896, 512]
+ "9:16 (Portrait)": [512, 896]
+ "4:3 (Classic Landscape)": [683, 512]
+ "3:4 (Classic Portrait)": [512, 683]
+ "3:2 (Landscape)": [768, 512]
+ "2:3 (Portrait)": [512, 768]
+ chroma1-radiance:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ chroma1:
+ "1:1 (Square)": [1024, 1024]
+ "16:9 (Landscape)": [1344, 768]
+ "9:16 (Portrait)": [768, 1344]
+ "4:3 (Classic)": [1152, 896]
+ "3:4 (Classic Portrait)": [896, 1152]
+ "3:2 (Photography)": [1216, 832]
+ "2:3 (Photography Portrait)": [832, 1216]
+ hunyuanimage:
+ "1:1 (Square)": [2048, 2048]
+ "16:9 (Landscape)": [2728, 1536]
+ "9:16 (Portrait)": [1536, 2728]
+ "4:3 (Classic)": [2368, 1776]
+ "3:4 (Classic Portrait)": [1776, 2368]
+ "3:2 (Photography)": [2504, 1672]
+ "2:3 (Photography Portrait)": [1672, 2504]
\ No newline at end of file
diff --git a/yaml/controlnet_models.yaml b/yaml/controlnet_models.yaml
index 625a447a646e46820e25001a3dab25219e297fd5..b3f668b7b52dc9b29623855c938b8939b9c5e94e 100644
--- a/yaml/controlnet_models.yaml
+++ b/yaml/controlnet_models.yaml
@@ -1,4 +1,31 @@
ControlNet:
+ Qwen-Image:
+ - Filepath: "Qwen-Image-InstantX-ControlNet-Union.safetensors"
+ Series: "InstantX Union"
+ Type: ["Canny", "Soft Edge", "Depth", "Pose"]
+ FLUX.1:
+ - Filepath: "FLUX.1-dev-ControlNet-Union-Pro-2.0.safetensors"
+ Series: "Shakker Labs Union Pro"
+ Type: ["Canny", "Tile", "Depth", "Blur", "Pose", "Gray", "Low Quality"]
+ - Filepath: "flux-canny-controlnet-v3.safetensors"
+ Series: "XLabs-AI"
+ Type: ["Canny"]
+ - Filepath: "flux-depth-controlnet-v3.safetensors"
+ Series: "XLabs-AI"
+ Type: ["Depth (Midas)"]
+ - Filepath: "flux-hed-controlnet-v3.safetensors"
+ Series: "XLabs-AI"
+ Type: ["HED"]
+ SD3.5:
+ - Filepath: "sd3.5_large_controlnet_blur.safetensors"
+ Series: "[Large] StabilityAI"
+ Type: ["Blur"]
+ - Filepath: "sd3.5_large_controlnet_canny.safetensors"
+ Series: "[Large] StabilityAI"
+ Type: ["Canny"]
+ - Filepath: "sd3.5_large_controlnet_depth.safetensors"
+ Series: "[Large] StabilityAI"
+ Type: ["Depth"]
SDXL:
- Filepath: "controlnet-union-sdxl-1.0_promax.safetensors"
Series: "xinsir Union"
@@ -104,4 +131,47 @@ ControlNet:
Type: ["Inpainting"]
- Filepath: "illustriousXLv1.1_tile_fp16.safetensors"
Series: "MIC-Lab/illustriousXLv1.1_controlnet"
- Type: ["Tile"]
\ No newline at end of file
+ Type: ["Tile"]
+ SD1.5:
+ - Filepath: "control_v11p_sd15_canny_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Canny"]
+ - Filepath: "control_v11f1p_sd15_depth_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Depth"]
+ - Filepath: "control_v11p_sd15_openpose_fp16.safetensors"
+ Series: "Standard"
+ Type: ["OpenPose"]
+ - Filepath: "control_v11p_sd15_lineart_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Lineart"]
+ - Filepath: "control_v11p_sd15_softedge_fp16.safetensors"
+ Series: "Standard"
+ Type: ["SoftEdge"]
+ - Filepath: "control_v11p_sd15_scribble_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Scribble"]
+ - Filepath: "control_v11p_sd15_seg_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Segmentation"]
+ - Filepath: "control_v11p_sd15_normalbae_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Normal BAE"]
+ - Filepath: "control_v11p_sd15_mlsd_fp16.safetensors"
+ Series: "Standard"
+ Type: ["MLSD"]
+ - Filepath: "control_v11p_sd15_inpaint_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Inpaint"]
+ - Filepath: "control_v11f1e_sd15_tile_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Tile"]
+ - Filepath: "control_v11e_sd15_shuffle_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Shuffle"]
+ - Filepath: "control_v11e_sd15_ip2p_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Instruct P2P"]
+ - Filepath: "control_v11p_sd15s2_lineart_anime_fp16.safetensors"
+ Series: "Standard"
+ Type: ["Anime Lineart"]
\ No newline at end of file
diff --git a/yaml/diffsynth_controlnet_models.yaml b/yaml/diffsynth_controlnet_models.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f8e4b06a57182748fdc067709eef1e1d2b7c8121
--- /dev/null
+++ b/yaml/diffsynth_controlnet_models.yaml
@@ -0,0 +1,8 @@
+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"]
\ No newline at end of file
diff --git a/yaml/file_list.yaml b/yaml/file_list.yaml
index f5d57af960062293298ad16b7614a9a5b9448cf8..b1e7a1e813189b663d11ba25c0e0ad2bf149c2e7 100644
--- a/yaml/file_list.yaml
+++ b/yaml/file_list.yaml
@@ -1,5 +1,81 @@
-file:
- checkpoints:
+file:
+ checkpoints:
+ # Lumina
+ - filename: "lumina_2.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Lumina_Image_2.0_Repackaged"
+ repository_file_path: "all_in_one/lumina_2.safetensors"
+ # SD3.5
+ - filename: "sd3.5_large_fp8_scaled.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/stable-diffusion-3.5-fp8"
+ repository_file_path: "sd3.5_large_fp8_scaled.safetensors"
+ - filename: "sd3.5_medium_incl_clips_t5xxlfp8scaled.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/stable-diffusion-3.5-fp8"
+ repository_file_path: "sd3.5_medium_incl_clips_t5xxlfp8scaled.safetensors"
+ # SDXL-NoobAI
+ - filename: "NoobAI-XL-Vpred-v1.0.safetensors"
+ source: hf
+ repo_id: "Laxhar/noobai-XL-Vpred-1.0"
+ repository_file_path: "NoobAI-XL-Vpred-v1.0.safetensors"
+ - filename: "NoobAI-XL-v1.1.safetensors"
+ source: hf
+ repo_id: "Laxhar/noobai-XL-1.1"
+ repository_file_path: "NoobAI-XL-v1.1.safetensors"
+ - filename: "noob_v_pencil-XL-v3.0.0.safetensors"
+ source: hf
+ repo_id: "bluepen5805/noob_v_pencil-XL"
+ repository_file_path: "noob_v_pencil-XL-v3.0.0.safetensors"
+ - filename: "Hikari_Noob_v-pred_1.2.4.safetensors"
+ source: hf
+ repo_id: "RedRayz/hikari_noob_v-pred_1.2.4"
+ repository_file_path: "Hikari_Noob_v-pred_1.2.4.safetensors"
+ - filename: "ChenkinNoob-XL-V0.5.safetensors"
+ source: hf
+ repo_id: "ChenkinNoob/ChenkinNoob-XL-V0.5"
+ repository_file_path: "ChenkinNoob-XL-V0.5.safetensors"
+ # SDXL-Illustrious
+ - filename: "waiIllustriousSDXL_v170.safetensors"
+ source: hf
+ repo_id: "zhenshipo/waiIllustriousSDXL_v170"
+ repository_file_path: "waiIllustriousSDXL_v170.safetensors"
+ - filename: "mellow_pencil-XL-v1.0.0.safetensors"
+ source: hf
+ repo_id: "bluepen5805/mellow_pencil-XL"
+ repository_file_path: "mellow_pencil-XL-v1.0.0.safetensors"
+ - filename: "illustrious_pencil-XL-v5.0.0.safetensors"
+ source: hf
+ repo_id: "bluepen5805/illustrious_pencil-XL"
+ repository_file_path: "illustrious_pencil-XL-v5.0.0.safetensors"
+ - filename: "hassakuXLIllustrious_v30.safetensors"
+ source: hf
+ repo_id: "misri/hassakuXLIllustrious_v30"
+ repository_file_path: "hassakuXLIllustrious_v30.safetensors"
+ - filename: "novaAnimeXL_ilV140.safetensors"
+ source: hf
+ repo_id: "frankjoshua/novaAnimeXL_ilV140"
+ repository_file_path: "novaAnimeXL_ilV140.safetensors"
+ - filename: "lemonsugarmix_v22.safetensors"
+ source: "civitai"
+ model_version_id: "2052748"
+ - filename: "Illustrious-XL-v2.0.safetensors"
+ source: hf
+ repo_id: "OnomaAIResearch/Illustrious-XL-v2.0"
+ repository_file_path: "Illustrious-XL-v2.0.safetensors"
+ - filename: "Illustrious-XL-v1.1.safetensors"
+ source: hf
+ repo_id: "OnomaAIResearch/Illustrious-XL-v1.1"
+ repository_file_path: "Illustrious-XL-v1.1.safetensors"
+ - filename: "Illustrious-XL-v1.0.safetensors"
+ source: hf
+ repo_id: "OnomaAIResearch/Illustrious-XL-v1.0"
+ repository_file_path: "Illustrious-XL-v1.0.safetensors"
+ - filename: "illustriousXL_v01.safetensors"
+ source: hf
+ repo_id: "AiAF/Illustrious-XL-v0.1.safetensors"
+ repository_file_path: "illustriousXL_v01.safetensors"
+ # SDXL-Animate
- filename: "animagine-xl-4.0.safetensors"
source: hf
repo_id: "cagliostrolab/animagine-xl-4.0"
@@ -20,19 +96,90 @@ file:
source: hf
repo_id: "bluepen5805/blue_pencil-XL"
repository_file_path: "blue_pencil-XL-v7.0.0.safetensors"
-
- clip_vision:
+ # SDXL-Pony
+ - filename: "ponyDiffusionV6XL_v6StartWithThisOne.safetensors"
+ source: hf
+ repo_id: "LyliaEngine/Pony_Diffusion_V6_XL"
+ repository_file_path: "ponyDiffusionV6XL_v6StartWithThisOne.safetensors"
+ - filename: "pony_pencil-XL-v2.0.0.safetensors"
+ source: hf
+ repo_id: "bluepen5805/pony_pencil-XL"
+ repository_file_path: "pony_pencil-XL-v2.0.0.safetensors"
+ - filename: "CyberRealisticPony_V14.0.safetensors"
+ source: hf
+ repo_id: "cyberdelia/CyberRealisticPony"
+ repository_file_path: "CyberRealisticPony_V14.0.safetensors"
+ # SDXL-Base
+ - filename: "sd_xl_base_1.0.safetensors"
+ source: "hf"
+ repo_id: "stabilityai/stable-diffusion-xl-base-1.0"
+ repository_file_path: "sd_xl_base_1.0.safetensors"
+ # SD1.5
+ - filename: "v1-5-pruned-emaonly.safetensors"
+ source: "hf"
+ repo_id: "stable-diffusion-v1-5/stable-diffusion-v1-5"
+ repository_file_path: "v1-5-pruned-emaonly.safetensors"
+ clip_vision:
+ # style_injector
+ - filename: "sigclip_vision_patch14_384.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/sigclip_vision_384"
+ repository_file_path: "sigclip_vision_patch14_384.safetensors"
+ # IPAdapter
+ - filename: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ source: "hf"
+ repo_id: "h94/IP-Adapter"
+ repository_file_path: "models/image_encoder/model.safetensors"
- filename: "CLIP-ViT-bigG-14-laion2B-39B-b160k.safetensors"
source: "hf"
repo_id: "h94/IP-Adapter"
repository_file_path: "sdxl_models/image_encoder/model.safetensors"
- - filename: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ # IPAdapter-SD3
+ - filename: "sigclip_vision_patch14_384.safetensors"
source: "hf"
- repo_id: "h94/IP-Adapter"
- repository_file_path: "models/image_encoder/model.safetensors"
-
- controlnet:
- # SDXL - xinsir
+ repo_id: "Comfy-Org/sigclip_vision_384"
+ repository_file_path: "sigclip_vision_patch14_384.safetensors"
+ controlnet:
+ # SD3.5
+ - filename: "sd3.5_large_controlnet_blur.safetensors"
+ source: "hf"
+ repo_id: "stabilityai/stable-diffusion-3.5-controlnets"
+ repository_file_path: "sd3.5_large_controlnet_blur.safetensors"
+ - filename: "sd3.5_large_controlnet_canny.safetensors"
+ source: "hf"
+ repo_id: "stabilityai/stable-diffusion-3.5-controlnets"
+ repository_file_path: "sd3.5_large_controlnet_canny.safetensors"
+ - filename: "sd3.5_large_controlnet_depth.safetensors"
+ source: "hf"
+ repo_id: "stabilityai/stable-diffusion-3.5-controlnets"
+ repository_file_path: "sd3.5_large_controlnet_depth.safetensors"
+ # Qwen-Image
+ - filename: "Qwen-Image-InstantX-ControlNet-Union.safetensors"
+ source: "hf"
+ repo_id: "InstantX/Qwen-Image-ControlNet-Union"
+ repository_file_path: "diffusion_pytorch_model.safetensors"
+ - filename: "Qwen-Image-InstantX-ControlNet-Inpainting.safetensors"
+ source: "hf"
+ repo_id: "InstantX/Qwen-Image-ControlNet-Inpainting"
+ repository_file_path: "diffusion_pytorch_model.safetensors"
+ # FLUX.1
+ - filename: "FLUX.1-dev-ControlNet-Union-Pro-2.0.safetensors"
+ source: "hf"
+ repo_id: "Shakker-Labs/FLUX.1-dev-ControlNet-Union-Pro-2.0"
+ repository_file_path: "diffusion_pytorch_model.safetensors"
+ - filename: "flux-canny-controlnet-v3.safetensors"
+ source: "hf"
+ repo_id: "XLabs-AI/flux-controlnet-collections"
+ repository_file_path: "flux-canny-controlnet-v3.safetensors"
+ - filename: "flux-depth-controlnet-v3.safetensors"
+ source: "hf"
+ repo_id: "XLabs-AI/flux-controlnet-collections"
+ repository_file_path: "flux-depth-controlnet-v3.safetensors"
+ - filename: "flux-hed-controlnet-v3.safetensors"
+ source: "hf"
+ repo_id: "XLabs-AI/flux-controlnet-collections"
+ repository_file_path: "flux-hed-controlnet-v3.safetensors"
+ # SDXL
- filename: "controlnet-union-sdxl-1.0_promax.safetensors"
source: "hf"
repo_id: "xinsir/controlnet-union-sdxl-1.0"
@@ -49,10 +196,6 @@ file:
source: "hf"
repo_id: "xinsir/controlnet-openpose-sdxl-1.0"
repository_file_path: "diffusion_pytorch_model.safetensors"
- - filename: "controlnet-openpose-sdxl-1.0.safetensors"
- source: "hf"
- repo_id: "xinsir/controlnet-openpose-sdxl-1.0_twins"
- repository_file_path: "diffusion_pytorch_model_twins.safetensors"
- filename: "controlnet-depth-sdxl-1.0.safetensors"
source: "hf"
repo_id: "xinsir/controlnet-depth-sdxl-1.0"
@@ -65,123 +208,255 @@ file:
source: "hf"
repo_id: "xinsir/anime-painter"
repository_file_path: "diffusion_pytorch_model.safetensors"
- # SDXL - NoobAI
- - filename: "noob_sdxl_controlnet_canny.fp16.safetensors"
+ # SD1.5
+ - filename: "control_v11e_sd15_ip2p_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11e_sd15_ip2p_fp16.safetensors"
+ - filename: "control_v11e_sd15_shuffle_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11e_sd15_shuffle_fp16.safetensors"
+ - filename: "control_v11f1e_sd15_tile_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11f1e_sd15_tile_fp16.safetensors"
+ - filename: "control_v11f1p_sd15_depth_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11f1p_sd15_depth_fp16.safetensors"
+ - filename: "control_v11p_sd15_canny_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_canny_fp16.safetensors"
+ - filename: "control_v11p_sd15_inpaint_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_inpaint_fp16.safetensors"
+ - filename: "control_v11p_sd15_lineart_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_lineart_fp16.safetensors"
+ - filename: "control_v11p_sd15_mlsd_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_mlsd_fp16.safetensors"
+ - filename: "control_v11p_sd15_normalbae_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_normalbae_fp16.safetensors"
+ - filename: "control_v11p_sd15_openpose_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_openpose_fp16.safetensors"
+ - filename: "control_v11p_sd15_scribble_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_scribble_fp16.safetensors"
+ - filename: "control_v11p_sd15_seg_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_seg_fp16.safetensors"
+ - filename: "control_v11p_sd15_softedge_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15_softedge_fp16.safetensors"
+ - filename: "control_v11p_sd15s2_lineart_anime_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11p_sd15s2_lineart_anime_fp16.safetensors"
+ - filename: "control_v11u_sd15_tile_fp16.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/ControlNet-v1-1_fp16_safetensors"
+ repository_file_path: "control_v11u_sd15_tile_fp16.safetensors"
+ diffusion_models:
+ # FLUX.2-klein-9B
+ - filename: "flux-2-klein-9b-fp8.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.2-klein-9b-fp8"
+ repository_file_path: "flux-2-klein-9b-fp8.safetensors"
+ # FLUX.2-klein-base-9B
+ - filename: "flux-2-klein-base-9b-fp8.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.2-klein-base-9b-fp8"
+ repository_file_path: "flux-2-klein-base-9b-fp8.safetensors"
+ # Anima
+ - filename: "anima-preview3-base.safetensors"
+ source: "hf"
+ repo_id: "circlestone-labs/Anima"
+ repository_file_path: "split_files/diffusion_models/anima-preview3-base.safetensors"
+ - filename: "AnimaYume_tuned_v04.safetensors"
+ source: "hf"
+ repo_id: "duongve/AnimaYume"
+ repository_file_path: "split_files/diffusion_models/AnimaYume_tuned_v04.safetensors"
+ # NewBie-Image
+ - filename: "NewBie-Image-Exp0.1-bf16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/NewBie-image-Exp0.1_repackaged"
+ repository_file_path: "split_files/diffusion_models/NewBie-Image-Exp0.1-bf16.safetensors"
+ # ERNIE-Image
+ - filename: "ernie-image.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/ERNIE-Image"
+ repository_file_path: "diffusion_models/ernie-image.safetensors"
+ - filename: "ernie-image-turbo.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/ERNIE-Image"
+ repository_file_path: "diffusion_models/ernie-image-turbo.safetensors"
+ # FLUX.2-klein-9B-KV
+ - filename: "flux-2-klein-9b-kv-fp8.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.2-klein-9b-kv-fp8"
+ repository_file_path: "flux-2-klein-9b-kv-fp8.safetensors"
+ # FLUX.2-klein-4B
+ - filename: "flux-2-klein-4b-fp8.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.2-klein-4b-fp8"
+ repository_file_path: "flux-2-klein-4b-fp8.safetensors"
+ # FLUX.2-klein-base-4B
+ - filename: "flux-2-klein-base-4b-fp8.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.2-klein-base-4b-fp8"
+ repository_file_path: "flux-2-klein-base-4b-fp8.safetensors"
+ # FLUX.2-klein-9B
+ - filename: "flux-2-klein-9b-fp8.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.2-klein-9b-fp8"
+ repository_file_path: "flux-2-klein-9b-fp8.safetensors"
+ # FLUX.2-klein-base-9B
+ - filename: "flux-2-klein-base-9b-fp8.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.2-klein-base-9b-fp8"
+ repository_file_path: "flux-2-klein-base-9b-fp8.safetensors"
+ # FLUX.2-dev
+ - filename: "flux2_dev_fp8mixed.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/flux2-dev"
+ repository_file_path: "split_files/diffusion_models/flux2_dev_fp8mixed.safetensors"
+ # LongCat-Image
+ - filename: "longcat_image_bf16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/LongCat-Image"
+ repository_file_path: "split_files/diffusion_models/longcat_image_bf16.safetensors"
+ # Ovis-Image
+ - filename: "ovis_image_bf16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Ovis-Image"
+ repository_file_path: "split_files/diffusion_models/ovis_image_bf16.safetensors"
+ # Z-Image
+ - filename: "z_image_turbo_bf16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/z_image_turbo"
+ repository_file_path: "split_files/diffusion_models/z_image_turbo_bf16.safetensors"
+ - filename: "z_image_bf16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/z_image"
+ repository_file_path: "split_files/diffusion_models/z_image_bf16.safetensors"
+ # Qwen-Image
+ - filename: "qwen_image_2512_fp8_e4m3fn.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Qwen-Image_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/qwen_image_2512_fp8_e4m3fn.safetensors"
+ - filename: "qwen_image_fp8_e4m3fn.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Qwen-Image_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/qwen_image_fp8_e4m3fn.safetensors"
+ # Flux.1
+ - filename: "flux1-dev-fp8-e4m3fn.safetensors"
+ source: "hf"
+ repo_id: "Kijai/flux-fp8"
+ repository_file_path: "flux1-dev-fp8-e4m3fn.safetensors"
+ - filename: "flux1-schnell-fp8-e4m3fn.safetensors"
+ source: "hf"
+ repo_id: "Kijai/flux-fp8"
+ repository_file_path: "flux1-schnell-fp8-e4m3fn.safetensors"
+ - filename: "flux1-dev-kontext_fp8_scaled.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/flux1-kontext-dev_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/flux1-dev-kontext_fp8_scaled.safetensors"
+ - filename: "flux1-krea-dev_fp8_scaled.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/FLUX.1-Krea-dev_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/flux1-krea-dev_fp8_scaled.safetensors"
+ # HiDream
+ - filename: "hidream_i1_dev_fp8.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HiDream-I1_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/hidream_i1_dev_fp8.safetensors"
+ - filename: "hidream_i1_fast_fp8.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HiDream-I1_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/hidream_i1_fast_fp8.safetensors"
+ - filename: "hidream_i1_full_fp8.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HiDream-I1_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/hidream_i1_full_fp8.safetensors"
+ - filename: "hunyuanimage2.1_fp8_e4m3fn.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HunyuanImage_2.1_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/hunyuanimage2.1_fp8_e4m3fn.safetensors"
+ - filename: "hunyuanimage2.1_distilled_fp8_e4m3fn.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HunyuanImage_2.1_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/hunyuanimage2.1_distilled_fp8_e4m3fn.safetensors"
+ - filename: "hunyuanimage2.1_refiner_fp8_e4m3fn.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HunyuanImage_2.1_ComfyUI"
+ repository_file_path: "split_files/diffusion_models/hunyuanimage2.1_refiner_fp8_e4m3fn.safetensors"
+ # Chroma1-Radiance
+ - filename: "Chroma1-Radiance-x0-fp8mixed_fullmm-20260104.safetensors"
+ source: "hf"
+ repo_id: "silveroxides/Chroma1-Radiance-fp8-scaled"
+ repository_file_path: "Chroma1-Radiance-x0-fp8mixed_fullmm-20260104.safetensors"
+ # Chroma1
+ - filename: "Chroma1-HD-Flash_float8_e4m3fn_scaled_learned_topk8_svd.safetensors"
+ source: "hf"
+ repo_id: "Clybius/Chroma-fp8-scaled"
+ repository_file_path: "Chroma1-HD/Chroma1-HD-Flash_float8_e4m3fn_scaled_learned_topk8_svd.safetensors"
+ - filename: "Chroma1-HD_float8_e4m3fn_scaled_learned_topk8_svd.safetensors"
+ source: "hf"
+ repo_id: "Clybius/Chroma-fp8-scaled"
+ repository_file_path: "Chroma1-HD/Chroma1-HD_float8_e4m3fn_scaled_learned_topk8_svd.safetensors"
+ - filename: "omnigen2_fp16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Omnigen2_ComfyUI_repackaged"
+ repository_file_path: "split_files/diffusion_models/omnigen2_fp16.safetensors"
+ ipadapter:
+ # SD3.5
+ - filename: "ip-adapter_sd35l_instantx.bin"
+ source: "hf"
+ repo_id: "InstantX/SD3.5-Large-IP-Adapter"
+ repository_file_path: "ip-adapter.bin"
+ # SD1.5
+ - filename: "ip-adapter_sd15.safetensors"
source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-canny"
- repository_file_path: "noob_sdxl_controlnet_canny.fp16.safetensors"
- - filename: "noob_sdxl_controlnet_depth.fp16.safetensors"
+ repo_id: "h94/IP-Adapter"
+ repository_file_path: "models/ip-adapter_sd15.safetensors"
+ - filename: "ip-adapter_sd15_light_v11.bin"
source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-depth"
- repository_file_path: "diffusion_pytorch_model.fp16.safetensors"
- - filename: "noob-sdxl-controlnet-lineart_anime.fp16.safetensors"
- source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-lineart_anime"
- repository_file_path: "diffusion_pytorch_model.fp16.safetensors"
- - filename: "noob-sdxl-controlnet-lineart_realistic.fp16.safetensors"
- source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-lineart_realistic"
- repository_file_path: "diffusion_pytorch_model.fp16.safetensors"
- - filename: "noob-sdxl-controlnet-manga_line.fp16.safetensors"
- source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-manga_line"
- repository_file_path: "diffusion_pytorch_model.fp16.safetensors"
- - filename: "noob-sdxl-controlnet-normal.fp16.safetensors"
- source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-normal"
- repository_file_path: "diffusion_pytorch_model.fp16.safetensors"
- - filename: "noob-sdxl-controlnet-softedge_hed.fp16.safetensors"
- source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-softedge_hed"
- repository_file_path: "diffusion_pytorch_model.fp16.safetensors"
- - filename: "noob-sdxl-controlnet-tile.fp16.safetensors"
- source: "hf"
- repo_id: "Eugeoter/noob-sdxl-controlnet-tile"
- repository_file_path: "diffusion_pytorch_model.fp16.safetensors"
- - filename: "NoobAI_Inpainting_ControlNet.safetensors"
- source: "hf"
- repo_id: "Wenaka/NoobAI_XL_Inpainting_ControlNet_Full"
- repository_file_path: "NoobAI_Inpainting_ControlNet.safetensors"
- - filename: "noob_openpose_pre.safetensors"
- source: "hf"
- repo_id: "Laxhar/noob_openpose"
- repository_file_path: "openpose_pre.safetensors"
- - filename: "noobaiXLControlnet_epsDepthMidasV11.safetensors"
- source: "hf"
- repo_id: "licyk/sd_control_collection"
- repository_file_path: "noobaiXLControlnet_epsDepthMidasV11.safetensors"
- - filename: "noobaiXLControlnet_epsNormalMidas.safetensors"
- source: "hf"
- repo_id: "licyk/sd_control_collection"
- repository_file_path: "noobaiXLControlnet_epsNormalMidas.safetensors"
- - filename: "noobaiXLControlnet_epsScribbleHed.safetensors"
- source: "hf"
- repo_id: "licyk/sd_control_collection"
- repository_file_path: "noobaiXLControlnet_epsScribbleHed.safetensors"
- - filename: "noobaiXLControlnet_epsScribblePidinet.safetensors"
- source: "hf"
- repo_id: "licyk/sd_control_collection"
- repository_file_path: "noobaiXLControlnet_epsScribblePidinet.safetensors"
- - filename: "noobaiXLControlnet_epsDepthMidas.safetensors"
- source: "hf"
- repo_id: "licyk/sd_control_collection"
- repository_file_path: "noobaiXLControlnet_epsDepthMidas.safetensors"
- - filename: "noobaiXLControlnet_openposeModel.safetensors"
- source: "hf"
- repo_id: "licyk/sd_control_collection"
- repository_file_path: "noobaiXLControlnet_openposeModel.safetensors"
- # SDXL - Illustrious-XL-v0.1
- - filename: "illustriousXLv0.1_Canny_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv0.1_controlnet"
- repository_file_path: "illustriousXLv0.1_Canny_fp16.safetensors"
- - filename: "illustriousXLv0.1_Lineart_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv0.1_controlnet"
- repository_file_path: "illustriousXLv0.1_Lineart_fp16.safetensors"
- - filename: "illustriousXLv0.1_Softedge_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv0.1_controlnet"
- repository_file_path: "illustriousXLv0.1_Softedge_fp16.safetensors"
- - filename: "illustriousXLv0.1_Tile_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv0.1_controlnet"
- repository_file_path: "illustriousXLv0.1_Tile_fp16.safetensors"
- - filename: "illustriousXLv0.1_depth_midas_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv0.1_controlnet"
- repository_file_path: "illustriousXLv0.1_depth_midas_fp16.safetensors"
- - filename: "illustriousXLv0.1_inpainting_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv0.1_controlnet"
- repository_file_path: "illustriousXLv0.1_inpainting_fp16.safetensors"
- # SDXL - Illustrious-XL-v1.1
- - filename: "illustriousXLv1.1_canny_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv1.1_controlnet"
- repository_file_path: "illustriousXLv1.1_canny_fp16.safetensors"
- - filename: "illustriousXLv1.1_depth_midas_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv1.1_controlnet"
- repository_file_path: "illustriousXLv1.1_depth_midas_fp16.safetensors"
- - filename: "illustriousXLv1.1_inpainting_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv1.1_controlnet"
- repository_file_path: "illustriousXLv1.1_inpainting_fp16.safetensors"
- - filename: "illustriousXLv1.1_tile_fp16.safetensors"
- source: "hf"
- repo_id: "MIC-Lab/illustriousXLv1.1_controlnet"
- repository_file_path: "illustriousXLv1.1_tile_fp16.safetensors"
-
- ipadapter:
- - filename: "ip-adapter_sdxl_vit-h.safetensors"
+ repo_id: "h94/IP-Adapter"
+ repository_file_path: "models/ip-adapter_sd15_light_v11.bin"
+ - filename: "ip-adapter-plus_sd15.safetensors"
source: "hf"
repo_id: "h94/IP-Adapter"
- repository_file_path: "sdxl_models/ip-adapter_sdxl_vit-h.safetensors"
- - filename: "ip-adapter_sdxl.safetensors"
+ repository_file_path: "models/ip-adapter-plus_sd15.safetensors"
+ - filename: "ip-adapter-plus-face_sd15.safetensors"
source: "hf"
repo_id: "h94/IP-Adapter"
- repository_file_path: "sdxl_models/ip-adapter_sdxl.safetensors"
+ repository_file_path: "models/ip-adapter-plus-face_sd15.safetensors"
+ - filename: "ip-adapter-full-face_sd15.safetensors"
+ source: "hf"
+ repo_id: "h94/IP-Adapter"
+ repository_file_path: "models/ip-adapter-full-face_sd15.safetensors"
+ - filename: "ip-adapter_sd15_vit-G.safetensors"
+ source: "hf"
+ repo_id: "h94/IP-Adapter"
+ repository_file_path: "models/ip-adapter_sd15_vit-G.safetensors"
+ # SDXL
+ - filename: "ip-adapter_sdxl_vit-h.safetensors"
+ source: "hf"
+ repo_id: "h94/IP-Adapter"
+ repository_file_path: "sdxl_models/ip-adapter_sdxl_vit-h.safetensors"
- filename: "ip-adapter-plus_sdxl_vit-h.safetensors"
source: "hf"
repo_id: "h94/IP-Adapter"
@@ -190,6 +465,22 @@ file:
source: "hf"
repo_id: "h94/IP-Adapter"
repository_file_path: "sdxl_models/ip-adapter-plus-face_sdxl_vit-h.safetensors"
+ - filename: "ip-adapter_sdxl.safetensors"
+ source: "hf"
+ repo_id: "h94/IP-Adapter"
+ repository_file_path: "sdxl_models/ip-adapter_sdxl.safetensors"
+ - filename: "ip-adapter-faceid_sd15.bin"
+ source: "hf"
+ repo_id: "h94/IP-Adapter-FaceID"
+ repository_file_path: "ip-adapter-faceid_sd15.bin"
+ - filename: "ip-adapter-faceid-plusv2_sd15.bin"
+ source: "hf"
+ repo_id: "h94/IP-Adapter-FaceID"
+ repository_file_path: "ip-adapter-faceid-plusv2_sd15.bin"
+ - filename: "ip-adapter-faceid-portrait-v11_sd15.bin"
+ source: "hf"
+ repo_id: "h94/IP-Adapter-FaceID"
+ repository_file_path: "ip-adapter-faceid-portrait-v11_sd15.bin"
- filename: "ip-adapter-faceid_sdxl.bin"
source: "hf"
repo_id: "h94/IP-Adapter-FaceID"
@@ -206,8 +497,36 @@ file:
source: "hf"
repo_id: "h94/IP-Adapter-FaceID"
repository_file_path: "ip-adapter-faceid-portrait_sdxl_unnorm.bin"
-
- loras:
+ ipadapter-flux:
+ - filename: "ip-adapter.bin"
+ source: "hf"
+ repo_id: "InstantX/FLUX.1-dev-IP-Adapter"
+ repository_file_path: "ip-adapter.bin"
+ style_models:
+ # FLUX.1-Redux-dev
+ - filename: "flux1-redux-dev.safetensors"
+ source: "hf"
+ repo_id: "black-forest-labs/FLUX.1-Redux-dev"
+ repository_file_path: "flux1-redux-dev.safetensors"
+ loras:
+ # Qwen-Image
+ - filename: "Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
+ source: "hf"
+ repo_id: "lightx2v/Qwen-Image-2512-Lightning"
+ repository_file_path: "Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
+ - filename: "Qwen-Image-fp8-e4m3fn-Lightning-4steps-V1.0-bf16.safetensors"
+ source: "hf"
+ repo_id: "lightx2v/Qwen-Image-Lightning"
+ repository_file_path: "Qwen-Image-fp8-e4m3fn-Lightning-4steps-V1.0-bf16.safetensors"
+ # SD1.5 FaceID
+ - filename: "ip-adapter-faceid_sd15_lora.safetensors"
+ source: "hf"
+ repo_id: "h94/IP-Adapter-FaceID"
+ repository_file_path: "ip-adapter-faceid_sd15_lora.safetensors"
+ - filename: "ip-adapter-faceid-plusv2_sd15_lora.safetensors"
+ source: "hf"
+ repo_id: "h94/IP-Adapter-FaceID"
+ repository_file_path: "ip-adapter-faceid-plusv2_sd15_lora.safetensors"
- filename: "ip-adapter-faceid_sdxl_lora.safetensors"
source: "hf"
repo_id: "h94/IP-Adapter-FaceID"
@@ -215,4 +534,112 @@ file:
- filename: "ip-adapter-faceid-plusv2_sdxl_lora.safetensors"
source: "hf"
repo_id: "h94/IP-Adapter-FaceID"
- repository_file_path: "ip-adapter-faceid-plusv2_sdxl_lora.safetensors"
\ No newline at end of file
+ repository_file_path: "ip-adapter-faceid-plusv2_sdxl_lora.safetensors"
+ model_patches:
+ # Z-Image
+ - filename: "Z-Image-Turbo-Fun-Controlnet-Union-2.1-8steps.safetensors"
+ source: "hf"
+ repo_id: "alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1"
+ repository_file_path: "Z-Image-Turbo-Fun-Controlnet-Union-2.1-8steps.safetensors"
+ - filename: "Z-Image-Turbo-Fun-Controlnet-Tile-2.1-8steps.safetensors"
+ 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"
+ text_encoders:
+ # Anima
+ - filename: "qwen_3_06b_base.safetensors"
+ source: "hf"
+ repo_id: "circlestone-labs/Anima"
+ repository_file_path: "split_files/text_encoders/qwen_3_06b_base.safetensors"
+ # NewBie-Image
+ - filename: "gemma_3_4b_it_bf16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/NewBie-image-Exp0.1_repackaged"
+ repository_file_path: "split_files/text_encoders/gemma_3_4b_it_bf16.safetensors"
+ - filename: "jina_clip_v2_bf16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/NewBie-image-Exp0.1_repackaged"
+ repository_file_path: "split_files/text_encoders/jina_clip_v2_bf16.safetensors"
+ # ERNIE-Image
+ - filename: "ministral-3-3b.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/ERNIE-Image"
+ repository_file_path: "text_encoders/ministral-3-3b.safetensors"
+ # FLUX.2-klein-4B & base
+ - filename: "qwen_3_4b.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/vae-text-encorder-for-flux-klein-4b"
+ repository_file_path: "split_files/text_encoders/qwen_3_4b.safetensors"
+ # FLUX.2-klein-9B & base
+ - filename: "qwen_3_8b_fp8mixed.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/vae-text-encorder-for-flux-klein-9b"
+ repository_file_path: "split_files/text_encoders/qwen_3_8b_fp8mixed.safetensors"
+ # FLUX.2-dev
+ - filename: "mistral_3_small_flux2_fp8.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/flux2-dev"
+ repository_file_path: "split_files/text_encoders/mistral_3_small_flux2_fp8.safetensors"
+ # Ovis-Image
+ - filename: "ovis_2.5.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Ovis-Image"
+ repository_file_path: "split_files/text_encoders/ovis_2.5.safetensors"
+ # Z-Image
+ - filename: "qwen_3_4b_fp8_mixed.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/z_image_turbo"
+ repository_file_path: "split_files/text_encoders/qwen_3_4b_fp8_mixed.safetensors"
+ - filename: "clip_l.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/flux_text_encoders"
+ repository_file_path: "clip_l.safetensors"
+ - filename: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ source: "hf"
+ repo_id: "comfyanonymous/flux_text_encoders"
+ repository_file_path: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ - filename: "clip_l_hidream.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HiDream-I1_ComfyUI"
+ repository_file_path: "split_files/text_encoders/clip_l_hidream.safetensors"
+ - filename: "clip_g_hidream.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HiDream-I1_ComfyUI"
+ repository_file_path: "split_files/text_encoders/clip_g_hidream.safetensors"
+ - filename: "llama_3.1_8b_instruct_fp8_scaled.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HiDream-I1_ComfyUI"
+ repository_file_path: "split_files/text_encoders/llama_3.1_8b_instruct_fp8_scaled.safetensors"
+ - filename: "qwen_2.5_vl_7b_fp8_scaled.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Qwen-Image_ComfyUI"
+ repository_file_path: "split_files/text_encoders/qwen_2.5_vl_7b_fp8_scaled.safetensors"
+ - filename: "byt5_small_glyphxl_fp16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HunyuanImage_2.1_ComfyUI"
+ repository_file_path: "split_files/text_encoders/byt5_small_glyphxl_fp16.safetensors"
+ - filename: "qwen_2.5_vl_fp16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Omnigen2_ComfyUI_repackaged"
+ repository_file_path: "split_files/text_encoders/qwen_2.5_vl_fp16.safetensors"
+ vae:
+ - filename: "qwen_image_vae.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Qwen-Image_ComfyUI"
+ repository_file_path: "split_files/vae/qwen_image_vae.safetensors"
+ - filename: "hunyuan_image_2.1_vae_fp16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HunyuanImage_2.1_ComfyUI"
+ repository_file_path: "split_files/vae/hunyuan_image_2.1_vae_fp16.safetensors"
+ - filename: "hunyuan_image_refiner_vae_fp16.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/HunyuanImage_2.1_ComfyUI"
+ repository_file_path: "split_files/vae/hunyuan_image_refiner_vae_fp16.safetensors"
+ - filename: "ae.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/Lumina_Image_2.0_Repackaged"
+ repository_file_path: "split_files/vae/ae.safetensors"
+ - filename: "flux2-vae.safetensors"
+ source: "hf"
+ repo_id: "Comfy-Org/flux2-dev"
+ repository_file_path: "split_files/vae/flux2-vae.safetensors"
\ No newline at end of file
diff --git a/yaml/image_gen_features.yaml b/yaml/image_gen_features.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..733507de35e081cddd9cf9ddf6803b5aaf746cc7
--- /dev/null
+++ b/yaml/image_gen_features.yaml
@@ -0,0 +1,117 @@
+default:
+ enabled_chains:
+ - lora
+ - controlnet
+ - ipadapter
+ - embedding
+ - style
+ - conditioning
+
+ernie-image:
+ enabled_chains:
+ - lora
+ - conditioning
+
+flux2:
+ enabled_chains:
+ - lora
+ - conditioning
+ - reference_latent
+
+flux2-kv:
+ enabled_chains:
+ - lora
+ - conditioning
+ - reference_latent
+
+z-image:
+ enabled_chains:
+ - lora
+ - conditioning
+ - controlnet_model_patch
+
+qwen-image:
+ enabled_chains:
+ - lora
+ - controlnet
+ - conditioning
+
+longcat-image:
+ enabled_chains:
+ - lora
+ - conditioning
+
+anima:
+ enabled_chains:
+ - lora
+ - conditioning
+
+newbie-image:
+ enabled_chains:
+ - lora
+ - embedding
+ - conditioning
+
+omnigen2:
+ enabled_chains:
+ - conditioning
+ - reference_latent
+
+lumina:
+ enabled_chains:
+ - lora
+ - embedding
+ - conditioning
+
+ovis-image:
+ enabled_chains:
+ - conditioning
+
+sd35:
+ enabled_chains:
+ - lora
+ - controlnet
+ - embedding
+ - conditioning
+ - sd3_ipadapter
+
+sdxl:
+ enabled_chains:
+ - lora
+ - controlnet
+ - ipadapter
+ - embedding
+ - conditioning
+
+sd15:
+ enabled_chains:
+ - lora
+ - controlnet
+ - ipadapter
+ - embedding
+ - conditioning
+
+flux1:
+ enabled_chains:
+ - lora
+ - controlnet
+ - style
+ - conditioning
+ - flux1_ipadapter
+
+hidream:
+ enabled_chains:
+ - lora
+ - conditioning
+
+chroma1:
+ enabled_chains:
+ - conditioning
+
+chroma1-radiance:
+ enabled_chains:
+ - conditioning
+
+hunyuanimage:
+ enabled_chains:
+ - conditioning
\ No newline at end of file
diff --git a/yaml/injectors.yaml b/yaml/injectors.yaml
index 5738a9bf22c33346847730c68f08bd0df0581f16..e3ff7780619ae60c86a7df3b388b694b676313be 100644
--- a/yaml/injectors.yaml
+++ b/yaml/injectors.yaml
@@ -1,15 +1,33 @@
injector_definitions:
dynamic_lora_chains:
module: "chain_injectors.lora_injector"
+ dynamic_newbie_lora_chains:
+ module: "chain_injectors.newbie_lora_injector"
dynamic_controlnet_chains:
module: "chain_injectors.controlnet_injector"
+ dynamic_diffsynth_controlnet_chains:
+ module: "chain_injectors.diffsynth_controlnet_injector"
dynamic_ipadapter_chains:
module: "chain_injectors.ipadapter_injector"
+ dynamic_flux1_ipadapter_chains:
+ module: "chain_injectors.flux1_ipadapter_injector"
+ dynamic_sd3_ipadapter_chains:
+ module: "chain_injectors.sd3_ipadapter_injector"
+ dynamic_style_chains:
+ module: "chain_injectors.style_injector"
dynamic_conditioning_chains:
module: "chain_injectors.conditioning_injector"
+ dynamic_reference_latent_chains:
+ module: "chain_injectors.reference_latent_injector"
injector_order:
- dynamic_lora_chains
+ - dynamic_newbie_lora_chains
+ - dynamic_diffsynth_controlnet_chains
- dynamic_ipadapter_chains
+ - dynamic_flux1_ipadapter_chains
+ - dynamic_sd3_ipadapter_chains
+ - dynamic_style_chains
- dynamic_conditioning_chains
+ - dynamic_reference_latent_chains
- dynamic_controlnet_chains
\ No newline at end of file
diff --git a/yaml/ipadapter.yaml b/yaml/ipadapter.yaml
index 38efaf66583de08a19b53b5eccdea511d9f43d66..6fed9eddbfcf91ed4b31a9b8550810cff9b20d40 100644
--- a/yaml/ipadapter.yaml
+++ b/yaml/ipadapter.yaml
@@ -1,33 +1,25 @@
-- preset_name: "STANDARD (medium strength)"
- vision_model: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
- ipadapter_model: "ip-adapter_sdxl_vit-h.safetensors"
+IPAdapter_presets:
+ SD1.5:
+ - "LIGHT - SD1.5 only (low strength)"
+ - "STANDARD (medium strength)"
+ - "VIT-G (medium strength)"
+ - "PLUS (high strength)"
+ - "PLUS FACE (portraits)"
+ - "FULL FACE - SD1.5 only (portraits stronger)"
+ SDXL:
+ - "STANDARD (medium strength)"
+ - "VIT-G (medium strength)"
+ - "PLUS (high strength)"
+ - "PLUS FACE (portraits)"
-- preset_name: "VIT-G (medium strength)"
- vision_model: "CLIP-ViT-bigG-14-laion2B-39B-b160k.safetensors"
- ipadapter_model: "ip-adapter_sdxl.safetensors"
-
-- preset_name: "PLUS (high strength)"
- vision_model: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
- ipadapter_model: "ip-adapter-plus_sdxl_vit-h.safetensors"
-
-- preset_name: "PLUS FACE (portraits)"
- vision_model: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
- ipadapter_model: "ip-adapter-plus-face_sdxl_vit-h.safetensors"
-
-- preset_name: "FACEID"
- vision_model: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
- ipadapter_model: "ip-adapter-faceid_sdxl.bin"
- lora_model: "ip-adapter-faceid_sdxl_lora.safetensors"
-
-- preset_name: "FACEID PLUS V2"
- vision_model: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
- ipadapter_model: "ip-adapter-faceid-plusv2_sdxl.bin"
- lora_model: "ip-adapter-faceid-plusv2_sdxl_lora.safetensors"
-
-- preset_name: "FACEID PORTRAIT (style transfer)"
- vision_model: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
- ipadapter_model: "ip-adapter-faceid-portrait_sdxl.bin"
-
-- preset_name: "FACEID PORTRAIT UNNORM - SDXL only (strong)"
- vision_model: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
- ipadapter_model: "ip-adapter-faceid-portrait_sdxl_unnorm.bin"
\ No newline at end of file
+IPAdapter_FaceID_presets:
+ SD1.5:
+ - "FACEID"
+ - "FACEID PLUS - SD1.5 only"
+ - "FACEID PLUS V2"
+ - "FACEID PORTRAIT (style transfer)"
+ SDXL:
+ - "FACEID"
+ - "FACEID PLUS V2"
+ - "FACEID PORTRAIT (style transfer)"
+ - "FACEID PORTRAIT UNNORM - SDXL only (strong)"
\ No newline at end of file
diff --git a/yaml/ipadapter_models.yaml b/yaml/ipadapter_models.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..f87d6b21c8415cce1ea8bbe3fabff36543d05fa1
--- /dev/null
+++ b/yaml/ipadapter_models.yaml
@@ -0,0 +1,55 @@
+- preset_name: "LIGHT - SD1.5 only (low strength)"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter_sd15_light_v11.bin"
+
+- preset_name: "STANDARD (medium strength)"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter_sdxl_vit-h.safetensors"
+ ipadapter: "ip-adapter_sd15.safetensors"
+
+- preset_name: "VIT-G (medium strength)"
+ clip_vision: "CLIP-ViT-bigG-14-laion2B-39B-b160k.safetensors"
+ ipadapter: "ip-adapter_sdxl.safetensors"
+ ipadapter: "ip-adapter_sd15_vit-G.safetensors"
+
+- preset_name: "PLUS (high strength)"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-plus_sdxl_vit-h.safetensors"
+ ipadapter: "ip-adapter-plus_sd15.safetensors"
+
+- preset_name: "PLUS FACE (portraits)"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-plus-face_sdxl_vit-h.safetensors"
+ ipadapter: "ip-adapter-plus-face_sd15.safetensors"
+
+- preset_name: "FULL FACE - SD1.5 only (portraits stronger)"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-full-face_sd15.safetensors"
+
+- preset_name: "FACEID"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-faceid_sdxl.bin"
+ loras: "ip-adapter-faceid_sdxl_lora.safetensors"
+ ipadapter: "ip-adapter-faceid_sd15.bin"
+ loras: "ip-adapter-faceid_sd15_lora.safetensors"
+
+- preset_name: "FACEID PLUS - SD1.5 only"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-faceid-plus_sd15.bin"
+ loras: "ip-adapter-faceid-plus_sd15_lora.safetensors"
+
+- preset_name: "FACEID PLUS V2"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-faceid-plusv2_sdxl.bin"
+ loras: "ip-adapter-faceid-plusv2_sdxl_lora.safetensors"
+ ipadapter: "ip-adapter-faceid-plusv2_sd15.bin"
+ loras: "ip-adapter-faceid-plusv2_sd15_lora.safetensors"
+
+- preset_name: "FACEID PORTRAIT (style transfer)"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-faceid-portrait_sdxl.bin"
+ ipadapter: "ip-adapter-faceid-portrait-v11_sd15.bin"
+
+- preset_name: "FACEID PORTRAIT UNNORM - SDXL only (strong)"
+ clip_vision: "CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors"
+ ipadapter: "ip-adapter-faceid-portrait_sdxl_unnorm.bin"
diff --git a/yaml/ipadapter_sd3_models.yaml b/yaml/ipadapter_sd3_models.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..2d80c4da70e9863b38863cdae6e9112a2fad246a
--- /dev/null
+++ b/yaml/ipadapter_sd3_models.yaml
@@ -0,0 +1,2 @@
+ipadapter: "ip-adapter_sd35l_instantx.bin"
+clip_vision: "sigclip_vision_patch14_384.safetensors"
\ No newline at end of file
diff --git a/yaml/model_architectures.yaml b/yaml/model_architectures.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..011b825f858e566a28855e1ef9185d271d70045f
--- /dev/null
+++ b/yaml/model_architectures.yaml
@@ -0,0 +1,79 @@
+architecture_order:
+ - "FLUX.2-KV"
+ - "FLUX.2"
+ - "ERNIE-Image"
+ - "Z-Image"
+ - "Qwen-Image"
+ - "LongCat-Image"
+ - "Anima"
+ - "NewBie-Image"
+ - "Ovis-Image"
+ - "HunyuanImage"
+ - "Chroma1-Radiance"
+ - "Chroma1"
+ - "OmniGen2"
+ - "Lumina"
+ - "HiDream"
+ - "FLUX.1"
+ - "SD3.5"
+ - "SDXL"
+ - "SD1.5"
+
+architectures:
+ "ERNIE-Image":
+ model_type: "ernie-image"
+ controlnet_key: "ERNIE-Image"
+ "FLUX.2-KV":
+ model_type: "flux2-kv"
+ controlnet_key: "FLUX.2"
+ "FLUX.2":
+ model_type: "flux2"
+ controlnet_key: "FLUX.2"
+ "Z-Image":
+ model_type: "z-image"
+ controlnet_key: "Z-Image"
+ "Qwen-Image":
+ model_type: "qwen-image"
+ controlnet_key: "Qwen-Image"
+ "LongCat-Image":
+ model_type: "longcat-image"
+ controlnet_key: "LongCat-Image"
+ "Anima":
+ model_type: "anima"
+ controlnet_key: "Anima"
+ "Chroma1-Radiance":
+ model_type: "chroma1-radiance"
+ controlnet_key: "Chroma1-Radiance"
+ "Chroma1":
+ model_type: "chroma1"
+ controlnet_key: "Chroma1"
+ "OmniGen2":
+ model_type: "omnigen2"
+ controlnet_key: "OmniGen2"
+ "Lumina":
+ model_type: "lumina"
+ controlnet_key: "Lumina"
+ "Ovis-Image":
+ model_type: "ovis-image"
+ controlnet_key: "Ovis-Image"
+ "HunyuanImage":
+ model_type: "hunyuanimage"
+ controlnet_key: "HunyuanImage"
+ "NewBie-Image":
+ model_type: "newbie-image"
+ controlnet_key: "NewBie-Image"
+ "FLUX.1":
+ model_type: "flux1"
+ controlnet_key: "FLUX.1"
+ "SDXL":
+ model_type: "sdxl"
+ controlnet_key: "SDXL"
+ "SD3.5":
+ model_type: "sd35"
+ controlnet_key: "SD3.5"
+ "HiDream":
+ model_type: "hidream"
+ controlnet_key: "HiDream"
+ "SD1.5":
+ model_type: "sd15"
+ controlnet_key: "SD1.5"
\ No newline at end of file
diff --git a/yaml/model_defaults.yaml b/yaml/model_defaults.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..3620a4b52629cd0a58d3e3edcf33550d0b35812d
--- /dev/null
+++ b/yaml/model_defaults.yaml
@@ -0,0 +1,206 @@
+Default:
+ steps: 25
+ cfg: 7.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ positive_prompt: ""
+ negative_prompt: ""
+
+ERNIE-Image:
+ _defaults:
+ steps: 20
+ cfg: 4.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ "baidu/ERNIE-Image-Turbo":
+ steps: 8
+ cfg: 1.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+
+FLUX.2:
+ _defaults:
+ steps: 20
+ cfg: 4.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ "black-forest-labs/FLUX.2-klein-4B":
+ steps: 4
+ cfg: 1.0
+ "black-forest-labs/FLUX.2-klein-9B":
+ steps: 4
+ cfg: 1.0
+
+FLUX.2-KV:
+ _defaults:
+ steps: 20
+ cfg: 4.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ "black-forest-labs/FLUX.2-klein-9B-KV":
+ steps: 4
+ cfg: 1.0
+
+Z-Image:
+ _defaults:
+ steps: 25
+ cfg: 4.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ "Tongyi-MAI/Z Image Turbo":
+ steps: 9
+ cfg: 1.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+
+Qwen-Image:
+ _defaults:
+ steps: 4
+ cfg: 1.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1763584
+
+LongCat-Image:
+ _defaults:
+ steps: 20
+ cfg: 4.0
+ guidance: 4.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+
+Anima:
+ _defaults:
+ steps: 30
+ cfg: 4.0
+ sampler_name: "er_sde"
+ scheduler: "simple"
+ total_pixels: 1048576
+ positive_prompt: "masterpiece, best quality, score_7, safe. "
+ negative_prompt: "worst quality, low quality, score_1, score_2, score_3, blurry, jpeg artifacts, sepia"
+
+NewBie-Image:
+ _defaults:
+ steps: 20
+ cfg: 5.5
+ sampler_name: "res_multistep"
+ scheduler: "simple"
+ positive_prompt: "You are an assistant designed to generate high-quality anime images with the highest degree of image-text alignment based on xml format textual prompts. "
+ negative_prompt: "You are an assistant designed to generate low-quality images based on textual prompts. "
+
+Ovis-Image:
+ _defaults:
+ steps: 20
+ cfg: 5.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+
+OmniGen2:
+ _defaults:
+ steps: 20
+ cfg: 5.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ positive_prompt: ""
+ negative_prompt: ""
+
+Chroma1:
+ _defaults:
+ steps: 30
+ cfg: 4.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ negative_prompt: "low quality, bad anatomy, extra digits, missing digits, extra limbs, missing limbs"
+ "lodestones/Chroma1-HD-Flash":
+ steps: 8
+ cfg: 1.0
+ scheduler: "beta"
+
+Chroma1-Radiance:
+ _defaults:
+ steps: 30
+ cfg: 4.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ negative_prompt: "low quality, bad anatomy, extra digits, missing digits, extra limbs, missing limbs, hands, fingers"
+
+SD3.5:
+ _defaults:
+ steps: 20
+ cfg: 4.0
+ sampler_name: "euler"
+ scheduler: "sgm_uniform"
+ total_pixels: 1048576
+
+SDXL:
+ _defaults:
+ steps: 25
+ cfg: 7.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ positive_prompt: ""
+ negative_prompt: ""
+
+SD1.5:
+ _defaults:
+ steps: 47
+ cfg: 7.0
+ sampler_name: "euler_ancestral"
+ scheduler: "simple"
+ total_pixels: 393216
+
+FLUX.1:
+ _defaults:
+ steps: 20
+ cfg: 1.0
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 1048576
+ "flux1-schnell":
+ steps: 4
+ cfg: 1.0
+ sampler_name: "euler"
+ scheduler: "simple"
+
+HiDream:
+ _defaults:
+ steps: 50
+ cfg: 3.0
+ sampler_name: "uni_pc"
+ scheduler: "simple"
+ total_pixels: 1048576
+ negative_prompt: "bad ugly jpeg artifacts"
+ "HiDream_i1_Dev":
+ steps: 28
+ cfg: 1.0
+ sampler_name: "lcm"
+ scheduler: "normal"
+ "HiDream_i1_Fast":
+ steps: 16
+ cfg: 1.0
+ sampler_name: "lcm"
+ scheduler: "normal"
+
+HunyuanImage:
+ _defaults:
+ steps: 20
+ cfg: 3.5
+ sampler_name: "euler"
+ scheduler: "simple"
+ total_pixels: 4194304
+ "HunyuanImage-2.1-Distilled":
+ steps: 8
+ cfg: 1.0
\ No newline at end of file
diff --git a/yaml/model_list.yaml b/yaml/model_list.yaml
index d34e772fc914e6805f33fc891da2dd45cd6a9112..47043561a7fd7a8006a90e8e0dfbeeb9cbb724a3 100644
--- a/yaml/model_list.yaml
+++ b/yaml/model_list.yaml
@@ -1,11 +1,305 @@
Checkpoint:
- - display_name: "CagliostroLab/Animagine XL 4.0"
- path: "animagine-xl-4.0.safetensors"
- - display_name: "CagliostroLab/Animagine XL 3.1"
- path: "animagine-xl-3.1.safetensors"
- - display_name: "blue_pen5805/4nima_pencil-XL v1.0.1"
- path: "4nima_pencil-XL-v1.0.1.safetensors"
- - display_name: "blue_pen5805/anima_pencil-XL v5.0.0"
- path: "anima_pencil-XL-v5.0.0.safetensors"
- - display_name: "blue_pen5805/blue_pencil-XL v7.0.0"
- path: "blue_pencil-XL-v7.0.0.safetensors"
\ No newline at end of file
+ FLUX.2-KV:
+ latent_type: flux2_latent
+ models:
+ - display_name: "black-forest-labs/FLUX.2-klein-9B-KV"
+ components:
+ unet: "flux-2-klein-9b-kv-fp8.safetensors"
+ clip: "qwen_3_8b_fp8mixed.safetensors"
+ vae: "flux2-vae.safetensors"
+ FLUX.2:
+ latent_type: flux2_latent
+ models:
+ - display_name: "black-forest-labs/FLUX.2-klein-4B"
+ components:
+ unet: "flux-2-klein-4b-fp8.safetensors"
+ clip: "qwen_3_4b.safetensors"
+ vae: "flux2-vae.safetensors"
+ - display_name: "black-forest-labs/FLUX.2-klein-9B"
+ components:
+ unet: "flux-2-klein-9b-fp8.safetensors"
+ clip: "qwen_3_8b_fp8mixed.safetensors"
+ vae: "flux2-vae.safetensors"
+ - display_name: "black-forest-labs/FLUX.2-klein-base-4B"
+ components:
+ unet: "flux-2-klein-base-4b-fp8.safetensors"
+ clip: "qwen_3_4b.safetensors"
+ vae: "flux2-vae.safetensors"
+ - display_name: "black-forest-labs/FLUX.2-klein-base-9B"
+ components:
+ unet: "flux-2-klein-base-9b-fp8.safetensors"
+ clip: "qwen_3_8b_fp8mixed.safetensors"
+ vae: "flux2-vae.safetensors"
+ - display_name: "black-forest-labs/FLUX.2-dev (Need to set ZeroGPU Duration to 120)"
+ components:
+ unet: "flux2_dev_fp8mixed.safetensors"
+ clip: "mistral_3_small_flux2_fp8.safetensors"
+ vae: "flux2-vae.safetensors"
+ ERNIE-Image:
+ latent_type: flux2_latent
+ models:
+ - display_name: "baidu/ERNIE-Image"
+ components:
+ unet: "ernie-image.safetensors"
+ vae: "flux2-vae.safetensors"
+ clip: "ministral-3-3b.safetensors"
+ - display_name: "baidu/ERNIE-Image-Turbo"
+ components:
+ unet: "ernie-image-turbo.safetensors"
+ vae: "flux2-vae.safetensors"
+ clip: "ministral-3-3b.safetensors"
+ Z-Image:
+ latent_type: sd3_latent
+ models:
+ - display_name: "Tongyi-MAI/Z Image Turbo"
+ components:
+ unet: "z_image_turbo_bf16.safetensors"
+ vae: "ae.safetensors"
+ clip: "qwen_3_4b_fp8_mixed.safetensors"
+ - display_name: "Tongyi-MAI/Z Image"
+ components:
+ unet: "z_image_bf16.safetensors"
+ vae: "ae.safetensors"
+ clip: "qwen_3_4b_fp8_mixed.safetensors"
+ Qwen-Image:
+ latent_type: sd3_latent
+ models:
+ - display_name: "Qwen/Qwen-Image-2512 + Lightning-4steps-V1.0 LoRA"
+ components:
+ unet: "qwen_image_2512_fp8_e4m3fn.safetensors"
+ vae: "qwen_image_vae.safetensors"
+ clip: "qwen_2.5_vl_7b_fp8_scaled.safetensors"
+ lora: "Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
+ - display_name: "Qwen/Qwen-Image + Lightning-4steps-V1.0 LoRA"
+ components:
+ unet: "qwen_image_fp8_e4m3fn.safetensors"
+ vae: "qwen_image_vae.safetensors"
+ clip: "qwen_2.5_vl_7b_fp8_scaled.safetensors"
+ lora: "Qwen-Image-fp8-e4m3fn-Lightning-4steps-V1.0-bf16.safetensors"
+ LongCat-Image:
+ latent_type: sd3_latent
+ models:
+ - display_name: "meituan-longcat/LongCat-Image"
+ components:
+ unet: "longcat_image_bf16.safetensors"
+ vae: "ae.safetensors"
+ clip: "qwen_2.5_vl_7b_fp8_scaled.safetensors"
+ Anima:
+ latent_type: latent
+ models:
+ - display_name: "duongve/AnimaYume-v0.4"
+ components:
+ unet: "AnimaYume_tuned_v04.safetensors"
+ vae: "qwen_image_vae.safetensors"
+ clip: "qwen_3_06b_base.safetensors"
+ - display_name: "circlestone-labs/Anima-preview3-base"
+ components:
+ unet: "anima-preview3-base.safetensors"
+ vae: "qwen_image_vae.safetensors"
+ clip: "qwen_3_06b_base.safetensors"
+ NewBie-Image:
+ latent_type: sd3_latent
+ models:
+ - display_name: "NewBie-AI/NewBie-image-Exp0.1"
+ components:
+ unet: "NewBie-Image-Exp0.1-bf16.safetensors"
+ vae: "ae.safetensors"
+ clip1: "gemma_3_4b_it_bf16.safetensors"
+ clip2: "jina_clip_v2_bf16.safetensors"
+ Ovis-Image:
+ latent_type: sd3_latent
+ models:
+ - display_name: "AIDC-AI/Ovis-Image"
+ components:
+ unet: "ovis_image_bf16.safetensors"
+ vae: "ae.safetensors"
+ clip: "ovis_2.5.safetensors"
+ HunyuanImage:
+ latent_type: hunyuan_latent
+ models:
+ - display_name: "HunyuanImage-2.1"
+ components:
+ unet: "hunyuanimage2.1_fp8_e4m3fn.safetensors"
+ vae: "hunyuan_image_2.1_vae_fp16.safetensors"
+ clip1: "qwen_2.5_vl_7b_fp8_scaled.safetensors"
+ clip2: "byt5_small_glyphxl_fp16.safetensors"
+ - display_name: "HunyuanImage-2.1-Distilled"
+ components:
+ unet: "hunyuanimage2.1_distilled_fp8_e4m3fn.safetensors"
+ vae: "hunyuan_image_2.1_vae_fp16.safetensors"
+ clip1: "qwen_2.5_vl_7b_fp8_scaled.safetensors"
+ clip2: "byt5_small_glyphxl_fp16.safetensors"
+ Chroma1-Radiance:
+ latent_type: chroma_radiance_latent
+ models:
+ - display_name: "lodestones/Chroma1-Radiance-x0"
+ components:
+ unet: "Chroma1-Radiance-x0-fp8mixed_fullmm-20260104.safetensors"
+ vae: "pixel_space"
+ clip: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ Chroma1:
+ latent_type: sd3_latent
+ models:
+ - display_name: "lodestones/Chroma1-HD"
+ components:
+ unet: "Chroma1-HD_float8_e4m3fn_scaled_learned_topk8_svd.safetensors"
+ vae: "ae.safetensors"
+ clip: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ - display_name: "lodestones/Chroma1-HD-Flash"
+ components:
+ unet: "Chroma1-HD-Flash_float8_e4m3fn_scaled_learned_topk8_svd.safetensors"
+ vae: "ae.safetensors"
+ clip: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ OmniGen2:
+ latent_type: sd3_latent
+ models:
+ - display_name: "OmniGen2"
+ components:
+ unet: "omnigen2_fp16.safetensors"
+ vae: "ae.safetensors"
+ clip: "qwen_2.5_vl_fp16.safetensors"
+ Lumina:
+ latent_type: sd3_latent
+ models:
+ - display_name: "Alpha-VLLM/Lumina-Image-2.0"
+ path: "lumina_2.safetensors"
+ HiDream:
+ latent_type: sd3_latent
+ models:
+ - display_name: "HiDream_i1_Dev"
+ components:
+ unet: "hidream_i1_dev_fp8.safetensors"
+ vae: "ae.safetensors"
+ clip1: "clip_l_hidream.safetensors"
+ clip2: "clip_g_hidream.safetensors"
+ clip3: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ clip4: "llama_3.1_8b_instruct_fp8_scaled.safetensors"
+ - display_name: "HiDream_i1_Full"
+ components:
+ unet: "hidream_i1_full_fp8.safetensors"
+ vae: "ae.safetensors"
+ clip1: "clip_l_hidream.safetensors"
+ clip2: "clip_g_hidream.safetensors"
+ clip3: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ clip4: "llama_3.1_8b_instruct_fp8_scaled.safetensors"
+ - display_name: "HiDream_i1_Fast"
+ components:
+ unet: "hidream_i1_fast_fp8.safetensors"
+ vae: "ae.safetensors"
+ clip1: "clip_l_hidream.safetensors"
+ clip2: "clip_g_hidream.safetensors"
+ clip3: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ clip4: "llama_3.1_8b_instruct_fp8_scaled.safetensors"
+ FLUX.1:
+ latent_type: sd3_latent
+ models:
+ - display_name: "flux1-dev"
+ components:
+ unet: "flux1-dev-fp8-e4m3fn.safetensors"
+ vae: "ae.safetensors"
+ clip1: "clip_l.safetensors"
+ clip2: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ - display_name: "flux1-schnell"
+ components:
+ unet: "flux1-schnell-fp8-e4m3fn.safetensors"
+ vae: "ae.safetensors"
+ clip1: "clip_l.safetensors"
+ clip2: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ - display_name: "flux1-krea-dev"
+ components:
+ unet: "flux1-krea-dev_fp8_scaled.safetensors"
+ vae: "ae.safetensors"
+ clip1: "clip_l.safetensors"
+ clip2: "t5xxl_fp8_e4m3fn_scaled.safetensors"
+ SD3.5:
+ latent_type: sd3_latent
+ models:
+ - display_name: "StabilityAI/SD3.5-Large"
+ path: "sd3.5_large_fp8_scaled.safetensors"
+ - display_name: "StabilityAI/SD3.5-Medium"
+ path: "sd3.5_medium_incl_clips_t5xxlfp8scaled.safetensors"
+ SDXL:
+ latent_type: latent
+ models:
+ # NoobAI
+ - display_name: "Laxhar/noobai-XL-Vpred-1.0"
+ path: "NoobAI-XL-Vpred-v1.0.safetensors"
+ category: "NoobAI"
+ - display_name: "Laxhar/noobai-XL-1.1"
+ path: "NoobAI-XL-v1.1.safetensors"
+ category: "NoobAI"
+ - display_name: "bluepen5805/noob_v_pencil-XL-3.0.0"
+ path: "noob_v_pencil-XL-v3.0.0.safetensors"
+ category: "NoobAI"
+ - display_name: "RedRayz/hikari_noob_v-pred_1.2.4"
+ path: "Hikari_Noob_v-pred_1.2.4.safetensors"
+ category: "NoobAI"
+ - display_name: "ChenkinNoob/ChenkinNoob-XL-V0.5"
+ path: "ChenkinNoob-XL-V0.5.safetensors"
+ category: "NoobAI"
+ # Illustrious
+ - display_name: "WAI0731/wai-illustrious-sdxl-v170"
+ path: "waiIllustriousSDXL_v170.safetensors"
+ category: "Illustrious"
+ - display_name: "blue_pen5805/mellow_pencil-XL-v1.0.0"
+ path: "mellow_pencil-XL-v1.0.0.safetensors"
+ category: "Illustrious"
+ - display_name: "blue_pen5805/illustrious_pencil-XL-v5.0.0"
+ path: "illustrious_pencil-XL-v5.0.0.safetensors"
+ category: "Illustrious"
+ - display_name: "Ikena/hassaku-xl-illustrious-v30"
+ path: "hassakuXLIllustrious_v30.safetensors"
+ category: "Illustrious"
+ - display_name: "Crody/Nova-Anime-XL-v14.0"
+ path: "novaAnimeXL_ilV140.safetensors"
+ category: "Illustrious"
+ - display_name: "oritatami_neko/LemonSugarMix v2.2"
+ path: "lemonsugarmix_v22.safetensors"
+ category: "Illustrious"
+ - display_name: "OnomaAIResearch/Illustrious-XL-v2.0"
+ path: "Illustrious-XL-v2.0.safetensors"
+ category: "Illustrious"
+ - display_name: "OnomaAIResearch/Illustrious-XL-v1.1"
+ path: "Illustrious-XL-v1.1.safetensors"
+ category: "Illustrious"
+ - display_name: "OnomaAIResearch/Illustrious-XL-v1.0"
+ path: "Illustrious-XL-v1.0.safetensors"
+ category: "Illustrious"
+ - display_name: "aria1th261/Illustrious-XL-v0.1"
+ path: "illustriousXL_v01.safetensors"
+ category: "Illustrious"
+ # SDXL-Animate
+ - display_name: "CagliostroLab/Animagine XL 4.0"
+ path: "animagine-xl-4.0.safetensors"
+ category: "Animate"
+ - display_name: "CagliostroLab/Animagine XL 3.1"
+ path: "animagine-xl-3.1.safetensors"
+ category: "Animate"
+ - display_name: "blue_pen5805/4nima_pencil-XL v1.0.1"
+ path: "4nima_pencil-XL-v1.0.1.safetensors"
+ category: "Animate"
+ - display_name: "blue_pen5805/anima_pencil-XL v5.0.0"
+ path: "anima_pencil-XL-v5.0.0.safetensors"
+ category: "Animate"
+ - display_name: "blue_pen5805/blue_pencil-XL v7.0.0"
+ path: "blue_pencil-XL-v7.0.0.safetensors"
+ category: "Animate"
+ # SDXL-Pony
+ - display_name: "PurpleSmartAI/Pony Diffusion V6 XL"
+ path: "ponyDiffusionV6XL_v6StartWithThisOne.safetensors"
+ category: "Pony"
+ - display_name: "blue_pen5805/pony_pencil-XL v2.0.0"
+ path: "pony_pencil-XL-v2.0.0.safetensors"
+ category: "Pony"
+ - display_name: "Cyberdelia/CyberRealistic Pony v14.0"
+ path: "CyberRealisticPony_V14.0.safetensors"
+ category: "Pony"
+ # SDXL-Base
+ - display_name: "stabilityai/stable-diffusion-xl-base-1.0"
+ path: "sd_xl_base_1.0.safetensors"
+ category: "Base"
+ SD1.5:
+ latent_type: latent
+ models:
+ - display_name: "stable-diffusion-v1-5/stable-diffusion-v1-5"
+ path: "v1-5-pruned-emaonly.safetensors"
\ No newline at end of file