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core/pipelines/pipeline_input_processor.py

@@ -42,6 +42,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
     ui_inputs['denoise'] = 1.0
     if task_type == 'img2img': ui_inputs['denoise'] = ui_inputs.get('img2img_denoise', 0.7)
     elif task_type == 'hires_fix': ui_inputs['denoise'] = ui_inputs.get('hires_denoise', 0.55)
+    elif task_type == 'inpaint': ui_inputs['denoise'] = ui_inputs.get('inpaint_denoise', 1.0)
     
     if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
 
@@ -331,4 +332,4 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
         "active_hidream_o1_reference": active_hidream_o1_reference,
         "active_conditioning": active_conditioning,
         "temp_files_to_clean": temp_files_to_clean
-    }
+    }

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

@@ -13,12 +13,6 @@ nodes:
     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"
@@ -27,8 +21,6 @@ nodes:
 
 connections:
   - from: "unet_loader:0"
-    to: "lora_loader:model"
-  - from: "lora_loader:0"
     to: "model_sampler:model"
 
   - from: "model_sampler:0"
@@ -53,7 +45,7 @@ dynamic_lora_chains:
   lora_chain:
     template: "LoraLoader"
     output_map:
-      "lora_loader:0": "model"
+      "unet_loader:0": "model"
       "clip_loader:0": "clip"
     input_map:
       "model": "model"
@@ -80,5 +72,4 @@ dynamic_pid_chains:
 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"
+  clip_name: "clip_loader:clip_name"

ui/events/change_handlers.py

@@ -16,7 +16,7 @@ from .config_loaders import (
     load_ipadapter_config
 )
 
-def make_update_fn(m_comp, cat_comp, cs_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None):
+def make_update_fn(m_comp, cat_comp, cs_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None):
     def update_fn(*args):
         arch = args[0]
         category = args[1]
@@ -67,6 +67,7 @@ def make_update_fn(m_comp, cat_comp, cs_comp, ar_comp, width_comp, height_comp,
         if ref_latent_acc: updates[ref_latent_acc] = gr.update(visible=('reference_latent' in enabled_chains))
         if hidream_o1_ref_acc: updates[hidream_o1_ref_acc] = gr.update(visible=('hidream_o1_reference' in enabled_chains))
         if pid_acc: updates[pid_acc] = gr.update(visible=('pid' in enabled_chains))
+        if vae_acc: updates[vae_acc] = gr.update(visible=('vae' in enabled_chains))
 
         if cs_comp:
             updates[cs_comp] = gr.update(visible=(arch_model_type == "sd15"))
@@ -131,7 +132,7 @@ def make_update_fn(m_comp, cat_comp, cs_comp, ar_comp, width_comp, height_comp,
     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, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, arch_comp_ref, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None):
+def make_model_change_fn(cat_comp_ref, cs_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, arch_comp_ref, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None):
     def change_fn(*args):
         model_name = args[0]
         idx = 1
@@ -187,6 +188,7 @@ def make_model_change_fn(cat_comp_ref, cs_comp, ar_comp, width_comp, height_comp
         if ref_latent_acc: updates[ref_latent_acc] = gr.update(visible=('reference_latent' in enabled_chains))
         if hidream_o1_ref_acc: updates[hidream_o1_ref_acc] = gr.update(visible=('hidream_o1_reference' in enabled_chains))
         if pid_acc: updates[pid_acc] = gr.update(visible=('pid' in enabled_chains))
+        if vae_acc: updates[vae_acc] = gr.update(visible=('vae' in enabled_chains))
 
         if cs_comp:
             updates[cs_comp] = gr.update(visible=(arch_model_type == "sd15"))

ui/events/main.py

@@ -61,6 +61,7 @@ def attach_event_handlers(ui_components, demo):
         ref_latent_accordion = ui_components.get(f'reference_latent_accordion_{prefix}')
         hidream_o1_ref_accordion = ui_components.get(f'hidream_o1_reference_accordion_{prefix}')
         pid_accordion = ui_components.get(f'pid_accordion_{prefix}')
+        vae_accordion = ui_components.get(f'vae_accordion_{prefix}')
         
         ipa_preset_list = ui_components.get(f'ipadapter_final_preset_{prefix}')
         
@@ -95,6 +96,7 @@ def attach_event_handlers(ui_components, demo):
             if ref_latent_accordion: outputs.append(ref_latent_accordion)
             if hidream_o1_ref_accordion: outputs.append(hidream_o1_ref_accordion)
             if pid_accordion: outputs.append(pid_accordion)
+            if vae_accordion: outputs.append(vae_accordion)
             if ipa_preset_list: outputs.append(ipa_preset_list)
             
             outputs.extend(valid_extra_comps)
@@ -106,7 +108,7 @@ def attach_event_handlers(ui_components, demo):
                 diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list, 
                 ipa_preset_list, lora_accordion, cn_accordion, anima_cn_accordion, diffsynth_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
                 ref_latent_accordion, hidream_o1_ref_accordion, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp,
-                pid_acc=pid_accordion
+                pid_acc=pid_accordion, vae_acc=vae_accordion
             )
             inputs = [arch_comp, cat_comp]
             if aspect_ratio_comp:
@@ -137,6 +139,7 @@ def attach_event_handlers(ui_components, demo):
             if ref_latent_accordion: outputs2.append(ref_latent_accordion)
             if hidream_o1_ref_accordion: outputs2.append(hidream_o1_ref_accordion)
             if pid_accordion: outputs2.append(pid_accordion)
+            if vae_accordion: outputs2.append(vae_accordion)
             if ipa_preset_list: outputs2.append(ipa_preset_list)
             
             outputs2.extend(valid_extra_comps)
@@ -153,7 +156,7 @@ def attach_event_handlers(ui_components, demo):
                     diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list, 
                     arch_comp, ipa_preset_list, lora_accordion, cn_accordion, anima_cn_accordion, diffsynth_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
                     ref_latent_accordion, hidream_o1_ref_accordion, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp,
-                    pid_acc=pid_accordion
+                    pid_acc=pid_accordion, vae_acc=vae_accordion
                 )
                 model_comp.change(fn=change_fn, inputs=inputs2, outputs=outputs2)
 

ui/events/run_handlers.py

@@ -30,7 +30,7 @@ def create_run_event(prefix: str, task_type: str, ui_components: dict):
     
     task_specific_map = {
         'img2img': {'img2img_image': f'input_image_{prefix}', 'img2img_denoise': f'denoise_{prefix}'},
-        'inpaint': {'inpaint_image_dict': f'input_image_dict_{prefix}', 'grow_mask_by': f'grow_mask_by_{prefix}'},
+        'inpaint': {'inpaint_image_dict': f'input_image_dict_{prefix}', 'grow_mask_by': f'grow_mask_by_{prefix}', 'inpaint_denoise': f'denoise_{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}'}
     }

ui/shared/hires_fix_ui.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from core.settings import MODEL_MAP_CHECKPOINT
+from core.settings import MODEL_MAP_CHECKPOINT, MODEL_DEFAULTS_CONFIG
 from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
 from .ui_components import (
     create_lora_settings_ui,
@@ -10,6 +10,14 @@ from .ui_components import (
     create_reference_latent_ui, create_hidream_o1_reference_ui
 )
 
+default_vals = MODEL_DEFAULTS_CONFIG.get('Default', {})
+DEFAULT_STEPS = default_vals.get('steps', 20)
+DEFAULT_CFG = default_vals.get('cfg', 5.0)
+DEFAULT_SAMPLER = default_vals.get('sampler_name', 'euler')
+DEFAULT_SCHEDULER = default_vals.get('scheduler', 'simple')
+DEFAULT_POS_PROMPT = default_vals.get('positive_prompt', '')
+DEFAULT_NEG_PROMPT = default_vals.get('negative_prompt', '')
+
 def create_ui():
     prefix = "hires_fix"
     components = {}
@@ -33,8 +41,8 @@ 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)
-                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3)
+                components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3, value=DEFAULT_POS_PROMPT)
+                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3, value=DEFAULT_NEG_PROMPT)
 
         with gr.Row():
             with gr.Column(scale=1):
@@ -52,11 +60,19 @@ def create_ui():
                     components[f'denoise_{prefix}'] = gr.Slider(label="Denoise Strength", minimum=0.0, maximum=1.0, step=0.01, value=0.55)
                 
                 with gr.Row():
-                    components[f'sampler_{prefix}'] = gr.Dropdown(label="Sampler", choices=SAMPLER_CHOICES, value='er_sde' if 'er_sde' in SAMPLER_CHOICES else SAMPLER_CHOICES[0])
-                    components[f'scheduler_{prefix}'] = gr.Dropdown(label="Scheduler", choices=SCHEDULER_CHOICES, value='simple' if 'simple' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0])
+                    components[f'sampler_{prefix}'] = gr.Dropdown(
+                        label="Sampler", 
+                        choices=SAMPLER_CHOICES, 
+                        value=DEFAULT_SAMPLER if DEFAULT_SAMPLER in SAMPLER_CHOICES else (SAMPLER_CHOICES[0] if SAMPLER_CHOICES else 'euler')
+                    )
+                    components[f'scheduler_{prefix}'] = gr.Dropdown(
+                        label="Scheduler", 
+                        choices=SCHEDULER_CHOICES, 
+                        value=DEFAULT_SCHEDULER if DEFAULT_SCHEDULER in SCHEDULER_CHOICES else (SCHEDULER_CHOICES[0] if SCHEDULER_CHOICES else 'simple')
+                    )
                 with gr.Row():
-                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=30)
-                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=4.0)
+                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=DEFAULT_STEPS)
+                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=DEFAULT_CFG)
                 with gr.Row():
                     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)

ui/shared/img2img_ui.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from core.settings import MODEL_MAP_CHECKPOINT
+from core.settings import MODEL_MAP_CHECKPOINT, MODEL_DEFAULTS_CONFIG
 from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
 from .ui_components import (
     create_lora_settings_ui,
@@ -10,6 +10,14 @@ from .ui_components import (
     create_reference_latent_ui, create_hidream_o1_reference_ui
 )
 
+default_vals = MODEL_DEFAULTS_CONFIG.get('Default', {})
+DEFAULT_STEPS = default_vals.get('steps', 20)
+DEFAULT_CFG = default_vals.get('cfg', 5.0)
+DEFAULT_SAMPLER = default_vals.get('sampler_name', 'euler')
+DEFAULT_SCHEDULER = default_vals.get('scheduler', 'simple')
+DEFAULT_POS_PROMPT = default_vals.get('positive_prompt', '')
+DEFAULT_NEG_PROMPT = default_vals.get('negative_prompt', '')
+
 def create_ui():
     prefix = "img2img"
     components = {}
@@ -28,19 +36,27 @@ 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)
-                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3)
+                components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3, value=DEFAULT_POS_PROMPT)
+                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3, value=DEFAULT_NEG_PROMPT)
 
         with gr.Row():
             with gr.Column(scale=1):
                 components[f'denoise_{prefix}'] = gr.Slider(label="Denoise Strength", minimum=0.0, maximum=1.0, step=0.01, value=0.7)
                 
                 with gr.Row():
-                    components[f'sampler_{prefix}'] = gr.Dropdown(label="Sampler", choices=SAMPLER_CHOICES, value='er_sde' if 'er_sde' in SAMPLER_CHOICES else SAMPLER_CHOICES[0])
-                    components[f'scheduler_{prefix}'] = gr.Dropdown(label="Scheduler", choices=SCHEDULER_CHOICES, value='simple' if 'simple' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0])
+                    components[f'sampler_{prefix}'] = gr.Dropdown(
+                        label="Sampler", 
+                        choices=SAMPLER_CHOICES, 
+                        value=DEFAULT_SAMPLER if DEFAULT_SAMPLER in SAMPLER_CHOICES else (SAMPLER_CHOICES[0] if SAMPLER_CHOICES else 'euler')
+                    )
+                    components[f'scheduler_{prefix}'] = gr.Dropdown(
+                        label="Scheduler", 
+                        choices=SCHEDULER_CHOICES, 
+                        value=DEFAULT_SCHEDULER if DEFAULT_SCHEDULER in SCHEDULER_CHOICES else (SCHEDULER_CHOICES[0] if SCHEDULER_CHOICES else 'simple')
+                    )
                 with gr.Row():
-                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=30)
-                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=4.0)
+                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=DEFAULT_STEPS)
+                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=DEFAULT_CFG)
                 with gr.Row():
                     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)

ui/shared/inpaint_ui.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from core.settings import MODEL_MAP_CHECKPOINT
+from core.settings import MODEL_MAP_CHECKPOINT, MODEL_DEFAULTS_CONFIG
 from .ui_components import (
     create_base_parameter_ui, create_lora_settings_ui,
     create_controlnet_ui, create_anima_controlnet_lllite_ui, create_diffsynth_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
@@ -9,6 +9,14 @@ from .ui_components import (
     create_reference_latent_ui, create_hidream_o1_reference_ui
 )
 
+default_vals = MODEL_DEFAULTS_CONFIG.get('Default', {})
+DEFAULT_STEPS = default_vals.get('steps', 20)
+DEFAULT_CFG = default_vals.get('cfg', 5.0)
+DEFAULT_SAMPLER = default_vals.get('sampler_name', 'euler')
+DEFAULT_SCHEDULER = default_vals.get('scheduler', 'simple')
+DEFAULT_POS_PROMPT = default_vals.get('positive_prompt', '')
+DEFAULT_NEG_PROMPT = default_vals.get('negative_prompt', '')
+
 def create_ui():
     prefix = "inpaint"
     components = {}
@@ -47,8 +55,8 @@ 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)
-                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=6)
+                components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=6, value=DEFAULT_POS_PROMPT)
+                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=6, value=DEFAULT_NEG_PROMPT)
             components[f'prompts_column_{prefix}'] = prompts_column
 
         with gr.Row() as params_and_gallery_row:
@@ -62,11 +70,19 @@ def create_ui():
                         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='er_sde' if 'er_sde' in SAMPLER_CHOICES else SAMPLER_CHOICES[0])
-                    components[f'scheduler_{prefix}'] = gr.Dropdown(label="Scheduler", choices=SCHEDULER_CHOICES, value='simple' if 'simple' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0])
+                    components[f'sampler_{prefix}'] = gr.Dropdown(
+                        label="Sampler", 
+                        choices=SAMPLER_CHOICES, 
+                        value=DEFAULT_SAMPLER if DEFAULT_SAMPLER in SAMPLER_CHOICES else (SAMPLER_CHOICES[0] if SAMPLER_CHOICES else 'euler')
+                    )
+                    components[f'scheduler_{prefix}'] = gr.Dropdown(
+                        label="Scheduler", 
+                        choices=SCHEDULER_CHOICES, 
+                        value=DEFAULT_SCHEDULER if DEFAULT_SCHEDULER in SCHEDULER_CHOICES else (SCHEDULER_CHOICES[0] if SCHEDULER_CHOICES else 'simple')
+                    )
                 with gr.Row():
-                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=30)
-                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=4.0)
+                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=DEFAULT_STEPS)
+                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=DEFAULT_CFG)
                 with gr.Row():
                     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)

ui/shared/outpaint_ui.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from core.settings import MODEL_MAP_CHECKPOINT
+from core.settings import MODEL_MAP_CHECKPOINT, MODEL_DEFAULTS_CONFIG
 from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
 from .ui_components import (
     create_lora_settings_ui,
@@ -10,6 +10,14 @@ from .ui_components import (
     create_reference_latent_ui, create_hidream_o1_reference_ui
 )
 
+default_vals = MODEL_DEFAULTS_CONFIG.get('Default', {})
+DEFAULT_STEPS = default_vals.get('steps', 20)
+DEFAULT_CFG = default_vals.get('cfg', 5.0)
+DEFAULT_SAMPLER = default_vals.get('sampler_name', 'euler')
+DEFAULT_SCHEDULER = default_vals.get('scheduler', 'simple')
+DEFAULT_POS_PROMPT = default_vals.get('positive_prompt', '')
+DEFAULT_NEG_PROMPT = default_vals.get('negative_prompt', '')
+
 def create_ui():
     prefix = "outpaint"
     components = {}
@@ -33,8 +41,8 @@ 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)
-                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3)
+                components[f'prompt_{prefix}'] = gr.Text(label="Prompt", lines=3, value=DEFAULT_POS_PROMPT)
+                components[f'neg_prompt_{prefix}'] = gr.Text(label="Negative prompt", lines=3, value=DEFAULT_NEG_PROMPT)
 
         with gr.Row():
             with gr.Column(scale=1):
@@ -48,11 +56,19 @@ def create_ui():
                 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='er_sde' if 'er_sde' in SAMPLER_CHOICES else SAMPLER_CHOICES[0])
-                    components[f'scheduler_{prefix}'] = gr.Dropdown(label="Scheduler", choices=SCHEDULER_CHOICES, value='simple' if 'simple' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0])
+                    components[f'sampler_{prefix}'] = gr.Dropdown(
+                        label="Sampler", 
+                        choices=SAMPLER_CHOICES, 
+                        value=DEFAULT_SAMPLER if DEFAULT_SAMPLER in SAMPLER_CHOICES else (SAMPLER_CHOICES[0] if SAMPLER_CHOICES else 'euler')
+                    )
+                    components[f'scheduler_{prefix}'] = gr.Dropdown(
+                        label="Scheduler", 
+                        choices=SCHEDULER_CHOICES, 
+                        value=DEFAULT_SCHEDULER if DEFAULT_SCHEDULER in SCHEDULER_CHOICES else (SCHEDULER_CHOICES[0] if SCHEDULER_CHOICES else 'simple')
+                    )
                 with gr.Row():
-                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=30)
-                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=4.0)
+                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=DEFAULT_STEPS)
+                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=DEFAULT_CFG)
                 with gr.Row():
                     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)

ui/shared/ui_components.py

@@ -4,7 +4,7 @@ from core.settings import (
     MAX_LORAS, LORA_SOURCE_CHOICES, MAX_EMBEDDINGS, MAX_CONDITIONINGS,
     MAX_CONTROLNETS, MAX_IPADAPTERS, RESOLUTION_MAP, ARCHITECTURES_CONFIG,
     MODEL_MAP_CHECKPOINT, MODEL_TYPE_MAP, FEATURES_CONFIG, ARCH_CATEGORIES_MAP,
-    VAE_DIR
+    VAE_DIR, MODEL_DEFAULTS_CONFIG
 )
 import yaml
 import os
@@ -18,6 +18,13 @@ default_arch_model_type = default_architectures_dict.get(default_m_type, {}).get
 default_arch_features = FEATURES_CONFIG.get(default_arch_model_type, FEATURES_CONFIG.get('default', {}))
 default_enabled_chains = default_arch_features.get('enabled_chains', [])
 
+default_vals = MODEL_DEFAULTS_CONFIG.get('Default', {})
+DEFAULT_STEPS = default_vals.get('steps', 20)
+DEFAULT_CFG = default_vals.get('cfg', 5.0)
+DEFAULT_SAMPLER = default_vals.get('sampler_name', 'euler')
+DEFAULT_SCHEDULER = default_vals.get('scheduler', 'simple')
+DEFAULT_POS_PROMPT = default_vals.get('positive_prompt', '')
+DEFAULT_NEG_PROMPT = default_vals.get('negative_prompt', '')
 
 @lru_cache(maxsize=1)
 def get_ipadapter_config_from_yaml():
@@ -90,11 +97,19 @@ def create_base_parameter_ui(prefix, defaults=None):
         components[f'width_{prefix}'] = gr.Number(label="Width", value=defaults.get('w', 1024), interactive=True)
         components[f'height_{prefix}'] = gr.Number(label="Height", value=defaults.get('h', 1024), interactive=True)
     with gr.Row():
-        components[f'sampler_{prefix}'] = gr.Dropdown(label="Sampler", choices=SAMPLER_CHOICES, value='er_sde' if 'er_sde' in SAMPLER_CHOICES else SAMPLER_CHOICES[0])
-        components[f'scheduler_{prefix}'] = gr.Dropdown(label="Scheduler", choices=SCHEDULER_CHOICES, value='simple' if 'simple' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0])
+        components[f'sampler_{prefix}'] = gr.Dropdown(
+            label="Sampler", 
+            choices=SAMPLER_CHOICES, 
+            value=DEFAULT_SAMPLER if DEFAULT_SAMPLER in SAMPLER_CHOICES else (SAMPLER_CHOICES[0] if SAMPLER_CHOICES else 'euler')
+        )
+        components[f'scheduler_{prefix}'] = gr.Dropdown(
+            label="Scheduler", 
+            choices=SCHEDULER_CHOICES, 
+            value=DEFAULT_SCHEDULER if DEFAULT_SCHEDULER in SCHEDULER_CHOICES else (SCHEDULER_CHOICES[0] if SCHEDULER_CHOICES else 'simple')
+        )
     with gr.Row():
-                    components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=30)
-                    components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=4.0)
+        components[f'steps_{prefix}'] = gr.Slider(label="Steps", minimum=1, maximum=100, step=1, value=DEFAULT_STEPS)
+        components[f'cfg_{prefix}'] = gr.Slider(label="CFG Scale", minimum=1.0, maximum=20.0, step=0.1, value=DEFAULT_CFG)
     with gr.Row():
         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)
@@ -548,7 +563,7 @@ def create_vae_override_ui(prefix: str):
     key = lambda name: f"{name}_{prefix}"
     source_choices = ["None"] + LORA_SOURCE_CHOICES
 
-    with gr.Accordion("VAE Settings (Override)", open=False) as vae_accordion:
+    with gr.Accordion("VAE Settings (Override)", open=False, visible=('vae' in default_enabled_chains)) as vae_accordion:
         components[key('vae_accordion')] = vae_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.")
         with gr.Row():

yaml/file_list.yaml

@@ -685,15 +685,6 @@ file:
       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"

yaml/model_defaults.yaml

@@ -1,10 +1,10 @@
 Default:
   steps: 20
   cfg: 5.0
-  sampler_name: "euler"
+  sampler_name: "er_sde"
   scheduler: "simple"
   positive_prompt: ""
-  negative_prompt: ""
+  negative_prompt: "low quality, worst quality, over-saturated, blurry, deformed, watermark"
 
 Ideogram-4:
   _defaults:
@@ -74,8 +74,8 @@ Z-Image:
 
 Qwen-Image:
   _defaults:
-    steps: 4
-    cfg: 1.0
+    steps: 20
+    cfg: 4.0
     sampler_name: "euler"
     scheduler: "simple"
 

yaml/model_list.yaml

@@ -94,18 +94,16 @@ Checkpoint:
   Qwen-Image:
     latent_type: sd3_latent
     models:
-      - display_name: "Qwen/Qwen-Image-2512 + Lightning-4steps-V1.0 LoRA"
+      - display_name: "Qwen-Image-2512"
         components:
           unet: "qwen_image_2512_fp8_e4m3fn.safetensors"
           vae: "qwen_image_vae.safetensors"
           clip: "qwen_2.5_vl_7b_nvfp4.safetensors"
-          lora: "Qwen-Image-2512-Lightning-4steps-V1.0-bf16.safetensors"
-      - display_name: "Qwen/Qwen-Image + Lightning-4steps-V1.0 LoRA"
+      - display_name: "Qwen-Image"
         components:
           unet: "qwen_image_fp8_e4m3fn.safetensors"
           vae: "qwen_image_vae.safetensors"
           clip: "qwen_2.5_vl_7b_nvfp4.safetensors"
-          lora: "Qwen-Image-fp8-e4m3fn-Lightning-4steps-V1.0-bf16.safetensors"
   LongCat-Image:
     latent_type: sd3_latent
     models: