Upgrade to Gradio 6

.gitignore

@@ -0,0 +1,15 @@
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Environments & IDE
+.env
+.venv/
+env/
+venv/
+.idea/
+.vscode/
+
+# Temporary files
+*.tmp
+*.temp

README.md

@@ -4,7 +4,6 @@ emoji: 🖼
 colorFrom: purple
 colorTo: red
 sdk: gradio
-sdk_version: "5.50.0"
 app_file: app.py
 python_version: 3.12
 short_description: Multi-task image generator with dynamic, chainable workflows

app.py

@@ -49,7 +49,7 @@ def dummy_gpu_for_startup():
     return "Startup check passed."
 
 
-def main():
+def create_app():
     from comfy_integration import setup as setup_comfyui
     from utils.app_utils import load_ipadapter_presets
     
@@ -80,7 +80,6 @@ def main():
     load_ipadapter_presets()
     print("--- ✅ IPAdapter setup complete. ---")
 
-
     print("--- Environment configured. Proceeding with module imports. ---")
     from ui.layout import build_ui
     from ui.events import attach_event_handlers
@@ -90,10 +89,10 @@ def main():
     print(f"✅ Working directory is stable: {os.getcwd()}")
 
     demo = build_ui(attach_event_handlers)
+    return demo
 
-    print("--- Launching Gradio Interface ---")
-    demo.queue().launch(mcp_server=True)
-
+demo = create_app()
 
 if __name__ == "__main__":
-    main()
+    print("--- Launching Gradio Interface ---")
+    demo.queue().launch(mcp_server=True, footer_links=["api", "gradio", "settings"])

core/pipelines/pipeline_input_processor.py

@@ -5,7 +5,10 @@ import gradio as gr
 from PIL import Image, ImageChops
 from typing import Dict, Any, List
 
-from core.settings import INPUT_DIR, MULTIPLIERS_MAP, LORA_DIR, EMBEDDING_DIR, VAE_DIR
+from core.settings import (
+    INPUT_DIR, MULTIPLIERS_MAP, LORA_DIR, EMBEDDING_DIR, VAE_DIR,
+    FEATURES_CONFIG, TASK_FEATURES_CONFIG
+)
 from utils.app_utils import (
     sanitize_filename,
     get_lora_path,
@@ -21,6 +24,10 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
     task_type = ui_inputs['task_type']
     temp_files_to_clean = []
     
+    arch_enabled_chains = FEATURES_CONFIG.get(workflow_model_type, {}).get('enabled_chains', [])
+    task_enabled_chains = TASK_FEATURES_CONFIG.get(task_type, {}).get('enabled_chains', [])
+    enabled_chains = set([c for c in arch_enabled_chains if c in task_enabled_chains])
+    
     multiplier = MULTIPLIERS_MAP.get(workflow_model_type, 8)
     img_w, img_h = 0, 0
     if task_type == 'txt2img':
@@ -53,7 +60,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
     
     lora_data = ui_inputs.get('lora_data', [])
     active_loras_for_gpu, active_loras_for_meta = [], []
-    if lora_data:
+    if 'lora' in enabled_chains and 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():
@@ -145,7 +152,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     embedding_data = ui_inputs.get('embedding_data', [])
     embedding_filenames = []
-    if embedding_data:
+    if 'embedding' in enabled_chains and embedding_data:
         emb_sources, emb_ids, emb_files = embedding_data[0::3], embedding_data[1::3], embedding_data[2::3]
         for i, (source, emb_id, _) in enumerate(zip(emb_sources, emb_ids, emb_files)):
             if emb_id and emb_id.strip():
@@ -165,7 +172,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     controlnet_data = ui_inputs.get('controlnet_data', [])
     active_controlnets = []
-    if controlnet_data:
+    if 'controlnet' in enabled_chains and 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":
@@ -181,7 +188,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
     
     anima_controlnet_lllite_data = ui_inputs.get('anima_controlnet_lllite_data', [])
     active_anima_controlnets = []
-    if anima_controlnet_lllite_data:
+    if 'anima_controlnet_lllite' in enabled_chains and anima_controlnet_lllite_data:
         (cn_images, _, _, cn_strengths, cn_filepaths, cn_starts, cn_ends) = [anima_controlnet_lllite_data[i::7] for i in range(7)]
         for i in range(len(cn_images)):
             if cn_images[i] and cn_strengths[i] > 0 and cn_filepaths[i] and cn_filepaths[i] != "None":
@@ -197,7 +204,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     diffsynth_controlnet_data = ui_inputs.get('diffsynth_controlnet_data', [])
     active_diffsynth_controlnets = []
-    if diffsynth_controlnet_data:
+    if 'diffsynth_controlnet' in enabled_chains and diffsynth_controlnet_data:
         (cn_images, _, _, cn_strengths, cn_filepaths) = [diffsynth_controlnet_data[i::5] for i in range(5)]
         for i in range(len(cn_images)):
             if cn_images[i] and cn_strengths[i] > 0 and cn_filepaths[i] and cn_filepaths[i] != "None":
@@ -213,7 +220,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
                 
     krea2_controlnet_data = ui_inputs.get('krea2_controlnet_data', [])
     active_krea2_controlnets = []
-    if krea2_controlnet_data:
+    if 'krea2_controlnet' in enabled_chains and krea2_controlnet_data:
         (cn_images, _, _, cn_strengths, cn_filepaths) = [krea2_controlnet_data[i::5] for i in range(5)]
         for i in range(len(cn_images)):
             if cn_images[i] and cn_strengths[i] > 0 and cn_filepaths[i] and cn_filepaths[i] != "None":
@@ -229,7 +236,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
     
     ipadapter_data = ui_inputs.get('ipadapter_data', [])
     active_ipadapters = []
-    if ipadapter_data:
+    if 'ipadapter' in enabled_chains and ipadapter_data:
         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)]
@@ -260,7 +267,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
             
     flux1_ipadapter_data = ui_inputs.get('flux1_ipadapter_data', [])
     active_flux1_ipadapters = []
-    if flux1_ipadapter_data:
+    if 'flux1_ipadapter' in enabled_chains and 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]
@@ -289,7 +296,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
                 
     sd3_ipadapter_data = ui_inputs.get('sd3_ipadapter_chain', [])
     active_sd3_ipadapters = []
-    if sd3_ipadapter_data:
+    if 'sd3_ipadapter' in enabled_chains and 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]
@@ -311,7 +318,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
                 
     style_data = ui_inputs.get('style_data', [])
     active_styles = []
-    if style_data:
+    if 'style' in enabled_chains and 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]
@@ -331,7 +338,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
             
     reference_latent_data = ui_inputs.get('reference_latent_data', [])
     active_reference_latents = []
-    if reference_latent_data:
+    if 'reference_latent' in enabled_chains and reference_latent_data:
         for img in reference_latent_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -342,7 +349,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
                 
     hidream_o1_reference_data = ui_inputs.get('hidream_o1_reference_data', [])
     active_hidream_o1_reference = []
-    if hidream_o1_reference_data:
+    if 'hidream_o1_reference' in enabled_chains and hidream_o1_reference_data:
         for img in hidream_o1_reference_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -353,7 +360,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
             
     joyai_reference_data = ui_inputs.get('joyai_reference_data', [])
     active_joyai_reference = []
-    if joyai_reference_data:
+    if 'joyai_image' in enabled_chains and joyai_reference_data:
         for img in joyai_reference_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -364,7 +371,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     krea2_identity_edit_data = ui_inputs.get('krea2_identity_edit_data', [])
     active_krea2_identity_edit = []
-    if krea2_identity_edit_data:
+    if 'krea2_identity_edit' in enabled_chains and krea2_identity_edit_data:
         for img in krea2_identity_edit_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -375,7 +382,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     krea2_reference_edit_data = ui_inputs.get('krea2_reference_edit_data', [])
     active_krea2_reference_edit = []
-    if krea2_reference_edit_data:
+    if 'krea2_style_reference' in enabled_chains and krea2_reference_edit_data:
         for img in krea2_reference_edit_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -386,7 +393,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     qwen_image_edit_data = ui_inputs.get('qwen_image_edit_data', [])
     active_qwen_image_edit = []
-    if qwen_image_edit_data:
+    if 'qwen_image_edit' in enabled_chains and qwen_image_edit_data:
         for img in qwen_image_edit_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -397,7 +404,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     boogu_edit_data = ui_inputs.get('boogu_edit_data', [])
     active_boogu_edit = []
-    if boogu_edit_data:
+    if 'boogu_image_edit' in enabled_chains and boogu_edit_data:
         for img in boogu_edit_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -408,7 +415,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     reference_image_data = ui_inputs.get('reference_image_data', [])
     active_reference_images = []
-    if reference_image_data:
+    if 'reference_image' in enabled_chains and reference_image_data:
         for img in reference_image_data:
             if img:
                 if not os.path.exists(INPUT_DIR): os.makedirs(INPUT_DIR)
@@ -420,7 +427,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
     vae_source = ui_inputs.get('vae_source')
     vae_id = ui_inputs.get('vae_id')
     vae_name_override = None
-    if vae_source and vae_source != "None":
+    if 'vae' in enabled_chains and vae_source and vae_source != "None":
         if vae_source == "File":
             vae_name_override = sanitize_filename(vae_id)
             local_path = os.path.join(VAE_DIR, vae_name_override)
@@ -435,7 +442,7 @@ def process_pipeline_inputs(ui_inputs: Dict[str, Any], progress: gr.Progress, wo
 
     conditioning_data = ui_inputs.get('conditioning_data', [])
     active_conditioning = []
-    if conditioning_data:
+    if 'conditioning' in enabled_chains and conditioning_data:
         num_units = len(conditioning_data) // 6
         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):

core/pipelines/sd_image_pipeline.py

@@ -70,7 +70,11 @@ class SdImagePipeline(BasePipeline):
 
         required_models = self.get_required_models(model_display_name=model_display_name)
 
-        is_pid_enabled = (ui_inputs.get('pid_settings', 'OFF') == 'ON' and task_type == 'txt2img')
+        arch_enabled_chains = FEATURES_CONFIG.get(workflow_model_type, {}).get('enabled_chains', [])
+        task_enabled_chains = TASK_FEATURES_CONFIG.get(task_type, {}).get('enabled_chains', [])
+        enabled_chains = set([c for c in arch_enabled_chains if c in task_enabled_chains])
+
+        is_pid_enabled = (ui_inputs.get('pid_settings', 'OFF') == 'ON' and 'pid' in enabled_chains and task_type == 'txt2img')
         if is_pid_enabled:
             import yaml
             pid_config_path = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))), 'yaml', 'pid.yaml')
@@ -149,7 +153,7 @@ class SdImagePipeline(BasePipeline):
             assembler = WorkflowAssembler(recipe_path, dynamic_values=dynamic_values)
             
             hidream_o1_smoothing_data = []
-            if workflow_model_type == 'hidream-o1' and model_display_name == "HiDream-O1-Image":
+            if 'hidream_o1_smoothing' in enabled_chains and model_display_name == "HiDream-O1-Image":
                 hidream_o1_smoothing_data.append({})
 
             workflow_inputs = {
@@ -159,8 +163,7 @@ class SdImagePipeline(BasePipeline):
                 "sampler_name": ui_inputs['sampler'], "scheduler": ui_inputs['scheduler'],
                 "batch_size": ui_inputs['batch_size'],
                 "denoise": ui_inputs['denoise'],
-                "vae_name": ui_inputs.get('vae_name'),
-                "guidance": ui_inputs.get('guidance', 3.5),
+                "vae_name": ui_inputs.get('vae_name') if 'vae' in enabled_chains else None,
                 "lora_chain": active_loras_for_gpu,
                 "controlnet_chain": active_controlnets if not active_anima_controlnets else [],
                 "anima_controlnet_lllite_chain": active_anima_controlnets,
@@ -179,7 +182,7 @@ class SdImagePipeline(BasePipeline):
                 "qwen_image_edit_chain": active_qwen_image_edit,
                 "boogu_image_edit_chain": active_boogu_edit,
                 "reference_image_chain": active_reference_images,
-                "vae_chain": [ui_inputs.get('vae_name')] if ui_inputs.get('vae_name') else [],
+                "vae_chain": [ui_inputs.get('vae_name')] if (ui_inputs.get('vae_name') and 'vae' in enabled_chains) else [],
                 "hidream_o1_smoothing_chain": hidream_o1_smoothing_data,
                 "pid_chain": [ui_inputs.get('pid_settings', 'OFF')] if is_pid_enabled else [],
                 "scheduler_width": ui_inputs.get('width', 1024),

core/pipelines/workflow_recipes/_partials/conditioning/flux1.yaml

@@ -22,6 +22,8 @@ nodes:
   flux_guidance:
     class_type: FluxGuidance
     title: "FluxGuidance"
+    params:
+      guidance: 3.5
 
 connections:
   - from: "unet_loader:0"
@@ -72,5 +74,4 @@ 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"
+  clip2_name: "clip_loader:clip_name2"

core/settings.py

@@ -38,7 +38,8 @@ _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_ARCH_FEATURES_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_architecture_features.yaml')
+_TASK_FEATURES_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'task_features.yaml')
 _MODEL_DEFAULTS_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'model_defaults.yaml')
 
 def load_constants_from_yaml(filepath=_CONSTANTS_PATH):
@@ -55,13 +56,20 @@ def load_architectures_config(filepath=_MODEL_ARCHITECTURES_PATH):
     with open(filepath, 'r', encoding='utf-8') as f:
         return yaml.safe_load(f)
 
-def load_features_config(filepath=_IMAGE_GEN_FEATURES_PATH):
+def load_features_config(filepath=_MODEL_ARCH_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_task_features_config(filepath=_TASK_FEATURES_PATH):
+    if not os.path.exists(filepath):
+        print(f"Warning: Task 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}.")
@@ -195,6 +203,7 @@ try:
     MULTIPLIERS_MAP = _constants.get('MULTIPLIERS_MAP', {})
     ARCHITECTURES_CONFIG = load_architectures_config()
     FEATURES_CONFIG = load_features_config()
+    TASK_FEATURES_CONFIG = load_task_features_config()
     MODEL_DEFAULTS_CONFIG = load_model_defaults()
 except Exception as e:
     print(f"FATAL: Could not load constants from YAML. Error: {e}")
@@ -204,4 +213,5 @@ except Exception as e:
     MULTIPLIERS_MAP = {}
     ARCHITECTURES_CONFIG = {}
     FEATURES_CONFIG = {}
+    TASK_FEATURES_CONFIG = {}
     MODEL_DEFAULTS_CONFIG = {}

mcp_tools/common.py

@@ -20,8 +20,9 @@ _YAML_DIR = os.path.join(_PROJECT_ROOT, "yaml")
 _MODEL_ARCHITECTURES_PATH = os.path.join(_YAML_DIR, "model_architectures.yaml")
 _MODEL_LIST_PATH = os.path.join(_YAML_DIR, "model_list.yaml")
 _MODEL_DEFAULTS_PATH = os.path.join(_YAML_DIR, "model_defaults.yaml")
-_IMAGE_GEN_FEATURES_PATH = os.path.join(_YAML_DIR, "image_gen_features.yaml")
+_IMAGE_GEN_FEATURES_PATH = os.path.join(_YAML_DIR, "model_architecture_features.yaml")
 _CHAIN_FEATURES_PATH = os.path.join(_YAML_DIR, "chain_features.yaml")
+_TASK_FEATURES_PATH = os.path.join(_YAML_DIR, "task_features.yaml")
 _CONSTANTS_PATH = os.path.join(_YAML_DIR, "constants.yaml")
 
 

mcp_tools/get_feature_list.py

@@ -1,6 +1,6 @@
 import os
 from copy import deepcopy
-from .common import _load_yaml, _CHAIN_FEATURES_PATH, _YAML_DIR
+from .common import _load_yaml, _CHAIN_FEATURES_PATH, _TASK_FEATURES_PATH, _YAML_DIR
 from .error_schema import make_not_found_error
 
 
@@ -79,14 +79,35 @@ def _get_default_example_chain_item(chain_name: str, chain_data: dict) -> dict:
     return item
 
 
-def _build_feature_entry(chain_name: str, chain_data: dict, include_schema: bool = False) -> dict:
+def _get_supported_tasks_for_feature(chain_name: str, chain_data: dict, task_features: dict) -> list:
+    feat_chains = chain_data.get("chains", chain_name)
+    if isinstance(feat_chains, str):
+        target_chains = {feat_chains, chain_name}
+    elif isinstance(feat_chains, (list, tuple, set)):
+        target_chains = set(feat_chains) | {chain_name}
+    else:
+        target_chains = {chain_name}
+
+    supported = []
+    for task_name, task_data in task_features.items():
+        if not isinstance(task_data, dict):
+            continue
+        enabled_chains = task_data.get("enabled_chains", [])
+        if any(c in enabled_chains for c in target_chains):
+            supported.append(task_name)
+    return supported
+
+
+def _build_feature_entry(chain_name: str, chain_data: dict, task_features: dict = None, include_schema: bool = False) -> dict:
+    if task_features is None:
+        task_features = _load_yaml(_TASK_FEATURES_PATH)
     example_item = _get_default_example_chain_item(chain_name, chain_data)
     entry = {
         "feature_name": chain_name,
         "chains": chain_data.get("chains", chain_name),
         "display_name": chain_data.get("display_name", chain_name),
         "description": chain_data.get("description", ""),
-        "supported_tasks": chain_data.get("supported_tasks", []),
+        "supported_tasks": _get_supported_tasks_for_feature(chain_name, chain_data, task_features),
         "max_count": chain_data.get("max_count", 1),
         "usage_guideline": chain_data.get("usage_guideline", ""),
         "example_chain_item": example_item,
@@ -158,6 +179,7 @@ def handle_get_feature_list(feature_name: str | list[str] = "") -> list | dict:
       returns complete feature details INCLUDING parameters_schema for the requested feature(s).
     """
     chain_features = _load_yaml(_CHAIN_FEATURES_PATH)
+    task_features = _load_yaml(_TASK_FEATURES_PATH)
 
     targets = []
     is_single_string_query = False
@@ -174,7 +196,7 @@ def handle_get_feature_list(feature_name: str | list[str] = "") -> list | dict:
     # Case 1: Empty input -> return summary list of all features (without parameters_schema)
     if not targets:
         return [
-            _build_feature_entry(name, data, include_schema=False)
+            _build_feature_entry(name, data, task_features, include_schema=False)
             for name, data in chain_features.items()
         ]
 
@@ -200,7 +222,7 @@ def handle_get_feature_list(feature_name: str | list[str] = "") -> list | dict:
 
     # Case 3: Return full info including parameters_schema
     results = [
-        _build_feature_entry(target, chain_features[target], include_schema=True)
+        _build_feature_entry(target, chain_features[target], task_features, include_schema=True)
         for target in resolved_targets
     ]
 

mcp_tools/mcp_gradio_integration.py

@@ -56,6 +56,7 @@ def cleanup_dependencies_api_names(demo):
         api_name = getattr(fn, "api_name", None)
         if api_name not in HIGH_LEVEL_MCP_API_NAMES:
             fn.show_api = False
+            fn.api_name = False
 
     deps = getattr(demo, "dependencies", None)
     if deps is None and hasattr(demo, "config") and isinstance(demo.config, dict):
@@ -67,6 +68,7 @@ def cleanup_dependencies_api_names(demo):
                 api_name = dep.get("api_name")
                 if api_name not in HIGH_LEVEL_MCP_API_NAMES:
                     dep["show_api"] = False
+                    dep["api_name"] = False
 
     print("[MCP Protection] Cleaned up demo dependencies. Suppressed atomic API endpoints.")
 

requirements.txt

@@ -1,5 +1,5 @@
 comfyui-frontend-package==1.49.6
-comfyui-workflow-templates==0.11.41
+comfyui-workflow-templates==0.11.44
 comfyui-embedded-docs==0.5.10
 torch
 torchsde

ui/events/change_handlers.py

@@ -3,6 +3,7 @@ from core.settings import (
     MODEL_TYPE_MAP,
     MODEL_MAP_CHECKPOINT,
     FEATURES_CONFIG,
+    TASK_FEATURES_CONFIG,
     ARCHITECTURES_CONFIG,
     MODEL_DEFAULTS_CONFIG,
     ARCH_CATEGORIES_MAP
@@ -17,7 +18,7 @@ from .config_loaders import (
     load_ipadapter_config
 )
 
-def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, krea2_cn_types, krea2_cn_series, krea2_cn_filepaths, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, krea2_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, boogu_edit_acc=None, ref_img_acc=None):
+def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, krea2_cn_types, krea2_cn_series, krea2_cn_filepaths, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, krea2_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, boogu_edit_acc=None, ref_img_acc=None, task_type=None, type_comp=None):
     def update_fn(*args):
         arch = args[0]
         category = args[1]
@@ -53,7 +54,20 @@ def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types,
         arch_model_type = architectures_dict.get(m_type, {}).get("model_type", m_type.lower().replace(" ", "").replace(".", ""))
 
         arch_features = FEATURES_CONFIG.get(arch_model_type, {})
-        enabled_chains = arch_features.get('enabled_chains', [])
+        arch_enabled_chains = arch_features.get('enabled_chains', [])
+
+        # Determine current task type for task-level feature filtering
+        current_task = task_type  # static task_type for standalone prefixes
+        if type_comp is not None:
+            # unified imagegen: task type comes from extra arg
+            type_arg_idx = 3 if ar_comp else 2
+            if len(args) > type_arg_idx:
+                type_val = args[type_arg_idx]
+                type_map = {'Txt2Img': 'txt2img', 'Img2Img': 'img2img', 'Inpaint': 'inpaint', 'Outpaint': 'outpaint', 'Hires. Fix': 'hires_fix'}
+                current_task = type_map.get(type_val, 'txt2img')
+
+        task_enabled_chains = TASK_FEATURES_CONFIG.get(current_task, {}).get('enabled_chains', []) if current_task else arch_enabled_chains
+        enabled_chains = [c for c in arch_enabled_chains if c in task_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))
@@ -76,9 +90,6 @@ def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types,
         if ref_img_acc: updates[ref_img_acc] = gr.update(visible=('reference_image' 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 guidance_comp:
-            updates[guidance_comp] = gr.update(visible=(arch_model_type == "flux1"))
         
         if ar_comp:
             res_key = arch_model_type
@@ -146,7 +157,7 @@ def make_update_fn(m_comp, cat_comp, ar_comp, width_comp, height_comp, cn_types,
     return update_fn
 
 
-def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, krea2_cn_types, krea2_cn_series, krea2_cn_filepaths, arch_comp_ref, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, krea2_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, boogu_edit_acc=None, ref_img_acc=None):
+def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_cn_types, anima_cn_series, anima_cn_filepaths, diffsynth_cn_types, diffsynth_cn_series, diffsynth_cn_filepaths, krea2_cn_types, krea2_cn_series, krea2_cn_filepaths, arch_comp_ref, ipa_preset, lora_acc, cn_acc, anima_cn_acc, diffsynth_cn_acc, krea2_cn_acc, ipa_acc, sd3_ipa_acc, flux1_ipa_acc, style_acc, embed_acc, cond_acc, ref_latent_acc, hidream_o1_ref_acc, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=None, vae_acc=None, joyai_ref_acc=None, krea2_identity_edit_acc=None, krea2_reference_edit_acc=None, qwen_image_edit_acc=None, boogu_edit_acc=None, ref_img_acc=None, task_type=None, type_comp=None):
     def change_fn(*args):
         model_name = args[0]
         idx = 1
@@ -187,7 +198,23 @@ def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_type
         arch_model_type = architectures_dict.get(m_type, {}).get("model_type", m_type.lower().replace(" ", "").replace(".", ""))
 
         arch_features = FEATURES_CONFIG.get(arch_model_type, {})
-        enabled_chains = arch_features.get('enabled_chains', [])
+        arch_enabled_chains = arch_features.get('enabled_chains', [])
+
+        # Determine current task type for task-level feature filtering
+        current_task = task_type  # static task_type for standalone prefixes
+        if type_comp is not None:
+            # unified imagegen: task type comes from extra arg after model, arch, cat, ar
+            type_arg_idx = 1
+            if arch_comp_ref: type_arg_idx += 1
+            if cat_comp_ref: type_arg_idx += 1
+            if ar_comp: type_arg_idx += 1
+            if len(args) > type_arg_idx:
+                type_val = args[type_arg_idx]
+                type_map = {'Txt2Img': 'txt2img', 'Img2Img': 'img2img', 'Inpaint': 'inpaint', 'Outpaint': 'outpaint', 'Hires. Fix': 'hires_fix'}
+                current_task = type_map.get(type_val, 'txt2img')
+
+        task_enabled_chains = TASK_FEATURES_CONFIG.get(current_task, {}).get('enabled_chains', []) if current_task else arch_enabled_chains
+        enabled_chains = [c for c in arch_enabled_chains if c in task_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))
@@ -210,9 +237,6 @@ def make_model_change_fn(cat_comp_ref, ar_comp, width_comp, height_comp, cn_type
         if ref_img_acc: updates[ref_img_acc] = gr.update(visible=('reference_image' 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 guidance_comp:
-            updates[guidance_comp] = gr.update(visible=(arch_model_type == "flux1"))
         
         if ar_comp:
             res_key = arch_model_type
@@ -292,7 +316,7 @@ def initialize_all_cn_dropdowns(ui_components):
     krea2_all_types, krea2_default_type, krea2_series_choices, krea2_default_series, krea2_filepath = get_krea2_cn_defaults()
     
     updates = {}
-    for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
+    for prefix in ["imagegen", "txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
         if f'controlnet_types_{prefix}' in ui_components:
             for type_dd in ui_components[f'controlnet_types_{prefix}']:
                 updates[type_dd] = gr.update(choices=all_types, value=default_type)
@@ -348,7 +372,7 @@ def initialize_all_ipa_dropdowns(ui_components):
     lora_strength_update = gr.update(visible=is_faceid_default)
     
     updates = {}
-    for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
+    for prefix in ["imagegen", "txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
         if f'ipadapter_final_preset_{prefix}' in ui_components:
             for lora_strength_slider in ui_components[f'ipadapter_lora_strengths_{prefix}']:
                 updates[lora_strength_slider] = lora_strength_update

ui/events/main.py

@@ -29,15 +29,16 @@ from .change_handlers import (
 from .run_handlers import create_run_event
 
 def attach_event_handlers(ui_components, demo):
-    for prefix, task_type in [
-        ("txt2img", "txt2img"), ("img2img", "img2img"), ("inpaint", "inpaint"),
-        ("outpaint", "outpaint"), ("hires_fix", "hires_fix"),
-    ]:
+    prefixes = ["imagegen", "txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]
+    active_prefixes = [p for p in prefixes if f'base_model_{p}' in ui_components]
+
+    for prefix in active_prefixes:
+        task_type = prefix if prefix != "imagegen" else None
+        type_comp = ui_components.get(f'type_{prefix}')  # for unified imagegen UI
 
         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}')
-        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')
@@ -94,7 +95,6 @@ def attach_event_handlers(ui_components, demo):
         
         if arch_comp and cat_comp and model_comp:
             outputs = [model_comp, cat_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(anima_cn_types_list + anima_cn_series_list + anima_cn_filepaths_list)
@@ -132,12 +132,15 @@ def attach_event_handlers(ui_components, demo):
                 diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list, 
                 krea2_cn_types_list, krea2_cn_series_list, krea2_cn_filepaths_list,
                 ipa_preset_list, lora_accordion, cn_accordion, anima_cn_accordion, diffsynth_cn_accordion, krea2_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
-                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, vae_acc=vae_accordion, joyai_ref_acc=joyai_ref_accordion, krea2_identity_edit_acc=krea2_identity_edit_accordion, krea2_reference_edit_acc=krea2_reference_edit_accordion, qwen_image_edit_acc=qwen_image_edit_accordion, boogu_edit_acc=boogu_edit_accordion, ref_img_acc=ref_img_accordion
+                ref_latent_accordion, hidream_o1_ref_accordion, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp,
+                pid_acc=pid_accordion, vae_acc=vae_accordion, joyai_ref_acc=joyai_ref_accordion, krea2_identity_edit_acc=krea2_identity_edit_accordion, krea2_reference_edit_acc=krea2_reference_edit_accordion, qwen_image_edit_acc=qwen_image_edit_accordion, boogu_edit_acc=boogu_edit_accordion, ref_img_acc=ref_img_accordion,
+                task_type=task_type, type_comp=type_comp
             )
             inputs = [arch_comp, cat_comp]
             if aspect_ratio_comp:
                 inputs.append(aspect_ratio_comp)
+            if type_comp:
+                inputs.append(type_comp)
             arch_comp.change(fn=update_fn, inputs=inputs, outputs=outputs)
             cat_comp.change(fn=update_fn, inputs=inputs, outputs=outputs)
 
@@ -145,7 +148,6 @@ def attach_event_handlers(ui_components, demo):
             outputs2 = []
             if arch_comp: outputs2.append(arch_comp)
             if cat_comp: outputs2.append(cat_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(anima_cn_types_list + anima_cn_series_list + anima_cn_filepaths_list)
@@ -188,9 +190,12 @@ def attach_event_handlers(ui_components, demo):
                     diffsynth_cn_types_list, diffsynth_cn_series_list, diffsynth_cn_filepaths_list, 
                     krea2_cn_types_list, krea2_cn_series_list, krea2_cn_filepaths_list,
                     arch_comp, ipa_preset_list, lora_accordion, cn_accordion, anima_cn_accordion, diffsynth_cn_accordion, krea2_cn_accordion, ipa_accordion, sd3_ipa_accordion, flux1_ipa_accordion, style_accordion, embedding_accordion, conditioning_accordion,
-                    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, vae_acc=vae_accordion, joyai_ref_acc=joyai_ref_accordion, krea2_identity_edit_acc=krea2_identity_edit_accordion, krea2_reference_edit_acc=krea2_reference_edit_accordion, qwen_image_edit_acc=qwen_image_edit_accordion, boogu_edit_acc=boogu_edit_accordion, ref_img_acc=ref_img_accordion
+                    ref_latent_accordion, hidream_o1_ref_accordion, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp,
+                    pid_acc=pid_accordion, vae_acc=vae_accordion, joyai_ref_acc=joyai_ref_accordion, krea2_identity_edit_acc=krea2_identity_edit_accordion, krea2_reference_edit_acc=krea2_reference_edit_accordion, qwen_image_edit_acc=qwen_image_edit_accordion, boogu_edit_acc=boogu_edit_accordion, ref_img_acc=ref_img_accordion,
+                    task_type=task_type, type_comp=type_comp
                 )
+                if type_comp:
+                    inputs2.append(type_comp)
                 model_comp.change(fn=change_fn, inputs=inputs2, outputs=outputs2)
 
         create_lora_event_handlers(prefix, ui_components)
@@ -214,6 +219,164 @@ def attach_event_handlers(ui_components, demo):
         create_reference_image_event_handlers(prefix, ui_components)
         create_run_event(prefix, task_type, ui_components)
 
+    # Dynamic Type toggle event for unified imagegen UI
+    if 'type_imagegen' in ui_components:
+        def on_type_change(type_val, model_name):
+            from core.settings import MODEL_TYPE_MAP, FEATURES_CONFIG, TASK_FEATURES_CONFIG, ARCHITECTURES_CONFIG
+            is_txt2img = (type_val == "Txt2Img")
+            is_img2img = (type_val == "Img2Img")
+            is_inpaint = (type_val == "Inpaint")
+            is_outpaint = (type_val == "Outpaint")
+            is_hires_fix = (type_val == "Hires. Fix")
+            
+            denoise_val = 0.7 if is_img2img else (1.0 if is_inpaint else (0.55 if is_hires_fix else 0.7))
+            run_text = "Run Inpaint" if is_inpaint else ("Run Outpaint" if is_outpaint else ("Run Hires. Fix" if is_hires_fix else "Run"))
+            
+            prompt_lines = 6 if is_inpaint else 3
+            gallery_cols = 2 if is_txt2img else 1
+            gallery_height = 627 if is_txt2img else (505 if is_img2img else (510 if is_inpaint else (685 if is_outpaint else 610)))
+            
+            updates = {
+                ui_components['image_input_col_imagegen']: gr.update(visible=not is_txt2img),
+                ui_components['input_image_imagegen']: gr.update(visible=(is_img2img or is_outpaint or is_hires_fix)),
+                ui_components['inpaint_box_imagegen']: gr.update(visible=is_inpaint),
+                ui_components['prompt_imagegen']: gr.update(lines=prompt_lines),
+                ui_components['neg_prompt_imagegen']: gr.update(lines=prompt_lines),
+                ui_components['aspect_ratio_row_imagegen']: gr.update(visible=is_txt2img),
+                ui_components['width_height_row_imagegen']: gr.update(visible=is_txt2img),
+                ui_components['denoise_row_imagegen']: gr.update(visible=(is_img2img or is_inpaint or is_hires_fix)),
+                ui_components['denoise_imagegen']: gr.update(value=denoise_val),
+                ui_components['grow_mask_by_imagegen']: gr.update(visible=is_inpaint),
+                ui_components['outpaint_pads_col_imagegen']: gr.update(visible=is_outpaint),
+                ui_components['hires_upscaler_row_imagegen']: gr.update(visible=is_hires_fix),
+                ui_components['run_imagegen']: gr.update(value=run_text),
+                ui_components['result_imagegen']: gr.update(columns=gallery_cols, height=gallery_height),
+            }
+
+            # Re-evaluate feature accordion visibility based on task + architecture intersection
+            type_map = {'Txt2Img': 'txt2img', 'Img2Img': 'img2img', 'Inpaint': 'inpaint', 'Outpaint': 'outpaint', 'Hires. Fix': 'hires_fix'}
+            current_task = type_map.get(type_val, 'txt2img')
+            
+            m_type = MODEL_TYPE_MAP.get(model_name, "SDXL") if model_name 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_enabled_chains = FEATURES_CONFIG.get(arch_model_type, {}).get('enabled_chains', [])
+            task_enabled_chains = TASK_FEATURES_CONFIG.get(current_task, {}).get('enabled_chains', [])
+            enabled_chains = [c for c in arch_enabled_chains if c in task_enabled_chains]
+
+            prefix = 'imagegen'
+            accordion_chain_map = {
+                f'lora_accordion_{prefix}': 'lora',
+                f'controlnet_accordion_{prefix}': 'controlnet',
+                f'anima_controlnet_lllite_accordion_{prefix}': 'anima_controlnet_lllite',
+                f'diffsynth_controlnet_accordion_{prefix}': 'diffsynth_controlnet',
+                f'krea2_controlnet_accordion_{prefix}': 'krea2_controlnet',
+                f'ipadapter_accordion_{prefix}': 'ipadapter',
+                f'sd3_ipadapter_accordion_{prefix}': 'sd3_ipadapter',
+                f'flux1_ipadapter_accordion_{prefix}': 'flux1_ipadapter',
+                f'style_accordion_{prefix}': 'style',
+                f'embedding_accordion_{prefix}': 'embedding',
+                f'conditioning_accordion_{prefix}': 'conditioning',
+                f'reference_latent_accordion_{prefix}': 'reference_latent',
+                f'hidream_o1_reference_accordion_{prefix}': 'hidream_o1_reference',
+                f'joyai_reference_accordion_{prefix}': 'joyai_image',
+                f'krea2_identity_edit_accordion_{prefix}': 'krea2_identity_edit',
+                f'krea2_reference_edit_accordion_{prefix}': 'krea2_style_reference',
+                f'qwen_image_edit_accordion_{prefix}': 'qwen_image_edit',
+                f'boogu_edit_accordion_{prefix}': 'boogu_image_edit',
+                f'reference_image_accordion_{prefix}': 'reference_image',
+                f'pid_accordion_{prefix}': 'pid',
+                f'vae_accordion_{prefix}': 'vae',
+            }
+            for comp_key, chain_name in accordion_chain_map.items():
+                comp = ui_components.get(comp_key)
+                if comp:
+                    updates[comp] = gr.update(visible=(chain_name in enabled_chains))
+
+            return updates
+
+        type_change_outputs = [
+            ui_components['image_input_col_imagegen'],
+            ui_components['input_image_imagegen'],
+            ui_components['inpaint_box_imagegen'],
+            ui_components['prompt_imagegen'],
+            ui_components['neg_prompt_imagegen'],
+            ui_components['aspect_ratio_row_imagegen'],
+            ui_components['width_height_row_imagegen'],
+            ui_components['denoise_row_imagegen'],
+            ui_components['denoise_imagegen'],
+            ui_components['grow_mask_by_imagegen'],
+            ui_components['outpaint_pads_col_imagegen'],
+            ui_components['hires_upscaler_row_imagegen'],
+            ui_components['run_imagegen'],
+            ui_components['result_imagegen'],
+        ]
+        # Add feature accordion outputs for task-based visibility
+        accordion_keys = [
+            'lora_accordion_imagegen', 'controlnet_accordion_imagegen',
+            'anima_controlnet_lllite_accordion_imagegen', 'diffsynth_controlnet_accordion_imagegen',
+            'krea2_controlnet_accordion_imagegen', 'ipadapter_accordion_imagegen',
+            'sd3_ipadapter_accordion_imagegen', 'flux1_ipadapter_accordion_imagegen',
+            'style_accordion_imagegen', 'embedding_accordion_imagegen',
+            'conditioning_accordion_imagegen', 'reference_latent_accordion_imagegen',
+            'hidream_o1_reference_accordion_imagegen', 'joyai_reference_accordion_imagegen',
+            'krea2_identity_edit_accordion_imagegen', 'krea2_reference_edit_accordion_imagegen',
+            'qwen_image_edit_accordion_imagegen', 'boogu_edit_accordion_imagegen',
+            'reference_image_accordion_imagegen', 'pid_accordion_imagegen', 'vae_accordion_imagegen',
+        ]
+        for key in accordion_keys:
+            if key in ui_components:
+                type_change_outputs.append(ui_components[key])
+        ui_components['type_imagegen'].change(
+            fn=on_type_change,
+            inputs=[ui_components['type_imagegen'], ui_components['base_model_imagegen']],
+            outputs=type_change_outputs,
+            show_progress=False
+        )
+
+    # Fullscreen view toggle for imagegen
+    if 'view_mode_imagegen' in ui_components:
+        def toggle_imagegen_fullscreen_view(view_mode):
+            is_fullscreen = (view_mode == "Fullscreen View")
+            other_elements_visible = not is_fullscreen
+            editor_height = 800 if is_fullscreen else 272
+            
+            updates = {
+                ui_components['type_imagegen']: gr.update(visible=other_elements_visible),
+                ui_components['prompts_col_imagegen']: gr.update(visible=other_elements_visible),
+                ui_components['params_and_gallery_row_imagegen']: gr.update(visible=other_elements_visible),
+                ui_components['accordion_wrapper_imagegen']: gr.update(visible=other_elements_visible),
+                ui_components['input_image_dict_imagegen']: gr.update(height=editor_height),
+            }
+            
+            model_and_run_rows = ui_components.get('model_and_run_row_imagegen', [])
+            for row in model_and_run_rows:
+                updates[row] = gr.update(visible=other_elements_visible)
+            
+            return updates
+        
+        output_components = [ui_components['type_imagegen']]
+        model_and_run_rows = ui_components.get('model_and_run_row_imagegen', [])
+        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_col_imagegen'],
+            ui_components['params_and_gallery_row_imagegen'], 
+            ui_components['accordion_wrapper_imagegen'],
+            ui_components['input_image_dict_imagegen']
+        ])
+        
+        ui_components['view_mode_imagegen'].change(
+            fn=toggle_imagegen_fullscreen_view, 
+            inputs=[ui_components['view_mode_imagegen']], 
+            outputs=output_components, 
+            show_progress=False
+        )
+
     if 'view_mode_inpaint' in ui_components:
         def toggle_inpaint_fullscreen_view(view_mode):
             is_fullscreen = (view_mode == "Fullscreen View")
@@ -255,7 +418,7 @@ def attach_event_handlers(ui_components, demo):
         )
 
     all_load_outputs = []
-    for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
+    for prefix in prefixes:
         if f'controlnet_types_{prefix}' in ui_components:
             all_load_outputs.extend(ui_components[f'controlnet_types_{prefix}'])
             all_load_outputs.extend(ui_components[f'controlnet_series_{prefix}'])
@@ -283,7 +446,7 @@ def attach_event_handlers(ui_components, demo):
             outputs=all_load_outputs
         )
 
-    for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]:
+    for prefix in prefixes:
         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')

ui/events/run_handlers.py

@@ -1,7 +1,21 @@
 import gradio as gr
 from core.generation_logic import generate_image_wrapper
 
-def create_run_event(prefix: str, task_type: str, ui_components: dict):
+TYPE_TASK_MAP = {
+    'Txt2Img': 'txt2img',
+    'Img2Img': 'img2img',
+    'Inpaint': 'inpaint',
+    'Outpaint': 'outpaint',
+    'Hires. Fix': 'hires_fix'
+}
+
+def create_run_event(prefix: str, task_type: str = None, ui_components: dict = None):
+    if ui_components is None and isinstance(task_type, dict):
+        ui_components = task_type
+        task_type = None
+
+    type_comp = ui_components.get(f'type_{prefix}')
+    
     run_inputs_map = {
         'model_display_name': ui_components[f'base_model_{prefix}'],
         'positive_prompt': ui_components.get(f'prompt_{prefix}') or ui_components.get(f'{prefix}_positive_prompt'),
@@ -13,29 +27,47 @@ def create_run_event(prefix: str, task_type: str, ui_components: dict):
         '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}'),
-        'guidance': ui_components.get(f'guidance_{prefix}'),
-        'task_type': gr.State(task_type)
     }
+
+    if type_comp:
+        run_inputs_map['ui_type'] = type_comp
+    elif task_type:
+        run_inputs_map['task_type'] = gr.State(task_type)
     
     if ui_components.get(f'pid_settings_{prefix}'):
         run_inputs_map['pid_settings'] = ui_components[f'pid_settings_{prefix}']
     
-    if task_type not in ['img2img', 'inpaint']:
-        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')
-        })
+    # Generic / Txt2Img inputs
+    if ui_components.get(f'width_{prefix}') or ui_components.get(f'{prefix}_width'):
+        run_inputs_map['width'] = ui_components.get(f'width_{prefix}') or ui_components.get(f'{prefix}_width')
+    if ui_components.get(f'height_{prefix}') or ui_components.get(f'{prefix}_height'):
+        run_inputs_map['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}', '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}'}
-    }
-    if task_type in task_specific_map:
-        for key, comp_name in task_specific_map[task_type].items():
-            if comp_name in ui_components:
-                run_inputs_map[key] = ui_components[comp_name]
+    # Task specific inputs
+    if ui_components.get(f'input_image_{prefix}'):
+        run_inputs_map['img2img_image'] = ui_components[f'input_image_{prefix}']
+        run_inputs_map['outpaint_image'] = ui_components[f'input_image_{prefix}']
+        run_inputs_map['hires_image'] = ui_components[f'input_image_{prefix}']
+    
+    if ui_components.get(f'denoise_{prefix}'):
+        run_inputs_map['denoise'] = ui_components[f'denoise_{prefix}']
+        run_inputs_map['img2img_denoise'] = ui_components[f'denoise_{prefix}']
+        run_inputs_map['inpaint_denoise'] = ui_components[f'denoise_{prefix}']
+        run_inputs_map['hires_denoise'] = ui_components[f'denoise_{prefix}']
+
+    if ui_components.get(f'input_image_dict_{prefix}'):
+        run_inputs_map['inpaint_image_dict'] = ui_components[f'input_image_dict_{prefix}']
+    if ui_components.get(f'grow_mask_by_{prefix}'):
+        run_inputs_map['grow_mask_by'] = ui_components[f'grow_mask_by_{prefix}']
+    
+    if ui_components.get(f'left_{prefix}'): run_inputs_map['left'] = ui_components[f'left_{prefix}']
+    if ui_components.get(f'right_{prefix}'): run_inputs_map['right'] = ui_components[f'right_{prefix}']
+    if ui_components.get(f'top_{prefix}'): run_inputs_map['top'] = ui_components[f'top_{prefix}']
+    if ui_components.get(f'bottom_{prefix}'): run_inputs_map['bottom'] = ui_components[f'bottom_{prefix}']
+    if ui_components.get(f'feathering_{prefix}'): run_inputs_map['feathering'] = ui_components[f'feathering_{prefix}']
+
+    if ui_components.get(f'hires_upscaler_{prefix}'): run_inputs_map['hires_upscaler'] = ui_components[f'hires_upscaler_{prefix}']
+    if ui_components.get(f'hires_scale_by_{prefix}'): run_inputs_map['hires_scale_by'] = ui_components[f'hires_scale_by_{prefix}']
     
     lora_data_components = ui_components.get(f'all_lora_components_flat_{prefix}', [])
     controlnet_data_components = ui_components.get(f'all_controlnet_components_flat_{prefix}', [])
@@ -103,6 +135,9 @@ def create_run_event(prefix: str, task_type: str, ui_components: dict):
         assign_chain_data('boogu_edit_data', boogu_edit_data_components)
         assign_chain_data('reference_image_data', reference_image_data_components)
 
+        if 'ui_type' in ui_dict:
+            ui_dict['task_type'] = TYPE_TASK_MAP.get(ui_dict['ui_type'], 'txt2img')
+
         return ui_dict
 
     run_btn = ui_components.get(f'run_{prefix}') or ui_components.get(f'{prefix}_run_button')

ui/{shared/inpaint_ui.py → imagegen_ui.py}

@@ -1,125 +1,197 @@
-import gradio as gr
-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_krea2_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, create_hidream_o1_reference_ui, create_joyai_reference_ui, create_reference_image_ui, create_krea2_identity_edit_ui, create_krea2_reference_edit_ui, create_qwen_image_edit_ui, create_boogu_edit_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 = {}
-    
-    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()), 
-                value=list(MODEL_MAP_CHECKPOINT.keys())[0], 
-                scale=3,
-                allow_custom_value=True
-            )
-            with gr.Column(scale=1): 
-                components[f'run_{prefix}'] = gr.Button("Run Inpaint", variant="primary")
-        
-        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:
-                components[f'view_mode_{prefix}'] = gr.Radio(
-                    ["Normal View", "Fullscreen View"], 
-                    label="Editor View", 
-                    value="Normal View", 
-                    interactive=True
-                )
-                components[f'input_image_dict_{prefix}'] = gr.ImageEditor(
-                    type="pil", 
-                    label="Image & Mask (No Scaling)", 
-                    height=272
-                )
-            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, 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:
-            with gr.Column(scale=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=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=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)
-                with gr.Row():
-                    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'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=510)
-        
-        components[f'params_and_gallery_row_{prefix}'] = params_and_gallery_row
-            
-        with gr.Column() as accordion_wrapper:
-
-            components.update(create_lora_settings_ui(prefix))
-            components.update(create_controlnet_ui(prefix))
-            components.update(create_anima_controlnet_lllite_ui(prefix))
-            components.update(create_diffsynth_controlnet_ui(prefix))
-            components.update(create_krea2_controlnet_ui(prefix))
-            components.update(create_ipadapter_ui(prefix))
-            components.update(create_flux1_ipadapter_ui(prefix))
-            components.update(create_sd3_ipadapter_ui(prefix))
-            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_hidream_o1_reference_ui(prefix))
-            components.update(create_joyai_reference_ui(prefix))
-            components.update(create_krea2_identity_edit_ui(prefix))
-            components.update(create_krea2_reference_edit_ui(prefix))
-            components.update(create_qwen_image_edit_ui(prefix))
-            components.update(create_boogu_edit_ui(prefix))
-            components.update(create_reference_image_ui(prefix))
-            components.update(create_vae_override_ui(prefix))
-        components[f'accordion_wrapper_{prefix}'] = accordion_wrapper
-            
-    return components
+import gradio as gr
+from core.settings import MODEL_MAP_CHECKPOINT, MODEL_DEFAULTS_CONFIG
+from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES
+from .shared.ui_components import (
+    RESOLUTION_MAP,
+    create_lora_settings_ui,
+    create_controlnet_ui, create_anima_controlnet_lllite_ui, create_diffsynth_controlnet_ui, create_krea2_controlnet_ui, create_ipadapter_ui, create_embedding_ui,
+    create_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, create_hidream_o1_reference_ui, create_joyai_reference_ui, create_reference_image_ui, create_krea2_identity_edit_ui, create_krea2_reference_edit_ui, create_qwen_image_edit_ui, create_boogu_edit_ui,
+    create_pid_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', '')
+
+TYPE_CHOICES = ["Txt2Img", "Img2Img", "Inpaint", "Outpaint", "Hires. Fix"]
+
+def create_ui():
+    """Creates the unified UI components for ImageGen."""
+    prefix = "imagegen"
+    components = {}
+    
+    with gr.Column():
+        components[f'type_{prefix}'] = gr.Radio(
+            choices=TYPE_CHOICES,
+            value="Txt2Img",
+            label="Task",
+            interactive=True
+        )
+
+        with gr.Row() as arch_row:
+            components.update(create_model_architecture_filter_ui(prefix))
+        components[f'arch_row_{prefix}'] = arch_row
+        
+        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()), 
+                value=list(MODEL_MAP_CHECKPOINT.keys())[0], 
+                scale=3,
+                allow_custom_value=True
+            )
+            with gr.Column(scale=1): 
+                components[f'run_{prefix}'] = gr.Button("Run", variant="primary")
+        components[f'model_and_run_row_{prefix}'] = [arch_row, model_and_run_row]
+
+        with gr.Row() as inputs_prompts_row:
+            with gr.Column(scale=1, visible=False) as image_input_col:
+                components[f'input_image_{prefix}'] = gr.Image(
+                    type="pil", 
+                    label="Input Image (No Scaling)", 
+                    height=255, 
+                    visible=False
+                )
+                with gr.Column(visible=False) as inpaint_box:
+                    components[f'view_mode_{prefix}'] = gr.Radio(
+                        ["Normal View", "Fullscreen View"], 
+                        label="Editor View", 
+                        value="Normal View", 
+                        interactive=True
+                    )
+                    components[f'input_image_dict_{prefix}'] = gr.ImageEditor(
+                        type="pil", 
+                        label="Image & Mask (No Scaling)", 
+                        height=272
+                    )
+                components[f'inpaint_box_{prefix}'] = inpaint_box
+            components[f'image_input_col_{prefix}'] = image_input_col
+
+            with gr.Column(scale=2) as prompts_col:
+                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)
+            components[f'prompts_col_{prefix}'] = prompts_col
+        components[f'inputs_prompts_row_{prefix}'] = inputs_prompts_row
+
+        with gr.Row() as params_and_gallery_row:
+            with gr.Column(scale=1) as params_col:
+                # Txt2Img parameters
+                with gr.Row(visible=True) as aspect_ratio_row:
+                    components[f'aspect_ratio_{prefix}'] = gr.Dropdown(
+                        label="Aspect Ratio",
+                        choices=list(RESOLUTION_MAP.get('sdxl', {}).keys()),
+                        value="1:1 (Square)",
+                        interactive=True,
+                        allow_custom_value=True
+                    )
+                components[f'aspect_ratio_row_{prefix}'] = aspect_ratio_row
+
+                with gr.Row(visible=True) as width_height_row:
+                    components[f'width_{prefix}'] = gr.Number(label="Width", value=1024, interactive=True)
+                    components[f'height_{prefix}'] = gr.Number(label="Height", value=1024, interactive=True)
+                components[f'width_height_row_{prefix}'] = width_height_row
+
+                # Img2Img / Inpaint / Hires. Fix Denoise parameter & Inpaint Grow Mask By parameter
+                with gr.Row(visible=False) as denoise_row:
+                    components[f'denoise_{prefix}'] = gr.Slider(
+                        label="Denoise Strength", 
+                        minimum=0.0, 
+                        maximum=1.0, 
+                        step=0.01, 
+                        value=0.7
+                    )
+                    components[f'grow_mask_by_{prefix}'] = gr.Slider(
+                        label="Grow Mask By", 
+                        minimum=0, 
+                        maximum=64, 
+                        step=1, 
+                        value=6,
+                        visible=False
+                    )
+                components[f'denoise_row_{prefix}'] = denoise_row
+
+                # Outpaint Pad & Feathering parameters
+                with gr.Column(visible=False) as outpaint_pads_col:
+                    with gr.Row():
+                        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'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)
+                components[f'outpaint_pads_col_{prefix}'] = outpaint_pads_col
+
+                # Hires. Fix Upscaler parameters
+                with gr.Row(visible=False) as hires_upscaler_row:
+                    components[f'hires_upscaler_{prefix}'] = gr.Dropdown(
+                        label="Upscaler", 
+                        choices=["nearest-exact", "bilinear", "area", "bicubic", "bislerp"], 
+                        value="nearest-exact"
+                    )
+                    components[f'hires_scale_by_{prefix}'] = gr.Slider(
+                        label="Upscale by", 
+                        minimum=1.0, 
+                        maximum=4.0, 
+                        step=0.1, 
+                        value=1.5
+                    )
+                components[f'hires_upscaler_row_{prefix}'] = hires_upscaler_row
+
+                # Common parameters
+                with gr.Row():
+                    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=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)
+                with gr.Row():
+                    components[f'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=60, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU. Longer jobs may need more time.")
+
+            with gr.Column(scale=1):
+                components[f'result_{prefix}'] = gr.Gallery(label="Result", show_label=False, columns=2, object_fit="contain", height=627)
+        components[f'params_and_gallery_row_{prefix}'] = params_and_gallery_row
+
+        with gr.Column() as accordion_wrapper:
+            components.update(create_lora_settings_ui(prefix))
+            components.update(create_controlnet_ui(prefix))
+            components.update(create_anima_controlnet_lllite_ui(prefix))
+            components.update(create_diffsynth_controlnet_ui(prefix))
+            components.update(create_krea2_controlnet_ui(prefix))
+            components.update(create_ipadapter_ui(prefix))
+            components.update(create_flux1_ipadapter_ui(prefix))
+            components.update(create_sd3_ipadapter_ui(prefix))
+            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_hidream_o1_reference_ui(prefix))
+            components.update(create_joyai_reference_ui(prefix))
+            components.update(create_krea2_identity_edit_ui(prefix))
+            components.update(create_krea2_reference_edit_ui(prefix))
+            components.update(create_qwen_image_edit_ui(prefix))
+            components.update(create_boogu_edit_ui(prefix))
+            components.update(create_reference_image_ui(prefix))
+            components.update(create_vae_override_ui(prefix))
+            components.update(create_pid_ui(prefix))
+        components[f'accordion_wrapper_{prefix}'] = accordion_wrapper
+        
+    return components

ui/layout.py

@@ -2,7 +2,7 @@ import os
 import gradio as gr
 from core.settings import *
 
-from .shared import txt2img_ui, img2img_ui, inpaint_ui, outpaint_ui, hires_fix_ui
+from .imagegen_ui import create_ui as create_imagegen_ui
 
 MAX_DYNAMIC_CONTROLS = 10
 
@@ -14,26 +14,9 @@ def build_ui(event_handler_function):
         gr.Markdown(
             "This demo is a streamlined version of the [Comfy web UI](https://github.com/RioShiina47/comfy-webui)'s [ImageGen](https://huggingface.co/spaces/RioShiina/ImageGen) functionality. Support [High-Level MCP](https://rioshiina-imagegen.hf.space/gradio_api/mcp/) 🤖"
         )
-        with gr.Tabs(elem_id="tabs_container") as 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("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("Hires. Fix", id=4):
-                ui_components.update(hires_fix_ui.create_ui())
-
-            ui_components["tabs"] = tabs
-            ui_components["image_gen_tabs"] = tabs
+        ui_components.update(create_imagegen_ui())
         
-        gr.Markdown("<div style='text-align: center; margin-top: 20px;'>Made by RioShiina with ❤️<br><a href='https://github.com/RioShiina47' target='_blank'>GitHub</a> | <a href='https://huggingface.co/RioShiina' target='_blank'>Hugging Face</a> | <a href='https://civitai.com/user/RioShiina' target='_blank'>Civitai</a></div>")
+        gr.Markdown("<div style='text-align: left; margin-top: 20px;'>Made by RioShiina with ❤️<br><a href='https://github.com/RioShiina47' target='_blank'>GitHub</a> | <a href='https://huggingface.co/RioShiina' target='_blank'>Hugging Face</a> | <a href='https://civitai.com/user/RioShiina' target='_blank'>Civitai</a></div>")
         
         event_handler_function(ui_components, demo)
 
@@ -54,5 +37,6 @@ def build_ui(event_handler_function):
         for fn in demo.fns.values():
             if getattr(fn, "api_name", None) not in high_level_names:
                 fn.show_api = False
+                fn.api_name = False
 
     return demo

ui/shared/hires_fix_ui.py

@@ -1,111 +0,0 @@
-import gradio as gr
-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,
-    create_controlnet_ui, create_anima_controlnet_lllite_ui, create_diffsynth_controlnet_ui, create_krea2_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, create_hidream_o1_reference_ui, create_joyai_reference_ui, create_reference_image_ui, create_krea2_identity_edit_ui, create_krea2_reference_edit_ui, create_qwen_image_edit_ui, create_boogu_edit_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 = {}
-    
-    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,
-                allow_custom_value=True
-            )
-            with gr.Column(scale=1): 
-                components[f'run_{prefix}'] = gr.Button("Run Hires. Fix", variant="primary")
-        
-        with gr.Row():
-            with gr.Column(scale=1):
-                components[f'input_image_{prefix}'] = gr.Image(type="pil", label="Input Image (No Scaling)", height=255)
-            with gr.Column(scale=2):
-                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):
-                with gr.Row():
-                    components[f'hires_upscaler_{prefix}'] = gr.Dropdown(
-                        label="Upscaler", 
-                        choices=["nearest-exact", "bilinear", "area", "bicubic", "bislerp"], 
-                        value="nearest-exact"
-                    )
-                    components[f'hires_scale_by_{prefix}'] = gr.Slider(
-                        label="Upscale by", minimum=1.0, maximum=4.0, step=0.1, value=1.5
-                    )
-                
-                with gr.Row():
-                    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=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=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)
-                with gr.Row():
-                    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'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_lora_settings_ui(prefix))
-        components.update(create_controlnet_ui(prefix))
-        components.update(create_anima_controlnet_lllite_ui(prefix))
-        components.update(create_diffsynth_controlnet_ui(prefix))
-        components.update(create_krea2_controlnet_ui(prefix))
-        components.update(create_ipadapter_ui(prefix))
-        components.update(create_flux1_ipadapter_ui(prefix))
-        components.update(create_sd3_ipadapter_ui(prefix))
-        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_hidream_o1_reference_ui(prefix))
-        components.update(create_joyai_reference_ui(prefix))
-        components.update(create_krea2_identity_edit_ui(prefix))
-        components.update(create_krea2_reference_edit_ui(prefix))
-        components.update(create_qwen_image_edit_ui(prefix))
-        components.update(create_boogu_edit_ui(prefix))
-        components.update(create_reference_image_ui(prefix))
-        components.update(create_vae_override_ui(prefix))
-            
-    return components

ui/shared/img2img_ui.py

@@ -1,92 +0,0 @@
-import gradio as gr
-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,
-    create_controlnet_ui, create_anima_controlnet_lllite_ui, create_diffsynth_controlnet_ui, create_krea2_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, create_hidream_o1_reference_ui, create_joyai_reference_ui, create_reference_image_ui, create_krea2_identity_edit_ui, create_krea2_reference_edit_ui, create_qwen_image_edit_ui, create_boogu_edit_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 = {}
-    
-    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, allow_custom_value=True)
-            with gr.Column(scale=1): 
-                components[f'run_{prefix}'] = gr.Button("Run", variant="primary")
-
-        with gr.Row():
-            with gr.Column(scale=1):
-                components[f'input_image_{prefix}'] = gr.Image(type="pil", label="Input Image (No Scaling)", height=255)
-
-            with gr.Column(scale=2):
-                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=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=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)
-                with gr.Row():
-                    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.")
-                
-            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_lora_settings_ui(prefix))
-        components.update(create_controlnet_ui(prefix))
-        components.update(create_anima_controlnet_lllite_ui(prefix))
-        components.update(create_diffsynth_controlnet_ui(prefix))
-        components.update(create_krea2_controlnet_ui(prefix))
-        components.update(create_ipadapter_ui(prefix))
-        components.update(create_flux1_ipadapter_ui(prefix))
-        components.update(create_sd3_ipadapter_ui(prefix))
-        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_hidream_o1_reference_ui(prefix))
-        components.update(create_joyai_reference_ui(prefix))
-        components.update(create_krea2_identity_edit_ui(prefix))
-        components.update(create_krea2_reference_edit_ui(prefix))
-        components.update(create_qwen_image_edit_ui(prefix))
-        components.update(create_boogu_edit_ui(prefix))
-        components.update(create_reference_image_ui(prefix))
-        components.update(create_vae_override_ui(prefix))
-            
-    return components

ui/shared/outpaint_ui.py

@@ -1,107 +0,0 @@
-import gradio as gr
-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,
-    create_controlnet_ui, create_anima_controlnet_lllite_ui, create_diffsynth_controlnet_ui, create_krea2_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, create_hidream_o1_reference_ui, create_joyai_reference_ui, create_reference_image_ui, create_krea2_identity_edit_ui, create_krea2_reference_edit_ui, create_qwen_image_edit_ui, create_boogu_edit_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 = {}
-    
-    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,
-                allow_custom_value=True
-            )
-            with gr.Column(scale=1): 
-                components[f'run_{prefix}'] = gr.Button("Run Outpaint", variant="primary")
-
-        with gr.Row():
-            with gr.Column(scale=1):
-                components[f'input_image_{prefix}'] = gr.Image(type="pil", label="Input Image (No Scaling)", height=255)
-            with gr.Column(scale=2):
-                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):
-                with gr.Row():
-                    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'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=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=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)
-                with gr.Row():
-                    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'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=685)
-        
-
-        components.update(create_lora_settings_ui(prefix))
-        components.update(create_controlnet_ui(prefix))
-        components.update(create_anima_controlnet_lllite_ui(prefix))
-        components.update(create_diffsynth_controlnet_ui(prefix))
-        components.update(create_krea2_controlnet_ui(prefix))
-        components.update(create_ipadapter_ui(prefix))
-        components.update(create_flux1_ipadapter_ui(prefix))
-        components.update(create_sd3_ipadapter_ui(prefix))
-        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_hidream_o1_reference_ui(prefix))
-        components.update(create_joyai_reference_ui(prefix))
-        components.update(create_krea2_identity_edit_ui(prefix))
-        components.update(create_krea2_reference_edit_ui(prefix))
-        components.update(create_qwen_image_edit_ui(prefix))
-        components.update(create_boogu_edit_ui(prefix))
-        components.update(create_reference_image_ui(prefix))
-        components.update(create_vae_override_ui(prefix))
-            
-    return components

ui/shared/txt2img_ui.py

@@ -1,66 +0,0 @@
-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_anima_controlnet_lllite_ui, create_diffsynth_controlnet_ui, create_krea2_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, create_hidream_o1_reference_ui, create_joyai_reference_ui, create_reference_image_ui, create_krea2_identity_edit_ui, create_krea2_reference_edit_ui, create_qwen_image_edit_ui, create_boogu_edit_ui,
-    create_pid_ui
-)
-
-def create_ui():
-    """Creates the UI components for the Txt2Img tab."""
-    prefix = "txt2img"
-    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,
-                allow_custom_value=True
-            )
-            with gr.Column(scale=1): 
-                components[f'run_{prefix}'] = gr.Button("Run", variant="primary")
-        
-        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):
-                param_defaults = {'w': 1024, 'h': 1024, 'cs_vis': False, 'cs_val': 1}
-                components.update(create_base_parameter_ui(prefix, param_defaults))
-            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_lora_settings_ui(prefix))
-        components.update(create_controlnet_ui(prefix))
-        components.update(create_anima_controlnet_lllite_ui(prefix))
-        components.update(create_diffsynth_controlnet_ui(prefix))
-        components.update(create_krea2_controlnet_ui(prefix))
-        components.update(create_ipadapter_ui(prefix))
-        components.update(create_flux1_ipadapter_ui(prefix))
-        components.update(create_sd3_ipadapter_ui(prefix))
-        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_hidream_o1_reference_ui(prefix))
-        components.update(create_joyai_reference_ui(prefix))
-        components.update(create_krea2_identity_edit_ui(prefix))
-        components.update(create_krea2_reference_edit_ui(prefix))
-        components.update(create_qwen_image_edit_ui(prefix))
-        components.update(create_boogu_edit_ui(prefix))
-        components.update(create_reference_image_ui(prefix))
-        components.update(create_vae_override_ui(prefix))
-        components.update(create_pid_ui(prefix))
-        
-    return components

ui/shared/ui_components.py

@@ -114,8 +114,7 @@ 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'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'zero_gpu_{prefix}'] = gr.Number(label="ZeroGPU Duration (s)", value=60, placeholder="Default: 60s, Max: 120s", info="Optional: Set how long to reserve the GPU.")
             
     return components
 

yaml/chain_features.yaml

@@ -5,12 +5,6 @@ lora:
   chains: lora
   display_name: "LoRA Fine-tuning Injector"
   description: "Injects LoRA weights into UNet/DiT model and CLIP text encoder for custom style, character, or domain adaptation. Note: For Civitai, specify the Version ID (modelVersionId) instead of the main Model ID."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Specify source ('Civitai' or 'Hugging Face'). For Civitai, provide lora_value as the Version ID (modelVersionId). For Hugging Face, provide HF repo file path. Scale (0.0~2.0) controls weight strength."
   parameters_schema:
@@ -37,12 +31,6 @@ ipadapter:
   chains: ipadapter
   display_name: "IP-Adapter Image Prompt"
   description: "Uses reference images to guide generation style, composition, structure, or face appearance without prompt text restrictions (SD1.5 & SDXL)."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Supply global settings (preset, embeds_scaling, combine_method, final_weight) and up to 5 reference images with individual weights. Preset must match the target model architecture (SD1.5 or SDXL)."
   parameters_schema:
@@ -99,12 +87,6 @@ controlnet:
   chains: controlnet
   display_name: "ControlNet Spatial Guidance"
   description: "Applies structural and spatial conditioning (depth, pose, lineart, tile, scribble, canny) to guide output composition."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Specify ControlNet type and series (must match requested model architecture e.g., SD1.5, SDXL, SD3.5, FLUX.1, Qwen-Image), pre-processed control image (Base64 Data URI or HTTP/HTTPS URL; system does NOT pre-process raw RGB images), and guidance strength."
   parameters_schema:
@@ -134,12 +116,6 @@ conditioning:
   chains: conditioning
   display_name: "Regional Conditioning / Area Prompt"
   description: "Defines rectangular areas (X, Y, Width, Height) and assigns specific text prompts and conditioning strengths to them."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 10
   usage_guideline: "Define rectangular spatial areas (X, Y, width, height) and assign specific prompts and strengths to them. Supports up to 10 area prompts."
   parameters_schema:
@@ -177,12 +153,6 @@ vae:
   chains: vae
   display_name: "Custom VAE Loader"
   description: "Overrides default VAE model used for latent space encoding and final image decoding."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 1
   usage_guideline: "Specify source ('Civitai' or 'Hugging Face'), then provide the vae_value (Civitai Version ID or HF file path)."
   parameters_schema:
@@ -203,8 +173,6 @@ pid:
   chains: pid
   display_name: "PiD High-Resolution Refinement"
   description: "Progressive Detail (PiD) upscale injector for fine detail enhancement and resolution upscaling."
-  supported_tasks:
-    - txt2img
   max_count: 1
   usage_guideline: "Enables PiD detail refinement pipeline using a boolean switch ('enabled': true/false)."
   parameters_schema:
@@ -221,12 +189,6 @@ flux1_style:
   chains: style
   display_name: "FLUX.1 Style Reference"
   description: "Applies artistic style conditioning from reference images onto FLUX.1 model generated outputs."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Supply style reference image(s) (up to 5) encoded as Base64 Data URI or HTTP/HTTPS URL and optional strength."
   parameters_schema:
@@ -248,12 +210,6 @@ reference_edit:
   chains: reference_latent
   display_name: "Reference Edit"
   description: "For multimodal models, 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."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 10
   usage_guideline: "Supply reference image(s) encoded as Base64 Data URI or HTTP/HTTPS URL. Passing a single reference image performs an Image Edit, while passing multiple images (up to 10) performs an Image Combine."
   parameters_schema:
@@ -269,12 +225,6 @@ mage_flow_reference_edit:
   chains: reference_image
   display_name: "Mage-Flow Reference Edit"
   description: " (Mage-Flow-Edit-Turbo/Mage-Flow-Edit recommended) For multimodal models, 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."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 10
   usage_guideline: "Supply reference image as Base64 Data URI or HTTP/HTTPS URL."
   parameters_schema:
@@ -290,12 +240,6 @@ krea2_identity_edit:
   chains: krea2_identity_edit
   display_name: "KREA2 Identity Edit"
   description: "Processed using the lbouaraba/comfyui-krea2edit node. (Krea-2-Turbo recommended, Krea-2-Raw need set ZeroGPU Duration (s) to 120 ) In txt2img mode, adding a single reference image performs an Image Edit, while adding multiple images performs an Image Combine."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 2
   usage_guideline: "Supply reference image as Base64 Data URI or HTTP/HTTPS URL."
   parameters_schema:
@@ -311,12 +255,6 @@ krea2_style_reference:
   chains: krea2_style_reference
   display_name: "KREA2 Style Reference"
   description: "(Krea-2-Turbo recommended) Add style reference images to perform style reference editing."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 3
   usage_guideline: "Supply style reference image as Base64 Data URI or HTTP/HTTPS URL."
   parameters_schema:
@@ -332,12 +270,6 @@ diffsynth_controlnet:
   chains: diffsynth_controlnet
   display_name: "DiffSynth ControlNet"
   description: "DiffSynth optimized ControlNet injector for Z-Image models."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Supply ControlNet type (e.g., 'Canny'), series (e.g., 'alibaba-pai Controlnet Union 2.1 8steps'), pre-processed control image (Base64 Data URI or HTTP/HTTPS URL; system does NOT pre-process raw RGB images), and optional strength."
   parameters_schema:
@@ -365,12 +297,6 @@ boogu_image_edit:
   chains: boogu_image_edit
   display_name: "Boogu-Image Edit"
   description: " (Boogu-Image-Edit-Turbo/Boogu-Image-Edit recommended, Boogu-Image-Edit need set ZeroGPU Duration (s) to 120 ) In txt2img mode, adding a single reference image performs an Image Edit, while adding multiple images performs an Image Combine."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 2
   usage_guideline: "Supply reference image as Base64 Data URI or HTTP/HTTPS URL."
   parameters_schema:
@@ -386,12 +312,6 @@ joyai_reference_edit:
   chains: joyai_image
   display_name: "JoyAI Reference Edit"
   description: " (JoyAI-Image-Edit recommended) For multimodal models, this feature enables powerful editing and combining capabilities. In txt2img mode, adding a single reference image performs an Image Edit (JoyAI-Image-Edit recommended), while adding multiple images performs an Image Combine (JoyAI-Image-Edit-Plus recommended with ZeroGPU Duration (s) set to 120)."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 2
   usage_guideline: "Supply JoyAI reference image as Base64 Data URI or HTTP/HTTPS URL."
   parameters_schema:
@@ -407,12 +327,6 @@ qwen_image_edit:
   chains: qwen_image_edit
   display_name: "Qwen-Image Edit"
   description: " (lightx2v/Qwen-Image-Edit-2511-Lightning recommended) In txt2img mode, adding a single reference image performs an Image Edit, while adding multiple images performs an Image Combine."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 3
   usage_guideline: "Supply reference image(s) (up to 3) encoded as Base64 Data URI or HTTP/HTTPS URL. Passing a single reference image performs an Image Edit, while passing multiple images performs an Image Combine."
   parameters_schema:
@@ -428,12 +342,6 @@ hidream_o1_smoothing:
   chains: hidream_o1_smoothing
   display_name: "HiDream O1 Smoothing Injector"
   description: "HiDream O1 detail smoothing and artifact reduction injector."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 1
   usage_guideline: "Configures smoothing factor for HiDream models."
   parameters_schema:
@@ -449,12 +357,6 @@ krea2_controlnet:
   chains: krea2_controlnet
   display_name: "KREA2 ControlNet"
   description: "Processed using the facok/comfyui-krea2-controlnet node."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Supply ControlNet type (e.g., 'Depth'), series (e.g., 'Patil'), pre-processed control image (Base64 Data URI or HTTP/HTTPS URL; system does NOT pre-process raw RGB images), and optional strength."
   parameters_schema:
@@ -489,12 +391,6 @@ anima_controlnet_lllite:
   chains: anima_controlnet_lllite
   display_name: "Anima ControlNet LLLite"
   description: "Anima model-specific lightweight ControlNet."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Supply Anima ControlNet LLLite type (e.g., 'Depth'), series (e.g., 'kohya-ss'), pre-processed control image (Base64 Data URI or HTTP/HTTPS URL; system does NOT pre-process raw RGB images), and optional strength."
   parameters_schema:
@@ -524,12 +420,6 @@ hidream_o1_reference:
   chains: hidream_o1_reference
   display_name: "HiDream-O1 Reference Edit"
   description: " (HiDream-O1-Image-Dev recommended with resolution set to 4.0MP, e.g., 2048x2048) For HiDream-O1 models, this feature enables reference image editing and combining capabilities. In txt2img mode, adding a single reference image performs an Image Edit, while adding multiple images performs an Image Combine."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 9
   usage_guideline: "Supply reference image(s) (up to 9) encoded as Base64 Data URI or HTTP/HTTPS URL. Passing a single reference image performs an Image Edit, while passing multiple images performs an Image Combine."
   parameters_schema:
@@ -545,12 +435,6 @@ flux1_ipadapter:
   chains: flux1_ipadapter
   display_name: "Flux1 IP-Adapter"
   description: "FLUX.1 model-specific IP-Adapter implementation."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Supply reference image (Base64 Data URI or HTTP/HTTPS URL), optional weight (default 1.0), start_at (default 0.0), and end_at (default 1.0). Up to 5 images supported."
   parameters_schema:
@@ -586,12 +470,6 @@ sd3_ipadapter:
   chains: sd3_ipadapter
   display_name: "SD3 IP-Adapter"
   description: "SD3/SD3.5 model-specific IP-Adapter implementation."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Supply reference image (Base64 Data URI or HTTP/HTTPS URL), optional weight (default 1.0), start_at (default 0.0), and end_at (default 1.0). Up to 5 images supported."
   parameters_schema:
@@ -627,12 +505,6 @@ embedding:
   chains: embedding
   display_name: "Textual Inversion Embedding Injector"
   description: "Downloads Textual Inversion embedding files from Civitai or Hugging Face to the server. Note: This feature ONLY handles file downloading/preparation. To activate the embedding, manually add 'embedding:<filename>' (e.g. 'embedding:civitai_456' for Civitai ID 456, or 'embedding:filename' for Hugging Face) into your prompt or negative_prompt."
-  supported_tasks:
-    - txt2img
-    - img2img
-    - inpaint
-    - outpaint
-    - hires_fix
   max_count: 5
   usage_guideline: "Specify source ('Civitai' or 'Hugging Face'), and embedding_value (Civitai Version ID or HF repo file path). The file is downloaded to server; manually enter 'embedding:<filename>' in prompt or negative_prompt to activate."
   parameters_schema:

yaml/{image_gen_features.yaml → model_architecture_features.yaml}

@@ -1,200 +1,200 @@
-# Feature names in enabled_chains correspond 1-to-1 with chain_injectors/<name>_injector.py
-krea-2:
-  enabled_chains:
-  - lora
-  - krea2_controlnet
-  - krea2_identity_edit
-  - krea2_style_reference
-  - pid
-
-mage-flow:
-  enabled_chains:
-  - reference_image
-
-joyai-image:
-  enabled_chains:
-  - joyai_image
-
-boogu-image:
-  enabled_chains:
-  - lora
-  - boogu_image_edit
-  - pid
-
-pixeldit:
-  enabled_chains:
-  - conditioning
-
-ideogram-4:
-  enabled_chains:
-  - vae
-  - pid
-
-lens:
-  enabled_chains:
-  - conditioning
-  - pid
-
-flux2-kv:
-  enabled_chains:
-  - lora
-  - reference_latent
-  - conditioning
-  - vae
-  - pid
-
-flux2:
-  enabled_chains:
-  - lora
-  - reference_latent
-  - conditioning
-  - vae
-  - pid
-
-ernie-image:
-  enabled_chains:
-  - conditioning
-  - pid
-
-z-image:
-  enabled_chains:
-  - lora
-  - diffsynth_controlnet
-  - conditioning
-  - vae
-  - pid
-
-qwen-image:
-  enabled_chains:
-  - lora
-  - conditioning
-  - controlnet
-  - qwen_image_edit
-  - vae
-  - pid
-
-longcat-image:
-  enabled_chains:
-  - lora
-  - conditioning
-  - pid
-
-cosmos-predict2:
-  enabled_chains:
-  - conditioning
-  - vae
-
-anima:
-  enabled_chains:
-  - lora
-  - conditioning
-  - anima_controlnet_lllite
-  - vae
-  - pid
-
-newbie-image:
-  enabled_chains:
-  - lora
-  - embedding
-  - conditioning
-  - vae
-  - pid
-
-kandinsky-5:
-  enabled_chains:
-  - conditioning
-  - vae
-  - pid
-
-ovis-image:
-  enabled_chains:
-  - conditioning
-  - vae
-  - pid
-
-hunyuanimage:
-  enabled_chains:
-  - conditioning
-  - vae
-
-chroma1-radiance:
-  enabled_chains:
-  - conditioning
-
-chroma1:
-  enabled_chains:
-  - conditioning
-  - vae
-  - pid
-
-omnigen2:
-  enabled_chains:
-  - reference_latent
-  - conditioning
-  - pid
-
-lumina:
-  enabled_chains:
-  - lora
-  - embedding
-  - conditioning
-  - vae
-  - pid
-
-hidream-o1:
-  enabled_chains:
-  - lora
-  - conditioning
-  - hidream_o1_smoothing
-  - hidream_o1_reference
-
-hidream-i1:
-  enabled_chains:
-  - lora
-  - conditioning
-  - pid
-
-flux1:
-  enabled_chains:
-  - lora
-  - flux1_ipadapter
-  - conditioning
-  - style
-  - controlnet
-  - vae
-  - pid
-
-auraflow:
-  enabled_chains:
-  - lora
-  - conditioning
-  - vae
-
-sd35:
-  enabled_chains:
-  - lora
-  - sd3_ipadapter
-  - embedding
-  - conditioning
-  - controlnet
-  - vae
-  - pid
-
-sdxl:
-  enabled_chains:
-  - lora
-  - ipadapter
-  - embedding
-  - conditioning
-  - controlnet
-  - vae
-  - pid
-
-sd15:
-  enabled_chains:
-  - lora
-  - ipadapter
-  - embedding
-  - conditioning
-  - controlnet
+# Feature names in enabled_chains correspond 1-to-1 with chain_injectors/<name>_injector.py
+krea-2:
+  enabled_chains:
+  - lora
+  - krea2_controlnet
+  - krea2_identity_edit
+  - krea2_style_reference
+  - pid
+
+mage-flow:
+  enabled_chains:
+  - reference_image
+
+joyai-image:
+  enabled_chains:
+  - joyai_image
+
+boogu-image:
+  enabled_chains:
+  - lora
+  - boogu_image_edit
+  - pid
+
+pixeldit:
+  enabled_chains:
+  - conditioning
+
+ideogram-4:
+  enabled_chains:
+  - vae
+  - pid
+
+lens:
+  enabled_chains:
+  - conditioning
+  - pid
+
+flux2-kv:
+  enabled_chains:
+  - lora
+  - reference_latent
+  - conditioning
+  - vae
+  - pid
+
+flux2:
+  enabled_chains:
+  - lora
+  - reference_latent
+  - conditioning
+  - vae
+  - pid
+
+ernie-image:
+  enabled_chains:
+  - conditioning
+  - pid
+
+z-image:
+  enabled_chains:
+  - lora
+  - diffsynth_controlnet
+  - conditioning
+  - vae
+  - pid
+
+qwen-image:
+  enabled_chains:
+  - lora
+  - conditioning
+  - controlnet
+  - qwen_image_edit
+  - vae
+  - pid
+
+longcat-image:
+  enabled_chains:
+  - lora
+  - conditioning
+  - pid
+
+cosmos-predict2:
+  enabled_chains:
+  - conditioning
+  - vae
+
+anima:
+  enabled_chains:
+  - lora
+  - conditioning
+  - anima_controlnet_lllite
+  - vae
+  - pid
+
+newbie-image:
+  enabled_chains:
+  - lora
+  - embedding
+  - conditioning
+  - vae
+  - pid
+
+kandinsky-5:
+  enabled_chains:
+  - conditioning
+  - vae
+  - pid
+
+ovis-image:
+  enabled_chains:
+  - conditioning
+  - vae
+  - pid
+
+hunyuanimage:
+  enabled_chains:
+  - conditioning
+  - vae
+
+chroma1-radiance:
+  enabled_chains:
+  - conditioning
+
+chroma1:
+  enabled_chains:
+  - conditioning
+  - vae
+  - pid
+
+omnigen2:
+  enabled_chains:
+  - reference_latent
+  - conditioning
+  - pid
+
+lumina:
+  enabled_chains:
+  - lora
+  - embedding
+  - conditioning
+  - vae
+  - pid
+
+hidream-o1:
+  enabled_chains:
+  - lora
+  - conditioning
+  - hidream_o1_smoothing
+  - hidream_o1_reference
+
+hidream-i1:
+  enabled_chains:
+  - lora
+  - conditioning
+  - pid
+
+flux1:
+  enabled_chains:
+  - lora
+  - flux1_ipadapter
+  - conditioning
+  - style
+  - controlnet
+  - vae
+  - pid
+
+auraflow:
+  enabled_chains:
+  - lora
+  - conditioning
+  - vae
+
+sd35:
+  enabled_chains:
+  - lora
+  - sd3_ipadapter
+  - embedding
+  - conditioning
+  - controlnet
+  - vae
+  - pid
+
+sdxl:
+  enabled_chains:
+  - lora
+  - ipadapter
+  - embedding
+  - conditioning
+  - controlnet
+  - vae
+  - pid
+
+sd15:
+  enabled_chains:
+  - lora
+  - ipadapter
+  - embedding
+  - conditioning
+  - controlnet
   - vae

yaml/task_features.yaml

@@ -0,0 +1,125 @@
+# Task-level feature support configuration
+# Defines which chains (features) are available for each task type.
+# A feature is visible in the UI only when BOTH the task AND the model architecture support it.
+# pid only supports txt2img; all other features support all 5 tasks.
+
+txt2img:
+  enabled_chains:
+  - lora
+  - controlnet
+  - anima_controlnet_lllite
+  - diffsynth_controlnet
+  - krea2_controlnet
+  - ipadapter
+  - flux1_ipadapter
+  - sd3_ipadapter
+  - style
+  - embedding
+  - conditioning
+  - reference_latent
+  - hidream_o1_reference
+  - hidream_o1_smoothing
+  - joyai_image
+  - krea2_identity_edit
+  - krea2_style_reference
+  - qwen_image_edit
+  - boogu_image_edit
+  - reference_image
+  - pid
+  - vae
+
+img2img:
+  enabled_chains:
+  - lora
+  - controlnet
+  - anima_controlnet_lllite
+  - diffsynth_controlnet
+  - krea2_controlnet
+  - ipadapter
+  - flux1_ipadapter
+  - sd3_ipadapter
+  - style
+  - embedding
+  - conditioning
+  - reference_latent
+  - hidream_o1_reference
+  - hidream_o1_smoothing
+  - joyai_image
+  - krea2_identity_edit
+  - krea2_style_reference
+  - qwen_image_edit
+  - boogu_image_edit
+  - reference_image
+  - vae
+
+inpaint:
+  enabled_chains:
+  - lora
+  - controlnet
+  - anima_controlnet_lllite
+  - diffsynth_controlnet
+  - krea2_controlnet
+  - ipadapter
+  - flux1_ipadapter
+  - sd3_ipadapter
+  - style
+  - embedding
+  - conditioning
+  - reference_latent
+  - hidream_o1_reference
+  - hidream_o1_smoothing
+  - joyai_image
+  - krea2_identity_edit
+  - krea2_style_reference
+  - qwen_image_edit
+  - boogu_image_edit
+  - reference_image
+  - vae
+
+outpaint:
+  enabled_chains:
+  - lora
+  - controlnet
+  - anima_controlnet_lllite
+  - diffsynth_controlnet
+  - krea2_controlnet
+  - ipadapter
+  - flux1_ipadapter
+  - sd3_ipadapter
+  - style
+  - embedding
+  - conditioning
+  - reference_latent
+  - hidream_o1_reference
+  - hidream_o1_smoothing
+  - joyai_image
+  - krea2_identity_edit
+  - krea2_style_reference
+  - qwen_image_edit
+  - boogu_image_edit
+  - reference_image
+  - vae
+
+hires_fix:
+  enabled_chains:
+  - lora
+  - controlnet
+  - anima_controlnet_lllite
+  - diffsynth_controlnet
+  - krea2_controlnet
+  - ipadapter
+  - flux1_ipadapter
+  - sd3_ipadapter
+  - style
+  - embedding
+  - conditioning
+  - reference_latent
+  - hidream_o1_reference
+  - hidream_o1_smoothing
+  - joyai_image
+  - krea2_identity_edit
+  - krea2_style_reference
+  - qwen_image_edit
+  - boogu_image_edit
+  - reference_image
+  - vae