import gradio as gr import yaml import os import shutil from functools import lru_cache from core.settings import * from utils.app_utils import * from core.generation_logic import * from comfy_integration.nodes import SAMPLER_CHOICES, SCHEDULER_CHOICES from core.pipelines.controlnet_preprocessor import CPU_ONLY_PREPROCESSORS from utils.app_utils import PREPROCESSOR_MODEL_MAP, PREPROCESSOR_PARAMETER_MAP, save_uploaded_file_with_hash from ui.shared.ui_components import RESOLUTION_MAP, MAX_CONTROLNETS, MAX_IPADAPTERS, MAX_EMBEDDINGS, MAX_CONDITIONINGS, MAX_LORAS @lru_cache(maxsize=1) def load_controlnet_config(): _PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) _CN_MODEL_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'controlnet_models.yaml') try: print("--- Loading controlnet_models.yaml ---") with open(_CN_MODEL_LIST_PATH, 'r', encoding='utf-8') as f: config = yaml.safe_load(f) print("--- ✅ controlnet_models.yaml loaded successfully ---") return config.get("ControlNet", {}).get("SDXL", []) except Exception as e: print(f"Error loading controlnet_models.yaml: {e}") return [] @lru_cache(maxsize=1) def load_ipadapter_config(): _PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) _IPA_MODEL_LIST_PATH = os.path.join(_PROJECT_ROOT, 'yaml', 'ipadapter.yaml') try: print("--- Loading ipadapter.yaml ---") with open(_IPA_MODEL_LIST_PATH, 'r', encoding='utf-8') as f: config = yaml.safe_load(f) print("--- ✅ ipadapter.yaml loaded successfully ---") return config except Exception as e: print(f"Error loading ipadapter.yaml: {e}") return {} def apply_data_to_ui(data, prefix, ui_components): final_sampler = data.get('sampler') if data.get('sampler') in SAMPLER_CHOICES else SAMPLER_CHOICES[0] default_scheduler = 'normal' if 'normal' in SCHEDULER_CHOICES else SCHEDULER_CHOICES[0] final_scheduler = data.get('scheduler') if data.get('scheduler') in SCHEDULER_CHOICES else default_scheduler updates = {} base_model_name = data.get('base_model') model_map = MODEL_MAP_CHECKPOINT if f'base_model_{prefix}' in ui_components: model_dropdown_component = ui_components[f'base_model_{prefix}'] if base_model_name and base_model_name in model_map: updates[model_dropdown_component] = base_model_name else: updates[model_dropdown_component] = gr.update() common_params = { f'prompt_{prefix}': data.get('prompt', ''), f'neg_prompt_{prefix}': data.get('negative_prompt', ''), f'seed_{prefix}': data.get('seed', -1), f'cfg_{prefix}': data.get('cfg_scale', 7.5), f'steps_{prefix}': data.get('steps', 28), f'sampler_{prefix}': final_sampler, f'scheduler_{prefix}': final_scheduler, } for comp_name, value in common_params.items(): if comp_name in ui_components: updates[ui_components[comp_name]] = value if prefix == 'txt2img': if f'width_{prefix}' in ui_components: updates[ui_components[f'width_{prefix}']] = data.get('width', 1024) if f'height_{prefix}' in ui_components: updates[ui_components[f'height_{prefix}']] = data.get('height', 1024) tab_indices = {"txt2img": 0, "img2img": 1, "inpaint": 2, "outpaint": 3, "hires_fix": 4} tab_index = tab_indices.get(prefix, 0) updates[ui_components['tabs']] = gr.Tabs(selected=0) updates[ui_components['image_gen_tabs']] = gr.Tabs(selected=tab_index) return updates def send_info_to_tab(image, prefix, ui_components): if not image or not image.info.get('parameters', ''): all_comps = [comp for comp_or_list in ui_components.values() for comp in (comp_or_list if isinstance(comp_or_list, list) else [comp_or_list])] return {comp: gr.update() for comp in all_comps} data = parse_parameters(image.info['parameters']) image_input_map = { "img2img": 'input_image_img2img', "inpaint": 'input_image_dict_inpaint', "outpaint": 'input_image_outpaint', "hires_fix": 'input_image_hires_fix' } updates = apply_data_to_ui(data, prefix, ui_components) if prefix in image_input_map and image_input_map[prefix] in ui_components: component_key = image_input_map[prefix] updates[ui_components[component_key]] = gr.update(value=image) return updates def send_info_by_hash(image, ui_components): if not image or not image.info.get('parameters', ''): all_comps = [comp for comp_or_list in ui_components.values() for comp in (comp_or_list if isinstance(comp_or_list, list) else [comp_or_list])] return {comp: gr.update() for comp in all_comps} data = parse_parameters(image.info['parameters']) return apply_data_to_ui(data, "txt2img", ui_components) def attach_event_handlers(ui_components, demo): def update_cn_input_visibility(choice): return { ui_components["cn_image_input"]: gr.update(visible=choice == "Image"), ui_components["cn_video_input"]: gr.update(visible=choice == "Video") } ui_components["cn_input_type"].change( fn=update_cn_input_visibility, inputs=[ui_components["cn_input_type"]], outputs=[ui_components["cn_image_input"], ui_components["cn_video_input"]] ) def update_preprocessor_models_dropdown(preprocessor_name): models = PREPROCESSOR_MODEL_MAP.get(preprocessor_name) if models: model_filenames = [m[1] for m in models] return gr.update(choices=model_filenames, value=model_filenames[0], visible=True) else: return gr.update(choices=[], value=None, visible=False) def update_preprocessor_settings_ui(preprocessor_name): from ui.layout import MAX_DYNAMIC_CONTROLS params = PREPROCESSOR_PARAMETER_MAP.get(preprocessor_name, []) slider_updates, dropdown_updates, checkbox_updates = [], [], [] s_idx, d_idx, c_idx = 0, 0, 0 for param in params: if s_idx + d_idx + c_idx >= MAX_DYNAMIC_CONTROLS: break name = param["name"] ptype = param["type"] config = param["config"] label = name.replace('_', ' ').title() if ptype == "INT" or ptype == "FLOAT": if s_idx < MAX_DYNAMIC_CONTROLS: slider_updates.append(gr.update( label=label, minimum=config.get('min', 0), maximum=config.get('max', 255), step=config.get('step', 0.1 if ptype == "FLOAT" else 1), value=config.get('default', 0), visible=True )) s_idx += 1 elif isinstance(ptype, list): if d_idx < MAX_DYNAMIC_CONTROLS: dropdown_updates.append(gr.update( label=label, choices=ptype, value=config.get('default', ptype[0] if ptype else None), visible=True )) d_idx += 1 elif ptype == "BOOLEAN": if c_idx < MAX_DYNAMIC_CONTROLS: checkbox_updates.append(gr.update( label=label, value=config.get('default', False), visible=True )) c_idx += 1 for _ in range(s_idx, MAX_DYNAMIC_CONTROLS): slider_updates.append(gr.update(visible=False)) for _ in range(d_idx, MAX_DYNAMIC_CONTROLS): dropdown_updates.append(gr.update(visible=False)) for _ in range(c_idx, MAX_DYNAMIC_CONTROLS): checkbox_updates.append(gr.update(visible=False)) return slider_updates + dropdown_updates + checkbox_updates def update_run_button_for_cpu(preprocessor_name): if preprocessor_name in CPU_ONLY_PREPROCESSORS: return gr.update(value="Run Preprocessor CPU Only", variant="primary"), gr.update(visible=False) else: return gr.update(value="Run Preprocessor", variant="primary"), gr.update(visible=True) ui_components["preprocessor_cn"].change( fn=update_preprocessor_models_dropdown, inputs=[ui_components["preprocessor_cn"]], outputs=[ui_components["preprocessor_model_cn"]] ).then( fn=update_preprocessor_settings_ui, inputs=[ui_components["preprocessor_cn"]], outputs=ui_components["cn_sliders"] + ui_components["cn_dropdowns"] + ui_components["cn_checkboxes"] ).then( fn=update_run_button_for_cpu, inputs=[ui_components["preprocessor_cn"]], outputs=[ui_components["run_cn"], ui_components["zero_gpu_cn"]] ) all_dynamic_inputs = ( ui_components["cn_sliders"] + ui_components["cn_dropdowns"] + ui_components["cn_checkboxes"] ) ui_components["run_cn"].click( fn=run_cn_preprocessor_entry, inputs=[ ui_components["cn_input_type"], ui_components["cn_image_input"], ui_components["cn_video_input"], ui_components["preprocessor_cn"], ui_components["preprocessor_model_cn"], ui_components["zero_gpu_cn"], ] + all_dynamic_inputs, outputs=[ui_components["output_gallery_cn"]] ) def create_lora_event_handlers(prefix): lora_rows = ui_components[f'lora_rows_{prefix}'] lora_ids = ui_components[f'lora_ids_{prefix}'] lora_scales = ui_components[f'lora_scales_{prefix}'] lora_uploads = ui_components[f'lora_uploads_{prefix}'] count_state = ui_components[f'lora_count_state_{prefix}'] add_button = ui_components[f'add_lora_button_{prefix}'] del_button = ui_components[f'delete_lora_button_{prefix}'] def add_lora_row(c): updates = {} if c < MAX_LORAS: c += 1 updates[lora_rows[c - 1]] = gr.update(visible=True) updates[count_state] = c updates[add_button] = gr.update(visible=c < MAX_LORAS) updates[del_button] = gr.update(visible=c > 1) return updates def del_lora_row(c): updates = {} if c > 1: updates[lora_rows[c - 1]] = gr.update(visible=False) updates[lora_ids[c - 1]] = "" updates[lora_scales[c - 1]] = 0.0 updates[lora_uploads[c - 1]] = None c -= 1 updates[count_state] = c updates[add_button] = gr.update(visible=True) updates[del_button] = gr.update(visible=c > 1) return updates add_outputs = [count_state, add_button, del_button] + lora_rows del_outputs = [count_state, add_button, del_button] + lora_rows + lora_ids + lora_scales + lora_uploads add_button.click(add_lora_row, [count_state], add_outputs, show_progress=False) del_button.click(del_lora_row, [count_state], del_outputs, show_progress=False) def create_controlnet_event_handlers(prefix): cn_rows = ui_components[f'controlnet_rows_{prefix}'] cn_types = ui_components[f'controlnet_types_{prefix}'] cn_series = ui_components[f'controlnet_series_{prefix}'] cn_filepaths = ui_components[f'controlnet_filepaths_{prefix}'] cn_images = ui_components[f'controlnet_images_{prefix}'] cn_strengths = ui_components[f'controlnet_strengths_{prefix}'] count_state = ui_components[f'controlnet_count_state_{prefix}'] add_button = ui_components[f'add_controlnet_button_{prefix}'] del_button = ui_components[f'delete_controlnet_button_{prefix}'] accordion = ui_components[f'controlnet_accordion_{prefix}'] def add_cn_row(c): c += 1 updates = { count_state: c, cn_rows[c-1]: gr.update(visible=True), add_button: gr.update(visible=c < MAX_CONTROLNETS), del_button: gr.update(visible=True) } return updates def del_cn_row(c): c -= 1 updates = { count_state: c, cn_rows[c]: gr.update(visible=False), cn_images[c]: None, cn_strengths[c]: 1.0, add_button: gr.update(visible=True), del_button: gr.update(visible=c > 0) } return updates add_outputs = [count_state, add_button, del_button] + cn_rows del_outputs = [count_state, add_button, del_button] + cn_rows + cn_images + cn_strengths add_button.click(fn=add_cn_row, inputs=[count_state], outputs=add_outputs, show_progress=False) del_button.click(fn=del_cn_row, inputs=[count_state], outputs=del_outputs, show_progress=False) def on_cn_type_change(selected_type): cn_config = load_controlnet_config() series_choices = [] if selected_type: series_choices = sorted(list(set( model.get("Series", "Default") for model in cn_config if selected_type in model.get("Type", []) ))) default_series = series_choices[0] if series_choices else None filepath = "None" if default_series: for model in cn_config: if model.get("Series") == default_series and selected_type in model.get("Type", []): filepath = model.get("Filepath") break return gr.update(choices=series_choices, value=default_series), filepath def on_cn_series_change(selected_series, selected_type): cn_config = load_controlnet_config() filepath = "None" if selected_series and selected_type: for model in cn_config: if model.get("Series") == selected_series and selected_type in model.get("Type", []): filepath = model.get("Filepath") break return filepath for i in range(MAX_CONTROLNETS): cn_types[i].change( fn=on_cn_type_change, inputs=[cn_types[i]], outputs=[cn_series[i], cn_filepaths[i]], show_progress=False ) cn_series[i].change( fn=on_cn_series_change, inputs=[cn_series[i], cn_types[i]], outputs=[cn_filepaths[i]], show_progress=False ) def on_accordion_expand(*images): return [gr.update() for _ in images] accordion.expand( fn=on_accordion_expand, inputs=cn_images, outputs=cn_images, show_progress=False ) def create_ipadapter_event_handlers(prefix): ipa_rows = ui_components[f'ipadapter_rows_{prefix}'] ipa_lora_strengths = ui_components[f'ipadapter_lora_strengths_{prefix}'] ipa_final_preset = ui_components[f'ipadapter_final_preset_{prefix}'] ipa_final_lora_strength = ui_components[f'ipadapter_final_lora_strength_{prefix}'] count_state = ui_components[f'ipadapter_count_state_{prefix}'] add_button = ui_components[f'add_ipadapter_button_{prefix}'] del_button = ui_components[f'delete_ipadapter_button_{prefix}'] accordion = ui_components[f'ipadapter_accordion_{prefix}'] def add_ipa_row(c): c += 1 return { count_state: c, ipa_rows[c - 1]: gr.update(visible=True), add_button: gr.update(visible=c < MAX_IPADAPTERS), del_button: gr.update(visible=True), } def del_ipa_row(c): c -= 1 return { count_state: c, ipa_rows[c]: gr.update(visible=False), add_button: gr.update(visible=True), del_button: gr.update(visible=c > 0), } add_outputs = [count_state, add_button, del_button] + ipa_rows del_outputs = [count_state, add_button, del_button] + ipa_rows add_button.click(fn=add_ipa_row, inputs=[count_state], outputs=add_outputs, show_progress=False) del_button.click(fn=del_ipa_row, inputs=[count_state], outputs=del_outputs, show_progress=False) def on_preset_change(preset_value): config = load_ipadapter_config() faceid_presets = [] if isinstance(config, list): faceid_presets = [ p.get('preset_name', '') for p in config if 'FACE' in p.get('preset_name', '') or 'FACEID' in p.get('preset_name', '') ] is_visible = preset_value in faceid_presets updates = [gr.update(visible=is_visible)] * (MAX_IPADAPTERS + 1) return updates all_lora_strength_sliders = [ipa_final_lora_strength] + ipa_lora_strengths ipa_final_preset.change(fn=on_preset_change, inputs=[ipa_final_preset], outputs=all_lora_strength_sliders, show_progress=False) accordion.expand(fn=lambda *imgs: [gr.update() for _ in imgs], inputs=ui_components[f'ipadapter_images_{prefix}'], outputs=ui_components[f'ipadapter_images_{prefix}'], show_progress=False) def create_embedding_event_handlers(prefix): rows = ui_components[f'embedding_rows_{prefix}'] ids = ui_components[f'embeddings_ids_{prefix}'] files = ui_components[f'embeddings_files_{prefix}'] count_state = ui_components[f'embedding_count_state_{prefix}'] add_button = ui_components[f'add_embedding_button_{prefix}'] del_button = ui_components[f'delete_embedding_button_{prefix}'] def add_row(c): c += 1 return { count_state: c, rows[c - 1]: gr.update(visible=True), add_button: gr.update(visible=c < MAX_EMBEDDINGS), del_button: gr.update(visible=True) } def del_row(c): c -= 1 return { count_state: c, rows[c]: gr.update(visible=False), ids[c]: "", files[c]: None, add_button: gr.update(visible=True), del_button: gr.update(visible=c > 0) } add_outputs = [count_state, add_button, del_button] + rows del_outputs = [count_state, add_button, del_button] + rows + ids + files add_button.click(fn=add_row, inputs=[count_state], outputs=add_outputs, show_progress=False) del_button.click(fn=del_row, inputs=[count_state], outputs=del_outputs, show_progress=False) def create_conditioning_event_handlers(prefix): rows = ui_components[f'conditioning_rows_{prefix}'] prompts = ui_components[f'conditioning_prompts_{prefix}'] count_state = ui_components[f'conditioning_count_state_{prefix}'] add_button = ui_components[f'add_conditioning_button_{prefix}'] del_button = ui_components[f'delete_conditioning_button_{prefix}'] def add_row(c): c += 1 return { count_state: c, rows[c - 1]: gr.update(visible=True), add_button: gr.update(visible=c < MAX_CONDITIONINGS), del_button: gr.update(visible=True), } def del_row(c): c -= 1 return { count_state: c, rows[c]: gr.update(visible=False), prompts[c]: "", add_button: gr.update(visible=True), del_button: gr.update(visible=c > 0), } add_outputs = [count_state, add_button, del_button] + rows del_outputs = [count_state, add_button, del_button] + rows + prompts add_button.click(fn=add_row, inputs=[count_state], outputs=add_outputs, show_progress=False) del_button.click(fn=del_row, inputs=[count_state], outputs=del_outputs, show_progress=False) def on_vae_upload(file_obj): if not file_obj: return gr.update(), gr.update(), None hashed_filename = save_uploaded_file_with_hash(file_obj, VAE_DIR) return hashed_filename, "File", file_obj def on_lora_upload(file_obj): if not file_obj: return gr.update(), gr.update() hashed_filename = save_uploaded_file_with_hash(file_obj, LORA_DIR) return hashed_filename, "File" def on_embedding_upload(file_obj): if not file_obj: return gr.update(), gr.update(), None hashed_filename = save_uploaded_file_with_hash(file_obj, EMBEDDING_DIR) return hashed_filename, "File", file_obj def create_run_event(prefix: str, task_type: str): run_inputs_map = { 'model_display_name': ui_components[f'base_model_{prefix}'], 'positive_prompt': ui_components[f'prompt_{prefix}'], 'negative_prompt': ui_components[f'neg_prompt_{prefix}'], 'seed': ui_components[f'seed_{prefix}'], 'batch_size': ui_components[f'batch_size_{prefix}'], 'guidance_scale': ui_components[f'cfg_{prefix}'], 'num_inference_steps': ui_components[f'steps_{prefix}'], 'sampler': ui_components[f'sampler_{prefix}'], 'scheduler': ui_components[f'scheduler_{prefix}'], 'zero_gpu_duration': ui_components[f'zero_gpu_{prefix}'], 'civitai_api_key': ui_components.get(f'civitai_api_key_{prefix}'), 'clip_skip': ui_components[f'clip_skip_{prefix}'], 'task_type': gr.State(task_type) } if task_type not in ['img2img', 'inpaint']: run_inputs_map.update({'width': ui_components[f'width_{prefix}'], 'height': ui_components[f'height_{prefix}']}) task_specific_map = { 'img2img': {'img2img_image': f'input_image_{prefix}', 'img2img_denoise': f'denoise_{prefix}'}, 'inpaint': {'inpaint_image_dict': f'input_image_dict_{prefix}'}, 'outpaint': {'outpaint_image': f'input_image_{prefix}', 'outpaint_left': f'outpaint_left_{prefix}', 'outpaint_top': f'outpaint_top_{prefix}', 'outpaint_right': f'outpaint_right_{prefix}', 'outpaint_bottom': f'outpaint_bottom_{prefix}'}, 'hires_fix': {'hires_image': f'input_image_{prefix}', 'hires_upscaler': f'hires_upscaler_{prefix}', 'hires_scale_by': f'hires_scale_by_{prefix}', 'hires_denoise': f'denoise_{prefix}'} } if task_type in task_specific_map: for key, comp_name in task_specific_map[task_type].items(): run_inputs_map[key] = ui_components[comp_name] lora_data_components = ui_components.get(f'all_lora_components_flat_{prefix}', []) controlnet_data_components = ui_components.get(f'all_controlnet_components_flat_{prefix}', []) ipadapter_data_components = ui_components.get(f'all_ipadapter_components_flat_{prefix}', []) embedding_data_components = ui_components.get(f'all_embedding_components_flat_{prefix}', []) conditioning_data_components = ui_components.get(f'all_conditioning_components_flat_{prefix}', []) run_inputs_map['vae_source'] = ui_components.get(f'vae_source_{prefix}') run_inputs_map['vae_id'] = ui_components.get(f'vae_id_{prefix}') run_inputs_map['vae_file'] = ui_components.get(f'vae_file_{prefix}') input_keys = list(run_inputs_map.keys()) input_list_flat = [v for v in run_inputs_map.values() if v is not None] input_list_flat += lora_data_components + controlnet_data_components + ipadapter_data_components + embedding_data_components + conditioning_data_components def create_ui_inputs_dict(*args): valid_keys = [k for k in input_keys if run_inputs_map[k] is not None] ui_dict = dict(zip(valid_keys, args[:len(valid_keys)])) arg_idx = len(valid_keys) ui_dict['lora_data'] = list(args[arg_idx : arg_idx + len(lora_data_components)]) arg_idx += len(lora_data_components) ui_dict['controlnet_data'] = list(args[arg_idx : arg_idx + len(controlnet_data_components)]) arg_idx += len(controlnet_data_components) ui_dict['ipadapter_data'] = list(args[arg_idx : arg_idx + len(ipadapter_data_components)]) arg_idx += len(ipadapter_data_components) ui_dict['embedding_data'] = list(args[arg_idx : arg_idx + len(embedding_data_components)]) arg_idx += len(embedding_data_components) ui_dict['conditioning_data'] = list(args[arg_idx : arg_idx + len(conditioning_data_components)]) return ui_dict ui_components[f'run_{prefix}'].click( fn=lambda *args, progress=gr.Progress(track_tqdm=True): generate_image_wrapper(create_ui_inputs_dict(*args), progress), inputs=input_list_flat, outputs=[ui_components[f'result_{prefix}']] ) for prefix, task_type in [ ("txt2img", "txt2img"), ("img2img", "img2img"), ("inpaint", "inpaint"), ("outpaint", "outpaint"), ("hires_fix", "hires_fix"), ]: if f'add_lora_button_{prefix}' in ui_components: create_lora_event_handlers(prefix) lora_uploads = ui_components[f'lora_uploads_{prefix}'] lora_ids = ui_components[f'lora_ids_{prefix}'] lora_sources = ui_components[f'lora_sources_{prefix}'] for i in range(MAX_LORAS): lora_uploads[i].upload( fn=on_lora_upload, inputs=[lora_uploads[i]], outputs=[lora_ids[i], lora_sources[i]], show_progress=False ) if f'add_controlnet_button_{prefix}' in ui_components: create_controlnet_event_handlers(prefix) if f'add_ipadapter_button_{prefix}' in ui_components: create_ipadapter_event_handlers(prefix) if f'add_embedding_button_{prefix}' in ui_components: create_embedding_event_handlers(prefix) if f'embeddings_uploads_{prefix}' in ui_components: emb_uploads = ui_components[f'embeddings_uploads_{prefix}'] emb_ids = ui_components[f'embeddings_ids_{prefix}'] emb_sources = ui_components[f'embeddings_sources_{prefix}'] emb_files = ui_components[f'embeddings_files_{prefix}'] for i in range(MAX_EMBEDDINGS): emb_uploads[i].upload( fn=on_embedding_upload, inputs=[emb_uploads[i]], outputs=[emb_ids[i], emb_sources[i], emb_files[i]], show_progress=False ) if f'add_conditioning_button_{prefix}' in ui_components: create_conditioning_event_handlers(prefix) if f'vae_source_{prefix}' in ui_components: upload_button = ui_components.get(f'vae_upload_button_{prefix}') if upload_button: upload_button.upload( fn=on_vae_upload, inputs=[upload_button], outputs=[ ui_components[f'vae_id_{prefix}'], ui_components[f'vae_source_{prefix}'], ui_components[f'vae_file_{prefix}'] ] ) create_run_event(prefix, task_type) ui_components["info_get_button"].click( get_png_info, [ui_components["info_image_input"]], [ui_components["info_prompt_output"], ui_components["info_neg_prompt_output"], ui_components["info_params_output"]] ) flat_ui_list = [comp for comp_or_list in ui_components.values() for comp in (comp_or_list if isinstance(comp_or_list, list) else [comp_or_list])] ui_components["send_to_txt2img_button"].click(lambda img: send_info_by_hash(img, ui_components), [ui_components["info_image_input"]], flat_ui_list) ui_components["send_to_img2img_button"].click(lambda img: send_info_to_tab(img, "img2img", ui_components), [ui_components["info_image_input"]], flat_ui_list) ui_components["send_to_inpaint_button"].click(lambda img: send_info_to_tab(img, "inpaint", ui_components), [ui_components["info_image_input"]], flat_ui_list) ui_components["send_to_outpaint_button"].click(lambda img: send_info_to_tab(img, "outpaint", ui_components), [ui_components["info_image_input"]], flat_ui_list) ui_components["send_to_hires_fix_button"].click(lambda img: send_info_to_tab(img, "hires_fix", ui_components), [ui_components["info_image_input"]], flat_ui_list) def on_aspect_ratio_change(ratio_key, model_display_name): model_type = MODEL_TYPE_MAP.get(model_display_name, 'sdxl').lower() res_map = RESOLUTION_MAP.get(model_type, RESOLUTION_MAP.get("sdxl", {})) w, h = res_map.get(ratio_key, (1024, 1024)) return w, h for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]: if f'aspect_ratio_{prefix}' in ui_components: aspect_ratio_dropdown = ui_components[f'aspect_ratio_{prefix}'] width_component = ui_components[f'width_{prefix}'] height_component = ui_components[f'height_{prefix}'] model_dropdown = ui_components[f'base_model_{prefix}'] aspect_ratio_dropdown.change(fn=on_aspect_ratio_change, inputs=[aspect_ratio_dropdown, model_dropdown], outputs=[width_component, height_component], show_progress=False) if 'view_mode_inpaint' in ui_components: def toggle_inpaint_fullscreen_view(view_mode): is_fullscreen = (view_mode == "Fullscreen View") other_elements_visible = not is_fullscreen editor_height = 800 if is_fullscreen else 272 return { ui_components['model_and_run_row_inpaint']: gr.update(visible=other_elements_visible), ui_components['prompts_column_inpaint']: gr.update(visible=other_elements_visible), ui_components['params_and_gallery_row_inpaint']: gr.update(visible=other_elements_visible), ui_components['accordion_wrapper_inpaint']: gr.update(visible=other_elements_visible), ui_components['input_image_dict_inpaint']: gr.update(height=editor_height), } output_components = [ ui_components['model_and_run_row_inpaint'], ui_components['prompts_column_inpaint'], ui_components['params_and_gallery_row_inpaint'], ui_components['accordion_wrapper_inpaint'], ui_components['input_image_dict_inpaint'] ] ui_components['view_mode_inpaint'].change(fn=toggle_inpaint_fullscreen_view, inputs=[ui_components['view_mode_inpaint']], outputs=output_components, show_progress=False) def initialize_all_cn_dropdowns(): cn_config = load_controlnet_config() if not cn_config: return {} all_types = sorted(list(set(t for model in cn_config for t in model.get("Type", [])))) default_type = all_types[0] if all_types else None series_choices = [] if default_type: series_choices = sorted(list(set(model.get("Series", "Default") for model in cn_config if default_type in model.get("Type", [])))) default_series = series_choices[0] if series_choices else None filepath = "None" if default_series and default_type: for model in cn_config: if model.get("Series") == default_series and default_type in model.get("Type", []): filepath = model.get("Filepath") break updates = {} for prefix in ["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) for series_dd in ui_components[f'controlnet_series_{prefix}']: updates[series_dd] = gr.update(choices=series_choices, value=default_series) for filepath_state in ui_components[f'controlnet_filepaths_{prefix}']: updates[filepath_state] = filepath return updates def initialize_all_ipa_dropdowns(): config = load_ipadapter_config() if not config or not isinstance(config, list): return {} unified_presets = [] faceid_presets = [] for preset_info in config: name = preset_info.get("preset_name") if not name: continue if "FACEID" in name or "FACE" in name: faceid_presets.append(name) else: unified_presets.append(name) all_presets = unified_presets + faceid_presets default_preset = all_presets[0] if all_presets else None is_faceid_default = default_preset in faceid_presets lora_strength_update = gr.update(visible=is_faceid_default) updates = {} for prefix in ["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 updates[ui_components[f'ipadapter_final_preset_{prefix}']] = gr.update(choices=all_presets, value=default_preset) updates[ui_components[f'ipadapter_final_lora_strength_{prefix}']] = lora_strength_update return updates def run_on_load(): cn_updates = initialize_all_cn_dropdowns() ipa_updates = initialize_all_ipa_dropdowns() all_updates = {**cn_updates, **ipa_updates} default_preprocessor = "Canny Edge" model_update = update_preprocessor_models_dropdown(default_preprocessor) all_updates[ui_components["preprocessor_model_cn"]] = model_update settings_outputs = update_preprocessor_settings_ui(default_preprocessor) dynamic_outputs = ui_components["cn_sliders"] + ui_components["cn_dropdowns"] + ui_components["cn_checkboxes"] for i, comp in enumerate(dynamic_outputs): all_updates[comp] = settings_outputs[i] run_button_update, zero_gpu_update = update_run_button_for_cpu(default_preprocessor) all_updates[ui_components["run_cn"]] = run_button_update all_updates[ui_components["zero_gpu_cn"]] = zero_gpu_update return all_updates all_load_outputs = [] for prefix in ["txt2img", "img2img", "inpaint", "outpaint", "hires_fix"]: 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}']) all_load_outputs.extend(ui_components[f'controlnet_filepaths_{prefix}']) if f'ipadapter_final_preset_{prefix}' in ui_components: all_load_outputs.extend(ui_components[f'ipadapter_lora_strengths_{prefix}']) all_load_outputs.append(ui_components[f'ipadapter_final_preset_{prefix}']) all_load_outputs.append(ui_components[f'ipadapter_final_lora_strength_{prefix}']) all_load_outputs.extend([ ui_components["preprocessor_model_cn"], *ui_components["cn_sliders"], *ui_components["cn_dropdowns"], *ui_components["cn_checkboxes"], ui_components["run_cn"], ui_components["zero_gpu_cn"] ]) demo.load( fn=run_on_load, outputs=all_load_outputs )