"""Event wiring for the unified ImageGen Studio workspace.""" from __future__ import annotations import gradio as gr from ui.guidance import model_hint, recommended_params, task_help from .chain_handlers import ( create_anima_controlnet_lllite_event_handlers, create_boogu_edit_event_handlers, create_conditioning_event_handlers, create_controlnet_event_handlers, create_diffsynth_controlnet_event_handlers, create_embedding_event_handlers, create_flux1_ipadapter_event_handlers, create_hidream_o1_reference_event_handlers, create_ipadapter_event_handlers, create_joyai_reference_event_handlers, create_krea2_controlnet_event_handlers, create_krea2_identity_edit_event_handlers, create_krea2_reference_edit_event_handlers, create_lora_event_handlers, create_qwen_image_edit_event_handlers, create_reference_image_event_handlers, create_reference_latent_event_handlers, create_sd3_ipadapter_event_handlers, create_style_event_handlers, ) from .change_handlers import ( make_model_change_fn, make_update_fn, on_aspect_ratio_change, run_on_load, ) from .run_handlers import create_run_event, create_unified_run_event CHAIN_EVENT_FACTORIES = ( create_lora_event_handlers, create_controlnet_event_handlers, create_anima_controlnet_lllite_event_handlers, create_diffsynth_controlnet_event_handlers, create_krea2_controlnet_event_handlers, create_ipadapter_event_handlers, create_embedding_event_handlers, create_conditioning_event_handlers, create_flux1_ipadapter_event_handlers, create_sd3_ipadapter_event_handlers, create_style_event_handlers, create_reference_latent_event_handlers, create_hidream_o1_reference_event_handlers, create_joyai_reference_event_handlers, create_krea2_identity_edit_event_handlers, create_krea2_reference_edit_event_handlers, create_qwen_image_edit_event_handlers, create_boogu_edit_event_handlers, create_reference_image_event_handlers, ) def _append_if(target, component): if component is not None: target.append(component) def _task_switch_values(task_type): uses_source = task_type in {"img2img", "outpaint", "hires_fix"} labels = { "img2img": "源图片（图生图）", "outpaint": "源图片（扩图）", "hires_fix": "源图片（高清修复）", } run_labels = { "txt2img": "开始生成", "img2img": "开始重绘", "inpaint": "开始局部重绘", "outpaint": "开始扩图", "hires_fix": "开始高清修复", } return ( task_help(task_type), gr.update(visible=uses_source), gr.update(label=labels.get(task_type, "源图片")), gr.update(visible=task_type == "inpaint"), gr.update(visible=task_type == "img2img"), gr.update(visible=task_type == "outpaint"), gr.update(visible=task_type == "hires_fix"), gr.update(visible=task_type == "txt2img"), gr.update(value=run_labels.get(task_type, "开始生成")), ) def _select_quick_preset(preset): if preset == "__manual__": return gr.update() return gr.update(value=preset) def _prefixes(ui_components): return ui_components.get( "_task_prefixes", [ ("txt2img", "txt2img"), ("img2img", "img2img"), ("inpaint", "inpaint"), ("outpaint", "outpaint"), ("hires_fix", "hires_fix"), ], ) def attach_event_handlers(ui_components, demo): task_prefixes = _prefixes(ui_components) for prefix, task_type in task_prefixes: arch_comp = ui_components.get(f"model_arch_{prefix}") cat_comp = ui_components.get(f"model_cat_{prefix}") model_comp = ui_components.get(f"base_model_{prefix}") clip_skip_comp = ui_components.get(f"clip_skip_{prefix}") or ui_components.get(f"{prefix}_clip_skip") guidance_comp = ui_components.get(f"guidance_{prefix}") or ui_components.get(f"{prefix}_guidance") aspect_ratio_comp = ui_components.get(f"aspect_ratio_{prefix}") or ui_components.get(f"{prefix}_aspect_ratio_dropdown") width_comp = ui_components.get(f"width_{prefix}") or ui_components.get(f"{prefix}_width") height_comp = ui_components.get(f"height_{prefix}") or ui_components.get(f"{prefix}_height") cn_types = ui_components.get(f"controlnet_types_{prefix}", []) cn_series = ui_components.get(f"controlnet_series_{prefix}", []) cn_filepaths = ui_components.get(f"controlnet_filepaths_{prefix}", []) anima_types = ui_components.get(f"anima_controlnet_lllite_types_{prefix}", []) anima_series = ui_components.get(f"anima_controlnet_lllite_series_{prefix}", []) anima_filepaths = ui_components.get(f"anima_controlnet_lllite_filepaths_{prefix}", []) diffsynth_types = ui_components.get(f"diffsynth_controlnet_types_{prefix}", []) diffsynth_series = ui_components.get(f"diffsynth_controlnet_series_{prefix}", []) diffsynth_filepaths = ui_components.get(f"diffsynth_controlnet_filepaths_{prefix}", []) krea2_types = ui_components.get(f"krea2_controlnet_types_{prefix}", []) krea2_series = ui_components.get(f"krea2_controlnet_series_{prefix}", []) krea2_filepaths = ui_components.get(f"krea2_controlnet_filepaths_{prefix}", []) accordion_names = { "lora": "lora_accordion", "cn": "controlnet_accordion", "anima": "anima_controlnet_lllite_accordion", "diffsynth": "diffsynth_controlnet_accordion", "krea2": "krea2_controlnet_accordion", "ipa": "ipadapter_accordion", "sd3_ipa": "sd3_ipadapter_accordion", "flux1_ipa": "flux1_ipadapter_accordion", "style": "style_accordion", "embed": "embedding_accordion", "cond": "conditioning_accordion", "ref_latent": "reference_latent_accordion", "hidream": "hidream_o1_reference_accordion", "joyai": "joyai_reference_accordion", "krea2_identity": "krea2_identity_edit_accordion", "krea2_reference": "krea2_reference_edit_accordion", "qwen_edit": "qwen_image_edit_accordion", "boogu": "boogu_edit_accordion", "ref_img": "reference_image_accordion", "pid": "pid_accordion", "vae": "vae_accordion", } acc = { key: ui_components.get(f"{component_name}_{prefix}") for key, component_name in accordion_names.items() } ipa_preset = ui_components.get(f"ipadapter_final_preset_{prefix}") prompt_comp = ui_components.get(f"prompt_{prefix}") or ui_components.get(f"{prefix}_positive_prompt") neg_prompt_comp = ui_components.get(f"neg_prompt_{prefix}") or ui_components.get(f"{prefix}_negative_prompt") steps_comp = ui_components.get(f"steps_{prefix}") or ui_components.get(f"{prefix}_steps") cfg_comp = ui_components.get(f"cfg_{prefix}") or ui_components.get(f"{prefix}_cfg") sampler_comp = ui_components.get(f"sampler_{prefix}") or ui_components.get(f"{prefix}_sampler_name") scheduler_comp = ui_components.get(f"scheduler_{prefix}") or ui_components.get(f"{prefix}_scheduler") auto_params_comp = ui_components.get(f"auto_model_params_{prefix}") parameter_outputs = [ item for item in ( prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, width_comp, height_comp, ) if item is not None ] if arch_comp is not None and cat_comp is not None and model_comp is not None: filter_outputs = [model_comp, cat_comp] for component in (clip_skip_comp, guidance_comp, aspect_ratio_comp): _append_if(filter_outputs, component) filter_outputs.extend( cn_types + cn_series + cn_filepaths + anima_types + anima_series + anima_filepaths + diffsynth_types + diffsynth_series + diffsynth_filepaths + krea2_types + krea2_series + krea2_filepaths ) for component in acc.values(): _append_if(filter_outputs, component) _append_if(filter_outputs, ipa_preset) filter_outputs.extend(parameter_outputs) filter_fn = make_update_fn( model_comp, cat_comp, clip_skip_comp, aspect_ratio_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_types, anima_series, anima_filepaths, diffsynth_types, diffsynth_series, diffsynth_filepaths, krea2_types, krea2_series, krea2_filepaths, ipa_preset, acc["lora"], acc["cn"], acc["anima"], acc["diffsynth"], acc["krea2"], acc["ipa"], acc["sd3_ipa"], acc["flux1_ipa"], acc["style"], acc["embed"], acc["cond"], acc["ref_latent"], acc["hidream"], guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=acc["pid"], vae_acc=acc["vae"], joyai_ref_acc=acc["joyai"], krea2_identity_edit_acc=acc["krea2_identity"], krea2_reference_edit_acc=acc["krea2_reference"], qwen_image_edit_acc=acc["qwen_edit"], boogu_edit_acc=acc["boogu"], ref_img_acc=acc["ref_img"], auto_params_comp=auto_params_comp, ) filter_inputs = [arch_comp, cat_comp, model_comp] if aspect_ratio_comp is not None: filter_inputs.append(aspect_ratio_comp) if auto_params_comp is not None: filter_inputs.append(auto_params_comp) arch_comp.change(filter_fn, filter_inputs, filter_outputs, show_progress="hidden") cat_comp.change(filter_fn, filter_inputs, filter_outputs, show_progress="hidden") if model_comp is not None: model_outputs = [] for component in (arch_comp, cat_comp, clip_skip_comp, guidance_comp, aspect_ratio_comp): _append_if(model_outputs, component) model_outputs.extend( cn_types + cn_series + cn_filepaths + anima_types + anima_series + anima_filepaths + diffsynth_types + diffsynth_series + diffsynth_filepaths + krea2_types + krea2_series + krea2_filepaths ) for component in acc.values(): _append_if(model_outputs, component) _append_if(model_outputs, ipa_preset) model_outputs.extend(parameter_outputs) model_inputs = [model_comp] for component in (arch_comp, cat_comp, aspect_ratio_comp): _append_if(model_inputs, component) _append_if(model_inputs, auto_params_comp) model_fn = make_model_change_fn( cat_comp, clip_skip_comp, aspect_ratio_comp, width_comp, height_comp, cn_types, cn_series, cn_filepaths, anima_types, anima_series, anima_filepaths, diffsynth_types, diffsynth_series, diffsynth_filepaths, krea2_types, krea2_series, krea2_filepaths, arch_comp, ipa_preset, acc["lora"], acc["cn"], acc["anima"], acc["diffsynth"], acc["krea2"], acc["ipa"], acc["sd3_ipa"], acc["flux1_ipa"], acc["style"], acc["embed"], acc["cond"], acc["ref_latent"], acc["hidream"], guidance_comp, prompt_comp, neg_prompt_comp, steps_comp, cfg_comp, sampler_comp, scheduler_comp, pid_acc=acc["pid"], vae_acc=acc["vae"], joyai_ref_acc=acc["joyai"], krea2_identity_edit_acc=acc["krea2_identity"], krea2_reference_edit_acc=acc["krea2_reference"], qwen_image_edit_acc=acc["qwen_edit"], boogu_edit_acc=acc["boogu"], ref_img_acc=acc["ref_img"], auto_params_comp=auto_params_comp, ) model_comp.change(model_fn, model_inputs, model_outputs, show_progress="hidden") for factory in CHAIN_EVENT_FACTORIES: factory(prefix, ui_components) if task_type is None: create_unified_run_event(prefix, ui_components) else: create_run_event(prefix, task_type, ui_components) if all(component is not None for component in (aspect_ratio_comp, width_comp, height_comp, model_comp)): aspect_ratio_comp.change( on_aspect_ratio_change, [aspect_ratio_comp, model_comp], [width_comp, height_comp], show_progress="hidden", api_name=False, show_api=False, ) if task_type is None: task_component = ui_components[f"task_type_{prefix}"] task_component.change( _task_switch_values, [task_component], [ ui_components[f"task_help_{prefix}"], ui_components[f"source_panel_{prefix}"], ui_components[f"source_image_{prefix}"], ui_components[f"inpaint_panel_{prefix}"], ui_components[f"img2img_panel_{prefix}"], ui_components[f"outpaint_panel_{prefix}"], ui_components[f"hires_panel_{prefix}"], ui_components[f"size_panel_{prefix}"], ui_components[f"run_{prefix}"], ], show_progress="hidden", api_name=False, show_api=False, ) preset = ui_components[f"quick_preset_{prefix}"] preset.change( _select_quick_preset, [preset], [model_comp], show_progress="hidden", api_name=False, show_api=False, ) model_comp.input( lambda: "__manual__", outputs=[preset], show_progress="hidden", api_name=False, show_api=False, ) model_comp.change( model_hint, [model_comp], [ui_components[f"model_hint_{prefix}"]], show_progress="hidden", api_name=False, show_api=False, ) ui_components[f"reset_model_params_{prefix}"].click( recommended_params, [model_comp], [steps_comp, cfg_comp, sampler_comp, scheduler_comp], show_progress="hidden", api_name=False, show_api=False, ) load_outputs = [] for prefix, _ in task_prefixes: for base_name in ( "controlnet_types", "controlnet_series", "controlnet_filepaths", "anima_controlnet_lllite_types", "anima_controlnet_lllite_series", "anima_controlnet_lllite_filepaths", "diffsynth_controlnet_types", "diffsynth_controlnet_series", "diffsynth_controlnet_filepaths", "krea2_controlnet_types", "krea2_controlnet_series", "krea2_controlnet_filepaths", ): load_outputs.extend(ui_components.get(f"{base_name}_{prefix}", [])) if f"ipadapter_final_preset_{prefix}" in ui_components: load_outputs.extend(ui_components.get(f"ipadapter_lora_strengths_{prefix}", [])) load_outputs.append(ui_components[f"ipadapter_final_preset_{prefix}"]) load_outputs.append(ui_components[f"ipadapter_final_lora_strength_{prefix}"]) if load_outputs: demo.load( lambda: run_on_load(ui_components), outputs=load_outputs, show_progress="hidden", api_name=False, show_api=False, )