ui/events.py

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_EMBEDDINGS, MAX_CONDITIONINGS, MAX_LORAS, MAX_REFERENCE_LATENTS


def on_model_change(model_display_name):
    """

    Callback function to update UI elements when the base model changes.

    It loads default values for steps and cfg from model_defaults.yaml.

    """
    defaults = ALL_MODEL_DEFAULTS.get('Default', {}).copy()
    
    model_found = False
    for category, models_in_category in ALL_MODEL_DEFAULTS.items():
        if category == 'Default' or not isinstance(models_in_category, dict):
            continue
            
        if model_display_name in models_in_category:
            if '_defaults' in models_in_category:
                defaults.update(models_in_category['_defaults'])
            defaults.update(models_in_category[model_display_name])
            model_found = True
            break
    
    if not model_found:
        print(f"No specific defaults found for '{model_display_name}'. Using category or global defaults.")

    steps_update = gr.update(value=defaults.get('steps'))
    cfg_update = gr.update(value=defaults.get('cfg'))
    
    return steps_update, cfg_update

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_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 create_reference_latent_event_handlers(prefix):
        rows = ui_components[f'reference_latent_rows_{prefix}']
        images = ui_components[f'reference_latent_images_{prefix}']
        count_state = ui_components[f'reference_latent_count_state_{prefix}']
        add_button = ui_components[f'add_reference_latent_button_{prefix}']
        del_button = ui_components[f'delete_reference_latent_button_{prefix}']

        def add_row(c):
            c += 1
            return {
                count_state: c,
                rows[c - 1]: gr.update(visible=True),
                add_button: gr.update(visible=c < MAX_REFERENCE_LATENTS),
                del_button: gr.update(visible=True),
            }

        def del_row(c):
            c -= 1
            return {
                count_state: c,
                rows[c]: gr.update(visible=False),
                images[c]: None,
                add_button: gr.update(visible=True),
                del_button: gr.update(visible=c > 0),
            }

        add_outputs = [count_state, add_button, del_button] + rows
        del_outputs = [count_state, add_button, del_button] + rows + images
        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}', [])
        embedding_data_components = ui_components.get(f'all_embedding_components_flat_{prefix}', [])
        conditioning_data_components = ui_components.get(f'all_conditioning_components_flat_{prefix}', [])
        reference_latent_components = ui_components.get(f'all_reference_latent_components_flat_{prefix}', [])
        
        run_inputs_map['vae_source'] = ui_components.get(f'vae_source_{prefix}')
        run_inputs_map['vae_id'] = ui_components.get(f'vae_id_{prefix}')
        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 + embedding_data_components + conditioning_data_components + reference_latent_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['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)])
            arg_idx += len(conditioning_data_components)
            ui_dict['reference_latent_data'] = list(args[arg_idx : arg_idx + len(reference_latent_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"),
    ]:
        model_dropdown = ui_components.get(f'base_model_{prefix}')
        steps_slider = ui_components.get(f'steps_{prefix}')
        cfg_slider = ui_components.get(f'cfg_{prefix}')
        if all([model_dropdown, steps_slider, cfg_slider]):
            model_dropdown.change(
                fn=on_model_change,
                inputs=[model_dropdown],
                outputs=[steps_slider, cfg_slider],
                show_progress=False
            )

        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_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'add_reference_latent_button_{prefix}' in ui_components: create_reference_latent_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)

    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 run_on_load():
        all_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 = [
        ui_components["preprocessor_model_cn"],
        *ui_components["cn_sliders"],
        *ui_components["cn_dropdowns"],
        *ui_components["cn_checkboxes"],
        ui_components["run_cn"],
        ui_components["zero_gpu_cn"]
    ]

    if all_load_outputs:
        demo.load(
            fn=run_on_load,
            outputs=all_load_outputs
        )