Update app.py

app.py

@@ -8,6 +8,7 @@ from stablepy import (
     check_scheduler_compatibility,
     TASK_AND_PREPROCESSORS,
     FACE_RESTORATION_MODELS,
+    PROMPT_WEIGHT_OPTIONS_PRIORITY,
     scheduler_names,
 )
 from constants import (
@@ -376,7 +377,7 @@ class GuiSD:
         t2i_adapter_preprocessor,
         t2i_adapter_conditioning_scale,
         t2i_adapter_conditioning_factor,
-        xformers_memory_efficient_attention,
+        enable_live_preview,
         freeu,
         generator_in_cpu,
         adetailer_inpaint_only,
@@ -544,7 +545,7 @@ class GuiSD:
             "sampler": sampler,
             "schedule_type": schedule_type,
             "schedule_prediction_type": schedule_prediction_type,
-            "xformers_memory_efficient_attention": xformers_memory_efficient_attention,
+            "xformers_memory_efficient_attention": False,
             "gui_active": True,
             "loop_generation": loop_generation,
             "controlnet_conditioning_scale": float(controlnet_output_scaling_in_unet),
@@ -559,7 +560,7 @@ class GuiSD:
             "leave_progress_bar": leave_progress_bar,
             "disable_progress_bar": disable_progress_bar,
             "image_previews": image_previews,
-            "display_images": display_images,
+            "display_images": False,
             "save_generated_images": save_generated_images,
             "filename_pattern": filename_pattern,
             "image_storage_location": image_storage_location,
@@ -636,8 +637,13 @@ class GuiSD:
                 if save_generated_images:
                     info_images += f"<br>{download_links}"
 
+                if not display_images:
+                    img = gr.update()
                 info_state = "COMPLETE"
 
+            elif not enable_live_preview:
+                img = gr.update()
+
             yield info_state, img, info_images
 
 
@@ -785,10 +791,14 @@ with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False) as
 
                     return gr.update(value=task_name, choices=new_choices)
 
-                task_gui = gr.Dropdown(label="Task", choices=SDXL_TASK, value=TASK_MODEL_LIST[0])
-                model_name_gui = gr.Dropdown(label="Model", choices=model_list, value=model_list[0], allow_custom_value=True)
+                with gr.Accordion("Model and Task", open=True, visible=True):
+                    task_gui = gr.Dropdown(label="Task", choices=SDXL_TASK, value=TASK_MODEL_LIST[0])
+                    model_name_gui = gr.Dropdown(label="Model", choices=model_list, value=model_list[0], allow_custom_value=True)
                 prompt_gui = gr.Textbox(lines=5, placeholder="Enter prompt", label="Prompt")
-                neg_prompt_gui = gr.Textbox(lines=3, placeholder="Enter Neg prompt", label="Negative prompt", value="lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, worst quality, low quality, very displeasing, (bad)")
+
+                with gr.Accordion("Negative prompt", open=False, visible=True):
+                    neg_prompt_gui = gr.Textbox(lines=3, placeholder="Enter Neg prompt", label="Negative prompt", value="bad anatomy, ((many hands, bad hands, missing fingers)), anatomical nonsense, ugly, deformed, bad proportions, bad shadow, extra limbs, missing limbs, floating limbs, disconnected limbs, malformed hands, poorly drawn, mutation, mutated hands and fingers, extra legs, interlocked fingers, extra arms, disfigured face, long neck, asymmetrical eyes, lowres, extra digit, fewer digits, cropped, jpeg artifacts, signature, watermark, username, blurry, duplicate, bad composition, text, worst quality, normal quality, low quality, very displeasing, monochrome, grayscale, black and white, desaturated, low contrast, muted tones, washed out, unfinished, incomplete, draft, logo, backlighting")
+                
                 with gr.Row(equal_height=False):
                     set_params_gui = gr.Button(value="↙️", variant="secondary", size="sm")
                     clear_prompt_gui = gr.Button(value="🗑️", variant="secondary", size="sm")
@@ -825,158 +835,166 @@ with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False) as
                         load_lora_cpu_gui = gr.Checkbox(value=False, container=False, label="Load LoRAs on CPU")
 
             with gr.Column(scale=1):
-                steps_gui = gr.Slider(minimum=1, maximum=100, step=1, value=28, label="Steps")
-                cfg_gui = gr.Slider(minimum=0, maximum=30, step=0.5, value=7., label="CFG")
-                sampler_gui = gr.Dropdown(label="Sampler", choices=scheduler_names, value="Euler")
-                schedule_type_gui = gr.Dropdown(label="Schedule type", choices=SCHEDULE_TYPE_OPTIONS, value=SCHEDULE_TYPE_OPTIONS[0])
-                img_width_gui = gr.Slider(minimum=64, maximum=4096, step=8, value=1024, label="Img Width")
-                img_height_gui = gr.Slider(minimum=64, maximum=4096, step=8, value=1024, label="Img Height")
-                seed_gui = gr.Number(minimum=-1, maximum=9999999999, value=-1, label="Seed")
-                pag_scale_gui = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=0.0, label="PAG Scale")
-                with gr.Row():
-                    clip_skip_gui = gr.Checkbox(value=True, label="Layer 2 Clip Skip")
-                    free_u_gui = gr.Checkbox(value=False, label="FreeU")
-
-                with gr.Row(equal_height=False):
-
-                    def run_set_params_gui(base_prompt, name_model):
-                        valid_receptors = {  # default values
-                            "prompt": gr.update(value=base_prompt),
-                            "neg_prompt": gr.update(value=""),
-                            "Steps": gr.update(value=30),
-                            "width": gr.update(value=1024),
-                            "height": gr.update(value=1024),
-                            "Seed": gr.update(value=-1),
-                            "Sampler": gr.update(value="Euler"),
-                            "CFG scale": gr.update(value=7.),  # cfg
-                            "Clip skip": gr.update(value=True),
-                            "Model": gr.update(value=name_model),
-                            "Schedule type": gr.update(value="Automatic"),
-                            "PAG": gr.update(value=.0),
-                            "FreeU": gr.update(value=False),
-                            "Hires upscaler": gr.update(),
-                            "Hires upscale": gr.update(),
-                            "Hires steps": gr.update(),
-                            "Hires denoising strength": gr.update(),
-                            "Hires CFG": gr.update(),
-                            "Hires sampler": gr.update(),
-                            "Hires schedule type": gr.update(),
-                            "Image resolution": gr.update(value=1024),
-                            "Strength": gr.update(),
-                        }
-
-                        # Generate up to 7 LoRAs
-                        for i in range(1, 8):
-                            valid_receptors[f"Lora_{i}"] = gr.update()
-                            valid_receptors[f"Lora_scale_{i}"] = gr.update()
-
-                        valid_keys = list(valid_receptors.keys())
-
-                        parameters = extract_parameters(base_prompt)
-                        # print(parameters)
-
-                        if "Sampler" in parameters:
-                            value_sampler = parameters["Sampler"]
-                            for s_type in SCHEDULE_TYPE_OPTIONS:
-                                if s_type in value_sampler:
-                                    value_sampler = value_sampler.replace(s_type, "").strip()
-                                    parameters["Sampler"] = value_sampler
-                                    parameters["Schedule type"] = s_type
-
-                        params_lora = []
-                        if ">" in parameters["prompt"] and "<" in parameters["prompt"]:
-                            params_lora = re.findall(r'<lora:[^>]+>', parameters["prompt"])
-                        if "Loras" in parameters:
-                            params_lora += re.findall(r'<lora:[^>]+>', parameters["Loras"])
-
-                        if params_lora:
-                            parsed_params = []
-                            for tag_l in params_lora:
-                                try:
-                                    inner = tag_l.strip("<>")        # remove < >
-                                    _, data_l = inner.split(":", 1)  # remove the "lora:" part
-                                    parts_l = data_l.split(":")
-
-                                    name_l = parts_l[0]
-                                    weight_l = float(parts_l[1]) if len(parts_l) > 1 else 1.0  # default weight = 1.0
-
-                                    parsed_params.append((name_l, weight_l))
-                                except Exception as e:
-                                    print(f"Error parsing LoRA tag {tag_l}: {e}")
-
-                            num_lora = 1
-                            for parsed_l, parsed_s in parsed_params:
-                                filtered_loras = [m for m in lora_model_list if parsed_l in m]
-                                if filtered_loras:
-                                    parameters[f"Lora_{num_lora}"] = filtered_loras[0]
-                                    parameters[f"Lora_scale_{num_lora}"] = parsed_s
-                                    num_lora += 1
-
-                        # continue = discard new value
-                        for key, val in parameters.items():
-                            # print(val)
-                            if key in valid_keys:
-                                try:
-                                    if key == "Sampler":
-                                        if val not in scheduler_names:
-                                            continue
-                                    if key in ["Schedule type", "Hires schedule type"]:
-                                        if val not in SCHEDULE_TYPE_OPTIONS:
-                                            continue
-                                    if key == "Hires sampler":
-                                        if val not in POST_PROCESSING_SAMPLER:
-                                            continue
-                                    elif key == "Clip skip":
-                                        if "," in str(val):
-                                            val = val.replace(",", "")
-                                        if int(val) >= 2:
-                                            val = True
-                                    if key == "prompt":
-                                        if ">" in val and "<" in val:
-                                            val = re.sub(r'<[^>]+>', '', val)  # Delete html and loras
-                                            print("Removed LoRA written in the prompt")
-                                    if key in ["prompt", "neg_prompt"]:
-                                        val = re.sub(r'\s+', ' ', re.sub(r',+', ',', val)).strip()
-                                    if key in ["Steps", "width", "height", "Seed", "Hires steps", "Image resolution"]:
-                                        val = int(val)
-                                    if key == "FreeU":
+                with gr.Accordion("Generation settings", open=True, visible=True):
+                    steps_gui = gr.Slider(minimum=1, maximum=100, step=1, value=30, label="Steps")
+                    cfg_gui = gr.Slider(minimum=0, maximum=30, step=0.5, value=7., label="CFG")
+                    sampler_gui = gr.Dropdown(label="Sampler", choices=scheduler_names, value="Euler")
+                    schedule_type_gui = gr.Dropdown(label="Schedule type", choices=SCHEDULE_TYPE_OPTIONS, value=SCHEDULE_TYPE_OPTIONS[0])
+                    img_width_gui = gr.Slider(minimum=64, maximum=4096, step=8, value=832, label="Img Width")
+                    img_height_gui = gr.Slider(minimum=64, maximum=4096, step=8, value=1216, label="Img Height")
+                    seed_gui = gr.Number(minimum=-1, maximum=9999999999, value=-1, label="Seed")
+                    pag_scale_gui = gr.Slider(minimum=0.0, maximum=10.0, step=0.1, value=0.0, label="PAG Scale")
+                    with gr.Row():
+                        clip_skip_gui = gr.Checkbox(value=True, label="Layer 2 Clip Skip")
+                        free_u_gui = gr.Checkbox(value=True, label="FreeU")
+
+                    with gr.Row(equal_height=False):
+                        num_images_gui = gr.Slider(minimum=1, maximum=(16 if IS_ZERO_GPU else 20), step=1, value=1, label="Images")
+                        prompt_syntax_gui = gr.Dropdown(label="Prompt Syntax", choices=PROMPT_W_OPTIONS, value=PROMPT_W_OPTIONS[2][1])
+                        vae_model_gui = gr.Dropdown(label="VAE Model", choices=vae_model_list, value=vae_model_list[0])
+
+                
+                def run_set_params_gui(base_prompt, name_model):
+                    valid_receptors = {  # default values
+                        "prompt": gr.update(value=base_prompt),
+                        "neg_prompt": gr.update(value=""),
+                        "Steps": gr.update(value=30),
+                        "width": gr.update(value=1024),
+                        "height": gr.update(value=1024),
+                        "Seed": gr.update(value=-1),
+                        "Sampler": gr.update(value="Euler"),
+                        "CFG scale": gr.update(value=7.),  # cfg
+                        "Clip skip": gr.update(value=True),
+                        "Model": gr.update(value=name_model),
+                        "Schedule type": gr.update(value="Automatic"),
+                        "PAG": gr.update(value=.0),
+                        "FreeU": gr.update(value=False),
+                        "Hires upscaler": gr.update(),
+                        "Hires upscale": gr.update(),
+                        "Hires steps": gr.update(),
+                        "Hires denoising strength": gr.update(),
+                        "Hires CFG": gr.update(),
+                        "Hires sampler": gr.update(),
+                        "Hires schedule type": gr.update(),
+                        "Image resolution": gr.update(value=1024),
+                        "Strength": gr.update(),
+                        "Prompt emphasis": gr.update(),
+                    }
+
+                    # Generate up to 7 LoRAs
+                    for i in range(1, 8):
+                        valid_receptors[f"Lora_{i}"] = gr.update()
+                        valid_receptors[f"Lora_scale_{i}"] = gr.update()
+
+                    valid_keys = list(valid_receptors.keys())
+
+                    parameters = extract_parameters(base_prompt)
+                    # print(parameters)
+
+                    if "Sampler" in parameters:
+                        value_sampler = parameters["Sampler"]
+                        for s_type in SCHEDULE_TYPE_OPTIONS:
+                            if s_type in value_sampler:
+                                value_sampler = value_sampler.replace(s_type, "").strip()
+                                parameters["Sampler"] = value_sampler
+                                parameters["Schedule type"] = s_type
+
+                    params_lora = []
+                    if ">" in parameters["prompt"] and "<" in parameters["prompt"]:
+                        params_lora = re.findall(r'<lora:[^>]+>', parameters["prompt"])
+                    if "Loras" in parameters:
+                        params_lora += re.findall(r'<lora:[^>]+>', parameters["Loras"])
+
+                    if params_lora:
+                        parsed_params = []
+                        for tag_l in params_lora:
+                            try:
+                                inner = tag_l.strip("<>")        # remove < >
+                                _, data_l = inner.split(":", 1)  # remove the "lora:" part
+                                parts_l = data_l.split(":")
+
+                                name_l = parts_l[0]
+                                weight_l = float(parts_l[1]) if len(parts_l) > 1 else 1.0  # default weight = 1.0
+
+                                parsed_params.append((name_l, weight_l))
+                            except Exception as e:
+                                print(f"Error parsing LoRA tag {tag_l}: {e}")
+
+                        new_lora_model_list = get_model_list(DIRECTORY_LORAS)
+                        new_lora_model_list.insert(0, "None")
+
+                        num_lora = 1
+                        for parsed_l, parsed_s in parsed_params:
+                            filtered_loras = [m for m in new_lora_model_list if parsed_l in m]
+                            if filtered_loras:
+                                parameters[f"Lora_{num_lora}"] = filtered_loras[0]
+                                parameters[f"Lora_scale_{num_lora}"] = parsed_s
+                                num_lora += 1
+
+                    # continue = discard new value
+                    for key, val in parameters.items():
+                        # print(val)
+                        if key in valid_keys:
+                            try:
+                                if key == "Sampler":
+                                    if val not in scheduler_names:
+                                        continue
+                                if key in ["Schedule type", "Hires schedule type"]:
+                                    if val not in SCHEDULE_TYPE_OPTIONS:
+                                        continue
+                                if key == "Hires sampler":
+                                    if val not in POST_PROCESSING_SAMPLER:
+                                        continue
+                                if key == "Prompt emphasis":
+                                    if val not in PROMPT_WEIGHT_OPTIONS_PRIORITY:
+                                        continue
+                                elif key == "Clip skip":
+                                    if "," in str(val):
+                                        val = val.replace(",", "")
+                                    if int(val) >= 2:
                                         val = True
-                                    if key in ["CFG scale", "PAG", "Hires upscale", "Hires denoising strength", "Hires CFG", "Strength"]:
-                                        val = float(val)
-                                    if key == "Model":
-                                        filtered_models = [m for m in model_list if val in m]
-                                        if filtered_models:
-                                            val = filtered_models[0]
-                                        else:
-                                            val = name_model
-                                    if key == "Hires upscaler":
-                                        if val not in UPSCALER_KEYS:
-                                            continue
-                                    if key == "Seed":
+                                if key == "prompt":
+                                    if ">" in val and "<" in val:
+                                        val = re.sub(r'<[^>]+>', '', val)  # Delete html and loras
+                                        print("Removed LoRA written in the prompt")
+                                if key in ["prompt", "neg_prompt"]:
+                                    val = re.sub(r'\s+', ' ', re.sub(r',+', ',', val)).strip()
+                                if key in ["Steps", "width", "height", "Seed", "Hires steps", "Image resolution"]:
+                                    val = int(val)
+                                if key == "FreeU":
+                                    val = True
+                                if key in ["CFG scale", "PAG", "Hires upscale", "Hires denoising strength", "Hires CFG", "Strength"]:
+                                    val = float(val)
+                                if key == "Model":
+                                    filtered_models = [m for m in model_list if val in m]
+                                    if filtered_models:
+                                        val = filtered_models[0]
+                                    else:
+                                        val = name_model
+                                if key == "Hires upscaler":
+                                    if val not in UPSCALER_KEYS:
                                         continue
+                                if key == "Seed":
+                                    continue
+
+                                valid_receptors[key] = gr.update(value=val)
+                                # print(val, type(val))
+                                # print(valid_receptors)
+                            except Exception as e:
+                                print(str(e))
+                    return [value for value in valid_receptors.values()]
+
+                def run_clear_prompt_gui():
+                    return gr.update(value=""), gr.update(value="")
+                clear_prompt_gui.click(
+                    run_clear_prompt_gui, [], [prompt_gui, neg_prompt_gui]
+                )
 
-                                    valid_receptors[key] = gr.update(value=val)
-                                    # print(val, type(val))
-                                    # print(valid_receptors)
-                                except Exception as e:
-                                    print(str(e))
-                        return [value for value in valid_receptors.values()]
-
-                    def run_clear_prompt_gui():
-                        return gr.update(value=""), gr.update(value="")
-                    clear_prompt_gui.click(
-                        run_clear_prompt_gui, [], [prompt_gui, neg_prompt_gui]
-                    )
-
-                    def run_set_random_seed():
-                        return -1
-                    set_random_seed.click(
-                        run_set_random_seed, [], seed_gui
-                    )
-
-                num_images_gui = gr.Slider(minimum=1, maximum=(8 if IS_ZERO_GPU else 20), step=1, value=1, label="Images")
-                prompt_syntax_gui = gr.Dropdown(label="Prompt Syntax", choices=PROMPT_W_OPTIONS, value=PROMPT_W_OPTIONS[0][1])
-                vae_model_gui = gr.Dropdown(label="VAE Model", choices=vae_model_list, value=vae_model_list[0])
+                def run_set_random_seed():
+                    return -1
+                set_random_seed.click(
+                    run_set_random_seed, [], seed_gui
+                )
 
                 with gr.Accordion("Hires fix", open=False, visible=True):
 
@@ -1012,10 +1030,10 @@ with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False) as
                     lora_scale_4_gui = lora_scale_slider("Lora Scale 4")
                     lora5_gui = lora_dropdown("Lora5")
                     lora_scale_5_gui = lora_scale_slider("Lora Scale 5")
-                    lora6_gui = lora_dropdown("Lora6", visible=(not IS_ZERO_GPU))
-                    lora_scale_6_gui = lora_scale_slider("Lora Scale 6", visible=(not IS_ZERO_GPU))
-                    lora7_gui = lora_dropdown("Lora7", visible=(not IS_ZERO_GPU))
-                    lora_scale_7_gui = lora_scale_slider("Lora Scale 7", visible=(not IS_ZERO_GPU))
+                    lora6_gui = lora_dropdown("Lora6")
+                    lora_scale_6_gui = lora_scale_slider("Lora Scale 6")
+                    lora7_gui = lora_dropdown("Lora7")
+                    lora_scale_7_gui = lora_scale_slider("Lora Scale 7")
 
                     with gr.Accordion("From URL", open=False, visible=True):
                         text_lora = gr.Textbox(
@@ -1171,6 +1189,8 @@ with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False) as
                     schedule_prediction_type_gui = gr.Dropdown(label="Discrete Sampling Type", choices=SCHEDULE_PREDICTION_TYPE_OPTIONS, value=SCHEDULE_PREDICTION_TYPE_OPTIONS[0])
                     guidance_rescale_gui = gr.Number(label="CFG rescale:", value=0., step=0.01, minimum=0., maximum=1.5)
                     save_generated_images_gui = gr.Checkbox(value=True, label="Create a download link for the images")
+                    enable_live_preview_gui = gr.Checkbox(value=True, label="Enable live previews")
+                    display_images_gui = gr.Checkbox(value=True, label="Show final results")
                     filename_pattern_gui = gr.Textbox(label="Filename pattern", value="model,seed", placeholder="model,seed,sampler,schedule_type,img_width,img_height,guidance_scale,num_steps,vae,prompt_section,neg_prompt_section", lines=1)
                     hires_before_adetailer_gui = gr.Checkbox(value=False, label="Hires Before Adetailer")
                     hires_after_adetailer_gui = gr.Checkbox(value=True, label="Hires After Adetailer")
@@ -1183,12 +1203,11 @@ with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False) as
                 with gr.Accordion("More settings", open=False, visible=False):
                     loop_generation_gui = gr.Slider(minimum=1, value=1, label="Loop Generation")
                     retain_task_cache_gui = gr.Checkbox(value=False, label="Retain task model in cache")
-                    display_images_gui = gr.Checkbox(value=False, label="Display Images")
-                    image_previews_gui = gr.Checkbox(value=True, label="Image Previews")
+                    
+                    image_previews_gui = gr.Checkbox(value=True, label="Image Previews (alt)")
                     retain_compel_previous_load_gui = gr.Checkbox(value=False, label="Retain Compel Previous Load")
                     retain_detailfix_model_previous_load_gui = gr.Checkbox(value=False, label="Retain Detailfix Model Previous Load")
                     retain_hires_model_previous_load_gui = gr.Checkbox(value=False, label="Retain Hires Model Previous Load")
-                    xformers_memory_efficient_attention_gui = gr.Checkbox(value=False, label="Xformers Memory Efficient Attention")
 
                 set_params_gui.click(
                     run_set_params_gui, [prompt_gui, model_name_gui], [
@@ -1214,6 +1233,7 @@ with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False) as
                         hires_schedule_type_gui,
                         image_resolution_gui,
                         strength_gui,
+                        prompt_syntax_gui,
                         lora1_gui,
                         lora_scale_1_gui,
                         lora2_gui,
@@ -1442,7 +1462,7 @@ with gr.Blocks(theme=args.theme, css=CSS, fill_width=True, fill_height=False) as
             t2i_adapter_preprocessor_gui,
             adapter_conditioning_scale_gui,
             adapter_conditioning_factor_gui,
-            xformers_memory_efficient_attention_gui,
+            enable_live_preview_gui,
             free_u_gui,
             generator_in_cpu_gui,
             adetailer_inpaint_only_gui,
@@ -1503,4 +1523,4 @@ if __name__ == "__main__":
         ssr_mode=args.ssr,
         allowed_paths=[allowed_path],
         show_api=(not HIDE_API),
-    )
+    )