Upload 4 files

spaghetti_ai.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6010b8e71b9f3c0f1a1a6ce1694f1c242f25e9e9fbd4e1955d187cd8211b9277
-size 86416
+oid sha256:099991965df4631d1c4eb0423fa9bf477e582e237926bad9bf7d8fe117205d45
+size 88891

spaghetti_ai_launcher.bat

@@ -27,8 +27,13 @@ REM        don't need an updated version. The older versions will not be deleted
 REM        automatically. That means your drive would eventually run out of
 REM        space if you never deleted older versions.
 REM
+REM        To have model data download, this variable must be set to 0 if using
+REM        this script. You must also set "only_use_local_files" to "0" in
+REM        "spaghetti_ai_script.py". If either is not that, model data will not
+REM        download.
+REM
 
-set HF_HUB_OFFLINE=0
+set HF_HUB_OFFLINE=1
 
 REM
 REM      HF_HUB_DISABLE_TELEMETRY
@@ -38,8 +43,15 @@ REM
 REM        About:
 REM          https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfhubdisabletelemetry
 REM
+REM      DO_NOT_TRACK
+REM
+REM        This one might do more.
+REM
+REM        About:
+REM          https://github.com/huggingface/huggingface_hub/pull/1920
 
 set HF_HUB_DISABLE_TELEMETRY=1
+set DO_NOT_TRACK=1
 
 REM ############################################################################
 
@@ -47,6 +59,6 @@ cd C:/Spaghetti_AI
 
 call .venv/Scripts/activate.bat
 
-call py .venv/app_files/spaghetti_ai_script.py
+py .venv/app_files/spaghetti_ai_script.py
 
 cmd /k

spaghetti_ai_script.py

@@ -6,6 +6,7 @@ from diffusers import DiffusionPipeline
 import os
 import random
 import torchsde
+from math import floor, copysign
 
 ##########
 
@@ -65,6 +66,71 @@ main_dir = "C:/Spaghetti_AI"
 
 ####################
 
+#
+#    Only Use Local Files (IMPORTANT)
+#
+#        Please read the section below the configuration. The app will not work
+#        unless this is set to "0" in order for it to download model data.
+#
+#        0    False (Model data will be downloaded)
+#        1    True (Model data will not be downloaded, even if missing)
+#
+
+only_use_local_files = 0
+
+#
+#        This is an important value. HuggingFace doesn't just download a model
+#        once and never try again. If something is updated, it will download it
+#        again. It will not delete the older version. This could eventually
+#        allow it to use all the space on your drive as that could potentially
+#        add 5 to 15 gigabytes of data each time a model updates. This variable
+#        forces the script not to check for model data. However, when set to
+#        "1", the app will not download any data for the models, including for
+#        refining and upscaling. That would mean the app will not work. You need
+#        to set this to "0" when you need to download data. While there are ways
+#        to not download as much data, it is not as simple. I prefer this
+#        method. You could check occasionally and manually delete model data,
+#        but if you're like me, you would forget.
+#
+#        To download data you can use each model in the app when this is set to
+#        "0" and it will download the needed data. That does require you to use
+#        each model. Then you could set this back to "1". However, if you want
+#        to download all the data, without having to use each model, including
+#        using refining and upscaling at some point at least once, there are
+#        two options.
+#
+#        To download all default model data, meaning the default model selected
+#        for each base model (set in
+#        "base_model_model_configuration_defaults_object"), including data for
+#        the refiner and upscaler, add this to the end of the url for option 1:
+#
+#            ?download_data=1
+#
+#        Like this for option 1:
+#            http://127.0.0.1:7860/?download_data=1
+#
+#        To download all model data, for everything in the
+#        "model_configuration_links_object", including data for the refiner and
+#        upscaler, add this to the end of the url for option 2:
+#
+#            ?download_data=2
+#
+#        Both options will download dozens of gigabytes of data, most especially
+#        the second option, so you may not want to do that. Before you do that,
+#        make sure you have removed from the configurations the models you do
+#        not want. For option 1, remove the base models you do not want to use
+#        in "base_model_array". For option 2, remove the model configurations
+#        you do not want to use in
+#        "base_model_object_of_model_configuration_arrays".
+#
+#        To have model data download, this variable must be set to 0. You must
+#        also set "HF_HUB_OFFLINE" to "0" in "spaghetti_ai_launcher.bat" if you
+#        use that script. If you use that script, and either is not that, model
+#        data will not download.
+#
+
+####################
+
 #
 #    Use Custom Hugging Face Cache Directory
 #
@@ -156,7 +222,7 @@ saved_images_folder_name = "saved_images"
 #    Auto Open Browser From Command Prompt
 #
 
-auto_open_browser = 1
+auto_open_browser = 0
 
 ####################
 
@@ -250,7 +316,7 @@ show_messages_in_modal_on_page = 0
 #    Suppress Hugging Face Hub Offline Status
 #
 #        By default, we add messages about the current setting of
-#        "HF_HUB_OFFLINE" in 
+#        "HF_HUB_OFFLINE".
 #
 
 suppress_hugging_face_hub_offline_status = 0
@@ -467,6 +533,13 @@ photoreal_online_configurations_object = {
 
 ####################
 
+base_models_not_supporting_denoising_end_for_base_model_object = {
+    "photoreal":       1,
+    "sd_1_5_runwayml": 1
+}
+
+####################
+
 hugging_face_refiner_partial_path = "stabilityai/stable-diffusion-xl-refiner-1.0"
 hugging_face_upscaler_partial_path = "stabilityai/sd-x2-latent-upscaler"
 
@@ -668,8 +741,8 @@ default_negative_prompt = ""
 default_width = 768
 default_height = 768
 
-minimum_width = 256
-minimum_height = 256
+minimum_width = 64
+minimum_height = 64
 
 maximum_width = 2048 # 1024
 maximum_height = 2048 # 1024
@@ -874,12 +947,17 @@ if script_being_run_on_hugging_face == 1:
     show_messages_in_modal_on_page = 0
     show_messages_in_command_prompt = 1
 
+    only_use_local_files = 0
+
     if device == "cpu":
 
         #    If on CPU at HuggingFace, I reduce what is available.
 
         show_image_creation_progress_log = 1
 
+        minimum_width = 256
+        minimum_height = 256
+
         maximum_width = 768
         maximum_height = 768
 
@@ -940,6 +1018,14 @@ if default_upscaler_steps > maximum_upscaler_steps:
 
 
 
+only_use_local_files_bool = False
+
+if only_use_local_files == 1:
+
+    only_use_local_files_bool = True
+
+
+
 if allow_online_configurations == 0:
 
     base_model_array = [
@@ -979,6 +1065,8 @@ if script_being_run_on_hugging_face == 0:
 
         hugging_face_hub_is_offline = 1
 
+        only_use_local_files = 1
+
     if suppress_hugging_face_hub_offline_status == 1:
 
         if hugging_face_hub_is_offline == 0:
@@ -1312,6 +1400,14 @@ if default_base_model == "sdxl_turbo":
 
 
 
+default_refining_use_denoising_start_in_base_model_when_using_refiner_field_row_visibility = True
+
+if default_base_model in base_models_not_supporting_denoising_end_for_base_model_object:
+
+    default_refining_use_denoising_start_in_base_model_when_using_refiner_field_row_visibility = False
+
+
+
 default_add_seed_into_pipe_field_row_visibility = False
 
 if is_default_config == 1:
@@ -1386,6 +1482,50 @@ if maximum_seed <= 9007199254740992:
 
 
 
+#####################
+#
+#    Rounded Number
+#
+#        A better, and seemingly more accurate, way to round.
+#
+#        https://realpython.com/python-rounding/
+
+#####################
+
+def rounded_number(n, decimals=0):
+    n = float(n)
+    multiplier = 10**decimals
+    rounded_abs = (floor(abs(n) * multiplier + 0.5) / multiplier)
+    rounded_value = round(copysign(rounded_abs, n), decimals)
+    return rounded_value
+
+
+
+
+
+
+
+#####################
+#
+#    Rounded Number
+#
+#        Format number to a certain number of decimal places and output it to a string.
+#
+#        https://stackoverflow.com/questions/1995615/how-can-i-format-a-decimal-to-always-show-2-decimal-places
+
+#####################
+
+def formatted_number(n, decimals=0):
+    rounded_value = rounded_number(n, decimals)
+    formatted_value = '{:.{prec}f}'.format(rounded_value, prec=decimals)
+    return formatted_value
+
+
+
+
+
+
+
 #####################
 #
 #    Show Message
@@ -1989,7 +2129,8 @@ def construct_pipe (
         base_model_kwargs["cache_dir"] = hugging_face_cache_dir
 
     pipe = DiffusionPipeline.from_pretrained(
-        model_configuration_links_object[model_configuration_name_value],
+        pretrained_model_name_or_path = model_configuration_links_object[model_configuration_name_value],
+        local_files_only = only_use_local_files_bool,
         **base_model_kwargs
     )
 
@@ -2235,7 +2376,8 @@ def construct_refiner ():
         refiner_kwargs["cache_dir"] = hugging_face_cache_dir
 
     refiner = DiffusionPipeline.from_pretrained(
-        hugging_face_refiner_partial_path,
+        pretrained_model_name_or_path = hugging_face_refiner_partial_path,
+        local_files_only = only_use_local_files_bool,
         **refiner_kwargs
     )
 
@@ -2299,7 +2441,8 @@ def construct_upscaler ():
         upscaler_kwargs["cache_dir"] = hugging_face_cache_dir
 
     upscaler = DiffusionPipeline.from_pretrained(
-        hugging_face_upscaler_partial_path,
+        pretrained_model_name_or_path = hugging_face_upscaler_partial_path,
+        local_files_only = only_use_local_files_bool,
         **upscaler_kwargs
     )
 
@@ -2500,8 +2643,8 @@ def create_image_function (
     base_model_num_inference_steps = int(base_model_num_inference_steps)
     base_model_steps_field_for_sdxl_turbo = int(base_model_steps_field_for_sdxl_turbo)
     actual_seed = int(actual_seed)
-    refining_denoise_start_for_default_config_field_value = round(float(refining_denoise_start_for_default_config_field_value), 2)
-    refining_denoise_start_for_online_config_field_value = round(float(refining_denoise_start_for_online_config_field_value), 2)
+    refining_denoise_start_for_default_config_field_value = rounded_number(refining_denoise_start_for_default_config_field_value, 2)
+    refining_denoise_start_for_online_config_field_value = rounded_number(refining_denoise_start_for_online_config_field_value, 2)
     refining_steps_for_sdxl_online_config_field_value = int(refining_steps_for_sdxl_online_config_field_value)
     upscaling_num_inference_steps = int(upscaling_num_inference_steps)
 
@@ -2528,9 +2671,19 @@ def create_image_function (
 
 
 
-    current_actual_total_base_model_steps = base_model_num_inference_steps
+    current_estimated_total_base_model_steps = base_model_num_inference_steps
+    current_estimated_total_refiner_steps = 0
+    current_estimated_total_upscaler_steps = upscaling_num_inference_steps
+
+
+
+    global current_actual_total_base_model_steps
+    global current_actual_total_base_model_steps
+    global current_actual_total_refiner_steps
+
+    current_actual_total_base_model_steps = 0
     current_actual_total_refiner_steps = 0
-    current_actual_total_upscaler_steps = upscaling_num_inference_steps
+    current_actual_total_upscaler_steps = 0
 
 
 
@@ -2538,7 +2691,7 @@ def create_image_function (
 
         negative_prompt_text = ""
         base_model_num_inference_steps = base_model_steps_field_for_sdxl_turbo
-        current_actual_total_base_model_steps = base_model_num_inference_steps
+        current_estimated_total_base_model_steps = base_model_num_inference_steps
         guidance_scale = 0
 
 
@@ -2596,6 +2749,7 @@ def create_image_function (
     refining_selection_online_config_automatically_selected_field_value = numerical_bool(refining_selection_online_config_automatically_selected_field_value)
 
 
+
     refining_use_denoising_start_in_base_model_when_using_refiner_field_value = numerical_bool(refining_use_denoising_start_in_base_model_when_using_refiner_field_value)
     refining_base_model_output_to_refiner_is_in_latent_space_field_value = numerical_bool(refining_base_model_output_to_refiner_is_in_latent_space_field_value)
 
@@ -2844,6 +2998,10 @@ def create_image_function (
 
 
 
+    denoising_end_applicable = 0
+
+
+
     if show_image_creation_progress_log == 1:
 
 
@@ -2897,10 +3055,14 @@ def create_image_function (
 
                 base_model_progress_text = "Base model processing started"
 
+            global current_actual_total_base_model_steps
+
+            current_actual_total_base_model_steps += 1
+
             progress(
                 progress = (
                     callback_step_index,
-                    current_actual_total_base_model_steps
+                    current_estimated_total_base_model_steps
                 ),
                 desc = base_model_progress_text,
                 unit = "base model steps"
@@ -2961,10 +3123,14 @@ def create_image_function (
 
                 refiner_progress_text = "Refiner processing started"
 
+            global current_actual_total_refiner_steps
+
+            current_actual_total_refiner_steps += 1
+
             progress(
                 progress = (
                     callback_step_index,
-                    current_actual_total_refiner_steps
+                    current_estimated_total_refiner_steps
                 ),
                 desc = refiner_progress_text,
                 unit = "refiner steps"
@@ -3024,10 +3190,14 @@ def create_image_function (
 
                 upscaler_progress_text = "Upscaler processing started"
 
+            global current_actual_total_upscaler_steps
+
+            current_actual_total_upscaler_steps += 1
+
             progress(
                 progress = (
                     callback_step_index,
-                    current_actual_total_upscaler_steps
+                    current_estimated_total_upscaler_steps
                 ),
                 desc = upscaler_progress_text,
                 unit = "upscaler steps"
@@ -3098,7 +3268,7 @@ def create_image_function (
 
                 upscaling_num_inference_steps = 5
 
-            current_actual_total_upscaler_steps = upscaling_num_inference_steps
+            current_estimated_total_upscaler_steps = upscaling_num_inference_steps
 
             if show_messages_in_command_prompt == 1:
 
@@ -3138,7 +3308,11 @@ def create_image_function (
                     desc = "Refining is beginning"
                 )
 
-            current_actual_total_refiner_steps = (refining_steps_for_sdxl_online_config_field_value - round(refining_steps_for_sdxl_online_config_field_value * refining_denoise_start_for_online_config_field_value))
+            current_estimated_total_refiner_steps = rounded_number(refining_steps_for_sdxl_online_config_field_value - (refining_steps_for_sdxl_online_config_field_value * refining_denoise_start_for_online_config_field_value))
+
+            if current_estimated_total_refiner_steps < 1:
+
+                current_estimated_total_refiner_steps = 1
 
             nice_refiner_denoise_start = str(refining_denoise_start_for_online_config_field_value)
 
@@ -3146,7 +3320,7 @@ def create_image_function (
                 "Refiner? Yes",
                 "Refiner denoise start %: " + nice_refiner_denoise_start,
                 "Refiner number of iterations: " + str(refining_steps_for_sdxl_online_config_field_value),
-                "Actual Refining Steps: " + str(current_actual_total_refiner_steps)
+                "Actual Refining Steps: " + formatted_number(current_actual_total_refiner_steps)
             ]
 
             image = refiner(
@@ -3250,14 +3424,11 @@ def create_image_function (
 
                 default_steps_in_diffusers = 50
 
-                current_actual_total_refiner_steps = (default_steps_in_diffusers - round(default_steps_in_diffusers * refining_denoise_start_for_online_config_field_value))
+                current_estimated_total_refiner_steps = rounded_number(default_steps_in_diffusers - (default_steps_in_diffusers * refining_denoise_start_for_online_config_field_value))
 
-                refiner_info_for_info_about_prompt_lines_array = [
-                    "Refiner? Yes",
-                    "Refiner denoise start %: " + nice_refiner_denoise_start,
-                    "Refiner number of iterations: " + str(default_steps_in_diffusers),
-                    "Actual Refining Steps: " + str(current_actual_total_refiner_steps)
-                ]
+                if current_estimated_total_refiner_steps < 1:
+
+                    current_estimated_total_refiner_steps = 1
 
                 image = refiner(
                     Prompt,
@@ -3268,6 +3439,15 @@ def create_image_function (
                     callback_on_step_end=callback_to_do_for_refiner_progress
                 ).images[0]
 
+                nice_refiner_denoise_start = str(refining_denoise_start_for_online_config_field_value)
+
+                refiner_info_for_info_about_prompt_lines_array = [
+                    "Refiner? Yes",
+                    "Refiner denoise start %: " + nice_refiner_denoise_start,
+                    "Refiner number of iterations: " + str(default_steps_in_diffusers),
+                    "Actual Refining Steps: " + formatted_number(current_actual_total_refiner_steps)
+                ]
+
             else:
 
                 if show_messages_in_command_prompt == 1:
@@ -3306,6 +3486,12 @@ def create_image_function (
 
 
 
+        if base_model_name_value not in base_models_not_supporting_denoising_end_for_base_model_object:
+
+            denoising_end_applicable = 1
+
+
+
         #
         #
         #
@@ -3316,11 +3502,18 @@ def create_image_function (
 
         if use_refiner == 1:
 
-            if refining_use_denoising_start_in_base_model_when_using_refiner_field_value == 1:
+            if (
+                (refining_use_denoising_start_in_base_model_when_using_refiner_field_value == 1) and
+                (denoising_end_applicable == 1)
+            ):
 
                 denoising_end = refining_denoise_start_for_default_config_field_value
 
-                current_actual_total_base_model_steps = round(base_model_num_inference_steps * refining_denoise_start_for_default_config_field_value)
+                current_estimated_total_base_model_steps = rounded_number(base_model_num_inference_steps * refining_denoise_start_for_default_config_field_value)
+
+                if current_estimated_total_base_model_steps < 1:
+
+                    current_estimated_total_base_model_steps = 1
 
             else:
 
@@ -3332,44 +3525,11 @@ def create_image_function (
 
                 output_type_before_refiner = "latent"
 
-            current_actual_total_refiner_steps = (base_model_num_inference_steps - round(base_model_num_inference_steps * refining_denoise_start_for_default_config_field_value))
+            current_estimated_total_refiner_steps = rounded_number(base_model_num_inference_steps - (base_model_num_inference_steps * refining_denoise_start_for_default_config_field_value))
 
-            refiner_info_for_info_about_prompt_lines_array = [
-                "Refiner? Yes"
-            ]
-
-            nice_refiner_denoise_start = str(refining_denoise_start_for_online_config_field_value)
+            if current_estimated_total_refiner_steps < 1:
 
-            if refining_use_denoising_start_in_base_model_when_using_refiner_field_value == 1:
-
-                refiner_info_for_info_about_prompt_lines_array.extend([
-                    "Set \"denoising_end\" in base model generation? Yes",
-                    "Base model denoise end %: " + nice_refiner_denoise_start,
-                    "Actual Base Model Steps: " + str(current_actual_total_base_model_steps)
-                ])
-
-            else:
-
-                refiner_info_for_info_about_prompt_lines_array.extend([
-                    "Set \"denoising_end\" in base model generation? No",
-                ])
-
-            refiner_info_for_info_about_prompt_lines_array.extend([
-                "Refiner denoise start %: " + nice_refiner_denoise_start,
-                "Actual Refining Steps: " + str(current_actual_total_refiner_steps)
-            ])
-
-            if refining_base_model_output_to_refiner_is_in_latent_space_field_value == 1:
-
-                refiner_info_for_info_about_prompt_lines_array.extend([
-                    "Base model output in latent space before refining? Yes",
-                ])
-
-            else:
-
-                refiner_info_for_info_about_prompt_lines_array.extend([
-                    "Base model output in latent space before refining? No",
-                ])
+                current_estimated_total_refiner_steps = 1
 
             if use_upscaler == 1:
 
@@ -3499,6 +3659,49 @@ def create_image_function (
 
                 image_to_return = refined_image
 
+
+
+            refiner_info_for_info_about_prompt_lines_array = [
+                "Refiner? Yes"
+            ]
+
+            nice_refiner_denoise_start = str(refining_denoise_start_for_default_config_field_value)
+
+            if denoising_end_applicable == 1:
+
+                if refining_use_denoising_start_in_base_model_when_using_refiner_field_value == 1:
+
+                    refiner_info_for_info_about_prompt_lines_array.extend([
+                        "Set \"denoising_end\" in base model generation? Yes",
+                        "Base model denoise end %: " + nice_refiner_denoise_start,
+                        "Actual Base Model Steps: " + formatted_number(current_actual_total_base_model_steps)
+                    ])
+
+                else:
+
+                    refiner_info_for_info_about_prompt_lines_array.extend([
+                        "Set \"denoising_end\" in base model generation? No",
+                    ])
+
+            refiner_info_for_info_about_prompt_lines_array.extend([
+                "Refiner denoise start %: " + nice_refiner_denoise_start,
+                "Actual Refining Steps: " + formatted_number(current_actual_total_refiner_steps)
+            ])
+
+            if refining_base_model_output_to_refiner_is_in_latent_space_field_value == 1:
+
+                refiner_info_for_info_about_prompt_lines_array.extend([
+                    "Base model output in latent space before refining? Yes",
+                ])
+
+            else:
+
+                refiner_info_for_info_about_prompt_lines_array.extend([
+                    "Base model output in latent space before refining? No",
+                ])
+
+
+
         else:
 
             if use_upscaler == 1:
@@ -3755,7 +3958,10 @@ def create_image_function (
 
     info_about_prompt = "\n".join(info_about_prompt_lines_array)
 
-    output_text_field_update = info_about_prompt
+    output_text_field_update = gr.Textbox(
+        value = info_about_prompt,
+        lines = 12,
+    )
 
 
 
@@ -3821,7 +4027,7 @@ def create_image_function (
         saved_text_file_path_and_file = saved_images_date_dir + file_name_without_extension + ".txt"
 
         prompt_info_file_handle = open(saved_text_file_path_and_file, "w")
-        prompt_info_file_handle.writelines(output_text_field_update)
+        prompt_info_file_handle.writelines(info_about_prompt)
         prompt_info_file_handle.close()
 
 
@@ -3831,7 +4037,7 @@ def create_image_function (
     )
 
     image_gallery_array_state_value.insert(0, image_to_return)
-    prompt_information_array_state_value.insert(0, output_text_field_update)
+    prompt_information_array_state_value.insert(0, info_about_prompt)
 
     output_image_gallery_field_update = gr.Gallery(
         value = image_gallery_array_state_value,
@@ -3913,17 +4119,7 @@ def cancel_image_processing():
 #    Download Data From HuggingFace
 #
 #        This will download a lot of data at once rather than waiting until you
-#        use each model. This is access by having this at the end of the URL:
-#
-#            ?download_data=1
-#
-#        Like this:
-#            http://127.0.0.1:7860/?download_data=1
-#
-#        A "1" will download only the default model configuration for each main
-#        model, as well as refiner and upscaler data. A "2" will download all
-#        model data needed in "model_configuration_links_object", including
-#        online configurations you may not want.
+#        use each model.
 #
 #####################
 
@@ -4463,8 +4659,56 @@ def set_base_model_and_model_configuration_from_query_params(
 #    Hide border when yield is used:
 #        https://github.com/gradio-app/gradio/issues/5479
 #        .generating {border: none !important;}
+#        I'm not currently using yield.
+
+css_to_use = """
 
-css_to_use = "footer{display:none !important}"
+footer
+{
+    display: none !important;
+}
+
+#output_text_field_id textarea
+{
+    resize: none;
+    overflow-y: auto !important;
+}
+     
+#output_text_field_id textarea::-webkit-scrollbar
+{
+    width: 15px;
+}
+
+#output_text_field_id textarea::-webkit-scrollbar-track
+{
+    background-color: rgb(245, 245, 245);
+    border222222222222222222: 0px;
+}
+
+#output_text_field_id textarea::-webkit-scrollbar-track:hover
+{
+    background-color: rgb(242, 242, 242);
+}
+
+#output_text_field_id textarea::-webkit-scrollbar-thumb
+{
+    background-color: rgb(214, 214, 214);
+    width: 100%;
+    height: 60px;
+    max-height: 80%;
+    border: 1px solid rgb(224, 224, 224);
+}
+
+#output_text_field_id textarea::-webkit-scrollbar-thumb:hover
+{
+    background-color: rgb(184, 184, 184);
+}
+
+a:hover {
+  background-color: yellow;
+}
+
+"""
 
 with gr.Blocks(
     title = "Spaghetti AI",
@@ -4581,7 +4825,10 @@ with gr.Blocks(
                             step = refiner_denoise_start_input_slider_steps
                         )
 
-                    with gr.Row():
+                    with gr.Row(
+                        elem_id = "refining_use_denoising_start_in_base_model_when_using_refiner_field_row_id",
+                        visible = default_refining_use_denoising_start_in_base_model_when_using_refiner_field_row_visibility
+                    ):
 
                         refining_use_denoising_start_in_base_model_when_using_refiner_field = gr.Checkbox(
                             label = "Use \"denoising_start\" value as \"denoising_end\" value in base model generation when using refiner",
@@ -4989,11 +5236,14 @@ with gr.Blocks(
             with gr.Row():
 
                 output_text_field = gr.Textbox(
+                    elem_id = "output_text_field_id",
                     label = "Prompt Information:",
                     value = "After an image is generated, its generation information will appear here. All of this information is also embedded in the image itself. If you open the image in a text program, it will appear at the top." + additional_prompt_info_html,
                     show_copy_button = True,
-                    lines = 10,
-                    max_lines = 20,
+                    lines = 6,
+#                    max_lines = 20,
+                    autoscroll = False,
+                    interactive = False,
                     container = True
                 )
 
@@ -5174,9 +5424,10 @@ async (
     var onlineConfigurationsObject = {3};
     var modelConfigurationForceRefinerObject = {4};
     var modelConfigurationIncludeRefinerNumberOfStepsObject = {5};
-    var modelConfigurationHideUpscalerStepsObject = {6};
+    var baseModelsNotSupportingDenoisingEndForBaseModelObject = {6}
+    var modelConfigurationHideUpscalerStepsObject = {7};
 
-    var allowOnlineConfigurations = {7};
+    var allowOnlineConfigurations = {8};
 
     var baseModelFullNamesToBaseModelIdConversion = {{}};
     Object.keys(baseModelNamesObject).forEach(key => {{
@@ -5314,11 +5565,19 @@ async (
 
         }}
 
-        var refiningNumberOfIterationsForOnlineConfigFieldDisplay = "none";
+        var refiningStepsForSdxlOnlineConfigFieldfigFieldDisplay = "none";
 
         if (Object.keys(modelConfigurationIncludeRefinerNumberOfStepsObject).includes(modelConfigurationNameValue)) {{
 
-             refiningNumberOfIterationsForOnlineConfigFieldDisplay = "block";
+             refiningStepsForSdxlOnlineConfigFieldfigFieldDisplay = "block";
+
+        }}
+
+        var refiningUseDenoisingStartInBaseModelWhenUsingRefinerFieldDisplay = "block";
+
+        if (Object.keys(baseModelsNotSupportingDenoisingEndForBaseModelObject).includes(baseModelFieldValue)) {{
+
+             refiningUseDenoisingStartInBaseModelWhenUsingRefinerFieldDisplay = "none";
 
         }}
 
@@ -5333,7 +5592,8 @@ async (
         document.getElementById("refining_selection_automatically_selected_message_field_id").style.display = refiningSelectionAutomaticallySelectedMessageFieldDisplay;
         document.getElementById("refining_selection_online_config_normal_field_id").style.display = refiningSelectionOnlineConfigNormalFieldDisplay;
         document.getElementById("refining_selection_online_config_automatically_selected_field_id").style.display = refiningSelectionOnlineConfigAutomaticallySelectedFieldDisplay;
-        document.getElementById("refining_steps_for_sdxl_online_config_field_row_id").style.display = refiningNumberOfIterationsForOnlineConfigFieldDisplay;
+        document.getElementById("refining_steps_for_sdxl_online_config_field_row_id").style.display = refiningStepsForSdxlOnlineConfigFieldfigFieldDisplay;
+        document.getElementById("refining_use_denoising_start_in_base_model_when_using_refiner_field_row_id").style.display = refiningUseDenoisingStartInBaseModelWhenUsingRefinerFieldDisplay;
         document.getElementById("upscaling_num_inference_steps_field_row_id").style.display = upscalingNumInferenceStepsFieldDisplay;
 
     }}
@@ -5347,6 +5607,7 @@ async (
     online_configurations_object,
     model_configuration_force_refiner_object,
     model_configuration_include_refiner_number_of_steps_object,
+    base_models_not_supporting_denoising_end_for_base_model_object,
     model_configuration_hide_upscaler_steps_object,
     allow_online_configurations
 )
@@ -5607,6 +5868,8 @@ async () => {{
 
     window.modelConfigurationDropdownFieldValuesObject = {{{0}}};
 
+    document.querySelector("#output_text_field_id textarea").classList.remove("scroll-hide");
+
 }}
 
 """.format(