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votepurchase-multiple-model

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John6666 commited on Sep 13

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3b2dce0

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1 Parent(s): 8771e29

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Files changed (16) hide show

README.md +1 -1
app.py +12 -9
constants.py +49 -23
dc.py +79 -44
env.py +1 -0
image_processor.py +2 -2
llmdolphin.py +44 -46
llmenv.py +742 -0
lora_dict.json +14 -0
modutils.py +6 -6
packages.txt +1 -1
requirements.txt +9 -9
tagger/fl2sd3longcap.py +12 -6
tagger/tagger.py +1 -1
tagger/v2.py +4 -5
utils.py +181 -104

README.md CHANGED Viewed

@@ -4,7 +4,7 @@ emoji: 🖼🖼️📦
 colorFrom: purple
 colorTo: red
 sdk: gradio
-sdk_version: 4.41.0
 app_file: app.py
 license: mit
 short_description: Text-to-Image

 colorFrom: purple
 colorTo: red
 sdk: gradio
+sdk_version: 5.44.1
 app_file: app.py
 license: mit
 short_description: Text-to-Image

app.py CHANGED Viewed

@@ -1,6 +1,7 @@
 import spaces
 import gradio as gr
 import numpy as np
 # DiffuseCraft
 from dc import (infer, _infer, pass_result, get_diffusers_model_list, get_samplers, save_image_history,
@@ -35,7 +36,7 @@ def description_ui():
 """
     )
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 4096
 MIN_IMAGE_SIZE = 256
@@ -51,7 +52,7 @@ css = """
 .image { margin: 0px auto; object-fit: contain; }
 """
-with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60, 3600)) as demo:
     gr.Markdown("# Votepurchase Multiple Model", elem_classes="title")
     state = gr.State(value={})
     with gr.Tab("Image Generator"):
@@ -124,7 +125,8 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
                         return gr.Dropdown(label=label, choices=get_all_lora_tupled_list(), value="", allow_custom_value=True, elem_classes="lora", min_width=320, visible=visible)
                     def lora_scale_slider(label, visible=True):
-                        return gr.Slider(minimum=-2, maximum=2, step=0.01, value=1.00, label=label, visible=visible)
                     def lora_textbox():
                         return gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
@@ -233,8 +235,8 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
                         low_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=100, label="'CANNY' low threshold")
                         high_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=200, label="'CANNY' high threshold")
                     with gr.Row():
-                        value_threshold = gr.Slider(minimum=1, maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
-                        distance_threshold = gr.Slider(minimum=1, maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
                     recolor_gamma_correction = gr.Number(minimum=0., maximum=25., value=1., step=0.001, label="'RECOLOR' gamma correction")
                     tile_blur_sigma = gr.Number(minimum=0, maximum=100, value=9, step=1, label="'TILE' blur sigma")
@@ -295,7 +297,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
                         with gr.Row():
                             upscaler_model_path = gr.Dropdown(label="Upscaler", choices=UPSCALER_KEYS, value=UPSCALER_KEYS[0])
                             upscaler_increases_size = gr.Slider(minimum=1.1, maximum=4., step=0.1, value=1.2, label="Upscale by")
-                            upscaler_tile_size = gr.Slider(minimum=0, maximum=512, step=16, value=0, label="Upscaler Tile Size", info="0 = no tiling")
                             upscaler_tile_overlap = gr.Slider(minimum=0, maximum=48, step=1, value=8, label="Upscaler Tile Overlap")
                         with gr.Row():
                             hires_steps = gr.Slider(minimum=0, value=30, maximum=100, step=1, label="Hires Steps")
@@ -351,7 +353,7 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
                             face_restoration_weight = gr.Slider(minimum=0., maximum=1., step=0.001, value=.5, label="Weight", info="(0 = maximum effect, 1 = minimum effect)")
                 with gr.Tab("Translation Settings"):
-                    chatbot = gr.Chatbot(render_markdown=False, visible=False) # component for auto-translation
                     chat_model = gr.Dropdown(choices=get_dolphin_models(), value=get_dolphin_models()[0], allow_custom_value=True, label="Model")
                     chat_model_info = gr.Markdown(value=get_dolphin_model_info(get_dolphin_models()[0]), label="Model info")
                     chat_format = gr.Dropdown(choices=get_llm_formats(), value=get_dolphin_model_format(get_dolphin_models()[0]), label="Message format")
@@ -682,5 +684,6 @@ with gr.Blocks(fill_width=True, elem_id="container", css=css, delete_cache=(60,
     gr.LoginButton()
     gr.DuplicateButton(value="Duplicate Space for private use (This demo does not work on CPU. Requires GPU Space)")
-demo.queue()
-demo.launch(show_error=True, debug=True)

 import spaces
 import gradio as gr
 import numpy as np
+import os
 # DiffuseCraft
 from dc import (infer, _infer, pass_result, get_diffusers_model_list, get_samplers, save_image_history,
 """
     )
+IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 4096
 MIN_IMAGE_SIZE = 256
 .image { margin: 0px auto; object-fit: contain; }
 """
+with gr.Blocks(fill_width=True, elem_id="container", css=css) as demo:
     gr.Markdown("# Votepurchase Multiple Model", elem_classes="title")
     state = gr.State(value={})
     with gr.Tab("Image Generator"):
                         return gr.Dropdown(label=label, choices=get_all_lora_tupled_list(), value="", allow_custom_value=True, elem_classes="lora", min_width=320, visible=visible)
                     def lora_scale_slider(label, visible=True):
+                        val_lora = 8 if IS_ZERO_GPU else 8 #
+                        return gr.Slider(minimum=-val_lora, maximum=val_lora, step=0.01, value=0.33, label=label, visible=visible)
                     def lora_textbox():
                         return gr.Textbox(label="", info="Example of prompt:", value="", show_copy_button=True, interactive=False, visible=False)
                         low_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=100, label="'CANNY' low threshold")
                         high_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=200, label="'CANNY' high threshold")
                     with gr.Row():
+                        value_threshold = gr.Slider(minimum=0.0, maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
+                        distance_threshold = gr.Slider(minimum=0.0, maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
                     recolor_gamma_correction = gr.Number(minimum=0., maximum=25., value=1., step=0.001, label="'RECOLOR' gamma correction")
                     tile_blur_sigma = gr.Number(minimum=0, maximum=100, value=9, step=1, label="'TILE' blur sigma")
                         with gr.Row():
                             upscaler_model_path = gr.Dropdown(label="Upscaler", choices=UPSCALER_KEYS, value=UPSCALER_KEYS[0])
                             upscaler_increases_size = gr.Slider(minimum=1.1, maximum=4., step=0.1, value=1.2, label="Upscale by")
+                            upscaler_tile_size = gr.Slider(minimum=0, maximum=512, step=16, value=(0 if IS_ZERO_GPU else 192), label="Upscaler Tile Size", info="0 = no tiling")
                             upscaler_tile_overlap = gr.Slider(minimum=0, maximum=48, step=1, value=8, label="Upscaler Tile Overlap")
                         with gr.Row():
                             hires_steps = gr.Slider(minimum=0, value=30, maximum=100, step=1, label="Hires Steps")
                             face_restoration_weight = gr.Slider(minimum=0., maximum=1., step=0.001, value=.5, label="Weight", info="(0 = maximum effect, 1 = minimum effect)")
                 with gr.Tab("Translation Settings"):
+                    chatbot = gr.Chatbot(type="messages", render_markdown=False, visible=False) # component for auto-translation
                     chat_model = gr.Dropdown(choices=get_dolphin_models(), value=get_dolphin_models()[0], allow_custom_value=True, label="Model")
                     chat_model_info = gr.Markdown(value=get_dolphin_model_info(get_dolphin_models()[0]), label="Model info")
                     chat_format = gr.Dropdown(choices=get_llm_formats(), value=get_dolphin_model_format(get_dolphin_models()[0]), label="Message format")
     gr.LoginButton()
     gr.DuplicateButton(value="Duplicate Space for private use (This demo does not work on CPU. Requires GPU Space)")
+if __name__ == "__main__":
+    demo.queue()
+    demo.launch(show_error=True, share=False, debug=True, ssr_mode=False)

constants.py CHANGED Viewed

@@ -9,6 +9,8 @@ from stablepy import (
     IP_ADAPTERS_SDXL,
 )
 # - **Download Models**
 DOWNLOAD_MODEL = "https://huggingface.co/TechnoByte/MilkyWonderland/resolve/main/milkyWonderland_v40.safetensors"
@@ -23,12 +25,12 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'Laxhar/noobai-XL-1.1',
     'Laxhar/noobai-XL-Vpred-1.0',
     'black-forest-labs/FLUX.1-dev',
     'John6666/blue-pencil-flux1-v021-fp8-flux',
     'John6666/wai-ani-flux-v10forfp8-fp8-flux',
     'John6666/xe-anime-flux-v04-fp8-flux',
     'John6666/lyh-anime-flux-v2a1-fp8-flux',
     'John6666/carnival-unchained-v10-fp8-flux',
-    'John6666/iniverse-mix-xl-sfwnsfw-fluxdfp16nsfwv11-fp8-flux',
     'Freepik/flux.1-lite-8B-alpha',
     'shauray/FluxDev-HyperSD-merged',
     'mikeyandfriends/PixelWave_FLUX.1-dev_03',
@@ -37,23 +39,19 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     # 'ostris/OpenFLUX.1',
     'shuttleai/shuttle-3-diffusion',
     'Laxhar/noobai-XL-1.0',
-    'John6666/noobai-xl-nai-xl-epsilonpred10version-sdxl',
     'Laxhar/noobai-XL-0.77',
     'John6666/noobai-xl-nai-xl-epsilonpred075version-sdxl',
     'Laxhar/noobai-XL-0.6',
     'John6666/noobai-xl-nai-xl-epsilonpred05version-sdxl',
     'John6666/noobai-cyberfix-v10-sdxl',
     'John6666/noobaiiter-xl-vpred-v075-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-v40-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-ntrmix35-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-v777-sdxl',
-    'John6666/ntr-mix-illustrious-xl-noob-xl-v777forlora-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xi-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xii-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xiii-sdxl',
     'John6666/mistoon-anime-v10illustrious-sdxl',
-    'John6666/hassaku-xl-illustrious-v10-sdxl',
-    'John6666/hassaku-xl-illustrious-v10style-sdxl',
     'John6666/haruki-mix-illustrious-v10-sdxl',
     'John6666/noobreal-v10-sdxl',
     'John6666/complicated-noobai-merge-vprediction-sdxl',
@@ -64,6 +62,7 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'Laxhar/noobai-XL-Vpred-0.65',
     'Laxhar/noobai-XL-Vpred-0.6',
     'John6666/cat-tower-noobai-xl-checkpoint-v14vpred-sdxl',
     'John6666/noobai-xl-nai-xl-vpred05version-sdxl',
     'John6666/noobai-fusion2-vpred-itercomp-v1-sdxl',
     'John6666/noobai-xl-nai-xl-vpredtestversion-sdxl',
@@ -74,19 +73,34 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/obsession-illustriousxl-v21-sdxl',
     'John6666/obsession-illustriousxl-v30-sdxl',
     'John6666/obsession-illustriousxl-v31-sdxl',
     'John6666/wai-nsfw-illustrious-v70-sdxl',
     'John6666/illustrious-pony-mix-v3-sdxl',
-    'John6666/nova-anime-xl-illustriousv10-sdxl',
-    'John6666/nova-orange-xl-v30-sdxl',
     'John6666/silvermoon-mix03-illustrious-v10-sdxl',
     'eienmojiki/Anything-XL',
     'eienmojiki/Starry-XL-v5.2',
     'John6666/meinaxl-v2-sdxl',
     'Eugeoter/artiwaifu-diffusion-2.0',
     'comin/IterComp',
-    'John6666/epicrealism-xl-vxiabeast-sdxl',
-    'John6666/epicrealism-xl-v10kiss2-sdxl',
     'John6666/epicrealism-xl-v8kiss-sdxl',
     'misri/zavychromaxl_v80',
     'SG161222/RealVisXL_V4.0',
     'SG161222/RealVisXL_V5.0',
@@ -102,8 +116,10 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/ebara-mfcg-pony-mix-v12-sdxl',
     'John6666/t-ponynai3-v51-sdxl',
     'John6666/t-ponynai3-v65-sdxl',
     'John6666/prefect-pony-xl-v3-sdxl',
     'John6666/prefect-pony-xl-v4-sdxl',
     'John6666/mala-anime-mix-nsfw-pony-xl-v5-sdxl',
     'John6666/wai-ani-nsfw-ponyxl-v10-sdxl',
     'John6666/wai-real-mix-v11-sdxl',
@@ -111,13 +127,14 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/wai-c-v6-sdxl',
     'John6666/iniverse-mix-xl-sfwnsfw-pony-guofeng-v43-sdxl',
     'John6666/sifw-annihilation-xl-v2-sdxl',
     'John6666/photo-realistic-pony-v5-sdxl',
     'John6666/pony-realism-v21main-sdxl',
     'John6666/pony-realism-v22main-sdxl',
-    'John6666/cyberrealistic-pony-v63-sdxl',
-    'John6666/cyberrealistic-pony-v64-sdxl',
     'John6666/cyberrealistic-pony-v65-sdxl',
     'John6666/cyberrealistic-pony-v7-sdxl',
     'GraydientPlatformAPI/realcartoon-pony-diffusion',
     'John6666/nova-anime-xl-pony-v5-sdxl',
     'John6666/autismmix-sdxl-autismmix-pony-sdxl',
@@ -127,13 +144,15 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'John6666/duchaiten-pony-real-v11fix-sdxl',
     'John6666/duchaiten-pony-real-v20-sdxl',
     'John6666/duchaiten-pony-xl-no-score-v70-sdxl',
-    'Spestly/OdysseyXL-3.0',
-    'Spestly/OdysseyXL-4.0',
     'KBlueLeaf/Kohaku-XL-Zeta',
     'cagliostrolab/animagine-xl-3.1',
     'yodayo-ai/kivotos-xl-2.0',
     'yodayo-ai/holodayo-xl-2.1',
     'yodayo-ai/clandestine-xl-1.0',
     'digiplay/majicMIX_sombre_v2',
     'digiplay/majicMIX_realistic_v6',
     'digiplay/majicMIX_realistic_v7',
@@ -159,9 +178,9 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'GraydientPlatformAPI/realcartoon3d-17',
     'GraydientPlatformAPI/realcartoon-pixar11',
     'GraydientPlatformAPI/realcartoon-real17',
-    'nitrosocke/Ghibli-Diffusion',
 ]
 DIFFUSERS_FORMAT_LORAS = [
     "nerijs/animation2k-flux",
     "XLabs-AI/flux-RealismLora",
@@ -183,8 +202,11 @@ DIRECTORY_VAES = 'vaes'
 DIRECTORY_EMBEDS = 'embedings'
 DIRECTORY_UPSCALERS = 'upscalers'
-CACHE_HF = "/home/user/.cache/huggingface/hub/"
 STORAGE_ROOT = "/home/user/"
 TASK_STABLEPY = {
     'txt2img': 'txt2img',
@@ -226,6 +248,7 @@ UPSCALER_DICT_GUI = {
     # "realesr-general-x4v3": "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth",
     # "realesr-general-wdn-x4v3": "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth",
     "4x-UltraSharp": "https://huggingface.co/Shandypur/ESRGAN-4x-UltraSharp/resolve/main/4x-UltraSharp.pth",
     "4x_foolhardy_Remacri": "https://huggingface.co/FacehugmanIII/4x_foolhardy_Remacri/resolve/main/4x_foolhardy_Remacri.pth",
     "Remacri4xExtraSmoother": "https://huggingface.co/hollowstrawberry/upscalers-backup/resolve/main/ESRGAN/Remacri%204x%20ExtraSmoother.pth",
     "AnimeSharp4x": "https://huggingface.co/hollowstrawberry/upscalers-backup/resolve/main/ESRGAN/AnimeSharp%204x.pth",
@@ -359,9 +382,11 @@ SUBTITLE_GUI = (
     " to perform different tasks in image generation."
 )
 HELP_GUI = (
-    """### Help:
-    - The current space runs on a ZERO GPU which is assigned for approximately 60 seconds; Therefore, if you submit expensive tasks, the operation may be canceled upon reaching the maximum allowed time with 'GPU TASK ABORTED'.
     - Distorted or strange images often result from high prompt weights, so it's best to use low weights and scales, and consider using Classic variants like 'Classic-original'.
     - For better results with Pony Diffusion, try using sampler DPM++ 1s or DPM2 with Compel or Classic prompt weights.
     """
@@ -485,7 +510,7 @@ EXAMPLES_GUI = [
         20,
         4.0,
         -1,
-        "loras/Coloring_book_-_LineArt.safetensors",
         1.0,
         "DPM++ 2M SDE",
         1024,
@@ -580,6 +605,7 @@ EXAMPLES_GUI = [
 RESOURCES = (
     """### Resources
     - John6666's space has some great features you might find helpful [link](https://huggingface.co/spaces/John6666/DiffuseCraftMod).
-    - You can also try the image generator in Colab’s free tier, which provides free GPU [link](https://github.com/R3gm/SD_diffusers_interactive).
     """
-)

     IP_ADAPTERS_SDXL,
 )
+IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
 # - **Download Models**
 DOWNLOAD_MODEL = "https://huggingface.co/TechnoByte/MilkyWonderland/resolve/main/milkyWonderland_v40.safetensors"
     'Laxhar/noobai-XL-1.1',
     'Laxhar/noobai-XL-Vpred-1.0',
     'black-forest-labs/FLUX.1-dev',
+    'black-forest-labs/FLUX.1-Krea-dev',
     'John6666/blue-pencil-flux1-v021-fp8-flux',
     'John6666/wai-ani-flux-v10forfp8-fp8-flux',
     'John6666/xe-anime-flux-v04-fp8-flux',
     'John6666/lyh-anime-flux-v2a1-fp8-flux',
     'John6666/carnival-unchained-v10-fp8-flux',
     'Freepik/flux.1-lite-8B-alpha',
     'shauray/FluxDev-HyperSD-merged',
     'mikeyandfriends/PixelWave_FLUX.1-dev_03',
     # 'ostris/OpenFLUX.1',
     'shuttleai/shuttle-3-diffusion',
     'Laxhar/noobai-XL-1.0',
     'Laxhar/noobai-XL-0.77',
     'John6666/noobai-xl-nai-xl-epsilonpred075version-sdxl',
     'Laxhar/noobai-XL-0.6',
     'John6666/noobai-xl-nai-xl-epsilonpred05version-sdxl',
     'John6666/noobai-cyberfix-v10-sdxl',
     'John6666/noobaiiter-xl-vpred-v075-sdxl',
+    'John6666/ripplemix-noob-vpred10-illustrious01-v14-sdxl',
+    'John6666/sigmaih-15-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xi-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xii-sdxl',
     'John6666/ntr-mix-illustrious-xl-noob-xl-xiii-sdxl',
     'John6666/mistoon-anime-v10illustrious-sdxl',
+    'John6666/hassaku-xl-illustrious-v22-sdxl',
     'John6666/haruki-mix-illustrious-v10-sdxl',
     'John6666/noobreal-v10-sdxl',
     'John6666/complicated-noobai-merge-vprediction-sdxl',
     'Laxhar/noobai-XL-Vpred-0.65',
     'Laxhar/noobai-XL-Vpred-0.6',
     'John6666/cat-tower-noobai-xl-checkpoint-v14vpred-sdxl',
+    'John6666/cat-tower-noobai-xl-checkpoint-v15vpred-sdxl',
     'John6666/noobai-xl-nai-xl-vpred05version-sdxl',
     'John6666/noobai-fusion2-vpred-itercomp-v1-sdxl',
     'John6666/noobai-xl-nai-xl-vpredtestversion-sdxl',
     'John6666/obsession-illustriousxl-v21-sdxl',
     'John6666/obsession-illustriousxl-v30-sdxl',
     'John6666/obsession-illustriousxl-v31-sdxl',
+    'John6666/one-obsession-13-sdxl',
+    'John6666/one-obsession-14-24d-sdxl',
+    'John6666/one-obsession-15-noobai-sdxl',
+    'John6666/one-obsession-v16-noobai-sdxl',
+    'John6666/prefect-illustrious-xl-v3-sdxl',
     'John6666/wai-nsfw-illustrious-v70-sdxl',
+    'John6666/wai-nsfw-illustrious-sdxl-v140-sdxl',
     'John6666/illustrious-pony-mix-v3-sdxl',
+    'John6666/nova-anime-xl-il-v90-sdxl',
+    'John6666/nova-anime-xl-il-v110-sdxl',
+    'John6666/nova-orange-xl-re-v10-sdxl',
+    'John6666/nova-orange-xl-v110-sdxl',
+    'John6666/nova-orange-xl-re-v20-sdxl',
+    'John6666/nova-unreal-xl-v60-sdxl',
+    'John6666/nova-unreal-xl-v70-sdxl',
+    'John6666/nova-unreal-xl-v80-sdxl',
+    'John6666/nova-cartoon-xl-v40-sdxl',
     'John6666/silvermoon-mix03-illustrious-v10-sdxl',
     'eienmojiki/Anything-XL',
     'eienmojiki/Starry-XL-v5.2',
+    'votepurchase/plantMilkModelSuite_walnut',
     'John6666/meinaxl-v2-sdxl',
     'Eugeoter/artiwaifu-diffusion-2.0',
     'comin/IterComp',
     'John6666/epicrealism-xl-v8kiss-sdxl',
+    'John6666/epicrealism-xl-v10kiss2-sdxl',
+    'John6666/epicrealism-xl-vxiabeast-sdxl',
+    'John6666/epicrealism-xl-vxvii-crystal-clear-realism-sdxl',
     'misri/zavychromaxl_v80',
     'SG161222/RealVisXL_V4.0',
     'SG161222/RealVisXL_V5.0',
     'John6666/ebara-mfcg-pony-mix-v12-sdxl',
     'John6666/t-ponynai3-v51-sdxl',
     'John6666/t-ponynai3-v65-sdxl',
+    'John6666/t-ponynai3-v7-sdxl',
     'John6666/prefect-pony-xl-v3-sdxl',
     'John6666/prefect-pony-xl-v4-sdxl',
+    'John6666/prefect-pony-xl-v50-sdxl',
     'John6666/mala-anime-mix-nsfw-pony-xl-v5-sdxl',
     'John6666/wai-ani-nsfw-ponyxl-v10-sdxl',
     'John6666/wai-real-mix-v11-sdxl',
     'John6666/wai-c-v6-sdxl',
     'John6666/iniverse-mix-xl-sfwnsfw-pony-guofeng-v43-sdxl',
     'John6666/sifw-annihilation-xl-v2-sdxl',
+    'John6666/sifw-annihilation-xl-v305illustrious-beta-sdxl',
     'John6666/photo-realistic-pony-v5-sdxl',
     'John6666/pony-realism-v21main-sdxl',
     'John6666/pony-realism-v22main-sdxl',
+    'John6666/pony-realism-v23-ultra-sdxl',
     'John6666/cyberrealistic-pony-v65-sdxl',
     'John6666/cyberrealistic-pony-v7-sdxl',
+    'John6666/cyberrealistic-pony-v127-alternative-sdxl',
     'GraydientPlatformAPI/realcartoon-pony-diffusion',
     'John6666/nova-anime-xl-pony-v5-sdxl',
     'John6666/autismmix-sdxl-autismmix-pony-sdxl',
     'John6666/duchaiten-pony-real-v11fix-sdxl',
     'John6666/duchaiten-pony-real-v20-sdxl',
     'John6666/duchaiten-pony-xl-no-score-v70-sdxl',
     'KBlueLeaf/Kohaku-XL-Zeta',
     'cagliostrolab/animagine-xl-3.1',
+    'cagliostrolab/animagine-xl-4.0',
     'yodayo-ai/kivotos-xl-2.0',
     'yodayo-ai/holodayo-xl-2.1',
     'yodayo-ai/clandestine-xl-1.0',
+    'https://huggingface.co/chemwolf/Karmix-XL-v0/resolve/main/Karmix-XL-v0.safetensors?download=true',
+    'https://civitai.com/api/download/models/128713?type=Model&format=SafeTensor&size=pruned&fp=fp16',
+    'https://civitai.com/models/30240?modelVersionId=125771',
     'digiplay/majicMIX_sombre_v2',
     'digiplay/majicMIX_realistic_v6',
     'digiplay/majicMIX_realistic_v7',
     'GraydientPlatformAPI/realcartoon3d-17',
     'GraydientPlatformAPI/realcartoon-pixar11',
     'GraydientPlatformAPI/realcartoon-real17',
 ]
 DIFFUSERS_FORMAT_LORAS = [
     "nerijs/animation2k-flux",
     "XLabs-AI/flux-RealismLora",
 DIRECTORY_EMBEDS = 'embedings'
 DIRECTORY_UPSCALERS = 'upscalers'
 STORAGE_ROOT = "/home/user/"
+CACHE_HF_ROOT = os.path.expanduser(os.getenv("HF_HOME")) if os.getenv("HF_HOME") else os.path.expanduser("~/cache/huggingface")
+CACHE_HF = os.path.join(CACHE_HF_ROOT, "hub")
+if IS_ZERO_GPU:
+    os.environ["HF_HOME"] = CACHE_HF
 TASK_STABLEPY = {
     'txt2img': 'txt2img',
     # "realesr-general-x4v3": "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-x4v3.pth",
     # "realesr-general-wdn-x4v3": "https://github.com/xinntao/Real-ESRGAN/releases/download/v0.2.5.0/realesr-general-wdn-x4v3.pth",
     "4x-UltraSharp": "https://huggingface.co/Shandypur/ESRGAN-4x-UltraSharp/resolve/main/4x-UltraSharp.pth",
+    "Real-ESRGAN-Anime-finetuning": "https://huggingface.co/danhtran2mind/Real-ESRGAN-Anime-finetuning/resolve/main/Real-ESRGAN-Anime-finetuning.pth",
     "4x_foolhardy_Remacri": "https://huggingface.co/FacehugmanIII/4x_foolhardy_Remacri/resolve/main/4x_foolhardy_Remacri.pth",
     "Remacri4xExtraSmoother": "https://huggingface.co/hollowstrawberry/upscalers-backup/resolve/main/ESRGAN/Remacri%204x%20ExtraSmoother.pth",
     "AnimeSharp4x": "https://huggingface.co/hollowstrawberry/upscalers-backup/resolve/main/ESRGAN/AnimeSharp%204x.pth",
     " to perform different tasks in image generation."
 )
+msg_zero = "" if not IS_ZERO_GPU else "- The current space runs on a ZERO GPU which is assigned for approximately 60 seconds; Therefore, if you submit expensive tasks, the operation may be canceled upon reaching the maximum allowed time with 'GPU TASK ABORTED'."
 HELP_GUI = (
+    f"""### Help:
+    {msg_zero}
     - Distorted or strange images often result from high prompt weights, so it's best to use low weights and scales, and consider using Classic variants like 'Classic-original'.
     - For better results with Pony Diffusion, try using sampler DPM++ 1s or DPM2 with Compel or Classic prompt weights.
     """
         20,
         4.0,
         -1,
+        ("loras/Coloring_book_-_LineArt.safetensors" if os.path.exists("loras/Coloring_book_-_LineArt.safetensors") else "None"),
         1.0,
         "DPM++ 2M SDE",
         1024,
 RESOURCES = (
     """### Resources
     - John6666's space has some great features you might find helpful [link](https://huggingface.co/spaces/John6666/DiffuseCraftMod).
+    - Try the image generator in Colab’s free tier, which provides free GPU [link](https://github.com/R3gm/SD_diffusers_interactive).
+    - `DiffuseCraft` in Colab:[link](https://github.com/R3gm/DiffuseCraft?tab=readme-ov-file#diffusecraft).
     """
+)

dc.py CHANGED Viewed

@@ -1,5 +1,6 @@
 import spaces
 import os
 from stablepy import (
     Model_Diffusers,
     SCHEDULE_TYPE_OPTIONS,
@@ -23,6 +24,7 @@ from constants import (
     DIFFUSERS_CONTROLNET_MODEL,
     IP_MODELS,
     MODE_IP_OPTIONS,
 )
 from stablepy.diffusers_vanilla.style_prompt_config import STYLE_NAMES
 import torch
@@ -41,6 +43,7 @@ from utils import (
     progress_step_bar,
     html_template_message,
     escape_html,
 )
 from image_processor import preprocessor_tab
 from datetime import datetime
@@ -53,15 +56,17 @@ from diffusers import FluxPipeline
 # import urllib.parse
 import subprocess
-IS_ZERO = True if os.getenv("SPACES_ZERO_GPU", None) else False
-if IS_ZERO:
     subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
-    torch.backends.cuda.matmul.allow_tf32 = True
 ImageFile.LOAD_TRUNCATED_IMAGES = True
 # os.environ["PYTORCH_NO_CUDA_MEMORY_CACHING"] = "1"
-print(os.getenv("SPACES_ZERO_GPU"))
 ## BEGIN MOD
 logging.getLogger("diffusers").setLevel(logging.ERROR)
@@ -103,14 +108,11 @@ for directory in directories:
 # Download stuffs
 for url in [url.strip() for url in download_model.split(',')]:
-    if not os.path.exists(f"./models/{url.split('/')[-1]}"):
-        download_things(DIRECTORY_MODELS, url, HF_TOKEN, CIVITAI_API_KEY)
 for url in [url.strip() for url in download_vae.split(',')]:
-    if not os.path.exists(f"./vaes/{url.split('/')[-1]}"):
-        download_things(DIRECTORY_VAES, url, HF_TOKEN, CIVITAI_API_KEY)
 for url in [url.strip() for url in download_lora.split(',')]:
-    if not os.path.exists(f"./loras/{url.split('/')[-1]}"):
-        download_things(DIRECTORY_LORAS, url, HF_TOKEN, CIVITAI_API_KEY)
 # Download Embeddings
 for url_embed in DOWNLOAD_EMBEDS:
@@ -138,15 +140,32 @@ def get_embed_list(pipeline_name):
 print('\033[33m🏁 Download and listing of valid models completed.\033[0m')
-flux_repo = "camenduru/FLUX.1-dev-diffusers"
-flux_pipe = FluxPipeline.from_pretrained(
-    flux_repo,
-    transformer=None,
-    torch_dtype=torch.bfloat16,
-)#.to("cuda")
-components = flux_pipe.components
-delete_model(flux_repo)
-#components = None
 ## BEGIN MOD
 class GuiSD:
@@ -164,6 +183,15 @@ class GuiSD:
             removal_candidate = self.inventory.pop(0)
             delete_model(removal_candidate)
     def update_inventory(self, model_name):
         if model_name not in single_file_model_list:
             self.inventory = [
@@ -174,19 +202,24 @@ class GuiSD:
     def load_new_model(self, model_name, vae_model, task, controlnet_model, progress=gr.Progress(track_tqdm=True)):
         # download link model > model_name
-        if "http" in model_name: #
             model_name, model_type = download_link_model(model_name, DIRECTORY_MODELS) #
             is_link_model = True #
         else: is_link_model = False #
-        self.update_storage_models()
         vae_model = vae_model if vae_model != "None" else None
         model_type = get_model_type(model_name) if not is_link_model else model_type #
         dtype_model = torch.bfloat16 if model_type == "FLUX" else torch.float16
         if not os.path.exists(model_name):
-            print("debug", model_name, vae_model, task, controlnet_model)
             _ = download_diffuser_repo(
                 repo_name=model_name,
                 model_type=model_type,
@@ -231,10 +264,10 @@ class GuiSD:
                     type_model_precision=dtype_model,
                     retain_task_model_in_cache=False,
                     controlnet_model=controlnet_model,
-                    device="cpu",
                     env_components=components,
                 )
-                self.model.advanced_params(image_preprocessor_cuda_active=True)
             else:
                 if self.model.base_model_id != model_name:
                     load_now_time = datetime.now()
@@ -244,7 +277,8 @@ class GuiSD:
                         print("Waiting for the previous model's time ops...")
                         time.sleep(9 - elapsed_time)
-                self.model.device = torch.device("cpu")
                 self.model.load_pipe(
                     model_name,
                     task_name=TASK_STABLEPY[task],
@@ -404,7 +438,7 @@ class GuiSD:
         lora_model_list = get_lora_model_list()
 ## END MOD
-        print("Config model:", model_name, vae_model, loras_list)
         task = TASK_STABLEPY[task]
@@ -502,19 +536,19 @@ class GuiSD:
             "distance_threshold": distance_threshold,
             "recolor_gamma_correction": float(recolor_gamma_correction),
             "tile_blur_sigma": int(tile_blur_sigma),
-            "lora_A": lora1 if lora1 != "None" else None,
             "lora_scale_A": lora_scale1,
-            "lora_B": lora2 if lora2 != "None" else None,
             "lora_scale_B": lora_scale2,
-            "lora_C": lora3 if lora3 != "None" else None,
             "lora_scale_C": lora_scale3,
-            "lora_D": lora4 if lora4 != "None" else None,
             "lora_scale_D": lora_scale4,
-            "lora_E": lora5 if lora5 != "None" else None,
             "lora_scale_E": lora_scale5,
-            "lora_F": lora6 if lora6 != "None" else None,
             "lora_scale_F": lora_scale6,
-            "lora_G": lora7 if lora7 != "None" else None,
             "lora_scale_G": lora_scale7,
 ## BEGIN MOD
             "textual_inversion": get_embed_list(self.model.class_name) if textual_inversion else [],
@@ -574,11 +608,11 @@ class GuiSD:
         # kwargs for diffusers pipeline
         if guidance_rescale:
             pipe_params["guidance_rescale"] = guidance_rescale
-        self.model.device = torch.device("cuda:0")
-        if hasattr(self.model.pipe, "transformer") and loras_list != ["None"] * self.model.num_loras:
-            self.model.pipe.transformer.to(self.model.device)
-            print("transformer to cuda")
         actual_progress = 0
         info_images = gr.update()
@@ -608,7 +642,7 @@ class GuiSD:
                 download_links = "<br>".join(
                     [
-                        f'<a href="{path.replace("/images/", "/file=/home/user/app/images/")}" download="{os.path.basename(path)}">Download Image {i + 1}</a>'
                         for i, path in enumerate(image_path)
                     ]
                 )
@@ -720,7 +754,8 @@ def sd_gen_generate_pipeline(*args):
 @spaces.GPU(duration=15)
 def process_upscale(image, upscaler_name, upscaler_size):
-    if image is None: return None
     from stablepy.diffusers_vanilla.utils import save_pil_image_with_metadata
     from stablepy import load_upscaler_model
@@ -737,7 +772,7 @@ def process_upscale(image, upscaler_name, upscaler_size):
         name_upscaler = f"./{DIRECTORY_UPSCALERS}/{name_upscaler.split('/')[-1]}"
-    scaler_beta = load_upscaler_model(model=name_upscaler, tile=0, tile_overlap=8, device="cuda", half=True)
     image_up = scaler_beta.upscale(image, upscaler_size, True)
     image_path = save_pil_image_with_metadata(image_up, f'{os.getcwd()}/up_images', exif_image)
@@ -746,8 +781,8 @@ def process_upscale(image, upscaler_name, upscaler_size):
 # https://huggingface.co/spaces/BestWishYsh/ConsisID-preview-Space/discussions/1#674969a022b99c122af5d407
-dynamic_gpu_duration.zerogpu = True
-sd_gen_generate_pipeline.zerogpu = True
 sd_gen = GuiSD()

 import spaces
 import os
+from argparse import ArgumentParser
 from stablepy import (
     Model_Diffusers,
     SCHEDULE_TYPE_OPTIONS,
     DIFFUSERS_CONTROLNET_MODEL,
     IP_MODELS,
     MODE_IP_OPTIONS,
+    CACHE_HF_ROOT,
 )
 from stablepy.diffusers_vanilla.style_prompt_config import STYLE_NAMES
 import torch
     progress_step_bar,
     html_template_message,
     escape_html,
+    clear_hf_cache,
 )
 from image_processor import preprocessor_tab
 from datetime import datetime
 # import urllib.parse
 import subprocess
+IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
+if IS_ZERO_GPU:
     subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
+IS_GPU_MODE = True if IS_ZERO_GPU else (True if torch.cuda.is_available() else False)
+img_path = "./images/"
+allowed_path = os.path.abspath(img_path)
+delete_cache_time = (9600, 9600) if IS_ZERO_GPU else (86400, 86400)
 ImageFile.LOAD_TRUNCATED_IMAGES = True
+torch.backends.cuda.matmul.allow_tf32 = True
 # os.environ["PYTORCH_NO_CUDA_MEMORY_CACHING"] = "1"
 ## BEGIN MOD
 logging.getLogger("diffusers").setLevel(logging.ERROR)
 # Download stuffs
 for url in [url.strip() for url in download_model.split(',')]:
+    download_things(DIRECTORY_MODELS, url, HF_TOKEN, CIVITAI_API_KEY)
 for url in [url.strip() for url in download_vae.split(',')]:
+    download_things(DIRECTORY_VAES, url, HF_TOKEN, CIVITAI_API_KEY)
 for url in [url.strip() for url in download_lora.split(',')]:
+    download_things(DIRECTORY_LORAS, url, HF_TOKEN, CIVITAI_API_KEY)
 # Download Embeddings
 for url_embed in DOWNLOAD_EMBEDS:
 print('\033[33m🏁 Download and listing of valid models completed.\033[0m')
+components = None
+if IS_ZERO_GPU:
+    flux_repo = "camenduru/FLUX.1-dev-diffusers"
+    flux_pipe = FluxPipeline.from_pretrained(
+        flux_repo,
+        transformer=None,
+        torch_dtype=torch.bfloat16,
+    )#.to("cuda")
+    components = flux_pipe.components
+    delete_model(flux_repo)
+parser = ArgumentParser(description='DiffuseCraft: Create images from text prompts.', add_help=True)
+parser.add_argument("--share", action="store_true", dest="share_enabled", default=False, help="Enable sharing")
+parser.add_argument('--theme', type=str, default="NoCrypt/miku", help='Set the theme (default: NoCrypt/miku)')
+parser.add_argument("--ssr", action="store_true", help="Enable SSR (Server-Side Rendering)")
+parser.add_argument("--log-level", type=str, default="INFO", choices=["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"], help="Set logging level (default: INFO)")
+args = parser.parse_args()
+logger.setLevel(
+    "INFO" if IS_ZERO_GPU else getattr(logging, args.log_level.upper())
+)
+def lora_chk(lora_):
+    if isinstance(lora_, str) and lora_.strip() not in ["", "None"]:
+        return lora_
+    return None
 ## BEGIN MOD
 class GuiSD:
             removal_candidate = self.inventory.pop(0)
             delete_model(removal_candidate)
+        # Cleanup after 60 seconds of inactivity
+        lowPrioCleanup = max((datetime.now() - self.last_load).total_seconds(), 0) > 60
+        if lowPrioCleanup and not self.status_loading and get_used_storage_gb(CACHE_HF_ROOT) > (storage_floor_gb * 2):
+            print("Cleaning up Hugging Face cache...")
+            clear_hf_cache()
+            self.inventory = [
+                m for m in self.inventory if os.path.exists(m)
+            ]
     def update_inventory(self, model_name):
         if model_name not in single_file_model_list:
             self.inventory = [
     def load_new_model(self, model_name, vae_model, task, controlnet_model, progress=gr.Progress(track_tqdm=True)):
         # download link model > model_name
+        if model_name.startswith("http"): #
+            yield f"Downloading model: {model_name}"
+            #model_name = download_things(DIRECTORY_MODELS, model_name, HF_TOKEN, CIVITAI_API_KEY)
             model_name, model_type = download_link_model(model_name, DIRECTORY_MODELS) #
+            if not model_name:
+                raise ValueError("Error retrieving model information from URL")
             is_link_model = True #
         else: is_link_model = False #
+        if IS_ZERO_GPU:
+            self.update_storage_models()
         vae_model = vae_model if vae_model != "None" else None
         model_type = get_model_type(model_name) if not is_link_model else model_type #
         dtype_model = torch.bfloat16 if model_type == "FLUX" else torch.float16
         if not os.path.exists(model_name):
+            logger.debug(f"model_name={model_name}, vae_model={vae_model}, task={task}, controlnet_model={controlnet_model}")
             _ = download_diffuser_repo(
                 repo_name=model_name,
                 model_type=model_type,
                     type_model_precision=dtype_model,
                     retain_task_model_in_cache=False,
                     controlnet_model=controlnet_model,
+                    device="cpu" if IS_ZERO_GPU else None,
                     env_components=components,
                 )
+                self.model.advanced_params(image_preprocessor_cuda_active=IS_GPU_MODE)
             else:
                 if self.model.base_model_id != model_name:
                     load_now_time = datetime.now()
                         print("Waiting for the previous model's time ops...")
                         time.sleep(9 - elapsed_time)
+                if IS_ZERO_GPU:
+                    self.model.device = torch.device("cpu")
                 self.model.load_pipe(
                     model_name,
                     task_name=TASK_STABLEPY[task],
         lora_model_list = get_lora_model_list()
 ## END MOD
+        logger.debug(f"Config model: {model_name}, {vae_model}, {loras_list}")
         task = TASK_STABLEPY[task]
             "distance_threshold": distance_threshold,
             "recolor_gamma_correction": float(recolor_gamma_correction),
             "tile_blur_sigma": int(tile_blur_sigma),
+            "lora_A": lora_chk(lora1),
             "lora_scale_A": lora_scale1,
+            "lora_B": lora_chk(lora2),
             "lora_scale_B": lora_scale2,
+            "lora_C": lora_chk(lora3),
             "lora_scale_C": lora_scale3,
+            "lora_D": lora_chk(lora4),
             "lora_scale_D": lora_scale4,
+            "lora_E": lora_chk(lora5),
             "lora_scale_E": lora_scale5,
+            "lora_F": lora_chk(lora6),
             "lora_scale_F": lora_scale6,
+            "lora_G": lora_chk(lora7),
             "lora_scale_G": lora_scale7,
 ## BEGIN MOD
             "textual_inversion": get_embed_list(self.model.class_name) if textual_inversion else [],
         # kwargs for diffusers pipeline
         if guidance_rescale:
             pipe_params["guidance_rescale"] = guidance_rescale
+        if IS_ZERO_GPU:
+            self.model.device = torch.device("cuda:0")
+            if hasattr(self.model.pipe, "transformer") and loras_list != ["None"] * self.model.num_loras:
+                self.model.pipe.transformer.to(self.model.device)
+                logger.debug("transformer to cuda")
         actual_progress = 0
         info_images = gr.update()
                 download_links = "<br>".join(
                     [
+                        f'<a href="{path.replace("/images/", f"/gradio_api/file={allowed_path}/")}" download="{os.path.basename(path)}">Download Image {i + 1}</a>'
                         for i, path in enumerate(image_path)
                     ]
                 )
 @spaces.GPU(duration=15)
 def process_upscale(image, upscaler_name, upscaler_size):
+    if image is None:
+        return None
     from stablepy.diffusers_vanilla.utils import save_pil_image_with_metadata
     from stablepy import load_upscaler_model
         name_upscaler = f"./{DIRECTORY_UPSCALERS}/{name_upscaler.split('/')[-1]}"
+    scaler_beta = load_upscaler_model(model=name_upscaler, tile=(0 if IS_ZERO_GPU else 192), tile_overlap=8, device=("cuda" if IS_GPU_MODE else "cpu"), half=IS_GPU_MODE)
     image_up = scaler_beta.upscale(image, upscaler_size, True)
     image_path = save_pil_image_with_metadata(image_up, f'{os.getcwd()}/up_images', exif_image)
 # https://huggingface.co/spaces/BestWishYsh/ConsisID-preview-Space/discussions/1#674969a022b99c122af5d407
+# dynamic_gpu_duration.zerogpu = True
+# sd_gen_generate_pipeline.zerogpu = True
 sd_gen = GuiSD()

env.py CHANGED Viewed

@@ -71,6 +71,7 @@ LOAD_DIFFUSERS_FORMAT_MODEL = [
     'Raelina/Raehoshi-illust-XL-4',
     'Raelina/Raehoshi-illust-XL-5',
     'Raelina/Raehoshi-illust-XL-5.1',
     'camenduru/FLUX.1-dev-diffusers',
     'black-forest-labs/FLUX.1-schnell',
     'sayakpaul/FLUX.1-merged',

     'Raelina/Raehoshi-illust-XL-4',
     'Raelina/Raehoshi-illust-XL-5',
     'Raelina/Raehoshi-illust-XL-5.1',
+    'Raelina/Raehoshi-illust-XL-6',
     'camenduru/FLUX.1-dev-diffusers',
     'black-forest-labs/FLUX.1-schnell',
     'sayakpaul/FLUX.1-merged',

image_processor.py CHANGED Viewed

@@ -92,8 +92,8 @@ def preprocessor_tab():
                     pre_processor_resolution = gr.Slider(minimum=64, maximum=2048, step=64, value=512, label="Preprocessor Resolution")
                     pre_low_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=100, label="'CANNY' low threshold")
                     pre_high_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=200, label="'CANNY' high threshold")
-                    pre_value_threshold = gr.Slider(minimum=1, maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
-                    pre_distance_threshold = gr.Slider(minimum=1, maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
                     pre_recolor_mode = gr.Dropdown(label="'RECOLOR' mode", choices=["luminance", "intensity"], value="luminance")
                     pre_recolor_gamma_correction = gr.Number(minimum=0., maximum=25., value=1., step=0.001, label="'RECOLOR' gamma correction")
                     pre_blur_k_size = gr.Number(minimum=0, maximum=100, value=9, step=1, label="'BLUR' sigma")

                     pre_processor_resolution = gr.Slider(minimum=64, maximum=2048, step=64, value=512, label="Preprocessor Resolution")
                     pre_low_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=100, label="'CANNY' low threshold")
                     pre_high_threshold = gr.Slider(minimum=1, maximum=255, step=1, value=200, label="'CANNY' high threshold")
+                    pre_value_threshold = gr.Slider(minimum=0., maximum=2.0, step=0.01, value=0.1, label="'MLSD' Hough value threshold")
+                    pre_distance_threshold = gr.Slider(minimum=0., maximum=20.0, step=0.01, value=0.1, label="'MLSD' Hough distance threshold")
                     pre_recolor_mode = gr.Dropdown(label="'RECOLOR' mode", choices=["luminance", "intensity"], value="luminance")
                     pre_recolor_gamma_correction = gr.Number(minimum=0., maximum=25., value=1., step=0.001, label="'RECOLOR' gamma correction")
                     pre_blur_k_size = gr.Number(minimum=0, maximum=100, value=9, step=1, label="'BLUR' sigma")

llmdolphin.py CHANGED Viewed

@@ -7,6 +7,7 @@ import gc
 import os
 import urllib
 from typing import Any
 from huggingface_hub import hf_hub_download, HfApi
 from llama_cpp import Llama
 from llama_cpp_agent import LlamaCppAgent, MessagesFormatterType
@@ -376,10 +377,10 @@ def get_raw_prompt(msg: str):
 # https://llama-cpp-python.readthedocs.io/en/latest/api-reference/
 @torch.inference_mode()
-@spaces.GPU(duration=59)
 def dolphin_respond(
     message: str,
-    history: list[tuple[str, str]],
     model: str = default_llm_model_filename,
     system_message: str = get_dolphin_sysprompt(),
     max_tokens: int = 1024,
@@ -434,16 +435,12 @@ def dolphin_respond(
         messages = BasicChatHistory()
         for msn in history:
-            user = {
-                'role': Roles.user,
-                'content': msn[0]
-            }
-            assistant = {
-                'role': Roles.assistant,
-                'content': msn[1]
-            }
-            messages.add_message(user)
-            messages.add_message(assistant)
         stream = agent.get_chat_response(
             message,
@@ -455,28 +452,28 @@ def dolphin_respond(
         progress(0.5, desc="Processing...")
-        outputs = ""
         for output in stream:
-            outputs += output
-            yield [(outputs, None)]
     except Exception as e:
         print(e)
         raise gr.Error(f"Error: {e}")
-        #yield [("", None)]
     finally:
         torch.cuda.empty_cache()
         gc.collect()
 def dolphin_parse(
-    history: list[tuple[str, str]],
     state: dict,
 ):
     try:
         dolphin_sysprompt_mode = get_state(state, "dolphin_sysprompt_mode")
         if dolphin_sysprompt_mode == "Chat with LLM" or not history or len(history) < 1:
             return "", gr.update(), gr.update()
-        msg = history[-1][0]
         raw_prompt = get_raw_prompt(msg)
         prompts = []
         if dolphin_sysprompt_mode == "Japanese to Danbooru Dictionary" and is_japanese(raw_prompt):
@@ -490,10 +487,10 @@ def dolphin_parse(
 @torch.inference_mode()
-@spaces.GPU(duration=59)
 def dolphin_respond_auto(
     message: str,
-    history: list[tuple[str, str]],
     model: str = default_llm_model_filename,
     system_message: str = get_dolphin_sysprompt(),
     max_tokens: int = 1024,
@@ -549,16 +546,12 @@ def dolphin_respond_auto(
         messages = BasicChatHistory()
         for msn in history:
-            user = {
-                'role': Roles.user,
-                'content': msn[0]
-            }
-            assistant = {
-                'role': Roles.assistant,
-                'content': msn[1]
-            }
-            messages.add_message(user)
-            messages.add_message(assistant)
         progress(0, desc="Translating...")
         stream = agent.get_chat_response(
@@ -571,13 +564,16 @@ def dolphin_respond_auto(
         progress(0.5, desc="Processing...")
-        outputs = ""
         for output in stream:
-            outputs += output
-            yield [(outputs, None)], gr.update(), gr.update()
     except Exception as e:
         print(e)
-        yield [("", None)], gr.update(), gr.update()
     finally:
         torch.cuda.empty_cache()
         gc.collect()
@@ -585,14 +581,14 @@ def dolphin_respond_auto(
 def dolphin_parse_simple(
     message: str,
-    history: list[tuple[str, str]],
     state: dict,
 ):
     try:
         #if not is_japanese(message): return message
         dolphin_sysprompt_mode = get_state(state, "dolphin_sysprompt_mode")
         if dolphin_sysprompt_mode == "Chat with LLM" or not history or len(history) < 1: return message
-        msg = history[-1][0]
         raw_prompt = get_raw_prompt(msg)
         prompts = []
         if dolphin_sysprompt_mode == "Japanese to Danbooru Dictionary" and is_japanese(raw_prompt):
@@ -611,10 +607,10 @@ cv2.setNumThreads(1)
 @torch.inference_mode()
-@spaces.GPU(duration=59)
 def respond_playground(
     message: str,
-    history: list[tuple[str, str]],
     model: str = default_llm_model_filename,
     system_message: str = get_dolphin_sysprompt(),
     max_tokens: int = 1024,
@@ -669,10 +665,12 @@ def respond_playground(
         # Add user and assistant messages to the history
         for msn in history:
-            user = {'role': Roles.user, 'content': msn[0]}
-            assistant = {'role': Roles.assistant, 'content': msn[1]}
-            messages.add_message(user)
-            messages.add_message(assistant)
         # Stream the response
         stream = agent.get_chat_response(
@@ -683,14 +681,14 @@ def respond_playground(
             print_output=False
         )
-        outputs = ""
         for output in stream:
-            outputs += output
-            yield outputs
     except Exception as e:
         print(e)
         raise gr.Error(f"Error: {e}")
-        #yield ""
     finally:
         torch.cuda.empty_cache()
         gc.collect()

 import os
 import urllib
 from typing import Any
+from gradio import MessageDict
 from huggingface_hub import hf_hub_download, HfApi
 from llama_cpp import Llama
 from llama_cpp_agent import LlamaCppAgent, MessagesFormatterType
 # https://llama-cpp-python.readthedocs.io/en/latest/api-reference/
 @torch.inference_mode()
+@spaces.GPU(duration=30)
 def dolphin_respond(
     message: str,
+    history: list[MessageDict],
     model: str = default_llm_model_filename,
     system_message: str = get_dolphin_sysprompt(),
     max_tokens: int = 1024,
         messages = BasicChatHistory()
         for msn in history:
+            if msn["role"] == "user":
+                user = {'role': Roles.user, 'content': msn["content"]}
+                messages.add_message(user)
+            elif msn["role"] == "assistant":
+                assistant = {'role': Roles.assistant, 'content': msn["content"]}
+                messages.add_message(assistant)
         stream = agent.get_chat_response(
             message,
         progress(0.5, desc="Processing...")
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": ""})
         for output in stream:
+            history[-1]['content'] += output
+            yield history
     except Exception as e:
         print(e)
         raise gr.Error(f"Error: {e}")
     finally:
         torch.cuda.empty_cache()
         gc.collect()
 def dolphin_parse(
+    history: list[MessageDict],
     state: dict,
 ):
     try:
         dolphin_sysprompt_mode = get_state(state, "dolphin_sysprompt_mode")
         if dolphin_sysprompt_mode == "Chat with LLM" or not history or len(history) < 1:
             return "", gr.update(), gr.update()
+        msg = history[-1]["content"]
         raw_prompt = get_raw_prompt(msg)
         prompts = []
         if dolphin_sysprompt_mode == "Japanese to Danbooru Dictionary" and is_japanese(raw_prompt):
 @torch.inference_mode()
+@spaces.GPU(duration=30)
 def dolphin_respond_auto(
     message: str,
+    history: list[MessageDict],
     model: str = default_llm_model_filename,
     system_message: str = get_dolphin_sysprompt(),
     max_tokens: int = 1024,
         messages = BasicChatHistory()
         for msn in history:
+            if msn["role"] == "user":
+                user = {'role': Roles.user, 'content': msn["content"]}
+                messages.add_message(user)
+            elif msn["role"] == "assistant":
+                assistant = {'role': Roles.assistant, 'content': msn["content"]}
+                messages.add_message(assistant)
         progress(0, desc="Translating...")
         stream = agent.get_chat_response(
         progress(0.5, desc="Processing...")
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": ""})
         for output in stream:
+            history[-1]['content'] += output
+            yield history, gr.update(), gr.update()
     except Exception as e:
         print(e)
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": message})
+        yield history, gr.update(), gr.update()
     finally:
         torch.cuda.empty_cache()
         gc.collect()
 def dolphin_parse_simple(
     message: str,
+    history: list[MessageDict],
     state: dict,
 ):
     try:
         #if not is_japanese(message): return message
         dolphin_sysprompt_mode = get_state(state, "dolphin_sysprompt_mode")
         if dolphin_sysprompt_mode == "Chat with LLM" or not history or len(history) < 1: return message
+        msg = history[-1]["content"]
         raw_prompt = get_raw_prompt(msg)
         prompts = []
         if dolphin_sysprompt_mode == "Japanese to Danbooru Dictionary" and is_japanese(raw_prompt):
 @torch.inference_mode()
+@spaces.GPU(duration=30)
 def respond_playground(
     message: str,
+    history: list[MessageDict],
     model: str = default_llm_model_filename,
     system_message: str = get_dolphin_sysprompt(),
     max_tokens: int = 1024,
         # Add user and assistant messages to the history
         for msn in history:
+            if msn["role"] == "user":
+                user = {'role': Roles.user, 'content': msn["content"]}
+                messages.add_message(user)
+            elif msn["role"] == "assistant":
+                assistant = {'role': Roles.assistant, 'content': msn["content"]}
+                messages.add_message(assistant)
         # Stream the response
         stream = agent.get_chat_response(
             print_output=False
         )
+        history.append({"role": "user", "content": message})
+        history.append({"role": "assistant", "content": ""})
         for output in stream:
+            history[-1]['content'] += output
+            yield history
     except Exception as e:
         print(e)
         raise gr.Error(f"Error: {e}")
     finally:
         torch.cuda.empty_cache()
         gc.collect()

llmenv.py CHANGED Viewed

@@ -14,6 +14,7 @@ llm_models = {
     "mn-12b-lyra-v2a1-q5_k_m.gguf": ["HalleyStarbun/MN-12B-Lyra-v2a1-Q5_K_M-GGUF", MessagesFormatterType.CHATML],
     "L3-8B-Tamamo-v1.i1-Q5_K_M.gguf": ["mradermacher/L3-8B-Tamamo-v1-i1-GGUF", MessagesFormatterType.LLAMA_3],
     "MN-Chinofun-12B-2.i1-Q4_K_M.gguf": ["mradermacher/MN-Chinofun-12B-2-i1-GGUF", MessagesFormatterType.MISTRAL],
     "Dolphin-5.1-7b.Q5_K_M.gguf": ["mradermacher/Dolphin-5.1-7b-GGUF", MessagesFormatterType.MISTRAL],
     "Captain-Eris-Diogenes_Twighlight-V0.420-12B.i1-Q4_K_M.gguf": ["mradermacher/Captain-Eris-Diogenes_Twighlight-V0.420-12B-i1-GGUF", MessagesFormatterType.MISTRAL],
     "Captain-Eris-Diogenes_Twilight-V0.420-12B.i1-Q4_K_M.gguf": ["mradermacher/Captain-Eris-Diogenes_Twilight-V0.420-12B-i1-GGUF", MessagesFormatterType.MISTRAL],
@@ -129,9 +130,41 @@ llm_models = {
     "Aurora-SCE-12B.Q4_K_M.gguf": ["mradermacher/Aurora-SCE-12B-GGUF", MessagesFormatterType.MISTRAL],
     "Rune-14b.Q4_K_M.gguf": ["mradermacher/Rune-14b-GGUF", MessagesFormatterType.OPEN_CHAT],
     "L3.1-Athena-e-8B.Q5_K_M.gguf": ["mradermacher/L3.1-Athena-e-8B-GGUF", MessagesFormatterType.LLAMA_3],
     "PR2-14B-Instruct.Q4_K_M.gguf": ["mradermacher/PR2-14B-Instruct-GGUF", MessagesFormatterType.OPEN_CHAT],
     "Nemo-12b-Humanize-KTO-Experimental-Latest.Q4_K_M.gguf": ["mradermacher/Nemo-12b-Humanize-KTO-Experimental-Latest-GGUF", MessagesFormatterType.CHATML],
     "Baptist-Christian-Bible-Expert-v1.1-12B.Q4_K_M.gguf": ["mradermacher/Baptist-Christian-Bible-Expert-v1.1-12B-GGUF", MessagesFormatterType.MISTRAL],
     "openbuddy-qwen2.5llamaify-14b-v23.1-200k.i1-Q4_K_M.gguf": ["mradermacher/openbuddy-qwen2.5llamaify-14b-v23.1-200k-i1-GGUF", MessagesFormatterType.OPEN_CHAT],
     "Trinas_Nectar-8B-model_stock.i1-Q4_K_M.gguf": ["mradermacher/Trinas_Nectar-8B-model_stock-i1-GGUF", MessagesFormatterType.MISTRAL],
     "ChatWaifu_Magnum_V0.2.Q4_K_M.gguf": ["mradermacher/ChatWaifu_Magnum_V0.2-GGUF", MessagesFormatterType.MISTRAL],
@@ -145,6 +178,715 @@ llm_models = {
     #"": ["", MessagesFormatterType.OPEN_CHAT],
     #"": ["", MessagesFormatterType.CHATML],
     #"": ["", MessagesFormatterType.PHI_3],
     "Hush-Qwen2.5-7B-MST-v1.1.Q5_K_M.gguf": ["mradermacher/Hush-Qwen2.5-7B-MST-v1.1-GGUF", MessagesFormatterType.OPEN_CHAT],
     "MFANNv0.22.1.Q5_K_M.gguf": ["mradermacher/MFANNv0.22.1-GGUF", MessagesFormatterType.LLAMA_3],
     "gemma2-9b-cpt-sea-lionv3-instruct.Q4_K_M.gguf": ["mradermacher/gemma2-9b-cpt-sea-lionv3-instruct-GGUF", MessagesFormatterType.ALPACA],

     "mn-12b-lyra-v2a1-q5_k_m.gguf": ["HalleyStarbun/MN-12B-Lyra-v2a1-Q5_K_M-GGUF", MessagesFormatterType.CHATML],
     "L3-8B-Tamamo-v1.i1-Q5_K_M.gguf": ["mradermacher/L3-8B-Tamamo-v1-i1-GGUF", MessagesFormatterType.LLAMA_3],
     "MN-Chinofun-12B-2.i1-Q4_K_M.gguf": ["mradermacher/MN-Chinofun-12B-2-i1-GGUF", MessagesFormatterType.MISTRAL],
+    "Shirayukihime-12B.Q4_K_M.gguf": ["mradermacher/Shirayukihime-12B-GGUF", MessagesFormatterType.CHATML],
     "Dolphin-5.1-7b.Q5_K_M.gguf": ["mradermacher/Dolphin-5.1-7b-GGUF", MessagesFormatterType.MISTRAL],
     "Captain-Eris-Diogenes_Twighlight-V0.420-12B.i1-Q4_K_M.gguf": ["mradermacher/Captain-Eris-Diogenes_Twighlight-V0.420-12B-i1-GGUF", MessagesFormatterType.MISTRAL],
     "Captain-Eris-Diogenes_Twilight-V0.420-12B.i1-Q4_K_M.gguf": ["mradermacher/Captain-Eris-Diogenes_Twilight-V0.420-12B-i1-GGUF", MessagesFormatterType.MISTRAL],
     "Aurora-SCE-12B.Q4_K_M.gguf": ["mradermacher/Aurora-SCE-12B-GGUF", MessagesFormatterType.MISTRAL],
     "Rune-14b.Q4_K_M.gguf": ["mradermacher/Rune-14b-GGUF", MessagesFormatterType.OPEN_CHAT],
     "L3.1-Athena-e-8B.Q5_K_M.gguf": ["mradermacher/L3.1-Athena-e-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "ElitePhi.i1-Q4_K_M.gguf": ["mradermacher/ElitePhi-i1-GGUF", MessagesFormatterType.LLAMA_3],
     "PR2-14B-Instruct.Q4_K_M.gguf": ["mradermacher/PR2-14B-Instruct-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Nemo_Pony_2-merged.Q4_K_M.gguf": ["mradermacher/Nemo_Pony_2-merged-GGUF", MessagesFormatterType.MISTRAL],
+    "MN-12B-Mimicore-Nocturne.Q4_K_M.gguf": ["mradermacher/MN-12B-Mimicore-Nocturne-GGUF", MessagesFormatterType.MISTRAL],
+    "Orca-2-13b-abliterated.Q4_K_M.gguf": ["mradermacher/Orca-2-13b-abliterated-GGUF", MessagesFormatterType.OPEN_CHAT],
     "Nemo-12b-Humanize-KTO-Experimental-Latest.Q4_K_M.gguf": ["mradermacher/Nemo-12b-Humanize-KTO-Experimental-Latest-GGUF", MessagesFormatterType.CHATML],
     "Baptist-Christian-Bible-Expert-v1.1-12B.Q4_K_M.gguf": ["mradermacher/Baptist-Christian-Bible-Expert-v1.1-12B-GGUF", MessagesFormatterType.MISTRAL],
+    "MN-Hekate-Enodia-12B.Q4_K_M.gguf": ["mradermacher/MN-Hekate-Enodia-12B-GGUF", MessagesFormatterType.MISTRAL],
+    "MN-Hekate-Ekklesia-12B.Q4_K_M.gguf": ["mradermacher/MN-Hekate-Ekklesia-12B-GGUF", MessagesFormatterType.MISTRAL],
+    "KANN-I-0.1-7b.Q5_K_M.gguf": ["mradermacher/KANN-I-0.1-7b-GGUF", MessagesFormatterType.MISTRAL],
+    "UnslopNemo-12B-v1.Q4_K_M.gguf": ["mradermacher/UnslopNemo-12B-v1-GGUF", MessagesFormatterType.MISTRAL],
+    "Irix-12B-Model_Stock.Q4_K_M.gguf": ["mradermacher/Irix-12B-Model_Stock-GGUF", MessagesFormatterType.CHATML],
+    "MagnaMellRei-v1-12B.Q4_K_M.gguf": ["mradermacher/MagnaMellRei-v1-12B-GGUF", MessagesFormatterType.CHATML],
+    "HMS-Slerp-12B.Q4_K_M.gguf": ["mradermacher/HMS-Slerp-12B-GGUF", MessagesFormatterType.CHATML],
+    "SnowElf-12B-v2.Q4_K_M.gguf": ["mradermacher/SnowElf-12B-v2-GGUF", MessagesFormatterType.CHATML],
+    "Queen-2.5-14B-aka.Q4_K_M.gguf": ["mradermacher/Queen-2.5-14B-aka-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "KnowledgeCore-12B.Q4_K_M.gguf": ["mradermacher/KnowledgeCore-12B-GGUF", MessagesFormatterType.CHATML],
+    "Mistral-Nemo-2407-Role-Playing-Final-4data_ga16_lr6e7.Q4_K_M.gguf": ["mradermacher/Mistral-Nemo-2407-Role-Playing-Final-4data_ga16_lr6e7-GGUF", MessagesFormatterType.CHATML],
+    "PatriSlush-DarkRPReign-12B.Q4_K_M.gguf": ["mradermacher/PatriSlush-DarkRPReign-12B-GGUF", MessagesFormatterType.MISTRAL],
+    "BianCang-Qwen2.5-14B-Instruct.Q4_K_M.gguf": ["mradermacher/BianCang-Qwen2.5-14B-Instruct-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Simulation_LLM_wiki_14B_V2.Q4_K_M.gguf": ["mradermacher/Simulation_LLM_wiki_14B_V2-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Neona-12B.i1-Q4_K_M.gguf": ["mradermacher/Neona-12B-i1-GGUF", MessagesFormatterType.MISTRAL],
+    "NeoSage-12B.Q4_K_M.gguf": ["mradermacher/NeoSage-12B-GGUF", MessagesFormatterType.MISTRAL],
+    "Patricide-12B-Forgottenslop-Mell.i1-Q4_K_M.gguf": ["mradermacher/Patricide-12B-Forgottenslop-Mell-i1-GGUF", MessagesFormatterType.MISTRAL],
+    "Pinecone-Rune-12b.Q4_K_M.gguf": ["mradermacher/Pinecone-Rune-12b-GGUF", MessagesFormatterType.MISTRAL],
+    "mn-12b-rp-without-dumb.Q4_K_M.gguf": ["mradermacher/mn-12b-rp-without-dumb-GGUF", MessagesFormatterType.MISTRAL],
+    "Denker-mistral-nemo-12B.Q4_K_M.gguf": ["mradermacher/Denker-mistral-nemo-12B-GGUF", MessagesFormatterType.MISTRAL],
+    "Goldcide-12B-Forgottenslop-Mell.Q4_K_M.gguf": ["mradermacher/Goldcide-12B-Forgottenslop-Mell-GGUF", MessagesFormatterType.MISTRAL],
+    "claude-3.7-sonnet-reasoning-gemma3-12B.Q4_K_M.gguf": ["mradermacher/claude-3.7-sonnet-reasoning-gemma3-12B-GGUF", MessagesFormatterType.ALPACA],
+    "allura-org_MN-Lyrebird-12B-Q4_K_M.gguf": ["bartowski/allura-org_MN-Lyrebird-12B-GGUF", MessagesFormatterType.MISTRAL],
+    "ape-fiction-2-mistral-nemo.Q4_K_M.gguf": ["mradermacher/ape-fiction-2-mistral-nemo-GGUF", MessagesFormatterType.MISTRAL],
+    "Irixxed_Homunculus-12B-Q3T-v.0.3-Reasoner.Q4_K_M.gguf": ["mradermacher/Irixxed_Homunculus-12B-Q3T-v.0.3-Reasoner-GGUF", MessagesFormatterType.MISTRAL],
+    "Gemma-2-Llama-Swallow-9b-pt-v0.1.Q4_K_M.gguf": ["mradermacher/Gemma-2-Llama-Swallow-9b-pt-v0.1-GGUF", MessagesFormatterType.ALPACA],
+    "Qwen2.5-7B-base-french-bespoke-stratos-full-sft.i1-Q5_K_S.gguf": ["mradermacher/Qwen2.5-7B-base-french-bespoke-stratos-full-sft-i1-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Protestant-Christian-Bible-Expert-v2.0-12B.Q4_K_M.gguf": ["mradermacher/Protestant-Christian-Bible-Expert-v2.0-12B-GGUF", MessagesFormatterType.MISTRAL],
     "openbuddy-qwen2.5llamaify-14b-v23.1-200k.i1-Q4_K_M.gguf": ["mradermacher/openbuddy-qwen2.5llamaify-14b-v23.1-200k-i1-GGUF", MessagesFormatterType.OPEN_CHAT],
     "Trinas_Nectar-8B-model_stock.i1-Q4_K_M.gguf": ["mradermacher/Trinas_Nectar-8B-model_stock-i1-GGUF", MessagesFormatterType.MISTRAL],
     "ChatWaifu_Magnum_V0.2.Q4_K_M.gguf": ["mradermacher/ChatWaifu_Magnum_V0.2-GGUF", MessagesFormatterType.MISTRAL],
     #"": ["", MessagesFormatterType.OPEN_CHAT],
     #"": ["", MessagesFormatterType.CHATML],
     #"": ["", MessagesFormatterType.PHI_3],
+    "SauerHuatuoSkyworkDeepWatt-o1-Llama-3.1-8B.Q5_K_M.gguf": ["mradermacher/SauerHuatuoSkyworkDeepWatt-o1-Llama-3.1-8B-GGUF", MessagesFormatterType.LLAMA_3],
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+    "EmojiLlama-3.1-8B.Q5_K_M.gguf": ["mradermacher/EmojiLlama-3.1-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "Kosmos-EVAA-gamma-v15-8B.Q5_K_M.gguf": ["mradermacher/Kosmos-EVAA-gamma-v15-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwen2.5-7B-Instruct-preference.Q5_K_M.gguf": ["mradermacher/Qwen2.5-7B-Instruct-preference-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "ZYH-LLM-Qwen2.5-14B-V4.Q4_K_M.gguf": ["mradermacher/ZYH-LLM-Qwen2.5-14B-V4-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Agente-GPT-Qwen2.5-3B-Instruct-Asistant-16bit-v2.Q5_K_M.gguf": ["mradermacher/Agente-GPT-Qwen2.5-3B-Instruct-Asistant-16bit-v2-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "TopicalChat_mistral_nemo.Q4_K_M.gguf": ["mradermacher/TopicalChat_mistral_nemo-GGUF", MessagesFormatterType.MISTRAL],
+    "Llama-3.2-3B-Fluxed-uncensored.Q5_K_M.gguf": ["mradermacher/Llama-3.2-3B-Fluxed-uncensored-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwen2.5-Coder-3B-few-shot-model.Q5_K_M.gguf": ["mradermacher/Qwen2.5-Coder-3B-few-shot-model-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Gigantes-v2-gemma2-9b-it.Q4_K_M.gguf": ["mradermacher/Gigantes-v2-gemma2-9b-it-GGUF", MessagesFormatterType.ALPACA],
+    "Unichat-llama3.1-Chinese-8B.Q5_K_M.gguf": ["mradermacher/Unichat-llama3.1-Chinese-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "HollandV2R1.Q5_K_M.gguf": ["mradermacher/HollandV2R1-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwen-2.5-3b-Text_to_SQL.Q5_K_M.gguf": ["mradermacher/Qwen-2.5-3b-Text_to_SQL-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "TableGPT2-7B.Q5_K_M.gguf": ["mradermacher/TableGPT2-7B-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Kosmos-EVAA-gamma-v14-8B.Q5_K_M.gguf": ["mradermacher/Kosmos-EVAA-gamma-v14-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "KPT-7b-v0.3.Q5_K_M.gguf": ["mradermacher/KPT-7b-v0.3-GGUF", MessagesFormatterType.MISTRAL],
+    "qwen2.5-coder-7b-instruct-fma.Q5_K_M.gguf": ["mradermacher/qwen2.5-coder-7b-instruct-fma-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "oh_v1.3_unnatural_instructions_x8.Q5_K_M.gguf": ["mradermacher/oh_v1.3_unnatural_instructions_x8-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwen2.5-Taiwan-7B-Instruct.Q5_K_M.gguf": ["mradermacher/Qwen2.5-Taiwan-7B-Instruct-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "NQLSG-Qwen2.5-14B-MegaFusion-v9.2.Q4_K_M.gguf": ["mradermacher/NQLSG-Qwen2.5-14B-MegaFusion-v9.2-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Ext2Gen-8B-R2.Q5_K_M.gguf": ["mradermacher/Ext2Gen-8B-R2-GGUF", MessagesFormatterType.LLAMA_3],
+    "Meta-Llama-3-8B-Instruct-abliterated.i1-Q5_K_M.gguf": ["mradermacher/Meta-Llama-3-8B-Instruct-abliterated-i1-GGUF", MessagesFormatterType.LLAMA_3],
+    "Dirty-Shirley-Writer-v3-9B.i1-Q4_K_M.gguf": ["mradermacher/Dirty-Shirley-Writer-v3-9B-i1-GGUF", MessagesFormatterType.ALPACA],
+    "EtherealAurora-12B-v2.Q4_K_M.gguf": ["mradermacher/EtherealAurora-12B-v2-GGUF", MessagesFormatterType.MISTRAL],
+    "Galactic-Qwen-14B-Exp2.Q4_K_M.gguf": ["mradermacher/Galactic-Qwen-14B-Exp2-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Qwen2.5-14B-Verged.Q4_K_M.gguf": ["mradermacher/Qwen2.5-14B-Verged-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Galactic-Qwen-14B-Exp1.Q4_K_M.gguf": ["mradermacher/Galactic-Qwen-14B-Exp1-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Volans-Opus-14B-Exp.Q4_K_M.gguf": ["mradermacher/Volans-Opus-14B-Exp-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "MN-Anathema-12B.Q4_K_M.gguf": ["mradermacher/MN-Anathema-12B-GGUF", MessagesFormatterType.CHATML],
+    "Gaea-Opus-14B-Exp.Q4_K_M.gguf": ["mradermacher/Gaea-Opus-14B-Exp-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "OnlyQ.Q5_K_M.gguf": ["mradermacher/OnlyQ-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "asteroid-14b-v0.1.Q4_K_M.gguf": ["mradermacher/asteroid-14b-v0.1-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Forgotten-Safeword-8B-V3.0.Q5_K_M.gguf": ["mradermacher/Forgotten-Safeword-8B-V3.0-GGUF", MessagesFormatterType.MISTRAL],
+    "Qwen2.5-7B-PubMeQA-Distill.Q5_K_M.gguf": ["mradermacher/Qwen2.5-7B-PubMeQA-Distill-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Llama-3.2-3b-RP-Toxic-Fuse.Q5_K_M.gguf": ["mradermacher/Llama-3.2-3b-RP-Toxic-Fuse-GGUF", MessagesFormatterType.LLAMA_3],
+    "v1-deepseek-instruct.Q5_K_M.gguf": ["mradermacher/v1-deepseek-instruct-GGUF", MessagesFormatterType.LLAMA_3],
+    "L3.1-Athena-l2-8B.Q5_K_M.gguf": ["mradermacher/L3.1-Athena-l2-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "L3.1-Athena-l4-8B.Q5_K_M.gguf": ["mradermacher/L3.1-Athena-l4-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "L3.1-Athena-l3-8B.Q5_K_M.gguf": ["mradermacher/L3.1-Athena-l3-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3.1-8B-AthenaSky-MegaMix.i1-Q5_K_M.gguf": ["mradermacher/Llama-3.1-8B-AthenaSky-MegaMix-i1-GGUF", MessagesFormatterType.LLAMA_3],
+    "Writing-Model-Qwen-7B.Q5_K_M.gguf": ["mradermacher/Writing-Model-Qwen-7B-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "open-r1_OlympicCoder-7B-Q5_K_M.gguf": ["bartowski/open-r1_OlympicCoder-7B-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Qwen-2.5-7B-deepscale-RL.Q5_K_M.gguf": ["mradermacher/Qwen-2.5-7B-deepscale-RL-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "L3.1-Athena-l-8B.i1-Q5_K_M.gguf": ["mradermacher/L3.1-Athena-l-8B-i1-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3.2-3B-Instruct-lyrics.Q5_K_M.gguf": ["mradermacher/Llama-3.2-3B-Instruct-lyrics-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3-Base-8B-DICE-Iter2.Q5_K_M.gguf": ["mradermacher/Llama-3-Base-8B-DICE-Iter2-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3-Base-8B-DICE-Iter1.Q5_K_M.gguf": ["mradermacher/Llama-3-Base-8B-DICE-Iter1-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3-8B-Instruct-Coding-Expert.Q5_K_M.gguf": ["mradermacher/Llama-3-8B-Instruct-Coding-Expert-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-O-3.1-8B-levent.Q5_K_M.gguf": ["mradermacher/Llama-O-3.1-8B-levent-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwen2.5-7B-task6.Q5_K_M.gguf": ["mradermacher/Qwen2.5-7B-task6-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "finance-Llama3-8B.Q5_K_M.gguf": ["mradermacher/finance-Llama3-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "OpenPipe_Deductive-Reasoning-Qwen-14B-Q4_K_M.gguf": ["bartowski/OpenPipe_Deductive-Reasoning-Qwen-14B-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Dirty-Shirley-Writer-v2-9B-Uncensored.i1-Q4_K_M.gguf": ["mradermacher/Dirty-Shirley-Writer-v2-9B-Uncensored-i1-GGUF", MessagesFormatterType.ALPACA],
+    "ichor_1.1-8B-Model_Stock.Q5_K_M.gguf": ["mradermacher/ichor_1.1-8B-Model_Stock-GGUF", MessagesFormatterType.LLAMA_3],
+    "gemma-2-2b-fa-v2.Q5_K_M.gguf": ["mradermacher/gemma-2-2b-fa-v2-GGUF", MessagesFormatterType.ALPACA],
+    "H_the_eighth-8B-LINEAR.Q5_K_M.gguf": ["mradermacher/H_the_eighth-8B-LINEAR-GGUF", MessagesFormatterType.LLAMA_3],
+    "granite-3.2-8b-instruct.Q5_K_M.gguf": ["mradermacher/granite-3.2-8b-instruct-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "tempestissimo-14b-0309.Q4_K_M.gguf": ["mradermacher/tempestissimo-14b-0309-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Deepseek-R1-Distill-NSFW-RP-vRedux-Proper.Q5_K_M.gguf": ["mradermacher/Deepseek-R1-Distill-NSFW-RP-vRedux-Proper-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "inexpertus_1.1-8B-LINEAR.Q5_K_M.gguf": ["mradermacher/inexpertus_1.1-8B-LINEAR-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3.1-8B-RainbowLight-EtherealMix.Q5_K_M.gguf": ["mradermacher/Llama-3.1-8B-RainbowLight-EtherealMix-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3.1-8B-SuperNova-EtherealHermes.Q5_K_M.gguf": ["mradermacher/Llama-3.1-8B-SuperNova-EtherealHermes-GGUF", MessagesFormatterType.LLAMA_3],
+    "Dirty-Shirley-Quill-v1-gemma-2-Ifable-9B-Uncensored-slerp.Q4_K_M.gguf": ["mradermacher/Dirty-Shirley-Quill-v1-gemma-2-Ifable-9B-Uncensored-slerp-GGUF", MessagesFormatterType.ALPACA],
+    "Llama3.1-SuperHawk-8B.Q5_K_M.gguf": ["mradermacher/Llama3.1-SuperHawk-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwen-2.5-7B-Reasoning.Q5_K_M.gguf": ["mradermacher/Qwen-2.5-7B-Reasoning-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "nsfw-sce-test-2-redux.Q5_K_M.gguf": ["mradermacher/nsfw-sce-test-2-redux-GGUF", MessagesFormatterType.LLAMA_3],
+    "DCFT-camel_physics_seed_science-etash.Q5_K_M.gguf": ["mradermacher/DCFT-camel_physics_seed_science-etash-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Qwen2.5-Coder-7B-Instruct-Ties.Q5_K_M.gguf": ["mradermacher/Qwen2.5-Coder-7B-Instruct-Ties-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Meta-Llama-3-8B-Instruct-abliterated.Q5_K_M.gguf": ["mradermacher/Meta-Llama-3-8B-Instruct-abliterated-GGUF", MessagesFormatterType.LLAMA_3],
+    "MFANN-llama3.1-abliterated-v2.Q5_K_M.gguf": ["mradermacher/MFANN-llama3.1-abliterated-v2-GGUF", MessagesFormatterType.LLAMA_3],
+    "lamarckvergence-14b-tensopolis-v1.Q4_K_M.gguf": ["mradermacher/lamarckvergence-14b-tensopolis-v1-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "NQLSG-Qwen2.5-14B-MegaFusion-v9.1.i1-Q4_K_M.gguf": ["mradermacher/NQLSG-Qwen2.5-14B-MegaFusion-v9.1-i1-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "s1-Qwen2.5-7B-Instruct.Q5_K_M.gguf": ["mradermacher/s1-Qwen2.5-7B-Instruct-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "s1-Qwen2.5-7B.Q5_K_M.gguf": ["mradermacher/s1-Qwen2.5-7B-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Llama3.1-IgneousIguana-8B.Q5_K_M.gguf": ["mradermacher/Llama3.1-IgneousIguana-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3-Instruct-8B-SPPO-Iter3-SimPO-merge.Q5_K_M.gguf": ["mradermacher/Llama-3-Instruct-8B-SPPO-Iter3-SimPO-merge-GGUF", MessagesFormatterType.LLAMA_3],
+    "recoilme-gemma-2-Ataraxy-9B-v0.1.i1-Q4_K_M.gguf": ["mradermacher/recoilme-gemma-2-Ataraxy-9B-v0.1-i1-GGUF", MessagesFormatterType.ALPACA],
+    "Gemma-Moon-2-9B-it.Q4_K_M.gguf": ["mradermacher/Gemma-Moon-2-9B-it-GGUF", MessagesFormatterType.ALPACA],
+    "CardProjector-7B-v2.Q5_K_M.gguf": ["mradermacher/CardProjector-7B-v2-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "PerpetualNight-12B.Q4_K_M.gguf": ["mradermacher/PerpetualNight-12B-GGUF", MessagesFormatterType.CHATML],
+    "Llama3.2-3B-Instruct-KAI.Q5_K_M.gguf": ["mradermacher/Llama3.2-3B-Instruct-KAI-GGUF", MessagesFormatterType.LLAMA_3],
+    "Llama-3.1-8B-SuperTulu-LexiNova.Q5_K_M.gguf": ["mradermacher/Llama-3.1-8B-SuperTulu-LexiNova-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwen2-1.5B-Ita_v5.Q5_K_M.gguf": ["mradermacher/Qwen2-1.5B-Ita_v5-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Llama-VARCO-8B-Instruct-LLaMAfied.i1-Q5_K_M.gguf": ["mradermacher/Llama-VARCO-8B-Instruct-LLaMAfied-i1-GGUF", MessagesFormatterType.LLAMA_3],
+    "llama3-1_8b_mlfoundations-dev-stackexchange_scicomp.Q5_K_M.gguf": ["mradermacher/llama3-1_8b_mlfoundations-dev-stackexchange_scicomp-GGUF", MessagesFormatterType.LLAMA_3],
+    "Gemma-Ko-Merge.i1-Q4_K_M.gguf": ["mradermacher/Gemma-Ko-Merge-i1-GGUF", MessagesFormatterType.ALPACA],
+    "gemma-2-9b-it-russian-strict-function-calling-DPO.Q4_K_M.gguf": ["mradermacher/gemma-2-9b-it-russian-strict-function-calling-DPO-GGUF", MessagesFormatterType.ALPACA],
+    "Llama-3.1-Supernova-Lite-Instruct-merge-abliterated-8B.Q5_K_M.gguf": ["mradermacher/Llama-3.1-Supernova-Lite-Instruct-merge-abliterated-8B-GGUF", MessagesFormatterType.LLAMA_3],
+    "Qwenslerp2-14B-F32.Q4_K_M.gguf": ["mradermacher/Qwenslerp2-14B-F32-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Llama-3-Instruct-8B-SimPO-SPPO-Iter3-merge.Q5_K_M.gguf": ["mradermacher/Llama-3-Instruct-8B-SimPO-SPPO-Iter3-merge-GGUF", MessagesFormatterType.LLAMA_3],
+    "gemma-2-baku-2b-it.i1-Q5_K_M.gguf": ["mradermacher/gemma-2-baku-2b-it-i1-GGUF", MessagesFormatterType.ALPACA],
+    "Nemo-Picaro-12B.i1-Q4_K_M.gguf": ["mradermacher/Nemo-Picaro-12B-i1-GGUF", MessagesFormatterType.CHATML],
+    "OpenCrystal-L3-15B-v2.1.Q4_K_M.gguf": ["mradermacher/OpenCrystal-L3-15B-v2.1-GGUF", MessagesFormatterType.LLAMA_3],
+    "LLMEvoLLaMA-3.1-8B-v0.1.Q5_K_M.gguf": ["mradermacher/LLMEvoLLaMA-3.1-8B-v0.1-GGUF", MessagesFormatterType.LLAMA_3],
+    "Peach-2.0-9B-8k-Roleplay.Q4_K_M.gguf": ["mradermacher/Peach-2.0-9B-8k-Roleplay-GGUF", MessagesFormatterType.CHATML],
+    "llama-3.1-8b-sarcasm.Q5_K_M.gguf": ["mradermacher/llama-3.1-8b-sarcasm-GGUF", MessagesFormatterType.LLAMA_3],
+    "walrus-gemma-2-9b-it-v01.Q4_K_M.gguf": ["mradermacher/walrus-gemma-2-9b-it-v01-GGUF", MessagesFormatterType.ALPACA],
+    "L3.1-Diffbot-Small-2412.Q5_K_M.gguf": ["mradermacher/L3.1-Diffbot-Small-2412-GGUF", MessagesFormatterType.LLAMA_3],
+    "s1.1-14B.Q4_K_M.gguf": ["mradermacher/s1.1-14B-GGUF", MessagesFormatterType.OPEN_CHAT],
+    "Lix-14B-v0.1-Uncensored-DeLMAT.Q4_K_M.gguf": ["mradermacher/Lix-14B-v0.1-Uncensored-DeLMAT-GGUF", MessagesFormatterType.OPEN_CHAT],
     "Hush-Qwen2.5-7B-MST-v1.1.Q5_K_M.gguf": ["mradermacher/Hush-Qwen2.5-7B-MST-v1.1-GGUF", MessagesFormatterType.OPEN_CHAT],
     "MFANNv0.22.1.Q5_K_M.gguf": ["mradermacher/MFANNv0.22.1-GGUF", MessagesFormatterType.LLAMA_3],
     "gemma2-9b-cpt-sea-lionv3-instruct.Q4_K_M.gguf": ["mradermacher/gemma2-9b-cpt-sea-lionv3-instruct-GGUF", MessagesFormatterType.ALPACA],

lora_dict.json CHANGED Viewed

@@ -8882,6 +8882,13 @@
     "https://civitai.com/models/491760",
     "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/36267afb-7093-4c71-ae47-516c7219fabd/width=450/14403049.jpeg"
   ],
   "triple_oral_-_triple_barrel_fellatio_-_triple_fellatio-000014": [
     "tripplebj / read description",
     "Pony",
@@ -9470,6 +9477,13 @@
     "https://civitai.com/models/850497",
     "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/0a48013a-809a-41a5-823d-e9183eae0dd0/width=450/34362448.jpeg"
   ],
   "\u7523\u5375\u65ad\u9762\u56f3": [
     "girl, egg laying, eggs in uterus",
     "Pony",

     "https://civitai.com/models/491760",
     "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/36267afb-7093-4c71-ae47-516c7219fabd/width=450/14403049.jpeg"
   ],
+  "tribbie-hsrIL-v1": [
+    "tribbie, wings, detached collar, puffy long sleeves, black gloves, black and white boots",
+    "Illustrious",
+    "[IL & PONY & SD1.5] Honkai Star Rail - Tribbie | \u7f07\u5b9d 3+1",
+    "https://civitai.com/models/1340805",
+    "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/f21f1b54-0b5a-4e92-ae08-6bf81eb2f0c2/width=1688/62634838.jpeg"
+  ],
   "triple_oral_-_triple_barrel_fellatio_-_triple_fellatio-000014": [
     "tripplebj / read description",
     "Pony",
     "https://civitai.com/models/850497",
     "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/0a48013a-809a-41a5-823d-e9183eae0dd0/width=450/34362448.jpeg"
   ],
+  "\u7231\u8bfa-Illustrious": [
+    "aino (genshin impact), pink hair, grey eyes, bangs pinned back, hair ornament, green dress, white coat, oversized clothes, mechanical tail, sleeves past fingers, mismatched legwear, asymmetrical legwear, open coat, sleeves past wrists",
+    "Illustrious",
+    "\u3010Genshin Impact\u3011\u7231\u8bfa\u4e28Aino\u4e28\u30a2\u30a4\u30ce",
+    "https://civitai.com/models/1792295",
+    "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/ced12386-d16d-42b2-ad02-2ef70e736f5e/width=1536/94782692.jpeg"
+  ],
   "\u7523\u5375\u65ad\u9762\u56f3": [
     "girl, egg laying, eggs in uterus",
     "Pony",

modutils.py CHANGED Viewed

@@ -1730,7 +1730,7 @@ EXAMPLES_GUI = [
         "votepurchase/ponyDiffusionV6XL",
     ],
     [
-        "1girl, oomuro sakurako, yuru yuri, official art, school uniform, anime artwork, anime style, vibrant, studio anime, highly detailed, masterpiece, best quality, very aesthetic, absurdres",
         "photo, deformed, black and white, realism, disfigured, low contrast, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]",
         1,
         40,
@@ -1743,17 +1743,17 @@ EXAMPLES_GUI = [
         "Raelina/Rae-Diffusion-XL-V2",
     ],
     [
-        "1girl, akaza akari, yuru yuri, official art, anime artwork, anime style, vibrant, studio anime, highly detailed, masterpiece, best quality, very aesthetic, absurdres",
-        "photo, deformed, black and white, realism, disfigured, low contrast, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]",
         1,
-        35,
-        7.0,
         True,
         -1,
         "Euler",
         1024,
         1024,
-        "Raelina/Raemu-XL-V5",
     ],
     [
         "yoshida yuuko, machikado mazoku, 1girl, solo, demon horns,horns, school uniform, long hair, open mouth, skirt, demon girl, ahoge, shiny, shiny hair, anime artwork",

         "votepurchase/ponyDiffusionV6XL",
     ],
     [
+        "1girl, oomuro sakurako, yuru yuri, official art, school uniform, anime artwork, anime style, studio anime, highly detailed, masterpiece, best quality, very aesthetic, absurdres",
         "photo, deformed, black and white, realism, disfigured, low contrast, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]",
         1,
         40,
         "Raelina/Rae-Diffusion-XL-V2",
     ],
     [
+        "1girl, akaza akari, yuru yuri, official art, anime screencap, anime coloring, masterpiece, best quality, absurdres",
+        "bad quality, worst quality, poorly drawn, sketch, multiple views, bad anatomy, bad hands, missing fingers, extra fingers, extra digits, fewer digits, signature, watermark, username",
         1,
+        28,
+        5.5,
         True,
         -1,
         "Euler",
         1024,
         1024,
+        "Raelina/Raehoshi-illust-XL-6",
     ],
     [
         "yoshida yuuko, machikado mazoku, 1girl, solo, demon horns,horns, school uniform, long hair, open mouth, skirt, demon girl, ahoge, shiny, shiny hair, anime artwork",

packages.txt CHANGED Viewed

	@@ -1 +1 @@
1	- git-lfs aria2 -y ffmpeg


1	+ git-lfs aria2 ffmpeg

requirements.txt CHANGED Viewed

@@ -1,10 +1,8 @@
 stablepy==0.6.2
-#diffusers==0.31.0
-#transformers==4.47.1
 accelerate
-invisible_watermark
-datasets
-torch==2.4.0
 numpy<2
 gdown
 opencv-python
@@ -12,17 +10,19 @@ huggingface_hub
 hf_xet
 hf_transfer
 scikit-build-core
-https://github.com/abetlen/llama-cpp-python/releases/download/v0.3.4-cu124/llama_cpp_python-0.3.4-cp310-cp310-linux_x86_64.whl
-git+https://github.com/Maximilian-Winter/llama-cpp-agent
 pybind11>=2.12
 rapidfuzz
 torchvision
 optimum[onnxruntime]
-dartrs
 translatepy
 timm
 wrapt-timeout-decorator
 sentencepiece
 unidecode
-ultralytics>=8.3.47
 pydantic==2.10.6

 stablepy==0.6.2
+diffusers
+transformers<=4.48.3
 accelerate
+torch==2.5.1
 numpy<2
 gdown
 opencv-python
 hf_xet
 hf_transfer
 scikit-build-core
+https://github.com/abetlen/llama-cpp-python/releases/download/v0.3.16-cu124/llama_cpp_python-0.3.16-cp310-cp310-linux_x86_64.whl
+git+https://github.com/John6666cat/llama-cpp-agent
 pybind11>=2.12
 rapidfuzz
 torchvision
 optimum[onnxruntime]
+#dartrs
+git+https://github.com/John6666cat/dartrs
 translatepy
 timm
 wrapt-timeout-decorator
 sentencepiece
 unidecode
+matplotlib-inline
+https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.4.11/flash_attn-2.8.3+cu124torch2.5-cp310-cp310-linux_x86_64.whl
 pydantic==2.10.6

tagger/fl2sd3longcap.py CHANGED Viewed

@@ -1,16 +1,22 @@
-from transformers import AutoProcessor, AutoModelForCausalLM
 import spaces
 import re
 from PIL import Image
 import torch
-import subprocess
-subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
 device = "cuda" if torch.cuda.is_available() else "cpu"
-fl_model = AutoModelForCausalLM.from_pretrained('gokaygokay/Florence-2-SD3-Captioner', trust_remote_code=True).to("cpu").eval()
-fl_processor = AutoProcessor.from_pretrained('gokaygokay/Florence-2-SD3-Captioner', trust_remote_code=True)
 def fl_modify_caption(caption: str) -> str:
     """
@@ -41,7 +47,7 @@ def fl_modify_caption(caption: str) -> str:
     return modified_caption if modified_caption != caption else caption
-@spaces.GPU(duration=30)
 def fl_run_example(image):
     task_prompt = "<DESCRIPTION>"
     prompt = task_prompt + "Describe this image in great detail."

 import spaces
+from transformers import AutoProcessor, AutoModelForCausalLM
 import re
 from PIL import Image
 import torch
+from transformers.utils import is_flash_attn_2_available
+if not is_flash_attn_2_available():
+    import subprocess
+    subprocess.run('pip install flash-attn --no-build-isolation', env={'FLASH_ATTENTION_SKIP_CUDA_BUILD': "TRUE"}, shell=True)
 device = "cuda" if torch.cuda.is_available() else "cpu"
+try:
+    fl_model = AutoModelForCausalLM.from_pretrained('gokaygokay/Florence-2-SD3-Captioner', trust_remote_code=True).to("cpu").eval()
+    fl_processor = AutoProcessor.from_pretrained('gokaygokay/Florence-2-SD3-Captioner', trust_remote_code=True)
+except Exception as e:
+    print(e)
+    fl_model = fl_processor = None
 def fl_modify_caption(caption: str) -> str:
     """
     return modified_caption if modified_caption != caption else caption
+@spaces.GPU(duration=10)
 def fl_run_example(image):
     task_prompt = "<DESCRIPTION>"
     prompt = task_prompt + "Describe this image in great detail."

tagger/tagger.py CHANGED Viewed

@@ -504,7 +504,7 @@ def gen_prompt(rating: list[str], character: list[str], general: list[str]):
     return ", ".join(all_tags)
-@spaces.GPU(duration=30)
 def predict_tags(image: Image.Image, general_threshold: float = 0.3, character_threshold: float = 0.8):
     inputs = wd_processor.preprocess(image, return_tensors="pt")

     return ", ".join(all_tags)
+@spaces.GPU(duration=10)
 def predict_tags(image: Image.Image, general_threshold: float = 0.3, character_threshold: float = 0.8):
     inputs = wd_processor.preprocess(image, return_tensors="pt")

tagger/v2.py CHANGED Viewed

@@ -1,4 +1,4 @@
-import time
 import torch
 from typing import Callable
 from pathlib import Path
@@ -16,16 +16,15 @@ from dartrs.v2 import (
 from dartrs.dartrs import DartTokenizer
 from dartrs.utils import get_generation_config
 import gradio as gr
 from gradio.components import Component
 try:
     from output import UpsamplingOutput
 except:
     from .output import UpsamplingOutput
 V2_ALL_MODELS = {
     "dart-v2-moe-sft": {
@@ -43,8 +42,8 @@ V2_ALL_MODELS = {
 def prepare_models(model_config: dict):
     model_name = model_config["repo"]
-    tokenizer = DartTokenizer.from_pretrained(model_name)
-    model = model_config["class"].from_pretrained(model_name)
     return {
         "tokenizer": tokenizer,

+import time, os
 import torch
 from typing import Callable
 from pathlib import Path
 from dartrs.dartrs import DartTokenizer
 from dartrs.utils import get_generation_config
 import gradio as gr
 from gradio.components import Component
 try:
     from output import UpsamplingOutput
 except:
     from .output import UpsamplingOutput
+HF_TOKEN = os.getenv("HF_TOKEN", None)
 V2_ALL_MODELS = {
     "dart-v2-moe-sft": {
 def prepare_models(model_config: dict):
     model_name = model_config["repo"]
+    tokenizer = DartTokenizer.from_pretrained(model_name, auth_token=HF_TOKEN)
+    model = model_config["class"].from_pretrained(model_name, auth_token=HF_TOKEN)
     return {
         "tokenizer": tokenizer,

utils.py CHANGED Viewed

@@ -9,6 +9,7 @@ from constants import (
     DIRECTORY_LORAS,
     DIRECTORY_MODELS,
     DIFFUSECRAFT_CHECKPOINT_NAME,
     CACHE_HF,
     STORAGE_ROOT,
 )
@@ -28,6 +29,7 @@ from urllib3.util import Retry
 import shutil
 import subprocess
 USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'
@@ -66,7 +68,8 @@ class ModelInformation:
         )
         self.filename_url = self.filename_url if self.filename_url else ""
         self.description = json_data.get("description", "")
-        if self.description is None: self.description = ""
         self.model_name = json_data.get("model", {}).get("name", "")
         self.model_type = json_data.get("model", {}).get("type", "")
         self.nsfw = json_data.get("model", {}).get("nsfw", False)
@@ -76,118 +79,175 @@ class ModelInformation:
         self.original_json = copy.deepcopy(json_data)
-def retrieve_model_info(url):
-    json_data = request_json_data(url)
-    if not json_data:
-        return None
-    model_descriptor = ModelInformation(json_data)
-    return model_descriptor
-def download_things(directory, url, hf_token="", civitai_api_key="", romanize=False):
-    url = url.strip()
-    downloaded_file_path = None
-    if "drive.google.com" in url:
-        original_dir = os.getcwd()
-        os.chdir(directory)
-        os.system(f"gdown --fuzzy {url}")
-        os.chdir(original_dir)
-    elif "huggingface.co" in url:
-        url = url.replace("?download=true", "")
-        # url = urllib.parse.quote(url, safe=':/')  # fix encoding
-        if "/blob/" in url:
-            url = url.replace("/blob/", "/resolve/")
-        user_header = f'"Authorization: Bearer {hf_token}"'
-        filename = unidecode(url.split('/')[-1]) if romanize else url.split('/')[-1]
-        if hf_token:
-            os.system(f"aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 {url} -d {directory}  -o {filename}")
-        else:
-            os.system(f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 {url} -d {directory}  -o {filename}")
-        downloaded_file_path = os.path.join(directory, filename)
-    elif "civitai.com" in url:
-        if not civitai_api_key:
-            print("\033[91mYou need an API key to download Civitai models.\033[0m")
-        model_profile = retrieve_model_info(url)
-        if (
-            model_profile is not None
-            and model_profile.download_url
-            and model_profile.filename_url
-        ):
-            url = model_profile.download_url
-            filename = unidecode(model_profile.filename_url) if romanize else model_profile.filename_url
-        else:
-            if "?" in url:
-                url = url.split("?")[0]
-            filename = ""
-        url_dl = url + f"?token={civitai_api_key}"
-        print(f"Filename: {filename}")
-        param_filename = ""
-        if filename:
-            param_filename = f"-o '{filename}'"
-        aria2_command = (
-            f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
-            f'-k 1M -s 16 -d "{directory}" {param_filename} "{url_dl}"'
-        )
         os.system(aria2_command)
-        if param_filename and os.path.exists(os.path.join(directory, filename)):
-            downloaded_file_path = os.path.join(directory, filename)
-        # # PLAN B
-        # # Follow the redirect to get the actual download URL
-        # curl_command = (
-        #     f'curl -L -sI --connect-timeout 5 --max-time 5 '
-        #     f'-H "Content-Type: application/json" '
-        #     f'-H "Authorization: Bearer {civitai_api_key}" "{url}"'
-        # )
-        # headers = os.popen(curl_command).read()
-        # # Look for the redirected "Location" URL
-        # location_match = re.search(r'location: (.+)', headers, re.IGNORECASE)
-        # if location_match:
-        #     redirect_url = location_match.group(1).strip()
-        #     # Extract the filename from the redirect URL's "Content-Disposition"
-        #     filename_match = re.search(r'filename%3D%22(.+?)%22', redirect_url)
-        #     if filename_match:
-        #         encoded_filename = filename_match.group(1)
-        #         # Decode the URL-encoded filename
-        #         decoded_filename = urllib.parse.unquote(encoded_filename)
-        #         filename = unidecode(decoded_filename) if romanize else decoded_filename
-        #         print(f"Filename: {filename}")
-        #         aria2_command = (
-        #             f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
-        #             f'-k 1M -s 16 -d "{directory}" -o "{filename}" "{redirect_url}"'
-        #         )
-        #         return_code = os.system(aria2_command)
-        #         # if return_code != 0:
-        #         #     raise RuntimeError(f"Failed to download file: {filename}. Error code: {return_code}")
-        #         downloaded_file_path = os.path.join(directory, filename)
-        #         if not os.path.exists(downloaded_file_path):
-        #             downloaded_file_path = None
-        # if not downloaded_file_path:
-        #     # Old method
-        #     if "?" in url:
-        #         url = url.split("?")[0]
-        #     url = url + f"?token={civitai_api_key}"
-        #     os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
     else:
         os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
@@ -216,14 +276,15 @@ def extract_parameters(input_string):
         if "Steps:" in input_string:
             input_string = input_string.replace("Steps:", "Negative prompt: Steps:")
         else:
-            print("Invalid metadata")
             parameters["prompt"] = input_string
             return parameters
     parm = input_string.split("Negative prompt:")
     parameters["prompt"] = parm[0].strip()
     if "Steps:" not in parm[1]:
-        print("Steps not detected")
         parameters["neg_prompt"] = parm[1].strip()
         return parameters
     parm = parm[1].split("Steps:")
@@ -306,7 +367,8 @@ def get_model_type(repo_id: str):
             model = api.model_info(repo_id=repo_id, timeout=5.0)
             tags = model.tags
             for tag in tags:
-                if tag in MODEL_TYPE_CLASS.keys(): return MODEL_TYPE_CLASS.get(tag, default)
     except Exception:
         return default
@@ -433,9 +495,9 @@ def get_folder_size_gb(folder_path):
     return total_size_gb
-def get_used_storage_gb():
     try:
-        used_gb = get_folder_size_gb(STORAGE_ROOT)
         print(f"Used Storage: {used_gb:.2f} GB")
     except Exception as e:
         used_gb = 999
@@ -455,6 +517,21 @@ def delete_model(removal_candidate):
             shutil.rmtree(diffusers_model)
 def progress_step_bar(step, total):
     # Calculate the percentage for the progress bar width
     percentage = min(100, ((step / total) * 100))

     DIRECTORY_LORAS,
     DIRECTORY_MODELS,
     DIFFUSECRAFT_CHECKPOINT_NAME,
+    CACHE_HF_ROOT,
     CACHE_HF,
     STORAGE_ROOT,
 )
 import shutil
 import subprocess
+IS_ZERO_GPU = bool(os.getenv("SPACES_ZERO_GPU"))
 USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'
         )
         self.filename_url = self.filename_url if self.filename_url else ""
         self.description = json_data.get("description", "")
+        if self.description is None:
+            self.description = ""
         self.model_name = json_data.get("model", {}).get("name", "")
         self.model_type = json_data.get("model", {}).get("type", "")
         self.nsfw = json_data.get("model", {}).get("nsfw", False)
         self.original_json = copy.deepcopy(json_data)
+def get_civit_params(url):
+    try:
+        json_data = request_json_data(url)
+        mdc = ModelInformation(json_data)
+        if mdc.download_url and mdc.filename_url:
+            return mdc.download_url, mdc.filename_url, mdc.model_url
+        else:
+            ValueError("Invalid Civitai model URL")
+    except Exception as e:
+        print(f"Error retrieving Civitai metadata: {e} — fallback to direct download")
+        return url, None, None
+def civ_redirect_down(url, dir_, civitai_api_key, romanize, alternative_name):
+    filename_base = filename = None
+    if alternative_name:
+        output_path = os.path.join(dir_, alternative_name)
+        if os.path.exists(output_path):
+            return output_path, alternative_name
+    # Follow the redirect to get the actual download URL
+    curl_command = (
+        f'curl -L -sI --connect-timeout 5 --max-time 5 '
+        f'-H "Content-Type: application/json" '
+        f'-H "Authorization: Bearer {civitai_api_key}" "{url}"'
+    )
+    headers = os.popen(curl_command).read()
+    # Look for the redirected "Location" URL
+    location_match = re.search(r'location: (.+)', headers, re.IGNORECASE)
+    if location_match:
+        redirect_url = location_match.group(1).strip()
+        # Extract the filename from the redirect URL's "Content-Disposition"
+        filename_match = re.search(r'filename%3D%22(.+?)%22', redirect_url)
+        if filename_match:
+            encoded_filename = filename_match.group(1)
+            # Decode the URL-encoded filename
+            decoded_filename = urllib.parse.unquote(encoded_filename)
+            filename = unidecode(decoded_filename) if romanize else decoded_filename
+            # print(f"Filename redirect: {filename}")
+    filename_base = alternative_name if alternative_name else filename
+    if not filename_base:
+        return None, None
+    elif os.path.exists(os.path.join(dir_, filename_base)):
+        return os.path.join(dir_, filename_base), filename_base
+    aria2_command = (
+        f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
+        f'-k 1M -s 16 -d "{dir_}" -o "{filename_base}" "{redirect_url}"'
+    )
+    r_code = os.system(aria2_command)  # noqa
+    # if r_code != 0:
+    #     raise RuntimeError(f"Failed to download file: {filename_base}. Error code: {r_code}")
+    output_path = os.path.join(dir_, filename_base)
+    if not os.path.exists(output_path):
+        return None, filename_base
+    return output_path, filename_base
+def civ_api_down(url, dir_, civitai_api_key, civ_filename):
+    """
+    This method is susceptible to being blocked because it generates a lot of temp redirect links with aria2c.
+    If an API key limit is reached, generating a new API key and using it can fix the issue.
+    """
+    output_path = None
+    url_dl = url + f"?token={civitai_api_key}"
+    if not civ_filename:
+        aria2_command = f'aria2c -c -x 1 -s 1 -d "{dir_}" "{url_dl}"'
         os.system(aria2_command)
+    else:
+        output_path = os.path.join(dir_, civ_filename)
+        if not os.path.exists(output_path):
+            aria2_command = (
+                f'aria2c --console-log-level=error --summary-interval=10 -c -x 16 '
+                f'-k 1M -s 16 -d "{dir_}" -o "{civ_filename}" "{url_dl}"'
+            )
+            os.system(aria2_command)
+    return output_path
+def drive_down(url, dir_):
+    import gdown
+    output_path = None
+    drive_id, _ = gdown.parse_url.parse_url(url, warning=False)
+    dir_files = os.listdir(dir_)
+    for dfile in dir_files:
+        if drive_id in dfile:
+            output_path = os.path.join(dir_, dfile)
+            break
+    if not output_path:
+        original_path = gdown.download(url, f"{dir_}/", fuzzy=True)
+        dir_name, base_name = os.path.split(original_path)
+        name, ext = base_name.rsplit(".", 1)
+        new_name = f"{name}_{drive_id}.{ext}"
+        output_path = os.path.join(dir_name, new_name)
+        os.rename(original_path, output_path)
+    return output_path
+def hf_down(url, dir_, hf_token, romanize):
+    url = url.replace("?download=true", "")
+    # url = urllib.parse.quote(url, safe=':/')  # fix encoding
+    filename = unidecode(url.split('/')[-1]) if romanize else url.split('/')[-1]
+    output_path = os.path.join(dir_, filename)
+    if os.path.exists(output_path):
+        return output_path
+    if "/blob/" in url:
+        url = url.replace("/blob/", "/resolve/")
+    if hf_token:
+        user_header = f'"Authorization: Bearer {hf_token}"'
+        os.system(f"aria2c --console-log-level=error --summary-interval=10 --header={user_header} -c -x 16 -k 1M -s 16 {url} -d {dir_}  -o {filename}")
+    else:
+        os.system(f"aria2c --optimize-concurrent-downloads --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 {url} -d {dir_}  -o {filename}")
+    return output_path
+def download_things(directory, url, hf_token="", civitai_api_key="", romanize=False):
+    url = url.strip()
+    downloaded_file_path = None
+    if "drive.google.com" in url:
+        downloaded_file_path = drive_down(url, directory)
+    elif "huggingface.co" in url:
+        downloaded_file_path = hf_down(url, directory, hf_token, romanize)
+    elif "civitai.com" in url:
+        if not civitai_api_key:
+            msg = "You need an API key to download Civitai models."
+            print(f"\033[91m{msg}\033[0m")
+            gr.Warning(msg)
+            return None
+        url, civ_filename, civ_page = get_civit_params(url)
+        if civ_page and not IS_ZERO_GPU:
+            print(f"\033[92mCivitai model: {civ_filename} [page: {civ_page}]\033[0m")
+        downloaded_file_path, civ_filename = civ_redirect_down(url, directory, civitai_api_key, romanize, civ_filename)
+        if not downloaded_file_path:
+            msg = (
+                "Download failed.\n"
+                "If this is due to an API limit, generating a new API key may resolve the issue.\n"
+                "Attempting to download using the old method..."
+            )
+            print(msg)
+            gr.Warning(msg)
+            downloaded_file_path = civ_api_down(url, directory, civitai_api_key, civ_filename)
     else:
         os.system(f"aria2c --console-log-level=error --summary-interval=10 -c -x 16 -k 1M -s 16 -d {directory} {url}")
         if "Steps:" in input_string:
             input_string = input_string.replace("Steps:", "Negative prompt: Steps:")
         else:
+            msg = "Generation data is invalid."
+            gr.Warning(msg)
+            print(msg)
             parameters["prompt"] = input_string
             return parameters
     parm = input_string.split("Negative prompt:")
     parameters["prompt"] = parm[0].strip()
     if "Steps:" not in parm[1]:
         parameters["neg_prompt"] = parm[1].strip()
         return parameters
     parm = parm[1].split("Steps:")
             model = api.model_info(repo_id=repo_id, timeout=5.0)
             tags = model.tags
             for tag in tags:
+                if tag in MODEL_TYPE_CLASS.keys():
+                    return MODEL_TYPE_CLASS.get(tag, default)
     except Exception:
         return default
     return total_size_gb
+def get_used_storage_gb(path_storage=STORAGE_ROOT):
     try:
+        used_gb = get_folder_size_gb(path_storage)
         print(f"Used Storage: {used_gb:.2f} GB")
     except Exception as e:
         used_gb = 999
             shutil.rmtree(diffusers_model)
+def clear_hf_cache():
+    """
+    Clears the entire Hugging Face cache at ~/.cache/huggingface.
+    Hugging Face will re-download models as needed later.
+    """
+    try:
+        if os.path.exists(CACHE_HF_ROOT):
+            shutil.rmtree(CACHE_HF_ROOT, ignore_errors=True)
+            print(f"Hugging Face cache cleared: {CACHE_HF_ROOT}")
+        else:
+            print(f"No Hugging Face cache found at: {CACHE_HF_ROOT}")
+    except Exception as e:
+        print(f"Error clearing Hugging Face cache: {e}")
 def progress_step_bar(step, total):
     # Calculate the percentage for the progress bar width
     percentage = min(100, ((step / total) * 100))