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Running
on
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Running
on
Zero
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README.md
CHANGED
@@ -4,7 +4,7 @@ emoji: 🧩🖼️📦
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colorFrom: red
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colorTo: pink
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sdk: gradio
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sdk_version: 4.
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app_file: app.py
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pinned: true
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header: mini
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colorFrom: red
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colorTo: pink
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sdk: gradio
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sdk_version: 4.38.1
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app_file: app.py
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pinned: true
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header: mini
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app.py
CHANGED
@@ -160,14 +160,6 @@ def process_string(input_string):
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return None
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directory_models = 'models'
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os.makedirs(directory_models, exist_ok=True)
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directory_loras = 'loras'
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os.makedirs(directory_loras, exist_ok=True)
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directory_vaes = 'vaes'
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os.makedirs(directory_vaes, exist_ok=True)
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## BEGIN MOD
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from modutils import (
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download_private_repo,
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list_sub,
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get_tupled_embed_list,
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update_lora_dict,
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HF_LORA_ESSENTIAL_PRIVATE_REPO,
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)
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# - **Download
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download_model = ""
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# - **Download VAEs**
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download_vae_list = [
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'https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/resolve/main/sdxl.vae.safetensors?download=true',
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'https://huggingface.co/nubby/blessed-sdxl-vae-fp16-fix/resolve/main/sdxl_vae-fp16fix-c-1.1-b-0.5.safetensors?download=true',
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'https://huggingface.co/nubby/blessed-sdxl-vae-fp16-fix/resolve/main/sdxl_vae-fp16fix-blessed.safetensors?download=true',
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]
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download_vae = ", ".join(download_vae_list)
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# - **Download LoRAs**
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download_lora_list = []
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download_lora = ", ".join(download_lora_list)
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download_private_repo(HF_LORA_ESSENTIAL_PRIVATE_REPO, directory_loras, True)
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download_private_repo(
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load_diffusers_format_model = [
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'stabilityai/stable-diffusion-xl-base-1.0',
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'cagliostrolab/animagine-xl-3.1',
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'misri/epicrealismXL_v7FinalDestination',
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'misri/juggernautXL_juggernautX',
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'misri/zavychromaxl_v80',
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'SG161222/RealVisXL_V4.0',
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'misri/newrealityxlAllInOne_Newreality40',
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'eienmojiki/Anything-XL',
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'eienmojiki/Starry-XL-v5.2',
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'gsdf/CounterfeitXL',
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'kitty7779/ponyDiffusionV6XL',
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'John6666/ebara-mfcg-pony-mix-v12-sdxl',
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'John6666/t-ponynai3-v51-sdxl',
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'yodayo-ai/kivotos-xl-2.0',
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'yodayo-ai/holodayo-xl-2.1',
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'digiplay/majicMIX_sombre_v2',
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'digiplay/majicMIX_realistic_v6',
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'digiplay/majicMIX_realistic_v7',
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'digiplay/DreamShaper_8',
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'digiplay/BeautifulArt_v1',
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'digiplay/DarkSushi2.5D_v1',
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'digiplay/darkphoenix3D_v1.1',
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'digiplay/BeenYouLiteL11_diffusers',
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'rubbrband/revAnimated_v2Rebirth',
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'youknownothing/cyberrealistic_v50',
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'votepurchase/counterfeitV30_v30',
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'Meina/MeinaMix_V11',
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'Meina/MeinaUnreal_V5',
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'Meina/MeinaPastel_V7',
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'rubbrband/realcartoon3d_v16',
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'rubbrband/realcartoonRealistic_v14',
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'KBlueLeaf/Kohaku-XL-Epsilon-rev2',
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'KBlueLeaf/Kohaku-XL-Epsilon-rev3',
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'Raelina/Rae-Diffusion-XL-V2',
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'Raelina/Raemu-XL-V4',
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]
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load_diffusers_format_model = list_uniq(get_model_id_list() + load_diffusers_format_model)
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## END MOD
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CIVITAI_API_KEY = os.environ.get("CIVITAI_API_KEY")
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hf_token = os.environ.get("HF_TOKEN")
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# Download stuffs
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for url in [url.strip() for url in download_model.split(',')]:
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if not os.path.exists(f"./models/{url.split('/')[-1]}"):
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download_things(directory_loras, url, hf_token, CIVITAI_API_KEY)
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# Download Embeddings
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directory_embeds = 'embedings'
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os.makedirs(directory_embeds, exist_ok=True)
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download_embeds = [
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'https://huggingface.co/datasets/Nerfgun3/bad_prompt/blob/main/bad_prompt_version2.pt',
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'https://huggingface.co/embed/negative/resolve/main/EasyNegativeV2.safetensors',
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'https://huggingface.co/embed/negative/resolve/main/bad-hands-5.pt',
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]
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for url_embed in download_embeds:
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if not os.path.exists(f"./embedings/{url_embed.split('/')[-1]}"):
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download_things(directory_embeds, url_embed, hf_token, CIVITAI_API_KEY)
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@@ -272,19 +227,13 @@ embed_list = get_model_list(directory_embeds)
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model_list = get_model_list(directory_models)
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model_list = load_diffusers_format_model + model_list
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## BEGIN MOD
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lora_model_list =
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lora_model_list.insert(0, "None")
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lora_model_list.insert(0, "")
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vae_model_list = get_model_list(directory_vaes)
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vae_model_list.insert(0, "None")
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directory_embeds_sdxl
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directory_embeds_postitive_sdxl = 'embedings_xl/positive'
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os.makedirs(directory_embeds_postitive_sdxl, exist_ok=True)
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download_private_repo('John6666/embeddingspositivetest', directory_embeds_postitive_sdxl, False)
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embed_sdxl_list = get_model_list(directory_embeds_sdxl) + get_model_list(directory_embeds_postitive_sdxl)
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def get_embed_list(pipeline_name):
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return get_tupled_embed_list(embed_sdxl_list if pipeline_name == "StableDiffusionXLPipeline" else embed_list)
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new_path = Path(f'{path.parent.name}/{escape_lora_basename(path.stem)}{path.suffix}')
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path.resolve().rename(new_path.resolve())
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update_lora_dict(str(new_path))
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new_lora_model_list =
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new_lora_model_list.insert(0, "None")
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new_lora_model_list.insert(0, "")
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return gr.update(
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choices=get_lora_tupled_list(new_lora_model_list), value=new_lora_model_list[-1]
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## BEGIN MOD
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prompt, neg_prompt = insert_model_recom_prompt(prompt, neg_prompt, model_name)
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## END MOD
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if model_name in model_list:
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fn=search_civitai_lora,
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inputs=[search_civitai_query_lora, search_civitai_basemodel_lora],
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outputs=[search_civitai_result_lora, search_civitai_desc_lora, search_civitai_button_lora, search_civitai_query_lora],
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scroll_to_output=True,
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)
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search_civitai_result_lora.change(select_civitai_lora, [search_civitai_result_lora], [text_lora, search_civitai_desc_lora], queue=False, scroll_to_output=True)
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return None
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## BEGIN MOD
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from modutils import (
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download_private_repo,
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list_sub,
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get_tupled_embed_list,
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update_lora_dict,
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get_lora_model_list,
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)
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from env import (
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hf_token,
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CIVITAI_API_KEY,
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HF_LORA_ESSENTIAL_PRIVATE_REPO,
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HF_VAE_PRIVATE_REPO,
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HF_SDXL_EMBEDS_NEGATIVE_PRIVATE_REPO,
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HF_SDXL_EMBEDS_POSITIVE_PRIVATE_REPO,
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directory_models,
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directory_loras,
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directory_vaes,
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directory_embeds,
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directory_embeds_sdxl,
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directory_embeds_positive_sdxl,
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load_diffusers_format_model,
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download_model_list,
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download_lora_list,
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download_vae_list,
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download_embeds,
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)
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# - **Download Models**
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download_model = ", ".join(download_model_list)
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# - **Download VAEs**
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download_vae = ", ".join(download_vae_list)
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# - **Download LoRAs**
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download_lora = ", ".join(download_lora_list)
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download_private_repo(HF_LORA_ESSENTIAL_PRIVATE_REPO, directory_loras, True)
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download_private_repo(HF_VAE_PRIVATE_REPO, directory_vaes, False)
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load_diffusers_format_model = list_uniq(get_model_id_list() + load_diffusers_format_model)
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## END MOD
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# Download stuffs
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for url in [url.strip() for url in download_model.split(',')]:
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if not os.path.exists(f"./models/{url.split('/')[-1]}"):
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download_things(directory_loras, url, hf_token, CIVITAI_API_KEY)
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# Download Embeddings
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for url_embed in download_embeds:
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if not os.path.exists(f"./embedings/{url_embed.split('/')[-1]}"):
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download_things(directory_embeds, url_embed, hf_token, CIVITAI_API_KEY)
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model_list = get_model_list(directory_models)
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model_list = load_diffusers_format_model + model_list
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## BEGIN MOD
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lora_model_list = get_lora_model_list()
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vae_model_list = get_model_list(directory_vaes)
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vae_model_list.insert(0, "None")
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download_private_repo(HF_SDXL_EMBEDS_NEGATIVE_PRIVATE_REPO, directory_embeds_sdxl, False)
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download_private_repo(HF_SDXL_EMBEDS_POSITIVE_PRIVATE_REPO, directory_embeds_positive_sdxl, False)
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embed_sdxl_list = get_model_list(directory_embeds_sdxl) + get_model_list(directory_embeds_positive_sdxl)
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def get_embed_list(pipeline_name):
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return get_tupled_embed_list(embed_sdxl_list if pipeline_name == "StableDiffusionXLPipeline" else embed_list)
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new_path = Path(f'{path.parent.name}/{escape_lora_basename(path.stem)}{path.suffix}')
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path.resolve().rename(new_path.resolve())
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update_lora_dict(str(new_path))
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new_lora_model_list = get_lora_model_list()
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return gr.update(
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choices=get_lora_tupled_list(new_lora_model_list), value=new_lora_model_list[-1]
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## BEGIN MOD
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prompt, neg_prompt = insert_model_recom_prompt(prompt, neg_prompt, model_name)
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global lora_model_list
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lora_model_list = get_lora_model_list()
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## END MOD
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if model_name in model_list:
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fn=search_civitai_lora,
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inputs=[search_civitai_query_lora, search_civitai_basemodel_lora],
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outputs=[search_civitai_result_lora, search_civitai_desc_lora, search_civitai_button_lora, search_civitai_query_lora],
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queue=True,
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scroll_to_output=True,
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)
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search_civitai_result_lora.change(select_civitai_lora, [search_civitai_result_lora], [text_lora, search_civitai_desc_lora], queue=False, scroll_to_output=True)
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env.py
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import os
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CIVITAI_API_KEY = os.environ.get("CIVITAI_API_KEY")
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hf_token = os.environ.get("HF_TOKEN")
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hf_read_token = os.environ.get('HF_READ_TOKEN') # only use for private repo
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# - **List Models**
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load_diffusers_format_model = [
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'stabilityai/stable-diffusion-xl-base-1.0',
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'cagliostrolab/animagine-xl-3.1',
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'misri/epicrealismXL_v7FinalDestination',
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'misri/juggernautXL_juggernautX',
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'misri/zavychromaxl_v80',
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'SG161222/RealVisXL_V4.0',
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'misri/newrealityxlAllInOne_Newreality40',
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'eienmojiki/Anything-XL',
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'eienmojiki/Starry-XL-v5.2',
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'gsdf/CounterfeitXL',
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'kitty7779/ponyDiffusionV6XL',
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'John6666/ebara-mfcg-pony-mix-v12-sdxl',
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'John6666/t-ponynai3-v51-sdxl',
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'yodayo-ai/kivotos-xl-2.0',
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'yodayo-ai/holodayo-xl-2.1',
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'digiplay/majicMIX_sombre_v2',
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'digiplay/majicMIX_realistic_v6',
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'digiplay/majicMIX_realistic_v7',
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'digiplay/DreamShaper_8',
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'digiplay/BeautifulArt_v1',
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'digiplay/DarkSushi2.5D_v1',
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'digiplay/darkphoenix3D_v1.1',
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'digiplay/BeenYouLiteL11_diffusers',
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'rubbrband/revAnimated_v2Rebirth',
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'youknownothing/cyberrealistic_v50',
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'votepurchase/counterfeitV30_v30',
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'Meina/MeinaMix_V11',
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'Meina/MeinaUnreal_V5',
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'Meina/MeinaPastel_V7',
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'rubbrband/realcartoon3d_v16',
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'rubbrband/realcartoonRealistic_v14',
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'KBlueLeaf/Kohaku-XL-Epsilon-rev2',
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'KBlueLeaf/Kohaku-XL-Epsilon-rev3',
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'Raelina/Rae-Diffusion-XL-V2',
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'Raelina/Raemu-XL-V4',
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]
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# List all Models for specified user
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HF_MODEL_USER_LIKES = ["votepurchase"] # sorted by number of likes
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48 |
+
HF_MODEL_USER_EX = ["John6666"] # sorted by a special rule
|
49 |
+
|
50 |
+
|
51 |
+
# - **Download Models**
|
52 |
+
download_model_list = [
|
53 |
+
]
|
54 |
+
|
55 |
+
# - **Download VAEs**
|
56 |
+
download_vae_list = [
|
57 |
+
'https://huggingface.co/madebyollin/sdxl-vae-fp16-fix/resolve/main/sdxl.vae.safetensors?download=true',
|
58 |
+
'https://huggingface.co/nubby/blessed-sdxl-vae-fp16-fix/resolve/main/sdxl_vae-fp16fix-c-1.1-b-0.5.safetensors?download=true',
|
59 |
+
'https://huggingface.co/nubby/blessed-sdxl-vae-fp16-fix/resolve/main/sdxl_vae-fp16fix-blessed.safetensors?download=true',
|
60 |
+
]
|
61 |
+
|
62 |
+
# - **Download LoRAs**
|
63 |
+
download_lora_list = [
|
64 |
+
]
|
65 |
+
|
66 |
+
# Download Embeddings
|
67 |
+
download_embeds = [
|
68 |
+
'https://huggingface.co/datasets/Nerfgun3/bad_prompt/blob/main/bad_prompt_version2.pt',
|
69 |
+
'https://huggingface.co/embed/negative/resolve/main/EasyNegativeV2.safetensors',
|
70 |
+
'https://huggingface.co/embed/negative/resolve/main/bad-hands-5.pt',
|
71 |
+
]
|
72 |
+
|
73 |
+
directory_models = 'models'
|
74 |
+
os.makedirs(directory_models, exist_ok=True)
|
75 |
+
directory_loras = 'loras'
|
76 |
+
os.makedirs(directory_loras, exist_ok=True)
|
77 |
+
directory_vaes = 'vaes'
|
78 |
+
os.makedirs(directory_vaes, exist_ok=True)
|
79 |
+
directory_embeds = 'embedings'
|
80 |
+
os.makedirs(directory_embeds, exist_ok=True)
|
81 |
+
|
82 |
+
directory_embeds_sdxl = 'embedings_xl'
|
83 |
+
os.makedirs(directory_embeds_sdxl, exist_ok=True)
|
84 |
+
directory_embeds_positive_sdxl = 'embedings_xl/positive'
|
85 |
+
os.makedirs(directory_embeds_positive_sdxl, exist_ok=True)
|
86 |
+
|
87 |
+
HF_LORA_PRIVATE_REPOS1 = ['John6666/loratest1', 'John6666/loratest3', 'John6666/loratest4', 'John6666/loratest6']
|
88 |
+
HF_LORA_PRIVATE_REPOS2 = ['John6666/loratest10', 'John6666/loratest'] # to be sorted as 1 repo
|
89 |
+
HF_LORA_PRIVATE_REPOS = HF_LORA_PRIVATE_REPOS1 + HF_LORA_PRIVATE_REPOS2
|
90 |
+
HF_LORA_ESSENTIAL_PRIVATE_REPO = 'John6666/loratest1' # to be downloaded on run app
|
91 |
+
HF_VAE_PRIVATE_REPO = 'John6666/vaetest'
|
92 |
+
HF_SDXL_EMBEDS_NEGATIVE_PRIVATE_REPO = 'John6666/embeddingstest'
|
93 |
+
HF_SDXL_EMBEDS_POSITIVE_PRIVATE_REPO = 'John6666/embeddingspositivetest'
|
modutils.py
CHANGED
@@ -1,18 +1,16 @@
|
|
1 |
-
import os
|
2 |
import json
|
3 |
import gradio as gr
|
4 |
-
from PIL import Image
|
5 |
from huggingface_hub import HfApi
|
6 |
-
from requests import HTTPError, Timeout
|
7 |
from pathlib import Path
|
8 |
|
9 |
-
|
10 |
-
|
11 |
-
|
12 |
-
|
13 |
-
|
14 |
-
|
15 |
-
hf_read_token
|
|
|
16 |
|
17 |
def get_user_agent():
|
18 |
return 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'
|
@@ -103,7 +101,10 @@ def get_private_model_list(repo_id, dir_path):
|
|
103 |
return model_list
|
104 |
|
105 |
|
|
|
106 |
def get_private_lora_model_lists():
|
|
|
|
|
107 |
models1 = []
|
108 |
models2 = []
|
109 |
for repo in HF_LORA_PRIVATE_REPOS1:
|
@@ -111,6 +112,7 @@ def get_private_lora_model_lists():
|
|
111 |
for repo in HF_LORA_PRIVATE_REPOS2:
|
112 |
models2.extend(get_private_model_list(repo, directory_loras))
|
113 |
models = list_uniq(models1 + sorted(models2))
|
|
|
114 |
return models
|
115 |
|
116 |
|
@@ -139,15 +141,19 @@ def get_model_id_list():
|
|
139 |
api = HfApi()
|
140 |
model_ids = []
|
141 |
try:
|
142 |
-
|
143 |
-
|
|
|
|
|
|
|
|
|
144 |
except Exception as e:
|
145 |
return model_ids
|
146 |
-
for model in
|
147 |
model_ids.append(model.id) if not model.private else ""
|
148 |
anime_models = []
|
149 |
real_models = []
|
150 |
-
for model in
|
151 |
if not model.private:
|
152 |
anime_models.append(model.id) if 'anime' in model.tags else real_models.append(model.id)
|
153 |
model_ids.extend(anime_models)
|
@@ -220,13 +226,15 @@ def save_gallery_images(images, progress=gr.Progress(track_tqdm=True)):
|
|
220 |
output_paths = []
|
221 |
for image in images:
|
222 |
filename = basename + str(i) + ".png"
|
223 |
-
|
224 |
-
|
|
|
|
|
|
|
225 |
output_paths.append(str(newpath))
|
226 |
output_images.append((str(newpath), str(filename)))
|
227 |
-
i += 1
|
228 |
progress(1, desc="Gallery updated.")
|
229 |
-
return gr.update(value=output_images), gr.update(value=output_paths), gr.update(visible=True)
|
230 |
|
231 |
|
232 |
optimization_list = {
|
@@ -302,10 +310,13 @@ def set_lora_prompt(prompt_gui, prompt_syntax_gui, lora1_gui, lora_scale_1_gui,
|
|
302 |
|
303 |
|
304 |
lora_trigger_dict = {"None": ["", "", "", "", ""], "": ["", "", "", "", ""]}
|
305 |
-
|
306 |
-
|
307 |
-
|
308 |
-
|
|
|
|
|
|
|
309 |
|
310 |
|
311 |
civitai_not_exists_list = []
|
@@ -332,7 +343,7 @@ def get_civitai_info(path):
|
|
332 |
url = base_url + hash_sha256
|
333 |
try:
|
334 |
r = session.get(url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
|
335 |
-
except
|
336 |
return ["", "", "", "", ""]
|
337 |
if not r.ok: return None
|
338 |
json = r.json()
|
@@ -357,6 +368,13 @@ def update_lora_dict(path):
|
|
357 |
lora_trigger_dict[key] = items
|
358 |
|
359 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
360 |
def get_lora_tupled_list(lora_model_list):
|
361 |
global lora_trigger_dict
|
362 |
if not lora_model_list: return []
|
@@ -389,7 +407,7 @@ def set_lora_trigger(lora_gui: str):
|
|
389 |
gr.update(value="", visible=False), gr.update(value="")
|
390 |
path = Path(lora_gui)
|
391 |
new_path = Path(f'{path.parent.name}/{escape_lora_basename(path.stem)}{path.suffix}')
|
392 |
-
if not new_path.stem in lora_trigger_dict.keys() and not str(path) in set(
|
393 |
return gr.update(value="", visible=False), gr.update(visible=False),\
|
394 |
gr.update(value="", visible=False), gr.update(value="")
|
395 |
if not new_path.exists():
|
@@ -416,7 +434,7 @@ def set_lora_trigger(lora_gui: str):
|
|
416 |
elif items[3]:
|
417 |
md = f'[LoRA Model URL]({items[3]})'
|
418 |
if tag and flag:
|
419 |
-
new_lora_model_list =
|
420 |
return gr.update(value=tag, label=label, visible=True), gr.update(visible=True),\
|
421 |
gr.update(value=md, visible=True), gr.update(value=str(new_path), choices=get_lora_tupled_list(new_lora_model_list))
|
422 |
elif tag:
|
@@ -456,9 +474,7 @@ def move_file_lora(filepaths):
|
|
456 |
path.resolve().rename(newpath.resolve())
|
457 |
update_lora_dict(str(newpath))
|
458 |
|
459 |
-
new_lora_model_list =
|
460 |
-
new_lora_model_list.insert(0, "None")
|
461 |
-
new_lora_model_list.insert(0, "")
|
462 |
|
463 |
return gr.update(
|
464 |
choices=get_lora_tupled_list(new_lora_model_list), value=new_lora_model_list[-1]
|
@@ -488,7 +504,7 @@ def search_lora_on_civitai(query: str, allow_model: list[str]):
|
|
488 |
session.mount("https://", HTTPAdapter(max_retries=retries))
|
489 |
try:
|
490 |
r = session.get(base_url, params=params, headers=headers, stream=True, timeout=(3.0, 30))
|
491 |
-
except
|
492 |
return None
|
493 |
if not r.ok: return None
|
494 |
json = r.json()
|
@@ -781,10 +797,11 @@ def set_quick_presets(genre:str = "None", type:str = "Auto", speed:str = "None",
|
|
781 |
|
782 |
|
783 |
textual_inversion_dict = {}
|
784 |
-
|
785 |
-
textual_inversion_dict =
|
786 |
-
|
787 |
-
|
|
|
788 |
textual_inversion_file_token_list = []
|
789 |
|
790 |
|
|
|
|
|
1 |
import json
|
2 |
import gradio as gr
|
|
|
3 |
from huggingface_hub import HfApi
|
|
|
4 |
from pathlib import Path
|
5 |
|
6 |
+
from env import (
|
7 |
+
HF_LORA_PRIVATE_REPOS1,
|
8 |
+
HF_LORA_PRIVATE_REPOS2,
|
9 |
+
HF_MODEL_USER_EX,
|
10 |
+
HF_MODEL_USER_LIKES,
|
11 |
+
directory_loras,
|
12 |
+
hf_read_token,
|
13 |
+
)
|
14 |
|
15 |
def get_user_agent():
|
16 |
return 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:127.0) Gecko/20100101 Firefox/127.0'
|
|
|
101 |
return model_list
|
102 |
|
103 |
|
104 |
+
private_lora_model_list = []
|
105 |
def get_private_lora_model_lists():
|
106 |
+
global private_lora_model_list
|
107 |
+
if len(private_lora_model_list) != 0: return private_lora_model_list
|
108 |
models1 = []
|
109 |
models2 = []
|
110 |
for repo in HF_LORA_PRIVATE_REPOS1:
|
|
|
112 |
for repo in HF_LORA_PRIVATE_REPOS2:
|
113 |
models2.extend(get_private_model_list(repo, directory_loras))
|
114 |
models = list_uniq(models1 + sorted(models2))
|
115 |
+
private_lora_model_list = models
|
116 |
return models
|
117 |
|
118 |
|
|
|
141 |
api = HfApi()
|
142 |
model_ids = []
|
143 |
try:
|
144 |
+
models_likes = []
|
145 |
+
for author in HF_MODEL_USER_LIKES:
|
146 |
+
models_likes.extend(api.list_models(author=author, cardData=True, sort="likes"))
|
147 |
+
models_ex = []
|
148 |
+
for author in HF_MODEL_USER_EX:
|
149 |
+
models_ex = api.list_models(author=author, cardData=True, sort="last_modified")
|
150 |
except Exception as e:
|
151 |
return model_ids
|
152 |
+
for model in models_likes:
|
153 |
model_ids.append(model.id) if not model.private else ""
|
154 |
anime_models = []
|
155 |
real_models = []
|
156 |
+
for model in models_ex:
|
157 |
if not model.private:
|
158 |
anime_models.append(model.id) if 'anime' in model.tags else real_models.append(model.id)
|
159 |
model_ids.extend(anime_models)
|
|
|
226 |
output_paths = []
|
227 |
for image in images:
|
228 |
filename = basename + str(i) + ".png"
|
229 |
+
i += 1
|
230 |
+
oldpath = Path(image[0])
|
231 |
+
newpath = oldpath
|
232 |
+
if oldpath.exists():
|
233 |
+
newpath = oldpath.resolve().rename(Path(filename).resolve())
|
234 |
output_paths.append(str(newpath))
|
235 |
output_images.append((str(newpath), str(filename)))
|
|
|
236 |
progress(1, desc="Gallery updated.")
|
237 |
+
return gr.update(value=output_images), gr.update(value=output_paths), gr.update(visible=True)
|
238 |
|
239 |
|
240 |
optimization_list = {
|
|
|
310 |
|
311 |
|
312 |
lora_trigger_dict = {"None": ["", "", "", "", ""], "": ["", "", "", "", ""]}
|
313 |
+
try:
|
314 |
+
with open('lora_dict.json', encoding='utf-8') as f:
|
315 |
+
temp_dict = json.load(f)
|
316 |
+
for k, v in temp_dict.items():
|
317 |
+
lora_trigger_dict[escape_lora_basename(k)] = v
|
318 |
+
except Exception:
|
319 |
+
pass
|
320 |
|
321 |
|
322 |
civitai_not_exists_list = []
|
|
|
343 |
url = base_url + hash_sha256
|
344 |
try:
|
345 |
r = session.get(url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
|
346 |
+
except Exception as e:
|
347 |
return ["", "", "", "", ""]
|
348 |
if not r.ok: return None
|
349 |
json = r.json()
|
|
|
368 |
lora_trigger_dict[key] = items
|
369 |
|
370 |
|
371 |
+
def get_lora_model_list():
|
372 |
+
loras = list_uniq(get_private_lora_model_lists() + get_local_model_list(directory_loras))
|
373 |
+
loras.insert(0, "None")
|
374 |
+
loras.insert(0, "")
|
375 |
+
return loras
|
376 |
+
|
377 |
+
|
378 |
def get_lora_tupled_list(lora_model_list):
|
379 |
global lora_trigger_dict
|
380 |
if not lora_model_list: return []
|
|
|
407 |
gr.update(value="", visible=False), gr.update(value="")
|
408 |
path = Path(lora_gui)
|
409 |
new_path = Path(f'{path.parent.name}/{escape_lora_basename(path.stem)}{path.suffix}')
|
410 |
+
if not new_path.stem in lora_trigger_dict.keys() and not str(path) in set(get_lora_model_list()):
|
411 |
return gr.update(value="", visible=False), gr.update(visible=False),\
|
412 |
gr.update(value="", visible=False), gr.update(value="")
|
413 |
if not new_path.exists():
|
|
|
434 |
elif items[3]:
|
435 |
md = f'[LoRA Model URL]({items[3]})'
|
436 |
if tag and flag:
|
437 |
+
new_lora_model_list = get_lora_model_list()
|
438 |
return gr.update(value=tag, label=label, visible=True), gr.update(visible=True),\
|
439 |
gr.update(value=md, visible=True), gr.update(value=str(new_path), choices=get_lora_tupled_list(new_lora_model_list))
|
440 |
elif tag:
|
|
|
474 |
path.resolve().rename(newpath.resolve())
|
475 |
update_lora_dict(str(newpath))
|
476 |
|
477 |
+
new_lora_model_list = get_lora_model_list()
|
|
|
|
|
478 |
|
479 |
return gr.update(
|
480 |
choices=get_lora_tupled_list(new_lora_model_list), value=new_lora_model_list[-1]
|
|
|
504 |
session.mount("https://", HTTPAdapter(max_retries=retries))
|
505 |
try:
|
506 |
r = session.get(base_url, params=params, headers=headers, stream=True, timeout=(3.0, 30))
|
507 |
+
except Exception as e:
|
508 |
return None
|
509 |
if not r.ok: return None
|
510 |
json = r.json()
|
|
|
797 |
|
798 |
|
799 |
textual_inversion_dict = {}
|
800 |
+
try:
|
801 |
+
with open('textual_inversion_dict.json', encoding='utf-8') as f:
|
802 |
+
textual_inversion_dict = json.load(f)
|
803 |
+
except Exception:
|
804 |
+
pass
|
805 |
textual_inversion_file_token_list = []
|
806 |
|
807 |
|