Upload 4 files

app.py

@@ -20,10 +20,10 @@ from mod import (clear_cache, get_repo_safetensors, is_repo_name, is_repo_exists
  description_ui, compose_lora_json, is_valid_lora, fuse_loras, save_image, preprocess_i2i_image,
  get_trigger_word, enhance_prompt, set_control_union_image,
  get_control_union_mode, set_control_union_mode, get_control_params, translate_to_en)
-from flux import (search_civitai_lora, select_civitai_lora, search_civitai_lora_json,
- download_my_lora, get_all_lora_tupled_list, apply_lora_prompt,
- update_loras)
-from modutils import get_t2i_model_info, download_hf_file
+from modutils import (search_civitai_lora, select_civitai_lora, search_civitai_lora_json,
+ download_my_lora_flux, get_all_lora_tupled_list, apply_lora_prompt_flux,
+ update_loras_flux, update_civitai_selection, get_civitai_tag, CIVITAI_SORT, CIVITAI_PERIOD,
+ get_t2i_model_info, download_hf_file)
 from tagger.tagger import predict_tags_wd, compose_prompt_to_copy
 from tagger.fl2flux import predict_tags_fl2_flux
 
@@ -674,7 +674,8 @@ css = '''
 #custom_lora_btn{margin-top: auto;margin-bottom: 11px}
 #random_btn{font-size: 300%}
 #component-11{align-self: stretch;}
-.info {text-align:center; !important}
+.info { align-items: center; text-align: center; }
+.desc [src$='#float'] { float: right; margin: 20px; }
 '''
 with gr.Blocks(theme='NoCrypt/miku@>=1.2.2', fill_width=True, css=css, delete_cache=(60, 3600)) as app:
  with gr.Tab("FLUX LoRA the Explorer"):
@@ -730,14 +731,8 @@ with gr.Blocks(theme='NoCrypt/miku@>=1.2.2', fill_width=True, css=css, delete_ca
  with gr.Row():
  with gr.Column():
  selected_info = gr.Markdown("")
- gallery = gr.Gallery(
- [(item["image"], item["title"]) for item in loras],
- label="LoRA Gallery",
- allow_preview=False,
- columns=5,
- elem_id="gallery",
- show_share_button=False
- )
+ gallery = gr.Gallery([(item["image"], item["title"]) for item in loras], label="LoRA Gallery", allow_preview=False,
+ columns=5, elem_id="gallery", show_share_button=False, interactive=False)
  with gr.Group():
  with gr.Row(elem_id="custom_lora_structure"):
  custom_lora = gr.Textbox(label="Custom LoRA", info="LoRA Hugging Face path or *.safetensors public URL", placeholder="multimodalart/vintage-ads-flux", scale=3, min_width=150)
@@ -802,15 +797,18 @@ with gr.Blocks(theme='NoCrypt/miku@>=1.2.2', fill_width=True, css=css, delete_ca
  with gr.Accordion("From URL", open=True, visible=True):
  with gr.Row():
  lora_search_civitai_basemodel = gr.CheckboxGroup(label="Search LoRA for", choices=["Flux.1 D", "Flux.1 S"], value=["Flux.1 D"])
- lora_search_civitai_sort = gr.Radio(label="Sort", choices=["Highest Rated", "Most Downloaded", "Newest"], value="Most Downloaded")
- lora_search_civitai_period = gr.Radio(label="Period", choices=["AllTime", "Year", "Month", "Week", "Day"], value="Month")
+ lora_search_civitai_sort = gr.Radio(label="Sort", choices=CIVITAI_SORT, value="Most Downloaded")
+ lora_search_civitai_period = gr.Radio(label="Period", choices=CIVITAI_PERIOD, value="Month")
  with gr.Row():
  lora_search_civitai_query = gr.Textbox(label="Query", placeholder="flux", lines=1)
- lora_search_civitai_tag = gr.Textbox(label="Tag", lines=1)
- lora_search_civitai_submit = gr.Button("Search on Civitai")
+ lora_search_civitai_tag = gr.Dropdown(label="Tag", choices=get_civitai_tag(), value=get_civitai_tag()[0], allow_custom_value=True)
+ lora_search_civitai_user = gr.Textbox(label="Username", lines=1)
+ lora_search_civitai_submit = gr.Button("Search on Civitai")
  with gr.Row():
  lora_search_civitai_json = gr.JSON(value={}, visible=False)
- lora_search_civitai_desc = gr.Markdown(value="", visible=False)
+ lora_search_civitai_desc = gr.Markdown(value="", visible=False, elem_classes="desc")
+ with gr.Accordion("Select from Gallery", open=False):
+ lora_search_civitai_gallery = gr.Gallery([], label="Results", allow_preview=False, columns=5, show_share_button=False, interactive=False)
  lora_search_civitai_result = gr.Dropdown(label="Search Results", choices=[("", "")], value="", allow_custom_value=True, visible=False)
  lora_download_url = gr.Textbox(label="LoRA URL", placeholder="https://civitai.com/api/download/models/28907", lines=1)
  with gr.Row():
@@ -901,22 +899,24 @@ with gr.Blocks(theme='NoCrypt/miku@>=1.2.2', fill_width=True, css=css, delete_ca
  prompt_enhance.click(enhance_prompt, [prompt], [prompt], queue=False, show_api=False)
 
  gr.on(
- triggers=[lora_search_civitai_submit.click, lora_search_civitai_query.submit, lora_search_civitai_tag.submit],
+ triggers=[lora_search_civitai_submit.click, lora_search_civitai_query.submit],
  fn=search_civitai_lora,
- inputs=[lora_search_civitai_query, lora_search_civitai_basemodel, lora_search_civitai_sort, lora_search_civitai_period, lora_search_civitai_tag],
- outputs=[lora_search_civitai_result, lora_search_civitai_desc, lora_search_civitai_submit, lora_search_civitai_query],
+ inputs=[lora_search_civitai_query, lora_search_civitai_basemodel, lora_search_civitai_sort, lora_search_civitai_period,
+ lora_search_civitai_tag, lora_search_civitai_user, lora_search_civitai_gallery],
+ outputs=[lora_search_civitai_result, lora_search_civitai_desc, lora_search_civitai_submit, lora_search_civitai_query, lora_search_civitai_gallery],
  scroll_to_output=True,
  queue=True,
  show_api=False,
  )
  lora_search_civitai_json.change(search_civitai_lora_json, [lora_search_civitai_query, lora_search_civitai_basemodel], [lora_search_civitai_json], queue=True, show_api=True) # fn for api
  lora_search_civitai_result.change(select_civitai_lora, [lora_search_civitai_result], [lora_download_url, lora_search_civitai_desc], scroll_to_output=True, queue=False, show_api=False)
+ lora_search_civitai_gallery.select(update_civitai_selection, None, [lora_search_civitai_result], queue=False, show_api=False)
 
  for i, l in enumerate(lora_repo):
  deselect_lora_button.click(lambda: ("", 1.0), None, [lora_repo[i], lora_wt[i]], queue=False, show_api=False)
  gr.on(
  triggers=[lora_download[i].click],
- fn=download_my_lora,
+ fn=download_my_lora_flux,
  inputs=[lora_download_url, lora_repo[i]],
  outputs=[lora_repo[i]],
  scroll_to_output=True,
@@ -925,14 +925,14 @@ with gr.Blocks(theme='NoCrypt/miku@>=1.2.2', fill_width=True, css=css, delete_ca
  )
  gr.on(
  triggers=[lora_repo[i].change, lora_wt[i].change],
- fn=update_loras,
+ fn=update_loras_flux,
  inputs=[prompt, lora_repo[i], lora_wt[i]],
  outputs=[prompt, lora_repo[i], lora_wt[i], lora_info[i], lora_md[i]],
  queue=False,
  trigger_mode="once",
  show_api=False,
  ).success(get_repo_safetensors, [lora_repo[i]], [lora_weights[i]], queue=False, show_api=False
- ).success(apply_lora_prompt, [lora_info[i]], [lora_trigger[i]], queue=False, show_api=False
+ ).success(apply_lora_prompt_flux, [lora_info[i]], [lora_trigger[i]], queue=False, show_api=False
  ).success(compose_lora_json, [lora_repo_json, lora_num[i], lora_repo[i], lora_wt[i], lora_weights[i], lora_trigger[i]], [lora_repo_json], queue=False, show_api=False)
  
  for i, m in enumerate(cn_mode):

mod.py

@@ -5,7 +5,8 @@ from PIL import Image
 from pathlib import Path
 import gc
 import subprocess
-from env import num_cns, model_trigger, HF_TOKEN
+from env import num_cns, model_trigger, HF_TOKEN, CIVITAI_API_KEY, download_lora_list, directory_loras
+from modutils import download_things
 import os
 
 
@@ -18,6 +19,12 @@ control_images = [None] * num_cns
 control_modes = [-1] * num_cns
 control_scales = [0] * num_cns
 
+# Download stuffs
+download_lora = ", ".join(download_lora_list)
+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)
+
 
 def is_repo_name(s):
  import re

modutils.py

@@ -2,11 +2,16 @@ import spaces
 import json
 import gradio as gr
 import os
+import re
 from pathlib import Path
 from PIL import Image
-from huggingface_hub import HfApi, HfFolder, hf_hub_download, snapshot_download
+import shutil
+import requests
+from requests.adapters import HTTPAdapter
+from urllib3.util import Retry
 import urllib.parse
-import re
+import pandas as pd
+from huggingface_hub import HfApi, HfFolder, hf_hub_download, snapshot_download
 
 
 from env import (HF_LORA_PRIVATE_REPOS1, HF_LORA_PRIVATE_REPOS2,
@@ -38,7 +43,6 @@ def list_sub(a, b):
 
 
 def is_repo_name(s):
- import re
  return re.fullmatch(r'^[^/]+?/[^/]+?$', s)
 
 
@@ -226,7 +230,6 @@ def save_gallery_images(images, progress=gr.Progress(track_tqdm=True)):
 
 
 def download_private_repo(repo_id, dir_path, is_replace):
- from huggingface_hub import snapshot_download
  if not hf_read_token: return
  try:
  snapshot_download(repo_id=repo_id, local_dir=dir_path, allow_patterns=['*.ckpt', '*.pt', '*.pth', '*.safetensors', '*.bin'], use_auth_token=hf_read_token)
@@ -265,7 +268,6 @@ def get_private_model_list(repo_id, dir_path):
 
 
 def download_private_file(repo_id, path, is_replace):
- from huggingface_hub import hf_hub_download
  file = Path(path)
  newpath = Path(f'{file.parent.name}/{escape_lora_basename(file.stem)}{file.suffix}') if is_replace else file
  if not hf_read_token or newpath.exists(): return
@@ -389,7 +391,9 @@ except Exception as e:
 loras_dict = {"None": ["", "", "", "", ""], "": ["", "", "", "", ""]} | private_lora_dict.copy()
 civitai_not_exists_list = []
 loras_url_to_path_dict = {} # {"URL to download": "local filepath", ...}
-civitai_lora_last_results = {} # {"URL to download": {search results}, ...}
+civitai_last_results = {} # {"URL to download": {search results}, ...}
+civitai_last_choices = [("", "")]
+civitai_last_gallery = []
 all_lora_list = []
 
 
@@ -413,9 +417,6 @@ private_lora_model_list = get_private_lora_model_lists()
 
 def get_civitai_info(path):
  global civitai_not_exists_list
- import requests
- from urllib3.util import Retry
- from requests.adapters import HTTPAdapter
  if path in set(civitai_not_exists_list): return ["", "", "", "", ""]
  if not Path(path).exists(): return None
  user_agent = get_user_agent()
@@ -450,7 +451,7 @@ def get_civitai_info(path):
 
 
 def get_lora_model_list():
- loras = list_uniq(get_private_lora_model_lists() + get_local_model_list(directory_loras) + DIFFUSERS_FORMAT_LORAS)
+ loras = list_uniq(get_private_lora_model_lists() + DIFFUSERS_FORMAT_LORAS + get_local_model_list(directory_loras))
  loras.insert(0, "None")
  loras.insert(0, "")
  return loras
@@ -525,7 +526,6 @@ def download_lora(dl_urls: str):
 
 
 def copy_lora(path: str, new_path: str):
- import shutil
  if path == new_path: return new_path
  cpath = Path(path)
  npath = Path(new_path)
@@ -589,7 +589,6 @@ def get_valid_lora_path(query: str):
 
 
 def get_valid_lora_wt(prompt: str, lora_path: str, lora_wt: float):
- import re
  wt = lora_wt
  result = re.findall(f'<lora:{to_lora_key(lora_path)}:(.+?)>', prompt)
  if not result: return wt
@@ -598,7 +597,6 @@ def get_valid_lora_wt(prompt: str, lora_path: str, lora_wt: float):
 
 
 def set_prompt_loras(prompt, prompt_syntax, model_name, lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt):
- import re
  if not "Classic" in str(prompt_syntax): return lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt
  lora1 = get_valid_lora_name(lora1, model_name)
  lora2 = get_valid_lora_name(lora2, model_name)
@@ -718,7 +716,6 @@ def apply_lora_prompt(prompt: str = "", lora_info: str = ""):
 
 
 def update_loras(prompt, prompt_syntax, lora1, lora1_wt, lora2, lora2_wt, lora3, lora3_wt, lora4, lora4_wt, lora5, lora5_wt):
- import re
  on1, label1, tag1, md1 = get_lora_info(lora1)
  on2, label2, tag2, md2 = get_lora_info(lora2)
  on3, label3, tag3, md3 = get_lora_info(lora3)
@@ -765,7 +762,6 @@ def update_loras(prompt, prompt_syntax, lora1, lora1_wt, lora2, lora2_wt, lora3,
 
 
 def get_my_lora(link_url):
- from pathlib import Path
  before = get_local_model_list(directory_loras)
  for url in [url.strip() for url in link_url.split(',')]:
  if not Path(f"{directory_loras}/{url.split('/')[-1]}").exists():
@@ -802,7 +798,6 @@ def upload_file_lora(files, progress=gr.Progress(track_tqdm=True)):
 
 
 def move_file_lora(filepaths):
- import shutil
  for file in filepaths:
  path = Path(shutil.move(Path(file).resolve(), Path(f"./{directory_loras}").resolve()))
  newpath = Path(f'{path.parent.name}/{escape_lora_basename(path.stem)}{path.suffix}')
@@ -825,11 +820,13 @@ def move_file_lora(filepaths):
  )
 
 
+CIVITAI_SORT = ["Highest Rated", "Most Downloaded", "Newest"]
+CIVITAI_PERIOD = ["AllTime", "Year", "Month", "Week", "Day"]
+CIVITAI_BASEMODEL = ["Pony", "SD 1.5", "SDXL 1.0", "Flux.1 D", "Flux.1 S"]
+
+
 def get_civitai_info(path):
  global civitai_not_exists_list, loras_url_to_path_dict
- import requests
- from requests.adapters import HTTPAdapter
- from urllib3.util import Retry
  default = ["", "", "", "", ""]
  if path in set(civitai_not_exists_list): return default
  if not Path(path).exists(): return None
@@ -867,16 +864,14 @@ def get_civitai_info(path):
 
 
 def search_lora_on_civitai(query: str, allow_model: list[str] = ["Pony", "SDXL 1.0"], limit: int = 100,
- sort: str = "Highest Rated", period: str = "AllTime", tag: str = ""):
- import requests
- from requests.adapters import HTTPAdapter
- from urllib3.util import Retry
+ sort: str = "Highest Rated", period: str = "AllTime", tag: str = "", user: str = "", page: int = 1):
  user_agent = get_user_agent()
  headers = {'User-Agent': user_agent, 'content-type': 'application/json'}
  base_url = 'https://civitai.com/api/v1/models'
- params = {'types': ['LORA'], 'sort': sort, 'period': period, 'limit': limit, 'nsfw': 'true'}
+ params = {'types': ['LORA'], 'sort': sort, 'period': period, 'limit': limit, 'page': int(page), 'nsfw': 'true'}
  if query: params["query"] = query
  if tag: params["tag"] = tag
+ if user: params["username"] = user
  session = requests.Session()
  retries = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
  session.mount("https://", HTTPAdapter(max_retries=retries))
@@ -893,46 +888,129 @@ def search_lora_on_civitai(query: str, allow_model: list[str] = ["Pony", "SDXL 1
  for j in json['items']:
  for model in j['modelVersions']:
  item = {}
- if model['baseModel'] not in set(allow_model): continue
+ if len(allow_model) != 0 and model['baseModel'] not in set(allow_model): continue
  item['name'] = j['name']
- item['creator'] = j['creator']['username']
- item['tags'] = j['tags']
- item['model_name'] = model['name']
- item['base_model'] = model['baseModel']
+ item['creator'] = j['creator']['username'] if 'creator' in j.keys() and 'username' in j['creator'].keys() else ""
+ item['tags'] = j['tags'] if 'tags' in j.keys() else []
+ item['model_name'] = model['name'] if 'name' in model.keys() else ""
+ item['base_model'] = model['baseModel'] if 'baseModel' in model.keys() else ""
+ item['description'] = model['description'] if 'description' in model.keys() else ""
  item['dl_url'] = model['downloadUrl']
- item['md'] = f'<img src="{model["images"][0]["url"]}" alt="thumbnail" width="150" height="240"><br>[LoRA Model URL](https://civitai.com/models/{j["id"]})'
+ item['md'] = ""
+ if 'images' in model.keys() and len(model["images"]) != 0:
+ item['img_url'] = model["images"][0]["url"]
+ item['md'] += f'<img src="{model["images"][0]["url"]}#float" alt="thumbnail" width="150" height="240"><br>'
+ else: item['img_url'] = "/home/user/app/null.png"
+ item['md'] += f'''Model URL: [https://civitai.com/models/{j["id"]}](https://civitai.com/models/{j["id"]})<br>Model Name: {item["name"]}<br>
+ Creator: {item["creator"]}<br>Tags: {", ".join(item["tags"])}<br>Base Model: {item["base_model"]}<br>Description: {item["description"]}'''
  items.append(item)
  return items
 
 
-def search_civitai_lora(query, base_model, sort="Highest Rated", period="AllTime", tag=""):
- global civitai_lora_last_results
- items = search_lora_on_civitai(query, base_model, 100, sort, period, tag)
+def search_civitai_lora(query, base_model=[], sort=CIVITAI_SORT[0], period=CIVITAI_PERIOD[0], tag="", user="", gallery=[]):
+ global civitai_last_results, civitai_last_choices, civitai_last_gallery
+ civitai_last_choices = [("", "")]
+ civitai_last_gallery = []
+ civitai_last_results = {}
+ items = search_lora_on_civitai(query, base_model, 100, sort, period, tag, user)
  if not items: return gr.update(choices=[("", "")], value="", visible=False),\
- gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True)
- civitai_lora_last_results = {}
+ gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+ civitai_last_results = {}
  choices = []
+ gallery = []
  for item in items:
  base_model_name = "Pony🐴" if item['base_model'] == "Pony" else item['base_model']
  name = f"{item['name']} (for {base_model_name} / By: {item['creator']} / Tags: {', '.join(item['tags'])})"
  value = item['dl_url']
  choices.append((name, value))
- civitai_lora_last_results[value] = item
+ gallery.append((item['img_url'], name))
+ civitai_last_results[value] = item
  if not choices: return gr.update(choices=[("", "")], value="", visible=False),\
- gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True)
- result = civitai_lora_last_results.get(choices[0][1], "None")
+ gr.update(value="", visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+ civitai_last_choices = choices
+ civitai_last_gallery = gallery
+ result = civitai_last_results.get(choices[0][1], "None")
  md = result['md'] if result else ""
  return gr.update(choices=choices, value=choices[0][1], visible=True), gr.update(value=md, visible=True),\
- gr.update(visible=True), gr.update(visible=True)
+ gr.update(visible=True), gr.update(visible=True), gr.update(value=gallery)
+
+
+def update_civitai_selection(evt: gr.SelectData):
+ try:
+ selected_index = evt.index
+ selected = civitai_last_choices[selected_index][1]
+ return gr.update(value=selected)
+ except Exception:
+ return gr.update(visible=True)
 
 
 def select_civitai_lora(search_result):
  if not "http" in search_result: return gr.update(value=""), gr.update(value="None", visible=True)
- result = civitai_lora_last_results.get(search_result, "None")
+ result = civitai_last_results.get(search_result, "None")
  md = result['md'] if result else ""
  return gr.update(value=search_result), gr.update(value=md, visible=True)
 
 
+def download_my_lora_flux(dl_urls: str, lora):
+ path = download_lora(dl_urls)
+ if path: lora = path
+ choices = get_all_lora_tupled_list()
+ return gr.update(value=lora, choices=choices)
+
+
+def apply_lora_prompt_flux(lora_info: str):
+ if lora_info == "None": return ""
+ lora_tag = lora_info.replace("/",",")
+ lora_tags = lora_tag.split(",") if str(lora_info) != "None" else []
+ lora_prompts = normalize_prompt_list(lora_tags)
+ prompt = ", ".join(list_uniq(lora_prompts))
+ return prompt
+
+
+def update_loras_flux(prompt, lora, lora_wt):
+ on, label, tag, md = get_lora_info(lora)
+ choices = get_all_lora_tupled_list()
+ return gr.update(value=prompt), gr.update(value=lora, choices=choices), gr.update(value=lora_wt),\
+ gr.update(value=tag, label=label, visible=on), gr.update(value=md, visible=on)
+
+
+def search_civitai_lora_json(query, base_model):
+ results = {}
+ items = search_lora_on_civitai(query, base_model)
+ if not items: return gr.update(value=results)
+ for item in items:
+ results[item['dl_url']] = item
+ return gr.update(value=results)
+
+
+def get_civitai_tag():
+ default = [""]
+ user_agent = get_user_agent()
+ headers = {'User-Agent': user_agent, 'content-type': 'application/json'}
+ base_url = 'https://civitai.com/api/v1/tags'
+ params = {'limit': 200}
+ session = requests.Session()
+ retries = Retry(total=5, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
+ session.mount("https://", HTTPAdapter(max_retries=retries))
+ url = base_url
+ try:
+ r = session.get(url, params=params, headers=headers, stream=True, timeout=(3.0, 15))
+ if not r.ok: return default
+ j = dict(r.json()).copy()
+ if "items" not in j.keys(): return default
+ items = []
+ for item in j["items"]:
+ items.append([str(item.get("name", "")), int(item.get("modelCount", 0))])
+ df = pd.DataFrame(items)
+ df.sort_values(1, ascending=False)
+ tags = df.values.tolist()
+ tags = [""] + [l[0] for l in tags]
+ return tags
+ except Exception as e:
+ print(e)
+ return default
+
+
 LORA_BASE_MODEL_DICT = {
  "diffusers:StableDiffusionPipeline": ["SD 1.5"],
  "diffusers:StableDiffusionXLPipeline": ["Pony", "SDXL 1.0"],
@@ -1177,15 +1255,6 @@ preset_quality = {k["name"]: (k["prompt"], k["negative_prompt"]) for k in qualit
 
 
 def process_style_prompt(prompt: str, neg_prompt: str, styles_key: str = "None", quality_key: str = "None", type: str = "Auto"):
- def to_list(s):
- return [x.strip() for x in s.split(",") if not s == ""]
- 
- def list_sub(a, b):
- return [e for e in a if e not in b]
- 
- def list_uniq(l):
- return sorted(set(l), key=l.index)
-
  animagine_ps = to_list("anime artwork, anime style, vibrant, studio anime, highly detailed, masterpiece, best quality, very aesthetic, absurdres")
  animagine_nps = to_list("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]")
  pony_ps = to_list("source_anime, score_9, score_8_up, score_7_up, masterpiece, best quality, very aesthetic, absurdres")
@@ -1337,7 +1406,6 @@ def set_textual_inversion_prompt(textual_inversion_gui, prompt_gui, neg_prompt_g
 
 
 def get_model_pipeline(repo_id: str):
- from huggingface_hub import HfApi
  api = HfApi(token=HF_TOKEN)
  default = "StableDiffusionPipeline"
  try: